def test_gridding(self):
"""Test building a image from a visibility data set."""
for filename, type in zip((idiFile, idiAltFile, uvFile),
('FITS-IDI', 'Alt. FITS-IDI', 'UVFITS')):
with self.subTest(filetype=type):
# Open the file
idi = utils.CorrelatedData(filename)
# Build the image
ds = idi.get_data_set(1)
junk = utils.build_gridded_image(ds, verbose=False)
# Error checking
self.assertRaises(RuntimeError,
utils.build_gridded_image,
ds,
pol='XY')
#
# VisibilityData test
#
ds2 = VisibilityData()
ds2.append(ds)
junk = utils.build_gridded_image(ds, verbose=False)
idi.close()
def __init__(self, ref_time=0.0, verbose=False):
"""
Initialize a new virtual writer object using a reference time given in
seconds since the UNIX 1970 ephem, a python datetime object, or a
string in the format of 'YYYY-MM-DDTHH:MM:SS'.
"""
WriterBase.__init__(self, '', ref_time=ref_time, verbose=verbose)
self.visibility_data = VisibilityData()
def test_add_noise(self):
"""Test that we can add baseline noise to a data dictionary without
error"""
# Setup
lwa1 = lwa_common.lwa1
antennas = lwa1.antennas[0:20]
freqs = numpy.arange(30e6, 50e6, 1e6)
aa = vis.build_sim_array(lwa1, antennas, freqs)
# Build the data dictionary
out = vis.build_sim_data(aa, vis.SOURCES)
# Add in the noise
na = vis.add_baseline_noise(out, 15e3, 0.061)
#
# Single-channel test
#
# Setup
lwa1 = lwa_common.lwa1
antennas = lwa1.antennas[0:20]
freqs = numpy.array([
30e6,
])
aa = vis.build_sim_array(lwa1, antennas, freqs)
# Build the data dictionary
out = vis.build_sim_data(aa, vis.SOURCES)
# Add in the noise
na = vis.add_baseline_noise(out, 15e3, 0.061, bandwidth=1e6)
#
# VisibilityData test
#
# Setup
lwa1 = lwa_common.lwa1
antennas = lwa1.antennas[0:20]
freqs = numpy.arange(30e6, 50e6, 1e6)
aa = vis.build_sim_array(lwa1, antennas, freqs)
# Build the data dictionary
out = vis.build_sim_data(aa, vis.SOURCES)
out2 = VisibilityData()
out2.append(out)
# Add in the noise
na2 = vis.add_baseline_noise(out2, 15e3, 0.061)
def test_shift_data(self):
"""Test that we can shift the uvw coordinates of a data dictionary
without error"""
# Setup
lwa1 = lwa_common.lwa1
antennas = lwa1.antennas[0:20]
freqs = numpy.arange(30e6, 50e6, 1e6)
aa = vis.build_sim_array(lwa1, antennas, freqs)
# Build the data dictionary
out = vis.build_sim_data(aa, vis.SOURCES)
# Shift
sft = vis.shift_data(out, aa)
#
# Single-channel test
#
# Setup
lwa1 = lwa_common.lwa1
antennas = lwa1.antennas[0:20]
freqs = numpy.array([
30e6,
])
aa = vis.build_sim_array(lwa1, antennas, freqs)
# Build the data dictionary
out = vis.build_sim_data(aa, vis.SOURCES)
# Shift
sft = vis.shift_data(out, aa)
#
# VisibilityData test
#
# Setup
lwa1 = lwa_common.lwa1
antennas = lwa1.antennas[0:20]
freqs = numpy.arange(30e6, 50e6, 1e6)
aa = vis.build_sim_array(lwa1, antennas, freqs)
# Build the data dictionary
out = vis.build_sim_data(aa, vis.SOURCES)
out2 = VisibilityData()
out2.append(out)
# Shift
sft2 = vis.shift_data(out2, aa)
def get_data_set(self,
sets,
include_auto=False,
sort=True,
min_uv=0,
max_uv=numpy.inf):
"""
Return a :class:`lsl.imaging.data.VisibilityDataSet` or
:class:`lsl.imaging.data.VisibilityData` object for all
baselines for a given set of observations for the specified data set.
By default this excludes the autocorrelations. To include
autocorrelations set the value of 'include_auto' to True. Setting the
'sort' keyword to False will disable the baseline sorting. Optionally,
baselines with lengths between min_uv and max_uv can only be returned.
.. note::
min_uv and max_uv should be specified in lambda
"""
dataSets = VisibilityData()
try:
len(sets)
except TypeError:
sets = range(sets, sets + 1)
for set in sets:
dataSets.append(self.visibility_data[set - 1])
# Sort
if sort:
dataSets.sort()
# Prune
if not include_auto and min_uv == 0:
min_uv = 1e-3
if min_uv != 0 or max_uv != numpy.inf:
dataSets = dataSets.get_uv_range(min_uv=min_uv, max_uv=max_uv)
# Prune a different way
if len(dataSets) == 1:
dataSets = dataSets.pop()
# Return
return dataSets
def build_sim_data(aa,
srcs,
pols=['xx', 'yy', 'xy', 'yx'],
jd=None,
chan=None,
phase_center='z',
baselines=None,
mask=None,
flat_response=False,
resolve_src=False,
verbose=False):
"""
Given an AIPY AntennaArray object and a dictionary of sources from
aipy.src.get_catalog, returned a :class:`lsl.imaging.data.VisibilityDataSet`
object of simulated data taken at zenith. Optinally, the data can be
masked using some referenced (observed) data set or only a specific sub-set
of baselines.
.. versionchanged:: 1.0.1
* Added a 'flat_response' keyword to make it easy to toggle on and off
the spectral and spatial response of the array for the simulation
* Added a 'resolve_src' keyword to turn on source resolution effects
..versionchanged:: 0.4.0
Added the 'pols' keyword to only compute certain polarization components
"""
# Update the JD if necessary
if jd is None:
jd = [aa.get_jultime()]
else:
try:
len(jd)
except TypeError:
jd = [jd]
# Build up output dictionary
freq = aa.get_afreqs() * 1e9
if len(freq.shape) == 2:
freq = freq[0, :]
UVData = VisibilityData()
# Loop over Julian days to fill in the simulated data set
jdCounter = 1
for juldate in jd:
oBlk = __build_sim_data(aa,
srcs,
pols=pols,
jd=juldate,
chan=chan,
phase_center=phase_center,
baselines=baselines,
mask=mask,
verbose=verbose,
count=jdCounter,
max=len(jd),
flat_response=flat_response,
resolve_src=resolve_src)
jdCounter = jdCounter + 1
UVData.append(oBlk)
# Trim
if len(UVData) == 1:
UVData = UVData.pop()
return UVData
def test_scale_data(self):
"""Test that we can scale a data dictionary without error"""
# Setup
lwa1 = lwa_common.lwa1
antennas = lwa1.antennas[0:20]
freqs = numpy.arange(30e6, 50e6, 1e6)
aa = vis.build_sim_array(lwa1, antennas, freqs)
# Build the data dictionary
out = vis.build_sim_data(aa, vis.SOURCES)
# Scale
amp = vis.scale_data(out,
numpy.ones(len(antennas)) * 2,
numpy.zeros(len(antennas)))
# Delay
phs = vis.scale_data(out, numpy.ones(len(antennas)),
numpy.ones(len(antennas)))
#
# Single-channel test
#
# Setup
lwa1 = lwa_common.lwa1
antennas = lwa1.antennas[0:20]
freqs = numpy.array([
30e6,
])
aa = vis.build_sim_array(lwa1, antennas, freqs)
# Build the data dictionary
out = vis.build_sim_data(aa, vis.SOURCES)
# Scale
amp = vis.scale_data(out,
numpy.ones(len(antennas)) * 2,
numpy.zeros(len(antennas)))
# Delay
phs = vis.scale_data(out, numpy.ones(len(antennas)),
numpy.ones(len(antennas)))
#
# VisibilityData test
#
# Setup
lwa1 = lwa_common.lwa1
antennas = lwa1.antennas[0:20]
freqs = numpy.arange(30e6, 50e6, 1e6)
aa = vis.build_sim_array(lwa1, antennas, freqs)
# Build the data dictionary
out = vis.build_sim_data(aa, vis.SOURCES)
out2 = VisibilityData(out)
# Scale
amp2 = vis.scale_data(out2,
numpy.ones(len(antennas)) * 2,
numpy.zeros(len(antennas)))
# Delay
phs2 = vis.scale_data(out2, numpy.ones(len(antennas)),
numpy.ones(len(antennas)))