Updated documentation of adjusted filters

Signed-off-by: Jared Duffey <[email protected]>

src/Plugins/OrientationAnalysis/docs/ComputeFeatureNeighborCAxisMisalignmentsFilter.md

@@ -12,6 +12,8 @@ This **Filter** determines, for each **Feature**, the C-axis misalignments with
 
 **NOTE:** Only features with identical phase values and a crystal structure of **Hexagonal_High** will be calculated. If two features have different phase values or a crystal structure that is *not* Hexagonal_High then a value of NaN is set for the misorientation.
 
+Results from this filter can differ from its original version in DREAM3D 6.6 by around 0.0001. This version uses double precision in part of its calculation to improve agreement and accuracy between platforms (notably ARM).
+
 % Auto generated parameter table will be inserted here
 
 ## Example Pipelines

src/Plugins/OrientationAnalysis/docs/ComputeFeatureReferenceCAxisMisorientationsFilter.md

@@ -10,6 +10,8 @@ This **Filter** calculates the misorientation angle between the C-axis of each *
 
 This filter requires at least one Hexagonal crystal structure phase (Hexagonal-Low 6/m or Hexagonal-High 6/mmm). Although it is not recommended, you can give input data with mixed phase types and all non hexagonal phases will be skipped in the calculations.
 
+Results from this filter can differ from its original version in DREAM3D 6.6 by around 0.0001. This version uses double precision in part of its calculation to improve agreement and accuracy between platforms (notably ARM).
+
 % Auto generated parameter table will be inserted here
 
 ## Example Pipelines

src/Plugins/SimplnxCore/docs/FeatureFaceCurvatureFilter.md

@@ -11,6 +11,8 @@ This **Filter** calculates *principal direction vectors* and the *principal curv
 Principal Curvatures 1 and 2 are the &kappa; <sub>1 </sub> and &kappa; <sub>2 </sub> from [1] and are the eigenvalues from the Wiengarten matrix. The Principal Directions 1 and 2 are the eigenvectors from the solution to the least squares fit algorithm. The Mean Curvature is (&kappa; <sub>1 </sub > + &kappa; <sub>2 </sub> ) / 2, while the Gaussian curvature is (&kappa; <sub>1 </sub> *
 &kappa; <sub>2 </sub>).
 
+The values of the principal directions can have their signs flipped. They are calculated using eigenvectors which are unique up to a sign.
+
 *Note*: Computing the Weingarten matrix values is an experimental feature, and there is no guarantee at this time that the values are correct.
 
 ![Curvature Coloring of a Feature](Images/FeatureFaceCurvatureFilter.png)