ForEST is a domain-specific language that adds parallel spatio-temporal computing to Python. It is designed FOR Expressing Spatial-Temporal (FOREST) computation using a combination of primitives and patterns.
Getting back from the whiteboard
We took a brief break from developing the ForEST code to work on the theoretical foundations of the language. We are excited to announce that we made some incredible breakthroughs during this period. We now have a solid theoretical model that was inspired by the earlier ForEST work. In the next few months we will start a redesign of ForEST to align with this new theoretical model. In the spirit of reproducible science we will also begin creating a number of examples to demonstrate how the theory operates using the ForEST language itself that anyone can reproduce using Jupyter Notebooks. Stay tuned as we transfer our whiteboard results to back to this public github space.
__________________ | | Sorry for the coding break, | def forest(): | but a summer of whiteboarding | awesome=True | has led to some exciting research. |__________________| We will return to this code shortly. ==================
Update: We are back!
After our summer whiteboard break and a busy semester we are returning to the code. We have some exciting news. ForEST is being used for research. Two projects are ramping up that will be using ForEST. One will be using ForEST to develop a spatial dispersal model of an invasive species in the state of Minnesota, the Brown Marmorated Stink Bug. This is a funded project and a postdoc will be working on this ForEST-based model for two years. The second will be using ForEST to analyze satellite imagery to identify farm fields. This is an exploratory project that will be funded soon hopefully. Certainly there will be more to come, but these projects will be some of the first that demonstrate the power of ForEST.