cosmopolitan/third_party/python/Modules/_decimal/libmpdec/convolute.c
Justine Tunney fa20edc44d
Reduce header complexity
- Remove most __ASSEMBLER__ __LINKER__ ifdefs
- Rename libc/intrin/bits.h to libc/serialize.h
- Block pthread cancelation in fchmodat() polyfill
- Remove `clang-format off` statements in third_party
2023-11-28 14:39:42 -08:00

157 lines
6.2 KiB
C

/*-*- mode:c;indent-tabs-mode:nil;c-basic-offset:4;tab-width:8;coding:utf-8 -*-│
│vi: set net ft=c ts=4 sts=4 sw=4 fenc=utf-8 :vi│
╞══════════════════════════════════════════════════════════════════════════════╡
│ Copyright (c) 2008-2016 Stefan Krah. All rights reserved. │
│ │
│ Redistribution and use in source and binary forms, with or without │
│ modification, are permitted provided that the following conditions │
│ are met: │
│ │
│ 1. Redistributions of source code must retain the above copyright │
│ notice, this list of conditions and the following disclaimer. │
│ │
│ 2. Redistributions in binary form must reproduce the above copyright │
│ notice, this list of conditions and the following disclaimer in │
│ the documentation and/or other materials provided with the │
│ distribution. │
│ │
│ THIS SOFTWARE IS PROVIDED BY THE AUTHOR AND CONTRIBUTORS "AS IS" AND │
│ ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE │
│ IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR │
│ PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE AUTHOR OR CONTRIBUTORS │
│ BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, │
│ OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT │
│ OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR │
│ BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, │
│ WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE │
│ OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, │
│ EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. │
╚─────────────────────────────────────────────────────────────────────────────*/
#include "third_party/python/Modules/_decimal/libmpdec/bits.h"
#include "third_party/python/Modules/_decimal/libmpdec/constants.h"
#include "third_party/python/Modules/_decimal/libmpdec/convolute.h"
#include "third_party/python/Modules/_decimal/libmpdec/fnt.h"
#include "third_party/python/Modules/_decimal/libmpdec/fourstep.h"
#include "third_party/python/Modules/_decimal/libmpdec/mpdecimal.h"
#include "third_party/python/Modules/_decimal/libmpdec/numbertheory.h"
#include "third_party/python/Modules/_decimal/libmpdec/sixstep.h"
#include "third_party/python/Modules/_decimal/libmpdec/umodarith.h"
asm(".ident\t\"\\n\\n\
libmpdec (BSD-2)\\n\
Copyright 2008-2016 Stefan Krah\"");
asm(".include \"libc/disclaimer.inc\"");
/* Bignum: Fast convolution using the Number Theoretic Transform.
Used for the multiplication of very large coefficients. */
/* Convolute the data in c1 and c2. Result is in c1. */
int
fnt_convolute(mpd_uint_t *c1, mpd_uint_t *c2, mpd_size_t n, int modnum)
{
int (*fnt)(mpd_uint_t *, mpd_size_t, int);
int (*inv_fnt)(mpd_uint_t *, mpd_size_t, int);
mpd_uint_t n_inv, umod;
mpd_size_t i;
SETMODULUS(modnum);
n_inv = POWMOD(n, (umod-2));
if (ispower2(n)) {
if (n > SIX_STEP_THRESHOLD) {
fnt = six_step_fnt;
inv_fnt = inv_six_step_fnt;
}
else {
fnt = std_fnt;
inv_fnt = std_inv_fnt;
}
}
else {
fnt = four_step_fnt;
inv_fnt = inv_four_step_fnt;
}
if (!fnt(c1, n, modnum)) {
return 0;
}
if (!fnt(c2, n, modnum)) {
return 0;
}
for (i = 0; i < n-1; i += 2) {
mpd_uint_t x0 = c1[i];
mpd_uint_t y0 = c2[i];
mpd_uint_t x1 = c1[i+1];
mpd_uint_t y1 = c2[i+1];
MULMOD2(&x0, y0, &x1, y1);
c1[i] = x0;
c1[i+1] = x1;
}
if (!inv_fnt(c1, n, modnum)) {
return 0;
}
for (i = 0; i < n-3; i += 4) {
mpd_uint_t x0 = c1[i];
mpd_uint_t x1 = c1[i+1];
mpd_uint_t x2 = c1[i+2];
mpd_uint_t x3 = c1[i+3];
MULMOD2C(&x0, &x1, n_inv);
MULMOD2C(&x2, &x3, n_inv);
c1[i] = x0;
c1[i+1] = x1;
c1[i+2] = x2;
c1[i+3] = x3;
}
return 1;
}
/* Autoconvolute the data in c1. Result is in c1. */
int
fnt_autoconvolute(mpd_uint_t *c1, mpd_size_t n, int modnum)
{
int (*fnt)(mpd_uint_t *, mpd_size_t, int);
int (*inv_fnt)(mpd_uint_t *, mpd_size_t, int);
mpd_uint_t n_inv, umod;
mpd_size_t i;
SETMODULUS(modnum);
n_inv = POWMOD(n, (umod-2));
if (ispower2(n)) {
if (n > SIX_STEP_THRESHOLD) {
fnt = six_step_fnt;
inv_fnt = inv_six_step_fnt;
}
else {
fnt = std_fnt;
inv_fnt = std_inv_fnt;
}
}
else {
fnt = four_step_fnt;
inv_fnt = inv_four_step_fnt;
}
if (!fnt(c1, n, modnum)) {
return 0;
}
for (i = 0; i < n-1; i += 2) {
mpd_uint_t x0 = c1[i];
mpd_uint_t x1 = c1[i+1];
MULMOD2(&x0, x0, &x1, x1);
c1[i] = x0;
c1[i+1] = x1;
}
if (!inv_fnt(c1, n, modnum)) {
return 0;
}
for (i = 0; i < n-3; i += 4) {
mpd_uint_t x0 = c1[i];
mpd_uint_t x1 = c1[i+1];
mpd_uint_t x2 = c1[i+2];
mpd_uint_t x3 = c1[i+3];
MULMOD2C(&x0, &x1, n_inv);
MULMOD2C(&x2, &x3, n_inv);
c1[i] = x0;
c1[i+1] = x1;
c1[i+2] = x2;
c1[i+3] = x3;
}
return 1;
}