fig2.savefig("align_zemax_%s_fig2_fit.png" % postfix)
fig3.savefig("align_zemax_%s_fig3_hist_dlambda.png" % postfix)
if 0:
from ecfit.ecfit import get_ordered_line_data, fit_2dspec, check_fit
d_x_wvl = {}
for order, z in echel.zdata.items():
xy_T = affine_tr.transform(np.array([z.x, z.y]).T)
x_T = xy_T[:,0]
d_x_wvl[order]=(x_T, z.wvl)
xl, yl, zl = get_ordered_line_data(d_x_wvl)
# xl : pixel
# yl : order
# zl : wvl * order
x_domain = [0, 2047]
orders_band = igrins_orders[band]
#orders = igrins_orders[band]
y_domain = [orders_band[0]-2, orders_band[-1]+2]
p = fit_2dspec(xl, yl, zl, x_degree=4, y_degree=3,
x_domain=x_domain, y_domain=y_domain)
if 0:
import matplotlib.pyplot as plt
fig = plt.figure(figsize=(12, 7))
check_fit(fig, xl, yl, zl, p, orders_band, d_x_wvl)
if 0:
postfix = "%s_%s" % (igrins_log.date, band)
fig1.savefig("align_zemax_%s_fig1_coverage.png" % postfix)
fig2.savefig("align_zemax_%s_fig2_fit.png" % postfix)
fig3.savefig("align_zemax_%s_fig3_hist_dlambda.png" % postfix)
if 0:
from ecfit.ecfit import get_ordered_line_data, fit_2dspec, check_fit
d_x_wvl = {}
for order, z in echel.zdata.items():
xy_T = affine_tr.transform(np.array([z.x, z.y]).T)
x_T = xy_T[:, 0]
d_x_wvl[order] = (x_T, z.wvl)
xl, yl, zl = get_ordered_line_data(d_x_wvl)
# xl : pixel
# yl : order
# zl : wvl * order
x_domain = [0, 2047]
orders_band = igrins_orders[band]
#orders = igrins_orders[band]
y_domain = [orders_band[0] - 2, orders_band[-1] + 2]
p = fit_2dspec(xl,
yl,
zl,
x_degree=4,
y_degree=3,
x_domain=x_domain,
y_domain=y_domain)
# xy_T = affine_tr.transform(np.array([z.x, z.y]).T)
# x_T = xy_T[:,0]
# d_x_wvl[order]=(x_T, z.wvl)
reidentified_lines_map = dict(zip(igrins_orders[band], reidentified_lines))
if band == "K":
json_name = "hitran_reidentified_K_%s.json" % igrins_log.date
r = json.load(open(json_name))
for i, s in r.items():
ss = reidentified_lines_map[int(i)]
ss0 = np.concatenate([ss[0], s["pixel"]])
ss1 = np.concatenate([ss[1], s["wavelength"]])
reidentified_lines_map[int(i)] = (ss0, ss1)
xl, yl, zl = get_ordered_line_data(reidentified_lines_map)
# xl : pixel
# yl : order
# zl : wvl * order
x_domain = [0, 2047]
orders_band = igrins_orders[band]
#orders = igrins_orders[band]
y_domain = [orders_band[0]-2, orders_band[-1]+2]
x_degree, y_degree = 4, 3
#x_degree, y_degree = 3, 2
p, m = fit_2dspec(xl, yl, zl, x_degree=x_degree, y_degree=y_degree,
x_domain=x_domain, y_domain=y_domain)
# filter out the line indices not well fit by the surface
# xy_T = affine_tr.transform(np.array([z.x, z.y]).T)
# x_T = xy_T[:,0]
# d_x_wvl[order]=(x_T, z.wvl)
reidentified_lines_map = dict(zip(igrins_orders[band], reidentified_lines))
if band == "K":
json_name = "hitran_reidentified_K_%s.json" % igrins_log.date
r = json.load(open(json_name))
for i, s in r.items():
ss = reidentified_lines_map[int(i)]
ss0 = np.concatenate([ss[0], s["pixel"]])
ss1 = np.concatenate([ss[1], s["wavelength"]])
reidentified_lines_map[int(i)] = (ss0, ss1)
xl, yl, zl = get_ordered_line_data(reidentified_lines_map)
# xl : pixel
# yl : order
# zl : wvl * order
x_domain = [0, 2047]
orders_band = igrins_orders[band]
#orders = igrins_orders[band]
y_domain = [orders_band[0] - 2, orders_band[-1] + 2]
x_degree, y_degree = 4, 3
#x_degree, y_degree = 3, 2
p, m = fit_2dspec(xl,
yl,
zl,
x_degree=x_degree,
y_degree=y_degree,