Numpy matrix.I function | Python

numpy.matrix() in Python

Last Updated : 09 Mar, 2022

This class returns a matrix from a string of data or array-like object. Matrix obtained is a specialised 2D array. Syntax :

numpy.matrix(data, dtype = None) :

Parameters :

data  : data needs to be array-like or string 
dtype : Data type of returned array.

Returns :

data interpreted as a matrix

Python

# Python Program illustrating
# numpy.matrix class

import numpy as geek

# string input
a = geek.matrix('1 2; 3 4')
print("Via string input : \n", a, "\n\n")

# array-like input
b = geek.matrix([[5, 6, 7], [4, 6]])
print("Via array-like input : \n", b)

Output :

Via string input : 
 [[1 2]
 [3 4]] 


Via array-like input : 
 [[[5, 6, 7] [4, 6]]]

References : https://docs.scipy.org/doc/numpy/reference/generated/numpy.mat.html#numpy.mat Note : These codes won't run on online IDE's. Please run them on your systems to explore the working .

Numpy matrix.I function | Python

M

Mohit Gupta_OMG

Improve

Article Tags :

Practice Tags :

Similar Reads

numpy.mean() in Python

numpy.mean(arr, axis = None) : Compute the arithmetic mean (average) of the given data (array elements) along the specified axis. Parameters : arr : [array_like]input array. axis : [int or tuples of int]axis along which we want to calculate the arithmetic mean. Otherwise, it will consider arr to be

numpy.matrix.A() function - Python

numpy.matrix.A() function return self as an ndarray object. Syntax : numpy.matrix.A() Parameters : None Return : [ndarray] Return self as an ndarray. Code #1 : Python3 # Python program explaining # numpy.matrix.A() function # importing numpy as geek import numpy as geek mat = geek.matrix(geek.arange

Numpy matrix.I function | Python

With the help ofnumpy.matrix.I() function we can get the multiplicative inverse of the same size as of our given matrix. Syntax : numpy.matrix.I() Return : [matrix object] If self is non-singular, ret is such that ret * self == self * ret == np.matrix(np.eye(self[0, :].size) all return True. Return

numpy.loadtxt() in Python

numpy.loadtxt() function is used to load data from a text file and return it as a NumPy array. It is ideal for reading large data sets that are stored in simple text formats, such as CSV files or space-separated files.Example: Basic Usage of numpy.loadtxt() for Reading a Simple Space-Separated FileT

Python | Numpy matrix.sum()

With the help of matrix.sum() method, we are able to find the sum of values in a matrix by using the same method. Syntax : matrix.sum() Return : Return sum of values in a matrix Example #1 : In this example we are able to find the sum of values in a matrix by using matrix.sum() method. Python3 1=1 #

numpy.asmatrix() in Python

numpy.asmatrix(data, dtype = None) Returns a matrix by interpreting the input as a matrix. Parameters : data : array-like input data dtype : Data type of returned array Returns : Interprets the input as a matrix Python # Python Programming illustrating # numpy.asmatrix import numpy as geek # array-l

numpy.multiply() in Python

The numpy.multiply() is a numpy function in Python which is used to find element-wise multiplication of two arrays or scalar (single value). It returns the product of two input array element by element.Syntax:numpy.multiply(arr1, arr2, out=None, where=True, casting='same_kind', order='K', dtype=None

Python | Numpy matrix.take()

With the help of Numpy matrix.take() method, we can select the elements from a given matrix by passing the parameter as index value of that element. It will return a matrix having one dimension. Remember it will work for one axis at a time. Syntax : matrix.take(index, axis) Return : Return matrix of

numpy.negative() in Python

numpy.negative() function is used when we want to compute the negative of array elements. It returns element-wise negative value of an array or negative value of a scalar. Syntax : numpy.negative(arr, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, ext

Python | Numpy numpy.matrix.A()

With the help of Numpy numpy.matrix.A() method, we can get the same matrix as self. It means through this method we can get the identical matrix. Syntax : numpy.matrix.A() Return : Return self matrix Example #1 : In this example we can see that with the help of matrix.A() method, we are able to get