Introduce 08-network

ommx_quantum_benchmarks/qoblib/08_network/models/integer_lp/model.py

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+import jijmodeling as jm
+
+def build_ip_formulation() -> jm.Problem:
+    """Create integer programming formulation for the arc-based flow problem.
+
+    This model aligns with the ZPL (0-based) specification, formulating a
+    multi-commodity flow problem with integer scaling and big-M constraints.
+
+    Sets:
+        - N = {0..n−1}
+        - A = {(i, j) | i ≠ j}
+        - T = {(k, i, j) | i ≠ j and k ≠ j}
+
+    Parameters:
+        - n (int): Number of nodes.
+        - t (ndarray, shape (n, n)): Demand matrix, with zero diagonal.
+        - M (int): Big-M constant for capacity constraints.
+        - intscale (int): Integer scaling factor.
+
+    Variables:
+        - x[i, j] ∈ {0, 1}: Binary arc selection variable.
+        - f[k, i, j] ∈ ℤ, 0..intscale·M: Flow of commodity k on arc (i, j).
+        - z ∈ ℤ, 0..intscale·M: Global upper bound on flow.
+
+    Objective:
+        - Minimize z.
+
+    Constraints:
+        - c1: ∀ i ∈ N: Σ_{j ≠ i} x[i, j] = 2 (out-degree = 2).
+        - c2: ∀ j ∈ N: Σ_{i ≠ j} x[i, j] = 2 (in-degree = 2).
+        - c11: ∀ (k, i), k ≠ i:
+                  Σ_{j ≠ i} f[k, j, i] − Σ_{j ≠ i, j ≠ k} f[k, i, j]
+                  = t[k, i]·intscale
+        - c14: ∀ (k, i, j), i ≠ j, k ≠ j:
+                  f[k, i, j] ≤ M·intscale·x[i, j]
+        - c100: ∀ (i, j), i ≠ j:
+                  Σ_{k ≠ j} f[k, i, j] ≤ z
+
+    Returns:
+        jm.Problem: JijModeling problem instance with all variables,
+        objective, and constraints defined.
+    """
+    # ---- Placeholders ----
+    n = jm.Placeholder("n")
+    t = jm.Placeholder("t", ndim=2)   # (n,n)
+    M = jm.Placeholder("M")
+    intscale = jm.Placeholder("intscale")
+
+    # ---- Indices ----
+    i = jm.Element("i", belong_to=(0, n))
+    j = jm.Element("j", belong_to=(0, n))
+    k = jm.Element("k", belong_to=(0, n))
+
+    # ---- Vars ----
+    x = jm.BinaryVar("x", shape=(n, n), description="arc i->j selected")
+    f = jm.IntegerVar(
+        "f", shape=(n, n, n),
+        lower_bound=0, upper_bound=intscale * M,
+        description="flow of commodity k on arc i->j"
+    )
+    z = jm.IntegerVar("z", lower_bound=0, upper_bound=intscale * M)
+
+    # ---- Problem & Objective ----
+    problem = jm.Problem("ip_formulation", sense=jm.ProblemSense.MINIMIZE)
+    problem += z
+
+    # c1: ∀ i ∈ N :  Σ_{j ≠ i} x[i,j] = 2
+    problem += jm.Constraint(
+        "c1_outdeg_eq_2",
+        jm.sum([(j, j != i)], x[i, j]) == 2,
+        forall=[i]
+    )
+
+    # c2: ∀ j ∈ N :  Σ_{i ≠ j} x[i,j] = 2
+    problem += jm.Constraint(
+        "c2_indeg_eq_2",
+        jm.sum([(i, i != j)], x[i, j]) == 2,
+        forall=[j]
+    )
+
+    # c11: flow balance
+    problem += jm.Constraint(
+        "c11_flow_balance",
+        jm.sum([(j, j != i)], f[k, j, i])
+        - jm.sum([(j, (j != i) & (j != k))], f[k, i, j])
+        == t[k, i] * intscale,
+        forall=[k, (i, k != i)]
+    )
+
+    # c14: capacity bound
+    problem += jm.Constraint(
+        "c14_capacity_by_x",
+        f[k, i, j] <= M * intscale * x[i, j],
+        forall=[k, i, (j, (i != j) & (k != j))]
+    )
+
+    # c100: z upper bound on flow
+    problem += jm.Constraint(
+        "c100_z_upper_bounds_flow",
+        jm.sum([(k, k != j)], f[k, i, j]) <= z,
+        forall=[i, (j, i != j)]
+    )
+
+    return problem

ommx_quantum_benchmarks/qoblib/08_network/models/integer_lp/ommx_create.py

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+import os
+import jijmodeling as jm
+import glob
+from ommx.artifact import ArtifactBuilder
+from model import build_ip_formulation
+from sol_reader import parse_solution_zfx
+
+
+def _pick_solution_file(sol_dir: str, base: str) -> str | None:
+    """Pick first existing solution file for a basename."""
+    candidates = [
+        os.path.join(sol_dir, f"{base}.opt.sol"),
+        os.path.join(sol_dir, f"{base}.best.sol"),
+        os.path.join(sol_dir, f"{base}.bst.sol"),
+        os.path.join(sol_dir, f"{base}.sol"),
+    ]
+    for p in candidates:
+        if os.path.exists(p):
+            return p
+    return None
+
+
+def batch_process(
+    sol_root: str = "../../solutions",
+    output_directory: str = "./ommx_output",
+):
+    """
+    Process instances from a QBench JSON file and corresponding solution files,
+    convert them into OMMX artifacts, and save them to the output directory.
+
+    Parameters:
+        sol_root (str): Path to the root solutions directory.
+        output_directory (str): Path to save the generated .ommx files.
+    """
+    os.makedirs(output_directory, exist_ok=True)
+
+    problem = build_ip_formulation()
+
+    processed_count = 0
+    error_count = 0
+
+    # scan all sol_root's .sol file and get the base name.
+    sol_files = glob.glob(os.path.join(sol_root, "*.sol"))
+    bases = set()
+    for path in sol_files:
+        name = os.path.basename(path)
+        for suffix in [".opt.sol", ".best.sol", ".bst.sol", ".sol"]:
+            if name.endswith(suffix):
+                bases.add(name[: -len(suffix)])
+                break
+
+    print(f"Found {len(bases)} bases: {sorted(bases)}")
+
+    def cut_matrix(t: list[list[int]], n: int) -> list[list[int]]:
+        if not (5 <= n <= 24):
+            raise ValueError("n must be between 5 and 24.")
+        return [row[:n] for row in t[:n]]
+
+    your_t_0based = [
+        [0, 24, 43, 23, 21, 41, 61, 21, 20, 0, 0, 0, 0, 0, 40, 0, 0, 0, 0, 0, 24, 19, 23, 0],
+        [0, 0, 0, 0, 21, 18, 39, 23, 0, 0, 40, 19, 64, 19, 17, 64, 80, 0, 0, 22, 24, 18, 19, 0],
+        [16, 0, 0, 20, 44, 0, 42, 22, 20, 0, 0, 23, 21, 0, 40, 21, 38, 97, 22, 17, 20, 37, 17, 20],
+        [42, 20, 18, 0, 40, 57, 43, 42, 0, 0, 19, 17, 0, 39, 0, 0, 22, 41, 0, 0, 17, 42, 40, 43],
+        [0, 0, 0, 40, 0, 83, 60, 0, 44, 0, 37, 60, 0, 40, 0, 0, 40, 19, 0, 39, 41, 17, 0, 0],
+        [60, 18, 0, 37, 18, 0, 21, 41, 23, 39, 0, 63, 60, 39, 0, 19, 0, 16, 16, 0, 0, 40, 0, 16],
+        [22, 0, 0, 0, 0, 0, 0, 61, 36, 80, 96, 19, 19, 41, 16, 0, 0, 0, 22, 0, 43, 0, 44, 22],
+        [0, 0, 20, 19, 17, 20, 40, 0, 0, 60, 61, 0, 20, 62, 20, 0, 0, 38, 0, 0, 0, 0, 24, 22],
+        [21, 22, 38, 0, 44, 20, 40, 39, 0, 36, 22, 21, 19, 39, 19, 0, 0, 21, 24, 16, 23, 21, 37, 0],
+        [0, 24, 23, 39, 20, 0, 0, 41, 0, 0, 0, 22, 0, 0, 44, 42, 22, 42, 22, 19, 20, 58, 18, 0],
+        [60, 57, 0, 0, 16, 0, 16, 37, 0, 0, 0, 44, 63, 0, 18, 0, 17, 18, 0, 0, 0, 100, 24, 23],
+        [0, 44, 44, 0, 23, 17, 39, 21, 0, 17, 40, 0, 24, 78, 17, 24, 20, 18, 0, 24, 24, 0, 20, 0],
+        [23, 16, 0, 0, 0, 23, 0, 0, 0, 0, 43, 58, 0, 0, 24, 60, 0, 0, 19, 0, 21, 0, 20, 0],
+        [44, 20, 0, 19, 21, 0, 39, 19, 0, 0, 0, 39, 22, 0, 0, 64, 24, 22, 0, 39, 0, 43, 42, 16],
+        [0, 60, 37, 18, 0, 0, 0, 20, 0, 41, 43, 16, 43, 24, 0, 0, 18, 18, 0, 44, 20, 0, 21, 37],
+        [0, 0, 23, 39, 0, 24, 40, 0, 37, 0, 40, 20, 44, 43, 0, 0, 0, 0, 0, 16, 0, 59, 0, 0],
+        [0, 42, 0, 0, 23, 24, 38, 19, 36, 0, 20, 60, 57, 0, 23, 40, 0, 0, 0, 16, 42, 0, 23, 0],
+        [0, 41, 36, 43, 23, 41, 17, 0, 38, 0, 0, 21, 21, 17, 16, 16, 39, 0, 22, 0, 21, 23, 16, 23],
+        [17, 0, 23, 23, 20, 0, 17, 58, 17, 0, 20, 0, 17, 24, 0, 0, 17, 42, 0, 58, 19, 22, 0, 24],
+        [42, 0, 16, 0, 43, 0, 24, 36, 0, 16, 24, 41, 41, 0, 24, 0, 0, 0, 0, 0, 56, 38, 63, 19],
+        [37, 23, 23, 0, 42, 16, 23, 76, 23, 0, 0, 24, 20, 41, 20, 24, 40, 23, 0, 0, 0, 39, 20, 0],
+        [43, 20, 17, 17, 0, 20, 19, 0, 80, 0, 0, 0, 40, 0, 40, 16, 19, 0, 0, 0, 18, 0, 17, 0],
+        [18, 20, 44, 40, 21, 18, 0, 20, 0, 0, 16, 24, 0, 0, 19, 18, 0, 17, 23, 0, 23, 44, 0, 42],
+        [44, 0, 0, 0, 62, 0, 17, 41, 0, 0, 0, 63, 0, 37, 22, 0, 20, 0, 0, 19, 57, 18, 38, 0],
+    ]
+
+    for base in sorted(bases):
+        # from base to obtain n, such like network05 → n=5
+        try:
+            n_str = "".join(ch for ch in base if ch.isdigit())
+            n_val = int(n_str) if n_str else 5
+        except Exception:
+            print(f"[{base}] Cannot parse n from base, skip.")
+            continue
+
+        try:
+            instance_data = {
+                "n": n_val,
+                "t": cut_matrix(your_t_0based, n_val),
+                "M": 1000,
+                "intscale": 1000,
+            }
+
+            interpreter = jm.Interpreter(instance_data)
+            ommx_instance = interpreter.eval_problem(problem)
+
+            sol_path = _pick_solution_file(sol_root, base)
+            solution = None
+            if sol_path:
+                try:
+                    print(f"  → Evaluating solution: {sol_path}")
+                    solution_dict = parse_solution_zfx(sol_path, n_val)
+                    solution = ommx_instance.evaluate(solution_dict)
+                    if (
+                        solution.feasible
+                        and abs(solution.objective - solution_dict[0]) < 1e-6
+                    ):
+                        print(
+                            f"    objective={solution.objective}, feasible={solution.feasible}"
+                        )
+                    else:
+                        print(
+                            "    ! Objective mismatch or infeasible; will save instance only."
+                        )
+                        solution = None
+                except Exception as sol_err:
+                    print(f"    ! Solution evaluation failed: {sol_err}")
+                    solution = None
+
+            out_path = os.path.join(output_directory, f"{base}.ommx")
+            if os.path.exists(out_path):
+                os.remove(out_path)
+
+            builder = ArtifactBuilder.new_archive_unnamed(out_path)
+            builder.add_instance(ommx_instance)
+            if solution is not None:
+                builder.add_solution(solution)
+            builder.build()
+
+            print(f"  ✓ Created: {out_path}")
+            print("-" * 50)
+            processed_count += 1
+
+        except Exception as e:
+            print(f"[{base}] Error: {e}")
+            print("-" * 50)
+            error_count += 1
+
+    print(f"Batch complete — processed: {processed_count}, errors: {error_count}")
+
+
+if __name__ == "__main__":
+    batch_process(
+        sol_root="../../solutions",
+        output_directory="./ommx_output",
+    )

ommx_quantum_benchmarks/qoblib/08_network/models/integer_lp/sol_reader.py

@@ -0,0 +1,77 @@
+import re
+
+def parse_solution_zfx(file_path: str, n: int) -> dict[int, int]:
+    """Parse Jij solution (.sol) into {id: value} with strict z→f→x ordering.
+
+    Order:
+      - id=0 : z
+      - id=1.. : f[k,i,j] (k=0..n-1, i=0..n-1, j=0..n-1)
+      - then: x[i,j] (i=0..n-1, j=0..n-1)
+
+    Args:
+        file_path (str): Path to solution file
+        n (int): Number of nodes
+
+    Returns:
+        dict[int,int]: {id: value} in z→f→x order
+    """
+    z_val = None
+    f_vals = {}
+    x_vals = {}
+
+    with open(file_path, "r") as f:
+        for line in f:
+            line = line.strip()
+            if not line or line.startswith("#"):
+                continue
+
+            # z
+            m = re.match(r"^z\s+([-+]?\d+\.?\d*)$", line)
+            if m:
+                z_val = int(m.group(1))
+                continue
+
+            # f#k#i#j
+            m = re.match(r"^f#(\d+)#(\d+)#(\d+)\s+([-+]?\d+\.?\d*)$", line)
+            if m:
+                k, i, j, val = (
+                    int(m.group(1)) - 1,
+                    int(m.group(2)) - 1,
+                    int(m.group(3)) - 1,
+                    int(m.group(4)),
+                )
+                f_vals[(k, i, j)] = val
+                continue
+
+            # x#i#j
+            m = re.match(r"^x#(\d+)#(\d+)\s+([-+]?\d+\.?\d*)$", line)
+            if m:
+                i, j, val = int(m.group(1)) - 1, int(m.group(2)) - 1, int(m.group(3))
+                x_vals[(i, j)] = val
+                continue
+
+    if z_val is None:
+        raise ValueError("No z found in solution file.")
+
+    # ---- Rebuild {id: value} ----
+    sol_dict = {}
+    idx = 0
+
+    # z
+    sol_dict[idx] = z_val
+    idx += 1
+
+    # f[k,i,j], dictionary order
+    for k in range(n):
+        for i in range(n):
+            for j in range(n):
+                sol_dict[idx] = f_vals.get((k, i, j), 0.0)
+                idx += 1
+
+    # x[i,j], dictionary order
+    for i in range(n):
+        for j in range(n):
+            sol_dict[idx] = x_vals.get((i, j), 0.0)
+            idx += 1
+
+    return sol_dict