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#!/usr/bin/python
#
# File: plotSpeedups.py
#
from ROOT import TCanvas, gROOT, TGraphErrors, TPaveText, TLatex, TFile, gStyle
from PerfHistoryTools import readPerformanceData
### these are the full series
commits = ["68c48276","4e5928c1","019d29a0","b356bad1","2c007289",
"298df455","a860eea3","e569cfb7","9e47e5fd","0877406d"]
# "143d582e","b92b66ba","3af4b3f2","b9437a06","e4c54450","c2f9b8cc","ec7c80a5","1047750f","30635340"]
#commits = ["143d582e","b92b66ba","3af4b3f2","b9437a06","e4c54450","c2f9b8cc","ec7c80a5","1047750f","30635340"]
#commits = ["c4154901", "1f673e0d", "458e6f08"]
shapes = ["Trapezoid"]
algoNames = ["inside", "distToIn", "safeToIn", "contains", "distToOut", "safeToOut"]
implNames = ["vect", "unspec", "spec", "root", "usolids", "geant4"]
#implNames = ["spec", "vect", "cuda"]
refNames = ["insidespec", "distToInspec","safeToInspec","containsspec","distToOutspec","safeToOutspec"]
### read in the data points from external files
#.. loop over available commits, filling perf data into datasets
datasets = {}
i = 0
while i < len(commits):
commit = commits[i]
filename = commit+"/"+commit+"-perf.dat"
#print "commit: <%s> and file=<%s>" % (commit, filename)
readPerformanceData( i+1, filename, datasets )
i = i + 1
#.. show how to loop over data
#for key,val in datasets.iteritems():
# print val._shape, val._algo, val._impl, len(val._data), val._minkey, val._maxkey
# for i in range(len(val._data)):
# print " ",val._data[i]._x,val._data[i]._y,val._data[i]._dy
#.. Prepare plotting canvas
c1 = TCanvas('c1','c1', 900, 600 )
c1.Divide(3,2)
#.. loop over all shapes requested
for shname in shapes:
shoffset = len(shname)
###.. define references for speedups
refGraphs = []
for name in refNames:
for key,value in datasets.iteritems():
if key==shname+name:
#print "Dataset %s: %d datasets between %s and %s" % (key, len(value._data), value._minkey, value._maxkey )
refGraphs.append( value )
### speedupGraphs will contain the normalized datasets
speedupGraphs = []
for i in range(6): speedupGraphs.append([]) # 6 empty lists for each shape, one list per algo
#.. loop over perf data loaded into datasets, to separate the data into the 6 distinct algorithms
for key,dset in datasets.iteritems() :
if dset._shape != shname: continue
algo = dset._algo
impl = dset._impl
#print "shname=%s - Dataset %s %s %s: %d elements between %s and %s" % (shname, dset._shape, algo, impl, len(dset._data), dset._minkey, dset._maxkey )
#.. search perf data for each algorithm requested
for ialgo in range(6):
ilen = shoffset + len(algoNames[ialgo])
if key[shoffset:ilen] == algoNames[ialgo]:
#evoGraph = dset.tgraphNormError()
speedupGraph = dset.tgraphSpeedup( refGraphs[ialgo] )
#.. search perf data for each implementation requested
for iimpl in range(6):
icolor = iimpl+1
if icolor>4: icolor+=1
#ilen2 = len(implNames[iimpl])
if key[ilen:] == implNames[iimpl]:
#print "found:",iimpl, implNames[iimpl]
speedupGraph.SetLineColor(icolor)
speedupGraph.SetMarkerStyle(20+iimpl)
speedupGraph.SetMarkerColor(icolor)
break
speedupGraphs[ialgo].append( speedupGraph )
#.. now plot the 6 separate groups of datasets
for ialgo in range(len(speedupGraphs)):
ipad = ialgo + 1
#.. scan data for ymin,ymax scale adjustment
ymin = 999999.
ymax = -ymin
for igraph in range(len(speedupGraphs[ialgo])):
tmp = speedupGraphs[ialgo][igraph]
npts = tmp.GetN()
x = tmp.GetX()
y = tmp.GetY()
for i in range(npts):
#print "point %i: (%f; %f)" % (i,x[i],y[i])
if y[i]<ymin: ymin = y[i]
if y[i]>ymax: ymax = y[i]
#print "ialgo=%i, igraph=%i, ymin=%f, ymax=%f" % (ialgo,igraph,ymin,ymax)
gPad = c1.cd(ipad)
gPad.SetGrid(1,1)
#gPad.SetLogx(1)
#gPad.SetLogy(1)
frame1 = gPad.DrawFrame(0, 0.01, 1+len(commits), 1.05*ymax)
frame1.SetTitle(algoNames[ialgo])
frame1.GetXaxis().SetTitle("N tracks")
frame1.GetYaxis().SetTitle("Speed-up")
for igra in range(len(speedupGraphs[ialgo])):
tmp = speedupGraphs[ialgo][igra]
#tmp.SetLineColor(ialgo+1)
if(tmp.GetN()>0): tmp.Draw("ELP")
c1.SetTitle("Speed-ups")
c1.Update()
c1.SaveAs("speedups-"+shname+".png")
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