def test_make_map(self):
params = Struct(map_maker="seek.mapmaking.healpy_mapper",
nside=2,
variance=False)
npix = hp.nside2npix(params.nside)
ind = 1
theta, phi = hp.pix2ang(params.nside, ind)
dec = np.pi * .5 - theta
ra = phi
times = np.array([[0, 0, 0, ra, dec], [0, 0, 0, ra, dec]])
rfi_mask = np.array([[False, False]], dtype=bool)
tod_vx = np.ma.array([[1., 2.]], mask=rfi_mask)
tod_vy = np.ma.array([[2., 4.]], mask=rfi_mask)
frequencies = np.array([1420.40575177])
ctx = Struct(params=params,
frequencies=frequencies,
times=times,
tod_vx=tod_vx,
tod_vy=tod_vy,
coords=Coords(times[:, -2], times[:, -1], None, None,
None))
plugin = make_maps.Plugin(ctx)
plugin()
assert len(ctx.map_idxs) == 3
assert ctx.maps[0] == tod_vx.sum()
assert ctx.maps[1] == tod_vy.sum()
assert ctx.counts[0] == tod_vx.shape[1]
assert ctx.counts[1] == tod_vy.shape[1]
def __call__(self):
if self.ctx.tod_vx.shape[0] > 0:
date = self.ctx.strategy_start
coord_path = self.ctx.coords_paths[format_date(date)]
coords = np.genfromtxt(coord_path, delimiter = ',', names = True)
time_axis = self.ctx.time_axis
azs = np.radians(np.interp(time_axis, coords['Time'], coords['AzAntenna']))
els = np.radians(np.interp(time_axis, coords['Time'], coords['ElAntenna']))
obs = sphere.get_observer(self.ctx.params)
strategy = convert_coords(date, time_axis, azs, els,obs)
self.ctx.coords = Coords(strategy[:, 0], strategy[:, 1], azs, els, time_axis)
else:
self.ctx.coords = Coords([], [], [], [], [])
def test_sun_masking(self):
tod = np.ma.array(np.random.uniform(size=(10,100)),
mask=False)
coords = Coords([4.14857973] * tod.shape[1], [-0.51101287] * tod.shape[1], [0.0] * tod.shape[1], [0.0] * tod.shape[1], [0.0] * tod.shape[1])
ctx = Struct(params=self.params,
tod_vx = tod,
tod_vy = tod,
coords = coords,
strategy_start=datetime(2014, 11, 25, 11, 00, 00))
plugin = mask_objects.Plugin(ctx)
plugin.mask_objects()
assert np.any(tod.mask == True)
def test_no_moon_sun_masking(self):
tod = np.ma.array(np.random.uniform(size=(10,100)),
mask=False)
times = np.zeros((tod.shape[1], 5))
ctx = Struct(params=self.params,
tod_vx = tod,
tod_vy = tod,
coords = Coords(times[:,0], times[:,1], times[:,1]*0.0, times[:,1]*0.0, times[:,1]*0.0),
strategy_start=datetime(2015, 01, 01, 00, 00, 00))
plugin = mask_objects.Plugin(ctx)
plugin.mask_objects()
assert np.all(tod.mask == False)
def test_moon_masking(self):
tod = np.ma.array(np.random.uniform(size=(10, 100)), mask=False)
ras = np.linspace(1.5, 2.5, tod.shape[1])
decs = [0.26] * tod.shape[1]
times = np.linspace(0, 4, tod.shape[1])
coords = Coords(ras, decs, None, None, times)
ctx = Struct(params=self.params,
tod_vx=tod,
tod_vy=tod,
coords=coords,
strategy_start=datetime(2015, 12, 26, 00, 00, 00))
plugin = mask_objects.Plugin(ctx)
plugin.mask_objects()
assert np.any(tod.mask == True)
def __call__(self):
filename = os.path.basename(self.ctx.file_paths[0])
filepath = os.path.join(self.ctx.params.post_processing_prefix,
filename)
if self.ctx.params.verbose:
print(filepath)
self.ctx.strategy_start = load_data.get_observation_start_from_hdf5(
filepath)
with h5py.File(filepath, "r") as fp:
tod = np.ma.array(fp["data"].value, mask=fp["mask"].value)
self.ctx.tod_vx = tod
self.ctx.tod_vy = tod.copy()
self.ctx.frequencies = fp["frequencies"].value
self.ctx.time_axis = fp["time"].value
self.ctx.coords = Coords(fp["ra"].value, fp["dec"].value, None,
None, self.ctx.time_axis)
self.ctx.ref_channel = fp["ref_channel"].value
def test_bkg_removal_smooth(self):
tod = np.ones((5, 9)) * np.arange(9)
mask = np.zeros((5, 9))
mask[:, 0] = 1
mask[:, -1] = 1
mask = mask.astype('bool')
ctx = Struct(params=Struct(background_model="smooth",
struct_size_0=1,
struct_size_1=1,
nside=1),
tod_vx=np.ma.array(tod, mask=mask),
tod_vy=np.ma.array(tod, mask=mask),
time_axis=np.arange(9),
coords=Coords(np.zeros(9), np.zeros(9), None, None, None),
simulation_mask=np.zeros(9, dtype=np.bool))
plugin = background_removal.Plugin(ctx)
plugin()
assert np.all(ctx.tod_vx.sum(axis=1) == 0)
assert np.all(ctx.tod_vy.sum(axis=1) == 0)
def test_get_map(self):
params = Struct(nside=2, variance=False)
npix = hp.nside2npix(params.nside)
ind = 1
theta, phi = hp.pix2ang(params.nside, ind)
dec = np.pi * .5 - theta
ra = phi
times = np.array([[0,0,0,ra,dec],[0,0,0,ra,dec]])
rfi_mask = np.array([[False, False]], dtype = bool)
tod_vx = np.ma.array([[1., 2.]], mask=rfi_mask)
tod_vy = np.ma.array([[2., 4.]], mask=rfi_mask)
frequencies = np.array([1420.40575177])
ctx = Struct(params = params,
frequencies = frequencies,
times = times,
tod_vx = tod_vx,
tod_vy = tod_vy,
coords = Coords(times[:,-2], times[:,-1], None, None, None)
)
maps, z, counts = healpy_mapper.get_map(ctx)
t = np.zeros((1, 2, npix))
t[0, 0, 1] = 3.
t[0, 1, 1] = 6.
assert np.allclose(maps, t)
t[0, 0, 1] = 2
t[0, 1, 1] = 2
assert np.allclose(counts, t)
assert np.isclose(z, 0)
ctx.params.variance = True
maps, z, counts = healpy_mapper.get_map(ctx)
t[0, 0, 1] = .5
t[0, 1, 1] = 2.
assert np.allclose(maps, t)