TMVA_CNN_Classification Namespace Reference

Functions
	MakeImagesTree (n, nh, nw)

Variables
	AdaBoostBeta
	Architecture
	backgroundTree = inputFile.Get("bkg_tree")
float	backgroundWeight = 1.0
	BaggedSampleFraction
	BatchSize
	BoostType
	c1 = factory.GetROCCurve(loader)
	Train Methods.
	CalcCorrelations
str	cnnMethodName = "TMVA_CNN_CPU"
	New DL (CNN).
str	cnnOptions = "CPU"
str	dnnMethodName = "TMVA_DNN_CPU"
str	dnnOptions = "CPU"
	ErrorStrategy
	factory
	Create TMVA Factory.
	FilenameModel
	FilenameTrainedModel
	GpuOptions
	H
str	hasCPU = "tmva-cpu" in ROOT.gROOT.GetConfigFeatures()
str	hasGPU = "tmva-gpu" in ROOT.gROOT.GetConfigFeatures()
int	imgSize = 16 * 16
	Setup Dataset(s).
	inputFile = TFile.Open(inputFileName)
str	inputFileName = "images_data_16x16.root"
	InputLayout
	Layout
	layoutString
	Booking Deep Neural Network.
	loader = TMVA.DataLoader("dataset")
	Declare DataLoader(s).
	loss
int	max_epochs = 10
	MaxDepth
	MinNodeSize
	model = Sequential()
str	mycutb = ""
str	mycuts = ""
	add event variables (image) use new method (from ROOT 6.20 to add a variable array for all image data)
	nCuts
	nEventsBkg = backgroundTree.GetEntries()
	nEventsSig = signalTree.GetEntries()
int	nevt = 1000
	NormMode
	nTrain_Background
	nTrain_Signal
float	nTrainBkg = 0.8 * nEventsBkg
float	nTrainSig = 0.8 * nEventsSig
	NTrees
int	num_threads = 4
	NumEpochs
list	opt = [1, 1, 1, 1, 1]
	optimizer
	outputFile = None
	pyTorchFileName = str(ROOT.gROOT.GetTutorialDir())
	Book Convolutional Neural Network in Keras using a generated model.
	SeparationType
	signalTree = inputFile.Get("sig_tree")
float	signalWeight = 1.0
	SplitMode
	SplitSeed
	TFile = ROOT.TFile
	TMVA = ROOT.TMVA
	torch_spec = importlib.util.find_spec("torch")
	TrainingStrategy
	trainingString1
	Book Convolutional Neural Network in TMVA.
	UseBaggedBoost
list	useKerasCNN = opt[1] if len(opt) > 1 else False
list	usePyTorchCNN = opt[4] if len(opt) > 4 else False
	UserCode
list	useTMVABDT = opt[3] if len(opt) > 3 else False
list	useTMVACNN = opt[0] if len(opt) > 0 else False
list	useTMVADNN = opt[2] if len(opt) > 2 else False
	V
	VarTransform
	weighted_metrics
	WeightInitialization
bool	writeOutputFile = True

Function Documentation

MakeImagesTree()

TMVA_CNN_Classification.MakeImagesTree	(		n,
			nh,
			nw )

Definition at line 42 of file TMVA_CNN_Classification.py.

Variable Documentation

AdaBoostBeta

TMVA_CNN_Classification.AdaBoostBeta

Definition at line 297 of file TMVA_CNN_Classification.py.

Architecture

TMVA_CNN_Classification.Architecture

Definition at line 346 of file TMVA_CNN_Classification.py.

backgroundTree

TMVA_CNN_Classification.backgroundTree = inputFile.Get("bkg_tree")

Definition at line 223 of file TMVA_CNN_Classification.py.

backgroundWeight

float TMVA_CNN_Classification.backgroundWeight = 1.0

Definition at line 230 of file TMVA_CNN_Classification.py.

BaggedSampleFraction

TMVA_CNN_Classification.BaggedSampleFraction

Definition at line 299 of file TMVA_CNN_Classification.py.

BatchSize

TMVA_CNN_Classification.BatchSize

Definition at line 435 of file TMVA_CNN_Classification.py.

BoostType

TMVA_CNN_Classification.BoostType

Definition at line 296 of file TMVA_CNN_Classification.py.

c1

TMVA_CNN_Classification.c1 = factory.GetROCCurve(loader)

Train Methods.

Test and Evaluate Methods

Plot ROC Curve

Definition at line 502 of file TMVA_CNN_Classification.py.

CalcCorrelations

TMVA_CNN_Classification.CalcCorrelations

Definition at line 270 of file TMVA_CNN_Classification.py.

cnnMethodName

str TMVA_CNN_Classification.cnnMethodName = "TMVA_CNN_CPU"

New DL (CNN).

Definition at line 388 of file TMVA_CNN_Classification.py.

cnnOptions

str TMVA_CNN_Classification.cnnOptions = "CPU"

Definition at line 389 of file TMVA_CNN_Classification.py.

dnnMethodName

str TMVA_CNN_Classification.dnnMethodName = "TMVA_DNN_CPU"

Definition at line 327 of file TMVA_CNN_Classification.py.

dnnOptions

str TMVA_CNN_Classification.dnnOptions = "CPU"

Definition at line 330 of file TMVA_CNN_Classification.py.

ErrorStrategy

TMVA_CNN_Classification.ErrorStrategy

Definition at line 341 of file TMVA_CNN_Classification.py.

factory

TMVA_CNN_Classification.factory

Initial value:

=  TMVA.Factory(
    "TMVA_CNN_Classification",
    outputFile,
    V=False,
    ROC=True,
    Silent=False,
    Color=True,
    AnalysisType="Classification",
    Transformations=None,
    Correlations=False,
)

Create TMVA Factory.

Definition at line 175 of file TMVA_CNN_Classification.py.

FilenameModel

TMVA_CNN_Classification.FilenameModel

Definition at line 432 of file TMVA_CNN_Classification.py.

FilenameTrainedModel

TMVA_CNN_Classification.FilenameTrainedModel

Definition at line 433 of file TMVA_CNN_Classification.py.

GpuOptions

TMVA_CNN_Classification.GpuOptions

Definition at line 485 of file TMVA_CNN_Classification.py.

H

TMVA_CNN_Classification.H

Definition at line 339 of file TMVA_CNN_Classification.py.

hasCPU

str TMVA_CNN_Classification.hasCPU = "tmva-cpu" in ROOT.gROOT.GetConfigFeatures()

Definition at line 111 of file TMVA_CNN_Classification.py.

hasGPU

str TMVA_CNN_Classification.hasGPU = "tmva-gpu" in ROOT.gROOT.GetConfigFeatures()

Definition at line 110 of file TMVA_CNN_Classification.py.

imgSize

int TMVA_CNN_Classification.imgSize = 16 * 16

Setup Dataset(s).

Definition at line 205 of file TMVA_CNN_Classification.py.

inputFile

TMVA_CNN_Classification.inputFile = TFile.Open(inputFileName)

Definition at line 212 of file TMVA_CNN_Classification.py.

inputFileName

str TMVA_CNN_Classification.inputFileName = "images_data_16x16.root"

Definition at line 206 of file TMVA_CNN_Classification.py.

InputLayout

TMVA_CNN_Classification.InputLayout

Definition at line 404 of file TMVA_CNN_Classification.py.

Layout

TMVA_CNN_Classification.Layout

Definition at line 344 of file TMVA_CNN_Classification.py.

layoutString

TMVA_CNN_Classification.layoutString

Initial value:

=  ROOT.TString(
        "DENSE|100|RELU,BNORM,DENSE|100|RELU,BNORM,DENSE|100|RELU,BNORM,DENSE|100|RELU,DENSE|1|LINEAR"
    )

Booking Deep Neural Network.

Definition at line 311 of file TMVA_CNN_Classification.py.

loader

TMVA_CNN_Classification.loader = TMVA.DataLoader("dataset")

Declare DataLoader(s).

Definition at line 197 of file TMVA_CNN_Classification.py.

loss

TMVA_CNN_Classification.loss

Definition at line 465 of file TMVA_CNN_Classification.py.

max_epochs

int TMVA_CNN_Classification.max_epochs = 10

Definition at line 135 of file TMVA_CNN_Classification.py.

MaxDepth

TMVA_CNN_Classification.MaxDepth

Definition at line 295 of file TMVA_CNN_Classification.py.

MinNodeSize

TMVA_CNN_Classification.MinNodeSize

Definition at line 294 of file TMVA_CNN_Classification.py.

model

TMVA_CNN_Classification.model = Sequential()

Definition at line 455 of file TMVA_CNN_Classification.py.

mycutb

str TMVA_CNN_Classification.mycutb = ""

Definition at line 247 of file TMVA_CNN_Classification.py.

mycuts

str TMVA_CNN_Classification.mycuts = ""

add event variables (image) use new method (from ROOT 6.20 to add a variable array for all image data)

Definition at line 246 of file TMVA_CNN_Classification.py.

nCuts

TMVA_CNN_Classification.nCuts

Definition at line 301 of file TMVA_CNN_Classification.py.

nEventsBkg

TMVA_CNN_Classification.nEventsBkg = backgroundTree.GetEntries()

Definition at line 226 of file TMVA_CNN_Classification.py.

nEventsSig

TMVA_CNN_Classification.nEventsSig = signalTree.GetEntries()

Definition at line 225 of file TMVA_CNN_Classification.py.

nevt

int TMVA_CNN_Classification.nevt = 1000

Definition at line 113 of file TMVA_CNN_Classification.py.

NormMode

TMVA_CNN_Classification.NormMode

Definition at line 268 of file TMVA_CNN_Classification.py.

nTrain_Background

TMVA_CNN_Classification.nTrain_Background

Definition at line 265 of file TMVA_CNN_Classification.py.

nTrain_Signal

TMVA_CNN_Classification.nTrain_Signal

Definition at line 264 of file TMVA_CNN_Classification.py.

nTrainBkg

float TMVA_CNN_Classification.nTrainBkg = 0.8 * nEventsBkg

Definition at line 257 of file TMVA_CNN_Classification.py.

nTrainSig

float TMVA_CNN_Classification.nTrainSig = 0.8 * nEventsSig

Definition at line 256 of file TMVA_CNN_Classification.py.

NTrees

TMVA_CNN_Classification.NTrees

Definition at line 293 of file TMVA_CNN_Classification.py.

num_threads

int TMVA_CNN_Classification.num_threads = 4

Definition at line 134 of file TMVA_CNN_Classification.py.

NumEpochs

TMVA_CNN_Classification.NumEpochs

Definition at line 434 of file TMVA_CNN_Classification.py.

opt

list TMVA_CNN_Classification.opt = [1, 1, 1, 1, 1]

Definition at line 30 of file TMVA_CNN_Classification.py.

optimizer

TMVA_CNN_Classification.optimizer

Definition at line 465 of file TMVA_CNN_Classification.py.

outputFile

TMVA_CNN_Classification.outputFile = None

Definition at line 149 of file TMVA_CNN_Classification.py.

pyTorchFileName

TMVA_CNN_Classification.pyTorchFileName = str(ROOT.gROOT.GetTutorialDir())

Book Convolutional Neural Network in Keras using a generated model.

Definition at line 416 of file TMVA_CNN_Classification.py.

SeparationType

TMVA_CNN_Classification.SeparationType

Definition at line 300 of file TMVA_CNN_Classification.py.

signalTree

TMVA_CNN_Classification.signalTree = inputFile.Get("sig_tree")

Definition at line 222 of file TMVA_CNN_Classification.py.

signalWeight

float TMVA_CNN_Classification.signalWeight = 1.0

Definition at line 229 of file TMVA_CNN_Classification.py.

SplitMode

TMVA_CNN_Classification.SplitMode

Definition at line 266 of file TMVA_CNN_Classification.py.

SplitSeed

TMVA_CNN_Classification.SplitSeed

Definition at line 267 of file TMVA_CNN_Classification.py.

TFile

TMVA_CNN_Classification.TFile = ROOT.TFile

Definition at line 38 of file TMVA_CNN_Classification.py.

TMVA

TMVA_CNN_Classification.TMVA = ROOT.TMVA

Definition at line 37 of file TMVA_CNN_Classification.py.

torch_spec

TMVA_CNN_Classification.torch_spec = importlib.util.find_spec("torch")

Definition at line 419 of file TMVA_CNN_Classification.py.

TrainingStrategy

TMVA_CNN_Classification.TrainingStrategy

Definition at line 345 of file TMVA_CNN_Classification.py.

trainingString1

TMVA_CNN_Classification.trainingString1

Initial value:

=  ROOT.TString(
        "LearningRate=1e-3,Momentum=0.9,Repetitions=1,"
        "ConvergenceSteps=5,BatchSize=100,TestRepetitions=1,"
        "WeightDecay=1e-4,Regularization=None,"
        "Optimizer=ADAM,DropConfig=0.0+0.0+0.0+0."
    )

Book Convolutional Neural Network in TMVA.

Definition at line 318 of file TMVA_CNN_Classification.py.

UseBaggedBoost

TMVA_CNN_Classification.UseBaggedBoost

Definition at line 298 of file TMVA_CNN_Classification.py.

useKerasCNN

bool TMVA_CNN_Classification.useKerasCNN = opt[1] if len(opt) > 1 else False

Definition at line 32 of file TMVA_CNN_Classification.py.

usePyTorchCNN

bool TMVA_CNN_Classification.usePyTorchCNN = opt[4] if len(opt) > 4 else False

Definition at line 35 of file TMVA_CNN_Classification.py.

UserCode

TMVA_CNN_Classification.UserCode

Definition at line 436 of file TMVA_CNN_Classification.py.

useTMVABDT

list TMVA_CNN_Classification.useTMVABDT = opt[3] if len(opt) > 3 else False

Definition at line 34 of file TMVA_CNN_Classification.py.

useTMVACNN

bool TMVA_CNN_Classification.useTMVACNN = opt[0] if len(opt) > 0 else False

Definition at line 31 of file TMVA_CNN_Classification.py.

useTMVADNN

bool TMVA_CNN_Classification.useTMVADNN = opt[2] if len(opt) > 2 else False

Definition at line 33 of file TMVA_CNN_Classification.py.

V

TMVA_CNN_Classification.V

Definition at line 269 of file TMVA_CNN_Classification.py.

VarTransform

TMVA_CNN_Classification.VarTransform

Definition at line 342 of file TMVA_CNN_Classification.py.

weighted_metrics

TMVA_CNN_Classification.weighted_metrics

Definition at line 465 of file TMVA_CNN_Classification.py.

WeightInitialization

TMVA_CNN_Classification.WeightInitialization

Definition at line 343 of file TMVA_CNN_Classification.py.

writeOutputFile

bool TMVA_CNN_Classification.writeOutputFile = True

Definition at line 132 of file TMVA_CNN_Classification.py.