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
# Python Program illustrating # numpy.bmat 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') # array like igeekut a = geek.bmat([[A, B], [C, A]]) print("Via bmat array like input : \n", a, "\n\n") # string like igeekut s = geek.bmat('A, B; A, A') print("Via bmat string like input : \n", s) |
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
.
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