mirror of
https://github.com/kuhyx/testsAndMisc.git
synced 2026-07-06 22:43:08 +02:00
Krzysztof kuhy Rudnicki
f6d3ae0c7e
- Added module docstrings to 19 Python files - Added class docstrings to 5 classes (ScreenLocker, PokerModifierApp, etc.) - Added method docstrings to 22 methods - Added function docstrings to 25 functions - Added __init__ docstrings to 5 classes - Removed D100-D107 from ruff ignore list (docstrings now enforced) - Removed deprecated ANN101, ANN102, UP038 rules from ignore list - Fixed UP038: use union types in isinstance() calls - All ruff checks now pass with full docstring enforcement
60 lines
1.9 KiB
Python
60 lines
1.9 KiB
Python
"""Distribute values symmetrically across N parts."""
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def calculate_symmetric_weights(N, middle_weight, factors=None):
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"""Calculate symmetric weights for both even and odd N.
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N: Number in which to split.
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middle_weight: The middle value for symmetry.
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factors: If provided, controls the difference in weights (used for the
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`split_x_into_n_symmetrically` function).
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Must have length N // 2 or N // 2 - 1 depending on N.
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"""
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half_N = N // 2
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weights_left = [middle_weight]
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if factors:
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for factor in factors:
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next_weight = weights_left[-1] + factor
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weights_left.append(next_weight)
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else:
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for i in range(half_N - 1):
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weights_left.append(middle_weight - (i + 1))
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if N % 2 == 0:
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weights = weights_left[::-1] + weights_left
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else:
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weights = [*weights_left[::-1], middle_weight, *weights_left]
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return weights
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def scale_to_total(X, weights):
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"""Scale the weights so that their sum is proportional to X.
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X: Total value to distribute.
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weights: The list of weights to be scaled.
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"""
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total_weight = sum(weights)
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base_unit = X / total_weight
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return [base_unit * weight for weight in weights]
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def split_x_into_n_symmetrically(X, N, factors):
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"""X: Total value to distribute.
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N: Number in which we split.
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factors: List controlling the difference in weights between consecutive days.
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Must have length of N // 2 (if N is odd) or (N // 2 - 1) (if N is even).
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"""
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weights = calculate_symmetric_weights(N, middle_weight=1, factors=factors)
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return scale_to_total(X, weights)
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def split_x_into_n_middle(X, N, middle_value):
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"""X: Total value to distribute.
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N: Number in which we split.
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middle_value: Value of the middle number (the biggest weight).
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"""
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weights = calculate_symmetric_weights(N, middle_weight=middle_value)
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return scale_to_total(X, weights)
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