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R/CHECKSUCCESS.R
In MoLE: Modeling Language Evolution
CHECKSUCCESS <-
function(speakerID, proposition, situation){
solutionMethod=world$solutionMethod; distinctiveness=world$distinctiveness; topicCopy=world$topicCopy; frequency=world$frequency; referenceThreshold=world$referenceThreshold; generalization=world$generalization; wordOrder=world$wordOrder
speaker=population[[speakerID]]
elaborate='unnecessary'
verb=proposition$verb
if(verb$type=='twoPlace'){
external=proposition$external
internal=proposition$internal
external$distractorTyping=VMATCH(external[, grep('^D\\d',names(external))], verb[,grep('^Int\\d',names(verb))])
internal$distractorTyping=VMATCH(internal[, grep('^D\\d',names(internal))], verb[,grep('^Ext\\d',names(verb))])
if(max(external$typing, internal$typing) < (max(external$distractorTyping, internal$distractorTyping) + distinctiveness)){elaborate='necessary'}
if('marker'%in%names(external) | 'marker'%in%names(internal)){elaborate='unnecessary'}
actor=ifelse(ACTOR(verb[,grep('^Ext\\d',names(verb))], verb[,grep('^Int\\d',names(verb))])==1, 'external','internal')
if(generalization==TRUE & elaborate=='necessary'){
index=speaker$usageHistory$index
yangIndex=TRUE %in% c(index$no < ((index$yes + index$no)/log(index$yes + index$no)))
if(yangIndex==TRUE){
externalRole=ifelse(actor=='external', 'actor', 'undergoer'); internalRole=ifelse(actor=='internal', 'actor', 'undergoer')
externalPerson=external$person; internalPerson=internal$person
if('extMarker'%in%names(verb)){
data=index[index$role==externalRole & index$person==externalPerson, ]
if(data$no < ((data$yes + data$no)/log(data$yes + data$no)) & externalPerson!=internalPerson){elaborate='unnecessary'}
}
if('intMarker'%in%names(verb)){
data=index[index$role==internalRole & index$person==internalPerson, ]
if(data$no < ((data$yes + data$no)/log(data$yes + data$no)) & externalPerson!=internalPerson){elaborate='unnecessary'}
} } }
if(elaborate=='necessary'){
#external
topic=external$topic
pronouns=speaker$nouns[speaker$nouns$person==external$person & speaker$nouns$productionEffort>referenceThreshold,]
if(external$person!=3){
if(nrow(pronouns)>1){
pronouns$match=VMATCH(verb[,grep('^Ext\\d',names(verb))], pronouns[,grep('^D\\d',names(pronouns))])
pronouns$collostruction=0
collostructions=speaker$collostructions$SV[speaker$collostructions$SV$V==verb$ID,]
pronouns[pronouns$ID%in%collostructions$S,]$collostruction=collostructions[na.omit(match(pronouns$ID, collostructions$S)),]$frequency
pronouns=pronouns[order(CANDIDATESCORE(pronouns), decreasing=TRUE),]
external=pronouns[1,]
} }
if(external$person==3){
distractors=situation$personA
if(actor=='internal'){distractors=situation$personU} #if non-standard role projection...
if(sum(distractors==external$person, na.rm=TRUE)==1){
pronouns$match=VMATCH(verb[,grep('^Ext\\d',names(verb))], pronouns[,grep('^D\\d',names(pronouns))])
pronouns$collostruction=0
collostructions=speaker$collostructions$SV[speaker$collostructions$SV$V==verb$ID,]
pronouns[pronouns$ID%in%collostructions$S,]$collostruction=collostructions[na.omit(match(pronouns$ID, collostructions$S)),]$frequency
pronouns=pronouns[order(CANDIDATESCORE(pronouns), decreasing=TRUE),]
external=pronouns[1,]
} }
external$topic=topic
external$typing=VMATCH(external[, grep('^D\\d',names(external))], verb[,grep('^Ext\\d',names(verb))])
#internal
topic=internal$topic
pronouns=speaker$nouns[speaker$nouns$person==internal$person & speaker$nouns$productionEffort>referenceThreshold,]
if(internal$person!=3){
if(nrow(pronouns)>1){
pronouns$match=VMATCH(verb[,grep('^Int\\d',names(verb))], pronouns[,grep('^D\\d',names(pronouns))])
pronouns$collostruction=0
collostructions=speaker$collostructions$OV[speaker$collostructions$OV$V==verb$ID,]
pronouns[pronouns$ID%in%collostructions$O,]$collostruction=collostructions[na.omit(match(pronouns$ID, collostructions$O)),]$frequency
pronouns=pronouns[order(CANDIDATESCORE(pronouns), decreasing=TRUE),]
internal=pronouns[1,]
} }
if(internal$person==3){
distractors=situation$personU
if(actor=='internal'){distractors=situation$personA}
if(sum(distractors==internal$person, na.rm=TRUE)==1){
pronouns$match=VMATCH(verb[,grep('^Int\\d',names(verb))], pronouns[,grep('^D\\d',names(pronouns))])
pronouns$collostruction=0
collostructions=speaker$collostructions$OV[speaker$collostructions$OV$V==verb$ID,]
pronouns[pronouns$ID%in%collostructions$O,]$collostruction=collostructions[na.omit(match(pronouns$ID, collostructions$O)),]$frequency
pronouns=pronouns[order(CANDIDATESCORE(pronouns), decreasing=TRUE),]
internal=pronouns[1,]
} }
internal$topic=topic
internal$typing=VMATCH(internal[,grep('^D\\d',names(internal))], verb[,grep('^Int\\d',names(verb))])
external$distractorTyping=VMATCH(external[, grep('^D\\d',names(external))], verb[,grep('^Int\\d',names(verb))])
internal$distractorTyping=VMATCH(internal[, grep('^D\\d',names(internal))], verb[,grep('^Ext\\d',names(verb))])
if(max(external$typing, internal$typing) > (max(external$distractorTyping, internal$distractorTyping) + distinctiveness)){elaborate='unnecessary'}
}
if(generalization==TRUE & wordOrder==TRUE & sum(speaker$wordOrder$success)>8){
yangWordOrder=TRUE %in%
c((sum(speaker$wordOrder$success)-speaker$wordOrder$success) < (sum(speaker$wordOrder$success)/log(sum(speaker$wordOrder$success)))) |
c(sum(speaker$wordOrder[grep('^A', speaker$wordOrder$order, invert=TRUE), ]$success) < (sum(speaker$wordOrder$success)/log(sum(speaker$wordOrder$success)))) |
c(sum(speaker$wordOrder[grep('V$', speaker$wordOrder$order, invert=TRUE), ]$success) < (sum(speaker$wordOrder$success)/log(sum(speaker$wordOrder$success)))) |
c(sum(speaker$wordOrder[grep('UV', speaker$wordOrder$order, invert=TRUE), ]$success) < (sum(speaker$wordOrder$success)/log(sum(speaker$wordOrder$success)))) |
c(sum(speaker$wordOrder[grep('VU', speaker$wordOrder$order, invert=TRUE), ]$success) < (sum(speaker$wordOrder$success)/log(sum(speaker$wordOrder$success))))
if(yangWordOrder==TRUE){
standard=speaker$wordOrder$order[(sum(speaker$wordOrder$success)-speaker$wordOrder$success) < (sum(speaker$wordOrder$success)/log(sum(speaker$wordOrder$success)))]
if(length(standard)==0){
if(sum(speaker$wordOrder[grep('^A', speaker$wordOrder$order, invert=TRUE), ]$success) < (sum(speaker$wordOrder$success)/log(sum(speaker$wordOrder$success)))){standard='^A'}
if(sum(speaker$wordOrder[grep('V$', speaker$wordOrder$order, invert=TRUE), ]$success) < (sum(speaker$wordOrder$success)/log(sum(speaker$wordOrder$success)))){standard='V$'}
if(sum(speaker$wordOrder[grep('UV', speaker$wordOrder$order, invert=TRUE), ]$success) < (sum(speaker$wordOrder$success)/log(sum(speaker$wordOrder$success)))){standard='UV'}
if(sum(speaker$wordOrder[grep('VU', speaker$wordOrder$order, invert=TRUE), ]$success) < (sum(speaker$wordOrder$success)/log(sum(speaker$wordOrder$success)))){standard='VU'}
}
undergoer=ifelse(actor=='external', 'internal', 'external')
order=paste(names(proposition), collapse=''); order=gsub(actor, 'A', order); order=gsub(undergoer, 'U', order); order=gsub('verb', 'V', order); order=gsub('target', '', order)
if(grepl(standard, order)){elaborate='unnecessary'}
} }
if(elaborate=='necessary'){
markers=speaker$nouns[speaker$nouns$person==3, ]
markers=markers[sample(nrow(markers)),]
if(solutionMethod=='random'){solutionMethod=sample(c('internal', 'external'),1)}
if(solutionMethod=='firstArgument'){solutionMethod=ifelse(grep('internal',names(proposition)) < grep('external',names(proposition)),'internal','external')}
if(solutionMethod=='secondArgument'){solutionMethod=ifelse(grep('internal',names(proposition)) > grep('external',names(proposition)),'internal','external')}
if(solutionMethod=='worstPerformer'){solutionMethod=ifelse((external$typing-external$distractorTyping) < (internal$typing-internal$distractorTyping), 'external', 'internal')}
if(solutionMethod=='firstFail'){solutionMethod=ifelse(grep('internal',names(proposition)) < grep('external',names(proposition)) & internal$typing < internal$distractorTyping, 'internal','external')}
if(solutionMethod=='bestMarker'){
#internal
markers$match=VMATCH(verb[,grep('^Int\\d',names(verb))], markers[,grep('^D\\d',names(markers))])
markers$collostruction=0
collostructions=speaker$collostructions$OV[speaker$collostructions$OV$V==verb$ID,]
markers[markers$ID%in%collostructions$O,]$collostruction=collostructions[na.omit(match(markers$ID, collostructions$O)),]$frequency
markers$internalScore=CANDIDATESCORE(markers, type='nounMarker')
#external
markers$match=VMATCH(verb[,grep('^Ext\\d',names(verb))], markers[,grep('^D\\d',names(markers))])
markers$collostruction=0
collostructions=speaker$collostructions$SV[speaker$collostructions$SV$V==verb$ID,]
markers[markers$ID%in%collostructions$S,]$collostruction=collostructions[na.omit(match(markers$ID, collostructions$S)),]$frequency
markers$externalScore=CANDIDATESCORE(markers, type='nounMarker')
if(max(markers$internalScore) == max(markers$externalScore)){solutionMethod=sample(c('internal','external'), 1)}
if(max(markers$internalScore) > max(markers$externalScore)){solutionMethod='internal'}
if(max(markers$internalScore) < max(markers$externalScore)){solutionMethod='external'}
}
if(solutionMethod=='internal' | solutionMethod=='both'){
markers$match=VMATCH(verb[,grep('^Int\\d',names(verb))], markers[,grep('^D\\d',names(markers))])
markers$collostruction=0
collostructions=speaker$collostructions$OV[speaker$collostructions$OV$V==verb$ID,]
markers[markers$ID%in%collostructions$O,]$collostruction=collostructions[na.omit(match(markers$ID, collostructions$O)),]$frequency
markers=markers[order(CANDIDATESCORE(markers, type='nounMarker'), decreasing=TRUE),]
markers$distractorMatch=VMATCH(verb[,grep('^Ext\\d',names(verb))], markers[,grep('^D\\d',names(markers))])
markerID=0
for (i in 1:nrow(markers)){
if(markers[i,]$match > (markers[i,]$distractorMatch + distinctiveness)){
markerID=markers[i,]$ID
markerCollostruction=markers[i,]$collostruction
break()
} }
if(markerID==0){
markerID=markers[MAX(markers$match, forceChoice=TRUE),]$ID
markerCollostruction=markers[MAX(markers$match, forceChoice=TRUE),]$collostruction
}
internal$markerID=markerID
internal$marker=speaker$nouns[speaker$nouns$ID==markerID,]$form
if(frequency=='absolute'){internal$markerFrequency=speaker$nouns[speaker$nouns$ID==markerID,]$frequency}
if(frequency=='relative'){internal$markerFrequency=speaker$nouns[speaker$nouns$ID==markerID,]$nounMarker}
internal$markerRecency=speaker$nouns[speaker$nouns$ID==markerID,]$recency
internal$markerCollostruction=markerCollostruction
}
if(solutionMethod=='external' | solutionMethod=='both'){
markers$match=VMATCH(verb[,grep('^Ext\\d',names(verb))], markers[,grep('^D\\d',names(markers))])
markers$collostruction=0
collostructions=speaker$collostructions$SV[speaker$collostructions$SV$V==verb$ID,]
markers[markers$ID%in%collostructions$S,]$collostruction=collostructions[na.omit(match(markers$ID, collostructions$S)),]$frequency
markers=markers[order(CANDIDATESCORE(markers, type='nounMarker'), decreasing=TRUE),]
markers$distractorMatch=VMATCH(verb[,grep('^Int\\d',names(verb))], markers[,grep('^D\\d',names(markers))])
markerID=0
for (i in 1:nrow(markers)){
if(markers[i,]$match > (markers[i,]$distractorMatch + distinctiveness)){
markerID=markers[i,]$ID
markerCollostruction=markers[i,]$collostruction
break()
} }
if(markerID==0){
markerID=markers[MAX(markers$match, forceChoice=TRUE),]$ID
markerCollostruction=markers[MAX(markers$match, forceChoice=TRUE),]$collostruction
}
external$markerID=markerID
external$marker=speaker$nouns[speaker$nouns$ID==markerID,]$form
if(frequency=='absolute'){external$markerFrequency=speaker$nouns[speaker$nouns$ID==markerID,]$frequency}
if(frequency=='relative'){external$markerFrequency=speaker$nouns[speaker$nouns$ID==markerID,]$nounMarker}
external$markerRecency=speaker$nouns[speaker$nouns$ID==markerID,]$recency
external$markerCollostruction=markerCollostruction
} }
proposition$external=external
proposition$internal=internal
}
proposition
}
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CHECKSUCCESS <-
function(speakerID, proposition, situation){
solutionMethod=world$solutionMethod; distinctiveness=world$distinctiveness; topicCopy=world$topicCopy; frequency=world$frequency; referenceThreshold=world$referenceThreshold; generalization=world$generalization; wordOrder=world$wordOrder
speaker=population[[speakerID]]
elaborate='unnecessary'
verb=proposition$verb
if(verb$type=='twoPlace'){
external=proposition$external
internal=proposition$internal
external$distractorTyping=VMATCH(external[, grep('^D\\d',names(external))], verb[,grep('^Int\\d',names(verb))])
internal$distractorTyping=VMATCH(internal[, grep('^D\\d',names(internal))], verb[,grep('^Ext\\d',names(verb))])
if(max(external$typing, internal$typing) < (max(external$distractorTyping, internal$distractorTyping) + distinctiveness)){elaborate='necessary'}
if('marker'%in%names(external) | 'marker'%in%names(internal)){elaborate='unnecessary'}
actor=ifelse(ACTOR(verb[,grep('^Ext\\d',names(verb))], verb[,grep('^Int\\d',names(verb))])==1, 'external','internal')
if(generalization==TRUE & elaborate=='necessary'){
index=speaker$usageHistory$index
yangIndex=TRUE %in% c(index$no < ((index$yes + index$no)/log(index$yes + index$no)))
if(yangIndex==TRUE){
externalRole=ifelse(actor=='external', 'actor', 'undergoer'); internalRole=ifelse(actor=='internal', 'actor', 'undergoer')
externalPerson=external$person; internalPerson=internal$person
if('extMarker'%in%names(verb)){
data=index[index$role==externalRole & index$person==externalPerson, ]
if(data$no < ((data$yes + data$no)/log(data$yes + data$no)) & externalPerson!=internalPerson){elaborate='unnecessary'}
}
if('intMarker'%in%names(verb)){
data=index[index$role==internalRole & index$person==internalPerson, ]
if(data$no < ((data$yes + data$no)/log(data$yes + data$no)) & externalPerson!=internalPerson){elaborate='unnecessary'}
} } }
if(elaborate=='necessary'){
#external
topic=external$topic
pronouns=speaker$nouns[speaker$nouns$person==external$person & speaker$nouns$productionEffort>referenceThreshold,]
if(external$person!=3){
if(nrow(pronouns)>1){
pronouns$match=VMATCH(verb[,grep('^Ext\\d',names(verb))], pronouns[,grep('^D\\d',names(pronouns))])
pronouns$collostruction=0
collostructions=speaker$collostructions$SV[speaker$collostructions$SV$V==verb$ID,]
pronouns[pronouns$ID%in%collostructions$S,]$collostruction=collostructions[na.omit(match(pronouns$ID, collostructions$S)),]$frequency
pronouns=pronouns[order(CANDIDATESCORE(pronouns), decreasing=TRUE),]
external=pronouns[1,]
} }
if(external$person==3){
distractors=situation$personA
if(actor=='internal'){distractors=situation$personU} #if non-standard role projection...
if(sum(distractors==external$person, na.rm=TRUE)==1){
pronouns$match=VMATCH(verb[,grep('^Ext\\d',names(verb))], pronouns[,grep('^D\\d',names(pronouns))])
pronouns$collostruction=0
collostructions=speaker$collostructions$SV[speaker$collostructions$SV$V==verb$ID,]
pronouns[pronouns$ID%in%collostructions$S,]$collostruction=collostructions[na.omit(match(pronouns$ID, collostructions$S)),]$frequency
pronouns=pronouns[order(CANDIDATESCORE(pronouns), decreasing=TRUE),]
external=pronouns[1,]
} }
external$topic=topic
external$typing=VMATCH(external[, grep('^D\\d',names(external))], verb[,grep('^Ext\\d',names(verb))])
#internal
topic=internal$topic
pronouns=speaker$nouns[speaker$nouns$person==internal$person & speaker$nouns$productionEffort>referenceThreshold,]
if(internal$person!=3){
if(nrow(pronouns)>1){
pronouns$match=VMATCH(verb[,grep('^Int\\d',names(verb))], pronouns[,grep('^D\\d',names(pronouns))])
pronouns$collostruction=0
collostructions=speaker$collostructions$OV[speaker$collostructions$OV$V==verb$ID,]
pronouns[pronouns$ID%in%collostructions$O,]$collostruction=collostructions[na.omit(match(pronouns$ID, collostructions$O)),]$frequency
pronouns=pronouns[order(CANDIDATESCORE(pronouns), decreasing=TRUE),]
internal=pronouns[1,]
} }
if(internal$person==3){
distractors=situation$personU
if(actor=='internal'){distractors=situation$personA}
if(sum(distractors==internal$person, na.rm=TRUE)==1){
pronouns$match=VMATCH(verb[,grep('^Int\\d',names(verb))], pronouns[,grep('^D\\d',names(pronouns))])
pronouns$collostruction=0
collostructions=speaker$collostructions$OV[speaker$collostructions$OV$V==verb$ID,]
pronouns[pronouns$ID%in%collostructions$O,]$collostruction=collostructions[na.omit(match(pronouns$ID, collostructions$O)),]$frequency
pronouns=pronouns[order(CANDIDATESCORE(pronouns), decreasing=TRUE),]
internal=pronouns[1,]
} }
internal$topic=topic
internal$typing=VMATCH(internal[,grep('^D\\d',names(internal))], verb[,grep('^Int\\d',names(verb))])
external$distractorTyping=VMATCH(external[, grep('^D\\d',names(external))], verb[,grep('^Int\\d',names(verb))])
internal$distractorTyping=VMATCH(internal[, grep('^D\\d',names(internal))], verb[,grep('^Ext\\d',names(verb))])
if(max(external$typing, internal$typing) > (max(external$distractorTyping, internal$distractorTyping) + distinctiveness)){elaborate='unnecessary'}
}
if(generalization==TRUE & wordOrder==TRUE & sum(speaker$wordOrder$success)>8){
yangWordOrder=TRUE %in%
c((sum(speaker$wordOrder$success)-speaker$wordOrder$success) < (sum(speaker$wordOrder$success)/log(sum(speaker$wordOrder$success)))) |
c(sum(speaker$wordOrder[grep('^A', speaker$wordOrder$order, invert=TRUE), ]$success) < (sum(speaker$wordOrder$success)/log(sum(speaker$wordOrder$success)))) |
c(sum(speaker$wordOrder[grep('V$', speaker$wordOrder$order, invert=TRUE), ]$success) < (sum(speaker$wordOrder$success)/log(sum(speaker$wordOrder$success)))) |
c(sum(speaker$wordOrder[grep('UV', speaker$wordOrder$order, invert=TRUE), ]$success) < (sum(speaker$wordOrder$success)/log(sum(speaker$wordOrder$success)))) |
c(sum(speaker$wordOrder[grep('VU', speaker$wordOrder$order, invert=TRUE), ]$success) < (sum(speaker$wordOrder$success)/log(sum(speaker$wordOrder$success))))
if(yangWordOrder==TRUE){
standard=speaker$wordOrder$order[(sum(speaker$wordOrder$success)-speaker$wordOrder$success) < (sum(speaker$wordOrder$success)/log(sum(speaker$wordOrder$success)))]
if(length(standard)==0){
if(sum(speaker$wordOrder[grep('^A', speaker$wordOrder$order, invert=TRUE), ]$success) < (sum(speaker$wordOrder$success)/log(sum(speaker$wordOrder$success)))){standard='^A'}
if(sum(speaker$wordOrder[grep('V$', speaker$wordOrder$order, invert=TRUE), ]$success) < (sum(speaker$wordOrder$success)/log(sum(speaker$wordOrder$success)))){standard='V$'}
if(sum(speaker$wordOrder[grep('UV', speaker$wordOrder$order, invert=TRUE), ]$success) < (sum(speaker$wordOrder$success)/log(sum(speaker$wordOrder$success)))){standard='UV'}
if(sum(speaker$wordOrder[grep('VU', speaker$wordOrder$order, invert=TRUE), ]$success) < (sum(speaker$wordOrder$success)/log(sum(speaker$wordOrder$success)))){standard='VU'}
}
undergoer=ifelse(actor=='external', 'internal', 'external')
order=paste(names(proposition), collapse=''); order=gsub(actor, 'A', order); order=gsub(undergoer, 'U', order); order=gsub('verb', 'V', order); order=gsub('target', '', order)
if(grepl(standard, order)){elaborate='unnecessary'}
} }
if(elaborate=='necessary'){
markers=speaker$nouns[speaker$nouns$person==3, ]
markers=markers[sample(nrow(markers)),]
if(solutionMethod=='random'){solutionMethod=sample(c('internal', 'external'),1)}
if(solutionMethod=='firstArgument'){solutionMethod=ifelse(grep('internal',names(proposition)) < grep('external',names(proposition)),'internal','external')}
if(solutionMethod=='secondArgument'){solutionMethod=ifelse(grep('internal',names(proposition)) > grep('external',names(proposition)),'internal','external')}
if(solutionMethod=='worstPerformer'){solutionMethod=ifelse((external$typing-external$distractorTyping) < (internal$typing-internal$distractorTyping), 'external', 'internal')}
if(solutionMethod=='firstFail'){solutionMethod=ifelse(grep('internal',names(proposition)) < grep('external',names(proposition)) & internal$typing < internal$distractorTyping, 'internal','external')}
if(solutionMethod=='bestMarker'){
#internal
markers$match=VMATCH(verb[,grep('^Int\\d',names(verb))], markers[,grep('^D\\d',names(markers))])
markers$collostruction=0
collostructions=speaker$collostructions$OV[speaker$collostructions$OV$V==verb$ID,]
markers[markers$ID%in%collostructions$O,]$collostruction=collostructions[na.omit(match(markers$ID, collostructions$O)),]$frequency
markers$internalScore=CANDIDATESCORE(markers, type='nounMarker')
#external
markers$match=VMATCH(verb[,grep('^Ext\\d',names(verb))], markers[,grep('^D\\d',names(markers))])
markers$collostruction=0
collostructions=speaker$collostructions$SV[speaker$collostructions$SV$V==verb$ID,]
markers[markers$ID%in%collostructions$S,]$collostruction=collostructions[na.omit(match(markers$ID, collostructions$S)),]$frequency
markers$externalScore=CANDIDATESCORE(markers, type='nounMarker')
if(max(markers$internalScore) == max(markers$externalScore)){solutionMethod=sample(c('internal','external'), 1)}
if(max(markers$internalScore) > max(markers$externalScore)){solutionMethod='internal'}
if(max(markers$internalScore) < max(markers$externalScore)){solutionMethod='external'}
}
if(solutionMethod=='internal' | solutionMethod=='both'){
markers$match=VMATCH(verb[,grep('^Int\\d',names(verb))], markers[,grep('^D\\d',names(markers))])
markers$collostruction=0
collostructions=speaker$collostructions$OV[speaker$collostructions$OV$V==verb$ID,]
markers[markers$ID%in%collostructions$O,]$collostruction=collostructions[na.omit(match(markers$ID, collostructions$O)),]$frequency
markers=markers[order(CANDIDATESCORE(markers, type='nounMarker'), decreasing=TRUE),]
markers$distractorMatch=VMATCH(verb[,grep('^Ext\\d',names(verb))], markers[,grep('^D\\d',names(markers))])
markerID=0
for (i in 1:nrow(markers)){
if(markers[i,]$match > (markers[i,]$distractorMatch + distinctiveness)){
markerID=markers[i,]$ID
markerCollostruction=markers[i,]$collostruction
break()
} }
if(markerID==0){
markerID=markers[MAX(markers$match, forceChoice=TRUE),]$ID
markerCollostruction=markers[MAX(markers$match, forceChoice=TRUE),]$collostruction
}
internal$markerID=markerID
internal$marker=speaker$nouns[speaker$nouns$ID==markerID,]$form
if(frequency=='absolute'){internal$markerFrequency=speaker$nouns[speaker$nouns$ID==markerID,]$frequency}
if(frequency=='relative'){internal$markerFrequency=speaker$nouns[speaker$nouns$ID==markerID,]$nounMarker}
internal$markerRecency=speaker$nouns[speaker$nouns$ID==markerID,]$recency
internal$markerCollostruction=markerCollostruction
}
if(solutionMethod=='external' | solutionMethod=='both'){
markers$match=VMATCH(verb[,grep('^Ext\\d',names(verb))], markers[,grep('^D\\d',names(markers))])
markers$collostruction=0
collostructions=speaker$collostructions$SV[speaker$collostructions$SV$V==verb$ID,]
markers[markers$ID%in%collostructions$S,]$collostruction=collostructions[na.omit(match(markers$ID, collostructions$S)),]$frequency
markers=markers[order(CANDIDATESCORE(markers, type='nounMarker'), decreasing=TRUE),]
markers$distractorMatch=VMATCH(verb[,grep('^Int\\d',names(verb))], markers[,grep('^D\\d',names(markers))])
markerID=0
for (i in 1:nrow(markers)){
if(markers[i,]$match > (markers[i,]$distractorMatch + distinctiveness)){
markerID=markers[i,]$ID
markerCollostruction=markers[i,]$collostruction
break()
} }
if(markerID==0){
markerID=markers[MAX(markers$match, forceChoice=TRUE),]$ID
markerCollostruction=markers[MAX(markers$match, forceChoice=TRUE),]$collostruction
}
external$markerID=markerID
external$marker=speaker$nouns[speaker$nouns$ID==markerID,]$form
if(frequency=='absolute'){external$markerFrequency=speaker$nouns[speaker$nouns$ID==markerID,]$frequency}
if(frequency=='relative'){external$markerFrequency=speaker$nouns[speaker$nouns$ID==markerID,]$nounMarker}
external$markerRecency=speaker$nouns[speaker$nouns$ID==markerID,]$recency
external$markerCollostruction=markerCollostruction
} }
proposition$external=external
proposition$internal=internal
}
proposition
}
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