numpy.expm1 () in Python



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
function # expm1 ()

 

import numpy as np

 

in_array = [ 1 , 3 , 5 ]

print ( "Input array:" , in_array)

  

exp_values ​​ = np .exp (in_array)

print ( "Exponential value of array element:"

"" , exp_values)

 

expm1_values ​​ = np.expm1 (in_array)

print ( "(Exponential value of array element) - (1)"

":" , 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

Output:
out_array: [1.71828183 2.32011692 3.05519997 3.95303242 5.04964746 6.3890561]

Links:
https://docs.scipy.org/doc/numpy -1.13.0 / reference / generated / numpy.expm1.html # numpy.expm1
,


# Show Python program
# Graphical view
function # expm1 ( )

 

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 ()