5439183423

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Build # 5439183423

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91.67

/pysr/export_numpy.py

"""Code for exporting discovered expressions to numpy"""
import numpy as np
import pandas as pd
from sympy import lambdify
import warnings


class CallableEquation:
    """Simple wrapper for numpy lambda functions built with sympy"""

    def __init__(self, sympy_symbols, eqn, selection=None, variable_names=None):
        self._sympy = eqn
        self._sympy_symbols = sympy_symbols
        self._selection = selection
        self._variable_names = variable_names

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

    def __call__(self, X):
        expected_shape = (X.shape[0],)
        if isinstance(X, pd.DataFrame):
            # Lambda function takes as argument:
            return self._lambda(
                **{k: X[k].values for k in self._variable_names}
            ) * np.ones(expected_shape)
        if self._selection is not None:
            if X.shape[1] != len(self._selection):
                warnings.warn(
                    "`X` should be of shape (n_samples, len(self._selection)). "
                    "Automatically filtering `X` to selection. "
                    "Note: Filtered `X` column order may not match column order in fit "
                    "this may lead to incorrect predictions and other errors."
                )
                X = X[:, self._selection]
        return self._lambda(*X.T) * np.ones(expected_shape)

    @property
    def _lambda(self):
        return lambdify(self._sympy_symbols, self._sympy)

1	"""Code for exporting discovered expressions to numpy"""
2	import numpy as np	1✔
3	import pandas as pd	1✔
4	from sympy import lambdify	1✔
5	import warnings	1✔
6
7
8	class CallableEquation:	1✔
9	"""Simple wrapper for numpy lambda functions built with sympy"""
10
11	def __init__(self, sympy_symbols, eqn, selection=None, variable_names=None):	1✔
12	self._sympy = eqn	1✔
13	self._sympy_symbols = sympy_symbols	1✔
14	self._selection = selection	1✔
15	self._variable_names = variable_names	1✔
16
17	def __repr__(self):	1✔
18	return f"PySRFunction(X=>{self._sympy})"	1✔
19
20	def __call__(self, X):	1✔
21	expected_shape = (X.shape[0],)	1✔
22	if isinstance(X, pd.DataFrame):	1✔
23	# Lambda function takes as argument:
24	return self._lambda(	1✔
25	**{k: X[k].values for k in self._variable_names}
26	) * np.ones(expected_shape)
27	if self._selection is not None:	1✔
28	if X.shape[1] != len(self._selection):	1✔
29	warnings.warn(	×
30	"`X` should be of shape (n_samples, len(self._selection)). "
31	"Automatically filtering `X` to selection. "
32	"Note: Filtered `X` column order may not match column order in fit "
33	"this may lead to incorrect predictions and other errors."
34	)
35	X = X[:, self._selection]	×
36	return self._lambda(X.T) np.ones(expected_shape)	1✔
37
38	@property	1✔
39	def _lambda(self):	1✔
40	return lambdify(self._sympy_symbols, self._sympy)	1✔

MilesCranmer / PySR / 5439183423

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