Add tests folders

tests/test_dimensionality_reduction.py

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+import unittest
+from sklearn import datasets
+from src.dimensionality_reduction import DimensionalityReduction
+
+dr = DimensionalityReduction()
+
+class TestDimensionalityReduction(unittest.TestCase):
+
+    def setUp(self):
+
+        iris_dataset = datasets.load_iris()
+
+        self.X = iris_dataset.data[:, :3]
+        self.y = iris_dataset.target
+
+    def test_tsne(self):
+
+        df = dr.tsne(self.X, self.y, 2)
+
+        assert df.shape == (150, 3)
+
+    def test_umap(self):
+
+        df = dr.UMAP(self.X, self.y, 2)
+
+        assert df.shape == (150, 3)
+
+    def test_lda(self):
+
+        df = dr.lda(self.X, self.y)
+
+        assert df.shape == (150, 3)   
+
+    def test_pca(self):
+
+        df = dr.pca(self.X, self.y, 2)
+
+        assert df.shape == (150, 3)
+
+    def test_factor_analysis(self):
+
+        df = dr.factor_analysis(self.X, self.y, 2)
+
+        assert df.shape == (150, 3)
+
+    def test_truncated_svd(self):
+
+        df = dr.truncated_svd(self.X, self.y, 2)
+
+        assert df.shape == (150, 3)
+
+    def test_kernal_pca(self):
+
+        df = dr.kernel_pca(self.X, self.y, 2)
+
+        assert df.shape == (150, 3)
+
+    def test_multidim_scaling(self):
+
+        df = dr.multidim_scaling(self.X, self.y, 2)
+
+        assert df.shape == (150, 3)
+
+    def test_isomap(self):
+
+        df = dr.isomap(self.X, self.y, 2)
+
+        assert df.shape == (150, 3)