for co2mult in mults:
co2vmr = co2mult * atm_pt[(atm, 2, 'co2')]
int_fun = interp_coeffs[(nam, 'int_fun')]
sc = interp_coeffs[(nam, 'signc')]
if int_fun.ndim == 1:
interplog = int_fun[ialt](co2vmr[ialt])
else:
interplog = np.array(
[intfu(co2vmr[ialt]) for intfu in int_fun[..., ialt]])
print(co2mult, interplog)
coefff.append(interplog)
coefff = np.stack(coefff)
colors = npl.color_set(n_alts_trlo)
fig, ax = plt.subplots()
ax.grid()
for j, col in zip(range(n_alts_trlo), colors):
ax.plot(mults, coefff[:, j], color=col, linewidth=0.5)
#plt.scatter(coeffs['co2profs'][:, ialt]/coeffs['co2profs'][1, ialt], -np.log(coeffs[nam][:, j, ialt]/coeffs['co2profs'][:, ialt]))
ax.set_title(nam + '[:, {}]'.format(ialt))
ax.set_xlabel('x CO2')
figs.append(fig)
axes.append(ax)
npl.adjust_ax_scale(axes)
npl.plot_pdfpages(cart_out_4 + 'check_{}_all.pdf'.format(nam), figs)
###### Check. correlazione fra acoeff e cose
hr_calc_v2 = npl.hr_from_xi(xis2_unif, atm, cco2, all_coeffs = all_coeffs, atm_pt = atm_pt, allatms = allatms, n_alts = n_alts)
# hr_ab_orig = npl.hr_atm_calc(atm, cco2)[:n_alts]
hr_calc_var = np.zeros(n_alts)
for ialt in range(n_alts):#range(n_alts_lte):
xis_var = best_var[(cco2, ialt)]
hr_calc_var[ialt] = npl.hr_from_xi_at_x0(xis_var, atm, cco2, ialt)
tit = 'co2: {} - atm: {}'.format(cco2, atm)
xlab = 'CR (K/day)'
ylab = 'Alt (km)'
# hrs = [hr_ref, hr_calc, hr_calc_v2, hr_calc_var]
# labels = ['ref', 'fit unif 1', 'fit unif 2', 'fit var']
hrs = [hr_ref, hr_calc_v2, hr_calc_var]
labels = ['ref', 'fit unif', 'fit var']
fig, a0, a1 = npl.manuel_plot(alts, hrs, labels, xlabel = xlab, ylabel = ylab, title = tit, xlimdiff = (-2., 2.))
# fig = plt.figure()
# plt.plot(hr_ref, alts, label = 'ref')
# plt.plot(hr_calc, alts, label = 'calc')
# plt.plot(hr_calc-hr_ref, alts, label = 'diff')
# plt.legend()
# plt.grid()
# plt.title('co2: {} - atm: {}'.format(cco2, atm))
figs.append(fig)
a0s.append(a0)
a1s.append(a1)
npl.adjust_ax_scale(a0s)
npl.adjust_ax_scale(a1s)
npl.plot_pdfpages(cart_out + 'check_newparam_LTE_unifit2_vs_varfit.pdf', figs)