def plot_azel(bvis_list, plot_file=None, **kwargs):
""" Standard plot of az el coverage
:param bvis_list:
:param plot_file:
:param kwargs:
:return:
"""
plt.clf()
r2d = 180.0 / numpy.pi
for ibvis, bvis in enumerate(bvis_list):
ha = calculate_blockvisibility_hourangles(bvis).value
az, el = calculate_blockvisibility_azel(bvis)
if ibvis == 0:
plt.plot(ha, az.deg, '.', color='r', label='Azimuth (deg)')
plt.plot(ha, el.deg, '.', color='b', label='Elevation (deg)')
else:
plt.plot(ha, az.deg, '.', color='r')
plt.plot(ha, el.deg, '.', color='b')
plt.xlabel('HA (hours)')
plt.ylabel('Angle')
plt.legend()
plt.title('Azimuth and elevation vs hour angle')
if plot_file is not None:
plt.savefig(plot_file)
plt.show(block=False)
def plot_pa(bvis_list, plot_file=None, **kwargs):
""" Standard plot of parallactic angle coverage
:param bvis_list:
:param plot_file:
:param kwargs:
:return:
"""
plt.clf()
for ibvis, bvis in enumerate(bvis_list):
ha = calculate_blockvisibility_hourangles(bvis).value
pa = calculate_blockvisibility_parallactic_angles(bvis)
if ibvis == 0:
plt.plot(ha, pa.deg, '.', color='r', label='PA (deg)')
else:
plt.plot(ha, pa.deg, '.', color='r')
plt.xlabel('HA (hours)')
plt.ylabel('Parallactic Angle')
plt.legend()
plt.title('Parallactic angle vs hour angle')
if plot_file is not None:
plt.savefig(plot_file)
plt.show(block=False)
def test_hourangle(self):
ha = calculate_blockvisibility_hourangles(self.bvis)
numpy.testing.assert_array_almost_equal(ha[0].deg, -88.487126)
def create_gaintable_from_screen(vis,
sc,
screen,
height=3e5,
vis_slices=None,
scale=1.0,
r0=5e3,
type_atmosphere='ionosphere',
**kwargs):
""" Create gaintables from a screen calculated using ARatmospy
Screen axes are ['XX', 'YY', 'TIME', 'FREQ']
:param vis:
:param sc: Sky components for which pierce points are needed
:param screen:
:param height: Height (in m) of screen above telescope e.g. 3e5
:param r0: r0 in meters
:param type_atmosphere: 'ionosphere' or 'troposphere'
:param scale: Multiply the screen by this factor
:return:
"""
assert isinstance(vis, BlockVisibility)
station_locations = vis.configuration.xyz
scale = numpy.power(r0 / 5000.0, -5.0 / 3.0)
if type_atmosphere == 'troposphere':
# In troposphere files, the units are phase in radians.
screen_to_phase = scale
else:
# In the ionosphere file, the units are dTEC.
screen_to_phase = -scale * 8.44797245e9 / numpy.array(vis.frequency)
nant = station_locations.shape[0]
t2r = numpy.pi / 43200.0
gaintables = [
create_gaintable_from_blockvisibility(vis, **kwargs) for i in sc
]
number_bad = 0
number_good = 0
ha_zero = numpy.average(calculate_blockvisibility_hourangles(vis))
for iha, rows in enumerate(vis_timeslice_iter(vis, vis_slices=vis_slices)):
v = create_visibility_from_rows(vis, rows)
ha = numpy.average(calculate_blockvisibility_hourangles(v) -
ha_zero).to('rad').value
for icomp, comp in enumerate(sc):
pp = find_pierce_points(station_locations,
(comp.direction.ra.rad + t2r * ha) *
units.rad,
comp.direction.dec,
height=height,
phasecentre=vis.phasecentre)
scr = numpy.zeros([nant])
for ant in range(nant):
pp0 = pp[ant][0:2]
# Using narrow band approach - we should loop over frequency
try:
worldloc = [
pp0[0], pp0[1], ha,
numpy.average(vis.frequency)
]
pixloc = screen.wcs.wcs_world2pix([worldloc],
0)[0].astype('int')
if type_atmosphere == 'troposphere':
pixloc[3] = 0
scr[ant] = screen_to_phase * screen.data[
pixloc[3], pixloc[2], pixloc[1], pixloc[0]]
number_good += 1
except (ValueError, IndexError):
number_bad += 1
scr[ant] = 0.0
# axes of gaintable.gain are time, ant, nchan, nrec
gaintables[icomp].gain[iha, :, :, :] = numpy.exp(
1j * scr)[..., numpy.newaxis, numpy.newaxis, numpy.newaxis]
gaintables[icomp].phasecentre = comp.direction
assert number_good > 0, "create_gaintable_from_screen: There are no pierce points inside the atmospheric screen image"
if number_bad > 0:
log.warning(
"create_gaintable_from_screen: %d pierce points are inside the atmospheric screen image"
% (number_good))
log.warning(
"create_gaintable_from_screen: %d pierce points are outside the atmospheric screen image"
% (number_bad))
return gaintables
def grid_gaintable_to_screen(vis,
gaintables,
screen,
height=3e5,
gaintable_slices=None,
scale=1.0,
r0=5e3,
type_atmosphere='ionosphere',
vis_slices=None,
**kwargs):
""" Grid a gaintable to a screen image
Screen axes are ['XX', 'YY', 'TIME', 'FREQ']
The phases are just averaged per grid cell, no phase unwrapping is performed.
:param vis:
:param gaintables: input gaintables
:param screen:
:param height: Height (in m) of screen above telescope e.g. 3e5
:param r0: r0 in meters
:param type_atmosphere: 'ionosphere' or 'troposphere'
:param scale: Multiply the screen by this factor
:return: gridded screen image, weights image
"""
assert isinstance(vis, BlockVisibility)
station_locations = vis.configuration.xyz
nant = station_locations.shape[0]
t2r = numpy.pi / 43200.0
newscreen = create_empty_image_like(screen)
weights = create_empty_image_like(screen)
nchan, ntimes, ny, nx = screen.shape
number_no_weight = 0
for gaintable in gaintables:
ha_zero = numpy.average(calculate_blockvisibility_hourangles(vis))
for iha, rows in enumerate(
vis_timeslice_iter(vis, vis_slices=vis_slices)):
v = create_visibility_from_rows(vis, rows)
ha = numpy.average(
calculate_blockvisibility_hourangles(v) -
ha_zero).to('rad').value
pp = find_pierce_points(station_locations,
(gaintable.phasecentre.ra.rad + t2r * ha) *
units.rad,
gaintable.phasecentre.dec,
height=height,
phasecentre=vis.phasecentre)
scr = numpy.angle(gaintable.gain[0, :, 0, 0, 0])
wt = gaintable.weight[0, :, 0, 0, 0]
for ant in range(nant):
pp0 = pp[ant][0:2]
for freq in vis.frequency:
scale = numpy.power(r0 / 5000.0, -5.0 / 3.0)
if type_atmosphere == 'troposphere':
# In troposphere files, the units are phase in radians.
screen_to_phase = scale
else:
# In the ionosphere file, the units are dTEC.
screen_to_phase = -scale * 8.44797245e9 / freq
worldloc = [pp0[0], pp0[1], ha, freq]
pixloc = newscreen.wcs.wcs_world2pix([worldloc],
0)[0].astype('int')
assert pixloc[0] >= 0
assert pixloc[0] < nx
assert pixloc[1] >= 0
assert pixloc[1] < ny
pixloc[3] = 0
newscreen.data[
pixloc[3], pixloc[2], pixloc[1],
pixloc[0]] += wt[ant] * scr[ant] / screen_to_phase
weights.data[pixloc[3], pixloc[2], pixloc[1],
pixloc[0]] += wt[ant]
if wt[ant] == 0.0:
number_no_weight += 1
if number_no_weight > 0:
log.warning(
"grid_gaintable_to_screen: %d pierce points are have no weight" %
(number_no_weight))
assert numpy.max(weights.data) > 0.0, "No points were gridded"
newscreen.data[weights.data > 0.0] = newscreen.data[
weights.data > 0.0] / weights.data[weights.data > 0.0]
return newscreen, weights
def simulate_gaintable_from_zernikes(vis,
sc,
vp_list,
vp_coeffs,
vis_slices=None,
order=3,
use_radec=False,
elevation_limit=15.0 * numpy.pi / 180.0,
**kwargs):
""" Create gaintables for a set of zernikes
:param vis:
:param sc: Sky components for which pierce points are needed
:param vp: List of Voltage patterns in AZELGEO frame
:param vp_coeffs: Fractional contribution [nants, nvp]
:param order: order of spline (default is 3)
:return:
"""
ntimes, nant = vis.vis.shape[0:2]
vp_coeffs = numpy.array(vp_coeffs)
gaintables = [
create_gaintable_from_blockvisibility(vis, **kwargs) for i in sc
]
if not use_radec:
assert isinstance(vis, BlockVisibility)
assert vis.configuration.mount[
0] == 'azel', "Mount %s not supported yet" % vis.configuration.mount[
0]
# The time in the Visibility is hour angle in seconds!
number_bad = 0
number_good = 0
# Cache the splines, one per voltage pattern
real_splines = list()
imag_splines = list()
for ivp, vp in enumerate(vp_list):
assert vp.wcs.wcs.ctype[0] == 'AZELGEO long', vp.wcs.wcs.ctype[0]
assert vp.wcs.wcs.ctype[1] == 'AZELGEO lati', vp.wcs.wcs.ctype[1]
nchan, npol, ny, nx = vp.data.shape
real_splines.append(
RectBivariateSpline(range(ny),
range(nx),
vp.data[0, 0, ...].real,
kx=order,
ky=order))
imag_splines.append(
RectBivariateSpline(range(ny),
range(nx),
vp.data[0, 0, ...].imag,
kx=order,
ky=order))
latitude = vis.configuration.location.lat.rad
r2d = 180.0 / numpy.pi
s2r = numpy.pi / 43200.0
# For each hourangle, we need to calculate the location of a component
# in AZELGEO. With that we can then look up the relevant gain from the
# voltage pattern
for iha, rows in enumerate(
vis_timeslice_iter(vis, vis_slices=vis_slices)):
v = create_visibility_from_rows(vis, rows)
ha = numpy.average(
calculate_blockvisibility_hourangles(v).to('rad').value)
# Calculate the az el for this hourangle and the phasecentre declination
utc_time = Time([numpy.average(v.time) / 86400.0],
format='mjd',
scale='utc')
azimuth_centre, elevation_centre = calculate_azel(
v.configuration.location, utc_time, vis.phasecentre)
azimuth_centre = azimuth_centre[0].to('deg').value
elevation_centre = elevation_centre[0].to('deg').value
for icomp, comp in enumerate(sc):
if elevation_centre >= elevation_limit:
antgain = numpy.zeros([nant], dtype='complex')
# Calculate the location of the component in AZELGEO, then add the pointing offset
# for each antenna
hacomp = comp.direction.ra.rad - vis.phasecentre.ra.rad + ha
deccomp = comp.direction.dec.rad
azimuth_comp, elevation_comp = hadec_to_azel(
hacomp, deccomp, latitude)
for ant in range(nant):
for ivp, vp in enumerate(vp_list):
nchan, npol, ny, nx = vp.data.shape
wcs_azel = vp.wcs.deepcopy()
# We use WCS sensible coordinate handling by labelling the axes misleadingly
wcs_azel.wcs.crval[0] = azimuth_centre
wcs_azel.wcs.crval[1] = elevation_centre
wcs_azel.wcs.ctype[0] = 'RA---SIN'
wcs_azel.wcs.ctype[1] = 'DEC--SIN'
worldloc = [
azimuth_comp * r2d, elevation_comp * r2d,
vp.wcs.wcs.crval[2], vp.wcs.wcs.crval[3]
]
try:
pixloc = wcs_azel.sub(2).wcs_world2pix(
[worldloc[:2]], 1)[0]
assert pixloc[0] > 2
assert pixloc[0] < nx - 3
assert pixloc[1] > 2
assert pixloc[1] < ny - 3
gain = real_splines[ivp].ev(pixloc[1], pixloc[0]) \
+ 1j * imag_splines[ivp](pixloc[1], pixloc[0])
antgain[ant] += vp_coeffs[ant, ivp] * gain
number_good += 1
except (ValueError, AssertionError):
number_bad += 1
antgain[ant] = 1.0
antgain[ant] = 1.0 / antgain[ant]
gaintables[icomp].gain[
iha, :, :, :] = antgain[:, numpy.newaxis,
numpy.newaxis, numpy.newaxis]
gaintables[icomp].phasecentre = comp.direction
else:
gaintables[icomp].gain[...] = 1.0 + 0.0j
gaintables[icomp].phasecentre = comp.direction
number_bad += nant
else:
assert isinstance(vis, BlockVisibility)
number_bad = 0
number_good = 0
# Cache the splines, one per voltage pattern
real_splines = list()
imag_splines = list()
for ivp, vp in enumerate(vp_list):
nchan, npol, ny, nx = vp.data.shape
real_splines.append(
RectBivariateSpline(range(ny),
range(nx),
vp.data[0, 0, ...].real,
kx=order,
ky=order))
imag_splines.append(
RectBivariateSpline(range(ny),
range(nx),
vp.data[0, 0, ...].imag,
kx=order,
ky=order))
for iha, rows in enumerate(
vis_timeslice_iter(vis, vis_slices=vis_slices)):
# The time in the Visibility is hour angle in seconds!
r2d = 180.0 / numpy.pi
# For each hourangle, we need to calculate the location of a component
# in AZELGEO. With that we can then look up the relevant gain from the
# voltage pattern
v = create_visibility_from_rows(vis, rows)
ha = numpy.average(calculate_blockvisibility_hourangles(v))
for icomp, comp in enumerate(sc):
antgain = numpy.zeros([nant], dtype='complex')
antwt = numpy.zeros([nant])
ra_comp = comp.direction.ra.rad
dec_comp = comp.direction.dec.rad
for ant in range(nant):
for ivp, vp in enumerate(vp_list):
assert vp.wcs.wcs.ctype[
0] == 'RA---SIN', vp.wcs.wcs.ctype[0]
assert vp.wcs.wcs.ctype[
1] == 'DEC--SIN', vp.wcs.wcs.ctype[1]
worldloc = [
ra_comp * r2d, dec_comp * r2d, vp.wcs.wcs.crval[2],
vp.wcs.wcs.crval[3]
]
nchan, npol, ny, nx = vp.data.shape
try:
pixloc = vp.wcs.sub(2).wcs_world2pix(
[worldloc[:2]], 1)[0]
assert pixloc[0] > 2
assert pixloc[0] < nx - 3
assert pixloc[1] > 2
assert pixloc[1] < ny - 3
gain = real_splines[ivp].ev(pixloc[1], pixloc[0]) \
+ 1j * imag_splines[ivp](pixloc[1], pixloc[0])
antgain[ant] += vp_coeffs[ant, ivp] * gain
antwt[ant] = 1.0
number_good += 1
except (ValueError, AssertionError):
number_bad += 1
antgain[ant] = 1e15
antwt[ant] = 0.0
antgain[ant] = 1.0 / antgain[ant]
gaintables[icomp].gain[
iha, :, :, :] = antgain[:, numpy.newaxis,
numpy.newaxis, numpy.newaxis]
gaintables[icomp].weight[
iha, :, :, :] = antwt[:, numpy.newaxis, numpy.newaxis,
numpy.newaxis]
gaintables[icomp].phasecentre = comp.direction
if number_bad > 0:
log.warning(
"simulate_gaintable_from_zernikes: %d points are inside the voltage pattern image"
% (number_good))
log.warning(
"simulate_gaintable_from_zernikes: %d points are outside the voltage pattern image"
% (number_bad))
return gaintables