Python and R Codes for Computing Permutation Entropy
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Updated
Dec 12, 2022 - Python
Python and R Codes for Computing Permutation Entropy
📦 Lempel-Ziv Complexity, fast implementations with 🐍 Python (naive, Numba or Cython for speedup), Open-Source (MIT) 👍 →
Parallel random matrix tools and complexity for deep learning
A collection of sorting algorithms implemented in C++
This source code (in Python) is a preliminary implementation of my quadratic-time positive integer matrix multiplication.
Genon is a generator of nonlinear preferences for intelligent artificial agents.
Generate Borderline Noise for Classification Problems
Assessing consciousness by perturbing a dynamic mean-field whole-brain model fitted to empirical neuroimaging data
Implementation of statistics used for paper soon to be cited here
Set of projects using diverse programming tecniques
📦 Lempel-Ziv Complexity, fast implementation in Julia, Open-Source (MIT) 👍 →
NeuroKit2: The Python Toolbox for Neurophysiological Signal Processing. This is an adaptation to take RRI or peak times from fetal and maternal heart rate data as input and output 60+ HRV measures including optimal time delay-based complexity measures with user-definable time window length. Huge thanks to the team of neurokit!
Cyclomatic complexity of R functions and expressions
Cyclomatic complexity toolkit for Python code
Projeto algorithms - Projeto avaliativo da Trybe do Bloco 35: Algoritmos
Technique to quantify textual complexity based on Kolmogorov complexity and implemented with PyLZMA compression.
C++ Code Complexity Measurement System
A series of programs that enable one's investigations in the algebraic complexity theory such as matrix multiplication algorithms, primality tests, algebraic complexity, sorting algorithms etc. Each algorithm is accompanied by a comparative time complexity analysis and a class of test cases and test suites.
Resources and exercises done for the Algorithmic Methods in Problems Resolution ("Métodos algorítmicos en resolución de problemas") subject.
A Python package implementing informational complexity (ICOMP) criteria for regression models
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