uploading my master thesis code

.coveragerc

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+[run]
+source = lung_cancer
+omit = */__init__.py
+
+[report]
+exclude_lines =
+    @abstractmethod

.github/workflows/flake8.yml

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+name: flake8
+
+on:
+   push:
+     branches:
+       - main
+   pull_request:
+     branches:
+       - main
+
+jobs:
+  flake8:
+
+    runs-on: ubuntu-latest
+
+    steps:
+    - uses: actions/checkout@v2
+
+    - name: Set up Python 3.9
+      uses: actions/setup-python@v1
+      with:
+        python-version: 3.9
+
+    - name: Install dependencies
+      run: |
+        pip install --upgrade pip
+        pip install flake8
+
+    - name: Lint with flake8
+      run: |
+        flake8 .

.github/workflows/pytest.yml

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+name: pytest-unit-tests
+
+on: [push]
+
+jobs:
+  pytest:
+    name: ${{ matrix.name }}
+    runs-on: "${{ matrix.os }}"
+
+    strategy:
+      matrix:
+        name: [
+           python38-ubuntu2204,
+           python39-ubuntu2204,
+           python310-ubuntu2204
+        ]
+        include:
+
+        - name: python38-ubuntu2204
+          python-version: 3.8
+          os: ubuntu-22.04
+
+        - name: python39-ubuntu2204
+          python-version: 3.9
+          os: ubuntu-22.04
+
+        - name: python310-ubuntu2204
+          python-version: '3.10'
+          os: ubuntu-22.04
+
+    steps:
+    - name: Checkout lung_cancer
+      uses: actions/checkout@v2
+
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@v4
+      with:
+        python-version: ${{ matrix.python-version }}
+
+    - name: Install dependencies
+      run: |
+        pip install --upgrade pip
+        pip install -e .
+        pip install -r requirements.txt
+
+    - name: Test with pytest
+      run: |
+        pytest tests/

.gitignore

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+# Ignore data
+data/raw/*
+!data/raw/.gitkeep
+data/preprocessed/*
+!data/preprocessed/.gitkeep
+
+# ignore pipelines
+pipelines/*
+!pipelines/.gitkeep
+!pipelines/README.md
+
+.DS_Store
+
+# the following code is used from:
+# https://github.com/github/gitignore/blob/main/Python.gitignore
+
+# Byte-compiled / optimized / DLL files
+__pycache__/
+*.py[cod]
+*$py.class
+
+# C extensions
+*.so
+
+# Distribution / packaging
+.Python
+build/
+develop-eggs/
+dist/
+downloads/
+eggs/
+.eggs/
+lib/
+lib64/
+parts/
+sdist/
+var/
+wheels/
+share/python-wheels/
+*.egg-info/
+.installed.cfg
+*.egg
+MANIFEST
+
+# PyInstaller
+#  Usually these files are written by a python script from a template
+#  before PyInstaller builds the exe, so as to inject date/other infos into it.
+*.manifest
+*.spec
+
+# Installer logs
+pip-log.txt
+pip-delete-this-directory.txt
+
+# Unit test / coverage reports
+htmlcov/
+.tox/
+.nox/
+.coverage
+.coverage.*
+.cache
+nosetests.xml
+coverage.xml
+*.cover
+*.py,cover
+.hypothesis/
+.pytest_cache/
+cover/
+
+# Sphinx documentation
+docs/_build/
+
+# Jupyter Notebook
+.ipynb_checkpoints
+
+# IPython
+profile_default/
+ipython_config.py
+
+__pypackages__/
+
+# Environments
+.env
+.venv
+env/
+venv/
+ENV/
+env.bak/
+venv.bak/

README.md

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+Timothy Geiger, acse-tfg22
+
+# Lung Cancer Drug Prediction Project
+
+This repository contains the implementation of a quantum model for predicting the reponse of lung cancer patients to drugs (TKIs). The dataset is provided by the Taipei Medical University (TMU) and includes medical details such as medical history, pathological information, genetic makeup, history of therapeutic interventions, and laboratory data like the white blood cell count. In addition to medical-specific details, the dataset also includes personal information about a patient like demographic factors, as well as insights into the patient’s personal history, e.g. smoking and drinking habits. The target variable can be one of two states: positive response to the drug or a negative response. The project focuses on the following key aspects:
+
+- The preprocessing of the dataset.
+- The development of a classical model to predict the drug response. A neural network and a random forest classifier were used as the classical methods.
+- Development of a quantum model to predict the drug response of lung cancer patients to TKIs. A quantum neural network (QNN) was chosen as the quantum model.
+- Comparison between the quantum model and classical models.
+- Development of an eXplainable Artificial Intelligence (XAI) method for the quantum model.
+
+
+## Folder Structure
+
+1. **Python Package** (`lung_cancer`):
+   - Contains classes and methods to simplify the visualization of complex plots.
+   - Provides a data wrapper to handle data preprocessing, addressing the differing data formats required by qiskit and PyTorch.
+   - Includes classifier wrappers with additional methods like live plotting and cross-validation.
+
+<br>
+
+2. **Notebooks** (`notebooks`):
+   - Includes the developed python package.
+   - Handles the preprocessing of the dataset.
+   - Used for the model development of the classical and the quantum model.
+   - Shows a new approach that combines XAI and quantum machine learning.
+
+<br>
+
+3. **Pipelines** (`pipelines`):
+   - Contains preprocessing pipelines for both the quantum and classical models.
+   - Instructions in the `pipelines` folder's README guide how to obtain the pipelines.
+
+<br>
+
+4. **Data** (`data`):
+   - Contains the data provided by TMU for the project.
+   - Due to privacy concerns, sensitive data is not included in this GitHub repository, in accordance with ethical principles.
+
+<br>
+
+5. **Documentation** (`docs`):
+   - This directory contains a comprehensive documentation for this project.
+   - A pre-generated PDF version is already included.
+   - Instructions in the README within the `docs` directory explains how to generate a HTML documentation or create a new PDF version if needed.
+
+<br>
+
+6. **Tests** (`tests`):
+   - Contains unit tests for the Python package, covering 100% of its functionality.
+
+<br>
+
+7. **Workflows** (`.github/workflows`):
+   - Contains GitHub Actions workflows.
+   - These workflows automate testing, flake8 checks, and compatibility tests on various Python and Linux versions.
+
+<br>
+
+8. **Environment Setup**:
+   - The `requirements.txt` file lists all necessary packages and their versions for running the package and notebooks.
+   - The `environment.yml` file can be used to create an Anaconda environment using the packages from `requirements.txt`.
+
+<br>
+
+Please refer to the other README files in the subfolders for more informations.
+
+## Getting Started
+
+To use the package, follow these steps:
+
+1. Create a conda environment using.
+    ```shell
+    $ conda env create -f environment.yml
+    ```
+
+<br>
+
+2. Activate the created enviroment.
+    ```shell
+    $ conda activate irp-tfg
+    ```
+
+<br>
+
+3. Install the developed python package using.
+    ```shell
+    $ pip install -e .
+    ```

data/README.MD

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+# Data
+
+This folder contains two sub folders: **raw** and **preprocessed**. The original data should be placed into the raw folder. After that the preprocessing notebooks can be executed. After executing each notebook a new file will be generated in the preprocessed folder for each notebook. However, due to storage constraints and privacy, the data will not be uploaded to GitHub.

docs/Makefile

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+# Minimal makefile for Sphinx documentation
+#
+
+# You can set these variables from the command line, and also
+# from the environment for the first two.
+SPHINXOPTS    ?=
+SPHINXBUILD   ?= sphinx-build
+SOURCEDIR     = source
+BUILDDIR      = build
+
+# Put it first so that "make" without argument is like "make help".
+help:
+	@$(SPHINXBUILD) -M help "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)
+
+.PHONY: help Makefile
+
+# Catch-all target: route all unknown targets to Sphinx using the new
+# "make mode" option.  $(O) is meant as a shortcut for $(SPHINXOPTS).
+%: Makefile
+	@$(SPHINXBUILD) -M $@ "$(SOURCEDIR)" "$(BUILDDIR)" $(SPHINXOPTS) $(O)

docs/README.MD

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+# Documentation
+
+This folder contains the PDF documentation. In order to regenerate this documentation again follow the following commands:
+
+1. Create and activate the environment.
+
+    ```shell
+    $ conda env create -f environment.yml
+    $ conda activate irp-tfg
+    $ pip install -e .
+    ```
+
+<br>
+
+2. Navigate to this folder:
+    ```shell
+    $ cd docs
+    ```
+
+<br>
+
+3. Create a build folder if it does not yet exists:
+    ```shell
+    $ mkdir build
+    ```
+
+<br>
+
+4. Generate the HTML documentation:
+
+    ```shell
+    $ sphinx-build -b html source build/html/
+    ```
+
+<br>
+
+5. Generate the PDF documentation:
+
+    ```shell
+    $ sphinx-build -b latex source build/latex/
+    ```
+
+<br>
+
+6. Navigate to this folder:
+
+    ```shell
+    $ cd build/latex
+    ```
+
+<br>
+
+7. Generate the PDF documentation:
+
+    ```shell
+    $ make
+    ```

docs/make.bat

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+@ECHO OFF
+
+pushd %~dp0
+
+REM Command file for Sphinx documentation
+
+if "%SPHINXBUILD%" == "" (
+	set SPHINXBUILD=sphinx-build
+)
+set SOURCEDIR=source
+set BUILDDIR=build
+
+%SPHINXBUILD% >NUL 2>NUL
+if errorlevel 9009 (
+	echo.
+	echo.The 'sphinx-build' command was not found. Make sure you have Sphinx
+	echo.installed, then set the SPHINXBUILD environment variable to point
+	echo.to the full path of the 'sphinx-build' executable. Alternatively you
+	echo.may add the Sphinx directory to PATH.
+	echo.
+	echo.If you don't have Sphinx installed, grab it from
+	echo.https://www.sphinx-doc.org/
+	exit /b 1
+)
+
+if "%1" == "" goto help
+
+%SPHINXBUILD% -M %1 %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
+goto end
+
+:help
+%SPHINXBUILD% -M help %SOURCEDIR% %BUILDDIR% %SPHINXOPTS% %O%
+
+:end
+popd