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)
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mdFnn.jl: estimates false nearest neighbors function for multidimensional dataset
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mdEmbed.jl embeds multidimensional timeseries
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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
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example_mdCRQA.jl: example script for running md-CRQA
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exampleData.csv: example input dataset. Contains hand position data for two participants in a joint task
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rqa_output.csv: example output data frame of md_RQAanalysis.
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crqa_output.csv: example output data frame of md_CRQAanalysis.
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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
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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
