root/library/bdm/itpp_ext.cpp @ 1274

//
// C++ Implementation: itpp_ext
//
// Description:
//
//
// Author: smidl <smidl@utia.cas.cz>, (C) 2008
//
// Copyright: See COPYING file that comes with this distribution
//
//

#include "itpp_ext.h"

#ifndef M_PI
#define M_PI        3.14159265358979323846
#endif
// from  algebra/lapack.h

extern "C" {  /* QR factorization of a general matrix A  */
    void dgeqrf_ ( int *m, int *n, double *a, int *lda, double *tau, double *work,
                   int *lwork, int *info );
};

namespace itpp {
vec empty_vec = vec ( 0 );

Array<int> to_Arr ( const ivec &indices ) {
    Array<int> a ( indices.size() );
    for ( int i = 0; i < a.size(); i++ ) {
        a ( i ) = indices ( i );
    }
    return a;
}

ivec linspace ( int from, int to ) {
    int n = to - from + 1;
    int i;
    it_assert_debug ( n > 0, "wrong linspace" );
    ivec iv ( n );
    for ( i = 0; i < n; i++ ) iv ( i ) = from + i;
    return iv;
};

void set_subvector ( vec &ov, const ivec &iv, const vec &v ) {
    it_assert_debug ( ( iv.length() <= v.length() ),
                      "Vec<>::set_subvector(ivec, vec<Num_T>): Indexing out "
                      "of range of v" );
    for ( int i = 0; i < iv.length(); i++ ) {
        it_assert_debug ( iv ( i ) < ov.length(),
                          "Vec<>::set_subvector(ivec, vec<Num_T>): Indexing out "
                          "of range of v" );
        ov ( iv ( i ) ) = v ( i );
    }
}

//! return vector of elements at positions given by indexlist
vec get_vec ( const vec &v, const ivec &indexlist ) {
    int size = indexlist.size();
    vec temp ( size );
    for ( int i = 0; i < size; ++i ) {
        temp ( i ) = v._data() [indexlist ( i ) ];
    }
    return temp;
}

// Gamma
#define log std::log
#define exp std::exp
#define sqrt std::sqrt
#define R_FINITE std::isfinite

bvec operator> ( const vec &t1, const vec &t2 ) {
    it_assert_debug ( t1.length() == t2.length(), "Vec<>::operator>(): different size of vectors" );
    bvec temp ( t1.length() );
    for ( int i = 0; i < t1.length(); i++ )
        temp ( i ) = ( t1[i] > t2[i] );
    return temp;
}

bvec operator< ( const vec &t1, const vec &t2 ) {
    it_assert_debug ( t1.length() == t2.length(), "Vec<>::operator>(): different size of vectors" );
    bvec temp ( t1.length() );
    for ( int i = 0; i < t1.length(); i++ )
        temp ( i ) = ( t1[i] < t2[i] );
    return temp;
}


bvec operator& ( const bvec &a, const bvec &b ) {
    it_assert_debug ( b.size() == a.size(), "operator&(): Vectors of different lengths" );

    bvec temp ( a.size() );
    for ( int i = 0; i < a.size(); i++ ) {
        temp ( i ) = a ( i ) & b ( i );
    }
    return temp;
}

bvec operator| ( const bvec &a, const bvec &b ) {
    it_assert_debug ( b.size() == a.size(), "operator|(): Vectors of different lengths" );

    bvec temp ( a.size() );
    for ( int i = 0; i < a.size(); i++ ) {
        temp ( i ) = a ( i ) | b ( i );
    }
    return temp;
}

//! poor man's operator vec(bvec) - copied for svn version of itpp
ivec get_from_bvec ( const ivec &v, const bvec &binlist ) {
    int size = binlist.size();
    it_assert_debug ( v.size() == size, "Vec<>::operator()(bvec &): "
                      "Wrong size of binlist vector" );
    ivec temp ( size );
    int j = 0;
    for ( int i = 0; i < size; ++i )
        if ( binlist ( i ) == bin ( 1 ) )
            temp ( j++ ) = v ( i );
    temp.set_size ( j, true );
    return temp;
}

vec get_from_ivec ( const ivec &v ) {
        vec temp ( v.size() );
        for ( int i = 0; i < v.size(); ++i )
                temp(i)=v(i);
        return temp;
}


//#if 0
Gamma_RNG::Gamma_RNG ( double a, double b ) {
    setup ( a, b );
}
double  Gamma_RNG::sample() {
    //A copy of rgamma code from the R package!!
    //

    /* Constants : */
    const static double sqrt32 = 5.656854;
    const static double exp_m1 = 0.36787944117144232159;/* exp(-1) = 1/e */

    /* Coefficients q[k] - for q0 = sum(q[k]*a^(-k))
     * Coefficients a[k] - for q = q0+(t*t/2)*sum(a[k]*v^k)
     * Coefficients e[k] - for exp(q)-1 = sum(e[k]*q^k)
     */
    const static double q1 = 0.04166669;
    const static double q2 = 0.02083148;
    const static double q3 = 0.00801191;
    const static double q4 = 0.00144121;
    const static double q5 = -7.388e-5;
    const static double q6 = 2.4511e-4;
    const static double q7 = 2.424e-4;

    const static double a1 = 0.3333333;
    const static double a2 = -0.250003;
    const static double a3 = 0.2000062;
    const static double a4 = -0.1662921;
    const static double a5 = 0.1423657;
    const static double a6 = -0.1367177;
    const static double a7 = 0.1233795;

    /* State variables [FIXME for threading!] :*/
    static double aa = 0.;
    static double aaa = 0.;
    static double s, s2, d;    /* no. 1 (step 1) */
    static double q0, b, si, c;/* no. 2 (step 4) */

    double e, p, q, r, t, u, v, w, x, ret_val;
    double a = alpha;
    double scale = 1.0 / beta;

    if ( !R_FINITE ( a ) || !R_FINITE ( scale ) || a < 0.0 || scale <= 0.0 ) {
        it_error ( "Gamma_RNG wrong parameters" );
    }

    if ( a < 1. ) { /* GS algorithm for parameters a < 1 */
        if ( a == 0 )
            return 0.;
        e = 1.0 + exp_m1 * a;
        for ( ;; ) {  //VS repeat
            p = e * unif_rand();
            if ( p >= 1.0 ) {
                x = -log ( ( e - p ) / a );
                if ( exp_rand() >= ( 1.0 - a ) * log ( x ) )
                    break;
            } else {
                x = exp ( log ( p ) / a );
                if ( exp_rand() >= x )
                    break;
            }
        }
        return scale * x;
    }

    /* --- a >= 1 : GD algorithm --- */

    /* Step 1: Recalculations of s2, s, d if a has changed */
    if ( a != aa ) {
        aa = a;
        s2 = a - 0.5;
        s = sqrt ( s2 );
        d = sqrt32 - s * 12.0;
    }
    /* Step 2: t = standard normal deviate,
               x = (s,1/2) -normal deviate. */

    /* immediate acceptance (i) */
    t = norm_rand();
    x = s + 0.5 * t;
    ret_val = x * x;
    if ( t >= 0.0 )
        return scale * ret_val;

    /* Step 3: u = 0,1 - uniform sample. squeeze acceptance (s) */
    u = unif_rand();
    if ( ( d * u ) <= ( t * t * t ) )
        return scale * ret_val;

    /* Step 4: recalculations of q0, b, si, c if necessary */

    if ( a != aaa ) {
        aaa = a;
        r = 1.0 / a;
        q0 = ( ( ( ( ( ( q7 * r + q6 ) * r + q5 ) * r + q4 ) * r + q3 ) * r
                 + q2 ) * r + q1 ) * r;

        /* Approximation depending on size of parameter a */
        /* The constants in the expressions for b, si and c */
        /* were established by numerical experiments */

        if ( a <= 3.686 ) {
            b = 0.463 + s + 0.178 * s2;
            si = 1.235;
            c = 0.195 / s - 0.079 + 0.16 * s;
        } else if ( a <= 13.022 ) {
            b = 1.654 + 0.0076 * s2;
            si = 1.68 / s + 0.275;
            c = 0.062 / s + 0.024;
        } else {
            b = 1.77;
            si = 0.75;
            c = 0.1515 / s;
        }
    }
    /* Step 5: no quotient test if x not positive */

    if ( x > 0.0 ) {
        /* Step 6: calculation of v and quotient q */
        v = t / ( s + s );
        if ( fabs ( v ) <= 0.25 )
            q = q0 + 0.5 * t * t * ( ( ( ( ( ( a7 * v + a6 ) * v + a5 ) * v + a4 ) * v
                                         + a3 ) * v + a2 ) * v + a1 ) * v;
        else
            q = q0 - s * t + 0.25 * t * t + ( s2 + s2 ) * log ( 1.0 + v );


        /* Step 7: quotient acceptance (q) */
        if ( log ( 1.0 - u ) <= q )
            return scale * ret_val;
    }

    for ( ;; ) { //VS repeat
        /* Step 8: e = standard exponential deviate
         *      u =  0,1 -uniform deviate
         *      t = (b,si)-double exponential (laplace) sample */
        e = exp_rand();
        u = unif_rand();
        u = u + u - 1.0;
        if ( u < 0.0 )
            t = b - si * e;
        else
            t = b + si * e;
        /* Step  9:  rejection if t < tau(1) = -0.71874483771719 */
        if ( t >= -0.71874483771719 ) {
            /* Step 10:  calculation of v and quotient q */
            v = t / ( s + s );
            if ( fabs ( v ) <= 0.25 )
                q = q0 + 0.5 * t * t *
                    ( ( ( ( ( ( a7 * v + a6 ) * v + a5 ) * v + a4 ) * v + a3 ) * v
                        + a2 ) * v + a1 ) * v;
            else
                q = q0 - s * t + 0.25 * t * t + ( s2 + s2 ) * log ( 1.0 + v );
            /* Step 11:  hat acceptance (h) */
            /* (if q not positive go to step 8) */
            if ( q > 0.0 ) {
                // TODO: w = expm1(q);
                w = exp ( q ) - 1;
                /*  ^^^^^ original code had approximation with rel.err < 2e-7 */
                /* if t is rejected sample again at step 8 */
                if ( ( c * fabs ( u ) ) <= ( w * exp ( e - 0.5 * t * t ) ) )
                    break;
            }
        }
    } /* repeat .. until  `t' is accepted */
    x = s + 0.5 * t;
    return scale * x * x;
}


bool qr ( const mat &A, mat &R ) {
    int info;
    int m = A.rows();
    int n = A.cols();
    int lwork = n;
    int k = std::min ( m, n );
    vec tau ( k );
    vec work ( lwork );

    R = A;

    // perform workspace query for optimum lwork value
    int lwork_tmp = -1;
    dgeqrf_ ( &m, &n, R._data(), &m, tau._data(), work._data(), &lwork_tmp,
              &info );
    if ( info == 0 ) {
        lwork = static_cast<int> ( work ( 0 ) );
        work.set_size ( lwork, false );
    }
    dgeqrf_ ( &m, &n, R._data(), &m, tau._data(), work._data(), &lwork, &info );

    // construct R
    for ( int i = 0; i < m; i++ )
        for ( int j = 0; j < std::min ( i, n ); j++ )
            R ( i, j ) = 0;

    return ( info == 0 );
}

//#endif
std::string num2str ( double d ) {
    char tmp[20];//that should do
    sprintf ( tmp, "%f", d );
    return std::string ( tmp );
};
std::string num2str ( int i ) {
    char tmp[10];//that should do
    sprintf ( tmp, "%d", i );
    return std::string ( tmp );
};

// digamma
// copied from C. Bonds' source
#include <math.h>
#define el 0.5772156649015329

double psi ( double x ) {
    double s, ps, xa, x2;
    int n, k;
    static double a[] = {
        -0.8333333333333e-01,
        0.83333333333333333e-02,
        -0.39682539682539683e-02,
        0.41666666666666667e-02,
        -0.75757575757575758e-02,
        0.21092796092796093e-01,
        -0.83333333333333333e-01,
        0.4432598039215686
    };

    xa = fabs ( x );
    s = 0.0;
    if ( ( x == ( int ) x ) && ( x <= 0.0 ) ) {
        ps = 1e308;
        return ps;
    }
    if ( xa == ( int ) xa ) {
        n = (int) xa;
        for ( k = 1; k < n; k++ ) {
            s += 1.0 / k;
        }
        ps =  s - el;
    } else if ( ( xa + 0.5 ) == ( ( int ) ( xa + 0.5 ) ) ) {
        n = (int) (xa - 0.5);
        for ( k = 1; k <= n; k++ ) {
            s += 1.0 / ( 2.0 * k - 1.0 );
        }
        ps = 2.0 * s - el - 1.386294361119891;
    } else {
        if ( xa < 10.0 ) {
            n = 10 - ( int ) xa;
            for ( k = 0; k < n; k++ ) {
                s += 1.0 / ( xa + k );
            }
            xa += n;
        }
        x2 = 1.0 / ( xa * xa );
        ps = log ( xa ) - 0.5 / xa + x2 * ( ( ( ( ( ( ( a[7] * x2 + a[6] ) * x2 + a[5] ) * x2 +
                                                a[4] ) * x2 + a[3] ) * x2 + a[2] ) * x2 + a[1] ) * x2 + a[0] );
        ps -= s;
    }
    if ( x < 0.0 )
        ps = ps - M_PI * std::cos ( M_PI * x ) / std::sin ( M_PI * x ) - 1.0 / x;
    return ps;
}

void triu ( mat &A ) {
    for ( int i = 1; i < A.rows(); i++ ) { // row cycle
        for ( int j = 0; (j < i) && (j<A.cols()); j++ ) {
            A ( i, j ) = 0;
        }
    }
}

//! Storage of randun() internals
class RandunStorage {
    const int A;
    const int M;
    static double seed;
    static int counter;
public:
    RandunStorage() : A ( 16807 ), M ( 2147483647 ) {};
    //!set seed of the randun() generator
    void set_seed ( double seed0 ) {
        seed = seed0;
    }
    //! generate randun() sample
    double get() {
        long long tmp = (long long) (A * seed);
        tmp = tmp % M;
        seed = (double) tmp;
        counter++;
        return seed / M;
    }
};
static RandunStorage randun_global_storage;
double RandunStorage::seed = 1111111;
int RandunStorage::counter = 0;
double randun() {
    return randun_global_storage.get();
};
vec randun ( int n ) {
    vec res ( n );
    for ( int i = 0; i < n; i++ ) {
        res ( i ) = randun();
    };
    return res;
};
mat randun ( int n, int m ) {
    mat res ( n, m );
    for ( int i = 0; i < n*m; i++ ) {
        res ( i ) = randun();
    };
    return res;
};

ivec unique ( const ivec &in ) {
    ivec uniq ( 0 );
    int j = 0;
    bool found = false;
    for ( int i = 0; i < in.length(); i++ ) {
        found = false;
        j = 0;
        while ( ( !found ) && ( j < uniq.length() ) ) {
            if ( in ( i ) == uniq ( j ) ) found = true;
            j++;
        }
        if ( !found ) uniq = concat ( uniq, in ( i ) );
    }
    return uniq;
}

ivec unique_complement ( const ivec &in, const ivec &base ) {
    // almost a copy of unique
    ivec uniq ( 0 );
    int j = 0;
    bool found = false;
    for ( int i = 0; i < in.length(); i++ ) {
        found = false;
        j = 0;
        while ( ( !found ) && ( j < uniq.length() ) ) {
            if ( in ( i ) == uniq ( j ) ) found = true;
            j++;
        }
        j = 0;
        while ( ( !found ) && ( j < base.length() ) ) {
            if ( in ( i ) == base ( j ) ) found = true;
            j++;
        }
        if ( !found ) uniq = concat ( uniq, in ( i ) );
    }
    return uniq;
}

}