md-recurrence-julia

multi-dimensional recurrence methods written in Julia.

• Adapted from Wallot and Mønster (2018) "Calculation of Average Mutual Information (AMI) and False-Nearest Neighbors (FNN) for the Estimation of Embedding Parameters of Multidimensional Time Series in Matlab." https://doi.org/10.3389/fpsyg.2018.01679
• credit to Dan Mønster: https://github.com/danm0nster/mdembedding and Sebastian Wallot (https://github.com/Wallot/MdRQA)

Files

• mdFnn.jl: estimates false nearest neighbors function for multidimensional dataset

• mdEmbed.jl embeds multidimensional timeseries

• example_mdRQA.jl: example script for running md-RQA, uses:

  • mdFnn.jl for multi-dimensional estimate of embedding
  • mdEmbed.jl for multi-dimensional embedding
  • DynamicalSystems.jl for delay-embedding and recurrence analysis

• example_mdCRQA.jl: example script for running md-CRQA

• exampleData.csv: example input dataset. Contains hand position data for two participants in a joint task

• rqa_output.csv: example output data frame of md_RQAanalysis.

• crqa_output.csv: example output data frame of md_CRQAanalysis.

• simple_diagnostic_plots_filename.png: output of diagnositic plot. Contains:

  • plot of AMI funciton and estimated delay (mean value of all dimensions)
  • plot of FNN function and estimated embedding
  • recurrence plot

  

• cross_rec_diagnostic_plots.png: output of diagnositic plot for md-CRQA. Contains for each timeseries:

  • movement timeseries plots
  • plot of AMI funciton and estimated delay (mean value of all dimensions)
  • plot of FNN function and estimated embedding
  • cross recurrence plot
  • diagonal RR plot