amici.ode_model.LogLikelihood
- class amici.ode_model.LogLikelihood(identifier, name, value)[source]
A LogLikelihood defines the distance between measurements and experiments for a particular observable. The final LogLikelihood value in the simulation will be the sum of all specified LogLikelihood instances evaluated at all timepoints, abbreviated by
Jy
.- __init__(identifier, name, value)[source]
Create a new Expression instance.
- Parameters
identifier (
sympy.core.symbol.Symbol
) – unique identifier of the LogLikelihoodname (
str
) – individual name of the LogLikelihood (does not need to be unique)value (
sympy.core.expr.Expr
) – formula
Methods Summary
__init__
(identifier, name, value)Create a new Expression instance.
get_id
()ModelQuantity identifier
get_name
()ModelQuantity name
get_val
()ModelQuantity value
set_val
(val)Set ModelQuantity value
Methods
- __init__(identifier, name, value)[source]
Create a new Expression instance.
- Parameters
identifier (
sympy.core.symbol.Symbol
) – unique identifier of the LogLikelihoodname (
str
) – individual name of the LogLikelihood (does not need to be unique)value (
sympy.core.expr.Expr
) – formula
- get_id()
ModelQuantity identifier
- Return type
- Returns
identifier of the ModelQuantity
- get_val()
ModelQuantity value
- Return type
- Returns
value of the ModelQuantity
- set_val(val)
Set ModelQuantity value
- Returns
value of the ModelQuantity