GaussianEstimatorTrainer Class Reference

Inheritance diagram for GaussianEstimatorTrainer:

Collaboration diagram for GaussianEstimatorTrainer:

Public Member Functions
def	__init__ (self)
def	plot_grouped_result (self, data)
def	create_result_dataframe (self)
def	fit_result_parameters (self)
def	train (self, data)
def	plot_fit_result (self, data)
def	create_dedx_bins (self, data)
def	create_p_bins (self, data)
def	use_only_the_highest_values (self, data, number_of_values=None)
def	create_fit_data (self, dedx_bin)
def	fit_p_to_dedx_bin (self, dedx_bin)
def	test (self, data)

Public Attributes
	dimension_of_fit_function
	cached value of the degrees of freedom in the fit
	fit_function
	cached copy of the fitting function
	train_function
	this class's training function
	result_function
	cached copy of the result function
	result_parameters_for_each_dedx_bin
	cached copy of the dictionary of fitting parameters for each dE/dx bin
	use_sigma_for_result_fitting
	cached copy of the flag to add mean+/-sigma values to the output Dataframe
	dedx_estimator_function
	cached copies of the fit parameters and estimator function
	dedx_column
	the default data column is 'dedx'

Static Public Attributes
int	number_of_bins_in_dedx = 20
	number of dE/dx bins
int	number_of_bins_in_p = 29
	number of track-momentum bins
int	number_of_head_values_used_to_fit = 20
	number of head values in fit

Detailed Description

Train a neural network for dE/dx-based particle identification using a Gaussian estimator

Definition at line 249 of file train.py.

Constructor & Destructor Documentation

__init__()

def __init__

(

self

)

Constructor

Reimplemented from DEDXEstimationTrainer.

Definition at line 252 of file train.py.

Member Function Documentation

create_dedx_bins()

def create_dedx_bins (   self,   data  )

inherited

Construct the dE/dx bins and then populate them with the data

Definition at line 52 of file train.py.

create_fit_data()

def create_fit_data (   self,   dedx_bin  )

inherited

Fit track-momentum values

Definition at line 74 of file train.py.

create_p_bins()

def create_p_bins (   self,   data  )

inherited

Construct the momentum bins and then populate them with the data

Definition at line 61 of file train.py.

create_result_dataframe()

def create_result_dataframe (   self )

inherited

Fit for the mean dE/dx and standard deviation, return the fit Dataframe

Definition at line 107 of file train.py.

fit_p_to_dedx_bin()

def fit_p_to_dedx_bin (   self,   dedx_bin  )

inherited

Fit the track-momentum values in the selected dE/dx bin, then train on the fitted values

Definition at line 86 of file train.py.

fit_result_parameters()

def fit_result_parameters (   self )

inherited

Define the parameters for the fit, assign initial guesses

Definition at line 126 of file train.py.

plot_fit_result()

def plot_fit_result (   self,   data  )

inherited

Plot the fitted results

Definition at line 154 of file train.py.

plot_grouped_result()

def plot_grouped_result (   self,   data  )

inherited

Plot the fitted grouped results

Reimplemented from FittedGroupedDEDXEstimatorTrainer.

Definition at line 222 of file train.py.

test()

def test (   self,   data  )

inherited

Get the trained neural-network output value for test data

Reimplemented in MVADEDXEstimationTrainer.

Definition at line 34 of file train.py.

train()

def train (   self,   data  )

inherited

Train the neural network using curated data

Reimplemented from DEDXEstimationTrainer.

Definition at line 140 of file train.py.

use_only_the_highest_values()

def use_only_the_highest_values (   self,   data,   number_of_values = None  )

inherited

Sort the data then select only the highest N values

Definition at line 67 of file train.py.

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The documentation for this class was generated from the following file:

• tracking/studies/low_momentum_vxd_estimation/train.py