https://github.com/wilkelab/isoband

isoband: An R package to generate contour lines and polygons.
https://github.com/wilkelab/isoband

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isoband: An R package to generate contour lines and polygons.

• Host: GitHub
• URL: https://github.com/wilkelab/isoband
• Owner: r-lib
• License: other
• Created: 2018-12-29T06:05:34.000Z (over 5 years ago)
• Default Branch: main
• Last Pushed: 2022-12-20T13:26:52.000Z (almost 2 years ago)
• Last Synced: 2024-04-10T06:06:37.448Z (6 months ago)
• Language: C++
• Homepage: https://isoband.r-lib.org
• Size: 36.7 MB
• Stars: 130
• Watchers: 8
• Forks: 13
• Open Issues: 6
• Metadata Files:
  • Readme: README.Rmd
  • License: LICENSE

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README

        
---

output: github_document

---

```{r setup, include = FALSE}

knitr::opts_chunk$set(

  collapse = TRUE,

  comment = "#>",

  fig.path = "man/figures/README-",

  dpi = 150

)

```

# isoband 

[![CRAN status](https://www.r-pkg.org/badges/version/isoband)](https://CRAN.R-project.org/package=isoband)

[![R-CMD-check](https://github.com/r-lib/isoband/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/r-lib/isoband/actions/workflows/R-CMD-check.yaml)

[![Codecov test coverage](https://codecov.io/gh/r-lib/isoband/branch/main/graph/badge.svg)](https://app.codecov.io/gh/r-lib/isoband?branch=main)

Generate contour lines (isolines) and contour polygons (isobands) from regularly spaced grids containing elevation data. Package originally written by Claus Wilke and donated to r-lib in 2022.

  

## Installation

Install the latest official release from CRAN via:

``` r

install.packages("isoband")

```

Install the current development from github via:

``` r

# install.packages("pak")

pak::pak("r-lib/isoband")

```

## Examples

The two main workhorses of the package are the functions `isolines()` and `isobands()`, respectively. They return a list of isolines/isobands for each isolevel specified. Each isoline/isoband consists of vectors of x and y coordinates, as well as a vector of ids specifying which sets of coordinates should be connected. This format can be handed directly to `grid.polyline()`/`grid.path()` for drawing. However, we can also convert the output to spatial features and draw with ggplot2 (see below).

```{r basic-example}

library(isoband)

m <- matrix(c(0, 0, 0, 0, 0,

              0, 1, 2, 1, 0,

              0, 1, 2, 0, 0,

              0, 1, 0, 1, 0,

              0, 0, 0, 0, 0), 5, 5, byrow = TRUE)

isolines(1:ncol(m), 1:nrow(m), m, 0.5)

isobands(1:ncol(m), 1:nrow(m), m, 0.5, 1.5)

```

The function `plot_iso()` is a convenience function for debugging and testing.

```{r basic-example-plot, fig.asp = 1, out.width = "50%"}

plot_iso(m, 0.5, 1.5)

```

The isolining and isobanding algorithms have no problem with larger datasets. Let’s calculate isolines and isobands for the volcano dataset, convert to sf, and plot with ggplot2.

```{r volcano, fig.asp = 1, out.width = "50%"}

library(ggplot2)

suppressWarnings(library(sf))

m <- volcano

b <- isobands((1:ncol(m))/(ncol(m)+1), (nrow(m):1)/(nrow(m)+1), m, 10*(9:19), 10*(10:20))

l <- isolines((1:ncol(m))/(ncol(m)+1), (nrow(m):1)/(nrow(m)+1), m, 10*(10:19))

bands <- iso_to_sfg(b)

data_bands <- st_sf(

  level = 1:length(bands),

  geometry = st_sfc(bands)

)

lines <- iso_to_sfg(l)

data_lines <- st_sf(

  level = 2:(length(lines)+1),

  geometry = st_sfc(lines)

)

ggplot() +

  geom_sf(data = data_bands, aes(fill = level), color = NA, alpha = 0.7) +

  geom_sf(data = data_lines, color = "black") +

  scale_fill_viridis_c(guide = "none") +

  coord_sf(expand = FALSE)

```