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Function transpose

numpy/core/fromnumeric.py:589–655  ·  view source on GitHub ↗

Returns an array with axes transposed. For a 1-D array, this returns an unchanged view of the original array, as a transposed vector is simply the same vector. To convert a 1-D array into a 2-D column vector, an additional dimension must be added, e.g., ``np.atleast2d(a).T`` ac

(a, axes=None)

Source from the content-addressed store, hash-verified

587
588@array_function_dispatch(_transpose_dispatcher)
589def transpose(a, axes=None):
590 """
591 Returns an array with axes transposed.
592
593 For a 1-D array, this returns an unchanged view of the original array, as a
594 transposed vector is simply the same vector.
595 To convert a 1-D array into a 2-D column vector, an additional dimension
596 must be added, e.g., ``np.atleast2d(a).T`` achieves this, as does
597 ``a[:, np.newaxis]``.
598 For a 2-D array, this is the standard matrix transpose.
599 For an n-D array, if axes are given, their order indicates how the
600 axes are permuted (see Examples). If axes are not provided, then
601 ``transpose(a).shape == a.shape[::-1]``.
602
603 Parameters
604 ----------
605 a : array_like
606 Input array.
607 axes : tuple or list of ints, optional
608 If specified, it must be a tuple or list which contains a permutation
609 of [0,1,...,N-1] where N is the number of axes of `a`. The `i`'th axis
610 of the returned array will correspond to the axis numbered ``axes[i]``
611 of the input. If not specified, defaults to ``range(a.ndim)[::-1]``,
612 which reverses the order of the axes.
613
614 Returns
615 -------
616 p : ndarray
617 `a` with its axes permuted. A view is returned whenever possible.
618
619 See Also
620 --------
621 ndarray.transpose : Equivalent method.
622 moveaxis : Move axes of an array to new positions.
623 argsort : Return the indices that would sort an array.
624
625 Notes
626 -----
627 Use ``transpose(a, argsort(axes))`` to invert the transposition of tensors
628 when using the `axes` keyword argument.
629
630 Examples
631 --------
632 >>> a = np.array([[1, 2], [3, 4]])
633 >>> a
634 array([[1, 2],
635 [3, 4]])
636 >>> np.transpose(a)
637 array([[1, 3],
638 [2, 4]])
639
640 >>> a = np.array([1, 2, 3, 4])
641 >>> a
642 array([1, 2, 3, 4])
643 >>> np.transpose(a)
644 array([1, 2, 3, 4])
645
646 >>> a = np.ones((1, 2, 3))

Callers 3

apply_along_axisFunction · 0.90
argwhereFunction · 0.70
moveaxisFunction · 0.70

Calls 1

_wrapfuncFunction · 0.85

Tested by

no test coverage detected