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Make compiled calculate, simulate, calculateDiff, and getLogProb work #10

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77c8cc0
get predefineds working and generated
perrydv May 29, 2026
8053561
model compiled and call path to calculate_impl works
perrydv May 31, 2026
3da626d
C++ model calculate, simulate, calculateDiff, and getLogProb are in p…
perrydv Jun 1, 2026
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326 changes: 152 additions & 174 deletions nimbleModel/R/declFunBaseClass.R
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Original file line number Diff line number Diff line change
@@ -1,190 +1,168 @@
#' @export
declFunBase_nClass <- nClass(
classname = "declFunBase_nClass",
Rpublic = list(
calculate = function(instr) {
calc_op(instr, "calc_one")
},
calculateDiff = function(instr) {
calc_op(instr, "calcDiff_one")
},
getLogProb = function(instr) {
calc_op(instr, "getLogProb_one")
},
calc_op = function(instr, fn) {
if(instr$type == 0) return(calc_0(instr, fn))
if(instr$type == 1) return(calc_1_seq(instr, fn))
if(instr$type == 2) return(calc_1_mat(instr, fn))
if(instr$type == 3) return(calc_1_matp(instr, fn))
return(0)
},
calc_0 = function(instr, fn) {
return(self[[fn]](0))
},
calc_1_seq =
function(instr, fn) {
logProb = 0
iStart <- instr$values[[1]][1] # Values seem to start offset by -1, a bit confusing
for(i in 1:instr$lens[1])
logProb <- logProb + self[[fn]](iStart + i)
return(logProb)
},
calc_1_mat =
function(instr, fn) {
logProb = 0
for(i in 1:instr$lens[1])
logProb <- logProb + self[[fn]](instr$values[[1]][i])
return(logProb)
},
calc_1_matp =
function(instr, fn) {
logProb = 0
for(i in 1:instr$lens[1])
logProb <- logProb + self[[fn]](instr$values[[1]][(instr$dims[1]*(i-1) + 1):(instr$dims[1]*i)]) ## Ok to call with a vector?
return(logProb)
},
simulate = function(instr) {
if(instr$type == 0) return(sim_0(instr))
if(instr$type == 1) return(sim_1_seq(instr))
if(instr$type == 2) return(sim_1_mat(instr))
if(instr$type == 3) return(sim_1_matp(instr))
},
sim_0 = function(instr) {
sim_one(0) ## sim_one will always has `idx` as arg?
},
sim_1_seq = function(instr) {
for(i in 1:instr$lens[1])
sim_one(instr$values[[1]][1]+i)
},
sim_1_mat = function(instr) {
for(i in 1:instr$lens[1])
sim_one(instr$values[[1]][i])
},
sim_1_matp = function(instr) {
for(i in 1:instr$lens[1])
sim_one(instr$values[[1]][(instr$dims[1]*(i-1) + 1):(instr$dims[1]*i)]) ## Ok to call with a vector?
}
),
Cpublic = list(
## model = 'modelBase_nClass',
ping = nFunction(
name = "ping",
function() {return(TRUE); returnType(logical())},
compileInfo = list(virtual=TRUE)
),
calculate_cpp = nFunction(
name = "calculate_cpp",
function(instr) {
stop("Uncompiled version of calculate_cpp should not be called.")
},
returnType = 'numericScalar',
compileInfo = list(virtual=TRUE,
C_fun = function(instr = 'instr_nClass') {
cppLiteral('Rprintf("declFunBase_nClass virtual base calculate_cpp should never be called (something is wrong)\\n");')
return(0)
})
),
calculateDiff_cpp = nFunction(
name = "calculateDiff_cpp",
function(instr) {
stop("Uncompiled version of calculateDiff_cpp should not be called.")
},
returnType = 'numericScalar',
compileInfo = list(virtual=TRUE,
C_fun = function(instr = 'instr_nClass') {
cppLiteral('Rprintf("declFunBase_nClass virtual base calculateDiff_cpp should never be called (something is wrong)\\n");')
return(0)
})
),
getLogProb_cpp = nFunction(
name = "getLogProb_cpp",
function(instr) {
stop("Uncompiled version of getLogProb_cpp should not be called.")
},
returnType = 'numericScalar',
compileInfo = list(virtual=TRUE,
C_fun = function(instr = 'instr_nClass') {
cppLiteral('Rprintf("declFunBase_nClass virtual base getLogProb_cpp should never be called (something is wrong)\\n");')
return(0)
})
),
simulate_cpp = nFunction(
name = "simulate_cpp",
function(instr) {
stop("Uncompiled version of simulate_cpp should not be called.")
},
returnType = 'void',
compileInfo = list(virtual=TRUE,
C_fun = function(instr = 'instr_nClass') {
cppLiteral('Rprintf("declFunBase_nClass virtual base simulate_cpp should never be called (something is wrong)\\n");')
})
)



calculate = nFunction(
name = "calculate",
fun = function(instr = 'instr_nClass') {
## TODO: how embed determination of vec and parallel cases here?
if(instr$type == 0) return(calc_0(instr))
if(instr$type == 1) return(calc_1_seq(instr))
if(instr$type == 2) return(calc_1_mat(instr))
if(instr$type == 3) return(calc_1_matp(instr))
return(0) ## Need to error trap/warn if unhandled type requested
}, returnType = 'numericScalar',
compileInfo = list(virtual=TRUE)
),
calc_0 = nFunction(
name = 'calc_0',
function(instr = 'instr_nClass') {
return(calc_one(0)) ## calc_one will always has `idx` as arg?
}, returnType = 'numericScalar'
),
calc_1_seq = nFunction(
name = 'calc_1_seq',
function(instr = 'instr_nClass') {
logProb = 0
for(i in 1:instr$lens[1])
logProb <- logProb + calc_one(instr$values[[1]][1]+i)
return(logProb)
}, returnType = 'numericScalar'
),
calc_1_mat = nFunction(
name = 'calc_1_mat',
function(instr = 'instr_nClass') {
logProb = 0
for(i in 1:instr$lens[1])
logProb <- logProb + calc_one(instr$values[[1]][i])
return(logProb)
}, returnType = 'numericScalar'
),
calc_1_matp = nFunction(
name = 'calc_1_mat',
function(instr = 'instr_nClass') {
logProb = 0
for(i in 1:instr$lens[1])
logProb <- logProb + calc_one(instr$values[[1]][(instr$dims[1]*(i-1) + 1):(instr$dims[1]*i)]) ## Ok to call with a vector?
return(logProb)
}, returnType = 'numericScalar'
),

calculateDiff = nFunction(
name = "calculateDiff",
fun = function(instr = 'instr_nClass') {
## TODO: how embed determination of vec and parallel cases here?
if(instr$type == 0) return(calcDiff_0(instr))
if(instr$type == 1) return(calcDiff_1_seq(instr))
if(instr$type == 2) return(calcDiff_1_mat(instr))
if(instr$type == 3) return(calcDiff_1_matp(instr))
return(0) ## Need to error trap/warn if unhandled type requested
}, returnType = 'numericScalar',
compileInfo = list(virtual=TRUE)
),
calcDiff_0 = nFunction(
name = 'calcDiff_0',
function(instr = 'instr_nClass') {
return(calcDiff_one(0)) ## calcDiff_one will always has `idx` as arg?
}, returnType = 'numericScalar'
),
calcDiff_1_seq = nFunction(
name = 'calcDiff_1_seq',
function(instr = 'instr_nClass') {
logProb = 0
for(i in 1:instr$lens[1])
logProb <- logProb + calcDiff_one(instr$values[[1]][1]+i)
return(logProb)
}, returnType = 'numericScalar'
),
calcDiff_1_mat = nFunction(
name = 'calcDiff_1_mat',
function(instr = 'instr_nClass') {
logProb = 0
for(i in 1:instr$lens[1])
logProb <- logProb + calcDiff_one(instr$values[[1]][i])
return(logProb)
}, returnType = 'numericScalar'
),
calcDiff_1_matp = nFunction(
name = 'calcDiff_1_mat',
function(instr = 'instr_nClass') {
logProb = 0
for(i in 1:instr$lens[1])
logProb <- logProb + calcDiff_one(instr$values[[1]][(instr$dims[1]*(i-1) + 1):(instr$dims[1]*i)]) ## Ok to call with a vector?
return(logProb)
}, returnType = 'numericScalar'
),


simulate = nFunction(
name = "simulate",
fun = function(instr = 'instr_nClass') {
## TODO: how embed determination of vec and parallel cases here?
if(instr$type == 0) sim_0(instr)
if(instr$type == 1) sim_1_seq(instr)
if(instr$type == 2) sim_1_mat(instr)
if(instr$type == 3) sim_1_matp(instr)
},
compileInfo = list(virtual=TRUE)
),
sim_0 = nFunction(
name = 'sim_0',
function(instr = 'instr_nClass') {
sim_one(0) ## sim_one will always has `idx` as arg?
}
),
sim_1_seq = nFunction(
name = 'sim_1_seq',
function(instr = 'instr_nClass') {
for(i in 1:instr$lens[1])
sim_one(instr$values[[1]][1]+i)
}
),
sim_1_mat = nFunction(
name = 'sim_1_mat',
function(instr = 'instr_nClass') {
for(i in 1:instr$lens[1])
sim_one(instr$values[[1]][i])
}
),
sim_1_matp = nFunction(
name = 'sim_1_mat',
function(instr = 'instr_nClass') {
for(i in 1:instr$lens[1])
sim_one(instr$values[[1]][(instr$dims[1]*(i-1) + 1):(instr$dims[1]*i)]) ## Ok to call with a vector?
}
),
# simulate = nFunction(
# name = "simulate",
# fun = function(instr = 'instr_nClass') {
# ## TODO: how embed determination of vec and parallel cases here?
# if(instr$type == 0) sim_0(instr)
# if(instr$type == 1) sim_1_seq(instr)
# if(instr$type == 2) sim_1_mat(instr)
# if(instr$type == 3) sim_1_matp(instr)
# },
# compileInfo = list(virtual=TRUE)
# ),
# sim_0 = nFunction(
# name = 'sim_0',
# function(instr = 'instr_nClass') {
# sim_one(0) ## sim_one will always has `idx` as arg?
# }
# ),
# sim_1_seq = nFunction(
# name = 'sim_1_seq',
# function(instr = 'instr_nClass') {
# for(i in 1:instr$lens[1])
# sim_one(instr$values[[1]][1]+i)
# }
# ),
# sim_1_mat = nFunction(
# name = 'sim_1_mat',
# function(instr = 'instr_nClass') {
# for(i in 1:instr$lens[1])
# sim_one(instr$values[[1]][i])
# }
# ),
# sim_1_matp = nFunction(
# name = 'sim_1_mat',
# function(instr = 'instr_nClass') {
# for(i in 1:instr$lens[1])
# sim_one(instr$values[[1]][(instr$dims[1]*(i-1) + 1):(instr$dims[1]*i)]) ## Ok to call with a vector?
# }
# ),

getLogProb = nFunction(
name = "getLogProb",
fun = function(instr = 'instr_nClass') {
## TODO: how embed determination of vec and parallel cases here?
if(instr$type == 0) return(getLogProb_0(instr))
if(instr$type == 1) return(getLogProb_1_seq(instr))
if(instr$type == 2) return(getLogProb_1_mat(instr))
if(instr$type == 3) return(getLogProb_1_matp(instr))
return(0) ## Need to error trap/warn if unhandled type requested
}, returnType = 'numericScalar',
compileInfo = list(virtual=TRUE)
),
getLogProb_0 = nFunction(
name = 'getLogProb_0',
function(instr = 'instr_nClass') {
return(getLogProb_one(0)) ## getLogProb_one will always has `idx` as arg?
}, returnType = 'numericScalar'
),
getLogProb_1_seq = nFunction(
name = 'getLogProb_1_seq',
function(instr = 'instr_nClass') {
logProb = 0
for(i in 1:instr$lens[1])
logProb <- logProb + getLogProb_one(instr$values[[1]][1]+i)
return(logProb)
}, returnType = 'numericScalar'
),
getLogProb_1_mat = nFunction(
name = 'getLogProb_1_mat',
function(instr = 'instr_nClass') {
logProb = 0
for(i in 1:instr$lens[1])
logProb <- logProb + getLogProb_one(instr$values[[1]][i])
return(logProb)
}, returnType = 'numericScalar'
),
getLogProb_1_matp = nFunction(
name = 'getLogProb_1_mat',
function(instr = 'instr_nClass') {
logProb = 0
for(i in 1:instr$lens[1])
logProb <- logProb + getLogProb_one(instr$values[[1]][(instr$dims[1]*(i-1) + 1):(instr$dims[1]*i)]) ## Ok to call with a vector?
return(logProb)
}, returnType = 'numericScalar'
)

),
## We haven't dealt with ensuring a virtual destructor when any method is virtual
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