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all interface unified with C++ code and style

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nix
Pierre Alexandre Tremblay 6 years ago
parent a56de773d2
commit 13af5e9c6e
21 changed files with 130 additions and 134 deletions
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4
release-packaging/Classes/FluidDataSetQuery.sc
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@ -41,8 +41,8 @@ FluidDataSetQuery : FluidManipulationClient {
this.prSendMsg(\limit, [rows], action);
}
transform{|sourceDataset, destDataset, action|
this.prSendMsg(\transform,[sourceDataset.asSymbol, destDataset.asSymbol],action);
transform{|sourceDataSet, destDataSet, action|
this.prSendMsg(\transform,[sourceDataSet.asSymbol, destDataSet.asSymbol],action);
}
}

9
release-packaging/Classes/FluidKDTree.sc
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@ -9,7 +9,7 @@ FluidKDTree : FluidDataClient {
var values = [numNeighbours] ++ this.prServerString(lookupDataSet.asSymbol);
var params = [names,values].lace;
/* env = Environment();
synthControls[1..].do{|x|
@ -17,14 +17,13 @@ FluidKDTree : FluidDataClient {
};
env.put(\numNeighbours,1); */
^super.new1(server,params);
^super.new1(server,params);
/* env,
[\numNeighbours]++lookupDataSet); */
}
fit{|dataset,action|
dataset.asSymbol.postln;
this.prSendMsg(\fit, [dataset.asSymbol], action);
fit{|dataSet,action|
this.prSendMsg(\fit, [dataSet.asSymbol], action);
}
kNearest{ |buffer, action|

14
release-packaging/Classes/FluidKMeans.sc
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@ -1,26 +1,26 @@
FluidKMeans : FluidDataClient {
*new {|server, numClusters = 4, maxIter = 100|
^super.new1(server,[\numClusters,numClusters,\maxIter,maxIter]);
^super.new1(server,[\numClusters,numClusters,\maxIter,maxIter]);
}
fit{|dataset,action|
fit{|dataSet,action|
this.prSendMsg(\fit,
[dataset.asSymbol], action,
[dataSet.asSymbol], action,
[numbers(FluidMessageResponse,_,this.numClusters,_)]
);
}
fitPredict{|dataset, labelset,action|
fitPredict{|dataSet, labelSet,action|
this.prSendMsg(\fitPredict,
[dataset.asSymbol,labelset.asSymbol],
[dataSet.asSymbol,labelSet.asSymbol],
action,[numbers(FluidMessageResponse,_,this.numClusters,_)]
);
}
predict{ |dataset, labelset,action|
predict{ |dataSet, labelSet,action|
this.prSendMsg(\predict,
[dataset.asSymbol, labelset.asSymbol], action,
[dataSet.asSymbol, labelSet.asSymbol], action,
[numbers(FluidMessageResponse,_,this.numClusters,_)]
);
}

8
release-packaging/Classes/FluidKNNClassifier.sc
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@ -4,13 +4,13 @@ FluidKNNClassifier : FluidDataClient {
^super.new1(server,[\numNeighbours,numNeighbours,\weight,weight]);
}
fit{|dataset, labelset, action|
this.prSendMsg(\fit,[dataset.asSymbol, labelset.asSymbol], action);
fit{|dataSet, labelSet, action|
this.prSendMsg(\fit,[dataSet.asSymbol, labelSet.asSymbol], action);
}
predict{|dataset, labelset, action|
predict{|dataSet, labelSet, action|
this.prSendMsg(\predict,
[dataset.asSymbol, labelset.asSymbol],
[dataSet.asSymbol, labelSet.asSymbol],
action);
}

8
release-packaging/Classes/FluidKNNRegressor.sc
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@ -4,16 +4,16 @@ FluidKNNRegressor : FluidDataClient {
^super.new1(server,[\numNeighbours,numNeighbours,\weight,weight]);
}
fit{|sourceDataset, targetDataset, action|
fit{|sourceDataSet, targetDataSet, action|
this.prSendMsg(\fit,
[sourceDataset.asSymbol, targetDataset.asSymbol],
[sourceDataSet.asSymbol, targetDataSet.asSymbol],
action
);
}
predict{ |sourceDataset, targetDataset,action|
predict{ |sourceDataSet, targetDataSet,action|
this.prSendMsg(\predict,
[sourceDataset.asSymbol, targetDataset.asSymbol],
[sourceDataSet.asSymbol, targetDataSet.asSymbol],
action);
}

4
release-packaging/Classes/FluidMDS.sc
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@ -16,9 +16,9 @@ FluidMDS : FluidManipulationClient {
id = uid;
}
fitTransform{|sourceDataset, destDataset, k, dist, action|
fitTransform{|sourceDataSet, destDataSet, numDimensions, distanceMetric, action|
this.prSendMsg(\fitTransform,
[sourceDataset.asSymbol, destDataset.asSymbol, k, dist], action);
[sourceDataSet.asSymbol, destDataSet.asSymbol, numDimensions, distanceMetric], action);
}
// not implemented

8
release-packaging/Classes/FluidMLPRegressor.sc
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@ -15,16 +15,16 @@ FluidMLPRegressor : FluidManipulationClient {
id = uid;
}
fit{|sourceDataset, targetDataset, action|
fit{|sourceDataSet, targetDataSet, action|
this.prSendMsg(\fit,
[sourceDataset.asSymbol, targetDataset.asSymbol],
[sourceDataSet.asSymbol, targetDataSet.asSymbol],
action,numbers(FluidMessageResponse,_,1,_)
);
}
predict{ |sourceDataset, targetDataset, layer, action|
predict{ |sourceDataSet, targetDataSet, layer, action|
this.prSendMsg(\predict,
[sourceDataset.asSymbol, targetDataset.asSymbol,layer],
[sourceDataSet.asSymbol, targetDataSet.asSymbol,layer],
action);
}

12
release-packaging/Classes/FluidNormalize.sc
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@ -4,19 +4,19 @@ FluidNormalize : FluidDataClient {
^super.new1(server,[\min,min,\max,max]);
}
fit{|dataset, action|
this.prSendMsg(\fit,[dataset.asSymbol], action);
fit{|dataSet, action|
this.prSendMsg(\fit,[dataSet.asSymbol], action);
}
transform{|sourceDataset, destDataset, action|
transform{|sourceDataSet, destDataSet, action|
this.prSendMsg(\transform,
[sourceDataset.asSymbol, destDataset.asSymbol], action
[sourceDataSet.asSymbol, destDataSet.asSymbol], action
);
}
fitTransform{|sourceDataset, destDataset, action|
fitTransform{|sourceDataSet, destDataSet, action|
this.prSendMsg(\fitTransform,
[sourceDataset.asSymbol, destDataset.asSymbol], action
[sourceDataSet.asSymbol, destDataSet.asSymbol], action
);
}

12
release-packaging/Classes/FluidPCA.sc
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@ -4,16 +4,16 @@ FluidPCA : FluidDataClient {
^super.new1(server,[\numDimensions,numDimensions]);
}
fit{|dataset, action|
this.prSendMsg(\fit,[dataset.asSymbol], action);
fit{|dataSet, action|
this.prSendMsg(\fit,[dataSet.asSymbol], action);
}
transform{|sourceDataset, destDataset, action|
this.prSendMsg(\transform,[sourceDataset.asSymbol, destDataset.asSymbol], action);
transform{|sourceDataSet, destDataSet, action|
this.prSendMsg(\transform,[sourceDataSet.asSymbol, destDataSet.asSymbol], action);
}
fitTransform{|sourceDataset, destDataset, action|
this.prSendMsg(\fitTransform,[sourceDataset.asSymbol, destDataset.asSymbol], action);
fitTransform{|sourceDataSet, destDataSet, action|
this.prSendMsg(\fitTransform,[sourceDataSet.asSymbol, destDataSet.asSymbol], action);
}

12
release-packaging/Classes/FluidStandardize.sc
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@ -1,17 +1,17 @@
FluidStandardize : FluidDataClient {
fit{|dataset, action|
this.prSendMsg(\fit, [dataset.asSymbol], action);
fit{|dataSet, action|
this.prSendMsg(\fit, [dataSet.asSymbol], action);
}
transform{|sourceDataset, destDataset, action|
transform{|sourceDataSet, destDataSet, action|
this.prSendMsg(\transform,
[sourceDataset.asSymbol, destDataset.asSymbol], action
[sourceDataSet.asSymbol, destDataSet.asSymbol], action
);
}
fitTransform{|sourceDataset, destDataset, action|
fitTransform{|sourceDataSet, destDataSet, action|
this.prSendMsg(\fitTransform,
[sourceDataset.asSymbol, destDataset.asSymbol], action
[sourceDataSet.asSymbol, destDataSet.asSymbol], action
);
}

16
release-packaging/HelpSource/Classes/FluidDataSet.schelp
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@ -11,12 +11,12 @@ CLASSMETHODS::
PRIVATE:: asUGenInput
METHOD:: new
Create a new instance of the dataset, with the given name. If a Dataset with this name already exists, an exception will be thrown (see link::Classes/FluidDataSet#at:: to access an extant Dataset).
Create a new instance of the DataSet, with the given name. If a DataSet with this name already exists, an exception will be thrown (see link::Classes/FluidDataSet#at:: to access an existant DataSet).
ARGUMENT:: server
The link::Classes/Server:: on which to create the data set.
ARGUMENT:: name
A symbol with the name of the dataset.
A symbol with the name of the DataSet.
​
returns:: The new instance
@ -24,9 +24,9 @@ METHOD:: at
Retrieves a cached instance of a FluidDataSet with the given name, or returns nil if no such object exists.
ARGUMENT:: server
The server associated with this dataset instance.
The server associated with this DataSet instance.
ARGUMENT:: name
The name of the Dataset to retrieve from the cache.
The name of the DataSet to retrieve from the cache.
INSTANCEMETHODS::
@ -34,8 +34,8 @@ INSTANCEMETHODS::
PRIVATE:: init,id,cache
METHOD:: addPoint
Add a new point to the data set. The dimensionality of the dataset is governed by the size of the first point added.
Will report an error if the label already exists, or if the size of the data does not match the dimensionality of the dataset.
Add a new point to the data set. The dimensionality of the DataSet is governed by the size of the first point added.
Will report an error if the label already exists, or if the size of the data does not match the dimensionality of the DataSet.
ARGUMENT:: label
A symbol or string with the label for the new point.
ARGUMENT:: buffer
@ -44,7 +44,7 @@ ARGUMENT:: action
A function to run when the point has been added.
​​
METHOD:: updatePoint
Update an existing label's data. Will report an error if the label doesn't exist, or if the size of the data does not match the given dimensionality of the dataset.
Update an existing label's data. Will report an error if the label doesn't exist, or if the size of the data does not match the given dimensionality of the DataSet.
METHOD:: getPoint
Retrieve a point from the data set into a link::Classes/Buffer::. Will report an error if the label or buffer doesn't exist​.
@ -59,7 +59,7 @@ METHOD:: free
Destroy the object on the server.
METHOD:: print
Post an abbreviated content of the dataset in the window by default, but you can supply a custom action instead.
Post an abbreviated content of the DataSet in the window by default, but you can supply a custom action instead.
​​
METHOD:: synth
The internal synth the object uses to communicate with the server

22
release-packaging/HelpSource/Classes/FluidDataSetQuery.schelp
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@ -84,10 +84,10 @@ Run when done
METHOD:: transform
Apply the query to a source link::Classes/FluidDataSet:: and write to a destination. Can be the same.
ARGUMENT:: sourceDataset
Source data, or the dataset name
ARGUMENT:: destDataset
Destination data, or the dataset name
ARGUMENT:: sourceDataSet
Source data, or the DataSet name
ARGUMENT:: destDataSet
Destination data, or the DataSet name
ARGUMENT:: action
Run when done
@ -99,19 +99,19 @@ code::
s.boot;
// Create a dataset with random data
~dataset= FluidDataSet(s,\help_fluid_dataset_query);
// Create a DataSet with random data
~dataSet= FluidDataSet(s,\help_fluid_dataset_query);
(
~points = 100.collect{24.collect{100.rand}};
~dataset.clear;
~dataSet.clear;
~tmpbuf = Buffer.alloc(s,24);
fork{
s.sync;
~points.do{|x,i|
~tmpbuf.setn(0,x);
~dataset.addPoint(i,~tmpbuf);
~dataSet.addPoint(i,~tmpbuf);
s.sync
}
}
@ -128,12 +128,12 @@ fork{
~query.and(2,"<",50);
~query.limit(10);
// Create an output dataset and run the query
// Create an output DataSet and run the query
~out = FluidDataSet(s,\help_fluid_dataset_query_out);
~query.transform(~dataset, ~out);
~query.transform(~dataSet, ~out);
// Check the results
~dataset.print;
~dataSet.print;
~out.print;

8
release-packaging/HelpSource/Classes/FluidKDTree.schelp
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@ -23,7 +23,7 @@ INSTANCEMETHODS::
METHOD:: fit
Build the tree by scanning the points of a LINK::Classes/FluidDataSet::
ARGUMENT:: dataset
ARGUMENT:: dataSet
The LINK::Classes/FluidDataSet:: of interest. This can either be a data set object itself, or the name of one.
ARGUMENT:: action
A function to run when indexing is complete.
@ -48,7 +48,7 @@ EXAMPLES::
code::
// Make a dataset of random 23D points
// Make a DataSet of random 23D points
s.boot;
(
fork{
@ -61,10 +61,10 @@ fork{
}
)
// Make a new tree, and fit it to the dataset
// Make a new tree, and fit it to the DataSet
~tree = FluidKDTree(s,numNeighbours:5,lookupDataSet:~ds);
//Fit it to the dataset
//Fit it to the DataSet
~tree.fit(~ds);
// Should be 100 points, 2 columns

26
release-packaging/HelpSource/Classes/FluidKMeans.schelp
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@ -26,25 +26,25 @@ PRIVATE::k
METHOD:: fit
Identify code::k:: clusters in a link::Classes/FluidDataSet::
ARGUMENT:: dataset
ARGUMENT:: dataSet
A link::Classes/FluidDataSet:: of data points.
ARGUMENT:: action
A function to run when fitting is complete, taking as its argument an array with the number of data points for each cluster.
METHOD:: predict
Given a trained object, return the cluster ID for each data point in a dataset to a label set.
ARGUMENT:: dataset
Given a trained object, return the cluster ID for each data point in a DataSet to a label set.
ARGUMENT:: dataSet
a link::Classes/FluidDataSet:: containing the data to predict.
ARGUMENT:: labelset
ARGUMENT:: labelSet
a link::Classes/FluidLabelSet:: to retrieve the predicted clusters.
ARGUMENT:: action
A function to run when the server responds.
METHOD:: fitPredict
Run link::Classes/FluidKMeans#*fit:: and link::Classes/FluidKMeans#*predict:: in a single pass: i.e. train the model on the incoming link::Classes/FluidDataSet:: and then return the learned clustering to the passed link::Classes/FluidLabelSet::
ARGUMENT:: dataset
ARGUMENT:: dataSet
a link::Classes/FluidDataSet:: containing the data to fit and predict.
ARGUMENT:: labelset
ARGUMENT:: labelSet
a link::Classes/FluidLabelSet:: to retrieve the predicted clusters.
ARGUMENT:: action
A function to run when the server responds
@ -58,9 +58,9 @@ A function to run when the server responds, taking the ID of the cluster as its
METHOD:: predict
Report cluster assignments for previously unseen data.
ARGUMENT:: dataset
ARGUMENT:: dataSet
A link::Classes/FluidDataSet:: of data points.
ARGUMENT:: labelset
ARGUMENT:: labelSet
A link::Classes/FluidLabelSet:: to contain assignments.
ARGUMENT:: action
A function to run when complete, taking an array of the counts for each category as its argument.
@ -71,17 +71,17 @@ Server.default.options.outDevice = "Built-in Output"
code::
(
//Make some clumped 2D points and place into a dataset
//Make some clumped 2D points and place into a DataSet
~points = (4.collect{
64.collect{(1.sum3rand) + [1,-1].choose}.clump(2)
}).flatten(1) * 0.5;
fork{
~dataset = FluidDataSet.new(s,\kmeans_help_rand2d);
~dataSet = FluidDataSet.new(s,\kmeans_help_rand2d);
d = Dictionary.with(
*[\cols -> 2,\data -> Dictionary.newFrom(
~points.collect{|x, i| [i, x]}.flatten)]);
s.sync;
~dataset.load(d, {~dataset.print});
~dataSet.load(d, {~dataSet.print});
}
)
@ -92,7 +92,7 @@ fork{
// Fit into 4 clusters
(
~kmeans.fitPredict(~dataset,~clusters,action: {|c|
~kmeans.fitPredict(~dataSet,~clusters,action: {|c|
"Fitted.\n # Points in each cluster:".postln;
c.do{|x,i|
("Cluster" + i + "->" + x.asInteger + "points").postln;
@ -100,7 +100,7 @@ fork{
});
)
// Cols of kmeans should match dataset, size is the number of clusters
// Cols of kmeans should match DataSet, size is the number of clusters
~kmeans.cols;
~kmeans.size;
~kmeans.dump;

19
release-packaging/HelpSource/Classes/FluidKNNClassifier.schelp
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@ -22,18 +22,18 @@ INSTANCEMETHODS::
METHOD:: fit
Fit the model to a source link::Classes/FluidDataSet:: and a target link::Classes/FluidLabelSet::. These need to be the same size
ARGUMENT:: dataset
ARGUMENT:: dataSet
Source data
ARGUMENT:: labelset
ARGUMENT:: labelSet
Labels for the source data
ARGUMENT:: action
Run when done
METHOD:: predict
Given a fitted model, predict labels for a link::Classes/FluidDataSet:: and write these to a link::Classes/FluidLabelSet::
ARGUMENT:: dataset
ARGUMENT:: dataSet
data to predict labels for
ARGUMENT:: labelset
ARGUMENT:: labelSet
place to write labels
ARGUMENT:: action
Run when done
@ -52,8 +52,8 @@ code::
// Make:
// - A KNN Classifier
// - A dataset of example points, and a label set of corresponding labels
// - A dataset of test data and a labelset for predicted labels
// - A DataSet of example points, and a label set of corresponding labels
// - A DataSet of test data and a LabelSet for predicted labels
(
~classifier = FluidKNNClassifier(s);
@ -63,7 +63,7 @@ code::
~mapping = FluidLabelSet(s,\knnclassify_help_mapping);
)
//Make some clumped 2D points and place into a dataset
//Make some clumped 2D points and place into a DataSet
(
~examplepoints = [[0.5,0.5],[-0.5,0.5],[0.5,-0.5],[-0.5,-0.5]];
~examplelabels = [\red,\orange,\green,\blue];
@ -87,7 +87,7 @@ d = Dictionary.with(
)
//Fit the classifier to the example dataset and labels, and then run prediction on the test data into our mapping label set
//Fit the classifier to the example DataSet and labels, and then run prediction on the test data into our mapping label set
(
~classifier.fit(~source,~labels);
~classifier.predict(~test, ~mapping, 1);
@ -193,6 +193,3 @@ code::
}.play(~classifier.synth,addAction:\addAfter);
)
::

12
release-packaging/HelpSource/Classes/FluidKNNRegressor.schelp
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@ -22,20 +22,20 @@ Whether to weight neighbours by distance when producing new point
INSTANCEMETHODS::
METHOD:: fit
Map a source link::Classes/FluidDataSet:: to a one-dimensional target; both datasets need to have the same number of points.
ARGUMENT:: sourceDataset
Map a source link::Classes/FluidDataSet:: to a one-dimensional target; both DataSets need to have the same number of points.
ARGUMENT:: sourceDataSet
Source data
ARGUMENT:: targetDataset
ARGUMENT:: targetDataSet
Target data
ARGUMENT:: action
Run when done
METHOD:: predict
Apply learned mapping to a link::Classes/FluidDataSet:: and write to an output dataset
ARGUMENT:: sourceDataset
Apply learned mapping to a link::Classes/FluidDataSet:: and write to an output DataSet
ARGUMENT:: sourceDataSet
data to regress
ARGUMENT:: targetDataset
ARGUMENT:: targetDataSet
output data
ARGUMENT:: action
Run when done

16
release-packaging/HelpSource/Classes/FluidMDS.schelp
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@ -45,13 +45,13 @@ PRIVATE:: init
METHOD:: fitTransform
Fit the model to a link::Classes/FluidDataSet:: and write the new projected data to a destination FluidDataSet.
ARGUMENT:: sourceDataset
Source data, or the dataset name
ARGUMENT:: destDataset
Destination data, or the dataset name
ARGUMENT:: k
ARGUMENT:: sourceDataSet
Source data, or the DataSet name
ARGUMENT:: destDataSet
Destination data, or the DataSet name
ARGUMENT:: numDimensions
The number of dimensions to reduce to
ARGUMENT:: dist
ARGUMENT:: distanceMetric
The distance metric to use (integer, 0-6, see flags above)
ARGUMENT:: action
Run when done
@ -105,9 +105,9 @@ FluidBufMFCC.process(s,~audio, features: ~mfcc_feature);
//First standardize our dataset, so that the MFCC dimensions are on comensurate scales
//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
//Download the dataset contents into an array for plotting
//Download the DataSet contents into an array for plotting
(
~reducedarray = Array.new(100);
~standardizer.fitTransform(~raw, ~standardized);

10
release-packaging/HelpSource/Classes/FluidMLPRegressor.schelp
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@ -42,10 +42,10 @@ PRIVATE:: init, uid
METHOD:: fit
Train the network to map between a source and target link::Classes/FluidDataSet::
ARGUMENT:: sourceDataset
ARGUMENT:: sourceDataSet
Source data
ARGUMENT:: targetDataset
ARGUMENT:: targetDataSet
Target data
ARGUMENT:: action
@ -54,12 +54,12 @@ Function to run when training is complete
returns:: The training loss, or -1 if training failed
METHOD:: predict
Apply the learned mapping to a dataset (given a trained network)
Apply the learned mapping to a DataSet (given a trained network)
ARGUMENT:: sourceDataset
ARGUMENT:: sourceDataSet
Input data
ARGUMENT:: targetDataset
ARGUMENT:: targetDataSet
Output data
ARGUMENT:: layer

10
release-packaging/HelpSource/Classes/FluidNormalize.schelp
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@ -26,16 +26,16 @@ INSTANCEMETHODS::
METHOD:: fit
Compute the normalization factors from a link::Classes/FluidDataSet:: for later.
ARGUMENT:: dataset
ARGUMENT:: dataSet
The link::Classes/FluidDataSet:: to normalize
ARGUMENT:: action
A function to run when processing is complete
METHOD:: transform
Normalize a link::Classes/FluidDataSet:: into another link::Classes/FluidDataSet::, using the learned extrema from a previous call to link::Classes/FluidNormalize#fit::
ARGUMENT:: sourceDataset
ARGUMENT:: sourceDataSet
The link::Classes/FluidDataSet:: to normalize
ARGUMENT:: destDataset
ARGUMENT:: destDataSet
The link::Classes/FluidDataSet:: to populate with normalized data
ARGUMENT:: action
A function to run when processing is complete
@ -43,9 +43,9 @@ A function to run when processing is complete
METHOD:: fitTransform
Normalize a link::Classes/FluidDataSet::
ARGUMENT:: sourceDataset
ARGUMENT:: sourceDataSet
The link::Classes/FluidDataSet:: to normalize
ARGUMENT:: destDataset
ARGUMENT:: destDataSet
The link::Classes/FluidDataSet:: to populate with normalized data
ARGUMENT:: action
A function to run when processing is complete

22
release-packaging/HelpSource/Classes/FluidPCA.schelp
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@ -24,26 +24,26 @@ PRIVATE:: init
METHOD:: fit
Train this model on a link::Classes/FluidDataSet:: but don't transform the data
ARGUMENT:: dataset
ARGUMENT:: dataSet
A link::Classes/FluidDataSet:: to analyse
ARGUMENT:: action
Run when done
METHOD:: transform
Given a trained model, apply the reduction to a source link::Classes/FluidDataSet:: and write to a destination. Can be the same
ARGUMENT:: sourceDataset
Source data, or the dataset name
ARGUMENT:: destDataset
Destination data, or the dataset name
ARGUMENT:: sourceDataSet
Source data, or the DataSet name
ARGUMENT:: destDataSet
Destination data, or the DataSet name
ARGUMENT:: action
Run when done
METHOD:: fitTransform
link::Classes/FluidPCA#fit:: and link::Classes/FluidPCA#transform:: in a single pass
ARGUMENT:: sourceDataset
Source data, or the dataset name
ARGUMENT:: destDataset
Destination data, or the dataset name
ARGUMENT:: sourceDataSet
Source data, or the DataSet name
ARGUMENT:: destDataSet
Destination data, or the DataSet name
ARGUMENT:: action
Run when done
@ -105,9 +105,9 @@ FluidBufMFCC.process(s,~audio, features: ~mfcc_feature);
)
//First standardize our dataset, so that the MFCC dimensions are on comensurate scales
//First standardize our DataSet, so that the MFCC dimensions are on comensurate scales
//Then apply the PCA in-place on the standardized data
//Download the dataset contents into an array for plotting
//Download the DataSet contents into an array for plotting
(
~reducedarray = Array.new(100);
~standardizer.fitTransform(~raw, ~standardized);

12
release-packaging/HelpSource/Classes/FluidStandardize.schelp
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@ -18,26 +18,26 @@ The server for this model
INSTANCEMETHODS::
METHOD:: fit
Fit model to a dataset without applying scaling
ARGUMENT:: dataset
Fit model to a DataSet without applying scaling
ARGUMENT:: dataSet
The link::Classes/FluidDataSet:: to standardize
ARGUMENT:: action
A function to run when processing is complete
METHOD:: transform
Standardize a link::Classes/FluidDataSet::, using the learned statistics from a previous call to link::Classes/FluidStandardize#fit::
ARGUMENT:: sourceDataset
ARGUMENT:: sourceDataSet
The link::Classes/FluidDataSet:: to standardize
ARGUMENT:: destDataset
ARGUMENT:: destDataSet
The link::Classes/FluidDataSet:: to populate with standardized data
ARGUMENT:: action
A function to run when processing is complete
METHOD:: fitTransform
Standardize a link::Classes/FluidDataSet:: into another link::Classes/FluidDataSet::
ARGUMENT:: sourceDataset
ARGUMENT:: sourceDataSet
The link::Classes/FluidDataSet:: to standardize
ARGUMENT:: destDataset
ARGUMENT:: destDataSet
The link::Classes/FluidDataSet:: to populate with standardized data
ARGUMENT:: action
A function to run when processing is complete

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