frontends4.h 82.3 KB
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#ifndef _SPEL_FRONTENDS_H_
#define _SPEL_FRONTENDS_H_

#include "cache2.h"
#include "basic_data.h"
#include "model.h"
/*#include "model/tests.h"*/
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#include <regex>
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#include <boost/math/distributions/normal.hpp> // for normal_distribution
  using boost::math::normal; // typedef provides default type is double.
  using boost::math::cdf;
  using boost::math::mean;
  using boost::math::variance;
  using boost::math::quantile;
  using boost::math::complement;


typedef std::pair<const chromosome*, double> selected_locus;

inline bool operator < (const selected_locus& sl1, const selected_locus& sl2) { return sl1.first < sl2.first || (sl1.first == sl2.first && sl1.second < sl2.second); }

inline std::ostream& operator << (std::ostream& os, const selected_locus& sl) { return os << sl.first->name << ':' << sl.second; }


struct chromosome_search_domain {
    const chromosome* chrom;
    std::vector<double> loci;

    chromosome_search_domain(const chromosome* c, const std::vector<double>& l) : chrom(c), loci(l) {}

    struct const_iterator {
        const chromosome_search_domain* this_csd;
        std::vector<double>::const_iterator i;
        const_iterator() : this_csd(NULL), i(__()) {}
        const_iterator(const chromosome_search_domain* t, const std::vector<double>::const_iterator& i_) : this_csd(t), i(i_) {}
        bool operator == (const const_iterator& other) const { return i == other.i; }
        bool operator != (const const_iterator& other) const { return i != other.i; }
        /*bool operator < (const const_iterator& other) const { return i < other.i; }*/
        /*size_t operator - (const const_iterator& other) const { return i - other.i; }*/
        std::pair<const chromosome*, double> operator * () const { return {this_csd->chrom, *i}; }
        const_iterator& operator ++ () { ++i; return *this; }
        const_iterator& operator -- () { --i; return *this; }
        static std::vector<double>::const_iterator __() { static std::vector<double> _; return _.end(); }
    };

    const_iterator begin() const { return {this, loci.begin()}; }
    const_iterator end() const { return {this, loci.end()}; }
    const_iterator cbegin() const { return {this, loci.begin()}; }
    const_iterator cend() const { return {this, loci.end()}; }
};


typedef std::vector<chromosome_search_domain> genome_search_domain;

struct gsd_iterator {
    std::vector<chromosome_search_domain>::const_iterator csd_i, csd_j;
    chromosome_search_domain::const_iterator i, j;

    bool operator == (const gsd_iterator& other) const { return csd_i == other.csd_i && i == other.i; }
    bool operator != (const gsd_iterator& other) const { return csd_i != other.csd_i || i != other.i; }

    gsd_iterator&
        operator ++ ()
        {
            ++i;
            if (i == j) {
                MSG_DEBUG("at end of chromosome!");
                ++csd_i;
                if (csd_i != csd_j) {
                    i = csd_i->begin();
                    j = csd_i->end();
                } else {
                    i = {};
                    j = {};
                }
            }
            return *this;
        }

    std::pair<const chromosome*, double> operator * () const { return *i; }
};

namespace std {
    inline gsd_iterator begin(const genome_search_domain& gsd) { return {gsd.begin(), gsd.end(), gsd.begin()->begin(), gsd.begin()->end()}; }
    inline gsd_iterator end(const genome_search_domain& gsd) { return {gsd.end(), gsd.end(), {}, {}}; }
}


typedef std::vector<selected_locus> locus_set;

typedef std::vector<locus_set> model_descriptor;

std::pair<bool, double>
detect_strongest_qtl(chromosome_value chr, const locus_key& lk,
                     const model& M0, const std::vector<double> pos);

MatrixXd
ftest_along_chromosome(chromosome_value chr, const locus_key& lk,
                       const model& M0, const std::vector<double> pos);


/* Definitions:
 * - cofactor: isolated POP (single chromosome, single locus)
 * - QTLs: joint POP (single chromosome, single or multiple loc(i)us)
 *
 *
 * Configurations:
 * - with/without Dominance                          D
 * - with/without Constraints (can/can't estimate)   WC
 * - Joint/Single POP computation mode               JS
 *
 *
 * Steps:                           D   JS  WC
 * - establish skeleton                      
 *   - manual (marker list)                  
 *   - by step                               
 * - discover cofactors                 S    
 *   - manual                           S    
 *   - forward                          S    
 *   - backward                         S    
 * - detect QTLs                    ?   J   Y
 *   - CIM-                         ?   J   Y
 *   - iQTLm                        ?   J   Y
 *   - iQTLm++                      ?   J   Y
 * - OPTIONALLY analyze epistasis   ?   J   Y
 * - estimate parameters            
 *
 *
 * Operations:
 * - select chromosome
 * - cofactors to QTLs for the current chromosome
 * - QTLs to cofactors for the current chromosome
 * - test along the chromosome
 * - test along all chromosomes
 * - add cofactor (if current chromosome in product probability mode)
 * - add QTL (if current chromosome in joint probability mode)
 * - remove cofactor/QTL
 */


struct signal_display {
#ifdef SIGNAL_DISPLAY_ONELINER
    static const char* tick(double x)
    {
        static const char* ticks[9] = { " ", "\u2581", "\u2582", "\u2583", "\u2584", "\u2585", "\u2586", "\u2587", "\u2588" };
        return ticks[x < 0. ? 0
                            : x >= 1. ? 8
                                      : ((int) floor(x * 9))];
    }

    VectorXd values;
    int imax_;
    bool above_;

    signal_display(const VectorXd& v, int imax, bool above)
        : values(v.innerSize()), imax_(imax), above_(above)
    {
        values = v;
#if 0
        int sig_cols = msg_handler_t::termcols() - 3;
        MSG_DEBUG("values.innerSize = " << values.innerSize());
        MSG_QUEUE_FLUSH();
        while (values.innerSize() >= sig_cols) {
            if (values.innerSize() & 1) {
                int sz = values.innerSize();
                values.conservativeResize(sz + 1);
                values(sz) = values(sz - 1);
            }
            int i = values.innerSize() >> 1;
            values = values.transpose() * kroneckerProduct(MatrixXd::Identity(i, i), MatrixXd::Constant(1, 2, .5));
            MSG_DEBUG("values.innerSize = " << values.innerSize());
            MSG_QUEUE_FLUSH();
        }
#endif
        double vmin = values.minCoeff();
        double vmax = values.maxCoeff();
        if (vmin == vmax) {
            values = (values.array() - vmin).matrix();
        } else {
            values = ((values.array() - vmin) / (vmax - vmin)).matrix();
        }
    }

    friend std::ostream& operator << (std::ostream& os, const signal_display& sd)
    {
        os << _WHITE << '[';
        for (int i = 0; i < sd.values.innerSize(); ++i) {
            if (i == sd.imax_) {
                os << (sd.above_ ? _GREEN : _RED);
            }
            os << tick(sd.values(i));
            if (i == sd.imax_) {
                os << _WHITE;
            }
        }
        return os << ']' << _NORMAL;
    }
#else
    braille_grid grid;

    signal_display(const chromosome& chr, const std::vector<double>& X, const VectorXd& y, int imax, double threshold)
        : grid(build(chr, X, y, imax, threshold))
    {}

    braille_grid
        build(const chromosome& chr, const std::vector<double>& X, const VectorXd& y, int imax, double threshold)
        {
            std::vector<double> Y(y.data(), y.data() + y.size());
            int padding_left = 0;
            int W = (int) (msg_handler_t::termcols() * .8);
            if (W > 1000) {
                W = 80;
            }
            braille_grid chr_map = chr.pretty_print(W, {}, {}, padding_left, false);

            braille_plot plot(W - padding_left, 5, 0, X.back(), 0, std::max(threshold, y(imax)));
            plot.plot(X, Y);
            plot.hline(threshold, 1, 1, 0, 255, 0);
            bool above = y(imax) > threshold;
            plot.vline(X[imax], 1, 0, above ? 0 : 255, above ? 255 : 0, 0);
            return plot.compose_vert(true, chr_map, false);
        }

    friend
        std::ostream&
        operator << (std::ostream& os, const signal_display& sd)
        {
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            std::stringstream tmp;
            tmp << sd.grid;
            return os << tmp.str();
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        }
#endif
};


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struct model_manager;

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struct QTL {
    std::string chromosome;
    double locus;
    std::vector<double> LOD_loci;
    std::vector<double> LOD;

    QTL(const std::string& n, double l, const std::vector<double>& x, const MatrixXd& y)
        : chromosome(n), locus(l), LOD_loci(x), LOD(y.data(), y.data() + y.size())
    {
        /*MSG_DEBUG("QTL at " << chromosome << ':' << locus);*/
        /*MSG_DEBUG(y);*/
        /*MSG_DEBUG(MATRIX_SIZE(y));*/
        /*MSG_DEBUG("" << LOD);*/
    }

    static
        double
        interpolate(double x0, double y0, double x1, double y1, double yT)
        {
            double delta_x = x1 - x0;
            double delta_y = y1 - y0;
            return delta_x * (yT - y0) / delta_y + x0;
        }

    std::pair<double, double>
        confidence_interval(const std::string& trait, const std::vector<QTL>& selection);
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    std::pair<double, double>
        confidence_interval();
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#if 0
        {
            /*MSG_DEBUG_INDENT_EXPR("[Confidence interval] ");*/
            /*MSG_DEBUG("LOD: " << LOD);*/
            double maxLOD = *std::max_element(LOD.begin(), LOD.end());
            double lod_cap = maxLOD - 1.5;
            /*MSG_DEBUG("max=" << maxLOD << " threshold=" << lod_cap);*/
            int i;
            for (i = 0; i < (int) LOD_loci.size() && LOD_loci[i] < locus && LOD[i] < lod_cap; ++i);
            /*MSG_DEBUG("LEFT i=" << i);*/
            double left;
            if (i > 0) {
                left = interpolate(LOD_loci[i - 1], LOD[i - 1], LOD_loci[i], LOD[i], lod_cap);
            } else {
                left = LOD_loci[i];
            }
            for (i = LOD_loci.size() - 1; i >= 0 && LOD_loci[i] > locus && LOD[i] < lod_cap; --i);
            /*MSG_DEBUG("RIGHT i=" << i);*/
            double right;
            if (i < (int) (LOD_loci.size() - 1)) {
                right = interpolate(LOD_loci[i], LOD[i], LOD_loci[i + 1], LOD[i + 1], lod_cap);
            } else {
                right = LOD_loci[i];
            }
            /*MSG_INFO("Confidence interval for " << chromosome << ':' << locus << " {" << left << ':' << right << '}');*/
            /*MSG_DEBUG_DEDENT;*/
            return {left, right};
        }
#endif
};


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enum class AR: int { RSS=1, Rank=2, Test=4, Model=8, All=0xFF };
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inline
bool
operator & (AR a, AR b) { return !!(((int) a) & ((int) b)); }
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enum probability_mode { Joint, Single };


struct analysis_report {

    bool output_rss;
    bool output_rank;
    bool output_test;
    bool output_model;

    std::string report_path;

    std::string trait_name;

    std::string full_path;

    file report_file;

    std::map<std::string, std::map<double, std::string>> poi;
    std::map<std::string, std::map<double, std::pair<double, double>>> roi;

    analysis_report(const std::string& path, AR what)
        : output_rss(what & AR::RSS), output_rank(what & AR::Rank), output_test(what & AR::Test), output_model(what & AR::Model)
        , report_path(path)
        , trait_name()
        , full_path()
        , report_file()
        , poi(), roi()
    {
        ensure_directories_exist(report_path);
    }

    ~analysis_report()
    {
        report_file.close();
        report_file.open(MESSAGE(report_path << "/full_map.txt"), std::fstream::out);
        for (const auto& chr: active_settings->map) {
            report_file << chr.pretty_print(200, poi[chr.name], roi[chr.name]) << std::endl;
        }
    }

    void attach_model_manager(model_manager& mm);
    void detach_model_manager(model_manager& mm);

    void report_trait(const std::string& /*name*/, const MatrixXd& values)
    {
        static Eigen::IOFormat trait_format(Eigen::FullPrecision, Eigen::DontAlignCols, "\t", "\n", "", "", "", "");
        std::string filename = MESSAGE(full_path << '/' << "trait_values.txt");
        ofile of(filename);
        of << values.format(trait_format);
        of.close();
    }

    void report_lod(const QTL& qtl)
    {
        std::string filename = MESSAGE(full_path << '/' << qtl.chromosome << ':' << qtl.locus << "_LOD.txt");
        ofile of(filename);
        for (size_t i = 0; i < qtl.LOD.size(); ++i) {
            of << qtl.LOD_loci[i] << '\t' << qtl.LOD[i] << std::endl;
        }
        of.close();
    }

    void report_model(const model& Mcurrent)
    {
        if (output_model) {
            Mcurrent.output_X_to_file(full_path);
            Mcurrent.output_XtX_inv_to_file(full_path);
        }
    }

    /*enum ComputationType { NoTest=0, FTest=1, FTestLOD=2, R2=4, Chi2=8, Mahalanobis=16 };*/
    std::string
        computation_type_to_string(ComputationType ct)
        {
            std::stringstream ret;
            if (ct & FTest) { ret << "_FTest"; }
            if (ct & FTestLOD) { ret << "_FTestLOD"; }
            if (ct & R2) { ret << "_R2"; }
            if (ct & Chi2) { ret << "_Chi2"; }
            if (ct & Mahalanobis) { ret << "_Mahalanobis"; }
            return ret.str();
        }

    void report_computation(const model& Mcurrent, const chromosome* chrom_under_study, const computation_along_chromosome& cac, ComputationType ct, ComputationResults /*cr*/, const std::vector<double>& testpos, probability_mode pmode=Single)
    {
        if (output_test | output_rss | output_rank) {
            /*MSG_DEBUG(MATRIX_SIZE(cac.ftest_pvalue));*/
            /*MSG_DEBUG(MATRIX_SIZE(cac.rss));*/
            std::string path = MESSAGE(full_path << '/' << chrom_under_study->name);
            ensure_directories_exist(path);
            std::string filename
                = MESSAGE(path << '/' << Mcurrent.keys()
                        << (output_test ? computation_type_to_string(ct) : "")
                        << (output_rss ? "_RSS" : "")
                        << (output_rank ? "_Rank" : "")
                        << (pmode == Joint ? "_Joint" : "")
                        << ".txt"
                        );
            ofile f(filename);
            if (output_test) { f << '\t' << "Test"; }
            if (output_rss) { for (int i = 0; i < cac.rss.innerSize(); ++i) { f << '\t' << "RSS"; } }
            if (output_rank) { f << '\t' << "Rank"; }
            f << std::endl;
            for (size_t i = 0; i < testpos.size(); ++i) {
                f << testpos[i];
                if (output_test) {
                    switch(ct) {
                        case ComputationType::FTest:
                            f << '\t' << cac.ftest_pvalue(0, i);
                            break;
                        case ComputationType::FTestLOD:
                            f << '\t' << cac.ftest_lod(0, i);
                            break;
                        case ComputationType::Chi2:
                            f << '\t' << cac.chi2(0, i);
                            break;
                        default:
                            /*last_computation = NULL;*/
                            ;
                    };
                }
                if (output_rss) {
                    for (int j = 0; j < cac.rss.innerSize(); ++j) {
                        f << '\t' << cac.rss(j, i);
                    }
                }
                if (output_rank) {
                    f << '\t' << cac.rank(i);
                }
                f << std::endl;
            }
            f.close();
        }
    }

    void report_final_model(model_manager& mm);

    void report_qtls(std::vector<QTL>& qtls);
};


typedef std::pair<double, double> forbidden_interval_type;
typedef std::vector<forbidden_interval_type> forbidden_interval_vector_type;
typedef std::map<chromosome_value, forbidden_interval_vector_type> forbidden_interval_map_type;

inline bool operator < (const forbidden_interval_type& fi1, const forbidden_interval_type& fi2) { return fi1.first < fi2.first; }

struct search_interval_type;

struct test_result {
    search_interval_type* this_interval;
    const chromosome* chrom;
    double locus;
    double test_value;
    int index;
    bool over_threshold;
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    model_block_key pop_block_key;
    value<model_block_type> pop_block;
    model_block_key dom_block_key;
    value<model_block_type> dom_block;
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    test_result()
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        : chrom(NULL), locus(0), test_value(0), index(0), over_threshold(false), pop_block_key(), pop_block(), dom_block_key(), dom_block()
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    {}

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    test_result(search_interval_type* ti, const chromosome* c, double l, double tv, int i, bool ot, const model_block_key& mbk, const value<model_block_type>& mb, const model_block_key& mbkd, const value<model_block_type>& mbd)
        : this_interval(ti), chrom(c), locus(l), test_value(tv), index(i), over_threshold(ot), pop_block_key(mbk), pop_block(mb), dom_block_key(mbkd), dom_block(mbd)
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    {}

    test_result(const test_result& tr)
        : this_interval(tr.this_interval),
        chrom(tr.chrom), locus(tr.locus), test_value(tr.test_value),
        index(tr.index), over_threshold(tr.over_threshold),
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        pop_block_key(tr.pop_block_key), pop_block(tr.pop_block),
        dom_block_key(tr.dom_block_key), dom_block(tr.dom_block)
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    {}

    test_result&
        operator = (const test_result& tr)
        {
            this_interval = tr.this_interval;
            chrom = tr.chrom;
            locus = tr.locus;
            test_value = tr.test_value;
            index = tr.index;
            over_threshold = tr.over_threshold;
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            pop_block_key = tr.pop_block_key;
            pop_block = tr.pop_block;
            dom_block_key = tr.dom_block_key;
            dom_block = tr.dom_block;
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            return *this;
        }

    void reset()
    {
        chrom = NULL;
        locus = 0;
        test_value = 0;
        index = 0;
        over_threshold = false;
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        /*block_key.selection.clear();*/
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        pop_block_key.reset();
        pop_block = value<model_block_type>();
        dom_block_key.reset();
        dom_block = value<model_block_type>();
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    }

    friend
        std::ostream& operator << (std::ostream& os, const test_result& tr)
        {
            os << "<result chrom=" << (tr.chrom ? tr.chrom->name : "nil")
                << " locus=" << tr.locus
                << " test=" << tr.test_value
                << " at=" << tr.index
                << " over?=" << tr.over_threshold
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                << " block_key=" << tr.pop_block_key
                << " dominance_block_key=" << tr.dom_block_key
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                << '>';
            return os;
        }

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    bool
        operator < (const test_result& other) const
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        {
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            return test_value < other.test_value;
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        }
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    void
        select(model_manager& mm) const;
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};


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locus_probabilities_type
locus_probabilities(const context_key& ck, const locus_key& lk,
                    /*const MatrixXd& mgo,*/
                    int ind,
                    const std::vector<double>& loci);

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struct search_interval_type {
    probability_mode mode;
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    const chromosome* chrom;
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    /* all positions in this interval */
    std::vector<double> all_positions;
    /* all USED positions in this interval */
    std::vector<double> positions;
    /* positions actually used in the segment test (all_positions \ selection \ forbidden_intervals) */
    std::vector<double> effective_positions;
    /* current selection (subset of base model's selection for this search interval) */
    locus_key selection;
    /* the model blocks along the chromosome currently under study */
    collection<model_block_type> locus_blocks;
    /* dominance matrices per locus per population */
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    collection<parental_origin_per_locus_type> dominance_blocks;
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    test_result local_max;

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    search_interval_type(probability_mode pm, const chromosome* chr)
        : mode(pm)
        , chrom(chr)
        , all_positions()
        , positions()
        , effective_positions()
        , selection()
        , locus_blocks()
        , dominance_blocks()
        , local_max()
    {}

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    search_interval_type(const search_interval_type& si)
        : mode(si.mode)
        , chrom(si.chrom)
        , all_positions(si.all_positions)
        , positions(si.positions)
        , effective_positions(si.effective_positions)
        , selection(si.selection)
        , locus_blocks(si.locus_blocks)
        , dominance_blocks(si.dominance_blocks)
        , local_max(si.local_max)
    {}

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    void
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        clear()
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        {
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            positions.clear();
            effective_positions.clear();
            locus_blocks.clear();
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        }

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    bool
        contains_position(double l) const
        {
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            return l >= all_positions.front() && l <= all_positions.back()/* && std::find(all_positions.begin(), all_positions.end(), l) != all_positions.end()*/;
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        }
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    void
        compute_positions(forbidden_interval_vector_type::const_iterator& fi, forbidden_interval_vector_type::const_iterator& fj)
        {
            positions.clear();
            positions.reserve(all_positions.size());
            for (double d: all_positions) {
                for (; fi != fj && d > fi->second; ++fi);
                if (fi == fj || d < fi->first) {
                    positions.push_back(d);
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                }
            }
        }
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    void
        test(const collection<population_value>& all_pops, int i0, computation_along_chromosome& cac, value<ComputationType> vct, value<ComputationResults> vcr, const value<model>& Mcurrent, const value<model>& Mbase, double threshold)
        {
            locus_key lk;
            if (mode == Joint) {
                lk = selection;
            }
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            /*MSG_DEBUG("Running test along interval with lk=" << lk);*/
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            test(all_pops, i0, cac, vct, vcr, Mcurrent, Mbase, lk, positions, threshold);
        }

    void
        test(const collection<population_value>& all_pops, int i0, computation_along_chromosome& cac, value<ComputationType> vct, value<ComputationResults> vcr, const value<model>& Mcurrent, const value<model>& Mbase,
             const locus_key& lk, const std::vector<double>& steps, double threshold)
        {
            if (positions.size()) {
                if (!locus_blocks.size()) {
                    _recompute(all_pops, lk, steps, effective_positions);
                }
                compute_along_interval<>(i0, cac, vct, vcr, Mcurrent, Mbase, lk, chrom, effective_positions, locus_blocks);
                local_max = find_max(i0, vct, cac, threshold);
            } else {
                local_max.reset();
            }
        }

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    std::pair<value<model_block_type>, value<model_block_type>>
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        compute_at(const collection<population_value>& all_pops, double position)
        {
            if (locus_blocks.size() > 0) {
                auto it = std::find(effective_positions.begin(), effective_positions.end(), position);
                if (it != effective_positions.end()) {
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                    auto ofs = it - effective_positions.begin();
                    return {locus_blocks[ofs], dominance_blocks[ofs]};
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                }
            }
            local_max.reset();
            std::vector<double> tmp_pos = {position};
            positions.swap(tmp_pos);
            locus_key lk;
            if (mode == Joint) {
                lk = selection;
            }
            _recompute(all_pops, lk, positions, effective_positions);
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            std::pair<value<model_block_type>, value<model_block_type>> ret;
            ret.first = locus_blocks[0];
            ret.second = dominance_blocks[0];
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            locus_blocks.clear();
            effective_positions.clear();
            positions.swap(tmp_pos);
            return ret;
        }

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    size_t
        count_positions() const
        {
            if (mode == Joint) {
                return positions.size() - selection->depth();
            }
            return positions.size();
        }

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    void
        _recompute(const collection<population_value>& all_pops, const locus_key& lk, const std::vector<double>& loci, std::vector<double>& effective_pos)
        {
            std::vector<double>::const_iterator i = loci.begin(), j = loci.end();
            effective_pos.clear();
            effective_pos.reserve(loci.size());
            if (lk) {
                for (; i != j; ++i) {
                    if (!lk->has(*i)) {
                        effective_pos.push_back(*i);
                    }
                }
            } else {
                effective_pos.assign(i, j);
            }
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            /*MSG_DEBUG("search_interval recompute mode=" << (mode == Joint ? "Joint" : "Single") << " lk=" << lk);*/
            /* precompute locus probabilities first */
            MSG_DEBUG("Precomputing locus probabilities per individual");
            for (const auto& vpop: all_pops) {
                context_key ck(new context_key_struc(*vpop, chrom, loci));
                for (auto& x: make_collection<Disk>(locus_probabilities,
                                                    as_value(ck), as_value(lk), range<int>(0, (*vpop)->size(), 1),
                                                    as_value(ck->loci))) {
                    (void)*x;
                }
            }
            MSG_DEBUG("Computing parental origin probabilities");
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            locus_blocks
                = compute_parental_origins_multipop(
                        all_pops,
                        as_value(chrom),
                        as_value(lk),
                        loci,
                        effective_pos);
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            MSG_DEBUG("Computing dominance probabilities");
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            dominance_blocks
                = compute_dominance_multipop(
                        all_pops,
                        as_value(chrom),
                        as_value(lk),
                        loci,
                        effective_pos);
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        }
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    test_result
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        find_max(int i0, value<ComputationType> vct, computation_along_chromosome &cac, double threshold)
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        {
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            MSG_DEBUG("call to find_max");
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            auto ct = *vct;
            auto last_computation =
                (ct == ComputationType::FTest ? cac.ftest_pvalue
                                              : ct == FTestLOD ? cac.ftest_lod
                                                               : /* has to be Chi2 */ cac.chi2).middleCols(i0, effective_positions.size());
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            if (effective_positions.size() != (size_t)(last_computation.outerSize())) {
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                MSG_ERROR("LOCI INCONSISTENT WITH COMPUTATION RESULT (" << effective_positions.size() << " vs " << last_computation.outerSize() << ")", "");
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            }
            int i_max = -1;
            double max = -1;
            for (int i = 0; i < last_computation.outerSize(); ++i) {
                if (last_computation(0, i) >= max) {
                    max = last_computation(0, i);
                    i_max = i;
                }
            }
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#ifdef SIGNAL_DISPLAY_ONELINER
        signal_display sd(last_computation.transpose(), i_max, max > threshold);
        MSG_DEBUG("[COMPUTATION] " << effective_positions.front() << sd << effective_positions.back() << " max=" << max << " at " << effective_positions[i_max]);
#else
        signal_display sd(*chrom, effective_positions, last_computation.transpose(), i_max, threshold);
        MSG_DEBUG("[COMPUTATION] " << effective_positions.front() << " ... " << effective_positions.back() << " max=" << max << " at " << effective_positions[i_max] << std::endl << sd);
#endif

        if (i_max == -1) {
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                return {};
            }
            /*model_block_key k = locus_base_key;*/
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            model_block_key mbk;
            if (mode == Joint) {
                mbk = model_block_key_struc::pop(chrom, selection + effective_positions[i_max]);
            } else {
                mbk = model_block_key_struc::pop(chrom, locus_key{} + effective_positions[i_max]);
            }
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            /*model_block_key mbk = locus_base_key;*/
            /*mbk += std::make_pair(chrom, (*loci)[i_max]);*/
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            /*MSG_DEBUG("locus_base_key " << locus_base_key << " mbk " << mbk);*/
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/*
            MSG_DEBUG("last_computation@" << last_computation);
            MSG_QUEUE_FLUSH();
            MSG_DEBUG((*last_computation));
            MSG_QUEUE_FLUSH();
*/
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            return {
                this, chrom,
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                effective_positions[i_max], max, i_max, max > threshold,
                mbk,
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                locus_blocks[i_max],
                dominance_blocks[i_max]->cols() ? model_block_key_struc::dominance(mbk) : model_block_key{},
                dominance_blocks[i_max]
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            };
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        }

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    void
        select(const test_result& tr, value<model> M)
        {
            assert(chrom == tr.chrom);
            if (mode == Joint) {
                M->remove_block(model_block_key_struc::pop(chrom, selection));
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                selection = tr.pop_block_key->loci;
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            } else {
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                selection = selection + tr.pop_block_key->loci;
            }
            MSG_DEBUG("Adding block " << tr.pop_block_key);
            M->add_block(tr.pop_block_key, tr.pop_block);
            if (tr.dom_block_key) {
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                model ref = *M;
                ref.compute();
                M->add_block_if_test_is_good(tr.dom_block_key, tr.dom_block, ref);
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            }
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        }
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    void
        deselect(double position, const collection<population_value>& all_pops, value<model> M)
        {
            if (mode == Joint) {
                auto vmbk = model_block_key_struc::pop(chrom, selection);
                value<model_block_type> vblock = M->m_blocks[vmbk];
                M->remove_block(vmbk);
                /* Need to add the reduced block now */
                if (selection->depth() > 1) {
                    reduce(all_pops, position, vblock);
                    M->add_block(model_block_key_struc::pop(chrom, selection - position), vblock);
                }
            } else {
                locus_key lk;
                lk = lk + position;
                M->remove_block(model_block_key_struc::pop(chrom, lk));
            }
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            locus_blocks.clear();
            selection = selection - position;
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            /*deselect(position);*/
        }

    std::pair<model_block_key, model_block_key>
        select(double pos)
        {
            std::pair<model_block_key, model_block_key> ret;
            if (mode == Joint) {
                ret.second = model_block_key_struc::pop(chrom, selection);
            }
            selection = selection + pos;
            if (mode == Single) {
                ret.first = model_block_key_struc::pop(chrom, locus_key{} + pos);
            } else {
                ret.first = model_block_key_struc::pop(chrom, selection);
            }
            locus_blocks.clear();
            return ret;
        }

    std::pair<model_block_key, model_block_key>
        deselect(double pos)
        {
            std::pair<model_block_key, model_block_key> ret;
            if (mode == Joint) {
                ret.second = model_block_key_struc::pop(chrom, selection);
            } else {
                ret.second = model_block_key_struc::pop(chrom, locus_key{} + pos);
            }
            selection = selection - pos;
            if (mode == Joint && selection) {
                ret.first = model_block_key_struc::pop(chrom, selection);
            }
            locus_blocks.clear();
            return ret;
        }

    void
        reduce(const collection<population_value>& all_pops, double position, value<model_block_type>& vblock)
        {
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            /* FIXME what about dominance?? */
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            locus_key lk2 = selection - position;
            auto pop_it = all_pops.begin();
            auto pb = disassemble_parental_origins_multipop(chrom, selection->parent, *vblock, all_pops);
            std::vector<collection<parental_origin_per_locus_type>> all_popl;
            all_popl.reserve(pb.size());
            for (auto& vmat: pb) {
                const qtl_pop_type* pop = **pop_it++;
                context_key ck(new context_key_struc(pop, chrom, std::vector<double>()));
                MatrixXd red = selection->reduce(active_settings->parent_count_per_pop_per_chr
                                                    .find(pop->qtl_generation_name)->second.find(chrom)->second,
                                                 position);
                MatrixXd data = vmat->data * red;
                vmat->data = data;
                vmat->column_labels = get_stpom_data(ck, lk2->parent)->row_labels;
                all_popl.emplace_back();
                all_popl.back().push_back(vmat);
            }
            vblock = assemble_parental_origins_multipop(as_value(chrom),
                                                        as_value(lk2->parent),
                                                        all_popl,
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                                                        all_pops,
                                                        true)[0];
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        }
};


typedef std::map<chromosome_value, std::vector<search_interval_type>> search_interval_map_type;


inline
search_interval_map_type
skeleton_search_intervals()
{
    search_interval_map_type ret;

    for (const chromosome& chr: active_settings->map) {
        ret[&chr].emplace_back(Single, &chr);
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    }

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    if (active_settings->skeleton_mode == "auto") {
        for (const chromosome& chr: active_settings->map) {
            double accept = -1.;
            for (double l: chr.condensed.marker_locus) {
                if (l > accept) {
                    ret[&chr].back().all_positions.push_back(l);
                    accept = l + active_settings->skeleton_interval;
                }
            }
        }
    } else if (active_settings->skeleton_mode == "manual") {
        for (const auto& name: active_settings->skeleton_markers) {
            bool found = false;
            for (const chromosome& chr: active_settings->map) {
                auto li = chr.condensed.marker_locus.begin();
                auto lj = chr.condensed.marker_locus.end();
                auto ni = chr.condensed.marker_name.begin();
                for (; li != lj; ++li, ++ni) {
                    if (*ni == name) {
                        ret[&chr].back().all_positions.push_back(*li);
                        found = true;
                        break;
                    }
                }
                if (found) {
                    break;
                }
            }
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        }
    }

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    return ret;
}


inline
search_interval_map_type
full_search_intervals()
{
    search_interval_map_type ret;
    /* TODO: add definition of intervals to command line: chromosome, mode, beginning, end */

    for (const chromosome& chr: active_settings->map) {
        ret[&chr].emplace_back(Single, &chr);
        ret[&chr].back().all_positions = active_settings->estimation_loci[&chr];
    }

    return ret;
}
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void
read_locus_list(std::string& s, settings_t* target);


952
struct model_manager {
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    /* name of the studied trait */
    std::string trait_name;
    double threshold;
    /* populations used in this model */
    collection<population_value> all_pops;
    /* thy reference model */
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    value<model> vMcurrent;
    /* thy maximum order for interaction blocks */
    size_t max_order;
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    /* all steps, split by haplotypic intervals, inside which joint probabilities must be computed */
965
    search_interval_map_type search_intervals;
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    /* the current selection split by haplotypic interval */
    std::map<chromosome_value, std::vector<locus_key>> selection;
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    /* a collection of intervals to not search in, if the user wishes so */
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    forbidden_interval_map_type forbidden_intervals;

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    /* structure to cache the results of the last computation along the chromosome */
    std::map<chromosome_value, computation_along_chromosome> cac;

976
    std::map<chromosome_value, std::vector<double>> testpos;
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    /* additiona, colpops.front()->ancestor_namesl data for output and postprocessing */
    std::map<std::string, std::map<double, std::pair<double, double>>> qtl_confidence_interval;

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    std::map<chromosome_value, MatrixXd*> last_computation;
    std::map<chromosome_value, test_result> last_best;

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    analysis_report* reporter;

/* Construction
 */
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    model_manager(const std::string& trait, const collection<population_value>& colpops,
989
                   const value<MatrixXd>& y,
990
                   size_t maximum_order = 1,
991
                   /*ComputationType ct = ComputationType::FTest,*/
992
                   SolverType st=SolverType::QR)
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        : trait_name(trait)
        , all_pops(colpops)
995
        , vMcurrent(model{y, active_settings->get_threshold(trait), colpops, (*colpops.front())->ancestor_names, maximum_order, st})
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        , max_order(maximum_order)
997
        , search_intervals()
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        , cac()
        , testpos()
        , qtl_confidence_interval()