def test():
scene = Scene(1024)
instrument = Instrument('instrument', PackedTable((32, 32)))
sampling = Sampling(1000)
acq = Acquisition(instrument,
sampling,
scene,
nprocs_sampling=max(size // 2, 1))
print(acq.comm.rank, acq.instrument.detector.comm.rank, '/',
acq.instrument.detector.comm.size, acq.sampling.comm.rank, '/',
acq.sampling.comm.size)
def func3(shape):
instrument = Instrument('', PackedTable(shape))
acq = MyAcquisition3(instrument, sampling, scene)
noise = acq.get_noise()
assert noise.shape == (len(acq.instrument), len(acq.sampling))
assert_allclose(np.std(noise), sigma, rtol=1e-2)
def __init__(self,
todfile,
invnttfile,
mapmaskfile,
convert,
ndetectors,
missing_value=None,
comm=MPI.COMM_WORLD):
# Get information from files
nslices, status = tmf.madmap1_nslices(invnttfile, ndetectors)
if status != 0: raise RuntimeError()
npixels_per_sample, nsamples, ncorrelations, status = tmf.madmap1_info(\
todfile, invnttfile, convert, ndetectors, nslices)
if status != 0: raise RuntimeError()
m = re.search(r'(?P<filename>.*)\[(?P<extname>\w+)\]$', mapmaskfile)
if m is None:
mask = pyfits.open(mapmaskfile)[0].data
else:
filename = m.group('filename')
extname = m.group('extname')
mask = pyfits.open(filename)[str(extname)].data #XXX Python3
if mask is None:
raise IOError('HDU ' + mapmaskfile + ' has no data.')
mapmask = np.zeros(mask.shape, dtype=bool)
if missing_value is None:
mapmask[mask != 0] = True
elif np.isnan(missing_value):
mapmask[np.isnan(mask)] = True
elif np.isinf(missing_value):
mapmask[np.isinf(mask)] = True
else:
mapmask[mask == missing_value] = True
# Store instrument information
self.instrument = Instrument('Unknown', (ndetectors, ), comm=comm)
# Store observation information
class MadMap1ObservationInfo(object):
pass
self.info = MadMap1ObservationInfo()
self.info.todfile = todfile
self.info.invnttfile = invnttfile
self.info.ncorrelations = ncorrelations
self.info.npixels_per_sample = npixels_per_sample
self.info.mapmaskfile = mapmaskfile
self.info.convert = convert
self.info.missing_value = missing_value
self.info.mapmask = mapmask
# Store slice information
self.slice = np.recarray(nslices,
dtype=[('start', int), ('stop', int),
('nsamples_all', int),
('invnttfile', 'S256')])
self.slice.nsamples_all = nsamples
self.slice.start[0] = 0
self.slice.start[1:] = np.cumsum(nsamples)[:-1]
self.slice.stop = np.cumsum(nsamples)
self.slice.nfinesamples = nsamples
self.slice.invnttfile = [
invnttfile + '.' + str(i) for i in range(nslices)
]
# Store pointing information
self.pointing = np.recarray(np.sum(nsamples), [('removed', np.bool_)])
self.pointing.removed = False
# Check communicator information
if self.instrument.comm.size > 1:
raise NotImplementedError('The parallelisation of the TOD is not ' \
'implemented')
def test_pack_unpack():
layout = PackedTable(4, selection=[True, False, True, True])
instrument = Instrument('instrument', layout)
v = [1, 2, 3, 4]
assert_same(instrument.pack(v), [1, 3, 4])
assert_same(instrument.unpack([1, 3, 4]), [1, -1, 3, 4])
