dace_query.sun package

Submodules

dace_query.sun.sun module

dace_query.sun.sun.Sun: SunClass = <dace_query.sun.sun.SunClass object>

Sun instance

class dace_query.sun.sun.SunClass(dace_instance: DaceClass | None = None)

Bases: object

The sun class. Use to retrieve data from the sun module.

A sun instance is already provided, to use it :

>>> from dace_query.sun import Sun
download(file_type: str, filters: dict | None = None, output_directory: str | None = None, output_filename: str | None = None) → None

Download Sun spectroscopy products (S1D, S2D, …).

Available file types are [ ‘s1d’, ‘s2d’, ‘ccf’, ‘bis’, ‘all’ ].

Parameters:

  • file_type – The type of files to download

  • filters (Optional[dict]) – Filters to apply to the query

  • output_directory (Optional[str]) – The directory where files will be saved

  • output_filename (Optional[str]) – The filename for the download

Returns:

None

>>> from dace_query.sun import Sun
>>> filters_to_use = {'file_rootpath': {'contains': ['r.HARPN.2016-01-03T15-36-20.496.fits']}}
>>> # Sun.download('s1d', filters=filters_to_use, output_directory='/tmp', output_filename='sun_spectroscopy_data.tar.gz')
download_files(file_type: str | None = 's1d', files: list[str] | None = None, output_directory: str | None = None, output_filename: str | None = None) → None

Download reduction products specified in argument for the list of raw files specified and save it locally.

Available file types are [ ‘s1d’, ‘s2d’, ‘ccf’, ‘bis’, ‘all’ ].

Parameters:

  • file_type (Optional[str]) – The type of files to download

  • files (list[str]) – The raw files

  • output_directory (Optional[str]) – The directory where files will be saved

  • output_filename (Optional[str]) – The filename for the download

Returns:

None

>>> from dace_query.sun import Sun
>>> files_to_retrieve = ['harpn/DRS-2.3.5/reduced/2016-01-03/r.HARPN.2016-01-03T15-36-20.496.fits']
>>> # Sun.download_files('s1d', files=files_to_retrieve, output_directory='/tmp', output_filename='files.tar.gz')
download_public_release_all(year: str, month: str, output_directory: str | None = None, output_filename: str | None = None) → None

Download public sun data of year and month specified in arguments.

Parameters:

  • year (str) – The year for sun data

  • month (str) – The month for sun data

  • output_directory (Optional[str]) – The directory where files will be saved

  • output_filename (Optional[str]) – The filename for the download

Returns:

None

>>> from dace_query.sun import Sun
>>> # Sun.download_public_release_all('2015','12', output_directory='/tmp', output_filename='release_all_2015-12.tar.gz')
download_public_release_ccf(year: str, output_directory: str | None = None, output_filename: str | None = None) → None

Download public ccf data realease of year specified in argument.

Parameters:

  • year – The year for the ccf data

  • output_directory (Optional[str]) – The directory where files will be saved

  • output_filename (Optional[str]) – The filename for the download

Returns:

None

>>> from dace_query.sun import Sun
>>> # Sun.download_public_release_ccf('2015', output_directory='/tmp', output_filename='cff.tar.gz')
download_public_release_timeseries(period: str | None = '2015-2018', output_directory: str | None = None, output_filename: str | None = None) → None

Download public timeseries data release for a specified period and save it locally.

The only available period is ‘2015-2018’.

Parameters:

  • period (Optional[str]) – The period

  • output_directory (Optional[str]) – The directory where files will be saved

  • output_filename (Optional[str]) – The filename for the download

Returns:

None

>>> from dace_query.sun import Sun
>>> # Sun.download_public_release_timeseries(output_directory='/tmp', output_filename='public_release_timeseries.rdb')
query_database(limit: int | None = 200000, filters: dict | None = None, sort: dict | None = None, output_format: str | None = None)

Query the sun database to retrieve data in the chosen format.

Filters and sorting order can be applied to the query via named arguments (see Filtering and sorting).

All available formats are defined in this section (see Output formats).

Parameters:

  • limit (Optional[int]) – Maximum number of rows to return

  • filters (Optional[dict]) – Filters to apply to the query

  • sort (Optional[dict]) – Sort order to apply to the query

  • output_format (Optional[str]) – Type of data returns

Returns:

The desired data in the chosen output format

Return type:

dict[str, ndarray] or DataFrame or Table or dict

>>> from dace_query.sun import Sun
>>> values = Sun.query_database()

Module contents