source: cpp/frams/genetics/fH/fH_oper.cpp @ 1288

// This file is a part of Framsticks SDK.  http://www.framsticks.com/
// Copyright (C) 1999-2020  Maciej Komosinski and Szymon Ulatowski.
// See LICENSE.txt for details.

#include "fH_oper.h"

#include <common/loggers/loggers.h>
#include <frams/param/syntparam.h>
#include <frams/param/paramobj.h>

#define FIELDSTRUCT Geno_fH

static ParamEntry geno_fH_paramtab[] =
{
        { "Genetics: fH", 1, FH_OPCOUNT + FH_ADD_OPCOUNT, },
        { "fH_mut_addition", 0, 0, "Add element", "f 0 100 4", FIELD(operations[FH_ADD]), "Probability of adding a new element", },
        { "fH_mut_add_joint", 0, 0, " - add joint", "f 0 100 4", FIELD(addoperations[FH_ADD_STICK]), "Probability of adding a new stick handle", },
        { "fH_mut_add_neuron", 0, 0, " - add neuron", "f 0 100 3", FIELD(addoperations[FH_ADD_NEURO]), "Probability of adding a new neuron handle", },
        { "fH_mut_add_connection", 0, 0, " - add neural connection", "f 0 100 1", FIELD(addoperations[FH_ADD_CONN]), "Probability of adding a new neuron connection handle", },
        { "fH_mut_deletion", 0, 0, "Delete element", "f 0 100 4", FIELD(operations[FH_DEL]), "Probability of removing an element", },
        { "fH_mut_handle", 0, 0, "Modify vectors of handles", "f 0 100 1", FIELD(operations[FH_HANDLE]), "Probability of changing values in vectors of a handle", },
        { "fH_mut_property", 0, 0, "Modify properties of handles", "f 0 100 4", FIELD(operations[FH_PROP]), "Probability of changing properties of handles", },
        { 0, },
};

#undef FIELDSTRUCT

Geno_fH::Geno_fH()
{
        par.setParamTab(geno_fH_paramtab);
        par.select(this);
        par.setDefault();
        supported_format = 'H';
}

int Geno_fH::checkValidity(const char* geno, const char* genoname)
{
        LoggerToMemory eh(LoggerBase::Enable | LoggerToMemory::StoreAllMessages, LOG_WARN);
        fH_Builder builder;
        // during parsing method tries to approximate error position
        int err = builder.parseGenotype(geno);
        if (err != 0)
        {
                return err;
        }
        if (builder.sticks.size() == 0)
        {
                return 1;
        }
        int amount = builder.removeNeuronsWithInvalidClasses();
        if (amount > 0)
        {
                return 1;
        }
        return GENOPER_OK;
}

int Geno_fH::validate(char *&geno, const char *genoname)
{
        // 'eh' variable is used for "hiding" error and warning messages generated during fH
        // genotype parsing
        LoggerToMemory eh(LoggerBase::Enable | LoggerToMemory::StoreAllMessages, LOG_WARN);
        fH_Builder builder;
        int err = builder.parseGenotype(geno);
        // if parsing failed, then it is impossible to repair the genotype
        if (err != 0)
        {
                return GENOPER_OK;
        }
        // method removes definitions of neurons that have an invalid genotype
        int amount = builder.removeNeuronsWithInvalidClasses();
        // if there were any warnings, then rewrite the genotype
        if (eh.getErrorWarningCount() > 0 || amount > 0)
        {
                free(geno);
                geno = strdup(builder.toString().c_str());
        }
        return GENOPER_OK;
}

int Geno_fH::crossOver(char *&g1, char *&g2, float& chg1, float& chg2)
{
        fH_Builder *parent1 = new fH_Builder();
        fH_Builder *parent2 = new fH_Builder();

        // first of all, both parents need to be parsed. If parents cannot be
        // parsed or their dimensionality differs, then method returns GENOPER_OPFAIL
        if (parent1->parseGenotype(g1) != 0 || parent2->parseGenotype(g2) != 0 ||
                parent1->dimensions != parent2->dimensions)
        {
                return GENOPER_OPFAIL;
        }

        // Builders for children are defined
        fH_Builder *child1 = new fH_Builder();
        fH_Builder *child2 = new fH_Builder();

        child1->dimensions = child2->dimensions = parent1->dimensions;

        // Children Params are prepared for incoming handles
        child1->prepareParams();
        child2->prepareParams();

        int child1count = 0;
        int child2count = 0;

        for (unsigned int i = 0; i < parent1->sticks.size(); i++)
        {
                if (rndUint(2) == 0)
                {
                        child1->sticks.push_back(parent1->sticks[i]);
                        child1count++;
                }
                else
                {
                        child2->sticks.push_back(parent1->sticks[i]);
                }
        }

        for (unsigned int i = 0; i < parent2->sticks.size(); i++)
        {
                if (rndUint(2) == 0)
                {
                        child1->sticks.push_back(parent2->sticks[i]);
                }
                else
                {
                        child2->sticks.push_back(parent2->sticks[i]);
                        child2count++;
                }
        }

        // if one of children does not have any sticks, then other child takes
        // everything else
        bool skip1 = false;
        bool skip2 = false;
        if (child1->sticks.size() == 0) skip1 = true;
        if (child2->sticks.size() == 0) skip2 = true;

        for (unsigned int i = 0; i < parent1->neurons.size(); i++)
        {
                if ((rndUint(2) == 0 || skip2) && !skip1)
                {
                        child1->neurons.push_back(parent1->neurons[i]);
                        child1count++;
                }
                else
                {
                        child2->neurons.push_back(parent1->neurons[i]);
                }
        }

        for (unsigned int i = 0; i < parent2->neurons.size(); i++)
        {
                if ((rndUint(2) == 0 || skip2) && !skip1)
                {
                        child1->neurons.push_back(parent2->neurons[i]);
                }
                else
                {
                        child2->neurons.push_back(parent2->neurons[i]);
                        child2count++;
                }
        }

        for (unsigned int i = 0; i < parent1->connections.size(); i++)
        {
                if ((rndUint(2) == 0 || skip2) && !skip1)
                {
                        child1->connections.push_back(parent1->connections[i]);
                        child1count++;
                }
                else
                {
                        child2->connections.push_back(parent1->connections[i]);
                }
        }

        for (unsigned int i = 0; i < parent2->connections.size(); i++)
        {
                if ((rndUint(2) == 0 || skip2) && !skip1)
                {
                        child1->connections.push_back(parent2->connections[i]);
                }
                else
                {
                        child2->connections.push_back(parent2->connections[i]);
                        child2count++;
                }
        }

        chg1 = (float)child1count / (parent1->sticks.size() + parent1->neurons.size() + parent1->connections.size());
        chg2 = (float)child2count / (parent2->sticks.size() + parent2->neurons.size() + parent2->connections.size());

        free(g1);
        free(g2);
        if (skip1 && !skip2)
        {
                g1 = strdup(child2->toString().c_str());
                g2 = strdup("");
        }
        else if (!skip1 && skip2)
        {
                g1 = strdup(child1->toString().c_str());
                g2 = strdup("");
        }
        else
        {
                g1 = strdup(child1->toString().c_str());
                g2 = strdup(child2->toString().c_str());
        }

        child1->sticks.clear();
        child1->neurons.clear();
        child1->connections.clear();

        child2->sticks.clear();
        child2->neurons.clear();
        child2->connections.clear();

        delete parent1;
        delete parent2;
        delete child1;
        delete child2;

        return GENOPER_OK;
}

int Geno_fH::mutate(char *&geno, float& chg, int &method)
{
        // method only needs to parse genotype - it won't create Model
        fH_Builder *creature = new fH_Builder();
        if (creature->parseGenotype(geno) != 0)
        {
                return GENOPER_OPFAIL;
        }

        // used for computing chg
        unsigned int sumgenes = creature->sticks.size() + creature->neurons.size() + creature->connections.size();

        // if there is only one element in genotype (stick), then deletion would end
        // up with wrong genotype. If this occurs, deletion is skipped (deletion is
        // last possible operation listed in #defines, so fH_OPCOUNT - 1 will skip
        // this mutation, and roulette method will normalize the rest of probabilities)
        int skipdelete = 0;
        if (creature->sticks.size() + creature->neurons.size() + creature->connections.size() == 1)
        {
                skipdelete = 1;
        }

        method = roulette(operations, FH_OPCOUNT - skipdelete);
        switch (method) {
        case FH_ADD:
        {
                fH_Handle *handle = NULL;
                method = FH_OPCOUNT + roulette(addoperations, FH_ADD_OPCOUNT);
                if (getActiveNeuroClassCount(Model::SHAPETYPE_BALL_AND_STICK) == 0) method = FH_OPCOUNT + FH_ADD_STICK;
                switch (method - FH_OPCOUNT)
                {
                case FH_ADD_STICK:
                {
                        handle = new fH_StickHandle(creature->dimensions, 0, 0);
                        createHandleVectors(handle, creature->stickparamtab, creature->dimensions);
                        break;
                }
                case FH_ADD_NEURO:
                {
                        handle = new fH_NeuronHandle(creature->dimensions, 0, 0);
                        createHandleVectors(handle, creature->neuronparamtab, creature->dimensions);
                        break;
                }
                case FH_ADD_CONN:
                {
                        handle = new fH_ConnectionHandle(creature->dimensions, 0, 0);
                        createHandleVectors(handle, creature->connectionparamtab, creature->dimensions);
                        break;
                }
                }
                creature->addHandle(handle);
                break;
        }
        case FH_HANDLE:
        {
                ParamEntry *tab = NULL;
                fH_Handle *handle = NULL;
                getRandomHandle(creature, handle, tab, true);
                mutateHandleValues(handle, tab, creature->dimensions, true, false);
                break;
        }
        case FH_PROP:
        {
                ParamEntry *tab = NULL;
                fH_Handle *handle = NULL;
                getRandomHandle(creature, handle, tab, true);
                if (handle->type == fHBodyType::NEURON)
                {
                        mutateNeuronHandleProperties((fH_NeuronHandle *)handle, creature->neuronparamtab);
                }
                else
                {
                        mutateHandleValues(handle, tab, creature->dimensions, false, true);
                }
                break;
        }
        case FH_DEL:
        {
                ParamEntry *tab = NULL;
                fH_Handle *handle = NULL;
                int todelete = getRandomHandle(creature, handle, tab, true);
                switch (handle->type)
                {
                case JOINT:
                        creature->sticks.erase(creature->sticks.begin() + todelete);
                        break;
                case NEURON:
                        creature->neurons.erase(creature->neurons.begin() + todelete);
                        break;
                case CONNECTION:
                        creature->connections.erase(creature->connections.begin() + todelete);
                        break;
                }
                delete handle;
                break;
        }
        }
        free(geno);
        geno = strdup(creature->toString().c_str());
        chg = (double)1.0 / sumgenes;
        delete creature;
        return GENOPER_OK;
}

void Geno_fH::mutateHandleValues(fH_Handle *handle, ParamEntry *tab,
        int dimensions, bool changedimensions, bool changeproperties)
{
        Param par(tab, handle->obj);
        handle->saveProperties(par);
        if (changedimensions)
        {
                int i = rndUint(2 * dimensions);
                changeDoubleProperty(i, par, handle->type);
        }

        if (changeproperties)
        {
                int i = 2 * dimensions + rndUint(par.getPropCount() - 2 * dimensions);
                changeDoubleProperty(i, par, handle->type);
        }
        handle->loadProperties(par);
        //ParamObject::freeObject(obj);
}

void Geno_fH::createHandleVectors(fH_Handle *handle, ParamEntry *tab, int dimensions)
{
        void *obj = ParamObject::makeObject(tab);
        Param par(tab, obj);
        par.setDefault();
        double min, max, def;
        par.getMinMaxDouble(0, min, max, def);
        for (int i = 0; i < dimensions; i++)
        {
                par.setDouble(i, min + rndDouble(max - min));
                par.setDouble(i + dimensions, min + rndDouble(max - min));
        }
        handle->loadProperties(par);
        if (handle->type != fHBodyType::NEURON)
        {
                int i = 2 * dimensions + rndUint(par.getPropCount() - 2 * dimensions);
                changeDoubleProperty(i, par, handle->type);
        }
        else
        {
                mutateNeuronHandleProperties((fH_NeuronHandle *)handle, tab, true);
        }
}

void Geno_fH::changeDoubleProperty(int id, Param &par, fHBodyType type)
{
        double min, max, def;
        if (*par.type(id) == 'f')
        {
                // need to check if property is not weight of connection
                if (type != fHBodyType::CONNECTION || *par.id(id) != 'w')
                {
                        par.getMinMaxDouble(id, min, max, def);
                        par.setDouble(id, mutateCreep('f', par.getDouble(id), min, max, true));
                }
                else
                {
                        // if it is weight, then method needs to use mutateNeuProperty
                        double current = par.getDouble(id);
                        par.setDouble(id, getMutatedNeuronConnectionWeight(current));
                }
        }
        else
        {
                logMessage("Geno_fH", "changeDoubleProperty", LOG_WARN, "fH mutations are not prepared for non-double properties");
        }
}

unsigned int Geno_fH::getRandomHandle(fH_Builder *creature, fH_Handle *&handle, ParamEntry *&tab, bool skipalonestick)
{
        unsigned int allhandlescount = creature->connections.size() + creature->neurons.size();
        if (!skipalonestick || creature->sticks.size() > 1)
        {
                allhandlescount += creature->sticks.size();
        }
        unsigned int toselect = rndUint(allhandlescount);
        if (toselect < creature->connections.size())
        {
                handle = creature->connections[toselect];
                tab = creature->connectionparamtab;
                return toselect;
        }
        else if (toselect - creature->connections.size() < creature->neurons.size())
        {
                toselect -= creature->connections.size();
                handle = creature->neurons[toselect];
                tab = creature->neuronparamtab;
                return toselect;
        }
        toselect -= creature->connections.size() + creature->neurons.size();
        handle = creature->sticks[toselect];
        tab = creature->stickparamtab;
        return toselect;
}

void Geno_fH::mutateNeuronProperties(SString &det) //used also by the "fB" and "fL" encodings
{
        Neuro neu;
        neu.setDetails(det == "" ? "N" : det);
        GenoOperators::mutateRandomNeuroClassProperty(&neu);
        det = neu.getDetails();
}

void Geno_fH::mutateNeuronHandleProperties(fH_NeuronHandle *handle, ParamEntry *tab, bool userandomclass)
{
        Param hpar(tab, handle->obj);
        SString det;
        if (userandomclass)
        {
                NeuroClass *nc = getRandomNeuroClass(Model::SHAPETYPE_BALL_AND_STICK); // checking that neuron classes are available should be done before
                det = nc->getName();
        }
        else
        {
                det = hpar.getStringById("d");
        }
        mutateNeuronProperties(det);
        hpar.setStringById("d", det);
}

//uint32_t Geno_fH::style(const char *geno, int pos)
//{
//      char ch = geno[pos];
//      uint32_t style = GENSTYLE_CS(0, GENSTYLE_STRIKEOUT);
//      if (pos == 0 || geno[pos - 1] == '\n' || ch == ':') // single-character handle type and all colons
//      {
//              style = GENSTYLE_CS(GENCOLOR_TEXT, GENSTYLE_BOLD);
//      }
//      else if (isalpha(ch)) // properties name
//      {
//              style = GENSTYLE_RGBS(0, 200, 0, GENSTYLE_BOLD);
//      }
//      else if (isdigit(ch) || strchr(",.=", ch)) // properties values
//      {
//              style = GENSTYLE_CS(GENCOLOR_TEXT, GENSTYLE_NONE);
//      }
//      else if (ch == '\"')
//      {
//              style = GENSTYLE_RGBS(200, 0, 0, GENSTYLE_BOLD);
//      }
//
//      return style;
//}

uint32_t Geno_fH::style(const char *g, int pos)
{
        char ch = g[pos];
        uint32_t style = GENSTYLE_CS(0, GENSTYLE_NONE); //default, should be changed below

        int pp = pos; //detect comment line
        while (pp > 1 && g[pp - 1] != '\n') pp--;
        if (g[pp] == '#') return GENSTYLE_RGBS(0, 220, 0, GENSTYLE_NONE); //comment line

        if (pos == 0 || g[pos - 1] == '\n' || ch == ':' || ch == ',') style = GENSTYLE_CS(0, GENSTYLE_BOLD); else
                if (ch == '\"') style = GENSTYLE_RGBS(150, 0, 0, GENSTYLE_BOLD); else
                {
                        int cudz = 0, neuclass = 1; //ile cudz. do poczatku linii; czy w nazwie neuroklasy?
                        while (pos > 0)
                        {
                                pos--;
                                if (g[pos] == '\"') cudz++;
                                if (cudz == 0 && (g[pos] == ':' || g[pos] == ',')) neuclass = 0;
                                if (g[pos] == '\n') break;
                        }
                        if (cudz % 2)
                        {
                                if (neuclass) style = GENSTYLE_RGBS(150, 0, 150, GENSTYLE_BOLD); else //neuroclass
                                        if (isalpha(ch)) style = GENSTYLE_RGBS(255, 140, 0, GENSTYLE_BOLD); else //property
                                                style = GENSTYLE_RGBS(200, 0, 0, GENSTYLE_NONE);
                        }
                        else
                                if (isalpha(ch)) style = GENSTYLE_RGBS(0, 0, 200, GENSTYLE_BOLD);
                }
        return style;
}