Akramz

Akramz

from __future__ import division
import numpy as np 
import pandas as pd
from keras.optimizers import rmsprop
from keras.models import model_from_json
from params import *
from datetime import datetime
from datetime import date, timedelta
import csv
import sqlite3

Akramz

# INIT
temp_mean     = {} 
humidity_mean = {}
wind_mean     = {}
temp_max      = {}
temp_min      = {}
humidity_max  = {}
humidity_min  = {}
wind_max      = {}
wind_min      = {}

Akramz

import sys
sys.path.insert(0, '/var/www/html/nuweth')

from nuapp import app as application

Akramz

from __future__ import division
import pandas as pd
import numpy as np 
import requests
import time
import os.path
from datetime import date, timedelta
from subprocess import call
import csv
import sqlite3

Akramz

import os
import csv
import sqlite3
import numpy as np
import pandas as pd
from flask import Flask,render_template
from flask import request, g
from flask import jsonify
from collections import Counter

Akramz

#include <mpi.h>
#include <math.h>
#include <stdio.h>

float fct(float x)
{
      return (x/sin(x))*(x/sin(x));
}

float integral(float a, int n, float h);

Akramz

#include "mpi.h"
#include <stdio.h>
#include <math.h>

double f( double );
double f( double a )
{
    return (4.0 / (1.0 + a*a));
}

Akramz

#include <mpi.h>
#include <math.h>
#include <stdio.h>

float integral(float a, int n, float h);

void main(argc,argv)
int argc;
char *argv[];
{

Akramz

import pandas as pd 
import numpy as np 
from sys import exit

data = pd.read_csv('../../data/train.csv', sep=',')
train = data[['Address']]

train = train.loc[train['Address'].str.contains(' / ')]
train['count'] = 1
train = train.groupby('Address').sum().reset_index()