Calculates the primary and secondary streams of multiple stream networks. The key to determining the priority is the shortest path algorithm using multiple iterations within a network graph.
This attribute defines, for each source junction of the network, a unique path (the shortest path) to reach the destination junction. All flow lines included in a path (from the sources to the destination) will have a stream priority attribute set to 1 (primary); all others are set to 2 (secondary).
Before using this transformer, you will need to specify the weights on the network lines in the source data by specifying the Forward Weight Attribute and optionally Reverse Weight Attribute if the network graph is non-oriented.
A weight is a property of a network line typically used to represent a cost for traversing across a network line. An example of a line weight is the length of the line. In a shortest path analysis, you would choose this weight if you wanted the resulting path to be of the shortest length. For line features, 2 weights can be used: one along the digitized direction of the line feature (the forward weight) and one against the digitized direction of the line feature (the reverse weight). The digitized direction of a line feature refers to the order of the vertices.
The goal is to flag the loops (cycles) in the network in order to highlight the primary network lines.
Input Ports
Line
Network lines with cycles (loops).
Destination
Destination nodes, located on an end point (leaf) of the network graph. All other end points on the network graph are considered sources.
Output Ports
Network
Streams that are connected will be assigned the same network ID attribute.
ExtraDestination
Only one destination node is allowed per network. Any extra destination nodes found are output through the ExtraDestination port.
Invalid
Destination nodes that are not found on any network are output through the Invalid port. All non-linear features are also output through the Invalid port.
Parameters
Transformer
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.
Parallel Processing
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.
Input Ordered
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.
Parameters
Forward Weight Attribute
An attribute name on the network lines that contains a weight along the digitized direction. This parameter is required to apply the shortest path algorithm.
Reverse Weight Attribute
An attribute name on the network lines that contains a weight against the digitized direction. This parameter is required to apply the shortest path algorithm if the digitized direction of network lines is significant. By example, the digitized direction can represent a downstream flow direction for a hydrographical network. If the digitized direction is not significant for a network graph, a user can provide the same attribute of the Forward Weight Attribute parameter.
Network ID Attribute
Streams that are connected will be assigned the same network ID in the Network ID Attribute. All streams will be assigned a stream priority value in the Stream Priority Attribute with either -1, 1 or 2. Streams that are not connected to the destination nodes will be assigned level priority value of -1. Meanwhile, primary or secondary streams will be assigned level priority value of 1 or 2 respectively.
Stream Priority Attribute
An attribute name that will store the stream priority value (1 for primary or 2 for secondary) for output network lines.
Expected Output
- Network lines with a stream priority attribute set to 1 (primary) or 2 (secondary). If it’s not possible to determine the priority (if there isn't a destination located on network graph) a stream priority attribute is set to -1. The network lines have also a Graph Identifier attribute. All network lines in a same graph will have the same value in this attribute.
- Unused destination (if the destination is not located on an end point of the network graph)
Usage Examples
This transformer can be used on network linear flow lines. There are two ways to determine the stream priority attribute:
- To calculate the stream priority attribute for the oriented network lines: for these lines, the digitized direction represents a downstream flow direction.
- To calculate the stream priority attribute for the non-oriented network lines: for these lines, the digitized direction is not significant.
Calculating the Stream Priority for Oriented Network Lines
When the network lines are oriented, the shortest path should not go against the digitized direction. So initially the weight along the digitized direction (the forward weight) is the length, and the weight against the digitized direction (reverse weight) is a bigger value.
Note that the reverse weight is optional, and usually not required.
Calculating the Stream Priority for Non-Oriented Network Lines
When the network lines are not oriented, the digitized direction of network lines is not significant. So the weight along the digitized direction (forward weight) and the weight against the digitized direction (reverse weight) are the same. In this case, you can use the same attribute corresponding to the length for both weight parameters. In this way, the loops are removed for the primary network lines (stream priority=1) and you can apply other algorithm to modify the digitized direction. This is how you can make network lines primary (stream priority=1) where the digitized direction represents a downstream flow direction.
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.
Transformer Categories
FME Licensing Level
FME Professional edition and above
Search FME Knowledge Center
Search for samples and information about this transformer on the FME Knowledge Center.
Tags Keywords: LevelPriorityCalculator