ASDI PROTOTYPE DEMO

TAP Service Introduction

Table Access Protocol (TAP) services allow more direct and flexible access to astronomical data than the simpler types of IVOA standard data services. Queries are built with the SQL-like Astronomical Data Query Language (ADQL), and can include geographic / spatial queries as well as filtering on other characteristics of the data. This also allows the user fine-grained control over the returned columns, unlike the fixed set of coumns returned from cone, image, and spectral services.

Every TAP service has a "Base URL" plus associated endpoints for synchronous and asynchronous queries, as well as status and capability information, and sometimes service-provided sample queries. The endpoints are predefined in the TAP standard, so clients can infer them using the base. We therefore only have to provide astroquery that base. The ASDI Demo Notebook utilizes the astroquery TapPlus library as the client to the search service, whose base URL is below:

from astroquery.utils.tap.core import TapPlus
TAP_URL = "http://vao.stsci.edu/ASDI/tapservice.aspx"
TAP_service = TapPlus(url=TAP_URL)

Browsing the Schema

TAP gives us access to descriptive metadata for this catalog. We can use this to narrow searches and filter our results. For the current catalog, there is only one table, with columns for the project name, nullable fields relevant to various projects, and a public path for downloading associated files.

table_descriptions = TAP_service.load_tables()
print('\n')
for table in table_descriptions:
    if(not table.name.startswith('tap_schema')):
        print('TAP table: ' + table.name)
        print(table.description)
        print('\n')
        for i, column in enumerate(table.columns):
            print(column.name)
            print(column.description,'\n')

Access the ASDI Demo Catalog

The ASDI CGM Spectra metadata catalog contains information about the individual absorption lines through sightlines in simulated galaxies' halos. The database table is accessed by the name dbo.ASDISpectra1DCGM as in the example below. For the ASDI Prototype, we have only one available project, contributed by the FOGGIE collaboration.

# Launch TAP query
job = TAP_service.launch_job("""
            SELECT *
            FROM dbo.ASDISpectra1DCGM 
            WHERE projectName = 'foggie'
            """)
# Obtain results
foggie_results = job.get_results()

# Print available columns in resulting catalog
for c in foggie_results.columns: print(c)

# Display example entires in resulting catalog
foggie_results[['lineName','redshift','totalColumn','impact','publicPath']][0:10]

For further information, see: Peeples et al. (2019)

The ASDI data simulation prototype uses an application programming interface (API) to expose a service that applies STIS instrumental effects to the pristine input spectra, and stream the results back to the user. For this beta version, the API is accessed from the base URL: "https://masttest.stsci.edu/asdi/api/v0.1/addsignature".

To access the API, we can construct Get requests in Python or other languages. The prototype service has only a few options for input parameters to specify the target pristine spectrum, as well as the desired output data simulation properties. Several of these parameters can be obtained by utilizing the ASDI TAP search service described above.

• instrument - Instrument for which we want to simulate data, currently only the 'STIS' option is available.
• element1 - Instrument element, currently only the 'E140H' option is available.
• line_name - Name of the spectral line to simulate, returned by ASDI TAP query.
• ext_num - Extension number of the pristine spectrum FITS file, returned by ASDI TAP query.
• public_path - Path to the pristine input spectrum FITS file, returned by ASDI TAP query.
• snratioresel - Signal to noise ratio per resolution element of the desired data simulation.
• override_observed_wavelength - Center the absorption line at this wavelength, for customizing the mock observation to explore differences in absorber redshift.

Parameter choices are passed to the service by augmenting the URL with strings, which is handled as in the example below using the Python requests library. The beta service can handle one spectrum at a time.

import requests

#use the foggie_results catalog returned from our VO TAP query above
example_result = foggie_results[0]
example_line_name = example_result['lineName']
example_ext_num = example_result['extNum']
example_path = example_result['publicPath']

#the ASDI prototype is accessed through this URL
inst_sim_url = "https://masttest.stsci.edu/asdi/api/v0.1/addsignature"

#construct a dictionary of input parameters
PARAMS = {'instrument':'STIS', 
          'line_name': example_line_name, 
          'ext_num': example_ext_num, 
          'public_path': example_path,
          'snratioresel': 25,
          'override_observed_wavelength': 1500.0} 

#pass the service URL and parameters to Python requests call
r = requests.get(url = inst_sim_url, params = PARAMS, allow_redirects = True)

This last command passes the parameters to the MAST service, which carries out the requested data simulation and returns a response to the user. The response is a JSON object which carries status and (if successful) the resulting simulated spectrum and associated FITS metadata, which allows us to save the result into a new FITS file.

#specify the FITS file in which to save the results
stis_file_path=os.path.join(save_location,STIS_sim_filename)

#response is returned as a JSON object which can be inspected for status and content.
if r.status_code != 200: #show what went wrong
    #print(r.headers)
    print(r.text)
else:
    #if successful, write the content to a FITS file
    open(stis_file_path, 'wb').write(r.content)

With the response saved into a FITS file, we can now inspect the new file and begin to use it:

fo=fits.open(stis_file_path)
print(fo.info())
print(fo['SyntheticData'].data.columns)

See the Demo Notebook at the link below for a more comprehensive demonstration.