Working with Subregions Using Region Manager

Some workflows shouldn't run against a whole map at once — a national land-use model might need different parameters per country, or a hydrology model might only make sense computed watershed by watershed. Region Manager is what makes that practical: define the regions once, from a categorical map whose class values are the boundaries, and everything downstream — reading metadata, narrowing to one region, splitting a map into pieces, and merging the pieces back — works against that single definition.

Region Manager is the container everything else on this page depends on.

A nonzero borderCells matters for anything that accumulates across neighboring cells — a cost surface, a neighborhood statistic — since without it, a region's edge cells would be computed as if the world stopped there.

Example — the shell everything else in this page builds on:

sourcesMap := LoadMap "c:/data/sources.tif";
frictionsMap := LoadMap "c:/data/frictions.tif";
regionsMap := LoadCategoricalMap "c:/data/regions.tif" .none .default 0;

RegionManager regionsMap 5 {{
    // everything below is added here, one section at a time
}};

Get All Regions Info returns boundary details for every region at once, as a table:

Get Region Info is the single-region equivalent, useful when you need more than a bounding box for one particular region — it also returns a mask isolating that region and its coordinate reference system:

Both are for reading region metadata itself — bounding boxes, a region's mask, its coordinate system — and neither one feeds into the running example that continues through the rest of this page. As a standalone check, either can simply be dropped inside the same shell:

RegionManager regionsMap 5 {{
    allRegions := GetAllRegionsInfo;
}};

The cheapest way to actually *visit* every region — which the running example does need — is covered separately, next.

Region narrows scope to a single region for whatever's nested inside it:

A region's ID is one of the regions map's own category values, so the cheapest way to visit every region is For Each Category against that categorization directly — no table needs to be built and then queried for its keys first, the way looping over Get All Regions Info's output would require. For Each Category takes a Categorization, but since Categorical Map Type converts to Categorization Type automatically on any connection, the regions map itself can be passed straight in — there's no need for an explicit extraction step like Get Map Categories first.

As with For Each, For Each Category's current-step output isn't named regionId, so Region is still nested inside to re-expose it under the right name — Regionalize Map and the rest of this page's functors auto-bind to a port by that exact name. step itself is an internal output, not an ordinary variable, so it can't be passed as a bare argument directly — it has to be aliased to a variable with = first, the same way Region Manager's own confirmed example aliases regionManager to manager before using it.

It's tempting to reach for For Each Region instead, since it bundles “define regions” and “loop over them” into one container. Resist that here: it has its own required regions input and creates its own region manager internally, rather than sharing one from an enclosing Region Manager. That's fine if the loop is the entire task, but this page's example needs the *same* region manager instance still available after the loop, for the merge — which For Each Region can't provide, since its manager stops existing once its own block ends.

RegionManager regionsMap 5 {{
    _ := ForEachCategory regionsMap {{
        regionId = step;

        Region regionId {{
            // regionManager auto-binds from the enclosing RegionManager.
        }};
    }};
}};

Regionalize Map and Regionalize Categorical Map cut a global map down to one region's extent:

This is where the actual per-region computation happens — split the global inputs, run whatever the model needs against the region-sized pieces, in this case Calc Cost Map. regionId and regionManager both auto-bind here from the enclosing Region, so neither needs to be passed explicitly:

Region regionId {{
    regionalSources := RegionalizeMap sourcesMap;
    regionalFrictions := RegionalizeMap frictionsMap;

    { costs = regionalCost, directions = _ } :=
        CalcCostMap regionalSources regionalFrictions .no;
}};

Regional Map and Regional Categorical Map tag a per-region fragment under a shared name as it's produced — neither has an output; they're pure collectors, accumulating fragments as a side effect of the loop running:

Region regionId {{
    regionalSources := RegionalizeMap sourcesMap;
    regionalFrictions := RegionalizeMap frictionsMap;

    { costs = regionalCost, directions = _ } :=
        CalcCostMap regionalSources regionalFrictions .no;

    RegionalMap "cost_map" regionalCost;
}};

Merge Regional Maps and Merge Regional Categorical Maps reassemble everything stored under a shared name back into one global mosaic:

There's a trap here worth naming: neither merge functor has a sequenceInput of its own, and nothing about globalMapName — just a literal string — creates a data dependency on the loop that populated it. Left as-is, the engine has no reason to run the merge *after* the loop rather than before or during it. For Each Category does expose a sequenceOutput once the whole loop finishes, but with nowhere on the merge functor to plug it into, the fix is a Group wrapped around the merge, whose own sequenceInput the loop's sequenceOutput connects into.

A few more things worth knowing before relying on the merge:

• The merged map's format is inherited from the first fragment stored, not negotiated across all of them. Cell type, null value, and categorization all come from whichever Regional Map or Regional Categorical Map call registered first for that name — only the dimensions come from the regions map itself. If regions are processed in an order that isn't guaranteed, don't rely on which fragment “wins.”
• Mismatched null values fail the merge, not silently overwrite each other. When mergeNonRegionCells brings overlapping border cells from two different regions together, they can only combine if they agree, or one of them is null — two regions disagreeing on what a cell's value should be raises an error rather than picking one.
• A layer's sparse storage survives the merge, so long as every regional fragment for that layer used it too — the merged global layer comes out sparse rather than being densified. See Map Type's Storage section for what sparse storage means.
• Fragments are consumed, not just read. Once the merge for a given globalMapName runs, the manager no longer holds those fragments — there's no merging the same name twice, and nothing left to read back under it afterward.

Region Manager Value exists purely to pass a Region Manager value through — the same relay role Struct's carrier functor plays for structs. Its own input auto-binds to the enclosing container's regionManager by default and cannot be given as a constant.

sourcesMap := LoadMap "c:/data/sources.tif";
frictionsMap := LoadMap "c:/data/frictions.tif";
regionsMap := LoadCategoricalMap "c:/data/regions.tif" .none .default 0;

RegionManager regionsMap 5 {{
    sequenceOut := ForEachCategory regionsMap {{
        regionId = step;

        Region regionId {{
            regionalSources := RegionalizeMap sourcesMap;
            regionalFrictions := RegionalizeMap frictionsMap;

            { costs = regionalCost, directions = _ } :=
                CalcCostMap regionalSources regionalFrictions .no;

            RegionalMap "cost_map" regionalCost;
        }};
    }};

    _ := Group sequenceOut {{
        costMap := MergeRegionalMaps "cost_map" .no;
        SaveMap costMap "c:/data/cost_map_merged.tif";
    }};
}};

One region manager, defined once at the top, is what threads the whole thing together: For Each Category loops directly against the categories already attached to regionsMap, Region narrows against the manager once per loop iteration, Regional Map stores fragments into it, and Merge Regional Maps — deliberately delayed until the loop's sequenceOutput fires — reads every one of those fragments back out of the same instance.

Calc Areas returns a table of every category's area within a map — this section computes one separately per region and accumulates them into a single table, one region's worth of rows at a time.

Since each region produces its own Category-keyed table, and the goal is one combined table across every region, the accumulator needs a second, leading key — RegionId — so each region's rows land in their own, non-overlapping slice. Mux Table carries that combined table across loop iterations:

This section doesn't use Region at all — regionId is used directly, since Regionalize Categorical Map and Set Table By Key both auto-bind or accept it positionally without needing it re-exposed under a container of its own:

landscapeMap := LoadCategoricalMap "c:/data/landscape.tif" .none .default 0;
regionsMap := LoadCategoricalMap "c:/data/regions.tif" .none .default 0;

emptyRegionAreas := Table [
    "RegionId*#real", "Category*#real", "Area_In_Cells#real", "Area_In_Hectares#real", "Area_In_Square_Meters#real"
];

RegionManager regionsMap 5 {{
    _ := ForEachCategory regionsMap {{
        regionId = step;

        accumulatedAreas := MuxTable emptyRegionAreas nextAccumulatedAreas;

        regionalLandscape := RegionalizeCategoricalMap landscapeMap regionId;
        areaTable := CalcAreas regionalLandscape .no;

        // regionId (an Integer Value) converts to a one-element Tuple
        // automatically here, since it's a connected variable, not a literal.
        nextAccumulatedAreas := SetTableByKey accumulatedAreas regionId areaTable;
    }};

    // nextAccumulatedAreas, not accumulatedAreas (the mux's own output,
    // which lags one iteration behind), holds every region's rows once the
    // loop finishes. The Table carrier passes it out of the loop's scope,
    // since := always binds a functor call.
    allRegionAreas := Table nextAccumulatedAreas;
    SaveTable allRegionAreas "c:/data/area_by_region.csv";
}};

Unlike the map-merging example earlier on this page, no Group/sequenceOutput workaround is needed to order the save correctly — nextAccumulatedAreas is an ordinary data value with a real dependency chain running back through every iteration, so the engine already knows to wait.

This loop runs one region strictly after another, not in parallel. Each iteration's accumulatedAreas is fed directly by the previous iteration's nextAccumulatedAreas, so the next region can't start until the current one has finished and been folded into the running table — even though, taken alone, no region's area calculation actually depends on any other region's.