https://github.com/esss/notebooks
This repo contains notebooks that explaining some cool stuff we learn every now and then...
https://github.com/esss/notebooks
ipynb
Last synced: 8 months ago
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This repo contains notebooks that explaining some cool stuff we learn every now and then...
- Host: GitHub
- URL: https://github.com/esss/notebooks
- Owner: ESSS
- License: mit
- Created: 2017-05-09T13:49:12.000Z (about 9 years ago)
- Default Branch: master
- Last Pushed: 2020-11-26T10:25:40.000Z (over 5 years ago)
- Last Synced: 2025-02-01T10:41:36.131Z (over 1 year ago)
- Topics: ipynb
- Language: Jupyter Notebook
- Homepage:
- Size: 712 KB
- Stars: 19
- Watchers: 18
- Forks: 3
- Open Issues: 0
-
Metadata Files:
- Readme: README.rst
- License: LICENSE
Awesome Lists containing this project
README
.. image:: https://mybinder.org/badge_logo.svg
:target: https://mybinder.org/v2/gh/ESSS/notebooks/master
notebooks
=========
This repo contains notebooks that explaining some cool stuff we learn every now and then.
Index
-----
* `Bounding Velocities `_: no description.
* `Creating block matrix structures using numpy and scipy `_: This notebook intends to provide a consistent way to create a block matrix structure from a simplified non-block matrix structure..
* `Einstein Summation `_: Einstein Summation.
* `Interpolate point cloud into structured grid `_: Interpolate point cloud into structured grid.
* `Smooth transition between analytic functions `_: Create a smooth transition in a place where a function is discontinuous.
* `Test Write Strategy `_: A simple test that emulates a simulation loop and write raw numpy data and an HDF5 file to compare sizes and times to output a large amount of data.
* `Accumulative Sum Benchmark `_: a comparison between different implementations to deal with accumulative sum using Python native loops, numpy.cumsum and sci20 Array.
* `Eigen Broadcast Cheatsheet `_: examples of how to do some not-so-simple broadcasting using Eigen. Check accompanying `Numpy version `_.
How to run
----------
1. Install `miniconda`
2. Install `nbformat` in the root environment: `conda install -n root nbformat`
3. Create an environment to run `jupyter notebook`: type `conda env create` in the root directory of this project (or `conda env update` if the `notebooks` environment was already created previously)
4. Activate the environment: type `activate notebooks` (Windows) or `source activate notebooks` (Unix)
5. Run and open it: `jupyter notebook`