/
test_o94.py
162 lines (123 loc) · 5.43 KB
/
test_o94.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
import numpy as np
import pytest
import astropy.units as u
from astropy.modeling import InputParameterError
from ..parameter_averages import O94
from .helpers import _invalid_x_range
@pytest.mark.parametrize("Rv_invalid", [-1.0, 0.0, 1.9, 6.1, 10.])
def test_invalid_Rv_input(Rv_invalid):
with pytest.raises(InputParameterError) as exc:
tmodel = O94(Rv=Rv_invalid)
assert exc.value.args[0] == 'parameter Rv must be between 2.0 and 6.0'
@pytest.mark.parametrize("x_invalid", [-1.0, 0.2, 10.1, 100.])
def test_invalid_wavenumbers(x_invalid):
_invalid_x_range(x_invalid, O94(Rv=3.1), 'O94')
@pytest.mark.parametrize("x_invalid_wavenumber",
[-1.0, 0.2, 10.1, 100.]/u.micron)
def test_invalid_wavenumbers_imicron(x_invalid_wavenumber):
_invalid_x_range(x_invalid_wavenumber, O94(Rv=3.1), 'O94')
@pytest.mark.parametrize("x_invalid_micron",
u.micron/[-1.0, 0.2, 10.1, 100.])
def test_invalid_micron(x_invalid_micron):
_invalid_x_range(x_invalid_micron, O94(Rv=3.1), 'O94')
@pytest.mark.parametrize("x_invalid_angstrom",
u.angstrom*1e4/[-1.0, 0.2, 10.1, 100.])
def test_invalid_angstrom(x_invalid_angstrom):
_invalid_x_range(x_invalid_angstrom, O94(Rv=3.1), 'O94')
def test_axav_o94_rv31():
# values from Bastiaasen (1992) Table 6
x = np.array([2.939, 2.863, 2.778, 2.642, 2.476, 2.385,
2.275, 2.224, 2.124, 2.000, 1.921, 1.849,
1.785, 1.718, 1.637, 1.563, 1.497, 1.408,
1.332, 1.270])
cor_vals = np.array([1.725, 1.651, 1.559, 1.431, 1.292, 1.206,
1.100, 1.027, 0.907, 0.738, 0.606, 0.491,
0.383, 0.301, 0.190, 0.098, -0.004, -0.128,
-0.236, -0.327])
# initialize extinction model
tmodel = O94(Rv=3.1)
# get the model results and change to E(l-1.5)/E(2.2-1.5)
mod_vals = tmodel(x)
norm_vals = tmodel([1.5, 2.2])
mod_vals = (mod_vals - norm_vals[0])/(norm_vals[1] - norm_vals[0])
# test (table in paper has limited precision)
np.testing.assert_allclose(mod_vals, cor_vals, atol=6e-2)
def get_axav_cor_vals(Rv):
# testing only NIR or UV wavenumbers (optical tested in previous test)
# O94 is the same as CCM89 for these wavelengths
x = np.array([10., 9., 8., 7.,
6., 5., 4.6, 4.,
0.8, 0.63,
0.46])
# add units
x = x/u.micron
# correct values
if Rv == 3.1:
cor_vals = np.array([5.23835484, 4.13406452, 3.33685933, 2.77962453,
2.52195399, 2.84252644, 3.18598916, 2.31531711,
0.28206957, 0.19200814,
0.11572348])
elif Rv == 2.0:
cor_vals = np.array([9.407, 7.3065, 5.76223881, 4.60825807,
4.01559036, 4.43845534, 4.93952892, 3.39275574,
0.21678862, 0.14757062,
0.08894094])
elif Rv == 3.0:
cor_vals = np.array([5.491, 4.32633333, 3.48385202, 2.8904508,
2.6124774, 2.9392494, 3.2922643, 2.38061642,
0.27811315, 0.18931496,
0.11410029])
elif Rv == 4.0:
cor_vals = np.array([3.533, 2.83625, 2.34465863, 2.03154717,
1.91092092, 2.18964643, 2.46863199, 1.87454675,
0.30877542, 0.21018713,
0.12667997])
elif Rv == 5.0:
cor_vals = np.array([2.3582, 1.9422, 1.66114259, 1.51620499,
1.48998704, 1.73988465, 1.97445261, 1.57090496,
0.32717278, 0.22271044,
0.13422778])
elif Rv == 6.0:
cor_vals = np.array([1.575, 1.34616667, 1.20546523, 1.17264354,
1.20936444, 1.44004346, 1.64499968, 1.36847709,
0.33943769, 0.23105931,
0.13925965])
else:
cor_vals = np.array([0.0])
return (x, cor_vals)
@pytest.mark.parametrize("Rv", [2.0, 3.0, 3.1, 4.0, 5.0, 6.0])
def test_extinction_O94_values(Rv):
# get the correct values
x, cor_vals = get_axav_cor_vals(Rv)
# initialize extinction model
tmodel = O94(Rv=Rv)
# test
np.testing.assert_allclose(tmodel(x), cor_vals)
def test_extinguish_no_av_or_ebv():
tmodel = O94()
with pytest.raises(InputParameterError) as exc:
tmodel.extinguish([1.0])
assert exc.value.args[0] == 'neither Av or Ebv passed, one required'
@pytest.mark.parametrize("Rv", [2.0, 3.0, 3.1, 4.0, 5.0, 6.0])
def test_extinction_O94_extinguish_values_Av(Rv):
# get the correct values
x, cor_vals = get_axav_cor_vals(Rv)
# calculate the cor_vals in fractional units
Av = 1.0
cor_vals = np.power(10.0, -0.4*(cor_vals*Av))
# initialize extinction model
tmodel = O94(Rv=Rv)
# test
np.testing.assert_allclose(tmodel.extinguish(x, Av=Av), cor_vals)
@pytest.mark.parametrize("Rv", [2.0, 3.0, 3.1, 4.0, 5.0, 6.0])
def test_extinction_O94_extinguish_values_Ebv(Rv):
# get the correct values
x, cor_vals = get_axav_cor_vals(Rv)
# calculate the cor_vals in fractional units
Ebv = 1.0
Av = Ebv*Rv
cor_vals = np.power(10.0, -0.4*(cor_vals*Av))
# initialize extinction model
tmodel = O94(Rv=Rv)
# test
np.testing.assert_allclose(tmodel.extinguish(x, Ebv=Ebv), cor_vals)