lmDS_rnd.daphne

/*
 * Copyright 2023 The DAPHNE Consortium
 *
 * Licensed 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.
 */

import "lmDS_.daph";

# Command-line arguments:
# r      ... the number of rows of the randomly generated feature matrix
# c      ... the number of columns of the randomly generated feature matrix
# icpt   ... the intercept value, must be in [0, 1, 2]
# rep    ... the number of repetitions

# Generate some random data.
X = rand($r, $c, 0.0, 1.0, 1, 12345);
y = rand($r,  1, 0.0, 1.0, 1, 67890);

# Parameters.
reg = 0.0000001;
verbose = false;

# Calculate and print something, such that the algorithm invocations are not optimized away.
foo = 0.0;

# Execute lmDS.
for(rep in 1:$rep) {
    t0 = now();
    b = lmDS_.lmDS(X, y, $icpt, reg, verbose);
    t1 = now();
    print((t1 - t0) + ";", false);
    foo = foo + sum(b);
}
print("\t", false);

print(foo, false);
print("\t", false);