nrep = len(Tlist)
filenames = [inprefix + '.' + str(n + rep1 + 1) for n in range(nrep)]
#OK, now we have a list of temperatures and filenames for each replicas
print "replica list:"
for n in range(nrep):
print Tlist[n], filenames[n]
print "USING nfree = ", nfree
#load data
datalist = load_data.loadData(filenames, [ecolumn], fskip=rskip)
#determine bin edges
binenergy1 = load_data.determineBinEdge(nebins,
datalist,
column=0,
exponential_bins=True)
#histogram the data
visits1d = load_data.binData1d(binenergy1, datalist)
#visits1d = np.transpose(visits1d)
wham = WHAM.Wham1d(Tlist, binenergy1[:-1], visits1d)
wham.minimize()
#wham.globalMinimization()
print "dumping WHAM1d to pickle file: ", pklname
pickle.dump(wham, open(pklname, "wb"))
else:
#OK, now we have a list of temperatures and filenames for each replicas
print "replica list:"
for n in range(nrep):
print Tlist[n], filenames[n]
#data = load_data.loadData2dExp(filenames, ecolumn, qcolumn, nqbins, fskip=rskip, qcombine=qcombine, nebins=nebins, dEmin=dEmin)
#load data
columns = [ecolumn]
if len(qcombine) != 3: columns.append(qcolumn)
datalist = load_data.loadData(filenames, columns, fskip=rskip, qcombine=qcombine )
#determine bin edges
binenergy1 = load_data.determineBinEdge(nebins, datalist, column=0, exponential_bins=use_exponential_bins)
binq1 = load_data.determineBinEdge(nqbins, datalist, column=1, exponential_bins=False)
#create histogram
visits2d = load_data.binData2d(binenergy1, binq1, datalist)
#visits2dnew = np.zeros( [nebins, nqbins, nrep] )
#for k in range(nrep): visits2dnew[:,:,k] = visits2d[k,:,:]
#visits2d = visits2dnew
wham = WHAM.wham2d(Tlist, binenergy1[:-1], binq1[:-1], visits2d)
wham.minimize()
print "dumping WHAM2d to pickle file: ", pklname
pickle.dump(wham,open(pklname,"wb"))
filenames=[inprefix+'.'+str(n+rep1+1) for n in range(nrep)]
#OK, now we have a list of temperatures and filenames for each replicas
print "replica list:"
for n in range(nrep):
print Tlist[n], filenames[n]
print "USING nfree = ", nfree
#load data
datalist = load_data.loadData(filenames, [ecolumn], fskip=rskip )
#determine bin edges
binenergy1 = load_data.determineBinEdge(nebins, datalist, column=0, exponential_bins=True)
#histogram the data
visits1d = load_data.binData1d(binenergy1, datalist)
#visits1d = np.transpose(visits1d)
wham = WHAM.wham1d(Tlist, binenergy1[:-1], visits1d)
wham.minimize()
#wham.globalMinimization()
print "dumping WHAM1d to pickle file: ", pklname
pickle.dump(wham,open(pklname,"wb"))
else:
print "=================================================================="
filenames = [inprefix + "." + str(n + rep1 + 1) for n in range(nrep)]
# OK, now we have a list of temperatures and filenames for each replicas
print "replica list:"
for n in range(nrep):
print Tlist[n], filenames[n]
# data = load_data.loadData2dExp(filenames, ecolumn, qcolumn, nqbins, fskip=rskip, qcombine=qcombine, nebins=nebins, dEmin=dEmin)
# load data
columns = [ecolumn]
if len(qcombine) != 3:
columns.append(qcolumn)
datalist = load_data.loadData(filenames, columns, fskip=rskip, qcombine=qcombine)
# determine bin edges
binenergy1 = load_data.determineBinEdge(nebins, datalist, column=0, exponential_bins=use_exponential_bins)
binq1 = load_data.determineBinEdge(nqbins, datalist, column=1, exponential_bins=False)
# create histogram
visits2d = load_data.binData2d(binenergy1, binq1, datalist)
# visits2dnew = np.zeros( [nebins, nqbins, nrep] )
# for k in range(nrep): visits2dnew[:,:,k] = visits2d[k,:,:]
# visits2d = visits2dnew
wham = WHAM.wham2d(Tlist, binenergy1[:-1], binq1[:-1], visits2d)
wham.minimize()
print "dumping WHAM2d to pickle file: ", pklname
pickle.dump(wham, open(pklname, "wb"))
