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updates/fixes based on PR comments

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This commit is contained in:
Jonathan Shook 2023-05-25 16:27:08 -05:00
parent dd1f039e09
commit a6b1bd3166
3 changed files with 22 additions and 7 deletions
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4
virtdata-lib-basics/src/main/java/io/nosqlbench/virtdata/library/basics/shared/from_long/to_vector/NormalizeVector.java
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@ -37,9 +37,9 @@ public class NormalizeVector implements Function<List<Double>,List<Double>> {
for (Double scalar : doubles) {
accumulator+=scalar*scalar;
}
double vectorLen = Math.sqrt(accumulator);
double scalarLen = Math.sqrt(accumulator);
for (double scalarComponent : doubles) {
unit.add(scalarComponent/vectorLen);
unit.add(scalarComponent/scalarLen);
}
return unit;
}

2
virtdata-lib-basics/src/main/java/io/nosqlbench/virtdata/library/basics/shared/from_long/to_vector/UniformVectorSizedStepped.java
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@ -58,7 +58,7 @@ public class UniformVectorSizedStepped implements LongFunction<List<Double>> {
this.funcs = new LongToDoubleFunction[dim];
for (int i = 0; i < dim; i++) {
if (i<dims.length/2) {
funcs[i]=new HashedDoubleRange(dims[i<<1].doubleValue(),dims[i<<1].doubleValue()+1);
funcs[i]=new HashedDoubleRange(dims[i<<1].doubleValue(),dims[(i<<1)+1].doubleValue());
} else {
funcs[i]=new HashedDoubleRange(0.0d,1.0d);
}

23
virtdata-lib-basics/src/test/java/io/nosqlbench/virtdata/library/basics/shared/from_long/to_vector/UniformVectorSteppedTest.java
View File

@ -16,8 +16,10 @@
package io.nosqlbench.virtdata.library.basics.shared.from_long.to_vector;
import org.assertj.core.data.Offset;
import org.junit.jupiter.api.Test;
import java.util.DoubleSummaryStatistics;
import java.util.List;
import static org.assertj.core.api.Assertions.assertThat;
@ -42,13 +44,26 @@ public class UniformVectorSteppedTest {
@Test
public void testUniformVectorSteppedHasRanges() {
UniformVectorSizedStepped f3 = new UniformVectorSizedStepped(4,3.0,5.0,7.0,9.0);
DoubleSummaryStatistics[] dssa = new DoubleSummaryStatistics[] {
new DoubleSummaryStatistics(),
new DoubleSummaryStatistics(),
new DoubleSummaryStatistics(),
new DoubleSummaryStatistics()
};
for (int i = 0; i < 1000; i++) {
List<Double> v4 = f3.apply(i);
assertThat(v4.get(0)).isBetween(3.0d,5.0d);
assertThat(v4.get(1)).isBetween(7.0d,9.0d);
assertThat(v4.get(2)).isBetween(0.0d,1.0d);
assertThat(v4.get(3)).isBetween(0.0d,1.0d);
for (int j = 0; j <= 3; j++) {
dssa[j].accept(v4.get(j));
}
}
assertThat(dssa[0].getMin()).isCloseTo(3.0d, Offset.offset(0.1d));
assertThat(dssa[0].getMax()).isCloseTo(5.0d, Offset.offset(0.1d));
assertThat(dssa[1].getMin()).isCloseTo(7.0d, Offset.offset(0.1d));
assertThat(dssa[1].getMax()).isCloseTo(9.0d, Offset.offset(0.1d));
assertThat(dssa[2].getMin()).isCloseTo(0.0d, Offset.offset(0.1d));
assertThat(dssa[2].getMax()).isCloseTo(1.0d, Offset.offset(0.1d));
assertThat(dssa[3].getMin()).isCloseTo(0.0d, Offset.offset(0.1d));
assertThat(dssa[3].getMax()).isCloseTo(1.0d, Offset.offset(0.1d));
}
}