The
full() and full_like()
functions are new additions to NumPy meant to facilitate initialization. Here's what the documentation says about them:
>>> help(np.full) Return a new array of given shape and type, filled with `fill_value`. >>> help(np.full_like) Return a full array with the same shape and type as a given array.
Let's see how full() and full_like() function:
Create a
1by2array withfull(), filled with the lucky number7:print(np.full((1, 2), 7))
Accordingly, we get the following array:
array([[ 7., 7.]])The array elements are floating-point numbers.
Specify an integer data type, as follows:
print(np.full((1, 2), 7, dtype=np.int))
The output changes accordingly:
array([[7, 7]])The
full_like()function checks the metadata of an array and reuses it for the new array. For example, create an array usinglinspace(), and apply it as a template for thefull_like()function:a =...