# 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)