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--- visual3d:documentation:pipeline:metric_commands:metric_compute_confidence_ellipse [2025/10/07 14:11] – [Example: Computing Confidence Ellipse for COFP] wikisysop
+++ visual3d:documentation:pipeline:metric_commands:metric_compute_confidence_ellipse [2025/10/31 19:12] (current) – [Notes] wikisysop
@@ Line 84: / Line 84: @@
 {{:visual3d:documentation:pipeline:metric_commands:ellipse_result.png|}}
-The metric for this example contains 3 components, with 3 values for each component.
+The metric for this example contains 3 components, with 3 values for each component. The results are as follows:
+Frame 1:
+|X| Volume|
+|Y| average of all frames of input component 1|
+|Z| average of all frames of input component 2|
+Frame 2: (for input component 1)
+|1| Eigenvalue|
+|2| Eigenvector|
+|3| Eigenvector|
+Frame 3: same as frame 2, but for input component 2
+If you have two input components, frame 1 X is the area, if you have three input components, Frame 1, X is the volume.
@@ Line 93: / Line 108: @@
 {{:visual3d:documentation:pipeline:metric_commands:ellipse_command.png|}}
-The resulting graph should look similar to this:
+The resulting graph should look similar to below:
 {{:visual3d:documentation:pipeline:metric_commands:ellipse_graph.png|}}
 ====Notes====
-[[http://www.real-statistics.com/multivariate-statistics/multivariate-normal-distribution/confidence-hyper-ellipse-eigenvalues/|For more information see]]
+For more information see, [[http://www.real-statistics.com/multivariate-statistics/multivariate-normal-distribution/confidence-hyper-ellipse-eigenvalues/|confidence hyper ellipse eigenvalues]].
-Resulting Signal
-Frame 1 contains volume and average value
-Starting at frame 2
-one frame for each dimension containing the eigenvalue and eigenvector (e.g. scale and unit vector)