if __name__ == "__main__":
path = "/Users/musthero/Documents/Yura/Applications/tmva_local/BDT_score_distributions_electrons.root"
hsig_path = "histo_tmva_sig"
hbkg_path = "histo_tmva_bkg"
rootfile = ROOT.TFile.Open(path)
if rootfile.IsZombie():
print "Root file is corrupt"
hSig = rootfile.Get(hsig_path)
hBkg = rootfile.Get(hbkg_path)
g = build_roc(hSig, hBkg, 1)
ll = [g]
g.SetLineColor(ROOT.kBlue)
g.Draw("AL") # draw TGraph with no marker dots
# Draw rectangular cuts
eff_rej = (0.889199,0.898912,0.000337,0.001671)
sig_eff_val = array('f', [eff_rej[0]])
sig_eff_err = array('f', [eff_rej[1]])
bkg_rej_val = array('f', [eff_rej[2]])
bkg_rej_err = array('f', [eff_rej[3]])
rootfile = ROOT.TFile.Open(path)
if rootfile.IsZombie():
print "Root file is corrupt"
hSig_skTMVA = rootfile.Get(hsig_skTMVA_path)
hBkg_skTMVA = rootfile.Get(hbkg_skTMVA_path)
hSig_sklearn = rootfile.Get(hsig_sklearn_path)
hBkg_sklearn = rootfile.Get(hbkg_sklearn_path)
# Stack for keeping plots
plots = []
# Getting ROC-curve for skTMVA
g1 = build_roc(hSig_skTMVA, hBkg_skTMVA)
g1.SetName("g1")
g1.SetTitle("ROC curve [electrons]")
plots.append(g1)
g1.SetLineColor(ROOT.kBlue)
g1.Draw("AL") # draw TGraph with no marker dots
# Getting ROC-curve for sklearn
g2 = build_roc(hSig_sklearn, hBkg_sklearn)
g2.SetName("g2")
g2.SetTitle("ROC curve [electrons]")
plots.append(g2)
g2.SetLineStyle(7)
g2.SetLineColor(ROOT.kRed)
sig_eff = array.array('f', [rate for rate in tpr])
bkg_rej = array.array('f', [(1 - rate) for rate in fpr])
# roc_curve_sk() - skTMVA version of roc_curve
from mva_tools.build_roc_simple import roc_curve_sk
fpr_comp, tpr_comp, _ = roc_curve_sk(y_test, sk_y_predicted)
sig_eff_comp = array.array('f', [rate for rate in tpr_comp])
bkg_rej_comp = array.array('f', [(1 - rate) for rate in fpr_comp])
# Stack for keeping plots
plots = []
# Getting ROC-curve for skTMVA
g1 = build_roc(histo_tmva_sig, histo_tmva_bkg)
g1.SetName("g1")
g1.SetTitle("skTMVA ROC curve [electrons]")
plots.append(g1)
g1.SetLineColor(8) # Green color
g1.Draw("AL") # draw TGraph with no marker dots
# Getting ROC-curve for sklearn
g2 = ROOT.TGraph(len(tpr), sig_eff, bkg_rej)
g2.GetXaxis().SetRangeUser(0.0, 1.0)
g2.GetYaxis().SetRangeUser(0.0, 1.0)
g2.SetName("g2")
g2.SetTitle("scikitlearn ROC curve [electrons]")
plots.append(g2)
if rootfile.IsZombie():
print "Root file is corrupt"
hSig_skTMVA = rootfile.Get(hsig_skTMVA_path)
hBkg_skTMVA = rootfile.Get(hbkg_skTMVA_path)
hSig_sklearn = rootfile.Get(hsig_sklearn_path)
hBkg_sklearn = rootfile.Get(hbkg_sklearn_path)
# Stack for keeping plots
plots = []
# Getting ROC-curve for skTMVA
g1 = build_roc(hSig_skTMVA, hBkg_skTMVA)
g1.SetName("g1")
g1.SetTitle("ROC curve [muons]")
plots.append(g1)
g1.SetLineColor(ROOT.kBlue)
g1.Draw("AL") # draw TGraph with no marker dots
# Getting ROC-curve for sklearn
g2 = build_roc(hSig_sklearn, hBkg_sklearn)
g2.SetName("g2")
g2.SetTitle("ROC curve [muons]")
plots.append(g2)
g2.SetLineStyle(7)
g2.SetLineColor(ROOT.kRed)
# roc_curve_sk() - skTMVA version of roc_curve
from mva_tools.build_roc_simple import roc_curve_sk
fpr_comp, tpr_comp, _ = roc_curve_sk(y_test, sk_y_predicted)
sig_eff_comp = array.array("f", [rate for rate in tpr_comp])
bkg_rej_comp = array.array("f", [(1 - rate) for rate in fpr_comp])
# Stack for keeping plots
plots = []
# Getting ROC-curve for skTMVA
g1 = build_roc(histo_tmva_sig, histo_tmva_bkg)
g1.SetName("g1")
g1.SetTitle("skTMVA ROC curve [electrons]")
plots.append(g1)
g1.SetLineColor(8) # Green color
g1.Draw("AL") # draw TGraph with no marker dots
# Getting ROC-curve for sklearn
g2 = ROOT.TGraph(len(tpr), sig_eff, bkg_rej)
g2.GetXaxis().SetRangeUser(0.0, 1.0)
g2.GetYaxis().SetRangeUser(0.0, 1.0)
g2.SetName("g2")
g2.SetTitle("scikitlearn ROC curve [electrons]")
plots.append(g2)
