Generalizer
From fmepedia
Generalizer is a Workbench Transformer.
| Table of contents |
Description
The Generalizer transformer can smooth, fit, measure and generalize features.
Smoothing
Smoothing algorithms will determine a new location for each vertex.
The available algorithms are:
- McMaster
- McMaster Weighted Distance
- NURBFit
Generalizing
Generalizing algorithms reduce the density of coordinates by removing vertices.
The available algorithms are:
- Douglas
- Thin
- ThinNoPoint
- Deveau
- Wang
Fit
Fitting algorithms replace the original geometry completely, with a new feature fitted to a specified line (eg to minimize the orthogonal distance to the original)
The available algorithms are:
- Orthogonal Distance Regression
Measure
Measuring algorithms calculate the location of points, and return a list of these points (eg to measure the sinuosity of a feature)
The available algorithms are:
- Inflection Points
