helicopter 0.0.6

Linking SciML Julia helicopter challenge to Microprediction.Org

helicopter

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Tiny repo that creates a helicopter data stream at Microprediction.Org

It also contains some snippets of code showing how to:

• Retrive and interpret bivariate stream data at Microprediction.Org
• Fit a copula function
• Make a prediction submission

See article for more explanation.

Background information

Yes this is a Python package but it was inspired by the Helicopter Julia Challenge created by Chris Rackausckas of the SciML group at MIT. In that challenge contestants are provided incomplete data from a helicopter and asked to infer the latent dynamics.

• Video of the helicopter https://www.youtube.com/watch?v=2g1-sDZ3BVw
• Home page of challenge https://github.com/SciML/HelicopterSciML.jl
• Chris will be teaching how to do automated discovery of missing physical equations from a first principle model at at workshop on July 26th, 2020. Sign up for JuliaCon at https://juliacon.org/2020/

The goal of the Julia challenge is to utilize automated tools to discover a physcially-explainable model that accurately predicts the dynamics of the system.

A quick peek at the helicopter data

import pandas as pd 
data = pd.read_csv('https://raw.githubusercontent.com/SciML/HelicopterSciML.jl/master/data/Lab-Helicopter_Experimental-data.csv').plot()

Fitting implied helicopter data

See helicopter/exploratory/helicopula.py

If you prefer notebooks:

https://github.com/microprediction/PDCI/blob/master/helicopula.ipynb