| #------------------------------------------------------------- |
| # |
| # 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. |
| # |
| #------------------------------------------------------------- |
| |
| # imports |
| source("staging/gaussian_process/covariance.dml") as covariance |
| |
| X = matrix("1 2 3 |
| 4 5 6 |
| 7 8 9", rows=3, cols=3); |
| |
| # ability to give cholesky factorization, tests for the positive |
| # definiteness of the covariance matrix. |
| tmp = covariance::cov(X); |
| |
| for(ri in 1:nrow(X)) { |
| for(ci in 1:ncol(X)) { |
| print(as.scalar(tmp[ri, ci]) ) |
| } |
| } |