%matplotlib inline
import numpy as np
import matplotlib.pyplot as plt
from isochrones.dartmouth import Dartmouth_Isochrone
from isochrones.starmodel import BinaryStarModel, StarModel
from isochrones.starmodel import TripleStarModel
dar = Dartmouth_Isochrone()
Example: A known EB KIC 6778289, or WISE J192824.57+421508.1 (http://keplerebs.villanova.edu/overview/?k=6778289)
mags = dict( W1=(11.808,0.022), W2=(11.834,0.021), W3=(11.675,0.170),
J=(12.119,0.021), H=(11.913,0.017), K=(11.873,0.019))
mod1 = StarModel(dar, maxAV=0.5, **mags)
mod2 = BinaryStarModel(dar, maxAV=0.5, **mags)
mod3 = TripleStarModel(dar, maxAV=0.5, **mags)
#mod1.fit_mcmc()
#mod2.fit_mcmc()
mod3.fit_mcmc(nburn=200, niter=100, nwalkers=300)
<emcee.ensemble.EnsembleSampler at 0x7f29c6b45d50>
#mod1.triangle_plots();
mod2.triangle_plots();
mod3.triangle_plots();
plt.plot(mod3.sampler.lnprobability.T);
plt.plot(mod2.sampler.lnprobability.T);
mod2.samples['lnprob'].min()
-166259.7482004466
inds = np.argsort(mod2.sampler.acceptance_fraction)
mod2.sampler.lnprobability.min(axis=1)[inds]
array([ -8.82407392e+04, -3.80914817e+04, -2.84509079e+04, -5.74920544e+00, 2.48844002e+00, -4.99759081e-01, 1.82551635e+00, -1.05312583e+00, 2.05311265e+00, -3.59541834e+00, -1.29806719e+00, 2.84733166e-01, -3.25435632e+00, 2.09441203e+00, 2.03775610e+00, -2.45976947e+00, -1.07509071e+00, -4.17168571e-01, -1.88337954e+00, -1.56804300e+00, -3.01655869e+00, -8.17378870e-01, -5.82865869e+00, -3.09716595e+00, 4.76800743e-01, -3.35666800e+04, -8.34352352e-01, -5.86074368e+00, -1.19644760e+00, -2.65834012e+00, -6.95430994e+00, -1.32971590e+00, -8.42395423e-01, -2.33910163e+00, -3.64685016e+00, -3.87966309e+00, -3.97066822e+00, -2.32958083e+00, -4.82025071e+00, 2.99573062e-01, 4.43838231e-01, -1.65061422e-01, -9.60913794e-01, -5.52345414e-01, -1.66259748e+05, -4.22179012e+00, -2.04048041e+00, -1.25587009e+00, -8.76026356e-01, -2.73934757e+00, -2.09980949e+00, -2.78484045e+00, -3.34738543e+00, -3.87683721e+00, -9.22048472e-01, 4.39031078e-02, -4.41216532e+00, -2.26274004e+00, -1.80040522e-01, -3.65695186e+00, -3.44542121e+00, -8.43533535e-01, -3.91907013e+00, -1.40878725e+00, -1.60125370e+00, -1.07783095e+00, -1.55365205e+00, -2.31953458e+00, -3.25202385e+00, -1.55290718e+00, 7.31498116e-01, -2.72477875e+00, -2.24001065e+00, -1.01801704e+00, -2.53578659e+00, -3.40010474e+00, -2.55082684e+00, -1.74035993e+00, -5.71295253e-01, -2.76214527e+00, -8.23167448e+00, -9.06078541e-01, -6.61649138e+00, -1.26829375e+00, -1.89726973e-01, -6.00569075e+00, -1.47141309e+00, -5.55054478e+00, -1.28466925e+00, -2.08508320e+00, -3.27561928e+00, -2.91092963e+00, -7.42691078e+00, -1.54383627e+00, -9.73652120e-01, -1.83971427e+00, -4.44296828e+00, -2.89204026e+00, -4.01087642e+00, -3.11016513e+00, -5.06106972e+00, -1.02212996e+00, -8.43029416e-01, -1.23168517e+00, -2.31626807e+00, -1.52485728e+00, -3.82011365e+00, -4.85232966e+00, -4.30397571e-02, -1.28781741e+00, -1.55482028e+00, -6.54938995e+00, -7.26948323e+00, -2.09020307e+00, -1.27359155e+00, -3.75016474e+00, -2.95169070e+00, -3.51424407e+00, -1.59118875e+00, -5.69433421e-01, -7.49260777e+00, -4.46294446e+00, -3.00644359e+00, -2.20411522e+00, -4.92137164e+00, -4.55391443e+00, -1.64353829e+00, -2.33394436e+00, -1.19504961e+00, -1.20949459e+00, -2.17005754e+00, -1.77969516e+00, -1.72348723e+00, -4.26385524e+00, -1.22785512e+00, -2.73899987e+00, -3.98473598e+00, -2.39433839e+00, -5.64669538e-01, -1.29319439e+00, -4.91099950e+00, -3.09904559e+00, -4.79775676e-01, -2.06048989e+00, -4.01571585e+00, -5.25273643e+00, -3.36500639e+00, -4.93302820e+00, -2.30799630e+00, -2.14770392e+00, -4.33473312e+00, -2.70753289e+00, -7.66879632e+00, -6.44388058e-01, -4.31354604e+00, -5.49188338e+00, -2.45742165e+00, -5.13122824e+00, -2.36486965e+00, -3.16773370e+00, -2.57336114e+00, -4.79818794e+00, -7.61981880e-01, -1.56916308e+00, -2.05150240e+00, 2.41139526e-02, -3.51042333e+00, -6.07272845e+00, -5.01743004e+00, -5.13637654e+00, -8.05200413e+00, -1.34231513e+00, -3.06602389e+00, -4.80140283e+00, 7.29236070e-01, -2.14219924e+00, -5.19790010e+00, -3.18969223e+00, -6.11875552e+00, -4.49610294e+00, -6.80635183e+00, -7.13673401e-01, -3.02386414e+00, -4.31334193e+00, -8.59090585e+00, -2.77289838e+00, -2.06949971e+00, -3.26356889e+00, -4.39696551e+00, -2.08893029e+00, -5.13378304e+00, -2.17088511e+00, -5.22689862e+00, -2.72890240e+00, -3.77642953e+00, 2.74210700e-01, -3.06951225e+00, -2.84967812e+00, -1.06557993e+01, -8.05104339e+00])
plt.plot(mod1.sampler.lnprobability.T);
--------------------------------------------------------------------------- AttributeError Traceback (most recent call last) <ipython-input-9-763be10e8a32> in <module>() ----> 1 plt.plot(mod1.sampler.lnprobability.T); /u/tdm/anaconda/lib/python2.7/site-packages/isochrones-0.8.3-py2.7.egg/isochrones/starmodel.pyc in sampler(self) 640 return self._sampler 641 else: --> 642 raise AttributeError('MCMC must be run to access sampler') 643 644 def _make_samples(self): AttributeError: MCMC must be run to access sampler
np.sort(mod1.sampler.acceptance_fraction)
array([ 0. , 0. , 0.01 , 0.015, 0.03 , 0.035, 0.07 , 0.08 , 0.08 , 0.105, 0.12 , 0.125, 0.125, 0.13 , 0.135, 0.14 , 0.145, 0.15 , 0.15 , 0.155, 0.16 , 0.16 , 0.165, 0.165, 0.165, 0.165, 0.165, 0.17 , 0.17 , 0.175, 0.18 , 0.18 , 0.18 , 0.185, 0.185, 0.185, 0.185, 0.185, 0.19 , 0.19 , 0.195, 0.195, 0.195, 0.195, 0.195, 0.2 , 0.2 , 0.2 , 0.205, 0.205, 0.205, 0.21 , 0.21 , 0.21 , 0.21 , 0.215, 0.215, 0.22 , 0.22 , 0.22 , 0.225, 0.225, 0.225, 0.225, 0.225, 0.225, 0.225, 0.225, 0.23 , 0.23 , 0.23 , 0.23 , 0.235, 0.235, 0.235, 0.235, 0.24 , 0.24 , 0.24 , 0.24 , 0.24 , 0.24 , 0.24 , 0.24 , 0.24 , 0.245, 0.245, 0.25 , 0.25 , 0.25 , 0.25 , 0.25 , 0.25 , 0.25 , 0.25 , 0.255, 0.255, 0.255, 0.255, 0.255, 0.255, 0.255, 0.255, 0.26 , 0.26 , 0.26 , 0.26 , 0.26 , 0.26 , 0.26 , 0.265, 0.265, 0.265, 0.265, 0.265, 0.265, 0.265, 0.265, 0.27 , 0.27 , 0.27 , 0.27 , 0.27 , 0.27 , 0.27 , 0.27 , 0.27 , 0.275, 0.275, 0.275, 0.275, 0.275, 0.275, 0.275, 0.28 , 0.28 , 0.28 , 0.28 , 0.28 , 0.28 , 0.285, 0.285, 0.285, 0.285, 0.285, 0.285, 0.285, 0.285, 0.285, 0.285, 0.285, 0.285, 0.285, 0.285, 0.29 , 0.29 , 0.29 , 0.29 , 0.29 , 0.29 , 0.29 , 0.29 , 0.29 , 0.29 , 0.295, 0.295, 0.295, 0.295, 0.295, 0.295, 0.295, 0.295, 0.295, 0.295, 0.295, 0.295, 0.295, 0.295, 0.295, 0.3 , 0.3 , 0.3 , 0.3 , 0.3 , 0.3 , 0.3 , 0.3 , 0.3 , 0.3 , 0.3 , 0.3 , 0.3 , 0.3 , 0.305, 0.305, 0.305, 0.305, 0.305, 0.305, 0.305, 0.305, 0.305, 0.305, 0.31 , 0.31 , 0.31 , 0.31 , 0.31 , 0.31 , 0.31 , 0.31 , 0.31 , 0.31 , 0.31 , 0.31 , 0.315, 0.315, 0.315, 0.315, 0.315, 0.315, 0.315, 0.315, 0.315, 0.315, 0.315, 0.315, 0.315, 0.315, 0.315, 0.32 , 0.32 , 0.32 , 0.32 , 0.32 , 0.32 , 0.32 , 0.32 , 0.32 , 0.32 , 0.32 , 0.32 , 0.32 , 0.32 , 0.32 , 0.325, 0.325, 0.325, 0.325, 0.325, 0.325, 0.325, 0.325, 0.325, 0.325, 0.325, 0.325, 0.325, 0.33 , 0.33 , 0.33 , 0.33 , 0.33 , 0.33 , 0.33 , 0.33 , 0.33 , 0.33 , 0.33 , 0.335, 0.335, 0.335, 0.335, 0.335, 0.335, 0.335, 0.335, 0.335, 0.335, 0.335, 0.335, 0.34 , 0.34 , 0.34 , 0.34 , 0.34 , 0.34 , 0.34 , 0.34 , 0.34 , 0.34 , 0.34 , 0.34 , 0.34 , 0.34 , 0.34 , 0.34 , 0.34 , 0.345, 0.345, 0.345, 0.345, 0.345, 0.345, 0.345, 0.345, 0.345, 0.345, 0.345, 0.345, 0.345, 0.345, 0.345, 0.345, 0.35 , 0.35 , 0.35 , 0.35 , 0.35 , 0.35 , 0.355, 0.355, 0.355, 0.355, 0.355, 0.355, 0.355, 0.355, 0.355, 0.355, 0.355, 0.36 , 0.36 , 0.36 , 0.36 , 0.36 , 0.36 , 0.36 , 0.36 , 0.36 , 0.365, 0.365, 0.365, 0.365, 0.365, 0.365, 0.365, 0.365, 0.365, 0.365, 0.365, 0.365, 0.365, 0.365, 0.365, 0.37 , 0.37 , 0.37 , 0.37 , 0.37 , 0.375, 0.375, 0.375, 0.38 , 0.38 , 0.38 , 0.38 , 0.38 , 0.38 , 0.38 , 0.385, 0.385, 0.385, 0.385, 0.39 , 0.39 , 0.39 , 0.39 , 0.39 , 0.39 , 0.395, 0.395, 0.395, 0.395, 0.395, 0.395, 0.4 , 0.4 , 0.4 , 0.4 , 0.405, 0.41 , 0.41 , 0.41 , 0.415, 0.415, 0.42 , 0.42 , 0.425, 0.435])