StreamOrderCalculator

All river streams connected to the destination node are output through the Network port with the Strahler order and/or Horton value assigned to the attribute(s) specified in the Strahler Order Attribute and/or Horton Order Attribute.

All river streams that are not connected to the destination node are output through the Unused port.

If any cycle exists, stream order is not computed and all lines are output through the Unused port. All nodes in which the cycles occur are output through the Cycle port.

All non-linear features and extra destination nodes are output through the <Rejected> port.

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.

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.

Considerations for Using Input is Ordered By

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.

You can choose to fix the direction of the streams to fit the downstream direction to the destination node by setting this parameter to Yes.

You can choose to detect cycles by setting Detect Cycles to Yes. This is useful to make sure that no cycles exist in the network prior to fixing flow direction or computing stream order.

If any cycle exists, stream order is not computed and all lines are output through the Unused port. All nodes in which the cycles occur are output through the Cycle port.

The Strahler order of the streams is calculated as follows:

• When two or more streams with the same Strahler orders join, the outflow streams are assigned this Strahler order plus 1.
• When two or more streams with different Strahler orders join, the outflow streams are assigned the maximum Strahler order.

Strahler order is output to an attribute specified by Strahler Order Attribute.

If Stream Order Type is set to Horton, then Strahler order is calculated internally before Horton order can be computed. Horton ordering is based on the idea of a main stream. It starts with finding out the main stream that flows to the sink node; the Horton order of the arcs in this main stream will be the maximum Strahler order of these arcs. This process continues for each of the remaining tributaries until all streams have been assigned a Horton order, which is output to an attribute specified by Horton Order Attribute.

Users can specify the rules by which main streams are determined. At each junction in the network, the main stream of the incoming streams is selected based on the following rules:

• If Horton Class Attribute is specified, always match the value of this attribute of the incoming streams to the main stream determined previously. If there is only one stream that matches, it is part of the current main stream.
• Otherwise, pick the stream with the highest value based the following formula:

priorityValue = (Horton Priority Weight) * (Horton Priority Attribute value) + (Horton Angle Weight) * (angle deviation between this stream and the previous main stream) + (Horton Length Weight) * (ratio of longest length to a source node)

The angle between this stream and the previous stream is normalized to a value between 0 and 1. The value is 1 if the incoming stream is 0 degrees (straight) away from the previous main stream. If the stream is 180 degrees (exact opposite direction) away from the previous main stream, then the value is 0. If the angle between the streams is 45 or 90 or 135 degrees, the value is computed as 0.75, 0.5 and 0.25 respectively.

The ratio of the longest length to a source node for a stream is calculated as follows:

ratio = (longest length of this stream to a source node) / (sum of all longest lengths of the incoming arcs to a source node)

If none of the Horton Priority Weight, Horton Angle Weight and Horton Length Weight are specified, then by default, a main stream is determined by the longest branch. All these weights must be real values greater than or equal to zero.