Solves proximity conflicts between features using a variant of the Nickerson displacement algorithm. This transformer is usually used after generalization.
Input and Output Ports
The features routed into the transformer through the Base port are geometrically frozen (cannot move).
The features routed in through the Candidate port are compared against the Base feature(s), displaced as necessary, and exit through the Displaced port. If no displacement occurred, they exit through the Untouched port.
Each comparison/displacement is independent of the others.
Base features with geometries other than point, curve or area (polygon or ellipse or donut) will exit through the InvalidBase port. Candidate features with geometries other than point, curve or simple area (polygon or ellipse) will exit through the InvalidCandidate port.
The ExtraBase port holds extra Base features as described in the Base Type parameter below.
You can use this option to narrow down which candidate features to compare with which base features.
Note: How parallel processing works with FME: see About Parallel Processing for detailed information.
This parameter determines whether or not the transformer should perform the work across parallel processes. If it is enabled, a process will be launched for each group specified by the Group By parameter.
Parallel Processing Levels
For example, on a quad-core machine, minimal parallelism will result in two simultaneous FME processes. Extreme parallelism on an 8-core machine would result in 16 simultaneous processes.
You can experiment with this feature and view the information in the Windows Task Manager and the Workbench Log window.
No: This is the default behavior. Processing will only occur in this transformer once all input is present.
By Group: This transformer will process input groups in order. Changes of the value of the Group By parameter on the input stream will trigger batch processing on the currently accumulating group. This will improve overall speed if groups are large/complex, but could cause undesired behavior if input groups are not truly ordered.
Using Ordered input can provide performance gains in some scenarios, however, it is not always preferable, or even possible. Consider the following when using it, with both one- and two-input transformers.
Single Datasets/Feature Types: Are generally the optimal candidates for Ordered processing. If you know that the dataset is correctly ordered by the Group By attribute, using Input is Ordered By can improve performance, depending on the size and complexity of the data.
If the input is coming from a database, using ORDER BY in a SQL statement to have the database pre-order the data can be an extremely effective way to improve performance. Consider using a Database Readers with a SQL statement, or the SQLCreator transformer.
Multiple Datasets/Feature Types: Since all features matching a Group By value need to arrive before any features (of any feature type or dataset) belonging to the next group, using Ordering with multiple feature types is more complicated than processing a single feature type.
Multiple feature types and features from multiple datasets will not generally naturally occur in the correct order.
One approach is to send all features through a Sorter, sorting on the expected Group By attribute. The Sorter is a feature-holding transformer, collecting all input features, performing the sort, and then releasing them all. They can then be sent through an appropriate filter (TestFilter, AttributeFilter, GeometryFilter, or others), which are not feature-holding, and will release the features one at a time to the transformer using Input is Ordered By, now in the expected order.
The processing overhead of sorting and filtering may negate the performance gains you will get from using Input is Ordered By. In this case, using Group By without using Input is Ordered By may be the equivalent and simpler approach.
In all cases when using Input is Ordered By, if you are not sure that the incoming features are properly ordered, they should be sorted (if a single feature type), or sorted and then filtered (for more than one feature or geometry type).
As with many scenarios, testing different approaches in your workspace with your data is the only definitive way to identify performance gains.
Specifies how much the displacement at one point in the candidate feature's geometry should affect the neighboring points. A lower value means that the candidate geometry can be deformed easily, while a higher value means that it will try its best to keep its original shape.
The Minimum Separating Distance parameter specifies the minimum separating distance between the candidate feature's geometry and the base feature's geometry after displacement.
The Displace Endpoints parameter specifies whether or not to displace the endpoints of candidate features whose geometries are unclosed lines.
The Base Type parameter specifies whether only a single Base feature will be used, or whether all Base features will be used. If Bases First is selected, then the transformer assumes that all Base features will enter the transformer before any Candidate features. Any further Base features that arrive after the first Candidate will be output through the ExtraBase port. The same goes for any Base features after the first when in Single Base mode.
Editing Transformer Parameters
Using a set of menu options, transformer parameters can be assigned by referencing other elements in the workspace. More advanced functions, such as an advanced editor and an arithmetic editor, are also available in some transformers. To access a menu of these options, click beside the applicable parameter. For more information, see Transformer Parameter Menu Options.
FME Licensing Level
FME Professional edition and above
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Tags Keywords: displacement resolve conflict generalization Nickerson generalize NickersonDisplacer