Aspect is a web-based nodal editor, built upon Typescript, Vue and Three.js. Its goal is to provide a graphical means of constructing Directed Acyclic Graphs (DAGs) which map to RPC APIs and map-reduce systems, defined elsewhere. In the broadest sense, Aspect can be thought of as a stateless function, which takes in a scene defintion and returns a new one.
Intended targets for Aspect-js are:
- Aspect: a python library that generates REST APIs around arbitrary python code through inspection.
- Apache Beam: A distributed map-reduce system.
- Apache Spark: A distributed map-reduce system common.
- Geode: A proprietary spatial, n-dimensional distributed map reduce framework I am working on.
After having worked years with several nodal systems: Nuke, Houdini, Maya's hypershade, Softimage, Fabric Engine, Modo's MeshOps, MeVisab, etc. And some time with several map reduce frameworks: Geode, Apache Spark, Apache Beam, and Apache Hadoop. And attempting to build custom dataflow oriented frameworks: Axon and interogrador, a custom map-reduce framework for mesh construction inside Modo. I have come to the conclusion that visual, DAG-oriented programming can be a very poweful paradigm for performing and comprehending complicated work, but that is bedevilled by its universal implementation as part of the context of solving problems related to, and only to, specific data structures, rather than as a general utility. This is especially so in the realm of data science, particularly computer vision.
Good nodal editors, say those popular in visual effects, have shallow learning curves, low technical barriers to entry and are incrediby useful. They are also proprietary, tied to proprietary formats and designed to run one a single machine, even though they are often found in render farms. Good data science libraries, can efficiently exploit large distributed systems, are made incredibly powerful through the use of machine learning, and can do things at a scale that no render farm and army of humans can. They also have no decent nodal editors, large technical barriers to entry and aren't easily accessible across locations.
Aspect-js is meant to combine these two worlds in a declarative manner, with predifined extensibility and careful attention paid towards how it maps to frameworks that solve hard problems at scale, rather than trying to compete with them.
A scene is a collection of graphs which may or may not connect to eachother. Graphs are comprized of nodes and edges. Nodes should be thought of as abstract, graphical representations of singular remote procedure calls. Nodes connect to eachother via ports. The outport of one node connects to the inport of another, and thus a graph network of computation becomes defined. Inports to a node, represent the singular parameters of the RPC function it abstracts. Outports represent what the RPC function returns. Edges are defined as an ordered pair of outport and inport.
The scene and all its components are represented within a single JSON object which represents the entire state of the DAG at one time. All other parts of Aspect; the Three.js wrapper classes, the Params class, the NodePane component, serve to manipulate this underlying data structure, as an aspect of it. For instance, the class Node serves as the graphical, 3D aspect of a node as defined within some graph of some scene. You can change its size, color, 3D position, etc. In the NodePane, a different aspect of this underlying structure is represented: its ports and their values. In the nodepane, you can alter the constant values values supplied to specific ports of a node, you can alter the GUI widgets used to represent each port, etc.
npm install
- install conda
conda create -n aspect-js --file requirements.txt
npm run serve
Alternatively, I would recommend
npm install -g @vue/cli
vue ui
and then click serve on the resulting vue ui page.
npm run build or click build in the vue ui page.
npm run lint or click lint in the vue ui page.
npm run test or click test in the vue ui page.
bin/build-docs.sh
