Page History
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Service name | Service Description | Type | Link to column descriptions |
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LoTSS-DR2 Gaussian catalog cone search | catalog | info | |
LoTSS-DR2 Source catalog cone search | |||
LoTSS-DR2 mosaics | image |
Selecting a data collection allows the user to perform a cone search through a webform (Fig. 40). The result is either a source or Gaussian list, or a table of data products of that given class overlapping a given pointing. The size of the continuum images as well as the cubes extend beyond the 10% primary beam level for cleaning the secondary lobes of bright offset sources. To ensure that the search is done in the area of maximum sensitivity the search is performed on a maxim radius of 0.75 degrees from the center (this represents the average value of where the sensitivity drops). This value can be modified using the Max distance from center. A different output with respect to the default can be customized using More output fields selection button.
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#To start you have to import the library pyvo (it is also possible to use astroquery if you want) import pyvo ## To perform a TAP query you have to connect to the service first tap_service = pyvo.dal.TAPService('https://vo.astron.nl/__system__/tap/run/tap') # This works also for form pyvo.registry.regtap import ivoid2service vo_tap_service = ivoid2service('ivo://astron.nl/tap')[0] # The TAPService object provides some introspection that allow you to check the various tables and their # description for example to print the available tables you can execute print('Tables present on http://vo.astron.nl') for table in tap_service.tables: print(table.name) print('-' * 10 + '\n' * 3) # or get the column names print('Available columns in apertif_dr1.continuum_images') print(tap_service.tables['apertif_dr1.continuum_images'].columns) print('-' * 10 + '\n' * 3) ## You can obviously perform tap queries accross the whole tap service as an example a cone search print('Performing TAP query') result = tap_service.search( "SELECT TOP 5 target, beam_number, accref, centeralpha, centerdelta, obsid, DISTANCE(" \ "POINT('ICRS', centeralpha, centerdelta),"\ "POINT('ICRS', 208.36, 52.36)) AS dist"\ " FROM apertif_dr1.continuum_images" \ " WHERE 1=CONTAINS(" " POINT('ICRS', centeralpha, centerdelta),"\ " CIRCLE('ICRS', 208.36, 52.36, 0.08333333)) "\ " ORDER BY dist ASC" ) print(result) # The result can also be obtained as an astropy table astropy_table = result.to_table() print('-' * 10 + '\n' * 3) ## You can also download and plot the image import astropy.io.fits as fits from astropy.wcs import WCS import matplotlib.pyplot as plt import requests, os import numpy as np # DOWNLOAD only the first result # print('Downloading only the first result') file_name = '{}_{}_{}.fits'.format( result[0]['obsid'].decode(), result[0]['target'].decode(), result[0]['beam_number']) path = os.path.join(os.getcwd(), file_name) http_result = requests.get(result[0]['accref'].decode()) print('Downloading file in', path) with open(file_name, 'wb') as fout: for content in http_result.iter_content(): fout.write(content) hdu = fits.open(file_name)[0] wcs = WCS(hdu.header) # dropping unnecessary axes wcs = wcs.dropaxis(2).dropaxis(2) plt.subplot(projection=wcs) plt.imshow(hdu.data[0, 0, :, :], vmax=0.0005) plt.xlabel('RA') plt.ylabel('DEC') plt.show() |
Export machine readable table
There are multiple ways to export a catalog of the various data products of the data release. On the vo.astron.nl pages, the results of a query can be exported to a csv file or fits table; running an empty query with a table limit of 5000 or more will return all entries.
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