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expected results for example 16
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rpoleski committed Jun 6, 2024
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21 changes: 21 additions & 0 deletions data/expected_example_output/example_16/ob03235_1/output.txt
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Mean acceptance fraction: 0.110
Mean autocorrelation time [steps]: nan
Fitted parameters:
t_0 : 2452848.07842 +0.09056 -0.11779
u_0 : 0.13006 +0.00292 -0.00434
t_E : 62.02397 +1.79534 -0.79956
rho : 0.00090 +0.00015 -0.00067
s : 1.12204 +0.28565 -0.00849
q : 0.0042899 +0.0015261 -0.0007855
alpha : 223.83464 +2.47217 -0.80972
Fitted fluxes (source and blending):
flux_s_1 : 8.89612 +0.21550 -0.17854
flux_b_1 : 3.01760 +0.28343 -0.20127
flux_s_2 : 607.65455 +16.23915 -23.18048
flux_b_2 : -600.97205 +25.34592 -16.12195
Best model:
chi2: 1644.3221
t_0 u_0 t_E rho s q alpha
2452848.1246413593 0.13077424756331346 62.1115925977469 0.0009026783479118898 1.118492277496811 0.003861855664894637 223.299712544845
Fluxes:
8.916830439840542 3.016002940234999 611.937887681789 -605.1043288009473
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/usr/local/lib/python3.8/site-packages/emcee/autocorr.py:38: RuntimeWarning: invalid value encountered in true_divide
acf /= acf[0]
The chain is shorter than 50 times the integrated autocorrelation time for 6 parameter(s). Use this estimate with caution and run a longer chain!
N/50 = 2;
tau: [11.36266927 11.79981449 10.97669426 12.13697319 11.39767236 12.87928857
nan]
/home/data/caustic/rpoleski/MulensModel/source/MulensModel/utils.py:147: UserWarning: Flux to magnitude conversion approached negative flux
warnings.warn(
/home/data/caustic/rpoleski/MulensModel/source/MulensModel/utils.py:150: RuntimeWarning: invalid value encountered in log10
mag = zeropoint - 2.5 * np.log10(flux)
/home/data/caustic/rpoleski/MulensModel/source/MulensModel/utils.py:147: UserWarning: Flux to magnitude conversion approached negative flux
warnings.warn(
/home/data/caustic/rpoleski/MulensModel/source/MulensModel/utils.py:150: RuntimeWarning: invalid value encountered in log10
mag = zeropoint - 2.5 * np.log10(flux)
/home/data/caustic/rpoleski/MulensModel/source/MulensModel/mulensdata.py:556: UserWarning: Some good data points have scaled errorbars with negative values. Setting them to zero for plotting.
Dataset: OB03235_MOA.txt
Epochs: [2451724.984743 2451735.999816 2451816.931292 2451817.868943
2452068.114436 2452176.880222 2452185.913052 2452420.970783
2452438.97773 2452458.914235 2452533.873316 2452547.926567
2452551.909314 2452551.924018 2452754.082603 2452759.235935]
warnings.warn(msg.format(kind, self._get_name(), self.time[indexes]))
/home/data/caustic/rpoleski/MulensModel/source/MulensModel/utils.py:147: UserWarning: Flux to magnitude conversion approached negative flux
warnings.warn(
/home/data/caustic/rpoleski/MulensModel/source/MulensModel/utils.py:150: RuntimeWarning: invalid value encountered in log10
mag = zeropoint - 2.5 * np.log10(flux)
/home/data/caustic/rpoleski/MulensModel/source/MulensModel/mulensdata.py:556: UserWarning: Some good data points have scaled errorbars with negative values. Setting them to zero for plotting.
Dataset: OB03235_MOA.txt
Epochs: [2451724.984743 2451735.999816 2451816.931292 2451817.868943
2452068.114436 2452176.880222 2452185.913052 2452420.970783
2452438.97773 2452458.914235 2452533.873316 2452547.926567
2452551.909314 2452551.924018 2452754.082603 2452759.235935]
warnings.warn(msg.format(kind, self._get_name(), self.time[indexes]))

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MulensModel and script versions: ['2.24.0', '0.36.2']
Mean acceptance fraction: 0.450
Mean autocorrelation time [steps]: nan
Fixed parameters:
t_0_par : 2452848.0
Fitted parameters:
# [median, sigma+, sigma-]
t_0 : [2452847.99392, +0.20297, -0.10625]
u_0 : [0.13133, +0.01190, -0.00989]
t_E : [61.53299, +0.84212, -0.61895]
rho : [0.00106, +0.00013, -0.00030]
pi_E_N : [0.00273, +0.00775, -0.01699]
pi_E_E : [-0.00115, +0.01221, -0.02237]
s : [1.10024, +0.00699, -0.00610]
q : [0.0029446, +0.0044348, -0.0015029]
alpha : [224.65427, +0.81415, -1.28011]
Fitted fluxes: # (source and blending)
# [median, sigma+, sigma-]
flux_s_1 : [8.98438, +0.23701, -0.58582]
flux_b_1 : [2.96644, +0.70747, -0.29924]
flux_s_2 : [591.38326, +34.62791, -33.72225]
flux_b_2 : [-582.47485, +34.28827, -35.26746]
Best model:
chi2: 1607.1935
Parameters:
t_0: 2452847.9813169586
u_0: 0.1244083012837355
t_E: 61.801994310224785
rho: 0.0009857729823665759
pi_E_N: -0.00290808473075553
pi_E_E: 3.233308746249976e-05
s: 1.1012189522525833
q: 0.00219719097185293
alpha: 223.18272670658607
Fluxes:
flux_s_1: 8.570631573704093
flux_b_1: 3.4774355109846873
flux_s_2: 577.1216293142585
flux_b_2: -569.0241772101244
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