Sun#

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

This is a singleton instance of the SunClass class.

To use it, simply import it :

from dace_query.sun import Sun
class dace_query.sun.sun.SunClass(dace_instance=None)#

Bases: object

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

Tip

A sun instance is already provided, to use it :

from dace_query.sun import Sun
download(file_type, filters=None, compressed=True, output_directory=None, output_filename=None)#

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

Available spectroscopy product types

file_type

description

's1d'

Extracted merged-1d spectra, corrected from the instrumental blaze, in the Sun’s rest-frame.

's2d'

Extracted echelle-order 1d spectra, corrected from the instrumental blaze, in the Earth rest-frame.

'ccf'

Cross Correlation Function (CCF) obtained by cross-correlating the S2D spectra with a synthetic mask optimised for the Sun.

'all'

Complete product set.

See the Product description document on DACE for more details.

Specifying compression behavior

You can control the compression behavior of the downloaded files using the compressed parameter.

By default, files will be compressed into a .tar.gz archive if multiple files are downloaded.

If you want to disable compression, set the compressed parameter to False. (will result in a .tar archive).

If you want to force compression, set the compressed parameter to True. (will result in a .tar.gz archive).

When downloading large datasets, it is recommended to disable compression by setting compressed=False. This will speed up the download process and reduce memory usage but will result in a larger file size.

Output directory is the location where the downloaded files will be saved.

Output filename is the name of the downloaded file. If not specified, a default name will be used.

Note

When specifying output_filename, be mindful of the appropriate file extension:

When downloading a single file : match the extension to the file type (e.g., output_filename="lightcurve.fits") or leave output_filename as None to use the default name When downloading multiple files : use a .tar or .tar.gz extension (e.g., output_filename="my_data.tar.gz") or leave output_filename as None to use the default name

Parameters:

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

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

  • compressed (Optional[bool]) – Specify whether to compress the downloaded files. (True for .tar.gz, False for .tar)

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

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

Return type:

None

Returns:

None

Downloading sun spectroscopy products using a filepath
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')
Downloading sun spectroscopy products using a specific date
from dace_query.sun import Sun
filters_to_use = {'date_night': {'contains': ['2016-12-10']}}
Sun.download('s1d', filters=filters_to_use)
download_files(file_type='s1d', files=None, output_directory=None, output_filename=None)#

Deprecated since version 2.0.0: This method is deprecated and will be removed in a future version. Use download() with `filters` instead :

files = ['harpn/DRS-3.0.1/reduced/2018-07-16/r.HARPN.2018-07-17T08-10-32.225.fits']
filters: dict = { 'file_rootpath': {'contains': files} }
Sun.download(file_type='s1d', filters=filters)

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

Available spectroscopy product types

file_type

description

's1d'

Extracted merged-1d spectra, corrected from the instrumental blaze, in the Sun’s rest-frame.

's2d'

Extracted echelle-order 1d spectra, corrected from the instrumental blaze, in the Earth rest-frame.

'ccf'

Cross Correlation Function (CCF) obtained by cross-correlating the S2D spectra with a synthetic mask optimised for the Sun.

'all'

Complete product set.

See the Product description document on DACE for more details.

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

Return type:

None

Returns:

None

Downloading sun spectroscopy products given a list of files
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, month, output_directory=None, output_filename=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

Return type:

None

Returns:

None

Downloading public sun data for a given year and month
from dace_query.sun import Sun
Sun.download_public_release_all('2015', '12')  # Downloads the sun data for December 2015
download_public_release_ccf(year, output_directory=None, output_filename=None)#

Download public ccf data realease of year specified in argument.

Parameters:

  • year (str) – 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

Return type:

None

Returns:

None

Downloading public ccf data for a given year
from dace_query.sun import Sun
Sun.download_public_release_ccf('2015') # Downloads the CCF data for 2015
download_public_release_timeseries(period='2015-2018', output_directory=None, output_filename=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

Return type:

None

Returns:

None

Downloading public timeseries data
from dace_query.sun import Sun
Sun.download_public_release_timeseries() # Downloads the timeseries data from 2015 to 2018
query_database(limit=200000, filters=None, sort=None, output_format=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

Getting all sun data
from dace_query.sun import Sun
values = Sun.query_database()