numpy.full_like
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numpy.full_like(a, fill_value, dtype=None, order='K', subok=True, shape=None)
[source] -
Return a full array with the same shape and type as a given array.
- Parameters
-
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aarray_like
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The shape and data-type of
a
define these same attributes of the returned array. -
fill_valuescalar
-
Fill value.
-
dtypedata-type, optional
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Overrides the data type of the result.
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order{‘C’, ‘F’, ‘A’, or ‘K’}, optional
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Overrides the memory layout of the result. ‘C’ means C-order, ‘F’ means F-order, ‘A’ means ‘F’ if
a
is Fortran contiguous, ‘C’ otherwise. ‘K’ means match the layout ofa
as closely as possible. -
subokbool, optional.
-
If True, then the newly created array will use the sub-class type of ‘a’, otherwise it will be a base-class array. Defaults to True.
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shapeint or sequence of ints, optional.
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Overrides the shape of the result. If order=’K’ and the number of dimensions is unchanged, will try to keep order, otherwise, order=’C’ is implied.
New in version 1.17.0.
-
- Returns
-
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outndarray
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Array of
fill_value
with the same shape and type asa
.
-
See also
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empty_like
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Return an empty array with shape and type of input.
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ones_like
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Return an array of ones with shape and type of input.
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zeros_like
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Return an array of zeros with shape and type of input.
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full
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Return a new array of given shape filled with value.
Examples
>>> x = np.arange(6, dtype=int) >>> np.full_like(x, 1) array([1, 1, 1, 1, 1, 1]) >>> np.full_like(x, 0.1) array([0, 0, 0, 0, 0, 0]) >>> np.full_like(x, 0.1, dtype=np.double) array([0.1, 0.1, 0.1, 0.1, 0.1, 0.1]) >>> np.full_like(x, np.nan, dtype=np.double) array([nan, nan, nan, nan, nan, nan])
>>> y = np.arange(6, dtype=np.double) >>> np.full_like(y, 0.1) array([0.1, 0.1, 0.1, 0.1, 0.1, 0.1])
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Licensed under the 3-clause BSD License.
https://numpy.org/doc/1.19/reference/generated/numpy.full_like.html