def bin_array_2d_super_smooth(x, y, nxbin, xlow, xhigh, nybin, ylow, yhigh,
n_per_smooth_fwhm=100,
completeness=None):
nx = len(x)
ny = len(y)
if nx != ny:
print 'Error: len(x) != len(y)'
return
xstep = float(xhigh-xlow)/nxbin
ystep = float(yhigh-ylow)/nybin
fwhm_list = (2.0 * N.sqrt(n_per_smooth_fwhm/(N.pi*N.arange(1,101))))
sigma_list = fwhm_list/2.3548
rmax = 4 * sigma_list[-1]
size = int(round(rmax)) * 2 + 1
gc = (size-1)/2
g_list = []
for sigma in sigma_list:
g = N.asarray(gaussian2d((size, size), 1.0, gc, gc, sigma, sigma))
g_list.append(g)
x_bin, y_bin, d_bin = bin_array_2d(x, y, nxbin, xlow, xhigh,
nybin, ylow, yhigh,
completeness)
N.putmask(d_bin, d_bin < 1, 1)
d_max = d_bin.max()
gindex_array = (100*d_bin / d_max).astype(N.int)
N.putmask(gindex_array, gindex_array < 0, 0)
N.putmask(gindex_array, gindex_array > 99, 99)
gindex_array_sorted = N.sort(N.ravel(gindex_array))
gindex_min = gindex_array_sorted[0]
gindex_max = gindex_array_sorted[-1]
print 'Smoothing FWHM varies between',
print '%3.2f and %3.2f bins'%(fwhm_list[gindex_min], fwhm_list[gindex_max])
d_bin_smooth = N.zeros((nybin+2*gc, nxbin+2*gc), N.float)
percent_prev = 0
print '%:',
for k in range(nx):
percent = int((100.0*k)/nx)
if percent/10 != percent_prev/10:
print percent,
percent_prev = percent
sys.stdout.flush()
jbin_index = int((x[k] - xlow)/xstep)
ibin_index = int((y[k] - ylow)/ystep)
if 0 <= jbin_index < nxbin and 0 <= ibin_index < nybin:
gindex = gindex_array[ibin_index, jbin_index]
d_bin_smooth[ibin_index:ibin_index+2*gc+1,
jbin_index:jbin_index+2*gc+1] += g_list[gindex]
print
d_bin_smooth = N.pi*(fwhm_list[gindex_min]/2.0)**2 * d_bin_smooth[gc:-gc, gc:-gc]
return x_bin, y_bin, d_bin_smooth, fwhm_list[gindex_min], fwhm_list[gindex_max]
def bin_array_2d_smooth(x, y, nxbin, xlow, xhigh, nybin, ylow, yhigh,
smooth_fwhm=10, completeness=None):
nx = len(x)
ny = len(y)
if nx != ny:
print 'Error: len(x) != len(y)'
return
xstep = float(xhigh-xlow)/nxbin
ystep = float(yhigh-ylow)/nybin
fwhm = smooth_fwhm
sigma = fwhm/2.3548
rmax = 4 * sigma
size = int(round(rmax)) * 2 + 1
gc = (size-1)/2
g = N.asarray(gaussian2d((size, size), 1.0, gc, gc, sigma, sigma))
x_bin = N.arange(nxbin) * xstep + xlow + xstep/2.0
y_bin = N.arange(nybin) * ystep + ylow + ystep/2.0
d_bin = N.zeros((nybin+2*gc, nxbin+2*gc), N.float)
percent_prev = 0
print '%:',
for k in range(nx):
percent = int((100.0*k)/nx)
if percent/10 != percent_prev/10:
print percent,
percent_prev = percent
sys.stdout.flush()
jbin_index = int((x[k] - xlow)/xstep)
ibin_index = int((y[k] - ylow)/ystep)
if completeness is None:
c = 1
else:
c = completeness[k]
if 0 <= jbin_index < nxbin and 0 <= ibin_index < nybin:
d_bin[ibin_index:ibin_index+2*gc+1,
jbin_index:jbin_index+2*gc+1] += g/c
print
d_bin = N.pi*(smooth_fwhm/2.0)**2 * d_bin[gc:-gc, gc:-gc]
return x_bin, y_bin, d_bin
import gaussian # SPB's own function
# produce a symmetrical 2d gaussian centred in stamp
# with sigma = 1 pixel, hence FWHM = 2.355 pixels.
d = gaussian.gaussian2d((25,25), 1.0, 12.0, 12.0, 1.0, 1.0)
pyfits.writeto('psf.fits', d)
