| | Class | Description |
|---|
 | EmpiricalModeDecomposition |
Empirical mode decomposition.
|
| FourPointPeakEvaluationDataSource |
Data source that evaluates a peak using a four-point method.
|
| FourPointPeakEvaluationOptions |
Options for a peak evaluation that uses 4 points on a curve.
The outer two points on the curve define a straight line under the peak.
The two inner points designate the minimal x and maximal x values to start and stop the integration.
Furthermore, it is assumed that the peak maximum is located between the two inner points.
|
| FourPointPeakEvaluationOptionsSerializationSurrogate0 |
2024-01-06 V0
|
| FourPointPeakEvaluationToolMouseHandlerOptions |
Options for the peak evaluation tool mouse handler.
|
| FourPointPeakEvaluationToolMouseHandlerOptionsSerializationSurrogate0 |
2024-01-06 V0
|
| FourPointStepEvaluation |
Executes a four point step evaluation and stores the result.
Two points on the curve define a left straight line, and two other points on the curve define a right straight line.
The step should be located in between the two inner points. The step position is then evaluated by building a regression
line of the curve between the inner points, but only from a certain level to another given level (e.g., from 25% to 75% of the distance between the left and right line).
|
| FourPointStepEvaluationDataSource |
Data source that evaluates a step using a four-point method.
|
| FourPointStepEvaluationOptions |
Options for a step evaluation that uses four points on a curve. Two points on the curve define a left straight line, and two other points on the curve define a right straight line.
The step should be located in between the two inner points. The step position is then evaluated by building a regression
line of the curve between the inner points, but only from a certain level to another given level, for example from 25% to 75% of the distance between the left and right lines.
|
| FourPointStepEvaluationOptionsSerializationSurrogate0 |
2024-12-22 V0
|
| FourPointStepEvaluationToolMouseHandlerOptions |
Options for the step evaluation tool mouse handler.
|
| FourPointStepEvaluationToolMouseHandlerOptionsSerializationSurrogate0 |
2024-12-23 V0
|
| PronySeriesRelaxation |
Performs a fit with a Prony series to a relaxation signal, either in the time domain or in the frequency domain.
If the signal is a time-domain signal, it is assumed to be a relaxation signal, i.e. it is decreasing with time.
If the signal is in the frequency domain, it is assumed to be a modulus, i.e. the real part is increasing with frequency.
|
| PronySeriesRelaxationSerializationSurrogate0 |
Serialization surrogate (version 0).
|
| PronySeriesRelaxationFrequencyDomainDataSource |
Data source that evaluates a Prony-series relaxation model in the frequency domain.
|
| PronySeriesRelaxationResult |
Represents the result of a Prony series fit to a relaxation process (for instance, a modulus), either
in the time domain or in the frequency domain.
|
| PronySeriesRelaxationTimeDomainDataSource |
Data source that evaluates a Prony-series relaxation model in the time domain.
|
| PronySeriesRetardation |
Performs a fit with a Prony series to a retardation signal (general susceptibility),
either in the time domain or in the frequency domain.
If the signal is a time-domain signal, it is assumed to be a retardation signal, i.e. it is increasing with time (for instance, strain at constant stress).
If the signal is in the frequency domain, it is assumed to be a susceptibility, i.e. the real part is decreasing with frequency.
|
| PronySeriesRetardationSerializationSurrogate0 |
Serialization surrogate (version 0).
|
| PronySeriesRetardationFrequencyDomainDataSource |
Data source that evaluates a Prony-series retardation model in the frequency domain.
|
| PronySeriesRetardationResult |
Represents the result of a Prony series fit to a retardation process (general susceptibility),
for instance a mechanical compliance, either in the time domain or in the frequency domain.
|
| PronySeriesRetardationTimeDomainDataSource |
Data source that evaluates a Prony-series retardation model in the time domain.
|
| SignalMath |
Provides helper methods for common operations on one-dimensional signals.
|
Classes