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Merge pull request #755 from galacticusorg/featDefaultParameterMap
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Allow a default `parameterMap` that includes all parameters
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@abensonca
abensonca authored Dec 9, 2024
2 parents 10b99e5 + b0c6d17 commit 6477dfc
Showing 1 changed file with 72 additions and 28 deletions.
100 changes: 72 additions & 28 deletions source/models.likelihoods.independent_likelihoods.F90
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Original file line number Diff line number Diff line change
Expand Up @@ -35,7 +35,28 @@

!![
<posteriorSampleLikelihood name="posteriorSampleLikelihoodIndependentLikelihoods">
<description>A posterior sampling likelihood class which combines other likelihoods assumed to be independent.</description>
<description>
A posterior sampling likelihood class which combines likelihoods from one or more other \refClass{posteriorSampleLikelihood}
classes that are assumed to be independent (i.e. the $\log \mathcal{L}$ of the models are simply summed to find the final
likelihood).

Since each \refClass{posteriorSampleLikelihood} class may require a different set of parameters a {\normalfont \ttfamily
[parameterMap]} parameter may be specified. If present, the number of {\normalfont \ttfamily [parameterMap]} parameters must
equal the number of {\normalfont \ttfamily [posteriorSampleLikelihood]} parameters. Each such parameter should give a
(space-separated) list of the names of parameters (as defined in the \refClass{modelParameterActive} class) which should be
passed to the corresponding {\normalfont \ttfamily [posteriorSampleLikelihood]}. If no {\normalfont \ttfamily
[parameterMap]} parameters are given then all parameters are passed to each \refClass{posteriorSampleLikelihood} class.

Similarly, a set of {\normalfont \ttfamily parameterInactiveMap} parameters may be given, to specify which (if any, an empty
{\normalfont \ttfamily value} is permissible) of the inactive parameters specified by \refClass{modelParameterInactive}
should be passed to the corresponding {\normalfont \ttfamily [posteriorSampleLikelihood]}. If no {\normalfont \ttfamily
[parameterInactiveMap]} then no inactive parameters are passed to any of the {\normalfont \ttfamily
[posteriorSampleLikelihood]} classes.

Optionally, a parameter {\normalfont \ttfamily [logLikelihoodAccept]} may be specified. Once the likelihood of a chain
reaches this value, no further evaluations of the likelihood will be made - the chain is assumed to be sufficiently likely
that it is ``acceptable''.
</description>
<linkedList type="posteriorSampleLikelihoodList" variable="modelLikelihoods" next="next" object="modelLikelihood_" objectType="posteriorSampleLikelihoodClass"/>
</posteriorSampleLikelihood>
!!]
Expand All @@ -46,6 +67,7 @@
private
type (posteriorSampleLikelihoodList), pointer :: modelLikelihoods => null()
double precision :: logLikelihoodAccept
logical :: parameterMapIdentity
contains
final :: independentLikelihoodsDestructor
procedure :: evaluate => independentLikelihoodsEvaluate
Expand Down Expand Up @@ -78,7 +100,7 @@ function independentLikelihoodsConstructorParameters(parameters) result(self)
integer :: i , parameterMapCount
type (enumerationInputParameterErrorStatusType ) :: errorStatus
type (varying_string ) :: parameterMapJoined

!![
<inputParameter>
<name>logLikelihoodAccept</name>
Expand All @@ -88,11 +110,18 @@ function independentLikelihoodsConstructorParameters(parameters) result(self)
<source>parameters</source>
</inputParameter>
!!]
self%parameterMapIdentity=.false.
if ( &
& parameters%copiesCount('posteriorSampleLikelihood',zeroIfNotPresent=.true.) &
& /= &
& parameters%copiesCount('parameterMap' ,zeroIfNotPresent=.true.) &
& ) call Error_Report('number of parameter maps must match number of likelihoods'//{introspection:location})
& ) then
if (parameters%copiesCount('parameterMap',zeroIfNotPresent=.true.) == 0) then
self%parameterMapIdentity=.true.
else
call Error_Report('number of parameter maps must match number of likelihoods'//{introspection:location})
end if
end if
self %modelLikelihoods => null()
modelLikelihood_ => null()
do i=1,parameters%copiesCount('posteriorSampleLikelihood',zeroIfNotPresent=.true.)
Expand All @@ -108,25 +137,32 @@ function independentLikelihoodsConstructorParameters(parameters) result(self)
!!]
modelLikelihood_%simulationState =posteriorSampleStateSimple(1)
modelLikelihood_%parameterMapInitialized=.false.
call parameters%value('parameterMap',parameterMapJoined,copyInstance=i)
parameterMapCount=String_Count_Words(char(parameterMapJoined)," ")
allocate(modelLikelihood_%parameterMap (parameterMapCount))
allocate(modelLikelihood_%parameterMapNames (parameterMapCount))
allocate(modelLikelihood_%modelParametersActive_(parameterMapCount))
call String_Split_Words(modelLikelihood_%parameterMapNames,char(parameterMapJoined)," ")
call modelLikelihood_%simulationState%parameterCountSet(parameterMapCount)
call parameters%value('parameterInactiveMap',parameterMapJoined,copyInstance=i,errorStatus=errorStatus)
if (errorStatus == inputParameterErrorStatusSuccess ) then
if (.not.self%parameterMapIdentity) then
call parameters%value('parameterMap',parameterMapJoined,copyInstance=i)
parameterMapCount=String_Count_Words(char(parameterMapJoined)," ")
allocate(modelLikelihood_%parameterMapInactive (parameterMapCount))
allocate(modelLikelihood_%parameterMapNamesInactive(parameterMapCount))
allocate(modelLikelihood_%modelParametersInactive_ (parameterMapCount))
call String_Split_Words(modelLikelihood_%parameterMapNamesInactive,char(parameterMapJoined)," ")
else if (errorStatus == inputParameterErrorStatusEmptyValue) then
! Empty value is acceptable.
allocate(modelLikelihood_%modelParametersInactive_ ( 0))
allocate(modelLikelihood_%parameterMap (parameterMapCount))
allocate(modelLikelihood_%parameterMapNames (parameterMapCount))
allocate(modelLikelihood_%modelParametersActive_(parameterMapCount))
call String_Split_Words(modelLikelihood_%parameterMapNames,char(parameterMapJoined)," ")
call modelLikelihood_%simulationState%parameterCountSet(parameterMapCount)
end if
if (parameters%copiesCount('parameterInactiveMap',zeroIfNotPresent=.true.) == 0) then
! No inactive parameter map is acceptable.
allocate (modelLikelihood_%modelParametersInactive_ ( 0))
else
call Error_Report('invalid parameter'//{introspection:location})
call parameters%value('parameterInactiveMap',parameterMapJoined,copyInstance=i,errorStatus=errorStatus)
if (errorStatus == inputParameterErrorStatusSuccess ) then
parameterMapCount=String_Count_Words(char(parameterMapJoined)," ")
allocate(modelLikelihood_%parameterMapInactive (parameterMapCount))
allocate(modelLikelihood_%parameterMapNamesInactive(parameterMapCount))
allocate(modelLikelihood_%modelParametersInactive_ (parameterMapCount))
call String_Split_Words(modelLikelihood_%parameterMapNamesInactive,char(parameterMapJoined)," ")
else if (errorStatus == inputParameterErrorStatusEmptyValue) then
! Empty value is acceptable.
allocate(modelLikelihood_%modelParametersInactive_ ( 0))
else
call Error_Report('invalid parameter'//{introspection:location})
end if
end if
end do
!![
Expand Down Expand Up @@ -215,16 +251,24 @@ Return the log-likelihood for the halo mass function likelihood function.
if (present(logLikelihoodVariance)) logLikelihoodVariance = 0.0d0
do while (associated(modelLikelihood_))
if (.not.modelLikelihood_%parameterMapInitialized) then
if (self%parameterMapIdentity) then
allocate(modelLikelihood_%parameterMap (size(modelParametersActive_)))
allocate(modelLikelihood_%modelParametersActive_(size(modelParametersActive_)))
end if
do i=1,size(modelLikelihood_%parameterMap)
! Determine the mapping of the simulation state vector to this likelihood.
modelLikelihood_%parameterMap(i)=-1
do j=1,size(modelParametersActive_)
if (modelParametersActive_(j)%modelParameter_%name() == modelLikelihood_%parameterMapNames(i)) then
modelLikelihood_%parameterMap(i)=j
exit
end if
end do
if (modelLikelihood_%parameterMap(i) == -1) call Error_Report('failed to find matching parameter ['//char(modelLikelihood_%parameterMapNames(i))//']'//{introspection:location})
if (self%parameterMapIdentity) then
modelLikelihood_%parameterMap(i)=i
else
modelLikelihood_%parameterMap(i)=-1
do j=1,size(modelParametersActive_)
if (modelParametersActive_(j)%modelParameter_%name() == modelLikelihood_%parameterMapNames(i)) then
modelLikelihood_%parameterMap(i)=j
exit
end if
end do
if (modelLikelihood_%parameterMap(i) == -1) call Error_Report('failed to find matching parameter ['//char(modelLikelihood_%parameterMapNames(i))//']'//{introspection:location})
end if
! Copy the model parameter definition.
allocate(modelLikelihood_%modelParametersActive_(i)%modelParameter_,mold=modelParametersActive_(modelLikelihood_%parameterMap(i))%modelParameter_)
!![
Expand Down

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