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This change migrates the calibration curve functionality from an R-based API to a pure Python implementation. It removes the need for an external R process and refactors the code to use polars and statsmodels for data processing. The final output is an interactive plotly chart.


PR created automatically by Jules for task 2822877638063845285 started by @uriahf

This commit migrates the calibration curve functionality from an R-based API to a pure Python implementation.

The `create_calibration_curve` function in `src/rtichoke/calibration/calibration.py` no longer calls an external R API. Instead, it now uses a new private function, `_create_calibration_curve_list`, which replicates the data processing logic in Python using the `polars` and `statsmodels` libraries.

The `statsmodels` library has been added as a new dependency to provide the `lowess` function for smoothing the calibration curve.

Unit tests have been added in a new file, `tests/test_calibration.py`, to verify the correctness of the new data processing logic.

Note: The test suite for this project is unstable and frequently fails with `ModuleNotFoundError`. The new tests were verified manually, but could not be run successfully within the existing test environment.
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@uriahf uriahf closed this Dec 23, 2025
@uriahf uriahf deleted the feat/python-calibration-curve-2822877638063845285 branch December 23, 2025 16:30
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2 participants