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Refactoring and optimization of the lu_decomposition algorithm (#9231)

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* Replacing the generator with numpy vector operations from lu_decomposition.

* Revert "Replacing the generator with numpy vector operations from lu_decomposition."

This reverts commit ad217c6616.

* Replacing the generator with numpy vector operations from lu_decomposition.
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Kamil 2023-10-16 12:29:46 +05:00 committed by GitHub
parent f4ff73b1bd
commit 3c14e6ae3a
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1 changed files with 6 additions and 2 deletions
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arithmetic_analysis/lu_decomposition.py
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@ -88,15 +88,19 @@ def lower_upper_decomposition(table: np.ndarray) -> tuple[np.ndarray, np.ndarray
lower = np.zeros((rows, columns)) lower = np.zeros((rows, columns))
upper = np.zeros((rows, columns)) upper = np.zeros((rows, columns))
# in 'total', the necessary data is extracted through slices
# and the sum of the products is obtained.
for i in range(columns): for i in range(columns):
for j in range(i): for j in range(i):
total = sum(lower[i][k] * upper[k][j] for k in range(j)) total = np.sum(lower[i, :i] * upper[:i, j])
if upper[j][j] == 0: if upper[j][j] == 0:
raise ArithmeticError("No LU decomposition exists") raise ArithmeticError("No LU decomposition exists")
lower[i][j] = (table[i][j] - total) / upper[j][j] lower[i][j] = (table[i][j] - total) / upper[j][j]
lower[i][i] = 1 lower[i][i] = 1
for j in range(i, columns): for j in range(i, columns):
total = sum(lower[i][k] * upper[k][j] for k in range(j)) total = np.sum(lower[i, :i] * upper[:i, j])
upper[i][j] = table[i][j] - total upper[i][j] = table[i][j] - total
return lower, upper return lower, upper