Description Usage Arguments Value Note See Also Examples
It makes a plot by sampling (e.g. monthly) the variables x
and y
1 2 3 4 5 6 7 8 9 10 11  plot_sample(x, y = normalizeGaussian_severalstations(x = as.data.frame(x),
data = as.data.frame(data), origin_x = origin_x, origin_data = origin_data,
sample = sample, step = step, prec = prec)[, 1], xlim = range(x, na.rm =
TRUE), legend_position = "topleft", ylim = range(y, na.rm = TRUE),
pch = 1, col = 1, col_max = 0.9, col_min = 0.1, origin,
sample = NULL, xhist = hist(x, breaks = breaks, plot = FALSE),
yhist = hist(y, breaks = breaks, plot = FALSE), axes = FALSE,
step = NULL, prec = 1e04, breaks = 50, origin_x = origin,
origin_data = origin, data = x, xlab = "", ylab = "", color = FALSE,
gray = TRUE, sort = FALSE, valmin_x = valmin, valmin_y = valmin,
valmin = 9999, abline = c(0, 1), ...)

x 
vector of input data 
y 
vector of second input data. Default is 
xlim, ylim, xlab, ylab 
see 
legend_position 
legend position. Default is 
pch 
integer single or multi values for 
col 
integer single or multi values for 
col_max 
maximum value for color scale to apply to 
col_min 
minimum value for color scale to apply to 
origin 
date of the first row of 
sample 
string character containg informatio how to sample 
xhist 
frequency histogram for 
yhist 
frequency histogram for 
axes 
see 
step, prec 
see 
breaks 
see 
origin_x 
see 
origin_data 

data 

color 
logical value. If 
gray 
logical value. If 
sort 
logical value. If 
valmin_x 
numerical threshold value over which the variable 
valmin_y 
numerical threshold value over which the variable 
valmin 
numerical threshold value for 
abline 
arguments for @usage plot_sample(x, y = normalizeGaussian_severalstations(x = as.data.frame(x), data = as.data.frame(data), origin_x = origin_x, origin_data = origin_data, sample = sample, step = step, prec = prec)[, 1], xlim = range(x, na.rm = TRUE), legend_position = "topleft", ylim = range(y, na.rm = TRUE), pch = 1, col = 1, col_max = 0.9, col_min = 0.1, origin, sample = NULL, xhist = hist(x, breaks = breaks, plot = FALSE), yhist = hist(y, breaks = breaks, plot = FALSE), axes = FALSE, step = NULL, prec = 1e04, breaks = 50, origin_x = origin, origin_data = origin, data = x, xlab = "", ylab = "", color = FALSE, gray = TRUE, sort = FALSE, valmin_x = valmin, valmin_y = valmin, valmin = 9999, abline = c(0, 1), ...) 
... 
see graphical parametes on 
0 in case of success
It makes a plot betwee x
and y
and shows thair respective probibilty histograms.
If y
is missing, it is automatically calculated as onedimensional Gaussianization of x
through the function normalizeGaussian_severalstations
.
plot.default
,extractmonths
, see normalizeGaussian_severalstations
1 2 3 4 5 6 7 8 9 10  library(RMAWGEN)
data(trentino)
plot_sample(x=TEMPERATURE_MIN$T0090,sample="monthly",
origin="195811",axes=FALSE,xlab="Tn [ degC]",
ylab="x")
set.seed(123456)
z < rexp(10000,rate=0.5)
x < normalizeGaussian(x=z,data=z)
plot_sample(x=z,xlab="z",ylab="x")

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