yt.load_particles cannot handle multiple types of dictionary fields.

yt-fido commented 9 years ago

Originally reported by: Benjamin Thompson (Bitbucket: cosmosquark, GitHub: cosmosquark)

yt.load_particles works fine so long as you keep the dictionary fields consistant.

For example

#!python

import numpy as np
import yt
from yt.units.yt_array import YTArray
from yt.units import kiloparsec, Msun, kilometer, second, Gyr

n_data = 3000

sim_data_verb = {"particle_mass": YTArray(np.random.rand(n_data) * 1000,"Msun"),
            "particle_position_x": np.random.rand(n_data),
            "particle_position_y": np.random.rand(n_data),
            "particle_position_z": np.random.rand(n_data),
            "particle_velocity_x": YTArray(np.random.rand(n_data), "kpc/s"),
            "particle_velocity_y": YTArray(np.random.rand(n_data), "kpc/s"),
            "particle_velocity_z": YTArray(np.random.rand(n_data), "kpc/s"),
            "particle_mass_birth_epoch": YTArray(np.random.rand(n_data), "Msun"),
            "particle_birth_epoch": YTArray(np.random.rand(n_data), "Gyr"),
            "particle_metallicity": YTArray(np.random.rand(n_data),"dimensionless")
        }

bbox = yt.YTArray(np.array([[0,1],[0,1],[0,1]]),"kpc")

ds = yt.load_particles(sim_data_verb, length_unit=kiloparsec, mass_unit=Msun, time_unit=second, bbox=bbox, n_ref=256)

ad = ds.all_data()

for key in sim_data_verb:
    print key, ad[key]

will work but will return

#!python

particle_position_z [ 0.2815859   0.38847204  0.22986295 ...,  0.29531876  0.66077444
  0.88342952] code_length
particle_position_x [ 0.35727259  0.52799574  0.7032232  ...,  0.78598736  0.43919501
  0.77617413] code_length
particle_position_y [ 0.21314061  0.71663901  0.19971711 ...,  0.41379908  0.20679615
  0.26690946] code_length
particle_metallicity [ 0.19719678  0.8893857   0.71944182 ...,  0.94147203  0.40978591
  0.37535933] dimensionless
particle_mass_birth_epoch [ 0.14538698  0.91165767  0.24366002 ...,  0.93701722  0.31856248
  0.2815376 ] dimensionless
particle_velocity_z [  1.32970858e+21   2.02143717e+21   8.91082065e+20 ...,   1.45218388e+20
   9.72945874e+20   3.02182398e+21] cm/s
particle_birth_epoch [ 0.74899177  0.80996651  0.39013562 ...,  0.55047881  0.21678475
  0.07351061] dimensionless
particle_mass [  4.94763075e+35   7.77704243e+35   1.12806228e+36 ...,   8.01759848e+35
   1.49906294e+36   2.58791744e+35] g
particle_velocity_x [  2.83463595e+21   2.21176517e+21   1.45116224e+21 ...,   1.15946794e+21
   2.20856829e+21   1.40417681e+21] cm/s
particle_velocity_y [  3.27195893e+20   1.88669889e+21   3.58577639e+20 ...,   1.01434342e+21
   2.92246102e+20   2.07493516e+21] cm/s

and e.g particle_mass_birth_epoch will be dimensionless

whereas if you were to be consistent with the arrays

#!python

import numpy as np
import yt
from yt.units.yt_array import YTArray
from yt.units import kiloparsec, Msun, kilometer, second, Gyr

n_data = 3000

sim_data_verb = {"particle_mass": YTArray(np.random.rand(n_data) * 1000,"Msun"),
            "particle_position_x": YTArray(np.random.rand(n_data),"kpc"),
            "particle_position_y": YTArray(np.random.rand(n_data),"kpc"),
            "particle_position_z": YTArray(np.random.rand(n_data),"kpc"),
            "particle_velocity_x": YTArray(np.random.rand(n_data), "kpc/s"),
            "particle_velocity_y": YTArray(np.random.rand(n_data), "kpc/s"),
            "particle_velocity_z": YTArray(np.random.rand(n_data), "kpc/s"),
            "particle_mass_birth_epoch": YTArray(np.random.rand(n_data), "Msun"),
            "particle_birth_epoch": YTArray(np.random.rand(n_data), "Gyr"),
            "particle_metallicity": YTArray(np.random.rand(n_data),"dimensionless")
        }

bbox = yt.YTArray(np.array([[0,1],[0,1],[0,1]]),"kpc")

ds = yt.load_particles(sim_data_verb, length_unit=kiloparsec, mass_unit=Msun, time_unit=second, bbox=bbox, n_ref=256)

ad = ds.all_data()

for key in sim_data_verb:
    print key, ad[key]

you get sensible results

#!python

particle_position_z [  1.91010138e+21   2.72597553e+21   1.88470277e+20 ...,   1.20441080e+21
   2.14680199e+21   5.77431567e+20] cm
particle_position_x [  2.08016250e+21   3.50853505e+20   1.58804046e+21 ...,   1.57472014e+21
   3.55352460e+20   2.40592132e+21] cm
particle_position_y [  1.53145514e+21   1.87942152e+21   3.01891288e+21 ...,   1.61942691e+21
   1.02154497e+21   2.49263525e+21] cm
particle_metallicity [ 0.20026758  0.74414137  0.11611151 ...,  0.71398545  0.9404482
  0.12193648] dimensionless
particle_mass_birth_epoch [ 0.55149932  0.80309968  0.07713267 ...,  0.16103389  0.85597544
  0.55997554] Msun
particle_velocity_z [  1.55542587e+21   2.57960677e+21   2.90400726e+21 ...,   1.90426357e+21
   2.94137672e+21   8.78600990e+20] cm/s
particle_birth_epoch [ 0.12942072  0.00235603  0.63535871 ...,  0.8858202   0.58461139
  0.34462516] Gyr
particle_mass [  1.05296456e+36   1.92696089e+36   3.48006468e+35 ...,   9.26929432e+35
   1.86347040e+36   1.21576381e+36] g
particle_velocity_x [  1.01967742e+21   2.38948376e+21   1.83127998e+21 ...,   1.18012037e+20
   1.90840829e+21   2.71858174e+21] cm/s
particle_velocity_y [  2.01127183e+20   8.90953057e+20   2.38801554e+21 ...,   1.68662686e+20
   3.00596354e+21   4.53271032e+20] cm/s

i.e particle_mass_birth_epoch now has dimensions

Bitbucket: https://bitbucket.org/yt_analysis/yt/issue/1026