print '[%d]' % i, entry
idx = raw_input('which one should I use? ')
idx = int(idx)
_, to_use = matches[idx]
print to_use.start.str, '-->', time.str
points.append((to_use.start.time, time.time))
#linear fit
from rootpy import ROOT
ROOT.gROOT.SetBatch()
from rootpy.plotting import Graph, F1, Canvas
fcn = F1(args.fitfunc)
graph = Graph(len(points))
for idx, point in enumerate(points):
x, y = point
graph.SetPoint(idx, x, y)
graph.fit(fcn)
canvas = Canvas()
graph.Draw()
canvas.SaveAs("shifts.png")
with open(args.out, 'w') as out:
for i, entry in enumerate(entries):
entry.remap(fcn)
out.write('%d\n' % i)
out.write('%s\n\n' % entry.string)
_, entry = j
print '[%d]' % i, entry
idx = raw_input('which one should I use? ')
idx = int(idx)
_, to_use = matches[idx]
print to_use.start.str, '-->', time.str
points.append((to_use.start.time, time.time))
#linear fit
from rootpy import ROOT
ROOT.gROOT.SetBatch()
from rootpy.plotting import Graph, F1, Canvas
fcn = F1(args.fitfunc)
graph = Graph(len(points))
for idx, point in enumerate(points):
x, y = point
graph.SetPoint(idx, x, y)
graph.fit(fcn)
canvas = Canvas()
graph.Draw()
canvas.SaveAs("shifts.png")
with open(args.out, 'w') as out:
for i, entry in enumerate(entries):
entry.remap(fcn)
out.write('%d\n' % i)
out.write('%s\n\n' % entry.string)
