numpy.expm1() in Python

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numpy.expm1(array, out = None, where = True, casting = ‘same_kind’, order = ‘K’, dtype = None) :
This mathematical function helps user to calculate exponential of all the elements subtracting 1 from all the input 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 exponential(all elements of input array) - 1.

Code 1 : Working

# Python program explaining 
# expm1() function 
  
import numpy as np 
  
in_array = [1, 3, 5] 
print ("Input array : \n", in_array) 
  
exp_values = np.exp(in_array) 
print ("\nExponential value of array element : "
       "\n", exp_values) 
  
expm1_values = np.expm1(in_array) 
print ("\n(Exponential value of array element) - (1) "
       ": \n", expm1_values) 

Output :

Input array : 
 [1, 3, 5]

Exponential value of array element : 
 [   2.71828183   20.08553692  148.4131591 ]

(Exponential value of array element) - (1) : 
 [   1.71828183   19.08553692  147.4131591 ]

Code 2 : Graphical representation

# Python program showing 
# Graphical representation of  
# expm1() function 
  
import numpy as np 
import matplotlib.pyplot as plt 
  
in_array = [1, 1.2, 1.4, 1.6, 1.8, 2] 
out_array = np.expm1(in_array) 
  
print("out_array : ", out_array) 
  
y = [1, 1.2, 1.4, 1.6, 1.8, 2] 
plt.plot(in_array, y, color = 'blue', marker = "*") 
  
# red for numpy.expm1() 
plt.plot(out_array, y, color = 'red', marker = "o") 
plt.title("numpy.expm1()") 
plt.xlabel("X") 
plt.ylabel("Y") 
plt.show()   