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backtracking -> word_search - replacing the example in doctest #10188

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Merged
merged 3 commits into from
Oct 10, 2023
Merged

backtracking -> word_search - replacing the example in doctest #10188

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eccea26
Replacing the generator with numpy vector operations from lu_decompos…
quant12345 Sep 29, 2023
4e34723
Revert "Replacing the generator with numpy vector operations from lu_…
quant12345 Sep 29, 2023
d5906d8
Replacing the example in doctest with a less resource-intensive example.
quant12345 Oct 9, 2023
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Replacing the generator with numpy vector operations from lu_decompos… 
…ition.
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@quant12345
quant12345 committed Oct 7, 2023
commit eccea262c10ff0e2fe6a5c6dbaf13a8be2371dca
8 changes: 6 additions & 2 deletions arithmetic_analysis/lu_decomposition.py
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Expand Up @@ -88,15 +88,19 @@ def lower_upper_decomposition(table: np.ndarray) -> tuple[np.ndarray, np.ndarray

lower = 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 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:
raise ArithmeticError("No LU decomposition exists")
lower[i][j] = (table[i][j] - total) / upper[j][j]
lower[i][i] = 1
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
return lower, upper

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