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Module « numpy.matlib »

Fonction delete - module numpy.matlib

Signature de la fonction delete

def delete(arr, obj, axis=None) 

Description

help(numpy.matlib.delete)

Return a new array with sub-arrays along an axis deleted. For a one
dimensional array, this returns those entries not returned by
`arr[obj]`.

Parameters
----------
arr : array_like
    Input array.
obj : slice, int, array-like of ints or bools
    Indicate indices of sub-arrays to remove along the specified axis.

    .. versionchanged:: 1.19.0
        Boolean indices are now treated as a mask of elements to remove,
        rather than being cast to the integers 0 and 1.

axis : int, optional
    The axis along which to delete the subarray defined by `obj`.
    If `axis` is None, `obj` is applied to the flattened array.

Returns
-------
out : ndarray
    A copy of `arr` with the elements specified by `obj` removed. Note
    that `delete` does not occur in-place. If `axis` is None, `out` is
    a flattened array.

See Also
--------
insert : Insert elements into an array.
append : Append elements at the end of an array.

Notes
-----
Often it is preferable to use a boolean mask. For example:

>>> arr = np.arange(12) + 1
>>> mask = np.ones(len(arr), dtype=bool)
>>> mask[[0,2,4]] = False
>>> result = arr[mask,...]

Is equivalent to ``np.delete(arr, [0,2,4], axis=0)``, but allows further
use of `mask`.

Examples
--------
>>> import numpy as np
>>> arr = np.array([[1,2,3,4], [5,6,7,8], [9,10,11,12]])
>>> arr
array([[ 1,  2,  3,  4],
       [ 5,  6,  7,  8],
       [ 9, 10, 11, 12]])
>>> np.delete(arr, 1, 0)
array([[ 1,  2,  3,  4],
       [ 9, 10, 11, 12]])

>>> np.delete(arr, np.s_[::2], 1)
array([[ 2,  4],
       [ 6,  8],
       [10, 12]])
>>> np.delete(arr, [1,3,5], None)
array([ 1,  3,  5,  7,  8,  9, 10, 11, 12])

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