def find_tscpos_positive_period(start, stop):
"""
find time periods of tscpos is located in positive position
input: start --- starting time in mm/dd/yy,hh:mm:ss
stop --- stopping time in mm/dd/yy,hh:mm:ss
output: positive_period a list of lists containing a list of time of period starting
and a list of time of period ending. both in seconds from 1998.1.1
"""
#
#--- extract sim data
#
dlist = hcf.run_arc5gl('retrieve',
start,
stop,
detector='sim',
level='0',
filetype='sim')
#
#--- find time period when tscpos is in positive side
#
positive_periods = create_data_period(start,
stop,
dlist,
colname='TSCPOS',
lgc='>=',
val=0)
#
#-- clean the output directory
#
for ent in dlist:
mcf.rm_file(ent)
return positive_periods
def extrct_hrchk_data(start, stop):
"""
extract hrchk fits file and get column data we need
input: start --- starting time
stop --- stopping time
output: out --- pyfits data table format of extracted data from data with datamore: NEXT_IN_LINE
"""
#
#--- extract hrchk fits files
#
dlist = hcf.run_arc5gl('retrieve', start, stop, dataset='flight', detector='hrc', level='0', filetype='hrchk')
nil_list = []
for fits in dlist:
#
#--- find datamode: we need only NEXT_IN_LINE case
#
dmode = hcf.read_header_value(fits, 'DATAMODE')
if dmode == 'NEXT_IN_LINE':
nil_list.append(fits)
if len(nil_list) > 0:
dout = hcf.combine_and_select_data(nil_list, hk_col_list)
else:
dout = NULL
#
#--- empty out the temporary direcotry
#
for ent in dlist:
mcf.rm_file(ent)
return dout
def find_scint(tstart, tstop):
"""
find integrated EPHIN flux
input: tstart --- starting time in seconds from 1998.1.1
tstop --- stopping time in seconds from 1998.1.1
output; avg --- average of ephin flux
std --- standard deviation of flux
"""
#
#--- extract ephin data
#
hcf.run_arc5gl('retrieve', tstart, tstop, dataset='flight',detector='ephin',\
level=1,filetype='ephrates')
#
#--- create extracted fits file list
#
ldir = exc_dir + 'Temp_dir/'
flist = hcf.get_file_list(ldir, 'lc1.fits.gz')
#
#--- combine all fits files into one
#
hcf.combine_fits_files(flist, 'ztemp.fits', azip=0)
[cols, tbdata] = hcf.read_fits_file('ztemp.fits')
#
#--- limit data to between tstart and tstop
#
tbdata = hcf.select_data_with_condition(tbdata, 'time', ">=", tstart)
tbdata = hcf.select_data_with_condition(tbdata, 'time', "<=", tstop)
#
#--- compute the basic stat
#
[avg, med, std, vmin, vmax, vcnt] = get_basic_stat(tbdata['scint'])
cmd = 'rm ztemp.fits' + '*'
os.system(cmd)
if hcf.check_file_in_dir(ldir):
cmd = 'rm ' + ldir + '*'
os.system(cmd)
return [avg, std]
def extract_fits_files(time_list, detector, level, filetype, subdetector=''):
"""
extract fits file for given time period
input: time_list --- a list of lists of start and stop time
detector --- detector name
level --- level
filetype --- file type
subdetector --- sub detector name
output: extracted fits files in <exc_dir>/Temp_dir/
fits_list --- a list of extracted fits file names
"""
if len(time_list) < 2:
return []
[start_list, stop_list] = time_list
#
#--- just in a case, start and stop time are not given in a list form
#--- make them into a list form
#
if not isinstance(start_list, list):
start_list = [start_list]
if not isinstance(stop_list, list):
stop_list = [stop_list]
fits_list = [] #--- just in a case nothing extracted
for m in range(0, len(start_list)):
try:
start = float(start_list[m])
stop = float(stop_list[m])
except:
break
#
#--- extract fits files
#
dlist = hcf.run_arc5gl('retrieve', start, stop, detector=detector, level=level,\
filetype=filetype, subdetector=subdetector)
if m == 0:
fits_list = dlist
else:
fits_list = fits_list + dlist
#
#--- since there are occasional overlap in periods, make sure that all fits names are uniqe
#
fits_list = hcf.remove_duplicate_from_list(fits_list)
return fits_list