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* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you under the Apache License, Version 2.0 (the
* "License"); you may not use this file except in compliance
* with the License. You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing,
* software distributed under the License is distributed on an
* "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
* KIND, either express or implied. See the License for the
* specific language governing permissions and limitations
* under the License.
*/
package org.apache.sysds.test.functions.binary.matrix;
import org.junit.Test;
import org.apache.sysds.test.AutomatedTestBase;
import org.apache.sysds.test.TestConfiguration;
import org.apache.sysds.test.TestUtils;
public class ScalarMultiplicationTest extends AutomatedTestBase
{
private static final String TEST_DIR = "functions/binary/matrix/";
private static final String TEST_CLASS_DIR = TEST_DIR + ScalarMultiplicationTest.class.getSimpleName() + "/";
@Override
public void setUp() {
TestUtils.clearAssertionInformation();
// positive tests
addTestConfiguration("IntConstTest", new TestConfiguration(TEST_CLASS_DIR,"ScalarMultiplicationTest",
new String[] { "vector_left", "vector_right", "matrix_left", "matrix_right" }));
addTestConfiguration("IntVarTest", new TestConfiguration(TEST_CLASS_DIR,"ScalarMultiplicationTest",
new String[] { "vector_left", "vector_right", "matrix_left", "matrix_right" }));
addTestConfiguration("DoubleConstTest", new TestConfiguration(TEST_CLASS_DIR,"ScalarMultiplicationTest",
new String[] { "vector_left", "vector_right", "matrix_left", "matrix_right" }));
addTestConfiguration("DoubleVarTest", new TestConfiguration(TEST_CLASS_DIR,"ScalarMultiplicationTest",
new String[] { "vector_left", "vector_right", "matrix_left", "matrix_right" }));
addTestConfiguration("SparseTest", new TestConfiguration(TEST_CLASS_DIR,"ScalarMultiplicationTest",
new String[] { "vector_left", "vector_right", "matrix_left", "matrix_right" }));
addTestConfiguration("EmptyTest", new TestConfiguration(TEST_CLASS_DIR,"ScalarMultiplicationTest",
new String[] { "vector_left", "vector_right", "matrix_left", "matrix_right" }));
// negative tests
}
@Test
public void testIntConst() {
int rows = 10;
int cols = 10;
int factor = 2;
TestConfiguration config = availableTestConfigurations.get("IntConstTest");
config.addVariable("rows", rows);
config.addVariable("cols", cols);
config.addVariable("vardeclaration", "");
config.addVariable("factor", factor);
loadTestConfiguration(config);
double[][] vector = getRandomMatrix(rows, 1, 0, 1, 1, -1);
double[][] computedVector = new double[rows][1];
for(int i = 0; i < rows; i++) {
computedVector[i][0] = vector[i][0] * factor;
}
writeInputMatrix("vector", vector);
writeExpectedMatrix("vector_left", computedVector);
writeExpectedMatrix("vector_right", computedVector);
double[][] matrix = getRandomMatrix(rows, cols, 0, 1, 1, -1);
double[][] computedMatrix = new double[rows][cols];
for(int i = 0; i < rows; i++) {
for(int j = 0; j < cols; j++) {
computedMatrix[i][j] = matrix[i][j] * factor;
}
}
writeInputMatrix("matrix", matrix);
writeExpectedMatrix("matrix_left", computedMatrix);
writeExpectedMatrix("matrix_right", computedMatrix);
runTest();
compareResults();
}
@Test
public void testIntVar() {
int rows = 10;
int cols = 10;
int factor = 2;
TestConfiguration config = availableTestConfigurations.get("IntVarTest");
config.addVariable("rows", rows);
config.addVariable("cols", cols);
config.addVariable("vardeclaration", "Factor = " + factor);
config.addVariable("factor", "Factor");
loadTestConfiguration(config);
double[][] vector = getRandomMatrix(rows, 1, 0, 1, 1, -1);
double[][] computedVector = new double[rows][1];
for(int i = 0; i < rows; i++) {
computedVector[i][0] = vector[i][0] * factor;
}
writeInputMatrix("vector", vector);
writeExpectedMatrix("vector_left", computedVector);
writeExpectedMatrix("vector_right", computedVector);
double[][] matrix = getRandomMatrix(rows, cols, 0, 1, 1, -1);
double[][] computedMatrix = new double[rows][cols];
for(int i = 0; i < rows; i++) {
for(int j = 0; j < cols; j++) {
computedMatrix[i][j] = matrix[i][j] * factor;
}
}
writeInputMatrix("matrix", matrix);
writeExpectedMatrix("matrix_left", computedMatrix);
writeExpectedMatrix("matrix_right", computedMatrix);
runTest();
compareResults();
}
@Test
public void testDoubleConst() {
int rows = 10;
int cols = 10;
double factor = 2;
TestConfiguration config = availableTestConfigurations.get("DoubleConstTest");
config.addVariable("rows", rows);
config.addVariable("cols", cols);
config.addVariable("vardeclaration", "");
config.addVariable("factor", factor);
loadTestConfiguration(config);
double[][] vector = getRandomMatrix(rows, 1, 0, 1, 1, -1);
double[][] computedVector = new double[rows][1];
for(int i = 0; i < rows; i++) {
computedVector[i][0] = vector[i][0] * factor;
}
writeInputMatrix("vector", vector);
writeExpectedMatrix("vector_left", computedVector);
writeExpectedMatrix("vector_right", computedVector);
double[][] matrix = getRandomMatrix(rows, cols, 0, 1, 1, -1);
double[][] computedMatrix = new double[rows][cols];
for(int i = 0; i < rows; i++) {
for(int j = 0; j < cols; j++) {
computedMatrix[i][j] = matrix[i][j] * factor;
}
}
writeInputMatrix("matrix", matrix);
writeExpectedMatrix("matrix_left", computedMatrix);
writeExpectedMatrix("matrix_right", computedMatrix);
runTest();
compareResults();
}
@Test
public void testDoubleVar() {
int rows = 10;
int cols = 10;
double factor = 2;
TestConfiguration config = availableTestConfigurations.get("DoubleVarTest");
config.addVariable("rows", rows);
config.addVariable("cols", cols);
config.addVariable("vardeclaration", "Factor = " + factor);
config.addVariable("factor", "Factor");
loadTestConfiguration(config);
double[][] vector = getRandomMatrix(rows, 1, 0, 1, 1, -1);
double[][] computedVector = new double[rows][1];
for(int i = 0; i < rows; i++) {
computedVector[i][0] = vector[i][0] * factor;
}
writeInputMatrix("vector", vector);
writeExpectedMatrix("vector_left", computedVector);
writeExpectedMatrix("vector_right", computedVector);
double[][] matrix = getRandomMatrix(rows, cols, 0, 1, 1, -1);
double[][] computedMatrix = new double[rows][cols];
for(int i = 0; i < rows; i++) {
for(int j = 0; j < cols; j++) {
computedMatrix[i][j] = matrix[i][j] * factor;
}
}
writeInputMatrix("matrix", matrix);
writeExpectedMatrix("matrix_left", computedMatrix);
writeExpectedMatrix("matrix_right", computedMatrix);
runTest();
compareResults();
}
@Test
public void testSparse() {
int rows = 100;
int cols = 50;
int factor = 2;
TestConfiguration config = availableTestConfigurations.get("SparseTest");
config.addVariable("rows", rows);
config.addVariable("cols", cols);
config.addVariable("vardeclaration", "");
config.addVariable("factor", factor);
loadTestConfiguration(config);
double[][] vector = getRandomMatrix(rows, 1, -1, 1, 0.05, -1);
double[][] computedVector = new double[rows][1];
for(int i = 0; i < rows; i++) {
computedVector[i][0] = vector[i][0] * factor;
}
writeInputMatrix("vector", vector);
writeExpectedMatrix("vector_left", computedVector);
writeExpectedMatrix("vector_right", computedVector);
double[][] matrix = getRandomMatrix(rows, cols, -1, 1, 0.05, -1);
double[][] computedMatrix = new double[rows][cols];
for(int i = 0; i < rows; i++) {
for(int j = 0; j < cols; j++) {
computedMatrix[i][j] = matrix[i][j] * factor;
}
}
writeInputMatrix("matrix", matrix);
writeExpectedMatrix("matrix_left", computedMatrix);
writeExpectedMatrix("matrix_right", computedMatrix);
runTest();
compareResults();
}
}