src/ports/postgres/modules/bayes/test/bayes.ic.sql_in

/* ----------------------------------------------------------------------- *//**
 *
 * 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.
 *
 *//* ----------------------------------------------------------------------- */

---------------------------------------------------------------------------
-- Rules:
-- ------
-- 1) Any DB objects should be created w/o schema prefix,
--    since this file is executed in a separate schema context.
-- 2) There should be no DROP statements in this script, since
--    all objects created in the default schema will be cleaned-up outside.
---------------------------------------------------------------------------

---------------------------------------------------------------------------
-- Setup:
---------------------------------------------------------------------------
CREATE OR REPLACE FUNCTION fill_feature(pre_class INT, p FLOAT, total INT)
RETURNS FLOAT AS $$
declare
	result FLOAT;
	thres INT;
begin
	thres = total*p;

	IF pre_class <= thres THEN
		result = 1;
	ELSE
		result = 0;
	END IF;
	RETURN result;
end
$$ language plpgsql;

-- ----------------
-- install_test_1()
-- ----------------
CREATE FUNCTION install_test_1() RETURNS VOID AS $$
declare
	num1 INT := 10;
	num2 INT := 10;

	result1 INT;
	count1 INT;
	tempvar INT[];

begin
	-- prepare training data: equal priors
	--DROP TABLE IF EXISTS data CASCADE;
	CREATE TABLE data_1( class INT, attrib FLOAT[] );
	INSERT INTO data_1 SELECT 1, ARRAY[fill_feature(id,0.3,num1),fill_feature(id,0.8,num1)] FROM generate_series(1,num1) as id;
	INSERT INTO data_1 SELECT 2, ARRAY[fill_feature(id,0.5,num2),fill_feature(id,0.5,num2)] FROM generate_series(1,num2) as id;

	-- prepare testing data
	--DROP TABLE IF EXISTS data_test CASCADE;
	CREATE TABLE data_test_1( id INT, attrib INT[], prob FLOAT[] );
	INSERT INTO data_test_1 VALUES (1,'{0,0}','{0.4,0.6}');
	INSERT INTO data_test_1 VALUES (2,'{0,1}','{0.66666,0.33333}');
	INSERT INTO data_test_1 VALUES (3,'{1,0}','{0.25,0.75}');
	INSERT INTO data_test_1 VALUES (4,'{1,1}','{0.5,0.5}');

	-- prepare true results for testing data
	--DROP TABLE IF EXISTS data_results;
	CREATE TABLE data_results_1 AS
		SELECT
			id,
			unnest('{1,2}'::INT[]) as class,
			unnest(prob) as prob
		FROM data_test_1;

	-- Process training
	--DROP TABLE IF EXISTS probs CASCADE;
	--DROP TABLE IF EXISTS priors CASCADE;
	PERFORM MADLIB_SCHEMA.create_nb_prepared_data_tables('data_1','class','attrib',2,'probs','priors');
	-- Classify
	--DROP VIEW IF EXISTS results;
	PERFORM MADLIB_SCHEMA.create_nb_classify_view('probs','priors','data_test_1','id','attrib',2,'results_1');
	-- Compute posteriors
	--DROP VIEW IF EXISTS probs_view;
	PERFORM MADLIB_SCHEMA.create_nb_probs_view('probs','priors','data_test_1','id','attrib',2,'probs_view_1');


end
$$ language plpgsql;

---------------------------------------------------------------------------
-- Test:
---------------------------------------------------------------------------
SELECT install_test_1();