def create_utservo(servo_file, offsets, utcc, ut):
"""Create file with servo data with fixed CC and UT
Parameters
----------
servo_file : str
filename of servo data
offsets : ndarray
CC offsets computed from gpstime, see find_clock_offsets_from_gpstime
utcc : ndarray
CC array related to UT
ut : ndarray
UT array
Returns
-------
writes utservo.fits file to disk
"""
print("Create UT timestamped servo data")
utservo = OrderedDict()
for device in DEVICES:
print('Processing ' + device)
utservo[device] = fits.read(servo_file, device)
utservo[device]['COMPUTERCLOCK'] = apply_cc_offsets(utservo[device]['COMPUTERCLOCK'], offsets)
utservo[device]['UT'] = np.interp( utservo[device]['COMPUTERCLOCK'], utcc, ut)
filename = 'utservo.fits'
print('Writing ' + filename)
fits.write(filename, utservo)
return utservo
def create_utservo(servo_file, offsets, utcc, ut):
"""Create file with servo data with fixed CC and UT
Parameters
----------
servo_file : str
filename of servo data
offsets : ndarray
CC offsets computed from gpstime, see find_clock_offsets_from_gpstime
utcc : ndarray
CC array related to UT
ut : ndarray
UT array
Returns
-------
writes utservo.fits file to disk
"""
print("Create UT timestamped servo data")
utservo = OrderedDict()
for device in DEVICES:
print('Processing ' + device)
utservo[device] = fits.read(servo_file, device)
utservo[device]['COMPUTERCLOCK'] = apply_cc_offsets(utservo[device]['COMPUTERCLOCK'], offsets)
utservo[device]['UT'] = np.interp( utservo[device]['COMPUTERCLOCK'], utcc, ut)
filename = 'utservo.fits'
print('Writing ' + filename)
fits.write(filename, utservo)
return utservo
def create_utscience(sci_file, gyro, revcounter, offsets, utcc, ut, freq):
"""Create file with science data with fixed CC and UT
see create_utservo
"""
data = fits.read(sci_file)
splitted_data = OrderedDict()
splitted_data['TIME'] = OrderedDict()
for ch_n in range(16):
ch_name = 'CH%d_' % ch_n
splitted_data[ch_name] = OrderedDict()
for comp in 'TQU':
splitted_data[ch_name][comp] = data[ch_name + comp]
splitted_data['TIME']['COMPUTERCLOCK'], splitted_data['TIME']['NOREVCOUNTFLAG']= create_science_computerclock(gyro, revcounter, data['REV'], offsets)
splitted_data['TIME']['UT'] = np.interp(splitted_data['TIME']['COMPUTERCLOCK'], utcc, ut)
filename = '%s_%dGHz_data.fits' % (os.path.basename(sci_file).split('.')[0], freq)
print('Writing ' + filename)
fits.write(filename, splitted_data)
return splitted_data
def create_utscience(sci_file, gyro, revcounter, offsets, utcc, ut, freq):
"""Create file with science data with fixed CC and UT
see create_utservo
"""
data = fits.read(sci_file)
splitted_data = OrderedDict()
splitted_data['TIME'] = OrderedDict()
for ch_n in range(16):
ch_name = 'CH%d_' % ch_n
splitted_data[ch_name] = OrderedDict()
for comp in 'TQU':
splitted_data[ch_name][comp] = data[ch_name + comp]
splitted_data['TIME']['COMPUTERCLOCK'], splitted_data['TIME']['NOREVCOUNTFLAG']= create_science_computerclock(gyro, revcounter, data['REV'], offsets)
splitted_data['TIME']['UT'] = np.interp(splitted_data['TIME']['COMPUTERCLOCK'], utcc, ut)
filename = '%s_%dGHz_data.fits' % (os.path.basename(sci_file).split('.')[0], freq)
print('Writing ' + filename)
fits.write(filename, splitted_data)
return splitted_data
h_jumps_scaled[h_jumps] *= np.round(np.diff(ut)[h_jumps]/typical_revlength)
unwrapped[1:] += np.cumsum(h_jumps_scaled) * np.pi * 2
#smooth
#unwrapped = smooth(unwrapped, 30)
#read ut science
ut_sci_10 = pyfits.getdata(os.path.join(folder, 'all_10GHz_data.fits'), 'TIME')['UT']
ut_sci_15 = pyfits.getdata(os.path.join(folder, 'all_15GHz_data.fits'), 'TIME')['UT']
#interpolate and reset to -pi pi
fixed_az_10 = np.mod(smooth(np.interp(ut_sci_10, ut, unwrapped),30) + np.pi, 2*np.pi) - np.pi
fixed_az_15 = np.mod(smooth(np.interp(ut_sci_15, ut, unwrapped),30) + np.pi, 2*np.pi) - np.pi
# TODO flagging
###gaps longer than ROTATION are flagged
flag_10 = np.ceil(np.interp(ut_sci_10, ut[1:], np.diff(ut) > 80/3600.)).astype(np.uint8)
flag_15 = np.ceil(np.interp(ut_sci_15, ut[1:], np.diff(ut) > 80/3600.)).astype(np.uint8)
##self.synched_data[device]['FLAG'] = flag
#plt.figure()
#plt.plot(ut_sci_10, fixed_az_10, 'r.', label='fixed')
#plt.xlabel('UT')
#plt.savefig('fixedaz.png')
import pycfitsio as fits
fits.write(os.path.join(folder, 'fixaz.fits'), OrderedDict([
('10GHz', OrderedDict([('UT', ut_sci_10), ('AZ', fixed_az_10), ('FLAG', flag_10)])),
('15GHz', OrderedDict([('UT', ut_sci_15), ('AZ', fixed_az_15), ('FLAG', flag_15)]))
]))
h_jumps_scaled[h_jumps] *= np.round(np.diff(ut)[h_jumps]/typical_revlength)
unwrapped[1:] += np.cumsum(h_jumps_scaled) * np.pi * 2
#smooth
#unwrapped = smooth(unwrapped, 30)
#read ut science
ut_sci_10 = pyfits.getdata(os.path.join(folder, 'all_10GHz_data.fits'), 'TIME')['UT']
ut_sci_15 = pyfits.getdata(os.path.join(folder, 'all_15GHz_data.fits'), 'TIME')['UT']
#interpolate and reset to -pi pi
fixed_az_10 = np.mod(smooth(np.interp(ut_sci_10, ut, unwrapped),30) + np.pi, 2*np.pi) - np.pi
fixed_az_15 = np.mod(smooth(np.interp(ut_sci_15, ut, unwrapped),30) + np.pi, 2*np.pi) - np.pi
# TODO flagging
###gaps longer than ROTATION are flagged
flag_10 = np.ceil(np.interp(ut_sci_10, ut[1:], np.diff(ut) > 80/3600.)).astype(np.uint8)
flag_15 = np.ceil(np.interp(ut_sci_15, ut[1:], np.diff(ut) > 80/3600.)).astype(np.uint8)
##self.synched_data[device]['FLAG'] = flag
#plt.figure()
#plt.plot(ut_sci_10, fixed_az_10, 'r.', label='fixed')
#plt.xlabel('UT')
#plt.savefig('fixedaz.png')
import pycfitsio as fits
fits.write(os.path.join(folder, 'fixaz.fits'), OrderedDict([
('10GHz', OrderedDict([('UT', ut_sci_10), ('AZ', fixed_az_10), ('FLAG', flag_10)])),
('15GHz', OrderedDict([('UT', ut_sci_15), ('AZ', fixed_az_15), ('FLAG', flag_15)]))
]))
