Commit aba79227 authored by unknown's avatar unknown
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v0.2.2.1 vignette updated for CRAN-compatibility

parent e5a23d18
Package: airGRteaching
Type: Package
Title: Teaching Hydrological Modelling with the GR Rainfall-Runoff Models ('Shiny' Interface Included)
Version: 0.2.2.0
Date: 2018-03-20
Version: 0.2.2.1
Date: 2018-03-21
Authors@R: c(person("Olivier", "Delaigue", role = c("aut", "cre"), email = "airGR@irstea.fr"), person("Laurent", "Coron", role = c("aut")), person("Pierre", "Brigode", role = c("aut")), person("Guillaume", "Thirel", role = c("ctb")))
Depends: airGR (>= 1.0.9.43)
Imports: dygraphs (>= 1.1.1.4), htmlwidgets (>= 1.0), markdown, plotrix, shiny, shinyjs, xts
Suggests: knitr, webshot
Suggests: knitr, rmarkdown
Description: Add-on package to the 'airGR' package that simplifies its use and is aimed at being used for teaching hydrology. The package provides 1) three functions that allow to complete very simply a hydrological modelling exercise 2) plotting functions to help students to explore observed data and to interpret the results of calibration and simulation of the GR ('Génie rural') models 3) a 'Shiny' graphical interface that allows for displaying the impact of model parameters on hydrographs and models internal variables.
License: GPL-2
NeedsCompilation: no
URL: https://webgr.irstea.fr/en/airGR/
Encoding: UTF-8
VignetteBuilder: knitr, webshot
VignetteBuilder: knitr, rmarkdown
############# Release History of the airGRteaching Package
## 0.2.2.0 Release Notes (2018-03-20)
## 0.2.2.1 Release Notes (2018-03-21)
Bug fixes
- bug fixed in ShinyGR(), the criteria values are now right on Unix system
......@@ -10,7 +10,7 @@
- vignette added
## 0.2.0.9 Release Notes (2018-03-15)
## 0.2.0.9 Release Notes (2018-03-16)
CRAN-compatibility updates
- embeding dygraphs functions to avoid user to install the last version of this package from GitHub (import of devtools not necessary)
......
......@@ -112,7 +112,7 @@ plot(PREP, main = "Observation")
By default (with the argument `which = "perf"`), the call of the `plot()` function with a `CalGR` object draws the classical `r airGR` plot diagnostics (observed and simulated time series together with diagnostic plot)
```{r, fig.width=7*1.5, fig.height=4.25*1.5, dev.args=list(pointsize=14), echo=TRUE, eval=FALSE}
```{r, echo=TRUE, eval=FALSE}
plot(CAL, which = "perf")
```
```{r, fig.width=7*1.5, fig.height=4.25*1.5, dev.args=list(pointsize=14), echo=FALSE, warning=FALSE}
......@@ -133,7 +133,7 @@ plot(CAL, which = "ts", main = "Calibration")
```
The call of the `plot()` function with a `SimGR` object draws the classical `r airGR` plot diagnostics.
```{r, fig.width=7*1.5, fig.height=4.25*1.5, dev.args=list(pointsize=14), eval=FALSE}
```{r, eval=FALSE}
plot(SIM)
```
......@@ -149,7 +149,7 @@ The user can zoom on the plot device and can read the exact values.
With this function, users can easily explore the data time series and also explore and interpret the possible problems of the calibration or simulation steps.
```{r, fig.width=7*1.5, fig.height=3.25*1.5, dev.args=list(pointsize=14), eval=TRUE}
```{r, eval=FALSE}
dyplot(SIM, main = "Simulation")
```
......
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