isaacs

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

huyng

### 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).

GaelVaroquaux

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

jacobian

#!/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]

minrk

#!/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).

minrk

#!/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

jonathan-taylor

"""
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

pprett

{"error": 42716.2954, "samples": 506, "value": [22.532806324110698], "label": "RM <= 6.94", "type": "split", "children": [{"error": 17317.3210, "samples": 430, "value": [19.93372093023257], "label": "LSTAT <= 14.40", "type": "split", "children": [{"error": 6632.2175, "samples": 255, "value": [23.349803921568636], "label": "DIS <= 1.38", "type": "split", "children": [{"error": 390.7280, "samples": 5, "value": [45.58], "label": "CRIM <= 10.59", "type": "split", "children": [{"error": 0.0000, "samples": 4, "value": [50.0], "label": "Leaf - 4", "type": "leaf"}, {"error": 0.0000, "samples": 1, "value": [27.9], "label": "Leaf - 5", "type": "leaf"}]}, {"error": 3721.1632, "samples": 250, "value": [22.90520000000001], "label": "RM <= 6.54", "type": "split", "children": [{"error": 1636.0675, "samples": 195, "value": [21.629743589743576], "label": "LSTAT <= 7.57", "type": "split", "children": [{"error": 129.6307, "samples": 43, "value": [23.969767441860473], "label": "TAX <= 222.50", "type": "split", "children": [{"err

mbostock

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

ChrisBeaumont

"""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'