test_charon_interpolator
========================

.. py:module:: test_charon_interpolator


Attributes
----------

.. autoapisummary::

   test_charon_interpolator.columns
   test_charon_interpolator.mist
   test_charon_interpolator.aa
   test_charon_interpolator.grouped
   test_charon_interpolator.mod
   test_charon_interpolator.mod2
   test_charon_interpolator.age
   test_charon_interpolator.nn
   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
   test_charon_interpolator.output
   test_charon_interpolator.output2


Functions
---------

.. autoapisummary::

   test_charon_interpolator.figcmd
   test_charon_interpolator.figimass
   test_charon_interpolator.figimass_zoom


Module Contents
---------------

.. py:data:: columns
   :value: ['EEP', 'UBVRIplus', 'log10_isochrone_age_yr', 'initial_mass', '[Fe/H]_init', 'phase', 'star_mass']


.. py:data:: mist

.. py:data:: aa

.. py:data:: grouped

.. py:data:: mod

.. py:data:: mod2

.. py:data:: 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])


.. py:data:: nn
   :value: 100000


.. py:data:: age

.. py:data:: met

.. py:data:: min_mass1

.. py:data:: min_mass2

.. py:data:: imass1

.. py:data:: imass2

.. py:data:: imass3

.. py:data:: imass

.. py:data:: iso1

.. py:data:: iso2

.. py:data:: prop
   :value: 'EEP'


.. py:data:: output

.. py:data:: 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()



.. py:function:: figcmd(ax, G, BP, RP, G1, BP1, RP1)

.. py:function:: figimass(ax, mod, imass, G1, G2, iso1, iso2)

.. py:function:: figimass_zoom(ax, mod, imass, G, iso1, iso2)