forked from apachecn/numpy-doc-zh
-
Notifications
You must be signed in to change notification settings - Fork 1
/
routines.ma.html
859 lines (857 loc) · 84.9 KB
/
routines.ma.html
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
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
768
769
770
771
772
773
774
775
776
777
778
779
780
781
782
783
784
785
786
787
788
789
790
791
792
793
794
795
796
797
798
799
800
801
802
803
804
805
806
807
808
809
810
811
812
813
814
815
816
817
818
819
820
821
822
823
824
825
826
827
828
829
830
831
832
833
834
835
836
837
838
839
840
841
842
843
844
845
846
847
848
849
850
851
852
853
854
855
856
857
858
859
<span id="routines-ma"></span><h1><span class="yiyi-st" id="yiyi-43">Masked array operations</span></h1>
<blockquote>
<p>原文：<a href="https://docs.scipy.org/doc/numpy/reference/routines.ma.html">https://docs.scipy.org/doc/numpy/reference/routines.ma.html</a></p>
<p>译者：<a href="https://github.com/wizardforcel">飞龙</a> <a href="http://usyiyi.cn/">UsyiyiCN</a></p>
<p>校对：（虚位以待）</p>
</blockquote>
<div class="section" id="constants">
<h2><span class="yiyi-st" id="yiyi-44">Constants</span></h2>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-45"><a class="reference internal" href="generated/numpy.ma.MaskType.html#numpy.ma.MaskType" title="numpy.ma.MaskType"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskType</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-46"><code class="xref py py-class docutils literal"><span class="pre">bool_</span></code>的别名</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="creation">
<h2><span class="yiyi-st" id="yiyi-47">Creation</span></h2>
<div class="section" id="from-existing-data">
<h3><span class="yiyi-st" id="yiyi-48">From existing data</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-49"><a class="reference internal" href="generated/numpy.ma.masked_array.html#numpy.ma.masked_array" title="numpy.ma.masked_array"><code class="xref py py-obj docutils literal"><span class="pre">ma.masked_array</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-50"><code class="xref py py-class docutils literal"><span class="pre">MaskedArray</span></code>的别名</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-51"><a class="reference internal" href="generated/numpy.ma.array.html#numpy.ma.array" title="numpy.ma.array"><code class="xref py py-obj docutils literal"><span class="pre">ma.array</span></code></a>（data [，dtype，copy，order，mask，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-52">可能带有掩码值的数组类。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-53"><a class="reference internal" href="generated/numpy.ma.copy.html#numpy.ma.copy" title="numpy.ma.copy"><code class="xref py py-obj docutils literal"><span class="pre">ma.copy</span></code></a>（self，\ * args，\ * \ * params）a.copy（order =）</span></td>
<td><span class="yiyi-st" id="yiyi-54">返回数组的副本。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-55"><a class="reference internal" href="generated/numpy.ma.frombuffer.html#numpy.ma.frombuffer" title="numpy.ma.frombuffer"><code class="xref py py-obj docutils literal"><span class="pre">ma.frombuffer</span></code></a>（buffer [，dtype，count，offset]）</span></td>
<td><span class="yiyi-st" id="yiyi-56">将缓冲区解释为1维数组。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-57"><a class="reference internal" href="generated/numpy.ma.fromfunction.html#numpy.ma.fromfunction" title="numpy.ma.fromfunction"><code class="xref py py-obj docutils literal"><span class="pre">ma.fromfunction</span></code></a>（function，shape，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-58">通过在每个坐标上执行函数来构造数组。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-59"><a class="reference internal" href="generated/numpy.ma.MaskedArray.copy.html#numpy.ma.MaskedArray.copy" title="numpy.ma.MaskedArray.copy"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.copy</span></code></a>（[order]）</span></td>
<td><span class="yiyi-st" id="yiyi-60">返回数组的副本。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="ones-and-zeros">
<h3><span class="yiyi-st" id="yiyi-61">Ones and zeros</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-62"><a class="reference internal" href="generated/numpy.ma.empty.html#numpy.ma.empty" title="numpy.ma.empty"><code class="xref py py-obj docutils literal"><span class="pre">ma.empty</span></code></a>（shape [，dtype，order]）</span></td>
<td><span class="yiyi-st" id="yiyi-63">返回给定形状和类型的新数组，而不初始化条目。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-64"><a class="reference internal" href="generated/numpy.ma.empty_like.html#numpy.ma.empty_like" title="numpy.ma.empty_like"><code class="xref py py-obj docutils literal"><span class="pre">ma.empty_like</span></code></a>（a [，dtype，order，subok]）</span></td>
<td><span class="yiyi-st" id="yiyi-65">返回具有与给定数组相同的形状和类型的新数组。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-66"><a class="reference internal" href="generated/numpy.ma.masked_all.html#numpy.ma.masked_all" title="numpy.ma.masked_all"><code class="xref py py-obj docutils literal"><span class="pre">ma.masked_all</span></code></a>（shape [，dtype]）</span></td>
<td><span class="yiyi-st" id="yiyi-67">与被掩没的所有元素的空的被掩没的数组。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-68"><a class="reference internal" href="generated/numpy.ma.masked_all_like.html#numpy.ma.masked_all_like" title="numpy.ma.masked_all_like"><code class="xref py py-obj docutils literal"><span class="pre">ma.masked_all_like</span></code></a>（arr）</span></td>
<td><span class="yiyi-st" id="yiyi-69">使用现有数组的属性空掩码数组。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-70"><a class="reference internal" href="generated/numpy.ma.ones.html#numpy.ma.ones" title="numpy.ma.ones"><code class="xref py py-obj docutils literal"><span class="pre">ma.ones</span></code></a>（shape [，dtype，order]）</span></td>
<td><span class="yiyi-st" id="yiyi-71">返回给定形状和类型的新数组，用数字填充。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-72"><a class="reference internal" href="generated/numpy.ma.zeros.html#numpy.ma.zeros" title="numpy.ma.zeros"><code class="xref py py-obj docutils literal"><span class="pre">ma.zeros</span></code></a>（shape [，dtype，order]）</span></td>
<td><span class="yiyi-st" id="yiyi-73">返回给定形状和类型的新数组，用零填充。</span></td>
</tr>
</tbody>
</table>
</div>
</div>
<hr class="docutils">
<div class="section" id="inspecting-the-array">
<h2><span class="yiyi-st" id="yiyi-74">Inspecting the array</span></h2>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-75"><a class="reference internal" href="generated/numpy.ma.all.html#numpy.ma.all" title="numpy.ma.all"><code class="xref py py-obj docutils literal"><span class="pre">ma.all</span></code></a>（self [，axis，out，keepdims]）</span></td>
<td><span class="yiyi-st" id="yiyi-76">如果所有元素均为True，则返回True。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-77"><a class="reference internal" href="generated/numpy.ma.any.html#numpy.ma.any" title="numpy.ma.any"><code class="xref py py-obj docutils literal"><span class="pre">ma.any</span></code></a>（self [，axis，out，keepdims]）</span></td>
<td><span class="yiyi-st" id="yiyi-78">如果<em class="xref py py-obj">a</em>的任何元素求值为True，则返回True。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-79"><a class="reference internal" href="generated/numpy.ma.count.html#numpy.ma.count" title="numpy.ma.count"><code class="xref py py-obj docutils literal"><span class="pre">ma.count</span></code></a>（self [，axis，keepdims]）</span></td>
<td><span class="yiyi-st" id="yiyi-80">沿给定轴计算数组的非屏蔽元素。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-81"><a class="reference internal" href="generated/numpy.ma.count_masked.html#numpy.ma.count_masked" title="numpy.ma.count_masked"><code class="xref py py-obj docutils literal"><span class="pre">ma.count_masked</span></code></a>（arr [，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-82">计算沿给定轴的蒙版元素的数量。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-83"><a class="reference internal" href="generated/numpy.ma.getmask.html#numpy.ma.getmask" title="numpy.ma.getmask"><code class="xref py py-obj docutils literal"><span class="pre">ma.getmask</span></code></a>（a）</span></td>
<td><span class="yiyi-st" id="yiyi-84">返回掩码数组或掩码的掩码。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-85"><a class="reference internal" href="generated/numpy.ma.getmaskarray.html#numpy.ma.getmaskarray" title="numpy.ma.getmaskarray"><code class="xref py py-obj docutils literal"><span class="pre">ma.getmaskarray</span></code></a>（arr）</span></td>
<td><span class="yiyi-st" id="yiyi-86">返回掩码数组的掩码，或者返回False的完全布尔数组。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-87"><a class="reference internal" href="generated/numpy.ma.getdata.html#numpy.ma.getdata" title="numpy.ma.getdata"><code class="xref py py-obj docutils literal"><span class="pre">ma.getdata</span></code></a>（a [，subok]）</span></td>
<td><span class="yiyi-st" id="yiyi-88">将掩码数组的数据作为ndarray返回。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-89"><a class="reference internal" href="generated/numpy.ma.nonzero.html#numpy.ma.nonzero" title="numpy.ma.nonzero"><code class="xref py py-obj docutils literal"><span class="pre">ma.nonzero</span></code></a>（self）</span></td>
<td><span class="yiyi-st" id="yiyi-90">返回非零的未屏蔽元素的索引。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-91"><a class="reference internal" href="generated/numpy.ma.shape.html#numpy.ma.shape" title="numpy.ma.shape"><code class="xref py py-obj docutils literal"><span class="pre">ma.shape</span></code></a>（obj）</span></td>
<td><span class="yiyi-st" id="yiyi-92">返回数组的形状。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-93"><a class="reference internal" href="generated/numpy.ma.size.html#numpy.ma.size" title="numpy.ma.size"><code class="xref py py-obj docutils literal"><span class="pre">ma.size</span></code></a>（obj [，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-94">返回给定轴上的元素数。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-95"><a class="reference internal" href="generated/numpy.ma.is_masked.html#numpy.ma.is_masked" title="numpy.ma.is_masked"><code class="xref py py-obj docutils literal"><span class="pre">ma.is_masked</span></code></a>（x）</span></td>
<td><span class="yiyi-st" id="yiyi-96">确定输入是否具有屏蔽值。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-97"><a class="reference internal" href="generated/numpy.ma.is_mask.html#numpy.ma.is_mask" title="numpy.ma.is_mask"><code class="xref py py-obj docutils literal"><span class="pre">ma.is_mask</span></code></a>（m）</span></td>
<td><span class="yiyi-st" id="yiyi-98">如果m是有效的标准掩码，则返回True。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-99"><a class="reference internal" href="maskedarray.baseclass.html#numpy.ma.MaskedArray.data" title="numpy.ma.MaskedArray.data"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.data</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-100">返回当前数据，作为原始基础数据的视图。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-101"><a class="reference internal" href="maskedarray.baseclass.html#numpy.ma.MaskedArray.mask" title="numpy.ma.MaskedArray.mask"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.mask</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-102">面具</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-103"><a class="reference internal" href="maskedarray.baseclass.html#numpy.ma.MaskedArray.recordmask" title="numpy.ma.MaskedArray.recordmask"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.recordmask</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-104">返回记录的掩码。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-105"><a class="reference internal" href="generated/numpy.ma.MaskedArray.all.html#numpy.ma.MaskedArray.all" title="numpy.ma.MaskedArray.all"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.all</span></code></a>（[axis，out，keepdims]）</span></td>
<td><span class="yiyi-st" id="yiyi-106">如果所有元素均为True，则返回True。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-107"><a class="reference internal" href="generated/numpy.ma.MaskedArray.any.html#numpy.ma.MaskedArray.any" title="numpy.ma.MaskedArray.any"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.any</span></code></a>（[axis，out，keepdims]）</span></td>
<td><span class="yiyi-st" id="yiyi-108">如果<em class="xref py py-obj">a</em>的任何元素求值为True，则返回True。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-109"><a class="reference internal" href="generated/numpy.ma.MaskedArray.count.html#numpy.ma.MaskedArray.count" title="numpy.ma.MaskedArray.count"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.count</span></code></a>（[axis，keepdims]）</span></td>
<td><span class="yiyi-st" id="yiyi-110">沿给定轴计算数组的非屏蔽元素。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-111"><a class="reference internal" href="generated/numpy.ma.MaskedArray.nonzero.html#numpy.ma.MaskedArray.nonzero" title="numpy.ma.MaskedArray.nonzero"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.nonzero</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-112">返回非零的未屏蔽元素的索引。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-113"><a class="reference internal" href="generated/numpy.ma.shape.html#numpy.ma.shape" title="numpy.ma.shape"><code class="xref py py-obj docutils literal"><span class="pre">ma.shape</span></code></a>（obj）</span></td>
<td><span class="yiyi-st" id="yiyi-114">返回数组的形状。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-115"><a class="reference internal" href="generated/numpy.ma.size.html#numpy.ma.size" title="numpy.ma.size"><code class="xref py py-obj docutils literal"><span class="pre">ma.size</span></code></a>（obj [，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-116">返回给定轴上的元素数。</span></td>
</tr>
</tbody>
</table>
</div>
<hr class="docutils">
<div class="section" id="manipulating-a-maskedarray">
<h2><span class="yiyi-st" id="yiyi-117">Manipulating a MaskedArray</span></h2>
<div class="section" id="changing-the-shape">
<h3><span class="yiyi-st" id="yiyi-118">Changing the shape</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-119"><a class="reference internal" href="generated/numpy.ma.ravel.html#numpy.ma.ravel" title="numpy.ma.ravel"><code class="xref py py-obj docutils literal"><span class="pre">ma.ravel</span></code></a>（self [，order]）</span></td>
<td><span class="yiyi-st" id="yiyi-120">作为视图返回self的1D版本。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-121"><a class="reference internal" href="generated/numpy.ma.reshape.html#numpy.ma.reshape" title="numpy.ma.reshape"><code class="xref py py-obj docutils literal"><span class="pre">ma.reshape</span></code></a>（a，new_shape [，order]）</span></td>
<td><span class="yiyi-st" id="yiyi-122">返回包含具有新形状的相同数据的数组。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-123"><a class="reference internal" href="generated/numpy.ma.resize.html#numpy.ma.resize" title="numpy.ma.resize"><code class="xref py py-obj docutils literal"><span class="pre">ma.resize</span></code></a>（x，new_shape）</span></td>
<td><span class="yiyi-st" id="yiyi-124">返回具有指定大小和形状的新的蒙版数组。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-125"><a class="reference internal" href="generated/numpy.ma.MaskedArray.flatten.html#numpy.ma.MaskedArray.flatten" title="numpy.ma.MaskedArray.flatten"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.flatten</span></code></a>（[order]）</span></td>
<td><span class="yiyi-st" id="yiyi-126">将折叠的数组的副本返回到一个维度。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-127"><a class="reference internal" href="generated/numpy.ma.MaskedArray.ravel.html#numpy.ma.MaskedArray.ravel" title="numpy.ma.MaskedArray.ravel"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.ravel</span></code></a>（[order]）</span></td>
<td><span class="yiyi-st" id="yiyi-128">作为视图返回self的1D版本。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-129"><a class="reference internal" href="generated/numpy.ma.MaskedArray.reshape.html#numpy.ma.MaskedArray.reshape" title="numpy.ma.MaskedArray.reshape"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.reshape</span></code></a>（\ * s，\ * \ * kwargs）</span></td>
<td><span class="yiyi-st" id="yiyi-130">为数组提供新形状，而不更改其数据。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-131"><a class="reference internal" href="generated/numpy.ma.MaskedArray.resize.html#numpy.ma.MaskedArray.resize" title="numpy.ma.MaskedArray.resize"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.resize</span></code></a>（newshape [，refcheck，...]）</span></td>
<td></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="modifying-axes">
<h3><span class="yiyi-st" id="yiyi-132">Modifying axes</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-133"><a class="reference internal" href="generated/numpy.ma.swapaxes.html#numpy.ma.swapaxes" title="numpy.ma.swapaxes"><code class="xref py py-obj docutils literal"><span class="pre">ma.swapaxes</span></code></a>（self，\ * args，...）</span></td>
<td><span class="yiyi-st" id="yiyi-134">返回数组的视图，其中<em class="xref py py-obj">axis1</em>和<em class="xref py py-obj">axis2</em>互换。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-135"><a class="reference internal" href="generated/numpy.ma.transpose.html#numpy.ma.transpose" title="numpy.ma.transpose"><code class="xref py py-obj docutils literal"><span class="pre">ma.transpose</span></code></a>（a [，axes]）</span></td>
<td><span class="yiyi-st" id="yiyi-136">允许数组的尺寸。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-137"><a class="reference internal" href="generated/numpy.ma.MaskedArray.swapaxes.html#numpy.ma.MaskedArray.swapaxes" title="numpy.ma.MaskedArray.swapaxes"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.swapaxes</span></code></a>（axis1，axis2）</span></td>
<td><span class="yiyi-st" id="yiyi-138">返回数组的视图，其中<em class="xref py py-obj">axis1</em>和<em class="xref py py-obj">axis2</em>互换。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-139"><a class="reference internal" href="generated/numpy.ma.MaskedArray.transpose.html#numpy.ma.MaskedArray.transpose" title="numpy.ma.MaskedArray.transpose"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.transpose</span></code></a>（\ * axes）</span></td>
<td><span class="yiyi-st" id="yiyi-140">返回具有轴转置的数组的视图。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="changing-the-number-of-dimensions">
<h3><span class="yiyi-st" id="yiyi-141">Changing the number of dimensions</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-142"><a class="reference internal" href="generated/numpy.ma.atleast_1d.html#numpy.ma.atleast_1d" title="numpy.ma.atleast_1d"><code class="xref py py-obj docutils literal"><span class="pre">ma.atleast_1d</span></code></a>（\ * arys）</span></td>
<td><span class="yiyi-st" id="yiyi-143">将输入转换为具有至少一个维度的数组。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-144"><a class="reference internal" href="generated/numpy.ma.atleast_2d.html#numpy.ma.atleast_2d" title="numpy.ma.atleast_2d"><code class="xref py py-obj docutils literal"><span class="pre">ma.atleast_2d</span></code></a>（\ * arys）</span></td>
<td><span class="yiyi-st" id="yiyi-145">将输入视为具有至少两个维度的数组。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-146"><a class="reference internal" href="generated/numpy.ma.atleast_3d.html#numpy.ma.atleast_3d" title="numpy.ma.atleast_3d"><code class="xref py py-obj docutils literal"><span class="pre">ma.atleast_3d</span></code></a>（\ * arys）</span></td>
<td><span class="yiyi-st" id="yiyi-147">将输入视为至少包含三个维度的数组。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-148"><a class="reference internal" href="generated/numpy.ma.expand_dims.html#numpy.ma.expand_dims" title="numpy.ma.expand_dims"><code class="xref py py-obj docutils literal"><span class="pre">ma.expand_dims</span></code></a>（x，axis）</span></td>
<td><span class="yiyi-st" id="yiyi-149">展开数组的形状。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-150"><a class="reference internal" href="generated/numpy.ma.squeeze.html#numpy.ma.squeeze" title="numpy.ma.squeeze"><code class="xref py py-obj docutils literal"><span class="pre">ma.squeeze</span></code></a>（a [，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-151">从数组的形状中删除单维条目。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-152"><a class="reference internal" href="generated/numpy.ma.MaskedArray.squeeze.html#numpy.ma.MaskedArray.squeeze" title="numpy.ma.MaskedArray.squeeze"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.squeeze</span></code></a>（[axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-153">从<em class="xref py py-obj">a形状删除单维条目</em>。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-154"><a class="reference internal" href="generated/numpy.ma.column_stack.html#numpy.ma.column_stack" title="numpy.ma.column_stack"><code class="xref py py-obj docutils literal"><span class="pre">ma.column_stack</span></code></a>（tup）</span></td>
<td><span class="yiyi-st" id="yiyi-155">将1-D数组作为列堆叠到2-D数组中。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-156"><a class="reference internal" href="generated/numpy.ma.concatenate.html#numpy.ma.concatenate" title="numpy.ma.concatenate"><code class="xref py py-obj docutils literal"><span class="pre">ma.concatenate</span></code></a>（arrays [，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-157">沿给定轴连接数组的序列。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-158"><a class="reference internal" href="generated/numpy.ma.dstack.html#numpy.ma.dstack" title="numpy.ma.dstack"><code class="xref py py-obj docutils literal"><span class="pre">ma.dstack</span></code></a>（tup）</span></td>
<td><span class="yiyi-st" id="yiyi-159">按照深度顺序（沿第三轴）堆叠数组。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-160"><a class="reference internal" href="generated/numpy.ma.hstack.html#numpy.ma.hstack" title="numpy.ma.hstack"><code class="xref py py-obj docutils literal"><span class="pre">ma.hstack</span></code></a>（tup）</span></td>
<td><span class="yiyi-st" id="yiyi-161">水平（按列顺序）堆叠数组。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-162"><a class="reference internal" href="generated/numpy.ma.hsplit.html#numpy.ma.hsplit" title="numpy.ma.hsplit"><code class="xref py py-obj docutils literal"><span class="pre">ma.hsplit</span></code></a>（ary，indices_or_sections）</span></td>
<td><span class="yiyi-st" id="yiyi-163">将数组水平（逐列）拆分为多个子数组。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-164"><a class="reference internal" href="generated/numpy.ma.mr_.html#numpy.ma.mr_" title="numpy.ma.mr_"><code class="xref py py-obj docutils literal"><span class="pre">ma.mr_</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-165">将切片对象转换为沿第一轴的连接。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-166"><a class="reference internal" href="generated/numpy.ma.row_stack.html#numpy.ma.row_stack" title="numpy.ma.row_stack"><code class="xref py py-obj docutils literal"><span class="pre">ma.row_stack</span></code></a>（tup）</span></td>
<td><span class="yiyi-st" id="yiyi-167">垂直（按行）顺序堆叠数组。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-168"><a class="reference internal" href="generated/numpy.ma.vstack.html#numpy.ma.vstack" title="numpy.ma.vstack"><code class="xref py py-obj docutils literal"><span class="pre">ma.vstack</span></code></a>（tup）</span></td>
<td><span class="yiyi-st" id="yiyi-169">垂直（按行）顺序堆叠数组。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="joining-arrays">
<h3><span class="yiyi-st" id="yiyi-170">Joining arrays</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-171"><a class="reference internal" href="generated/numpy.ma.column_stack.html#numpy.ma.column_stack" title="numpy.ma.column_stack"><code class="xref py py-obj docutils literal"><span class="pre">ma.column_stack</span></code></a>（tup）</span></td>
<td><span class="yiyi-st" id="yiyi-172">将1-D数组作为列堆叠到2-D数组中。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-173"><a class="reference internal" href="generated/numpy.ma.concatenate.html#numpy.ma.concatenate" title="numpy.ma.concatenate"><code class="xref py py-obj docutils literal"><span class="pre">ma.concatenate</span></code></a>（arrays [，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-174">沿给定轴连接数组的序列。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-175"><a class="reference internal" href="generated/numpy.ma.append.html#numpy.ma.append" title="numpy.ma.append"><code class="xref py py-obj docutils literal"><span class="pre">ma.append</span></code></a>（a，b [，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-176">将值附加到数组的末尾。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-177"><a class="reference internal" href="generated/numpy.ma.dstack.html#numpy.ma.dstack" title="numpy.ma.dstack"><code class="xref py py-obj docutils literal"><span class="pre">ma.dstack</span></code></a>（tup）</span></td>
<td><span class="yiyi-st" id="yiyi-178">按照深度顺序（沿第三轴）堆叠数组。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-179"><a class="reference internal" href="generated/numpy.ma.hstack.html#numpy.ma.hstack" title="numpy.ma.hstack"><code class="xref py py-obj docutils literal"><span class="pre">ma.hstack</span></code></a>（tup）</span></td>
<td><span class="yiyi-st" id="yiyi-180">水平（按列顺序）堆叠数组。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-181"><a class="reference internal" href="generated/numpy.ma.vstack.html#numpy.ma.vstack" title="numpy.ma.vstack"><code class="xref py py-obj docutils literal"><span class="pre">ma.vstack</span></code></a>（tup）</span></td>
<td><span class="yiyi-st" id="yiyi-182">垂直（按行）顺序堆叠数组。</span></td>
</tr>
</tbody>
</table>
</div>
</div>
<hr class="docutils">
<div class="section" id="operations-on-masks">
<h2><span class="yiyi-st" id="yiyi-183">Operations on masks</span></h2>
<div class="section" id="creating-a-mask">
<h3><span class="yiyi-st" id="yiyi-184">Creating a mask</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-185"><a class="reference internal" href="generated/numpy.ma.make_mask.html#numpy.ma.make_mask" title="numpy.ma.make_mask"><code class="xref py py-obj docutils literal"><span class="pre">ma.make_mask</span></code></a>（m [，copy，shrink，dtype]）</span></td>
<td><span class="yiyi-st" id="yiyi-186">从数组中创建一个布尔掩码。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-187"><a class="reference internal" href="generated/numpy.ma.make_mask_none.html#numpy.ma.make_mask_none" title="numpy.ma.make_mask_none"><code class="xref py py-obj docutils literal"><span class="pre">ma.make_mask_none</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-188">返回给定形状的布尔掩码，填充False。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-189"><a class="reference internal" href="generated/numpy.ma.mask_or.html#numpy.ma.mask_or" title="numpy.ma.mask_or"><code class="xref py py-obj docutils literal"><span class="pre">ma.mask_or</span></code></a>（m1，m2 [，copy，shrink]）</span></td>
<td><span class="yiyi-st" id="yiyi-190">使用<code class="docutils literal"><span class="pre">logical_or</span></code>运算符组合两个掩码。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-191"><a class="reference internal" href="generated/numpy.ma.make_mask_descr.html#numpy.ma.make_mask_descr" title="numpy.ma.make_mask_descr"><code class="xref py py-obj docutils literal"><span class="pre">ma.make_mask_descr</span></code></a>（ndtype）</span></td>
<td><span class="yiyi-st" id="yiyi-192">从给定的dtype构造dtype描述列表。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="accessing-a-mask">
<h3><span class="yiyi-st" id="yiyi-193">Accessing a mask</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-194"><a class="reference internal" href="generated/numpy.ma.getmask.html#numpy.ma.getmask" title="numpy.ma.getmask"><code class="xref py py-obj docutils literal"><span class="pre">ma.getmask</span></code></a>（a）</span></td>
<td><span class="yiyi-st" id="yiyi-195">返回掩码数组或掩码的掩码。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-196"><a class="reference internal" href="generated/numpy.ma.getmaskarray.html#numpy.ma.getmaskarray" title="numpy.ma.getmaskarray"><code class="xref py py-obj docutils literal"><span class="pre">ma.getmaskarray</span></code></a>（arr）</span></td>
<td><span class="yiyi-st" id="yiyi-197">返回掩码数组的掩码，或者返回False的完全布尔数组。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-198"><a class="reference internal" href="generated/numpy.ma.masked_array.mask.html#numpy.ma.masked_array.mask" title="numpy.ma.masked_array.mask"><code class="xref py py-obj docutils literal"><span class="pre">ma.masked_array.mask</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-199">面具</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="finding-masked-data">
<h3><span class="yiyi-st" id="yiyi-200">Finding masked data</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-201"><a class="reference internal" href="generated/numpy.ma.flatnotmasked_contiguous.html#numpy.ma.flatnotmasked_contiguous" title="numpy.ma.flatnotmasked_contiguous"><code class="xref py py-obj docutils literal"><span class="pre">ma.flatnotmasked_contiguous</span></code></a>（a）</span></td>
<td><span class="yiyi-st" id="yiyi-202">沿给定轴在屏蔽数组中找到连续的未屏蔽数据。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-203"><a class="reference internal" href="generated/numpy.ma.flatnotmasked_edges.html#numpy.ma.flatnotmasked_edges" title="numpy.ma.flatnotmasked_edges"><code class="xref py py-obj docutils literal"><span class="pre">ma.flatnotmasked_edges</span></code></a>（a）</span></td>
<td><span class="yiyi-st" id="yiyi-204">查找第一个和最后一个未屏蔽值的索引。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-205"><a class="reference internal" href="generated/numpy.ma.notmasked_contiguous.html#numpy.ma.notmasked_contiguous" title="numpy.ma.notmasked_contiguous"><code class="xref py py-obj docutils literal"><span class="pre">ma.notmasked_contiguous</span></code></a>（a [，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-206">沿给定轴在屏蔽数组中找到连续的未屏蔽数据。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-207"><a class="reference internal" href="generated/numpy.ma.notmasked_edges.html#numpy.ma.notmasked_edges" title="numpy.ma.notmasked_edges"><code class="xref py py-obj docutils literal"><span class="pre">ma.notmasked_edges</span></code></a>（a [，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-208">找到沿轴的第一个和最后一个未屏蔽值的索引。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-209"><a class="reference internal" href="generated/numpy.ma.clump_masked.html#numpy.ma.clump_masked" title="numpy.ma.clump_masked"><code class="xref py py-obj docutils literal"><span class="pre">ma.clump_masked</span></code></a>（a）</span></td>
<td><span class="yiyi-st" id="yiyi-210">返回与1-D数组的蒙版簇对应的切片列表。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-211"><a class="reference internal" href="generated/numpy.ma.clump_unmasked.html#numpy.ma.clump_unmasked" title="numpy.ma.clump_unmasked"><code class="xref py py-obj docutils literal"><span class="pre">ma.clump_unmasked</span></code></a>（a）</span></td>
<td><span class="yiyi-st" id="yiyi-212">返回与1-D数组的未屏蔽块相对应的切片的列表。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="modifying-a-mask">
<h3><span class="yiyi-st" id="yiyi-213">Modifying a mask</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-214"><a class="reference internal" href="generated/numpy.ma.mask_cols.html#numpy.ma.mask_cols" title="numpy.ma.mask_cols"><code class="xref py py-obj docutils literal"><span class="pre">ma.mask_cols</span></code></a>（a [，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-215">屏蔽包含屏蔽值的2D数组的列。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-216"><a class="reference internal" href="generated/numpy.ma.mask_or.html#numpy.ma.mask_or" title="numpy.ma.mask_or"><code class="xref py py-obj docutils literal"><span class="pre">ma.mask_or</span></code></a>（m1，m2 [，copy，shrink]）</span></td>
<td><span class="yiyi-st" id="yiyi-217">使用<code class="docutils literal"><span class="pre">logical_or</span></code>运算符组合两个掩码。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-218"><a class="reference internal" href="generated/numpy.ma.mask_rowcols.html#numpy.ma.mask_rowcols" title="numpy.ma.mask_rowcols"><code class="xref py py-obj docutils literal"><span class="pre">ma.mask_rowcols</span></code></a>（a [，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-219">屏蔽包含屏蔽值的2D数组的行和/或列。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-220"><a class="reference internal" href="generated/numpy.ma.mask_rows.html#numpy.ma.mask_rows" title="numpy.ma.mask_rows"><code class="xref py py-obj docutils literal"><span class="pre">ma.mask_rows</span></code></a>（a [，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-221">屏蔽包含屏蔽值的2D数组的行。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-222"><a class="reference internal" href="generated/numpy.ma.harden_mask.html#numpy.ma.harden_mask" title="numpy.ma.harden_mask"><code class="xref py py-obj docutils literal"><span class="pre">ma.harden_mask</span></code></a>（self）</span></td>
<td><span class="yiyi-st" id="yiyi-223">强迫面罩硬。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-224"><a class="reference internal" href="generated/numpy.ma.soften_mask.html#numpy.ma.soften_mask" title="numpy.ma.soften_mask"><code class="xref py py-obj docutils literal"><span class="pre">ma.soften_mask</span></code></a>（self）</span></td>
<td><span class="yiyi-st" id="yiyi-225">强迫面罩柔软。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-226"><a class="reference internal" href="generated/numpy.ma.MaskedArray.harden_mask.html#numpy.ma.MaskedArray.harden_mask" title="numpy.ma.MaskedArray.harden_mask"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.harden_mask</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-227">强迫面具硬。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-228"><a class="reference internal" href="generated/numpy.ma.MaskedArray.soften_mask.html#numpy.ma.MaskedArray.soften_mask" title="numpy.ma.MaskedArray.soften_mask"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.soften_mask</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-229">强迫面罩柔软。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-230"><a class="reference internal" href="generated/numpy.ma.MaskedArray.shrink_mask.html#numpy.ma.MaskedArray.shrink_mask" title="numpy.ma.MaskedArray.shrink_mask"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.shrink_mask</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-231">如果可能，减少掩码到nomask。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-232"><a class="reference internal" href="generated/numpy.ma.MaskedArray.unshare_mask.html#numpy.ma.MaskedArray.unshare_mask" title="numpy.ma.MaskedArray.unshare_mask"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.unshare_mask</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-233">复制掩码并将sharedmask标志设置为False。</span></td>
</tr>
</tbody>
</table>
</div>
</div>
<hr class="docutils">
<div class="section" id="conversion-operations">
<h2><span class="yiyi-st" id="yiyi-234">Conversion operations</span></h2>
<div class="section" id="to-a-masked-array">
<h3><span class="yiyi-st" id="yiyi-235">> to a masked array</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-236"><a class="reference internal" href="generated/numpy.ma.asarray.html#numpy.ma.asarray" title="numpy.ma.asarray"><code class="xref py py-obj docutils literal"><span class="pre">ma.asarray</span></code></a>（a [，dtype，order]）</span></td>
<td><span class="yiyi-st" id="yiyi-237">将输入转换为给定数据类型的屏蔽数组。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-238"><a class="reference internal" href="generated/numpy.ma.asanyarray.html#numpy.ma.asanyarray" title="numpy.ma.asanyarray"><code class="xref py py-obj docutils literal"><span class="pre">ma.asanyarray</span></code></a>（a [，dtype]）</span></td>
<td><span class="yiyi-st" id="yiyi-239">将输入转换为屏蔽的数组，保留子类。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-240"><a class="reference internal" href="generated/numpy.ma.fix_invalid.html#numpy.ma.fix_invalid" title="numpy.ma.fix_invalid"><code class="xref py py-obj docutils literal"><span class="pre">ma.fix_invalid</span></code></a>（a [，mask，copy，fill_value]）</span></td>
<td><span class="yiyi-st" id="yiyi-241">返回带有无效数据的输入，并用填充值替换。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-242"><a class="reference internal" href="generated/numpy.ma.masked_equal.html#numpy.ma.masked_equal" title="numpy.ma.masked_equal"><code class="xref py py-obj docutils literal"><span class="pre">ma.masked_equal</span></code></a>（x，value [，copy]）</span></td>
<td><span class="yiyi-st" id="yiyi-243">屏蔽等于给定值的数组。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-244"><a class="reference internal" href="generated/numpy.ma.masked_greater.html#numpy.ma.masked_greater" title="numpy.ma.masked_greater"><code class="xref py py-obj docutils literal"><span class="pre">ma.masked_greater</span></code></a>（x，value [，copy]）</span></td>
<td><span class="yiyi-st" id="yiyi-245">屏蔽大于给定值的数组。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-246"><a class="reference internal" href="generated/numpy.ma.masked_greater_equal.html#numpy.ma.masked_greater_equal" title="numpy.ma.masked_greater_equal"><code class="xref py py-obj docutils literal"><span class="pre">ma.masked_greater_equal</span></code></a>（x，value [，copy]）</span></td>
<td><span class="yiyi-st" id="yiyi-247">屏蔽大于或等于给定值的数组。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-248"><a class="reference internal" href="generated/numpy.ma.masked_inside.html#numpy.ma.masked_inside" title="numpy.ma.masked_inside"><code class="xref py py-obj docutils literal"><span class="pre">ma.masked_inside</span></code></a>（x，v1，v2 [，copy]）</span></td>
<td><span class="yiyi-st" id="yiyi-249">屏蔽给定间隔内的数组。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-250"><a class="reference internal" href="generated/numpy.ma.masked_invalid.html#numpy.ma.masked_invalid" title="numpy.ma.masked_invalid"><code class="xref py py-obj docutils literal"><span class="pre">ma.masked_invalid</span></code></a>（a [，copy]）</span></td>
<td><span class="yiyi-st" id="yiyi-251">屏蔽发生无效值的数组（NaN或inf）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-252"><a class="reference internal" href="generated/numpy.ma.masked_less.html#numpy.ma.masked_less" title="numpy.ma.masked_less"><code class="xref py py-obj docutils literal"><span class="pre">ma.masked_less</span></code></a>（x，value [，copy]）</span></td>
<td><span class="yiyi-st" id="yiyi-253">屏蔽小于给定值的数组。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-254"><a class="reference internal" href="generated/numpy.ma.masked_less_equal.html#numpy.ma.masked_less_equal" title="numpy.ma.masked_less_equal"><code class="xref py py-obj docutils literal"><span class="pre">ma.masked_less_equal</span></code></a>（x，value [，copy]）</span></td>
<td><span class="yiyi-st" id="yiyi-255">屏蔽小于或等于给定值的数组。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-256"><a class="reference internal" href="generated/numpy.ma.masked_not_equal.html#numpy.ma.masked_not_equal" title="numpy.ma.masked_not_equal"><code class="xref py py-obj docutils literal"><span class="pre">ma.masked_not_equal</span></code></a>（x，value [，copy]）</span></td>
<td><span class="yiyi-st" id="yiyi-257">屏蔽数组，其中<em class="xref py py-obj">不</em>等于给定值。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-258"><a class="reference internal" href="generated/numpy.ma.masked_object.html#numpy.ma.masked_object" title="numpy.ma.masked_object"><code class="xref py py-obj docutils literal"><span class="pre">ma.masked_object</span></code></a>（x，value [，copy，shrink]）</span></td>
<td><span class="yiyi-st" id="yiyi-259">屏蔽数组<em class="xref py py-obj">x</em>，其中数据与值完全相等。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-260"><a class="reference internal" href="generated/numpy.ma.masked_outside.html#numpy.ma.masked_outside" title="numpy.ma.masked_outside"><code class="xref py py-obj docutils literal"><span class="pre">ma.masked_outside</span></code></a>（x，v1，v2 [，copy]）</span></td>
<td><span class="yiyi-st" id="yiyi-261">在给定间隔之外屏蔽数组。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-262"><a class="reference internal" href="generated/numpy.ma.masked_values.html#numpy.ma.masked_values" title="numpy.ma.masked_values"><code class="xref py py-obj docutils literal"><span class="pre">ma.masked_values</span></code></a>（x，value [，rtol，atol，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-263">使用浮点平等的掩码。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-264"><a class="reference internal" href="generated/numpy.ma.masked_where.html#numpy.ma.masked_where" title="numpy.ma.masked_where"><code class="xref py py-obj docutils literal"><span class="pre">ma.masked_where</span></code></a>（condition，a [，copy]）</span></td>
<td><span class="yiyi-st" id="yiyi-265">屏蔽满足条件的数组。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="to-a-ndarray">
<h3><span class="yiyi-st" id="yiyi-266">> to a ndarray</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-267"><a class="reference internal" href="generated/numpy.ma.compress_cols.html#numpy.ma.compress_cols" title="numpy.ma.compress_cols"><code class="xref py py-obj docutils literal"><span class="pre">ma.compress_cols</span></code></a>（a）</span></td>
<td><span class="yiyi-st" id="yiyi-268">抑制包含屏蔽值的2-D数组的整列。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-269"><a class="reference internal" href="generated/numpy.ma.compress_rowcols.html#numpy.ma.compress_rowcols" title="numpy.ma.compress_rowcols"><code class="xref py py-obj docutils literal"><span class="pre">ma.compress_rowcols</span></code></a>（x [，axis]）</span></td>
<td><span class="yiyi-st" id="yiyi-270">抑制包含屏蔽值的2-D数组的行和/或列。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-271"><a class="reference internal" href="generated/numpy.ma.compress_rows.html#numpy.ma.compress_rows" title="numpy.ma.compress_rows"><code class="xref py py-obj docutils literal"><span class="pre">ma.compress_rows</span></code></a>（a）</span></td>
<td><span class="yiyi-st" id="yiyi-272">抑制包含屏蔽值的2-D数组的所有行。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-273"><a class="reference internal" href="generated/numpy.ma.compressed.html#numpy.ma.compressed" title="numpy.ma.compressed"><code class="xref py py-obj docutils literal"><span class="pre">ma.compressed</span></code></a>（x）</span></td>
<td><span class="yiyi-st" id="yiyi-274">将所有非屏蔽数据作为1-D数组。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-275"><a class="reference internal" href="generated/numpy.ma.filled.html#numpy.ma.filled" title="numpy.ma.filled"><code class="xref py py-obj docutils literal"><span class="pre">ma.filled</span></code></a>（a [，fill_value]）</span></td>
<td><span class="yiyi-st" id="yiyi-276">将输入作为数组，将掩码数据替换为填充值。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-277"><a class="reference internal" href="generated/numpy.ma.MaskedArray.compressed.html#numpy.ma.MaskedArray.compressed" title="numpy.ma.MaskedArray.compressed"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.compressed</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-278">将所有非屏蔽数据作为1-D数组。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-279"><a class="reference internal" href="generated/numpy.ma.MaskedArray.filled.html#numpy.ma.MaskedArray.filled" title="numpy.ma.MaskedArray.filled"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.filled</span></code></a>（[fill_value]）</span></td>
<td><span class="yiyi-st" id="yiyi-280">返回self的副本，掩码值填充给定值。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="to-another-object">
<h3><span class="yiyi-st" id="yiyi-281">> to another object</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-282"><a class="reference internal" href="generated/numpy.ma.MaskedArray.tofile.html#numpy.ma.MaskedArray.tofile" title="numpy.ma.MaskedArray.tofile"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.tofile</span></code></a>（fid [，sep，format]）</span></td>
<td><span class="yiyi-st" id="yiyi-283">以二进制格式将掩码数组保存到文件。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-284"><a class="reference internal" href="generated/numpy.ma.MaskedArray.tolist.html#numpy.ma.MaskedArray.tolist" title="numpy.ma.MaskedArray.tolist"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.tolist</span></code></a>（[fill_value]）</span></td>
<td><span class="yiyi-st" id="yiyi-285">将掩码数组的数据部分作为分层Python列表返回。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-286"><a class="reference internal" href="generated/numpy.ma.MaskedArray.torecords.html#numpy.ma.MaskedArray.torecords" title="numpy.ma.MaskedArray.torecords"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.torecords</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-287">将隐藏的数组转换为灵活类型的数组。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-288"><a class="reference internal" href="generated/numpy.ma.MaskedArray.tobytes.html#numpy.ma.MaskedArray.tobytes" title="numpy.ma.MaskedArray.tobytes"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.tobytes</span></code></a>（[fill_value，order]）</span></td>
<td><span class="yiyi-st" id="yiyi-289">将数组数据作为包含数组中原始字节的字符串返回。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="pickling-and-unpickling">
<h3><span class="yiyi-st" id="yiyi-290">Pickling and unpickling</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-291"><a class="reference internal" href="generated/numpy.ma.dump.html#numpy.ma.dump" title="numpy.ma.dump"><code class="xref py py-obj docutils literal"><span class="pre">ma.dump</span></code></a>（a，F）</span></td>
<td><span class="yiyi-st" id="yiyi-292">选择一个蒙版的数组到文件。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-293"><a class="reference internal" href="generated/numpy.ma.dumps.html#numpy.ma.dumps" title="numpy.ma.dumps"><code class="xref py py-obj docutils literal"><span class="pre">ma.dumps</span></code></a>（a）</span></td>
<td><span class="yiyi-st" id="yiyi-294">返回一个对应于掩蔽数组的pickling的字符串。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-295"><a class="reference internal" href="generated/numpy.ma.load.html#numpy.ma.load" title="numpy.ma.load"><code class="xref py py-obj docutils literal"><span class="pre">ma.load</span></code></a>（F）</span></td>
<td><span class="yiyi-st" id="yiyi-296">封装在<code class="docutils literal"><span class="pre">cPickle.load</span></code>周围，它接受类似文件的对象或文件名。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-297"><a class="reference internal" href="generated/numpy.ma.loads.html#numpy.ma.loads" title="numpy.ma.loads"><code class="xref py py-obj docutils literal"><span class="pre">ma.loads</span></code></a>（strg）</span></td>
<td><span class="yiyi-st" id="yiyi-298">从当前字符串加载pickle。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="filling-a-masked-array">
<h3><span class="yiyi-st" id="yiyi-299">Filling a masked array</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-300"><a class="reference internal" href="generated/numpy.ma.common_fill_value.html#numpy.ma.common_fill_value" title="numpy.ma.common_fill_value"><code class="xref py py-obj docutils literal"><span class="pre">ma.common_fill_value</span></code></a>（a，b）</span></td>
<td><span class="yiyi-st" id="yiyi-301">返回两个屏蔽数组的公共填充值（如果有）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-302"><a class="reference internal" href="generated/numpy.ma.default_fill_value.html#numpy.ma.default_fill_value" title="numpy.ma.default_fill_value"><code class="xref py py-obj docutils literal"><span class="pre">ma.default_fill_value</span></code></a>（obj）</span></td>
<td><span class="yiyi-st" id="yiyi-303">返回参数对象的默认填充值。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-304"><a class="reference internal" href="generated/numpy.ma.maximum_fill_value.html#numpy.ma.maximum_fill_value" title="numpy.ma.maximum_fill_value"><code class="xref py py-obj docutils literal"><span class="pre">ma.maximum_fill_value</span></code></a>（obj）</span></td>
<td><span class="yiyi-st" id="yiyi-305">返回可由对象的dtype表示的最小值。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-306"><a class="reference internal" href="generated/numpy.ma.maximum_fill_value.html#numpy.ma.maximum_fill_value" title="numpy.ma.maximum_fill_value"><code class="xref py py-obj docutils literal"><span class="pre">ma.maximum_fill_value</span></code></a>（obj）</span></td>
<td><span class="yiyi-st" id="yiyi-307">返回可由对象的dtype表示的最小值。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-308"><a class="reference internal" href="generated/numpy.ma.set_fill_value.html#numpy.ma.set_fill_value" title="numpy.ma.set_fill_value"><code class="xref py py-obj docutils literal"><span class="pre">ma.set_fill_value</span></code></a>（a，fill_value）</span></td>
<td><span class="yiyi-st" id="yiyi-309">设置a的填充值，如果a是掩码数组。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-310"><a class="reference internal" href="generated/numpy.ma.MaskedArray.get_fill_value.html#numpy.ma.MaskedArray.get_fill_value" title="numpy.ma.MaskedArray.get_fill_value"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.get_fill_value</span></code></a>()</span></td>
<td><span class="yiyi-st" id="yiyi-311">返回掩码数组的填充值。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-312"><a class="reference internal" href="generated/numpy.ma.MaskedArray.set_fill_value.html#numpy.ma.MaskedArray.set_fill_value" title="numpy.ma.MaskedArray.set_fill_value"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.set_fill_value</span></code></a>（[value]）</span></td>
<td><span class="yiyi-st" id="yiyi-313">设置掩码数组的填充值。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-314"><a class="reference internal" href="maskedarray.baseclass.html#numpy.ma.MaskedArray.fill_value" title="numpy.ma.MaskedArray.fill_value"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.fill_value</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-315">灌装值。</span></td>
</tr>
</tbody>
</table>
</div>
</div>
<hr class="docutils">
<div class="section" id="masked-arrays-arithmetics">
<h2><span class="yiyi-st" id="yiyi-316">Masked arrays arithmetics</span></h2>
<div class="section" id="arithmetics">
<h3><span class="yiyi-st" id="yiyi-317">Arithmetics</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-318"><a class="reference internal" href="generated/numpy.ma.anom.html#numpy.ma.anom" title="numpy.ma.anom"><code class="xref py py-obj docutils literal"><span class="pre">ma.anom</span></code></a>（self [，axis，dtype]）</span></td>
<td><span class="yiyi-st" id="yiyi-319">沿给定轴计算异常（与算术平均值的偏差）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-320"><a class="reference internal" href="generated/numpy.ma.anomalies.html#numpy.ma.anomalies" title="numpy.ma.anomalies"><code class="xref py py-obj docutils literal"><span class="pre">ma.anomalies</span></code></a>（self [，axis，dtype]）</span></td>
<td><span class="yiyi-st" id="yiyi-321">沿给定轴计算异常（与算术平均值的偏差）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-322"><a class="reference internal" href="generated/numpy.ma.average.html#numpy.ma.average" title="numpy.ma.average"><code class="xref py py-obj docutils literal"><span class="pre">ma.average</span></code></a>（a [，axis，weights，returned]）</span></td>
<td><span class="yiyi-st" id="yiyi-323">返回给定轴上数组的加权平均值。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-324"><a class="reference internal" href="generated/numpy.ma.conjugate.html#numpy.ma.conjugate" title="numpy.ma.conjugate"><code class="xref py py-obj docutils literal"><span class="pre">ma.conjugate</span></code></a>（x [，out]）</span></td>
<td><span class="yiyi-st" id="yiyi-325">按元素方式返回复共轭。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-326"><a class="reference internal" href="generated/numpy.ma.corrcoef.html#numpy.ma.corrcoef" title="numpy.ma.corrcoef"><code class="xref py py-obj docutils literal"><span class="pre">ma.corrcoef</span></code></a>（x [，y，rowvar，bias，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-327">返回Pearson乘积矩相关系数。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-328"><a class="reference internal" href="generated/numpy.ma.cov.html#numpy.ma.cov" title="numpy.ma.cov"><code class="xref py py-obj docutils literal"><span class="pre">ma.cov</span></code></a>（x [，y，rowvar，bias，allow_masked，ddof]）</span></td>
<td><span class="yiyi-st" id="yiyi-329">估计协方差矩阵。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-330"><a class="reference internal" href="generated/numpy.ma.cumsum.html#numpy.ma.cumsum" title="numpy.ma.cumsum"><code class="xref py py-obj docutils literal"><span class="pre">ma.cumsum</span></code></a>（self [，axis，dtype，out]）</span></td>
<td><span class="yiyi-st" id="yiyi-331">返回给定轴上的数组元素的累积和。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-332"><a class="reference internal" href="generated/numpy.ma.cumprod.html#numpy.ma.cumprod" title="numpy.ma.cumprod"><code class="xref py py-obj docutils literal"><span class="pre">ma.cumprod</span></code></a>（self [，axis，dtype，out]）</span></td>
<td><span class="yiyi-st" id="yiyi-333">返回给定轴上的数组元素的累积乘积。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-334"><a class="reference internal" href="generated/numpy.ma.mean.html#numpy.ma.mean" title="numpy.ma.mean"><code class="xref py py-obj docutils literal"><span class="pre">ma.mean</span></code></a>（self [，axis，dtype，out，keepdims]）</span></td>
<td><span class="yiyi-st" id="yiyi-335">返回沿给定轴的数组元素的平均值。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-336"><a class="reference internal" href="generated/numpy.ma.median.html#numpy.ma.median" title="numpy.ma.median"><code class="xref py py-obj docutils literal"><span class="pre">ma.median</span></code></a>（a [，axis，out，overwrite_input，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-337">计算沿指定轴的中值。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-338"><a class="reference internal" href="generated/numpy.ma.power.html#numpy.ma.power" title="numpy.ma.power"><code class="xref py py-obj docutils literal"><span class="pre">ma.power</span></code></a>（a，b [，third]）</span></td>
<td><span class="yiyi-st" id="yiyi-339">返回从第二个数组提升为幂的基于元素的基数。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-340"><a class="reference internal" href="generated/numpy.ma.prod.html#numpy.ma.prod" title="numpy.ma.prod"><code class="xref py py-obj docutils literal"><span class="pre">ma.prod</span></code></a>（self [，axis，dtype，out，keepdims]）</span></td>
<td><span class="yiyi-st" id="yiyi-341">返回给定轴上的数组元素的乘积。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-342"><a class="reference internal" href="generated/numpy.ma.std.html#numpy.ma.std" title="numpy.ma.std"><code class="xref py py-obj docutils literal"><span class="pre">ma.std</span></code></a>（self [，axis，dtype，out，ddof，keepdims]）</span></td>
<td><span class="yiyi-st" id="yiyi-343">返回给定轴上的数组元素的标准偏差。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-344"><a class="reference internal" href="generated/numpy.ma.sum.html#numpy.ma.sum" title="numpy.ma.sum"><code class="xref py py-obj docutils literal"><span class="pre">ma.sum</span></code></a>（self [，axis，dtype，out，keepdims]）</span></td>
<td><span class="yiyi-st" id="yiyi-345">返回给定轴上的数组元素的总和。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-346"><a class="reference internal" href="generated/numpy.ma.var.html#numpy.ma.var" title="numpy.ma.var"><code class="xref py py-obj docutils literal"><span class="pre">ma.var</span></code></a>（self [，axis，dtype，out，ddof，keepdims]）</span></td>
<td><span class="yiyi-st" id="yiyi-347">计算沿指定轴的方差。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-348"><a class="reference internal" href="generated/numpy.ma.MaskedArray.anom.html#numpy.ma.MaskedArray.anom" title="numpy.ma.MaskedArray.anom"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.anom</span></code></a>（[axis，dtype]）</span></td>
<td><span class="yiyi-st" id="yiyi-349">沿给定轴计算异常（与算术平均值的偏差）。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-350"><a class="reference internal" href="generated/numpy.ma.MaskedArray.cumprod.html#numpy.ma.MaskedArray.cumprod" title="numpy.ma.MaskedArray.cumprod"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.cumprod</span></code></a>（[axis，dtype，out]）</span></td>
<td><span class="yiyi-st" id="yiyi-351">返回给定轴上的数组元素的累积乘积。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-352"><a class="reference internal" href="generated/numpy.ma.MaskedArray.cumsum.html#numpy.ma.MaskedArray.cumsum" title="numpy.ma.MaskedArray.cumsum"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.cumsum</span></code></a>（[axis，dtype，out]）</span></td>
<td><span class="yiyi-st" id="yiyi-353">返回给定轴上的数组元素的累积和。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-354"><a class="reference internal" href="generated/numpy.ma.MaskedArray.mean.html#numpy.ma.MaskedArray.mean" title="numpy.ma.MaskedArray.mean"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.mean</span></code></a>（[axis，dtype，out，keepdims]）</span></td>
<td><span class="yiyi-st" id="yiyi-355">返回沿给定轴的数组元素的平均值。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-356"><a class="reference internal" href="generated/numpy.ma.MaskedArray.prod.html#numpy.ma.MaskedArray.prod" title="numpy.ma.MaskedArray.prod"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.prod</span></code></a>（[axis，dtype，out，keepdims]）</span></td>
<td><span class="yiyi-st" id="yiyi-357">返回给定轴上的数组元素的乘积。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-358"><a class="reference internal" href="generated/numpy.ma.MaskedArray.std.html#numpy.ma.MaskedArray.std" title="numpy.ma.MaskedArray.std"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.std</span></code></a>（[axis，dtype，out，ddof，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-359">返回给定轴上的数组元素的标准偏差。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-360"><a class="reference internal" href="generated/numpy.ma.MaskedArray.sum.html#numpy.ma.MaskedArray.sum" title="numpy.ma.MaskedArray.sum"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.sum</span></code></a>（[axis，dtype，out，keepdims]）</span></td>
<td><span class="yiyi-st" id="yiyi-361">返回给定轴上的数组元素的总和。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-362"><a class="reference internal" href="generated/numpy.ma.MaskedArray.var.html#numpy.ma.MaskedArray.var" title="numpy.ma.MaskedArray.var"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.var</span></code></a>（[axis，dtype，out，ddof，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-363">计算沿指定轴的方差。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="minimum-maximum">
<h3><span class="yiyi-st" id="yiyi-364">Minimum/maximum</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-365"><a class="reference internal" href="generated/numpy.ma.argmax.html#numpy.ma.argmax" title="numpy.ma.argmax"><code class="xref py py-obj docutils literal"><span class="pre">ma.argmax</span></code></a>（self [，axis，fill_value，out]）</span></td>
<td><span class="yiyi-st" id="yiyi-366">返回沿给定轴的最大值的索引的数组。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-367"><a class="reference internal" href="generated/numpy.ma.argmin.html#numpy.ma.argmin" title="numpy.ma.argmin"><code class="xref py py-obj docutils literal"><span class="pre">ma.argmin</span></code></a>（self [，axis，fill_value，out]）</span></td>
<td><span class="yiyi-st" id="yiyi-368">将指数的数组返回给定轴的最小值。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-369"><a class="reference internal" href="generated/numpy.ma.max.html#numpy.ma.max" title="numpy.ma.max"><code class="xref py py-obj docutils literal"><span class="pre">ma.max</span></code></a>（obj [，axis，out，fill_value，keepdims]）</span></td>
<td><span class="yiyi-st" id="yiyi-370">沿给定轴返回最大值。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-371"><a class="reference internal" href="generated/numpy.ma.min.html#numpy.ma.min" title="numpy.ma.min"><code class="xref py py-obj docutils literal"><span class="pre">ma.min</span></code></a>（obj [，axis，out，fill_value，keepdims]）</span></td>
<td><span class="yiyi-st" id="yiyi-372">沿给定轴返回最小值。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-373"><a class="reference internal" href="generated/numpy.ma.ptp.html#numpy.ma.ptp" title="numpy.ma.ptp"><code class="xref py py-obj docutils literal"><span class="pre">ma.ptp</span></code></a>（obj [，axis，out，fill_value]）</span></td>
<td><span class="yiyi-st" id="yiyi-374">沿给定尺寸的返回（最大 - 最小）。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-375"><a class="reference internal" href="generated/numpy.ma.MaskedArray.argmax.html#numpy.ma.MaskedArray.argmax" title="numpy.ma.MaskedArray.argmax"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.argmax</span></code></a>（[axis，fill_value，out]）</span></td>
<td><span class="yiyi-st" id="yiyi-376">返回沿给定轴的最大值的索引的数组。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-377"><a class="reference internal" href="generated/numpy.ma.MaskedArray.argmin.html#numpy.ma.MaskedArray.argmin" title="numpy.ma.MaskedArray.argmin"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.argmin</span></code></a>（[axis，fill_value，out]）</span></td>
<td><span class="yiyi-st" id="yiyi-378">将指数的数组返回给定轴的最小值。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-379"><a class="reference internal" href="generated/numpy.ma.MaskedArray.max.html#numpy.ma.MaskedArray.max" title="numpy.ma.MaskedArray.max"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.max</span></code></a>（[axis，out，fill_value，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-380">沿给定轴返回最大值。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-381"><a class="reference internal" href="generated/numpy.ma.MaskedArray.min.html#numpy.ma.MaskedArray.min" title="numpy.ma.MaskedArray.min"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.min</span></code></a>（[axis，out，fill_value，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-382">沿给定轴返回最小值。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-383"><a class="reference internal" href="generated/numpy.ma.MaskedArray.ptp.html#numpy.ma.MaskedArray.ptp" title="numpy.ma.MaskedArray.ptp"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.ptp</span></code></a>（[axis，out，fill_value]）</span></td>
<td><span class="yiyi-st" id="yiyi-384">沿给定尺寸的返回（最大 - 最小）。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="sorting">
<h3><span class="yiyi-st" id="yiyi-385">Sorting</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-386"><a class="reference internal" href="generated/numpy.ma.argsort.html#numpy.ma.argsort" title="numpy.ma.argsort"><code class="xref py py-obj docutils literal"><span class="pre">ma.argsort</span></code></a>（a [，axis，kind，order，fill_value]）</span></td>
<td><span class="yiyi-st" id="yiyi-387">返回沿指定轴对数组进行排序的索引数组。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-388"><a class="reference internal" href="generated/numpy.ma.sort.html#numpy.ma.sort" title="numpy.ma.sort"><code class="xref py py-obj docutils literal"><span class="pre">ma.sort</span></code></a>（a [，axis，kind，order，endwith，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-389">就地对数组进行排序</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-390"><a class="reference internal" href="generated/numpy.ma.MaskedArray.argsort.html#numpy.ma.MaskedArray.argsort" title="numpy.ma.MaskedArray.argsort"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.argsort</span></code></a>（[axis，kind，order，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-391">返回沿指定轴对数组进行排序的索引数组。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-392"><a class="reference internal" href="generated/numpy.ma.MaskedArray.sort.html#numpy.ma.MaskedArray.sort" title="numpy.ma.MaskedArray.sort"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.sort</span></code></a>（[axis，kind，order，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-393">就地对数组进行排序</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="algebra">
<h3><span class="yiyi-st" id="yiyi-394">Algebra</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-395"><a class="reference internal" href="generated/numpy.ma.diag.html#numpy.ma.diag" title="numpy.ma.diag"><code class="xref py py-obj docutils literal"><span class="pre">ma.diag</span></code></a>（v [，k]）</span></td>
<td><span class="yiyi-st" id="yiyi-396">提取对角线或构造对角数组。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-397"><a class="reference internal" href="generated/numpy.ma.dot.html#numpy.ma.dot" title="numpy.ma.dot"><code class="xref py py-obj docutils literal"><span class="pre">ma.dot</span></code></a>（a，b [，strict，out]）</span></td>
<td><span class="yiyi-st" id="yiyi-398">返回两个数组的点积。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-399"><a class="reference internal" href="generated/numpy.ma.identity.html#numpy.ma.identity" title="numpy.ma.identity"><code class="xref py py-obj docutils literal"><span class="pre">ma.identity</span></code></a>（n [，dtype]）</span></td>
<td><span class="yiyi-st" id="yiyi-400">返回身份数组。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-401"><a class="reference internal" href="generated/numpy.ma.inner.html#numpy.ma.inner" title="numpy.ma.inner"><code class="xref py py-obj docutils literal"><span class="pre">ma.inner</span></code></a>（a，b）</span></td>
<td><span class="yiyi-st" id="yiyi-402">两个数组的内积。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-403"><a class="reference internal" href="generated/numpy.ma.innerproduct.html#numpy.ma.innerproduct" title="numpy.ma.innerproduct"><code class="xref py py-obj docutils literal"><span class="pre">ma.innerproduct</span></code></a>（a，b）</span></td>
<td><span class="yiyi-st" id="yiyi-404">两个数组的内积。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-405"><a class="reference internal" href="generated/numpy.ma.outer.html#numpy.ma.outer" title="numpy.ma.outer"><code class="xref py py-obj docutils literal"><span class="pre">ma.outer</span></code></a>（a，b）</span></td>
<td><span class="yiyi-st" id="yiyi-406">计算两个向量的外积。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-407"><a class="reference internal" href="generated/numpy.ma.outerproduct.html#numpy.ma.outerproduct" title="numpy.ma.outerproduct"><code class="xref py py-obj docutils literal"><span class="pre">ma.outerproduct</span></code></a>（a，b）</span></td>
<td><span class="yiyi-st" id="yiyi-408">计算两个向量的外积。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-409"><a class="reference internal" href="generated/numpy.ma.trace.html#numpy.ma.trace" title="numpy.ma.trace"><code class="xref py py-obj docutils literal"><span class="pre">ma.trace</span></code></a>（self [，offset，axis1，axis2，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-410">沿数组的对角线返回总和。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-411"><a class="reference internal" href="generated/numpy.ma.transpose.html#numpy.ma.transpose" title="numpy.ma.transpose"><code class="xref py py-obj docutils literal"><span class="pre">ma.transpose</span></code></a>（a [，axes]）</span></td>
<td><span class="yiyi-st" id="yiyi-412">允许数组的尺寸。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-413"><a class="reference internal" href="generated/numpy.ma.MaskedArray.trace.html#numpy.ma.MaskedArray.trace" title="numpy.ma.MaskedArray.trace"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.trace</span></code></a>（[offset，axis1，axis2，...]）</span></td>
<td><span class="yiyi-st" id="yiyi-414">沿数组的对角线返回总和。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-415"><a class="reference internal" href="generated/numpy.ma.MaskedArray.transpose.html#numpy.ma.MaskedArray.transpose" title="numpy.ma.MaskedArray.transpose"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.transpose</span></code></a>（\ * axes）</span></td>
<td><span class="yiyi-st" id="yiyi-416">返回具有轴转置的数组的视图。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="polynomial-fit">
<h3><span class="yiyi-st" id="yiyi-417">Polynomial fit</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-418"><a class="reference internal" href="generated/numpy.ma.vander.html#numpy.ma.vander" title="numpy.ma.vander"><code class="xref py py-obj docutils literal"><span class="pre">ma.vander</span></code></a>（x [，n]）</span></td>
<td><span class="yiyi-st" id="yiyi-419">生成Vandermonde矩阵。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-420"><a class="reference internal" href="generated/numpy.ma.polyfit.html#numpy.ma.polyfit" title="numpy.ma.polyfit"><code class="xref py py-obj docutils literal"><span class="pre">ma.polyfit</span></code></a>（x，y，deg [，rcond，full，w，cov]）</span></td>
<td><span class="yiyi-st" id="yiyi-421">最小二乘多项式拟合。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="clipping-and-rounding">
<h3><span class="yiyi-st" id="yiyi-422">Clipping and rounding</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-423"><a class="reference internal" href="generated/numpy.ma.around.html#numpy.ma.around" title="numpy.ma.around"><code class="xref py py-obj docutils literal"><span class="pre">ma.around</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-424">将数组舍入到给定的小数位数。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-425"><a class="reference internal" href="generated/numpy.ma.clip.html#numpy.ma.clip" title="numpy.ma.clip"><code class="xref py py-obj docutils literal"><span class="pre">ma.clip</span></code></a>（a，a_min，a_max [，out]）</span></td>
<td><span class="yiyi-st" id="yiyi-426">剪辑（限制）数组中的值。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-427"><a class="reference internal" href="generated/numpy.ma.round.html#numpy.ma.round" title="numpy.ma.round"><code class="xref py py-obj docutils literal"><span class="pre">ma.round</span></code></a>（a [，decimals，out]）</span></td>
<td><span class="yiyi-st" id="yiyi-428">返回a的副本，四舍五入为“小数”位。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-429"><a class="reference internal" href="generated/numpy.ma.MaskedArray.clip.html#numpy.ma.MaskedArray.clip" title="numpy.ma.MaskedArray.clip"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.clip</span></code></a>（[min，max，out]）</span></td>
<td><span class="yiyi-st" id="yiyi-430">返回值限于<code class="docutils literal"><span class="pre">[min，</span> <span class="pre">max]</span></code>的数组。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-431"><a class="reference internal" href="generated/numpy.ma.MaskedArray.round.html#numpy.ma.MaskedArray.round" title="numpy.ma.MaskedArray.round"><code class="xref py py-obj docutils literal"><span class="pre">ma.MaskedArray.round</span></code></a>（[decimal，out]）</span></td>
<td><span class="yiyi-st" id="yiyi-432">返回四舍五入到给定小数位数的每个元素。</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="miscellanea">
<h3><span class="yiyi-st" id="yiyi-433">Miscellanea</span></h3>
<table border="1" class="longtable docutils">
<colgroup>
<col width="10%">
<col width="90%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-434"><a class="reference internal" href="generated/numpy.ma.allequal.html#numpy.ma.allequal" title="numpy.ma.allequal"><code class="xref py py-obj docutils literal"><span class="pre">ma.allequal</span></code></a>（a，b [，fill_value]）</span></td>
<td><span class="yiyi-st" id="yiyi-435">如果a和b的所有条目都相等，则返回True，使用fill_value作为其中一个或两者都被掩蔽的真值。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-436"><a class="reference internal" href="generated/numpy.ma.allclose.html#numpy.ma.allclose" title="numpy.ma.allclose"><code class="xref py py-obj docutils literal"><span class="pre">ma.allclose</span></code></a>（a，b [，masked_equal，rtol，atol]）</span></td>
<td><span class="yiyi-st" id="yiyi-437">如果两个数组在元素方面在公差内相等，则返回True。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-438"><a class="reference internal" href="generated/numpy.ma.apply_along_axis.html#numpy.ma.apply_along_axis" title="numpy.ma.apply_along_axis"><code class="xref py py-obj docutils literal"><span class="pre">ma.apply_along_axis</span></code></a>（func1d，axis，arr，...）</span></td>
<td><span class="yiyi-st" id="yiyi-439">沿着给定轴向1-D切片应用函数。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-440"><a class="reference internal" href="generated/numpy.ma.arange.html#numpy.ma.arange" title="numpy.ma.arange"><code class="xref py py-obj docutils literal"><span class="pre">ma.arange</span></code></a>（[start，] stop [，step，] [，dtype]）</span></td>
<td><span class="yiyi-st" id="yiyi-441">在给定间隔内返回均匀间隔的值。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-442"><a class="reference internal" href="generated/numpy.ma.choose.html#numpy.ma.choose" title="numpy.ma.choose"><code class="xref py py-obj docutils literal"><span class="pre">ma.choose</span></code></a>（indices，choices [，out，mode]）</span></td>
<td><span class="yiyi-st" id="yiyi-443">使用索引数组从一组选择中构造新的数组。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-444"><a class="reference internal" href="generated/numpy.ma.ediff1d.html#numpy.ma.ediff1d" title="numpy.ma.ediff1d"><code class="xref py py-obj docutils literal"><span class="pre">ma.ediff1d</span></code></a>（arr [，to_end，to_begin]）</span></td>
<td><span class="yiyi-st" id="yiyi-445">计算数组的连续元素之间的差异。</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-446"><a class="reference internal" href="generated/numpy.ma.indices.html#numpy.ma.indices" title="numpy.ma.indices"><code class="xref py py-obj docutils literal"><span class="pre">ma.indices</span></code></a>（dimensions [，dtype]）</span></td>
<td><span class="yiyi-st" id="yiyi-447">返回表示网格索引的数组。</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-448"><a class="reference internal" href="generated/numpy.ma.where.html#numpy.ma.where" title="numpy.ma.where"><code class="xref py py-obj docutils literal"><span class="pre">ma.where</span></code></a>（condition [，x，y]）</span></td>
<td><span class="yiyi-st" id="yiyi-449">根据条件返回带有x或y元素的蒙版数组。</span></td>
</tr>
</tbody>
</table>
</div>
</div>