File: array-numpy-compatibility.rst

package info (click to toggle)
dask 2024.12.1%2Bdfsg-2
  • links: PTS, VCS
  • area: main
  • in suites: forky, sid, trixie
  • size: 20,024 kB
  • sloc: python: 105,182; javascript: 1,917; makefile: 159; sh: 88
file content (390 lines) | stat: -rw-r--r-- 21,549 bytes parent folder | download
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
Compatibility with numpy functions
==================================

The following table describes the compatibilities between `numpy` and `dask.array`
functions.
Please be aware that some inconsistencies with the two versions may exist.

This table has been compiled manually and may not reflect the current Dask state.
Update contributions are welcome. 

* A blank entry indicates that the function is not implemented in Dask.
* Direct implementation are direct calls to numpy functions.
* Element-wise implementations are derived from numpy but applied element-wise: the
  argument should be a dask array.
* Dask equivalent are Dask implementations, which may lack or add parameters with respect
  to the numpy function.

A more in-depth comparison in the framework of the `Array API <https://data-apis.org/array-api/latest/>`_
is available via the `Array API Comparison repository <https://github.com/data-apis/array-api-comparison>`_.

.. csv-table::
   :header: NumPy, Dask, Implementation

   :obj:`numpy.absolute`, :obj:`dask.array.absolute` or :obj:`dask.array.abs`, direct (ufunc)
   :obj:`numpy.add`, :obj:`dask.array.add`, direct (ufunc)
   :obj:`numpy.all`, :obj:`dask.array.all` [#1]_, dask equivalent
   :obj:`numpy.allclose`, :obj:`dask.array.allclose`, dask equivalent
   :obj:`numpy.amax`, :obj:`dask.array.max` [#1]_ [#2]_, dask equivalent
   :obj:`numpy.amin`, :obj:`dask.array.min` [#1]_ [#2]_, dask equivalent
   :obj:`numpy.angle`, :obj:`dask.array.angle` [#3]_, dask equivalent
   :obj:`numpy.any`, :obj:`dask.array.any` [#1]_, dask equivalent
   :obj:`numpy.append`, :obj:`dask.array.append`, dask equivalent
   :obj:`numpy.apply_along_axis`, :obj:`dask.array.apply_along_axis`, dask equivalent
   :obj:`numpy.apply_over_axes`, :obj:`dask.array.apply_over_axes`, dask equivalent
   :obj:`numpy.arange`, :obj:`dask.array.arange`, dask equivalent
   :obj:`numpy.arccos`, :obj:`dask.array.arccos`, direct (ufunc)
   :obj:`numpy.arccosh`, :obj:`dask.array.arccosh`, direct (ufunc)
   :obj:`numpy.arcsin`, :obj:`dask.array.arcsin`, direct (ufunc)
   :obj:`numpy.arcsinh`, :obj:`dask.array.arcsinh`, direct (ufunc)
   :obj:`numpy.arctan`, :obj:`dask.array.arctan`, direct (ufunc)
   :obj:`numpy.arctan2`, :obj:`dask.array.arctan2`, direct (ufunc)
   :obj:`numpy.arctanh`, :obj:`dask.array.arctanh`, direct (ufunc)
   :obj:`numpy.argmax`, :obj:`dask.array.argmax`, dask equivalent
   :obj:`numpy.argmin`, :obj:`dask.array.argmin`, dask equivalent
   :obj:`numpy.argpartition`, \-
   :obj:`numpy.argsort`, :obj:`dask.array.argtopk` [#5]_
   :obj:`numpy.argwhere`, :obj:`dask.array.argwhere`, dask equivalent
   :obj:`numpy.around`, :obj:`dask.array.around` [#3]_ [#6]_ or :obj:`dask.array.round`, dask equivalent
   :obj:`numpy.array`, :obj:`dask.array.array`, dask equivalent
   :obj:`numpy.array2string`, \-
   :obj:`numpy.array_equal`, \-
   :obj:`numpy.array_equiv`, \-
   :obj:`numpy.array_repr`, \-
   :obj:`numpy.array_split`, \-
   :obj:`numpy.array_str`, \-
   :obj:`numpy.asanyarray`, :obj:`dask.array.asanyarray`, dask equivalent
   :obj:`numpy.asarray`, :obj:`dask.array.asarray`, dask equivalent
   :obj:`numpy.asarray_chkfinite`, \-
   :obj:`numpy.ascontiguousarray`, \-
   :obj:`numpy.asfarray`, \-
   :obj:`numpy.asfortranarray`, \-
   :obj:`numpy.asmatrix`, \- [#7]_
   :obj:`numpy.atleast_1d`, :obj:`dask.array.atleast_1d`, dask equivalent
   :obj:`numpy.atleast_2d`, :obj:`dask.array.atleast_2d`, dask equivalent
   :obj:`numpy.atleast_3d`, :obj:`dask.array.atleast_3d`, dask equivalent
   :obj:`numpy.average`, :obj:`dask.array.average`, dask equivalent
   :obj:`numpy.bartlett`, \-
   :obj:`numpy.bincount`, :obj:`dask.array.bincount`, dask equivalent
   :obj:`numpy.bitwise_and`, :obj:`dask.array.bitwise_and`, direct (ufunc)
   :obj:`numpy.bitwise_or`, :obj:`dask.array.bitwise_or`, direct (ufunc)
   :obj:`numpy.bitwise_xor`, :obj:`dask.array.bitwise_xor`, direct (ufunc)
   :obj:`numpy.blackman`, \-
   :obj:`numpy.block`, :obj:`dask.array.block`, dask equivalent
   :obj:`numpy.bmat`, \- [#7]_
   :obj:`numpy.broadcast`, \-
   :obj:`numpy.broadcast_arrays`, :obj:`dask.array.broadcast_arrays`, dask equivalent
   :obj:`numpy.broadcast_shapes`, \-
   :obj:`numpy.broadcast_to`, :obj:`dask.array.broadcast_to`, dask equivalent
   :obj:`numpy.byte_bounds`, \-
   :obj:`numpy.c_`, \-
   :obj:`numpy.can_cast`, \-
   :obj:`numpy.cbrt`, :obj:`dask.array.cbrt`, direct (ufunc)
   :obj:`numpy.ceil`, :obj:`dask.array.ceil`, direct (ufunc)
   :obj:`numpy.choose`, :obj:`dask.array.choose` [#8]_, dask equivalent
   :obj:`numpy.clip`, :obj:`dask.array.clip` [#3]_ [#6]_, direct (non-ufunc elementwise)
   :obj:`numpy.column_stack`, \-
   :obj:`numpy.common_type`, \-
   :obj:`numpy.compress`, :obj:`dask.array.compress` [#6]_, dask equivalent
   :obj:`numpy.concatenate`, :obj:`dask.array.concatenate`, dask equivalent
   :obj:`numpy.conj`, :obj:`dask.array.conj`, direct (ufunc)
   :obj:`numpy.conjugate`,  :obj:`dask.array.conj`, direct (ufunc)
   :obj:`numpy.convolve`, \-
   :obj:`numpy.copy`, \-
   :obj:`numpy.copysign`, :obj:`dask.array.copysign`, direct (ufunc)
   :obj:`numpy.copyto`, \-
   :obj:`numpy.corrcoef`, :obj:`dask.array.corrcoef`, dask equivalent
   :obj:`numpy.correlate`, \-
   :obj:`numpy.cos`, :obj:`dask.array.cos`, direct (ufunc)
   :obj:`numpy.cosh`, :obj:`dask.array.cosh`, direct (ufunc)
   :obj:`numpy.count_nonzero`, :obj:`dask.array.count_nonzero` [#9]_, dask equivalent
   :obj:`numpy.cov`, :obj:`dask.array.cov` [#10]_, dask equivalent
   :obj:`numpy.cross`, \-
   :obj:`numpy.cumprod`, :obj:`dask.array.cumprod` [#3]_ [#18]_, dask equivalent
   :obj:`numpy.cumsum`, :obj:`dask.array.cumsum` [#3]_ [#18]_, dask equivalent
   :obj:`numpy.datetime_as_string`, \-
   :obj:`numpy.deg2rad`, :obj:`dask.array.deg2rad`, direct (ufunc)
   :obj:`numpy.degrees`, :obj:`dask.array.degrees`, direct (ufunc)
   :obj:`numpy.delete`, :obj:`dask.array.delete`, dask equivalent
   :obj:`numpy.diag`, :obj:`dask.array.diag`, dask equivalent
   :obj:`numpy.diag_indices`, \-
   :obj:`numpy.diag_indices_from`, \-
   :obj:`numpy.diagflat`, \-
   :obj:`numpy.diagonal`, :obj:`dask.array.diagonal`, dask equivalent
   :obj:`numpy.diff`, :obj:`dask.array.diff`, dask equivalent
   :obj:`numpy.digitize`, :obj:`dask.array.digitize` [#3]_, dask equivalent
   :obj:`numpy.divide`, :obj:`dask.array.divide`, direct (ufunc)
   :obj:`numpy.divmod`, :obj:`dask.array.divmod`, dask equivalent
   :obj:`numpy.dot`, :obj:`dask.array.dot` [#6]_, dask equivalent
   :obj:`numpy.dsplit`, \-
   :obj:`numpy.dstack`, :obj:`dask.array.dstack`, dask equivalent
   :obj:`numpy.ediff1d`, :obj:`dask.array.ediff1d`, dask equivalent
   :obj:`numpy.einsum`, :obj:`dask.array.einsum` [#6]_, dask equivalent
   :obj:`numpy.einsum_path`, \-
   :obj:`numpy.empty`, :obj:`dask.array.empty`, dask equivalent
   :obj:`numpy.empty_like`, :obj:`dask.array.empty_like`, dask equivalent
   :obj:`numpy.equal`, :obj:`dask.array.equal`, direct (ufunc)
   :obj:`numpy.exp`, :obj:`dask.array.exp`, direct (ufunc)
   :obj:`numpy.exp2`, :obj:`dask.array.exp2`, direct (ufunc)
   :obj:`numpy.expand_dims`, :obj:`dask.array.expand_dims`, dask equivalent
   :obj:`numpy.expm1`, :obj:`dask.array.expm1`, direct (ufunc)
   :obj:`numpy.extract`, :obj:`dask.array.extract`, dask equivalent
   :obj:`numpy.eye`, :obj:`dask.array.eye`, dask equivalent
   :obj:`numpy.fabs`, :obj:`dask.array.fabs`, direct (ufunc)
   :obj:`numpy.fill_diagonal`, \-
   :obj:`numpy.fix`, :obj:`dask.array.fix`, direct (non-ufunc elementwise)
   :obj:`numpy.flatnonzero`, :obj:`dask.array.flatnonzero`, dask equivalent
   :obj:`numpy.flip`, :obj:`dask.array.flip`, dask equivalent
   :obj:`numpy.fliplr`, :obj:`dask.array.fliplr`, dask equivalent
   :obj:`numpy.flipud`, :obj:`dask.array.flipud`, dask equivalent
   :obj:`numpy.float_power`, :obj:`dask.array.float_power`, direct (ufunc)
   :obj:`numpy.floor`, :obj:`dask.array.floor`, direct (ufunc)
   :obj:`numpy.floor_divide`, :obj:`dask.array.floor_divide`, direct (ufunc)
   :obj:`numpy.fmax`, :obj:`dask.array.fmax`, direct (ufunc)
   :obj:`numpy.fmin`, :obj:`dask.array.fmin`, direct (ufunc)
   :obj:`numpy.fmod`, :obj:`dask.array.fmod`, direct (ufunc)
   :obj:`numpy.frexp`, :obj:`dask.array.frexp`, dask equivalent
   :obj:`numpy.from_dlpack`, \-
   :obj:`numpy.frombuffer`, \-
   :obj:`numpy.fromfile`, \-
   :obj:`numpy.fromfunction`, :obj:`dask.array.fromfunction` [#11]_, dask equivalent
   :obj:`numpy.fromiter`, \-
   :obj:`numpy.frompyfunc`, :obj:`dask.array.frompyfunc` [#12]_, dask equivalent
   :obj:`numpy.fromregex`, \-
   :obj:`numpy.fromstring`, \-
   :obj:`numpy.full`, :obj:`dask.array.full`, dask equivalent
   :obj:`numpy.full_like`, :obj:`dask.array.full_like`, dask equivalent
   :obj:`numpy.gcd`, \-
   :obj:`numpy.genfromtxt`, \-
   :obj:`numpy.geomspace`, \-
   :obj:`numpy.gradient`, :obj:`dask.array.gradient` [#13]_, dask equivalent
   :obj:`numpy.greater`, :obj:`dask.array.greater`, direct (ufunc)
   :obj:`numpy.greater_equal`, :obj:`dask.array.greater_equal`, direct (ufunc)
   :obj:`numpy.hamming`, \-
   :obj:`numpy.hanning`, \-
   :obj:`numpy.heaviside`, \-
   :obj:`numpy.histogram`, :obj:`dask.array.histogram`, dask equivalent
   :obj:`numpy.histogram2d`, :obj:`dask.array.histogram2d`, dask equivalent
   :obj:`numpy.histogram_bin_edges`, \-
   :obj:`numpy.histogramdd`, :obj:`dask.array.histogramdd` [#14]_, dask equivalent
   :obj:`numpy.hsplit`, \-
   :obj:`numpy.hstack`, :obj:`dask.array.hstack`, dask equivalent
   :obj:`numpy.hypot`, :obj:`dask.array.hypot`, direct (ufunc)
   :obj:`numpy.i0`, :obj:`dask.array.i0`, direct (non-ufunc elementwise)
   :obj:`numpy.identity`, \-
   :obj:`numpy.imag`, :obj:`dask.array.imag`, direct (non-ufunc elementwise)
   :obj:`numpy.in1d`, \-
   :obj:`numpy.indices`, :obj:`dask.array.indices`, dask equivalent
   :obj:`numpy.inner`, \-
   :obj:`numpy.insert`, :obj:`dask.array.insert` [#15]_, dask equivalent
   :obj:`numpy.interp`, \-
   :obj:`numpy.intersect1d`, \-
   :obj:`numpy.invert`, :obj:`dask.array.invert` or :obj:`dask.array.bitwise_not`, direct (ufunc)
   :obj:`numpy.is_busday`, \-
   :obj:`numpy.isclose`, :obj:`dask.array.isclose`, dask equivalent
   :obj:`numpy.iscomplex`, :obj:`dask.array.iscomplex`, direct (non-ufunc elementwise)
   :obj:`numpy.iscomplexobj`, \-
   :obj:`numpy.isfinite`, :obj:`dask.array.isfinite`, direct (ufunc)
   :obj:`numpy.isfortran`, \-
   :obj:`numpy.isin`, :obj:`dask.array.isin`, dask equivalent
   :obj:`numpy.isinf`, :obj:`dask.array.isinf`, direct (ufunc)
   :obj:`numpy.isnan`, :obj:`dask.array.isnan`, direct (ufunc)
   :obj:`numpy.isnat`, \-
   :obj:`numpy.isneginf`, :obj:`dask.array.isneginf`, direct (ufunc)
   :obj:`numpy.isposinf`, :obj:`dask.array.isposinf`, direct (ufunc)
   :obj:`numpy.isreal`, :obj:`dask.array.isreal`, direct (non-ufunc elementwise)
   :obj:`numpy.ix_`, \-
   :obj:`numpy.kaiser`, \-
   :obj:`numpy.kron`, \-
   :obj:`numpy.lcm`, \-
   :obj:`numpy.ldexp`, :obj:`dask.array.ldexp`, direct (ufunc)
   :obj:`numpy.left_shift`, :obj:`dask.array.left_shift`, direct (ufunc)
   :obj:`numpy.less`, :obj:`dask.array.less`, direct (ufunc)
   :obj:`numpy.less_equal`, :obj:`dask.array.less_equal`, direct (ufunc)
   :obj:`numpy.lexsort`, \-
   :obj:`numpy.linspace`, :obj:`dask.array.linspace`, dask equivalent
   :obj:`numpy.load`, \-
   :obj:`numpy.loadtxt`, \-
   :obj:`numpy.log`, :obj:`dask.array.log`, direct (ufunc)
   :obj:`numpy.log10`, :obj:`dask.array.log10`, direct (ufunc)
   :obj:`numpy.log1p`, :obj:`dask.array.log1p`, direct (ufunc)
   :obj:`numpy.log2`, :obj:`dask.array.log2`, direct (ufunc)
   :obj:`numpy.logaddexp`, :obj:`dask.array.logaddexp`, direct (ufunc)
   :obj:`numpy.logaddexp2`, :obj:`dask.array.logaddexp2`, direct (ufunc)
   :obj:`numpy.logical_and`, :obj:`dask.array.logical_and`, direct (ufunc)
   :obj:`numpy.logical_not`, :obj:`dask.array.logical_not`, direct (ufunc)
   :obj:`numpy.logical_or`, :obj:`dask.array.logical_or`, direct (ufunc)
   :obj:`numpy.logical_xor`, :obj:`dask.array.logical_xor`, direct (ufunc)
   :obj:`numpy.logspace`, \-
   :obj:`numpy.mask_indices`, \-
   :obj:`numpy.mat`, \- [#7]_
   :obj:`numpy.matmul`, :obj:`dask.array.matmul`, dask equivalent
   :obj:`numpy.matrix`, \- [#7]_
   :obj:`numpy.maximum`, :obj:`dask.array.maximum`, direct (ufunc)
   :obj:`numpy.may_share_memory`, \-
   :obj:`numpy.mean`, :obj:`dask.array.mean` [#1]_, dask equivalent
   :obj:`numpy.median`, :obj:`dask.array.median` [#16]_, dask equivalent
   :obj:`numpy.memmap`, \-
   :obj:`numpy.meshgrid`, :obj:`dask.array.meshgrid` [#17]_, dask equivalent
   :obj:`numpy.mgrid`, \-
   :obj:`numpy.minimum`, :obj:`dask.array.minimum`, direct (ufunc)
   :obj:`numpy.mintypecode`, \-
   :obj:`numpy.mod`, :obj:`dask.array.mod`, direct (ufunc)
   :obj:`numpy.modf`, :obj:`dask.array.modf`, dask equivalent
   :obj:`numpy.moveaxis`, :obj:`dask.array.moveaxis`, dask equivalent
   :obj:`numpy.multiply`, :obj:`dask.array.multiply`, direct (ufunc)
   :obj:`numpy.nan_to_num`, :obj:`dask.array.nan_to_num`, direct (non-ufunc elementwise)
   :obj:`numpy.nanargmax`, :obj:`dask.array.nanargmax`, dask equivalent
   :obj:`numpy.nanargmin`, :obj:`dask.array.nanargmin`, dask equivalent
   :obj:`numpy.nancumprod`, :obj:`dask.array.nancumprod` [#3]_ [#18]_, dask equivalent
   :obj:`numpy.nancumsum`, :obj:`dask.array.nancumsum` [#3]_ [#18]_, dask equivalent
   :obj:`numpy.nanmax`, :obj:`dask.array.nanmax` [#1]_ [#2]_, dask equivalent
   :obj:`numpy.nanmean`, :obj:`dask.array.nanmean` [#1]_, dask equivalent
   :obj:`numpy.nanmedian`, :obj:`dask.array.nanmedian` [#16]_, dask equivalent
   :obj:`numpy.nanmin`, :obj:`dask.array.nanmin` [#1]_ [#2]_, dask equivalent
   :obj:`numpy.nanpercentile`, :obj:`dask.array.nanpercentile`
   :obj:`numpy.nanprod`, :obj:`dask.array.nanprod` [#1]_ [#2]_, dask equivalent
   :obj:`numpy.nanquantile`, :obj:`dask.array.nanquantile`
   :obj:`numpy.nanstd`, :obj:`dask.array.nanstd` [#1]_, dask equivalent
   :obj:`numpy.nansum`, :obj:`dask.array.nansum` [#1]_ [#2]_, dask equivalent
   :obj:`numpy.nanvar`, :obj:`dask.array.nanvar` [#1]_, dask equivalent
   :obj:`numpy.ndenumerate`, \-
   :obj:`numpy.ndindex`, \-
   :obj:`numpy.nditer`, \-
   :obj:`numpy.negative`, :obj:`dask.array.negative`, direct (ufunc)
   :obj:`numpy.nested_iters`, \-
   :obj:`numpy.nextafter`, :obj:`dask.array.nextafter`, direct (ufunc)
   :obj:`numpy.nonzero`, :obj:`dask.array.nonzero`, dask equivalent
   :obj:`numpy.not_equal`, :obj:`dask.array.not_equal`, direct (ufunc)
   :obj:`numpy.ogrid`, \-
   :obj:`numpy.ones`, :obj:`dask.array.ones`, dask equivalent
   :obj:`numpy.ones_like`, :obj:`dask.array.ones_like`, dask equivalent
   :obj:`numpy.outer`, :obj:`dask.array.outer`, dask equivalent
   :obj:`numpy.packbits`, \-
   :obj:`numpy.pad`, :obj:`dask.array.pad`, dask equivalent
   :obj:`numpy.partition`, \-
   :obj:`numpy.percentile`, :obj:`dask.array.percentile`, dask equivalent
   :obj:`numpy.piecewise`, :obj:`dask.array.piecewise`, dask equivalent
   :obj:`numpy.place`, \-
   :obj:`numpy.poly`, \-
   :obj:`numpy.poly1d`, \-
   :obj:`numpy.polyadd`, \-
   :obj:`numpy.polyder`, \-
   :obj:`numpy.polydiv`, \-
   :obj:`numpy.polyfit`, \-
   :obj:`numpy.polyint`, \-
   :obj:`numpy.polymul`, \-
   :obj:`numpy.polysub`, \-
   :obj:`numpy.polyval`, \-
   :obj:`numpy.positive`, :obj:`dask.array.positive`, direct (ufunc)
   :obj:`numpy.power`, :obj:`dask.array.power`, direct (ufunc)
   :obj:`numpy.prod`, :obj:`dask.array.prod`, dask equivalent
   :obj:`numpy.ptp`, :obj:`dask.array.ptp`, dask equivalent
   :obj:`numpy.put`, \-
   :obj:`numpy.put_along_axis`, \-
   :obj:`numpy.putmask`, \-
   :obj:`numpy.quantile`, :obj:`dask.array.quantile`
   :obj:`numpy.r_`, \-
   :obj:`numpy.rad2deg`, :obj:`dask.array.rad2deg`, direct (ufunc)
   :obj:`numpy.radians`, :obj:`dask.array.radians`, direct (ufunc)
   :obj:`numpy.ravel`, :obj:`dask.array.ravel` [#3]_ [#4]_, dask equivalent
   :obj:`numpy.ravel_multi_index`, :obj:`dask.array.ravel_multi_index`, dask equivalent
   :obj:`numpy.real`, :obj:`dask.array.real`, direct (non-ufunc elementwise)
   :obj:`numpy.real_if_close`, \-
   :obj:`numpy.reciprocal`, :obj:`dask.array.reciprocal`, direct (ufunc)
   :obj:`numpy.remainder`, :obj:`dask.array.remainder`, direct (ufunc)
   :obj:`numpy.repeat`, :obj:`dask.array.repeat`, dask equivalent
   :obj:`numpy.require`, \-
   :obj:`numpy.reshape`, :obj:`dask.array.reshape`, dask equivalent
   :obj:`numpy.resize`, \-
   :obj:`numpy.result_type`, :obj:`dask.array.result_type`, dask equivalent
   :obj:`numpy.right_shift`, :obj:`dask.array.right_shift`, direct (ufunc)
   :obj:`numpy.rint`, :obj:`dask.array.rint`, direct (ufunc)
   :obj:`numpy.roll`, :obj:`dask.array.roll`, dask equivalent
   :obj:`numpy.rollaxis`, :obj:`dask.array.rollaxis`, dask equivalent
   :obj:`numpy.roots`, \-
   :obj:`numpy.rot90`, :obj:`dask.array.rot90`, dask equivalent
   :obj:`numpy.row_stack`, \-
   :obj:`numpy.save`, \-
   :obj:`numpy.savetxt`, \-
   :obj:`numpy.savez`, \-
   :obj:`numpy.savez_compressed`, \-
   :obj:`numpy.searchsorted`, :obj:`dask.array.searchsorted`, dask equivalent
   :obj:`numpy.select`, :obj:`dask.array.select`, dask equivalent
   :obj:`numpy.setdiff1d`, \-
   :obj:`numpy.setxor1d`, \-
   :obj:`numpy.shape`, :obj:`dask.array.shape` [#3]_, dask equivalent
   :obj:`numpy.shares_memory`, \-
   :obj:`numpy.sign`, :obj:`dask.array.sign`, direct (ufunc)
   :obj:`numpy.signbit`, :obj:`dask.array.signbit`, direct (ufunc)
   :obj:`numpy.sin`, :obj:`dask.array.sin`, direct (ufunc)
   :obj:`numpy.sinc`, :obj:`dask.array.sinc`, direct (non-ufunc elementwise)
   :obj:`numpy.sinh`, :obj:`dask.array.sinh`, direct (ufunc)
   :obj:`numpy.sort`, :obj:`dask.array.topk` [#5]_
   :obj:`numpy.sort_complex`, \-
   :obj:`numpy.source`, \-
   :obj:`numpy.spacing`, :obj:`dask.array.spacing`, direct (ufunc)
   :obj:`numpy.split`, \-
   :obj:`numpy.sqrt`, :obj:`dask.array.sqrt`, direct (ufunc)
   :obj:`numpy.square`, :obj:`dask.array.square`, direct (ufunc)
   :obj:`numpy.squeeze`, :obj:`dask.array.squeeze`, dask equivalent
   :obj:`numpy.stack`, :obj:`dask.array.stack`, dask equivalent
   :obj:`numpy.std`, :obj:`dask.array.std` [#1]_, dask equivalent
   :obj:`numpy.subtract`, :obj:`dask.array.subtract`, direct (ufunc)
   :obj:`numpy.sum`, :obj:`dask.array.sum` [#1]_ [#2]_, dask equivalent
   :obj:`numpy.swapaxes`, :obj:`dask.array.swapaxes`, dask equivalent
   :obj:`numpy.take`, :obj:`dask.array.take` [#8]_, dask equivalent
   :obj:`numpy.take_along_axis`, \-
   :obj:`numpy.tan`, :obj:`dask.array.tan`, direct (ufunc)
   :obj:`numpy.tanh`, :obj:`dask.array.tanh`, direct (ufunc)
   :obj:`numpy.tensordot`, :obj:`dask.array.tensordot`, dask equivalent
   :obj:`numpy.tile`, :obj:`dask.array.tile`, dask equivalent
   :obj:`numpy.trace`, :obj:`dask.array.trace` [#6]_, dask equivalent
   :obj:`numpy.transpose`, :obj:`dask.array.transpose`, dask equivalent
   :obj:`numpy.trapz`, \-
   :obj:`numpy.tri`, :obj:`dask.array.tri`, dask equivalent
   :obj:`numpy.tril`, :obj:`dask.array.tril`, dask equivalent
   :obj:`numpy.tril_indices`, :obj:`dask.array.tril_indices`, dask equivalent
   :obj:`numpy.tril_indices_from`, :obj:`dask.array.tril_indices_from`, dask equivalent
   :obj:`numpy.trim_zeros`, \-
   :obj:`numpy.triu`, :obj:`dask.array.triu`, dask equivalent
   :obj:`numpy.triu_indices`, :obj:`dask.array.triu_indices`, dask equivalent
   :obj:`numpy.triu_indices_from`, :obj:`dask.array.triu_indices_from`, dask equivalent
   :obj:`numpy.true_divide`, :obj:`dask.array.true_divide`, direct (ufunc)
   :obj:`numpy.trunc`, :obj:`dask.array.trunc`, direct (ufunc)
   :obj:`numpy.union1d`, :obj:`dask.array.union1d`, dask equivalent
   :obj:`numpy.unique`, :obj:`dask.array.unique` [#19]_, dask equivalent
   :obj:`numpy.unpackbits`, \-
   :obj:`numpy.unravel_index`, :obj:`dask.array.unravel_index`, dask equivalent
   :obj:`numpy.unwrap`, \-
   :obj:`numpy.vander`, \-
   :obj:`numpy.var`, :obj:`dask.array.var` [#1]_, dask equivalent
   :obj:`numpy.vdot`, :obj:`dask.array.vdot`, dask equivalent
   :obj:`numpy.vsplit`, \-
   :obj:`numpy.vstack`, :obj:`dask.array.vstack` [#20]_, dask equivalent
   :obj:`numpy.where`, :obj:`dask.array.where`, dask equivalent
   :obj:`numpy.zeros`, :obj:`dask.array.zeros`, dask equivalent
   :obj:`numpy.zeros_like`, :obj:`dask.array.zeros_like`, dask equivalent

.. rubric:: Footnotes

.. [#1] ``where`` parameter not supported.
.. [#2] ``initial`` parameter not supported.
.. [#3] Input must be a dask array.
.. [#4] ``order`` parameter not supported.
.. [#5] Sort operations are notoriously difficult to do in parallel. Parallel-friendly alternatives sort the k largest elements.
.. [#6] ``out`` parameter not supported.
.. [#7] Use of numpy.matrix is discouraged in NumPy and thus there is no need to add it.
.. [#8] ``mode`` parameter not supported.
.. [#9] ``keepdims`` parameter not supported.
.. [#10] ``fweights``, ``aweights``, ``dtype`` parameters not supported.
.. [#11] ``like`` parameter not supported. Callable functions not supported.
.. [#12] Not implemented with more than one output.
.. [#13] ``edge_order`` parameter not supported.
.. [#14] Chunking of the input data (sample) is only allowed along the 0th (row) axis.
.. [#15] Only implemented for monotonic ``obj`` arguments.
.. [#16] ``overwrite_input`` parameter not supported.
.. [#17] ``copy`` parameter not supported.
.. [#18] Dask implementation introduces an additional parameter ``method``.
.. [#19] ``axis`` parameter not supported.
.. [#20] ``casting`` parameter not supported.