Stephen Mayhew mayhewsw

## convertD3graph.js
// almost d3-style graph
var graph = {"nodes" : [
      {"name":"somenode"},
      {"name":"somenewnode"}
    ],
    "links":[
      {"source":"somenode", "target":"somenewnode"}
    ]
};

## index.html
<html>
  <head>
    <title>Put stuff here</title>

  </head>
  <body>
    <h2>This is my block/gist!</h2>
    <div id="putstuffhere"></div>
    <script src="https://cdnjs.cloudflare.com/ajax/libs/d3/3.5.5/d3.min.js"></script>
    <script>

## README.md

      
              3 files
            
          
              0 forks
            
          
              0 comments
            
          
              0 stars
            
          
                mayhewsw
                / README.md
            
            
              Created
              August 1, 2015 20:21
            
          
    cs-shirt.txt is from the UIUC CS shirt. The binary digits are shaped to form a big I. The cs-shirt.py translates the shirt into text.

  
## nospaces.py
import sys

if len(sys.argv) != 2:
	print "Usage: python nospaces.py <inputfile>"
	exit()

infile = sys.argv[1]

print "Removing the spaces from " + infile + "..."

## FeatureWeightCalculator.java
package edu.illinois.cs.cogcomp.tutorial;

import edu.illinois.cs.cogcomp.lbjava.learn.Lexicon;
import edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner;

import java.io.ByteArrayOutputStream;
import java.io.PrintStream;
import java.util.*;
import java.util.stream.Stream;

## makeall.sh
#!/bin/sh
for f in *.xml.gz; do
    if [ $f == "English.xml.gz" ] ; then
        continue;
    fi

    python makeplaintext.py $f English.xml.gz;
done

## getlist.py
#!/usr/bin/python
from bs4 import BeautifulSoup

# use url: http://unicode.org/iso15924/iso15924-codes.html

with open("iso15924list.html") as f:
    html_doc = f.read()

soup = BeautifulSoup(html_doc, 'html.parser')

## plotcm.py
import numpy as np
import matplotlib.pyplot as plt
import matplotlib as mpl
import matplotlib.patches as patches

mpl.rcParams['font.family'] = "Times New Roman"
#mpl.rcParams['font.size'] = "11"
mpl.rc('pdf', fonttype=42)


## editdist.py
import numpy as np
import math
import sys

np.set_printoptions(linewidth=400)

def EditDistance(s, t):
  # For all i and j, d[i,j] will hold the Levenshtein distance between
  # the first i characters of s and the first j characters of t.
  # Note that d has (m+1)  x(n+1) values.

## cgm.py
from __future__ import division
import numpy as np

Q = [[3, -1], [-1, 3]]
b = [1,0]

x = [1,1]

d = []
r = []
	// almost d3-style graph
	var graph = {"nodes" : [
	{"name":"somenode"},
	{"name":"somenewnode"}
	],
	"links":[
	{"source":"somenode", "target":"somenewnode"}
	]
	};
	<html>
	<head>
	<title>Put stuff here</title>

	</head>
	<body>
	<h2>This is my block/gist!</h2>
	<div id="putstuffhere"></div>
	<script src="https://cdnjs.cloudflare.com/ajax/libs/d3/3.5.5/d3.min.js"></script>
	<script>
	import sys

	if len(sys.argv) != 2:
	print "Usage: python nospaces.py <inputfile>"
	exit()

	infile = sys.argv[1]

	print "Removing the spaces from " + infile + "..."
	package edu.illinois.cs.cogcomp.tutorial;

	import edu.illinois.cs.cogcomp.lbjava.learn.Lexicon;
	import edu.illinois.cs.cogcomp.lbjava.learn.SparseNetworkLearner;

	import java.io.ByteArrayOutputStream;
	import java.io.PrintStream;
	import java.util.*;
	import java.util.stream.Stream;
	#!/bin/sh
	for f in *.xml.gz; do
	if [ $f == "English.xml.gz" ] ; then
	continue;
	fi

	python makeplaintext.py $f English.xml.gz;
	done
	#!/usr/bin/python
	from bs4 import BeautifulSoup

	# use url: http://unicode.org/iso15924/iso15924-codes.html

	with open("iso15924list.html") as f:
	html_doc = f.read()

	soup = BeautifulSoup(html_doc, 'html.parser')
	import numpy as np
	import matplotlib.pyplot as plt
	import matplotlib as mpl
	import matplotlib.patches as patches

	mpl.rcParams['font.family'] = "Times New Roman"
	#mpl.rcParams['font.size'] = "11"
	mpl.rc('pdf', fonttype=42)
	import numpy as np
	import math
	import sys

	np.set_printoptions(linewidth=400)

	def EditDistance(s, t):
	# For all i and j, d[i,j] will hold the Levenshtein distance between
	# the first i characters of s and the first j characters of t.
	# Note that d has (m+1) x(n+1) values.
	from __future__ import division
	import numpy as np

	Q = [[3, -1], [-1, 3]]
	b = [1,0]

	x = [1,1]

	d = []
	r = []