tech.tablesaw.api.ShortColumn Maven / Gradle / Ivy
package tech.tablesaw.api;
import com.google.common.base.Preconditions;
import com.google.common.primitives.Shorts;
import it.unimi.dsi.fastutil.ints.IntRBTreeSet;
import it.unimi.dsi.fastutil.shorts.ShortArrayList;
import it.unimi.dsi.fastutil.shorts.ShortArrays;
import it.unimi.dsi.fastutil.shorts.ShortComparators;
import it.unimi.dsi.fastutil.shorts.ShortListIterator;
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.HashSet;
import java.util.Iterator;
import java.util.Set;
import java.util.stream.Stream;
import tech.tablesaw.columns.AbstractColumnParser;
import tech.tablesaw.columns.Column;
import tech.tablesaw.columns.numbers.DoubleColumnType;
import tech.tablesaw.columns.numbers.NumberColumnFormatter;
import tech.tablesaw.columns.numbers.ShortColumnType;
import tech.tablesaw.selection.BitmapBackedSelection;
import tech.tablesaw.selection.Selection;
/** A column that contains short values */
public class ShortColumn extends NumberColumn
implements CategoricalColumn {
protected final ShortArrayList data;
protected ShortColumn(final String name, ShortArrayList data) {
super(ShortColumnType.instance(), name, ShortColumnType.DEFAULT_PARSER);
setPrintFormatter(NumberColumnFormatter.ints());
this.data = data;
}
/** {@inheritDoc} */
@Override
public int valueHash(int rowNumber) {
return getShort(rowNumber);
}
/** {@inheritDoc} */
@Override
public boolean equals(int rowNumber1, int rowNumber2) {
return getShort(rowNumber1) == getShort(rowNumber2);
}
public static ShortColumn create(final String name) {
return new ShortColumn(name, new ShortArrayList());
}
public static ShortColumn create(final String name, final short... arr) {
return new ShortColumn(name, new ShortArrayList(arr));
}
public static ShortColumn create(final String name, final int initialSize) {
ShortColumn column = new ShortColumn(name, new ShortArrayList(initialSize));
for (int i = 0; i < initialSize; i++) {
column.appendMissing();
}
return column;
}
public static ShortColumn create(final String name, final Short[] arr) {
return new ShortColumn(name, new ShortArrayList(Shorts.toArray(Arrays.asList(arr))));
}
public static ShortColumn create(String name, Stream stream) {
ShortColumn column = create(name);
stream.forEach(column::append);
return column;
}
/** {@inheritDoc} */
@Override
public ShortColumn createCol(final String name, final int initialSize) {
return create(name, initialSize);
}
/** {@inheritDoc} */
@Override
public ShortColumn createCol(final String name) {
return create(name);
}
public static boolean valueIsMissing(int value) {
return ShortColumnType.valueIsMissing(value);
}
/** {@inheritDoc} */
@Override
public Short get(int index) {
short result = getShort(index);
return isMissingValue(result) ? null : result;
}
public short getShort(int index) {
return data.getShort(index);
}
/** {@inheritDoc} */
@Override
public ShortColumn subset(final int[] rows) {
final ShortColumn c = this.emptyCopy();
for (final int row : rows) {
c.append(getShort(row));
}
return c;
}
public Selection isIn(final int... numbers) {
final Selection results = new BitmapBackedSelection();
final IntRBTreeSet intSet = new IntRBTreeSet(numbers);
for (int i = 0; i < size(); i++) {
if (intSet.contains(getInt(i))) {
results.add(i);
}
}
return results;
}
public Selection isNotIn(final int... numbers) {
final Selection results = new BitmapBackedSelection();
results.addRange(0, size());
results.andNot(isIn(numbers));
return results;
}
/** {@inheritDoc} */
@Override
public int size() {
return data.size();
}
/** {@inheritDoc} */
@Override
public void clear() {
data.clear();
}
/** {@inheritDoc} */
@Override
public ShortColumn unique() {
final ShortSet values = new ShortOpenHashSet();
for (int i = 0; i < size(); i++) {
values.add(getShort(i));
}
final ShortColumn column = ShortColumn.create(name() + " Unique values");
for (short value : values) {
column.append(value);
}
return column;
}
/** {@inheritDoc} */
@Override
public ShortColumn top(int n) {
final ShortArrayList top = new ShortArrayList();
final short[] values = data.toShortArray();
ShortArrays.parallelQuickSort(values, ShortComparators.OPPOSITE_COMPARATOR);
for (int i = 0; i < n && i < values.length; i++) {
top.add(values[i]);
}
return new ShortColumn(name() + "[Top " + n + "]", top);
}
/** {@inheritDoc} */
@Override
public ShortColumn bottom(final int n) {
final ShortArrayList bottom = new ShortArrayList();
final short[] values = data.toShortArray();
ShortArrays.parallelQuickSort(values);
for (int i = 0; i < n && i < values.length; i++) {
bottom.add(values[i]);
}
return new ShortColumn(name() + "[Bottoms " + n + "]", bottom);
}
/** {@inheritDoc} */
@Override
public ShortColumn lag(int n) {
final int srcPos = n >= 0 ? 0 : -n;
final short[] dest = new short[size()];
final int destPos = Math.max(n, 0);
final int length = n >= 0 ? size() - n : size() + n;
for (int i = 0; i < size(); i++) {
dest[i] = ShortColumnType.missingValueIndicator();
}
short[] array = data.toShortArray();
System.arraycopy(array, srcPos, dest, destPos, length);
return new ShortColumn(name() + " lag(" + n + ")", new ShortArrayList(dest));
}
/** {@inheritDoc} */
@Override
public ShortColumn removeMissing() {
ShortColumn result = copy();
result.clear();
ShortListIterator iterator = data.iterator();
while (iterator.hasNext()) {
final short v = iterator.nextShort();
if (!isMissingValue(v)) {
result.append(v);
}
}
return result;
}
public ShortColumn append(short i) {
data.add(i);
return this;
}
/** {@inheritDoc} */
@Override
public ShortColumn append(Short val) {
if (val == null) {
appendMissing();
} else {
append(val.shortValue());
}
return this;
}
/** {@inheritDoc} */
@Override
public ShortColumn emptyCopy() {
return super.emptyCopy();
}
/** {@inheritDoc} */
@Override
public ShortColumn emptyCopy(final int rowSize) {
return super.emptyCopy(rowSize);
}
/** {@inheritDoc} */
@Override
public ShortColumn copy() {
ShortColumn copy = new ShortColumn(name(), data.clone());
copy.setPrintFormatter(getPrintFormatter());
copy.locale = locale;
return copy;
}
/** {@inheritDoc} */
@Override
public Iterator iterator() {
return data.iterator();
}
/** {@inheritDoc} */
@Override
public Short[] asObjectArray() {
final Short[] output = new Short[size()];
for (int i = 0; i < size(); i++) {
if (!isMissing(i)) {
output[i] = getShort(i);
} else {
output[i] = null;
}
}
return output;
}
public short[] asShortArray() {
return data.toShortArray();
}
/** {@inheritDoc} */
@Override
public int compare(Short o1, Short o2) {
return Short.compare(o1, o2);
}
/** {@inheritDoc} */
@Override
public ShortColumn set(int i, Short val) {
return val == null ? setMissing(i) : set(i, (short) val);
}
public ShortColumn set(int i, short val) {
data.set(i, val);
return this;
}
/** {@inheritDoc} */
@Override
public Column set(int row, String stringValue, AbstractColumnParser parser) {
return set(row, parser.parseShort(stringValue));
}
/** {@inheritDoc} */
@Override
public ShortColumn append(final Column column) {
Preconditions.checkArgument(
column.type() == this.type(),
"Column '%s' has type %s, but column '%s' has type %s.",
name(),
type(),
column.name(),
column.type());
final ShortColumn numberColumn = (ShortColumn) column;
final int size = numberColumn.size();
for (int i = 0; i < size; i++) {
append(numberColumn.getShort(i));
}
return this;
}
/** {@inheritDoc} */
@Override
public String getString(final int row) {
final short value = getShort(row);
return String.valueOf(getPrintFormatter().format(value));
}
/** {@inheritDoc} */
@Override
public ShortColumn append(Column column, int row) {
Preconditions.checkArgument(
column.type() == this.type(),
"Column '%s' has type %s, but column '%s' has type %s.",
name(),
type(),
column.name(),
column.type());
return append(((ShortColumn) column).getShort(row));
}
/** {@inheritDoc} */
@Override
public ShortColumn set(int row, Column column, int sourceRow) {
Preconditions.checkArgument(
column.type() == this.type(),
"Column '%s' has type %s, but column '%s' has type %s.",
name(),
type(),
column.name(),
column.type());
return set(row, ((ShortColumn) column).getShort(sourceRow));
}
/** {@inheritDoc} */
@Override
public ShortColumn appendMissing() {
return append(ShortColumnType.missingValueIndicator());
}
/** {@inheritDoc} */
@Override
public byte[] asBytes(int rowNumber) {
return ByteBuffer.allocate(ShortColumnType.instance().byteSize())
.putShort(getShort(rowNumber))
.array();
}
/** {@inheritDoc} */
@Override
public int countUnique() {
ShortSet uniqueElements = new ShortOpenHashSet();
for (int i = 0; i < size(); i++) {
uniqueElements.add(getShort(i));
}
return uniqueElements.size();
}
/**
* Returns the value at the given index. The actual value is returned if the ColumnType is INTEGER
*
* Returns the closest {@code int} to the argument, with ties rounding to positive infinity.
*
*
Special cases:
*
*
Special cases:
*
*
* - If the argument is NaN, the result is 0.
*
- If the argument is positive infinity or any value greater than or equal to the value of
* {@code Integer.MAX_VALUE}, an error will be thrown
*
*
* @param row the index of the value to be rounded to an integer.
* @return the value of the argument rounded to the nearest {@code int} value.
* @throws ClassCastException if the absolute value of the value to be rounded is too large to be
* cast to an int
*/
public int getInt(int row) {
return data.getShort(row);
}
/** {@inheritDoc} */
@Override
public double getDouble(int row) {
short value = data.getShort(row);
if (isMissingValue(value)) {
return DoubleColumnType.missingValueIndicator();
}
return value;
}
public boolean isMissingValue(short value) {
return ShortColumnType.valueIsMissing(value);
}
/** {@inheritDoc} */
@Override
public boolean isMissing(int rowNumber) {
return isMissingValue(getShort(rowNumber));
}
/** {@inheritDoc} */
@Override
public ShortColumn setMissing(int i) {
return set(i, ShortColumnType.missingValueIndicator());
}
/** {@inheritDoc} */
@Override
public void sortAscending() {
data.sort(ShortComparators.NATURAL_COMPARATOR);
}
/** {@inheritDoc} */
@Override
public void sortDescending() {
data.sort(ShortComparators.OPPOSITE_COMPARATOR);
}
/** {@inheritDoc} */
@Override
public ShortColumn appendObj(Object obj) {
if (obj == null) {
return appendMissing();
}
if (obj instanceof Short) {
return append((short) obj);
}
throw new IllegalArgumentException("Could not append " + obj.getClass());
}
/** {@inheritDoc} */
@Override
public ShortColumn appendCell(final String value) {
try {
return append(parser().parseShort(value));
} catch (final NumberFormatException e) {
throw new NumberFormatException(
"Error adding value to column " + name() + ": " + e.getMessage());
}
}
/** {@inheritDoc} */
@Override
public ShortColumn appendCell(final String value, AbstractColumnParser parser) {
try {
return append(parser.parseShort(value));
} catch (final NumberFormatException e) {
throw new NumberFormatException(
"Error adding value to column " + name() + ": " + e.getMessage());
}
}
/** {@inheritDoc} */
@Override
public String getUnformattedString(final int row) {
final int value = getInt(row);
if (ShortColumnType.valueIsMissing(value)) {
return "";
}
return String.valueOf(value);
}
/**
* Returns a new LongColumn containing a value for each value in this column
*
* A widening primitive conversion from short to long does not lose any information at all; the
* numeric value is preserved exactly.
*
*
A missing value in the receiver is converted to a missing value in the result
*/
@Override
public LongColumn asLongColumn() {
LongColumn result = LongColumn.create(name());
for (short d : data) {
if (ShortColumnType.valueIsMissing(d)) {
result.appendMissing();
} else {
result.append(d);
}
}
return result;
}
/**
* Returns a new FloatColumn containing a value for each value in this column, truncating if
* necessary.
*
*
A widening primitive conversion from an int to a float does not lose information about the
* overall magnitude of a numeric value. It may, however, result in loss of precision - that is,
* the result may lose some of the least significant bits of the value. In this case, the
* resulting floating-point value will be a correctly rounded version of the integer value, using
* IEEE 754 round-to-nearest mode.
*
*
Despite the fact that a loss of precision may occur, a widening primitive conversion never
* results in a run-time exception.
*
*
A missing value in the receiver is converted to a missing value in the result
*/
@Override
public FloatColumn asFloatColumn() {
FloatColumn result = FloatColumn.create(name());
for (short d : data) {
if (ShortColumnType.valueIsMissing(d)) {
result.appendMissing();
} else {
result.append(d);
}
}
return result;
}
/**
* Returns a new DoubleColumn containing a value for each value in this column, truncating if
* necessary.
*
*
A widening primitive conversion from an int to a double does not lose information about the
* overall magnitude of a numeric value. It may, however, result in loss of precision - that is,
* the result may lose some of the least significant bits of the value. In this case, the
* resulting floating-point value will be a correctly rounded version of the integer value, using
* IEEE 754 round-to-nearest mode.
*
*
Despite the fact that a loss of precision may occur, a widening primitive conversion never
* results in a run-time exception.
*
*
A missing value in the receiver is converted to a missing value in the result
*/
@Override
public DoubleColumn asDoubleColumn() {
DoubleColumn result = DoubleColumn.create(name());
for (short d : data) {
if (ShortColumnType.valueIsMissing(d)) {
result.appendMissing();
} else {
result.append(d);
}
}
return result;
}
/** {@inheritDoc} */
@Override
public IntColumn asIntColumn() {
IntColumn result = IntColumn.create(name());
for (short d : data) {
if (ShortColumnType.valueIsMissing(d)) {
result.appendMissing();
} else {
result.append(d);
}
}
return result;
}
/** {@inheritDoc} */
@Override
public Set asSet() {
return new HashSet<>(unique().asList());
}
}