Through help on another thread
http://www.eastgate.com/Tinderbox/forum//YaBB.pl?num=1300367231, I've completed my personal activity tracking visualization file. If you find it useful or find ways to improve it, I'd love to hear about it. If you have questions about using it, I'll try to answer. By the way--I used TBX 5.8. If you have an older version, you'll likely need to test this out with the demo, as I don't think it will work properly in the older version due to my use of some of the new action codes.
You can grab the template file from my site
http://memoryfailure.net/tbx/TimeReports.tbx. Pasted below is the note I made about it and a screenshot:
This file was made with data generated by a Time logging program that exports data in a csv format (aTimeLogger, an iPhone app). That csv was opened in Numbers, cleaned up a bit, and dropped into the "Data" container (if interested, I can further explain how to clean up the data from aTimeLogger to get it into TBX). Then, the individual notes were dropped into the "Week 11" container, which applies several "OnAdd" actions.
From here, everything else is automated. You can view the day visualizations (Timeline or Map) by changing the title of the note in the "Day" container to a different date. Similarly, for the "Week" visualizations, change the title of the "Week of:" notes to the first day of the week.
Similarly, the visualizations in the "Viz" container can be changed by renaming the note to a new date (the week and 30 days agents simply find notes 7 or 30 days after the name of the note).
The visualizations depend on a "duration" number (the number of minutes of each activity) and a "goal" number. The graph depicts the percentage of the duration to the goal. To change the goal, just change the $Goal attribute of the agent using the inspector.
For the Timeline, the agents in the "day" and "week" prototypes set the TimelineBand attribute, so these can be changed by adjusting the Agent's "OnAdd" actions.
I have attempted to make the performance of the file a bit more efficient by adding a rule that turns all the prototype agents off, while leaving the rest of the agents on.

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