numpy.sinc() in Python Last Updated : 29 Nov, 2018 Comments Improve Suggest changes Like Article Like Report numpy.sinc(array) : This mathematical function helps user to calculate sinc function for all x(being the array elements). Parameters : array : [array_like] elements are in radians. 2pi Radians = 36o degrees Return : An array with sinc value of x for all x i.e. array elements. Code #1 : Working Python3 1== # Python3 program explaining # sinc() function import numpy as np import math in_array = [0, math.pi / 2, np.pi / 3, np.pi] print ("Input array : \n", in_array) sinc_Values = np.sinc(in_array) print ("\nSinc values : \n", sinc_Values) Output: Input array : [0, 1.5707963267948966, 1.0471975511965976, 3.141592653589793] Sinc values : [ 1. -0.19765087 -0.04490537 -0.04359863] Code #2 : Graphical Representation Python3 1== # Python program showing Graphical # representation of sinc() function import numpy as np import matplotlib.pyplot as plt in_array = np.linspace(-np.pi, np.pi, 12) out_array = np.sinc(in_array) print("in_array : ", in_array) print("\nout_array : ", out_array) # red for numpy.sinc() plt.plot(in_array, out_array, color = 'red', marker = "o") plt.title("numpy.sinc()") plt.xlabel("X") plt.ylabel("Y") plt.show() Output: in_array : [-3.14159265 -2.57039399 -1.99919533 -1.42799666 -0.856798 -0.28559933 0.28559933 0.856798 1.42799666 1.99919533 2.57039399 3.14159265] out_array : [-4.35986286e-02 1.20821077e-01 -4.02499006e-04 -2.17227951e-01 1.61555129e-01 8.71125992e-01 8.71125992e-01 1.61555129e-01 -2.17227951e-01 -4.02499006e-04 1.20821077e-01 -4.35986286e-02] Comment More infoAdvertise with us Next Article numpy.sinc() in Python M mohit gupta_omg :) Follow Improve Article Tags : Python Python-numpy Python numpy-Mathematical Function Practice Tags : python Similar Reads numpy.sin() in Python numpy.sin(x[, out]) = ufunc 'sin') : This mathematical function helps user to calculate trigonometric sine for all x(being the array elements). Parameters : array : [array_like]elements are in radians. 2pi Radians = 36o degrees Return : An array with trigonometric sine of x for all x i.e. array elem 1 min read numpy.sinh() in Python The numpy.sinh() is a mathematical function that helps user to calculate hyperbolic sine for all x(being the array elements). Equivalent to 1/2 * (np.exp(x) - np.exp(-x)) or -1j * np.sin(1j*x). Syntax: numpy.sinh(x[, out]) = ufunc 'sin') Parameters : array : [array_like] elements are in radians. 2pi 2 min read numpy.tan() in Python numpy.tan(array[, out]) = ufunc 'tan') : This mathematical function helps user to calculate trigonometric tangent for all x(being the array elements). Parameters : array : [array_like]elements are in radians. out : [optional]shape same as array. 2pi Radians = 360 degrees tan(x) = sin(x) / cos(x) Ret 2 min read numpy.std() in Python numpy.std() is a function provided by the NumPy library that calculates the standard deviation of an array or a set of values. Standard deviation is a measure of the amount of variation or dispersion of a set of values.\text{Standard Deviation} = \sqrt{\text{mean} \left( (x - x.\text{mean}())^2 \rig 3 min read numpy.sqrt() in Python numpy.sqrt() in Python is a function from the NumPy library used to compute the square root of each element in an array or a single number. It returns a new array of the same shape with the square roots of the input values. The function handles both positive and negative numbers, returning NaN for n 2 min read Like