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source: cpp/frams/genetics/fS/fS_oper.cpp @ 1026

Last change on this file since 1026 was 1017, checked in by Maciej Komosinski, 4 years ago
fS: faster collision detection, depends on "geometry" algorithms
File size: 23.0 KB

Rev	Line
[958]	1	// This file is a part of Framsticks SDK. http://www.framsticks.com/
	2	// Copyright (C) 2019-2020 Maciej Komosinski and Szymon Ulatowski.
	3	// See LICENSE.txt for details.
	4
	5	#include <float.h>
	6	#include <assert.h>
	7	#include "fS_oper.h"
	8	#include "frams/util/rndutil.h"
	9
	10	#define FIELDSTRUCT GenoOper_fS
[974]	11	static ParamEntry genooper_fS_paramtab[] =
[958]	12	{
	13	{"Genetics: fS", 1, FS_OPCOUNT + 5,},
[1000]	14	{"fS_mut_add_part", 0, 0, "Add part", "f 0 100 10", FIELD(prob[FS_ADD_PART]), "mutation: probability of adding a part",},
	15	{"fS_mut_rem_part", 0, 0, "Remove part", "f 0 100 10", FIELD(prob[FS_REM_PART]), "mutation: probability of deleting a part",},
	16	{"fS_mut_mod_part", 0, 0, "Modify part", "f 0 100 10", FIELD(prob[FS_MOD_PART]), "mutation: probability of changing the part type",},
	17	{"fS_mut_change_joint", 0, 0, "Change joint", "f 0 100 10", FIELD(prob[FS_CHANGE_JOINT]), "mutation: probability of changing a joint",},
	18	{"fS_mut_add_param", 0, 0, "Add param", "f 0 100 10", FIELD(prob[FS_ADD_PARAM]), "mutation: probability of adding a parameter",},
	19	{"fS_mut_rem_param", 0, 0, "Remove param", "f 0 100 10", FIELD(prob[FS_REM_PARAM]), "mutation: probability of removing a parameter",},
	20	{"fS_mut_mod_param", 0, 0, "Modify param", "f 0 100 10", FIELD(prob[FS_MOD_PARAM]), "mutation: probability of modifying a parameter",},
	21	{"fS_mut_mod_mod", 0, 0, "Modify modifier", "f 0 100 10", FIELD(prob[FS_MOD_MOD]), "mutation: probability of modifying a modifier",},
	22	{"fS_mut_add_neuro", 0, 0, "Add neuron", "f 0 100 10", FIELD(prob[FS_ADD_NEURO]), "mutation: probability of adding a neuron",},
	23	{"fS_mut_rem_neuro", 0, 0, "Remove neuron", "f 0 100 10", FIELD(prob[FS_REM_NEURO]), "mutation: probability of removing a neuron",},
	24	{"fS_mut_mod_neuro_conn", 0, 0, "Modify neuron connection", "f 0 100 10", FIELD(prob[FS_MOD_NEURO_CONNECTION]), "mutation: probability of changing a neuron connection",},
	25	{"fS_mut_add_neuro_conn", 0, 0, "Add neuron connection", "f 0 100 10", FIELD(prob[FS_ADD_NEURO_CONNECTION]), "mutation: probability of adding a neuron connection",},
[1017]	26	{"fS_mut_rem_neuro_conn", 0, 0, "Remove neuron connection", "f 0 100 10", FIELD(prob[FS_REM_NEURO_CONNECTION]), "mutation: probability of removing a neuron connection",},
[1000]	27	{"fS_mut_mod_neuro_params", 0, 0, "Modify neuron params", "f 0 100 10", FIELD(prob[FS_MOD_NEURO_PARAMS]), "mutation: probability of changing a neuron param",},
	28	{"fS_circle_section", 0, 0, "Ensure circle section", "d 0 1 1", FIELD(ensureCircleSection), "Ensure that ellipsoids and cylinders have circle cross-section"},
	29	{"fS_use_elli", 0, 0, "Use ellipsoids in mutations", "d 0 1 1", FIELD(useElli), "Use ellipsoids in mutations"},
	30	{"fS_use_cub", 0, 0, "Use cuboids in mutations", "d 0 1 1", FIELD(useCub), "Use cuboids in mutations"},
	31	{"fS_use_cyl", 0, 0, "Use cylinders in mutations", "d 0 1 1", FIELD(useCyl), "Use cylinders in mutations"},
	32	{"fS_mut_add_part_strong", 0, 0, "Strong add part mutation", "d 0 1 1", FIELD(strongAddPart), "Add part mutation will produce more parametrized parts"},
[958]	33	};
	34
	35	#undef FIELDSTRUCT
	36
	37	GenoOper_fS::GenoOper_fS()
	38	{
[974]	39	par.setParamTab(genooper_fS_paramtab);
[958]	40	par.select(this);
	41	par.setDefault();
[969]	42	supported_format = 'S';
[958]	43	}
	44
	45	int GenoOper_fS::checkValidity(const char geno, const char genoname)
	46	{
	47	try
	48	{
	49	fS_Genotype genotype(geno);
	50	int errorPosition = genotype.checkValidityOfPartSizes();
[1000]	51	if (errorPosition != 0)
[958]	52	{
[1000]	53	logPrintf("GenoOper_fS", "checkValidity", LOG_WARN, "Invalid part size");
[969]	54	return errorPosition;
[958]	55	}
	56	}
	57	catch (fS_Exception &e)
	58	{
[1000]	59	logPrintf("GenoOper_fS", "checkValidity", LOG_WARN, e.what());
[958]	60	return 1 + e.errorPosition;
	61	}
	62	return 0;
	63	}
	64
	65
	66	int GenoOper_fS::mutate(char *&geno, float &chg, int &method)
	67	{
[1000]	68	try
	69	{
	70	fS_Genotype genotype(geno);
[958]	71
[1000]	72	// Calculate available part types
	73	vector <Part::Shape> availablePartShapes;
	74	if (useElli)
	75	availablePartShapes.push_back(Part::Shape::SHAPE_ELLIPSOID);
	76	if (useCub)
	77	availablePartShapes.push_back(Part::Shape::SHAPE_CUBOID);
	78	if (useCyl)
	79	availablePartShapes.push_back(Part::Shape::SHAPE_CYLINDER);
[958]	80
[1000]	81	// Select a mutation
	82	bool result = false;
	83	method = GenoOperators::roulette(prob, FS_OPCOUNT);
	84	switch (method)
	85	{
	86	case FS_ADD_PART:
	87	result = addPart(genotype, availablePartShapes);
	88	break;
	89	case FS_REM_PART:
	90	result = removePart(genotype);
	91	break;
	92	case FS_MOD_PART:
	93	result = changePartType(genotype, availablePartShapes);
	94	break;
	95	case FS_CHANGE_JOINT:
	96	result = changeJoint(genotype);
	97	break;
	98	case FS_ADD_PARAM:
	99	result = addParam(genotype);
	100	break;
	101	case FS_REM_PARAM:
	102	result = removeParam(genotype);
	103	break;
	104	case FS_MOD_PARAM:
	105	result = changeParam(genotype);
	106	break;
	107	case FS_MOD_MOD:
	108	result = changeModifier(genotype);
	109	break;
	110	case FS_ADD_NEURO:
	111	result = addNeuro(genotype);
	112	break;
	113	case FS_REM_NEURO:
	114	result = removeNeuro(genotype);
	115	break;
	116	case FS_MOD_NEURO_CONNECTION:
	117	result = changeNeuroConnection(genotype);
	118	break;
	119	case FS_ADD_NEURO_CONNECTION:
	120	result = addNeuroConnection(genotype);
	121	break;
	122	case FS_REM_NEURO_CONNECTION:
	123	result = removeNeuroConnection(genotype);
	124	break;
	125	case FS_MOD_NEURO_PARAMS:
	126	result = changeNeuroParam(genotype);
	127	break;
	128	}
	129
	130	if (result)
	131	{
	132	free(geno);
	133	geno = strdup(genotype.getGeno().c_str());
	134	return GENOPER_OK;
	135	}
	136	return GENOPER_OPFAIL;
[958]	137	}
[1000]	138	catch (fS_Exception &e)
[958]	139	{
[1000]	140	logPrintf("GenoOper_fS", "mutate", LOG_WARN, e.what());
	141	return GENOPER_OPFAIL;
[958]	142	}
	143	}
	144
	145	int GenoOper_fS::crossOver(char &g0, char &g1, float &chg0, float &chg1)
	146	{
[1000]	147	try
	148	{
	149	assert(PARENT_COUNT == 2); // Cross over works only for 2 parents
	150	fS_Genotype *parents[PARENT_COUNT] = {new fS_Genotype(g0), new fS_Genotype(g1)};
[958]	151
[1000]	152	// Choose random subtrees that have similar size
	153	Node *selected[PARENT_COUNT];
	154	vector < Node * > allNodes0 = parents[0]->getAllNodes();
	155	vector < Node * > allNodes1 = parents[1]->getAllNodes();
[958]	156
[1000]	157	double bestQuotient = DBL_MAX;
	158	for (int i = 0; i < crossOverTries; i++)
[958]	159	{
[1000]	160	Node *tmp0 = allNodes0[rndUint(allNodes0.size())];
	161	Node *tmp1 = allNodes1[rndUint(allNodes1.size())];
	162	// Choose this pair if it is the most similar
	163	double quotient = double(tmp0->getNodeCount()) / double(tmp1->getNodeCount());
	164	if (quotient < 1.0)
	165	quotient = 1.0 / quotient;
	166	if (quotient < bestQuotient)
	167	{
	168	bestQuotient = quotient;
	169	selected[0] = tmp0;
	170	selected[1] = tmp1;
	171	}
	172	if (bestQuotient == 1.0)
	173	break;
[958]	174	}
	175
[1000]	176	// Compute gene percentages in children
	177	double subtreeSizes[PARENT_COUNT], restSizes[PARENT_COUNT];
	178	for (int i = 0; i < PARENT_COUNT; i++)
	179	{
[958]	180
[1000]	181	subtreeSizes[i] = selected[i]->getNodeCount();
	182	restSizes[i] = parents[i]->getNodeCount() - subtreeSizes[i];
	183	}
	184	chg0 = restSizes[0] / (restSizes[0] + subtreeSizes[1]);
	185	chg1 = restSizes[1] / (restSizes[1] + subtreeSizes[0]);
[958]	186
[1000]	187	// Rearrange neurons before crossover
	188	int subOldStart[PARENT_COUNT] {-1, -1};
	189	rearrangeConnectionsBeforeCrossover(parents[0], selected[0], subOldStart[0]);
	190	rearrangeConnectionsBeforeCrossover(parents[1], selected[1], subOldStart[1]);
[958]	191
[1000]	192	// Swap the subtress
	193	for (int i = 0; i < PARENT_COUNT; i++)
[958]	194	{
[1000]	195	Node *other = selected[1 - i];
	196	Node *p = selected[i]->parent;
	197	if (p != nullptr)
	198	{
	199	size_t index = std::distance(p->children.begin(), std::find(p->children.begin(), p->children.end(), selected[i]));
	200	p->children[index] = other;
	201	} else
	202	parents[i]->startNode = other;
	203	}
[958]	204
[1000]	205	// Rearrange neurons after crossover
	206	rearrangeConnectionsAfterCrossover(parents[0], selected[1], subOldStart[0]);
	207	rearrangeConnectionsAfterCrossover(parents[1], selected[0], subOldStart[1]);
[958]	208
[1000]	209	// Clenup, assign children to result strings
	210	free(g0);
	211	free(g1);
	212	g0 = strdup(parents[0]->getGeno().c_str());
	213	g1 = strdup(parents[1]->getGeno().c_str());
[958]	214
[1000]	215	delete parents[0];
	216	delete parents[1];
	217	}
	218	catch (fS_Exception &e)
	219	{
	220	logPrintf("GenoOper_fS", "crossOver", LOG_WARN, e.what());
	221	return GENOPER_OPFAIL;
	222	}
[958]	223	return GENOPER_OK;
	224	}
	225
[1000]	226	const char *GenoOper_fS::getSimplest()
[958]	227	{
[1000]	228	return "1.1:C{x=0.80599;y=0.80599;z=0.80599}";
[958]	229	}
	230
	231	uint32_t GenoOper_fS::style(const char *geno, int pos)
	232	{
	233	char ch = geno[pos];
	234	uint32_t style = GENSTYLE_CS(0, GENSTYLE_NONE);
	235	if (ch == ELLIPSOID \|\| ch == CUBOID \|\| ch == CYLINDER) // part type
	236	{
	237	style = GENSTYLE_RGBS(0, 0, 200, GENSTYLE_BOLD);
[1000]	238	} else if (JOINTS.find(ch) != string::npos) // Joint type
[958]	239	{
	240	style = GENSTYLE_RGBS(0, 200, 200, GENSTYLE_BOLD);
[1000]	241	} else if (MODIFIERS.find(ch) != string::npos) // Modifier
[958]	242	{
	243	style = GENSTYLE_RGBS(0, 200, 0, GENSTYLE_NONE);
[1000]	244	} else if (isdigit(ch) \|\| strchr(".", ch)) // Numerical value
[958]	245	{
	246	style = GENSTYLE_RGBS(200, 0, 0, GENSTYLE_NONE);
[1000]	247	} else if (strchr("()_;[],=", ch))
[958]	248	{
	249	style = GENSTYLE_CS(0, GENSTYLE_BOLD); // Important char
	250	}
	251
	252	return style;
	253	}
	254
	255	void GenoOper_fS::rearrangeConnectionsBeforeCrossover(fS_Genotype geno, Node sub, int &subStart)
	256	{
[1000]	257	vector < fS_Neuron * > genoNeurons = geno->getAllNeurons();
	258	vector < fS_Neuron * > subNeurons = fS_Genotype::extractNeurons(sub);
[958]	259
	260	if (!subNeurons.empty())
	261	{
	262	subStart = fS_Genotype::getNeuronIndex(genoNeurons, subNeurons[0]);
	263	fS_Genotype::shiftNeuroConnections(genoNeurons, subStart, subStart + subNeurons.size() - 1, SHIFT::LEFT);
	264	}
	265	}
	266
	267	void GenoOper_fS::rearrangeConnectionsAfterCrossover(fS_Genotype geno, Node sub, int subOldStart)
	268	{
[1000]	269	vector < fS_Neuron * > genoNeurons = geno->getAllNeurons();
	270	vector < fS_Neuron * > subNeurons = fS_Genotype::extractNeurons(sub);
[958]	271
	272	// Shift the inputs right
	273	if (!subNeurons.empty())
	274	{
	275	int subStart = fS_Genotype::getNeuronIndex(genoNeurons, subNeurons[0]);
	276	int subCount = subNeurons.size();
	277	int subEnd = subStart + subCount - 1;
	278	for (int i = 0; i < subCount; i++)
	279	{
	280	auto inputs = subNeurons[i]->inputs;
	281	std::map<int, double> newInputs;
	282	// TODO figure out how to keep internal connections in subtree
	283	// for (auto it = inputs.begin(); it != inputs.end(); ++it)
	284	// {
	285	// int newIndex = it->first + subStart;
	286	// if(subEnd > newIndex && newIndex > subStart)
	287	// newInputs[newIndex] = it->second;
	288	// }
	289	subNeurons[i]->inputs = newInputs;
	290	}
	291	fS_Genotype::shiftNeuroConnections(genoNeurons, subStart, subEnd, SHIFT::RIGHT);
	292	}
	293	}
	294
[1000]	295	bool GenoOper_fS::addPart(fS_Genotype &geno, const vector <Part::Shape> &availablePartShapes, bool mutateSize)
[958]	296	{
[1017]	297	geno.getState(false);
[958]	298	Node *node = geno.chooseNode();
[1006]	299	char partType = SHAPE_TO_GENE.at(availablePartShapes[rndUint(availablePartShapes.size())]);
[958]	300
	301	Substring substring(&partType, 0, 1);
[1000]	302	Node *newNode = new Node(substring, node, node->genotypeParams);
[958]	303	// Add random rotation
[1000]	304	string rotationParams[] {ROT_X, ROT_Y, ROT_Z};
	305	if (strongAddPart)
[958]	306	{
[1000]	307	for (int i = 0; i < 3; i++)
[969]	308	newNode->params[rotationParams[i]] = RndGen.Uni(-M_PI / 2, M_PI / 2);
[1000]	309	} else
[958]	310	{
	311	string selectedParam = rotationParams[rndUint(3)];
[969]	312	newNode->params[selectedParam] = RndGen.Uni(-M_PI / 2, M_PI / 2);
[958]	313	}
[1000]	314	string rParams[] {RX, RY, RZ};
	315	if (strongAddPart)
[958]	316	{
[1000]	317	for (int i = 0; i < 3; i++)
[969]	318	newNode->params[rParams[i]] = RndGen.Uni(-M_PI / 2, M_PI / 2);
[1000]	319	} else
[958]	320	{
	321	string selectedParam = rParams[rndUint(3)];
[969]	322	newNode->params[selectedParam] = RndGen.Uni(-M_PI / 2, M_PI / 2);
[958]	323	}
	324	// Assign part size to default value
	325	double volumeMultiplier = pow(node->getParam(SIZE) * node->state->s, 3);
	326	double minVolume = Model::getMinPart().volume;
	327	double defVolume = Model::getDefPart().volume * volumeMultiplier; // Default value after applying modifiers
	328	double maxVolume = Model::getMaxPart().volume;
	329	double volume = std::min(maxVolume, std::max(minVolume, defVolume));
	330	double relativeVolume = volume / volumeMultiplier; // Volume without applying modifiers
	331
[969]	332	double newRadius = std::cbrt(relativeVolume / volumeMultipliers.at(newNode->partType));
[958]	333	newNode->params[SIZE_X] = newRadius;
	334	newNode->params[SIZE_Y] = newRadius;
	335	newNode->params[SIZE_Z] = newRadius;
	336	node->children.push_back(newNode);
	337
	338	if (mutateSize)
	339	{
[1017]	340	geno.getState(false);
[1006]	341	mutateSizeParam(newNode, SIZE_X, true);
	342	mutateSizeParam(newNode, SIZE_Y, true);
	343	mutateSizeParam(newNode, SIZE_Z, true);
[958]	344	}
	345	return true;
	346	}
	347
	348	bool GenoOper_fS::removePart(fS_Genotype &geno)
	349	{
	350	Node randomNode, selectedChild;
	351	// Choose a parent with children
[1017]	352	// It may be difficult to choose a eligible node, so the number of tries should be high
	353	for (int i = 0; i < 10 * mutationTries; i++)
[958]	354	{
	355	randomNode = geno.chooseNode();
	356	int childCount = randomNode->children.size();
	357	if (childCount > 0)
	358	{
	359	int selectedIndex = rndUint(childCount);
	360	selectedChild = randomNode->children[selectedIndex];
	361	if (selectedChild->children.empty() && selectedChild->neurons.empty())
	362	{
	363	// Remove the selected child
	364	swap(randomNode->children[selectedIndex], randomNode->children[childCount - 1]);
	365	randomNode->children.pop_back();
	366	randomNode->children.shrink_to_fit();
	367	delete selectedChild;
	368	return true;
	369	}
	370	}
	371	}
	372	return false;
	373	}
	374
[1000]	375	bool GenoOper_fS::changePartType(fS_Genotype &geno, const vector <Part::Shape> &availablePartShapes)
[958]	376	{
[1000]	377	int availShapesLen = availablePartShapes.size();
[958]	378	for (int i = 0; i < mutationTries; i++)
	379	{
	380	Node *randomNode = geno.chooseNode();
[1000]	381	int index = rndUint(availShapesLen);
	382	if (availablePartShapes[index] == randomNode->partType)
	383	index = (index + 1 + rndUint(availShapesLen - 1)) % availShapesLen;
	384	Part::Shape newType = availablePartShapes[index];
[958]	385
	386	#ifdef _DEBUG
	387	if(newType == randomNode->partType)
	388	throw fS_Exception("Internal error: invalid part type chosen in mutation.", 1);
	389	#endif
	390
[1017]	391	geno.getState(false);
[969]	392	double sizeMultiplier = randomNode->getParam(SIZE) * randomNode->state->s;
	393	double relativeVolume = randomNode->calculateVolume() / pow(sizeMultiplier, 3.0);
	394
[1000]	395	if (!ensureCircleSection \|\| newType == Part::Shape::SHAPE_CUBOID \|\| (randomNode->partType == Part::Shape::SHAPE_ELLIPSOID && newType == Part::Shape::SHAPE_CYLINDER))
[958]	396	{
[969]	397	double radiusQuotient = std::cbrt(volumeMultipliers.at(randomNode->partType) / volumeMultipliers.at(newType));
	398	randomNode->params[SIZE_X] = randomNode->getParam(SIZE_X) * radiusQuotient;
	399	randomNode->params[SIZE_Y] = randomNode->getParam(SIZE_Y) * radiusQuotient;
	400	randomNode->params[SIZE_Z] = randomNode->getParam(SIZE_Z) * radiusQuotient;
[1000]	401	} else if (randomNode->partType == Part::Shape::SHAPE_CUBOID && newType == Part::Shape::SHAPE_CYLINDER)
[969]	402	{
	403	double newRadius = 0.5 * (randomNode->getParam(SIZE_X) + randomNode->getParam(SIZE_Y));
[1000]	404	randomNode->params[SIZE_X] = 0.5 * relativeVolume / (M_PI * newRadius * newRadius);
[969]	405	randomNode->params[SIZE_Y] = newRadius;
[1000]	406	randomNode->params[SIZE_Z] = newRadius;
	407	} else if (newType == Part::Shape::SHAPE_ELLIPSOID)
[969]	408	{
	409	double newRelativeRadius = cbrt(relativeVolume / volumeMultipliers.at(newType));
	410	randomNode->params[SIZE_X] = newRelativeRadius;
	411	randomNode->params[SIZE_Y] = newRelativeRadius;
	412	randomNode->params[SIZE_Z] = newRelativeRadius;
[1000]	413	} else
[969]	414	{
	415	throw fS_Exception("Invalid part type", 1);
	416	}
[958]	417	randomNode->partType = newType;
	418	return true;
	419	}
	420	return false;
	421	}
	422
[969]	423	bool GenoOper_fS::changeJoint(fS_Genotype &geno)
[958]	424	{
	425	if (geno.startNode->children.empty())
	426	return false;
	427
[969]	428	Node *randomNode = geno.chooseNode(1); // First part does not have joints
[1000]	429	int jointLen = ALL_JOINTS.length();
[969]	430	int index = rndUint(jointLen);
	431	if (ALL_JOINTS[index] == randomNode->joint)
	432	index = (index + 1 + rndUint(jointLen - 1)) % jointLen;
[958]	433
[969]	434	randomNode->joint = ALL_JOINTS[index];
	435	return true;
[958]	436	}
	437
	438	bool GenoOper_fS::addParam(fS_Genotype &geno)
	439	{
	440	Node *randomNode = geno.chooseNode();
	441	int paramCount = randomNode->params.size();
	442	if (paramCount == int(PARAMS.size()))
	443	return false;
[969]	444	string key = PARAMS[rndUint(PARAMS.size())];
	445	if (randomNode->params.count(key) > 0)
[958]	446	return false;
	447	// Do not allow invalid changes in part size
[1000]	448	bool isRadiusOfBase = key == SIZE_Y \|\| key == SIZE_Z;
	449	bool isRadius = isRadiusOfBase \|\| key == SIZE_X;
[958]	450	if (ensureCircleSection && isRadius)
	451	{
	452	if (randomNode->partType == Part::Shape::SHAPE_ELLIPSOID)
	453	return false;
	454	if (randomNode->partType == Part::Shape::SHAPE_CYLINDER && isRadiusOfBase)
	455	return false;
	456	}
	457	// Add modified default value for param
[1017]	458	randomNode->params[key] = randomNode->defaultValues.at(key);
	459	geno.getState(false);
	460	return mutateParamValue(randomNode, key);
[958]	461	}
	462
	463	bool GenoOper_fS::removeParam(fS_Genotype &geno)
	464	{
	465	// Choose a node with params
	466	for (int i = 0; i < mutationTries; i++)
	467	{
	468	Node *randomNode = geno.chooseNode();
	469	int paramCount = randomNode->params.size();
	470	if (paramCount >= 1)
	471	{
	472	auto it = randomNode->params.begin();
	473	advance(it, rndUint(paramCount));
[1017]	474	string key = it->first;
	475	double value = it->second;
	476
	477	randomNode->params.erase(key);
	478	if(geno.checkValidityOfPartSizes() == 0)
	479	return true;
	480	else
	481	{
	482	randomNode->params[key] = value;
	483	}
[958]	484	}
	485	}
	486	return false;
	487	}
	488
[1017]	489
	490	bool GenoOper_fS::mutateParamValue(Node *node, string key)
	491	{
	492	// Do not allow invalid changes in part size
	493	if (std::find(SIZE_PARAMS.begin(), SIZE_PARAMS.end(), key) == SIZE_PARAMS.end())
	494	{
	495	node->params[key] = GenoOperators::mutateCreep('f', node->getParam(key), Node::minValues.at(key), Node::maxValues.at(key), true);
	496	return true;
	497	} else
	498	return mutateSizeParam(node, key, ensureCircleSection);
	499	}
	500
[958]	501	bool GenoOper_fS::changeParam(fS_Genotype &geno)
	502	{
[1017]	503	geno.getState(false);
[958]	504	for (int i = 0; i < mutationTries; i++)
	505	{
	506	Node *randomNode = geno.chooseNode();
	507	int paramCount = randomNode->params.size();
	508	if (paramCount >= 1)
	509	{
	510	auto it = randomNode->params.begin();
	511	advance(it, rndUint(paramCount));
[1017]	512	return mutateParamValue(randomNode, it->first);
[958]	513	}
	514	}
	515	return false;
	516	}
	517
	518	bool GenoOper_fS::changeModifier(fS_Genotype &geno)
	519	{
	520	Node *randomNode = geno.chooseNode();
	521	char randomModifier = MODIFIERS[rndUint(MODIFIERS.length())];
[1017]	522	int oldValue = randomNode->modifiers[randomModifier];
	523
[958]	524	randomNode->modifiers[randomModifier] += rndUint(2) == 0 ? 1 : -1;
	525
	526	bool isSizeMod = tolower(randomModifier) == SIZE_MODIFIER;
	527	if (isSizeMod && geno.checkValidityOfPartSizes() != 0)
	528	{
[1017]	529	randomNode->modifiers[randomModifier] = oldValue;
[958]	530	return false;
	531	}
	532	return true;
	533	}
	534
	535	bool GenoOper_fS::addNeuro(fS_Genotype &geno)
	536	{
	537	Node *randomNode = geno.chooseNode();
	538	fS_Neuron *newNeuron;
[1000]	539	NeuroClass *rndclass = GenoOperators::getRandomNeuroClass(Model::SHAPETYPE_SOLIDS);
	540	if (rndclass->preflocation == NeuroClass::PREFER_JOINT && randomNode == geno.startNode)
[958]	541	return false;
	542
	543	const char *name = rndclass->getName().c_str();
	544	newNeuron = new fS_Neuron(name, randomNode->partDescription->start, strlen(name));
	545	int effectiveInputCount = rndclass->prefinputs > -1 ? rndclass->prefinputs : 1;
	546	if (effectiveInputCount > 0)
	547	{
	548	// Create as many connections for the neuron as possible (at most prefinputs)
[1000]	549	vector < fS_Neuron * > allNeurons = geno.getAllNeurons();
[958]	550	vector<int> neuronsWithOutput;
	551	for (int i = 0; i < int(allNeurons.size()); i++)
	552	{
	553	if (allNeurons[i]->getClass()->prefoutput > 0)
	554	neuronsWithOutput.push_back(i);
	555	}
	556	int size = neuronsWithOutput.size();
	557	if (size > 0)
	558	{
	559	for (int i = 0; i < effectiveInputCount; i++)
	560	{
	561	int selectedNeuron = neuronsWithOutput[rndUint(size)];
	562	newNeuron->inputs[selectedNeuron] = DEFAULT_NEURO_CONNECTION_WEIGHT;
	563	}
	564	}
	565	}
	566
	567	randomNode->neurons.push_back(newNeuron);
	568
	569	geno.rearrangeNeuronConnections(newNeuron, SHIFT::RIGHT);
	570	return true;
	571	}
	572
	573	bool GenoOper_fS::removeNeuro(fS_Genotype &geno)
	574	{
	575	Node *randomNode = geno.chooseNode();
	576	for (int i = 0; i < mutationTries; i++)
	577	{
	578	randomNode = geno.chooseNode();
	579	if (!randomNode->neurons.empty())
	580	{
	581	// Remove the selected neuron
	582	int size = randomNode->neurons.size();
	583	fS_Neuron *it = randomNode->neurons[rndUint(size)];
	584	geno.rearrangeNeuronConnections(it, SHIFT::LEFT); // Important to rearrange the neurons before deleting
	585	swap(it, randomNode->neurons.back());
	586	randomNode->neurons.pop_back();
	587	randomNode->neurons.shrink_to_fit();
	588	delete it;
	589	return true;
	590	}
	591	}
	592	return false;
	593	}
	594
	595	bool GenoOper_fS::changeNeuroConnection(fS_Genotype &geno)
	596	{
[1000]	597	vector < fS_Neuron * > neurons = geno.getAllNeurons();
[958]	598	if (neurons.empty())
	599	return false;
	600
	601	int size = neurons.size();
	602	for (int i = 0; i < mutationTries; i++)
	603	{
	604	fS_Neuron *selectedNeuron = neurons[rndUint(size)];
	605	if (!selectedNeuron->inputs.empty())
	606	{
	607	int inputCount = selectedNeuron->inputs.size();
	608	auto it = selectedNeuron->inputs.begin();
	609	advance(it, rndUint(inputCount));
	610
[969]	611	it->second = GenoOperators::getMutatedNeuronConnectionWeight(it->second);
[958]	612	return true;
	613	}
	614	}
	615	return false;
	616	}
	617
	618	bool GenoOper_fS::addNeuroConnection(fS_Genotype &geno)
	619	{
[1000]	620	vector < fS_Neuron * > neurons = geno.getAllNeurons();
[958]	621	if (neurons.empty())
	622	return false;
	623
	624	int size = neurons.size();
	625	fS_Neuron *selectedNeuron;
	626	for (int i = 0; i < mutationTries; i++)
	627	{
	628	selectedNeuron = neurons[rndUint(size)];
	629	if (selectedNeuron->acceptsInputs())
	630	break;
	631	}
	632	if (!selectedNeuron->acceptsInputs())
	633	return false;
	634
	635	for (int i = 0; i < mutationTries; i++)
	636	{
	637	int index = rndUint(size);
	638	if (selectedNeuron->inputs.count(index) == 0 && neurons[index]->getClass()->getPreferredOutput() > 0)
	639	{
	640
	641	selectedNeuron->inputs[index] = DEFAULT_NEURO_CONNECTION_WEIGHT;
	642	return true;
	643	}
	644	}
	645	return false;
	646	}
	647
	648	bool GenoOper_fS::removeNeuroConnection(fS_Genotype &geno)
	649	{
[1000]	650	vector < fS_Neuron * > neurons = geno.getAllNeurons();
[958]	651	if (neurons.empty())
	652	return false;
	653
	654	int size = neurons.size();
	655	for (int i = 0; i < mutationTries; i++)
	656	{
	657	fS_Neuron *selectedNeuron = neurons[rndUint(size)];
	658	if (!selectedNeuron->inputs.empty())
	659	{
	660	int inputCount = selectedNeuron->inputs.size();
	661	auto it = selectedNeuron->inputs.begin();
	662	advance(it, rndUint(inputCount));
	663	selectedNeuron->inputs.erase(it->first);
	664	return true;
	665	}
	666	}
	667	return false;
	668	}
	669
	670	bool GenoOper_fS::changeNeuroParam(fS_Genotype &geno)
	671	{
[1000]	672	vector < fS_Neuron * > neurons = geno.getAllNeurons();
[958]	673	if (neurons.empty())
	674	return false;
	675
	676	fS_Neuron *neu = neurons[rndUint(neurons.size())];
[969]	677	return GenoOperators::mutateRandomNeuroClassProperty(neu);
[1000]	678	}
	679
[1006]	680	bool GenoOper_fS::mutateSizeParam(Node *node, string key, bool ensureCircleSection)
[1000]	681	{
[1006]	682	double oldValue = node->getParam(key);
	683	double volume = node->calculateVolume();
[1000]	684	double valueAtMinVolume, valueAtMaxVolume;
	685	if(key == SIZE)
	686	{
	687	valueAtMinVolume = oldValue * std::cbrt(Model::getMinPart().volume / volume);
	688	valueAtMaxVolume = oldValue * std::cbrt(Model::getMaxPart().volume / volume);
	689	}
	690	else
	691	{
	692	valueAtMinVolume = oldValue * Model::getMinPart().volume / volume;
	693	valueAtMaxVolume = oldValue * Model::getMaxPart().volume / volume;
	694	}
	695
[1017]	696	double min = std::max(Node::minValues.at(key), valueAtMinVolume);
	697	double max = std::min(Node::maxValues.at(key), valueAtMaxVolume);
[1000]	698
[1006]	699	node->params[key] = GenoOperators::mutateCreep('f', node->getParam(key), min, max, true);
[1000]	700
[1006]	701	if (!ensureCircleSection \|\| node->isPartSizeValid())
[1000]	702	return true;
	703	else
	704	{
[1006]	705	node->params[key] = oldValue;
[1000]	706	return false;
	707	}
	708	}

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