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# HVC_paper | ||
1. Contents | ||
------------------- | ||
This package contains the raw data files as well as source code required for | ||
the analysis. In case of questions or difficulties running the code, please contact | ||
[email protected] | ||
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Updates regarding data and code will be made available on | ||
https://github.com/jmrk84/HVC_paper | ||
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2. Provided data | ||
------------------- | ||
2.1 Registered raw EM dataset | ||
A streaming configuration file is provided for KNOSSOS (www.knossostool.org) that can be used | ||
to easily access all image data and perform your own tracings in the dataset. If the hosting source | ||
changes, an updated streaming configuration file will be provided on github. | ||
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The configuration file can also be used together with the knossosDataset class provided | ||
in the public knossos_utils package to directly work with the dataset (e.g. download it, convert | ||
to an image stack, etc). | ||
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2.2 Skeleton files | ||
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3. Source code | ||
------------------- | ||
3.1 License | ||
All source code is licensed under the GPL v2 license. | ||
Copyright, J. Kornfeld, Max Planck Society | ||
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3.2 Dependencies | ||
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The provided Python source code requires some additional libraries to be installed to run. | ||
* knossos_utils (see https://github.com/knossos-project/knossos_utils for installation | ||
instructions) | ||
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* numpy (pip install numpy) | ||
* matplotlib (pip install matplotlib) | ||
* networkx (pip install networkx) | ||
* pandas (pip install pandas) | ||
* mayavi (pip install mayavi) | ||
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All pip-installable libraries come with anaconda, it is therefore advised to install the | ||
anaconda Python distribution. |