Remove billiard walk keep only accelerated billiard, enhance volume tests, fix typos

Author: vissarion

CMakeLists.txt

@@ -46,7 +46,7 @@ if(NOT Eigen3_FOUND)
 endif()
 
 # ─── Find Boost ──────────────────────────────────────────────────────────────
-# volesti only needs Boost headers (random, math) – no compiled libraries required
+# volesti only needs Boost headers (random, math) - no compiled libraries required
 find_package(Boost 1.56 REQUIRED)
 if(NOT Boost_FOUND)
     # Fallback: locate headers manually

README.md

@@ -35,7 +35,7 @@ a high-performance library for **volume approximation** and **sampling** of conv
 | Boost | ≥ 1.56 (headers + `random`, `math`) |
 
 Optional:
-* **LP-solve 5.5** – needed for VPolytope inner ball computation (otherwise auto-disabled)
+* **LP-solve 5.5** - needed for VPolytope inner ball computation (otherwise auto-disabled)
 
 ---
 
@@ -237,7 +237,7 @@ volestipy/
 ├── pyproject.toml
 ├── README.md
 ├── external/
-│   └── volesti/                 # git submodule – volesti library
+│   └── volesti/                 # git submodule - volesti library
 ├── src/
 │   └── bindings/
 │       └── volesti_bindings.cpp # pybind11 binding definitions
@@ -257,15 +257,15 @@ volestipy/
 
 ## Relationship to Other Projects
 
-* **[volesti](https://github.com/GeomScale/volesti)** – the underlying C++ library
-* **[dingo](https://github.com/GeomScale/dingo)** – metabolic network analysis using volesti
-* **volestipy** – a standalone, general-purpose Python binding via pybind11
+* **[volesti](https://github.com/GeomScale/volesti)** - the underlying C++ library
+* **[dingo](https://github.com/GeomScale/dingo)** - metabolic network analysis using volesti
+* **volestipy** - a standalone, general-purpose Python binding via pybind11
 
 ---
 
 ## License
 
 GNU Lesser General Public License v3.0 — see [LICENSE](LICENSE).
 
-Copyright (c) 2012–2024 Vissarion Fisikopoulos, Apostolos Chalkis, Elias Tsigaridas
+Copyright (c) 2012-2024 Vissarion Fisikopoulos, Apostolos Chalkis, Elias Tsigaridas
 and contributors.

examples/example_hypercube.py

@@ -17,13 +17,13 @@
 
 def main():
     print("=" * 60)
-    print("volestipy – hypercube example")
+    print("volestipy - hypercube example")
     print("=" * 60)
 
     # ------------------------------------------------------------------
     # 1. Build the 4-D hypercube [-1, 1]^4
     # ------------------------------------------------------------------
-    d = 10
+    d = 40
     P = hypercube(d)
     print(f"\nPolytope: {P}")
     center, radius = P.compute_inner_ball()

examples/example_random_polytope.py

@@ -32,7 +32,7 @@ def random_hpoly(d: int, m: int, seed: int = 0) -> HPolytope:
 
 def main():
     print("=" * 60)
-    print("volestipy – random polytope example")
+    print("volestipy - random polytope example")
     print("=" * 60)
 
     d = 5    # dimension

setup.py

@@ -1,5 +1,5 @@
 """
-setup.py for volestipy – Python bindings for the volesti library.
+setup.py for volestipy - Python bindings for the volesti library.
 
 Build:
     pip install . --no-build-isolation
@@ -98,7 +98,7 @@ def build_extension(self, ext: CMakeExtension) -> None:
         "License :: OSI Approved :: GNU Lesser General Public License v3 (LGPLv3)",
         "Programming Language :: Python :: 3",
         "Programming Language :: C++",
-        "Topic :: Scientific/Engineering :: Mathematics",
+        "Topic :: Scientific/Engineering :: Mathematics :: Optimization",
     ],
     zip_safe=False,
 )

src/bindings/volesti_bindings.cpp

@@ -128,14 +128,10 @@ MatrixXd hpoly_uniform_sample(HPolytopeType& P,
         uniform_sampling<BallWalk>(randPoints, P, rng,
                                    walk_length, n_samples,
                                    starting_point, n_burns);
-    } else if (walk_type == "billiard" || walk_type == "BilliardWalk") {
+    } else if (walk_type == "billiard" || walk_type == "AcceleratedBilliardWalk") {
         uniform_sampling<BilliardWalk>(randPoints, P, rng,
                                        walk_length, n_samples,
                                        starting_point, n_burns);
-    } else if (walk_type == "accelerated_billiard" || walk_type == "AcceleratedBilliardWalk") {
-        uniform_sampling<AcceleratedBilliardWalk>(randPoints, P, rng,
-                                                  walk_length, n_samples,
-                                                  starting_point, n_burns);
     } else if (walk_type == "dikin" || walk_type == "DikinWalk") {
         uniform_sampling<DikinWalk>(randPoints, P, rng,
                                     walk_length, n_samples,
@@ -151,7 +147,7 @@ MatrixXd hpoly_uniform_sample(HPolytopeType& P,
     } else {
         throw std::invalid_argument("Unknown walk type: '" + walk_type +
             "'. Choose from: cdhr, rdhr, ball_walk, billiard, "
-            "accelerated_billiard, dikin, john, vaidya.");
+            "dikin, john, vaidya.");
     }
 
     return points_to_matrix(randPoints);
@@ -492,7 +488,7 @@ PYBIND11_MODULE(_volestipy, m) {
             Number of burn-in steps.
         walk_type : str
             Walk algorithm. One of: 'cdhr', 'rdhr', 'ball_walk',
-            'billiard', 'accelerated_billiard', 'dikin', 'john', 'vaidya'.
+            'billiard', 'dikin', 'john', 'vaidya'.
         seed : int
             Random seed.
 

tests/conftest.py

@@ -1,4 +1,4 @@
-# conftest.py – shared pytest fixtures for volestipy tests
+# conftest.py - shared pytest fixtures for volestipy tests
 import pytest
 import numpy as np
 

tests/test_hpolytope.py

@@ -1,5 +1,5 @@
 """
-Tests for volestipy.HPolytope – construction, membership, sampling, volume.
+Tests for volestipy.HPolytope - construction, membership, sampling, volume.
 """
 import math
 import numpy as np
@@ -168,9 +168,9 @@ def test_invalid_walk_type(self):
         with pytest.raises((RuntimeError, ValueError, Exception)):
             P.sample(walk_type="unknown_walk_xyz")
 
-    def test_accelerated_billiard(self):
+    def test_billiard(self):
         P = make_cube_hpoly(4)
-        samples = P.sample(n_samples=50, walk_type="accelerated_billiard", seed=0)
+        samples = P.sample(n_samples=50, walk_type="billiard", seed=0)
         assert samples.shape == (4, 50)
 
     @pytest.mark.parametrize("walk_type", ["dikin", "john", "vaidya"])

tests/test_vpolytope.py

@@ -1,5 +1,5 @@
 """
-Tests for volestipy.VPolytope – construction, membership, sampling, volume.
+Tests for volestipy.VPolytope - construction, membership, sampling, volume.
 """
 import math
 import numpy as np
@@ -105,7 +105,7 @@ def test_inner_ball_simplex(self):
 # ── Sampling tests ────────────────────────────────────────────────────────────
 
 class TestVPolytopeUniformSampling:
-    @pytest.mark.parametrize("walk_type", ["cdhr", "rdhr", "ball_walk"])
+    @pytest.mark.parametrize("walk_type", ["cdhr", "rdhr", "ball_walk", "billiard"])
     def test_sample_shape(self, walk_type):
         P = make_simplex_vpoly(3)
         samples = P.sample(n_samples=100, walk_type=walk_type, seed=42)
@@ -135,21 +135,25 @@ def test_sample_inside_square(self):
 # ── Volume tests ──────────────────────────────────────────────────────────────
 
 class TestVPolytopeVolume:
-    def test_simplex_volume_2d(self):
+    #cooling_gaussians not applicable to V-polytopes
+    @pytest.mark.parametrize("volume_algo", ["cooling_balls", "sequence_of_balls"]) 
+    def test_simplex_volume_2d(self, volume_algo):
         # Vol(triangle with vertices (0,0),(1,0),(0,1)) = 0.5
         V = np.array([[0., 0.], [1., 0.], [0., 1.]])
         P = VPolytope(V)
-        vol = P.volume(error=0.3, algorithm="cooling_balls")
+        vol = P.volume(error=0.3, algorithm=volume_algo)
         expected = 0.5
         assert abs(vol - expected) / expected < 1.0, f"vol={vol:.4f}"
 
-    def test_square_volume(self):
+    @pytest.mark.parametrize("volume_algo", ["cooling_balls", "sequence_of_balls"])
+    def test_square_volume(self, volume_algo):
         P = make_cube_vpoly_2d()
-        vol = P.volume(error=0.3, algorithm="cooling_balls")
+        vol = P.volume(error=0.3, algorithm=volume_algo)
         expected = 4.0  # 2x2 square
         assert abs(vol - expected) / expected < 0.5, f"vol={vol:.3f}"
 
-    def test_volume_positive(self):
+    @pytest.mark.parametrize("volume_algo", ["cooling_balls", "sequence_of_balls"])
+    def test_volume_positive(self, volume_algo):
         P = make_simplex_vpoly(3)
-        vol = P.volume(error=0.3)
+        vol = P.volume(error=0.3, algorithm=volume_algo)
         assert vol > 0

volestipy/__init__.py

@@ -1,5 +1,5 @@
 """
-volestipy – Python bindings for the volesti C++ library.
+volestipy - Python bindings for the volesti C++ library.
 
 This module re-exports the C++ pybind11 extension and adds
 convenient Python-level wrappers and utilities.
@@ -74,7 +74,7 @@ class HPolytope:
     """
     H-Polytope: a convex polytope in half-space representation.
 
-        P = { x ∈ ℝ^d : A x ≤ b }
+        P = { x ∈ R^d : A x ≤ b }
 
     Parameters
     ----------
@@ -174,14 +174,13 @@ def sample(
         walk_type : str
             MCMC walk type. Supported options:
 
-            * ``'cdhr'`` – Coordinate Directions Hit-and-Run (default)
-            * ``'rdhr'`` – Random Directions Hit-and-Run
-            * ``'ball_walk'`` – Ball Walk
-            * ``'billiard'`` – Billiard Walk
-            * ``'accelerated_billiard'`` – Accelerated Billiard Walk
-            * ``'dikin'`` – Dikin Walk
-            * ``'john'`` – John Walk
-            * ``'vaidya'`` – Vaidya Walk
+            * ``'cdhr'`` - Coordinate Directions Hit-and-Run (default)
+            * ``'rdhr'`` - Random Directions Hit-and-Run
+            * ``'ball_walk'`` - Ball Walk
+            * ``'billiard'`` - Billiard Walk (Accelerated Billiard Walk)
+            * ``'dikin'`` - Dikin Walk
+            * ``'john'`` - John Walk
+            * ``'vaidya'`` - Vaidya Walk
         seed : int
             Random number generator seed.