Merge pull request #541 from nci/release_0_9_1

Release 0.9.1

Author: tennlee

CITATION.cff

@@ -0,0 +1,73 @@
+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

docs/conf.py

@@ -9,7 +9,7 @@
 
 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__
 

docs/data.md

@@ -2,9 +2,9 @@
 
 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.

docs/maintainer.md

@@ -73,7 +73,7 @@ Information relevant for package maintenance
 
 |     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

src/scores/__init__.py

@@ -13,7 +13,7 @@
 import scores.sample_data
 import scores.stats.statistical_tests  # noqa: F401
 
-__version__ = "0.9.0"
+__version__ = "0.9.1"
 
 __all__ = [
     "scores.categorical",