Add example to CI.

.github/workflows/ci.yml

@@ -44,6 +44,8 @@ jobs:
         run: pixi run -e ${{ matrix.environment }} install-nightlies
       - name: Install repository
         run: pixi run -e ${{ matrix.environment }} postinstall
+      - name: Run Malte's example
+        run: pixi run -e ${{ matrix.environment }} python example.py 
       - name: Run pytest
         run: pixi run -e ${{ matrix.environment }} test -nauto -m "not high_memory"
       - name: Run doctest

example.py

@@ -0,0 +1,37 @@
+import numpy as np
+
+import tabmat
+
+np.set_printoptions(suppress=True)
+
+for dtype in [np.float32, np.float64]:
+    X = np.array(
+        [
+            [46.231056, 126.05263, 144.46439],
+            [46.231224, 128.66818, 0.7667693],
+            [46.231186, 104.97506, 193.8872],
+            [46.230835, 130.10156, 143.88954],
+            [46.230896, 116.76007, 7.5629334],
+        ],
+        dtype=dtype,
+    )
+    v = np.array(
+        [0.12428328, 0.67062443, 0.6471895, 0.6153851, 0.38367754], dtype=dtype
+    )
+
+    weights = np.full(X.shape[0], 1 / X.shape[0], dtype=dtype)
+
+    stmat, out_means, col_stds = tabmat.DenseMatrix(X).standardize(weights, True, True)
+
+    print(stmat.toarray().T @ v)
+    print(stmat.transpose_matvec(v))
+
+    # compute by hand
+    res = np.zeros(X.shape[1], dtype=dtype)
+    for col in range(X.shape[1]):
+        res[col] += (
+            stmat.shift[col] + stmat.mult[col] * stmat.mat.toarray()[:, col]
+        ) @ v
+
+    print(res)
+    print("\n")