/*
 * Copyright 2020 Red Hat, Inc. and/or its affiliates.
 *
 * 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.
 */
package org.kie.pmml.kogito.quarkus.example;

import org.junit.jupiter.api.Test;

import io.quarkus.test.junit.QuarkusTest;
import io.restassured.RestAssured;
import io.restassured.http.ContentType;
import io.restassured.path.json.config.JsonPathConfig;

import static io.restassured.RestAssured.given;
import static io.restassured.config.JsonConfig.jsonConfig;
import static org.hamcrest.Matchers.closeTo;
import static org.hamcrest.Matchers.comparesEqualTo;
import static org.hamcrest.Matchers.is;

@QuarkusTest
public class DMNRegressionTest {

    static {
        RestAssured.enableLoggingOfRequestAndResponseIfValidationFails();
    }

    @Test
    public void testEvaluateRegressionDMN() {
        String inputData = "{\"fld1\":3.0, \"fld2\":2.0, \"fld3\":\"y\"}";
        given()
                .config(RestAssured.config().jsonConfig(jsonConfig().numberReturnType(JsonPathConfig.NumberReturnType.DOUBLE)))
                .contentType(ContentType.JSON)
                .body(inputData)
                .when()
                .post("/TestRegressionDMN")
                .then()
                .statusCode(200)
                .body("RegressionModelBKM", is("function RegressionModelBKM( fld1, fld2, fld3 )"))
                .body("fld3", is("y")) // was input
                .body("fld2", is(comparesEqualTo(2))) // was input
                .body("fld1", is(comparesEqualTo(3))) // was input
                .body("Decision", is(closeTo(52.5, 0))) // real decision output 
        ;
    }
}
