a gamma simulator
Project description
Gamma_simulator
This is a gamma pulse simulator jointly developed by Shamoon College of Engineering(SCE) in Israel and Shanghai Advanced Research Institute 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.For any questions about the software, you can leave a message or send an email to me, I will reply as soon as possilble
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:
Parameter name | Parameter description |
---|---|
verbose | Whether to output detailed information |
verbose_plots | Whether images need to be output |
source | The simulated radioactive source |
signal_len | Length of time to simulate sampling(s) |
fs | Analog sampling rate |
lambda_value | Analog pulse count rate(cps) |
dict_type | Shape type model of the simulated pulse |
dict_shape_params | dict shape params |
noise_unit | Unit of noise |
noise | The magnitude of noise in the given unit |
dict_size | Shape dictionary size due to jitter |
seed | The simulated random number seed |
Shape parameters:
Parameter name | Parameter description |
---|---|
t_rise | rise time of the shape |
t_fall | fall time of the shape |
shape_len | length of the shape in samples |
shape_len_sec | length of the shape in seconds |
Events parameters:
Parameter name | Parameter description |
---|---|
n_events | number of events in the signal |
times | arrival times of the events |
energies | energy values for each event |
lambda_measured | actual event rate |
shape_param1, shape_param2 | shape parameters for each event |
Signal parameters:
Parameter name | Parameter description |
---|---|
signal_len | length of the signal in samples |
signal_len_sec | length of the signal in seconds |
duty_cycle | duty cycle of the signal |
pile_up_stat | number of the pile-ups in the generated signal |
measured_snr | measured SNR of the generated signal (dB) |
Use
Install
Make sure you have the following libraries in your environment
- numpy
- scipy
- matplotlib
- urllib
You can use the following command to install the libaries
pip install numpy scipy matplotlib urllib
Import
from 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': 1.1,
'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': 1.1,
'std1': 0.001,
'mean2': 1e5,
'std2': 1e3}
or
{dict_type='double_exponential',
dict_shape_params={'mean1': 1e-7,
'std1': 1e-9,
'mean2': 1e-5,
'std2': 1e-7}
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 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-7, # continuous-time parameters measured in seconds
'std1': 1e-9,
'mean2': 1e-5,
'std2': 1e-7},
noise_unit='std',
noise=1e-3,
dict_size=10,
seed=42)
signal = simulator.generate_signal()
from 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': 1.1, # 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()
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
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