An open API service indexing awesome lists of open source software.

https://github.com/jbisits/rasterhistograms.jl

Empirical distribution fitting for Rasters.jl.
https://github.com/jbisits/rasterhistograms.jl

histogram julia raster

Last synced: about 1 year ago
JSON representation

Empirical distribution fitting for Rasters.jl.

Awesome Lists containing this project

README

          

# RasterHistograms

[![Stable](https://img.shields.io/badge/docs-stable-blue.svg)](https://jbisits.github.io/RasterHistograms.jl/stable/)
[![Dev](https://img.shields.io/badge/docs-dev-blue.svg)](https://jbisits.github.io/RasterHistograms.jl/dev/)
[![Build Status](https://github.com/jbisits/RasterHistograms.jl/actions/workflows/CI.yml/badge.svg?branch=main)](https://github.com/jbisits/RasterHistograms.jl/actions/workflows/CI.yml?query=branch%3Amain)
[![Coverage](https://codecov.io/gh/jbisits/RasterHistograms.jl/branch/main/graph/badge.svg)](https://codecov.io/gh/jbisits/RasterHistograms.jl)

[Rasters.jl](https://rafaqz.github.io/Rasters.jl/dev/) provides excellent methods for reading, analysing and plotting for geospatial data.
This package provides empirical distribution fitting for `Raster` data structures aiming to provide functionality similar to python's [xhistogram](https://xhistogram.readthedocs.io/en/latest/index.html) for [xarray](https://docs.xarray.dev/en/stable/) in Julia.

## Using the package

The package is installed using Julia's package manager

```julia
julia> ]
(@v1.9) pkg> add RasterHistograms
```

To start using the package you will also need to have [Rasters.jl](https://github.com/rafaqz/Rasters.jl) installed (in the same manner as above but replace `RasterHistograms` with `Rasters`).
To then use the packages type

```julia
julia> using Rasters, RasterHistograms
```

into the repl.