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CPC_P22_1810.R
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###########################################################################################################################
## Project: NEXTDATA ##
## Parameter: CPC ##
## Script first purpose: create monthly, semester, annual and seasonal graphic and statistics data reports ##
## Script second purpose: create time variation data reports ##
## Run time: the script may run daily (e.g. by using a crontab) or may be used when needed ##
##_______________________________________________________________________________________________________________________##
## Authors: Luca Naitza, Davide Putero ##
## Organization: National Research Council of Italy, Institute for Atmospheric Science and Climate (CNR-ISAC) ##
## Address: Via Gobetti 101, 40129, Bologna, Italy ##
## Project Contact: Paolo Cristofanelli ##
## Email: [email protected] ##
## Phone number: (+39) 051 639 9597 ##
##_______________________________________________________________________________________________________________________##
## Script filename: CPC_P22_1810.R ##
## Version Date: February 2019
## Feb. 12th, 2019: fixed MONTHLY/ANNUAL issue of creating empty plots when data from ancillary parameters are missing
###########################################################################################################################
# > > > > > > > > > > > > > > I N S T R U C T I O N S < < < < < < < < < < < < < < < < < < < < < < < < #
#
# This script consists of several parts and sub-parts.
#
# Part 0 is the setting section, in which the User should replace the marked values (e.g. directory paths)
# Part 0.1 defines environmental variables, such as raw data and destination directories. The user should modify these values.
# Part 0.2 specifies the characteristics of User Station/Laboratory/Instrument/parameter. Most of these variables are used
# as metadata in the EBAS file format header. The User should provide proper information.
#
# Part 1 is another setting section; it should not be modified by the User unless strictly needed.
# Part 1.1 sets and loads the most commonly used R libraries. The User should not modify this sub-part.
# Part 1.2 specifies the time variables used in the processing. The User should not modify this sub-part. If the User needs
# to apply the script to data older than the current year, he/she may modify the lines explicitly marked for this purpose.
#
# Part 2 is the data processing section, it should not be modified by the User.
# Part 2.x contain the code to produce the EBAS format file and to process data. The User should not modify this sub-part(s).
#
# Part 3 is the data reporting section, it should not be modified by the User.
# Part 3.x contain the code to produce graphic reports. The User should not modify this sub-part(s).
#
# > > > > > > > > > > > > > > > > > > > > > > > > > > > < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < < #
###########################################################################################################################
## # PART 0.1 #
## ______________________________________________________________________________________________________________________##
## Setting environmental variables
## ______________________________________________________________________________________________________________________##
## USE: set the following paths of origin raw data and of destination processing data, replacing values with yours
# WARNING: Proper setting up of the following paths and values is crucial. Please, replace the strings correctly
#
setwd("~/")
# -------- RAW DATA PATH ----------------------------------------------------------------------# REPLACE THE FOLLOWING PATHS
CALIB_DIR = '../naitza/NEXTDATA/PROD/CIMONE/AEROSOL/CPC/RAW_DATA_UTC/CALIB'
RAW_DIR = '../naitza/NEXTDATA/PROD/CIMONE/AEROSOL/CPC/RAW_DATA_UTC'
METEO_RAW_DIR = '../naitza/NEXTDATA/PROD/CIMONE/AEROSOL/NEPH/RAW_DATA_UTC'
#
# -------- DATA DESTINATION PATH --------------------------------------------------------------# REPLACE THE FOLLOWING PATHS
L0_DIR = '../naitza/NEXTDATA/DISTRIBUTION_DIR/CIMONE/AEROSOL/CPC/LEVEL_0'
L1_DIR = '../naitza/NEXTDATA/DISTRIBUTION_DIR/CIMONE/AEROSOL/CPC/LEVEL_1'
L2_DIR = '../naitza/NEXTDATA/DISTRIBUTION_DIR/CIMONE/AEROSOL/CPC/LEVEL_2'
L0_ANCIL_DIR = '../naitza/NEXTDATA/DISTRIBUTION_DIR/CIMONE/AEROSOL/CPC/LEVEL_0/ANCILLARY'
#
# -------- GRAPH DESTINATION PATH -------------------------------------------------------------# REPLACE THE FOLLOWING PATHS
REP_DIR = '../naitza/NEXTDATA/DISTRIBUTION_DIR/CIMONE/AEROSOL/CPC/REPORT'
REP_GRAPH_DIR = '../naitza/NEXTDATA/DISTRIBUTION_DIR/CIMONE/AEROSOL/CPC/REPORT/DAILY_GRAPH'
PLOT_DIR_M = '../naitza/NEXTDATA/DISTRIBUTION_DIR/CIMONE/AEROSOL/CPC/REPORT/MONTHLY_GRAPH'
PLOT_DIR_S = '../naitza/NEXTDATA/DISTRIBUTION_DIR/CIMONE/AEROSOL/CPC/REPORT/SEASONAL_GRAPH'
PLOT_DIR_Y = '../naitza/NEXTDATA/DISTRIBUTION_DIR/CIMONE/AEROSOL/CPC/REPORT/ANNUAL_GRAPH'
PLOT_DIR_Y_PDF = '../naitza/NEXTDATA/DISTRIBUTION_DIR/CIMONE/AEROSOL/CPC/REPORT/ANNUAL_GRAPH/PDF'
PLOT_DIR_T = '../naitza/NEXTDATA/DISTRIBUTION_DIR/CIMONE/AEROSOL/CPC/REPORT/TIMEVARIATION_GRAPH'
#
# -------- SCRIPTS PATH ----------------------------------------------------------------------# REPLACE THE FOLLOWING PATHS
SCRIPT_DIR = '../naitza/NEXTDATA/R_SCRIPT'
## Loading functions for numflags
## The "NXD_numflag_functions_180301.R" scripts assigns the numflag value to the Data set, according to EBAS Flag List
## (https://ebas-submit.nilu.no/Submit-Data/List-of-Data-flags)
## The "NXD_EBAS_numflag_FullList_180103.txt" text file contains the EBAS Flag List, reporting codes, category and description
## Please, do NOT apply any change to the following function settings, unless you need to specify a different table of flags
#
source(paste(SCRIPT_DIR,"NXD_numflag_functions_180301.R", sep="/"))
tab_nf <- read.table(file = paste(SCRIPT_DIR,"NXD_EBAS_numflag_FullList_180103.txt",sep="/"),
sep = ";", header = TRUE, quote = NULL)
## # END PART 0.1 #
###########################################################################################################################
###########################################################################################################################
## # PART 0.2 #
## ______________________________________________________________________________________________________________________##
## Setting Level-0 Data sheet
##
## ______________________________________________________________________________________________________________________##
# Station/Laboratory/Instrument/parameter variables
#
# -------- EBAS HEADER FILE (METADATA) -----------------------------------------------------# REPLACE THE FOLLOWING VALUES
#
s_code <- "IT0009R" # replace the value with your Station code
#
s_GAW_ID <- "CMN" # replace the value with your Station GAW ID
#
inst_type <- "CPC" # replace the value with your instrument type
#
## # END PART 0.2 #
###########################################################################################################################
###########################################################################################################################
## # PART 1.0 #
## ______________________________________________________________________________________________________________________##
## Loading libraries
## ______________________________________________________________________________________________________________________##
## NOTE: some of the following libraries may not be actually used by this script
# Please, do NOT apply any change, unless it is necessary to load specific libraries
#
library(data.table)
library(openair)
library(lattice)
library(RColorBrewer)
library(latticeExtra)
library(proto)
library(gsubfn)
library(RSQLite)
library(padr)
library(caTools)
library(zoo)
library(plyr)
library(forecast)
library("sqldf")
library(TTR)
library(ggplot2)
library(reshape2)
library(stringr)
library(png)
library(lubridate)
library(hydroTSM)
#
## # END PART 1.0 #
###########################################################################################################################
###########################################################################################################################
## # PART 1.1 #
## ______________________________________________________________________________________________________________________##
## Setting time and name variables
## Cleaning destination directory
## ______________________________________________________________________________________________________________________##
#
#
# -------------------------------------------------------------------------------------------
# Time variables
# NOTE: the following variables should not be modified, except those with explicit comments
#
questo_anno <-format(Sys.Date(), "%Y")
# -------- PREVIOUS YEAR(S) DATA PROCESSING ---------------------------------------# IF NEEDED, UN-COMMENT THE FOLLOWING LINE
#questo_anno <-as.numeric(questo_anno) -1 # the value "-1" means "last year". Change to "-2" or "-3" etc. for previous
questo_mese <-format(Sys.Date(), "%m")
questo_mese_nome <-format(Sys.Date(), "%B")
questo_giorno <-format(Sys.Date(), "%d")
if (questo_mese == "01" & questo_giorno == "01") { questo_anno == questo_anno-1 }
questo_capodanno <-paste(questo_anno,"01","01",sep="-")
questo_annomesegiorno <-paste(questo_anno,questo_mese,questo_giorno,sep="")
questa_ora <-format(Sys.time(), "%H")
questo_minuto <-format(Sys.time(), "%M")
questo_inizioanno <-paste(questo_anno,"0101000000",sep = "")
questa_start_time <-as.Date(paste(paste(questo_anno,"01","01",sep = "-"), " 00:00:00",sep = ""))
myweekday <-as.POSIXlt(Sys.Date())$wday
questo_startdate <-paste(questo_anno,"0101",sep="")
new_date <-gsub("-","",
gsub(" ","",
gsub(":","",
as.character(strptime(Sys.time(),
format = "%Y - %m - %d %H : %M")))))
new_date_name <-paste(".",new_date,sep="")
rev_datime <-gsub("-","",
gsub(" ","",
gsub(":","",
as.character(strptime(new_date,
format = "%Y%m%d%H%M%S")-3600))))
DATA_OSS <-paste(questo_anno,"01 01")
DATA_REV <-gsub("-"," ",Sys.Date())
DATA_INSERT <-paste(DATA_OSS,DATA_REV,sep=" ")
#
# -------------------------------------------------------------------------------------------
# Check point: printing variables
#
questo_anno
questo_mese
questo_mese_nome
questo_giorno
questo_capodanno
questo_annomesegiorno
questa_ora
questo_minuto
questo_inizioanno
questa_start_time
myweekday
questo_startdate
new_date
new_date_name
rev_datime
#
## # END PART 1.1 #
###########################################################################################################################
###########################################################################################################################
## # PART 2.0 #
## ______________________________________________________________________________________________________________________##
## Reading Level-0, Level-1, Level-2 data sheets
## Cleaning Destination directory
## Formatting Level-1 header
## ______________________________________________________________________________________________________________________##
#
# -------------------------------------------------------------------------------------------
# Reading Level-0
#
FILE_L0 <-list.files(path = L0_DIR, pattern = glob2rx(paste(s_code,".",questo_anno,"*",sep = "")),
all.files = FALSE,
full.names = F, recursive = FALSE,
ignore.case = FALSE, include.dirs = F, no.. = FALSE)
EBAS_L0_FILENAME <-as.character(FILE_L0[1])
EBAS_L0_FILENAME
#
# -------------------------------------------------------------------------------------------
#Reading header lines of Level-0 Data sheet
#
L0_n_lines <- as.integer(unlist(strsplit(readLines(paste(L0_DIR,EBAS_L0_FILENAME,sep = "/"), n=1), " "))[1])
L0_n_lines
#
# Creating temporary data table of Level-0
#
temp_L00 <-read.table(paste(L0_DIR,EBAS_L0_FILENAME,sep = "/"), skip = L0_n_lines-1, header = T)
#
# -------------------------------------------------------------------------------------------
# Setting NA to 9999.999 values
#
temp_L00$p_int [temp_L00$p_int == 9999.99] <- NA
temp_L00$T_int [temp_L00$T_int == 9999.99] <- NA
temp_L00$RH [temp_L00$RH == 9999.99] <- NA
#
# -------------------------------------------------------------------------------------------
#Converting JD values to date
#
temp_L00$jd <-as.integer(temp_L00$start_time)
#
temp_L00$day <-as.Date(temp_L00$start_time, origin=questa_start_time)
temp_L00$time.dec <-temp_L00$start_time-temp_L00$jd
temp_L00$time <-temp_L00$time.dec*1440+0.01
temp_L00$hour <-as.integer(temp_L00$time/60)
temp_L00$min <-as.integer(temp_L00$time-temp_L00$hour*60)
temp_L00$date <-paste(temp_L00$day," ",temp_L00$hour,":",temp_L00$min,":00",sep="")
temp_L00$date <-as.POSIXct(strptime(temp_L00$date, format = "%Y-%m-%d %H:%M:%S", tz = "GMT"))
temp_L00$monthNum <-format(temp_L00$date, "%m")
#
# -------------------------------------------------------------------------------------------
# Reading Level-1
#
FILE_L1 <-list.files(path = L1_DIR, pattern = glob2rx(paste(s_code,".",questo_anno,"*",sep = "")),
all.files = FALSE,
full.names = F, recursive = FALSE,
ignore.case = FALSE, include.dirs = F, no.. = FALSE)
EBAS_L1_FILENAME <-as.character(FILE_L1[1])
EBAS_L1_FILENAME
# -------------------------------------------------------------------------------------------
#Reading header lines of Level-1 Data sheet
#
L1_n_lines <- as.integer(unlist(strsplit(readLines(paste(L1_DIR,EBAS_L1_FILENAME,sep = "/"), n=1), " "))[1])
L1_n_lines
#
# -------------------------------------------------------------------------------------------
# Creating temporary data table of Level-1
#
temp_L01 <-read.table(paste(L1_DIR,EBAS_L1_FILENAME,sep = "/"),skip = L1_n_lines-1,header = T)
# -------------------------------------------------------------------------------------------
# Setting NA to 9999.999 values
#
temp_L01$p_int [temp_L01$p_int == 9999.99] <- NA
temp_L01$T_int [temp_L01$T_int == 9999.99] <- NA
#
# -------------------------------------------------------------------------------------------
#Converting JD values to date
#
temp_L01$jd <-as.integer(temp_L01$start_time)
#
temp_L01$day <-as.Date(temp_L01$start_time, origin=questa_start_time)
temp_L01$time.dec <-temp_L01$start_time-temp_L01$jd
temp_L01$time <-temp_L01$time.dec*1440+0.01
temp_L01$hour <-as.integer(temp_L01$time/60)
temp_L01$min <-as.integer(temp_L01$time-temp_L01$hour*60)
temp_L01$date <-paste(temp_L01$day," ",temp_L01$hour,":",temp_L01$min,":00",sep="")
temp_L01$date <-as.POSIXct(strptime(temp_L01$date, format = "%Y-%m-%d %H:%M:%S", tz = "GMT"))
temp_L01$monthNum <-format(temp_L01$date,"%m")
temp_L01$month <-format(temp_L01$date,"%B")
temp_L01$day <-format(temp_L01$date,"%d")
#
temp_L01$nf_validity <-sapply(temp_L01$numflag, nf_val_check, tab_nf$numflag, tab_nf$category)
# -------------------------------------------------------------------------------------------
# Reading Level-2
# Creating temporary data table of Level-2
#
FILE_L2 <-list.files(path = L2_DIR, pattern = glob2rx(paste(s_code,".",questo_anno,"*",sep = "")), all.files = FALSE,
full.names = F, recursive = FALSE,
ignore.case = FALSE, include.dirs = F, no.. = FALSE)
EBAS_L2_FILENAME <-as.character(FILE_L2[1])
EBAS_L2_FILENAME
# -------------------------------------------------------------------------------------------
#Reading header lines of Level-2 Data sheet
#
L2_n_lines <- as.integer(unlist(strsplit(readLines(paste(L2_DIR,EBAS_L2_FILENAME,sep = "/"), n=1), " "))[1])
L2_n_lines
#
# -------------------------------------------------------------------------------------------
# Creating temporary data table of Level-2
#
temp_L02 <-read.table(paste(L2_DIR,EBAS_L2_FILENAME,sep = "/"),skip = L2_n_lines-1, header = T)
#
# -------------------------------------------------------------------------------------------
# Creating a subset over L02 data
#
temp_L02 <- subset(temp_L02, temp_L02$start_time < strptime(as.POSIXct(Sys.Date()), "%Y-%m-%d %H:%M")$yday)
#
# -------------------------------------------------------------------------------------------
#Converting JD values to date
#
temp_L02$jd <-as.integer(temp_L02$start_time)
#
temp_L02$day <-as.Date(temp_L02$start_time, origin=questa_start_time)
temp_L02$time.dec <-temp_L02$start_time-temp_L02$jd
temp_L02$time <-temp_L02$time.dec*1440+0.01
temp_L02$hour <-as.integer(temp_L02$time/60)
temp_L02$min <-as.integer(temp_L02$time-temp_L02$hour*60)
temp_L02$min <-as.integer(temp_L02$time-temp_L02$hour*60)
temp_L02$date <-paste(temp_L02$day," ",temp_L02$hour,":",temp_L02$min,":00",sep="")
temp_L02$date <-as.POSIXct(strptime(temp_L02$date, format = "%Y-%m-%d %H:%M:%S", tz = "GMT"))
temp_L02$monthNum <-format(temp_L02$date, "%m")
#
CPC_L02_today <-data.frame(temp_L02$date,temp_L02$conc,temp_L02$numflag)
#
colnames(CPC_L02_today) <- c("date","conc","numflag")
#
CPC_L02_today$month <- format(CPC_L02_today$date,"%B")
CPC_L02_today$monthNum <- as.numeric(format(CPC_L02_today$date,"%m"))
CPC_L02_today$day <- as.numeric(format(CPC_L02_today$date,"%d"))
#
CPC_FAIL_today <- subset(CPC_L02_today, numflag == 0.999)
#
TFAIL <- subset(CPC_FAIL_today, select=c("month","day","monthNum","numflag"))
mesi_FAIL <- data.frame(TFAIL[!duplicated(TFAIL[1:2]),])
mesi_FAIL_COUNT <- data.frame(mesi_FAIL[!duplicated(mesi_FAIL[1]),],count(mesi_FAIL,"monthNum"))
#
if (nrow(mesi_FAIL) > 0) { mesi_FAIL_COUNT$print <-paste(mesi_FAIL_COUNT$month," (",mesi_FAIL_COUNT$freq," days)",sep = "")
Somma_giorni_FAIL <- sum(mesi_FAIL_COUNT$freq)}
if (nrow(mesi_FAIL) == 0) { }
#
CPC_L02_today_Y <- subset(CPC_L02_today, numflag != 0.999)
#
unico <- c(CPC_L02_today_Y[!duplicated(CPC_L02_today_Y[,c('month')]),]$month)
#
# -------------------------------------------------------------------------------------------
#
## # END PART 2.0 #
###########################################################################################################################
###########################################################################################################################
## # PART 3.0 #
## ______________________________________________________________________________________________________________________##
## Creating statistcs/graphic reports
## MONTHLY GRAPHS
## Cleaning Destination directory
##
## ______________________________________________________________________________________________________________________##
# Subsetting data by month
#
unico_M <- c(CPC_L02_today_Y[!duplicated(CPC_L02_today_Y[,c('monthNum')]),]$monthNum)
for (qm in unico_M)
{
CPC_L02_ThisMonth <-subset(CPC_L02_today_Y, as.integer(monthNum)==qm)
temp_L02_ThisMonth <-subset(temp_L02, as.integer(monthNum)==qm)
temp_L01_ThisMonth <-subset(temp_L01, as.integer(monthNum)==qm)
temp_L00_ThisMonth <-subset(temp_L00, as.integer(monthNum)==qm)
OBS_Month_start <-head(format(temp_L02_ThisMonth$date,"%d %B %Y"),1)
OBS_Month_end <-tail(format(temp_L02_ThisMonth$date,"%d %B %Y"),1)
#
# -------------------------------------------------------------------------------------------
# Calculating days with invalid flags
#
FAIL_ThisMonth <- subset(CPC_FAIL_today, as.integer(monthNum) == qm)
FAIL_ThisMonth$day <-format(FAIL_ThisMonth$date,"%d")
FAIL_unico <-data.frame(FAIL_ThisMonth[!duplicated(FAIL_ThisMonth[,c('day')]),])
FAIL_DAYS <-nrow(FAIL_unico)
mensile <-subset(CPC_L02_ThisMonth, numflag != 0.999)
mensile$giorno <-format(mensile$date,"%d")
This_Month <-format(mensile$date,"%m")[1]
This_Month_Name <-format(mensile$date,"%B")[1]
print(paste("ora il ",This_Month_Name[1], FAIL_DAYS)) # check point: printing month and failing days
#
# -------------------------------------------------------------------------------------------
# Calculating monthly statistics
#
mensile$mean <-mean(mensile$conc)
mensile$sd <-sd(mensile$conc)
men_MIN <-subset(mensile, conc == min(mensile$conc))
men_MAX <-subset(mensile, conc == max(mensile$conc))
# -------------------------------------------------------------------------------------------
# Cleaning Destination directory
#
FILE_PLOT_M<-list.files(path = PLOT_DIR_M, pattern = paste(s_GAW_ID,inst_type,questo_anno,This_Month,"MONTHLY_GRAPH_*",sep = "_"),
all.files = FALSE,
full.names = F, recursive = FALSE,
ignore.case = FALSE, include.dirs = F, no.. = FALSE)
FILE_PLOT_M
LISTA_PLOT_M<-as.character(FILE_PLOT_M)
for(f in LISTA_PLOT_M)
{
file.remove(paste(PLOT_DIR_M,f,sep = "/"))
}
#
# -------------------------------------------------------------------------------------------
# Preparing plotting files
#
PLOT_M_NAME <-paste(s_GAW_ID, inst_type, questo_anno, This_Month, "MONTHLY_GRAPH", gsub("-","",Sys.Date()), sep = "_")
PLOT_M_NAME_FULL <-paste (PLOT_DIR_M,paste(PLOT_M_NAME,".png",sep = ""),sep = "/")
png(file=,PLOT_M_NAME_FULL, width = 2480, height = 3508)
#
# -------------------------------------------------------------------------------------------
# Preparing plotting parameters (font size, margins, ...)
#
par(mfrow = c(6,1))
par(ps = 14, cex = 2.5, cex.main = 3.5,cex.sub=2.2, cex.lab=3.5, cex.axis = 3.5, mai=c(0.3,1.8,0.5,0.5))
#
# -------------------------------------------------------------------------------------------
# Crating the plotting matrix
#
m <- rbind(c(1, 1), c(2, 2), c(3, 3), c(4, 4), c(5, 5), c(6, 7))#, c(7, 8))
layout(m)
#
# -------------------------------------------------------------------------------------------
# -------------------------------------------------------------------------------------------
# Plotting CONC
#
plot(ylim=c(men_MIN$conc[1]-300,men_MAX$conc[1]+300),
xlim = c(min(c(CPC_L02_ThisMonth$date,temp_L01_ThisMonth$date,temp_L00_ThisMonth$date)),
max(c(CPC_L02_ThisMonth$date,temp_L01_ThisMonth$date,temp_L00_ThisMonth$date))),
mgp = c(8, 4, 0),
mensile$date, mensile$conc, type = "h",
xlab = "",ylab =expression(paste("Ntot (#/cm"^{3},") - L02")), col="lightblue", panel.first = grid(nx=0,ny=NULL, lty = 1, lwd = 1))
title(paste("Ntot - L02 -",questo_anno,This_Month_Name), line = -3)
lines(CPC_L02_ThisMonth$date, mensile$conc, type = "l", lty = 1, col="darkred",lwd = 2)
points(men_MAX$date[1], men_MAX$conc[1], col= "magenta",pch=20)
text(men_MAX$date[1], men_MAX$conc[1], labels = paste("Max (", format(men_MAX$date[1],"%B %d"), ")", sep=""),col="magenta",pos=3,cex = 1.8)
segments(men_MAX$date[1], men_MAX$conc[1], men_MAX$date[1], men_MIN$conc[1]-400, lty = 2, col="black",lwd = 1)
points(men_MIN$date[1], men_MIN$conc[1], col= "blue",pch=20)
text(men_MIN$date[1], men_MIN$conc[1], labels = paste("Min (", format(men_MIN$date[1],"%B %d"), ")", sep =""),col="blue",pos=1,cex = 1.8)
segments(men_MIN$date[1], men_MIN$conc[1], men_MIN$date[1], men_MIN$conc[1]-400, lty = 2, col="black",lwd = 1)
lines(mensile$date,mensile$mean, type = "l", lty = 1, col="red",lwd = 1)
text(mensile$date[1],mensile$mean[1]+200, labels = c("Mean"),col="red",cex = 1.8)
#
# -------------------------------------------------------------------------------------------
# -------------------------------------------------------------------------------------------
# Plotting NUMFLAG (L01)
#
plot(ylim=c(0,1.1),
xlim = c(min(c(CPC_L02_ThisMonth$date,temp_L01_ThisMonth$date,temp_L00_ThisMonth$date)),
max(c(CPC_L02_ThisMonth$date,temp_L01_ThisMonth$date,temp_L00_ThisMonth$date))),
mgp = c(8, 4, 0),
temp_L01_ThisMonth$date, temp_L01_ThisMonth$numflag, type = "h",
xlab = "",ylab =("numflag - L01"), col="tan", panel.first = grid(nx=0,ny=NULL, lty = 1, lwd = 1))
title(paste("numflag - L01 -",questo_anno,This_Month_Name), line = -3)
lines(temp_L01_ThisMonth$date, temp_L01_ThisMonth$numflag, type = "l",
lty = 1,
col = "lightgreen",
lwd = 2)
#
# -------------------------------------------------------------------------------------------
# -------------------------------------------------------------------------------------------
# Plotting P
#
if(all(is.na(temp_L00_ThisMonth$p_int)))
{
plot(ylim = c(690,890),
xlim = c(min(c(CPC_L02_ThisMonth$date,temp_L01_ThisMonth$date,temp_L00_ThisMonth$date)),
max(c(CPC_L02_ThisMonth$date,temp_L01_ThisMonth$date,temp_L00_ThisMonth$date))),
mgp = c(8, 4, 0),
temp_L00_ThisMonth$date, temp_L00_ThisMonth$p_int, type = "h",
xlab = "",ylab =("P_int (hPa) - L00"), col="lightblue", panel.first = grid(nx=0,ny=NULL, lty = 1, lwd = 1))
title(paste("Internal pressure - L00 - data for this month are absent"), line = -3)
title(paste("No data"), line = -28, cex = 0.8)
} else {
plot(ylim=c(mean(temp_L00_ThisMonth$p_int, na.rm = TRUE)-100,mean(temp_L00_ThisMonth$p_int, na.rm = TRUE)+100),
xlim = c(min(c(CPC_L02_ThisMonth$date,temp_L01_ThisMonth$date,temp_L00_ThisMonth$date)),
max(c(CPC_L02_ThisMonth$date,temp_L01_ThisMonth$date,temp_L00_ThisMonth$date))),
mgp = c(8, 4, 0),
temp_L00_ThisMonth$date, temp_L00_ThisMonth$p_int, type = "h",
xlab = "",ylab =("P_int (hPa) - L00"), col="lightblue", panel.first = grid(nx=0,ny=NULL, lty = 1, lwd = 1))
lines(temp_L00_ThisMonth$date, temp_L00_ThisMonth$p_int, type = "l", lty = 1, col="darkblue",lwd = 0.5)
title(paste("Internal pressure - L00 -",questo_anno,This_Month_Name), line = -3)
}
#
# -------------------------------------------------------------------------------------------
# -------------------------------------------------------------------------------------------
# Plotting T_int
#
if(all(is.na(temp_L00_ThisMonth$T_int)))
{
plot(ylim = c(280,320),
xlim = c(min(c(CPC_L02_ThisMonth$date,temp_L01_ThisMonth$date,temp_L00_ThisMonth$date)),
max(c(CPC_L02_ThisMonth$date,temp_L01_ThisMonth$date,temp_L00_ThisMonth$date))),
mgp = c(8, 4, 0),
temp_L00_ThisMonth$date, temp_L00_ThisMonth$T_int, type = "h",
xlab = "",ylab =("T_int (K) - L00"), col="pink", panel.first = grid(nx=0,ny=NULL, lty = 1, lwd = 1))
title(paste("Internal temperature - L00 - data for this month are absent"), line = -3)
title(paste("No data"), line = -28, cex = 0.8)
} else {
plot(ylim=c(mean(temp_L00_ThisMonth$T_int, na.rm = TRUE)-20,mean(temp_L00_ThisMonth$T_int, na.rm = TRUE)+20),
xlim = c(min(c(CPC_L02_ThisMonth$date,temp_L01_ThisMonth$date,temp_L00_ThisMonth$date)),
max(c(CPC_L02_ThisMonth$date,temp_L01_ThisMonth$date,temp_L00_ThisMonth$date))),
mgp = c(8, 4, 0),
temp_L00_ThisMonth$date, temp_L00_ThisMonth$T_int, type = "h",
xlab = "",ylab =("T_int (K) - L00"), col="pink", panel.first = grid(nx=0,ny=NULL, lty = 1, lwd = 1))
lines(temp_L00_ThisMonth$date, temp_L00_ThisMonth$T_int, type = "l", lty = 1, col="blue",lwd = 0.5)
title(paste("Internal temperature - L00 -",questo_anno,This_Month_Name), line = -3)
}
#
# -------------------------------------------------------------------------------------------
# -------------------------------------------------------------------------------------------
# Plotting RH
#
if(all(is.na(temp_L00_ThisMonth$RH)))
{
plot(ylim = c(0,100),
xlim = c(min(c(CPC_L02_ThisMonth$date,temp_L01_ThisMonth$date,temp_L00_ThisMonth$date)),
max(c(CPC_L02_ThisMonth$date,temp_L01_ThisMonth$date,temp_L00_ThisMonth$date))),
mgp = c(8, 4, 0),
temp_L00_ThisMonth$date, temp_L00_ThisMonth$RH, type = "h",
xlab = "",ylab =("RH (%) - L00"), col="seashell", panel.first = grid(nx=0,ny=NULL, lty = 1, lwd = 1))
title(paste("Relative humidity - L00 - data for this month are absent"), line = -3)
title(paste("No data"), line = -28, cex = 0.8)
} else {
plot(ylim=c(0,100),
xlim = c(min(c(CPC_L02_ThisMonth$date,temp_L01_ThisMonth$date,temp_L00_ThisMonth$date)),
max(c(CPC_L02_ThisMonth$date,temp_L01_ThisMonth$date,temp_L00_ThisMonth$date))),
mgp = c(8, 4, 0),
temp_L00_ThisMonth$date, temp_L00_ThisMonth$RH, type = "h",
xlab = "",ylab =("RH (%) - L00"), col="seashell", panel.first = grid(nx=0,ny=NULL, lty = 1, lwd = 1))
lines(temp_L00_ThisMonth$date, temp_L00_ThisMonth$RH, type = "l", lty = 1, col="mediumorchid4",lwd = 0.5)
title(paste("Relative humidity - L00 -",questo_anno,This_Month_Name), line = -3)
}
#
# -------------------------------------------------------------------------------------------
# -------------------------------------------------------------------------------------------
# Plotting Text
#
plot(c(0, 1), c(0, 1), ann = F, bty = 'n', type = 'n', xaxt = 'n', yaxt = 'n')
text(x = 0, y = 0.95, paste (PLOT_M_NAME," - ",This_Month_Name," ",questo_anno),
cex = 3.3, col = "darkred",pos = 4)
text(x = -0.005, y = 0.75, paste(" Observations from", OBS_Month_start," to ", OBS_Month_end,
"\n",
"(days of observation: ", 1+(as.integer(tail((mensile$date),1)-head((mensile$date)),1)),")")
, cex = 2.8, col = "black",pos = 4)
plot(c(0, 1), c(0, 1), ann = F, bty = 'n', type = 'n', xaxt = 'n', yaxt = 'n')
text(x = 0, y = 0.95, paste ("Statistics - ",This_Month_Name," ",questo_anno),
cex = 3.3, col = "darkred",pos = 4)
text(x = 0, y = 0.55, paste("\n", "Ntot min: (", round(min(mensile$conc),0),") - Ntot max: (", round(max(mensile$conc),0),") - Ntot mean: (", round(mean(mensile$conc),0),") - Ntot sd: (", round(sd(mensile$conc),0),")","\n",
"Ntot percentile: 5th: (",round(quantile(mensile$conc, probs = c(0.05)),digits=0),")",
" - 25th: (",round(quantile(mensile$conc, probs = c(0.25)),digits=0),")",
" - 50th: (",round(quantile(mensile$conc, probs = c(0.50)),digits=0),")",
" - 75th: (",round(quantile(mensile$conc, probs = c(0.75)),digits=0),")",
" - 95th: (",round(quantile(mensile$conc, probs = c(0.95)),digits=0),")","\n","\n",
"L02 numflag = 0.999 (number of days affected): ", FAIL_DAYS,
" (",round((FAIL_DAYS/days_in_month(temp_L02_ThisMonth$date[1]))*100,digits=2),"%)",
"\n",
"Days of ",This_Month_Name," affected:","\n",
if (FAIL_DAYS==0){"none"},
if (!is.na(FAIL_unico$day[1])){FAIL_unico$day[1]} ," ",
if (!is.na(FAIL_unico$day[2])){FAIL_unico$day[2]} ," ",
if (!is.na(FAIL_unico$day[3])){FAIL_unico$day[3]} ," ",
if (!is.na(FAIL_unico$day[4])){FAIL_unico$day[4]} ," ",
if (!is.na(FAIL_unico$day[5])){FAIL_unico$day[5]} ," ",
if (!is.na(FAIL_unico$day[6])){FAIL_unico$day[6]} ," ",
if (!is.na(FAIL_unico$day[7])){FAIL_unico$day[7]} ," ",
if (!is.na(FAIL_unico$day[8])){FAIL_unico$day[8]} ," ",
if (!is.na(FAIL_unico$day[9])){FAIL_unico$day[9]} ," ",
if (!is.na(FAIL_unico$day[10])){FAIL_unico$day[10]} ," ",
if (!is.na(FAIL_unico$day[11])){FAIL_unico$day[11]} ," ",
if (!is.na(FAIL_unico$day[12])){FAIL_unico$day[12]} ," ",
if (!is.na(FAIL_unico$day[13])){FAIL_unico$day[13]} ," ",
if (!is.na(FAIL_unico$day[14])){FAIL_unico$day[14]} ," ",
if (!is.na(FAIL_unico$day[15])){FAIL_unico$day[15]} ," ",
"\n",
if (!is.na(FAIL_unico$day[16])){FAIL_unico$day[16]} ," ",
if (!is.na(FAIL_unico$day[17])){FAIL_unico$day[17]} ," ",
if (!is.na(FAIL_unico$day[18])){FAIL_unico$day[18]} ," ",
if (!is.na(FAIL_unico$day[19])){FAIL_unico$day[19]} ," ",
if (!is.na(FAIL_unico$day[20])){FAIL_unico$day[20]} ," ",
if (!is.na(FAIL_unico$day[21])){FAIL_unico$day[21]} ," ",
if (!is.na(FAIL_unico$day[22])){FAIL_unico$day[22]} ," ",
if (!is.na(FAIL_unico$day[23])){FAIL_unico$day[23]} ," ",
if (!is.na(FAIL_unico$day[24])){FAIL_unico$day[24]} ," ",
if (!is.na(FAIL_unico$day[25])){FAIL_unico$day[25]} ," ",
if (!is.na(FAIL_unico$day[26])){FAIL_unico$day[26]} ," ",
if (!is.na(FAIL_unico$day[27])){FAIL_unico$day[27]} ," ",
if (!is.na(FAIL_unico$day[28])){FAIL_unico$day[28]} ," ",
if (!is.na(FAIL_unico$day[29])){FAIL_unico$day[29]} ," ",
if (!is.na(FAIL_unico$day[30])){FAIL_unico$day[30]} ," ",
if (!is.na(FAIL_unico$day[31])){FAIL_unico$day[31]} ," ",
sep=""),
cex = 2.8, col = "black",pos = 4)
dev.off()
}
#
# -------------------------------------------------------------------------------------------
## # END PART 3.0 #
###########################################################################################################################
###########################################################################################################################
## # PART 3.1 #
## ______________________________________________________________________________________________________________________##
## Creating statistcs/graphic reports
## SEMESTER GRAPHS
## Cleaning Destination directory
##
## ______________________________________________________________________________________________________________________##
# Subsetting data by semester
# First semester
#
Fhalf <-subset(CPC_L02_today_Y,monthNum<7)
if (nrow(Fhalf)==0){ } else
{
# -------------------------------------------------------------------------------------------
# Cleaning Destination directory
#
FILE_PLOT_1HM<-list.files(path = PLOT_DIR_M, pattern = paste(s_GAW_ID, inst_type,questo_anno,"SEMESTER_1st_GRAPH_*",sep = "_"), all.files = FALSE,
full.names = F, recursive = FALSE,
ignore.case = FALSE, include.dirs = F, no.. = FALSE)
FILE_PLOT_1HM
LISTA_PLOT_1HM<-as.character(FILE_PLOT_1HM)
for(f in LISTA_PLOT_1HM)
{
file.remove(paste(PLOT_DIR_M,f,sep = "/"))
}
#
# -------------------------------------------------------------------------------------------
# Preparing plotting files
#
unico<-c(Fhalf[!duplicated(Fhalf[,c('month')]),]$month)
#
# -------------------------------------------------------------------------------------------
# Preparing plotting parameters (font size, margins, ...)
#
png(file=paste(PLOT_DIR_M,paste(s_GAW_ID,"_",inst_type,"_",questo_anno,"_SEMESTER_1st_GRAPH_",gsub("-","",Sys.Date()),".png",sep = ""),sep = "/"),
width = 2480, height = 3508)
#
# -------------------------------------------------------------------------------------------
# Creating the plotting matrix
#
layout(matrix(c(1,2,3,4,5,6,7),ncol=1), widths=c(10,10,10,10,10,10,10), heights=c(2.2,2.2,2.2,2.2,2.2,2.2,0.2), TRUE)
par(ps = 12, cex = 1.8, cex.main = 1.8,cex.sub=1.8, cex.lab=1.8, cex.axis = 1.5, mai=c(0.3,1.8,0.5,0.5)) # make labels and margins smaller (mai= giu, sx,su,dx)
for (i in unico[1:length(unico)])
{
print(i)
mensile <-subset(CPC_L02_today_Y, month == i)
mensile$giorno <-format(mensile$date,"%d")
mensile$mean <-mean(mensile$conc)
mensile$sd <-sd(mensile$conc)
men_MIN <-subset(mensile, conc == min(mensile$conc))
men_MAX <-subset(mensile, conc == max(mensile$conc))
{
plot(ylim=c(men_MIN$conc[1]-500,men_MAX$conc[1]+500),
mensile$date, mensile$conc, type = "h",
xlab = "",ylab =expression(paste("Ntot (#/cm"^{3},") - L02")), col="lightblue", panel.first = grid(nx=0,ny=NULL, lty = 1, lwd = 1))
title(main=paste(i,questo_anno,sep=" "),
line = -2.2)
title(paste("Statistics: min: (", round(min(mensile$conc),0),") - max: (", round(max(mensile$conc),0),") - mean: (", round(mean(mensile$conc),0),") - sd: (", round(sd(mensile$conc),0),")")
,col="black",cex.main = 1.2, line = -3.8, font.main = 1)
lines(mensile$date, mensile$conc, type = "l", lty = 1, col="darkred",lwd = 2)
points(men_MAX$date[1], men_MAX$conc[1], col= "magenta",pch=20)
text(men_MAX$date[1], men_MAX$conc[1], labels = paste("Max (",format(men_MAX$date[1],"%B %d"),")",sep=""),col="magenta",pos=3)
segments(men_MAX$date[1], men_MAX$conc[1], men_MAX$date[1], men_MIN$conc[1]-400, lty = 2, col="black",lwd = 1)
points(men_MIN$date[1], men_MIN$conc[1], col= "blue",pch=20)
text(men_MIN$date[1], men_MIN$conc[1], labels = paste("Min (",format(men_MIN$date[1],"%B %d"),")",sep=""),col="blue",pos=1)
segments(men_MIN$date[1], men_MIN$conc[1], men_MIN$date[1], men_MIN$conc[1]-400, lty = 2, col="black",lwd = 1)
}
}
dev.off()
}
#
# -------------------------------------------------------------------------------------------
# Subsetting data by semester
# Second semester
#
Shalf<-subset(CPC_L02_today_Y,monthNum>6)
if (nrow(Shalf)==0){}else
{
# -------------------------------------------------------------------------------------------
# Cleaning Destination directory
#
FILE_PLOT_2HM<-list.files(path = PLOT_DIR_M, pattern = paste(s_GAW_ID, inst_type,questo_anno,"SEMESTER_1st_GRAPH_*",sep = "_"), all.files = FALSE,
full.names = F, recursive = FALSE,
ignore.case = FALSE, include.dirs = F, no.. = FALSE)
FILE_PLOT_2HM
LISTA_PLOT_2HM<-as.character(FILE_PLOT_2HM)
for(f in LISTA_PLOT_2HM)
{
file.remove(paste(PLOT_DIR_M,f,sep = "/"))
}
#
# -------------------------------------------------------------------------------------------
# Preparing plotting files
#
unico<-c(Shalf[!duplicated(Shalf[,c('month')]),]$month)
#
# -------------------------------------------------------------------------------------------
# Preparing plotting parameters (font size, margins, ...)
#
png(file=paste(PLOT_DIR_M,paste(s_GAW_ID,"_",inst_type,"_",questo_anno,"_SEMESTER_2st_GRAPH_",gsub("-","",Sys.Date()),".png",sep = ""),sep = "/"),
width = 2480, height = 3508)
#
# -------------------------------------------------------------------------------------------
# Creating the plotting matrix
#
layout(matrix(c(1,2,3,4,5,6,7),ncol=1), widths=c(10,10,10,10,10,10,10), heights=c(2.2,2.2,2.2,2.2,2.2,2.2,0.2), TRUE)
par(ps = 12, cex = 1.8, cex.main = 1.8,cex.sub=1.8, cex.lab=1.8, cex.axis = 1.5, mai=c(0.3,1.8,0.5,0.5)) # make labels and margins smaller (mai= giu, sx,su,dx)
for (i in unico[1:length(unico)])
{
print(i)
mensile <-subset(CPC_L02_today_Y, month == i)
mensile$giorno <-format(mensile$date,"%d")
mensile$mean <-mean(mensile$conc)
mensile$sd <-sd(mensile$conc)
men_MIN <-subset(mensile, conc == min(mensile$conc))
men_MAX <-subset(mensile, conc == max(mensile$conc))
{
plot(ylim=c(men_MIN$conc[1]-500,men_MAX$conc[1]+500),
mensile$date, mensile$conc, type = "h",
xlab = "",ylab =expression(paste("Ntot (#/cm"^{3},") - L02")), col="lightblue", panel.first = grid(nx=0,ny=NULL, lty = 1, lwd = 1))
title(main=paste(i,questo_anno,sep=" "),
line = -2.2)
title(paste("Statistics: min: (", round(min(mensile$conc),0),") - max: (", round(max(mensile$conc),0),") - mean: (", round(mean(mensile$conc),0),") - sd: (", round(sd(mensile$conc),0),")")
,col="black",cex.main = 1.2, line = -3.8, font.main = 1)
lines(mensile$date, mensile$conc, type = "l", lty = 1, col="darkred",lwd = 2)
points(men_MAX$date[1], men_MAX$conc[1], col= "magenta",pch=20)
text(men_MAX$date[1], men_MAX$conc[1], labels = paste("Max (",format(men_MAX$date[1],"%B %d"),")",sep=""),col="magenta",pos=3)
segments(men_MAX$date[1], men_MAX$conc[1], men_MAX$date[1], men_MIN$conc[1]-400, lty = 2, col="black",lwd = 1)
points(men_MIN$date[1], men_MIN$conc[1], col= "blue",pch=20)
text(men_MIN$date[1], men_MIN$conc[1], labels = paste("Min (",format(men_MIN$date[1],"%B %d"),")",sep=""),col="blue",pos=1)
segments(men_MIN$date[1], men_MIN$conc[1], men_MIN$date[1], men_MIN$conc[1]-400, lty = 2, col="black",lwd = 1)
}
}
dev.off()
}
#
# -------------------------------------------------------------------------------------------
## # END PART 3.1 #
###########################################################################################################################
###########################################################################################################################
## # PART 3.2 #
## ______________________________________________________________________________________________________________________##
## Creating statistcs/graphic reports
## SEASONAL GRAPHS
## Cleaning Destination directory
##
## ______________________________________________________________________________________________________________________##
# -------------------------------------------------------------------------------------------
# Cleaning Destination directory
#
FILE_PLOT_S <-list.files(path = PLOT_DIR_S, pattern = paste(s_GAW_ID, inst_type,questo_anno,"SEASONAL_GRAPH_*",sep = "_"),
all.files = FALSE,
full.names = F, recursive = FALSE,
ignore.case = FALSE, include.dirs = F, no.. = FALSE)
LISTA_PLOT_S <-as.character(FILE_PLOT_S)
for(f in LISTA_PLOT_S){
file.remove(paste(PLOT_DIR_S,f,sep = "/"))
}
#
# -------------------------------------------------------------------------------------------
# Defining seasons (quadrimesters)
#
CPC_L02_today_Y$season[CPC_L02_today_Y$monthNum>=1 & CPC_L02_today_Y$monthNum<=3] <- 1
CPC_L02_today_Y$season[CPC_L02_today_Y$monthNum>=4 & CPC_L02_today_Y$monthNum<=6] <- 2
CPC_L02_today_Y$season[CPC_L02_today_Y$monthNum>=7 & CPC_L02_today_Y$monthNum<=9] <- 3
CPC_L02_today_Y$season[CPC_L02_today_Y$monthNum>=10 & CPC_L02_today_Y$monthNum<=12] <- 4
#
# -------------------------------------------------------------------------------------------
# Creating temporary season tables (Level-2)
#
temp_L02$season[as.integer(temp_L02$monthNum)>=1 & as.integer(temp_L02$monthNum)<=3] <- 1
temp_L02$season[as.integer(temp_L02$monthNum)>=4 & as.integer(temp_L02$monthNum)<=6] <- 2
temp_L02$season[as.integer(temp_L02$monthNum)>=7 & as.integer(temp_L02$monthNum)<=9] <- 3
temp_L02$season[as.integer(temp_L02$monthNum)>=10 & as.integer(temp_L02$monthNum)<=12]<- 4
temp_L00$season[as.integer(temp_L00$monthNum)>=1 & as.integer(temp_L00$monthNum)<=3] <- 1
temp_L00$season[as.integer(temp_L00$monthNum)>=4 & as.integer(temp_L00$monthNum)<=6] <- 2
temp_L00$season[as.integer(temp_L00$monthNum)>=7 & as.integer(temp_L00$monthNum)<=9] <- 3
temp_L00$season[as.integer(temp_L00$monthNum)>=10 & as.integer(temp_L00$monthNum)<=12]<- 4
seasons<-c(CPC_L02_today_Y[!duplicated(CPC_L02_today_Y[,c('season')]),]$season)
seasons
# -------------------------------------------------------------------------------------------
# Preparing plotting files
#
PLOT_S_NAME <-paste(s_GAW_ID,"_",inst_type,"_",questo_anno,"_SEASONAL_GRAPH_",gsub("-","",Sys.Date()),sep = "")
PLOT_S_NAME_FULL <-paste (PLOT_DIR_S,paste(PLOT_S_NAME,".png",sep = ""),sep = "/")
png(file=,PLOT_S_NAME_FULL, width = 2480, height = 3508)# width=2100,height=2970,res=300)
#
# -------------------------------------------------------------------------------------------
# Preparing plotting parameters (font size, margins, ...)
#
par(mfrow = c(8,1))
par(ps = 14, cex = 2, cex.main = 4.0,cex.sub=2.2, cex.lab=3.5, cex.axis = 3.2, mai=c(0.6,1.8,0.5,0.5))
#
# -------------------------------------------------------------------------------------------
# Creating the plotting matrix
#
m <- rbind(c(1, 1), c(2, 3), c(4, 4), c(5, 6), c(7, 7), c(8, 9), c(10, 10), c(11, 12))
layout(m)
#
# -------------------------------------------------------------------------------------------
# Creating the plotting matrix
#
for (stg in seasons)
{
if(stg==1){stg_name<-"JAN - FEB - MAR"}
if(stg==2){stg_name<-"APR - MAY - JUN"}
if(stg==3){stg_name<-"JUL - AUG - SEP"}
if(stg==4){stg_name<-"OCT - NOV - DEC"}
print(stg)
print(stg_name)
CPC_L02_stg <-subset(CPC_L02_today_Y, season == stg)
temp_L02_stg <-subset(temp_L02, season == stg)
temp_L00_stg <-subset(temp_L00, season == stg)
OBS_stg_start <-head(format(temp_L02_stg$date,"%d %B %Y"),1)
OBS_stg_end <-tail(format(temp_L02_stg$date,"%d %B %Y"),1)
FAIL_stg <-subset(temp_L02_stg, numflag == 0.999)
FAIL_stg$day <-format(FAIL_stg$date,"%d")
FAIL_unico <-data.frame(FAIL_stg[!duplicated(FAIL_stg[,c('day')]),])
FAIL_DAYS <-nrow(FAIL_unico)
stagionale<-subset(CPC_L02_stg, numflag != 0.999)
stagionale$giorno <- format(stagionale$date,"%d")
This_stg <- c(format(stagionale$date,"%m"))
This_stg_Name <- c(format(stagionale$date,"%B"))
print(paste("ora il ",This_stg_Name[1], FAIL_DAYS))
stagionale$mean <- mean(stagionale$conc)
stagionale$sd <- sd(stagionale$conc)
stg_MIN <- subset(stagionale, conc == min(stagionale$conc))
stg_MAX <- subset(stagionale, conc == max(stagionale$conc))
#
# -------------------------------------------------------------------------------------------
# -------------------------------------------------------------------------------------------
# Plotting conc
#
plot(ylim=c(stg_MIN$conc[1]-700,stg_MAX$conc[1]+500),
stagionale$date, stagionale$conc, type = "h",
mgp = c(7, 3, 0),
xlab = "",ylab =expression(paste("Ntot (#/cm"^{3},") - L02")), col="lightblue", panel.first = grid(nx=0,ny=NULL, lty = 1, lwd = 0.5))
lines(stagionale$date, stagionale$conc, type = "l", lty = 1, col="darkred",lwd = 1)
title(main=paste("Ntot",questo_anno," ",stg_name), line = -4.5)
mtext(paste("Observations from", OBS_stg_start,
" to ", OBS_stg_end,"(",1+(as.integer(tail((CPC_L02_stg$date),1)-head((CPC_L02_stg$date)),1)),"days) - Statistics: ",
" Ntot min: (", round(min(stagionale$conc),0),") - Ntot max: (", round(max(stagionale$conc),0),") - Ntot mean: (", round(mean(stagionale$conc),0),") - Ntot sd: (", round(sd(stagionale$conc),0),")"),
col="black",cex = 1.7, line = -8.0, font.main = 1)
points(stg_MAX$date[1], stg_MAX$conc[1], col= "magenta",pch=20)
segments(stg_MAX$date[1], stg_MAX$conc[1], stg_MAX$date[1], stg_MIN$conc[1]-600, lty = 2, col="black",lwd = 1)
text(stg_MAX$date[1], stg_MIN$conc[1]-500, labels = paste("Max","(",(format(stg_MAX$date[1],"%B %d")),")"),
col="magenta",
pos=1,
cex = 1.6)
points(stg_MIN$date[1], stg_MIN$conc[1], col= "blue",pch=20)
segments(stg_MIN$date[1], stg_MIN$conc[1], stg_MIN$date[1], stg_MIN$conc[1]-600, lty = 2, col="black",lwd = 1)
text(stg_MIN$date[1], stg_MIN$conc[1]-500, labels = paste("Min","(",(format(stg_MIN$date[1],"%B %d")),")"),
col="blue",
pos=1,
cex = 1.6)
#
# -------------------------------------------------------------------------------------------
# -------------------------------------------------------------------------------------------
# Plotting HISTOGRAMS
#
hist(stagionale$conc,xlab="",
ylab="Relative frequency",
main="",
mgp = c(7, 3, 0),
col = "mediumaquamarine",
border="darkred",lwd = 2)
d <- density(stagionale$conc)
plot(d,xlab="",
ylab="Density",
main="",
mgp = c(7, 3, 0),
polygon(d, col="steelblue", border="blue"))
}
dev.off()
# -------------------------------------------------------------------------------------------
## # END PART 3.2 #
###########################################################################################################################
###########################################################################################################################
## # PART 3.3 #
## ______________________________________________________________________________________________________________________##
## Creating statistcs/graphic reports
## ANNUAL GRAPHS
## Cleaning Destination directory
##
## ______________________________________________________________________________________________________________________##
# Cleaning Destination directory
#
FILE_PLOT_Y <-list.files(path = PLOT_DIR_Y, pattern = paste(s_GAW_ID, inst_type,questo_anno,"ANNUAL_GRAPH_*",sep = "_"), all.files = FALSE,
full.names = F, recursive = FALSE,
ignore.case = FALSE, include.dirs = F, no.. = FALSE)
FILE_PLOT_Y
LISTA_PLOT_Y <-as.character(FILE_PLOT_Y)
for(f in LISTA_PLOT_Y) { file.remove(paste(PLOT_DIR_Y,f,sep = "/")) }
#
# -------------------------------------------------------------------------------------------
# Defining statistics
#
CPC_L02_today_Y$mean <-mean(CPC_L02_today_Y$conc)
Y_MIN <-subset(CPC_L02_today_Y, conc == min(CPC_L02_today_Y$conc))
Y_MAX <-subset(CPC_L02_today_Y, conc == max(CPC_L02_today_Y$conc))
OBS_start <-head(format(temp_L00$date,"%d %B %Y"),1)
OBS_end <-tail(format(temp_L00$date,"%d %B %Y"),1)
#
# -------------------------------------------------------------------------------------------
# Defining plotting parameters
#
PLOT_Y_NAME <-paste(s_GAW_ID, inst_type, questo_anno,"ANNUAL_GRAPH_",gsub("-","",Sys.Date()),sep = "_")
PLOT_Y_NAME_FULL <-paste (PLOT_DIR_Y,paste(PLOT_Y_NAME,".png",sep = ""),sep = "/")
png(file=,PLOT_Y_NAME_FULL, width = 2480, height = 3508)
# -------------------------------------------------------------------------------------------
# Preparing plotting parameters (font size, margins, ...)
#
par(mfrow = c(6,1))
par(ps = 14, cex = 2.5, cex.main = 3.5,cex.sub=2.2, cex.lab=3.5, cex.axis = 3.5, mai=c(0.3,1.8,0.5,0.5))
#
# -------------------------------------------------------------------------------------------
# Crating the plotting matrix
#
m <- rbind(c(1, 1), c(2, 2), c(3, 3), c(4, 4), c(5, 5), c(6, 7))
layout(m)
#
# -------------------------------------------------------------------------------------------
# -------------------------------------------------------------------------------------------
# Plotting CONC
#
plot(ylim=c(Y_MIN$conc[1]-300,Y_MAX$conc[1]+300),