def fs_from_file(filename, frq, src,
del_t=900, transposed=True, subtract_avg=False):
f = h5py.File(filename, 'r')
times = f['index_map']['time'].value['ctime'] + 10.6
src_trans = eph.transit_times(src, times[0])
# try to account for differential arrival time from cylinder rotation.
del_phi = (src._dec - np.radians(eph.CHIMELATITUDE)) * np.sin(np.radians(1.988))
del_phi *= (24 * 3600.0) / (2 * np.pi)
# Adjust the transit time accordingly
src_trans += del_phi
# Select +- del_t of transit, accounting for the mispointing
t_range = np.where((times < src_trans + del_t) & (times > src_trans - del_t))[0]
times = times[t_range[0]:t_range[-1]]#[offp::2] test
print "Time range:", times[0], times[-1]
print "\n...... This data is from %s starting at RA: %f ...... \n" \
% (eph.unix_to_datetime(times[0]), eph.transit_RA(times[0]))
if transposed is True:
v = f['vis'][frq[0]:frq[-1]+1, :]
v = v[..., t_range[0]:t_range[-1]]
vis = v['r'] + 1j * v['i']
del v
# Read in time and freq slice if data has not yet been transposed
if transposed is False:
v = f['vis'][t_range[0]:t_range[-1], frq[0]:frq[-1]+1, :]
vis = v['r'][:] + 1j * v['i'][:]
del v
vis = np.transpose(vis, (1, 2, 0))
inp = gen_inp()[0]
# Remove offset from galaxy
if subtract_avg is True:
vis -= 0.5 * (vis[..., 0] + vis[..., -1])[..., np.newaxis]
freq_MHZ = 800.0 - np.array(frq) / 1024.0 * 400.
print len(inp)
baddies = np.where(np.isnan(tools.get_feed_positions(inp)[:, 0]))[0]
# Fringestop to location of "src"
data_fs = tools.fringestop_pathfinder(vis, eph.transit_RA(times), freq_MHZ, inp, src)
# data_fs = fringestop_pathfinder(vis, eph.transit_RA(times), freq_MHZ, inp, src)
return data_fs
def fringestop_and_sum(fn, feeds, freq, src, transposed=True,
return_unfs=True, meridian=False, del_t=1500, frick=None):
""" Take an input file fn and a set of feeds and return
a formed beam on src.
"""
if transposed is True:
r = andata.Reader(fn)
r.freq_sel = freq
X = r.read()
times = r.time
else:
f = h5py.File(fn, 'r')
times = f['index_map']['time'].value['ctime']
print "Read in data"
# Get transit time for source
src_trans = eph.transit_times(src, times[0])
del_phi = 1.30 * (src._dec - np.radians(eph.CHIMELATITUDE)) * np.sin(np.radians(1.988))
del_phi *= (24 * 3600.0) / (2 * np.pi)
# Adjust the transit time accordingly
src_trans += del_phi
# Select +- del_t of transit, accounting for the mispointing
t_range = np.where((times < src_trans + del_t) & (times > src_trans - del_t))[0]
times = times[t_range[0]:t_range[-1]]#[offp::2] test
print "Time range:", times[0], times[-1]
# Generate correctly ordered corrinputs
corrinput_real = gen_inp()[0]
inp = np.array(corrinput_real)
# Ensure vis array is in correct order (freq, prod, time)
if transposed is True:
data = X.vis[:, :, t_range[0]:t_range[-1]]
freq = X.freq
else:
v = f['vis'][t_range[0]:t_range[-1], freq, :]
vis = v['r'] + 1j * v['i']
data = vis.transpose()[np.newaxis]
del vis
freq = 800 - 400.0 / 1024 * freq
freq = np.array([freq])
# autos = auto_corrs(256)
# offp = (abs(data[:, autos, 0::2]).mean() > (abs(data[:, autos, 1::2]).mean())).astype(int)
# data = data[..., offp::2] test
data_unfs = sum_corrs(data.copy(), feeds)
ra_ = eph.transit_RA(times)
ra_2 = nolan_ra(times)
#ra_ = ra_2.copy()
if meridian is True:
ra = np.ones_like(ra_) * np.degrees(src._ra)
else:
ra = ra_
print len(inp)
dfs = tools.fringestop_pathfinder(data.copy(), ra, freq, inp, src)
#dfs = fringestop_pathfinder(data.copy(), ra_2, freq, inp, src, frick=frick)
# dfs = fringestop_pathfinder(data.copy(), ra_1, freq, inp, src, frick=frick)
# fp = np.loadtxt('/home/connor/feed_layout_decrease.txt')
# PH = fill_nolan(times, src._ra * 180.0 / np.pi, src._dec * 180.0 / np.pi, fp)
dfs_sum = sum_corrs(dfs, feeds)
if return_unfs is True:
return dfs_sum, ra_, dfs, data
else:
return dfs_sum, ra_
def solve_ps_transit(filename, corrs, feeds, inp,
src, nfreq=1024, transposed=False, nfeed=128):
""" Function that fringestops time slice
where point source is in the beam, takes
all correlations for a given polarization, and then
eigendecomposes the correlation matrix freq by freq
after removing the fpga phases. It will also
plot intermediate steps to verify the phase solution.
Parameters
----------
filename : np.str
Full-path filename
corrs : list
List of correlations to use in solver
feeds : list
List of feeds to use
inp :
Correlator inputs (output of ch_util.tools.get_correlator_inputs)
src : ephem.FixedBody
Source to calibrate off of. e.g. ch_util.ephemeris.TauA
Returns
-------
Gains : np.array
Complex gain array (nfreq, nfeed)
"""
nsplit = 32 # Number of freq chunks to divide nfreq into
del_t = 800
f = h5py.File(filename, 'r')
# Add half an integration time to each. Hack.
times = f['index_map']['time'].value['ctime'] + 10.50
src_trans = eph.transit_times(src, times[0])
# try to account for differential arrival time from
# cylinder rotation.
del_phi = (src._dec - np.radians(eph.CHIMELATITUDE)) \
* np.sin(np.radians(1.988))
del_phi *= (24 * 3600.0) / (2 * np.pi)
# Adjust the transit time accordingly
src_trans += del_phi
# Select +- del_t of transit, accounting for the mispointing
t_range = np.where((times < src_trans +
del_t) & (times > src_trans - del_t))[0]
print "\n...... This data is from %s starting at RA: %f ...... \n" \
% (eph.unix_to_datetime(times[0]), eph.transit_RA(times[0]))
assert (len(t_range) > 0), "Source is not in this acq"
# Create gains array to fill in solution
Gains = np.zeros([nfreq, nfeed], np.complex128)
print "Starting the solver"
times = times[t_range[0]:t_range[-1]]
k=0
# Start at a strong freq channel that can be plotted
# and from which we can find the noise source on-sample
for i in range(12, nsplit) + range(0, 12):
k+=1
# Divides the arrays up into nfreq / nsplit freq chunks and solves those
frq = range(i * nfreq // nsplit, (i+1) * nfreq // nsplit)
print " %d:%d \n" % (frq[0], frq[-1])
# Read in time and freq slice if data has already been transposed
if transposed is True:
v = f['vis'][frq[0]:frq[-1]+1, corrs, :]
v = v[..., t_range[0]:t_range[-1]]
vis = v['r'] + 1j * v['i']
if k==1:
autos = auto_corrs(nfeed)
offp = (abs(vis[:, autos, 0::2]).mean() > \
(abs(vis[:, autos, 1::2]).mean())).astype(int)
times = times[offp::2]
vis = vis[..., offp::2]
gg = f['gain_coeff'][frq[0]:frq[-1]+1,
feeds, t_range[0]:t_range[-1]][..., offp::2]
gain_coeff = gg['r'] + 1j * gg['i']
del gg
# Read in time and freq slice if data has not yet been transposed
if transposed is False:
print "TRANSPOSED V OF CODE DOESN'T WORK YET!"
v = f['vis'][t_range[0]:t_range[-1]:2, frq[0]:frq[-1]+1, corrs]
vis = v['r'][:] + 1j * v['i'][:]
del v
gg = f['gain_coeff'][0, frq[0]:frq[-1]+1, feeds]
gain_coeff = gg['r'][:] + 1j * gg['i'][:]
vis = vis[..., offp::2]
vis = np.transpose(vis, (1, 2, 0))
# Remove fpga gains from data
vis = remove_fpga_gains(vis, gain_coeff, nfeed=nfeed, triu=False)
# Remove offset from galaxy
vis -= 0.5 * (vis[..., 0] + vis[..., -1])[..., np.newaxis]
# Get physical freq for fringestopper
freq_MHZ = 800.0 - np.array(frq) / 1024.0 * 400.
baddies = np.where(np.isnan(tools.get_feed_positions(inp)[:, 0]))[0]
a, b, c = select_corrs(baddies, nfeed=128)
vis[:, a + b] = 0.0
# Fringestop to location of "src"
data_fs = tools.fringestop_pathfinder(vis, eph.transit_RA(times), freq_MHZ, inp, src)
del vis
dr, sol_arr = solve_gain(data_fs)
# Find index of point source transit
drlist = np.argmax(dr, axis=-1)
# If multiple freq channels are zerod, the trans_pix
# will end up being 0. This is bad, so ensure that
# you are only looking for non-zero transit pixels.
drlist = [x for x in drlist if x != 0]
trans_pix = np.argmax(np.bincount(drlist))
assert trans_pix != 0.0
Gains[frq] = sol_arr[..., trans_pix-3:trans_pix+4].mean(-1)
zz = h5py.File('data' + str(i) + '.hdf5','w')
zz.create_dataset('data', data=dr)
zz.close()
print "%f, %d Nans out of %d" % (np.isnan(sol_arr).sum(), np.isnan(Gains[frq]).sum(), np.isnan(Gains[frq]).sum())
print trans_pix, sol_arr[..., trans_pix-3:trans_pix+4].mean(-1).sum(), sol_arr.mean(-1).sum()
# Plot up post-fs phases to see if everything has been fixed
if frq[0] == 12 * nsplit:
print "======================"
print " Plotting up freq: %d" % frq[0]
print "======================"
img_nm = './phs_plots/dfs' + np.str(frq[17]) + np.str(np.int(time.time())) +'.png'
img_nmcorr = './phs_plots/dfs' + np.str(frq[17]) + np.str(np.int(time.time())) +'corr.png'
plt_gains(data_fs, 0, img_name=img_nm, bad_chans=baddies)
dfs_corr = correct_dfs(data_fs, np.angle(Gains[frq])[..., np.newaxis], nfeed=128)
plt_gains(dfs_corr, 0, img_name=img_nmcorr, bad_chans=baddies)
del dfs_corr
del data_fs, a
return Gains
def fringestop_and_sum(fn,
feeds,
freq,
src,
transposed=True,
return_unfs=True,
meridian=False,
del_t=1500,
frick=None):
""" Take an input file fn and a set of feeds and return
a formed beam on src.
"""
if transposed is True:
r = andata.Reader(fn)
r.freq_sel = freq
X = r.read()
times = r.time
else:
f = h5py.File(fn, 'r')
times = f['index_map']['time'].value['ctime']
print "Read in data"
# Get transit time for source
src_trans = eph.transit_times(src, times[0])
del_phi = 1.30 * (src._dec - np.radians(eph.CHIMELATITUDE)) * np.sin(
np.radians(1.988))
del_phi *= (24 * 3600.0) / (2 * np.pi)
# Adjust the transit time accordingly
src_trans += del_phi
# Select +- del_t of transit, accounting for the mispointing
t_range = np.where((times < src_trans + del_t)
& (times > src_trans - del_t))[0]
times = times[t_range[0]:t_range[-1]] #[offp::2] test
print "Time range:", times[0], times[-1]
# Generate correctly ordered corrinputs
corrinput_real = gen_inp()[0]
inp = np.array(corrinput_real)
# Ensure vis array is in correct order (freq, prod, time)
if transposed is True:
data = X.vis[:, :, t_range[0]:t_range[-1]]
freq = X.freq
else:
v = f['vis'][t_range[0]:t_range[-1], freq, :]
vis = v['r'] + 1j * v['i']
data = vis.transpose()[np.newaxis]
del vis
freq = 800 - 400.0 / 1024 * freq
freq = np.array([freq])
# autos = auto_corrs(256)
# offp = (abs(data[:, autos, 0::2]).mean() > (abs(data[:, autos, 1::2]).mean())).astype(int)
# data = data[..., offp::2] test
data_unfs = sum_corrs(data.copy(), feeds)
ra_ = eph.transit_RA(times)
ra_2 = nolan_ra(times)
#ra_ = ra_2.copy()
if meridian is True:
ra = np.ones_like(ra_) * np.degrees(src._ra)
else:
ra = ra_
print len(inp)
dfs = tools.fringestop_pathfinder(data.copy(), ra, freq, inp, src)
#dfs = fringestop_pathfinder(data.copy(), ra_2, freq, inp, src, frick=frick)
# dfs = fringestop_pathfinder(data.copy(), ra_1, freq, inp, src, frick=frick)
# fp = np.loadtxt('/home/connor/feed_layout_decrease.txt')
# PH = fill_nolan(times, src._ra * 180.0 / np.pi, src._dec * 180.0 / np.pi, fp)
dfs_sum = sum_corrs(dfs, feeds)
if return_unfs is True:
return dfs_sum, ra_, dfs, data
else:
return dfs_sum, ra_
def fs_from_file(filename,
frq,
src,
del_t=900,
transposed=True,
subtract_avg=False):
f = h5py.File(filename, 'r')
times = f['index_map']['time'].value['ctime'] + 10.6
src_trans = eph.transit_times(src, times[0])
# try to account for differential arrival time from cylinder rotation.
del_phi = (src._dec - np.radians(eph.CHIMELATITUDE)) * np.sin(
np.radians(1.988))
del_phi *= (24 * 3600.0) / (2 * np.pi)
# Adjust the transit time accordingly
src_trans += del_phi
# Select +- del_t of transit, accounting for the mispointing
t_range = np.where((times < src_trans + del_t)
& (times > src_trans - del_t))[0]
times = times[t_range[0]:t_range[-1]] #[offp::2] test
print "Time range:", times[0], times[-1]
print "\n...... This data is from %s starting at RA: %f ...... \n" \
% (eph.unix_to_datetime(times[0]), eph.transit_RA(times[0]))
if transposed is True:
v = f['vis'][frq[0]:frq[-1] + 1, :]
v = v[..., t_range[0]:t_range[-1]]
vis = v['r'] + 1j * v['i']
del v
# Read in time and freq slice if data has not yet been transposed
if transposed is False:
v = f['vis'][t_range[0]:t_range[-1], frq[0]:frq[-1] + 1, :]
vis = v['r'][:] + 1j * v['i'][:]
del v
vis = np.transpose(vis, (1, 2, 0))
inp = gen_inp()[0]
# Remove offset from galaxy
if subtract_avg is True:
vis -= 0.5 * (vis[..., 0] + vis[..., -1])[..., np.newaxis]
freq_MHZ = 800.0 - np.array(frq) / 1024.0 * 400.
print len(inp)
baddies = np.where(np.isnan(tools.get_feed_positions(inp)[:, 0]))[0]
# Fringestop to location of "src"
data_fs = tools.fringestop_pathfinder(vis, eph.transit_RA(times), freq_MHZ,
inp, src)
# data_fs = fringestop_pathfinder(vis, eph.transit_RA(times), freq_MHZ, inp, src)
return data_fs
def solve_ps_transit(filename,
corrs,
feeds,
inp,
src,
nfreq=1024,
transposed=False,
nfeed=128):
""" Function that fringestops time slice
where point source is in the beam, takes
all correlations for a given polarization, and then
eigendecomposes the correlation matrix freq by freq
after removing the fpga phases. It will also
plot intermediate steps to verify the phase solution.
Parameters
----------
filename : np.str
Full-path filename
corrs : list
List of correlations to use in solver
feeds : list
List of feeds to use
inp :
Correlator inputs (output of ch_util.tools.get_correlator_inputs)
src : ephem.FixedBody
Source to calibrate off of. e.g. ch_util.ephemeris.TauA
Returns
-------
Gains : np.array
Complex gain array (nfreq, nfeed)
"""
nsplit = 32 # Number of freq chunks to divide nfreq into
del_t = 800
f = h5py.File(filename, 'r')
# Add half an integration time to each. Hack.
times = f['index_map']['time'].value['ctime'] + 10.50
src_trans = eph.transit_times(src, times[0])
# try to account for differential arrival time from
# cylinder rotation.
del_phi = (src._dec - np.radians(eph.CHIMELATITUDE)) \
* np.sin(np.radians(1.988))
del_phi *= (24 * 3600.0) / (2 * np.pi)
# Adjust the transit time accordingly
src_trans += del_phi
# Select +- del_t of transit, accounting for the mispointing
t_range = np.where((times < src_trans + del_t)
& (times > src_trans - del_t))[0]
print "\n...... This data is from %s starting at RA: %f ...... \n" \
% (eph.unix_to_datetime(times[0]), eph.transit_RA(times[0]))
assert (len(t_range) > 0), "Source is not in this acq"
# Create gains array to fill in solution
Gains = np.zeros([nfreq, nfeed], np.complex128)
print "Starting the solver"
times = times[t_range[0]:t_range[-1]]
k = 0
# Start at a strong freq channel that can be plotted
# and from which we can find the noise source on-sample
for i in range(12, nsplit) + range(0, 12):
k += 1
# Divides the arrays up into nfreq / nsplit freq chunks and solves those
frq = range(i * nfreq // nsplit, (i + 1) * nfreq // nsplit)
print " %d:%d \n" % (frq[0], frq[-1])
# Read in time and freq slice if data has already been transposed
if transposed is True:
v = f['vis'][frq[0]:frq[-1] + 1, corrs, :]
v = v[..., t_range[0]:t_range[-1]]
vis = v['r'] + 1j * v['i']
if k == 1:
autos = auto_corrs(nfeed)
offp = (abs(vis[:, autos, 0::2]).mean() > \
(abs(vis[:, autos, 1::2]).mean())).astype(int)
times = times[offp::2]
vis = vis[..., offp::2]
gg = f['gain_coeff'][frq[0]:frq[-1] + 1, feeds,
t_range[0]:t_range[-1]][..., offp::2]
gain_coeff = gg['r'] + 1j * gg['i']
del gg
# Read in time and freq slice if data has not yet been transposed
if transposed is False:
print "TRANSPOSED V OF CODE DOESN'T WORK YET!"
v = f['vis'][t_range[0]:t_range[-1]:2, frq[0]:frq[-1] + 1, corrs]
vis = v['r'][:] + 1j * v['i'][:]
del v
gg = f['gain_coeff'][0, frq[0]:frq[-1] + 1, feeds]
gain_coeff = gg['r'][:] + 1j * gg['i'][:]
vis = vis[..., offp::2]
vis = np.transpose(vis, (1, 2, 0))
# Remove fpga gains from data
vis = remove_fpga_gains(vis, gain_coeff, nfeed=nfeed, triu=False)
# Remove offset from galaxy
vis -= 0.5 * (vis[..., 0] + vis[..., -1])[..., np.newaxis]
# Get physical freq for fringestopper
freq_MHZ = 800.0 - np.array(frq) / 1024.0 * 400.
baddies = np.where(np.isnan(tools.get_feed_positions(inp)[:, 0]))[0]
a, b, c = select_corrs(baddies, nfeed=128)
vis[:, a + b] = 0.0
# Fringestop to location of "src"
data_fs = tools.fringestop_pathfinder(vis, eph.transit_RA(times),
freq_MHZ, inp, src)
del vis
dr, sol_arr = solve_gain(data_fs)
# Find index of point source transit
drlist = np.argmax(dr, axis=-1)
# If multiple freq channels are zerod, the trans_pix
# will end up being 0. This is bad, so ensure that
# you are only looking for non-zero transit pixels.
drlist = [x for x in drlist if x != 0]
trans_pix = np.argmax(np.bincount(drlist))
assert trans_pix != 0.0
Gains[frq] = sol_arr[..., trans_pix - 3:trans_pix + 4].mean(-1)
zz = h5py.File('data' + str(i) + '.hdf5', 'w')
zz.create_dataset('data', data=dr)
zz.close()
print "%f, %d Nans out of %d" % (np.isnan(sol_arr).sum(),
np.isnan(Gains[frq]).sum(),
np.isnan(Gains[frq]).sum())
print trans_pix, sol_arr[..., trans_pix - 3:trans_pix +
4].mean(-1).sum(), sol_arr.mean(-1).sum()
# Plot up post-fs phases to see if everything has been fixed
if frq[0] == 12 * nsplit:
print "======================"
print " Plotting up freq: %d" % frq[0]
print "======================"
img_nm = './phs_plots/dfs' + np.str(frq[17]) + np.str(
np.int(time.time())) + '.png'
img_nmcorr = './phs_plots/dfs' + np.str(frq[17]) + np.str(
np.int(time.time())) + 'corr.png'
plt_gains(data_fs, 0, img_name=img_nm, bad_chans=baddies)
dfs_corr = correct_dfs(data_fs,
np.angle(Gains[frq])[..., np.newaxis],
nfeed=128)
plt_gains(dfs_corr, 0, img_name=img_nmcorr, bad_chans=baddies)
del dfs_corr
del data_fs, a
return Gains