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application.py
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/
application.py
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import numpy as np
import pandas as pd
import csv
import io
from sklearn.model_selection import train_test_split
from werkzeug import *
from flask import Flask, render_template, request, redirect, url_for, make_response
''' Import from Otis repo '''
from Network import *
nerual = Network
app = Flask(__name__)
@app.route('/')
def homepage():
return render_template('home.html', title='Home')
@app.route('/data', methods=['POST'])
def getinfo():
data = []
result = request.form
f = request.files['data_file']
stream = io.StringIO(f.stream.read().decode("UTF8"), newline=None)
data = pd.read_csv(stream)
'''Get user specs from form'''
output = result['output']
output = int(output)
'''Separate input data from output data'''
outdata = data.iloc[:, output - 1:output]
indata = data.drop(data.columns[output - 1], axis=1)
'''Testing purposes to ensure data is placed correctly'''
'''Further separation of daata file'''
#inTrain, inTest, outTrain, outTest = train_test_split(indata, outdata, test_size=0.3, random_state=101)
# print(inTrain)
# print(inTest)
# print(outTrain)
# print(outTest)
inTest = indata.tail(1)
outTest = outdata.tail(1)
inTrain = indata[:-1]
outTrain = outdata[:-1]
'''Train data'''
neural = Network(inTrain.values, outTrain.values)
Network.train(neural, 1000)
outputList = pd.DataFrame(Network.run(neural, inTest))
return render_template("view.html", tables=[inTest.to_html(classes='intext'), outTest.to_html(classes='outTest'),outputList.to_html(classes='outTest')],titles = ['na','IN','OUT','OTIS'])
if __name__ == '__main__':
app.run(debug=True)