helper.py

import sys
import matplotlib.pyplot as plt

''' This function takes in a set of x-values, y-values
    a starting x-value and starting y-value. The function
    then aproximates the derivative over the  set of data
    and then returns the y-values. '''
def derivative(x,y,start,end):
    y_prime = []
    prevX = start
    prevY = end
    for i in range(0,len(x)):
        delta_x = x[i] - prevX
        delta_y = y[i] - prevY
        if (delta_x == 0):
            delta_x = 1
        y_prime.append(delta_y/delta_x)
        prevX = x[i]
        prevY = y[i]
    return y_prime

''' This function just takes in a "Data" dictionary that
    contains all of the necessary info to properly plot a
    graph in mathplotlib. '''
def plotData(Data):
    plt.plot([day for day in range(0,Data["days"])], Data["data"])  
    plt.title(Data["title"])  
    # naming the x axis 
    plt.xlabel(Data["xlabel"]) 
    # naming the y axis 
    plt.ylabel(Data["ylabel"])    


    # function to show the plot 
    plt.show() 


''' This function is used to create a progress bar when fetching
    the data '''
def progressbar(it, prefix="", size=60, file=sys.stdout):
    count = len(it)
    def show(j):
        x = int(size*j/count)
        file.write("%s[%s%s] %i/%i\r" % (prefix, "#"*x, "."*(size-x), j, count))
        file.flush()        
    show(0)
    for i, item in enumerate(it):
        yield item
        show(i+1)
    file.write("\n")
    file.flush()

''' Turns a row into a csv 'ready-to-write' string'''
def csvify(row):
    f = []
    for ele in row:
        f.append(ele)
        f.append(",")
    f = f[:len(f)-2]
    f.append('\n')
    return ''.join(f)