Analyze NASA TESS data in the cloud.
Reason this release was yanked:
Insufficient connection pooling - please do not use.
Project description
Analyze the TESS open dataset in AWS S3.
tess-cloud is a user-friendly package which provides fast access to TESS Full-Frame Image (FFI) data in the cloud. It builds upon aioboto3, asyncio, and diskcache to access the TESS data set in AWS S3 in a fast, asynchronous, and cached way.
Installation
python -m pip install tess-cloud
Example use
Retrieve the AWS S3 location of a TESS image:
>>> import tess_cloud
>>> tess_cloud.get_s3_uri("tess2019199202929-s0014-2-3-0150-s_ffic.fits")
"s3://stpubdata/tess/public/ffi/s0014/2019/199/2-3/tess2019199202929-s0014-2-3-0150-s_ffic.fits"
List the images of a TESS sector:
>>> tess_cloud.list_images(sector=5, camera=2, ccd=3)
<TessImageList>
Read a TESS image from S3 into local memory:
>>> from tess_cloud import TessImage
>>> img = TessImage("tess2019199202929-s0014-2-3-0150-s_ffic.fits")
>>> img.read()
<astropy.io.fits.HDUList>
Read only the header of a TESS image into local memory:
>>> img.read_header(ext=1)
<astropy.io.fits.FitsHeader>
Cutout a Target Pixel File for a stationary object:
>>> from tess_cloud import cutout
>>> cutout("Alpha Cen", shape=(10, 10))
TargetPixelFile("Alpha Cen")
Cutout a Target Pixel File centered on a moving asteroid:
>>> from tess_cloud import cutout_asteroid
>>> cutout_asteroid("Vesta", start="2019-04-28", stop="2019-06-28)
TargetPixelFile("Vesta")
Documentation
Coming soon!
Similar services
TESScut is an excellent API service which allows cut outs to be obtained for stationary objects. Tess-cloud provides an alternative implementation of this service by leveraging the TESS public data set on AWS S3.
At this time tess-cloud is an experiment, we recommend that you keep using TESScut for now!
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