Context Navigation

fS_oper.cpp @ 1227

Last change on this file since 1227 was 1130, checked in by Maciej Komosinski, 4 years ago
Used std::min(), std::max() explicitly to avoid compiler confusion. Used std::size() explicitly instead of the equivalent macro
File size: 23.4 KB

Rev	Line
[958]	1	// This file is a part of Framsticks SDK. http://www.framsticks.com/
[1130]	2	// Copyright (C) 2019-2021 Maciej Komosinski and Szymon Ulatowski.
[958]	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"
[1130]	9	#include <algorithm>
[958]	10
	11	#define FIELDSTRUCT GenoOper_fS
[974]	12	static ParamEntry genooper_fS_paramtab[] =
[958]	13	{
	14	{"Genetics: fS", 1, FS_OPCOUNT + 5,},
[1000]	15	{"fS_mut_add_part", 0, 0, "Add part", "f 0 100 10", FIELD(prob[FS_ADD_PART]), "mutation: probability of adding a part",},
	16	{"fS_mut_rem_part", 0, 0, "Remove part", "f 0 100 10", FIELD(prob[FS_REM_PART]), "mutation: probability of deleting a part",},
	17	{"fS_mut_mod_part", 0, 0, "Modify part", "f 0 100 10", FIELD(prob[FS_MOD_PART]), "mutation: probability of changing the part type",},
	18	{"fS_mut_change_joint", 0, 0, "Change joint", "f 0 100 10", FIELD(prob[FS_CHANGE_JOINT]), "mutation: probability of changing a joint",},
	19	{"fS_mut_add_param", 0, 0, "Add param", "f 0 100 10", FIELD(prob[FS_ADD_PARAM]), "mutation: probability of adding a parameter",},
	20	{"fS_mut_rem_param", 0, 0, "Remove param", "f 0 100 10", FIELD(prob[FS_REM_PARAM]), "mutation: probability of removing a parameter",},
	21	{"fS_mut_mod_param", 0, 0, "Modify param", "f 0 100 10", FIELD(prob[FS_MOD_PARAM]), "mutation: probability of modifying a parameter",},
	22	{"fS_mut_mod_mod", 0, 0, "Modify modifier", "f 0 100 10", FIELD(prob[FS_MOD_MOD]), "mutation: probability of modifying a modifier",},
	23	{"fS_mut_add_neuro", 0, 0, "Add neuron", "f 0 100 10", FIELD(prob[FS_ADD_NEURO]), "mutation: probability of adding a neuron",},
	24	{"fS_mut_rem_neuro", 0, 0, "Remove neuron", "f 0 100 10", FIELD(prob[FS_REM_NEURO]), "mutation: probability of removing a neuron",},
	25	{"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",},
	26	{"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]	27	{"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]	28	{"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",},
	29	{"fS_circle_section", 0, 0, "Ensure circle section", "d 0 1 1", FIELD(ensureCircleSection), "Ensure that ellipsoids and cylinders have circle cross-section"},
	30	{"fS_use_elli", 0, 0, "Use ellipsoids in mutations", "d 0 1 1", FIELD(useElli), "Use ellipsoids in mutations"},
	31	{"fS_use_cub", 0, 0, "Use cuboids in mutations", "d 0 1 1", FIELD(useCub), "Use cuboids in mutations"},
	32	{"fS_use_cyl", 0, 0, "Use cylinders in mutations", "d 0 1 1", FIELD(useCyl), "Use cylinders in mutations"},
	33	{"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]	34	};
	35
	36	#undef FIELDSTRUCT
	37
	38	GenoOper_fS::GenoOper_fS()
	39	{
[974]	40	par.setParamTab(genooper_fS_paramtab);
[958]	41	par.select(this);
	42	par.setDefault();
[969]	43	supported_format = 'S';
[958]	44	}
	45
	46	int GenoOper_fS::checkValidity(const char geno, const char genoname)
	47	{
	48	try
	49	{
	50	fS_Genotype genotype(geno);
	51	int errorPosition = genotype.checkValidityOfPartSizes();
[1000]	52	if (errorPosition != 0)
[958]	53	{
[1030]	54	logPrintf("GenoOper_fS", "checkValidity", LOG_WARN, "Invalid part scale");
[969]	55	return errorPosition;
[958]	56	}
	57	}
	58	catch (fS_Exception &e)
	59	{
[1000]	60	logPrintf("GenoOper_fS", "checkValidity", LOG_WARN, e.what());
[958]	61	return 1 + e.errorPosition;
	62	}
	63	return 0;
	64	}
	65
	66
	67	int GenoOper_fS::mutate(char *&geno, float &chg, int &method)
	68	{
[1000]	69	try
	70	{
	71	fS_Genotype genotype(geno);
[958]	72
[1000]	73	// Calculate available part types
	74	vector <Part::Shape> availablePartShapes;
	75	if (useElli)
	76	availablePartShapes.push_back(Part::Shape::SHAPE_ELLIPSOID);
	77	if (useCub)
	78	availablePartShapes.push_back(Part::Shape::SHAPE_CUBOID);
	79	if (useCyl)
	80	availablePartShapes.push_back(Part::Shape::SHAPE_CYLINDER);
[958]	81
[1000]	82	// Select a mutation
	83	bool result = false;
	84	method = GenoOperators::roulette(prob, FS_OPCOUNT);
	85	switch (method)
	86	{
	87	case FS_ADD_PART:
	88	result = addPart(genotype, availablePartShapes);
	89	break;
	90	case FS_REM_PART:
	91	result = removePart(genotype);
	92	break;
	93	case FS_MOD_PART:
	94	result = changePartType(genotype, availablePartShapes);
	95	break;
	96	case FS_CHANGE_JOINT:
	97	result = changeJoint(genotype);
	98	break;
	99	case FS_ADD_PARAM:
	100	result = addParam(genotype);
	101	break;
	102	case FS_REM_PARAM:
	103	result = removeParam(genotype);
	104	break;
	105	case FS_MOD_PARAM:
	106	result = changeParam(genotype);
	107	break;
	108	case FS_MOD_MOD:
	109	result = changeModifier(genotype);
	110	break;
	111	case FS_ADD_NEURO:
	112	result = addNeuro(genotype);
	113	break;
	114	case FS_REM_NEURO:
	115	result = removeNeuro(genotype);
	116	break;
	117	case FS_MOD_NEURO_CONNECTION:
	118	result = changeNeuroConnection(genotype);
	119	break;
	120	case FS_ADD_NEURO_CONNECTION:
	121	result = addNeuroConnection(genotype);
	122	break;
	123	case FS_REM_NEURO_CONNECTION:
	124	result = removeNeuroConnection(genotype);
	125	break;
	126	case FS_MOD_NEURO_PARAMS:
	127	result = changeNeuroParam(genotype);
	128	break;
	129	}
	130
	131	if (result)
	132	{
	133	free(geno);
	134	geno = strdup(genotype.getGeno().c_str());
	135	return GENOPER_OK;
	136	}
	137	return GENOPER_OPFAIL;
[958]	138	}
[1000]	139	catch (fS_Exception &e)
[958]	140	{
[1000]	141	logPrintf("GenoOper_fS", "mutate", LOG_WARN, e.what());
	142	return GENOPER_OPFAIL;
[958]	143	}
	144	}
	145
	146	int GenoOper_fS::crossOver(char &g0, char &g1, float &chg0, float &chg1)
	147	{
[1000]	148	try
	149	{
	150	assert(PARENT_COUNT == 2); // Cross over works only for 2 parents
	151	fS_Genotype *parents[PARENT_COUNT] = {new fS_Genotype(g0), new fS_Genotype(g1)};
[958]	152
[1000]	153	// Choose random subtrees that have similar size
	154	Node *selected[PARENT_COUNT];
	155	vector < Node * > allNodes0 = parents[0]->getAllNodes();
	156	vector < Node * > allNodes1 = parents[1]->getAllNodes();
[958]	157
[1000]	158	double bestQuotient = DBL_MAX;
	159	for (int i = 0; i < crossOverTries; i++)
[958]	160	{
[1000]	161	Node *tmp0 = allNodes0[rndUint(allNodes0.size())];
	162	Node *tmp1 = allNodes1[rndUint(allNodes1.size())];
	163	// Choose this pair if it is the most similar
	164	double quotient = double(tmp0->getNodeCount()) / double(tmp1->getNodeCount());
	165	if (quotient < 1.0)
	166	quotient = 1.0 / quotient;
	167	if (quotient < bestQuotient)
	168	{
	169	bestQuotient = quotient;
	170	selected[0] = tmp0;
	171	selected[1] = tmp1;
	172	}
	173	if (bestQuotient == 1.0)
	174	break;
[958]	175	}
	176
[1000]	177	// Compute gene percentages in children
	178	double subtreeSizes[PARENT_COUNT], restSizes[PARENT_COUNT];
	179	for (int i = 0; i < PARENT_COUNT; i++)
	180	{
[958]	181
[1000]	182	subtreeSizes[i] = selected[i]->getNodeCount();
	183	restSizes[i] = parents[i]->getNodeCount() - subtreeSizes[i];
	184	}
	185	chg0 = restSizes[0] / (restSizes[0] + subtreeSizes[1]);
	186	chg1 = restSizes[1] / (restSizes[1] + subtreeSizes[0]);
[958]	187
[1000]	188	// Rearrange neurons before crossover
	189	int subOldStart[PARENT_COUNT] {-1, -1};
	190	rearrangeConnectionsBeforeCrossover(parents[0], selected[0], subOldStart[0]);
	191	rearrangeConnectionsBeforeCrossover(parents[1], selected[1], subOldStart[1]);
[958]	192
[1000]	193	// Swap the subtress
	194	for (int i = 0; i < PARENT_COUNT; i++)
[958]	195	{
[1000]	196	Node *other = selected[1 - i];
	197	Node *p = selected[i]->parent;
	198	if (p != nullptr)
	199	{
	200	size_t index = std::distance(p->children.begin(), std::find(p->children.begin(), p->children.end(), selected[i]));
	201	p->children[index] = other;
	202	} else
	203	parents[i]->startNode = other;
	204	}
[958]	205
[1000]	206	// Rearrange neurons after crossover
	207	rearrangeConnectionsAfterCrossover(parents[0], selected[1], subOldStart[0]);
	208	rearrangeConnectionsAfterCrossover(parents[1], selected[0], subOldStart[1]);
[958]	209
[1000]	210	// Clenup, assign children to result strings
	211	free(g0);
	212	free(g1);
	213	g0 = strdup(parents[0]->getGeno().c_str());
	214	g1 = strdup(parents[1]->getGeno().c_str());
[958]	215
[1000]	216	delete parents[0];
	217	delete parents[1];
	218	}
	219	catch (fS_Exception &e)
	220	{
	221	logPrintf("GenoOper_fS", "crossOver", LOG_WARN, e.what());
	222	return GENOPER_OPFAIL;
	223	}
[958]	224	return GENOPER_OK;
	225	}
	226
[1000]	227	const char *GenoOper_fS::getSimplest()
[958]	228	{
[1032]	229	return "1.1,0,0.4:C{x=0.80599,y=0.80599,z=0.80599}";
[958]	230	}
	231
	232	uint32_t GenoOper_fS::style(const char *geno, int pos)
	233	{
	234	char ch = geno[pos];
	235	uint32_t style = GENSTYLE_CS(0, GENSTYLE_NONE);
	236	if (ch == ELLIPSOID \|\| ch == CUBOID \|\| ch == CYLINDER) // part type
	237	{
	238	style = GENSTYLE_RGBS(0, 0, 200, GENSTYLE_BOLD);
[1000]	239	} else if (JOINTS.find(ch) != string::npos) // Joint type
[958]	240	{
	241	style = GENSTYLE_RGBS(0, 200, 200, GENSTYLE_BOLD);
[1000]	242	} else if (MODIFIERS.find(ch) != string::npos) // Modifier
[958]	243	{
	244	style = GENSTYLE_RGBS(0, 200, 0, GENSTYLE_NONE);
[1000]	245	} else if (isdigit(ch) \|\| strchr(".", ch)) // Numerical value
[958]	246	{
	247	style = GENSTYLE_RGBS(200, 0, 0, GENSTYLE_NONE);
[1000]	248	} else if (strchr("()_;[],=", ch))
[958]	249	{
	250	style = GENSTYLE_CS(0, GENSTYLE_BOLD); // Important char
	251	}
	252
	253	return style;
	254	}
	255
	256	void GenoOper_fS::rearrangeConnectionsBeforeCrossover(fS_Genotype geno, Node sub, int &subStart)
	257	{
[1000]	258	vector < fS_Neuron * > genoNeurons = geno->getAllNeurons();
	259	vector < fS_Neuron * > subNeurons = fS_Genotype::extractNeurons(sub);
[958]	260
	261	if (!subNeurons.empty())
	262	{
	263	subStart = fS_Genotype::getNeuronIndex(genoNeurons, subNeurons[0]);
	264	fS_Genotype::shiftNeuroConnections(genoNeurons, subStart, subStart + subNeurons.size() - 1, SHIFT::LEFT);
	265	}
	266	}
	267
	268	void GenoOper_fS::rearrangeConnectionsAfterCrossover(fS_Genotype geno, Node sub, int subOldStart)
	269	{
[1000]	270	vector < fS_Neuron * > genoNeurons = geno->getAllNeurons();
	271	vector < fS_Neuron * > subNeurons = fS_Genotype::extractNeurons(sub);
[958]	272
	273	// Shift the inputs right
	274	if (!subNeurons.empty())
	275	{
	276	int subStart = fS_Genotype::getNeuronIndex(genoNeurons, subNeurons[0]);
	277	int subCount = subNeurons.size();
	278	int subEnd = subStart + subCount - 1;
	279	for (int i = 0; i < subCount; i++)
	280	{
	281	auto inputs = subNeurons[i]->inputs;
	282	std::map<int, double> newInputs;
	283	// TODO figure out how to keep internal connections in subtree
	284	// for (auto it = inputs.begin(); it != inputs.end(); ++it)
	285	// {
	286	// int newIndex = it->first + subStart;
	287	// if(subEnd > newIndex && newIndex > subStart)
	288	// newInputs[newIndex] = it->second;
	289	// }
	290	subNeurons[i]->inputs = newInputs;
	291	}
	292	fS_Genotype::shiftNeuroConnections(genoNeurons, subStart, subEnd, SHIFT::RIGHT);
	293	}
	294	}
	295
[1000]	296	bool GenoOper_fS::addPart(fS_Genotype &geno, const vector <Part::Shape> &availablePartShapes, bool mutateSize)
[958]	297	{
[1017]	298	geno.getState(false);
[958]	299	Node *node = geno.chooseNode();
[1030]	300	char partShape = SHAPE_TO_GENE.at(availablePartShapes[rndUint(availablePartShapes.size())]);
[958]	301
[1030]	302	Substring substring(&partShape, 0, 1);
[1000]	303	Node *newNode = new Node(substring, node, node->genotypeParams);
[958]	304	// Add random rotation
[1000]	305	string rotationParams[] {ROT_X, ROT_Y, ROT_Z};
	306	if (strongAddPart)
[958]	307	{
[1000]	308	for (int i = 0; i < 3; i++)
[969]	309	newNode->params[rotationParams[i]] = RndGen.Uni(-M_PI / 2, M_PI / 2);
[1000]	310	} else
[958]	311	{
	312	string selectedParam = rotationParams[rndUint(3)];
[969]	313	newNode->params[selectedParam] = RndGen.Uni(-M_PI / 2, M_PI / 2);
[958]	314	}
[1000]	315	string rParams[] {RX, RY, RZ};
	316	if (strongAddPart)
[958]	317	{
[1000]	318	for (int i = 0; i < 3; i++)
[969]	319	newNode->params[rParams[i]] = RndGen.Uni(-M_PI / 2, M_PI / 2);
[1000]	320	} else
[958]	321	{
	322	string selectedParam = rParams[rndUint(3)];
[969]	323	newNode->params[selectedParam] = RndGen.Uni(-M_PI / 2, M_PI / 2);
[958]	324	}
[1030]	325	// Assign part scale to default value
	326	double volumeMultiplier = pow(node->getParam(SCALE) * node->state->s, 3);
[958]	327	double minVolume = Model::getMinPart().volume;
	328	double defVolume = Model::getDefPart().volume * volumeMultiplier; // Default value after applying modifiers
	329	double maxVolume = Model::getMaxPart().volume;
	330	double volume = std::min(maxVolume, std::max(minVolume, defVolume));
	331	double relativeVolume = volume / volumeMultiplier; // Volume without applying modifiers
	332
[1030]	333	double newRadius = std::cbrt(relativeVolume / volumeMultipliers.at(newNode->partShape));
	334	newNode->params[SCALE_X] = newRadius;
	335	newNode->params[SCALE_Y] = newRadius;
	336	newNode->params[SCALE_Z] = newRadius;
[958]	337	node->children.push_back(newNode);
	338
	339	if (mutateSize)
	340	{
[1017]	341	geno.getState(false);
[1056]	342	mutateScaleParam(newNode, SCALE_X, true); //TODO 2020-12: mac->JS: should be true or rather ensureCircleSection?
[1030]	343	mutateScaleParam(newNode, SCALE_Y, true);
	344	mutateScaleParam(newNode, SCALE_Z, true);
[958]	345	}
	346	return true;
	347	}
	348
	349	bool GenoOper_fS::removePart(fS_Genotype &geno)
	350	{
	351	Node randomNode, selectedChild;
	352	// Choose a parent with children
[1030]	353	// It may be difficult to choose an eligible node, so the number of tries should be high
[1017]	354	for (int i = 0; i < 10 * mutationTries; i++)
[958]	355	{
	356	randomNode = geno.chooseNode();
	357	int childCount = randomNode->children.size();
	358	if (childCount > 0)
	359	{
	360	int selectedIndex = rndUint(childCount);
	361	selectedChild = randomNode->children[selectedIndex];
	362	if (selectedChild->children.empty() && selectedChild->neurons.empty())
	363	{
	364	// Remove the selected child
[1130]	365	std::swap(randomNode->children[selectedIndex], randomNode->children[childCount - 1]);
[958]	366	randomNode->children.pop_back();
	367	randomNode->children.shrink_to_fit();
	368	delete selectedChild;
	369	return true;
	370	}
	371	}
	372	}
	373	return false;
	374	}
	375
[1000]	376	bool GenoOper_fS::changePartType(fS_Genotype &geno, const vector <Part::Shape> &availablePartShapes)
[958]	377	{
[1000]	378	int availShapesLen = availablePartShapes.size();
[958]	379	for (int i = 0; i < mutationTries; i++)
	380	{
	381	Node *randomNode = geno.chooseNode();
[1000]	382	int index = rndUint(availShapesLen);
[1030]	383	if (availablePartShapes[index] == randomNode->partShape)
[1000]	384	index = (index + 1 + rndUint(availShapesLen - 1)) % availShapesLen;
	385	Part::Shape newType = availablePartShapes[index];
[958]	386
	387	#ifdef _DEBUG
[1030]	388	if(newType == randomNode->partShape)
[958]	389	throw fS_Exception("Internal error: invalid part type chosen in mutation.", 1);
	390	#endif
	391
[1017]	392	geno.getState(false);
[1030]	393	double scaleMultiplier = randomNode->getParam(SCALE) * randomNode->state->s;
	394	double relativeVolume = randomNode->calculateVolume() / pow(scaleMultiplier, 3.0);
[969]	395
[1030]	396	if (!ensureCircleSection \|\| newType == Part::Shape::SHAPE_CUBOID \|\| (randomNode->partShape == Part::Shape::SHAPE_ELLIPSOID && newType == Part::Shape::SHAPE_CYLINDER))
[958]	397	{
[1030]	398	double radiusQuotient = std::cbrt(volumeMultipliers.at(randomNode->partShape) / volumeMultipliers.at(newType));
	399	randomNode->params[SCALE_X] = randomNode->getParam(SCALE_X) * radiusQuotient;
	400	randomNode->params[SCALE_Y] = randomNode->getParam(SCALE_Y) * radiusQuotient;
	401	randomNode->params[SCALE_Z] = randomNode->getParam(SCALE_Z) * radiusQuotient;
	402	} else if (randomNode->partShape == Part::Shape::SHAPE_CUBOID && newType == Part::Shape::SHAPE_CYLINDER)
[969]	403	{
[1030]	404	double newRadius = 0.5 * (randomNode->getParam(SCALE_X) + randomNode->getParam(SCALE_Y));
	405	randomNode->params[SCALE_X] = 0.5 * relativeVolume / (M_PI * newRadius * newRadius);
	406	randomNode->params[SCALE_Y] = newRadius;
	407	randomNode->params[SCALE_Z] = newRadius;
[1000]	408	} else if (newType == Part::Shape::SHAPE_ELLIPSOID)
[969]	409	{
	410	double newRelativeRadius = cbrt(relativeVolume / volumeMultipliers.at(newType));
[1030]	411	randomNode->params[SCALE_X] = newRelativeRadius;
	412	randomNode->params[SCALE_Y] = newRelativeRadius;
	413	randomNode->params[SCALE_Z] = newRelativeRadius;
[1000]	414	} else
[969]	415	{
	416	throw fS_Exception("Invalid part type", 1);
	417	}
[1030]	418	randomNode->partShape = newType;
[958]	419	return true;
	420	}
	421	return false;
	422	}
	423
[969]	424	bool GenoOper_fS::changeJoint(fS_Genotype &geno)
[958]	425	{
	426	if (geno.startNode->children.empty())
	427	return false;
	428
[969]	429	Node *randomNode = geno.chooseNode(1); // First part does not have joints
[1000]	430	int jointLen = ALL_JOINTS.length();
[969]	431	int index = rndUint(jointLen);
	432	if (ALL_JOINTS[index] == randomNode->joint)
	433	index = (index + 1 + rndUint(jointLen - 1)) % jointLen;
[958]	434
[969]	435	randomNode->joint = ALL_JOINTS[index];
	436	return true;
[958]	437	}
	438
	439	bool GenoOper_fS::addParam(fS_Genotype &geno)
	440	{
	441	Node *randomNode = geno.chooseNode();
	442	int paramCount = randomNode->params.size();
	443	if (paramCount == int(PARAMS.size()))
	444	return false;
[969]	445	string key = PARAMS[rndUint(PARAMS.size())];
	446	if (randomNode->params.count(key) > 0)
[958]	447	return false;
	448	// Do not allow invalid changes in part size
[1030]	449	bool isRadiusOfBase = key == SCALE_Y \|\| key == SCALE_Z;
	450	bool isRadius = isRadiusOfBase \|\| key == SCALE_X;
[958]	451	if (ensureCircleSection && isRadius)
	452	{
[1030]	453	if (randomNode->partShape == Part::Shape::SHAPE_ELLIPSOID)
[958]	454	return false;
[1030]	455	if (randomNode->partShape == Part::Shape::SHAPE_CYLINDER && isRadiusOfBase)
[958]	456	return false;
	457	}
	458	// Add modified default value for param
[1017]	459	randomNode->params[key] = randomNode->defaultValues.at(key);
	460	geno.getState(false);
	461	return mutateParamValue(randomNode, key);
[958]	462	}
	463
	464	bool GenoOper_fS::removeParam(fS_Genotype &geno)
	465	{
	466	// Choose a node with params
	467	for (int i = 0; i < mutationTries; i++)
	468	{
	469	Node *randomNode = geno.chooseNode();
	470	int paramCount = randomNode->params.size();
	471	if (paramCount >= 1)
	472	{
	473	auto it = randomNode->params.begin();
	474	advance(it, rndUint(paramCount));
[1017]	475	string key = it->first;
	476	double value = it->second;
	477
	478	randomNode->params.erase(key);
	479	if(geno.checkValidityOfPartSizes() == 0)
	480	return true;
	481	else
	482	{
	483	randomNode->params[key] = value;
	484	}
[958]	485	}
	486	}
	487	return false;
	488	}
	489
[1017]	490
	491	bool GenoOper_fS::mutateParamValue(Node *node, string key)
	492	{
[1030]	493	// Do not allow invalid changes in part scale
	494	if (std::find(SCALE_PARAMS.begin(), SCALE_PARAMS.end(), key) == SCALE_PARAMS.end())
[1017]	495	{
[1030]	496	double max = Node::maxValues.at(key);
	497	double min = Node::minValues.at(key);
	498	double stddev = (max - min) * node->genotypeParams.paramMutationStrength;
	499	node->params[key] = GenoOperators::mutateCreep('f', node->getParam(key), min, max, stddev, true);
[1017]	500	return true;
	501	} else
[1030]	502	return mutateScaleParam(node, key, ensureCircleSection);
[1017]	503	}
	504
[958]	505	bool GenoOper_fS::changeParam(fS_Genotype &geno)
	506	{
[1017]	507	geno.getState(false);
[958]	508	for (int i = 0; i < mutationTries; i++)
	509	{
	510	Node *randomNode = geno.chooseNode();
	511	int paramCount = randomNode->params.size();
	512	if (paramCount >= 1)
	513	{
	514	auto it = randomNode->params.begin();
	515	advance(it, rndUint(paramCount));
[1017]	516	return mutateParamValue(randomNode, it->first);
[958]	517	}
	518	}
	519	return false;
	520	}
	521
	522	bool GenoOper_fS::changeModifier(fS_Genotype &geno)
	523	{
	524	Node *randomNode = geno.chooseNode();
	525	char randomModifier = MODIFIERS[rndUint(MODIFIERS.length())];
[1017]	526	int oldValue = randomNode->modifiers[randomModifier];
	527
[958]	528	randomNode->modifiers[randomModifier] += rndUint(2) == 0 ? 1 : -1;
	529
[1030]	530	bool isSizeMod = tolower(randomModifier) == SCALE_MODIFIER;
[958]	531	if (isSizeMod && geno.checkValidityOfPartSizes() != 0)
	532	{
[1017]	533	randomNode->modifiers[randomModifier] = oldValue;
[958]	534	return false;
	535	}
	536	return true;
	537	}
	538
	539	bool GenoOper_fS::addNeuro(fS_Genotype &geno)
	540	{
	541	Node *randomNode = geno.chooseNode();
	542	fS_Neuron *newNeuron;
[1000]	543	NeuroClass *rndclass = GenoOperators::getRandomNeuroClass(Model::SHAPETYPE_SOLIDS);
	544	if (rndclass->preflocation == NeuroClass::PREFER_JOINT && randomNode == geno.startNode)
[958]	545	return false;
	546
	547	const char *name = rndclass->getName().c_str();
	548	newNeuron = new fS_Neuron(name, randomNode->partDescription->start, strlen(name));
	549	int effectiveInputCount = rndclass->prefinputs > -1 ? rndclass->prefinputs : 1;
	550	if (effectiveInputCount > 0)
	551	{
	552	// Create as many connections for the neuron as possible (at most prefinputs)
[1000]	553	vector < fS_Neuron * > allNeurons = geno.getAllNeurons();
[958]	554	vector<int> neuronsWithOutput;
	555	for (int i = 0; i < int(allNeurons.size()); i++)
	556	{
	557	if (allNeurons[i]->getClass()->prefoutput > 0)
	558	neuronsWithOutput.push_back(i);
	559	}
	560	int size = neuronsWithOutput.size();
	561	if (size > 0)
	562	{
	563	for (int i = 0; i < effectiveInputCount; i++)
	564	{
	565	int selectedNeuron = neuronsWithOutput[rndUint(size)];
	566	newNeuron->inputs[selectedNeuron] = DEFAULT_NEURO_CONNECTION_WEIGHT;
	567	}
	568	}
	569	}
	570
	571	randomNode->neurons.push_back(newNeuron);
	572
	573	geno.rearrangeNeuronConnections(newNeuron, SHIFT::RIGHT);
	574	return true;
	575	}
	576
	577	bool GenoOper_fS::removeNeuro(fS_Genotype &geno)
	578	{
	579	Node *randomNode = geno.chooseNode();
	580	for (int i = 0; i < mutationTries; i++)
	581	{
	582	randomNode = geno.chooseNode();
	583	if (!randomNode->neurons.empty())
	584	{
	585	// Remove the selected neuron
	586	int size = randomNode->neurons.size();
	587	fS_Neuron *it = randomNode->neurons[rndUint(size)];
	588	geno.rearrangeNeuronConnections(it, SHIFT::LEFT); // Important to rearrange the neurons before deleting
[1130]	589	std::swap(it, randomNode->neurons.back());
[958]	590	randomNode->neurons.pop_back();
	591	randomNode->neurons.shrink_to_fit();
	592	delete it;
	593	return true;
	594	}
	595	}
	596	return false;
	597	}
	598
	599	bool GenoOper_fS::changeNeuroConnection(fS_Genotype &geno)
	600	{
[1000]	601	vector < fS_Neuron * > neurons = geno.getAllNeurons();
[958]	602	if (neurons.empty())
	603	return false;
	604
	605	int size = neurons.size();
	606	for (int i = 0; i < mutationTries; i++)
	607	{
	608	fS_Neuron *selectedNeuron = neurons[rndUint(size)];
	609	if (!selectedNeuron->inputs.empty())
	610	{
	611	int inputCount = selectedNeuron->inputs.size();
	612	auto it = selectedNeuron->inputs.begin();
	613	advance(it, rndUint(inputCount));
	614
[969]	615	it->second = GenoOperators::getMutatedNeuronConnectionWeight(it->second);
[958]	616	return true;
	617	}
	618	}
	619	return false;
	620	}
	621
	622	bool GenoOper_fS::addNeuroConnection(fS_Genotype &geno)
	623	{
[1000]	624	vector < fS_Neuron * > neurons = geno.getAllNeurons();
[958]	625	if (neurons.empty())
	626	return false;
	627
	628	int size = neurons.size();
	629	fS_Neuron *selectedNeuron;
	630	for (int i = 0; i < mutationTries; i++)
	631	{
	632	selectedNeuron = neurons[rndUint(size)];
	633	if (selectedNeuron->acceptsInputs())
	634	break;
	635	}
	636	if (!selectedNeuron->acceptsInputs())
	637	return false;
	638
	639	for (int i = 0; i < mutationTries; i++)
	640	{
	641	int index = rndUint(size);
	642	if (selectedNeuron->inputs.count(index) == 0 && neurons[index]->getClass()->getPreferredOutput() > 0)
	643	{
	644
	645	selectedNeuron->inputs[index] = DEFAULT_NEURO_CONNECTION_WEIGHT;
	646	return true;
	647	}
	648	}
	649	return false;
	650	}
	651
	652	bool GenoOper_fS::removeNeuroConnection(fS_Genotype &geno)
	653	{
[1000]	654	vector < fS_Neuron * > neurons = geno.getAllNeurons();
[958]	655	if (neurons.empty())
	656	return false;
	657
	658	int size = neurons.size();
	659	for (int i = 0; i < mutationTries; i++)
	660	{
	661	fS_Neuron *selectedNeuron = neurons[rndUint(size)];
	662	if (!selectedNeuron->inputs.empty())
	663	{
	664	int inputCount = selectedNeuron->inputs.size();
	665	auto it = selectedNeuron->inputs.begin();
	666	advance(it, rndUint(inputCount));
	667	selectedNeuron->inputs.erase(it->first);
	668	return true;
	669	}
	670	}
	671	return false;
	672	}
	673
	674	bool GenoOper_fS::changeNeuroParam(fS_Genotype &geno)
	675	{
[1000]	676	vector < fS_Neuron * > neurons = geno.getAllNeurons();
[958]	677	if (neurons.empty())
	678	return false;
	679
	680	fS_Neuron *neu = neurons[rndUint(neurons.size())];
[969]	681	return GenoOperators::mutateRandomNeuroClassProperty(neu);
[1000]	682	}
	683
[1030]	684	bool GenoOper_fS::mutateScaleParam(Node *node, string key, bool ensureCircleSection)
[1000]	685	{
[1006]	686	double oldValue = node->getParam(key);
	687	double volume = node->calculateVolume();
[1000]	688	double valueAtMinVolume, valueAtMaxVolume;
[1030]	689	if(key == SCALE)
[1000]	690	{
	691	valueAtMinVolume = oldValue * std::cbrt(Model::getMinPart().volume / volume);
	692	valueAtMaxVolume = oldValue * std::cbrt(Model::getMaxPart().volume / volume);
	693	}
	694	else
	695	{
	696	valueAtMinVolume = oldValue * Model::getMinPart().volume / volume;
	697	valueAtMaxVolume = oldValue * Model::getMaxPart().volume / volume;
	698	}
	699
[1017]	700	double min = std::max(Node::minValues.at(key), valueAtMinVolume);
	701	double max = std::min(Node::maxValues.at(key), valueAtMaxVolume);
[1030]	702	double stdev = (max - min) * node->genotypeParams.paramMutationStrength;
[1000]	703
[1030]	704	node->params[key] = GenoOperators::mutateCreep('f', node->getParam(key), min, max, stdev, true);
[1000]	705
[1030]	706	if (!ensureCircleSection \|\| node->isPartScaleValid())
[1000]	707	return true;
	708	else
	709	{
[1006]	710	node->params[key] = oldValue;
[1000]	711	return false;
	712	}
	713	}

Note: See TracBrowser for help on using the repository browser.

Context Navigation

source: cpp/frams/genetics/fS/fS_oper.cpp @ 1227

Download in other formats: