def _store_fits_header(self):
"""
Store the FITS headers we need to remember
"""
insert = FITS_HEADER.insert()
header = self._hdu_list[0].header
index = 0
ctype1 = None
ctype2 = None
for keyword in header:
# The new version of PyFits supports comments
value = header[index]
comment = header.comments[index]
self._connection.execute(insert.values(galaxy_id=self._galaxy_id, keyword=keyword, value=value, comment=comment))
# Record the ctype so we can get the RA and DEC
if keyword == 'CTYPE1':
ctype1 = value
elif keyword == 'CTYPE2':
ctype2 = value
# Record the RA and DEC if we can
if keyword == 'RA_CENT' or (ctype1 == 'RA---TAN' and keyword == 'CRVAL1'):
self._connection.execute(GALAXY.update().where(GALAXY.c.galaxy_id == self._galaxy_id).values(ra_cent=float(value)))
elif keyword == 'DEC_CENT' or (ctype2 == 'DEC--TAN' and keyword == 'CRVAL2'):
self._connection.execute(GALAXY.update().where(GALAXY.c.galaxy_id == self._galaxy_id).values(dec_cent=float(value)))
index += 1
def processed_data(connection):
"""
Work out which galaxies have been processed
:param connection:
:return:
"""
# Get the work units still being processed
engine = create_engine(BOINC_DB_LOGIN)
connection_boinc = engine.connect()
current_jobs = []
for result in connection_boinc.execute(select([RESULT]).where(RESULT.c.server_state != 5)):
current_jobs.append(result[RESULT.c.name])
connection_boinc.close()
sorted_data = sort_data(connection, current_jobs)
for key in sorted(sorted_data.iterkeys()):
LOG.info('{0}: {1} results'.format(key, len(sorted_data[key])))
# Get the galaxies we know are still processing
processed = []
for galaxy in connection.execute(select([GALAXY]).where(GALAXY.c.status_id == COMPUTING)):
if finish_processing(galaxy[GALAXY.c.name], galaxy[GALAXY.c.galaxy_id], sorted_data):
processed.append(galaxy[GALAXY.c.galaxy_id])
LOG.info('%d %s has completed', galaxy[GALAXY.c.galaxy_id], galaxy[GALAXY.c.name])
for galaxy_id in processed:
connection.execute(GALAXY.update().where(GALAXY.c.galaxy_id == galaxy_id).values(status_id=PROCESSED, status_time=datetime.datetime.now()))
LOG.info('Marked %d galaxies ready for archiving', len(processed))
LOG.info('%d galaxies are still being processed', len(sorted_data))
def original_image_checked_ami():
"""
We're running in the AMI instance - so do the actual work
Check the newly created images to make sure the images have been created
:return:
"""
# Connect to the database - the login string is set in the database package
ENGINE = create_engine(DB_LOGIN)
connection = ENGINE.connect()
s3helper = S3Helper()
try:
# Look in the database for the galaxies
galaxy_ids = []
for galaxy in connection.execute(select([GALAXY]).where(and_(GALAXY.c.original_image_checked == None, GALAXY.c.pixel_count > 0)).order_by(GALAXY.c.galaxy_id)):
galaxy_ids.append(galaxy[GALAXY.c.galaxy_id])
for galaxy_id in galaxy_ids:
galaxy = connection.execute(select([GALAXY]).where(GALAXY.c.galaxy_id == galaxy_id)).first()
if not image_files_exist(galaxy[GALAXY.c.name], galaxy[GALAXY.c.run_id], galaxy[GALAXY.c.galaxy_id], s3helper):
mark_as_checked = regenerated_original_images(galaxy[GALAXY.c.name], galaxy[GALAXY.c.run_id], galaxy[GALAXY.c.galaxy_id], s3helper, connection)
else:
mark_as_checked = True
if mark_as_checked:
connection.execute(GALAXY.update().where(GALAXY.c.galaxy_id == galaxy_id).values(original_image_checked=datetime.datetime.now()))
except Exception:
LOG.exception('Major error')
finally:
connection.close()
def delete_galaxy(connection, galaxy_ids):
try:
for galaxy_id_str in galaxy_ids:
transaction = connection.begin()
galaxy_id1 = int(galaxy_id_str)
galaxy = connection.execute(
select([GALAXY
]).where(GALAXY.c.galaxy_id == galaxy_id1)).first()
if galaxy is None:
LOG.info('Error: Galaxy with galaxy_id of %d was not found',
galaxy_id1)
else:
LOG.info('Deleting Galaxy with galaxy_id of %d - %s',
galaxy_id1, galaxy[GALAXY.c.name])
area_count = connection.execute(
select([func.count(AREA.c.area_id)
]).where(AREA.c.galaxy_id == galaxy[
GALAXY.c.galaxy_id])).first()[0]
counter = 1
for area_id1 in connection.execute(
select(
[AREA.c.area_id]).where(AREA.c.galaxy_id == galaxy[
GALAXY.c.galaxy_id]).order_by(AREA.c.area_id)):
LOG.info("Deleting galaxy {0} area {1}. {2} of {3}".format(
galaxy_id_str, area_id1[0], counter, area_count))
connection.execute(PIXEL_RESULT.delete().where(
PIXEL_RESULT.c.area_id == area_id1[0]))
# Give the rest of the world a chance to access the database
time.sleep(0.1)
counter += 1
# Now empty the bucket
s3helper = S3Helper()
bucket = s3helper.get_bucket(get_files_bucket())
galaxy_file_name = get_galaxy_file_name(
galaxy[GALAXY.c.name], galaxy[GALAXY.c.run_id],
galaxy[GALAXY.c.galaxy_id])
for key in bucket.list(
prefix='{0}/sed/'.format(galaxy_file_name)):
# Ignore the key
if key.key.endswith('/'):
continue
bucket.delete_key(key)
# Now the folder
key = Key(bucket)
key.key = '{0}/sed/'.format(galaxy_file_name)
bucket.delete_key(key)
LOG.info('Galaxy with galaxy_id of %d was deleted', galaxy_id1)
connection.execute(
GALAXY.update().where(GALAXY.c.galaxy_id == galaxy_id1).values(
status_id=DELETED, status_time=datetime.datetime.now()))
transaction.commit()
except Exception:
LOG.exception('Major error')
def fix_galaxy(galaxy, bucket_files, bucket_galaxy_image):
"""
Fix the galaxy name
:param galaxy:
:return:
"""
old_name = galaxy[GALAXY.c.name]
new_name = old_name[:-1]
galaxy_id = galaxy[GALAXY.c.galaxy_id]
run_id = galaxy[GALAXY.c.run_id]
LOG.info('Fixing {0}({1}) t0 {2}'.format(old_name, galaxy_id, new_name))
for extension in ['fits', 'hdf5']:
copy_files(old_name, new_name, run_id, galaxy_id, extension,
bucket_files)
remove_files_folder(old_name, run_id, galaxy_id, bucket_files)
for file_name in [
'colour_1.png', 'colour_2.png', 'colour_3.png', 'colour_4.png',
'ldust.png', 'm.png', 'mu.png', 'sfr.png', 'tn_colour_1.png'
]:
copy_galaxy_images(old_name, new_name, run_id, galaxy_id, file_name,
bucket_galaxy_image)
remove_galaxy_images_folder(old_name, run_id, galaxy_id,
bucket_galaxy_image)
if DRY_RUN:
LOG.info('Updating {0} to {1}'.format(galaxy_id, new_name))
else:
connection.execute(GALAXY.update().where(
GALAXY.c.galaxy_id == galaxy_id).values(name=new_name))
def delete_galaxy(connection, galaxy_ids):
for galaxy_id in galaxy_ids:
transaction = connection.begin()
galaxy = connection.execute(select([GALAXY]).where(GALAXY.c.galaxy_id == galaxy_id)).first()
if galaxy is None:
LOG.info('Error: Galaxy with galaxy_id of %d was not found', galaxy_id)
else:
LOG.info('Deleting Galaxy with galaxy_id of %d - %s', galaxy_id, galaxy[GALAXY.c.name])
area_count = connection.execute(select([func.count(AREA.c.area_id)]).where(AREA.c.galaxy_id == galaxy[GALAXY.c.galaxy_id])).first()[0]
counter = 1
for area_id1 in connection.execute(select([AREA.c.area_id]).where(AREA.c.galaxy_id == galaxy[GALAXY.c.galaxy_id]).order_by(AREA.c.area_id)):
LOG.info("Deleting galaxy {0} area {1}. {2} of {3}".format(galaxy_id, area_id1[0], counter, area_count))
connection.execute(PIXEL_RESULT.delete().where(PIXEL_RESULT.c.area_id == area_id1[0]))
# Give the rest of the world a chance to access the database
time.sleep(0.1)
counter += 1
if shutdown() is True:
transaction.rollback()
raise SystemExit
LOG.info("Deleting FITS headers for galaxy {0}".format(galaxy_id))
connection.execute(FITS_HEADER.delete().where(FITS_HEADER.c.galaxy_id == galaxy[GALAXY.c.galaxy_id]))
# Now empty the bucket of the sed files
s3helper = S3Helper()
bucket = s3helper.get_bucket(get_sed_files_bucket())
galaxy_file_name = get_galaxy_file_name(galaxy[GALAXY.c.name], galaxy[GALAXY.c.run_id], galaxy[GALAXY.c.galaxy_id])
for key in bucket.list(prefix='{0}/'.format(galaxy_file_name)):
# Ignore the key
if key.key.endswith('/'):
continue
bucket.delete_key(key)
if shutdown() is True:
transaction.rollback()
raise SystemExit
# Now the folder
key = Key(bucket)
key.key = '{0}/'.format(galaxy_file_name)
bucket.delete_key(key)
LOG.info('Galaxy with galaxy_id of %d was deleted', galaxy_id)
connection.execute(GALAXY.update().where(GALAXY.c.galaxy_id == galaxy_id).values(status_id=DELETED, status_time=datetime.datetime.now()))
if shutdown() is True:
transaction.rollback()
raise SystemExit
transaction.commit()
def store_files(hdf5_dir):
"""
Scan a directory for files and send them to the archive
:param hdf5_dir: the directory to scan
:return:
"""
LOG.info('Directory: %s', hdf5_dir)
# Get the work units still being processed
ENGINE = create_engine(DB_LOGIN)
connection = ENGINE.connect()
files = os.path.join(hdf5_dir, '*.hdf5')
file_count = 0
try:
s3helper = S3Helper()
bucket_name = get_files_bucket()
for file_name in glob.glob(files):
size = os.path.getsize(file_name)
galaxy_id, galaxy_name = get_galaxy_id_and_name(file_name)
if galaxy_id >= 0:
key = '{0}/{0}.hdf5'.format(galaxy_name)
LOG.info('File name: %s', file_name)
LOG.info('File size: %d', size)
LOG.info('Bucket: %s', bucket_name)
LOG.info('Key: %s', key)
s3helper.add_file_to_bucket(bucket_name, key, file_name)
file_count += 1
os.remove(file_name)
connection.execute(GALAXY.update().where(
GALAXY.c.galaxy_id == galaxy_id).values(
status_id=STORED, status_time=datetime.datetime.now()))
else:
LOG.error('File name: %s', file_name)
LOG.error('File size: %d', size)
LOG.error('Could not get the galaxy id')
except Exception:
LOG.exception('Major error')
finally:
connection.close()
return file_count
def store_files(hdf5_dir):
"""
Scan a directory for files and send them to the archive
:param hdf5_dir: the directory to scan
:return:
"""
LOG.info('Directory: %s', hdf5_dir)
# Get the work units still being processed
ENGINE = create_engine(DB_LOGIN)
connection = ENGINE.connect()
files = os.path.join(hdf5_dir, '*.hdf5')
file_count = 0
try:
s3helper = S3Helper()
bucket_name = get_files_bucket()
for file_name in glob.glob(files):
size = os.path.getsize(file_name)
galaxy_id, galaxy_name = get_galaxy_id_and_name(file_name)
if galaxy_id >= 0:
key = '{0}/{0}.hdf5'.format(galaxy_name)
LOG.info('File name: %s', file_name)
LOG.info('File size: %d', size)
LOG.info('Bucket: %s', bucket_name)
LOG.info('Key: %s', key)
s3helper.add_file_to_bucket(bucket_name, key, file_name)
file_count += 1
os.remove(file_name)
connection.execute(GALAXY.update().where(GALAXY.c.galaxy_id == galaxy_id).values(status_id=STORED, status_time=datetime.datetime.now()))
else:
LOG.error('File name: %s', file_name)
LOG.error('File size: %d', size)
LOG.error('Could not get the galaxy id')
except Exception:
LOG.exception('Major error')
finally:
connection.close()
return file_count
def processed_data(connection, modulus, remainder):
"""
Work out which galaxies have been processed
:param connection:
:return:
"""
# Get the work units still being processed
engine = create_engine(BOINC_DB_LOGIN)
connection_boinc = engine.connect()
current_jobs = []
LOG.info('Getting results from BOINC')
# The use of appid ensures MySQL uses an index otherwise it does a full table scan
for result in connection_boinc.execute(
select([RESULT]).where(
and_(RESULT.c.server_state != 5, RESULT.c.appid == 1))):
current_jobs.append(result[RESULT.c.name])
connection_boinc.close()
LOG.info('Got results')
sorted_data = sort_data(connection, current_jobs, modulus, remainder)
for key in sorted(sorted_data.iterkeys()):
LOG.info('{0}: {1} results'.format(key, len(sorted_data[key])))
# Get the galaxies we know are still processing
processed = []
for galaxy in connection.execute(
select([GALAXY]).where(GALAXY.c.status_id == COMPUTING)):
if modulus is None or int(
galaxy[GALAXY.c.galaxy_id]) % modulus == remainder:
if finish_processing(galaxy[GALAXY.c.name],
galaxy[GALAXY.c.galaxy_id], sorted_data):
processed.append(galaxy[GALAXY.c.galaxy_id])
LOG.info('%d %s has completed', galaxy[GALAXY.c.galaxy_id],
galaxy[GALAXY.c.name])
for galaxy_id in processed:
connection.execute(
GALAXY.update().where(GALAXY.c.galaxy_id == galaxy_id).values(
status_id=PROCESSED, status_time=datetime.datetime.now()))
if shutdown() is True:
raise SystemExit
LOG.info('Marked %d galaxies ready for archiving', len(processed))
LOG.info('%d galaxies are still being processed', len(sorted_data))
def original_image_checked_ami():
"""
We're running in the AMI instance - so do the actual work
Check the newly created images to make sure the images have been created
:return:
"""
# Connect to the database - the login string is set in the database package
engine = create_engine(DB_LOGIN)
connection = engine.connect()
s3helper = S3Helper()
try:
# Look in the database for the galaxies
galaxy_ids = []
for galaxy in connection.execute(
select([GALAXY]).where(
and_(GALAXY.c.original_image_checked == None,
GALAXY.c.pixel_count > 0)).order_by(
GALAXY.c.galaxy_id)):
galaxy_ids.append(galaxy[GALAXY.c.galaxy_id])
for galaxy_id in galaxy_ids:
galaxy = connection.execute(
select([GALAXY
]).where(GALAXY.c.galaxy_id == galaxy_id)).first()
if not image_files_exist(galaxy[GALAXY.c.name],
galaxy[GALAXY.c.run_id],
galaxy[GALAXY.c.galaxy_id], s3helper):
mark_as_checked = regenerated_original_images(
galaxy[GALAXY.c.name], galaxy[GALAXY.c.run_id],
galaxy[GALAXY.c.galaxy_id], s3helper, connection)
else:
mark_as_checked = True
if mark_as_checked:
connection.execute(GALAXY.update().where(
GALAXY.c.galaxy_id == galaxy_id).values(
original_image_checked=datetime.datetime.now()))
except Exception:
LOG.exception('Major error')
finally:
connection.close()
def delete_galaxy(connection, galaxy_ids):
try:
for galaxy_id_str in galaxy_ids:
transaction = connection.begin()
galaxy_id1 = int(galaxy_id_str)
galaxy = connection.execute(select([GALAXY]).where(GALAXY.c.galaxy_id == galaxy_id1)).first()
if galaxy is None:
LOG.info('Error: Galaxy with galaxy_id of %d was not found', galaxy_id1)
else:
LOG.info('Deleting Galaxy with galaxy_id of %d - %s', galaxy_id1, galaxy[GALAXY.c.name])
area_count = connection.execute(select([func.count(AREA.c.area_id)]).where(AREA.c.galaxy_id == galaxy[GALAXY.c.galaxy_id])).first()[0]
counter = 1
for area_id1 in connection.execute(select([AREA.c.area_id]).where(AREA.c.galaxy_id == galaxy[GALAXY.c.galaxy_id]).order_by(AREA.c.area_id)):
LOG.info("Deleting galaxy {0} area {1}. {2} of {3}".format(galaxy_id_str, area_id1[0], counter, area_count))
connection.execute(PIXEL_RESULT.delete().where(PIXEL_RESULT.c.area_id == area_id1[0]))
# Give the rest of the world a chance to access the database
time.sleep(0.1)
counter += 1
# Now empty the bucket
s3helper = S3Helper()
bucket = s3helper.get_bucket(get_files_bucket())
galaxy_file_name = get_galaxy_file_name(galaxy[GALAXY.c.name], galaxy[GALAXY.c.run_id], galaxy[GALAXY.c.galaxy_id])
for key in bucket.list(prefix='{0}/sed/'.format(galaxy_file_name)):
# Ignore the key
if key.key.endswith('/'):
continue
bucket.delete_key(key)
# Now the folder
key = Key(bucket)
key.key = '{0}/sed/'.format(galaxy_file_name)
bucket.delete_key(key)
LOG.info('Galaxy with galaxy_id of %d was deleted', galaxy_id1)
connection.execute(GALAXY.update().where(GALAXY.c.galaxy_id == galaxy_id1).values(status_id=DELETED, status_time=datetime.datetime.now()))
transaction.commit()
except Exception:
LOG.exception('Major error')
def store_files(connection, modulus, remainder):
"""
Scan a directory for files and send them to the archive
"""
LOG.info('Directory: %s', HDF5_OUTPUT_DIRECTORY)
to_store_dir = os.path.join(HDF5_OUTPUT_DIRECTORY, 'to_store')
files = os.path.join(to_store_dir, '*.hdf5')
file_count = 0
s3helper = S3Helper()
bucket_name = get_saved_files_bucket()
for file_name in glob.glob(files):
galaxy_id, galaxy_name = get_galaxy_id_and_name(file_name)
if galaxy_id >= 0:
if modulus is None or galaxy_id % modulus == remainder:
size = os.path.getsize(file_name)
key = '{0}/{0}.hdf5'.format(galaxy_name)
LOG.info('File name: %s', file_name)
LOG.info('File size: %d', size)
LOG.info('Bucket: %s', bucket_name)
LOG.info('Key: %s', key)
s3helper.add_file_to_bucket(bucket_name, key, file_name)
file_count += 1
os.remove(file_name)
connection.execute(
GALAXY.update()
.where(GALAXY.c.galaxy_id == galaxy_id)
.values(status_id=STORED, status_time=datetime.datetime.now()))
else:
LOG.error('File name: %s', file_name)
LOG.error('Could not get the galaxy id')
if shutdown() is True:
raise SystemExit
return file_count
def store_files(connection, modulus, remainder):
"""
Scan a directory for files and send them to the archive
"""
LOG.info('Directory: %s', HDF5_OUTPUT_DIRECTORY)
to_store_dir = os.path.join(HDF5_OUTPUT_DIRECTORY, 'to_store')
files = os.path.join(to_store_dir, '*.hdf5')
file_count = 0
s3helper = S3Helper()
bucket_name = get_saved_files_bucket()
for file_name in glob.glob(files):
galaxy_id, galaxy_name = get_galaxy_id_and_name(file_name)
if galaxy_id >= 0:
if modulus is None or galaxy_id % modulus == remainder:
size = os.path.getsize(file_name)
key = '{0}/{0}.hdf5'.format(galaxy_name)
LOG.info('File name: %s', file_name)
LOG.info('File size: %d', size)
LOG.info('Bucket: %s', bucket_name)
LOG.info('Key: %s', key)
s3helper.add_file_to_bucket(bucket_name, key, file_name)
file_count += 1
os.remove(file_name)
connection.execute(GALAXY.update().where(
GALAXY.c.galaxy_id == galaxy_id).values(
status_id=STORED, status_time=datetime.datetime.now()))
else:
LOG.error('File name: %s', file_name)
LOG.error('Could not get the galaxy id')
if shutdown() is True:
raise SystemExit
return file_count
def processed_data(connection, modulus, remainder):
"""
Work out which galaxies have been processed
:param connection:
:return:
"""
# Get the work units still being processed
engine = create_engine(BOINC_DB_LOGIN)
connection_boinc = engine.connect()
current_jobs = []
LOG.info('Getting results from BOINC')
# The use of appid ensures MySQL uses an index otherwise it does a full table scan
for result in connection_boinc.execute(select([RESULT]).where(and_(RESULT.c.server_state != 5, RESULT.c.appid == 1))):
current_jobs.append(result[RESULT.c.name])
connection_boinc.close()
LOG.info('Got results')
sorted_data = sort_data(connection, current_jobs, modulus, remainder)
for key in sorted(sorted_data.iterkeys()):
LOG.info('{0}: {1} results'.format(key, len(sorted_data[key])))
# Get the galaxies we know are still processing
processed = []
for galaxy in connection.execute(select([GALAXY]).where(GALAXY.c.status_id == COMPUTING)):
if modulus is None or int(galaxy[GALAXY.c.galaxy_id]) % modulus == remainder:
if finish_processing(galaxy[GALAXY.c.name], galaxy[GALAXY.c.galaxy_id], sorted_data):
processed.append(galaxy[GALAXY.c.galaxy_id])
LOG.info('%d %s has completed', galaxy[GALAXY.c.galaxy_id], galaxy[GALAXY.c.name])
for galaxy_id in processed:
connection.execute(GALAXY.update().where(GALAXY.c.galaxy_id == galaxy_id).values(status_id=PROCESSED, status_time=datetime.datetime.now()))
if shutdown() is True:
raise SystemExit
LOG.info('Marked %d galaxies ready for archiving', len(processed))
LOG.info('%d galaxies are still being processed', len(sorted_data))
def store_files(connection):
"""
Scan a directory for files and send them to the archive
:param hdf5_dir: the directory to scan
:return:
"""
LOG.info('Directory: %s', HDF5_OUTPUT_DIRECTORY)
to_store_dir = os.path.join(HDF5_OUTPUT_DIRECTORY, 'to_store')
files = os.path.join(to_store_dir, '*.hdf5')
file_count = 0
s3helper = S3Helper()
bucket_name = get_files_bucket()
for file_name in glob.glob(files):
size = os.path.getsize(file_name)
galaxy_id, galaxy_name = get_galaxy_id_and_name(file_name)
if galaxy_id >= 0:
key = '{0}/{0}.hdf5'.format(galaxy_name)
LOG.info('File name: %s', file_name)
LOG.info('File size: %d', size)
LOG.info('Bucket: %s', bucket_name)
LOG.info('Key: %s', key)
s3helper.add_file_to_bucket(bucket_name, key, file_name)
file_count += 1
os.remove(file_name)
connection.execute(GALAXY.update().where(GALAXY.c.galaxy_id == galaxy_id).values(status_id=STORED, status_time=datetime.datetime.now()))
else:
LOG.error('File name: %s', file_name)
LOG.error('File size: %d', size)
LOG.error('Could not get the galaxy id')
return file_count
def fix_galaxy(galaxy, bucket_files, bucket_galaxy_image):
"""
Fix the galaxy name
:param galaxy:
:return:
"""
old_name = galaxy[GALAXY.c.name]
new_name = old_name[:-1]
galaxy_id = galaxy[GALAXY.c.galaxy_id]
run_id = galaxy[GALAXY.c.run_id]
LOG.info('Fixing {0}({1}) t0 {2}'.format(old_name, galaxy_id, new_name))
for extension in ['fits', 'hdf5']:
copy_files(old_name, new_name, run_id, galaxy_id, extension, bucket_files)
remove_files_folder(old_name, run_id, galaxy_id, bucket_files)
for file_name in ['colour_1.png', 'colour_2.png', 'colour_3.png', 'colour_4.png', 'ldust.png', 'm.png', 'mu.png', 'sfr.png', 'tn_colour_1.png']:
copy_galaxy_images(old_name, new_name, run_id, galaxy_id, file_name, bucket_galaxy_image)
remove_galaxy_images_folder(old_name, run_id, galaxy_id, bucket_galaxy_image)
if DRY_RUN:
LOG.info('Updating {0} to {1}'.format(galaxy_id, new_name))
else:
connection.execute(GALAXY.update().where(GALAXY.c.galaxy_id == galaxy_id).values(name=new_name))
def delete_galaxy(connection, galaxy_ids):
for galaxy_id in galaxy_ids:
transaction = connection.begin()
galaxy = connection.execute(
select([GALAXY]).where(GALAXY.c.galaxy_id == galaxy_id)).first()
if galaxy is None:
LOG.info('Error: Galaxy with galaxy_id of %d was not found',
galaxy_id)
else:
LOG.info('Deleting Galaxy with galaxy_id of %d - %s', galaxy_id,
galaxy[GALAXY.c.name])
area_count = connection.execute(
select([func.count(AREA.c.area_id)]).where(
AREA.c.galaxy_id == galaxy[GALAXY.c.galaxy_id])).first()[0]
counter = 1
for area_id1 in connection.execute(
select([AREA.c.area_id]).where(AREA.c.galaxy_id == galaxy[
GALAXY.c.galaxy_id]).order_by(AREA.c.area_id)):
LOG.info("Deleting galaxy {0} area {1}. {2} of {3}".format(
galaxy_id, area_id1[0], counter, area_count))
connection.execute(PIXEL_RESULT.delete().where(
PIXEL_RESULT.c.area_id == area_id1[0]))
# Give the rest of the world a chance to access the database
time.sleep(0.1)
counter += 1
if shutdown() is True:
transaction.rollback()
raise SystemExit
LOG.info("Deleting FITS headers for galaxy {0}".format(galaxy_id))
connection.execute(FITS_HEADER.delete().where(
FITS_HEADER.c.galaxy_id == galaxy[GALAXY.c.galaxy_id]))
# Now empty the bucket of the sed files
s3helper = S3Helper()
bucket = s3helper.get_bucket(get_sed_files_bucket())
galaxy_file_name = get_galaxy_file_name(galaxy[GALAXY.c.name],
galaxy[GALAXY.c.run_id],
galaxy[GALAXY.c.galaxy_id])
for key in bucket.list(prefix='{0}/'.format(galaxy_file_name)):
# Ignore the key
if key.key.endswith('/'):
continue
bucket.delete_key(key)
if shutdown() is True:
transaction.rollback()
raise SystemExit
# Now the folder
key = Key(bucket)
key.key = '{0}/'.format(galaxy_file_name)
bucket.delete_key(key)
LOG.info('Galaxy with galaxy_id of %d was deleted', galaxy_id)
connection.execute(
GALAXY.update().where(GALAXY.c.galaxy_id == galaxy_id).values(
status_id=DELETED, status_time=datetime.datetime.now()))
if shutdown() is True:
transaction.rollback()
raise SystemExit
transaction.commit()
sorted_data = sort_data(connection, current_jobs)
for key in sorted(sorted_data.iterkeys()):
LOG.info('{0}: {1} results'.format(key, len(sorted_data[key])))
try:
# Get the galaxies we know are still processing
processed = []
for galaxy in connection.execute(
select([GALAXY]).where(GALAXY.c.status_id == COMPUTING)):
if finish_processing(galaxy[GALAXY.c.name], galaxy[GALAXY.c.galaxy_id],
sorted_data):
processed.append(galaxy[GALAXY.c.galaxy_id])
LOG.info('%d %s has completed', galaxy[GALAXY.c.galaxy_id],
galaxy[GALAXY.c.name])
transaction = connection.begin()
for galaxy_id in processed:
connection.execute(
GALAXY.update().where(GALAXY.c.galaxy_id == galaxy_id).values(
status_id=PROCESSED, status_time=datetime.datetime.now()))
transaction.commit()
LOG.info('Marked %d galaxies ready for archiving', len(processed))
LOG.info('%d galaxies are still being processed', len(sorted_data))
except Exception:
LOG.exception('Major error')
finally:
connection.close()
galaxy[GALAXY.c.dimension_z], area_count, OUTPUT_DIRECTORY,
map_parameter_name)
# Flush the HDF5 data to disk
h5_file.flush()
h5_file.close()
# Move the file
to_store = os.path.join(OUTPUT_DIRECTORY, 'to_store')
LOG.info('Moving the file %s to %s', filename, to_store)
if not os.path.exists(to_store):
os.makedirs(to_store)
shutil.move(filename, to_store)
connection.execute(
GALAXY.update().where(GALAXY.c.galaxy_id == galaxy_id1).values(
status_id=ARCHIVED, status_time=datetime.datetime.now()))
end_time = time.time()
LOG.info('Galaxy with galaxy_id of %d was archived.', galaxy_id1)
LOG.info('Copied %d areas %d pixels.', area_count, pixel_count)
total_time = end_time - start_time
LOG.info('Total time %d mins %.1f secs', int(total_time / 60),
total_time % 60)
except Exception:
LOG.exception('Major error')
finally:
connection.close()
pixel_group,
galaxy[GALAXY.c.dimension_x],
galaxy[GALAXY.c.dimension_y],
filter_layers,
galaxy[GALAXY.c.pixel_count])
# Flush the HDF5 data to disk
h5_file.flush()
h5_file.close()
# Move the file
to_store = os.path.join(OUTPUT_DIRECTORY, 'to_store')
LOG.info('Moving the file %s to %s', filename, to_store)
if not os.path.exists(to_store):
os.makedirs(to_store)
shutil.move(filename, to_store)
connection.execute(GALAXY.update().where(GALAXY.c.galaxy_id == galaxy_id1).values(status_id = ARCHIVED))
end_time = time.time()
LOG.info('Galaxy with galaxy_id of %d was archived.', galaxy_id1)
LOG.info('Copied %d areas %d pixels.', area_count, pixel_count)
total_time = end_time - start_time
LOG.info('Total time %d mins %.1f secs', int(total_time / 60), total_time % 60)
except Exception:
LOG.exception('Major error')
finally:
connection.close()
def process_file(self, registration):
"""
Process a registration.
:param registration:
"""
self._filename = registration[REGISTER.c.filename]
self._galaxy_name = registration[REGISTER.c.galaxy_name]
self._galaxy_type = registration[REGISTER.c.galaxy_type]
self._priority = registration[REGISTER.c.priority]
self._redshift = registration[REGISTER.c.redshift]
self._run_id = registration[REGISTER.c.run_id]
self._sigma = registration[REGISTER.c.sigma]
self._sigma_filename = registration[REGISTER.c.sigma_filename]
# Have we files that we can use for this?
self._rounded_redshift = self._get_rounded_redshift()
if self._rounded_redshift is None:
LOG.error('No models matching the redshift of %.4f', self._redshift)
return 0
self._hdu_list = pyfits.open(self._filename, memmap=True)
self._layer_count = len(self._hdu_list)
# Do we need to open and sort the S/N Ratio file
if self._sigma_filename is not None:
self._sigma = 0.0
self._signal_noise_hdu = pyfits.open(self._sigma_filename, memmap=True)
if self._layer_count != len(self._signal_noise_hdu):
LOG.error('The layer counts do not match %d vs %d', self._layer_count, len(self._signal_noise_hdu))
return 0, 0
else:
self._sigma = float(self._sigma)
self._end_y = self._hdu_list[0].data.shape[0]
self._end_x = self._hdu_list[0].data.shape[1]
LOG.info("Image dimensions: %(x)d x %(y)d x %(z)d => %(pix).2f Mpixels" % {'x': self._end_x, 'y': self._end_y, 'z': self._layer_count, 'pix': self._end_x * self._end_y / 1000000.0})
# Get the flops estimate amd cobblestone factor
run = self._connection.execute(select([RUN]).where(RUN.c.run_id == self._run_id)).first()
self._fpops_est_per_pixel = run[RUN.c.fpops_est]
self._cobblestone_scaling_factor = run[RUN.c.cobblestone_factor]
# Create and save the object
datetime_now = datetime.now()
result = self._connection.execute(GALAXY.insert().values(name=self._galaxy_name,
dimension_x=self._end_x,
dimension_y=self._end_y,
dimension_z=self._layer_count,
redshift=self._redshift,
sigma=self._sigma,
create_time=datetime_now,
image_time=datetime_now,
galaxy_type=self._galaxy_type,
ra_cent=0,
dec_cent=0,
pixel_count=0,
pixels_processed=0,
run_id=self._run_id))
self._galaxy_id = result.inserted_primary_key[0]
LOG.info("Writing %s to database", self._galaxy_name)
# Store the fits header
self._store_fits_header()
# Get the filters we're using for this run and sort the layers
self._get_filters_sort_layers()
# Build the template file we need if necessary
self._build_template_file()
# Copy the filter and model files we need
self._copy_important_files()
# Now break up the galaxy into chunks
self._break_up_galaxy()
self._connection.execute(GALAXY.update().where(GALAXY.c.galaxy_id == self._galaxy_id).values(pixel_count=self._pixel_count))
LOG.info('Building the images')
galaxy_file_name = get_galaxy_file_name(self._galaxy_name, self._run_id, self._galaxy_id)
s3helper = S3Helper()
image = FitsImage(self._connection)
image.build_image(self._filename, galaxy_file_name, self._galaxy_id, get_galaxy_image_bucket())
# Copy the fits file to S3 - renamed to make it unique
bucket_name = get_files_bucket()
s3helper.add_file_to_bucket(bucket_name, get_key_fits(self._galaxy_name, self._run_id, self._galaxy_id), self._filename)
if self._sigma_filename is not None:
s3helper.add_file_to_bucket(bucket_name, get_key_sigma_fits(self._galaxy_name, self._run_id, self._galaxy_id), self._sigma_filename)
return self._work_units_added, self._pixel_count
# Connect to the database - the login string is set in the database package
ENGINE = create_engine(DB_LOGIN)
connection = ENGINE.connect()
sorted_data = sort_data(connection, current_jobs)
for key in sorted(sorted_data.iterkeys()):
LOG.info('{0}: {1} results'.format(key, len(sorted_data[key])))
try:
# Get the galaxies we know are still processing
processed = []
for galaxy in connection.execute(select([GALAXY]).where(GALAXY.c.status_id == COMPUTING)):
if finish_processing(galaxy[GALAXY.c.name], galaxy[GALAXY.c.galaxy_id], sorted_data):
processed.append(galaxy[GALAXY.c.galaxy_id])
LOG.info('%d %s has completed', galaxy[GALAXY.c.galaxy_id], galaxy[GALAXY.c.name])
transaction = connection.begin()
for galaxy_id in processed:
connection.execute(GALAXY.update().where(GALAXY.c.galaxy_id == galaxy_id).values(status_id=PROCESSED, status_time=datetime.datetime.now()))
transaction.commit()
LOG.info('Marked %d galaxies ready for archiving', len(processed))
LOG.info('%d galaxies are still being processed', len(sorted_data))
except Exception:
LOG.exception('Major error')
finally:
connection.close()
def archive_to_hdf5(connection):
"""
Archive data to an HDF5 file
:param connection:
:return:
"""
# Load the parameter name map
map_parameter_name = {}
for parameter_name in connection.execute(select([PARAMETER_NAME])):
map_parameter_name[parameter_name[PARAMETER_NAME.c.name]] = parameter_name[PARAMETER_NAME.c.parameter_name_id]
# Look in the database for the galaxies
galaxy_ids = []
for galaxy in connection.execute(select([GALAXY]).where(GALAXY.c.status_id == PROCESSED).order_by(GALAXY.c.galaxy_id)):
galaxy_ids.append(galaxy[GALAXY.c.galaxy_id])
for galaxy_id_str in galaxy_ids:
start_time = time.time()
galaxy_id1 = int(galaxy_id_str)
galaxy = connection.execute(select([GALAXY]).where(GALAXY.c.galaxy_id == galaxy_id1)).first()
if galaxy is None:
LOG.info('Error: Galaxy with galaxy_id of %d was not found', galaxy_id1)
else:
LOG.info('Archiving Galaxy with galaxy_id of %d - %s', galaxy_id1, galaxy[GALAXY.c.name])
# Copy the galaxy details
galaxy_file_name = get_galaxy_file_name(galaxy[GALAXY.c.name], galaxy[GALAXY.c.run_id], galaxy[GALAXY.c.galaxy_id])
filename = os.path.join(HDF5_OUTPUT_DIRECTORY, '{0}.hdf5'.format(galaxy_file_name))
h5_file = h5py.File(filename, 'w')
# Build the groups
galaxy_group = h5_file.create_group('galaxy')
area_group = galaxy_group.create_group('area')
pixel_group = galaxy_group.create_group('pixel')
# Write the galaxy data
galaxy_group.attrs['galaxy_id'] = galaxy[GALAXY.c.galaxy_id]
galaxy_group.attrs['run_id'] = galaxy[GALAXY.c.run_id]
galaxy_group.attrs['name'] = galaxy[GALAXY.c.name]
galaxy_group.attrs['dimension_x'] = galaxy[GALAXY.c.dimension_x]
galaxy_group.attrs['dimension_y'] = galaxy[GALAXY.c.dimension_y]
galaxy_group.attrs['dimension_z'] = galaxy[GALAXY.c.dimension_z]
galaxy_group.attrs['redshift'] = float(galaxy[GALAXY.c.redshift])
galaxy_group.attrs['create_time'] = str(galaxy[GALAXY.c.create_time])
galaxy_group.attrs['image_time'] = str(galaxy[GALAXY.c.image_time])
galaxy_group.attrs['galaxy_type'] = galaxy[GALAXY.c.galaxy_type]
galaxy_group.attrs['ra_cent'] = galaxy[GALAXY.c.ra_cent]
galaxy_group.attrs['dec_cent'] = galaxy[GALAXY.c.dec_cent]
galaxy_group.attrs['sigma'] = float(galaxy[GALAXY.c.sigma])
galaxy_group.attrs['pixel_count'] = galaxy[GALAXY.c.pixel_count]
galaxy_group.attrs['pixels_processed'] = galaxy[GALAXY.c.pixels_processed]
galaxy_group.attrs['output_format'] = OUTPUT_FORMAT_1_03
galaxy_id_aws = galaxy[GALAXY.c.galaxy_id]
# Store the data associated with the galaxy
store_fits_header(connection, galaxy_id_aws, galaxy_group)
store_image_filters(connection, galaxy_id_aws, galaxy_group)
# Store the data associated with the areas
area_count = store_area(connection, galaxy_id_aws, area_group)
store_area_user(connection, galaxy_id_aws, area_group)
h5_file.flush()
# Store the values associated with a pixel
pixel_count = store_pixels(connection,
galaxy_file_name,
pixel_group,
galaxy[GALAXY.c.dimension_x],
galaxy[GALAXY.c.dimension_y],
galaxy[GALAXY.c.dimension_z],
area_count,
galaxy[GALAXY.c.galaxy_id],
map_parameter_name)
# Flush the HDF5 data to disk
h5_file.flush()
h5_file.close()
# Move the file
to_store = os.path.join(HDF5_OUTPUT_DIRECTORY, 'to_store')
LOG.info('Moving the file %s to %s', filename, to_store)
if not os.path.exists(to_store):
os.makedirs(to_store)
# Sometimes the file can exist so remove it
old_filename = os.path.join(to_store, '{0}.hdf5'.format(galaxy_file_name))
LOG.info('Checking for old file %s', old_filename)
if os.path.exists(old_filename):
LOG.info('Removing old file %s', old_filename)
os.remove(old_filename)
shutil.move(filename, to_store)
connection.execute(GALAXY.update().where(GALAXY.c.galaxy_id == galaxy_id1).values(status_id=ARCHIVED, status_time=datetime.datetime.now()))
end_time = time.time()
LOG.info('Galaxy with galaxy_id of %d was archived.', galaxy_id1)
LOG.info('Copied %d areas %d pixels.', area_count, pixel_count)
total_time = end_time - start_time
LOG.info('Total time %d mins %.1f secs', int(total_time / 60), total_time % 60)
galaxy[GALAXY.c.dimension_y],
filter_layers,
galaxy[GALAXY.c.pixel_count])
# Flush the HDF5 data to disk
h5_file.flush()
h5_file.close()
# Move the file
to_store = os.path.join(OUTPUT_DIRECTORY, 'to_store')
LOG.info('Moving the file %s to %s', filename, to_store)
if not os.path.exists(to_store):
os.makedirs(to_store)
shutil.move(filename, to_store)
connection.execute(GALAXY.update().where(
GALAXY.c.galaxy_id == galaxy_id1).values(status_id=ARCHIVED))
end_time = time.time()
LOG.info('Galaxy with galaxy_id of %d was archived.', galaxy_id1)
LOG.info('Copied %d areas %d pixels.', area_count, pixel_count)
total_time = end_time - start_time
LOG.info('Total time %d mins %.1f secs', int(total_time / 60),
total_time % 60)
except Exception:
LOG.exception('Major error')
finally:
connection.close()
pixels_processed += 1
try:
array[row__y, row__x, 0] = row[PIXEL_RESULT.c.mu]
array[row__y, row__x, 1] = row[PIXEL_RESULT.c.m]
array[row__y, row__x, 2] = row[PIXEL_RESULT.c.ldust]
# the SFR is a log
array[row__y, row__x, 3] = math.pow(10,
row[PIXEL_RESULT.c.sfr])
except TypeError:
LOG.error('Error at x: {0}, y: {1}'.format(row__x, row__y))
transaction = connection.begin()
connection.execute(GALAXY.update().where(
GALAXY.c.galaxy_id == galaxy[GALAXY.c.galaxy_id]).values(
image_time=datetime.datetime.now(),
pixel_count=pixel_count,
pixels_processed=pixels_processed))
transaction.commit()
galaxy_count += 1
# Now right the files
blackRGB = (0, 0, 0)
for name in PNG_IMAGE_NAMES:
value = 0
height = galaxy[GALAXY.c.dimension_y]
width = galaxy[GALAXY.c.dimension_x]
idx = 0
if name == 'mu':
idx = 0
elif name == 'm':
ra_eqj2000 = table.array['pos_ra_equ_J2000_d'][0]
dec_eqj2000 = table.array['pos_dec_equ_J2000_d'][0]
LOG.info('VOTable data collected from NED for {0}'.format(name))
return True, float(ra_eqj2000), float(dec_eqj2000)
except Exception:
pass
# Try Hyperleda
try:
url = 'http://leda.univ-lyon1.fr/G.cgi?n=113&c=o&o=' + name + '&a=x&z=d'
table = getVOTable(url, 0)
ra_eqj2000 = table.array['alpha'][0]
dec_eqj2000 = table.array['delta'][0]
LOG.info('VOTable data collected from Hyperleda for {0}'.format(name))
return True, float(ra_eqj2000), float(dec_eqj2000)
except Exception:
LOG.exception('ERROR: Getting VO data for {0}'.format(name))
return False, 0.0, 0.0
for galaxy in connection.execute(select([GALAXY]).where(or_(GALAXY.c.ra_cent == None, GALAXY.c.ra_cent == 0.0, GALAXY.c.dec_cent == None, GALAXY.c.dec_cent == 0.0))):
LOG.info('Processing %d - %s', galaxy[GALAXY.c.galaxy_id], galaxy[GALAXY.c.name])
name = fix_name(galaxy[GALAXY.c.name])
(found, ra, dec) = get_ra_dec(name)
if found:
LOG.info('Updating {0} to RA: {1}, DEC: {2}'.format(name, ra, dec))
connection.execute(GALAXY.update().where(GALAXY.c.galaxy_id == galaxy[GALAXY.c.galaxy_id]).values(ra_cent=ra, dec_cent=dec))
connection.close()
def build_png_image_ami():
"""
Build the images
:return:
"""
# First check the galaxy exists in the database
engine = create_engine(DB_LOGIN)
connection = engine.connect()
try:
query = select([GALAXY]).distinct().where(and_(AREA.c.galaxy_id == GALAXY.c.galaxy_id, AREA.c.update_time >= GALAXY.c.image_time))
galaxy_count = 0
s3helper = S3Helper()
bucket_name = get_galaxy_image_bucket()
# Start the shutdown signal poller to check when this instance must close
start_poll()
galaxy_list = []
for galaxy in connection.execute(query):
galaxy_list.append(galaxy)
total_galaxies = len(galaxy_list)
processed_galaxies = 0
processed_print_point = 50
for galaxy in galaxy_list:
if processed_galaxies == processed_print_point:
LOG.info('{0} out of {1} galaxies processed'.format(processed_galaxies, total_galaxies))
processed_print_point += 50
processed_galaxies += 1
LOG.info('Working on galaxy %s', galaxy[GALAXY.c.name])
array = numpy.empty((galaxy[GALAXY.c.dimension_y], galaxy[GALAXY.c.dimension_x], len(PNG_IMAGE_NAMES)), dtype=numpy.float)
array.fill(numpy.NaN)
# Return the rows
pixel_count = 0
pixels_processed = 0
for row in connection.execute(select([PIXEL_RESULT]).where((PIXEL_RESULT.c.galaxy_id == galaxy[GALAXY.c.galaxy_id]) and PIXEL_RESULT.c.x > -1)):
row__x = row[PIXEL_RESULT.c.x]
row__y = row[PIXEL_RESULT.c.y]
pixel_count += 1
if row[PIXEL_RESULT.c.workunit_id] is not None:
pixels_processed += 1
# Defend against bad values
if row[PIXEL_RESULT.c.mu] is not None:
array[row__y, row__x, 0] = row[PIXEL_RESULT.c.mu]
if row[PIXEL_RESULT.c.m] is not None:
array[row__y, row__x, 1] = row[PIXEL_RESULT.c.m]
if row[PIXEL_RESULT.c.ldust] is not None:
array[row__y, row__x, 2] = row[PIXEL_RESULT.c.ldust]
if row[PIXEL_RESULT.c.sfr] is not None:
# the SFR is a log
array[row__y, row__x, 3] = math.pow(10, row[PIXEL_RESULT.c.sfr])
connection.execute(GALAXY.update()
.where(GALAXY.c.galaxy_id == galaxy[GALAXY.c.galaxy_id])
.values(image_time=datetime.datetime.now(), pixel_count=pixel_count, pixels_processed=pixels_processed))
galaxy_count += 1
# Now write the files
black_rgb = (0, 0, 0)
for name in PNG_IMAGE_NAMES:
value = 0
height = galaxy[GALAXY.c.dimension_y]
width = galaxy[GALAXY.c.dimension_x]
idx = 0
if name == 'mu':
idx = 0
elif name == 'm':
idx = 1
elif name == 'ldust':
idx = 2
elif name == 'sfr':
idx = 3
values = []
for x in range(0, width - 1):
for y in range(0, height - 1):
value = array[y, x, idx]
if not math.isnan(value) and value > 0:
values.append(value)
values.sort()
if len(values) > 1000:
top_count = int(len(values) * 0.005)
top_value = values[len(values) - top_count]
elif len(values) > 0:
top_value = values[len(values) - 1]
else:
top_value = 1
if len(values) > 1:
median_value = values[int(len(values) / 2)]
elif len(values) > 0:
median_value = values[0]
else:
median_value = 1
sigma = 1 / median_value
multiplier = 255.0 / math.asinh(top_value * sigma)
image = Image.new("RGB", (width, height), black_rgb)
for x in range(0, width - 1):
for y in range(0, height - 1):
value = array[y, x, idx]
if not math.isnan(value) and value > 0:
value = int(math.asinh(value * sigma) * multiplier)
if value > 255:
value = 255
red = FIRE_R[value]
green = FIRE_G[value]
blue = FIRE_B[value]
image.putpixel((x, height - y - 1), (red, green, blue))
file_name = '{0}/image.png'.format(POGS_TMP)
image.save(file_name)
s3helper.add_file_to_bucket(bucket_name,
get_build_png_name(get_galaxy_file_name(galaxy[GALAXY.c.name], galaxy[GALAXY.c.run_id], galaxy[GALAXY.c.galaxy_id]),
name),
file_name)
if shutdown() is True:
LOG.info('Spot Instance Terminate Notice received, build_png_image is shutting down')
break
except:
LOG.exception('An exception occurred.')
finally:
connection.close()
LOG.info('Built images for %d galaxies', galaxy_count)
# Try Hyperleda
try:
url = 'http://leda.univ-lyon1.fr/G.cgi?n=113&c=o&o=' + name + '&a=x&z=d'
table = getVOTable(url, 0)
ra_eqj2000 = table.array['alpha'][0]
dec_eqj2000 = table.array['delta'][0]
LOG.info('VOTable data collected from Hyperleda for {0}'.format(name))
return True, float(ra_eqj2000), float(dec_eqj2000)
except Exception:
LOG.exception('ERROR: Getting VO data for {0}'.format(name))
return False, 0.0, 0.0
for galaxy in connection.execute(
select([GALAXY]).where(
or_(GALAXY.c.ra_cent == None, GALAXY.c.ra_cent == 0.0,
GALAXY.c.dec_cent == None, GALAXY.c.dec_cent == 0.0))):
LOG.info('Processing %d - %s', galaxy[GALAXY.c.galaxy_id],
galaxy[GALAXY.c.name])
name = fix_name(galaxy[GALAXY.c.name])
(found, ra, dec) = get_ra_dec(name)
if found:
LOG.info('Updating {0} to RA: {1}, DEC: {2}'.format(name, ra, dec))
connection.execute(GALAXY.update().where(
GALAXY.c.galaxy_id == galaxy[GALAXY.c.galaxy_id]).values(
ra_cent=ra, dec_cent=dec))
connection.close()
pixel_count += 1
if row[PIXEL_RESULT.c.mu] is not None and row[PIXEL_RESULT.c.m] is not None and row[PIXEL_RESULT.c.ldust] is not None and row[PIXEL_RESULT.c.sfr] is not None:
pixels_processed += 1
try:
array[row__y, row__x, 0] = row[PIXEL_RESULT.c.mu]
array[row__y, row__x, 1] = row[PIXEL_RESULT.c.m]
array[row__y, row__x, 2] = row[PIXEL_RESULT.c.ldust]
# the SFR is a log
array[row__y, row__x, 3] = math.pow(10, row[PIXEL_RESULT.c.sfr])
except TypeError:
LOG.error('Error at x: {0}, y: {1}'.format(row__x, row__y))
transaction = connection.begin()
connection.execute(GALAXY.update()
.where(GALAXY.c.galaxy_id == galaxy[GALAXY.c.galaxy_id])
.values(image_time=datetime.datetime.now(), pixel_count=pixel_count, pixels_processed=pixels_processed))
transaction.commit()
galaxy_count += 1
# Now right the files
blackRGB = (0, 0, 0)
for name in PNG_IMAGE_NAMES:
value = 0
height = galaxy[GALAXY.c.dimension_y]
width = galaxy[GALAXY.c.dimension_x]
idx = 0
if name == 'mu':
idx = 0
elif name == 'm':
idx = 1