getCartesianCoordinates

Transforms Databot indizes to exact cartesian coordinates on an toroid two dimensional grid.

Algorithms implementing populations of agents that interact with one another and sense their environment may exhibit emergent behavior such as self-organization and swarm intelligence. Here, a swarm system called Databionic swarm (DBS) is introduced which was published in Thrun, M.C., Ultsch A.: "Swarm Intelligence for Self-Organized Clustering" (2020), Artificial Intelligence, <DOI:10.1016/j.artint.2020.103237>. DBS is able to adapt itself to structures of high-dimensional data such as natural clusters characterized by distance and/or density based structures in the data space. The first module is the parameter-free projection method called Pswarm (Pswarm()), which exploits the concepts of self-organization and emergence, game theory, swarm intelligence and symmetry considerations. The second module is the parameter-free high-dimensional data visualization technique, which generates projected points on the topographic map with hypsometric tints defined by the generalized U-matrix (GeneratePswarmVisualization()). The third module is the clustering method itself with non-critical parameters (DBSclustering()). Clustering can be verified by the visualization and vice versa. The term DBS refers to the method as a whole. It enables even a non-professional in the field of data mining to apply its algorithms for visualization and/or clustering to data sets with completely different structures drawn from diverse research fields. The comparison to common projection methods can be found in the book of Thrun, M.C.: "Projection Based Clustering through Self-Organization and Swarm Intelligence" (2018) <DOI:10.1007/978-3-658-20540-9>.

Michael Thrun

DatabionicSwarm

Swarm Intelligence for Self-Organized Clustering

Quirin Stier

getCartesianCoordinates function

<dl><dt>DataBotsPosRe</dt>
<dd>[1:N] real part of complex vector Two Indizes per Databot
describing its positions in an two dimensional grid</dd><dt>DataBotsPosIm</dt>
<dd>[1:N] imaginary part of complex vector Two Indizes per
Databot describing its positions in an two dimensional grid</dd><dt>GridRadius</dt>
<dd>[Columns, Lines] Radii Matrix of all possible Positions of
DataBots in Grid, see also documentation of <code>setPolarGrid</code></dd><dt>GridAngle</dt>
<dd>[Columns, Lines] Angle Matrix of all possible Positions of
DataBots in Grid, see also documentation of <code>setPolarGrid</code></dd><dt>QuadOrHexa</dt>
<dd>Optional, FALSE=If DataPos on hexadiagonal grid, round to 2
decimals after value, Default=TRUE</dd></dl>

Arguments

Author

Intern function: Transformation of Databot indizes to coordinates — getCartesianCoordinates

<dl>

<dt>DataBotsPosRe</dt>
<dd>[1:N] real part of complex vector Two Indizes per Databot
describing its positions in an two dimensional grid</dd>

<dt>DataBotsPosIm</dt>
<dd>[1:N] imaginary part of complex vector Two Indizes per
Databot describing its positions in an two dimensional grid</dd>

<dt>GridRadius</dt>
<dd>[Columns, Lines] Radii Matrix of all possible Positions of
DataBots in Grid, see also documentation of <code>setPolarGrid</code></dd>

<dt>GridAngle</dt>
<dd>[Columns, Lines] Angle Matrix of all possible Positions of
DataBots in Grid, see also documentation of <code>setPolarGrid</code></dd>

<dt>QuadOrHexa</dt>
<dd>Optional, FALSE=If DataPos on hexadiagonal grid, round to 2
decimals after value, Default=TRUE</dd>

</dl>

getCartesianCoordinates: Intern function: Transformation of Databot indizes to coordinates

Description

Usage

Value

Arguments

Author

Details

References