Package org.eobjects.analyzer.beans.valuedist

Examples of org.eobjects.analyzer.beans.valuedist.ValueCountListImpl.register()

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    topValueCount.register(new ValueCount("o", 6));
    topValueCount.register(new ValueCount("p", 6));
    topValueCount.register(new ValueCount("q", 7));
    topValueCount.register(new ValueCount("r", 7));
    topValueCount.register(new ValueCount("s", 8));
    topValueCount.register(new ValueCount("t", 8));
    topValueCount.register(new ValueCount("u", 9));
    topValueCount.register(new ValueCount("v", 9));

    // even though it is not nescesary for the slice threshold to group
    // these 4 values, we do so for the sake of "grouping consistency"
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    topValueCount.register(new ValueCount("p", 6));
    topValueCount.register(new ValueCount("q", 7));
    topValueCount.register(new ValueCount("r", 7));
    topValueCount.register(new ValueCount("s", 8));
    topValueCount.register(new ValueCount("t", 8));
    topValueCount.register(new ValueCount("u", 9));
    topValueCount.register(new ValueCount("v", 9));

    // even though it is not nescesary for the slice threshold to group
    // these 4 values, we do so for the sake of "grouping consistency"
    // (because they all have count=9).
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    topValueCount.register(new ValueCount("q", 7));
    topValueCount.register(new ValueCount("r", 7));
    topValueCount.register(new ValueCount("s", 8));
    topValueCount.register(new ValueCount("t", 8));
    topValueCount.register(new ValueCount("u", 9));
    topValueCount.register(new ValueCount("v", 9));

    // even though it is not nescesary for the slice threshold to group
    // these 4 values, we do so for the sake of "grouping consistency"
    // (because they all have count=9).
    topValueCount.register(new ValueCount("hi", 10));
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    topValueCount.register(new ValueCount("v", 9));

    // even though it is not nescesary for the slice threshold to group
    // these 4 values, we do so for the sake of "grouping consistency"
    // (because they all have count=9).
    topValueCount.register(new ValueCount("hi", 10));
    topValueCount.register(new ValueCount("hello", 10));
    topValueCount.register(new ValueCount("howdy", 10));
    topValueCount.register(new ValueCount("mjellow", 10));

    // preferred size is 13, which would earlier on mean that all the 4
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    // even though it is not nescesary for the slice threshold to group
    // these 4 values, we do so for the sake of "grouping consistency"
    // (because they all have count=9).
    topValueCount.register(new ValueCount("hi", 10));
    topValueCount.register(new ValueCount("hello", 10));
    topValueCount.register(new ValueCount("howdy", 10));
    topValueCount.register(new ValueCount("mjellow", 10));

    // preferred size is 13, which would earlier on mean that all the 4
    // values above could be individually included in the dataset.
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    // even though it is not nescesary for the slice threshold to group
    // these 4 values, we do so for the sake of "grouping consistency"
    // (because they all have count=9).
    topValueCount.register(new ValueCount("hi", 10));
    topValueCount.register(new ValueCount("hello", 10));
    topValueCount.register(new ValueCount("howdy", 10));
    topValueCount.register(new ValueCount("mjellow", 10));

    // preferred size is 13, which would earlier on mean that all the 4
    // values above could be individually included in the dataset.
    ValueDistributionResultSwingRendererGroupDelegate r = new ValueDistributionResultSwingRendererGroupDelegate("foo",
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    // these 4 values, we do so for the sake of "grouping consistency"
    // (because they all have count=9).
    topValueCount.register(new ValueCount("hi", 10));
    topValueCount.register(new ValueCount("hello", 10));
    topValueCount.register(new ValueCount("howdy", 10));
    topValueCount.register(new ValueCount("mjellow", 10));

    // preferred size is 13, which would earlier on mean that all the 4
    // values above could be individually included in the dataset.
    ValueDistributionResultSwingRendererGroupDelegate r = new ValueDistributionResultSwingRendererGroupDelegate("foo",
        13, 100);
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  public void testPreferredSizeGrouping() throws Exception {
    ValueCountListImpl topValueCount = ValueCountListImpl.createFullList();
    for (int i = 0; i < 2000; i++) {
      // 2000 values but with only 10 different counts - should yield 10
      // groups
      topValueCount.register(new ValueCount("v" + i, 2 + (int) (Math.random() * 10)));
    }

    ValueDistributionResultSwingRendererGroupDelegate r = new ValueDistributionResultSwingRendererGroupDelegate("foo",
        17, 20);
    r.renderGroupResult(new ValueDistributionGroupResult("foo", topValueCount, null, 0, 0, 0, 0));
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  public void testMaxSizeGrouping() throws Exception {
    ValueCountListImpl topValueCount = ValueCountListImpl.createFullList();
    for (int i = 0; i < 5000; i++) {
      // 5000 values with 10 different counts
      topValueCount.register(new ValueCount("v" + i, 2 + (int) (Math.random() * 10)));
    }

    // 10 additional values that will be grouped in 3 range-groups
    topValueCount.register(new ValueCount("r1", 100));
    topValueCount.register(new ValueCount("r2", 110));
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      // 5000 values with 10 different counts
      topValueCount.register(new ValueCount("v" + i, 2 + (int) (Math.random() * 10)));
    }

    // 10 additional values that will be grouped in 3 range-groups
    topValueCount.register(new ValueCount("r1", 100));
    topValueCount.register(new ValueCount("r2", 110));
    topValueCount.register(new ValueCount("r3", 130));
    topValueCount.register(new ValueCount("r4", 160));
    topValueCount.register(new ValueCount("r5", 210));
    topValueCount.register(new ValueCount("r6", 340));
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