# Copyright (C) 2020 David J. Wooten
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
from typing import Type
import numpy as np
from synergy.combination.synergy_model_2d import DoseDependentSynergyModel2D
from synergy.single.dose_response_model_1d import DoseResponseModel1D
from synergy.single.log_linear import LogLinear
[docs]class HSA(DoseDependentSynergyModel2D):
"""Highest single agent (HSA)
HSA says that any improvement a combination gives over the strongest single agent counts as synergy.
Members
-------
synergy : array_like, float
(-inf,0)=antagonism, (0,inf)=synergism
"""
def __init__(self, stronger_orientation=np.minimum, drug1_model=None, drug2_model=None, **kwargs):
super().__init__(drug1_model=drug1_model, drug2_model=drug2_model, **kwargs)
self.stronger_orientation = stronger_orientation
[docs] def E_reference(self, d1, d2):
E1_alone = self.drug1_model.E(d1)
E2_alone = self.drug2_model.E(d2)
return self.stronger_orientation(E1_alone, E2_alone)
def _get_synergy(self, d1, d2, E):
synergy = self.reference - E
return self._sanitize_synergy(d1, d2, synergy, 0)
@property
def _required_single_drug_class(self) -> Type[DoseResponseModel1D]:
return DoseResponseModel1D
@property
def _default_single_drug_class(self) -> Type[DoseResponseModel1D]:
return LogLinear