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fritz.py documentation

**THIS DOCUMENTATION IS OUTDATED FOR VERSION >1.14 ; SEE TUTORIALS FOR NOW **

ztfquery.fritz.py is module to access data from fritz.science.

Requirements

  • You need an account on fritz.science and you need to create a token from your profile
  • You need a ztfquery version >= 1.12.0

Examples

LightCurves and Photometry

from ztfquery import fritz
lc = fritz.download_lightcurve("ZTF20acmzoxo", get_object=True)
# or if you already have done it and want the stored version:
# lc = fritz.get_local_lightcurve("ZTF20acmzoxo", directory="default")
lc.show()

The data downloaded from fritz are store, as pandas.DataFrame as lc.data:

print(lc.data.columns)
> Index(['obj_id', 'ra', 'dec', 'filter', 'mjd', 'instrument_id',
       'instrument_name', 'ra_unc', 'dec_unc', 'origin', 'id', 'groups', 'mag',
       'magerr', 'magsys', 'limiting_mag'],
      dtype='object')

You can for instance get all the reported coordinates by doing:

lc.get_coordinates(full=True)
> # DataFrame
              ra	dec
    0	331.205290	16.856651
    2	331.205307	16.856643
    4	331.205307	16.856643
    5	331.205293	16.856643
    6	331.205317	16.856641
    ...	...	...
    289	331.205293	16.856636
    290	331.205293	16.856636
    291	331.205295	16.856650
    292	331.205303	16.856639
    293	331.205295	16.856650

or get an estimation of the likely extact coordinate by taking a median of that:

lc.get_coordinates(method="nanmedian")
> array([331.2052937,  16.8566374])

Finally, you can simply filter the input data using the get_data() method. Say you want the "i" band detected data from 22nd of Oct 2020 to 15th of Nov 2020:

filtereddata = lc.get_data(filters="ztfi", detected=True, time_range=["2020-10-22", "2020-11-15"])

You can pass this filtering to the show() method:

from ztfquery import fritz
lc = fritz.download_lightcurve("ZTF20acmzoxo", get_object=True)
lc.show(filtering= dict(filters="ztfi", detected=True, time_range=["2020-10-22", "2020-11-15"]) )

I/O: Use the lc.store(fileout) to store the lightcurve. (calling spec.to_csv, spec.to_hdf or spec.to_json depending on the extension given)

Spectra

from ztfquery import fritz
spec = fritz.download_spectra("ZTF20acmzoxo", get_object=True, dirout="default")
# or if you already have done it and want the stored version: 
# spec = fritz.get_local_spectra("ZTF20acmzoxo", directory="default")
spec.show()

The data downloaded from () are stored as spec.fritzdict:

print(spec.fritzdict.keys())
> dict_keys(['created_at', 'followup_request_id', 'modified', 'assignment_id', 'wavelengths', 'altdata', 'fluxes', 'original_file_string', 'errors', 'original_file_filename', 'obj_id', 'owner_id', 'observed_at', 'id', 'origin', 'instrument_id', 'groups', 'instrument_name', 'reducers', 'observers'])

An pyifu.Spectrum object is created as spec.spectrum (from which the aforementioned show() comes from). It contains methods like spec.spectrum.synthesize_photometry(filter_wave, filter_trans) or spec.spectrum.scale_by(flux_or_array).

I/O: Use the spec.store(fileout) to store the spectrum. (calling spec.to_fits, spec.to_ascii, spec.to_json or spec.to_txt depending on the extension given)

FritzAccess

FritzAccess is a general user-based access to Fritz. The mostly enables you to access the sources associated to your groups.

faccess = fritz.FritzAccess()

Load your group (loading the faccess.groups FritzGroups object, see download_groups())

faccess.load_groups()

the groups you have access to are:

print(faccess.groups.accessible)
> # DataFrame
       nickname	       modified	              id	name	       single_user_group	created_at
0	infant	2020-10-21T06:20:34.549465	49	Infant Supernovae	False	2020-10-21T06:20:34.549465
...
4	SNeIa	2020-11-15T09:33:18.151551	177	Type Ia Supernovae	False	2020-11-15T09:33:18.151551

and to get the sources associated to a group (might be slow).

faccess.load_sources("SNeIa")

You can load several groups one at the time or together by providing a list like faccess.load_sources(["infant","SNeIa"]) to get load sources be only from one group:

source_df= faccess.get_group_sources("SNeIa")
print(source_df.keys())
> Index(['id', 'origin', 'dist_nearest_source', 'ra_dis', 'internal_key',
       'mag_nearest_source', 'dec_dis', 'detect_photometry_count',
       'e_mag_nearest_source', 'ra_err', 'created_at', 'transient', 'dec_err',
       'modified', 'varstar', 'offset', 'ra', 'is_roid', 'redshift', 'dec',
       'score', 'redshift_history', 'altdata', 'thumbnails', 'comments',
       'classifications', 'annotations', 'last_detected', 'gal_lon', 'gal_lat',
       'luminosity_distance', 'dm', 'angular_diameter_distance', 'groups'],
      dtype='object')

FritzAccess.get_target_{}

Finally, you have faccess.get_target_{}([options]) methods where {} could be classification, coordinates, redshift, jdrange and data.

You have in addition faccess.get_target_metadataquery() that you can directly pass to ZTFQuery.load_metatable() to download IRSA data associated to this source.

FritzAccess.load_local()

Since downloading sources could be very slow, every time you do that, the data are stored locally as $ZTFDATA/fritz/{groupname}_sources.csv. If you are happy with accessing the stored versions, simply do:

from ztfquery import fritz
faccess = fritz.FritzAccess.load_local()

(you can still do facces.load_sources(groupname) to download the latest version, which will automatically be stored, updating $ZTFDATA/fritz/{groupname}_sources.csv).

Source(s)

Alerts

Groups

Structure

With ztfquery.fritz.py you can download and store locally lightcurve, spectra, alerts, sources and groups information. For convinience, each of these have a dedicated python object, e.g., FritzSpectrum, FritzGroups or FritzPhotometry.

ztfquery.fritz.py has global functions for quick access:

  • For downloading: download_{}
  • For getting local data: get_local_{}

Downloads

The functions are called download_{}:

  • download_lightcurve(source_name, [option])
  • download_spectra(source_name, [option])
  • download_alerts(source_name, [option])
  • download_source(source_name, [option])
  • download_sources([option])
  • download_groups([option])

See the [option] to get details but each should have at least the following:

  • token: you can directly provide a token. If not, the first time, this will call for you token (see your profile). I will store it in ~/.ztfquery
  • get_object: Set that to True to for the dedicated FritzObject implemented in ztfquery.fritz.py, if not, this returns the direct download.
  • dirout: Directory where the data are stored. None means no storing at all and 'default' is the ztfquery default structure (highly recommanded).

Get Local

Similarly as download_{} you can access your local files (already downloaded) using the corresponding get_local_{}