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Function stack

numpy/_core/shape_base.py:379–466  ·  view source on GitHub ↗

Join a sequence of arrays along a new axis. The ``axis`` parameter specifies the index of the new axis in the dimensions of the result. For example, if ``axis=0`` it will be the first dimension and if ``axis=-1`` it will be the last dimension. Parameters ---------- arr

(arrays, axis=0, out=None, *, dtype=None, casting="same_kind")

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377
378@array_function_dispatch(_stack_dispatcher)
379def stack(arrays, axis=0, out=None, *, dtype=None, casting="same_kind"):
380 """
381 Join a sequence of arrays along a new axis.
382
383 The ``axis`` parameter specifies the index of the new axis in the
384 dimensions of the result. For example, if ``axis=0`` it will be the first
385 dimension and if ``axis=-1`` it will be the last dimension.
386
387 Parameters
388 ----------
389 arrays : sequence of ndarrays
390 Each array must have the same shape. In the case of a single ndarray
391 array_like input, it will be treated as a sequence of arrays; i.e.,
392 each element along the zeroth axis is treated as a separate array.
393
394 axis : int, optional
395 The axis in the result array along which the input arrays are stacked.
396
397 out : ndarray, optional
398 If provided, the destination to place the result. The shape must be
399 correct, matching that of what stack would have returned if no
400 out argument were specified.
401
402 dtype : str or dtype
403 If provided, the destination array will have this dtype. Cannot be
404 provided together with `out`.
405
406 .. versionadded:: 1.24
407
408 casting : {'no', 'equiv', 'safe', 'same_kind', 'unsafe'}, optional
409 Controls what kind of data casting may occur. Defaults to 'same_kind'.
410
411 .. versionadded:: 1.24
412
413
414 Returns
415 -------
416 stacked : ndarray
417 The stacked array has one more dimension than the input arrays.
418
419 See Also
420 --------
421 concatenate : Join a sequence of arrays along an existing axis.
422 block : Assemble an nd-array from nested lists of blocks.
423 split : Split array into a list of multiple sub-arrays of equal size.
424 unstack : Split an array into a tuple of sub-arrays along an axis.
425
426 Examples
427 --------
428 >>> import numpy as np
429 >>> rng = np.random.default_rng()
430 >>> arrays = [rng.normal(size=(3,4)) for _ in range(10)]
431 >>> np.stack(arrays, axis=0).shape
432 (10, 3, 4)
433
434 >>> np.stack(arrays, axis=1).shape
435 (3, 10, 4)
436

Callers 10

test_start_stop_arrayMethod · 0.90
test_base_arrayMethod · 0.90
test_stop_base_arrayMethod · 0.90
test_start_stop_arrayMethod · 0.90
test_start_stop_arrayMethod · 0.90
test_stackFunction · 0.90
test_stack_out_and_dtypeFunction · 0.90
test_stack_1dMethod · 0.85
test_stack_masksMethod · 0.85
test_stack_ndMethod · 0.85

Calls 2

asanyarrayFunction · 0.85
sliceFunction · 0.85

Tested by 10

test_start_stop_arrayMethod · 0.72
test_base_arrayMethod · 0.72
test_stop_base_arrayMethod · 0.72
test_start_stop_arrayMethod · 0.72
test_start_stop_arrayMethod · 0.72
test_stackFunction · 0.72
test_stack_out_and_dtypeFunction · 0.72
test_stack_1dMethod · 0.68
test_stack_masksMethod · 0.68
test_stack_ndMethod · 0.68

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