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bpo-37798: Minor code formatting and comment clean-ups. (GH-15526) (GH-15527)

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(cherry picked from commit 6fee0f8ea7)

Co-authored-by: Raymond Hettinger <rhettinger@users.noreply.github.com>
This commit is contained in:
Miss Islington (bot) 2019-08-26 12:10:00 -07:00 • committed by Raymond Hettinger
parent 2bb4fc379b
commit 56c4d2d057
1 changed files with 22 additions and 13 deletions
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35
Modules/_statisticsmodule.c
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@ -1,4 +1,4 @@
/* statistics accelerator C extensor: _statistics module. */ /* statistics accelerator C extension: _statistics module. */
#include "Python.h" #include "Python.h"
#include "structmember.h" #include "structmember.h"
@ -10,11 +10,13 @@ module _statistics
[clinic start generated code]*/ [clinic start generated code]*/
/*[clinic end generated code: output=da39a3ee5e6b4b0d input=864a6f59b76123b2]*/ /*[clinic end generated code: output=da39a3ee5e6b4b0d input=864a6f59b76123b2]*/
/*
static PyMethodDef speedups_methods[] = { * There is no closed-form solution to the inverse CDF for the normal
_STATISTICS__NORMAL_DIST_INV_CDF_METHODDEF * distribution, so we use a rational approximation instead:
{NULL, NULL, 0, NULL} * Wichura, M.J. (1988). "Algorithm AS241: The Percentage Points of the
}; * Normal Distribution". Applied Statistics. Blackwell Publishing. 37
* (3): 477–484. doi:10.2307/2347330. JSTOR 2347330.
*/
/*[clinic input] /*[clinic input]
_statistics._normal_dist_inv_cdf -> double _statistics._normal_dist_inv_cdf -> double
@ -34,7 +36,7 @@ _statistics__normal_dist_inv_cdf_impl(PyObject *module, double p, double mu,
// Algorithm AS 241: The Percentage Points of the Normal Distribution // Algorithm AS 241: The Percentage Points of the Normal Distribution
if(fabs(q) <= 0.425) { if(fabs(q) <= 0.425) {
r = 0.180625 - q * q; r = 0.180625 - q * q;
// Hash sum AB: 55.88319 28806 14901 4439 // Hash sum-55.8831928806149014439
num = (((((((2.5090809287301226727e+3 * r + num = (((((((2.5090809287301226727e+3 * r +
3.3430575583588128105e+4) * r + 3.3430575583588128105e+4) * r +
6.7265770927008700853e+4) * r + 6.7265770927008700853e+4) * r +
@ -54,11 +56,11 @@ _statistics__normal_dist_inv_cdf_impl(PyObject *module, double p, double mu,
x = num / den; x = num / den;
return mu + (x * sigma); return mu + (x * sigma);
} }
r = q <= 0.0? p : 1.0-p; r = (q <= 0.0) ? p : (1.0 - p);
r = sqrt(-log(r)); r = sqrt(-log(r));
if (r <= 5.0) { if (r <= 5.0) {
r = r - 1.6; r = r - 1.6;
// Hash sum CD: 49.33206 50330 16102 89036 // Hash sum-49.33206503301610289036
num = (((((((7.74545014278341407640e-4 * r + num = (((((((7.74545014278341407640e-4 * r +
2.27238449892691845833e-2) * r + 2.27238449892691845833e-2) * r +
2.41780725177450611770e-1) * r + 2.41780725177450611770e-1) * r +
@ -77,7 +79,7 @@ _statistics__normal_dist_inv_cdf_impl(PyObject *module, double p, double mu,
1.0); 1.0);
} else { } else {
r -= 5.0; r -= 5.0;
// Hash sum EF: 47.52583 31754 92896 71629 // Hash sum-47.52583317549289671629
num = (((((((2.01033439929228813265e-7 * r + num = (((((((2.01033439929228813265e-7 * r +
2.71155556874348757815e-5) * r + 2.71155556874348757815e-5) * r +
1.24266094738807843860e-3) * r + 1.24266094738807843860e-3) * r +
@ -96,23 +98,30 @@ _statistics__normal_dist_inv_cdf_impl(PyObject *module, double p, double mu,
1.0); 1.0);
} }
x = num / den; x = num / den;
if (q < 0.0) x = -x; if (q < 0.0) {
x = -x;
}
return mu + (x * sigma); return mu + (x * sigma);
} }
static PyMethodDef statistics_methods[] = {
_STATISTICS__NORMAL_DIST_INV_CDF_METHODDEF
{NULL, NULL, 0, NULL}
};
static struct PyModuleDef statisticsmodule = { static struct PyModuleDef statisticsmodule = {
PyModuleDef_HEAD_INIT, PyModuleDef_HEAD_INIT,
"_statistics", "_statistics",
_statistics__normal_dist_inv_cdf__doc__, _statistics__normal_dist_inv_cdf__doc__,
-1, -1,
speedups_methods, statistics_methods,
NULL, NULL,
NULL, NULL,
NULL, NULL,
NULL NULL
}; };
PyMODINIT_FUNC PyMODINIT_FUNC
PyInit__statistics(void) PyInit__statistics(void)
{ {