1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
|
Numpy core libraries
====================
.. sectionauthor:: David Cournapeau
.. versionadded:: 1.3.0
Starting from numpy 1.3.0, we are working on separating the pure C,
"computational" code from the python dependent code. The goal is twofolds:
making the code cleaner, and enabling code reuse by other extensions outside
numpy (scipy, etc...).
Numpy core math library
-----------------------
The numpy core math library ('npymath') is a first step in this direction. This
library contains most math-related C99 functionality, which can be used on
platforms where C99 is not well supported. The core math functions have the
same API as the C99 ones, except for the npy_* prefix.
The available functions are defined in npy_math.h - please refer to this header
in doubt.
Floating point classification
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. cvar:: NPY_NAN
This macro is defined to a NaN (Not a Number), and is guaranteed to have
the signbit unset ('positive' NaN). The corresponding single and extension
precision macro are available with the suffix F and L.
.. cvar:: NPY_INFINITY
This macro is defined to a positive inf. The corresponding single and
extension precision macro are available with the suffix F and L.
.. cvar:: NPY_PZERO
This macro is defined to positive zero. The corresponding single and
extension precision macro are available with the suffix F and L.
.. cvar:: NPY_NZERO
This macro is defined to negative zero (that is with the sign bit set). The
corresponding single and extension precision macro are available with the
suffix F and L.
.. cfunction:: int npy_isnan(x)
This is a macro, and is equivalent to C99 isnan: works for single, double
and extended precision, and return a non 0 value is x is a NaN.
.. cfunction:: int npy_isfinite(x)
This is a macro, and is equivalent to C99 isfinite: works for single,
double and extended precision, and return a non 0 value is x is neither a
NaN or a infinity.
.. cfunction:: int npy_isinf(x)
This is a macro, and is equivalent to C99 isinf: works for single, double
and extended precision, and return a non 0 value is x is infinite (positive
and negative).
.. cfunction:: int npy_signbit(x)
This is a macro, and is equivalent to C99 signbit: works for single, double
and extended precision, and return a non 0 value is x has the signbit set
(that is the number is negative).
.. cfunction:: double npy_copysign(double x, double y)
This is a function equivalent to C99 copysign: return x with the same sign
as y. Works for any value, including inf and nan. Single and extended
precisions are available with suffix f and l.
.. versionadded:: 1.4.0
Useful math constants
~~~~~~~~~~~~~~~~~~~~~
The following math constants are available in npy_math.h. Single and extended
precision are also available by adding the F and L suffixes respectively.
.. cvar:: NPY_E
Base of natural logarithm (:math:`e`)
.. cvar:: NPY_LOG2E
Logarithm to base 2 of the Euler constant (:math:`\frac{\ln(e)}{\ln(2)}`)
.. cvar:: NPY_LOG10E
Logarithm to base 10 of the Euler constant (:math:`\frac{\ln(e)}{\ln(10)}`)
.. cvar:: NPY_LOGE2
Natural logarithm of 2 (:math:`\ln(2)`)
.. cvar:: NPY_LOGE10
Natural logarithm of 10 (:math:`\ln(10)`)
.. cvar:: NPY_PI
Pi (:math:`\pi`)
.. cvar:: NPY_PI_2
Pi divided by 2 (:math:`\frac{\pi}{2}`)
.. cvar:: NPY_PI_4
Pi divided by 4 (:math:`\frac{\pi}{4}`)
.. cvar:: NPY_1_PI
Reciprocal of pi (:math:`\frac{1}{\pi}`)
.. cvar:: NPY_2_PI
Two times the reciprocal of pi (:math:`\frac{2}{\pi}`)
.. cvar:: NPY_EULER
The Euler constant
:math:`\lim_{n\rightarrow\infty}({\sum_{k=1}^n{\frac{1}{k}}-\ln n})`
Low-level floating point manipulation
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
Those can be useful for precise floating point comparison.
.. cfunction:: double npy_nextafter(double x, double y)
This is a function equivalent to C99 nextafter: return next representable
floating point value from x in the direction of y. Single and extended
precisions are available with suffix f and l.
.. versionadded:: 1.4.0
.. cfunction:: double npy_spacing(double x)
This is a function equivalent to Fortran intrinsic. Return distance between
x and next representable floating point value from x, e.g. spacing(1) ==
eps. spacing of nan and +/- inf return nan. Single and extended precisions
are available with suffix f and l.
.. versionadded:: 1.4.0
Complex functions
~~~~~~~~~~~~~~~~~
.. versionadded:: 1.4.0
C99-like complex functions have been added. Those can be used if you wish to
implement portable C extensions. Since we still support platforms without C99
complex type, you need to restrict to C90-compatible syntax, e.g.:
.. code-block:: c
/* a = 1 + 2i \*/
npy_complex a = npy_cpack(1, 2);
npy_complex b;
b = npy_log(a);
Linking against the core math library in an extension
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
.. versionadded:: 1.4.0
To use the core math library in your own extension, you need to add the npymath
compile and link options to your extension in your setup.py:
>>> from numpy.distutils.misc_utils import get_info
>>> info = get_info('npymath')
>>> config.add_extension('foo', sources=['foo.c'], extra_info=**info)
In other words, the usage of info is exactly the same as when using blas_info
and co.
|
