caliver

caliver: CALIbration and VERification of gridded fire danger models

https://github.com/ecmwf/caliver

Science Score: 23.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • CITATION.cff file
  • codemeta.json file
  • .zenodo.json file
  • DOI references
    Found 9 DOI reference(s) in README
  • Academic publication links
    Links to: zenodo.org
  • Committers with academic emails
  • Institutional organization owner
  • JOSS paper metadata
  • Scientific vocabulary similarity
    Low similarity (16.5%) to scientific vocabulary

Keywords

calibration geospatial-data natural-hazard netcdf r verification wildfire
Last synced: 6 months ago · JSON representation

Repository

caliver: CALIbration and VERification of gridded fire danger models

Basic Info
Statistics
  • Stars: 18
  • Watchers: 4
  • Forks: 8
  • Open Issues: 2
  • Releases: 0
Topics
calibration geospatial-data natural-hazard netcdf r verification wildfire
Created over 9 years ago · Last pushed almost 4 years ago
Metadata Files
Readme Contributing

README.md

caliver

An R package for the calibration and verification of gridded models

DOI R-CMD-check Codecov test coverage

CRAN Status Badge CRAN Total Downloads CRAN Monthly Downloads <!-- badges: end -->

caliver is a package developed for the R programming language. The name stands for calIbration and verification of gridded models. Although caliver was initially designed for wildfire danger models such as GEFF (developed by ECMWF) and RISICO (developed by CIMA Research Foundation), the algorithms can be applied to any gridded model output. Caliver is available with an APACHE-2 license.

For more details, please see the following papers:

  • Vitolo C, Di Giuseppe F, D’Andrea M (2018) Caliver: An R package for CALIbration and VERification of forest fire gridded model outputs. PLOS ONE 13(1): e0189419. https://doi.org/10.1371/journal.pone.0189419 Please note: in the latest version of the caliver package many functionalities described in this paper have become obsolete and deprecated, please refer to the vignette "An introduction to the caliver package" for more details.

  • Vitolo C., Di Giuseppe F., Barnard C., Coughlan R., Krzeminski B., San-Miguel-Ayanz J. ERA5-based global meteorological wildfire danger maps. Sci Data 7, 216 (2020). https://doi.org/10.1038/s41597-020-0554-z

  • Vitolo C., Di Giuseppe F., Krzeminski B., San-Miguel-Ayanz J. A 1980–2018 global fire danger re-analysis dataset for the Canadian Fire Weather Indices, Sci Data 6, 190032 (2019). https://doi.org/10.1038/sdata.2019.32

Installation

The installation of the caliver package depends on the following libraries:

  • Geospatial Data Abstraction Library (GDAL)
  • NetCDF4 (netcdf4)

Make sure you have the above libraries installed before attempting to install caliver. Once all the dependencies are installed, get caliver's development version from github using devtools:

r install.packages("remotes") remotes::install_github("ecmwf/caliver")

Alternatively, the stable version of this package is available on CRAN and can be installed as shown below.

r install.packages("caliver")

Load the package:

r library("caliver")

Docker

In this repository you find a Dockerfile that contains all the necessary dependencies and the caliver package already installed.

docker build -t ecmwf/caliver:latest -f Dockerfile .

Alternatively, you can use the image we host on docker hub: docker run -it --rm ecmwf/caliver:latest bash

Meta

  • This package and functions herein are part of an experimental open-source project. They are provided as is, without any guarantee.
  • Contributions are welcome! Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.
  • Please report any issues or bugs.
  • License: Apache License 2.0
  • Get citation information for caliver in R doing citation(package = "caliver")

Owner

  • Name: European Centre for Medium-Range Weather Forecasts
  • Login: ecmwf
  • Kind: organization
  • Email: Software.Support@ecmwf.int
  • Location: Shinfield Park, Reading, United Kingdom

Providing software to work with meteorological data and services

GitHub Events

Total
Last Year

Committers

Last synced: 7 months ago

All Time
  • Total Commits: 610
  • Total Committers: 4
  • Avg Commits per committer: 152.5
  • Development Distribution Score (DDS): 0.061
Past Year
  • Commits: 0
  • Committers: 0
  • Avg Commits per committer: 0.0
  • Development Distribution Score (DDS): 0.0
Top Committers
Name Email Commits
Claudia Vitolo c****o@g****m 573
Claudia Vitolo m****0@b****t 34
Mirko D'Andrea m****a@g****m 2
Carlos Valiente c****e@e****t 1
Committer Domains (Top 20 + Academic)

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 11
  • Total pull requests: 17
  • Average time to close issues: 10 months
  • Average time to close pull requests: about 3 hours
  • Total issue authors: 3
  • Total pull request authors: 3
  • Average comments per issue: 1.45
  • Average comments per pull request: 0.47
  • Merged pull requests: 17
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Top Authors
Issue Authors
  • cvitolo (9)
  • julimi26 (1)
  • jeffcsauer (1)
Pull Request Authors
  • cvitolo (15)
  • carletes (1)
  • mirkodandrea (1)
Top Labels
Issue Labels
help wanted (2)
Pull Request Labels

Dependencies

DESCRIPTION cran
  • R >= 3.5 depends
  • ggplot2 * imports
  • graphics * imports
  • ncdf4 * imports
  • raster * imports
  • reshape2 * imports
  • rworldmap * imports
  • scales * imports
  • sp * imports
  • stats * imports
  • covr * suggests
  • knitr * suggests
  • lintr * suggests
  • rmarkdown * suggests
  • testthat >= 2.1.0 suggests