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source: cpp/frams/genetics/fL/fL_oper.cpp @ 969

Last change on this file since 969 was 935, checked in by Maciej Komosinski, 5 years ago
Utility functions that provide a set of all neuron classes fulfilling given criteria now also filter neuron classes by the desired Model shape type (BALL_AND_STICK or SOLIDS)
File size: 26.2 KB

Line
1	// This file is a part of Framsticks SDK. http://www.framsticks.com/
2	// Copyright (C) 1999-2020 Maciej Komosinski and Szymon Ulatowski.
3	// See LICENSE.txt for details.
4
5	#include "fL_oper.h"
6	#include <common/loggers/loggers.h>
7	#include "../fH/fH_oper.h"
8	#include <algorithm>
9
10	#define FIELDSTRUCT Geno_fL
11	static ParamEntry GENOfLparam_tab[] =
12	{
13	{"Genetics: fL", 3, FL_OPCOUNT + FL_MUTGROUPSCOUNT + FL_CHG_COUNT + 2 + FL_ADD_COUNT, },
14	{"Genetics: fL: Probabilities of mutating axiom and rules", },
15	{"Genetics: fL: Probabilities of mutation types", },
16	{"fL_maxdefinedwords", 0, 0, "Maximum number of defined words", "d 0 100 10", FIELD(maxdefinedwords), "Maximum number of words that can be defined in L-System", },
17
18	{"fL_axm_mut_prob", 1, 0, "Axiom mutation", "f 0 1 0.2", FIELD(groupprobabilities[FL_AXM_WORD_MUT_PROB]), "Probability of performing mutation operations on axiom", },
19	{"fL_rul_mut_prob", 1, 0, "Rule's successor mutation", "f 0 1 0.8", FIELD(groupprobabilities[FL_RUL_WORD_MUT_PROB]), "Probability of performing mutation operations on the successor of random rule", },
20
21	{"fL_mut_addition", 2, 0, "Addition of word to sequence", "f 0 1 0.2", FIELD(operations[FL_ADD_WORD]), "Probability of adding random existing word to the axiom or one of successors", },
22
23	{"fL_mut_add_stick", 2, 0, " - addition of stick", "f 0 1 0.2", FIELD(addtypes[FL_ADD_STICK]), "Probability of adding stick", },
24	{"fL_mut_add_neuro", 2, 0, " - addition of neuron", "f 0 1 0.2", FIELD(addtypes[FL_ADD_NEURO]), "Probability of adding neuron", },
25	{"fL_mut_add_conn", 2, 0, " - addition of neuron connection", "f 0 1 0.2", FIELD(addtypes[FL_ADD_CONN]), "Probability of adding connection", },
26	{"fL_mut_add_rot", 2, 0, " - addition of rotation words", "f 0 1 0.2", FIELD(addtypes[FL_ADD_ROT]), "Probability of adding one of rotation words", },
27	{"fL_mut_add_branch", 2, 0, " - addition of branched stick", "f 0 1 0.2", FIELD(addtypes[FL_ADD_BRANCH]), "Probability of adding branch with rotation and stick", },
28	{"fL_mut_add_other", 2, 0, " - addition of defined words", "f 0 1 0.4", FIELD(addtypes[FL_ADD_OTHER]), "Probability of adding other word, defined in genotype", },
29
30	{"fL_mut_worddefaddition", 2, 0, "Addition of new word definition", "f 0 1 0.05", FIELD(operations[FL_ADD_WDEF]), "Probability of adding new word definition to the genotype", },
31	{"fL_mut_ruleaddition", 2, 0, "Addition of new rule definition", "f 0 1 0.1", FIELD(operations[FL_ADD_RULE]), "Probability of adding new rule definition for existing word", },
32	{"fL_mut_rulecond", 2, 0, "Modification of rule condition", "f 0 1 0.1", FIELD(operations[FL_CHG_COND]), "Probability of modifying random rule condition", },
33
34	{"fL_mut_changeword", 2, 0, "Change of random word", "f 0 1 0.3", FIELD(operations[FL_CHG_WORD]), "Probability of changing word name or formula of a random word from axiom or one of successors", },
35	{"fL_mut_changeword_formula", 2, 0, " - change of formula", "f 0 1 0.7", FIELD(chgoperations[FL_CHG_WORD_FORMULA]), "Probability of changing formula in word", },
36	{"fL_mut_changeword_name", 2, 0, " - change of name", "f 0 1 0.3", FIELD(chgoperations[FL_CHG_WORD_NAME]), "Probability of changing name in word", },
37
38	{"fL_mut_changeiter", 2, 0, "Change of L-System iteration", "f 0 1 0.3", FIELD(operations[FL_CHG_ITER]), "Probability of changing number of iterations of L-Systems", },
39	{"fL_mut_changeiter_step", 2, 0, "Step of iteration changing", "f 0 1 1.0", FIELD(iterchangestep), "Minimal step that should be used for changing iterations in L-Systems", },
40	{"fL_mut_deletion", 2, 0, "Deletion of random word", "f 0 1 0.2", FIELD(operations[FL_DEL_WORD]), "Probability of deleting random word from axiom or random successor (also deletes rule if there is only one word in successor)", },
41	{ 0, },
42	};
43	#undef FIELDSTRUCT
44
45	Geno_fL::Geno_fL()
46	{
47	par.setParamTab(GENOfLparam_tab);
48	par.select(this);
49	par.setDefault();
50	supported_format = 'L';
51	iterchangestep = 1.0;
52	maxdefinedwords = 10;
53	}
54
55	int Geno_fL::checkValidity(const char geno, const char genoname)
56	{
57	LoggerToMemory eh(LoggerBase::Enable \| LoggerToMemory::StoreAllMessages, LOG_WARN);
58	fL_Builder builder(false, false);
59
60	int err = builder.parseGenotype(geno);
61	if (err != 0)
62	{
63	return err;
64	}
65
66	if (builder.countSticksInSequence(&builder.genotype) == 0)
67	{
68	return GENOPER_OPFAIL;
69	}
70	double neededtime = 0;
71	Model *m = builder.developModel(neededtime);
72	if (!m)
73	{
74	return GENOPER_OPFAIL;
75	}
76	if (!m->isValid())
77	{
78	delete m;
79	return GENOPER_OPFAIL;
80	}
81	delete m;
82
83
84	return GENOPER_OK;
85	}
86
87	int Geno_fL::validate(char &geno, const char genoname)
88	{
89	LoggerToMemory eh(LoggerBase::Enable \| LoggerToMemory::StoreAllMessages, LOG_WARN);
90	fL_Builder builder(false, false);
91
92	int err = builder.parseGenotype(geno);
93	if (err != 0)
94	{
95	return err;
96	}
97	double neededtime = 0;
98	Model *m = builder.developModel(neededtime);
99	if (!m->isValid())
100	{
101	delete m;
102	return GENOPER_OPFAIL;
103	}
104	if (neededtime != builder.time)
105	{
106	builder.time = neededtime;
107	free(geno);
108	geno = strdup(builder.toString().c_str());
109	delete m;
110	return GENOPER_OK;
111	}
112	delete m;
113	return GENOPER_OK;
114	}
115
116	bool Geno_fL::addWord(std::list<fL_Word > list, fL_Word definition, std::list<fL_Word >::iterator it)
117	{
118	fL_Word *newword = new fL_Word();
119	newword = definition;
120
121	// if word has parameters
122	if (newword->npar > 0)
123	{
124	// create ParamObject that will hold parameter data
125	newword->data = ParamObject::makeObject(newword->tab);
126	Param par(newword->tab);
127	par.select(newword->data);
128	par.setDefault();
129	for (int i = 0; i < par.getPropCount(); i++)
130	{
131	newword->parevals.push_back(NULL);
132	}
133	if (newword->name.startsWith("rot"))
134	{
135	double rot = rndDouble(2);
136	MathEvaluation *eval = new MathEvaluation(0);
137	eval->convertString(SString::valueOf(rot).c_str());
138	newword->parevals[0] = eval;
139	}
140	else if (newword->name == "N")
141	{
142	SString det;
143	NeuroClass *cls = getRandomNeuroClass(Model::SHAPE_BALL_AND_STICK);
144	det = cls->getName();
145	Geno_fH::mutateNeuronProperties(det);
146	par.setStringById(FL_PE_NEURO_DET, det);
147	}
148	else if (newword->name == "C")
149	{
150	MathEvaluation *eval = new MathEvaluation(0);
151	eval->convertString(SString::valueOf(rndDouble(2) - 1).c_str());
152	newword->parevals[0] = eval;
153	}
154	}
155
156	list->insert(it, newword);
157	return true;
158	}
159
160	std::list<fL_Word > Geno_fL::selectRandomSequence(fL_Builder *creature, int &numparams, int &ruleid)
161	{
162	std::list<fL_Word > list = NULL;
163	int axiomorrules = roulette(groupprobabilities, FL_MUTGROUPSCOUNT);
164	bool axiomused = axiomorrules == FL_AXM_WORD_MUT_PROB \|\| creature->rules.size() == 0;
165	if (axiomused)
166	{
167	list = &creature->genotype;
168	numparams = 0;
169	ruleid = -1;
170	}
171	else
172	{
173	int rid = rndUint(creature->rules.size());
174	list = &creature->rules[rid]->objsucc;
175	numparams = creature->rules[rid]->objpred->npar;
176	ruleid = rid;
177	}
178	return list;
179	}
180
181	fL_Word* Geno_fL::randomWordDefinition(fL_Builder *creature, int method)
182	{
183	if (method == FL_ADD_OTHER && creature->builtincount < (int)creature->words.size())
184	{
185	return creature->words[creature->wordnames[creature->builtincount + rndUint((int)creature->words.size() - creature->builtincount)]];
186	}
187	else
188	{
189	if (method == FL_ADD_OTHER) // we should be able to select stick, neuro or conn
190	{
191	double alttypes[FL_ADD_COUNT - 2];
192	alttypes[FL_ADD_STICK] = addtypes[FL_ADD_STICK];
193	alttypes[FL_ADD_NEURO] = addtypes[FL_ADD_NEURO];
194	alttypes[FL_ADD_CONN] = addtypes[FL_ADD_CONN];
195	alttypes[FL_ADD_ROT] = addtypes[FL_ADD_ROT];
196	method = roulette(alttypes, FL_ADD_COUNT - 2);
197	}
198	switch (method)
199	{
200	case FL_ADD_STICK:
201	return creature->words["S"];
202	case FL_ADD_NEURO:
203	if (getActiveNeuroClassCount(Model::SHAPE_BALL_AND_STICK) == 0)
204	return creature->words["S"];
205	else
206	return creature->words["N"];
207	case FL_ADD_CONN:
208	return creature->words["C"];
209	case FL_ADD_ROT:
210	{
211	int rottype = rndUint(3);
212	switch (rottype)
213	{
214	case 0:
215	return creature->words["rotX"];
216	case 1:
217	return creature->words["rotY"];
218	case 2:
219	return creature->words["rotZ"];
220	}
221	break;
222	}
223	case FL_ADD_BRANCH:
224	// return NULL
225	break;
226	}
227	}
228	return NULL;
229	}
230
231	void Geno_fL::deleteBranch(std::list<fL_Word > list, std::list<fL_Word *>::iterator openbranchposition)
232	{
233	fL_Branch branch = (fL_Branch )(*openbranchposition);
234	if (branch->btype == fL_Branch::BranchType::OPEN)
235	{
236	int bcount = 1;
237	delete (*openbranchposition);
238	openbranchposition = list->erase(openbranchposition);
239	for (; openbranchposition != list->end(); openbranchposition++)
240	{
241	if ((*openbranchposition)->type == fLElementType::BRANCH)
242	{
243	branch = (fL_Branch )(openbranchposition);
244	if (branch->btype == fL_Branch::BranchType::OPEN)
245	{
246	bcount++;
247	}
248	else
249	{
250	bcount--;
251	if (bcount == 0)
252	{
253	delete branch;
254	list->erase(openbranchposition);
255	break;
256	}
257	}
258	}
259	}
260	}
261	else
262	{
263	openbranchposition++;
264	if (openbranchposition != list->end())
265	{
266	delete (*openbranchposition);
267	list->erase(openbranchposition);
268	}
269	}
270	}
271
272	int Geno_fL::mutate(char *&geno, float& chg, int &method)
273	{
274	fL_Builder *creature = new fL_Builder(false, false);
275
276	if (creature->parseGenotype(geno) != 0)
277	{
278	delete creature;
279	return GENOPER_OPFAIL;
280	}
281
282	int before = creature->countWordsInLSystem();
283
284	method = roulette(operations, FL_OPCOUNT);
285	switch (method)
286	{
287	case FL_CHG_ITER:
288	{
289	if (rndUint(2) == 0)
290	{
291	creature->time = creature->time + iterchangestep <= ExtValue::getDouble(FL_MAXITER) ?
292	creature->time + iterchangestep : creature->time - iterchangestep;
293	}
294	else
295	{
296	creature->time = creature->time - iterchangestep >= 0 ?
297	creature->time - iterchangestep : creature->time + iterchangestep;
298	}
299	break;
300	}
301	case FL_CHG_COND:
302	{
303	if (creature->rules.size() > 0)
304	{
305	int ruleid = rndUint(creature->rules.size());
306	if (!creature->rules[ruleid]->condeval)
307	{
308	creature->rules[ruleid]->condeval = new MathEvaluation(creature->rules[ruleid]->objpred->npar);
309	}
310	creature->rules[ruleid]->condeval->mutateConditional();
311	break;
312	}
313	// if there are no rules - create one
314	}
315	[[fallthrough]];
316	case FL_ADD_RULE:
317	{
318	std::unordered_map<std::string, fL_Word *>::iterator pred = creature->words.begin();
319	std::vector<fL_Word *> wordswithnorules;
320	for (; pred != creature->words.end(); pred++)
321	{
322	if (!pred->second->builtin)
323	{
324	bool norules = true;
325	for (fL_Rule * r : creature->rules)
326	{
327	if (pred->second->name == r->objpred->name &&
328	pred->second->npar == r->objpred->npar)
329	{
330	norules = false;
331	break;
332	}
333	}
334	if (norules)
335	{
336	wordswithnorules.push_back(pred->second);
337	}
338	}
339	}
340	if (wordswithnorules.size() > 0)
341	{
342	int predid = rndUint(wordswithnorules.size());
343	fL_Rule *newrule = new fL_Rule(0,0);
344	fL_Word *pred = new fL_Word();
345	pred = wordswithnorules[predid];
346	newrule->objpred = pred;
347	fL_Word *initdef = randomWordDefinition(creature, roulette(addtypes, FL_ADD_COUNT - 1)); // -1 to avoid branching
348	addWord(&newrule->objsucc, initdef, newrule->objsucc.begin());
349	creature->rules.push_back(newrule);
350	break;
351	}
352	else if (creature->rules.size() > 0)
353	{
354	int ruleid = rndUint(creature->rules.size());
355	fL_Rule *newrule = new fL_Rule(0, 0);
356	fL_Word *pred = new fL_Word();
357	pred = creature->rules[ruleid]->objpred;
358	newrule->objpred = pred;
359	if (creature->rules[ruleid]->condeval)
360	{
361	std::string formula = "";
362	creature->rules[ruleid]->condeval->RPNToInfix(formula);
363	if (formula.find("1.0-(") != 0)
364	{
365	std::string res = "1.0-(";
366	res += formula;
367	res += ")";
368	newrule->condeval = new MathEvaluation(pred->npar);
369	newrule->condeval->convertString(res);
370	}
371	else
372	{
373	newrule->condeval = new MathEvaluation(pred->npar);
374	newrule->condeval->mutateConditional();
375	}
376	}
377	else
378	{
379	newrule->condeval = new MathEvaluation(pred->npar);
380	newrule->condeval->mutateConditional();
381	}
382	fL_Word *worddef = randomWordDefinition(creature, roulette(addtypes, FL_ADD_COUNT - 1));
383	addWord(&newrule->objsucc, worddef, newrule->objsucc.begin());
384	creature->rules.push_back(newrule);
385	break;
386	}
387	// if there are no words, from which rules can be formed, then add one
388	}
389	[[fallthrough]];
390	case FL_ADD_WDEF:
391	{
392	if (creature->countDefinedWords() <= maxdefinedwords)
393	{
394	int npar = rndUint(ExtValue::getInt(FL_MAXPARAMS, false));
395	for (int i = 0; i < maxdefinedwords; i++)
396	{
397	std::string name = "w";
398	name += std::to_string(i);
399	if (creature->words.find(name) == creature->words.end())
400	{
401	fL_Word *word = new fL_Word(false, 0, 0);
402	word->npar = npar;
403	word->name = name.c_str();
404	word->processDefinition(creature);
405	break;
406	}
407	}
408	break;
409	}
410	//no break at the end of case - if there is too many words, then
411	// deletion should be performed
412	}
413	[[fallthrough]];
414	case FL_DEL_WORD:
415	{
416	int numpars = 0;
417	int ruleid = 0;
418	std::list<fL_Word > list = selectRandomSequence(creature, numpars, ruleid);
419	if (ruleid == -1 && creature->countSticksInSequence(list) == 1)
420	{
421	if (list->size() > 1)
422	{
423	int rndid = rndUint(list->size() - 1);
424	int j = 0;
425	std::list<fL_Word *>::iterator it = list->begin();
426	if ((*it)->name == "S")
427	{
428	it++;
429	}
430	while (it != list->end() && j < rndid && ((*it)->name == "S"))
431	{
432	if ((*it)->name != "S")
433	{
434	j++;
435	}
436	it++;
437	}
438	if (it != list->end())
439	{
440	if ((*it)->type == fLElementType::BRANCH)
441	{
442	deleteBranch(list, it);
443	}
444	else
445	{
446	delete (*it);
447	list->erase(it);
448	}
449	break;
450	}
451	// else add word
452	}
453	// else add word
454	}
455	else
456	{
457	int rndid = rndUint(list->size());
458	std::list<fL_Word *>::iterator it = list->begin();
459	std::advance(it, rndid);
460	if ((*it)->type == fLElementType::BRANCH)
461	{
462	deleteBranch(list, it);
463	}
464	else
465	{
466	delete (*it);
467	list->erase(it);
468	}
469	if (ruleid > -1 && creature->rules[ruleid]->objsucc.size() == 0)
470	{
471	delete creature->rules[ruleid];
472	creature->rules.erase(creature->rules.begin() + ruleid);
473	}
474	break;
475	}
476	// if no words available, then add word
477	}
478	[[fallthrough]];
479	case FL_ADD_WORD:
480	{
481	int numpars = 0;
482	int tmp = 0;
483	std::list<fL_Word > list = selectRandomSequence(creature, numpars, tmp);
484	int rndid = rndUint(list->size());
485	std::list<fL_Word *>::iterator it = list->begin();
486	std::advance(it, rndid);
487	int meth = roulette(addtypes, FL_ADD_COUNT);
488	if (tmp == -1)
489	{ // if sequence is axiom and it does not have non-builtin words
490	bool hasdefined = false;
491	for (std::list<fL_Word *>::iterator elem = list->begin(); elem != list->end(); elem++)
492	{
493	if (!(*elem)->builtin)
494	{
495	hasdefined = true;
496	break;
497	}
498	}
499	if (!hasdefined)
500	{
501	meth = FL_ADD_OTHER;
502	}
503
504	}
505	if (meth != FL_ADD_BRANCH)
506	{
507	fL_Word *worddef = randomWordDefinition(creature, meth);
508	addWord(list, worddef, it);
509	}
510	else
511	{
512	fL_Branch *start = new fL_Branch(fL_Branch::BranchType::OPEN, 0, 0);
513	list->insert(it, start);
514	int rottype = rndUint(2);
515	switch (rottype)
516	{
517	case 0:
518	addWord(list, creature->words["rotY"], it);
519	case 1:
520	addWord(list, creature->words["rotZ"], it);
521	}
522	addWord(list, creature->words["S"], it);
523	fL_Branch *end = new fL_Branch(fL_Branch::BranchType::CLOSE, 0, 0);
524	list->insert(it, end);
525	}
526	break;
527	}
528	case FL_CHG_WORD:
529	{
530	int numpars = 0;
531	int tmp = 0;
532	std::list<fL_Word > list = selectRandomSequence(creature, numpars, tmp);
533	int rndid = rndUint(list->size());
534	std::list<fL_Word *>::iterator selectedword = list->begin();
535	std::advance(selectedword, rndid);
536	if ((*selectedword)->type == fLElementType::BRANCH)
537	{
538	break;
539	}
540	int chgtype = roulette(chgoperations, FL_CHG_COUNT);
541	if (creature->countSticksInSequence(list) == 1 && tmp == -1) // if sequence is axiom
542	{
543	fL_Word *worddef = randomWordDefinition(creature, roulette(addtypes, FL_ADD_COUNT - 1));
544
545	int numpars = 0;
546	std::list<fL_Word > list = selectRandomSequence(creature, numpars, tmp);
547	int rndid = rndUint(list->size());
548	std::list<fL_Word *>::iterator it = list->begin();
549	std::advance(it, rndid);
550
551	addWord(list, worddef, it);
552
553	break;
554	}
555	else if (chgtype == FL_CHG_WORD_NAME)
556	{
557	if ((*selectedword)->builtin)
558	{
559	delete (*selectedword);
560	selectedword = list->erase(selectedword);
561	fL_Word *worddef = randomWordDefinition(creature, roulette(addtypes, FL_ADD_COUNT - 1));
562	addWord(list, worddef, selectedword);
563	}
564	else
565	{
566	std::vector<fL_Word *> available;
567	for (std::unordered_map<std::string, fL_Word *>::iterator wit = creature->words.begin();
568	wit != creature->words.end(); wit++)
569	{
570	if ((*selectedword)->npar == wit->second->npar &&
571	(*selectedword)->name != wit->second->name &&
572	!wit->second->builtin)
573	{
574	available.push_back(wit->second);
575	}
576	}
577	if (available.size() > 0)
578	{
579	int newnameid = rndUint(available.size());
580	(*selectedword)->name = available[newnameid]->name;
581	}
582	else
583	{
584	delete (*selectedword);
585	selectedword = list->erase(selectedword);
586	fL_Word *worddef = randomWordDefinition(creature, roulette(addtypes, FL_ADD_COUNT - 1));
587	addWord(list, worddef, selectedword);
588	}
589	}
590	}
591	else
592	{
593	if ((*selectedword)->npar > 0)
594	{
595	int randeval = rndUint((*selectedword)->npar);
596	Param par((selectedword)->tab, (selectedword)->data);
597	if ((selectedword)->builtin && (selectedword)->name == "N"
598	&& strcmp(par.id(randeval), FL_PE_NEURO_DET) == 0)
599	{
600	SString res = par.getStringById(FL_PE_NEURO_DET);
601	Geno_fH::mutateNeuronProperties(res);
602	par.setStringById(FL_PE_NEURO_DET, res);
603	}
604	else if ((*selectedword)->builtin &&
605	(*selectedword)->name == "C" &&
606	strcmp(par.id(randeval), FL_PE_CONN_ATTR) == 0)
607	{
608	SString strattractor = par.getStringById(FL_PE_CONN_ATTR);
609	if (strattractor.len() > 0)
610	{
611	fL_Word *w = NULL;
612	creature->createWord(strattractor, w, numpars, 0, 0);
613	// mutate attractor parameter
614	if (w->npar > 0)
615	{
616	int rndattr = rndUint(w->npar);
617	if (!w->parevals[rndattr])
618	{
619	w->parevals[rndattr] = new MathEvaluation(numpars);
620	}
621	w->parevals[rndattr]->mutate(false, false);
622	}
623	strattractor = w->stringify(true);
624	par.setStringById(FL_PE_CONN_ATTR, strattractor);
625	delete w;
626	}
627	else
628	{
629	if (creature->builtincount < (int)creature->words.size())
630	{
631	fL_Word *wdef = randomWordDefinition(creature, FL_ADD_OTHER);
632	fL_Word *w = new fL_Word();
633	w = wdef;
634	w->data = ParamObject::makeObject(w->tab);
635	Param apar(w->tab);
636	apar.select(w->data);
637	apar.setDefault();
638	if (w->npar > 0)
639	{
640	int rndattr = rndUint(w->npar);
641	for (int i = 0; i < w->npar; i++)
642	{
643	if (i == rndattr)
644	{
645	MathEvaluation *ev = new MathEvaluation(numpars);
646	ev->mutate(false, false);
647	w->parevals.push_back(ev);
648	}
649	else
650	{
651	w->parevals.push_back(NULL);
652	}
653	}
654
655	}
656	strattractor = w->stringify(false);
657	par.setStringById(FL_PE_CONN_ATTR, strattractor);
658	delete w;
659	}
660	}
661	}
662	else
663	{
664	if (!(*selectedword)->parevals[randeval])
665	{
666	(*selectedword)->parevals[randeval] = new MathEvaluation(numpars);
667	}
668	(*selectedword)->parevals[randeval]->mutate(false, iterchangestep != 1.0);
669	}
670	}
671	}
672	break;
673	}
674	}
675
676	free(geno);
677	geno = strdup(creature->toString().c_str());
678	chg = (double)abs(before - creature->countWordsInLSystem()) / before;
679	delete creature;
680
681	return GENOPER_OK;
682	}
683
684	fL_Word* Geno_fL::getAppropriateWord(fL_Builder from, fL_Builder to, fL_Word *fromword, std::unordered_map<std::string, std::string> &map)
685	{
686	if (fromword->name == "[" \|\| fromword->name == "]") // if words are branching words
687	{
688	fL_Branch *newword = new fL_Branch(fromword->name == "[" ? fL_Branch::BranchType::OPEN : fL_Branch::BranchType::CLOSE, 0, 0);
689	return newword;
690	}
691	if (fromword->builtin)
692	{
693	fL_Word *newword = new fL_Word();
694	(newword) = (to->words[fromword->name.c_str()]);
695	return newword;
696	}
697	if (map.find(fromword->name.c_str()) != map.end()) // if word is already mapped
698	{
699	fL_Word *newword = new fL_Word();
700	(newword) = (to->words[map[fromword->name.c_str()]]);
701	return newword;
702	}
703	else if (to->words.find(fromword->name.c_str()) != to->words.end() &&
704	to->words[fromword->name.c_str()]->npar == fromword->npar) // if there is already same word with same number of parameters
705	{
706	fL_Word *newword = new fL_Word();
707	map[fromword->name.c_str()] = fromword->name.c_str();
708	(newword) = (to->words[map[fromword->name.c_str()]]);
709	return newword;
710	}
711	for (std::unordered_map<std::string, fL_Word *>::iterator it = to->words.begin();
712	it != to->words.end(); it++)
713	{ // find word with same number of parameters
714	if (fromword->npar == it->second->npar && map.find(fromword->name.c_str()) == map.end() && !it->second->builtin)
715	{ // if there is a word with same number of parameters
716	map[fromword->name.c_str()] = it->second->name.c_str();
717	fL_Word *newword = new fL_Word();
718	(newword) = (it->second);
719	return newword;
720	}
721	}
722	fL_Word *newworddef = new fL_Word();
723	(newworddef) = (fromword);
724	newworddef->parevals.clear();
725	if (to->words.find(newworddef->name.c_str()) != to->words.end())
726	{
727	int i = 0;
728	while (true)
729	{
730	std::string name = "w";
731	name += std::to_string(i);
732	if (to->words.find(name) == to->words.end())
733	{
734	newworddef->name = name.c_str();
735	break;
736	}
737	i++;
738	}
739	}
740	newworddef->processDefinition(to);
741	map[fromword->name.c_str()] = newworddef->name.c_str();
742	fL_Word *newword = new fL_Word();
743	(newword) = (to->words[map[fromword->name.c_str()]]);
744	return newword;
745	}
746
747	void Geno_fL::migrateRandomRules(fL_Builder from, fL_Builder to, int numselrules)
748	{
749	std::unordered_map<std::string, std::string> map;
750	if (from->rules.size() > 0)
751	{
752	for (int i = 0; i < numselrules; i++)
753	{
754	int rulid = rndUint(from->rules.size());
755	fL_Rule *rul = from->rules[rulid];
756	fL_Rule *newrule = new fL_Rule(0, 0);
757	newrule->objpred = getAppropriateWord(from, to, rul->objpred, map);
758	for (fL_Word *w : rul->objsucc)
759	{
760	fL_Word *el = getAppropriateWord(from, to, w, map);
761	if (el->type == fLElementType::BRANCH)
762	{
763	newrule->objsucc.push_back(el);
764	continue;
765	}
766	Param origpar(w->tab);
767	origpar.select(w->data);
768	el->data = ParamObject::makeObject(el->tab);
769	Param par(el->tab);
770	par.select(el->data);
771	par.setDefault();
772	for (int i = 0; i < el->npar; i++)
773	{
774	std::string form;
775	if (w->builtin && w->name == "N"
776	&& strcmp(par.id(i), FL_PE_NEURO_DET) == 0)
777	{
778	SString res = origpar.getStringById(FL_PE_NEURO_DET);
779	par.setStringById(FL_PE_NEURO_DET, res);
780	el->parevals.push_back(NULL);
781	}
782	else if (w->builtin && w->name == "C"
783	&& strcmp(par.id(i), FL_PE_CONN_ATTR) == 0)
784	{
785	SString strattractor = origpar.getStringById(FL_PE_CONN_ATTR);
786	if (strattractor.len() > 0)
787	{
788	fL_Word *tmp = NULL;
789	from->createWord(strattractor, tmp, newrule->objpred->npar, 0, 0);
790	fL_Word *newsuccword = getAppropriateWord(from, to, tmp, map);
791	newsuccword->data = ParamObject::makeObject(el->tab);
792	newsuccword->parevals = tmp->parevals;
793	tmp->parevals.clear();
794	strattractor = newsuccword->stringify(true);
795	par.setStringById(FL_PE_CONN_ATTR, strattractor);
796	delete newsuccword;
797	delete tmp;
798	}
799	par.setStringById(FL_PE_CONN_ATTR, strattractor);
800	el->parevals.push_back(NULL);
801	}
802	else if (w->parevals[i])
803	{
804	MathEvaluation *eval = new MathEvaluation(newrule->objpred->npar);
805	w->parevals[i]->RPNToInfix(form);
806	eval->convertString(form);
807	el->parevals.push_back(eval);
808	}
809	else
810	{
811	el->parevals.push_back(NULL);
812	}
813	}
814	newrule->objsucc.push_back(el);
815	}
816	to->rules.push_back(newrule);
817	}
818	}
819	}
820
821	int Geno_fL::crossOver(char &g1, char &g2, float& chg1, float& chg2)
822	{
823	fL_Builder *creature1 = new fL_Builder(false, false);
824	fL_Builder *creature1template = new fL_Builder(false, false);
825	fL_Builder *creature2 = new fL_Builder(false, false);
826	fL_Builder *creature2template = new fL_Builder(false, false);
827
828	int count1 = creature1->countWordsInLSystem();
829	int count2 = creature2->countWordsInLSystem();
830
831	if (creature1->parseGenotype(g1) != 0 \|\| creature2->parseGenotype(g2) != 0)
832	{
833	delete creature1;
834	delete creature2;
835	delete creature1template;
836	delete creature2template;
837	return GENOPER_OPFAIL;
838	}
839
840	creature1template->parseGenotype(g1);
841	creature2template->parseGenotype(g2);
842
843	int numselrules = 1 + rndUint(XOVER_MAX_MIGRATED_RULES);
844	numselrules = numselrules < (int)creature1->rules.size() ? numselrules : (int)creature1->rules.size();
845
846	migrateRandomRules(creature1template, creature2, numselrules);
847
848	numselrules = 1 + rndUint(XOVER_MAX_MIGRATED_RULES);
849	numselrules = numselrules < (int)creature1->rules.size() ? numselrules : (int)creature1->rules.size();
850
851	migrateRandomRules(creature2template, creature1, numselrules);
852
853	free(g1);
854	free(g2);
855
856	g1 = strdup(creature1->toString().c_str());
857	g2 = strdup(creature2->toString().c_str());
858
859	chg1 = (double)count1 / creature1->countWordsInLSystem();
860	chg1 = (double)count2 / creature2->countWordsInLSystem();
861
862	delete creature1;
863	delete creature2;
864	delete creature1template;
865	delete creature2template;
866
867	return GENOPER_OK;
868	}
869
870	uint32_t Geno_fL::style(const char *geno, int pos)
871	{
872	char ch = geno[pos];
873	uint32_t style = GENSTYLE_CS(0, GENSTYLE_STRIKEOUT);
874	if (pos == 0 \|\| geno[pos - 1] == '\n' \|\| ch == ':') // single-character line definition
875	{
876	style = GENSTYLE_CS(GENCOLOR_TEXT, GENSTYLE_BOLD);
877	}
878	else if (strchr("()", ch) != NULL)
879	{
880	style = GENSTYLE_RGBS(50, 50, 50, GENSTYLE_BOLD);
881	}
882	else if (isalpha(ch)) // properties name
883	{
884	style = GENSTYLE_RGBS(0, 200, 0, GENSTYLE_BOLD);
885	}
886	else if (isdigit(ch) \|\| strchr(",.=", ch)) // properties values
887	{
888	style = GENSTYLE_CS(GENCOLOR_TEXT, GENSTYLE_NONE);
889	}
890	else if (ch == '\"')
891	{
892	style = GENSTYLE_RGBS(200, 0, 0, GENSTYLE_BOLD);
893	}
894
895	return style;
896	}

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