def run_update_with_ska(msid, group, msid_sub_list=[], glim=''):
"""
extract data from ska database and update the data for the msids in the msid_list
input: msid --- a list of msids
group --- the group of the msids
msid_sub_list --- a list of lists of:
[msid, msid_1, msid_2, operand]
this is used to compute the first msid from following two
msid values with operand (+/-/*)
glim --- glim usually found in this function, but you can give it; default: ''
output: <msid>_data.fits, <msid>_short_data,fits, <msid>_week_data.fits
"""
#
#--- get basic information dict/list
#
[udict, ddict, mta_db, mta_cross] = ecf.get_basic_info_dict()
#
#--- set starting and stopping data period
#
test_fits = data_dir + group.capitalize() + '/' + msid + '_data.fits'
if os.path.isfile(test_fits):
tstart = ecf.find_the_last_entry_time(test_fits)
ttemp = time.strftime("%Y:%j:00:00:00", time.gmtime())
tstop = Chandra.Time.DateTime(ttemp).secs - 86400.0
if tstop < tstart:
exit(1)
if len(msid_sub_list) != 0:
[dtime, tdata] = compute_sub_msid(msid, msid_sub_list, tstart, tstop)
else:
out = fetch.MSID(msid, tstart, tstop)
ok = ~out.bads
dtime = out.times[ok]
tdata = out.vals[ok]
#
#--- fetch occasionally adds -999.xxx to the output data of some msids; remove them (Jun 13, 2018)
#
tind = [(tdata > -999) | (tdata <= -1000)]
dtime = dtime[tind]
tdata = tdata[tind]
#
#--- get limit data table for the msid
#
if glim == '':
try:
tchk = ecf.convert_unit_indicator(udict[msid])
except:
tchk = 0
if msid in sp_limt_case_c:
tchk = 1
glim = ecf.get_limit(msid, tchk, mta_db, mta_cross)
#
#--- update database
#
update_database(msid, group, dtime, tdata, glim)
def extract_hrcveto_data():
"""
extract hrc veto data
input: none
output: fits file data related to grad and comp
"""
#
#--- set basic information
#
group = 'Hrcveto'
cols = ['TLEVART', 'VLEVART', 'SHEVART']
[udict, ddict, mta_db, mta_cross] = ecf.get_basic_info_dict()
#
#--- find the date to be filled
#
ctime = ecf.find_the_last_entry_time(testfits)
start = Chandra.Time.DateTime(ctime).date
today = time.strftime("%Y:%j:00:00:00", time.gmtime())
ctime = Chandra.Time.DateTime(today).secs - 43200.0
stop = Chandra.Time.DateTime(ctime).date
print("Group: " + group + ': ' + str(start) + '<-->' + str(stop))
[xxx, tbdata] = uds.extract_data_arc5gl('hrc', '0', 'hrcss', start, stop)
#
#--- get time data in the list form
#
dtime = list(tbdata.field('time'))
for col in cols:
#
#---- extract data in a list form
#
data = list(tbdata.field(col))
#
#--- change col name to msid
#
msid = col.lower()
#
#--- get limit data table for the msid
#
try:
tchk = ecf.convert_unit_indicator(udict[msid])
except:
tchk = 0
glim = ecf.get_limit(msid, tchk, mta_db, mta_cross)
#
#--- update database
#
uds.update_database(msid, group, dtime, data, glim)
def run_update_with_archive(msid_list, group, date_list, detector, level, filetype, tstart, tstop, sub=''):
"""
extract data using arc5gl and update the data for the msids in the msid_list
input: msid_list --- the name of the list of msids
group --- a group name
date_list --- a list of date to be processed in the form of <yyyy>:<ddd>
detector --- detector name
level --- level
filetype --- file name
tstart --- starting time
tstop --- stopping time
sub --- subdetector name; defalut "" --- no sub detector
output: <msid>_data.fits, <msid>_short_data,fits, <msid>_week_data.fits
"""
#
#--- get basic information dict/list
#
[udict, ddict, mta_db, mta_cross] = ecf.get_basic_info_dict()
#
#--- extract data using arc5gl
#
[cols, tbdata] = extract_data_arc5gl(detector, level, filetype, tstart, tstop, sub='')
#
#--- get time data in the list form
#
dtime = list(tbdata.field('time'))
for col in msid_list:
#
#---- extract data in a list form
#
data = list(tbdata.field(col))
#
#--- change col name to msid
#
msid = col.lower()
#
#--- get limit data table for the msid
#
try:
tchk = ecf.convert_unit_indicator(udict[msid])
except:
tchk = 0
glim = ecf.get_limit(msid, tchk, mta_db, mta_cross)
#
#--- update database
#
update_database(msid, group, dtime, data, glim)
def update_simsuppl_data(date=''):
"""
collect sim msids data
input: date ---- the date in yyyymmdd format. if not given, yesterday's date is used
output: fits file data related to sim
"""
#
#--- read group names which need special treatment
#
sfile = house_keeping + 'msid_list_simactu_supple'
data = mcf.read_data_file(sfile)
cols = []
g_dir = {}
for ent in data:
atemp = re.split('\s+', ent)
cols.append(atemp[0])
g_dir[atemp[0]] = atemp[1]
#
#--- get the basic information
#
[udict, ddict, mta_db, mta_cross] = ecf.get_basic_info_dict()
#
#--- find date to read the data
#
if date == '':
date_list = ecf.create_date_list_to_yestaday(testfits)
else:
date_list = [date]
for sday in date_list:
sday = sday[:4] + '-' + sday[4:6] + '-' + sday[6:]
print("Date: " + sday)
start = sday + 'T00:00:00'
stop = sday + 'T23:59:59'
[xxx, tbdata] = extract_data_arc5gl('sim', '0', 'sim', start, stop)
#
#--- get time data in the list form
#
dtime = list(tbdata.field('time'))
for k in range(0, len(cols)):
#
#--- select col name without ST_ (which is standard dev)
#
col = cols[k]
#
#---- extract data in a list form
#
data = list(tbdata.field(col))
#
#--- change col name to msid
#
msid = col.lower()
#
#--- get limit data table for the msid
#
try:
tchk = ecf.convert_unit_indicator(udict[msid])
except:
tchk = 0
glim = ecf.get_limit(msid, tchk, mta_db, mta_cross)
#
#--- update database
#
update_database(msid, g_dir[msid], dtime, data, glim)
def tephin_leak_data_update(year=''):
"""
update tephin - ephin rate/leak current data
input: year --- year of the data to be updated. if it is '', the current year is used
output: <data_dir>/<msid>/<msid>_data_<year>.fits
"""
#
#--- set data extraction period
#
tout = set_time_period(year)
if len(tout) == 6:
[ltstart, ltstop, lyear, tstart, tstop, year] = tout
chk = 1
else:
[tstart, tstop, year] = tout
chk = 0
#
#--- get the basic information
#
[udict, ddict, mta_db, mta_cross] = ecf.get_basic_info_dict()
#
#--- extract tephin data
#
tchk = ecf.convert_unit_indicator(udict['tephin'])
glim = ecf.get_limit('tephin', tchk, mta_db, mta_cross)
#
#--- for the case the time span goes over the year boundary
#
if chk == 1:
ltephin = update_database('tephin', 'Eleak', glim, ltstart, ltstop,
lyear)
tephin = update_database('tephin', 'Eleak', glim, tstart, tstop, year)
#
#--- read msid list
#
mfile = house_keeping + 'msid_list_eph_tephin'
data = mcf.read_data_file(mfile)
for ent in data:
#
#--- find msid and group name
#
mc = re.search('#', ent)
if mc is not None:
continue
try:
[msid, group] = re.split('\s+', ent)
except:
atemp = re.split('\s+', ent)
msid = atemp[0]
group = atemp[1]
msid.strip()
group.strip()
#
#--- get limit data table for the msid
#
try:
tchk = ecf.convert_unit_indicator(udict[msid])
except:
tchk = 0
glim = ecf.get_limit(msid, tchk, mta_db, mta_cross)
#
#--- update database
#
try:
out = fetch.MSID(msid, '2017:001:00:00:00', '2017:002')
print("MSID: " + msid)
except:
missed = house_keeping + '/missing_data'
with open(missed, 'a') as fo:
fo.write(msid + '\n')
continue
#
#--- for the case, the time span goes over the year boundary
#
if chk == 1:
update_database(msid,
group,
glim,
ltstart,
ltstop,
lyear,
sdata=ltephin)
try:
update_database(msid,
group,
glim,
tstart,
tstop,
year,
sdata=tephin)
except:
pass
def gratgen_categorize_data():
"""
separate gratgen data into different categories
input: none but use <data_dir>/Gratgen/*.fits
output: <data_dir>/Gratgen_<catogry>/*.fits
"""
#
#--- get the basic information
#
[udict, ddict, mta_db, mta_cross] = ecf.get_basic_info_dict()
for msid in msid_list:
cols = ['time', msid, 'med', 'std', 'min', 'max', 'ylower',\
'yupper', 'rlower', 'rupper', 'dcount', 'ylimlower',\
'ylimupper', 'rlimlower', 'rlimupper']
glim = ecf.get_limit(msid, 0, mta_db, mta_cross)
for category in cname_list:
print("Running: " + str(msid) + '<-->' + category)
cfile1 = data_dir + 'Gratgen/' + category.capitalize(
) + '/' + msid + '_data.fits'
cfile2 = data_dir + 'Gratgen/' + category.capitalize(
) + '/' + msid + '_short_data.fits'
cfile3 = data_dir + 'Gratgen/' + category.capitalize(
) + '/' + msid + '_week_data.fits'
stday = time.strftime("%Y:%j:00:00:00", time.gmtime())
tcut1 = 0.0
tcut2 = Chandra.Time.DateTime(
stday).secs - 31622400.0 #--- a year agao
tcut3 = Chandra.Time.DateTime(
stday).secs - 864000.0 #--- 10 days ago
if os.path.isfile(cfile1):
tchk = ecf.find_the_last_entry_time(cfile1)
else:
tchk = 0
ifile = house_keeping + category
data = mcf.read_data_file(ifile)
start = []
stop = []
for ent in data:
atemp = re.split('\s+', ent)
val1 = float(atemp[0])
val2 = float(atemp[1])
if val1 > tchk:
start.append(val1)
stop.append(val2)
if len(start) == 0:
continue
for k in range(0, len(start)):
diff = stop[k] - start[k]
if diff < 300:
start[k] -= 100
stop[k] = start[k] + 300.
data = fetch.MSID(msid, start[k], stop[k])
if k == 0:
ttime = list(data.times)
tdata = list(data.vals)
else:
ttime = ttime + list(data.times)
tdata = tdata + list(data.vals)
if len(ttime) == 0:
continue
stat_out1 = get_stat(ttime, tdata, glim, 86400.0)
stat_out2 = get_stat(ttime, tdata, glim, 3600.0)
stat_out3 = get_stat(ttime, tdata, glim, 300.0)
if tchk > 0:
ecf.update_fits_file(cfile1, cols, stat_out1, tcut=tcut1)
ecf.update_fits_file(cfile2, cols, stat_out2, tcut=tcut2)
ecf.update_fits_file(cfile3, cols, stat_out3, tcut=tcut3)
else:
ecf.create_fits_file(cfile1, cols, stat_out1, tcut=tcut1)
ecf.create_fits_file(cfile2, cols, stat_out2, tcut=tcut2)
ecf.create_fits_file(cfile3, cols, stat_out3, tcut=tcut3)
