ggplot(df, aes(time,value)) + geom_line() + facet_grid(series ~ .)
require(ggplot2)
require(reshape)
df <- data.frame(time = 1:10,
a = cumsum(rnorm(10)),
b = cumsum(rnorm(10)),
c = cumsum(rnorm(10)))
df <- melt(df , id.vars = 'time', variable.name = 'series')
# plot on same grid, each series colored differently --
# good if the series have same scale
ggplot(df, aes(time,value)) + geom_line(aes(colour = series))
# or plot on different plots
ggplot(df, aes(time,value)) + geom_line() + facet_grid(series ~ .)
install.packages(c("ggplot2", "reshape"))
require(ggplot2)
require(reshape)
df <- data.frame(time = 1:10,
a = cumsum(rnorm(10)),
b = cumsum(rnorm(10)),
c = cumsum(rnorm(10)))
df <- melt(df , id.vars = 'time', variable.name = 'series')
# plot on same grid, each series colored differently --
# good if the series have same scale
ggplot(df, aes(time,value)) + geom_line(aes(colour = series))
# or plot on different plots
ggplot(df, aes(time,value)) + geom_line() + facet_grid(series ~ .)
require(ggplot2)
require(reshape)
df <- data.frame(time = 1:10,
a = cumsum(rnorm(10)),
b = cumsum(rnorm(10)),
c = cumsum(rnorm(10)))
df <- melt(df , id.vars = 'time', variable.name = 'series')
# plot on same grid, each series colored differently --
# good if the series have same scale
ggplot(df, aes(time,value)) + geom_line(aes(colour = series))
# or plot on different plots
ggplot(df, aes(time,value)) + geom_line() + facet_grid(series ~ .)
NC.50U <- read.csv("~/Dropbox/Mestrado/Pesquisa/adaptivecaching/results/Experiments/Petclinic/NC-50U.csv")
View(NC.50U)
View(NC.50U)
View(NC.50U)
NC.50U
NC.50U[sequencial]
NC.50U['sequencial']
dat <- data.frame(X = cumsum(rnorm(100)), Y = cumsum(rnorm(100)),
Z = cumsum(rnorm(100)))
## convert to multivariate zoo object
datz <- zoo(dat)
## plot it
plot(datz)
dat <- data.frame(X = cumsum(rnorm(100)), Y = cumsum(rnorm(100)),
Z = cumsum(rnorm(100)))
## convert to multivariate zoo object
datz <- zoo(dat)
## plot it
plot(datz)
install.packages("zoo")
require(zoo)
dat <- data.frame(X = cumsum(rnorm(100)), Y = cumsum(rnorm(100)),
Z = cumsum(rnorm(100)))
## convert to multivariate zoo object
datz <- zoo(dat)
## plot it
plot(datz)
plot(NC.50U)
require(zoo)
dat <- data.frame(X = cumsum(rnorm(100)), Y = cumsum(rnorm(100)),
Z = cumsum(rnorm(100)))
## convert to multivariate zoo object
datz <- zoo(dat)
## plot it
plot(datz)
plot(NC.50U['sequencial'])
range(1..3000)
range(1:3000)
range(3000)
require(ggplot2)
require(reshape)
df <- data.frame(time = 1:10,
a = cumsum(rnorm(10)),
b = cumsum(rnorm(10)),
c = cumsum(rnorm(10)))
df <- melt(df , id.vars = 'time', variable.name = 'series')
# plot on same grid, each series colored differently --
# good if the series have same scale
ggplot(df, aes(time,value)) + geom_line(aes(colour = series))
# or plot on different plots
ggplot(df, aes(time,value)) + geom_line() + facet_grid(series ~ .)
require(zoo)
dat <- data.frame(X = cumsum(rnorm(100)), Y = cumsum(rnorm(100)),
Z = cumsum(rnorm(100)))
## convert to multivariate zoo object
datz <- zoo(dat)
## plot it
plot(NC.50U['sequencial'])
plot(NC.50U['sequencial'], 1:30000)
NC.50U['sequencial'].length
length(NC.50U['sequencial'])
NC.50U['sequencial']
## plot it
plot(NC.50U['sequencial'])
## plot it
plot(NC.50U['sequencial'], type="l")
type(NC.50U)
NC.50U$sequencial
## plot it
plot(NC.50U$sequencial, type="l")
length(NC.50U$sequencial)
1:length(NC.50U$sequencial)
## plot it
plot(NC.50U$sequencial,1:length(NC.50U$sequencial), type="l")
MC.50U <- read.csv("~/Dropbox/Mestrado/Pesquisa/adaptivecaching/results/Experiments/Petclinic/MC-50U.csv")
View(MC.50U)
## plot it
plot(NC.50U$sequencial, 1:length(NC.50U$sequencial), type="l")
plot(MC.50U$sequencial, 1:length(NC.50U$sequencial), type="l")
## plot it
plot(NC.50U$sequencial, 1:length(NC.50U$sequencial), type="l")
plot(MC.50U$sequencial, 1:length(MC.50U$sequencial), type="l")
## plot it
plot(NC.50U$sequencial, 1:length(NC.50U$sequencial), type="l")
par(new=T)
plot(MC.50U$sequencial, 1:length(MC.50U$sequencial), type="l", axes=F)
par(new=F)
## plot it
plot(NC.50U$sequencial, 1:20000, type="l")
par(new=T)
plot(MC.50U$sequencial, 1:20000, type="l", axes=F)
par(new=F)
plot(NC.50U$sequencial,length(NC.50U$sequencial),type="l",col="red")
lines(MC.50U$sequencial,length(MC.50U$sequencial),col="green")
View(MC.50U)
MC.50U = head(MC.50U,-200)
NC.50U = head(NC.50U,-1346)
plot(NC.50U$sequencial,length(NC.50U$sequencial),type="l",col="red")
lines(MC.50U$sequencial,length(MC.50U$sequencial),col="green")
MC.50U = head(MC.50U,-200)
NC.50U = head(NC.50U,-1346)
plot(NC.50U$sequencial,1:30000,type="l",col="red")
lines(MC.50U$sequencial,1:30000,col="green")
MC.50U = head(MC.50U,-200)
NC.50U = head(NC.50U,-1346)
plot(NC.50U$sequencial,1:30000,type="l",col="red")
#lines(MC.50U$sequencial,1:30000,col="green")
length(NC.50U$sequencial)
MC.50U = head(MC.50U,-9600)
NC.50U = head(NC.50U,-7308)
plot(NC.50U$sequencial,1:30000,type="l",col="red")
#lines(MC.50U$sequencial,1:30000,col="green")
#MC.50U = head(MC.50U,-9600)
#NC.50U = head(NC.50U,-7308)
plot(NC.50U$sequencial,1:20000,type="l",col="red")
#lines(MC.50U$sequencial,1:30000,col="green")
#MC.50U = head(MC.50U,-9600)
#NC.50U = head(NC.50U,-7308)
plot(NC.50U$sequencial,1:20000,type="l",col="red")
lines(MC.50U$sequencial,1:20000,col="green")
#MC.50U = head(MC.50U,-9600)
#NC.50U = head(NC.50U,-7308)
plot(NC.50U$sequencial,type="l",col="red")
lines(MC.50U$sequencial,col="green")
#MC.50U = head(MC.50U,-9600)
#NC.50U = head(NC.50U,-7308)
plot(1:20000, NC.50U$sequencial,type="l",col="red")
lines(1:20000, MC.50U$sequencial,col="green")
#MC.50U = head(MC.50U,-9600)
#NC.50U = head(NC.50U,-7308)
plot.ts(1:20000, NC.50U$sequencial,type="l",col="red")
lines.ts(1:20000, MC.50U$sequencial,col="green")
#MC.50U = head(MC.50U,-9600)
#NC.50U = head(NC.50U,-7308)
plot.ts(NC.50U$sequencial)
#plot.ts(1:20000, NC.50U$sequencial,type="l",col="red")
#lines.ts(1:20000, MC.50U$sequencial,col="green")
#MC.50U = head(MC.50U,-9600)
#NC.50U = head(NC.50U,-7308)
plot.ts(NC.50U$sequencial, 1:20000)
#plot.ts(1:20000, NC.50U$sequencial,type="l",col="red")
#lines.ts(1:20000, MC.50U$sequencial,col="green")
#MC.50U = head(MC.50U,-9600)
#NC.50U = head(NC.50U,-7308)
plot.ts(NC.50U$sequencial)
#plot.ts(1:20000, NC.50U$sequencial,type="l",col="red")
#lines.ts(1:20000, MC.50U$sequencial,col="green")
#MC.50U = head(MC.50U,-9600)
#NC.50U = head(NC.50U,-7308)
plot.ts(NC.50U)
#plot.ts(1:20000, NC.50U$sequencial,type="l",col="red")
#lines.ts(1:20000, MC.50U$sequencial,col="green")
#MC.50U = head(MC.50U,-9600)
#NC.50U = head(NC.50U,-7308)
plot.ts(ts(NC.50U$sequencial,frequency = 1))
#plot.ts(1:20000, NC.50U$sequencial,type="l",col="red")
#lines.ts(1:20000, MC.50U$sequencial,col="green")
#MC.50U = head(MC.50U,-9600)
#NC.50U = head(NC.50U,-7308)
plot.ts(ts(NC.50U$sequencial,n = 3))
#plot.ts(1:20000, NC.50U$sequencial,type="l",col="red")
#lines.ts(1:20000, MC.50U$sequencial,col="green")
#MC.50U = head(MC.50U,-9600)
#NC.50U = head(NC.50U,-7308)
plot.ts(NC.50U['sequencial'])
#plot.ts(1:20000, NC.50U$sequencial,type="l",col="red")
#lines.ts(1:20000, MC.50U$sequencial,col="green")
#MC.50U = head(MC.50U,-9600)
#NC.50U = head(NC.50U,-7308)
plot(NC.50U['sequencial'])
#plot.ts(1:20000, NC.50U$sequencial,type="l",col="red")
#lines.ts(1:20000, MC.50U$sequencial,col="green")