numpy.log() in Python
The numpy.log() is a mathematical function that helps user to calculate Natural logarithm of x where x belongs to all the input array elements.
Natural logarithm log is the inverse of the exp(), so that log(exp(x)) = x. The natural logarithm is log in base e.
Syntax :numpy.log(x[, out] = ufunc ‘log1p’)
Parameters :array : [array_like] Input array or object.
out : [ndarray, optional] Output array with same dimensions as Input array, placed with result.Return :
An array with Natural logarithmic value of x; where x belongs to all elements of input array.
Code #1 : Working
# Python program explaining# log() functionimport numpy as np in_array = [1, 3, 5, 2**8]print ("Input array : ", in_array) out_array = np.log(in_array)print ("Output array : ", out_array) print("\nnp.log(4**4) : ", np.log(4**4))print("np.log(2**8) : ", np.log(2**8)) |
Output :
Input array : [1, 3, 5, 256] Output array : [ 0. 1.09861229 1.60943791 5.54517744] np.log(4**4) : 5.54517744448 np.log(2**8) : 5.54517744448
Code #2 : Graphical representation
# Python program showing# Graphical representation # of log() functionimport numpy as npimport matplotlib.pyplot as plt in_array = [1, 1.2, 1.4, 1.6, 1.8, 2]out_array = np.log(in_array) print ("out_array : ", out_array) plt.plot(in_array, in_array, color = 'blue', marker = "*") # red for numpy.log()plt.plot(out_array, in_array, color = 'red', marker = "o") plt.title("numpy.log()")plt.xlabel("out_array")plt.ylabel("in_array")plt.show() |
Output :
out_array : [ 0. 0.18232156 0.33647224 0.47000363 0.58778666 0.69314718]
References : https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.log.html#numpy.log
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Last Updated on November 1, 2021 by admin