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1495382367
* Fixed Bug #2257 * = Co-authored-by: Svn-Sp <svn-sp@email> Co-authored-by: Christian Clauss <cclauss@me.com>
35 lines
969 B
Python
35 lines
969 B
Python
"""Lower-Upper (LU) Decomposition."""
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# lower–upper (LU) decomposition - https://en.wikipedia.org/wiki/LU_decomposition
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import numpy
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def LUDecompose(table):
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# Table that contains our data
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# Table has to be a square array so we need to check first
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rows, columns = numpy.shape(table)
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L = numpy.zeros((rows, columns))
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U = numpy.zeros((rows, columns))
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if rows != columns:
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return []
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for i in range(columns):
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for j in range(i):
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sum = 0
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for k in range(j):
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sum += L[i][k] * U[k][j]
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L[i][j] = (table[i][j] - sum) / U[j][j]
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L[i][i] = 1
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for j in range(i, columns):
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sum1 = 0
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for k in range(i):
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sum1 += L[i][k] * U[k][j]
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U[i][j] = table[i][j] - sum1
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return L, U
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if __name__ == "__main__":
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matrix = numpy.array([[2, -2, 1], [0, 1, 2], [5, 3, 1]])
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L, U = LUDecompose(matrix)
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print(L)
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print(U)
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