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- ESA Integral Science Legacy Archive (ISLA) (`astroquery.esa.integral`)

# ESA Integral Science Legacy Archive (ISLA) (`astroquery.esa.integral`)

INTEGRAL is the INTernational Gamma-Ray Astrophysics Laboratory of the European Space Agency. It observes the Universe in the X-ray and soft gamma-ray band. Since its launch, on October 17, 2002, the ISDC receives the spacecraft telemetry within seconds and provides alerts, processed data and analysis software to the worldwide scientific community.

## Examples

### 1. ADQL Queries to ISLA TAP

The Query TAP functionality facilitates the execution of custom Table Access Protocol (TAP) queries within the Integral Science Legacy Archive. Results can be exported to a specified file in the chosen format, and queries may be executed asynchronously.

    >>> from astroquery.esa.integral import IntegralClass
    >>> isla = IntegralClass()
    >>> isla.query_tap(query='select * from ivoa.obscore')
    <Table length=6743>
    access_estsize   access_format                                     access_url                                   calib_level ...    t_max       t_min    t_resolution t_xel
        int64            object                                          object                                        int32    ...   float64     float64     float64    int64
    -------------- ----------------- ------------------------------------------------------------------------------ ----------- ... ----------- ----------- ------------ -----
             26923 application/x-tar https://isla.esac.esa.int/tap/data?retrieval_type=SCW&b2JzaWQ9MDA2MDAwMjAwMDE=           2 ... 52594.80985 52593.47308      6.1e-05     1
            488697 application/x-tar https://isla.esac.esa.int/tap/data?retrieval_type=SCW&b2JzaWQ9MDA2MDAwNDAwMDE=           2 ... 52596.64583 52596.46613      6.1e-05     1
           3459831 application/x-tar https://isla.esac.esa.int/tap/data?retrieval_type=SCW&b2JzaWQ9MDA2MDAwNjAwMDI=           2 ... 52600.54167  52599.4592      6.1e-05     1
               ...               ...                                                                            ...         ... ...         ...         ...          ...   ...
            351253 application/x-tar https://isla.esac.esa.int/tap/data?retrieval_type=SCW&b2JzaWQ9ODg4MDExMzAwMDQ=           2 ... 57188.63542 57188.28125      6.1e-05     1
             10195 application/x-tar https://isla.esac.esa.int/tap/data?retrieval_type=SCW&b2JzaWQ9ODg4MDExMzAwMDU=           2 ... 57189.64284 57189.28867      6.1e-05     1
            817730 application/x-tar https://isla.esac.esa.int/tap/data?retrieval_type=SCW&b2JzaWQ9ODg5OTgwMTAzMDE=           2 ... 52636.82597 52636.49534      6.1e-05     1

### 2. Getting sources

Users can utilize this method to retrieve a target from the Archive by specifying a target name. The output can be formatted and saved as needed.

    >>> from astroquery.esa.integral import IntegralClass
    >>> isla = IntegralClass()
    >>> isla.get_sources(target_name='crab')
    <Table length=1>
     name          ra               dec           source_id
    object      float64           float64           object
    ------ ----------------- ----------------- ----------------
      Crab 83.63320922851562 22.01447105407715 J053432.0+220052

### 3. Getting metadata associated to sources

By invoking this method, users gain access to detailed metadata for a given source, identified by its target name. The metadata provides in-depth information about the source’s archival.

    >>> from astroquery.esa.integral import IntegralClass
    >>> isla = IntegralClass()
    >>> metadata = isla.get_source_metadata(target_name='Crab')
    >>> metadata
    [{'name': 'Integral', 'link': None, 'metadata': [{'param': 'Name', 'value': 'Crab'}, {'param': 'Id', 'value': 'J053432.0+220052'}, {'param': 'Coordinates degrees', 'value': '83.6324 22.0174'}, {'param': 'Coordinates', 'value': '05 34 31.78 22 01 02.64'}, {'param': 'Galactic', 'value': '184.55 -5.78'}, {'param': 'Isgri flag2', 'value': 'very bright source'}, {'param': 'Jemx flag', 'value': 'detected'}, {'param': 'Spi flag', 'value': 'detected'}, {'param': 'Picsit flag', 'value': 'detected'}]}, {'name': 'Simbad', 'link': 'https://simbad.cds.unistra.fr/simbad/sim-id?Ident=Crab', 'metadata': [{'param': 'Id', 'value': 'NAME Crab'}, {'param': 'Type', 'value': 'SuperNova Remnant'}, {'param': 'Other types', 'value': 'HII|IR|Psr|Rad|SNR|X|gam'}]}]

### 4. Retrieving observations from ISLA

Observation data can be extracted using this method, defining a criteria such as target name, coordinates, search radius, time range, or revolution number range. The data can be formatted and saved to a file, with the option to perform the operation asynchronously.

    >>> from astroquery.esa.integral import IntegralClass
    >>> isla = IntegralClass()
    >>> isla.get_observations(target_name='crab', radius=12.0, start_revno='0290', end_revno='0599')
    <Table length=27>
        dec                 email              end_revno       endtime       ...      starttime       surname                               title
     float64               str60                object         object       ...        object         str20                                str120
    ---------- ------------------------------ --------- ------------------- ... ------------------- ---------- --------------------------------------------------------------
    26.3157778 peter.kretschmar!@obs.unige.ch      0352 2005-09-02 21:20:59 ... 2005-08-31 11:07:06 Kretschmar Target of Opportunity Observations of an Outburst in A 0535+26
        22.684             isdc-iswt@unige.ch      0300 2005-03-30 22:42:38 ... 2005-03-30 10:34:41       ISWT                                 Crab spring/05 IBIS 10 deg arc
        20.611             isdc-iswt@unige.ch      0300 2005-03-31 13:35:11 ... 2005-03-30 22:44:07       ISWT                                 Crab spring/05 IBIS 10 deg arc
           ...                            ...       ...                 ... ...                 ...        ...                                                            ...
    22.0144444         inthelp@sciops.esa.int      0541 2007-03-21 00:08:52 ... 2007-03-20 21:30:30     Public                       Crab-2007 Spring: JEM-X VC settings test
    22.0144444         inthelp@sciops.esa.int      0541 2007-03-22 03:16:24 ... 2007-03-21 00:10:22     Public                         Crab-2007 Spring: IBIS on-axis staring
    22.0144444         inthelp@sciops.esa.int      0541 2007-03-20 15:35:22 ... 2007-03-19 12:53:21     Public                              Crab-2007 Spring: SPI 5x5 pattern

### 5. Downloading Science Windows

Science window data can be downloaded using this method by providing only one identifier, such as science window IDs, observation ID, revolution number, or proposal ID. An additional parameter, read_fits (default value True) reads automatically the downloaded FITS files.

- If `read_fits=True`, a list of objects containing filename, path and the FITS file opened is returned.

- If `read_fits=False`, the file name and path where the file has been downloaded is provided.

    >>> from astroquery.esa.integral import IntegralClass
    >>> isla = IntegralClass()
    >>> results = isla.download_science_windows(science_windows=['008100430010', '033400230030'], output_file=None)

### 6. Timeline retrieval

This method enables the exploration of the observation timeline for a specific region in the sky. Users can provide right ascension (RA) and declination (Dec) coordinates and adjust the radius to refine their search.

    >>> from astroquery.esa.integral import IntegralClass
    >>> from astropy.coordinates import SkyCoord
    >>> isla = IntegralClass()
    >>> coordinates = SkyCoord(83.63320922851562, 22.01447105407715, unit="deg")
    >>> timeline = isla.get_timeline(coordinates=coordinates)
    >>> timeline
    {'total_items': 8714, 'fraFC': 0.8510442965343126, 'totEffExpo': 16416293.994214607, 'timeline': <Table length=8714>
         scwExpo            scwRevs                scwTimes                scwOffAxis
         float64            float64                 object                  float64
    ------------------ ------------------ -------------------------- ---------------------
     5147.824025240096  39.07800595179441 2003-02-07 07:01:25.500000 0.0025430719729003476
     4212.920636876789  39.09690979681126 2003-02-07 08:21:21.500000 0.0025430719729003476
     4212.920651101999  39.11392562227784 2003-02-07 09:33:18.500000 0.0025430719729003476
                   ...                ...                        ...                   ...
    1675.7455103834102 2767.3106645083526 2024-04-17 13:39:13.500000     4.729406754053243
    1815.2853971426027   2767.31963717696 2024-04-17 14:13:35.500000     4.203559877974954
      2014.34083657953 2767.3294779577823        2024-04-17 14:51:17     4.731196416616404}

### 7. Retrieving epochs

A list of observation epochs can be retrieved using this method, focusing on periods when data for a specific target, instrument, or energy band is available.

    >>> from astroquery.esa.integral import IntegralClass
    >>> isla = IntegralClass()
    >>> isla.get_epochs(target_name='J011705.1-732636', band='28_40')
    <Table length=50>
         epoch
         object
    ----------------
    0152_01200360001
    0745_06340000001
    0746_06340000001
                 ...
    1618_12200430006
    1618_12200430009
    1618_12200430011

This will perform an ADQL search to the Integral database and will return the output.

### 8. Data Download

For each of the following features, an additional parameter, read_fits, is available.

- If `read_fits=True`, a list of objects containing filename, path and the FITS file opened is returned.

- If `read_fits=False`, the file names and paths where the files have been downloaded is provided.

#### 8.1. Retrieving Long-Term Timeseries

This method provides access to long-term timeseries data for a specified target. Users can refine their results by selecting an instrument or energy band.

    >>> from astroquery.esa.integral import IntegralClass
    >>> isla = IntegralClass()
    >>> ltt = isla.get_long_term_timeseries(target_name='J174537.0-290107', instrument='jem-x')

#### 8.2. Retrieving Short-Term Timeseries

This method allows for the download of short-term time series data for a target and epoch of interest. Users can refine their search using instrument or energy band filters and the results are saved to a file for detailed examination.

    >>> from astroquery.esa.integral import IntegralClass
    >>> isla = IntegralClass()
    >>> stt = isla.get_short_term_timeseries(target_name='J011705.1-732636', band='28_40', epoch='0745_06340000001')

#### 8.3. Retrieving spectra

This method allows users to download spectral data for a target and epoch. Users can apply filters, such as instrument or energy band, and save the results to an output file for further processing.

    >>> from astroquery.esa.integral import IntegralClass
    >>> isla = IntegralClass()
    >>> spectra = isla.get_spectra(target_name='J011705.1-732636', instrument='ibis', epoch='0745_06340000001')

#### 8.4. Retrieving mosaics

Mosaic images corresponding to a specified epoch can be downloaded using this method. Users can filter by instrument or energy band and save the resulting image to a file for later use.

    >>> from astroquery.esa.integral import IntegralClass
    >>> isla = IntegralClass()
    >>> mosaics = isla.get_mosaic(epoch='0727_88601650001', instrument='ibis')

##### Reference/API

###### astroquery.esa.integral Package

European Space Astronomy Centre (ESAC) European Space Agency (ESA)

###### Classes

`IntegralClass`([auth_session]) | Class to init ESA Integral Module and communicate with isla
`Conf`() | Configuration parameters for `astroquery.esa.integral`.