Mercurial > octave
view liboctave/numeric/oct-rand.cc @ 31210:9ad55d2e1bbf stable
Make sure we don't pass short 8.3 path to latex on Windows (bug #62779).
* latex-text-renderer.cc (latex_renderer::write_tex_file): On Windows, use
canonicalized path of temporary directory.
author | Pantxo Diribarne <pantxo.diribarne@gmail.com> |
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date | Sun, 28 Aug 2022 22:44:49 +0200 |
parents | 796f54d4ddbf |
children | e88a07dec498 |
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//////////////////////////////////////////////////////////////////////// // // Copyright (C) 2003-2022 The Octave Project Developers // // See the file COPYRIGHT.md in the top-level directory of this // distribution or <https://octave.org/copyright/>. // // This file is part of Octave. // // Octave is free software: you can redistribute it and/or modify it // under the terms of the GNU General Public License as published by // the Free Software Foundation, either version 3 of the License, or // (at your option) any later version. // // Octave is distributed in the hope that it will be useful, but // WITHOUT ANY WARRANTY; without even the implied warranty of // MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the // GNU General Public License for more details. // // You should have received a copy of the GNU General Public License // along with Octave; see the file COPYING. If not, see // <https://www.gnu.org/licenses/>. // //////////////////////////////////////////////////////////////////////// #if defined (HAVE_CONFIG_H) # include "config.h" #endif #include <cassert> #include <cstdint> #include <limits> #include "lo-error.h" #include "lo-ieee.h" #include "lo-mappers.h" #include "lo-ranlib-proto.h" #include "mach-info.h" #include "oct-locbuf.h" #include "oct-rand.h" #include "oct-time.h" #include "quit.h" #include "randgamma.h" #include "randmtzig.h" #include "randpoisson.h" #include "singleton-cleanup.h" namespace octave { rand *rand::m_instance = nullptr; rand::rand (void) : m_current_distribution (uniform_dist), m_use_old_generators (false), m_rand_states () { initialize_ranlib_generators (); initialize_mersenne_twister (); } bool rand::instance_ok (void) { bool retval = true; if (! m_instance) { m_instance = new rand (); singleton_cleanup_list::add (cleanup_instance); } return retval; } double rand::do_seed (void) { union d2i { double d; int32_t i[2]; }; union d2i u; mach_info::float_format ff = mach_info::native_float_format (); switch (ff) { case mach_info::flt_fmt_ieee_big_endian: F77_FUNC (getsd, GETSD) (u.i[1], u.i[0]); break; default: F77_FUNC (getsd, GETSD) (u.i[0], u.i[1]); break; } return u.d; } static int32_t force_to_fit_range (int32_t i, int32_t lo, int32_t hi) { assert (hi > lo && lo >= 0); i = (i > 0 ? i : -i); if (i < lo) i = lo; else if (i > hi) i = i % hi; return i; } void rand::do_seed (double s) { m_use_old_generators = true; int i0, i1; union d2i { double d; int32_t i[2]; }; union d2i u; u.d = s; mach_info::float_format ff = mach_info::native_float_format (); switch (ff) { case mach_info::flt_fmt_ieee_big_endian: i1 = force_to_fit_range (u.i[0], 1, 2147483563); i0 = force_to_fit_range (u.i[1], 1, 2147483399); break; default: i0 = force_to_fit_range (u.i[0], 1, 2147483563); i1 = force_to_fit_range (u.i[1], 1, 2147483399); break; } F77_FUNC (setsd, SETSD) (i0, i1); } void rand::do_reset (void) { m_use_old_generators = true; initialize_ranlib_generators (); } uint32NDArray rand::do_state (const std::string& d) { return m_rand_states[d.empty () ? m_current_distribution : get_dist_id (d)]; } void rand::do_state (const uint32NDArray& s, const std::string& d) { m_use_old_generators = false; int old_dist = m_current_distribution; int new_dist = (d.empty () ? m_current_distribution : get_dist_id (d)); uint32NDArray saved_state; if (old_dist != new_dist) saved_state = get_internal_state (); set_internal_state (s); m_rand_states[new_dist] = get_internal_state (); if (old_dist != new_dist) m_rand_states[old_dist] = saved_state; } void rand::do_reset (const std::string& d) { m_use_old_generators = false; int old_dist = m_current_distribution; int new_dist = (d.empty () ? m_current_distribution : get_dist_id (d)); uint32NDArray saved_state; if (old_dist != new_dist) saved_state = get_internal_state (); init_mersenne_twister (); m_rand_states[new_dist] = get_internal_state (); if (old_dist != new_dist) m_rand_states[old_dist] = saved_state; } std::string rand::do_distribution (void) { std::string retval; switch (m_current_distribution) { case uniform_dist: retval = "uniform"; break; case normal_dist: retval = "normal"; break; case expon_dist: retval = "exponential"; break; case poisson_dist: retval = "poisson"; break; case gamma_dist: retval = "gamma"; break; default: (*current_liboctave_error_handler) ("rand: invalid distribution ID = %d", m_current_distribution); break; } return retval; } void rand::do_distribution (const std::string& d) { int id = get_dist_id (d); switch (id) { case uniform_dist: rand::uniform_distribution (); break; case normal_dist: rand::normal_distribution (); break; case expon_dist: rand::exponential_distribution (); break; case poisson_dist: rand::poisson_distribution (); break; case gamma_dist: rand::gamma_distribution (); break; default: (*current_liboctave_error_handler) ("rand: invalid distribution ID = %d", id); break; } } void rand::do_uniform_distribution (void) { switch_to_generator (uniform_dist); F77_FUNC (setcgn, SETCGN) (uniform_dist); } void rand::do_normal_distribution (void) { switch_to_generator (normal_dist); F77_FUNC (setcgn, SETCGN) (normal_dist); } void rand::do_exponential_distribution (void) { switch_to_generator (expon_dist); F77_FUNC (setcgn, SETCGN) (expon_dist); } void rand::do_poisson_distribution (void) { switch_to_generator (poisson_dist); F77_FUNC (setcgn, SETCGN) (poisson_dist); } void rand::do_gamma_distribution (void) { switch_to_generator (gamma_dist); F77_FUNC (setcgn, SETCGN) (gamma_dist); } template <> OCTAVE_API double rand::uniform<double> (void) { double retval; if (m_use_old_generators) F77_FUNC (dgenunf, DGENUNF) (0.0, 1.0, retval); else retval = rand_uniform<double> (); return retval; } template <> OCTAVE_API double rand::normal<double> (void) { double retval; if (m_use_old_generators) F77_FUNC (dgennor, DGENNOR) (0.0, 1.0, retval); else retval = rand_normal<double> (); return retval; } template <> OCTAVE_API double rand::exponential<double> (void) { double retval; if (m_use_old_generators) F77_FUNC (dgenexp, DGENEXP) (1.0, retval); else retval = rand_exponential<double> (); return retval; } template <> OCTAVE_API double rand::poisson<double> (double a) { double retval; if (m_use_old_generators) { if (a < 0.0 || ! math::isfinite (a)) retval = numeric_limits<double>::NaN (); else { // workaround bug in ignpoi, by calling with different Mu F77_FUNC (dignpoi, DIGNPOI) (a + 1, retval); F77_FUNC (dignpoi, DIGNPOI) (a, retval); } } else retval = rand_poisson<double> (a); return retval; } template <> OCTAVE_API double rand::gamma<double> (double a) { double retval; if (m_use_old_generators) { if (a <= 0.0 || ! math::isfinite (a)) retval = numeric_limits<double>::NaN (); else F77_FUNC (dgengam, DGENGAM) (1.0, a, retval); } else retval = rand_gamma<double> (a); return retval; } template <> OCTAVE_API float rand::uniform<float> (void) { float retval; if (m_use_old_generators) F77_FUNC (fgenunf, FGENUNF) (0.0f, 1.0f, retval); else retval = rand_uniform<float> (); return retval; } template <> OCTAVE_API float rand::normal<float> (void) { float retval; if (m_use_old_generators) F77_FUNC (fgennor, FGENNOR) (0.0f, 1.0f, retval); else retval = rand_normal<float> (); return retval; } template <> OCTAVE_API float rand::exponential<float> (void) { float retval; if (m_use_old_generators) F77_FUNC (fgenexp, FGENEXP) (1.0f, retval); else retval = rand_exponential<float> (); return retval; } template <> OCTAVE_API float rand::poisson<float> (float a) { float retval; if (m_use_old_generators) { if (a < 0.0f || ! math::isfinite (a)) retval = numeric_limits<float>::NaN (); else { // workaround bug in ignpoi, by calling with different Mu F77_FUNC (fignpoi, FIGNPOI) (a + 1, retval); F77_FUNC (fignpoi, FIGNPOI) (a, retval); } } else { // Keep poisson distribution in double precision for accuracy retval = rand_poisson<double> (a); } return retval; } template <> OCTAVE_API float rand::gamma<float> (float a) { float retval; if (m_use_old_generators) { if (a <= 0.0f || ! math::isfinite (a)) retval = numeric_limits<float>::NaN (); else F77_FUNC (fgengam, FGENGAM) (1.0f, a, retval); } else retval = rand_gamma<float> (a); return retval; } template <typename T> T rand::do_scalar (T a) { T retval = 0; switch (m_current_distribution) { case uniform_dist: retval = uniform<T> (); break; case normal_dist: retval = normal<T> (); break; case expon_dist: retval = exponential<T> (); break; case poisson_dist: retval = poisson<T> (a); break; case gamma_dist: retval = gamma<T> (a); break; default: (*current_liboctave_error_handler) ("rand: invalid distribution ID = %d", m_current_distribution); break; } if (! m_use_old_generators) save_state (); return retval; } template OCTAVE_API double rand::do_scalar<double> (double); template OCTAVE_API float rand::do_scalar<float> (float); template <typename T> Array<T> rand::do_vector (octave_idx_type n, T a) { Array<T> retval; if (n > 0) { retval.clear (n, 1); fill (retval.numel (), retval.fortran_vec (), a); } else if (n < 0) (*current_liboctave_error_handler) ("rand: invalid negative argument"); return retval; } template OCTAVE_API Array<double> rand::do_vector<double> (octave_idx_type, double); template OCTAVE_API Array<float> rand::do_vector<float> (octave_idx_type, float); NDArray rand::do_nd_array (const dim_vector& dims, double a) { NDArray retval; if (! dims.all_zero ()) { retval.clear (dims); fill (retval.numel (), retval.fortran_vec (), a); } return retval; } FloatNDArray rand::do_float_nd_array (const dim_vector& dims, float a) { FloatNDArray retval; if (! dims.all_zero ()) { retval.clear (dims); fill (retval.numel (), retval.fortran_vec (), a); } return retval; } // Make the random number generator give us a different sequence every // time we start octave unless we specifically set the seed. The // technique used below will cycle monthly, but it does seem to // work ok to give fairly different seeds each time Octave starts. void rand::initialize_ranlib_generators (void) { sys::localtime tm; int stored_distribution = m_current_distribution; F77_FUNC (setcgn, SETCGN) (uniform_dist); int hour = tm.hour () + 1; int minute = tm.min () + 1; int second = tm.sec () + 1; int32_t s0 = tm.mday () * hour * minute * second; int32_t s1 = hour * minute * second; s0 = force_to_fit_range (s0, 1, 2147483563); s1 = force_to_fit_range (s1, 1, 2147483399); F77_FUNC (setall, SETALL) (s0, s1); F77_FUNC (setcgn, SETCGN) (stored_distribution); } void rand::initialize_mersenne_twister (void) { uint32NDArray s; init_mersenne_twister (); s = get_internal_state (); m_rand_states[uniform_dist] = s; init_mersenne_twister (); s = get_internal_state (); m_rand_states[normal_dist] = s; init_mersenne_twister (); s = get_internal_state (); m_rand_states[expon_dist] = s; init_mersenne_twister (); s = get_internal_state (); m_rand_states[poisson_dist] = s; init_mersenne_twister (); s = get_internal_state (); m_rand_states[gamma_dist] = s; // All of the initializations above have messed with the internal state. // Restore the state of the currently selected distribution. set_internal_state (m_rand_states[m_current_distribution]); } uint32NDArray rand::get_internal_state (void) { uint32NDArray s (dim_vector (MT_N + 1, 1)); get_mersenne_twister_state (reinterpret_cast<uint32_t *> (s.fortran_vec ())); return s; } void rand::save_state (void) { m_rand_states[m_current_distribution] = get_internal_state ();; } int rand::get_dist_id (const std::string& d) { int retval = unknown_dist; if (d == "uniform" || d == "rand") retval = uniform_dist; else if (d == "normal" || d == "randn") retval = normal_dist; else if (d == "exponential" || d == "rande") retval = expon_dist; else if (d == "poisson" || d == "randp") retval = poisson_dist; else if (d == "gamma" || d == "randg") retval = gamma_dist; else (*current_liboctave_error_handler) ("rand: invalid distribution '%s'", d.c_str ()); return retval; } void rand::set_internal_state (const uint32NDArray& s) { octave_idx_type len = s.numel (); const uint32_t *sdata = reinterpret_cast <const uint32_t *> (s.data ()); if (len == MT_N + 1 && sdata[MT_N] <= MT_N && sdata[MT_N] > 0) set_mersenne_twister_state (sdata); else init_mersenne_twister (sdata, len); } void rand::switch_to_generator (int dist) { if (dist != m_current_distribution) { m_current_distribution = dist; set_internal_state (m_rand_states[dist]); } } void rand::fill (octave_idx_type len, double *v, double a) { if (len < 1) return; switch (m_current_distribution) { case uniform_dist: if (m_use_old_generators) std::generate_n (v, len, [](void) { double x; F77_FUNC (dgenunf, DGENUNF) (0.0, 1.0, x); return x; }); else rand_uniform<double> (len, v); break; case normal_dist: if (m_use_old_generators) std::generate_n (v, len, [](void) { double x; F77_FUNC (dgennor, DGENNOR) (0.0, 1.0, x); return x; }); else rand_normal<double> (len, v); break; case expon_dist: if (m_use_old_generators) std::generate_n (v, len, [](void) { double x; F77_FUNC (dgenexp, DGENEXP) (1.0, x); return x; }); else rand_exponential<double> (len, v); break; case poisson_dist: if (m_use_old_generators) { if (a < 0.0 || ! math::isfinite (a)) std::fill_n (v, len, numeric_limits<double>::NaN ()); else { // workaround bug in ignpoi, by calling with different Mu double tmp; F77_FUNC (dignpoi, DIGNPOI) (a + 1, tmp); std::generate_n (v, len, [a](void) { double x; F77_FUNC (dignpoi, DIGNPOI) (a, x); return x; }); } } else rand_poisson<double> (a, len, v); break; case gamma_dist: if (m_use_old_generators) { if (a <= 0.0 || ! math::isfinite (a)) std::fill_n (v, len, numeric_limits<double>::NaN ()); else std::generate_n (v, len, [a](void) { double x; F77_FUNC (dgengam, DGENGAM) (1.0, a, x); return x; }); } else rand_gamma<double> (a, len, v); break; default: (*current_liboctave_error_handler) ("rand: invalid distribution ID = %d", m_current_distribution); break; } save_state (); return; } void rand::fill (octave_idx_type len, float *v, float a) { if (len < 1) return; switch (m_current_distribution) { case uniform_dist: if (m_use_old_generators) std::generate_n (v, len, [](void) { float x; F77_FUNC (fgenunf, FGENUNF) (0.0f, 1.0f, x); return x; }); else rand_uniform<float> (len, v); break; case normal_dist: if (m_use_old_generators) std::generate_n (v, len, [](void) { float x; F77_FUNC (fgennor, FGENNOR) (0.0f, 1.0f, x); return x; }); else rand_normal<float> (len, v); break; case expon_dist: if (m_use_old_generators) std::generate_n (v, len, [](void) { float x; F77_FUNC (fgenexp, FGENEXP) (1.0f, x); return x; }); else rand_exponential<float> (len, v); break; case poisson_dist: if (m_use_old_generators) { if (a < 0.0f || ! math::isfinite (a)) std::fill_n (v, len, numeric_limits<float>::NaN ()); else { // workaround bug in ignpoi, by calling with different Mu float tmp; F77_FUNC (fignpoi, FIGNPOI) (a + 1, tmp); std::generate_n (v, len, [a](void) { float x; F77_FUNC (fignpoi, FIGNPOI) (a, x); return x; }); } } else rand_poisson<float> (a, len, v); break; case gamma_dist: if (m_use_old_generators) { if (a <= 0.0f || ! math::isfinite (a)) std::fill_n (v, len, numeric_limits<float>::NaN ()); else std::generate_n (v, len, [a](void) { float x; F77_FUNC (fgengam, FGENGAM) (1.0f, a, x); return x; }); } else rand_gamma<float> (a, len, v); break; default: (*current_liboctave_error_handler) ("rand: invalid distribution ID = %d", m_current_distribution); break; } save_state (); return; } }