numpy.matrix.A() function - Python

numpy.matrix.A() function - Python

Last Updated : 18 Jun, 2020

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(9).reshape((3, 3)))
  
gfg = mat.getA()
  
print (gfg)

Output :

[[0 1 2]
 [3 4 5]
 [6 7 8]]

Code #2 :

Python3

# Python program explaining
# numpy.matrix.A() function
        
# importing numpy as geek 
import numpy as geek 
    
mat = geek.matrix(geek.arange(20).reshape((4, 5)))
  
gfg = mat.getA()
  
print (gfg)

Output :

[[ 0  1  2  3  4]
 [ 5  6  7  8  9]
 [10 11 12 13 14]
 [15 16 17 18 19]]

numpy.matrix.A() function - Python

sanjoy_62

Improve

Article Tags :

Practice Tags :

python

Similar Reads

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.matrix() in Python

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

numpy.i0() function | Python

numpy.i0() function is the modified Bessel function of the first kind, order 0. it's usually denoted by I0. Syntax : numpy.i0(x) Parameters : x : [array_like, dtype float or complex] Argument of the Bessel function. Return : [ndarray, shape = x.shape, dtype = x.dtype] The modified Bessel function ev

numpy.matlib.empty() function | Python

numpy.matlib.empty() function return a new matrix of given shape and type, without initializing entries. Syntax : numpy.matlib.empty(shape, dtype = None, order = 'C') Parameters : shape : [int or tuple of int] Shape of the empty matrix. dtype : [data-type, optional] Desired output data-type. order :

numpy matrix operations | eye() function

numpy.matlib.eye() is another function for doing matrix operations in numpy. It returns a matrix with ones on the diagonal and zeros elsewhere. Syntax : numpy.matlib.eye(n, M=None, k=0, dtype='float', order='C') Parameters : n : [int] Number of rows in the output matrix. M : [int, optional] Number o

numpy.matlib.zeros() function | Python

numpy.matlib.zeros() function return matrix of given shape and type, filled with zeros. Syntax : numpy.matlib.zeros(shape, dtype = None, order = 'C') Parameters : shape : [sequence of ints] Shape of the empty matrix. dtype : [data-type, optional] The desired data-type for the matrix, default is floa

numpy matrix operations | empty() function

numpy.matlib.empty() is another function for doing matrix operations in numpy.It returns a new matrix of given shape and type, without initializing entries. Syntax : numpy.matlib.empty(shape, dtype=None, order='C') Parameters : shape : [int or tuple of int] Shape of the desired output empty matrix.

numpy.pad() function in Python

numpy.pad() function is used to pad the Numpy arrays. Sometimes there is a need to perform padding in Numpy arrays, then numPy.pad() function is used. The function returns the padded array of rank equal to the given array and the shape will increase according to pad_width. Syntax: numpy.pad(array, p

Numpy ndarray.dot() function | Python

The numpy.ndarray.dot() function computes the dot product of two arrays. It is widely used in linear algebra, machine learning and deep learning for operations like matrix multiplication and vector projections.Example:Pythonimport numpy as np a = np.array([1, 2, 3]) b = np.array([4, 5, 6]) result =

numpy matrix operations | ones() function

numpy.matlib.ones() is another function for doing matrix operations in numpy. It returns a matrix of given shape and type, filled with ones. Syntax : numpy.matlib.ones(shape, dtype=None, order='C') Parameters : shape : [int, int] Number of rows and columns in the output matrix.If shape has length on