GHA: Add simulation workflow

.github/workflows/simulate.yml

@@ -0,0 +1,41 @@
+name: Simulate
+on:
+  push:
+    branches:
+      - master
+  workflow_dispatch:
+  merge_group:
+  schedule:
+    - cron: '0 0 * * *'
+
+jobs:
+  simulate_amici:
+    runs-on: ubuntu-latest
+    steps:
+    - name: Check out repository
+      uses: actions/checkout@v5
+
+    - name: Prepare Python
+      uses: actions/setup-python@v6
+      with:
+        python-version: "3.13"
+
+    - name: Install AMICI
+      env:
+        AMICI_PARALLEL_COMPILE: ""
+      run: |
+        pip install --upgrade pip
+        # TODO: once amici 1.0 is released, replace with:
+        # pip install amici[petab]
+        pip install petab
+        pip install "git+https://github.com/dweindl/amici.git@6a85422ad233fc268fb71272bba39f5b82db387a#egg=amici&subdirectory=python/sdist"
+
+    - name: Simulate with nominal parameters
+      env:
+        AMICI_PARALLEL_COMPILE: ""
+      run: |
+        for problem in `ls -1 Benchmark-Models/`; do
+            python src/python/simulate.py "$problem" -j
+            echo
+            echo
+        done

src/python/simulate.py

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+#!/usr/bin/env python3
+"""
+Script to simulate a model using AMICI.
+
+Basic usage: simulate.py <problem_id>
+See --help for more options.
+"""
+
+import os
+import argparse
+import benchmark_models_petab
+import amici.sim.sundials as ass
+from amici.importers.petab.v1 import (
+    import_petab_problem,
+    simulate_petab,
+    LLH,
+    RDATAS,
+)
+import logging
+from petab.v1.lint import measurement_table_has_timepoint_specific_mappings
+from petab.v1.core import flatten_timepoint_specific_output_overrides
+
+
+def parse_cli_args():
+    """Parse command line arguments."""
+    parser = argparse.ArgumentParser(
+        description="Simulate a model using AMICI."
+    )
+    parser.add_argument(
+        "problem_id",
+        type=str,
+        help="Identifier for the problem/model to simulate.",
+    )
+    parser.add_argument(
+        "-j",
+        dest="num_threads",
+        nargs="?",
+        default=None,
+        const="all",
+        help=(
+            "Number of cores to use. "
+            "`-j` (no value) uses all available cores. "
+            "If omitted, threading is left unchanged."
+        ),
+    )
+    args = parser.parse_args()
+
+    args.num_threads = (
+        os.cpu_count()
+        if args.num_threads == "all"
+        else 1
+        if args.num_threads is None
+        else max(1, int(args.num_threads))
+    )
+
+    return args
+
+
+def main():
+    """Simulate a PEtab problem with AMICI using nominal parameter values."""
+    args = parse_cli_args()
+
+    # Import and simulate
+    print(args.problem_id)
+    print("-" * len(args.problem_id), flush=True)
+
+    problem = benchmark_models_petab.get_problem(args.problem_id)
+
+    if measurement_table_has_timepoint_specific_mappings(
+        problem.measurement_df,
+    ):
+        flatten_timepoint_specific_output_overrides(problem)
+
+    model = import_petab_problem(
+        problem, generate_sensitivity_code=False, verbose=logging.INFO
+    )
+    solver = model.create_solver()
+    solver.set_return_data_reporting_mode(
+        ass.RDataReporting.observables_likelihood
+    )
+    res = simulate_petab(
+        problem, model, solver=solver, num_threads=args.num_threads
+    )
+
+    for rdata in res[RDATAS]:
+        print(
+            f"{rdata.id}: llh = {rdata.llh}, chi2 = {rdata.chi2}, status = {rdata.status}"
+        )
+
+    print()
+    print("Total log-likelihood:", res[LLH])
+    print()
+
+
+if __name__ == "__main__":
+    main()