Commit d090c5c7 authored by unknown's avatar unknown
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v1.0.3 vignette updated

parent 947b9698
......@@ -42,7 +42,7 @@ OutputsModel <- RunModel_GR4J(InputsModel = InputsModel, RunOptions = RunOptions
str(OutputsModel)
## ----eval=F--------------------------------------------------------------
# plot_OutputsModel(OutputsModel = OutputsModel, Qobs = BasinObs$Qmm[Ind_Run])
# plot(OutputsModel, Qobs = BasinObs$Qmm[Ind_Run])
## ------------------------------------------------------------------------
OutputsCrit <- ErrorCrit_NSE(InputsCrit = InputsCrit, OutputsModel = OutputsModel)
......
......@@ -230,18 +230,18 @@ str(OutputsModel)
## Results preview
Although it is possible for the user to design its own graphics from the outputs of the `RunModel*()` functions, the **airGR** package offers the possibility to make use of the `plot_OutputsModel()` function. This function returns a dashboard of results including various graphs (depending on the model used):
Although it is possible for the user to design its own graphics from the outputs of the `RunModel*()` functions, the **airGR** package offers the possibility to make use of the `plot.OutputsModel()` function (or `plotl()` with a `OutputsModel` object). This function returns a dashboard of results including various graphs (depending on the model used):
* time series of total precipitation and simulated streamflows (and observed streamflows if provided)
* interannual median monthly simulated streamflows (and monthly observed streamflows if provided)
* correlation plot between simulated and observed streamflows (if observed streamflows provided)
* cumulative frequency plot for simulated streamflows (and for observed streamflows if provided)
* correlation plot between simulated and observed streamflows (if observed streamflows provided)
```{r,eval=F}
plot_OutputsModel(OutputsModel = OutputsModel, Qobs = BasinObs$Qmm[Ind_Run])
plot(OutputsModel, Qobs = BasinObs$Qmm[Ind_Run])
```
Moreover, if the CemaNeige model is used, the simulated snowpack time series are plotted.
Moreover, if the CemaNeige model is used, the temperature and the simulated snowpack time series are plotted.
## Efficiency criterion
......
......@@ -95,6 +95,16 @@ code > span.in { color: #60a0b0; font-weight: bold; font-style: italic; } /* Inf
<p>In the following example, we use a data sample contained in the package. For real applications, the user has to import its data into <strong>R</strong> and to prepare it with an adequate data.frame format as described below.</p>
<p>First, it is necessary to load the <strong>airGR</strong> package:</p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">library</span>(airGR)</code></pre></div>
<pre><code>##
## To cite airGR in publications use these two references:
##
## Coron, L., Thirel, G., Delaigue, O., Perrin, C. and Andréassian,
## V. (submitted). airGR: A suite of lumped hydrological models in
## an R-package. Environmental Modelling and software.
##
## Coron, L., Perrin, C. and Michel, C. (2017). airGR: Suite of GR
## hydrological models for precipitation-runoff modelling. R
## package version 1.0.4. https://webgr.irstea.fr/airGR/?lang=en.</code></pre>
<p>This is an example of a <code>data.frame</code> of hydrometeorological observations time series for a fictional catchment included in the <strong>airGR</strong> package that contains:</p>
<ul>
<li><em>DatesR</em>: dates in the POSIXt format</li>
......@@ -297,15 +307,15 @@ Param</code></pre></div>
</div>
<div id="results-preview" class="section level2">
<h2>Results preview</h2>
<p>Although it is possible for the user to design its own graphics from the outputs of the <code>RunModel*()</code> functions, the <strong>airGR</strong> package offers the possibility to make use of the <code>plot_OutputsModel()</code> function. This function returns a dashboard of results including various graphs (depending on the model used):</p>
<p>Although it is possible for the user to design its own graphics from the outputs of the <code>RunModel*()</code> functions, the <strong>airGR</strong> package offers the possibility to make use of the <code>plot.OutputsModel()</code> function (or <code>plotl()</code> with a <code>OutputsModel</code> object). This function returns a dashboard of results including various graphs (depending on the model used):</p>
<ul>
<li>time series of total precipitation and simulated streamflows (and observed streamflows if provided)</li>
<li>interannual median monthly simulated streamflows (and monthly observed streamflows if provided)</li>
<li>correlation plot between simulated and observed streamflows (if observed streamflows provided)</li>
<li>cumulative frequency plot for simulated streamflows (and for observed streamflows if provided)</li>
<li>correlation plot between simulated and observed streamflows (if observed streamflows provided)</li>
</ul>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">plot_OutputsModel</span>(<span class="dt">OutputsModel =</span> OutputsModel, <span class="dt">Qobs =</span> BasinObs$Qmm[Ind_Run])</code></pre></div>
<p>Moreover, if the CemaNeige model is used, the simulated snowpack time series are plotted.</p>
<div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="kw">plot</span>(OutputsModel, <span class="dt">Qobs =</span> BasinObs$Qmm[Ind_Run])</code></pre></div>
<p>Moreover, if the CemaNeige model is used, the temperature and the simulated snowpack time series are plotted.</p>
</div>
<div id="efficiency-criterion" class="section level2">
<h2>Efficiency criterion</h2>
......
......@@ -230,18 +230,18 @@ str(OutputsModel)
## Results preview
Although it is possible for the user to design its own graphics from the outputs of the `RunModel*()` functions, the **airGR** package offers the possibility to make use of the `plot_OutputsModel()` function. This function returns a dashboard of results including various graphs (depending on the model used):
Although it is possible for the user to design its own graphics from the outputs of the `RunModel*()` functions, the **airGR** package offers the possibility to make use of the `plot.OutputsModel()` function (or `plotl()` with a `OutputsModel` object). This function returns a dashboard of results including various graphs (depending on the model used):
* time series of total precipitation and simulated streamflows (and observed streamflows if provided)
* interannual median monthly simulated streamflows (and monthly observed streamflows if provided)
* correlation plot between simulated and observed streamflows (if observed streamflows provided)
* cumulative frequency plot for simulated streamflows (and for observed streamflows if provided)
* correlation plot between simulated and observed streamflows (if observed streamflows provided)
```{r,eval=F}
plot_OutputsModel(OutputsModel = OutputsModel, Qobs = BasinObs$Qmm[Ind_Run])
plot(OutputsModel, Qobs = BasinObs$Qmm[Ind_Run])
```
Moreover, if the CemaNeige model is used, the simulated snowpack time series are plotted.
Moreover, if the CemaNeige model is used, the temperature and the simulated snowpack time series are plotted.
## Efficiency criterion
......
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