[tremblap]

fixes #120

I removed the nonsensical condition, and added 2 asserts to make sure we get the right values passed, assuming that a dataset with at least one point will have the right type. Maybe @weefuzzy will want to change the checking - I also thought of checking that the passed info was a vector of float instead of the asserts, and maybe that would be better. I'm opened to suggestions.

[tremblap]

example code to check in SC:

// make and plot a dataset with 5 globs
(
fork{defer{
	var counter = 0;
	var dict = Dictionary.newFrom(["cols",2,"data",Dictionary.new]);
	var xybuf = Buffer.alloc(s,2);

	1000.do{
		arg i;
		var x = [-0.7,0.7,0,0.7,-0.7][i % 5];
		var y = [-0.7,0.7,0,-0.7,0.7][i % 5];
		x = gauss(x,0.1).clip(-1,1);
		y = gauss(y,0.1).clip(-1,1);
		dict["data"][i] = [x,y];
	};

	~mean_seeds = FluidDataSet(s);

	~fp = FluidPlotter(bounds:Rect(0,0,800,800), xmin: -1, ymin: -1, dict:dict,mouseMoveAction:{
		arg view, x, y ...a;
		a[2] !? {
			xybuf.setn(0,[x,y]);
			~mean_seeds.addPoint(counter,xybuf,{
				counter = counter + 1;
				~mean_seeds.print;
			});
		};
	});
}}
)

// click to place at least 5 centroids, then run this code for kmean

(
~ds = FluidDataSet(s).load(~fp.dict);

~kmeans = FluidKMeans(s).setMeans(~mean_seeds);
~labels = FluidLabelSet(s);
~kmeans.predict(~ds,~labels,{
	~labels.dump({
		arg labels;
		~fp.categories_(labels);
	});
});
)

// same with skmean

(
~ds = FluidDataSet(s).load(~fp.dict);

~skmeans = FluidSKMeans(s).setMeans(~mean_seeds);
~labels = FluidLabelSet(s);
~skmeans.predict(~ds,~labels,{
	~labels.dump({
		arg labels;
		~fp.categories_(labels);
	});
});
)