numpy.frompyfunc() in Python
Last Updated :
29 Jun, 2021
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numpy.frompyfunc(func, nin, nout) function allows to create an arbitrary Python function as Numpy ufunc (universal function).
Parameters:
func: [A python function object ] An arbitrary python function
nin: [int] Number of input arguments to that function.
nout: [int] Number of objects returned by that function.
Return: A Numpy universal function object.
For example, abs_value = numpy.frompyfunc(abs, 1, 1) will create a ufunc that will return the absolute values of array elements.
Code #1:
# Python code to demonstrate the
# use of numpy.frompyfunc
import numpy as np
# create an array of numbers
a = np.array([34, 67, 89, 15, 33, 27])
# python str function as ufunc
string_generator = np.frompyfunc(str, 1, 1)
print("Original array-", a)
print("After conversion to string-", string_generator(a))
Output:
Original array- [34 67 89 15 33 27] After conversion to string- ['34' '67' '89' '15' '33' '27']
Code #2:
# Python code to demonstrate
# user-defined function as ufunc
import numpy as np
# create an array of numbers
a = np.array([345, 122, 454, 232, 334, 56, 66])
# user-defined function to check
# whether a no. is palindrome or not
def fun(x):
s = str(x)
return s[::-1]== s
# 'check_palindrome' as universal function
check_palindrome = np.frompyfunc(fun, 1, 1)
print("Original array-", a)
print("Checking of number as palindrome-",
check_palindrome(a))
Output:
Original array- [345 122 454 232 334 56 66] Checking of number as palindrome- [False False True True False False True]
Note: This custom ufunc created using frompyfunc always accept a ndarray as an input argument and also return a ndarray object as output.
