Issue #7518: Move substitute definitions of C99 math functions from

pymath.c to Modules/_math.c.
This commit is contained in:
Mark Dickinson 2009-12-21 15:22:00 +00:00
parent 08dca0d6da
commit 12748b003c
8 changed files with 250 additions and 231 deletions

View File

@ -8,9 +8,9 @@ Symbols and macros to supply platform-independent interfaces to mathematical
functions and constants
**************************************************************************/
/* Python provides implementations for copysign, acosh, asinh, atanh,
* log1p and hypot in Python/pymath.c just in case your math library doesn't
* provide the functions.
/* Python provides implementations for copysign, round and hypot in
* Python/pymath.c just in case your math library doesn't provide the
* functions.
*
*Note: PC/pyconfig.h defines copysign as _copysign
*/
@ -22,22 +22,6 @@ extern double copysign(double, double);
extern double round(double);
#endif
#ifndef HAVE_ACOSH
extern double acosh(double);
#endif
#ifndef HAVE_ASINH
extern double asinh(double);
#endif
#ifndef HAVE_ATANH
extern double atanh(double);
#endif
#ifndef HAVE_LOG1P
extern double log1p(double);
#endif
#ifndef HAVE_HYPOT
extern double hypot(double, double);
#endif

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@ -168,7 +168,7 @@ GLHACK=-Dclear=__GLclear
# Modules that should always be present (non UNIX dependent):
#array arraymodule.c # array objects
#cmath cmathmodule.c # -lm # complex math library functions
#cmath cmathmodule.c _math.c # -lm # complex math library functions
#math mathmodule.c _math.c # -lm # math library functions, e.g. sin()
#_struct _struct.c # binary structure packing/unpacking
#time timemodule.c # -lm # time operations and variables

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@ -1,8 +1,161 @@
/* Definitions of some C99 math library functions, for those platforms
that don't implement these functions already. */
#include "Python.h"
#include <float.h>
#include <math.h>
/* The following copyright notice applies to the original
implementations of acosh, asinh and atanh. */
/*
* ====================================================
* Copyright (C) 1993 by Sun Microsystems, Inc. All rights reserved.
*
* Developed at SunPro, a Sun Microsystems, Inc. business.
* Permission to use, copy, modify, and distribute this
* software is freely granted, provided that this notice
* is preserved.
* ====================================================
*/
static const double ln2 = 6.93147180559945286227E-01;
static const double two_pow_m28 = 3.7252902984619141E-09; /* 2**-28 */
static const double two_pow_p28 = 268435456.0; /* 2**28 */
static const double zero = 0.0;
/* acosh(x)
* Method :
* Based on
* acosh(x) = log [ x + sqrt(x*x-1) ]
* we have
* acosh(x) := log(x)+ln2, if x is large; else
* acosh(x) := log(2x-1/(sqrt(x*x-1)+x)) if x>2; else
* acosh(x) := log1p(t+sqrt(2.0*t+t*t)); where t=x-1.
*
* Special cases:
* acosh(x) is NaN with signal if x<1.
* acosh(NaN) is NaN without signal.
*/
double
_Py_acosh(double x)
{
if (Py_IS_NAN(x)) {
return x+x;
}
if (x < 1.) { /* x < 1; return a signaling NaN */
errno = EDOM;
#ifdef Py_NAN
return Py_NAN;
#else
return (x-x)/(x-x);
#endif
}
else if (x >= two_pow_p28) { /* x > 2**28 */
if (Py_IS_INFINITY(x)) {
return x+x;
} else {
return log(x)+ln2; /* acosh(huge)=log(2x) */
}
}
else if (x == 1.) {
return 0.0; /* acosh(1) = 0 */
}
else if (x > 2.) { /* 2 < x < 2**28 */
double t = x*x;
return log(2.0*x - 1.0 / (x + sqrt(t - 1.0)));
}
else { /* 1 < x <= 2 */
double t = x - 1.0;
return log1p(t + sqrt(2.0*t + t*t));
}
}
/* asinh(x)
* Method :
* Based on
* asinh(x) = sign(x) * log [ |x| + sqrt(x*x+1) ]
* we have
* asinh(x) := x if 1+x*x=1,
* := sign(x)*(log(x)+ln2)) for large |x|, else
* := sign(x)*log(2|x|+1/(|x|+sqrt(x*x+1))) if|x|>2, else
* := sign(x)*log1p(|x| + x^2/(1 + sqrt(1+x^2)))
*/
double
_Py_asinh(double x)
{
double w;
double absx = fabs(x);
if (Py_IS_NAN(x) || Py_IS_INFINITY(x)) {
return x+x;
}
if (absx < two_pow_m28) { /* |x| < 2**-28 */
return x; /* return x inexact except 0 */
}
if (absx > two_pow_p28) { /* |x| > 2**28 */
w = log(absx)+ln2;
}
else if (absx > 2.0) { /* 2 < |x| < 2**28 */
w = log(2.0*absx + 1.0 / (sqrt(x*x + 1.0) + absx));
}
else { /* 2**-28 <= |x| < 2= */
double t = x*x;
w = log1p(absx + t / (1.0 + sqrt(1.0 + t)));
}
return copysign(w, x);
}
/* atanh(x)
* Method :
* 1.Reduced x to positive by atanh(-x) = -atanh(x)
* 2.For x>=0.5
* 1 2x x
* atanh(x) = --- * log(1 + -------) = 0.5 * log1p(2 * --------)
* 2 1 - x 1 - x
*
* For x<0.5
* atanh(x) = 0.5*log1p(2x+2x*x/(1-x))
*
* Special cases:
* atanh(x) is NaN if |x| >= 1 with signal;
* atanh(NaN) is that NaN with no signal;
*
*/
double
_Py_atanh(double x)
{
double absx;
double t;
if (Py_IS_NAN(x)) {
return x+x;
}
absx = fabs(x);
if (absx >= 1.) { /* |x| >= 1 */
errno = EDOM;
#ifdef Py_NAN
return Py_NAN;
#else
return x/zero;
#endif
}
if (absx < two_pow_m28) { /* |x| < 2**-28 */
return x;
}
if (absx < 0.5) { /* |x| < 0.5 */
t = absx+absx;
t = 0.5 * log1p(t + t*absx / (1.0 - absx));
}
else { /* 0.5 <= |x| <= 1.0 */
t = 0.5 * log1p((absx + absx) / (1.0 - absx));
}
return copysign(t, x);
}
/* Mathematically, expm1(x) = exp(x) - 1. The expm1 function is designed
to avoid the significant loss of precision that arises from direct
@ -29,3 +182,47 @@ _Py_expm1(double x)
else
return exp(x) - 1.0;
}
/* log1p(x) = log(1+x). The log1p function is designed to avoid the
significant loss of precision that arises from direct evaluation when x is
small. */
double
_Py_log1p(double x)
{
/* For x small, we use the following approach. Let y be the nearest float
to 1+x, then
1+x = y * (1 - (y-1-x)/y)
so log(1+x) = log(y) + log(1-(y-1-x)/y). Since (y-1-x)/y is tiny, the
second term is well approximated by (y-1-x)/y. If abs(x) >=
DBL_EPSILON/2 or the rounding-mode is some form of round-to-nearest
then y-1-x will be exactly representable, and is computed exactly by
(y-1)-x.
If abs(x) < DBL_EPSILON/2 and the rounding mode is not known to be
round-to-nearest then this method is slightly dangerous: 1+x could be
rounded up to 1+DBL_EPSILON instead of down to 1, and in that case
y-1-x will not be exactly representable any more and the result can be
off by many ulps. But this is easily fixed: for a floating-point
number |x| < DBL_EPSILON/2., the closest floating-point number to
log(1+x) is exactly x.
*/
double y;
if (fabs(x) < DBL_EPSILON/2.) {
return x;
} else if (-0.5 <= x && x <= 1.) {
/* WARNING: it's possible than an overeager compiler
will incorrectly optimize the following two lines
to the equivalent of "return log(1.+x)". If this
happens, then results from log1p will be inaccurate
for small x. */
y = 1.+x;
return log(y)-((y-1.)-x)/y;
} else {
/* NaNs and infinities should end up here */
return log(1.+x);
}
}

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@ -1,4 +1,32 @@
double _Py_acosh(double x);
double _Py_asinh(double x);
double _Py_atanh(double x);
double _Py_expm1(double x);
double _Py_log1p(double x);
#ifdef HAVE_ACOSH
#define m_acosh acosh
#else
/* if the system doesn't have acosh, use the substitute
function defined in Modules/_math.c. */
#define m_acosh _Py_acosh
#endif
#ifdef HAVE_ASINH
#define m_asinh asinh
#else
/* if the system doesn't have asinh, use the substitute
function defined in Modules/_math.c. */
#define m_asinh _Py_asinh
#endif
#ifdef HAVE_ATANH
#define m_atanh atanh
#else
/* if the system doesn't have atanh, use the substitute
function defined in Modules/_math.c. */
#define m_atanh _Py_atanh
#endif
#ifdef HAVE_EXPM1
#define m_expm1 expm1
@ -7,3 +35,11 @@ double _Py_expm1(double x);
function defined in Modules/_math.c. */
#define m_expm1 _Py_expm1
#endif
#ifdef HAVE_LOG1P
#define m_log1p log1p
#else
/* if the system doesn't have log1p, use the substitute
function defined in Modules/_math.c. */
#define m_log1p _Py_log1p
#endif

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@ -3,6 +3,7 @@
/* much code borrowed from mathmodule.c */
#include "Python.h"
#include "_math.h"
/* we need DBL_MAX, DBL_MIN, DBL_EPSILON, DBL_MANT_DIG and FLT_RADIX from
float.h. We assume that FLT_RADIX is either 2 or 16. */
#include <float.h>
@ -149,7 +150,7 @@ c_acos(Py_complex z)
s2.imag = z.imag;
s2 = c_sqrt(s2);
r.real = 2.*atan2(s1.real, s2.real);
r.imag = asinh(s2.real*s1.imag - s2.imag*s1.real);
r.imag = m_asinh(s2.real*s1.imag - s2.imag*s1.real);
}
errno = 0;
return r;
@ -181,7 +182,7 @@ c_acosh(Py_complex z)
s2.real = z.real + 1.;
s2.imag = z.imag;
s2 = c_sqrt(s2);
r.real = asinh(s1.real*s2.real + s1.imag*s2.imag);
r.real = m_asinh(s1.real*s2.real + s1.imag*s2.imag);
r.imag = 2.*atan2(s1.imag, s2.real);
}
errno = 0;
@ -238,7 +239,7 @@ c_asinh(Py_complex z)
s2.real = 1.-z.imag;
s2.imag = z.real;
s2 = c_sqrt(s2);
r.real = asinh(s1.real*s2.imag-s2.real*s1.imag);
r.real = m_asinh(s1.real*s2.imag-s2.real*s1.imag);
r.imag = atan2(z.imag, s1.real*s2.real-s1.imag*s2.imag);
}
errno = 0;
@ -342,7 +343,7 @@ c_atanh(Py_complex z)
errno = 0;
}
} else {
r.real = log1p(4.*z.real/((1-z.real)*(1-z.real) + ay*ay))/4.;
r.real = m_log1p(4.*z.real/((1-z.real)*(1-z.real) + ay*ay))/4.;
r.imag = -atan2(-2.*z.imag, (1-z.real)*(1+z.real) - ay*ay)/2.;
errno = 0;
}
@ -552,7 +553,7 @@ c_log(Py_complex z)
if (0.71 <= h && h <= 1.73) {
am = ax > ay ? ax : ay; /* max(ax, ay) */
an = ax > ay ? ay : ax; /* min(ax, ay) */
r.real = log1p((am-1)*(am+1)+an*an)/2.;
r.real = m_log1p((am-1)*(am+1)+an*an)/2.;
} else {
r.real = log(h);
}

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@ -799,18 +799,18 @@ math_2(PyObject *args, double (*func) (double, double), char *funcname)
FUNC1(acos, acos, 0,
"acos(x)\n\nReturn the arc cosine (measured in radians) of x.")
FUNC1(acosh, acosh, 0,
FUNC1(acosh, m_acosh, 0,
"acosh(x)\n\nReturn the hyperbolic arc cosine (measured in radians) of x.")
FUNC1(asin, asin, 0,
"asin(x)\n\nReturn the arc sine (measured in radians) of x.")
FUNC1(asinh, asinh, 0,
FUNC1(asinh, m_asinh, 0,
"asinh(x)\n\nReturn the hyperbolic arc sine (measured in radians) of x.")
FUNC1(atan, atan, 0,
"atan(x)\n\nReturn the arc tangent (measured in radians) of x.")
FUNC2(atan2, m_atan2,
"atan2(y, x)\n\nReturn the arc tangent (measured in radians) of y/x.\n"
"Unlike atan(y/x), the signs of both x and y are considered.")
FUNC1(atanh, atanh, 0,
FUNC1(atanh, m_atanh, 0,
"atanh(x)\n\nReturn the hyperbolic arc tangent (measured in radians) of x.")
FUNC1(ceil, ceil, 0,
"ceil(x)\n\nReturn the ceiling of x as a float.\n"
@ -840,7 +840,7 @@ FUNC1A(gamma, m_tgamma,
"gamma(x)\n\nGamma function at x.")
FUNC1A(lgamma, m_lgamma,
"lgamma(x)\n\nNatural logarithm of absolute value of Gamma function at x.")
FUNC1(log1p, log1p, 1,
FUNC1(log1p, m_log1p, 1,
"log1p(x)\n\nReturn the natural logarithm of 1+x (base e).\n"
"The result is computed in a way which is accurate for x near zero.")
FUNC1(sin, sin, 0,

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@ -77,202 +77,3 @@ round(double x)
return copysign(y, x);
}
#endif /* HAVE_ROUND */
#ifndef HAVE_LOG1P
#include <float.h>
double
log1p(double x)
{
/* For x small, we use the following approach. Let y be the nearest
float to 1+x, then
1+x = y * (1 - (y-1-x)/y)
so log(1+x) = log(y) + log(1-(y-1-x)/y). Since (y-1-x)/y is tiny,
the second term is well approximated by (y-1-x)/y. If abs(x) >=
DBL_EPSILON/2 or the rounding-mode is some form of round-to-nearest
then y-1-x will be exactly representable, and is computed exactly
by (y-1)-x.
If abs(x) < DBL_EPSILON/2 and the rounding mode is not known to be
round-to-nearest then this method is slightly dangerous: 1+x could
be rounded up to 1+DBL_EPSILON instead of down to 1, and in that
case y-1-x will not be exactly representable any more and the
result can be off by many ulps. But this is easily fixed: for a
floating-point number |x| < DBL_EPSILON/2., the closest
floating-point number to log(1+x) is exactly x.
*/
double y;
if (fabs(x) < DBL_EPSILON/2.) {
return x;
} else if (-0.5 <= x && x <= 1.) {
/* WARNING: it's possible than an overeager compiler
will incorrectly optimize the following two lines
to the equivalent of "return log(1.+x)". If this
happens, then results from log1p will be inaccurate
for small x. */
y = 1.+x;
return log(y)-((y-1.)-x)/y;
} else {
/* NaNs and infinities should end up here */
return log(1.+x);
}
}
#endif /* HAVE_LOG1P */
/*
* ====================================================
* Copyright (C) 1993 by Sun Microsystems, Inc. All rights reserved.
*
* Developed at SunPro, a Sun Microsystems, Inc. business.
* Permission to use, copy, modify, and distribute this
* software is freely granted, provided that this notice
* is preserved.
* ====================================================
*/
static const double ln2 = 6.93147180559945286227E-01;
static const double two_pow_m28 = 3.7252902984619141E-09; /* 2**-28 */
static const double two_pow_p28 = 268435456.0; /* 2**28 */
static const double zero = 0.0;
/* asinh(x)
* Method :
* Based on
* asinh(x) = sign(x) * log [ |x| + sqrt(x*x+1) ]
* we have
* asinh(x) := x if 1+x*x=1,
* := sign(x)*(log(x)+ln2)) for large |x|, else
* := sign(x)*log(2|x|+1/(|x|+sqrt(x*x+1))) if|x|>2, else
* := sign(x)*log1p(|x| + x^2/(1 + sqrt(1+x^2)))
*/
#ifndef HAVE_ASINH
double
asinh(double x)
{
double w;
double absx = fabs(x);
if (Py_IS_NAN(x) || Py_IS_INFINITY(x)) {
return x+x;
}
if (absx < two_pow_m28) { /* |x| < 2**-28 */
return x; /* return x inexact except 0 */
}
if (absx > two_pow_p28) { /* |x| > 2**28 */
w = log(absx)+ln2;
}
else if (absx > 2.0) { /* 2 < |x| < 2**28 */
w = log(2.0*absx + 1.0 / (sqrt(x*x + 1.0) + absx));
}
else { /* 2**-28 <= |x| < 2= */
double t = x*x;
w = log1p(absx + t / (1.0 + sqrt(1.0 + t)));
}
return copysign(w, x);
}
#endif /* HAVE_ASINH */
/* acosh(x)
* Method :
* Based on
* acosh(x) = log [ x + sqrt(x*x-1) ]
* we have
* acosh(x) := log(x)+ln2, if x is large; else
* acosh(x) := log(2x-1/(sqrt(x*x-1)+x)) if x>2; else
* acosh(x) := log1p(t+sqrt(2.0*t+t*t)); where t=x-1.
*
* Special cases:
* acosh(x) is NaN with signal if x<1.
* acosh(NaN) is NaN without signal.
*/
#ifndef HAVE_ACOSH
double
acosh(double x)
{
if (Py_IS_NAN(x)) {
return x+x;
}
if (x < 1.) { /* x < 1; return a signaling NaN */
errno = EDOM;
#ifdef Py_NAN
return Py_NAN;
#else
return (x-x)/(x-x);
#endif
}
else if (x >= two_pow_p28) { /* x > 2**28 */
if (Py_IS_INFINITY(x)) {
return x+x;
} else {
return log(x)+ln2; /* acosh(huge)=log(2x) */
}
}
else if (x == 1.) {
return 0.0; /* acosh(1) = 0 */
}
else if (x > 2.) { /* 2 < x < 2**28 */
double t = x*x;
return log(2.0*x - 1.0 / (x + sqrt(t - 1.0)));
}
else { /* 1 < x <= 2 */
double t = x - 1.0;
return log1p(t + sqrt(2.0*t + t*t));
}
}
#endif /* HAVE_ACOSH */
/* atanh(x)
* Method :
* 1.Reduced x to positive by atanh(-x) = -atanh(x)
* 2.For x>=0.5
* 1 2x x
* atanh(x) = --- * log(1 + -------) = 0.5 * log1p(2 * --------)
* 2 1 - x 1 - x
*
* For x<0.5
* atanh(x) = 0.5*log1p(2x+2x*x/(1-x))
*
* Special cases:
* atanh(x) is NaN if |x| >= 1 with signal;
* atanh(NaN) is that NaN with no signal;
*
*/
#ifndef HAVE_ATANH
double
atanh(double x)
{
double absx;
double t;
if (Py_IS_NAN(x)) {
return x+x;
}
absx = fabs(x);
if (absx >= 1.) { /* |x| >= 1 */
errno = EDOM;
#ifdef Py_NAN
return Py_NAN;
#else
return x/zero;
#endif
}
if (absx < two_pow_m28) { /* |x| < 2**-28 */
return x;
}
if (absx < 0.5) { /* |x| < 0.5 */
t = absx+absx;
t = 0.5 * log1p(t + t*absx / (1.0 - absx));
}
else { /* 0.5 <= |x| <= 1.0 */
t = 0.5 * log1p((absx + absx) / (1.0 - absx));
}
return copysign(t, x);
}
#endif /* HAVE_ATANH */

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@ -410,9 +410,9 @@ class PyBuildExt(build_ext):
# array objects
exts.append( Extension('array', ['arraymodule.c']) )
# complex math library functions
exts.append( Extension('cmath', ['cmathmodule.c'],
exts.append( Extension('cmath', ['cmathmodule.c', '_math.c'],
depends=['_math.h'],
libraries=math_libs) )
# math library functions, e.g. sin()
exts.append( Extension('math', ['mathmodule.c', '_math.c'],
depends=['_math.h'],