..
   Copyright 2022 Lawrence Livermore National Security, LLC and other
   Thicket Project Developers. See the top-level LICENSE file for details.

   SPDX-License-Identifier: MIT

#####################################
 Thicket Visualization Demonstration
#####################################

*******************
 Top-down Analysis
*******************

In this gif we demonstrate the top-down analysis visualization. Each top-down
metric is color-coded. The colors associated with each metric are shown by the
legend at the top of the visualization.

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   .. figure:: images/thicket_gifs_and_source_vids/topdown_analysis.gif

This visualization shows how the distribution of topdown metrics associated
with each node changes as the problem size increases. Each group represents a
series of trials at a given problem size and each bar represents a single
profiling run.

Near the end of the gif we see a series of run which become more backend bound
as the problem size increases; highlighting an opportunity for optimization.

***************************
 Parallel Coordinates Plot
***************************

The visualization is then initialized using the `%metadata_vis` magic command.
This command has multiple arguments. The Thicket we are visualizing, the
specific metadata we are interested in, and the node metrics which the scatter
plots will show. Initially the parallel coordinates are empty until we select
runs from a scatterplot.

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   .. figure:: images/thicket_gifs_and_source_vids/metadata_vis_load.gif

      In this gif, we show the loading of libraries into our notebook and the
      subsequent loading of data into a thicket object.

The left scatterplot plots a metric against one metadata value to provide a
perspective of how an independent variable may impact the measured performance
across a range of runs. The right scatterplot plots two metrics relative to one
another. The axis can be changed using the dropdown menus above each chart.

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   .. figure:: images/thicket_gifs_and_source_vids/metadata_changing_axis.gif

To populate the lines on the parallel coordinate plot, a user brushes over one
of the scatterplots. Either scatterplot can be brushed over. In this example, we
select all the data points but fewer can be selected at a time.

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   .. figure:: images/thicket_gifs_and_source_vids/metadata_selecting_data.gif

To better identify patterns of behavior linked to specific metadata across all
metadata values, we provide a means to color profiles by a particular metadata
field. A user may click on any of the crayon icons to the left of a parallel
coordinate axis to color all lines and dots in the scatterplot according to
that metadata field.

Quantitative variables are colored on a spectrum from light to dark green.
Categorical variables are colored with a discrete color map. In this case, we
have only one "user" who is colored blue.

At the end of this gif, we demonstrate sub-selecting a group of large
parallelism and large runtime profiles.

.. only:: html

   .. figure:: images/thicket_gifs_and_source_vids/metadata_color_encoding_and_subselecting.gif