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Start visualization

tacoma offers the possibility to interactively visualize temporal networks. The visualization process works comparable to a video, where the temporal network is binned to a certain duration dt, called a frame. Then the visualization ticks through the frames.

The visualization can be started with the function tacoma.interactive.visualize().

For a visualization, a new directory is created in tacoma’s internal directory, ~/.tacoma/web, and filled with temporary tacos. The program then starts a local HTTP-server and boots the visualization. In order to stop the server, use the KeyboardInterrupt signal, i.e. in the console use Ctr+C and in Jupyter notebooks use the stop button.

Here’s an example on how it works. I think the GUI is pretty self-explanatory.

>>> import tacoma as tc
>>> from tacoma.interactive import visualize
>>> temporal_network = tc.download_and_convert_sociopatterns_hypertext_2009()
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>>> visualize(temporal_network, frame_dt = 20)

This is the result:

visualization example

You can pause the visualization using space and tick through single frames using the ← and → keys.

The concurrent visualization of multiple temporal networks is possible if you provide a list of temporal networks and all of them have the same duration.

In order to tailor the visualization to your needs you can pass the argument config to the function, wich is a dictionary of settings for the visualization. The standard configuration is

config = {

    # width of the visualization
    "plot_width" : 320 ,

    # Height of the network plot
    "network_plot_height" : 250,

    # Height of the edge activity plot
    "edges_plot_height" : 100,

    # whitespace between plots
    "padding" : 10,

    # at which frame to start the visualization
    "start_it" : 0,

    # node radius
    "node_radius" : 2.5,

    # mean distance between nodes
    "link_distance" : 10,

    # repelling force between nodes
    "node_charge": -8,

    # width of edges in edge activity plot
    "edge_line_width" : 1,

    # font size of titles and temporal labels
    "font_size_in_px" : 14,

    # width of links in the network plot
    "link_width" : 1,

    # precision of time label
    "d3_format_string": ".3f",

Export visualization

It’s also possible to concurrently visualize and export the visualization to a directory. Say you want to export to ~/Websites/HT09_visualization. You can simply do

import tacoma as tc
from tacoma.interactive import visualize
visualize(temporal_network, frame_dt = 20, export_path='~/Websites/HT09_visualization')

Now the directory ~/Websites/HT09_visualization holds all files necessary to reproduce the visualization. You could, e.g., use the terminal to do the following

cd ~/Websites/HT09_visualization
python -m "http.server" 1313

Then the visualization is reachable on your machine at http://localhost:1313/. The directory does not have to be the webpage’s root directory though – it works as any subdirectory, too, e.g.

cd ~/Websites
python -m "http.server" 1313

would give you the same visualization, but this time at http://localhost:1313/HT09_visualization.

Of course you can copy the files to your webserver, too, which will make it possible to explore the visualization online.