nreusse

diff --git a/config.h b/config.h
index 8cb8804..b1be9e2 100644
--- a/config.h
+++ b/config.h
@@ -5,8 +5,8 @@
  *
  * font: see http://freedesktop.org/software/fontconfig/fontconfig-user.html
  */
-static char font[] = "Liberation Mono:pixelsize=12:antialias=false:autohint=false";
-static int borderpx = 2;

russelldavies

// Run in the JavaScript console of the hterm browser window

// Clear all existing settings - you probably don't want to do this.
// Preferences are now stored in "chrome.storage.sync" instead of
// "window.localStorage" so if you clear your preferences the changes
// will be propagated to other devices.
//term_.prefs_.storage.clear();


var htermProfiles = [

gjkerns

# Condorcet

Votes <- read.csv("Votes.csv")

candidates <- names(Votes)
nvoters <- dim(Votes)[1]
ncand <- dim(Votes)[2]

allpairs <- combn(1:ncand, 2)

audreyfeldroy

• Update HISTORY.md
• Commit the changes:

git add HISTORY.md
git commit -m "Changelog for upcoming release 0.1.1."

• Update version number (can also be minor or major)

bumpversion patch

amitsaha

# README:
# Copy this file to /usr/lib/systemd/system/
# sudo systemctl daemon-reload
# systemctl enable ipython-notebook 
# systemctl start ipython-notebook
# The WorkingDirectory and ipython-dir must exist
# If you don't want anything fancy, go to http://127.0.0.1:8888 to see your notebook
# wheneber you want it

[Unit]

romainfrancois

x = <0x1038ff8a0>, dataptr = <0x1038ff8c8>
x = <0x1038ff8a0>, dataptr = <0x1038ff8c8>
x = <0x1038ff8a0>, dataptr = <0x1038ff8c8>
x = <0x1038ff8a0>, dataptr = <0x1038ff8c8>
x = <0x1038ff8a0>, dataptr = <0x1038ff8c8>
x = <0x1038ff8a0>, dataptr = <0x1038ff8c8>
x = <0x1038ff8a0>, dataptr = <0x1038ff8c8>
x = <0x1038ff8a0>, dataptr = <0x1038ff8c8>
x = <0x1038ff8a0>, dataptr = <0x1038ff8c8>
x = <0x1038ff8a0>, dataptr = <0x1038ff8c8>

mwhite

"""
Outputs history with bash and git aliases expanded.
"""
from __future__ import print_function

import re
from subprocess import check_output

BASH_ALIASES = {}
for line in check_output('bash -i -c "alias -p"', shell=True).split('\n'):

shunsukeaihara

# -*- coding: utf-8 -*-
import numpy as np
import math


def LevinsonDurbin(r, lpcOrder):
    """
    from http://aidiary.hatenablog.com/entry/20120415/1334458954
    """
    a = np.zeros(lpcOrder + 1,dtype=np.float64)

debasishg

General Background and Overview

1. Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
2. Models and Issues in Data Stream Systems
3. Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
4. Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
5. [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t

XVilka

THIS GIST WAS MOVED TO TERMSTANDARD/COLORS REPOSITORY.

PLEASE ASK YOUR QUESTIONS OR ADD ANY SUGGESTIONS AS A REPOSITORY ISSUES OR PULL REQUESTS INSTEAD!