# limit=Inf to not censor any day (TODO: finite limit? 60?)
tdays = getSimilarDaysIndices(today, data, limit=Inf, same_season=TRUE,
days_in=tdays_cut, operational=opera)
-# if (length(tdays) <= 1)
-# return (NA)
# TODO: 10 == magic number
tdays = .getConstrainedNeighbs(today, data, tdays, min_neighbs=10)
if (length(tdays) == 1)
}
return ( data$getSerie(tdays[1])[predict_from:horizon] )
}
- max_neighbs = 10 #TODO: 12 = arbitrary number
+ max_neighbs = 10 #TODO: 10 or 12 or... ?
if (length(tdays) > max_neighbs)
{
distances2 <- .computeDistsEndo(data, today, tdays, predict_from)
.getConstrainedNeighbs = function(today, data, tdays, min_neighbs=10)
{
levelToday = data$getLevelHat(today)
-# levelYersteday = data$getLevel(today-1)
- distances = sapply(tdays, function(i) {
-# sqrt((data$getLevel(i-1)-levelYersteday)^2 + (data$getLevel(i)-levelToday)^2)
- abs(data$getLevel(i)-levelToday)
- })
+ distances = sapply( tdays, function(i) abs(data$getLevel(i) - levelToday) )
#TODO: 1, +1, +3 : magic numbers
dist_thresh = 1
min_neighbs = min(min_neighbs,length(tdays))
break
dist_thresh = dist_thresh + ifelse(dist_thresh>1,3,1)
}
- tdays = tdays[same_pollution]
-# max_neighbs = 12
-# if (nb_neighbs > max_neighbs)
-# {
-# # Keep only max_neighbs closest neighbors
-# tdays = tdays[ order(distances[same_pollution])[1:max_neighbs] ]
-# }
- tdays
+ tdays[same_pollution]
}
# compute similarities
sapply(tdays, function(i) {
delta = lastSerie - c(data$getSerie(i-1),
data$getSerie(i)[if (predict_from>=2) 1:(predict_from-1) else c()])
-# sqrt(mean(delta^2))
- sqrt(sum(delta^2))
+ sqrt(mean(delta^2))
})
}