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A MicroAnalysis Toolkit.

Project description

SMAK3.0

MicroAnalysis Toolkit v3

Installation with Conda

  1. Create a new environment from Anaconda prompt/navigator. Choose 'y' when prompted. conda create -n smakenv python==3.10
  2. Activate the new environment conda activate smakenv
  3. Install package via pip pip install smak
  4. Navigate to the folder within your anaconda environment where smak has been installed. This can be tricky to find.
    • To start, type in PATH (windows) or $PATH (mac). This will provide a list of Anaconda directories. Yours may look something like this: \Username\AppData\Local\anaconda3\envs\smakenv
    • Copy one of the paths from the previous step and navigate to that folder on your computer in finder/file explorer.
    • From the new Anaconda environment folder, navigate to "Lib\site-packages\smak" (windows) or "Lib\site-packages\python 3.10\smak"(mac)
    • Bookmark this folder, you will need to access it frequently

Optional: Segmentation and image registration

To use the full functionality of SMAK, you will need to follow a few additional steps. This is not necessary unless you plan to use segmentation and image registration.

  1. Download the files from the following links. They are quite large and may take a while to download.
  1. Move the files into the main smak folder. This is the folder you found and bookmarked in step 4 of "Installation with Conda".

Running SMAK

  1. Open Anaconda prompt/navigator.
  2. Activate the environment you use to run smak conda activate smakenv
  3. Navigate to the folder within your anaconda environment where smak has been installed. This is the folder you found and bookmarked in step 4 of "Installation with Conda".
  4. Run smak python smak.py

Improvements on this installation process and guide are underway! In the meantime, don't hesitate to reach out to Joy (joy.a.wood@dartmouth.edu) or Sam (samwebb@slac.stanford.edu) for assistance.

Project details


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smak-3.0.1.tar.gz (5.6 MB view hashes)

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smak-3.0.1-py3-none-any.whl (4.4 MB view hashes)

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