diff --git a/plotting/layout.R b/plotting/layout.R
index 80233e166cb465b633abcc5a41c0727d0ecbf248..b77da5a77f1b5dcc6fac02e6611f8dccf9d809d5 100644
--- a/plotting/layout.R
+++ b/plotting/layout.R
@@ -42,6 +42,7 @@ library(RColorBrewer)
library(rgdal)
library(shadowtext)
+
# Sourcing R file
source('plotting/datasheet.R', encoding='UTF-8')
source('plotting/map.R', encoding='UTF-8')
diff --git a/plotting/matrix.R b/plotting/matrix.R
index 4b7ef422a5ec7d52b996d58e38c6ea03b85220ba..b4e37f050b06d48523e5b275f964d11c7f9aeb4c 100644
--- a/plotting/matrix.R
+++ b/plotting/matrix.R
@@ -180,7 +180,8 @@ matrix_panel = function (list_df2plot, df_meta, trend_period, mean_period, slice
# Blank vectors to store info about trend analyses
Periods_trend = c()
NPeriod_trend = c()
- Var_trend = list()
+ Var_trend = c()
+ Type_trend = c()
Code_trend = c()
Pthresold_trend = c()
TrendMean_trend = c()
@@ -201,6 +202,8 @@ matrix_panel = function (list_df2plot, df_meta, trend_period, mean_period, slice
p_threshold = list_df2plot[[i]]$p_threshold
# Extract the variable of the plot
var = list_df2plot[[i]]$var
+ # Extract the type of the variable to plot
+ type = list_df2plot[[i]]$type
# Extracts the data corresponding to the code
df_data_code = df_data[df_data$code == code,]
# Extracts the trend corresponding to the code
@@ -257,6 +260,7 @@ matrix_panel = function (list_df2plot, df_meta, trend_period, mean_period, slice
Periods_trend = append(Periods_trend, Periods)
NPeriod_trend = append(NPeriod_trend, j)
Var_trend = append(Var_trend, var)
+ Type_trend = append(Type_trend, type)
Code_trend = append(Code_trend, code)
Pthresold_trend = append(Pthresold_trend, Pthresold)
TrendMean_trend = append(TrendMean_trend, trendMean)
@@ -272,7 +276,8 @@ matrix_panel = function (list_df2plot, df_meta, trend_period, mean_period, slice
# Blank vectors to store info about breaking analysis
Periods_mean = c()
NPeriod_mean = c()
- Var_mean = list()
+ Var_mean = c()
+ Type_mean = c()
Code_mean = c()
DataMean_mean = c()
BreakMean_mean = c()
@@ -303,6 +308,8 @@ matrix_panel = function (list_df2plot, df_meta, trend_period, mean_period, slice
df_data = list_df2plot[[i]]$data
# Extract the variable of the plot
var = list_df2plot[[i]]$var
+ # Extract the type of the variable to plot
+ type = list_df2plot[[i]]$type
# Extracts the data corresponding to the code
df_data_code = df_data[df_data$code == code,]
@@ -347,6 +354,7 @@ matrix_panel = function (list_df2plot, df_meta, trend_period, mean_period, slice
Periods_mean = append(Periods_mean, Periods)
NPeriod_mean = append(NPeriod_mean, j)
Var_mean = append(Var_mean, var)
+ Type_mean = append(Type_mean, type)
Code_mean = append(Code_mean, code)
DataMean_mean = append(DataMean_mean, dataMean)
BreakMean_mean = append(BreakMean_mean,
@@ -399,6 +407,10 @@ 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
@@ -436,6 +448,7 @@ matrix_panel = function (list_df2plot, df_meta, trend_period, mean_period, slice
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]
@@ -449,6 +462,7 @@ matrix_panel = function (list_df2plot, df_meta, trend_period, mean_period, slice
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]
@@ -502,6 +516,8 @@ matrix_panel = function (list_df2plot, df_meta, trend_period, mean_period, slice
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 =
@@ -684,6 +700,8 @@ matrix_panel = function (list_df2plot, df_meta, trend_period, mean_period, slice
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 =
@@ -838,8 +856,6 @@ matrix_panel = function (list_df2plot, df_meta, trend_period, mean_period, slice
hjust=0.5, vjust=0.5,
size=3.25, color='grey20')
- library(ggtext)
-
# If this is not the first period
if (j > 1) {
mat = mat +
@@ -850,23 +866,11 @@ matrix_panel = function (list_df2plot, df_meta, trend_period, mean_period, slice
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=expr(Delta*!!var),
- # bquote('d'*.(var)),
- # hjust=0.5, vjust=0.5,
- # size=3.25, color='grey20')
-
- geom_richtext(aes(x=Xr_mean[i],
- y=max(Y) + 0.9,
- label="delta"),
- hjust=0.5, vjust=0.5,
- size=3.25, color='grey20',
- fill=NA, label.color=NA,
- label.padding=
- grid::unit(rep(0, 4),
- "pt"))
-
+ 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')
}
}
@@ -955,7 +959,8 @@ matrix_panel = function (list_df2plot, df_meta, trend_period, mean_period, slice
ggsave(plot=mat,
path=outdirTmp,
filename=paste(outnameTmp, '_', fL,
- imat, '.pdf', sep=''),
+ imat, sep=''),
+ device='pdf',
width=width, height=height,
units='cm', dpi=dpi)
}