Curve fit base - #54
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Additional details and impacted files@@ Coverage Diff @@
## dev #54 +/- ##
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- Coverage 98.69% 84.15% -14.54%
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Files 9 10 +1
Lines 229 309 +80
Branches 26 33 +7
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+ Hits 226 260 +34
- Misses 2 48 +46
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| numpy==2.2.6 | |||
| matplotlib==3.10.3 | |||
| scipy>=1.7.3 | |||
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I'm not sure about this because scipy==1.7.3 is the latest version that supports Python 3.7, but it only supports Python versions up to 3.10. What should we do in this case?
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There is no need to be concerned. As you may know, we do not directly install this fixed version, and this file is intended solely for triggering Dependabot. PyPI automatically installs the latest available version of each dependency across different Python versions.
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| ## [Unreleased] | ||
| ### Added | ||
| - `CurveFit` object |
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| # Single point of registration mapping a model name to its class. | ||
| MODEL_CLASSES: Dict[str, Type[DrugReleaseModel]] = { |
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Don't use typing for internal variables.
| if self._fit_result is None: | ||
| return f"drux.CurveFit({self._model_name}, not fitted)" | ||
| params = ", ".join(f"{k}={v:.4f}" for k, v in self._fit_result.parameters.items()) | ||
| return f"drux.CurveFit({self._model_name}: {params}, R²={self._fit_result.r_squared:.4f})" |
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Don't use Unicode superscript ² (R²) in this function.
| for name in self._parameter_names | ||
| } | ||
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| def _equation(self, t: np.ndarray, *free_values: float) -> np.ndarray: |
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Add docstring for inputs.
:param t: ...
:param free_values: ...
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| self._fit_result: Optional[FitResult] = None | ||
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| def _merge_parameters(self, free_values: Sequence[float]) -> Dict[str, float]: |
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Add docstring for inputs.
| } | ||
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| def _model_parameter_names(model_class: Type[DrugReleaseModel]) -> List[str]: |
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Add docstring for inputs.
| ERROR_INVALID_GEOMETRY_FACTOR = "Geometry factor (n) must be 1 (slab), 2 (cylinder), or 3 (sphere)." | ||
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| # Error messages for curve fitting | ||
| ERROR_UNKNOWN_MODEL = "Unknown model '{}'. Available models: {}." |
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I strongly suggest using names in formatting.
For example:
ERROR_UNKNOWN_MODEL = "Unknown model '{model_name}'. Available models: {available_models}."And then:
ERROR_UNKNOWN_MODEL.format(model_name=model_name, available_models=available_models)
| ## [Unreleased] | ||
| ### Added | ||
| - `CurveFit` class | ||
| - `FitResult` object |
| for name in self._parameter_names | ||
| } | ||
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| def _equation(self, t: np.ndarray, *free_values: float) -> np.ndarray: |
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Are you sure about the type of *free_values?
3 participants
What does this implement?
CurveFitclass is added