Artificial tick labels for seaborn heatmaps
<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>