plot_sample | R Documentation |
x
and y
It makes a plot by sampling (e.g. monthly) the variables x
and y
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 = 1e-04,
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 |
... |
see graphical parametes on @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 = 1e-04, 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), ...) |
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 one-dimensional Gaussianization of x
through the function normalizeGaussian_severalstations
.
plot.default
,extractmonths
, see normalizeGaussian_severalstations
## Not run:
library(lubridate)
data(trentino)
plot_sample(x=TEMPERATURE_MIN$T0090,sample="monthly",
origin="1958-1-1",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")
## End(Not run)
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