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source: cpp/frams/genetics/f1/conv_f1.cpp @ 671

Last change on this file since 671 was 671, checked in by Maciej Komosinski, 7 years ago
Unified property names of f1 and f4; improved docs; 3.141 -> M_PI
Property svn:eol-style set to `native`
File size: 16.4 KB

Rev	Line
[286]	1	// This file is a part of Framsticks SDK. http://www.framsticks.com/
[671]	2	// Copyright (C) 1999-2017 Maciej Komosinski and Szymon Ulatowski.
[286]	3	// See LICENSE.txt for details.
[109]	4
	5	#include "conv_f1.h"
	6	#include <common/nonstd_stl.h>
[375]	7	#include <common/log.h>
[109]	8	#include <frams/util/multirange.h>
	9	#include <frams/util/multimap.h>
	10	#include <ctype.h>
	11
[671]	12	//#define v1f1COMPATIBLE //as in ancient Framsticks 1.x
[109]	13
[671]	14	F1Props stdprops = { 1, 0, 1, 0.4, 0.25, 0.25, 0.25, 0.25, 0.0, 1.0, 1.0, 1,
	15	0.2, 0.5, 0.5, 0.5 };
[109]	16
	17	class Builder
	18	{
	19	public:
[671]	20	Builder(const char*g, int mapping = 0) :invalid(0), genbegin(g), usemapping(mapping), first_part_mapping(NULL), model_energy(0), model_energy_max(0) {}
	21	~Builder() { SAFEDELETE(first_part_mapping); }
	22	char tmp[222];
	23	bool invalid;
	24	Model model;
	25	const char *genbegin;
	26	SList neuro_f1_to_f0; // neuro_f1_to_f0(f1_refno) = actual neuro pointer
	27	Neuro *last_f1_neuro;
	28	SyntParam *neuro_cls_param;
[109]	29
[671]	30	struct Connection
	31	{
	32	int n1, n2; double w;
	33	Connection(int _n1, int _n2, double _w) :n1(_n1), n2(_n2), w(_w) {}
	34	};
[109]	35
[671]	36	SListTempl<Connection> connections;
	37	int usemapping;
	38	MultiRange range;
	39	MultiRange *first_part_mapping;
	40	double lastjoint_muscle_power;
	41	double model_energy, model_energy_max;
	42	void grow(int part1, const char*g, Pt3D k, F1Props c);
	43	void setPartMapping(int p, const char* g);
	44	int growJoint(int part1, int part2, Pt3D &angle, F1Props &c, const char *g);
	45	int growPart(F1Props &c, const char *g);
	46	const char skipNeuro(const char z);
	47	const char* growNeuro(const char* t, F1Props &c, int&);
	48	void growConnection(const char* begin, const char* colon, const char* end, F1Props& props);
	49	int countBranches(const char*g, SList &out);
	50	SyntParam* lastNeuroClassParam();
	51	void addClassParam(const char* name, double value);
	52	void addClassParam(const char* name, const char* value);
[109]	53
[671]	54	const MultiRange* makeRange(const char*g) { return makeRange(g, g); }
	55	const MultiRange* makeRange(const charg, const charg2);
	56	Part *getLastPart() { return getLastJoint()->part2; }
	57	Neuro *getLastNeuro() { return model.getNeuro(model.getNeuroCount() - 1); }
	58	Joint *getLastJoint() { return model.getJoint(model.getJointCount() - 1); }
	59	void addOrRememberInput(int n1, int n2, double w)
	60	{
[109]	61	//if (!addInput(n1,n2,w,false))
[671]	62	connections += Connection(n1, n2, w);
	63	}
	64	bool addInput(int n1, int n2, double w, bool final)
	65	{
	66	if ((n1 < 0) \|\| (n2 < 0) \|\| (n1 >= neuro_f1_to_f0.size()) \|\| (n2 >= neuro_f1_to_f0.size()))
[109]	67	{
[671]	68	if (final) logPrintf("GenoConvF1", "addInput", LOG_WARN,
	69	"illegal neuron connection %d <- %d (ignored)", n1, n2);
[109]	70	return 0;
[671]	71	}
	72	Neuro neuro = (Neuro)neuro_f1_to_f0(n1);
	73	Neuro input = (Neuro)neuro_f1_to_f0(n2);
	74	neuro->addInput(input, w);
[109]	75	return 1;
[671]	76	}
	77	void addPendingInputs()
	78	{
	79	for (int i = 0; i < connections.size(); i++)
[109]	80	{
[671]	81	Connection *c = &connections(i);
	82	addInput(c->n1, c->n2, c->w, true);
[109]	83	}
[671]	84	}
[109]	85	};
	86
[671]	87	const MultiRange* Builder::makeRange(const charg, const charg2)
[109]	88	{
[671]	89	if (!usemapping) return 0;
	90	range.clear();
	91	range.add(g - genbegin, g2 - genbegin);
	92	return &range;
[109]	93	}
	94
[671]	95	void F1Props::normalizeBiol4()
[109]	96	{
[671]	97	double sum = muscle_power + assimilation + stamina + ingestion;
	98	muscle_power /= sum;
	99	assimilation /= sum;
	100	stamina /= sum;
	101	ingestion /= sum;
[109]	102	}
	103
	104	/** main conversion function - with conversion map support */
[671]	105	SString GenoConv_f1::convert(SString &i, MultiMap *map)
[109]	106	{
[671]	107	const char* g = i.c_str();
	108	Builder builder(g, map ? 1 : 0);
	109	builder.model.open();
	110	builder.grow(-1, g, Pt3D_0, stdprops); // uses Model::singleStepBuild to create model elements
	111	if (builder.invalid) return SString();
	112	builder.addPendingInputs();
	113	builder.model.startenergy = (builder.model_energy_max > 0) ? (builder.model_energy / builder.model_energy_max) : 1.0;
	114	builder.model.close(); // model is ready to use now
	115	if (map) builder.model.getCurrentToF0Map(*map); // generate f1-to-f0 conversion map
	116	return builder.model.getF0Geno().getGenes();
[109]	117	}
	118
[671]	119	void Builder::setPartMapping(int p, const char* g)
[109]	120	{
[671]	121	if (!usemapping) return;
	122	const MultiRange *r = makeRange(g);
	123	if (p < 0)
[109]	124	{ //special case: mapping the part which is not yet created
[671]	125	if (first_part_mapping) first_part_mapping->add(*r);
	126	else first_part_mapping = new MultiRange(*r);
[109]	127	}
[671]	128	else
	129	model.getPart(p)->addMapping(*r);
[109]	130	}
	131
[671]	132	void Builder::grow(int part1, const char*g, Pt3D k, F1Props c)
[109]	133	{
[671]	134	int hasmuscles = 0;
	135	k += Pt3D(c.twist, 0, c.curvedness);
	136	while (1)
[109]	137	{
[671]	138	switch (*g)
	139	{
	140	case 0: case ',': case ')': return;
	141	case 'R': k.x += 0.7853; setPartMapping(part1, g); break;
	142	case 'r': k.x -= 0.7853; setPartMapping(part1, g); break;
	143	case 'Q': c.twist += (1.58 - c.twist)*0.3; setPartMapping(part1, g); break;
	144	case 'q': c.twist += (-1.58 - c.twist)*0.3; setPartMapping(part1, g); break;
[109]	145	#ifdef v1f1COMPATIBLE
[671]	146	case 'L': c.length += (3.0 - c.length)*0.3; setPartMapping(part1, g); break;
[109]	147	#else
[671]	148	case 'L': c.length += (2.0 - c.length)*0.3; setPartMapping(part1, g); break;
[109]	149	#endif
[671]	150	case 'l': c.length += (0.33 - c.length)*0.3; setPartMapping(part1, g); break;
	151	case 'A': c.assimilation += (1 - c.assimilation)*0.8; c.normalizeBiol4(); setPartMapping(part1, g); break;
	152	case 'a': c.assimilation -= c.assimilation*0.4; c.normalizeBiol4(); setPartMapping(part1, g); break;
	153	case 'I': c.ingestion += (1 - c.ingestion)*0.8; c.normalizeBiol4(); setPartMapping(part1, g); break;
	154	case 'i': c.ingestion -= c.ingestion*0.4; c.normalizeBiol4(); setPartMapping(part1, g); break;
	155	case 'S': c.stamina += (1 - c.stamina)*0.8; c.normalizeBiol4(); setPartMapping(part1, g); break;
	156	case 's': c.stamina -= c.stamina*0.4; c.normalizeBiol4(); setPartMapping(part1, g); break;
	157	case 'M': c.muscle_power += (1 - c.muscle_power)*0.8; c.normalizeBiol4(); setPartMapping(part1, g); break;
	158	case 'm': c.muscle_power -= c.muscle_power*0.4; c.normalizeBiol4(); setPartMapping(part1, g); break;
	159	case 'C': c.curvedness += (2.0 - c.curvedness)*0.25; setPartMapping(part1, g); break;
	160	case 'c': c.curvedness += (-2.0 - c.curvedness)*0.25; setPartMapping(part1, g); break;
	161	case 'F': c.friction += (4 - c.friction)*0.2; setPartMapping(part1, g); break;
	162	case 'f': c.friction -= c.friction*0.2; setPartMapping(part1, g); break;
	163	case 'W': c.weight += (2.0 - c.weight)*0.3; setPartMapping(part1, g); break;
	164	case 'w': c.weight += (0.5 - c.weight)*0.3; setPartMapping(part1, g); break;
	165	case 'E': c.energy += (10.0 - c.energy)*0.1; setPartMapping(part1, g); break;
	166	case 'e': c.energy -= c.energy*0.1; setPartMapping(part1, g); break;
[109]	167
[671]	168	case 'D': c.cred += (1.0 - c.cred)*0.25; setPartMapping(part1, g); break;
	169	case 'd': c.cred += (0.0 - c.cred)*0.25; setPartMapping(part1, g); break;
	170	case 'G': c.cgreen += (1.0 - c.cgreen)*0.25; setPartMapping(part1, g); break;
	171	case 'g': c.cgreen += (0.0 - c.cgreen)*0.25; setPartMapping(part1, g); break;
	172	case 'B': c.cblue += (1.0 - c.cblue)*0.25; setPartMapping(part1, g); break;
	173	case 'b': c.cblue += (0.0 - c.cblue)*0.25; setPartMapping(part1, g); break;
	174	case 'H': c.visual_size += (0.7 - c.visual_size)*0.25; setPartMapping(part1, g); break;
	175	case 'h': c.visual_size += (0.05 - c.visual_size)*0.25; setPartMapping(part1, g); break;
[109]	176
[671]	177	case '[': //neuron
	178	// setdebug(g-(char*)geny,DEBUGNEURO \| !l_neu);
	179	if (model.getJointCount())
	180	g = growNeuro(g + 1, c, hasmuscles);
	181	else
[109]	182	{
[671]	183	logMessage("GenoConv_F1", "grow", 1, "Illegal neuron position (ignored)");
	184	g = skipNeuro(g + 1);
[109]	185	}
[671]	186	break;
	187	case 'X':
[109]	188	{
[671]	189	int freshpart = 0;
	190	//setdebug(g-(char*)geny,DEBUGEST \| !l_est);
	191	if (part1 < 0) //initial grow
[109]	192	{
[671]	193	if (model.getPartCount() > 0)
	194	part1 = 0;
	195	else
	196	{
	197	part1 = growPart(c, g);
	198	freshpart = 1;
	199	if (first_part_mapping)
	200	model.getPart(part1)->setMapping(*first_part_mapping);
	201	}
	202	}
	203	if (!freshpart)
[109]	204	{
[671]	205	Part *part = model.getPart(part1);
	206	part->density = ((part->masspart->density) + 1.0 / c.weight) / (part->mass + 1.0); // v=md
	207	// part->volume+=1.0/c.weight;
	208	part->mass += 1.0;
[109]	209	}
[671]	210	model_energy += 0.9*c.energy + 0.1;
	211	model_energy_max += 1.0;
[109]	212
[671]	213	int part2 = growPart(c, g);
	214	growJoint(part1, part2, k, c, g);
	215	// est* e = new est(s,s2,k,c,zz,this);
[109]	216
[671]	217	// attenuate properties as they are propagated along the structure
	218	c.length = 0.5c.length + 0.5stdprops.length;
	219	c.visual_size = 0.5c.visual_size + 0.5stdprops.visual_size;
	220	c.curvedness = 0.66*c.curvedness;
	221	c.twist = 0.66*c.twist;
	222	c.friction = 0.8c.friction + 0.2stdprops.friction;
[109]	223
[671]	224	c.assimilation = 0.8c.assimilation + 0.2stdprops.assimilation;
	225	c.stamina = 0.8c.stamina + 0.2stdprops.stamina;
	226	c.muscle_power = 0.8c.muscle_power + 0.2stdprops.muscle_power;
	227	c.ingestion = 0.8c.ingestion + 0.2stdprops.ingestion;
	228	c.weight += (stdprops.weight - c.weight)*0.5;
	229	c.normalizeBiol4();
	230
	231	if (c.muscle_reset_range) c.muscle_bend_range = 1.0; else c.muscle_reset_range = true;
	232	grow(part2, g + 1, Pt3D_0, c);
	233	return;
[109]	234	}
[671]	235	case '(':
[109]	236	{
[671]	237	setPartMapping(part1, g);
	238	SList ga;
	239	int i, count;
	240	count = countBranches(g + 1, ga);
	241	c.muscle_reset_range = false;
	242	c.muscle_bend_range = 1.0 / count;
	243	for (i = 0; i < count; i++)
	244	grow(part1, (char)ga(i), k + Pt3D(0, 0, -M_PI + (i + 1)(2*M_PI / (count + 1))), c);
	245	return;
[109]	246	}
[671]	247	case ' ': case '\t': case '\n': case '\r': break;
	248	default: invalid = 1; return;
	249	}
	250	g++;
[109]	251	}
	252	}
	253
	254	SyntParam* Builder::lastNeuroClassParam()
	255	{
[671]	256	if (!neuro_cls_param)
[109]	257	{
[671]	258	NeuroClass *cls = last_f1_neuro->getClass();
	259	if (cls)
[109]	260	{
[671]	261	neuro_cls_param = new SyntParam(last_f1_neuro->classProperties());
	262	// this is equivalent to:
	263	// SyntParam tmp=last_f1_neuro->classProperties();
	264	// neuro_cls_param=new SyntParam(tmp);
	265	// interestingly, some compilers eliminate the call to new SyntParam,
	266	// realizing that a copy constructor is redundant when the original object is
	267	// temporary. there are no side effect of such optimization, as long as the
	268	// copy-constructed object is exact equivalent of the original.
[109]	269	}
	270	}
[671]	271	return neuro_cls_param;
[109]	272	}
	273
[671]	274	void Builder::addClassParam(const char* name, double value)
[109]	275	{
[671]	276	lastNeuroClassParam();
	277	if (neuro_cls_param)
	278	neuro_cls_param->setDoubleById(name, value);
[109]	279	}
	280
[671]	281	void Builder::addClassParam(const char* name, const char* value)
[109]	282	{
[671]	283	lastNeuroClassParam();
	284	if (neuro_cls_param)
[109]	285	{
[671]	286	ExtValue e(value);
	287	const ExtValue &re(e);
	288	neuro_cls_param->setById(name, re);
[109]	289	}
	290	}
	291
[671]	292	int Builder::countBranches(const char*g, SList &out)
[109]	293	{
[671]	294	int gl = 0;
	295	out += (void*)g;
	296	while (gl >= 0)
[109]	297	{
[671]	298	switch (*g)
[109]	299	{
[671]	300	case 0: gl = -1; break;
[109]	301	case '(': case '[': ++gl; break;
	302	case ')': case ']': --gl; break;
[671]	303	case ',': if (!gl) out += (void*)(g + 1);
[109]	304	}
[671]	305	g++;
[109]	306	}
[671]	307	return out.size();
[109]	308	}
	309
[671]	310	int Builder::growJoint(int part1, int part2, Pt3D &angle, F1Props &c, const char *g)
[109]	311	{
[671]	312	double len = min(2.0, c.length);
	313	sprintf(tmp, "j:p1=%ld,p2=%ld,dx=%lg,rx=%lg,ry=%lg,rz=%lg,stam=%lg,vr=%g,vg=%g,vb=%g",
	314	part1, part2, len, angle.x, angle.y, angle.z, c.stamina, c.cred, c.cgreen, c.cblue);
	315	lastjoint_muscle_power = c.muscle_power;
	316	return model.singleStepBuild(tmp, makeRange(g));
[109]	317	}
	318
[671]	319	int Builder::growPart(F1Props &c, const char *g)
[109]	320	{
[671]	321	sprintf(tmp, "p:dn=%lg,fr=%lg,ing=%lg,as=%lg,vs=%g,vr=%g,vg=%g,vb=%g",
	322	1.0 / c.weight, c.friction, c.ingestion, c.assimilation, c.visual_size, c.cred, c.cgreen, c.cblue);
	323	return model.singleStepBuild(tmp, makeRange(g));
[109]	324	}
	325
	326	const char Builder::skipNeuro(const char z)
	327	{
[671]	328	for (; z; z++) if ((z == ']') \|\| (*z == ')')) break;
	329	return z - 1;
[109]	330	}
	331
[671]	332	const char* Builder::growNeuro(const char* t, F1Props& props, int &hasmuscles)
[109]	333	{
[671]	334	const char*neuroend = skipNeuro(t);
	335	last_f1_neuro = model.addNewNeuro();
	336	neuro_cls_param = NULL;
	337	last_f1_neuro->attachToPart(getLastPart());
	338	const MultiRange *mr = makeRange(t - 1, neuroend + 1);
	339	if (mr) last_f1_neuro->addMapping(*mr);
	340	neuro_f1_to_f0 += last_f1_neuro;
[109]	341
[671]	342	SString clsname;
	343	bool haveclass = 0;
	344	while (t && t <= ' ') t++;
	345	const char* next = (*t) ? (t + 1) : t;
	346	while (next && next <= ' ') next++;
	347	if (t && next != ',' && *next != ']') // old style muscles [\|rest] or [@rest]
	348	switch (*t)
[109]	349	{
[671]	350	case '@': if (t[1] == ':') break;
	351	haveclass = 1;
	352	// if (!(hasmuscles&1))
	353	{
	354	hasmuscles \|= 1;
	355	Neuro *muscle = model.addNewNeuro();
	356	sprintf(tmp, "@:p=%lg", lastjoint_muscle_power);
	357	muscle->addInput(last_f1_neuro);
	358	muscle->setDetails(tmp);
	359	muscle->attachToJoint(getLastJoint());
	360	if (usemapping) muscle->addMapping(*makeRange(t));
	361	}
	362	t++;
	363	break;
	364	case '\|': if (t[1] == ':') break;
	365	haveclass = 1;
	366	// if (!(hasmuscles&2))
	367	{
	368	hasmuscles \|= 2;
	369	Neuro *muscle = model.addNewNeuro();
	370	sprintf(tmp, "\|:p=%lg,r=%lg", lastjoint_muscle_power, props.muscle_bend_range);
	371	muscle->addInput(last_f1_neuro);
	372	muscle->setDetails(tmp);
	373	muscle->attachToJoint(getLastJoint());
	374	if (usemapping) muscle->addMapping(*makeRange(t));
	375	}
	376	t++;
	377	break;
[109]	378	}
[671]	379	while (t && t <= ' ') t++;
	380	bool finished = 0;
	381	const char *begin = t;
	382	const char* colon = 0;
	383	SString classparams;
	384	while (!finished)
[109]	385	{
[671]	386	switch (*t)
[109]	387	{
[671]	388	case ':': colon = t; break;
	389	case 0: case ']': case ')': finished = 1;
[109]	390	// NO break!
	391	case ',':
[671]	392	if (!haveclass && !colon && t > begin)
	393	{
	394	haveclass = 1;
	395	SString clsname(begin, t - begin);
	396	clsname = trim(clsname);
[109]	397	last_f1_neuro->setClassName(clsname);
[671]	398	NeuroClass *cls = last_f1_neuro->getClass();
[109]	399	if (cls)
[671]	400	{
	401	if (cls->getPreferredLocation() == 2)
[109]	402	last_f1_neuro->attachToJoint(getLastJoint());
[671]	403	else if (cls->getPreferredLocation() == 1)
[109]	404	last_f1_neuro->attachToPart(getLastPart());
	405
	406	lastNeuroClassParam();
	407	//special handling: muscle properties (can be overwritten by subsequent property assignments)
[671]	408	if (!strcmp(cls->getName().c_str(), "\|"))
	409	{
	410	neuro_cls_param->setDoubleById("p", lastjoint_muscle_power);
	411	neuro_cls_param->setDoubleById("r", props.muscle_bend_range);
[109]	412	}
[671]	413	else if (!strcmp(cls->getName().c_str(), "@"))
	414	{
	415	neuro_cls_param->setDoubleById("p", lastjoint_muscle_power);
	416	}
[109]	417	}
[671]	418	}
	419	else if (colon && (colon > begin) && (t > colon))
	420	growConnection(begin, colon, t, props);
	421	if (t[0] != ',') t--;
	422	begin = t + 1; colon = 0;
[109]	423	break;
	424	}
[671]	425	t++;
[109]	426	}
[671]	427	SAFEDELETE(neuro_cls_param);
	428	return t;
[109]	429	}
[671]	430	void Builder::growConnection(const char* begin, const char* colon, const char* end, F1Props& props)
[109]	431	{
[671]	432	while (begin && begin <= ' ') begin++;
	433	int i;
	434	if (isdigit(begin[0]) \|\| (begin[0] == '-'))
[109]	435	{
[671]	436	double conn_weight = ExtValue::getDouble(trim(SString(colon + 1, end - (colon + 1))).c_str());
	437	paInt relative = ExtValue::getInt(trim(SString(begin, colon - begin)).c_str(), false);
	438	int this_refno = neuro_f1_to_f0.size() - 1;
	439	addOrRememberInput(this_refno, this_refno + relative, conn_weight);
[109]	440	}
[671]	441	else if ((i = last_f1_neuro->extraProperties().findIdn(begin, colon - begin)) >= 0)
[109]	442	{
[671]	443	last_f1_neuro->extraProperties().set(i, colon + 1);
[109]	444	}
[671]	445	else if (isupper(begin[0]) \|\| strchr("*\|@", begin[0]))
[109]	446	{
[671]	447	SString clsname(begin, colon - begin);
	448	trim(clsname);
	449	Neuro *receptor = model.addNewNeuro();
	450	receptor->setClassName(clsname);
	451	NeuroClass *cls = receptor->getClass();
	452	if (cls)
[109]	453	{
[671]	454	if (cls->getPreferredLocation() == 2) receptor->attachToJoint(getLastJoint());
	455	else if (cls->getPreferredLocation() == 1) receptor->attachToPart(getLastPart());
[109]	456	}
[671]	457	last_f1_neuro->addInput(receptor, ExtValue::getDouble(trim(SString(colon + 1, end - (colon + 1))).c_str()));
	458	if (usemapping) receptor->addMapping(*makeRange(begin, end - 1));
[109]	459	}
[671]	460	else if ((begin[0] == '>') && (begin[1]))
[109]	461	{
[671]	462	Neuro *out = model.addNewNeuro();
	463	out->addInput(last_f1_neuro, ExtValue::getDouble(trim(SString(colon + 1, end - (colon + 1))).c_str()));
	464	out->setClassName(SString(begin + 1, end - colon - 1));
	465	if (begin[1] == '@')
[109]	466	{
[671]	467	sprintf(tmp, "p=%lg", lastjoint_muscle_power);
	468	out->setClassParams(tmp);
[109]	469	}
[671]	470	else if (begin[1] == '\|')
[109]	471	{
[671]	472	sprintf(tmp, "p=%lg,r=%lg", lastjoint_muscle_power, props.muscle_bend_range);
	473	out->setClassParams(tmp);
[109]	474	}
[671]	475	NeuroClass *cls = out->getClass();
	476	if (cls)
[109]	477	{
[671]	478	if (cls->getPreferredLocation() == 2) out->attachToJoint(getLastJoint());
	479	else if (cls->getPreferredLocation() == 1) out->attachToPart(getLastPart());
[109]	480	}
[671]	481	if (usemapping) out->addMapping(*makeRange(begin, end - 1));
[109]	482	}
[671]	483	else if (*begin == '!') addClassParam("fo", ExtValue::getDouble(trim(SString(colon + 1, end - (colon + 1))).c_str()));
	484	else if (*begin == '=') addClassParam("in", ExtValue::getDouble(trim(SString(colon + 1, end - (colon + 1))).c_str()));
	485	else if (*begin == '/') addClassParam("si", ExtValue::getDouble(trim(SString(colon + 1, end - (colon + 1))).c_str()));
	486	else if (islower(begin[0]))
[109]	487	{
[671]	488	SString name(begin, colon - begin);
	489	SString value(colon + 1, end - (colon + 1));
	490	addClassParam(name.c_str(), value.c_str());
[109]	491	}
	492	}

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