numpy.bmat(obj, l_dict = None, g_dict = None) : Return specialised 2-D matrix from nested objects that can be string-like or array-like.
Parameters :
object : array-like or string
l_dict : (dict, optional) replaces local operands,
A dictionary that replaces local operands in current frame
g_dict : (dict, optional) replaces global operands,
A dictionary that replaces global operands in current frame.
Returns :
2-D matrix from nested objects
import numpy as geek
A = geek.mat( '4 1; 22 1' )
B = geek.mat( '5 2; 5 2' )
C = geek.mat( '8 4; 6 6' )
a = geek.bmat([[A, B], [C, A]])
print ( "Via bmat array like input : \n" , a, "\n\n" )
s = geek.bmat( 'A, B; A, A' )
print ( "Via bmat string like input : \n" , s)
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Output :
Via bmat array like input :
[[ 4 1 5 2]
[22 1 5 2]
[ 8 4 4 1]
[ 6 6 22 1]]
Via bmat string like input :
[[ 4 1 5 2]
[22 1 5 2]
[ 4 1 4 1]
[22 1 22 1]]
Note :
These codes won’t run on online IDE’s. Please run them on your systems to explore the working
.
Last Updated :
09 Mar, 2022
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