ArtTopology

The code provided here reproduces the figures from the paper:

• Dmitruk, E., Bajno, B., Dreszer, J., Bałaj, B., Ratajczak, E., Hajnowski, M., Janik, R. A., Kuś, M., Kadir, S. N., & Rogala, J.: Art’s Hidden Topology: A window into human perception (p. 2024.10.16.618741). bioRxiv.

Introduction

The code was written by Emil Dmitruk*, and the underlying ideas are the result of joint work with Shabnam Kadir(*), Jacek Rogala and Marek Kuś.

(*)UHBiocomputation Group

This code base is using the Julia Language and DrWatson to make a reproducible scientific project named

arttoppaper

Installation and requirements

0. Download this code base. Notice that raw data are typically not included in the git-history and may need to be downloaded independently.
   • raw data should be placed in under "data/exp_raw"
1. Open the terminal and navigate to the downloaded repository
2. Run Julia in the terminal and run the following:

   julia> ]
   (julia-version) pkg> add DrWatson # install globally, for using `quickactivate`
   (julia-version) pkg> activate .
   (ArtTopology) pkg> instantiate
   

Please note that the first line uses a closing square bracket to activate Julia's package manager.

The last step will install all the packages necessary to run most of the scripts. However, 1 additional dependency is required to run the code (please see below).

3. Python in version 3 with Numpy version 2.0 and above

Note: The DrWatson package ensures that all the file management should work out of the box, using repository structure for navigation.

Preprocessing

All images must be converted into grayscale before being used in the repository. This can be done with the script scripts/0a_convert_samples_to_bw.jl. In order to utilise the automation of the script for a dataset, it is advised to do the following:

1. Add a dataset to folder data/exp_raw under some name, e.g. art and pseudoart
2. Add a tuple with the dataset name to the configuration file scripts/config.jl under "Datasets paths configuration" and add it to the raw_paths variable (please see that file for 2 samples that were used in the paper).
3. Run the conversion script as

julia scripts/0a_convert_samples_to_bw.jl --data_set dataset1 --data_config BW

to run the conversion to grayscale (optionally, BW could be changed to WB to create inversed, greyscale of the image, which is required for some scripts).

• this loads files from data/exp_raw/dataset1
• results are saved in data/exp_pro/img_initial_preprocessing/dataset1

Obtaining figures from the paper

Figures from the paper can be obtained by executing the scripts, e.g. the following code:

julia scripts/2gd2_makie_average_landscapes_comparison_all_landscapes.jl --data_set pseudoart --data_config BW

will provide figures presented in Figure 14. Option dataset determines which images will be used from the paper. Option data_config determines which filtration will be used (please see src/ArgsParsing.jl for all details about the arguments for the scripts). Please use the list below to obtain desired figures.

List of figures that were produced with scripts

• fig 5. Produced with 17g, 17id, 17ie2
• fig 13. Produced with 2f3b2
• fig 14. Produced with 2gd2
• fig 15. Produced with 2m4
• fig 16. Produced with 17ig3lb2
• fig 17. Produced with 17jg3k2

List of Supplementary figures that were produced with scripts

• Supplementary fig 3. Produced with 2f3b2
• Supplementary fig 4. Produced with 2f3b2
• Supplementary fig 5. Produced with 2m4
• Supplementary fig 6. Produced with 2f3f
• Supplementary fig 7. Produced with 2gb2a
• Supplementary fig 8. Produced with 12c2
• Supplementary fig 9. Produced with 17g
• Supplementary fig 10. Produced with 17g
• Supplementary fig 11. Produced with 17g
• Supplementary fig 12. Produced with 17g
• Supplementary fig 13. Produced with 2f3hb
• Supplementary fig 14. Produced with 2f3hb
• Supplementary fig 15. Produced with 2f3hb
• Supplementary fig 16. Produced with 2f3hb
• Supplementary fig 17. Produced with 2f3hb
• Supplementary fig 18. Produced with 2f3hb
• Supplementary fig 19. Produced with 2f3hb
• Supplementary fig 20. Produced with 2f3hb
• Supplementary fig 21. Produced with 2n3a
• Supplementary fig 22. Produced with 2n3a
• Supplementary fig 23. Produced with 2n3a
• Supplementary fig 24. Produced with 2n3a
• Supplementary fig 25. Produced with 2n3b
• Supplementary fig 26. Produced with 2n3b
• Supplementary fig 27. Produced with 17h4
• Supplementary fig 28. Produced with 17ig2g and 17jg2g
• Supplementary fig 29. Produced with 17ig2g and 17jg2g
• Supplementary fig 30. Produced with 17ig2g and 17jg2g
• Supplementary fig 31. Produced with 17ig3da
• Supplementary fig 32. Produced with 17ig3da
• Supplementary fig 33. Produced with 17ig3da

Section 17

To run code from the section 17, Python has to be installed, together with a Numpy library- an error will be thrown if Numpy is not available. If this happens, please follow the instructions provided in the message.

Please note that those computations are may take a while and the saved intermidiate results may take a lot of disk space.