Np expand_dims | Numpy expand_dims() Contoh dengan Python #python #numpy #np #programming Numpy expand_dims() memperluas bentuk array. np expand_dims menyisipkan sumbu baru yang akan muncul pada posisi sumbu dalam bentuk array yang diperluas.
Metode numpy expand_dims() memperluas bentuk array. np expand_dims menyisipkan sumbu baru yang akan muncul pada posisi sumbu dalam bentuk array yang diperluas.
Metode Python Numpy expand_dims() memperluas array dengan memasukkan sumbu baru pada posisi yang ditentukan. Fungsi ini membutuhkan dua parameter.
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With the help of Numpy.expand_dims() method, we can get the expanded dimensions of an array by using Numpy.expand_dims() method.
Syntax : Numpy.expand_dims()
Return : Return the expanded array.
Example #1 :
In this example we can see that using Numpy.expand_dims() method, we are able to get the expanded array using this method.
import numpy as np
gfg = np.array([1, 2])
print(gfg.shape)
gfg = np.expand_dims(gfg, axis = 0)
print(gfg.shape)
Output :
(2, )
(1, 2)
Example #2 :
import numpy as np
gfg = np.array([[1, 2], [7, 8]])
print(gfg.shape)
gfg = np.expand_dims(gfg, axis = 0)
print(gfg.shape)
Output :
(2, 2)
(1, 2, 2)
Expand the shape of an array.
Insert a new axis that will appear at the axis position in the expanded array shape.
Parametersaarray_likeInput array.
axisint or tuple of intsPosition in the expanded axes where the new axis (or axes) is placed.
Deprecated since version 1.13.0: Passing an axis where axis > a.ndim will be treated as axis == a.ndim, and passing axis < -a.ndim - 1 will be treated as axis == 0. This behavior is deprecated.
Changed in version 1.18.0: A tuple of axes is now supported. Out of range axes as described above are now forbidden and raise an AxisError.
ReturnsresultndarrayView of a with the number of dimensions increased.
Examples
>>> x = np.array([1, 2]) >>> x.shape (2,)
The following is equivalent to x[np.newaxis, :] or x[np.newaxis]:
>>> y = np.expand_dims(x, axis=0) >>> y array([[1, 2]]) >>> y.shape (1, 2)
The following is equivalent to x[:, np.newaxis]:
>>> y = np.expand_dims(x, axis=1) >>> y array([[1], [2]]) >>> y.shape (2, 1)
axis may also be a tuple:
>>> y = np.expand_dims(x, axis=(0, 1)) >>> y array([[[1, 2]]])
>>> y = np.expand_dims(x, axis=(2, 0)) >>> y array([[[1], [2]]])
Note that some examples may use None instead of np.newaxis. These are the same objects:
>>> np.newaxis is None True