plotting.Rmd

```{r, echo = FALSE}
suppressPackageStartupMessages(library("foehnix"))
```

## Windrose

The `foehnix` package comes with methods to create windrose plot for
foehn classification models (see [getting started](foehnix.html),
[`foehnix reference`](../references/foehnix.html)) and observation
data. Two types of windrose plots are available:

* **density**: empirical density
* **histogram**: empirical circular histogram

### Windrose Plot for Observation Data

The [`windrose`](../references/windrose.html) function can be called
with a set of (observed) wind direction and wind speed values. Wind
direction has to be the meteorological wind direction in degrees
(`[0, 360]`, `0` and `360` corresponds to wind coming from North,
`90` for wind from East, `180` for wind from South, and `270` from
West).


```{r, echo = TRUE, figure = TRUE, fig.width = 10, fig.height = 5}
# Loading the demo data set for station Ellboegen
data <- demodata("ellboegen")
print(head(data))

# Plotting windrose
windrose(data$dd, data$ff, type = "density")
windrose(as.numeric(data$dd), as.numeric(data$ff), type = "histogram")
```

### Windrose Plot for foehnix Models

Windrose plots can also be created for `foehnix` foehn classification
models if wind speed and wind direction information has been provided
to the [`foehnix`](../references/foehnix.html) function when estimating
the classification model.

```{r, echo = TRUE, figure = TRUE, fig.width = 8, fig.height = 5}
# Loading the demo data set for Tyrol (Ellboegen and Innsbruck)
data <- demodata("tyrol") # default
print(head(data))

# Estimate a foehnix classification model
filter <- list(dd = c(43, 223), crest_dd = c(90, 270))
mod <- foehnix(diff_t ~ ff + rh, data = data, filter = filter,
               switch = TRUE, verbose = FALSE)

# Plotting windroses
windrose(mod)
```

By default, `windrose` expects that the parameters are called `dd` (wind direction)
and `ff` (wind speed), however, custom names can also be used.

```{r, echo = TRUE, figure = TRUE, fig.width = 8, fig.height = 5}
# Loading the demo data set for station Ellboegen and Sattelberg (combined)
data <- demodata("tyrol") # default
names(data) <- gsub("dd$", "winddir", names(data))
names(data) <- gsub("ff$", "windspd", names(data))
print(head(data))

# Estimate a foehnix classification model
filter <- list(winddir = c(43, 223), crest_winddir = c(90, 270))
mod <- foehnix(diff_t ~ windspd + rh, data = data, filter = filter,
               switch = TRUE, verbose = FALSE)

# Plotting windroses
windrose(mod, ddvar = "winddir", ffvar = "windspd")
```


## Default Time Series Plot

TODO: Write vignette.

```{r, echo = TRUE, figure = TRUE, fig.width = 8, fig.height = 8}
# Loading the demo data set for station Ellboegen and Sattelberg (combined)
data <- demodata("tyrol")
filter <- list(dd = c(43, 223), crest_dd = c(90, 270))
mod <- foehnix(diff_t ~ ff + rh, data = data, filter = filter,
               switch = TRUE, verbose = FALSE)

# Time Series Plot
tsplot(mod, start = "2018-03-01", end = "2018-03-20")
```