def dofit(xs, slambdas, alpha, sinbeta, gamma, delta, band, y):
xs = np.array(xs)
ok = np.isfinite(slambdas)
lsf = Fit.do_fit_wavelengths(xs[ok], lines[ok], alpha, sinbeta,
gamma, delta, band, y, error=slambdas[ok])
(order, pixel_y, alpha, sinbeta, gamma, delta) = lsf.params
print "order alpha sinbeta gamma delta"
print "%1.0i %5.7f %3.5f %3.2e %5.2f" % (order, alpha, sinbeta,
gamma, delta)
ll = Fit.wavelength_model(lsf.params, pix)
if DRAW:
pl.figure(3)
pl.clf()
pl.plot(ll, spec)
pl.title("Pixel %4.4f" % pos)
for lam in lines:
pl.axvline(lam, color='r')
pl.draw()
return [np.abs((
Fit.wavelength_model(lsf.params, xs[ok]) - lines[ok]))*1e4,
lsf.params]
def dofit(xs, slambdas, lines, alpha, sinbeta, gamma, delta, band):
xs = np.array(xs)
ok = np.isfinite(slambdas)
lsf = Fit.do_fit_wavelengths(xs[ok], lines[ok], alpha, sinbeta,
gamma, delta, band, error=slambdas[ok])
(order, alpha, sinbeta, gamma, delta) = lsf.params
print "order alpha sinbeta gamma delta"
print "%1.0i %5.7f %3.5f %3.2e %5.2f" % (order, alpha, sinbeta,
gamma, delta)
pix = np.arange(2048.)
ll = Fit.wavelength_model(lsf.params, pix)
return [np.abs((
Fit.wavelength_model(lsf.params, xs[ok]) - lines[ok]))*1e4,
lsf.params]
def dofit(xs, sxs, alpha, beta, band):
xs = np.array(xs)
sxs = np.array(sxs)/1000.
lsf = Fit.do_fit_wavelengths(xs, lines, alpha, beta, band, error=sxs)
(order, alpha, beta, gamma, delta) = lsf.params
print "alpha beta gamma delta"
print "%5.7f %3.5f %3.2e %5.2f" % (alpha, beta, gamma, delta)
ll = Fit.wavelength_model(lsf.params, pix)
if False:
pl.figure(3)
pl.clf()
pl.plot(ll, spec)
pl.title("Pixel %4.4f" % pos)
for lam in lines:
pl.axvline(lam, color='r')
pl.draw()
return [np.abs((Fit.wavelength_model(lsf.params, xs) - lines))/lines,
lsf.params]
