Kinetics Toolkit 0.14 has been released!

[felixchenier]

This is a pretty big release, particularly for the Player which can now be completely scripted and stylized, and which can export images and videos. Also, the TimeSeries has been polished and is now easier than ever to use conjointly with your current code. Here is the complete release notes:

New features

Scripting API for the Player

The Player can now be entirely scripted:

• Get/set the TimeSeries to be visualized using Player.get_contents() and Player.set_contents()
• Get/set the point interconnections using Player.get_interconnections() and Player.set_interconnections()
• Play/pause using Player.play() and Player.pause()
• Access and modify all settings using properties such as current_index, current_time, target, zoom, elevation, azimuth, etc.

Styling the Player

Every element can now be stylized using properties such as background_color, default_point_color, point_size, frame_size, frame_width, grid_size, grid_subdivision_size, etc.

Exporting the Player's content to images and videos

You can now export the Player's content to image files such as PNG, JPEG, PDF, SVG or TIFF using Player.to_image(), or to MP4 videos using Player.to_video(). This, combined to styling, should help you giving nice presentations!

Standard views in the Player

By defining which axes (x, y, z, -x, -y, -z) correspond to the up and anterior direction using the up and anterior properties, you can now switch to standard orthogonal views using Player.set_view(). For example: p.set_view("front"), p.set_view("top"), p.set_view("right"), etc. These views are also available interactively using number keys 1 to 6.

Interconnection wildcards in the Player

Create interconnections for one body, and apply it to multiple bodies at once, using wildcard (*) in point names. This should facilitate visualizing acquisitions with more than one person (e.g., use *C7 and *T1 instead of Body1:C7, Body1:T1, Body2:C7, Body2:T1) or to create a sequence of movements (e.g., use C7* and T1* instead of C7_frame0, T1_frame0, C7_frame1, T1_frame1).

Convert anything to a TimeSeries

It is now easier than never to create a TimeSeries. For instance, a list of data:

some_list = [1.0, 1.1, 1.2, 1.1, 1.4, 1.5]

can be transformed into a TimeSeries using:

some_timeseries = ktk.TimeSeries(some_list)

It works for any other array-like such as nested lists, NumPy arrays, Pandas Series, Pandas DataFrames. It can also be used to create copies of TimeSeries.

New TimeSeries.add_data method

The new TimeSeries.add_data method now complements its siblings TimeSeries.rename_data and TimeSeries.remove_data. Using this method ensures that the added data is compatible with the data already present in the TimeSeries (e.g., it has the same dimension across the time dimension) and that you specify wether or not existing data of the same name must be overwritten.

New overwrite option to TimeSeries.add_data_info

A new parameter overwrite has been added to TimeSeries.add_data_info so that you can specify wether or not already existing data info of the same name must be overwritten.

Improvements

Improved TimeSeries assignations

It is now possible to assign any array-like value to a TimeSeries' time or data property; it will be converted automatically to a proper NumPy array.

Improved parameter checking

Parameter checking has been generally improved, so that if you make a mistake, you will be more likely to get a helpful error message.

Warning on non-interactive mode

You will now get a warning if you attempt to use an interactive Matplotlib object (e.g., the Player, or a GUI-based method) without having configured Matplotlib to be interactive.