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ApplicationRegressionKeras.py
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1#!/usr/bin/env python
2## \file
3## \ingroup tutorial_tmva_keras
4## \notebook -nodraw
5## This tutorial shows how to apply a trained model to new data (regression).
6##
7## \macro_code
8##
9## \date 2017
10## \author TMVA Team
11
12from ROOT import TMVA, TFile, TString
13from array import array
14from subprocess import call
15from os.path import isfile
16
17# Setup TMVA
20reader = TMVA.Reader("Color:!Silent")
21
22# Load data
23if not isfile('tmva_reg_example.root'):
24 call(['curl', '-O', 'http://root.cern.ch/files/tmva_reg_example.root'])
25
26data = TFile.Open('tmva_reg_example.root')
27tree = data.Get('TreeR')
28
29branches = {}
30for branch in tree.GetListOfBranches():
31 branchName = branch.GetName()
32 branches[branchName] = array('f', [-999])
33 tree.SetBranchAddress(branchName, branches[branchName])
34 if branchName != 'fvalue':
35 reader.AddVariable(branchName, branches[branchName])
36
37# Book methods
38reader.BookMVA('PyKeras', TString('dataset/weights/TMVARegression_PyKeras.weights.xml'))
39
40# Print some example regressions
41print('Some example regressions:')
42for i in range(20):
43 tree.GetEntry(i)
44 print('True/MVA value: {}/{}'.format(branches['fvalue'][0],reader.EvaluateMVA('PyKeras')))
static TFile * Open(const char *name, Option_t *option="", const char *ftitle="", Int_t compress=ROOT::RCompressionSetting::EDefaults::kUseCompiledDefault, Int_t netopt=0)
Create / open a file.
Definition TFile.cxx:3997
static void PyInitialize()
Initialize Python interpreter.
The Reader class serves to use the MVAs in a specific analysis context.
Definition Reader.h:64
static Tools & Instance()
Definition Tools.cxx:75
Basic string class.
Definition TString.h:136