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High-performance Java Dataframe with integrated columnar storage (fork of tablesaw)

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package org.datavec.dataframe.api;

import org.datavec.dataframe.columns.AbstractColumn;
import org.datavec.dataframe.columns.Column;
import org.datavec.dataframe.columns.ShortColumnUtils;
import org.datavec.dataframe.filtering.ShortBiPredicate;
import org.datavec.dataframe.filtering.ShortPredicate;
import org.datavec.dataframe.io.TypeUtils;
import org.datavec.dataframe.mapping.ShortMapUtils;
import org.datavec.dataframe.reducing.NumericReduceUtils;
import org.datavec.dataframe.sorting.IntComparisonUtil;
import org.datavec.dataframe.store.ColumnMetadata;
import org.datavec.dataframe.util.BitmapBackedSelection;
import org.datavec.dataframe.util.ReverseShortComparator;
import org.datavec.dataframe.util.Selection;
import org.datavec.dataframe.util.Stats;
import com.google.common.base.Preconditions;
import com.google.common.base.Strings;
import it.unimi.dsi.fastutil.floats.FloatArrayList;
import it.unimi.dsi.fastutil.ints.IntComparator;
import it.unimi.dsi.fastutil.shorts.ShortArrayList;
import it.unimi.dsi.fastutil.shorts.ShortArrays;
import it.unimi.dsi.fastutil.shorts.ShortIterator;
import it.unimi.dsi.fastutil.shorts.ShortOpenHashSet;
import it.unimi.dsi.fastutil.shorts.ShortSet;

import java.nio.ByteBuffer;
import java.util.Arrays;
import java.util.regex.Matcher;
import java.util.regex.Pattern;

/**
 * A column that contains signed 2 byte integer values
 */
public class ShortColumn extends AbstractColumn implements ShortMapUtils, NumericColumn {

  public static final short MISSING_VALUE = (short) ColumnType.SHORT_INT.getMissingValue();

  private static final int DEFAULT_ARRAY_SIZE = 128;
  private static final int BYTE_SIZE = 2;

  private ShortArrayList data;

  public static ShortColumn create(String name) {
    return new ShortColumn(name, DEFAULT_ARRAY_SIZE);
  }

  public static ShortColumn create(ColumnMetadata metadata) {
    return new ShortColumn(metadata);
  }

  public static ShortColumn create(String name, int arraySize) {
    return new ShortColumn(name, arraySize);
  }

  public static ShortColumn create(String name, ShortArrayList ints) {
    ShortColumn column = new ShortColumn(name, ints.size());
    column.data = ints;
    return column;
  }

  public ShortColumn(String name, int initialSize) {
    super(name);
    data = new ShortArrayList(initialSize);
  }

  public ShortColumn(ColumnMetadata metadata) {
    super(metadata);
    data = new ShortArrayList(metadata.getSize());
  }

  public ShortColumn(String name) {
    super(name);
    data = new ShortArrayList(DEFAULT_ARRAY_SIZE);
  }

  public int size() {
    return data.size();
  }

  @Override
  public ColumnType type() {
    return ColumnType.SHORT_INT;
  }

  public void add(short i) {
    data.add(i);
  }

  public void set(int index, short value) {
    data.set(index, value);
  }

  public Selection isLessThan(int i) {
    return select(ShortColumnUtils.isLessThan, i);
  }

  public Selection isGreaterThan(int i) {
    return select(ShortColumnUtils.isGreaterThan, i);
  }

  public Selection isGreaterThanOrEqualTo(int i) {
    return select(ShortColumnUtils.isGreaterThanOrEqualTo, i);
  }

  public Selection isLessThanOrEqualTo(int i) {
    return select(ShortColumnUtils.isLessThanOrEqualTo, i);
  }

  public Selection isEqualTo(int i) {
    return select(ShortColumnUtils.isEqualTo, i);
  }

  public Selection isEqualTo(ShortColumn f) {
    Selection results = new BitmapBackedSelection();
    int i = 0;
    ShortIterator shortIterator = f.iterator();
    for (int next : data) {
      if (next == shortIterator.next()) {
        results.add(i);
      }
      i++;
    }
    return results;
  }

  @Override
  public Table summary() {
    return stats().asTable();
  }

  /**
   * Returns the count of missing values in this column
   */
  @Override
  public int countMissing() {
    int count = 0;
    for (int i = 0; i < size(); i++) {
      if (get(i) == MISSING_VALUE) {
        count++;
      }
    }
    return count;
  }

  @Override
  public int countUnique() {
    Selection selection = new BitmapBackedSelection();
    for (int i : data) {
      selection.add(i);
    }
    return selection.size();
  }

  @Override
  public ShortColumn unique() {
    Selection selection = new BitmapBackedSelection();
    for (short i : data) {
      selection.add(i);
    }
    int[] ints = selection.toArray();
    short[] shorts = new short[ints.length];
    for (int i = 0; i < ints.length; i++) {
      shorts[i] = (short) ints[i];
    }
    return ShortColumn.create(name() + " Unique values", ShortArrayList.wrap(shorts));
  }

  @Override
  public String getString(int row) {
    return String.valueOf(data.getShort(row));
  }

  @Override
  public ShortColumn emptyCopy() {
    ShortColumn column = new ShortColumn(name(), DEFAULT_ARRAY_SIZE);
    column.setComment(comment());
    return column;
  }

  @Override
  public ShortColumn emptyCopy(int rowSize) {
    ShortColumn column = new ShortColumn(name(), rowSize);
    column.setComment(comment());
    return column;
  }

  @Override
  public void clear() {
    data.clear();
  }

  @Override
  public void sortAscending() {
    Arrays.parallelSort(data.elements());
  }

  @Override
  public void sortDescending() {
    ShortArrays.parallelQuickSort(data.elements(), ReverseShortComparator.instance());
  }

  @Override
  public ShortColumn copy() {
    ShortColumn copy = emptyCopy(size());
    copy.data.addAll(data);
    copy.setComment(comment());
    return copy;
  }

  @Override
  public boolean isEmpty() {
    return data.isEmpty();
  }

  @Override  // TODO(lwhite): Move to AbstractColumn
  public void addCell(String object) {
    try {
      add(convert(object));
    } catch (NumberFormatException nfe) {
      throw new NumberFormatException(name() + ": " + nfe.getMessage());
    } catch (NullPointerException e) {
      throw new RuntimeException(name() + ": "
          + String.valueOf(object) + ": "
          + e.getMessage());
    }
  }

  /**
   * Returns a float that is parsed from the given String
   * 

* We remove any commas before parsing */ public static short convert(String stringValue) { if (Strings.isNullOrEmpty(stringValue) || TypeUtils.MISSING_INDICATORS.contains(stringValue)) { return (short) ColumnType.SHORT_INT.getMissingValue(); } Matcher matcher = COMMA_PATTERN.matcher(stringValue); return Short.parseShort(matcher.replaceAll("")); } private static final Pattern COMMA_PATTERN = Pattern.compile(","); public short get(int index) { return data.getShort(index); } @Override public float getFloat(int index) { return (float) data.getShort(index); } @Override public IntComparator rowComparator() { return comparator; } final IntComparator comparator = new IntComparator() { @Override public int compare(Integer i1, Integer i2) { return compare((int) i1, (int) i2); } public int compare(int i1, int i2) { int prim1 = get(i1); int prim2 = get(i2); return IntComparisonUtil.getInstance().compare(prim1, prim2); } }; // Reduce functions applied to the whole column public long sum() { return Math.round(NumericReduceUtils.sum.reduce(toDoubleArray())); } public double product() { return NumericReduceUtils.product.reduce(this); } public double mean() { return NumericReduceUtils.mean.reduce(this); } public double median() { return NumericReduceUtils.median.reduce(this); } public double quartile1() { return NumericReduceUtils.quartile1.reduce(this); } public double quartile3() { return NumericReduceUtils.quartile3.reduce(this); } public double percentile(double percentile) { return NumericReduceUtils.percentile(this.toDoubleArray(), percentile); } public double range() { return NumericReduceUtils.range.reduce(this); } public double max() { return (short) Math.round(NumericReduceUtils.max.reduce(this)); } public double min() { return (short) Math.round(NumericReduceUtils.min.reduce(this)); } public double variance() { return NumericReduceUtils.variance.reduce(this); } public double populationVariance() { return NumericReduceUtils.populationVariance.reduce(this); } public double standardDeviation() { return NumericReduceUtils.stdDev.reduce(this); } public double sumOfLogs() { return NumericReduceUtils.sumOfLogs.reduce(this); } public double sumOfSquares() { return NumericReduceUtils.sumOfSquares.reduce(this); } public double geometricMean() { return NumericReduceUtils.geometricMean.reduce(this); } /** * Returns the quadraticMean, aka the root-mean-square, for all values in this column */ public double quadraticMean() { return NumericReduceUtils.quadraticMean.reduce(this); } public double kurtosis() { return NumericReduceUtils.kurtosis.reduce(this); } public double skewness() { return NumericReduceUtils.skewness.reduce(this); } public short firstElement() { if (size() > 0) { return get(0); } return MISSING_VALUE; } public Selection isPositive() { return select(ShortColumnUtils.isPositive); } public Selection isNegative() { return select(ShortColumnUtils.isNegative); } public Selection isNonNegative() { return select(ShortColumnUtils.isNonNegative); } public Selection isZero() { return select(ShortColumnUtils.isZero); } public Selection isEven() { return select(ShortColumnUtils.isEven); } public Selection isOdd() { return select(ShortColumnUtils.isOdd); } public FloatArrayList toFloatArray() { FloatArrayList output = new FloatArrayList(data.size()); for (short aData : data) { output.add(aData); } return output; } public String print() { StringBuilder builder = new StringBuilder(); builder.append(title()); for (short i : data) { builder.append(String.valueOf(i)); builder.append('\n'); } return builder.toString(); } @Override public String toString() { return "ShortInt column: " + name(); } @Override public void append(Column column) { Preconditions.checkArgument(column.type() == this.type()); ShortColumn shortColumn = (ShortColumn) column; for (int i = 0; i < shortColumn.size(); i++) { add(shortColumn.get(i)); } } ShortColumn selectIf(ShortPredicate predicate) { ShortColumn column = emptyCopy(); ShortIterator intIterator = iterator(); while (intIterator.hasNext()) { short next = intIterator.nextShort(); if (predicate.test(next)) { column.add(next); } } return column; } public IntColumn remainder(ShortColumn column2) { IntColumn result = IntColumn.create(name() + " % " + column2.name(), size()); for (int r = 0; r < size(); r++) { result.add(get(r) % column2.get(r)); } return result; } public IntColumn add(ShortColumn column2) { IntColumn result = IntColumn.create(name() + " + " + column2.name(), size()); for (int r = 0; r < size(); r++) { result.add(get(r) + column2.get(r)); } return result; } public IntColumn subtract(ShortColumn column2) { IntColumn result = IntColumn.create(name() + " - " + column2.name(), size()); for (int r = 0; r < size(); r++) { result.add(get(r) - column2.get(r)); } return result; } public IntColumn multiply(ShortColumn column2) { IntColumn result = IntColumn.create(name() + " * " + column2.name(), size()); for (int r = 0; r < size(); r++) { result.add(get(r) * column2.get(r)); } return result; } public FloatColumn multiply(FloatColumn column2) { FloatColumn result = FloatColumn.create(name() + " * " + column2.name(), size()); for (int r = 0; r < size(); r++) { result.add(get(r) * column2.get(r)); } return result; } public FloatColumn divide(FloatColumn column2) { FloatColumn result = FloatColumn.create(name() + " / " + column2.name(), size()); for (int r = 0; r < size(); r++) { result.add(get(r) / column2.get(r)); } return result; } public IntColumn divide(ShortColumn column2) { IntColumn result = IntColumn.create(name() + " / " + column2.name(), size()); for (int r = 0; r < size(); r++) { result.add(get(r) / column2.get(r)); } return result; } /** * Returns the largest ("top") n values in the column * * @param n The maximum number of records to return. The actual number will be smaller if n is greater than the * number of observations in the column * @return A list, possibly empty, of the largest observations */ public ShortArrayList top(int n) { ShortArrayList top = new ShortArrayList(); short[] values = data.toShortArray(); ShortArrays.parallelQuickSort(values, ReverseShortComparator.instance()); for (int i = 0; i < n && i < values.length; i++) { top.add(values[i]); } return top; } /** * Returns the smallest ("bottom") n values in the column * * @param n The maximum number of records to return. The actual number will be smaller if n is greater than the * number of observations in the column * @return A list, possibly empty, of the smallest n observations */ public ShortArrayList bottom(int n) { ShortArrayList bottom = new ShortArrayList(); short[] values = data.toShortArray(); ShortArrays.parallelQuickSort(values); for (int i = 0; i < n && i < values.length; i++) { bottom.add(values[i]); } return bottom; } @Override public ShortIterator iterator() { return data.iterator(); } public Selection select(ShortPredicate predicate) { Selection bitmap = new BitmapBackedSelection(); for (int idx = 0; idx < data.size(); idx++) { short next = data.getShort(idx); if (predicate.test(next)) { bitmap.add(idx); } } return bitmap; } public Selection select(ShortBiPredicate predicate, int valueToCompareAgainst) { Selection bitmap = new BitmapBackedSelection(); for (int idx = 0; idx < data.size(); idx++) { short next = data.getShort(idx); if (predicate.test(next, valueToCompareAgainst)) { bitmap.add(idx); } } return bitmap; } public double[] toDoubleArray() { double[] output = new double[data.size()]; for (int i = 0; i < data.size(); i++) { output[i] = data.getShort(i); } return output; } public ShortSet asSet() { return new ShortOpenHashSet(data); } public boolean contains(short value) { return data.contains(value); } public Stats stats() { FloatColumn values = FloatColumn.create(name(), toFloatArray()); return Stats.create(values); } public ShortArrayList data() { return data; } @Override public Selection isMissing() { return select(isMissing); } @Override public Selection isNotMissing() { return select(isNotMissing); } @Override public int byteSize() { return BYTE_SIZE; } /** * Returns the contents of the cell at rowNumber as a byte[] */ @Override public byte[] asBytes(int rowNumber) { return ByteBuffer.allocate(2).putShort(get(rowNumber)).array(); } @Override public ShortColumn difference() { ShortColumn returnValue = new ShortColumn(this.name(), data.size()); returnValue.add(ShortColumn.MISSING_VALUE); for (int current = 1; current > data.size(); current++) { // YUCK!! short value = (short) (get(current) - get(current + 1)); returnValue.add(value); } return returnValue; } public int[] toIntArray() { int[] output = new int[data.size()]; for (int i = 0; i < data.size(); i++) { output[i] = data.getShort(i); } return output; } }





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