Examples of model.MARK_II.SpatialPooler.performPooling()

model.MARK_II.SpatialPooler.performPooling()
This method recomputes all Column states within this functional Region. Through local inhibition, only a sparse set of Columns become active to represent the current 2D array of sensory data or a lower Region's output. @return A sparse set of active Columns within this Region.

        retina.seeBMPImage("2.bmp");


        int totalNumberOfSequenceSegments = 0;
        int totalNumberOfLearningNeurons = 0;
        for (int i = 0; i < (int) numberOfIterations; i++) {
            spatialPooler.performPooling();
            temporalPooler.performPooling();


            temporalPooler.getLearningAlgorithmStatistics().updateModelLearningMetrics(temporalPooler.getRegion());
            totalNumberOfSequenceSegments += temporalPooler.getLearningAlgorithmStatistics()
                    .getTotalNumberOfSequenceSegmentsInCurrentTimeStep();

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        SpatialPooler spatialPooler = new SpatialPooler(region);
        spatialPooler.setLearningState(true);


        retina.seeBMPImage("2.bmp");


        spatialPooler.performPooling(); // 11 active columns
        Set<ColumnPosition> columnActivityAfterSeeingImage2 = spatialPooler
                .getActiveColumnPositions();
        // = (6,5)(6, 3)(6, 2)(5, 3)(3, 5)(2, 2)(1, 3)(1, 2)(2, 5)(1, 5)(4, 4)


        // -----------------------compute SDR score----------------------------

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        for (int i = 1; i < (numberOfImagesToSee + 1); i++) {
            mnistManager.setCurrent(i);
            int[][] image = mnistManager.readImage();


            retina.see2DIntArray(image);
            spatialPooler.performPooling();
            Set<ColumnPosition> columnActivityAfterSeeingCurrentMNISTImage = spatialPooler
                    .getActiveColumnPositions();


            // compute SDR score
            int totalNumberOfColumnsInRegion = region.getNumberOfRowsAlongRegionYAxis()

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        SpatialPooler spatialPooler = new SpatialPooler(region);
        spatialPooler.setLearningState(true);


        retina.seeBMPImage("2.bmp");


        spatialPooler.performPooling(); // 11 active columns
        this.columnActivityAfterSeeingImage2 = spatialPooler
                .getActiveColumnPositions();
        // = (6,5)(6, 3)(6, 2)(5, 3)(3, 5)(2, 2)(1, 3)(1, 2)(2, 5)(1, 5)(4, 4)
    }

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        retina.seeBMPImage("2.bmp");


        SpatialPooler spatialPooler = new SpatialPooler(LGNRegion);
        spatialPooler.setLearningState(true);
        spatialPooler.performPooling();
        Set<ColumnPosition> LGNNeuronActivity = spatialPooler
                .getActiveColumnPositions();


        assertEquals(11, LGNNeuronActivity.size());

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        // run spatial pooling on a image
        SpatialPooler spatialPooler = new SpatialPooler(LGNRegion);
        spatialPooler.setLearningState(true);


        retina.seeBMPImage("2.bmp");
        Set<Column> LGNNeuronActivity = spatialPooler
                .performPooling();


        assertEquals(11, LGNNeuronActivity.size());


        Gson gson2 = new Gson();

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        assertEquals(emptySet, spatialPooler.getActiveColumnPositions());


        // view the image, which will activate Columns in the spatialPooler
        retina.seeBMPImage("2.bmp");
        spatialPooler.performPooling();


        // filledSet contains ((6, 5), (6, 2), (1, 2), (2, 5), (4, 4))
        assertEquals(filledSet, spatialPooler.getActiveColumnPositions());
    }
}

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