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73 changes: 37 additions & 36 deletions README.md
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<a href="https://www.ultralytics.com/" target="_blank"><img src="https://raw.githubusercontent.com/ultralytics/assets/main/logo/Ultralytics_Logotype_Original.svg" width="320" alt="Ultralytics logo"></a>
<a href="https://www.ultralytics.com/"><img src="https://raw.githubusercontent.com/ultralytics/assets/main/logo/Ultralytics_Logotype_Original.svg" width="320" alt="Ultralytics logo"></a>

# 🌟 Introduction

Welcome to the Neutron TimeCube (NTC) analysis tools repository! This project is designed to provide researchers and data analysts with tools to interpret and visualize data from the NTC, a sophisticated device used in neutron detection and characterization.
Welcome to the Neutron TimeCube (NTC) analysis tools repository! This project provides researchers and data analysts with essential tools for interpreting and visualizing data generated by the NTC, a sophisticated device used in [neutron detection](https://en.wikipedia.org/wiki/Neutron_detection) and characterization.

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## πŸ“œ Description
## πŸ“œ Project Overview

The repository available at [ultralytics/ntc](https://github.com/ultralytics/ntc) houses a suite of MATLAB scripts and functions tailored for the analysis of neutron detection data. With these tools, users can process, analyze, and visualize NTC data, facilitating cutting-edge research in neutron science.
The repository, available at [ultralytics/ntc](https://github.com/ultralytics/ntc), contains a suite of [MATLAB](https://www.mathworks.com/products/matlab.html) scripts and functions specifically designed for analyzing neutron detection data. These tools empower users to process, analyze, and visualize NTC data, supporting advanced research in [neutron science](https://en.wikipedia.org/wiki/Neutron_science).

## βš™οΈ Requirements
## βš™οΈ Prerequisites

Before diving in, make sure you have the following prerequisites:
Before you begin, ensure you meet the following requirements:

- [MATLAB](https://www.mathworks.com/products/matlab.html) version 2018a or higher.
- Access to the 'functions-matlab' common functions repository:
- **MATLAB:** Version 2018a or newer.
- **Common Functions:** Access to the `functions-matlab` common functions repository. Clone it using:
```bash
$ git clone https://github.com/ultralytics/functions-matlab
git clone https://github.com/ultralytics/functions-matlab
```
Add the repository to the MATLAB path using:
Then, add the repository to your MATLAB path:
```matlab
>> addpath(genpath('/path/to/functions-matlab'))
addpath(genpath('/path/to/functions-matlab')) % Replace with the actual path
```
- The following MATLAB toolboxes should be installed:
- Statistics and Machine Learning Toolbox
- Signal Processing Toolbox
- **MATLAB Toolboxes:** The following toolboxes must be installed:
- [Statistics and Machine Learning Toolbox](https://www.mathworks.com/products/statistics.html)
- [Signal Processing Toolbox](https://www.mathworks.com/products/signal.html)

Ensure that all installations and configurations match these requirements to smoothly run the NTC analysis tools.
Verify that all installations and path configurations are correctly set up to ensure the NTC analysis tools run smoothly.

## πŸƒ Running the Tools
## πŸš€ Getting Started

To begin analyzing your data:
To start analyzing your NTC data:

1. Open MATLAB
2. Execute the command:
```matlab
>> NTCviewer
```
1. Open MATLAB.
2. Navigate to the repository directory.
3. Execute the following command in the [MATLAB Command Window](https://www.mathworks.com/help/matlab/learn_matlab/command-window.html):
```matlab
NTCviewer
```

Here is a glimpse of the kind of interface you can expect with our `NTCviewer`:
Below is an example of the `NTCviewer` interface you will interact with:

![mtcView Interface](https://github.com/ultralytics/ntc/assets/26833433/32d0b7b9-4626-43c8-9ae1-85930414ea70)

## 🀝 Contribute
## 🀝 Contributing

We welcome contributions from the community! Whether you're fixing bugs, adding new features, or improving documentation, your input is invaluable. Take a look at our [Contributing Guide](https://docs.ultralytics.com/help/contributing/) to get started. Also, we'd love to hear about your experience with Ultralytics products. Please consider filling out our [Survey](https://www.ultralytics.com/survey?utm_source=github&utm_medium=social&utm_campaign=Survey). A huge πŸ™ and thank you to all of our contributors!
Contributions from the [GitHub](https://github.com/) community are highly encouraged! Whether it involves fixing bugs, adding new features, or enhancing documentation, your input is valuable. Please review our [Contributing Guide](https://docs.ultralytics.com/help/contributing/) for detailed instructions on how to participate. We also invite you to share your experiences with [Ultralytics](https://www.ultralytics.com/) products by completing our brief [Survey](https://www.ultralytics.com/survey?utm_source=github&utm_medium=social&utm_campaign=Survey). A big thank you πŸ™ to all our contributors!

<!-- Ultralytics contributors -->
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<a href="https://github.com/ultralytics/yolov5/graphs/contributors">
<img width="100%" src="https://github.com/ultralytics/assets/raw/main/im/image-contributors.png" alt="Ultralytics open-source contributors"></a>
## ©️ Licensing

## ©️ License
Ultralytics offers two licensing options to accommodate different usage scenarios:

Ultralytics is excited to offer two different licensing options to meet your needs:
- **AGPL-3.0 License:** This [OSI-approved](https://opensource.org/license) open-source license is ideal for students and enthusiasts interested in open collaboration and knowledge sharing. See the [LICENSE](https://github.com/ultralytics/ntc/blob/main/LICENSE) file for specifics.
- **Enterprise License:** Designed for commercial applications, this license permits the integration of Ultralytics software and AI models into commercial products and services without the open-source requirements of AGPL-3.0. If your project involves commercial use, please inquire about an [Enterprise License](https://www.ultralytics.com/license).

- **AGPL-3.0 License**: Perfect for students and hobbyists, this [OSI-approved](https://opensource.org/license) open-source license encourages collaborative learning and knowledge sharing. Please refer to the [LICENSE](https://github.com/ultralytics/ultralytics/blob/main/LICENSE) file for detailed terms.
- **Enterprise License**: Ideal for commercial use, this license allows for the integration of Ultralytics software and AI models into commercial products without the open-source requirements of AGPL-3.0. For use cases that involve commercial applications, please contact us via [Ultralytics Licensing](https://www.ultralytics.com/license).
## πŸ“¬ Get in Touch

## πŸ“¬ Contact Us

For bug reports, feature requests, and contributions, head to [GitHub Issues](https://github.com/ultralytics/velocity/issues). For questions and discussions about this project and other Ultralytics endeavors, join us on [Discord](https://discord.com/invite/ultralytics)!
For bug reports, feature suggestions, and contributions, please use the [GitHub Issues](https://github.com/ultralytics/ntc/issues) section of the repository. For broader questions and discussions about this project or other Ultralytics initiatives, join the [Ultralytics community](https://community.ultralytics.com/) or connect with us on [Discord](https://discord.com/invite/ultralytics)!

<br>
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2 changes: 2 additions & 0 deletions mapping/NTCIRSDmap.m
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% Ultralytics πŸš€ AGPL-3.0 License - https://ultralytics.com/license

function X = NTCIRSDmap(i,mapto)
%This functions maps the NTC pixels 1-128 into SRCCH format and vice versa
%See NTC Rosetta Stone: https://docs.google.com/spreadsheets/d/1RBM7bU40RPUYE5Yir00huaN4qAF6mQY3DwBZ1RnqrHs/edit#gid=1975841640
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2 changes: 2 additions & 0 deletions mapping/plotNTC.m
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% Ultralytics πŸš€ AGPL-3.0 License - https://ultralytics.com/license

function [] = plotNTC(input0,output)

i = MTCSRCCH2pixelID(NTCIRSDmap(1:128,'SRCCH'));
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2 changes: 2 additions & 0 deletions nanporch.m
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% Ultralytics πŸš€ AGPL-3.0 License - https://ultralytics.com/license

function porch = nanporch(V,threshold)
%Best practice is to remove spikes before subtracting porch!
%porch defined as baseline of every point before first crossing of threshold
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2 changes: 2 additions & 0 deletions processDRS4.m
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% Ultralytics πŸš€ AGPL-3.0 License - https://ultralytics.com/license

function [] = processDRS4()
clc; f=''; tic
%p='/Users/glennjocher/Downloads/DATA/DRS4/Serge/11.25/';
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2 changes: 2 additions & 0 deletions triggerCell2timebase.m
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% Ultralytics πŸš€ AGPL-3.0 License - https://ultralytics.com/license

function [that, X] = triggerCell2timebase(ei,board,ch,tc,X)
ei=ei(:); board=board(:); ch=ch(:); tc=tc(:); if any(ch==0); ch=ch+1; end

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2 changes: 2 additions & 0 deletions viewer/NTCviewer.m
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% Ultralytics πŸš€ AGPL-3.0 License - https://ultralytics.com/license

function [] = NTCviewer()
clc; close all; format short g
s = mfilename('fullpath'); s = s(1:find(s==filesep,1,'last')); cd(s)
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2 changes: 2 additions & 0 deletions viewer/motionNTC.m
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% Ultralytics πŸš€ AGPL-3.0 License - https://ultralytics.com/license

function [] = motionNTC()
ha=gca;
p=ha.CurrentPoint; x1=p(1,:); x2=p(2,:); %mouse pointing vector
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2 changes: 2 additions & 0 deletions xml/DRS4stats.m
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% Ultralytics πŸš€ AGPL-3.0 License - https://ultralytics.com/license

function [] = DRS4stats()
clc; close all
%filename='scintillator.air.coupling.5gsps.xml';
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2 changes: 2 additions & 0 deletions xml/filterV.m
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% Ultralytics πŸš€ AGPL-3.0 License - https://ultralytics.com/license

function H = filterV(V)
x=1:numel(V); clc; close all

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2 changes: 2 additions & 0 deletions xml/loadDRS4xml.m
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% Ultralytics πŸš€ AGPL-3.0 License - https://ultralytics.com/license

function C = loadDRS4xml(filename, pathname)
%pathname='/Users/glennjocher/Downloads/DRS4/autoTrigger/';
if nargin==0; filename='scintillator.air.coupling.5gsps.xml'; end %for debugging
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