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source: cpp/frams/genetics/fL/fL_oper.cpp @ 1282

Last change on this file since 1282 was 1273, checked in by Maciej Komosinski, 15 months ago
fH, fB, fL: improved default parameter values, syntax coloring and code logic
File size: 26.6 KB

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1	// This file is a part of Framsticks SDK. http://www.framsticks.com/
2	// Copyright (C) 1999-2023 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
11
12	//TODO fix: occasionally happens (note that fL extensively uses Param parsing, see fL_word_paramtab): Param.loadSingleLine: Unknown property 'Word.w0(n1' (ignored)
13	//TODO reconsider and maybe improve sensor and effector embodiment; see "MacKo 2023-07: embody" in fL_general.cpp.
14
15
16
17	#define FIELDSTRUCT Geno_fL
18	static ParamEntry geno_fL_paramtab[] =
19	{
20	{"Genetics: fL", 3, FL_OPCOUNT + FL_MUTGROUPSCOUNT + FL_CHG_COUNT + 2 + FL_ADD_COUNT, },
21	{"Genetics: fL: Probabilities of mutating axiom and rules", },
22	{"Genetics: fL: Probabilities of mutation types", },
23	{"fL_maxdefinedwords", 0, 0, "Maximum number of defined words", "d 0 100 10", FIELD(maxdefinedwords), "Maximum number of words that can be defined in the L-System", },
24
25	{"fL_axm_mut_prob", 1, 0, "Axiom mutation", "f 0 100 4", FIELD(groupprobabilities[FL_AXM_WORD_MUT_PROB]), "Probability of performing mutation operations on axiom", },
26	{"fL_rul_mut_prob", 1, 0, "Rule's successor mutation", "f 0 100 1", FIELD(groupprobabilities[FL_RUL_WORD_MUT_PROB]), "Probability of performing mutation operations on the successor of a random rule", },
27
28	{"fL_mut_addition", 2, 0, "Addition of a word to a sequence", "f 0 100 4", FIELD(operations[FL_ADD_WORD]), "Probability of adding a random existing word to the axiom or to one of successors", },
29
30	{"fL_mut_add_stick", 2, 0, " - addition of a stick", "f 0 100 1", FIELD(addtypes[FL_ADD_STICK]), "Probability of adding a stick", },
31	{"fL_mut_add_neuro", 2, 0, " - addition of a neuron", "f 0 100 4", FIELD(addtypes[FL_ADD_NEURO]), "Probability of adding a neuron", },
32	{"fL_mut_add_conn", 2, 0, " - addition of a neuron connection", "f 0 100 4", FIELD(addtypes[FL_ADD_CONN]), "Probability of adding a neuron connection", },
33	{"fL_mut_add_rot", 2, 0, " - addition of rotation words", "f 0 100 2", FIELD(addtypes[FL_ADD_ROT]), "Probability of adding one of rotation words", },
34	{"fL_mut_add_branch", 2, 0, " - addition of a branched stick", "f 0 100 4", FIELD(addtypes[FL_ADD_BRANCH]), "Probability of adding a branch with a rotation and a stick", },
35	{"fL_mut_add_other", 2, 0, " - addition of defined words", "f 0 100 1", FIELD(addtypes[FL_ADD_OTHER]), "Probability of adding another word defined in the genotype", },
36
37	{"fL_mut_worddefaddition", 2, 0, "Addition of a new word definition", "f 0 100 1", FIELD(operations[FL_ADD_WDEF]), "Probability of adding a new word definition to the genotype", },
38	{"fL_mut_ruleaddition", 2, 0, "Addition of a new rule definition", "f 0 100 1", FIELD(operations[FL_ADD_RULE]), "Probability of adding a new rule definition for an existing word", },
39	{"fL_mut_rulecond", 2, 0, "Modification of a rule condition", "f 0 100 1", FIELD(operations[FL_CHG_COND]), "Probability of modifying a random rule condition", },
40
41	{"fL_mut_changeword", 2, 0, "Change a random word", "f 0 100 4", FIELD(operations[FL_CHG_WORD]), "Probability of changing a word name or a formula of a random word from an axiom or one of successors", },
42	{"fL_mut_changeword_formula", 2, 0, " - change of a formula", "f 0 100 4", FIELD(chgoperations[FL_CHG_WORD_FORMULA]), "Probability of changing a formula in a word", },
43	{"fL_mut_changeword_name", 2, 0, " - change of a name", "f 0 100 2", FIELD(chgoperations[FL_CHG_WORD_NAME]), "Probability of changing a name in a word", },
44
45	{"fL_mut_changeiter", 2, 0, "Change the number of iterations", "f 0 100 1", FIELD(operations[FL_CHG_ITER]), "Probability of changing the number of iterations of the L-System", },
46	{"fL_mut_changeiter_step", 2, 0, "Step of the iteration change", "f 0 1 1.0", FIELD(iterchangestep), "The minimal step that should be used for changing iterations in the L-System", },
47	{"fL_mut_deletion", 2, 0, "Deletion of a random word", "f 0 100 4", FIELD(operations[FL_DEL_WORD]), "Probability of deleting a random word from an axiom or a random successor (also deletes the rule if there is only one word in the successor)", },
48	{ 0, },
49	};
50	#undef FIELDSTRUCT
51
52	Geno_fL::Geno_fL()
53	{
54	par.setParamTab(geno_fL_paramtab);
55	par.select(this);
56	par.setDefault();
57	supported_format = 'L';
58	iterchangestep = 1.0;
59	maxdefinedwords = 10;
60	}
61
62	int Geno_fL::checkValidity(const char geno, const char genoname)
63	{
64	LoggerToMemory eh(LoggerBase::Enable \| LoggerToMemory::StoreAllMessages, LOG_WARN);
65	fL_Builder builder(false, false);
66
67	int err = builder.parseGenotype(geno);
68	if (err != 0)
69	{
70	return err;
71	}
72
73	if (builder.countSticksInSequence(&builder.genotype) == 0)
74	{
75	return 1;
76	}
77	double neededtime = 0;
78	Model *m = builder.developModel(neededtime);
79	if (m == NULL)
80	{
81	return 1;
82	}
83	if (!m->isValid())
84	{
85	delete m;
86	return 1;
87	}
88	delete m;
89
90	return GENOPER_OK;
91	}
92
93	int Geno_fL::validate(char &geno, const char genoname)
94	{
95	LoggerToMemory eh(LoggerBase::Enable \| LoggerToMemory::StoreAllMessages, LOG_WARN);
96	fL_Builder builder(false, false);
97
98	int err = builder.parseGenotype(geno);
99	if (err != 0)
100	{
101	return GENOPER_OK;
102	}
103	double neededtime = 0;
104	Model *m = builder.developModel(neededtime);
105	if (m == NULL)
106	{
107	return GENOPER_OK;
108	}
109	if (!m->isValid())
110	{
111	delete m;
112	return GENOPER_OK;
113	}
114	if (neededtime != builder.time)
115	{
116	builder.time = neededtime;
117	free(geno);
118	geno = strdup(builder.toString().c_str());
119	delete m;
120	return GENOPER_OK;
121	}
122	delete m;
123	return GENOPER_OK;
124	}
125
126	bool Geno_fL::addWord(std::list<fL_Word > list, fL_Word definition, std::list<fL_Word >::iterator it)
127	{
128	fL_Word *newword = new fL_Word();
129	newword = definition;
130
131	// if word has parameters
132	if (newword->npar > 0)
133	{
134	// create ParamObject that will hold parameter data
135	newword->data = ParamObject::makeObject(newword->tab);
136	Param par(newword->tab);
137	par.select(newword->data);
138	par.setDefault();
139	for (int i = 0; i < par.getPropCount(); i++)
140	{
141	newword->parevals.push_back(NULL);
142	}
143	if (newword->name.startsWith("rot"))
144	{
145	double rot = rndDouble(2);
146	MathEvaluation *eval = new MathEvaluation(0);
147	eval->convertString(SString::valueOf(rot).c_str());
148	newword->parevals[0] = eval;
149	}
150	else if (newword->name == "N")
151	{
152	SString det;
153	NeuroClass *cls = getRandomNeuroClass(Model::SHAPETYPE_BALL_AND_STICK);
154	det = cls->getName();
155	Geno_fH::mutateNeuronProperties(det);
156	par.setStringById(FL_PE_NEURO_DET, det);
157	}
158	else if (newword->name == "C")
159	{
160	MathEvaluation *eval = new MathEvaluation(0);
161	eval->convertString(SString::valueOf(rndDouble(2) - 1).c_str());
162	newword->parevals[0] = eval;
163	}
164	}
165
166	list->insert(it, newword);
167	return true;
168	}
169
170	std::list<fL_Word > Geno_fL::selectRandomSequence(fL_Builder *creature, int &numparams, int &ruleid)
171	{
172	std::list<fL_Word > list = NULL;
173	int axiomorrules = roulette(groupprobabilities, FL_MUTGROUPSCOUNT);
174	bool axiomused = axiomorrules == FL_AXM_WORD_MUT_PROB \|\| creature->rules.size() == 0;
175	if (axiomused)
176	{
177	list = &creature->genotype;
178	numparams = 0;
179	ruleid = -1;
180	}
181	else
182	{
183	int rid = rndUint((unsigned int)creature->rules.size());
184	list = &creature->rules[rid]->objsucc;
185	numparams = creature->rules[rid]->objpred->npar;
186	ruleid = rid;
187	}
188	return list;
189	}
190
191	fL_Word* Geno_fL::randomWordDefinition(fL_Builder *creature, int method)
192	{
193	if (method == FL_ADD_OTHER && creature->builtincount < (int)creature->words.size())
194	{
195	return creature->words[creature->wordnames[creature->builtincount + rndUint((int)creature->words.size() - creature->builtincount)]];
196	}
197	else
198	{
199	if (method == FL_ADD_OTHER) // we should be able to select stick, neuro or conn
200	{
201	double alttypes[FL_ADD_COUNT - 2];
202	alttypes[FL_ADD_STICK] = addtypes[FL_ADD_STICK];
203	alttypes[FL_ADD_NEURO] = addtypes[FL_ADD_NEURO];
204	alttypes[FL_ADD_CONN] = addtypes[FL_ADD_CONN];
205	alttypes[FL_ADD_ROT] = addtypes[FL_ADD_ROT];
206	method = roulette(alttypes, FL_ADD_COUNT - 2);
207	}
208	switch (method)
209	{
210	case FL_ADD_STICK:
211	return creature->words["S"];
212	case FL_ADD_NEURO:
213	if (getActiveNeuroClassCount(Model::SHAPETYPE_BALL_AND_STICK) == 0)
214	return creature->words["S"];
215	else
216	return creature->words["N"];
217	case FL_ADD_CONN:
218	return creature->words["C"];
219	case FL_ADD_ROT:
220	{
221	int rottype = rndUint(3);
222	switch (rottype)
223	{
224	case 0:
225	return creature->words["rotX"];
226	case 1:
227	return creature->words["rotY"];
228	case 2:
229	return creature->words["rotZ"];
230	}
231	break;
232	}
233	case FL_ADD_BRANCH:
234	// return NULL
235	break;
236	}
237	}
238	return NULL;
239	}
240
241	void Geno_fL::deleteBranch(std::list<fL_Word > list, std::list<fL_Word *>::iterator openbranchposition)
242	{
243	fL_Branch branch = (fL_Branch )(*openbranchposition);
244	if (branch->btype == fL_Branch::BranchType::OPEN)
245	{
246	int bcount = 1;
247	delete (*openbranchposition);
248	openbranchposition = list->erase(openbranchposition);
249	for (; openbranchposition != list->end(); openbranchposition++)
250	{
251	if ((*openbranchposition)->type == fLElementType::BRANCH)
252	{
253	branch = (fL_Branch )(openbranchposition);
254	if (branch->btype == fL_Branch::BranchType::OPEN)
255	{
256	bcount++;
257	}
258	else
259	{
260	bcount--;
261	if (bcount == 0)
262	{
263	delete branch;
264	list->erase(openbranchposition);
265	break;
266	}
267	}
268	}
269	}
270	}
271	else
272	{
273	openbranchposition++;
274	if (openbranchposition != list->end())
275	{
276	delete (*openbranchposition);
277	list->erase(openbranchposition);
278	}
279	}
280	}
281
282	int Geno_fL::mutate(char *&geno, float& chg, int &method)
283	{
284	fL_Builder *creature = new fL_Builder(false, false);
285
286	if (creature->parseGenotype(geno) != 0)
287	{
288	delete creature;
289	return GENOPER_OPFAIL;
290	}
291
292	int before = creature->countWordsInLSystem();
293
294	method = roulette(operations, FL_OPCOUNT);
295	switch (method)
296	{
297	case FL_CHG_ITER:
298	{
299	if (rndUint(2) == 0)
300	{
301	creature->time = creature->time + iterchangestep <= ExtValue::getDouble(FL_MAXITER) ?
302	creature->time + iterchangestep : creature->time - iterchangestep;
303	}
304	else
305	{
306	creature->time = creature->time - iterchangestep >= 0 ?
307	creature->time - iterchangestep : creature->time + iterchangestep;
308	}
309	break;
310	}
311	case FL_CHG_COND:
312	{
313	if (creature->rules.size() > 0)
314	{
315	int ruleid = rndUint((unsigned int)creature->rules.size());
316	if (!creature->rules[ruleid]->condeval)
317	{
318	creature->rules[ruleid]->condeval = new MathEvaluation(creature->rules[ruleid]->objpred->npar);
319	}
320	creature->rules[ruleid]->condeval->mutateConditional();
321	break;
322	}
323	// if there are no rules - create one
324	}
325	[[fallthrough]];
326	case FL_ADD_RULE:
327	{
328	std::unordered_map<std::string, fL_Word *>::iterator pred = creature->words.begin();
329	std::vector<fL_Word *> wordswithnorules;
330	for (; pred != creature->words.end(); pred++)
331	{
332	if (!pred->second->builtin)
333	{
334	bool norules = true;
335	for (fL_Rule * r : creature->rules)
336	{
337	if (pred->second->name == r->objpred->name &&
338	pred->second->npar == r->objpred->npar)
339	{
340	norules = false;
341	break;
342	}
343	}
344	if (norules)
345	{
346	wordswithnorules.push_back(pred->second);
347	}
348	}
349	}
350	if (wordswithnorules.size() > 0)
351	{
352	int predid = rndUint((unsigned int)wordswithnorules.size());
353	fL_Rule *newrule = new fL_Rule(0, 0);
354	fL_Word *pred = new fL_Word();
355	pred = wordswithnorules[predid];
356	newrule->objpred = pred;
357	fL_Word *initdef = randomWordDefinition(creature, roulette(addtypes, FL_ADD_COUNT - 1)); // -1 to avoid branching
358	addWord(&newrule->objsucc, initdef, newrule->objsucc.begin());
359	creature->rules.push_back(newrule);
360	break;
361	}
362	else if (creature->rules.size() > 0)
363	{
364	int ruleid = rndUint((unsigned int)creature->rules.size());
365	fL_Rule *newrule = new fL_Rule(0, 0);
366	fL_Word *pred = new fL_Word();
367	pred = creature->rules[ruleid]->objpred;
368	newrule->objpred = pred;
369	if (creature->rules[ruleid]->condeval)
370	{
371	std::string formula = "";
372	creature->rules[ruleid]->condeval->RPNToInfix(formula);
373	if (formula.find("1.0-(") != 0)
374	{
375	std::string res = "1.0-(";
376	res += formula;
377	res += ")";
378	newrule->condeval = new MathEvaluation(pred->npar);
379	newrule->condeval->convertString(res);
380	}
381	else
382	{
383	newrule->condeval = new MathEvaluation(pred->npar);
384	newrule->condeval->mutateConditional();
385	}
386	}
387	else
388	{
389	newrule->condeval = new MathEvaluation(pred->npar);
390	newrule->condeval->mutateConditional();
391	}
392	fL_Word *worddef = randomWordDefinition(creature, roulette(addtypes, FL_ADD_COUNT - 1));
393	addWord(&newrule->objsucc, worddef, newrule->objsucc.begin());
394	creature->rules.push_back(newrule);
395	break;
396	}
397	// if there are no words, from which rules can be formed, then add one
398	}
399	[[fallthrough]];
400	case FL_ADD_WDEF:
401	{
402	if (creature->countDefinedWords() <= maxdefinedwords)
403	{
404	int npar = rndUint(ExtValue::getInt(FL_MAXPARAMS, false));
405	for (int i = 0; i < maxdefinedwords; i++)
406	{
407	std::string name = "w";
408	name += std::to_string(i);
409	if (creature->words.find(name) == creature->words.end())
410	{
411	fL_Word *word = new fL_Word(false, 0, 0);
412	word->npar = npar;
413	word->name = name.c_str();
414	word->processDefinition(creature);
415	break;
416	}
417	}
418	break;
419	}
420	//no break at the end of case - if there is too many words, then
421	// deletion should be performed
422	}
423	[[fallthrough]];
424	case FL_DEL_WORD:
425	{
426	int numpars = 0;
427	int ruleid = 0;
428	std::list<fL_Word > list = selectRandomSequence(creature, numpars, ruleid);
429	if (ruleid == -1 && creature->countSticksInSequence(list) == 1)
430	{
431	if (list->size() > 1)
432	{
433	int rndid = rndUint(int(list->size()) - 1);
434	int j = 0;
435	std::list<fL_Word *>::iterator it = list->begin();
436	if ((*it)->name == "S")
437	{
438	it++;
439	}
440	while (it != list->end() && j < rndid && ((*it)->name == "S"))
441	{
442	if ((*it)->name != "S")
443	{
444	j++;
445	}
446	it++;
447	}
448	if (it != list->end())
449	{
450	if ((*it)->type == fLElementType::BRANCH)
451	{
452	deleteBranch(list, it);
453	}
454	else
455	{
456	delete (*it);
457	list->erase(it);
458	}
459	break;
460	}
461	// else add word
462	}
463	// else add word
464	}
465	else
466	{
467	int rndid = rndUint((unsigned int)list->size());
468	std::list<fL_Word *>::iterator it = list->begin();
469	std::advance(it, rndid);
470	if ((*it)->type == fLElementType::BRANCH)
471	{
472	deleteBranch(list, it);
473	}
474	else
475	{
476	delete (*it);
477	list->erase(it);
478	}
479	if (ruleid > -1 && creature->rules[ruleid]->objsucc.size() == 0)
480	{
481	delete creature->rules[ruleid];
482	creature->rules.erase(creature->rules.begin() + ruleid);
483	}
484	break;
485	}
486	// if no words available, then add word
487	}
488	[[fallthrough]];
489	case FL_ADD_WORD:
490	{
491	int numpars = 0;
492	int tmp = 0;
493	std::list<fL_Word > list = selectRandomSequence(creature, numpars, tmp);
494	int rndid = rndUint((unsigned int)list->size());
495	std::list<fL_Word *>::iterator it = list->begin();
496	std::advance(it, rndid);
497	int meth = roulette(addtypes, FL_ADD_COUNT);
498	if (tmp == -1)
499	{ // if sequence is axiom and it does not have non-builtin words
500	bool hasdefined = false;
501	for (std::list<fL_Word *>::iterator elem = list->begin(); elem != list->end(); elem++)
502	{
503	if (!(*elem)->builtin)
504	{
505	hasdefined = true;
506	break;
507	}
508	}
509	if (!hasdefined)
510	{
511	meth = FL_ADD_OTHER;
512	}
513
514	}
515	if (meth != FL_ADD_BRANCH)
516	{
517	fL_Word *worddef = randomWordDefinition(creature, meth);
518	addWord(list, worddef, it);
519	}
520	else
521	{
522	fL_Branch *start = new fL_Branch(fL_Branch::BranchType::OPEN, 0, 0);
523	list->insert(it, start);
524	int rottype = rndUint(2);
525	switch (rottype)
526	{
527	case 0:
528	addWord(list, creature->words["rotY"], it);
529	case 1:
530	addWord(list, creature->words["rotZ"], it);
531	}
532	addWord(list, creature->words["S"], it);
533	fL_Branch *end = new fL_Branch(fL_Branch::BranchType::CLOSE, 0, 0);
534	list->insert(it, end);
535	}
536	break;
537	}
538	case FL_CHG_WORD:
539	{
540	int numpars = 0;
541	int tmp = 0;
542	std::list<fL_Word > list = selectRandomSequence(creature, numpars, tmp);
543	int rndid = rndUint((unsigned int)list->size());
544	std::list<fL_Word *>::iterator selectedword = list->begin();
545	std::advance(selectedword, rndid);
546	if ((*selectedword)->type == fLElementType::BRANCH)
547	{
548	break;
549	}
550	int chgtype = roulette(chgoperations, FL_CHG_COUNT);
551	if (creature->countSticksInSequence(list) == 1 && tmp == -1) // if sequence is axiom
552	{
553	fL_Word *worddef = randomWordDefinition(creature, roulette(addtypes, FL_ADD_COUNT - 1));
554
555	int numpars = 0;
556	std::list<fL_Word > list = selectRandomSequence(creature, numpars, tmp);
557	int rndid = rndUint((unsigned int)list->size());
558	std::list<fL_Word *>::iterator it = list->begin();
559	std::advance(it, rndid);
560
561	addWord(list, worddef, it);
562
563	break;
564	}
565	else if (chgtype == FL_CHG_WORD_NAME)
566	{
567	if ((*selectedword)->builtin)
568	{
569	delete (*selectedword);
570	selectedword = list->erase(selectedword);
571	fL_Word *worddef = randomWordDefinition(creature, roulette(addtypes, FL_ADD_COUNT - 1));
572	addWord(list, worddef, selectedword);
573	}
574	else
575	{
576	std::vector<fL_Word *> available;
577	for (std::unordered_map<std::string, fL_Word *>::iterator wit = creature->words.begin();
578	wit != creature->words.end(); wit++)
579	{
580	if ((*selectedword)->npar == wit->second->npar &&
581	(*selectedword)->name != wit->second->name &&
582	!wit->second->builtin)
583	{
584	available.push_back(wit->second);
585	}
586	}
587	if (available.size() > 0)
588	{
589	int newnameid = rndUint((unsigned int)available.size());
590	(*selectedword)->name = available[newnameid]->name;
591	}
592	else
593	{
594	delete (*selectedword);
595	selectedword = list->erase(selectedword);
596	fL_Word *worddef = randomWordDefinition(creature, roulette(addtypes, FL_ADD_COUNT - 1));
597	addWord(list, worddef, selectedword);
598	}
599	}
600	}
601	else
602	{
603	if ((*selectedword)->npar > 0)
604	{
605	int randeval = rndUint((*selectedword)->npar);
606	Param par((selectedword)->tab, (selectedword)->data);
607	if ((selectedword)->builtin && (selectedword)->name == "N"
608	&& strcmp(par.id(randeval), FL_PE_NEURO_DET) == 0)
609	{
610	SString res = par.getStringById(FL_PE_NEURO_DET);
611	Geno_fH::mutateNeuronProperties(res);
612	par.setStringById(FL_PE_NEURO_DET, res);
613	}
614	else if ((*selectedword)->builtin &&
615	(*selectedword)->name == "C" &&
616	strcmp(par.id(randeval), FL_PE_CONN_ATTR) == 0)
617	{
618	SString strattractor = par.getStringById(FL_PE_CONN_ATTR);
619	if (strattractor.length() > 0)
620	{
621	fL_Word *w = NULL;
622	creature->createWord(strattractor, w, numpars, 0, 0);
623	// mutate attractor parameter
624	if (w->npar > 0)
625	{
626	int rndattr = rndUint(w->npar);
627	if (!w->parevals[rndattr])
628	{
629	w->parevals[rndattr] = new MathEvaluation(numpars);
630	}
631	w->parevals[rndattr]->mutate(false, false);
632	}
633	strattractor = w->stringify(true);
634	par.setStringById(FL_PE_CONN_ATTR, strattractor);
635	delete w;
636	}
637	else
638	{
639	if (creature->builtincount < (int)creature->words.size())
640	{
641	fL_Word *wdef = randomWordDefinition(creature, FL_ADD_OTHER);
642	fL_Word *w = new fL_Word();
643	w = wdef;
644	w->data = ParamObject::makeObject(w->tab);
645	Param apar(w->tab);
646	apar.select(w->data);
647	apar.setDefault();
648	if (w->npar > 0)
649	{
650	int rndattr = rndUint(w->npar);
651	for (int i = 0; i < w->npar; i++)
652	{
653	if (i == rndattr)
654	{
655	MathEvaluation *ev = new MathEvaluation(numpars);
656	ev->mutate(false, false);
657	w->parevals.push_back(ev);
658	}
659	else
660	{
661	w->parevals.push_back(NULL);
662	}
663	}
664
665	}
666	strattractor = w->stringify(false);
667	par.setStringById(FL_PE_CONN_ATTR, strattractor);
668	delete w;
669	}
670	}
671	}
672	else
673	{
674	if (!(*selectedword)->parevals[randeval])
675	{
676	(*selectedword)->parevals[randeval] = new MathEvaluation(numpars);
677	}
678	(*selectedword)->parevals[randeval]->mutate(false, iterchangestep != 1.0);
679	}
680	}
681	}
682	break;
683	}
684	}
685
686	free(geno);
687	geno = strdup(creature->toString().c_str());
688	chg = (double)abs(before - creature->countWordsInLSystem()) / before;
689	delete creature;
690
691	return GENOPER_OK;
692	}
693
694	fL_Word* Geno_fL::getAppropriateWord(fL_Builder from, fL_Builder to, fL_Word *fromword, std::unordered_map<std::string, std::string> &map)
695	{
696	if (fromword->name == "[" \|\| fromword->name == "]") // if words are branching words
697	{
698	fL_Branch *newword = new fL_Branch(fromword->name == "[" ? fL_Branch::BranchType::OPEN : fL_Branch::BranchType::CLOSE, 0, 0);
699	return newword;
700	}
701	if (fromword->builtin)
702	{
703	fL_Word *newword = new fL_Word();
704	(newword) = (to->words[fromword->name.c_str()]);
705	return newword;
706	}
707	if (map.find(fromword->name.c_str()) != map.end()) // if word is already mapped
708	{
709	fL_Word *newword = new fL_Word();
710	(newword) = (to->words[map[fromword->name.c_str()]]);
711	return newword;
712	}
713	else if (to->words.find(fromword->name.c_str()) != to->words.end() &&
714	to->words[fromword->name.c_str()]->npar == fromword->npar) // if there is already same word with same number of parameters
715	{
716	fL_Word *newword = new fL_Word();
717	map[fromword->name.c_str()] = fromword->name.c_str();
718	(newword) = (to->words[map[fromword->name.c_str()]]);
719	return newword;
720	}
721	for (std::unordered_map<std::string, fL_Word *>::iterator it = to->words.begin();
722	it != to->words.end(); it++)
723	{ // find word with same number of parameters
724	if (fromword->npar == it->second->npar && map.find(fromword->name.c_str()) == map.end() && !it->second->builtin)
725	{ // if there is a word with same number of parameters
726	map[fromword->name.c_str()] = it->second->name.c_str();
727	fL_Word *newword = new fL_Word();
728	(newword) = (it->second);
729	return newword;
730	}
731	}
732	fL_Word *newworddef = new fL_Word();
733	(newworddef) = (fromword);
734	newworddef->parevals.clear();
735	if (to->words.find(newworddef->name.c_str()) != to->words.end())
736	{
737	int i = 0;
738	while (true)
739	{
740	std::string name = "w";
741	name += std::to_string(i);
742	if (to->words.find(name) == to->words.end())
743	{
744	newworddef->name = name.c_str();
745	break;
746	}
747	i++;
748	}
749	}
750	newworddef->processDefinition(to);
751	map[fromword->name.c_str()] = newworddef->name.c_str();
752	fL_Word *newword = new fL_Word();
753	(newword) = (to->words[map[fromword->name.c_str()]]);
754	return newword;
755	}
756
757	void Geno_fL::migrateRandomRules(fL_Builder from, fL_Builder to, int numselrules)
758	{
759	std::unordered_map<std::string, std::string> map;
760	if (from->rules.size() > 0)
761	{
762	for (int i = 0; i < numselrules; i++)
763	{
764	int rulid = rndUint((unsigned int)from->rules.size());
765	fL_Rule *rul = from->rules[rulid];
766	fL_Rule *newrule = new fL_Rule(0, 0);
767	newrule->objpred = getAppropriateWord(from, to, rul->objpred, map);
768	for (fL_Word *w : rul->objsucc)
769	{
770	fL_Word *el = getAppropriateWord(from, to, w, map);
771	if (el->type == fLElementType::BRANCH)
772	{
773	newrule->objsucc.push_back(el);
774	continue;
775	}
776	Param origpar(w->tab);
777	origpar.select(w->data);
778	el->data = ParamObject::makeObject(el->tab);
779	Param par(el->tab);
780	par.select(el->data);
781	par.setDefault();
782	for (int i = 0; i < el->npar; i++)
783	{
784	std::string form;
785	if (w->builtin && w->name == "N"
786	&& strcmp(par.id(i), FL_PE_NEURO_DET) == 0)
787	{
788	SString res = origpar.getStringById(FL_PE_NEURO_DET);
789	par.setStringById(FL_PE_NEURO_DET, res);
790	el->parevals.push_back(NULL);
791	}
792	else if (w->builtin && w->name == "C"
793	&& strcmp(par.id(i), FL_PE_CONN_ATTR) == 0)
794	{
795	SString strattractor = origpar.getStringById(FL_PE_CONN_ATTR);
796	if (strattractor.length() > 0)
797	{
798	fL_Word *tmp = NULL;
799	from->createWord(strattractor, tmp, newrule->objpred->npar, 0, 0);
800	fL_Word *newsuccword = getAppropriateWord(from, to, tmp, map);
801	newsuccword->data = ParamObject::makeObject(el->tab);
802	newsuccword->parevals = tmp->parevals;
803	tmp->parevals.clear();
804	strattractor = newsuccword->stringify(true);
805	par.setStringById(FL_PE_CONN_ATTR, strattractor);
806	delete newsuccword;
807	delete tmp;
808	}
809	par.setStringById(FL_PE_CONN_ATTR, strattractor);
810	el->parevals.push_back(NULL);
811	}
812	else if (w->parevals[i])
813	{
814	MathEvaluation *eval = new MathEvaluation(newrule->objpred->npar);
815	w->parevals[i]->RPNToInfix(form);
816	eval->convertString(form);
817	el->parevals.push_back(eval);
818	}
819	else
820	{
821	el->parevals.push_back(NULL);
822	}
823	}
824	newrule->objsucc.push_back(el);
825	}
826	to->rules.push_back(newrule);
827	}
828	}
829	}
830
831	int Geno_fL::crossOver(char &g1, char &g2, float& chg1, float& chg2)
832	{
833	fL_Builder *creature1 = new fL_Builder(false, false);
834	fL_Builder *creature1template = new fL_Builder(false, false);
835	fL_Builder *creature2 = new fL_Builder(false, false);
836	fL_Builder *creature2template = new fL_Builder(false, false);
837
838	int count1 = creature1->countWordsInLSystem();
839	int count2 = creature2->countWordsInLSystem();
840
841	if (creature1->parseGenotype(g1) != 0 \|\| creature2->parseGenotype(g2) != 0)
842	{
843	delete creature1;
844	delete creature2;
845	delete creature1template;
846	delete creature2template;
847	return GENOPER_OPFAIL;
848	}
849
850	creature1template->parseGenotype(g1);
851	creature2template->parseGenotype(g2);
852
853	int numselrules = 1 + rndUint(XOVER_MAX_MIGRATED_RULES);
854	numselrules = numselrules < (int)creature1->rules.size() ? numselrules : (int)creature1->rules.size();
855
856	migrateRandomRules(creature1template, creature2, numselrules);
857
858	numselrules = 1 + rndUint(XOVER_MAX_MIGRATED_RULES);
859	numselrules = numselrules < (int)creature1->rules.size() ? numselrules : (int)creature1->rules.size();
860
861	migrateRandomRules(creature2template, creature1, numselrules);
862
863	free(g1);
864	free(g2);
865
866	g1 = strdup(creature1->toString().c_str());
867	g2 = strdup(creature2->toString().c_str());
868
869	chg1 = (double)count1 / creature1->countWordsInLSystem();
870	chg1 = (double)count2 / creature2->countWordsInLSystem();
871
872	delete creature1;
873	delete creature2;
874	delete creature1template;
875	delete creature2template;
876
877	return GENOPER_OK;
878	}
879
880	uint32_t Geno_fL::style(const char *geno, int pos)
881	{
882	char ch = geno[pos];
883	uint32_t style = GENSTYLE_CS(0, GENSTYLE_STRIKEOUT);
884	if (pos == 0 \|\| geno[pos - 1] == '\n' \|\| ch == ':') // single-character line definition
885	{
886	style = GENSTYLE_CS(GENCOLOR_TEXT, GENSTYLE_BOLD);
887	}
888	else if (strchr("()", ch) != NULL)
889	{
890	style = GENSTYLE_RGBS(50, 50, 50, GENSTYLE_BOLD);
891	}
892	else if (isalpha(ch)) // properties name
893	{
894	style = GENSTYLE_RGBS(0, 200, 0, GENSTYLE_BOLD);
895	}
896	else if (isdigit(ch) \|\| strchr(",.=", ch)) // properties values
897	{
898	style = GENSTYLE_CS(GENCOLOR_TEXT, GENSTYLE_NONE);
899	}
900	else if (ch == '\"')
901	{
902	style = GENSTYLE_RGBS(200, 0, 0, GENSTYLE_BOLD);
903	}
904	else if (strchr("<>$[]&\\ @\|*", ch) != NULL) // other allowed symbols and special neuron symbols
905	{
906	style = GENSTYLE_CS(GENCOLOR_TEXT, ch == '[' \|\| ch == ']' ? GENSTYLE_BOLD : GENSTYLE_NONE);
907	}
908	return style;
909	}

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