signalAggregation

Signal aggregation functions for <code>circularProjection</code>
and <code>polarProjection</code> internal calls. The aggregation should be 
symmetric with respect to signal polarity, ensuring that opposite signals 
produce corresponding outputs.

For a given graph containing vertices, edges, and a signal associated with the vertices, the 'PathwaySpace' package performs a convolution operation, which involves a weighted combination of neighboring vertices and their associated signals. The package then uses a decay function to project these signals, creating geodesic paths on a 2D-image space. 'PathwaySpace' could have various applications, such as visualizing network data in a graphical format that highlights the relationships and signal strengths between vertices. It can be particularly useful for understanding the influence of signals through complex networks. By combining graph theory, signal processing, and visualization, the 'PathwaySpace' package provides a novel way of representing graph data.

Mauro Castro

PathwaySpace

Spatial Projection of Network Signals along Geodesic Paths

Victor Apolonio

Vinicius Chagas

Sysbiolab and Collaborators 

signalAggregation function

<dl><dt>method</dt>
<dd>A character string specifying the method for
signal aggregation, returning either a customized <code><a href="/link/mean?package=PathwaySpace&version=1.1.0" data-mini-rdoc="PathwaySpace::mean">mean</a></code> or 
<code><a href="/link/weighted.mean?package=PathwaySpace&version=1.1.0" data-mini-rdoc="PathwaySpace::weighted.mean">weighted.mean</a></code> function.</dd></dl>

Arguments

Author

Signal aggregation functions — signalAggregation

<dl>

<dt>method</dt>
<dd>A character string specifying the method for
signal aggregation, returning either a customized <code><a href='https://rdrr.io/r/base/mean.html'>mean</a></code> or 
<code><a href='https://rdrr.io/r/stats/weighted.mean.html'>weighted.mean</a></code> function.</dd>

</dl>

signalAggregation: Signal aggregation functions

Description

Usage

Value

Arguments

Author

See Also

Examples