def __prerequisites(): """ Fetch the basic proposal data depending on the CYCLE_ID This is basically stage0 :return: """ CYCLE_ID = Pipeline().pipeline_configuration()["cycle_id"] CYCLE_PATH = Pipeline().pipeline_configuration()["cycle_path"] CYCLE_ID = str(CYCLE_ID) sql_query = "select distinct o.observation_no, p.proposal_id, g.file_path, p.backend_type from " \ "gmrt.proposal p inner join das.observation o on p.proposal_id = o.proj_code " \ "inner join das.scangroup g on g.observation_no = o.observation_no " \ "inner join das.scans s on s.scangroup_id = g.scangroup_id " \ "inner join gmrt.sourceobservationtype so on p.proposal_id = so.proposal_id " \ "where p.cycle_id ='" + CYCLE_ID + "' " \ "and so.obs_type not like 'pulsar%' " \ "and so.obs_type not like 'phased array'" \ "and s.sky_freq1=s.sky_freq2 " \ "and s.sky_freq1 < 900000000 " \ "and s.chan_width >= 62500 " \ "and o.proj_code not like '16_279' " \ "and o.proj_code not like '17_072' " \ "and o.proj_code not like '18_031' " \ "and o.proj_code not like '19_043' " \ "and o.proj_code not like '20_083' " \ "and o.proj_code not like '21_057';" dbutils = DBUtils() data = dbutils.select_query(sql_query) gadpudata = {} for each_row in data: gadpudata[each_row[0]] = { "proposal_id": each_row[1], "file_path": each_row[2], "backend_type": each_row[3], "cycle_id": CYCLE_ID } return (gadpudata, CYCLE_PATH)
def __prerequisites_ghb(self): CYCLE_ID = 15 CYCLE_PATH = '/GARUDATA/IMAGING15/CYCLE15/' CYCLE_ID = str(CYCLE_ID) sql_query = "select distinct o.observation_no, p.proposal_id, g.file_path, p.backend_type from " \ "gmrt.proposal p inner join das.observation o on p.proposal_id = o.proj_code " \ "inner join das.scangroup g on g.observation_no = o.observation_no " \ "inner join das.scans s on s.scangroup_id = g.scangroup_id " \ "inner join gmrt.sourceobservationtype so on p.proposal_id = so.proposal_id " \ "where p.cycle_id ='" + CYCLE_ID + "' " \ "and so.obs_type not like 'pulsar%' " \ "and so.obs_type not like 'phased array'" \ "and s.sky_freq1=s.sky_freq2 " \ "and s.sky_freq1 < 900000000 " \ "and s.chan_width >= 62500 " \ "and o.proj_code not like '16_279' " \ "and o.proj_code not like '17_072' " \ "and o.proj_code not like '18_031' " \ "and o.proj_code not like '19_043' " \ "and o.proj_code not like '20_083' " \ "and o.proj_code not like '23_066' " \ "and o.proj_code not like '26_063' " \ "and o.proj_code not like 'ddtB014' " \ "and o.proj_code not like 'ddtB015' " \ "and o.proj_code not like 'ddtB028' " \ "and o.proj_code not like '21_057';" dbutils = DBUtils() data = dbutils.select_query(sql_query) gadpudata = {} for each_row in data: gadpudata[each_row[0]] = { "proposal_id": each_row[1], "file_path": each_row[2], "backend_type": each_row[3], "cycle_id": CYCLE_ID } return (gadpudata, CYCLE_PATH)
jpeg_images_path = '/GARUDATA/jpeg_images/' data = dbutils.select_gadpu_query(sql_query) counter=0 for each_row in data: counter+=1 base_path = each_row[0] observation_no = each_row[1] jpeg_img_file = each_row[2].replace('.FITS','.jpeg') source_name = jpeg_img_file.split('.')[0] jpeg_img_path = base_path+'/FITS_IMAGE/'+jpeg_img_file if os.path.exists(jpeg_img_path): sql_query = "select distinct scan_id, observation_no, source from das.scans where observation_no = "+str(observation_no)+" and source like '"+source_name+"'" scans_data = dbutils.select_query(sql_query) # print(int(observation_no), source_name, jpeg_img_path) if scans_data: cycle_dir = base_path.split('/')[3] images_path = jpeg_images_path+cycle_dir+'/'+str(observation_no) if not os.path.exists(images_path): os.system("mkdir -p "+images_path) copying = os.system("cp "+jpeg_img_path+" "+images_path+"/") for each_scan in scans_data: scan_id = each_scan[0] scans_update_data = { "set": { "jpeg_img_path": str(images_path+'/'+jpeg_img_file).replace('GARUDATA','data') }, "where": { "scan_id": int(scan_id)