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Allow multiple sympy conversions #36

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Allow multiple sympy conversions #36

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20760ba
Refactor get_best_individual_sympy to handle multiple individuals and…
PeterMollmann Mar 5, 2026
bc98cd3
Add petsc and petsc4py to environment dependencies
PeterMollmann Mar 5, 2026
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2 changes: 2 additions & 0 deletions environment.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -18,6 +18,8 @@ dependencies:
- typeguard
- yaml
- pygraphviz
- petsc
- petsc4py
- pip
- pip:
- git+https://github.com/cpml-au/dctkit
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24 changes: 15 additions & 9 deletions src/flex/gp/regressor.py
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Expand Up @@ -44,7 +44,7 @@ class GPSymbolicRegressor(RegressorMixin, BaseEstimator):
- Elitism and overlapping or non-overlapping generations
- Parallel fitness evaluation using Ray
- Validation-set monitoring
- Conversion of the best individual to a SymPy expression
- Conversion of the best individuals to a SymPy expression

Args:
pset_config: set of primitives and terminals (loosely or strongly typed).
Expand Down Expand Up @@ -942,25 +942,31 @@ def __save_train_fit_history(self, output_path: str):
join(output_path, "val_score_history.npy"), self.__val_score_history
)

def get_best_individual_sympy(
def get_best_individuals_sympy(
self,
sympy_conversion_rules: Dict = conversion_rules,
special_term_name: str = "c",
n_ind: int = 1,
):
"""Returns the SymPy expression of the best individual.
"""Returns the SymPy expression of the best individuals.

Args:
sympy_conversion_rules: mapping from GP primitives (DEAP) to SymPy
primitives.
special_term_name: name used for constants during SymPy conversion.
n_ind: number of best individuals to convert to SymPy.

Returns:
sympy representation of the best individual if conversion is enabled.
"""

best_sympy = parse_expr(
stringify_for_sympy(self._best, sympy_conversion_rules, special_term_name)
)
sympy representation of the best individuals.
"""
best_inds = self.get_best_individuals(n_ind=n_ind)
best_sympy = [None] * n_ind
for i in range(n_ind):
best_sympy[i] = parse_expr(
stringify_for_sympy(
best_inds[i], sympy_conversion_rules, special_term_name
)
)
return best_sympy

def get_train_fit_history(self):
Expand Down