toc = pd.read_table(tocfilename)
# Estimate the model for one case to generate timing table with different regions of interest.
#for f in folderlist:
# path = 'ELBO/%s' %str(folderlist.index(f))
for dilution in np.unique(toc[toc.isRef == 'N'].Dilution):
logging.debug("Processing dilution: %0.1f" % dilution)
h5FileName = "Case%s.hdf5" % str(dilution).replace(".", "_", 1)
try:
with h5py.File(h5FileName, 'r') as f:
pass
except IOError as e:
dsample = 10000
region = "top_400_positions"
#caseFileList = ['./depth_chart/%s/%s/20100916_c3_p1.07_CGT.dc' % (dsample, region)] # For single file
caseFileList = [
"./depth_chart/10000/top_400_positions/%s" % filename
for filename in toc.Filename[toc.Dilution == dilution]
]
logging.info('Estimate %s' % caseFileList)
(r, n, loc, refb) = rvd3.load_depth(caseFileList)
casephi, caseq = rvd3.ELBO_opt(r,
n,
seed=19860522,
pool=60,
dsample=dsample,
region=region)
logging.debug("Saving model in %s" % h5FileName)
rvd3.save_model(h5FileName, r, n, casephi, caseq, loc, refb)
import multiprocessing as mp
import logging
import pdb
# <codecell>
logging.basicConfig(level=logging.DEBUG,
format='%(levelname)s:%(module)s:%(message)s')
rvddir = os.path.join('./')
sys.path.insert(0, rvddir)
import rvd3
##pool =None
pool = mp.Pool(processes=64)
# Estimate the model for the control
logging.debug("Processing control data.")
h5FileName = "c4-34_MTH1_M0times1000.hdf5"
try:
with h5py.File(h5FileName, 'r') as f:
pass
except IOError as e:
filename = "c4-34_MTH1.dc"
controlFileList = [
"../2016-01-12_Run_rvd3_Dan_data_regions/dc/E1/%s" % filename
]
(r, n, loc, refb) = rvd3.load_depth(controlFileList)
controlphi, controlq = rvd3.ELBO_opt(r, n, seed=20160210, pool=62)
logging.debug("Saving model in %s" % h5FileName)
rvd3.save_model(h5FileName, r, n, controlphi, controlq, loc, refb)