v0.5.0

Contributors to this version: Juliette Lavoie (juliettelavoie), Trevor James Smith (@Zeitsperre).

New features

• Added support for collecting and converting ptype ECMWF ERA5 variable.
• A new "_frequency": true toggle for returning the output frequency of converted data.
• Added a new JSON template for NEX-GDDP-CMIP6 datasets.
• miranda is now PEP 517 <https://peps.python.org/pep-0517/>_ and PEP 621 <https://peps.python.org/pep-0621/>_ compliant, using the flit <https://flit.pypa.io/en/stable/>_ backend.

Internal changes

• Various fixes to existing docstrings.
• Time frequency checks are more resilient when converting Monthly time-step data.
• Masking and regridding of datasets when running convert_dataset is now optional or automatic.
• Updated templates to newest API.
• Created a gis recipe for exclusively installing GIS libraries.
• Removed many unneeded dependencies, cleaned up Makefile.
• All public-facing functions now contain at least a minimal docstring for documentation generation.

v0.4.0

Contributors to this version: Trevor James Smith (:user:Zeitsperre), Pascal Bourgault (:user:aulemahal), Travis Logan (:user:tlogan2000).

New features

• Improvements have been made to the development documentation; Project URLs, ReadTheDocs theming, and other quality of life changes.
• Conversion JSON definitions now support pre-processing to render dimensions and variable names consistent before running corrections/conversions.
• New datasets with CF-like attributes conversion supported:
  • RDRS (ECCC)
  • GRNCH (ETS)
• Preliminary miranda.io module for organizing output-writing functionality.
• New miranda.io.fetch_chunk_config function for "rechunking" datasets according to project presets.
• New mirands.io.utils.name_output_file for generating names from Dataset facets or from a dictionary.
• New mirands.gis.subset_domain for clipping dataset to a preconfigured region.

Bug fixes

• Many data-related utilities now have more accurate static typing.
• Converted dataset global attributes are now synchronized for consistency.
• ECMWF-based datasets now implement more consistent conversion factors and metadata.
• miranda.storage.file_size now handles dictionaries of Pathlib objects.

Internal changes

• Pre-commit version updates.
• Improvements have been made to the development documentation; Project URLs, ReadTheDocs theming, installation methods, and other quality of life changes.
• Schema and folder structure updates:
  • gridded-obs -> reconstruction
  • bias-adjust-project is used when present and not just when level=="biasadjusted"
• CI now using tox>=4.0 and ubuntu-latest virtual machine images.

v0.3.0

Contributors to this version: Trevor James Smith (@Zeitsperre), Pascal Bourgault (@aulemahal), David Huard (@huard), Travis Logan (@tlogan2000), Gabriel Rondeau-Genesse (@RondeauG), and Sébastien Biner (@sbiner).

Announcements

• First public release on PyPI.

New features

• Dataset conversion tools (miranda.convert) use a JSON-definition file to dynamically populate metadata, run data quality checks, and convert units to CF-compliant standard. Supported datasets are:
  • ERA5/ERA5-Land (complete)
  • MELCC (stations) (beta)
  • ECCC (stations) (alpha)
  • NASA DayMet (WIP)
  • NASA AgMerra/AgCFSR (WIP)
  • Hydro Québec (stations) (WIP)
  • DEH (stations) (WIP)
  • WFDEI-GEM-CAPA (WIP)
• Module (miranda.eccc) for ECCC station data and ECCC Adjusted and Homogenized Canadian Climate Data (AHCCD) conversion (WIP).
• Module (miranda.ncar) for fetching interpolated CORDEX-NAM (22i/44i) from NCAR AWS data storage.
• Module (miranda.ecmwf) for fetching ECMWF ERA5/-Land (single-levels, pressure-levels, monthly-means) datasets via CDSAPI.
• Module (miranda.gis) for setting specific subsetting domains used when converting gridded datasets.
• Modules (miranda.archive and miranda.remote) for performing data archiving actions locally and remotely (powered by [fabric](https://github.com/fabric/fabric>`_ and `paramiko <https://github.com/paramiko/paramiko)) (WIP).
• Module (miranda.decode) for ingesting and parsing dataset metadata based on filename and dataset attributes. Supported datasets are:
  • miranda converted datasets
  • CMIP6
  • CMIP5
  • CMIP5-CORDEX
  • ISIMIP-FT
  • CanDCS-U6 (PCIC)
• Module (miranda.structure) for create constructing file-tree databases based on YAML-defined metadata schemas (WIP).
• Modules (miranda.cv and miranda.validators) for validating metadata using ESGF controlled vocabularies (taken from pyessv-archive <https://github.com/ES-DOC/pyessv-archive>_) and schema definitions (powered by schema), respectively (WIP).