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Element-wise operations: Difference between revisions
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Note that in some branches of mathematics, it has been traditional to define multiplication such that it is not performed element-wise. This can introduce some complications ([[wp:Einstein notation]] is arguably the best approach for resolving those complexities in latex, when they occur frequently enough that mentioning and using the notation is not more complicated than explicitly describing the multiply-and-sum) and makes expressing element-wise multiplication complicated. J deals with this conflict by making its multiplication primitive be elementwise (consistent with the rest of the language) and by using a different verb (typically +/ .*) to represent the traditional non-element-wise multiply and sum operation.
=={{header|Java}}==
<lang Java>
import java.util.Arrays;
import java.util.HashMap;
import java.util.Map;
import java.util.function.BiFunction;
import java.util.stream.Stream;
@SuppressWarnings("serial")
public class ElementWiseOp {
static final Map<String, BiFunction<Double, Double, Double>> OPERATIONS = new HashMap<String, BiFunction<Double, Double, Double>>() {
{
put("add", (a, b) -> a + b);
put("sub", (a, b) -> a - b);
put("mul", (a, b) -> a * b);
put("div", (a, b) -> a / b);
put("pow", (a, b) -> Math.pow(a, b));
put("mod", (a, b) -> a % b);
}
};
public static Double[][] scalarOp(String op, Double[][] matr, Double scalar) {
BiFunction<Double, Double, Double> operation = OPERATIONS.getOrDefault(op, (a, b) -> a);
Double[][] result = new Double[matr.length][matr[0].length];
for (int i = 0; i < matr.length; i++) {
for (int j = 0; j < matr[i].length; j++) {
result[i][j] = operation.apply(matr[i][j], scalar);
}
}
return result;
}
public static Double[][] matrOp(String op, Double[][] matr, Double[][] scalar) {
BiFunction<Double, Double, Double> operation = OPERATIONS.getOrDefault(op, (a, b) -> a);
Double[][] result = new Double[matr.length][Stream.of(matr).mapToInt(a -> a.length).max().getAsInt()];
for (int i = 0; i < matr.length; i++) {
for (int j = 0; j < matr[i].length; j++) {
result[i][j] = operation.apply(matr[i][j], scalar[i % scalar.length][j
% scalar[i % scalar.length].length]);
}
}
return result;
}
public static void printMatrix(Double[][] matr) {
Stream.of(matr).map(Arrays::toString).forEach(System.out::println);
}
public static void main(String[] args) {
printMatrix(scalarOp("mul", new Double[][] {
{ 1.0, 2.0, 3.0 },
{ 4.0, 5.0, 6.0 },
{ 7.0, 8.0, 9.0 }
}, 3.0));
printMatrix(matrOp("div", new Double[][] {
{ 1.0, 2.0, 3.0 },
{ 4.0, 5.0, 6.0 },
{ 7.0, 8.0, 9.0 }
}, new Double[][] {
{ 1.0, 2.0},
{ 3.0, 4.0}
}));
}
}
</lang>
=={{header|jq}}==
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