https://doi.org/10.5061/dryad.sbcc2frdf

This dataset contains the images, .csv files, and code needed to reproduce the results to support the conclusion of the manuscript.

Files and Folders

The file structure is ordered relative to the dataset collected for each main figure in the manuscript, as well as some of the supplemental information data. Each folder can contain images (.png, .tif), .csv files, and Jupyter notebooks (.ipynb) that will help reproduce the dataset in the main manuscript. Each folder that has code has a README.md that helps facilitate installing and running the code.

/Figure 1

• README.md

  • Markdown (.md) file that has details for installing a conda python environment to run the necessary analysis code for the data in Figure 1.

• environment.yml

  • YAML (.yml) file that declares all necessary python libraries to run the analysis code (orderParams.py and OrderParameterAnalysis.ipynb)

• orderParams.py

  • Python (.py) file containing necessary functions to run analysis code (OrderParameterAnalysis.ipynb)

• OrderParameterAnalysis.ipynb

  • Jupyter notebook (.ipynb) file that contains the analysis code to generate the spatial pair distribution function, g(r), and the bond order parameter image found in Figure 1.

• WP-008-H11.png

  • Portable Network Graphics (.png) file of truncated tetrahedrons assembled on a 2D surface at a low gravitational field. This is the raw data/image used to run the analysis code on (OrderParameterAnalysis.ipynb).

• WP-008-H11_centers.csv

  • Comma separated valued (.csv) file of the centers of the particles found in WP-008-H11.png. The first column is the x-pixel value and the second column is the y-pixel value. This is needed to run the analysis code (OrderParameterAnalysis.ipynb).

/Figure 2

• README.md

  • Markdown (.md) file that has details for installing a conda python environment to run the necessary analysis code for the data in Figure 2.

• environment.yml

  • YAML (.yml) file that declares all necessary python libraries to run the analysis code (orderParams.py and OrderParameterAnalysis.ipynb)

• orderParams.py

  • Python (.py) file containing necessary functions to run analysis code (OrderParameterAnalysis.ipynb)

• OrderParameterAnalysis.ipynb

  • Jupyter notebook (.ipynb) file that contains the analysis code to generate the spatial pair distribution function, g(r), graph and the bond order parameter image in Figure 2.

• SUM_WP-008-H11_001.png

  • Portable Network Graphics (.png) file of truncated tetrahedrons assembled on a 2D surface at a higher gravitational field. This is the raw image used to run the analysis code (OrderParameterAnalysis.ipynb).

• SUM_WP-008-H11_001.czi

  • .CZI file of truncated tetrahedrons assembled on a 2D surface at a higher gravitational field. This is the raw confocal image with multiple z-planes.

• SUM_WP-008-H11_001_centers.csv

  • Comma separated valued (.csv) file of the centers of the particles found in SUM_WP-008-H11_001.png. The first column is the x-coordinate (in microns) and the second column is the y -coordinate (in microns). This is needed to run the analysis code (OrderParameterAnalysis.ipynb).

/Figure 3

• README.md

  • Markdown (.md) file that has details for installing a conda python environment to run the necessary analysis code to generate data in Figure 3.

• environment_entropy.yml

  • YAML (.yml) file that declares all necessary python libraries to run the entropy model analysis code (EntropyModel.ipynb)

• EntropyModel.ipynb

  • Jupyter notebook (.ipynb) file that contains the code to generate the single-cell occupancy free energy curves as a function of packing fraction seen in Figure 3.

• environment_hpmc.yml

  • YAML (.yml) file that declares all the necessary python libraries to run the hard-particle Monte Carlo (hpmc) simulations (hpmc.ipynb)

• hpmc.ipynb

  • Jupyter notebook (.ipynb) file that contains the code to generate the hard-particle Monte Carlo simulations seen in Figure 3.

• ATT_centered.stl

  • 3D model (.STL) file of an Archimedean truncated tetrahedron that is used for the hard-particle Monte Carlo simulations (hpmc.ipynb).

/Supplemental_Avrami

• README.md

  • Markdown (.md) file that has details for installing a conda python environment to run the necessary analysis code to generate data in Supplementary Figure 5.

• environment.yml

  • YAML (.yml) file that declares all necessary python libraries to run the entropy model analysis code (grainAnalysis.ipynb)

• grainAnalysis.ipynb

  • Jupyter notebook (.ipynb) file that contains the code to estimate the number of particles in either a 3-fold or 6-fold bond order configuration for the data found in Supplementary Figure 5.

• /output

  • Empty folder for the generated output image data generated from grainAnalysis.ipynb.

• WP-009-L14_timelapse_10x002-3.tif

  • Multi-image file (.tif) of raw data for calculating the number of particles in either a 3-fold or 6-fold bond order configuration. This is the same file as the Supplementary Video 3. Each frame corresponds to ~5 seconds. This is needed to run the analysis code (grainAnalysis.ipynb)

• WP-009-L14_timelapse_10x002-3_centers.csv

  • Comma separated valued (.csv) file of the centers of the particles found in WP-009-L14_timelapse_10x002-3.tif for each frame. Each particle is denoted by an ID (Column B), which has a unique x coordinate (in pixels), Column E "POSITION_X", and y coordinate (in pixels), Column F "POSITION_Y" . Each frame can be identified by the Column I "FRAME". This is needed to run the analysis code (grainAnalysis.ipynb).

Code/Software

The code run on each dataset is provided in each folder in the form of a Jupyter notebook that is tested in a conda environment. The dependencies are given in the form of a .yml file. Each folder that has code has an individual README.md that helps facilitate installing and running the code. Each code was tested on 11/28/2023 by author(s) and the output cells that are available in the notebook reflect the code run on the dataset given.