The Ball Mapper Algorithm
Create vertices and edges (with additional properties) of a Ball Mappe...
This function will provide a new coloring which is the minimal and ave...
Produce a collection of png files with mapper graphs colored by follow...
Produce a new coloring vector being an average of values of given func...
Produce a new coloring vector being a standard deviation of values of ...
This procedure produces a dynamic graph with colors. It allows zoom-in...
Produce a static color visualization of the Ball Mapper graph. It is b...
This is an auxiliery function. It take the coordinates of points, ids ...
This procedure take two subset of points (that come from the vertices ...
This procedure take two subset of points (that come from the vertices ...
Produce a static grayscale visualization of the Ball Mapper graph. It ...
This function normalize each column (variable) of the input dataset so...
This function normalize each column (variable) of the input dataset so...
This function returns a list of points covered by the given collection...
Produce a two column list. The first column contain the number of poin...
This procedure read the BallMapper object from file. The parameter of ...
This is a simple example of dynamic visualization using networkD3 libr...
This procedure store the Ball Mapper graph in a file in the following ...
The core algorithm is described in "Ball mapper: a shape summary for topological data analysis" by Pawel Dlotko, (2019) <arXiv:1901.07410>. Please consult the following youtube video <https://www.youtube.com/watch?v=M9Dm1nl_zSQfor> the idea of functionality. Ball Mapper provide a topologically accurate summary of a data in a form of an abstract graph. To create it, please provide the coordinates of points (in the points array), values of a function of interest at those points (can be initialized randomly if you do not have it) and the value epsilon which is the radius of the ball in the Ball Mapper construction. It can be understood as the minimal resolution on which we use to create the model of the data.