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)
