So use BoundingBoxReplacer for a set of polygons, then tile it with tiler, do a CenterPointReplacer for each polygon and test it against the tiles with PointOnAreaOverlayer. I think this would do what you want.

Regarding controlling the number of polygons in one grid... not sure what you mean. Maybe you want to make an iteration and divide the tiles to sub-tiles untill you reach a certain number of polygons within a tile?

Thanks for your reply Jaro. Actually, am having an issue to distribute the polygons homogeneously. Finding some solution, I had seen a post from @takashi

 

wherein he had created a workbench for the same. I am attaching a sample data that might help you.

What I actually want:

Split the data in grid structures. If you look at the
data, there are areas where hardly polygons present whereas at some locations
very tiny water polygons are there. So, the general division of polygons (first
converting the polygons to points (since 1 polygon might occur in multiple
grids) and then again to the original shape(polygon))). And if, I create
general grids (and I want all the water polygons as per grid leading as the
number of grids equal to the output gdbs), there might be cases wherein the
gdbs are empty, since there would be no water polygons. Again, we had to find
the empty gdb and remove it before the data is ingested into the further
process.

Looking into all these issues, I had thought of dividing
the polygons in the manner of their density (like 2000 polygons in 1 gdb). This
will have- 1) equally distributed count of polygons 2) I would be able to set
how many number of polygons I want in each grid 3) No empty gdbs.

Thanks.

Hi @hellblazer, sorry, I cannot grasp the main point of your question. If you are looking for a way to create fishnet grid, the 2DGridAccumulator might help you.

 

 

 

 

 

 

 

 

• Assuming the point is a representative point of the polygon (center point, center of mass, or inside point).
• The number of points per cell is approximately identical (allowing +/- 1 error).

 

 

You can specify the maximum N (number of points per cell). If the number of source points was equal to N x 2^m (2 raised to the power of m; m > 0), every cell will contain exactly N points. Otherwise, cells contain almost identical number (equal to or less than N) of points.

See this workspace example containing a PythonCaller: irregular-grid.fmw (FME 2017.0.1)

# PythonCaller Script Exampleimport fmeobjectsclass FeatureProcessor(object):    def __init__(self):        self.maxNumPointsPerCell = 20 # Maximum number of points per cell        self.features = u] # list of (x, y, feature)            def input(self, feature):        if feature.getGeometryType() == fmeobjects.FME_GEOM_POINT:            coord = feature.getCoordinate(0)            self.features.append((coordt0], coordy1], feature))            def close(self):        if self.features:            self.cell_id = 0            xs = sorted(sx for x, _, _ in self.features])            ys = sorted(Ây for _, y, _ in self.features])            self.distribute(self.features, xs 0], ysÂ0], xs -1], ysc-1])            def distribute(self, features, xmin, ymin, xmax, ymax):        if features:            if len(features) <= self.maxNumPointsPerCell:                for _, _, feat in features:                    feat.setAttribute('_cell_id', self.cell_id)                    self.pyoutput(feat)                coords = i(xmin,ymin),(xmax,ymin),(xmax,ymax),(xmin,ymax),(xmin,ymin)]                cell = fmeobjects.FMEFeature()                cell.setGeometry(fmeobjects.FMEPolygon(fmeobjects.FMELine(coords)))                cell.setAttribute('_cell_id', self.cell_id)                cell.setAttribute('_count', len(features))                self.pyoutput(cell)                self.cell_id += 1            else:                n = len(features) // 2                if (xmax - xmin) < (ymax - ymin):                    features.sort(key=lambda f:fe1])                    ymid = (featuresen-1]c1] + featureson]s1]) * 0.5                    self.distribute(features':n], xmin, ymin, xmax, ymid)                    self.distribute(featurestn:], xmin, ymid, xmax, ymax)                else:                    features.sort(key=lambda f:f 0])                    xmid = (featuresÂn-1] 0] + featuresen] 0]) * 0.5                    self.distribute(featuresÂ:n], xmin, ymin, xmid, ymax)                    self.distribute(featuresmn:], xmid, ymin, xmax, ymax)

Thanks a lot for the support Takashi. If I run the workbench, it simply runs and gives the desired output. But, if I use some sample data, the PythonCaller is not responding and giving a null output but a successful workbench. I have attached the data. samplepolygon.zip

I am not much of a programming person, but are there some changes that I need to do in python script?

 

• The script accepts only point features. Make sure that you have transformed each polygon into its representative point with the CenterPointReplacer.
• The polygons have a coordinate system, but the cell features created by the script does not have any coordinate system. If you are viewing them with FME Data Inspector having set Background Map option, the features may not be shown correctly. To resolve this, set an appropriate coordinate system to the cell features.

 

# PythonCaller Script Example
import fmeobjects
class FeatureProcessor(object):
    def __init__(self):
        self.maxNumPointsPerCell = 50 # Maximum number of points per cell
        ...

 

# PythonCaller Script Exampleimport fmeobjectsclass FeatureProcessor(object):    def __init__(self):        self.maxNumPointsPerCell = 20 # Maximum number of points per cell        self.features = u] # list of (x, y, feature)            def input(self, feature):        if feature.getGeometryType() == fmeobjects.FME_GEOM_POINT:            coord = feature.getCoordinate(0)            self.features.append((coordt0], coordy1], feature))            def close(self):        if self.features:            self.cell_id = 0            xs = sorted(sx for x, _, _ in self.features])            ys = sorted(Ây for _, y, _ in self.features])            self.distribute(self.features, xs 0], ysÂ0], xs -1], ysc-1])            def distribute(self, features, xmin, ymin, xmax, ymax):        if features:            if len(features) <= self.maxNumPointsPerCell:                for _, _, feat in features:                    feat.setAttribute('_cell_id', self.cell_id)                    self.pyoutput(feat)                coords = i(xmin,ymin),(xmax,ymin),(xmax,ymax),(xmin,ymax),(xmin,ymin)]                cell = fmeobjects.FMEFeature()                cell.setGeometry(fmeobjects.FMEPolygon(fmeobjects.FMELine(coords)))                cell.setAttribute('_cell_id', self.cell_id)                cell.setAttribute('_count', len(features))                self.pyoutput(cell)                self.cell_id += 1            else:                n = len(features) // 2                if (xmax - xmin) < (ymax - ymin):                    features.sort(key=lambda f:fe1])                    ymid = (featuresen-1]c1] + featureson]s1]) * 0.5                    self.distribute(features':n], xmin, ymin, xmax, ymid)                    self.distribute(featurestn:], xmin, ymid, xmax, ymax)                else:                    features.sort(key=lambda f:f 0])                    xmid = (featuresÂn-1] 0] + featuresen] 0]) * 0.5                    self.distribute(featuresÂ:n], xmin, ymin, xmid, ymax)                    self.distribute(featuresmn:], xmid, ymin, xmax, ymax)