def select(self, **kwargs):
""" Select data from the BST observation file.
:param freqrange:
Frequency range (see :attr:`BST_Data.freqrange`).
:type freqrange: `float`, `list`, :class:`numpy.ndarray`
or :class:`astropy.units.Quantity`, optional
:param timerange:
Time range (see :attr:`BST_Data.timerange`).
:type timerange: `str`, `list`, :class:`numpy.ndarray` or :class:`astropy.time.Time`
:param dbeam:
Digital beam index (see :attr:`BST_Data.dbeam`)
:type dbeam: `int`, optional
:param polar:
Polarization (see :attr:`BST_Data.polar`)
:type polar: `str`, optional
:returns: Selected data
:rtype: :class:`nenupy.beamlet.sdata.SData`
"""
self._fill_attr(kwargs)
data = self.data[np.ix_(self._time_idx, self._polar_idx,
self._freq_idx)]
return SData(data=np.swapaxes(data, 1, 2),
time=self.time,
freq=self.freq,
polar=self.polar)
def test_sdata_div():
dts = TimeDelta(np.arange(2), format='sec')
s1 = SData(
data=np.ones((2, 3, 1)),
time=Time('2020-04-01 12:00:00') + dts,
freq=np.arange(3) * u.MHz,
polar=['NE']
)
s2 = SData(
data=np.ones((2, 3, 1)),
time=Time('2020-04-01 12:00:00') + dts,
freq=np.arange(3) * u.MHz,
polar=['NE']
)
s = s1 / s2
assert isinstance(s, SData)
assert (s.data == 1.).all()
s = s1 / 2
(s.data == 0.5).all()
def test_sdata_def_error():
dts = TimeDelta(np.arange(2), format='sec')
with pytest.raises(AssertionError):
# Time shape error
s = SData(
data=np.ones((3, 3, 1)),
time=Time('2020-04-01 12:00:00') + dts,
freq=np.arange(3) * u.MHz,
polar=['NE']
)
with pytest.raises(AssertionError):
# Freq shape error
s = SData(
data=np.ones((2, 4, 1)),
time=Time('2020-04-01 12:00:00') + dts,
freq=np.arange(3) * u.MHz,
polar=['NE']
)
with pytest.raises(AssertionError):
# Polar shape error
s = SData(
data=np.ones((2, 3, 2)),
time=Time('2020-04-01 12:00:00') + dts,
freq=np.arange(3) * u.MHz,
polar=['NE']
)
with pytest.raises(TypeError):
# Time type error
s = SData(
data=np.ones((2, 3, 1)),
time=np.arange(2),
freq=np.arange(3) * u.MHz,
polar=['NE']
)
with pytest.raises(TypeError):
# Freq type error
s = SData(
data=np.ones((2, 3, 1)),
time=Time('2020-04-01 12:00:00') + dts,
freq=np.arange(3),
polar=['NE']
)
def test_sdata_concat_f():
dts = TimeDelta(np.arange(2), format='sec')
s1 = SData(
data=np.ones((2, 3, 1)),
time=Time('2020-04-01 12:00:00') + dts,
freq=np.arange(3) * u.MHz,
polar=['NE']
)
with pytest.raises(TypeError):
s = s1 & 'other'
with pytest.raises(ValueError):
s2 = SData(
data=np.ones((2, 3, 1)),
time=Time('2020-04-01 12:00:00') + dts,
freq=(1 + np.arange(3)) * u.MHz,
polar=['NW']
)
# Different polars
s = s1 & s2
with pytest.raises(ValueError):
s2 = SData(
data=np.ones((2, 3, 1)),
time=Time('2020-04-01 13:00:00') + dts,
freq=(1 + np.arange(3)) * u.MHz,
polar=['NE']
)
# Different times
s = s1 & s2
s2 = SData(
data=np.ones((2, 3, 1)),
time=Time('2020-04-01 12:00:00') + dts,
freq=(1 + np.arange(3)) * u.MHz,
polar=['NE']
)
s = s1 & s2
assert s.data.shape == (2, 6, 1)
def test_sdata_attr():
dts = TimeDelta(np.arange(2), format='sec')
s1 = SData(
data=np.ones((2, 3, 1)),
time=Time('2020-04-01 12:00:00') + dts,
freq=np.arange(3) * u.MHz,
polar='NE'
)
assert s1.amp.shape == (2, 3)
assert (s1.amp == 1.).all()
assert s1.db.shape == (2, 3)
assert (s1.db == 0.).all()
assert s1.mjd.size == 2
testmjd = np.array([0.50000, 0.50001])
assert testmjd == pytest.approx(s1.mjd-58940, 1e-5)
assert s1.jd.size == 2
assert s1.datetime.size == 2
def time_profile(self, times, anadir, digdir=None, **kwargs):
"""
"""
amp_list = []
time_list = []
# Make sure kwargs is emptied from some keywords
for key in ['azana', 'elana', 'azdig', 'eldig']:
try:
del kwargs[key]
except KeyError:
pass
# Instanciate the SkyModel
if self.model == 'gsm':
smodel = HpxGSM(freq=self.freq, resolution=self.resolution)
elif self.model == 'lofar':
smodel = HpxLOFAR(freq=self.freq,
resolution=self.resolution,
smooth=False)
# Loop over times
for i, time in enumerate(tqdm(times)):
self._gain.beam(time=time,
azana=anadir[i].az.deg,
elana=anadir[i].alt.deg,
azdig=None if digdir is None else digdir[i].az,
eldig=None if digdir is None else digdir[i].alt,
freq=self.freq,
**kwargs)
# Rotate the HPX mask of the GSM
smodel.time = time
# Multiply and sum GMS and Beam
vmask = smodel._is_visible
gsmcut = smodel.skymap[vmask]
beamcut = self._gain.skymap[vmask]
amp_list.append(ne.evaluate('sum(gsmcut*beamcut)'))
time_list.append(time.mjd)
return SData(data=np.expand_dims(np.array(amp_list), axis=(1, 2)),
time=Time(time_list, format='mjd'),
freq=self.freq,
polar=self._gain.polar)
def test_sdata_plot(mock_show):
dts = TimeDelta(np.arange(2), format='sec')
s1 = SData(
data=np.ones((2, 3, 1)),
time=Time('2020-04-01 12:00:00') + dts,
freq=np.arange(3) * u.MHz,
polar=['NE']
)
# Default plot
s1.plot()
# Custom plot
s1.plot(
db=False,
cmap='Blues',
vmin=-0.1,
vmax=0.1,
title='test title',
cblabel='test cblabel',
figsize=(6, 6),
)
def test_sdata_add():
dts = TimeDelta(np.arange(2), format='sec')
s1 = SData(
data=np.ones((2, 3, 1)),
time=Time('2020-04-01 12:00:00') + dts,
freq=np.arange(3) * u.MHz,
polar=['NE']
)
s2 = SData(
data=np.ones((2, 3, 1)),
time=Time('2020-04-01 12:00:00') + dts,
freq=np.arange(3) * u.MHz,
polar=['NE']
)
s = s1 + s2
assert isinstance(s, SData)
assert (s.data == 2.).all()
s = s1 + 2
assert (s.data == 3.).all()
s = s1 + np.ones((2, 3, 1)) * 3
assert (s.data == 4.).all()
# Test operation errors
with pytest.raises(ValueError):
# Data not same shape
s3 = SData(
data=np.ones((2, 4, 1)),
time=Time('2020-04-01 12:00:00') + dts,
freq=np.arange(4) * u.MHz,
polar=['NE']
)
s = s1 + s3
with pytest.raises(ValueError):
# Polar not same
s3 = SData(
data=np.ones((2, 3, 1)),
time=Time('2020-04-01 12:00:00') + dts,
freq=np.arange(3) * u.MHz,
polar=['NW']
)
s = s1 + s3
with pytest.raises(ValueError):
# Time not same
s3 = SData(
data=np.ones((2, 3, 1)),
time=Time('2020-04-01 13:00:00') + dts,
freq=np.arange(3) * u.MHz,
polar=['NE']
)
s = s1 + s3
with pytest.raises(ValueError):
# Freq not same
s3 = SData(
data=np.ones((2, 3, 1)),
time=Time('2020-04-01 12:00:00') + dts,
freq=(np.arange(3)+1) * u.MHz,
polar=['NE']
)
s = s1 + s3
with pytest.raises(Exception):
s = s1 + 'wrong'
with pytest.raises(ValueError):
s = s1 + np.ones((1, 3, 1)) * 3
