def process_magnitudes(self):
job = self.analysis.astrometry_job
submission = job.submission
logger.info('-> Processing reference stars/magnitudes for submission %d' % \
(submission.subid))
coords = urllib.urlopen(self.analysis.coords_json_url).read()
correlations = urllib.urlopen(self.analysis.astrometry_corr_fits_url).read()
# Compute reference stars and their apparent magnitudes.
ref_stars, unknown_stars = \
catalog.choose_reference_stars(self.image_fits_data, correlations, coords)
name = '%d_%d_image_reference_stars.json' % (submission.subid, job.jobid)
logger.info(' -> Uploading %s...' % name)
if not args.dry_run:
self.analysis.image_reference_stars = ref_stars
self.analysis.image_reference_stars_json_url = \
s3_util.upload_to_s3(json.dumps(ref_stars, indent=2, use_decimal=True), \
self.get_upload_key_prefix(), name)
logger.info('-> Uploaded reference stars for submission %d' % \
(submission.subid))
name = '%d_%d_image_unknown_stars.json' % (submission.subid, job.jobid)
logger.info(' -> Uploading %s...' % name)
if not args.dry_run:
self.analysis.image_unknown_stars = unknown_stars
self.analysis.image_unknown_stars_json_url = \
s3_util.upload_to_s3(json.dumps(unknown_stars, indent=2, use_decimal=True), \
self.get_upload_key_prefix(), name)
logger.info('-> Uploaded unknown stars for submission %d' % \
(submission.subid))
# Get reference star standard magnitudes.
standard_mags = catalog.get_standard_magnitudes_urat1(ref_stars)
name = '%d_%d_catalog_reference_stars.json' % (submission.subid, job.jobid)
logger.info(' -> Uploading %s...' % name)
if not args.dry_run:
self.analysis.catalog_reference_stars = standard_mags
self.analysis.catalog_reference_stars_json_url = \
s3_util.upload_to_s3(json.dumps(standard_mags, indent=2, use_decimal=True), \
self.get_upload_key_prefix(), name)
# Combine into single annotated point sources object.
all_points = catalog.merge_known_with_unknown(standard_mags, unknown_stars)
name = '%d_%d_annotated_point_sources.json' % (submission.subid, job.jobid)
logger.info(' -> Uploading %s...' % name)
if not args.dry_run:
self.analysis.annotated_point_sources = all_points
self.analysis.annotated_point_sources_json_url = \
s3_util.upload_to_s3(json.dumps(all_points, indent=2, use_decimal=True), \
self.get_upload_key_prefix(), name)
logger.info('-> Uploaded annotated point sources for submission %d' % \
(submission.subid))
def upload_graph(lightcurve, img_graph):
logger.info('-> Uploading tf graph for lightcurve %d' % (lightcurve.id))
upload_key_prefix = 'processed/lightcurve/%d' % (lightcurve.id)
name = 'tf_graph.jpg'
logger.info(' -> Uploading %s...' % name)
return upload_to_s3(img_graph, upload_key_prefix, name)
def edit_lightcurve(user, imgs, lightcurve_id):
lc = get_object_or_404(LightCurve, id=lightcurve_id, user=user)
for img in imgs:
url = s3_util.upload_to_s3(img.read(), 'raw', img.name)
print 'Uploaded %s to s3 url: %s' % (img.name, url)
UserUploadedImage(user=user,
image_url=url,
original_filename=img.name,
lightcurve=lc).save()
return lc
def process_submission(self, job):
submission = self.submission
logger.info('-> Uploading analysis for submission %d' %
(submission.subid))
# TODO(ian): Move this to astropy_util.py
original_display_url = astrometry_original_image_client.get_url(
submission.subid)
annotated_display_url = 'http://35.202.61.141:8081/annotated_display/%d' \
% (job.jobid)
new_image_fits_url = 'http://35.202.61.141:8081/new_fits_file/%d' \
% (job.jobid)
corr_url = 'http://35.202.61.141:8081/corr_file/%d' \
% (job.jobid)
# Original
name = '%d_%d_original.jpg' % (submission.subid, job.jobid)
logger.info(' -> Uploading %s...' % name)
if not args.dry_run:
self.analysis.astrometry_original_display_url = \
s3_util.upload_to_s3_via_url(original_display_url, \
self.get_upload_key_prefix(), name)
# Annotated jpg.
name = '%d_%d_annotated.jpg' % (submission.subid, job.jobid)
logger.info(' -> Uploading %s...' % name)
if not args.dry_run:
self.analysis.astrometry_annotated_display_url = \
s3_util.upload_to_s3_via_url(annotated_display_url, \
self.get_upload_key_prefix(), name)
# CORR.
name = '%d_%d_corr.fits' % (submission.subid, job.jobid)
logger.info(' -> Uploading %s...' % name)
if not args.dry_run:
self.analysis.astrometry_corr_fits_url = \
s3_util.upload_to_s3_via_url(corr_url, \
self.get_upload_key_prefix(), name)
# FITS.
name = '%d_%d_image.fits' % (submission.subid, job.jobid)
# TODO(ian): Process this raw fits data here using some util fn, rather
# than processing it in point_source_extraction.
self.image_fits_data = urllib.urlopen(new_image_fits_url).read()
logger.info(' -> Uploading %s...' % name)
if not args.dry_run:
self.analysis.astrometry_image_fits_url = \
s3_util.upload_to_s3(self.image_fits_data, \
self.get_upload_key_prefix(), name)
logger.info('-> Uploaded analysis for submission %d' %
(submission.subid))
def upload_image(request):
if request.method == 'POST':
img = request.FILES['image']
# Data is read just once to avoid rewinding.
img_data = img.read()
url = s3_util.upload_to_s3(img_data, 'raw', img.name)
submission = process_astrometry_online(url)
# Redirect to submission viewing page.
return redirect('view_submission', subid=submission.subid)
return render_to_response('upload_image.html', {},
context_instance=RequestContext(request))
def create_new_lightcurve(user, imgs):
date = datetime.datetime.today().strftime('%Y-%m-%d')
lc = LightCurve(user=user, name='%s %s' % (user.username, date))
lc.save()
for img in imgs:
url = s3_util.upload_to_s3(img.read(), 'raw', img.name)
print 'Uploaded %s to s3 url: %s' % (img.name, url)
UserUploadedImage(user=user,
image_url=url,
original_filename=img.name,
lightcurve=lc).save()
return lc
def save_submission_results(self, job, result):
submission = self.submission
logger.info('-> Uploading results for submission %d' % (submission.subid))
annotated_display_url = 'http://nova.astrometry.net/annotated_display/%d' \
% (job.jobid)
new_image_fits_url = 'http://nova.astrometry.net/new_fits_file/%d' \
% (job.jobid)
corr_url = 'http://nova.astrometry.net/corr_file/%d' \
% (job.jobid)
# Timestamp is added to name automatically.
upload_key_prefix = 'processed/%d' % (submission.subid)
# Annotated jpg.
name = '%d_%d_annotated.jpg' % (submission.subid, job.jobid)
logger.info(' -> Uploading %s...' % name)
if not args['dry_run']:
result.astrometry_annotated_display_url = \
s3_util.upload_to_s3_via_url(annotated_display_url, \
upload_key_prefix, name)
# CORR.
name = '%d_%d_corr.fits' % (submission.subid, job.jobid)
logger.info(' -> Uploading %s...' % name)
if not args['dry_run']:
result.astrometry_corr_fits_url = \
s3_util.upload_to_s3_via_url(corr_url, \
upload_key_prefix, name)
# FITS.
name = '%d_%d_image.fits' % (submission.subid, job.jobid)
fits_image_data = urllib.urlopen(new_image_fits_url).read()
logger.info(' -> Uploading %s...' % name)
if not args['dry_run']:
result.astrometry_image_fits_url = \
s3_util.upload_to_s3(fits_image_data, \
upload_key_prefix, name)
logger.info('-> Uploaded results for submission %d' % (submission.subid))
# Point source extraction processing.
self.process_fits_image(fits_image_data, job, result, upload_key_prefix)
