NumPy: numpy.copyto() function
numpy.copyto() function
The numpy.copyto() function is used to copy values from one array to another, broadcasting as necessary.
The numpy.copyto() function can be useful when we want to copy the values of one array to another array with different dimensions, shapes, or sizes. It provides the flexibility to copy values into the specified output array or a new array can be created and values can be copied. One important thing to note that the function raises a TypeError if the casting rule is violated, and if where is provided, it selects which elements to copy.
Syntax:
numpy.copyto(dst, src, casting=’same_kind’, where=True)
Parameters:
Name | Description | Required / Optional |
---|---|---|
dst | The array into which values are copied. | Required |
src | The array from which values are copied. | Required |
casting | Controls what kind of data
casting may occur when copying.
|
Optional |
where | A boolean array which is broadcasted to match the dimensions of dst, and selects elements to copy from src to dst wherever it contains the value True. | Optional |
Example: Copy the values from one array to another array using numpy.copyto()
import numpy as np
# Creating two numpy arrays of the same shape
arr1 = np.array([1, 2, 3])
arr2 = np.array([4, 5, 6])
# Using copyto() to copy the values from arr1 to arr2
np.copyto(arr2, arr1)
print("arr1: ", arr1)
print("arr2: ", arr2)
Output:
arr1: [1 2 3] arr2: [1 2 3]
In the above example, the numpy.copyto() function is used to copy values from one array to another (Values from arr1 are copied to arr2).
Example: Copy the values from list to array using numpy.copyto()
import numpy as np
# Creating a numpy array and a Python list
arr1 = np.array([1, 2, 3])
lst = [4, 5, 6]
# Using copyto() to copy the values from lst to arr1
np.copyto(arr1, lst)
print("arr1: ", arr1)
Output:
arr1: [4 5 6]
In the above example, the numpy.copyto() function values from the Python list 'lst' are copied to the 'arr1' numpy array.
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