Shear Induced Diffusion of Platelets revisited

* Dataset and python files (Python3) to reproduce all figures and simulations presented in the manuscript.

•  ANALYSIS of NPFEM DATA:
  1. FILES: Data_npFEM.zip (separate files of platelets trajectory); analysis_npFEM.py (python code to reproduce the figures presented in the manuscript); module_npFEM.py (python module with functions used in analysis_npFEM.py
  2. EXECUTION: python3 analysis_npFEM.py arg1 arg2 arg3
  3. ARGUMENTS: arg1 (path to the data); arg2 (0 or 1 ; "1" means that the figure is reproduced); arg3 (0 or 1 ; "1" means that the figure is reproduced);
  4. EXEMPLE: To execute the code with the second figure reproduced only; python3 analysis_npFEM.py Data_npFEM/ 0 1
  5. REQUIREMENTS: pandas,  numpy, scipy, os, powerlaw (https://doi.org/10.1371/journal.pone.0085777)

• ANALYSIS of STOCHASTIC MODEL:
  1. FILES: Data_stochastic_model.zip (contains data from npFEM used in the analysis of the stochastic model); analysis_stochastic_model.py (python code to reproduce the figures presented in the manuscript); module_stochastic_model.py (python module with functions used in analysis_stochastic_model.py
  2. EXECUTION: python3 analysis_npFEM.py arg1 arg2 arg3 arg4 arg5 arg6
  3. ARGUMENTS: arg1 (path to the data); arg2 (0 or 1 ; "1" means that the figure is reproduced); same for arg3, arg4, arg5 and arg6
  4. EXEMPLE: To execute the code with the fourth figure reproduced only; python3 analysis_stochastic_model.py Data_stochastic_model/ 0 0 0 1 0
  5. REQUIREMENTS: numpy, scipy, random, powerlaw (https://doi.org/10.1371/journal.pone.0085777)