Histograms
Histograms#
Summary
On this page, you will see how to
use
.plot.facet_grid.hist
to plot histogramsuse
.plot.facet_grid.hist
to plot panels of histograms
WIP 🚧
Plotting several panels of histograms with
.plot.facet_grid.hist
does not yet work.
Histograms are one of the most commonly used plots to visualise distributions. Let us run the SEIRD model with a fixed configuration multiple times over different seeds, and plot a histogram of the maximum peak height of the number of infected agents.
To plot a histogram, base your plot on .plot.facet_grid.hist
.
We can use the np.max
operation in the data transformation process to select the maximum density for each run:
histogram:
based_on:
- .creator.multiverse
- .plot.facet_grid.hist
# Select only the infected population
select_and_combine:
fields:
infected:
path: densities
transform:
- .sel: [!dag_prev , { kind: [infected] }]
# Get the maximum value
transform:
- np.max: [!dag_tag infected]
kwargs:
axis: 3
tag: data
# Helpers
helpers:
set_title:
title: Maximum density of infected agents
set_labels:
x: Peak height
y: ' '
Any additional entries are keyword arguments that will be passed to the low-level plotting function, in this case matplotlib.pyplot.hist. For example, we can specify the number of bins and color by adding
histogram:
# all the previous entries ...
color: mediumseagreen
bins: 50
The output will look something like this: