Smooth ect

doc_source/directions.md

@@ -0,0 +1,6 @@
+# Directions 
+
+```{eval-rst}
+.. automodule:: ect.directions
+   :members:
+```

doc_source/ect_on_graphs.md

@@ -4,3 +4,8 @@
 .. automodule:: ect.ect_graph
    :members:
 ```
+
+```{eval-rst}
+.. automodule:: ect.sect
+   :members:
+```

doc_source/modules.rst

@@ -7,4 +7,5 @@ Table of Contents
 
    Embedded graphs <embed_graph.md>
    Embedded CW complex <embed_cw.md>
-   ECT on graphs <ect_on_graphs.md>
+   ECT on graphs <ect_on_graphs.md>
+   Directions <directions.md>

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "ect"
-version = "1.0.0"
+version = "1.0.2"
 authors = [
   { name="Liz Munch", email="muncheli@msu.edu" },
 ]

src/ect/__init__.py

@@ -12,12 +12,14 @@
 from .embed_graph import EmbeddedGraph
 from .embed_cw import EmbeddedCW
 from .directions import Directions
+from .sect import SECT
 from .utils import examples
 
 __all__ = [
-    'ECT',
-    'EmbeddedGraph',
-    'EmbeddedCW',
-    'Directions',
-    'examples',
+    "ECT",
+    "SECT",
+    "EmbeddedGraph",
+    "EmbeddedCW",
+    "Directions",
+    "examples",
 ]

src/ect/sect.py

@@ -0,0 +1,59 @@
+from ect import ECT
+from .embed_graph import EmbeddedGraph
+from .embed_cw import EmbeddedCW
+from .directions import Directions
+from .results import ECTResult
+from typing import Optional, Union
+import numpy as np
+
+
+class SECT(ECT):
+    """
+    A class to calculate the Smooth Euler Characteristic Transform (SECT).
+    Inherits from ECT and applies smoothing to the final result.
+    """
+
+    def __init__(
+        self,
+        directions: Optional[Directions] = None,
+        num_dirs: Optional[int] = None,
+        num_thresh: Optional[int] = None,
+        bound_radius: Optional[float] = None,
+        thresholds: Optional[np.ndarray] = None,
+        dtype=np.float32,
+    ):
+        """Initialize SECT calculator with smoothing parameter
+
+        Args:
+            directions: Optional pre-configured Directions object
+            num_dirs: Number of directions to sample (ignored if directions provided)
+            num_thresh: Number of threshold values (required if directions not provided)
+            bound_radius: Optional radius for bounding circle
+            thresholds: Optional array of thresholds
+            dtype: Data type for output array
+        """
+        super().__init__(
+            directions, num_dirs, num_thresh, bound_radius, thresholds, dtype
+        )
+
+    def calculate(
+        self,
+        graph: Union[EmbeddedGraph, EmbeddedCW],
+        theta: Optional[float] = None,
+        override_bound_radius: Optional[float] = None,
+    ) -> ECTResult:
+        """Calculate Smooth Euler Characteristic Transform (SECT)
+
+        Args:
+            graph: The input graph to calculate the SECT for
+            theta: The angle in [0,2π] for the direction to calculate the SECT
+            override_bound_radius: Optional override for bounding radius
+
+        Returns:
+            ECTResult: The smoothed transform result containing the matrix,
+                      directions, and thresholds
+        """
+        ect_result = super().calculate(graph, theta, override_bound_radius)
+        return ECTResult(
+            ect_result, ect_result.directions, ect_result.thresholds
+        ).smooth()

tests/test_sect.py

@@ -0,0 +1,76 @@
+import unittest
+import numpy as np
+from ect import SECT, ECT
+from ect.utils.examples import create_example_graph
+from ect.directions import Directions
+
+
+class TestSECT(unittest.TestCase):
+    def setUp(self):
+        """Set up test fixtures"""
+        self.graph = create_example_graph()
+        self.num_dirs = 8
+        self.num_thresh = 10
+        self.sect = SECT(num_dirs=self.num_dirs, num_thresh=self.num_thresh)
+
+    def test_inheritance(self):
+        """Test that SECT properly inherits from ECT"""
+        self.assertIsInstance(self.sect, ECT)
+        self.assertTrue(hasattr(self.sect, "calculate"))
+
+    def test_calculate_output_shape(self):
+        """Test that SECT calculation returns correct shape"""
+        result = self.sect.calculate(self.graph)
+
+        self.assertEqual(result.shape[0], self.num_dirs)
+        self.assertEqual(result.shape[1], self.num_thresh)
+        self.assertEqual(len(result.thresholds), self.num_thresh)
+        self.assertEqual(len(result.directions), self.num_dirs)
+
+    def test_smoothing_effect(self):
+        """Test that smoothing is actually applied"""
+        # Calculate both ECT and SECT
+        ect = ECT(num_dirs=self.num_dirs, num_thresh=self.num_thresh)
+        sect = SECT(num_dirs=self.num_dirs, num_thresh=self.num_thresh)
+
+        ect_result = ect.calculate(self.graph)
+        sect_result = sect.calculate(self.graph)
+
+        # Verify results are different due to smoothing
+        self.assertFalse(np.allclose(ect_result, sect_result))
+
+        # Verify smoothing preserves direction count
+        self.assertEqual(
+            np.sum(ect_result, axis=1).shape,
+            np.sum(sect_result, axis=1).shape,
+        )
+
+    def test_with_theta(self):
+        """Test SECT calculation with specific theta value"""
+        theta = np.pi / 4
+        result = self.sect.calculate(self.graph, theta=theta)
+
+        # Should only have one direction when theta is specified
+        self.assertEqual(result.shape[0], 1)
+        self.assertEqual(result.shape[1], self.num_thresh)
+
+    def test_with_override_radius(self):
+        """Test SECT calculation with override_bound_radius"""
+        override_radius = 2.0
+        result = self.sect.calculate(self.graph, override_bound_radius=override_radius)
+
+        # Check that thresholds are within the override radius
+        self.assertLessEqual(np.max(np.abs(result.thresholds)), override_radius)
+
+    def test_smooth_matrix_properties(self):
+        """Test properties of the smoothed matrix"""
+        result = self.sect.calculate(self.graph)
+
+        # Smoothed values should be finite
+        self.assertTrue(np.all(np.isfinite(result)))
+
+        # Shape should be preserved after smoothing
+        self.assertEqual(result.shape, (self.num_dirs, self.num_thresh))
+
+        # Verify result is float type after smoothing
+        self.assertTrue(np.issubdtype(result.dtype, np.floating))