content: #!/usr/bin/python
  # Generate heatmap of points
  
  import numpy as np
  import seaborn as sns
  sns.set()
  import matplotlib.pyplot as plt
  
  from heatmap_data import *
  
  # image_name=
  # im = plt.imread(image_name);
  # implot = plt.imshow(im);
  
  # Load the example flights dataset and conver to long-form
  # flights_long = sns.load_dataset("flights")
  # flights = flights_long.pivot("month", "year", "passengers")
  
  
  def sample_kde_data(data):
      u = np.exp(data)
      z = np.sum(u)
      p = (u / z) * 1000
  
      xs = []
      ys = []
      for yind in xrange(len(p)):
          for xind in xrange(len(p[yind])):
              c = int(p[yind][xind])
              xs += [xind] * c
              ys += [NUM_POINTS - yind] * c
  
      return (np.array(xs), np.array(ys))
  
  
  NUM_POINTS=25
  def plot_kde(data, cmap):
      (xs, ys) = sample_kde_data(data)
      print len(xs)
      sns.kdeplot(xs, ys, cmap=cmap, shade=True, shade_lowest=False, clip=[[0,NUM_POINTS], [0, NUM_POINTS]], alpha=0.5)
  
  
  # img = plt.imread("data/dqa_parts_v1/fighter-jet/fighter-jet_0000.png")
  img = plt.imread("data/dqa_parts_v1/antelope/antelope_0000.png")
  
  fig, ax = plt.subplots()
  ax.imshow(img, extent=[0, NUM_POINTS, 0, NUM_POINTS])
  
  plot_kde(neck_data3, "Blues")
  # plot_kde(leg_data2, "Reds")
  # plot_kde(tail_data2, "Greens")
  
  plt.axis('off')
  plt.show()
  
  # Draw a heatmap with the numeric values in each cell
  # sns.heatmap(data, cbar=False, cmap="coolwarm")
  # plt.show()
  
  