numpy.expm1() in Python

numpy.exp2() in Python

Last Updated : 29 Nov, 2018

numpy.exp2(array, out = None, where = True, casting = 'same_kind', order = 'K', dtype = None) : This mathematical function helps user to calculate 2**x for all x being the array elements. Parameters :

array : [array_like]Input array or object whose elements, we need to test. out : [ndarray, optional]Output array with same dimensions as Input array, placed with result. **kwargs : Allows you to pass keyword variable length of argument to a function. It is 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 :

An array with 2**x(power of 2) for all x i.e. array elements

Code 1 : Working

Python

# Python program explaining
# exp2() function
import numpy as np

in_array = [1, 3, 5, 4]
print ("Input array : \n", in_array)

exp2_values = np.exp2(in_array)
print ("\n2**x values : \n", exp2_values)

Output :

Input array : 
 [1, 3, 5, 4]

2**x values : 
 [  2.   8.  32.  16.]

Code 2 : Graphical representation

Python

# Python program showing
# Graphical representation of 
# exp2() function
import numpy as np
import matplotlib.pyplot as plt

in_array = [1, 2, 3, 4, 5 ,6]
out_array = np.exp2(in_array)

print("out_array : ", out_array)

y = [1, 2, 3, 4, 5 ,6]
plt.plot(in_array, y, color = 'blue', marker = "*")

# red for numpy.exp2()
plt.plot(out_array, y, color = 'red', marker = "o")
plt.title("numpy.exp2()")
plt.xlabel("X")
plt.ylabel("Y")
plt.show()

Output : out_array : [ 2. 4. 8. 16. 32. 64.]

References : https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.exp2.html .

numpy.expm1() in Python

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