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To create you own ufunc, you have to define a function, like you do with normal functions in Python, then youadd it to your NumPy ufunc library with the frompyfunc() method
To create you own ufunc, you have to define a function, like you do with normal functions in Python, then you
add it to your NumPy ufunc library with the frompyfunc() method.
The frompyfunc() method takes the following arguments:
function - the name of the function.inputs - the number of input arguments (arrays).outputs - the number of output arrays.Create your own ufunc for addition:
import numpy as np
def myadd(x, y):
return x+y
myadd = np.frompyfunc(myadd, 2, 1)
print(myadd([1, 2,
3, 4], [5, 6, 7, 8]))
Check the type of a function to check if it is a ufunc or not.
A ufunc should return <class 'numpy.ufunc'>.
Check if a function is a ufunc:
import numpy as np
print(type(np.add))
If it is not a ufunc, it will return another type, like this built-in NumPy function for joining two or more arrays:
Check the type of another function: concatenate():
import numpy as np
print(type(np.concatenate))
If the function is not recognized at all, it will return an error:
Check the type of something that does not exist. This will produce an error:
import numpy as np
print(type(np.blahblah))
To test if the function is a ufunc in an if statement, use the numpy.ufunc value
(or np.ufunc if you use np as an alias for numpy):
Use an if statement to check if the function is a ufunc or not:
import numpy as np
if type(np.add) == np.ufunc:
print('add is ufunc')
else:
print('add is not ufunc')