ihsansatriawan

ihsansatriawan

#add 'node_modules' to .gitignore file

git rm -r --cached node_modules
git commit -m 'Remove the now ignored directory node_modules'
git push origin master

ihsansatriawan

look process:
`lsof -i :<PORT NUMBER>
kill process
`kill -9 <PID>`

ihsansatriawan

tmux shortcuts & cheatsheet

start new:

tmux

start new with session name:

tmux new -s myname

ihsansatriawan

git branch -d branch_name #local
git push origin --delete <branch_name>

ihsansatriawan

http://stackoverflow.com/questions/927358/how-to-undo-last-commits-in-git
http://askubuntu.com/questions/97936/terminal-command-to-set-audio-volume
http://utahcon.com/i3-config-and-xev/
http://www.ninjaducks.in/hacking/gnome-3-to-i-3/
http://blog.tunnelshade.in/2014/05/making-i3-beautiful.html
http://stackoverflow.com/questions/4241211/how-do-i-convert-an-activerecord-result-array-to-a-normal-array
http://stackoverflow.com/questions/942543/operation-on-every-pair-of-element-in-a-list
http://askubuntu.com/questions/40126/how-to-copy-paste-a-table-from-libreoffice-calc-to-libreoffice-writer
https://ask.libreoffice.org/en/question/21286/change-page-numbering-in-the-content-field/
http://imron02.blogspot.co.id/2012/04/penomoran-halaman-pada-libreoffice.html

ihsansatriawan

#!/bin/sh
# Git pre-commit hook to check all staged Ruby (*.rb/haml/coffee) files 
# for Pry binding references
#
# Installation
#
#   ln -s /path/to/pre-commit.sh /path/to/project/.git/hooks/pre-commit
#   chmod +x pre-commit
#
# Based on 

ihsansatriawan

class ClusteringQuality:
    """
    Instances of this class implement the two measures of clustering quality discussed in the article, namely the davies
    bouldin index and the silhouette index. It also implements a number of useful helper methods.
    :param solution: the clustering solution of type Clustering
    :param minimum: the minimum distance allowable
    """

    def __init__(self, solution, minimum):
        """

ihsansatriawan

import math
import random
import csv
import cProfile
import numpy as np
import hashlib

memoization = {}

ihsansatriawan

# Importing the libraries
from scipy.stats.stats import pearsonr
import pandas as pd
import numpy as np
import json

data = pd.read_csv("../../Downloads/data_books.csv", sep = ",", header=None,
                         names=['Reviewer', 'Book', 'Rating'])

# Picking 2 books