@@ -89,11 +89,9 @@ the URLs for downloading the corresponding data.
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caom:CFHT/2366188 2366188 ... md5:f0ec6252250a86963a102351c23d0ca7
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caom:CFHT/2480747 2480747 ... md5:a7cccd9710cbca222dc8f8b1eedff3b5
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caom:CFHT/2480747 2480747 ... md5:c24ace389b760c290a5bf31842fb4ea9
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-
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- .. doctest-skip ::
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>>> urls = cadc.get_data_urls(result)
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>>> for url in urls:
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- ... print (url)
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+ ... print (url) # doctest: +IGNORE_OUTPUT
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...
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https://www.cadc-ccda.hia-iha.nrc-cnrc.gc.ca/data/pub/CFHT/2366432o.fits.fz?RUNID=queoo1qg8y4pgiep
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https://www.cadc-ccda.hia-iha.nrc-cnrc.gc.ca/data/pub/CFHT/2366432p.fits.fz?RUNID=queoo1qg8y4pgiep
@@ -118,12 +116,10 @@ auxiliary data (in this case preview files)
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>>> result = cadc.query_region(' 08h45m07.5s +54d18m00s' )
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>>> print (len (result))
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-
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- .. doctest-skip ::
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>>> urls = cadc.get_data_urls(result[result[' target_name' ] == ' Nr3491_1' ],
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... include_auxiliaries= True )
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>>> for url in urls:
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- ... print (url)
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+ ... print (url) # doctest: +IGNORE_OUTPUT
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...
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https://www.cadc-ccda.hia-iha.nrc-cnrc.gc.ca/data/pub/CFHT/2376828o_preview_zoom_1024.jpg?RUNID=tqlxhnxndjs1xhd3
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https://www.cadc-ccda.hia-iha.nrc-cnrc.gc.ca/data/pub/CFHT/2376828o_preview_256.jpg?RUNID=tqlxhnxndjs1xhd3
@@ -160,7 +156,6 @@ If only a subsection of the FITS file is needed, CADC can query an
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area and resolve the cutout of a result.
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.. code-block :: python
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- .. doctest-skip ::
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.. doctest-remote-data ::
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>>> from astropy import units as u
@@ -170,7 +165,7 @@ area and resolve the cutout of a result.
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>>> radius = 0.01 * u.deg
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>>> images = cadc.get_images(coords, radius, collection = ' CFHT' )
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>>> for image in images:
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- ... print (image)
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+ ... print (image) # doctest: +IGNORE_OUTPUT
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...
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[<astropy.io.fits.hdu.image.PrimaryHDU object at 0x7f3805a06ef0>]
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[<astropy.io.fits.hdu.image.PrimaryHDU object at 0x7f3805b23b38>]
@@ -180,7 +175,6 @@ Alternatively, if the query result is large and data does not need to be
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in memory, lazy access to the downloaded FITS file can be used.
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.. code-block :: python
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- .. doctest-skip ::
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.. doctest-remote-data ::
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>>> from astropy import units as u
@@ -192,7 +186,7 @@ in memory, lazy access to the downloaded FITS file can be used.
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>>> readable_objs = cadc.get_images_async(coords, radius,
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... collection= ' CFHT' )
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>>> for obj in readable_objs:
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- ... print (obj)
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+ ... print (obj) # doctest: +IGNORE_OUTPUT
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...
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Downloaded object from URL https://www.cadc-ccda.hia-iha.nrc-cnrc.gc.ca/caom2ops/sync?ID=ad%3ACFHT%2F2234132o.fits.fz&RUNID=pot39nwwtaht03wc&POS=CIRCLE+26.2812589776878+23.299999818906816+0.01 with ID 140045451168112
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Downloaded object from URL https://www.cadc-ccda.hia-iha.nrc-cnrc.gc.ca/caom2ops/sync?ID=ad%3ACFHT%2F2368279p.fits.fz&RUNID=pot39nwwtaht03wc&POS=CIRCLE+26.2812589776878+23.299999818906816+0.01 with ID 140045451142576
@@ -212,7 +206,6 @@ are needed, the result table can be passed into the
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cutout coordinates and radius.
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.. code-block :: python
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- .. doctest-skip ::
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.. doctest-remote-data ::
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>>> from astroquery.cadc import Cadc
@@ -223,7 +216,7 @@ cutout coordinates and radius.
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>>> results = cadc.query_region(coords, radius, collection = ' CFHT' )
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>>> filtered_results = results[results[' time_exposure' ] > 120.0 ]
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>>> image_list = cadc.get_image_list(filtered_results, coords, radius)
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- >>> print (image_list)
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+ >>> print (image_list) # doctest: +IGNORE_OUTPUT
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['https://www.cadc-ccda.hia-iha.nrc-cnrc.gc.ca/caom2ops/sync?ID=ad%3ACFHT%2F2368278o.fits.fz&RUNID=dbuswaj4zwruzi92&POS=CIRCLE+26.2812589776878+23.299999818906816+0.1',
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'https://www.cadc-ccda.hia-iha.nrc-cnrc.gc.ca/caom2ops/sync?ID=ad%3ACFHT%2F2368278p.fits.fz&RUNID=dbuswaj4zwruzi92&POS=CIRCLE+26.2812589776878+23.299999818906816+0.1',
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'https://www.cadc-ccda.hia-iha.nrc-cnrc.gc.ca/caom2ops/sync?ID=ad%3ACFHT%2F2368279p.fits.fz&RUNID=dbuswaj4zwruzi92&POS=CIRCLE+26.2812589776878+23.299999818906816+0.1',
@@ -508,15 +501,14 @@ The results can be saved in memory (default) or in a file.
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Query without saving results in a file:
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.. code-block :: python
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- .. doctest-skip ::
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.. doctest-remote-data ::
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>>> from astroquery.cadc import Cadc
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>>> cadc = Cadc()
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>>> job = cadc.create_async(" SELECT TOP 100 observationID, instrument_name, target_name FROM caom2.Observation AS Observation" )
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>>> job.run().wait()
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>>> job.raise_if_error()
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- >>> print (job.fetch_result().to_table())
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+ >>> print (job.fetch_result().to_table()) # doctest: +IGNORE_OUTPUT
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observationID intent
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----------------------------------------------- -----------
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j8eh03boq science
@@ -552,7 +544,6 @@ the job.
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.. code-block :: python
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- .. doctest-skip ::
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.. doctest-remote-data ::
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>>> from astroquery.cadc import Cadc
@@ -561,7 +552,7 @@ the job.
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>>> job.run().wait()
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>>> job.raise_if_error()
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>>> loaded_job = cadc.load_async_job(jobid = job.job_id)
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- >>> print (loaded_job.fetch_result().to_table())
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+ >>> print (loaded_job.fetch_result().to_table()) # doctest: +IGNORE_OUTPUT
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observationID instrument_name target_name
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---------------------------- ---------------- --------------------------------
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C090503_0500 CPAPIR SH87
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