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AmpScan

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    Joshua Steer authored
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    AmpScan

    AmpScan is an open-source Python package for analysis and visualisation of digitised surface scan data, specifically for applications within Prosthetics and Orthotics. These industries are increasingly using surface scanners as part of clinical practice to capture the patient's individual geometry to design personalised devices. AmpScan gives researchers within this field access to powerful tools to analyse the collected scans to help inform clinical practice towards improved patient-outcomes. This package has been designed to be accessible for researchers with only a limited knowledge of Python. Therefore, analysis procedures can all be accessed using the lightweight Graphical User Interface.

    AmpScan relies heavily on NumPy and SciPy to perform mathematical operations with visualisation handled by PyQt and VTK. The package is still under development by researchers at the University of Southampton. For full documentation, visit the AmpScan website.

    Installing with Conda (Recommended)

    AmpScan has a number of dependencies, namely; NumPy, SciPy, Matplotlib, PyQt and vtk. We recommend using conda to deal with these. Before installation, ensure your environment is using Python 3. Verify that you are running the latest version of pip:

    python -m pip install --upgrade pip

    Install dependencies using conda:

    conda install numpy scipy pyqt matplotlib vtk==8.1.0

    Install AmpScan using pip:

    pip install AmpScan

    Installing with Pip

    AmpScan has a number of dependencies, namely; NumPy, SciPy, Matplotlib, PyQt and vtk. Before installing, ensure you have the latest version of pip:

    python -m pip install --upgrade pip

    Then install the dependencies using:

    pip install numpy matplotlib scipy pyqt5 vtk==8.1.0

    You can then install AmpScan from test PyPI using:

    pip install AmpScan

    Developer Install

    For the most up to date version of AmpScan, clone directly from the gitlab repository using:

    git clone https://git.soton.ac.uk/js22g12/AmpScan.git

    Navigate to the AmpScan/ directory and run a pip install using:

    pip install -e .

    Maintainer Notes

    Documentation for the AmpScan library is automatically generated using sphinx. Any additional code should be documented in accordance with 'numpy style' docstrings. A template can be found here.

    How to acknowledge

    Find license here