def get_tod(self, unit=None):
"""
Method to get the Tod from this observation
"""
tod = Tod.empty((self.get_ndetectors(), np.sum(self.get_nsamples())))
sizeofpmatrix = self.info.npixels_per_sample * tod.size
pmatrix = np.zeros(sizeofpmatrix, dtype=int)
status = tmf.madmap1_read_tod(self.info.todfile, self.info.invnttfile,
self.info.convert, self.info.npixels_per_sample, 0, tod.T, pmatrix)
if status != 0: raise RuntimeError()
if unit is not None:
tod.unit = unit
return tod
def get_tod(self, unit=None):
"""
Method to get the Tod from this observation
"""
tod = Tod.empty((self.get_ndetectors(), np.sum(self.get_nsamples())))
sizeofpmatrix = self.info.npixels_per_sample * tod.size
pmatrix = np.zeros(sizeofpmatrix, dtype=int)
status = tmf.madmap1_read_tod(self.info.todfile, self.info.invnttfile,
self.info.convert,
self.info.npixels_per_sample, 0, tod.T,
pmatrix)
if status != 0: raise RuntimeError()
if unit is not None:
tod.unit = unit
return tod
def mapper_naive(tod, model, unit=None):
"""
Returns a naive map, i.e.: map = model.T(tod) / model.T(1)
This equation is valid for a map and a Time Ordered Data (TOD) expressed as
a surface brightness, so when the TOD does not meet this requirement and
is a quantity per detector, a unit conversion is attempted.
Parameters
----------
tod : Tod
The input Time Ordered Data
model : Operator
The instrument model such as tod = model(map)
unit : string
Output map unit. By default, the output map unit is chosen to be
compatible with the model (usually pixel^-1)
"""
# apply mask
if hasattr(tod, 'mask') and tod.mask is not None:
mask = MaskOperator(tod.mask)
else:
mask = IdentityOperator()
tod = mask(tod)
# get tod units
if not hasattr(tod, '_unit') or len(tod._unit) == 0:
attr = {'_unit': {'?': 1.}}
model.propagate_attributes(None, attr)
u = getattr(attr, '_unit', {})
if 'detector' in u and u['detector'] == -1:
u = {'detector': -1.}
elif u == {'?': 1.}:
u = {}
elif len(u) > 1:
raise ValueError(
'The timeline units are not known and cannot be in'
'ferred from the model.')
tod_du = getattr(attr, '_derived_units', {})
tod = Tod(tod.magnitude, unit=u, derived_units=tod_du, copy=False)
else:
attr = {'_unit': {'?': 1}}
model.T.propagate_attributes(None, attr)
u = attr['_unit']
if 'detector' not in tod._unit and 'detector' in u and u[
'detector'] == 1:
raise ValueError("The model is incompatible with input units '{0}'"\
.format(tod.unit))
tod_unit = tod._unit
tod_du = tod._derived_units
# make sure the input is a surface brightness
if 'detector' in tod._unit:
tod.inunit(tod.unit + ' detector / arcsec^2')
elif 'detector_reference' in tod._unit:
tod.inunit(tod.unit + ' detector_reference / arcsec^2')
# compute model.T(tod)/model.T(one)
mymap = model.T(tod.magnitude)
tod[...] = 1
mask(tod, tod)
map_weights = model.T(tod.magnitude)
old_settings = np.seterr(divide='ignore', invalid='ignore')
mymap /= map_weights
mymap.unit = tod.unit
np.seterr(**old_settings)
mymap.coverage = Map(map_weights.magnitude,
header=mymap.header,
copy=False)
if unit is not None:
mymap.inunit(unit)
return mymap
# set map units according to model
attr = {'_unit': tod_unit, '_derived_units': tod_du}
model.T.propagate_attributes(None, attr)
if '_derived_units' in attr:
mymap.derived_units = attr['_derived_units']
if '_unit' in attr:
mymap.inunit(attr['_unit'])
return mymap
tod = obs.get_tod(unit='Jy/beam')
projection = obs.get_projection_operator()
packing = PackOperator(obs.info.mapmask)
model = projection * packing
map_naive = mapper_naive(tod, model)
map_ref = pyfits.open(path + 'naivemapSpirePsw.fits')['image'].data
def test_madcap1():
assert all_eq(map_naive, map_ref)
map_naive_1d = mapper_naive(tod, projection)
map_naive_2d = packing.T(map_naive_1d)
map_naive_2d = packing.T(projection.T(tod) / projection.T(Tod.ones(tod.shape)))
map_naive_2d[obs.info.mapmask] = np.nan
def test_madcap2():
assert all_eq(map_naive_2d, map_ref)
M = DiagonalOperator(packing(1 / map_naive.coverage))
assert np.all(np.isfinite(M.data))
class Callback:
def __init__(self):
self.niterations = 0
def mapper_naive(tod, model, unit=None):
"""
Returns a naive map, i.e.: map = model.T(tod) / model.T(1)
This equation is valid for a map and a Time Ordered Data (TOD) expressed as
a surface brightness, so when the TOD does not meet this requirement and
is a quantity per detector, a unit conversion is attempted.
Parameters
----------
tod : Tod
The input Time Ordered Data
model : Operator
The instrument model such as tod = model(map)
unit : string
Output map unit. By default, the output map unit is chosen to be
compatible with the model (usually pixel^-1)
"""
# apply mask
if hasattr(tod, 'mask') and tod.mask is not None:
mask = MaskOperator(tod.mask)
else:
mask = IdentityOperator()
tod = mask(tod)
# get tod units
if not hasattr(tod, '_unit') or len(tod._unit) == 0:
attr = {'_unit' : {'?' : 1.}}
model.propagate_attributes(None, attr)
u = getattr(attr, '_unit', {})
if 'detector' in u and u['detector'] == -1:
u = {'detector' : -1.}
elif u == {'?':1.}:
u = {}
elif len(u) > 1:
raise ValueError('The timeline units are not known and cannot be in'
'ferred from the model.')
tod_du = getattr(attr, '_derived_units', {})
tod = Tod(tod.magnitude, unit=u, derived_units=tod_du, copy=False)
else:
attr = {'_unit' : {'?':1}}
model.T.propagate_attributes(None, attr)
u = attr['_unit']
if 'detector' not in tod._unit and 'detector' in u and u['detector']==1:
raise ValueError("The model is incompatible with input units '{0}'"\
.format(tod.unit))
tod_unit = tod._unit
tod_du = tod._derived_units
# make sure the input is a surface brightness
if 'detector' in tod._unit:
tod.inunit(tod.unit + ' detector / arcsec^2')
elif 'detector_reference' in tod._unit:
tod.inunit(tod.unit + ' detector_reference / arcsec^2')
# compute model.T(tod)/model.T(one)
mymap = model.T(tod.magnitude)
tod[...] = 1
mask(tod, tod)
map_weights = model.T(tod.magnitude)
old_settings = np.seterr(divide='ignore', invalid='ignore')
mymap /= map_weights
mymap.unit = tod.unit
np.seterr(**old_settings)
mymap.coverage = Map(map_weights.magnitude, header=mymap.header, copy=False)
if unit is not None:
mymap.inunit(unit)
return mymap
# set map units according to model
attr = {'_unit' : tod_unit, '_derived_units' : tod_du}
model.T.propagate_attributes(None, attr)
if '_derived_units' in attr:
mymap.derived_units = attr['_derived_units']
if '_unit' in attr:
mymap.inunit(attr['_unit'])
return mymap
obs.instrument.name = 'SPIRE/PSW'
tod = obs.get_tod(unit='Jy/beam')
projection = obs.get_projection_operator()
packing = PackOperator(obs.info.mapmask)
model = projection*packing
map_naive = mapper_naive(tod, model)
map_ref = pyfits.open(path+'naivemapSpirePsw.fits')['image'].data
def test_madcap1():
assert all_eq(map_naive, map_ref)
map_naive_1d = mapper_naive(tod, projection)
map_naive_2d = packing.T(map_naive_1d)
map_naive_2d = packing.T(projection.T(tod)/projection.T(Tod.ones(tod.shape)))
map_naive_2d[obs.info.mapmask] = np.nan
def test_madcap2():
assert all_eq(map_naive_2d, map_ref)
M = DiagonalOperator(packing(1/map_naive.coverage))
assert np.all(np.isfinite(M.data))
class Callback:
def __init__(self):
self.niterations = 0
def __call__(self, x):
self.niterations += 1
callback = Callback()
#callback = None
def teardown():
for file in glob.glob(filename + '*'):
os.remove(file)
a = np.ones((4, 3))
a[1, 2] = 4
q = Quantity(a, unit='myunit', derived_units={'myunit': Quantity(2., 'Jy')})
header = create_fitsheader(fromdata=q, cdelt=0.5, crval=(4., 8.))
header['BUNIT'] = 'myunit'
f = FitsArray(q, header=header)
m = Map(f, origin='upper', error=a * 2, coverage=a * 3)
mask = np.zeros((4, 3), np.bool8)
mask[0, 2] = True
t = Tod(f, mask=mask)
del mask
def test_copy_false_subok_true():
def func(obj1, t):
obj2 = t(obj1, copy=False, subok=True)
if isinstance(obj, t):
assert obj1 is obj2
else:
assert obj1 is not obj2
assert_equal(obj1, obj2)
for obj in [q, f, m, t]:
for ty in types:
yield func, obj, ty
