---
title: "Get started"
output: bookdown::html_vignette2
vignette: >
  %\VignetteIndexEntry{Get started}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

Welcome to the slopes vignette, a type of long-form documentation/article that introduces the core functions and functionality of the `slopes` package.

# Installation

You can install the released version of slopes from [CRAN](https://CRAN.R-project.org) with:

```r
install.packages("slopes")
```

Install the development version from [GitHub](https://github.com/) with:

```{r, eval=FALSE}
# install.packages("remotes")
remotes::install_github("ropensci/slopes")
```

### Installation for DEM downloads

If you do not already have DEM data and want to make use of the package's ability to download them using the `ceramic` package, install the package with suggested dependencies, as follows:

```{r, eval=FALSE}
# install.packages("remotes")
remotes::install_github("ropensci/slopes", dependencies = "Suggests")
```

Furthermore, you will need to add a MapBox API key to be able to get DEM datasets, by signing up and registering for a key at `https://account.mapbox.com/access-tokens/` and then following these steps:

```{r, eval=FALSE}
usethis::edit_r_environ()
# Then add the following line to the file that opens:
# MAPBOX_API_KEY=xxxxx # replace XXX with your api key
```


# Functions 

## Elevation

- `elevation_add()` Take a linestring and add a third dimension (z) to its coordinates
- `elevation_get()` Get elevation data from hosted maptile services (returns a `SpatRaster`)
- `elevation_extract()` Extract elevations from coordinates

## Slope calculation

- `slope_vector()` Calculate the gradient of line segments from distance and elevation vectors
- `slope_distance()` Calculate the slopes associated with consecutive distances and elevations
- `slope_distance_mean()` Calculate the mean average slopes associated with consecutive distances and elevations
- `slope_distance_weighted()` Calculate the slopes associated with consecutive distances and elevations, weighted by distance
- `slope_matrix()` Calculate the slope of lines based on a DEM matrix
- `slope_matrix_mean()` Calculate the mean slope of lines based on a DEM matrix
- `slope_matrix_weighted()` Calculate the weighted mean slope of lines based on a DEM matrix
- `slope_raster()` Calculate the slope of lines based on a raster DEM
- `slope_xyz()` Calculate the slope of lines based on XYZ coordinates

## Plotting

- `plot_slope()` Plot slope data for a 3d linestring

## Helper functions

- `sequential_dist()` Calculate cumulative distances along a linestring
- `z_value()` Extract Z coordinates from an `sfc` object
- `z_start()` Get the starting Z coordinate
- `z_end()` Get the ending Z coordinate
- `z_mean()` Calculate the mean Z coordinate
- `z_max()` Get the maximum Z coordinate
- `z_min()` Get the minimum Z coordinate
- `z_elevation_change_start_end()` Calculate the elevation change from start to end
- `z_direction()` Determine the direction of slope (uphill/downhill)
- `z_cumulative_difference()` Calculate the cumulative elevation difference

# Examples

This section shows some basic examples of how to use the `slopes` package.

First, load the necessary packages and data:

```{r}
library(slopes)
library(sf)

# Load example data
data(lisbon_route)
dem_lisbon <- dem_lisbon()
```

## Add elevation to a linestring

If you have a 2D linestring and a DEM, you can add elevation data to the linestring using `elevation_add()`:

```{r}
sf_linestring_xyz_local <- elevation_add(lisbon_route, dem = dem_lisbon)
head(sf::st_coordinates(sf_linestring_xyz_local))
```

If you don't have a local DEM, `elevation_add()` can download elevation data (this requires a MapBox API key and the `ceramic` package):

```{r, eval=FALSE}
# Requires a MapBox API key and the ceramic package
# sf_linestring_xyz_mapbox = elevation_add(lisbon_route)
# head(sf::st_coordinates(sf_linestring_xyz_mapbox))
```

## Calculate slope

Once you have a 3D linestring (with XYZ coordinates), you can calculate its average slope using `slope_xyz()`:

```{r}
slope <- slope_xyz(sf_linestring_xyz_local)
slope
```

## Plot elevation profile

You can visualize the elevation profile of a 3D linestring using `plot_slope()`:

```{r}
# ensure a palette and breaks exist
brks <- c(3, 6, 10, 20, 40, 100)
pal <- slopes_palette(length(brks) - 1)

plot_slope(sf_linestring_xyz_local, pal = pal, brks = brks)
```

## Working with segments

The `slopes` package can also work with individual segments of a linestring.
There are two ways to split a route into segments:

### By vertex (native segments of the linestring)

`route_to_segments()` splits the route at every existing vertex, producing one 2-point segment per coordinate pair:

```{r}
lisbon_route_xyz <- elevation_add(lisbon_route, dem = dem_lisbon())
lisbon_route_segments_xyz <- route_to_segments(lisbon_route_xyz)
lisbon_route_segments_xyz$slope <- slope_xyz(lisbon_route_segments_xyz)
summary(lisbon_route_segments_xyz$slope)
```

```{r}
plot(st_geometry(lisbon_route_segments_xyz),
  col = heat.colors(length(lisbon_route_segments_xyz$slope))[rank(lisbon_route_segments_xyz$slope)],
  lwd = 3, main = "Slope by vertex segments"
)
```

### By fixed length (using stplanr)

`stplanr::line_segment()` splits the route into segments of a given length (e.g. 100 m).
Elevation must be added after segmenting, since the new endpoints won't have Z coordinates yet:

```{r warning=FALSE}
lisbon_route_100m <- stplanr::line_segment(lisbon_route, segment_length = 100)
lisbon_route_100m_xyz <- elevation_add(lisbon_route_100m, dem = dem_lisbon())
lisbon_route_100m_xyz$slope <- slope_xyz(lisbon_route_100m_xyz)
summary(lisbon_route_100m_xyz$slope)
```

```{r}
plot(st_geometry(lisbon_route_100m_xyz),
  col = heat.colors(length(lisbon_route_100m_xyz$slope))[rank(lisbon_route_100m_xyz$slope)],
  lwd = 3, main = "Slope by 100 m segments"
)
```

This vignette provides a basic overview. For more detailed information and advanced use cases, please refer to the other vignettes and the function documentation.