MilesCranmer commited on
Commit
8b29fef
·
1 Parent(s): 21ae49d

Hide other internal functions

Browse files
Files changed (1) hide show
  1. pysr/sr.py +5 -5
pysr/sr.py CHANGED
@@ -192,7 +192,7 @@ def pysr(X=None, y=None, weights=None,
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  (as strings).
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194
  """
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- raise_depreciation_errors(limitPowComplexity, threads)
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  if isinstance(X, pd.DataFrame):
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  variable_names = list(X.columns)
@@ -210,7 +210,7 @@ def pysr(X=None, y=None, weights=None,
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  if len(X) > 10000 and not batching:
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  warnings.warn("Note: you are running with more than 10,000 datapoints. You should consider turning on batching (https://pysr.readthedocs.io/en/latest/docs/options/#batching). You should also reconsider if you need that many datapoints. Unless you have a large amount of noise (in which case you should smooth your dataset first), generally < 10,000 datapoints is enough to find a functional form with symbolic regression. More datapoints will lower the search speed.")
212
 
213
- X, variable_names = handle_feature_selection(
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  X, select_k_features,
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  use_custom_variable_names, variable_names, y
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  )
@@ -516,7 +516,7 @@ def _using_test_input(X, test, y):
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  return X, y
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518
 
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- def handle_feature_selection(X, select_k_features, use_custom_variable_names, variable_names, y):
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  if select_k_features is not None:
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  selection = run_feature_selection(X, y, select_k_features)
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  print(f"Using features {selection}")
@@ -562,7 +562,7 @@ def _set_paths(tempdir):
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  weights_filename=weights_filename, y_filename=y_filename)
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- def check_assertions(X, binary_operators, unary_operators, use_custom_variable_names, variable_names, weights, y):
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  # Check for potential errors before they happen
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  assert len(unary_operators) + len(binary_operators) > 0
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  assert len(X.shape) == 2
@@ -575,7 +575,7 @@ def check_assertions(X, binary_operators, unary_operators, use_custom_variable_n
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  assert len(variable_names) == X.shape[1]
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- def raise_depreciation_errors(limitPowComplexity, threads):
579
  if threads is not None:
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  raise ValueError("The threads kwarg is deprecated. Use procs.")
581
  if limitPowComplexity:
 
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  (as strings).
193
 
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  """
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+ _raise_depreciation_errors(limitPowComplexity, threads)
196
 
197
  if isinstance(X, pd.DataFrame):
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  variable_names = list(X.columns)
 
210
  if len(X) > 10000 and not batching:
211
  warnings.warn("Note: you are running with more than 10,000 datapoints. You should consider turning on batching (https://pysr.readthedocs.io/en/latest/docs/options/#batching). You should also reconsider if you need that many datapoints. Unless you have a large amount of noise (in which case you should smooth your dataset first), generally < 10,000 datapoints is enough to find a functional form with symbolic regression. More datapoints will lower the search speed.")
212
 
213
+ X, variable_names = _handle_feature_selection(
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  X, select_k_features,
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  use_custom_variable_names, variable_names, y
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  )
 
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  return X, y
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518
 
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+ def _handle_feature_selection(X, select_k_features, use_custom_variable_names, variable_names, y):
520
  if select_k_features is not None:
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  selection = run_feature_selection(X, y, select_k_features)
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  print(f"Using features {selection}")
 
562
  weights_filename=weights_filename, y_filename=y_filename)
563
 
564
 
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+ def _check_assertions(X, binary_operators, unary_operators, use_custom_variable_names, variable_names, weights, y):
566
  # Check for potential errors before they happen
567
  assert len(unary_operators) + len(binary_operators) > 0
568
  assert len(X.shape) == 2
 
575
  assert len(variable_names) == X.shape[1]
576
 
577
 
578
+ def _raise_depreciation_errors(limitPowComplexity, threads):
579
  if threads is not None:
580
  raise ValueError("The threads kwarg is deprecated. Use procs.")
581
  if limitPowComplexity: