HSA

class synergy.combination.HSA(stronger_orientation=<ufunc 'minimum'>, drug1_model=None, drug2_model=None, **kwargs)

Bases: DoseDependentSynergyModel2D

Highest single agent (HSA)

HSA says that any improvement a combination gives over the strongest single agent counts as synergy.

Members

synergyarray_like, float

(-inf,0)=antagonism, (0,inf)=synergism

E_reference(d1, d2)

Return the expected effect of the combination of drugs at doses d1 and d2.

Parameters:

• d1 (ArrayLike) – Concentration of drug 1

• d2 (ArrayLike) – Concentration of drug 2

Return ArrayLike:

Reference (additive) values of E at the given doses

fit(d1, d2, E, **kwargs)

Fit the model to data.

Parameters:

• d1 (ArrayLike) – Concentration of drug 1

• d2 (ArrayLike) – Concentration of drug 2

• E (ArrayLike) – Effect of the combination of drugs at doses d1 and d2

• kwargs (dict) –

  • use_jacobian: whether to use the model jacobian when fitting single-drug models

  • Additional keyword arguments for scipy.optimize.curve_fit()

Return ArrayLike:

Synergy values

property is_fit

True if the model has been fit to data.

property is_specified

True if each single-drug model is specified.