import matplotlib.pyplot as plt
import matplotlib.animation as animation
from mpl_toolkits.mplot3d import Axes3D
import time
import numpy as np

fig = plt.figure()
ax1 = fig.add_subplot(111, projection='3d')

def animate(i):
    #This is sample of reading from the file while keep updating the file:
    try:
        pullData = open("tteeth_extended_calibration.csv","r").read()
        sampleArray = pullData.split('\n')
    #Obviously, the data in sampleData.txt file should be in this format:
    #x1,y1
    #x2,y2
    #.
    #.
    #=============================================

    #this is just a sample array, you can easily replace
    #numbers in this array and see the cahnges.
    #Each index is a point and first value is x, second value is y
    #sampleArray = ['1,2', '2,3', '3,6', '4,9', '5,4', '6,7', '7,7', '8,4', '9,3', '10,7', '100,2', '110,2']
    #print (sampleArray)
    #print("_______\n")
        xar = []
        yar = []
        for eachLine in sampleArray:
            if len(eachLine)>1:
                try:
                    xmin,ymin,zmin,xmax,ymax,zmax,g,t = eachLine.split(',')
                    # xar.append(int(xmin))
                    # xar.append(int(xmax))
                    # yar.append(int(ymin))
                    # yar.append(int(ymax))
                    ax1.scatter(int(xmin), int(ymin), int(0), c='b', marker='o');
                    ax1.scatter(int(0), int(ymin), int(zmin), c='r', marker='o');
                    ax1.scatter(int(xmin), int(0), int(zmin), c='g', marker='^');

                except ValueError:
                    print "Oops again"
        ax1.clear()
        #ax1.scatter(xar,yar)
    except  IOError:
        print "OOOOOps"

ani = animation.FuncAnimation(fig, animate, interval=100)
#INTERVAL argument for funcanimatiin is basically the speed of updating,
# You can make it faster by decreasing the value
plt.show()