Source code for biogeme.expressions.logical_or
"""Arithmetic expressions accepted by Biogeme: logical or
Michel Bierlaire
Sat Jun 14 2025, 10:26:25
"""
from __future__ import annotations
import logging
import jax.numpy as jnp
import pandas as pd
from biogeme.expressions import PymcModelBuilderType
from biogeme.floating_point import JAX_FLOAT
from pytensor.tensor import TensorVariable, neq, switch
from .base_expressions import ExpressionOrNumeric
from .binary_expressions import BinaryOperator
from .jax_utils import JaxFunctionType
logger = logging.getLogger(__name__)
[docs]
class Or(BinaryOperator):
"""
Logical or
"""
def __init__(self, left: ExpressionOrNumeric, right: ExpressionOrNumeric):
"""Constructor
:param left: first arithmetic expression
:type left: biogeme.expressions.Expression
:param right: second arithmetic expression
:type right: biogeme.expressions.Expression
"""
super().__init__(left, right)
[docs]
def deep_flat_copy(self) -> Or:
"""Provides a copy of the expression. It is deep in the sense that it generates copies of the children.
It is flat in the sense that any `MultipleExpression` is transformed into the currently selected expression.
The flat part is irrelevant for this expression.
"""
copy_left = self.left.deep_flat_copy()
copy_right = self.right.deep_flat_copy()
return type(self)(left=copy_left, right=copy_right)
def __str__(self) -> str:
return f'({self.left} or {self.right})'
def __repr__(self) -> str:
return f'({repr(self.left)} or {repr(self.right)})'
[docs]
def get_value(self) -> float:
"""Evaluates the value of the expression
:return: value of the expression
:rtype: float
"""
if self.left.get_value() != 0.0:
return 1.0
if self.right.get_value() != 0.0:
return 1.0
return 0.0
[docs]
def recursive_construct_jax_function(
self, numerically_safe: bool
) -> JaxFunctionType:
"""
Generates a function to be used by biogeme_jax. Must be overloaded by each expression
:return: the function takes two parameters: the parameters, and one row of the database.
"""
left_jax: JaxFunctionType = self.left.recursive_construct_jax_function(
numerically_safe=numerically_safe
)
right_jax: JaxFunctionType = self.right.recursive_construct_jax_function(
numerically_safe=numerically_safe
)
def the_jax_function(
parameters: jnp.ndarray,
one_row: jnp.ndarray,
the_draws: jnp.ndarray,
the_random_variables: jnp.ndarray,
) -> float:
left_value = left_jax(parameters, one_row, the_draws, the_random_variables)
right_value = right_jax(
parameters, one_row, the_draws, the_random_variables
)
condition = (left_value != 0.0) | (right_value != 0.0)
return condition.astype(JAX_FLOAT)
return the_jax_function
[docs]
def recursive_construct_pymc_model_builder(self) -> PymcModelBuilderType:
"""
Generates recursively a function to be used by PyMC.
Implements logical OR using numeric convention:
- 0 → False
- ≠0 → True
Returns 0.0 if both sides are zero, else 1.0.
"""
left_pymc = self.left.recursive_construct_pymc_model_builder()
right_pymc = self.right.recursive_construct_pymc_model_builder()
def builder(dataframe: pd.DataFrame) -> TensorVariable:
left_value = left_pymc(dataframe=dataframe)
right_value = right_pymc(dataframe=dataframe)
# Convert to boolean using nonzero test
left_bool = neq(left_value, 0.0)
right_bool = neq(right_value, 0.0)
# Logical and, then convert back to float (0.0 or 1.0)
return switch(left_bool | right_bool, 1.0, 0.0)
return builder