# Design Characterization for Black-and-White Textures in Visualization

This is a repository for all data and analysis scripts used in the paper "[Design Characterization for Black-and-White Textures in Visualization](https://doi.org/10.1109/TVCG.2023.3326941)", presented at [IEEE Visualization 2023](http://ieeevis.org/year/2023/welcome) and published in the journal [IEEE Transactions on Visualization and Computer Graphics](https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=2945). If you use the results in new projects or use it in a different way we would appreciate a citation:

Tingying He, Yuanyang Zhong, Petra Isenberg, and Tobias Isenberg. Design Characterization for Black-and-White Textures in Visualization. IEEE Transactions on Visualization and Computer Graphics, 2024. To appear. doi: [10.1109/TVCG.2023.3326941](https://doi.org/10.1109/TVCG.2023.3326941); open-access versions are available at [HAL](https://inria.hal.science/hal-04167900) and at [arXiv](https://arxiv.org/abs/2307.10089).

## BibTex

```
@article{He:2024:DCB,
  author      = {Tingying He and Yuanyang Zhong and Petra Isenberg and Tobias Isenberg},
  title       = {Design Characterization for Black-and-White Textures in Visualization},
  journal     = {IEEE Transactions on Visualization and Computer Graphics},
  year        = {2024},
  doi         = {10.1109/TVCG.2023.3326941},
  doi_url     = {https://doi.org/10.1109/TVCG.2023.3326941},
  oa_hal_url  = {https://hal.inria.fr/hal-04167900},
  preprint    = {https://doi.org/10.48550/arXiv.2307.10089},
  osf_url     = {https://osf.io/n5zut/},
  url         = {https://tobias.isenberg.cc/VideosAndDemos/He2024DCB},
  github_url  = {https://github.com/tingying-he/design-characterization-for-black-and-white-textures-in-visualization},
  pdf         = {https://tobias.isenberg.cc/personal/papers/He_2024_DCB.pdf},
  video       = {https://youtu.be/PfhSx-n02so},
}
```

## Project websites

* https://tingying-he.github.io/projects/He_2024_Textures.html
* https://tobias.isenberg.cc/VideosAndDemos/He2024DCB
* https://www.aviz.fr/Research/BWTextures

## Instructions for generating figures ([Graphics Replicability Stamp](https://www.replicabilitystamp.org/))
### Requirements

The R script contained within this repository requires, in addition to a normal R installation, several packages including (potentially more):

* `plyr`
* `dplyr`
* `tidyr`
* `reshape2`
* `ggplot2`
* `propCIs`

To install these required packages, run the following call from a command line: `Rscript -e "install.packages(c('plyr', 'dplyr', 'tidyr', 'reshape2', 'ggplot2', 'propCIs'), repos='https://cran.rstudio.com')"`

If you encounter problem with Pandoc:
1. To check whether Pandoc was correctly installed: ``Rscript -e "rmarkdown::pandoc_exec()"``
2. To install Pandoc from its official website: https://pandoc.org/installing.html . If you use macOS, you can also use Homebrew to install it: ``brew install pandoc``

### Running the R script

1. Clone this repository using `git clone git@github.com:tingying-he/design-characterization-for-black-and-white-textures-in-visualization.git` or download the code as a ZIP file from the repository.
2. Change to the cloned directory, and then navigate to the `graphics-replicability-stamp` folder by using the command `cd graphics-replicability-stamp`. All files related to the Graphics Replicability Stamp Initiative are stored in this folder.
3. Once you are in the `graphics-replicability-stamp` directory, knit the `all-exp2-exp3-figures.Rmd` file by running `Rscript -e "library(rmarkdown); rmarkdown::render('./all-exp2-exp3-figures.Rmd', 'html_document')"`

### Files produced

After the script completes, in the `graphics-replicability-stamp/results` folder you should see the following figures from [the paper](https://tingying-he.github.io/assets/publications/papers/He_2024_Textures.pdf) in PDF format.

* Fig. 4 
  * Figure4a-exp2_beauvis_bar.pdf
  * Figure4b-exp2_beauvis_pie.pdf
  * Figure4c-exp2_beauvis_map.pdf
  * Figure4d-exp2_beauvis_diff_bar.pdf
  * Figure4e-exp2_beauvis_diff_pie.pdf
  * Figure4f-exp2_beauvis_diff_map.pdf
* Fig. 5
  * Figure5a-exp2_vibratory_bar.pdf
  * Figure5b-exp2_vibratory_pie.pdf
  * Figure5c-exp2_vibratory_map.pdf
  * Figure5d-exp2_vibratory_diff_bar.pdf
  * Figure5e-exp2_vibratory_diff_pie.pdf
  * Figure5f-exp2_vibratory_diff_map.pdf
* Fig. 6
  * Figure6a-exp3_correct_rate_bar.pdf
  * Figure6b-exp3_correct_rate_pie.pdf
  * Figure6c-exp3_correct_rate_diff_bar.pdf
  * Figure6d-exp3_correct_rate_diff_pie.pdf
* Fig. 7
  * Figure7a-exp3_response_time_bar.pdf
  * Figure7b-exp3_response_time_pie.pdf
  * Figure7c-exp3_response_time_diff_bar.pdf
  * Figure7d-exp3_response_time_diff_pie.pdf
* Fig. 8
  * Figure8a-exp3_readable_bar.pdf
  * Figure8b-exp3_readable_pie.pdf
  * Figure8c-exp3_readable_diff_bar.pdf
  * Figure8d-exp3_readable_diff_pie.pdf
* Fig. 9
  * Figure9a-exp3_beauvis_bar.pdf
  * Figure9b-exp3_beauvis_pie.pdf
  * Figure9c-exp3_beauvis_diff_bar.pdf
  * Figure9d-exp3_beauvis_diff_pie.pdf

We are unable to script the other images in our paper, as they are design samples created by participants or old visualization examples.