Node coloring

By default, the nodes in the Mapper output are colored by the average filter value: for all points in a node, the average filter value is computed, and then a color map is applied to all nodes. Currently, the color map is Matplotlib’s default “jet” color map, with a range from the lowest to the highest filter value of all points. Low filter values are represented by blue, high filter values by red.

The “jet” color map

The Python Mapper GUI allows user code to assign arbitrary scalar values to nodes for a different coloring. Code can be entered in the field “Node coloring” in Step 5:

As in the Input data processing and Filter processing examples, any Python code can be entered. In particular, new modules may be imported for more complex procesing.

The following variables are predefined when the Python interpreter processes the code:

f

The filter function, a 1-dimensional numpy.ndarray with double data type and length equal to the number of data points.

data

The input data of the Mapper algorithm, a numpy.ndarray with double data type. If it is one-dimensional (len(data.shape)==1), it is a compressed array of pairwise distances. Otherwise, it contains vector data.

nodes

A list of mapper.mapper_output.node objects. If information contained in the nodes should be extracted, please refer to the source file mapper_output.py for details.

node_color

Initially None. If this is assigned a numpy.ndarray of shape (n,) for n nodes, then the nodes are colored according to the scalar values in this array.

point_color

Initially None. If this is assigned a numpy.ndarray of shape (N,) for N data points, then the nodes are colored according to the average value for all points in a node.

name

Initially the string 'custom scheme'. Replace it with the name of the coloring scheme for the figure legend.

np

This gives access to the NumPy package.

Only one of the variables node_color and point_color may be given a value different from None.

As a simple example, the line

name = 'z-coordinate'; point_color = data[:,2]

colorizes vector data according to the 3rd coordinate. With this coloring, the horse example looks like this:

Horse colorized by the 3rd coordinate.

The color map ranges from dark blue at the tail to red at the head.