title: Artificial tick labels for seaborn heatmaps
body: <p>I have a seaborn heatmap that looks like this:</p>
  
  <p><a href="https://i.stack.imgur.com/MQNJW.png" rel="noreferrer"><img src="https://i.stack.imgur.com/MQNJW.png" alt="enter image description here"></a></p>
  
  <p>...generated from a pandas dataframe of randomly generated values a piece of which looks like this:</p>
  
  <p><a href="https://i.stack.imgur.com/xgcSo.png" rel="noreferrer"><img src="https://i.stack.imgur.com/xgcSo.png" alt="enter image description here"></a></p>
  
  <p>The values along the y axis are all in the range [0,1], and the ones on the x axis in the range [0,2*pi], and I just want some short floats at regular intervals for my tick labels, but I can only seem to get values that are in my dataframe. When I try specifying the values I want, it doesn't put them in the right place, as seen in the plot above. He's my code right now. How can I get the axis labels that I tried specifying with xticks and yticks in this code in the correct places (which would be evenly spaced along the axes)?</p>
  
  <pre><code>import pandas as pd
  import numpy as np
  import matplotlib as plt
  from matplotlib.mlab import griddata
  
  sns.set_style("darkgrid")
  PHI, COSTH = np.meshgrid(phis, cos_thetas)
  THICK = griddata(phis, cos_thetas, thicknesses, PHI, COSTH, interp='linear')
  
  thick_df = pd.DataFrame(THICK, columns=phis, index=cos_thetas)
  thick_df = thick_df.sort_index(axis=0, ascending=False)
  thick_df = thick_df.sort_index(axis=1)
  
  cmap = sns.cubehelix_palette(start=1.6, light=0.8, as_cmap=True, reverse=True)
  
  yticks = np.array([0,0.2,0.4,0.6,0.8,1.0])
  
  xticks = np.array([0,1,2,3,4,5,6])
  
  g = sns.heatmap(thick_df, linewidth=0, xticklabels=xticks, yticklabels=yticks, square=True, cmap=cmap)
  
  plt.show(g)
  </code></pre>