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"""Various functions to deprecate features."""
import warnings
from .julia_import import jl
def install(*args, **kwargs):
del args, kwargs
warnings.warn(
"The `install` function has been removed. "
"PySR now uses the `juliacall` package to install its dependencies automatically at import time. ",
FutureWarning,
)
def init_julia(*args, **kwargs):
del args, kwargs
warnings.warn(
"The `init_julia` function has been removed. "
"Julia is now initialized automatically at import time.",
FutureWarning,
)
return jl
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."
)
DEPRECATED_KWARGS = {
"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",
"weightSwapOperands": "weight_swap_operands",
"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",
"ncyclesperiteration": "ncycles_per_iteration",
"loss": "elementwise_loss",
"full_objective": "loss_function",
}
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