gamma-simulator 1.0.5

a gamma simulator

Gamma_simulator

This is a gamma pulse simulator jointly developed by Shamoon College of Engineering(SCE) in Israel and Shanghai Advanced Research Institute,CAS in China.Here we will give a brief introduction to our software, including the what and why. For more specific implementation steps of the software, please refer to our paper. Of course,if you are a pure user, please jump directly to Use to see how to use it.

Contents

• Introduction
  • What is Gamma Simulator
  • Why do we creat it
• Software structure
  • Macrostructure
  • Implementation structure
  • Parameter description
  • Main function
• Use
  • Install
  • Import
  • Run
• Notice
  • Shape parameter
  • Plot setting
• Examples
• Contributors
• Known issue
• Todo

Introduction

What is Gamma Simulator?

Gamma simulator is a gamma pulse simulator with parameter customization function, you can specify the type of radioactive source and pulse count rate and other characteristics, generate pulse signals that meet the corresponding characteristics

Why do we creat it?

The original intention of the gamma simulator was to introduce deep learning into energy spectroscopy in the later stage. The use of deep learning to process pulse signals requires that the collected pulse signals have corresponding labels, which is impossible in commercial energy spectrometer. Therefore, we used the simulator to label the pulse signals while generating them, so as to facilitate the reference of deep learning methods. At the same time, simulators can greatly reduce the manpower, material and financial resources of the signal collection process, and can be used to preliminarily test signal processing methods

Software structure

Macrostructure

Implementation structure

Parameter description

Setting Parameters:		type	Default value
verbose	Whether to output detailed information	bool	False
verbose_plots	Whether images need to be output	dict	None
source	The simulated radioactive source	str or dict	'Co-60'
signal_len	Length of time to simulate sampling(s)	int or float	1024
fs	Analog sampling rate	float	1
lambda_value	Analog pulse count rate(cps)	float	0.1
dict_type	Shape type model of the simulated pulse	str	'gamma'
dict_shape_params	dict shape params	dict	Please see Notice
noise_unit	Unit of noise	str	'std'
noise	The magnitude of noise in the given unit	float	0.01
dict_size	Shape dictionary size due to jitter	int	100
seed	The simulated random number seed	int	None

The above parameters can be set and customized by users. The chart shows the default values of parameters and draws discrete pulse signals. For specific parameter Settings in applications, please refer to the example section ,more specific parameter Settings and parameter tests are presented in the example folder

Shape parameters:		type	eg
t_rise	rise time of the shape	float	4.560e-07
t_fall	fall time of the shape	float	6.134e-05
shape_len	length of the shape in samples	int	61
shape_len_sec	length of the shape in seconds	float	6.180e-05
Events parameters:
hist_energy	The energy contained in the spectrum (the transverse axis of the desired spectrum)	array	[0.02,0.04,0.06,... ,1667.20]
hist_counts	The probability of generating energy corresponding to the simulated source(vertical axis of the desired energy spectrum)	array	[0.0002,0.001,0.0015,... ,0.0001]
n_events	number of events in the signal	int	16054
times	arrival times of the events	array	[0.7e-05,1.8e-05,... ,0.92]
energies	The energy sequence of the pulses produced in this simulation	array	[223.2,453.6,889.4,... ,635.4]
lambda_measured	actual event rate	float	13672.2
shape_param1, shape_param2	shape parameters for each event	array	two sequences of n_event values conforming to the Gaussian distribution of the given parameter
Signal parameters:
signal_len	The number of samples at a given frequency in the simulated time	int or float	1e6
signal_len_sec	The length of time of the analog signal(s)	int or float	1
duty_cycle	The proportion of the time to detect the signal to the total analog time	float	0.67
pile_up_stat	number of the pile-ups in the generated signal	int	4302
measured_snr	measured SNR of the generated signal (dB)	float	66.26

These values are intermediate values generated during the simulation, so there are no default values. Here are some examples of these values to give the reader an idea of what these values are

Main function

Function name	input	output	Function action
load_weighted_spectrum	source	hist_energy hist_counts	The energy spectrum of the simulated source (both elemental and mixture)
generate_energy_distribution	seed, n_events, hist_energy, hist_counts	energies	Generate n_event pulses energy sequences conforming to the probability density distribution of the target energy spectrum
generate_arrival_times	seed, lambda_value	times	Generates a Poisson process event arrival time series with a specified count rate(lambda_value)
generate_all_dict_shapes	dict_type,dict_shape_params, dict_size	shapes	Produces a shape dictionary of the specified shapes generated by the specified parameters as a selection library of energy shapes
generate_signal_without_noise	times, energies,shapes_len, shapes	signal without noise	The independent pulses and shapes that we have generated are pieced together to form an analog noiseless signal
generate_signal_with_noise	signal without noise, noise_unit, noise	signal	The noiseless signal is superimposed on the specified unit and size of noise to obtain a real analog signal

A large number of parameters mentioned above are used in the function introduction. In our real code, there is a high degree of integration and a large number of function reuse. Some inputs are not directly called in this function, but by calling other functions, and some output intermediate outputs are directly called by another function after the result is generated, so these temporary variables are not reflected in the description. So this function introduction is not particularly strict, but it is definitely the most suitable for readers to clarify the code logic of the introduction

Use

Install

Make sure you have the following libraries in your environment

• numpy
• scipy
• matplotlib
• urllib
  (It doesn't matter that you don't have these, because these dependencies will be installed when you install the gamma-simulator package)

Please use the following command to install our program

pip install gamma-simulator

Import

from gamma_simulator.gamma_simulator import gamma_simulator

Run

Step 1.Creat an instance

simulator = gamma_simulator()

Step 2.Define parameters

simulator = gamma_simulator(verbose=True,
                            verbose_plots={'shapes': True, 'signal': True},
                            source={'name': 'Co-60', 'weights': 1},
                            signal_len=1,  # "analog" signal of 1 second that are 1e7 samples
                            fs=10e5,
                            lambda_value=1e4,
                            dict_type='gamma',
                            dict_shape_params={'mean1':  0.1,
                                               'std1': 0.001,
                                               'mean2': 1e5,
                                               'std2': 1e3},
                            noise_unit='std',
                            noise=1e-3,
                            dict_size=10,
                            seed=42)

Step 3.Creat the signal

signal = simulator.generate_signal()

Notice

Shape parameter

If you are not familiar with shape parameters, use the following combination of parameters

{dict_type='gamma',
dict_shape_params={'mean1':  0.1,
'std1': 0.001,
'mean2': 1e5,
'std2': 1e3}

or

{dict_type='double_exponential',
dict_shape_params={'mean1': 1e-5, 
'std1': 1e-7,
'mean2': 1e-7,
'std2': 1e-9}

Plot setting

Our simulator supports drawing a variety of graphs, including energy, shape, signal and spectrum.

• Energy：Ideal energy spectrum of the drawn signal source (simulator built-in database)
• Shape：Draws a dictionary set of all possible signal shapes
• Signal：When the length of the resulting signal is less than 2000, the generated signal is drawn, and when the length is greater than 2000, the first 2000 sampling points are drawn

The default option is not to draw, if you need to draw, you need to change the specified value in the parameter definition to True

verbose_plots={'energy':True, 'shapes': True, 'signal': True}

Examples

from gamma_simulator.gamma_simulator import gamma_simulator
simulator = gamma_simulator(verbose=True,
                            verbose_plots={'shapes': True, 'signal': True},
                            source={'name': 'Co-60', 'weights': 1},
                            signal_len=1,  # "analog" signal of 1 second that are 1e7 samples
                            fs=10e6,
                            lambda_value=1e4,
                            dict_type='double_exponential',
                            dict_shape_params={'mean1': 1e-5,  # continuous-time parameters measured in seconds
                                               'std1': 1e-7,
                                               'mean2': 1e-7,
                                               'std2': 1e-9},
                            noise_unit='std',
                            noise=1e-3,
                            dict_size=10,
                            seed=42)
signal = simulator.generate_signal()

from gamma_simulator.gamma_simulator import gamma_simulator
simulator = gamma_simulator(verbose=True,
                            verbose_plots={'energy': True, 'signal': True},
                            source={'name': ['Co-60', 'I-125'], 'weights': [1, 2]},
                            signal_len=1,  # "analog" signal of 1 second that are 1e7 samples
                            fs=10e6,
                            lambda_value=1e4,
                            dict_type='gamma',
                            dict_shape_params={'mean1':  0.1,  # continuous-time parameters measured in seconds
                                               'std1': 0.001,
                                               'mean2': 1e5,
                                               'std2': 1e3},
                            noise_unit='std',
                            noise=1e-3,
                            dict_size=10,
                            seed=42)
signal = simulator.generate_signal()

You can see the result in examples

Contributors

Dima Bykhovsky,Tom Trigano,Zikang Chen

Known issue

Todo

version

1.0.1 upload to pypi

1.0.2 add license and install_requires

1.0.3 can't import

1.0.4 successfully import and fix some bug about gamma.pdf and gamma.ppf parameters

1.0.5 change the bug about hist_energy