Data Structure
Networking
RDBMS
Operating System
Java
MS Excel
iOS
HTML
CSS
Android
Python
C Programming
C++
C#
MongoDB
MySQL
Javascript
PHP
- Selected Reading
- UPSC IAS Exams Notes
- Developer's Best Practices
- Questions and Answers
- Effective Resume Writing
- HR Interview Questions
- Computer Glossary
- Who is Who
Compute Truth Value of Array Element-wise in NumPy
To compute the truth value of an array OR another array element-wise, use the numpy.logical_or() method in Python Numpy. Return value is either True or False. Return value is the boolean result of the logical OR operation applied to the elements of x1 and x2; the shape is determined by broadcasting. This is a scalar if both x1 and x2 are scalars
The out is 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. A tuple (possible only as a keyword argument) must have length equal to the number of outputs.
Steps
At first, import the required library −
import numpy as np
Creating two 2D numpy array using the array() method. We have inserted elements −
arr1 = np.array([[True, False, False], [False, True, True]]) arr2 = np.array([[True, False, True], [True, True, False]])
Display the arrays −
print("Array 1...", arr1) print("Array 2...", arr2)
Get the type of the arrays −
print("Our Array 1 type...", arr1.dtype) print("Our Array 2 type...", arr2.dtype)
Get the dimensions of the Arrays −
print("Our Array 1 Dimensions...",arr1.ndim) print("Our Array 2 Dimensions...",arr2.ndim)
Get the shape of the Arrays −
print("Our Array 1 Shape...",arr1.shape) print("Our Array 2 Shape...",arr2.shape)
To compute the truth value of an array OR another array element-wise, use the numpy.logical_or() method. Return value is either True or False −
print("Result (OR)...",np.logical_or(arr1, arr2))
Example
import numpy as np # Creating two 2D numpy array using the array() method # We have inserted elements arr1 = np.array([[True, False, False], [False, True, True]]) arr2 = np.array([[True, False, True], [True, True, False]]) # Display the arrays print("Array 1...", arr1) print("Array 2...", arr2) # Get the type of the arrays print("Our Array 1 type...", arr1.dtype) print("Our Array 2 type...", arr2.dtype) # Get the dimensions of the Arrays print("Our Array 1 Dimensions...",arr1.ndim) print("Our Array 2 Dimensions...",arr2.ndim) # Get the shape of the Arrays print("Our Array 1 Shape...",arr1.shape) print("Our Array 2 Shape...",arr2.shape) # To compute the truth value of an array OR another array elementwise, use the numpy.logical_or() method in Python Numpy # Return value is either True or False print("Result (OR)...",np.logical_or(arr1, arr2))
Output
Array 1... [[ True False False] [False True True]] Array 2... [[ True False True] [ True True False]] Our Array 1 type... bool Our Array 2 type... bool Our Array 1 Dimensions... 2 Our Array 2 Dimensions... 2 Our Array 1 Shape... (2, 3) Our Array 2 Shape... (2, 3) Result (OR)... [[ True False True] [ True True True]]
2K+ Views
