subtr-actor

subtr-actor

subtr-actor is a versatile library designed to facilitate the process of working with and extracting data from Rocket League replays. Utilizing the powerful [boxcars] library for parsing, subtr-actor simplifies the underlying complex actor-based structure of replay files, making them more accessible and easier to manipulate.

Overview of Key Components

• [ReplayProcessor]: This struct is at the heart of subtr-actor's replay processing capabilities. The [ReplayProcessor] traverses the actor graph, pushing frames through an [ActorStateModeler] to capture the state of all actors at any given moment. It provides a suite of helper methods to assist in the navigation of the actor graph and the retrieval of information about the game as it progresses.

• [Collector]: This trait outlines the blueprint for data collection from replays. The Collector interfaces with a ReplayProcessor, handling frame data and guiding the pace of replay progression. It is typically invoked repeatedly through the [ReplayProcessor::process] method as the replay is processed frame by frame.

Notably, subtr-actor includes implementations of the [Collector] trait,

• [NDArrayCollector]: This [Collector] implementations translates frame-based replay data into a 2 dimensional array in the form of a [::ndarray::Array2] instance. The exact data that is recorded in each frame can be configured with the [FeatureAdder] and [PlayerFeatureAdder] instances that are provided to its constructor ([NDArrayCollector::new]). This representation is ideal for use with machine learning libraries like pytorch and tensorflow.

• [ReplayData]: This [Collector] implementation provides an easy way to get a serializable to e.g. json (though [serde::Serialize]) representation of the replay. The representation differs from what you might get from e.g. raw boxcars in that it is not a complicated graph of actor objects and is instead something more akin to the way a human might think of the data contained in a replay.