Gamma radiation from INESC TEC station (Porto) - 2019

In [1]:
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))
In [11]:
myfile <- getURL('https://rdm.inesctec.pt/dataset/7ff52a34-c10e-402c-9db8-ecfac9d5e514/resource/e3a825d8-da8f-4af7-abe6-3b987d9c1773/download/gammainesc201901.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)
data2019.01 <- full_join(df,data.frame(dat.times=dat.times, gamma=gamma))
[1] "data from 2019-01-01 to 2019-01-31 23:55:00"
Joining, by = "dat.times"
In [12]:
ts.zoo=zoo(data2019.01$gamma,data2019.01$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 - January 2019",xaxt="n",type="b",pch=20)
axis(1, at = ticks,labels=labs, tcl = -0.3)
In [13]:
myfile <- getURL('https://rdm.inesctec.pt/dataset/7ff52a34-c10e-402c-9db8-ecfac9d5e514/resource/2f22039a-8ab7-47e1-9caa-f461c21269ce/download/gammainesc201902.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)
data2019.02 <- full_join(df,data.frame(dat.times=dat.times, gamma=gamma))
[1] "data from 2019-02-01 to 2019-02-28 23:55:00"
Joining, by = "dat.times"
In [14]:
ts.zoo=zoo(data2019.02$gamma,data2019.02$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 - February 2019",xaxt="n",type="b",pch=20)
axis(1, at = ticks,labels=labs, tcl = -0.3)
In [15]:
myfile <- getURL('https://rdm.inesctec.pt/dataset/7ff52a34-c10e-402c-9db8-ecfac9d5e514/resource/39672e54-a57b-4087-a2fe-c073bb7b647d/download/gammainesc201903.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)
data2019.03 <- full_join(df,data.frame(dat.times=dat.times, gamma=gamma))
[1] "data from 2019-03-01 to 2019-03-31 23:55:00"
Joining, by = "dat.times"
In [16]:
ts.zoo=zoo(data2019.03$gamma,data2019.03$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 2019",xaxt="n",type="b",pch=20)
axis(1, at = ticks,labels=labs, tcl = -0.3)
In [2]:
myfile <- getURL('https://rdm.inesctec.pt/dataset/7ff52a34-c10e-402c-9db8-ecfac9d5e514/resource/e6f02e4b-1329-446a-86e6-d6e745eaacaa/download/gammainesc201904.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)
data2019.04 <- full_join(df,data.frame(dat.times=dat.times, gamma=gamma))
[1] "data from 2019-04-01 to 2019-04-30 23:55:00"
Joining, by = "dat.times"
In [3]:
ts.zoo=zoo(data2019.04$gamma,data2019.04$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 2019",xaxt="n",type="b",pch=20)
axis(1, at = ticks,labels=labs, tcl = -0.3)
In [4]:
myfile <- getURL('https://rdm.inesctec.pt/dataset/7ff52a34-c10e-402c-9db8-ecfac9d5e514/resource/d7d7f4dc-e217-4028-8381-0110ed964b81/download/gammainesc201905.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)
data2019.05 <- full_join(df,data.frame(dat.times=dat.times, gamma=gamma))
[1] "data from 2019-05-01 to 2019-05-31 23:55:00"
Joining, by = "dat.times"
In [5]:
ts.zoo=zoo(data2019.05$gamma,data2019.05$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 2019",xaxt="n",type="b",pch=20)
axis(1, at = ticks,labels=labs, tcl = -0.3)
In [6]:
myfile <- getURL('https://rdm.inesctec.pt/dataset/7ff52a34-c10e-402c-9db8-ecfac9d5e514/resource/6683d3a2-201b-413f-8157-1dcb8e4dc5f1/download/gammainesc201906.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)
data2019.06 <- full_join(df,data.frame(dat.times=dat.times, gamma=gamma))
[1] "data from 2019-06-01 to 2019-06-10 22:50:00"
Joining, by = "dat.times"
In [7]:
ts.zoo=zoo(data2019.06$gamma,data2019.06$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 2019",xaxt="n",type="b",pch=20)
axis(1, at = ticks,labels=labs, tcl = -0.3)
In [ ]: