# How many filter layers are there (check a row with some)
pixel_result = connection.execute(
select([PIXEL_RESULT]).where(
and_(PIXEL_RESULT.c.galaxy_id == galaxy_id1,
PIXEL_RESULT.c.i_sfh != None))).first()
if pixel_result is not None:
filter_layers = connection.execute(
select([
func.count(PIXEL_FILTER.c.pxfilter_id)
]).where(PIXEL_FILTER.c.pxresult_id == pixel_result[
PIXEL_RESULT.c.pxresult_id])).first()[0]
# Store the values associated with a pixel
pixel_count = store_pixels(connection, galaxy_id_aws,
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_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, 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(
# 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()
# How many filter layers are there (check a row with some)
pixel_result = connection.execute(select([PIXEL_RESULT]).where(and_(PIXEL_RESULT.c.galaxy_id == galaxy_id1, PIXEL_RESULT.c.i_sfh != None))).first()
if pixel_result is not None:
filter_layers = connection.execute(select([func.count(PIXEL_FILTER.c.pxfilter_id)]).where(PIXEL_FILTER.c.pxresult_id == pixel_result[PIXEL_RESULT.c.pxresult_id])).first()[0]
# Store the values associated with a pixel
pixel_count = store_pixels(connection,
galaxy_id_aws,
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)
# 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,
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)
