numpy.arccosh() in Python Last Updated : 29 Nov, 2018 Comments Improve Suggest changes Like Article Like Report numpy.arccosh() : This mathematical function helps user to calculate inverse hyperbolic cosine, element-wise for all arr. Syntax : numpy.arccosh(arr, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, ufunc 'arccosh') Parameters : arr : array_like Input array. out : [ndarray, optional] A location into which the result is stored. -> If provided, it must have a shape that the inputs broadcast to. -> If not provided or None, a freshly-allocated array is returned. where : array_like, optional Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone. **kwargs :Allows to pass keyword variable length of argument to a function. Used when we want to handle named argument in a function. Return : An array with inverse hyperbolic cosine of arr for all arr i.e. array elements. Note : 2pi Radians = 360 degrees The convention is to return the angle of arr whose imaginary part lies in [-pi, pi] and the real part in [0, inf]. Code #1 : Working Python # Python program explaining # arccosh() function import numpy as np in_array = [2, 1, 10, 100] print ("Input array : \n", in_array) arccosh_Values = np.arccosh(in_array) print ("\nInverse hyperbolic Cosine values : \n", arccosh_Values) Output : Input array : [2, 1, 10, 100] Inverse hyperbolic Cosine values : [ 1.3169579 0. 2.99322285 5.29829237] Code #2 : Graphical representation Python # Python program showing # Graphical representation # of arccosh() function %matplotlib inline import numpy as np import matplotlib.pyplot as plt in_array = np.linspace(1, np.pi, 18) out_array1 = np.cos(in_array) out_array2 = np.arccosh(in_array) print("in_array : ", in_array) print("\nout_array with cos : ", out_array1) print("\nout_array with arccosh : ", out_array2) #blue for numpy.cosh() # red for numpy.arccosh() plt.plot(in_array, out_array1, color = 'blue', marker = ".") plt.plot(in_array, out_array2, color = 'red', marker = "+") plt.title("blue : numpy.cos() \nred : numpy.arccosh()") plt.xlabel("X") plt.ylabel("Y") Output : in_array : [ 1. 1.12597604 1.25195208 1.37792812 1.50390415 1.62988019 1.75585623 1.88183227 2.00780831 2.13378435 2.25976038 2.38573642 2.51171246 2.6376885 2.76366454 2.88964058 3.01561662 3.14159265] out_array with cos : [ 0.54030231 0.43029566 0.31346927 0.19167471 0.0668423 -0.0590495 -0.18400541 -0.30604504 -0.42323415 -0.53371544 -0.63573787 -0.72768451 -0.80809809 -0.87570413 -0.92943115 -0.96842762 -0.99207551 -1. ] out_array with arccosh : [ 0. 0.49682282 0.69574433 0.84411504 0.96590748 1.07053332 1.16287802 1.24587516 1.32145434 1.39096696 1.45540398 1.51551804 1.57189678 1.62500948 1.67523791 1.7228975 1.76825238 1.81152627] ) Comment More info J jana_sayantan Follow Improve Article Tags : Python Python-numpy Python numpy-Mathematical Function Explore Python FundamentalsPython Introduction 3 min read Input and Output in Python 4 min read Python Variables 5 min read Python Operators 5 min read Python Keywords 2 min read Python Data Types 8 min read Conditional Statements in Python 3 min read Loops in Python - For, While and Nested Loops 7 min read Python Functions 5 min read Recursion in Python 6 min read Python Lambda Functions 5 min read Python Data StructuresPython String 5 min read Python Lists 5 min read Python Tuples 4 min read Python Dictionary 3 min read Python Sets 6 min read Python Arrays 7 min read List Comprehension in Python 4 min read Advanced PythonPython OOP Concepts 11 min read Python Exception Handling 5 min read File Handling in Python 4 min read Python Database Tutorial 4 min read Python MongoDB Tutorial 2 min read Python MySQL 9 min read Python Packages 12 min read Python Modules 7 min read Python DSA Libraries 15 min read List of Python GUI Library and Packages 3 min read Data Science with PythonNumPy Tutorial - Python Library 3 min read Pandas Tutorial 6 min read Matplotlib Tutorial 5 min read Python Seaborn Tutorial 15+ min read StatsModel Library- Tutorial 4 min read Learning Model Building in Scikit-learn 8 min read TensorFlow Tutorial 2 min read PyTorch Tutorial 7 min read Web Development with PythonFlask Tutorial 8 min read Django Tutorial | Learn Django Framework 7 min read Django ORM - Inserting, Updating & Deleting Data 4 min read Templating With Jinja2 in Flask 6 min read Django Templates 7 min read Python | Build a REST API using Flask 3 min read How to Create a basic API using Django Rest Framework ? 4 min read Python PracticePython Quiz 3 min read Python Coding Practice 1 min read Python Interview Questions and Answers 15+ min read Like