def setUp(self) :
Reader = fitsGBT.Reader(test_file, feedback=0)
blocks = Reader.read((),())
for Data in blocks :
rotate_pol.rotate(Data, (1,2,3,4))
Writer = fitsGBT.Writer(blocks, feedback=0)
Writer.write('test_rot.testout.fits')
self.params = {'pc_file_middles' : ("test",),
'pc_input_end' : "_rot.testout.fits",
'pc_output_end' : "_polcal.testout.fits",
'pc_mueler_file' : test_mueler_file
}
def process_file(self, file_ind):
"""Process on file from the list to be processed based on the passed
index.
"""
self.file_ind = file_ind
params = self.params
file_middle = params['file_middles'][file_ind]
input_fname = (params['input_root'] + file_middle +
params['input_end'])
output_fname = (params['output_root'] + file_middle +
params['output_end'])
Writer = fitsGBT.Writer(feedback=self.feedback)
# Read in the data, and loop over data blocks.
Reader = fitsGBT.Reader(input_fname, feedback=self.feedback)
if hasattr(self, 'feedback_title') and self.feedback > 1:
print self.feedback_title,
# Get the number of scans if asked for all of them.
scan_inds = params['scans']
if len(scan_inds) == 0 or scan_inds is None:
scan_inds = range(len(Reader.scan_set))
# Loop over scans.
for thisscan in scan_inds:
Blocks = Reader.read(thisscan, params['IFs'], force_tuple=True)
# Function that loops over DataBlocks within a scan.
NewBlocks = self.scan_action(Blocks)
del Blocks
Writer.add_data(NewBlocks)
# Go to a new line if we are printing statistics.
if hasattr(self, 'feedback_title') and self.feedback > 1:
print ''
# Finally write the data back to file.
utils.mkparents(output_fname)
Writer.write(output_fname)
def replace(in_dir, out_dir):
kiyopy.utils.mkdir_p(out_dir)
files = glob.glob(in_dir + '/*.fits')
data_dir = os.getenv('GBT_DATA')
for file in files:
out_fname = out_dir + file.split('/')[-1]
data_fname = data_dir + '/'.join(file.split('/')[-2:])
if not os.path.isfile(data_fname):
msg = "Raw data file: %s missing" % data_fname
raise ValueError(msg)
raw_Reader = fitsGBT.Reader(data_fname)
raw_data_list = raw_Reader.read()
Reader = fitsGBT.Reader(file)
data_list = Reader.read()
if len(raw_data_list) != len(data_list):
raise ValueError("Wrong number of scans in raw data.")
for ii in range(len(data_list)):
raw_data = raw_data_list[ii]
ra = raw_data.field['RA']
ra_format = raw_data.field_formats['RA']
ra_axes = raw_data.field_axes['RA']
data_list[ii].set_field('RA',
ra,
axis_names=ra_axes,
format=ra_format)
dec = raw_data.field['DEC']
dec_format = raw_data.field_formats['DEC']
dec_axes = raw_data.field_axes['DEC']
data_list[ii].set_field('DEC',
dec,
axis_names=dec_axes,
format=dec_format)
Writer = fitsGBT.Writer(data_list)
Writer.write(out_fname)
def process_file(self, file_ind):
params = self.params
file_middle = params['file_middles'][file_ind]
input_fname = (params['input_root'] + file_middle +
params['input_end'])
sub_input_fname = (params['subtracted_input_root'] + file_middle +
params['input_end'])
output_fname = (params['output_root'] + file_middle +
params['output_end'])
sub_output_fname = (params['subtracted_output_root'] + file_middle +
params['output_end'])
Writer = fitsGBT.Writer(feedback=self.feedback)
SubWriter = fitsGBT.Writer(feedback=self.feedback)
# Read in the data, and loop over data blocks.
Reader = fitsGBT.Reader(input_fname, feedback=self.feedback)
SubReader = fitsGBT.Reader(sub_input_fname, feedback=self.feedback)
if (sp.any(Reader.scan_set != SubReader.scan_set)
or sp.any(Reader.IF_set != SubReader.IF_set)):
raise ce.DataError("IFs and scans don't match signal subtracted"
" data.")
# Get the number of scans if asked for all of them.
scan_inds = params['scans']
if len(scan_inds) == 0 or scan_inds is None:
scan_inds = range(len(Reader.scan_set))
if_inds = params['IFs']
if len(if_inds) == 0 or scan_inds is None:
if_inds = range(len(Reader.IF_set))
if self.feedback > 1:
print "New flags each block:",
# Loop over scans and IFs
for thisscan in scan_inds:
for thisIF in if_inds:
Data = Reader.read(thisscan, thisIF)
SubData = SubReader.read(thisscan, thisIF)
# Make sure they have agreeing masks to start.
SubData.data[ma.getmaskarray(Data.data)] = ma.masked
Data.data[ma.getmaskarray(SubData.data)] = ma.masked
# Get initial number of flags.
n_flags = ma.count_masked(Data.data)
# Now do the flagging.
flag(Data, SubData, params['thres'],
params['max_noise_factor'],
params['smooth_modes_subtract'], params['filter_type'])
Data.add_history(
"Reflaged for outliers.",
("Used file: " +
utils.abbreviate_file_path(sub_input_fname), ))
SubData.add_history("Reflaged for outliers.")
Writer.add_data(Data)
SubWriter.add_data(SubData)
# Report the number of new flags.
n_flags = ma.count_masked(Data.data) - n_flags
if self.feedback > 1:
print n_flags,
if self.feedback > 1:
print ''
# Finally write the data back to file.
utils.mkparents(output_fname)
utils.mkparents(sub_output_fname)
Writer.write(output_fname)
SubWriter.write(sub_output_fname)
import scipy as sp
import pyfits
from core import fitsGBT, data_block
from time_stream import stitch_windows_crude
# A calibration file from which I will copy headers and the like.
data_file_name = (os.getenv('GBT10B_DATA') +
'/05_3c286_onoff_161-164.raw.acs.fits')
# Where I saved Kevin's Tables.
kevin_table_dir = os.getenv('GBT10B_OUT') + '/kevin_cal/'
out_file = kevin_table_dir + 'cal_21.fits'
input_root = kevin_table_dir + '21_3c48_113-116_noisecal_'
Writer = fitsGBT.Writer()
Reader = fitsGBT.Reader(data_file_name)
Blocks = Reader.read(0, ())
required_fields = ('CRVAL1', 'CDELT1', 'CRPIX1', 'SCAN')
CalBlocks = ()
# Loop over IFs and read in the appropriate cal data.
for Data in Blocks:
CalT = data_block.DataBlock()
for field in required_fields:
CalT.set_field(field, Data.field[field], Data.field_axes[field],
Data.field_formats[field])
elif not band2:
band2 = band
band2_Blocks.append(Data)
else :
raise RuntimeError()
# Measure the parameters.
file_pars[band1] = measure_noise.measure_noise_parameters(band1_Blocks,
["channel_var", "mean_over_f",
"freq_modes_over_f_2", "freq_modes_over_f_4",
"freq_modes_over_f_6"])
file_pars[band2] = measure_noise.measure_noise_parameters(band2_Blocks,
["channel_var", "mean_over_f",
"freq_modes_over_f_2", "freq_modes_over_f_4",
"freq_modes_over_f_6"])
out_db = shelve.open('./testdata/testfile_guppi_noise_parameters.shelve', 'n')
out_db["testfile_guppi_rotated"] = file_pars
out_db.close()
Writer = fitsGBT.Writer(Blocks)
Writer.write('./testdata/testfile_guppi_rebinned.fits')
Writer = fitsGBT.Writer(split_Blocks)
Writer.write('./testdata/testfile_guppi_split.fits')
Writer = fitsGBT.Writer(comb_Blocks)
Writer.write('./testdata/testfile_guppi_combined.fits')
Writer = fitsGBT.Writer(rot_Blocks)
Writer.write('./testdata/testfile_guppi_rotated.fits')