Color-magnitude diagram: broadband filters

This tutorial shows how to create a color-magnitude diagram which combines the photometry of field and young/low-gravity objects, synthetic photometry computed from isochrones and model spectra, and photometry of directly imaged planets and brown dwarfs.

Initiating species

We start by importing the required modules.

[1]:
import urllib.request
import numpy as np
import species

Next, we initiate the species workflow and create an instance of Database.

[2]:
species.SpeciesInit()
database = species.Database()
Initiating species v0.3.1... [DONE]
Creating species_config.ini... [DONE]
Database: /Users/tomasstolker/applications/species/docs/tutorials/species_database.hdf5
Data folder: /Users/tomasstolker/applications/species/docs/tutorials/data
Working folder: /Users/tomasstolker/applications/species/docs/tutorials
Creating species_database.hdf5... [DONE]
Creating data folder... [DONE]

Adding data to the database

Available photometric data of directly imaged planets and brown dwarfs are added to the database with add_companion by setting name=None. These data are extracted from the dictionary with magnitudes in the data.companions module.

[3]:
database.add_companion(name=None)
Downloading Vega spectrum (270 kB)... [DONE]
Adding Vega spectrum... [DONE]
Adding filter: LCO/VisAO.Ys... [DONE]
Adding filter: Paranal/NACO.J... [DONE]
Adding filter: Gemini/NICI.ED286... [DONE]
Adding filter: Paranal/NACO.H... [DONE]
Adding filter: Paranal/NACO.Ks... [DONE]
Adding filter: Paranal/NACO.NB374... [DONE]
Adding filter: Paranal/NACO.Lp... [DONE]
Adding filter: Paranal/NACO.NB405... [DONE]
Adding filter: Paranal/NACO.Mp... [DONE]
Adding filter: Paranal/SPHERE.IRDIS_D_K12_1... [DONE]
Adding filter: Paranal/SPHERE.IRDIS_D_K12_2... [DONE]
Adding object: beta Pic b
   - Distance (pc) = 19.75 +/- 0.13
   - LCO/VisAO.Ys:
      - Apparent magnitude = 15.53 +/- 0.34
      - Flux (W m-2 um-1) = 4.27e-15 +/- 1.36e-15
   - Paranal/NACO.J:
      - Apparent magnitude = 14.11 +/- 0.21
      - Flux (W m-2 um-1) = 6.87e-15 +/- 1.34e-15
   - Gemini/NICI.ED286:
      - Apparent magnitude = 13.18 +/- 0.15
      - Flux (W m-2 um-1) = 6.99e-15 +/- 9.69e-16
   - Paranal/NACO.H:
      - Apparent magnitude = 13.32 +/- 0.14
      - Flux (W m-2 um-1) = 5.47e-15 +/- 7.08e-16
   - Paranal/NACO.Ks:
      - Apparent magnitude = 12.64 +/- 0.11
      - Flux (W m-2 um-1) = 4.04e-15 +/- 4.10e-16
   - Paranal/NACO.NB374:
      - Apparent magnitude = 11.25 +/- 0.23
      - Flux (W m-2 um-1) = 1.69e-15 +/- 3.61e-16
   - Paranal/NACO.Lp:
      - Apparent magnitude = 11.30 +/- 0.06
      - Flux (W m-2 um-1) = 1.59e-15 +/- 8.79e-17
   - Paranal/NACO.NB405:
      - Apparent magnitude = 10.98 +/- 0.05
      - Flux (W m-2 um-1) = 1.61e-15 +/- 7.42e-17
   - Paranal/NACO.Mp:
      - Apparent magnitude = 11.10 +/- 0.12
      - Flux (W m-2 um-1) = 7.86e-16 +/- 8.70e-17
   - Paranal/SPHERE.IRDIS_D_K12_1:
      - Apparent magnitude = 12.57 +/- 0.00
      - Flux (W m-2 um-1) = 4.56e-15 +/- 1.26e-17
   - Paranal/SPHERE.IRDIS_D_K12_2:
      - Apparent magnitude = 12.21 +/- 0.00
      - Flux (W m-2 um-1) = 4.92e-15 +/- 9.05e-18
Adding filter: Paranal/SPHERE.IRDIS_D_H23_2... [DONE]
Adding filter: Paranal/SPHERE.IRDIS_D_H23_3... [DONE]
Adding object: HIP 65426 b
   - Distance (pc) = 109.21 +/- 0.75
   - Paranal/SPHERE.IRDIS_D_H23_2:
      - Apparent magnitude = 17.94 +/- 0.05
      - Flux (W m-2 um-1) = 8.73e-17 +/- 4.02e-18
   - Paranal/SPHERE.IRDIS_D_H23_3:
      - Apparent magnitude = 17.58 +/- 0.06
      - Flux (W m-2 um-1) = 1.03e-16 +/- 5.70e-18
   - Paranal/SPHERE.IRDIS_D_K12_1:
      - Apparent magnitude = 17.01 +/- 0.09
      - Flux (W m-2 um-1) = 7.63e-17 +/- 6.33e-18
   - Paranal/SPHERE.IRDIS_D_K12_2:
      - Apparent magnitude = 16.79 +/- 0.09
      - Flux (W m-2 um-1) = 7.21e-17 +/- 5.98e-18
   - Paranal/NACO.Lp:
      - Apparent magnitude = 15.33 +/- 0.12
      - Flux (W m-2 um-1) = 3.88e-17 +/- 4.30e-18
   - Paranal/NACO.NB405:
      - Apparent magnitude = 15.23 +/- 0.22
      - Flux (W m-2 um-1) = 3.21e-17 +/- 6.55e-18
   - Paranal/NACO.Mp:
      - Apparent magnitude = 14.65 +/- 0.29
      - Flux (W m-2 um-1) = 2.99e-17 +/- 8.07e-18
Adding filter: MKO/NSFCam.J... [DONE]
Adding filter: MKO/NSFCam.H... [DONE]
Adding filter: MKO/NSFCam.K... [DONE]
Adding filter: Paranal/SPHERE.IRDIS_B_H... [DONE]
Adding filter: Keck/NIRC2.Lp... [DONE]
Adding filter: Keck/NIRC2.Ms... [DONE]
Adding object: 51 Eri b
   - Distance (pc) = 29.78 +/- 0.12
   - MKO/NSFCam.J:
      - Apparent magnitude = 19.04 +/- 0.40
      - Flux (W m-2 um-1) = 7.52e-17 +/- 2.83e-17
   - MKO/NSFCam.H:
      - Apparent magnitude = 18.99 +/- 0.21
      - Flux (W m-2 um-1) = 3.12e-17 +/- 6.07e-18
   - MKO/NSFCam.K:
      - Apparent magnitude = 18.67 +/- 0.19
      - Flux (W m-2 um-1) = 1.42e-17 +/- 2.49e-18
   - Paranal/SPHERE.IRDIS_B_H:
      - Apparent magnitude = 19.45 +/- 0.29
      - Flux (W m-2 um-1) = 2.06e-17 +/- 5.57e-18
   - Paranal/SPHERE.IRDIS_D_H23_2:
      - Apparent magnitude = 18.41 +/- 0.26
      - Flux (W m-2 um-1) = 5.66e-17 +/- 1.37e-17
   - Paranal/SPHERE.IRDIS_D_K12_1:
      - Apparent magnitude = 17.55 +/- 0.14
      - Flux (W m-2 um-1) = 4.64e-17 +/- 6.00e-18
   - Keck/NIRC2.Lp:
      - Apparent magnitude = 16.20 +/- 0.11
      - Flux (W m-2 um-1) = 1.79e-17 +/- 1.81e-18
   - Keck/NIRC2.Ms:
      - Apparent magnitude = 16.10 +/- 0.50
      - Flux (W m-2 um-1) = 8.47e-18 +/- 4.04e-18
Adding filter: Subaru/CIAO.z... [DONE]
Adding filter: Paranal/SPHERE.IRDIS_B_J...
/Users/tomasstolker/applications/species/species/data/filters.py:169: UserWarning: The minimum transmission value of Subaru/CIAO.z is smaller than zero (-1.80e-03). Wavelengths with negative transmission values will be removed.
  warnings.warn(f'The minimum transmission value of {filter_id} is smaller than zero '
 [DONE]
Adding filter: Keck/NIRC2.H... [DONE]
Adding filter: Keck/NIRC2.Ks... [DONE]
Adding object: HR 8799 b
   - Distance (pc) = 41.29 +/- 0.15
   - Subaru/CIAO.z:
      - Apparent magnitude = 21.22 +/- 0.29
      - Flux (W m-2 um-1) = 1.93e-17 +/- 5.22e-18
   - Paranal/SPHERE.IRDIS_B_J:
      - Apparent magnitude = 19.78 +/- 0.09
      - Flux (W m-2 um-1) = 3.90e-17 +/- 3.24e-18
   - Keck/NIRC2.H:
      - Apparent magnitude = 18.05 +/- 0.09
      - Flux (W m-2 um-1) = 7.32e-17 +/- 6.08e-18
   - Paranal/SPHERE.IRDIS_D_H23_2:
      - Apparent magnitude = 18.08 +/- 0.14
      - Flux (W m-2 um-1) = 7.67e-17 +/- 9.92e-18
   - Paranal/SPHERE.IRDIS_D_H23_3:
      - Apparent magnitude = 17.78 +/- 0.10
      - Flux (W m-2 um-1) = 8.57e-17 +/- 7.91e-18
   - Keck/NIRC2.Ks:
      - Apparent magnitude = 17.03 +/- 0.08
      - Flux (W m-2 um-1) = 6.98e-17 +/- 5.15e-18
   - Paranal/SPHERE.IRDIS_D_K12_1:
      - Apparent magnitude = 17.15 +/- 0.06
      - Flux (W m-2 um-1) = 6.71e-17 +/- 3.71e-18
   - Paranal/SPHERE.IRDIS_D_K12_2:
      - Apparent magnitude = 16.97 +/- 0.09
      - Flux (W m-2 um-1) = 6.11e-17 +/- 5.07e-18
   - Paranal/NACO.Lp:
      - Apparent magnitude = 15.52 +/- 0.10
      - Flux (W m-2 um-1) = 3.26e-17 +/- 3.01e-18
   - Paranal/NACO.NB405:
      - Apparent magnitude = 14.82 +/- 0.18
      - Flux (W m-2 um-1) = 4.69e-17 +/- 7.80e-18
   - Keck/NIRC2.Ms:
      - Apparent magnitude = 16.05 +/- 0.30
      - Flux (W m-2 um-1) = 8.87e-18 +/- 2.48e-18
Adding object: HR 8799 c
   - Distance (pc) = 41.29 +/- 0.15
   - Paranal/SPHERE.IRDIS_B_J:
      - Apparent magnitude = 18.60 +/- 0.13
      - Flux (W m-2 um-1) = 1.16e-16 +/- 1.39e-17
   - Keck/NIRC2.H:
      - Apparent magnitude = 17.06 +/- 0.13
      - Flux (W m-2 um-1) = 1.82e-16 +/- 2.19e-17
   - Paranal/SPHERE.IRDIS_D_H23_2:
      - Apparent magnitude = 17.09 +/- 0.12
      - Flux (W m-2 um-1) = 1.91e-16 +/- 2.12e-17
   - Paranal/SPHERE.IRDIS_D_H23_3:
      - Apparent magnitude = 16.78 +/- 0.10
      - Flux (W m-2 um-1) = 2.15e-16 +/- 1.99e-17
   - Keck/NIRC2.Ks:
      - Apparent magnitude = 16.11 +/- 0.08
      - Flux (W m-2 um-1) = 1.63e-16 +/- 1.20e-17
   - Paranal/SPHERE.IRDIS_D_K12_1:
      - Apparent magnitude = 16.19 +/- 0.05
      - Flux (W m-2 um-1) = 1.62e-16 +/- 7.48e-18
   - Paranal/SPHERE.IRDIS_D_K12_2:
      - Apparent magnitude = 15.86 +/- 0.07
      - Flux (W m-2 um-1) = 1.70e-16 +/- 1.10e-17
   - Paranal/NACO.Lp:
      - Apparent magnitude = 14.65 +/- 0.11
      - Flux (W m-2 um-1) = 7.27e-17 +/- 7.38e-18
   - Paranal/NACO.NB405:
      - Apparent magnitude = 13.97 +/- 0.11
      - Flux (W m-2 um-1) = 1.03e-16 +/- 1.04e-17
   - Keck/NIRC2.Ms:
      - Apparent magnitude = 15.03 +/- 0.14
      - Flux (W m-2 um-1) = 2.27e-17 +/- 2.93e-18
Adding object: HR 8799 d
   - Distance (pc) = 41.29 +/- 0.15
   - Paranal/SPHERE.IRDIS_B_J:
      - Apparent magnitude = 18.59 +/- 0.37
      - Flux (W m-2 um-1) = 1.17e-16 +/- 4.06e-17
   - Keck/NIRC2.H:
      - Apparent magnitude = 16.71 +/- 0.24
      - Flux (W m-2 um-1) = 2.52e-16 +/- 5.61e-17
   - Paranal/SPHERE.IRDIS_D_H23_2:
      - Apparent magnitude = 17.02 +/- 0.17
      - Flux (W m-2 um-1) = 2.04e-16 +/- 3.20e-17
   - Paranal/SPHERE.IRDIS_D_H23_3:
      - Apparent magnitude = 16.85 +/- 0.16
      - Flux (W m-2 um-1) = 2.02e-16 +/- 2.99e-17
   - Keck/NIRC2.Ks:
      - Apparent magnitude = 16.09 +/- 0.12
      - Flux (W m-2 um-1) = 1.66e-16 +/- 1.84e-17
   - Paranal/SPHERE.IRDIS_D_K12_1:
      - Apparent magnitude = 16.20 +/- 0.07
      - Flux (W m-2 um-1) = 1.61e-16 +/- 1.04e-17
   - Paranal/SPHERE.IRDIS_D_K12_2:
      - Apparent magnitude = 15.84 +/- 0.10
      - Flux (W m-2 um-1) = 1.73e-16 +/- 1.60e-17
   - Paranal/NACO.Lp:
      - Apparent magnitude = 14.55 +/- 0.14
      - Flux (W m-2 um-1) = 7.97e-17 +/- 1.03e-17
   - Paranal/NACO.NB405:
      - Apparent magnitude = 13.87 +/- 0.15
      - Flux (W m-2 um-1) = 1.12e-16 +/- 1.56e-17
   - Keck/NIRC2.Ms:
      - Apparent magnitude = 14.65 +/- 0.35
      - Flux (W m-2 um-1) = 3.22e-17 +/- 1.06e-17
Adding object: HR 8799 e
   - Distance (pc) = 41.29 +/- 0.15
   - Paranal/SPHERE.IRDIS_B_J:
      - Apparent magnitude = 18.40 +/- 0.21
      - Flux (W m-2 um-1) = 1.39e-16 +/- 2.71e-17
   - Paranal/SPHERE.IRDIS_D_H23_2:
      - Apparent magnitude = 16.91 +/- 0.20
      - Flux (W m-2 um-1) = 2.25e-16 +/- 4.18e-17
   - Paranal/SPHERE.IRDIS_D_H23_3:
      - Apparent magnitude = 16.68 +/- 0.21
      - Flux (W m-2 um-1) = 2.36e-16 +/- 4.59e-17
   - Keck/NIRC2.Ks:
      - Apparent magnitude = 15.91 +/- 0.22
      - Flux (W m-2 um-1) = 1.96e-16 +/- 4.00e-17
   - Paranal/SPHERE.IRDIS_D_K12_1:
      - Apparent magnitude = 16.12 +/- 0.10
      - Flux (W m-2 um-1) = 1.73e-16 +/- 1.60e-17
   - Paranal/SPHERE.IRDIS_D_K12_2:
      - Apparent magnitude = 15.82 +/- 0.11
      - Flux (W m-2 um-1) = 1.76e-16 +/- 1.79e-17
   - Paranal/NACO.Lp:
      - Apparent magnitude = 14.49 +/- 0.21
      - Flux (W m-2 um-1) = 8.42e-17 +/- 1.64e-17
   - Paranal/NACO.NB405:
      - Apparent magnitude = 13.72 +/- 0.20
      - Flux (W m-2 um-1) = 1.29e-16 +/- 2.39e-17
Adding filter: Gemini/GPI.H... [DONE]
Adding filter: Gemini/GPI.K1... [DONE]
Adding object: HD 95086 b
   - Distance (pc) = 86.44 +/- 0.24
   - Gemini/GPI.H:
      - Apparent magnitude = 20.51 +/- 0.25
      - Flux (W m-2 um-1) = 7.41e-18 +/- 1.72e-18
   - Gemini/GPI.K1:
      - Apparent magnitude = 18.99 +/- 0.20
      - Flux (W m-2 um-1) = 1.38e-17 +/- 2.56e-18
   - Paranal/NACO.Lp:
      - Apparent magnitude = 16.27 +/- 0.19
      - Flux (W m-2 um-1) = 1.63e-17 +/- 2.87e-18
Adding object: PDS 70 b
   - Distance (pc) = 113.43 +/- 0.52
   - Paranal/SPHERE.IRDIS_D_H23_2:
      - Apparent magnitude = 18.12 +/- 0.21
      - Flux (W m-2 um-1) = 7.40e-17 +/- 1.44e-17
   - Paranal/SPHERE.IRDIS_D_H23_3:
      - Apparent magnitude = 17.97 +/- 0.18
      - Flux (W m-2 um-1) = 7.20e-17 +/- 1.20e-17
   - Paranal/SPHERE.IRDIS_D_K12_1:
      - Apparent magnitude = 16.66 +/- 0.04
      - Flux (W m-2 um-1) = 1.05e-16 +/- 3.88e-18
   - Paranal/SPHERE.IRDIS_D_K12_2:
      - Apparent magnitude = 16.37 +/- 0.06
      - Flux (W m-2 um-1) = 1.06e-16 +/- 5.87e-18
   - MKO/NSFCam.J:
      - Apparent magnitude = 20.04 +/- 0.09
      - Flux (W m-2 um-1) = 2.99e-17 +/- 2.48e-18
   - MKO/NSFCam.H:
      - Apparent magnitude = 18.24 +/- 0.04
      - Flux (W m-2 um-1) = 6.22e-17 +/- 2.29e-18
   - Paranal/NACO.Lp:
      - Apparent magnitude = 14.68 +/- 0.22
      - Flux (W m-2 um-1) = 7.07e-17 +/- 1.44e-17
   - Paranal/NACO.NB405:
      - Apparent magnitude = 14.68 +/- 0.27
      - Flux (W m-2 um-1) = 5.33e-17 +/- 1.34e-17
   - Paranal/NACO.Mp:
      - Apparent magnitude = 13.80 +/- 0.27
      - Flux (W m-2 um-1) = 6.53e-17 +/- 1.64e-17
   - Keck/NIRC2.Lp:
      - Apparent magnitude = 14.64 +/- 0.18
      - Flux (W m-2 um-1) = 7.52e-17 +/- 1.25e-17
Adding object: PDS 70 c
   - Distance (pc) = 113.43 +/- 0.52
   - Paranal/NACO.NB405:
      - Apparent magnitude = 14.91 +/- 0.35
      - Flux (W m-2 um-1) = 4.31e-17 +/- 1.41e-17
   - Keck/NIRC2.Lp:
      - Apparent magnitude = 15.50 +/- 0.46
      - Flux (W m-2 um-1) = 3.40e-17 +/- 1.49e-17
Adding filter: HST/NICMOS1.F090M... [DONE]
Adding filter: HST/NICMOS1.F110M... [DONE]
Adding filter: HST/NICMOS1.F145M... [DONE]
Adding filter: HST/NICMOS1.F160W... [DONE]
Adding object: 2M1207 b
   - Distance (pc) = 64.42 +/- 0.65
   - HST/NICMOS1.F090M:
      - Apparent magnitude = 22.58 +/- 0.35
      - Flux (W m-2 um-1) = 7.90e-18 +/- 2.59e-18
   - HST/NICMOS1.F110M:
      - Apparent magnitude = 20.61 +/- 0.15
      - Flux (W m-2 um-1) = 2.71e-17 +/- 3.76e-18
   - HST/NICMOS1.F145M:
      - Apparent magnitude = 19.05 +/- 0.03
      - Flux (W m-2 um-1) = 4.33e-17 +/- 1.20e-18
   - HST/NICMOS1.F160W:
      - Apparent magnitude = 18.27 +/- 0.02
      - Flux (W m-2 um-1) = 6.37e-17 +/- 1.17e-18
   - Paranal/NACO.J:
      - Apparent magnitude = 20.00 +/- 0.20
      - Flux (W m-2 um-1) = 3.03e-17 +/- 5.61e-18
   - Paranal/NACO.H:
      - Apparent magnitude = 18.09 +/- 0.21
      - Flux (W m-2 um-1) = 6.76e-17 +/- 1.32e-17
   - Paranal/NACO.Ks:
      - Apparent magnitude = 16.93 +/- 0.11
      - Flux (W m-2 um-1) = 7.78e-17 +/- 7.89e-18
   - Paranal/NACO.Lp:
      - Apparent magnitude = 15.28 +/- 0.14
      - Flux (W m-2 um-1) = 4.07e-17 +/- 5.26e-18
Adding object: AB Pic B
   - Distance (pc) = 50.12 +/- 0.07
   - Paranal/NACO.J:
      - Apparent magnitude = 16.18 +/- 0.10
      - Flux (W m-2 um-1) = 1.02e-15 +/- 9.41e-17
   - Paranal/NACO.H:
      - Apparent magnitude = 14.69 +/- 0.10
      - Flux (W m-2 um-1) = 1.55e-15 +/- 1.43e-16
   - Paranal/NACO.Ks:
      - Apparent magnitude = 14.14 +/- 0.08
      - Flux (W m-2 um-1) = 1.02e-15 +/- 7.49e-17
Adding object: HD 206893 B
   - Distance (pc) = 40.81 +/- 0.11
   - Paranal/SPHERE.IRDIS_B_H:
      - Apparent magnitude = 16.79 +/- 0.06
      - Flux (W m-2 um-1) = 2.39e-16 +/- 1.32e-17
   - Paranal/SPHERE.IRDIS_D_K12_1:
      - Apparent magnitude = 15.20 +/- 0.10
      - Flux (W m-2 um-1) = 4.04e-16 +/- 3.73e-17
   - Paranal/SPHERE.IRDIS_D_K12_2:
      - Apparent magnitude = 14.88 +/- 0.09
      - Flux (W m-2 um-1) = 4.19e-16 +/- 3.48e-17
   - Paranal/NACO.Lp:
      - Apparent magnitude = 13.79 +/- 0.31
      - Flux (W m-2 um-1) = 1.60e-16 +/- 4.64e-17
   - Paranal/NACO.NB405:
      - Apparent magnitude = 13.16 +/- 0.34
      - Flux (W m-2 um-1) = 2.16e-16 +/- 6.88e-17
   - Paranal/NACO.Mp:
      - Apparent magnitude = 12.77 +/- 0.27
      - Flux (W m-2 um-1) = 1.69e-16 +/- 4.24e-17
Adding filter: Paranal/SPHERE.IRDIS_B_Ks... [DONE]
Adding object: RZ Psc B
   - Distance (pc) = 195.86 +/- 4.03
   - Paranal/SPHERE.IRDIS_B_H (2 values):
      - Apparent magnitude = 13.71 +/- 0.14
      - Flux (W m-2 um-1) = 4.07e-15 +/- 5.26e-16
      - Apparent magnitude = 13.85 +/- 0.26
      - Flux (W m-2 um-1) = 3.58e-15 +/- 8.65e-16
   - Paranal/SPHERE.IRDIS_B_Ks:
      - Apparent magnitude = 13.51 +/- 0.20
      - Flux (W m-2 um-1) = 1.69e-15 +/- 3.12e-16
Adding filter: HST/WFPC2-PC.F606W... [DONE]
Adding filter: HST/WFPC2-PC.F814W... [DONE]
Adding filter: HST/NICMOS2.F171M... [DONE]
Adding filter: HST/NICMOS2.F190N... [DONE]
Adding filter: HST/NICMOS2.F215N... [DONE]
Adding filter: Magellan/VisAO.ip... [DONE]
Adding filter: Magellan/VisAO.zp... [DONE]
Adding filter: Magellan/VisAO.Ys... [DONE]
Adding filter: Subaru/CIAO.CH4s... [DONE]
Adding filter: Subaru/CIAO.K... [DONE]
Adding filter: Subaru/CIAO.Lp... [DONE]
Adding object: GQ Lup B
   - Distance (pc) = 151.82 +/- 1.10
   - HST/WFPC2-PC.F606W:
      - Apparent magnitude = 19.19 +/- 0.07
      - Flux (W m-2 um-1) = 5.94e-16 +/- 3.83e-17
   - HST/WFPC2-PC.F814W:
      - Apparent magnitude = 17.67 +/- 0.05
      - Flux (W m-2 um-1) = 1.02e-15 +/- 4.68e-17
   - HST/NICMOS2.F171M:
      - Apparent magnitude = 13.84 +/- 0.13
      - Flux (W m-2 um-1) = 2.91e-15 +/- 3.49e-16
   - HST/NICMOS2.F190N:
      - Apparent magnitude = 14.08 +/- 0.20
      - Flux (W m-2 um-1) = 1.65e-15 +/- 3.06e-16
   - HST/NICMOS2.F215N:
      - Apparent magnitude = 13.40 +/- 0.15
      - Flux (W m-2 um-1) = 1.94e-15 +/- 2.69e-16
   - Magellan/VisAO.ip:
      - Apparent magnitude = 18.89 +/- 0.24
      - Flux (W m-2 um-1) = 3.77e-16 +/- 8.40e-17
   - Magellan/VisAO.zp:
      - Apparent magnitude = 16.40 +/- 0.10
      - Flux (W m-2 um-1) = 2.33e-15 +/- 2.15e-16
   - Magellan/VisAO.Ys:
      - Apparent magnitude = 15.88 +/- 0.10
      - Flux (W m-2 um-1) = 3.09e-15 +/- 2.85e-16
   - Paranal/NACO.Ks (4 values):
      - Apparent magnitude = 13.47 +/- 0.03
      - Flux (W m-2 um-1) = 1.88e-15 +/- 5.36e-17
      - Apparent magnitude = 13.39 +/- 0.03
      - Flux (W m-2 um-1) = 2.03e-15 +/- 6.00e-17
      - Apparent magnitude = 13.50 +/- 0.05
      - Flux (W m-2 um-1) = 1.84e-15 +/- 8.47e-17
      - Apparent magnitude = 13.50 +/- 0.03
      - Flux (W m-2 um-1) = 1.83e-15 +/- 4.72e-17
   - Subaru/CIAO.CH4s:
      - Apparent magnitude = 13.76 +/- 0.26
      - Flux (W m-2 um-1) = 3.96e-15 +/- 9.58e-16
   - Subaru/CIAO.K:
      - Apparent magnitude = 13.37 +/- 0.12
      - Flux (W m-2 um-1) = 1.87e-15 +/- 2.07e-16
   - Subaru/CIAO.Lp:
      - Apparent magnitude = 12.44 +/- 0.22
      - Flux (W m-2 um-1) = 5.78e-16 +/- 1.18e-16
Adding filter: Paranal/SPHERE.ZIMPOL_R_PRIM... [DONE]
Adding filter: Paranal/SPHERE.ZIMPOL_I_PRIM... [DONE]
Adding filter: Gemini/NIRI.H2S1v2-1-G0220... [DONE]
Adding object: PZ Tel B
   - Distance (pc) = 47.13 +/- 0.13
   - Paranal/SPHERE.ZIMPOL_R_PRIM:
      - Apparent magnitude = 17.84 +/- 0.31
      - Flux (W m-2 um-1) = 1.83e-15 +/- 5.29e-16
   - Paranal/SPHERE.ZIMPOL_I_PRIM:
      - Apparent magnitude = 15.16 +/- 0.12
      - Flux (W m-2 um-1) = 1.09e-14 +/- 1.20e-15
   - Paranal/SPHERE.IRDIS_D_H23_2:
      - Apparent magnitude = 11.78 +/- 0.19
      - Flux (W m-2 um-1) = 2.54e-14 +/- 4.47e-15
   - Paranal/SPHERE.IRDIS_D_H23_3:
      - Apparent magnitude = 11.65 +/- 0.19
      - Flux (W m-2 um-1) = 2.43e-14 +/- 4.27e-15
   - Paranal/SPHERE.IRDIS_D_K12_1:
      - Apparent magnitude = 11.56 +/- 0.09
      - Flux (W m-2 um-1) = 1.15e-14 +/- 9.58e-16
   - Paranal/SPHERE.IRDIS_D_K12_2:
      - Apparent magnitude = 11.29 +/- 0.10
      - Flux (W m-2 um-1) = 1.14e-14 +/- 1.05e-15
   - Paranal/NACO.J:
      - Apparent magnitude = 12.47 +/- 0.20
      - Flux (W m-2 um-1) = 3.11e-14 +/- 5.76e-15
   - Paranal/NACO.H:
      - Apparent magnitude = 11.93 +/- 0.14
      - Flux (W m-2 um-1) = 1.97e-14 +/- 2.55e-15
   - Paranal/NACO.Ks:
      - Apparent magnitude = 11.53 +/- 0.07
      - Flux (W m-2 um-1) = 1.12e-14 +/- 7.25e-16
   - Paranal/NACO.Lp:
      - Apparent magnitude = 11.04 +/- 0.22
      - Flux (W m-2 um-1) = 2.02e-15 +/- 4.12e-16
   - Paranal/NACO.NB405:
      - Apparent magnitude = 10.94 +/- 0.07
      - Flux (W m-2 um-1) = 1.67e-15 +/- 1.08e-16
   - Paranal/NACO.Mp:
      - Apparent magnitude = 10.93 +/- 0.03
      - Flux (W m-2 um-1) = 9.19e-16 +/- 2.54e-17
   - Gemini/NICI.ED286:
      - Apparent magnitude = 11.68 +/- 0.14
      - Flux (W m-2 um-1) = 2.78e-14 +/- 3.60e-15
   - Gemini/NIRI.H2S1v2-1-G0220:
      - Apparent magnitude = 11.39 +/- 0.14
      - Flux (W m-2 um-1) = 1.06e-14 +/- 1.37e-15
Adding filter: Subaru/CIAO.J... [DONE]
Adding filter: Subaru/CIAO.H... [DONE]
Adding filter: Subaru/CIAO.Ks... [DONE]
Adding filter: LBT/LMIRCam.M_77K... [DONE]
Adding object: kappa And b
   - Distance (pc) = 50.06 +/- 0.87
   - Subaru/CIAO.J:
      - Apparent magnitude = 15.86 +/- 0.21
      - Flux (W m-2 um-1) = 1.41e-15 +/- 2.74e-16
   - Subaru/CIAO.H:
      - Apparent magnitude = 14.95 +/- 0.13
      - Flux (W m-2 um-1) = 1.29e-15 +/- 1.55e-16
   - Subaru/CIAO.Ks:
      - Apparent magnitude = 14.32 +/- 0.09
      - Flux (W m-2 um-1) = 8.53e-16 +/- 7.08e-17
   - Keck/NIRC2.Lp:
      - Apparent magnitude = 13.12 +/- 0.10
      - Flux (W m-2 um-1) = 3.05e-16 +/- 2.81e-17
   - LBT/LMIRCam.M_77K:
      - Apparent magnitude = 13.30 +/- 0.30
      - Flux (W m-2 um-1) = 1.02e-16 +/- 2.86e-17
Adding filter: MKO/NSFCam.Ks... [DONE]
Adding object: HD 1160 B
   - Distance (pc) = 125.90 +/- 1.20
   - MKO/NSFCam.J:
      - Apparent magnitude = 14.69 +/- 0.05
      - Flux (W m-2 um-1) = 4.13e-15 +/- 1.90e-16
   - MKO/NSFCam.H:
      - Apparent magnitude = 14.21 +/- 0.02
      - Flux (W m-2 um-1) = 2.55e-15 +/- 4.69e-17
   - MKO/NSFCam.Ks:
      - Apparent magnitude = 14.12 +/- 0.05
      - Flux (W m-2 um-1) = 1.03e-15 +/- 4.73e-17
   - Paranal/NACO.Lp:
      - Apparent magnitude = 13.60 +/- 0.10
      - Flux (W m-2 um-1) = 1.91e-16 +/- 1.76e-17
   - Keck/NIRC2.Ms:
      - Apparent magnitude = 13.81 +/- 0.24
      - Flux (W m-2 um-1) = 6.98e-17 +/- 1.56e-17
Adding filter: Keck/NIRC2.J... [DONE]
Adding object: ROXs 42 Bb
   - Distance (pc) = 144.16 +/- 1.53
   - Keck/NIRC2.J:
      - Apparent magnitude = 16.91 +/- 0.11
      - Flux (W m-2 um-1) = 5.32e-16 +/- 5.40e-17
   - Keck/NIRC2.H:
      - Apparent magnitude = 15.88 +/- 0.05
      - Flux (W m-2 um-1) = 5.40e-16 +/- 2.49e-17
   - Keck/NIRC2.Ks:
      - Apparent magnitude = 15.01 +/- 0.06
      - Flux (W m-2 um-1) = 4.49e-16 +/- 2.48e-17
   - Keck/NIRC2.Lp:
      - Apparent magnitude = 13.97 +/- 0.06
      - Flux (W m-2 um-1) = 1.39e-16 +/- 7.70e-18
   - Keck/NIRC2.Ms:
      - Apparent magnitude = 14.01 +/- 0.23
      - Flux (W m-2 um-1) = 5.80e-17 +/- 1.24e-17
Adding filter: Paranal/SPHERE.IRDIS_D_Y23_2... [DONE]
Adding filter: Paranal/SPHERE.IRDIS_D_Y23_3... [DONE]
Adding filter: Paranal/SPHERE.IRDIS_D_J23_3... [DONE]
Adding filter: Subaru/IRCS.Lp... [DONE]
Adding object: GJ 504 b
   - Distance (pc) = 17.54 +/- 0.08
   - Paranal/SPHERE.IRDIS_D_Y23_2:
      - Apparent magnitude = 20.98 +/- 0.20
      - Flux (W m-2 um-1) = 2.43e-17 +/- 4.51e-18
   - Paranal/SPHERE.IRDIS_D_Y23_3:
      - Apparent magnitude = 20.14 +/- 0.09
      - Flux (W m-2 um-1) = 4.45e-17 +/- 3.69e-18
   - Paranal/SPHERE.IRDIS_D_J23_3:
      - Apparent magnitude = 19.01 +/- 0.17
      - Flux (W m-2 um-1) = 7.08e-17 +/- 1.11e-17
   - Paranal/SPHERE.IRDIS_D_H23_2:
      - Apparent magnitude = 18.95 +/- 0.30
      - Flux (W m-2 um-1) = 3.44e-17 +/- 9.64e-18
   - Paranal/SPHERE.IRDIS_D_H23_3:
      - Apparent magnitude = 21.81 +/- 0.35
      - Flux (W m-2 um-1) = 2.09e-18 +/- 6.87e-19
   - Paranal/SPHERE.IRDIS_D_K12_1:
      - Apparent magnitude = 18.77 +/- 0.20
      - Flux (W m-2 um-1) = 1.51e-17 +/- 2.79e-18
   - Subaru/CIAO.J:
      - Apparent magnitude = 19.78 +/- 0.10
      - Flux (W m-2 um-1) = 3.80e-17 +/- 3.51e-18
   - Subaru/CIAO.H:
      - Apparent magnitude = 20.01 +/- 0.14
      - Flux (W m-2 um-1) = 1.22e-17 +/- 1.58e-18
   - Subaru/CIAO.Ks:
      - Apparent magnitude = 19.38 +/- 0.11
      - Flux (W m-2 um-1) = 8.07e-18 +/- 8.19e-19
   - Subaru/CIAO.CH4s:
      - Apparent magnitude = 19.58 +/- 0.13
      - Flux (W m-2 um-1) = 1.86e-17 +/- 2.23e-18
   - Subaru/IRCS.Lp:
      - Apparent magnitude = 16.70 +/- 0.17
      - Flux (W m-2 um-1) = 1.14e-17 +/- 1.80e-18
Adding filter: Gemini/GMOS-S.z... [DONE]
Adding filter: CFHT/Wircam.Y... [DONE]
Adding filter: CFHT/Wircam.J... [DONE]
Adding filter: CFHT/Wircam.H... [DONE]
Adding filter: CFHT/Wircam.Ks... [DONE]
Adding filter: WISE/WISE.W1... [DONE]
Adding filter: WISE/WISE.W2... [DONE]
Adding object: GU Psc b
   - Distance (pc) = 47.61 +/- 0.16
   - Gemini/GMOS-S.z:
      - Apparent magnitude = 21.75 +/- 0.07
      - Flux (W m-2 um-1) = 1.63e-17 +/- 1.05e-18
   - CFHT/Wircam.Y:
      - Apparent magnitude = 19.40 +/- 0.05
      - Flux (W m-2 um-1) = 1.06e-16 +/- 4.87e-18
   - CFHT/Wircam.J:
      - Apparent magnitude = 18.12 +/- 0.03
      - Flux (W m-2 um-1) = 1.72e-16 +/- 4.76e-18
   - CFHT/Wircam.H:
      - Apparent magnitude = 17.70 +/- 0.03
      - Flux (W m-2 um-1) = 1.02e-16 +/- 2.82e-18
   - CFHT/Wircam.Ks:
      - Apparent magnitude = 17.40 +/- 0.03
      - Flux (W m-2 um-1) = 4.98e-17 +/- 1.38e-18
   - WISE/WISE.W1:
      - Apparent magnitude = 17.17 +/- 0.33
      - Flux (W m-2 um-1) = 1.14e-17 +/- 3.52e-18
   - WISE/WISE.W2:
      - Apparent magnitude = 15.41 +/- 0.22
      - Flux (W m-2 um-1) = 1.70e-17 +/- 3.48e-18
Adding object: 2M0103 ABb
   - Distance (pc) = 47.20 +/- 3.10
   - Paranal/NACO.J:
      - Apparent magnitude = 15.47 +/- 0.30
      - Flux (W m-2 um-1) = 1.96e-15 +/- 5.49e-16
   - Paranal/NACO.H:
      - Apparent magnitude = 14.27 +/- 0.20
      - Flux (W m-2 um-1) = 2.28e-15 +/- 4.23e-16
   - Paranal/NACO.Ks:
      - Apparent magnitude = 13.67 +/- 0.20
      - Flux (W m-2 um-1) = 1.57e-15 +/- 2.90e-16
   - Paranal/NACO.Lp:
      - Apparent magnitude = 12.67 +/- 0.10
      - Flux (W m-2 um-1) = 4.50e-16 +/- 4.15e-17
Adding filter: Gemini/NIRI.J-G0202w... [DONE]
Adding filter: Gemini/NIRI.H-G0203w... [DONE]
Adding filter: Gemini/NIRI.K-G0204w... [DONE]
Adding filter: Gemini/NIRI.Lprime-G0207w... [DONE]
Adding object: 1RXS 1609 B
   - Distance (pc) = 139.67 +/- 1.33
   - Gemini/NIRI.J-G0202w:
      - Apparent magnitude = 17.90 +/- 0.12
      - Flux (W m-2 um-1) = 2.12e-16 +/- 2.35e-17
   - Gemini/NIRI.H-G0203w:
      - Apparent magnitude = 16.87 +/- 0.07
      - Flux (W m-2 um-1) = 2.11e-16 +/- 1.36e-17
   - Gemini/NIRI.K-G0204w:
      - Apparent magnitude = 16.17 +/- 0.18
      - Flux (W m-2 um-1) = 1.38e-16 +/- 2.30e-17
   - Gemini/NIRI.Lprime-G0207w:
      - Apparent magnitude = 14.80 +/- 0.30
      - Flux (W m-2 um-1) = 6.56e-17 +/- 1.84e-17
Adding filter: MKO/NSFCam.Kp... [DONE]
Adding filter: MKO/NSFCam.Lp... [DONE]
Adding object: GSC 06214 B
   - Distance (pc) = 108.84 +/- 0.51
   - MKO/NSFCam.J:
      - Apparent magnitude = 16.24 +/- 0.04
      - Flux (W m-2 um-1) = 9.91e-16 +/- 3.65e-17
   - MKO/NSFCam.H:
      - Apparent magnitude = 15.55 +/- 0.04
      - Flux (W m-2 um-1) = 7.41e-16 +/- 2.73e-17
   - MKO/NSFCam.Kp:
      - Apparent magnitude = 14.95 +/- 0.05
      - Flux (W m-2 um-1) = 5.08e-16 +/- 2.34e-17
   - MKO/NSFCam.Lp:
      - Apparent magnitude = 13.75 +/- 0.07
      - Flux (W m-2 um-1) = 1.73e-16 +/- 1.12e-17
   - LBT/LMIRCam.M_77K:
      - Apparent magnitude = 13.75 +/- 0.30
      - Flux (W m-2 um-1) = 6.75e-17 +/- 1.89e-17
Adding object: HD 72946 B
   - Distance (pc) = 25.87 +/- 0.03
   - Paranal/SPHERE.IRDIS_D_H23_2:
      - Apparent magnitude = 14.56 +/- 0.07
      - Flux (W m-2 um-1) = 1.96e-15 +/- 1.27e-16
   - Paranal/SPHERE.IRDIS_D_H23_3:
      - Apparent magnitude = 14.40 +/- 0.07
      - Flux (W m-2 um-1) = 1.93e-15 +/- 1.24e-16
Adding object: HIP 64892 B
   - Distance (pc) = 125.20 +/- 1.42
   - Paranal/SPHERE.IRDIS_D_H23_2:
      - Apparent magnitude = 14.21 +/- 0.17
      - Flux (W m-2 um-1) = 2.71e-15 +/- 4.26e-16
   - Paranal/SPHERE.IRDIS_D_H23_3:
      - Apparent magnitude = 13.94 +/- 0.17
      - Flux (W m-2 um-1) = 2.94e-15 +/- 4.63e-16
   - Paranal/SPHERE.IRDIS_D_K12_1:
      - Apparent magnitude = 13.77 +/- 0.17
      - Flux (W m-2 um-1) = 1.51e-15 +/- 2.37e-16
   - Paranal/SPHERE.IRDIS_D_K12_2:
      - Apparent magnitude = 13.45 +/- 0.19
      - Flux (W m-2 um-1) = 1.56e-15 +/- 2.75e-16
   - Paranal/NACO.Lp:
      - Apparent magnitude = 13.09 +/- 0.17
      - Flux (W m-2 um-1) = 3.06e-16 +/- 4.81e-17

We also add the photometry and parallaxes of the Database of Ultracool Parallaxes.

[4]:
database.add_photometry('vlm-plx')
Downloading Database of Ultracool Parallaxes (307 kB)... [DONE]
Adding Database of Ultracool Parallaxes... [DONE]

The isochrones from the AMES-Cond and AMES-Dusty are downloaded with urllib.request.

[5]:
urllib.request.urlretrieve('https://phoenix.ens-lyon.fr/Grids/AMES-Cond/ISOCHRONES/model.AMES-Cond-2000.M-0.0.NaCo.Vega',
                           'data/model.AMES-Cond-2000.M-0.0.NaCo.Vega')
[5]:
('data/model.AMES-Cond-2000.M-0.0.NaCo.Vega',
 <http.client.HTTPMessage at 0x1420247b8>)
[6]:
urllib.request.urlretrieve('https://phoenix.ens-lyon.fr/Grids/AMES-Dusty/ISOCHRONES/model.AMES-dusty.M-0.0.NaCo.Vega',
                           'data/model.AMES-dusty.M-0.0.NaCo.Vega')
[6]:
('data/model.AMES-dusty.M-0.0.NaCo.Vega',
 <http.client.HTTPMessage at 0x142024fd0>)

And the isochronse are added to the database.

[7]:
database.add_isochrones(filename='data/model.AMES-Cond-2000.M-0.0.NaCo.Vega',
                        tag='iso_cond',
                        model='baraffe')

database.add_isochrones(filename='data/model.AMES-dusty.M-0.0.NaCo.Vega',
                        tag='iso_dusty',
                        model='baraffe')
Adding isochrones: iso_cond... [DONE]
Adding isochrones: iso_dusty... [DONE]

Finally, the AMES-Cond grid with synthetic spectra are downloaded and added. Spectra with Teff values outside the chosen teff_range are excluded.

[8]:
database.add_model(model='ames-cond',
                   teff_range=(100., 4000.))
Downloading AMES-Cond model spectra (150 MB)... [DONE]
Unpacking AMES-Cond model spectra (150 MB)... [DONE]
Adding AMES-Cond model spectra... [DONE]
Grid points stored in the database:
   - Teff = [ 100.  200.  300.  400.  500.  600.  700.  800.  900. 1000. 1100. 1200.
 1300. 1400. 1500. 1600. 1700. 1800. 1900. 2000. 2100. 2200. 2300. 2400.
 2500. 2600. 2700. 2800. 2900. 3000. 3100. 3200. 3300. 3400. 3500. 3600.
 3700. 3800. 3900. 4000.]
   - log(g) = [2.5 3.  3.5 4.  4.5 5.  5.5]
Number of grid points per parameter:
   - teff: 40
   - logg: 7
Fix missing grid points with a linear interpolation:
   - teff = 200.0, logg = 5.5
   - teff = 900.0, logg = 2.5
Number of stored grid points: 280
Number of interpolated grid points: 2
Number of missing grid points: 0
/Users/tomasstolker/applications/species/species/util/data_util.py:275: RuntimeWarning: divide by zero encountered in log10
  flux = np.log10(flux)

The spectra at two grid points were missing in the original grid. These have been linearly interpolated species from neighboring grid points.

Also the AMES-Dusty spectra are also downloaded and imported into the database.

[9]:
database.add_model(model='ames-dusty',
                   teff_range=(100., 4000.))
Downloading AMES-Dusty model spectra (59 MB)... [DONE]
Unpacking AMES-Dusty model spectra (59 MB)... [DONE]
Adding AMES-Dusty model spectra... [DONE]
Grid points stored in the database:
   - Teff = [ 500.  600.  700.  800.  900. 1000. 1100. 1200. 1300. 1400. 1500. 1600.
 1700. 1800. 1900. 2000. 2100. 2200. 2300. 2400. 2500. 2600. 2700. 2800.
 2900. 3000. 3100. 3200. 3300. 3400. 3500. 3600. 3700. 3800. 3900. 4000.]
   - log(g) = [3.5 4.  4.5 5.  5.5 6. ]
Number of grid points per parameter:
   - teff: 36
   - logg: 6
Fix missing grid points with a linear interpolation:
   - teff = 900.0, logg = 6.0
   - teff = 1200.0, logg = 5.5
   - teff = 2100.0, logg = 3.5
   - teff = 2100.0, logg = 4.5
   - teff = 2200.0, logg = 3.5
   - teff = 2400.0, logg = 5.0
   - teff = 3100.0, logg = 3.5
   - teff = 3200.0, logg = 3.5
   - teff = 3300.0, logg = 3.5
   - teff = 3400.0, logg = 3.5
   - teff = 3500.0, logg = 3.5
   - teff = 3600.0, logg = 3.5
   - teff = 3700.0, logg = 3.5
   - teff = 3800.0, logg = 3.5
   - teff = 3900.0, logg = 3.5
   - teff = 3900.0, logg = 6.0
   - teff = 4000.0, logg = 3.5
   - teff = 4000.0, logg = 4.0
   - teff = 4000.0, logg = 4.5
   - teff = 4000.0, logg = 5.5
   - teff = 4000.0, logg = 6.0
Could not interpolate 15 grid points so storing zeros instead. [WARNING]
The grid points that are missing:
   - teff = 3100.0, logg = 3.5
   - teff = 3200.0, logg = 3.5
   - teff = 3300.0, logg = 3.5
   - teff = 3400.0, logg = 3.5
   - teff = 3500.0, logg = 3.5
   - teff = 3600.0, logg = 3.5
   - teff = 3700.0, logg = 3.5
   - teff = 3800.0, logg = 3.5
   - teff = 3900.0, logg = 3.5
   - teff = 3900.0, logg = 6.0
   - teff = 4000.0, logg = 3.5
   - teff = 4000.0, logg = 4.0
   - teff = 4000.0, logg = 4.5
   - teff = 4000.0, logg = 5.5
   - teff = 4000.0, logg = 6.0
Number of stored grid points: 216
Number of interpolated grid points: 6
Number of missing grid points: 15

A number of spectra were missing of which 6 have been interpolated. For 15 spectra this was not possible because of incompleteness of the grid so these fluxes have been set to zero. Therefore, one needs to be careful when interpolating spectra in those parts of the parameter space.

Database content

Let’s have a look at all the data that is stored in the database.

[10]:
database.list_content()
Database content:
- filters: <HDF5 group "/filters" (11 members)>
        - CFHT: <HDF5 group "/filters/CFHT" (4 members)>
                - Wircam.H: <HDF5 dataset "Wircam.H": shape (747, 2), type "<f4">
                        - det_type: energy
                - Wircam.J: <HDF5 dataset "Wircam.J": shape (1077, 2), type "<f4">
                        - det_type: energy
                - Wircam.Ks: <HDF5 dataset "Wircam.Ks": shape (791, 2), type "<f4">
                        - det_type: energy
                - Wircam.Y: <HDF5 dataset "Wircam.Y": shape (875, 2), type "<f4">
                        - det_type: energy
        - Gemini: <HDF5 group "/filters/Gemini" (9 members)>
                - GMOS-S.z: <HDF5 dataset "GMOS-S.z": shape (928, 2), type "<f4">
                        - det_type: energy
                - GPI.H: <HDF5 dataset "GPI.H": shape (1895, 2), type "<f4">
                        - det_type: energy
                - GPI.K1: <HDF5 dataset "GPI.K1": shape (2128, 2), type "<f4">
                        - det_type: energy
                - NICI.ED286: <HDF5 dataset "NICI.ED286": shape (387, 2), type "<f4">
                        - det_type: energy
                - NIRI.H-G0203w: <HDF5 dataset "NIRI.H-G0203w": shape (368, 2), type "<f4">
                        - det_type: energy
                - NIRI.H2S1v2-1-G0220: <HDF5 dataset "NIRI.H2S1v2-1-G0220": shape (129, 2), type "<f4">
                        - det_type: energy
                - NIRI.J-G0202w: <HDF5 dataset "NIRI.J-G0202w": shape (213, 2), type "<f4">
                        - det_type: energy
                - NIRI.K-G0204w: <HDF5 dataset "NIRI.K-G0204w": shape (423, 2), type "<f4">
                        - det_type: energy
                - NIRI.Lprime-G0207w: <HDF5 dataset "NIRI.Lprime-G0207w": shape (933, 2), type "<f4">
                        - det_type: energy
        - HST: <HDF5 group "/filters/HST" (9 members)>
                - NICMOS1.F090M: <HDF5 dataset "NICMOS1.F090M": shape (633, 2), type "<f4">
                        - det_type: photon
                - NICMOS1.F110M: <HDF5 dataset "NICMOS1.F110M": shape (768, 2), type "<f4">
                        - det_type: photon
                - NICMOS1.F145M: <HDF5 dataset "NICMOS1.F145M": shape (829, 2), type "<f4">
                        - det_type: photon
                - NICMOS1.F160W: <HDF5 dataset "NICMOS1.F160W": shape (1319, 2), type "<f4">
                        - det_type: photon
                - NICMOS2.F171M: <HDF5 dataset "NICMOS2.F171M": shape (1226, 2), type "<f4">
                        - det_type: photon
                - NICMOS2.F190N: <HDF5 dataset "NICMOS2.F190N": shape (375, 2), type "<f4">
                        - det_type: photon
                - NICMOS2.F215N: <HDF5 dataset "NICMOS2.F215N": shape (506, 2), type "<f4">
                        - det_type: photon
                - WFPC2-PC.F606W: <HDF5 dataset "WFPC2-PC.F606W": shape (1347, 2), type "<f4">
                        - det_type: photon
                - WFPC2-PC.F814W: <HDF5 dataset "WFPC2-PC.F814W": shape (1535, 2), type "<f4">
                        - det_type: photon
        - Keck: <HDF5 group "/filters/Keck" (5 members)>
                - NIRC2.H: <HDF5 dataset "NIRC2.H": shape (1552, 2), type "<f4">
                        - det_type: photon
                - NIRC2.J: <HDF5 dataset "NIRC2.J": shape (1054, 2), type "<f4">
                        - det_type: photon
                - NIRC2.Ks: <HDF5 dataset "NIRC2.Ks": shape (1445, 2), type "<f4">
                        - det_type: photon
                - NIRC2.Lp: <HDF5 dataset "NIRC2.Lp": shape (1746, 2), type "<f4">
                        - det_type: photon
                - NIRC2.Ms: <HDF5 dataset "NIRC2.Ms": shape (500, 2), type "<f4">
                        - det_type: photon
        - LBT: <HDF5 group "/filters/LBT" (1 members)>
                - LMIRCam.M_77K: <HDF5 dataset "LMIRCam.M_77K": shape (626, 2), type "<f4">
                        - det_type: energy
        - LCO: <HDF5 group "/filters/LCO" (1 members)>
                - VisAO.Ys: <HDF5 dataset "VisAO.Ys": shape (27, 2), type "<f8">
                        - det_type: energy
        - MKO: <HDF5 group "/filters/MKO" (6 members)>
                - NSFCam.H: <HDF5 dataset "NSFCam.H": shape (970, 2), type "<f4">
                        - det_type: energy
                - NSFCam.J: <HDF5 dataset "NSFCam.J": shape (1253, 2), type "<f4">
                        - det_type: energy
                - NSFCam.K: <HDF5 dataset "NSFCam.K": shape (971, 2), type "<f4">
                        - det_type: energy
                - NSFCam.Kp: <HDF5 dataset "NSFCam.Kp": shape (998, 2), type "<f4">
                        - det_type: energy
                - NSFCam.Ks: <HDF5 dataset "NSFCam.Ks": shape (1102, 2), type "<f4">
                        - det_type: energy
                - NSFCam.Lp: <HDF5 dataset "NSFCam.Lp": shape (1242, 2), type "<f4">
                        - det_type: energy
        - Magellan: <HDF5 group "/filters/Magellan" (3 members)>
                - VisAO.Ys: <HDF5 dataset "VisAO.Ys": shape (27, 2), type "<f8">
                        - det_type: energy
                - VisAO.ip: <HDF5 dataset "VisAO.ip": shape (461, 2), type "<f8">
                        - det_type: energy
                - VisAO.zp: <HDF5 dataset "VisAO.zp": shape (694, 2), type "<f8">
                        - det_type: energy
        - Paranal: <HDF5 group "/filters/Paranal" (19 members)>
                - NACO.H: <HDF5 dataset "NACO.H": shape (23, 2), type "<f4">
                        - det_type: energy
                - NACO.J: <HDF5 dataset "NACO.J": shape (20, 2), type "<f4">
                        - det_type: energy
                - NACO.Ks: <HDF5 dataset "NACO.Ks": shape (27, 2), type "<f4">
                        - det_type: energy
                - NACO.Lp: <HDF5 dataset "NACO.Lp": shape (31, 2), type "<f4">
                        - det_type: energy
                - NACO.Mp: <HDF5 dataset "NACO.Mp": shape (18, 2), type "<f4">
                        - det_type: energy
                - NACO.NB374: <HDF5 dataset "NACO.NB374": shape (46, 2), type "<f4">
                        - det_type: energy
                - NACO.NB405: <HDF5 dataset "NACO.NB405": shape (67, 2), type "<f4">
                        - det_type: energy
                - SPHERE.IRDIS_B_H: <HDF5 dataset "SPHERE.IRDIS_B_H": shape (481, 2), type "<f4">
                        - det_type: energy
                - SPHERE.IRDIS_B_J: <HDF5 dataset "SPHERE.IRDIS_B_J": shape (393, 2), type "<f4">
                        - det_type: energy
                - SPHERE.IRDIS_B_Ks: <HDF5 dataset "SPHERE.IRDIS_B_Ks": shape (415, 2), type "<f4">
                        - det_type: energy
                - SPHERE.IRDIS_D_H23_2: <HDF5 dataset "SPHERE.IRDIS_D_H23_2": shape (113, 2), type "<f4">
                        - det_type: energy
                - SPHERE.IRDIS_D_H23_3: <HDF5 dataset "SPHERE.IRDIS_D_H23_3": shape (180, 2), type "<f4">
                        - det_type: energy
                - SPHERE.IRDIS_D_J23_3: <HDF5 dataset "SPHERE.IRDIS_D_J23_3": shape (129, 2), type "<f4">
                        - det_type: energy
                - SPHERE.IRDIS_D_K12_1: <HDF5 dataset "SPHERE.IRDIS_D_K12_1": shape (175, 2), type "<f4">
                        - det_type: energy
                - SPHERE.IRDIS_D_K12_2: <HDF5 dataset "SPHERE.IRDIS_D_K12_2": shape (191, 2), type "<f4">
                        - det_type: energy
                - SPHERE.IRDIS_D_Y23_2: <HDF5 dataset "SPHERE.IRDIS_D_Y23_2": shape (94, 2), type "<f4">
                        - det_type: energy
                - SPHERE.IRDIS_D_Y23_3: <HDF5 dataset "SPHERE.IRDIS_D_Y23_3": shape (89, 2), type "<f4">
                        - det_type: energy
                - SPHERE.ZIMPOL_I_PRIM: <HDF5 dataset "SPHERE.ZIMPOL_I_PRIM": shape (189, 2), type "<f4">
                        - det_type: energy
                - SPHERE.ZIMPOL_R_PRIM: <HDF5 dataset "SPHERE.ZIMPOL_R_PRIM": shape (169, 2), type "<f4">
                        - det_type: energy
        - Subaru: <HDF5 group "/filters/Subaru" (8 members)>
                - CIAO.CH4s: <HDF5 dataset "CIAO.CH4s": shape (150, 2), type "<f4">
                        - det_type: energy
                - CIAO.H: <HDF5 dataset "CIAO.H": shape (967, 2), type "<f4">
                        - det_type: energy
                - CIAO.J: <HDF5 dataset "CIAO.J": shape (1253, 2), type "<f4">
                        - det_type: energy
                - CIAO.K: <HDF5 dataset "CIAO.K": shape (958, 2), type "<f4">
                        - det_type: energy
                - CIAO.Ks: <HDF5 dataset "CIAO.Ks": shape (200, 2), type "<f4">
                        - det_type: energy
                - CIAO.Lp: <HDF5 dataset "CIAO.Lp": shape (1242, 2), type "<f4">
                        - det_type: energy
                - CIAO.z: <HDF5 dataset "CIAO.z": shape (198, 2), type "<f4">
                        - det_type: energy
                - IRCS.Lp: <HDF5 dataset "IRCS.Lp": shape (1224, 2), type "<f4">
                        - det_type: energy
        - WISE: <HDF5 group "/filters/WISE" (2 members)>
                - WISE.W1: <HDF5 dataset "WISE.W1": shape (141, 2), type "<f4">
                        - det_type: energy
                - WISE.W2: <HDF5 dataset "WISE.W2": shape (168, 2), type "<f4">
                        - det_type: energy
- isochrones: <HDF5 group "/isochrones" (2 members)>
        - iso_cond: <HDF5 group "/isochrones/iso_cond" (3 members)>
                - evolution: <HDF5 dataset "evolution": shape (1940, 8), type "<f8">
                        - model: baraffe
                - filters: <HDF5 dataset "filters": shape (38,), type "|O">
                - magnitudes: <HDF5 dataset "magnitudes": shape (1940, 38), type "<f8">
        - iso_dusty: <HDF5 group "/isochrones/iso_dusty" (3 members)>
                - evolution: <HDF5 dataset "evolution": shape (1459, 8), type "<f8">
                        - model: baraffe
                - filters: <HDF5 dataset "filters": shape (38,), type "|O">
                - magnitudes: <HDF5 dataset "magnitudes": shape (1459, 38), type "<f8">
- models: <HDF5 group "/models" (2 members)>
        - ames-cond: <HDF5 group "/models/ames-cond" (4 members)>
                - flux: <HDF5 dataset "flux": shape (40, 7, 17704), type "<f8">
                - logg: <HDF5 dataset "logg": shape (7,), type "<f8">
                - teff: <HDF5 dataset "teff": shape (40,), type "<f8">
                - wavelength: <HDF5 dataset "wavelength": shape (17704,), type "<f8">
        - ames-dusty: <HDF5 group "/models/ames-dusty" (4 members)>
                - flux: <HDF5 dataset "flux": shape (36, 6, 17704), type "<f8">
                - logg: <HDF5 dataset "logg": shape (6,), type "<f8">
                - teff: <HDF5 dataset "teff": shape (36,), type "<f8">
                - wavelength: <HDF5 dataset "wavelength": shape (17704,), type "<f8">
- objects: <HDF5 group "/objects" (26 members)>
        - 1RXS 1609 B: <HDF5 group "/objects/1RXS 1609 B" (2 members)>
                - Gemini: <HDF5 group "/objects/1RXS 1609 B/Gemini" (4 members)>
                        - NIRI.H-G0203w: <HDF5 dataset "NIRI.H-G0203w": shape (4,), type "<f8">
                                - n_phot: 1
                        - NIRI.J-G0202w: <HDF5 dataset "NIRI.J-G0202w": shape (4,), type "<f8">
                                - n_phot: 1
                        - NIRI.K-G0204w: <HDF5 dataset "NIRI.K-G0204w": shape (4,), type "<f8">
                                - n_phot: 1
                        - NIRI.Lprime-G0207w: <HDF5 dataset "NIRI.Lprime-G0207w": shape (4,), type "<f8">
                                - n_phot: 1
                - distance: <HDF5 dataset "distance": shape (2,), type "<f8">
        - 2M0103 ABb: <HDF5 group "/objects/2M0103 ABb" (2 members)>
                - Paranal: <HDF5 group "/objects/2M0103 ABb/Paranal" (4 members)>
                        - NACO.H: <HDF5 dataset "NACO.H": shape (4,), type "<f8">
                                - n_phot: 1
                        - NACO.J: <HDF5 dataset "NACO.J": shape (4,), type "<f8">
                                - n_phot: 1
                        - NACO.Ks: <HDF5 dataset "NACO.Ks": shape (4,), type "<f8">
                                - n_phot: 1
                        - NACO.Lp: <HDF5 dataset "NACO.Lp": shape (4,), type "<f8">
                                - n_phot: 1
                - distance: <HDF5 dataset "distance": shape (2,), type "<f8">
        - 2M1207 b: <HDF5 group "/objects/2M1207 b" (3 members)>
                - HST: <HDF5 group "/objects/2M1207 b/HST" (4 members)>
                        - NICMOS1.F090M: <HDF5 dataset "NICMOS1.F090M": shape (4,), type "<f8">
                                - n_phot: 1
                        - NICMOS1.F110M: <HDF5 dataset "NICMOS1.F110M": shape (4,), type "<f8">
                                - n_phot: 1
                        - NICMOS1.F145M: <HDF5 dataset "NICMOS1.F145M": shape (4,), type "<f8">
                                - n_phot: 1
                        - NICMOS1.F160W: <HDF5 dataset "NICMOS1.F160W": shape (4,), type "<f8">
                                - n_phot: 1
                - Paranal: <HDF5 group "/objects/2M1207 b/Paranal" (4 members)>
                        - NACO.H: <HDF5 dataset "NACO.H": shape (4,), type "<f8">
                                - n_phot: 1
                        - NACO.J: <HDF5 dataset "NACO.J": shape (4,), type "<f8">
                                - n_phot: 1
                        - NACO.Ks: <HDF5 dataset "NACO.Ks": shape (4,), type "<f8">
                                - n_phot: 1
                        - NACO.Lp: <HDF5 dataset "NACO.Lp": shape (4,), type "<f8">
                                - n_phot: 1
                - distance: <HDF5 dataset "distance": shape (2,), type "<f8">
        - 51 Eri b: <HDF5 group "/objects/51 Eri b" (4 members)>
                - Keck: <HDF5 group "/objects/51 Eri b/Keck" (2 members)>
                        - NIRC2.Lp: <HDF5 dataset "NIRC2.Lp": shape (4,), type "<f8">
                                - n_phot: 1
                        - NIRC2.Ms: <HDF5 dataset "NIRC2.Ms": shape (4,), type "<f8">
                                - n_phot: 1
                - MKO: <HDF5 group "/objects/51 Eri b/MKO" (3 members)>
                        - NSFCam.H: <HDF5 dataset "NSFCam.H": shape (4,), type "<f8">
                                - n_phot: 1
                        - NSFCam.J: <HDF5 dataset "NSFCam.J": shape (4,), type "<f8">
                                - n_phot: 1
                        - NSFCam.K: <HDF5 dataset "NSFCam.K": shape (4,), type "<f8">
                                - n_phot: 1
                - Paranal: <HDF5 group "/objects/51 Eri b/Paranal" (3 members)>
                        - SPHERE.IRDIS_B_H: <HDF5 dataset "SPHERE.IRDIS_B_H": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_H23_2: <HDF5 dataset "SPHERE.IRDIS_D_H23_2": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_K12_1: <HDF5 dataset "SPHERE.IRDIS_D_K12_1": shape (4,), type "<f8">
                                - n_phot: 1
                - distance: <HDF5 dataset "distance": shape (2,), type "<f8">
        - AB Pic B: <HDF5 group "/objects/AB Pic B" (2 members)>
                - Paranal: <HDF5 group "/objects/AB Pic B/Paranal" (3 members)>
                        - NACO.H: <HDF5 dataset "NACO.H": shape (4,), type "<f8">
                                - n_phot: 1
                        - NACO.J: <HDF5 dataset "NACO.J": shape (4,), type "<f8">
                                - n_phot: 1
                        - NACO.Ks: <HDF5 dataset "NACO.Ks": shape (4,), type "<f8">
                                - n_phot: 1
                - distance: <HDF5 dataset "distance": shape (2,), type "<f8">
        - GJ 504 b: <HDF5 group "/objects/GJ 504 b" (3 members)>
                - Paranal: <HDF5 group "/objects/GJ 504 b/Paranal" (6 members)>
                        - SPHERE.IRDIS_D_H23_2: <HDF5 dataset "SPHERE.IRDIS_D_H23_2": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_H23_3: <HDF5 dataset "SPHERE.IRDIS_D_H23_3": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_J23_3: <HDF5 dataset "SPHERE.IRDIS_D_J23_3": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_K12_1: <HDF5 dataset "SPHERE.IRDIS_D_K12_1": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_Y23_2: <HDF5 dataset "SPHERE.IRDIS_D_Y23_2": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_Y23_3: <HDF5 dataset "SPHERE.IRDIS_D_Y23_3": shape (4,), type "<f8">
                                - n_phot: 1
                - Subaru: <HDF5 group "/objects/GJ 504 b/Subaru" (5 members)>
                        - CIAO.CH4s: <HDF5 dataset "CIAO.CH4s": shape (4,), type "<f8">
                                - n_phot: 1
                        - CIAO.H: <HDF5 dataset "CIAO.H": shape (4,), type "<f8">
                                - n_phot: 1
                        - CIAO.J: <HDF5 dataset "CIAO.J": shape (4,), type "<f8">
                                - n_phot: 1
                        - CIAO.Ks: <HDF5 dataset "CIAO.Ks": shape (4,), type "<f8">
                                - n_phot: 1
                        - IRCS.Lp: <HDF5 dataset "IRCS.Lp": shape (4,), type "<f8">
                                - n_phot: 1
                - distance: <HDF5 dataset "distance": shape (2,), type "<f8">
        - GQ Lup B: <HDF5 group "/objects/GQ Lup B" (5 members)>
                - HST: <HDF5 group "/objects/GQ Lup B/HST" (5 members)>
                        - NICMOS2.F171M: <HDF5 dataset "NICMOS2.F171M": shape (4,), type "<f8">
                                - n_phot: 1
                        - NICMOS2.F190N: <HDF5 dataset "NICMOS2.F190N": shape (4,), type "<f8">
                                - n_phot: 1
                        - NICMOS2.F215N: <HDF5 dataset "NICMOS2.F215N": shape (4,), type "<f8">
                                - n_phot: 1
                        - WFPC2-PC.F606W: <HDF5 dataset "WFPC2-PC.F606W": shape (4,), type "<f8">
                                - n_phot: 1
                        - WFPC2-PC.F814W: <HDF5 dataset "WFPC2-PC.F814W": shape (4,), type "<f8">
                                - n_phot: 1
                - Magellan: <HDF5 group "/objects/GQ Lup B/Magellan" (3 members)>
                        - VisAO.Ys: <HDF5 dataset "VisAO.Ys": shape (4,), type "<f8">
                                - n_phot: 1
                        - VisAO.ip: <HDF5 dataset "VisAO.ip": shape (4,), type "<f8">
                                - n_phot: 1
                        - VisAO.zp: <HDF5 dataset "VisAO.zp": shape (4,), type "<f8">
                                - n_phot: 1
                - Paranal: <HDF5 group "/objects/GQ Lup B/Paranal" (1 members)>
                        - NACO.Ks: <HDF5 dataset "NACO.Ks": shape (4, 4), type "<f8">
                                - n_phot: 4
                - Subaru: <HDF5 group "/objects/GQ Lup B/Subaru" (3 members)>
                        - CIAO.CH4s: <HDF5 dataset "CIAO.CH4s": shape (4,), type "<f8">
                                - n_phot: 1
                        - CIAO.K: <HDF5 dataset "CIAO.K": shape (4,), type "<f8">
                                - n_phot: 1
                        - CIAO.Lp: <HDF5 dataset "CIAO.Lp": shape (4,), type "<f8">
                                - n_phot: 1
                - distance: <HDF5 dataset "distance": shape (2,), type "<f8">
        - GSC 06214 B: <HDF5 group "/objects/GSC 06214 B" (3 members)>
                - LBT: <HDF5 group "/objects/GSC 06214 B/LBT" (1 members)>
                        - LMIRCam.M_77K: <HDF5 dataset "LMIRCam.M_77K": shape (4,), type "<f8">
                                - n_phot: 1
                - MKO: <HDF5 group "/objects/GSC 06214 B/MKO" (4 members)>
                        - NSFCam.H: <HDF5 dataset "NSFCam.H": shape (4,), type "<f8">
                                - n_phot: 1
                        - NSFCam.J: <HDF5 dataset "NSFCam.J": shape (4,), type "<f8">
                                - n_phot: 1
                        - NSFCam.Kp: <HDF5 dataset "NSFCam.Kp": shape (4,), type "<f8">
                                - n_phot: 1
                        - NSFCam.Lp: <HDF5 dataset "NSFCam.Lp": shape (4,), type "<f8">
                                - n_phot: 1
                - distance: <HDF5 dataset "distance": shape (2,), type "<f8">
        - GU Psc b: <HDF5 group "/objects/GU Psc b" (4 members)>
                - CFHT: <HDF5 group "/objects/GU Psc b/CFHT" (4 members)>
                        - Wircam.H: <HDF5 dataset "Wircam.H": shape (4,), type "<f8">
                                - n_phot: 1
                        - Wircam.J: <HDF5 dataset "Wircam.J": shape (4,), type "<f8">
                                - n_phot: 1
                        - Wircam.Ks: <HDF5 dataset "Wircam.Ks": shape (4,), type "<f8">
                                - n_phot: 1
                        - Wircam.Y: <HDF5 dataset "Wircam.Y": shape (4,), type "<f8">
                                - n_phot: 1
                - Gemini: <HDF5 group "/objects/GU Psc b/Gemini" (1 members)>
                        - GMOS-S.z: <HDF5 dataset "GMOS-S.z": shape (4,), type "<f8">
                                - n_phot: 1
                - WISE: <HDF5 group "/objects/GU Psc b/WISE" (2 members)>
                        - WISE.W1: <HDF5 dataset "WISE.W1": shape (4,), type "<f8">
                                - n_phot: 1
                        - WISE.W2: <HDF5 dataset "WISE.W2": shape (4,), type "<f8">
                                - n_phot: 1
                - distance: <HDF5 dataset "distance": shape (2,), type "<f8">
        - HD 1160 B: <HDF5 group "/objects/HD 1160 B" (4 members)>
                - Keck: <HDF5 group "/objects/HD 1160 B/Keck" (1 members)>
                        - NIRC2.Ms: <HDF5 dataset "NIRC2.Ms": shape (4,), type "<f8">
                                - n_phot: 1
                - MKO: <HDF5 group "/objects/HD 1160 B/MKO" (3 members)>
                        - NSFCam.H: <HDF5 dataset "NSFCam.H": shape (4,), type "<f8">
                                - n_phot: 1
                        - NSFCam.J: <HDF5 dataset "NSFCam.J": shape (4,), type "<f8">
                                - n_phot: 1
                        - NSFCam.Ks: <HDF5 dataset "NSFCam.Ks": shape (4,), type "<f8">
                                - n_phot: 1
                - Paranal: <HDF5 group "/objects/HD 1160 B/Paranal" (1 members)>
                        - NACO.Lp: <HDF5 dataset "NACO.Lp": shape (4,), type "<f8">
                                - n_phot: 1
                - distance: <HDF5 dataset "distance": shape (2,), type "<f8">
        - HD 206893 B: <HDF5 group "/objects/HD 206893 B" (2 members)>
                - Paranal: <HDF5 group "/objects/HD 206893 B/Paranal" (6 members)>
                        - NACO.Lp: <HDF5 dataset "NACO.Lp": shape (4,), type "<f8">
                                - n_phot: 1
                        - NACO.Mp: <HDF5 dataset "NACO.Mp": shape (4,), type "<f8">
                                - n_phot: 1
                        - NACO.NB405: <HDF5 dataset "NACO.NB405": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_B_H: <HDF5 dataset "SPHERE.IRDIS_B_H": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_K12_1: <HDF5 dataset "SPHERE.IRDIS_D_K12_1": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_K12_2: <HDF5 dataset "SPHERE.IRDIS_D_K12_2": shape (4,), type "<f8">
                                - n_phot: 1
                - distance: <HDF5 dataset "distance": shape (2,), type "<f8">
        - HD 72946 B: <HDF5 group "/objects/HD 72946 B" (2 members)>
                - Paranal: <HDF5 group "/objects/HD 72946 B/Paranal" (2 members)>
                        - SPHERE.IRDIS_D_H23_2: <HDF5 dataset "SPHERE.IRDIS_D_H23_2": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_H23_3: <HDF5 dataset "SPHERE.IRDIS_D_H23_3": shape (4,), type "<f8">
                                - n_phot: 1
                - distance: <HDF5 dataset "distance": shape (2,), type "<f8">
        - HD 95086 b: <HDF5 group "/objects/HD 95086 b" (3 members)>
                - Gemini: <HDF5 group "/objects/HD 95086 b/Gemini" (2 members)>
                        - GPI.H: <HDF5 dataset "GPI.H": shape (4,), type "<f8">
                                - n_phot: 1
                        - GPI.K1: <HDF5 dataset "GPI.K1": shape (4,), type "<f8">
                                - n_phot: 1
                - Paranal: <HDF5 group "/objects/HD 95086 b/Paranal" (1 members)>
                        - NACO.Lp: <HDF5 dataset "NACO.Lp": shape (4,), type "<f8">
                                - n_phot: 1
                - distance: <HDF5 dataset "distance": shape (2,), type "<f8">
        - HIP 64892 B: <HDF5 group "/objects/HIP 64892 B" (2 members)>
                - Paranal: <HDF5 group "/objects/HIP 64892 B/Paranal" (5 members)>
                        - NACO.Lp: <HDF5 dataset "NACO.Lp": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_H23_2: <HDF5 dataset "SPHERE.IRDIS_D_H23_2": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_H23_3: <HDF5 dataset "SPHERE.IRDIS_D_H23_3": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_K12_1: <HDF5 dataset "SPHERE.IRDIS_D_K12_1": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_K12_2: <HDF5 dataset "SPHERE.IRDIS_D_K12_2": shape (4,), type "<f8">
                                - n_phot: 1
                - distance: <HDF5 dataset "distance": shape (2,), type "<f8">
        - HIP 65426 b: <HDF5 group "/objects/HIP 65426 b" (2 members)>
                - Paranal: <HDF5 group "/objects/HIP 65426 b/Paranal" (7 members)>
                        - NACO.Lp: <HDF5 dataset "NACO.Lp": shape (4,), type "<f8">
                                - n_phot: 1
                        - NACO.Mp: <HDF5 dataset "NACO.Mp": shape (4,), type "<f8">
                                - n_phot: 1
                        - NACO.NB405: <HDF5 dataset "NACO.NB405": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_H23_2: <HDF5 dataset "SPHERE.IRDIS_D_H23_2": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_H23_3: <HDF5 dataset "SPHERE.IRDIS_D_H23_3": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_K12_1: <HDF5 dataset "SPHERE.IRDIS_D_K12_1": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_K12_2: <HDF5 dataset "SPHERE.IRDIS_D_K12_2": shape (4,), type "<f8">
                                - n_phot: 1
                - distance: <HDF5 dataset "distance": shape (2,), type "<f8">
        - HR 8799 b: <HDF5 group "/objects/HR 8799 b" (4 members)>
                - Keck: <HDF5 group "/objects/HR 8799 b/Keck" (3 members)>
                        - NIRC2.H: <HDF5 dataset "NIRC2.H": shape (4,), type "<f8">
                                - n_phot: 1
                        - NIRC2.Ks: <HDF5 dataset "NIRC2.Ks": shape (4,), type "<f8">
                                - n_phot: 1
                        - NIRC2.Ms: <HDF5 dataset "NIRC2.Ms": shape (4,), type "<f8">
                                - n_phot: 1
                - Paranal: <HDF5 group "/objects/HR 8799 b/Paranal" (7 members)>
                        - NACO.Lp: <HDF5 dataset "NACO.Lp": shape (4,), type "<f8">
                                - n_phot: 1
                        - NACO.NB405: <HDF5 dataset "NACO.NB405": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_B_J: <HDF5 dataset "SPHERE.IRDIS_B_J": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_H23_2: <HDF5 dataset "SPHERE.IRDIS_D_H23_2": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_H23_3: <HDF5 dataset "SPHERE.IRDIS_D_H23_3": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_K12_1: <HDF5 dataset "SPHERE.IRDIS_D_K12_1": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_K12_2: <HDF5 dataset "SPHERE.IRDIS_D_K12_2": shape (4,), type "<f8">
                                - n_phot: 1
                - Subaru: <HDF5 group "/objects/HR 8799 b/Subaru" (1 members)>
                        - CIAO.z: <HDF5 dataset "CIAO.z": shape (4,), type "<f8">
                                - n_phot: 1
                - distance: <HDF5 dataset "distance": shape (2,), type "<f8">
        - HR 8799 c: <HDF5 group "/objects/HR 8799 c" (3 members)>
                - Keck: <HDF5 group "/objects/HR 8799 c/Keck" (3 members)>
                        - NIRC2.H: <HDF5 dataset "NIRC2.H": shape (4,), type "<f8">
                                - n_phot: 1
                        - NIRC2.Ks: <HDF5 dataset "NIRC2.Ks": shape (4,), type "<f8">
                                - n_phot: 1
                        - NIRC2.Ms: <HDF5 dataset "NIRC2.Ms": shape (4,), type "<f8">
                                - n_phot: 1
                - Paranal: <HDF5 group "/objects/HR 8799 c/Paranal" (7 members)>
                        - NACO.Lp: <HDF5 dataset "NACO.Lp": shape (4,), type "<f8">
                                - n_phot: 1
                        - NACO.NB405: <HDF5 dataset "NACO.NB405": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_B_J: <HDF5 dataset "SPHERE.IRDIS_B_J": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_H23_2: <HDF5 dataset "SPHERE.IRDIS_D_H23_2": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_H23_3: <HDF5 dataset "SPHERE.IRDIS_D_H23_3": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_K12_1: <HDF5 dataset "SPHERE.IRDIS_D_K12_1": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_K12_2: <HDF5 dataset "SPHERE.IRDIS_D_K12_2": shape (4,), type "<f8">
                                - n_phot: 1
                - distance: <HDF5 dataset "distance": shape (2,), type "<f8">
        - HR 8799 d: <HDF5 group "/objects/HR 8799 d" (3 members)>
                - Keck: <HDF5 group "/objects/HR 8799 d/Keck" (3 members)>
                        - NIRC2.H: <HDF5 dataset "NIRC2.H": shape (4,), type "<f8">
                                - n_phot: 1
                        - NIRC2.Ks: <HDF5 dataset "NIRC2.Ks": shape (4,), type "<f8">
                                - n_phot: 1
                        - NIRC2.Ms: <HDF5 dataset "NIRC2.Ms": shape (4,), type "<f8">
                                - n_phot: 1
                - Paranal: <HDF5 group "/objects/HR 8799 d/Paranal" (7 members)>
                        - NACO.Lp: <HDF5 dataset "NACO.Lp": shape (4,), type "<f8">
                                - n_phot: 1
                        - NACO.NB405: <HDF5 dataset "NACO.NB405": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_B_J: <HDF5 dataset "SPHERE.IRDIS_B_J": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_H23_2: <HDF5 dataset "SPHERE.IRDIS_D_H23_2": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_H23_3: <HDF5 dataset "SPHERE.IRDIS_D_H23_3": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_K12_1: <HDF5 dataset "SPHERE.IRDIS_D_K12_1": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_K12_2: <HDF5 dataset "SPHERE.IRDIS_D_K12_2": shape (4,), type "<f8">
                                - n_phot: 1
                - distance: <HDF5 dataset "distance": shape (2,), type "<f8">
        - HR 8799 e: <HDF5 group "/objects/HR 8799 e" (3 members)>
                - Keck: <HDF5 group "/objects/HR 8799 e/Keck" (1 members)>
                        - NIRC2.Ks: <HDF5 dataset "NIRC2.Ks": shape (4,), type "<f8">
                                - n_phot: 1
                - Paranal: <HDF5 group "/objects/HR 8799 e/Paranal" (7 members)>
                        - NACO.Lp: <HDF5 dataset "NACO.Lp": shape (4,), type "<f8">
                                - n_phot: 1
                        - NACO.NB405: <HDF5 dataset "NACO.NB405": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_B_J: <HDF5 dataset "SPHERE.IRDIS_B_J": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_H23_2: <HDF5 dataset "SPHERE.IRDIS_D_H23_2": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_H23_3: <HDF5 dataset "SPHERE.IRDIS_D_H23_3": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_K12_1: <HDF5 dataset "SPHERE.IRDIS_D_K12_1": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_K12_2: <HDF5 dataset "SPHERE.IRDIS_D_K12_2": shape (4,), type "<f8">
                                - n_phot: 1
                - distance: <HDF5 dataset "distance": shape (2,), type "<f8">
        - PDS 70 b: <HDF5 group "/objects/PDS 70 b" (4 members)>
                - Keck: <HDF5 group "/objects/PDS 70 b/Keck" (1 members)>
                        - NIRC2.Lp: <HDF5 dataset "NIRC2.Lp": shape (4,), type "<f8">
                                - n_phot: 1
                - MKO: <HDF5 group "/objects/PDS 70 b/MKO" (2 members)>
                        - NSFCam.H: <HDF5 dataset "NSFCam.H": shape (4,), type "<f8">
                                - n_phot: 1
                        - NSFCam.J: <HDF5 dataset "NSFCam.J": shape (4,), type "<f8">
                                - n_phot: 1
                - Paranal: <HDF5 group "/objects/PDS 70 b/Paranal" (7 members)>
                        - NACO.Lp: <HDF5 dataset "NACO.Lp": shape (4,), type "<f8">
                                - n_phot: 1
                        - NACO.Mp: <HDF5 dataset "NACO.Mp": shape (4,), type "<f8">
                                - n_phot: 1
                        - NACO.NB405: <HDF5 dataset "NACO.NB405": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_H23_2: <HDF5 dataset "SPHERE.IRDIS_D_H23_2": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_H23_3: <HDF5 dataset "SPHERE.IRDIS_D_H23_3": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_K12_1: <HDF5 dataset "SPHERE.IRDIS_D_K12_1": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_K12_2: <HDF5 dataset "SPHERE.IRDIS_D_K12_2": shape (4,), type "<f8">
                                - n_phot: 1
                - distance: <HDF5 dataset "distance": shape (2,), type "<f8">
        - PDS 70 c: <HDF5 group "/objects/PDS 70 c" (3 members)>
                - Keck: <HDF5 group "/objects/PDS 70 c/Keck" (1 members)>
                        - NIRC2.Lp: <HDF5 dataset "NIRC2.Lp": shape (4,), type "<f8">
                                - n_phot: 1
                - Paranal: <HDF5 group "/objects/PDS 70 c/Paranal" (1 members)>
                        - NACO.NB405: <HDF5 dataset "NACO.NB405": shape (4,), type "<f8">
                                - n_phot: 1
                - distance: <HDF5 dataset "distance": shape (2,), type "<f8">
        - PZ Tel B: <HDF5 group "/objects/PZ Tel B" (3 members)>
                - Gemini: <HDF5 group "/objects/PZ Tel B/Gemini" (2 members)>
                        - NICI.ED286: <HDF5 dataset "NICI.ED286": shape (4,), type "<f8">
                                - n_phot: 1
                        - NIRI.H2S1v2-1-G0220: <HDF5 dataset "NIRI.H2S1v2-1-G0220": shape (4,), type "<f8">
                                - n_phot: 1
                - Paranal: <HDF5 group "/objects/PZ Tel B/Paranal" (12 members)>
                        - NACO.H: <HDF5 dataset "NACO.H": shape (4,), type "<f8">
                                - n_phot: 1
                        - NACO.J: <HDF5 dataset "NACO.J": shape (4,), type "<f8">
                                - n_phot: 1
                        - NACO.Ks: <HDF5 dataset "NACO.Ks": shape (4,), type "<f8">
                                - n_phot: 1
                        - NACO.Lp: <HDF5 dataset "NACO.Lp": shape (4,), type "<f8">
                                - n_phot: 1
                        - NACO.Mp: <HDF5 dataset "NACO.Mp": shape (4,), type "<f8">
                                - n_phot: 1
                        - NACO.NB405: <HDF5 dataset "NACO.NB405": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_H23_2: <HDF5 dataset "SPHERE.IRDIS_D_H23_2": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_H23_3: <HDF5 dataset "SPHERE.IRDIS_D_H23_3": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_K12_1: <HDF5 dataset "SPHERE.IRDIS_D_K12_1": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_K12_2: <HDF5 dataset "SPHERE.IRDIS_D_K12_2": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.ZIMPOL_I_PRIM: <HDF5 dataset "SPHERE.ZIMPOL_I_PRIM": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.ZIMPOL_R_PRIM: <HDF5 dataset "SPHERE.ZIMPOL_R_PRIM": shape (4,), type "<f8">
                                - n_phot: 1
                - distance: <HDF5 dataset "distance": shape (2,), type "<f8">
        - ROXs 42 Bb: <HDF5 group "/objects/ROXs 42 Bb" (2 members)>
                - Keck: <HDF5 group "/objects/ROXs 42 Bb/Keck" (5 members)>
                        - NIRC2.H: <HDF5 dataset "NIRC2.H": shape (4,), type "<f8">
                                - n_phot: 1
                        - NIRC2.J: <HDF5 dataset "NIRC2.J": shape (4,), type "<f8">
                                - n_phot: 1
                        - NIRC2.Ks: <HDF5 dataset "NIRC2.Ks": shape (4,), type "<f8">
                                - n_phot: 1
                        - NIRC2.Lp: <HDF5 dataset "NIRC2.Lp": shape (4,), type "<f8">
                                - n_phot: 1
                        - NIRC2.Ms: <HDF5 dataset "NIRC2.Ms": shape (4,), type "<f8">
                                - n_phot: 1
                - distance: <HDF5 dataset "distance": shape (2,), type "<f8">
        - RZ Psc B: <HDF5 group "/objects/RZ Psc B" (2 members)>
                - Paranal: <HDF5 group "/objects/RZ Psc B/Paranal" (2 members)>
                        - SPHERE.IRDIS_B_H: <HDF5 dataset "SPHERE.IRDIS_B_H": shape (4, 2), type "<f8">
                                - n_phot: 2
                        - SPHERE.IRDIS_B_Ks: <HDF5 dataset "SPHERE.IRDIS_B_Ks": shape (4,), type "<f8">
                                - n_phot: 1
                - distance: <HDF5 dataset "distance": shape (2,), type "<f8">
        - beta Pic b: <HDF5 group "/objects/beta Pic b" (4 members)>
                - Gemini: <HDF5 group "/objects/beta Pic b/Gemini" (1 members)>
                        - NICI.ED286: <HDF5 dataset "NICI.ED286": shape (4,), type "<f8">
                                - n_phot: 1
                - LCO: <HDF5 group "/objects/beta Pic b/LCO" (1 members)>
                        - VisAO.Ys: <HDF5 dataset "VisAO.Ys": shape (4,), type "<f8">
                                - n_phot: 1
                - Paranal: <HDF5 group "/objects/beta Pic b/Paranal" (9 members)>
                        - NACO.H: <HDF5 dataset "NACO.H": shape (4,), type "<f8">
                                - n_phot: 1
                        - NACO.J: <HDF5 dataset "NACO.J": shape (4,), type "<f8">
                                - n_phot: 1
                        - NACO.Ks: <HDF5 dataset "NACO.Ks": shape (4,), type "<f8">
                                - n_phot: 1
                        - NACO.Lp: <HDF5 dataset "NACO.Lp": shape (4,), type "<f8">
                                - n_phot: 1
                        - NACO.Mp: <HDF5 dataset "NACO.Mp": shape (4,), type "<f8">
                                - n_phot: 1
                        - NACO.NB374: <HDF5 dataset "NACO.NB374": shape (4,), type "<f8">
                                - n_phot: 1
                        - NACO.NB405: <HDF5 dataset "NACO.NB405": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_K12_1: <HDF5 dataset "SPHERE.IRDIS_D_K12_1": shape (4,), type "<f8">
                                - n_phot: 1
                        - SPHERE.IRDIS_D_K12_2: <HDF5 dataset "SPHERE.IRDIS_D_K12_2": shape (4,), type "<f8">
                                - n_phot: 1
                - distance: <HDF5 dataset "distance": shape (2,), type "<f8">
        - kappa And b: <HDF5 group "/objects/kappa And b" (4 members)>
                - Keck: <HDF5 group "/objects/kappa And b/Keck" (1 members)>
                        - NIRC2.Lp: <HDF5 dataset "NIRC2.Lp": shape (4,), type "<f8">
                                - n_phot: 1
                - LBT: <HDF5 group "/objects/kappa And b/LBT" (1 members)>
                        - LMIRCam.M_77K: <HDF5 dataset "LMIRCam.M_77K": shape (4,), type "<f8">
                                - n_phot: 1
                - Subaru: <HDF5 group "/objects/kappa And b/Subaru" (3 members)>
                        - CIAO.H: <HDF5 dataset "CIAO.H": shape (4,), type "<f8">
                                - n_phot: 1
                        - CIAO.J: <HDF5 dataset "CIAO.J": shape (4,), type "<f8">
                                - n_phot: 1
                        - CIAO.Ks: <HDF5 dataset "CIAO.Ks": shape (4,), type "<f8">
                                - n_phot: 1
                - distance: <HDF5 dataset "distance": shape (2,), type "<f8">
- photometry: <HDF5 group "/photometry" (1 members)>
        - vlm-plx: <HDF5 group "/photometry/vlm-plx" (11 members)>
                - 2MASS: <HDF5 group "/photometry/vlm-plx/2MASS" (3 members)>
                        - 2MASS.H: <HDF5 dataset "2MASS.H": shape (618,), type ">f4">
                        - 2MASS.J: <HDF5 dataset "2MASS.J": shape (618,), type ">f4">
                        - 2MASS.Ks: <HDF5 dataset "2MASS.Ks": shape (618,), type ">f4">
                - MKO: <HDF5 group "/photometry/vlm-plx/MKO" (6 members)>
                        - NSFCam.H: <HDF5 dataset "NSFCam.H": shape (618,), type ">f4">
                        - NSFCam.J: <HDF5 dataset "NSFCam.J": shape (618,), type ">f4">
                        - NSFCam.K: <HDF5 dataset "NSFCam.K": shape (618,), type ">f4">
                        - NSFCam.Lp: <HDF5 dataset "NSFCam.Lp": shape (618,), type ">f4">
                        - NSFCam.Mp: <HDF5 dataset "NSFCam.Mp": shape (618,), type ">f4">
                        - NSFCam.Y: <HDF5 dataset "NSFCam.Y": shape (618,), type ">f4">
                - dec: <HDF5 dataset "dec": shape (618,), type ">f8">
                - distance: <HDF5 dataset "distance": shape (618,), type "<f4">
                - distance_error: <HDF5 dataset "distance_error": shape (618,), type "<f4">
                - flag: <HDF5 dataset "flag": shape (618,), type "|O">
                - name: <HDF5 dataset "name": shape (618,), type "|O">
                - parallax: <HDF5 dataset "parallax": shape (618,), type ">f4">
                - parallax_error: <HDF5 dataset "parallax_error": shape (618,), type ">f4">
                - ra: <HDF5 dataset "ra": shape (618,), type ">f8">
                - sptype: <HDF5 dataset "sptype": shape (618,), type "|O">
- spectra: <HDF5 group "/spectra" (1 members)>
        - calibration: <HDF5 group "/spectra/calibration" (1 members)>
                - vega: <HDF5 dataset "vega": shape (3, 8827), type "<f8">

Synthetic photometry from isochrones

Magnitudes from the isochrone data can be extracted with the get_isochrone function of ReadIsochrone. However, in this example, we consistently recompute the synthetic photometry by making use of both the evolutionary trakcs and the synthetic spectra.

The isochrones will be iterpolated for three different ages and the synthetic photometry is computed at 100 logarithmically spaced masses.

[11]:
ages = [20., 100., 1000.]  # (Myr)
masses = np.logspace(0., 3., 100)  # (Mjup)

Objects of ReadIsochones are initiated for both the AMES-Cond and AMES-Dusty isochrones. We note though that the evolutionary data of these two models are actually the same. Only the magnitudes of the isochrones (which we do not use) are different.

[12]:
read_iso_cond = species.ReadIsochrone(tag='iso_cond')
read_iso_dusty = species.ReadIsochrone(tag='iso_dusty')

The colors and magnitudes are computed by chosing the corresponding model grids from the database. The output is stored in ColorMagBox objects for the three different ages.

[13]:
boxes = []

for item in ages:

    modelcolor1 = read_iso_cond.get_color_magnitude(age=item,
                                                    masses=masses,
                                                    model='ames-cond',
                                                    filters_color=('MKO/NSFCam.H', 'MKO/NSFCam.Lp'),
                                                    filter_mag='MKO/NSFCam.Lp')

    modelcolor2 = read_iso_dusty.get_color_magnitude(age=item,
                                                     masses=masses,
                                                     model='ames-dusty',
                                                     filters_color=('MKO/NSFCam.H', 'MKO/NSFCam.Lp'),
                                                     filter_mag='MKO/NSFCam.Lp')

    boxes.append(modelcolor1)
    boxes.append(modelcolor2)
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:228: UserWarning: The value of teff is 4018.701890028295, which is above the upper bound of the model grid (4000.0). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 4018.701890028295, 'logg': 4.3520097138585845, 'mass': 932.60334688322, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:228: UserWarning: The value of teff is 4163.517520486652, which is above the upper bound of the model grid (4000.0). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 4163.517520486652, 'logg': 4.329146850334322, 'mass': 1000.0, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 2.917784581524866, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 501.3728693602355, 'logg': 2.917784581524866, 'mass': 1.0, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 2.972779343287681, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 502.51561905255875, 'logg': 2.972779343287681, 'mass': 1.0722672220103233, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 3.035244115774989, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 504.9110749694396, 'logg': 3.035244115774989, 'mass': 1.1497569953977358, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 3.1022230438434617, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 507.4796438308816, 'logg': 3.1022230438434617, 'mass': 1.2328467394420661, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 3.2067743991749165, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 519.9830583907551, 'logg': 3.2067743991749165, 'mass': 1.321941148466029, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 3.3063735241310974, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 533.9699983677936, 'logg': 3.3063735241310974, 'mass': 1.4174741629268053, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 3.338631698699009, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 543.9407068706029, 'logg': 3.338631698699009, 'mass': 1.5199110829529336, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 3.3721167739343065, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 556.1780019724513, 'logg': 3.3721167739343065, 'mass': 1.6297508346206442, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 3.406958013871118, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 570.788844526598, 'logg': 3.406958013871118, 'mass': 1.7475284000076838, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 3.444317133429558, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 586.455572083363, 'logg': 3.444317133429558, 'mass': 1.8738174228603839, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 3.484376092775238, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 603.2544905186481, 'logg': 3.484376092775238, 'mass': 2.0092330025650473, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:228: UserWarning: The value of teff is 4080.941184987095, which is above the upper bound of the model grid (4000.0). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 4080.941184987095, 'logg': 4.668039214755509, 'mass': 657.9332246575682, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:228: UserWarning: The value of teff is 4184.730732201826, which is above the upper bound of the model grid (4000.0). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 4184.730732201826, 'logg': 4.6566960948413305, 'mass': 705.4802310718645, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:228: UserWarning: The value of teff is 4324.721356066847, which is above the upper bound of the model grid (4000.0). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 4324.721356066847, 'logg': 4.64125318265924, 'mass': 756.463327554629, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:228: UserWarning: The value of teff is 4511.081667094552, which is above the upper bound of the model grid (4000.0). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 4511.081667094552, 'logg': 4.6107725046114005, 'mass': 811.1308307896873, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:228: UserWarning: The value of teff is 4703.704854345524, which is above the upper bound of the model grid (4000.0). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 4703.704854345524, 'logg': 4.572016990295442, 'mass': 869.7490026177834, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:228: UserWarning: The value of teff is 4914.026121931334, which is above the upper bound of the model grid (4000.0). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 4914.026121931334, 'logg': 4.528038855434338, 'mass': 932.60334688322, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:228: UserWarning: The value of teff is 5128.711930018601, which is above the upper bound of the model grid (4000.0). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 5128.711930018601, 'logg': 4.487440551002966, 'mass': 1000.0, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 2.7961643169092065, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 501.58228263626506, 'logg': 2.7961643169092065, 'mass': 1.0, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 2.807202282142855, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 501.6881276697485, 'logg': 2.807202282142855, 'mass': 1.0722672220103233, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 2.8207367618605548, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 501.66498143680707, 'logg': 2.8207367618605548, 'mass': 1.1497569953977358, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 2.835249340828809, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 501.6401624899111, 'logg': 2.835249340828809, 'mass': 1.2328467394420661, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 2.855554520370349, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 501.6536660458051, 'logg': 2.855554520370349, 'mass': 1.321941148466029, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 2.8798041133905197, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 501.6890923462297, 'logg': 2.8798041133905197, 'mass': 1.4174741629268053, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 2.9058061571331404, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 501.72707880697214, 'logg': 2.9058061571331404, 'mass': 1.5199110829529336, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 2.933837016464927, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 501.8458205253471, 'logg': 2.933837016464927, 'mass': 1.6297508346206442, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 2.9643361277954554, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 502.20372397743654, 'logg': 2.9643361277954554, 'mass': 1.7475284000076838, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 3.0024737804589394, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 503.0056049678062, 'logg': 3.0024737804589394, 'mass': 1.8738174228603839, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 3.044216208740176, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 503.93073039348104, 'logg': 3.044216208740176, 'mass': 2.0092330025650473, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 3.088975246353262, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 504.92271206368054, 'logg': 3.088975246353262, 'mass': 2.154434690031884, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 3.1487127161744426, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 506.11774555623947, 'logg': 3.1487127161744426, 'mass': 2.3101297000831598, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 3.2281475586776205, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 506.36601770555274, 'logg': 3.2281475586776205, 'mass': 2.4770763559917106, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 3.3306644276556674, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 505.0681954083842, 'logg': 3.3306644276556674, 'mass': 2.6560877829466865, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 3.4405899059639538, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 503.6765830991362, 'logg': 3.4405899059639538, 'mass': 2.848035868435802, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:228: UserWarning: The value of teff is 4120.946352836504, which is above the upper bound of the model grid (4000.0). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 4120.946352836504, 'logg': 4.660088284523991, 'mass': 705.4802310718645, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:228: UserWarning: The value of teff is 4300.40424121095, which is above the upper bound of the model grid (4000.0). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 4300.40424121095, 'logg': 4.626879773988859, 'mass': 756.463327554629, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:228: UserWarning: The value of teff is 4506.927166172272, which is above the upper bound of the model grid (4000.0). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 4506.927166172272, 'logg': 4.595579378458551, 'mass': 811.1308307896873, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:228: UserWarning: The value of teff is 4707.3014562864355, which is above the upper bound of the model grid (4000.0). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 4707.3014562864355, 'logg': 4.556022653727256, 'mass': 869.7490026177834, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:228: UserWarning: The value of teff is 4921.624179159618, which is above the upper bound of the model grid (4000.0). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 4921.624179159618, 'logg': 4.516029141575753, 'mass': 932.60334688322, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:228: UserWarning: The value of teff is 5152.162284450254, which is above the upper bound of the model grid (4000.0). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 5152.162284450254, 'logg': 4.467440551002966, 'mass': 1000.0, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:209: UserWarning: The value of Teff is NaN for the following isochrone sample: {'teff': nan, 'logg': nan, 'mass': 1.0, 'distance': 10.0}. Setting the magnitudes to NaN.
  warnings.warn(f'The value of Teff is NaN for the following isochrone sample: '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:209: UserWarning: The value of Teff is NaN for the following isochrone sample: {'teff': nan, 'logg': nan, 'mass': 1.0722672220103233, 'distance': 10.0}. Setting the magnitudes to NaN.
  warnings.warn(f'The value of Teff is NaN for the following isochrone sample: '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:209: UserWarning: The value of Teff is NaN for the following isochrone sample: {'teff': nan, 'logg': nan, 'mass': 1.1497569953977358, 'distance': 10.0}. Setting the magnitudes to NaN.
  warnings.warn(f'The value of Teff is NaN for the following isochrone sample: '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:209: UserWarning: The value of Teff is NaN for the following isochrone sample: {'teff': nan, 'logg': nan, 'mass': 1.2328467394420661, 'distance': 10.0}. Setting the magnitudes to NaN.
  warnings.warn(f'The value of Teff is NaN for the following isochrone sample: '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:209: UserWarning: The value of Teff is NaN for the following isochrone sample: {'teff': nan, 'logg': nan, 'mass': 1.321941148466029, 'distance': 10.0}. Setting the magnitudes to NaN.
  warnings.warn(f'The value of Teff is NaN for the following isochrone sample: '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:209: UserWarning: The value of Teff is NaN for the following isochrone sample: {'teff': nan, 'logg': nan, 'mass': 1.4174741629268053, 'distance': 10.0}. Setting the magnitudes to NaN.
  warnings.warn(f'The value of Teff is NaN for the following isochrone sample: '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:209: UserWarning: The value of Teff is NaN for the following isochrone sample: {'teff': nan, 'logg': nan, 'mass': 1.5199110829529336, 'distance': 10.0}. Setting the magnitudes to NaN.
  warnings.warn(f'The value of Teff is NaN for the following isochrone sample: '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:209: UserWarning: The value of Teff is NaN for the following isochrone sample: {'teff': nan, 'logg': nan, 'mass': 1.6297508346206442, 'distance': 10.0}. Setting the magnitudes to NaN.
  warnings.warn(f'The value of Teff is NaN for the following isochrone sample: '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:209: UserWarning: The value of Teff is NaN for the following isochrone sample: {'teff': nan, 'logg': nan, 'mass': 1.7475284000076838, 'distance': 10.0}. Setting the magnitudes to NaN.
  warnings.warn(f'The value of Teff is NaN for the following isochrone sample: '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:209: UserWarning: The value of Teff is NaN for the following isochrone sample: {'teff': nan, 'logg': nan, 'mass': 1.8738174228603839, 'distance': 10.0}. Setting the magnitudes to NaN.
  warnings.warn(f'The value of Teff is NaN for the following isochrone sample: '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:209: UserWarning: The value of Teff is NaN for the following isochrone sample: {'teff': nan, 'logg': nan, 'mass': 2.0092330025650473, 'distance': 10.0}. Setting the magnitudes to NaN.
  warnings.warn(f'The value of Teff is NaN for the following isochrone sample: '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:209: UserWarning: The value of Teff is NaN for the following isochrone sample: {'teff': nan, 'logg': nan, 'mass': 2.154434690031884, 'distance': 10.0}. Setting the magnitudes to NaN.
  warnings.warn(f'The value of Teff is NaN for the following isochrone sample: '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:209: UserWarning: The value of Teff is NaN for the following isochrone sample: {'teff': nan, 'logg': nan, 'mass': 2.3101297000831598, 'distance': 10.0}. Setting the magnitudes to NaN.
  warnings.warn(f'The value of Teff is NaN for the following isochrone sample: '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:209: UserWarning: The value of Teff is NaN for the following isochrone sample: {'teff': nan, 'logg': nan, 'mass': 2.4770763559917106, 'distance': 10.0}. Setting the magnitudes to NaN.
  warnings.warn(f'The value of Teff is NaN for the following isochrone sample: '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:209: UserWarning: The value of Teff is NaN for the following isochrone sample: {'teff': nan, 'logg': nan, 'mass': 2.6560877829466865, 'distance': 10.0}. Setting the magnitudes to NaN.
  warnings.warn(f'The value of Teff is NaN for the following isochrone sample: '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:209: UserWarning: The value of Teff is NaN for the following isochrone sample: {'teff': nan, 'logg': nan, 'mass': 2.848035868435802, 'distance': 10.0}. Setting the magnitudes to NaN.
  warnings.warn(f'The value of Teff is NaN for the following isochrone sample: '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:209: UserWarning: The value of Teff is NaN for the following isochrone sample: {'teff': nan, 'logg': nan, 'mass': 3.0538555088334154, 'distance': 10.0}. Setting the magnitudes to NaN.
  warnings.warn(f'The value of Teff is NaN for the following isochrone sample: '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:209: UserWarning: The value of Teff is NaN for the following isochrone sample: {'teff': nan, 'logg': nan, 'mass': 3.2745491628777286, 'distance': 10.0}. Setting the magnitudes to NaN.
  warnings.warn(f'The value of Teff is NaN for the following isochrone sample: '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:209: UserWarning: The value of Teff is NaN for the following isochrone sample: {'teff': nan, 'logg': nan, 'mass': 3.511191734215131, 'distance': 10.0}. Setting the magnitudes to NaN.
  warnings.warn(f'The value of Teff is NaN for the following isochrone sample: '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 3.0001460766654837, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 502.332884883845, 'logg': 3.0001460766654837, 'mass': 3.7649358067924683, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 3.047947876133678, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 502.22378010837764, 'logg': 3.047947876133678, 'mass': 4.0370172585965545, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 3.0992041788565317, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 502.1067906338791, 'logg': 3.0992041788565317, 'mass': 4.328761281083058, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 3.150891938884781, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 502.24537153600613, 'logg': 3.150891938884781, 'mass': 4.641588833612779, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 3.182737668064635, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 504.2960734607087, 'logg': 3.182737668064635, 'mass': 4.977023564332112, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 3.2168847996252103, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 506.49497391668075, 'logg': 3.2168847996252103, 'mass': 5.3366992312063095, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 3.261573007971667, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 508.2034265008656, 'logg': 3.261573007971667, 'mass': 5.722367659350217, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 3.333802455475893, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 508.0799020173222, 'logg': 3.333802455475893, 'mass': 6.1359072734131725, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 3.4112517244985905, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 507.94745076250285, 'logg': 3.4112517244985905, 'mass': 6.579332246575681, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '
/Users/tomasstolker/applications/species/species/read/read_isochrone.py:218: UserWarning: The value of logg is 3.494298037040288, which is below the lower bound of the model grid (3.5). Setting the magnitudes to NaN for the following isochrone sample: {'teff': 507.80542762344595, 'logg': 3.494298037040288, 'mass': 7.054802310718643, 'distance': 10.0}.
  warnings.warn(f'The value of {item_bounds} is {model_param[item_bounds]}, '

Some warnings are printed when Teff or log(g) from the evolutionary tracks are outside the parameter boundaries of the grid with spectra. Also, some of the chosen masses are below the lowest masses that are available in the evolutionary tracks. Therefore these colors and magnitudes are set to NaN and will be ignored when plotting the isochrones later one.

Synthetic photometry from blackbody spectra

In addition to the isochrones, we also calculate colors and magnitudes for blackbody radiation. We start by creating an instance of ReadPlanck for a wavelength range between 0.5 and 10 um.

[14]:
read_planck = species.ReadPlanck(wavel_range=(0.5, 10.))

Next, we use the get_color_magnitude methode to calculate the synthetic photometry for the same filters from before. Here we chose 100 logarithmically-spaced temperatures between 100 and 10000 K. The radius, which only impacts the absolute magnitude, is set to 1 Rjup.

[15]:
color_planck = read_planck.get_color_magnitude(temperatures=np.logspace(2, 4, 100),
                                               radius=1.,
                                               filters_color=('MKO/NSFCam.H', 'MKO/NSFCam.Lp'),
                                               filter_mag='MKO/NSFCam.Lp')

The returned ColorMagBox is added to the list of boxes.

[16]:
boxes.append(color_planck)

Photometry of directly imaged objects

Before selecting the photometric data of the directly imaged planets and brown dwarfs, let’s see which objects and magnitudes are stored in the database.

[17]:
database.list_companions()
Object name = beta Pic b
Distance (pc) = 19.75 +/- 0.13
LCO/VisAO.Ys (mag) = 15.53 +/- 0.34
Paranal/NACO.J (mag) = 14.11 +/- 0.21
Gemini/NICI.ED286 (mag) = 13.18 +/- 0.15
Paranal/NACO.H (mag) = 13.32 +/- 0.14
Paranal/NACO.Ks (mag) = 12.64 +/- 0.11
Paranal/NACO.NB374 (mag) = 11.25 +/- 0.23
Paranal/NACO.Lp (mag) = 11.3 +/- 0.06
Paranal/NACO.NB405 (mag) = 10.98 +/- 0.05
Paranal/NACO.Mp (mag) = 11.1 +/- 0.12
Paranal/SPHERE.IRDIS_D_K12_1 (mag) = 12.568 +/- 0.003
Paranal/SPHERE.IRDIS_D_K12_2 (mag) = 12.206 +/- 0.002

Object name = HIP 65426 b
Distance (pc) = 109.21 +/- 0.75
Paranal/SPHERE.IRDIS_D_H23_2 (mag) = 17.94 +/- 0.05
Paranal/SPHERE.IRDIS_D_H23_3 (mag) = 17.58 +/- 0.06
Paranal/SPHERE.IRDIS_D_K12_1 (mag) = 17.01 +/- 0.09
Paranal/SPHERE.IRDIS_D_K12_2 (mag) = 16.79 +/- 0.09
Paranal/NACO.Lp (mag) = 15.33 +/- 0.12
Paranal/NACO.NB405 (mag) = 15.23 +/- 0.22
Paranal/NACO.Mp (mag) = 14.65 +/- 0.29

Object name = 51 Eri b
Distance (pc) = 29.78 +/- 0.12
MKO/NSFCam.J (mag) = 19.04 +/- 0.4
MKO/NSFCam.H (mag) = 18.99 +/- 0.21
MKO/NSFCam.K (mag) = 18.67 +/- 0.19
Paranal/SPHERE.IRDIS_B_H (mag) = 19.45 +/- 0.29
Paranal/SPHERE.IRDIS_D_H23_2 (mag) = 18.41 +/- 0.26
Paranal/SPHERE.IRDIS_D_K12_1 (mag) = 17.55 +/- 0.14
Keck/NIRC2.Lp (mag) = 16.2 +/- 0.11
Keck/NIRC2.Ms (mag) = 16.1 +/- 0.5

Object name = HR 8799 b
Distance (pc) = 41.29 +/- 0.15
Subaru/CIAO.z (mag) = 21.22 +/- 0.29
Paranal/SPHERE.IRDIS_B_J (mag) = 19.78 +/- 0.09
Keck/NIRC2.H (mag) = 18.05 +/- 0.09
Paranal/SPHERE.IRDIS_D_H23_2 (mag) = 18.08 +/- 0.14
Paranal/SPHERE.IRDIS_D_H23_3 (mag) = 17.78 +/- 0.1
Keck/NIRC2.Ks (mag) = 17.03 +/- 0.08
Paranal/SPHERE.IRDIS_D_K12_1 (mag) = 17.15 +/- 0.06
Paranal/SPHERE.IRDIS_D_K12_2 (mag) = 16.97 +/- 0.09
Paranal/NACO.Lp (mag) = 15.52 +/- 0.1
Paranal/NACO.NB405 (mag) = 14.82 +/- 0.18
Keck/NIRC2.Ms (mag) = 16.05 +/- 0.3

Object name = HR 8799 c
Distance (pc) = 41.29 +/- 0.15
Paranal/SPHERE.IRDIS_B_J (mag) = 18.6 +/- 0.13
Keck/NIRC2.H (mag) = 17.06 +/- 0.13
Paranal/SPHERE.IRDIS_D_H23_2 (mag) = 17.09 +/- 0.12
Paranal/SPHERE.IRDIS_D_H23_3 (mag) = 16.78 +/- 0.1
Keck/NIRC2.Ks (mag) = 16.11 +/- 0.08
Paranal/SPHERE.IRDIS_D_K12_1 (mag) = 16.19 +/- 0.05
Paranal/SPHERE.IRDIS_D_K12_2 (mag) = 15.86 +/- 0.07
Paranal/NACO.Lp (mag) = 14.65 +/- 0.11
Paranal/NACO.NB405 (mag) = 13.97 +/- 0.11
Keck/NIRC2.Ms (mag) = 15.03 +/- 0.14

Object name = HR 8799 d
Distance (pc) = 41.29 +/- 0.15
Paranal/SPHERE.IRDIS_B_J (mag) = 18.59 +/- 0.37
Keck/NIRC2.H (mag) = 16.71 +/- 0.24
Paranal/SPHERE.IRDIS_D_H23_2 (mag) = 17.02 +/- 0.17
Paranal/SPHERE.IRDIS_D_H23_3 (mag) = 16.85 +/- 0.16
Keck/NIRC2.Ks (mag) = 16.09 +/- 0.12
Paranal/SPHERE.IRDIS_D_K12_1 (mag) = 16.2 +/- 0.07
Paranal/SPHERE.IRDIS_D_K12_2 (mag) = 15.84 +/- 0.1
Paranal/NACO.Lp (mag) = 14.55 +/- 0.14
Paranal/NACO.NB405 (mag) = 13.87 +/- 0.15
Keck/NIRC2.Ms (mag) = 14.65 +/- 0.35

Object name = HR 8799 e
Distance (pc) = 41.29 +/- 0.15
Paranal/SPHERE.IRDIS_B_J (mag) = 18.4 +/- 0.21
Paranal/SPHERE.IRDIS_D_H23_2 (mag) = 16.91 +/- 0.2
Paranal/SPHERE.IRDIS_D_H23_3 (mag) = 16.68 +/- 0.21
Keck/NIRC2.Ks (mag) = 15.91 +/- 0.22
Paranal/SPHERE.IRDIS_D_K12_1 (mag) = 16.12 +/- 0.1
Paranal/SPHERE.IRDIS_D_K12_2 (mag) = 15.82 +/- 0.11
Paranal/NACO.Lp (mag) = 14.49 +/- 0.21
Paranal/NACO.NB405 (mag) = 13.72 +/- 0.2

Object name = HD 95086 b
Distance (pc) = 86.44 +/- 0.24
Gemini/GPI.H (mag) = 20.51 +/- 0.25
Gemini/GPI.K1 (mag) = 18.99 +/- 0.2
Paranal/NACO.Lp (mag) = 16.27 +/- 0.19

Object name = PDS 70 b
Distance (pc) = 113.43 +/- 0.52
Paranal/SPHERE.IRDIS_D_H23_2 (mag) = 18.12 +/- 0.21
Paranal/SPHERE.IRDIS_D_H23_3 (mag) = 17.97 +/- 0.18
Paranal/SPHERE.IRDIS_D_K12_1 (mag) = 16.66 +/- 0.04
Paranal/SPHERE.IRDIS_D_K12_2 (mag) = 16.37 +/- 0.06
MKO/NSFCam.J (mag) = 20.04 +/- 0.09
MKO/NSFCam.H (mag) = 18.24 +/- 0.04
Paranal/NACO.Lp (mag) = 14.68 +/- 0.22
Paranal/NACO.NB405 (mag) = 14.68 +/- 0.27
Paranal/NACO.Mp (mag) = 13.8 +/- 0.27
Keck/NIRC2.Lp (mag) = 14.64 +/- 0.18

Object name = PDS 70 c
Distance (pc) = 113.43 +/- 0.52
Paranal/NACO.NB405 (mag) = 14.91 +/- 0.35
Keck/NIRC2.Lp (mag) = 15.5 +/- 0.46

Object name = 2M1207 b
Distance (pc) = 64.42 +/- 0.65
HST/NICMOS1.F090M (mag) = 22.58 +/- 0.35
HST/NICMOS1.F110M (mag) = 20.61 +/- 0.15
HST/NICMOS1.F145M (mag) = 19.05 +/- 0.03
HST/NICMOS1.F160W (mag) = 18.27 +/- 0.02
Paranal/NACO.J (mag) = 20.0 +/- 0.2
Paranal/NACO.H (mag) = 18.09 +/- 0.21
Paranal/NACO.Ks (mag) = 16.93 +/- 0.11
Paranal/NACO.Lp (mag) = 15.28 +/- 0.14

Object name = AB Pic B
Distance (pc) = 50.12 +/- 0.07
Paranal/NACO.J (mag) = 16.18 +/- 0.1
Paranal/NACO.H (mag) = 14.69 +/- 0.1
Paranal/NACO.Ks (mag) = 14.14 +/- 0.08

Object name = HD 206893 B
Distance (pc) = 40.81 +/- 0.11
Paranal/SPHERE.IRDIS_B_H (mag) = 16.79 +/- 0.06
Paranal/SPHERE.IRDIS_D_K12_1 (mag) = 15.2 +/- 0.1
Paranal/SPHERE.IRDIS_D_K12_2 (mag) = 14.88 +/- 0.09
Paranal/NACO.Lp (mag) = 13.79 +/- 0.31
Paranal/NACO.NB405 (mag) = 13.16 +/- 0.34
Paranal/NACO.Mp (mag) = 12.77 +/- 0.27

Object name = RZ Psc B
Distance (pc) = 195.86 +/- 4.03
Paranal/SPHERE.IRDIS_B_H (mag) = (13.71, 0.14) +/- (13.85, 0.26)
Paranal/SPHERE.IRDIS_B_Ks (mag) = 13.51 +/- 0.2

Object name = GQ Lup B
Distance (pc) = 151.82 +/- 1.1
HST/WFPC2-PC.F606W (mag) = 19.19 +/- 0.07
HST/WFPC2-PC.F814W (mag) = 17.67 +/- 0.05
HST/NICMOS2.F171M (mag) = 13.84 +/- 0.13
HST/NICMOS2.F190N (mag) = 14.08 +/- 0.2
HST/NICMOS2.F215N (mag) = 13.4 +/- 0.15
Magellan/VisAO.ip (mag) = 18.89 +/- 0.24
Magellan/VisAO.zp (mag) = 16.4 +/- 0.1
Magellan/VisAO.Ys (mag) = 15.88 +/- 0.1
Paranal/NACO.Ks (mag) = (13.474, 0.031) +/- (13.386, 0.032)
Subaru/CIAO.CH4s (mag) = 13.76 +/- 0.26
Subaru/CIAO.K (mag) = 13.37 +/- 0.12
Subaru/CIAO.Lp (mag) = 12.44 +/- 0.22

Object name = PZ Tel B
Distance (pc) = 47.13 +/- 0.13
Paranal/SPHERE.ZIMPOL_R_PRIM (mag) = 17.84 +/- 0.31
Paranal/SPHERE.ZIMPOL_I_PRIM (mag) = 15.16 +/- 0.12
Paranal/SPHERE.IRDIS_D_H23_2 (mag) = 11.78 +/- 0.19
Paranal/SPHERE.IRDIS_D_H23_3 (mag) = 11.65 +/- 0.19
Paranal/SPHERE.IRDIS_D_K12_1 (mag) = 11.56 +/- 0.09
Paranal/SPHERE.IRDIS_D_K12_2 (mag) = 11.29 +/- 0.1
Paranal/NACO.J (mag) = 12.47 +/- 0.2
Paranal/NACO.H (mag) = 11.93 +/- 0.14
Paranal/NACO.Ks (mag) = 11.53 +/- 0.07
Paranal/NACO.Lp (mag) = 11.04 +/- 0.22
Paranal/NACO.NB405 (mag) = 10.94 +/- 0.07
Paranal/NACO.Mp (mag) = 10.93 +/- 0.03
Gemini/NICI.ED286 (mag) = 11.68 +/- 0.14
Gemini/NIRI.H2S1v2-1-G0220 (mag) = 11.39 +/- 0.14

Object name = kappa And b
Distance (pc) = 50.06 +/- 0.87
Subaru/CIAO.J (mag) = 15.86 +/- 0.21
Subaru/CIAO.H (mag) = 14.95 +/- 0.13
Subaru/CIAO.Ks (mag) = 14.32 +/- 0.09
Keck/NIRC2.Lp (mag) = 13.12 +/- 0.1
LBT/LMIRCam.M_77K (mag) = 13.3 +/- 0.3

Object name = HD 1160 B
Distance (pc) = 125.9 +/- 1.2
MKO/NSFCam.J (mag) = 14.69 +/- 0.05
MKO/NSFCam.H (mag) = 14.21 +/- 0.02
MKO/NSFCam.Ks (mag) = 14.12 +/- 0.05
Paranal/NACO.Lp (mag) = 13.6 +/- 0.1
Keck/NIRC2.Ms (mag) = 13.81 +/- 0.24

Object name = ROXs 42 Bb
Distance (pc) = 144.16 +/- 1.53
Keck/NIRC2.J (mag) = 16.91 +/- 0.11
Keck/NIRC2.H (mag) = 15.88 +/- 0.05
Keck/NIRC2.Ks (mag) = 15.01 +/- 0.06
Keck/NIRC2.Lp (mag) = 13.97 +/- 0.06
Keck/NIRC2.Ms (mag) = 14.01 +/- 0.23

Object name = GJ 504 b
Distance (pc) = 17.54 +/- 0.08
Paranal/SPHERE.IRDIS_D_Y23_2 (mag) = 20.98 +/- 0.2
Paranal/SPHERE.IRDIS_D_Y23_3 (mag) = 20.14 +/- 0.09
Paranal/SPHERE.IRDIS_D_J23_3 (mag) = 19.01 +/- 0.17
Paranal/SPHERE.IRDIS_D_H23_2 (mag) = 18.95 +/- 0.3
Paranal/SPHERE.IRDIS_D_H23_3 (mag) = 21.81 +/- 0.35
Paranal/SPHERE.IRDIS_D_K12_1 (mag) = 18.77 +/- 0.2
Subaru/CIAO.J (mag) = 19.78 +/- 0.1
Subaru/CIAO.H (mag) = 20.01 +/- 0.14
Subaru/CIAO.Ks (mag) = 19.38 +/- 0.11
Subaru/CIAO.CH4s (mag) = 19.58 +/- 0.13
Subaru/IRCS.Lp (mag) = 16.7 +/- 0.17

Object name = GU Psc b
Distance (pc) = 47.61 +/- 0.16
Gemini/GMOS-S.z (mag) = 21.75 +/- 0.07
CFHT/Wircam.Y (mag) = 19.4 +/- 0.05
CFHT/Wircam.J (mag) = 18.12 +/- 0.03
CFHT/Wircam.H (mag) = 17.7 +/- 0.03
CFHT/Wircam.Ks (mag) = 17.4 +/- 0.03
WISE/WISE.W1 (mag) = 17.17 +/- 0.33
WISE/WISE.W2 (mag) = 15.41 +/- 0.22

Object name = 2M0103 ABb
Distance (pc) = 47.2 +/- 3.1
Paranal/NACO.J (mag) = 15.47 +/- 0.3
Paranal/NACO.H (mag) = 14.27 +/- 0.2
Paranal/NACO.Ks (mag) = 13.67 +/- 0.2
Paranal/NACO.Lp (mag) = 12.67 +/- 0.1

Object name = 1RXS 1609 B
Distance (pc) = 139.67 +/- 1.33
Gemini/NIRI.J-G0202w (mag) = 17.9 +/- 0.12
Gemini/NIRI.H-G0203w (mag) = 16.87 +/- 0.07
Gemini/NIRI.K-G0204w (mag) = 16.17 +/- 0.18
Gemini/NIRI.Lprime-G0207w (mag) = 14.8 +/- 0.3

Object name = GSC 06214 B
Distance (pc) = 108.84 +/- 0.51
MKO/NSFCam.J (mag) = 16.24 +/- 0.04
MKO/NSFCam.H (mag) = 15.55 +/- 0.04
MKO/NSFCam.Kp (mag) = 14.95 +/- 0.05
MKO/NSFCam.Lp (mag) = 13.75 +/- 0.07
LBT/LMIRCam.M_77K (mag) = 13.75 +/- 0.3

Object name = HD 72946 B
Distance (pc) = 25.87 +/- 0.03
Paranal/SPHERE.IRDIS_D_H23_2 (mag) = 14.56 +/- 0.07
Paranal/SPHERE.IRDIS_D_H23_3 (mag) = 14.4 +/- 0.07

Object name = HIP 64892 B
Distance (pc) = 125.2 +/- 1.42
Paranal/SPHERE.IRDIS_D_H23_2 (mag) = 14.21 +/- 0.17
Paranal/SPHERE.IRDIS_D_H23_3 (mag) = 13.94 +/- 0.17
Paranal/SPHERE.IRDIS_D_K12_1 (mag) = 13.77 +/- 0.17
Paranal/SPHERE.IRDIS_D_K12_2 (mag) = 13.45 +/- 0.19
Paranal/NACO.Lp (mag) = 13.09 +/- 0.17

We create a list with object names and filters for the colors and magnitudes that we want to include in the color-magnitude diagram.

[18]:
objects = [('HR 8799 b', 'Keck/NIRC2.H', 'Paranal/NACO.Lp', 'Paranal/NACO.Lp'),
           ('HR 8799 c', 'Keck/NIRC2.H', 'Paranal/NACO.Lp', 'Paranal/NACO.Lp'),
           ('HR 8799 d', 'Keck/NIRC2.H', 'Paranal/NACO.Lp', 'Paranal/NACO.Lp'),
           ('HR 8799 e', 'Paranal/SPHERE.IRDIS_D_H23_2', 'Paranal/NACO.Lp', 'Paranal/NACO.Lp'),
           ('kappa And b', 'Subaru/CIAO.H', 'Keck/NIRC2.Lp', 'Keck/NIRC2.Lp'),
           ('GSC 06214 B', 'MKO/NSFCam.H', 'MKO/NSFCam.Lp', 'MKO/NSFCam.Lp'),
           ('ROXs 42 Bb', 'Keck/NIRC2.H', 'Keck/NIRC2.Lp', 'Keck/NIRC2.Lp'),
           ('51 Eri b', 'MKO/NSFCam.H', 'Keck/NIRC2.Lp', 'Keck/NIRC2.Lp'),
           ('2M1207 b', 'Paranal/NACO.H', 'Paranal/NACO.Lp', 'Paranal/NACO.Lp'),
           ('2M0103 ABb', 'Paranal/NACO.H', 'Paranal/NACO.Lp', 'Paranal/NACO.Lp'),
           ('1RXS 1609 B', 'Gemini/NIRI.H-G0203w', 'Gemini/NIRI.Lprime-G0207w', 'Gemini/NIRI.Lprime-G0207w'),
           ('beta Pic b', 'Paranal/NACO.H', 'Paranal/NACO.Lp', 'Paranal/NACO.Lp'),
           ('HIP 65426 b', 'Paranal/SPHERE.IRDIS_D_H23_2', 'Paranal/NACO.Lp', 'Paranal/NACO.Lp'),
           ('PZ Tel B', 'Paranal/NACO.H', 'Paranal/NACO.Lp', 'Paranal/NACO.Lp'),
           ('HD 206893 B', 'Paranal/SPHERE.IRDIS_B_H', 'Paranal/NACO.Lp', 'Paranal/NACO.Lp')]

Reading color-magnitude data

The colors and magnitude of the Database of Ultracool Parallaxes are read from the database by creating an object of ReadColorMagnitude.

[19]:
colormag = species.ReadColorMagnitude(library='vlm-plx',
                                      filters_color=('MKO/NSFCam.H', 'MKO/NSFCam.Lp'),
                                      filter_mag='MKO/NSFCam.Lp')

And then extracting the ColorMagBox objects for field and young/low-gravity objects separately.

[20]:
color_field = colormag.get_color_magnitude(object_type='field')
color_young = colormag.get_color_magnitude(object_type='young')

Also these ColorMagBox objects are added to the list of boxes.

[21]:
boxes.append(color_field)
boxes.append(color_young)

Plotting a color-magnitude diagram

The color-magnitude diagram is now plotted with the plot_color_magnitude function. The list with boxes is provided as argument of the boxes parameter. The list with objects is provided separately as argument of objects. See the documentation of plot_color_magnitude for further details on the function parameters.

[22]:
species.plot_color_magnitude(boxes=boxes,
                             objects=objects,
                             mass_labels=[3., 5., 10., 20., 50.],
                             companion_labels=False,
                             field_range=('late M', 'late T'),
                             label_x='H - L$^\prime$',
                             label_y='M$_\mathregular{L\prime}$',
                             xlim=(0.3, 4.),
                             ylim=(15., 7.1),
                             offset=(-0.08, -0.09),
                             legend=(0.04, 0.04),
                             output='color_mag.png')
Plotting color-magnitude diagram: color_mag.png... [DONE]

Let’s have a look at the plot!

[23]:
from IPython.display import Image
Image('color_mag.png')
[23]:
../_images/tutorials_color_magnitude_broadband_58_0.png