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"""Various functions to deprecate features."""
import warnings
def pysr(X, y, weights=None, **kwargs): # pragma: no cover
from .sr import PySRRegressor
warnings.warn(
"Calling `pysr` is deprecated. "
"Please use `model = PySRRegressor(**params); "
"model.fit(X, y)` going forward.",
FutureWarning,
)
model = PySRRegressor(**kwargs)
model.fit(X, y, weights=weights)
return model.equations_
def best(*args, **kwargs): # pragma: no cover
raise NotImplementedError(
"`best` has been deprecated. "
"Please use the `PySRRegressor` interface. "
"After fitting, you can return `.sympy()` "
"to get the sympy representation "
"of the best equation."
)
def best_row(*args, **kwargs): # pragma: no cover
raise NotImplementedError(
"`best_row` has been deprecated. "
"Please use the `PySRRegressor` interface. "
"After fitting, you can run `print(model)` to view the best equation, "
"or "
"`model.get_best()` to return the best equation's "
"row in `model.equations_`."
)
def best_tex(*args, **kwargs): # pragma: no cover
raise NotImplementedError(
"`best_tex` has been deprecated. "
"Please use the `PySRRegressor` interface. "
"After fitting, you can return `.latex()` to "
"get the sympy representation "
"of the best equation."
)
def best_callable(*args, **kwargs): # pragma: no cover
raise NotImplementedError(
"`best_callable` has been deprecated. Please use the `PySRRegressor` "
"interface. After fitting, you can use "
"`.predict(X)` to use the best callable."
)
def make_deprecated_kwargs_for_pysr_regressor():
"""Create dict of deprecated kwargs."""
deprecation_string = """
fractionReplaced => fraction_replaced
fractionReplacedHof => fraction_replaced_hof
npop => population_size
hofMigration => hof_migration
shouldOptimizeConstants => should_optimize_constants
weightAddNode => weight_add_node
weightDeleteNode => weight_delete_node
weightDoNothing => weight_do_nothing
weightInsertNode => weight_insert_node
weightMutateConstant => weight_mutate_constant
weightMutateOperator => weight_mutate_operator
weightRandomize => weight_randomize
weightSimplify => weight_simplify
crossoverProbability => crossover_probability
perturbationFactor => perturbation_factor
batchSize => batch_size
warmupMaxsizeBy => warmup_maxsize_by
useFrequency => use_frequency
useFrequencyInTournament => use_frequency_in_tournament
"""
# Turn this into a dict:
deprecated_kwargs = {}
for line in deprecation_string.splitlines():
line = line.replace(" ", "")
if line == "":
continue
old, new = line.split("=>")
deprecated_kwargs[old] = new
return deprecated_kwargs
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