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climate_indices

Climate indices for drought monitoring

https://github.com/monocongo/climate_indices

Science Score: 59.0%

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

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    CITATION.cff file
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    DOI references
    Found 7 DOI reference(s) in README
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    Academic publication links
    Links to: researchgate.net
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    Committers with academic emails
    2 of 20 committers (10.0%) from academic institutions
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    Scientific vocabulary similarity
    Low similarity (10.7%) to scientific vocabulary

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Last synced: 6 months ago · JSON representation

Repository

Climate indices for drought monitoring

Basic Info
Statistics
  • Stars: 376
  • Watchers: 21
  • Forks: 173
  • Open Issues: 107
  • Releases: 2
Created over 8 years ago · Last pushed 7 months ago
Metadata Files
Readme Changelog Contributing License Code of conduct

README.md

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climate_indices

Actions Status License PyPI - Python Version

Python library of indices useful for climate monitoring

This project contains Python implementations of various climate index algorithms which provide a geographical and temporal picture of the severity and duration of precipitation and temperature anomalies useful for climate monitoring and research.

The following indices are provided:

  • SPI, Standardized Precipitation Index, utilizing both gamma and Pearson Type III distributions
  • SPEI, Standardized Precipitation Evapotranspiration Index, utilizing both gamma and Pearson Type III distributions
  • PET, Potential Evapotranspiration, utilizing either Thornthwaite or Hargreaves equations
  • PNP, Percentage of Normal Precipitation
  • PCI, Precipitation Concentration Index

This Python implementation of the above climate index algorithms is being developed with the following goals in mind:

  • to provide an open source software package to compute a suite of climate indices commonly used for climate monitoring, with well documented code that is faithful to the relevant literature and which produces scientifically verifiable results
  • to provide a central, open location for participation and collaboration for researchers, developers, and users of climate indices
  • to facilitate standardization and consensus on best-of-breed climate index algorithms and corresponding compliant implementations in Python
  • to provide transparency into the operational code used for climate monitoring activities at NCEI/NOAA, and consequent reproducibility of published datasets computed from this package
  • to incorporate modern software engineering principles and scientific programming best practices

This is a developmental/forked version of code that was originally developed by NIDIS/NCEI/NOAA. See drought.gov.

Migration Guide for v2.2.0

Breaking Change: Exception-Based Error Handling

Version 2.2.0 introduces a significant architectural improvement in error handling. The library now uses exception-based error handling instead of returning None tuples for error conditions.

What Changed

Before (v2.1.x and earlier): ```python

Old behavior - functions returned None tuples on failure

result = someinternalfunction(data) if result == (None, None, None, None): # Handle error case pass ```

After (v2.2.0+): ```python

New behavior - functions raise specific exceptions

try: result = someinternalfunction(data) except climateindices.compute.InsufficientDataError as e: # Handle insufficient data case print(f"Not enough data: {e.nonzerocount} values found, {e.requiredcount} required") except climate_indices.compute.PearsonFittingError as e: # Handle fitting failure case print(f"Fitting failed: {e}") ```

New Exception Hierarchy

  • DistributionFittingError (base class)
    • InsufficientDataError - raised when there are too few non-zero values for statistical fitting
    • PearsonFittingError - raised when L-moments calculation fails for Pearson Type III distribution

Impact on Users

  • Direct API users: No changes needed - the public SPI/SPEI functions handle exceptions internally
  • Library integrators: If you were checking for None return values from internal functions, update to use try/catch blocks
  • Benefits: More informative error messages, better debugging, and automatic fallback from Pearson to Gamma distribution when appropriate

Code Quality Improvements

Version 2.2.0 also addresses floating point comparison issues (python:S1244) throughout the codebase:

Floating Point Comparisons: ```python

❌ OLD: Direct equality checks (unreliable)

if values == 0.0: handlezerocase()

✅ NEW: Safe comparison using numpy.isclose()

if np.isclose(values, 0.0, atol=1e-8): handlezerocase() ```

Benefits: - Eliminates floating point precision issues in statistical parameter validation - Improves test reliability and numerical robustness - Follows scientific computing best practices for floating point arithmetic - See docs/floating_point_best_practices.md for comprehensive guidelines

Citation

You can cite climate_indices in your projects and research papers via the BibTeX entry below. @misc {climate_indices, author = "James Adams", title = "climate_indices, an open source Python library providing reference implementations of commonly used climate indices", url = "https://github.com/monocongo/climate_indices", month = "may", year = "2017--" }

Owner

  • Name: James Adams
  • Login: monocongo
  • Kind: user

GitHub Events

Total
  • Issues event: 14
  • Watch event: 30
  • Delete event: 1
  • Issue comment event: 34
  • Push event: 9
  • Pull request review comment event: 5
  • Pull request review event: 2
  • Pull request event: 10
  • Fork event: 9
  • Create event: 3
Last Year
  • Issues event: 14
  • Watch event: 30
  • Delete event: 1
  • Issue comment event: 34
  • Push event: 9
  • Pull request review comment event: 5
  • Pull request review event: 2
  • Pull request event: 10
  • Fork event: 9
  • Create event: 3

Committers

Last synced: 7 months ago

All Time
  • Total Commits: 1,001
  • Total Committers: 20
  • Avg Commits per committer: 50.05
  • Development Distribution Score (DDS): 0.351
Past Year
  • Commits: 37
  • Committers: 3
  • Avg Commits per committer: 12.333
  • Development Distribution Score (DDS): 0.378
Top Committers
Name Email Commits
James Adams m****o@g****m 650
James.Adams J****s@C****l 213
james.adams j****s@o****m 60
james.a j****a@c****m 23
James Adams j****s@v****m 11
Benjamin Root b****t@g****m 10
Arnab Paul Choudhury a****4@g****m 9
Nathan Nayda n****a@s****m 6
kikocorreoso k****o@g****m 4
dependabot[bot] 4****] 3
AGericke g****e@i****n 3
Ben Lewis b****n 1
David de Klerk d****k@e****k 1
DeepSource Bot b****t@d****o 1
haysengithub d****e@g****m 1
Scott Wales s****s@u****u 1
Laura Guillory l****y@g****m 1
deepsource-autofix[bot] 6****] 1
kikocorreoso y****u@e****m 1
snyk-bot s****t@s****o 1
Committer Domains (Top 20 + Academic)
snyk.io: 1 unimelb.edu.au: 1 deepsource.io: 1 ed.ac.uk: 1 secondpillar.com: 1 verisk.com: 1 claraanalytics.com: 1 opensignal.com: 1

Issues and Pull Requests

Last synced: 6 months ago

All Time
  • Total issues: 323
  • Total pull requests: 246
  • Average time to close issues: 3 months
  • Average time to close pull requests: 15 days
  • Total issue authors: 110
  • Total pull request authors: 18
  • Average comments per issue: 2.74
  • Average comments per pull request: 0.93
  • Merged pull requests: 219
  • Bot issues: 0
  • Bot pull requests: 3
Past Year
  • Issues: 14
  • Pull requests: 11
  • Average time to close issues: about 5 hours
  • Average time to close pull requests: 21 days
  • Issue authors: 10
  • Pull request authors: 1
  • Average comments per issue: 0.71
  • Average comments per pull request: 1.64
  • Merged pull requests: 10
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
  • monocongo (164)
  • crestedcaracaryn (6)
  • bennyistanto (5)
  • kikocorreoso (5)
  • WeatherGod (4)
  • aleccourt (4)
  • SouhailAB (4)
  • tommylees112 (3)
  • Lixia0911 (3)
  • wsor330 (3)
  • s-m-t-c (3)
  • itati01 (3)
  • jamaa (2)
  • yheng0821 (2)
  • fipoucat (2)
Pull Request Authors
  • monocongo (216)
  • WeatherGod (10)
  • Seven-milk (7)
  • kikocorreoso (3)
  • dependabot[bot] (3)
  • nnayda (2)
  • go1me (1)
  • oshin94 (1)
  • cshields143 (1)
  • dawiedotcom (1)
  • ScottWales (1)
  • Emmadd (1)
  • itati01 (1)
  • Daafip (1)
  • Laura-Guillory (1)
Top Labels
Issue Labels
enhancement (28) help wanted (19) bug (11) question (3) documentation (2)
Pull Request Labels
dependencies (4) enhancement (1)

Packages

  • Total packages: 2
  • Total downloads:
    • pypi 1,350 last-month
  • Total docker downloads: 100
  • Total dependent packages: 0
    (may contain duplicates)
  • Total dependent repositories: 0
    (may contain duplicates)
  • Total versions: 18
  • Total maintainers: 1
proxy.golang.org: github.com/monocongo/climate_indices
  • Versions: 2
  • Dependent Packages: 0
  • Dependent Repositories: 0
Rankings
Dependent packages count: 5.4%
Average: 5.6%
Dependent repos count: 5.8%
Last synced: 6 months ago
pypi.org: climate-indices

Reference implementations of various climate indices typically used for drought monitoring

  • Versions: 16
  • Dependent Packages: 0
  • Dependent Repositories: 0
  • Downloads: 1,350 Last month
  • Docker Downloads: 100
Rankings
Dependent packages count: 8.7%
Average: 29.0%
Dependent repos count: 49.2%
Maintainers (1)
monocongo
Last synced: 6 months ago

Dependencies

.github/workflows/unit-tests-workflow.yml actions
  • actions/checkout v3 composite
  • actions/setup-python v2 composite
pyproject.toml pypi
  • pytest * develop
  • toml 0.10.2 develop
  • cftime 1.6.2
  • dask 2022.2.0
  • h5netcdf 1.1.0
  • python >=3.8,<3.12
  • scipy 1.9.3
  • xarray 2023.1.0
docs/requirements.txt pypi
  • toml >=0.10.2