miranda.eccc package

Environment and Climate Change Canada specialized conversion module.

Submodules

miranda.eccc._homogenized module

Adjusted and Homogenized Canadian Clime Data module.

miranda.eccc._homogenized.convert_ahccd(data_source: str | Path, output_dir: str | Path, variable: str, generation: int | None = None) → None

Convert Adjusted and Homogenized Canadian Climate Dataset files.

Parameters:

• data_source (str or Path)

• output_dir (str or Path)

• variable (str)

• generation (int, optional)

Returns:

None

miranda.eccc._homogenized.convert_ahccd_fwf_files(ff: Path | str, metadata: DataFrame, variable: str, generation: int | None = None, cols_specs: list[tuple[int, int]] | None = None, attrs: dict | None = None) → Dataset

Convert AHCCD fixed-width files.

Parameters:

• ff (str or Path)

• metadata (pandas.DataFrame)

• variable (str)

• generation

• cols_specs

• attrs

Returns:

xarray.Dataset

miranda.eccc._homogenized.create_canhomt_xarray(in_files: list, variable_meta: dict, station_meta: DataFrame, project: str) → Dataset | None

Create a xarray dataset from CanHomT raw .csv files.

Parameters:

• in_files (list) – A list of input files.

• variable_meta (dict) – Variable metadata.

• station_meta (pd.DataFrame) – Station metadata.

• project (str) – Project name.

Returns:

xr.Dataset, optional – Dataset.

miranda.eccc._homogenized.download_canhomt(project: str, working_folder: str | PathLike[str] | None = None, update_raw: bool = False, timeout: int | None = None, retry: int = 5, n_workers: int | None = None) → None

Download CanHomT data.

Parameters:

• project ({“canhomt_dly”}) – Project name.

• working_folder (str or os.PathLink[str], optional) – Temporary files folder.

• update_raw (bool) – Whether to update the raw files or not.

• timeout (int, optional) – Request timeout in seconds.

• retry (int) – Number of retries.

• n_workers (int, optional) – Number of workers to use. Not implemented.

Raises:

• ValueError – If the project name is unknown.

• OSError – If there is an error downloading the data.

miranda.eccc._raw module

miranda.eccc._raw.aggregate_stations(source_files: str | PathLike | None = None, output_folder: str | PathLike | None = None, time_step: str | None = None, variables: str | int | list[str | int] | None = None, include_flags: bool = True, groupings: int | None = None, mf_dataset_freq: str | None = None, temp_directory: str | PathLike | None = None, n_workers: int = 1) → None

Aggregate stations.

Parameters:

• source_files (str or Path) – Source files to be aggregated.

• output_folder (str or Path) – Output folder for the aggregated files.

• variables (str or int or list of str or int, optional) – The variable codes to be aggregated.

• time_step ({“hourly”, “daily”}) – The time step to be used for aggregation.

• include_flags (bool) – Include flags in the output files.

• groupings (int) – The number of files in each group used for converting to multi-file Datasets.

• mf_dataset_freq (str, optional) – Resampling frequency for creating output multi-file Datasets. E.g. ‘YS’: 1 year per file, ‘5YS’: 5 years per file.

• temp_directory (str or Path, optional) – Use another temporary directory location in case default location is not spacious enough.

• n_workers (int) – The number of workers to use.

Returns:

None

miranda.eccc._raw.convert_flat_files(source_files: str | PathLike, output_folder: str | PathLike | list[str | int], variables: str | int | list[str | int], mode: str = 'hourly', n_workers: int = 4) → None

Convert flat formatted files.

Parameters:

• source_files (str or Path)

• output_folder (str or Path)

• variables (str or List[str])

• mode ({“hourly”, “daily”})

• n_workers (int)

Returns:

None

miranda.eccc._raw.merge_converted_variables(source_files: str | PathLike, output_folder: str | PathLike, variables: str | int | list[str | int] | None = None, station_metadata: str | PathLike | None = None, overwrite: bool = False, n_workers: int = 1) → None

Merge converted variables.

Parameters:

• source_files (str, Path)

• output_folder (str, Path)

• variables (str or int or list of str or int, optional)

• station_metadata (str or Path, optional)

• overwrite (bool)

• n_workers (int)

Returns:

None

miranda.eccc._support_rvt module

miranda.eccc._support_rvt.gather_eccc_stations(timestep: str, start_date: datetime | str | None = None, end_date: datetime | str | None = None, climate_id: str | None = None) → DataFrame

Collect ECCC station data from the Environment and Climate Change Canada API.

Parameters:

• timestep (str)

• start_date (datetime.datetime or str, optional)

• end_date (datetime.datetime or str, optional)

• climate_id (str, optional)

Returns:

pandas.DataFrame

miranda.eccc._utils module

miranda.eccc._utils.cf_ahccd_metadata(code: str, gen: int)

CF compliant metadata for ECCC Adjusted and Homogenized Climate Data (AHCCD).

Parameters:

• code ({“dx”, “dn”, “dm”, “dt”, “ds”, “dr”})

• gen ({1, 2, 3})

Returns:

dict[str, int or str or float], dict, list[tuple[int, int]], int

miranda.eccc._utils.cf_station_metadata(variable_code: int | str) → Mapping[str, int | float | str]

CF metadata for hourly station data.

Parameters:

variable_code (int or str)

Returns:

dict

miranda.eccc.geomet module

ECCC Geomet Module.

miranda.eccc.geomet.load_station_metadata(meta: str | PathLike | None) → Dataset

Method to load station metadata from a file or URL.

Parameters:

meta (str or os.PathLike or None) – The path to the file or URL.

Returns:

xr.Dataset – The station metadata.