From 40e3dbda6667045a7640523fcdf21604867c78ca Mon Sep 17 00:00:00 2001 From: emilio-berti Date: Thu, 4 Apr 2024 15:13:00 +0200 Subject: [PATCH] vignette to master --- .Rbuildignore | 1 + .Rproj.user/shared/notebooks/paths | 1 + README.Rmd | 162 +++++++++++++++++++++ README.md | 203 ++++++++++++++++++++++++++- man/figures/README-centroids-1.png | Bin 0 -> 29680 bytes man/figures/README-enerscape-1.png | Bin 0 -> 334132 bytes man/figures/README-plot-path-1.png | Bin 0 -> 350346 bytes man/figures/README-replot-path-1.png | Bin 0 -> 350346 bytes man/figures/README-torasters-1.png | Bin 0 -> 235222 bytes 9 files changed, 366 insertions(+), 1 deletion(-) create mode 100644 README.Rmd create mode 100644 man/figures/README-centroids-1.png create mode 100644 man/figures/README-enerscape-1.png create mode 100644 man/figures/README-plot-path-1.png create mode 100644 man/figures/README-replot-path-1.png create mode 100644 man/figures/README-torasters-1.png diff --git a/.Rbuildignore b/.Rbuildignore index a763355..fb6afe3 100644 --- a/.Rbuildignore +++ b/.Rbuildignore @@ -4,3 +4,4 @@ .github README.md CITATION.cff +README.Rmd diff --git a/.Rproj.user/shared/notebooks/paths b/.Rproj.user/shared/notebooks/paths index 0631ae1..d3a9d40 100644 --- a/.Rproj.user/shared/notebooks/paths +++ b/.Rproj.user/shared/notebooks/paths @@ -4,6 +4,7 @@ /home/eb97ziwi/parthian/R/cost-graph.R="98801E53" /home/eb97ziwi/parthian/R/data.R="7CFC1534" /home/eb97ziwi/parthian/R/path-functions.R="96394A10" +/home/eb97ziwi/parthian/README.Rmd="6C7A0E00" /home/eb97ziwi/parthian/README.md="84F1FA77" /home/eb97ziwi/parthian/man/edgelist.Rd="C93D0D2A" /home/eb97ziwi/parthian/src/RcppExports.cpp="3C6A6A50" diff --git a/README.Rmd b/README.Rmd new file mode 100644 index 0000000..ed00c54 --- /dev/null +++ b/README.Rmd @@ -0,0 +1,162 @@ +--- +author: Emilio Berti +output: + github_document: + pandoc_args: --webtex +--- + +[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.10890031.svg)](https://doi.org/10.5281/zenodo.10890031) + +```{r, include = FALSE} +knitr::opts_chunk$set( + collapse = TRUE, + comment = "#>", + fig.path = "man/figures/README-", + fig.width = 4, + fig.height = 4, + fig.align='center', + dpi = 300, + out.width = "50%" +) +``` + +# Development and dependecies + +The R package _parthian_ is developed and maintained by Emilio Berti (). +There are several dependencies for _parthian_: + + - Rcpp + - igraph + - terra + - enerscape + +They are all stable packages with long history, except for _enerscape_, which I developed in 2021 and maintain since then: and . + +```{r} +library(terra) +library(enerscape) +library(igraph) +library(parthian) +``` + +# Workflow + +## Introduction + +The scope of _parthian_ is to quantify the importance of areas in the landscape based on energy cost of movement for animals. +This is achieved by building a weighted graph between adjacent cells using as weights the cost of transport ($E_{COT}$) between them. +This weighted graph is used to obtain least-cost paths and to rank areas based on their importance in promoting movement across such paths. + +There are two datasets in _parthian_: + + - dem: a digital elevation model for an area in Sicily, Italy. + - pa: the protected areas in the same region. + +These are matrices, as it is easier to store them in an R package. +The first thing is to transform them into raster. + +```{r torasters} +data(dem) +dem <- rast( + dem, + crs = "+proj=utm +zone=32 +datum=WGS84 +units=m +no_defs" +) +data(pa) +pa <- rast( + pa, + crs = "+proj=utm +zone=32 +datum=WGS84 +units=m +no_defs" +) +plot(dem, col = colorRampPalette(c("darkblue", "seagreen", "white"))(100)) +plot(pa, add = TRUE, col = adjustcolor("gold", alpha.f = .5), legend = FALSE) +lines(as.polygons(pa)) +``` + +The resolution and extent of the layers are wrong (I need to fix this in the package data), but it does not matter too much for the examples. + +## Energy landscape + +The next step is to calcualte the energy landscape for the animal. +Here, I am assuming an animal of 10 kg. + +```{r enerscape} +en <- enerscape(dem, 10, "kcal") +plot(en, col = colorRampPalette(c("grey95", "tomato", "darkred"))(100)) +plot(pa, add = TRUE, col = adjustcolor("gold", alpha.f = .5), legend = FALSE) +lines(as.polygons(pa)) +``` + + +## Weighted graph + +The main task of _parthian_ is to create a graph where vertices (_V_) are the cells of the energy landscapes and weighted edges (_E_) $E_{ij} = E_{COT}$ if two cells are adjacent, and $E_{ij} = 0$ if they are not. + +```{r cost-graph} +g <- cost_graph(en) +``` + +Generally, there are as many vertices as number of cells + +```{r vertices} +length(V(g)) == ncell(en) +``` + +but the number of edges may be lower than $8V$, as some paths may be blocked, in this example by the sea. + +```{r edges} +length(E(g)) == ncell(en) * 8 +``` + +## Least cost paths +Least-cost paths can be obtained using the weighted graph created by `cost_graph()` and the _igraph_ `shortest_paths()` function. +First, let's get the centroids of the protected area, after exlcuding very small areas ($\leq 100 m^2$): + +```{r centroids} +pas <- disagg(as.polygons(pa)) +pas <- pas[expanse(pas, "m") > 100, ] +centrs <- centroids(pas) +plot(pa, col = "gold") +points(centrs, cex = 1, pch = 21) +points(centrs[c(1, 4), ], cex = 1, pch = 20) +``` +Let's calcualte the least-cost path between the two areas highlighted by the solid circle. +Because there is a one-to-one correspondence between cell and vertex ID, this can be achieved by: + +```{r lcp} +xy <- extract(en, centrs[c(1, 4), ], cells = TRUE) +lcp <- shortest_paths(g, xy$cell[1], xy$cell[2]) +path <- lcp$vpath[[1]] +path <- xyFromCell(en, as.numeric(path)) +path <- vect(path, crs = crs(dem)) +total_costs <- sum(extract(en, path)[["EnergyScape"]]) +``` + +```{r plot-path} +plot(en, col = colorRampPalette(c("grey95", "tomato", "darkred"))(100)) +plot(pa, add = TRUE, col = adjustcolor("gold", alpha.f = .5), legend = FALSE) +lines(as.polygons(pa)) +lines(as.lines(path), lw = 3, col = "green4") +text(220, 350, paste("Energy costs:", round(total_costs), "kcal")) +``` + +The function `parthian_path()` wraps the above code and can be called from _parthian_. + +```{r path} +lcp <- parthian_path(g, en, centrs[1], centrs[4]) +lcp +``` + +`parthian_path()` returns the least-cost path as a SpatVector and its total travel costs, which are the same as before. + +```{r replot-path} +plot(en, col = colorRampPalette(c("grey95", "tomato", "darkred"))(100)) +plot(pa, add = TRUE, col = adjustcolor("gold", alpha.f = .5), legend = FALSE) +lines(as.polygons(pa)) +lines(lcp$lcp, lw = 3, col = "green4") +text(220, 350, paste("Energy costs:", round(lcp$costs), "kcal")) +``` + +Instead of calculating least-cost paths manually, _parthian_ uses the function `parthian_paths()` to obtain them iteratively between all cells. + +```{r paths} +message("to do") +``` diff --git a/README.md b/README.md index c0c8755..9cd492a 100644 --- a/README.md +++ b/README.md @@ -1,5 +1,206 @@ - +Emilio Berti [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.10890031.svg)](https://doi.org/10.5281/zenodo.10890031) +# Development and dependecies + +The R package *parthian* is developed and maintained by Emilio Berti +(). There are several dependencies for *parthian*: + +- Rcpp +- igraph +- terra +- enerscape + +They are all stable packages with long history, except for *enerscape*, +which I developed in 2021 and maintain since then: + and +. + +``` r +library(terra) +#> terra 1.7.71 +library(enerscape) +library(igraph) +#> +#> Attaching package: 'igraph' +#> The following object is masked from 'package:enerscape': +#> +#> distances +#> The following objects are masked from 'package:terra': +#> +#> blocks, compare, union +#> The following objects are masked from 'package:stats': +#> +#> decompose, spectrum +#> The following object is masked from 'package:base': +#> +#> union +library(parthian) +``` + +# Workflow + +## Introduction + +The scope of *parthian* is to quantify the importance of areas in the +landscape based on energy cost of movement for animals. This is achieved +by building a weighted graph between adjacent cells using as weights the +cost of transport +(![E\_{COT}](https://latex.codecogs.com/png.latex?E_%7BCOT%7D "E_{COT}")) +between them. This weighted graph is used to obtain least-cost paths and +to rank areas based on their importance in promoting movement across +such paths. + +There are two datasets in *parthian*: + +- dem: a digital elevation model for an area in Sicily, Italy. +- pa: the protected areas in the same region. + +These are matrices, as it is easier to store them in an R package. The +first thing is to transform them into raster. + +``` r +data(dem) +dem <- rast( + dem, + crs = "+proj=utm +zone=32 +datum=WGS84 +units=m +no_defs" +) +data(pa) +pa <- rast( + pa, + crs = "+proj=utm +zone=32 +datum=WGS84 +units=m +no_defs" +) +plot(dem, col = colorRampPalette(c("darkblue", "seagreen", "white"))(100)) +plot(pa, add = TRUE, col = adjustcolor("gold", alpha.f = .5), legend = FALSE) +lines(as.polygons(pa)) +``` + + + +The resolution and extent of the layers are wrong (I need to fix this in +the package data), but it does not matter too much for the examples. + +## Energy landscape + +The next step is to calcualte the energy landscape for the animal. Here, +I am assuming an animal of 10 kg. + +``` r +en <- enerscape(dem, 10, "kcal") +#> DEM is assumed to have planar CRS in meters. +plot(en, col = colorRampPalette(c("grey95", "tomato", "darkred"))(100)) +plot(pa, add = TRUE, col = adjustcolor("gold", alpha.f = .5), legend = FALSE) +lines(as.polygons(pa)) +``` + + + +## Weighted graph + +The main task of *parthian* is to create a graph where vertices (*V*) +are the cells of the energy landscapes and weighted edges (*E*) +![E\_{ij} = E\_{COT}](https://latex.codecogs.com/png.latex?E_%7Bij%7D%20%3D%20E_%7BCOT%7D "E_{ij} = E_{COT}") +if two cells are adjacent, and +![E\_{ij} = 0](https://latex.codecogs.com/png.latex?E_%7Bij%7D%20%3D%200 "E_{ij} = 0") +if they are not. + +``` r +g <- cost_graph(en) +``` + +Generally, there are as many vertices as number of cells + +``` r +length(V(g)) == ncell(en) +#> [1] TRUE +``` + +but the number of edges may be lower than +![8V](https://latex.codecogs.com/png.latex?8V "8V"), as some paths may +be blocked, in this example by the sea. + +``` r +length(E(g)) == ncell(en) * 8 +#> [1] FALSE +``` + +## Least cost paths + +Least-cost paths can be obtained using the weighted graph created by +`cost_graph()` and the *igraph* `shortest_paths()` function. First, +let’s get the centroids of the protected area, after exlcuding very +small areas +(![\leq 100 m^2](https://latex.codecogs.com/png.latex?%5Cleq%20100%20m%5E2 "\leq 100 m^2")): + +``` r +pas <- disagg(as.polygons(pa)) +pas <- pas[expanse(pas, "m") > 100, ] +centrs <- centroids(pas) +plot(pa, col = "gold") +points(centrs, cex = 1, pch = 21) +points(centrs[c(1, 4), ], cex = 1, pch = 20) +``` + + +Let’s calcualte the least-cost path between the two areas highlighted by +the solid circle. Because there is a one-to-one correspondence between +cell and vertex ID, this can be achieved by: + +``` r +xy <- extract(en, centrs[c(1, 4), ], cells = TRUE) +lcp <- shortest_paths(g, xy$cell[1], xy$cell[2]) +path <- lcp$vpath[[1]] +path <- xyFromCell(en, as.numeric(path)) +path <- vect(path, crs = crs(dem)) +total_costs <- sum(extract(en, path)[["EnergyScape"]]) +``` + +``` r +plot(en, col = colorRampPalette(c("grey95", "tomato", "darkred"))(100)) +plot(pa, add = TRUE, col = adjustcolor("gold", alpha.f = .5), legend = FALSE) +lines(as.polygons(pa)) +lines(as.lines(path), lw = 3, col = "green4") +text(220, 350, paste("Energy costs:", round(total_costs), "kcal")) +``` + + + +The function `parthian_path()` wraps the above code and can be called +from *parthian*. + +``` r +lcp <- parthian_path(g, en, centrs[1], centrs[4]) +lcp +#> $lcp +#> class : SpatVector +#> geometry : lines +#> dimensions : 1, 0 (geometries, attributes) +#> extent : 319.5, 386.5, 250.5, 485.5 (xmin, xmax, ymin, ymax) +#> coord. ref. : +proj=utm +zone=32 +datum=WGS84 +units=m +no_defs +#> +#> $costs +#> [1] 406.3804 +``` + +`parthian_path()` returns the least-cost path as a SpatVector and its +total travel costs, which are the same as before. + +``` r +plot(en, col = colorRampPalette(c("grey95", "tomato", "darkred"))(100)) +plot(pa, add = TRUE, col = adjustcolor("gold", alpha.f = .5), legend = FALSE) +lines(as.polygons(pa)) +lines(lcp$lcp, lw = 3, col = "green4") +text(220, 350, paste("Energy costs:", round(lcp$costs), "kcal")) +``` + + + +Instead of calculating least-cost paths manually, *parthian* uses the +function `parthian_paths()` to obtain them iteratively between all +cells. +``` r +message("to do") +#> to do +``` diff --git a/man/figures/README-centroids-1.png b/man/figures/README-centroids-1.png new file mode 100644 index 0000000000000000000000000000000000000000..4a274c69647015dc08d0a9dc186f0aad15f636bb GIT binary patch literal 29680 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