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calma_key_histogram_FAST_cabaret.R
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calma_key_histogram_FAST_cabaret.R
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library("RCurl")
library("SPARQL")
library("rrdf")
library("ggplot2")
library("plyr")
library("dplyr")
library("magrittr")
library("stringr")
# if the following is true, override the etreeTrackQuery and use the sample instead
injectSample <- FALSE
setwd(tempdir())
#following line: see http://www.bramschoenmakers.nl/en/node/726
#options( java.parameters = "-Xmx3g" )
endpoint = "http://etree.linkedmusic.org/sparql"
etreeTrackQuery <- "
PREFIX etree:<http://etree.linkedmusic.org/vocab/>
PREFIX mo:<http://purl.org/ontology/mo/>
PREFIX event:<http://purl.org/NET/c4dm/event.owl#>
PREFIX skos:<http://www.w3.org/2004/02/skos/core#>
PREFIX timeline:<http://purl.org/NET/c4dm/timeline.owl#>
PREFIX rdf:<http://www.w3.org/1999/02/22-rdf-syntax-ns#>
PREFIX calma:<http://calma.linkedmusic.org/vocab/>
SELECT ?track ?calma
{
BIND(<http://etree.linkedmusic.org/artist/422feb50-4aac-012f-19e9-00254bd44c28> as ?artist) .
?artist mo:performed ?performance .
?performance event:hasSubEvent ?track .
?track calma:data ?calma ;
skos:prefLabel \"Parachute\" .
}
ORDER BY ?calma
LIMIT 100
"
whatFeaturesQuery <- "
prefix prov: <http://www.w3.org/ns/prov#>
select distinct ?feature where {
?file prov:wasAssociatedWith ?feature
}
ORDER BY ?feature"
calmaFeatureQuery <- "
PREFIX af: <http://purl.org/ontology/af/>
PREFIX mo: <http://purl.org/ontology/mo/>
PREFIX event: <http://purl.org/NET/c4dm/event.owl#>
PREFIX tl: <http://purl.org/NET/c4dm/timeline.owl#>
PREFIX rdfs: <http://www.w3.org/2000/01/rdf-schema#>
select distinct ?event ?feature ?key ?onsetTime where {
# ?event a af:Tempo;
?event a af:KeyChange ;
event:time ?time ;
af:feature ?feature ;
rdfs:label ?key .
?time tl:at ?onsetTime .
}
ORDER BY ?event"
graphify <- function(files, remote=TRUE) {
if(remote) {
files <- gsub('<|>', '', files) # get rid of uri decoration if any
data <- gsub('\\"', '"', getURL(files)) # un-escape quote marks
# files = gsub("http://calma.linkedmusic.org/data/", "", files)
files = gsub("http://calma.linkedmusic.org/data/../", "", files)
files = gsub("/", "--", files)
}
else { # got sent a local directory
files <- paste0(files, "/", list.files(files))
}
g = new.rdf()
for (f in 1:length(files)) {
if(remote){ # need to write to our local tmp folder
track <- files[f]
track <- regmatches(track, gregexpr(pattern = "track_[^/]*", track))[[1]]
cat(x=data[f], file=files[f], append=FALSE)
}
thisg = load.rdf(filename = files[f], format="TURTLE")
g = combine.rdf(g, load.rdf(filename = files[f], format="TURTLE"))
summarize.rdf(g)
}
return(g)
}
untarBlobs <- function(blobURIs) {
tmp = tempfile(tmpdir = tempdir())
blobFiles <- basename(blobURIs)
for (f in 1:length(blobFiles)) {
download.file(blobURIs[f], blobFiles[f])
untar(blobFiles[f], compressed = 'gzip', exdir = tmp)
file = gsub(".tar.gz", "", blobFiles[f])
file = gsub(".tar.bz2", "", file)
file <- paste0(tmp, "/", file)
}
files <- paste0(tmp, "/", list.files(tmp))
print("---------------------")
for (f in 1:length(files)) {
contextualized <- gsub("<#>", paste0("<", files[f], "#>"), readLines(files[f]))
cat(x = contextualized, file=files[f], append = FALSE)
}
return(tmp)
}
queryFeatureFiles <- function(g, feature) {
calmaFileQuery <- paste0("
prefix prov: <http://www.w3.org/ns/prov#>
select distinct ?file where {
?file prov:wasAssociatedWith <", feature, ">
}
ORDER BY ?file")
files <- sparql.rdf(g, calmaFileQuery)
return (files)
}
calculateEventDurations <- function(featureData) {
calcPerTrack <- function(trackData) {
for(i in 1:nrow(trackData)) {
trackData[i, "duration"] <- trackData[i+1, "onsetTime"] - trackData[i, "onsetTime"]
# FIXME for last event, calculate based on track duration
}
return(trackData)
}
result <- data.frame()
tracks <- unique(featureData$track)
for (t in 1:length(tracks)){
result <- rbind(result, calcPerTrack(featureData[featureData$track == tracks[t], ]))
}
return (result)
}
if(injectSample) {
sample_files <- getSampleTracks()
sample_files$calmatrack <- str_replace_all(sample_files$calma, '(<http://calma.linkedmusic.org/data/|>)', '')
sample_files$newloc = substr(sample_files$calmatrack, start = 7, stop=8)
files <- paste0("http://eeboo.oerc.ox.ac.uk/sample_calma_data/", sample_files$newloc, "/", sample_files$tracks, sample_files$calmatrack, "/analyses.ttl")
sample_files$files <- files
sample_files$artist <- factor(sample_files$artist)
sample_files$trackname <- factor(sample_files$trackname)
by_artist_song_features <- sample_files %>%
group_by(artist) %>%
select(artist)
grand_output <- dlply(sample_files, "artist", getFeatureData)
} else {
result <- SPARQL(endpoint, etreeTrackQuery)$results
# chop off the <'s and >'s
calma <- substr(result$calma, 2, nchar(result$calma))
calma <- substr(calma, 1, nchar(calma)-1)
# add trailing /
calma <- paste0(calma, "/")
files <- paste0(calma, "analyses.ttl")
etreeCalma <- cbind(result, files)
}
g <- graphify(files, remote=TRUE)
# What features are available for these files?
features <- sparql.rdf(g, whatFeaturesQuery)
#featurefiles <- queryFeatureFiles(g, features[18])
featurefiles <- queryFeatureFiles(g, features[9])
g <- graphify(featurefiles)
etreeCalma <- cbind(etreeCalma, featurefiles)
names(etreeCalma) <- c("etree", "calma", "analysis.ttl", "feature")
etreeCalma$etree <- factor(etreeCalma$etree)
etreeCalma$calma<- factor(etreeCalma$calma)
query = "select distinct ?blob where {
?s <http://calma.linkedmusic.org/vocab/feature_blob> ?blob
}
ORDER BY ?blob"
blobFileURIs <- sparql.rdf(g, query)
blobFileDir <- untarBlobs(blobFileURIs)
featureGraph <- graphify(blobFileDir, remote=FALSE)
summarize.rdf(featureGraph)
featureData <- as.data.frame(sparql.rdf(featureGraph, calmaFeatureQuery))
#featureData$track <- factor((gsub(".*/([^/#]+).*$", "\\1", as.character(featureData$event),fixed=FALSE, perl=TRUE)))
featureData$track <- factor((gsub(".*/([^/#]+)\\.wav.*$", "\\1", as.character(featureData$event),fixed=FALSE, perl=TRUE)))
featureData$eventNum <- as.numeric(gsub(".*event_(\\d+)", "\\1", as.character(featureData$event),fixed=FALSE, perl=TRUE))
featureData$feature <- as.numeric(as.character(featureData$feature))
featureData$onsetTime <- as.numeric(gsub("[PTS]", "", as.character(featureData$onsetTime), fixed=FALSE, perl=TRUE))
featureData <- unique(featureData[order(featureData$track, featureData$eventNum),])
featureData <- calculateEventDurations(featureData)
featureData <- select(featureData, key, track, duration) %>%
group_by(track, key) %>%
filter(key != "N") %>% # remove NA's
summarise(key_duration = sum(duration, na.rm=TRUE))
featureData <- inner_join(featureData, select(featureData, track, key_duration) %>%
group_by(track) %>%
summarise(track_duration = sum(key_duration, na.rm=TRUE)))
corpusScore <- group_by(featureData, key) %>%
summarise(key_corpus_duration = sum(key_duration)) %>%
ungroup() %>%
mutate(total_corpus_duration = sum(key_corpus_duration)) %>%
mutate(key_corpus_proportion = key_corpus_duration / total_corpus_duration) %>%
arrange(desc(key_corpus_proportion)) %>%
mutate(key_corpus_rank = seq_along(key_corpus_proportion))
# normalise corpus proportions
maxProp <- max(corpusScore$key_corpus_proportion)
corpusScore$normalised_key_corpus_prop <- corpusScore$key_corpus_proportion / maxProp
#keyScore <- group_by(featureData, track) %>%
# arrange(desc(key_duration)) %>%
# mutate(key_rank = seq_along(key_duration)) %>%
# mutate(key_duration_weighted = (key_duration / (track_duration*(key_rank)))) %>%
# summarise(keyScore = sum(key_duration_weighted))
keyScore <- inner_join(featureData, corpusScore, by="key") %>%
mutate(track_key_score = (key_duration / track_duration) * key_corpus_proportion) %>%
mutate(normalised_track_key_score = (key_duration / track_duration) * normalised_key_corpus_prop) %>%
summarise(key_score = sum(track_key_score), normalised_key_score = sum(normalised_track_key_score))
# order tracks by key score
keyScore <- keyScore[order(desc(keyScore$key_score)),]
featureData$track <- factor(featureData$track, levels = keyScore$track)
# add font size relative to duration in key per track
featureData <- featureData %>%
group_by(track, key) %>%
mutate(fontSize = min(6, 10*(key_duration/track_duration)))
ggplot(featureData, aes(key, key_duration)) + geom_bar(stat="identity") + facet_wrap(~track) + theme_bw() +
#geom_text(data=keymappings, aes(feature, 0, label=key, angle=90), color="#aaaaaa", hjust=0, size=2) +
geom_text(data=featureData, aes(key, key_duration + 5, label=key, size=5+fontSize), color="#aaaaaa") +
geom_text(data=keyScore, aes(5, 200, label=round(normalised_key_score, digits = 2)), color="red") +
labs(x="Feature (Key). Normalised key typicality score in red.", y = "Total duration (seconds)") + scale_y_continuous(breaks=seq(0,300,50)) +
theme(text = element_text(size = 10), axis.text.x = element_blank(), axis.ticks.x = element_blank()) +
guides(size = FALSE)
#----scratch-----#
#every_third_track <- keyScore[seq(1,110,3),c("track")]$track
#every_third_track <- every_third_track[-37]
#forty_tracks <- keyScore[floor(seq(1,110, length.out = 40)),]$track
#ggplot(featureData[featureData$track %in% forty_tracks,], aes(key, key_duration)) + geom_bar(stat="identity") + facet_wrap(~track, ncol=5) + theme_bw() +
#geom_text(data=keymappings, aes(feature, 0, label=key, angle=90), color="#aaaaaa", hjust=0, size=2) +
# geom_text(aes(key, key_duration + 25, label = key, size = (key_duration/track_duration)*.5), color="#aaaaaa") +
# geom_text(data=keyScore[keyScore$track %in% forty_tracks,], aes(23.5, 228, label=round(normalised_key_score, digits = 2)), color="red") +
# labs(x="Key detected", y = "Duration (seconds)") + scale_y_continuous(breaks=seq(0,300,50), limits = c(0,250)) +
# theme(text = element_text(size = 13), axis.text.x = element_blank(), axis.ticks.x = element_blank(), strip.text=element_blank(), strip.background=element_blank()) +
# guides(size = FALSE)