25 lines
708 B
Python
25 lines
708 B
Python
import numpy as np
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print("*********Jacobi-Verfahren*********")
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def Jacobi(A,b,x,steps):
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L = np.tril(A,k=-1)
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D = np.diag(np.diag(A))
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R = np.triu(A, k=1)
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for steps in range(steps):
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x = -np.linalg.inv(D) @ (L + R) @ x + np.linalg.inv(D) @ b
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#print(np.linalg.norm((-np.linalg.inv(D) @ (L + R)),np.inf))
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return x
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A = np.array([[8,5,2],[5,9,1],[4,2,7]])
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b = np.array([[19],[5],[34]])
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x = np.array([[1],[-1],[3]])
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steps = 3
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print(Jacobi(A,b,x,steps))
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print("Sum of vector:")
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#print(np.sum(Jacobi(A,b,x,steps)))
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#print(np.linalg.norm(Jacobi(A,b,x,3)-Jacobi(A,b,x,2),np.inf)*7)
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print(np.linalg.norm(Jacobi(A,b,x,3)-Jacobi(A,b,x,2),np.inf))
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print((0.0001*0.125)/0.7693452380952384) |