In [19]:
from time import time
from multiprocessing import cpu_count, Pool
import warnings
from itertools import izip
from os import path
from ast import literal_eval

import numpy as np
import emcee as mc
from scipy.linalg import inv
import h5py

from pearce.emulator import OriginalRecipe, ExtraCrispy, SpicyBuffalo, NashvilleHot

In [20]:
lnprob = lambda x: 0

In [21]:
num_params = 4
nwalkers = 50
pos0 = np.random.randn(nwalkers, num_params)
pool=Pool(processes=4)
sampler = mc.EnsembleSampler(nwalkers, num_params, lnprob, pool=pool)

In [22]:
from pearce.inference import run_mcmc_config
rmi = run_mcmc_iterator([None], ['','','',''],[None], [np.eye(10)], np.arange(10),\ nwalkers=nwalkers, nsteps=100, nburn = 0)

In [31]:
fname = '/scratch/users/swmclau2/PearceMCMC/pearce_mcmc_nh_gg.hdf5'

In [40]:
run_mcmc_config(fname)


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In [44]:
import h5py

In [53]:
f = h5py.File(fname, 'r')

In [54]:
f.attrs['nwalkers']


Out[54]:
50

In [36]:
f.attrs['nsteps'] = 5

In [37]:
f.attrs.keys()


Out[37]:
[u'emu_type',
 u'training_file',
 u'fixed_params',
 u'emu_hps',
 u'sim',
 u'obs',
 u'cov',
 u'nburn',
 u'seed',
 u'chain_fixed_params',
 u'nwalkers',
 u'nsteps',
 u'param_names']

In [43]:
f['chain'].value


Out[43]:
array([[  0.02361925,   0.10700469,  -1.17617762, ...,   0.18557537,
         14.5115366 ,   1.055632  ],
       [  0.02239174,   0.10926513,  -0.85765904, ...,   0.21402553,
         14.20062828,   0.88841033],
       [  0.02254332,   0.10574937,  -1.0205977 , ...,   0.28405845,
         14.29493618,   1.14422739],
       ..., 
       [  0.02242335,   0.11394774,  -0.91191655, ...,   0.24203114,
         14.32448864,   1.01942146],
       [  0.02241263,   0.11718851,  -0.92839056, ...,   0.25440517,
         14.46947861,   1.07101607],
       [  0.02203491,   0.11678351,  -0.85468692, ...,   0.32152689,
         14.34209156,   1.00782597]], dtype=float32)

In [55]:
f.close()

In [ ]:
f.attrs