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feat(ga): Implement quality filtering and precision-based clustering (#19)
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The previous GA logic was returning the "top N" solutions, which led to test failures when the algorithm correctly converged on only one of all possible roots (e.g., returning 1000 variations of -1.0).

This commit fixes the root-finding logic to correctly identify and return *all* unique, high-quality roots:

1.  **feat(api):** Adds `root_precision` to `GA_Options`. This new parameter (default: 5) allows the user to control the number of decimal places for clustering unique roots.

2.  **fix(ga):** Replaces the flawed "top N" logic in both `_solve_x_numpy` and `_solve_x_cuda`. The new process is:
    * Dynamically sets a `quality_threshold` based on the user's `root_precision` (e.g., `precision=5` requires a rank > `1e6`).
    * Filters the *entire* final population for all solutions that meet this quality threshold.
    * Rounds these high-quality solutions to `root_precision`.
    * Returns only the `np.unique()` results.

This ensures the solver returns all distinct roots that meet the accuracy requirements, rather than just the top N variations of a single root.

Reviewed-on: #19
Co-authored-by: Jonathan Rampersad <rampersad.jonathan@gmail.com>
Co-committed-by: Jonathan Rampersad <rampersad.jonathan@gmail.com>
This commit was merged in pull request #19.
This commit is contained in:
Jonathan Rampersad
2025-10-27 19:26:50 +00:00
committed by Jonathan Rampersad
parent 962eab5af7
commit 4e46c11f83
3 changed files with 46 additions and 21 deletions
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4
tests/test_polysolve.py
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@@ -101,7 +101,7 @@ def test_get_real_roots_numpy(quadratic_func):
Tests that the NumPy-based genetic algorithm approximates the roots correctly.
"""
# Using more generations for higher accuracy in testing
ga_opts = GA_Options(num_of_generations=25, data_size=50000)
ga_opts = GA_Options(num_of_generations=50, data_size=200000, root_precision=3)
roots = quadratic_func.get_real_roots(ga_opts, use_cuda=False)
@@ -124,7 +124,7 @@ def test_get_real_roots_cuda(quadratic_func):
It will be skipped automatically if CuPy is not available.
"""
ga_opts = GA_Options(num_of_generations=25, data_size=50000)
ga_opts = GA_Options(num_of_generations=50, data_size=200000, root_precision=3)
roots = quadratic_func.get_real_roots(ga_opts, use_cuda=True)