plot {airGRteaching}R Documentation

Static plots for time series of PrepGR, CalGR and SimGR objects

Description

Static plots for time series of PrepGR, CalGR and SimGR objects. Also plot of the evolution of parameters and objective function during the calibration step for CalGR object.

Usage

## S3 method for class 'PrepGR'
plot(x, type = "l",
     col.Precip = "royalblue", col.Q = "black", col.na = "grey",
     xlab = NULL, ylab = NULL, main = NULL,
     plot.na = TRUE, ...)

## S3 method for class 'CalGR'
plot(x, xlab = NULL, ylab = NULL, main = NULL,
     which = c("perf", "iter", "ts"), ...)

## S3 method for class 'SimGR'
plot(x, ...)

Arguments

x

[PrepGR], [CalGR] or [SimGR] containing the vector of dates (POSIXt) and the time series of numeric values list perturbed inputs and DA model outputs (see PrepGR, CalGR and SimGR)

type

[character] the type of plot that should be drawn (see plot for details)

col.Precip

(optional) [character]color code or name for precipitation, see par

col.Q

(optional) [character] color code or name for observed flow, see par

col.na

(optional) [character] color code or name for missing values, see par

xlab

(optional) [character] a label for the x-axis (see title)

ylab

(optional) [character] a label for the y-axis (vector of 1 or 2 values for rainfall and flow respectively; see title)

main

(optional) [character] a main title for the plot (see title)

plot.na

[boolean] boolean indicating if the missing values are plotted on the x-axis

which

[character] choice of the plot type ("perf" (default): plot diagnostics; "iter": parameter and calibration criterion values during the iterations of the steepest descent step of the airGR calibration algorithm; "ts": time series of observed precipitation and observed and simulated flows)

...

other parameters to be passed through to plotting functions

Author(s)

Olivier Delaigue

See Also

airGR plot.OutputsModel function

airGRteaching dyplot function to display dynamic plots

PrepGR, CalGR, SimGR

Examples

library(airGRteaching)

## data.frame of observed data
data(L0123001, package = "airGR")
BasinObs2 <- BasinObs[, c("DatesR", "P", "E", "Qmm", "T")]

## Preparation of observed data for modelling
PREP <- PrepGR(ObsDF = BasinObs2, HydroModel = "GR4J", CemaNeige = FALSE)

## Observed data plotting
plot(PREP)

[Package airGRteaching version 0.2.11 Index]