Plotting outliers script called by https://github.com/monochromegane/smartsifter example.

plot.py

import os
import numpy as np
import matplotlib.pyplot as plt

def plot(f, points):
    n = int(f.split('_')[1].split('.')[0])

    size = 100
    scores = np.loadtxt("tmp/{}".format(f), delimiter=",").reshape(size, size)
    xs = np.linspace(-2.5, 2.5, size, endpoint=False)
    ys = np.linspace(-2.5, 2.5, size, endpoint=False)

    plt.figure(figsize=(3.25,2.25))
    plt.title('Online outlier by SmartSifter')
    plt.pcolor(xs, ys, scores, vmin=0.0, vmax=15.0)
    plt.colorbar()
    plt.scatter(points[0:n:,0], points[0:n,1])
    plt.savefig("out/{0:03d}.jpg".format(n))

def load_data(f):
    points = np.loadtxt(f, delimiter=",")
    x = points[:,0]
    y = points[:,1]
    x = (x - x.mean()) / x.std()
    y = (y - y.mean()) / y.std()
    return np.dstack((x, y))[0]

points = load_data('faithful.csv')
if not os.path.exists('out'):
    os.mkdir('out')
for i, f in enumerate(os.listdir('tmp')):
    if i%4 == 0:
        plot(f, points)