v0.5.0 (2023-06-19)#

Contributors to this version: Juliette Lavoie (:user: 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 and PEP 621 compliant, using the flit 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 (2023-03-30)#

Contributors to this version: Trevor James Smith (@Zeitsperre), Pascal Bourgault (@aulemahal), Travis Logan (@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 (2022-11-24)#

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).


  • 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)


  • 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 and 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



    • 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) and schema definitions (powered by schema), respectively (WIP).