From 11a6542bf2704de3cbba22843fa8322e87569cc0 Mon Sep 17 00:00:00 2001
From: Krishna Vedala <7001608+kvedala@users.noreply.github.com>
Date: Fri, 26 Jun 2020 08:04:01 -0400
Subject: [PATCH] added test cases

---
 .../ordinary_least_squares_regressor.cpp      | 39 +++++++++++++++++++
 1 file changed, 39 insertions(+)

diff --git a/numerical_methods/ordinary_least_squares_regressor.cpp b/numerical_methods/ordinary_least_squares_regressor.cpp
index bbd75a742..d36a84042 100644
--- a/numerical_methods/ordinary_least_squares_regressor.cpp
+++ b/numerical_methods/ordinary_least_squares_regressor.cpp
@@ -9,6 +9,7 @@
  *
  * \author [Krishna Vedala](https://github.com/kvedala)
  */
+#include <cassert>
 #include <iomanip>  // for print formatting
 #include <iostream>
 #include <vector>
@@ -352,10 +353,48 @@ std::vector<float> predict_OLS_regressor(std::vector<std::vector<T>> const &X,
     return result;
 }
 
+/** Self test checks */
+void test() {
+    int F = 3, N = 5;
+
+    // test function = x^2 -5
+    std::cout << "Test 1 (quadratic function)....";
+    std::vector<std::vector<float>> data1(
+        {{-5, 25, -125}, {-1, 1, -1}, {0, 0, 0}, {1, 1, 1}, {6, 36, 216}});
+    std::vector<float> Y1({20, -4, -5, -4, 31});
+    std::vector<float> beta1 = fit_OLS_regressor(data1, Y1);
+    std::vector<std::vector<float>> test1(
+        {{-2, 4, -8}, {2, 4, 8}, {-10, 100, -1000}, {10, 100, 1000}});
+    std::vector<float> expected1({-1, -1, 95, 95});
+    std::vector<float> out1 = predict_OLS_regressor(test1, beta1);
+    for (size_t rows = 0; rows < out1.size(); rows++)
+        assert(std::abs(out1[rows] - expected1[rows]) < 0.01);  // accuracy
+    std::cout << "passed\n";
+
+    // test function = x^3 + x^2 - 100
+    std::cout << "Test 2 (cubic function)....";
+    std::vector<std::vector<float>> data2(
+        {{-5, 25, -125}, {-1, 1, -1}, {0, 0, 0}, {1, 1, 1}, {6, 36, 216}});
+    std::vector<float> Y2({-200, -100, -100, 98, 152});
+    std::vector<float> beta2 = fit_OLS_regressor(data2, Y2);
+    std::vector<std::vector<float>> test2(
+        {{-2, 4, -8}, {2, 4, 8}, {-10, 100, -1000}, {10, 100, 1000}});
+    std::vector<float> expected2({-104, -88, -1000, 1000});
+    std::vector<float> out2 = predict_OLS_regressor(test2, beta2);
+    for (size_t rows = 0; rows < out2.size(); rows++)
+        assert(std::abs(out2[rows] - expected2[rows]) < 0.01);  // accuracy
+    std::cout << "passed\n";
+
+    std::cout << std::endl;  // ensure test results are displayed on screen
+                             // (flush stdout)
+}
+
 /**
  * main function
  */
 int main() {
+    test();
+
     size_t N, F;
 
     std::cout << "Enter number of features: ";