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diff --git a/pyext/professor2/dataio.py b/pyext/professor2/dataio.py
--- a/pyext/professor2/dataio.py
+++ b/pyext/professor2/dataio.py
@@ -1,171 +1,171 @@
# -*- python -*-
from professor2.histos import *
from professor2.paramsio import *
def read_histos_root(path):
"Load histograms from a ROOT file, into a dict of path -> yoda.Histo[DataBin]"
histos = {}
# TODO: Could just use YODA for everything, including ROOT reading?
try:
import ROOT
ROOT.gROOT.SetBatch(True)
except ImportError:
print "PyROOT not available... skipping"
return histos
# TODO: use yoda.root.getall
def _getallrootobjs(d, basepath="/"):
"Recurse through a ROOT file/dir and generate (path, obj) pairs"
for key in d.GetListOfKeys():
kname = key.GetName()
if key.IsFolder():
# TODO: -> "yield from" in Py3
for i in _getallrootobjs(d.Get(kname), basepath+kname+"/"):
yield i
else:
yield basepath+kname, d.Get(kname)
try:
f = ROOT.TFile(path)
for rname, robj in _getallrootobjs(f):
bins = []
if robj.InheritsFrom("TH1"):
# TODO: allow 2D histos
if robj.InheritsFrom("TH2"):
continue
for ib in xrange(robj.GetBins()):
xmin = robj.GetXaxis().GetBinLowEdge(ib+1)
xmax = robj.GetXaxis().GetBinUpEdge(ib+1)
y = robj.GetBinContent(ib+1)
ey = robj.GetBinError(ib+1)
bins.append(DataBin(xmin, xmax, y, ey))
histos[rname] = Histo(bins, rname)
elif robj.InheritsFrom("TGraph"):
for ip in xrange(robj.GetN()):
x, y = ROOT.Double(), ROOT.Double()
robj.GetPoint(ip, x, y)
xmin = x - robj.GetErrorXlow(ip)
xmax = x + robj.GetErrorXhigh(ip)
ey = (robj.GetErrorXlow(ip) + robj.GetErrorXhigh(ip)) / 2.0
bins.append(DataBin(xmin, xmax, y, ey))
histos[rname] = Histo(bins, rname)
f.Close()
except Exception, e:
print "Can't load histos from ROOT file '%s': %s" % (path, e)
return histos
def read_histos_yoda(path):
"Load histograms from a YODA-supported file type, into a dict of path -> yoda.Histo[DataBin]"
histos = {}
try:
import yoda
s2s = []
aos = yoda.read(path, asdict=False)
for ao in aos:
import os
## Skip the Rivet cross-section and event counter objects
# TODO: Avoid Rivet-specific behaviour by try block handling & scatter.dim requirements
if os.path.basename(ao.path).startswith("_"):
continue
##
s2s.append(ao.mkScatter())
del aos #< pro-active YODA memory clean-up
#
#s2s = [ao.mkScatter() for ao in yoda.read(path, asdict=False)]
for s2 in s2s:
bins = [DataBin(p.xMin, p.xMax, p.y, p.yErrAvg) for p in s2.points]
#bins = [DataBin(p.xMin, p.xMax, p.y*(p.xMax-p.xMin), p.yErrAvg) for p in s2.points]
# bins = [DataBin(p.xMin, p.xMax, p.y, p.yErrs) for p in s2.points]
histos[s2.path] = Histo(bins, s2.path)
del s2s #< pro-active YODA memory clean-up
except Exception, e:
print "Can't load histos from file '%s': %s" % (path, e)
return histos
def read_histos(path):
"Load histograms from file, into a dict of path -> yoda.Histo[DataBin]"
histos = {}
if path.endswith(".root"):
histos.update(read_histos_root(path))
elif any(path.endswith(ext) for ext in [".yoda", ".aida", ".flat"]):
histos.update(read_histos_yoda(path))
return histos
def read_rundata(dirs, pfname="params.dat", verbosity=1): #, formats="yoda,root,aida,flat"):
"""
Read interpolation anchor point data from a provided set of run directory paths.
Returns a pair of dicts, the first mapping run names (i.e. rundir basenames) to
the parameter value list for each run, and the second mapping observable names
(i.e. histogram paths) to a run -> histo dict.
"""
params, histos = {}, {}
import os, glob, re
re_pfname = re.compile(pfname) if pfname else None
numruns = len(dirs)
for num, d in enumerate(sorted(dirs)):
run = os.path.basename(d)
- if verbosity >= 2 or (verbosity >= 1 and (num % 50 == 0 or num == numruns)):
+ if verbosity >= 2 or (verbosity >= 1 and (num % 100 == 0 or num == numruns)):
pct = 100*num/float(numruns)
print "Reading run '%s' data: %d/%d = %2.0f%%" % (run, num, numruns, pct)
files = glob.glob(os.path.join(d, "*"))
for f in files:
## Params file
#if os.path.basename(f) == pfname:
if re_pfname and re_pfname.search(os.path.basename(f)):
params[run] = read_paramsfile(f)
## Histo file
else:
try:
## Read as a path -> Histo dict
hs = read_histos(f)
## Restructure into the path -> run -> Histo return dict
for path, hist in hs.iteritems():
histos.setdefault(path, {})[run] = hist
except:
pass #< skip files that can't be read as histos
## Check that a params file was found and read in this dir... or that no attempt was made to find one
if pfname:
if run not in params.keys():
raise Exception("No params file '%s' found in run dir '%s'" % (pfname, d))
else:
params = None
return params, histos
# TODO: remove this alias
load_rundata = read_rundata
def find_maxerrs(histos):
"""
Helper function to find the maximum error values found for each bin in the histos double-dict.
histos is a nested dict of DataHisto objects, indexed first by histo path and then by
run name, i.e. it is the second of the two objects returned by read_histos().
Returns a dict of lists of floats, indexed by histo path. Each list of floats contains the
max error size seen for each bin of the named observable, across the collection of runs
histos.keys().
This functions is useful for regularising chi2 etc. computation by constraining interpolated
uncertainties to within the range seen in the run data used to create the ipols, to avoid
blow-up of uncertainties with corresponding distortion of fit optimisation.
TODO: asymm version?
"""
rtn = {}
for hn, hs in histos.iteritems():
numbins_h = hs.next().nbins
maxerrs_h = []
for ib in xrange(numbins_h):
emax = max(h.bins[ib].err for h in hs.values())
maxerrs_h.append(emax)
rtn[hn] = maxerrs_h
return rtn

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