contour

Overview

This is the only module that depends on anything besides networkx, it depends on numpy, scipy and matplotlib.

Functions

metaknowledge.contour.plotting.graphDensityContourPlot(G, iters=50, layout=None, layoutScaleFactor=1, overlay=False, nodeSize=10, axisSamples=100, blurringFactor=0.1, contours=15, graphType='coloured')

Creates a 3D plot giving the density of nodes on a 2D plane, as a surface in 3D.

Most of the options are for tweaking the final appearance. layout and layoutScaleFactor allow a pre-layout graph to be provided. If a layout is not provided the networkx.spring_layout() is used after iters iterations. Then, once the graph has been laid out a grid of axisSamples cells by axisSamples cells is overlaid and the number of nodes in each cell is determined, a gaussian blur is then applied with a sigma of blurringFactor. This then forms a surface in 3 dimensions, which is then plotted.

If you find the resultant image looks too banded raise the the contours number to ~50.

Parameters

G : networkx Graph

The graph to be plotted

iters : optional [int]

Default 50, the number of iterations for the spring layout if layout is not provided.

layout : optional [networkx layout dictionary]

Default None, if provided will be used as a layout of the graph, the maximum distance from the origin along any axis must also given as layoutScaleFactor, which is by default 1.

layoutScaleFactor : optional [double]

Default 1, The maximum distance from the origin allowed along any axis given by layout, i.e. the layout must fit in a square centered at the origin with side lengths 2 * layoutScaleFactor

overlay : optional [bool]

Default False, if True the 2D graph will be plotted on the X-Y plane at Z = 0.

nodeSize : optional [double]

Default 10, the size of the nodes dawn in the overlay

axisSamples : optional [int]

Default 100, the number of cells used along each axis for sampling. A larger number will mean a lower average density.

blurringFactor : optional [double]

Default 0.1, the sigma value used for smoothing the surface density. The higher this number the smoother the surface.

contours : optional [int]

Default 15, the number of different heights drawn. If this number is low the resultant image will look very banded. It is recommended this be raised above 50 if you want your images to look good, Warning this will make them much slower to generate and interact with.

graphType : optional [str]

Default 'coloured', if 'coloured' the image will have a destiny based colourization applied, the only other option is 'solid' which removes the colourization.

metaknowledge.contour.plotting.quickVisual(G, showLabel=False)

Just makes a simple matplotlib figure and displays it, with each node coloured by its type. You can add labels with showLabel. This looks a bit nicer than the one provided my networkx’s defaults.

Parameters

showLabel : optional [bool]

Default False, if True labels will be added to the nodes giving their IDs.