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() |
Output :
out_array : [ 1.71828183 2.32011692 3.05519997 3.95303242 5.04964746 6.3890561 ]
References :
https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.expm1.html#numpy.expm1
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