Input Namespace Reference

Variables
string	Training_Data = 'SSS'
	TRAINING DATA & DATA SET STRUCTURE #########. More...
string	DirName = '/home/axel/4TB/uniqorn_data/rand_DW'
int	NDatasets = 400
	DATA SET STRUCTURE FOR SINGLE SHOTS: ###. More...
int	Npoints = 256
int	NShots = 400
int	NShotsPerSample = 100
float	TrainFraction = 0.75
bool	NormalizeData = False
bool	momData = False
bool	Plot = False
bool	AxisFlipping = False
bool	DataThreshold = False
bool	DataThresholdTest = False
float	DataThresholdLow = 0.03
float	DataThresholdHigh = 0.3
bool	MultiSSSOrder = True
int	MultiSSS_NOrder = 3
bool	batch_loading = False
	BATCHING & EPOCHS #########. More...
int	batch_size = 10
int	epochs = 200
bool	Randomize = False
bool	Shuffle = True
string	Loss = 'mse'
string	Job_Type = 'SUPERV_REGR'
	MACHINE LEARNING TASKS #########. More...
string	Learn = 'DENS'
int	Dimensionality = 1
int	NViz = 20
bool	Visualization_Save = True
bool	TrainingFlag = True
bool	Visualization_Accuracies = True
bool	Visualization_Losses = True
bool	Visualization_Errors = True
bool	Visualization_ErrorHistograms = True
bool	VisualizationFlag = True
string	Model = 'custom'
string	Model_Name = 'Seq128Dropout'
bool	ConvNet = False
list	callbacks = ['reduce_lr','earlystopping']
list	layers = [512,256,128,64]
list	regularizations = [0.0,0.3,0.1,0.01]
list	filters = [256,256,16]
list	kernelsizes = [(1,50),(8,1),(8,1)]
list	pooling = ['max','none','max']
list	batchnormalization = [True,False,False,False,False,False,False,False]
float	OutputDropout = 0.3
float	FragmentationLowerBound = 0.01
	TASK-SPECIFIC FLAGS #########. More...
float	FragmentationUpperBound = 0.5
float	FragmentationThreshold = 0.1
int	num_classes = 2
int	NPartLowerBound = 1
	PARTICLE NUMBER TASKS: ###. More...
int	NPartUpperBound = 100
bool	momLabels = False
	DENSITY TASKS: ###. More...
bool	NormalizeLabels = False
bool	InterpolatePredictions = False
bool	LearnInterpolationKnots = False
int	InterpolNpoints = 10
float	RegularizationWeight = 0.01
int	InterpolOrder = 5
int	PhaseBins = 20
	PHASE TASKS: ###. More...

Variable Documentation

AxisFlipping

bool Input.AxisFlipping = False

batch_loading

bool Input.batch_loading = False

BATCHING & EPOCHS #########.

batch_size

int Input.batch_size = 10

batchnormalization

list Input.batchnormalization = [True,False,False,False,False,False,False,False]

callbacks

list Input.callbacks = ['reduce_lr','earlystopping']

ConvNet

bool Input.ConvNet = False

DataThreshold

bool Input.DataThreshold = False

DataThresholdHigh

float Input.DataThresholdHigh = 0.3

DataThresholdLow

float Input.DataThresholdLow = 0.03

DataThresholdTest

bool Input.DataThresholdTest = False

Dimensionality

int Input.Dimensionality = 1

DirName

string Input.DirName = '/home/axel/4TB/uniqorn_data/rand_DW'

epochs

int Input.epochs = 200

filters

list Input.filters = [256,256,16]

FragmentationLowerBound

float Input.FragmentationLowerBound = 0.01

TASK-SPECIFIC FLAGS #########.

FRAGMENTATION TASKS: ###

FragmentationThreshold

float Input.FragmentationThreshold = 0.1

FragmentationUpperBound

float Input.FragmentationUpperBound = 0.5

InterpolatePredictions

bool Input.InterpolatePredictions = False

InterpolNpoints

int Input.InterpolNpoints = 10

InterpolOrder

int Input.InterpolOrder = 5

Job_Type

string Input.Job_Type = 'SUPERV_REGR'

MACHINE LEARNING TASKS #########.

kernelsizes

list Input.kernelsizes = [(1,50),(8,1),(8,1)]

layers

list Input.layers = [512,256,128,64]

Learn

string Input.Learn = 'DENS'

LearnInterpolationKnots

bool Input.LearnInterpolationKnots = False

Loss

string Input.Loss = 'mse'

Model

string Input.Model = 'custom'

Model_Name

string Input.Model_Name = 'Seq128Dropout'

momData

bool Input.momData = False

momLabels

bool Input.momLabels = False

DENSITY TASKS: ###.

MultiSSS_NOrder

int Input.MultiSSS_NOrder = 3

MultiSSSOrder

bool Input.MultiSSSOrder = True

NDatasets

int Input.NDatasets = 400

DATA SET STRUCTURE FOR SINGLE SHOTS: ###.

NormalizeData

bool Input.NormalizeData = False

NormalizeLabels

bool Input.NormalizeLabels = False

NPartLowerBound

int Input.NPartLowerBound = 1

PARTICLE NUMBER TASKS: ###.

NPartUpperBound

int Input.NPartUpperBound = 100

Npoints

int Input.Npoints = 256

NShots

int Input.NShots = 400

NShotsPerSample

int Input.NShotsPerSample = 100

num_classes

int Input.num_classes = 2

NViz

int Input.NViz = 20

OutputDropout

float Input.OutputDropout = 0.3

PhaseBins

int Input.PhaseBins = 20

PHASE TASKS: ###.

Plot

bool Input.Plot = False

pooling

list Input.pooling = ['max','none','max']

Randomize

bool Input.Randomize = False

regularizations

list Input.regularizations = [0.0,0.3,0.1,0.01]

RegularizationWeight

float Input.RegularizationWeight = 0.01

Shuffle

bool Input.Shuffle = True

TrainFraction

float Input.TrainFraction = 0.75

Training_Data

string Input.Training_Data = 'SSS'

TRAINING DATA & DATA SET STRUCTURE #########.

TrainingFlag

bool Input.TrainingFlag = True

Visualization_Accuracies

bool Input.Visualization_Accuracies = True

Visualization_ErrorHistograms

bool Input.Visualization_ErrorHistograms = True

Visualization_Errors

bool Input.Visualization_Errors = True

Visualization_Losses

bool Input.Visualization_Losses = True

Visualization_Save

bool Input.Visualization_Save = True

VisualizationFlag

bool Input.VisualizationFlag = True