| Class | Description |
|---|---|
| ArithmeticMean |
Class that computes the arithmetic mean of the given column distances.
|
| DistanceSum |
Sets the overall distance to the sum of the column distances.
|
| EuclideanDistance |
Class for computation of the Euclidean distance of two vectors.
|
| ManhattanDistance |
Class for computation of the Manhattan distance of two vectors.
|
| Mathematics |
This class contains a collection of mathematical functions like the faculty, logarithms and
several trigonometric functions.
|
| MatrixOperations |
Class used to perform matrix operations, focusing on finding vector solutions to the vector
equation F(x) = 0.
|
| MaxAbsDistance |
An implementation of maxAbsDistance.
|
| MaxDivergenceTolerance |
An implementation of core comparison metric of the simulator's result with the pre-defined
results.
|
| MeanFunction |
In this class functions for the computation of an overall distance based on the distance values
determined for each column of a table are defined.
|
| N_Metric |
An implementation of an n-metric.
|
| PearsonCorrelation |
Implementation of the Pearson correlation.
|
| QualityMeasure |
This class is the basis of various implementations of distance functions.
|
| Relative_N_Metric |
Computes the relative distance of two vectors based on the
N_Metric distance. |
| RelativeEuclideanDistance |
Class for computation of the relative Euclidean distance of two vectors.
|
| RelativeManhattanDistance |
Class for computation of the relative Manhattan distance of two vectors.
|
| RelativeMaxDistance |
Computes the relative distance of two vectors based on the
MaxAbsDistance distance. |
| RelativeSquaredError |
An implementation of the relative squared error with a default value to avoid division by zero.
|
| Exception | Description |
|---|---|
| MatrixOperations.MatrixException |
This exception is thrown when errors in the computation of matrix-related solutions, their
eigenvalues or eigenvectors.
|
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