test_charon_interpolator
Attributes
w1,w2,w3,w4 = mod.get_weights(met, np.log10(age)+9,metlow, methigh, lower,upper ) |
Functions
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Module Contents
- test_charon_interpolator.columns = ['EEP', 'UBVRIplus', 'log10_isochrone_age_yr', 'initial_mass', '[Fe/H]_init', 'phase', 'star_mass']
- test_charon_interpolator.mist
- test_charon_interpolator.aa
- test_charon_interpolator.grouped
- test_charon_interpolator.mod
- test_charon_interpolator.mod2
- test_charon_interpolator.age
plt.semilogy(mod.tips.loc[-0.25].tip0,”r+”) plt.semilogy(mod.tips.loc[-0.25].tip1,’g+’) plt.semilogy(mod.tips.loc[-0.25].tip2,’b+’) plt.semilogy(age, mod.tips0_func(-0.25, age, grid=False), ‘r’) plt.semilogy(age, mod.tips1_func(-0.25, age, grid=False), ‘g’) plt.semilogy(age, mod.tips2_func(-0.25, age, grid=False), ‘b’) plt.xlim([7,10]) plt.ylim([0.5,25])
- test_charon_interpolator.nn = 100000
- test_charon_interpolator.age
- test_charon_interpolator.met
- test_charon_interpolator.min_mass1
- test_charon_interpolator.min_mass2
- test_charon_interpolator.imass1
- test_charon_interpolator.imass2
- test_charon_interpolator.imass3
- test_charon_interpolator.imass
- test_charon_interpolator.iso1
- test_charon_interpolator.iso2
- test_charon_interpolator.prop = 'EEP'
- test_charon_interpolator.output
- test_charon_interpolator.output2
w1,w2,w3,w4 = mod.get_weights(met, np.log10(age)+9,metlow, methigh, lower,upper ) print(w1[0], w2[0], w3[0], w4[0])
mass1 = mod.get_modified_mass(imass,met, np.log10(age)+9, methigh, lower) mass2 = mod.get_modified_mass(imass,met, np.log10(age)+9, methigh, upper) pp = { prop, “Gaia_G_EDR3”, “Gaia_BP_EDR3”, “Gaia_RP_EDR3”} p_f1_charon, in_grid1 = mod.interp_props(mass1, methigh, lower, pp) p_f2_charon, in_grid2 = mod.interp_props(mass2, methigh, upper, pp)
plt.plot(aa.initial_mass, aa[prop],’g’) iprop = list(pp).index(prop) plt.plot(imass, p_f1_charon[:,iprop],’b’) plt.plot(mass1, p_f1_charon[:,iprop],’b–‘) plt.plot(imass, p_f2_charon[:,iprop],’r’) plt.plot(mass2, p_f2_charon[:,iprop],’r–‘)
#plt.plot(imass, output[prop],’g’) #plt.plot(imass, output2[prop],’r’) plt.axvline(mod.endp_func(met[0], np.log10(age[0])+9, grid=False), color=”k”) plt.axvline(mod.tips2_func(met[0], np.log10(age[0])+9, grid=False), color=”k”) plt.axvline(mod.endp_func(met[0], lower[0], grid=False), color=”k”, linestyle=”:”) plt.axvline(mod.tips2_func(met[0], lower[0], grid=False), color=”k”, linestyle=”:”) plt.axvline(mod.endp_func(met[0], upper[0], grid=False), color=”k”, linestyle=”–“) plt.axvline(mod.tips2_func(met[0], upper[0], grid=False), color=”k”,linestyle=”–“)
plt.figure() bb1 = mod.grouped_iso.get_group((methigh[0], lower[0])) bb2 = mod.grouped_iso.get_group((methigh[0], upper[0]))
plt.plot(bb1.EEP, bb1[prop],’r’) plt.plot(bb2.EEP, bb2[prop],’g’) plt.plot(aa.EEP, aa[prop],’b’)
ig = list(pp).index(“Gaia_G_EDR3”) irp = list(pp).index(“Gaia_RP_EDR3”) ibp = list(pp).index(“Gaia_BP_EDR3”) plt.figure()
plt.plot(bb2.Gaia_BP_EDR3-bb2.Gaia_RP_EDR3, bb2.Gaia_G_EDR3,’k’, lw=0.5)
plt.plot(aa.Gaia_BP_EDR3-aa.Gaia_RP_EDR3, aa.Gaia_G_EDR3,’g’, lw=8, alpha=0.2) plt.plot(aa.Gaia_BP_EDR3-aa.Gaia_RP_EDR3, aa.Gaia_G_EDR3,’g’, lw=8, alpha=0.2) plt.plot(aa.Gaia_BP_EDR3-aa.Gaia_RP_EDR3, aa.Gaia_G_EDR3,’g’, lw=8, alpha=0.2) plt.plot(output[“Gaia_BP_EDR3”]-output[“Gaia_RP_EDR3”], output[“Gaia_G_EDR3”],’g.’,ms=1) plt.plot(output2[“Gaia_BP_EDR3”]-output2[“Gaia_RP_EDR3”], output2[“Gaia_G_EDR3”],’r.’, ms=1) plt.plot(p_f1_charon[:,ibp]-p_f1_charon[:,irp], p_f1_charon[:,ig],’c’, lw=0.5) plt.plot(p_f2_charon[:,ibp]-p_f2_charon[:,irp], p_f2_charon[:,ig],’b’, lw=0.5) print(len(aa)) print(max(output[“Gaia_BP_EDR3”])) print(len(output[“Gaia_BP_EDR3”])) plt.gca().invert_yaxis()
- test_charon_interpolator.figcmd(ax, G, BP, RP, G1, BP1, RP1)
- test_charon_interpolator.figimass(ax, mod, imass, G1, G2, iso1, iso2)
- test_charon_interpolator.figimass_zoom(ax, mod, imass, G, iso1, iso2)