diff --git a/plotting/matrix.R b/plotting/matrix.R
index b4e37f050b06d48523e5b275f964d11c7f9aeb4c..c043b1882b83049c4ad1ee0f324a19eccc9bd9e2 100644
--- a/plotting/matrix.R
+++ b/plotting/matrix.R
@@ -407,562 +407,595 @@ matrix_panel = function (list_df2plot, df_meta, trend_period, mean_period, slice
slice = nCode
}
-
- Type = levels(factor(Type_trend)) ####
-
-
- # Extracts each possibilities of first letter of station code
- firstLetter = levels(factor(substr(Code, 1, 1)))
- # Number of different first letters
- nfL = length(firstLetter)
- # For all the available first letter
- for (ifL in 1:nfL) {
- # Gets the first letter
- fL = firstLetter[ifL]
- # Print the matrix name
- print(paste('Matrix for region : ', fL,
- " (", round(ifL/nfL*100, 1), " %)",
- sep=''))
-
- # Get only station code with the same first letter
- subCodefL = Code[substr(Code, 1, 1) == fL]
- # Counts the number of station in it
- nsubCodefL = length(subCodefL)
- # Computes the number of pages needed to plot all stations
- nMat = as.integer(nsubCodefL/slice) + 1
- # For all the pages
- for (imat in 1:nMat) {
- # Extracts the station for the current page
- subCode = subCodefL[(slice*(imat-1)+1):(slice*imat)]
- # Removes NA stations
- subCode = subCode[!is.na(subCode)]
- # Reverses verticale order of stations
- subCode = rev(subCode)
- # Gets the number of station for the page
- nsubCode = length(subCode)
-
- # Creates logical vector to select only info about
- # stations that will be plot on the page
- CodefL_trend = Code_trend %in% subCode
- # Extracts those info
- subPeriods_trend = Periods_trend[CodefL_trend]
- subNPeriod_trend = NPeriod_trend[CodefL_trend]
- subVar_trend = Var_trend[CodefL_trend]
- subType_trend = Type_trend[CodefL_trend]
- subCode_trend = Code_trend[CodefL_trend]
- subPthresold_trend = Pthresold_trend[CodefL_trend]
- subTrendMean_trend = TrendMean_trend[CodefL_trend]
- subDataMean_trend = DataMean_trend[CodefL_trend]
- subFill_trend = Fill_trend[CodefL_trend]
- subColor_trend = Color_trend[CodefL_trend]
-
- # Same for breaking analysis
- CodefL_mean = Code_mean %in% subCode
- # Extracts right info
- subPeriods_mean = Periods_mean[CodefL_mean]
- subNPeriod_mean = NPeriod_mean[CodefL_mean]
- subVar_mean = Var_mean[CodefL_mean]
- subType_mean = Type_mean[CodefL_mean]
- subCode_mean = Code_mean[CodefL_mean]
- subDataMean_mean = DataMean_mean[CodefL_mean]
- subBreakMean_mean = BreakMean_mean[CodefL_mean]
- subFill_mean = Fill_mean[CodefL_mean]
- subColor_mean = Color_mean[CodefL_mean]
-
- # Extracts the name of the currently hydrological
- # region plotted
- title = df_meta[df_meta$code == subCode[1],]$region_hydro
-
- ### Plot ###
- # Fixes the height and width of the table according to
- # the number of station and the number of column to draw
- height = nsubCode
- width = nbp * 2 * nPeriod_trend + nPeriod_trend + nPeriod_mean * nbp + nPeriod_mean + nbp
-
- # Fixes the size of the plot area to keep proportion right
- options(repr.plot.width=width, repr.plot.height=height)
-
- # Open a new plot with a personalise theme
- mat = ggplot() + theme_ash +
- # Modification of theme in order to remove axis
- theme(
- panel.border=element_blank(),
- axis.text.x=element_blank(),
- axis.text.y=element_blank(),
- axis.ticks.y=element_blank(),
- axis.ticks.x=element_blank(),
- axis.title.y=element_blank(),
- plot.margin=margin(t=5, r=5, b=5, l=5, unit="mm")
- )
- # Postion and name of the title
- xt = 1 - 6
- yt = height + 2
- Title = bquote(bold(.(title)))
- # Writes the title
- mat = mat +
- annotate("text", x=xt, y=yt,
- label=Title,
- hjust=0, vjust=1,
- size=6, color="#00A3A8")
-
- ### Trend ###
- # For all the trend period
- for (j in 1:nPeriod_trend) {
- # Extracts the info to plot associated to the
- # right period
- Periods_trend_per =
- subPeriods_trend[subNPeriod_trend == j]
- NPeriods_trend_per =
- subNPeriod_trend[subNPeriod_trend == j]
- Var_trend_per =
- subVar_trend[subNPeriod_trend == j]
- Type_trend_per =
- subType_trend[subNPeriod_trend == j]
- Code_trend_per =
- subCode_trend[subNPeriod_trend == j]
- Pthresold_trend_per =
- subPthresold_trend[subNPeriod_trend == j]
- TrendMean_trend_per =
- subTrendMean_trend[subNPeriod_trend == j]
- DataMean_trend_per =
- subDataMean_trend[subNPeriod_trend == j]
- Fill_trend_per =
- subFill_trend[subNPeriod_trend == j]
- Color_trend_per =
- subColor_trend[subNPeriod_trend == j]
-
- # Converts the variable list into levels for factor
- levels = unlist(Var_trend_per)
- # Converts the vector of hydrological variable to
- # a vector of integer associated to those variable
- Xtmp = as.integer(factor(as.character(Var_trend_per),
- levels=levels))
-
- # Computes X position of the column for the period dates
- Xc = j + (j - 1)*nbp*2
- # Computes X positions of columns for the mean of
- # variables
- Xm = Xtmp + (j - 1)*nbp*2 + j
- # Computes X positions of columns for the averaged trend
- X = Xtmp + (j - 1)*nbp*2 + nbp + j
+ # Gets all the different type of plots
+ Type = levels(factor(Type_trend))
+ nbType = length(Type)
+ # For all the type of plots
+ for (itype in 1:nbType) {
+ # Gets the type
+ type = Type[itype]
+
+ # Extracts each possibilities of first letter of station code
+ firstLetter = levels(factor(substr(Code, 1, 1)))
+ # Number of different first letters
+ nfL = length(firstLetter)
+ # For all the available first letter
+ for (ifL in 1:nfL) {
+ # Gets the first letter
+ fL = firstLetter[ifL]
+
+ # Get only station code with the same first letter
+ subCodefL = Code[substr(Code, 1, 1) == fL]
+ # Counts the number of station in it
+ nsubCodefL = length(subCodefL)
+ # Computes the number of pages needed to plot all stations
+ nMat = as.integer(nsubCodefL/slice) + 1
+ # For all the pages
+ for (iMat in 1:nMat) {
+ # Print the matrix name
+ print(paste('Matrix ', iMat, '/', nMat,
+ ' of ', type,
+ ' for region : ', fL,
+ " (",
+ round((ifL + nfL*(itype-1)) / (nfL*2) * 100,
+ 1),
+ " %)",
+ sep=''))
- # Computes Y positions of each line for each station
- Y = as.integer(factor(Code_trend_per))
- # Reverses vertical order of stations
- Y = rev(Y)
-
- # Position of a line to delimite periods
- x = Xc - 0.4
- xend = X[length(X)] + 0.25
- y = height + 1.1
- yend = height + 1.1
- # Drawing of the line
- mat = mat +
- annotate("segment",
- x=x, xend=xend,
- y=y, yend=yend,
- color="grey40", size=0.35)
-
- # Position of the name of the current period
- yt = y + 0.15
- Start = trend_period[[j]][1]
- End = trend_period[[j]][2]
- # Name of the period
- periodName = bquote(bold('Période')~bold(.(as.character(j))))
- # Naming the period
+ # Extracts the station for the current page
+ subCode = subCodefL[(slice*(iMat-1)+1):(slice*iMat)]
+ # Removes NA stations
+ subCode = subCode[!is.na(subCode)]
+ # Reverses verticale order of stations
+ subCode = rev(subCode)
+ # Gets the number of station for the page
+ nsubCode = length(subCode)
+
+ # Creates logical vector to select only info about
+ # stations that will be plot on the page
+ CodefL_trend =
+ Code_trend %in% subCode & Type_trend == type
+ # Extracts those info
+ subPeriods_trend = Periods_trend[CodefL_trend]
+ subNPeriod_trend = NPeriod_trend[CodefL_trend]
+ subVar_trend = Var_trend[CodefL_trend]
+ subType_trend = Type_trend[CodefL_trend]
+ subCode_trend = Code_trend[CodefL_trend]
+ subPthresold_trend = Pthresold_trend[CodefL_trend]
+ subTrendMean_trend = TrendMean_trend[CodefL_trend]
+ subDataMean_trend = DataMean_trend[CodefL_trend]
+ subFill_trend = Fill_trend[CodefL_trend]
+ subColor_trend = Color_trend[CodefL_trend]
+
+ # Same for breaking analysis
+ CodefL_mean =
+ Code_mean %in% subCode & Type_mean == type
+ # Extracts right info
+ subPeriods_mean = Periods_mean[CodefL_mean]
+ subNPeriod_mean = NPeriod_mean[CodefL_mean]
+ subVar_mean = Var_mean[CodefL_mean]
+ subType_mean = Type_mean[CodefL_mean]
+ subCode_mean = Code_mean[CodefL_mean]
+ subDataMean_mean = DataMean_mean[CodefL_mean]
+ subBreakMean_mean = BreakMean_mean[CodefL_mean]
+ subFill_mean = Fill_mean[CodefL_mean]
+ subColor_mean = Color_mean[CodefL_mean]
+
+ # Gets the number of variable to plot in
+ # function of the current type
+ nbpMod =
+ length(levels(factor(subVar_trend)))
+
+ ### Plot ###
+ # Fixes the height and width of the table according to
+ # the number of station and the number of column to draw
+ height = nsubCode
+ width = nbpMod * 2 * nPeriod_trend + nPeriod_trend + nPeriod_mean * nbpMod + nPeriod_mean + nbpMod
+
+ # Fixes the size of the plot area to keep proportion right
+ options(repr.plot.width=width, repr.plot.height=height)
+
+ # Open a new plot with a personalise theme
+ mat = ggplot() + theme_ash +
+ # Modification of theme in order to remove axis
+ theme(
+ panel.border=element_blank(),
+ axis.text.x=element_blank(),
+ axis.text.y=element_blank(),
+ axis.ticks.y=element_blank(),
+ axis.ticks.x=element_blank(),
+ axis.title.y=element_blank(),
+ plot.margin=margin(t=5, r=5, b=5, l=5, unit="mm")
+ )
+
+ # Extracts the name of the currently hydrological
+ # region plotted
+ title = df_meta[df_meta$code == subCode[1],]$region_hydro
+
+ subtitle = paste(' ', iMat, '/', nMat,' ', type,
+ sep='')
+ # Postion and name of the title
+ xt = 1 - 6
+ yt = height + 2
+ Title = bquote(bold(.(title))[.(subtitle)])
+ # Writes the title
mat = mat +
- annotate("text", x=x, y=yt,
- label=periodName,
- hjust=0, vjust=0.5,
- size=3, color='grey40')
-
- # For all the variable
- for (i in 1:length(X)) {
- mat = mat +
- # Plots circles for averaged trends
- gg_circle(r=0.45, xc=X[i], yc=Y[i],
- fill=Fill_trend_per[i],
- color=Color_trend_per[i]) +
- # Plots circles for averaged of variables
- gg_circle(r=0.45, xc=Xm[i], yc=Y[i],
- fill='white', color='grey40') +
- # Plots circles for the column of period dates
- gg_circle(r=0.45, xc=Xc, yc=Y[i],
- fill='white', color='grey40')
- }
- # For all averaged trends on this periods
- for (i in 1:length(TrendMean_trend_per)) {
- # Extracts the value of the averaged trend
- trendMean = TrendMean_trend_per[i]
- # Converts it to the right format with two
- # significant figures
- trendMeanC = signif(trendMean*100, 2)
-
- # If it is significative
- if (!is.na(Pthresold_trend_per[i])) {
- # The text color is white
- Tcolor = 'white'
- # Otherwise
- } else {
- # The text is grey
- Tcolor = 'grey85'
- }
+ annotate("text", x=xt, y=yt,
+ label=Title,
+ hjust=0, vjust=1,
+ size=6, color="#00A3A8")
+
+ ### Trend ###
+ # For all the trend period
+ for (j in 1:nPeriod_trend) {
+ # Extracts the info to plot associated to the
+ # right period
+ Periods_trend_per =
+ subPeriods_trend[subNPeriod_trend == j]
+ NPeriods_trend_per =
+ subNPeriod_trend[subNPeriod_trend == j]
+ Var_trend_per =
+ subVar_trend[subNPeriod_trend == j]
+ Type_trend_per =
+ subType_trend[subNPeriod_trend == j]
+ Code_trend_per =
+ subCode_trend[subNPeriod_trend == j]
+ Pthresold_trend_per =
+ subPthresold_trend[subNPeriod_trend == j]
+ TrendMean_trend_per =
+ subTrendMean_trend[subNPeriod_trend == j]
+ DataMean_trend_per =
+ subDataMean_trend[subNPeriod_trend == j]
+ Fill_trend_per =
+ subFill_trend[subNPeriod_trend == j]
+ Color_trend_per =
+ subColor_trend[subNPeriod_trend == j]
+
+ # Converts the variable list into levels for factor
+ levels = unlist(Var_trend_per)
+ # Converts the vector of hydrological variable to
+ # a vector of integer associated to those variable
+ Xtmp = as.integer(factor(as.character(Var_trend_per),
+ levels=levels))
+
+ # Computes X position of the column for
+ # the period dates
+ Xc = j + (j - 1)*nbpMod*2
+ # Computes X positions of columns for
+ # the mean of variables
+ Xm = Xtmp + (j - 1)*nbpMod*2 + j
+ # Computes X positions of columns for
+ # the averaged trend
+ X = Xtmp + (j - 1)*nbpMod*2 + nbpMod + j
- # Same for averaged variables over
- # the current period
- dataMean = DataMean_trend_per[i]
- dataMeanC = signif(dataMean, 2)
+ # Computes Y positions of each line for each station
+ Y = as.integer(factor(Code_trend_per))
+ # Reverses vertical order of stations
+ Y = rev(Y)
+
+ # Position of a line to delimite periods
+ x = Xc - 0.4
+ xend = X[length(X)] + 0.4
+ y = height + 1.1
+ yend = height + 1.1
+ # Drawing of the line
+ mat = mat +
+ annotate("segment",
+ x=x, xend=xend,
+ y=y, yend=yend,
+ color="grey40", size=0.35)
+ # Position of the name of the current period
+ yt = y + 0.15
+ Start = trend_period[[j]][1]
+ End = trend_period[[j]][2]
+ # Name of the period
+ periodName =
+ bquote(bold('Période')~bold(.(as.character(j))))
+ # Naming the period
mat = mat +
- # Writes the mean trend
- annotate('text', x=X[i], y=Y[i],
- label=trendMeanC,
- hjust=0.5, vjust=0.5,
- size=3, color=Tcolor) +
- # Writes the mean of the associated variable
- annotate('text', x=Xm[i], y=Y[i],
- label=dataMeanC,
- hjust=0.5, vjust=0.5,
+ annotate("text", x=x, y=yt,
+ label=periodName,
+ hjust=0, vjust=0.5,
size=3, color='grey40')
- }
-
- # Writes a name for the period dates column
- mat = mat +
- annotate('text', x=Xc, y=max(Y) + 0.9,
- label=bquote(bold('Début')),
- hjust=0.5, vjust=0.5,
- size=3, color='grey20') +
- annotate('text', x=Xc, y=max(Y) + 0.63,
- label=bquote(bold('Fin')),
- hjust=0.5, vjust=0.5,
- size=3, color='grey20')
-
- # For all variable
- for (i in 1:nbp) {
- # Extract the variable of the plot
- var = list_df2plot[[i]]$var
- mat = mat +
- # Writes the unit of the variable
- annotate('text', x=X[i], y=max(Y) + 0.63,
- label=bquote('[%.'*ans^{-1}*']'),
- hjust=0.5, vjust=0.5,
- size=2, color='grey40') +
- # Writes the type of the variable
- annotate('text', x=X[i], y=max(Y) + 0.9,
- label=bquote(.(var)),
- hjust=0.5, vjust=0.5,
- size=3.25, color='grey20') +
- # Writes the unit of the averaged variable
- annotate('text', x=Xm[i], y=max(Y) + 0.63,
- label=bquote('['*m^3*'.'*s^{-1}*']'),
- hjust=0.5, vjust=0.5,
- size=2, color='grey40') +
- # Writes the type of the averaged variable
- annotate('text', x=Xm[i], y=max(Y) + 0.9,
- label=expr(bar(!!var)),
- hjust=0.5, vjust=0.5,
- size=3.25, color='grey20')
- }
- # For all the station on the page
- for (k in 1:nsubCode) {
- # Gets the code
- code = subCode[k]
- # Extracts label for the period dates
- label = Periods_trend_per[Code_trend_per == code][1]
- # Gets the start and end of the period
- # for the station
- periodStart = substr(label, 1, 4)
- periodEnd = substr(label, 14, 17)
+ # For all the variable
+ for (i in 1:length(X)) {
+ mat = mat +
+ # Plots circles for averaged trends
+ gg_circle(r=0.45, xc=X[i], yc=Y[i],
+ fill=Fill_trend_per[i],
+ color=Color_trend_per[i]) +
+ # Plots circles for averaged of variables
+ gg_circle(r=0.45, xc=Xm[i], yc=Y[i],
+ fill='white', color='grey40') +
+ # Plots circles for the column of period dates
+ gg_circle(r=0.45, xc=Xc, yc=Y[i],
+ fill='white', color='grey40')
+ }
+ # For all averaged trends on this periods
+ for (i in 1:length(TrendMean_trend_per)) {
+ # Extracts the value of the averaged trend
+ trendMean = TrendMean_trend_per[i]
+ # Converts it to the right format with two
+ # significant figures
+ trendMeanC = signif(trendMean*100, 2)
+
+ # If it is significative
+ if (!is.na(Pthresold_trend_per[i])) {
+ # The text color is white
+ Tcolor = 'white'
+ # Otherwise
+ } else {
+ # The text is grey
+ Tcolor = 'grey85'
+ }
+
+ # Same for averaged variables over
+ # the current period
+ dataMean = DataMean_trend_per[i]
+ dataMeanC = signif(dataMean, 2)
+
+ mat = mat +
+ # Writes the mean trend
+ annotate('text', x=X[i], y=Y[i],
+ label=trendMeanC,
+ hjust=0.5, vjust=0.5,
+ size=3, color=Tcolor) +
+ # Writes the mean of the associated variable
+ annotate('text', x=Xm[i], y=Y[i],
+ label=dataMeanC,
+ hjust=0.5, vjust=0.5,
+ size=3, color='grey40')
+ }
+ # Writes a name for the period dates column
mat = mat +
- # Writes the starting value
- annotate('text', x=Xc, y=k + 0.13,
- label=bquote(bold(.(periodStart))),
+ annotate('text', x=Xc, y=max(Y) + 0.9,
+ label=bquote(bold('Début')),
hjust=0.5, vjust=0.5,
- size=3, color='grey40') +
- # Writes the ending value
- annotate('text', x=Xc, y=k - 0.13,
- label=bquote(bold(.(periodEnd))),
+ size=3, color='grey20') +
+ annotate('text', x=Xc, y=max(Y) + 0.63,
+ label=bquote(bold('Fin')),
hjust=0.5, vjust=0.5,
- size=3, color='grey40')
+ size=3, color='grey20')
+
+ # For all variable
+ for (i in 1:nbpMod) {
+ # Extract the variable of the plot
+ var = subVar_trend[i]
+ mat = mat +
+ # Writes the unit of the variable
+ annotate('text', x=X[i], y=max(Y) + 0.63,
+ label=bquote('[%.'*ans^{-1}*']'),
+ hjust=0.5, vjust=0.5,
+ size=2, color='grey40') +
+ # Writes the type of the variable
+ annotate('text', x=X[i], y=max(Y) + 0.9,
+ label=bquote(.(var)),
+ hjust=0.5, vjust=0.5,
+ size=3.25, color='grey20') +
+ # Writes the unit of the averaged variable
+ annotate('text', x=Xm[i], y=max(Y) + 0.63,
+ label=bquote('['*m^3*'.'*s^{-1}*']'),
+ hjust=0.5, vjust=0.5,
+ size=2, color='grey40') +
+ # Writes the type of the averaged variable
+ annotate('text', x=Xm[i], y=max(Y) + 0.9,
+ label=expr(bar(!!var)),
+ hjust=0.5, vjust=0.5,
+ size=3.25, color='grey20')
+ }
+
+ # For all the station on the page
+ for (k in 1:nsubCode) {
+ # Gets the code
+ code = subCode[k]
+ # Extracts label for the period dates
+ label =
+ Periods_trend_per[Code_trend_per == code][1]
+ # Gets the start and end of the period
+ # for the station
+ periodStart = substr(label, 1, 4)
+ periodEnd = substr(label, 14, 17)
+
+ mat = mat +
+ # Writes the starting value
+ annotate('text', x=Xc, y=k + 0.13,
+ label=bquote(bold(.(periodStart))),
+ hjust=0.5, vjust=0.5,
+ size=3, color='grey40') +
+ # Writes the ending value
+ annotate('text', x=Xc, y=k - 0.13,
+ label=bquote(bold(.(periodEnd))),
+ hjust=0.5, vjust=0.5,
+ size=3, color='grey40')
+ }
}
- }
- ### Mean ###
- # For all the trend period
- for (j in 1:nPeriod_mean) {
- # Extracts the info to plot associated to the
- # right period
- Periods_mean_per =
- subPeriods_mean[subNPeriod_mean == j]
- NPeriods_mean_per =
- subNPeriod_mean[subNPeriod_mean == j]
- Var_mean_per =
- subVar_mean[subNPeriod_mean == j]
- Type_mean_per =
- subType_mean[subNPeriod_mean == j]
- Code_mean_per =
- subCode_mean[subNPeriod_mean == j]
- DataMean_mean_per =
- subDataMean_mean[subNPeriod_mean == j]
- BreakMean_mean_per =
- subBreakMean_mean[subNPeriod_mean == j]
- Fill_mean_per =
- subFill_mean[subNPeriod_mean == j]
- Color_mean_per =
- subColor_mean[subNPeriod_mean == j]
-
- # Converts the variable list into levels for factor
- levels = unlist(Var_mean_per)
- # Converts the vector of hydrological variable to
- # a vector of integer associated to those variable
- Xtmp_mean = as.integer(factor(as.character(Var_mean_per),
- levels=levels))
- # Computes X position of the column for the period dates
- Xc_mean = j + (j - 1)*nbp + X[length(X)]
- # Computes X positions of columns for the mean of
- # variables
- Xm_mean = Xtmp_mean + (j - 1)*nbp + j + X[length(X)]
- # Computes X positions of columns for the difference of
- # mean between periods (break)
- Xr_mean = Xtmp_mean + (j - 1)*nbp*2 + j + X[length(X)]
-
- # Computes Y positions of each line for each station
- Y_mean = as.integer(factor(Code_mean_per))
- # Reverses vertical order of stations
- Y_mean = rev(Y_mean)
-
- # Position of a line to delimite periods
- x = Xc_mean - 0.4
- xend = Xm_mean[length(Xm_mean)] + 0.25
- y = height + 1.1
- yend = height + 1.1
- # Drawing of the line
- mat = mat +
- annotate("segment",
- x=x, xend=xend,
- y=y, yend=yend,
- color="grey40", size=0.35)
-
- # Position of the name of the current period
- yt = y + 0.15
- Start = mean_period[[j]][1]
- End = mean_period[[j]][2]
- # Name of the period
- periodName = bquote(bold('Période')~bold(.(as.character(j+nPeriod_trend))))
- # Naming the period
- mat = mat +
- annotate("text", x=x, y=yt,
- label=periodName,
- hjust=0, vjust=0.5,
- size=3, color='grey40')
-
- # If this is not the first period
- if (j > 1) {
- # Position of a line to delimite results of
- # difference of mean bewteen periods
- x = Xr_mean[1] - 0.4
- xend = Xr_mean[length(Xr_mean)] + 0.25
+ ### Mean ###
+ # For all the trend period
+ for (j in 1:nPeriod_mean) {
+ # Extracts the info to plot associated to the
+ # right period
+ Periods_mean_per =
+ subPeriods_mean[subNPeriod_mean == j]
+ NPeriods_mean_per =
+ subNPeriod_mean[subNPeriod_mean == j]
+ Var_mean_per =
+ subVar_mean[subNPeriod_mean == j]
+ Type_mean_per =
+ subType_mean[subNPeriod_mean == j]
+ Code_mean_per =
+ subCode_mean[subNPeriod_mean == j]
+ DataMean_mean_per =
+ subDataMean_mean[subNPeriod_mean == j]
+ BreakMean_mean_per =
+ subBreakMean_mean[subNPeriod_mean == j]
+ Fill_mean_per =
+ subFill_mean[subNPeriod_mean == j]
+ Color_mean_per =
+ subColor_mean[subNPeriod_mean == j]
+
+ # Converts the variable list into levels for factor
+ levels = unlist(Var_mean_per)
+ # Converts the vector of hydrological variable to
+ # a vector of integer associated to those variable
+ Xtmp_mean =
+ as.integer(factor(as.character(Var_mean_per),
+ levels=levels))
+ # Computes X position of the column for
+ # the period dates
+ Xc_mean = j + (j - 1)*nbpMod + X[length(X)]
+ # Computes X positions of columns for
+ # the mean of variables
+ Xm_mean =
+ Xtmp_mean + (j - 1)*nbpMod + j + X[length(X)]
+ # Computes X positions of columns for
+ # the difference of mean between periods (break)
+ Xr_mean =
+ Xtmp_mean + (j - 1)*nbpMod*2 + j + X[length(X)]
+
+ # Computes Y positions of each line for each station
+ Y_mean = as.integer(factor(Code_mean_per))
+ # Reverses vertical order of stations
+ Y_mean = rev(Y_mean)
+
+ # Position of a line to delimite periods
+ x = Xc_mean - 0.4
+ xend = Xm_mean[length(Xm_mean)] + 0.25
+ y = height + 1.1
+ yend = height + 1.1
# Drawing of the line
mat = mat +
annotate("segment",
x=x, xend=xend,
y=y, yend=yend,
color="grey40", size=0.35)
- # Naming the breaking columns
- breakName = bquote(bold('Écart')~bold(.(as.character(j-1+nPeriod_trend)))*bold('-')*bold(.(as.character(j+nPeriod_trend))))
- # Writes the name
+
+ # Position of the name of the current period
+ yt = y + 0.15
+ Start = mean_period[[j]][1]
+ End = mean_period[[j]][2]
+ # Name of the period
+ periodName = bquote(bold('Période')~bold(.(as.character(j+nPeriod_trend))))
+ # Naming the period
mat = mat +
annotate("text", x=x, y=yt,
- label=breakName,
+ label=periodName,
hjust=0, vjust=0.5,
size=3, color='grey40')
- }
- # For all the variable
- for (i in 1:length(Xm_mean)) {
- mat = mat +
- # Plots circles for averaged variables
- gg_circle(r=0.45, xc=Xm_mean[i], yc=Y[i],
- fill='white', color='grey40') +
- # Plots circles for the column of period dates
- gg_circle(r=0.45, xc=Xc_mean, yc=Y[i],
- fill='white', color='grey40')
-
# If this is not the first period
if (j > 1) {
+ # Position of a line to delimite results of
+ # difference of mean bewteen periods
+ x = Xr_mean[1] - 0.4
+ xend = Xr_mean[length(Xr_mean)] + 0.25
+ # Drawing of the line
mat = mat +
- # Plots circles for breaking results
- gg_circle(r=0.45, xc=Xr_mean[i], yc=Y[i],
- fill=Fill_mean_per[i],
- color=Color_mean_per[i])
+ annotate("segment",
+ x=x, xend=xend,
+ y=y, yend=yend,
+ color="grey40", size=0.35)
+ # Naming the breaking columns
+ breakName = bquote(bold('Écart')~bold(.(as.character(j-1+nPeriod_trend)))*bold('-')*bold(.(as.character(j+nPeriod_trend))))
+ # Writes the name
+ mat = mat +
+ annotate("text", x=x, y=yt,
+ label=breakName,
+ hjust=0, vjust=0.5,
+ size=3, color='grey40')
}
- }
- # For all averaged variables on this period
- for (i in 1:length(DataMean_mean_per)) {
- # Extracts values of averaged variables
- dataMean = DataMean_mean_per[i]
- # Converts it to the right format with two
- # significant figures
- dataMeanC = signif(dataMean, 2)
- # Writes averaged variables values
- mat = mat +
- annotate('text', x=Xm_mean[i], y=Y[i],
- label=dataMeanC,
- hjust=0.5, vjust=0.5,
- size=3, color='grey40')
- # If this is not the first period
- if (j > 1) {
- # Extracts values of breaking between periods
- BreakMean = BreakMean_mean_per[i]
+ # For all the variable
+ for (i in 1:length(Xm_mean)) {
+ mat = mat +
+ # Plots circles for averaged variables
+ gg_circle(r=0.45, xc=Xm_mean[i], yc=Y[i],
+ fill='white', color='grey40') +
+ # Plots circles for the column of period dates
+ gg_circle(r=0.45, xc=Xc_mean, yc=Y[i],
+ fill='white', color='grey40')
+
+ # If this is not the first period
+ if (j > 1) {
+ mat = mat +
+ # Plots circles for breaking results
+ gg_circle(r=0.45, xc=Xr_mean[i], yc=Y[i],
+ fill=Fill_mean_per[i],
+ color=Color_mean_per[i])
+ }
+ }
+
+ # For all averaged variables on this period
+ for (i in 1:length(DataMean_mean_per)) {
+ # Extracts values of averaged variables
+ dataMean = DataMean_mean_per[i]
# Converts it to the right format with two
# significant figures
- BreakMeanC = signif(BreakMean*100, 2)
- # Writes breaking values
+ dataMeanC = signif(dataMean, 2)
+ # Writes averaged variables values
mat = mat +
- annotate('text', x=Xr_mean[i], y=Y[i],
- label=BreakMeanC,
+ annotate('text', x=Xm_mean[i], y=Y[i],
+ label=dataMeanC,
hjust=0.5, vjust=0.5,
- size=3, color='white')
+ size=3, color='grey40')
+ # If this is not the first period
+ if (j > 1) {
+ # Extracts values of breaking between periods
+ BreakMean = BreakMean_mean_per[i]
+ # Converts it to the right format with two
+ # significant figures
+ BreakMeanC = signif(BreakMean*100, 2)
+ # Writes breaking values
+ mat = mat +
+ annotate('text', x=Xr_mean[i], y=Y[i],
+ label=BreakMeanC,
+ hjust=0.5, vjust=0.5,
+ size=3, color='white')
+ }
}
- }
- # Writes a name for the period dates column
- mat = mat +
- annotate('text', x=Xc_mean, y=max(Y) + 0.9,
- label=bquote(bold('Début')),
- hjust=0.5, vjust=0.5,
- size=3, color='grey20') +
- annotate('text', x=Xc_mean, y=max(Y) + 0.63,
- label=bquote(bold('Fin')),
- hjust=0.5, vjust=0.5,
- size=3, color='grey20')
-
- # For all variables
- for (i in 1:nbp) {
- # Extract the variable of the plot
- var = list_df2plot[[i]]$var
+ # Writes a name for the period dates column
mat = mat +
- # Writes the unit of the averaged variable
- annotate('text', x=Xm_mean[i], y=max(Y) + 0.63,
- label=bquote('['*m^3*'.'*s^{-1}*']'),
+ annotate('text', x=Xc_mean, y=max(Y) + 0.9,
+ label=bquote(bold('Début')),
hjust=0.5, vjust=0.5,
- size=2, color='grey40') +
- # Writes the type of the averaged variable
- annotate('text', x=Xm_mean[i], y=max(Y) + 0.9,
- label=expr(bar(!!var)),
+ size=3, color='grey20') +
+ annotate('text', x=Xc_mean, y=max(Y) + 0.63,
+ label=bquote(bold('Fin')),
hjust=0.5, vjust=0.5,
- size=3.25, color='grey20')
-
- # If this is not the first period
- if (j > 1) {
+ size=3, color='grey20')
+
+ # For all variables
+ for (i in 1:nbpMod) {
+ # Extract the variable of the plot
+ var = subVar_mean[i]
mat = mat +
- # Writes the unit of the breaking variable
- annotate('text', x=Xr_mean[i],
- y=max(Y) + 0.63,
- label=bquote('[%]'),
+ # Writes the unit of the averaged variable
+ annotate('text',
+ x=Xm_mean[i], y=max(Y) + 0.63,
+ label=bquote('['*m^3*'.'*s^{-1}*']'),
hjust=0.5, vjust=0.5,
size=2, color='grey40') +
- # Writes the type of the breaking variable
- annotate('text', x=Xr_mean[i],
- y=max(Y) + 0.9,
- label=paste("d", var, sep=''),
- hjust=0.5, vjust=0.5,
+ # Writes the type of the averaged variable
+ annotate('text',
+ x=Xm_mean[i], y=max(Y) + 0.9,
+ label=expr(bar(!!var)),
+ hjust=0.5, vjust=0.5,
size=3.25, color='grey20')
+
+ # If this is not the first period
+ if (j > 1) {
+ mat = mat +
+ # Writes the unit of the breaking variable
+ annotate('text', x=Xr_mean[i],
+ y=max(Y) + 0.63,
+ label=bquote('[%]'),
+ hjust=0.5, vjust=0.5,
+ size=2, color='grey40') +
+ # Writes the type of the breaking variable
+ annotate('text', x=Xr_mean[i],
+ y=max(Y) + 0.9,
+ label=paste("d", var, sep=''),
+ hjust=0.5, vjust=0.5,
+ size=3.25, color='grey20')
+ }
}
- }
- # For all the station on the page
+ # For all the station on the page
+ for (k in 1:nsubCode) {
+ # Gets the code
+ code = subCode[k]
+ # Extracts label for the period dates
+ label = Periods_mean_per[Code_mean_per == code][1]
+ # Gets the start and end of the period
+ # for the station
+ periodStart = substr(label, 1, 4)
+ periodEnd = substr(label, 14, 17)
+
+ mat = mat +
+ # # Writes the starting value
+ annotate('text', x=Xc_mean, y=k + 0.13,
+ label=bquote(bold(.(periodStart))),
+ hjust=0.5, vjust=0.5,
+ size=3, color='grey40') +
+ # Writes the ending value
+ annotate('text', x=Xc_mean, y=k - 0.13,
+ label=bquote(bold(.(periodEnd))),
+ hjust=0.5, vjust=0.5,
+ size=3, color='grey40')
+ }
+ }
+
+ ### Code ###
+ # For all the station
for (k in 1:nsubCode) {
# Gets the code
code = subCode[k]
- # Extracts label for the period dates
- label = Periods_mean_per[Code_mean_per == code][1]
- # Gets the start and end of the period
- # for the station
- periodStart = substr(label, 1, 4)
- periodEnd = substr(label, 14, 17)
+ # Gets the name of the station
+ name = df_meta[df_meta$code == code,]$nom
+ # Fixes a limit for the max number
+ # of characters available
+ ncharMax = 38
+ # If the number of character of the name is greater
+ # than the limit
+ if (nchar(name) > ncharMax) {
+ # Cuts the name and add '...'
+ name = paste(substr(name, 1, ncharMax),
+ '...', sep='')
+ }
mat = mat +
- # # Writes the starting value
- annotate('text', x=Xc_mean, y=k + 0.13,
- label=bquote(bold(.(periodStart))),
- hjust=0.5, vjust=0.5,
- size=3, color='grey40') +
- # Writes the ending value
- annotate('text', x=Xc_mean, y=k - 0.13,
- label=bquote(bold(.(periodEnd))),
- hjust=0.5, vjust=0.5,
- size=3, color='grey40')
- }
- }
-
- ### Code ###
- # For all the station
- for (k in 1:nsubCode) {
- # Gets the code
- code = subCode[k]
- # Gets the name of the station
- name = df_meta[df_meta$code == code,]$nom
- # Fixes a limit for the max number
- # of characters available
- ncharMax = 38
- # If the number of character of the name is greater
- # than the limit
- if (nchar(name) > ncharMax) {
- # Cuts the name and add '...'
- name = paste(substr(name, 1, ncharMax),
- '...', sep='')
+ # Writes the code of the station
+ annotate('text', x=0.3, y=k + 0.14,
+ label=bquote(bold(.(code))),
+ hjust=1, vjust=0.5,
+ size=3.5, color="#00A3A8") +
+ # Writes the name of the station
+ annotate('text', x=0.3, y=k - 0.14,
+ label=name,
+ hjust=1, vjust=0.5,
+ size=3.5, color="#00A3A8")
}
+ ### Environment ###
mat = mat +
- # Writes the code of the station
- annotate('text', x=0.3, y=k + 0.14,
- label=bquote(bold(.(code))),
- hjust=1, vjust=0.5,
- size=3.5, color="#00A3A8") +
- # Writes the name of the station
- annotate('text', x=0.3, y=k - 0.14,
- label=name,
- hjust=1, vjust=0.5,
- size=3.5, color="#00A3A8")
- }
+ # Fixed coordinate system
+ coord_fixed() +
+ # X axis
+ scale_x_continuous(limits=c(1 - rel(6),
+ width + rel(0.5)),
+ expand=c(0, 0)) +
+ # Y axis
+ scale_y_continuous(limits=c(1 - rel(0.5),
+ height + rel(2)),
+ expand=c(0, 0))
+
+ # Paper format in A3 if needed
+ if (A3) {
+ width = 42
+ height = 29.7
+ dpi = 300
+ # Otherwise in A4
+ } else {
+ width = 29.7
+ height = 21
+ dpi = 100
+ }
- ### Environment ###
- mat = mat +
- # Fixed coordinate system
- coord_fixed() +
- # X axis
- scale_x_continuous(limits=c(1 - rel(6),
- width + rel(0.5)),
- expand=c(0, 0)) +
- # Y axis
- scale_y_continuous(limits=c(1 - rel(0.5),
- height + rel(2)),
- expand=c(0, 0))
-
- # Paper format in A3 if needed
- if (A3) {
- width = 42
- height = 29.7
- dpi = 300
- # Otherwise in A4
- } else {
- width = 29.7
- height = 21
- dpi = 100
+ # Saving
+ ggsave(plot=mat,
+ path=outdirTmp,
+ filename=paste(outnameTmp,
+ '_', type,
+ '_', fL,
+ iMat, sep=''),
+ device='pdf',
+ width=width, height=height,
+ units='cm', dpi=dpi)
}
-
- # Saving
- ggsave(plot=mat,
- path=outdirTmp,
- filename=paste(outnameTmp, '_', fL,
- imat, sep=''),
- device='pdf',
- width=width, height=height,
- units='cm', dpi=dpi)
- }
- }
+ }
+ }
}
diff --git a/processing/format.R b/processing/format.R
index 97cba2bf3edd5ab279218e342638109860d202b3..d6398ece9eb8c83e86e5be12f696fac96b493e46 100644
--- a/processing/format.R
+++ b/processing/format.R
@@ -180,11 +180,15 @@ prepare_date = function(df_XEx, df_Xlist) {
# dExMean = apply(rbind(dXExUp, dXExDown), 2, mean, na.rm=TRUE)
meanXEx_code = mean(XEx_code, na.rm=TRUE)
- dXEx_code = abs(XEx_code - meanXEx_code)
+ dXEx_code = meanXEx_code - XEx_code
stdXEx_code = sd(XEx_code, na.rm=TRUE)
XEx_code[dXEx_code >= stdXEx_code*3] =
XEx_code[dXEx_code >= stdXEx_code*3] + 365
+
+ # print(group)
+ # print(df_XEx$datetime[df_XEx$group1 == group][dXEx_code >= stdXEx_code*3])
+
df_XEx$values[OkXEx_code] = XEx_code
}
diff --git a/script.R b/script.R
index f67bfa4115d6c91fc498a9b19bd898d5453a9b88..218cf88210017ce31c647f6b25ff69649e580f4e 100644
--- a/script.R
+++ b/script.R
@@ -66,7 +66,7 @@ filename =
# )
c(
- # "S4214010_HYDRO_QJM.txt"
+ # "S4214010_HYDRO_QJM.txt",
# "O0384010_HYDRO_QJM.txt",
"Q7002910_HYDRO_QJM.txt"
)
@@ -291,8 +291,8 @@ df_shapefile = ini_shapefile(computer_data_path,
### 4.2. Analysis layout
datasheet_layout(toplot=c(
- # 'datasheet'
- 'matrix'
+ 'datasheet'
+ # 'matrix',
# 'map'
),
df_meta=df_meta,