def getTimeInterval():
"""
Replace generic getTimeInterval with one that calls logs.readSourceScans instead.
"""
return logs.readSourceScanTimes(autoprocess_start_date, autoprocess_stop_date, my_name,
nscans_min=nscans_min, nscans_max=nscans_max,
log_summary_dir=directories['log_summary_dir'])
def readInterval(interval):
'''Just read some data'''
interval = logs.readSourceScanTimes(interval[0],
interval[1],
source,
nscans_min=50)[0]
data = SPTDataReader(interval[0],
interval[1],
quiet=True,
config_file="sptpol_stripped_master_config")
data.readData(interval[0],
interval[1],
correct_global_pointing=False,
standardize_samplerates=False)
return data
if __name__ == '__main__':
# times = [['140326 22:30:51', '140327 01:02:21'], # dither 6
# ['140328 10:26:20', '140328 12:57:40'], # dither 12
# ['140329 22:28:40', '140330 01:02:44'], # dither 18
# ['140331 12:59:38', '140331 15:32:02'], # dither 0
# ['140403 07:49:00',
# SptDatetime.now().strftime('%y%m%d %H:%M:%S')]]
times = [
['140525 05:01:19', '140525 07:40:23'], # dither 0
['140525 14:16:48', '140525 16:57:01']
] # dither 9
OUTPUT_DIR = '/data/ndhuang/fast_500d_map/run1/proj1'
datas = []
for t in times:
realtimes = logs.readSourceScanTimes(t[0],
t[1],
'ra0hdec-57.5',
nscans_min=0)
for rt in realtimes:
start = SptDatetime(rt[0])
stop = SptDatetime(rt[1])
data = SPTDataReader(start_date=start, stop_date=stop, quiet=True)
data.readData(start, stop, correct_global_pointing=False)
datas.append(data)
break
# make_map(start, stop)
# coadd = sum(maps)
# ma = MapAnalyzer(delta_ell=25, set_special_bb_bins = False)
# cls = ma.calculateCls()
# pl.plot(cls.ell.TT, cls.TT)
# savefig('/home/ndhuang/plots/ra0hdec-57.5_fast_TT.png')
]
maps_right = [
cMapping(i, doreal=True, use_leftgoing=False,
**map_args)[str(idfs[0].band)] for i in idfs
]
left = np.sum(maps_left)
right = np.sum(maps_right)
left.writeToHDF5(os.path.join(
outdir, 'left', 'sunop_map_{:03d}ghz.h5'.format(idfs[0].band)),
overwrite=True)
right.writeToHDF5(os.path.join(
outdir, 'right', 'sunop_map_{:03d}ghz.h5'.format(idfs[0].band)),
overwrite=True)
return left, right
if __name__ == '__main__':
N_PROCS = 4
OUTPUT_DIR = '/data/ndhuang/sunop_sidelobe'
realtimes = logs.readSourceScanTimes('20150201',
'20150205',
'opsun',
nscans_min=0)
# make_idf_pieces(realtimes[0][0], realtimes[0][1])
idf90 = glob.glob(os.path.join(OUTPUT_DIR, 'idf*090ghz*.h5'))
map_from_many_idfs(idf90, OUTPUT_DIR)
idf150 = glob.glob(os.path.join(OUTPUT_DIR, 'idf*150ghz*.h5'))
map_from_many_idfs(idf150, OUTPUT_DIR)
import os
import numpy as np
import matplotlib
matplotlib.use('Agg')
from matplotlib import mlab, pyplot as pl
from sptpol_software.autotools import logs
from sptpol_software.data.readout import SPTDataReader
from sptpol_software.analysis.processing import getGoodBolos
if __name__ == '__main__':
# start = '140611 06:03:43' # new fast scan
# stop = '140611 08:42:36'
start = '140325 02:54:31' # lead-trail
stop = '140325 08:47:35'
start, stop = logs.readSourceScanTimes(start, stop, 'ra0hdec-57.5',
nscans_min = 30)[0]
data = SPTDataReader(start, stop, quiet = True)
data.readData(start, stop, correct_global_pointing = False)
scan_len = [(s.stop_index - s.start_index) for s in data.scan]
scan_len = max(scan_len)
coadd = [np.zeros(scan_len), np.zeros(scan_len)]
coadd_el = [np.zeros(scan_len), np.zeros(scan_len)]
coadd_err = [np.zeros(scan_len), np.zeros(scan_len)]
nfft = 2048
pxx = [np.zeros(nfft / 2 + 1), np.zeros(nfft / 2 + 1)]
pxx_el = [np.zeros(nfft / 2 + 1), np.zeros(nfft / 2 + 1)]
pxx_err = [np.zeros(nfft / 2 + 1), np.zeros(nfft / 2 + 1)]
good_bolos = getGoodBolos(data, 'map_default')
for s in data.scan:
if s.is_leftgoing:
ind = 0
import numpy as np
from matplotlib import pyplot as pl
from sptpol_software.autotools import logs
import sptPyReadArc as arc
# read in data
start, stop = logs.readSourceScanTimes('20150201',
'20150204',
'opsun',
nscans_min=10)[0]
# First, read in the entire with one bolo
data_small = arc.readArc([
'receiver.bolometers.adcCountsI[0]~ double',
'antenna0.tracker.scan_flag~ uint'
], str(start), str(stop), '/data/sptdat/arcfile_directory/20150129_000000/')
# Now, the full set (~60 GB)
data_full = arc.readArc([
'receiver.bolometers.adcCountsI[0-1599]~ double',
'antenna0.tracker.scan_flag~ uint'
], str(start), str(stop), '/data/sptdat/arcfile_directory/20150129_000000/')
# Upsample the scan flags
# I have tested that the scan flags are identical between data_full and
# data_small, but you can test this:
# np.nonzero(data_small['antenna0.tracker.scan_flag'][0] -
# data_full['antenna0.tracker.scan_flag'][0])
# I am assuming that the scan flags and bolodata vectors cover exactly the
# same amount of time so I can use the index as a proxy for time.
# Since this works with the small data sample, I believe the assumptions
# are correct
from datetime import datetime
from sptpol_software.data.readout import SPTDataReader
from sptpol_software.util.time import SptDatetime
from sptpol_software.analysis import processing
from sptpol_software.autotools import logs
readout_kwargs = {
'timestream_units':
'Watts', # Convert to T_CMB in preprocessing functions.
'correct_global_pointing': True,
'downsample_bolodata': 4,
'project_iq': True,
'exception_on_no_iq': True
}
for times in logs.readSourceScanTimes('20-Mar-2012',
'now',
'ra23h30dec-55',
nscans_min=1):
start = SptDatetime(times[0])
end = SptDatetime(times[1])
try:
data = SPTDataReader(start, end)
data.readData(**readout_kwargs)
processing.notchFilter(data, verbose=True)
except ValueError, err:
print err