viz.md

Visualisation

Create interactive charts using Altair and view them in your browser.

>>> chart = df.plot(reference_source=df.lineage.sources[0], show_accuracy=True)
>>> chart.serve()

This will create an interactive Vega-Lite chart (Satyanarayan et al., 2016) like the one in the screenshot at the top of our main Readme. At this time, we chose to show the (possibly more intuitive) forecast horizon for visualisation, rather than our more precise definition of belief horizon.

Table of contents

1. Installation
2. How to interact with the chart
   1. Select a time window
   2. Select a belief time
   3. Select a horizon
   4. Switch viewpoints
3. Ridgeline plots
   1. Belief history
   2. Fixed viewpoint
4. References

Installation

To enable visualization support, use pip install timely-beliefs[viz] to install the required dependencies.

How to interact with the chart

Select a time window

Click and drag in Select time window to zoom in on a subset of your data. You can then drag your selected time window to move through time. Reset with a double click.

Select a belief time

Travel through time as you select a belief time by clicking in Model results. Reset with a double click.

Select a horizon

Look only at what was believed some duration before each event by clicking in Select forecasting horizon. Double click to select all horizons.

Switch viewpoints

The chart allows you to switch between a fixed and rolling viewpoint as follows:

• Fixed viewpoint: first select all horizons by double-clicking in Select forecasting horizon, then click anywhere in Model results to travel through time.
• Rolling viewpoint: first click somewhere on the far right in Model results to look back at the full range of your data, then select a specific horizon by clicking in Select forecasting horizon.

Ridgeline plots

Create ridgeline plots showing how the confidence of beliefs improves as we approach an event (by plotting a belief history), or deteriorates as we look further into the future (by taking a fixed viewpoint).

Belief history

A ridgeline plot of a belief history (e.g. of temperature forecasts) can be created as follows:

>>> df = timely_beliefs.examples.get_temperature_df()
>>> chart = df.plot_ridgeline_belief_history(
        datetime(2015, 3, 1, 13, 0, tzinfo=pytz.utc),
        df,
        past_only=True,
        distribution="normal",
        event_value_window=(0, 22),
    )
>>> chart.serve()

Fixed viewpoint

A ridgeline plot of beliefs (e.g. temperature forecasts) with a fixed viewpoint can be created as follows:

>>> df = timely_beliefs.examples.get_temperature_df()
>>> chart = df.plot_ridgeline_fixed_viewpoint(
        datetime(2015, 3, 1, 13, 0, tzinfo=pytz.utc),
        df,
        future_only=True,
        distribution="normal",
        event_value_window=(-1, 16),
    )
>>> chart.serve()

References

• Arvind Satyanarayan, Dominik Moritz, Kanit Wongsuphasawat, and Jeffrey Heer. Vega-Lite: A Grammar of Interactive Graphics in IEEE transactions on visualization and computer graphics, Volume 23, No. 1, pages 341-350, 2016.