def det(M):
# check dimension of M
m, n = M.shape
if (m != n):
print('It is not a square matrix, no determinant define !')
else:
# U : upper triangular (row echelon matrix)
# nre : number of row-exchange
U, rank, nre = LA.upperTri(M)
# the determinant of M is the product of U[i,i]
determinant = 1
for i in range(m):
determinant = determinant * U[i, i]
# number of row-exchange will decide the sign
if (nre % 2 == 1): # nre is odd
determinant = -1 * determinant
# determinant = LA.det(M)
return determinant
def det(M):
# check dimension of M
m,n = M.shape
if (m!=n):
print('It is not a square matrix, no determinant define !')
else :
# U : upper triangular (row echelon matrix)
# nre : number of row-exchange
U,rank,nre = LA.upperTri(M)
# the determinant of M is the product of U[i,i]
determinant = 1;
for i in range(m):
determinant = determinant*U[i,i]
# number of row-exchange will decide the sign
if (nre%2==1): # nre is odd
determinant = -1*determinant
# determinant = LA.det(M)
return determinant
# -*- coding: utf-8 -*- """ Created on Sat Oct 15 2015 Modified on Fri Oct 15 2015 @author: david """ import LA import numpy as np #A=np.array([[1,2,1],[4,5,2],[4,8,3]]) A=np.array([[1,2],[4,5],[7,8]]) #A=np.array([[0,2,3],[0,5,6],[0,8,9]]) #A=np.array([[1,2,3],[3,5,6]]) print(A) U=LA.upperTri(A) R=LA.rref(A) print(U) print(R) print(LA.det(A)) print(LA.inv(A)) b=np.array([3,6,9]) print(LA.solve(A,b))
# -*- coding: utf-8 -*- """ Created on Sat Oct 15 2015 Modified on Fri Oct 15 2015 @author: david """ import LA import numpy as np # A=np.array([[1,2,1],[4,5,2],[4,8,3]]) A = np.array([[1, 2], [4, 5], [7, 8]]) # A=np.array([[0,2,3],[0,5,6],[0,8,9]]) # A=np.array([[1,2,3],[3,5,6]]) print(A) U = LA.upperTri(A) R = LA.rref(A) print(U) print(R) print(LA.det(A)) print(LA.inv(A)) b = np.array([3, 6, 9]) print(LA.solve(A, b))
