witzit/README.md

# witzit - What In The Zap Is That?
`witzit` --- What In The Zap Is That?
AI categorization of spectra from SciAps analyzers.


# Install
## Install Dependencies
Get system dependency and upgrade Python pip.
Perhaps do something like this, or
set up a Python virtual environment.

```
sudo apt update
sudo apt install git python3-pip
pip install --user --upgrade pip
```


## Clone Git Repo
Get source code with `git`.

```
git clone https://spacecruft.org/spacecruft/witzit
cd witzit/
pip install --user --upgrade -r requirements.txt
```


# Usage
HOWTO USE.


# Status
Alpha software under development.


# Hardware

* SciAps LIBS Analyzer

* SciAps XRF Analyzer


# Deep Learning Algorithm
Can use lots from `wut`.

* https://spacecruft.org/spacecruft/satnogs-wut/src/branch/master/wut-worker-mas.py#L67-L79

```
def uncompiled_model():
  model = Sequential([
    Conv2D(16, 3, padding='same', activation='relu', input_shape=(IMG_HEIGHT, IMG_WIDTH ,3)),
    MaxPooling2D(),
    Conv2D(32, 3, padding='same', activation='relu'),
    MaxPooling2D(),
    Conv2D(64, 3, padding='same', activation='relu'),
    MaxPooling2D(),
    Flatten(),
    Dense(512, activation='relu'),
    Dense(1, activation='sigmoid')
  ])
  return model
```


Amazingly (to me), the paper
*Classification of radioxenon spectra with deep learning algorithm*
(2021) by Azimi, et al. uses nearly the identical CNN `Sequence()` as
`wut` uses, indicating it may be a very good base to start from.

Paper is non-gratis science:

* https://www.sciencedirect.com/science/article/abs/pii/S0265931X21001909


The `Sequence()` diagram is pulled from the Azimi paper, but is the
same as in `wut`, so makes a good reference.


![Deep Learning Sequence](img/sequence.png)


# Articles:

* https://www.sciencedirect.com/science/article/abs/pii/S0265931X21001909
*Classification of radioxenon spectra with deep learning algorithm*

* https://www.sciencedirect.com/science/article/pii/S0030401822000402
*Deep convolutional neural networks as a unified solution for Raman spectroscopy-based classification in biomedical applications*

* https://www.sciencedirect.com/science/article/abs/pii/S058485472030313X
*Automatic preprocessing of laser-induced breakdown spectra using partial least squares regression and feed-forward artificial neural network: Applications to Earth and Mars data*

* https://www.sciencedirect.com/science/article/abs/pii/S0584854719306068 
*Determination of minor metal elements in steel using laser-induced breakdown spectroscopy combined with machine learning algorithms*

* https://www.sciencedirect.com/science/article/abs/pii/S1386142521009380
*Feature selection of infrared spectra analysis with convolutional neural network*

# Misc

Will likely work best with binary categorizations. E.g. like this:
Is it element A or not element A?
Is it element B or not element B?
Is it element C or not element C?
Not "is it element A, B, or C?" 


# Unofficial
Unofficial, unaffiliated with SciAps.


# License
License: GPLv3 or any later version. 

Copyright (C) 2022, Jeff Moe