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- Rename PYTHON/ to python_pkg/ (fix N999 uppercase folder) - Rename camelCase folders to snake_case: - randomJPG -> random_jpg - tagDivider -> tag_divider - downloadCats -> download_cats - keyboardCoop -> keyboard_coop - extractLinks -> extract_links - scapeWebsite -> scrape_website - Rename camelCase files: - generateJpeg.py -> generate_jpeg.py - tagDivider.py -> tag_divider.py - Rename poker-modifier-app to poker_modifier_app (fix INP001) - Add __init__.py to poker_modifier_app - Replace random module with secrets.SystemRandom (fix S311) - Fix S110 try-except-pass with contextlib.suppress - Update all imports and config references
61 lines
1.9 KiB
Python
61 lines
1.9 KiB
Python
"""Distribute values symmetrically across N parts."""
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def calculate_symmetric_weights(
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n: int, middle_weight: float, factors: list[float] | None = None
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) -> list[float]:
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"""Calculate symmetric weights for both even and odd N.
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Args:
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n: Number of parts to split into.
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middle_weight: The middle value for symmetry.
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factors: If provided, controls the difference in weights.
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Must have length n // 2 or n // 2 - 1 depending on n.
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Returns:
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List of symmetric weights.
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"""
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half_n = n // 2
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weights_left: list[float] = [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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weights_left.extend(middle_weight - (i + 1) for i in range(half_n - 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: float, weights: list[float]) -> list[float]:
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"""Scale the weights so that their sum is proportional to X.
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Args:
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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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Returns:
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List of scaled values summing to x.
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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: float, n: int, factors: list[float]) -> list[float]:
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"""Split X into N parts with symmetric weights controlled by factors."""
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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: float, n: int, middle_value: float) -> list[float]:
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"""Split X into N parts with symmetric weights using middle_value as peak."""
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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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