Control
Features that enter the Control port represent the control features used to compute the corrections.
Performs warping operations on the spatial coordinates of features. It is used to adjust a set of observed input features according to a spatial transform defined by a set of control vectors. This transformer computes an affine (scale, rotation, and offset) transformation based on Control vector features and applies this transformation to the Observed features to generate output, and produces good corrections when the entire set of Observed data requires a single transformation.
Each Control feature represents a control vector (a 2-point line feature) whose start point is at some location in the original Observed data space, and whose end point is at the corresponding location in the desired output data space. Each control vector represents the correction required to go from the observed vertex to the desired vertex, in terms of direction and distance. Control vectors with only one point are interpreted as a requirement that this location not change from the observed dataset to the reference dataset. This is often referred to as a tie point.
Control vectors can be stored in a dataset of any format and read into FME, or generated directly in an FME workspace, which is often the case when the vectors are not known in advance and must be generated from incoming data.
Two sets of features must be routed into this transformer.
Control
Features that enter the Control port represent the control features used to compute the corrections.
Observed
Features that enter the Observed port are the features that will be corrected.
Corrected
The modified Observed features are output via the Corrected port.
Group By
The default behavior is to use the entire set of input features as the group. This option allows you to select attributes that define which groups to form. Each set of features that have the same value for all of these attributes will be processed as an independent group.
Group By Mode
Process At End (Blocking): This is the default behavior. Processing will only occur in this transformer once all input is present.
Process When Group Changes (Advanced): This transformer will process input groups in order. Changes of the value of the Group By parameter on the input stream will trigger processing on the currently accumulating group. This may improve overall speed (particularly with multiple, equally-sized groups), but could cause undesired behavior if input groups are not truly ordered.
Considerations for Using Group By
There are two typical reasons for using Process When Group Changes (Advanced) . The first is incoming data that is intended to be processed in groups (and is already so ordered). In this case, the structure dictates Group By usage - not performance considerations.
The second possible reason is potential performance gains.
Performance gains are most likely when the data is already sorted (or read using a SQL ORDER BY statement) since less work is required of FME. If the data needs ordering, it can be sorted in the workspace (though the added processing overhead may negate any gains).
Sorting becomes more difficult according to the number of data streams. Multiple streams of data could be almost impossible to sort into the correct order, 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. In this case, using Group By with Process At End (Blocking) may be the equivalent and simpler approach.
Note: Multiple feature types and features from multiple datasets will not generally naturally occur in the correct order.
As with many scenarios, testing different approaches in your workspace with your data is the only definitive way to identify performance gains.
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 Professional edition and above
Search for samples and information about this transformer on the FME Community.
Associated FME function or factory: WarpFactory
Keywords: pointcloud