options(jupyter.plot_mimetypes = c("text/plain", "image/png" )) 
options(repr.plot.width=8, repr.plot.height=4)

suppressPackageStartupMessages(library(dplyr))
suppressPackageStartupMessages(library(zoo))
suppressPackageStartupMessages(library(lubridate))
suppressPackageStartupMessages(library(RCurl))
suppressPackageStartupMessages(library(xts))

myfile <- getURL('https://rdm.inesctec.pt/dataset/7ff52a34-c10e-402c-9db8-ecfac9d5e514/resource/c4e3851e-ae90-485e-bbeb-a5bffdf323d7/download/gammainesc201803.txt',ssl.verifyhost=FALSE, ssl.verifypeer=FALSE)
dat=read.table(textConnection(myfile),header=FALSE,sep="",stringsAsFactors=FALSE)

# data date/time as POSIXct
dat.times=as.POSIXct(paste(dat$V1,dat$V2),format="%Y-%m-%d %H:%M:%S",tz="UTC")

start.time=dat.times[1]
end.time=dat.times[length(dat.times)]

print(paste("data from", start.time, "to", end.time))

gamma=dat$V3

# check for continuity of record [0 --> continuous record]; result=number of gaps
# 5-minute measurements --> 300 sec
ngaps=length(which(c(1,round(diff(unclass(dat.times)/300)))!=1))
gaps=which(c(1,round(diff(unclass(dat.times)/300)))!=1)

#fill-in gaps by adding missing times as NA values 
all.times <- seq.POSIXt(from=start.time, to=end.time, by=300)
df <- data.frame(dat.times=all.times,stringsAsFactors=FALSE)
data2018.03 <- full_join(df,data.frame(dat.times=dat.times, gamma=gamma)) 

ts.zoo=zoo(data2018.03$gamma,data2018.03$dat.times)

times <- time(zoo(ts.zoo))
ticks <- seq(times[1], times[length(times)], by = "days")

fmt <- "%d-%m" # format for axis labels
labs <- format(ticks, fmt)

plot(ts.zoo,ylab = "counts/minute",xlab="day",col="cornflowerblue", main="Gamma - March 2018",xaxt="n",type="b",pch=20)
axis(1, at = ticks,labels=labs, tcl = -0.3)


myfile <- getURL('https://rdm.inesctec.pt/dataset/7ff52a34-c10e-402c-9db8-ecfac9d5e514/resource/8e54c830-937b-45c3-8ee3-6d84fbdbd0c8/download/gammainesc201804.txt',ssl.verifyhost=FALSE, ssl.verifypeer=FALSE)
dat=read.table(textConnection(myfile),header=FALSE,sep="",stringsAsFactors=FALSE)

# data date/time as POSIXct
dat.times=as.POSIXct(paste(dat$V1,dat$V2),format="%Y-%m-%d %H:%M:%S",tz="UTC")

start.time=dat.times[1]
end.time=dat.times[length(dat.times)]

print(paste("data from", start.time, "to", end.time))

gamma=dat$V3

# check for continuity of record [0 --> continuous record]; result=number of gaps
# 5-minute measurements --> 300 sec
ngaps=length(which(c(1,round(diff(unclass(dat.times)/300)))!=1))
gaps=which(c(1,round(diff(unclass(dat.times)/300)))!=1)

#fill-in gaps by adding missing times as NA values 
all.times <- seq.POSIXt(from=start.time, to=end.time, by=300)
df <- data.frame(dat.times=all.times,stringsAsFactors=FALSE)
data2018.04 <- full_join(df,data.frame(dat.times=dat.times, gamma=gamma)) 

ts.zoo=zoo(data2018.04$gamma,data2018.04$dat.times)

times <- time(zoo(ts.zoo))
ticks <- seq(times[1], times[length(times)], by = "days")

fmt <- "%d-%m" # format for axis labels
labs <- format(ticks, fmt)

plot(ts.zoo,ylab = "counts/minute",xlab="day",col="cornflowerblue", main="Gamma - April 2018",xaxt="n",type="b",pch=20)
axis(1, at = ticks,labels=labs, tcl = -0.3)

myfile <- getURL('https://rdm.inesctec.pt/dataset/7ff52a34-c10e-402c-9db8-ecfac9d5e514/resource/2354f2bd-bfc8-486b-9e13-33d16b0ccd14/download/gammainesc201805.txt',ssl.verifyhost=FALSE, ssl.verifypeer=FALSE)
dat=read.table(textConnection(myfile),header=FALSE,sep="",stringsAsFactors=FALSE)

# data date/time as POSIXct
dat.times=as.POSIXct(paste(dat$V1,dat$V2),format="%Y-%m-%d %H:%M:%S",tz="UTC")

start.time=dat.times[1]
end.time=dat.times[length(dat.times)]

print(paste("data from", start.time, "to", end.time))

gamma=dat$V3

# check for continuity of record [0 --> continuous record]; result=number of gaps
# 5-minute measurements --> 300 sec
ngaps=length(which(c(1,round(diff(unclass(dat.times)/300)))!=1))
gaps=which(c(1,round(diff(unclass(dat.times)/300)))!=1)

#fill-in gaps by adding missing times as NA values 
all.times <- seq.POSIXt(from=start.time, to=end.time, by=300)
df <- data.frame(dat.times=all.times,stringsAsFactors=FALSE)
data2018.05 <- full_join(df,data.frame(dat.times=dat.times, gamma=gamma)) 

ts.zoo=zoo(data2018.05$gamma,data2018.05$dat.times)

times <- time(zoo(ts.zoo))
ticks <- seq(times[1], times[length(times)], by = "days")

fmt <- "%d-%m" # format for axis labels
labs <- format(ticks, fmt)

plot(ts.zoo,ylab = "counts/minute",xlab="day",col="cornflowerblue", main="Gamma - May 2018",xaxt="n",type="b",pch=20)
axis(1, at = ticks,labels=labs, tcl = -0.3)

myfile <- getURL('https://rdm.inesctec.pt/dataset/7ff52a34-c10e-402c-9db8-ecfac9d5e514/resource/e100b818-5f5f-4805-a16a-bc3d77c134c0/download/gammainesc201806.txt',ssl.verifyhost=FALSE, ssl.verifypeer=FALSE)
dat=read.table(textConnection(myfile),header=FALSE,sep="",stringsAsFactors=FALSE)

# data date/time as POSIXct
dat.times=as.POSIXct(paste(dat$V1,dat$V2),format="%Y-%m-%d %H:%M:%S",tz="UTC")

start.time=dat.times[1]
end.time=dat.times[length(dat.times)]

print(paste("data from", start.time, "to", end.time))

gamma=dat$V3

# check for continuity of record [0 --> continuous record]; result=number of gaps
# 5-minute measurements --> 300 sec
ngaps=length(which(c(1,round(diff(unclass(dat.times)/300)))!=1))
gaps=which(c(1,round(diff(unclass(dat.times)/300)))!=1)

#fill-in gaps by adding missing times as NA values 
all.times <- seq.POSIXt(from=start.time, to=end.time, by=300)
df <- data.frame(dat.times=all.times,stringsAsFactors=FALSE)
data2018.06 <- full_join(df,data.frame(dat.times=dat.times, gamma=gamma)) 

ts.zoo=zoo(data2018.06$gamma,data2018.06$dat.times)

times <- time(zoo(ts.zoo))
ticks <- seq(times[1], times[length(times)], by = "days")

fmt <- "%d-%m" # format for axis labels
labs <- format(ticks, fmt)

plot(ts.zoo,ylab = "counts/minute",xlab="day",col="cornflowerblue", main="Gamma - June 2018",xaxt="n",type="b",pch=20)
axis(1, at = ticks,labels=labs, tcl = -0.3)

myfile <- getURL('https://rdm.inesctec.pt/dataset/7ff52a34-c10e-402c-9db8-ecfac9d5e514/resource/5e597b69-aca4-4642-b4e2-0a0982c44288/download/gammainesc201807.txt',ssl.verifyhost=FALSE, ssl.verifypeer=FALSE)
dat=read.table(textConnection(myfile),header=FALSE,sep="",stringsAsFactors=FALSE)

# data date/time as POSIXct
dat.times=as.POSIXct(paste(dat$V1,dat$V2),format="%Y-%m-%d %H:%M:%S",tz="UTC")

start.time=dat.times[1]
end.time=dat.times[length(dat.times)]

print(paste("data from", start.time, "to", end.time))

gamma=dat$V3

# check for continuity of record [0 --> continuous record]; result=number of gaps
# 5-minute measurements --> 300 sec
ngaps=length(which(c(1,round(diff(unclass(dat.times)/300)))!=1))
gaps=which(c(1,round(diff(unclass(dat.times)/300)))!=1)

#fill-in gaps by adding missing times as NA values 
all.times <- seq.POSIXt(from=start.time, to=end.time, by=300)
df <- data.frame(dat.times=all.times,stringsAsFactors=FALSE)
data2018.07 <- full_join(df,data.frame(dat.times=dat.times, gamma=gamma)) 

ts.zoo=zoo(data2018.07$gamma,data2018.07$dat.times)

times <- time(zoo(ts.zoo))
ticks <- seq(times[1], times[length(times)], by = "days")

fmt <- "%d-%m" # format for axis labels
labs <- format(ticks, fmt)

plot(ts.zoo,ylab = "counts/minute",xlab="day",col="cornflowerblue", main="Gamma - July 2018",xaxt="n",type="b",pch=20)
axis(1, at = ticks,labels=labs, tcl = -0.3)

myfile <- getURL('https://rdm.inesctec.pt/dataset/7ff52a34-c10e-402c-9db8-ecfac9d5e514/resource/e840a838-3f9e-4aac-9143-b10da72e5a2c/download/gammainesc201808.txt',ssl.verifyhost=FALSE, ssl.verifypeer=FALSE)
dat=read.table(textConnection(myfile),header=FALSE,sep="",stringsAsFactors=FALSE)

# data date/time as POSIXct
dat.times=as.POSIXct(paste(dat$V1,dat$V2),format="%Y-%m-%d %H:%M:%S",tz="UTC")

start.time=dat.times[1]
end.time=dat.times[length(dat.times)]

print(paste("data from", start.time, "to", end.time))

gamma=dat$V3

# check for continuity of record [0 --> continuous record]; result=number of gaps
# 5-minute measurements --> 300 sec
ngaps=length(which(c(1,round(diff(unclass(dat.times)/300)))!=1))
gaps=which(c(1,round(diff(unclass(dat.times)/300)))!=1)

#fill-in gaps by adding missing times as NA values 
all.times <- seq.POSIXt(from=start.time, to=end.time, by=300)
df <- data.frame(dat.times=all.times,stringsAsFactors=FALSE)
data2018.08 <- full_join(df,data.frame(dat.times=dat.times, gamma=gamma)) 

ts.zoo=zoo(data2018.08$gamma,data2018.08$dat.times)

times <- time(zoo(ts.zoo))
ticks <- seq(times[1], times[length(times)], by = "days")

fmt <- "%d-%m" # format for axis labels
labs <- format(ticks, fmt)

plot(ts.zoo,ylab = "counts/minute",xlab="day",col="cornflowerblue", main="Gamma - August 2018",xaxt="n",type="b",pch=20)
axis(1, at = ticks,labels=labs, tcl = -0.3)

myfile <- getURL('https://rdm.inesctec.pt/dataset/7ff52a34-c10e-402c-9db8-ecfac9d5e514/resource/8d8b7bea-6964-46f3-b34b-6e83e760f74b/download/gammainesc201809.txt',ssl.verifyhost=FALSE, ssl.verifypeer=FALSE)
dat=read.table(textConnection(myfile),header=FALSE,sep="",stringsAsFactors=FALSE)

# data date/time as POSIXct
dat.times=as.POSIXct(paste(dat$V1,dat$V2),format="%Y-%m-%d %H:%M:%S",tz="UTC")

start.time=dat.times[1]
end.time=dat.times[length(dat.times)]

print(paste("data from", start.time, "to", end.time))

gamma=dat$V3

# check for continuity of record [0 --> continuous record]; result=number of gaps
# 5-minute measurements --> 300 sec
ngaps=length(which(c(1,round(diff(unclass(dat.times)/300)))!=1))
gaps=which(c(1,round(diff(unclass(dat.times)/300)))!=1)

#fill-in gaps by adding missing times as NA values 
all.times <- seq.POSIXt(from=start.time, to=end.time, by=300)
df <- data.frame(dat.times=all.times,stringsAsFactors=FALSE)
data2018.09 <- full_join(df,data.frame(dat.times=dat.times, gamma=gamma)) 

ts.zoo=zoo(data2018.09$gamma,data2018.09$dat.times)

times <- time(zoo(ts.zoo))
ticks <- seq(times[1], times[length(times)], by = "days")

fmt <- "%d-%m" # format for axis labels
labs <- format(ticks, fmt)

plot(ts.zoo,ylab = "counts/minute",xlab="day",col="cornflowerblue", main="Gamma - September 2018",xaxt="n",type="b",pch=20)
axis(1, at = ticks,labels=labs, tcl = -0.3)

myfile <- getURL('https://rdm.inesctec.pt/dataset/7ff52a34-c10e-402c-9db8-ecfac9d5e514/resource/ce71bb1b-3c27-4579-b74d-f8009a489259/download/gammainesc201810.txt ',ssl.verifyhost=FALSE, ssl.verifypeer=FALSE)
dat=read.table(textConnection(myfile),header=FALSE,sep="",stringsAsFactors=FALSE)

# data date/time as POSIXct
dat.times=as.POSIXct(paste(dat$V1,dat$V2),format="%Y-%m-%d %H:%M:%S",tz="UTC")

start.time=dat.times[1]
end.time=dat.times[length(dat.times)]

print(paste("data from", start.time, "to", end.time))

gamma=dat$V3

# check for continuity of record [0 --> continuous record]; result=number of gaps
# 5-minute measurements --> 300 sec
ngaps=length(which(c(1,round(diff(unclass(dat.times)/300)))!=1))
gaps=which(c(1,round(diff(unclass(dat.times)/300)))!=1)

#fill-in gaps by adding missing times as NA values 
all.times <- seq.POSIXt(from=start.time, to=end.time, by=300)
df <- data.frame(dat.times=all.times,stringsAsFactors=FALSE)
data2018.10 <- full_join(df,data.frame(dat.times=dat.times, gamma=gamma)) 

ts.zoo=zoo(data2018.10$gamma,data2018.10$dat.times)

times <- time(zoo(ts.zoo))
ticks <- seq(times[1], times[length(times)], by = "days")

fmt <- "%d-%m" # format for axis labels
labs <- format(ticks, fmt)

plot(ts.zoo,ylab = "counts/minute",xlab="day",col="cornflowerblue", main="Gamma - October 2018",xaxt="n",type="b",pch=20)
axis(1, at = ticks,labels=labs, tcl = -0.3)

myfile <- getURL('https://rdm.inesctec.pt/dataset/7ff52a34-c10e-402c-9db8-ecfac9d5e514/resource/11e916ff-8795-407a-a04f-c6bd488a8ebd/download/gammainesc201811.txt',ssl.verifyhost=FALSE, ssl.verifypeer=FALSE)
dat=read.table(textConnection(myfile),header=FALSE,sep="",stringsAsFactors=FALSE)

# data date/time as POSIXct
dat.times=as.POSIXct(paste(dat$V1,dat$V2),format="%Y-%m-%d %H:%M:%S",tz="UTC")

start.time=dat.times[1]
end.time=dat.times[length(dat.times)]

print(paste("data from", start.time, "to", end.time))

gamma=dat$V3

# check for continuity of record [0 --> continuous record]; result=number of gaps
# 5-minute measurements --> 300 sec
ngaps=length(which(c(1,round(diff(unclass(dat.times)/300)))!=1))
gaps=which(c(1,round(diff(unclass(dat.times)/300)))!=1)

#fill-in gaps by adding missing times as NA values 
all.times <- seq.POSIXt(from=start.time, to=end.time, by=300)
df <- data.frame(dat.times=all.times,stringsAsFactors=FALSE)
data2018.11 <- full_join(df,data.frame(dat.times=dat.times, gamma=gamma)) 

ts.zoo=zoo(data2018.11$gamma,data2018.11$dat.times)

times <- time(zoo(ts.zoo))
ticks <- seq(times[1], times[length(times)], by = "days")

fmt <- "%d-%m" # format for axis labels
labs <- format(ticks, fmt)

plot(ts.zoo,ylab = "counts/minute",xlab="day",col="cornflowerblue", main="Gamma - November 2018",xaxt="n",type="b",pch=20)
axis(1, at = ticks,labels=labs, tcl = -0.3)

myfile <- getURL('https://rdm.inesctec.pt/dataset/7ff52a34-c10e-402c-9db8-ecfac9d5e514/resource/77369a4f-dd39-4126-b68e-31bcbd412a42/download/gammainesc201812.txt',ssl.verifyhost=FALSE, ssl.verifypeer=FALSE)
dat=read.table(textConnection(myfile),header=FALSE,sep="",stringsAsFactors=FALSE)

# data date/time as POSIXct
dat.times=as.POSIXct(paste(dat$V1,dat$V2),format="%Y-%m-%d %H:%M:%S",tz="UTC")

start.time=dat.times[1]
end.time=dat.times[length(dat.times)]

print(paste("data from", start.time, "to", end.time))

gamma=dat$V3

# check for continuity of record [0 --> continuous record]; result=number of gaps
# 5-minute measurements --> 300 sec
ngaps=length(which(c(1,round(diff(unclass(dat.times)/300)))!=1))
gaps=which(c(1,round(diff(unclass(dat.times)/300)))!=1)

#fill-in gaps by adding missing times as NA values 
all.times <- seq.POSIXt(from=start.time, to=end.time, by=300)
df <- data.frame(dat.times=all.times,stringsAsFactors=FALSE)
data2018.12 <- full_join(df,data.frame(dat.times=dat.times, gamma=gamma)) 

ts.zoo=zoo(data2018.12$gamma,data2018.12$dat.times)

times <- time(zoo(ts.zoo))
ticks <- seq(times[1], times[length(times)], by = "days")

fmt <- "%d-%m" # format for axis labels
labs <- format(ticks, fmt)

plot(ts.zoo,ylab = "counts/minute",xlab="day",col="cornflowerblue", main="Gamma - December 2018",xaxt="n",type="b",pch=20)
axis(1, at = ticks,labels=labs, tcl = -0.3)