{{ message }}
-
Notifications
You must be signed in to change notification settings - Fork 62
Expand file tree
/
Copy pathnumpy.html
More file actions
396 lines (329 loc) · 27.7 KB
/
Copy pathnumpy.html
File metadata and controls
396 lines (329 loc) · 27.7 KB
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
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Transitional//EN"
"http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
<html xmlns="http://www.w3.org/1999/xhtml">
<head>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
<title>numpy — Matplotlib 2.2.5 documentation</title>
<link rel="stylesheet" href="../_static/mpl.css"
type="text/css" />
<link rel="stylesheet" href="../_static/pygments.css"
type="text/css" />
<link rel="stylesheet" href="../_static/graphviz.css" type="text/css" />
<link rel="stylesheet" href="../_static/gallery.css" type="text/css" />
<script type="text/javascript">
var DOCUMENTATION_OPTIONS = {
URL_ROOT: '../',
VERSION: '2.2.5',
COLLAPSE_INDEX: false,
FILE_SUFFIX: '.html',
HAS_SOURCE: true,
SOURCELINK_SUFFIX: '.txt'
};
</script>
<script type="text/javascript" src="../_static/jquery.js"></script>
<script type="text/javascript" src="../_static/underscore.js"></script>
<script type="text/javascript" src="../_static/doctools.js"></script>
<script type="text/javascript" src="../_static/language_data.js"></script>
<script type="text/javascript" src="https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/latest.js?config=TeX-AMS-MML_HTMLorMML"></script>
<link rel="search" type="application/opensearchdescription+xml"
title="Search within Matplotlib 2.2.5 documentation"
href="../_static/opensearch.xml"/>
<link rel="shortcut icon" href="../_static/favicon.ico"/>
<link rel="index" title="Index" href="../genindex.html"
/>
<link rel="search" title="Search" href="../search.html"
/>
<link rel="top" title="Matplotlib 2.2.5 documentation" href="../index.html" />
<link rel="up" title="Module code" href="index.html" />
<link rel="canonical" href="https://matplotlib.org/3.4.3/_modules/numpy.html" />
<script data-domain="matplotlib.org" defer="defer" src="https://views.scientific-python.org/js/script.js"></script>
</head>
<body>
<div id="unreleased-message"> You are reading an old version of the documentation (v2.2.5). For the latest version see <a href="/stable/">https://matplotlib.org/stable/</a> </div>
<div style="background-color: white; text-align: left; padding: 10px 10px 15px 15px; position: relative;">
<a href="../index.html">
<div style="float: left; position: absolute; width: 496px; bottom: 0; padding-bottom: 24px"><span style="float: right; color: #789; background: white">Version 2.2.5</span></div>
<img src="../_static/logo2.png" height="125px" border="0" alt="matplotlib"/></a>
<!-- The "Fork me on github" ribbon -->
<div id="forkongithub"><a href="https://github.com/matplotlib/matplotlib">Fork me on GitHub</a></div>
</div>
<div class="related">
<h3>Navigation</h3>
<ul>
<li class="right" style="margin-right: 10px">
<a href="../genindex.html" title="General Index"
accesskey="I">index</a></li>
<li class="right" >
<a href="../py-modindex.html" title="Python Module Index"
>modules</a> |</li>
<li><a href="../index.html">home</a>| </li>
<li><a href="../gallery/index.html">examples</a>| </li>
<li><a href="../tutorials/index.html">tutorials</a>| </li>
<li><a href="../api/pyplot_summary.html">pyplot</a>| </li>
<li><a href="../contents.html">docs</a> »</li>
<li><a href="index.html" accesskey="U">Module code</a> »</li>
</ul>
</div>
<div class="sphinxsidebar">
<div class="sphinxsidebarwrapper">
<div id="searchbox" style="display: none" role="search">
<h3>Quick search</h3>
<div class="searchformwrapper">
<form class="search" action="../search.html" method="get">
<input type="text" name="q" />
<input type="submit" value="Go" />
<input type="hidden" name="check_keywords" value="yes" />
<input type="hidden" name="area" value="default" />
</form>
</div>
</div>
<script type="text/javascript">$('#searchbox').show(0);</script><div class="relations">
<h3>Related Topics</h3>
<ul>
<li><a href="../contents.html">Documentation overview</a><ul>
<li><a href="index.html">Module code</a><ul>
</ul></li>
</ul></li>
</ul>
</div>
</div>
</div>
<div class="document">
<div class="documentwrapper">
<div class="bodywrapper">
<div class="body">
<h1>Source code for numpy</h1><div class="highlight"><pre>
<span></span><span class="sd">"""</span>
<span class="sd">NumPy</span>
<span class="sd">=====</span>
<span class="sd">Provides</span>
<span class="sd"> 1. An array object of arbitrary homogeneous items</span>
<span class="sd"> 2. Fast mathematical operations over arrays</span>
<span class="sd"> 3. Linear Algebra, Fourier Transforms, Random Number Generation</span>
<span class="sd">How to use the documentation</span>
<span class="sd">----------------------------</span>
<span class="sd">Documentation is available in two forms: docstrings provided</span>
<span class="sd">with the code, and a loose standing reference guide, available from</span>
<span class="sd">`the NumPy homepage <https://www.scipy.org>`_.</span>
<span class="sd">We recommend exploring the docstrings using</span>
<span class="sd">`IPython <https://ipython.org>`_, an advanced Python shell with</span>
<span class="sd">TAB-completion and introspection capabilities. See below for further</span>
<span class="sd">instructions.</span>
<span class="sd">The docstring examples assume that `numpy` has been imported as `np`::</span>
<span class="sd"> >>> import numpy as np</span>
<span class="sd">Code snippets are indicated by three greater-than signs::</span>
<span class="sd"> >>> x = 42</span>
<span class="sd"> >>> x = x + 1</span>
<span class="sd">Use the built-in ``help`` function to view a function's docstring::</span>
<span class="sd"> >>> help(np.sort)</span>
<span class="sd"> ... # doctest: +SKIP</span>
<span class="sd">For some objects, ``np.info(obj)`` may provide additional help. This is</span>
<span class="sd">particularly true if you see the line "Help on ufunc object:" at the top</span>
<span class="sd">of the help() page. Ufuncs are implemented in C, not Python, for speed.</span>
<span class="sd">The native Python help() does not know how to view their help, but our</span>
<span class="sd">np.info() function does.</span>
<span class="sd">To search for documents containing a keyword, do::</span>
<span class="sd"> >>> np.lookfor('keyword')</span>
<span class="sd"> ... # doctest: +SKIP</span>
<span class="sd">General-purpose documents like a glossary and help on the basic concepts</span>
<span class="sd">of numpy are available under the ``doc`` sub-module::</span>
<span class="sd"> >>> from numpy import doc</span>
<span class="sd"> >>> help(doc)</span>
<span class="sd"> ... # doctest: +SKIP</span>
<span class="sd">Available subpackages</span>
<span class="sd">---------------------</span>
<span class="sd">doc</span>
<span class="sd"> Topical documentation on broadcasting, indexing, etc.</span>
<span class="sd">lib</span>
<span class="sd"> Basic functions used by several sub-packages.</span>
<span class="sd">random</span>
<span class="sd"> Core Random Tools</span>
<span class="sd">linalg</span>
<span class="sd"> Core Linear Algebra Tools</span>
<span class="sd">fft</span>
<span class="sd"> Core FFT routines</span>
<span class="sd">polynomial</span>
<span class="sd"> Polynomial tools</span>
<span class="sd">testing</span>
<span class="sd"> NumPy testing tools</span>
<span class="sd">f2py</span>
<span class="sd"> Fortran to Python Interface Generator.</span>
<span class="sd">distutils</span>
<span class="sd"> Enhancements to distutils with support for</span>
<span class="sd"> Fortran compilers support and more.</span>
<span class="sd">Utilities</span>
<span class="sd">---------</span>
<span class="sd">test</span>
<span class="sd"> Run numpy unittests</span>
<span class="sd">show_config</span>
<span class="sd"> Show numpy build configuration</span>
<span class="sd">dual</span>
<span class="sd"> Overwrite certain functions with high-performance Scipy tools</span>
<span class="sd">matlib</span>
<span class="sd"> Make everything matrices.</span>
<span class="sd">__version__</span>
<span class="sd"> NumPy version string</span>
<span class="sd">Viewing documentation using IPython</span>
<span class="sd">-----------------------------------</span>
<span class="sd">Start IPython with the NumPy profile (``ipython -p numpy``), which will</span>
<span class="sd">import `numpy` under the alias `np`. Then, use the ``cpaste`` command to</span>
<span class="sd">paste examples into the shell. To see which functions are available in</span>
<span class="sd">`numpy`, type ``np.<TAB>`` (where ``<TAB>`` refers to the TAB key), or use</span>
<span class="sd">``np.*cos*?<ENTER>`` (where ``<ENTER>`` refers to the ENTER key) to narrow</span>
<span class="sd">down the list. To view the docstring for a function, use</span>
<span class="sd">``np.cos?<ENTER>`` (to view the docstring) and ``np.cos??<ENTER>`` (to view</span>
<span class="sd">the source code).</span>
<span class="sd">Copies vs. in-place operation</span>
<span class="sd">-----------------------------</span>
<span class="sd">Most of the functions in `numpy` return a copy of the array argument</span>
<span class="sd">(e.g., `np.sort`). In-place versions of these functions are often</span>
<span class="sd">available as array methods, i.e. ``x = np.array([1,2,3]); x.sort()``.</span>
<span class="sd">Exceptions to this rule are documented.</span>
<span class="sd">"""</span>
<span class="kn">from</span> <span class="nn">__future__</span> <span class="kn">import</span> <span class="n">division</span><span class="p">,</span> <span class="n">absolute_import</span><span class="p">,</span> <span class="n">print_function</span>
<span class="kn">import</span> <span class="nn">sys</span>
<span class="kn">import</span> <span class="nn">warnings</span>
<span class="kn">from</span> <span class="nn">._globals</span> <span class="kn">import</span> <span class="n">ModuleDeprecationWarning</span><span class="p">,</span> <span class="n">VisibleDeprecationWarning</span>
<span class="kn">from</span> <span class="nn">._globals</span> <span class="kn">import</span> <span class="n">_NoValue</span>
<span class="c1"># We first need to detect if we're being called as part of the numpy setup</span>
<span class="c1"># procedure itself in a reliable manner.</span>
<span class="k">try</span><span class="p">:</span>
<span class="n">__NUMPY_SETUP__</span>
<span class="k">except</span> <span class="ne">NameError</span><span class="p">:</span>
<span class="n">__NUMPY_SETUP__</span> <span class="o">=</span> <span class="kc">False</span>
<span class="k">if</span> <span class="n">__NUMPY_SETUP__</span><span class="p">:</span>
<span class="n">sys</span><span class="o">.</span><span class="n">stderr</span><span class="o">.</span><span class="n">write</span><span class="p">(</span><span class="s1">'Running from numpy source directory.</span><span class="se">\n</span><span class="s1">'</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">try</span><span class="p">:</span>
<span class="kn">from</span> <span class="nn">numpy.__config__</span> <span class="kn">import</span> <span class="n">show</span> <span class="k">as</span> <span class="n">show_config</span>
<span class="k">except</span> <span class="ne">ImportError</span><span class="p">:</span>
<span class="n">msg</span> <span class="o">=</span> <span class="s2">"""Error importing numpy: you should not try to import numpy from</span>
<span class="s2"> its source directory; please exit the numpy source tree, and relaunch</span>
<span class="s2"> your python interpreter from there."""</span>
<span class="k">raise</span> <span class="ne">ImportError</span><span class="p">(</span><span class="n">msg</span><span class="p">)</span>
<span class="kn">from</span> <span class="nn">.version</span> <span class="kn">import</span> <span class="n">git_revision</span> <span class="k">as</span> <span class="n">__git_revision__</span>
<span class="kn">from</span> <span class="nn">.version</span> <span class="kn">import</span> <span class="n">version</span> <span class="k">as</span> <span class="n">__version__</span>
<span class="n">__all__</span> <span class="o">=</span> <span class="p">[</span><span class="s1">'ModuleDeprecationWarning'</span><span class="p">,</span>
<span class="s1">'VisibleDeprecationWarning'</span><span class="p">]</span>
<span class="c1"># Allow distributors to run custom init code</span>
<span class="kn">from</span> <span class="nn">.</span> <span class="kn">import</span> <span class="n">_distributor_init</span>
<span class="kn">from</span> <span class="nn">.</span> <span class="kn">import</span> <span class="n">core</span>
<span class="kn">from</span> <span class="nn">.core</span> <span class="kn">import</span> <span class="o">*</span>
<span class="kn">from</span> <span class="nn">.</span> <span class="kn">import</span> <span class="n">compat</span>
<span class="kn">from</span> <span class="nn">.</span> <span class="kn">import</span> <span class="n">lib</span>
<span class="c1"># FIXME: why have numpy.lib if everything is imported here??</span>
<span class="kn">from</span> <span class="nn">.lib</span> <span class="kn">import</span> <span class="o">*</span>
<span class="kn">from</span> <span class="nn">.</span> <span class="kn">import</span> <span class="n">linalg</span>
<span class="kn">from</span> <span class="nn">.</span> <span class="kn">import</span> <span class="n">fft</span>
<span class="kn">from</span> <span class="nn">.</span> <span class="kn">import</span> <span class="n">polynomial</span>
<span class="kn">from</span> <span class="nn">.</span> <span class="kn">import</span> <span class="n">random</span>
<span class="kn">from</span> <span class="nn">.</span> <span class="kn">import</span> <span class="n">ctypeslib</span>
<span class="kn">from</span> <span class="nn">.</span> <span class="kn">import</span> <span class="n">ma</span>
<span class="kn">from</span> <span class="nn">.</span> <span class="kn">import</span> <span class="n">matrixlib</span> <span class="k">as</span> <span class="n">_mat</span>
<span class="kn">from</span> <span class="nn">.matrixlib</span> <span class="kn">import</span> <span class="o">*</span>
<span class="kn">from</span> <span class="nn">.compat</span> <span class="kn">import</span> <span class="n">long</span>
<span class="c1"># Make these accessible from numpy name-space</span>
<span class="c1"># but not imported in from numpy import *</span>
<span class="c1"># TODO[gh-6103]: Deprecate these</span>
<span class="k">if</span> <span class="n">sys</span><span class="o">.</span><span class="n">version_info</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span> <span class="o">>=</span> <span class="mi">3</span><span class="p">:</span>
<span class="kn">from</span> <span class="nn">builtins</span> <span class="kn">import</span> <span class="nb">bool</span><span class="p">,</span> <span class="nb">int</span><span class="p">,</span> <span class="nb">float</span><span class="p">,</span> <span class="nb">complex</span><span class="p">,</span> <span class="nb">object</span><span class="p">,</span> <span class="nb">str</span>
<span class="n">unicode</span> <span class="o">=</span> <span class="nb">str</span>
<span class="k">else</span><span class="p">:</span>
<span class="kn">from</span> <span class="nn">__builtin__</span> <span class="kn">import</span> <span class="nb">bool</span><span class="p">,</span> <span class="nb">int</span><span class="p">,</span> <span class="nb">float</span><span class="p">,</span> <span class="nb">complex</span><span class="p">,</span> <span class="nb">object</span><span class="p">,</span> <span class="n">unicode</span><span class="p">,</span> <span class="nb">str</span>
<span class="kn">from</span> <span class="nn">.core</span> <span class="kn">import</span> <span class="nb">round</span><span class="p">,</span> <span class="nb">abs</span><span class="p">,</span> <span class="nb">max</span><span class="p">,</span> <span class="nb">min</span>
<span class="c1"># now that numpy modules are imported, can initialize limits</span>
<span class="n">core</span><span class="o">.</span><span class="n">getlimits</span><span class="o">.</span><span class="n">_register_known_types</span><span class="p">()</span>
<span class="n">__all__</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span><span class="s1">'__version__'</span><span class="p">,</span> <span class="s1">'show_config'</span><span class="p">])</span>
<span class="n">__all__</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="n">core</span><span class="o">.</span><span class="n">__all__</span><span class="p">)</span>
<span class="n">__all__</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="n">_mat</span><span class="o">.</span><span class="n">__all__</span><span class="p">)</span>
<span class="n">__all__</span><span class="o">.</span><span class="n">extend</span><span class="p">(</span><span class="n">lib</span><span class="o">.</span><span class="n">__all__</span><span class="p">)</span>
<span class="n">__all__</span><span class="o">.</span><span class="n">extend</span><span class="p">([</span><span class="s1">'linalg'</span><span class="p">,</span> <span class="s1">'fft'</span><span class="p">,</span> <span class="s1">'random'</span><span class="p">,</span> <span class="s1">'ctypeslib'</span><span class="p">,</span> <span class="s1">'ma'</span><span class="p">])</span>
<span class="c1"># These are added by `from .core import *` and `core.__all__`, but we</span>
<span class="c1"># overwrite them above with builtins we do _not_ want to export.</span>
<span class="n">__all__</span><span class="o">.</span><span class="n">remove</span><span class="p">(</span><span class="s1">'long'</span><span class="p">)</span>
<span class="n">__all__</span><span class="o">.</span><span class="n">remove</span><span class="p">(</span><span class="s1">'unicode'</span><span class="p">)</span>
<span class="c1"># Remove things that are in the numpy.lib but not in the numpy namespace</span>
<span class="c1"># Note that there is a test (numpy/tests/test_public_api.py:test_numpy_namespace)</span>
<span class="c1"># that prevents adding more things to the main namespace by accident.</span>
<span class="c1"># The list below will grow until the `from .lib import *` fixme above is</span>
<span class="c1"># taken care of</span>
<span class="n">__all__</span><span class="o">.</span><span class="n">remove</span><span class="p">(</span><span class="s1">'Arrayterator'</span><span class="p">)</span>
<span class="k">del</span> <span class="n">Arrayterator</span>
<span class="c1"># Filter out Cython harmless warnings</span>
<span class="n">warnings</span><span class="o">.</span><span class="n">filterwarnings</span><span class="p">(</span><span class="s2">"ignore"</span><span class="p">,</span> <span class="n">message</span><span class="o">=</span><span class="s2">"numpy.dtype size changed"</span><span class="p">)</span>
<span class="n">warnings</span><span class="o">.</span><span class="n">filterwarnings</span><span class="p">(</span><span class="s2">"ignore"</span><span class="p">,</span> <span class="n">message</span><span class="o">=</span><span class="s2">"numpy.ufunc size changed"</span><span class="p">)</span>
<span class="n">warnings</span><span class="o">.</span><span class="n">filterwarnings</span><span class="p">(</span><span class="s2">"ignore"</span><span class="p">,</span> <span class="n">message</span><span class="o">=</span><span class="s2">"numpy.ndarray size changed"</span><span class="p">)</span>
<span class="c1"># oldnumeric and numarray were removed in 1.9. In case some packages import</span>
<span class="c1"># but do not use them, we define them here for backward compatibility.</span>
<span class="n">oldnumeric</span> <span class="o">=</span> <span class="s1">'removed'</span>
<span class="n">numarray</span> <span class="o">=</span> <span class="s1">'removed'</span>
<span class="k">if</span> <span class="n">sys</span><span class="o">.</span><span class="n">version_info</span><span class="p">[:</span><span class="mi">2</span><span class="p">]</span> <span class="o">>=</span> <span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">7</span><span class="p">):</span>
<span class="c1"># Importing Tester requires importing all of UnitTest which is not a</span>
<span class="c1"># cheap import Since it is mainly used in test suits, we lazy import it</span>
<span class="c1"># here to save on the order of 10 ms of import time for most users</span>
<span class="c1">#</span>
<span class="c1"># The previous way Tester was imported also had a side effect of adding</span>
<span class="c1"># the full `numpy.testing` namespace</span>
<span class="c1">#</span>
<span class="c1"># module level getattr is only supported in 3.7 onwards</span>
<span class="c1"># https://www.python.org/dev/peps/pep-0562/</span>
<span class="k">def</span> <span class="fm">__getattr__</span><span class="p">(</span><span class="n">attr</span><span class="p">):</span>
<span class="k">if</span> <span class="n">attr</span> <span class="o">==</span> <span class="s1">'testing'</span><span class="p">:</span>
<span class="kn">import</span> <span class="nn">numpy.testing</span> <span class="k">as</span> <span class="nn">testing</span>
<span class="k">return</span> <span class="n">testing</span>
<span class="k">elif</span> <span class="n">attr</span> <span class="o">==</span> <span class="s1">'Tester'</span><span class="p">:</span>
<span class="kn">from</span> <span class="nn">.testing</span> <span class="kn">import</span> <span class="n">Tester</span>
<span class="k">return</span> <span class="n">Tester</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">AttributeError</span><span class="p">(</span><span class="s2">"module </span><span class="si">{!r}</span><span class="s2"> has no attribute "</span>
<span class="s2">"</span><span class="si">{!r}</span><span class="s2">"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="vm">__name__</span><span class="p">,</span> <span class="n">attr</span><span class="p">))</span>
<span class="k">def</span> <span class="fm">__dir__</span><span class="p">():</span>
<span class="k">return</span> <span class="nb">list</span><span class="p">(</span><span class="nb">globals</span><span class="p">()</span><span class="o">.</span><span class="n">keys</span><span class="p">())</span> <span class="o">+</span> <span class="p">[</span><span class="s1">'Tester'</span><span class="p">,</span> <span class="s1">'testing'</span><span class="p">]</span>
<span class="k">else</span><span class="p">:</span>
<span class="c1"># We don't actually use this ourselves anymore, but I'm not 100% sure that</span>
<span class="c1"># no-one else in the world is using it (though I hope not)</span>
<span class="kn">from</span> <span class="nn">.testing</span> <span class="kn">import</span> <span class="n">Tester</span>
<span class="c1"># Pytest testing</span>
<span class="kn">from</span> <span class="nn">numpy._pytesttester</span> <span class="kn">import</span> <span class="n">PytestTester</span>
<span class="n">test</span> <span class="o">=</span> <span class="n">PytestTester</span><span class="p">(</span><span class="vm">__name__</span><span class="p">)</span>
<span class="k">del</span> <span class="n">PytestTester</span>
<span class="k">def</span> <span class="nf">_sanity_check</span><span class="p">():</span>
<span class="sd">"""</span>
<span class="sd"> Quick sanity checks for common bugs caused by environment.</span>
<span class="sd"> There are some cases e.g. with wrong BLAS ABI that cause wrong</span>
<span class="sd"> results under specific runtime conditions that are not necessarily</span>
<span class="sd"> achieved during test suite runs, and it is useful to catch those early.</span>
<span class="sd"> See https://github.com/numpy/numpy/issues/8577 and other</span>
<span class="sd"> similar bug reports.</span>
<span class="sd"> """</span>
<span class="k">try</span><span class="p">:</span>
<span class="n">x</span> <span class="o">=</span> <span class="n">ones</span><span class="p">(</span><span class="mi">2</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="n">float32</span><span class="p">)</span>
<span class="k">if</span> <span class="ow">not</span> <span class="nb">abs</span><span class="p">(</span><span class="n">x</span><span class="o">.</span><span class="n">dot</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="o">-</span> <span class="mf">2.0</span><span class="p">)</span> <span class="o"><</span> <span class="mf">1e-5</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">AssertionError</span><span class="p">()</span>
<span class="k">except</span> <span class="ne">AssertionError</span><span class="p">:</span>
<span class="n">msg</span> <span class="o">=</span> <span class="p">(</span><span class="s2">"The current Numpy installation (</span><span class="si">{!r}</span><span class="s2">) fails to "</span>
<span class="s2">"pass simple sanity checks. This can be caused for example "</span>
<span class="s2">"by incorrect BLAS library being linked in, or by mixing "</span>
<span class="s2">"package managers (pip, conda, apt, ...). Search closed "</span>
<span class="s2">"numpy issues for similar problems."</span><span class="p">)</span>
<span class="k">raise</span> <span class="ne">RuntimeError</span><span class="p">(</span><span class="n">msg</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="vm">__file__</span><span class="p">))</span>
<span class="n">_sanity_check</span><span class="p">()</span>
<span class="k">del</span> <span class="n">_sanity_check</span>
</pre></div>
</div>
</div>
</div>
<div class="clearer"></div>
</div>
<div class="footer">
© Copyright 2002 - 2012 John Hunter, Darren Dale, Eric Firing, Michael Droettboom and the Matplotlib development team; 2012 - 2018 The Matplotlib development team.
<br />
Last updated on Feb 09, 2020.
Created using
<ahref="http://sphinx-doc.org/">Sphinx</a> 1.8.5.
Doc version v2.2.5-2-ga847ffac5.
</div>
</body>
<footer>
</footer>
</html>
You can’t perform that action at this time.