Examples Archive

Check out all examples in the archive. Click on a headline to read the teaser.

SALR clustering › 5D scatter-point data

This example works with a real 5D dataset that describes the amount of cell nuclei damage. The distance transform cannot be used to create the confining potential for this data set; so, the data density will be used and the confining force scaled. In addition, the distance metric when modeling the particles will be changed to a Minkowski distance and the solver space will be isotropically scaled. Finally, this example will compare the results of SALR clustering with k-means and show that SALR clustering produces seed-points that locate the region centers better. Read More ›

SALR clustering › 3D scatter-point data

This example uses a simple 3D data set, made to resemble 3D nuclei, for the purpose of validating the SALR particle clustering result with the k-means clustering result. The confining potential will be based on the distance transform, and all parameters for the SALR clustering, other than the particle's initial locations, will be exactly the same as those used for the 2D nuclei example. Read More ›

SALR clustering › Locating nuclei centers

This example will apply SALR clustering to locate the centers of ~7800 nuclei that are clumped together into ~2500 clumps of partially overlapping nuclei. At the end, the SALR clustering results will be compared against the true nuclei centers locations. Read More ›