diff --git a/plotting/datasheet.R b/plotting/datasheet.R
index 37c776404c4364a1d31cc328cb0336e3d5aee6a9..eb6213794b3bf58a049a17e75116ff3fda9725ca 100644
--- a/plotting/datasheet.R
+++ b/plotting/datasheet.R
@@ -31,11 +31,11 @@ source('processing/analyse.R', encoding='UTF-8') # hydrograph
source('plotting/shortcut.R', encoding='UTF-8')
-## 1. DATASHEET PANEL ________________________________________________
+## 1. DATASHEET PANEL MANAGER ________________________________________
# Manages datasheets creations for all stations. Makes the call to
# the different headers, trend analysis graphs and realises arranging
# every plots.
-datasheet_panel = function (list_df2plot, df_meta, trend_period, mean_period, info_header, time_header, foot_note, layout_matrix, info_height, time_ratio, var_ratio, foot_height, resources_path, logo_dir, AEAGlogo_file, INRAElogo_file, FRlogo_file, outdirTmp, df_page=NULL) {
+datasheet_panel = function (list_df2plot, df_meta, trend_period, mean_period, colorForce, info_header, time_header, foot_note, layout_matrix, info_height, time_ratio, var_ratio, foot_height, resources_path, logo_dir, AEAGlogo_file, INRAElogo_file, FRlogo_file, outdirTmp, df_page=NULL) {
# The percentage of augmentation and diminution of the min
# and max limits for y axis
@@ -55,7 +55,7 @@ datasheet_panel = function (list_df2plot, df_meta, trend_period, mean_period, in
nPeriod_trend = length(trend_period)
# Extracts the min and the max of the mean trend for all the station
- res = short_trendExtremes(list_df2plot, Code, nPeriod_trend, nbp, nCode)
+ res = short_trendExtremes(list_df2plot, Code, nPeriod_trend, nbp, nCode, colorForce)
minTrendValue = res$min
maxTrendValue = res$max
}
@@ -179,7 +179,8 @@ datasheet_panel = function (list_df2plot, df_meta, trend_period, mean_period, in
max(time_header_code$Date))
# Gets the time serie plot
Htime = time_panel(time_header_code, df_trend_code=NULL,
- trend_period=trend_period, missRect=TRUE,
+ trend_period=trend_period,
+ axis_xlim=axis_xlim, missRect=TRUE,
unit2day=365.25, var='Q', type='sévérité',
grid=TRUE, ymin_lim=0,
NspaceMax=NspaceMax[k],
@@ -197,7 +198,7 @@ datasheet_panel = function (list_df2plot, df_meta, trend_period, mean_period, in
# Extracts the trend corresponding to the
# current variable
df_trend = list_df2plot[[i]]$trend
- alpha = list_df2plot[[i]]$alpha
+
unit2day = list_df2plot[[i]]$unit2day
missRect = list_df2plot[[i]]$missRect
# Extract the variable of the plot
@@ -216,6 +217,7 @@ datasheet_panel = function (list_df2plot, df_meta, trend_period, mean_period, in
for (j in 1:nPeriod_trend) {
# If the trend is significant
+ # if (df_trend_code$p[j] <= alpha | colorForce){
if (df_trend_code$p[j] <= alpha){
# Extract start and end of trend periods
Start = df_trend_code$period_start[j]
@@ -259,10 +261,11 @@ datasheet_panel = function (list_df2plot, df_meta, trend_period, mean_period, in
reverse=TRUE)
# Stores it temporarily
colortmp = color_res
+
# Otherwise
} else {
# Stores the default grey color
- colortmp = paste('grey85', sep='')
+ colortmp = 'grey85'
}
# Stores the color
@@ -289,7 +292,7 @@ datasheet_panel = function (list_df2plot, df_meta, trend_period, mean_period, in
# Computes the time panel associated to the current variable
p = time_panel(df_data_code, df_trend_code, var=var,
- type=type, alpha=alpha,
+ type=type, alpha=alpha, colorForce=colorForce,
missRect=missRect, trend_period=trend_period,
mean_period=mean_period, axis_xlim=axis_xlim,
unit2day=unit2day, grid=grid,
@@ -411,9 +414,9 @@ datasheet_panel = function (list_df2plot, df_meta, trend_period, mean_period, in
}
-## 2. OTHER PANEL FOR THE DATASHEET __________________________________
+## 2. PANEL FOR THE DATASHEET __________________________________
### 2.1. Time panel __________________________________________________
-time_panel = function (df_data_code, df_trend_code, var, type, alpha=0.1, missRect=FALSE, unit2day=365.25, trend_period=NULL, mean_period=NULL, axis_xlim=NULL, grid=TRUE, ymin_lim=NULL, color=NULL, NspaceMax=NULL, first=FALSE, last=FALSE, lim_pct=10) {
+time_panel = function (df_data_code, df_trend_code, var, type, alpha=0.1, colorForce=FALSE, missRect=FALSE, unit2day=365.25, trend_period=NULL, mean_period=NULL, axis_xlim=NULL, grid=TRUE, ymin_lim=NULL, color=NULL, NspaceMax=NULL, first=FALSE, last=FALSE, lim_pct=10) {
# Compute max and min of flow
maxQ = max(df_data_code$Value, na.rm=TRUE)
@@ -547,31 +550,8 @@ time_panel = function (df_data_code, df_trend_code, var, type, alpha=0.1, missRe
theme(plot.margin=margin(t=2, r=0, b=2, l=0, unit="mm"))
}
-
## Sub period background ##
if (!is.null(trend_period)) {
-
- # trend_period = as.list(trend_period)
- # Imin = 10^99
- # for (per in trend_period) {
- # I = interval(per[1], per[2])
- # if (I < Imin) {
- # Imin = I
- # trend_period_min = as.Date(per)
- # }
- # }
- # p = p +
- # geom_rect(aes(xmin=min(df_data_code$Date),
- # ymin=0,
- # xmax=trend_period_min[1],
- # ymax= maxQ*1.1),
- # linetype=0, fill='grey97') +
-
- # geom_rect(aes(xmin=trend_period_min[2],
- # ymin=0,
- # xmax=max(df_data_code$Date),
- # ymax= maxQ*1.1),
- # linetype=0, fill='grey97')
# Convert trend period to list if it is not
trend_period = as.list(trend_period)
@@ -592,39 +572,35 @@ time_panel = function (df_data_code, df_trend_code, var, type, alpha=0.1, missRe
minPer = trend_period_min[1]
maxPer = trend_period_min[2]
-
- # If it is not a flow or sqrt of flow time serie
- if (var != 'sqrt(Q)' & var != 'Q') {
- # If there is an 'axis_lim'
- if (!is.null(axis_xlim)) {
- # If the temporary start of period is smaller
- # than the fix start of x axis limit
- if (minPer < axis_xlim[1]) {
- # Set the start of the period to the start of
- # the x axis limit
- minPer = axis_xlim[1]
- }
- }
- }
- # If it is not a flow or sqrt of flow time serie
- if (var != 'sqrt(Q)' & var != 'Q') {
- # If there is an 'axis_lim'
- if (!is.null(axis_xlim)) {
- # If the temporary end of period plus one year
- # is smaller than the fix end of x axis limit
- if (maxPer + years(1) < axis_xlim[2]) {
- # Add one year the the temporary end of period
- maxPer = maxPer + years(1)
- } else {
- # Set the start of the period to the start of
- # the x axis limit
- maxPer = axis_xlim[2]
- }
+ # If there is an 'axis_lim'
+ if (!is.null(axis_xlim)) {
+ # If the temporary start of period is smaller
+ # than the fix start of x axis limit
+ if (minPer < axis_xlim[1]) {
+ # Set the start of the period to the start of
+ # the x axis limit
+ minPer = axis_xlim[1]
+ }
+
+ # If the temporary end of period plus one year
+ # is smaller than the fix end of x axis limit
+ if (maxPer + years(1) < axis_xlim[2]) {
# Add one year the the temporary end of period
- # if there is no 'axis_lim'
+ maxPer = maxPer + years(1)
} else {
- maxPer = maxPer + years(1)
+ # Set the start of the period to the start of
+ # the x axis limit
+ maxPer = axis_xlim[2]
+ }
+
+ # If there is no 'axis_lim'
+ } else {
+ if (minPer < min(df_data_code$Date)) {
+ minPer = min(df_data_code$Date)
+ }
+ if (maxPer > max(df_data_code$Date)) {
+ maxPer = max(df_data_code$Date)
}
}
@@ -990,9 +966,33 @@ time_panel = function (df_data_code, df_trend_code, var, type, alpha=0.1, missRe
trend = df_trend_code_per$trend
# Gets the p value
pVal = df_trend_code_per$p
- # Converts it to character
- pValC = as.character(format(round(pVal, 2),
- nsmall=2))
+
+ # if (colorForce) {
+ # if (pVal <= alpha) {
+ # colorLine = color[i]
+ # colorLabel = color[i]
+ # } else {
+ # colorLine = color[i]
+ # colorLabel = 'grey85'
+ # }
+ # } else {
+ # if (pVal <= alpha) {
+ # colorLine = color[i]
+ # colorLabel = color[i]
+ # } else {
+ # colorLine = 'grey85'
+ # colorLabel = 'grey85'
+ # }
+ # }
+
+ if (pVal <= alpha) {
+ colorLine = color[i]
+ colorLabel = color[i]
+ } else {
+ colorLine = 'grey85'
+ colorLabel = 'grey85'
+ }
+
# Computes the mean trend
trendMean = trend/dataMean
# Computes the magnitude of the trend
@@ -1034,11 +1034,12 @@ time_panel = function (df_data_code, df_trend_code, var, type, alpha=0.1, missRe
leg_trendtmp = tibble(x=x, xend=xend,
y=y, yend=yend,
xt=xt,
+ colorLine=colorLine,
+ colorLabel=colorLabel,
trendC=trendC,
powerC=powerC,
spaceC=spaceC,
trendMeanC=trendMeanC,
- pValC=pValC,
xminR=xminR, yminR=yminR,
xmaxR=xmaxR, ymaxR=ymaxR,
period=i)
@@ -1059,19 +1060,14 @@ time_panel = function (df_data_code, df_trend_code, var, type, alpha=0.1, missRe
xmax=xmaxR,
ymax=ymaxR),
linetype=0, fill='white', alpha=0.5)
- }
-
- # For all periods
- for (i in 1:nPeriod_trend) {
- # Extract the trend of the current sub period
- leg_trend_per = leg_trend[leg_trend$period == i,]
# Get the character variable for naming the trend
+ colorLine = leg_trend_per$colorLine
+ colorLabel = leg_trend_per$colorLabel
trendC = leg_trend_per$trendC
powerC = leg_trend_per$powerC
spaceC = leg_trend_per$spaceC
trendMeanC = leg_trend_per$trendMeanC
- pValC = leg_trend_per$pValC
# If it is a flow variable
if (type == 'sévérité') {
@@ -1089,7 +1085,7 @@ time_panel = function (df_data_code, df_trend_code, var, type, alpha=0.1, missRe
annotate("segment",
x=leg_trend_per$x, xend=leg_trend_per$xend,
y=leg_trend_per$y, yend=leg_trend_per$yend,
- color=color[i],
+ color=colorLine,
linetype='solid',
lwd=0.8) +
@@ -1097,7 +1093,7 @@ time_panel = function (df_data_code, df_trend_code, var, type, alpha=0.1, missRe
label=label, size=2.8,
x=leg_trend_per$xt, y=leg_trend_per$y,
hjust=0, vjust=0.5,
- color=color[i])
+ color=colorLabel)
}
# For all periods
diff --git a/plotting/layout.R b/plotting/layout.R
index 0bbd98c0441fe5b516c3ba94ae8962b45357d7fa..4242719dab5c8a7d8d0e2b00a1606412632e01bb 100644
--- a/plotting/layout.R
+++ b/plotting/layout.R
@@ -131,7 +131,8 @@ datasheet_layout = function (df_data, df_meta, layout_matrix,
variable='', df_trend=NULL,
alpha=0.1, unit2day=365.25, var='',
type='', glose=NULL, trend_period=NULL,
- mean_period=NULL, axis_xlim=NULL,
+ mean_period=NULL, colorForce=FALSE,
+ axis_xlim=NULL,
missRect=TRUE, time_header=NULL,
info_header=NULL, foot_note=TRUE,
info_height=2.8, time_ratio=2,
@@ -251,6 +252,7 @@ datasheet_layout = function (df_data, df_meta, layout_matrix,
idPer_trend=length(trend_period),
trend_period=trend_period,
mean_period=mean_period,
+ colorForce=colorForce,
df_shapefile=df_shapefile,
foot_note=foot_note,
foot_height=foot_height,
@@ -269,6 +271,7 @@ datasheet_layout = function (df_data, df_meta, layout_matrix,
df_meta,
trend_period,
mean_period,
+ colorForce=colorForce,
slice=19,
outdirTmp=outdirTmp,
A3=TRUE,
@@ -288,6 +291,7 @@ datasheet_layout = function (df_data, df_meta, layout_matrix,
df_meta,
trend_period=trend_period,
mean_period=mean_period,
+ colorForce=colorForce,
info_header=info_header,
time_header=time_header,
foot_note=foot_note,
diff --git a/plotting/map.R b/plotting/map.R
index 644092b63455548e35db8f3e9557a87c94f55cf2..931218190410bfbb99f0cebd59e9a7106a20d8c1 100644
--- a/plotting/map.R
+++ b/plotting/map.R
@@ -29,8 +29,8 @@
## 1. MAP PANEL ______________________________________________________
# Generates a map plot of the tendancy of a hydrological variable
map_panel = function (list_df2plot, df_meta, df_shapefile, idPer_trend=1,
- trend_period,
- mean_period, outdirTmp='', codeLight=NULL,
+ trend_period, mean_period, colorForce=FALSE,
+ outdirTmp='', codeLight=NULL,
margin=NULL, showSea=TRUE,
foot_note=FALSE,
foot_height=0, resources_path=NULL,
@@ -59,7 +59,7 @@ map_panel = function (list_df2plot, df_meta, df_shapefile, idPer_trend=1,
nPeriod_trend = length(trend_period)
# Extracts the min and the max of the mean trend for all the station
- res = short_trendExtremes(list_df2plot, Code, nPeriod_trend, nbp, nCode)
+ res = short_trendExtremes(list_df2plot, Code, nPeriod_trend, nbp, nCode, colorForce)
minTrendValue = res$min
maxTrendValue = res$max
}
@@ -298,13 +298,13 @@ map_panel = function (list_df2plot, df_meta, df_shapefile, idPer_trend=1,
value = breakValue_code[j, i, k]
minValue = minBreakValue[j, i]
maxValue = maxBreakValue[j, i]
- pvalue = 0
+ pVal = 0
} else if (is.null(trend_period)) {
value = NA
minValue = NULL
maxValue = NULL
- pvalue = 0
+ pVal = 0
} else {
@@ -358,7 +358,7 @@ map_panel = function (list_df2plot, df_meta, df_shapefile, idPer_trend=1,
minValue = minTrendValue[idPer_trend, i]
maxValue = maxTrendValue[idPer_trend, i]
- pvalue = df_trend_code_per$p
+ pVal = df_trend_code_per$p
}
@@ -385,7 +385,7 @@ map_panel = function (list_df2plot, df_meta, df_shapefile, idPer_trend=1,
} else {
# If it is significative
- if (pvalue <= alpha){
+ if (pVal <= alpha){
# The computed color is stored
filltmp = color_res
# If the mean tend is positive
@@ -399,7 +399,12 @@ map_panel = function (list_df2plot, df_meta, df_shapefile, idPer_trend=1,
# of the marker
shapetmp = 25
}
- # If it is not significative
+ } else if (pVal > alpha & colorForce) {
+ # The computed color is stored
+ filltmp = color_res
+ # The marker is a circle
+ shapetmp = 21
+ # If it is not significative
} else {
# The fill color is grey
filltmp = 'grey97'
@@ -421,7 +426,7 @@ map_panel = function (list_df2plot, df_meta, df_shapefile, idPer_trend=1,
shape = c(shape, shapetmp)
Value = c(Value, value)
# If the trend analysis is significative a TRUE is stored
- OkVal = c(OkVal, pvalue <= alpha)
+ OkVal = c(OkVal, pVal <= alpha)
}
# Creates a tibble to stores all the data to plot
plot_map = tibble(lon=lon, lat=lat, fill=fill,
@@ -709,7 +714,7 @@ map_panel = function (list_df2plot, df_meta, df_shapefile, idPer_trend=1,
}
# Takes only the significative ones
- yValue = yValue[OkVal]
+ yValueOk = yValue[OkVal]
# Histogram distribution
# Computes the histogram of values
diff --git a/plotting/matrix.R b/plotting/matrix.R
index 663c553dd7f132cbd134c0ea8025d410ecdc02a5..1874fd19a5986d10707fe7c49a667d0726e0b298 100644
--- a/plotting/matrix.R
+++ b/plotting/matrix.R
@@ -28,7 +28,9 @@
## 1. MATRIX PANEL ___________________________________________________
# Generates a summarizing matrix of the trend analyses of all station for different hydrological variables and periods. Also shows difference of means between specific periods.
-matrix_panel = function (list_df2plot, df_meta, trend_period, mean_period, slice=NULL, outdirTmp='', outnameTmp='matrix', title=NULL, A3=FALSE,
+matrix_panel = function (list_df2plot, df_meta, trend_period, mean_period,
+ colorForce=FALSE, slice=NULL, outdirTmp='',
+ outnameTmp='matrix', title=NULL, A3=FALSE,
foot_note=FALSE,
foot_height=0, resources_path=NULL,
logo_dir=NULL,
@@ -48,7 +50,7 @@ matrix_panel = function (list_df2plot, df_meta, trend_period, mean_period, slice
nPeriod_trend = length(trend_period)
# Extracts the min and the max of the mean trend for all the station
- res = short_trendExtremes(list_df2plot, Code, nPeriod_trend, nbp, nCode)
+ res = short_trendExtremes(list_df2plot, Code, nPeriod_trend, nbp, nCode, colorForce)
minTrendValue = res$min
maxTrendValue = res$max
@@ -124,24 +126,34 @@ matrix_panel = function (list_df2plot, df_meta, trend_period, mean_period, slice
trendValue = df_trend_code_per$trend
}
+ # Gets the color associated to the averaged trend
+ color_res = get_color(trendValue,
+ minTrendValue[j, i],
+ maxTrendValue[j, i],
+ palette_name='perso',
+ reverse=TRUE)
+
+ pVal = df_trend_code_per$p
+
# If the p value is under the threshold
- if (df_trend_code_per$p <= alpha){
- # Gets the color associated to the averaged trend
- color_res = get_color(trendValue,
- minTrendValue[j, i],
- maxTrendValue[j, i],
- palette_name='perso',
- reverse=TRUE)
+ if (pVal <= alpha){
# Specifies the color fill and contour of
# table cells
fill = color_res
- color = 'white'
- Alpha = TRUE
+ color = color_res
+ Alpha = 'TRUE'
+
+ } else if (pVal > alpha & colorForce) {
+ # Specifies the color fill and contour of
+ # table cells
+ fill = 'white'
+ color = color_res
+ Alpha = 'FORCE'
# Otherwise it is not significative
} else {
fill = 'white'
color = 'grey85'
- Alpha = FALSE
+ Alpha = 'FALSE'
}
# Stores info needed to plot
@@ -449,6 +461,9 @@ matrix_panel = function (list_df2plot, df_meta, trend_period, mean_period, slice
plot.margin=margin(t=0, r=0, b=0, l=0, unit="mm")
)
+ colorBack = 'grey94'
+ radius = 0.43
+
# Extracts the name of the currently hydrological
# region plotted
title = df_meta[df_meta$code == subCode[1],]$region_hydro
@@ -518,42 +533,51 @@ matrix_panel = function (list_df2plot, df_meta, trend_period, mean_period, slice
# 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
+ y = height + 1.13
# Drawing of the line
mat = mat +
annotate("segment",
x=x, xend=xend,
- y=y, yend=yend,
+ y=y, yend=y,
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))))
+ # periodName =
+ # bquote(bold('Période')~bold(.(as.character(j))))
+ if (j == 1) {
+ periodName = bquote(bold("Analyse de tendance sur la série entière"))
+ } else if (j == 2) {
+ periodName = bquote(bold("Analyse de tendance sur la période commune"))
+ }
+
# Naming the period
mat = mat +
annotate("text", x=x, y=yt,
label=periodName,
hjust=0, vjust=0.5,
- size=3, color='grey40')
-
+ size=3.5, 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],
+ gg_circle(r=radius, xc=X[i], yc=Y[i],
fill=Fill_trend_per[i],
- color=Color_trend_per[i]) +
+ color=Color_trend_per[i],
+ size=0.75) +
# Plots circles for averaged of variables
- gg_circle(r=0.45, xc=Xm[i], yc=Y[i],
- fill='white', color='grey40') +
+ gg_circle(r=radius, xc=Xm[i], yc=Y[i],
+ fill=colorBack, color=colorBack,
+ size=0.75) +
# Plots circles for the column of period dates
- gg_circle(r=0.45, xc=Xc, yc=Y[i],
- fill='white', color='grey40')
+ gg_circle(r=radius, xc=Xc, yc=Y[i],
+ fill=colorBack, color=colorBack,
+ size=0.75)
}
# For all averaged trends on this periods
@@ -578,11 +602,14 @@ matrix_panel = function (list_df2plot, df_meta, trend_period, mean_period, slice
}
# If it is significative
- if (Alpha_trend_per[i]) {
+ if (Alpha_trend_per[i] == 'TRUE') {
# The text color is white
Tcolor = 'white'
- # Otherwise
- } else {
+
+ } else if (Alpha_trend_per[i] == 'FORCE') {
+ Tcolor = Color_trend_per[i]
+ # Otherwise
+ } else if (Alpha_trend_per[i] == 'FALSE') {
# The text is grey
Tcolor = 'grey85'
}
@@ -732,69 +759,128 @@ matrix_panel = function (list_df2plot, df_meta, trend_period, mean_period, slice
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
+ # # 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
+ # mat = mat +
+ # annotate("text", x=x, y=yt,
+ # label=breakName,
+ # hjust=0, vjust=0.5,
+ # size=3, color='grey40')
+ # }
+
# 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
+ if (j == 1) {
+ x = Xc_mean - 0.4
+ } else {
+ x = Xc_mean - 0.5
+ }
+ xend = Xm_mean[length(Xm_mean)] + 0.5
+ y = height + 1.13
# Drawing of the line
mat = mat +
annotate("segment",
x=x, xend=xend,
- y=y, yend=yend,
+ y=y, yend=y,
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 (j == 1) {
+ # 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('Différence entre les moyennes sur périodes de 20 ans '))
+ # Naming the period
+ mat = mat +
+ annotate("text", x=x, y=yt,
+ label=periodName,
+ hjust=0, vjust=0.5,
+ size=3.5, 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
+ x = Xr_mean[1] - 0.5
+ if (j == nPeriod_mean) {
+ xend = Xr_mean[length(Xr_mean)] + 0.25
+ } else {
+ xend = Xr_mean[length(Xr_mean)] + 0.5
+ }
# Drawing of the line
mat = mat +
annotate("segment",
x=x, xend=xend,
- y=y, yend=yend,
+ y=y, yend=y,
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 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') +
+ gg_circle(r=radius, xc=Xm_mean[i], yc=Y[i],
+ fill=colorBack, color=colorBack,
+ size=0.75) +
# Plots circles for the column of period dates
- gg_circle(r=0.45, xc=Xc_mean, yc=Y[i],
- fill='white', color='grey40')
+ gg_circle(r=radius, xc=Xc_mean, yc=Y[i],
+ fill=colorBack, color=colorBack,
+ size=0.75)
# 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],
+ gg_circle(r=radius, xc=Xr_mean[i],
+ yc=Y[i],
fill=Fill_mean_per[i],
color=Color_mean_per[i])
}
diff --git a/plotting/shortcut.R b/plotting/shortcut.R
index 76bebdfaaf684f5fb29035294ca7eda3b4a5cf8f..ca61529f75aea6bdd14bf4cf5c9a54c7be5544e7 100644
--- a/plotting/shortcut.R
+++ b/plotting/shortcut.R
@@ -25,7 +25,7 @@
## 1. EXTREMES OF VALUE FOR ALL STATION ______________________________
### 1.1. Trend _______________________________________________________
-short_trendExtremes = function (list_df2plot, Code, nPeriod_trend, nbp, nCode) {
+short_trendExtremes = function (list_df2plot, Code, nPeriod_trend, nbp, nCode, colorForce=FALSE) {
# Blank array to store mean of the trend for each
# station, perdiod and variable
@@ -48,7 +48,6 @@ short_trendExtremes = function (list_df2plot, Code, nPeriod_trend, nbp, nCode) {
df_trend = list_df2plot[[i]]$trend
# Extracts the type of the variable
type = list_df2plot[[i]]$type
- alpha = list_df2plot[[i]]$alpha
# Extracts the data corresponding to the code
df_data_code = df_data[df_data$code == code,]
df_trend_code = df_trend[df_trend$code == code,]
@@ -87,7 +86,7 @@ short_trendExtremes = function (list_df2plot, Code, nPeriod_trend, nbp, nCode) {
}
# If the p value is under the threshold
- if (df_trend_code_per$p <= alpha) {
+ if (df_trend_code_per$p <= alpha | colorForce) {
# Stores the mean trend
TrendValue_code[j, i, k] = trendValue
# Otherwise
diff --git a/plotting/tools.R b/plotting/tools.R
index 94624efcbeada58bde26fed61fa7aab3361603e6..ffa30109571349b5f36e7870361f610d638a0fe6 100644
--- a/plotting/tools.R
+++ b/plotting/tools.R
@@ -30,6 +30,7 @@
# between the min and the max of the variable
get_color = function (value, min, max, ncolor=256, palette_name='perso', reverse=FALSE) {
+
# If the value is a NA return NA color
if (is.na(value)) {
return (NA)
@@ -65,16 +66,25 @@ get_color = function (value, min, max, ncolor=256, palette_name='perso', reverse
# If the value is negative
if (value < 0) {
- # Gets the relative position of the value in respect
- # to its span
- idNorm = (value + maxAbs) / maxAbs
+ if (maxAbs == 0) {
+ idNorm = 0
+ } else {
+ # Gets the relative position of the value in respect
+ # to its span
+ idNorm = (value + maxAbs) / maxAbs
+ }
# The index corresponding
- id = round(idNorm*(ncolor - 1) + 1, 0)
+ id = round(idNorm*(ncolor - 1) + 1, 0)
# The associated color
color = palette_cold[id]
+
# Same if it is a positive value
} else {
- idNorm = value / maxAbs
+ if (maxAbs == 0) {
+ idNorm = 0
+ } else {
+ idNorm = value / maxAbs
+ }
id = round(idNorm*(ncolor - 1) + 1, 0)
color = palette_hot[id]
}
diff --git a/processing/analyse.R b/processing/analyse.R
index 7718eb5fe9e87bcdb74b2f39a92da2c97c590aa0..87b1d3d96a86654b31824f57408014dca28501df 100644
--- a/processing/analyse.R
+++ b/processing/analyse.R
@@ -128,7 +128,8 @@ get_QAtrend = function (df_data, df_meta, period, alpha, yearLac_day, df_mod=tib
na.rm=TRUE)
# Compute the trend analysis
df_QAtrend = Estimate.stats(data.extract=df_QAEx,
- level=alpha)
+ level=alpha,
+ dep.option='AR1')
# Get the associated time interval
I = interval(per[1], per[2])
@@ -204,7 +205,8 @@ get_QMNAtrend = function (df_data, df_meta, period, alpha, sampleSpan, yearLac_d
na.rm=TRUE)
# Compute the trend analysis
df_QMNAtrend = Estimate.stats(data.extract=df_QMNAEx,
- level=alpha)
+ level=alpha,
+ dep.option='AR1')
# Get the associated time interval
I = interval(per[1], per[2])
@@ -308,7 +310,8 @@ get_VCN10trend = function (df_data, df_meta, period, alpha, sampleSpan, yearLac_
na.rm=TRUE)
# Compute the trend analysis
df_VCN10trend = Estimate.stats(data.extract=df_VCN10Ex,
- level=alpha)
+ level=alpha,
+ dep.option='AR1')
# Get the associated time interval
I = interval(per[1], per[2])
@@ -494,7 +497,8 @@ get_tDEBtrend = function (df_data, df_meta, period, alpha, sampleSpan, yearLac_d
# Compute the trend analysis
df_tDEBtrend = Estimate.stats(data.extract=df_tDEBEx,
- level=alpha)
+ level=alpha,
+ dep.option='AR1')
# Get the associated time interval
I = interval(per[1], per[2])
@@ -572,7 +576,8 @@ get_tCENtrend = function (df_data, df_meta, period, alpha, sampleSpan, yearLac_d
# Compute the trend analysis
df_tCENtrend = Estimate.stats(data.extract=df_tCENEx,
- level=alpha)
+ level=alpha,
+ dep.option='AR1')
# Get the associated time interval
I = interval(per[1], per[2])
diff --git a/script.R b/script.R
index 75c35ab4d5de3ccadf0fd90a4f4d7e9e837357e0..d5b18e8af32dd5c3abe4f3df79b10593ae17fb71 100644
--- a/script.R
+++ b/script.R
@@ -55,21 +55,22 @@ filedir =
# Name of the file that will be analysed from the BH directory
# (if 'all', all the file of the directory will be chosen)
filename =
- # ""
+ ""
# "all"
- c(
+ # c(
# "S2235610_HYDRO_QJM.txt",
# "P1712910_HYDRO_QJM.txt",
# "P0885010_HYDRO_QJM.txt",
# "O5055010_HYDRO_QJM.txt",
# "O0384010_HYDRO_QJM.txt",
# "S4214010_HYDRO_QJM.txt",
- "Q7002910_HYDRO_QJM.txt"
- # "Q0214010_HYDRO_QJM.txt"
+ # "Q7002910_HYDRO_QJM.txt",
+ # "Q0214010_HYDRO_QJM.txt",
# "O3035210_HYDRO_QJM.txt",
# "O0554010_HYDRO_QJM.txt",
- # "O1584610_HYDRO_QJM.txt"
- )
+ # "Q6332510_HYDRO_QJM.txt"
+ # "O8255010_HYDRO_QJM.txt"
+ # )
## AGENCE EAU ADOUR GARONNE SELECTION
@@ -79,8 +80,8 @@ AEAGlistdir =
""
AEAGlistname =
- ""
- # "Liste-station_RRSE.docx"
+ # ""
+ "Liste-station_RRSE.docx"
## NIVALE SELECTION
@@ -118,7 +119,7 @@ sampleSpan = c('05-01', '11-30')
## MAP
# Is the hydrological network needs to be plot
-is_river = FALSE
+is_river = TRUE
############### END OF REGION TO MODIFY (without risk) ###############
@@ -361,68 +362,69 @@ df_shapefile = ini_shapefile(resources_path,
### 5.1. Simple time panel to criticize station data _________________
# Plot time panel of debit by stations
-datasheet_layout(toplot=c('datasheet'),
- df_meta=df_meta,
- df_data=list(df_data,
- df_sqrt),
- var=list('Q', 'sqrt(Q)'),
- type=list('data', 'data'),
- layout_matrix=matrix(c(1, 2), ncol=1),
- info_header=df_data,
- df_shapefile=df_shapefile,
- figdir=figdir,
- resources_path=resources_path,
- logo_dir=logo_dir,
- AEAGlogo_file=AEAGlogo_file,
- INRAElogo_file=INRAElogo_file,
- FRlogo_file=FRlogo_file)
-
-
-### 5.2. Analysis layout _____________________________________________
-# datasheet_layout(toplot=c(
-# 'datasheet'
-# # 'matrix',
-# # 'map'
-# ),
+# datasheet_layout(toplot=c('datasheet'),
# df_meta=df_meta,
-
-# df_data=list(
-# res_QAtrend$data,
-# res_QMNAtrend$data,
-# res_VCN10trend$data,
-# res_tDEBtrend$data,
-# res_tCENtrend$data
-# ),
-
-# df_trend=list(
-# res_QAtrend$trend,
-# res_QMNAtrend$trend,
-# res_VCN10trend$trend,
-# res_tDEBtrend$trend,
-# res_tCENtrend$trend
-# ),
-
-# var=var,
-# type=type,
-# glose=glose,
-
-# layout_matrix=matrix(c(1, 2, 3, 4, 5), ncol=1),
-
-# missRect=TRUE,
-# trend_period=trend_period,
-# mean_period=mean_period,
+# df_data=list(df_data,
+# df_sqrt),
+# var=list('Q', 'sqrt(Q)'),
+# type=list('data', 'data'),
+# layout_matrix=matrix(c(1, 2), ncol=1),
# info_header=df_data,
-# time_header=df_data,
-# foot_note=TRUE,
-# info_height=2.8,
-# time_ratio=2,
-# var_ratio=3,
-# foot_height=1.25,
# df_shapefile=df_shapefile,
# figdir=figdir,
-# filename_opt='',
# resources_path=resources_path,
# logo_dir=logo_dir,
# AEAGlogo_file=AEAGlogo_file,
# INRAElogo_file=INRAElogo_file,
# FRlogo_file=FRlogo_file)
+
+
+### 5.2. Analysis layout _____________________________________________
+datasheet_layout(toplot=c(
+ 'datasheet',
+ 'matrix',
+ 'map'
+ ),
+ df_meta=df_meta,
+
+ df_data=list(
+ res_QAtrend$data,
+ res_QMNAtrend$data,
+ res_VCN10trend$data,
+ res_tDEBtrend$data,
+ res_tCENtrend$data
+ ),
+
+ df_trend=list(
+ res_QAtrend$trend,
+ res_QMNAtrend$trend,
+ res_VCN10trend$trend,
+ res_tDEBtrend$trend,
+ res_tCENtrend$trend
+ ),
+
+ var=var,
+ type=type,
+ glose=glose,
+
+ layout_matrix=matrix(c(1, 2, 3, 4, 5), ncol=1),
+
+ missRect=TRUE,
+ trend_period=trend_period,
+ mean_period=mean_period,
+ colorForce=TRUE,
+ info_header=df_data,
+ time_header=df_data,
+ foot_note=TRUE,
+ info_height=2.8,
+ time_ratio=2,
+ var_ratio=3,
+ foot_height=1.25,
+ df_shapefile=df_shapefile,
+ figdir=figdir,
+ filename_opt='',
+ resources_path=resources_path,
+ logo_dir=logo_dir,
+ AEAGlogo_file=AEAGlogo_file,
+ INRAElogo_file=INRAElogo_file,
+ FRlogo_file=FRlogo_file)