def create_test_image(
canonical=True,
cellsize=None,
frequency=None,
channel_bandwidth=None,
phasecentre=None,
polarisation_frame=PolarisationFrame("stokesI")) -> Image:
"""Create a useful test image
This is the test image M31 widely used in ALMA and other simulations. It is actually part of an Halpha region in
M31.
:param canonical: Make the image into a 4 dimensional image
:param cellsize:
:param frequency: Frequency (array) in Hz
:param channel_bandwidth: Channel bandwidth (array) in Hz
:param phasecentre: Phase centre of image (SkyCoord)
:param polarisation_frame: Polarisation frame
:return: Image
"""
check_data_directory()
if frequency is None:
frequency = [1e8]
im = import_image_from_fits(rascil_path("data/models/M31.MOD"))
if canonical:
if polarisation_frame is None:
im.polarisation_frame = PolarisationFrame("stokesI")
elif isinstance(polarisation_frame, PolarisationFrame):
im.polarisation_frame = polarisation_frame
else:
raise ValueError("polarisation_frame is not valid")
im = replicate_image(im,
frequency=frequency,
polarisation_frame=im.polarisation_frame)
if cellsize is not None:
im.wcs.wcs.cdelt[0] = -180.0 * cellsize / numpy.pi
im.wcs.wcs.cdelt[1] = +180.0 * cellsize / numpy.pi
if frequency is not None:
im.wcs.wcs.crval[3] = frequency[0]
if channel_bandwidth is not None:
im.wcs.wcs.cdelt[3] = channel_bandwidth[0]
else:
if len(frequency) > 1:
im.wcs.wcs.cdelt[3] = frequency[1] - frequency[0]
else:
im.wcs.wcs.cdelt[3] = 0.001 * frequency[0]
im.wcs.wcs.radesys = 'ICRS'
im.wcs.wcs.equinox = 2000.00
if phasecentre is not None:
im.wcs.wcs.crval[0] = phasecentre.ra.deg
im.wcs.wcs.crval[1] = phasecentre.dec.deg
# WCS is 1 relative
im.wcs.wcs.crpix[0] = im.data.shape[3] // 2 + 1
im.wcs.wcs.crpix[1] = im.data.shape[2] // 2 + 1
return im
def create_configuration_from_MIDfile(antfile: str,
location=None,
mount: str = 'azel',
rmax=None,
name='') -> Configuration:
""" Define configuration from a SKA MID format file
:param antfile: Antenna file name
:param mount: mount type: 'azel', 'xy'
:param rmax: Maximum distance from array centre (m)
:param name: Name of array
:return: Configuration
"""
check_data_directory()
# X Y Z Diam Station
# 9.36976 35.48262 1052.99987 13.50 M001
antxyz = numpy.genfromtxt(antfile,
skip_header=5,
usecols=[0, 1, 2],
delimiter=" ")
antxyz = xyz_at_latitude(antxyz, location.lat.rad)
antxyz += [
location.geocentric[0].to(u.m).value,
location.geocentric[1].to(u.m).value,
location.geocentric[2].to(u.m).value
]
nants = antxyz.shape[0]
assert antxyz.shape[
1] == 3, "Antenna array has wrong shape %s" % antxyz.shape
anames = numpy.genfromtxt(antfile,
dtype='str',
skip_header=5,
usecols=[4],
delimiter=" ")
mounts = numpy.repeat(mount, nants)
diameters = numpy.genfromtxt(antfile,
dtype='str',
skip_header=5,
usecols=[3],
delimiter=" ")
antxyz, diameters, anames, mounts = limit_rmax(antxyz, diameters, anames,
mounts, rmax)
fc = Configuration(location=location,
names=anames,
mount=mounts,
xyz=antxyz,
diameter=diameters,
name=name)
return fc
def create_configuration_from_SKAfile(antfile: str,
mount: str = 'azel',
names: str = "%d",
rmax=None,
name='',
location=None) -> Configuration:
""" Define configuration from a SKA format file
:param antfile: Antenna file name
:param location: Earthlocation of array
:param mount: mount type: 'azel', 'xy', 'equatorial'
:param names: Antenna names e.g. "VLA%d"
:param rmax: Maximum distance from array centre (m)
:param name: Name of array
:return: Configuration
"""
check_data_directory()
antdiamlonglat = numpy.genfromtxt(antfile,
usecols=[0, 1, 2],
delimiter="\t")
assert antdiamlonglat.shape[1] == 3, ("Antenna array has wrong shape %s" %
antdiamlonglat.shape)
antxyz = numpy.zeros([antdiamlonglat.shape[0] - 1, 3])
diameters = numpy.zeros([antdiamlonglat.shape[0] - 1])
for ant in range(antdiamlonglat.shape[0] - 1):
loc = EarthLocation(lon=antdiamlonglat[ant, 1],
lat=antdiamlonglat[ant, 2],
height=0.0).geocentric
antxyz[ant] = [
loc[0].to(u.m).value, loc[1].to(u.m).value, loc[2].to(u.m).value
]
diameters[ant] = antdiamlonglat[ant, 0]
nants = antxyz.shape[0]
anames = [names % ant for ant in range(nants)]
mounts = numpy.repeat(mount, nants)
antxyz, diameters, anames, mounts = limit_rmax(antxyz, diameters, anames,
mounts, rmax)
fc = Configuration(location=location,
names=anames,
mount=mounts,
xyz=antxyz,
diameter=diameters,
name=name)
return fc
def create_configuration_from_file(antfile: str,
location: EarthLocation = None,
mount: str = 'azel',
names: str = "%d",
diameter=35.0,
rmax=None,
name='') -> Configuration:
""" Define configuration from a text file
:param antfile: Antenna file name
:param location: Earthlocation of array
:param mount: mount type: 'azel', 'xy', 'equatorial'
:param names: Antenna names e.g. "VLA%d"
:param diameter: Effective diameter of station or antenna
:param rmax: Maximum distance from array centre (m)
:param name: Name of array
:return: Configuration
"""
check_data_directory()
antxyz = numpy.genfromtxt(antfile, delimiter=",")
assert antxyz.shape[1] == 3, ("Antenna array has wrong shape %s" %
antxyz.shape)
latitude = location.geodetic[1].to(u.rad).value
antxyz = xyz_at_latitude(antxyz, latitude)
antxyz += [
location.geocentric[0].to(u.m).value,
location.geocentric[1].to(u.m).value,
location.geocentric[2].to(u.m).value
]
nants = antxyz.shape[0]
diameters = diameter * numpy.ones(nants)
anames = [names % ant for ant in range(nants)]
mounts = numpy.repeat(mount, nants)
antxyz, diameters, anames, mounts = limit_rmax(antxyz, diameters, anames,
mounts, rmax)
fc = Configuration(location=location,
names=anames,
mount=mounts,
xyz=antxyz,
diameter=diameters,
name=name)
return fc
def create_LOFAR_configuration(antfile: str,
location,
rmax=1e6) -> Configuration:
""" Define configuration from the LOFAR configuration file
:param antfile:
:param location: EarthLocation
:param rmax: Maximum distance from array centre (m)
:return: Configuration
"""
check_data_directory()
antxyz = numpy.genfromtxt(antfile,
skip_header=2,
usecols=[1, 2, 3],
delimiter=",")
nants = antxyz.shape[0]
assert antxyz.shape[
1] == 3, "Antenna array has wrong shape %s" % antxyz.shape
anames = numpy.genfromtxt(antfile,
dtype='str',
skip_header=2,
usecols=[0],
delimiter=",")
mounts = numpy.repeat('XY', nants)
diameters = numpy.repeat(35.0, nants)
antxyz, diameters, mounts, anames = limit_rmax(antxyz, diameters, anames,
mounts, rmax)
fc = Configuration(location=location,
names=anames,
mount=mounts,
xyz=antxyz,
diameter=diameters,
name='LOFAR')
return fc
def create_low_test_skycomponents_from_gleam(flux_limit=0.1, polarisation_frame=PolarisationFrame("stokesI"),
frequency=numpy.array([1e8]), kind='cubic', phasecentre=None,
radius=1.0) \
-> List[Skycomponent]:
"""Create sky components from the GLEAM survey
Stokes I is estimated from a cubic spline fit to the measured fluxes. The polarised flux is always zero.
See http://www.mwatelescope.org/science/gleam-survey The catalog is available from Vizier.
VIII/100 GaLactic and Extragalactic All-sky MWA survey (Hurley-Walker+, 2016)
GaLactic and Extragalactic All-sky Murchison Wide Field Array (GLEAM) survey. I: A low-frequency extragalactic
catalogue. Hurley-Walker N., et al., Mon. Not. R. Astron. Soc., 464, 1146-1167 (2017), 2017MNRAS.464.1146H
:param flux_limit: Only write components brighter than this (Jy)
:param polarisation_frame: Polarisation frame (default PolarisationFrame("stokesI"))
:param frequency: Frequencies at which the flux will be estimated
:param kind: Kind of interpolation (see scipy.interpolate.interp1d) Default: linear
:param phasecentre: Desired phase centre (SkyCoord) default None implies all sources
:param radius: Radius of sources selected around phasecentre (default 1.0 rad)
:return: List of Skycomponents
"""
check_data_directory()
fitsfile = rascil_path("data/models/GLEAM_EGC.fits")
rad2deg = 180.0 / numpy.pi
decmin = phasecentre.dec.to('deg').value - rad2deg * radius / 2.0
decmax = phasecentre.dec.to('deg').value + rad2deg * radius / 2.0
hdulist = fits.open(fitsfile, lazy_load_hdus=False)
recs = hdulist[1].data[0].array
fluxes = recs['peak_flux_wide']
mask = fluxes > flux_limit
filtered_recs = recs[mask]
decs = filtered_recs['DEJ2000']
mask = decs > decmin
filtered_recs = filtered_recs[mask]
decs = filtered_recs['DEJ2000']
mask = decs < decmax
filtered_recs = filtered_recs[mask]
ras = filtered_recs['RAJ2000']
decs = filtered_recs['DEJ2000']
names = filtered_recs['Name']
if polarisation_frame is None:
polarisation_frame = PolarisationFrame("stokesI")
npol = polarisation_frame.npol
nchan = len(frequency)
# For every source, we read all measured fluxes and interpolate to the
# required frequencies
gleam_freqs = numpy.array([
76, 84, 92, 99, 107, 115, 122, 130, 143, 151, 158, 166, 174, 181, 189,
197, 204, 212, 220, 227
])
gleam_flux_freq = numpy.zeros([len(names), len(gleam_freqs)])
for i, f in enumerate(gleam_freqs):
gleam_flux_freq[:, i] = filtered_recs['int_flux_%03d' % (f)][:]
skycomps = []
directions = SkyCoord(ra=ras * u.deg, dec=decs * u.deg)
if phasecentre is not None:
separations = directions.separation(phasecentre).to('rad').value
else:
separations = numpy.zeros(len(names))
for isource, name in enumerate(names):
direction = directions[isource]
if separations[isource] < radius:
fint = interpolate.interp1d(gleam_freqs * 1.0e6,
gleam_flux_freq[isource, :],
kind=kind)
flux = numpy.zeros([nchan, npol])
flux[:, 0] = fint(frequency)
if not numpy.isnan(flux).any():
skycomps.append(
Skycomponent(direction=direction,
flux=flux,
frequency=frequency,
name=name,
shape='Point',
polarisation_frame=polarisation_frame))
log.info(
'create_low_test_skycomponents_from_gleam: %d sources above flux limit %.3f'
% (len(skycomps), flux_limit))
hdulist.close()
return skycomps
def create_low_test_skymodel_from_gleam(npixel=512,
polarisation_frame=PolarisationFrame(
"stokesI"),
cellsize=0.000015,
frequency=numpy.array([1e8]),
channel_bandwidth=numpy.array([1e6]),
phasecentre=None,
kind='cubic',
applybeam=True,
flux_limit=0.1,
flux_max=numpy.inf,
flux_threshold=1.0,
insert_method='Nearest',
telescope='LOW') -> SkyModel:
"""Create LOW test skymodel from the GLEAM survey
Stokes I is estimated from a cubic spline fit to the measured fluxes. The polarised flux is always zero.
See http://www.mwatelescope.org/science/gleam-survey The catalog is available from Vizier.
VIII/100 GaLactic and Extragalactic All-sky MWA survey (Hurley-Walker+, 2016)
GaLactic and Extragalactic All-sky Murchison Wide Field Array (GLEAM) survey. I: A low-frequency extragalactic
catalogue. Hurley-Walker N., et al., Mon. Not. R. Astron. Soc., 464, 1146-1167 (2017), 2017MNRAS.464.1146H
:param telescope:
:param npixel: Number of pixels
:param polarisation_frame: Polarisation frame (default PolarisationFrame("stokesI"))
:param cellsize: cellsize in radians
:param frequency:
:param channel_bandwidth: Channel width (Hz)
:param phasecentre: phasecentre (SkyCoord)
:param kind: Kind of interpolation (see scipy.interpolate.interp1d) Default: cubic
:param applybeam: Apply the primary beam?
:param flux_limit: Weakest component
:param flux_max: Maximum strength component to be included in components
:param flux_threshold: Split between components (brighter) and image (weaker)
:param insert_method: Nearest | PSWF | Lanczos
:return:
:return: SkyModel
"""
check_data_directory()
if phasecentre is None:
phasecentre = SkyCoord(ra=+15.0 * u.deg,
dec=-35.0 * u.deg,
frame='icrs',
equinox='J2000')
radius = npixel * cellsize
sc = create_low_test_skycomponents_from_gleam(
flux_limit=flux_limit,
polarisation_frame=polarisation_frame,
frequency=frequency,
phasecentre=phasecentre,
kind=kind,
radius=radius)
sc = filter_skycomponents_by_flux(sc, flux_max=flux_max)
if polarisation_frame is None:
polarisation_frame = PolarisationFrame("stokesI")
npol = polarisation_frame.npol
nchan = len(frequency)
shape = [nchan, npol, npixel, npixel]
w = WCS(naxis=4)
# The negation in the longitude is needed by definition of RA, DEC
w.wcs.cdelt = [
-cellsize * 180.0 / numpy.pi, cellsize * 180.0 / numpy.pi, 1.0,
channel_bandwidth[0]
]
w.wcs.crpix = [npixel // 2 + 1, npixel // 2 + 1, 1.0, 1.0]
w.wcs.ctype = ["RA---SIN", "DEC--SIN", 'STOKES', 'FREQ']
w.wcs.crval = [phasecentre.ra.deg, phasecentre.dec.deg, 1.0, frequency[0]]
w.naxis = 4
w.wcs.radesys = 'ICRS'
w.wcs.equinox = 2000.0
model = create_image_from_array(numpy.zeros(shape),
w,
polarisation_frame=polarisation_frame)
if applybeam:
beam = create_pb(model, telescope=telescope, use_local=False)
sc = apply_beam_to_skycomponent(sc, beam)
weaksc = filter_skycomponents_by_flux(sc, flux_max=flux_threshold)
brightsc = filter_skycomponents_by_flux(sc, flux_min=flux_threshold)
model = insert_skycomponent(model, weaksc, insert_method=insert_method)
log.info(
'create_low_test_skymodel_from_gleam: %d bright sources above flux threshold %.3f, %d weak sources below '
% (len(brightsc), flux_threshold, len(weaksc)))
return SkyModel(components=brightsc,
image=model,
mask=None,
gaintable=None)
def create_low_test_image_from_gleam(npixel=512,
polarisation_frame=PolarisationFrame(
"stokesI"),
cellsize=0.000015,
frequency=numpy.array([1e8]),
channel_bandwidth=numpy.array([1e6]),
phasecentre=None,
kind='cubic',
applybeam=False,
flux_limit=0.1,
flux_max=numpy.inf,
flux_min=-numpy.inf,
radius=None,
insert_method='Nearest') -> Image:
"""Create LOW test image from the GLEAM survey
Stokes I is estimated from a cubic spline fit to the measured fluxes. The polarised flux is always zero.
See http://www.mwatelescope.org/science/gleam-survey The catalog is available from Vizier.
VIII/100 GaLactic and Extragalactic All-sky MWA survey (Hurley-Walker+, 2016)
GaLactic and Extragalactic All-sky Murchison Wide Field Array (GLEAM) survey. I: A low-frequency extragalactic
catalogue. Hurley-Walker N., et al., Mon. Not. R. Astron. Soc., 464, 1146-1167 (2017), 2017MNRAS.464.1146H
:param npixel: Number of pixels
:param polarisation_frame: Polarisation frame (default PolarisationFrame("stokesI"))
:param cellsize: cellsize in radians
:param frequency:
:param channel_bandwidth: Channel width (Hz)
:param phasecentre: phasecentre (SkyCoord)
:param kind: Kind of interpolation (see scipy.interpolate.interp1d) Default: linear
:return: Image
"""
check_data_directory()
if phasecentre is None:
phasecentre = SkyCoord(ra=+15.0 * u.deg,
dec=-35.0 * u.deg,
frame='icrs',
equinox='J2000')
if radius is None:
radius = npixel * cellsize / numpy.sqrt(2.0)
sc = create_low_test_skycomponents_from_gleam(
flux_limit=flux_limit,
polarisation_frame=polarisation_frame,
frequency=frequency,
phasecentre=phasecentre,
kind=kind,
radius=radius)
sc = filter_skycomponents_by_flux(sc, flux_min=flux_min, flux_max=flux_max)
if polarisation_frame is None:
polarisation_frame = PolarisationFrame("stokesI")
npol = polarisation_frame.npol
nchan = len(frequency)
shape = [nchan, npol, npixel, npixel]
w = WCS(naxis=4)
# The negation in the longitude is needed by definition of RA, DEC
w.wcs.cdelt = [
-cellsize * 180.0 / numpy.pi, cellsize * 180.0 / numpy.pi, 1.0,
channel_bandwidth[0]
]
w.wcs.crpix = [npixel // 2 + 1, npixel // 2 + 1, 1.0, 1.0]
w.wcs.ctype = ["RA---SIN", "DEC--SIN", 'STOKES', 'FREQ']
w.wcs.crval = [phasecentre.ra.deg, phasecentre.dec.deg, 1.0, frequency[0]]
w.naxis = 4
w.wcs.radesys = 'ICRS'
w.wcs.equinox = 2000.0
model = create_image_from_array(numpy.zeros(shape),
w,
polarisation_frame=polarisation_frame)
model = insert_skycomponent(model, sc, insert_method=insert_method)
if applybeam:
beam = create_pb(model, telescope='LOW', use_local=False)
model.data[...] *= beam.data[...]
return model
def create_test_skycomponents_from_s3(polarisation_frame=PolarisationFrame(
"stokesI"),
frequency=numpy.array([1e8]),
channel_bandwidth=numpy.array([1e6]),
phasecentre=None,
fov=20,
flux_limit=1e-3,
radius=None):
"""Create test image from S3
The input catalog was generated at http://s-cubed.physics.ox.ac.uk/s3_sex using the following query::
Database: s3_sex
SQL: select * from Galaxies where (pow(10,itot_151)*1000 > 1.0) and (right_ascension between -5 and 5) and (declination between -5 and 5);;
Number of rows returned: 29966
For frequencies < 610MHz, there are three tables to use::
data/models/S3_151MHz_10deg.csv, use fov=10
data/models/S3_151MHz_20deg.csv, use fov=20
data/models/S3_151MHz_40deg.csv, use fov=40
For frequencies > 610MHz, there are three tables:
data/models/S3_1400MHz_1mJy_10deg.csv, use flux_limit>= 1e-3
data/models/S3_1400MHz_100uJy_10deg.csv, use flux_limit < 1e-3
data/models/S3_1400MHz_1mJy_18deg.csv, use flux_limit>= 1e-3
data/models/S3_1400MHz_100uJy_18deg.csv, use flux_limit < 1e-3
The component spectral index is calculated from the 610MHz and 151MHz or 1400MHz and 610MHz, and then calculated
for the specified frequencies.
If polarisation_frame is not stokesI then the image will a polarised axis but the values will be zero.
:param polarisation_frame: Polarisation frame (default PolarisationFrame("stokesI"))
:param frequency:
:param channel_bandwidth: Channel width (Hz)
:param phasecentre: phasecentre (SkyCoord)
:param fov: fov 10 | 20 | 40
:param flux_limit: Minimum flux (Jy)
:return: Image
"""
check_data_directory()
ras = []
decs = []
fluxes = []
names = []
if phasecentre is None:
phasecentre = SkyCoord(ra=+180.0 * u.deg,
dec=-60.0 * u.deg,
frame='icrs',
equinox='J2000')
if polarisation_frame is None:
polarisation_frame = PolarisationFrame("stokesI")
if numpy.max(frequency) > 6.1E8:
if fov > 10:
fovstr = '18'
else:
fovstr = '10'
if flux_limit >= 1e-3:
csvfilename = rascil_data_path('models/S3_1400MHz_1mJy_%sdeg.csv' %
fovstr)
else:
csvfilename = rascil_data_path(
'models/S3_1400MHz_100uJy_%sdeg.csv' % fovstr)
log.info(
'create_test_skycomponents_from_s3: Reading S3-SEX sources from %s '
% csvfilename)
else:
assert fov in [
10, 20, 40
], "Field of view invalid: use one of %s" % ([10, 20, 40])
csvfilename = rascil_data_path('models/S3_151MHz_%ddeg.csv' % (fov))
log.info(
'create_test_skycomponents_from_s3: Reading S3-SEX sources from %s '
% csvfilename)
skycomps = list()
with open(csvfilename) as csvfile:
readCSV = csv.reader(csvfile, delimiter=',')
r = 0
for row in readCSV:
# Skip first row
if r > 0:
ra = float(row[4]) / numpy.cos(
phasecentre.dec.rad) + phasecentre.ra.deg
dec = float(row[5]) + phasecentre.dec.deg
if numpy.max(frequency) > 6.1E8:
alpha = (float(row[11]) - float(row[10])) / numpy.log10(
1400.0 / 610.0)
flux = numpy.power(10, float(row[10])) * numpy.power(
frequency / 1.4e9, alpha)
else:
alpha = (float(row[10]) - float(row[9])) / numpy.log10(
610.0 / 151.0)
flux = numpy.power(10, float(row[9])) * numpy.power(
frequency / 1.51e8, alpha)
if numpy.max(flux) > flux_limit:
ras.append(ra)
decs.append(dec)
if polarisation_frame == PolarisationFrame("stokesIQUV"):
polscale = numpy.array([1.0, 0.0, 0.0, 0.0])
fluxes.append(numpy.outer(flux, polscale))
else:
fluxes.append([[f] for f in flux])
names.append("S3_%s" % row[0])
r += 1
csvfile.close()
assert len(fluxes) > 0, "No sources found above flux limit %s" % flux_limit
directions = SkyCoord(ra=ras * u.deg, dec=decs * u.deg)
if phasecentre is not None:
separations = directions.separation(phasecentre).to('rad').value
else:
separations = numpy.zeros(len(names))
for isource, name in enumerate(names):
direction = directions[isource]
if separations[isource] < radius:
if not numpy.isnan(flux).any():
skycomps.append(
Skycomponent(direction=direction,
flux=fluxes[isource],
frequency=frequency,
name=names[isource],
shape='Point',
polarisation_frame=polarisation_frame))
log.info(
'create_test_skycomponents_from_s3: %d sources found above fluxlimit inside search radius'
% len(skycomps))
return skycomps
def create_test_image_from_s3(npixel=16384,
polarisation_frame=PolarisationFrame("stokesI"),
cellsize=0.000015,
frequency=numpy.array([1e8]),
channel_bandwidth=numpy.array([1e6]),
phasecentre=None,
fov=20,
flux_limit=1e-3) -> Image:
"""Create MID test image from S3
The input catalog was generated at http://s-cubed.physics.ox.ac.uk/s3_sex using the following query::
Database: s3_sex
SQL: select * from Galaxies where (pow(10,itot_151)*1000 > 1.0) and (right_ascension between -5 and 5) and (declination between -5 and 5);;
Number of rows returned: 29966
For frequencies < 610MHz, there are three tables to use::
data/models/S3_151MHz_10deg.csv, use fov=10
data/models/S3_151MHz_20deg.csv, use fov=20
data/models/S3_151MHz_40deg.csv, use fov=40
For frequencies > 610MHz, there are three tables:
data/models/S3_1400MHz_1mJy_10deg.csv, use flux_limit>= 1e-3
data/models/S3_1400MHz_100uJy_10deg.csv, use flux_limit < 1e-3
data/models/S3_1400MHz_1mJy_18deg.csv, use flux_limit>= 1e-3
data/models/S3_1400MHz_100uJy_18deg.csv, use flux_limit < 1e-3
The component spectral index is calculated from the 610MHz and 151MHz or 1400MHz and 610MHz, and then calculated
for the specified frequencies.
If polarisation_frame is not stokesI then the image will a polarised axis but the values will be zero.
:param npixel: Number of pixels
:param polarisation_frame: Polarisation frame (default PolarisationFrame("stokesI"))
:param cellsize: cellsize in radians
:param frequency:
:param channel_bandwidth: Channel width (Hz)
:param phasecentre: phasecentre (SkyCoord)
:param fov: fov 10 | 20 | 40
:param flux_limit: Minimum flux (Jy)
:return: Image
"""
check_data_directory()
ras = []
decs = []
fluxes = []
if phasecentre is None:
phasecentre = SkyCoord(ra=+180.0 * u.deg,
dec=-60.0 * u.deg,
frame='icrs',
equinox='J2000')
if polarisation_frame is None:
polarisation_frame = PolarisationFrame("stokesI")
npol = polarisation_frame.npol
nchan = len(frequency)
shape = [nchan, npol, npixel, npixel]
w = WCS(naxis=4)
# The negation in the longitude is needed by definition of RA, DEC
w.wcs.cdelt = [
-cellsize * 180.0 / numpy.pi, cellsize * 180.0 / numpy.pi, 1.0,
channel_bandwidth[0]
]
w.wcs.crpix = [npixel // 2 + 1, npixel // 2 + 1, 1.0, 1.0]
w.wcs.ctype = ["RA---SIN", "DEC--SIN", 'STOKES', 'FREQ']
w.wcs.crval = [phasecentre.ra.deg, phasecentre.dec.deg, 1.0, frequency[0]]
w.naxis = 4
w.wcs.radesys = 'ICRS'
w.wcs.equinox = 2000.0
model = create_image_from_array(numpy.zeros(shape),
w,
polarisation_frame=polarisation_frame)
if numpy.max(frequency) > 6.1E8:
if fov > 10:
fovstr = '18'
else:
fovstr = '10'
if flux_limit >= 1e-3:
csvfilename = rascil_data_path('models/S3_1400MHz_1mJy_%sdeg.csv' %
fovstr)
else:
csvfilename = rascil_data_path(
'models/S3_1400MHz_100uJy_%sdeg.csv' % fovstr)
log.info('create_test_image_from_s3: Reading S3 sources from %s ' %
csvfilename)
else:
assert fov in [
10, 20, 40
], "Field of view invalid: use one of %s" % ([10, 20, 40])
csvfilename = rascil_data_path('models/S3_151MHz_%ddeg.csv' % (fov))
log.info('create_test_image_from_s3: Reading S3 sources from %s ' %
csvfilename)
with open(csvfilename) as csvfile:
readCSV = csv.reader(csvfile, delimiter=',')
r = 0
for row in readCSV:
# Skip first row
if r > 0:
ra = float(row[4]) + phasecentre.ra.deg
dec = float(row[5]) + phasecentre.dec.deg
if numpy.max(frequency) > 6.1E8:
alpha = (float(row[11]) - float(row[10])) / numpy.log10(
1400.0 / 610.0)
flux = numpy.power(10, float(row[10])) * numpy.power(
frequency / 1.4e9, alpha)
else:
alpha = (float(row[10]) - float(row[9])) / numpy.log10(
610.0 / 151.0)
flux = numpy.power(10, float(row[9])) * numpy.power(
frequency / 1.51e8, alpha)
if numpy.max(flux) > flux_limit:
ras.append(ra)
decs.append(dec)
fluxes.append(flux)
r += 1
csvfile.close()
assert len(fluxes) > 0, "No sources found above flux limit %s" % flux_limit
log.info('create_test_image_from_s3: %d sources read' % (len(fluxes)))
p = w.sub(2).wcs_world2pix(numpy.array(ras), numpy.array(decs), 1)
fluxes = numpy.array(fluxes)
total_flux = numpy.sum(fluxes)
ip = numpy.round(p).astype('int')
ok = numpy.where((0 <= ip[0, :]) & (npixel > ip[0, :]) & (0 <= ip[1, :])
& (npixel > ip[1, :]))[0]
ps = ip[:, ok]
fluxes = fluxes[ok]
actual_flux = numpy.sum(fluxes)
log.info('create_test_image_from_s3: %d sources inside the image' %
(ps.shape[1]))
log.info(
'create_test_image_from_s3: average channel flux in S3 model = %.3f, actual average channel flux in '
'image = %.3f' %
(total_flux / float(nchan), actual_flux / float(nchan)))
for chan in range(nchan):
for iflux, flux in enumerate(fluxes):
model.data[chan, 0, ps[1, iflux], ps[0, iflux]] = flux[chan]
return model
from rascil.data_models.polarisation import PolarisationFrame
from rascil.processing_components.calibration.chain_calibration import create_calibration_controls
from rascil.processing_components.calibration.operations import create_gaintable_from_blockvisibility, apply_gaintable
from rascil.processing_components.image.operations import create_image_from_array
from rascil.processing_components.image.operations import import_image_from_fits
from rascil.processing_components.imaging import predict_2d, dft_skycomponent_visibility, \
create_image_from_visibility, advise_wide_field
from rascil.processing_components.imaging.primary_beams import create_pb
from rascil.processing_components.skycomponent.operations import create_skycomponent, insert_skycomponent, \
apply_beam_to_skycomponent, filter_skycomponents_by_flux
from rascil.processing_components.visibility.base import create_blockvisibility, create_visibility
from rascil.processing_components.visibility.coalesce import convert_blockvisibility_to_visibility, \
convert_visibility_to_blockvisibility
from rascil.processing_components.util.installation_checks import check_data_directory
check_data_directory()
log = logging.getLogger('logger')
def create_test_image(
canonical=True,
cellsize=None,
frequency=None,
channel_bandwidth=None,
phasecentre=None,
polarisation_frame=PolarisationFrame("stokesI")) -> Image:
"""Create a useful test image
This is the test image M31 widely used in ALMA and other simulations. It is actually part of an Halpha region in
M31.
def create_named_configuration(name: str = 'LOWBD2',
**kwargs) -> Configuration:
""" Create standard configurations e.g. LOWBD2, MIDBD2
Possible configurations are::
LOWBD1
LOWBD2
LOWBD2-core
LOW == LOWR3
MID == MIDR5
ASKAP
LOFAR
VLAA
VLAA_north
:param name: name of Configuration LOWBD2, LOWBD1, LOFAR, VLAA, ASKAP
:param rmax: Maximum distance of station from the average (m)
:return:
For LOWBD2, setting rmax gives the following number of stations
100.0 13
300.0 94
1000.0 251
3000.0 314
10000.0 398
30000.0 476
100000.0 512
"""
check_data_directory()
if name == 'LOWBD2':
location = EarthLocation(lon="116.76444824",
lat="-26.824722084",
height=300.0)
log.info("create_named_configuration: %s\n\t%s\n\t%s" %
(name, location.geocentric, location.geodetic))
fc = create_configuration_from_file(
antfile=rascil_path("data/configurations/LOWBD2.csv"),
location=location,
mount='xy',
names='LOWBD2_%d',
diameter=35.0,
name=name,
**kwargs)
elif name == 'LOWBD1':
location = EarthLocation(lon="116.76444824",
lat="-26.824722084",
height=300.0)
log.info("create_named_configuration: %s\n\t%s\n\t%s" %
(name, location.geocentric, location.geodetic))
fc = create_configuration_from_file(
antfile=rascil_path("data/configurations/LOWBD1.csv"),
location=location,
mount='xy',
names='LOWBD1_%d',
diameter=35.0,
name=name,
**kwargs)
elif name == 'LOWBD2-CORE':
location = EarthLocation(lon="116.76444824",
lat="-26.824722084",
height=300.0)
log.info("create_named_configuration: %s\n\t%s\n\t%s" %
(name, location.geocentric, location.geodetic))
fc = create_configuration_from_file(
antfile=rascil_path("data/configurations/LOWBD2-CORE.csv"),
location=location,
mount='xy',
names='LOWBD2_%d',
diameter=35.0,
name=name,
**kwargs)
elif (name == 'LOW') or (name == 'LOWR3'):
location = EarthLocation(lon="116.76444824",
lat="-26.824722084",
height=300.0)
log.info("create_named_configuration: %s\n\t%s\n\t%s" %
(name, location.geocentric, location.geodetic))
fc = create_configuration_from_MIDfile(
antfile=rascil_path("data/configurations/ska1low_local.cfg"),
mount='xy',
name=name,
location=location,
**kwargs)
elif (name == 'MID') or (name == "MIDR5"):
location = EarthLocation(lon="21.443803", lat="-30.712925", height=0.0)
log.info("create_named_configuration: %s\n\t%s\n\t%s" %
(name, location.geocentric, location.geodetic))
fc = create_configuration_from_MIDfile(
antfile=rascil_path("data/configurations/ska1mid_local.cfg"),
mount='azel',
name=name,
location=location,
**kwargs)
elif name == 'ASKAP':
location = EarthLocation(lon="+116.6356824",
lat="-26.7013006",
height=377.0)
log.info("create_named_configuration: %s\n\t%s\n\t%s" %
(name, location.geocentric, location.geodetic))
fc = create_configuration_from_file(
antfile=rascil_path("data/configurations/A27CR3P6B.in.csv"),
mount='equatorial',
names='ASKAP_%d',
diameter=12.0,
name=name,
location=location,
**kwargs)
elif name == 'LOFAR':
location = EarthLocation(x=3826923.9 * u.m,
y=460915.1 * u.m,
z=5064643.2 * u.m)
log.info("create_named_configuration: %s\n\t%s\n\t%s" %
(name, location.geocentric, location.geodetic))
assert get_parameter(kwargs, "meta", False) is False
fc = create_LOFAR_configuration(
antfile=rascil_path("data/configurations/LOFAR.csv"),
location=location)
elif name == 'VLAA':
location = EarthLocation(lon="-107.6184", lat="34.0784", height=2124.0)
log.info("create_named_configuration: %s\n\t%s\n\t%s" %
(name, location.geocentric, location.geodetic))
fc = create_configuration_from_file(
antfile=rascil_path("data/configurations/VLA_A_hor_xyz.csv"),
location=location,
mount='azel',
names='VLA_%d',
diameter=25.0,
name=name,
**kwargs)
elif name == 'VLAA_north':
location = EarthLocation(lon="-107.6184", lat="90.000", height=0.0)
log.info("create_named_configuration: %s\n\t%s\n\t%s" %
(name, location.geocentric, location.geodetic))
fc = create_configuration_from_file(
antfile=rascil_path("data/configurations/VLA_A_hor_xyz.csv"),
location=location,
mount='azel',
names='VLA_%d',
diameter=25.0,
name=name,
**kwargs)
else:
raise ValueError("No such Configuration %s" % name)
return fc
