DOI: 10.5281/zenodo.11352807
title: Code and simulation data for model of ideal chemotactic agent combining spatial and temporal gradient-sensing

description: This repository contains python code and simulation data files for the paper “Information theory of chemotactic agents using both spatial and temporal gradient-sensing” by Julian Rode, Maja Novak, Benjamin M. Friedrich.

The code in this repository was developed by Julian Rode based on an earlier version by Andrea Auconi in the research group of Benjamin M. Friedrich at TU Dresden, Dresden, Germany.

The python package ‘pyegotaxis’ contained in ’pyegotaxis-0.2.zip’ is a snapshot (tag 0.2) of the git repository used for all simulations and data analysis in the paper, available also here:https://github.com/rodjul42/pyegotaxis

The file ‘readme.MD’ in ‘pyegotaxis-0.2.zip’ includes instructions for installation and a minimal example. 

The jupyter notebooks contained in notebooks.zip recreate the figures 2-5 of the paper, as well as the supplementary figures S1-S10 and movies, using the data files.

 

Data files needed to recreate figures: 




maxLD0_sum.fea


Needed for Fig 2 and S1

Maximum likelihood no motility noise



infoD0_sum.fea


Needed for Fig 2 and S1

Infotaxis no motility noise



maxLDrot_sum.fea


Needed for Fig 3 and S2

Maximum likelihood motility noise



infoDrot_sum.fea


Needed for Fig 3 and S2

Infotaxis motility noise



infoINFO_small_sum.fea


Needed for Fig 4 and Fig 5

Infotaxis SC vs TC



maxLINFO_small_sum.fea


Needed for Fig 4 and Fig 5

Maximum likelihood SC vs TC



expdata.hdf


Needed for Fig 5

SC vs TC data from experiments



expdata_trajectories.npz


Needed for Fig 5

Trajectories from experiments



expdata.hdf


Needed for Fig 5

SC vs TC data from experiments



10008_0.0.npz


Needed for Fig S3

example for SC vs TC infotaxis



2222_0.0.npz


Needed for Fig S3

example for SC vs TC maximum likelihood



Drotlam_kernel_large_sum2.fea


Needed for Fig S4

Infotaxis motility noise larger domain



spaceD_lT_sum.fea


Needed for Fig S5

infotaxis smaller space discretization and normal target size



spaceD_O_sum.fea


Needed for Fig S5

infotaxis normal space discretization and normal target size



spaceD_sum.fea


Needed for Fig S5

infotaxis smaller space discretization and smaller target size



infomaxlEXP_sum.fea


Needed for Fig S6

Maximum likelihood SC vs TC for exponentialconcentration field



infoInfoEXP_20_sum.fea


Needed for Fig S6

Infotaxis SC vs TC for exponentialconcentration field



infoRoblam_small_sum.fea


Needed for Fig S7

Infotaxis robustness sensing noise



maxLRoblam_small_sum.fea


Needed for Fig S7

Maximum likelihood robustness sensing noise



mDrotinfo_sum.fea


Needed for Fig S8

infotaxis robustness motility noise



mDrotmaxL_sum.fea


Needed for Fig S8

Maximum likelihood robustness motility noise



gamma.fea


Needed for Fig S9

infotaxis robustness non-radial concentration field, x(t0)=(-R0,0)



gamma2.fea


Needed for Fig S9

infotaxis robustness non-radial concentration field, x(t0)=(0,-R0)



vdrift.fea


Needed for Fig S10

infotaxis robustness concentration field distorted by drift, x(t0)=(0,-R0)



vdrift2.fea


Needed for Fig S10

infotaxis robustness concentration field distorted by drift, x(t0)=(-R0,0)



vdrift3.fea


Needed for Fig S10

infotaxis robustness concentration field distorted by drift, x(t0)=(R0,0)