Norm Components Matrix (NCM) algorithm for the correlation sums calculation.

The correlation sums are the building block for the evaluation of correlation dimension and the sample entropy -- complexity parameters useful in the (medical) time series analysis.

This is the parallel implementation written in Python language.

To run this software you have to have MPI and mpi4py installed. The sample bash command to run the programme would be:

$ mpirun python run.py ncm_mpi /path/to/data/data_file.dat 10 1 /path/to/results/results_file.dat --normalize --rsteps 1000

The full usage info (the output from $ pyton run.py --help):

usage: run.py [-h] [--normalize] [--rsteps RSTEPS] [--fmin FMIN] [--fmax FMAX] file m tau output

NCM algorithm for correlation sums

positional arguments:

• method for calculating correlation sums (ncm_plain / ncm_mpi)
• file Signal data - single column file or REA format
• m Embeding dimension (default: 10)
• tau Time lag (default: 1)
• output Output file name

optional arguments:

• -h, --help show this help message and exit
• --normalize Should the output be normalized?
• --rsteps RSTEPS Number of treshold values
• --fmin FMIN SD * f_min - lower value for tresholds range (default: 0.001)
• --fmax FMAX SD * f_max - upper value for tresholds range (default: 5.0)

Requirements

• sudo apt install libopenmpi-dev
• pip install mpi4py
• pip install numpy