Output Analysis Target Data

Class packaging the shared “target data” arguments used by 1D function output analyses (axis labels, log-scale flags, and target value/covariance arrays). Bundling these into a single object lets downstream output-analysis constructors expose one optional argument instead of seven, which avoids a \(2^N\) combinatorial explosion in the Python wrapper’s optional-argument branching. All fields are themselves optional at construction; omitted labels default to empty (or 'x'/'y' for the axis labels), omitted log-scale flags default to false, and the target arrays default to unallocated.

Default implementation: outputAnalysisTargetDataStandard

Methods

hasTarget → logical

Return whether the value and covariance target arrays are both allocated (i.e.a comparison dataset is present).

outputAnalysisTargetDataStandard

The standard outputAnalysisTargetDataClass class — a simple struct holding axis labels, log-scale flags, and target value/covariance arrays. All fields are optional at construction; omitted axis labels default to 'x'/'y', omitted target/log-scale flags default to empty/false, and the target arrays remain unallocated.

(Default implementation)

Methods

• factors — Compute factors needed for tidal tensor calculation.

• tidalTensorGet — Get the tidal tensor.

Parameters

• [xAxisLabel] (string; default x) — Axis label for the property (x-axis) of the output analysis.

• [yAxisLabel] (string; default y) — Axis label for the function value (y-axis) of the output analysis.

• [targetLabel] (string) — Label identifying the comparison/target dataset, if any.

• [xAxisIsLog] (boolean; default .false.) — Whether the x-axis should be displayed on a logarithmic scale.

• [yAxisIsLog] (boolean; default .false.) — Whether the y-axis should be displayed on a logarithmic scale.

• [valueTarget] (real) — Target dataset values to compare against, one per bin of the output analysis.

• [covarianceTarget] (real) — Target-dataset covariance matrix corresponding to the valueTarget array.