conkit.plot.ContactDensityPlot module¶

A module to produce a domain boundary plot

class ContactDensityFigure(hierarchy, bw_method='bowman', **kwargs)[source]¶

Bases: conkit.plot._Figure.Figure

A Figure object specifically for a contact density illustration.

This figure is an adaptation of the algorithm published by Sadowski (2013) [1].

[1]	Sadowski M. (2013). Prediction of protein domain boundaries from inverse covariances. Proteins 81(2), 253-260.

Examples

>>> import conkit
>>> cmap = conkit.io.read('toxd/toxd.mat', 'ccmpred').top_map
>>> conkit.plot.ContactDensityFigure(cmap)

Attributes

`hierarchy`	A ConKit `ContactMap`
`bw_method`	The method to estimate the bandwidth

Methods

`bowman_bandwidth`(X)	This is the optimal bandwidth if the point distribution is Gaussian.
`redraw`()	Re-draw the plot with updated parameters

static bowman_bandwidth(X)[source]¶

This is the optimal bandwidth if the point distribution is Gaussian.

To calculate the bandwidth for the 1D data array X with n data points, the following equation is used:

\[bandwidth=\sqrt{\frac{\sum{X}^2}{n}-(\frac{\sum{X}}{n})^2}*(\frac{3*n}{4})^\frac{-1}{5}\]

This equation is a direct implementation taken from Bowman & Azzalini [2].

[2]	Bowman, A.W. & Azzalini, A. (1997). Applied Smoothing Techniques for Data Analysis.

Parameters:

Parameters:	X : list, tuple A list of data points

X : list, tuple

A list of data points