Ask Claude's opinion on improvements

Author: WrathfulSpatula

pyproject.toml

@@ -7,7 +7,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "pyqrackising"
-version = "9.11.3"
+version = "9.11.4"
 requires-python = ">=3.8"
 description = "Fast MAXCUT, TSP, and sampling heuristics from near-ideal transverse field Ising model (TFIM)"
 readme = {file = "README.txt", content-type = "text/markdown"}

pyqrackising/spin_glass_solver.py

@@ -118,7 +118,7 @@ def pick_gray_seeds(best_theta, thread_count, gray_seed_multiple, G_m, n, is_spi
         best_energies[i] = energies[idx]
 
     if is_spin_glass:
-        best_energies[0] *= 2.0
+        best_energies *= 2.0
 
     return best_seeds, best_energies[0]
 
@@ -352,6 +352,7 @@ def spin_glass_solver(
         best_guess = None
 
     bitstring = ""
+    cut_value = None
     if isinstance(best_guess, str):
         bitstring = best_guess
     elif isinstance(best_guess, int):
@@ -372,7 +373,12 @@ def spin_glass_solver(
         )
 
     best_theta = np.array([b == "1" for b in list(bitstring)], dtype=np.bool_)
-    max_energy = compute_energy(best_theta, G_m, n_qubits) if is_spin_glass else cut_value
+    if is_spin_glass:
+        max_energy = compute_energy(best_theta, G_m, n_qubits)
+    elif cut_value is None:
+        max_energy = compute_cut(best_theta, G_m, n_qubits)
+    else:
+        max_energy = cut_value
 
     if n_qubits < heuristic_threshold:
         bitstring, l, r = get_cut(best_theta, nodes, n_qubits)

pyqrackising/spin_glass_solver_sparse.py

@@ -419,6 +419,7 @@ def spin_glass_solver_sparse(
         best_guess = None
 
     bitstring = ""
+    cut_value = None
     if isinstance(best_guess, str):
         bitstring = best_guess
     elif isinstance(best_guess, int):
@@ -439,7 +440,12 @@ def spin_glass_solver_sparse(
         )
 
     best_theta = np.array([b == "1" for b in list(bitstring)], dtype=np.bool_)
-    max_energy = compute_energy_sparse(best_theta, G_m.data, G_m.indptr, G_m.indices, n_qubits) if is_spin_glass else cut_value
+    if is_spin_glass:
+        max_energy = compute_energy_sparse(best_theta, G_m.data, G_m.indptr, G_m.indices, n_qubits)
+    elif cut_value is None:
+        max_energy = compute_cut_sparse(best_theta, G_m.data, G_m.indptr, G_m.indices, n_qubits)
+    else:
+        max_energy = cut_value
 
     if n_qubits < heuristic_threshold_sparse:
         bitstring, l, r = get_cut(best_theta, nodes, n_qubits)

pyqrackising/spin_glass_solver_streaming.py

@@ -109,7 +109,7 @@ def pick_gray_seeds(best_theta, thread_count, gray_seed_multiple, G_func, nodes,
         best_energies[i] = energies[idx]
 
     if is_spin_glass:
-        best_energies[0] *= 2.0
+        best_energies *= 2.0
 
     return best_seeds, best_energies[0]
 
@@ -180,6 +180,7 @@ def spin_glass_solver_streaming(
         best_guess = None
 
     bitstring = ""
+    cut_value = None
     if isinstance(best_guess, str):
         bitstring = best_guess
     elif isinstance(best_guess, int):
@@ -199,7 +200,12 @@ def spin_glass_solver_streaming(
         )
 
     best_theta = np.array([b == "1" for b in list(bitstring)], dtype=np.bool_)
-    max_energy = compute_energy(best_theta, G_m, n_qubits) if is_spin_glass else cut_value
+    if is_spin_glass:
+        max_energy = compute_energy_streaming(best_theta, G_func, nodes, n_qubits)
+    elif cut_value is None:
+        max_energy = compute_cut_streaming(best_theta, G_func, nodes, n_qubits)
+    else:
+        max_energy = cut_value
 
     if n_qubits < heuristic_threshold:
         bitstring, l, r = get_cut(best_theta, nodes, n_qubits)

setup.py

@@ -7,7 +7,7 @@
 
 setup(
     name="pyqrackising",
-    version="9.11.3",
+    version="9.11.4",
     author="Dan Strano",
     author_email="stranoj@gmail.com",
     description="Fast MAXCUT, TSP, and sampling heuristics from near-ideal transverse field Ising model (TFIM)",