Underscore example:
_.each([1, 2, 3], function(num) { alert(num); });
// It is important to declare your variables. | |
(function() { | |
var foo = 'Hello, world!'; | |
print(foo); //=> Hello, world! | |
})(); | |
// Because if you don't, the become global variables. | |
(function() { |
#!/bin/bash | |
tmup () | |
{ | |
echo -n "Updating to latest tmux environment..."; | |
export IFS=","; | |
for line in $(tmux showenv -t $(tmux display -p "#S") | tr "\n" ","); | |
do | |
if [[ $line == -* ]]; then | |
unset $(echo $line | cut -c2-); |
This is a quick attempt at writing a ball tree for nearest neighbor searches using numba. I've included a pure python version, and a version with numba jit decorators. Because class support in numba is not yet complete, all the code is factored out to stand-alone functions in the numba version. The resulting code produced by numba is about ~10 times slower than the cython ball tree in scikit-learn. My guess is that part of this stems from lack of inlining in numba, while the rest is due to some sort of overhead
#!/usr/bin/env python | |
# -*- coding: utf-8 -*- | |
# extract stay points from a GPS log file | |
# implementation of algorithm in | |
# [1] Q. Li, Y. Zheng, X. Xie, Y. Chen, W. Liu, and W.-Y. Ma, "Mining user similarity based on location history", in Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems, New York, NY, USA, 2008, pp. 34:1--34:10. | |
import time | |
import os | |
import sys |
#!/usr/bin/env python | |
# -*- coding: utf-8 -*- | |
"""Implements Partial Directed Coherence and Direct Transfer Function | |
using MVAR processes. | |
Reference | |
--------- | |
Luiz A. Baccala and Koichi Sameshima. Partial directed coherence: | |
a new concept in neural structure determination. |
from __future__ import division, print_function | |
import numpy as np | |
from scipy import signal | |
import matplotlib.pyplot as plt | |
def plot_response(fs, w, h, title): | |
plt.figure() | |
plt.plot(0.5*fs*w/np.pi, 20*np.log10(np.abs(h))) |
# Example animations using matplotlib's FuncAnimation | |
# Ken Hughes. 18 June 2016. | |
# For more detail, see | |
# https://brushingupscience.wordpress.com/2016/06/21/matplotlib-animations-the-easy-way/ | |
# Examples include | |
# - line plot | |
# - pcolor plot | |
# - scatter plot |
I recently had several days of extremely frustrating experiences with service workers. Here are a few things I've since learned which would have made my life much easier but which isn't particularly obvious from most of the blog posts and videos I've seen.
I'll add to this list over time – suggested additions welcome in the comments or via twitter.com/rich_harris.
Chrome 51 has some pretty wild behaviour related to console.log
in service workers. Canary doesn't, and it has a load of really good service worker related stuff in devtools.
# command: source | |
# Allow autocomplete for conda environments | |
_complete_source_activate_conda(){ | |
if [ ${COMP_WORDS[COMP_CWORD-1]} != "activate" ] | |
then | |
return 0 | |
fi | |
local cur=${COMP_WORDS[COMP_CWORD]} | |
COMPREPLY=($(ls ~/anaconda3/envs | xargs -I dirs bash -c "compgen -W dirs $cur")) |