Do a contour plot on a 3D array

contour_plot

import scipy.stats as st
import numpy as np
import matplotlib.pytlot as plt

def contour_plot(array3d, **kwargs):
    """
    Do the contour plot of a X, Y, Z vector. 
    
    Parameters
    ----------

    array3d :  A 3D array.

    scale : If equals to 'log', do a logarithmic scale
    xlabel : Set x-label of plot
    ylabel : Set y-label of plot
    title : Set plot title
    save : Save as a different name. If not set, save as 'contour.pdf'    
    """
    print 'Plotting the countour plot'
    x = st.itemfreq(array3d[:, 0])[:, 0]
    y = st.itemfreq(array3d[:, 1])[:, 0]
    
    X, Y = np.meshgrid(x, y)
    
    Z = np.zeros([len(y), len(x)], float)
    
    for i in range(len(X)):
        for j in range(len(X[0])):
            for k in array3d:
                if X[i, j] == k[0] and \
                np.round(Y[i, j], 2) == np.round(k[1], 2):
                    Z[i, j] = k[2]
   
    #Apply scale, if defined
    if kwargs.has_key('scale') and kwargs['scale'] == 'log':
        Z = np.log(Z)
        
    #Do contour plot
    plt.figure()
    CS = plt.contour(X, Y, Z)
    plt.clabel(CS, inline=1, fontsize=10)
    plt.axis([15000, 29000, 3.5, 4.5])
    if kwargs.has_key('xlabel'):
        plt.xlabel(kwargs['xlabel'])
    if kwargs.has_key('ylabel'):
        plt.ylabel(kwargs['ylabel'])
    if kwargs.has_key('title'):
        plt.title(kwargs['title'])

    if kwargs.has_key('save'):
        plt.savefig(kwargs['save'])
    else:
        plt.savefig('contour.pdf')
    plt.clf()
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