Evaluation of weighted Voronoi decompositions of physicochemical ensembles

Foam Data Key: The data are organized into two main trees with the same structure, 1000 balls and 100 balls. Within these folders lies six subfolders: 1. PBC Overlap 0.0r 2. NonPBC Overlap 0.0r 3. PBC Overlap 0.5r 4. NonPBC Overlap 0.5r 5. PBC Overlap 1.0r 6. NonPBC Overlap 1.0r Within each subfolder lies the data for each setting across different CV and Density values. These range as follows: CV Values (11) = [0.05, 0.10, 0.20, 0.30, 0.40, 0.50, 0.60, 0.70, 0.80, 0.90, 1.00] Density Values (10) = [0.05, 0.10, 0.15, 0.20, 0.25, 0.30, 0.35, 0.40, 0.45, 0.50] Each combination has 20 different iterations bringing the total number of subfolders to 11 x 10 x 20 = 2200. (Note: in ensembles with no overlap, some combinations of low CV and high density are missing due to their difficulty to generate). The subfolders are named with the settings used to create the ensembles they house. These naming settings are, in order, as follows: 1. Mean - The average ball size in the grouping of balls 2. CV - The coefficient of variation of the set of balls 3. Number of Balls - The number of balls in the ensemble (note that if the ensemble has periodic boundary conditions, the number of balls in the actual ball file will be 27x this number) 4. Density - How tightly packed the balls are. Density = Volume of balls / Volume of the box that contains them 5. Number - File number for repeated runs with the same settings Example: 1.0_0.2_1000_0.5_3 = Mean: 1.0, CV: 0.2, # of Balls: 1000, Density: 0.5, Iteration: 3 Each subfolder has the following files in the following structure: > aw > aw_verts.txt - The vertices from the additively weighted Voronoi diagram. > aw_logs.csv - The complete logs of the additively weighted Voronoi diagram > pow > pow_verts.txt - The vertices from the power Voronoi diagram. > pow_logs.csv - The complete logs of the power Voronoi diagram > balls.pdb - A pdb file with the location, radius, and grouping of the balls in the foam. This works as a viewable file in molecular visualization software like PyMOL. > balls.txt - A text file with the locations and radii of the balls for more precise calculation than the pdb. > retaining_box.off - This is an object file that shows the box that the balls were constructed using. The volume os the box is used in the density calculation. Note: depending on if the ensemble has a periodic boundary, the balls in the central grouping may hang outside of the box, but in either case their centers will lie inside the box. > set_balls.pml - This file is a PyMOL script file that sets the radii of the balls in viewer.泡沫数据集说明： 本数据集分为两个结构一致的主目录，分别对应1000个球和100个球的数据集。每个主目录下包含6个子目录，分别为： 1. 周期性边界条件（Periodic Boundary Conditions, PBC）重叠率0.0r 2. 非周期性边界条件（Non-Periodic Boundary Conditions, NonPBC）重叠率0.0r 3. PBC重叠率0.5r 4. NonPBC重叠率0.5r 5. PBC重叠率1.0r 6. NonPBC重叠率1.0r 每个子目录下存储了不同变异系数（Coefficient of Variation, CV）与密度参数下的各设置对应数据，参数范围如下： CV值（共11组）：[0.05, 0.10, 0.20, 0.30, 0.40, 0.50, 0.60, 0.70, 0.80, 0.90, 1.00] 密度值（共10组）：[0.05, 0.10, 0.15, 0.20, 0.25, 0.30, 0.35, 0.40, 0.45, 0.50] 每一种参数组合包含20次重复迭代，因此总子目录数量为11×10×20=2200个。注意：在无重叠的数据集组中，部分低CV、高密的参数组合因生成困难而缺失。 子目录的命名规则按顺序依次为： 1. Mean：球组的平均粒径 2. CV：球体集合的变异系数 3. Number of Balls：数据集内的球体数量（注：若数据集采用周期性边界条件，实际球体文件中的球体数量为该数值的27倍） 4. Density：球体填充紧密程度，定义为球体总体积与容纳箱体体积的比值 5. Number：相同参数设置下重复实验的文件编号 示例： 1.0_0.2_1000_0.5_3 对应的参数含义为：平均粒径1.0，CV值0.2，球体数量1000，密度0.5，迭代编号3。 每个子目录下包含以下文件，结构如下： - aw_verts.txt：加权重Voronoi图（additively weighted Voronoi diagram）的顶点数据 - aw_logs.csv：加权重Voronoi图的完整日志文件 - pow_verts.txt：幂Voronoi图（power Voronoi diagram）的顶点数据 - pow_logs.csv：幂Voronoi图的完整日志文件 - balls.pdb：包含泡沫中球体的位置、半径及分组信息的PDB文件，可在PyMOL等分子可视化软件中打开查看 - balls.txt：包含球体位置与半径信息的文本文件，可用于比PDB文件更精确的计算 - retaining_box.off：记录构建球体所用箱体的OFF格式对象文件，箱体体积用于密度计算。注：根据数据集是否采用周期性边界条件，中心区域的球体可能会超出箱体范围，但无论哪种情况，球体的质心均位于箱体内 - set_balls.pml：用于在可视化软件中设置球体现实半径的PyMOL脚本文件