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Collection of code, notebooks and documentation for the SInCohMap project

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SInCohMap

Collection of code, notebooks and documentation for the SInCohMap project

Instructions

You can run the notebooks locally (please note: the Anaconda Python enviornment has been tested on Linux Ubuntu 18.04, on Windows it might not work due to different library versions):

  1. Install Anaconda to manage virtual environments. You can follow the instructions here
  2. Clone the repository and get into the repo folder:
git clone https://github.com/SARScripts/SInCohMap
cd SInCohMap
  1. Create a new conda environment with the following command:
conda env create -f environment.yml
  1. Once the process is complete, you can activate the environment:
conda activate sincohmap
  1. Now you can start the Jupyter Notebook Server and use the notebooks, just typing:
jupyter notebook
  1. This should open up a new window in your default web browser, where you can select the notebook you prefer.

Using an existing Jupyter instance

If there is already a Jupyter instance (i.e. the JupyterHub offered by Eurac Research), you can add the kernel from the newly created conda environment without running another one. The necessary additional steps are:

$ conda activate sincohmap
(sincohmap)$ conda install ipykernel
(sincohmap)$ ipython kernel install --user --name=sincohmap
(sincohmap)$ conda deactivate

Source: stackoverflow

Please note: if your console does not recognize the conda command, you need to initialize it before running the previous commands, using: $ conda init bash

Now the new kernel should be available in your Jupyter Lab. To use the new kernel:

  1. Click on the kernel selector in the upper right corner of the page
  2. Select the new kernel
  3. Restart the kernel image

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Collection of code, notebooks and documentation for the SInCohMap project

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