(continued from previous page from scipy linalg import lu anp mat(' 'define matrix print(np shape( )( at np transpose(atranspose of matrix 'aprint(np shape(at)( eye(nis used for (nxnidentity matrix = *np eye( identity matrix print(np shape( )( * print(np shape( )( llu(aprint(llisting lu factorization of matrix scipyex py import numpy as np import lu factorization command from scipy linalg from scipy linalg import lu #define matrix 'aanp mat(' 'define matrix perform lu factorization and save the values in pl and as it returns values [plu]lu( print values of pl and print(" "pprint(" "lprint(" "np round( , ) print("type of "type( )#type of pndarray * * will give wrong results because types are not matrix (but ndarrayas shown above dot(ldot(uprint(" " #for * * we need to change the ndarray to matrix type as belowprint("type of after np mat"type(np mat( )) np mat( )*np mat( )*np mat(uprint(" " ''outputs [ ] [ - ] [ (continues on next page numpyscipy and matplotlib