numpy.exp() in Python
numpy.exp(array, out = None, where = True, casting = ‘same_kind’, order = ‘K’, dtype = None) :
This mathematical function helps user to calculate exponential of all the elements in the input array.
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 of all elements of input array.
Code 1 : Working
# Python program explaining # exp() function import numpy as np in_array = [1, 3, 5] print ("Input array : ", in_array) out_array = np.exp(in_array) print ("Output array : ", out_array) |
Output :
Input array : [1, 3, 5] Output array : [ 2.71828183 20.08553692 148.4131591 ]
Code 2 : Graphical representation
# Python program showing # Graphical representation of # exp() 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.exp(in_array) y = [1, 1.2, 1.4, 1.6, 1.8, 2] plt.plot(in_array, y, color = 'blue', marker = "*") # red for numpy.exp() plt.plot(out_array, y, color = 'red', marker = "o") plt.title("numpy.exp()") plt.xlabel("X") plt.ylabel("Y") plt.show() |
Output :
References :
https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.exp.html
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