prerelease tidy up

release-packaging/Examples/dataset/1-learning examples/1a-starting-1D-example.scd

@@ -43,7 +43,7 @@ Routine{
 }.play
 )
 
-~labels = FluidLabelSet(s,\simple1label);
+~labels = FluidLabelSet(s);
 
 ~kmeans.predict(~ds,~labels, {|x| ("Size of each cluster" +  x).postln})
 

release-packaging/Examples/dataset/1-learning examples/2a-starting-1D-example2.scd

@@ -47,7 +47,7 @@ Routine{
 }.play
 )
 
-~labels = FluidLabelSet(s,\simple1label);
+~labels = FluidLabelSet(s);
 
 ~kmeans.predict(~ds,~labels, {|x| ("Size of each cluster" +  x).postln})
 

release-packaging/Examples/dataset/1-learning examples/7a-making-datasets-with-json.scd

@@ -8,7 +8,7 @@
 ~dict.add(\cols -> 10)
 
 //create a dataset, then loading the dictionary
-~ds = FluidDataSet.new(s,\simple1data);
+~ds =  FluidDataSet(s);
 ~ds.load(~dict)
 ~ds.print
 
@@ -33,7 +33,7 @@
 ~dict2.add(\cols -> 1)
 
 // creating a labelset and loading the dictionary
-~ls = FluidLabelSet.new(s,\simplelabel);
+~ls =  FluidLabelSet(s);
 ~ls.load(~dict2)
 ~ls.print
 

release-packaging/Examples/dataset/1-learning examples/8c-mlp-regressor-as-dim-redux.scd

@@ -34,10 +34,10 @@ FluidBufMelBands.process(s,~audio, features: ~melfeatures,action: {\done.postln;
 	dsWr = FluidDataSetWr.kr(~raw, buf: buf, trig: Done.kr(stats));
 	LocalOut.kr( Done.kr(dsWr));
 	FreeSelf.kr(count - 99);
-	Poll.kr(trig,count);
+	Poll.kr(trig,(100-count));
 }.play;
 )
-// wait for the post window to acknoledge the job is done. Check the dataset if curious (loads of small numbers)
+// wait for the count to reaches 0 in the post window. Check the dataset if curious (loads of small numbers)
 ~raw.print;
 
 // normalize the input

release-packaging/HelpSource/Classes/FluidAmpSlice.schelp

@@ -70,7 +70,7 @@ code::
 // another solution: minslicelength
 (
 {var env, source = SinOsc.ar(320,0,LFSaw.ar(20, 0, -0.4, 0.6));
-	env = FluidAmpSlice.ar(source,fastRampUp: 5,fastRampDown: 50,slowRampUp: 220,slowRampDown: 220, onThreshold: 10, offThreshold: 7,floor: -60, minSliceLength: 220);
+	env = FluidAmpSlice.ar(source,fastRampUp: 5,fastRampDown: 50,slowRampUp: 220,slowRampDown: 220, onThreshold: 10, offThreshold: 7,floor: -60, minSliceLength: 441);
 	[source, env]
 }.plot(0.08);
 )

release-packaging/HelpSource/Classes/FluidDataSet.schelp

@@ -89,7 +89,7 @@ d = Dictionary.new;
 d.add(\cols -> 1);
 d.add(\data -> Dictionary.newFrom(10.collect{|i|[i.asString, [i.asFloat]]}.flatten));
 fork{
-    ~ds = FluidDataSet.new(s); s.sync;
+    ~ds = FluidDataSet.new(s);
     ~ds.load(d); s.sync;
     ~ds.dump; s.sync; ~ds.free;
 }

release-packaging/HelpSource/Classes/FluidDataSetQuery.schelp

@@ -160,9 +160,9 @@ code::
 //this is how to join 2 datasets, adding columns to items with the same label
 //create 3 datasets
 (
-~dsA = FluidDataSet.new(s,\joinA);
-~dsB = FluidDataSet.new(s,\joinB);
-~dsC = FluidDataSet.new(s,\joinC);
+~dsA =  FluidDataSet(s);
+~dsB =  FluidDataSet(s);
+~dsC =  FluidDataSet(s);
 )
 
 //feed them items with almost overlaping label lists but with different dimensions

release-packaging/HelpSource/Classes/FluidDataSetWr.schelp

@@ -45,7 +45,7 @@ EXAMPLES::
 code::
 s.reboot;
 (
-~ds = FluidDataSet(s,\FluidDataSetWr);
+~ds = FluidDataSet(s);
 )
 
 (

release-packaging/HelpSource/Classes/FluidKDTree.schelp

@@ -52,12 +52,11 @@ code::
 s.reboot;
 (
 fork{
-    ~ds = FluidDataSet.new(s,\kdtree_help_rand2d);
-    d = Dictionary.with(
-        *[\cols -> 2,\data -> Dictionary.newFrom(
-            100.collect{|i| [i, [ 1.0.linrand,1.0.linrand]]}.flatten)]);
-    s.sync;
-    ~ds.load(d, {~ds.print});
+	d = Dictionary.with(
+		*[\cols -> 2,\data -> Dictionary.newFrom(
+			100.collect{|i| [i, [ 1.0.linrand,1.0.linrand]]}.flatten)]);
+	~ds = FluidDataSet(s);
+	~ds.load(d, {~ds.print});
 }
 )
 
@@ -106,7 +105,7 @@ fork{
 )
 
 // enter a valid radius.
-~tree.radius = 0.05;
+~tree.radius = 0.1;
 // FluidKDTree will return only values that are within that radius, up to numNeighbours values
 (
 ~tmpbuf = Buffer.loadCollection(s, ~p, 1, {
@@ -139,7 +138,7 @@ Routine{
         var point = 2.collect{TRand.kr(0,1,trig)};
         point.collect{|p,i| BufWr.kr([p],inputBuffer,i)};
         ~tree.kr(trig,inputBuffer,outputBuffer,5,nil);
-        Poll.kr(trig, BufRd.kr(1,outputBuffer,Array.iota(5)),5.collect{|i| "Neighbour" + i});
+		Poll.kr(trig, BufRd.kr(1,outputBuffer,Array.iota(10)),10.collect{|i| "Neighbour" + (i/2).asInteger ++ "-" ++ (i.mod(2))});
         Silent.ar;
     }.play;
 }.play;
@@ -148,12 +147,11 @@ Routine{
 //Using a lookup data set instead:
 //here we populate with numbers that are in effect the indicies, but it could be anything numerical that will be returned on the server-side and would be usable on that side
 (
-~dsL = FluidDataSet.new(s);
 fork{
-    d = Dictionary.with(
-        *[\cols -> 1,\data -> Dictionary.newFrom(
-            100.collect{|i| [i, [ i ]]}.flatten)]);
-    s.sync;
+	d = Dictionary.with(
+		*[\cols -> 1,\data -> Dictionary.newFrom(
+			100.collect{|i| [i, [ i ]]}.flatten)]);
+	~dsL = FluidDataSet.new(s);
 	~dsL.load(d, {~dsL.print});
 }
 )
@@ -169,10 +167,9 @@ Routine{
         var point = 2.collect{TRand.kr(0,1,trig)};
         point.collect{|p,i| BufWr.kr([p],inputBuffer,i)};
         ~tree.kr(trig,inputBuffer,outputBuffer,5,~dsL);
-        Poll.kr(trig, BufRd.kr(1,outputBuffer,Array.iota(5)),5.collect{|i| "Neighbour" + i});
+		Poll.kr(trig, BufRd.kr(1,outputBuffer,Array.iota(5)),5.collect{|i| "Neighbour" + i});
         Silent.ar;
     }.play;
 }.play;
 )
 ::
-

release-packaging/HelpSource/Classes/FluidKMeans.schelp

@@ -75,7 +75,7 @@ code::
 		       64.collect{(1.sum3rand) + [1,-1].choose}.clump(2)
 	       }).flatten(1) * 0.5;
 fork{
-    ~dataSet = FluidDataSet.new(s,\kmeans_help_rand2d);
+    ~dataSet =  FluidDataSet(s);
     d = Dictionary.with(
         *[\cols -> 2,\data -> Dictionary.newFrom(
 			~points.collect{|x, i| [i, x]}.flatten)]);

release-packaging/HelpSource/Classes/FluidKNNRegressor.schelp

@@ -106,7 +106,7 @@ d = Dictionary.with(
 
 //We should see a single cycle of a chirp
 ~outputdata.plot;
-s.dumpOSC
+
 // single point transform on arbitrary value
 ~inbuf = Buffer.loadCollection(s,[0.5]);
 ~regressor.predictPoint(~inbuf,{|x|x.postln;});
@@ -115,7 +115,7 @@ s.dumpOSC
 subsection:: Server Side Queries
 
 code::
-//Setup
+//we are here querying with a saw in control rate, all on the server, via a buffer interface
 (
 {
 	var input = Saw.kr(2).linlin(-1,1,0,1);
@@ -124,7 +124,7 @@ code::
     var outputPoint = LocalBuf(1);
 	BufWr.kr(input,inputPoint,0);
     ~regressor.kr(trig,inputPoint,outputPoint);
-    BufRd.kr(1,outputPoint,0);//,"mapped value")
+    BufRd.kr(1,outputPoint,0);
 }.scope
 )
 

release-packaging/HelpSource/Classes/FluidMDS.schelp

@@ -1,7 +1,7 @@
 TITLE:: FluidMDS
 summary:: Dimensionality Reduction with Multidimensional Scaling
 categories:: Dimensionality Reduction, Data Processing
-related:: Classes/FluidMDS, Classes/FluidDataSet
+related:: Classes/FluidPCA, Classes/FluidDataSet
 
 DESCRIPTION::
 
@@ -99,10 +99,10 @@ FluidBufMFCC.process(s,~audio, features: ~mfcc_feature);
 	dsWr = FluidDataSetWr.kr(~raw, buf: buf, trig: Done.kr(stats),blocking:1);
     LocalOut.kr(Done.kr(dsWr));
     FreeSelf.kr(count - 99);
-	Poll.kr(trig,count);
+	Poll.kr(trig,(100-count));
 }.play;
 )
-// wait for the post window to acknoledge the job is done.
+// wait for the count to reaches 0 in the post window.
 
 //First standardize our DataSet, so that the MFCC dimensions are on comensurate scales
 //Then apply the MDS in-place on the standardized data to get 2 dimensions, using a Euclidean distance metric

release-packaging/HelpSource/Classes/FluidNormalize.schelp

@@ -69,8 +69,8 @@ s.boot;
 // FluidNormalize.dumpAllMethods
 (
 ~audiofile = File.realpath(FluidBufPitch.class.filenameSymbol).dirname +/+ "../AudioFiles/Tremblay-ASWINE-ScratchySynth-M.wav";
-~raw = FluidDataSet(s,\norm_help_raw);
-~norm = FluidDataSet(s,\norm_help_normd);
+~raw = FluidDataSet(s);
+~norm = FluidDataSet(s);
 ~pitch_feature = Buffer.new(s);
 ~stats = Buffer.alloc(s, 7, 2);
 ~normalizer = FluidNormalize(s);

release-packaging/HelpSource/Classes/FluidPCA.schelp

@@ -102,10 +102,10 @@ FluidBufMFCC.process(s,~audio, features: ~mfcc_feature,action:{"Done MFCCs".post
 	dsWr = FluidDataSetWr.kr(~raw, buf: buf, trig: Done.kr(stats));
 	LocalOut.kr( Done.kr(dsWr));
 	FreeSelf.kr(count - 99);
-	Poll.kr(trig,count);
+	Poll.kr(trig,(100 - count));
 }.play;
 )
-// wait for the post window to acknoledge the job is done.
+// wait for the count to reaches 0 in the post window.
 
 //First standardize our DataSet, so that the MFCC dimensions are on comensurate scales
 //Then apply the PCA in-place on the standardized data

release-packaging/HelpSource/Classes/FluidProcessSlices.schelp

@@ -93,7 +93,7 @@ s.reboot;
 ~slicer = FluidSliceCorpus({ |src,start,num,dest|
 		FluidBufOnsetSlice.kr(src,start,num,indices:dest, threshold:2)
 });
-~pitchdata = FluidDataSet(s,\FluidProcessSlicesHelp);
+~pitchdata = FluidDataSet(s);
 ~pitchbufs = 4.collect{Buffer.new};
 ~statsbufs = 4.collect{Buffer.new};
 )

release-packaging/HelpSource/Classes/FluidUMAP.schelp

@@ -223,9 +223,6 @@ w.front;
 ~standardizer.transformPoint(~sourcePoint,~standed);
 ~umap.transformPoint(~standed, ~umaped, {~umaped.getn(0,2,{|x|x.postln})})
 
-//poking at the data structure within
-~umap.dump{|x|x.keys.do{|i|"%: %\n".postf(i,x[i]);}}
-
 // one can also retrieve in control rate with Server Side Queries
 // Let's map our learned UMAP dimensions to the controls of a processor