MilesCranmer / PySR / 7375284807

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92.0
/pysr/export_numpy.py
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"""Code for exporting discovered expressions to numpy"""
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import warnings
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import numpy as np




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import pandas as pd




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from sympy import lambdify




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def sympy2numpy(eqn, sympy_symbols, *, selection=None):




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    return CallableEquation(eqn, sympy_symbols, selection=selection)




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class CallableEquation:




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    """Simple wrapper for numpy lambda functions built with sympy"""










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    def __init__(self, eqn, sympy_symbols, selection=None):




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        self._sympy = eqn




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        self._sympy_symbols = sympy_symbols




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        self._selection = selection




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    def __repr__(self):




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        return f"PySRFunction(X=>{self._sympy})"




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    def __call__(self, X):




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        expected_shape = (X.shape[0],)




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        if isinstance(X, pd.DataFrame):




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            # Lambda function takes as argument:










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            return self._lambda(




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                **{k: X[k].values for k in map(str, self._sympy_symbols)}










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            ) * np.ones(expected_shape)










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        if self._selection is not None:




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            if X.shape[1] != len(self._selection):




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                warnings.warn(




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                    "`X` should be of shape (n_samples, len(self._selection)). "










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                    "Automatically filtering `X` to selection. "










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                    "Note: Filtered `X` column order may not match column order in fit "










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                    "this may lead to incorrect predictions and other errors."










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                )










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                X = X[:, self._selection]




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        return self._lambda(*X.T) * np.ones(expected_shape)




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    @property




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    def _lambda(self):




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        return lambdify(self._sympy_symbols, self._sympy)




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