A 2D Density Plot is a way to display the distribution of data as a 2D heat map. It uses color-coding to represent areas of high and low density in a scatterplot, with darker colors indicating areas of higher density. It is useful for visualizing large datasets and identifying patterns in the data. Who said this?
It would be easy to count the result when we have only a few cells in an image. But once you got thousands of cells in an image and/or you got hundreds of repeats, the work would be tedious and laboring. But with the help of python, we can do more than sample counts and gray intensity calculation. We can apply more complicated techniques like Vironoi spacial calculation and Delaunay triangulation. I'll show how can we apply these two algorithms to finally determine whether cells may share boundaries or be physically contacted.