MilesCranmer commited on
Commit
bad0567
1 Parent(s): 358f0ab

Move shape checking to fit()

Browse files
Files changed (1) hide show
  1. pysr/sr.py +11 -10
pysr/sr.py CHANGED
@@ -1015,16 +1015,6 @@ class PySRRegressor(BaseEstimator, RegressorMixin, MultiOutputMixin):
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  Validated list of variable names for each feature in `X`.
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  """
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- if X.shape[1] > 10000 and not self.batching:
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- warnings.warn(
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- "Note: you are running with more than 10,000 datapoints. "
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- "You should consider turning on batching (https://astroautomata.com/PySR/#/options?id=batching). "
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- "You should also reconsider if you need that many datapoints. "
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- "Unless you have a large amount of noise (in which case you "
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- "should smooth your dataset first), generally < 10,000 datapoints "
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- "is enough to find a functional form with symbolic regression. "
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- "More datapoints will lower the search speed."
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- )
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  if isinstance(X, pd.DataFrame):
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  if variable_names:
@@ -1415,6 +1405,17 @@ class PySRRegressor(BaseEstimator, RegressorMixin, MultiOutputMixin):
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  self._setup_equation_file()
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  # Parameter input validation (for parameters defined in __init__)
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  X, y, Xresampled, variable_names = self._validate_fit_params(
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  X, y, Xresampled, variable_names
 
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  Validated list of variable names for each feature in `X`.
1016
 
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  """
 
 
 
 
 
 
 
 
 
 
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  if isinstance(X, pd.DataFrame):
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  if variable_names:
 
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  self._setup_equation_file()
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+ if X.shape[1] > 10000 and not self.batching:
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+ warnings.warn(
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+ "Note: you are running with more than 10,000 datapoints. "
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+ "You should consider turning on batching (https://astroautomata.com/PySR/#/options?id=batching). "
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+ "You should also reconsider if you need that many datapoints. "
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+ "Unless you have a large amount of noise (in which case you "
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+ "should smooth your dataset first), generally < 10,000 datapoints "
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+ "is enough to find a functional form with symbolic regression. "
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+ "More datapoints will lower the search speed."
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+ )
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+
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  # Parameter input validation (for parameters defined in __init__)
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  X, y, Xresampled, variable_names = self._validate_fit_params(
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  X, y, Xresampled, variable_names