numpy.log1p() in Python Last Updated : 29 Nov, 2018 Suggest changes Share Like Article Like Report numpy.log1p(arr, out = None, *, where = True, casting = 'same_kind', order = 'K', dtype = None, ufunc 'log1p') : This mathematical function helps user to calculate natural logarithmic value of x+1 where x belongs to all the input array elements. log1p is reverse of exp(x) - 1. Parameters : array : [array_like]Input array or object. 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 natural logarithmic value of x + 1; where x belongs to all elements of input array. Code 1 : Working Python # Python program explaining # log1p() function import numpy as np in_array = [1, 3, 5] print ("Input array : ", in_array) out_array = np.log1p(in_array) print ("Output array : ", out_array) Output : Input array : [1, 3, 5] Output array : [ 0.69314718 1.38629436 1.79175947] Code 2 : Graphical representation Python # Python program showing # Graphical representation of # log1p() 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.log1p(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.log1xp() plt.plot(out_array, y, color = 'red', marker = "o") plt.title("numpy.log1p()") plt.xlabel("X") plt.ylabel("Y") plt.show() Output : out_array : [ 0.69314718 0.78845736 0.87546874 0.95551145 1.02961942 1.09861229] References : https://docs.scipy.org/doc/numpy-1.13.0/reference/generated/numpy.exp.html . M mohit gupta_omg :) Follow Article Tags : Python Python-numpy Python numpy-Mathematical Function Explore Python FundamentalsPython Introduction 2 min read Input and Output in Python 4 min read Python Variables 5 min read Python Operators 4 min read Python Keywords 2 min read Python Data Types 7 min read Conditional Statements in Python 3 min read Loops in Python - For, While and Nested Loops 5 min read Python Functions 5 min read Recursion in Python 4 min read Python Lambda Functions 5 min read Python Data StructuresPython String 5 min read Python Lists 4 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 10 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 4 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 6 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 1 min read My Profile ${profileImgHtml} My Profile Edit Profile My Courses Join Community Transactions Logout Like