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#!/bin/bash
# Get the scope of given class in a given file
# Then show the evelution of the class via git log -L
# usage: show_scope [classname] [filename]
# cname='class HttpAuthHandler'
# fname='HttpAuthHandler.java'

cname=$1
fname=$2
begin=$(grep -n ".*$cname.*" $fname | grep -Eo "^[0-9]{1,5}")

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import numpy as np
import scipy as sc
import networkx as nx
from matplotlib.colors import LogNorm
from pylab import *


def sample(n):
    m = sc.misc.comb(n, 2)
    r_vals = np.random.random(m)

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CREATE KEYSPACE unittest WITH REPLICATION = { 'class' : 'SimpleStrategy', 'replication_factor' : 1 };

USE unittest;

CREATE TABLE commits (
id text,
path text,
author_email text,
author_name text,
subject text,

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from pylab import *
import pandas as pd


df =pd.read_csv("PS04_1a.dat", names=range(1,35))
p1 = pd.DataFrame({'max': df.max(), 'mean':df.mean()})
p1.plot(marker='.', markersize=10, title='')

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2	1
3	1
3	2
4	1
4	2
4	3
5	1
6	1
7	1
7	5

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authors=(`git log --format='%ae' | sort -u`)
for author in ${author[*]}
do
files=(`git log --no-merges --stat --author="$author" --name-only --pretty=format:"" | sort -u`)
for file in ${files[*]}
do
echo $author $file
done
done

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words1 = "pa’Daq ghah taH tera’ngan ’e".replace("’","'").split()
tags1 = "N PRO V N PRO".split()

words2 = "ja’chuqmeH rojHom neH tera’ngan".replace("’","'").split()
tags2 = "V N V N".split()

words3 = "tera’ngan qIp puq ’eg puq qIp tera’ngan".replace("’","'").split()
tags3 = "N V N CONJ N V N".split()

train = []

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from collections import defaultdict
from nltk.corpus import brown

print ">>> Procssing"
word_tag = defaultdict(set)
for word, tag in brown.tagged_words():
    word_tag[word].add(tag)

num_words_by_num_tags = defaultdict(int)
words_with_max_tags = [None, 0]

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import csv

with open('ps03-4.csv','rb') as file:
    contents = csv.reader(file)
    matrix = list()
    for row in contents:
        matrix.append(row)

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# origin: http://stackoverflow.com/questions/24662006/python-networkx-graph-different-colored-nodes-using-two-lists
## assign a node attribute, which I am going to color according to
for node in G.nodes():
    G.node[node]['category'] = my_category_dict[node]
## put together a color map, one color for a category
color_map = {'type_A':'b', 'type_B':'#FF0099', 'type_C':'#660066'} 
## construct a list of colors then pass to node_color
nx.draw(G, node_color=[color_map[G.node[node]['category']] for node in G])
plt.show()