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command.c

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Last change on this file was 19057, checked in by westram, 3 years ago
fix linking of MrBayes with gcc 10 series (duplicated non-static symbols defined in two modules).
File size: 693.2 KB

Line
1	/*
2	* MrBayes 3
3	*
4	* (c) 2002-2010
5	*
6	* John P. Huelsenbeck
7	* Dept. Integrative Biology
8	* University of California, Berkeley
9	* Berkeley, CA 94720-3140
10	* johnh@berkeley.edu
11	*
12	* Fredrik Ronquist
13	* Swedish Museum of Natural History
14	* Box 50007
15	* SE-10405 Stockholm, SWEDEN
16	* fredrik.ronquist@nrm.se
17	*
18	* With important contributions by
19	*
20	* Paul van der Mark (paulvdm@sc.fsu.edu)
21	* Maxim Teslenko (maxim.teslenko@nrm.se)
22	*
23	* and by many users (run 'acknowledgements' to see more info)
24	*
25	* This program is free software; you can redistribute it and/or
26	* modify it under the terms of the GNU General Public License
27	* as published by the Free Software Foundation; either version 2
28	* of the License, or (at your option) any later version.
29	*
30	* This program is distributed in the hope that it will be useful,
31	* but WITHOUT ANY WARRANTY; without even the implied warranty of
32	* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
33	* GNU General Public License for more details (www.gnu.org).
34	*
35	*/
36
37	#include <assert.h>
38	#include <stdio.h>
39	#include <stdlib.h>
40	#include <time.h>
41	#include <math.h>
42	#include <string.h>
43	#include <ctype.h>
44	#include "mb.h"
45	#include "mbbeagle.h"
46	#include "globals.h"
47	#include "command.h"
48	#include "bayes.h"
49	#include "model.h"
50	#include "mcmc.h"
51	#include "plot.h"
52	#include "sump.h"
53	#include "sumt.h"
54	#include "tree.h"
55	#include "utils.h"
56	#if defined (BEAGLE_ENABLED)
57	#include "libhmsbeagle/beagle.h"
58	#endif
59	#if defined(__MWERKS__)
60	#include "SIOUX.h"
61	#endif
62
63	const char* const svnRevisionCommandC="$Rev: 513 $"; /* Revision keyword which is expended/updated by svn on each commit/update*/
64
65	#define NUMCOMMANDS 61 /* Note: NUMCOMMANDS gives the total number */
66	/* of commands in the program */
67	#define NUMPARAMS 269
68	#define PARAM(i, s, f, l) p->string = s; \
69	p->fp = f; \
70	p->valueList = l; \
71	p++;
72	#define HIDE 0
73	#define SHOW 1
74
75	/* Debugging options */
76	#undef SHOW_TOKENS
77	#undef ECHO_PROCESSED_COMMANDS
78
79
80	/* Local function prototypes */
81	int AddNameSet(NameSet nameSetList, int numNameSets, char nameSet, int numNames);
82	int AddToSet (int i, int j, int k, int id);
83	int AllocCharacters (void);
84	int AllocMatrix (void);
85	int AllocTaxa (void);
86	char ChangeCase (char c);
87	int CharacterCode (char ch, int *charCode, int chType);
88	int CharacterNumber (int charCode, int chType);
89	int CheckInitialPartitions (void);
90	int Dex (TreeNode *p);
91	int DoAbout (void);
92	int DoAcknowledgments (void);
93	int DoBeginParm (char parmName, char tkn);
94	int DoBreaks (void);
95	int DoBreaksParm (char parmName, char tkn);
96	int DoCalibrate (void);
97	int DoCalibrateParm (char parmName, char tkn);
98	int DoCharset (void);
99	int DoCharsetParm (char parmName, char tkn);
100	int DoCharStat (void);
101	int DoCitations (void);
102	int DoConstraint (void);
103	int DoConstraintParm (char parmName, char tkn);
104	int DoCtype (void);
105	int DoCtypeParm (char parmName, char tkn);
106	int DoDelete (void);
107	int DoDeleteParm (char parmName, char tkn);
108	int DoDimensions (void);
109	int DoDimensionsParm (char parmName, char tkn);
110	int DoDisclaimer (void);
111	int DoEndBlock (void);
112	int DoExecuteParm (char parmName, char tkn);
113	int DoExclude (void);
114	int DoExcludeParm (char parmName, char tkn);
115	int DoFormat (void);
116	int DoFormatParm (char parmName, char tkn);
117	int DoHelp (void);
118	int DoHelpParm (char parmName, char tkn);
119	int DoInclude (void);
120	int DoIncludeParm (char parmName, char tkn);
121	int DoLog (void);
122	int DoLogParm (char parmName, char tkn);
123	int DoManual (void);
124	int DoManualParm (char parmName, char tkn);
125	int DoMatrix (void);
126	int DoMatrixParm (char parmName, char tkn);
127	int DoNexusParm (char parmName, char tkn);
128	int DoOutgroup (void);
129	int DoOutgroupParm (char parmName, char tkn);
130	int DoPairs (void);
131	int DoPairsParm (char parmName, char tkn);
132	int DoPartition (void);
133	int DoPartitionParm (char parmName, char tkn);
134	int DoRestore (void);
135	int DoRestoreParm (char parmName, char tkn);
136	int DoSet (void);
137	int DoSetParm (char parmName, char tkn);
138	int DoShowMatrix (void);
139	int DoShowUserTrees (void);
140	int DoShowBeagle (void);
141	int DoSpeciespartition (void);
142	int DoSpeciespartitionParm (char parmName, char tkn);
143	int DoTaxaset (void);
144	int DoTaxasetParm (char parmName, char tkn);
145	int DoTaxaStat (void);
146	int DoTaxlabels (void);
147	int DoTaxlabelsParm (char parmName, char tkn);
148	int DoTranslate (void);
149	int DoTranslateParm (char parmName, char tkn);
150	int DoTree (void);
151	int DoTreeParm (char parmName, char tkn);
152	int DoUserTree (void);
153	int DoUserTreeParm (char parmName, char tkn);
154	int DoVersion (void);
155	int FindValidParam (char tk, int numMatches);
156	int FreeCharacters (void);
157	int FreeMatrix (void);
158	int FreeTaxa (void);
159	int GetNumPartDivisions (int n);
160	int GetUserHelp (char *helpTkn);
161	int IsAmbig (int charCode, int dType);
162	int IsMissing (int charCode, int dType);
163	int MBResID (char nuc);
164	int NBits (int x);
165	int NucID (char nuc);
166	void PrintSettings (char command, ModelInfo mp);
167	void PrintYesNo (int yn, char s[4]);
168	int ProtID (char aa);
169	int SetPartition (int part);
170	int SetSpeciespartition (int part);
171	int SetTaxaFromTranslateTable (void);
172	int StandID (char nuc);
173	void WhatVariableExp (SafeLong exp, char *st);
174	char WhichAA (int x);
175	MrBFlt WhichCont (int x);
176	char WhichRes (int x);
177	char WhichStand (int x);
178
179
180
181	/* globals */
182	int autoClose; /* autoclose */
183	int autoOverwrite; /* Overwrite or append outputfiles when nowarnings=yes */
184	Calibration calibrationPtr; / ptr to calibration being set */
185	CharInformation charInfo; / holds critical information about characters */
186	SafeLong *charSet; / holds information about defined charsets */
187	char *charSetNames; / holds names of character sets */
188	Comptree comptreeParams; /* holds parameters for comparetree command */
189	char *constraintNames; / holds names of constraints */
190	int dataType; /* type of data */
191	Calibration defaultCalibration; /* default calibration */
192	SafeLong *definedConstraint; / bitfields representing taxa sets of defined constraints */
193	SafeLong *definedConstraintTwo;/ bitfields representing second taxa sets of defined constraints (used for PARTIAL constraints) */
194	SafeLong *definedConstraintPruned; / bitfields representing taxa sets of defined constraints after delited taxa are removed */
195	SafeLong *definedConstraintTwoPruned;/ bitfields representing second taxa sets of defined constraints for PARTIAL constraints after delited*/
196	/* taxa are removed and for NEGATIVE constraint it contains complements of definedConstraintPruned */
197	int echoMB; /* flag used by Manual to prevent echoing */
198	SafeLong expecting; /* variable denoting expected token type */
199	int foundNewLine; /* whether a new line has been found */
200	int inComment; /* flag for whether input stream is commented */
201	int inComparetreeCommand; /* flag set whenever you enter comparetree cmd */
202	int inferAncStates; /* should ancestral states be inferred (y/n) */
203	int inferSiteOmegas; /* should site omegas be inferred (y/n) */
204	int inferSiteRates; /* should site rates be inferred (y/n) */
205	int inMrbayesBlock; /* flag for whether we are in a mrbayes block */
206	int inSumtCommand; /* flag set whenever you enter sumt cmd */
207	int inTreesBlock; /* flag for whether we are in a trees block */
208	int inValidCommand; /* a useful flag set whenever you enter a cmd */
209	int isInAmbig, isInPoly; /* flags whether we are within () or {} */
210	int isTaxsetDef; /* is a taxon set defined */
211	int isTranslateDef; /* is a translation block defined */
212	int isTranslateDiff; /* is translate different from current taxaset? */
213	char logFileName[100]; /* name of the log file */
214	int logToFile; /* should screen output be logged to a file */
215	FILE logFileFp; / file pointer to log file */
216	int longIntegerSize; /* size of an unsigned integer */
217	char manFileName[100]; /* name of the file for the command help info */
218	int matrix; / matrix containing original data */
219	int matrixHasPoly; /* flag for whether matrix has polymorphisms */
220	int memAllocs[NUM_ALLOCS]; /* allocated memory flags */
221	int mode; /* mode of program (interactive/noninteractive) */
222	Calibration nodeCalibration; / holds information about node calibrations */
223	int noWarn; /* no warnings on overwriting files */
224	int numChar; /* number of characters in character matrix */
225	int numCharSets; /* number of character sets */
226	int numComments; /* counts how deeply nested a comment is */
227	int numDefinedConstraints; /* number of constraints defined */
228	int numDefinedPartitions; /* number of partitions defined */
229	int numDefinedSpeciespartitions; /* number of speciespartitions defined */
230	int numNamedTaxa; /* number of named taxa during parsing of cmd */
231	int numOpenExeFiles; /* number of execute files open */
232	int numSpecies; /* number of species in current speciespartition */
233	int numTaxa; /* number of taxa in character matrix */
234	int numTaxaSets; /* number of taxa sets */
235	int numTranslates; /* number of taxa in active translate block */
236	int outGroupNum; /* number of outgroup taxon */
237	ParmInfo paramTable[NUMPARAMS]; /* information on parameters */
238	char *partitionNames; / hold names of partitions (first is "default") */
239	int *partitionId; / holds information about defined partitions */
240	int partitionNum; /* index of current partition */
241	Plot plotParams; /* holds parameters for plot command */
242	int precision; /* precision of samples and summary stats */
243	int quitOnError; /* quit on error? */
244	int replaceLogFile; /* should logfile be replace/appended to */
245	int scientific; /* use scientific format for samples ? */
246	char spacer[10]; /* holds blanks for printing indentations */
247	NameSet speciesNameSets; / hold species name sets, one for each speciespartition */
248	int *speciespartitionId; / holds info about defined speciespartitions */
249	char *speciespartitionNames; / hold names of speciespartitions (first is "default") */
250	int speciespartitionNum; /* index of current speciespartition */
251	Sump sumpParams; /* holds parameters for sump command */
252	Sumt sumtParams; /* holds parameters for sumt command */
253	Sumss sumssParams; /* holds parameters for sumss command */
254	TaxaInformation taxaInfo; / holds critical information about taxa */
255	char *taxaNames; / holds name of taxa */
256	SafeLong *taxaSet; / holds information about defined taxasets */
257	char *taxaSetNames; / holds names of taxa sets */
258	int tempActiveConstraints;/ temporarily holds active constraints size allcated */
259	enum ConstraintType definedConstraintsType;/ Store type of constraint */
260	int tempSet; / temporarily holds defined set */
261	int tempSetNeg; / holds bitset of negative set of taxa for partial constraint*/
262	int theAmbigChar; /* int containing ambiguous character */
263	Calibration tipCalibration; / holds information about node calibrations */
264	char *transFrom; / translation block information */
265	char *transTo; / translation block information */
266	int userBrlensDef; /* are the branch lengths on user tree defined */
267
268	#if defined (BEAGLE_ENABLED)
269	int tryToUseBEAGLE; /* try to use the BEAGLE library */
270	int beagleScalingScheme; /* BEAGLE dynamic scaling */
271	int beagleScalingFrequency;/* BEAGLE dynamic scaling frequency */
272	long beagleFlags; /* BEAGLE required resource flags */
273	int beagleResource; / BEAGLE resource choice list */
274	int beagleResourceCount; /* BEAGLE resource choice list length */
275	int beagleInstanceCount; /* total number of BEAGLE instances */
276	#endif
277
278	#if defined (THREADS_ENABLED)
279	int tryToUseThreads; /* try to use pthreads with BEAGLE library */
280	#endif
281
282
283	/* local (to this file) */
284	char tokenP, token[CMD_STRING_LENGTH], cmdStr=NULL;
285	Calibration defaultCalibration = {
286	/* name = */ "Unconstrained",
287	/* prior = / 0, / = unconstrained */
288	/* max = */ -1.0,
289	/* min = */ -1.0,
290	/* offset = */ -1.0,
291	/* lambda = */ -1.0,
292	/* age = */ -1.0};
293
294	CmdType commands[] =
295	{
296	/* Information on commands initialization:
297
298	1 = Command number (cmdNumber)
299	2 = Command name (string)
300	3 = Special command (YES/NO) (specialCmd)
301	4 = Pointer to finishing function (fp)
302	5 = Number of valid parameters (numParms)
303	6 = List of valid parameters (parmList)
304	7 = Expecting (2^TokenType) (expect) (PARAMETER = 4; SEMICOLON = 32; ALPHA = 16384;
305	ALPHA \| QUESTIONMARK \| DASH \| NUMBER \| ASTERISK \| EXCLAMATIONMARK \| PERCENT \| WEIRD \| SEMICOLON = 11715360;
306	ALPHA \| QUESTIONMARK \| DASH \| NUMBER \| ASTERISK \| EXCLAMATIONMARK \| PERCENT \| WEIRD \| SEMICOLON \| LEFTPAR \| RIGHTPAR \| LEFTCURL \| RIGHTCURL = 112381728;
307	PARAMETER \| SEMICOLON = 36; NUMBER \| ALPHA = 49152; ALPHA \| SEMICOLON = 16416; EQUALSIGN = 8; NUMBER = 32768)
308	8 = Description of the command (cmdDescription)
309	9 = Where should the command be used (cmdUse) (IN_CMD = used from command line or mrbayes block; IN_FILE = used in data block or in tree block)
310	10 = Should the command be shown when "help" is typed (hiding).
311
312	#1 #2 #3 #4 #5 #6 #7 #8 #9 #10
313	-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- */
314	{ 0, "#", NO, NULL, 1, {0}, 4, "", IN_FILE, HIDE },
315	{ 1, "About", NO, DoAbout, 0, {-1}, 32, "Describes the program", IN_CMD, SHOW },
316	{ 2, "Acknowledgments", NO, DoAcknowledgments, 0, {-1}, 32, "Shows program acknowledgments", IN_CMD, SHOW },
317	{ 3, "Begin", NO, NULL, 6, {1,2,3,201,226,227}, 4, "Denotes beginning of block in file", IN_FILE, SHOW },
318	{ 4, "Calibrate", NO, DoCalibrate, 1, {119}, 4, "Assigns dates to terminals or interior nodes", IN_CMD, SHOW },
319	{ 5, "Charset", NO, DoCharset, 1, {15}, 4, "Assigns a group of sites to a set", IN_CMD, SHOW },
320	{ 6, "Charstat", NO, DoCharStat, 0, {-1}, 32, "Shows status of characters", IN_CMD, SHOW },
321	{ 7, "Citations", NO, DoCitations, 0, {-1}, 32, "Citation of program, models, and methods", IN_CMD, SHOW },
322	{ 8, "Comparetree", NO, DoCompareTree, 7, {127,128,129,130,221,222,223}, 36, "Compares the trees from two tree files", IN_CMD, SHOW },
323	{ 9, "Constraint", NO, DoConstraint, 1, {66}, 4, "Defines a constraint on tree topology", IN_CMD, SHOW },
324	{ 10, "Ctype", NO, DoCtype, 1, {65}, 4, "Assigns ordering for the characters", IN_CMD, SHOW },
325	{ 11, "Databreaks", YES, DoBreaks, 1, {93}, 32768, "Defines data breaks for autodiscrete gamma model", IN_CMD, SHOW },
326	{ 12, "Delete", YES, DoDelete, 1, {47}, 49152, "Deletes taxa from the analysis", IN_CMD, SHOW },
327	{ 13, "Dimensions", NO, DoDimensions, 2, {4,5}, 4, "Defines size of character matrix", IN_FILE, SHOW },
328	{ 14, "Disclaimer", NO, DoDisclaimer, 0, {-1}, 32, "Describes program disclaimer", IN_CMD, SHOW },
329	{ 15, "End", NO, DoEndBlock, 0, {-1}, 32, "Denotes end of a block in file", IN_FILE, SHOW },
330	{ 16, "Endblock", NO, DoEndBlock, 0, {-1}, 32, "Alternative way of denoting end of a block", IN_FILE, SHOW },
331	{ 17, "Exclude", YES, DoExclude, 1, {45}, 49152, "Excludes sites from the analysis", IN_CMD, SHOW },
332	{ 18, "Execute", YES, DoExecute, 1, {12}, 16384, "Executes a file", IN_CMD, SHOW },
333	{ 19, "Format", NO, DoFormat, 7, {6,7,8,9,10,219,220}, 4, "Defines character format in data block", IN_FILE, SHOW },
334	{ 20, "Help", YES, DoHelp, 1, {50}, 16416, "Provides detailed description of commands", IN_CMD, SHOW },
335	{ 21, "Include", YES, DoInclude, 1, {46}, 49152, "Includes sites", IN_CMD, SHOW },
336	{ 22, "Link", NO, DoLink, 27, {55,56,57,58,59,60,61,62,63,72,73,74,75,76,105,118,193,194,195,196,197,242,243,252,253,255,256}, 4, "Links parameters across character partitions", IN_CMD, SHOW },
337	{ 23, "Log", NO, DoLog, 5, {85,86,87,88,89}, 4, "Logs screen output to a file", IN_CMD, SHOW },
338	{ 24, "Lset", NO, DoLset, 16, {28,29,30,31,32,33,34,40,51,52,53,90,91,131,188,189}, 4, "Sets the parameters of the likelihood model", IN_CMD, SHOW },
339	{ 25, "Manual", NO, DoManual, 1, {126}, 36, "Prints a command reference to a text file", IN_CMD, SHOW },
340	{ 26, "Matrix", YES, DoMatrix, 1, {11},112381728, "Defines matrix of characters in data block", IN_FILE, SHOW },
341	{ 27, "Mcmc", NO, DoMcmc, 46, {17,18,19,20,21,22,23,24,25,26,27,84,98,112,113,114,115,116,132,142,143,144,148,149,150,151,152,
342	153,154,155,156,157,158,159,160,166,169,190,191,198,199,200,202,213,214,215}, 36, "Starts Markov chain Monte Carlo analysis", IN_CMD, SHOW },
343	{ 28, "Mcmcp", NO, DoMcmcp, 46, {17,18,19,20,21,22,23,24,25,26,27,84,98,112,113,114,115,116,132,142,143,144,148,149,150,151,152,
344	153,154,155,156,157,158,159,160,166,169,190,191,198,199,200,202,213,214,215}, 4, "Sets the parameters of a chain (without starting analysis)", IN_CMD, SHOW },
345	{ 29, "Outgroup", YES, DoOutgroup, 1, {78}, 49152, "Changes outgroup taxon", IN_CMD, SHOW },
346	{ 30, "Pairs", YES, DoPairs, 1, {92}, 32768, "Defines nucleotide pairs (doublets) for stem models", IN_CMD, SHOW },
347	{ 31, "Partition", NO, DoPartition, 1, {16}, 4, "Assigns a character partition", IN_CMD, SHOW },
348	{ 32, "Plot", NO, DoPlot, 6, {106,107,108,109,224,225}, 36, "Plots parameters from MCMC analysis", IN_CMD, SHOW },
349	{ 33, "Prset", NO, DoPrset, 41, {35,36,37,38,39,41,42,43,44,54,64,67,68,69,70,71,77,100,101,102,103,104,110,111,117,120,121,133,
350	168,172,173,174,183,184,185,218,241,246,247,251,254}, 4, "Sets the priors for the parameters", IN_CMD, SHOW },
351	{ 34, "Propset", NO, DoPropset, 1, {186}, 4, "Sets proposal probabilities and tuning parameters", IN_CMD, SHOW },
352	{ 35, "Quit", NO, DoQuit, 0, {-1}, 32, "Quits the program", IN_CMD, SHOW },
353	{ 36, "Report", NO, DoReport, 9, {122,123,124,125,134,135,136,192,217}, 4, "Controls how model parameters are reported", IN_CMD, SHOW },
354	{ 37, "Restore", YES, DoRestore, 1, {48}, 49152, "Restores taxa", IN_CMD, SHOW },
355	{ 38, "Set", NO, DoSet, 22, {13,14,94,145,170,171,179,181,182,216,229,233,234,235,236,237,238,239,240,245,268}, 4, "Sets run conditions and defines active data partition", IN_CMD, SHOW },
356	{ 39, "Showbeagle", NO, DoShowBeagle, 0, {-1}, 32, "Show available BEAGLE resources", IN_CMD, SHOW },
357	{ 40, "Showmatrix", NO, DoShowMatrix, 0, {-1}, 32, "Shows current character matrix", IN_CMD, SHOW },
358	{ 41, "Showmcmctrees", NO, DoShowMcmcTrees, 0, {-1}, 32, "Shows trees used in mcmc analysis", IN_CMD, SHOW },
359	{ 42, "Showmodel", NO, DoShowModel, 0, {-1}, 32, "Shows model settings", IN_CMD, SHOW },
360	{ 43, "Showmoves", NO, DoShowMoves, 1, {180}, 36, "Shows moves for current model", IN_CMD, SHOW },
361	{ 44, "Showparams", NO, DoShowParams, 0, {-1}, 32, "Shows parameters in current model", IN_CMD, SHOW },
362	{ 45, "Showusertrees", NO, DoShowUserTrees, 0, {-1}, 32, "Shows user-defined trees", IN_CMD, SHOW },
363	{ 46,"Speciespartition", NO,DoSpeciespartition, 1, {244}, 4, "Defines a partition of tips into species", IN_CMD, SHOW },
364	{ 47, "Ss", NO, DoSs, 50, {17,18,19,20,21,22,23,24,25,26,27,84,98,112,113,114,115,116,132,142,143,144,148,149,150,151,152,
365	153,154,155,156,157,158,159,160,166,169,190,191,198,199,200,202,213,214,215,248,249,250,257}, 36, "Starts stepping-stone sampling", IN_CMD, SHOW },
366	{ 48, "Ssp", NO, DoSsp, 50, {17,18,19,20,21,22,23,24,25,26,27,84,98,112,113,114,115,116,132,142,143,144,148,149,150,151,152,
367	153,154,155,156,157,158,159,160,166,169,190,191,198,199,200,202,213,214,215,248,249,250,257}, 36, "Sets the parameters of a stepping-stone (without starting)", IN_CMD, SHOW },
368	{ 49, "Startvals", NO, DoStartvals, 1, {187}, 4, "Sets starting values of parameters", IN_CMD, SHOW },
369	{ 50, "Sump", NO, DoSump, 13, {96,97,137,138,139,140,141,161,162,178,211,212,231}, 36, "Summarizes parameters from MCMC analysis", IN_CMD, SHOW },
370	{ 51, "Sumss", NO, DoSumSs, 10, {258,259,260,261,262,263,264,265,266,267}, 36, "Summarizes parameters from stepping-stone analysis", IN_CMD, SHOW },
371	{ 52, "Sumt", NO, DoSumt, 21, {80,81,82,95,146,147,163,164,165,167,175,177,204,205,206,207,208,209,210,230,232}, 36, "Summarizes trees from MCMC analysis", IN_CMD, SHOW },
372	{ 53, "Taxastat", NO, DoTaxaStat, 0, {-1}, 32, "Shows status of taxa", IN_CMD, SHOW },
373	{ 54, "Taxset", NO, DoTaxaset, 1, {49}, 4, "Assigns a group of taxa to a set", IN_CMD, SHOW },
374	{ 55, "Taxlabels", YES, DoTaxlabels, 1, {228}, 49152, "Defines taxon labels", IN_FILE, SHOW },
375	{ 56, "Translate", YES, DoTranslate, 1, {83}, 49152, "Defines alternative names for taxa", IN_FILE, SHOW },
376	{ 57, "Tree", NO, DoTree, 1, {79}, 4, "Defines a tree", IN_FILE, SHOW },
377	{ 58, "Unlink", NO, DoUnlink, 23, {55,56,57,58,59,60,61,62,63,72,73,74,75,76,105,118,193,194,195,196,197,242,243}, 4, "Unlinks parameters across character partitions", IN_CMD, SHOW },
378	{ 59, "Usertree", YES, DoUserTree, 1, {203}, 8, "Defines a single user tree", IN_CMD, HIDE },
379	{ 60, "Version", NO, DoVersion, 0, {-1}, 32, "Shows program version", IN_CMD, SHOW },
380	/* NOTE: If you add a command here, make certain to change NUMCOMMANDS (above, in this file) appropriately! */
381	{ 999, NULL, NO, NULL, 0, {-1}, 32, "", IN_CMD, HIDE }
382	};
383	static int fromI, toJ, isNegative, foundDash, foundExp, foundEqual;
384	int inDataBlock, inForeignBlock, isInterleaved, isFirstMatrixRead, isFirstInterleavedBlock,
385	taxonCount, everyK, foundSlash, foundFirst, isMixed, whichPartition,
386	numDivisions, charOrdering, foundColon, isFirstNode, nextAvailableNode,
387	pairId, firstPair, inTaxaBlock, inCharactersBlock;
388	char gapId, missingId, matchId, tempSetName[100], **tempNames;
389	CmdType commandPtr; /Points to the commands array entery which corresponds to currently processed command*/
390	ParmInfoPtr paramPtr; /Points to paramTable table array entery which corresponds to currently processed parameter of current command/
391	TreeNode pPtr, qPtr;
392
393	enum ConstraintType consrtainType; /* Used only in processing of constraine command to indicate what is the type of constrain */
394
395
396
397	int AddToGivenSet (int i, int j, int k, int id, int *Set)
398
399	{
400
401	int m, n;
402
403	if (id <= 0)
404	{
405	MrBayesPrint ("%s The id for a temporary set should be greater than 0\n", spacer);
406	return (ERROR);
407	}
408
409	if (i < 0 && j < 0)
410	return (ERROR);
411	else if (i < 0 && j >= 0)
412	return (ERROR);
413	else if (i >= 0 && j < 0)
414	{
415	if (k >= 0)
416	return (ERROR);
417	else
418	{
419	if (Set[i] != 0)
420	{
421	MrBayesPrint ("%s Character %d defined more than once\n", spacer, i+1);
422	return (ERROR);
423	}
424	Set[i] = id;
425	}
426	}
427	else if (i >= 0 && j >= 0)
428	{
429	if (k < 0)
430	{
431	for (m=i; m<=j; m++)
432	{
433	if (Set[m] != 0)
434	{
435	MrBayesPrint ("%s Character %d defined more than once\n", spacer, m+1);
436	return (ERROR);
437	}
438	Set[m] = id;
439	}
440	}
441	else
442	{
443	n = k;
444	for (m=i; m<=j; m++)
445	{
446	if (n % k == 0)
447	{
448	if (Set[m] != 0)
449	{
450	MrBayesPrint ("%s Character %d defined more than once\n", spacer, m+1);
451	return (ERROR);
452	}
453	Set[m] = id;
454	}
455	n++;
456	}
457	}
458	}
459
460
461	return (NO_ERROR);
462
463	}
464
465
466
467
468
469	int AddToSet (int i, int j, int k, int id)
470	{
471	return AddToGivenSet (i, j, k,id, tempSet);
472	}
473
474
475
476
477	/* AddNameSet: Push a name set onto the end of a list of name sets, with reallocation
478	of list to hold the extra element. The calling function needs to keep track of
479	the counter holding the length of the list. */
480	int AddNameSet (NameSet nameSetList, int numNameSets, char nameSet, int numNames)
481	{
482	int i;
483
484	(nameSetList) = (NameSet) SafeRealloc ((void)(nameSetList), (size_t)(((numNameSets+1)*sizeof(NameSet))));
485
486	(*nameSetList)[numNameSets].names = NULL;
487	(*nameSetList)[numNameSets].numNames = numNames;
488
489	for (i=0; i<numNames; i++)
490	AddString(&((*nameSetList)[numNameSets].names), i, nameSet[i]);
491
492	return NO_ERROR;
493	}
494
495
496
497
498
499	/* AddString: Push a string onto the end of a list, with reallocation of list
500	to hold the extra element. The calling function needs to keep track of
501	the counter holding the length of the list. */
502	int AddString (char **list, int len, char token)
503	{
504	(list) = (char ) SafeRealloc ((void )(list), (size_t)((len+1)sizeof(char*)));
505	if (!(*list))
506	return ERROR;
507
508	(list)[len] = (char ) SafeCalloc ((size_t)(strlen(token)+1), sizeof(char));
509	if (!(*list)[len])
510	return ERROR;
511
512	strcpy ((*list)[len], token);
513
514	return NO_ERROR;
515	}
516
517
518
519
520
521	int AllocCharacters (void)
522
523	{
524
525	int i, tempSetSize;
526
527	if (memAllocs[ALLOC_MATRIX] == YES)
528	goto errorExit;
529	matrix = (int )SafeMalloc((size_t) (numTaxa numChar * sizeof(int)));
530	if (!matrix)
531	{
532	MrBayesPrint ("%s Problem allocating matrix (%d)\n", spacer, numTaxa * numChar * sizeof(int));
533	goto errorExit;
534	}
535	for (i=0; i<numTaxa * numChar; i++)
536	matrix[i] = 0;
537	memAllocs[ALLOC_MATRIX] = YES;
538
539	if (memAllocs[ALLOC_CHARINFO] == YES)
540	goto errorExit;
541	charInfo = (CharInformation )SafeMalloc((size_t) (numChar sizeof(CharInformation)));
542	if (!charInfo)
543	{
544	MrBayesPrint ("%s Problem allocating charInfo (%d)\n", spacer, numChar * sizeof(CharInformation));
545	goto errorExit;
546	}
547	for (i=0; i<numChar; i++)
548	{
549	charInfo[i].isExcluded = NO;
550	charInfo[i].numStates = 0;
551	charInfo[i].charType = 0;
552	charInfo[i].isMissAmbig = NO;
553	charInfo[i].ctype = UNORD;
554	charInfo[i].charId = 0;
555	charInfo[i].pairsId = 0;
556	charInfo[i].bigBreakAfter = NO;
557	}
558	memAllocs[ALLOC_CHARINFO] = YES;
559
560	if (memAllocs[ALLOC_CHARSETS] == YES)
561	goto errorExit;
562	charSetNames = NULL;
563	charSet = NULL;
564	numCharSets = 0;
565	memAllocs[ALLOC_CHARSETS] = YES; /* safe to do free */
566
567	if (memAllocs[ALLOC_PARTITIONS] == YES)
568	goto errorExit;
569	partitionNames = NULL;
570	partitionId = (int*) SafeMalloc ((size_t)(numCharsizeof(int*)));
571	for (i=0; i<numChar; i++)
572	partitionId[i] = (int ) SafeMalloc ((size_t)(1 sizeof(int)));
573	numDefinedPartitions = 0; /* number of defined partitions */
574	memAllocs[ALLOC_PARTITIONS] = YES; /* safe to do free */
575
576	if (memAllocs[ALLOC_PARTITIONVARS] == YES)
577	goto errorExit;
578	numVars = NULL;
579	tempLinkUnlinkVec = NULL;
580	activeParts = NULL;
581	tempLinkUnlinkVec = NULL;
582	tempNum = NULL;
583	linkTable[0] = NULL;
584	tempLinkUnlink[0] = NULL;
585	for (i=0; i<NUM_LINKED; i++)
586	{
587	linkTable[i] = NULL;
588	tempLinkUnlink[i] = NULL;
589	activeParams[i] = NULL;
590	}
591	memAllocs[ALLOC_PARTITIONVARS] = YES;
592
593	if (memAllocs[ALLOC_TMPSET] == NO)
594	goto errorExit;
595	if (numChar > numTaxa)
596	tempSetSize = numChar;
597	else
598	tempSetSize = numTaxa;
599	tempSet = (int )SafeRealloc((void )tempSet, (size_t) (tempSetSize * sizeof(int)));
600	tempSetNeg = (int )SafeRealloc((void )tempSetNeg, (size_t) (tempSetSize * sizeof(int)));
601	if (!tempSet \|\| !tempSetNeg)
602	{
603	MrBayesPrint ("%s Problem reallocating tempSet (%d)\n", spacer, tempSetSize * sizeof(int));
604	goto errorExit;
605	}
606
607	MrBayesPrint ("%s Allocated matrix\n", spacer);
608	return (NO_ERROR);
609
610	errorExit:
611	MrBayesPrint ("%s Problem allocating matrix\n", spacer);
612	FreeMatrix();
613	return (ERROR);
614	}
615
616
617
618
619
620	int AllocMatrix (void)
621
622	{
623	if (memAllocs[ALLOC_TAXA] == NO && AllocTaxa() == ERROR)
624	return ERROR;
625	else
626	return (AllocCharacters());
627	}
628
629
630
631
632
633	int AllocTaxa (void)
634
635	{
636
637	int i;
638
639	if (defTaxa==NO)
640	{
641	MrBayesPrint ("%s Number of taxa not defined\n", spacer);
642	return (ERROR);
643	}
644	if (numTaxa == 0)
645	{
646	MrBayesPrint ("%s Number of taxa is 0\n", spacer);
647	return (ERROR);
648	}
649
650	/* allocate space for taxa */
651	if (memAllocs[ALLOC_TAXA] == YES)
652	goto errorExit;
653	taxaNames = NULL; /* This variable is allocated in AddString */
654	taxaInfo = (TaxaInformation )SafeMalloc((size_t) (numTaxa sizeof(TaxaInformation)));
655	if (!taxaInfo)
656	{
657	goto errorExit;
658	}
659	tipCalibration = (Calibration )SafeMalloc((size_t) (numTaxa sizeof(Calibration)));
660	if (!tipCalibration)
661	{
662	free (taxaInfo);
663	taxaInfo = NULL;
664	goto errorExit;
665	}
666	for (i=0; i<numTaxa; i++)
667	{
668	taxaInfo[i].isDeleted = NO;
669	taxaInfo[i].charCount = 0;
670	}
671	memAllocs[ALLOC_TAXA] = YES;
672
673	/* taxa sets */
674	if (memAllocs[ALLOC_TAXASETS] == YES)
675	goto errorExit;
676	taxaSetNames = NULL;
677	taxaSet = NULL;
678	numTaxaSets = 0;
679	memAllocs[ALLOC_TAXASETS] = YES; /* safe to free */
680
681	/* species partitions; allocate space and set default species partition */
682	if (memAllocs[ALLOC_SPECIESPARTITIONS] == YES)
683	goto errorExit;
684	speciespartitionNames = NULL;
685	speciesNameSets = NULL;
686	speciespartitionId = (int*) SafeMalloc ((size_t)(numTaxasizeof(int*)));
687	for (i=0; i<numTaxa; i++)
688	{
689	speciespartitionId[i] = (int ) SafeMalloc ((size_t)(1 sizeof(int)));
690	speciespartitionId[i][0] = i + 1; /* 1-based taxon index, do not ask me why */
691	}
692	numDefinedSpeciespartitions = 0; /* number of defined species partitions */
693	memAllocs[ALLOC_SPECIESPARTITIONS] = YES; /* safe to do free */
694
695	/* constraints */
696	if (memAllocs[ALLOC_CONSTRAINTS] == YES)
697	goto errorExit;
698	constraintNames = NULL;
699	definedConstraintsType = NULL;
700	definedConstraint = NULL;
701	definedConstraintTwo = NULL;
702	definedConstraintPruned = NULL;
703	definedConstraintTwoPruned = NULL;
704	numDefinedConstraints = 0;
705	tempActiveConstraints = NULL;
706	memAllocs[ALLOC_CONSTRAINTS] = YES; /* safe to free */
707
708	/* translate table */
709	transFrom = NULL;
710	transTo = NULL;
711	numTranslates = 0;
712
713	/* tempSet */
714	if (memAllocs[ALLOC_TMPSET] == YES)
715	goto errorExit;
716	tempSet = (int ) SafeMalloc ((size_t)(numTaxasizeof(int)));
717	tempSetNeg = (int ) SafeMalloc ((size_t)(numTaxasizeof(int)));
718	if (!tempSet \|\| !tempSetNeg)
719	goto errorExit;
720	memAllocs[ALLOC_TMPSET] = YES;
721
722	/* make sure previous user trees are freed */
723	if (numUserTrees > 0)
724	{
725	MrBayesPrint ("%s Previous user trees not freed\n", spacer);
726	goto errorExit;
727	}
728
729	MrBayesPrint ("%s Allocated taxon set\n", spacer);
730	return NO_ERROR;
731
732	errorExit:
733	MrBayesPrint ("%s Problem allocating taxon set\n", spacer);
734	FreeTaxa();
735	return ERROR;
736	}
737
738
739
740
741
742	char ChangeCase (char c)
743
744	{
745
746	int x;
747
748	x = tolower(c);
749	return (x);
750
751	}
752
753
754
755
756
757	int CharacterCode (char ch, int *charCode, int chType)
758
759	{
760
761
762	if (chType == DNA \|\| chType == RNA)
763	{
764	if ((*charCode = NucID (ch)) == -1)
765	{
766	MrBayesPrint ("%s Unrecognized DNA/RNA character '%c'\n", spacer, ch);
767	return (ERROR);
768	}
769	}
770	else if (chType == PROTEIN)
771	{
772	if ((*charCode = ProtID (ch)) == -1)
773	{
774	MrBayesPrint ("%s Unrecognized Protein character '%c'\n", spacer, ch);
775	return (ERROR);
776	}
777	}
778	else if (chType == RESTRICTION)
779	{
780	if ((*charCode = MBResID (ch)) == -1)
781	{
782	MrBayesPrint ("%s Unrecognized Restriction character '%c'\n", spacer, ch);
783	return (ERROR);
784	}
785	}
786	else if (chType == STANDARD)
787	{
788	if ((*charCode = StandID (ch)) == -1)
789	{
790	MrBayesPrint ("%s Unrecognized Standard character '%c'\n", spacer, ch);
791	return (ERROR);
792	}
793	}
794	else if (chType == CONTINUOUS)
795	{
796	MrBayesPrint ("%s CharacterCode function cannot check continuous characters\n", spacer);
797	}
798	else
799	{
800	MrBayesPrint ("%s Unrecognized character type (%d)\n", spacer, chType);
801	return (ERROR);
802	}
803
804	return (NO_ERROR);
805
806	}
807
808
809
810
811
812	int CharacterNumber (int charCode, int chType)
813
814	{
815
816	int i, x = charCode;
817
818	if (chType == CONTINUOUS)
819	return 0;
820
821	for (i=0; x!=0; i++)
822	x >>= 1;
823
824	return (i);
825
826	}
827
828
829
830
831
832	int CheckInitialPartitions (void)
833
834	{
835
836	int i;
837
838	for (i=0; i<numChar; i++)
839	{
840	if (partitionId[i][0] <= 0 \|\| partitionId[i][0] > numDivisions)
841	{
842	MrBayesPrint ("%s The partition for site %d is incorrect\n", spacer, i+1);
843	return (ERROR);
844	}
845	}
846
847	return (NO_ERROR);
848
849	}
850
851
852
853
854
855	int CheckStringValidity (char *s)
856
857	{
858
859	int i, numUnknownChars, tempNumComments, tempInComment;
860	char temp[100];
861
862	i = 0;
863	numUnknownChars = 0;
864	tempNumComments = numComments;
865	tempInComment = inComment;
866
867	while(s[i] != '\0')
868	{
869	if (tempInComment == NO)
870	{
871	if ( !IsIn(s[i],"=abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ_0123456789.;:,#()[]?-*/'\\'!%\"&~+^$@\|{}`>< ") )
872	{
873	if (IsWhite(s[i]) == 1 \|\| IsWhite(s[i]) == 2)
874	{
875
876	}
877	else
878	{
879	if ( commandPtr == NULL)
880	return (ERROR);
881	MrBayesPrint ("%s Unknown character \"%c\" (ASCII code %d)\n", spacer, s[i], s[i]);
882	if (!strcmp(commandPtr->string,"Matrix"))
883	{
884	if (foundNewLine == NO)
885	{
886	MrBayesPrint ("%s The error is in character %d for taxon %s\n", spacer, taxaInfo[taxonCount-1].charCount+i+1, "???"); /* bug? */
887	}
888	else
889	{
890	if (taxonCount == 0)
891	MrBayesPrint ("%s The error is in the first taxon name\n", spacer);
892	else
893	{
894	strcpy(temp, taxaNames[taxonCount]);
895	if (isInterleaved == NO)
896	MrBayesPrint ("%s The error is in the name of the taxon following taxon %s\n", spacer, temp);
897	else
898	{
899	MrBayesPrint ("%s The error is in the name of the taxon following taxon %s\n", spacer, temp);
900	MrBayesPrint ("%s in one of the interleaved data blocks\n", spacer);
901	}
902	}
903	}
904	}
905	else if (!strcmp(commandPtr->string,"Execute"))
906	{
907	MrBayesPrint ("%s Assuming irrelevant characters at beginning of file; processing continues\n", spacer);
908	return (NO_ERROR);
909	}
910	return (ERROR);
911	}
912	}
913	if (s[i]=='[')
914	{
915	tempInComment = YES;
916	tempNumComments++;
917	}
918	}
919	else if (tempInComment == YES)
920	{
921	if (s[i]==']')
922	{
923	tempNumComments--;
924	if (tempNumComments == 0)
925	tempInComment = NO;
926	}
927	}
928	i++;
929	}
930
931	if (numUnknownChars > 0)
932	return (ERROR);
933	else
934	return (NO_ERROR);
935
936	}
937
938
939
940
941
942	/* CheckString: This function simply checks a vector of strings for a match against token.
943	Upon return, matchIndex contains the index of the matched string. An
944	ERROR is returned if there are no matches. */
945	int CheckString (char *list, int len, char token, int *matchIndex)
946	{
947	int i;
948
949	*matchIndex = -1;
950	for (i=0; i<len; i++)
951	{
952	if (StrCmpCaseInsensitive(token,list[i]) == 0)
953	{
954	*matchIndex = i;
955	return (NO_ERROR);
956	}
957	}
958
959	return (ERROR);
960	}
961
962
963
964
965
966	int Dex (TreeNode *p)
967
968	{
969
970	return (p == NULL) ? -1 : p->index;
971
972	}
973
974
975
976
977
978	int DoAbout (void)
979
980	{
981
982	MrBayesPrint (" --------------------------------------------------------------------------- \n");
983	MrBayesPrint (" About the program \n");
984	MrBayesPrint (" \n");
985	MrBayesPrint (" MrBayes is a program for the Bayesian estimation of phylogeny. Bayesian \n");
986	MrBayesPrint (" inference of phylogeny is based upon the posterior probability distribution \n");
987	MrBayesPrint (" of trees. Trees are labelled T1, T2, ..., Tn, where n is the number of \n");
988	MrBayesPrint (" possible trees. The posterior probability of the i-th tree is calculated \n");
989	MrBayesPrint (" using Bayes\'s formula as \n");
990	MrBayesPrint (" \n");
991	MrBayesPrint (" Pr[Ti \| X] = Pr[X \| Ti] X Pr[Ti] / Pr[X] \n");
992	MrBayesPrint (" \n");
993	MrBayesPrint (" where X is a character matrix. Here, \"Pr[Ti \| X]\" is the posterior \n");
994	MrBayesPrint (" probability of the i-th tree, \"Pr[X \| Ti]\" is the likelihood of the \n");
995	MrBayesPrint (" i-th tree, and \"Pr[Ti]\" is the prior probability of the i-th tree. The \n");
996	MrBayesPrint (" denominator of Bayes\'s formula (\"Pr[X]\") is a normalizing constant that \n");
997	MrBayesPrint (" involves a summation over all possible trees. The likelihood, as described \n");
998	MrBayesPrint (" above, cannot be calculated with knowledge of only the tree\'s topology. You \n");
999	MrBayesPrint (" also need to have information on the lenths of the branches and on the \n");
1000	MrBayesPrint (" mechanism of character change. Hence, the likelihood (\"Pr[X \| Ti]\") \n");
1001	MrBayesPrint (" involves a multidimensional integral over all possible combinations of \n");
1002	MrBayesPrint (" branch lengths and substitution model parameters. \n");
1003	MrBayesPrint (" \n");
1004	MrBayesPrint (" In practice, it is impossible to calculate the posterior probability dist- \n");
1005	MrBayesPrint (" ribution of trees analytically. Instead, the posterior probability \n");
1006	MrBayesPrint (" of trees must be approximated. MrBayes uses a method called Markov chain \n");
1007	MrBayesPrint (" Monte Carlo (MCMC) to approximate the posterior probability of trees. \n");
1008	MrBayesPrint (" The object of MCMC is to construct a Markov chain that has as its state \n");
1009	MrBayesPrint (" space the parameters of the phylogenetic model and a stationary distribution \n");
1010	MrBayesPrint (" that is the posterior probability distribution of trees. MCMC takes valid, \n");
1011	MrBayesPrint (" albeit dependent, samples from the posterior probability distribution of \n");
1012	MrBayesPrint (" trees. The fraction of the time any tree appears in this sample is a \n");
1013	MrBayesPrint (" valid approximation of the posterior probability of the tree. MrBayes keeps \n");
1014	MrBayesPrint (" track of all the parameters of the phylogenetic model. The trees (with branch \n");
1015	MrBayesPrint (" lengths) that were sampled by the MCMC procedure are saved in one file \n");
1016	MrBayesPrint (" (a file with a \".t\" extension) whereas the parameters of the model of \n");
1017	MrBayesPrint (" character change are saved in another file (a file with a \".p\" ext- \n");
1018	MrBayesPrint (" ension). You can summarize the results in the \".t\" and \".p\" files \n");
1019	MrBayesPrint (" using the \"sumt\" and \"sump\" commands, respectively. \n");
1020	MrBayesPrint (" \n");
1021	MrBayesPrint (" MrBayes was originally written by John Huelsenbeck in August of 2000 and was \n");
1022	MrBayesPrint (" intended to be distributed to a small number of people. In March of 2001, \n");
1023	MrBayesPrint (" Fredrik Ronquist started making contributions to the program. The contribu- \n");
1024	MrBayesPrint (" tions were of such a significant nature that he was made a coauthor of the \n");
1025	MrBayesPrint (" program. Version 3 of MrBayes was a fully joint effort, started in the summer \n");
1026	MrBayesPrint (" of 2002 when JPH visited Sweden on a grant from the Wenner-Gren Foundations. \n");
1027	MrBayesPrint (" Several others have contributed to the MrBayes code since then, most notably \n");
1028	MrBayesPrint (" Paul van der Mark and Maxim Teslenko, both postdocs/programmers in Fredrik's \n");
1029	MrBayesPrint (" lab. A large number of users and students, too many to list here, have also \n");
1030	MrBayesPrint (" contributed importantly to the project (type 'Acknowledgments' for a list of \n");
1031	MrBayesPrint (" some of them). \n");
1032	MrBayesPrint (" \n");
1033	MrBayesPrint (" Since 2003, MrBayes has been distributed from SourceForge. Bugs can be repor- \n");
1034	MrBayesPrint (" ted to the MrBayes site on SourceForge or by contacting Maxim Teslenko \n");
1035	MrBayesPrint (" (maxim.teslenko@nrm.se) directly. \n");
1036	MrBayesPrint (" --------------------------------------------------------------------------- \n");
1037
1038	return (NO_ERROR);
1039
1040	}
1041
1042
1043
1044
1045
1046	int DoAcknowledgments (void)
1047
1048	{
1049
1050	MrBayesPrint (" --------------------------------------------------------------------------- \n");
1051	MrBayesPrint (" Acknowledgments \n");
1052	MrBayesPrint (" \n");
1053	MrBayesPrint (" JPH and FR would like to thank Gautam Altekar, Andrea Betancourt, Jon \n");
1054	MrBayesPrint (" Bollback, Barry Hall, Jimmy McGuire, Rasmus Nielsen, David Swofford, \n");
1055	MrBayesPrint (" Johan Nylander, Mikael Thollesson, and Derrick Zwickl for help during the \n");
1056	MrBayesPrint (" initial development of this program. Gautam Altekar, especially, was instru- \n");
1057	MrBayesPrint (" mental in getting the parallel version of the program working. Important bug- \n");
1058	MrBayesPrint (" fixes and additional functionality was contributed by Clemens Lakner, Sebas- \n");
1059	MrBayesPrint (" tian Hoehna, Paul Lewis, Mark Holder, Julian Catchen and Bret Larget. Marc \n");
1060	MrBayesPrint (" Suchard, Daniel Ayres and Aaron Darling got mrbayes working with beagle and \n");
1061	MrBayesPrint (" contributed a lot of related functionality and bug fixes. Aaron Darling was \n");
1062	MrBayesPrint (" instrumental in getting the Windows installer set up. Liu Liang and Dennis \n");
1063	MrBayesPrint (" Pearl helped integrate MrBayes with BEST. \n");
1064	MrBayesPrint (" \n");
1065	MrBayesPrint (" Bug fixes and user support was provided by Paul van der Mark (2005-2007) and \n");
1066	MrBayesPrint (" from 2010 by Maxim Teslenko (maxim.teslenko@nrm.se). \n");
1067	MrBayesPrint (" \n");
1068	MrBayesPrint (" Our wives -- Edna Huelsenbeck and Eva Ronquist -- showed extraordinary \n");
1069	MrBayesPrint (" patience with us while we spent many late nights programming. \n");
1070	MrBayesPrint (" \n");
1071	MrBayesPrint (" JPH was supported by NSF grants DEB-007540 and MCB-0075404 and a Wenner- \n");
1072	MrBayesPrint (" Gren scholarship while writing this program. FR was supported by grants \n");
1073	MrBayesPrint (" from the Swedish Natural Science Research Council and the Swedish Research \n");
1074	MrBayesPrint (" Council. \n");
1075	MrBayesPrint (" --------------------------------------------------------------------------- \n");
1076
1077	return (NO_ERROR);
1078
1079	}
1080
1081
1082
1083
1084
1085	int DoBeginParm (char parmName, char tkn)
1086
1087	{
1088
1089	if (expecting == Expecting(PARAMETER))
1090	{
1091	/* set Data (inDataBlock) *************************************************************/
1092	if (!strcmp(parmName, "Data"))
1093	{
1094	if (FreeModel () == ERROR)
1095	return (ERROR);
1096	if (FreeMatrix () == ERROR)
1097	return (ERROR);
1098	MrBayesPrint (" Reading data block\n");
1099	inDataBlock = YES;
1100	expecting = Expecting(SEMICOLON);
1101	strcpy (spacer, " ");
1102	}
1103	/* set Characters (inCharactersBlock) *************************************************************/
1104	else if (!strcmp(parmName, "Characters"))
1105	{
1106	if (FreeModel () == ERROR)
1107	return (ERROR);
1108	if (FreeCharacters () == ERROR)
1109	return (ERROR);
1110	MrBayesPrint (" Reading characters block\n");
1111	inCharactersBlock = YES;
1112	expecting = Expecting(SEMICOLON);
1113	strcpy (spacer, " ");
1114	}
1115	/* set Taxa (inTaxaBlock) *************************************************************/
1116	else if (!strcmp(parmName, "Taxa"))
1117	{
1118	if (FreeModel () == ERROR)
1119	return (ERROR);
1120	if (FreeMatrix () == ERROR)
1121	return (ERROR);
1122	MrBayesPrint (" Reading taxa block\n");
1123	inTaxaBlock = YES;
1124	expecting = Expecting(SEMICOLON);
1125	strcpy (spacer, " ");
1126	}
1127	/* set Mrbayes (inMrbayesBlock) *******************************************************/
1128	else if (!strcmp(parmName, "Mrbayes"))
1129	{
1130	MrBayesPrint (" Reading mrbayes block\n");
1131	inMrbayesBlock = YES;
1132	expecting = Expecting(SEMICOLON);
1133	strcpy (spacer, " ");
1134	}
1135	/* set Trees (inTreesBlock) *******************************************************/
1136	else if (!strcmp(parmName, "Trees"))
1137	{
1138	MrBayesPrint (" Reading trees block\n");
1139	inTreesBlock = YES;
1140	expecting = Expecting(SEMICOLON);
1141	strcpy (spacer, " ");
1142	}
1143	/* set Foreign (inForeignBlock) *******************************************************/
1144	else
1145	{
1146	MrBayesPrint (" Skipping \"%s\" block\n", tkn);
1147	inForeignBlock = YES;
1148	expecting = Expecting(SEMICOLON);
1149	strcpy (spacer, "");
1150	}
1151	}
1152	else
1153	return (ERROR);
1154
1155	return (NO_ERROR);
1156
1157	}
1158
1159
1160
1161
1162
1163	int DoBreaks (void)
1164
1165	{
1166
1167	int i, numBreaks;
1168
1169	numBreaks = 0;
1170	for (i=0; i<numChar; i++)
1171	{
1172	if (charInfo[i].bigBreakAfter == YES)
1173	{
1174	numBreaks++;
1175	}
1176	}
1177
1178	if (numBreaks > 0)
1179	{
1180	if (numBreaks == 1)
1181	MrBayesPrint ("%s One data break found after character ", spacer, numBreaks);
1182	else
1183	MrBayesPrint ("%s %d data breaks found after characters: ", spacer, numBreaks);
1184	for (i=0; i<numChar; i++)
1185	{
1186	if (charInfo[i].bigBreakAfter == YES)
1187	{
1188	MrBayesPrint ("%d ", i+1);
1189	}
1190	}
1191	MrBayesPrint ("\n");
1192
1193	if (numBreaks == 1)
1194	MrBayesPrint ("%s Successfully defined one break in data\n", spacer);
1195	else
1196	MrBayesPrint ("%s Successfully defined %d breaks in data\n", spacer, numBreaks);
1197	}
1198	else
1199	{
1200	MrBayesPrint ("%s No breaks in data found\n", spacer);
1201	}
1202
1203	return (NO_ERROR);
1204
1205	}
1206
1207
1208
1209
1210
1211	int DoBreaksParm (char parmName, char tkn)
1212
1213	{
1214
1215	int i, tempInt;
1216
1217	if (defMatrix == NO)
1218	{
1219	MrBayesPrint ("%s A matrix must be specified before you can define breaks in the data\n", spacer);
1220	return (ERROR);
1221	}
1222
1223	if (expecting == Expecting(NUMBER))
1224	{
1225	sscanf (tkn, "%d", &tempInt);
1226	if (tempInt <= 0 \|\| tempInt > numChar)
1227	{
1228	MrBayesPrint ("%s Character number %d is out of range (should be between %d and %d)\n", spacer, tempInt, 1, numChar);
1229	for (i=0; i<numChar; i++)
1230	charInfo[i].bigBreakAfter = NO;
1231	return (ERROR);
1232	}
1233	if (tempInt == numChar)
1234	{
1235	MrBayesPrint ("%s Character number %d is the last character. MrBayes will define the\n", spacer, tempInt);
1236	MrBayesPrint ("%s break, even though it doesn't make too much sense.\n", spacer);
1237	}
1238	tempInt--;
1239
1240	charInfo[tempInt].bigBreakAfter = YES;
1241
1242	expecting = (Expecting(NUMBER) \| Expecting(SEMICOLON));
1243	}
1244	else
1245	{
1246	for (i=0; i<numChar; i++)
1247	charInfo[i].bigBreakAfter = NO;
1248	return (ERROR);
1249	}
1250
1251	return (NO_ERROR);
1252	MrBayesPrint ("%s", parmName); /* just because I am tired of seeing the unused parameter error msg */
1253
1254	}
1255
1256
1257
1258
1259
1260	int DoCalibrate (void)
1261
1262	{
1263
1264	int i;
1265
1266	/* show calibration times (for debugging) */
1267	#if 0
1268	MrBayesPrint ("Taxon ages\n");
1269	for (i=0; i<numTaxa; i++)
1270	MrBayesPrint ("%4d -- %s\n", i+1, tipCalibration[i].name);
1271	MrBayesPrint ("Constraint ages\n");
1272	for (i=0; i<numDefinedConstraints; i++)
1273	{
1274	if( definedConstraintsType[i] != HARD )
1275	continue;
1276	MrBayesPrint ("%4d -- %s\n", i+1, nodeCalibration[i].name);
1277	}
1278	#endif
1279
1280	/* Update model if calibrations enforced */
1281	for (i=0; i<numCurrentDivisions; i++)
1282	{
1283	if (!strcmp(modelParams[i].nodeAgePr,"Calibrated"))
1284	{
1285	if (SetUpAnalysis (&globalSeed) == ERROR)
1286	return (ERROR);
1287	break;
1288	}
1289	}
1290
1291	return (NO_ERROR);
1292	}
1293
1294
1295
1296
1297
1298	int DoCalibrateParm (char parmName, char tkn)
1299
1300	{
1301
1302	static int isTaxon;
1303	static char nodeName[100];
1304	int howMany, index;
1305	char s[20], tempStr[100];
1306	MrBFlt tempD;
1307
1308	if (defMatrix == NO)
1309	{
1310	MrBayesPrint ("%s A matrix must be specified before you can calibrate nodes\n", spacer);
1311	return (ERROR);
1312	}
1313
1314	if (expecting == Expecting(PARAMETER))
1315	{
1316	if (strcmp(parmName, "Xxxxxxxxxx") != 0)
1317	{
1318	MrBayesPrint ("%s Unexpected error - Wrong parmName in DoCalibrateParm\n", spacer);
1319	return (ERROR);
1320	}
1321
1322	/* find taxon with this name */
1323	calibrationPtr = NULL;
1324	howMany = 0;
1325
1326	/* first look in constraint names */
1327	if (CheckString (constraintNames, numDefinedConstraints, tkn, &index) != ERROR && definedConstraintsType[index] == HARD )
1328	{
1329	calibrationPtr = &nodeCalibration[index];
1330	howMany++;
1331	isTaxon = NO;
1332	strcpy (nodeName, tkn);
1333	}
1334
1335	/* then look in terminal taxon names */
1336	if (CheckString (taxaNames, numTaxa, tkn, &index) != ERROR)
1337	{
1338	calibrationPtr = &tipCalibration[index];
1339	howMany++;
1340	isTaxon = YES;
1341	strcpy (nodeName, tkn);
1342	}
1343
1344	/* return error if not found or ambiguous */
1345	if (howMany == 0)
1346	{
1347	MrBayesPrint ("%s No taxon or hard constraint named ""%s"" found. Note that only hard constraint can be calibrated.\n", spacer, tkn);
1348	return (ERROR);
1349	}
1350	else if (howMany > 1)
1351	{
1352	MrBayesPrint ("%s Both a taxon and a constraint named ""%s"" encountered -- please rename one\n", spacer, tkn);
1353	return (ERROR);
1354	}
1355
1356	if (calibrationPtr->prior != unconstrained)
1357	{
1358	MrBayesPrint ("%s Resetting previous calibration for ""%s""\n", spacer, tkn);
1359	}
1360
1361	/* reset the values of the calibration */
1362	calibrationPtr->prior = defaultCalibration.prior;
1363	calibrationPtr->age = defaultCalibration.age;
1364	calibrationPtr->lambda = defaultCalibration.lambda;
1365	calibrationPtr->offset = defaultCalibration.offset;
1366	calibrationPtr->min = defaultCalibration.min;
1367	calibrationPtr->max = defaultCalibration.max;
1368	strcpy(calibrationPtr->name, defaultCalibration.name);
1369
1370	/* get ready to find the equal sign */
1371	expecting = Expecting(EQUALSIGN);
1372	}
1373
1374	else if (expecting == Expecting(EQUALSIGN))
1375	{
1376	/* get ready to find the calibration prior */
1377	expecting = Expecting(ALPHA);
1378	}
1379
1380	else if (expecting == Expecting(ALPHA))
1381	{
1382	/* set the calibration prior type */
1383	if (IsArgValid(tkn,tempStr) == NO_ERROR)
1384	{
1385	if (!strcmp (tempStr, "Uniform"))
1386	calibrationPtr->prior = uniform;
1387	else if (!strcmp (tempStr, "Offsetexponential"))
1388	calibrationPtr->prior = offsetExponential;
1389	else if (!strcmp (tempStr, "Fixed"))
1390	calibrationPtr->prior = fixed;
1391	else /* if (!strcmp (tempStr, "Unconstrained")) */
1392	calibrationPtr->prior = unconstrained;
1393	strcpy (calibrationPtr->name, tempStr);
1394	if (calibrationPtr->prior == unconstrained)
1395	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
1396	else
1397	expecting = Expecting(LEFTPAR);
1398	}
1399	else
1400	{
1401	MrBayesPrint ("%s Invalid calibration prior argument \n", spacer);
1402	return (ERROR);
1403	}
1404	}
1405	else if (expecting == Expecting(LEFTPAR))
1406	{
1407	strcat (calibrationPtr->name, "(");
1408	expecting = Expecting(NUMBER);
1409	}
1410	else if (expecting == Expecting(NUMBER))
1411	{
1412	if (calibrationPtr->prior == fixed)
1413	{
1414	sscanf (tkn, "%lf", &tempD);
1415	if (tempD < 0.0)
1416	{
1417	MrBayesPrint ("%s Age must be nonnegative\n", spacer);
1418	calibrationPtr->prior = unconstrained;
1419	return (ERROR);
1420	}
1421	calibrationPtr->age = tempD;
1422	expecting = Expecting(RIGHTPAR);
1423	}
1424	else if (calibrationPtr->prior == uniform)
1425	{
1426	sscanf (tkn, "%lf", &tempD);
1427	if (tempD < 0.0)
1428	{
1429	MrBayesPrint ("%s Age must be nonnegative\n", spacer);
1430	calibrationPtr->prior = unconstrained;
1431	return (ERROR);
1432	}
1433	if (calibrationPtr->min < 0.0)
1434	{
1435	calibrationPtr->min = tempD;
1436	expecting = Expecting(COMMA);
1437	}
1438	else
1439	{
1440	if (tempD <= calibrationPtr->min)
1441	{
1442	MrBayesPrint ("%s Maximum age must be larger than minimum age\n", spacer);
1443	calibrationPtr->prior = unconstrained;
1444	return (ERROR);
1445	}
1446	calibrationPtr->max = tempD;
1447	expecting = Expecting(RIGHTPAR);
1448	}
1449	}
1450	else if (calibrationPtr->prior == offsetExponential)
1451	{
1452	sscanf (tkn, "%lf", &tempD);
1453	if (calibrationPtr->offset < 0.0)
1454	{
1455	if (tempD < 0.0)
1456	{
1457	MrBayesPrint ("%s Offset age must be nonnegative\n", spacer);
1458	calibrationPtr->prior = unconstrained;
1459	return (ERROR);
1460	}
1461	calibrationPtr->offset = tempD;
1462	expecting = Expecting(COMMA);
1463	}
1464	else
1465	{
1466	if (tempD <= OFFSETEXPLAMBDA_MIN)
1467	{
1468	MrBayesPrint ("%s Offset exponential lambda parameter must be larger than %lf\n", spacer, OFFSETEXPLAMBDA_MIN);
1469	calibrationPtr->prior = unconstrained;
1470	return (ERROR);
1471	}
1472	else if (tempD >= OFFSETEXPLAMBDA_MAX)
1473	{
1474	MrBayesPrint ("%s Offset exponential lambda parameter must be smaller than %lf\n", spacer, OFFSETEXPLAMBDA_MAX);
1475	calibrationPtr->prior = unconstrained;
1476	return (ERROR);
1477	}
1478	calibrationPtr->lambda = tempD;
1479	expecting = Expecting(RIGHTPAR);
1480	}
1481	}
1482	sprintf (s, "%1.2lf", tempD);
1483	strcat (calibrationPtr->name, s);
1484	}
1485	else if (expecting == Expecting(COMMA))
1486	{
1487	strcat (calibrationPtr->name, ",");
1488	expecting = Expecting(NUMBER);
1489	}
1490	else if (expecting == Expecting(RIGHTPAR))
1491	{
1492	strcat (calibrationPtr->name, ")");
1493	if (isTaxon == YES)
1494	MrBayesPrint ("%s Setting age of taxon '%s' to %s\n", spacer, nodeName, calibrationPtr->name);
1495	else
1496	MrBayesPrint ("%s Setting age of constraint node '%s' to %s\n", spacer, nodeName, calibrationPtr->name);
1497	/* get ready to find more calibrated nodes or taxa, if present */
1498	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
1499	}
1500	else
1501	return (ERROR);
1502
1503	return (NO_ERROR);
1504
1505	}
1506
1507
1508
1509
1510	int DoCharset (void)
1511
1512	{
1513
1514	/* first add set to tempSet */
1515	if (fromI >= 0 && toJ < 0)
1516	{
1517	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
1518	return (ERROR);
1519	}
1520	else if (fromI >= 0 && toJ >= 0 && everyK < 0)
1521	{
1522	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
1523	return (ERROR);
1524	}
1525	else if (fromI >= 0 && toJ >= 0 && everyK >= 0)
1526	{
1527	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
1528	return (ERROR);
1529	}
1530
1531	/* add name to charSetNames */
1532	if (AddString (&charSetNames, numCharSets, tempSetName) == ERROR)
1533	{
1534	MrBayesPrint ("%s Problem adding charset %s to list\n", spacer, tempSetName);
1535	return (ERROR);
1536	}
1537
1538	/* store charset */
1539	AddBitfield (&charSet, numCharSets, tempSet, numChar);
1540
1541	/* increment number of char sets */
1542	numCharSets++;
1543
1544	return (NO_ERROR);
1545
1546	}
1547
1548
1549
1550
1551
1552	int DoCharsetParm (char parmName, char tkn)
1553
1554	{
1555
1556	int i, index, tempInt, allDigit;
1557
1558	if (defMatrix == NO)
1559	{
1560	MrBayesPrint ("%s A matrix must be specified before charsets can be defined\n", spacer);
1561	return (ERROR);
1562	}
1563
1564	if (expecting == Expecting(PARAMETER))
1565	{
1566	if (!strcmp(parmName, "Xxxxxxxxxx"))
1567	{
1568	/* check that the name of the charset is not a number */
1569	allDigit = YES;
1570	for (i=0; i<(int)strlen(tkn); i++)
1571	{
1572	if (tkn[i] == '0' \|\| tkn[i] == '1' \|\| tkn[i] == '2' \|\| tkn[i] == '3' \|\| tkn[i] == '4' \|\|
1573	tkn[i] == '5' \|\| tkn[i] == '6' \|\| tkn[i] == '7' \|\| tkn[i] == '8' \|\| tkn[i] == '9' \|\| tkn[i] == '.')
1574	{}
1575	else
1576	allDigit = NO;
1577	}
1578	if (allDigit == YES)
1579	{
1580	MrBayesPrint ("%s Charset name may not be a number\n", spacer);
1581	return (ERROR);
1582	}
1583
1584	/* check size of charset name */
1585	if (strlen(tkn) > 99)
1586	{
1587	MrBayesPrint ("%s Charset name is too long\n", spacer);
1588	return (ERROR);
1589	}
1590
1591	/* check to see if the name has already been used as a charset */
1592	if (numCharSets > 1)
1593	{
1594	if (CheckString (charSetNames, numCharSets, tkn, &index) == ERROR)
1595	{
1596	/* if the charset name has not been used, then we should have an ERROR returned */
1597	/* we _want_ to be here */
1598
1599	}
1600	else
1601	{
1602	MrBayesPrint ("%s Charset name has been used previously\n", spacer);
1603	return (ERROR);
1604	}
1605	}
1606
1607	/* add the name to the character set */
1608	strcpy (tempSetName, tkn);
1609
1610	/* clear tempSet */
1611	for (i=0; i<numChar; i++)
1612	tempSet[i] = 0;
1613
1614	fromI = toJ = everyK = -1;
1615	foundDash = foundSlash = NO;
1616	MrBayesPrint ("%s Defining charset called %s\n", spacer, tkn);
1617	expecting = Expecting(EQUALSIGN);
1618	}
1619	else
1620	return (ERROR);
1621	}
1622	else if (expecting == Expecting(EQUALSIGN))
1623	{
1624	expecting = Expecting(ALPHA);
1625	expecting \|= Expecting(NUMBER);
1626	}
1627	else if (expecting == Expecting(ALPHA))
1628	{
1629	/* We are defining a character set in terms of another (called tkn, here). We should be able
1630	to find tkn in the list of character set names. If we cannot, then we have a problem and
1631	return an error. */
1632	if (numCharSets < 1)
1633	{
1634	MrBayesPrint ("%s Could not find a character set called %s\n", spacer, tkn);
1635	return (ERROR);
1636	}
1637	if (CheckString (charSetNames, numCharSets, tkn, &index) == ERROR)
1638	{
1639	MrBayesPrint ("%s Could not find a character set called %s\n", spacer, tkn);
1640	return (ERROR);
1641	}
1642	/* add characters from charset "tkn" to new tempset */
1643	for (i=0; i<numChar; i++)
1644	{
1645	if (IsBitSet(i,charSet[index]) == YES)
1646	tempSet[i] = 1;
1647	}
1648	fromI = toJ = everyK = -1;
1649
1650	expecting = Expecting(ALPHA);
1651	expecting \|= Expecting(NUMBER);
1652	expecting \|= Expecting(SEMICOLON);
1653	}
1654	else if (expecting == Expecting(NUMBER))
1655	{
1656	if (strlen(tkn) == 1 && tkn[0] == '.')
1657	tempInt = numChar;
1658	else
1659	sscanf (tkn, "%d", &tempInt);
1660	if (tempInt <= 0 \|\| tempInt > numChar)
1661	{
1662	MrBayesPrint ("%s Character number %d is out of range (should be between %d and %d)\n", spacer, tempInt, 1, numChar);
1663	return (ERROR);
1664	}
1665	tempInt--;
1666	if (foundDash == YES)
1667	{
1668	if (fromI >= 0)
1669	toJ = tempInt;
1670	else
1671	{
1672	MrBayesPrint ("%s Improperly formatted charset\n", spacer);
1673	return (ERROR);
1674	}
1675	foundDash = NO;
1676	}
1677	else if (foundSlash == YES)
1678	{
1679	tempInt++;
1680	if (tempInt <= 1)
1681	{
1682	MrBayesPrint ("%s Improperly formatted charset\n", spacer);
1683	return (ERROR);
1684	}
1685	if (fromI >= 0 && toJ >= 0 && fromI < toJ)
1686	everyK = tempInt;
1687	else
1688	{
1689	MrBayesPrint ("%s Improperly formatted charset\n", spacer);
1690	return (ERROR);
1691	}
1692	foundSlash = NO;
1693	}
1694	else
1695	{
1696	if (fromI >= 0 && toJ < 0)
1697	{
1698	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
1699	return (ERROR);
1700	fromI = tempInt;
1701	}
1702	else if (fromI < 0 && toJ < 0)
1703	{
1704	fromI = tempInt;
1705	}
1706	else if (fromI >= 0 && toJ >= 0 && everyK < 0)
1707	{
1708	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
1709	return (ERROR);
1710	fromI = tempInt;
1711	toJ = everyK = -1;
1712	}
1713	else if (fromI >= 0 && toJ >= 0 && everyK >= 0)
1714	{
1715	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
1716	return (ERROR);
1717	fromI = tempInt;
1718	toJ = everyK = -1;
1719	}
1720	else
1721	{
1722	MrBayesPrint ("%s Improperly formatted charset\n", spacer);
1723	{
1724	return (ERROR);
1725	}
1726	}
1727
1728	}
1729
1730
1731	expecting = Expecting(ALPHA);
1732	expecting \|= Expecting(NUMBER);
1733	expecting \|= Expecting(SEMICOLON);
1734	expecting \|= Expecting(DASH);
1735	expecting \|= Expecting(BACKSLASH);
1736	}
1737	else if (expecting == Expecting(DASH))
1738	{
1739	foundDash = YES;
1740	expecting = Expecting(NUMBER);
1741	}
1742	else if (expecting == Expecting(BACKSLASH))
1743	{
1744	foundSlash = YES;
1745	expecting = Expecting(NUMBER);
1746	}
1747	else
1748	return (ERROR);
1749
1750	return (NO_ERROR);
1751
1752	}
1753
1754
1755
1756
1757
1758	int DoCharStat (void)
1759
1760	{
1761
1762	int i, j, numDivs;
1763	char tempName[100];
1764
1765	if (defMatrix == NO)
1766	{
1767	MrBayesPrint ("%s A character matrix must be defined first\n", spacer);
1768	return (ERROR);
1769	}
1770
1771	if (numDefinedPartitions == 1)
1772	MrBayesPrint ("%s 1 character partition defined:\n", spacer, numDefinedPartitions);
1773	else
1774	MrBayesPrint ("%s %d character partitions defined:\n", spacer, numDefinedPartitions);
1775	for (i=0; i<numDefinedPartitions; i++)
1776	{
1777	numDivs = GetNumPartDivisions (i+1);
1778	if (numDivs == 1)
1779	MrBayesPrint ("%s Partition %d (\"%s\") does not divide the characters\n", spacer, i+1, partitionNames[i]);
1780	else
1781	MrBayesPrint ("%s Partition %d (\"%s\") divides the characters into %d parts\n", spacer, i+1, partitionNames[i], numDivs);
1782	}
1783	MrBayesPrint ("%s Current partition is \"%s\"\n", spacer, partitionNames[partitionNum]);
1784	MrBayesPrint ("\n");
1785
1786	/* print out list of characters with information about each */
1787	MrBayesPrint ("%s Showing character status:\n\n", spacer);
1788	MrBayesPrint ("%s Partition(s)\n", spacer);
1789	MrBayesPrint ("%s # Type In/Out Ambiguity Order ", spacer);
1790	for (i=0; i<numDefinedPartitions; i++)
1791	MrBayesPrint (" %2d", i+1);
1792	MrBayesPrint ("\n");
1793	MrBayesPrint ("%s -----------------------------------------------", spacer);
1794	for (i=0; i<numDefinedPartitions; i++)
1795	MrBayesPrint ("---");
1796	MrBayesPrint ("\n");
1797	for (i=0; i<numChar; i++)
1798	{
1799	MrBayesPrint ("%s %4d -- ", spacer, i+1);
1800
1801	if (charInfo[i].charType == DNA)
1802	MrBayesPrint (" DNA");
1803	else if (charInfo[i].charType == RNA)
1804	MrBayesPrint (" RNA");
1805	else if (charInfo[i].charType == PROTEIN)
1806	MrBayesPrint (" Prot");
1807	else if (charInfo[i].charType == RESTRICTION)
1808	MrBayesPrint (" Rest");
1809	else if (charInfo[i].charType == STANDARD)
1810	MrBayesPrint (" Stand");
1811	else if (charInfo[i].charType == CONTINUOUS)
1812	MrBayesPrint (" Cont");
1813
1814	if (charInfo[i].charType == DNA)
1815	MrBayesPrint (" 4");
1816	else if (charInfo[i].charType == RNA)
1817	MrBayesPrint (" 4");
1818	else if (charInfo[i].charType == PROTEIN)
1819	MrBayesPrint (" 20");
1820	else if (charInfo[i].charType == RESTRICTION)
1821	MrBayesPrint (" 2");
1822	else if (charInfo[i].charType == STANDARD)
1823	MrBayesPrint (" %2d", charInfo[i].numStates);
1824	else if (charInfo[i].charType == CONTINUOUS)
1825	MrBayesPrint (" Inf");
1826
1827	if (charInfo[i].isExcluded == NO)
1828	MrBayesPrint (" Included");
1829	else
1830	MrBayesPrint (" Excluded");
1831
1832	if (charInfo[i].isMissAmbig == YES)
1833	MrBayesPrint (" MissAmbig");
1834	else
1835	MrBayesPrint (" None");
1836
1837	if (charInfo[i].ctype == UNORD)
1838	MrBayesPrint (" Unord");
1839	else if (charInfo[i].ctype == ORD)
1840	MrBayesPrint (" Ord");
1841	else if (charInfo[i].ctype == DOLLO)
1842	MrBayesPrint (" Dollo");
1843	else if (charInfo[i].ctype == IRREV)
1844	MrBayesPrint (" Irrev");
1845
1846	MrBayesPrint (" ");
1847
1848	for (j=0; j<numDefinedPartitions; j++)
1849	MrBayesPrint (" %2d", partitionId[i][j]);
1850
1851	/* MrBayesPrint ("%4d ", charSet[i]);*/
1852
1853	if (charInfo[i].pairsId > 0)
1854	{
1855	/* find paired character */
1856	for (j=0; j<numChar; j++)
1857	{
1858	if (i != j && charInfo[j].pairsId == charInfo[i].pairsId)
1859	{
1860	MrBayesPrint (" (coupled with %d)", j+1);
1861	break;
1862	}
1863	}
1864	}
1865
1866	MrBayesPrint ("\n");
1867
1868	if (charInfo[i].bigBreakAfter == YES)
1869	{
1870	MrBayesPrint ("%s ", spacer);
1871	MrBayesPrint (" - - - - - - - - - - - - - - - - - - - - \n");
1872	}
1873
1874	/* we may want to pause */
1875	if (autoClose == NO)
1876	{
1877	if ((i+1) % 100 == 0)
1878	{
1879	MrBayesPrint ("%s Hit return key to continue ", spacer);
1880	fflush (stdin);
1881	if( fgets (tempName, 100, stdin) == NULL )
1882	{
1883	printf("Error in function: %s at line: %d in file: %s", __FUNCTION__, __LINE__, __FILE__);
1884	}
1885	}
1886	}
1887	}
1888
1889	return (NO_ERROR);
1890
1891	}
1892
1893
1894
1895
1896
1897	int DoCitations (void)
1898
1899	{
1900
1901	MrBayesPrint (" --------------------------------------------------------------------------- \n");
1902	MrBayesPrint (" Citations \n");
1903	MrBayesPrint (" \n");
1904	MrBayesPrint (" If you publish results obtained using MrBayes you may want to cite the \n");
1905	MrBayesPrint (" program using one of these papers: \n");
1906	MrBayesPrint (" \n");
1907	MrBayesPrint (" Huelsenbeck, J. P. and F. Ronquist. 2001. MRBAYES: Bayesian \n");
1908	MrBayesPrint (" inference of phylogeny. Bioinformatics 17:754-755. \n");
1909	MrBayesPrint (" Ronquist, F. and J. P. Huelsenbeck. 2003. MRBAYES 3: Bayesian phylogenetic \n");
1910	MrBayesPrint (" inference under mixed models. Bioinformatics 19:1572-1574. \n");
1911	MrBayesPrint (" Ronquist, F. et al. 2012. MRBAYES 3.2: Efficient Bayesian phylogenetic \n");
1912	MrBayesPrint (" inference and model selection across a large model space. Systematic \n");
1913	MrBayesPrint (" Biology 61 (in press). \n");
1914	MrBayesPrint (" \n");
1915	MrBayesPrint (" If you use the parallel abilities of the program, you may also want to cite \n");
1916	MrBayesPrint (" \n");
1917	MrBayesPrint (" Altekar, G., S. Dwarkadas, J. P. Huelsenbeck, and F. Ronquist. 2004. \n");
1918	MrBayesPrint (" Parallel Metropolis-coupled Markov chain Monte Carlo for Bayesian \n");
1919	MrBayesPrint (" phylogenetic inference. Bioinformatics 20:407-415. \n");
1920	MrBayesPrint (" \n");
1921	MrBayesPrint (" If you use the BEAGLE library, the appropriate citation is \n");
1922	MrBayesPrint (" \n");
1923	MrBayesPrint (" Ayres, D. L., A. Darling, D. J. Zwickl, P. Beerli, M. T. Holder, P. O. \n");
1924	MrBayesPrint (" J. P. Huelsenbeck, F. Ronquist, D. L. Swofford, M. P. Cummings, A. \n");
1925	MrBayesPrint (" Rambaut, and M. A. Suchard. 2012. BEAGLE: an application programming \n");
1926	MrBayesPrint (" interface for statistical phylogenetics. Syst. Biol. 61:170-173. \n");
1927	MrBayesPrint (" \n");
1928	MrBayesPrint (" \n");
1929	MrBayesPrint (" You should also cite other papers for different ideas that are implemented \n");
1930	MrBayesPrint (" in the program. For example, the program performs Bayesian inference of \n");
1931	MrBayesPrint (" phylogeny, an idea that was first proposed in the following papers: \n");
1932	MrBayesPrint (" \n");
1933	MrBayesPrint (" Larget, B., and D. Simon. 1999. Markov chain Monte Carlo \n");
1934	MrBayesPrint (" algorithms for the Bayesian analysis of phylogenetic trees. \n");
1935	MrBayesPrint (" Mol. Biol. Evol. 16:750-759. \n");
1936	MrBayesPrint (" \n");
1937	MrBayesPrint (" Li, S. 1996. Phylogenetic tree construction using Markov chain \n");
1938	MrBayesPrint (" Monte carlo. Ph. D. dissertation, Ohio State University, Columbus. \n");
1939	MrBayesPrint (" \n");
1940	MrBayesPrint (" Mau, B. 1996. Bayesian phylogenetic inference via Markov chain \n");
1941	MrBayesPrint (" Monte carlo methods. Ph. D. dissertation, University of \n");
1942	MrBayesPrint (" Wisconsin, Madison. \n");
1943	MrBayesPrint (" \n");
1944	MrBayesPrint (" Mau, B., and M. Newton. 1997. Phylogenetic inference for binary \n");
1945	MrBayesPrint (" data on dendrograms using Markov chain Monte Carlo. Journal of \n");
1946	MrBayesPrint (" Computational and Graphical Statistics 6:122-131. \n");
1947	MrBayesPrint (" \n");
1948	MrBayesPrint (" Mau, B., M. Newton, and B. Larget. 1999. Bayesian phylogenetic \n");
1949	MrBayesPrint (" inference via Markov chain Monte carlo methods. Biometrics. 55:1-12. \n");
1950	MrBayesPrint (" \n");
1951	MrBayesPrint (" Newton, M., B. Mau, and B. Larget. 1999. Markov chain Monte Carlo \n");
1952	MrBayesPrint (" for the Bayesian analysis of evolutionary trees from aligned \n");
1953	MrBayesPrint (" molecular sequences. In Statistics in molecular biology (F. Seillier- \n");
1954	MrBayesPrint (" Moseiwitch, T. P. Speed, and M. Waterman, eds.). Monograph Series \n");
1955	MrBayesPrint (" of the Institute of Mathematical Statistics. \n");
1956	MrBayesPrint (" \n");
1957	MrBayesPrint (" Rannala, B., and Z. Yang. 1996. Probability distribution of \n");
1958	MrBayesPrint (" molecular evolutionary trees: a new method of phylogenetic \n");
1959	MrBayesPrint (" inference. J. Mol. Evol. 43:304-311. \n");
1960	MrBayesPrint (" \n");
1961	MrBayesPrint (" Yang, Z., and B. Rannala. 1997. Bayesian phylogenetic inference \n");
1962	MrBayesPrint (" using DNA sequences: a Markov chain Monte carlo method. Molecular \n");
1963	MrBayesPrint (" Biology and Evolution. 14:717-724. \n");
1964	MrBayesPrint (" \n");
1965	MrBayesPrint (" \n");
1966	MrBayesPrint (" MrBayes uses Markov chain Monte Carlo (MCMC) to approximate the posterior \n");
1967	MrBayesPrint (" probability of trees. MCMC was developed in the following papers: \n");
1968	MrBayesPrint (" \n");
1969	MrBayesPrint (" Metropolis, N., A. W. Rosenbluth, M. N. Rosenbluth, A. H. Teller, \n");
1970	MrBayesPrint (" and E. Teller. 1953. Equations of state calculations by fast \n");
1971	MrBayesPrint (" computing machines. J. Chem. Phys. 21:1087-1091. \n");
1972	MrBayesPrint (" \n");
1973	MrBayesPrint (" Hastings, W. K. 1970. Monte Carlo sampling methods using Markov \n");
1974	MrBayesPrint (" chains and their applications. Biometrika 57:97-109. \n");
1975	MrBayesPrint (" \n");
1976	MrBayesPrint (" In particular, MrBayes implements a variant of MCMC that was described by \n");
1977	MrBayesPrint (" Charles Geyer: \n");
1978	MrBayesPrint (" \n");
1979	MrBayesPrint (" Geyer, C. J. 1991. Markov chain Monte Carlo maximum likelihood. \n");
1980	MrBayesPrint (" Pages 156-163 in Computing Science and Statistics: Proceed- \n");
1981	MrBayesPrint (" ings of the 23rd Symposium on the Interface. (E. M. Keramidas, \n");
1982	MrBayesPrint (" ed.). Fairfax Station: Interface Foundation. \n");
1983	MrBayesPrint (" \n");
1984	MrBayesPrint (" \n");
1985	MrBayesPrint (" MrBayes implements a large number of DNA substitution models. These models \n");
1986	MrBayesPrint (" are of three different structures. The \"4by4\" models are the usual \n");
1987	MrBayesPrint (" flavor of phylogenetic models. The \"Doublet\" model was first proposed \n");
1988	MrBayesPrint (" by \n");
1989	MrBayesPrint (" \n");
1990	MrBayesPrint (" Schoniger, M., and A. von Haeseler. 1994. A stochastic model and the \n");
1991	MrBayesPrint (" evolution of autocorrelated DNA sequences. Molecular Phylogenetics \n");
1992	MrBayesPrint (" and Evolution 3:240-247. \n");
1993	MrBayesPrint (" \n");
1994	MrBayesPrint (" The program also implements codon models. Two papers, published back-to-back \n");
1995	MrBayesPrint (" were the first to implement a codon model of DNA substitution in which the \n");
1996	MrBayesPrint (" substitution process is modelled on the codon, not on a site-by-site basis: \n");
1997	MrBayesPrint (" \n");
1998	MrBayesPrint (" Goldman, N., and Z. Yang. 1994. A codon-based model of nucleotide \n");
1999	MrBayesPrint (" substitution for protein coding DNA sequences. Molecular Biology \n");
2000	MrBayesPrint (" and Evolution. 11:725-736. \n");
2001	MrBayesPrint (" \n");
2002	MrBayesPrint (" Muse, S., and B. Gaut. 1994. A likelihood approach for comparing \n");
2003	MrBayesPrint (" synonymous and non-synonymous substitution rates, with application \n");
2004	MrBayesPrint (" to the chloroplast genome. Molecular Biology and Evolution. \n");
2005	MrBayesPrint (" 11:715-724. \n");
2006	MrBayesPrint (" \n");
2007	MrBayesPrint (" The program can be used to detect positively slected amino-acid sites using \n");
2008	MrBayesPrint (" a full hierarchical Bayes analysis. The method is based on the excellent paper\n");
2009	MrBayesPrint (" by Nielsen and Yang: \n");
2010	MrBayesPrint (" \n");
2011	MrBayesPrint (" Nielsen, R., and Z. Yang. 1998. Likelihood models for detecting \n");
2012	MrBayesPrint (" positively selected amino acid sites and applications to the HIV-1 \n");
2013	MrBayesPrint (" envelope gene. Genetics. 148:929-936. \n");
2014	MrBayesPrint (" \n");
2015	MrBayesPrint (" The previous four papers describe three different stuctures for the nuc- \n");
2016	MrBayesPrint (" leotide models implemented in MrBayes--the four-by-four models, the \n");
2017	MrBayesPrint (" 16-by-16 (doublet) models and the 64-by-64 (codon) models. The program \n");
2018	MrBayesPrint (" implements three different substitution models within each model structure. \n");
2019	MrBayesPrint (" These include the nst=1 models: \n");
2020	MrBayesPrint (" \n");
2021	MrBayesPrint (" Jukes, T., and C. Cantor. 1969. Evolution of protein molecules. \n");
2022	MrBayesPrint (" Pages 21-132 in Mammalian Protein Metabolism. (H. Munro, ed.). \n");
2023	MrBayesPrint (" Academic Press, New York. \n");
2024	MrBayesPrint (" \n");
2025	MrBayesPrint (" Felsenstein, J. 1981. Evolutionary trees from DNA sequences: A \n");
2026	MrBayesPrint (" maximum likelihood approach. Journal of Molecular Evolution \n");
2027	MrBayesPrint (" 17:368-376. \n");
2028	MrBayesPrint (" \n");
2029	MrBayesPrint (" the nst=2 models: \n");
2030	MrBayesPrint (" \n");
2031	MrBayesPrint (" Kimura, M. 1980. A simple method for estimating evolutionary rates \n");
2032	MrBayesPrint (" of base substitutions through comparative studies of nucleotide \n");
2033	MrBayesPrint (" sequences. Journal of Molecular Evolution. 16:111-120. \n");
2034	MrBayesPrint (" \n");
2035	MrBayesPrint (" Hasegawa, M., T. Yano, and H. Kishino. 1984. A new molecular clock \n");
2036	MrBayesPrint (" of mitochondrial DNA and the evolution of Hominoids. Proc. \n");
2037	MrBayesPrint (" Japan Acad. Ser. B 60:95-98. \n");
2038	MrBayesPrint (" \n");
2039	MrBayesPrint (" Hasegawa, M., H. Kishino, and T. Yano. 1985. Dating the human-ape \n");
2040	MrBayesPrint (" split by a molecular clock of mitochondrial DNA. Journal of \n");
2041	MrBayesPrint (" Molecular Evolution 22:160-174. \n");
2042	MrBayesPrint (" \n");
2043	MrBayesPrint (" and the the nst=6 models: \n");
2044	MrBayesPrint (" \n");
2045	MrBayesPrint (" Tavare, S. 1986. Some probabilistic and statisical problems on the \n");
2046	MrBayesPrint (" analysis of DNA sequences. Lect. Math. Life Sci. 17:57-86. \n");
2047	MrBayesPrint (" 17:368-376. \n");
2048	MrBayesPrint (" \n");
2049	MrBayesPrint (" \n");
2050	MrBayesPrint (" MrBayes implements a large number of amino-acid models. These include: \n");
2051	MrBayesPrint (" \n");
2052	MrBayesPrint (" Poisson -- \n");
2053	MrBayesPrint (" \n");
2054	MrBayesPrint (" Bishop, M.J., and A.E. Friday. 1987. Tetropad relationships: the \n");
2055	MrBayesPrint (" molecular evidence. Pp. 123ï¿œ139 in Molecules and morphology in \n");
2056	MrBayesPrint (" evolution: conflict or compromise? (C. Patterson, ed.). Cambridge \n");
2057	MrBayesPrint (" University Press, Cambridge, England. \n");
2058	MrBayesPrint (" \n");
2059	MrBayesPrint (" Jones -- \n");
2060	MrBayesPrint (" \n");
2061	MrBayesPrint (" Jones, D.T., W. R. Taylor, and J. M. Thornton. 1992. The rapid generation \n");
2062	MrBayesPrint (" of mutation data matrices from protein sequences. Comput. Appl. \n");
2063	MrBayesPrint (" Biosci. 8:275ï¿œ282. \n");
2064	MrBayesPrint (" \n");
2065	MrBayesPrint (" Dayhoff -- \n");
2066	MrBayesPrint (" \n");
2067	MrBayesPrint (" Dayhoff, M.O., R.M. Schwartz, and B.C. Orcutt. 1978. A model of evol- \n");
2068	MrBayesPrint (" utionary change in proteins. Pp. 345ï¿œ352 in Atlas of protein sequence \n");
2069	MrBayesPrint (" and structure. Vol. 5, Suppl. 3. National Biomedical Research \n");
2070	MrBayesPrint (" Foundation, Washington, D.C. \n");
2071	MrBayesPrint (" \n");
2072	MrBayesPrint (" Mtrev -- \n");
2073	MrBayesPrint (" \n");
2074	MrBayesPrint (" Adachi, J. and M. Hasegawa. 1996. MOLPHY version 2.3: programs for \n");
2075	MrBayesPrint (" molecular phylogenetics based on maximum likelihood. Computer Science \n");
2076	MrBayesPrint (" Monographs of Institute of Statistical Mathematics 28:1-150. \n");
2077	MrBayesPrint (" \n");
2078	MrBayesPrint (" Mtmam -- \n");
2079	MrBayesPrint (" \n");
2080	MrBayesPrint (" Cao, Y., A. Janke, P.J. Waddell, M. Westerman, O. Takenaka, S. Murata, \n");
2081	MrBayesPrint (" N. Okada, S. Paabo, and M. Hasegawa. 1998. Conflict amongst individual \n");
2082	MrBayesPrint (" mitochondrial proteins in resolving the phylogeny of eutherian orders. \n");
2083	MrBayesPrint (" Journal of Molecular Evolution \n");
2084	MrBayesPrint (" \n");
2085	MrBayesPrint (" Yang, Z., R. Nielsen, and M. Hasegawa. 1998. Models of amino acid \n");
2086	MrBayesPrint (" substitution and applications to mitochondrial protein evolution \n");
2087	MrBayesPrint (" Molecular Biology and Evolution 15:1600ï¿œ1611. \n");
2088	MrBayesPrint (" \n");
2089	MrBayesPrint (" WAG -- \n");
2090	MrBayesPrint (" \n");
2091	MrBayesPrint (" Whelan, S. and Goldman, N. 2001. A general empirical model of protein \n");
2092	MrBayesPrint (" evolution derived from multiple protein families using a maximum- \n");
2093	MrBayesPrint (" likelihood approach. Molecular Biology and Evolution 18:691-699. \n");
2094	MrBayesPrint (" \n");
2095	MrBayesPrint (" Rtrev -- \n");
2096	MrBayesPrint (" \n");
2097	MrBayesPrint (" Dimmic M.W., J.S. Rest, D.P. Mindell, and D. Goldstein. 2002. RArtREV: \n");
2098	MrBayesPrint (" An amino acid substitution matrix for inference of retrovirus and \n");
2099	MrBayesPrint (" reverse transcriptase phylogeny. Journal of Molecular Evolution \n");
2100	MrBayesPrint (" 55: 65-73. \n");
2101	MrBayesPrint (" \n");
2102	MrBayesPrint (" Cprev -- \n");
2103	MrBayesPrint (" \n");
2104	MrBayesPrint (" Adachi, J., P. Waddell, W. Martin, and M. Hasegawa. 2000. Plastid \n");
2105	MrBayesPrint (" genome phylogeny and a model of amino acid substitution for proteins \n");
2106	MrBayesPrint (" encoded by chloroplast DNA. Journal of Molecular Evolution \n");
2107	MrBayesPrint (" 50:348-358. \n");
2108	MrBayesPrint (" \n");
2109	MrBayesPrint (" Blosum -- \n");
2110	MrBayesPrint (" \n");
2111	MrBayesPrint (" Henikoff, S., and J. G. Henikoff. 1992. Amino acid substitution \n");
2112	MrBayesPrint (" matrices from protein blocks. Proc. Natl. Acad. Sci., U.S.A. \n");
2113	MrBayesPrint (" 89:10915-10919. The matrix implemented in MrBayes is Blosum62. \n");
2114	MrBayesPrint (" \n");
2115	MrBayesPrint (" Vt -- \n");
2116	MrBayesPrint (" \n");
2117	MrBayesPrint (" Muller, T., and M. Vingron. 2000. Modeling amino acid replacement. \n");
2118	MrBayesPrint (" Journal of Computational Biology 7:761-776. \n");
2119	MrBayesPrint (" \n");
2120	MrBayesPrint (" \n");
2121	MrBayesPrint (" MrBayes implements a simple Jukes-Cantor-like model for restriction sites \n");
2122	MrBayesPrint (" and other binary data. A problem with some of these data is that there is a \n");
2123	MrBayesPrint (" coding bias, such that certain characters are missing from any observable \n");
2124	MrBayesPrint (" data matrix. It is impossible, for instance, to observe restriction sites that\n");
2125	MrBayesPrint (" are absent in all the studied taxa. However, MrBayes corrects for this coding \n");
2126	MrBayesPrint (" bias according to an idea described in \n");
2127	MrBayesPrint (" \n");
2128	MrBayesPrint (" Felsenstein, J. 1992. Phylogenies from restriction sites: A maximum- \n");
2129	MrBayesPrint (" likelihood approach. Evolution 46:159-173. \n");
2130	MrBayesPrint (" \n");
2131	MrBayesPrint (" \n");
2132	MrBayesPrint (" The model used by MrBayes for 'standard' or morphological data is based on \n");
2133	MrBayesPrint (" the ideas originally presented by \n");
2134	MrBayesPrint (" \n");
2135	MrBayesPrint (" Lewis, P. O. 2001. A likelihood approach to estimating phylogeny from \n");
2136	MrBayesPrint (" discrete morphological character data. Systematic Biology 50:913-925. \n");
2137	MrBayesPrint (" \n");
2138	MrBayesPrint (" \n");
2139	MrBayesPrint (" For both DNA sequence and amino-acid data, the program allows rates to \n");
2140	MrBayesPrint (" change under a covarion-like model, first described by Tuffley and Steel \n");
2141	MrBayesPrint (" \n");
2142	MrBayesPrint (" Tuffley, C., and M. Steel. 1998. Modeling the covarion hypothesis \n");
2143	MrBayesPrint (" of nucleotide substitution. Mathematical Biosciences 147:63-91. \n");
2144	MrBayesPrint (" \n");
2145	MrBayesPrint (" and implemented by Huelsenbeck (2002) \n");
2146	MrBayesPrint (" \n");
2147	MrBayesPrint (" Huelsenbeck, J. P. 2002. Testing a covariotide model of DNA sub- \n");
2148	MrBayesPrint (" stitution. Molecular Biology and Evolution 19(5):698-707. \n");
2149	MrBayesPrint (" \n");
2150	MrBayesPrint (" Galtier (2001) implements a different variant of the covarion model in \n");
2151	MrBayesPrint (" a paper that is worth reading: \n");
2152	MrBayesPrint (" \n");
2153	MrBayesPrint (" Galtier, N. 2001. Maximum-likelihood phylogenetic analysis under a \n");
2154	MrBayesPrint (" covarion-like model. Mol. Biol. Evol. 18:866-873. \n");
2155	MrBayesPrint (" \n");
2156	MrBayesPrint (" \n");
2157	MrBayesPrint (" A number of models are available that allow rates to vary \n");
2158	MrBayesPrint (" across the characters. The program implements the proportion \n");
2159	MrBayesPrint (" of invariable sites model and two variants of gamma distributed \n");
2160	MrBayesPrint (" rate variation. Yang\'s (1993) paper is a good one to cite for \n");
2161	MrBayesPrint (" implementing a gamma-distributed rates model. In the 1994 paper he \n");
2162	MrBayesPrint (" provides a way to approximate the continuous gamma distribution: \n");
2163	MrBayesPrint (" \n");
2164	MrBayesPrint (" Yang, Z. 1993. Maximum likelihood estimation of phylogeny from DNA \n");
2165	MrBayesPrint (" sequences when substitution rates differ over sites. Molecular \n");
2166	MrBayesPrint (" Biology and Evolution 10:1396-1401. \n");
2167	MrBayesPrint (" \n");
2168	MrBayesPrint (" Yang, Z. 1994. Maximum likelihood phylogenetic estimation from DNA \n");
2169	MrBayesPrint (" sequences with variable rates over sites: Approximate methods. \n");
2170	MrBayesPrint (" Journal of Molecular Evolution 39:306-314. \n");
2171	MrBayesPrint (" \n");
2172	MrBayesPrint (" The program also implements Yang\'s autocorrelated gamma model. In \n");
2173	MrBayesPrint (" this model, the rate at one site depends to some extent on the rate at \n");
2174	MrBayesPrint (" an adjacent site. The appropriate citation for this model is: \n");
2175	MrBayesPrint (" \n");
2176	MrBayesPrint (" Yang, Z. 1995. A space-time process model for the evolution of \n");
2177	MrBayesPrint (" DNA sequences. Genetics 139:993-1005. \n");
2178	MrBayesPrint (" \n");
2179	MrBayesPrint (" \n");
2180	MrBayesPrint (" The following two papers show how ancestral states on a tree can be recon- \n");
2181	MrBayesPrint (" structed. The Yang et al. paper implements an empirical Bayes approach while \n");
2182	MrBayesPrint (" Huelsenbeck and Bollback use a pure, hierarchical Bayes approach. The method \n");
2183	MrBayesPrint (" used in MrBayes is the latter, since it integrates over uncertainty in model \n");
2184	MrBayesPrint (" parameters. \n");
2185	MrBayesPrint (" \n");
2186	MrBayesPrint (" Yang, Z., S. Kumar, and M. Nei. 1995. A new method of inference of \n");
2187	MrBayesPrint (" ancestral nucleotide and amino acid sequences. Genetics 141:1641 \n");
2188	MrBayesPrint (" 1650. \n");
2189	MrBayesPrint (" \n");
2190	MrBayesPrint (" Huelsenbeck, J. P., and J. P. Bollback. 2001. Empirical and hier- \n");
2191	MrBayesPrint (" archical Bayesian estimation of ancestral states. Systematic \n");
2192	MrBayesPrint (" Biology 50:351-366. \n");
2193	MrBayesPrint (" \n");
2194	MrBayesPrint (" You may also want to consult a more recent review of Bayesian reconstruction \n");
2195	MrBayesPrint (" of ancestral states and character evolution: \n");
2196	MrBayesPrint (" \n");
2197	MrBayesPrint (" Ronquist, F. 2004. Bayesian inference of character evolution. Trends in \n");
2198	MrBayesPrint (" Ecology and Evolution 19: 475-481. \n");
2199	MrBayesPrint (" \n");
2200	MrBayesPrint (" \n");
2201	MrBayesPrint (" MrBayes allows you to analyze gene tree - species tree problems using the \n");
2202	MrBayesPrint (" multi-species coalescent approach originally proposed by Edwards et al: \n");
2203	MrBayesPrint (" \n");
2204	MrBayesPrint (" Edwards, S., L. Liu, and D. Pearl. 2007. High-resolution species trees \n");
2205	MrBayesPrint (" without concatenation. Proc. Natl. Acad. Sci. USA 104: 5936-5941. \n");
2206	MrBayesPrint (" \n");
2207	MrBayesPrint (" \n");
2208	MrBayesPrint (" The program implements an incredibly parameter rich model, first described \n");
2209	MrBayesPrint (" by Tuffley and Steel (1997), that orders trees in the same way as the \n");
2210	MrBayesPrint (" so-called parsimony method of phylogenetic inference. The appropriate \n");
2211	MrBayesPrint (" citation is: \n");
2212	MrBayesPrint (" \n");
2213	MrBayesPrint (" Tuffley, C., and M. Steel. 1997. Links between maximum likelihood \n");
2214	MrBayesPrint (" and maximum parsimony under a simple model of site substitution. \n");
2215	MrBayesPrint (" Bull. Math. Bio. 59:581-607. \n");
2216	MrBayesPrint (" \n");
2217	MrBayesPrint (" \n");
2218	MrBayesPrint (" MrBayes implements three relaxed clock models: the Compound Poisson Process \n");
2219	MrBayesPrint (" (CPP), the Thorne-Kishino 2002 (TK02), and the Independent Gamma Rates (IGR) \n");
2220	MrBayesPrint (" models. The CPP model was first described by Huelsenbeck et al. (2000). It \n");
2221	MrBayesPrint (" is an autocorrelated discrete model of rate variation over time. Instead of \n");
2222	MrBayesPrint (" the modified gamma distribution originally proposed for the rate multipliers, \n");
2223	MrBayesPrint (" MrBayes uses a lognormal distribution. The extensions necessary to sample over\n");
2224	MrBayesPrint (" tree space under this model are original to MrBayes; the original paper only \n");
2225	MrBayesPrint (" considered fixed trees. \n");
2226	MrBayesPrint (" \n");
2227	MrBayesPrint (" The TK02 model was first described by Thorne and Kishino (2002), and is a \n");
2228	MrBayesPrint (" variant of a model presented by them earlier (Thorne et al., 1998). It is an \n");
2229	MrBayesPrint (" autocorrelated continuous model, in which rates vary according to a lognormal \n");
2230	MrBayesPrint (" distribution. Specifically, the rate of a descendant node is assumed to be \n");
2231	MrBayesPrint (" drawn from a lognormal distribution with the mean being the rate of the an- \n");
2232	MrBayesPrint (" cestral node, and the variance being proportional to the length of the branch \n");
2233	MrBayesPrint (" separating the nodes (measured in terms of expected substitutions per site at \n");
2234	MrBayesPrint (" the base rate of the clock). \n");
2235	MrBayesPrint (" \n");
2236	MrBayesPrint (" The final relaxed clock model is the IGR model, in which branch rates are \n");
2237	MrBayesPrint (" modeled as being drawn independently from a scaled gamma distribution. The \n");
2238	MrBayesPrint (" model was originally described in the literature as the 'White Noise' model \n");
2239	MrBayesPrint (" by Lepage et al. (2007), but the original MrBayes implementation predates that\n");
2240	MrBayesPrint (" paper. The IGR model is closely related to the uncorrelated gamma model pre- \n");
2241	MrBayesPrint (" sented originally by Drummond et al. (2006), but it is more elegant in that \n");
2242	MrBayesPrint (" it truly lacks time structure. See Lepage et al. (2007) for details. \n");
2243	MrBayesPrint (" \n");
2244	MrBayesPrint (" Huelsenbeck, J. P., B. Larget, and D. Swofford. 2000. A compound Poisson \n");
2245	MrBayesPrint (" process for relaxing the molecular clock. Genetics 154: 1879-1892. \n");
2246	MrBayesPrint (" \n");
2247	MrBayesPrint (" Thorne, J. L., H. Kishino, and I. S. Painter. 1998. Estimating the rate \n");
2248	MrBayesPrint (" of evolution of the rate of molecular evolution. Mol. Biol. Evol. \n");
2249	MrBayesPrint (" 15: 1647-1657. \n");
2250	MrBayesPrint (" \n");
2251	MrBayesPrint (" Thorne, J. L., and H. Kishino. 2002. Divergence time and evolutionary \n");
2252	MrBayesPrint (" rate estimation with multilocus data. Syst. Biol. 51: 689-702. \n");
2253	MrBayesPrint (" \n");
2254	MrBayesPrint (" Drummond, A. J., S. Y. W. Ho, M. J. Phillips, and A. Rambaut. 2006. \n");
2255	MrBayesPrint (" Relaxed phylogenetics and dating with confidence. PLoS Biology \n");
2256	MrBayesPrint (" 4: 699-710. \n");
2257	MrBayesPrint (" \n");
2258	MrBayesPrint (" Lepage, T., D. Bryant, H. Philippe, and N. Lartillot. 2007. A general \n");
2259	MrBayesPrint (" comparison of relaxed molecular clock models. Mol. Biol. Evol. \n");
2260	MrBayesPrint (" 24: 2669-2680. \n");
2261	MrBayesPrint (" \n");
2262	MrBayesPrint (" \n");
2263	MrBayesPrint (" The standard tree proposals used by MrBayes are described by Lakner et al. \n");
2264	MrBayesPrint (" (2008). The parsimony-biased tree proposals are still undescribed, although \n");
2265	MrBayesPrint (" a rough outline of the idea is presented in the same paper. \n");
2266	MrBayesPrint (" \n");
2267	MrBayesPrint (" Lakner, C., P. van der Mark, J. P. Huelsenbeck, B. Larget, and F. Ronquist.\n");
2268	MrBayesPrint (" 2008. Efficiency of Markov chain Monte Carlo tree proposals in Bayesian \n");
2269	MrBayesPrint (" phylogenetics. Syst. Biol. 57: 86-103. \n");
2270	MrBayesPrint (" \n");
2271	MrBayesPrint (" \n");
2272	MrBayesPrint (" The topology convergence diagnostic used by MrBayes, the average standard \n");
2273	MrBayesPrint (" deviation of split frequencies, is described by Lakner et al. (2008). The \n");
2274	MrBayesPrint (" potential scale reduction factor, the diagnostic used by MrBayes for contin- \n");
2275	MrBayesPrint (" uous parameters, was first proposed by Gelman and Rubin (1992). The auto- \n");
2276	MrBayesPrint (" tuning mechanism used in MrBayes is based on a paper by Roberts and Rosenthal \n");
2277	MrBayesPrint (" (2009). \n");
2278	MrBayesPrint (" \n");
2279	MrBayesPrint (" Gelman, A., and D. B. Rubin. 1992. Inference from iterative simulation \n");
2280	MrBayesPrint (" using multiple sequences. Statistical Science 7: 457-472. \n");
2281	MrBayesPrint (" Bull. Math. Bio. 59:581-607. \n");
2282	MrBayesPrint (" \n");
2283	MrBayesPrint (" Lakner, C., P. van der Mark, J. P. Huelsenbeck, B. Larget, and F. Ronquist.\n");
2284	MrBayesPrint (" 2008. Efficiency of Markov chain Monte Carlo tree proposals in Bayesian \n");
2285	MrBayesPrint (" phylogenetics. Syst. Biol. 57: 86-103. \n");
2286	MrBayesPrint (" \n");
2287	MrBayesPrint (" Roberts, G. O., and J. S. Rosenthal. 2009. Examples of adaptive MCMC. Jour-\n");
2288	MrBayesPrint (" nal of Compuational and Graphical Statistics 18: 349-367. \n");
2289	MrBayesPrint (" \n");
2290	MrBayesPrint (" \n");
2291	MrBayesPrint (" The harmonic mean estimator of model likelihoods, used for Bayes factor tes- \n");
2292	MrBayesPrint (" ting, was discussed by Newton and Raftery (1996). The more accurate stepping- \n");
2293	MrBayesPrint (" stone algorithm was first proposed by Xie et al. (2011). The paper by \n");
2294	MrBayesPrint (" Lartillot and Philippe (2006) presents an interesting discussion of the \n");
2295	MrBayesPrint (" shortcomings of the harmonic mean estimator and describes thermodynamic \n");
2296	MrBayesPrint (" integration, a technique that is similar to the stepping-stone algorithm. \n");
2297	MrBayesPrint (" \n");
2298	MrBayesPrint (" Newton, M. A., and A. E. Raftery. 1994. Approcimate Bayesian inference \n");
2299	MrBayesPrint (" with the weighted likelihood bootstrap. J. R. Stat. Soc. B. 56. 3-48. \n");
2300	MrBayesPrint (" \n");
2301	MrBayesPrint (" Lartillot, N., and H. Philippe. 2006. Computing Bayes factors using \n");
2302	MrBayesPrint (" thermodynamic integration. Syst. Biol. 55: 195-207. \n");
2303	MrBayesPrint (" \n");
2304	MrBayesPrint (" Xie, W., P. O. Lewis, Y. Fan, L. Kuo, and M.-H. Chen. 2011. Improving \n");
2305	MrBayesPrint (" marginal likelihood estimation for Bayesian phylogenetic model \n");
2306	MrBayesPrint (" selection. Syst. Biol. 60: 150-160. \n");
2307	MrBayesPrint (" \n");
2308	MrBayesPrint (" \n");
2309	MrBayesPrint (" \n");
2310	MrBayesPrint (" --------------------------------------------------------------------------- \n");
2311
2312	return (NO_ERROR);
2313
2314	}
2315
2316
2317
2318
2319
2320	int DoConstraint (void)
2321
2322	{
2323
2324	int i, howMany;
2325	int *tset;
2326
2327	if( consrtainType == PARTIAL )
2328	tset=tempSetNeg;
2329	else
2330	tset=tempSet;
2331
2332	/* add set to tempSet */
2333	if (fromI >= 0 && toJ < 0)
2334	{
2335	if (AddToGivenSet (fromI, toJ, everyK, 1, tset) == ERROR)
2336	return (ERROR);
2337	}
2338	else if (fromI >= 0 && toJ >= 0 && everyK < 0)
2339	{
2340	if (AddToGivenSet (fromI, toJ, everyK, 1, tset) == ERROR)
2341	return (ERROR);
2342	}
2343	else if (fromI >= 0 && toJ >= 0 && everyK >= 0)
2344	{
2345	if (AddToGivenSet (fromI, toJ, everyK, 1, tset) == ERROR)
2346	return (ERROR);
2347	}
2348
2349	/* check that this is not a stupid constraint */
2350	howMany = 0;
2351	for (i=0; i<numTaxa; i++)
2352	if (tempSet[i] != 0)
2353	howMany++;
2354
2355	if (howMany == 0)
2356	{
2357	MrBayesPrint ("%s This constraint does not include any taxa and will not be defined\n", spacer);
2358	return (ERROR);
2359	}
2360
2361	if( consrtainType == HARD )
2362	{
2363	if (howMany == numTaxa)
2364	{
2365	/* We allow this so we can report states from and calibrate root */
2366	}
2367
2368	} /end consrtainType == HARD /
2369	else if( consrtainType == PARTIAL )
2370	{
2371	if (howMany == 1)
2372	{
2373	MrBayesPrint ("%s This partial constraint include only one taxa. It is alwayes satisfied and will not be defined.\n", spacer);
2374	return (ERROR);
2375	}
2376
2377	howMany = 0;
2378	for (i=0; i<numTaxa; i++)
2379	{
2380	if (tempSetNeg[i] != 0)
2381	{
2382	howMany++;
2383	if (tempSetNeg[i] == tempSet[i])
2384	{
2385	MrBayesPrint ("%s Two sets of taxa in partial constraint are not allowed to intersect. Constraint will not be defined\n", spacer);
2386	return (ERROR);
2387	}
2388	}
2389	}
2390	if (howMany == 0)
2391	{
2392	MrBayesPrint ("%s This partial constraint does not include any taxa in the second set and will not be defined\n", spacer);
2393	return (ERROR);
2394	}
2395	}
2396	else if( consrtainType == NEGATIVE)
2397	{
2398	if (howMany == 1)
2399	{
2400	MrBayesPrint ("%s Negative constraint should include more than one taxa. Constraint will not be defined\n", spacer);
2401	return (ERROR);
2402	}
2403	}
2404
2405	/* add name to constraintNames */
2406	if (AddString (&constraintNames, numDefinedConstraints, tempSetName) == ERROR)
2407	{
2408	MrBayesPrint ("%s Problem adding constraint %s to list\n", spacer, tempSetName);
2409	return (ERROR);
2410	}
2411
2412	/* store tempSet */
2413	AddBitfield (&definedConstraint, numDefinedConstraints, tempSet, numTaxa);
2414	if( consrtainType == PARTIAL)
2415	{
2416	AddBitfield (&definedConstraintTwo, numDefinedConstraints, tempSetNeg, numTaxa);
2417	}
2418	else
2419	{
2420	definedConstraintTwo = (SafeLong *) SafeRealloc ((void )(definedConstraintTwo), (size_t)((numDefinedConstraints+1)sizeof(SafeLong )));
2421	if ( definedConstraintTwo==NULL )
2422	return ERROR;
2423	definedConstraintTwo[numDefinedConstraints]=NULL;
2424	}
2425
2426	/* add a default node calibration */
2427	nodeCalibration = (Calibration ) SafeRealloc ((void )nodeCalibration, (size_t)((numDefinedConstraints+1)*sizeof(Calibration)));
2428	nodeCalibration[numDefinedConstraints].prior = defaultCalibration.prior;
2429	nodeCalibration[numDefinedConstraints].offset = defaultCalibration.offset;
2430	nodeCalibration[numDefinedConstraints].lambda = defaultCalibration.lambda;
2431	nodeCalibration[numDefinedConstraints].min = defaultCalibration.min;
2432	nodeCalibration[numDefinedConstraints].max = defaultCalibration.max;
2433	nodeCalibration[numDefinedConstraints].age = defaultCalibration.age;
2434	strcpy(nodeCalibration[numDefinedConstraints].name, defaultCalibration.name);
2435
2436	/* increment number of defined constraints */
2437	numDefinedConstraints++;
2438
2439	/* reallocate and initialize space for activeConstraints */
2440	for (i=0; i<numCurrentDivisions; i++)
2441	{
2442	modelParams[i].activeConstraints = (int ) SafeRealloc((void )(modelParams[i].activeConstraints), (size_t)(numDefinedConstraints*sizeof(int)));
2443	modelParams[i].activeConstraints[numDefinedConstraints-1] = NO;
2444	}
2445
2446	/* reallocate and initialize space for tempActiveConstraints */
2447	tempActiveConstraints = (int ) SafeRealloc((void )(tempActiveConstraints), (size_t)(numDefinedConstraints*sizeof(int)));
2448	tempActiveConstraints[numDefinedConstraints-1] = NO;
2449
2450	definedConstraintsType = (enum ConstraintType ) SafeRealloc((void )(definedConstraintsType), (size_t)(numDefinedConstraints*sizeof(enum ConstraintType)));
2451	if ( definedConstraintsType==NULL )
2452	return ERROR;
2453	definedConstraintsType[numDefinedConstraints-1] = consrtainType;
2454
2455	definedConstraintPruned = (SafeLong *) SafeRealloc ((void )(definedConstraintPruned), (size_t)((numDefinedConstraints)sizeof(SafeLong )));
2456	if ( definedConstraintPruned==NULL )
2457	return ERROR;
2458	definedConstraintPruned[numDefinedConstraints-1]=NULL;
2459
2460
2461	definedConstraintTwoPruned = (SafeLong *) SafeRealloc ((void )(definedConstraintTwoPruned), (size_t)((numDefinedConstraints)sizeof(SafeLong )));
2462	if ( definedConstraintTwoPruned==NULL )
2463	return ERROR;
2464	definedConstraintTwoPruned[numDefinedConstraints-1]=NULL;
2465
2466
2467
2468	/* show taxset (for debugging) */
2469	# if 0
2470	for (i=0; i<numTaxa; i++)
2471	MrBayesPrint ("%4d %4d\n", i+1, taxaInfo[i].constraints[numDefinedConstraints-1]);
2472	# endif
2473
2474	return (NO_ERROR);
2475
2476	}
2477
2478
2479
2480
2481
2482	int DoConstraintParm (char parmName, char tkn)
2483
2484	{
2485
2486	int i, index, tempInt;
2487	MrBFlt tempD;
2488	static int *tempSetCurrent;
2489
2490	if (defMatrix == NO)
2491	{
2492	MrBayesPrint ("%s A matrix must be specified before constraints can be defined\n", spacer);
2493	return (ERROR);
2494	}
2495
2496	if (expecting == Expecting(PARAMETER))
2497	{
2498	if (!strcmp(parmName, "Xxxxxxxxxx"))
2499	{
2500	/* check size of constraint name */
2501	if (strlen(tkn) > 99)
2502	{
2503	MrBayesPrint ("%s Constraint name is too long\n", spacer);
2504	return (ERROR);
2505	}
2506
2507	/* check to see if the name has already been used as a constraint */
2508	if (numDefinedConstraints > 0)
2509	{
2510	if (CheckString (constraintNames, numDefinedConstraints, tkn, &index) == ERROR)
2511	{
2512	/* if the constraint name has not been used, then we should have an ERROR returned */
2513	/* we _want_ to be here */
2514	}
2515	else
2516	{
2517	MrBayesPrint ("%s Constraint name '%s' has been used previously\n", spacer, tkn);
2518	return (ERROR);
2519	}
2520	}
2521
2522	/* copy the name to the temporary constraint names string */
2523	strcpy (tempSetName, tkn);
2524
2525	/* clear tempSet */
2526	for (i=0; i<numTaxa; i++)
2527	tempSet[i] = 0;
2528
2529	consrtainType=HARD; /set default constrain type/
2530	tempSetCurrent=tempSet;
2531	fromI = toJ = everyK = -1;
2532	foundDash = foundSlash = NO;
2533	MrBayesPrint ("%s Defining constraint called '%s'\n", spacer, tkn);
2534	foundExp = NO;
2535	foundFirst = YES;
2536	foundEqual = NO;
2537	isNegative = NO;
2538	foundColon = NO;
2539	expecting = Expecting(ALPHA);
2540	expecting \|= Expecting(NUMBER);
2541	expecting \|= Expecting(DASH);
2542	expecting \|= Expecting(EQUALSIGN);
2543	}
2544	else
2545	return (ERROR);
2546	}
2547
2548	else if (expecting == Expecting(EQUALSIGN))
2549	{
2550	foundEqual = YES;
2551	expecting = Expecting(ALPHA);
2552	expecting \|= Expecting(NUMBER);
2553	}
2554	else if (expecting == Expecting(LEFTPAR))
2555	{
2556	isNegative = NO;
2557	expecting = Expecting(NUMBER);
2558	expecting \|= Expecting(DASH);
2559	}
2560	else if (expecting == Expecting(RIGHTPAR))
2561	{
2562	isNegative = NO;
2563	foundExp = NO;
2564	expecting = Expecting(EQUALSIGN);
2565	}
2566	else if (expecting == Expecting(DASH))
2567	{
2568	if (foundExp == YES)
2569	isNegative = YES;
2570	else
2571	foundDash = YES;
2572	expecting = Expecting(NUMBER);
2573	}
2574	else if (expecting == Expecting(ALPHA))
2575	{
2576	if (foundFirst == YES && foundEqual == NO)
2577	{
2578	/* We are filling in the probability for the constraint. Specifically, we expect exp(number). */
2579	if(IsSame ("Partial", tkn) == SAME)
2580	{
2581	for (i=0; i<numTaxa; i++)
2582	tempSetNeg[i] = 0;
2583
2584	consrtainType=PARTIAL;
2585	expecting = Expecting(EQUALSIGN);
2586	expecting \|= Expecting(ALPHA);
2587	}
2588	else if(IsSame ("Hard", tkn) == SAME)
2589	{
2590	consrtainType=HARD;
2591	expecting = Expecting(EQUALSIGN);
2592	expecting \|= Expecting(ALPHA);
2593	}
2594	else if(IsSame ("Negative", tkn) == SAME)
2595	{
2596	consrtainType=NEGATIVE;
2597	expecting = Expecting(EQUALSIGN);
2598	expecting \|= Expecting(ALPHA);
2599	}
2600	else if (IsSame ("Exp", tkn) == SAME \|\| IsSame ("Exp", tkn) == CONSISTENT_WITH)
2601	{
2602	foundExp = YES;
2603	foundDash = NO;
2604	isNegative = NO;
2605	expecting = Expecting(LEFTPAR);
2606	}
2607	else
2608	{
2609	MrBayesPrint ("%s Do not understand %s\n", spacer, tkn);
2610	return (ERROR);
2611	}
2612	}
2613	else
2614	{
2615	/* We are defining a constraint in terms of a taxon set (called tkn, here) or we are referring to
2616	the taxon name. We should be able to find tkn in the list of taxon set names or in the list
2617	of taxon names. If we cannot, then we have a problem and return an error. */
2618	if (CheckString (taxaNames, numTaxa, tkn, &index) == ERROR)
2619	{
2620	if (numTaxaSets < 1)
2621	{
2622	MrBayesPrint ("%s Could not find a taxset called %s\n", spacer, tkn);
2623	return (ERROR);
2624	}
2625	if (CheckString (taxaSetNames, numTaxaSets, tkn, &index) == ERROR)
2626	{
2627	MrBayesPrint ("%s Could not find a taxset called %s\n", spacer, tkn);
2628	return (ERROR);
2629	}
2630	/* add taxa from taxset tkn to new tempSet */
2631	for (i=0; i<numTaxa; i++)
2632	{
2633	if (IsBitSet(i, taxaSet[index]) == YES)
2634	{
2635	tempSetCurrent[i] = 1;
2636	}
2637	}
2638	}
2639	else
2640	{
2641	tempSetCurrent[index] = 1;
2642	}
2643	fromI = toJ = everyK = -1;
2644
2645	expecting = Expecting(ALPHA);
2646	expecting \|= Expecting(NUMBER);
2647	if( consrtainType != PARTIAL \|\| foundColon == YES )
2648	expecting \|= Expecting(SEMICOLON);
2649	else
2650	expecting \|= Expecting(COLON);
2651	}
2652	}
2653	else if (expecting == Expecting(NUMBER))
2654	{
2655	if (foundFirst == YES && foundEqual == NO)
2656	{
2657	/* We are filling in the probability for the constraint. Specifically, we expect number. */
2658	sscanf (tkn, "%lf", &tempD);
2659	if (foundExp == NO && tempD < 0.0)
2660	{
2661	MrBayesPrint ("%s The probability of a clade cannot be less than zero\n", spacer, tkn);
2662	return (ERROR);
2663	}
2664	if (isNegative == YES \|\| foundDash == YES)
2665	tempD *= -1.0;
2666	if (foundExp == YES)
2667	{
2668	expecting = Expecting(RIGHTPAR);
2669	}
2670	else
2671	{
2672	expecting = Expecting(EQUALSIGN);
2673	}
2674	foundFirst = NO;
2675	foundDash = NO;
2676	}
2677	else
2678	{
2679	if (strlen(tkn) == 1 && !strcmp(tkn, "."))
2680	{
2681	tempInt = numTaxa;
2682	}
2683	else
2684	{
2685	sscanf (tkn, "%d", &tempInt);
2686	if (tempInt <= 0 \|\| tempInt > numTaxa)
2687	{
2688	MrBayesPrint ("%s Taxon number %d is out of range (should be between %d and %d)\n", spacer, tempInt, 1, numTaxa);
2689	return (ERROR);
2690	}
2691	}
2692	tempInt--;
2693	if (foundDash == YES)
2694	{
2695	if (fromI >= 0)
2696	toJ = tempInt;
2697	else
2698	{
2699	MrBayesPrint ("%s Improperly formatted constraint\n", spacer);
2700	return (ERROR);
2701	}
2702	foundDash = NO;
2703	}
2704	else if (foundSlash == YES)
2705	{
2706	tempInt++;
2707	if (tempInt <= 1)
2708	{
2709	MrBayesPrint ("%s Improperly formatted constraint\n", spacer);
2710	return (ERROR);
2711	}
2712	if (fromI >= 0 && toJ >= 0 && fromI < toJ)
2713	everyK = tempInt;
2714	else
2715	{
2716	MrBayesPrint ("%s Improperly formatted constraint\n", spacer);
2717	return (ERROR);
2718	}
2719	foundSlash = NO;
2720	}
2721	else
2722	{
2723	if (fromI >= 0 && toJ < 0)
2724	{
2725	if (AddToGivenSet (fromI, toJ, everyK, 1, tempSetCurrent) == ERROR)
2726	return (ERROR);
2727	fromI = tempInt;
2728	}
2729	else if (fromI < 0 && toJ < 0)
2730	{
2731	fromI = tempInt;
2732	}
2733	else if (fromI >= 0 && toJ >= 0 && everyK < 0)
2734	{
2735	if (AddToGivenSet (fromI, toJ, everyK, 1, tempSetCurrent) == ERROR)
2736	return (ERROR);
2737	fromI = tempInt;
2738	toJ = everyK = -1;
2739	}
2740	else if (fromI >= 0 && toJ >= 0 && everyK >= 0)
2741	{
2742	if (AddToGivenSet (fromI, toJ, everyK, 1, tempSetCurrent) == ERROR)
2743	return (ERROR);
2744	fromI = tempInt;
2745	toJ = everyK = -1;
2746	}
2747	else
2748	{
2749	MrBayesPrint ("%s Improperly formatted constraint\n", spacer);
2750	{
2751	return (ERROR);
2752	}
2753	}
2754	}
2755
2756	expecting = Expecting(ALPHA);
2757	expecting \|= Expecting(NUMBER);
2758	expecting \|= Expecting(DASH);
2759	expecting \|= Expecting(BACKSLASH);
2760	if( consrtainType != PARTIAL \|\| foundColon == YES )
2761	expecting \|= Expecting(SEMICOLON);
2762	else
2763	expecting \|= Expecting(COLON);
2764	}
2765	}
2766	else if (expecting == Expecting(BACKSLASH))
2767	{
2768	foundSlash = YES;
2769	expecting = Expecting(NUMBER);
2770	}
2771	else if (expecting == Expecting(COLON))
2772	{
2773	if( foundColon == YES )
2774	{
2775	MrBayesPrint ("%s Improperly formatted constraint: two colon charactors in constraint command.\n", spacer);
2776	return (ERROR);
2777	}
2778
2779	/* add set to tempSet */
2780	if (fromI >= 0 && toJ < 0)
2781	{
2782	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
2783	return (ERROR);
2784	}
2785	else if (fromI >= 0 && toJ >= 0 && everyK < 0)
2786	{
2787	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
2788	return (ERROR);
2789	}
2790	else if (fromI >= 0 && toJ >= 0 && everyK >= 0)
2791	{
2792	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
2793	return (ERROR);
2794	}
2795	fromI = toJ = everyK = -1;
2796	foundDash = foundSlash = NO;
2797
2798	foundColon = YES;
2799	tempSetCurrent = tempSetNeg;
2800	expecting = Expecting(ALPHA);
2801	expecting \|= Expecting(NUMBER);
2802	}
2803	else
2804	return (ERROR);
2805
2806	return (NO_ERROR);
2807
2808	}
2809
2810
2811
2812
2813
2814	int DoCtype (void)
2815
2816	{
2817
2818	int i, foundIllegal, marks[5], numAppliedTo;
2819
2820	/* add set to tempSet */
2821	if (fromI >= 0 && toJ < 0)
2822	{
2823	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
2824	return (ERROR);
2825	}
2826	else if (fromI >= 0 && toJ >= 0 && everyK < 0)
2827	{
2828	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
2829	return (ERROR);
2830	}
2831	else if (fromI >= 0 && toJ >= 0 && everyK >= 0)
2832	{
2833	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
2834	return (ERROR);
2835	}
2836
2837	/* merge tempSet with ctype */
2838	numAppliedTo = 0;
2839	for (i=0; i<5; i++)
2840	marks[i] = NO;
2841	for (i=0; i<numChar; i++)
2842	{
2843	if (tempSet[i] != 0)
2844	{
2845	foundIllegal = NO;
2846	if (charOrdering != UNORD)
2847	{
2848	if (charInfo[i].charType == DNA)
2849	{
2850	foundIllegal = YES;
2851	if (marks[0] == NO)
2852	MrBayesPrint ("%s Ctype not applied to DNA states which must be unordered\n", spacer);
2853	marks[0] = YES;
2854	}
2855	else if (charInfo[i].charType == RNA)
2856	{
2857	foundIllegal = YES;
2858	if (marks[1] == NO)
2859	MrBayesPrint ("%s Ctype not applied to RNA states which must be unordered\n", spacer);
2860	marks[1] = YES;
2861	}
2862	else if (charInfo[i].charType == PROTEIN)
2863	{
2864	foundIllegal = YES;
2865	if (marks[2] == NO)
2866	MrBayesPrint ("%s Ctype not applied to amino acid states which must be unordered\n", spacer);
2867	marks[2] = YES;
2868	}
2869	else if (charInfo[i].charType == RESTRICTION)
2870	{
2871	foundIllegal = YES;
2872	if (marks[3] == NO)
2873	MrBayesPrint ("%s Ctype not applied to restriction site states which must be unordered\n", spacer);
2874	marks[3] = YES;
2875	}
2876	else if (charInfo[i].charType == CONTINUOUS)
2877	{
2878	foundIllegal = YES;
2879	if (marks[4] == NO)
2880	MrBayesPrint ("%s Ctype not applied to continuous characters\n", spacer);
2881	marks[4] = YES;
2882	}
2883	}
2884	if (foundIllegal == NO)
2885	{
2886	charInfo[i].ctype = charOrdering;
2887	numAppliedTo++;
2888	}
2889	}
2890	}
2891	if (numAppliedTo > 0)
2892	{
2893	MrBayesPrint ("%s Ctype was applied to %d standard characters\n", spacer, numAppliedTo);
2894	}
2895	else
2896	{
2897	MrBayesPrint ("%s No standard characters found to apply ctype to\n", spacer);
2898	}
2899
2900	# if 0
2901	for (i=0; i<numChar; i++)
2902	MrBayesPrint ("%4d -- %d\n", i, ctype[i]);
2903	# endif
2904
2905	return (NO_ERROR);
2906
2907	}
2908
2909
2910
2911
2912
2913	int DoCtypeParm (char parmName, char tkn)
2914
2915	{
2916
2917	int i, index, tempInt;
2918
2919	if (defMatrix == NO)
2920	{
2921	MrBayesPrint ("%s A matrix must be specified before typesets can be defined\n", spacer);
2922	return (ERROR);
2923	}
2924
2925	if (expecting == Expecting(PARAMETER))
2926	{
2927	if (!strcmp(parmName, "Xxxxxxxxxx"))
2928	{
2929	if (IsSame ("Ordered", tkn) == SAME \|\| IsSame ("Ordered", tkn) == CONSISTENT_WITH)
2930	charOrdering = ORD;
2931	else if (IsSame ("Unordered", tkn) == SAME \|\| IsSame ("Unordered", tkn) == CONSISTENT_WITH)
2932	charOrdering = UNORD;
2933	else if (IsSame ("Dollo", tkn) == SAME \|\| IsSame ("Dollo", tkn) == CONSISTENT_WITH)
2934	charOrdering = DOLLO;
2935	else if (IsSame ("Irreversible", tkn) == SAME \|\| IsSame ("Irreversible", tkn) == CONSISTENT_WITH)
2936	charOrdering = IRREV;
2937	else
2938	{
2939	MrBayesPrint ("%s Do not understand delimiter \"%s\"\n", spacer, tkn);
2940	return (ERROR);
2941	}
2942
2943	/* clear tempSet */
2944	for (i=0; i<numChar; i++)
2945	tempSet[i] = 0;
2946
2947	fromI = toJ = everyK = -1;
2948	foundDash = foundSlash = NO;
2949	MrBayesPrint ("%s Setting characters to %s\n", spacer, tkn);
2950	expecting = Expecting(COLON);
2951	}
2952	else
2953	return (ERROR);
2954	}
2955	else if (expecting == Expecting(COLON))
2956	{
2957	expecting = Expecting(ALPHA) \| Expecting(NUMBER);
2958	}
2959	else if (expecting == Expecting(ALPHA))
2960	{
2961	/* first, check that we are not trying to put in another character ordering */
2962	if (IsSame ("Ordered", tkn) == SAME \|\| IsSame ("Ordered", tkn) == CONSISTENT_WITH)
2963	{
2964	MrBayesPrint ("%s You cannot specify more than one ordering with a single use of ctype\n", spacer, tkn);
2965	return (ERROR);
2966	}
2967	else if (IsSame ("Unordered", tkn) == SAME \|\| IsSame ("Unordered", tkn) == CONSISTENT_WITH)
2968	{
2969	MrBayesPrint ("%s You cannot specify more than one ordering with a single use of ctype\n", spacer, tkn);
2970	return (ERROR);
2971	}
2972	else if (IsSame ("Dollo", tkn) == SAME \|\| IsSame ("Dollo", tkn) == CONSISTENT_WITH)
2973	{
2974	MrBayesPrint ("%s You cannot specify more than one ordering with a single use of ctype\n", spacer, tkn);
2975	return (ERROR);
2976	}
2977	else if (IsSame ("Irreversible", tkn) == SAME \|\| IsSame ("Irreversible", tkn) == CONSISTENT_WITH)
2978	{
2979	MrBayesPrint ("%s You cannot specify more than one ordering with a single use of ctype\n", spacer, tkn);
2980	return (ERROR);
2981	}
2982
2983	/* We are defining a type set in terms of another (called tkn, here). We should be able
2984	to find tkn in the list of character set names. If we cannot, then we have a problem and
2985	return an error. */
2986	if (IsSame ("All", tkn) == SAME)
2987	{
2988	for (i=0; i<numChar; i++)
2989	tempSet[i] = 1;
2990	fromI = toJ = everyK = -1;
2991	expecting = Expecting(SEMICOLON);
2992	}
2993	else
2994	{
2995	if (numCharSets < 1)
2996	{
2997	MrBayesPrint ("%s Could not find a character set called %s\n", spacer, tkn);
2998	return (ERROR);
2999	}
3000	if (CheckString (charSetNames, numCharSets, tkn, &index) == ERROR)
3001	{
3002	MrBayesPrint ("%s Could not find a character set called %s\n", spacer, tkn);
3003	return (ERROR);
3004	}
3005
3006	/* add characters from charset tkn to new tempset */
3007	for (i=0; i<numChar; i++)
3008	{
3009	if (IsBitSet(i, charSet[index]) == YES)
3010	tempSet[i] = 1;
3011	}
3012	fromI = toJ = everyK = -1;
3013	expecting = Expecting(ALPHA);
3014	expecting \|= Expecting(NUMBER);
3015	expecting \|= Expecting(SEMICOLON);
3016	}
3017	}
3018	else if (expecting == Expecting(NUMBER))
3019	{
3020	if (strlen(tkn) == 1 && tkn[0] == '.')
3021	tempInt = numChar;
3022	else
3023	sscanf (tkn, "%d", &tempInt);
3024	if (tempInt <= 0 \|\| tempInt > numChar)
3025	{
3026	MrBayesPrint ("%s Character number %d is out of range (should be between %d and %d)\n", spacer, tempInt, 1, numChar);
3027	return (ERROR);
3028	}
3029	tempInt--;
3030	if (foundDash == YES)
3031	{
3032	if (fromI >= 0)
3033	toJ = tempInt;
3034	else
3035	{
3036	MrBayesPrint ("%s Improperly formatted ctype\n", spacer);
3037	return (ERROR);
3038	}
3039	foundDash = NO;
3040	}
3041	else if (foundSlash == YES)
3042	{
3043	tempInt++;
3044	if (tempInt <= 1)
3045	{
3046	MrBayesPrint ("%s Improperly formatted ctype\n", spacer);
3047	return (ERROR);
3048	}
3049	if (fromI >= 0 && toJ >= 0 && fromI < toJ)
3050	everyK = tempInt;
3051	else
3052	{
3053	MrBayesPrint ("%s Improperly formatted ctype\n", spacer);
3054	return (ERROR);
3055	}
3056	foundSlash = NO;
3057	}
3058	else
3059	{
3060	if (fromI >= 0 && toJ < 0)
3061	{
3062	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
3063	return (ERROR);
3064	fromI = tempInt;
3065	}
3066	else if (fromI < 0 && toJ < 0)
3067	{
3068	fromI = tempInt;
3069	}
3070	else if (fromI >= 0 && toJ >= 0 && everyK < 0)
3071	{
3072	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
3073	return (ERROR);
3074	fromI = tempInt;
3075	toJ = everyK = -1;
3076	}
3077	else if (fromI >= 0 && toJ >= 0 && everyK >= 0)
3078	{
3079	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
3080	return (ERROR);
3081	fromI = tempInt;
3082	toJ = everyK = -1;
3083	}
3084	else
3085	{
3086	MrBayesPrint ("%s Improperly formatted ctype\n", spacer);
3087	{
3088	return (ERROR);
3089	}
3090	}
3091
3092	}
3093
3094
3095	expecting = Expecting(ALPHA);
3096	expecting \|= Expecting(NUMBER);
3097	expecting \|= Expecting(SEMICOLON);
3098	expecting \|= Expecting(DASH);
3099	expecting \|= Expecting(BACKSLASH);
3100	}
3101	else if (expecting == Expecting(DASH))
3102	{
3103	foundDash = YES;
3104	expecting = Expecting(NUMBER);
3105	}
3106	else if (expecting == Expecting(BACKSLASH))
3107	{
3108	foundSlash = YES;
3109	expecting = Expecting(NUMBER);
3110	}
3111	else
3112	return (ERROR);
3113
3114	return (NO_ERROR);
3115
3116	}
3117
3118
3119
3120
3121
3122	int DoDelete (void)
3123
3124	{
3125
3126	int i, alreadyDone;
3127
3128	MrBayesPrint ("%s Excluding taxa\n", spacer);
3129
3130	/* add set to tempSet */
3131	if (fromI >= 0 && toJ < 0)
3132	{
3133	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
3134	return (ERROR);
3135	}
3136	else if (fromI >= 0 && toJ >= 0 && everyK < 0)
3137	{
3138	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
3139	return (ERROR);
3140	}
3141	else if (fromI >= 0 && toJ >= 0 && everyK >= 0)
3142	{
3143	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
3144	return (ERROR);
3145	}
3146
3147	/* merge tempSet with taxaset */
3148	alreadyDone = NO;
3149	for (i=0; i<numTaxa; i++)
3150	{
3151	if (tempSet[i] == 1)
3152	{
3153	if (taxaInfo[i].isDeleted == YES && alreadyDone == NO)
3154	{
3155	MrBayesPrint ("%s Some taxa already excluded\n", spacer);
3156	alreadyDone = YES;
3157	}
3158	taxaInfo[i].isDeleted = YES;
3159	}
3160	}
3161
3162	SetLocalTaxa ();
3163	SetUpAnalysis(&globalSeed);
3164
3165	/* show tempSet (for debugging) */
3166	# if 0
3167	for (i=0; i<numTaxa; i++)
3168	MrBayesPrint ("%4d %4d\n", i+1, tempSet[i]);
3169	# endif
3170
3171	return (NO_ERROR);
3172
3173	}
3174
3175
3176
3177
3178
3179	int DoDeleteParm (char parmName, char tkn)
3180
3181	{
3182
3183	int i, index, tempInt;
3184
3185	if (defMatrix == NO)
3186	{
3187	MrBayesPrint ("%s A matrix must be specified before you can delete taxa\n", spacer);
3188	return (ERROR);
3189	}
3190
3191	if (foundFirst == NO)
3192	{
3193	/* this is the first time in */
3194	fromI = toJ = everyK = -1;
3195	foundDash = NO;
3196	for (i=0; i<numTaxa; i++) /* clear tempSet */
3197	tempSet[i] = 0;
3198	foundFirst = YES;
3199	}
3200
3201	if (expecting == Expecting(ALPHA))
3202	{
3203	if (IsSame ("All", tkn) == SAME \|\| IsSame ("All", tkn) == CONSISTENT_WITH)
3204	{
3205	for (i=0; i<numTaxa; i++)
3206	tempSet[i] = 1;
3207	}
3208	else
3209	{
3210	if (CheckString (taxaNames, numTaxa, tkn, &index) == ERROR)
3211	{
3212	/* we are using a pre-defined taxa set */
3213	if (numTaxaSets < 1)
3214	{
3215	MrBayesPrint ("%s Could not find a taxset called %s\n", spacer, tkn);
3216	return (ERROR);
3217	}
3218	if (CheckString (taxaSetNames, numTaxaSets, tkn, &index) == ERROR)
3219	{
3220	MrBayesPrint ("%s Could not find a taxset called %s\n", spacer, tkn);
3221	return (ERROR);
3222	}
3223	/* add taxa from taxset tkn to new tempSet */
3224	for (i=0; i<numTaxa; i++)
3225	{
3226	if (IsBitSet (i, taxaSet[index]) == YES)
3227	tempSet[i] = 1;
3228	}
3229	}
3230	else
3231	{
3232	/* we found the taxon name */
3233	if (fromI >= 0 && toJ < 0)
3234	{
3235	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
3236	return (ERROR);
3237	}
3238	else if (fromI >= 0 && toJ >= 0)
3239	{
3240	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
3241	return (ERROR);
3242	}
3243
3244	tempSet[index] = 1;
3245	}
3246	}
3247	foundDash = NO;
3248	fromI = toJ = everyK = -1;
3249
3250	expecting = Expecting(ALPHA);
3251	expecting \|= Expecting(NUMBER);
3252	expecting \|= Expecting(SEMICOLON);
3253	}
3254	else if (expecting == Expecting(NUMBER))
3255	{
3256	if (strlen(tkn) == 1 && !strcmp(tkn, "."))
3257	tempInt = numTaxa;
3258	else
3259	{
3260	sscanf (tkn, "%d", &tempInt);
3261	if (tempInt <= 0 \|\| tempInt > numTaxa)
3262	{
3263	MrBayesPrint ("%s Taxon number %d is out of range (should be between %d and %d)\n", spacer, tempInt, 1, numTaxa);
3264	return (ERROR);
3265	}
3266	}
3267	tempInt--;
3268	if (foundDash == YES)
3269	{
3270	if (fromI >= 0)
3271	toJ = tempInt;
3272	else
3273	{
3274	MrBayesPrint ("%s Improperly formatted delete set\n", spacer);
3275	return (ERROR);
3276	}
3277	foundDash = NO;
3278	}
3279	else
3280	{
3281	if (fromI >= 0 && toJ < 0)
3282	{
3283	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
3284	return (ERROR);
3285	fromI = tempInt;
3286	}
3287	else if (fromI < 0 && toJ < 0)
3288	{
3289	fromI = tempInt;
3290	}
3291	else if (fromI >= 0 && toJ >= 0 && everyK < 0)
3292	{
3293	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
3294	return (ERROR);
3295	fromI = tempInt;
3296	toJ = everyK = -1;
3297	}
3298	else if (fromI >= 0 && toJ >= 0 && everyK >= 0)
3299	{
3300	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
3301	return (ERROR);
3302	fromI = tempInt;
3303	toJ = everyK = -1;
3304	}
3305	else
3306	{
3307	MrBayesPrint ("%s Improperly formatted delete set\n", spacer);
3308	{
3309	return (ERROR);
3310	}
3311	}
3312	}
3313	expecting = Expecting(ALPHA);
3314	expecting \|= Expecting(NUMBER);
3315	expecting \|= Expecting(SEMICOLON);
3316	expecting \|= Expecting(DASH);
3317	}
3318	else if (expecting == Expecting(DASH))
3319	{
3320	foundDash = YES;
3321	expecting = Expecting(NUMBER);
3322	}
3323	else
3324	return (ERROR);
3325
3326	return (NO_ERROR);
3327	MrBayesPrint ("%s", parmName); /just because I am tired of seeing the unused parameter error msg /
3328
3329	}
3330
3331
3332
3333
3334
3335	int DoDimensions (void)
3336
3337	{
3338
3339	if (inDataBlock == NO && inTaxaBlock == NO && inCharactersBlock == NO)
3340	{
3341	MrBayesPrint ("%s Dimensions can only be defined in a data, characters or taxa block\n", spacer);
3342	return (ERROR);
3343	}
3344
3345	/* other problems are detected already when reading in DoDimensionsParm */
3346	if (inDataBlock == YES && (defTaxa == NO \|\| defChars == NO))
3347	{
3348	MrBayesPrint ("%s Expecting both Ntax and Nchar to be defined in a data block\n", spacer);
3349	return (ERROR);
3350	}
3351
3352	/* allocate matrix */
3353	if (inTaxaBlock == YES)
3354	{
3355	if (AllocTaxa () == ERROR)
3356	return ERROR;
3357	MrBayesPrint ("%s Defining new set of %d taxa\n", spacer, numTaxa);
3358	}
3359
3360	if (inCharactersBlock == YES)
3361	{
3362	if (AllocMatrix() == ERROR)
3363	return (ERROR);
3364	MrBayesPrint ("%s Defining new character matrix with %d characters\n", spacer, numChar);
3365	}
3366
3367	if (inDataBlock == YES)
3368	{
3369	if (AllocMatrix() == ERROR)
3370	return (ERROR);
3371	MrBayesPrint ("%s Defining new matrix with %d taxa and %d characters\n", spacer, numTaxa, numChar);
3372	}
3373
3374	return (NO_ERROR);
3375
3376	}
3377
3378
3379
3380
3381
3382	int DoDimensionsParm (char parmName, char tkn)
3383
3384	{
3385
3386	if (expecting == Expecting(PARAMETER))
3387	{
3388	expecting = Expecting(EQUALSIGN);
3389	}
3390	else
3391	{
3392	/* set Ntax (numTaxa) *****************************************************************/
3393	if (!strcmp(parmName, "Ntax"))
3394	{
3395	if (inCharactersBlock == YES)
3396	{
3397	MrBayesPrint ("%s You cannot define ntax in a characters block\n");
3398	return (ERROR);
3399	}
3400	if (expecting == Expecting(EQUALSIGN))
3401	expecting = Expecting(NUMBER);
3402	else if (expecting == Expecting(NUMBER))
3403	{
3404	sscanf (tkn, "%d", &numTaxa);
3405	defTaxa = YES;
3406	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
3407	}
3408	else
3409	return (ERROR);
3410	}
3411	/* set Nchar (numChar) ****************************************************************/
3412	else if (!strcmp(parmName, "Nchar"))
3413	{
3414	if (inTaxaBlock == YES)
3415	{
3416	MrBayesPrint ("%s You cannot define nchar in a taxa block\n");
3417	return (ERROR);
3418	}
3419	if (expecting == Expecting(EQUALSIGN))
3420	expecting = Expecting(NUMBER);
3421	else if (expecting == Expecting(NUMBER))
3422	{
3423	sscanf (tkn, "%d", &numChar);
3424	defChars = YES;
3425	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
3426	}
3427	else
3428	return (ERROR);
3429	}
3430	else
3431	return (ERROR);
3432	}
3433
3434	return (NO_ERROR);
3435	}
3436
3437
3438
3439
3440
3441	int DoDisclaimer (void)
3442
3443	{
3444
3445	MrBayesPrint (" --------------------------------------------------------------------------- \n");
3446	MrBayesPrint (" Disclaimer \n");
3447	MrBayesPrint (" \n");
3448	MrBayesPrint (" Copyright 2003 by John P. Huelsenbeck and Fredrik Ronquist \n");
3449	MrBayesPrint (" \n");
3450	MrBayesPrint (" This software package is provided \"as is\" and without a warranty of any \n");
3451	MrBayesPrint (" kind. In no event shall the authors be held responsible for any damage \n");
3452	MrBayesPrint (" resulting from the use of this software. The program--including source code, \n");
3453	MrBayesPrint (" example data sets, and executables--is distributed free of charge for \n");
3454	MrBayesPrint (" academic use only. \n");
3455	MrBayesPrint (" --------------------------------------------------------------------------- \n");
3456
3457	return (NO_ERROR);
3458
3459	}
3460
3461
3462
3463
3464
3465	int DoEndBlock (void)
3466
3467	{
3468
3469	if (inMrbayesBlock == YES)
3470	{
3471	MrBayesPrint (" Exiting mrbayes block\n");
3472	inMrbayesBlock = NO;
3473	}
3474	else if (inDataBlock == YES)
3475	{
3476	MrBayesPrint (" Exiting data block\n");
3477	inDataBlock = NO;
3478	}
3479	else if (inCharactersBlock == YES)
3480	{
3481	MrBayesPrint (" Exiting characters block\n");
3482	inCharactersBlock = NO;
3483	}
3484	else if (inTaxaBlock == YES)
3485	{
3486	MrBayesPrint (" Exiting taxa block\n");
3487	if (numNamedTaxa < numTaxa)
3488	{
3489	MrBayesPrint ("%s Leaving taxa block without taxon labels being defined\n", spacer);
3490	FreeTaxa();
3491	}
3492	inTaxaBlock = NO;
3493	}
3494	else if (inTreesBlock == YES)
3495	{
3496	MrBayesPrint (" Exiting trees block\n");
3497	inTreesBlock = NO;
3498	ResetTranslateTable();
3499	}
3500	else if (inForeignBlock == YES)
3501	{
3502	MrBayesPrint (" Exiting foreign block\n");
3503	inForeignBlock = NO;
3504	}
3505	else
3506	{
3507	MrBayesPrint (" Unknown \"end\" statement\n");
3508	return (ERROR);
3509	}
3510
3511	strcpy(spacer,""); /* reset indentation */
3512	return (NO_ERROR);
3513
3514	}
3515
3516
3517
3518
3519
3520	int DoExecute (void)
3521
3522	{
3523
3524	int c, i, rc, cmdLine, lineTerm, longestLineLength, nErrors;
3525	char *s, exeFileName[100];
3526	FILE *fp;
3527	CmdType *oldCommandPtr;
3528	# if defined (MPI_ENABLED)
3529	int sumErrors;
3530	# endif
3531
3532	nErrors = 0;
3533	cmdLine = 0;
3534	numOpenExeFiles++;
3535	s = NULL;
3536	strncpy(exeFileName, inputFileName, 98);
3537
3538	if (numOpenExeFiles > 1)
3539	MrBayesPrint ("\n%s Executing file \"%s\"...\n\n", spacer, inputFileName);
3540	else
3541	MrBayesPrint ("%s Executing file \"%s\"\n", spacer, inputFileName);
3542
3543	/* Save old command ptr */
3544	oldCommandPtr = commandPtr;
3545
3546	/* open binary file */
3547	if ((fp = OpenBinaryFileR(inputFileName)) == NULL)
3548	nErrors++;
3549
3550	/* set indentation to 0 */
3551	strcpy (spacer, "");
3552
3553	# if defined (MPI_ENABLED)
3554	MPI_Allreduce (&nErrors, &sumErrors, 1, MPI_INT, MPI_SUM, MPI_COMM_WORLD);
3555	if (sumErrors > 0)
3556	{
3557	MrBayesPrint ("%s There was an error on at least one processor\n", spacer);
3558	goto errorExit;
3559	}
3560	# else
3561	if (nErrors > 0)
3562	goto errorExit;
3563	# endif
3564
3565	/* find out what type of line termination is used */
3566	lineTerm = LineTermType (fp);
3567	if (lineTerm == LINETERM_MAC)
3568	MrBayesPrint ("%s Macintosh line termination\n", spacer);
3569	else if (lineTerm == LINETERM_DOS)
3570	MrBayesPrint ("%s DOS line termination\n", spacer);
3571	else if (lineTerm == LINETERM_UNIX)
3572	MrBayesPrint ("%s UNIX line termination\n", spacer);
3573	else
3574	{
3575	MrBayesPrint ("%s Unknown line termination\n", spacer);
3576	nErrors++;
3577	}
3578	# if defined (MPI_ENABLED)
3579	MPI_Allreduce (&nErrors, &sumErrors, 1, MPI_INT, MPI_SUM, MPI_COMM_WORLD);
3580	if (sumErrors > 0)
3581	{
3582	MrBayesPrint ("%s There was an error on at least one processor\n", spacer);
3583	goto errorExit;
3584	}
3585	# else
3586	if (nErrors > 0)
3587	goto errorExit;
3588	# endif
3589
3590	/* find length of longest line */
3591	longestLineLength = LongestLine (fp);
3592	MrBayesPrint ("%s Longest line length = %d\n", spacer, longestLineLength);
3593	longestLineLength += 50;
3594
3595	/* check that longest line is not longer than CMD_STRING_LENGTH */
3596	if (longestLineLength >= CMD_STRING_LENGTH - 100)
3597	{
3598	/MrBayesPrint ("%s A maximum of %d characters is allowed on a single line\n", spacer, CMD_STRING_LENGTH - 100);/
3599	MrBayesPrint ("%s The longest line of the file %s\n", spacer, inputFileName);
3600	MrBayesPrint ("%s contains at least one line with %d characters.\n", spacer, longestLineLength);
3601	}
3602	/*
3603	# if defined (MPI_ENABLED)
3604	MPI_Allreduce (&nErrors, &sumErrors, 1, MPI_INT, MPI_SUM, MPI_COMM_WORLD);
3605	if (sumErrors > 0)
3606	{
3607	MrBayesPrint ("%s There was an error on at least one processor\n", spacer);
3608	goto errorExit;
3609	}
3610	# else
3611	if (nErrors > 0)
3612	goto errorExit;
3613	# endif
3614	*/
3615
3616	/* allocate a string long enough to hold a line */
3617	s = (char )SafeMalloc((size_t) (longestLineLength sizeof(char)));
3618	if (!s)
3619	{
3620	MrBayesPrint ("%s Problem allocating string for reading file\n", spacer);
3621	nErrors++;
3622	}
3623	# if defined (MPI_ENABLED)
3624	MPI_Allreduce (&nErrors, &sumErrors, 1, MPI_INT, MPI_SUM, MPI_COMM_WORLD);
3625	if (sumErrors > 0)
3626	{
3627	MrBayesPrint ("%s There was an error on at least one processor\n", spacer);
3628	goto errorExit;
3629	}
3630	# else
3631	if (nErrors > 0)
3632	goto errorExit;
3633	# endif
3634
3635	/* close binary file */
3636	SafeFclose (&fp);
3637
3638	/* open text file */
3639	if ((fp = OpenTextFileR(inputFileName)) == NULL)
3640	{
3641	nErrors++;
3642	}
3643	# if defined (MPI_ENABLED)
3644	MPI_Allreduce (&nErrors, &sumErrors, 1, MPI_INT, MPI_SUM, MPI_COMM_WORLD);
3645	if (sumErrors > 0)
3646	{
3647	MrBayesPrint ("%s There was an error on at least one processor\n", spacer);
3648	goto errorExit;
3649	}
3650	# else
3651	if (nErrors > 0)
3652	goto errorExit;
3653	# endif
3654
3655	/* parse file, reading each line in turn */
3656	MrBayesPrint ("%s Parsing file\n", spacer);
3657
3658	inMrbayesBlock = inDataBlock = inForeignBlock = inTreesBlock = NO;
3659	foundNewLine = NO;
3660	expecting = Expecting(COMMAND);
3661	cmdLine = 0;
3662
3663	do {
3664	/* read in a new line into s */
3665	i = 0;
3666	do {
3667	c = fgetc(fp);
3668	if (c == '\r' \|\| c == '\n' \|\| c == EOF)
3669	s[i++] = '\n';
3670	else
3671	s[i++] = c;
3672	} while (s[i-1] != '\n');
3673	s[i] = '\0';
3674	foundNewLine = YES;
3675	cmdLine++;
3676
3677	/* process string if not empty */
3678	if (strlen(s) > 1)
3679	{
3680	/* check that all characters in the string are valid */
3681	if (CheckStringValidity (s) == ERROR)
3682	{
3683	nErrors++;
3684	}
3685	# if defined (MPI_ENABLED)
3686	MPI_Allreduce (&nErrors, &sumErrors, 1, MPI_INT, MPI_SUM, MPI_COMM_WORLD);
3687	if (sumErrors > 0)
3688	{
3689	MrBayesPrint ("%s There was an error on at least one processor\n", spacer);
3690	goto errorExit;
3691	}
3692	# else
3693	if (nErrors > 0)
3694	goto errorExit;
3695	# endif
3696
3697	/* interpret commands on line */
3698	rc = ParseCommand (s);
3699	if (rc == ERROR)
3700	nErrors++;
3701	# if defined (MPI_ENABLED)
3702	MPI_Allreduce (&nErrors, &sumErrors, 1, MPI_INT, MPI_SUM, MPI_COMM_WORLD);
3703	if (sumErrors > 0)
3704	{
3705	MrBayesPrint ("%s There was an error on at least one processor\n", spacer);
3706	goto errorExit;
3707	}
3708	# else
3709	if (nErrors > 0)
3710	goto errorExit;
3711	# endif
3712	if (rc == NO_ERROR_QUIT)
3713	nErrors++;
3714	# if defined (MPI_ENABLED)
3715	MPI_Allreduce (&nErrors, &sumErrors, 1, MPI_INT, MPI_SUM, MPI_COMM_WORLD);
3716	if (sumErrors > 0)
3717	goto quitExit;
3718	# else
3719	if (nErrors > 0)
3720	goto quitExit;
3721	# endif
3722	}
3723	} while (c != EOF);
3724
3725	MrBayesPrint ("%s Reached end of file\n", spacer);
3726
3727	if (inComment == YES)
3728	nErrors++;
3729
3730	# if defined (MPI_ENABLED)
3731	MPI_Allreduce (&nErrors, &sumErrors, 1, MPI_INT, MPI_SUM, MPI_COMM_WORLD);
3732	if (sumErrors > 0)
3733	{
3734	MrBayesPrint ("%s There was an error on at least one processor\n", spacer);
3735	goto errorExit;
3736	}
3737	# else
3738	if (nErrors > 0)
3739	goto errorExit;
3740	# endif
3741
3742	if (s)
3743	free (s);
3744	SafeFclose (&fp);
3745	numOpenExeFiles--;
3746
3747	if (numOpenExeFiles > 0)
3748	{
3749	inMrbayesBlock = YES;
3750	MrBayesPrint ("\n Returning execution to calling file ...\n\n");
3751	strcpy (spacer, " ");
3752	}
3753	else
3754	strcpy (spacer, "");
3755
3756	commandPtr = oldCommandPtr;
3757
3758	return (NO_ERROR);
3759
3760	quitExit:
3761	if (s)
3762	free (s);
3763	SafeFclose (&fp);
3764	numOpenExeFiles--;
3765	if (numOpenExeFiles > 0)
3766	{
3767	inMrbayesBlock = YES;
3768	strcpy (spacer, " ");
3769	}
3770	else
3771	strcpy (spacer, "");
3772
3773	commandPtr = oldCommandPtr;
3774
3775	return (NO_ERROR_QUIT);
3776
3777	errorExit:
3778	if (inComment == YES)
3779	{
3780	MrBayesPrint ("%s ERROR: Reached end of file while in comment.\n", spacer);
3781	inComment = NO;
3782	numComments = 0;
3783	}
3784	if (fp)
3785	{
3786	MrBayesPrint ("%s The error occurred when reading char. %d on line %d\n", spacer, tokenP-cmdStr-strlen(token)+1, cmdLine);
3787	MrBayesPrint ("%s in the file '%s'\n", spacer, exeFileName);
3788	}
3789	if (s)
3790	free (s);
3791	SafeFclose (&fp);
3792	numOpenExeFiles--; /* we increase the value above even if no file is successfully opened */
3793
3794	/* make sure we exit the block we were reading from correctly */
3795	if (inMrbayesBlock == YES)
3796	inMrbayesBlock = NO;
3797	else if (inDataBlock == YES)
3798	inDataBlock = NO;
3799	else if (inTreesBlock == YES)
3800	{
3801	inTreesBlock = NO;
3802	ResetTranslateTable();
3803	}
3804	else if (inForeignBlock == YES)
3805	inForeignBlock = NO;
3806
3807	/* make sure correct return if we came from mrbayes block in another execute file */
3808	if (numOpenExeFiles > 0)
3809	{
3810	inMrbayesBlock = YES;
3811	MrBayesPrint ("\n Returning execution to calling file ...\n\n");
3812	strcpy (spacer, " ");
3813	commandPtr = oldCommandPtr;
3814	return (ERROR);
3815	}
3816	else
3817	strcpy (spacer, "");
3818
3819	commandPtr = oldCommandPtr;
3820
3821	return (ERROR);
3822
3823	}
3824
3825
3826
3827
3828
3829	int DoExecuteParm (char parmName, char tkn)
3830
3831	{
3832
3833	if(strlen(tkn)>99)
3834	{
3835	MrBayesPrint ("%s Maximum allowed length of file name is 99 characters. The given name:\n", spacer);
3836	MrBayesPrint ("%s '%s'\n", spacer,tkn);
3837	MrBayesPrint ("%s has %d characters.\n", spacer,strlen(tkn));
3838	return (ERROR);
3839	}
3840	strcpy (inputFileName, tkn);
3841
3842	expecting = Expecting (SEMICOLON);
3843
3844	return (NO_ERROR);
3845	MrBayesPrint ("%s", parmName); /* just because I am tired of seeing the unused parameter error msg */
3846
3847	}
3848
3849
3850
3851
3852
3853	int DoExclude (void)
3854
3855	{
3856
3857	int i, alreadyDone;
3858
3859	MrBayesPrint ("%s Excluding character(s)\n", spacer);
3860
3861	/* add set to tempSet */
3862	if (fromI >= 0 && toJ < 0)
3863	{
3864	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
3865	return (ERROR);
3866	}
3867	else if (fromI >= 0 && toJ >= 0 && everyK < 0)
3868	{
3869	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
3870	return (ERROR);
3871	}
3872	else if (fromI >= 0 && toJ >= 0 && everyK >= 0)
3873	{
3874	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
3875	return (ERROR);
3876	}
3877
3878	/* merge tempSet with charset */
3879	alreadyDone = NO;
3880	for (i=0; i<numChar; i++)
3881	{
3882	if (tempSet[i] == 1)
3883	{
3884	if (charInfo[i].isExcluded == YES && alreadyDone == NO)
3885	{
3886	MrBayesPrint ("%s Some characters already excluded\n", spacer);
3887	alreadyDone = YES;
3888	}
3889	charInfo[i].isExcluded = YES;
3890	}
3891	}
3892
3893	foundFirst = NO;
3894
3895	/* reset analysis to recompress data */
3896	SetUpAnalysis(&globalSeed);
3897
3898	return (NO_ERROR);
3899
3900	}
3901
3902
3903
3904
3905
3906	int DoExcludeParm (char parmName, char tkn)
3907
3908	{
3909
3910	int i, index, tempInt;
3911
3912	if (defMatrix == NO)
3913	{
3914	MrBayesPrint ("%s A matrix must be specified before you can exclude characters\n", spacer);
3915	return (ERROR);
3916	}
3917
3918	if (foundFirst == NO)
3919	{
3920	/* this is the first time in */
3921	fromI = toJ = everyK = -1;
3922	foundDash = foundSlash = NO;
3923	for (i=0; i<numChar; i++) /* clear tempSet */
3924	tempSet[i] = 0;
3925	foundFirst = YES;
3926	}
3927
3928	if (expecting == Expecting(ALPHA))
3929	{
3930	if (IsSame ("All", tkn) == SAME \|\| IsSame ("All", tkn) == CONSISTENT_WITH)
3931	{
3932	for (i=0; i<numChar; i++)
3933	tempSet[i] = 1;
3934	}
3935	else if (IsSame ("Missambig", tkn) == SAME \|\| IsSame ("Missambig", tkn) == CONSISTENT_WITH)
3936	{
3937	for (i=0; i<numChar; i++)
3938	{
3939	if (charInfo[i].isMissAmbig == YES)
3940	tempSet[i] = 1;
3941	}
3942	}
3943	else
3944	{
3945	/* we are using a pre-defined character set */
3946	if (numCharSets < 1)
3947	{
3948	MrBayesPrint ("%s Could not find a character set called %s\n", spacer, tkn);
3949	return (ERROR);
3950	}
3951	if (CheckString (charSetNames, numCharSets, tkn, &index) == ERROR)
3952	{
3953	MrBayesPrint ("%s Could not find a character set called %s\n", spacer, tkn);
3954	return (ERROR);
3955	}
3956	/* add characters from charset tkn to new tempSet */
3957	for (i=0; i<numChar; i++)
3958	{
3959	if (IsBitSet(i, charSet[index]) == YES)
3960	tempSet[i] = 1;
3961	}
3962	fromI = toJ = everyK = -1;
3963	}
3964
3965	expecting = Expecting(ALPHA);
3966	expecting \|= Expecting(NUMBER);
3967	expecting \|= Expecting(SEMICOLON);
3968	}
3969	else if (expecting == Expecting(NUMBER))
3970	{
3971	if (strlen(tkn) == 1 && tkn[0] == '.')
3972	tempInt = numChar;
3973	else
3974	sscanf (tkn, "%d", &tempInt);
3975	if (tempInt <= 0 \|\| tempInt > numChar)
3976	{
3977	MrBayesPrint ("%s Character number %d is out of range (should be between %d and %d)\n", spacer, tempInt, 1, numChar);
3978	return (ERROR);
3979	}
3980	tempInt--;
3981	if (foundDash == YES)
3982	{
3983	if (fromI >= 0)
3984	toJ = tempInt;
3985	else
3986	{
3987	MrBayesPrint ("%s Improperly formatted exclude set\n", spacer);
3988	return (ERROR);
3989	}
3990	foundDash = NO;
3991	}
3992	else if (foundSlash == YES)
3993	{
3994	tempInt++;
3995	if (tempInt <= 1)
3996	{
3997	MrBayesPrint ("%s Improperly formatted exclude set\n", spacer);
3998	return (ERROR);
3999	}
4000	if (fromI >= 0 && toJ >= 0 && fromI < toJ)
4001	everyK = tempInt;
4002	else
4003	{
4004	MrBayesPrint ("%s Improperly formatted exclude set\n", spacer);
4005	return (ERROR);
4006	}
4007	foundSlash = NO;
4008	}
4009	else
4010	{
4011	if (fromI >= 0 && toJ < 0)
4012	{
4013	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
4014	return (ERROR);
4015	fromI = tempInt;
4016	}
4017	else if (fromI < 0 && toJ < 0)
4018	{
4019	fromI = tempInt;
4020	}
4021	else if (fromI >= 0 && toJ >= 0 && everyK < 0)
4022	{
4023	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
4024	return (ERROR);
4025	fromI = tempInt;
4026	toJ = everyK = -1;
4027	}
4028	else if (fromI >= 0 && toJ >= 0 && everyK >= 0)
4029	{
4030	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
4031	return (ERROR);
4032	fromI = tempInt;
4033	toJ = everyK = -1;
4034	}
4035	else
4036	{
4037	MrBayesPrint ("%s Improperly formatted exclude set\n", spacer);
4038	{
4039	return (ERROR);
4040	}
4041	}
4042	}
4043	expecting = Expecting(ALPHA);
4044	expecting \|= Expecting(NUMBER);
4045	expecting \|= Expecting(SEMICOLON);
4046	expecting \|= Expecting(DASH);
4047	expecting \|= Expecting(BACKSLASH);
4048	}
4049	else if (expecting == Expecting(DASH))
4050	{
4051	foundDash = YES;
4052	expecting = Expecting(NUMBER);
4053	}
4054	else if (expecting == Expecting(BACKSLASH))
4055	{
4056	foundSlash = YES;
4057	expecting = Expecting(NUMBER);
4058	}
4059	else
4060	return (ERROR);
4061
4062	return (NO_ERROR);
4063	MrBayesPrint ("%s", parmName); /* just because I am tired of seeing the unused parameter error msg */
4064
4065	}
4066
4067
4068
4069
4070
4071	int DoFormat (void)
4072
4073	{
4074
4075	if (inDataBlock == NO && inCharactersBlock == NO)
4076	{
4077	MrBayesPrint ("%s Formats can only be defined in a data or characters block\n", spacer);
4078	return (ERROR);
4079	}
4080
4081	return CheckInitialPartitions();
4082	}
4083
4084
4085
4086
4087
4088	int DoFormatParm (char parmName, char tkn)
4089
4090	{
4091
4092	int i, tempInt;
4093	char tempStr[100];
4094	static int foundQuote;
4095
4096	if (inDataBlock == NO && inCharactersBlock == NO)
4097	{
4098	MrBayesPrint ("%s Formats can only be defined in a data or characters block\n", spacer);
4099	return (ERROR);
4100	}
4101	if (defTaxa == NO \|\| defChars == NO)
4102	{
4103	MrBayesPrint ("%s The dimensions of the matrix must be defined before the format\n", spacer);
4104	return (ERROR);
4105	}
4106
4107	if (expecting == Expecting(PARAMETER))
4108	{
4109	expecting = Expecting(EQUALSIGN);
4110	if (!strcmp(parmName, "Interleave"))
4111	{
4112	expecting = Expecting(EQUALSIGN) \| Expecting(PARAMETER) \| Expecting(SEMICOLON);
4113	isInterleaved = YES;
4114	}
4115	}
4116	else
4117	{
4118	/* set Datatype (dataType) ************************************************************/
4119	if (!strcmp(parmName, "Datatype"))
4120	{
4121	if (expecting == Expecting(EQUALSIGN))
4122	expecting = Expecting(ALPHA);
4123	else if (expecting == Expecting(ALPHA))
4124	{
4125	if (IsArgValid(tkn, tempStr) == NO_ERROR)
4126	{
4127	if (isMixed == NO)
4128	{
4129	if (!strcmp(tempStr, "Dna"))
4130	dataType = DNA;
4131	else if (!strcmp(tempStr, "Rna"))
4132	dataType = RNA;
4133	else if (!strcmp(tempStr, "Protein"))
4134	dataType = PROTEIN;
4135	else if (!strcmp(tempStr, "Restriction"))
4136	dataType = RESTRICTION;
4137	else if (!strcmp(tempStr, "Standard"))
4138	dataType = STANDARD;
4139	else if (!strcmp(tempStr, "Continuous"))
4140	dataType = CONTINUOUS;
4141	else if (!strcmp(tempStr, "Mixed"))
4142	{
4143	dataType = MIXED;
4144	isMixed = YES;
4145	for (i=0; i<numChar; i++)
4146	tempSet[i] = 0;
4147	fromI = toJ = everyK = -1;
4148	foundDash = foundSlash = NO;
4149	numDivisions = 0;
4150	MrBayesPrint ("%s Data is Mixed\n", spacer);
4151	}
4152	if (dataType == MIXED)
4153	expecting = Expecting(LEFTPAR);
4154	else
4155	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
4156	}
4157	else
4158	{
4159	if (!strcmp(tempStr, "Dna"))
4160	dataType = DNA;
4161	else if (!strcmp(tempStr, "Rna"))
4162	dataType = RNA;
4163	else if (!strcmp(tempStr, "Protein"))
4164	dataType = PROTEIN;
4165	else if (!strcmp(tempStr, "Restriction"))
4166	dataType = RESTRICTION;
4167	else if (!strcmp(tempStr, "Standard"))
4168	dataType = STANDARD;
4169	else if (!strcmp(tempStr, "Continuous"))
4170	dataType = CONTINUOUS;
4171	else if (!strcmp(tempStr, "Mixed"))
4172	{
4173	MrBayesPrint ("%s Cannot have mixed datatype within a mixed datatype\n", spacer);
4174	return (ERROR);
4175	}
4176	expecting = Expecting(COLON);
4177	for (i=0; i<numChar; i++)
4178	tempSet[i] = 0;
4179	fromI = toJ = everyK = -1;
4180	foundDash = foundSlash = NO;
4181	}
4182	if (isMixed == NO)
4183	{
4184	numDivisions = 1;
4185	for (i=0; i<numChar; i++)
4186	{
4187	charInfo[i].charType = dataType;
4188	partitionId[i][0] = numDivisions;
4189	}
4190	}
4191	}
4192	else
4193	{
4194	MrBayesPrint ("%s Invalid data type argument\n", spacer);
4195	return (ERROR);
4196	}
4197	if (isMixed == NO)
4198	MrBayesPrint ("%s Data is %s\n", spacer, tempStr);
4199	else if (strcmp(tempStr, "Mixed"))
4200	MrBayesPrint ("%s Data for partition %d is %s\n", spacer, numDivisions+1, tempStr);
4201	}
4202	else if (expecting == Expecting(LEFTPAR))
4203	{
4204	expecting = Expecting(ALPHA);
4205	}
4206	else if (expecting == Expecting(COLON))
4207	{
4208	expecting = Expecting(NUMBER);
4209	}
4210	else if (expecting == Expecting(NUMBER))
4211	{
4212	if (strlen(tkn) == 1 && tkn[0] == '.')
4213	tempInt = numChar;
4214	else
4215	sscanf (tkn, "%d", &tempInt);
4216	if (tempInt <= 0 \|\| tempInt > numChar)
4217	{
4218	MrBayesPrint ("%s Character number %d is out of range (should be between %d and %d)\n", spacer, tempInt, 1, numChar);
4219	return (ERROR);
4220	}
4221	tempInt--;
4222	if (foundDash == YES)
4223	{
4224	if (fromI >= 0)
4225	toJ = tempInt;
4226	else
4227	{
4228	MrBayesPrint ("%s Improperly formatted partition\n", spacer);
4229	return (ERROR);
4230	}
4231	foundDash = NO;
4232	}
4233	else if (foundSlash == YES)
4234	{
4235	tempInt++;
4236	if (tempInt <= 1)
4237	{
4238	MrBayesPrint ("%s Improperly formatted partition\n", spacer);
4239	return (ERROR);
4240	}
4241	if (fromI >= 0 && toJ >= 0 && fromI < toJ)
4242	everyK = tempInt;
4243	else
4244	{
4245	MrBayesPrint ("%s Improperly formatted partition\n", spacer);
4246	return (ERROR);
4247	}
4248	foundSlash = NO;
4249	}
4250	else
4251	{
4252	if (fromI >= 0 && toJ < 0)
4253	{
4254	if (AddToSet (fromI, toJ, everyK, numDivisions+1) == ERROR)
4255	return (ERROR);
4256	fromI = tempInt;
4257	}
4258	else if (fromI < 0 && toJ < 0)
4259	{
4260	fromI = tempInt;
4261	}
4262	else if (fromI >= 0 && toJ >= 0 && everyK < 0)
4263	{
4264	if (AddToSet (fromI, toJ, everyK, numDivisions+1) == ERROR)
4265	return (ERROR);
4266	fromI = tempInt;
4267	toJ = everyK = -1;
4268	}
4269	else if (fromI >= 0 && toJ >= 0 && everyK >= 0)
4270	{
4271	if (AddToSet (fromI, toJ, everyK, numDivisions+1) == ERROR)
4272	return (ERROR);
4273	fromI = tempInt;
4274	toJ = everyK = -1;
4275	}
4276	else
4277	{
4278	MrBayesPrint ("%s Improperly formatted partition\n", spacer);
4279	{
4280	return (ERROR);
4281	}
4282	}
4283
4284	}
4285	expecting = Expecting(NUMBER);
4286	expecting \|= Expecting(DASH);
4287	expecting \|= Expecting(BACKSLASH);
4288	expecting \|= Expecting(COMMA);
4289	expecting \|= Expecting(RIGHTPAR);
4290	}
4291	else if (expecting == Expecting(DASH))
4292	{
4293	foundDash = YES;
4294	expecting = Expecting(NUMBER);
4295	}
4296	else if (expecting == Expecting(BACKSLASH))
4297	{
4298	foundSlash = YES;
4299	expecting = Expecting(NUMBER);
4300	}
4301	else if (expecting == Expecting(COMMA))
4302	{
4303	/* add set to tempSet */
4304	if (fromI >= 0 && toJ < 0)
4305	{
4306	if (AddToSet (fromI, toJ, everyK, numDivisions+1) == ERROR)
4307	return (ERROR);
4308	}
4309	else if (fromI >= 0 && toJ >= 0 && everyK < 0)
4310	{
4311	if (AddToSet (fromI, toJ, everyK, numDivisions+1) == ERROR)
4312	return (ERROR);
4313	}
4314	else if (fromI >= 0 && toJ >= 0 && everyK >= 0)
4315	{
4316	if (AddToSet (fromI, toJ, everyK, numDivisions+1) == ERROR)
4317	return (ERROR);
4318	}
4319	for (i=0; i<numChar; i++)
4320	{
4321	if (tempSet[i] == numDivisions)
4322	charInfo[i].charType = dataType;
4323	}
4324
4325	/* merge tempSet */
4326	for (i=0; i<numChar; i++)
4327	{
4328	if (tempSet[i] != 0)
4329	{
4330	if (partitionId[i][0] == 0)
4331	{
4332	charInfo[i].charType = dataType;
4333	partitionId[i][0] = numDivisions + 1;
4334	}
4335	else
4336	{
4337	MrBayesPrint ("%s Improperly formatted partition (same character found in multiple partitions)\n", spacer);
4338	return (ERROR);
4339	}
4340	}
4341	}
4342
4343	/* increment number of partitions */
4344	numDivisions++;
4345	expecting = Expecting(ALPHA);
4346	}
4347	else if (expecting == Expecting(RIGHTPAR))
4348	{
4349	/* add set to tempSet */
4350	if (fromI >= 0 && toJ < 0)
4351	{
4352	if (AddToSet (fromI, toJ, everyK, numDivisions+1) == ERROR)
4353	return (ERROR);
4354	}
4355	else if (fromI >= 0 && toJ >= 0 && everyK < 0)
4356	{
4357	if (AddToSet (fromI, toJ, everyK, numDivisions+1) == ERROR)
4358	return (ERROR);
4359	}
4360	else if (fromI >= 0 && toJ >= 0 && everyK >= 0)
4361	{
4362	if (AddToSet (fromI, toJ, everyK, numDivisions+1) == ERROR)
4363	return (ERROR);
4364	}
4365
4366	/* merge tempSet */
4367	for (i=0; i<numChar; i++)
4368	{
4369	if (tempSet[i] != 0)
4370	{
4371	if (partitionId[i][0] == 0)
4372	{
4373	charInfo[i].charType = dataType;
4374	partitionId[i][0] = numDivisions + 1;
4375	}
4376	else
4377	{
4378	MrBayesPrint ("%s Improperly formatted partition (same character found in multiple partitions)\n", spacer);
4379	return (ERROR);
4380	}
4381	}
4382	}
4383
4384	/* increment number of partitions */
4385	numDivisions++;
4386	if (isMixed == YES)
4387	dataType = MIXED;
4388
4389	if (numDivisions > 1)
4390	MrBayesPrint ("%s There are a total of %d default data divisions\n", spacer, numDivisions);
4391	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
4392	}
4393	else
4394	return (ERROR);
4395	}
4396	/* set Interleave (isInterleaved) *****************************************************/
4397	else if (!strcmp(parmName, "Interleave"))
4398	{
4399	if (expecting == Expecting(EQUALSIGN))
4400	expecting = Expecting(ALPHA);
4401	else if (expecting == Expecting(ALPHA))
4402	{
4403	if (IsArgValid(tkn, tempStr) == NO_ERROR)
4404	{
4405	if (!strcmp(tempStr, "Yes"))
4406	isInterleaved = YES;
4407	else
4408	isInterleaved = NO;
4409	}
4410	else
4411	{
4412	MrBayesPrint ("%s Invalid argument for interleaved data\n", spacer);
4413	return (ERROR);
4414	}
4415	if (isInterleaved == YES)
4416	MrBayesPrint ("%s Data matrix is interleaved\n", spacer);
4417	else
4418	MrBayesPrint ("%s Data matrix is not interleaved\n", spacer);
4419	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
4420	}
4421	else
4422	return (ERROR);
4423	}
4424	/* set Gap (gapId) ********************************************************************/
4425	else if (!strcmp(parmName, "Gap"))
4426	{
4427	if (expecting == Expecting(EQUALSIGN))
4428	{
4429	expecting = Expecting(ALPHA);
4430	expecting \|= Expecting(QUESTIONMARK);
4431	expecting \|= Expecting(DASH);
4432	expecting \|= Expecting(NUMBER);
4433	expecting \|= Expecting(ASTERISK);
4434	expecting \|= Expecting(EXCLAMATIONMARK);
4435	expecting \|= Expecting(PERCENT);
4436	expecting \|= Expecting(WEIRD);
4437	}
4438	else if (((expecting & Expecting(ALPHA)) == Expecting(ALPHA)) \|\|
4439	((expecting & Expecting(QUESTIONMARK)) == Expecting(QUESTIONMARK)) \|\|
4440	((expecting & Expecting(DASH)) == Expecting(DASH)) \|\|
4441	((expecting & Expecting(NUMBER)) == Expecting(NUMBER)) \|\|
4442	((expecting & Expecting(ASTERISK)) == Expecting(ASTERISK)) \|\|
4443	((expecting & Expecting(EXCLAMATIONMARK)) == Expecting(EXCLAMATIONMARK)) \|\|
4444	((expecting & Expecting(PERCENT)) == Expecting(PERCENT)) \|\|
4445	((expecting & Expecting(WEIRD)) == Expecting(WEIRD)))
4446	{
4447	if (strlen(tkn) == 1)
4448	{
4449	if (tkn[0] == matchId \|\| tkn[0] == missingId)
4450	{
4451	MrBayesPrint ("%s Gap character matches matching or missing characters\n", spacer);
4452	return (ERROR);
4453	}
4454	gapId = tkn[0];
4455	}
4456	else
4457	{
4458	MrBayesPrint ("%s Invalid gap argument %s\n", spacer, tkn);
4459	return (ERROR);
4460	}
4461	MrBayesPrint ("%s Gaps coded as %s\n", spacer, tkn);
4462	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
4463	}
4464	else
4465	return (ERROR);
4466	}
4467	/* set Missing (missingId) ************************************************************/
4468	else if (!strcmp(parmName, "Missing"))
4469	{
4470	if (expecting == Expecting(EQUALSIGN))
4471	{
4472	expecting = Expecting(ALPHA);
4473	expecting \|= Expecting(QUESTIONMARK);
4474	expecting \|= Expecting(DASH);
4475	expecting \|= Expecting(NUMBER);
4476	expecting \|= Expecting(ASTERISK);
4477	expecting \|= Expecting(EXCLAMATIONMARK);
4478	expecting \|= Expecting(PERCENT);
4479	expecting \|= Expecting(WEIRD);
4480	}
4481	else if (((expecting & Expecting(ALPHA)) == Expecting(ALPHA)) \|\|
4482	((expecting & Expecting(QUESTIONMARK)) == Expecting(QUESTIONMARK)) \|\|
4483	((expecting & Expecting(DASH)) == Expecting(DASH)) \|\|
4484	((expecting & Expecting(NUMBER)) == Expecting(NUMBER)) \|\|
4485	((expecting & Expecting(ASTERISK)) == Expecting(ASTERISK)) \|\|
4486	((expecting & Expecting(EXCLAMATIONMARK)) == Expecting(EXCLAMATIONMARK)) \|\|
4487	((expecting & Expecting(PERCENT)) == Expecting(PERCENT)) \|\|
4488	((expecting & Expecting(WEIRD)) == Expecting(WEIRD)))
4489	{
4490	if (strlen(tkn) == 1)
4491	{
4492	if (tkn[0] == gapId \|\| tkn[0] == matchId)
4493	{
4494	MrBayesPrint ("%s Missing character matches matching or gap characters\n", spacer);
4495	return (ERROR);
4496	}
4497	missingId = tkn[0];
4498	}
4499	else
4500	{
4501	MrBayesPrint ("%s Invalid missing argument %s\n", spacer, tkn);
4502	return (ERROR);
4503	}
4504	MrBayesPrint ("%s Missing data coded as %s\n", spacer, tkn);
4505	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
4506	}
4507	else
4508	return (ERROR);
4509	}
4510	/* set Matchchar (matchId) ************************************************************/
4511	else if (!strcmp(parmName, "Matchchar"))
4512	{
4513	if (expecting == Expecting(EQUALSIGN))
4514	{
4515	expecting = Expecting(ALPHA);
4516	expecting \|= Expecting(QUESTIONMARK);
4517	expecting \|= Expecting(DASH);
4518	expecting \|= Expecting(NUMBER);
4519	expecting \|= Expecting(ASTERISK);
4520	expecting \|= Expecting(EXCLAMATIONMARK);
4521	expecting \|= Expecting(PERCENT);
4522	expecting \|= Expecting(WEIRD);
4523	}
4524	else if (((expecting & Expecting(ALPHA)) == Expecting(ALPHA)) \|\|
4525	((expecting & Expecting(QUESTIONMARK)) == Expecting(QUESTIONMARK)) \|\|
4526	((expecting & Expecting(DASH)) == Expecting(DASH)) \|\|
4527	((expecting & Expecting(NUMBER)) == Expecting(NUMBER)) \|\|
4528	((expecting & Expecting(ASTERISK)) == Expecting(ASTERISK)) \|\|
4529	((expecting & Expecting(EXCLAMATIONMARK)) == Expecting(EXCLAMATIONMARK)) \|\|
4530	((expecting & Expecting(PERCENT)) == Expecting(PERCENT)) \|\|
4531	((expecting & Expecting(WEIRD)) == Expecting(WEIRD)))
4532	{
4533	if (strlen(tkn) == 1)
4534	{
4535	if (tkn[0] == gapId \|\| tkn[0] == missingId)
4536	{
4537	MrBayesPrint ("%s Matching character matches gap or missing characters\n", spacer);
4538	return (ERROR);
4539	}
4540	matchId = tkn[0];
4541	}
4542	else
4543	{
4544	MrBayesPrint ("%s Invalid matchchar argument %s\n", spacer, tkn);
4545	return (ERROR);
4546	}
4547	MrBayesPrint ("%s Matching characters coded as %s\n", spacer, tkn);
4548	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
4549	}
4550	else
4551	return (ERROR);
4552	}
4553	/* skip Symbols ***************************************************************/
4554	else if (!strcmp(parmName, "Symbols"))
4555	{
4556	if (expecting == Expecting(EQUALSIGN))
4557	{
4558	MrBayesPrint ("%s Warning: MrBayes does not support 'symbols' specifications; default symbols assumed\n", spacer);
4559	expecting = Expecting(QUOTATIONMARK);
4560	foundQuote = NO;
4561	}
4562	else if (expecting == Expecting(QUOTATIONMARK))
4563	{
4564	if (foundQuote == NO)
4565	{
4566	foundQuote = YES;
4567	expecting = Expecting(ALPHA);
4568	}
4569	else /* if (foundQuote == YES) */
4570	{
4571	foundQuote = NO;
4572	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
4573	}
4574	}
4575	else if (expecting == Expecting(ALPHA))
4576	{
4577	expecting = Expecting(ALPHA) \| Expecting(COMMA);
4578	}
4579	else
4580	return (ERROR);
4581	}
4582	/* on Equate return ERROR ***************************************************************/
4583	else if (!strcmp(parmName, "Equate"))
4584	{
4585	MrBayesPrint ("%s Error: MrBayes does not support 'Equate' macros; please remove or comment out\n", spacer);
4586	return (ERROR);
4587	}
4588	else
4589	return (ERROR);
4590	}
4591
4592	return (NO_ERROR);
4593
4594	}
4595
4596
4597
4598
4599
4600	int DoHelp (void)
4601
4602	{
4603
4604	int i, j, longestDescription;
4605	CmdType *p;
4606
4607	if (foundFirst == NO)
4608	{
4609	longestDescription = 0;
4610	for (i=1; i<NUMCOMMANDS; i++)
4611	{
4612	p = commands + i;
4613	if ((int)strlen(p->string) > longestDescription)
4614	longestDescription = (int) strlen(p->string);
4615	}
4616
4617	MrBayesPrint (" --------------------------------------------------------------------------- \n");
4618	MrBayesPrint (" Commands that are available from the command \n");
4619	MrBayesPrint (" line or from a MrBayes block include: \n");
4620	MrBayesPrint (" \n");
4621	for (i=1; i<NUMCOMMANDS; i++)
4622	{
4623	p = commands + i;
4624	if (p->cmdUse == IN_CMD && p->hiding == SHOW)
4625	{
4626	MrBayesPrint (" %s", p->string);
4627	for (j=0; j<longestDescription - (int) strlen(p->string); j++)
4628	MrBayesPrint (" ");
4629	MrBayesPrint (" -- %s\n", p->cmdDescription);
4630	}
4631	}
4632	MrBayesPrint (" \n");
4633	MrBayesPrint (" Commands that should be in a NEXUS file (data \n");
4634	MrBayesPrint (" block, trees block or taxa block) include: \n");
4635	MrBayesPrint (" \n");
4636	for (i=1; i<NUMCOMMANDS; i++)
4637	{
4638	p = commands + i;
4639	if (p->cmdUse == IN_FILE && p->hiding == SHOW)
4640	{
4641	MrBayesPrint (" %s", p->string);
4642	for (j=0; j<longestDescription - (int) strlen(p->string); j++)
4643	MrBayesPrint (" ");
4644	MrBayesPrint (" -- %s\n", p->cmdDescription);
4645	}
4646	}
4647	MrBayesPrint (" \n");
4648	MrBayesPrint (" Note that this program supports the use of the shortest unambiguous \n");
4649	MrBayesPrint (" spelling of the above commands (e.g., \"exe\" instead of \"execute\"). \n");
4650	MrBayesPrint (" --------------------------------------------------------------------------- \n");
4651	}
4652	foundFirst = NO;
4653
4654	return (NO_ERROR);
4655
4656	}
4657
4658
4659
4660
4661
4662	int DoHelpParm (char parmName, char tkn)
4663
4664	{
4665
4666	int i, j, tkLen, targetLen, numDiff, numMatches;
4667	CmdType p, q=NULL;
4668
4669	if (expecting == Expecting(ALPHA))
4670	{
4671	p = commands + 0;
4672	tkLen = (int) strlen(tkn);
4673	numMatches = 0;
4674	for (i=0; i<NUMCOMMANDS; i++)
4675	{
4676	targetLen = (int) strlen(p->string);
4677	if (tkLen <= targetLen)
4678	{
4679	for (j=0, numDiff=0; j<tkLen; j++)
4680	{
4681	if (ChangeCase(tkn[j]) != ChangeCase(p->string[j]))
4682	numDiff++;
4683	}
4684	if (numDiff == 0)
4685	{
4686	numMatches++;
4687	q = p;
4688	if (tkLen == targetLen)
4689	break;
4690	}
4691	}
4692	p++;
4693	}
4694	if (numMatches == 0)
4695	{
4696	MrBayesPrint ("%s Could not find command \"%s\"\n", spacer, tkn);
4697	return (ERROR);
4698	}
4699	else if (numMatches == 1)
4700	{
4701	if (GetUserHelp (q->string) == ERROR)
4702	{
4703	MrBayesPrint ("%s Problem getting help for command \"%s\"\n", spacer, q->string);
4704	}
4705	}
4706	else
4707	{
4708	MrBayesPrint ("%s Ambiguous command \"%s\"\n", spacer, tkn);
4709	return (ERROR);
4710	}
4711
4712	expecting = Expecting(SEMICOLON);
4713	foundFirst = YES;
4714	}
4715	else
4716	return (ERROR);
4717
4718	return (NO_ERROR);
4719	MrBayesPrint ("%s", parmName); /* just because I am tired of seeing the unused parameter error msg */
4720
4721	}
4722
4723
4724
4725
4726
4727	int DoInclude (void)
4728
4729	{
4730
4731	int i, alreadyDone;
4732
4733	MrBayesPrint ("%s Including character(s)\n", spacer);
4734
4735	/* add set to tempSet */
4736	if (fromI >= 0 && toJ < 0)
4737	{
4738	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
4739	return (ERROR);
4740	}
4741	else if (fromI >= 0 && toJ >= 0 && everyK < 0)
4742	{
4743	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
4744	return (ERROR);
4745	}
4746	else if (fromI >= 0 && toJ >= 0 && everyK >= 0)
4747	{
4748	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
4749	return (ERROR);
4750	}
4751
4752	/* merge tempSet with excludedChars */
4753	alreadyDone = NO;
4754	for (i=0; i<numChar; i++)
4755	{
4756	if (tempSet[i] == 1)
4757	{
4758	if (charInfo[i].isExcluded == NO && alreadyDone == NO)
4759	{
4760	MrBayesPrint ("%s Some characters already included\n", spacer);
4761	alreadyDone = YES;
4762	}
4763	charInfo[i].isExcluded = NO;
4764	}
4765	}
4766
4767	return (NO_ERROR);
4768
4769	}
4770
4771
4772
4773
4774
4775	int DoIncludeParm (char parmName, char tkn)
4776
4777	{
4778
4779	int i, index, tempInt;
4780
4781	if (defMatrix == NO)
4782	{
4783	MrBayesPrint ("%s A matrix must be specified before you can include characters\n", spacer);
4784	return (ERROR);
4785	}
4786
4787	if (foundFirst == NO)
4788	{
4789	/* this is the first time in */
4790	fromI = toJ = everyK = -1;
4791	foundDash = foundSlash = NO;
4792	for (i=0; i<numChar; i++) /* clear tempSet */
4793	tempSet[i] = 0;
4794	foundFirst = YES;
4795	}
4796
4797	if (expecting == Expecting(ALPHA))
4798	{
4799	if (IsSame ("All", tkn) == SAME \|\| IsSame ("All", tkn) == CONSISTENT_WITH)
4800	{
4801	for (i=0; i<numChar; i++)
4802	tempSet[i] = 1;
4803	}
4804	else if (IsSame ("Missambig", tkn) == SAME \|\| IsSame ("Missambig", tkn) == CONSISTENT_WITH)
4805	{
4806	for (i=0; i<numChar; i++)
4807	{
4808	if (charInfo[i].isMissAmbig == YES)
4809	tempSet[i] = 1;
4810	}
4811	}
4812	else
4813	{
4814	/* we are using a pre-defined character set */
4815	if (numCharSets < 1)
4816	{
4817	MrBayesPrint ("%s Could not find a character set called %s\n", spacer, tkn);
4818	return (ERROR);
4819	}
4820	if (CheckString (charSetNames, numCharSets, tkn, &index) == ERROR)
4821	{
4822	MrBayesPrint ("%s Could not find a character set called %s\n", spacer, tkn);
4823	return (ERROR);
4824	}
4825	/* add characters from charset tkn to new tempSet */
4826	for (i=0; i<numChar; i++)
4827	{
4828	if (IsBitSet(i, charSet[index]) == YES)
4829	tempSet[i] = 1;
4830	}
4831	fromI = toJ = everyK = -1;
4832	}
4833
4834	expecting = Expecting(ALPHA);
4835	expecting \|= Expecting(NUMBER);
4836	expecting \|= Expecting(SEMICOLON);
4837	}
4838	else if (expecting == Expecting(NUMBER))
4839	{
4840	if (strlen(tkn) == 1 && tkn[0] == '.')
4841	tempInt = numChar;
4842	else
4843	sscanf (tkn, "%d", &tempInt);
4844	if (tempInt <= 0 \|\| tempInt > numChar)
4845	{
4846	MrBayesPrint ("%s Character number %d is out of range (should be between %d and %d)\n", spacer, tempInt, 1, numChar);
4847	return (ERROR);
4848	}
4849	tempInt--;
4850	if (foundDash == YES)
4851	{
4852	if (fromI >= 0)
4853	toJ = tempInt;
4854	else
4855	{
4856	MrBayesPrint ("%s Improperly formatted include set\n", spacer);
4857	return (ERROR);
4858	}
4859	foundDash = NO;
4860	}
4861	else if (foundSlash == YES)
4862	{
4863	tempInt++;
4864	if (tempInt <= 1)
4865	{
4866	MrBayesPrint ("%s Improperly formatted include set\n", spacer);
4867	return (ERROR);
4868	}
4869	if (fromI >= 0 && toJ >= 0 && fromI < toJ)
4870	everyK = tempInt;
4871	else
4872	{
4873	MrBayesPrint ("%s Improperly formatted include set\n", spacer);
4874	return (ERROR);
4875	}
4876	foundSlash = NO;
4877	}
4878	else
4879	{
4880	if (fromI >= 0 && toJ < 0)
4881	{
4882	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
4883	return (ERROR);
4884	fromI = tempInt;
4885	}
4886	else if (fromI < 0 && toJ < 0)
4887	{
4888	fromI = tempInt;
4889	}
4890	else if (fromI >= 0 && toJ >= 0 && everyK < 0)
4891	{
4892	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
4893	return (ERROR);
4894	fromI = tempInt;
4895	toJ = everyK = -1;
4896	}
4897	else if (fromI >= 0 && toJ >= 0 && everyK >= 0)
4898	{
4899	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
4900	return (ERROR);
4901	fromI = tempInt;
4902	toJ = everyK = -1;
4903	}
4904	else
4905	{
4906	MrBayesPrint ("%s Improperly formatted include set\n", spacer);
4907	{
4908	return (ERROR);
4909	}
4910	}
4911	}
4912	expecting = Expecting(ALPHA);
4913	expecting \|= Expecting(NUMBER);
4914	expecting \|= Expecting(SEMICOLON);
4915	expecting \|= Expecting(DASH);
4916	expecting \|= Expecting(BACKSLASH);
4917	}
4918	else if (expecting == Expecting(DASH))
4919	{
4920	foundDash = YES;
4921	expecting = Expecting(NUMBER);
4922	}
4923	else if (expecting == Expecting(BACKSLASH))
4924	{
4925	foundSlash = YES;
4926	expecting = Expecting(NUMBER);
4927	}
4928	else
4929	return (ERROR);
4930
4931	return (NO_ERROR);
4932	MrBayesPrint ("%s", parmName); /* just because I am tired of seeing the unused parameter error msg */
4933
4934	}
4935
4936
4937
4938
4939
4940	int DoLog (void)
4941
4942	{
4943
4944	if (logToFile == YES)
4945	{
4946	SafeFclose (&logFileFp);
4947	if (replaceLogFile == YES)
4948	{
4949	if ((logFileFp = OpenTextFileW (logFileName)) == NULL)
4950	{
4951	logToFile = NO;
4952	return (ERROR);
4953	}
4954	}
4955	else
4956	{
4957	if ((logFileFp = OpenTextFileA (logFileName)) == NULL)
4958	{
4959	logToFile = NO;
4960	return (ERROR);
4961	}
4962	}
4963	MrBayesPrint ("%s Logging screen output to file \"%s\"\n", spacer, logFileName);
4964	}
4965	else
4966	{
4967	SafeFclose (&logFileFp);
4968	MrBayesPrint ("%s Terminating log output\n", spacer);
4969	}
4970
4971	return (NO_ERROR);
4972
4973	}
4974
4975
4976
4977
4978
4979	int DoLogParm (char parmName, char tkn)
4980
4981	{
4982
4983	if (expecting == Expecting(PARAMETER))
4984	{
4985	if (!strcmp(parmName, "Start"))
4986	{
4987	if (logToFile == YES)
4988	MrBayesPrint ("%s Logging to file is already on\n", spacer, logFileName);
4989	else
4990	logToFile = YES;
4991	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
4992	}
4993	else if (!strcmp(parmName, "Stop"))
4994	{
4995	if (logToFile == NO)
4996	MrBayesPrint ("%s Logging to file is already off\n", spacer, logFileName);
4997	else
4998	logToFile = NO;
4999	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
5000	}
5001	else if (!strcmp(parmName, "Replace"))
5002	{
5003	replaceLogFile = YES;
5004	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
5005	}
5006	else if (!strcmp(parmName, "Append"))
5007	{
5008	replaceLogFile = NO;
5009	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
5010	}
5011	else
5012	expecting = Expecting(EQUALSIGN);
5013	}
5014	else
5015	{
5016	if (!strcmp(parmName, "Filename"))
5017	{
5018	if (expecting == Expecting(EQUALSIGN))
5019	{
5020	expecting = Expecting(ALPHA);
5021	readWord = YES;
5022	}
5023	else if (expecting == Expecting(ALPHA))
5024	{
5025	strcpy (logFileName, tkn);
5026	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
5027	}
5028	else
5029	return (ERROR);
5030	}
5031	else
5032	{
5033	MrBayesPrint ("%s Unknown parameter in Log\n", spacer);
5034	return (ERROR);
5035	}
5036	}
5037
5038	return (NO_ERROR);
5039
5040	}
5041
5042
5043
5044
5045
5046	int DoManual (void)
5047
5048	{
5049
5050	int i, j, logSetting;
5051	char title[100];
5052	FILE fp, logfp;
5053	CmdType *p;
5054
5055	/* try to open file, return error if present */
5056	if ((fp = OpenTextFileRQuait(manFileName)) != NULL)
5057	{
5058	MrBayesPrint ("%s File \"%s\" already exists \n", spacer, manFileName);
5059	SafeFclose(&fp);
5060	return (ERROR);
5061	}
5062
5063	/* try to open file for writing, return error if not possible */
5064	if ((fp = OpenTextFileW(manFileName)) == NULL)
5065	return (ERROR);
5066
5067	/* print message */
5068	MrBayesPrint ("%s Producing command reference file \"%s\"\n", spacer, manFileName);
5069
5070	/* temporarily disable normal logging and switch echoing off */
5071	logSetting = logToFile;
5072	logfp = logFileFp;
5073	echoMB = NO;
5074	logToFile = YES;
5075	logFileFp = fp;
5076
5077	/* produce command reference file */
5078	/* header */
5079	strcpy (title, "Command Reference for MrBayes ver. ");
5080	strcat (title, VERSION_NUMBER);
5081
5082	i = (70 - (int) strlen (title)) / 2;
5083	j = 70 - i - (int) strlen(title);
5084
5085	MrBayesPrint (" \n");
5086	MrBayesPrint (" \n");
5087	MrBayesPrint (" \n");
5088	MrBayesPrint (" \n");
5089	MrBayesPrint (" %c%s%c \n", i, ' ', title, j, ' ');
5090	MrBayesPrint (" \n");
5091	MrBayesPrint (" (c) John P. Huelsenbeck, Fredrik Ronquist \n");
5092	MrBayesPrint (" and Maxim Teslenko \n");
5093	MrBayesPrint (" \n");
5094
5095	/* summary */
5096	MrBayesPrint (" \n");
5097	MrBayesPrint (" *************************************************************************** \n");
5098	MrBayesPrint (" * * \n");
5099	MrBayesPrint (" * 1. Command summary * \n");
5100	MrBayesPrint (" * * \n");
5101	MrBayesPrint (" *************************************************************************** \n");
5102	MrBayesPrint (" \n");
5103	foundFirst = NO;
5104	if (DoHelp() == ERROR)
5105	{
5106	MrBayesPrint ("%s Could not produce command reference summary\n", spacer);
5107	goto errorExit;
5108	}
5109
5110	/* list of MrBayes commands */
5111	MrBayesPrint (" \n");
5112	MrBayesPrint (" *************************************************************************** \n");
5113	MrBayesPrint (" * * \n");
5114	MrBayesPrint (" * 2. MrBayes commands * \n");
5115	MrBayesPrint (" * * \n");
5116	MrBayesPrint (" *************************************************************************** \n");
5117	MrBayesPrint (" \n");
5118	for (i=1; i<NUMCOMMANDS; i++)
5119	{
5120	p = commands + i;
5121	if (p->cmdUse == IN_CMD && p->hiding == SHOW)
5122	{
5123	if (GetUserHelp(p->string)==ERROR)
5124	goto errorExit;
5125	}
5126	}
5127
5128	/* list of data or tree block commands */
5129	MrBayesPrint (" \n");
5130	MrBayesPrint (" *************************************************************************** \n");
5131	MrBayesPrint (" * * \n");
5132	MrBayesPrint (" * 3. 'Data' or 'tree' block commands (in #NEXUS file) * \n");
5133	MrBayesPrint (" * * \n");
5134	MrBayesPrint (" *************************************************************************** \n");
5135	MrBayesPrint (" \n");
5136	for (i=1; i<NUMCOMMANDS; i++)
5137	{
5138	p = commands + i;
5139	if (p->cmdUse == IN_FILE && p->hiding == SHOW)
5140	{
5141	if (GetUserHelp(p->string) == ERROR)
5142	goto errorExit;
5143	}
5144	}
5145
5146	/* return logging to previous setings and switch echoing on */
5147	SafeFclose (&fp);
5148	logToFile = logSetting;
5149	logFileFp = logfp;
5150	echoMB = YES;
5151
5152	MrBayesPrint ("%s Successfully produced command reference file \"%s\"\n", spacer, manFileName);
5153
5154	return (NO_ERROR);
5155
5156	errorExit:
5157	SafeFclose (&fp);
5158	logToFile = logSetting;
5159	logFileFp = logfp;
5160	echoMB = YES;
5161
5162	return (ERROR);
5163
5164	}
5165
5166
5167
5168
5169
5170	int DoManualParm (char parmName, char tkn)
5171
5172	{
5173
5174	if (expecting == Expecting(PARAMETER))
5175	{
5176	expecting = Expecting(EQUALSIGN);
5177	}
5178	else
5179	{
5180	if (!strcmp(parmName, "Filename"))
5181	{
5182	if (expecting == Expecting(EQUALSIGN))
5183	{
5184	expecting = Expecting(ALPHA);
5185	readWord = YES;
5186	}
5187	else if (expecting == Expecting(ALPHA))
5188	{
5189	strcpy (manFileName, tkn);
5190	expecting = Expecting(SEMICOLON);
5191	}
5192	else
5193	return (ERROR);
5194	}
5195	else
5196	{
5197	MrBayesPrint ("%s Unknown parameter in Manual\n", spacer);
5198	return (ERROR);
5199	}
5200	}
5201
5202	return (NO_ERROR);
5203
5204	}
5205
5206
5207
5208
5209
5210	int DoMatrix (void)
5211
5212	{
5213
5214	int i, j, hasMissingAmbig;
5215
5216	if (taxonCount != numTaxa)
5217	{
5218	MrBayesPrint ("%s Problem with number of taxa read in (%d taxa read in, while expecting %d)\n", spacer, taxonCount, numTaxa);
5219	FreeMatrix();
5220	return (ERROR);
5221	}
5222	for (i=0; i<numTaxa; i++)
5223	{
5224	if (taxaInfo[i].charCount != numChar)
5225	{
5226	MrBayesPrint ("%s Problem with number of characters read in (%d expected for taxon %d, %d read in)\n", spacer, numChar, i, taxaInfo[i].charCount);
5227	FreeMatrix();
5228	return (ERROR);
5229	}
5230	}
5231
5232	/* find out which characters have missing or ambiguous states (one time only, so no special function) */
5233	for (i=0; i<numChar; i++)
5234	{
5235	hasMissingAmbig = NO;
5236	for (j=0; j<numTaxa; j++)
5237	{
5238	if (IsMissing (matrix[pos(j,i,numChar)], charInfo[i].charType) == YES)
5239	hasMissingAmbig = YES;
5240	if (IsAmbig (matrix[pos(j,i,numChar)], charInfo[i].charType) == YES)
5241	hasMissingAmbig = YES;
5242	}
5243	if (hasMissingAmbig == YES)
5244	charInfo[i].isMissAmbig = YES;
5245	}
5246
5247	MrBayesPrint ("%s Successfully read matrix\n", spacer);
5248	if (matrixHasPoly == YES)
5249	MrBayesPrint ("%s Matrix contains polymorphisms, interpreted as ambiguity\n", spacer);
5250	defMatrix = YES;
5251	isTaxsetDef = YES;
5252
5253	/* add name of default partition */
5254	if (AddString (&partitionNames, 0, "Default") == ERROR)
5255	{
5256	MrBayesPrint ("%s Problem adding Default name to partition list\n", spacer);
5257	return (ERROR);
5258	}
5259	numDefinedPartitions = 1;
5260
5261	if (numDefinedSpeciespartitions == 0) /* the default species partition could have been added already in DoTaxLabels */
5262	{
5263	/* add default speciespartition name to list of valid speciespartitions */
5264	if (AddString (&speciespartitionNames, 0, "Default") == ERROR)
5265	{
5266	MrBayesPrint ("%s Problem adding Default speciespartition to list\n", spacer);
5267	return (ERROR);
5268	}
5269
5270	/* add default species name set */
5271	AddNameSet(&speciesNameSets, 0, taxaNames, numTaxa);
5272
5273	/* set number of defined speciespartitions to 1 */
5274	numDefinedSpeciespartitions = 1;
5275	}
5276
5277	if (SetPartition (0) == ERROR)
5278	return ERROR;
5279
5280	if (SetSpeciespartition (0) == ERROR)
5281	return ERROR;
5282
5283	if (numCurrentDivisions == 1)
5284	MrBayesPrint ("%s Setting default partition (does not divide up characters)\n", spacer);
5285	else
5286	MrBayesPrint ("%s Setting default partition, dividing characters into %d parts\n", spacer, numCurrentDivisions);
5287
5288	if (SetModelDefaults () == ERROR)
5289	return (ERROR);
5290
5291	if (SetUpAnalysis (&globalSeed) == ERROR)
5292	return (ERROR);
5293
5294	/* set default names for some output file names based on processed file */
5295	strcpy (sumtParams.sumtFileName, inputFileName);
5296	strcpy (sumtParams.sumtOutfile, inputFileName);
5297	strcpy (sumpParams.sumpFileName, inputFileName);
5298	strcpy (sumpParams.sumpOutfile, inputFileName);
5299	strcpy (comptreeParams.comptOutfile, inputFileName);
5300
5301	if (chainParams.numRuns == 1)
5302	{
5303	sprintf (comptreeParams.comptFileName1, "%s.t", inputFileName);
5304	sprintf (comptreeParams.comptFileName2, "%s.t", inputFileName);
5305	}
5306	else /* if (chainParams.numRuns > 1) */
5307	{
5308	sprintf (comptreeParams.comptFileName1, "%s.run1.t", inputFileName);
5309	sprintf (comptreeParams.comptFileName2, "%s.run2.t", inputFileName);
5310	}
5311
5312	if (chainParams.numRuns == 1)
5313	sprintf (plotParams.plotFileName, "%s.p", inputFileName);
5314	else /* if (chainParams.numRuns > 1) */
5315	sprintf (plotParams.plotFileName, "%s.run1.p", inputFileName);
5316
5317	strcpy (chainParams.chainFileName, inputFileName);
5318
5319	if (chainParams.numRuns > 1)
5320	MrBayesPrint ("%s Setting output file names to \"%s.run<i>.<p\|t>\"\n", spacer, chainParams.chainFileName);
5321	else
5322	MrBayesPrint ("%s Setting output file names to \"%s.<p\|t>\"\n", spacer, chainParams.chainFileName);
5323
5324	# if 0
5325	for (i=0; i<numChar; i++)
5326	{
5327	int j;
5328	MrBayesPrint ("%4d -- ", i+1);
5329	for (j=0; j<numTaxa; j++)
5330	MrBayesPrint ("%2d ", matrix[pos(j,i,numChar)]);
5331	MrBayesPrint ("\n");
5332	}
5333	# endif
5334
5335	return (NO_ERROR);
5336
5337	}
5338
5339
5340
5341
5342
5343	int DoMatrixParm (char parmName, char tkn)
5344
5345	{
5346
5347	int i, j, charCode, index;
5348	MrBFlt charValue;
5349
5350	expecting = Expecting(ALPHA);
5351	expecting \|= Expecting(QUESTIONMARK);
5352	expecting \|= Expecting(DASH);
5353	expecting \|= Expecting(NUMBER);
5354	expecting \|= Expecting(ASTERISK);
5355	expecting \|= Expecting(EXCLAMATIONMARK);
5356	expecting \|= Expecting(PERCENT);
5357	expecting \|= Expecting(WEIRD);
5358	expecting \|= Expecting(SEMICOLON);
5359	expecting \|= Expecting(LEFTPAR);
5360	expecting \|= Expecting(RIGHTPAR);
5361	expecting \|= Expecting(LEFTCURL);
5362	expecting \|= Expecting(RIGHTCURL);
5363
5364	if (defTaxa == NO \|\| defChars == NO)
5365	{
5366	MrBayesPrint ("%s Number of taxa and characters needs to be defined before matrix is read\n", spacer);
5367	goto errorExit;
5368	}
5369	if (inDataBlock == NO && inCharactersBlock == NO)
5370	{
5371	MrBayesPrint ("%s Must be in data or characters block to read in character matrix\n", spacer);
5372	goto errorExit;
5373	}
5374
5375	if (isFirstMatrixRead == YES)
5376	{
5377	foundNewLine = YES;
5378	isFirstInterleavedBlock = YES;
5379	taxonCount = 0;
5380	isNegative = NO;
5381	}
5382	isFirstMatrixRead = NO;
5383
5384	/* allow line breaks in non-interleaved matrices */
5385	if (isInterleaved == NO)
5386	{
5387	if (foundNewLine == YES && taxonCount > 0)
5388	{
5389	if (taxaInfo[taxonCount-1].charCount < numChar)
5390	foundNewLine = NO;
5391	}
5392	}
5393
5394	if (taxonCount >= numTaxa && foundNewLine == YES)
5395	{
5396	if (isInterleaved == YES)
5397	{
5398	taxonCount = 0;
5399	isFirstInterleavedBlock = NO;
5400	}
5401	else
5402	{
5403	MrBayesPrint ("%s Too many taxa in matrix\n", spacer);
5404	goto errorExit;
5405	}
5406	}
5407
5408	if (taxaInfo[0].charCount > 4010)
5409	i = 1;
5410
5411	if (foundNewLine == YES)
5412	{
5413	/* Should be a taxon. */
5414	if (isFirstInterleavedBlock == YES)
5415	{
5416	/* If this is the first interleaved block, then we need to add the taxon
5417	to the set of taxon names unless there is already a defined taxon set. */
5418	if ( strlen(tkn)>99 )
5419	{
5420	MrBayesPrint ("%s Taxon name %s is too long. Maximun 99 characters is allowed.\n", spacer, tkn);
5421	goto errorExit;
5422	}
5423	if (isTaxsetDef == NO && AddString (&taxaNames, taxonCount, tkn) == ERROR)
5424	{
5425	MrBayesPrint ("%s Problem adding taxon %s to taxon set\n", spacer, tkn);
5426	goto errorExit;
5427	}
5428	if (numTaxa < 10)
5429	MrBayesPrint ("%s Taxon %d -> %s\n", spacer, taxonCount+1, tkn);
5430	else if (numTaxa < 100 && numTaxa >= 10)
5431	MrBayesPrint ("%s Taxon %2d -> %s\n", spacer, taxonCount+1, tkn);
5432	else if (numTaxa < 1000 && numTaxa >= 100)
5433	MrBayesPrint ("%s Taxon %3d -> %s\n", spacer, taxonCount+1, tkn);
5434	else
5435	MrBayesPrint ("%s Taxon %4d -> %s\n", spacer, taxonCount+1, tkn);
5436	}
5437	else
5438	{
5439	/* If this is not the first interleaved block, then we need to
5440	check to see if taxon name is present and in correct place. */
5441	if (CheckString (taxaNames, numTaxa, tkn, &index) == ERROR)
5442	{
5443	MrBayesPrint ("%s Could not find taxon %s in list of taxa\n", spacer, tkn);
5444	goto errorExit;
5445	}
5446	if (index != taxonCount)
5447	{
5448	MrBayesPrint ("%s Could not find taxon %s in correct position in list of taxa\n", spacer, tkn);
5449	goto errorExit;
5450	}
5451	}
5452	foundNewLine = NO;
5453	isNegative = NO;
5454	taxonCount++;
5455	}
5456	else
5457	{
5458	/* Should be a character (either continuous or otherwise). */
5459	if (charInfo[taxaInfo[taxonCount-1].charCount].charType == CONTINUOUS)
5460	{
5461	/* If we have a CONTINUOUS character, then the entire token should either be
5462	a number or a dash (for a negative sign). */
5463	if (!strcmp(tkn, "-"))
5464	{
5465	/* Dealing with a negative number. We will multiply the next tkn, which
5466	had better be a number, by -1. */
5467	isNegative = YES;
5468	}
5469	else
5470	{
5471	/* We have a number, we hope. */
5472	if (tkn[0] == matchId)
5473	{
5474	/* If the token is a matchchar, then things are simple. */
5475	if (taxonCount == 1)
5476	{
5477	MrBayesPrint ("%s Matching characters cannot be in first taxon\n", spacer);
5478	goto errorExit;
5479	}
5480	charCode = matrix[pos(0,taxaInfo[taxonCount-1].charCount,numChar)];
5481	matrix[pos(taxonCount-1,taxaInfo[taxonCount-1].charCount,numChar)] = charCode;
5482	}
5483	else
5484	{
5485	/* Otherwise, we have a number. Check that it is a valid number first... */
5486	if (!IsIn(tkn[0],"0123456789."))
5487	{
5488	MrBayesPrint ("%s Expecting a number for the continuous character\n", spacer);
5489	goto errorExit;
5490	}
5491	/* ... and then put the character into the matrix. Note that matrix
5492	is defined as an integer, but we may have floating precision continuous
5493	characters. To get around this, we multiply the value of the character
5494	by 1000 before putting it into matrix. We will divide by 1000 later on
5495	when/if we use the characters. */
5496	sscanf (tkn, "%lf", &charValue);
5497	charValue *= 1000.0;
5498	if (isNegative == YES)
5499	{
5500	charValue *= -1.0;
5501	isNegative = NO;
5502	}
5503	/MrBayesPrint ("%d \n", (int)charValue);/
5504	matrix[pos(taxonCount-1,taxaInfo[taxonCount-1].charCount++,numChar)] = (int)charValue;
5505	}
5506	}
5507	}
5508	else
5509	{
5510	/* Otherwise, we are dealing with a run-of-the-mill character, and we
5511	cannot expect the entire token to contain only a single character. We
5512	must, therefore, go through the token character-by-character. */
5513	i = 0;
5514	while (tkn[i] != '\0')
5515	{
5516	/MrBayesPrint ("%c", tkn[i]);/
5517	if (tkn[i] == matchId)
5518	{
5519	if (taxonCount == 1)
5520	{
5521	MrBayesPrint ("%s Matching characters cannot be in first taxon\n", spacer);
5522	goto errorExit;
5523	}
5524	charCode = matrix[pos(0,taxaInfo[taxonCount-1].charCount,numChar)];
5525	matrix[pos(taxonCount-1,taxaInfo[taxonCount-1].charCount++,numChar)] = charCode;
5526	}
5527	else
5528	{
5529	if ((tkn[i] == ')' && isInAmbig == YES) \|\| (tkn[i] == '}' && isInPoly == YES))
5530	{
5531	isInAmbig = isInPoly = NO;
5532	charCode = theAmbigChar;
5533	j = CharacterNumber (charCode, charInfo[taxaInfo[taxonCount-1].charCount].charType);
5534	if (j > charInfo[taxaInfo[taxonCount-1].charCount].numStates)
5535	charInfo[taxaInfo[taxonCount-1].charCount].numStates = j;
5536	matrix[pos(taxonCount-1,taxaInfo[taxonCount-1].charCount++,numChar)] = charCode;
5537	theAmbigChar = 0;
5538	}
5539	else if ((tkn[i] == '(' && isInAmbig == YES) \|\| (tkn[i] == '{' && isInPoly == YES))
5540	{
5541	if (isInAmbig == YES)
5542	MrBayesPrint ("%s Found an inappropriate \"(\"\n", spacer);
5543	else
5544	MrBayesPrint ("%s Found an inappropriate \"{\"\n", spacer);
5545	goto errorExit;
5546	}
5547	else if (isInAmbig == YES \|\| isInPoly == YES)
5548	{
5549	if (tkn[i] == ',')
5550	expecting \|= Expecting (COMMA);
5551	else
5552	{
5553	if (CharacterCode(tkn[i], &charCode, charInfo[taxaInfo[taxonCount-1].charCount].charType) == ERROR)
5554	goto errorExit;
5555	if (charCode == MISSING \|\| charCode == GAP)
5556	goto errorExit;
5557	theAmbigChar \|= charCode;
5558	expecting ^= Expecting (COMMA);
5559	}
5560	}
5561	else if (tkn[i] == '{' && isInPoly == NO && isInAmbig == NO)
5562	{
5563	isInPoly = YES;
5564	matrixHasPoly = YES;
5565	theAmbigChar = 0;
5566	}
5567	else if (tkn[i] == '(' && isInPoly == NO && isInAmbig == NO)
5568	{
5569	isInAmbig = YES;
5570	theAmbigChar = 0;
5571	}
5572	else if (tkn[i] == '(' && isInPoly == NO && isInAmbig == NO)
5573	{
5574	isInAmbig = YES;
5575	theAmbigChar = 0;
5576	}
5577	else
5578	{
5579	if (CharacterCode(tkn[i], &charCode, charInfo[taxaInfo[taxonCount-1].charCount].charType) == ERROR)
5580	{
5581	MrBayesPrint ("%s Error while reading character position %d (charCode %d)\n", spacer, taxaInfo[taxonCount-1].charCount+1, charCode);
5582	goto errorExit;
5583	}
5584	if (charCode != MISSING && charCode != GAP)
5585	{
5586	j = CharacterNumber (charCode, charInfo[taxaInfo[taxonCount-1].charCount].charType);
5587	if (j > charInfo[taxaInfo[taxonCount-1].charCount].numStates)
5588	charInfo[taxaInfo[taxonCount-1].charCount].numStates = j;
5589	}
5590	matrix[pos(taxonCount-1,taxaInfo[taxonCount-1].charCount++,numChar)] = charCode;
5591	}
5592	}
5593	i++;
5594	}
5595	}
5596	}
5597
5598	return (NO_ERROR);
5599	MrBayesPrint ("%s", parmName); /* just because I am tired of seeing the unused parameter error msg */
5600	errorExit:
5601	numTaxa=taxonCount;
5602	FreeMatrix();
5603	return (ERROR);
5604
5605	}
5606
5607
5608
5609
5610
5611	int DoNexusParm (char parmName, char tkn)
5612
5613	{
5614
5615	if (!strcmp(parmName, "NEXUS"))
5616	{
5617	MrBayesPrint ("%s Expecting NEXUS formatted file\n", spacer);
5618	expecting = Expecting(COMMAND);
5619	}
5620	else
5621	{
5622	MrBayesPrint ("%s Found %s\n", spacer, tkn);
5623	return (ERROR);
5624	}
5625
5626	return (NO_ERROR);
5627
5628	}
5629
5630
5631
5632
5633
5634	int DoOutgroup (void)
5635
5636	{
5637
5638	MrBayesPrint ("%s Setting outgroup to taxon \"%s\"\n", spacer, taxaNames[outGroupNum]);
5639
5640	return (NO_ERROR);
5641
5642	}
5643
5644
5645
5646
5647
5648	int DoOutgroupParm (char parmName, char tkn)
5649
5650
5651	{
5652
5653	int index, tempInt;
5654
5655	if (expecting == Expecting(ALPHA))
5656	{
5657	if (CheckString (taxaNames, numTaxa, tkn, &index) == ERROR)
5658	{
5659	MrBayesPrint ("%s Could not find taxon %s in list of taxa\n", spacer, tkn);
5660	return (ERROR);
5661	}
5662	outGroupNum = index;
5663
5664	expecting = Expecting(SEMICOLON);
5665	}
5666	else if (expecting == Expecting(NUMBER))
5667	{
5668	if (CheckString (taxaNames, numTaxa, tkn, &index) == ERROR)
5669	{
5670	/* OK, as we expect, the taxon is not a digit. So, now we assume that
5671	the user is assigning the outgroup by its number */
5672	sscanf (tkn, "%d", &tempInt);
5673	if (tempInt < 1 \|\| tempInt > numTaxa)
5674	{
5675	MrBayesPrint ("%s Taxon number %d is out of range\n", spacer, tempInt);
5676	return (ERROR);
5677	}
5678	outGroupNum = tempInt - 1;
5679	}
5680	else
5681	{
5682	outGroupNum = index;
5683	}
5684
5685	expecting = Expecting(SEMICOLON);
5686	}
5687	else
5688	return (ERROR);
5689
5690	return (NO_ERROR);
5691	MrBayesPrint ("%s", parmName); /* just because I am tired of seeing the unused parameter error msg */
5692
5693	}
5694
5695
5696
5697
5698
5699	int DoPairs (void)
5700
5701	{
5702
5703	MrBayesPrint ("\n");
5704	MrBayesPrint ("%s Successfully defined character pairings\n", spacer);
5705
5706	defPairs = YES;
5707	foundFirst = NO;
5708
5709	return (NO_ERROR);
5710
5711	}
5712
5713
5714
5715
5716
5717	int DoPairsParm (char parmName, char tkn)
5718
5719	{
5720
5721	int i, tempInt;
5722
5723	if (defMatrix == NO)
5724	{
5725	MrBayesPrint ("%s A matrix must be specified before you can define pairs of characters\n", spacer);
5726	return (ERROR);
5727	}
5728
5729	if (defPairs == YES)
5730	{
5731	MrBayesPrint ("%s Character pairs have been previously defined \n", spacer);
5732	MrBayesPrint ("%s Now overwriting old pairings\n", spacer);
5733	for (i=0; i<numChar; i++)
5734	charInfo[i].pairsId = 0;
5735	defPairs = NO;
5736	}
5737
5738	if (foundFirst == NO)
5739	{
5740	/* this is the first time in */
5741	pairId = 1;
5742	firstPair = YES;
5743	foundFirst = YES;
5744	MrBayesPrint ("%s Defining character pairings:\n\n", spacer);
5745	MrBayesPrint ("%s Pair -- First Second \n", spacer);
5746	}
5747
5748	if (expecting == Expecting(NUMBER))
5749	{
5750	sscanf (tkn, "%d", &tempInt);
5751	if (tempInt <= 0 \|\| tempInt > numChar)
5752	{
5753	MrBayesPrint ("\n");
5754	MrBayesPrint ("%s Character number %d is out of range (should be between %d and %d)\n", spacer, tempInt, 1, numChar);
5755	for (i=0; i<numChar; i++)
5756	charInfo[i].pairsId = 0;
5757	return (ERROR);
5758	}
5759	tempInt--;
5760
5761	if (charInfo[tempInt].pairsId != 0)
5762	{
5763	MrBayesPrint ("\n");
5764	MrBayesPrint ("%s Character number %d has already been included in a pairing\n", spacer, tempInt+1);
5765	for (i=0; i<numChar; i++)
5766	charInfo[i].pairsId = 0;
5767	return (ERROR);
5768	}
5769	if (charInfo[tempInt].charType != DNA && charInfo[tempInt].charType != RNA)
5770	{
5771	MrBayesPrint ("\n");
5772	MrBayesPrint ("%s Pairings may only include nucleotide data\n", spacer);
5773	if (charInfo[tempInt].charType == PROTEIN)
5774	MrBayesPrint ("%s Character %d is an amino acid character\n", spacer, tempInt+1);
5775	else if (charInfo[tempInt].charType == RESTRICTION)
5776	MrBayesPrint ("%s Character %d is a restriction site character\n", spacer, tempInt+1);
5777	else if (charInfo[tempInt].charType == STANDARD)
5778	MrBayesPrint ("%s Character %d is a \"standard\" character\n", spacer, tempInt+1);
5779	else if (charInfo[tempInt].charType == CONTINUOUS)
5780	MrBayesPrint ("%s Character %d is a continuously varying character\n", spacer, tempInt+1);
5781	for (i=0; i<numChar; i++)
5782	charInfo[i].pairsId = 0;
5783	return (ERROR);
5784	}
5785
5786	charInfo[tempInt].pairsId = pairId;
5787
5788	if (firstPair == YES)
5789	{
5790	MrBayesPrint ("%s %4d -- %5d ", spacer, pairId, tempInt+1);
5791	expecting = Expecting(COLON);
5792	firstPair = NO;
5793	}
5794	else
5795	{
5796	MrBayesPrint ("%5d\n", tempInt+1);
5797	expecting = (Expecting(COMMA) \| Expecting(SEMICOLON));
5798	firstPair = YES;
5799	}
5800	}
5801	else if (expecting == Expecting(COMMA))
5802	{
5803	pairId++;
5804	expecting = Expecting(NUMBER);
5805	}
5806	else if (expecting == Expecting(COLON))
5807	{
5808	expecting = Expecting(NUMBER);
5809	}
5810	else
5811	{
5812	for (i=0; i<numChar; i++)
5813	charInfo[i].pairsId = 0;
5814	return (ERROR);
5815	}
5816
5817	return (NO_ERROR);
5818	MrBayesPrint ("%s", parmName); /* just because I am tired of seeing the unused parameter error msg */
5819
5820	}
5821
5822
5823
5824
5825
5826	int DoPartition (void)
5827
5828	{
5829
5830	int i, *partTypes;
5831
5832	/* add set to tempSet */
5833	if (fromI >= 0)
5834	if (AddToSet (fromI, toJ, everyK, whichPartition+1) == ERROR)
5835	return (ERROR);
5836
5837	/* check that all characters are included */
5838	for (i=0; i<numChar; i++)
5839	{
5840	if (tempSet[i] == 0)
5841	{
5842	MrBayesPrint ("%s Character %d not included in partition\n", spacer, i+1);
5843	return (ERROR);
5844	}
5845	/MrBayesPrint ("%4d %4d \n", i, tempSet[i]);/
5846	}
5847
5848
5849	/* check how many partitions were found against how many were expected */
5850	if (whichPartition != numDivisions - 1)
5851	{
5852	MrBayesPrint ("%s Did not find correct number of partitions (expecting %d, found %d)\n", spacer, numDivisions, whichPartition + 1);
5853	return (ERROR);
5854	}
5855
5856	partTypes = (int *) SafeCalloc (numDivisions, sizeof(int));
5857	if (!partTypes)
5858	return ERROR;
5859
5860	/* make certain that the partition labels go from 1 - numDivisions, inclusive */
5861	for (i=0; i<numChar; i++)
5862	partTypes[tempSet[i] - 1] = -1; //partTypes is temporary used here not as an indicator of partition type
5863	for (i=0; i<numDivisions; i++)
5864	{
5865	if (partTypes[i] == 0)
5866	{
5867	MrBayesPrint ("%s Could not find a single character for division %d\n", spacer, i+1);
5868	return (ERROR);
5869	}
5870	}
5871
5872	/* check if partition overruns data types */
5873	/* partTypes[i] = -1 is already set in previouse loop
5874	for (i=0; i<numDivisions; i++)
5875	partTypes[i] = -1;
5876	*/
5877	for (i=0; i<numChar; i++)
5878	{
5879	if (partTypes[ tempSet[i]-1 ] == -1)
5880	partTypes[ tempSet[i]-1 ] = charInfo[i].charType;
5881	else
5882	{
5883	if (partTypes[ tempSet[i]-1 ] != charInfo[i].charType)
5884	{
5885	MrBayesPrint ("%s There are two different data types for partition division %d\n", spacer, tempSet[i]);
5886	free (partTypes);
5887	return (ERROR);
5888	}
5889	}
5890	}
5891	free (partTypes);
5892
5893	/* add name to list of valid partitions */
5894	if (AddString (&partitionNames, numDefinedPartitions, tempSetName) == ERROR)
5895	{
5896	MrBayesPrint ("%s Problem adding partition %s to list\n", spacer, tempSetName);
5897	return (ERROR);
5898	}
5899
5900	/* add new partition */
5901	for (i=0; i<numChar; i++) {
5902	partitionId[i] = (int ) SafeRealloc ((void )(partitionId[i]), (size_t)((numDefinedPartitions + 1) * sizeof(int)));
5903	if (!partitionId[i])
5904	return ERROR;
5905	}
5906
5907	/* set new partition */
5908	for (i=0; i<numChar; i++)
5909	partitionId[i][numDefinedPartitions] = tempSet[i];
5910
5911	/* increment number of defined partitions */
5912	numDefinedPartitions++;
5913
5914	return (NO_ERROR);
5915
5916	}
5917
5918
5919
5920
5921
5922	int DoPartitionParm (char parmName, char tkn)
5923
5924	{
5925
5926	int i, index, tempInt;
5927
5928	if (defMatrix == NO)
5929	{
5930	MrBayesPrint ("%s A matrix must be specified before partitions can be defined\n", spacer);
5931	return (ERROR);
5932	}
5933
5934	if (expecting == Expecting(PARAMETER))
5935	{
5936	/* set Partition ( ) ******************************************************************/
5937	if (!strcmp(parmName, "Xxxxxxxxxx"))
5938	{
5939	/* check size of partition name */
5940	if (strlen(tkn) > 99)
5941	{
5942	MrBayesPrint ("%s Partition name is too long. Max 100 characters\n", spacer);
5943	return (ERROR);
5944	}
5945
5946	/* check to see if the name has already been used as a partition */
5947	if (numDefinedPartitions > 1)
5948	{
5949	if (CheckString (partitionNames, numDefinedPartitions, tkn, &index) == ERROR)
5950	{
5951	/* if the partition name has not been used, then we should have an ERROR returned */
5952	/* we _want_ to be here */
5953
5954	}
5955	else
5956	{
5957	MrBayesPrint ("%s Partition name '%s' has been used previously\n", spacer, tkn);
5958	return (ERROR);
5959	}
5960	}
5961
5962	/* add the name temporarily to tempSetName */
5963	strcpy (tempSetName, tkn);
5964
5965	/* clear tempSet */
5966	for (i=0; i<numChar; i++)
5967	tempSet[i] = 0;
5968
5969	fromI = toJ = everyK = -1;
5970	foundDash = foundSlash = NO;
5971	whichPartition = 0;
5972	foundFirst = NO;
5973	numDivisions = 0;
5974	MrBayesPrint ("%s Defining partition called %s\n", spacer, tkn);
5975	expecting = Expecting(EQUALSIGN);
5976	}
5977	else
5978	return (ERROR);
5979	}
5980	else if (expecting == Expecting(EQUALSIGN))
5981	{
5982	expecting = Expecting(NUMBER);
5983	}
5984	else if (expecting == Expecting(ALPHA))
5985	{
5986	/* We are defining a partition in terms of a character set (called tkn, here). We should be able
5987	to find tkn in the list of character set names. If we cannot, then we have a problem and
5988	return an error. */
5989	if (numCharSets < 1)
5990	{
5991	MrBayesPrint ("%s Could not find a character set called %s\n", spacer, tkn);
5992	return (ERROR);
5993	}
5994	if (CheckString (charSetNames, numCharSets, tkn, &index) == ERROR)
5995	{
5996	MrBayesPrint ("%s Could not find a character set called %s\n", spacer, tkn);
5997	return (ERROR);
5998	}
5999	/* add characters from charset tkn to new tempSet */
6000	for (i=0; i<numChar; i++)
6001	{
6002	if (IsBitSet (i, charSet[index]) == YES)
6003	tempSet[i] = whichPartition + 1;
6004	}
6005	fromI = toJ = everyK = -1;
6006
6007	expecting = Expecting(ALPHA);
6008	expecting \|= Expecting(NUMBER);
6009	expecting \|= Expecting(SEMICOLON);
6010	expecting \|= Expecting(COMMA);
6011	}
6012	else if (expecting == Expecting(NUMBER))
6013	{
6014	if (foundFirst == NO)
6015	{
6016	sscanf (tkn, "%d", &tempInt);
6017	numDivisions = tempInt;
6018	expecting = Expecting(COLON);
6019	foundFirst = YES;
6020	}
6021	else
6022	{
6023	if (strlen(tkn) == 1 && tkn[0] == '.')
6024	tempInt = numChar;
6025	else
6026	sscanf (tkn, "%d", &tempInt);
6027	if (tempInt <= 0 \|\| tempInt > numChar)
6028	{
6029	MrBayesPrint ("%s Character number %d is out of range (should be between %d and %d)\n", spacer, tempInt, 1, numChar);
6030	return (ERROR);
6031	}
6032	tempInt--;
6033	if (foundDash == YES)
6034	{
6035	if (fromI >= 0)
6036	toJ = tempInt;
6037	else
6038	{
6039	MrBayesPrint ("%s Improperly formatted partition\n", spacer);
6040	return (ERROR);
6041	}
6042	foundDash = NO;
6043	}
6044	else if (foundSlash == YES)
6045	{
6046	tempInt++;
6047	if (tempInt <= 1)
6048	{
6049	MrBayesPrint ("%s Improperly formatted charset\n", spacer);
6050	return (ERROR);
6051	}
6052	if (fromI >= 0 && toJ >= 0 && fromI < toJ)
6053	everyK = tempInt;
6054	else
6055	{
6056	MrBayesPrint ("%s Improperly formatted charset\n", spacer);
6057	return (ERROR);
6058	}
6059	foundSlash = NO;
6060	}
6061	else
6062	{
6063	if (fromI >= 0 && toJ < 0)
6064	{
6065	if (AddToSet (fromI, toJ, everyK, whichPartition+1) == ERROR)
6066	return (ERROR);
6067	fromI = tempInt;
6068	}
6069	else if (fromI < 0 && toJ < 0)
6070	{
6071	fromI = tempInt;
6072	}
6073	else if (fromI >= 0 && toJ >= 0 && everyK < 0)
6074	{
6075	if (AddToSet (fromI, toJ, everyK, whichPartition+1) == ERROR)
6076	return (ERROR);
6077	fromI = tempInt;
6078	toJ = everyK = -1;
6079	}
6080	else if (fromI >= 0 && toJ >= 0 && everyK >= 0)
6081	{
6082	if (AddToSet (fromI, toJ, everyK, whichPartition+1) == ERROR)
6083	return (ERROR);
6084	fromI = tempInt;
6085	toJ = everyK = -1;
6086	}
6087	else
6088	{
6089	MrBayesPrint ("%s Improperly formatted charset\n", spacer);
6090	{
6091	return (ERROR);
6092	}
6093	}
6094	}
6095
6096	expecting = Expecting(ALPHA);
6097	expecting \|= Expecting(NUMBER);
6098	expecting \|= Expecting(SEMICOLON);
6099	expecting \|= Expecting(DASH);
6100	expecting \|= Expecting(BACKSLASH);
6101	expecting \|= Expecting(COMMA);
6102	}
6103	}
6104	else if (expecting == Expecting(COMMA))
6105	{
6106	/* add set to tempSet */
6107	if (fromI >= 0)
6108	if (AddToSet (fromI, toJ, everyK, whichPartition+1) == ERROR)
6109	return (ERROR);
6110
6111	fromI = toJ = everyK = -1;
6112	foundDash = foundSlash = NO;
6113	whichPartition++;
6114	if (whichPartition > numDivisions)
6115	{
6116	MrBayesPrint ("%s Too many partitions of the data (expecting %d)\n", spacer, numDivisions);
6117	return (ERROR);
6118	}
6119	expecting = Expecting(NUMBER);
6120	expecting \|= Expecting(ALPHA);
6121	}
6122	else if (expecting == Expecting(COLON))
6123	{
6124	expecting = Expecting(NUMBER);
6125	expecting \|= Expecting(ALPHA);
6126	}
6127	else if (expecting == Expecting(DASH))
6128	{
6129	foundDash = YES;
6130	expecting = Expecting(NUMBER);
6131	}
6132	else if (expecting == Expecting(BACKSLASH))
6133	{
6134	foundSlash = YES;
6135	expecting = Expecting(NUMBER);
6136	}
6137	else
6138	return (ERROR);
6139
6140	return (NO_ERROR);
6141
6142	}
6143
6144
6145	int DoRestore (void)
6146
6147	{
6148
6149	int i, alreadyDone;
6150
6151	MrBayesPrint ("%s Restore taxa\n", spacer);
6152
6153	/* add set to tempSet */
6154	if (fromI >= 0 && toJ < 0)
6155	{
6156	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
6157	return (ERROR);
6158	}
6159	else if (fromI >= 0 && toJ >= 0 && everyK < 0)
6160	{
6161	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
6162	return (ERROR);
6163	}
6164	else if (fromI >= 0 && toJ >= 0 && everyK >= 0)
6165	{
6166	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
6167	return (ERROR);
6168	}
6169
6170	/* merge tempSet with excludedTaxa */
6171	alreadyDone = NO;
6172	for (i=0; i<numTaxa; i++)
6173	{
6174	if (tempSet[i] == 1)
6175	{
6176	if (taxaInfo[i].isDeleted == NO && alreadyDone == NO)
6177	{
6178	MrBayesPrint ("%s Some taxa already included\n", spacer);
6179	alreadyDone = YES;
6180	}
6181	taxaInfo[i].isDeleted = NO;
6182	}
6183	}
6184
6185	SetLocalTaxa();
6186
6187	/* show tempSet (for debugging) */
6188	# if 0
6189	for (i=0; i<numTaxa; i++)
6190	MrBayesPrint ("%4d %4d\n", i+1, tempSet[i]);
6191	# endif
6192
6193	return (NO_ERROR);
6194
6195	}
6196
6197
6198
6199
6200
6201	int DoRestoreParm (char parmName, char tkn)
6202
6203	{
6204
6205	int i, index, tempInt;
6206
6207	if (defMatrix == NO)
6208	{
6209	MrBayesPrint ("%s A matrix must be specified before you can restore taxa\n", spacer);
6210	return (ERROR);
6211	}
6212
6213	if (foundFirst == NO)
6214	{
6215	/* this is the first time in */
6216	fromI = toJ = everyK = -1;
6217	foundDash = NO;
6218	for (i=0; i<numTaxa; i++) /* clear tempSet */
6219	tempSet[i] = 0;
6220	foundFirst = YES;
6221	}
6222
6223	if (expecting == Expecting(ALPHA))
6224	{
6225	if (IsSame ("All", tkn) == SAME \|\| IsSame ("All", tkn) == CONSISTENT_WITH)
6226	{
6227	for (i=0; i<numTaxa; i++)
6228	tempSet[i] = 1;
6229	}
6230	else
6231	{
6232	if (CheckString (taxaNames, numTaxa, tkn, &index) == ERROR)
6233	{
6234	/* we are using a pre-defined taxa set */
6235	if (numTaxaSets < 1)
6236	{
6237	MrBayesPrint ("%s Could not find a taxset called %s\n", spacer, tkn);
6238	return (ERROR);
6239	}
6240	if (CheckString (taxaSetNames, numTaxaSets, tkn, &index) == ERROR)
6241	{
6242	MrBayesPrint ("%s Could not find a taxset called %s\n", spacer, tkn);
6243	return (ERROR);
6244	}
6245	/* add taxa from taxset tkn to new tempSet */
6246	for (i=0; i<numTaxa; i++)
6247	{
6248	if (IsBitSet (i, taxaSet[index]) == YES)
6249	tempSet[i] = 1;
6250	}
6251	}
6252	else
6253	{
6254	/* we found the taxon name */
6255	if (fromI >= 0 && toJ < 0)
6256	{
6257	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
6258	return (ERROR);
6259	}
6260	else if (fromI >= 0 && toJ >= 0)
6261	{
6262	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
6263	return (ERROR);
6264	}
6265	tempSet[index] = 1;
6266	}
6267	fromI = toJ = everyK = -1;
6268	}
6269
6270	expecting = Expecting(ALPHA);
6271	expecting \|= Expecting(NUMBER);
6272	expecting \|= Expecting(SEMICOLON);
6273	}
6274	else if (expecting == Expecting(NUMBER))
6275	{
6276	if (strlen(tkn) == 1 && !strcmp(tkn, "."))
6277	{
6278	tempInt = numTaxa;
6279	}
6280	else
6281	{
6282	sscanf (tkn, "%d", &tempInt);
6283	if (tempInt <= 0 \|\| tempInt > numTaxa)
6284	{
6285	MrBayesPrint ("%s Taxon number %d is out of range (should be between %d and %d)\n", spacer, tempInt, 1, numTaxa);
6286	return (ERROR);
6287	}
6288	}
6289	tempInt--;
6290	if (foundDash == YES)
6291	{
6292	if (fromI >= 0)
6293	toJ = tempInt;
6294	else
6295	{
6296	MrBayesPrint ("%s Improperly formatted restore set\n", spacer);
6297	return (ERROR);
6298	}
6299	foundDash = NO;
6300	}
6301	else
6302	{
6303	if (fromI >= 0 && toJ < 0)
6304	{
6305	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
6306	return (ERROR);
6307	fromI = tempInt;
6308	}
6309	else if (fromI < 0 && toJ < 0)
6310	{
6311	fromI = tempInt;
6312	}
6313	else if (fromI >= 0 && toJ >= 0 && everyK < 0)
6314	{
6315	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
6316	return (ERROR);
6317	fromI = tempInt;
6318	toJ = everyK = -1;
6319	}
6320	else if (fromI >= 0 && toJ >= 0 && everyK >= 0)
6321	{
6322	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
6323	return (ERROR);
6324	fromI = tempInt;
6325	toJ = everyK = -1;
6326	}
6327	else
6328	{
6329	MrBayesPrint ("%s Improperly formatted restore set\n", spacer);
6330	{
6331	return (ERROR);
6332	}
6333	}
6334	}
6335	expecting = Expecting(ALPHA);
6336	expecting \|= Expecting(NUMBER);
6337	expecting \|= Expecting(SEMICOLON);
6338	expecting \|= Expecting(DASH);
6339	}
6340	else if (expecting == Expecting(DASH))
6341	{
6342	foundDash = YES;
6343	expecting = Expecting(NUMBER);
6344	}
6345	else
6346	return (ERROR);
6347
6348	return (NO_ERROR);
6349	MrBayesPrint ("%s", parmName); /* just because I am tired of seeing the unused parameter error msg */
6350
6351	}
6352
6353
6354
6355
6356
6357	int DoSet (void)
6358
6359	{
6360
6361	return (NO_ERROR);
6362
6363	}
6364
6365
6366
6367
6368
6369	int DoSetParm (char parmName, char tkn)
6370
6371	{
6372
6373	int index;
6374	char tempStr[100];
6375	int tempI;
6376
6377	if (expecting == Expecting(PARAMETER))
6378	{
6379	expecting = Expecting(EQUALSIGN);
6380	}
6381	else
6382	{
6383	/* set Autoclose (autoClose) **********************************************************/
6384	if (!strcmp(parmName, "Autoclose"))
6385	{
6386	if (expecting == Expecting(EQUALSIGN))
6387	expecting = Expecting(ALPHA);
6388	else if (expecting == Expecting(ALPHA))
6389	{
6390	if (IsArgValid(tkn, tempStr) == NO_ERROR)
6391	{
6392	if (!strcmp(tempStr, "Yes"))
6393	autoClose = YES;
6394	else
6395	autoClose = NO;
6396	}
6397	else
6398	{
6399	MrBayesPrint ("%s Invalid argument for autoclose\n", spacer);
6400	return (ERROR);
6401	}
6402	if (autoClose == YES)
6403	MrBayesPrint ("%s Setting autoclose to yes\n", spacer);
6404	else
6405	MrBayesPrint ("%s Setting autoclose to no\n", spacer);
6406	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
6407	}
6408	else
6409	return (ERROR);
6410	}
6411	/* set Nowarnings (noWarn) **********************************************************/
6412	else if (!strcmp(parmName, "Nowarnings"))
6413	{
6414	if (expecting == Expecting(EQUALSIGN))
6415	expecting = Expecting(ALPHA);
6416	else if (expecting == Expecting(ALPHA))
6417	{
6418	if (IsArgValid(tkn, tempStr) == NO_ERROR)
6419	{
6420	if (!strcmp(tempStr, "Yes"))
6421	noWarn = YES;
6422	else
6423	noWarn = NO;
6424	}
6425	else
6426	{
6427	MrBayesPrint ("%s Invalid argument for nowarnings\n", spacer);
6428	return (ERROR);
6429	}
6430	if (noWarn == YES)
6431	MrBayesPrint ("%s Setting nowarnings to yes\n", spacer);
6432	else
6433	MrBayesPrint ("%s Setting nowarnings to no\n", spacer);
6434	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
6435	}
6436	else
6437	return (ERROR);
6438	}
6439	/* set Quitonerror (quitOnError) **************************************************/
6440	else if (!strcmp(parmName, "Quitonerror"))
6441	{
6442	if (expecting == Expecting(EQUALSIGN))
6443	expecting = Expecting(ALPHA);
6444	else if (expecting == Expecting(ALPHA))
6445	{
6446	if (IsArgValid(tkn, tempStr) == NO_ERROR)
6447	{
6448	if (!strcmp(tempStr, "Yes"))
6449	quitOnError = YES;
6450	else
6451	quitOnError = NO;
6452	}
6453	else
6454	{
6455	MrBayesPrint ("%s Invalid argument for quitonerror\n", spacer);
6456	return (ERROR);
6457	}
6458	if (quitOnError == YES)
6459	MrBayesPrint ("%s Setting quitonerror to yes\n", spacer);
6460	else
6461	MrBayesPrint ("%s Setting quitonerror to no\n", spacer);
6462	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
6463	}
6464	else
6465	return (ERROR);
6466	}
6467	/* set Autoreplace (autoOverwrite) **************************************************/
6468	else if (!strcmp(parmName, "Autoreplace"))
6469	{
6470	if (expecting == Expecting(EQUALSIGN))
6471	expecting = Expecting(ALPHA);
6472	else if (expecting == Expecting(ALPHA))
6473	{
6474	if (IsArgValid(tkn, tempStr) == NO_ERROR)
6475	{
6476	if (!strcmp(tempStr, "Yes"))
6477	{
6478	autoOverwrite = YES;
6479	MrBayesPrint ("%s Setting autoreplace to yes\n", spacer);
6480	}
6481	else
6482	{
6483	autoOverwrite = NO;
6484	MrBayesPrint ("%s Setting autoreplace to no\n", spacer);
6485	}
6486	}
6487	else
6488	{
6489	MrBayesPrint ("%s Invalid argument for autoreplace\n", spacer);
6490	return (ERROR);
6491	}
6492	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
6493	}
6494	else
6495	return (ERROR);
6496	}
6497	/* set Scientific (scientific) *********************************************/
6498	else if (!strcmp(parmName, "Scientific"))
6499	{
6500	if (expecting == Expecting(EQUALSIGN))
6501	expecting = Expecting(ALPHA);
6502	else if (expecting == Expecting(ALPHA))
6503	{
6504	if (IsArgValid(tkn, tempStr) == NO_ERROR)
6505	{
6506	if (!strcmp(tempStr, "Yes"))
6507	scientific = YES;
6508	else
6509	scientific = NO;
6510	}
6511	else
6512	{
6513	MrBayesPrint ("%s Invalid argument for Scientific\n", spacer);
6514	return (ERROR);
6515	}
6516	if ( scientific == YES)
6517	MrBayesPrint ("%s Setting Scientific to Yes\n", spacer);
6518	else
6519	MrBayesPrint ("%s Setting Scientific to No\n", spacer);
6520	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
6521	}
6522	else
6523	return (ERROR);
6524	}
6525	/* set Userlevel (userLevel) **********************************************************/
6526	else if (!strcmp(parmName, "Userlevel"))
6527	{
6528	if (expecting == Expecting(EQUALSIGN))
6529	expecting = Expecting(ALPHA);
6530	else if (expecting == Expecting(ALPHA))
6531	{
6532	if (IsArgValid(tkn, tempStr) == NO_ERROR)
6533	{
6534	if (!strcmp(tempStr, "Standard"))
6535	userLevel = STANDARD_USER;
6536	else if (!strcmp (tempStr,"Developer"))
6537	userLevel = DEVELOPER;
6538	}
6539	else
6540	{
6541	MrBayesPrint ("%s Invalid argument for userlevel\n", spacer);
6542	return (ERROR);
6543	}
6544	MrBayesPrint ("%s Setting userlevel to %s\n", spacer, tempStr);
6545	if (SetMoves() == ERROR)
6546	{
6547	MrBayesPrint ("%s Problem seting up the moves for this user level\n", spacer);
6548	return (ERROR);
6549	}
6550	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
6551	}
6552	else
6553	return (ERROR);
6554	}
6555	/* set Npthreads (number of pthreads) ****************************************************/
6556	else if (!strcmp(parmName, "Npthreads"))
6557	{
6558	if (expecting == Expecting(EQUALSIGN))
6559	expecting = Expecting(NUMBER);
6560	else if (expecting == Expecting(NUMBER))
6561	{
6562	sscanf (tkn, "%d", &tempI);
6563	nPThreads = tempI;
6564	MrBayesPrint ("%s Setting Npthreads to %ld\n", spacer, nPThreads);
6565	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
6566	}
6567	else
6568	return (ERROR);
6569	}
6570	/* set Precision (number of decimals) ****************************************************/
6571	else if (!strcmp(parmName, "Precision"))
6572	{
6573	if (expecting == Expecting(EQUALSIGN))
6574	expecting = Expecting(NUMBER);
6575	else if (expecting == Expecting(NUMBER))
6576	{
6577	sscanf (tkn, "%d", &tempI);
6578	if (tempI < 3 \|\| tempI > 15)
6579	{
6580	MrBayesPrint ("%s Precision must be in the range 3 to 15\n", spacer);
6581	return ERROR;
6582	}
6583	precision = tempI;
6584	MrBayesPrint ("%s Setting Precision to %d\n", spacer, precision);
6585	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
6586	}
6587	else
6588	return (ERROR);
6589	}
6590	/* set Partition (partitionNum) *******************************************************/
6591	else if (!strcmp(parmName, "Partition"))
6592	{
6593	if (defMatrix == NO)
6594	{
6595	MrBayesPrint ("%s A character matrix must be defined first\n", spacer);
6596	return (ERROR);
6597	}
6598	if (expecting == Expecting(EQUALSIGN))
6599	expecting = Expecting(ALPHA) \| Expecting(NUMBER);
6600	else if (expecting == Expecting(ALPHA))
6601	{
6602	/* first check to see if name is there */
6603	if (CheckString (partitionNames, numDefinedPartitions, tkn, &index) == ERROR)
6604	{
6605	MrBayesPrint ("%s Could not find \"%s\" as a defined partition\n", spacer, tkn);
6606	return (ERROR);
6607	}
6608	if (SetPartition (index) == ERROR)
6609	return ERROR;
6610	if (numCurrentDivisions == 1)
6611	MrBayesPrint ("%s Setting %s as the partition (does not divide up characters).\n", spacer, tkn);
6612	else
6613	MrBayesPrint ("%s Setting %s as the partition, dividing characters into %d parts.\n", spacer, tkn, numCurrentDivisions);
6614	if (SetModelDefaults () == ERROR)
6615	return (ERROR);
6616	if (SetUpAnalysis (&globalSeed) == ERROR)
6617	return (ERROR);
6618	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
6619	}
6620	else if (expecting == Expecting(NUMBER))
6621	{
6622	sscanf (tkn, "%d", &index);
6623	if (index > numDefinedPartitions)
6624	{
6625	MrBayesPrint ("%s Partition number %d is not a valid partition. Only %d partitions\n", spacer, index, numDefinedPartitions);
6626	MrBayesPrint ("%s have been defined.\n", spacer);
6627	return (ERROR);
6628	}
6629	if (index < 1)
6630	{
6631	MrBayesPrint ("%s Partition number %d is not a valid partition. Must be between 1 and %d.\n", spacer, index+1, numDefinedPartitions);
6632	return (ERROR);
6633	}
6634	if (SetPartition (index) == ERROR)
6635	return ERROR;
6636	if (numCurrentDivisions == 1)
6637	MrBayesPrint ("%s Setting %s as the partition (does not divide up characters).\n", spacer, partitionNames[index]);
6638	else
6639	MrBayesPrint ("%s Setting %s as the partition, dividing characters into %d parts.\n", spacer, partitionNames[index], numCurrentDivisions);
6640	if (SetModelDefaults () == ERROR)
6641	return (ERROR);
6642	if (SetUpAnalysis (&globalSeed) == ERROR)
6643	return (ERROR);
6644	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
6645	}
6646	else
6647	return (ERROR);
6648	}
6649	/* set Speciespartition (speciespartitionNum) *******************************************************/
6650	else if (!strcmp(parmName, "Speciespartition"))
6651	{
6652	if (defTaxa == NO)
6653	{
6654	MrBayesPrint ("%s A taxaset must be defined first\n", spacer);
6655	return (ERROR);
6656	}
6657	if (expecting == Expecting(EQUALSIGN))
6658	expecting = Expecting(ALPHA) \| Expecting(NUMBER);
6659	else if (expecting == Expecting(ALPHA))
6660	{
6661	/* first check to see if name is there */
6662	if (CheckString (speciespartitionNames, numDefinedSpeciespartitions, tkn, &index) == ERROR)
6663	{
6664	MrBayesPrint ("%s Could not find \"%s\" as a defined speciespartition\n", spacer, tkn);
6665	return (ERROR);
6666	}
6667	if (SetSpeciespartition (index) == ERROR)
6668	return ERROR;
6669	MrBayesPrint ("%s Setting %s as the speciespartition, dividing taxa into %d species.\n", spacer, tkn, numSpecies);
6670	if (SetModelDefaults () == ERROR)
6671	return (ERROR);
6672	if (SetUpAnalysis (&globalSeed) == ERROR)
6673	return (ERROR);
6674	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
6675	}
6676	else if (expecting == Expecting(NUMBER))
6677	{
6678	sscanf (tkn, "%d", &index);
6679	if (index > numDefinedSpeciespartitions)
6680	{
6681	MrBayesPrint ("%s Speciespartition number %d is not valid. Only %d speciespartitions\n", spacer, index, numDefinedSpeciespartitions);
6682	MrBayesPrint ("%s have been defined.\n", spacer);
6683	return (ERROR);
6684	}
6685	if (index < 1)
6686	{
6687	MrBayesPrint ("%s Speciespartition number %d is not valid. Must be between 1 and %d.\n", spacer, index, numDefinedSpeciespartitions);
6688	return (ERROR);
6689	}
6690	if (SetSpeciespartition (index-1) == ERROR)
6691	return ERROR;
6692	MrBayesPrint ("%s Setting %s as the speciespartition, dividing taxa into %d species.\n", spacer, speciespartitionNames[index-1], numSpecies);
6693	if (SetModelDefaults () == ERROR)
6694	return (ERROR);
6695	if (SetUpAnalysis (&globalSeed) == ERROR)
6696	return (ERROR);
6697	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
6698	}
6699	else
6700	return (ERROR);
6701	}
6702	/* set Seed (global variable globalSeed) ****************************************************/
6703	else if (!strcmp(parmName, "Seed"))
6704	{
6705	if (expecting == Expecting(EQUALSIGN))
6706	expecting = Expecting(NUMBER);
6707	else if (expecting == Expecting(NUMBER))
6708	{
6709	sscanf (tkn, "%d", &tempI);
6710	if( tempI == 0 \|\| tempI == 2147483647 )
6711	{
6712	MrBayesPrint ("%s Error: Seed can be any natural number except 0 and 2147483647\n", spacer);
6713	return (ERROR);
6714	}
6715	globalSeed = tempI;
6716	MrBayesPrint ("%s Setting seed to %ld\n", spacer, globalSeed);
6717	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
6718	}
6719	else
6720	return (ERROR);
6721	}
6722	/* set Swapseed (global variable swapSeed) ***************************************************************/
6723	else if (!strcmp(parmName, "Swapseed"))
6724	{
6725	if (expecting == Expecting(EQUALSIGN))
6726	expecting = Expecting(NUMBER);
6727	else if (expecting == Expecting(NUMBER))
6728	{
6729	sscanf (tkn, "%d", &tempI);
6730	if( tempI == 0 \|\| tempI == 2147483647 )
6731	{
6732	MrBayesPrint ("%s Error: Swapseed can be any natural number except 0 and 2147483647\n", spacer);
6733	return (ERROR);
6734	}
6735	swapSeed = tempI;
6736	MrBayesPrint ("%s Setting swapseed to %ld\n", spacer, swapSeed);
6737	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
6738	}
6739	else
6740	return (ERROR);
6741	}
6742	/* set Dir (global variable workingDir) ***************************************************************/
6743	else if (!strcmp(parmName, "Dir"))
6744	{
6745	if (expecting == Expecting(EQUALSIGN))
6746	{
6747	expecting = Expecting(ALPHA);
6748	readWord = YES;
6749	}
6750	else if (expecting == Expecting(ALPHA))
6751	{
6752	if(strlen(tkn)>99)
6753	{
6754	MrBayesPrint ("%s Maximum allowed length of working directory name is 99 characters. The given name:\n", spacer);
6755	MrBayesPrint ("%s '%s'\n", spacer,tkn);
6756	MrBayesPrint ("%s has %d characters.\n", spacer,strlen(tkn));
6757	return (ERROR);
6758	}
6759	strcpy (workingDir, tkn);
6760	#if defined (WIN_VERSION)
6761	/* Reformat to Windows with trailing '\' */
6762	for (index=0; index<(int)strlen(workingDir); index++)
6763	{
6764	if (workingDir[index] == ':' \|\| workingDir[index] == '/')
6765	workingDir[index] = '\\';
6766	}
6767	if (strlen(workingDir) > 0 && workingDir[strlen(workingDir)-1] != '\\')
6768	strcat(workingDir,"\\");
6769	#else
6770	/* Reformat to Unix with trailing '/' */
6771	for (index=0; index<(int)strlen(workingDir); index++)
6772	{
6773	if (workingDir[index] == ':' \|\| workingDir[index] == '\\')
6774	workingDir[index] = '/';
6775	}
6776	if (strlen(workingDir) > 0 && workingDir[strlen(workingDir)-1] != '/')
6777	strcat(workingDir,"/");
6778	#endif
6779	MrBayesPrint ("%s Setting working directory to \"%s\"\n", spacer, workingDir);
6780	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
6781	}
6782	else
6783	return (ERROR);
6784	}
6785	/* set Usebeagle (global variable BEAGLE usage) ***************************************************************/
6786	else if (!strcmp(parmName, "Usebeagle"))
6787	{
6788	if (expecting == Expecting(EQUALSIGN))
6789	expecting = Expecting(ALPHA);
6790	else if (expecting == Expecting(ALPHA))
6791	{
6792	#if defined (BEAGLE_ENABLED)
6793	if (IsArgValid(tkn, tempStr) == NO_ERROR)
6794	{
6795	if (!strcmp(tempStr, "Yes"))
6796	tryToUseBEAGLE = YES;
6797	else
6798	tryToUseBEAGLE = NO;
6799	}
6800	else
6801	{
6802	MrBayesPrint ("%s Invalid argument for usebeagle\n", spacer);
6803	return (ERROR);
6804	}
6805	if (tryToUseBEAGLE == YES)
6806	MrBayesPrint ("%s Setting usebeagle to yes\n", spacer);
6807	else
6808	MrBayesPrint ("%s Setting usebeagle to no\n", spacer);
6809	#else
6810	BeagleNotLinked();
6811	#endif
6812	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
6813	}
6814	else
6815	return (ERROR);
6816	}
6817	/* set Beagle resources requirements (global variable BEAGLE flag) ****************************************/
6818	else if (!strcmp(parmName, "Beagledevice"))
6819	{
6820	if (expecting == Expecting(EQUALSIGN))
6821	expecting = Expecting(ALPHA);
6822	else if (expecting == Expecting(ALPHA))
6823	{
6824	#if defined (BEAGLE_ENABLED)
6825	if (IsArgValid(tkn, tempStr) == NO_ERROR)
6826	{
6827	long oldFlags = beagleFlags;
6828	if (!strcmp(tempStr, "Gpu"))
6829	{
6830	beagleFlags &= ~BEAGLE_FLAG_PROCESSOR_CPU;
6831	beagleFlags \|= BEAGLE_FLAG_PROCESSOR_GPU;
6832	BeagleAddGPUDevicesToList(&beagleResource, &beagleResourceCount);
6833	}
6834	else
6835	{
6836	beagleFlags &= ~BEAGLE_FLAG_PROCESSOR_GPU;
6837	beagleFlags \|= BEAGLE_FLAG_PROCESSOR_CPU;
6838	BeagleRemoveGPUDevicesFromList(&beagleResource, &beagleResourceCount);
6839	}
6840	if (BeagleCheckFlagCompatability(beagleFlags) == NO) {
6841	beagleFlags = oldFlags;
6842	} else {
6843	if (beagleFlags & BEAGLE_FLAG_PROCESSOR_GPU)
6844	MrBayesPrint ("%s Setting beagledevice to GPU\n", spacer);
6845	else
6846	MrBayesPrint ("%s Setting beagledevice to CPU\n", spacer);
6847	}
6848	}
6849	else
6850	{
6851	MrBayesPrint ("%s Invalid argument for beagledevice\n", spacer);
6852	return (ERROR);
6853	}
6854	#else
6855	BeagleNotLinked();
6856	#endif
6857	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
6858	}
6859	else
6860	return (ERROR);
6861	}
6862	else if (!strcmp(parmName, "Beagleprecision"))
6863	{
6864	if (expecting == Expecting(EQUALSIGN))
6865	expecting = Expecting(ALPHA);
6866	else if (expecting == Expecting(ALPHA))
6867	{
6868	#if defined (BEAGLE_ENABLED)
6869	if (IsArgValid(tkn, tempStr) == NO_ERROR)
6870	{
6871	long oldFlags = beagleFlags;
6872	if (!strcmp(tempStr, "Single"))
6873	{
6874	beagleFlags &= ~BEAGLE_FLAG_PRECISION_DOUBLE;
6875	beagleFlags \|= BEAGLE_FLAG_PRECISION_SINGLE;
6876	}
6877	else
6878	{
6879	beagleFlags &= ~BEAGLE_FLAG_PRECISION_SINGLE;
6880	beagleFlags \|= BEAGLE_FLAG_PRECISION_DOUBLE;
6881	}
6882	if (BeagleCheckFlagCompatability(beagleFlags) == NO) {
6883	beagleFlags = oldFlags;
6884	} else {
6885	if (beagleFlags & BEAGLE_FLAG_PRECISION_DOUBLE)
6886	MrBayesPrint ("%s Setting beagleprecision to double\n", spacer);
6887	else
6888	MrBayesPrint ("%s Setting beagleprecision to single\n", spacer);
6889	}
6890	}
6891	else
6892	{
6893	MrBayesPrint ("%s Invalid argument for beagleprecision\n", spacer);
6894	return (ERROR);
6895	}
6896	#else
6897	BeagleNotLinked();
6898	#endif
6899	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
6900	}
6901	else
6902	return (ERROR);
6903	}
6904	else if (!strcmp(parmName, "Beagleopenmp"))
6905	{
6906	if (expecting == Expecting(EQUALSIGN))
6907	expecting = Expecting(ALPHA);
6908	else if (expecting == Expecting(ALPHA))
6909	{
6910	#if defined (BEAGLE_ENABLED)
6911	if (IsArgValid(tkn, tempStr) == NO_ERROR)
6912	{
6913	long oldFlags = beagleFlags;
6914	if (!strcmp(tempStr, "Yes"))
6915	{
6916	beagleFlags \|= BEAGLE_FLAG_THREADING_OPENMP;
6917	}
6918	else
6919	{
6920	beagleFlags &= ~BEAGLE_FLAG_THREADING_OPENMP;
6921	}
6922	if (BeagleCheckFlagCompatability(beagleFlags) == NO) {
6923	beagleFlags = oldFlags;
6924	} else {
6925	if (beagleFlags & BEAGLE_FLAG_THREADING_OPENMP)
6926	MrBayesPrint ("%s Setting beagleopenmp to Yes\n", spacer);
6927	else
6928	MrBayesPrint ("%s Setting beagleopenmp to No\n", spacer);
6929	}
6930	}
6931	else
6932	{
6933	MrBayesPrint ("%s Invalid argument for beagleopenmp\n", spacer);
6934	return (ERROR);
6935	}
6936	#else
6937	BeagleNotLinked();
6938	#endif
6939	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
6940	}
6941	else
6942	return (ERROR);
6943	}
6944	else if (!strcmp(parmName, "Beaglefreq"))
6945	{
6946	if (expecting == Expecting(EQUALSIGN))
6947	expecting = Expecting(NUMBER);
6948	else if (expecting == Expecting(NUMBER))
6949	{
6950	#if defined (BEAGLE_ENABLED)
6951	sscanf (tkn, "%d", &tempI);
6952	if (tempI < 0)
6953	{
6954	MrBayesPrint ("%s Beaglefreq must be greater than 0\n", spacer);
6955	return ERROR;
6956	}
6957	beagleScalingFrequency= tempI;
6958	MrBayesPrint ("%s Setting Beaglefreq to %d\n", spacer, beagleScalingFrequency);
6959	#else
6960	BeagleNotLinked();
6961	#endif
6962	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
6963	}
6964	else
6965	return (ERROR);
6966	}
6967	else if (!strcmp(parmName, "Beaglesse"))
6968	{
6969	if (expecting == Expecting(EQUALSIGN))
6970	expecting = Expecting(ALPHA);
6971	else if (expecting == Expecting(ALPHA))
6972	{
6973	#if defined (BEAGLE_ENABLED)
6974	if (IsArgValid(tkn, tempStr) == NO_ERROR)
6975	{
6976	long oldFlags = beagleFlags;
6977	if (!strcmp(tempStr, "Yes"))
6978	{
6979	beagleFlags \|= BEAGLE_FLAG_VECTOR_SSE;
6980	}
6981	else
6982	{
6983	beagleFlags &= ~BEAGLE_FLAG_VECTOR_SSE;
6984	}
6985	if (BeagleCheckFlagCompatability(beagleFlags) == NO) {
6986	beagleFlags = oldFlags;
6987	} else {
6988	if (beagleFlags & BEAGLE_FLAG_VECTOR_SSE)
6989	MrBayesPrint ("%s Setting beaglesse to Yes\n", spacer);
6990	else
6991	MrBayesPrint ("%s Setting beaglesse to No\n", spacer);
6992	}
6993	}
6994	else
6995	{
6996	MrBayesPrint ("%s Invalid argument for beagleopenmp\n", spacer);
6997	return (ERROR);
6998	}
6999	#else
7000	BeagleNotLinked();
7001	#endif
7002	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
7003	}
7004	else
7005	return (ERROR);
7006	}
7007	else if (!strcmp(parmName, "Beaglethreads"))
7008	{
7009	if (expecting == Expecting(EQUALSIGN))
7010	expecting = Expecting(ALPHA);
7011	else if (expecting == Expecting(ALPHA))
7012	{
7013	#if defined (BEAGLE_ENABLED) && defined (THREADS_ENABLED)
7014	if (IsArgValid(tkn, tempStr) == NO_ERROR)
7015	{
7016	if (!strcmp(tempStr, "Yes"))
7017	{
7018	tryToUseThreads = YES;
7019	}
7020	else
7021	{
7022	tryToUseThreads = NO;
7023	}
7024
7025	if (tryToUseThreads == YES)
7026	MrBayesPrint ("%s Setting beaglethreads to Yes\n", spacer);
7027	else
7028	MrBayesPrint ("%s Setting beaglethreads to No\n", spacer);
7029	}
7030	else
7031	{
7032	MrBayesPrint ("%s Invalid argument for beaglethreads\n", spacer);
7033	return (ERROR);
7034	}
7035	#else
7036	BeagleThreadsNotLinked();
7037	#endif
7038	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
7039	}
7040	}
7041	else if (!strcmp(parmName, "Beaglescaling"))
7042	{
7043	if (expecting == Expecting(EQUALSIGN))
7044	expecting = Expecting(ALPHA);
7045	else if (expecting == Expecting(ALPHA))
7046	{
7047	#if defined (BEAGLE_ENABLED)
7048	if (IsArgValid(tkn, tempStr) == NO_ERROR)
7049	{
7050	if (!strcmp(tempStr, "Always"))
7051	{
7052	beagleScalingScheme = MB_BEAGLE_SCALE_ALWAYS;
7053	}
7054	else
7055	{
7056	beagleScalingScheme = MB_BEAGLE_SCALE_DYNAMIC;
7057	}
7058
7059	if (beagleScalingScheme == MB_BEAGLE_SCALE_ALWAYS)
7060	MrBayesPrint ("%s Setting beaglescaling to Always\n", spacer);
7061	else
7062	MrBayesPrint ("%s Setting beaglescaling to Dynamic\n", spacer);
7063	}
7064	else
7065	{
7066	MrBayesPrint ("%s Invalid argument for beaglescaling\n", spacer);
7067	return (ERROR);
7068	}
7069	#else
7070	BeagleThreadsNotLinked();
7071	#endif
7072	expecting = Expecting(PARAMETER) \| Expecting(SEMICOLON);
7073	}
7074	else
7075	return (ERROR);
7076	}
7077	else
7078	return (ERROR);
7079
7080	}
7081
7082	return (NO_ERROR);
7083
7084	}
7085
7086
7087
7088
7089
7090	int DoShowMatrix (void)
7091
7092	{
7093
7094	int i, j, nameLen, start, finish, ct, longestName;
7095	char tempStr[100], stride;
7096
7097	if (defMatrix == NO)
7098	{
7099	MrBayesPrint ("%s A character matrix must be defined first\n", spacer);
7100	return (ERROR);
7101	}
7102
7103	longestName = 0;
7104	for (i=0; i<numTaxa; i++)
7105	{
7106	nameLen = (int) strlen(taxaNames[i]);
7107	if (nameLen > longestName)
7108	longestName = nameLen;
7109	}
7110
7111	stride = 50;
7112	start = finish = 0;
7113	do
7114	{
7115	finish += stride;
7116	if (finish > numChar)
7117	finish = numChar;
7118
7119	MrBayesPrint ("%s ", spacer);
7120	for (j=0; j<longestName; j++)
7121	MrBayesPrint (" ");
7122	MrBayesPrint (" ");
7123	MrBayesPrint ("%d\n", start+1);
7124
7125
7126	for (i=0; i<numTaxa; i++)
7127	{
7128	strcpy (tempStr, taxaNames[i]);
7129	nameLen = (int) strlen(tempStr);
7130
7131	MrBayesPrint ("%s ", spacer);
7132	if (nameLen >= longestName)
7133	{
7134	for (j=0; j<longestName; j++)
7135	MrBayesPrint ("%c", tempStr[j]);
7136	}
7137	else
7138	{
7139	MrBayesPrint ("%s", tempStr);
7140	for (j=0; j<longestName-nameLen; j++)
7141	MrBayesPrint (" ");
7142	}
7143	MrBayesPrint (" ");
7144
7145	for (j=start; j<finish; j++)
7146	{
7147	ct = charInfo[j].charType;
7148	if (ct == DNA \|\| ct == RNA)
7149	MrBayesPrint ("%c", WhichNuc(matrix[pos(i,j,numChar)]));
7150	else if (ct == PROTEIN)
7151	MrBayesPrint ("%c", WhichAA(matrix[pos(i,j,numChar)]));
7152	else if (ct == STANDARD)
7153	MrBayesPrint ("%c", WhichStand(matrix[pos(i,j,numChar)]));
7154	else if (ct == RESTRICTION)
7155	MrBayesPrint ("%c", WhichRes(matrix[pos(i,j,numChar)]));
7156	else if (ct == CONTINUOUS)
7157	{
7158	if (WhichCont(matrix[pos(i,j,numChar)]) < 0.0)
7159	MrBayesPrint (" %2.2lf", WhichCont(matrix[pos(i,j,numChar)]));
7160	else
7161	MrBayesPrint (" %2.2lf", WhichCont(matrix[pos(i,j,numChar)]));
7162	}
7163	else
7164	{
7165	MrBayesPrint ("%s Unknown data type\n", spacer);
7166	return (ERROR);
7167	}
7168
7169	}
7170	MrBayesPrint ("\n");
7171	}
7172	MrBayesPrint ("\n");
7173	start = finish;
7174	} while (finish != numChar);
7175
7176	return (NO_ERROR);
7177
7178	}
7179
7180
7181
7182
7183
7184	int DoShowUserTrees (void)
7185
7186	{
7187
7188	int i;
7189
7190	if (numUserTrees == 0)
7191	{
7192	MrBayesPrint ("%s No user trees have been defined\n", spacer);
7193	}
7194	else
7195	{
7196	for (i=0; i<numUserTrees; i++)
7197	{
7198	MrBayesPrint ("\n Tree #%d -- '%s':\n\n", i+1, userTree[i]->name);
7199	ShowConTree (stdout, userTree[i], 70, NO);
7200	MrBayesPrint ("\n");
7201	}
7202	}
7203
7204	return (NO_ERROR);
7205
7206	}
7207
7208
7209
7210
7211
7212	int DoShowBeagle (void)
7213
7214	{
7215	#if defined (BEAGLE_ENABLED)
7216	BeaglePrintResources();
7217	#else
7218	BeagleNotLinked();
7219	#endif
7220	return (NO_ERROR);
7221	}
7222
7223
7224
7225
7226
7227	int DoTaxlabels (void)
7228
7229	{
7230
7231	isTaxsetDef = YES;
7232
7233	/* add default speciespartition name to list of valid speciespartitions */
7234	if (AddString (&speciespartitionNames, 0, "Default") == ERROR)
7235	{
7236	MrBayesPrint ("%s Problem adding Default speciespartition to list\n", spacer);
7237	return (ERROR);
7238	}
7239
7240	/* add default species name set */
7241	AddNameSet(&speciesNameSets, 0, taxaNames, numTaxa);
7242
7243	/* set number of defined speciespartitions to 1 */
7244	numDefinedSpeciespartitions = 1;
7245
7246	return (NO_ERROR);
7247
7248	}
7249
7250
7251
7252
7253
7254	int DoTaxlabelsParm (char parmName, char tkn)
7255
7256	{
7257
7258	int index;
7259
7260	if (inTaxaBlock == NO)
7261	{
7262	MrBayesPrint ("%s You must be in a taxa block to read a taxlabels command\n", spacer);
7263	return (ERROR);
7264	}
7265
7266	if (defTaxa == NO)
7267	{
7268	MrBayesPrint ("%s The number of taxa must be given before a set of taxon labels can be read\n", spacer);
7269	return ERROR;
7270	}
7271
7272	if (isTaxsetDef == YES)
7273	{
7274	MrBayesPrint ("%s A set of taxon labels has already been defined\n", spacer);
7275	if (defMatrix == NO)
7276	if (WantTo ("Do you want to delete the current set of taxon labels") == NO)
7277	return (SKIP_COMMAND);
7278	else
7279	FreeTaxa();
7280	else
7281	if (WantTo ("Do you want to delete the current character matrix") == NO)
7282	return (SKIP_COMMAND);
7283	else
7284	FreeMatrix();
7285	}
7286
7287	if (expecting == Expecting(ALPHA) \|\|
7288	expecting == Expecting(NUMBER))
7289	{
7290	if (CheckString (taxaNames, numNamedTaxa, tkn, &index) == ERROR)
7291	{
7292	if ( strlen(tkn)>99 )
7293	{
7294	MrBayesPrint ("%s Taxon name %s is too long. Maximun 99 characters is allowed.\n", spacer, tkn);
7295	return (ERROR);
7296	}
7297	if (AddString (&taxaNames, numNamedTaxa, tkn) == ERROR)
7298	{
7299	MrBayesPrint ("%s Problem adding label %s to list of taxon labels\n", spacer, tkn);
7300	return (ERROR);
7301	}
7302	numNamedTaxa++;
7303	}
7304	else
7305	{
7306	MrBayesPrint ("%s Taxon label '%s' is included twice in list of taxon labels\n", spacer, tkn);
7307	return (ERROR);
7308	}
7309	if (numNamedTaxa < numTaxa)
7310	{
7311	expecting = Expecting(ALPHA);
7312	expecting \|= Expecting(NUMBER);
7313	}
7314	else
7315	expecting \|= Expecting(SEMICOLON);
7316	}
7317
7318	return (NO_ERROR);
7319	MrBayesPrint ("%s", parmName); /* just because I am tired of seeing the unused parameter error msg */
7320	MrBayesPrint ("%s", tkn);
7321
7322	}
7323
7324
7325
7326
7327
7328	int DoSpeciespartition (void)
7329
7330	{
7331
7332	int i, *partCount;
7333
7334	/* add set to tempSet */
7335	if (fromI >= 0)
7336	if (AddToSet (fromI, toJ, everyK, whichPartition+1) == ERROR)
7337	{
7338	for (i=0; i<numDivisions; i++)
7339	free(tempNames[i]);
7340	free (tempNames);
7341	tempNames = NULL;
7342	return (ERROR);
7343	}
7344
7345	/* set numDivisions; not set while reading the speciespartition */
7346	numDivisions = whichPartition + 1;
7347
7348	/* check that all species are included */
7349	for (i=0; i<numTaxa; i++)
7350	{
7351	if (tempSet[i] == 0)
7352	{
7353	MrBayesPrint ("%s Tip %d not included in speciespartition\n", spacer, i+1);
7354	for (i=0; i<numDivisions; i++)
7355	free(tempNames[i]);
7356	free (tempNames);
7357	tempNames = NULL;
7358	return (ERROR);
7359	}
7360	/MrBayesPrint ("%4d %4d \n", i, tempSet[i]);/
7361	}
7362
7363	partCount = (int *) SafeCalloc (numDivisions, sizeof(int));
7364	if (!partCount)
7365	{
7366	for (i=0; i<numDivisions; i++)
7367	free(tempNames[i]);
7368	free (tempNames);
7369	tempNames = NULL;
7370	return ERROR;
7371	}
7372
7373	/* make certain that the partition labels go from 1 - numTaxa, inclusive */
7374	for (i=0; i<numTaxa; i++)
7375	{
7376	if (tempSet[i] < 1 \|\| tempSet[i] > numTaxa)
7377	{
7378	MrBayesPrint ("%s Speciespartition index for tip %d out of bound (%d)\n", spacer, i+1, tempSet[i]);
7379	free (partCount);
7380	for (i=0; i<numDivisions; i++)
7381	free(tempNames[i]);
7382	free (tempNames);
7383	tempNames = NULL;
7384	return (ERROR);
7385	}
7386	partCount[tempSet[i] - 1]++;
7387	}
7388	for (i=0; i<numDivisions; i++)
7389	{
7390	if (partCount[i] == 0)
7391	{
7392	MrBayesPrint ("%s Could not find a single tip for species %d\n", spacer, i+1);
7393	free (partCount);
7394	for (i=0; i<numDivisions; i++)
7395	free(tempNames[i]);
7396	free (tempNames);
7397	tempNames = NULL;
7398	return (ERROR);
7399	}
7400	}
7401	free (partCount);
7402
7403	/* add name to list of valid partitions */
7404	if (AddString (&speciespartitionNames, numDefinedSpeciespartitions, tempSetName) == ERROR)
7405	{
7406	MrBayesPrint ("%s Problem adding speciespartition %s to list\n", spacer, tempSetName);
7407	for (i=0; i<numDivisions; i++)
7408	free(tempNames[i]);
7409	free (tempNames);
7410	tempNames = NULL;
7411	return (ERROR);
7412	}
7413
7414	/* add new partition */
7415	for (i=0; i<numTaxa; i++)
7416	{
7417	speciespartitionId[i] = (int ) SafeRealloc ((void )(speciespartitionId[i]), (size_t)((numDefinedSpeciespartitions + 1) * sizeof(int)));
7418	if (!speciespartitionId[i])
7419	{
7420	for (i=0; i<numDivisions; i++)
7421	free(tempNames[i]);
7422	free (tempNames);
7423	tempNames = NULL;
7424	return ERROR;
7425	}
7426	}
7427
7428	/* set new partition */
7429	for (i=0; i<numTaxa; i++)
7430	speciespartitionId[i][numDefinedSpeciespartitions] = tempSet[i];
7431
7432	/* add new set of species names */
7433	AddNameSet(&speciesNameSets, numDefinedSpeciespartitions, tempNames, numDivisions);
7434
7435	/* free species names */
7436	for (i=0; i<numDivisions; i++)
7437	free(tempNames[i]);
7438	free (tempNames);
7439	tempNames = NULL;
7440
7441	/* increment number of defined partitions */
7442	numDefinedSpeciespartitions++;
7443
7444	return (NO_ERROR);
7445
7446	}
7447
7448
7449
7450
7451
7452	int DoSpeciespartitionParm (char parmName, char tkn)
7453
7454	{
7455
7456	int i, index, tempInt;
7457
7458	if (defTaxa == NO \|\| numTaxa == 0)
7459	{
7460	MrBayesPrint ("%s A matrix or taxaset must be specified before partitions can be defined\n", spacer);
7461	return (ERROR);
7462	}
7463
7464	if (expecting == Expecting(PARAMETER))
7465	{
7466	/* set Speciespartition name ******************************************************************/
7467	if (!strcmp(parmName, "Xxxxxxxxxx"))
7468	{
7469	/* check size of partition name */
7470	if (strlen(tkn) > 99)
7471	{
7472	MrBayesPrint ("%s Partition name is too long. Max 100 characters\n", spacer);
7473	return (ERROR);
7474	}
7475
7476	/* check to see if the name has already been used as a partition */
7477	if (numDefinedSpeciespartitions > 0)
7478	{
7479	if (CheckString (speciespartitionNames, numDefinedSpeciespartitions, tkn, &index) == ERROR)
7480	{
7481	/* if the partition name has not been used, then we should have an ERROR returned */
7482	/* we _want_ to be here */
7483
7484	}
7485	else
7486	{
7487	MrBayesPrint ("%s Speciespartition name '%s' has been used previously\n", spacer, tkn);
7488	return (ERROR);
7489	}
7490	}
7491
7492	/* add the name temporarily to tempSetName */
7493	strcpy (tempSetName, tkn);
7494
7495	/* clear tempSet */
7496	for (i=0; i<numTaxa; i++)
7497	tempSet[i] = 0;
7498
7499	/* make sure tempNames is NULL */
7500	assert (tempNames == NULL);
7501
7502	fromI = toJ = everyK = -1;
7503	foundDash = foundSlash = NO;
7504	whichPartition = 0;
7505	foundFirst = NO;
7506	numDivisions = 0;
7507	MrBayesPrint ("%s Defining speciespartition called %s\n", spacer, tkn);
7508	expecting = Expecting(EQUALSIGN);
7509	}
7510	else
7511	return (ERROR);
7512	}
7513	else if (expecting == Expecting(EQUALSIGN))
7514	{
7515	expecting = Expecting(ALPHA);
7516	}
7517	else if (expecting == Expecting(ALPHA))
7518	{
7519	if (foundFirst == NO)
7520	{
7521	AddString(&tempNames, whichPartition, tkn);
7522	foundFirst = YES;
7523	expecting = Expecting(COLON);
7524	}
7525	else
7526	{
7527	/* We are defining a species partition in terms of a tip name (called tkn, here). We should be able
7528	to find tkn in the list of tip names. If we cannot, then we have a problem and
7529	return an error. */
7530	if (CheckString (taxaNames, numTaxa, tkn, &index) == ERROR)
7531	{
7532	MrBayesPrint ("%s Could not find a tip called %s\n", spacer, tkn);
7533	return (ERROR);
7534	}
7535	/* add index of the tip named tkn to new tempSet */
7536	tempSet[index] = whichPartition + 1;
7537	fromI = toJ = everyK = -1;
7538
7539	expecting = Expecting(ALPHA);
7540	expecting \|= Expecting(NUMBER);
7541	expecting \|= Expecting(SEMICOLON);
7542	expecting \|= Expecting(COMMA);
7543	}
7544	}
7545	else if (expecting == Expecting(NUMBER))
7546	{
7547	if (strlen(tkn) == 1 && tkn[0] == '.')
7548	tempInt = numTaxa;
7549	else
7550	sscanf (tkn, "%d", &tempInt);
7551	if (tempInt <= 0 \|\| tempInt > numTaxa)
7552	{
7553	MrBayesPrint ("%s Tip number %d is out of range (should be between %d and %d)\n", spacer, tempInt, 1, numTaxa);
7554	for (i=0; i<whichPartition; i++)
7555	free(tempNames[i]);
7556	free (tempNames);
7557	tempNames = NULL;
7558	return (ERROR);
7559	}
7560	tempInt--;
7561	if (foundDash == YES)
7562	{
7563	if (fromI >= 0)
7564	toJ = tempInt;
7565	else
7566	{
7567	MrBayesPrint ("%s Improperly formatted speciespartition\n", spacer);
7568	for (i=0; i<whichPartition; i++)
7569	free(tempNames[i]);
7570	free (tempNames);
7571	tempNames = NULL;
7572	return (ERROR);
7573	}
7574	foundDash = NO;
7575	}
7576	else if (foundSlash == YES)
7577	{
7578	tempInt++;
7579	if (tempInt <= 1)
7580	{
7581	MrBayesPrint ("%s Improperly formatted speciespartition\n", spacer);
7582	for (i=0; i<whichPartition; i++)
7583	free(tempNames[i]);
7584	free (tempNames);
7585	tempNames = NULL;
7586	return (ERROR);
7587	}
7588	if (fromI >= 0 && toJ >= 0 && fromI < toJ)
7589	everyK = tempInt;
7590	else
7591	{
7592	MrBayesPrint ("%s Improperly formatted speciespartition\n", spacer);
7593	for (i=0; i<whichPartition; i++)
7594	free(tempNames[i]);
7595	free (tempNames);
7596	tempNames = NULL;
7597	return (ERROR);
7598	}
7599	foundSlash = NO;
7600	}
7601	else
7602	{
7603	if (fromI >= 0 && toJ < 0)
7604	{
7605	if (AddToSet (fromI, toJ, everyK, whichPartition+1) == ERROR)
7606	{
7607	for (i=0; i<whichPartition; i++)
7608	free(tempNames[i]);
7609	free (tempNames);
7610	tempNames = NULL;
7611	return (ERROR);
7612	}
7613	fromI = tempInt;
7614	}
7615	else if (fromI < 0 && toJ < 0)
7616	{
7617	fromI = tempInt;
7618	}
7619	else if (fromI >= 0 && toJ >= 0 && everyK < 0)
7620	{
7621	if (AddToSet (fromI, toJ, everyK, whichPartition+1) == ERROR)
7622	return (ERROR);
7623	fromI = tempInt;
7624	toJ = everyK = -1;
7625	}
7626	else if (fromI >= 0 && toJ >= 0 && everyK >= 0)
7627	{
7628	if (AddToSet (fromI, toJ, everyK, whichPartition+1) == ERROR)
7629	return (ERROR);
7630	fromI = tempInt;
7631	toJ = everyK = -1;
7632	}
7633	else
7634	{
7635	MrBayesPrint ("%s Improperly formatted speciespartition\n", spacer);
7636	{
7637	for (i=0; i<whichPartition; i++)
7638	free(tempNames[i]);
7639	free (tempNames);
7640	tempNames = NULL;
7641	return (ERROR);
7642	}
7643	}
7644	}
7645	expecting = Expecting(ALPHA);
7646	expecting \|= Expecting(NUMBER);
7647	expecting \|= Expecting(SEMICOLON);
7648	expecting \|= Expecting(DASH);
7649	expecting \|= Expecting(BACKSLASH);
7650	expecting \|= Expecting(COMMA);
7651	}
7652	else if (expecting == Expecting(COMMA))
7653	{
7654	/* add set to tempSet */
7655	if (fromI >= 0)
7656	if (AddToSet (fromI, toJ, everyK, whichPartition+1) == ERROR)
7657	{
7658	for (i=0; i<whichPartition; i++)
7659	free(tempNames[i]);
7660	free (tempNames);
7661	tempNames = NULL;
7662	return (ERROR);
7663	}
7664
7665	fromI = toJ = everyK = -1;
7666	foundDash = foundSlash = foundFirst = NO;
7667	whichPartition++;
7668	if (whichPartition > numTaxa)
7669	{
7670	MrBayesPrint ("%s Too many speciespartitions (expecting maximum %d speciespartitions)\n", spacer, numTaxa);
7671	for (i=0; i<whichPartition; i++)
7672	free(tempNames[i]);
7673	free (tempNames);
7674	tempNames = NULL;
7675	return (ERROR);
7676	}
7677	expecting = Expecting(ALPHA);
7678	}
7679	else if (expecting == Expecting(COLON))
7680	{
7681	expecting = Expecting(NUMBER);
7682	expecting \|= Expecting(ALPHA);
7683	}
7684	else if (expecting == Expecting(DASH))
7685	{
7686	foundDash = YES;
7687	expecting = Expecting(NUMBER);
7688	}
7689	else if (expecting == Expecting(BACKSLASH))
7690	{
7691	foundSlash = YES;
7692	expecting = Expecting(NUMBER);
7693	}
7694	else
7695	{
7696	for (i=0; i<whichPartition; i++)
7697	free(tempNames[i]);
7698	free (tempNames);
7699	tempNames = NULL;
7700	return (ERROR);
7701	}
7702
7703	return (NO_ERROR);
7704
7705	}
7706
7707
7708
7709
7710
7711	int DoTaxaset (void)
7712
7713	{
7714	/* add set to tempSet */
7715	if (fromI >= 0 && toJ < 0)
7716	{
7717	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
7718	return (ERROR);
7719	}
7720	else if (fromI >= 0 && toJ >= 0 && everyK < 0)
7721	{
7722	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
7723	return (ERROR);
7724	}
7725	else if (fromI >= 0 && toJ >= 0 && everyK >= 0)
7726	{
7727	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
7728	return (ERROR);
7729	}
7730
7731	/* add name to taxaSetNames */
7732	if (AddString (&taxaSetNames, numTaxaSets, tempSetName) == ERROR)
7733	{
7734	MrBayesPrint ("%s Problem adding taxset %s to list\n", spacer, tempSetName);
7735	return (ERROR);
7736	}
7737
7738	/* merge tempSet with taxaSet */
7739	AddBitfield (&taxaSet, numTaxaSets, tempSet, numTaxa);
7740
7741	/* increment number of char sets */
7742	numTaxaSets++;
7743
7744	/* show taxset (for debugging) */
7745	# if 0
7746	for (i=0; i<numTaxa; i++)
7747	MrBayesPrint ("%4d %4d\n", i+1, tempSet[i]);
7748	# endif
7749
7750	return (NO_ERROR);
7751
7752	}
7753
7754
7755
7756
7757
7758	int DoTaxasetParm (char parmName, char tkn)
7759
7760	{
7761
7762	int i, index, tempInt;
7763
7764	if (defMatrix == NO)
7765	{
7766	MrBayesPrint ("%s A matrix must be specified before taxsets can be defined\n", spacer);
7767	return (ERROR);
7768	}
7769
7770	if (expecting == Expecting(PARAMETER))
7771	{
7772	if (!strcmp(parmName, "Xxxxxxxxxx"))
7773	{
7774	/* check size of taxset name */
7775	if (strlen(tkn) > 99)
7776	{
7777	MrBayesPrint ("%s Taxset name is too long\n", spacer);
7778	return (ERROR);
7779	}
7780
7781	/* check to see if the name has already been used as a taxset */
7782	if (numTaxaSets > 0)
7783	{
7784	if (CheckString (taxaSetNames, numTaxaSets, tkn, &index) == ERROR)
7785	{
7786	/* if the taxset name has not been used, then we should have an ERROR returned */
7787	/* we _want_ to be here */
7788
7789	}
7790	else
7791	{
7792	MrBayesPrint ("%s Taxset name has been used previously\n", spacer);
7793	return (ERROR);
7794	}
7795	}
7796	else if (numTaxaSets > 30)
7797	{
7798	MrBayesPrint ("%s You cannot define more than 30 taxsets\n", spacer);
7799	return (ERROR);
7800	}
7801
7802	/* add the name to the taxa set */
7803	strcpy (tempSetName, tkn);
7804
7805	/* clear tempSet */
7806	for (i=0; i<numTaxa; i++)
7807	tempSet[i] = 0;
7808
7809	fromI = toJ = everyK = -1;
7810	foundDash = foundSlash = NO;
7811	MrBayesPrint ("%s Defining taxset called %s\n", spacer, tkn);
7812	expecting = Expecting(EQUALSIGN);
7813	}
7814	else
7815	return (ERROR);
7816	}
7817	else if (expecting == Expecting(EQUALSIGN))
7818	{
7819	expecting = Expecting(ALPHA);
7820	expecting \|= Expecting(NUMBER);
7821	}
7822	else if (expecting == Expecting(ALPHA))
7823	{
7824	/* We are defining a taxon set in terms of another (called tkn, here) or we are referring to
7825	the taxon name. We should be able to find tkn in the list of character set names or in the list
7826	of taxon names. If we cannot, then we have a problem and return an error. */
7827	if (CheckString (taxaNames, numTaxa, tkn, &index) == ERROR)
7828	{
7829	if (numTaxaSets < 1)
7830	{
7831	MrBayesPrint ("%s Could not find a taxset called %s\n", spacer, tkn);
7832	return (ERROR);
7833	}
7834	if (CheckString (taxaSetNames, numTaxaSets, tkn, &index) == ERROR)
7835	{
7836	MrBayesPrint ("%s Could not find a taxset called %s\n", spacer, tkn);
7837	return (ERROR);
7838	}
7839	/* add taxa from taxset tkn to new tempSet */
7840	for (i=0; i<numTaxa; i++)
7841	{
7842	if (IsBitSet (i, taxaSet[index]) == YES)
7843	tempSet[i] = 1;
7844	}
7845	}
7846	else
7847	{
7848	tempSet[index] = 1;
7849	}
7850	fromI = toJ = everyK = -1;
7851
7852	expecting = Expecting(ALPHA);
7853	expecting \|= Expecting(NUMBER);
7854	expecting \|= Expecting(SEMICOLON);
7855	}
7856	else if (expecting == Expecting(NUMBER))
7857	{
7858	if (strlen(tkn) == 1 && !strcmp(tkn, "."))
7859	{
7860	tempInt = numTaxa;
7861	}
7862	else
7863	{
7864	sscanf (tkn, "%d", &tempInt);
7865	if (tempInt <= 0 \|\| tempInt > numTaxa)
7866	{
7867	MrBayesPrint ("%s Taxon number %d is out of range (should be between %d and %d)\n", spacer, tempInt, 1, numTaxa);
7868	return (ERROR);
7869	}
7870	}
7871	tempInt--;
7872	if (foundDash == YES)
7873	{
7874	if (fromI >= 0)
7875	toJ = tempInt;
7876	else
7877	{
7878	MrBayesPrint ("%s Improperly formatted taxset\n", spacer);
7879	return (ERROR);
7880	}
7881	foundDash = NO;
7882	}
7883	else if (foundSlash == YES)
7884	{
7885	tempInt++;
7886	if (tempInt <= 1)
7887	{
7888	MrBayesPrint ("%s Improperly formatted taxset\n", spacer);
7889	return (ERROR);
7890	}
7891	if (fromI >= 0 && toJ >= 0 && fromI < toJ)
7892	everyK = tempInt;
7893	else
7894	{
7895	MrBayesPrint ("%s Improperly formatted taxset\n", spacer);
7896	return (ERROR);
7897	}
7898	foundSlash = NO;
7899	}
7900	else
7901	{
7902	if (fromI >= 0 && toJ < 0)
7903	{
7904	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
7905	return (ERROR);
7906	fromI = tempInt;
7907	}
7908	else if (fromI < 0 && toJ < 0)
7909	{
7910	fromI = tempInt;
7911	}
7912	else if (fromI >= 0 && toJ >= 0 && everyK < 0)
7913	{
7914	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
7915	return (ERROR);
7916	fromI = tempInt;
7917	toJ = everyK = -1;
7918	}
7919	else if (fromI >= 0 && toJ >= 0 && everyK >= 0)
7920	{
7921	if (AddToSet (fromI, toJ, everyK, 1) == ERROR)
7922	return (ERROR);
7923	fromI = tempInt;
7924	toJ = everyK = -1;
7925	}
7926	else
7927	{
7928	MrBayesPrint ("%s Improperly formatted taxset\n", spacer);
7929	{
7930	return (ERROR);
7931	}
7932	}
7933	}
7934
7935	expecting = Expecting(ALPHA);
7936	expecting \|= Expecting(NUMBER);
7937	expecting \|= Expecting(SEMICOLON);
7938	expecting \|= Expecting(DASH);
7939	expecting \|= Expecting(BACKSLASH);
7940	}
7941	else if (expecting == Expecting(DASH))
7942	{
7943	foundDash = YES;
7944	expecting = Expecting(NUMBER);
7945	}
7946	else if (expecting == Expecting(BACKSLASH))
7947	{
7948	foundSlash = YES;
7949	expecting = Expecting(NUMBER);
7950	}
7951	else
7952	return (ERROR);
7953
7954	return (NO_ERROR);
7955
7956	}
7957
7958
7959
7960
7961
7962	int DoTaxaStat (void)
7963
7964	{
7965
7966	int i, j, maxLen, nameLen, nIncludedTaxa;
7967	char tempName[100];
7968
7969	if (defMatrix == NO)
7970	{
7971	MrBayesPrint ("%s A character matrix must be defined first\n", spacer);
7972	return (ERROR);
7973	}
7974
7975	/* find maximum length of taxon name */
7976	maxLen = nIncludedTaxa = 0;
7977	for (i=0; i<numTaxa; i++)
7978	{
7979	strcpy (tempName, taxaNames[i]);
7980	if ((int)strlen(tempName) > maxLen)
7981	maxLen = (int) strlen(tempName);
7982	if (taxaInfo[i].isDeleted == NO)
7983	nIncludedTaxa++;
7984	}
7985
7986	MrBayesPrint ("%s Showing taxon status:\n\n", spacer);
7987	if (nIncludedTaxa == numTaxa)
7988	MrBayesPrint ("%s Number of taxa = %d (all of which are included)\n", spacer, numTaxa);
7989	else
7990	MrBayesPrint ("%s Number of taxa = %d (of which %d are included)\n", spacer, numTaxa, nIncludedTaxa);
7991	MrBayesPrint ("%s Number of constraints = %d\n\n", spacer, numDefinedConstraints);
7992
7993	if (numDefinedConstraints > 0)
7994	{
7995	for (j=0; j<numDefinedConstraints; j++)
7996	{
7997	strcpy (tempName, constraintNames[j]);
7998
7999	/* for now, ignore the probability */
8000	if( definedConstraintsType[j] == HARD )
8001	MrBayesPrint ("%s %2d -- Trees with 'hard' constraint \"%s\" are infinitely\n", spacer, j+1, tempName);
8002	else if( definedConstraintsType[j] == PARTIAL )
8003	MrBayesPrint ("%s %2d -- Trees with 'partial' constraint \"%s\" are infinitely\n", spacer, j+1, tempName);
8004	else
8005	MrBayesPrint ("%s %2d -- Trees with 'negative' constraint \"%s\" are infinitely\n", spacer, j+1, tempName);
8006	MrBayesPrint ("%s more probable than those without \n", spacer);
8007
8008	}
8009	MrBayesPrint ("\n");
8010	for (j=0; j<maxLen; j++)
8011	MrBayesPrint (" ");
8012	MrBayesPrint (" Constraints\n");
8013	}
8014	MrBayesPrint ("%s Taxon ", spacer);
8015	for (j=0; j<maxLen; j++)
8016	MrBayesPrint (" ");
8017	MrBayesPrint (" Inclusion");
8018	MrBayesPrint (" ");
8019	for (j=0; j<numDefinedConstraints; j++)
8020	MrBayesPrint (" %2d", j+1);
8021	MrBayesPrint ("\n");
8022	MrBayesPrint ("%s -------", spacer);
8023	for (j=0; j<maxLen; j++)
8024	MrBayesPrint ("-");
8025	MrBayesPrint ("--------------");
8026
8027	if (numDefinedConstraints > 0)
8028	{
8029	MrBayesPrint ("----");
8030	for (j=0; j<numDefinedConstraints; j++)
8031	MrBayesPrint ("---");
8032	}
8033	MrBayesPrint ("\n");
8034	for (i=0; i<numTaxa; i++)
8035	{
8036	strcpy (tempName, taxaNames[i]);
8037	nameLen = (int) strlen(tempName);
8038
8039	if (i == outGroupNum)
8040	MrBayesPrint ("%s ->%4d (%s) ", spacer, i+1, tempName);
8041	else
8042	MrBayesPrint ("%s %4d (%s) ", spacer, i+1, tempName);
8043	for (j=0; j<(maxLen-nameLen); j++)
8044	MrBayesPrint (" ");
8045	MrBayesPrint (" -- ");
8046
8047	if (taxaInfo[i].isDeleted == YES)
8048	MrBayesPrint ("Deleted ");
8049	else
8050	MrBayesPrint ("Included");
8051
8052	MrBayesPrint (" ");
8053
8054	for (j=0; j<numDefinedConstraints; j++)
8055	{
8056	if( definedConstraintsType[j] == HARD )
8057	{
8058	if (IsBitSet(i, definedConstraint[j]) == NO)
8059	MrBayesPrint (" .");
8060	else
8061	MrBayesPrint (" *");
8062	}
8063	else if( definedConstraintsType[j] == PARTIAL )
8064	{
8065	if (IsBitSet(i, definedConstraint[j]) == YES)
8066	MrBayesPrint (" +");
8067	else if(IsBitSet(i, definedConstraintTwo[j]) == YES)
8068	MrBayesPrint (" -");
8069	else
8070	MrBayesPrint (" .");
8071	}
8072	else if( definedConstraintsType[j] == NEGATIVE )
8073	{
8074	if (IsBitSet(i, definedConstraint[j]) == NO)
8075	MrBayesPrint (" .");
8076	else
8077	MrBayesPrint (" #");
8078	}
8079	}
8080	MrBayesPrint ("\n");
8081	}
8082
8083	MrBayesPrint ("\n");
8084	MrBayesPrint ("%s '.' indicate that the taxon is not present in the constraint. \n", spacer);
8085	MrBayesPrint ("%s '*' indicate that the taxon is present in the 'hard' constraint. \n", spacer);
8086	MrBayesPrint ("%s '+' indicate that the taxon is present in the first groupe of 'partial' constraint. \n", spacer);
8087	MrBayesPrint ("%s '-' indicate that the taxon is present in the second groupe of 'partial' constraint. \n", spacer);
8088	MrBayesPrint ("%s '#' indicate that the taxon is present in the 'negative' constraint. \n", spacer);
8089	MrBayesPrint ("%s Arrow indicates current outgroup. \n", spacer);
8090
8091	return (NO_ERROR);
8092
8093	}
8094
8095
8096
8097
8098
8099	int DoTranslate (void)
8100
8101	{
8102	int i, j;
8103
8104	if (inTreesBlock == NO)
8105	{
8106	MrBayesPrint ("%s You must be in a trees block to read a translate command\n", spacer);
8107	return (ERROR);
8108	}
8109	numTranslates++; /* number of taxa in translate table */
8110	isTranslateDef = YES;
8111
8112	isTranslateDiff = NO;
8113	if (isTaxsetDef == NO)
8114	SetTaxaFromTranslateTable();
8115	else
8116	{
8117	for (i=0; i<numTranslates; i++)
8118	{
8119	strcpy (token, transFrom[i]);
8120	if (CheckString (taxaNames, numTaxa, token, &j) == ERROR)
8121	{
8122	isTranslateDiff = YES;
8123	}
8124	}
8125	if (numTranslates != numTaxa)
8126	isTranslateDiff = YES;
8127	}
8128
8129	return (NO_ERROR);
8130
8131	}
8132
8133
8134
8135
8136
8137	int DoTranslateParm (char parmName, char tkn)
8138
8139	{
8140
8141	int index;
8142	static int whichTranslate;
8143
8144	if (inTreesBlock == NO)
8145	{
8146	MrBayesPrint ("%s You must be in a trees block to read a translate command\n", spacer);
8147	return (ERROR);
8148	}
8149
8150	if (isTranslateDef == YES)
8151	{
8152	MrBayesPrint ("%s A translation has already been defined for this tree block\n", spacer);
8153	return (ERROR);
8154	}
8155
8156	if (expecting == Expecting(ALPHA) \|\|
8157	expecting == Expecting(NUMBER))
8158	{
8159	if( numTaxa == 0 )
8160	{
8161	MrBayesPrint ("%s Data matrix should be defined before translation table could be set.\n", spacer);
8162	return (ERROR);
8163	}
8164	if (numTranslates == numTaxa)
8165	{
8166	MrBayesPrint ("%s Too many entries in translation table. Maximum number of taxon names to translate is %d\n", spacer,numTaxa);
8167	return (ERROR);
8168	}
8169	if (whichTranslate == 0)
8170	{
8171	if (CheckString (transTo, numTranslates, tkn, &index) == ERROR)
8172	{
8173	if (AddString (&transTo, numTranslates, tkn) == ERROR)
8174	{
8175	MrBayesPrint ("%s Problem adding taxon %s to list\n", spacer, tkn);
8176	return (ERROR);
8177	}
8178	}
8179	else
8180	{
8181	MrBayesPrint ("%s Already found name (%s) in list\n", spacer, tkn);
8182	return (ERROR);
8183	}
8184	whichTranslate++;
8185	expecting = Expecting(ALPHA);
8186	expecting \|= Expecting(NUMBER);
8187	}
8188	else
8189	{
8190	if (CheckString (transFrom, numTranslates, tkn, &index) == ERROR)
8191	{
8192	if (AddString (&transFrom, numTranslates, tkn) == ERROR)
8193	{
8194	MrBayesPrint ("%s Problem adding taxon %s to list\n", spacer, tkn);
8195	return (ERROR);
8196	}
8197	}
8198	else
8199	{
8200	MrBayesPrint ("%s Already found name (%s) in list\n", spacer, tkn);
8201	return (ERROR);
8202	}
8203	whichTranslate = 0;
8204	expecting = Expecting(COMMA);
8205	expecting \|= Expecting(SEMICOLON);
8206	}
8207	}
8208	else if (expecting == Expecting(COMMA))
8209	{
8210	numTranslates++;
8211	expecting = Expecting(ALPHA);
8212	expecting \|= Expecting(NUMBER);
8213	}
8214
8215	return (NO_ERROR);
8216	MrBayesPrint ("%s", parmName); /* just because I am tired of seeing the unused parameter error msg */
8217	MrBayesPrint ("%s", tkn);
8218	}
8219
8220
8221
8222
8223
8224	int DoTree (void)
8225
8226	{
8227
8228	readComment = NO;
8229
8230	if (inSumtCommand == YES \|\| inComparetreeCommand == YES)
8231	return (DoSumtTree ());
8232
8233	return (NO_ERROR);
8234	}
8235
8236
8237
8238
8239
8240	int DoTreeParm (char parmName, char tkn)
8241
8242	{
8243
8244	int i, tempInt, index;
8245	MrBFlt tempD;
8246	char tempName[100];
8247	static SafeLong lastExpecting; /* keep track of what we expected before a comment, in case we want to skip a comment */
8248	static char tempNameString=NULL; / Contains multiple tokens which form name string of param set*/
8249	static int foundAmpersand, foundColon, foundComment, foundE, foundB, foundN, foundFirst,
8250	foundCurly, /* is set to YES when we are between two curly bracets ONLY while processing CppEvent name */
8251	foundClockrate,
8252	foundName, /is set to YES when param set name token is found and set to NO once full param set name is processed/
8253	eSetIndex, /* is set in the begining of reading CppEvent for a node/branch to the index of currently processed CppEvent set */
8254	bSetIndex, eventIndex, treeIndex, nextIntNodeIndex;
8255	static PolyNode pp, qq;
8256	static PolyTree *t;
8257
8258	/* This function will read in components of a tree description. We expect one of the following formats:
8259
8260	tree <name> = [&R] <newick-description>;
8261	tree <name> = [&U] <newick-description>;
8262	tree <name> [&E CppEvents{1,2,5}] = [&R] [&clockrate = 1.23] ((1:0.021[&E CppEvents{1,2,5} 2:(0.10 1.11,0.83 3.17)],2:0.021):0.038,3:0.059);
8263	tree <name> [&B TK02BranchRates{1,2,5}] = [&R] [&clockrate = 1.23] ((1:0.021[&B TK02BranchRates{1,2,5} 1.12],2:0.021[&B TK02BranchRates{1,2,5}...
8264
8265	Values will be stored in event sets that go with the tree and that are used to initialize the relaxed clock
8266	parameters before a run is started. Note that several sets of events can be stored with each tree.
8267	*/
8268
8269
8270	if (isTaxsetDef == NO)
8271	{
8272	MrBayesPrint ("%s Taxon labels must be specified before a tree could be red in\n", spacer);
8273	return (ERROR);
8274	}
8275	if (inTreesBlock == NO)
8276	{
8277	MrBayesPrint ("%s You must be in a trees block to read a tree\n", spacer);
8278	return (ERROR);
8279	}
8280
8281	if (expecting == Expecting(PARAMETER))
8282	{
8283	/* this is the name of the tree */
8284	if (inSumtCommand==YES \|\| inComparetreeCommand == YES)
8285	{
8286	/* we are reading in a tree to sumt or comparetree counters */
8287	t = sumtParams.tree;
8288	ResetPolyTree (t);
8289	}
8290	else
8291	{
8292	/* we are reading in a user tree */
8293	/* check if the tree exists */
8294	treeIndex = 0;
8295	for (i=0; i<numUserTrees; i++)
8296	if (strcmp(tkn,userTree[i]->name) == 0)
8297	break;
8298	treeIndex = i;
8299	if (treeIndex < numUserTrees)
8300	{
8301	MrBayesPrint ("%s Overwriting tree '%s'.\n", spacer, userTree[treeIndex]);
8302	FreePolyTree (userTree[treeIndex]);
8303	}
8304	if ((userTree[treeIndex] = AllocatePolyTree (numTaxa)) == NULL)
8305	return (ERROR);
8306	t = userTree[treeIndex];
8307	}
8308	strncpy (t->name, tkn, 99);
8309	foundColon = foundAmpersand = foundEqual = foundComment = NO;
8310	foundE = foundB = foundN = foundFirst = foundClockrate = foundName = NO;
8311	eSetIndex = bSetIndex = eventIndex = 0;
8312	nextAvailableNode = 0;
8313	if (isTranslateDef == YES && isTranslateDiff == YES)
8314	nextIntNodeIndex = numTranslates;
8315	else
8316	nextIntNodeIndex = numTaxa;
8317	pp = &t->nodes[nextAvailableNode++];
8318	t->root = pp;
8319	t->isRooted = NO; /* expect unrooted tree */
8320	t->isClock = NO; /* expect nonclock tree */
8321	t->isCalibrated = NO; /* expect uncalibrated tree */
8322	t->isRelaxed = NO; /* expect strict clock if clock tree */
8323	t->clockRate = 0.0; /* expect no clock rate */
8324	t->popSizeSet = NO;
8325	readComment = YES;
8326	expecting = Expecting(EQUALSIGN) \| Expecting(LEFTCOMMENT);
8327	lastExpecting = expecting;
8328	}
8329	else if (expecting == Expecting(EQUALSIGN))
8330	{
8331	if (foundClockrate == YES)
8332	expecting = Expecting(NUMBER);
8333	else
8334	{
8335	for (i=0; i<numTaxa; i++)
8336	tempSet[i] = NO;
8337	foundEqual = YES;
8338	expecting = Expecting(LEFTPAR) \| Expecting(LEFTCOMMENT);
8339	lastExpecting = expecting;
8340	}
8341	}
8342	else if (expecting == Expecting(LEFTPAR))
8343	{
8344	if (foundE == YES)
8345	{
8346	expecting = Expecting(NUMBER);
8347	}
8348	else
8349	{
8350	if (nextAvailableNode >= 2*numTaxa)
8351	{
8352	MrBayesPrint ("%s Too many nodes on tree '%s'\n", spacer, t->name);
8353	if (inSumtCommand == NO && inComparetreeCommand == NO)
8354	FreePolyTree (userTree[treeIndex]);
8355	return (ERROR);
8356	}
8357	qq = &t->nodes[nextAvailableNode++];
8358	qq->anc = pp;
8359	pp->left = qq;
8360	pp->index = nextIntNodeIndex++;
8361	pp = qq;
8362	expecting = Expecting(LEFTPAR);
8363	expecting \|= Expecting(ALPHA);
8364	expecting \|= Expecting(NUMBER);
8365	expecting \|= Expecting(LEFTCOMMENT);
8366	lastExpecting = expecting;
8367	}
8368	}
8369	else if (expecting == Expecting(ALPHA))
8370	{
8371	if (foundAmpersand == YES)
8372	{
8373	if (strcmp(tkn,"E") == 0)
8374	{
8375	foundE = YES;
8376	expecting = Expecting(ALPHA);
8377	}
8378	else if (strcmp(tkn,"B") == 0)
8379	{
8380	foundB = YES;
8381	expecting = Expecting(ALPHA);
8382	}
8383	else if (strcmp(tkn,"N") == 0)
8384	{
8385	foundN = YES;
8386	expecting = Expecting(ALPHA);
8387	}
8388	else if (strcmp(tkn, "R") == 0)
8389	{
8390	t->isRooted = YES;
8391	t->isClock = YES; /* assume clock if rooted */
8392	expecting = Expecting(RIGHTCOMMENT);
8393	}
8394	else if (strcmp(tkn, "U") == 0)
8395	{
8396	t->isRooted = NO;
8397	expecting = Expecting(RIGHTCOMMENT);
8398	}
8399	else if (strcmp(tkn, "clockrate") == 0)
8400	{
8401	t->isCalibrated = YES;
8402	foundClockrate = YES;
8403	expecting = Expecting(EQUALSIGN);
8404	}
8405	else
8406	{
8407	inComment = YES;
8408	numComments++;
8409	expecting = lastExpecting;
8410	}
8411	foundAmpersand = NO;
8412	}
8413	else if (foundName == YES && foundCurly == YES)
8414	{
8415	if( strcmp("all",tkn) == 0 )
8416	{
8417	SafeStrcat (&tempNameString,tkn);
8418	expecting = Expecting(RIGHTCURL);
8419	}
8420	else
8421	{
8422	MrBayesPrint ("%s Urecognized argument '%s'\n", spacer, tkn);
8423	return (ERROR);
8424	}
8425	}
8426	else if (foundE == YES) /* We have seen &E */
8427	{
8428	if (foundEqual == NO) /* We have not seen name before and we are in header */
8429	{
8430	t->nESets++;
8431	t->isRelaxed = YES;
8432	t->nEvents = (int *) SafeRealloc ((void )t->nEvents, t->nESetssizeof(int ));
8433	t->position = (MrBFlt **) SafeRealloc ((void )t->position, t->nESetssizeof(MrBFlt *));
8434	t->rateMult = (MrBFlt **) SafeRealloc ((void )t->rateMult, t->nESetssizeof(MrBFlt *));
8435	t->nEvents[t->nESets-1] = (int ) SafeCalloc ((size_t)(2numTaxa), sizeof(int));
8436	t->position[t->nESets-1] = (MrBFlt *) SafeCalloc ((size_t)(2numTaxa), sizeof(MrBFlt *));
8437	t->rateMult[t->nESets-1] = (MrBFlt *) SafeCalloc ((size_t)(2numTaxa), sizeof(MrBFlt *));
8438	t->eSetName = (char *) SafeRealloc ((void )t->eSetName, t->nESetssizeof(char *));
8439	}
8440	SafeStrcpy (&tempNameString,tkn);
8441	foundName = YES;
8442	expecting = Expecting(LEFTCURL);
8443	if (foundEqual == YES)
8444	expecting \|= Expecting(NUMBER);
8445	else
8446	expecting \|= Expecting(RIGHTCOMMENT);
8447	}
8448	else if (foundB == YES)
8449	{
8450	if (foundEqual == NO)
8451	{
8452	t->nBSets++;
8453	t->isRelaxed = YES;
8454	t->effectiveBrLen = (MrBFlt *) SafeRealloc ((void )t->effectiveBrLen, (size_t)(t->nBSetssizeof(MrBFlt )));
8455	t->effectiveBrLen[t->nBSets-1] = (MrBFlt ) SafeCalloc ((size_t)(2numTaxa),sizeof(MrBFlt));
8456	for (i=0; i<2*numTaxa; i++)
8457	t->effectiveBrLen[t->nBSets-1][i] = 1.0;
8458	t->bSetName = (char *) SafeRealloc ((void )t->bSetName, t->nBSetssizeof(char *));
8459	t->bSetName[t->nBSets-1] = (char *) SafeCalloc (strlen(tkn)+1,sizeof(char));
8460	}
8461	SafeStrcpy (&tempNameString,tkn);
8462	foundName = YES;
8463	expecting = Expecting(LEFTCURL);
8464	if (foundEqual == YES)
8465	expecting \|= Expecting(NUMBER);
8466	else
8467	expecting \|= Expecting(RIGHTCOMMENT);
8468	}
8469	else if (foundN == YES)
8470	{
8471	if (foundEqual == NO)
8472	{
8473	if (t->popSizeSet == YES)
8474	{
8475	MrBayesPrint ("%s Cannot hold more than one population size set\n", spacer);
8476	if (inSumtCommand == NO && inComparetreeCommand == NO)
8477	FreePolyTree (userTree[treeIndex]);
8478	return (ERROR);
8479	}
8480	t->popSizeSet = YES;
8481	if (isTranslateDef == YES && isTranslateDiff == YES)
8482	t->popSize = (MrBFlt ) SafeCalloc (2numTranslates-1, sizeof(MrBFlt));
8483	else
8484	t->popSize = (MrBFlt ) SafeCalloc (2numLocalTaxa-1, sizeof(MrBFlt));
8485	}
8486	SafeStrcpy (&tempNameString,tkn);
8487	foundName = YES;
8488	expecting = Expecting(LEFTCURL);
8489	if (foundEqual == YES)
8490	expecting \|= Expecting(NUMBER);
8491	else
8492	expecting \|= Expecting(RIGHTCOMMENT);
8493	}
8494	else /* taxon name */
8495	{
8496	if (isTranslateDef == YES)
8497	{
8498	/* we are using the translation table */
8499	if (CheckString (transTo, numTranslates, tkn, &index) == ERROR)
8500	{
8501	MrBayesPrint ("%s Could not find token '%s' in taxon translation table\n", spacer, tkn);
8502	if (inSumtCommand == NO && inComparetreeCommand == NO)
8503	FreePolyTree (userTree[treeIndex]);
8504	return (ERROR);
8505	}
8506	strcpy (tempName, transFrom[index]);
8507	if (isTranslateDiff == NO && CheckString (taxaNames, numTaxa, tempName, &index) == ERROR)
8508	{
8509	MrBayesPrint ("%s Could not find taxon '%s' in list of taxa\n", spacer, tkn);
8510	if (inSumtCommand == NO && inComparetreeCommand == NO)
8511	FreePolyTree (userTree[treeIndex]);
8512	return (ERROR);
8513	}
8514	if (tempSet[index] == YES)
8515	{
8516	MrBayesPrint ("%s Taxon name '%s' already used in tree\n", spacer, tkn);
8517	if (inSumtCommand == NO && inComparetreeCommand == NO)
8518	FreePolyTree (userTree[treeIndex]);
8519	return (ERROR);
8520	}
8521	tempSet[index] = YES;
8522	strcpy (pp->label, tempName);
8523	pp->index = index;
8524	}
8525	else
8526	{
8527	/* Check to see if the name is in the list of taxon names. */
8528	if (CheckString (taxaNames, numTaxa, tkn, &index) == ERROR)
8529	{
8530	MrBayesPrint ("%s Could not find taxon '%s' in list of taxa\n", spacer, tkn);
8531	if (inSumtCommand == NO && inComparetreeCommand == NO)
8532	FreePolyTree (userTree[treeIndex]);
8533	return (ERROR);
8534	}
8535	if (tempSet[index] == YES)
8536	{
8537	MrBayesPrint ("%s Taxon name '%s' already used in tree\n", spacer, tkn);
8538	if (inSumtCommand == NO && inComparetreeCommand == NO)
8539	FreePolyTree (userTree[treeIndex]);
8540	return (ERROR);
8541	}
8542	tempSet[index] = YES;
8543	strcpy (pp->label, tkn);
8544	pp->index = index;
8545	}
8546	expecting = Expecting(COMMA);
8547	expecting \|= Expecting(COLON);
8548	expecting \|= Expecting(RIGHTPAR);
8549	}
8550	}
8551	else if (expecting == Expecting(RIGHTPAR))
8552	{
8553	if (foundE == YES)
8554	expecting = Expecting(RIGHTCOMMENT);
8555	else
8556	{
8557	if (pp->anc == NULL)
8558	{
8559	MrBayesPrint ("%s Incorrect tree format: cannot go down\n", spacer);//, tkn
8560	if (inSumtCommand == NO && inComparetreeCommand == NO)
8561	FreePolyTree (userTree[treeIndex]);
8562	return (ERROR);
8563	}
8564	if( pp->anc->left == pp )
8565	{
8566	MrBayesPrint ("%s Incorrect tree format: all nodes except tips should have more then one child. Either a single\n", spacer);
8567	MrBayesPrint ("%s taxon is surrounded with brackets or there is a clade surrounded by double brackets.\n", spacer);
8568	if (inSumtCommand == NO && inComparetreeCommand == NO)
8569	FreePolyTree (userTree[treeIndex]);
8570	return (ERROR);
8571	}
8572	pp = pp->anc;
8573	if (pp->anc == NULL)
8574	{
8575	/* finish up tree */
8576	t->nNodes = nextAvailableNode;
8577	t->nIntNodes = t->nNodes;
8578	for (i=0; i<t->nNodes; i++)
8579	{
8580	if (t->nodes[i].left == NULL)
8581	t->nIntNodes--;
8582	}
8583	GetPolyDownPass(t);
8584
8585	/* check that number of taxa is correct */
8586	if (t->isRooted == NO && t->nNodes-t->nIntNodes == t->nIntNodes + 1)
8587	t->isRooted = YES;
8588	if ((t->isRooted == YES && t->nNodes-t->nIntNodes != t->nIntNodes + 1) \|\|
8589	(t->isRooted == NO && t->nNodes-t->nIntNodes != t->nIntNodes + 2))
8590	{
8591	/* we are protected from adding too many taxa by taxon-matching code above */
8592	if (t->isRooted == YES && t->nNodes-t->nIntNodes == t->nIntNodes + 2)
8593	{
8594	MrBayesPrint ("%s The tree is declared as rooted (by comment [&R]) but\n", spacer);
8595	MrBayesPrint ("%s the given tree has unrooted structure.\n", spacer);
8596	}
8597	else
8598	MrBayesPrint ("%s Taxa missing in tree\n", spacer);
8599
8600	return (ERROR);
8601	}
8602
8603	/* check other properties */
8604	if (t->isClock == YES && t->isRooted == NO)
8605	{
8606	MrBayesPrint ("%s Tree has clock rate but is not rooted\n", spacer);
8607	return (ERROR);
8608	/* Note: any deviation from an ultrametric tree must be assumed to be due to dated
8609	tips at this point */
8610	}
8611	if (t->isRelaxed == YES && t->isClock == NO)
8612	{
8613	MrBayesPrint ("%s Tree has relaxed clock rates but is not a clock tree\n", spacer);
8614	return (ERROR);
8615	}
8616	if (inSumtCommand == NO && inComparetreeCommand == NO)
8617	{
8618	if (treeIndex == numUserTrees)
8619	numUserTrees++;
8620	MrBayesPrint ("%s Successfully read tree '%s'\n", spacer, userTree[treeIndex]->name);
8621	}
8622	if (t->popSize == NULL)
8623	{
8624	readComment = NO;
8625	expecting = Expecting(SEMICOLON);
8626	}
8627	else
8628	{
8629	readComment = YES;
8630	expecting = Expecting(LEFTCOMMENT);
8631	lastExpecting = expecting;
8632	}
8633	}
8634	else
8635	{
8636	expecting = Expecting(COMMA);
8637	expecting \|= Expecting(COLON);
8638	expecting \|= Expecting(RIGHTPAR);
8639	}
8640	}
8641	}
8642	else if (expecting == Expecting(COLON))
8643	{
8644	foundColon = YES;
8645	if (foundE == YES)
8646	expecting = Expecting(LEFTPAR);
8647	else
8648	expecting = Expecting(NUMBER);
8649	expecting \|= Expecting(LEFTCOMMENT);
8650	lastExpecting = expecting;
8651	}
8652	else if (expecting == Expecting(COMMA))
8653	{
8654	if (foundName == YES)
8655	{
8656	SafeStrcat (&tempNameString,",");
8657	expecting = Expecting(NUMBER);
8658	}
8659	else if (foundE == YES)
8660	{
8661	expecting = Expecting(NUMBER);
8662	}
8663	else
8664	{
8665	if (nextAvailableNode >= 2*numTaxa)
8666	{
8667	MrBayesPrint ("%s Too many nodes on tree '%s'\n", spacer, t->name);
8668	if (inSumtCommand == NO && inComparetreeCommand == NO)
8669	FreePolyTree (userTree[treeIndex]);
8670	return (ERROR);
8671	}
8672	qq = &t->nodes[nextAvailableNode++];
8673	pp->sib = qq;
8674	qq->anc = pp->anc;
8675	pp = qq;
8676	expecting = Expecting(LEFTPAR);
8677	expecting \|= Expecting(ALPHA);
8678	expecting \|= Expecting(NUMBER);
8679	expecting \|= Expecting(LEFTCOMMENT);
8680	lastExpecting = expecting;
8681	}
8682	}
8683	else if (expecting == Expecting(NUMBER))
8684	{
8685	if (foundClockrate == YES)
8686	{
8687	sscanf (tkn, "%lf", &tempD);
8688	t->clockRate = tempD;
8689	foundClockrate = NO;
8690	expecting = Expecting(RIGHTCOMMENT);
8691	}
8692	else if (foundName == YES && foundCurly == YES)
8693	{
8694	/* still assembling name of a param set */
8695	SafeStrcat (&tempNameString,tkn);
8696	expecting = Expecting(RIGHTCURL) \| Expecting(COMMA);
8697	}
8698	else if (foundN == YES)
8699	{
8700	/* we only know now that name is complete if it does not have curlies in it */
8701	foundName = NO;
8702
8703	if (strcmp(tempNameString,t->popSizeSetName) != 0)
8704	{
8705	MrBayesPrint ("%s Could not find population size set '%s'\n", spacer, tempNameString);
8706	if (inSumtCommand == NO && inComparetreeCommand == NO)
8707	FreePolyTree (userTree[treeIndex]);
8708	return (ERROR);
8709	}
8710
8711	sscanf (tkn, "%lf", &tempD);
8712	t->popSize[pp->index] = tempD;
8713	foundN = NO;
8714	expecting = Expecting(RIGHTCOMMENT);
8715	}
8716	else if (foundB == YES)
8717	{
8718	/* we only know now that name is complete if it does not have curlies in it */
8719	foundName = NO;
8720
8721	/* find the right effective branch length set */
8722	for (i=0; i<t->nBSets; i++)
8723	if (strcmp(t->bSetName[i],tempNameString) == 0)
8724	break;
8725	if (i == t->nBSets)
8726	{
8727	MrBayesPrint ("%s Could not find effective branch length set '%s'\n", spacer, tempNameString);
8728	if (inSumtCommand == NO && inComparetreeCommand == NO)
8729	FreePolyTree (userTree[treeIndex]);
8730	return (ERROR);
8731	}
8732	bSetIndex = i;
8733
8734	sscanf (tkn, "%lf", &tempD);
8735	t->effectiveBrLen[bSetIndex][pp->index] = tempD;
8736	foundB = NO;
8737	expecting = Expecting(RIGHTCOMMENT);
8738	}
8739	else if (foundE == YES)
8740	{
8741	if (foundColon == NO)
8742	{
8743	/* we only know now that name is complete if it does not have curlies in it */
8744	foundName = NO;
8745
8746	/* find the right event set */
8747	for (i=0; i<t->nESets; i++)
8748	if (strcmp(t->eSetName[i],tempNameString) == 0)
8749	break;
8750	if (i == t->nESets)
8751	{
8752	MrBayesPrint ("%s Could not find event set '%s'\n", spacer, tempNameString);
8753	if (inSumtCommand == NO && inComparetreeCommand == NO)
8754	FreePolyTree (userTree[treeIndex]);
8755	return (ERROR);
8756	}
8757	eSetIndex = i;
8758
8759	sscanf (tkn, "%d", &tempInt);
8760	if (tempInt < 0)
8761	{
8762	MrBayesPrint ("%s Wrong number of events (%d) for event set '%s'\n", spacer, tempInt, t->eSetName[eSetIndex]);
8763	if (inSumtCommand == NO && inComparetreeCommand == NO)
8764	FreePolyTree (userTree[treeIndex]);
8765	return (ERROR);
8766	}
8767	t->nEvents[eSetIndex][pp->index] = tempInt;
8768	if (tempInt > 0)
8769	{
8770	t->position[eSetIndex][pp->index] = (MrBFlt *) SafeCalloc (tempInt, sizeof(MrBFlt));
8771	t->rateMult[eSetIndex][pp->index] = (MrBFlt *) SafeCalloc (tempInt, sizeof(MrBFlt));
8772	expecting = Expecting (COLON);
8773	if (inSumtCommand == YES \|\| inComparetreeCommand == YES)
8774	expecting \|= Expecting (RIGHTCOMMENT); /* we allow empty event specifications in sumt and comparetree */
8775	}
8776	else
8777	expecting = Expecting (RIGHTCOMMENT);
8778	eventIndex = 0;
8779	}
8780	else if (foundFirst == NO)
8781	{
8782	/* processing the first number in the cpp event pair <position rate>*/
8783	sscanf (tkn, "%lf", &tempD);
8784	t->position[eSetIndex][pp->index][eventIndex] = tempD;
8785	expecting = Expecting(NUMBER);
8786	foundFirst = YES;
8787	}
8788	else
8789	{
8790	/* processing the second number in the cpp event pair <position rate>*/
8791	foundFirst = NO;
8792	sscanf (tkn, "%lf", &tempD);
8793	t->rateMult[eSetIndex][pp->index][eventIndex] = tempD;
8794	#if defined (PRINT_RATEMULTIPLIERS_CPP)
8795	//if(rateMultfp!=NULL)
8796	// fprintf(rateMultfp,"%s\n",tkn);
8797	#endif
8798	eventIndex++;
8799	if (eventIndex == t->nEvents[eSetIndex][pp->index])
8800	{
8801	expecting = Expecting(RIGHTPAR);
8802	foundColon = NO;
8803	}
8804	else
8805	expecting = Expecting(COMMA);
8806	}
8807	}
8808	else if (foundColon == YES)
8809	{
8810	/* branch length */
8811	sscanf (tkn, "%lf", &tempD);
8812	pp->length = tempD;
8813	foundColon = NO;
8814	t->brlensDef = YES;
8815	expecting = Expecting(COMMA);
8816	expecting \|= Expecting(RIGHTPAR);
8817	expecting \|= Expecting(LEFTCOMMENT);
8818	lastExpecting = expecting;
8819	}
8820	else /* taxon identifier */
8821	{
8822	if (isTranslateDef == YES)
8823	{
8824	/* we are using the translation table */
8825	if (CheckString (transTo, numTranslates, tkn, &index) == ERROR)
8826	{
8827	MrBayesPrint ("%s Could not find token '%s' in taxon translation table\n", spacer, tkn);
8828	if (inSumtCommand == NO && inComparetreeCommand == NO)
8829	FreePolyTree (userTree[treeIndex]);
8830	return (ERROR);
8831	}
8832	strcpy (tempName, transFrom[index]);
8833	if (isTranslateDiff == NO && CheckString (taxaNames, numTaxa, tempName, &index) == ERROR)
8834	{
8835	MrBayesPrint ("%s Could not find taxon '%s' in list of taxa\n", spacer, tkn);
8836	if (inSumtCommand == NO && inComparetreeCommand == NO)
8837	FreePolyTree (userTree[treeIndex]);
8838	return (ERROR);
8839	}
8840	if (tempSet[index] == YES)
8841	{
8842	MrBayesPrint ("%s Taxon name '%s' already used in tree\n", spacer, tkn);
8843	if (inSumtCommand == NO && inComparetreeCommand == NO)
8844	FreePolyTree (userTree[treeIndex]);
8845	return (ERROR);
8846	}
8847	tempSet[index] = YES;
8848	strcpy (pp->label, tempName);
8849	pp->index = index;
8850	}
8851	else
8852	{
8853	/* Simply use taxon number; first check to see if the name is in the list of taxon names. */
8854	if (CheckString (taxaNames, numTaxa, tkn, &index) == ERROR)
8855	{
8856	/* The number could not be found as a taxon name in the list of taxon names. We will
8857	assume that the user has then input taxa as numbers and not the names. */
8858	sscanf (tkn, "%d", &index);
8859	if (index < 1 \|\| index > numTaxa)
8860	{
8861	MrBayesPrint ("%s Taxon number %d is out of range\n", spacer, index);
8862	if (inSumtCommand == NO && inComparetreeCommand == NO)
8863	FreePolyTree (userTree[treeIndex]);
8864	return (ERROR);
8865	}
8866	index--;
8867	if (tempSet[index] == YES)
8868	{
8869	MrBayesPrint ("%s Taxon name %d has already been used in tree '%s'\n", spacer, index+1, t->name);
8870	if (inSumtCommand == NO && inComparetreeCommand == NO)
8871	FreePolyTree (userTree[treeIndex]);
8872	return (ERROR);
8873	}
8874	}
8875	else
8876	{
8877	/* The number is in the list of taxon names */
8878	if (index < 0 \|\| index >= numTaxa)
8879	{
8880	MrBayesPrint ("%s Taxon name %s could not be found\n", spacer, tkn);
8881	if (inSumtCommand == NO && inComparetreeCommand == NO)
8882	FreePolyTree (userTree[treeIndex]);
8883	return (ERROR);
8884	}
8885	if (tempSet[index] == YES)
8886	{
8887	MrBayesPrint ("%s Taxon %d has already been used in tree '%s'\n", spacer, index+1, t->name);
8888	if (inSumtCommand == NO && inComparetreeCommand == NO)
8889	FreePolyTree (userTree[treeIndex]);
8890	return (ERROR);
8891	}
8892	}
8893	tempSet[index] = YES;
8894	strcpy (pp->label, taxaNames[index]);
8895	pp->index = index;
8896	}
8897	expecting = Expecting(COMMA);
8898	expecting \|= Expecting(COLON);
8899	expecting \|= Expecting(RIGHTPAR);
8900	expecting \|= Expecting(LEFTCOMMENT);
8901	lastExpecting = expecting;
8902	}
8903	}
8904	else if (expecting == Expecting(LEFTCOMMENT))
8905	{
8906	expecting = Expecting(AMPERSAND);
8907	foundComment = YES;
8908	}
8909	else if (expecting == Expecting(RIGHTCOMMENT))
8910	{
8911	if (foundEqual == NO)
8912	{
8913	/* We may have a complete name of a set of branch parameters, which needs to be recorded */
8914	if (foundName == YES)
8915	{
8916	if (foundE == YES)
8917	{
8918	t->eSetName[t->nESets-1] = (char *) SafeCalloc (strlen(tempNameString)+1,sizeof(char));
8919	strcat(t->eSetName[t->nESets-1],tempNameString);
8920	}
8921	else if (foundB == YES)
8922	{
8923	t->bSetName[t->nBSets-1] = (char *) SafeCalloc (strlen(tempNameString)+1,sizeof(char));
8924	strcat(t->bSetName[t->nBSets-1],tempNameString);
8925	}
8926	else if (foundN == YES)
8927	{
8928	t->popSizeSetName = (char *) SafeCalloc (strlen(tempNameString)+1,sizeof(char));
8929	strcpy(t->popSizeSetName,tempNameString);
8930	}
8931	foundName = NO;
8932	}
8933	expecting = Expecting(EQUALSIGN);
8934	}
8935	else
8936	{
8937	if (pp->anc == NULL)
8938	{
8939	if (pp->left == NULL)
8940	expecting = Expecting(LEFTPAR);
8941	else
8942	expecting = Expecting(SEMICOLON);
8943	}
8944	else if (pp == pp->anc->left)
8945	expecting = Expecting(COMMA);
8946	else
8947	expecting = Expecting(RIGHTPAR);
8948	}
8949	foundE = foundB = foundN = NO;
8950	expecting \|= Expecting(LEFTCOMMENT);
8951	}
8952	else if (expecting == Expecting(AMPERSAND))
8953	{
8954	foundAmpersand = YES;
8955	foundComment = NO;
8956	expecting = Expecting (ALPHA);
8957	}
8958	else if (foundComment == YES)
8959	{
8960	numComments++;
8961	foundComment = NO;
8962	}
8963	else if (expecting == Expecting(LEFTCURL))
8964	{
8965	if( foundName == YES)
8966	{
8967	foundCurly=YES;
8968	SafeStrcat (&tempNameString,"{");
8969	expecting = Expecting(NUMBER) \| Expecting(ALPHA);
8970	}
8971	else
8972	return(ERROR);
8973	}
8974	else if (expecting == Expecting(RIGHTCURL))
8975	{
8976	if( foundName == YES)
8977	{
8978	SafeStrcat (&tempNameString,"}");
8979	foundCurly=NO;
8980	if (foundEqual == NO)
8981	{
8982	/* We are processing a name of a set of branch params in the header of a tree. */
8983	expecting = Expecting(RIGHTCOMMENT);
8984	}
8985	else
8986	{
8987	/* We are processing a param value of a branch param set */
8988	expecting = Expecting(NUMBER);
8989	}
8990	}
8991	else
8992	return(ERROR);
8993	}
8994	return (NO_ERROR);
8995
8996	MrBayesPrint ("%s", parmName); /* just because I am tired of seeing the unused parameter error msg */
8997
8998	}
8999
9000
9001
9002
9003
9004
9005	int DoUserTree (void)
9006
9007	{
9008	MrBayesPrint ("%s Usertree command deprecated. Define the tree in a treeblock and use 'Startvals' instead.\n", spacer);
9009	return (ERROR);
9010	}
9011
9012
9013
9014
9015
9016	int DoUserTreeParm (char parmName, char tkn)
9017
9018	{
9019	if (expecting == Expecting(EQUALSIGN))
9020	{
9021	expecting = Expecting(LEFTPAR);
9022	expecting \|= Expecting(RIGHTPAR);
9023	expecting \|= Expecting(COLON);
9024	expecting \|= Expecting(NUMBER);
9025	expecting \|= Expecting(ALPHA);
9026	expecting \|= Expecting(SEMICOLON);
9027	}
9028	else if (expecting == Expecting(LEFTPAR))
9029	{
9030	expecting = Expecting(LEFTPAR);
9031	expecting \|= Expecting(ALPHA);
9032	expecting \|= Expecting(NUMBER);
9033	}
9034	else if (expecting == Expecting(ALPHA))
9035	{
9036	expecting = Expecting(COLON);
9037	expecting \|= Expecting(COMMA);
9038	expecting \|= Expecting(RIGHTPAR);
9039	}
9040	else if (expecting == Expecting(NUMBER))
9041	{
9042	expecting = Expecting(COLON);
9043	expecting \|= Expecting(COMMA);
9044	expecting \|= Expecting(RIGHTPAR);
9045	}
9046	else if (expecting == Expecting(COLON))
9047	{
9048	expecting = Expecting(NUMBER);
9049	}
9050	else if (expecting == Expecting(COMMA))
9051	{
9052	expecting = Expecting(LEFTPAR);
9053	expecting \|= Expecting(ALPHA);
9054	expecting \|= Expecting(NUMBER);
9055	}
9056	else if (expecting == Expecting(RIGHTPAR))
9057	{
9058	expecting = Expecting(RIGHTPAR);
9059	expecting \|= Expecting(COMMA);
9060	expecting \|= Expecting(COLON);
9061	expecting \|= Expecting(SEMICOLON);
9062	}
9063	else
9064	return (ERROR);
9065	return (NO_ERROR);
9066	}
9067
9068
9069
9070
9071
9072	int DoVersion (void)
9073
9074	{
9075
9076	MrBayesPrint (" --------------------------------------------------------------------------- \n");
9077	MrBayesPrint (" Version \n");
9078	MrBayesPrint (" \n");
9079	MrBayesPrint (" MrBayes v%s \n", VERSION_NUMBER);
9080	MrBayesPrint (" --------------------------------------------------------------------------- \n");
9081
9082	return (NO_ERROR);
9083
9084	}
9085
9086
9087
9088
9089
9090	SafeLong Expecting (int y)
9091
9092	{
9093
9094	SafeLong x;
9095
9096	x = (SafeLong)pow(2.0, (MrBFlt)y);
9097
9098	return (x);
9099
9100	}
9101
9102
9103
9104
9105
9106	#ifdef HAVE_LIBREADLINE
9107	/* This function is for commandline substitution: first word is always a command */
9108	char command_generator(const char text, int state) {
9109	static int list_index, len;
9110	char *command;
9111
9112	if(state==0)
9113	{
9114	list_index=0;
9115	len= (int) strlen(text);
9116	}
9117	while ((command=commands[list_index].string)!=NULL)
9118	{
9119	list_index++;
9120	if (strncasecmp(command,text,len)==0)
9121	/* memory is freed by the readline library so we need a strdup here */
9122	return strdup(command);
9123	}
9124	return (char *)NULL;
9125	}
9126	#endif
9127
9128
9129
9130	int FindValidCommand (char tk, int numMatches)
9131
9132	{
9133
9134	int i, j, tkLen, targetLen, numDiff;
9135	CmdType *p;
9136
9137	p = commands + 0;
9138	tkLen = (int) strlen(tk);
9139
9140	(*numMatches) = 0;
9141	for (i=0; i<NUMCOMMANDS; i++)
9142	{
9143	targetLen = (int) strlen(p->string);
9144	if (tkLen <= targetLen)
9145	{
9146	for (j=0, numDiff=0; j<tkLen; j++)
9147	{
9148	if (ChangeCase(tk[j]) != ChangeCase(p->string[j]))
9149	numDiff++;
9150	}
9151	if (numDiff == 0)
9152	{
9153	(*numMatches)++;
9154	commandPtr = p;
9155	if (tkLen == targetLen)
9156	break;
9157	}
9158	}
9159	p++;
9160	}
9161
9162	inValidCommand = NO;
9163	if (*numMatches == 1)
9164	{
9165	inValidCommand = YES;
9166	return (NO_ERROR);
9167	}
9168	else
9169	return (ERROR);
9170
9171	}
9172
9173
9174
9175
9176
9177	int FindValidParam (char tk, int numMatches)
9178
9179	{
9180
9181	int i, j, tkLen, targetLen, numDiff;
9182	CmdType *p;
9183	ParmInfoPtr q;
9184
9185	if (commandPtr)
9186	p = commandPtr;
9187	else
9188	{
9189	MrBayesPrint ("%s Command pointer is NULL\n", spacer);
9190	return (ERROR);
9191	}
9192	tkLen = (int) strlen(tk);
9193
9194	*numMatches = 0;
9195	for (i=0; i<p->numParms; i++)
9196	{
9197	q = paramTable + (p->parmList[i]);
9198	targetLen = (int) strlen(q->string);
9199	/printf ("%s %d (%s %d)\n", q->string, targetLen, tk, p->numParms);/
9200	if (!strcmp(q->string, "Xxxxxxxxxx"))
9201	{
9202	(*numMatches)++;
9203	paramPtr = q;
9204	}
9205	else if (tkLen <= targetLen)
9206	{
9207	for (j=0, numDiff=0; j<tkLen; j++)
9208	{
9209	if (ChangeCase(tk[j]) != ChangeCase(q->string[j]))
9210	numDiff++;
9211	}
9212	if (numDiff == 0)
9213	{
9214	(*numMatches)++;
9215	paramPtr = q;
9216	if (tkLen == targetLen)
9217	break;
9218	}
9219	}
9220	}
9221
9222	if (*numMatches == 1)
9223	return (NO_ERROR);
9224	else
9225	return (ERROR);
9226
9227	}
9228
9229
9230
9231
9232
9233	int FreeCharacters (void)
9234
9235	{
9236
9237	int i, memoryLetFree;
9238
9239	memoryLetFree = NO;
9240
9241	if (memAllocs[ALLOC_TMPSET] == YES)
9242	{
9243	if (numChar > numTaxa)
9244	tempSet = (int ) SafeRealloc ((void ) tempSet, (size_t)(numTaxa*sizeof(int)));
9245	tempSetNeg = (int ) SafeRealloc ((void ) tempSetNeg, (size_t)(numTaxa*sizeof(int)));
9246	}
9247	if (memAllocs[ALLOC_MATRIX] == YES)
9248	{
9249	free (matrix);
9250	matrix = NULL;
9251	defMatrix = NO;
9252	memAllocs[ALLOC_MATRIX] = NO;
9253	memoryLetFree = YES;
9254	}
9255	if (memAllocs[ALLOC_CHARINFO] == YES)
9256	{
9257	free (charInfo);
9258	charInfo = NULL;
9259	memAllocs[ALLOC_CHARINFO] = NO;
9260	memoryLetFree = YES;
9261	}
9262	if (memAllocs[ALLOC_CHARSETS] == YES)
9263	{
9264	for (i=0; i<numCharSets; i++)
9265	{
9266	free (charSetNames[i]);
9267	free (charSet[i]);
9268	}
9269	free (charSetNames);
9270	free (charSet);
9271	charSetNames = NULL;
9272	charSet = NULL;
9273	numCharSets = 0;
9274	memAllocs[ALLOC_CHARSETS] = NO;
9275	memoryLetFree = YES;
9276	}
9277	if (memAllocs[ALLOC_PARTITIONS] == YES)
9278	{
9279	for (i=0; i<numDefinedPartitions; i++)
9280	free (partitionNames[i]);
9281	free (partitionNames);
9282	partitionNames = NULL;
9283	for (i=0; i<numChar; i++)
9284	free (partitionId[i]);
9285	free (partitionId);
9286	numDefinedPartitions = 0;
9287	memAllocs[ALLOC_PARTITIONS] = NO;
9288	memoryLetFree = YES;
9289	}
9290	if (memAllocs[ALLOC_PARTITIONVARS] == YES)
9291	{
9292	free (numVars);
9293	numVars = NULL;
9294	free (tempNum);
9295	tempNum = NULL;
9296	free (activeParams[0]);
9297	activeParams[0] = NULL;
9298	free (linkTable[0]);
9299	linkTable[0] = NULL;
9300	tempLinkUnlinkVec = NULL;
9301	activeParts = NULL;
9302	tempLinkUnlinkVec = NULL;
9303	for (i=0; i<NUM_LINKED; i++)
9304	{
9305	linkTable[i] = NULL;
9306	activeParams[i] = NULL;
9307	}
9308	memAllocs[ALLOC_PARTITIONVARS] = NO;
9309	memoryLetFree = YES;
9310	}
9311
9312	ResetCharacterFlags();
9313
9314	return (NO_ERROR);
9315	}
9316
9317
9318
9319
9320
9321	int FreeMatrix (void)
9322
9323	{
9324
9325	if (FreeCharacters() == ERROR)
9326	return ERROR;
9327
9328	return (FreeTaxa());
9329
9330	}
9331
9332
9333
9334
9335
9336	int FreeTaxa (void)
9337
9338	{
9339	int i, memoryLetFree;
9340
9341	memoryLetFree = NO;
9342	if (memAllocs[ALLOC_TAXA] == YES)
9343	{
9344	if (taxaNames)
9345	{
9346	for (i=0; i<numTaxa; i++)
9347	free (taxaNames[i]);
9348	}
9349	free (taxaNames);
9350	taxaNames = NULL;
9351	free (taxaInfo);
9352	taxaInfo = NULL;
9353	free (tipCalibration);
9354	tipCalibration = NULL;
9355	numTaxa = 0;
9356	memAllocs[ALLOC_TAXA] = NO;
9357	memoryLetFree = YES;
9358	}
9359	if (memAllocs[ALLOC_TMPSET] == YES)
9360	{
9361	free (tempSet);
9362	tempSet = NULL;
9363	free (tempSetNeg);
9364	tempSetNeg = NULL;
9365	memAllocs[ALLOC_TMPSET] = NO;
9366	memoryLetFree = YES;
9367	}
9368	if (memAllocs[ALLOC_TAXASETS] == YES)
9369	{
9370	for (i=0; i<numTaxaSets; i++)
9371	{
9372	free (taxaSetNames[i]);
9373	free (taxaSet[i]);
9374	}
9375	free (taxaSetNames);
9376	taxaSetNames = NULL;
9377	free (taxaSet);
9378	taxaSet = NULL;
9379	numTaxaSets = 0;
9380	memAllocs[ALLOC_TAXASETS] = NO;
9381	memoryLetFree = YES;
9382	}
9383	if (memAllocs[ALLOC_SPECIESPARTITIONS] == YES)
9384	{
9385	for (i=0; i<numDefinedSpeciespartitions; i++)
9386	free (speciespartitionNames[i]);
9387	free (speciespartitionNames);
9388	speciespartitionNames = NULL;
9389	for (i=0; i<numTaxa; i++)
9390	free (speciespartitionId[i]);
9391	free (speciespartitionId);
9392	speciespartitionId = NULL;
9393	numDefinedSpeciespartitions = 0;
9394	memAllocs[ALLOC_SPECIESPARTITIONS] = NO;
9395	memoryLetFree = YES;
9396	}
9397	if (memAllocs[ALLOC_CONSTRAINTS] == YES)
9398	{
9399	for (i=0; i<numDefinedConstraints; i++)
9400	{
9401	free(definedConstraint[i]);
9402	free(definedConstraintTwo[i]);
9403	free(definedConstraintPruned[i]);
9404	free(definedConstraintTwoPruned[i]);
9405	free (constraintNames[i]);
9406	}
9407	free (definedConstraint);
9408	definedConstraint = NULL;
9409	free (definedConstraintTwo);
9410	definedConstraintTwo = NULL;
9411	free (definedConstraintsType);
9412	definedConstraintsType = NULL;
9413	free (constraintNames);
9414	constraintNames = NULL;
9415	free (nodeCalibration);
9416	nodeCalibration = NULL;
9417	numDefinedConstraints = 0;
9418	free (tempActiveConstraints);
9419	tempActiveConstraints = NULL;
9420	memAllocs[ALLOC_CONSTRAINTS] = NO;
9421	memoryLetFree = YES;
9422	}
9423	if (numUserTrees > 0)
9424	{
9425	MrBayesPrint ("%s Deleting user trees\n", spacer);
9426	for (i=0; i<numUserTrees; i++)
9427	{
9428	FreePolyTree(userTree[i]);
9429	userTree[i] = NULL;
9430	}
9431	numUserTrees = 0;
9432	}
9433
9434	FreeCharacters();
9435
9436	if (memoryLetFree == YES)
9437	MrBayesPrint ("%s Deleting previously defined taxon set\n", spacer);
9438
9439	/* reinitialize taxa variables */
9440	ResetTaxaFlags();
9441
9442	return NO_ERROR;
9443	}
9444
9445
9446
9447
9448
9449	int GetNumPartDivisions (int n)
9450
9451	{
9452
9453	int i, maxDiv, numDivs, *divFound;
9454
9455	maxDiv = 0;
9456	for (i=0; i<numChar; i++)
9457	if (partitionId[i][n] > maxDiv)
9458	maxDiv = partitionId[i][n];
9459
9460	divFound = (int *) SafeCalloc (maxDiv, sizeof(int));
9461
9462	for (i=0; i<maxDiv; i++)
9463	divFound[i] = NO;
9464
9465	for (i=0; i<numChar; i++)
9466	divFound[partitionId[i][n]] = YES;
9467
9468	numDivs = 0;
9469	for (i=0; i<maxDiv; i++)
9470	if (divFound[i] == YES)
9471	numDivs++;
9472
9473	free (divFound);
9474
9475	return (numDivs);
9476
9477	}
9478
9479
9480
9481
9482
9483	int GetToken (char token, int tokenType, char **sourceH)
9484
9485	{
9486
9487	int allNumbers, foundExp, foundExpSign;
9488	register char *temp;
9489	char *tempMax;
9490
9491	(*tokenType) = 0;
9492	temp = token;
9493	tempMax = temp + CMD_STRING_LENGTH - 10;
9494
9495	while (IsWhite(sourceH) == 1 \|\| IsWhite(sourceH) == 2)
9496	{
9497	if (IsWhite(**sourceH) == 2)
9498	{
9499	*tokenType = RETURNSYMBOL;
9500	/* foundNewLine = YES; Why is this commented out?? */
9501	/* MrBayesPrint ("RETURN\n"); */
9502	}
9503	++(*sourceH);
9504	}
9505
9506	if (readWord == YES && **sourceH != '"')
9507	{
9508	if (**sourceH==';')
9509	{
9510	*temp++ = ';';
9511	*tokenType = SEMICOLON;
9512	}
9513	else
9514	{
9515	while (isgraph(sourceH) && sourceH!=';')
9516	{
9517	if( temp > tempMax )
9518	{
9519	*tokenType = NOTHING;
9520	token[20]='\0';
9521	MrBayesPrint ("%s Error while parsing a string. Token \"%s...[followed by at least %d more charectors]\" is too long.\n", spacer,token,tempMax-token-20 );
9522	MrBayesPrint ("%s Maximum allowed lenght of a token is %d\n", spacer,tempMax-token );
9523	return (ERROR);
9524	}
9525	temp++ = (*sourceH)++;
9526	}
9527	*tokenType = ALPHA;
9528	}
9529	*temp = '\0';
9530	readWord = NO;
9531	return (NO_ERROR);;
9532	}
9533
9534	*tokenType = UNKNOWN_TOKEN_TYPE;
9535	if (IsIn(**sourceH,"="))
9536	{
9537	temp++ = (*sourceH)++;
9538	*tokenType = EQUALSIGN;
9539	}
9540	else if (IsIn(**sourceH,";"))
9541	{
9542	temp++ = (*sourceH)++;
9543	*tokenType = SEMICOLON;
9544	}
9545	else if (IsIn(**sourceH,":"))
9546	{
9547	temp++ = (*sourceH)++;
9548	*tokenType = COLON;
9549	}
9550	else if (IsIn(**sourceH,","))
9551	{
9552	temp++ = (*sourceH)++;
9553	*tokenType = COMMA;
9554	}
9555	else if (IsIn(**sourceH,"#"))
9556	{
9557	temp++ = (*sourceH)++;
9558	*tokenType = POUNDSIGN;
9559	}
9560	else if (IsIn(**sourceH,"("))
9561	{
9562	temp++ = (*sourceH)++;
9563	*tokenType = LEFTPAR;
9564	}
9565	else if (IsIn(**sourceH,")"))
9566	{
9567	temp++ = (*sourceH)++;
9568	*tokenType = RIGHTPAR;
9569	}
9570	else if (IsIn(**sourceH,"{"))
9571	{
9572	temp++ = (*sourceH)++;
9573	*tokenType = LEFTCURL;
9574	}
9575	else if (IsIn(**sourceH,"}"))
9576	{
9577	temp++ = (*sourceH)++;
9578	*tokenType = RIGHTCURL;
9579	}
9580	else if (IsIn(**sourceH,"["))
9581	{
9582	temp++ = (*sourceH)++;
9583	*tokenType = LEFTCOMMENT;
9584	}
9585	else if (IsIn(**sourceH,"]"))
9586	{
9587	temp++ = (*sourceH)++;
9588	*tokenType = RIGHTCOMMENT;
9589	}
9590	else if (IsIn(**sourceH,"?"))
9591	{
9592	temp++ = (*sourceH)++;
9593	*tokenType = QUESTIONMARK;
9594	}
9595	else if (IsIn(**sourceH,"-"))
9596	{
9597	temp++ = (*sourceH)++;
9598	*tokenType = DASH;
9599	}
9600	else if (IsIn(**sourceH,"$"))
9601	{
9602	temp++ = (*sourceH)++;
9603	*tokenType = DOLLAR;
9604	}
9605	else if (IsIn(**sourceH,"\"") && readWord == YES)
9606	{
9607	(*sourceH)++;
9608	while(sourceH != '"' && sourceH != '\0')
9609	{
9610	if( temp > tempMax )
9611	{
9612	*tokenType = NOTHING;
9613	token[20]='\0';
9614	MrBayesPrint ("%s Error while parsing a string. Token \"%s...[followed by at least %d more charectors]\" is too long.\n", spacer,token,tempMax-token-20 );
9615	MrBayesPrint ("%s Maximum allowed lenght of a token is %d\n", spacer,tempMax-token );
9616	return (ERROR);
9617	}
9618	temp++ = ((*sourceH)++);
9619	}
9620	*temp='\0';
9621	*tokenType = ALPHA;
9622	(*sourceH)++;
9623	readWord = NO;
9624	}
9625	else if (IsIn(**sourceH,"abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ_0123456789."))
9626	{
9627	if (IsIn(**sourceH,"0123456789."))
9628	allNumbers = TRUE;
9629	else
9630	allNumbers = FALSE;
9631	foundExp = foundExpSign = FALSE;
9632	temp++ = (*sourceH)++;
9633	while(IsIn(**sourceH,"abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ_0123456789.-+"))
9634	{
9635	if( temp > tempMax )
9636	{
9637	*tokenType = NOTHING;
9638	token[20]='\0';
9639	MrBayesPrint ("%s Error while parsing a string. Token \"%s...[followed by at least %d more charectors]\" is too long.\n", spacer,token,tempMax-token-20 );
9640	MrBayesPrint ("%s Maximum allowed lenght of a token is %d\n", spacer,tempMax-token );
9641	return (ERROR);
9642	}
9643	if(allNumbers == TRUE && !IsIn((sourceH)[-1],"Ee") && *sourceH=='-')
9644	break;
9645	else if (allNumbers == TRUE && IsIn(**sourceH,"Ee") && foundExp == NO)
9646	foundExp = TRUE;
9647	else if (allNumbers == TRUE && IsIn(*sourceH,"+-") && IsIn((sourceH)[-1],"Ee"))
9648	foundExpSign = TRUE;
9649	else if (!IsIn(**sourceH,"0123456789."))
9650	allNumbers = FALSE;
9651	temp++ = (*sourceH)++;
9652	}
9653	if (allNumbers == TRUE)
9654	*tokenType = NUMBER;
9655	else
9656	*tokenType = ALPHA;
9657	}
9658	else if (IsIn(*sourceH,""))
9659	{
9660	temp++ = (*sourceH)++;
9661	*tokenType = ASTERISK;
9662	}
9663	else if (IsIn(**sourceH,"/"))
9664	{
9665	temp++ = (*sourceH)++;
9666	*tokenType = FORWARDSLASH;
9667	}
9668	else if (IsIn(**sourceH,"'\\'"))
9669	{
9670	temp++ = (*sourceH)++;
9671	*tokenType = BACKSLASH;
9672	}
9673	else if (IsIn(**sourceH,"!"))
9674	{
9675	temp++ = (*sourceH)++;
9676	*tokenType = EXCLAMATIONMARK;
9677	}
9678	else if (IsIn(**sourceH,"%"))
9679	{
9680	temp++ = (*sourceH)++;
9681	*tokenType = PERCENT;
9682	}
9683	else if (IsIn(**sourceH,"\""))
9684	{
9685	temp++ = (*sourceH)++;
9686	*tokenType = QUOTATIONMARK;
9687	}
9688	else if (IsIn(**sourceH,"&"))
9689	{
9690	temp++ = (*sourceH)++;
9691	*tokenType = AMPERSAND;
9692	}
9693	else if (IsIn(**sourceH,"~+^@\|{}`><"))
9694	{
9695	temp++ = (*sourceH)++;
9696	*tokenType = WEIRD;
9697	}
9698
9699	*temp = '\0';
9700	return (NO_ERROR);
9701
9702	}
9703
9704
9705
9706
9707
9708	int GetUserHelp (char *helpTkn)
9709
9710	{
9711
9712	int i, j, k, tempInt;
9713	char yesNoStr[4], tempString[100];
9714	Model *mp;
9715
9716	if (!strcmp(helpTkn, "Begin"))
9717	{
9718	MrBayesPrint (" --------------------------------------------------------------------------- \n");
9719	MrBayesPrint (" Begin \n");
9720	MrBayesPrint (" \n");
9721	MrBayesPrint (" This command is used to format data or commands in the program. The correct \n");
9722	MrBayesPrint (" usage is \n");
9723	MrBayesPrint (" \n");
9724	MrBayesPrint (" begin <data or mrbayes>; \n");
9725	MrBayesPrint (" \n");
9726	MrBayesPrint (" The two valid uses of the \"begin\" command, then, are \n");
9727	MrBayesPrint (" \n");
9728	MrBayesPrint (" begin data; \n");
9729	MrBayesPrint (" begin mrbayes; \n");
9730	MrBayesPrint (" \n");
9731	MrBayesPrint (" The \"data\" specifier is used to specify the beginning of a data block; your \n");
9732	MrBayesPrint (" character data should follow. For example, the following is an example of \n");
9733	MrBayesPrint (" a data block for four taxa and ten DNA sites: \n");
9734	MrBayesPrint (" \n");
9735	MrBayesPrint (" begin data; \n");
9736	MrBayesPrint (" dimensions ntax=4 nchar=10; \n");
9737	MrBayesPrint (" format datatype=dna; \n");
9738	MrBayesPrint (" matrix \n");
9739	MrBayesPrint (" taxon_1 AACGATTCGT \n");
9740	MrBayesPrint (" taxon_2 AAGGATTCCA \n");
9741	MrBayesPrint (" taxon_3 AACGACTCCT \n");
9742	MrBayesPrint (" taxon_4 AAGGATTCCT \n");
9743	MrBayesPrint (" ; \n");
9744	MrBayesPrint (" end; \n");
9745	MrBayesPrint (" \n");
9746	MrBayesPrint (" The other commands -- dimensions, format, and matrix -- are discussed \n");
9747	MrBayesPrint (" in the appropriate help menu. The only thing to note here is that the \n");
9748	MrBayesPrint (" block begins with a \"begin data\" command. The \"mrbayes\" command is \n");
9749	MrBayesPrint (" used to enter commands specific to the MrBayes program into the file. \n");
9750	MrBayesPrint (" This allows you to automatically process commands on execution of the \n");
9751	MrBayesPrint (" program. The following is a simple mrbayes block: \n");
9752	MrBayesPrint (" \n");
9753	MrBayesPrint (" begin mrbayes; \n");
9754	MrBayesPrint (" charset first = 1-10\\3; \n");
9755	MrBayesPrint (" charset second = 2-10\\3; \n");
9756	MrBayesPrint (" charset third = 3-10\\3; \n");
9757	MrBayesPrint (" end; \n");
9758	MrBayesPrint (" \n");
9759	MrBayesPrint (" This mrbayes block sets off the three \"charset\" commands, used to \n");
9760	MrBayesPrint (" predefine some blocks of characters. The mrbayes block can be very useful. \n");
9761	MrBayesPrint (" For example, in this case, it would save you the time of typing the char- \n");
9762	MrBayesPrint (" acter sets each time you executed the file. Also, note that every \n");
9763	MrBayesPrint (" \"begin <data or mrbayes>\" command ends with an \"end\". Finally, you can \n");
9764	MrBayesPrint (" have so-called foreign blocks in the file. An example of a foreign block \n");
9765	MrBayesPrint (" would be \"begin paup\". The program will simply skip this block. This is \n");
9766	MrBayesPrint (" useful because it means that you can use the same file for MrBayes, PAUP* \n");
9767	MrBayesPrint (" or MacClade (although it isn't clear why you would want to use those other \n");
9768	MrBayesPrint (" programs). \n");
9769	MrBayesPrint (" --------------------------------------------------------------------------- \n");
9770	}
9771	else if (!strcmp(helpTkn, "End"))
9772	{
9773	MrBayesPrint (" --------------------------------------------------------------------------- \n");
9774	MrBayesPrint (" End \n");
9775	MrBayesPrint (" \n");
9776	MrBayesPrint (" This command is used to terminate a data or mrbayes block. The correct \n");
9777	MrBayesPrint (" usage is \n");
9778	MrBayesPrint (" \n");
9779	MrBayesPrint (" end; \n");
9780	MrBayesPrint (" \n");
9781	MrBayesPrint (" For more information on this, check the help for the \"begin\" command. \n");
9782	MrBayesPrint (" --------------------------------------------------------------------------- \n");
9783	}
9784	else if (!strcmp(helpTkn, "Endblock"))
9785	{
9786	MrBayesPrint (" --------------------------------------------------------------------------- \n");
9787	MrBayesPrint (" Endblock \n");
9788	MrBayesPrint (" \n");
9789	MrBayesPrint (" This is an older, deprecated version of \"End\", see that command. \n");
9790	MrBayesPrint (" --------------------------------------------------------------------------- \n");
9791	}
9792	else if (!strcmp(helpTkn, "Plot"))
9793	{
9794	MrBayesPrint (" --------------------------------------------------------------------------- \n");
9795	MrBayesPrint (" Plot \n");
9796	MrBayesPrint (" \n");
9797	MrBayesPrint (" This command plots specified parameters in the .p file or one of the .p files \n");
9798	MrBayesPrint (" created during an MCMC analysis. An x-y graph of the parameter over the course\n");
9799	MrBayesPrint (" of the chain is created. The command can be useful for visually diagnosing \n");
9800	MrBayesPrint (" convergence for many of the parameters of the phylogenetic model. The para- \n");
9801	MrBayesPrint (" meter to be plotted is specified by the \"parameter\" option. Several para- \n");
9802	MrBayesPrint (" meters can be plotted at once by using the \"match\" option, which has a \n");
9803	MrBayesPrint (" default value of \"perfect\". For example, if you were to set \"parameter = pi\"\n");
9804	MrBayesPrint (" and \"match = consistentwith\", then all of the state frequency parameters \n");
9805	MrBayesPrint (" would be plotted. You can also set \"match=all\", in which case all of the \n");
9806	MrBayesPrint (" parameters are plotted. \n");
9807	MrBayesPrint (" \n");
9808	MrBayesPrint (" Note that the \"Sump\" command provides a different set of convergence diag- \n");
9809	MrBayesPrint (" nostics tools that you may also want to explore. Unlike \"Plot\", \"Sump\" can\n");
9810	MrBayesPrint (" compare two or more parameter samples and will calculate convergence diagnos- \n");
9811	MrBayesPrint (" tics as wel as parameter summaries for the pooled sample. \n");
9812	MrBayesPrint (" \n");
9813	MrBayesPrint (" Options: \n");
9814	MrBayesPrint (" \n");
9815	MrBayesPrint (" Relburnin -- If this option is set to 'Yes', then a proportion of the \n");
9816	MrBayesPrint (" samples will be discarded as burnin when creating the plot. \n");
9817	MrBayesPrint (" The proportion to be discarded is set with Burninfrac (see \n");
9818	MrBayesPrint (" Burninfrac below). When the Relburnin option is set to 'No', \n");
9819	MrBayesPrint (" then a specific number of samples is discarded instead. This \n");
9820	MrBayesPrint (" number is set by Burnin (see below). Note that the burnin \n");
9821	MrBayesPrint (" setting is shared across the 'comparetree', 'sump' and 'sumt'\n");
9822	MrBayesPrint (" commands. \n");
9823	MrBayesPrint (" Burnin -- Determines the number of samples (not generations) that will \n");
9824	MrBayesPrint (" be discarded when summary statistics are calculated. The \n");
9825	MrBayesPrint (" value of this option is only relevant when Relburnin is set \n");
9826	MrBayesPrint (" to 'No'. \n");
9827	MrBayesPrint (" Burninfrac -- Determines the fraction of samples that will be discarded \n");
9828	MrBayesPrint (" when creating a plot. The value of this parameter is only \n");
9829	MrBayesPrint (" relevant when Relburnin is set to 'Yes'. Example: A value of \n");
9830	MrBayesPrint (" this option of 0.25 means that 25%% of the samples will be \n");
9831	MrBayesPrint (" discarded. \n");
9832	MrBayesPrint (" Filename -- The name of the file to plot. \n");
9833	MrBayesPrint (" Parameter -- Specification of parameters to be plotted. See above for \n");
9834	MrBayesPrint (" details. \n");
9835	MrBayesPrint (" Match -- Specifies how to match parameter names to the Parameter \n");
9836	MrBayesPrint (" specification. See above for details. \n");
9837	MrBayesPrint (" \n");
9838	MrBayesPrint (" Current settings: \n");
9839	MrBayesPrint (" \n");
9840	MrBayesPrint (" Parameter Options Current Setting \n");
9841	MrBayesPrint (" ------------------------------------------------------------ \n");
9842	MrBayesPrint (" Relburnin Yes/No %s \n", chainParams.relativeBurnin == YES ? "Yes" : "No");
9843	MrBayesPrint (" Burnin <number> %d \n", chainParams.chainBurnIn);
9844	MrBayesPrint (" Burninfrac <number> %1.2lf \n", chainParams.burninFraction);
9845	MrBayesPrint (" Filename <name> %s \n", plotParams.plotFileName);
9846	MrBayesPrint (" Parameter <name> %s \n", plotParams.parameter);
9847	MrBayesPrint (" Match Perfect/Consistentwith/All %s \n", plotParams.match);
9848	MrBayesPrint (" \n");
9849	MrBayesPrint (" --------------------------------------------------------------------------- \n");
9850	}
9851	else if (!strcmp(helpTkn, "Dimensions"))
9852	{
9853	MrBayesPrint (" --------------------------------------------------------------------------- \n");
9854	MrBayesPrint (" Dimensions \n");
9855	MrBayesPrint (" \n");
9856	MrBayesPrint (" This command is used in a data block to define the number of taxa and \n");
9857	MrBayesPrint (" characters. The correct usage is \n");
9858	MrBayesPrint (" \n");
9859	MrBayesPrint (" dimensions ntax=<number> nchar=<number> \n");
9860	MrBayesPrint (" \n");
9861	MrBayesPrint (" The dimensions must be the first command in a data block. The following \n");
9862	MrBayesPrint (" provides an example of the proper use of this command: \n");
9863	MrBayesPrint (" \n");
9864	MrBayesPrint (" begin data; \n");
9865	MrBayesPrint (" dimensions ntax=4 nchar=10; \n");
9866	MrBayesPrint (" format datatype=dna; \n");
9867	MrBayesPrint (" matrix \n");
9868	MrBayesPrint (" taxon_1 AACGATTCGT \n");
9869	MrBayesPrint (" taxon_2 AAGGATTCCA \n");
9870	MrBayesPrint (" taxon_3 AACGACTCCT \n");
9871	MrBayesPrint (" taxon_4 AAGGATTCCT \n");
9872	MrBayesPrint (" ; \n");
9873	MrBayesPrint (" end; \n");
9874	MrBayesPrint (" \n");
9875	MrBayesPrint (" Here, the dimensions command tells MrBayes to expect a matrix with four \n");
9876	MrBayesPrint (" taxa and 10 characters. \n");
9877	MrBayesPrint (" --------------------------------------------------------------------------- \n");
9878	}
9879	else if (!strcmp(helpTkn, "Format"))
9880	{
9881	MrBayesPrint (" --------------------------------------------------------------------------- \n");
9882	MrBayesPrint (" Format \n");
9883	MrBayesPrint (" \n");
9884	MrBayesPrint (" This command is used in a data block to define the format of the char- \n");
9885	MrBayesPrint (" acter matrix. The correct usage is \n");
9886	MrBayesPrint (" \n");
9887	MrBayesPrint (" format datatype=<name> ... <parameter>=<option> \n");
9888	MrBayesPrint (" \n");
9889	MrBayesPrint (" The format command must be the second command in a data block. The following \n");
9890	MrBayesPrint (" provides an example of the proper use of this command: \n");
9891	MrBayesPrint (" \n");
9892	MrBayesPrint (" begin data; \n");
9893	MrBayesPrint (" dimensions ntax=4 nchar=10; \n");
9894	MrBayesPrint (" format datatype=dna gap=-; \n");
9895	MrBayesPrint (" matrix \n");
9896	MrBayesPrint (" taxon_1 AACGATTCGT \n");
9897	MrBayesPrint (" taxon_2 AAGGAT--CA \n");
9898	MrBayesPrint (" taxon_3 AACGACTCCT \n");
9899	MrBayesPrint (" taxon_4 AAGGATTCCT \n");
9900	MrBayesPrint (" ; \n");
9901	MrBayesPrint (" end; \n");
9902	MrBayesPrint (" \n");
9903	MrBayesPrint (" Here, the format command tells MrBayes to expect a matrix with DNA char- \n");
9904	MrBayesPrint (" acters and with gaps coded as \"-\". \n");
9905	MrBayesPrint (" \n");
9906	MrBayesPrint (" The following are valid options for format: \n");
9907	MrBayesPrint (" \n");
9908	MrBayesPrint (" Datatype -- This parameter MUST BE INCLUDED in the format command. More- \n");
9909	MrBayesPrint (" over, it must be the first parameter in the line. The \n");
9910	MrBayesPrint (" datatype command specifies what type of characters are \n");
9911	MrBayesPrint (" in the matrix. The following are valid options: \n");
9912	MrBayesPrint (" Datatype = Dna: DNA states (A,C,G,T,R,Y,M,K,S,W,H,B, \n");
9913	MrBayesPrint (" V,D,N) \n");
9914	MrBayesPrint (" Datatype = Rna: DNA states (A,C,G,U,R,Y,M,K,S,W,H,B, \n");
9915	MrBayesPrint (" V,D,N) \n");
9916	MrBayesPrint (" Datatype = Protein: Amino acid states (A,R,N,D,C,Q,E, \n");
9917	MrBayesPrint (" G,H,I,L,K,M,F,P,S,T,W,Y,V) \n");
9918	MrBayesPrint (" Datatype = Restriction: Restriction site (0,1) states \n");
9919	MrBayesPrint (" Datatype = Standard: Morphological (0,1) states \n");
9920	MrBayesPrint (" Datatype = Continuous: Real number valued states \n");
9921	MrBayesPrint (" Datatype = Mixed(<type>:<range>,...,<type>:<range>): A \n");
9922	MrBayesPrint (" mixture of the above datatypes. For example, \n");
9923	MrBayesPrint (" \"datatype=mixed(dna:1-100,protein:101-200)\" \n");
9924	MrBayesPrint (" would specify a mixture of DNA and amino acid \n");
9925	MrBayesPrint (" characters with the DNA characters occupying \n");
9926	MrBayesPrint (" the first 100 sites and the amino acid char- \n");
9927	MrBayesPrint (" acters occupying the last 100 sites. \n");
9928	MrBayesPrint (" \n");
9929	MrBayesPrint (" Interleave -- This parameter specifies whether the data matrix is in \n");
9930	MrBayesPrint (" interleave format. The valid options are \"Yes\" or \"No\", \n");
9931	MrBayesPrint (" with \"No\" as the default. An interleaved matrix looks like \n");
9932	MrBayesPrint (" \n");
9933	MrBayesPrint (" format datatype=dna gap=- interleave=yes; \n");
9934	MrBayesPrint (" matrix \n");
9935	MrBayesPrint (" taxon_1 AACGATTCGT \n");
9936	MrBayesPrint (" taxon_2 AAGGAT--CA \n");
9937	MrBayesPrint (" taxon_3 AACGACTCCT \n");
9938	MrBayesPrint (" taxon_4 AAGGATTCCT \n");
9939	MrBayesPrint (" \n");
9940	MrBayesPrint (" taxon_1 CCTGGTAC \n");
9941	MrBayesPrint (" taxon_2 CCTGGTAC \n");
9942	MrBayesPrint (" taxon_3 ---GGTAG \n");
9943	MrBayesPrint (" taxon_4 ---GGTAG \n");
9944	MrBayesPrint (" ; \n");
9945	MrBayesPrint (" \n");
9946	MrBayesPrint (" Gap -- This parameter specifies the format for gaps. Note that \n");
9947	MrBayesPrint (" gap character can only be a single character and that it \n");
9948	MrBayesPrint (" cannot correspond to a standard state (e.g., A,C,G,T,R,Y, \n");
9949	MrBayesPrint (" M,K,S,W,H,B,V,D,N for nucleotide data). \n");
9950	MrBayesPrint (" \n");
9951	MrBayesPrint (" Missing -- This parameter specifies the format for missing data. Note \n");
9952	MrBayesPrint (" that the missing character can only be a single character and \n");
9953	MrBayesPrint (" cannot correspond to a standard state (e.g., A,C,G,T,R,Y, \n");
9954	MrBayesPrint (" M,K,S,W,H,B,V,D,N for nucleotide data). This is often an \n");
9955	MrBayesPrint (" unnecessary parameter to set because many data types, such \n");
9956	MrBayesPrint (" as nucleotide or amino acid, already have a missing char- \n");
9957	MrBayesPrint (" acter specified. However, for morphological or restriction \n");
9958	MrBayesPrint (" site data, \"missing=?\" is often used to specify ambiguity \n");
9959	MrBayesPrint (" or unobserved data. \n");
9960	MrBayesPrint (" \n");
9961	MrBayesPrint (" Matchchar -- This parameter specifies the matching character for the \n");
9962	MrBayesPrint (" matrix. For example, \n");
9963	MrBayesPrint (" \n");
9964	MrBayesPrint (" format datatype=dna gap=- matchchar=.; \n");
9965	MrBayesPrint (" matrix \n");
9966	MrBayesPrint (" taxon_1 AACGATTCGT \n");
9967	MrBayesPrint (" taxon_2 ..G...--CA \n");
9968	MrBayesPrint (" taxon_3 .....C..C. \n");
9969	MrBayesPrint (" taxon_4 ..G.....C. \n");
9970	MrBayesPrint (" ; \n");
9971	MrBayesPrint (" \n");
9972	MrBayesPrint (" is equivalent to \n");
9973	MrBayesPrint (" \n");
9974	MrBayesPrint (" format datatype=dna gap=-; \n");
9975	MrBayesPrint (" matrix \n");
9976	MrBayesPrint (" taxon_1 AACGATTCGT \n");
9977	MrBayesPrint (" taxon_2 AAGGAT--CA \n");
9978	MrBayesPrint (" taxon_3 AACGACTCCT \n");
9979	MrBayesPrint (" taxon_4 AAGGATTCCT \n");
9980	MrBayesPrint (" ; \n");
9981	MrBayesPrint (" \n");
9982	MrBayesPrint (" The only non-standard NEXUS format option is the use of the \"mixed\", \n");
9983	MrBayesPrint (" \"restriction\", \"standard\" and \"continuous\" datatypes. Hence, if \n");
9984	MrBayesPrint (" you use any of these datatype specifiers, a program like PAUP* or \n");
9985	MrBayesPrint (" MacClade will report an error (as they should because MrBayes is not \n");
9986	MrBayesPrint (" strictly NEXUS compliant). \n");
9987	MrBayesPrint (" --------------------------------------------------------------------------- \n");
9988	}
9989	else if (!strcmp(helpTkn, "Matrix"))
9990	{
9991	MrBayesPrint (" --------------------------------------------------------------------------- \n");
9992	MrBayesPrint (" Matrix \n");
9993	MrBayesPrint (" \n");
9994	MrBayesPrint (" This command specifies the actual data for the phylogenetic analysis. \n");
9995	MrBayesPrint (" The character matrix should follow the dimensions and format commands \n");
9996	MrBayesPrint (" in a data block. The matrix can have all of the characters for a taxon \n");
9997	MrBayesPrint (" on a single line: \n");
9998	MrBayesPrint (" \n");
9999	MrBayesPrint (" begin data; \n");
10000	MrBayesPrint (" dimensions ntax=4 nchar=10; \n");
10001	MrBayesPrint (" format datatype=dna gap=-; \n");
10002	MrBayesPrint (" matrix \n");
10003	MrBayesPrint (" taxon_1 AACGATTCGT \n");
10004	MrBayesPrint (" taxon_2 AAGGAT--CA \n");
10005	MrBayesPrint (" taxon_3 AACGACTCCT \n");
10006	MrBayesPrint (" taxon_4 AAGGATTCCT \n");
10007	MrBayesPrint (" ; \n");
10008	MrBayesPrint (" end; \n");
10009	MrBayesPrint (" \n");
10010	MrBayesPrint (" or be in \"interleaved\" format: \n");
10011	MrBayesPrint (" \n");
10012	MrBayesPrint (" begin data; \n");
10013	MrBayesPrint (" dimensions ntax=4 nchar=20; \n");
10014	MrBayesPrint (" format datatype=dna gap=- interleave=yes; \n");
10015	MrBayesPrint (" matrix \n");
10016	MrBayesPrint (" taxon_1 AACGATTCGT \n");
10017	MrBayesPrint (" taxon_2 AAGGAT--CA \n");
10018	MrBayesPrint (" taxon_3 AACGACTCCT \n");
10019	MrBayesPrint (" taxon_4 AAGGATTCCT \n");
10020	MrBayesPrint (" \n");
10021	MrBayesPrint (" taxon_1 TTTTCGAAGC \n");
10022	MrBayesPrint (" taxon_2 TTTTCGGAGC \n");
10023	MrBayesPrint (" taxon_3 TTTTTGATGC \n");
10024	MrBayesPrint (" taxon_4 TTTTCGGAGC \n");
10025	MrBayesPrint (" ; \n");
10026	MrBayesPrint (" end; \n");
10027	MrBayesPrint (" \n");
10028	MrBayesPrint (" Note that the taxon names must not have spaces. If you really want to \n");
10029	MrBayesPrint (" indicate a space in a taxon name (perhaps between a genus and species \n");
10030	MrBayesPrint (" name), then you might use an underline (\"_\"). There should be at \n");
10031	MrBayesPrint (" least a single space after the taxon name, separating the name from \n");
10032	MrBayesPrint (" the actual data on that line. There can be spaces between the char- \n");
10033	MrBayesPrint (" acters. \n");
10034	MrBayesPrint (" \n");
10035	MrBayesPrint (" If you have mixed data, then you specify all of the data in the same \n");
10036	MrBayesPrint (" matrix. Here is an example that includes two different data types: \n");
10037	MrBayesPrint (" \n");
10038	MrBayesPrint (" begin data; \n");
10039	MrBayesPrint (" dimensions ntax=4 nchar=20; \n");
10040	MrBayesPrint (" format datatype=mixed(dna:1-10,standard:21-30) interleave=yes; \n");
10041	MrBayesPrint (" matrix \n");
10042	MrBayesPrint (" taxon_1 AACGATTCGT \n");
10043	MrBayesPrint (" taxon_2 AAGGAT--CA \n");
10044	MrBayesPrint (" taxon_3 AACGACTCCT \n");
10045	MrBayesPrint (" taxon_4 AAGGATTCCT \n");
10046	MrBayesPrint (" \n");
10047	MrBayesPrint (" taxon_1 0001111111 \n");
10048	MrBayesPrint (" taxon_2 0111110000 \n");
10049	MrBayesPrint (" taxon_3 1110000000 \n");
10050	MrBayesPrint (" taxon_4 1000001111 \n");
10051	MrBayesPrint (" ; \n");
10052	MrBayesPrint (" end; \n");
10053	MrBayesPrint (" \n");
10054	MrBayesPrint (" The matrix command is terminated by a semicolon. \n");
10055	MrBayesPrint (" \n");
10056	MrBayesPrint (" Finally, just a note on data presentation. It is much easier for others \n");
10057	MrBayesPrint (" to (1) understand your data and (2) repeat your analyses if you make \n");
10058	MrBayesPrint (" your data clean, comment it liberally (using the square brackets), and \n");
10059	MrBayesPrint (" embed the commands you used in a publication in the mrbayes block. \n");
10060	MrBayesPrint (" Remember that the data took a long time for you to collect. You might \n");
10061	MrBayesPrint (" as well spend a little time making the data file look nice and clear to \n");
10062	MrBayesPrint (" any that may later request the data for further analysis. \n");
10063	MrBayesPrint (" --------------------------------------------------------------------------- \n");
10064	}
10065	else if (!strcmp(helpTkn, "Pairs"))
10066	{
10067	MrBayesPrint (" --------------------------------------------------------------------------- \n");
10068	MrBayesPrint (" Pairs \n");
10069	MrBayesPrint (" \n");
10070	MrBayesPrint (" This command is used to specify pairs of nucleotides. For example, your \n");
10071	MrBayesPrint (" data may be RNA sequences with a known secondary structure of stems and \n");
10072	MrBayesPrint (" loops. Substitutions in nucleotides involved in a Watson-Crick pairing \n");
10073	MrBayesPrint (" in stems are not strictly independent; a change in one changes the prob- \n");
10074	MrBayesPrint (" ability of a change in the partner. A solution to this problem is to \n");
10075	MrBayesPrint (" expand the model around the pair of nucleotides in the stem. This \n");
10076	MrBayesPrint (" command allows you to do this. The correct usage is: \n");
10077	MrBayesPrint (" \n");
10078	MrBayesPrint (" pairs <NUC1>:<NUC2>, <NUC1>:<NUC2>,..., <NUC1>:<NUC2>; \n");
10079	MrBayesPrint (" \n");
10080	MrBayesPrint (" For example, \n");
10081	MrBayesPrint (" \n");
10082	MrBayesPrint (" pairs 30:56, 31:55, 32:54, 33:53, 34:52, 35:51, 36:50; \n");
10083	MrBayesPrint (" \n");
10084	MrBayesPrint (" specifies pairings between nucleotides 30 and 56, 31 and 55, etc. Only \n");
10085	MrBayesPrint (" nucleotide data (DNA or RNA) may be paired using this command. Note that \n");
10086	MrBayesPrint (" in order for the program to actually implement a \"doublet\" model \n");
10087	MrBayesPrint (" involving a 16 X 16 rate matrix, you must specify that the structure of \n");
10088	MrBayesPrint (" the model is 16 X 16 using \"lset nucmodel=doublet\". \n");
10089	MrBayesPrint (" --------------------------------------------------------------------------- \n");
10090	}
10091	else if (!strcmp(helpTkn, "Databreaks"))
10092	{
10093	MrBayesPrint (" --------------------------------------------------------------------------- \n");
10094	MrBayesPrint (" Databreaks \n");
10095	MrBayesPrint (" \n");
10096	MrBayesPrint (" This command is used to specify breaks in your input data matrix. Your \n");
10097	MrBayesPrint (" data may be a mixture of genes or a mixture of different types of data. \n");
10098	MrBayesPrint (" Some of the models implemented by MrBayes account for nonindependence at \n");
10099	MrBayesPrint (" adjacent characters. The autocorrelated gamma model, for example, allows \n");
10100	MrBayesPrint (" rates at adjacent sites to be correlated. However, there is no way for \n");
10101	MrBayesPrint (" such a model to tell whether two sites, adjacent in the matrix, are \n");
10102	MrBayesPrint (" actually separated by many kilobases or megabases in the genome. The \n");
10103	MrBayesPrint (" databreaks command allows you to specify such breaks. The correct \n");
10104	MrBayesPrint (" usage is: \n");
10105	MrBayesPrint (" \n");
10106	MrBayesPrint (" databreaks <break 1> <break 2> <break 3> ... \n");
10107	MrBayesPrint (" \n");
10108	MrBayesPrint (" For example, say you have a data matrix of 3204 characters that include \n");
10109	MrBayesPrint (" nucleotide data from three genes. The first gene covers characters 1 to \n");
10110	MrBayesPrint (" 970, the second gene covers characters 971 to 2567, and the third gene \n");
10111	MrBayesPrint (" covers characters 2568 to 3204. Also, let's assume that the genes are \n");
10112	MrBayesPrint (" not directly adjacent to one another in the genome, as might be likely \n");
10113	MrBayesPrint (" if you have mitochondrial sequences. In this case, you can specify \n");
10114	MrBayesPrint (" breaks between the genes using: \n");
10115	MrBayesPrint (" \n");
10116	MrBayesPrint (" databreaks 970 2567; \n");
10117	MrBayesPrint (" \n");
10118	MrBayesPrint (" The first break, between genes one and two, is after character 970 and \n");
10119	MrBayesPrint (" the second break, between genes two and three, is after character 2567. \n");
10120	MrBayesPrint (" --------------------------------------------------------------------------- \n");
10121	}
10122	else if (!strcmp(helpTkn, "Acknowledgments"))
10123	{
10124	MrBayesPrint (" --------------------------------------------------------------------------- \n");
10125	MrBayesPrint (" Acknowledgments \n");
10126	MrBayesPrint (" \n");
10127	MrBayesPrint (" This command shows the authors' acknowledgments. \n");
10128	MrBayesPrint (" --------------------------------------------------------------------------- \n");
10129	}
10130	else if (!strcmp(helpTkn, "About"))
10131	{
10132	MrBayesPrint (" --------------------------------------------------------------------------- \n");
10133	MrBayesPrint (" About \n");
10134	MrBayesPrint (" \n");
10135	MrBayesPrint (" This command provides some general information about the program. \n");
10136	MrBayesPrint (" --------------------------------------------------------------------------- \n");
10137	}
10138	else if (!strcmp(helpTkn, "Version"))
10139	{
10140	MrBayesPrint (" --------------------------------------------------------------------------- \n");
10141	MrBayesPrint (" Version \n");
10142	MrBayesPrint (" \n");
10143	MrBayesPrint (" This command shows the release version of the program. \n");
10144	MrBayesPrint (" --------------------------------------------------------------------------- \n");
10145	}
10146	else if (!strcmp(helpTkn, "Citations"))
10147	{
10148	MrBayesPrint (" --------------------------------------------------------------------------- \n");
10149	MrBayesPrint (" Citations \n");
10150	MrBayesPrint (" \n");
10151	MrBayesPrint (" This command shows a thorough list of citations you may consider using \n");
10152	MrBayesPrint (" when publishing the results of a MrBayes analysis. \n");
10153	MrBayesPrint (" --------------------------------------------------------------------------- \n");
10154	}
10155	else if (!strcmp(helpTkn, "Showmatrix"))
10156	{
10157	MrBayesPrint (" --------------------------------------------------------------------------- \n");
10158	MrBayesPrint (" Showmatrix \n");
10159	MrBayesPrint (" \n");
10160	MrBayesPrint (" This command shows the character matrix currently in memory. \n");
10161	MrBayesPrint (" --------------------------------------------------------------------------- \n");
10162	}
10163	else if (!strcmp(helpTkn, "Showbeagle"))
10164	{
10165	MrBayesPrint (" --------------------------------------------------------------------------- \n");
10166	MrBayesPrint (" Showbeagle \n");
10167	MrBayesPrint (" \n");
10168	MrBayesPrint (" This command shows available BEAGLE resources. \n");
10169	MrBayesPrint (" --------------------------------------------------------------------------- \n");
10170	}
10171	else if (!strcmp(helpTkn, "Speciespartition"))
10172	{
10173	MrBayesPrint (" --------------------------------------------------------------------------- \n");
10174	MrBayesPrint (" Speciespartition \n");
10175	MrBayesPrint (" \n");
10176	MrBayesPrint (" Defines a partition of tips into species. The format for the speciespartition \n");
10177	MrBayesPrint (" command is \n");
10178	MrBayesPrint (" \n");
10179	MrBayesPrint (" Speciespartition <name> = <species name>:<taxon list> ,...,<sp nm>:<tx lst>\n");
10180	MrBayesPrint (" \n");
10181	MrBayesPrint (" The command enumerates comma separated list of pairs consisting of 'species \n");
10182	MrBayesPrint (" name' and 'taxon list'. The 'taxon list' is a standard taxon list, as used by \n");
10183	MrBayesPrint (" the 'Taxset' command. This means that you can use either the index or the name\n");
10184	MrBayesPrint (" of a sequence ('taxon'). Ranges are specified using a dash, and a period can \n");
10185	MrBayesPrint (" be used as a synonym of the last sequence in the matrix. \n");
10186	MrBayesPrint (" \n");
10187	MrBayesPrint (" For exammple: speciespartition species = SpeciesA: 1, SpeciesB: 2-. \n");
10188	MrBayesPrint (" Here, we name two species. SpeciesA is represented by a single sequence while \n");
10189	MrBayesPrint (" SpeciesB is represented by all remaining sequences in the matrix. \n");
10190	MrBayesPrint (" Each sequence is specified by its row index in the data matrix. \n");
10191	MrBayesPrint (" \n");
10192	MrBayesPrint (" As with ordinary partitioning you may define multiple species partitioning \n");
10193	MrBayesPrint (" scheme. You have to use command 'set speciespartition' to enable use of one of\n");
10194	MrBayesPrint (" them. \n");
10195	MrBayesPrint (" \n");
10196	MrBayesPrint (" Currently defined Speciespartitions: \n");
10197	MrBayesPrint (" \n");
10198	MrBayesPrint (" Number Speciespartition name Number of species \n");
10199	MrBayesPrint (" -------------------------------------------------------------------------- \n");
10200	for (i=0; i<numDefinedSpeciespartitions; i++)
10201	{
10202	tempInt=0;
10203	for (j=0; j<numTaxa; j++)
10204	{
10205	if (tempInt < speciespartitionId[j][i])
10206	tempInt = speciespartitionId[j][i];
10207	}
10208	MrBayesPrint (" %4d %-24.24s %4d",i+1, speciespartitionNames[i], tempInt);
10209	MrBayesPrint ("\n");
10210	}
10211	MrBayesPrint (" \n");
10212	MrBayesPrint (" -------------------------------------------------------------------------- \n");
10213
10214
10215	}
10216	else if (!strcmp(helpTkn, "Constraint"))
10217	{
10218	MrBayesPrint (" --------------------------------------------------------------------------- \n");
10219	MrBayesPrint (" Constraint \n");
10220	MrBayesPrint (" \n");
10221	MrBayesPrint (" This command defines a tree constraint. The format for the constraint \n");
10222	MrBayesPrint (" command is \n");
10223	MrBayesPrint (" \n");
10224	MrBayesPrint (" constraint <name> [hard\|negative\|partial] = <taxon list> [:<taxon list>] \n");
10225	MrBayesPrint (" \n");
10226	MrBayesPrint (" There are three types of constraint implemented in MrBayes. The type of the \n");
10227	MrBayesPrint (" constraint is specified by using one of the three keywords 'hard', 'negative',\n");
10228	MrBayesPrint (" or 'partial' right after the name of the constraint. If no type is specified, \n");
10229	MrBayesPrint (" then the constraint is assumed to be 'hard'. \n");
10230	MrBayesPrint (" \n");
10231	MrBayesPrint (" In a rooted tree, a 'hard' constraint forces the taxa in the list to form a \n");
10232	MrBayesPrint (" monophyletic group. In an unrooted tree, the taxon split that separates the \n");
10233	MrBayesPrint (" taxa in the list from other taxa is forced to be present. The interpretation \n");
10234	MrBayesPrint (" of this depends on whether the tree is rooted on a taxon outside the list or \n");
10235	MrBayesPrint (" a taxon in the list. If the outgroup is excluded , the taxa in the list are \n");
10236	MrBayesPrint (" assumed to form a monophyletic group, but if the outgroup is included, it is \n");
10237	MrBayesPrint (" the taxa that are not in the list that are forced together. \n");
10238	MrBayesPrint (" \n");
10239	MrBayesPrint (" A 'negative' constraint bans all the trees that have the listed taxa in the \n");
10240	MrBayesPrint (" same subtree. In other words, it is the opposite of a hard constraint. \n");
10241	MrBayesPrint (" \n");
10242	MrBayesPrint (" A 'partial' or backbone constraint is defined in terms of two sets of taxa \n");
10243	MrBayesPrint (" separated by a colon character. The constraint forces all taxa in the first \n");
10244	MrBayesPrint (" list to form a monophyletic group that does not include any taxon in the \n");
10245	MrBayesPrint (" second list. Taxa that are not included in either list can be placed in any \n");
10246	MrBayesPrint (" position on the tree, either inside or outside the constrained group. In an \n");
10247	MrBayesPrint (" unrooted tree, the two taxon lists can be switched with each other with no \n");
10248	MrBayesPrint (" effect. For a rooted tree, it is the taxa in the first list that have to be \n");
10249	MrBayesPrint (" monophyletic, that is, these taxa must share a common ancestor not shared with\n");
10250	MrBayesPrint (" any taxon in the second list. The taxa in the second list may or may not fall \n");
10251	MrBayesPrint (" in a monophyletic group depending on the rooting of the tree. \n");
10252	MrBayesPrint (" \n");
10253	MrBayesPrint (" A list of taxa can be specified using a taxset, taxon names, taxon numbers, or\n");
10254	MrBayesPrint (" any combination of the above, sepatated by spaces. The constraint is treated \n");
10255	MrBayesPrint (" as an absolute requirement of trees, that is, trees that are not compatible \n");
10256	MrBayesPrint (" with the constraint have zero prior (and hence zero posterior) probabilty. \n");
10257	MrBayesPrint (" \n");
10258	MrBayesPrint (" If you are interested in inferring ancestral states for a particular node, \n");
10259	MrBayesPrint (" you need to 'hard' constrain that node first using the 'constraint' command. \n");
10260	MrBayesPrint (" The same applies if you wish to calibrate an interior node in a dated \n");
10261	MrBayesPrint (" analysis. For more information on how to infer ancestral states, see the help \n");
10262	MrBayesPrint (" for the 'report' command. For more on dating, see the 'calibrate' command. \n");
10263	MrBayesPrint (" \n");
10264	MrBayesPrint (" It is important to note that simply defining a constraint using this \n");
10265	MrBayesPrint (" command is not sufficient for the program to actually implement the \n");
10266	MrBayesPrint (" constraint in an analysis. You must also enforce the constraints using \n");
10267	MrBayesPrint (" 'prset topologypr = constraints (<list of constraints>)'. For more infor- \n");
10268	MrBayesPrint (" mation on this, see the help on the 'prset' command. \n");
10269	MrBayesPrint (" \n");
10270	MrBayesPrint (" Examples: \n");
10271	MrBayesPrint (" \n");
10272	MrBayesPrint (" constraint myclade = Homo Pan Gorilla \n");
10273	MrBayesPrint (" \n");
10274	MrBayesPrint (" Defines a hard constraint forcing Homo, Pan, and Gorilla to form a mono- \n");
10275	MrBayesPrint (" phyletic group or a split that does not include any other taxa. \n");
10276	MrBayesPrint (" \n");
10277	MrBayesPrint (" constraint forbiddenclade negative = Homo Pan Gorilla \n");
10278	MrBayesPrint (" \n");
10279	MrBayesPrint (" Defines a negative constraint that associates all trees where Homon, Pan, and \n");
10280	MrBayesPrint (" Gorilla form a monophyletic group with zero posterior probability. In other \n");
10281	MrBayesPrint (" words, such trees will not be sampled during MCMC. \n");
10282	MrBayesPrint (" \n");
10283	MrBayesPrint (" constraint backbone partial = Homo Gorilla : Mus \n");
10284	MrBayesPrint (" \n");
10285	MrBayesPrint (" Defines a partial constraint that keeps Mus outside of the clade defined by \n");
10286	MrBayesPrint (" the most recent common ancestor of Homo and Gorilla. Other taxa are allowed to\n");
10287	MrBayesPrint (" sit anywhere in the tree. \n");
10288	MrBayesPrint (" \n");
10289	MrBayesPrint (" To define a more complex constraint tree, simply combine constraints into a \n");
10290	MrBayesPrint (" list when issuing the 'prset topologypr' command. \n");
10291	MrBayesPrint (" \n");
10292	if (numDefinedConstraints > 0)
10293	{
10294	MrBayesPrint (" Currently defined constraints: \n");
10295	MrBayesPrint (" \n");
10296	MrBayesPrint (" Number Constraint name type Number of taxa in[:out] \n");
10297	MrBayesPrint (" -------------------------------------------------------------------------- \n");
10298	}
10299	for (i=0; i<numDefinedConstraints; i++)
10300	{
10301	strncpy (tempString, constraintNames[i], 22);
10302	MrBayesPrint (" %4d %-22.22s ",i+1, tempString);
10303	if( definedConstraintsType[i] == HARD )
10304	MrBayesPrint ("hard ");
10305	else if( definedConstraintsType[i] == PARTIAL )
10306	MrBayesPrint ("partial ");
10307	else
10308	{
10309	assert(definedConstraintsType[i] == NEGATIVE );
10310	MrBayesPrint ("negative ");
10311	}
10312	k = NumBits (definedConstraint[i], numTaxa/nBitsInALong + 1);
10313	MrBayesPrint ("%d", k);
10314	if( definedConstraintsType[i] == PARTIAL )
10315	{
10316	k = NumBits (definedConstraintTwo[i], numTaxa/nBitsInALong + 1);
10317	MrBayesPrint (":%d", k);
10318	}
10319	MrBayesPrint ("\n");
10320	}
10321	MrBayesPrint (" \n");
10322	MrBayesPrint (" -------------------------------------------------------------------------- \n");
10323	}
10324	else if (!strcmp(helpTkn, "Calibrate"))
10325	{
10326	MrBayesPrint (" --------------------------------------------------------------------------- \n");
10327	MrBayesPrint (" Calibrate \n");
10328	MrBayesPrint (" \n");
10329	MrBayesPrint (" This command dates a terminal or interior node in the tree. The format is \n");
10330	MrBayesPrint (" \n");
10331	MrBayesPrint (" calibrate <node_name> = <age_prior> \n");
10332	MrBayesPrint (" \n");
10333	MrBayesPrint (" where <node_name> is the name of a defined interior constraint node or the \n");
10334	MrBayesPrint (" name of a terminal node (tip) and <age_prior> is a prior probability distribu-\n");
10335	MrBayesPrint (" tion on the age of the node. The latter can either be a fixed date, a uniform \n");
10336	MrBayesPrint (" probability distribution between a minimum and a maximum age, or an offset \n");
10337	MrBayesPrint (" exponential distribution with a minimum age and a rate parameter. The \n");
10338	MrBayesPrint (" format is: \n");
10339	MrBayesPrint (" \n");
10340	MrBayesPrint (" calibrate <node_name> = fixed(<age>) \n");
10341	MrBayesPrint (" calibrate <node_name> = uniform(<min_age>,<max_age>) \n");
10342	MrBayesPrint (" calibrate <node_name> = offsetexponential(<min_age>,<rate>) \n");
10343	MrBayesPrint (" \n");
10344	MrBayesPrint (" For instance, assume that we had three fossil terminals in our analyses named \n");
10345	MrBayesPrint (" 'FossilA', 'FossilB', and 'FossilC'. Assume further that we want to fix the \n");
10346	MrBayesPrint (" age of FossilA to 100.0 million years, we think that FossilB is somewhere \n");
10347	MrBayesPrint (" between 100.0 and 200.0 million years old, and that FossilC is at least 300.0 \n");
10348	MrBayesPrint (" million years old, possibly older but relatively unlikely to be more than \n");
10349	MrBayesPrint (" 400.0 million years old. Then we might use the commands: \n");
10350	MrBayesPrint (" \n");
10351	MrBayesPrint (" calibrate FossilA = fixed(100) FossilB = uniform(100,200) \n");
10352	MrBayesPrint (" calibrate FossilC = offsetexponential(300,0.01) \n");
10353	MrBayesPrint (" \n");
10354	MrBayesPrint (" Note that it is possible to give more than one calibration for each \n");
10355	MrBayesPrint (" 'calibrate' statement. The offset exponential distribution has its expectation\n");
10356	MrBayesPrint (" at the minimum age plus the inverse of the rate parameter. That is, the \n");
10357	MrBayesPrint (" offsetexponential(300,0.01) has the minimum 300 , the expectation 400 = \n");
10358	MrBayesPrint (" = 300 + 1/0.01 and the mode < 400, so that most of the probability distribu- \n");
10359	MrBayesPrint (" tion is on values smaller than 400. \n");
10360	MrBayesPrint (" \n");
10361	MrBayesPrint (" To actually use the calibrations to obtain dated trees, you also need to set \n");
10362	MrBayesPrint (" a clock model using relevant 'brlenspr' and 'nodeagepr' options of the 'prset'\n");
10363	MrBayesPrint (" command. You may also want to examine the 'clockvarpr' and 'clockratepr' op- \n");
10364	MrBayesPrint (" tions. Furthermore, you need to activate the relevant constraint(s) using \n");
10365	MrBayesPrint (" 'topologypr', if you use any dated interior nodes in the tree. \n");
10366	MrBayesPrint (" \n");
10367	MrBayesPrint (" You may wish to remove a calibration from an interior or terminal node, which \n");
10368	MrBayesPrint (" has previously been calibrated. You can do that using \n");
10369	MrBayesPrint (" \n");
10370	MrBayesPrint (" calibrate <node_name> = unconstrained \n");
10371	MrBayesPrint (" \n");
10372	j = 0;
10373	for (i=0; i<numTaxa; i++)
10374	if (tipCalibration[i].prior != unconstrained)
10375	j++;
10376	for (i=0; i<numDefinedConstraints; i++)
10377	if (nodeCalibration[i].prior != unconstrained)
10378	j++;
10379	if (j > 0)
10380	{
10381	MrBayesPrint (" \n");
10382	MrBayesPrint (" Currently defined calibrations: \n");
10383	MrBayesPrint (" \n");
10384	MrBayesPrint (" Node name Type Calibration \n");
10385	MrBayesPrint (" ------------------------------------------------------------------ \n");
10386	for (i=0; i<numTaxa+numDefinedConstraints; i++)
10387	{
10388	if (i<numTaxa)
10389	calibrationPtr = &tipCalibration[i];
10390	else
10391	calibrationPtr = &nodeCalibration[i-numTaxa];
10392	if (calibrationPtr != NULL && calibrationPtr->prior != unconstrained)
10393	{
10394	if (i<numTaxa)
10395	strncpy (tempString, taxaNames[i], 22);
10396	else
10397	strncpy (tempString, constraintNames[i-numTaxa], 22);
10398	if (i<numTaxa)
10399	MrBayesPrint (" %-22.22s Terminal %s\n", tempString, calibrationPtr->name);
10400	else
10401	MrBayesPrint (" %-22.22s Interior %s\n", tempString, calibrationPtr->name);
10402	}
10403	}
10404	}
10405	MrBayesPrint (" \n");
10406	MrBayesPrint (" --------------------------------------------------------------------------- \n");
10407	}
10408	else if (!strcmp(helpTkn, "Showmodel"))
10409	{
10410	MrBayesPrint (" --------------------------------------------------------------------------- \n");
10411	MrBayesPrint (" Showmodel \n");
10412	MrBayesPrint (" \n");
10413	MrBayesPrint (" This command shows the current model settings. The correct usage is \n");
10414	MrBayesPrint (" \n");
10415	MrBayesPrint (" showmodel \n");
10416	MrBayesPrint (" \n");
10417	MrBayesPrint (" After typing \"showmodel\", the modelling assumptions are shown on a \n");
10418	MrBayesPrint (" partition-by-partition basis. \n");
10419	MrBayesPrint (" --------------------------------------------------------------------------- \n");
10420	}
10421	else if (!strcmp(helpTkn, "Execute"))
10422	{
10423	MrBayesPrint (" --------------------------------------------------------------------------- \n");
10424	MrBayesPrint (" Execute \n");
10425	MrBayesPrint (" \n");
10426	MrBayesPrint (" This command executes a file called <file name>. The correct usage is: \n");
10427	MrBayesPrint (" \n");
10428	MrBayesPrint (" execute <file name> \n");
10429	MrBayesPrint (" \n");
10430	MrBayesPrint (" For example, \n");
10431	MrBayesPrint (" \n");
10432	MrBayesPrint (" execute replicase.nex \n");
10433	MrBayesPrint (" \n");
10434	MrBayesPrint (" would execute the file named \"replicase.nex\". This file must be in the \n");
10435	MrBayesPrint (" same directory as the executable. \n");
10436	MrBayesPrint (" --------------------------------------------------------------------------- \n");
10437	}
10438	else if (!strcmp(helpTkn, "Lset"))
10439	{
10440	MrBayesPrint (" --------------------------------------------------------------------------- \n");
10441	MrBayesPrint (" Lset \n");
10442	MrBayesPrint (" \n");
10443	MrBayesPrint (" This command sets the parameters of the likelihood model. The likelihood \n");
10444	MrBayesPrint (" function is the probability of observing the data conditional on the phylo- \n");
10445	MrBayesPrint (" genetic model. In order to calculate the likelihood, you must assume a \n");
10446	MrBayesPrint (" model of character change. This command lets you tailor the biological \n");
10447	MrBayesPrint (" assumptions made in the phylogenetic model. The correct usage is \n");
10448	MrBayesPrint (" \n");
10449	MrBayesPrint (" lset <parameter>=<option> ... <parameter>=<option> \n");
10450	MrBayesPrint (" \n");
10451	MrBayesPrint (" For example, \"lset nst=6 rates=gamma\" would set the model to a general \n");
10452	MrBayesPrint (" model of DNA substition (the GTR) with gamma-distributed rate variation \n");
10453	MrBayesPrint (" across sites. \n");
10454	MrBayesPrint (" \n");
10455	MrBayesPrint (" Options: \n");
10456	MrBayesPrint (" \n");
10457	MrBayesPrint (" Applyto -- This option allows you to apply the lset commands to specific \n");
10458	MrBayesPrint (" partitions. This command should be the first in the list of \n");
10459	MrBayesPrint (" commands specified in lset. Moreover, it only makes sense to \n");
10460	MrBayesPrint (" be using this command if the data have been partitioned. A \n");
10461	MrBayesPrint (" default partition is set on execution of a matrix. If the data \n");
10462	MrBayesPrint (" are homogeneous (i.e., all of the same data type), then this \n");
10463	MrBayesPrint (" partition will not subdivide the characters. Up to 30 other \n");
10464	MrBayesPrint (" partitions can be defined, and you can switch among them using \n");
10465	MrBayesPrint (" \"set partition=<partition name>\". Now, you may want to \n");
10466	MrBayesPrint (" specify different models to different partitions of the data. \n");
10467	MrBayesPrint (" Applyto allows you to do this. For example, say you have \n");
10468	MrBayesPrint (" partitioned the data by codon position, and you want to apply \n");
10469	MrBayesPrint (" a nst=2 model to the first two partitions and nst=6 to the \n");
10470	MrBayesPrint (" last. This could be implemented in two uses of lset: \n");
10471	MrBayesPrint (" \n");
10472	MrBayesPrint (" lset applyto=(1,2) nst=2 \n");
10473	MrBayesPrint (" \n");
10474	MrBayesPrint (" lset applyto=(3) nst=6 \n");
10475	MrBayesPrint (" \n");
10476	MrBayesPrint (" The first applies the parameters after \"applyto\" to the \n");
10477	MrBayesPrint (" first and second partitions. The second lset applies nst=6 \n");
10478	MrBayesPrint (" to the third partition. You can also use applyto=(all), which \n");
10479	MrBayesPrint (" attempts to apply the parameter settings to all of the data \n");
10480	MrBayesPrint (" partitions. Importantly, if the option is not consistent with \n");
10481	MrBayesPrint (" the data in the partition, the program will not apply the \n");
10482	MrBayesPrint (" lset option to that partition. \n");
10483	MrBayesPrint (" Nucmodel -- This specifies the general form of the nucleotide substitution \n");
10484	MrBayesPrint (" model. The options are \"4by4\" [the standard model of DNA \n");
10485	MrBayesPrint (" substitution in which there are only four states (A,C,G,T/U)], \n");
10486	MrBayesPrint (" \"doublet\" (a model appropriate for modelling the stem regions \n");
10487	MrBayesPrint (" of ribosomal genes where the state space is the 16 doublets of \n");
10488	MrBayesPrint (" nucleotides), \"codon\" (the substitution model is expanded \n");
10489	MrBayesPrint (" around triplets of nucleotides--a codon), and \"Protein\" \n");
10490	MrBayesPrint (" (triplets of nucleotides are translated to amino acids, which \n");
10491	MrBayesPrint (" form the basis of the substitution model). \n");
10492	MrBayesPrint (" Nst -- Sets the number of substitution types: \"1\" constrains all of \n");
10493	MrBayesPrint (" the rates to be the same (e.g., a JC69 or F81 model); \"2\" all- \n");
10494	MrBayesPrint (" ows transitions and transversions to have potentially different \n");
10495	MrBayesPrint (" rates (e.g., a K80 or HKY85 model); \"6\" allows all rates to \n");
10496	MrBayesPrint (" be different, subject to the constraint of time-reversibility \n");
10497	MrBayesPrint (" (e.g., a GTR model). Finally, 'nst' can be set to 'mixed', which \n");
10498	MrBayesPrint (" results in the Markov chain sampling over the space of all poss- \n");
10499	MrBayesPrint (" ible reversible substitution models, including the GTR model and \n");
10500	MrBayesPrint (" all models that can be derived from it model by grouping the six \n");
10501	MrBayesPrint (" rates in various combinations. This includes all the named models\n");
10502	MrBayesPrint (" above and a large number of others, with or without name. \n");
10503	MrBayesPrint (" Code -- Enforces the use of a particular genetic code. The default \n");
10504	MrBayesPrint (" is the universal code. Other options include \"vertmt\" for \n");
10505	MrBayesPrint (" vertebrate mitocondrial DNA, \"mycoplasma\", \"yeast\", \n");
10506	MrBayesPrint (" \"ciliates\", and \"metmt\" (for metazoan mitochondrial DNA \n");
10507	MrBayesPrint (" except vertebrates). \n");
10508	MrBayesPrint (" Ploidy -- Specifies the ploidy of the organism. Options are \"Haploid\", \n");
10509	MrBayesPrint (" \"Diploid\" or \"Zlinked\". This option is used when a coalescence\n");
10510	MrBayesPrint (" prior is used on trees. \n");
10511	MrBayesPrint (" Rates -- Sets the model for among-site rate variation. In general, the \n");
10512	MrBayesPrint (" rate at a site is considered to be an unknown random variable. \n");
10513	MrBayesPrint (" The valid options are: \n");
10514	MrBayesPrint (" * equal -- No rate variation across sites. \n");
10515	MrBayesPrint (" * gamma -- Gamma-distributed rates across sites. The rate \n");
10516	MrBayesPrint (" at a site is drawn from a gamma distribution. \n");
10517	MrBayesPrint (" The gamma distribution has a single parameter \n");
10518	MrBayesPrint (" that describes how much rates vary. \n");
10519	MrBayesPrint (" * adgamma -- Autocorrelated rates across sites. The marg- \n");
10520	MrBayesPrint (" inal rate distribution is gamma, but adjacent \n");
10521	MrBayesPrint (" sites have correlated rates. \n");
10522	MrBayesPrint (" * propinv -- A proportion of the sites are invariable. \n");
10523	MrBayesPrint (" * invgamma -- A proportion of the sites are invariable while \n");
10524	MrBayesPrint (" the rate for the remaining sites are drawn from \n");
10525	MrBayesPrint (" a gamma distribution. \n");
10526	MrBayesPrint (" Note that MrBayes versions 2.0 and earlier supported options \n");
10527	MrBayesPrint (" that allowed site specific rates (e.g., ssgamma). In versions \n");
10528	MrBayesPrint (" 3.0 and later, site specific rates are allowed, but set using \n");
10529	MrBayesPrint (" the 'prset ratepr' command for each partition. \n");
10530	MrBayesPrint (" Ngammacat -- Sets the number of rate categories for the gamma distribution. \n");
10531	MrBayesPrint (" The gamma distribution is continuous. However, it is virtually \n");
10532	MrBayesPrint (" impossible to calculate likelihoods under the continuous gamma \n");
10533	MrBayesPrint (" distribution. Hence, an approximation to the continuous gamma \n");
10534	MrBayesPrint (" is used; the gamma distribution is broken into ncat categories \n");
10535	MrBayesPrint (" of equal weight (1/ncat). The mean rate for each category rep- \n");
10536	MrBayesPrint (" resents the rate for the entire cateogry. This option allows \n");
10537	MrBayesPrint (" you to specify how many rate categories to use when approx- \n");
10538	MrBayesPrint (" imating the gamma. The approximation is better as ncat is inc- \n");
10539	MrBayesPrint (" reased. In practice, \"ncat=4\" does a reasonable job of \n");
10540	MrBayesPrint (" approximating the continuous gamma. \n");
10541	#if 0
10542	/* Temporarily disable this because of conflict with likelihood calculators. It should be renamed to samplerates when reintroduced. */
10543	MrBayesPrint (" Usegibbs -- Specifies whether site probabilities under the discrete gamma \n");
10544	MrBayesPrint (" model of rate variation across sites will be summed across rate \n");
10545	MrBayesPrint (" categories ('Usegibbs=No') or sampled using a Gibbs sampler \n");
10546	MrBayesPrint (" ('Usegibbs=Yes'). The Gibbs sampling approach is much faster and \n");
10547	MrBayesPrint (" requires less memory but the likelihood of the sampled points \n");
10548	MrBayesPrint (" will be considerably higher than with the standard approach of \n");
10549	MrBayesPrint (" summing probabilities, so you need to be aware of this when com- \n");
10550	MrBayesPrint (" paring your results with those you obtain with other programs. \n");
10551	MrBayesPrint (" Assume that you are using n rate categories in your discrete \n");
10552	MrBayesPrint (" gamma distribution. Then the Gibbs approach is up to n times \n");
10553	MrBayesPrint (" faster and requires 1/n as much memory as the standard method. \n");
10554	MrBayesPrint (" Unfortunately, the state space also becomes larger so the chain \n");
10555	MrBayesPrint (" may need more time to converge. The approach should work best \n");
10556	MrBayesPrint (" for large trees, where the uncertainty concerning the best rate \n");
10557	MrBayesPrint (" category for each site is negligible. Gibbs sampling cannot be \n");
10558	MrBayesPrint (" used for the autocorrelated discrete gamma model, for standard \n");
10559	MrBayesPrint (" data, or for restriction data. Also, MrBayes will not use Gibbs \n");
10560	MrBayesPrint (" sampling when you want to infer site rates. \n");
10561	MrBayesPrint (" Gibbsfreq -- Sets the frequency with which the rate categories of the discrete\n");
10562	MrBayesPrint (" gamma will be Gibbs sampled. In practice, we have found that a \n");
10563	MrBayesPrint (" resampling frequency of every 100 MCMC generations works well for\n");
10564	MrBayesPrint (" reasonably long runs. The more frequent the Gibbs sampling, the \n");
10565	MrBayesPrint (" slower the Gibbs sampling approach will be. If you have k rate \n");
10566	MrBayesPrint (" categories and Gibbs sample them every n generations, then the \n");
10567	MrBayesPrint (" time it takes to complete n generations will roughly be propor- \n");
10568	MrBayesPrint (" tional to n+k. Compare this with the traditional approach of \n");
10569	MrBayesPrint (" summing across the n rate categories in every generation, which \n");
10570	MrBayesPrint (" requires time proportional to n*k. In practice, however, the \n");
10571	MrBayesPrint (" speed difference is not quite as large as this. \n");
10572	#endif
10573	MrBayesPrint (" Nbetacat -- Sets the number of rate categories for the beta distribution. \n");
10574	MrBayesPrint (" A symmetric beta distribution is used to model the station- \n");
10575	MrBayesPrint (" ary frequencies when morphological data are used. This option \n");
10576	MrBayesPrint (" specifies how well the beta distribution will be approx- \n");
10577	MrBayesPrint (" imated. \n");
10578	MrBayesPrint (" Omegavar -- Allows the nonsynonymous/synonymous rate ratio (omega) to vary \n");
10579	MrBayesPrint (" across codons. Ny98 assumes that there are three classes, with \n");
10580	MrBayesPrint (" potentially different omega values (omega1, omega2, omega3): \n");
10581	MrBayesPrint (" omega2 = 1; 0 < omega1 <1; and omega3 > 1. Like the Ny98 model, \n");
10582	MrBayesPrint (" the M3 model has three omega classes. However, their values are \n");
10583	MrBayesPrint (" less constrained, with omega1 < omega2 < omega3. The default \n");
10584	MrBayesPrint (" (omegavar = equal) has no variation on omega across sites. \n");
10585	MrBayesPrint (" Covarion -- This forces the use of a covarion-like model of substitution \n");
10586	MrBayesPrint (" for nucleotide or amino acid data. The valid options are \"yes\" \n");
10587	MrBayesPrint (" and \"no\". The covarion model allows the rate at a site to \n");
10588	MrBayesPrint (" change over its evolutionary history. Specifically, the site \n");
10589	MrBayesPrint (" is either on or off. When it is off, no substitutions are poss- \n");
10590	MrBayesPrint (" ible. When the process is on, substitutions occur according to \n");
10591	MrBayesPrint (" a specified substitution model (specified using the other \n");
10592	MrBayesPrint (" lset options). \n");
10593	MrBayesPrint (" Coding -- This specifies how characters were sampled. If all site pat- \n");
10594	MrBayesPrint (" terns had the possibility of being sampled, then \"all\" should \n");
10595	MrBayesPrint (" be specified (the default). Otherwise \"variable\" (only var- \n");
10596	MrBayesPrint (" iable characters had the possibility of being sampled), \n");
10597	MrBayesPrint (" \"noabsence\" (characters for which all taxa were coded as \n");
10598	MrBayesPrint (" absent were not sampled), and \"nopresence\" (characters for \n");
10599	MrBayesPrint (" which all taxa were coded as present were not sampled. \"All\" \n");
10600	MrBayesPrint (" works for all data types. However, the others only work for \n");
10601	MrBayesPrint (" morphological (all/variable) or restriction site (all/variable/ \n");
10602	MrBayesPrint (" noabsence/nopresence) data. \n");
10603	MrBayesPrint (" Parsmodel -- This forces calculation under the so-called parsimony model \n");
10604	MrBayesPrint (" described by Tuffley and Steel (1998). The options are \"yes\" \n");
10605	MrBayesPrint (" or \"no\". Note that the biological assumptions of this model \n");
10606	MrBayesPrint (" are anything but parsimonious. In fact, this model assumes many \n");
10607	MrBayesPrint (" more parameters than the next most complicated model imple- \n");
10608	MrBayesPrint (" mented in this program. If you really believe that the pars- \n");
10609	MrBayesPrint (" imony model makes the biological assumptions described by \n");
10610	MrBayesPrint (" Tuffley and Steel, then the parsimony method is miss-named. \n");
10611	/*MrBayesPrint (" Augment -- This allows the chain to consider the missing entries of \n");
10612	MrBayesPrint (" the data matrix as random variables. A Gibbs sampler is \n");
10613	MrBayesPrint (" used to sample states. \n");*/
10614	MrBayesPrint (" \n");
10615	if (numCurrentDivisions == 0)
10616	tempInt = 1;
10617	else
10618	tempInt = numCurrentDivisions;
10619	for (i=0; i<tempInt; i++)
10620	{
10621	if (numCurrentDivisions == 0)
10622	{
10623	MrBayesPrint (" Default model settings: \n");
10624	mp = &defaultModel;
10625	}
10626	else
10627	{
10628	MrBayesPrint (" Model settings for partition %d: \n", i+1);
10629	mp = &modelParams[i];
10630	}
10631	MrBayesPrint (" \n");
10632	MrBayesPrint (" Parameter Options Current Setting \n");
10633	MrBayesPrint (" ------------------------------------------------------------------ \n");
10634	MrBayesPrint (" Nucmodel 4by4/Doublet/Codon/Protein %s \n", mp->nucModel);
10635	MrBayesPrint (" Nst 1/2/6/Mixed %s \n", mp->nst);
10636	MrBayesPrint (" Code Universal/Vertmt/Mycoplasma/ \n");
10637	MrBayesPrint (" Yeast/Ciliates/Metmt %s \n", mp->geneticCode);
10638	MrBayesPrint (" Ploidy Haploid/Diploid/Zlinked %s \n", mp->ploidy);
10639	MrBayesPrint (" Rates Equal/Gamma/Propinv/Invgamma/Adgamma %s \n", mp->ratesModel);
10640	MrBayesPrint (" Ngammacat <number> %d \n", mp->numGammaCats);
10641	#if 0
10642	/* Temporarily disable this because of conflict with likelihood calculators. It should be renamed to samplerates when reintroduced. */
10643	MrBayesPrint (" Usegibbs Yes/No %s \n", mp->useGibbs);
10644	MrBayesPrint (" Gibbsfreq <number> %d \n", mp->gibbsFreq);
10645	#endif
10646	MrBayesPrint (" Nbetacat <number> %d \n", mp->numBetaCats);
10647	MrBayesPrint (" Omegavar Equal/Ny98/M3 %s \n", mp->omegaVar);
10648	MrBayesPrint (" Covarion No/Yes %s \n", mp->covarionModel);
10649	MrBayesPrint (" Coding All/Variable/Noabsencesites/ \n");
10650	MrBayesPrint (" Nopresencesites %s \n", mp->coding);
10651	MrBayesPrint (" Parsmodel No/Yes %s \n", mp->parsModel);
10652	/MrBayesPrint (" Augment No/Yes %s \n", mp->augmentData);/
10653	MrBayesPrint (" ------------------------------------------------------------------ \n");
10654	MrBayesPrint (" \n");
10655	}
10656	}
10657	else if (!strcmp(helpTkn, "Prset"))
10658	{
10659	MrBayesPrint (" --------------------------------------------------------------------------- \n");
10660	MrBayesPrint (" Prset \n");
10661	MrBayesPrint (" \n");
10662	MrBayesPrint (" This command sets the priors for the phylogenetic model. Remember that \n");
10663	MrBayesPrint (" in a Bayesian analysis, you must specify a prior probability distribution \n");
10664	MrBayesPrint (" for the parameters of the likelihood model. The prior distribution rep- \n");
10665	MrBayesPrint (" resents your prior beliefs about the parameter before observation of the \n");
10666	MrBayesPrint (" data. This command allows you to tailor your prior assumptions to a large \n");
10667	MrBayesPrint (" extent. \n");
10668	MrBayesPrint (" \n");
10669	MrBayesPrint (" Options: \n");
10670	MrBayesPrint (" \n");
10671	MrBayesPrint (" Applyto -- This option allows you to apply the prset commands to \n");
10672	MrBayesPrint (" specific partitions. This command should be the first \n");
10673	MrBayesPrint (" in the list of commands specified in prset. Moreover, it \n");
10674	MrBayesPrint (" only makes sense to be using this command if the data \n");
10675	MrBayesPrint (" have been partitioned. A default partition is set on \n");
10676	MrBayesPrint (" execution of a matrix. If the data are homogeneous \n");
10677	MrBayesPrint (" (i.e., all of the same data type), then this partition \n");
10678	MrBayesPrint (" will not subdivide the characters. Up to 30 other part- \n");
10679	MrBayesPrint (" itions can be defined, and you can switch among them using \n");
10680	MrBayesPrint (" \"set partition=<partition name>\". Now, you may want to \n");
10681	MrBayesPrint (" specify different priors to different partitions of the \n");
10682	MrBayesPrint (" data. Applyto allows you to do this. For example, say \n");
10683	MrBayesPrint (" you have partitioned the data by codon position, and \n");
10684	MrBayesPrint (" you want to fix the statefreqs to equal for the first two \n");
10685	MrBayesPrint (" partitions but apply a flat Dirichlet prior to the state- \n");
10686	MrBayesPrint (" freqs of the last. This could be implemented in two uses of \n");
10687	MrBayesPrint (" prset: \n");
10688	MrBayesPrint (" \n");
10689	MrBayesPrint (" prset applyto=(1,2) statefreqs=fixed(equal) \n");
10690	MrBayesPrint (" \n");
10691	MrBayesPrint (" prset applyto=(3) statefreqs=dirichlet(1,1,1,1) \n");
10692	MrBayesPrint (" \n");
10693	MrBayesPrint (" The first applies the parameters after \"applyto\" \n");
10694	MrBayesPrint (" to the first and second partitions. The second prset \n");
10695	MrBayesPrint (" applies a flat Dirichlet to the third partition. You can \n");
10696	MrBayesPrint (" also use applyto=(all), which attempts to apply the para- \n");
10697	MrBayesPrint (" meter settings to all of the data partitions. Importantly, \n");
10698	MrBayesPrint (" if the option is not consistent with the data in the part- \n");
10699	MrBayesPrint (" ition, the program will not apply the prset option to \n");
10700	MrBayesPrint (" that partition. \n");
10701	MrBayesPrint (" Tratiopr -- This parameter sets the prior for the transition/trans- \n");
10702	MrBayesPrint (" version rate ratio (tratio). The options are: \n");
10703	MrBayesPrint (" \n");
10704	MrBayesPrint (" prset tratiopr = beta(<number>, <number>) \n");
10705	MrBayesPrint (" prset tratiopr = fixed(<number>) \n");
10706	MrBayesPrint (" \n");
10707	MrBayesPrint (" The program assumes that the transition and transversion \n");
10708	MrBayesPrint (" rates are independent gamma-distributed random variables \n");
10709	MrBayesPrint (" with the same scale parameter when beta is selected. If you \n");
10710	MrBayesPrint (" want a diffuse prior that puts equal emphasis on transition/ \n");
10711	MrBayesPrint (" transversion rate ratios above 1.0 and below 1.0, then use a \n");
10712	MrBayesPrint (" flat Beta, beta(1,1), which is the default. If you wish to \n");
10713	MrBayesPrint (" concentrate this distribution more in the equal-rates region,\n");
10714	MrBayesPrint (" then use a prior of the type beta(x,x), where the magnitude \n");
10715	MrBayesPrint (" of x determines how much the prior is concentrated in the \n");
10716	MrBayesPrint (" equal rates region. For instance, a beta(20,20) puts more \n");
10717	MrBayesPrint (" probability on rate ratios close to 1.0 than a beta(1,1). If \n");
10718	MrBayesPrint (" you think it is likely that the transition/transversion rate \n");
10719	MrBayesPrint (" ratio is 2.0, you can use a prior of the type beta(2x,x), \n");
10720	MrBayesPrint (" where x determines how strongly the prior is concentrated on \n");
10721	MrBayesPrint (" tratio values near 2.0. For instance, a beta(2,1) is much \n");
10722	MrBayesPrint (" more diffuse than a beta(80,40) but both have the expected \n");
10723	MrBayesPrint (" tratio 2.0 in the absence of data. The parameters of the \n");
10724	MrBayesPrint (" Beta can be interpreted as counts: if you have observed x \n");
10725	MrBayesPrint (" transitions and y transversions, then a beta(x+1,y+1) is a \n");
10726	MrBayesPrint (" good representation of this information. The fixed option \n");
10727	MrBayesPrint (" allows you to fix the tratio to a particular value. \n");
10728	MrBayesPrint (" Revmatpr -- This parameter sets the prior for the substitution rates \n");
10729	MrBayesPrint (" of the GTR model for nucleotide data. The options are: \n");
10730	MrBayesPrint (" \n");
10731	MrBayesPrint (" prset revmatpr = dirichlet(<number>,<number>,...,<number>)\n");
10732	MrBayesPrint (" prset revmatpr = fixed(<number>,<number>,...,<number>) \n");
10733	MrBayesPrint (" \n");
10734	MrBayesPrint (" The program assumes that the six substitution rates \n");
10735	MrBayesPrint (" are independent gamma-distributed random variables with the \n");
10736	MrBayesPrint (" same scale parameter when dirichlet is selected. The six \n");
10737	MrBayesPrint (" numbers in brackets each corresponds to a particular substi- \n");
10738	MrBayesPrint (" tution type. Together, they determine the shape of the prior.\n");
10739	MrBayesPrint (" The six rates are in the order A<->C, A<->G, A<->T, C<->G, \n");
10740	MrBayesPrint (" C<->T, and G<->T. If you want an uninformative prior you can \n");
10741	MrBayesPrint (" use dirichlet(1,1,1,1,1,1), also referred to as a 'flat' \n");
10742	MrBayesPrint (" Dirichlet. This is the default setting. If you wish a prior \n");
10743	MrBayesPrint (" where the C<->T rate is 5 times and the A<->G rate 2 times \n");
10744	MrBayesPrint (" higher, on average, than the transversion rates, which are \n");
10745	MrBayesPrint (" all the same, then you should use a prior of the form \n");
10746	MrBayesPrint (" dirichlet(x,2x,x,x,5x,x), where x determines how much the \n");
10747	MrBayesPrint (" prior is focused on these particular rates. For more info, \n");
10748	MrBayesPrint (" see tratiopr. The fixed option allows you to fix the substi- \n");
10749	MrBayesPrint (" tution rates to particular values. \n");
10750	MrBayesPrint (" Revratepr -- This parameter sets the prior for each substitution rate of \n");
10751	MrBayesPrint (" the GTR model subspace when 'nst' is set to 'mixed' (see the \n");
10752	MrBayesPrint (" 'lset' command). The only option is \n");
10753	MrBayesPrint (" \n");
10754	MrBayesPrint (" prset revratepr = symdir(<number>) \n");
10755	MrBayesPrint (" \n");
10756	MrBayesPrint (" which will associate each independent rate in the rate matrix\n");
10757	MrBayesPrint (" with a modified symmetric Dirichlet prior, where a singleton \n");
10758	MrBayesPrint (" rate has the specified alpha parameter, while a rate that \n");
10759	MrBayesPrint (" applies to n pairwise substitution types has an alpha that is\n");
10760	MrBayesPrint (" n times the specified number. The higher the specified num- \n");
10761	MrBayesPrint (" ber, the more focused the prior will be on equal rates. The \n");
10762	MrBayesPrint (" default value is 1, which gives an effect similar to a flat \n");
10763	MrBayesPrint (" Dirichlet. \n");
10764	MrBayesPrint (" Aamodelpr -- This parameter sets the rate matrix for amino acid data. \n");
10765	MrBayesPrint (" You can either fix the model by specifying aamodelpr= \n");
10766	MrBayesPrint (" fixed(<model name>), where <model name> is 'poisson' (a \n");
10767	MrBayesPrint (" glorified Jukes-Cantor model), 'jones', 'dayhoff', 'mtrev', \n");
10768	MrBayesPrint (" 'mtmam', 'wag', 'rtrev', 'cprev', 'vt', 'blosum', 'equalin' \n");
10769	MrBayesPrint (" (a glorified Felsenstein 1981 model), or 'gtr'. You can also \n");
10770	MrBayesPrint (" average over the first ten models by specifying aamodelpr= \n");
10771	MrBayesPrint (" mixed. If you do so, the Markov chain will sample each model \n");
10772	MrBayesPrint (" according to its probability. The sampled model is reported \n");
10773	MrBayesPrint (" as an index: poisson(0), jones(1), dayhoff(2), mtrev(3), \n");
10774	MrBayesPrint (" mtmam(4), wag(5), rtrev(6), cprev(7), vt(8), or blosum(9). \n");
10775	MrBayesPrint (" The 'Sump' command summarizes the MCMC samples and calculates\n");
10776	MrBayesPrint (" the posterior probability estimate for each of these models. \n");
10777	MrBayesPrint (" Aarevmatpr -- This parameter sets the prior for the substitution rates \n");
10778	MrBayesPrint (" of the GTR model for amino acid data. The options are: \n");
10779	MrBayesPrint (" \n");
10780	MrBayesPrint (" prset revmatpr = dirichlet(<number>,<number>,...,<number>)\n");
10781	MrBayesPrint (" prset revmatpr = fixed(<number>,<number>,...,<number>) \n");
10782	MrBayesPrint (" \n");
10783	MrBayesPrint (" The options are the same as those for 'Revmatpr' except that \n");
10784	MrBayesPrint (" they are defined over the 190 rates of the time-reversible \n");
10785	MrBayesPrint (" GTR model for amino acids instead of over the 6 rates of the \n");
10786	MrBayesPrint (" GTR model for nucleotides. The rates are in the order A<->R, \n");
10787	MrBayesPrint (" A<->N, etc to Y<->V. In other words, amino acids are listed \n");
10788	MrBayesPrint (" in alphabetic order based on their full name. The first amino\n");
10789	MrBayesPrint (" acid (Alanine) is then combined in turn with all amino acids \n");
10790	MrBayesPrint (" following it in the list, starting with amino acid 2 (Argi- \n");
10791	MrBayesPrint (" nine) and finishing with amino acid 20 (Valine). The second \n");
10792	MrBayesPrint (" amino acid (Arginine) is then combined in turn with all amino\n");
10793	MrBayesPrint (" acids following it, starting with amino acid 3 (Asparagine) \n");
10794	MrBayesPrint (" and finishing with amino acid 20 (Valine), and so on. \n");
10795	MrBayesPrint (" Omegapr -- This parameter specifies the prior on the nonsynonymous/ \n");
10796	MrBayesPrint (" synonymous rate ratio. The options are: \n");
10797	MrBayesPrint (" \n");
10798	MrBayesPrint (" prset omegapr = uniform(<number>,<number>) \n");
10799	MrBayesPrint (" prset omegapr = exponential(<number>) \n");
10800	MrBayesPrint (" prset omegapr = fixed(<number>) \n");
10801	MrBayesPrint (" \n");
10802	MrBayesPrint (" This parameter is only in effect if the nucleotide sub- \n");
10803	MrBayesPrint (" stitution model is set to codon using the lset command \n");
10804	MrBayesPrint (" (lset nucmodel=codon). Moreover, it only applies to the \n");
10805	MrBayesPrint (" case when there is no variation in omega across sites (i.e., \n");
10806	MrBayesPrint (" \"lset omegavar=equal\"). \n");
10807	MrBayesPrint (" Ny98omega1pr -- This parameter specifies the prior on the nonsynonymous/ \n");
10808	MrBayesPrint (" synonymous rate ratio for sites under purifying selection. \n");
10809	MrBayesPrint (" The options are: \n");
10810	MrBayesPrint (" \n");
10811	MrBayesPrint (" prset Ny98omega1pr = beta(<number>,<number>) \n");
10812	MrBayesPrint (" prset Ny98omega1pr = fixed(<number>) \n");
10813	MrBayesPrint (" \n");
10814	MrBayesPrint (" This parameter is only in effect if the nucleotide sub- \n");
10815	MrBayesPrint (" stitution model is set to codon using the lset command \n");
10816	MrBayesPrint (" (lset nucmodel=codon). Moreover, it only applies to the \n");
10817	MrBayesPrint (" case where omega varies across sites using the model of \n");
10818	MrBayesPrint (" Nielsen and Yang (1998) (i.e., \"lset omegavar=ny98\"). If \n");
10819	MrBayesPrint (" fixing the parameter, you must specify a number between \n");
10820	MrBayesPrint (" 0 and 1. \n");
10821	MrBayesPrint (" Ny98omega3pr -- This parameter specifies the prior on the nonsynonymous/ \n");
10822	MrBayesPrint (" synonymous rate ratio for positively selected sites. The \n");
10823	MrBayesPrint (" options are: \n");
10824	MrBayesPrint (" \n");
10825	MrBayesPrint (" prset Ny98omega3pr = uniform(<number>,<number>) \n");
10826	MrBayesPrint (" prset Ny98omega3pr = exponential(<number>) \n");
10827	MrBayesPrint (" prset Ny98omega3pr = fixed(<number>) \n");
10828	MrBayesPrint (" \n");
10829	MrBayesPrint (" This parameter is only in effect if the nucleotide sub- \n");
10830	MrBayesPrint (" stitution model is set to codon using the lset command \n");
10831	MrBayesPrint (" (lset nucmodel=codon). Moreover, it only applies to the \n");
10832	MrBayesPrint (" case where omega varies across sites according to the \n");
10833	MrBayesPrint (" NY98 model. Note that if the NY98 model is specified \n");
10834	MrBayesPrint (" that this parameter must be greater than 1, so you should \n");
10835	MrBayesPrint (" not specify a uniform(0,10) prior, for example. \n");
10836	MrBayesPrint (" M3omegapr -- This parameter specifies the prior on the nonsynonymous/ \n");
10837	MrBayesPrint (" synonymous rate ratios for all three classes of sites for \n");
10838	MrBayesPrint (" the M3 model. The options are: \n");
10839	MrBayesPrint (" \n");
10840	MrBayesPrint (" prset M3omegapr = exponential \n");
10841	MrBayesPrint (" prset M3omegapr = fixed(<number>,<number>,<number>) \n");
10842	MrBayesPrint (" \n");
10843	MrBayesPrint (" This parameter is only in effect if the nucleotide sub- \n");
10844	MrBayesPrint (" stitution model is set to codon using the lset command \n");
10845	MrBayesPrint (" (lset nucmodel=codon). Moreover, it only applies to the \n");
10846	MrBayesPrint (" case where omega varies across sites using the M3 model of \n");
10847	MrBayesPrint (" Yang et al. (2000) (i.e., \"lset omegavar=M3\"). Under the \n");
10848	MrBayesPrint (" exponential prior, the four rates (dN1, dN2, dN3, and dS) \n");
10849	MrBayesPrint (" are all considered to be independent draws from the same \n");
10850	MrBayesPrint (" exponential distribution (the parameter of the exponential \n");
10851	MrBayesPrint (" does not matter, and so you don't need to specify it). The \n");
10852	MrBayesPrint (" rates dN1, dN2, and dN3 are taken to be the order statistics \n");
10853	MrBayesPrint (" with dN1 < dN2 < dN3. These three rates are all scaled to \n");
10854	MrBayesPrint (" the same synonymous rate, dS. The other option is to simply \n");
10855	MrBayesPrint (" fix the three rate ratios to some values. \n");
10856	MrBayesPrint (" Codoncatfreqs -- This parameter specifies the prior on frequencies of sites \n");
10857	MrBayesPrint (" under purifying, neutral, and positive selection. The \n");
10858	MrBayesPrint (" options are: \n");
10859	MrBayesPrint (" \n");
10860	MrBayesPrint (" prset codoncatfreqs = dirichlet(<num>,<num>,<num>) \n");
10861	MrBayesPrint (" prset codoncatfreqs = fixed(<number>,<number>,<number>) \n");
10862	MrBayesPrint (" \n");
10863	MrBayesPrint (" This parameter is only in effect if the nucleotide sub- \n");
10864	MrBayesPrint (" stitution model is set to codon using the lset command \n");
10865	MrBayesPrint (" (lset nucmodel=codon). Moreover, it only applies to the \n");
10866	MrBayesPrint (" case where omega varies across sites using the models of \n");
10867	MrBayesPrint (" Nielsen and Yang (1998) (i.e., \"lset omegavar=ny98\") \n");
10868	MrBayesPrint (" or Yang et al. (2000) (i.e., \"lset omegavar=M3\") \n");
10869	MrBayesPrint (" Note that the sum of the three frequencies must be 1. \n");
10870	MrBayesPrint (" Statefreqpr -- This parameter specifies the prior on the state freq- \n");
10871	MrBayesPrint (" uencies. The options are: \n");
10872	MrBayesPrint (" \n");
10873	MrBayesPrint (" prset statefreqpr = dirichlet(<number>) \n");
10874	MrBayesPrint (" prset statefreqpr = dirichlet(<number>,...,<number>) \n");
10875	MrBayesPrint (" prset statefreqpr = fixed(equal) \n");
10876	MrBayesPrint (" prset statefreqpr = fixed(empirical) \n");
10877	MrBayesPrint (" prset statefreqpr = fixed(<number>,...,<number>) \n");
10878	MrBayesPrint (" \n");
10879	MrBayesPrint (" For the dirichlet, you can specify either a single number \n");
10880	MrBayesPrint (" or as many numbers as there are states. If you specify a \n");
10881	MrBayesPrint (" single number, then the prior has all states equally \n");
10882	MrBayesPrint (" probable with a variance related to the single parameter \n");
10883	MrBayesPrint (" passed in. \n");
10884	MrBayesPrint (" Shapepr -- This parameter specifies the prior for the gamma shape \n");
10885	MrBayesPrint (" parameter for among-site rate variation. The options are: \n");
10886	MrBayesPrint (" \n");
10887	MrBayesPrint (" prset shapepr = uniform(<number>,<number>) \n");
10888	MrBayesPrint (" prset shapepr = exponential(<number>) \n");
10889	MrBayesPrint (" prset shapepr = fixed(<number>) \n");
10890	MrBayesPrint (" \n");
10891	MrBayesPrint (" Pinvarpr -- This parameter specifies the prior for the proportion of \n");
10892	MrBayesPrint (" invariable sites. The options are: \n");
10893	MrBayesPrint (" \n");
10894	MrBayesPrint (" prset pinvarpr = uniform(<number>,<number>) \n");
10895	MrBayesPrint (" prset pinvarpr = fixed(<number>) \n");
10896	MrBayesPrint (" \n");
10897	MrBayesPrint (" Note that the valid range for the parameter is between 0 \n");
10898	MrBayesPrint (" and 1. Hence, \"prset pinvarpr=uniform(0,0.8)\" is valid \n");
10899	MrBayesPrint (" while \"prset pinvarpr=uniform(0,10)\" is not. The def- \n");
10900	MrBayesPrint (" ault setting is \"prset pinvarpr=uniform(0,1)\". \n");
10901	MrBayesPrint (" Ratecorrpr -- This parameter specifies the prior for the autocorrelation \n");
10902	MrBayesPrint (" parameter of the autocorrelated gamma distribution for \n");
10903	MrBayesPrint (" among-site rate variation. The options are: \n");
10904	MrBayesPrint (" \n");
10905	MrBayesPrint (" prset ratecorrpr = uniform(<number>,<number>) \n");
10906	MrBayesPrint (" prset ratecorrpr = fixed(<number>) \n");
10907	MrBayesPrint (" \n");
10908	MrBayesPrint (" Note that the valid range for the parameter is between -1 \n");
10909	MrBayesPrint (" and 1. Hence, \"prset ratecorrpr=uniform(-1,1)\" is valid \n");
10910	MrBayesPrint (" while \"prset ratecorrpr=uniform(-11,10)\" is not. The \n");
10911	MrBayesPrint (" default setting is \"prset ratecorrpr=uniform(-1,1)\". \n");
10912	MrBayesPrint (" Covswitchpr -- This option sets the prior for the covarion switching \n");
10913	MrBayesPrint (" rates. The options are: \n");
10914	MrBayesPrint (" \n");
10915	MrBayesPrint (" prset covswitchpr = uniform(<number>,<number>) \n");
10916	MrBayesPrint (" prset covswitchpr = exponential(<number>) \n");
10917	MrBayesPrint (" prset covswitchpr = fixed(<number>,<number>) \n");
10918	MrBayesPrint (" \n");
10919	MrBayesPrint (" The covarion model has two rates: a rate from on to off \n");
10920	MrBayesPrint (" and a rate from off to on. The rates are assumed to have \n");
10921	MrBayesPrint (" independent priors that individually are either uniformly \n");
10922	MrBayesPrint (" or exponentially distributed. The other option is to \n");
10923	MrBayesPrint (" fix the switching rates, in which case you must specify \n");
10924	MrBayesPrint (" both rates. (The first number is off->on and the second \n");
10925	MrBayesPrint (" is on->off). \n");
10926	MrBayesPrint (" Symdirihyperpr - This option sets the prior for the stationary frequencies \n");
10927	MrBayesPrint (" of the states for morphological (standard) data. There can \n");
10928	MrBayesPrint (" be as many as 10 states for standard data. However, the \n");
10929	MrBayesPrint (" labelling of the states is somewhat arbitrary. For example, \n");
10930	MrBayesPrint (" the state \"1\" for different characters does not have the \n");
10931	MrBayesPrint (" same meaning. This is not true for DNA characters, for ex- \n");
10932	MrBayesPrint (" ample, where a \"G\" has the same meaning across characters. \n");
10933	MrBayesPrint (" The fact that the labelling of morphological characters is \n");
10934	MrBayesPrint (" arbitrary makes it difficult to allow unequal character- \n");
10935	MrBayesPrint (" state frequencies. MrBayes gets around this problem by \n");
10936	MrBayesPrint (" assuming that the states have a dirichlet prior, with all \n");
10937	MrBayesPrint (" states having equal frequency. The variation in the diri- \n");
10938	MrBayesPrint (" chlet can be controlled by this parameter--symdirihyperpr. \n");
10939	MrBayesPrint (" Symdirihyperpr specifies the distribution on the variance \n");
10940	MrBayesPrint (" parameter of the dirichlet. The valid options are: \n");
10941	MrBayesPrint (" \n");
10942	MrBayesPrint (" prset Symdirihyperpr = uniform(<number>,<number>) \n");
10943	MrBayesPrint (" prset Symdirihyperpr = exponential(<number>) \n");
10944	MrBayesPrint (" prset Symdirihyperpr = fixed(<number>) \n");
10945	MrBayesPrint (" prset Symdirihyperpr = fixed(infinity) \n");
10946	MrBayesPrint (" \n");
10947	MrBayesPrint (" If \"fixed(infinity)\" is chosen, the dirichlet prior is \n");
10948	MrBayesPrint (" fixed such that all character states have equal frequency. \n");
10949	MrBayesPrint (" Topologypr -- This parameter specifies the prior probabilities of \n");
10950	MrBayesPrint (" phylogenies. The options are: \n");
10951	MrBayesPrint (" \n");
10952	MrBayesPrint (" prset topologypr = uniform \n");
10953	MrBayesPrint (" prset topologypr = speciestree \n");
10954	MrBayesPrint (" prset topologypr = constraints(<list>) \n");
10955	MrBayesPrint (" prset topologypr = fixed(<treename>) \n");
10956	MrBayesPrint (" \n");
10957	MrBayesPrint (" If the prior is selected to be \"uniform\", the default, \n");
10958	MrBayesPrint (" then all possible trees are considered a priori equally \n");
10959	MrBayesPrint (" probable. The 'speciestree' option is used when the topology \n");
10960	MrBayesPrint (" is constrained to fold inside a species tree together with \n");
10961	MrBayesPrint (" other (gene) trees. The constraints option allows you to \n");
10962	MrBayesPrint (" specify complicated prior probabilities on trees (constraints\n");
10963	MrBayesPrint (" are discussed more fully in \"help constraint\"). Note that \n");
10964	MrBayesPrint (" you must specify a list of constraints that you wish to be \n");
10965	MrBayesPrint (" obeyed. The list can be either the constraints' name or \n");
10966	MrBayesPrint (" number. Finally, you can fix the topology to that of a user \n");
10967	MrBayesPrint (" tree defined in a trees block. Branch lengths will still be \n");
10968	MrBayesPrint (" sampled as usual on the fixed topology. \n");
10969	MrBayesPrint (" Brlenspr -- This parameter specifies the prior probability dist- \n");
10970	MrBayesPrint (" ribution on branch lengths. The options are: \n");
10971	MrBayesPrint (" \n");
10972	MrBayesPrint (" prset brlenspr = unconstrained:uniform(<num>,<num>) \n");
10973	MrBayesPrint (" prset brlenspr = unconstrained:exponential(<number>) \n");
10974	MrBayesPrint (" prset brlenspr = clock:uniform \n");
10975	MrBayesPrint (" prset brlenspr = clock:birthdeath \n");
10976	MrBayesPrint (" prset brlenspr = clock:coalescence \n");
10977	MrBayesPrint (" prset brlenspr = clock:speciestreecoalescence \n");
10978	MrBayesPrint (" prset brlenspr = fixed(<treename>) \n");
10979	MrBayesPrint (" \n");
10980	MrBayesPrint (" Trees with unconstrained branch lengths are unrooted \n");
10981	MrBayesPrint (" whereas clock-constrained trees are rooted. The option \n");
10982	MrBayesPrint (" after the colon specifies the details of the probability \n");
10983	MrBayesPrint (" density of branch lengths. If you choose a birth-death \n");
10984	MrBayesPrint (" or coalescence prior, you may want to modify the details \n");
10985	MrBayesPrint (" of the parameters of those processes (speciation rate, \n");
10986	MrBayesPrint (" extinction rate and sample probability for the birth-death \n");
10987	MrBayesPrint (" prior; population size and clock rate parameter for the \n");
10988	MrBayesPrint (" coalescence prior). When gene trees are constrained to fold \n");
10989	MrBayesPrint (" inside species trees, the appropriate branch length prior is \n");
10990	MrBayesPrint (" 'clock:speciestreecoalescence'. Under this model, it is poss-\n");
10991	MrBayesPrint (" ible to control whether the population size is constant or \n");
10992	MrBayesPrint (" varies across the species tree using the 'popvarpr' setting. \n");
10993	MrBayesPrint (" Branch lengths can also be fixed but only if the topology is \n");
10994	MrBayesPrint (" fixed. \n");
10995	MrBayesPrint (" Treeagepr -- This parameter specifies the prior probability distribution \n");
10996	MrBayesPrint (" on the tree age when a uniform prior is used on the branch \n");
10997	MrBayesPrint (" lengths of a clock tree. \n");
10998	MrBayesPrint (" \n");
10999	MrBayesPrint (" The options are: \n");
11000	MrBayesPrint (" \n");
11001	MrBayesPrint (" prset treeagepr = Gamma(<num>,<num>) \n");
11002	MrBayesPrint (" prset treeagepr = Exponential(<number>) \n");
11003	MrBayesPrint (" prset treeagepr = Fixed(<number>) \n");
11004	MrBayesPrint (" \n");
11005	MrBayesPrint (" (And, yes, we know the exponential is a special case of the \n");
11006	MrBayesPrint (" gamma distribution.) The tree age is simply the age of the \n");
11007	MrBayesPrint (" most recent common ancestor of the tree. If the clock rate \n");
11008	MrBayesPrint (" is fixed to 1.0, which is the default, the tree age is equi- \n");
11009	MrBayesPrint (" valent to the expected number of substitutions from the root \n");
11010	MrBayesPrint (" to the tip of the tree. The tree age prior ensures that the \n");
11011	MrBayesPrint (" joint prior probability distribution for the uniform prior \n");
11012	MrBayesPrint (" model of branch lengths on a clock tree is proper. The de- \n");
11013	MrBayesPrint (" fault setting is 'Exponential(1)'. If the root node in the \n");
11014	MrBayesPrint (" tree is calibrated, the root calibration replaces the tree \n");
11015	MrBayesPrint (" age prior. \n");
11016	MrBayesPrint (" Speciationpr -- This parameter sets the prior on the net speciation rate, \n");
11017	MrBayesPrint (" that is, lambda - mu in the birth-death model. Options are: \n");
11018	MrBayesPrint (" \n");
11019	MrBayesPrint (" prset speciationpr = uniform(<number>,<number>) \n");
11020	MrBayesPrint (" prset speciationpr = exponential(<number>) \n");
11021	MrBayesPrint (" prset speciationpr = fixed(<number>) \n");
11022	MrBayesPrint (" \n");
11023	MrBayesPrint (" This parameter is only relevant if the birth-death \n");
11024	MrBayesPrint (" process is selected as the prior on branch lengths. \n");
11025	MrBayesPrint (" Extinctionpr -- This parameter sets the prior on the relative extinction \n");
11026	MrBayesPrint (" rate, that is, mu / lambda in the birth-death model; values \n");
11027	MrBayesPrint (" of this parameter are in the range (0,1). Prior options are: \n");
11028	MrBayesPrint (" \n");
11029	MrBayesPrint (" prset extinctionpr = beta(<number>,<number>) \n");
11030	MrBayesPrint (" prset extinctionpr = fixed(<number>) \n");
11031	MrBayesPrint (" \n");
11032	MrBayesPrint (" This parameter is only relevant if the birth-death \n");
11033	MrBayesPrint (" process is selected as the prior on branch lengths. \n");
11034	MrBayesPrint (" SampleStrat -- This parameter sets the strategy under which species \n");
11035	MrBayesPrint (" where sampled in the analysis. This is used with the \n");
11036	MrBayesPrint (" birth-death prior on trees (see HÃ¶hna et al, 2011). \n");
11037	MrBayesPrint (" Sampleprob -- This parameter sets the fraction of species that are \n");
11038	MrBayesPrint (" sampled in the analysis. This is used with the birth- \n");
11039	MrBayesPrint (" death prior on trees (see Yang and Rannala, 1997). \n");
11040	MrBayesPrint (" Popsizepr -- This parameter sets the prior on the population size compo- \n");
11041	MrBayesPrint (" nent of the coalescent parameter. The options are: \n");
11042	MrBayesPrint (" \n");
11043	MrBayesPrint (" prset popsizepr = uniform(<number>,<number>) \n");
11044	MrBayesPrint (" prset popsizepr = exponential(<number>) \n");
11045	MrBayesPrint (" prset popsizepr = fixed(<number>) \n");
11046	MrBayesPrint (" \n");
11047	MrBayesPrint (" This parameter is only relevant if the coalescence process is\n");
11048	MrBayesPrint (" selected as the prior on branch lengths. Note that the set- \n");
11049	MrBayesPrint (" ting of 'ploidy' in 'lset' is important for how this para- \n");
11050	MrBayesPrint (" meter is interpreted. \n");
11051	MrBayesPrint (" Popvarpr -- In a gene tree - species tree model, this parameter deter- \n");
11052	MrBayesPrint (" mines whether the population size is the same for the entire \n");
11053	MrBayesPrint (" species tree ('popvarpr = equal', the default), or varies \n");
11054	MrBayesPrint (" across branches of the species tree ('popvarpr=variable'). \n");
11055	/* MrBayesPrint (" Growthpr -- This parameter sets the prior on the exponential growth \n");
11056	MrBayesPrint (" parameter of the coalescence process. The options are: \n");
11057	MrBayesPrint (" \n");
11058	MrBayesPrint (" prset growthpr = uniform(<number>,<number>) \n");
11059	MrBayesPrint (" prset growthpr = exponential(<number>) \n");
11060	MrBayesPrint (" prset growthpr = fixed(<number>) \n");
11061	MrBayesPrint (" \n");
11062	MrBayesPrint (" This parameter is only relevant if the coalescence \n");
11063	MrBayesPrint (" process is selected as the prior on branch lengths. \n");*/
11064	MrBayesPrint (" Nodeagepr -- This parameter specifies the assumptions concerning the age \n");
11065	MrBayesPrint (" of the terminal and interior nodes in the tree. The default \n");
11066	MrBayesPrint (" model ('nodeagepr = unconstrained') assumes that all terminal\n");
11067	MrBayesPrint (" nodes are of the same age while the age of interior nodes is \n");
11068	MrBayesPrint (" unconstrained. The alternative ('nodeagepr = calibrated') \n");
11069	MrBayesPrint (" option derives a prior probability distribution on terminal \n");
11070	MrBayesPrint (" and interior node ages from the calibration settings (see \n");
11071	MrBayesPrint (" the 'calibrate' command). The 'nodeagepr' parameter is only \n");
11072	MrBayesPrint (" relevant for clock trees. \n");
11073	MrBayesPrint (" Clockratepr -- This parameter specifies the prior assumptions concerning the\n");
11074	MrBayesPrint (" base substitution rate of the tree, measured in expected num-\n");
11075	MrBayesPrint (" ber of substitutions per site per time unit. The default set-\n");
11076	MrBayesPrint (" ting is 'Fixed(1.0)', which effectively means that the time \n");
11077	MrBayesPrint (" unit is the number of expected substitutions per site. If you\n");
11078	MrBayesPrint (" apply age constraints to the tree, the default setting chan- \n");
11079	MrBayesPrint (" ges automatically to 'Exponential(<x>)', where '<x>' is set \n");
11080	MrBayesPrint (" such that the expectation of the exponential is ten times the\n");
11081	MrBayesPrint (" age of the maximum age constraint. This will give you a very \n");
11082	MrBayesPrint (" vague prior, which may or may not be adequate for your parti-\n");
11083	MrBayesPrint (" cular problem. \n");
11084	MrBayesPrint (" \n");
11085	MrBayesPrint (" If you do not have any age calibrations in the tree, you can \n");
11086	MrBayesPrint (" still calibrate the tree using 'Clockratepr'. For instance, \n");
11087	MrBayesPrint (" if you know that your sequence data evolve at a rate of 0.20 \n");
11088	MrBayesPrint (" substitutions per million years, you might calibrate the tree\n");
11089	MrBayesPrint (" by fixing the substitution rate to 0.20 using \n");
11090	MrBayesPrint (" \n");
11091	MrBayesPrint (" prset clockratepr = fixed(0.20) \n");
11092	MrBayesPrint (" \n");
11093	MrBayesPrint (" after which the tree will be calibrated using millions of \n");
11094	MrBayesPrint (" years as the unit. \n");
11095	MrBayesPrint (" \n");
11096	MrBayesPrint (" You can also assign a prior probability distribution to the \n");
11097	MrBayesPrint (" substitution rate, accommodating the uncertainty about its \n");
11098	MrBayesPrint (" value. You can choose between normal, lognormal, exponential \n");
11099	MrBayesPrint (" and gamma distributions for this purpose. For instance, if \n");
11100	MrBayesPrint (" you would like to associate the substitution rate with a \n");
11101	MrBayesPrint (" normal distribution truncated at 0, so that only positive \n");
11102	MrBayesPrint (" values are allowed, and with mean 0.20 and standard deviation\n");
11103	MrBayesPrint (" of 0.02, you would use \n");
11104	MrBayesPrint (" \n");
11105	MrBayesPrint (" prset clockratepr = normal(0.20,0.02) \n");
11106	MrBayesPrint (" \n");
11107	MrBayesPrint (" The lognormal distribution is parameterized in terms of the \n");
11108	MrBayesPrint (" mean and standard deviation on the log scale (natural logs). \n");
11109	MrBayesPrint (" For instance, \n");
11110	MrBayesPrint (" \n");
11111	MrBayesPrint (" prset clockratepr = lognormal(-1.61,0.10) \n");
11112	MrBayesPrint (" \n");
11113	MrBayesPrint (" specifies a lognormal distribution with a mean of log values \n");
11114	MrBayesPrint (" of -1.61 and a standard deviation of log values of 0.10. In \n");
11115	MrBayesPrint (" such a case, the mean value of the lognormal distribution is \n");
11116	MrBayesPrint (" equal to e^(-1.61 + 0.10^2/2) = 0.20. \n");
11117	MrBayesPrint (" \n");
11118	MrBayesPrint (" Note that the 'Clockratepr' parameter has no effect on non- \n");
11119	MrBayesPrint (" clock trees. \n");
11120	MrBayesPrint (" Clockvarpr -- This parameter allows you to specify the type of clock you \n");
11121	MrBayesPrint (" are assuming. The default is 'strict', which corresponds to \n");
11122	MrBayesPrint (" the standard clock model where the evolutionary rate is \n");
11123	MrBayesPrint (" constant throughout the tree. You can also use 'cpp', which \n");
11124	MrBayesPrint (" invokes a relaxed clock model where the rate evolves \n");
11125	MrBayesPrint (" according to a Compound Poisson Process (CPP) model (see \n");
11126	MrBayesPrint (" Huelsenbeck et al., 2000) or 'tk02', which invokes the \n");
11127	MrBayesPrint (" Brownian Motion (TK02) model described by Thorne and Kishino \n");
11128	MrBayesPrint (" (2002). Finally, you can use a model where each branch has an\n");
11129	MrBayesPrint (" independent rate drawn from a scaled gamma distribution, such\n");
11130	MrBayesPrint (" that there is a specified variance in the effective height of\n");
11131	MrBayesPrint (" the tree in the prior, the Independent Gamma Rate (IGR) \n");
11132	MrBayesPrint (" model (LePage et al., 2007). Each of the relaxed clock models\n");
11133	MrBayesPrint (" has additional parameters with priors. For the CPP model, it \n");
11134	MrBayesPrint (" is 'cppratepr' and 'cppmultdevpr'; for the TK02 model, it is \n");
11135	MrBayesPrint (" 'tk02varpr'; for the IGR model, it is 'igrvarpr'. The \n");
11136	MrBayesPrint (" 'clockvarpr' parameter is only relevant for clock trees. \n");
11137	MrBayesPrint (" \n");
11138	MrBayesPrint (" For backward compatibility, 'bm' is allowed as a synonym of \n");
11139	MrBayesPrint (" 'tk02', and 'ibr' as a synonym of 'igr'. \n");
11140	MrBayesPrint (" Cppratepr -- This parameter allows you to specify a prior probability \n");
11141	MrBayesPrint (" distribution on the rate of the Poisson process generating \n");
11142	MrBayesPrint (" changes in the evolutionary rate in the CPP relaxed clock \n");
11143	MrBayesPrint (" model. You can either fix the rate or associate it with an \n");
11144	MrBayesPrint (" exponential prior using \n");
11145	MrBayesPrint (" \n");
11146	MrBayesPrint (" prset cppratepr = fixed(<number>) \n");
11147	MrBayesPrint (" prset cppratepr = exponential(<number>) \n");
11148	MrBayesPrint (" \n");
11149	MrBayesPrint (" For instance, if you fix the rate to 2, then on a branch \n");
11150	MrBayesPrint (" with the length equual to one expresed in terms of average \n");
11151	MrBayesPrint (" expected number of substitution per site, you expect to see, \n");
11152	MrBayesPrint (" on average, two rate-modifying events. \n");
11153	MrBayesPrint (" If you put an exponential(0.1) on the rate, you will be \n");
11154	MrBayesPrint (" estimating the rate against a prior probability distribution \n");
11155	MrBayesPrint (" where the expected rate is 10 (= 1/0.1). \n");
11156	MrBayesPrint (" Cppmultdevpr -- This parameter allows you to specify the standard deviation \n");
11157	MrBayesPrint (" of the log-normal distribution from which the rate multi- \n");
11158	MrBayesPrint (" pliers of the CPP relaxed clock model are drawn. The standard\n");
11159	MrBayesPrint (" deviation is given on the log scale. The default value of 1.0\n");
11160	MrBayesPrint (" thus corresponds to rate multipliers varying from 0.37 (1/e) \n");
11161	MrBayesPrint (" to 2.7 (e) when they are +/- one standard deviation from the \n");
11162	MrBayesPrint (" expected mean. The expected mean of the logarithm of the mul-\n");
11163	MrBayesPrint (" pliers is fixed to 0, ensuring that the expected mean rate is\n");
11164	MrBayesPrint (" 1.0. You can change the default value by using \n");
11165	MrBayesPrint (" \n");
11166	MrBayesPrint (" prset cppmultdevpr = fixed(<number>) \n");
11167	MrBayesPrint (" \n");
11168	MrBayesPrint (" where <number> is the standard deviation on the log scale. \n");
11169	MrBayesPrint (" TK02varpr -- This parameter allows you to specify the prior probability \n");
11170	MrBayesPrint (" distribution for the variance of the rate multiplier in the \n");
11171	MrBayesPrint (" Thorne-Kishino ('Brownian motion') relaxed clock model. \n");
11172	MrBayesPrint (" Specifically, the parameter specifies the rate at which the \n");
11173	MrBayesPrint (" variance increases with respect to the base rate of the \n");
11174	MrBayesPrint (" clock. If you have a branch of a length corresponding to 0.4 \n");
11175	MrBayesPrint (" expected changes per site according to the base rate of the \n");
11176	MrBayesPrint (" clock, and the tk02var parameter has a value of 2.0, then the\n");
11177	MrBayesPrint (" rate multiplier at the end of the branch will be drawn from a\n");
11178	MrBayesPrint (" lognormal distribution with a variance of 0.4*2.0 (on the \n");
11179	MrBayesPrint (" linear, not the logarithm scale). The mean is the same as the\n");
11180	MrBayesPrint (" rate multiplier at the start of the branch (again on the \n");
11181	MrBayesPrint (" linear scale). \n");
11182	MrBayesPrint (" \n");
11183	MrBayesPrint (" You can set the parameter to a fixed value, or specify that \n");
11184	MrBayesPrint (" it is drawn from an exponential or uniform distribution: \n");
11185	MrBayesPrint (" \n");
11186	MrBayesPrint (" prset tk02varpr = fixed(<number>) \n");
11187	MrBayesPrint (" prset tk02varpr = exponential(<number>) \n");
11188	MrBayesPrint (" prset tk02varpr = uniform(<number>,<number>) \n");
11189	MrBayesPrint (" \n");
11190	MrBayesPrint (" For backward compatibility, 'bmvarpr' is allowed as a synonym\n");
11191	MrBayesPrint (" of 'tko2varpr'. \n");
11192	MrBayesPrint (" Igrvarpr -- This parameter allows you to specify a prior on the variance \n");
11193	MrBayesPrint (" of the gamma distribution from which the branch lengths are \n");
11194	MrBayesPrint (" drawn in the independent branch rate (IGR) relaxed clock \n");
11195	MrBayesPrint (" model. Specifically, the parameter specifies the rate at \n");
11196	MrBayesPrint (" which the variance increases with respect to the base rate of\n");
11197	MrBayesPrint (" the clock. If you have a branch of a length corresponding to \n");
11198	MrBayesPrint (" 0.4 expected changes per site according to the base rate of \n");
11199	MrBayesPrint (" the clock, and the igrvar parameter has a value of 2.0, then \n");
11200	MrBayesPrint (" the effective branch length will be drawn from a distribution\n");
11201	MrBayesPrint (" with a variance of 0.4*2.0. \n");
11202	MrBayesPrint (" \n");
11203	MrBayesPrint (" You can set the parameter to a fixed value, or specify that \n");
11204	MrBayesPrint (" it is drawn from an exponential or uniform distribution: \n");
11205	MrBayesPrint (" \n");
11206	MrBayesPrint (" prset igrvarpr = fixed(<number>) \n");
11207	MrBayesPrint (" prset igrvarpr = exponential(<number>) \n");
11208	MrBayesPrint (" prset igrvarpr = uniform(<number>,<number>) \n");
11209	MrBayesPrint (" \n");
11210	MrBayesPrint (" For backward compatibility, 'ibrvarpr' is allowed as a syn- \n");
11211	MrBayesPrint (" onym of 'igrvarpr'. \n");
11212	MrBayesPrint (" Ratepr -- This parameter allows you to specify the site specific rates \n");
11213	MrBayesPrint (" model or any other model that allows different partitions to \n");
11214	MrBayesPrint (" evolve at different rates. First, you must have defined a \n");
11215	MrBayesPrint (" partition of the characters. For example, you may define a \n");
11216	MrBayesPrint (" partition that divides the characters by codon position, if \n");
11217	MrBayesPrint (" you have DNA data. You can also divide your data using a \n");
11218	MrBayesPrint (" partition that separates different genes from each other. \n");
11219	MrBayesPrint (" The next step is to make the desired partition the active one\n");
11220	MrBayesPrint (" using the set command. For example, if your partition is \n");
11221	MrBayesPrint (" called \"by_codon\", then you make that the active partition \n");
11222	MrBayesPrint (" using \"set partition=by_codon\". Now that you have defined \n");
11223	MrBayesPrint (" and activated a partition, you can specify the rate multi- \n");
11224	MrBayesPrint (" pliers for the various partitions. The options are: \n");
11225	MrBayesPrint (" \n");
11226	MrBayesPrint (" prset ratepr = fixed \n");
11227	MrBayesPrint (" prset ratepr = variable \n");
11228	MrBayesPrint (" prset ratepr = dirichlet(<number>,<number>,...,<number>) \n");
11229	MrBayesPrint (" \n");
11230	MrBayesPrint (" If you specify \"fixed\", then the rate multiplier for \n");
11231	MrBayesPrint (" that partition is set to 1 (i.e., the rate is fixed to \n");
11232	MrBayesPrint (" the average rate across partitions). On the other hand, \n");
11233	MrBayesPrint (" if you specify \"variable\", then the rate is allowed to \n");
11234	MrBayesPrint (" vary across partitions subject to the constraint that the \n");
11235	MrBayesPrint (" average rate of substitution across the partitions is 1. \n");
11236	MrBayesPrint (" You must specify a variable rate prior for at least two \n");
11237	MrBayesPrint (" partitions, otherwise the option is not activated when \n");
11238	MrBayesPrint (" calculating likelihoods. The variable option automatically \n");
11239	MrBayesPrint (" associates the partition rates with a dirichlet(1,...,1) \n");
11240	MrBayesPrint (" prior. The dirichlet option is an alternative way of setting \n");
11241	MrBayesPrint (" a partition rate to be variable, and also gives accurate \n");
11242	MrBayesPrint (" control of the shape of the prior. The parameters of the \n");
11243	MrBayesPrint (" Dirichlet are listed in the order of the partitions that the \n");
11244	MrBayesPrint (" ratepr is applied to. For instance, \"prset applyto=(1,3,4) \n");
11245	MrBayesPrint (" ratepr = dirichlet(10,40,15)\" would set the Dirichlet para- \n");
11246	MrBayesPrint (" meter 10 to partition 1, 40 to partition 3, and 15 to parti- \n");
11247	MrBayesPrint (" tion 4. The Dirichlet distribution is applied to the weighted\n");
11248	MrBayesPrint (" rates; that is, it weights the partition rates according to \n");
11249	MrBayesPrint (" the number of included characters in each partition. \n");
11250	MrBayesPrint (" \n");
11251	if (numCurrentDivisions == 0)
11252	tempInt = 1;
11253	else
11254	tempInt = numCurrentDivisions;
11255	for (i=0; i<tempInt; i++)
11256	{
11257	if (numCurrentDivisions == 0)
11258	{
11259	MrBayesPrint (" Default model settings: \n");
11260	mp = &defaultModel;
11261	}
11262	else
11263	{
11264	MrBayesPrint (" Model settings for partition %d: \n", i+1);
11265	mp = &modelParams[i];
11266	}
11267	MrBayesPrint (" \n");
11268	MrBayesPrint (" Parameter Options Current Setting \n");
11269	MrBayesPrint (" ------------------------------------------------------------------ \n");
11270
11271	MrBayesPrint (" Tratiopr Beta/Fixed %s", mp->tRatioPr);
11272	if (!strcmp(mp->tRatioPr, "Beta"))
11273	MrBayesPrint ("(%1.1lf,%1.1lf)\n", mp->tRatioDir[0], mp->tRatioDir[1]);
11274	else
11275	MrBayesPrint ("(%1.1lf)\n", mp->tRatioFix);
11276
11277	MrBayesPrint (" Revmatpr Dirichlet/Fixed %s", mp->revMatPr);
11278	if (!strcmp(mp->revMatPr, "Dirichlet"))
11279	MrBayesPrint ("(%1.1lf,%1.1lf,%1.1lf,%1.1lf,%1.1lf,%1.1lf)\n", mp->revMatDir[0],
11280	mp->revMatDir[1], mp->revMatDir[2], mp->revMatDir[3],
11281	mp->revMatDir[4], mp->revMatDir[5]);
11282	else
11283	MrBayesPrint ("(%1.1lf,%1.1lf,%1.1lf,%1.1lf,%1.1lf,%1.1lf)\n", mp->revMatFix[0],
11284	mp->revMatFix[1], mp->revMatFix[2], mp->revMatFix[3],
11285	mp->revMatFix[4], mp->revMatFix[5]);
11286
11287	MrBayesPrint (" Aamodelpr Fixed/Mixed %s", mp->aaModelPr);
11288	if (!strcmp(mp->aaModelPr, "Fixed"))
11289	MrBayesPrint ("(%s)\n", mp->aaModel);
11290	else
11291	MrBayesPrint ("\n");
11292
11293	MrBayesPrint (" Aarevmatpr Dirichlet/Fixed %s", mp->aaRevMatPr);
11294	if (!strcmp(mp->revMatPr, "Dirichlet"))
11295	{
11296	for (j=1; j<190; j++)
11297	if (AreDoublesEqual (mp->aaRevMatDir[0], mp->aaRevMatDir[j], 0.00001) == NO)
11298	break;
11299	if (j==190)
11300	MrBayesPrint ("(%1.1lf,%1.1lf,...)\n", mp->revMatDir[0], mp->revMatDir[0]);
11301	else
11302	MrBayesPrint (" (use 'Showmodel' to see values set by user)\n");
11303	}
11304	else
11305	{
11306	for (j=1; j<190; j++)
11307	if (AreDoublesEqual (mp->aaRevMatFix[0], mp->aaRevMatFix[j], 0.00001) == NO)
11308	break;
11309	if (j==190)
11310	MrBayesPrint ("(%1.1lf,%1.1lf,...)\n", mp->revMatFix[0], mp->revMatFix[0]);
11311	else
11312	MrBayesPrint (" (use 'Showmodel' to see values set by user)\n");
11313	}
11314
11315	MrBayesPrint (" Omegapr Dirichlet/Fixed %s", mp->omegaPr);
11316	if (!strcmp(mp->omegaPr, "Dirichlet"))
11317	MrBayesPrint ("(%1.1lf,%1.1lf)\n", mp->omegaDir[0], mp->omegaDir[1]);
11318	else
11319	MrBayesPrint ("(%1.1lf)\n", mp->omegaFix);
11320
11321	MrBayesPrint (" Ny98omega1pr Beta/Fixed %s", mp->ny98omega1pr);
11322	if (!strcmp(mp->ny98omega1pr, "Beta"))
11323	MrBayesPrint ("(%1.1lf,%1.1lf)\n", mp->ny98omega1Beta[0], mp->ny98omega1Beta[1]);
11324	else if (!strcmp(mp->ny98omega1pr, "Fixed"))
11325	MrBayesPrint ("(%1.1lf)\n", mp->ny98omega1Fixed);
11326
11327	MrBayesPrint (" Ny98omega3pr Uniform/Exponential/Fixed %s", mp->ny98omega3pr);
11328	if (!strcmp(mp->ny98omega3pr, "Uniform"))
11329	MrBayesPrint ("(%1.1lf,%1.1lf)\n", mp->ny98omega3Uni[0], mp->ny98omega3Uni[1]);
11330	else if (!strcmp(mp->ny98omega3pr, "Exponential"))
11331	MrBayesPrint ("(%1.1lf)\n", mp->ny98omega3Exp);
11332	else
11333	MrBayesPrint ("(%1.1lf)\n", mp->ny98omega3Fixed);
11334
11335	MrBayesPrint (" M3omegapr Exponential/Fixed %s", mp->m3omegapr);
11336	if (!strcmp(mp->m3omegapr, "Exponential"))
11337	MrBayesPrint ("\n");
11338	else if (!strcmp(mp->m3omegapr, "Fixed"))
11339	MrBayesPrint ("(%1.1lf,%1.1lf,%1.1lf)\n", mp->m3omegaFixed[0], mp->m3omegaFixed[1], mp->m3omegaFixed[2]);
11340
11341	MrBayesPrint (" Codoncatfreqs Dirichlet/Fixed %s", mp->codonCatFreqPr);
11342	if (!strcmp(mp->codonCatFreqPr, "Dirichlet"))
11343	MrBayesPrint ("(%1.1lf,%1.1lf,%1.1lf)\n", mp->codonCatDir[0], mp->codonCatDir[1], mp->codonCatDir[2]);
11344	else
11345	MrBayesPrint ("(%1.1lf,%1.1lf,%1.1lf)\n", mp->codonCatFreqFix[0], mp->codonCatFreqFix[1], mp->codonCatFreqFix[2]);
11346
11347	MrBayesPrint (" Statefreqpr Dirichlet/Fixed %s", mp->stateFreqPr);
11348	if (!strcmp(mp->stateFreqPr, "Dirichlet"))
11349	{
11350	if (mp->dataType == DNA \|\| mp->dataType == RNA)
11351	{
11352	if (!strcmp(mp->nucModel, "4by4"))
11353	MrBayesPrint ("(%1.1lf,%1.1lf,%1.1lf,%1.1lf)\n", mp->stateFreqsDir[0], mp->stateFreqsDir[1],
11354	mp->stateFreqsDir[2], mp->stateFreqsDir[3]);
11355	else
11356	MrBayesPrint ("\n");
11357	}
11358	else if (mp->dataType == RESTRICTION)
11359	{
11360	MrBayesPrint ("(%1.1lf,%1.1lf)\n", mp->stateFreqsDir[0], mp->stateFreqsDir[1]);
11361	}
11362	else
11363	MrBayesPrint ("\n");
11364	}
11365	else if (!strcmp(mp->stateFreqPr, "Fixed"))
11366	{
11367	if (mp->dataType == DNA \|\| mp->dataType == RNA)
11368	{
11369	if (!strcmp(mp->nucModel, "4by4"))
11370	MrBayesPrint ("(%1.1lf,%1.1lf,%1.1lf,%1.1lf)\n", mp->stateFreqsFix[0], mp->stateFreqsFix[1],
11371	mp->stateFreqsFix[2], mp->stateFreqsFix[3]);
11372	else
11373	MrBayesPrint ("\n");
11374	}
11375	else if (mp->dataType == RESTRICTION)
11376	{
11377	MrBayesPrint ("(%1.1lf,%1.1lf)\n", mp->stateFreqsFix[0], mp->stateFreqsFix[1]);
11378	}
11379	else
11380	MrBayesPrint ("\n");
11381	}
11382
11383	MrBayesPrint (" Shapepr Uniform/Exponential/Fixed %s", mp->shapePr);
11384	if (!strcmp(mp->shapePr, "Uniform"))
11385	MrBayesPrint ("(%1.1lf,%1.1lf)\n", mp->shapeUni[0], mp->shapeUni[1]);
11386	else if (!strcmp(mp->shapePr, "Exponential"))
11387	MrBayesPrint ("(%1.1lf)\n", mp->shapeExp);
11388	else
11389	MrBayesPrint ("(%1.1lf)\n", mp->shapeFix);
11390
11391	MrBayesPrint (" Ratecorrpr Uniform/Fixed %s", mp->adGammaCorPr);
11392	if (!strcmp(mp->adGammaCorPr, "Uniform"))
11393	MrBayesPrint ("(%1.1lf,%1.1lf)\n", mp->corrUni[0], mp->corrUni[1]);
11394	else
11395	MrBayesPrint ("(%1.1lf)\n", mp->corrFix);
11396
11397	MrBayesPrint (" Pinvarpr Uniform/Fixed %s", mp->pInvarPr);
11398	if (!strcmp(mp->pInvarPr, "Uniform"))
11399	MrBayesPrint ("(%1.1lf,%1.1lf)\n", mp->pInvarUni[0], mp->pInvarUni[1]);
11400	else
11401	MrBayesPrint ("(%1.1lf)\n", mp->pInvarFix);
11402
11403	MrBayesPrint (" Covswitchpr Uniform/Exponential/Fixed %s", mp->covSwitchPr);
11404	if (!strcmp(mp->covSwitchPr, "Uniform"))
11405	MrBayesPrint ("(%1.1lf,%1.1lf)\n", mp->covswitchUni[0], mp->covswitchUni[1]);
11406	else if (!strcmp(mp->covSwitchPr, "Exponential"))
11407	MrBayesPrint ("(%1.1lf)\n", mp->covswitchExp);
11408	else
11409	MrBayesPrint ("(%1.1lf,%1.1lf)\n", mp->covswitchFix[0], mp->covswitchFix[1]);
11410
11411	MrBayesPrint (" Symdirihyperpr Uniform/Exponential/Fixed %s", mp->symPiPr);
11412	if (!strcmp(mp->symPiPr, "Uniform"))
11413	MrBayesPrint ("(%1.1lf,%1.1lf)\n", mp->symBetaUni[0], mp->symBetaUni[1]);
11414	else if (!strcmp(mp->covSwitchPr, "Exponential"))
11415	MrBayesPrint ("(%1.1lf)\n", mp->symBetaExp);
11416	else
11417	{
11418	if (mp->symBetaFix < 0)
11419	MrBayesPrint ("(Infinity)\n");
11420	else
11421	MrBayesPrint ("(%1.1lf)\n", mp->symBetaFix);
11422	}
11423
11424	MrBayesPrint (" Topologypr Uniform/Constraints/Fixed %s", mp->topologyPr);
11425	if (!strcmp(mp->topologyPr, "Constraints"))
11426	{
11427	MrBayesPrint ("(");
11428	for (j=0; j<numDefinedConstraints; j++)
11429	{
11430	if (mp->activeConstraints[j] == YES)
11431	{
11432	MrBayesPrint ("%d", j+1);
11433	break;
11434	}
11435	}
11436	for (j++; j<numDefinedConstraints; j++)
11437	{
11438	if (mp->activeConstraints[j] == YES)
11439	{
11440	MrBayesPrint (",%d", j+1);
11441	}
11442	}
11443	MrBayesPrint (")\n");
11444	}
11445	else if (!strcmp(mp->topologyPr, "Fixed"))
11446	MrBayesPrint("(%s)\n", userTree[mp->topologyFix]->name);
11447	else
11448	MrBayesPrint ("\n");
11449
11450	MrBayesPrint (" Brlenspr Unconstrained/Clock/Fixed %s", mp->brlensPr);
11451	if (!strcmp(mp->brlensPr, "Unconstrained"))
11452	{
11453	if (!strcmp(mp->unconstrainedPr, "Uniform"))
11454	MrBayesPrint (":Uni(%1.1lf,%1.1lf)\n", mp->brlensUni[0], mp->brlensUni[1]);
11455	else
11456	MrBayesPrint (":Exp(%1.1lf)\n", mp->brlensExp);
11457	}
11458	else if (!strcmp(mp->brlensPr, "Clock"))
11459	{
11460	if (!strcmp(mp->clockPr,"Fixed"))
11461	MrBayesPrint (":%s(%s)\n", mp->clockPr, userTree[mp->brlensFix]->name);
11462	else
11463	MrBayesPrint (":%s\n", mp->clockPr);
11464	}
11465	else if (!strcmp(mp->brlensPr, "Fixed"))
11466	MrBayesPrint("(%s)\n", userTree[mp->brlensFix]->name);
11467
11468	MrBayesPrint (" Treeagepr Exponential/Gamma/Fixed %s", mp->treeAgePr);
11469	if (!strcmp(mp->treeAgePr, "Gamma"))
11470	MrBayesPrint ("(%1.1lf,%1.1lf)\n", mp->treeAgeGamma[0], mp->treeAgeGamma[1]);
11471	else if (!strcmp(mp->treeAgePr, "Fixed"))
11472	MrBayesPrint ("(%1.1lf)\n", mp->treeAgeFix);
11473	else /* if (!strcmp(mp->speciationPr, "Exponential")) */
11474	MrBayesPrint ("(%1.1lf)\n", mp->treeAgeExp);
11475
11476	MrBayesPrint (" Speciationpr Uniform/Exponential/Fixed %s", mp->speciationPr);
11477	if (!strcmp(mp->speciationPr, "Uniform"))
11478	MrBayesPrint ("(%1.1lf,%1.1lf)\n", mp->speciationUni[0], mp->speciationUni[1]);
11479	else if (!strcmp(mp->speciationPr, "Exponential"))
11480	MrBayesPrint ("(%1.1lf)\n", mp->speciationExp);
11481	else
11482	MrBayesPrint ("(%1.1lf)\n", mp->speciationFix);
11483
11484	MrBayesPrint (" Extinctionpr Beta/Fixed %s", mp->extinctionPr);
11485	if (!strcmp(mp->extinctionPr, "Beta"))
11486	MrBayesPrint ("(%1.1lf,%1.1lf)\n", mp->extinctionBeta[0], mp->extinctionBeta[1]);
11487	else
11488	MrBayesPrint ("(%1.1lf)\n", mp->extinctionFix);
11489	MrBayesPrint (" SampleStrat Random/Diversity/Cluster %s\n", mp->sampleStrat);
11490	MrBayesPrint (" Sampleprob <number> %1.2lf\n", mp->sampleProb);
11491
11492	MrBayesPrint (" Popsizepr Lognormal/Gamma/Uniform/ %s", mp->popSizePr);
11493	if (!strcmp(mp->popSizePr, "Uniform"))
11494	MrBayesPrint ("(%1.1lf,%1.1lf)\n", mp->popSizeUni[0], mp->popSizeUni[1]);
11495	else if (!strcmp(mp->popSizePr, "Lognormal"))
11496	MrBayesPrint ("(%1.1lf,%1.1lf)\n", mp->popSizeLognormal[0], mp->popSizeLognormal[1]);
11497	else if (!strcmp(mp->popSizePr, "Normal"))
11498	MrBayesPrint ("(%1.1lf,%1.1lf)\n", mp->popSizeNormal[0], mp->popSizeNormal[1]);
11499	else if (!strcmp(mp->popSizePr, "Gamma"))
11500	MrBayesPrint ("(%1.1lf,%1.1lf)\n", mp->popSizeGamma[0], mp->popSizeGamma[1]);
11501	else
11502	MrBayesPrint ("(%1.1lf)\n", mp->popSizeFix);
11503	MrBayesPrint (" Normal/Fixed \n");
11504
11505	MrBayesPrint (" Popvarpr Equal/Variable %s\n", mp->popVarPr);
11506
11507	/*
11508	MrBayesPrint (" Growthpr Uniform/Exponential/ \n");
11509	MrBayesPrint (" Fixed/Normal %s", mp->growthPr);
11510	if (!strcmp(mp->growthPr, "Uniform"))
11511	MrBayesPrint ("(%1.1lf,%1.1lf)\n", mp->growthUni[0], mp->growthUni[1]);
11512	else if (!strcmp(mp->growthPr, "Exponential"))
11513	MrBayesPrint ("(%1.1lf)\n", mp->growthExp);
11514	else if (!strcmp(mp->growthPr, "Normal"))
11515	MrBayesPrint ("(%1.1lf,%1.1lf)\n", mp->growthNorm[0], mp->growthNorm[1]);
11516	else
11517	MrBayesPrint ("(%1.1lf)\n", mp->growthFix);
11518	*/
11519
11520	MrBayesPrint (" Nodeagepr Unconstrained/Calibrated %s\n", mp->nodeAgePr);
11521
11522	MrBayesPrint (" Clockratepr Fixed/Normal/Lognormal/\n%s", spacer);
11523	MrBayesPrint (" Exponential/Gamma %s", mp->clockRatePr);
11524	if (!strcmp(mp->clockRatePr, "Fixed"))
11525	MrBayesPrint ("(%1.2lf)\n", mp->clockRateFix);
11526	else if (!strcmp(mp->clockRatePr,"Exponential"))
11527	MrBayesPrint ("(%1.2lf)\n", mp->clockRateExp);
11528	else if (!strcmp(mp->clockRatePr,"Normal"))
11529	MrBayesPrint ("(%1.2lf,%1.2lf)\n", mp->clockRateNormal[0], mp->clockRateNormal[1]);
11530	else if (!strcmp(mp->clockRatePr,"Lognormal"))
11531	MrBayesPrint ("(%1.2lf,%1.2lf)\n", mp->clockRateLognormal[0], mp->clockRateLognormal[1]);
11532	else
11533	{
11534	assert (!strcmp(mp->clockRatePr,"Gamma"));
11535	MrBayesPrint ("(%1.2lf,%1.2lf)\n", mp->clockRateGamma[0], mp->clockRateGamma[1]);
11536	}
11537
11538	MrBayesPrint (" Clockvarpr Strict/Cpp/TK02/Igr %s\n", mp->clockVarPr);
11539
11540	MrBayesPrint (" Cppratepr Fixed/Exponential %s", mp->cppRatePr);
11541	if (!strcmp(mp->cppRatePr, "Fixed"))
11542	MrBayesPrint ("(%1.2lf)\n", mp->cppRateFix);
11543	else /* if (!strcmp(mp->cppRatePr,"Exponential")) */
11544	MrBayesPrint ("(%1.2lf)\n", mp->cppRateExp);
11545
11546	MrBayesPrint (" Cppmultdevpr Fixed %s", mp->cppMultDevPr);
11547	MrBayesPrint ("(%1.2lf)\n", mp->cppMultDevFix);
11548
11549	MrBayesPrint (" TK02varpr Fixed/Exponential/Uniform %s", mp->tk02varPr);
11550	if (!strcmp(mp->tk02varPr, "Fixed"))
11551	MrBayesPrint ("(%1.2lf)\n", mp->tk02varFix);
11552	else if (!strcmp(mp->tk02varPr,"Exponential"))
11553	MrBayesPrint ("(%1.2lf)\n", mp->tk02varExp);
11554	else
11555	{
11556	assert (!strcmp(mp->tk02varPr,"Uniform"));
11557	MrBayesPrint ("(%1.2lf,%1.2lf)\n", mp->tk02varUni[0], mp->tk02varUni[1]);
11558	}
11559
11560	MrBayesPrint (" Igrvarpr Fixed/Exponential/Uniform %s", mp->igrvarPr);
11561	if (!strcmp(mp->igrvarPr, "Fixed"))
11562	MrBayesPrint ("(%1.2lf)\n", mp->igrvarFix);
11563	else if (!strcmp(mp->igrvarPr,"Exponential"))
11564	MrBayesPrint ("(%1.2lf)\n", mp->igrvarExp);
11565	else
11566	{
11567	assert (!strcmp(mp->igrvarPr,"Uniform"));
11568	MrBayesPrint ("(%1.2lf,%1.2lf)\n", mp->igrvarUni[0], mp->igrvarUni[1]);
11569	}
11570
11571
11572	MrBayesPrint (" Ratepr Fixed/Variable=Dirichlet %s", mp->ratePr);
11573	if (!strcmp(mp->ratePr, "Dirichlet"))
11574	MrBayesPrint ("(...,%1.1lf,...)\n", mp->ratePrDir);
11575	else
11576	MrBayesPrint ("\n");
11577
11578	MrBayesPrint (" ------------------------------------------------------------------ \n");
11579	MrBayesPrint (" \n");
11580	}
11581	}
11582	else if (!strcmp(helpTkn, "Ctype"))
11583	{
11584	MrBayesPrint (" --------------------------------------------------------------------------- \n");
11585	MrBayesPrint (" Ctype \n");
11586	MrBayesPrint (" \n");
11587	MrBayesPrint (" This command sets the character ordering for standard-type data. The \n");
11588	MrBayesPrint (" correct usage is: \n");
11589	MrBayesPrint (" \n");
11590	MrBayesPrint (" ctype <ordering>:<characters> \n");
11591	MrBayesPrint (" \n");
11592	MrBayesPrint (" The available options for the <ordering> specifier are: \n");
11593	MrBayesPrint (" \n");
11594	MrBayesPrint (" unordered -- Movement directly from one state to another is \n");
11595	MrBayesPrint (" allowed in an instant of time. \n");
11596	MrBayesPrint (" ordered -- Movement is only allowed between adjacent characters. \n");
11597	MrBayesPrint (" For example, perhaps only between 0 <-> 1 and 1 <-> 2 \n");
11598	MrBayesPrint (" for a three state character ordered as 0 - 1 - 2. \n");
11599	MrBayesPrint (" irreversible -- Rates of change for losses are 0. \n");
11600	MrBayesPrint (" \n");
11601	MrBayesPrint (" The characters to which the ordering is applied is specified in manner \n");
11602	MrBayesPrint (" that is identical to commands such as \"include\" or \"exclude\". For \n");
11603	MrBayesPrint (" example, \n");
11604	MrBayesPrint (" \n");
11605	MrBayesPrint (" ctype ordered: 10 23 45 \n");
11606	MrBayesPrint (" \n");
11607	MrBayesPrint (" defines charactes 10, 23, and 45 to be of type ordered. Similarly, \n");
11608	MrBayesPrint (" \n");
11609	MrBayesPrint (" ctype irreversible: 54 - 67 71-92 \n");
11610	MrBayesPrint (" \n");
11611	MrBayesPrint (" defines characters 54 to 67 and characters 71 to 92 to be of type \n");
11612	MrBayesPrint (" irreversible. You can use the \".\" to denote the last character, and \n");
11613	MrBayesPrint (" \"all\" to denote all of the characters. Finally, you can use the \n");
11614	MrBayesPrint (" specifier \"\\\" to apply the ordering to every n-th character or \n");
11615	MrBayesPrint (" you can use predefined charsets to specify the character. \n");
11616	MrBayesPrint (" \n");
11617	MrBayesPrint (" Only one ordering can be used on any specific application of ctype. \n");
11618	MrBayesPrint (" If you want to apply different orderings to different characters, then \n");
11619	MrBayesPrint (" you need to use ctype multiple times. For example, \n");
11620	MrBayesPrint (" \n");
11621	MrBayesPrint (" ctype ordered: 1-50 \n");
11622	MrBayesPrint (" ctype irreversible: 51-100 \n");
11623	MrBayesPrint (" \n");
11624	MrBayesPrint (" sets characters 1 to 50 to be ordered and characters 51 to 100 to be \n");
11625	MrBayesPrint (" irreversible. \n");
11626	MrBayesPrint (" \n");
11627	MrBayesPrint (" The ctype command is only sensible with morphological (here called \n");
11628	MrBayesPrint (" \"standard\") characters. The program ignores attempts to apply char- \n");
11629	MrBayesPrint (" acter orderings to other types of characters, such as DNA characters. \n");
11630
11631	MrBayesPrint (" --------------------------------------------------------------------------- \n");
11632	}
11633	else if (!strcmp(helpTkn, "Propset"))
11634	{
11635	MrBayesPrint (" --------------------------------------------------------------------------- \n");
11636	MrBayesPrint (" Propset \n");
11637	MrBayesPrint (" \n");
11638	MrBayesPrint (" This command allows the user to change the details of the MCMC samplers \n");
11639	MrBayesPrint (" (moves) that update the state of the chain. The useage is: \n");
11640	MrBayesPrint (" \n");
11641	MrBayesPrint (" propset <move_name>$<tuning-parameter>=<value> \n");
11642	MrBayesPrint (" \n");
11643	MrBayesPrint (" Assume we have a topology parameter called 'Tau{all}', which is sampled by \n");
11644	MrBayesPrint (" the move 'ExtTBR(Tau{all})' (note that the parameter name is included in the \n");
11645	MrBayesPrint (" move name). This move has three tuning parameters: (1) 'prob', the relative \n");
11646	MrBayesPrint (" proposal probability (a weight defining its probability relative to other \n");
11647	MrBayesPrint (" moves); (2) 'p_ext', the extension probability; and (3) 'lambda', the tuning \n");
11648	MrBayesPrint (" parameter of the branch length multiplier. A list of the tuning parameters is \n");
11649	MrBayesPrint (" available by using 'Showmoves' (see below). To change the relative proposal \n");
11650	MrBayesPrint (" probability to 20 and the extension probability to 0.7, use: \n");
11651	MrBayesPrint (" \n");
11652	MrBayesPrint (" propset etbr(tau{all})$prob=20 etbr(tau{all})$p_ext=0.7 \n");
11653	MrBayesPrint (" \n");
11654	MrBayesPrint (" This change would apply to all chains in all runs. It is also possible to set \n");
11655	MrBayesPrint (" the tuning parameters of individual runs and chains using the format: \n");
11656	MrBayesPrint (" \n");
11657	MrBayesPrint (" propset <move_name>$<tuning-parameter>(<run>,<chain>)=<value> \n");
11658	MrBayesPrint (" \n");
11659	MrBayesPrint (" where <run> and <chain> are the index numbers of the run and chain for which \n");
11660	MrBayesPrint (" you want to change the value. If you leave out the index of the run, the \n");
11661	MrBayesPrint (" change will apply to all runs; if you leave out the index of the chain, the \n");
11662	MrBayesPrint (" change will similarly apply to all chains. To switch off the exttbr(tau{all}) \n");
11663	MrBayesPrint (" move in chain 2 of all runs, use: \n");
11664	MrBayesPrint (" \n");
11665	MrBayesPrint (" propset etbr(tau{all})$prob(,2)=0 \n");
11666	MrBayesPrint (" \n");
11667	MrBayesPrint (" It is important to note that all moves are not available until the model has \n");
11668	MrBayesPrint (" been completely defined. Any change to the model will cause all proposal \n");
11669	MrBayesPrint (" tuning parameters to return to their default values. To see a list of all the \n");
11670	MrBayesPrint (" moves that are currently switched on for the model, use 'showmoves'. You can \n");
11671	MrBayesPrint (" also see other available moves by using 'showmoves allavailable=yes'. A list \n");
11672	MrBayesPrint (" of the moves for each parameter in the model is available by using the command\n");
11673	MrBayesPrint (" 'Showparams'. If you change proposal probabilities, make sure that all \n");
11674	MrBayesPrint (" parameters that are not fixed in your model have at least one move switched \n");
11675	MrBayesPrint (" on. \n");
11676	MrBayesPrint (" \n");
11677	MrBayesPrint (" One word of warning: You should be extremely careful when modifying any \n");
11678	MrBayesPrint (" of the chain parameters using 'propset'. It is quite possible to completely \n");
11679	MrBayesPrint (" wreck any hope of achieving convergence by inappropriately setting the \n");
11680	MrBayesPrint (" tuning parameters. In general, you want to set move tuning parameters such \n");
11681	MrBayesPrint (" that the acceptance rate of the move is intermediate (we suggest targeting \n");
11682	MrBayesPrint (" the range 10%% to 70%% acceptance, if possible). If the acceptance rate is \n");
11683	MrBayesPrint (" outside of this range, the MCMC chain will probably not sample that parameter \n");
11684	MrBayesPrint (" very efficiently. The acceptance rates for all moves in the cold chain(s) are \n");
11685	MrBayesPrint (" summarized at the end of each run in the screen output. The acceptance rates \n");
11686	MrBayesPrint (" (potentially for all chains, cold and heated) are also printed to the .mcmc \n");
11687	MrBayesPrint (" file if Mcmc convergence diagnostics are turned on (using 'Mcmc' or 'Mcmcp'). \n");
11688	MrBayesPrint (" --------------------------------------------------------------------------- \n");
11689	}
11690	else if (!strcmp(helpTkn, "Log"))
11691	{
11692	MrBayesPrint (" --------------------------------------------------------------------------- \n");
11693	MrBayesPrint (" Log \n");
11694	MrBayesPrint (" \n");
11695	MrBayesPrint (" This command allows output to the screen to also be output to a file. \n");
11696	MrBayesPrint (" The useage is: \n");
11697	MrBayesPrint (" \n");
11698	MrBayesPrint (" log start/stop filename=<name> append/replace \n");
11699	MrBayesPrint (" \n");
11700	MrBayesPrint (" The options are: \n");
11701	MrBayesPrint (" \n");
11702	MrBayesPrint (" Start/Stop -- Starts or stops logging of output to file. \n");
11703	MrBayesPrint (" Append/Replace -- Either append to or replace existing file. \n");
11704	MrBayesPrint (" Filename -- Name of log file (currently, the name of the log \n");
11705	MrBayesPrint (" file is \"%s\").\n", logFileName);
11706	MrBayesPrint (" --------------------------------------------------------------------------- \n");
11707	}
11708	else if (!strcmp(helpTkn, "Translate"))
11709	{
11710	MrBayesPrint (" --------------------------------------------------------------------------- \n");
11711	MrBayesPrint (" Translate \n");
11712	MrBayesPrint (" \n");
11713	MrBayesPrint (" This command is used by MrBayes to specify the mapping between taxon names \n");
11714	MrBayesPrint (" and taxon numbers in a Nexus tree file. For instance, \n");
11715	MrBayesPrint (" \n");
11716	MrBayesPrint (" translate \n");
11717	MrBayesPrint (" 1 Homo, \n");
11718	MrBayesPrint (" 2 Pan, \n");
11719	MrBayesPrint (" 3 Gorilla, \n");
11720	MrBayesPrint (" 4 Hylobates; \n");
11721	MrBayesPrint (" \n");
11722	MrBayesPrint (" establishes that the taxon labeled 1 in the trees that follow is Homo, the \n");
11723	MrBayesPrint (" taxon labeled 2 is Pan, etc. \n");
11724	MrBayesPrint (" --------------------------------------------------------------------------- \n");
11725	}
11726	else if (!strcmp(helpTkn, "Usertree"))
11727	{
11728	MrBayesPrint (" --------------------------------------------------------------------------- \n");
11729	MrBayesPrint (" Usertree \n");
11730	MrBayesPrint (" \n");
11731	MrBayesPrint (" This command allows you to specify a user tree. The user tree can then be \n");
11732	MrBayesPrint (" used as a starting tree for a MCMC analysis. The format for the command is \n");
11733	MrBayesPrint (" \n");
11734	MrBayesPrint (" usertree = <tree in Newick format> \n");
11735	MrBayesPrint (" \n");
11736	MrBayesPrint (" For example, \n");
11737	MrBayesPrint (" \n");
11738	MrBayesPrint (" usertree = (A,B,(C,D)) \n");
11739	MrBayesPrint (" \n");
11740	MrBayesPrint (" specifies an unrooted tree of four species. Note that the program re- \n");
11741	MrBayesPrint (" quires that trees are binary (i.e., strictly bifurcating). Hence, there \n");
11742	MrBayesPrint (" can be only one three-way split, as shown in the example. If the tree \n");
11743	MrBayesPrint (" is not binary, the program will return an error. \n");
11744	MrBayesPrint (" --------------------------------------------------------------------------- \n");
11745	}
11746	else if (!strcmp(helpTkn, "Mcmc"))
11747	{
11748	MrBayesPrint (" --------------------------------------------------------------------------- \n");
11749	MrBayesPrint (" Mcmc \n");
11750	MrBayesPrint (" \n");
11751	MrBayesPrint (" This command starts the Markov chain Monte Carlo (MCMC) analysis. The \n");
11752	MrBayesPrint (" posterior probability of phylogenetic trees (and other parameters of the \n");
11753	MrBayesPrint (" substitution model) cannot be determined analytically. Instead, MCMC is \n");
11754	MrBayesPrint (" used to approximate the posterior probabilities of trees by drawing \n");
11755	MrBayesPrint (" (dependent) samples from the posterior distribution. This program can \n");
11756	MrBayesPrint (" implement a variant of MCMC called \"Metropolis-coupled Markov chain Monte \n");
11757	MrBayesPrint (" Carlo\", or MCMCMC for short. Basically, \"Nchains\" are run, with \n");
11758	MrBayesPrint (" Nchains - 1 of them heated. The chains are labelled 1, 2, ..., Nchains. \n");
11759	MrBayesPrint (" The heat that is applied to the i-th chain is B = 1 / (1 + temp X i). B \n");
11760	MrBayesPrint (" is the power to which the posterior probability is raised. When B = 0, all \n");
11761	MrBayesPrint (" trees have equal probability and the chain freely visits trees. B = 1 is \n");
11762	MrBayesPrint (" the \"cold\" chain (or the distribution of interest). MCMCMC can mix \n");
11763	MrBayesPrint (" better than ordinary MCMC; after all of the chains have gone through \n");
11764	MrBayesPrint (" one cycle, two chains are chosen at random and an attempt is made to \n");
11765	MrBayesPrint (" swap the states (with the probability of a swap being determined by the \n");
11766	MrBayesPrint (" Metropolis et al. equation). This allows the chain to potentially jump \n");
11767	MrBayesPrint (" a valley in a single bound. The correct usage is \n");
11768	MrBayesPrint (" \n");
11769	MrBayesPrint (" mcmc <parameter> = <value> ... <parameter> = <value> \n");
11770	MrBayesPrint (" \n");
11771	MrBayesPrint (" For example, \n");
11772	MrBayesPrint (" \n");
11773	MrBayesPrint (" mcmc ngen=100000 nchains=4 temp=0.5 \n");
11774	MrBayesPrint (" \n");
11775	MrBayesPrint (" performs a MCMCMC analysis with four chains with the temperature set to \n");
11776	MrBayesPrint (" 0.5. The chains would be run for 100,000 cycles. \n");
11777	MrBayesPrint (" \n");
11778	MrBayesPrint (" Options: \n");
11779	MrBayesPrint (" \n");
11780	MrBayesPrint (" Ngen -- This option sets the number of cycles for the MCMC alg- \n");
11781	MrBayesPrint (" orithm. This should be a big number as you want the chain \n");
11782	MrBayesPrint (" to first reach stationarity, and then remain there for \n");
11783	MrBayesPrint (" enough time to take lots of samples. \n");
11784	MrBayesPrint (" Nruns -- How many independent analyses are started simultaneously. \n");
11785	MrBayesPrint (" Nchains -- How many chains are run for each analysis for the MCMCMC \n");
11786	MrBayesPrint (" variant. The default is 4: 1 cold chain and 3 heated chains. \n");
11787	MrBayesPrint (" If Nchains is set to 1, MrBayes will use regular MCMC sam- \n");
11788	MrBayesPrint (" pling, without heating. \n");
11789	MrBayesPrint (" Temp -- The temperature parameter for heating the chains. The higher \n");
11790	MrBayesPrint (" the temperature, the more likely the heated chains are to \n");
11791	MrBayesPrint (" move between isolated peaks in the posterior distribution. \n");
11792	MrBayesPrint (" However, excessive heating may lead to very low acceptance \n");
11793	MrBayesPrint (" rates for swaps between different chains. Before changing the \n");
11794	MrBayesPrint (" default setting, however, note that the acceptance rates of \n");
11795	MrBayesPrint (" swaps tend to fluctuate during the burn-in phase of the run. \n");
11796	MrBayesPrint (" Reweight -- Here, you specify three numbers, that respectively represent \n");
11797	MrBayesPrint (" the percentage of characters to decrease in weight, the \n");
11798	MrBayesPrint (" percentage of characters to increase in weight, and the \n");
11799	MrBayesPrint (" increment. An increase/decrease in weight is acheived by \n");
11800	MrBayesPrint (" replicating/removing a character in the matrix. This is \n");
11801	MrBayesPrint (" only done to non-cold chains. The format for this parameter \n");
11802	MrBayesPrint (" is \"reweight=(<number>,<number>)\" or \"reweight=(<number>, \n");
11803	MrBayesPrint (" <number>,<number>)\". \n");
11804	MrBayesPrint (" Swapfreq -- This specifies how often swaps of states between chains are \n");
11805	MrBayesPrint (" attempted. You must be running at least two chains for this \n");
11806	MrBayesPrint (" option to be relevant. The default is Swapfreq=1, resulting \n");
11807	MrBayesPrint (" in Nswaps (see below) swaps being tried each generation of \n");
11808	MrBayesPrint (" the run. If Swapfreq is set to 10, then Nswaps swaps will be \n");
11809	MrBayesPrint (" tried every tenth generation of the run. \n");
11810	MrBayesPrint (" Nswaps -- The number of swaps tried for each swapping generation of the \n");
11811	MrBayesPrint (" chain (see also Swapfreq). \n");
11812	MrBayesPrint (" Samplefreq -- This specifies how often the Markov chain is sampled. You \n");
11813	MrBayesPrint (" can sample the chain every cycle, but this results in very \n");
11814	MrBayesPrint (" large output files. Thinning the chain is a way of making \n");
11815	MrBayesPrint (" these files smaller and making the samples more independent. \n");
11816	MrBayesPrint (" Printfreq -- This specifies how often information about the chain is \n");
11817	MrBayesPrint (" printed to the screen. \n");
11818	MrBayesPrint (" Printall -- If set to NO, only cold chains in a MCMC analysis are printed \n");
11819	MrBayesPrint (" to screen. If set to YES, both cold and heated chains will be \n");
11820	MrBayesPrint (" output. This setting only affects the printing to screen, it \n");
11821	MrBayesPrint (" does not change the way values are written to file. \n");
11822	MrBayesPrint (" Printmax -- The maximum number of chains to print to screen. \n");
11823	MrBayesPrint (" Mcmcdiagn -- Determines whether acceptance ratios of moves and swaps will \n");
11824	MrBayesPrint (" be printed to file. The file will be named similarly to the \n");
11825	MrBayesPrint (" '.p' and '.t' files, but will have the ending '.mcmc'. If \n");
11826	MrBayesPrint (" more than one independent analysis is run simultaneously (see \n");
11827	MrBayesPrint (" Nruns below), convergence diagnostics for tree topology will \n");
11828	MrBayesPrint (" also be printed to this file. The convergence diagnostic used \n");
11829	MrBayesPrint (" is the average standard deviation in partition frequency \n");
11830	MrBayesPrint (" values across independent analyses. The Burnin setting (see \n");
11831	MrBayesPrint (" below) determines how many samples will be discarded as burnin\n");
11832	MrBayesPrint (" before calculating the partition frequencies. The Minpartfreq \n");
11833	MrBayesPrint (" setting (see below) determines the minimum partition frequency\n");
11834	MrBayesPrint (" required for a partition to be included in the calculation. As\n");
11835	MrBayesPrint (" the independent analyses approach stationarity (converge), the\n");
11836	MrBayesPrint (" value of the diagnostic is expected to approach zero. \n");
11837	MrBayesPrint (" Diagnfreq -- The number of generations between the calculation of MCMC \n");
11838	MrBayesPrint (" diagnostics (see Mcmcdiagn above). \n");
11839	MrBayesPrint (" Diagnstat -- The statistic to use for run-time convergence diagnostics. \n");
11840	MrBayesPrint (" Choices are 'Avgstddev' for average standard deviation of \n");
11841	MrBayesPrint (" split frequencies and 'Maxstddev' for maximum standard devia- \n");
11842	MrBayesPrint (" tion of split frequencies. \n");
11843	MrBayesPrint (" Savetrees -- If you are using a relative burnin for run-time convergence \n");
11844	MrBayesPrint (" diagnostics, tree samples need to be deleted from split \n");
11845	MrBayesPrint (" frequency counters as the cut-off point for the burnin moves \n");
11846	MrBayesPrint (" during the run. If 'Savetrees' is set to 'No', tree samples \n");
11847	MrBayesPrint (" to be discarded are read back in from file. If 'Savetrees' is \n");
11848	MrBayesPrint (" set to 'Yes', the tree samples to be removed will be stored \n");
11849	MrBayesPrint (" in the internal memory instead. This can use up a lot of \n");
11850	MrBayesPrint (" memory in large analyses. \n");
11851	MrBayesPrint (" Minpartfreq -- The minimum frequency required for a partition to be included \n");
11852	MrBayesPrint (" in the calculation of the topology convergence diagnostic. The\n");
11853	MrBayesPrint (" partition is included if the minimum frequency is reached in \n");
11854	MrBayesPrint (" at least one of the independent tree samples that are com- \n");
11855	MrBayesPrint (" pared. \n");
11856	MrBayesPrint (" Allchains -- If this option is set to YES, acceptance ratios for moves are \n");
11857	MrBayesPrint (" recorded for all chains, cold or heated. By default, only the \n");
11858	MrBayesPrint (" acceptance ratios for the cold chain are recorded. \n");
11859	MrBayesPrint (" Allcomps -- If this option is set to YES, topological convergence diag- \n");
11860	MrBayesPrint (" nostics are calculated over all pairwise comparisons of runs. \n");
11861	MrBayesPrint (" If it is set to NO, only the overall value is reported. \n");
11862	MrBayesPrint (" Relburnin -- If this option is set to YES, then a proportion of the sampled\n");
11863	MrBayesPrint (" values will be discarded as burnin when calculating the con- \n");
11864	MrBayesPrint (" vergence diagnostic. The proportion to be discarded is set \n");
11865	MrBayesPrint (" with Burninfrac (see below). When the Relburnin option is set \n");
11866	MrBayesPrint (" to NO, then a specific number of samples will be discarded \n");
11867	MrBayesPrint (" instead. This number is set by Burnin (see below). \n");
11868	MrBayesPrint (" Burnin -- Determines the number of samples (not generations) that will \n");
11869	MrBayesPrint (" be discarded when convergence diagnostics are calculated. \n");
11870	MrBayesPrint (" The value of this option is only relevant when Relburnin is \n");
11871	MrBayesPrint (" set to NO. \n");
11872	MrBayesPrint (" BurninFrac -- Determines the fraction of samples that will be discarded \n");
11873	MrBayesPrint (" when convergence diagnostics are calculated. The value of \n");
11874	MrBayesPrint (" this option is only relevant when Relburnin is set to YES. \n");
11875	MrBayesPrint (" Example: A value for this option of 0.25 means that 25%% of \n");
11876	MrBayesPrint (" the samples will be discarded. \n");
11877	MrBayesPrint (" Stoprule -- If this option is set to NO, then the chain is run the number \n");
11878	MrBayesPrint (" of generations determined by Ngen. If it is set to YES, and \n");
11879	MrBayesPrint (" topological convergence diagnostics are calculated (Mcmcdiagn \n");
11880	MrBayesPrint (" is set to YES), then the chain will be stopped before the pre-\n");
11881	MrBayesPrint (" determined number of generations if the convergence diagnostic\n");
11882	MrBayesPrint (" falls below the stop value. \n");
11883	MrBayesPrint (" Stopval -- The critical value for the topological convergence diagnostic.\n");
11884	MrBayesPrint (" Only used when Stoprule and Mcmcdiagn are set to yes, and \n");
11885	MrBayesPrint (" more than one analysis is run simultaneously (Nruns > 1). \n");
11886	MrBayesPrint (" Checkpoint -- If this parameter is set to 'Yes', all the current parameter \n");
11887	MrBayesPrint (" values of all chains will be printed to a check-pointing file \n");
11888	MrBayesPrint (" every 'Checkfreq' generation of the analysis. The file will be\n");
11889	MrBayesPrint (" named <Filename>.ckp and allows you to restart the analysis \n");
11890	MrBayesPrint (" from the last check point. This can be handy if you are \n");
11891	MrBayesPrint (" running a long analysis and want to extend it, or if there is \n");
11892	MrBayesPrint (" a risk that a long analysis will be inadvertently interupted \n");
11893	MrBayesPrint (" by hardware failure or other factors that are out of your \n");
11894	MrBayesPrint (" control. \n");
11895	MrBayesPrint (" Checkfreq -- The number of generations between check-pointing. See the \n");
11896	MrBayesPrint (" 'Checkpoint' parameter above for more information. \n");
11897	MrBayesPrint (" Filename -- The name of the files that will be generated. Two files \n");
11898	MrBayesPrint (" are generated: \"<Filename>.t\" and \"<Filename>.p\". \n");
11899	MrBayesPrint (" The .t file contains the trees whereas the .p file con- \n");
11900	MrBayesPrint (" tains the sampled values of the parameters. \n");
11901	MrBayesPrint (" Startparams -- The starting values for the model parameters are set to \n");
11902	MrBayesPrint (" arbitrary or random values when the parameters are created. \n");
11903	MrBayesPrint (" These starting values can be altered using the 'Startvals' \n");
11904	MrBayesPrint (" command. The 'Startparams=reset' option allows you to reset \n");
11905	MrBayesPrint (" the starting values to the default at the start of the ana- \n");
11906	MrBayesPrint (" lysis, overriding any previous user-defined starting values. \n");
11907	MrBayesPrint (" Under the default option, 'current', the chains will use the \n");
11908	MrBayesPrint (" current starting values. \n");
11909	MrBayesPrint (" Starttree -- The starting tree(s) for the chain can either be randomly \n");
11910	MrBayesPrint (" selected or user-defined. It might be a good idea to \n");
11911	MrBayesPrint (" start from randomly chosen trees; convergence seems \n");
11912	MrBayesPrint (" likely if independently run chains, each of which \n");
11913	MrBayesPrint (" started from different random trees, converge to the same \n");
11914	MrBayesPrint (" answer. If you want the chain to start from user-defined \n");
11915	MrBayesPrint (" trees instead, you first need to read in your tree(s) from a \n");
11916	MrBayesPrint (" Nexus file with a 'trees' block, and then you need to set the \n");
11917	MrBayesPrint (" starting tree(s) using the 'Startvals' command. Finally, you \n");
11918	MrBayesPrint (" need to make sure that 'Starttree' is set to 'current'. If \n");
11919	MrBayesPrint (" you do not set the starting tree(s), the chains will start \n");
11920	MrBayesPrint (" with random trees. Setting 'Starttree' to 'random' causes \n");
11921	MrBayesPrint (" new starting trees to be drawn randomly at the start of the \n");
11922	MrBayesPrint (" run, overwriting any previous user-defined starting trees. \n");
11923	MrBayesPrint (" Nperts -- This is the number of random perturbations to apply to the \n");
11924	MrBayesPrint (" user starting tree. This allows you to have something \n");
11925	MrBayesPrint (" between completely random and user-defined trees start \n");
11926	MrBayesPrint (" the chain. \n");
11927	MrBayesPrint (" Savebrlens -- This specifies whether branch length information is \n");
11928	MrBayesPrint (" saved on the trees. \n");
11929	MrBayesPrint (" Data -- When Data is set to NO, the chain is run without data. This \n");
11930	MrBayesPrint (" should be used only for examining induced priors. DO NOT SET \n");
11931	MrBayesPrint (" 'DATA' TO 'NO' UNLESS YOU KNOW WHAT YOU ARE DOING! \n");
11932	MrBayesPrint (" Ordertaxa -- Determines whether taxa should be ordered before trees are \n");
11933	MrBayesPrint (" printed to file. If set to 'Yes', terminals in the sampled \n");
11934	MrBayesPrint (" trees will be reordered to match the order of the taxa in the \n");
11935	MrBayesPrint (" data matrix as closely as possible. By default, trees will be \n");
11936	MrBayesPrint (" printed without reordering of taxa. \n");
11937	MrBayesPrint (" Append -- Set this to 'Yes' to append the results of the current run to \n");
11938	MrBayesPrint (" a previous run. MrBayes will first read in the results of the \n");
11939	MrBayesPrint (" previous run (number of generations and sampled splits) and \n");
11940	MrBayesPrint (" will then continue that run where you left it off. Make sure \n");
11941	MrBayesPrint (" that the output file names used in the previous run are the \n");
11942	MrBayesPrint (" same as those in the current run. \n");
11943	MrBayesPrint (" Autotune -- Set this to 'Yes' to autotune the proposals that change \n");
11944	MrBayesPrint (" substitution model parameters. When set to 'No', the tuning \n");
11945	MrBayesPrint (" parameters are fixed to their starting values. Note that the \n");
11946	MrBayesPrint (" autotuning occurs independently for each chain. The target \n");
11947	MrBayesPrint (" acceptance rate for each move can be changed using the \n");
11948	MrBayesPrint (" 'Propset' command. \n");
11949	MrBayesPrint (" Tunefreq -- When a proposal has been tried 'Tunefreq' times, its tuning \n");
11950	MrBayesPrint (" parameter is adjusted to reach the target acceptance rate \n");
11951	MrBayesPrint (" if 'Autotune' is set to 'Yes'. \n");
11952	MrBayesPrint (" \n");
11953	PrintSettings ("Mcmc", NULL);
11954	MrBayesPrint (" --------------------------------------------------------------------------- \n");
11955	}
11956	else if (!strcmp(helpTkn, "Mcmcp"))
11957	{
11958	PrintYesNo (chainParams.saveBrlens, yesNoStr);
11959	MrBayesPrint (" --------------------------------------------------------------------------- \n");
11960	MrBayesPrint (" Mcmcp \n");
11961	MrBayesPrint (" \n");
11962	MrBayesPrint (" This command sets the parameters of the Markov chain Monte Carlo (MCMC) \n");
11963	MrBayesPrint (" analysis without actually starting the chain. This command is identical \n");
11964	MrBayesPrint (" in all respects to Mcmc, except that the analysis will not start after \n");
11965	MrBayesPrint (" this command is issued. For more details on the options, check the help \n");
11966	MrBayesPrint (" menu for Mcmc.\n");
11967	MrBayesPrint (" \n");
11968	PrintSettings ("Mcmc", NULL);
11969	MrBayesPrint (" --------------------------------------------------------------------------- \n");
11970	}
11971	else if (!strcmp(helpTkn, "Ss"))
11972	{
11973	MrBayesPrint (" --------------------------------------------------------------------------- \n");
11974	MrBayesPrint (" Ss \n");
11975	MrBayesPrint (" \n");
11976	MrBayesPrint (" This command is used to start stepping-stone sampling, which is an efficient \n");
11977	MrBayesPrint (" and accurate method for estimating the marginal likelihood of the currently \n");
11978	MrBayesPrint (" specified model. It is considerably more accurate than the harmonic mean of \n");
11979	MrBayesPrint (" the likelihoods from a standard MCMC run on the model (calculated by the \n");
11980	MrBayesPrint (" 'Sump' command) but it requires a separate MCMC-like run. To be more specific,\n");
11981	MrBayesPrint (" stepping-stone sampling uses importance sampling to estimate each ratio in a \n");
11982	MrBayesPrint (" series of discrete steps bridging the posterior and prior distributions. \n");
11983	MrBayesPrint (" The importance distributions that are used are called power posterior distri- \n");
11984	MrBayesPrint (" butions, and are defined as prior*(likelihood^beta). By varying beta from 1 to\n");
11985	MrBayesPrint (" 0, we get a series of distributions that connect the posterior (beta = 1) to \n");
11986	MrBayesPrint (" the prior (beta = 0). \n");
11987	MrBayesPrint (" \n");
11988	MrBayesPrint (" The power posterior distributions are sampled using MCMC. First, we start a \n");
11989	MrBayesPrint (" standard MCMC chain on the posterior distribution, and let it run until we \n");
11990	MrBayesPrint (" have reached the criterion specified by the 'Burninss' option. After this, we \n");
11991	MrBayesPrint (" step through the power posterior distributions until we reach the prior dis- \n");
11992	MrBayesPrint (" tribution. In each of the 'Nsteps' steps, we sample from a new power poster- \n");
11993	MrBayesPrint (" ior distribution with a distinct beta value. The beta values correspond to \n");
11994	MrBayesPrint (" 'Nsteps' evenly spaced quantiles in a Beta distribution with the parameters \n");
11995	MrBayesPrint (" 'Alpha' and 1.0. For the first sampling step, the beta value is equal to the \n");
11996	MrBayesPrint (" last quantile, i.e., it is close to 1.0. For each successive step, the beta \n");
11997	MrBayesPrint (" value takes on the value of the next quantile, in decreasing order, until it \n");
11998	MrBayesPrint (" reaches the value of 0.0. If you change value of 'FromPrior' from default 'No'\n");
11999	MrBayesPrint (" to 'Yes' then the direction of power posterior change during SS analizes is \n");
12000	MrBayesPrint (" opposite to the one described above, i.e. we start from sampling prior and \n");
12001	MrBayesPrint (" finish close to posterior. \n");
12002	MrBayesPrint (" \n");
12003	MrBayesPrint (" The 'Ss' procedure uses the same machinery as the standard 'Mcmc' algorithm, \n");
12004	MrBayesPrint (" and shares most of its parameters with the 'Mcmc' and 'Mcmcp' commands. All \n");
12005	MrBayesPrint (" 'Mcmc' parameters, except those related to burnin, have the same meaning and \n");
12006	MrBayesPrint (" usage in the 'Ss' command as they have in the 'Mcmc' command. The 'Mcmc' \n");
12007	MrBayesPrint (" burnin parameters are used to set up burnin within each step. The 'Ss' command\n");
12008	MrBayesPrint (" also uses its own burnin parameter, 'Burninss' (see below for details). The \n");
12009	MrBayesPrint (" 'Ss' command also has its own parameters for specifying the number of steps \n");
12010	MrBayesPrint (" and the shape of the Beta distribution from which the beta values are computed\n");
12011	MrBayesPrint (" (see below). \n");
12012	MrBayesPrint (" \n");
12013	MrBayesPrint (" Note that the 'Ngen' parameter of 'Mcmc' is used to set the maximum number of \n");
12014	MrBayesPrint (" generations processed, including both the burnin and the following steps in \n");
12015	MrBayesPrint (" the stepping-stone sampling phase. For instance, assume that 'Burninss' is set\n");
12016	MrBayesPrint (" to '-1', 'Nsteps' to '49', 'Ngen' to '1000000' and 'Samplefreq' to '1000'. \n");
12017	MrBayesPrint (" We will then get 1,000 samples in total (1,000,000 / 1,000). These will fall \n");
12018	MrBayesPrint (" into 50 bins, one of which represents the burnin and is discarded. Each step \n");
12019	MrBayesPrint (" in the algorithm will thus be represented by 20 samples. \n");
12020	MrBayesPrint (" \n");
12021	MrBayesPrint (" More information on 'Mcmc' parameters is available in the help for the 'Mcmc' \n");
12022	MrBayesPrint (" and 'Mcmcp' commands. Only the exclusive 'Ss' parameters are listed below. \n");
12023	MrBayesPrint (" These can only be set up using the 'Ss' command, while the parameters shared \n");
12024	MrBayesPrint (" with 'Mcmc' and 'Mcmcp' can also be set up using those commands. \n");
12025	MrBayesPrint (" \n");
12026	MrBayesPrint (" The correct usage is \n");
12027	MrBayesPrint (" \n");
12028	MrBayesPrint (" ss <parameter>=<value> ... <parameter>=<value> \n");
12029	MrBayesPrint (" \n");
12030	MrBayesPrint (" Note that a command: \n");
12031	MrBayesPrint (" \n");
12032	MrBayesPrint (" ss <setting parameters shared with mcmc> <setting exclusive ss parameters> \n");
12033	MrBayesPrint (" \n");
12034	MrBayesPrint (" would be equivalent to executing two commands: \n");
12035	MrBayesPrint (" \n");
12036	MrBayesPrint (" mcmcp <setting parameters shared with mcmc>; \n");
12037	MrBayesPrint (" ss <setting exclusive ss parameters>; \n");
12038	MrBayesPrint (" \n");
12039	MrBayesPrint (" For more information on the stepping-stone algorithm, see: \n");
12040	MrBayesPrint (" \n");
12041	MrBayesPrint (" Xie, W., P. O. Lewis, Y. Fan, L. Kuo, and M.-H. Chen. 2011. Improving marginal\n");
12042	MrBayesPrint (" likelihood estimation for Bayesian phylogenetic model selection. Systematic\n");
12043	MrBayesPrint (" Biology 60:150-160. \n");
12044	MrBayesPrint (" \n");
12045	MrBayesPrint (" Available options: \n");
12046	MrBayesPrint (" (NB: Only exclusive ss parameters listed here. For additional parameters, see \n");
12047	MrBayesPrint (" help on 'mcmc' or 'mcmcp'. \n");
12048	MrBayesPrint (" \n");
12049	MrBayesPrint (" Alpha -- The beta values used in the stepping-stone sampling procedure \n");
12050	MrBayesPrint (" correspond to evenly spaced quantiles from a Beta('Alpha',1.0)\n");
12051	MrBayesPrint (" distribution. The parameter 'Alpha' determines the skewness of\n");
12052	MrBayesPrint (" the beta values. If 'Alpha' is set to '1.0', the beta values \n");
12053	MrBayesPrint (" would be spaced uniformly on the interval (0.0,1.0). However, \n");
12054	MrBayesPrint (" better results are obtained if the beta values are skewed. \n");
12055	MrBayesPrint (" Empirically, it was observed that 'Alpha' values in the range \n");
12056	MrBayesPrint (" of 0.3 to 0.5 produce the most accurate results. \n");
12057	MrBayesPrint (" Burninss -- Fixed number of samples discarded before sampling of the first\n");
12058	MrBayesPrint (" step starts. 'Burninss' can be specified using either a pos- \n");
12059	MrBayesPrint (" itive or a negative number. If the number is positive, it is \n");
12060	MrBayesPrint (" interpreted as the number of samples to discard as burnin. If \n");
12061	MrBayesPrint (" the number is negative, its absolute value is interpreted as \n");
12062	MrBayesPrint (" the length of the burnin in terms of the length of each of the\n");
12063	MrBayesPrint (" following steps in the stepping-stone algorithm. For instance,\n");
12064	MrBayesPrint (" a value of '-1' means that the length of the burnin is the \n");
12065	MrBayesPrint (" same as the length of each of the subsequent steps. \n");
12066	MrBayesPrint (" Nsteps -- Number of steps in the stepping-stone algorithm. Typically, a \n");
12067	MrBayesPrint (" number above 30 is sufficient for accurate results. \n");
12068	MrBayesPrint (" FromPrior -- If it is set to 'Yes', it indicates that in the first step we \n");
12069	MrBayesPrint (" sample from the prior, with each consequtive step we sample \n");
12070	MrBayesPrint (" closer to the posterior. 'No' indicates the opposite direction\n");
12071	MrBayesPrint (" of power posterior change, i.e. in the first step we sample \n");
12072	MrBayesPrint (" close to the posterior, and with each consequtive step we \n");
12073	MrBayesPrint (" sample closer to the prior. \n");
12074	MrBayesPrint (" \n");
12075	MrBayesPrint (" Current settings: \n");
12076	MrBayesPrint (" \n");
12077	MrBayesPrint (" Parameter Options Current Setting \n");
12078	MrBayesPrint (" -------------------------------------------------------- \n");
12079	MrBayesPrint (" Alpha <number> %1.2lf\n", chainParams.alphaSS);
12080	MrBayesPrint (" BurninSS <number> %d\n", chainParams.burninSS);
12081	MrBayesPrint (" Nsteps <number> %d\n", chainParams.numStepsSS);
12082	MrBayesPrint (" FromPrior Yes/No %s \n", chainParams.startFromPriorSS == YES ? "Yes" : "No");
12083	MrBayesPrint (" \n");
12084	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12085	}
12086	else if (!strcmp(helpTkn, "Ssp"))
12087	{
12088	PrintYesNo (chainParams.saveBrlens, yesNoStr);
12089	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12090	MrBayesPrint (" Ssp \n");
12091	MrBayesPrint (" \n");
12092	MrBayesPrint (" This command sets the parameters of the stepping-stone sampling \n");
12093	MrBayesPrint (" analysis without actually starting the chain. This command is identical \n");
12094	MrBayesPrint (" in all respects to Ss, except that the analysis will not start after \n");
12095	MrBayesPrint (" this command is issued. For more details on the options, check the help \n");
12096	MrBayesPrint (" menu for Ss.\n");
12097	MrBayesPrint (" \n");
12098	MrBayesPrint (" Current settings: \n");
12099	MrBayesPrint (" \n");
12100	MrBayesPrint (" Parameter Options Current Setting \n");
12101	MrBayesPrint (" -------------------------------------------------------- \n");
12102	MrBayesPrint (" Alpha <number> %1.2lf\n", chainParams.alphaSS);
12103	MrBayesPrint (" BurninSS <number> %d\n", chainParams.burninSS);
12104	MrBayesPrint (" Nsteps <number> %d\n", chainParams.numStepsSS);
12105	MrBayesPrint (" FromPrior Yes/No %s \n", chainParams.startFromPriorSS == YES ? "Yes" : "No");
12106	MrBayesPrint (" \n");
12107	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12108	}
12109	else if (!strcmp(helpTkn, "Set"))
12110	{
12111	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12112	MrBayesPrint (" Set \n");
12113	MrBayesPrint (" \n");
12114	MrBayesPrint (" This command is used to set some general features of the model or program \n");
12115	MrBayesPrint (" behavior. The correct usage is \n");
12116	MrBayesPrint (" \n");
12117	MrBayesPrint (" set <parameter>=<value> ... <parameter>=<value> \n");
12118	MrBayesPrint (" \n");
12119	MrBayesPrint (" Available options: \n");
12120	MrBayesPrint (" \n");
12121	MrBayesPrint (" Seed -- Sets the seed number for the random number generator. The \n");
12122	MrBayesPrint (" random number seed is initialized haphazardly at the beg- \n");
12123	MrBayesPrint (" inning of each MrBayes session. This option allows you to \n");
12124	MrBayesPrint (" set the seed to some specific value, thereby allowing you \n");
12125	MrBayesPrint (" to exactly repeat an analysis. If the analysis uses swapping \n");
12126	MrBayesPrint (" between cold and heated chains, you must also set the swap \n");
12127	MrBayesPrint (" seed (see below) to exactly repeat the analysis. \n");
12128	MrBayesPrint (" Swapseed -- Sets the seed used for generating the swapping sequence \n");
12129	MrBayesPrint (" when Metropolis-coupled heated chains are used. This seed \n");
12130	MrBayesPrint (" is initialized haphazardly at the beginning of each MrBayes \n");
12131	MrBayesPrint (" session. This option allows you to set the seed to some \n");
12132	MrBayesPrint (" specific value, thereby allowing you to exactly repeat a \n");
12133	MrBayesPrint (" swap sequence. See also the 'Seed' option. \n");
12134	MrBayesPrint (" Dir -- The working directory. Specifies the absolute or relative path\n");
12135	MrBayesPrint (" to the working directory. If left empty, the working directory\n");
12136	MrBayesPrint (" is the current directory. \n");
12137	MrBayesPrint (" Partition -- Set this option to a valid partition id, either the number or \n");
12138	MrBayesPrint (" name of a defined partition, to enforce a specific partition- \n");
12139	MrBayesPrint (" ing of the data. When a data matrix is read in, a partition \n");
12140	MrBayesPrint (" called \"Default\" is automatically created. It divides the \n");
12141	MrBayesPrint (" data into one part for each data type. If you only have one \n");
12142	MrBayesPrint (" data type, DNA for instance, the default partition will not \n");
12143	MrBayesPrint (" divide up the data at all. The default partition is always \n");
12144	MrBayesPrint (" the first partition, so 'set partition=1' is the same as \n");
12145	MrBayesPrint (" 'set partition=default'. \n");
12146	MrBayesPrint (" Speciespartition -- Set this option to a valid speciespartition id, either the\n");
12147	MrBayesPrint (" number or name of a defined speciespartition, to enforce a \n");
12148	MrBayesPrint (" specific partitioning of taxa to species. When a data matrix \n");
12149	MrBayesPrint (" is read in, a speciespartition called \"Default\" is auto- \n");
12150	MrBayesPrint (" matically created. It assigns one taxon for each species. The \n");
12151	MrBayesPrint (" default speciespartition is always the first speciespartition,\n");
12152	MrBayesPrint (" so 'set speciespartition=1' is the same as \n");
12153	MrBayesPrint (" 'set speciespartition=default'. \n");
12154	MrBayesPrint (" Autoclose -- If autoclose is set to 'yes', then the program will not prompt\n");
12155	MrBayesPrint (" you during the course of executing a file. This is particular-\n");
12156	MrBayesPrint (" ly useful when you run MrBayes in batch mode. \n");
12157	MrBayesPrint (" Nowarnings -- If nowarnings is set to yes, then the program will not prompt \n");
12158	MrBayesPrint (" you when overwriting or appending an ouput file that is al- \n");
12159	MrBayesPrint (" ready present. If 'nowarnings=no' (the default setting), then \n");
12160	MrBayesPrint (" the program propts the user before overwriting output files. \n");
12161	MrBayesPrint (" Autoreplace -- When nowarnings is set to yes, then MrBayes will by default \n");
12162	MrBayesPrint (" overwrite output files that already exists. This may cause \n");
12163	MrBayesPrint (" irrecoverable loss of previous results if you have not removed\n");
12164	MrBayesPrint (" or renamed the files from previous runs. To override this be- \n");
12165	MrBayesPrint (" havior, set autooverwrite to no, in which case new output will\n");
12166	MrBayesPrint (" be appended to existing files instead. \n");
12167	MrBayesPrint (" Quitonerror -- If quitonerror is set to yes, then the program will quit when \n");
12168	MrBayesPrint (" an error is encountered, after printing an error message. If \n");
12169	MrBayesPrint (" quitonerror is set to no (the default setting), then the \n");
12170	MrBayesPrint (" program will wait for additional commands from the command \n");
12171	MrBayesPrint (" line after the error message is printed. \n");
12172	MrBayesPrint (" Scientific -- Set this option to 'Yes' to write sampled values to file in \n");
12173	MrBayesPrint (" scientific format and to 'No' to write them in fixed format. \n");
12174	MrBayesPrint (" Fixed format is easier for humans to read but you risk losing \n");
12175	MrBayesPrint (" precision for small numbers. For instance, sampled values that\n");
12176	MrBayesPrint (" are less than 1E-6 will print to file as '0.000000' if fixed \n");
12177	MrBayesPrint (" format is used and 'precision' is set to 6. \n");
12178	MrBayesPrint (" Precision -- Precision allows you to set the number of decimals to be prin-\n");
12179	MrBayesPrint (" ted when sampled values are written to file. Precision must be\n");
12180	MrBayesPrint (" in the range 3 to 15. \n");
12181	#if defined (BEAGLE_ENABLED)
12182	MrBayesPrint (" Usebeagle -- Set this option to 'Yes' to attempt to use the BEAGLE library \n");
12183	MrBayesPrint (" to compute the phylogenetic likelihood on a variety of high- \n");
12184	MrBayesPrint (" performance hardware including multicore CPUs and GPUs. Some \n");
12185	MrBayesPrint (" models in MrBayes are not yet supported by BEAGLE. \n");
12186	MrBayesPrint (" Beagledevice -- Set this option to 'GPU' or 'CPU' to select processor. \n");
12187	MrBayesPrint (" Beagleprecision -- Selection 'Single' or 'Double' precision computation. \n");
12188	MrBayesPrint (" Beaglescaling -- 'Always' rescales partial likelihoods at each evaluation. \n");
12189	MrBayesPrint (" 'Dynamic' rescales less frequently and should run faster. \n");
12190	MrBayesPrint (" Beaglesse -- Use SSE instructions on Intel CPU processors. \n");
12191	MrBayesPrint (" Beagleopenmp -- Use OpenMP to parallelize across multi-core CPU processors. \n");
12192	#endif
12193	#if defined (THREADS_ENABLED)
12194	MrBayesPrint (" Beaglethreads -- Set this option to 'Yes' to employ multiple threads to drive \n");
12195	MrBayesPrint (" multiple BEAGLE resource simultaneously. This is highly \n");
12196	MrBayesPrint (" recommended for more than one GPU, and for sufficiently large\n");
12197	MrBayesPrint (" data partitions, multi-core CPUs should also demonstrate \n");
12198	MrBayesPrint (" speed-ups. \n");
12199	#endif
12200	MrBayesPrint (" \n");
12201	MrBayesPrint (" Current settings: \n");
12202	MrBayesPrint (" \n");
12203	MrBayesPrint (" Parameter Options Current Setting \n");
12204	MrBayesPrint (" -------------------------------------------------------- \n");
12205	MrBayesPrint (" Seed <number> %ld \n", globalSeed);
12206	MrBayesPrint (" Swapseed <number> %ld \n", swapSeed);
12207	MrBayesPrint (" Dir <name> \"%s\"\n", workingDir);
12208	if (defMatrix == YES)
12209	MrBayesPrint (" Partition <name> %s\n", partitionNames[partitionNum]);
12210	else
12211	MrBayesPrint (" Partition <name> \"\"\n");
12212	if (defTaxa == YES)
12213	MrBayesPrint (" Speciespartition <name> %s\n", speciespartitionNames[speciespartitionNum]);
12214	else
12215	MrBayesPrint (" Speciespartition <name> \"\"\n");
12216	MrBayesPrint (" Autoclose Yes/No %s \n", autoClose == YES ? "Yes" : "No");
12217	MrBayesPrint (" Nowarnings Yes/No %s \n", noWarn == YES ? "Yes" : "No");
12218	MrBayesPrint (" Autoreplace Yes/No %s \n", autoOverwrite == YES ? "Yes" : "No");
12219	MrBayesPrint (" Quitonerror Yes/No %s \n", quitOnError == YES ? "Yes" : "No");
12220	MrBayesPrint (" Sientific Yes/No %s \n", scientific == YES ? "Yes" : "No");
12221	MrBayesPrint (" Precision <number> %d \n", precision);
12222	#if defined (BEAGLE_ENABLED)
12223	MrBayesPrint (" Usebeagle Yes/No %s \n", tryToUseBEAGLE == YES ? "Yes" : "No");
12224	MrBayesPrint (" Beagledevice CPU/GPU %s \n", beagleFlags & BEAGLE_FLAG_PROCESSOR_GPU ? "GPU" : "CPU");
12225	MrBayesPrint (" Beagleprecision Single/Double %s \n", beagleFlags & BEAGLE_FLAG_PRECISION_SINGLE ? "Single" : "Double");
12226	MrBayesPrint (" Beaglescaling Always/Dynamic %s \n", beagleScalingScheme == MB_BEAGLE_SCALE_ALWAYS ? "Always" : "Dynamic");
12227	MrBayesPrint (" Beaglesse Yes/No %s \n", beagleFlags & BEAGLE_FLAG_VECTOR_SSE ? "Yes" : "No");
12228	MrBayesPrint (" Beagleopenmp Yes/No %s \n", beagleFlags & BEAGLE_FLAG_THREADING_OPENMP ? "Yes" : "No");
12229	#endif
12230	#if defined (THREADS_ENABLED)
12231	MrBayesPrint (" Beaglethreads Yes/No %s \n", tryToUseThreads == YES ? "Yes" : "No");
12232	#endif
12233	MrBayesPrint (" \n");
12234	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12235	}
12236	else if (!strcmp(helpTkn, "Charset"))
12237	{
12238	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12239	MrBayesPrint (" Charset \n");
12240	MrBayesPrint (" \n");
12241	MrBayesPrint (" This command defines a character set. The format for the charset command \n");
12242	MrBayesPrint (" is \n");
12243	MrBayesPrint (" \n");
12244	MrBayesPrint (" charset <name> = <character numbers> \n");
12245	MrBayesPrint (" \n");
12246	MrBayesPrint (" For example, \"charset first_pos = 1-720\\3\" defines a character set \n");
12247	MrBayesPrint (" called \"first_pos\" that includes every third site from 1 to 720. \n");
12248	MrBayesPrint (" The character set name cannot have any spaces in it. The slash (\\) \n");
12249	MrBayesPrint (" is a nifty way of telling the program to assign every third (or \n");
12250	MrBayesPrint (" second, or fifth, or whatever) character to the character set. \n");
12251	MrBayesPrint (" This option is best used not from the command line, but rather as a \n");
12252	MrBayesPrint (" line in the mrbayes block of a file. Note that you can use \".\" to \n");
12253	MrBayesPrint (" stand in for the last character (e.g., charset 1-.\\3). \n");
12254	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12255	}
12256	else if (!strcmp(helpTkn, "Outgroup"))
12257	{
12258	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12259	MrBayesPrint (" Outgroup \n");
12260	MrBayesPrint (" \n");
12261	MrBayesPrint (" This command assigns a taxon to the outgroup. The correct usage is: \n");
12262	MrBayesPrint (" \n");
12263	MrBayesPrint (" outgroup <number>/<taxon name> \n");
12264	MrBayesPrint (" \n");
12265	MrBayesPrint (" For example, \"outgroup 3\" assigns the third taxon in the matrix to be \n");
12266	MrBayesPrint (" the outgroup. Similarly, \"outgroup Homo_sapiens\" assings the taxon \n");
12267	MrBayesPrint (" \"Homo_sapiens\" to be the outgroup (assuming that there is a taxon named \n");
12268	MrBayesPrint (" \"Homo_sapiens\" in the matrix). Only a single taxon can be assigned to \n");
12269	MrBayesPrint (" be the outgroup. \n");
12270	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12271	}
12272	else if (!strcmp(helpTkn, "Showusertrees"))
12273	{
12274	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12275	MrBayesPrint (" Showusertrees \n");
12276	MrBayesPrint (" \n");
12277	MrBayesPrint (" This command shows the currently defined user trees. The correct usage \n");
12278	MrBayesPrint (" is \"showusertrees\". \n");
12279	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12280	}
12281	else if (!strcmp(helpTkn, "Showmcmctrees"))
12282	{
12283	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12284	MrBayesPrint (" Showmcmctrees \n");
12285	MrBayesPrint (" \n");
12286	MrBayesPrint (" This command shows the current trees used by the Markov chains. \n");
12287	MrBayesPrint (" is \"showmcmctrees\". \n");
12288	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12289	}
12290	else if (!strcmp(helpTkn, "Deroot"))
12291	{
12292	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12293	MrBayesPrint (" Deroot \n");
12294	MrBayesPrint (" \n");
12295	MrBayesPrint (" This command deroots the user tree. If the tree is already unrooted, a \n");
12296	MrBayesPrint (" warning is issued. The correct usage is \"deroot\". \n");
12297	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12298	}
12299	else if (!strcmp(helpTkn, "Root"))
12300	{
12301	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12302	MrBayesPrint (" Root \n");
12303	MrBayesPrint (" \n");
12304	MrBayesPrint (" This command roots the tree. If the tree is already rooted, a warning \n");
12305	MrBayesPrint (" is issued. The tree is rooted at the midpoint between the outgroup species \n");
12306	MrBayesPrint (" and the ingroup species. The correct usage is \"root\". \n");
12307	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12308	}
12309	else if (!strcmp(helpTkn, "Taxset"))
12310	{
12311	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12312	MrBayesPrint (" Taxset \n");
12313	MrBayesPrint (" \n");
12314	MrBayesPrint (" This command defines a taxon set. The format for the taxset command \n");
12315	MrBayesPrint (" is \n");
12316	MrBayesPrint (" \n");
12317	MrBayesPrint (" taxset <name> = <taxon names or numbers> \n");
12318	MrBayesPrint (" \n");
12319	MrBayesPrint (" For example, \"taxset apes = Homo Pan Gorilla Orang gibbon\" defines a \n");
12320	MrBayesPrint (" taxon set called \"apes\" that includes five taxa (namely, apes). \n");
12321	MrBayesPrint (" You can assign up to 30 taxon sets. This option is best used \n");
12322	MrBayesPrint (" not from the command line but rather as a line in the mrbayes block \n");
12323	MrBayesPrint (" of a file. \n");
12324	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12325	}
12326	else if (!strcmp(helpTkn, "Taxlabels"))
12327	{
12328	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12329	MrBayesPrint (" Taxlabels \n");
12330	MrBayesPrint (" \n");
12331	MrBayesPrint (" This command defines taxon labels. It could be used within taxa block. \n");
12332	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12333	}
12334	else if (!strcmp(helpTkn, "Charstat"))
12335	{
12336	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12337	MrBayesPrint (" Charstat \n");
12338	MrBayesPrint (" \n");
12339	MrBayesPrint (" This command shows the status of all the characters. The correct usage \n");
12340	MrBayesPrint (" is \n");
12341	MrBayesPrint (" \n");
12342	MrBayesPrint (" charstat \n");
12343	MrBayesPrint (" \n");
12344	MrBayesPrint (" After typing \"charstat\", the character number, whether it is excluded \n");
12345	MrBayesPrint (" or included, and the partition identity are shown. The output is paused \n");
12346	MrBayesPrint (" every 100 characters. This pause can be turned off by setting autoclose \n");
12347	MrBayesPrint (" to \"yes\" (set autoclose=yes). \n");
12348	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12349	}
12350	else if (!strcmp(helpTkn, "Taxastat"))
12351	{
12352	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12353	MrBayesPrint (" Taxastat \n");
12354	MrBayesPrint (" \n");
12355	MrBayesPrint (" This command shows the status of all the taxa. The correct usage is \n");
12356	MrBayesPrint (" \n");
12357	MrBayesPrint (" taxastat \n");
12358	MrBayesPrint (" \n");
12359	MrBayesPrint (" After typing \"taxastat\", the taxon number, name, and whether it is \n");
12360	MrBayesPrint (" excluded or included are shown. \n");
12361	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12362	}
12363	else if (!strcmp(helpTkn, "Partition"))
12364	{
12365	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12366	MrBayesPrint (" Partition \n");
12367	MrBayesPrint (" \n");
12368	MrBayesPrint (" This command allows you to specify a character partition. The format for \n");
12369	MrBayesPrint (" this command is \n");
12370	MrBayesPrint (" \n");
12371	MrBayesPrint (" partition <name> = <num parts>:<chars in first>, ...,<chars in last> \n");
12372	MrBayesPrint (" \n");
12373	MrBayesPrint (" For example, \"partition by_codon = 3:1st_pos,2nd_pos,3rd_pos\" specifies \n");
12374	MrBayesPrint (" a partition called \"by_codon\" which consists of three parts (first, \n");
12375	MrBayesPrint (" second, and third codon positions). Here, we are assuming that the sites \n");
12376	MrBayesPrint (" in each partition were defined using the charset command. You can specify \n");
12377	MrBayesPrint (" a partition without using charset as follows: \n");
12378	MrBayesPrint (" \n");
12379	MrBayesPrint (" partition by_codon = 3:1 4 6 9 12,2 5 7 10 13,3 6 8 11 14 \n");
12380	MrBayesPrint (" \n");
12381	MrBayesPrint (" However, we recommend that you use the charsets to define a set of char- \n");
12382	MrBayesPrint (" acters and then use these predefined sets when defining the partition. \n");
12383	MrBayesPrint (" Also, it makes more sense to define a partition as a line in the mrbayes \n");
12384	MrBayesPrint (" block than to issue the command from the command line (then again, you \n");
12385	MrBayesPrint (" may be a masochist, and want to do extra work). \n");
12386	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12387	}
12388	else if (!strcmp(helpTkn, "Exclude"))
12389	{
12390	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12391	MrBayesPrint (" Exclude \n");
12392	MrBayesPrint (" \n");
12393	MrBayesPrint (" This command excludes characters from the analysis. The correct usage is \n");
12394	MrBayesPrint (" \n");
12395	MrBayesPrint (" exclude <number> <number> <number> \n");
12396	MrBayesPrint (" \n");
12397	MrBayesPrint (" or \n");
12398	MrBayesPrint (" \n");
12399	MrBayesPrint (" exclude <number> - <number> \n");
12400	MrBayesPrint (" \n");
12401	MrBayesPrint (" or \n");
12402	MrBayesPrint (" \n");
12403	MrBayesPrint (" exclude <charset> \n");
12404	MrBayesPrint (" \n");
12405	MrBayesPrint (" or some combination thereof. Moreover, you can use the specifier \"\\\" to \n");
12406	MrBayesPrint (" exclude every nth character. For example, the following \n");
12407	MrBayesPrint (" \n");
12408	MrBayesPrint (" exclude 1-100\\3 \n");
12409	MrBayesPrint (" \n");
12410	MrBayesPrint (" would exclude every third character. As a specific example, \n");
12411	MrBayesPrint (" \n");
12412	MrBayesPrint (" exclude 2 3 10-14 22 \n");
12413	MrBayesPrint (" \n");
12414	MrBayesPrint (" excludes sites 2, 3, 10, 11, 12, 13, 14, and 22 from the analysis. Also, \n");
12415	MrBayesPrint (" \n");
12416	MrBayesPrint (" exclude all \n");
12417	MrBayesPrint (" \n");
12418	MrBayesPrint (" excludes all of the characters from the analysis. Excluding all characters \n");
12419	MrBayesPrint (" does not leave you much information for inferring phylogeny. \n");
12420	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12421	}
12422	else if (!strcmp(helpTkn, "Include"))
12423	{
12424	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12425	MrBayesPrint (" Include \n");
12426	MrBayesPrint (" \n");
12427	MrBayesPrint (" This command includes characters that were previously excluded from the \n");
12428	MrBayesPrint (" analysis. The correct usage is \n");
12429	MrBayesPrint (" \n");
12430	MrBayesPrint (" include <number> <number> <number> \n");
12431	MrBayesPrint (" \n");
12432	MrBayesPrint (" or \n");
12433	MrBayesPrint (" \n");
12434	MrBayesPrint (" include <number> - <number> \n");
12435	MrBayesPrint (" \n");
12436	MrBayesPrint (" or \n");
12437	MrBayesPrint (" \n");
12438	MrBayesPrint (" include <charset> \n");
12439	MrBayesPrint (" \n");
12440	MrBayesPrint (" or some combination thereof. Moreover, you can use the specifier \"\\\" to \n");
12441	MrBayesPrint (" include every nth character. For example, the following \n");
12442	MrBayesPrint (" \n");
12443	MrBayesPrint (" include 1-100\\3 \n");
12444	MrBayesPrint (" \n");
12445	MrBayesPrint (" would include every third character. As a specific example, \n");
12446	MrBayesPrint (" \n");
12447	MrBayesPrint (" include 2 3 10-14 22 \n");
12448	MrBayesPrint (" \n");
12449	MrBayesPrint (" includes sites 2, 3, 10, 11, 12, 13, 14, and 22 from the analysis. Also, \n");
12450	MrBayesPrint (" \n");
12451	MrBayesPrint (" include all \n");
12452	MrBayesPrint (" \n");
12453	MrBayesPrint (" includes all of the characters in the analysis. Including all of the \n");
12454	MrBayesPrint (" characters (even if many of them are bad) is a very total-evidence-like \n");
12455	MrBayesPrint (" thing to do. Doing this will make a certain group of people very happy. \n");
12456	MrBayesPrint (" On the other hand, simply using this program would make those same people \n");
12457	MrBayesPrint (" unhappy. \n");
12458	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12459	}
12460	else if (!strcmp(helpTkn, "Delete"))
12461	{
12462	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12463	MrBayesPrint (" Delete \n");
12464	MrBayesPrint (" \n");
12465	MrBayesPrint (" This command deletes taxa from the analysis. The correct usage is: \n");
12466	MrBayesPrint (" \n");
12467	MrBayesPrint (" delete <name and/or number and/or taxset> ... \n");
12468	MrBayesPrint (" \n");
12469	MrBayesPrint (" A list of the taxon names or taxon numbers (labelled 1 to ntax in the order \n");
12470	MrBayesPrint (" in the matrix) or taxset(s) can be used. For example, the following: \n");
12471	MrBayesPrint (" \n");
12472	MrBayesPrint (" delete 1 2 Homo_sapiens \n");
12473	MrBayesPrint (" \n");
12474	MrBayesPrint (" deletes taxa 1, 2, and the taxon labelled Homo_sapiens from the analysis. \n");
12475	MrBayesPrint (" You can also use \"all\" to delete all of the taxa. For example, \n");
12476	MrBayesPrint (" \n");
12477	MrBayesPrint (" delete all \n");
12478	MrBayesPrint (" \n");
12479	MrBayesPrint (" deletes all of the taxa from the analysis. Of course, a phylogenetic anal- \n");
12480	MrBayesPrint (" ysis that does not include any taxa is fairly uninteresting. \n");
12481	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12482	}
12483	else if (!strcmp(helpTkn, "Restore"))
12484	{
12485	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12486	MrBayesPrint (" Restore \n");
12487	MrBayesPrint (" \n");
12488	MrBayesPrint (" This command restores taxa to the analysis. The correct usage is: \n");
12489	MrBayesPrint (" \n");
12490	MrBayesPrint (" restore <name and/or number and/or taxset> ... \n");
12491	MrBayesPrint (" \n");
12492	MrBayesPrint (" A list of the taxon names or taxon numbers (labelled 1 to ntax in the order \n");
12493	MrBayesPrint (" in the matrix) or taxset(s) can be used. For example, the following: \n");
12494	MrBayesPrint (" \n");
12495	MrBayesPrint (" restore 1 2 Homo_sapiens \n");
12496	MrBayesPrint (" \n");
12497	MrBayesPrint (" restores taxa 1, 2, and the taxon labelled Homo_sapiens to the analysis. \n");
12498	MrBayesPrint (" You can also use \"all\" to restore all of the taxa. For example, \n");
12499	MrBayesPrint (" \n");
12500	MrBayesPrint (" restore all \n");
12501	MrBayesPrint (" \n");
12502	MrBayesPrint (" restores all of the taxa to the analysis. \n");
12503	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12504	}
12505	else if (!strcmp(helpTkn, "Quit"))
12506	{
12507	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12508	MrBayesPrint (" Quit \n");
12509	MrBayesPrint (" \n");
12510	MrBayesPrint (" This command quits the program. The correct usage is: \n");
12511	MrBayesPrint (" \n");
12512	MrBayesPrint (" quit \n");
12513	MrBayesPrint (" \n");
12514	MrBayesPrint (" It is a very easy command to use properly. \n");
12515	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12516	}
12517	else if (!strcmp(helpTkn, "Disclaimer"))
12518	{
12519	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12520	MrBayesPrint (" Disclaimer \n");
12521	MrBayesPrint (" \n");
12522	MrBayesPrint (" This command shows the disclaimer for the program. In short, the disclaimer \n");
12523	MrBayesPrint (" states that the authors are not responsible for any silly things you may do \n");
12524	MrBayesPrint (" to your computer or any unforseen but possibly nasty things the computer \n");
12525	MrBayesPrint (" program may inadvertently do to you. \n");
12526	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12527	}
12528	else if (!strcmp(helpTkn, "Unlink"))
12529	{
12530	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12531	MrBayesPrint (" Unlink \n");
12532	MrBayesPrint (" \n");
12533	MrBayesPrint (" This command unlinks model parameters across partitions of the data. The \n");
12534	MrBayesPrint (" correct usage is: \n");
12535	MrBayesPrint (" \n");
12536	MrBayesPrint (" unlink <parameter name> = (<all> or <partition list>) \n");
12537	MrBayesPrint (" \n");
12538	MrBayesPrint (" A little background is necessary to understand this command. Upon exe- \n");
12539	MrBayesPrint (" cution of a file, a default partition is set up. This partition refer- \n");
12540	MrBayesPrint (" enced either by its name (\"default\") or number (0). If your data are \n");
12541	MrBayesPrint (" all of one type, then this default partition does not actually divide up \n");
12542	MrBayesPrint (" your characters. However, if your datatype is mixed, then the default \n");
12543	MrBayesPrint (" partition contains as many divisions as there are datatypes in your \n");
12544	MrBayesPrint (" character matrix. Of course, you can also define other partitions, and \n");
12545	MrBayesPrint (" switch among them using the set command (\"set partition=<name/number>\"). \n");
12546	MrBayesPrint (" Importantly, you can also assign model parameters to individual part- \n");
12547	MrBayesPrint (" itions or to groups of them using the \"applyto\" option in lset and \n");
12548	MrBayesPrint (" prset. When the program attempts to perform an analysis, the model is \n");
12549	MrBayesPrint (" set for individual partitions. If the same parameter applies to differ- \n");
12550	MrBayesPrint (" partitions and if that parameter has the same prior, then the program \n");
12551	MrBayesPrint (" will link the parameters: that is, it will use a single value for the \n");
12552	MrBayesPrint (" parameter. The program's default, then, is to strive for parsimony. \n");
12553	MrBayesPrint (" However, there are lots of cases where you may want unlink a parameter \n");
12554	MrBayesPrint (" across partitions. For example, you may want a different transition/ \n");
12555	MrBayesPrint (" transversion rate ratio to apply to different partitions. This command \n");
12556	MrBayesPrint (" allows you to unlink the parameters, or to make them different across \n");
12557	MrBayesPrint (" partitions. The converse of this command is \"link\", which links to- \n");
12558	MrBayesPrint (" gether parameters that were previously told to be different. The list \n");
12559	MrBayesPrint (" of parameters that can be unlinked includes: \n");
12560	MrBayesPrint (" \n");
12561	MrBayesPrint (" Tratio -- Transition/transversion rate ratio \n");
12562	MrBayesPrint (" Revmat -- Substitution rates of GTR model \n");
12563	MrBayesPrint (" Omega -- Nonsynonymous/synonymous rate ratio \n");
12564	MrBayesPrint (" Statefreq -- Character state frequencies \n");
12565	MrBayesPrint (" Shape -- Gamma shape parameter \n");
12566	MrBayesPrint (" Pinvar -- Proportion of invariable sites \n");
12567	MrBayesPrint (" Correlation -- Correlation parameter of autodiscrete gamma \n");
12568	MrBayesPrint (" Switchrates -- Switching rates for covarion model \n");
12569	MrBayesPrint (" Brlens -- Branch lengths of tree \n");
12570	MrBayesPrint (" Topology -- Topology of tree \n");
12571	MrBayesPrint (" Speciationrates -- Speciation rates for birth-death process \n");
12572	MrBayesPrint (" Ratemultiplier -- Rate multiplier for partitions \n");
12573	MrBayesPrint (" Extinctionrates -- Extinction rates for birth-death process \n");
12574	MrBayesPrint (" Theta -- Parameter for coalescence process \n");
12575	MrBayesPrint (" Growthrate -- Growth rate of coalescence process \n");
12576	MrBayesPrint (" Aamodel -- Aminoacid rate matrix \n");
12577	MrBayesPrint (" Cpprate -- Rate of Compound Poisson Process (CPP) \n");
12578	MrBayesPrint (" Cppmultdev -- Standard dev. of CPP rate multipliers (log scale) \n");
12579	MrBayesPrint (" Cppevents -- CPP events \n");
12580	MrBayesPrint (" TK02var -- Variance increase in TK02 relaxed clock model \n");
12581	MrBayesPrint (" TK02branchrates -- Branch rates of TK02 relaxed clock model \n");
12582	MrBayesPrint (" Igrvar -- Variance increase in IGR relaxed clock model \n");
12583	MrBayesPrint (" Igrbranchlens -- Branch lengths of IGR relaxed clock model \n");
12584	MrBayesPrint (" \n");
12585	MrBayesPrint (" For example, \n");
12586	MrBayesPrint (" \n");
12587	MrBayesPrint (" unlink shape=(all) \n");
12588	MrBayesPrint (" \n");
12589	MrBayesPrint (" unlinks the gamma shape parameter across all partitions of the data. \n");
12590	MrBayesPrint (" You can use \"showmodel\" to see the current linking status of the \n");
12591	MrBayesPrint (" characters. \n");
12592	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12593	}
12594	else if (!strcmp(helpTkn, "Link"))
12595	{
12596	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12597	MrBayesPrint (" Link \n");
12598	MrBayesPrint (" \n");
12599	MrBayesPrint (" This command links model parameters across partitions of the data. The \n");
12600	MrBayesPrint (" correct usage is: \n");
12601	MrBayesPrint (" \n");
12602	MrBayesPrint (" link <parameter name> = (<all> or <partition list>) \n");
12603	MrBayesPrint (" \n");
12604	MrBayesPrint (" The list of parameters that can be linked includes: \n");
12605	MrBayesPrint (" \n");
12606	MrBayesPrint (" Tratio -- Transition/transversion rate ratio \n");
12607	MrBayesPrint (" Revmat -- Substitution rates of GTR model \n");
12608	MrBayesPrint (" Omega -- Nonsynonymous/synonymous rate ratio \n");
12609	MrBayesPrint (" Statefreq -- Character state frequencies \n");
12610	MrBayesPrint (" Shape -- Gamma shape parameter \n");
12611	MrBayesPrint (" Pinvar -- Proportion of invariable sites \n");
12612	MrBayesPrint (" Correlation -- Correlation parameter of autodiscrete gamma \n");
12613	MrBayesPrint (" Switchrates -- Switching rates for covarion model \n");
12614	MrBayesPrint (" Brlens -- Branch lengths of tree \n");
12615	MrBayesPrint (" Topology -- Topology of tree \n");
12616	MrBayesPrint (" Speciationrates -- Speciation rates for birth-death process \n");
12617	MrBayesPrint (" Extinctionrates -- Extinction rates for birth-death process \n");
12618	MrBayesPrint (" Theta -- Parameter for coalescence process \n");
12619	MrBayesPrint (" Growthrate -- Growth rate of coalescence process \n");
12620	MrBayesPrint (" Aamodel -- Aminoacid rate matrix \n");
12621	MrBayesPrint (" Cpprate -- Rate of Compound Poisson Process (CPP) \n");
12622	MrBayesPrint (" Cppmultdev -- Standard dev. of CPP rate multipliers (log scale) \n");
12623	MrBayesPrint (" Cppevents -- CPP events \n");
12624	MrBayesPrint (" TK02var -- Variance increase in TK02 relaxed clock model \n");
12625	MrBayesPrint (" TK02branchrates -- Branch rates of TK02 relaxed clock model \n");
12626	MrBayesPrint (" Igrvar -- Variance increase in IGR relaxed clock model \n");
12627	MrBayesPrint (" Igrbrlens -- Branch lengths of IGR relaxed clock model \n");
12628	MrBayesPrint (" \n");
12629	MrBayesPrint (" For example, \n");
12630	MrBayesPrint (" \n");
12631	MrBayesPrint (" link shape=(all) \n");
12632	MrBayesPrint (" \n");
12633	MrBayesPrint (" links the gamma shape parameter across all partitions of the data. \n");
12634	MrBayesPrint (" You can use \"showmodel\" to see the current linking status of the \n");
12635	MrBayesPrint (" characters. For more information on this command, see the help menu \n");
12636	MrBayesPrint (" for link's converse, unlink (\"help unlink\"); \n");
12637	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12638	}
12639	else if (!strcmp(helpTkn, "Help"))
12640	{
12641	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12642	MrBayesPrint (" Help \n");
12643	MrBayesPrint (" \n");
12644	MrBayesPrint (" This command provides useful information on the use of this program. The \n");
12645	MrBayesPrint (" correct usage is \n");
12646	MrBayesPrint (" \n");
12647	MrBayesPrint (" help \n");
12648	MrBayesPrint (" \n");
12649	MrBayesPrint (" which gives a list of all available commands with a brief description of \n");
12650	MrBayesPrint (" each or \n");
12651	MrBayesPrint (" \n");
12652	MrBayesPrint (" help <command> \n");
12653	MrBayesPrint (" \n");
12654	MrBayesPrint (" which gives detailed information on the use of <command>. \n");
12655	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12656	}
12657	else if (!strcmp(helpTkn, "Sump"))
12658	{
12659	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12660	MrBayesPrint (" Sump \n");
12661	MrBayesPrint (" \n");
12662	MrBayesPrint (" During an MCMC analysis, MrBayes prints the sampled parameter values to one or\n");
12663	MrBayesPrint (" more tab-delimited text files, one for each independent run in your analysis. \n");
12664	MrBayesPrint (" The command 'Sump' summarizes the information in this parameter file or these \n");
12665	MrBayesPrint (" parameter files. By default, the root of the parameter file name(s) is assumed\n");
12666	MrBayesPrint (" to be the name of the last matrix-containing nexus file. MrBayes also remem- \n");
12667	MrBayesPrint (" bers the number of independent runs in the last analysis that you set up, re- \n");
12668	MrBayesPrint (" gardless of whether you actually ran it. For instance, if there were two in- \n");
12669	MrBayesPrint (" dependent runs, which is the initial setting when you read in a new matrix, \n");
12670	MrBayesPrint (" MrBayes will assume that there are two parameter files with the endings \n");
12671	MrBayesPrint (" '.run1.p' and '.run2.p'. You can change the root of the file names and the \n");
12672	MrBayesPrint (" number of runs using the 'Filename' and 'Nruns' settings. \n");
12673	MrBayesPrint (" \n");
12674	MrBayesPrint (" When you invoke the 'Sump' command, three items are output: (1) a generation \n");
12675	MrBayesPrint (" plot of the likelihood values; (2) estimates of the marginal likelihood of \n");
12676	MrBayesPrint (" the model; and (3) a table with the mean, variance, and 95 percent credible \n");
12677	MrBayesPrint (" interval for the sampled parameters. All three items are output to screen. \n");
12678	MrBayesPrint (" The table of marginal likelihoods is also printed to a file with the ending \n");
12679	MrBayesPrint (" '.lstat' and the parameter table to a file with the ending '.pstat'. For some \n");
12680	MrBayesPrint (" model parameters, there may also be a '.mstat' file. \n");
12681	MrBayesPrint (" \n");
12682	MrBayesPrint (" When running 'Sump' you typically want to discard a specified number or \n");
12683	MrBayesPrint (" fraction of samples from the beginning of the chain as the burn in. This is \n");
12684	MrBayesPrint (" done using the same mechanism used by the 'mcmc' command. That is, if you \n");
12685	MrBayesPrint (" run an mcmc analysis with a relative burn in of 25 %% of samples for con- \n");
12686	MrBayesPrint (" vergence diagnostics, then the same burn in will be used for a subsequent \n");
12687	MrBayesPrint (" sump command, unless a different burn in is specified. That is, issuing \n");
12688	MrBayesPrint (" \n");
12689	MrBayesPrint (" sump \n");
12690	MrBayesPrint (" \n");
12691	MrBayesPrint (" immediately after 'mcmc', will result in using the same burn in settings as \n");
12692	MrBayesPrint (" for the 'mcmc' command. All burnin settings are reset to default values every \n");
12693	MrBayesPrint (" time a new matrix is read in, namely relative burnin ('relburnin=yes') with \n");
12694	MrBayesPrint (" 25 %% of samples discarded ('burninfrac = 0.25'). \n");
12695	MrBayesPrint (" \n");
12696	MrBayesPrint (" Options: \n");
12697	MrBayesPrint (" \n");
12698	MrBayesPrint (" Relburnin -- If this option is set to 'Yes', then a proportion of the \n");
12699	MrBayesPrint (" samples will be discarded as burnin when calculating summary \n");
12700	MrBayesPrint (" statistics. The proportion to be discarded is set with \n");
12701	MrBayesPrint (" 'Burninfrac' (see below). When the 'Relburnin' option is set \n");
12702	MrBayesPrint (" to 'No', then a specific number of samples is discarded \n");
12703	MrBayesPrint (" instead. This number is set by 'Burnin' (see below). Note that\n");
12704	MrBayesPrint (" the burnin setting is shared across the 'sumt', 'sump', and \n");
12705	MrBayesPrint (" 'mcmc' commands. \n");
12706	MrBayesPrint (" Burnin -- Determines the number of samples (not generations) that will \n");
12707	MrBayesPrint (" be discarded when summary statistics are calculated. The \n");
12708	MrBayesPrint (" value of this option is only applicable when 'Relburnin' is \n");
12709	MrBayesPrint (" set to 'No'. \n");
12710	MrBayesPrint (" Burninfrac -- Determines the fraction of samples that will be discarded when\n");
12711	MrBayesPrint (" summary statistics are calculated. The setting only takes \n");
12712	MrBayesPrint (" effect if 'Relburnin' is set to 'Yes'. \n");
12713	MrBayesPrint (" Nruns -- Determines how many '.p' files from independent analyses that \n");
12714	MrBayesPrint (" will be summarized. If Nruns > 1 then the names of the files \n");
12715	MrBayesPrint (" are derived from 'Filename' by adding '.run1.p', '.run2.p', \n");
12716	MrBayesPrint (" etc. If Nruns=1, then the single file name is obtained by \n");
12717	MrBayesPrint (" adding '.p' to 'Filename'. \n");
12718	MrBayesPrint (" Filename -- The name of the file to be summarized. This is the base of the\n");
12719	MrBayesPrint (" file name to which endings are added according to the current \n");
12720	MrBayesPrint (" setting of the 'Nruns' parameter. If 'Nruns' is 1, then only \n");
12721	MrBayesPrint (" '.p' is added to the file name. Otherwise, the endings will \n");
12722	MrBayesPrint (" be '.run1.p', '.run2.p', etc. \n");
12723	MrBayesPrint (" Outputname -- Base name of the file(s) to which 'Sump' results will be \n");
12724	MrBayesPrint (" printed. \n");
12725	MrBayesPrint (" Hpd -- Determines whether credibility intervals will be given as the \n");
12726	MrBayesPrint (" region of Highest Posterior Density ('Yes') or as the interval\n");
12727	MrBayesPrint (" containing the median 95 %% of sampled values ('No'). \n");
12728	MrBayesPrint (" Minprob -- Determines the minimum probability of submodels to be included\n");
12729	MrBayesPrint (" in summary statistics. Only applicable to models that explore \n");
12730	MrBayesPrint (" submodel spaces, like 'nst=mixed' and 'aamodelpr=mixed'. \n");
12731	MrBayesPrint (" \n");
12732	MrBayesPrint (" Current settings: \n");
12733	MrBayesPrint (" \n");
12734	MrBayesPrint (" Parameter Options Current Setting \n");
12735	MrBayesPrint (" -------------------------------------------------------- \n");
12736	MrBayesPrint (" Relburnin Yes/No %s \n", chainParams.relativeBurnin == YES ? "Yes" : "No");
12737	MrBayesPrint (" Burnin <number> %d \n", chainParams.chainBurnIn);
12738	MrBayesPrint (" Burninfrac <number> %1.2lf \n", chainParams.burninFraction);
12739	MrBayesPrint (" Nruns <number> %d \n", sumpParams.numRuns);
12740	if (sumpParams.numRuns == 1)
12741	MrBayesPrint (" Filename <name> %s<.p>\n", sumpParams.sumpFileName);
12742	else
12743	MrBayesPrint (" Filename <name> %s<.run<i>.p>\n", sumpParams.sumpFileName);
12744	MrBayesPrint (" Outputname <name> %s<.pstat etc>\n", sumpParams.sumpOutfile);
12745	MrBayesPrint (" Hpd Yes/No %s \n", sumpParams.HPD == YES ? "Yes" : "No");
12746	MrBayesPrint (" Minprob <number> %1.3lf \n", sumpParams.minProb);
12747	MrBayesPrint (" \n");
12748	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12749	}
12750	else if (!strcmp(helpTkn, "Sumss"))
12751	{
12752	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12753	MrBayesPrint (" Sumss \n");
12754	MrBayesPrint (" \n");
12755	MrBayesPrint (" This command summarizes results of stepping stone analyses. It is a tool to \n");
12756	MrBayesPrint (" investigate the obtained results, and to help find the proper step burn-in. \n");
12757	MrBayesPrint (" To get more help information on stepping-stone analyses, use 'help ss'. \n");
12758	MrBayesPrint (" \n");
12759	MrBayesPrint (" During stepping-stone analysis, MrBayes collects the sampled likelihoods in \n");
12760	MrBayesPrint (" order to estimate the marginal likelihood at the end. It also prints the sam- \n");
12761	MrBayesPrint (" pled parameter values to one or more tab-delimited text files, one for each \n");
12762	MrBayesPrint (" independent run in your analysis. The command 'Sumss' summarizes likelihood \n");
12763	MrBayesPrint (" values stored in these parameter files and calculates marginal likelihood es- \n");
12764	MrBayesPrint (" timates. The names of the files that are summarized are exactly the same as \n");
12765	MrBayesPrint (" the names of the files used for the 'sump' command. In fact, the 'filename' \n");
12766	MrBayesPrint (" setting is a shared setting for the 'sump' and 'sumss' commands. That is, if \n");
12767	MrBayesPrint (" you change the setting in one of the commands, it would change the setting in \n");
12768	MrBayesPrint (" the other command as well. \n");
12769	MrBayesPrint (" \n");
12770	MrBayesPrint (" When you invoke the 'Sumss' command, three items are output: (1) 'Step contri-\n");
12771	MrBayesPrint (" bution table' - summarizes the contribution of each step to the overall esti- \n");
12772	MrBayesPrint (" mate; (2) 'Step plot' - plot of the likelihood values for the initial burn-in \n");
12773	MrBayesPrint (" phase or a chosen step in the stepping-stone algorithm; (3) 'Joined plot' - \n");
12774	MrBayesPrint (" summarizes sampling across all steps in the algorithm. \n");
12775	MrBayesPrint (" \n");
12776	MrBayesPrint (" Step contribution table \n");
12777	MrBayesPrint (" The printed table is similar to the one output to the .ss file. The main pur- \n");
12778	MrBayesPrint (" pose of the table is to summarize marginal likelihood for different values of \n");
12779	MrBayesPrint (" the step burn-in after the stepping stone analysis has finished. The burn-in \n");
12780	MrBayesPrint (" is controlled by the 'Relburnin', 'Burnin' and 'Burninfrac' settings. \n");
12781	MrBayesPrint (" Note that during stepping-stone analyses, step contributions to marginal \n");
12782	MrBayesPrint (" likelihood are calculated based on all generations excluding burn-in. 'Sumss' \n");
12783	MrBayesPrint (" on the other hand makes estimates based only on the sampled generations. This \n");
12784	MrBayesPrint (" may lead to slight difference in results compared to the one printed to the \n");
12785	MrBayesPrint (" .ss file. \n");
12786	MrBayesPrint (" \n");
12787	MrBayesPrint (" Step plot \n");
12788	MrBayesPrint (" The main objective of the plot is to provide a close look at a given step in \n");
12789	MrBayesPrint (" the analysis. Which step is printed here is defined by the 'Steptoplot' set- \n");
12790	MrBayesPrint (" ting. The plot could be used to inspect if the chosen step burn-in is appro- \n");
12791	MrBayesPrint (" priate for the given step. It could also be used to check if the initial burn-\n");
12792	MrBayesPrint (" in phase has converged. Note that the amount of discarded samples is controled\n");
12793	MrBayesPrint (" by the 'Discardfrac' setting, and not by the ordinary burn-in settings. \n");
12794	MrBayesPrint (" \n");
12795	MrBayesPrint (" Joined plot \n");
12796	MrBayesPrint (" Different steps sample from different power posterior distributions. When we \n");
12797	MrBayesPrint (" switch from one distribution to another, it takes some number of generations \n");
12798	MrBayesPrint (" before the chain settles at the correct stationary distribution. This lag is \n");
12799	MrBayesPrint (" called a 'temperature lag' and if the corresponding samples are not removed, \n");
12800	MrBayesPrint (" it will result in a biased estimate. It is difficult to determine the lag be- \n");
12801	MrBayesPrint (" forehand, but MrBayes allows you to explore different step burn-in settings \n");
12802	MrBayesPrint (" after you have finished the stepping-stone algorithm, without having to rerun \n");
12803	MrBayesPrint (" the whole analysis. The 'Joined plot' helps to facilitate the choice of the \n");
12804	MrBayesPrint (" right step burn-in. The plot summarizes samples across all steps and gives you\n");
12805	MrBayesPrint (" a quick overview of the whole analysis. \n");
12806	MrBayesPrint (" \n");
12807	MrBayesPrint (" Specifically, the following procedure is used to obtain the joined plot. Each \n");
12808	MrBayesPrint (" step has the same number N of samples taken. We number each sample 1 to N \n");
12809	MrBayesPrint (" within steps according to the order in which the samples are taken. The first \n");
12810	MrBayesPrint (" sample in each step is numbered 1, and the last sample is N. For each number i\n");
12811	MrBayesPrint (" in [1,..., N], we sum up log likelihoods for all samples numbered i across all\n");
12812	MrBayesPrint (" steps. The joined plot is a graph of the step number versus the normalized \n");
12813	MrBayesPrint (" sums we get in the procedure describe above. This directly visualizes the tem-\n");
12814	MrBayesPrint (" perature lag and allows you to select the appropriate step burn-in. \n");
12815	MrBayesPrint (" \n");
12816	MrBayesPrint (" Ideally, after you discard the appropriate step burn-in, the graph should \n");
12817	MrBayesPrint (" appear as white noise around the estimated value. If you see an increasing or \n");
12818	MrBayesPrint (" decreasing tendency in the beginning of the graph, you should increase the \n");
12819	MrBayesPrint (" step burn-in. If you see an increasing or decreasing tendency across the whole\n");
12820	MrBayesPrint (" graph, then the initial burn-in phase was not long enough. In this case, you \n");
12821	MrBayesPrint (" need to rerun the analysis with a longer initial burn-in. \n");
12822	MrBayesPrint (" \n");
12823	MrBayesPrint (" To make it easier to observe tendencies in the plotted graph you can choose \n");
12824	MrBayesPrint (" different levels of curve smoothing. If 'Smoothing' is set to k, it means that\n");
12825	MrBayesPrint (" for each step i we take an average over step i and k neighboring samples in \n");
12826	MrBayesPrint (" both directions, i.e., the k-smoothed estimate for step i is an average over \n");
12827	MrBayesPrint (" values for steps [i-k,...,i+k]. \n");
12828	MrBayesPrint (" \n");
12829	MrBayesPrint (" \n");
12830	MrBayesPrint (" Options: \n");
12831	MrBayesPrint (" \n");
12832	MrBayesPrint (" Allruns -- If set to 'Yes', it forces all runs to be printed on the same \n");
12833	MrBayesPrint (" graph when drawing joined and step plots. If set to 'No', each\n");
12834	MrBayesPrint (" run is printed on a separat plot. \n");
12835	MrBayesPrint (" Askmore -- Long analyses may produce huge .p files. Reading in them may \n");
12836	MrBayesPrint (" take several minutes. If you want to investigate different \n");
12837	MrBayesPrint (" aspects of your analyses, it could be very inconvenient to \n");
12838	MrBayesPrint (" wait for several minutes each time you want to get a new sum- \n");
12839	MrBayesPrint (" mary for different settings. If you set 'Askmore' to 'YES', \n");
12840	MrBayesPrint (" sumss will read .p files only once. After responding to the \n");
12841	MrBayesPrint (" original query, it will interactivaly ask you if you wish to \n");
12842	MrBayesPrint (" produce more tables and plots for different settings of \n");
12843	MrBayesPrint (" 'Burnin' or 'Smoothing' (see below). \n");
12844	MrBayesPrint (" Relburnin -- If this option is set to 'Yes', then a proportion of the \n");
12845	MrBayesPrint (" samples from each step will be discarded as burnin when calcu-\n");
12846	MrBayesPrint (" lsting summary statistics. The proportion to be discarded is \n");
12847	MrBayesPrint (" set with 'Burninfrac' (see below). When the 'Relburnin' option\n");
12848	MrBayesPrint (" is set to 'No', then a specific number of samples is discarded\n");
12849	MrBayesPrint (" instead. This number is set by 'Burnin'. Note that the burnin \n");
12850	MrBayesPrint (" settings --- 'Relburnin', 'Burnin', and 'Burninfrac' --- are \n");
12851	MrBayesPrint (" shared across the 'sumt', 'sump', 'sumss' and 'mcmc' commands.\n");
12852	MrBayesPrint (" Burnin -- Determines the number of samples (not generations) that will \n");
12853	MrBayesPrint (" be discarded from each step when summary statistics are calcu-\n");
12854	MrBayesPrint (" lated. The value of this option is only applicable when \n");
12855	MrBayesPrint (" 'Relburnin' is set to 'No'. \n");
12856	MrBayesPrint (" Burninfrac -- Determines the fraction of samples that will be discarded from\n");
12857	MrBayesPrint (" each step when summary statistics are calculated. The setting \n");
12858	MrBayesPrint (" only takes effect if 'Relburnin' is set to 'Yes'. \n");
12859	MrBayesPrint (" Discardfrac -- Determines the fraction of samples that will be discarded when\n");
12860	MrBayesPrint (" a step plot is printed. It is similar to the 'Burninfrac' set-\n");
12861	MrBayesPrint (" ting, but unlike 'Burninfrac' it is used only for better vis- \n");
12862	MrBayesPrint (" ualization of the step plot. It has no effect on the number of\n");
12863	MrBayesPrint (" samples discarded during marginal likelihood computation. \n");
12864	MrBayesPrint (" Filename -- The name of the file to be summarized. This is the base of the\n");
12865	MrBayesPrint (" file name to which endings are added according to the current \n");
12866	MrBayesPrint (" setting of the 'Nruns' parameter. If 'Nruns' is 1, then only \n");
12867	MrBayesPrint (" '.p' is added to the file name. Otherwise, the endings will \n");
12868	MrBayesPrint (" be '.run1.p', '.run2.p', etc. Note that the 'Filename' setting\n");
12869	MrBayesPrint (" is shared with 'sump' command. \n");
12870	MrBayesPrint (" Nruns -- Determines how many '.p' files from independent analyses that \n");
12871	MrBayesPrint (" will be summarized. If Nruns > 1 then the names of the files \n");
12872	MrBayesPrint (" are derived from 'Filename' by adding '.run1.p', '.run2.p', \n");
12873	MrBayesPrint (" etc. If Nruns=1, then the single file name is obtained by \n");
12874	MrBayesPrint (" adding '.p' to 'Filename'. \n");
12875	MrBayesPrint (" Steptoplot -- Defines which step will be printed in the step plot.If the \n");
12876	MrBayesPrint (" value is set to 0, then the initial sample from the posterior \n");
12877	MrBayesPrint (" will be used. \n");
12878	MrBayesPrint (" Smoothing -- Determines smoothing of the joined plot (see above). A value \n");
12879	MrBayesPrint (" equal to 0 results in no smoothing. \n");
12880	MrBayesPrint (" \n");
12881	MrBayesPrint (" Current settings: \n");
12882	MrBayesPrint (" \n");
12883	MrBayesPrint (" Parameter Options Current Setting \n");
12884	MrBayesPrint (" -------------------------------------------------------- \n");
12885	MrBayesPrint (" Allruns Yes/No %s \n", sumssParams.allRuns == YES ? "Yes" : "No");
12886	MrBayesPrint (" Askmore Yes/No %s \n", sumssParams.askForMorePlots == YES ? "Yes" : "No");
12887	MrBayesPrint (" Relburnin Yes/No %s \n", chainParams.relativeBurnin == YES ? "Yes" : "No");
12888	MrBayesPrint (" Burnin <number> %d \n", chainParams.chainBurnIn);
12889	MrBayesPrint (" Burninfrac <number> %1.2lf \n", chainParams.burninFraction);
12890	MrBayesPrint (" Discardfrac <number> %1.2lf \n", sumssParams.discardFraction);
12891	if (sumpParams.numRuns == 1)
12892	MrBayesPrint (" Filename <name> %s<.p>\n", sumpParams.sumpFileName);
12893	else
12894	MrBayesPrint (" Filename <name> %s<.run<i>.p>\n", sumpParams.sumpFileName);
12895	MrBayesPrint (" Nruns <number> %d \n", sumpParams.numRuns);
12896	MrBayesPrint (" Steptoplot <number> %d \n", sumssParams.stepToPlot);
12897	MrBayesPrint (" Smoothing <number> %d \n", sumssParams.smoothing);
12898	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12899	}
12900	else if (!strcmp(helpTkn, "Comparetree"))
12901	{
12902	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12903	MrBayesPrint (" Comparetree \n");
12904	MrBayesPrint (" \n");
12905	MrBayesPrint (" This command compares the trees in two files, called \"filename1\" and \n");
12906	MrBayesPrint (" \"filename2\". It will output a bivariate plot of the split frequencies \n");
12907	MrBayesPrint (" as well as plots of the tree distance as a function of the generation. The \n");
12908	MrBayesPrint (" plots can be used to get a quick indication of whether two runs have con- \n");
12909	MrBayesPrint (" verged onto the same set of trees. The \"Comparetree\" command will also \n");
12910	MrBayesPrint (" produce a \".pairs\" file and a \".dists\" file (these file endings are added \n");
12911	MrBayesPrint (" to the end of the \"Outputname\"). The \".pairs\" file contains the paired \n");
12912	MrBayesPrint (" split frequencies from the two tree samples; the \".dists\" file contains the \n");
12913	MrBayesPrint (" tree distance values. \n");
12914	MrBayesPrint (" \n");
12915	MrBayesPrint (" Note that the \"Sumt\" command provides a different set of convergence diag- \n");
12916	MrBayesPrint (" nostics tools that you may also want to explore. Unlike \"Comparetree\", \"Sumt\"\n");
12917	MrBayesPrint (" can compare more than two tree samples and will calculate consensus trees and \n");
12918	MrBayesPrint (" split frequencies from the pooled samples. \n");
12919	MrBayesPrint (" \n");
12920	MrBayesPrint (" Options: \n");
12921	MrBayesPrint (" \n");
12922	MrBayesPrint (" Relburnin -- If this option is set to 'Yes', then a proportion of the \n");
12923	MrBayesPrint (" samples will be discarded as burnin when calculating summary \n");
12924	MrBayesPrint (" statistics. The proportion to be discarded is set with \n");
12925	MrBayesPrint (" Burninfrac (see below). When the Relburnin option is set to \n");
12926	MrBayesPrint (" 'No', then a specific number of samples is discarded instead.\n");
12927	MrBayesPrint (" This number is set by Burnin (see below). Note that the \n");
12928	MrBayesPrint (" burnin setting is shared with the 'mcmc', 'sumt', 'sump' and \n");
12929	MrBayesPrint (" 'plot' commands. \n");
12930	MrBayesPrint (" Burnin -- Determines the number of samples (not generations) that will \n");
12931	MrBayesPrint (" be discarded when summary statistics are calculated. The \n");
12932	MrBayesPrint (" value of this option is only relevant when Relburnin is set \n");
12933	MrBayesPrint (" to 'No'. \n");
12934	MrBayesPrint (" BurninFrac -- Determines the fraction of samples that will be discarded \n");
12935	MrBayesPrint (" when summary statistics are calculated. The value of this \n");
12936	MrBayesPrint (" option is only relevant when Relburnin is set to 'Yes'. \n");
12937	MrBayesPrint (" Example: A value for this option of 0.25 means that 25%% of \n");
12938	MrBayesPrint (" the samples will be discarded. \n");
12939	MrBayesPrint (" Minpartfreq -- The minimum probability of partitions to include in summary \n");
12940	MrBayesPrint (" statistics. \n");
12941	MrBayesPrint (" Filename1 -- The name of the first tree file to compare. \n");
12942	MrBayesPrint (" Filename2 -- The name of the second tree file to compare. \n");
12943	MrBayesPrint (" Outputname -- Name of the file to which 'comparetree' results will be \n");
12944	MrBayesPrint (" printed. \n");
12945	MrBayesPrint (" \n");
12946	MrBayesPrint (" Current settings: \n");
12947	MrBayesPrint (" \n");
12948	MrBayesPrint (" Parameter Options Current Setting \n");
12949	MrBayesPrint (" -------------------------------------------------------- \n");
12950	MrBayesPrint (" Relburnin Yes/No %s \n", chainParams.relativeBurnin == YES ? "Yes" : "No");
12951	MrBayesPrint (" Burnin <number> %d \n", chainParams.chainBurnIn);
12952	MrBayesPrint (" Burninfrac <number> %1.2lf \n", chainParams.burninFraction);
12953	MrBayesPrint (" Minpartfreq <number> %1.2lf \n", comptreeParams.minPartFreq);
12954	MrBayesPrint (" Filename1 <name> %s \n", comptreeParams.comptFileName1);
12955	MrBayesPrint (" Filename2 <name> %s \n", comptreeParams.comptFileName2);
12956	MrBayesPrint (" Outputname <name> %s \n", comptreeParams.comptOutfile);
12957	MrBayesPrint (" \n");
12958	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12959	}
12960	else if (!strcmp(helpTkn, "Sumt"))
12961	{
12962	MrBayesPrint (" --------------------------------------------------------------------------- \n");
12963	MrBayesPrint (" Sumt \n");
12964	MrBayesPrint (" \n");
12965	MrBayesPrint (" This command is used to produce summary statistics for trees sampled during \n");
12966	MrBayesPrint (" a Bayesian MCMC analysis. You can either summarize trees from one individual \n");
12967	MrBayesPrint (" analysis, or trees coming from several independent analyses. In either case, \n");
12968	MrBayesPrint (" all the sampled trees are read in and the proportion of the time any single \n");
12969	MrBayesPrint (" taxon bipartition (split) is found is counted. The proportion of the time that\n");
12970	MrBayesPrint (" the bipartition is found is an approximation of the posterior probability of \n");
12971	MrBayesPrint (" the bipartition. (Remember that a taxon bipartition is defined by removing a \n");
12972	MrBayesPrint (" branch on the tree, dividing the tree into those taxa to the left and right \n");
12973	MrBayesPrint (" of the removed branch. This set is called a taxon bipartition.) The branch \n");
12974	MrBayesPrint (" length of the bipartition is also recorded, if branch lengths have been saved \n");
12975	MrBayesPrint (" to file. The result is a list of the taxon bipartitions found, the frequency \n");
12976	MrBayesPrint (" with which they were found, the posterior probability of the bipartition \n");
12977	MrBayesPrint (" and, the mean and variance of the branch lengths or node depths, and various \n");
12978	MrBayesPrint (" other statistics. \n");
12979	MrBayesPrint (" \n");
12980	MrBayesPrint (" The key to the partitions is output to a file with the suffix '.parts'. The \n");
12981	MrBayesPrint (" summary statistics pertaining to bipartition probabilities are output to a \n");
12982	MrBayesPrint (" file with the suffix '.tstat', and the statistics pertaining to branch or node\n");
12983	MrBayesPrint (" parameters are output to a file with the suffix '.vstat'. \n");
12984	MrBayesPrint (" \n");
12985	MrBayesPrint (" A consensus tree is also printed to a file with the suffix '.con.tre' and \n");
12986	MrBayesPrint (" printed to the screen as a cladogram, and as a phylogram if branch lengths \n");
12987	MrBayesPrint (" have been saved. The consensus tree is either a 50 percent majority rule tree \n");
12988	MrBayesPrint (" or a majority rule tree showing all compatible partitions. If branch lengths \n");
12989	MrBayesPrint (" have been recorded during the run, the '.con.tre' file will contain a consen- \n");
12990	MrBayesPrint (" sus tree with branch lengths and interior nodes labelled with support values. \n");
12991	MrBayesPrint (" By default, the consensus tree will also contain other summary information in \n");
12992	MrBayesPrint (" a format understood by the program 'FigTree'. To use a simpler format under- \n");
12993	MrBayesPrint (" stood by other tree-drawing programs, such as 'TreeView', set 'Conformat' to \n");
12994	MrBayesPrint (" 'Simple'. \n");
12995	MrBayesPrint (" \n");
12996	MrBayesPrint (" MrBayes alo produces a file with the ending \".trprobs\" that contains a list \n");
12997	MrBayesPrint (" of all the trees that were found during the MCMC analysis, sorted by their \n");
12998	MrBayesPrint (" probabilities. This list of trees can be used to construct a credible set of \n");
12999	MrBayesPrint (" trees. For example, if you want to construct a 95 percent credible set of \n");
13000	MrBayesPrint (" trees, you include all of those trees whose cumulative probability is less \n");
13001	MrBayesPrint (" than or equal to 0.95. You have the option of displaying the trees to the \n");
13002	MrBayesPrint (" screen using the \"Showtreeprobs\" option. The default is to not display the \n");
13003	MrBayesPrint (" trees to the screen; the number of different trees sampled by the chain can \n");
13004	MrBayesPrint (" be quite large. If you are analyzing a large set of taxa, you may actually \n");
13005	MrBayesPrint (" want to skip the calculation of tree probabilities entirely by setting \n");
13006	MrBayesPrint (" 'Calctreeprobs' to 'No'. \n");
13007	MrBayesPrint (" \n");
13008	MrBayesPrint (" When calculating summary statistics you probably want to skip those trees that\n");
13009	MrBayesPrint (" were sampled in the initial part of the run, the so-called burn-in period. The\n");
13010	MrBayesPrint (" number of skipped samples is controlled by the 'Relburnin', 'Burnin', and \n");
13011	MrBayesPrint (" 'Burninfrac' settings, just as for the 'Mcmc' command. Since version 3.2.0, \n");
13012	MrBayesPrint (" the burn-in settings are shared across the 'Sumt', 'Sump' and 'Mcmc' commands.\n");
13013	MrBayesPrint (" That is, changing the burn-in setting for one command will change the settings\n");
13014	MrBayesPrint (" for subsequent calls to any of the other commands. \n");
13015	MrBayesPrint (" \n");
13016	MrBayesPrint (" If you are summarizing the trees sampled in several independent analyses, \n");
13017	MrBayesPrint (" such as those resulting from setting the 'Nruns' option of the 'Mcmc' command \n");
13018	MrBayesPrint (" to a value larger than 1, MrBayes will also calculate convergence diagnostics \n");
13019	MrBayesPrint (" for the sampled topologies and branch lengths. These values can help you \n");
13020	MrBayesPrint (" determine whether it is likely that your chains have converged. \n");
13021	MrBayesPrint (" \n");
13022	MrBayesPrint (" The 'Sumt' command expands the 'Filename' according to the current values of \n");
13023	MrBayesPrint (" the 'Nruns' and 'Ntrees' options. For instance, if both 'Nruns' and 'Ntrees' \n");
13024	MrBayesPrint (" are set to 1, 'Sumt' will try to open a file named '<Filename>.t'. If 'Nruns' \n");
13025	MrBayesPrint (" is set to 2 and 'Ntrees' to 1, then 'Sumt' will open two files, the first \n");
13026	MrBayesPrint (" named '<Filename>.run1.t' and the second '<Filename>.run2.t', etc. By default,\n");
13027	MrBayesPrint (" the 'Filename' option is set such that 'Sumt' automatically summarizes all the\n");
13028	MrBayesPrint (" results from your immediately preceding 'Mcmc' command. You can also use the \n");
13029	MrBayesPrint (" 'Sumt' command to summarize tree samples in older analyses. If you want to do \n");
13030	MrBayesPrint (" that, remember to first read in a matrix so that MrBayes knows what taxon \n");
13031	MrBayesPrint (" names to expect in the trees. Then set the 'Nruns', 'Ntrees' and 'Filename' \n");
13032	MrBayesPrint (" options appropriately if they differ from the MrBayes defaults. \n");
13033	MrBayesPrint (" \n");
13034	MrBayesPrint (" Options: \n");
13035	MrBayesPrint (" \n");
13036	MrBayesPrint (" Relburnin -- If this option is set to YES, then a proportion of the \n");
13037	MrBayesPrint (" samples will be discarded as burnin when calculating summary \n");
13038	MrBayesPrint (" statistics. The proportion to be discarded is set with \n");
13039	MrBayesPrint (" Burninfrac (see below). When the Relburnin option is set to \n");
13040	MrBayesPrint (" NO, then a specific number of samples is discarded instead. \n");
13041	MrBayesPrint (" This number is set by Burnin (see below). Note that the \n");
13042	MrBayesPrint (" burnin setting is shared across the 'sumt', 'sump', and \n");
13043	MrBayesPrint (" 'mcmc' commands. \n");
13044	MrBayesPrint (" Burnin -- Determines the number of samples (not generations) that will \n");
13045	MrBayesPrint (" be discarded when summary statistics are calculated. The \n");
13046	MrBayesPrint (" value of this option is only relevant when Relburnin is set \n");
13047	MrBayesPrint (" to NO. \n");
13048	MrBayesPrint (" BurninFrac -- Determines the fraction of samples that will be discarded \n");
13049	MrBayesPrint (" when summary statistics are calculated. The value of this \n");
13050	MrBayesPrint (" option is only relevant when Relburnin is set to YES. \n");
13051	MrBayesPrint (" Example: A value for this option of 0.25 means that 25%% of \n");
13052	MrBayesPrint (" the samples will be discarded. \n");
13053	MrBayesPrint (" Nruns -- Determines how many '.t' files from independent analyses that\n");
13054	MrBayesPrint (" will be summarized. If Nruns > 1 then the names of the files \n");
13055	MrBayesPrint (" are derived from 'Filename' by adding '.run1.t', '.run2.t', \n");
13056	MrBayesPrint (" etc. If Nruns=1 and Ntrees=1 (see below), then only '.t' is \n");
13057	MrBayesPrint (" added to 'Filename'. \n");
13058	MrBayesPrint (" Ntrees -- Determines how many trees there are in the sampled model. If \n");
13059	MrBayesPrint (" 'Ntrees' > 1 then the names of the files are derived from \n");
13060	MrBayesPrint (" 'Filename' by adding '.tree1.t', '.tree2.t', etc. If there \n");
13061	MrBayesPrint (" are both multiple trees and multiple runs, the filenames will\n");
13062	MrBayesPrint (" be '<Filename>.tree1.run1.t', '<Filename>.tree1.run2.t', etc.\n");
13063	MrBayesPrint (" Filename -- The name of the file(s) to be summarized. This is the base of\n");
13064	MrBayesPrint (" the file name, to which endings are added according to the \n");
13065	MrBayesPrint (" current settings of the 'Nruns' and 'Ntrees' options. \n");
13066	MrBayesPrint (" Minpartfreq -- The minimum probability of partitions to include in summary \n");
13067	MrBayesPrint (" statistics. \n");
13068	MrBayesPrint (" Contype -- Type of consensus tree. 'Halfcompat' results in a 50%% major-\n");
13069	MrBayesPrint (" ity rule tree, 'Allcompat' adds all compatible groups to such\n");
13070	MrBayesPrint (" a tree. \n");
13071	MrBayesPrint (" Conformat -- Format of consensus tree. The 'Figtree' setting results in a \n");
13072	MrBayesPrint (" consensus tree formatted for the program FigTree, with rich \n");
13073	MrBayesPrint (" summary statistics. The 'Simple' setting results in a simple \n");
13074	MrBayesPrint (" consensus tree written in a format read by a variety of pro- \n");
13075	MrBayesPrint (" grams. \n");
13076	MrBayesPrint (" Outputname -- Base name of the file(s) to which 'sumt' results will be \n");
13077	MrBayesPrint (" printed. The default is the same as 'Filename'. \n");
13078	MrBayesPrint (" Calctreeprobs -- Determines whether tree probabilities should be calculated. \n");
13079	MrBayesPrint (" Showtreeprobs -- Determines whether tree probabilities should be displayed on \n");
13080	MrBayesPrint (" screen. \n");
13081	MrBayesPrint (" Hpd -- Determines whether credibility intervals will be given as the\n");
13082	MrBayesPrint (" region of Highest Posterior Density ('Yes') or as the inter- \n");
13083	MrBayesPrint (" val containing the median 95 %% of sampled values ('No'). \n");
13084	MrBayesPrint (" \n");
13085	MrBayesPrint (" Current settings: \n");
13086	MrBayesPrint (" \n");
13087	MrBayesPrint (" Parameter Options Current Setting \n");
13088	MrBayesPrint (" -------------------------------------------------------- \n");
13089	MrBayesPrint (" Relburnin Yes/No %s \n", chainParams.relativeBurnin == YES ? "Yes" : "No");
13090	MrBayesPrint (" Burnin <number> %d \n", chainParams.chainBurnIn);
13091	MrBayesPrint (" Burninfrac <number> %1.2lf \n", chainParams.burninFraction);
13092	MrBayesPrint (" Nruns <number> %d \n", sumtParams.numRuns);
13093	MrBayesPrint (" Ntrees <number> %d \n", sumtParams.numTrees);
13094	if (sumtParams.numRuns == 1 && sumtParams.numTrees == 1)
13095	MrBayesPrint (" Filename <name> %s<.t>\n", sumtParams.sumtFileName);
13096	else if (sumtParams.numRuns == 1 && sumtParams.numTrees > 1)
13097	MrBayesPrint (" Filename <name> %s<.tree<i>.t>\n", sumtParams.sumtFileName);
13098	else if (sumtParams.numRuns > 1 && sumtParams.numTrees == 1)
13099	MrBayesPrint (" Filename <name> %s<.run<i>.t>\n", sumtParams.sumtFileName);
13100	else if (sumtParams.numRuns > 1 && sumtParams.numTrees > 1)
13101	MrBayesPrint (" Filename <name> %s<.tree<i>.run<i>.t>\n", sumtParams.sumtFileName);
13102	MrBayesPrint (" Minpartfreq <number> %1.2lf \n", sumtParams.minPartFreq);
13103	MrBayesPrint (" Contype Halfcompat/Allcompat %s\n", sumtParams.sumtConType);
13104	MrBayesPrint (" Conformat Figtree/Simple %s \n", sumtParams.consensusFormat == SIMPLE ? "Simple" : "Figtree");
13105	MrBayesPrint (" Outputname <name> %s<.parts etc>\n", sumtParams.sumtOutfile);
13106	MrBayesPrint (" Calctreeprobs Yes/No %s \n", sumtParams.calcTreeprobs == YES ? "Yes" : "No");
13107	MrBayesPrint (" Showtreeprobs Yes/No %s \n", sumtParams.showSumtTrees == YES ? "Yes" : "No");
13108	MrBayesPrint (" Hpd Yes/No %s \n", sumtParams.HPD == YES ? "Yes" : "No");
13109	MrBayesPrint (" \n");
13110	MrBayesPrint (" --------------------------------------------------------------------------- \n");
13111	}
13112	else if (!strcmp(helpTkn, "Tree"))
13113	{
13114	MrBayesPrint (" --------------------------------------------------------------------------- \n");
13115	MrBayesPrint (" Tree \n");
13116	MrBayesPrint (" \n");
13117	MrBayesPrint (" This command is used by MrBayes to write trees to a nexus tree file. Trees \n");
13118	MrBayesPrint (" are written in the Newick format. For instance, \n");
13119	MrBayesPrint (" \n");
13120	MrBayesPrint (" tree ((1,2),3,4); \n");
13121	MrBayesPrint (" \n");
13122	MrBayesPrint (" describes an unrooted tree with taxa 1 and 2 being more closely related to \n");
13123	MrBayesPrint (" each other than to taxa 3 and 4. If branch lengths are saved to file, they \n");
13124	MrBayesPrint (" are given after a colon sign immediately following the terminal taxon or the \n");
13125	MrBayesPrint (" interior node they refer to. An example of an unrooted tree with branch \n");
13126	MrBayesPrint (" lengths is: \n");
13127	MrBayesPrint (" \n");
13128	MrBayesPrint (" tree ((1:0.064573,2:0.029042):0.041239,3:0.203988,4:0.187654); \n");
13129	MrBayesPrint (" \n");
13130	MrBayesPrint (" Trees that are rooted (clock trees) are written with a basal dichotomy \n");
13131	MrBayesPrint (" instead of a basal trichotomy. If the tree described above had been rooted \n");
13132	MrBayesPrint (" on the branch leading to taxon 4, it would have been represented as: \n");
13133	MrBayesPrint (" \n");
13134	MrBayesPrint (" tree (((1,2),3),4); \n");
13135	MrBayesPrint (" \n");
13136	MrBayesPrint (" --------------------------------------------------------------------------- \n");
13137	}
13138	else if (!strcmp(helpTkn, "Report"))
13139	{
13140	MrBayesPrint (" --------------------------------------------------------------------------- \n");
13141	MrBayesPrint (" Report \n");
13142	MrBayesPrint (" \n");
13143	MrBayesPrint (" This command allows you to control how the posterior distribution is \n");
13144	MrBayesPrint (" reported. For rate parameters, it allows you to choose among several popular \n");
13145	MrBayesPrint (" parameterizations. The report command also allows you to request printing of \n");
13146	MrBayesPrint (" some model aspects that are usually not reported. For instance, if a node is \n");
13147	MrBayesPrint (" constrained in the analysis, MrBayes can print the probabilities of the \n");
13148	MrBayesPrint (" ancestral states at that node. Similarly, if there is rate variation in the \n");
13149	MrBayesPrint (" model, MrBayes can print the inferred site rates, and if there is omega varia-\n");
13150	MrBayesPrint (" tion, MrBayes can print the inferred omega (positive selection) values for \n");
13151	MrBayesPrint (" each codon. In a complex model with several partitions, each partition is \n");
13152	MrBayesPrint (" controlled separately using the same 'Applyto' mechanism as in the 'Lset' and \n");
13153	MrBayesPrint (" 'Prset' commands. \n");
13154	MrBayesPrint (" \n");
13155	MrBayesPrint (" Options: \n");
13156	MrBayesPrint (" \n");
13157	MrBayesPrint (" Applyto -- This option allows you to apply the report commands to specific \n");
13158	MrBayesPrint (" partitions. This command should be the first in the list of \n");
13159	MrBayesPrint (" commands specified in 'report'. \n");
13160	MrBayesPrint (" For example, \n");
13161	MrBayesPrint (" \n");
13162	MrBayesPrint (" report applyto=(1,2) tratio=ratio \n");
13163	MrBayesPrint (" \n");
13164	MrBayesPrint (" report applyto=(3) tratio=dirichlet \n");
13165	MrBayesPrint (" \n");
13166	MrBayesPrint (" would result in the transition and transversion rates of the \n");
13167	MrBayesPrint (" first and second partitions in the model being reported as a \n");
13168	MrBayesPrint (" ratio and the transition and transversion rates of the third \n");
13169	MrBayesPrint (" partition being reported as proportions of the rate sum (the \n");
13170	MrBayesPrint (" Dirichlet parameterization). \n");
13171	MrBayesPrint (" Tratio -- This specifies the report format for the transition and trans- \n");
13172	MrBayesPrint (" version rates of a nucleotide substituion model with nst=2. \n");
13173	MrBayesPrint (" If 'ratio' is selected, the rates will be reported as a ratio \n");
13174	MrBayesPrint (" (transition rate/transversion rate). If 'dirichlet' is selected, \n");
13175	MrBayesPrint (" the transition and transversion rates will instead be reported \n");
13176	MrBayesPrint (" as proportions of the rate sum. For example, if the transition \n");
13177	MrBayesPrint (" rate is three times the transversion rate and 'ratio' is selec- \n");
13178	MrBayesPrint (" ted, this will reported as a single value, '3.0'. If 'dirichlet' \n");
13179	MrBayesPrint (" is selected instead, the same rates will be reported using two \n");
13180	MrBayesPrint (" values, '0.75 0.25'. The sum of the Dirichlet values is always 1.\n");
13181	MrBayesPrint (" Although the Dirichlet format may be unfamiliar to some users, \n");
13182	MrBayesPrint (" it is more convenient for specifying priors than the ratio \n");
13183	MrBayesPrint (" format. \n");
13184	MrBayesPrint (" Revmat -- This specifies the report format for the substitution rates of \n");
13185	MrBayesPrint (" a GTR substitution model for nucleotide or amino acid data. If \n");
13186	MrBayesPrint (" 'ratio' is selected, the rates will be reported scaled to the \n");
13187	MrBayesPrint (" G-T rate (for nucleotides) or the Y-V rate (for amino acids). If \n");
13188	MrBayesPrint (" 'dirichlet' is specified instead, the rates are reported as pro- \n");
13189	MrBayesPrint (" portions of the rate sum. For instance, assume that the C-T rate \n");
13190	MrBayesPrint (" is twice the A-G rate and four times the transversion rates, \n");
13191	MrBayesPrint (" which are equal. If the report format is set to 'ratio', this \n");
13192	MrBayesPrint (" would be reported as '1.0 2.0 1.0 1.0 4.0 1.0' since the rates \n");
13193	MrBayesPrint (" are reported in the order rAC, rAG, rAT, rCG, rCT, rGT and scaled\n");
13194	MrBayesPrint (" relative to the last rate, the G-T rate. If 'dirichlet' is selec-\n");
13195	MrBayesPrint (" ted instead, the same rates would have been reported as '0.1 0.2 \n");
13196	MrBayesPrint (" 0.1 0.1 0.4 0.1' since the rates are now scaled so that they sum \n");
13197	MrBayesPrint (" to 1.0. The Dirichlet format is the parameterization used for \n");
13198	MrBayesPrint (" formulating priors on the rates. \n");
13199	MrBayesPrint (" Ratemult -- This specifies the report format used for the rate multiplier of \n");
13200	MrBayesPrint (" different model partitions. Three formats are available. If \n");
13201	MrBayesPrint (" 'scaled' is selected, then rates are scaled such that the mean \n");
13202	MrBayesPrint (" rate per site across partitions is 1.0. If 'ratio' is chosen, \n");
13203	MrBayesPrint (" the rates are scaled relative to the rate of the first parti- \n");
13204	MrBayesPrint (" tion. Finally, if 'dirichlet' is chosen, the rates are given as \n");
13205	MrBayesPrint (" proportions of the rate sum. The latter is the format used \n");
13206	MrBayesPrint (" when formulating priors on the rate multiplier. \n");
13207	MrBayesPrint (" Tree -- This specifies the report format used for the tree(s). Two op- \n");
13208	MrBayesPrint (" tions are available. 'Topology' results in only the topology \n");
13209	MrBayesPrint (" being printed to file, whereas 'brlens' causes branch lengths to \n");
13210	MrBayesPrint (" to be printed as well. \n");
13211	MrBayesPrint (" Ancstates -- If this option is set to 'yes', MrBayes will print the pro- \n");
13212	MrBayesPrint (" bability of the ancestral states at all constrained nodes. Typ- \n");
13213	MrBayesPrint (" ically, you are interested in the ancestral states of only a few \n");
13214	MrBayesPrint (" characters and only at one node in the tree. To perform such \n");
13215	MrBayesPrint (" an analysis, first define and enforce a topology constraint \n");
13216	MrBayesPrint (" using 'constraint' and 'prset topologypr = constraints (...)'. \n");
13217	MrBayesPrint (" Then put the character(s) of interest in a separate partition and\n");
13218	MrBayesPrint (" set MrBayes to report the ancestral states for that partition. \n");
13219	MrBayesPrint (" For instance, if the characters of interest are in partition 2, \n");
13220	MrBayesPrint (" use 'report applyto=(2) ancstates=yes' to force MrBayes to print \n");
13221	MrBayesPrint (" the probability of the ancestral states of those characters at \n");
13222	MrBayesPrint (" the constrained node to the '.p' file. \n");
13223	MrBayesPrint (" Siterates -- If this option is set to 'yes' and the relevant model has rate \n");
13224	MrBayesPrint (" variation across sites, then the site rates, weighted over rate \n");
13225	MrBayesPrint (" categories, will be reported to the '.p' file. \n");
13226	MrBayesPrint (" Possel -- If this option is set to 'yes' and the relevant model has omega \n");
13227	MrBayesPrint (" variation across sites, the probability that each model site \n");
13228	MrBayesPrint (" (codon in this case) is positively selected will be written to \n");
13229	MrBayesPrint (" file. \n");
13230	MrBayesPrint (" Siteomega -- If this option is set to 'yes' and the relevant model has omega \n");
13231	MrBayesPrint (" variation across sites, the weighted omega value (over omega \n");
13232	MrBayesPrint (" categories) for each model site will be reported to file. \n");
13233	MrBayesPrint (" \n");
13234	if (numCurrentDivisions == 0)
13235	tempInt = 1;
13236	else
13237	tempInt = numCurrentDivisions;
13238	for (i=0; i<tempInt; i++)
13239	{
13240	if (numCurrentDivisions == 0)
13241	{
13242	MrBayesPrint (" Default report settings: \n");
13243	mp = &defaultModel;
13244	}
13245	else
13246	{
13247	MrBayesPrint (" Current report settings for partition %d: \n", i+1);
13248	mp = &modelParams[i];
13249	}
13250	MrBayesPrint (" \n");
13251	MrBayesPrint (" Parameter Options Current Setting \n");
13252	MrBayesPrint (" -------------------------------------------------------- \n");
13253	MrBayesPrint (" Tratio Ratio/Dirichlet %s \n", mp->tratioFormat);
13254	MrBayesPrint (" Revmat Ratio/Dirichlet %s \n", mp->revmatFormat);
13255	MrBayesPrint (" Ratemult Scaled/Ratio/Dirichlet %s \n", mp->ratemultFormat);
13256	MrBayesPrint (" Tree Brlens/Topology %s \n", mp->treeFormat);
13257	MrBayesPrint (" Ancstates Yes/No %s \n", mp->inferAncStates);
13258	MrBayesPrint (" Siterates Yes/No %s \n", mp->inferSiteRates);
13259	MrBayesPrint (" Possel Yes/No %s \n", mp->inferPosSel);
13260	MrBayesPrint (" Siteomega Yes/No %s \n", mp->inferSiteOmegas);
13261	MrBayesPrint (" \n");
13262	MrBayesPrint (" ------------------------------------------------------------------ \n");
13263	MrBayesPrint (" \n");
13264	}
13265	}
13266	else if (!strcmp(helpTkn, "Manual"))
13267	{
13268	MrBayesPrint (" --------------------------------------------------------------------------- \n");
13269	MrBayesPrint (" Manual \n");
13270	MrBayesPrint (" \n");
13271	MrBayesPrint (" This command allows you to generate a text file containing help information \n");
13272	MrBayesPrint (" on all the available commands. This text file can be used as an up-to-date \n");
13273	MrBayesPrint (" command reference. You can set the name of the text file using the \n");
13274	MrBayesPrint (" \"filename\" option; the default is \"commref_mb<version>.txt\". \n");
13275	MrBayesPrint (" \n");
13276	MrBayesPrint (" Parameter Options Current Setting \n");
13277	MrBayesPrint (" -------------------------------------------------------- \n");
13278	MrBayesPrint (" Filename <name> %s \n", manFileName);
13279	MrBayesPrint (" \n");
13280	MrBayesPrint (" --------------------------------------------------------------------------- \n");
13281	}
13282	else if (!strcmp(helpTkn, "Showmoves"))
13283	{
13284	MrBayesPrint (" --------------------------------------------------------------------------- \n");
13285	MrBayesPrint (" Showmoves \n");
13286	MrBayesPrint (" \n");
13287	MrBayesPrint (" This command shows the MCMC samplers (moves) that are switched on for the \n");
13288	MrBayesPrint (" parameters in the current model. The basic usage is \n");
13289	MrBayesPrint (" \n");
13290	MrBayesPrint (" showmoves \n");
13291	MrBayesPrint (" \n");
13292	MrBayesPrint (" If you want to see all available moves, use \n");
13293	MrBayesPrint (" \n");
13294	MrBayesPrint (" showmoves allavailable=yes \n");
13295	MrBayesPrint (" \n");
13296	MrBayesPrint (" If you want to change any of the tuning parameters for the moves, use the \n");
13297	MrBayesPrint (" 'propset' command. \n");
13298	MrBayesPrint (" --------------------------------------------------------------------------- \n");
13299	}
13300	else if (!strcmp(helpTkn, "Showparams"))
13301	{
13302	MrBayesPrint (" --------------------------------------------------------------------------- \n");
13303	MrBayesPrint (" Showparams \n");
13304	MrBayesPrint (" \n");
13305	MrBayesPrint (" This command shows all of the parameters in the current model. The basic \n");
13306	MrBayesPrint (" usage is \n");
13307	MrBayesPrint (" \n");
13308	MrBayesPrint (" showparams \n");
13309	MrBayesPrint (" \n");
13310	MrBayesPrint (" The parameters are listed together with their priors, the available moves, \n");
13311	MrBayesPrint (" and the current value(s), which will be used as the starting values in the \n");
13312	MrBayesPrint (" next mcmc analysis. \n");
13313	MrBayesPrint (" --------------------------------------------------------------------------- \n");
13314	}
13315	else if (!strcmp(helpTkn, "Startvals"))
13316	{
13317	MrBayesPrint (" --------------------------------------------------------------------------- \n");
13318	MrBayesPrint (" Startvals \n");
13319	MrBayesPrint (" \n");
13320	MrBayesPrint (" Use this command to change the current values for parameters in your model. \n");
13321	MrBayesPrint (" These values will be used as the starting values in the next mcmc analysis. \n");
13322	MrBayesPrint (" The basic format is: \n");
13323	MrBayesPrint (" \n");
13324	MrBayesPrint (" startvals <param>=(<value_1>,<value_2>,...,<value_n>) \n");
13325	MrBayesPrint (" \n");
13326	MrBayesPrint (" for all substitution model parameters. The format is slightly different for \n");
13327	MrBayesPrint (" parameters that are written to a tree file: \n");
13328	MrBayesPrint (" \n");
13329	MrBayesPrint (" startvals <param>=<tree_name> \n");
13330	MrBayesPrint (" \n");
13331	MrBayesPrint (" This version of the command will look for a tree with the specified name \n");
13332	MrBayesPrint (" among the trees read in previously when parsing a tree block. The information \n");
13333	MrBayesPrint (" stored in that tree will be used to set the starting value of the parameter. \n");
13334	MrBayesPrint (" The parameters that are set using this mechanism include topology and branch \n");
13335	MrBayesPrint (" length parameters, as well as relaxed clock branch rates, cpp events and \n");
13336	MrBayesPrint (" cpp branch rate multipliers. \n");
13337	MrBayesPrint (" \n");
13338	MrBayesPrint (" The above versions of the command will set the value for all runs and chains. \n");
13339	MrBayesPrint (" You can also set the value for an individual run and chain by using the format\n");
13340	MrBayesPrint (" \n");
13341	MrBayesPrint (" startvals <param>(<run>,<chain>)=(<value_1>,...) \n");
13342	MrBayesPrint (" \n");
13343	MrBayesPrint (" where <run> is the index of the run and <chain> the index of the chain. If \n");
13344	MrBayesPrint (" the run index is omitted, the values will be changed for all runs. Similarly, \n");
13345	MrBayesPrint (" if the chain index is omitted, all chains will be set to the specified value. \n");
13346	MrBayesPrint (" For example, if we wanted to set the values of the stationary frequency \n");
13347	MrBayesPrint (" parameter pi{1} to (0.1,0.1,0.4,0.4) for all chains in run 1, and to \n");
13348	MrBayesPrint (" (0.3,0.3,0.2,0.2) for chain 3 of run 2, we would use \n");
13349	MrBayesPrint (" \n");
13350	MrBayesPrint (" startvals pi{1}(1,)=(0.1,0.1,0.4,0.4) pi{1}(2,3)=(0.3,0.3,0.2,0.2) \n");
13351	MrBayesPrint (" \n");
13352	MrBayesPrint (" --------------------------------------------------------------------------- \n");
13353	}
13354	else
13355	{
13356	return (ERROR);
13357	}
13358
13359	return (NO_ERROR);
13360
13361	}
13362
13363
13364
13365
13366
13367	/* IsAmbig: This function returns YES if character is set as ambiguous
13368	either by using parenthetic notation or by ambiguity codes. It returns
13369	NO if character is unambiguous, missing or gapped */
13370	int IsAmbig (int charCode, int dType)
13371
13372	{
13373
13374	if (dType == DNA \|\| dType == RNA \|\| dType == STANDARD
13375	\|\| dType == RESTRICTION \|\| dType == PROTEIN)
13376	{
13377	if (charCode != MISSING && charCode != GAP)
13378	if (NBits(charCode) > 1)
13379	return (YES);
13380	}
13381	else if (dType == CONTINUOUS)
13382	{
13383	/* do nothing, these cannot be partly ambiguous */
13384
13385	}
13386	else
13387	{
13388	MrBayesPrint ("Unknown datatype in \"IsAmbig\"\n", spacer);
13389	}
13390
13391	return (NO);
13392
13393	}
13394
13395
13396
13397
13398
13399	int IsArgValid (char tk, char validArg)
13400
13401	{
13402
13403	int i, j, k, tkLen, targetLen, numDiff, numStrMatches;
13404	char tempStr[100];
13405	ParmInfoPtr p;
13406
13407	p = paramPtr;
13408	tkLen = (int) strlen(tk);
13409
13410	numStrMatches = i = j = 0;
13411	do
13412	{
13413	if (p->valueList[i] == '\|' \|\| p->valueList[i] == '\0')
13414	{
13415	tempStr[j++] = '\0';
13416	targetLen = (int) strlen(tempStr);
13417	if (tkLen <= targetLen)
13418	{
13419	numDiff = 0;
13420	for (k=0; k<tkLen; k++)
13421	if (ChangeCase(tk[k]) != ChangeCase(tempStr[k]))
13422	numDiff++;
13423	if (numDiff == 0)
13424	{
13425	numStrMatches++;
13426	strcpy (validArg, tempStr);
13427	}
13428	}
13429	j = 0;
13430	}
13431	else
13432	tempStr[j++] = p->valueList[i];
13433	i++;
13434	}
13435	while (p->valueList[i] != '\0');
13436
13437	if (numStrMatches == 0)
13438	{
13439	MrBayesPrint ("%s No valid match for argument \"%s\"\n", spacer, tk);
13440	return (ERROR);
13441	}
13442	else if (numStrMatches == 1)
13443	{
13444	return (NO_ERROR);
13445	}
13446	else
13447	{
13448	MrBayesPrint ("%s Argument \"%s\" is ambiguous\n", spacer, tk);
13449	return (ERROR);
13450	}
13451
13452	}
13453
13454
13455
13456
13457
13458	int IsIn (char ch, char *s)
13459
13460	{
13461
13462	while (*s)
13463	{
13464	if (*s++ == ch)
13465	return 1;
13466	}
13467	return 0;
13468
13469	}
13470
13471
13472
13473
13474
13475	int IsMissing (int charCode, int dType)
13476
13477	{
13478
13479	if (dType == DNA \|\| dType == RNA)
13480	{
13481	if (charCode == 15 \|\| charCode == 16)
13482	return (YES);
13483	}
13484	else if (dType == STANDARD \|\| dType == PROTEIN)
13485	{
13486	if (charCode == MISSING \|\| charCode == GAP)
13487	return (YES);
13488	}
13489	else if (dType == RESTRICTION)
13490	{
13491	if (charCode == 3 \|\| charCode == 4)
13492	return (YES);
13493	}
13494	else if (dType == CONTINUOUS)
13495	{
13496
13497	}
13498	else
13499	{
13500	MrBayesPrint ("Unknown datatype in \"IsMissing\"\n", spacer);
13501	}
13502	return (NO);
13503
13504	}
13505
13506
13507
13508
13509
13510	int IsSame (char s1, char s2)
13511
13512	{
13513
13514	int i, nDiff, isIdentical, len;
13515
13516	isIdentical = YES;
13517	if (strlen(s1) != strlen(s2))
13518	isIdentical = NO; /* strings cannot be identical because they are different lengths */
13519
13520	/* now, we go through both strings, one character at a time, to see if
13521	any are different */
13522	if (strlen(s1) > strlen(s2))
13523	len = (int) strlen(s2);
13524	else
13525	len = (int) strlen(s1);
13526	i = nDiff = 0;
13527	while (i < len)
13528	{
13529	if (tolower(s1[i]) != tolower(s2[i]))
13530	nDiff++;
13531	i++;
13532	}
13533	if (nDiff == 0 && isIdentical == YES)
13534	return (SAME);
13535	else if (nDiff == 0 && isIdentical == NO)
13536	return (CONSISTENT_WITH);
13537	else
13538	return (DIFFERENT);
13539
13540	}
13541
13542
13543
13544
13545
13546	int IsWhite (char c)
13547
13548	{
13549
13550	if (c == ' ' \|\| c == '\t' \|\| c == '\n' \|\| c == '\r')
13551	{
13552	if (c == '\n' \|\| c == '\r')
13553	return 2;
13554	return 1;
13555	}
13556	return 0;
13557
13558	}
13559
13560
13561
13562
13563
13564	/* NBits: count bits in an int */
13565	int NBits (int x)
13566
13567	{
13568
13569	int n=0;
13570
13571	for (n=0; x != 0; n++)
13572	x &= (x-1);
13573
13574	return n;
13575
13576	}
13577
13578
13579
13580
13581
13582	int NucID (char nuc)
13583
13584	{
13585
13586	char n;
13587
13588	if (nuc == 'U' \|\| nuc == 'u')
13589	n = 'T';
13590	else
13591	n = nuc;
13592
13593	if (n == 'A' \|\| n == 'a')
13594	{
13595	return 1;
13596	}
13597	else if (n == 'C' \|\| n == 'c')
13598	{
13599	return 2;
13600	}
13601	else if (n == 'G' \|\| n == 'g')
13602	{
13603	return 4;
13604	}
13605	else if (n == 'T' \|\| n == 't')
13606	{
13607	return 8;
13608	}
13609	else if (n == 'R' \|\| n == 'r')
13610	{
13611	return 5;
13612	}
13613	else if (n == 'Y' \|\| n == 'y')
13614	{
13615	return 10;
13616	}
13617	else if (n == 'M' \|\| n == 'm')
13618	{
13619	return 3;
13620	}
13621	else if (n == 'K' \|\| n == 'k')
13622	{
13623	return 12;
13624	}
13625	else if (n == 'S' \|\| n == 's')
13626	{
13627	return 6;
13628	}
13629	else if (n == 'W' \|\| n == 'w')
13630	{
13631	return 9;
13632	}
13633	else if (n == 'H' \|\| n == 'h')
13634	{
13635	return 11;
13636	}
13637	else if (n == 'B' \|\| n == 'b')
13638	{
13639	return 14;
13640	}
13641	else if (n == 'V' \|\| n == 'v')
13642	{
13643	return 7;
13644	}
13645	else if (n == 'D' \|\| n == 'd')
13646	{
13647	return 13;
13648	}
13649	else if (n == 'N' \|\| n == 'n')
13650	{
13651	return 15;
13652	}
13653	else if (n == gapId)
13654	{
13655	return GAP;
13656	}
13657	else if (n == missingId)
13658	{
13659	return MISSING;
13660	}
13661	else
13662	return -1;
13663
13664	}
13665
13666
13667
13668
13669
13670	/*-------\| ParseCommand \|------------------------------------------------
13671	\|
13672	\| This function is used to parse a file. The expected format is:
13673	\|
13674	\| command parameter=value parameter=value ... ;
13675	\|
13676	\| For example, the following is a valid line for this parser:
13677	\|
13678	\| lset nst=2;
13679	\|
13680	\| In some cases, however, the format is:
13681	\|
13682	\| command stuff more stuff ... ;
13683	\|
13684	\| For example, when reading a data file, the matrix command might be:
13685	\|
13686	\| matrix
13687	\| taxon_1 data
13688	\| taxon_2 data
13689	\| taxon_3 data
13690	\| ;
13691	\|
13692	\| Like before, the command and all of the stuff for that command are
13693	\| terminated by a semicolon.
13694	\|
13695	*/
13696	int ParseCommand (char *s)
13697
13698	{
13699
13700	int rc, tokenType, inError, numMatches, skipCmd;
13701	char errStr[100];
13702
13703	cmdStr = s;
13704	tokenP = &s[0];
13705
13706	# if defined (ECHO_PROCESSED_COMMANDS)
13707	MrBayesPrint ("Currently processing command: %s\n", s);
13708	# endif
13709
13710	inError = skipCmd = NO;
13711	do
13712	{
13713	/* Get the next token. A token is a valid word in a line. Token type is defined in "globals.h". */
13714	if( GetToken (token, &tokenType, &tokenP))
13715	{
13716	inError = YES;
13717	break;
13718	}
13719	if (strlen(token) > 0 \|\| tokenType == ALPHA)
13720	{
13721	# if defined (SHOW_TOKENS)
13722	MrBayesPrint ("%s\n", token);
13723	# endif
13724	if (tokenType == LEFTCOMMENT)
13725	{
13726	/* If the token is a left comment "[", then we don't want to
13727	actually process commands until we find a right comment. */
13728	/* The exception is if readComment is set to YES, in which case
13729	we will leave it to the parser functions to decide on whether
13730	they want to read the comment or not */
13731	if (readComment == NO \|\| inComment == YES)
13732	{
13733	inComment = YES;
13734	numComments++;
13735	}
13736	}
13737	if (inComment == NO && inForeignBlock == NO)
13738	{
13739	if (tokenType != SEMICOLON)
13740	{
13741	/* If the token is not a semicolon, then we will be processing
13742	either a command or a parameter. */
13743	if (expecting == Expecting(COMMAND))
13744	{
13745	/* We are expecting to find a command (defined above in "commands[]"). Find the
13746	correct command and set a pointer to that command. */
13747	commandPtr = NULL;
13748	if (FindValidCommand (token, &numMatches) == ERROR)
13749	{
13750	/* We couldn't find the command or the user did not specify enough letters
13751	to unambiguously determine the command. The command pointer (commandPtr)
13752	is NULL. */
13753	if (numMatches == 0)
13754	MrBayesPrint ("%s Could not find command \"%s\"\n", spacer, token);
13755	else
13756	MrBayesPrint ("%s Ambiguous command \"%s\"\n", spacer, token);
13757	inError = YES;
13758	}
13759	else
13760	{
13761	/* We did find a valid command. Set what we are expecting to see next. */
13762	expecting = commandPtr->expect;
13763
13764	/* Check to see if we have one of the so-called special cases in which a
13765	command is not necessarily followed by a parameter (e.g., matrix). If we
13766	do have a special case, then we want to set the parameter pointer (paramPtr)
13767	appropriately. In this case, simply go to the first parameter in the parmList. */
13768	if (commandPtr->specialCmd == YES)
13769	{
13770	isFirstMatrixRead = YES;
13771	foundFirst = NO;
13772	paramPtr = paramTable + commandPtr->parmList[0];
13773	}
13774	if (strcmp(commandPtr->string, "Execute")==0)
13775	{
13776	/* set the tokenizer to recognize quoted strings */
13777	readWord = YES;
13778	}
13779	}
13780	}
13781	else
13782	{
13783	/* We are expecting to find a parameter or a value for the parameter, not a command. */
13784	if ((expecting & Expecting(PARAMETER)) == Expecting(PARAMETER) &&
13785	(expecting & Expecting(tokenType)) != Expecting(tokenType))
13786	{
13787	/* Specifically, if we are here, we need to go through the parameter list,
13788	checking to see if the token is a valid parameter. */
13789	expecting = (expecting & Expecting(PARAMETER));
13790	if (FindValidParam (token, &numMatches) == ERROR)
13791	{
13792	/* The token is not a valid parameter. */
13793	if (numMatches == 0)
13794	MrBayesPrint ("%s Could not find parameter \"%s\"\n", spacer, token);
13795	else
13796	MrBayesPrint ("%s Ambiguous parameter \"%s\"\n", spacer, token);
13797	inError = YES;
13798	}
13799	else
13800	{
13801	/* The token is a valid parameter. Call the appropriate function ("DoXxxxParm"). */
13802	if ((paramPtr->fp)(paramPtr->string, token) == ERROR)
13803	{
13804	if (strcmp("Xxxxxxxxxx", paramPtr->string))
13805	MrBayesPrint ("%s Error when setting parameter \"%s\" (1)\n", spacer, paramPtr->string);
13806	inError = YES;
13807	}
13808	}
13809	}
13810	else
13811	{
13812	/* Otherwise, we are expecting a value for the parameter. Call the appropriate function ("DoXxxxParm"). */
13813	if ((expecting & Expecting(tokenType)) != 0)
13814	expecting = (expecting & Expecting(tokenType));
13815	if ((Expecting(tokenType) & expecting) == Expecting(tokenType))
13816	{
13817	if ((paramPtr->fp)(paramPtr->string, token) == ERROR)
13818	{
13819	if (strcmp("Xxxxxxxxxx", paramPtr->string))
13820	MrBayesPrint ("%s Error when setting parameter \"%s\" (2)\n", spacer, paramPtr->string);
13821	inError = YES;
13822	}
13823	}
13824	else
13825	{
13826	inError = YES;
13827	WhatVariableExp (expecting, errStr);
13828	MrBayesPrint ("%s Expecting '%s'\n", spacer, errStr+1); /* there will be an initial space in errStr so print from pos 1 */
13829	if (numOpenExeFiles > 0)
13830	MrBayesPrint ("%s Instead found '%s' in command '%s'\n",
13831	spacer, token, commandPtr->string);
13832	else
13833	MrBayesPrint ("%s Instead found '%s' in command '%s' at position %d\n",
13834	spacer, token, commandPtr->string, tokenP - cmdStr - strlen(token)+1);
13835	}
13836	}
13837	}
13838	}
13839	else
13840	{
13841	/* The token is a semicolon. This means that we are at the end of processing one command. We
13842	need to clean things up. We do this by calling the finishing function ("DoXxxx"). */
13843	if ((Expecting(SEMICOLON) & expecting) == Expecting(SEMICOLON))
13844	{
13845	if (commandPtr->cmdFxnPtr != NULL)
13846	{
13847	/* Finish up the command here. */
13848	rc = (commandPtr->cmdFxnPtr) ();
13849	if (rc == ERROR \|\| rc == ABORT)
13850	{
13851	if (rc == ABORT)
13852	{
13853	MrBayesPrint (" Mcmc run aborted\n");
13854	}
13855	else if (rc == SKIP_COMMAND)
13856	{
13857	MrBayesPrint (" Cancelled execution of command\n");
13858	skipCmd = YES;
13859	}
13860	else
13861	{
13862	MrBayesPrint ("%s Error in command \"%s\"\n", spacer, commandPtr->string);
13863	inError = YES;
13864	}
13865	}
13866	}
13867	/* if the user typed "quit", then we want to bail out of this loop, with a NO_ERROR_QUIT */
13868	if (!strcmp(commandPtr->string, "Quit"))
13869	return (NO_ERROR_QUIT);
13870	expecting = Expecting(COMMAND);
13871	}
13872	else
13873	{
13874	inError = YES;
13875	WhatVariableExp (expecting, errStr);
13876	MrBayesPrint ("%s Expecting %s\n", spacer, errStr);
13877	}
13878	}
13879	}
13880	/* Check to see if a comment is terminated. A comment can either be a right comment "]" or, if we were in a foreign nexus block
13881	(e.g., a "paup" block) the terminating comment will be "end". */
13882	if (tokenType == RIGHTCOMMENT)
13883	{
13884	if (inComment == NO && readComment == NO)
13885	{
13886	MrBayesPrint ("%s Found \"]\", without having previously found \"[\"\n", spacer);
13887	inError = YES;
13888	}
13889	else if (inComment == NO && readComment == YES)
13890	{
13891	/* This is OK, we just pass through and rely on the command to handle the RIGHTCOMMENT */
13892	}
13893	else
13894	{
13895	numComments--;
13896	if (numComments == 0)
13897	inComment = NO;
13898	}
13899	}
13900	if ((IsSame(token, "end") == SAME \|\| IsSame(token, "endblock") == SAME) && inForeignBlock == YES)
13901	{
13902	strcpy (spacer, "");
13903	inForeignBlock = NO;
13904	}
13905	}
13906
13907	} while ((*token \|\| tokenType == ALPHA) && inError == NO && skipCmd == NO);
13908
13909	if (inError == YES)
13910	{
13911	readComment = NO; /* reset this in case it is set to YES in command and we get an error exit */
13912	return (ERROR);
13913	}
13914	else
13915	return (NO_ERROR);
13916
13917	}
13918
13919
13920
13921
13922
13923	void PrintSettings (char command, ModelInfo mp)
13924
13925	{
13926	char yesNoStr[20];
13927
13928	if (!strcmp(command,"Mcmc"))
13929	{
13930	MrBayesPrint (" Parameter Options Current Setting \n");
13931	MrBayesPrint (" ----------------------------------------------------- \n");
13932	MrBayesPrint (" Ngen <number> %d \n", chainParams.numGen);
13933	MrBayesPrint (" Nruns <number> %d \n", chainParams.numRuns);
13934	MrBayesPrint (" Nchains <number> %d \n", chainParams.numChains);
13935	MrBayesPrint (" Temp <number> %lf \n", chainParams.chainTemp);
13936	MrBayesPrint (" Reweight <number>,<number> %1.2lf v %1.2lf ^ \n", chainParams.weightScheme[0], chainParams.weightScheme[1]);
13937	MrBayesPrint (" Swapfreq <number> %d \n", chainParams.swapFreq);
13938	MrBayesPrint (" Nswaps <number> %d \n", chainParams.numSwaps);
13939	MrBayesPrint (" Samplefreq <number> %d \n", chainParams.sampleFreq);
13940	MrBayesPrint (" Printfreq <number> %d \n", chainParams.printFreq);
13941	PrintYesNo (chainParams.printAll, yesNoStr);
13942	MrBayesPrint (" Printall Yes/No %s \n", yesNoStr);
13943	MrBayesPrint (" Printmax <number> %d \n", chainParams.printMax);
13944	PrintYesNo (chainParams.mcmcDiagn, yesNoStr);
13945	MrBayesPrint (" Mcmcdiagn Yes/No %s \n", yesNoStr);
13946	MrBayesPrint (" Diagnfreq <number> %d \n", chainParams.diagnFreq);
13947	if (chainParams.diagnStat == AVGSTDDEV)
13948	strcpy (yesNoStr, "Avgstddev");
13949	else
13950	strcpy (yesNoStr, "Maxstddev");
13951	MrBayesPrint (" Diagnstat Avgstddev/Maxstddev %s \n", yesNoStr);
13952	MrBayesPrint (" Minpartfreq <number> %1.2lf \n", chainParams.minPartFreq);
13953	PrintYesNo (chainParams.allChains, yesNoStr);
13954	MrBayesPrint (" Allchains Yes/No %s \n", yesNoStr);
13955	PrintYesNo (chainParams.allComps, yesNoStr);
13956	MrBayesPrint (" Allcomps Yes/No %s \n", yesNoStr);
13957	PrintYesNo (chainParams.relativeBurnin, yesNoStr);
13958	MrBayesPrint (" Relburnin Yes/No %s \n", yesNoStr);
13959	MrBayesPrint (" Burnin <number> %d \n", chainParams.chainBurnIn);
13960	MrBayesPrint (" Burninfrac <number> %1.2lf \n", chainParams.burninFraction);
13961	PrintYesNo (chainParams.stopRule, yesNoStr);
13962	MrBayesPrint (" Stoprule Yes/No %s \n", yesNoStr);
13963	MrBayesPrint (" Stopval <number> %1.2lf \n", chainParams.stopVal);
13964	PrintYesNo (chainParams.saveTrees, yesNoStr);
13965	MrBayesPrint (" Savetrees Yes/No %s \n", yesNoStr);
13966	PrintYesNo (chainParams.checkPoint, yesNoStr);
13967	MrBayesPrint (" Checkpoint Yes/No %s \n", yesNoStr);
13968	MrBayesPrint (" Checkfreq <number> %d \n", chainParams.checkFreq);
13969	MrBayesPrint (" Filename <name> %s.<p/t>\n", chainParams.chainFileName);
13970	MrBayesPrint (" Startparams Current/Reset %s \n", chainParams.startParams);
13971	MrBayesPrint (" Starttree Current/Random/ %s \n", chainParams.startTree);
13972	MrBayesPrint (" Parsimony \n");
13973	MrBayesPrint (" Nperts <number> %d \n", chainParams.numStartPerts);
13974	PrintYesNo (chainParams.runWithData, yesNoStr);
13975	MrBayesPrint (" Data Yes/No %s \n", yesNoStr);
13976	MrBayesPrint (" Ordertaxa Yes/No %s \n", chainParams.orderTaxa == YES? "Yes" : "No");
13977	MrBayesPrint (" Append Yes/No %s \n", chainParams.append == YES? "Yes" : "No");
13978	MrBayesPrint (" Autotune Yes/No %s \n", chainParams.autotune == YES? "Yes" : "No");
13979	MrBayesPrint (" Tunefreq <number> %d \n", chainParams.tuneFreq);
13980	MrBayesPrint (" \n");
13981	}
13982	}
13983
13984
13985
13986
13987	void PrintYesNo (int yn, char s[4])
13988
13989	{
13990
13991	if (yn == YES)
13992	strcpy (s, "Yes");
13993	else
13994	strcpy (s, "No");
13995
13996	}
13997
13998
13999
14000
14001
14002	int ProtID (char aa)
14003
14004	{
14005
14006
14007	if (aa == 'A' \|\| aa == 'a') /* Ala */
14008	{
14009	return 1;
14010	}
14011	else if (aa == 'R' \|\| aa == 'r') /* Arg */
14012	{
14013	return 2;
14014	}
14015	else if (aa == 'N' \|\| aa == 'n') /* Asn */
14016	{
14017	return 4;
14018	}
14019	else if (aa == 'D' \|\| aa == 'd') /* Asp */
14020	{
14021	return 8;
14022	}
14023	else if (aa == 'C' \|\| aa == 'c') /* Cys */
14024	{
14025	return 16;
14026	}
14027	else if (aa == 'Q' \|\| aa == 'q') /* Gln */
14028	{
14029	return 32;
14030	}
14031	else if (aa == 'E' \|\| aa == 'e') /* Glu */
14032	{
14033	return 64;
14034	}
14035	else if (aa == 'G' \|\| aa == 'g') /* Gly */
14036	{
14037	return 128;
14038	}
14039	else if (aa == 'H' \|\| aa == 'h') /* His */
14040	{
14041	return 256;
14042	}
14043	else if (aa == 'I' \|\| aa == 'i') /* Ile */
14044	{
14045	return 512;
14046	}
14047	else if (aa == 'L' \|\| aa == 'l') /* Leu */
14048	{
14049	return 1024;
14050	}
14051	else if (aa == 'K' \|\| aa == 'k') /* Lys */
14052	{
14053	return 2048;
14054	}
14055	else if (aa == 'M' \|\| aa == 'm') /* Met */
14056	{
14057	return 4096;
14058	}
14059	else if (aa == 'F' \|\| aa == 'f') /* Phe */
14060	{
14061	return 8192;
14062	}
14063	else if (aa == 'P' \|\| aa == 'p') /* Pro */
14064	{
14065	return 16384;
14066	}
14067	else if (aa == 'S' \|\| aa == 's') /* Ser */
14068	{
14069	return 32768;
14070	}
14071	else if (aa == 'T' \|\| aa == 't') /* Thr */
14072	{
14073	return 65536;
14074	}
14075	else if (aa == 'W' \|\| aa == 'w') /* Trp */
14076	{
14077	return 131072;
14078	}
14079	else if (aa == 'Y' \|\| aa == 'y') /* Tyr */
14080	{
14081	return 262144;
14082	}
14083	else if (aa == 'V' \|\| aa == 'v') /* Val */
14084	{
14085	return 524288;
14086	}
14087	else if (aa == 'X' \|\| aa == 'x') /* Nonidentified */
14088	{
14089	return MISSING;
14090	}
14091	else if (aa == gapId)
14092	{
14093	return GAP;
14094	}
14095	else if (aa == missingId)
14096	{
14097	return MISSING;
14098	}
14099	else
14100	return -1;
14101
14102	}
14103
14104
14105
14106
14107
14108	int RemoveLastFromString (char *s1)
14109
14110	{
14111
14112	int i, j, numPrev, numRemoved;
14113
14114	/* We remove the last name from the string simply by deleting the last "\|". */
14115
14116	i = numPrev = 0;
14117	while (s1[i] != '\0')
14118	{
14119	if (s1[i] == '\|')
14120	numPrev++;
14121	i++;
14122	}
14123
14124	i = j = numRemoved = 0;
14125	while (s1[i] != '\0')
14126	{
14127	if (s1[i] == '\|')
14128	j++;
14129	if (numPrev == j)
14130	{
14131	s1[i] = ' ';
14132	numRemoved++;
14133	break;
14134	}
14135	i++;
14136	}
14137
14138	if (numRemoved != 1)
14139	{
14140	MrBayesPrint ("%s Could not find name to remove\n", spacer);
14141	return (ERROR);
14142	}
14143
14144	return (NO_ERROR);
14145
14146	}
14147
14148
14149
14150
14151
14152	int MBResID (char nuc)
14153
14154	{
14155
14156	char n;
14157
14158	n = nuc;
14159
14160	if (n == '0' \|\| n == 'a' \|\| n == 'A')
14161	{
14162	return 1;
14163	}
14164	else if (n == '1' \|\| n == 'b' \|\| n == 'B')
14165	{
14166	return 2;
14167	}
14168	else if (n == gapId)
14169	{
14170	return GAP;
14171	}
14172	else if (n == missingId)
14173	{
14174	return MISSING;
14175	}
14176	else
14177	return -1;
14178
14179	}
14180
14181
14182
14183
14184
14185	/* Reset character flags */
14186	void ResetCharacterFlags (void)
14187	{
14188	/* reset all characters flags */
14189	numChar = 0; /* number of defined characters */
14190	defChars = NO; /* flag for whether number of characters is known*/
14191	defMatrix = NO; /* flag for whether matrix is successfull read */
14192	matrixHasPoly = NO; /* flag for whether matrix has polymorphisms */
14193	isInAmbig = NO; /* flag for whether the parser is within () */
14194	isInPoly = NO; /* flag for whether the parser is within {} */
14195	defPartition = NO; /* flag for whether character partition is read */
14196	defPairs = NO; /* flag indicating whether pairs have been defnd */
14197	numDefinedPartitions = 0; /* number of defined partitions */
14198	partitionNum = 0; /* partition number currently enforced */
14199	numCurrentDivisions = 0; /* number of partitions of data */
14200	numCharSets = 0; /* holds number of character sets */
14201	numDivisions = 1; /* holds number of partitions */
14202	isMixed = NO; /* are data mixed ? */
14203	dataType = NONE; /* holds datatype */
14204	matchId = '\0'; /* no default for match character */
14205	gapId = '\0'; /* no default for gap character */
14206	missingId = '\0'; /* no default for missing characters */
14207	}
14208
14209
14210
14211
14212
14213	/* Reset taxa flags */
14214	void ResetTaxaFlags (void)
14215	{
14216	numTaxa = 0; /* number of taxa */
14217	numNamedTaxa = 0; /* number of named taxa */
14218	defTaxa = NO; /* flag for whether number of taxa is known */
14219	isTaxsetDef = NO; /* is a taxlabels set defined */
14220	numDefinedConstraints = 0; /* holds number of defined constraints */
14221	definedConstraint = NULL;
14222	definedConstraintTwo = NULL;
14223	definedConstraintPruned = NULL;
14224	definedConstraintTwoPruned = NULL;
14225	constraintNames = NULL;
14226	nodeCalibration = NULL;
14227	tempActiveConstraints = NULL; /* holds temp info on active constraints */
14228	outGroupNum = 0; /* default outgroup */
14229	numTaxaSets = 0; /* holds number of taxa sets */
14230	}
14231
14232
14233
14234
14235
14236	/* SetPartition: Set model partition */
14237	int SetPartition (int part)
14238
14239	{
14240	int i, j;
14241
14242	/* Free space for modelParams and modelSettings */
14243	if (memAllocs[ALLOC_MODEL] == YES)
14244	{
14245	for (i=0; i<numCurrentDivisions; i++)
14246	free (modelParams[i].activeConstraints);
14247	free (modelParams);
14248	free (modelSettings);
14249	modelParams = NULL;
14250	modelSettings = NULL;
14251	memAllocs[ALLOC_MODEL] = NO;
14252	}
14253
14254	/* Set model partition */
14255	partitionNum = part;
14256	numCurrentDivisions = 0;
14257
14258	/* Set numCurrentDivisions to maximum division a character belongs to in partition part */
14259	for (i=0; i<numChar; i++)
14260	{
14261	j = partitionId[i][part];
14262	if (j > numCurrentDivisions)
14263	numCurrentDivisions = j;
14264	}
14265
14266	/* Allocate space for partition models */
14267	modelParams = (Model *) SafeCalloc (numCurrentDivisions, sizeof (Model));
14268	modelSettings = (ModelInfo *) SafeCalloc (numCurrentDivisions, sizeof (ModelInfo));
14269	if (!modelParams \|\| !modelSettings)
14270	{
14271	MrBayesPrint ("%s Could not allocate modelParams or modelSettings\n", spacer);
14272	if (modelParams)
14273	free (modelParams);
14274	if (modelSettings)
14275	free (modelSettings);
14276	return (ERROR);
14277	}
14278	memAllocs[ALLOC_MODEL] = YES;
14279
14280	numVars = (int ) SafeRealloc ((void ) numVars, (size_t)(3 * numCurrentDivisions * sizeof(int)));
14281	tempLinkUnlinkVec = numVars + numCurrentDivisions;
14282	activeParts = numVars + 2*numCurrentDivisions;
14283
14284	tempNum = (MrBFlt ) SafeRealloc ((void ) tempNum, (size_t)(6 * sizeof(MrBFlt)));
14285
14286	activeParams[0] = (int ) SafeRealloc ((void ) (activeParams[0]), (size_t)(NUM_LINKED * numCurrentDivisions * sizeof(int)));
14287	for (i=1; i<NUM_LINKED; i++)
14288	activeParams[i] = activeParams[0] + i*numCurrentDivisions;
14289
14290	linkTable[0] = (int ) SafeRealloc ((void ) (linkTable[0]), (size_t)(3 * NUM_LINKED * numCurrentDivisions * sizeof(int)));
14291	tempLinkUnlink[0] = linkTable[0] + NUM_LINKED*numCurrentDivisions;
14292	for (i=1; i<NUM_LINKED; i++)
14293	{
14294	linkTable[i] = linkTable[0] + i*numCurrentDivisions;
14295	tempLinkUnlink[i] = tempLinkUnlink[0] + i*numCurrentDivisions;
14296	}
14297
14298	return (NO_ERROR);
14299	}
14300
14301
14302
14303
14304
14305	/* SetSpeciespartition: Set speciespartition */
14306	int SetSpeciespartition (int part)
14307
14308	{
14309	int i, j;
14310
14311	/* Set model partition */
14312	speciespartitionNum = part;
14313	numSpecies = 0;
14314
14315	/* Set numSpecies to maximum species a taxon belongs to in partition part */
14316	for (i=0; i<numTaxa; i++)
14317	{
14318	j = speciespartitionId[i][part];
14319	if (j > numSpecies)
14320	numSpecies = j;
14321	}
14322
14323	return (NO_ERROR);
14324	}
14325
14326
14327
14328
14329
14330	int SetTaxaFromTranslateTable (void)
14331	{
14332	int i;
14333
14334	if (numTaxa != 0)
14335	return ERROR;
14336
14337	for (i=0; i<numTranslates; i++)
14338	{
14339	if ( strlen(transFrom[i])>99 )
14340	{
14341	MrBayesPrint ("%s Taxon name %s is too long. Maximun 99 characters is allowed.\n", spacer, transFrom[i]);
14342	return (ERROR);
14343	}
14344	AddString(&taxaNames, numTaxa, transFrom[i]);
14345	numTaxa++;
14346	}
14347
14348	return NO_ERROR;
14349	}
14350
14351
14352
14353
14354
14355	void SetUpParms (void)
14356
14357	{
14358
14359	ParmInfoPtr p = paramTable;
14360
14361	PARAM ( 0, "NEXUS", DoNexusParm, "NEXUS\|\0");
14362	PARAM ( 1, "Data", DoBeginParm, "\0");
14363	PARAM ( 2, "Mrbayes", DoBeginParm, "\0");
14364	PARAM ( 3, "Trees", DoBeginParm, "\0");
14365	PARAM ( 4, "Ntax", DoDimensionsParm, "\0");
14366	PARAM ( 5, "Nchar", DoDimensionsParm, "\0");
14367	PARAM ( 6, "Interleave", DoFormatParm, "Yes\|No\|\0");
14368	PARAM ( 7, "Datatype", DoFormatParm, "Dna\|Rna\|Protein\|Restriction\|Standard\|Continuous\|Mixed\|\0");
14369	PARAM ( 8, "Gap", DoFormatParm, "\0");
14370	PARAM ( 9, "Missing", DoFormatParm, "\0");
14371	PARAM ( 10, "Matchchar", DoFormatParm, "\0");
14372	PARAM ( 11, "MatrixInfo", DoMatrixParm, "\0");
14373	PARAM ( 12, "Filename", DoExecuteParm, "\0");
14374	PARAM ( 13, "Autoclose", DoSetParm, "Yes\|No\|\0");
14375	PARAM ( 14, "Partition", DoSetParm, "\0");
14376	PARAM ( 15, "Xxxxxxxxxx", DoCharsetParm, "\0");
14377	PARAM ( 16, "Xxxxxxxxxx", DoPartitionParm, "\0");
14378	PARAM ( 17, "Seed", DoMcmcParm, "\0");
14379	PARAM ( 18, "Ngen", DoMcmcParm, "\0");
14380	PARAM ( 19, "Samplefreq", DoMcmcParm, "\0");
14381	PARAM ( 20, "Printfreq", DoMcmcParm, "\0");
14382	PARAM ( 21, "Nchains", DoMcmcParm, "\0");
14383	PARAM ( 22, "Temp", DoMcmcParm, "\0");
14384	PARAM ( 23, "Filename", DoMcmcParm, "\0");
14385	PARAM ( 24, "Burnin", DoMcmcParm, "\0");
14386	PARAM ( 25, "Starttree", DoMcmcParm, "Random\|Current\|User\|Parsimony\|NJ\|\0");
14387	PARAM ( 26, "Nperts", DoMcmcParm, "\0");
14388	PARAM ( 27, "Savebrlens", DoMcmcParm, "Yes\|No\|\0");
14389	PARAM ( 28, "Nucmodel", DoLsetParm, "4by4\|Doublet\|Codon\|Protein\|\0");
14390	PARAM ( 29, "Nst", DoLsetParm, "1\|2\|6\|Mixed\|\0");
14391	PARAM ( 30, "Aamodel", DoLsetParm, "Poisson\|Equalin\|Jones\|Dayhoff\|Mtrev\|Mtmam\|Wag\|Rtrev\|Cprev\|Vt\|Blosum\|Blossum\|\0");
14392	PARAM ( 31, "Parsmodel", DoLsetParm, "Yes\|No\|\0");
14393	PARAM ( 32, "Omegavar", DoLsetParm, "Equal\|Ny98\|M3\|M10\|\0");
14394	PARAM ( 33, "Code", DoLsetParm, "Universal\|Vertmt\|Mycoplasma\|Yeast\|Ciliates\|Metmt\|\0");
14395	PARAM ( 34, "Coding", DoLsetParm, "All\|Variable\|Noabsencesites\|Nopresencesites\|Informative\|\0");
14396	PARAM ( 35, "Seqerror", DoPrsetParm, "\0");
14397	PARAM ( 36, "Tratiopr", DoPrsetParm, "Beta\|Fixed\|\0");
14398	PARAM ( 37, "Revmatpr", DoPrsetParm, "Dirichlet\|Fixed\|\0");
14399	PARAM ( 38, "Omegapr", DoPrsetParm, "Uniform\|Exponential\|Fixed\|\0");
14400	PARAM ( 39, "Statefreqpr", DoPrsetParm, "Dirichlet\|Fixed\|\0");
14401	PARAM ( 40, "Ngammacat", DoLsetParm, "\0");
14402	PARAM ( 41, "Shapepr", DoPrsetParm, "Uniform\|Exponential\|Fixed\|\0");
14403	PARAM ( 42, "Ratecorrpr", DoPrsetParm, "Uniform\|Fixed\|\0");
14404	PARAM ( 43, "Pinvarpr", DoPrsetParm, "Uniform\|Fixed\|\0");
14405	PARAM ( 44, "Covswitchpr", DoPrsetParm, "Uniform\|Exponential\|Fixed\|\0");
14406	PARAM ( 45, "Xxxxxxxxxx", DoExcludeParm, "\0");
14407	PARAM ( 46, "Xxxxxxxxxx", DoIncludeParm, "\0");
14408	PARAM ( 47, "Xxxxxxxxxx", DoDeleteParm, "\0");
14409	PARAM ( 48, "Xxxxxxxxxx", DoRestoreParm, "\0");
14410	PARAM ( 49, "Xxxxxxxxxx", DoTaxasetParm, "\0");
14411	PARAM ( 50, "Xxxxxxxxxx", DoHelpParm, "\0");
14412	PARAM ( 51, "Applyto", DoLsetParm, "\0");
14413	PARAM ( 52, "Rates", DoLsetParm, "Equal\|Gamma\|Propinv\|Invgamma\|Adgamma\|\0");
14414	PARAM ( 53, "Covarion", DoLsetParm, "Yes\|No\|\0");
14415	PARAM ( 54, "Applyto", DoPrsetParm, "\0");
14416	PARAM ( 55, "Tratio", DoLinkParm, "\0");
14417	PARAM ( 56, "Revmat", DoLinkParm, "\0");
14418	PARAM ( 57, "Omega", DoLinkParm, "\0");
14419	PARAM ( 58, "Statefreq", DoLinkParm, "\0");
14420	PARAM ( 59, "Shape", DoLinkParm, "\0");
14421	PARAM ( 60, "Pinvar", DoLinkParm, "\0");
14422	PARAM ( 61, "Correlation", DoLinkParm, "\0");
14423	PARAM ( 62, "Ratemultiplier", DoLinkParm, "\0");
14424	PARAM ( 63, "Switchrates", DoLinkParm, "\0");
14425	PARAM ( 64, "Symdirihyperpr", DoPrsetParm, "Uniform\|Exponential\|Fixed\|\0");
14426	PARAM ( 65, "Xxxxxxxxxx", DoCtypeParm, "\0");
14427	PARAM ( 66, "Xxxxxxxxxx", DoConstraintParm, "\0");
14428	PARAM ( 67, "Topologypr", DoPrsetParm, "Uniform\|Constraints\|Fixed\|Speciestree\|\0");
14429	PARAM ( 68, "Brlenspr", DoPrsetParm, "Unconstrained\|Clock\|Relaxedclock\|Fixed\|\0");
14430	PARAM ( 69, "Speciationpr", DoPrsetParm, "Uniform\|Exponential\|Fixed\|\0");
14431	PARAM ( 70, "Extinctionpr", DoPrsetParm, "Beta\|Fixed\|\0");
14432	PARAM ( 71, "Popsizepr", DoPrsetParm, "Lognormal\|Uniform\|Gamma\|Normal\|Fixed\|\0");
14433	PARAM ( 72, "Topology", DoLinkParm, "\0");
14434	PARAM ( 73, "Brlens", DoLinkParm, "\0");
14435	PARAM ( 74, "Speciationrate", DoLinkParm, "\0");
14436	PARAM ( 75, "Extinctionrate", DoLinkParm, "\0");
14437	PARAM ( 76, "Theta", DoLinkParm, "\0");
14438	PARAM ( 77, "Ratepr", DoPrsetParm, "Variable\|Dirichlet\|Fixed\|\0");
14439	PARAM ( 78, "Xxxxxxxxxx", DoOutgroupParm, "\0");
14440	PARAM ( 79, "Xxxxxxxxxx", DoTreeParm, "\0");
14441	PARAM ( 80, "Filename", DoSumtParm, "\0");
14442	PARAM ( 81, "Burnin", DoSumtParm, "\0");
14443	PARAM ( 82, "Contype", DoSumtParm, "Halfcompat\|Allcompat\|\0");
14444	PARAM ( 83, "Xxxxxxxxxx", DoTranslateParm, "\0");
14445	PARAM ( 84, "Swapfreq", DoMcmcParm, "\0");
14446	PARAM ( 85, "Start", DoLogParm, "\0");
14447	PARAM ( 86, "Stop", DoLogParm, "\0");
14448	PARAM ( 87, "Filename", DoLogParm, "\0");
14449	PARAM ( 88, "Append", DoLogParm, "\0");
14450	PARAM ( 89, "Replace", DoLogParm, "\0");
14451	PARAM ( 90, "Nbetacat", DoLsetParm, "\0");
14452	PARAM ( 91, "Augment", DoLsetParm, "Yes\|No\|\0");
14453	PARAM ( 92, "Xxxxxxxxxx", DoPairsParm, "\0");
14454	PARAM ( 93, "Xxxxxxxxxx", DoBreaksParm, "\0");
14455	PARAM ( 94, "Nowarnings", DoSetParm, "Yes\|No\|\0");
14456	PARAM ( 95, "Showtreeprobs", DoSumtParm, "Yes\|No\|\0");
14457	PARAM ( 96, "Filename", DoSumpParm, "\0");
14458	PARAM ( 97, "Burnin", DoSumpParm, "\0");
14459	PARAM ( 98, "Reweight", DoMcmcParm, "\0");
14460	PARAM ( 99, "Noop", DoMcmcParm, "\0");
14461	PARAM (100, "Ny98omega1pr", DoPrsetParm, "Beta\|Fixed\|\0");
14462	PARAM (101, "Ny98omega3pr", DoPrsetParm, "Uniform\|Exponential\|Fixed\|\0");
14463	PARAM (102, "Codoncatfreqs", DoPrsetParm, "Dirichlet\|Fixed\|\0");
14464	PARAM (103, "Sampleprob", DoPrsetParm, "\0");
14465	PARAM (104, "Aamodelpr", DoPrsetParm, "Fixed\|Mixed\|\0");
14466	PARAM (105, "Aamodel", DoLinkParm, "\0");
14467	PARAM (106, "Filename", DoPlotParm, "\0");
14468	PARAM (107, "Parameter", DoPlotParm, "\0");
14469	PARAM (108, "Match", DoPlotParm, "Perfect\|Consistentwith\|All\|\0");
14470	PARAM (109, "Burnin", DoPlotParm, "\0");
14471	PARAM (110, "Brownscalepr", DoPrsetParm, "Uniform\|Gamma\|Gammamean\|Fixed\|\0");
14472	PARAM (111, "Browncorrpr", DoPrsetParm, "Uniform\|Fixed\|\0");
14473	PARAM (112, "Pbf", DoMcmcParm, "Yes\|No\|\0");
14474	PARAM (113, "Pbfinitburnin", DoMcmcParm, "\0");
14475	PARAM (114, "Pbfsamplefreq", DoMcmcParm, "\0");
14476	PARAM (115, "Pbfsampletime", DoMcmcParm, "\0");
14477	PARAM (116, "Pbfsampleburnin",DoMcmcParm, "\0");
14478	PARAM (117, "Growthpr", DoPrsetParm, "Uniform\|Exponential\|Fixed\|Normal\|\0");
14479	PARAM (118, "Growthrate", DoLinkParm, "\0");
14480	PARAM (119, "Xxxxxxxxxx", DoCalibrateParm, "Uniform\|Offsetexponential\|Fixed\|Unconstrained\|\0");
14481	PARAM (120, "Calwaitpr", DoPrsetParm, "Exponential\|Fixed\|\0"); /* not used but leave it in to not destroy mapping to commands */
14482	PARAM (121, "M3omegapr", DoPrsetParm, "Exponential\|Fixed\|\0");
14483	PARAM (122, "Applyto", DoReportParm, "\0");
14484	PARAM (123, "Tratio", DoReportParm, "Dirichlet\|Ratio\|\0");
14485	PARAM (124, "Revmat", DoReportParm, "Dirichlet\|Ratio\|\0");
14486	PARAM (125, "Ratemult", DoReportParm, "Dirichlet\|Scaled\|Ratio\|\0");
14487	PARAM (126, "Filename", DoManualParm, "\0");
14488	PARAM (127, "Filename1", DoCompareTreeParm, "\0");
14489	PARAM (128, "Filename2", DoCompareTreeParm, "\0");
14490	PARAM (129, "Outputname", DoCompareTreeParm, "\0");
14491	PARAM (130, "Burnin", DoCompareTreeParm, "\0");
14492	PARAM (131, "Ploidy", DoLsetParm, "Haploid\|Diploid\|Zlinked\|\0");
14493	PARAM (132, "Swapadjacent", DoMcmcParm, "Yes\|No\|\0");
14494	PARAM (133, "Treeagepr", DoPrsetParm, "Gamma\|Exponential\|Fixed\|\0");
14495	PARAM (134, "Ancstates", DoReportParm, "Yes\|No\|\0");
14496	PARAM (135, "Siterates", DoReportParm, "Yes\|No\|\0");
14497	PARAM (136, "Possel", DoReportParm, "Yes\|No\|\0");
14498	PARAM (137, "Plot", DoSumpParm, "Yes\|No\|\0");
14499	PARAM (138, "Table", DoSumpParm, "Yes\|No\|\0");
14500	PARAM (139, "Minprob", DoSumpParm, "\0");
14501	PARAM (140, "Printtofile", DoSumpParm, "Yes\|No\|\0");
14502	PARAM (141, "Outputname", DoSumpParm, "\0");
14503	PARAM (142, "Redirect", DoMcmcParm, "Yes\|No\|\0");
14504	PARAM (143, "Swapseed", DoMcmcParm, "\0");
14505	PARAM (144, "Runidseed", DoMcmcParm, "\0");
14506	PARAM (145, "Quitonerror", DoSetParm, "Yes\|No\|\0");
14507	PARAM (146, "Printbrlens", DoSumtParm, "Yes\|No\|\0");
14508	PARAM (147, "Brlensgeq", DoSumtParm, "\0");
14509	PARAM (148, "Minpartfreq", DoMcmcParm, "\0");
14510	PARAM (149, "Allchains", DoMcmcParm, "Yes\|No\|\0");
14511	PARAM (150, "Mcmcdiagn", DoMcmcParm, "Yes\|No\|\0");
14512	PARAM (151, "Diagnfreq", DoMcmcParm, "\0");
14513	PARAM (152, "Nruns", DoMcmcParm, "\0");
14514	PARAM (153, "Stoprule", DoMcmcParm, "Yes\|No\|\0");
14515	PARAM (154, "Stopval", DoMcmcParm, "\0");
14516	PARAM (155, "Relburnin", DoMcmcParm, "Yes\|No\|\0");
14517	PARAM (156, "Burninfrac", DoMcmcParm, "\0");
14518	PARAM (157, "Allcomps", DoMcmcParm, "Yes\|No\|\0");
14519	PARAM (158, "Printall", DoMcmcParm, "Yes\|No\|\0");
14520	PARAM (159, "Printmax", DoMcmcParm, "\0");
14521	PARAM (160, "Data", DoMcmcParm, "Yes\|No\|\0");
14522	PARAM (161, "Nruns", DoSumpParm, "\0");
14523	PARAM (162, "Allruns", DoSumpParm, "Yes\|No\|\0");
14524	PARAM (163, "Nruns", DoSumtParm, "\0");
14525	PARAM (164, "Ntrees", DoSumtParm, "\0");
14526	PARAM (165, "Calctreeprobs", DoSumtParm, "Yes\|No\|\0");
14527	PARAM (166, "Ordertaxa", DoMcmcParm, "Yes\|No\|\0");
14528	PARAM (167, "Ordertaxa", DoSumtParm, "Yes\|No\|\0");
14529	PARAM (168, "Aarevmatpr", DoPrsetParm, "Dirichlet\|Fixed\|\0");
14530	PARAM (169, "Nswaps", DoMcmcParm, "\0");
14531	PARAM (170, "Autoreplace", DoSetParm, "Yes\|No\|\0");
14532	PARAM (171, "Npthreads", DoSetParm, "\0");
14533	PARAM (172, "Cppratepr", DoPrsetParm, "Fixed\|Exponential\|\0");
14534	PARAM (173, "Cppmultdevpr", DoPrsetParm, "Fixed\|\0");
14535	PARAM (174, "TK02varpr", DoPrsetParm, "Fixed\|Exponential\|Uniform\|\0");
14536	PARAM (175, "Pfile", DoSumtParm, "\0");
14537	PARAM (176, "Pfile", DoSumtParm, "\0");
14538	PARAM (177, "Autocomplete", DoSumtParm, "Yes\|No\|\0");
14539	PARAM (178, "Autocomplete", DoSumpParm, "Yes\|No\|\0");
14540	PARAM (179, "Userlevel", DoSetParm, "Standard\|Developer\|\0");
14541	PARAM (180, "Allavailable", DoShowmovesParm, "Yes\|No\|\0");
14542	PARAM (181, "Seed", DoSetParm, "\0");
14543	PARAM (182, "Swapseed", DoSetParm, "\0");
14544	PARAM (183, "Clockratepr", DoPrsetParm, "Fixed\|Normal\|Lognormal\|Exponential\|Gamma\|\0");
14545	PARAM (184, "Nodeagepr", DoPrsetParm, "Unconstrained\|Calibrated\|\0");
14546	PARAM (185, "Clockvarpr", DoPrsetParm, "Strict\|Cpp\|TK02\|Igr\|Bm\|Ibr\|\0");
14547	PARAM (186, "Xxxxxxxxxx", DoPropsetParm, "\0");
14548	PARAM (187, "Xxxxxxxxxx", DoStartvalsParm, "\0");
14549	PARAM (188, "Usegibbs", DoLsetParm, "Yes\|No\|\0");
14550	PARAM (189, "Gibbsfreq", DoLsetParm, "\0");
14551	PARAM (190, "Checkpoint", DoMcmcParm, "Yes\|No\|\0");
14552	PARAM (191, "Checkfreq", DoMcmcParm, "\0");
14553	PARAM (192, "Tree", DoReportParm, "Topology\|Brlens\|\0");
14554	PARAM (193, "Cpprate", DoLinkParm, "\0");
14555	PARAM (194, "Cppmultdev", DoLinkParm, "\0");
14556	PARAM (195, "Cppevents", DoLinkParm, "\0");
14557	PARAM (196, "TK02var", DoLinkParm, "\0");
14558	PARAM (197, "TK02branchrates",DoLinkParm, "\0");
14559	PARAM (198, "Savetrees", DoMcmcParm, "Yes\|No\|\0");
14560	PARAM (199, "Diagnstat", DoMcmcParm, "Avgstddev\|Maxstddev\|\0");
14561	PARAM (200, "Startparams", DoMcmcParm, "Reset\|Current\|\0");
14562	PARAM (201, "Characters", DoBeginParm, "\0");
14563	PARAM (202, "Startingtrees", DoMcmcParm, "\0");
14564	PARAM (203, "Xxxxxxxxxx", DoUserTreeParm, "\0");
14565	PARAM (204, "Outputname", DoSumtParm, "\0");
14566	PARAM (205, "Table", DoSumtParm, "Yes\|No\|\0");
14567	PARAM (206, "Summary", DoSumtParm, "Yes\|No\|\0");
14568	PARAM (207, "Consensus", DoSumtParm, "Yes\|No\|\0");
14569	PARAM (208, "Minpartfreq", DoSumtParm, "\0");
14570	PARAM (209, "Relburnin", DoSumtParm, "Yes\|No\|\0");
14571	PARAM (210, "Burninfrac", DoSumtParm, "\0");
14572	PARAM (211, "Relburnin", DoSumpParm, "Yes\|No\|\0");
14573	PARAM (212, "Burninfrac", DoSumpParm, "\0");
14574	PARAM (213, "Append", DoMcmcParm, "Yes\|No\|\0");
14575	PARAM (214, "Autotune", DoMcmcParm, "Yes\|No\|\0");
14576	PARAM (215, "Tunefreq", DoMcmcParm, "\0");
14577	PARAM (216, "Scientific", DoSetParm, "Yes\|No\|\0");
14578	PARAM (217, "Siteomega", DoReportParm, "Yes\|No\|\0");
14579	PARAM (218, "Igrvarpr", DoPrsetParm, "Fixed\|Exponential\|Uniform\|\0");
14580	PARAM (219, "Symbols", DoFormatParm, "\0");
14581	PARAM (220, "Equate", DoFormatParm, "\0");
14582	PARAM (221, "Relburnin", DoCompareTreeParm, "Yes\|No\|\0");
14583	PARAM (222, "Burninfrac", DoCompareTreeParm, "\0");
14584	PARAM (223, "Minpartfreq", DoCompareTreeParm, "\0");
14585	PARAM (224, "Relburnin", DoPlotParm, "Yes\|No\|\0");
14586	PARAM (225, "Burninfrac", DoPlotParm, "\0");
14587	PARAM (226, "Taxa", DoBeginParm, "\0");
14588	PARAM (227, "Xxxxxxxxxx", DoBeginParm, "\0");
14589	PARAM (228, "Xxxxxxxxxx", DoTaxlabelsParm, "\0");
14590	PARAM (229, "Dir", DoSetParm, "\0");
14591	PARAM (230, "Conformat", DoSumtParm, "Figtree\|Simple\|\0");
14592	PARAM (231, "Hpd", DoSumpParm, "Yes\|No\|\0");
14593	PARAM (232, "Hpd", DoSumtParm, "Yes\|No\|\0");
14594	PARAM (233, "Usebeagle", DoSetParm, "Yes\|No\|\0");
14595	PARAM (234, "Beagledevice", DoSetParm, "Cpu\|Gpu\|\0");
14596	PARAM (235, "Beagleprecision",DoSetParm, "Single\|Double\|\0");
14597	PARAM (236, "Beaglesse", DoSetParm, "Yes\|No\|\0");
14598	PARAM (237, "Beagleopenmp", DoSetParm, "Yes\|No\|\0");
14599	PARAM (238, "Beaglethreads", DoSetParm, "Yes\|No\|\0");
14600	PARAM (239, "Beaglescaling", DoSetParm, "Always\|Dynamic\|\0");
14601	PARAM (240, "Beaglefreq", DoSetParm, "\0");
14602	PARAM (241, "Popvarpr", DoPrsetParm, "Equal\|Variable\|\0");
14603	PARAM (242, "Igrvar", DoLinkParm, "\0");
14604	PARAM (243, "Igrbranchlens", DoLinkParm, "\0");
14605	PARAM (244, "Xxxxxxxxxx", DoSpeciespartitionParm, "\0");
14606	PARAM (245, "Speciespartition",DoSetParm, "\0");
14607	PARAM (246, "Revratepr", DoPrsetParm, "Symdir\|\0");
14608	PARAM (247, "Samplestrat", DoPrsetParm, "Random\|Diversity\|Cluster\|\0");
14609	PARAM (248, "Burninss", DoSsParm, "\0");
14610	PARAM (249, "Nsteps", DoSsParm, "\0");
14611	PARAM (250, "Alpha", DoSsParm, "\0");
14612	PARAM (251, "Bmvarpr", DoPrsetParm, "Fixed\|Exponential\|Uniform\|\0");
14613	PARAM (252, "Bmvar", DoLinkParm, "\0");
14614	PARAM (253, "Bmbranchrates", DoLinkParm, "\0");
14615	PARAM (254, "Ibrvarpr", DoPrsetParm, "Fixed\|Exponential\|Uniform\|\0");
14616	PARAM (255, "Ibrvar", DoLinkParm, "\0");
14617	PARAM (256, "Ibrbranchlens", DoLinkParm, "\0");
14618	PARAM (257, "FromPrior", DoSsParm, "Yes\|No\|\0");
14619	PARAM (258, "Filename", DoSumSsParm, "\0");
14620	PARAM (259, "Burnin", DoSumSsParm, "\0");
14621	PARAM (260, "Nruns", DoSumSsParm, "\0");
14622	PARAM (261, "Allruns", DoSumSsParm, "Yes\|No\|\0");
14623	PARAM (262, "Askmore", DoSumSsParm, "Yes\|No\|\0");
14624	PARAM (263, "Relburnin", DoSumSsParm, "Yes\|No\|\0");
14625	PARAM (264, "Burninfrac", DoSumSsParm, "\0");
14626	PARAM (265, "Discardfrac", DoSumSsParm, "\0");
14627	PARAM (266, "Smoothing", DoSumSsParm, "\0");
14628	PARAM (267, "Steptoplot", DoSumSsParm, "\0");
14629	PARAM (268, "Precision", DoSetParm, "\0");
14630
14631
14632	/* NOTE: If a change is made to the parameter table, make certain you
14633	change the number of elements (now 269) in paramTable[] at the top of this file. */
14634
14635	}
14636
14637
14638
14639
14640
14641	void ShowNodes (TreeNode *p, int indent, int isThisTreeRooted)
14642
14643	{
14644
14645	if (p != NULL)
14646	{
14647	printf (" ");
14648	if (p->left == NULL && p->right == NULL && p->anc != NULL)
14649	{
14650	printf("%*cN %d (l=%d r=%d a=%d) %1.15lf (%s) scalerNode=%d isDated=%d ",
14651	indent, ' ', Dex(p), Dex(p->left), Dex(p->right), Dex(p->anc), p->length, p->label, p->scalerNode, p->isDated);
14652	}
14653	else if (p->left != NULL && p->right == NULL && p->anc == NULL)
14654	{
14655	if (isThisTreeRooted == NO)
14656	{
14657	if (p->label[0] == '\0' \|\| p->label[0] == '\n' \|\| p->label[0] == ' ')
14658	printf("%*cN %d (l=%d r=%d a=%d) (---) scalerNode=%d ",
14659	indent, ' ', Dex(p), Dex(p->left), Dex(p->right), Dex(p->anc), p->scalerNode);
14660	else
14661	printf("%*cN %d (l=%d r=%d a=%d) (%s) scalerNode=%d ",
14662	indent, ' ', Dex(p), Dex(p->left), Dex(p->right), Dex(p->anc), p->label, p->scalerNode);
14663	}
14664	else
14665	{
14666	printf("%*cN %d (l=%d r=%d a=%d) X.XXXXXX scalerNode=%d ",
14667	indent, ' ', Dex(p), Dex(p->left), Dex(p->right), Dex(p->anc), p->scalerNode);
14668	}
14669	}
14670	else
14671	{
14672	if (p->anc != NULL)
14673	{
14674	if (p->anc->anc == NULL && isThisTreeRooted == YES)
14675	printf("%*cN %d (l=%d r=%d a=%d) X.XXXXXX scalerNode=%d ",
14676	indent, ' ', Dex(p), Dex(p->left), Dex(p->right), Dex(p->anc), p->scalerNode);
14677	else
14678	printf("%*cN %d (l=%d r=%d a=%d) %1.15lf scalerNode=%d ",
14679	indent, ' ', Dex(p), Dex(p->left), Dex(p->right), Dex(p->anc), p->length, p->scalerNode);
14680	}
14681	}
14682	if (isThisTreeRooted == YES)
14683	printf ("depth=%1.15lf\n", p->nodeDepth);
14684	else
14685	printf ("\n");
14686	ShowNodes (p->left, indent + 2, isThisTreeRooted);
14687	ShowNodes (p->right, indent + 2, isThisTreeRooted);
14688	}
14689
14690	}
14691
14692
14693
14694
14695
14696	int StandID (char nuc)
14697
14698	{
14699
14700	char n;
14701
14702	/* Note that if you change how many states are recognized, you need
14703	to look at IsMissing */
14704	n = nuc;
14705
14706	if (n == '0')
14707	{
14708	return 1;
14709	}
14710	else if (n == '1')
14711	{
14712	return 2;
14713	}
14714	else if (n == '2')
14715	{
14716	return 4;
14717	}
14718	else if (n == '3')
14719	{
14720	return 8;
14721	}
14722	else if (n == '4')
14723	{
14724	return 16;
14725	}
14726	else if (n == '5')
14727	{
14728	return 32;
14729	}
14730	else if (n == '6')
14731	{
14732	return 64;
14733	}
14734	else if (n == '7')
14735	{
14736	return 128;
14737	}
14738	else if (n == '8')
14739	{
14740	return 256;
14741	}
14742	else if (n == '9')
14743	{
14744	return 512;
14745	}
14746	else if (n == missingId)
14747	{
14748	return MISSING;
14749	}
14750	else if (n == gapId)
14751	{
14752	return GAP;
14753	}
14754	else
14755	return -1;
14756
14757	}
14758
14759
14760
14761
14762
14763	void State_CODON (char *state, int code, int division)
14764	{
14765	state[0] = StateCode_NUC4(modelParams[division].codonNucs[code][0]);
14766	state[1] = StateCode_NUC4(modelParams[division].codonNucs[code][1]);
14767	state[2] = StateCode_NUC4(modelParams[division].codonNucs[code][2]);
14768	state[3] = '\0';
14769	}
14770
14771
14772
14773
14774
14775	void State_DOUBLET (char *state, int code)
14776	{
14777	state[0] = code/4 + 'A';
14778	state[1] = code%4 + 'A';
14779	state[2] = '\0';
14780	}
14781
14782
14783
14784
14785
14786	int StateCode_AA (int n)
14787
14788	{
14789	if (n == 0)
14790	return 'A'; /* Ala */
14791	else if (n == 1)
14792	return 'R'; /* Arg */
14793	else if (n == 2)
14794	return 'N'; /* Asn */
14795	else if (n == 3)
14796	return 'D'; /* Asp */
14797	else if (n == 4)
14798	return 'C'; /* Cys */
14799	else if (n == 5)
14800	return 'Q'; /* Gln */
14801	else if (n == 6)
14802	return 'E'; /* Glu */
14803	else if (n == 7)
14804	return 'G'; /* Gly */
14805	else if (n == 8)
14806	return 'H'; /* His */
14807	else if (n == 9)
14808	return 'I'; /* Ile */
14809	else if (n == 10)
14810	return 'L'; /* Leu */
14811	else if (n == 11)
14812	return 'K'; /* Lys */
14813	else if (n == 12)
14814	return 'M'; /* Met */
14815	else if (n == 13)
14816	return 'F'; /* Phe */
14817	else if (n == 14)
14818	return 'P'; /* Pro */
14819	else if (n == 15)
14820	return 'S'; /* Ser */
14821	else if (n == 16)
14822	return 'T'; /* Thr */
14823	else if (n == 17)
14824	return 'W'; /* Trp */
14825	else if (n == 18)
14826	return 'Y'; /* Tyr */
14827	else if (n == 19)
14828	return 'V'; /* Val */
14829	else
14830	return '?';
14831	}
14832
14833
14834
14835	int StateCode_NUC4 (int n)
14836
14837	{
14838	if (n == 0)
14839	return 'A';
14840	else if (n == 1)
14841	return 'C';
14842	else if (n == 2)
14843	return 'G';
14844	else if (n == 3)
14845	return 'T';
14846	else return '?';
14847	}
14848
14849
14850
14851
14852	int StateCode_Std (int n)
14853
14854	{
14855	if (n <= 9 && n >= 0)
14856	return '0' + n;
14857	else return '?';
14858	}
14859
14860
14861
14862
14863	void WhatVariableExp (SafeLong exp, char *st)
14864
14865	{
14866
14867	int n;
14868
14869	strcpy (st, "");
14870	n = 0;
14871	if (exp == 0)
14872	strcat(st, " nothing");
14873	else
14874	{
14875	if ((exp & Expecting(COMMAND)) == Expecting(COMMAND))
14876	{
14877	strcat(st, " command");
14878	n++;
14879	}
14880	if ((exp & Expecting(PARAMETER)) == Expecting(PARAMETER))
14881	{
14882	if (n > 0)
14883	strcat(st, " or");
14884	strcat(st, " parameter");
14885	n++;
14886	}
14887	if ((exp & Expecting(EQUALSIGN)) == Expecting(EQUALSIGN))
14888	{
14889	if (n > 0)
14890	strcat(st, " or");
14891	strcat(st, " =");
14892	n++;
14893	}
14894	if ((exp & Expecting(COLON)) == Expecting(COLON))
14895	{
14896	if (n > 0)
14897	strcat(st, " or");
14898	strcat(st, " :");
14899	n++;
14900	}
14901	if ((exp & Expecting(SEMICOLON)) == Expecting(SEMICOLON))
14902	{
14903	if (n > 0)
14904	strcat(st, " or");
14905	strcat(st, " ;");
14906	n++;
14907	}
14908	if ((exp & Expecting(COMMA)) == Expecting(COMMA))
14909	{
14910	if (n > 0)
14911	strcat(st, " or");
14912	strcat(st, " ,");
14913	n++;
14914	}
14915	if ((exp & Expecting(POUNDSIGN)) == Expecting(POUNDSIGN))
14916	{
14917	if (n > 0)
14918	strcat(st, " or");
14919	strcat(st, " #");
14920	n++;
14921	}
14922	if ((exp & Expecting(QUESTIONMARK)) == Expecting(QUESTIONMARK))
14923	{
14924	if (n > 0)
14925	strcat(st, " or");
14926	strcat(st, " ?");
14927	n++;
14928	}
14929	if ((exp & Expecting(DASH)) == Expecting(DASH))
14930	{
14931	if (n > 0)
14932	strcat(st, " or");
14933	strcat(st, " -");
14934	n++;
14935	}
14936	if ((exp & Expecting(LEFTPAR)) == Expecting(LEFTPAR))
14937	{
14938	if (n > 0)
14939	strcat(st, " or");
14940	strcat(st, " (");
14941	n++;
14942	}
14943	if ((exp & Expecting(RIGHTPAR)) == Expecting(RIGHTPAR))
14944	{
14945	if (n > 0)
14946	strcat(st, " or");
14947	strcat(st, " )");
14948	n++;
14949	}
14950	if ((exp & Expecting(LEFTCOMMENT)) == Expecting(LEFTCOMMENT))
14951	{
14952	if (n > 0)
14953	strcat(st, " or");
14954	strcat(st, " [");
14955	n++;
14956	}
14957	if ((exp & Expecting(RIGHTCOMMENT)) == Expecting(RIGHTCOMMENT))
14958	{
14959	if (n > 0)
14960	strcat(st, " or");
14961	strcat(st, " ]");
14962	n++;
14963	}
14964	if ((exp & Expecting(ALPHA)) == Expecting(ALPHA))
14965	{
14966	if (n > 0)
14967	strcat(st, " or");
14968	strcat(st, " <name>");
14969	n++;
14970	}
14971	if ((exp & Expecting(NUMBER)) == Expecting(NUMBER))
14972	{
14973	if (n > 0)
14974	strcat(st, " or");
14975	strcat(st, " <number>");
14976	n++;
14977	}
14978	if ((exp & Expecting(RETURNSYMBOL)) == Expecting(RETURNSYMBOL))
14979	{
14980	if (n > 0)
14981	strcat(st, " or");
14982	strcat(st, " return");
14983	n++;
14984	}
14985	if ((exp & Expecting(ASTERISK)) == Expecting(ASTERISK))
14986	{
14987	if (n > 0)
14988	strcat(st, " or");
14989	strcat(st, " *");
14990	n++;
14991	}
14992	if ((exp & Expecting(BACKSLASH)) == Expecting(BACKSLASH))
14993	{
14994	if (n > 0)
14995	strcat(st, " or");
14996	strcat(st, " /");
14997	n++;
14998	}
14999	if ((exp & Expecting(BACKSLASH)) == Expecting(BACKSLASH))
15000	{
15001	if (n > 0)
15002	strcat(st, " or");
15003	strcat(st, " \\");
15004	n++;
15005	}
15006	if ((exp & Expecting(EXCLAMATIONMARK)) == Expecting(EXCLAMATIONMARK))
15007	{
15008	if (n > 0)
15009	strcat(st, " or");
15010	strcat(st, " !");
15011	n++;
15012	}
15013	if ((exp & Expecting(PERCENT)) == Expecting(PERCENT))
15014	{
15015	if (n > 0)
15016	strcat(st, " or");
15017	strcat(st, " %");
15018	n++;
15019	}
15020	if ((exp & Expecting(LEFTCURL)) == Expecting(LEFTCURL))
15021	{
15022	if (n > 0)
15023	strcat(st, " or");
15024	strcat(st, " {");
15025	n++;
15026	}
15027	if ((exp & Expecting(RIGHTCURL)) == Expecting(RIGHTCURL))
15028	{
15029	if (n > 0)
15030	strcat(st, " or");
15031	strcat(st, " }");
15032	n++;
15033	}
15034	if ((exp & Expecting(WEIRD)) == Expecting(WEIRD))
15035	{
15036	if (n > 0)
15037	strcat(st, " or");
15038	strcat(st, " <whatever>");
15039	n++;
15040	}
15041	if ((exp & Expecting(UNKNOWN_TOKEN_TYPE)) == Expecting(UNKNOWN_TOKEN_TYPE))
15042	{
15043	if (n > 0)
15044	strcat(st, " or");
15045	strcat(st, " no clue");
15046	n++;
15047	}
15048	}
15049
15050	}
15051
15052
15053
15054
15055
15056	char WhichAA (int x)
15057
15058	{
15059
15060	if (x == 1)
15061	return ('A');
15062	else if (x == 2)
15063	return ('R');
15064	else if (x == 4)
15065	return ('N');
15066	else if (x == 8)
15067	return ('D');
15068	else if (x == 16)
15069	return ('C');
15070	else if (x == 32)
15071	return ('Q');
15072	else if (x == 64)
15073	return ('E');
15074	else if (x == 128)
15075	return ('G');
15076	else if (x == 256)
15077	return ('H');
15078	else if (x == 512)
15079	return ('I');
15080	else if (x == 1024)
15081	return ('L');
15082	else if (x == 2048)
15083	return ('K');
15084	else if (x == 4096)
15085	return ('M');
15086	else if (x == 8192)
15087	return ('F');
15088	else if (x == 16384)
15089	return ('P');
15090	else if (x == 32768)
15091	return ('S');
15092	else if (x == 65536)
15093	return ('T');
15094	else if (x == 131072)
15095	return ('W');
15096	else if (x == 262144)
15097	return ('Y');
15098	else if (x == 524288)
15099	return ('V');
15100	else if (x > 0 && x < 524288)
15101	return ('*');
15102	else if (x == MISSING)
15103	return ('?');
15104	else if (x == GAP)
15105	return ('-');
15106	else
15107	return (' ');
15108
15109	}
15110
15111
15112
15113
15114
15115	MrBFlt WhichCont (int x)
15116
15117	{
15118
15119	return ((MrBFlt)(x / 1000.0));
15120
15121	}
15122
15123
15124
15125
15126
15127	char WhichNuc (int x)
15128
15129	{
15130
15131	if (x == 1)
15132	return ('A');
15133	else if (x == 2)
15134	return ('C');
15135	else if (x == 3)
15136	return ('M');
15137	else if (x == 4)
15138	return ('G');
15139	else if (x == 5)
15140	return ('R');
15141	else if (x == 6)
15142	return ('S');
15143	else if (x == 7)
15144	return ('V');
15145	else if (x == 8)
15146	return ('T');
15147	else if (x == 9)
15148	return ('W');
15149	else if (x == 10)
15150	return ('Y');
15151	else if (x == 11)
15152	return ('H');
15153	else if (x == 12)
15154	return ('K');
15155	else if (x == 13)
15156	return ('D');
15157	else if (x == 14)
15158	return ('B');
15159	else if (x == 15)
15160	return ('N');
15161	else if (x == MISSING)
15162	return ('?');
15163	else if (x == GAP)
15164	return ('-');
15165	else
15166	return (' ');
15167
15168	}
15169
15170
15171
15172
15173
15174	char WhichRes (int x)
15175
15176	{
15177
15178	if (x == 1)
15179	return ('0');
15180	else if (x == 2)
15181	return ('1');
15182	else if (x == 3)
15183	return ('*');
15184	else if (x == MISSING)
15185	return ('N');
15186	else if (x == GAP)
15187	return ('-');
15188	else
15189	return (' ');
15190
15191	}
15192
15193
15194
15195
15196
15197	char WhichStand (int x)
15198
15199	{
15200
15201	if (x == 1)
15202	return ('0');
15203	else if (x == 2)
15204	return ('1');
15205	else if (x == 4)
15206	return ('2');
15207	else if (x == 8)
15208	return ('3');
15209	else if (x == 16)
15210	return ('4');
15211	else if (x == 32)
15212	return ('5');
15213	else if (x == 64)
15214	return ('6');
15215	else if (x == 128)
15216	return ('7');
15217	else if (x == 256)
15218	return ('8');
15219	else if (x == 512)
15220	return ('9');
15221	else if (x > 0 && x < 512)
15222	return ('*');
15223	else if (x == MISSING)
15224	return ('N');
15225	else if (x == GAP)
15226	return ('-');
15227	else
15228	return (' ');
15229
15230	}
15231
15232

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source: branches/ali/GDE/MrBAYES/mrbayes_3.2.1/command.c

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