def frf_data(data): #FRF FULL LENGTH DATA
aa2 = a.cal.get_aa(opts.cal, freqs) #All freqs for data instead of subset
bins = fringe.gen_frbins(inttime)
frp, bins = fringe.aa_to_fr_profile(aa2, ij, len(freqs) / 2, bins=bins)
timebins, firs = fringe.frp_to_firs(frp,
bins,
aa2.get_freqs(),
fq0=aa2.get_freqs()[len(freqs) / 2])
_, blconj, _ = zsa.grid2ij(aa2.ant_layout)
if blconj[a.miriad.ij2bl(ij[0], ij[1])]:
fir = {(ij[0], ij[1], POL): n.conj(firs)}
else:
fir = {(ij[0], ij[1], POL): firs}
dij = n.transpose(data)
wij = n.ones(dij.shape, dtype=bool) #XXX flags are all true (times,freqs)
#dij and wij are (times,freqs)
_d, _w, _, _ = fringe.apply_frf(aa2,
dij,
wij,
ij[0],
ij[1],
pol=POL,
bins=bins,
firs=fir)
_d = n.transpose(_d)
return _d
def frf_data(data): #FRF FULL LENGTH DATA
aa2 = a.cal.get_aa(opts.cal, freqs) #All freqs for data instead of subset
bins = fringe.gen_frbins(inttime)
frp, bins = fringe.aa_to_fr_profile(aa2, ij, len(freqs)/2, bins=bins)
timebins, firs = fringe.frp_to_firs(frp, bins, aa2.get_freqs(), fq0=aa2.get_freqs()[len(freqs)/2])
_,blconj,_ = zsa.grid2ij(aa2.ant_layout)
if blconj[a.miriad.ij2bl(ij[0],ij[1])]: fir = {(ij[0],ij[1],POL):n.conj(firs)}
else: fir = {(ij[0],ij[1],POL):firs}
dij = n.transpose(data)
wij = n.ones(dij.shape,dtype=bool) #XXX flags are all true (times,freqs)
#dij and wij are (times,freqs)
_d,_w,_,_ = fringe.apply_frf(aa2,dij,wij,ij[0],ij[1],pol=POL,bins=bins,firs=fir)
_d = n.transpose(_d)
return _d
def getBaselines(freqs, intSeps, exampleDataFile, calFile='psa6622_v003'):
aa = a.cal.get_aa(calFile, freqs)
blstr, _, bl2sep = zsa.grid2ij(aa.ant_layout)
m, _, mdl,_= omni.from_npz(exampleDataFile)
bls = [(0,i) for i in intSeps]
for ij in mdl['xx'].keys():
bl = a.miriad.ij2bl(ij[0],ij[1])
try:
s = tuple(map(int,bl2sep[bl].split(',')))
except(KeyError):
continue
if s in bls and s[0] == 0:
bls[s[-1]-1] = ij
return bls
def getBaselines(freqs, intSeps, exampleDataFile, calFile='psa6622_v003'):
aa = a.cal.get_aa(calFile, freqs)
blstr, _, bl2sep = zsa.grid2ij(aa.ant_layout)
m, _, mdl, _ = omni.from_npz(exampleDataFile)
bls = [(0, i) for i in intSeps]
for ij in mdl['xx'].keys():
bl = a.miriad.ij2bl(ij[0], ij[1])
try:
s = tuple(map(int, bl2sep[bl].split(',')))
except (KeyError):
continue
if s in bls and s[0] == 0:
bls[s[-1] - 1] = ij
return bls
inttime = (t2-t1) * (3600*24)
del(uv)
afreqs = freqs.take(chans)
nchan = chans.size
fq = n.average(afreqs)
z = capo.pspec.f2z(fq)
# aa = a.cal.get_aa(opts.cal, n.array([.150]))
aa = a.cal.get_aa(opts.cal, afreqs)
bls, conj = capo.red.group_redundant_bls(aa.ant_layout)
jy2T = capo.pspec.jy2T(afreqs)
window = a.dsp.gen_window(nchan, WINDOW)
if not WINDOW == 'none':
window.shape = (nchan, 1)
sep2ij, blconj, bl2sep = zsa.grid2ij(aa.ant_layout)
# B = sdf * afreqs.size / capo.pfb.NOISE_EQUIV_BW[WINDOW]
# this is wrong if we aren't inverting
# the window post delay transform
# (or at least dividing out by the gain of the window)
# For windowed data, the FFT divides out by the full bandwidth, B, which is
# then squared.
# Proper normalization is to multiply by
# B**2 / (B / NoiseEqBand) = B * NoiseEqBand
# XXX NEED TO FIGURE OUT BW NORMALIZATION
B = sdf * afreqs.size * capo.pfb.NOISE_EQUIV_BW[WINDOW] # proper normalization
etas = n.fft.fftshift(capo.pspec.f2eta(afreqs))
# create etas (fourier dual to frequency)
# etas = capo.pspec.f2eta(afreqs) #create etas (fourier dual to frequency)
kpl = etas * capo.pspec.dk_deta(z) # 111
#! /usr/bin/env python -u
import numpy as n
import aipy as a
import optparse, sys
import capo.omni as omni, capo.zsa as zsa, capo.arp as arp
import pylab as p
o = optparse.OptionParser()
a.scripting.add_standard_options(o, cal=True)
opts, args = o.parse_args(sys.argv[1:])
pol = 'xx'
freqs = n.arange(.1, .2, .1 / 203)
aa = a.cal.get_aa('psa6622_v003', freqs)
blstr, _, bl2sep = zsa.grid2ij(aa.ant_layout)
_, _, mdl, _, jds, lsts, freqs = omni.from_npz(args[0])
seps = n.arange(1, 16) #* 15m = baseline lengths
bls = [(0, i) for i in seps]
sep2ij = {}
for ij in mdl['xx'].keys():
bl = a.miriad.ij2bl(ij[0], ij[1])
try:
s = tuple(map(int, bl2sep[bl].split(',')))
except (KeyError):
continue
if s in bls and s[0] == 0:
bls[s[-1] - 1] = ij
print bls
conjugate = [(0, 101), (0, 62), (0, 100), (0, 97), (12, 43), (57, 64)]
scalar = 1
if not DELAY:
# XXX this is a hack
if WINDOW == 'hamming':
scalar /= 3.67
elif WINDOW == 'blackman-harris':
scalar /= 5.72
print 'Freq:', fq
print 'z:', z
print 'B:', B
print 'scalar:', scalar
sys.stdout.flush()
# Prep FRF Stuff
antstr = 'cross'
_, blconj, _ = zsa.grid2ij(aa.ant_layout)
days = dsets.keys()
s,d,f = capo.miriad.read_files([dsets[days[0]][0]], antstr=antstr, polstr=POL) # read first file
ij = d.keys()[0] # use first baseline
if blconj[a.miriad.ij2bl(ij[0], ij[1])]:
# makes sure FRP will be the same whether bl is a conjugated one or not
if ij[0] < ij[1]:
temp = (ij[1], ij[0])
ij = temp
sep_type = bl2sep[a.miriad.ij2bl(ij[0], ij[1])]
# convert uvw in light-nanoseconds to m, (cosmo_units.c in m/s)
uvw = aa.get_baseline(ij[0], ij[1], src='z') * cosmo_units.c * 1e-9
bins = fringe.gen_frbins(inttime)
mychan = 101 # XXX use this to match frf_filter.py
frp, bins = fringe.aa_to_fr_profile(aa, ij, mychan, bins=bins)
timebins, firs = fringe.frp_to_firs(frp, bins, aa.get_freqs(),
(uvw, t2, (i, j)), d = uv.read()
while t1 == t2:
(uvw, t2, (i, j)), d = uv.read()
data_inttime = (t2 - t1) * (3600 * 24)
#manually calculate the inttime so frf time bins match data
if opts.inttime: inttime = opts.inttime
else: inttime = float(data_inttime)
del (uv)
#inttime=50.
#set channel to make frf
if opts.chan: mychan = int(opts.chan)
else: mychan = 101
#Get only the antennas of interest
sep2ij, blconj, bl2sep = zsa.grid2ij(aa.ant_layout)
print "Using normalization for old FRF: ", opts.alietal
print "Looking for baselines matching ", opts.ant
ants = [b[0] for b in a.scripting.parse_ants(opts.ant, nants)]
seps = [bl2sep[b] for b in ants]
seps = n.unique(seps)
print 'These are the spearations that we are going to use ', seps
print 'This is the channel we are using to build the frf: ', mychan
print 'Current inttime use for gen_frbins: ', inttime
#Get the fir filters for the separation used.
baselines = ''.join(sep2ij[sep] for sep in seps)
times, data, flags = zsa.get_dict_of_uv_data(args,
baselines,
pol,
if not DELAY:
# XXX this is a hack
if WINDOW == 'hamming': scalar /= 3.67
elif WINDOW == 'blackman-harris': scalar /= 5.72
print 'Freq:', fq
print 'z:', z
print 'B:', B
print 'scalar:', scalar
sys.stdout.flush()
#Acquire data
data_dict = {}
flg_dict = {}
conj_dict = {}
antstr = 'cross'
_, blconj, _ = zsa.grid2ij(aa.ant_layout)
days = dsets.keys()
lsts, data, flgs = {}, {}, {}
for k in days:
lsts[k], data[k], flgs[k] = capo.miriad.read_files(dsets[k],
antstr=antstr,
polstr=POL,
verbose=True)
lsts[k] = n.array(lsts[k]['lsts'])
for bl in data[k]:
d = n.array(data[k][bl][POL])[:,
chans] * jy2T #extract frequency range
flg = n.array(flgs[k][bl][POL])[:, chans]
key = (k, bl, POL)
data_dict[key] = d
flg_dict[key] = n.logical_not(flg)
#! /usr/bin/env python
import numpy as n
import aipy as a
import optparse,sys
import capo.omni as omni, capo.zsa as zsa, capo.arp as arp
import pylab as p, os
o = optparse.OptionParser()
a.scripting.add_standard_options(o, cal=True)
opts,args = o.parse_args(sys.argv[1:])
pol='xx'
freqs = n.arange(.1,.2,.1/203)
aa = a.cal.get_aa('psa6622_v003', freqs)
blstr, _, bl2sep = zsa.grid2ij(aa.ant_layout)
m, _, mdl,_= omni.from_npz(args[0])
seps = n.arange(1,16) #* 15m = baseline lengths
bls = [(0,i) for i in seps]
sep2ij = {}
for ij in mdl['xx'].keys():
bl = a.miriad.ij2bl(ij[0],ij[1])
try:
s = tuple(map(int,bl2sep[bl].split(',')))
except(KeyError):
continue
if s in bls and s[0] == 0:
bls[s[-1]-1] = ij
#print bls
conjugate = [(0,101), (0,62), (0,100), (0,97), (12,43), (57,64)]
