From caff6c3c297ec2ec6a198f1024ffb032954df3ba Mon Sep 17 00:00:00 2001
From: Pierre Alexandre Tremblay <info@pierrealexandretremblay.com>
Date: Mon, 21 Dec 2020 09:24:15 +0000
Subject: [PATCH] umap: improved class definition and help example

---
 release-packaging/Classes/FluidUMAP.sc        |  3 --
 .../HelpSource/Classes/FluidUMAP.schelp       | 40 ++++++++++++++++---
 2 files changed, 34 insertions(+), 9 deletions(-)

diff --git a/release-packaging/Classes/FluidUMAP.sc b/release-packaging/Classes/FluidUMAP.sc
index 00c459e..bf4f252 100644
--- a/release-packaging/Classes/FluidUMAP.sc
+++ b/release-packaging/Classes/FluidUMAP.sc
@@ -50,8 +50,5 @@ FluidUMAP : FluidModelObject {
 
 	// not implemented
 	cols {|action|}
-	read{|filename,action|}
-	write{|filename,action|}
 	size { |action|}
-
 }
diff --git a/release-packaging/HelpSource/Classes/FluidUMAP.schelp b/release-packaging/HelpSource/Classes/FluidUMAP.schelp
index 9d1ac1e..9c63a7c 100644
--- a/release-packaging/HelpSource/Classes/FluidUMAP.schelp
+++ b/release-packaging/HelpSource/Classes/FluidUMAP.schelp
@@ -52,7 +52,7 @@ code::
 ~reduced = FluidDataSet(s);
 ~normalized = FluidDataSet(s);
 ~standardizer  = FluidStandardize(s);
-~normalizer = FluidNormalize(s);
+~normalizer = FluidNormalize(s, 0.05, 0.95);
 ~umap = FluidUMAP(s).numDimensions_(2).numNeighbours_(5).minDist_(0.2).iterations_(50).learnRate_(0.2);
 )
 
@@ -93,10 +93,7 @@ w.front;
 )
 
 //play with parameters
-~umap.numNeighbours = 10;
-~umap.minDist = 0.5;
-~umap.learnRate = 0.1;
-~umap.iterations = 100;
+~umap.numNeighbours_(10).minDist_(0.5).iterations_(100).learnRate_(0.1);
 
 //rerun the UMAP
 ~umap.fitTransform(~standardized,~reduced,action:{"Finished UMAP".postln});
@@ -166,6 +163,37 @@ w.front;
 });
 )
 
-//same process as above in 2 passes maybe?
+//if we process the original dataset, we will see small differences in positions
+~reduced2 = FluidDataSet(s);
+~umap.transform(~standardized, ~reduced2, action: {\done.postln;});
+
+//then we can draw and look
+(
+~normalizer.transform(~reduced2,~normalized,action:{
+	"Normalized Output".postln;
+	~normalized.dump{|x|
+		~normalizedDict = x["data"];
+		{
+			t = Window("old material", Rect(728, 64, 200, 200));
+			t.drawFunc = {
+				Pen.use {
+					~normalizedDict.keysValuesDo{|key, val|
+						Pen.fillColor = Color.new(~colours[key.asSymbol][0], ~colours[key.asSymbol][1],~colours[key.asSymbol][2]);
+						Pen.fillOval(Rect((val[0] * 200), (val[1] * 200), 5, 5));
+						~colours[key.asSymbol].flat;
+					};
+				};
+			};
+			t.refresh;
+			t.front;
+		}.defer;
+	};
+});
+)
+
+//this is because the fitTransform method has the advantage of being certain that the data it transforms is the one that has been used to fit the model. This allows for more accurate distance measurement.
+
+//poking at the data structure within
+~umap.dump{|x|x.keys.do{|i|"%: %\n".postf(i,x[i]);}}
 
 ::