The numpy.reciprocal() is a mathematical function that is used to calculate reciprocal of all the elements in the input array.
Syntax :numpy.reciprocal(x, /, out=None, *, where=True)
Parameters :x[array_like]: Input array or object whose elements needed to test.
out [ndarray, optional]: A location into which the result is stored.
–> If provided, it must have a shape that the inputs broadcast to.
–> If not provided or None, a freshly-allocated array is returned.**kwargs : Allows to pass keyword variable length of argument to a function. Used when we want to handle named argument in a function.
where [array_like, optional]: True value means to calculate the universal functions(ufunc) at that position, False value means to leave the value in the output alone.
Return :
y : ndarray. This is a scalar if x is a scalar.
Note: For integer arguments with absolute value larger than 1, the result is always zero because of the way Python handles integer division. For integer zero the result is an overflow.
Code #1 :
# Python3 code demonstrate reciprocal() function # importing numpy import numpy as np in_num = 2.0print ("Input number : ", in_num) out_num = np.reciprocal(in_num) print ("Output number : ", out_num) |
Output :
Input number : 2.0 Output number : 0.5
Code #2 :
# Python3 code demonstrate reciprocal() function # importing numpy import numpy as np in_arr = [2., 3., 8.] print ("Input array : ", in_arr) out_arr = np.reciprocal(in_arr) print ("Output array : ", out_arr) |
Output :
Input array : [2.0, 3.0, 8.0] Output array : [ 0.5 0.33333333 0.125 ]
Code #3 : Exception in reciprocal() function. Result is always zero.
# Python3 code demonstrate Exception in reciprocal() function # importing numpy import numpy as np in_arr = [2, 3, 8] print ("Input array : ", in_arr) out_arr = np.reciprocal(in_arr) print ("Output array : ", out_arr) |
Output :
Input array : [2, 3, 8] Output array : [0 0 0]
… [Trackback]
[…] Read More Info here to that Topic: geeksforgeeks.org/numpy-reciprocal-in-python/ […]