import numpy as np
import matplotlib.pyplot as pl
import pdb

def plotData(data, options='', limits=[]):
    group_colors = []      
    for i,dset in enumerate(data):
        x = np.array([point['x'] for point in dset])
        y = np.array([-point['y'] for point in dset])
        if options != '':
            pl.plot(x,y,options)
        else:
            pl.plot(x,y)
        pl.hold(True)
        pl.annotate(str(i), xy = (x[0],y[0]))
    if len(limits):
        pl.gca().set_xlim(limits[0],limits[1])
        pl.gca().set_ylim(limits[2],limits[3])        

def testPlot(): 
    colors = ['b','g','r','c','m','k','y']
    data1 = [[dict(x=1,y=1),dict(x=2,y=2),dict(x=3,y=3)],[dict(x=2,y=2),dict(x=4,y=4)],[dict(x=5,y=5),dict(x=6,y=8)]]
    data2 = [[dict(x=1,y=1),dict(x=2,y=2),dict(x=3,y=3)],[dict(x=2,y=2),dict(x=4,y=4)]]
    data = []
    data.append(data1)
    data.append(data2)
    data.append(data1)
    pl.figure()
    pl.ion()
    pl.subplot(2,1,1)
    # Title with best definition from dictionary
    pl.title("Title on top")
    # Plot the data but colored according to segmentation in top plot
    for i in range(len(data1)):
        plotData([data1[i]],colors[i%len(colors)])
    # Then plot segmentation parts (radicals) in different corresponding colors
    # Title each plot with radical names
    for i in range(len(data)):
        pl.subplot(2,3,4+i)
        pl.title("Row 2 subplot {0}".format(i))
        plotData(data[i],colors[i%len(colors)],[0, 15, 0, 15])