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Fix ruff (#11527)
* updating DIRECTORY.md
* Fix ruff
* Fix
* Fix
* Fix
* Revert "Fix"
This reverts commit 5bc3bf3422
.
* find_max.py: noqa: PLR1730
---------
Co-authored-by: MaximSmolskiy <MaximSmolskiy@users.noreply.github.com>
Co-authored-by: Christian Clauss <cclauss@me.com>
This commit is contained in:
parent
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commit
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@ -16,7 +16,7 @@ repos:
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- id: auto-walrus
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- id: auto-walrus
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- repo: https://github.com/astral-sh/ruff-pre-commit
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- repo: https://github.com/astral-sh/ruff-pre-commit
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rev: v0.5.7
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rev: v0.6.2
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hooks:
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hooks:
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- id: ruff
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- id: ruff
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- id: ruff-format
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- id: ruff-format
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@ -31,8 +31,7 @@ def binomial_coefficient(n: int, k: int) -> int:
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"""
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"""
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result = 1 # To kept the Calculated Value
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result = 1 # To kept the Calculated Value
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# Since C(n, k) = C(n, n-k)
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# Since C(n, k) = C(n, n-k)
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if k > (n - k):
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k = min(k, n - k)
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k = n - k
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# Calculate C(n,k)
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# Calculate C(n,k)
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for i in range(k):
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for i in range(k):
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result *= n - i
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result *= n - i
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@ -54,8 +54,7 @@ def dis_between_closest_pair(points, points_counts, min_dis=float("inf")):
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for i in range(points_counts - 1):
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for i in range(points_counts - 1):
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for j in range(i + 1, points_counts):
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for j in range(i + 1, points_counts):
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current_dis = euclidean_distance_sqr(points[i], points[j])
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current_dis = euclidean_distance_sqr(points[i], points[j])
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if current_dis < min_dis:
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min_dis = min(min_dis, current_dis)
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min_dis = current_dis
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return min_dis
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return min_dis
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@ -76,8 +75,7 @@ def dis_between_closest_in_strip(points, points_counts, min_dis=float("inf")):
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for i in range(min(6, points_counts - 1), points_counts):
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for i in range(min(6, points_counts - 1), points_counts):
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for j in range(max(0, i - 6), i):
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for j in range(max(0, i - 6), i):
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current_dis = euclidean_distance_sqr(points[i], points[j])
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current_dis = euclidean_distance_sqr(points[i], points[j])
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if current_dis < min_dis:
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min_dis = min(min_dis, current_dis)
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min_dis = current_dis
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return min_dis
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return min_dis
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@ -17,8 +17,7 @@ def longest_distance(graph):
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for x in graph[vertex]:
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for x in graph[vertex]:
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indegree[x] -= 1
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indegree[x] -= 1
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if long_dist[vertex] + 1 > long_dist[x]:
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long_dist[x] = max(long_dist[x], long_dist[vertex] + 1)
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long_dist[x] = long_dist[vertex] + 1
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if indegree[x] == 0:
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if indegree[x] == 0:
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queue.append(x)
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queue.append(x)
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@ -20,7 +20,7 @@ def find_max_iterative(nums: list[int | float]) -> int | float:
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raise ValueError("find_max_iterative() arg is an empty sequence")
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raise ValueError("find_max_iterative() arg is an empty sequence")
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max_num = nums[0]
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max_num = nums[0]
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for x in nums:
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for x in nums:
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if x > max_num:
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if x > max_num: # noqa: PLR1730
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max_num = x
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max_num = x
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return max_num
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return max_num
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@ -61,8 +61,7 @@ def _binomial_coefficient(total_elements: int, elements_to_choose: int) -> int:
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if elements_to_choose in {0, total_elements}:
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if elements_to_choose in {0, total_elements}:
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return 1
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return 1
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if elements_to_choose > total_elements - elements_to_choose:
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elements_to_choose = min(elements_to_choose, total_elements - elements_to_choose)
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elements_to_choose = total_elements - elements_to_choose
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coefficient = 1
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coefficient = 1
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for i in range(elements_to_choose):
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for i in range(elements_to_choose):
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@ -31,7 +31,7 @@ stream_handler = logging.StreamHandler(sys.stdout)
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logger.addHandler(stream_handler)
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logger.addHandler(stream_handler)
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@pytest.mark.mat_ops()
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@pytest.mark.mat_ops
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@pytest.mark.parametrize(
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@pytest.mark.parametrize(
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("mat1", "mat2"), [(mat_a, mat_b), (mat_c, mat_d), (mat_d, mat_e), (mat_f, mat_h)]
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("mat1", "mat2"), [(mat_a, mat_b), (mat_c, mat_d), (mat_d, mat_e), (mat_f, mat_h)]
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)
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)
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@ -51,7 +51,7 @@ def test_addition(mat1, mat2):
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matop.add(mat1, mat2)
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matop.add(mat1, mat2)
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@pytest.mark.mat_ops()
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@pytest.mark.mat_ops
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@pytest.mark.parametrize(
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@pytest.mark.parametrize(
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("mat1", "mat2"), [(mat_a, mat_b), (mat_c, mat_d), (mat_d, mat_e), (mat_f, mat_h)]
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("mat1", "mat2"), [(mat_a, mat_b), (mat_c, mat_d), (mat_d, mat_e), (mat_f, mat_h)]
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)
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)
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@ -71,7 +71,7 @@ def test_subtraction(mat1, mat2):
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assert matop.subtract(mat1, mat2)
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assert matop.subtract(mat1, mat2)
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@pytest.mark.mat_ops()
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@pytest.mark.mat_ops
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@pytest.mark.parametrize(
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@pytest.mark.parametrize(
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("mat1", "mat2"), [(mat_a, mat_b), (mat_c, mat_d), (mat_d, mat_e), (mat_f, mat_h)]
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("mat1", "mat2"), [(mat_a, mat_b), (mat_c, mat_d), (mat_d, mat_e), (mat_f, mat_h)]
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)
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)
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@ -93,21 +93,21 @@ def test_multiplication(mat1, mat2):
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assert matop.subtract(mat1, mat2)
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assert matop.subtract(mat1, mat2)
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@pytest.mark.mat_ops()
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@pytest.mark.mat_ops
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def test_scalar_multiply():
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def test_scalar_multiply():
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act = (3.5 * np.array(mat_a)).tolist()
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act = (3.5 * np.array(mat_a)).tolist()
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theo = matop.scalar_multiply(mat_a, 3.5)
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theo = matop.scalar_multiply(mat_a, 3.5)
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assert theo == act
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assert theo == act
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@pytest.mark.mat_ops()
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@pytest.mark.mat_ops
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def test_identity():
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def test_identity():
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act = (np.identity(5)).tolist()
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act = (np.identity(5)).tolist()
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theo = matop.identity(5)
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theo = matop.identity(5)
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assert theo == act
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assert theo == act
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@pytest.mark.mat_ops()
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@pytest.mark.mat_ops
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@pytest.mark.parametrize("mat", [mat_a, mat_b, mat_c, mat_d, mat_e, mat_f])
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@pytest.mark.parametrize("mat", [mat_a, mat_b, mat_c, mat_d, mat_e, mat_f])
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def test_transpose(mat):
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def test_transpose(mat):
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if (np.array(mat)).shape < (2, 2):
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if (np.array(mat)).shape < (2, 2):
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@ -75,8 +75,7 @@ def solution(n: str = N) -> int:
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product = 1
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product = 1
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for j in range(13):
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for j in range(13):
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product *= int(n[i + j])
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product *= int(n[i + j])
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if product > largest_product:
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largest_product = max(largest_product, product)
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largest_product = product
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return largest_product
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return largest_product
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@ -39,8 +39,7 @@ def solution(n: int = 1000) -> int:
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c = n - a - b
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c = n - a - b
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if c * c == (a * a + b * b):
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if c * c == (a * a + b * b):
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candidate = a * b * c
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candidate = a * b * c
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if candidate >= product:
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product = max(product, candidate)
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product = candidate
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return product
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return product
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@ -63,8 +63,7 @@ def largest_product(grid):
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max_product = max(
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max_product = max(
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vert_product, horz_product, lr_diag_product, rl_diag_product
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vert_product, horz_product, lr_diag_product, rl_diag_product
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)
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)
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if max_product > largest:
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largest = max(largest, max_product)
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largest = max_product
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return largest
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return largest
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@ -45,15 +45,13 @@ def solution():
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for i in range(20):
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for i in range(20):
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for j in range(17):
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for j in range(17):
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temp = grid[i][j] * grid[i][j + 1] * grid[i][j + 2] * grid[i][j + 3]
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temp = grid[i][j] * grid[i][j + 1] * grid[i][j + 2] * grid[i][j + 3]
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if temp > maximum:
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maximum = max(maximum, temp)
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maximum = temp
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# down
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# down
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for i in range(17):
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for i in range(17):
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for j in range(20):
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for j in range(20):
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temp = grid[i][j] * grid[i + 1][j] * grid[i + 2][j] * grid[i + 3][j]
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temp = grid[i][j] * grid[i + 1][j] * grid[i + 2][j] * grid[i + 3][j]
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if temp > maximum:
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maximum = max(maximum, temp)
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maximum = temp
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# diagonal 1
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# diagonal 1
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for i in range(17):
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for i in range(17):
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@ -64,8 +62,7 @@ def solution():
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* grid[i + 2][j + 2]
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* grid[i + 2][j + 2]
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* grid[i + 3][j + 3]
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* grid[i + 3][j + 3]
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)
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)
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if temp > maximum:
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maximum = max(maximum, temp)
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maximum = temp
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# diagonal 2
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# diagonal 2
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for i in range(17):
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for i in range(17):
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@ -76,8 +73,7 @@ def solution():
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* grid[i + 2][j - 2]
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* grid[i + 2][j - 2]
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* grid[i + 3][j - 3]
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* grid[i + 3][j - 3]
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)
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)
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if temp > maximum:
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maximum = max(maximum, temp)
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maximum = temp
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return maximum
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return maximum
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i = 0
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i = 0
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while finished_process[i] == 1:
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while finished_process[i] == 1:
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i += 1
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i += 1
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if current_time < arrival_time[i]:
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current_time = max(current_time, arrival_time[i])
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current_time = arrival_time[i]
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response_ratio = 0
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response_ratio = 0
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# Index showing the location of the process being performed
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# Index showing the location of the process being performed
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@ -66,8 +66,7 @@ def calculate_waitingtime(
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finar = finish_time - arrival_time[short]
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finar = finish_time - arrival_time[short]
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waiting_time[short] = finar - burst_time[short]
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waiting_time[short] = finar - burst_time[short]
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if waiting_time[short] < 0:
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waiting_time[short] = max(waiting_time[short], 0)
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waiting_time[short] = 0
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# Increment time
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# Increment time
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increment_time += 1
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increment_time += 1
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