write.csv2(xxevents, file="data/test/events-f5.csv", row.names=FALSE)
xxdistinct <- distinct_(xxevents, "number")
toString(xxdistinct$number[1])
xxnewt <- NULL
for(i in 1:nrow(xxdistinct))
{
n <- xxdistinct$number[i]
set <- paste(xxevents$set_state_id[xxevents$number==n],collapse = ",")
c <- cbind(toString(xxdistinct$number[i]),xset)
mset <- paste(xxevents$mset_state_id[xxevents$number==n],collapse = ",")
c <- cbind(c,mset)
seq <- paste(xxevents$seq_state_id[xxevents$number==n],collapse = ",")
c <- cbind(c,seq)
xxnewt <- rbind(xxnewt,c)
}
xxnewtdt <- as.data.frame(xxnewt)
colnames(xxnewtdt) <- c("number","set","mset","seq")
xxnewtdt2 <- setDT(xxnewtdt)
counter <- xxnewtdt2[, .(`Number of rows` = .N), by = set]
write.csv2(counter, file="data/test/events-f5-counter-set.csv", row.names=FALSE)
counter <- xxnewtdt2[, .(`Number of rows` = .N), by = mset]
write.csv2(counter, file="data/test/events-f5-counter-mset.csv", row.names=FALSE)
counter <- xxnewtdt2[, .(`Number of rows` = .N), by = seq]
write.csv2(counter, file="data/test/events-f5-counter-seq.csv", row.names=FALSE)
# teste de média e desvio padrão
#av1 <- sample(10)
#av2 <- sample(10) # sample apenas reordena
av1 <- sample(5:10, 100, replace=TRUE)
av2 <- sample(1:5, 100, replace=TRUE)
am1 <- mean(av1)
am2 <- mean(av2)
avar1 <- var(av1)
avar2 <- var(av2)
asd1 <- sd(av1)
asd2 <- sd(av2)
am3 <- (mean(c(am1,am2)))
asd3 <- mean(c(asd1,asd2))
av4 <- c(av1,av2)
am4 <- mean(av4)
asd4 <- sd(av4)
asdv <- (avar1 - avar2)^2
rm(am1,am2,am3,am4,asd1,asd2,asd3,asd4,asdv,av1,av2,av4,avar1,avar2)
# ddply(av1, .fun = mean())
#
# datac <- ddply(data, groupvars, .drop=.drop,
# .fun = function(xx, col) {
# c(N = length2(xx[[col]], na.rm=na.rm),
# mean = ceiling(mean (xx[[col]], na.rm=na.rm)),
# sd = ceiling(sd (xx[[col]], na.rm=na.rm)),
# median = ceiling(median (xx[[col]], na.rm=na.rm)),
# min = ceiling(min (xx[[col]], na.rm=na.rm)),
# max = ceiling(max (xx[[col]], na.rm=na.rm))
# )
# },
# measurevar
x <- sample(1:10, 100, replace=TRUE)
y <- sample(1:10, 100, replace=TRUE)
xerr <- abs(x-y)
xmape <- MAPE(y,x)
xm <- NULL
for(i in 1:length(x)) {
xm[i] <- MAPE(y[i],x[i])
}
mean(xm)
mean(y)-mean(x)/mean(x)
Accuracy(y,x) # Accuracy <- mean(y_true == y_pred)
#o erro é relativo: não espero acertar exatamente nos segundos
xt1 <- as.POSIXct(strptime("01/12/2018 22:10:15", "%d/%m/%Y %H:%M:%S"))
xt2 <- as.POSIXct(strptime("01/12/2018 22:11:15", "%d/%m/%Y %H:%M:%S"))
xi1 <- as.integer(xt1)
xi2 <- as.integer(xt2)
xi2 - xi1
# código para converter factors em numeric
yourdat[] <- lapply(yourdat, function(x) if(is.factor(x)) as.numeric(levels(x))[x] else x)
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