def trainData():
target = list()
input = ps.parse()
featWrds = loadFeatureFromFile('tester.txt')
twtCounter = 0
x = list()
for tweet in input:
twtCounter = twtCounter + 1
target.append(tweet.pop(-1))
featNum = []
counter = 0
for wrd in featWrds:
if wrd in tweet:
featNum.append(1)
else:
featNum.append(0)
counter = counter + 1
x.append(featNum)
#print x
model.fit(x, target)
givenAnswer = model.predict(x)
listToSum = abs(givenAnswer - target)
print sum(givenAnswer)
print twtCounter
def onlyOnInit():
st = LancasterStemmer()
yes = dict()
no = dict()
(yes,no) = loadWordsFromFile('tester.txt')
valText = ps.parse()
stemmedWordList = []
#for each tweet, manipulate dictionary (part of training)
for row in valText:
#pop V bit from end of row
V = row.pop(-1)
filtered_words = [w for w in row if not w in stopwords.words('english')]
#print "stemmed" + str([w for w in row if w in stopwords.words('english')])
for word in filtered_words:
#if the key does not exist in the dictionary, add it with 1 weight
try:
prevWord = word
word = st.stem(str(word))
word = str(word)
if yes.get(word, 'none') == 'none':
if(V==1):
yes[word] = 1
no[word] = 0
else:
yes[word] = 0
no[word] = 1
else:
if(V==1):
yes[word] += 1
#print words[word]
else:
no[word] += 1
except:
print "Exception " + str(prevWord)
storeWordsToFile(yes, no,'tester.txt')
import motor
import threading
import subprocess
import random
import time
import os
import parseFile
import xlsxwriter
import openpyxl
from openpyxl.chart import *
import serial
define("port", default=8000, help="run on the given port", type=int)
cwd = os.getcwd() # used by static file server
print("Current Working directory :" + cwd)
parseFile.parse()
temperature = []
light = []
voltage = []
current = []
timestamp = []
class IndexPageHandler(RequestHandler):
"""
index page
"""
@gen.coroutine
def get(self, *args, **kwargs):
self.set_header('Content-Type', 'html')
self.set_header("Access-Control-Allow-Origin", "*")