{{ message }}
-
Notifications
You must be signed in to change notification settings - Fork 62
Expand file tree
/
Copy pathscale.html
More file actions
746 lines (596 loc) · 86.3 KB
/
Copy pathscale.html
File metadata and controls
746 lines (596 loc) · 86.3 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
397
398
399
400
401
402
403
404
405
406
407
408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
424
425
426
427
428
429
430
431
432
433
434
435
436
437
438
439
440
441
442
443
444
445
446
447
448
449
450
451
452
453
454
455
456
457
458
459
460
461
462
463
464
465
466
467
468
469
470
471
472
473
474
475
476
477
478
479
480
481
482
483
484
485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
501
502
503
504
505
506
507
508
509
510
511
512
513
514
515
516
517
518
519
520
521
522
523
524
525
526
527
528
529
530
531
532
533
534
535
536
537
538
539
540
541
542
543
544
545
546
547
548
549
550
551
552
553
554
555
556
557
558
559
560
561
562
563
564
565
566
567
568
569
570
571
572
573
574
575
576
577
578
579
580
581
582
583
584
585
586
587
588
589
590
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
610
611
612
613
614
615
616
617
618
619
620
621
622
623
624
625
626
627
628
629
630
631
632
633
634
635
636
637
638
639
640
641
642
643
644
645
646
647
648
649
650
651
652
653
654
655
656
657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
684
685
686
687
688
689
690
691
692
693
694
695
696
697
698
699
700
701
702
703
704
705
706
707
708
709
710
711
712
713
714
715
716
717
718
719
720
721
722
723
724
725
726
727
728
729
730
731
732
733
734
735
736
737
738
739
740
741
742
743
744
745
746
<!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>matplotlib.scale — Matplotlib 2.2.4 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: '2.2.4',
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 2.2.4 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 2.2.4 documentation" href="../../index.html" />
<link rel="up" title="matplotlib" href="../matplotlib.html" />
<link rel="canonical" href="https://matplotlib.org/3.4.3/_modules/matplotlib/scale.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 (v2.2.4). 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 2.2.4</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" >Module code</a> »</li>
<li><a href="../matplotlib.html" accesskey="U">matplotlib</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>
<li><a href="../matplotlib.html">matplotlib</a><ul>
</ul></li>
</ul></li>
</ul></li>
</ul>
</div>
</div>
</div>
<div class="document">
<div class="documentwrapper">
<div class="bodywrapper">
<div class="body">
<h1>Source code for matplotlib.scale</h1><div class="highlight"><pre>
<span></span><span class="kn">from</span> <span class="nn">__future__</span> <span class="k">import</span> <span class="p">(</span><span class="n">absolute_import</span><span class="p">,</span> <span class="n">division</span><span class="p">,</span> <span class="n">print_function</span><span class="p">,</span>
<span class="n">unicode_literals</span><span class="p">)</span>
<span class="kn">import</span> <span class="nn">six</span>
<span class="kn">import</span> <span class="nn">numpy</span> <span class="k">as</span> <span class="nn">np</span>
<span class="kn">from</span> <span class="nn">numpy</span> <span class="k">import</span> <span class="n">ma</span>
<span class="kn">from</span> <span class="nn">matplotlib</span> <span class="k">import</span> <span class="n">cbook</span><span class="p">,</span> <span class="n">docstring</span><span class="p">,</span> <span class="n">rcParams</span>
<span class="kn">from</span> <span class="nn">matplotlib.ticker</span> <span class="k">import</span> <span class="p">(</span>
<span class="n">NullFormatter</span><span class="p">,</span> <span class="n">ScalarFormatter</span><span class="p">,</span> <span class="n">LogFormatterSciNotation</span><span class="p">,</span> <span class="n">LogitFormatter</span><span class="p">,</span>
<span class="n">NullLocator</span><span class="p">,</span> <span class="n">LogLocator</span><span class="p">,</span> <span class="n">AutoLocator</span><span class="p">,</span> <span class="n">AutoMinorLocator</span><span class="p">,</span>
<span class="n">SymmetricalLogLocator</span><span class="p">,</span> <span class="n">LogitLocator</span><span class="p">)</span>
<span class="kn">from</span> <span class="nn">matplotlib.transforms</span> <span class="k">import</span> <span class="n">Transform</span><span class="p">,</span> <span class="n">IdentityTransform</span>
<div class="viewcode-block" id="ScaleBase"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.ScaleBase">[docs]</a><span class="k">class</span> <span class="nc">ScaleBase</span><span class="p">(</span><span class="nb">object</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> The base class for all scales.</span>
<span class="sd"> Scales are separable transformations, working on a single dimension.</span>
<span class="sd"> Any subclasses will want to override:</span>
<span class="sd"> - :attr:`name`</span>
<span class="sd"> - :meth:`get_transform`</span>
<span class="sd"> - :meth:`set_default_locators_and_formatters`</span>
<span class="sd"> And optionally:</span>
<span class="sd"> - :meth:`limit_range_for_scale`</span>
<span class="sd"> """</span>
<div class="viewcode-block" id="ScaleBase.get_transform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.ScaleBase.get_transform">[docs]</a> <span class="k">def</span> <span class="nf">get_transform</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Return the :class:`~matplotlib.transforms.Transform` object</span>
<span class="sd"> associated with this scale.</span>
<span class="sd"> """</span>
<span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">()</span></div>
<div class="viewcode-block" id="ScaleBase.set_default_locators_and_formatters"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.ScaleBase.set_default_locators_and_formatters">[docs]</a> <span class="k">def</span> <span class="nf">set_default_locators_and_formatters</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">axis</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Set the :class:`~matplotlib.ticker.Locator` and</span>
<span class="sd"> :class:`~matplotlib.ticker.Formatter` objects on the given</span>
<span class="sd"> axis to match this scale.</span>
<span class="sd"> """</span>
<span class="k">raise</span> <span class="ne">NotImplementedError</span><span class="p">()</span></div>
<div class="viewcode-block" id="ScaleBase.limit_range_for_scale"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.ScaleBase.limit_range_for_scale">[docs]</a> <span class="k">def</span> <span class="nf">limit_range_for_scale</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">vmin</span><span class="p">,</span> <span class="n">vmax</span><span class="p">,</span> <span class="n">minpos</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Returns the range *vmin*, *vmax*, possibly limited to the</span>
<span class="sd"> domain supported by this scale.</span>
<span class="sd"> *minpos* should be the minimum positive value in the data.</span>
<span class="sd"> This is used by log scales to determine a minimum value.</span>
<span class="sd"> """</span>
<span class="k">return</span> <span class="n">vmin</span><span class="p">,</span> <span class="n">vmax</span></div></div>
<div class="viewcode-block" id="LinearScale"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LinearScale">[docs]</a><span class="k">class</span> <span class="nc">LinearScale</span><span class="p">(</span><span class="n">ScaleBase</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> The default linear scale.</span>
<span class="sd"> """</span>
<span class="n">name</span> <span class="o">=</span> <span class="s1">'linear'</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">axis</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">pass</span>
<div class="viewcode-block" id="LinearScale.set_default_locators_and_formatters"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LinearScale.set_default_locators_and_formatters">[docs]</a> <span class="k">def</span> <span class="nf">set_default_locators_and_formatters</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">axis</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Set the locators and formatters to reasonable defaults for</span>
<span class="sd"> linear scaling.</span>
<span class="sd"> """</span>
<span class="n">axis</span><span class="o">.</span><span class="n">set_major_locator</span><span class="p">(</span><span class="n">AutoLocator</span><span class="p">())</span>
<span class="n">axis</span><span class="o">.</span><span class="n">set_major_formatter</span><span class="p">(</span><span class="n">ScalarFormatter</span><span class="p">())</span>
<span class="n">axis</span><span class="o">.</span><span class="n">set_minor_formatter</span><span class="p">(</span><span class="n">NullFormatter</span><span class="p">())</span>
<span class="c1"># update the minor locator for x and y axis based on rcParams</span>
<span class="k">if</span> <span class="n">rcParams</span><span class="p">[</span><span class="s1">'xtick.minor.visible'</span><span class="p">]:</span>
<span class="n">axis</span><span class="o">.</span><span class="n">set_minor_locator</span><span class="p">(</span><span class="n">AutoMinorLocator</span><span class="p">())</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">axis</span><span class="o">.</span><span class="n">set_minor_locator</span><span class="p">(</span><span class="n">NullLocator</span><span class="p">())</span></div>
<div class="viewcode-block" id="LinearScale.get_transform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LinearScale.get_transform">[docs]</a> <span class="k">def</span> <span class="nf">get_transform</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> The transform for linear scaling is just the</span>
<span class="sd"> :class:`~matplotlib.transforms.IdentityTransform`.</span>
<span class="sd"> """</span>
<span class="k">return</span> <span class="n">IdentityTransform</span><span class="p">()</span></div></div>
<div class="viewcode-block" id="LogTransformBase"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogTransformBase">[docs]</a><span class="k">class</span> <span class="nc">LogTransformBase</span><span class="p">(</span><span class="n">Transform</span><span class="p">):</span>
<span class="n">input_dims</span> <span class="o">=</span> <span class="mi">1</span>
<span class="n">output_dims</span> <span class="o">=</span> <span class="mi">1</span>
<span class="n">is_separable</span> <span class="o">=</span> <span class="kc">True</span>
<span class="n">has_inverse</span> <span class="o">=</span> <span class="kc">True</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">nonpos</span><span class="o">=</span><span class="s1">'clip'</span><span class="p">):</span>
<span class="n">Transform</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_clip</span> <span class="o">=</span> <span class="p">{</span><span class="s2">"clip"</span><span class="p">:</span> <span class="kc">True</span><span class="p">,</span> <span class="s2">"mask"</span><span class="p">:</span> <span class="kc">False</span><span class="p">}[</span><span class="n">nonpos</span><span class="p">]</span>
<div class="viewcode-block" id="LogTransformBase.transform_non_affine"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogTransformBase.transform_non_affine">[docs]</a> <span class="k">def</span> <span class="nf">transform_non_affine</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">a</span><span class="p">):</span>
<span class="c1"># Ignore invalid values due to nans being passed to the transform</span>
<span class="k">with</span> <span class="n">np</span><span class="o">.</span><span class="n">errstate</span><span class="p">(</span><span class="n">divide</span><span class="o">=</span><span class="s2">"ignore"</span><span class="p">,</span> <span class="n">invalid</span><span class="o">=</span><span class="s2">"ignore"</span><span class="p">):</span>
<span class="n">out</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="n">a</span><span class="p">)</span>
<span class="n">out</span> <span class="o">/=</span> <span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">base</span><span class="p">)</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_clip</span><span class="p">:</span>
<span class="c1"># SVG spec says that conforming viewers must support values up</span>
<span class="c1"># to 3.4e38 (C float); however experiments suggest that</span>
<span class="c1"># Inkscape (which uses cairo for rendering) runs into cairo's</span>
<span class="c1"># 24-bit limit (which is apparently shared by Agg).</span>
<span class="c1"># Ghostscript (used for pdf rendering appears to overflow even</span>
<span class="c1"># earlier, with the max value around 2 ** 15 for the tests to</span>
<span class="c1"># pass. On the other hand, in practice, we want to clip beyond</span>
<span class="c1"># np.log10(np.nextafter(0, 1)) ~ -323</span>
<span class="c1"># so 1000 seems safe.</span>
<span class="n">out</span><span class="p">[</span><span class="n">a</span> <span class="o"><=</span> <span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="o">-</span><span class="mi">1000</span>
<span class="k">return</span> <span class="n">out</span></div>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="s2">"</span><span class="si">{}</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="nb">type</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="vm">__name__</span><span class="p">,</span> <span class="s2">"clip"</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_clip</span> <span class="k">else</span> <span class="s2">"mask"</span><span class="p">)</span></div>
<div class="viewcode-block" id="InvertedLogTransformBase"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.InvertedLogTransformBase">[docs]</a><span class="k">class</span> <span class="nc">InvertedLogTransformBase</span><span class="p">(</span><span class="n">Transform</span><span class="p">):</span>
<span class="n">input_dims</span> <span class="o">=</span> <span class="mi">1</span>
<span class="n">output_dims</span> <span class="o">=</span> <span class="mi">1</span>
<span class="n">is_separable</span> <span class="o">=</span> <span class="kc">True</span>
<span class="n">has_inverse</span> <span class="o">=</span> <span class="kc">True</span>
<div class="viewcode-block" id="InvertedLogTransformBase.transform_non_affine"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.InvertedLogTransformBase.transform_non_affine">[docs]</a> <span class="k">def</span> <span class="nf">transform_non_affine</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">a</span><span class="p">):</span>
<span class="k">return</span> <span class="n">ma</span><span class="o">.</span><span class="n">power</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">base</span><span class="p">,</span> <span class="n">a</span><span class="p">)</span></div>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="s2">"</span><span class="si">{}</span><span class="s2">()"</span><span class="o">.</span><span class="n">format</span><span class="p">(</span><span class="nb">type</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="vm">__name__</span><span class="p">)</span></div>
<div class="viewcode-block" id="Log10Transform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.Log10Transform">[docs]</a><span class="k">class</span> <span class="nc">Log10Transform</span><span class="p">(</span><span class="n">LogTransformBase</span><span class="p">):</span>
<span class="n">base</span> <span class="o">=</span> <span class="mf">10.0</span>
<div class="viewcode-block" id="Log10Transform.inverted"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.Log10Transform.inverted">[docs]</a> <span class="k">def</span> <span class="nf">inverted</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">InvertedLog10Transform</span><span class="p">()</span></div></div>
<div class="viewcode-block" id="InvertedLog10Transform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.InvertedLog10Transform">[docs]</a><span class="k">class</span> <span class="nc">InvertedLog10Transform</span><span class="p">(</span><span class="n">InvertedLogTransformBase</span><span class="p">):</span>
<span class="n">base</span> <span class="o">=</span> <span class="mf">10.0</span>
<div class="viewcode-block" id="InvertedLog10Transform.inverted"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.InvertedLog10Transform.inverted">[docs]</a> <span class="k">def</span> <span class="nf">inverted</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">Log10Transform</span><span class="p">()</span></div></div>
<div class="viewcode-block" id="Log2Transform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.Log2Transform">[docs]</a><span class="k">class</span> <span class="nc">Log2Transform</span><span class="p">(</span><span class="n">LogTransformBase</span><span class="p">):</span>
<span class="n">base</span> <span class="o">=</span> <span class="mf">2.0</span>
<div class="viewcode-block" id="Log2Transform.inverted"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.Log2Transform.inverted">[docs]</a> <span class="k">def</span> <span class="nf">inverted</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">InvertedLog2Transform</span><span class="p">()</span></div></div>
<div class="viewcode-block" id="InvertedLog2Transform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.InvertedLog2Transform">[docs]</a><span class="k">class</span> <span class="nc">InvertedLog2Transform</span><span class="p">(</span><span class="n">InvertedLogTransformBase</span><span class="p">):</span>
<span class="n">base</span> <span class="o">=</span> <span class="mf">2.0</span>
<div class="viewcode-block" id="InvertedLog2Transform.inverted"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.InvertedLog2Transform.inverted">[docs]</a> <span class="k">def</span> <span class="nf">inverted</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">Log2Transform</span><span class="p">()</span></div></div>
<div class="viewcode-block" id="NaturalLogTransform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.NaturalLogTransform">[docs]</a><span class="k">class</span> <span class="nc">NaturalLogTransform</span><span class="p">(</span><span class="n">LogTransformBase</span><span class="p">):</span>
<span class="n">base</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">e</span>
<div class="viewcode-block" id="NaturalLogTransform.inverted"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.NaturalLogTransform.inverted">[docs]</a> <span class="k">def</span> <span class="nf">inverted</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">InvertedNaturalLogTransform</span><span class="p">()</span></div></div>
<div class="viewcode-block" id="InvertedNaturalLogTransform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.InvertedNaturalLogTransform">[docs]</a><span class="k">class</span> <span class="nc">InvertedNaturalLogTransform</span><span class="p">(</span><span class="n">InvertedLogTransformBase</span><span class="p">):</span>
<span class="n">base</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">e</span>
<div class="viewcode-block" id="InvertedNaturalLogTransform.inverted"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.InvertedNaturalLogTransform.inverted">[docs]</a> <span class="k">def</span> <span class="nf">inverted</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">NaturalLogTransform</span><span class="p">()</span></div></div>
<div class="viewcode-block" id="LogTransform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogTransform">[docs]</a><span class="k">class</span> <span class="nc">LogTransform</span><span class="p">(</span><span class="n">LogTransformBase</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">base</span><span class="p">,</span> <span class="n">nonpos</span><span class="o">=</span><span class="s1">'clip'</span><span class="p">):</span>
<span class="n">LogTransformBase</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">nonpos</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">base</span> <span class="o">=</span> <span class="n">base</span>
<div class="viewcode-block" id="LogTransform.inverted"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogTransform.inverted">[docs]</a> <span class="k">def</span> <span class="nf">inverted</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">InvertedLogTransform</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">base</span><span class="p">)</span></div></div>
<div class="viewcode-block" id="InvertedLogTransform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.InvertedLogTransform">[docs]</a><span class="k">class</span> <span class="nc">InvertedLogTransform</span><span class="p">(</span><span class="n">InvertedLogTransformBase</span><span class="p">):</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">base</span><span class="p">):</span>
<span class="n">InvertedLogTransformBase</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">base</span> <span class="o">=</span> <span class="n">base</span>
<div class="viewcode-block" id="InvertedLogTransform.inverted"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.InvertedLogTransform.inverted">[docs]</a> <span class="k">def</span> <span class="nf">inverted</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">LogTransform</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">base</span><span class="p">)</span></div></div>
<div class="viewcode-block" id="LogScale"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogScale">[docs]</a><span class="k">class</span> <span class="nc">LogScale</span><span class="p">(</span><span class="n">ScaleBase</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> A standard logarithmic scale. Care is taken so non-positive</span>
<span class="sd"> values are not plotted.</span>
<span class="sd"> For computational efficiency (to push as much as possible to Numpy</span>
<span class="sd"> C code in the common cases), this scale provides different</span>
<span class="sd"> transforms depending on the base of the logarithm:</span>
<span class="sd"> - base 10 (:class:`Log10Transform`)</span>
<span class="sd"> - base 2 (:class:`Log2Transform`)</span>
<span class="sd"> - base e (:class:`NaturalLogTransform`)</span>
<span class="sd"> - arbitrary base (:class:`LogTransform`)</span>
<span class="sd"> """</span>
<span class="n">name</span> <span class="o">=</span> <span class="s1">'log'</span>
<span class="c1"># compatibility shim</span>
<span class="n">LogTransformBase</span> <span class="o">=</span> <span class="n">LogTransformBase</span>
<span class="n">Log10Transform</span> <span class="o">=</span> <span class="n">Log10Transform</span>
<span class="n">InvertedLog10Transform</span> <span class="o">=</span> <span class="n">InvertedLog10Transform</span>
<span class="n">Log2Transform</span> <span class="o">=</span> <span class="n">Log2Transform</span>
<span class="n">InvertedLog2Transform</span> <span class="o">=</span> <span class="n">InvertedLog2Transform</span>
<span class="n">NaturalLogTransform</span> <span class="o">=</span> <span class="n">NaturalLogTransform</span>
<span class="n">InvertedNaturalLogTransform</span> <span class="o">=</span> <span class="n">InvertedNaturalLogTransform</span>
<span class="n">LogTransform</span> <span class="o">=</span> <span class="n">LogTransform</span>
<span class="n">InvertedLogTransform</span> <span class="o">=</span> <span class="n">InvertedLogTransform</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">axis</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> *basex*/*basey*:</span>
<span class="sd"> The base of the logarithm</span>
<span class="sd"> *nonposx*/*nonposy*: ['mask' | 'clip' ]</span>
<span class="sd"> non-positive values in *x* or *y* can be masked as</span>
<span class="sd"> invalid, or clipped to a very small positive number</span>
<span class="sd"> *subsx*/*subsy*:</span>
<span class="sd"> Where to place the subticks between each major tick.</span>
<span class="sd"> Should be a sequence of integers. For example, in a log10</span>
<span class="sd"> scale: ``[2, 3, 4, 5, 6, 7, 8, 9]``</span>
<span class="sd"> will place 8 logarithmically spaced minor ticks between</span>
<span class="sd"> each major tick.</span>
<span class="sd"> """</span>
<span class="k">if</span> <span class="n">axis</span><span class="o">.</span><span class="n">axis_name</span> <span class="o">==</span> <span class="s1">'x'</span><span class="p">:</span>
<span class="n">base</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'basex'</span><span class="p">,</span> <span class="mf">10.0</span><span class="p">)</span>
<span class="n">subs</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'subsx'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
<span class="n">nonpos</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'nonposx'</span><span class="p">,</span> <span class="s1">'clip'</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">base</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'basey'</span><span class="p">,</span> <span class="mf">10.0</span><span class="p">)</span>
<span class="n">subs</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'subsy'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
<span class="n">nonpos</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'nonposy'</span><span class="p">,</span> <span class="s1">'clip'</span><span class="p">)</span>
<span class="k">if</span> <span class="nb">len</span><span class="p">(</span><span class="n">kwargs</span><span class="p">):</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">((</span><span class="s2">"provided too many kwargs, can only pass "</span>
<span class="s2">"{'basex', 'subsx', nonposx'} or "</span>
<span class="s2">"{'basey', 'subsy', nonposy'}. You passed "</span><span class="p">)</span> <span class="o">+</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="n">kwargs</span><span class="p">))</span>
<span class="k">if</span> <span class="n">nonpos</span> <span class="ow">not</span> <span class="ow">in</span> <span class="p">[</span><span class="s1">'mask'</span><span class="p">,</span> <span class="s1">'clip'</span><span class="p">]:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">"nonposx, nonposy kwarg must be 'mask' or 'clip'"</span><span class="p">)</span>
<span class="k">if</span> <span class="n">base</span> <span class="o"><=</span> <span class="mi">0</span> <span class="ow">or</span> <span class="n">base</span> <span class="o">==</span> <span class="mi">1</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s1">'The log base cannot be <= 0 or == 1'</span><span class="p">)</span>
<span class="k">if</span> <span class="n">base</span> <span class="o">==</span> <span class="mf">10.0</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_transform</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">Log10Transform</span><span class="p">(</span><span class="n">nonpos</span><span class="p">)</span>
<span class="k">elif</span> <span class="n">base</span> <span class="o">==</span> <span class="mf">2.0</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_transform</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">Log2Transform</span><span class="p">(</span><span class="n">nonpos</span><span class="p">)</span>
<span class="k">elif</span> <span class="n">base</span> <span class="o">==</span> <span class="n">np</span><span class="o">.</span><span class="n">e</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_transform</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">NaturalLogTransform</span><span class="p">(</span><span class="n">nonpos</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_transform</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">LogTransform</span><span class="p">(</span><span class="n">base</span><span class="p">,</span> <span class="n">nonpos</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">base</span> <span class="o">=</span> <span class="n">base</span>
<span class="bp">self</span><span class="o">.</span><span class="n">subs</span> <span class="o">=</span> <span class="n">subs</span>
<div class="viewcode-block" id="LogScale.set_default_locators_and_formatters"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogScale.set_default_locators_and_formatters">[docs]</a> <span class="k">def</span> <span class="nf">set_default_locators_and_formatters</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">axis</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Set the locators and formatters to specialized versions for</span>
<span class="sd"> log scaling.</span>
<span class="sd"> """</span>
<span class="n">axis</span><span class="o">.</span><span class="n">set_major_locator</span><span class="p">(</span><span class="n">LogLocator</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">base</span><span class="p">))</span>
<span class="n">axis</span><span class="o">.</span><span class="n">set_major_formatter</span><span class="p">(</span><span class="n">LogFormatterSciNotation</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">base</span><span class="p">))</span>
<span class="n">axis</span><span class="o">.</span><span class="n">set_minor_locator</span><span class="p">(</span><span class="n">LogLocator</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">base</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">subs</span><span class="p">))</span>
<span class="n">axis</span><span class="o">.</span><span class="n">set_minor_formatter</span><span class="p">(</span>
<span class="n">LogFormatterSciNotation</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">base</span><span class="p">,</span>
<span class="n">labelOnlyBase</span><span class="o">=</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">subs</span> <span class="ow">is</span> <span class="ow">not</span> <span class="kc">None</span><span class="p">)))</span></div>
<div class="viewcode-block" id="LogScale.get_transform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogScale.get_transform">[docs]</a> <span class="k">def</span> <span class="nf">get_transform</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Return a :class:`~matplotlib.transforms.Transform` instance</span>
<span class="sd"> appropriate for the given logarithm base.</span>
<span class="sd"> """</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_transform</span></div>
<div class="viewcode-block" id="LogScale.limit_range_for_scale"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogScale.limit_range_for_scale">[docs]</a> <span class="k">def</span> <span class="nf">limit_range_for_scale</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">vmin</span><span class="p">,</span> <span class="n">vmax</span><span class="p">,</span> <span class="n">minpos</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Limit the domain to positive values.</span>
<span class="sd"> """</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">np</span><span class="o">.</span><span class="n">isfinite</span><span class="p">(</span><span class="n">minpos</span><span class="p">):</span>
<span class="n">minpos</span> <span class="o">=</span> <span class="mf">1e-300</span> <span class="c1"># This value should rarely if ever</span>
<span class="c1"># end up with a visible effect.</span>
<span class="k">return</span> <span class="p">(</span><span class="n">minpos</span> <span class="k">if</span> <span class="n">vmin</span> <span class="o"><=</span> <span class="mi">0</span> <span class="k">else</span> <span class="n">vmin</span><span class="p">,</span>
<span class="n">minpos</span> <span class="k">if</span> <span class="n">vmax</span> <span class="o"><=</span> <span class="mi">0</span> <span class="k">else</span> <span class="n">vmax</span><span class="p">)</span></div></div>
<div class="viewcode-block" id="SymmetricalLogTransform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.SymmetricalLogTransform">[docs]</a><span class="k">class</span> <span class="nc">SymmetricalLogTransform</span><span class="p">(</span><span class="n">Transform</span><span class="p">):</span>
<span class="n">input_dims</span> <span class="o">=</span> <span class="mi">1</span>
<span class="n">output_dims</span> <span class="o">=</span> <span class="mi">1</span>
<span class="n">is_separable</span> <span class="o">=</span> <span class="kc">True</span>
<span class="n">has_inverse</span> <span class="o">=</span> <span class="kc">True</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">base</span><span class="p">,</span> <span class="n">linthresh</span><span class="p">,</span> <span class="n">linscale</span><span class="p">):</span>
<span class="n">Transform</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">base</span> <span class="o">=</span> <span class="n">base</span>
<span class="bp">self</span><span class="o">.</span><span class="n">linthresh</span> <span class="o">=</span> <span class="n">linthresh</span>
<span class="bp">self</span><span class="o">.</span><span class="n">linscale</span> <span class="o">=</span> <span class="n">linscale</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_linscale_adj</span> <span class="o">=</span> <span class="p">(</span><span class="n">linscale</span> <span class="o">/</span> <span class="p">(</span><span class="mf">1.0</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">base</span> <span class="o">**</span> <span class="o">-</span><span class="mi">1</span><span class="p">))</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_log_base</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="n">base</span><span class="p">)</span>
<div class="viewcode-block" id="SymmetricalLogTransform.transform_non_affine"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.SymmetricalLogTransform.transform_non_affine">[docs]</a> <span class="k">def</span> <span class="nf">transform_non_affine</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">a</span><span class="p">):</span>
<span class="n">sign</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sign</span><span class="p">(</span><span class="n">a</span><span class="p">)</span>
<span class="n">masked</span> <span class="o">=</span> <span class="n">ma</span><span class="o">.</span><span class="n">masked_inside</span><span class="p">(</span><span class="n">a</span><span class="p">,</span>
<span class="o">-</span><span class="bp">self</span><span class="o">.</span><span class="n">linthresh</span><span class="p">,</span>
<span class="bp">self</span><span class="o">.</span><span class="n">linthresh</span><span class="p">,</span>
<span class="n">copy</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
<span class="n">log</span> <span class="o">=</span> <span class="n">sign</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">linthresh</span> <span class="o">*</span> <span class="p">(</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_linscale_adj</span> <span class="o">+</span>
<span class="n">ma</span><span class="o">.</span><span class="n">log</span><span class="p">(</span><span class="n">np</span><span class="o">.</span><span class="n">abs</span><span class="p">(</span><span class="n">masked</span><span class="p">)</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">linthresh</span><span class="p">)</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">_log_base</span><span class="p">)</span>
<span class="k">if</span> <span class="n">masked</span><span class="o">.</span><span class="n">mask</span><span class="o">.</span><span class="n">any</span><span class="p">():</span>
<span class="k">return</span> <span class="n">ma</span><span class="o">.</span><span class="n">where</span><span class="p">(</span><span class="n">masked</span><span class="o">.</span><span class="n">mask</span><span class="p">,</span> <span class="n">a</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">_linscale_adj</span><span class="p">,</span> <span class="n">log</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">log</span></div>
<div class="viewcode-block" id="SymmetricalLogTransform.inverted"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.SymmetricalLogTransform.inverted">[docs]</a> <span class="k">def</span> <span class="nf">inverted</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">InvertedSymmetricalLogTransform</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">base</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">linthresh</span><span class="p">,</span>
<span class="bp">self</span><span class="o">.</span><span class="n">linscale</span><span class="p">)</span></div></div>
<div class="viewcode-block" id="InvertedSymmetricalLogTransform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.InvertedSymmetricalLogTransform">[docs]</a><span class="k">class</span> <span class="nc">InvertedSymmetricalLogTransform</span><span class="p">(</span><span class="n">Transform</span><span class="p">):</span>
<span class="n">input_dims</span> <span class="o">=</span> <span class="mi">1</span>
<span class="n">output_dims</span> <span class="o">=</span> <span class="mi">1</span>
<span class="n">is_separable</span> <span class="o">=</span> <span class="kc">True</span>
<span class="n">has_inverse</span> <span class="o">=</span> <span class="kc">True</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">base</span><span class="p">,</span> <span class="n">linthresh</span><span class="p">,</span> <span class="n">linscale</span><span class="p">):</span>
<span class="n">Transform</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span>
<span class="n">symlog</span> <span class="o">=</span> <span class="n">SymmetricalLogTransform</span><span class="p">(</span><span class="n">base</span><span class="p">,</span> <span class="n">linthresh</span><span class="p">,</span> <span class="n">linscale</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">base</span> <span class="o">=</span> <span class="n">base</span>
<span class="bp">self</span><span class="o">.</span><span class="n">linthresh</span> <span class="o">=</span> <span class="n">linthresh</span>
<span class="bp">self</span><span class="o">.</span><span class="n">invlinthresh</span> <span class="o">=</span> <span class="n">symlog</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">linthresh</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">linscale</span> <span class="o">=</span> <span class="n">linscale</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_linscale_adj</span> <span class="o">=</span> <span class="p">(</span><span class="n">linscale</span> <span class="o">/</span> <span class="p">(</span><span class="mf">1.0</span> <span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">base</span> <span class="o">**</span> <span class="o">-</span><span class="mi">1</span><span class="p">))</span>
<div class="viewcode-block" id="InvertedSymmetricalLogTransform.transform_non_affine"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.InvertedSymmetricalLogTransform.transform_non_affine">[docs]</a> <span class="k">def</span> <span class="nf">transform_non_affine</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">a</span><span class="p">):</span>
<span class="n">sign</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">sign</span><span class="p">(</span><span class="n">a</span><span class="p">)</span>
<span class="n">masked</span> <span class="o">=</span> <span class="n">ma</span><span class="o">.</span><span class="n">masked_inside</span><span class="p">(</span><span class="n">a</span><span class="p">,</span> <span class="o">-</span><span class="bp">self</span><span class="o">.</span><span class="n">invlinthresh</span><span class="p">,</span>
<span class="bp">self</span><span class="o">.</span><span class="n">invlinthresh</span><span class="p">,</span> <span class="n">copy</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
<span class="n">exp</span> <span class="o">=</span> <span class="n">sign</span> <span class="o">*</span> <span class="bp">self</span><span class="o">.</span><span class="n">linthresh</span> <span class="o">*</span> <span class="p">(</span>
<span class="n">ma</span><span class="o">.</span><span class="n">power</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">base</span><span class="p">,</span> <span class="p">(</span><span class="n">sign</span> <span class="o">*</span> <span class="p">(</span><span class="n">masked</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">linthresh</span><span class="p">))</span>
<span class="o">-</span> <span class="bp">self</span><span class="o">.</span><span class="n">_linscale_adj</span><span class="p">))</span>
<span class="k">if</span> <span class="n">masked</span><span class="o">.</span><span class="n">mask</span><span class="o">.</span><span class="n">any</span><span class="p">():</span>
<span class="k">return</span> <span class="n">ma</span><span class="o">.</span><span class="n">where</span><span class="p">(</span><span class="n">masked</span><span class="o">.</span><span class="n">mask</span><span class="p">,</span> <span class="n">a</span> <span class="o">/</span> <span class="bp">self</span><span class="o">.</span><span class="n">_linscale_adj</span><span class="p">,</span> <span class="n">exp</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="k">return</span> <span class="n">exp</span></div>
<div class="viewcode-block" id="InvertedSymmetricalLogTransform.inverted"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.InvertedSymmetricalLogTransform.inverted">[docs]</a> <span class="k">def</span> <span class="nf">inverted</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">SymmetricalLogTransform</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">base</span><span class="p">,</span>
<span class="bp">self</span><span class="o">.</span><span class="n">linthresh</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">linscale</span><span class="p">)</span></div></div>
<div class="viewcode-block" id="SymmetricalLogScale"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.SymmetricalLogScale">[docs]</a><span class="k">class</span> <span class="nc">SymmetricalLogScale</span><span class="p">(</span><span class="n">ScaleBase</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> The symmetrical logarithmic scale is logarithmic in both the</span>
<span class="sd"> positive and negative directions from the origin.</span>
<span class="sd"> Since the values close to zero tend toward infinity, there is a</span>
<span class="sd"> need to have a range around zero that is linear. The parameter</span>
<span class="sd"> *linthresh* allows the user to specify the size of this range</span>
<span class="sd"> (-*linthresh*, *linthresh*).</span>
<span class="sd"> """</span>
<span class="n">name</span> <span class="o">=</span> <span class="s1">'symlog'</span>
<span class="c1"># compatibility shim</span>
<span class="n">SymmetricalLogTransform</span> <span class="o">=</span> <span class="n">SymmetricalLogTransform</span>
<span class="n">InvertedSymmetricalLogTransform</span> <span class="o">=</span> <span class="n">InvertedSymmetricalLogTransform</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">axis</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> *basex*/*basey*:</span>
<span class="sd"> The base of the logarithm</span>
<span class="sd"> *linthreshx*/*linthreshy*:</span>
<span class="sd"> A single float which defines the range (-*x*, *x*), within</span>
<span class="sd"> which the plot is linear. This avoids having the plot go to</span>
<span class="sd"> infinity around zero.</span>
<span class="sd"> *subsx*/*subsy*:</span>
<span class="sd"> Where to place the subticks between each major tick.</span>
<span class="sd"> Should be a sequence of integers. For example, in a log10</span>
<span class="sd"> scale: ``[2, 3, 4, 5, 6, 7, 8, 9]``</span>
<span class="sd"> will place 8 logarithmically spaced minor ticks between</span>
<span class="sd"> each major tick.</span>
<span class="sd"> *linscalex*/*linscaley*:</span>
<span class="sd"> This allows the linear range (-*linthresh* to *linthresh*)</span>
<span class="sd"> to be stretched relative to the logarithmic range. Its</span>
<span class="sd"> value is the number of decades to use for each half of the</span>
<span class="sd"> linear range. For example, when *linscale* == 1.0 (the</span>
<span class="sd"> default), the space used for the positive and negative</span>
<span class="sd"> halves of the linear range will be equal to one decade in</span>
<span class="sd"> the logarithmic range.</span>
<span class="sd"> """</span>
<span class="k">if</span> <span class="n">axis</span><span class="o">.</span><span class="n">axis_name</span> <span class="o">==</span> <span class="s1">'x'</span><span class="p">:</span>
<span class="n">base</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'basex'</span><span class="p">,</span> <span class="mf">10.0</span><span class="p">)</span>
<span class="n">linthresh</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'linthreshx'</span><span class="p">,</span> <span class="mf">2.0</span><span class="p">)</span>
<span class="n">subs</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'subsx'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
<span class="n">linscale</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'linscalex'</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">)</span>
<span class="k">else</span><span class="p">:</span>
<span class="n">base</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'basey'</span><span class="p">,</span> <span class="mf">10.0</span><span class="p">)</span>
<span class="n">linthresh</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'linthreshy'</span><span class="p">,</span> <span class="mf">2.0</span><span class="p">)</span>
<span class="n">subs</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'subsy'</span><span class="p">,</span> <span class="kc">None</span><span class="p">)</span>
<span class="n">linscale</span> <span class="o">=</span> <span class="n">kwargs</span><span class="o">.</span><span class="n">pop</span><span class="p">(</span><span class="s1">'linscaley'</span><span class="p">,</span> <span class="mf">1.0</span><span class="p">)</span>
<span class="k">if</span> <span class="n">base</span> <span class="o"><=</span> <span class="mf">1.0</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">"'basex/basey' must be larger than 1"</span><span class="p">)</span>
<span class="k">if</span> <span class="n">linthresh</span> <span class="o"><=</span> <span class="mf">0.0</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">"'linthreshx/linthreshy' must be positive"</span><span class="p">)</span>
<span class="k">if</span> <span class="n">linscale</span> <span class="o"><=</span> <span class="mf">0.0</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">"'linscalex/linthreshy' must be positive"</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_transform</span> <span class="o">=</span> <span class="bp">self</span><span class="o">.</span><span class="n">SymmetricalLogTransform</span><span class="p">(</span><span class="n">base</span><span class="p">,</span>
<span class="n">linthresh</span><span class="p">,</span>
<span class="n">linscale</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">base</span> <span class="o">=</span> <span class="n">base</span>
<span class="bp">self</span><span class="o">.</span><span class="n">linthresh</span> <span class="o">=</span> <span class="n">linthresh</span>
<span class="bp">self</span><span class="o">.</span><span class="n">linscale</span> <span class="o">=</span> <span class="n">linscale</span>
<span class="bp">self</span><span class="o">.</span><span class="n">subs</span> <span class="o">=</span> <span class="n">subs</span>
<div class="viewcode-block" id="SymmetricalLogScale.set_default_locators_and_formatters"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.SymmetricalLogScale.set_default_locators_and_formatters">[docs]</a> <span class="k">def</span> <span class="nf">set_default_locators_and_formatters</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">axis</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Set the locators and formatters to specialized versions for</span>
<span class="sd"> symmetrical log scaling.</span>
<span class="sd"> """</span>
<span class="n">axis</span><span class="o">.</span><span class="n">set_major_locator</span><span class="p">(</span><span class="n">SymmetricalLogLocator</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">get_transform</span><span class="p">()))</span>
<span class="n">axis</span><span class="o">.</span><span class="n">set_major_formatter</span><span class="p">(</span><span class="n">LogFormatterSciNotation</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">base</span><span class="p">))</span>
<span class="n">axis</span><span class="o">.</span><span class="n">set_minor_locator</span><span class="p">(</span><span class="n">SymmetricalLogLocator</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">get_transform</span><span class="p">(),</span>
<span class="bp">self</span><span class="o">.</span><span class="n">subs</span><span class="p">))</span>
<span class="n">axis</span><span class="o">.</span><span class="n">set_minor_formatter</span><span class="p">(</span><span class="n">NullFormatter</span><span class="p">())</span></div>
<div class="viewcode-block" id="SymmetricalLogScale.get_transform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.SymmetricalLogScale.get_transform">[docs]</a> <span class="k">def</span> <span class="nf">get_transform</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Return a :class:`SymmetricalLogTransform` instance.</span>
<span class="sd"> """</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_transform</span></div></div>
<div class="viewcode-block" id="LogitTransform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogitTransform">[docs]</a><span class="k">class</span> <span class="nc">LogitTransform</span><span class="p">(</span><span class="n">Transform</span><span class="p">):</span>
<span class="n">input_dims</span> <span class="o">=</span> <span class="mi">1</span>
<span class="n">output_dims</span> <span class="o">=</span> <span class="mi">1</span>
<span class="n">is_separable</span> <span class="o">=</span> <span class="kc">True</span>
<span class="n">has_inverse</span> <span class="o">=</span> <span class="kc">True</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">nonpos</span><span class="o">=</span><span class="s1">'mask'</span><span class="p">):</span>
<span class="n">Transform</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_nonpos</span> <span class="o">=</span> <span class="n">nonpos</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_clip</span> <span class="o">=</span> <span class="p">{</span><span class="s2">"clip"</span><span class="p">:</span> <span class="kc">True</span><span class="p">,</span> <span class="s2">"mask"</span><span class="p">:</span> <span class="kc">False</span><span class="p">}[</span><span class="n">nonpos</span><span class="p">]</span>
<div class="viewcode-block" id="LogitTransform.transform_non_affine"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogitTransform.transform_non_affine">[docs]</a> <span class="k">def</span> <span class="nf">transform_non_affine</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">a</span><span class="p">):</span>
<span class="sd">"""logit transform (base 10), masked or clipped"""</span>
<span class="k">with</span> <span class="n">np</span><span class="o">.</span><span class="n">errstate</span><span class="p">(</span><span class="n">divide</span><span class="o">=</span><span class="s2">"ignore"</span><span class="p">,</span> <span class="n">invalid</span><span class="o">=</span><span class="s2">"ignore"</span><span class="p">):</span>
<span class="n">out</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">log10</span><span class="p">(</span><span class="n">a</span> <span class="o">/</span> <span class="p">(</span><span class="mi">1</span> <span class="o">-</span> <span class="n">a</span><span class="p">))</span>
<span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_clip</span><span class="p">:</span> <span class="c1"># See LogTransform for choice of clip value.</span>
<span class="n">out</span><span class="p">[</span><span class="n">a</span> <span class="o"><=</span> <span class="mi">0</span><span class="p">]</span> <span class="o">=</span> <span class="o">-</span><span class="mi">1000</span>
<span class="n">out</span><span class="p">[</span><span class="mi">1</span> <span class="o"><=</span> <span class="n">a</span><span class="p">]</span> <span class="o">=</span> <span class="mi">1000</span>
<span class="k">return</span> <span class="n">out</span></div>
<div class="viewcode-block" id="LogitTransform.inverted"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogitTransform.inverted">[docs]</a> <span class="k">def</span> <span class="nf">inverted</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">LogisticTransform</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_nonpos</span><span class="p">)</span></div>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="s2">"</span><span class="si">{}</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="nb">type</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="vm">__name__</span><span class="p">,</span>
<span class="s2">"clip"</span> <span class="k">if</span> <span class="bp">self</span><span class="o">.</span><span class="n">_clip</span> <span class="k">else</span> <span class="s2">"mask"</span><span class="p">)</span></div>
<div class="viewcode-block" id="LogisticTransform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogisticTransform">[docs]</a><span class="k">class</span> <span class="nc">LogisticTransform</span><span class="p">(</span><span class="n">Transform</span><span class="p">):</span>
<span class="n">input_dims</span> <span class="o">=</span> <span class="mi">1</span>
<span class="n">output_dims</span> <span class="o">=</span> <span class="mi">1</span>
<span class="n">is_separable</span> <span class="o">=</span> <span class="kc">True</span>
<span class="n">has_inverse</span> <span class="o">=</span> <span class="kc">True</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">nonpos</span><span class="o">=</span><span class="s1">'mask'</span><span class="p">):</span>
<span class="n">Transform</span><span class="o">.</span><span class="fm">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_nonpos</span> <span class="o">=</span> <span class="n">nonpos</span>
<div class="viewcode-block" id="LogisticTransform.transform_non_affine"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogisticTransform.transform_non_affine">[docs]</a> <span class="k">def</span> <span class="nf">transform_non_affine</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">a</span><span class="p">):</span>
<span class="sd">"""logistic transform (base 10)"""</span>
<span class="k">return</span> <span class="mf">1.0</span> <span class="o">/</span> <span class="p">(</span><span class="mi">1</span> <span class="o">+</span> <span class="mi">10</span><span class="o">**</span><span class="p">(</span><span class="o">-</span><span class="n">a</span><span class="p">))</span></div>
<div class="viewcode-block" id="LogisticTransform.inverted"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogisticTransform.inverted">[docs]</a> <span class="k">def</span> <span class="nf">inverted</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="n">LogitTransform</span><span class="p">(</span><span class="bp">self</span><span class="o">.</span><span class="n">_nonpos</span><span class="p">)</span></div>
<span class="k">def</span> <span class="nf">__str__</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="k">return</span> <span class="s2">"</span><span class="si">{}</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="nb">type</span><span class="p">(</span><span class="bp">self</span><span class="p">)</span><span class="o">.</span><span class="vm">__name__</span><span class="p">,</span> <span class="bp">self</span><span class="o">.</span><span class="n">_nonpos</span><span class="p">)</span></div>
<div class="viewcode-block" id="LogitScale"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogitScale">[docs]</a><span class="k">class</span> <span class="nc">LogitScale</span><span class="p">(</span><span class="n">ScaleBase</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Logit scale for data between zero and one, both excluded.</span>
<span class="sd"> This scale is similar to a log scale close to zero and to one, and almost</span>
<span class="sd"> linear around 0.5. It maps the interval ]0, 1[ onto ]-infty, +infty[.</span>
<span class="sd"> """</span>
<span class="n">name</span> <span class="o">=</span> <span class="s1">'logit'</span>
<span class="k">def</span> <span class="nf">__init__</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">axis</span><span class="p">,</span> <span class="n">nonpos</span><span class="o">=</span><span class="s1">'mask'</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> *nonpos*: ['mask' | 'clip' ]</span>
<span class="sd"> values beyond ]0, 1[ can be masked as invalid, or clipped to a number</span>
<span class="sd"> very close to 0 or 1</span>
<span class="sd"> """</span>
<span class="k">if</span> <span class="n">nonpos</span> <span class="ow">not</span> <span class="ow">in</span> <span class="p">[</span><span class="s1">'mask'</span><span class="p">,</span> <span class="s1">'clip'</span><span class="p">]:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">"nonposx, nonposy kwarg must be 'mask' or 'clip'"</span><span class="p">)</span>
<span class="bp">self</span><span class="o">.</span><span class="n">_transform</span> <span class="o">=</span> <span class="n">LogitTransform</span><span class="p">(</span><span class="n">nonpos</span><span class="p">)</span>
<div class="viewcode-block" id="LogitScale.get_transform"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogitScale.get_transform">[docs]</a> <span class="k">def</span> <span class="nf">get_transform</span><span class="p">(</span><span class="bp">self</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Return a :class:`LogitTransform` instance.</span>
<span class="sd"> """</span>
<span class="k">return</span> <span class="bp">self</span><span class="o">.</span><span class="n">_transform</span></div>
<div class="viewcode-block" id="LogitScale.set_default_locators_and_formatters"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogitScale.set_default_locators_and_formatters">[docs]</a> <span class="k">def</span> <span class="nf">set_default_locators_and_formatters</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">axis</span><span class="p">):</span>
<span class="c1"># ..., 0.01, 0.1, 0.5, 0.9, 0.99, ...</span>
<span class="n">axis</span><span class="o">.</span><span class="n">set_major_locator</span><span class="p">(</span><span class="n">LogitLocator</span><span class="p">())</span>
<span class="n">axis</span><span class="o">.</span><span class="n">set_major_formatter</span><span class="p">(</span><span class="n">LogitFormatter</span><span class="p">())</span>
<span class="n">axis</span><span class="o">.</span><span class="n">set_minor_locator</span><span class="p">(</span><span class="n">LogitLocator</span><span class="p">(</span><span class="n">minor</span><span class="o">=</span><span class="kc">True</span><span class="p">))</span>
<span class="n">axis</span><span class="o">.</span><span class="n">set_minor_formatter</span><span class="p">(</span><span class="n">LogitFormatter</span><span class="p">())</span></div>
<div class="viewcode-block" id="LogitScale.limit_range_for_scale"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.LogitScale.limit_range_for_scale">[docs]</a> <span class="k">def</span> <span class="nf">limit_range_for_scale</span><span class="p">(</span><span class="bp">self</span><span class="p">,</span> <span class="n">vmin</span><span class="p">,</span> <span class="n">vmax</span><span class="p">,</span> <span class="n">minpos</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Limit the domain to values between 0 and 1 (excluded).</span>
<span class="sd"> """</span>
<span class="k">if</span> <span class="ow">not</span> <span class="n">np</span><span class="o">.</span><span class="n">isfinite</span><span class="p">(</span><span class="n">minpos</span><span class="p">):</span>
<span class="n">minpos</span> <span class="o">=</span> <span class="mf">1e-7</span> <span class="c1"># This value should rarely if ever</span>
<span class="c1"># end up with a visible effect.</span>
<span class="k">return</span> <span class="p">(</span><span class="n">minpos</span> <span class="k">if</span> <span class="n">vmin</span> <span class="o"><=</span> <span class="mi">0</span> <span class="k">else</span> <span class="n">vmin</span><span class="p">,</span>
<span class="mi">1</span> <span class="o">-</span> <span class="n">minpos</span> <span class="k">if</span> <span class="n">vmax</span> <span class="o">>=</span> <span class="mi">1</span> <span class="k">else</span> <span class="n">vmax</span><span class="p">)</span></div></div>
<span class="n">_scale_mapping</span> <span class="o">=</span> <span class="p">{</span>
<span class="s1">'linear'</span><span class="p">:</span> <span class="n">LinearScale</span><span class="p">,</span>
<span class="s1">'log'</span><span class="p">:</span> <span class="n">LogScale</span><span class="p">,</span>
<span class="s1">'symlog'</span><span class="p">:</span> <span class="n">SymmetricalLogScale</span><span class="p">,</span>
<span class="s1">'logit'</span><span class="p">:</span> <span class="n">LogitScale</span><span class="p">,</span>
<span class="p">}</span>
<div class="viewcode-block" id="get_scale_names"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.get_scale_names">[docs]</a><span class="k">def</span> <span class="nf">get_scale_names</span><span class="p">():</span>
<span class="k">return</span> <span class="nb">sorted</span><span class="p">(</span><span class="n">_scale_mapping</span><span class="p">)</span></div>
<div class="viewcode-block" id="scale_factory"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.scale_factory">[docs]</a><span class="k">def</span> <span class="nf">scale_factory</span><span class="p">(</span><span class="n">scale</span><span class="p">,</span> <span class="n">axis</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Return a scale class by name.</span>
<span class="sd"> ACCEPTS: [ %(names)s ]</span>
<span class="sd"> """</span>
<span class="n">scale</span> <span class="o">=</span> <span class="n">scale</span><span class="o">.</span><span class="n">lower</span><span class="p">()</span>
<span class="k">if</span> <span class="n">scale</span> <span class="ow">is</span> <span class="kc">None</span><span class="p">:</span>
<span class="n">scale</span> <span class="o">=</span> <span class="s1">'linear'</span>
<span class="k">if</span> <span class="n">scale</span> <span class="ow">not</span> <span class="ow">in</span> <span class="n">_scale_mapping</span><span class="p">:</span>
<span class="k">raise</span> <span class="ne">ValueError</span><span class="p">(</span><span class="s2">"Unknown scale type '</span><span class="si">%s</span><span class="s2">'"</span> <span class="o">%</span> <span class="n">scale</span><span class="p">)</span>
<span class="k">return</span> <span class="n">_scale_mapping</span><span class="p">[</span><span class="n">scale</span><span class="p">](</span><span class="n">axis</span><span class="p">,</span> <span class="o">**</span><span class="n">kwargs</span><span class="p">)</span></div>
<span class="n">scale_factory</span><span class="o">.</span><span class="vm">__doc__</span> <span class="o">=</span> <span class="n">cbook</span><span class="o">.</span><span class="n">dedent</span><span class="p">(</span><span class="n">scale_factory</span><span class="o">.</span><span class="vm">__doc__</span><span class="p">)</span> <span class="o">%</span> \
<span class="p">{</span><span class="s1">'names'</span><span class="p">:</span> <span class="s2">" | "</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">get_scale_names</span><span class="p">())}</span>
<div class="viewcode-block" id="register_scale"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.register_scale">[docs]</a><span class="k">def</span> <span class="nf">register_scale</span><span class="p">(</span><span class="n">scale_class</span><span class="p">):</span>
<span class="sd">"""</span>
<span class="sd"> Register a new kind of scale.</span>
<span class="sd"> *scale_class* must be a subclass of :class:`ScaleBase`.</span>
<span class="sd"> """</span>
<span class="n">_scale_mapping</span><span class="p">[</span><span class="n">scale_class</span><span class="o">.</span><span class="n">name</span><span class="p">]</span> <span class="o">=</span> <span class="n">scale_class</span></div>
<div class="viewcode-block" id="get_scale_docs"><a class="viewcode-back" href="../../api/scale_api.html#matplotlib.scale.get_scale_docs">[docs]</a><span class="k">def</span> <span class="nf">get_scale_docs</span><span class="p">():</span>
<span class="sd">"""</span>
<span class="sd"> Helper function for generating docstrings related to scales.</span>
<span class="sd"> """</span>
<span class="n">docs</span> <span class="o">=</span> <span class="p">[]</span>
<span class="k">for</span> <span class="n">name</span> <span class="ow">in</span> <span class="n">get_scale_names</span><span class="p">():</span>
<span class="n">scale_class</span> <span class="o">=</span> <span class="n">_scale_mapping</span><span class="p">[</span><span class="n">name</span><span class="p">]</span>
<span class="n">docs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s2">" '</span><span class="si">%s</span><span class="s2">'"</span> <span class="o">%</span> <span class="n">name</span><span class="p">)</span>
<span class="n">docs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s2">""</span><span class="p">)</span>
<span class="n">class_docs</span> <span class="o">=</span> <span class="n">cbook</span><span class="o">.</span><span class="n">dedent</span><span class="p">(</span><span class="n">scale_class</span><span class="o">.</span><span class="fm">__init__</span><span class="o">.</span><span class="vm">__doc__</span><span class="p">)</span>
<span class="n">class_docs</span> <span class="o">=</span> <span class="s2">""</span><span class="o">.</span><span class="n">join</span><span class="p">([</span><span class="s2">" </span><span class="si">%s</span><span class="se">\n</span><span class="s2">"</span> <span class="o">%</span>
<span class="n">x</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">class_docs</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s2">"</span><span class="se">\n</span><span class="s2">"</span><span class="p">)])</span>
<span class="n">docs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">class_docs</span><span class="p">)</span>
<span class="n">docs</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="s2">""</span><span class="p">)</span>
<span class="k">return</span> <span class="s2">"</span><span class="se">\n</span><span class="s2">"</span><span class="o">.</span><span class="n">join</span><span class="p">(</span><span class="n">docs</span><span class="p">)</span></div>
<span class="n">docstring</span><span class="o">.</span><span class="n">interpd</span><span class="o">.</span><span class="n">update</span><span class="p">(</span>
<span class="n">scale</span><span class="o">=</span><span class="s1">' | '</span><span class="o">.</span><span class="n">join</span><span class="p">([</span><span class="nb">repr</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="k">for</span> <span class="n">x</span> <span class="ow">in</span> <span class="n">get_scale_names</span><span class="p">()]),</span>
<span class="n">scale_docs</span><span class="o">=</span><span class="n">get_scale_docs</span><span class="p">()</span><span class="o">.</span><span class="n">rstrip</span><span class="p">(),</span>
<span class="p">)</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 28, 2019.
Created using
<ahref="http://sphinx-doc.org/">Sphinx</a> 1.8.4.
Doc version v2.2.4-2-g38a93e9a0-dirty.
</div>
</body>
<footer>
</footer>
</html>
You can’t perform that action at this time.