Package org.vocvark.DataTypes

Examples of org.vocvark.DataTypes.FeatureDefinition

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        this.featureNames = featureNames;
        String names = featureNames[0];
        for (int i = 1; i < featureNames.length; ++i) {
            names += " " + featureNames[i];
        }
        definition = new FeatureDefinition("Area Moments: " + names, "2D moments constructed from features " + names + ".", true, 10);
    }
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        return new Mean();
    }

    @Override
    public void setSource(FeatureExtractor feature) {
        FeatureDefinition this_def = feature.getFeatureDefinition();
        definition = new FeatureDefinition(this_def.name + " Overall Average",
                this_def.description + System.getProperty("line.separator")
                        + "This is the overall average over all windows.",
                this_def.is_sequential, this_def.dimensions);

    }
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        count++;

        // Identify the type of tag
        tag_identifier = 0;
        if (name.equals("feature"))
            current_definition = new FeatureDefinition();
        else if (name.equals("name"))
            tag_identifier = 1;
        else if (name.equals("description"))
            tag_identifier = 2;
        else if (name.equals("is_sequential"))
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        feature = featureIndecis[0];
    }

    @Override
    public void setSource(FeatureExtractor feature) {
        FeatureDefinition this_def = feature.getFeatureDefinition();
        definition = new FeatureDefinition(this_def.name
                + " Overall Standard Deviation", this_def.description
                + LINE_SEP
                + "This is the overall standard deviation over all windows.",
                this_def.is_sequential, this_def.dimensions);
    }
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        featureIndex = featureIndecis;
    }

    @Override
    public void setSource(FeatureExtractor feature) {
        definition = new FeatureDefinition(
                feature.getFeatureDefinition().name + "/DUMMY", feature
                .getFeatureDefinition().name
                + "/DUMMY",
                feature.getFeatureDefinition().is_sequential, feature
                .getFeatureDefinition().dimensions);
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        int dimensions = 0;
        for (int i = 0; i < fe.length; ++i) {
            name += " " + fe[i];
            description += " " + fe[i];
        }
        definition = new FeatureDefinition(name, description, true, dimensions);
        binsPerDimension = bins;
        metadata = new AggregatorDefinition("Multiple Feature Histogram",
                "a histogram of categories of input", false,
                new String[]{"Number of bins for 1st dimension"});
    }
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                    description += " " + features[i];
                    // dimensions +=
                    // features[i].getFeatureDefinition().dimensions;
                }
                // dimensions = (int) Math.pow(binsPerDimension, dimensions);
                definition = new FeatureDefinition(name, description, true,
                        dimensions);

            } catch (NumberFormatException e) {
                throw new Exception(
                        "Parameters to MultipleFeatureHistogram must be an integer");
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        this.featureNames = featureNames;
        String names = featureNames[0];
        for (int i = 1; i < featureNames.length; ++i) {
            names += " " + featureNames[i];
        }
        definition = new FeatureDefinition("2D Polynomial Approximation: " + names, "2D moments constructed from features " + names + ".", true, 0);
    }
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        index = featureIndecis[0];
    }

    @Override
    public void setSource(FeatureExtractor feature) {
        FeatureDefinition source = feature.getFeatureDefinition();
        definition = new FeatureDefinition("MFCC: " + source.name,
                source.description + System.getProperty("line.separator")
                        + "MFCC of each dimension of this feature",
                source.is_sequential, source.dimensions * 4);

    }
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        String name = "Strongest Beat";
        String description = "The strongest beat in a signal, in beats per minute, " +
                "found by finding the strongest bin in the beat histogram.";
        boolean is_sequential = true;
        int dimensions = 1;
        definition = new FeatureDefinition(name,
                description,
                is_sequential,
                dimensions);

        dependencies = new String[2];
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Related Classes of org.vocvark.DataTypes.FeatureDefinition

  • org.vocvark.Aggregators.AreaMoments
  • org.vocvark.Aggregators.AreaPolynomialApproximation
  • org.vocvark.Aggregators.DummyAgg
  • org.vocvark.Aggregators.Mean
  • org.vocvark.Aggregators.MFCC
  • org.vocvark.Aggregators.MultipleFeatureHistogram
  • org.vocvark.Aggregators.StandardDeviation
  • org.vocvark.AudioFeatures.AreaMoments
  • org.vocvark.AudioFeatures.BeatHistogram
  • org.vocvark.AudioFeatures.BeatHistogramLabels
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