src/ports/postgres/modules/linalg/test/matrix_ops.ic.sql_in

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 * 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
 *
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 * Unless required by applicable law or agreed to in writing,
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 * "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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 *//* ----------------------------------------------------------------------- */

m4_include(`SQLCommon.m4')

CREATE TABLE s(
    row_id INT8,
    col_id INT8,
    val INT4
)
m4_ifdef(`__GREENPLUM__',
`WITH (APPENDONLY=TRUE) DISTRIBUTED BY (row_id)');

INSERT INTO s VALUES(1, 1, 1) , (1, 2, 3) , (2, 1, 4) , (2, 2, 5) , (3, 1, 7) ,
                    (3, 2, 8), (3, 3, 0);

DROP TABLE IF EXISTS s_t;
SELECT matrix_trans('s', 'row=row_id, col=col_id, val=val', 's_t', 'row=row_num, col=col_num, val=val');

DROP TABLE IF EXISTS d;
SELECT matrix_densify('s', 'row=row_id, col=col_id, val=val', 'd');

DROP TABLE IF EXISTS s;
SELECT matrix_sparsify('d', 'row=row_id', 's', 'row=row_id, col=col_id, val=val');

DROP TABLE IF EXISTS s2;
SELECT matrix_mult('s', 'row=row_id, col=col_id, val=val, trans=false',
                   's_t', 'row=row_num, col=col_num, val=val, trans=false', 's2');

DROP TABLE IF EXISTS dd;
SELECT matrix_max('d', 'row=row_id', 1, 'dd', true);

DROP TABLE IF EXISTS dd;
SELECT matrix_min('d', 'row=row_id', 2, 'dd', true);

SELECT matrix_extract_col('d', 'row=row_id', 3);
SELECT matrix_extract_row('s', 'row=row_id, col=col_id, val=val', 1);

DROP TABLE IF EXISTS d_d;
SELECT matrix_square('d', 'row=row_id', 'd_d');

DROP TABLE IF EXISTS s3;
SELECT matrix_add('s', 'row=row_id, col=col_id, val=val',
                  's', 'row=row_id, col=col_id, val=val',
                  's3');

DROP TABLE IF EXISTS s3;
SELECT matrix_sub('s', 'row=row_id, col=col_id, val=val',
                  's', 'row=row_id, col=col_id, val=val',
                  's3');

DROP TABLE IF EXISTS s3;
SELECT matrix_elem_mult('s', 'row=row_id, col=col_id, val=val',
                        's', 'row=row_id, col=col_id, val=val',
                        's3');

CREATE TABLE b(
    row_id INT4,
    col_id INT4,
    block INT4[]
)
m4_ifdef(`__GREENPLUM__',
`WITH (APPENDONLY=TRUE) DISTRIBUTED BY (row_id)');

INSERT INTO b VALUES(1, 1, array[[1,2], [3,4]]);
INSERT INTO b VALUES(2, 1, array[[5,6], [7,8]]);
INSERT INTO b VALUES(3, 1, array[[9,10]]);


SELECT matrix_mem_trans(array[[1,2,3], [4,5,6]]);
SELECT matrix_mem_mult(array[[1,2,3], [4,5,6]], array[[1,4],[2,5],[3,6]]);

DROP TABLE if exists b_t;
SELECT matrix_block_trans('b', 'row=row_id, col=col_id, val=block', 'b_t', NULL);

DROP TABLE if exists b2;
SELECT matrix_block_square('b', 'row=row_id, col=col_id, val=block', 'b2', NULL);

DROP TABLE if exists b2;
SELECT matrix_block_mult('b', 'row=row_id, col=col_id, val=block',
                         'b_t', 'row=row_id, col=col_id, val=block',
                         'b2', NULL);

DROP TABLE if exists d_b;
SELECT matrix_blockize('d', 'row=row_id', 2, 2, 'd_b');

DROP TABLE if exists d_r;
SELECT matrix_unblockize('d_b', 'row=row_id', 'd_r', NULL);



CREATE TABLE random_matrix(row_id INTEGER, row_vec DOUBLE PRECISION[]);
INSERT INTO random_matrix VALUES
  (1, array[2, 2, 0]), (2, array[15, 2, 0]), (3, array[0, 5, 2]);

SELECT array_to_1d(__matrix_dense_inverse(3, row_id - 1, row_vec)) as result
FROM random_matrix;

CREATE TABLE random_sparse_matrix(row_id INTEGER, col_id INTEGER, val DOUBLE PRECISION);
INSERT INTO random_sparse_matrix VALUES
  (1, 1, 2), (1, 2, 2), (2, 1, 15), (2, 2, 2), (3, 2, 5), (3, 3, 2);
SELECT array_to_1d(__matrix_sparse_inverse(3, 3, row_id - 1, col_id - 1, val)) as result
FROM random_sparse_matrix