/PermutationCCC

Repository for codes for Permutation compression complexity causality

Primary LanguageMATLAB

PermutationCCC

Permutation Compression Complexity Causality (PCCC) Toolbox

Version 1.0

This is a Permutation Compression Complexity Causality or PCCC (MATLAB) toolbox which uses 'Compression Complexity Causality (CCC)' and 'Effort to Compress (ETC)', published in the following works:

  1. Kathpalia, A., & Nagaraj, N. (2019). Data-based intervention approach for Complexity-Causality measure. PeerJ Computer Science, 5, e196.
  2. Nagaraj, N., Balasubramanian, K., & Dey, S. (2013). A new complexity measure for time series analysis and classification. The European Physical Journal Special Topics, 222(3), 847-860.

This toolbox can be used standalone after including it on the MATLAB path. It is meant for research purposes only.

Run 'Main_PCCC_surr_analysis.m' for a demo using coupled time-series from Rossler systems in 'Rossler_data_demo.mat'

List of files and their functionality:

  1. 'Main_PCCC_surr_analysis.m' loads Rossler data and estimates PCCC between the coupled processes in both directions and determines whether PCCC in either direction is significant.
  2. 'perm_binning_std.m' is used to bin/ symbolize the time series using ordinal patterns embedding.
  3. 'Partition.m' is used for equidistant binning/ symbolization of the time series.
  4. 'CCC_binned_seqs.m' estimates CCC between pre-binned sequences. This is called PCCC when the cause is binned using permutation/ ordinal patterns. This is what is being done in the demo.
  5. 'AAFTsur.m' generates surrogates of given data using the Amplitude Adjusted Fourier Transform method.
  6. 'stationary_bootstrap.m' generates surrogates of given data using the stationary bootstrap method.
  7. 'ETC_1D.m' and 'ETC_2D.m' are employed by the 'CCC_binned_seqs.m' to compute CCC. These functions compute individual and joint ETC values respectively.

License

Copyright 2022 Aditi Kathpalia and Milan Paluš

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.