numpy matrix operations | zeros() function
Last Updated :
21 Feb, 2019
numpy.matlib.zeros() is another function for doing matrix operations in numpy. It returns a matrix of given shape and type, filled with zeros.
Syntax : numpy.matlib.zeros(shape, dtype=None, order='C')
Parameters :
shape : [int, int] Number of rows and columns in the output matrix.If shape has length one i.e. (N, ), or is a scalar N, out becomes a single row matrix of shape (1, N).
dtype : [optional] Desired output data-type.
order : Whether to store multi-dimensional data in row-major (C-style) or column-major (Fortran-style) order in memory.
Return : Matrix of zeros of given shape, dtype, and order.
Code #1 :
Python3
# Python program explaining
# numpy.matlib.zeros() function
# importing matrix library from numpy
import numpy as geek
import numpy.matlib
# desired 3 x 4 zero output matrix
out_mat = geek.matlib.zeros((3, 4))
print ("Output matrix : ", out_mat)
Output :
Output matrix : [[ 0. 0. 0. 0.]
[ 0. 0. 0. 0.]
[ 0. 0. 0. 0.]]
Code #2 :
Python3
# Python program explaining
# numpy.matlib.zeros() function
# importing numpy and matrix library
import numpy as geek
import numpy.matlib
# desired 1 x 5 zero output matrix
out_mat = geek.matlib.zeros(shape = 5, dtype = int)
print ("Output matrix : ", out_mat)
Output :
Output matrix : [[0 0 0 0 0]]