README.Rmd

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Tool to estimate bicycle flows throughout the network of metropolitan Paris, France.

## How?

Start by installing and loading the package:

```{r load, eval = FALSE}
remotes::install_github ("UrbanAnalyst/paris-bikes")
library (parisbikes)
```

Then just two steps. First, get the street network of Paris (or anywhere) from Open Street Map.

```{r get-network, eval = FALSE}
path <- "<local>/<directory>/<for>/<paris>/<data>"
pb_get_network (location = "Paris France", path)
```

That function will create a file called "paris-sc.Rds" in the location
specified by "path". Then load the resultant network and use that to calculate
centrality:

```{r centrality, eval = FALSE}
dat <- readRDS ("/<path>/<to>/paris-sc.Rds")
network <- pb_centrality (dat, mode = "bicycle")
```

It is also possible to calculate centrality including the effects of elevation
changes, by specifying an additional "elev_file" parameter as the path to a
local 'geotiff' elevation file. See the function documentation of
`pb_centrality` for details.

## Visualising the results

The following code can be used to visualise the resultant network centrality,
using [the `mapdeck` package](https://symbolixau.github.io/mapdeck/index.html)
(which first requires an API token, as explained in the documentation). The
following code rescales the centrality measures using a value of 3.71 derived
elsewhere to optimally match observed distributions of cycling densities in
Paris.

```{r viz, eval = FALSE}
index <- which (network$centrality > 0)
network <- dodgr::merge_directed_graph (network [index, ])
network$flow <- network$centrality / max (network$centrality)
network$flow <- network$flow ^ (1 / 3.71)
network$width <- 5 * network$flow
```

The following lines will then open an interactive visualization of the flow
densities throughout Paris.

```{r mapdeck, eval = FALSE}
library (mapdeck)
mapdeck (style = mapdeck_style ()) %>%
    add_line (net, 
              origin = c (".vx0_x", ".vx0_y"),
              destination = c (".vx1_x", ".vx1_y"),
              stroke_colour = "flow",
              stroke_width = "width",
              stroke_opacity = "flow",
              palette = "matlab_like2",
              legend = TRUE)
```