119 lines
3.3 KiB
Python
119 lines
3.3 KiB
Python
''' mbinary
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#########################################################################
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# File : linear_equation.py
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# Author: mbinary
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# Mail: zhuheqin1@gmail.com
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# Blog: https://mbinary.xyz
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# Github: https://github.com/mbinary
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# Created Time: 2018-10-02 21:14
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# Description:
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#########################################################################
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'''
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#coding: utf-8
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'''************************************************************************
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> File Name: doolittle.py
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> Author: mbinary
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> Mail: zhuheqin1@gmail.com
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> Blog: https://mbinary.xyz
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> Created Time: 2018-04-20 08:32
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************************************************************************'''
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import numpy as np
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def getLU(A):
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'''doolittle : A = LU,
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L is in down-triangle form,
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U is in up-triangle form
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'''
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m,n = A.shape
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if m!=n:raise Exception("this matrix is not inversable")
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L = np.zeros([m,m])
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U = np.zeros([m,m])
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L = np.matrix(L)
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U = np. matrix(U)
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U[0] = A[0]
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L[:,0] = A[:,0] / A[0,0]
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for i in range(1,m):
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for j in range(i,m):
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U[i,j]= A[i,j] - sum(L[i,k]*U[k,j] for k in range(i))
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L[j,i] = (A[j,i] - sum(L[j,k]*U[k,i] for k in range(i)))/U[i,i]
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print(L)
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print(U)
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return L,U
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def gauss_prior_elimination(A):
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'''using guass elimination,get up_trianglge form of A'''
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m,n = A.shape
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if m!=n:raise Exception("[Error]: matrix is not inversable")
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B = np.matrix(A,dtype=float) # necessary,otherwise when the dtype of A is int, then it will be wrong
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for i in range(m-1):
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col = abs(B[i:,i]) # note using abs value, return a matrix in (m-i)x1 form
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mx = col.max()
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if mx==0: raise Exception("[Error]: matrix is not inversable")
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pos = i+col.argmax()
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if pos != i : B[[pos,i],:] = B[[i,pos],:] # note how to swap cols/rows
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B[i,:] = 1/mx*B[i,:]
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for j in range(i+1,m):
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#print(B)
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B[j,:] -= B[j,i] * B[i,:]
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print(B)
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return B
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def solveDown(A,b):
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'''A is a matrix in down-triangle form'''
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sol = np.zeros(b.shape)
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for i in range(b.shape[0]):
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sol[i,0] = (b[i,0]-sum(A[i,j]*sol[j,0] for j in range(i)))/A[i,i]
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return sol
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def solveUp(A,b):
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'''A is a matrix in up-triangle form'''
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sol = np.zeros(b.shape)
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n = b.shape[0]
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for i in range(n-1,-1,-1):
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sol[i,0] = (b[i,0]-sum(A[i,j]*sol[j,0] for j in range(n-1,i,-1)))/A[i,i]
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return sol
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def doolittle(A,b):
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L,U = getLU(A)
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y = solveDown(L,b)
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x = solveUp(U,y)
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print(y)
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print(x)
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return x
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def ldlt(A,b):
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L,U = getLU(A)
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D = np.diag(np.diag(U))
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print(D,"D")
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z = np.linalg.solve(L,b)
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print(z,"z")
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y = np.linalg.solve(D,z)
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print(y,"y")
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x = np.linalg.solve(L.T,y)
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print(x,"x")
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return x
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if __name__ == '__main__':
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A = np.matrix([[10,5,0,0],
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[2,2,1,0],
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[0,10,0,5],
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[0,0,2,1]])
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b = np.matrix([[5],[3],[27],[6]])
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gauss_prior_elimination(A)
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'''ldlt
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A = np.matrix([[-6,3,2],
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[3,5,1],
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[2,1,6]])
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b = np.matrix([[-4],[11],[-8]])
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ldlt(A,b)
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'''
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'''
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A = np.matrix([[2,1,1],
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[1,3,2],
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[1,2,2]])
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b = np.matrix([[4],[6],[5]])
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doolittle(A,b)
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'''
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