Extracting different number of points for different class in GEE

Question

I want to write a function that takes class id and number of points for each class as argument and samples points from polygons, returning a FeatureCollection.

I could only write a function that samples the same number of points [100 points in the example] for each class with iteration as below:

GEE Link: Reproducible GEE Example

Let me know if you can't open the polygon file

// Reproducible Example for Training Point Sampling

// Create id List
var idList = ee.List.sequence(11, 13).map(function(x) {return ee.Number(x)});

// Extraction Function
var collectTrain = function(id, featureCol) {
  // cast
  id = ee.Number(id);
  featureCol = ee.FeatureCollection(featureCol);
  // Extract
  var point = ee.FeatureCollection.randomPoints(
   polygons.filter(ee.Filter.eq('id', id)), 100)
   .map(function(feat){
      feat = ee.Feature(feat);  
      return feat.set('id', id);  
   });
  
  return featureCol.merge(point);
};

// Initial FeatureCollection
var point = ee.FeatureCollection.randomPoints(
   polygons.filter(ee.Filter.eq('id', 11)), 1)
   .map(function(feat){
      feat = ee.Feature(feat);  
      return feat.set('id', 11);  
   });

//Iterate over idList starting from the initial point
var training = ee.FeatureCollection(idList.iterate(collectTrain, point));
print(training);

How could we write such a function that takes two lists as arguments, such as in R with purrr::map2 and works with iterating those two lists. Arguments should be like:

id = [11, 12, 13]
point = [100, 150, 120]

Answer 1

It is explained here by Gorelick:

Stratified random sampling with Google Earth Engine Error

We need to use stratifiedSample. Editing Gorelick's answer:

GEE Example

// Reproducible Example for Training Point Sampling - ClassBand

// Converting tables to FeatureCollection
var polygonsF = ee.FeatureCollection(polygons);

// Creating Class Image
var classes = ee.Image().byte().paint(polygonsF, "id").rename("class").toUint8();

// Sampling from Class Image - Returns FeatureCollections
var stratified = classes.addBands(ee.Image.pixelLonLat())
    .stratifiedSample({
      numPoints: 10, // This will be overridden by ClassValues & ClassPoints 
      classBand: 'class',
      projection: 'EPSG:32635',
      scale: 10,
      region: polygons,
      classValues: [11, 12, 13],
      classPoints: [100, 150, 120]
    }).map(function(f) {
      return f.setGeometry(ee.Geometry.Point([f.get('longitude'), f.get('latitude')]));
    });

print(stratified);

However, I couldn't find a way to restrict sampling only on some classes with this approach. You have to sample from all classes and then filter from them as:

// Sampling from Class Image - Returns FeatureCollections
var stratified = classes.addBands(ee.Image.pixelLonLat())
    .stratifiedSample({
      numPoints: 10, // This will be overridden by ClassValues & ClassPoints 
      classBand: 'class',
      projection: 'EPSG:32635',
      scale: 10,
      region: polygons,
      classValues: [11, 12],  // This will not throw id=13 out
      classPoints: [100, 150] // 10 points will be sampled from id=13
    }).map(function(f) {      // as defined in 'numPoints'
      return f.setGeometry(ee.Geometry.Point([f.get('longitude'), f.get('latitude')]));
    }).filter(ee.Filter.inList('class', [11, 12])); // getting desired Class