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MET_P22_1810.R
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###########################################################################################################################
## Project: NEXTDATA ##
## Parameter: METEO ##
## 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: MET_P22_1810.R ##
## Version Date: December 2018 ##
###########################################################################################################################
# > > > > > > > > > > > > > > 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/METEO/METEO/RAW_DATA_UTC/CALIB'
RAW_DIR = '../naitza/NEXTDATA/PROD/CIMONE/METEO/METEO/RAW_DATA_UTC'
#
# -------- DATA DESTINATION PATH --------------------------------------------------------------# REPLACE THE FOLLOWING PATHS
L0_DIR = '../naitza/NEXTDATA/DISTRIBUTION_DIR/CIMONE/METEO/METEO/LEVEL_0'
L1_DIR = '../naitza/NEXTDATA/DISTRIBUTION_DIR/CIMONE/METEO/METEO/LEVEL_1'
L2_DIR = '../naitza/NEXTDATA/DISTRIBUTION_DIR/CIMONE/METEO/METEO/LEVEL_2'
L0_ANCIL_DIR = '../naitza/NEXTDATA/DISTRIBUTION_DIR/CIMONE/METEO/METEO/LEVEL_0/ANCILLARY'
#
# -------- GRAPH DESTINATION PATH -------------------------------------------------------------# REPLACE THE FOLLOWING PATHS
REP_DIR = '../naitza/NEXTDATA/DISTRIBUTION_DIR/CIMONE/METEO/METEO/REPORT'
REP_GRAPH_DIR = '../naitza/NEXTDATA/DISTRIBUTION_DIR/CIMONE/METEO/METEO/REPORT/DAILY_GRAPH'
PLOT_DIR_M = '../naitza/NEXTDATA/DISTRIBUTION_DIR/CIMONE/METEO/METEO/REPORT/MONTHLY_GRAPH'
PLOT_DIR_S = '../naitza/NEXTDATA/DISTRIBUTION_DIR/CIMONE/METEO/METEO/REPORT/SEASONAL_GRAPH'
PLOT_DIR_Y = '../naitza/NEXTDATA/DISTRIBUTION_DIR/CIMONE/METEO/METEO/REPORT/ANNUAL_GRAPH'
PLOT_DIR_Y_PDF = '../naitza/NEXTDATA/DISTRIBUTION_DIR/CIMONE/METEO/METEO/REPORT/ANNUAL_GRAPH/PDF'
PLOT_DIR_T = '../naitza/NEXTDATA/DISTRIBUTION_DIR/CIMONE/METEO/METEO/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 <- "METEO" # 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)
#
## # 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)
#
# -------------------------------------------------------------------------------------------
#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$date, "%m")
#
# # -------------------------------------------------------------------------------------------
# # Reading Level-1
# #
# FILE_L1 <-list.files(path = L1_DIR, pattern = glob2rx(paste(s_code,".",questo_anno,"*",sep = "")),
# all.files = FALSE,
# full.names = F, recursive = FALSE,
# ignore.case = FALSE, include.dirs = F, no.. = FALSE)
# EBAS_L1_FILENAME <-as.character(FILE_L1[1])
# EBAS_L1_FILENAME
# # -------------------------------------------------------------------------------------------
# #Reading header lines of Level-1 Data sheet
# #
# L1_n_lines <- as.integer(unlist(strsplit(readLines(paste(L1_DIR,EBAS_L1_FILENAME,sep = "/"), n=1), " "))[1])
# L1_n_lines
# #
# # -------------------------------------------------------------------------------------------
# # Creating temporary data table of Level-1
# #
# temp_L01 <-read.table(paste(L1_DIR,EBAS_L1_FILENAME,sep = "/"),skip = L1_n_lines-1,header = T)
# #
# # -------------------------------------------------------------------------------------------
# #Converting of JD values to date
# #
# temp_L01$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$category)
#
# METEO_L01_today_Y <- subset(temp_L01, nf_validity == "V")
# -------------------------------------------------------------------------------------------
# Reading Level-2
# Creating temporary data table of Level-2
#
FILE_L2 <-list.files(path = L2_DIR, pattern = glob2rx(paste(s_code,".",questo_anno,"*",sep = "")), all.files = FALSE,
full.names = F, recursive = FALSE,
ignore.case = FALSE, include.dirs = F, no.. = FALSE)
EBAS_L2_FILENAME <-as.character(FILE_L2[1])
EBAS_L2_FILENAME
# -------------------------------------------------------------------------------------------
#Reading header lines of Level-2 Data sheet
#
L2_n_lines <- as.integer(unlist(strsplit(readLines(paste(L2_DIR,EBAS_L2_FILENAME,sep = "/"), n=1), " "))[1])
L2_n_lines
#
# -------------------------------------------------------------------------------------------
# Creating temporary data table of Level-2
#
temp_L02 <-read.table(paste(L2_DIR,EBAS_L2_FILENAME,sep = "/"),skip = L2_n_lines-1, header = T)
#
# -------------------------------------------------------------------------------------------
# Creating a subset over L02 data
#
temp_L02 <- subset(temp_L02, temp_L02$start_time < strptime(as.POSIXct(Sys.Date()), "%Y-%m-%d %H:%M")$yday)
#
names(temp_L02)[3] <- "ws"
names(temp_L02)[4] <- "flag_ws"
names(temp_L02)[5] <- "wd"
names(temp_L02)[6] <- "flag_wd"
names(temp_L02)[7] <- "t"
names(temp_L02)[8] <- "flag_t"
names(temp_L02)[9] <- "rh"
names(temp_L02)[10] <- "flag_rh"
names(temp_L02)[11] <- "p"
names(temp_L02)[12] <- "flag_p"
names(temp_L02)[13] <- "rad"
names(temp_L02)[14] <- "flag_rad"
#
# -------------------------------------------------------------------------------------------
# Converting JD values to date
#
temp_L02$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$month <-format(temp_L02$date, "%B")
temp_L02$monthNum <-format(temp_L02$date, "%m")
print(head(temp_L02, 3))
#
# -------------------------------------------------------------------------------------------
# Subsetting dataset by WS
#
ws_FAIL_today <- subset(temp_L02, flag_ws > 0.900)
ws_TFAIL <- subset(ws_FAIL_today, select=c("month","day","flag_ws"))
ws_mesi_FAIL <- data.frame(ws_TFAIL[!duplicated(ws_TFAIL[1:2]),])
ws_mesi_FAIL_COUNT <- data.frame(ws_mesi_FAIL[!duplicated(ws_mesi_FAIL[1]),],count(ws_mesi_FAIL,"month"))
if (nrow(ws_mesi_FAIL) > 0){
ws_mesi_FAIL_COUNT$print <-paste(ws_mesi_FAIL_COUNT$month," (",ws_mesi_FAIL_COUNT$freq," gg)",sep = "")
ws_Somma_giorni_FAIL <-sum(ws_mesi_FAIL_COUNT$freq)
}
if (nrow(ws_mesi_FAIL) == 0){}
ws_L02_today_Y <- subset(temp_L02, flag_ws < 0.900)
ws_unico <-c (ws_L02_today_Y[!duplicated(ws_L02_today_Y[,c('month')]),]$month)
#
# -------------------------------------------------------------------------------------------
# Subsetting dataset by WD
#
wd_FAIL_today <- subset(temp_L02, flag_wd > 0.900)
wd_TFAIL <- subset(wd_FAIL_today, select=c("month","day","flag_wd"))
wd_mesi_FAIL <- data.frame(wd_TFAIL[!duplicated(wd_TFAIL[1:2]),])
wd_mesi_FAIL_COUNT <- data.frame(wd_mesi_FAIL[!duplicated(wd_mesi_FAIL[1]),],count(wd_mesi_FAIL,"month"))
if (nrow(wd_mesi_FAIL) > 0){
wd_mesi_FAIL_COUNT$print <-paste(wd_mesi_FAIL_COUNT$month," (",wd_mesi_FAIL_COUNT$freq," gg)",sep = "")
wd_Somma_giorni_FAIL <-sum(wd_mesi_FAIL_COUNT$freq)
}
if (nrow(wd_mesi_FAIL) == 0){}
wd_L02_today_Y <- subset(temp_L02, flag_wd < 0.900)
wd_unico <-c (wd_L02_today_Y[!duplicated(wd_L02_today_Y[,c('month')]),]$month)
#
# -------------------------------------------------------------------------------------------
# Subsetting dataset by T
#
t_FAIL_today <- subset(temp_L02, flag_t > 0.900)
t_TFAIL <- subset(t_FAIL_today, select=c("month","day","flag_t"))
t_mesi_FAIL <- data.frame(t_TFAIL[!duplicated(t_TFAIL[1:2]),])
t_mesi_FAIL_COUNT <- data.frame(t_mesi_FAIL[!duplicated(t_mesi_FAIL[1]),],count(t_mesi_FAIL,"month"))
if (nrow(t_mesi_FAIL) > 0){
t_mesi_FAIL_COUNT$print <-paste(t_mesi_FAIL_COUNT$month," (",t_mesi_FAIL_COUNT$freq," gg)",sep = "")
t_Somma_giorni_FAIL <-sum(t_mesi_FAIL_COUNT$freq)
}
if (nrow(t_mesi_FAIL) == 0){}
t_L02_today_Y <- subset(temp_L02, flag_t < 0.900)
t_unico <-c (t_L02_today_Y[!duplicated(t_L02_today_Y[,c('month')]),]$month)
#
# -------------------------------------------------------------------------------------------
# Subsetting dataset by RH
#
rh_FAIL_today <- subset(temp_L02, flag_rh > 0.900)
rh_TFAIL <- subset(rh_FAIL_today, select=c("month","day","flag_rh"))
rh_mesi_FAIL <- data.frame(rh_TFAIL[!duplicated(rh_TFAIL[1:2]),])
rh_mesi_FAIL_COUNT <- data.frame(rh_mesi_FAIL[!duplicated(rh_mesi_FAIL[1]),],count(rh_mesi_FAIL,"month"))
if (nrow(rh_mesi_FAIL) > 0){
rh_mesi_FAIL_COUNT$print <-paste(rh_mesi_FAIL_COUNT$month," (",rh_mesi_FAIL_COUNT$freq," gg)",sep = "")
rh_Somma_giorni_FAIL <-sum(rh_mesi_FAIL_COUNT$freq)
}
if (nrow(rh_mesi_FAIL) == 0){}
rh_L02_today_Y <- subset(temp_L02, flag_rh < 0.900)
rh_unico <-c (rh_L02_today_Y[!duplicated(rh_L02_today_Y[,c('month')]),]$month)
#
# -------------------------------------------------------------------------------------------
# Subsetting dataset by P
#
p_FAIL_today <- subset(temp_L02, flag_p > 0.900)
p_TFAIL <- subset(p_FAIL_today, select=c("month","day","flag_p"))
p_mesi_FAIL <- data.frame(p_TFAIL[!duplicated(p_TFAIL[1:2]),])
p_mesi_FAIL_COUNT <- data.frame(p_mesi_FAIL[!duplicated(p_mesi_FAIL[1]),],count(p_mesi_FAIL,"month"))
if (nrow(p_mesi_FAIL) > 0){
p_mesi_FAIL_COUNT$print <-paste(p_mesi_FAIL_COUNT$month," (",p_mesi_FAIL_COUNT$freq," gg)",sep = "")
p_Somma_giorni_FAIL <-sum(p_mesi_FAIL_COUNT$freq)
}
if (nrow(p_mesi_FAIL) == 0){}
p_L02_today_Y <- subset(temp_L02, flag_p < 0.900)
p_unico <-c (p_L02_today_Y[!duplicated(p_L02_today_Y[,c('month')]),]$month)
#
# -------------------------------------------------------------------------------------------
# Subsetting dataset by RAD
#
rad_FAIL_today <- subset(temp_L02, flag_rad > 0.900)
rad_TFAIL <- subset(rad_FAIL_today, select=c("month","day","flag_rad"))
rad_mesi_FAIL <- data.frame(rad_TFAIL[!duplicated(rad_TFAIL[1:2]),])
rad_mesi_FAIL_COUNT <- data.frame(rad_mesi_FAIL[!duplicated(rad_mesi_FAIL[1]),],count(rad_mesi_FAIL,"month"))
if (nrow(rad_mesi_FAIL) > 0){
rad_mesi_FAIL_COUNT$print <-paste(rad_mesi_FAIL_COUNT$month," (",rad_mesi_FAIL_COUNT$freq," gg)",sep = "")
rad_Somma_giorni_FAIL <-sum(rad_mesi_FAIL_COUNT$freq)
}
if (nrow(rad_mesi_FAIL) == 0){}
rad_L02_today_Y <- subset(temp_L02, flag_rad < 0.900)
rad_unico <-c (rad_L02_today_Y[!duplicated(rad_L02_today_Y[,c('month')]),]$month)
#
# -------------------------------------------------------------------------------------------
#
## # END PART 2.0 #
###########################################################################################################################
###########################################################################################################################
## # PART 3.0 #
## ______________________________________________________________________________________________________________________##
## Creating statistcs/graphic reports
## MONTHLY GRAPHS
## Cleaning Destination directory
##
## ______________________________________________________________________________________________________________________##
# Subsetting data by month
#
ws_unico_M <-c(ws_L02_today_Y [!duplicated(ws_L02_today_Y [,c('monthNum')]),]$monthNum)
wd_unico_M <-c(wd_L02_today_Y [!duplicated(wd_L02_today_Y [,c('monthNum')]),]$monthNum)
t_unico_M <-c(t_L02_today_Y [!duplicated(t_L02_today_Y [,c('monthNum')]),]$monthNum)
rh_unico_M <-c(rh_L02_today_Y [!duplicated(rh_L02_today_Y [,c('monthNum')]),]$monthNum)
p_unico_M <-c(p_L02_today_Y [!duplicated(p_L02_today_Y [,c('monthNum')]),]$monthNum)
rad_unico_M <-c(rad_L02_today_Y[!duplicated(rad_L02_today_Y[,c('monthNum')]),]$monthNum)
for (qm in na.omit(wd_unico_M))
{print(qm)
#
# -------------------------------------------------------------------------------------------
# Defining month
#
temp_L02_ThisMonth <-subset(temp_L02, monthNum==qm)
#
# -------------------------------------------------------------------------------------------
# Subsetting dataset by monthly values of WS
#
ws_L02_ThisMonth <-subset(ws_L02_today_Y, monthNum==qm)
ws_temp_L02_ThisMonth <-subset(temp_L02, monthNum==qm)
OBS_Month_start <-head(format(ws_temp_L02_ThisMonth$date,"%d %B %Y"),1)
OBS_Month_end <-tail(format(ws_temp_L02_ThisMonth$date,"%d %B %Y"),1)
ws_FAIL_ThisMonth <-subset(ws_temp_L02_ThisMonth, flag_ws >0.900)
ws_FAIL_ThisMonth$day <-format(ws_FAIL_ThisMonth$date,"%d")
ws_FAIL_unico <-data.frame(ws_FAIL_ThisMonth[!duplicated(ws_FAIL_ThisMonth[,c('day')]),])
ws_FAIL_DAYS <-nrow(ws_FAIL_unico)
ws_mensile <-subset(ws_L02_ThisMonth, flag_ws<0.900)
ws_mensile$giorno <-format(ws_mensile$date,"%d")
ws_This_Month <-format(ws_mensile$date,"%m")[1]
ws_This_Month_Name <-format(ws_mensile$date,"%B")[1]
ws_men_MIN <-subset(ws_mensile, ws == min(ws_mensile$ws))
ws_men_MAX <-subset(ws_mensile, ws == max(ws_mensile$ws))
print(paste("ws ",ws_This_Month_Name[1], ws_FAIL_DAYS))
#
# -------------------------------------------------------------------------------------------
# Subsetting dataset by monthly values of WD
#
wd_L02_ThisMonth <-subset(wd_L02_today_Y, monthNum==qm)
wd_temp_L02_ThisMonth <-subset(temp_L02, monthNum==qm)
OBS_Month_start <-head(format(wd_temp_L02_ThisMonth$date,"%d %B %Y"),1)
OBS_Month_end <-tail(format(wd_temp_L02_ThisMonth$date,"%d %B %Y"),1)
wd_FAIL_ThisMonth <-subset(wd_temp_L02_ThisMonth, flag_wd>0.900)
wd_FAIL_ThisMonth$day <-format(wd_FAIL_ThisMonth$date,"%d")
wd_FAIL_unico <-data.frame(wd_FAIL_ThisMonth[!duplicated(wd_FAIL_ThisMonth[,c('day')]),])
wd_FAIL_DAYS <-nrow(wd_FAIL_unico)
wd_mensile <-subset(wd_L02_ThisMonth, flag_wd<0.900)
wd_mensile$giorno <-format(wd_mensile$date,"%d")
wd_This_Month <-format(wd_mensile$date,"%m")[1]
wd_This_Month_Name <-format(wd_mensile$date,"%B")[1]
wd_men_MIN <-subset(wd_mensile, wd == min(ws_mensile$wd))
wd_men_MAX <-subset(wd_mensile, wd == max(ws_mensile$wd))
print(paste("wd ",wd_This_Month_Name[1], wd_FAIL_DAYS))
#
# -------------------------------------------------------------------------------------------
# Subsetting dataset by monthly values of T
#
t_L02_ThisMonth <-subset(t_L02_today_Y, monthNum==qm)
t_temp_L02_ThisMonth <-subset(temp_L02, monthNum==qm)
OBS_Month_start <-head(format(t_temp_L02_ThisMonth$date,"%d %B %Y"),1)
OBS_Month_end <-tail(format(t_temp_L02_ThisMonth$date,"%d %B %Y"),1)
t_FAIL_ThisMonth <-subset(t_temp_L02_ThisMonth, flag_t>0.900)
t_FAIL_ThisMonth$day <-format(t_FAIL_ThisMonth$date,"%d")
t_FAIL_unico <-data.frame(t_FAIL_ThisMonth[!duplicated(t_FAIL_ThisMonth[,c('day')]),])
t_FAIL_DAYS <-nrow(t_FAIL_unico)
t_mensile <-subset(t_L02_ThisMonth, flag_t<0.900)
t_mensile$giorno <-format(t_mensile$date,"%d")
t_This_Month <-format(t_mensile$date,"%m")[1]
t_This_Month_Name <-format(t_mensile$date,"%B")[1]
t_men_MIN <-subset(t_mensile, t == min(t_mensile$t))
t_men_MAX <-subset(t_mensile, t == max(t_mensile$t))
print(paste("t ",t_This_Month_Name[1], t_FAIL_DAYS))
#
# -------------------------------------------------------------------------------------------
# Subsetting dataset by monthly values of RH
#
rh_L02_ThisMonth <-subset(rh_L02_today_Y, monthNum==qm)
rh_temp_L02_ThisMonth <-subset(temp_L02, monthNum==qm)
OBS_Month_start <-head(format(rh_temp_L02_ThisMonth$date,"%d %B %Y"),1)
OBS_Month_end <-tail(format(rh_temp_L02_ThisMonth$date,"%d %B %Y"),1)
rh_FAIL_ThisMonth <-subset(rh_temp_L02_ThisMonth, flag_rh>0.900)
rh_FAIL_ThisMonth$day <-format(rh_FAIL_ThisMonth$date,"%d")
rh_FAIL_unico <-data.frame(rh_FAIL_ThisMonth[!duplicated(rh_FAIL_ThisMonth[,c('day')]),])
rh_FAIL_DAYS <-nrow(rh_FAIL_unico)
rh_mensile <-subset(rh_L02_ThisMonth, flag_rh<0.900)
rh_mensile$giorno <-format(rh_mensile$date,"%d")
rh_This_Month <-format(rh_mensile$date,"%m")[1]
rh_This_Month_Name <-format(rh_mensile$date,"%B")[1]
rh_men_MIN <-subset(rh_mensile, rh == min(rh_mensile$rh))
rh_men_MAX <-subset(rh_mensile, rh == max(rh_mensile$rh))
print(paste("rh ",rh_This_Month_Name[1], rh_FAIL_DAYS))
#
# -------------------------------------------------------------------------------------------
# Subsetting dataset by monthly values of P
#
p_L02_ThisMonth <-subset(p_L02_today_Y, monthNum==qm)
p_temp_L02_ThisMonth <-subset(temp_L02, monthNum==qm)
OBS_Month_start <-head(format(p_temp_L02_ThisMonth$date,"%d %B %Y"),1)
OBS_Month_end <-tail(format(p_temp_L02_ThisMonth$date,"%d %B %Y"),1)
p_FAIL_ThisMonth <-subset(p_temp_L02_ThisMonth, flag_p>0.900)
p_FAIL_ThisMonth$day <-format(p_FAIL_ThisMonth$date,"%d")
p_FAIL_unico <-data.frame(p_FAIL_ThisMonth[!duplicated(p_FAIL_ThisMonth[,c('day')]),])
p_FAIL_DAYS <-nrow(p_FAIL_unico)
p_mensile <-subset(p_L02_ThisMonth, flag_p<0.900)
p_mensile$giorno <-format(p_mensile$date,"%d")
p_This_Month <-format(p_mensile$date,"%m")[1]
p_This_Month_Name <-format(p_mensile$date,"%B")[1]
p_men_MIN <-subset(p_mensile, p == min(p_mensile$p))
p_men_MAX <-subset(p_mensile, p == max(p_mensile$p))
print(paste("p ",p_This_Month_Name[1], p_FAIL_DAYS))
#
# -------------------------------------------------------------------------------------------
# Subsetting dataset by monthly values of RAD
#
rad_L02_ThisMonth <-subset(rad_L02_today_Y, monthNum==qm)
rad_temp_L02_ThisMonth <-subset(temp_L02, monthNum==qm)
OBS_Month_start <-head(format(rad_temp_L02_ThisMonth$date,"%d %B %Y"),1)
OBS_Month_end <-tail(format(rad_temp_L02_ThisMonth$date,"%d %B %Y"),1)
rad_FAIL_ThisMonth <-subset(rad_temp_L02_ThisMonth, flag_rad>0.900)
rad_FAIL_ThisMonth$day <-format(rad_FAIL_ThisMonth$date,"%d")
rad_FAIL_unico <-data.frame(rad_FAIL_ThisMonth[!duplicated(rad_FAIL_ThisMonth[,c('day')]),])
rad_FAIL_DAYS <-nrow(rad_FAIL_unico)
rad_mensile <-subset(rad_L02_ThisMonth, flag_rad<0.900)
rad_mensile$giorno <-format(rad_mensile$date,"%d")
rad_This_Month <-format(rad_mensile$date,"%m")[1]
rad_This_Month_Name <-format(rad_mensile$date,"%B")[1]
rad_men_MIN <-subset(rad_mensile, rad == min(rad_mensile$rad))
rad_men_MAX <-subset(rad_mensile, rad == max(rad_mensile$rad))
print(paste("rad ",rad_This_Month_Name[1], rad_FAIL_DAYS))
#
# -------------------------------------------------------------------------------------------
# Cleaning Destination directory
#
FILE_PLOT_M<-list.files(path = PLOT_DIR_M, pattern = paste(s_GAW_ID,inst_type,questo_anno,ws_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, ws_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(7,1)) # par(mfrow = c(8,1))
par(ps = 14, cex = 2, cex.main = 3.5,cex.sub=2.2, cex.lab=2.8, cex.axis = 2.2, 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, 6), c(7, 8))
layout(m)
#
# -------------------------------------------------------------------------------------------
# -------------------------------------------------------------------------------------------
# Plotting WS
#
if(nrow(ws_mensile) > 0 )
{
plot(ylim=c(-0.1,max(ws_mensile$ws)+0.2),
xlim = c(min(temp_L02_ThisMonth$date),max(temp_L02_ThisMonth$date)),
mgp = c(8, 4, 0),
ws_L02_ThisMonth$date, ws_mensile$ws, type = "h",
xlab = "",ylab =("WS (m/s) - L02"), col="darkseagreen1", panel.first = grid(nx=0,ny=NULL, lty = 1, lwd = 1))
title(paste("Wind speed - L02 -",questo_anno,ws_This_Month_Name), line = -3)
lines(ws_L02_ThisMonth$date, ws_mensile$ws, type = "l", lty = 1, col="darkred",lwd = 2)
points(ws_men_MAX$date[1], ws_men_MAX$ws[1], col= "magenta",pch=20)
text(ws_men_MAX$date[1], ws_men_MIN$ws[1], labels = paste("Max (", format(ws_men_MAX$date[1],"%B %d"), ")", sep=""),col="magenta",pos=1,cex = 1.8)
segments(ws_men_MAX$date[1], ws_men_MAX$ws[1], ws_men_MAX$date[1], ws_men_MIN$ws[1]-0.02, lty = 2, col="black",lwd = 1)
points(ws_men_MIN$date[1], ws_men_MIN$ws[1], col= "blue",pch=20)
text(ws_men_MIN$date[1], ws_men_MIN$ws[1], labels = paste("Min (", format(ws_men_MIN$date[1],"%B %d"), ")", sep =""),col="blue",pos=1,cex = 1.8)
segments(ws_men_MIN$date[1], ws_men_MIN$ws[1], ws_men_MIN$date[1], ws_men_MIN$ws[1]-0.02, lty = 2, col="black",lwd = 1)
}
if(nrow(ws_mensile) == 0 )
{
temp_L02_ThisMonth$rad[temp_L02_ThisMonth$rad > 900] <- 0
plot(ylim = c(-30,100),
xlim = c(min(temp_L02_ThisMonth$date),max(temp_L02_ThisMonth$date)),
temp_L02_ThisMonth$date, temp_L02_ThisMonth$rad, type = "l",
xlab = "",ylab =("WS (m/s) - L02"), col="goldenrod", panel.first = grid(nx=0,ny=NULL, lty = 1, lwd = 1))
title(paste("Wind speed - L02 - data for this month are absent"), line = -3)
title(paste("No data"), line = -28, cex = 0.8)
}
#
#
# -------------------------------------------------------------------------------------------
# -------------------------------------------------------------------------------------------
# Plotting WD
#
if(nrow(wd_mensile) > 0 )
{
plot(ylim=c(-15,400),
xlim = c(min(temp_L02_ThisMonth$date),max(temp_L02_ThisMonth$date)),
mgp = c(8, 4, 0),
wd_mensile$date, wd_mensile$wd, type = "h",
xlab = "",ylab =("WD (deg) - L02"), col="paleturquoise", panel.first = grid(nx=0,ny=NULL, lty = 1, lwd = 1))
title(paste("Wind direction - L02",questo_anno,wd_This_Month_Name), line = -3)
lines(wd_mensile$date, wd_mensile$wd, type = "l", lty = 1, col="darkblue",lwd = 2)
segments(head(wd_mensile$date), 360, tail(wd_mensile$date), 360, lty = 1, col="midnightblue",lwd = 0.5)
text(wd_mensile$date[1],368, labels = c("360°"),col="midnightblue",cex = 1.8)
segments(head(wd_mensile$date), 270, tail(wd_mensile$date), 270, lty = 1, col="dodgerblue3",lwd = 0.5)
text(wd_mensile$date[1],278, labels = c("270°"),col="dodgerblue3",cex = 1.8)
segments(head(wd_mensile$date), 180, tail(wd_mensile$date), 180, lty = 1, col="steelblue4",lwd = 0.5)
text(wd_mensile$date[1],188, labels = c("180°"),col="steelblue4",cex = 1.8)
segments(head(wd_mensile$date), 90, tail(wd_mensile$date), 90, lty = 1, col="lightskyblue3",lwd = 0.5)
text(wd_mensile$date[1],98, labels = c("90°"),col="lightskyblue3",cex = 1.8)
}
if(nrow(wd_mensile) == 0 )
{
temp_L02_ThisMonth$rad[temp_L02_ThisMonth$rad > 900] <- 0
plot(ylim = c(-30,100),
xlim = c(min(temp_L02_ThisMonth$date),max(temp_L02_ThisMonth$date)),
temp_L02_ThisMonth$date, temp_L02_ThisMonth$rad, type = "l",
xlab = "",ylab =("WD (deg) - L02"), col="goldenrod", panel.first = grid(nx=0,ny=NULL, lty = 1, lwd = 1))
title(paste("Wind direction - L02 - data for this month are absent"), line = -3)
title(paste("No data"), line = -28, cex = 0.8)
}
#
# -------------------------------------------------------------------------------------------
# -------------------------------------------------------------------------------------------
# Plotting T
#
if(nrow(t_mensile) > 0 )
{
plot(ylim=c(min(t_mensile$t)-1,max(t_mensile$t)+1),
xlim = c(min(temp_L02_ThisMonth$date),max(temp_L02_ThisMonth$date)),
mgp = c(8, 4, 0),
t_L02_ThisMonth$date, t_mensile$t, type = "h",
xlab = "",ylab =("T (°C) - L02"), col="darksalmon", panel.first = grid(nx=0,ny=NULL, lty = 1, lwd = 1))
title(paste("Temperature - L02 -",questo_anno,t_This_Month_Name), line = -3)
lines(t_L02_ThisMonth$date, t_mensile$t, type = "l", lty = 1, col="darkred",lwd = 2)
points(t_men_MAX$date[1], t_men_MAX$t[1], col= "magenta",pch=20)
text(t_men_MAX$date[1], t_men_MIN$t[1], labels = paste("Max (", format(t_men_MAX$date[1],"%B %d"), ")", sep=""),col="magenta",pos=1,cex = 1.8)
segments(t_men_MAX$date[1], t_men_MAX$t[1], t_men_MAX$date[1], t_men_MIN$t[1]-0.02, lty = 2, col="black",lwd = 1)
points(t_men_MIN$date[1], t_men_MIN$t[1], col= "blue",pch=20)
text(t_men_MIN$date[1], t_men_MIN$t[1], labels = paste("Min (", format(t_men_MIN$date[1],"%B %d"), ")", sep=""),col="blue",pos=1,cex = 1.8)
segments(t_men_MIN$date[1], t_men_MIN$t[1], t_men_MIN$date[1], t_men_MIN$t[1]-0.02, lty = 2, col="black",lwd = 1)
segments(head(t_mensile$date), 0, tail(t_mensile$date), 0, lty = 1, col="midnightblue",lwd = 1)
text(t_mensile$date[1],0.5, labels = c("0°C"),col="midnightblue",cex = 1.8)
}
if(nrow(t_mensile) == 0 )
{
temp_L02_ThisMonth$rad[temp_L02_ThisMonth$rad > 900] <- 0
plot(ylim = c(-30,100),
xlim = c(min(temp_L02_ThisMonth$date),max(temp_L02_ThisMonth$date)),
temp_L02_ThisMonth$date, temp_L02_ThisMonth$rad, type = "l",
xlab = "",ylab =("T (°C) - L02"), col="goldenrod", panel.first = grid(nx=0,ny=NULL, lty = 1, lwd = 1))
title(paste("Temperature - L02 - data for this month are absent"), line = -3)
title(paste("No data"), line = -28, cex = 0.8)
}
#
# -------------------------------------------------------------------------------------------
# -------------------------------------------------------------------------------------------
# Plotting RH
#
if(nrow(rh_mensile) > 0 )
{
plot(ylim=c(min(rh_mensile$rh)-10,140),
xlim = c(min(temp_L02_ThisMonth$date),max(temp_L02_ThisMonth$date)),
mgp = c(8, 4, 0),
rh_L02_ThisMonth$date, rh_mensile$rh, type = "h",
xlab = "",ylab =("RH (%) - L02"), col="slategray2", panel.first = grid(nx=0,ny=NULL, lty = 1, lwd = 1))
title(paste("Relative humidity - L02 -",questo_anno,rh_This_Month_Name), line = -3)
lines(rh_L02_ThisMonth$date, rh_mensile$rh, type = "l", lty = 1, col="darkred",lwd = 2)
points(rh_men_MAX$date[1], rh_men_MAX$rh[1], col= "magenta",pch=20)
text(rh_men_MAX$date[1], rh_men_MIN$rh[1], labels = paste("Max (", format(rh_men_MAX$date[1],"%B %d"), ")", sep=""),col="magenta",pos=1,cex = 1.8)
segments(rh_men_MAX$date[1], rh_men_MAX$rh[1], rh_men_MAX$date[1], rh_men_MIN$rh[1]-0.02, lty = 2, col="black",lwd = 1)
points(rh_men_MIN$date[1], rh_men_MIN$rh[1], col= "blue",pch=20)
text(rh_men_MIN$date[1], rh_men_MIN$rh[1], labels = paste("Min (", format(rh_men_MIN$date[1],"%B %d"), ")", sep=""),col="blue",pos=1,cex = 1.8)
segments(rh_men_MIN$date[1], rh_men_MIN$rh[1], rh_men_MIN$date[1], rh_men_MIN$rh[1]-0.02, lty = 2, col="black",lwd = 1)
}
if(nrow(rh_mensile) == 0 )
{
temp_L02_ThisMonth$rad[temp_L02_ThisMonth$rad > 900] <- 0
plot(ylim = c(-30,100),
xlim = c(min(temp_L02_ThisMonth$date),max(temp_L02_ThisMonth$date)),
temp_L02_ThisMonth$date, temp_L02_ThisMonth$rad, type = "l",
xlab = "",ylab =("RH (%%) - L02"), col="goldenrod", panel.first = grid(nx=0,ny=NULL, lty = 1, lwd = 1))
title(paste("Relative humidity - L02 - data for this month are absent"), line = -3)
title(paste("No data"), line = -28, cex = 0.8)
}
#
# -------------------------------------------------------------------------------------------
# -------------------------------------------------------------------------------------------
# Plotting P
#
if(nrow(p_mensile) > 0 )
{
plot(ylim=c(min(p_mensile$p)-7,max(p_mensile$p)+7),
xlim = c(min(temp_L02_ThisMonth$date),max(temp_L02_ThisMonth$date)),
mgp = c(8, 4, 0),
p_L02_ThisMonth$date, p_mensile$p, type = "h",
xlab = "",ylab =("P (hPa) - L02"), col="thistle3", panel.first = grid(nx=0,ny=NULL, lty = 1, lwd = 1))
title(paste("Pressure - L02 -",questo_anno,p_This_Month_Name), line = -3)
lines(p_L02_ThisMonth$date, p_mensile$p, type = "l", lty = 1, col="darkred",lwd = 2)
points(p_men_MAX$date[1], p_men_MAX$p[1], col= "magenta",pch=20)
text(p_men_MAX$date[1], p_men_MIN$p[1], labels = paste("Max (", format(p_men_MAX$date[1],"%B %d"), ")", sep=""),col="magenta",pos=1,cex = 1.8)
segments(p_men_MAX$date[1], p_men_MAX$p[1], p_men_MAX$date[1], p_men_MIN$p[1]-0.02, lty = 2, col="black",lwd = 1)
points(p_men_MIN$date[1], p_men_MIN$p[1], col= "blue",pch=20)
text(p_men_MIN$date[1], p_men_MIN$p[1], labels = paste("Min (", format(p_men_MIN$date[1],"%B %d"), ")", sep=""),col="blue",pos=1,cex = 1.8)
segments(p_men_MIN$date[1], p_men_MIN$p[1], p_men_MIN$date[1], p_men_MIN$p[1]-0.02, lty = 2, col="black",lwd = 1)
}
if(nrow(p_mensile) == 0 )
{
temp_L02_ThisMonth$rad[temp_L02_ThisMonth$rad > 900] <- 0
plot(ylim = c(-30,100),
xlim = c(min(temp_L02_ThisMonth$date),max(temp_L02_ThisMonth$date)),
temp_L02_ThisMonth$date, temp_L02_ThisMonth$rad, type = "l",
xlab = "",ylab =("P (hPa) - L02"), col="goldenrod", panel.first = grid(nx=0,ny=NULL, lty = 1, lwd = 1))
title(paste("Pressure - L02 - data for this month are absent"), line = -3)
title(paste("No data"), line = -28, cex = 0.8)
}
#
# -------------------------------------------------------------------------------------------
# -------------------------------------------------------------------------------------------
# Plotting RAD
#
if(nrow(rad_mensile) > 0 )
{
plot(ylim = c(-30,max(rad_mensile$rad)[1]+20),
xlim = c(min(temp_L02_ThisMonth$date),max(temp_L02_ThisMonth$date)),
mgp = c(8, 4, 0),
rad_L02_ThisMonth$date, rad_mensile$rad, type = "h",
xlab = "",ylab =expression(paste("RAD (W/m"^{2},") - L02")), col="goldenrod", panel.first = grid(nx=0,ny=NULL, lty = 1, lwd = 1))
title(paste("Global radiation - L02 -",questo_anno,rad_This_Month_Name), line = -3)
lines(rad_L02_ThisMonth$date, rad_mensile$rad, type = "l", lty = 1, col="darkred",lwd = 2)
points(rad_men_MAX$date[1], rad_men_MAX$rad[1], col= "magenta",pch=20)
text(rad_men_MAX$date[1], rad_men_MIN$rad[1], labels = paste("Max (", format(rad_men_MAX$date[1],"%B %d"), ")", sep=""),col="magenta",pos=1,cex = 1.8)
segments(rad_men_MAX$date[1], rad_men_MAX$rad[1], rad_men_MAX$date[1], rad_men_MIN$rad[1]-0.02, lty = 2, col="black",lwd = 1)
points(rad_men_MIN$date[1], rad_men_MIN$rad[1], col= "blue",pch=20)
text(rad_men_MIN$date[1], rad_men_MIN$rad[1], labels = paste("Min (", format(p_men_MIN$date[1],"%B %d"), ")", sep=""),col="blue",pos=1,cex = 1.8)
segments(rad_men_MIN$date[1], rad_men_MIN$rad[1], rad_men_MIN$date[1], rad_men_MIN$rad[1]-0.02, lty = 2, col="black",lwd = 1)
}
if(nrow(rad_mensile) == 0 )
{
temp_L02_ThisMonth$rad[temp_L02_ThisMonth$rad > 900] <- 0
plot(ylim = c(-30,100),
xlim = c(min(temp_L02_ThisMonth$date),max(temp_L02_ThisMonth$date)),
temp_L02_ThisMonth$date, temp_L02_ThisMonth$rad, type = "l",
xlab = "",ylab =expression(paste("RAD (W/m"^{2},") - L02")), col="goldenrod", panel.first = grid(nx=0,ny=NULL, lty = 1, lwd = 1))
title(paste("Global radiation - L02 - data for this month are absent"), line = -3,cex = 1.8)
title(paste("No data"), line = -28, cex = 0.8)
}
#
# -------------------------------------------------------------------------------------------
# -------------------------------------------------------------------------------------------
# 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," - ",ws_This_Month_Name," ",questo_anno),
cex = 3.1, col = "darkred",pos = 4)
text(x = -0.005, y = 0.37, paste(" Observations from ", OBS_Month_start," to ", OBS_Month_end,
"\n",
"(Days of observation: ", 1+(as.integer(tail((ws_mensile$date),1)-head((ws_mensile$date)),1)),")","\n","\n",
"WS min: (", round(min(ws_mensile$ws),1),") - WS max: (", round(max(ws_mensile$ws),1),") - WS mean: (", round(mean(ws_mensile$ws),1),") - WS sd: (", round(sd(ws_mensile$ws),1),")","\n",
"WS percentile: 5th: (",round(quantile(ws_mensile$ws, probs = c(0.05)),digits=1),")",
" - 25th: (",round(quantile(ws_mensile$ws, probs = c(0.25)),digits=1),")",
" - 50th: (",round(quantile(ws_mensile$ws, probs = c(0.50)),digits=1),")",
" - 75th: (",round(quantile(ws_mensile$ws, probs = c(0.75)),digits=1),")",
" - 95th: (",round(quantile(ws_mensile$ws, probs = c(0.95)),digits=1),")","\n","\n",
"T min: (", round(min(t_mensile$t),1),") - T max: (", round(max(t_mensile$t),1),") - T mean: (", round(mean(t_mensile$t),1),") - T sd: (", round(sd(t_mensile$t),1),")","\n",
"T percentile: 5th: (",round(quantile(t_mensile$t, probs = c(0.05)),digits=1),")",
" - 25th: (",round(quantile(t_mensile$t, probs = c(0.25)),digits=1),")",
" - 50th: (",round(quantile(t_mensile$t, probs = c(0.50)),digits=1),")",
" - 75th: (",round(quantile(t_mensile$t, probs = c(0.75)),digits=1),")",
" - 95th: (",round(quantile(t_mensile$t, probs = c(0.95)),digits=1),")","\n","\n",
sep="")
, 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 - ",ws_This_Month_Name," ",questo_anno),
cex = 3.1, col = "darkred",pos = 4)
text(x = 0, y = 0.38, paste("\n",
"RH min: (", round(min(rh_mensile$rh),1),") - RH max: (", round(max(rh_mensile$rh),1),") - RH mean: (", round(mean(rh_mensile$rh),1),") - RH sd: (", round(sd(rh_mensile$rh),1),")","\n",
"RH percentile: 5th: (",round(quantile(rh_mensile$rh, probs = c(0.05)),digits=1),")",
" - 25th: (",round(quantile(rh_mensile$rh, probs = c(0.25)),digits=1),")",
" - 50th: (",round(quantile(rh_mensile$rh, probs = c(0.50)),digits=1),")",
" - 75th: (",round(quantile(rh_mensile$rh, probs = c(0.75)),digits=1),")",
" - 95th: (",round(quantile(rh_mensile$rh, probs = c(0.95)),digits=1),")","\n","\n",
"P min: (", round(min(p_mensile$p),1),") - P max: (", round(max(p_mensile$p),1),") - P mean: (", round(mean(p_mensile$p),1),") - P sd: (", round(sd(p_mensile$p),1),")","\n",
"P percentile: 5th: (",round(quantile(p_mensile$p, probs = c(0.05)),digits=1),")",
" - 25th: (",round(quantile(p_mensile$p, probs = c(0.25)),digits=1),")",
" - 50th: (",round(quantile(p_mensile$p, probs = c(0.50)),digits=1),")",
" - 75th: (",round(quantile(p_mensile$p, probs = c(0.75)),digits=1),")",
" - 95th: (",round(quantile(p_mensile$p, probs = c(0.95)),digits=1),")","\n","\n",
"RAD min: (", round(min(rad_mensile$rad),1),") - RAD max: (", round(max(rad_mensile$rad),1),") - RAD mean: (", round(mean(rad_mensile$rad),1),") - RAD sd: (", round(sd(rad_mensile$rad),1),")","\n",
"RAD percentile: 5th: (",round(quantile(rad_mensile$rad, probs = c(0.05)),digits=1),")",
" - 25th: (",round(quantile(rad_mensile$rad, probs = c(0.25)),digits=1),")",
" - 50th: (",round(quantile(rad_mensile$rad, probs = c(0.50)),digits=1),")",
" - 75th: (",round(quantile(rad_mensile$rad, probs = c(0.75)),digits=1),")",
" - 95th: (",round(quantile(rad_mensile$rad, probs = c(0.95)),digits=1),")","\n","\n",
sep=""),
cex = 2.8, col = "black",pos = 4)
dev.off()
}
#
# -------------------------------------------------------------------------------------------
## # END PART 3.0 #
###########################################################################################################################
###########################################################################################################################
## # PART 3.1 #
## ______________________________________________________________________________________________________________________##
## Creating statistcs/graphic reports
## WS SEMESTER GRAPHS
## Cleaning Destination directory
##
## ______________________________________________________________________________________________________________________##
# Subsetting data by semester
# First semester
#
Fhalf <-subset(ws_L02_today_Y,as.numeric(monthNum) < 7)
if (nrow(Fhalf)==0){ } else
{
# -------------------------------------------------------------------------------------------
# Cleaning Destination directory
#
FILE_PLOT_1HM<-list.files(path = PLOT_DIR_M, pattern = paste(s_GAW_ID, inst_type,"WS",questo_anno,"SEMESTER_1st_GRAPH_*",sep = "_"), all.files = FALSE,
full.names = F, recursive = FALSE,
ignore.case = FALSE, include.dirs = F, no.. = FALSE)
FILE_PLOT_1HM
LISTA_PLOT_1HM<-as.character(FILE_PLOT_1HM)
for(f in LISTA_PLOT_1HM)
{
file.remove(paste(PLOT_DIR_M,f,sep = "/"))
}
#
# -------------------------------------------------------------------------------------------
# Preparing plotting files
#
unico<-c(Fhalf[!duplicated(Fhalf[,c('month')]),]$month)
#
# -------------------------------------------------------------------------------------------
# Preparing plotting parameters (font size, margins, ...)
#
png(file=paste(PLOT_DIR_M,paste(s_GAW_ID,"_",inst_type,"_WS_",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)
par(mfrow = c(6,1))
par(ps = 14, cex = 1.8, cex.main = 2, cex.lab=1, cex.axis = 1, 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)