Add testing infrastructure

.github/workflows/tests.yml

@@ -0,0 +1,27 @@
+name: Run pyECT E2E Tests
+
+on:
+  pull_request:
+    branches: ["main"]
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.10"
+
+      - name: Install dependencies
+        run: |
+          pip install --upgrade pip
+          pip install pytest
+          pip install -e .
+
+      - name: Run tests
+        run: pytest tests/

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "pyect"
-version = "0.1.7"
+version = "0.1.8"
 description = "Generalized computation of the weighted Euler characteristic transform using PyTorch."
 readme = "README.md"
 requires-python = ">=3.8"

tests/test_wect_triangle.py

@@ -0,0 +1,72 @@
+import torch
+import pytest
+
+from pyect import WECT
+from pyect import Complex
+
+
+def build_triangle_complexes(device="cpu"):
+    vcoords = torch.tensor(
+        [[-1.0, 0.0],
+         [ 0.0, 1.0],
+         [ 1.0, 0.0]], device=device
+    )
+    vweights_ones = torch.ones(3, device=device)
+    vweights = torch.tensor([0.5, 1.0, 1.5], device=device)
+
+    ecoords = torch.tensor(
+        [[0, 1],
+         [1, 2],
+         [2, 0]], device=device
+    )
+    eweights_ones = torch.ones(3, device=device)
+    eweights = torch.tensor([.5, 1.0, 0.5], device=device)
+
+    fcoords = torch.tensor([[0, 1, 2]], device=device)
+    fweights_ones = torch.ones(1, device=device)
+    fweights = torch.tensor([0.5], device=device)
+
+    return Complex(
+        (vcoords, vweights_ones),
+        (ecoords, eweights_ones),
+        (fcoords, fweights_ones),
+    ), Complex(
+        (vcoords, vweights),
+        (ecoords, eweights),
+        (fcoords, fweights),
+    ), 
+
+
+# ----------------------------------------------------------
+# WECT TEST
+# ----------------------------------------------------------
+
+def test_wect_exact_triangle_direction_10():
+    device = torch.device("cpu")
+
+    complex_unweighted, complex_weighted = build_triangle_complexes(device=device)
+
+
+    # UNWEIGHTED COMPLEX
+    # single direction (1,0)
+    dirs = torch.tensor([[1.0, 0.0]], device=device)
+
+    num_bins = 3
+    wect = WECT(dirs, num_bins).eval()
+
+    result = wect(complex_unweighted)  # shape (1,3)
+
+    assert result.shape == (1, num_bins)
+    assert torch.isfinite(result).all()
+
+    expected = torch.tensor([1.0, 1.0, 1.0], device=device)
+
+    assert torch.allclose(result[0], expected, atol=1e-6)
+
+    # WEIGHTED COMPLEX
+    result = wect(complex_weighted)  # shape (1,3)
+    assert result.shape == (1, num_bins)
+    assert torch.isfinite(result).all()
+
+    expected = torch.tensor([0.5, 1.0, 1.5], device=device)
+    assert torch.allclose(result[0], expected, atol=1e-6)