def test_difference(self):
h, b, w, hifit = old_fringe.get_optimal_kernel_at_ref(self.aa, 100, (1, 4), binwidth=.00005)
interps = old_fringe.get_beam_w_fr(self.aa, (1,4), ref_chan=100)
t,firs, frbins, frspace = old_fringe.get_fringe_rate_kernels(interps, 42.9, 399)
print len(frbins), frbins[0], frbins[-1]
p.subplot(121)
p.plot(t, firs[100], '+')
p.plot(t, n.abs(firs[100]), '+')
p.subplot(122)
p.plot(b, h, 'k+')
p.plot(frbins, frspace[100], 'b+', label='old')
p.legend()
def test_difference(self):
h, b, w, hifit = old_fringe.get_optimal_kernel_at_ref(self.aa,
100, (1, 4),
binwidth=.00005)
interps = old_fringe.get_beam_w_fr(self.aa, (1, 4), ref_chan=100)
t, firs, frbins, frspace = old_fringe.get_fringe_rate_kernels(
interps, 42.9, 399)
print len(frbins), frbins[0], frbins[-1]
p.subplot(121)
p.plot(t, firs[100], '+')
p.plot(t, n.abs(firs[100]), '+')
p.subplot(122)
p.plot(b, h, 'k+')
p.plot(frbins, frspace[100], 'b+', label='old')
p.legend()
def test_get_optimal_kernel_at_ref(self):
ch = 100
binwidth = .00005
freq = self.aa.get_afreqs()[ch]
bin_edges = n.arange(-.01 + binwidth / 2, .01, binwidth)
h = a.healpix.HealpixMap(nside=64)
xyz = h.px2crd(n.arange(h.map.size), ncrd=3)
top_x, top_y, top_z = n.dot(self.aa._eq2zen, xyz)
_bmx = self.aa[0].bm_response((top_x, top_y, top_z), pol='x')[ch]
_bmy = self.aa[0].bm_response((top_x, top_y, top_z), pol='y')[ch]
bmxx = n.where(top_z > 0, _bmx**2, 0)
bmyy = n.where(top_z > 0, _bmy**2, 0)
bm_I = 0.5 * (bmxx + bmyy)
lat = self.aa.lat
DIM = 800
RES = .5
SIZE = DIM / RES
im = a.img.Img(DIM, res=RES)
def proj_hmap(dat, mode='e'):
h.map = dat
#if mode == 'e': x,y,z = im.get_eq(dec=aa.lat, center=(SIZE/2,SIZE/2))
if mode == 'e':
x, y, z = im.get_eq(dec=lat, center=(SIZE / 2, SIZE / 2))
elif mode == 't':
x, y, z = im.get_top(center=(SIZE / 2, SIZE / 2))
else:
raise ValueError(mode)
v = n.logical_not(x.mask)
x, y, z = x.flatten(), y.flatten(), z.flatten()
d = h[x, y, z]
d.shape = (SIZE, SIZE)
d = n.where(v, d, n.NaN)
return d
m = Basemap(projection='ortho', lat_0=lat, lon_0=180, rsphere=1.)
def plot_hmap(dat, mode='log', mx=0, drng=3):
d = proj_hmap(dat, 'e')
if mode == 'log':
d = n.log10(n.abs(d).clip(10**(mx - drng), n.Inf))
elif mode == 'real':
d = d.real
m.imshow(d,
vmax=mx,
vmin=mx - drng,
origin='lower',
interpolation='bicubic',
cmap='jet')
p.subplot(121)
plot_hmap(bm_I)
m.drawmapboundary(linewidth=2)
m.drawmeridians(n.arange(0, 360, 30), linewidth=2)
m.drawparallels(n.arange(-90, 90, 30), linewidth=2)
print bm_I.sum() * (4 * n.pi / h.npix()),
bm_I2 = bm_I**2
print bm_I.sum() * (4 * n.pi / h.npix())
p.subplot(122)
plot_hmap(bm_I2)
m.drawmapboundary(linewidth=2)
m.drawmeridians(n.arange(0, 360, 30), linewidth=2)
m.drawparallels(n.arange(-90, 90, 30), linewidth=2)
p.show()
xyz = (xyz[1], xyz[0], xyz[2])
bl = self.aa.get_baseline(1, 4, 'r') * freq
print 'Baseline:', bl
fng = fringe.mk_fng(bl, *xyz)
h_I, bin_edges = n.histogram(fng, bins=bin_edges, weights=bm_I2)
h_I = n.sqrt(h_I)
h_I /= h_I.max()
p.plot(bin_edges[:-1], h_I, label='rederived')
h_I, bins, wgt, (cen, wid) = fringe.get_optimal_kernel_at_ref(
self.aa, ch, (1, 4), binwidth=binwidth)
p.plot(bins, h_I, label='frf_conv')
p.plot(bins, fringe.gauss(bins, cen, wid), label='gaussian')
p.legend(loc='best')
p.show()
def test_get_optimal_kernel_at_ref(self):
ch = 100
binwidth=.00005
freq = self.aa.get_afreqs()[ch]
bin_edges = n.arange(-.01+binwidth/2,.01,binwidth)
h = a.healpix.HealpixMap(nside=64)
xyz = h.px2crd(n.arange(h.map.size), ncrd=3)
top_x, top_y, top_z = n.dot(self.aa._eq2zen, xyz)
_bmx = self.aa[0].bm_response((top_x,top_y,top_z), pol='x')[ch]
_bmy = self.aa[0].bm_response((top_x,top_y,top_z), pol='y')[ch]
bmxx = n.where(top_z > 0, _bmx**2, 0)
bmyy = n.where(top_z > 0, _bmy**2, 0)
bm_I = 0.5 * (bmxx + bmyy)
lat = self.aa.lat
DIM = 800
RES = .5
SIZE = DIM / RES
im = a.img.Img(DIM, res=RES)
def proj_hmap(dat, mode='e'):
h.map = dat
#if mode == 'e': x,y,z = im.get_eq(dec=aa.lat, center=(SIZE/2,SIZE/2))
if mode == 'e': x,y,z = im.get_eq(dec=lat, center=(SIZE/2,SIZE/2))
elif mode == 't': x,y,z = im.get_top(center=(SIZE/2,SIZE/2))
else: raise ValueError(mode)
v = n.logical_not(x.mask)
x,y,z = x.flatten(), y.flatten(), z.flatten()
d = h[x,y,z]
d.shape = (SIZE,SIZE)
d = n.where(v, d, n.NaN)
return d
m = Basemap(projection='ortho', lat_0=lat, lon_0=180, rsphere=1.)
def plot_hmap(dat, mode='log', mx=0, drng=3):
d = proj_hmap(dat,'e')
if mode == 'log': d = n.log10(n.abs(d).clip(10**(mx-drng),n.Inf))
elif mode == 'real': d = d.real
m.imshow(d, vmax=mx, vmin=mx-drng, origin='lower', interpolation='bicubic', cmap='jet')
p.subplot(121)
plot_hmap(bm_I)
m.drawmapboundary(linewidth=2)
m.drawmeridians(n.arange(0, 360, 30), linewidth=2)
m.drawparallels(n.arange(-90,90,30), linewidth=2)
print bm_I.sum()*(4*n.pi/h.npix()),
bm_I2 = bm_I**2
print bm_I.sum()*(4*n.pi/h.npix())
p.subplot(122)
plot_hmap(bm_I2)
m.drawmapboundary(linewidth=2)
m.drawmeridians(n.arange(0, 360, 30), linewidth=2)
m.drawparallels(n.arange(-90,90,30), linewidth=2)
p.show()
xyz = (xyz[1], xyz[0], xyz[2])
bl = self.aa.get_baseline(1,4,'r') * freq
print 'Baseline:', bl
fng = fringe.mk_fng(bl, *xyz)
h_I, bin_edges = n.histogram(fng, bins=bin_edges, weights=bm_I2)
h_I = n.sqrt(h_I)
h_I /= h_I.max()
p.plot(bin_edges[:-1], h_I, label='rederived')
h_I, bins, wgt, (cen,wid) = fringe.get_optimal_kernel_at_ref(self.aa, ch, (1,4), binwidth=binwidth)
p.plot(bins, h_I, label='frf_conv')
p.plot(bins, fringe.gauss(bins, cen, wid), label='gaussian')
p.legend(loc='best')
p.show()
