https://github.com/jni/numpy-skimage-tutorial

A quick tutorial of NumPy and scikit-image for the COMBINE Python workshop, 2014-11-27
https://github.com/jni/numpy-skimage-tutorial

Last synced: 12 days ago
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A quick tutorial of NumPy and scikit-image for the COMBINE Python workshop, 2014-11-27

• Host: GitHub
• URL: https://github.com/jni/numpy-skimage-tutorial
• Owner: jni
• License: bsd-3-clause
• Created: 2014-11-25T12:08:30.000Z (almost 10 years ago)
• Default Branch: master
• Last Pushed: 2014-11-27T08:25:19.000Z (almost 10 years ago)
• Last Synced: 2024-10-17T09:09:40.769Z (about 1 month ago)
• Language: Python
• Size: 8.88 MB
• Stars: 2
• Watchers: 3
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
numpy-skimage-tutorial

======================

A quick tutorial of NumPy and scikit-image for the COMBINE Python workshop,

2014-11-27

## Prerequisites

We will be using the "memory_profiler" module to demonstrate NumPy's memory

advantages. To install it, it's best to create a new conda environment, and

then use "pip":

```

conda create -n tutorial --clone root

source activate tutorial

pip install memory_profiler

```

## Instructions

Make sure you are running the "tutorial" environment created above. If in

doubt, type "source activate tutorial" before starting below:

- Clone this repository.

- cd into the 'notebooks' directory

- run `ipython notebook`

- click on "2014 COMBINE Python Workshop -- NumPy and scikit-image.ipynb"