A web-application to interactively visualize badminton exercises in 3d.
bev uses plotly for the creation of the visualization.
The entire project is based on json-objects.
Therefore, you can save and load states of the web-application.
You can also write your own presets directly in json if you prefer that over the user interface.
For details to the different available options I recommend you have a look at the Schema.json file (available from within the UI).
Have a look at Figure 2 for a visualization example.
An acknowledgement if you find the application useful is appreciated.
Example plot for a bev visualization.
The shown exercise (Feeding Butterfly) shows the player on the $y > 7.5$ side.
The feeder is positioned on the opposite end.
lstein
A python plotting framework to visualize 2.5 dimensional data (set of dataseries where each series is linked to one additional unique value) in 2 dimensions.
I originally developed lstein to solve the manypbchallenge, but realized that the method is general enough to potentially be useful in other fields as well.
Have a look at Figure 1.
Please cite the paper if you use lstein in your work
Example plot for an lstein plot.
The displayed object is a simulated snii from elasticc.
Different colors denote different passbands.
The $\theta$-axis (angular) shows the passband wavelength.
On the $y$-axis (angular, individual panels i.e., fraction of the entire semicircle plots the brightness in fluxcal).
Finally, in radial direction ($x$-axis) I show time relative to the first recorded datapoint.
thump
Web application to facilitate visualization and prescreening of a large amount of images (mostly thumbnails).
The original intended use is to quickly select interesting objects from difference images of large astrophysical surveys such as lsst.
The name is inspired by a few words:
"Thumb" for thumbnail.
"Dump" referring to dumping a bunch of data in one place.
And finally "thump" (onomatopoetic), the dull sound it makes when you hit your thumb with a hammer, because we all experienced a similar feeling when trying to sift through a large amount of data.
Have a look at Figure 3 for visualization examples.
An acknowledgement if you find the application useful is appreciated.
Example screenshots of a thump.
The left shows the initially intended application for screening thumbnails.
On the right I show a variation where lines are visualized for each row in the corresponding thumbnail.
