Customization of plotannot annotations

This notebook contains examples of how to customize the look of plotannot annotations.

Load packages and data

#Load a few packages for plotting
import numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
np.random.seed(1) #make notebook reproducible

#Load plotannot
import plotannot

#Create some fake data
table = pd.DataFrame(np.random.random((100,50)))
table.head()

	0	1	2	3	4	5	6	7	8	9	...	40	41	42	43	44	45	46	47	48	49
0	0.417022	0.720324	0.000114	0.302333	0.146756	0.092339	0.186260	0.345561	0.396767	0.538817	...	0.988861	0.748166	0.280444	0.789279	0.103226	0.447894	0.908596	0.293614	0.287775	0.130029
1	0.019367	0.678836	0.211628	0.265547	0.491573	0.053363	0.574118	0.146729	0.589306	0.699758	...	0.114746	0.949489	0.449912	0.578390	0.408137	0.237027	0.903380	0.573679	0.002870	0.617145
2	0.326645	0.527058	0.885942	0.357270	0.908535	0.623360	0.015821	0.929437	0.690897	0.997323	...	0.556240	0.136455	0.059918	0.121343	0.044552	0.107494	0.225709	0.712989	0.559717	0.012556
3	0.071974	0.967276	0.568100	0.203293	0.252326	0.743826	0.195429	0.581359	0.970020	0.846829	...	0.263297	0.065961	0.735066	0.772178	0.907816	0.931972	0.013952	0.234362	0.616778	0.949016
4	0.950176	0.556653	0.915606	0.641566	0.390008	0.485991	0.604310	0.549548	0.926181	0.918733	...	0.315245	0.892889	0.577857	0.184010	0.787929	0.612031	0.053909	0.420194	0.679069	0.918602

5 rows × 50 columns

Control the relative width of labels when calculating overlaps with ‘rel_label_size’

fig, axarr = plt.subplots(ncols=3, figsize=(15,2))

to_label = range(0,10)
rel_label_sizes = [0.5,1,2]

for i, ax in enumerate(axarr):
    sns.heatmap(table, xticklabels=True, yticklabels=False, cbar=False, ax=ax)

    plotannot.annotate_ticks(ax, axis="xaxis", labels=to_label, rel_label_size=rel_label_sizes[i])
    ax.set_title(f"rel_label_size: {rel_label_sizes[i]}")

Control extent of axis with ‘expand_axis’

fig, axarr = plt.subplots(ncols=2, figsize=(10,2))

ax = sns.heatmap(table, xticklabels=True, yticklabels=False, cbar=False)
to_label = range(0,20)
expand_axis_lst = [0, 0.4]

#Apply annotation
for i, ax in enumerate(axarr):
    sns.heatmap(table, xticklabels=True, yticklabels=False, cbar=False, ax=ax)

    plotannot.annotate_ticks(ax, axis="xaxis", labels=to_label, expand_axis=expand_axis_lst[i])
    ax.set_title(f"expand_axis: {expand_axis_lst[i]}")

Control the extent of the annotation lines with ‘rel_tick_size’ and ‘perp_shift’

#Options for plotannot
to_label = range(0,15)
rel_tick_size_lst = [0.1,0.5,0.9]
perp_shift_lst = [5,10,20]

#Setup plot
fig, axarr = plt.subplots(3,3, figsize=(12,10))
plt.subplots_adjust(hspace=0.7)

#Plot and annotate with different options
for i, perp_shift in enumerate(perp_shift_lst):
    for j, rel_tick_size in enumerate(rel_tick_size_lst):

        ax = axarr[i,j]
        sns.heatmap(table, xticklabels=True, yticklabels=False, cbar=False, ax=ax)

        plotannot.annotate_ticks(ax, axis="xaxis", labels=to_label, rel_tick_size=rel_tick_size, perp_shift=perp_shift)
        _ = ax.set_title(f"rel_tick_size={rel_tick_size} | perp_shift={perp_shift}")