Hi, I have the following exclusive (disjointed) sets:
A : 7516
A&B : 781
A&B&C : 324
A&B&C&D : 10336
A&B&D : 2525
A&C : 817
A&C&D : 8847
A&D : 6418
B : 7621
B&C : 369
B&C&D : 1149
B&D : 1465
C : 3152
C&D : 4118
D : 26642
Depending on whether I plot as ellipses or circles, there is some number of overlap areas missing. I guess that there is some kind of trade being made by eulerr between approximating areas and if some cutoff is made (ie the areas are too far from representing the true areas) then that overlap is left out. For reference, the webtool at https://www.meta-chart.com is able to plot this data (though likely imperfectly). So my questions are 1. is there a way to adjust this cutoff to be less stringent? ie force it to plot all areas, despite loss in accuracy? 2. is there a better R tool for what I am trying to accomplish? 3. is there some work-around, such as rounding / adjusting the data myself? I need this to be able to fit into a shell where the number of overlaps will differ between experiments. Thank you!
Hi, I have the following exclusive (disjointed) sets:
A : 7516
A&B : 781
A&B&C : 324
A&B&C&D : 10336
A&B&D : 2525
A&C : 817
A&C&D : 8847
A&D : 6418
B : 7621
B&C : 369
B&C&D : 1149
B&D : 1465
C : 3152
C&D : 4118
D : 26642
Depending on whether I plot as ellipses or circles, there is some number of overlap areas missing. I guess that there is some kind of trade being made by eulerr between approximating areas and if some cutoff is made (ie the areas are too far from representing the true areas) then that overlap is left out. For reference, the webtool at https://www.meta-chart.com is able to plot this data (though likely imperfectly). So my questions are 1. is there a way to adjust this cutoff to be less stringent? ie force it to plot all areas, despite loss in accuracy? 2. is there a better R tool for what I am trying to accomplish? 3. is there some work-around, such as rounding / adjusting the data myself? I need this to be able to fit into a shell where the number of overlaps will differ between experiments. Thank you!