add FluidKNNClassifier / FluidKNNRegressor

release-packaging/Classes/FluidKNNClassifier.sc

@@ -0,0 +1,19 @@
+FluidKNNClassifier : FluidManipulationClient {
+    fit{|dataset, labelset, action|
+       this.pr_sendMsg(\fit,[dataset.asString, labelset.asString], action);
+    }
+
+    predict{ |dataset, labelset, k, action|
+        this.pr_sendMsg(\predict,
+			[dataset.asString, labelset.asString, k],
+			action, [string(FluidMessageResponse,_,_)]
+		);
+    }
+
+    predictPoint { |buffer, k, action|
+        this.pr_sendMsg(\predictPoint,
+			[buffer.asUGenInput, k], action,
+			[number(FluidMessageResponse,_,_)]
+		);
+	}
+}

release-packaging/Classes/FluidKNNRegressor.sc

@@ -0,0 +1,20 @@
+FluidKNNRegressor : FluidManipulationClient {
+    fit{|sourceDataset, targetDataset, action|
+       this.pr_sendMsg(\fit,
+			[sourceDataset.asString, targetDataset.asString],
+			action
+		);
+    }
+
+    predict{ |sourceDataset, targetDataset, k, action|
+        this.pr_sendMsg(\predict,
+			[sourceDataset.asString, targetDataset.asString, k],
+			action,
+			[string(FluidMessageResponse,_,_)]);
+    }
+
+    predictPoint { |buffer, k, action|
+        this.pr_sendMsg(\predictPoint, [buffer.asUGenInput, k], action,
+			[number(FluidMessageResponse,_,_)]);
+    }
+}

release-packaging/Examples/dataset/super-simple-classifier-example.scd

@@ -2,7 +2,7 @@
 ~simpleInput = FluidDataSet(s,\simpleInput,2);
 ~simpleOutput = FluidLabelSet(s,\simpleOutput,2);
 b = Buffer.alloc(s,2);
-~knn = FluidKNN(s);
+~knn = FluidKNNClassifier(s);
 k = 3
 )
 
@@ -23,7 +23,7 @@ v.mouseDownAction = {|view, x, y|myx=x;myy=y;w.refresh;
 	Routine{
 		b.setn(0,[myx,myy]);
 		s.sync;
-		~knn.classifyPoint(b, ~simpleOutput, k, {|x|x.postln;});
+		~knn.predictPoint(b, k, {|x|x.postln;});
 }.play;};
 
 //custom redraw function
@@ -58,6 +58,6 @@ Routine{
 )
 
 // fit the dataset
-~knn.fit(~simpleInput,action:{"fitting done".postln})
+~knn.fit(~simpleInput,~simpleOutput, action:{"fitting done".postln})
 
 // now click on the grid and read the estimated class according to the nearest K neighbours.

release-packaging/Examples/dataset/super-simple-regressor-example.scd

@@ -36,8 +36,8 @@ Routine{
 ~mappingresult = Buffer.alloc(s,512);
 
 //make the process then fit the data
-~knn = FluidKNN(s)
-~knn.fit(~simpleInput,action:{"fitting done".postln})
+~knn = FluidKNNRegressor(s)
+~knn.fit(~simpleInput, ~simpleOutput, action:{"fitting done".postln})
 
 // query 512 points along the line (slow because of all that sync'ing)
 (
@@ -46,7 +46,7 @@ Routine{
 	512.do{|i|
 		b.set(0,i*61);
 		s.sync;
-		~knn.regressPoint(b,~simpleOutput,k,action:{|d|~mappingresult.set(i,d);});
+		~knn.predictPoint(b,k,action:{|d|~mappingresult.set(i,d);});
 		s.sync;
 		i.postln;
 	}