Matplotlib colorbar labels to fit into boxes

Question

I created a scatter plot using matplotlib but I am somehow unable to get the labels to center into the boxes within the colorbar..

This is the code I have so far:

cMap = ListedColormap(['Orange', 'Purple', 'Blue','Red','Green'])
fig, ax = plt.subplots()
plt.figure(figsize=(12,12),dpi = 80)

#data
dist = np.random.rand(1900,1900)

#legend
cbar = plt.colorbar(scatter)

cbar.ax.get_yaxis().set_ticks([])
for j, lab in enumerate(['$Training$','$None$','$GS$','$ML$','$Both$']):
    cbar.ax.text( .5, j - .985, lab, ha='left', va='center', rotation = 270)
cbar.ax.get_yaxis().labelpad = 15
cbar.ax.set_ylabel('Outliers', rotation=270)

indices = np.where(outlier_label != -2)[0]
plt.scatter(dist[indices, 0], dist[indices, 1], c=outlier_label[indices], cmap=cMap, s=20)
plt.gca().set_aspect('equal', 'datalim')
plt.title('Projection of the data', fontsize=24)

Thanks!

Answer 1

In line cbar.ax.text( .5, j - .985, lab, ha='left', va='center', rotation = 270) you have to work and change with '.985' with try and error to get better results.

Answer 2

You can extract the y limits of the colorbar to know its top and bottom. Dividing that area into 11 equally spaced positions, will have the 5 centers at the odd positions of that list. Similarly, you can extract the x limits to find the horizontal center.

Some remarks:

• If you already called plt.subplots(), then plt.figure() will create a new figure, leaving the first plot empty. You can set the figsize directly via plt.subplots(figsize=...)
• You are mixing matplotlib's "object-oriented interface" with the pyplot interface. This can lead to a lot of confusion. It is best to stick to one or the other. (The object-oriented interface is preferred, especially when you are creating non-trivial plots.)
• You set dist = np.random.rand(1900,1900) of dimensions 1900x1900 while you are only using dimensions 1900x2.
• The code nor the text give an indication of the values inside outlier_label. The code below assumes they are 5 equally-spaced numbers, and that both the lowest and the highest value are present in the data.

import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap
import numpy as np

colors = ['Orange', 'Purple', 'Blue', 'Red', 'Green']
cmap = ListedColormap(colors)
fig, ax = plt.subplots(figsize=(12, 12), dpi=80)

# data
dist = np.random.randn(1900, 2).cumsum(axis=0)

outlier_label = np.repeat(np.arange(5), 1900 // 5)

indices = outlier_label != -2
scatter = ax.scatter(dist[indices, 0], dist[indices, 1], c=outlier_label[indices], cmap=cmap, s=20)

# legend
cbar = plt.colorbar(scatter, ax=ax)

cbar.ax.get_yaxis().set_ticks([])
cb_xmin, cb_xmax = cbar.ax.get_xlim()
cb_ymin, cb_ymax = cbar.ax.get_ylim()
num_colors = len(colors)
for j, lab in zip(np.linspace(cb_ymin, cb_ymax, 2 * num_colors + 1)[1::2],
                  ['$Training$', '$None$', '$GS$', '$ML$', '$Both$']):
     cbar.ax.text((cb_xmin + cb_xmax) / 2, j, lab, ha='center', va='center', rotation=270, color='white', fontsize=16)
cbar.ax.get_yaxis().labelpad = 25
cbar.ax.set_ylabel('Outliers', rotation=270, fontsize=18)

ax.set_aspect('equal', 'datalim')
ax.set_title('Projection of the data', fontsize=24)

plt.show()