WebAug 15, 2024 · The way FME works I’d guess that to make (for example) feature-4 available, we’d also need to fetch/store feature-1, feature-2, feature-3 – because FME’s features are processed sequentially. That makes it a bit more awkward, and I don’t know that using an attribute value for the Number of Prior/Subsequent Features would work ... WebFunctions that receive non-numeric, null, missing, or empty string arguments should return null, with the fme_expression_warnings list attribute appended to. For all functions with fixed arguments that return double precision values, expect a …
Using FME to create a Polygon datasets froma Point dataset
WebMay 21, 2024 · Expand the Advanced Attribute Value Handling section and set Substitute Missing, Null and Empty to Closest Adjacent Feature Check the box for Enable Adjacent Feature Attributes and set how many features you want to check. You said the "next" so perhaps you would leave Prior Features to zero and just set Subsequent Features. WebNov 27, 2015 · An alternative is the QGIS NNJoin Plugin, that for each feature in the input dataset finds the nearest neighbour in the join dataset. The resulting layer will contain all the features from the input dataset with all the attributes from the nearest join feature added, and also a new attribute that contains the distance to the nearest (join) feature. pop and insert python
Open fme file
WebMar 1, 2011 · 2. There are some fairly standard ways of improving this kind of search, and how complicated you want to get depends on how many points you are searching. A … WebAug 3, 2024 · Incidentally, the closest team to this fabled spot: Coventry City. Coventry fans rejoice. ... The football thing is fun, and I do hope some non-FME’ers find their way here for that alone. But the real point is how well FME does at data integration, data transformation, automation, web services, and much more. ... WebThere are a number of transformers available in FME that could help you with your task. Firstly, there is the NeighborFinder. You can use this to find features which are close to each other. Finds the Candidate features closest to each Base feature and merges their attributes onto the Base feature according to the Accumulation Mode parameter. sharepoint cce online