NumPy: broadcast_to() function
numpy.broadcast_to() function
The broadcast_to() function is used to produce an object that mimics broadcasting.
Syntax:
numpy.broadcast_to(array, shape, subok=False)
Version: 1.15.0
Parameter:
Name | Description | Required / Optional |
---|---|---|
array | The array to broadcast. | Required |
shape | The shape of the desired array. | Required |
subok | If True, then sub-classes will be passed-through, otherwise the returned array will be forced to be a base-class array (default). | Optional |
Return value:
If True, then sub-classes will be passed-through, otherwise the returned array will be forced to be a base-class array (default).
Raises: ValueError - If the array is not compatible with the new shape according to NumPy’s broadcasting rules.
Example-1: numpy.broadcast_to()
>>> import numpy as np
>>> a = np.array([2,3,4])
>>> np.broadcast_to(a, (3, 3))
array([[2, 3, 4],
[2, 3, 4],
[2, 3, 4]])
Pictorial Presentation:
Example-2: numpy.broadcast_to()
>>> import numpy as np
>>> from numpy import array
>>> x = array([[2, 3, 4], [2, 3, 4]])
>>> print(x.shape)
(2, 3)
Pictorial Presentation:
Example-3: numpy.broadcast_to()
>>> import numpy as np
>>> y = array([2, 3])
>>> print(y.shape)
(2,)
Pictorial Presentation:
Example-4: numpy.broadcast_to()
>>> import numpy as np
>>> x = np.ma.array([2, 3, 4], mask=[False, True, False])
>>> y = np.broadcast_to(x, (3, 3), subok=True)
>>> y.mask
False
>>> y.mask = np.broadcast_to(x.mask, y.shape)
>>> y
masked_array(data =
[[2 -- 4]
[2 -- 4]
[2 -- 4]],
mask =
[[False True False]
[False True False]
[False True False]],
fill_value = 999999)
Python - NumPy Code Editor:
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