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Merge pull request #541 from nci/release_0_9_1
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Release 0.9.1
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tennlee committed Jun 14, 2024
2 parents f8bee63 + 922f5dc commit 273481b
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73 changes: 73 additions & 0 deletions CITATION.cff
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cff-version: 1.2.0
message: "If you use this software, please cite it as below."
authors:
- given-names: Tennessee
family-names: Leeuwenburg
orcid: "https://orcid.org/0009-0008-2024-1967"
- given-names: Nicholas
family-names: Loveday
orcid: "https://orcid.org/0009-0000-5796-7069"
- given-names: Elizabeth E.
family-names: Ebert
- given-names: Harrison
family-names: Cook
orcid: "https://orcid.org/0009-0009-3207-4876"
- given-names: Mohammadreza
family-names: Khanarmuei
orcid: "https://orcid.org/0000-0002-5017-9622"
- given-names: Robert J.
family-names: Taggart
orcid: "https://orcid.org/0000-0002-0067-5687"
- given-names: Nikeeth
family-names: Ramanathan
orcid: "https://orcid.org/0009-0002-7406-7438"
- given-names: Maree
family-names: Carroll
orcid: "https://orcid.org/0009-0008-6830-8251"
- given-names: Stephanie
family-names: Chong
orcid: "https://orcid.org/0009-0007-0796-4127"
- given-names: Aidan
family-names: Griffiths
- given-names: John
family-names: Sharples

title: "scores: A Python package for verifying and evaluating models and predictions with xarray and pandas"

preferred-citation:
type: article
doi: "10.48550/arXiv.2406.07817"
journal: "arXiv"
title: "scores: A Python package for verifying and evaluating models and predictions with xarray and pandas"
authors:
- given-names: Tennessee
family-names: Leeuwenburg
orcid: "https://orcid.org/0009-0008-2024-1967"
- given-names: Nicholas
family-names: Loveday
orcid: "https://orcid.org/0009-0000-5796-7069"
- given-names: Elizabeth E.
family-names: Ebert
- given-names: Harrison
family-names: Cook
orcid: "https://orcid.org/0009-0009-3207-4876"
- given-names: Mohammadreza
family-names: Khanarmuei
orcid: "https://orcid.org/0000-0002-5017-9622"
- given-names: Robert J.
family-names: Taggart
orcid: "https://orcid.org/0000-0002-0067-5687"
- given-names: Nikeeth
family-names: Ramanathan
orcid: "https://orcid.org/0009-0002-7406-7438"
- given-names: Maree
family-names: Carroll
orcid: "https://orcid.org/0009-0008-6830-8251"
- given-names: Stephanie
family-names: Chong
orcid: "https://orcid.org/0009-0007-0796-4127"
- given-names: Aidan
family-names: Griffiths
- given-names: John
family-names: Sharples
year: 2024
2 changes: 1 addition & 1 deletion docs/conf.py
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project = "scores"
copyright = "Licensed under Apache 2.0 - https://www.apache.org/licenses/LICENSE-2.0"
release = "0.9.0"
release = "0.9.1"

version = __version__

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4 changes: 2 additions & 2 deletions docs/data.md
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Overview of Some Relevant Data Sources

This section suggests how to obtain some 'getting started' weather and climate data for examining the use of the scores and metrics contained in this package. Data referred to here is available under various licenses, and the onus is on the user to understand the conditions of those licenses. The tutorials and walkthroughs in the 'tutorials' directory contain more information and explore the data in more depth.
This section suggests how to obtain sample data for 'getting started' with weather and climate information. Data referred to here is available under various licenses, and the onus is on the user to understand the conditions of those licenses. The tutorials and walkthroughs in the 'tutorials' directory contain more information and explore the data in more depth.

This page will be improved to provide more specific instructions on downloading and preparing the data in accordance with the scores roadmap. For the moment, it notes a few key datasets which have global coverage and are easily accessible.
This page will be improved to provide more specific instructions on downloading and preparing the data. For the moment, it notes a few key datasets which have global coverage and are easily accessible.

## Gridded global numerical weather prediction data
Global weather prediction models are used to generate medium range forecasts and provide the initial and boundary conditions for higher-resolution regional models. Their global coverage makes them a good starting point for demonstrating the application of scoring methods in any region of interest.
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2 changes: 1 addition & 1 deletion docs/maintainer.md
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| what | when | why |
| ------------ | ----------- | ------------ |
| README | a new is score added | in case it deserves a mention
| README | a new score is added | in case it deserves a mention
| api.md | a new function is added | each function must be added individually
| included.md | a new function is added | each function (and each variation of the function name) must be added individually
| Tutorial_Gallery.ipynb | a new tutorial is added | navigation throughout the docs
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2 changes: 1 addition & 1 deletion src/scores/__init__.py
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import scores.sample_data
import scores.stats.statistical_tests # noqa: F401

__version__ = "0.9.0"
__version__ = "0.9.1"

__all__ = [
"scores.categorical",
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