fdeheeger

Cython example of exposing C-computed arrays in Python without data copies

The goal of this example is to show how an existing C codebase for numerical computing (here c_code.c) can be wrapped in Cython to be exposed in Python.

The meat of the example is that the data is allocated in C, but exposed in Python without a copy using the PyArray_SimpleNewFromData numpy

	echo 'export PATH=$HOME/local/bin:$PATH' >> ~/.bashrc
	. ~/.bashrc
	mkdir ~/local
	mkdir ~/node-latest-install
	cd ~/node-latest-install
	curl http://nodejs.org/dist/node-latest.tar.gz \| tar xz --strip-components=1
	./configure --prefix=~/local
	make install # ok, fine, this step probably takes more than 30 seconds...
	curl https://www.npmjs.org/install.sh \| sh

	### MATPLOTLIBRC FORMAT

	# This is a sample matplotlib configuration file - you can find a copy
	# of it on your system in
	# site-packages/matplotlib/mpl-data/matplotlibrc. If you edit it
	# there, please note that it will be overridden in your next install.
	# If you want to keep a permanent local copy that will not be
	# over-written, place it in HOME/.matplotlib/matplotlibrc (unix/linux
	# like systems) and C:\Documents and Settings\yourname\.matplotlib
	# (win32 systems).

	#!/usr/bin/env python

	"""
	Install a package from your local pip download cache without having to touch
	the 'net at all.

	You'll need to be using a pip download cache; that is, you'll need the
	following in your ~/.pip/pip.cfg:

	[install]

	#!/usr/bin/env python
	"""
	simple example script for running and testing notebooks.

	Usage: `ipnbdoctest.py foo.ipynb [bar.ipynb [...]]`

	Each cell is submitted to the kernel, and the outputs are compared with those stored in the notebook.
	"""
	# License: Public Domain, but credit is nice (Min RK).

	#!/usr/bin/env python
	"""
	simple example script for running notebooks and reporting exceptions.

	Usage: `checkipnb.py foo.ipynb [bar.ipynb [...]]`

	Each cell is submitted to the kernel, and checked for errors.
	"""

	import os,sys,time

	"""
	simple example script for running notebooks and saving the resulting notebook.

	Usage: `execute_and_save.py foo.ipynb [bar.ipynb [...]]`

	Each cell is submitted to the kernel, and the outputs are overwritten and
	stored in new notebooks foo_executed.ipynb, etc.
	"""

	import os,sys,time

	license: gpl-3.0
	border: no
	height: 960
	redirect: https://observablehq.com/@d3/brushable-scatterplot-matrix

	"""From the numba examples
	(https://github.com/numba/numba/blob/master/examples/mandel.py),
	but tweaked to recalculate on the fly as the viewport changes"""
	from numba import autojit
	import numpy as np
	from pylab import imshow, jet, show, ion
	import matplotlib.pyplot as plt
	from matplotlib import rcParams

	rcParams['image.origin'] = 'lower'