{ "cells": [ { "cell_type": "markdown", "id": "90ad2b4d", "metadata": {}, "source": [ "# `dtalite-tap` — DTALite's static Frank-Wolfe, an IDENTITY compile map\n", "\n", "**What.** `dtalite-tap` wraps the PyPI `DTALite` wheel's `assignment()` entry\n", "(Zhou & Taylor 2014, `[zhou2014dtalite]`,\n", "[docs/REFERENCES.md](../../docs/REFERENCES.md)): a static Frank-Wolfe\n", "user-equilibrium solver — the wheel's own source calls it *TAPLite*, a\n", "Bar-Gera `FW.zip`-derived link-based FW loop on per-link BPR costs. This\n", "adapter compiles a fixed-demand scenario into the engine's GMNS CSVs, runs\n", "`assignment()` in a throwaway subprocess, reads the flows back, and lets the\n", "harness certify the equilibrium gap under the scenario's DECLARED BPR (P1).\n", "\n", "**Why it is in the benchmark, and why it is different from `sumo-marouter`.**\n", "`sumo-marouter` (adr-027) mapped the repo's BPR into a hardcoded linear class\n", "law — a real, measured MAPPING FLOOR. DTALite's per-link\n", "`vdf_fftt/vdf_alpha/vdf_beta` is, with the right constants, the repo BPR\n", "`t = fft (1 + b (v/cap)^power)` **exactly** — there is no mapping floor to\n", "separate out. Sioux Falls' `power=4` links, unrepresentable in marouter's\n", "linear law, map here with no cost-model approximation at all — the first\n", "external engine on the power-4 ladder. See\n", "[docs/design/adr-029-dtalite-tap.md](../../docs/design/adr-029-dtalite-tap.md)\n", "for the full derivation (the tool-paper sourcing discipline: `zhou2014dtalite`\n", "anchors the software LINEAGE, not this static-FW formulation, which is\n", "Bar-Gera's) and every measured anchor.\n", "\n", "**Scope.** The identity compile map (Decision 3), a certified Sioux Falls\n", "power-4 run with the gap recomputed in-cell, the `returncode`-never-trusted\n", "lesson (the engine exits 0 on corrupted input — success is defined by the\n", "read-back, not the exit code) and the sorted-links fix it motivated, and the\n", "honest headline against a converged `bfw`." ] }, { "cell_type": "markdown", "id": "dd993e69", "metadata": {}, "source": [ "## How this notebook is graded\n", "\n", "**A notebook never claims a number it does not compute in that cell.** Every\n", "scored quantity below is recomputed live by the P1 `Evaluator` from the flows\n", "the engine emitted, in the cell where it is claimed. The engine's own\n", "self-reported gap (`engine_relative_gap`, a DIFFERENT `(TSTT-SPTT)/SPTT`\n", "normalization) is shown only as provenance, diffed against the certificate,\n", "never trusted on its own — the same discipline as every other model here\n", "([README](../../README.md), *Certified, not self-reported*)." ] }, { "cell_type": "code", "execution_count": 1, "id": "47334c34", "metadata": { "execution": { "iopub.execute_input": "2026-07-21T13:55:49.946154Z", "iopub.status.busy": "2026-07-21T13:55:49.945846Z", "iopub.status.idle": "2026-07-21T13:55:52.057377Z", "shell.execute_reply": "2026-07-21T13:55:52.055999Z" } }, "outputs": [], "source": [ "# Setup. `dtalite-tap` is GUARDED behind the optional `DTALite` wheel\n", "# (`pip install tabench[dtalite]`). Unlike the torch/sumo guards, this one\n", "# NEVER `import DTALite` even to probe it: the package prints a version\n", "# banner to stdout and ctypes-loads a compiled engine + OpenMP into the host\n", "# process on import. `importlib.util.find_spec` touches neither -- the exact\n", "# probe the adapter module itself uses (adr-029).\n", "%matplotlib inline\n", "import dataclasses\n", "import importlib.util\n", "\n", "if importlib.util.find_spec(\"DTALite\") is None:\n", " raise ModuleNotFoundError(\n", " \"dtalite-tap needs the optional 'dtalite' extra: pip install tabench[dtalite]\"\n", " )\n", "\n", "import numpy as np\n", "\n", "from tabench import (\n", " BiconjugateFrankWolfeModel,\n", " Budget,\n", " Evaluator,\n", " RngBundle,\n", " Trace,\n", " braess_scenario,\n", " load_scenario,\n", " two_route_scenario,\n", " viz,\n", ")\n", "from tabench.core.scenario import Demand, Scenario\n", "from tabench.models.adapters.dtalite_tap import DTALiteTapModel" ] }, { "cell_type": "markdown", "id": "09b152a6", "metadata": {}, "source": [ "## The identity compile map (adr-029, Decision 3)\n", "\n", "Writing `lanes = 1`, a 1-hour demand period, `vdf_plf = 1`, and the repo's\n", "`(free_flow_time, b, power, capacity)` verbatim into the engine's per-link VDF\n", "`t = vdf_fftt (1 + vdf_alpha (I / (lanes cap period plf))^vdf_beta)` collapses\n", "it to the repo BPR EXACTLY — no approximation, unlike marouter's linear class\n", "law. The adapter enforces this at runtime, not just by construction: every\n", "solve re-verifies the engine's own `travel_time` column against\n", "`network.link_cost` on every link (A2), and raises rather than certifying a\n", "row if it does not match — so a successful `solve()` below IS the mapping-\n", "fidelity proof, not merely an assumption." ] }, { "cell_type": "code", "execution_count": 2, "id": "a3f29f4e", "metadata": { "execution": { "iopub.execute_input": "2026-07-21T13:55:52.062600Z", "iopub.status.busy": "2026-07-21T13:55:52.062308Z", "iopub.status.idle": "2026-07-21T13:55:52.133413Z", "shell.execute_reply": "2026-07-21T13:55:52.132190Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "scenario : siouxfalls\n", "content hash : 7f5035885f0a03ef…\n", "links/power : 76 (power=[4.0])\n", "certified relative gap : 5.0343e-03\n", "feasible : 1\n", "engine (provenance) : engine_relative_gap=5.0598e-03, executed FW iterations=99\n", "flow NRMSE vs best-known UE : 0.0147 (measured ~1.5-1.6%)\n" ] } ], "source": [ "scenario = load_scenario(\"siouxfalls\") # BPR power == 4: marouter-unrepresentable\n", "print(f\"scenario : {scenario.name}\")\n", "print(f\"content hash : {scenario.content_hash()[:16]}…\")\n", "print(f\"links/power : {scenario.network.n_links} (power={sorted(set(scenario.network.power.tolist()))})\")\n", "\n", "model = DTALiteTapModel()\n", "bundle = model.solve(scenario, Budget(iterations=100), RngBundle(0), Trace())\n", "final = bundle.final\n", "metrics = Evaluator(scenario).evaluate(final.link_flows)\n", "print(f\"certified relative gap : {metrics['relative_gap']:.4e}\")\n", "print(f\"feasible : {metrics['feasible']:.0f}\")\n", "print(f\"engine (provenance) : engine_relative_gap={final.self_report['engine_relative_gap']:.4e}, \"\n", " f\"executed FW iterations={final.self_report['engine_iterations_executed']:.0f}\")\n", "assert metrics[\"feasible\"] == 1.0\n", "assert metrics[\"relative_gap\"] < 5e-2 # the engine's line-search floor (measured ~5.0e-3)\n", "\n", "oracle = scenario.reference.link_flows\n", "nrmse = float(np.sqrt(np.mean((final.link_flows - oracle) ** 2)) / np.sqrt(np.mean(oracle ** 2)))\n", "print(f\"flow NRMSE vs best-known UE : {nrmse:.4f} (measured ~1.5-1.6%)\")\n", "assert nrmse < 0.05" ] }, { "cell_type": "markdown", "id": "ed105ce5", "metadata": {}, "source": [ "## `returncode == 0` is never trusted, and why links are written sorted\n", "\n", "Almost no bad input crashes this engine: missing files, dropped links, a\n", "`zone_id != node_id` mismatch — all exit 0 with zero or garbage flows. So\n", "success here is DEFINED as the read-back (every repo link matched exactly\n", "once, the echoed VDF parameters agreeing, and the A2 cost-match holding), not\n", "the exit code. The CRITICAL finding this discipline caught: the engine builds\n", "its adjacency from CONTIGUOUS `(from_node_id, to_node_id)` ranges, so an\n", "UNGROUPED `link.csv` silently corrupts routing — a permuted Braess once\n", "certified `feasible=1` at the WRONG flows (measured RG 0.208 vs the true\n", "0.0118), and a permuted Sioux Falls sent the Frank-Wolfe loop into an\n", "INFINITE loop. The fix: links are always written sorted by node pair. Proven\n", "live below — a permuted network reproduces the unpermuted solve exactly." ] }, { "cell_type": "code", "execution_count": 3, "id": "e21f4f08", "metadata": { "execution": { "iopub.execute_input": "2026-07-21T13:55:52.137672Z", "iopub.status.busy": "2026-07-21T13:55:52.137421Z", "iopub.status.idle": "2026-07-21T13:55:52.277261Z", "shell.execute_reply": "2026-07-21T13:55:52.275839Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "unpermuted flows : [4.1999 1.8001 2.4096 1.7903 4.2097]\n", "3 permuted link orderings reproduce the unpermuted solve (mapped back), atol=1e-6: OK\n" ] } ], "source": [ "base = braess_scenario()\n", "f_base = DTALiteTapModel().solve(base, Budget(iterations=100), RngBundle(0), Trace()).final.link_flows\n", "net = base.network\n", "\n", "for perm in ([4, 3, 2, 1, 0], [0, 2, 1, 3, 4], [3, 0, 4, 1, 2]):\n", " p = np.asarray(perm)\n", " pnet = dataclasses.replace(\n", " net, init_node=net.init_node[p], term_node=net.term_node[p],\n", " capacity=net.capacity[p], length=net.length[p],\n", " free_flow_time=net.free_flow_time[p], b=net.b[p], power=net.power[p],\n", " toll=net.toll[p], link_type=net.link_type[p],\n", " )\n", " psc = Scenario(name=\"braess-perm\", network=pnet, demand=Demand(base.demand.matrix))\n", " f_perm = DTALiteTapModel().solve(psc, Budget(iterations=100), RngBundle(0), Trace()).final.link_flows\n", " assert np.allclose(f_perm, f_base[p], atol=1e-6)\n", "\n", "print(f\"unpermuted flows : {np.round(f_base, 4)}\")\n", "print(\"3 permuted link orderings reproduce the unpermuted solve (mapped back), atol=1e-6: OK\")" ] }, { "cell_type": "markdown", "id": "c66b7cb6", "metadata": {}, "source": [ "## The honest headline: a converged `bfw` still wins the convergence axis\n", "\n", "The engine's Armijo line search collapses to step 0 within a few iterations\n", "(the certified gap freezes at a floor — Braess ~1.2e-2, Sioux Falls ~5.0e-3),\n", "far above a converged white-box solver. Because the compile map is the\n", "identity (A2 above), that floor is honestly the engine's own line-search\n", "stall, not a cost-model mismatch — \"DTALite's static assignment certifies RG\n", "X at N iterations on the SAME BPR the white-box solvers optimize.\"" ] }, { "cell_type": "code", "execution_count": 4, "id": "16de4154", "metadata": { "execution": { "iopub.execute_input": "2026-07-21T13:55:52.281302Z", "iopub.status.busy": "2026-07-21T13:55:52.281100Z", "iopub.status.idle": "2026-07-21T13:55:52.944887Z", "shell.execute_reply": "2026-07-21T13:55:52.943652Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "bfw (converged) : relative_gap=3.228e-06\n", "dtalite-tap : relative_gap=5.034e-03\n" ] } ], "source": [ "bfw_trace = Trace()\n", "BiconjugateFrankWolfeModel().solve(\n", " scenario, Budget(iterations=300, target_relative_gap=1e-12), RngBundle(0), bfw_trace\n", ")\n", "bfw_gap = Evaluator(scenario).evaluate(bfw_trace.final.link_flows)[\"relative_gap\"]\n", "print(f\"bfw (converged) : relative_gap={bfw_gap:.3e}\")\n", "print(f\"dtalite-tap : relative_gap={metrics['relative_gap']:.3e}\")\n", "assert bfw_gap < metrics[\"relative_gap\"] / 10.0" ] }, { "cell_type": "markdown", "id": "876e792c", "metadata": {}, "source": [ "## Refusals this adapter makes, naming the field\n", "\n", "`sue_theta` and the other endogenous-task fields are refused (the engine's\n", "static `assignment()` cannot represent them certifiably); a link capacity\n", "below `0.1` is refused because the engine clamps it at `fmax(0.1, cap)` **in\n", "the cost law only** (the Beckmann integral stays unclamped — a link in\n", "`(1e-4, 0.1)` would equilibrate under a DIFFERENT BPR while still passing a\n", "naive echo read-back, measured relative A2 error ~0.93)." ] }, { "cell_type": "code", "execution_count": 5, "id": "76af3fdf", "metadata": { "execution": { "iopub.execute_input": "2026-07-21T13:55:52.949017Z", "iopub.status.busy": "2026-07-21T13:55:52.948770Z", "iopub.status.idle": "2026-07-21T13:55:52.955570Z", "shell.execute_reply": "2026-07-21T13:55:52.954653Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "SUE-theta scenario refused : dtalite-tap accepts only fixed-demand deterministic-UE scenarios; scenario 'tworo…\n", "capacity < 0.1 refused : dtalite-tap cannot represent scenario 'low-cap': a link capacity < 0.1 is CLAMPE…\n" ] } ], "source": [ "try:\n", " DTALiteTapModel().solve(two_route_scenario(), Budget(iterations=5), RngBundle(0), Trace())\n", " raise AssertionError(\"expected an SUE-theta scenario to be refused\")\n", "except ValueError as exc:\n", " print(f\"SUE-theta scenario refused : {exc}\"[:110] + \"…\")\n", "\n", "low_cap_net = dataclasses.replace(two_route_scenario(sue_theta=None).network,\n", " capacity=np.full(4, 0.05))\n", "low_cap_sc = Scenario(name=\"low-cap\", network=low_cap_net,\n", " demand=Demand(two_route_scenario(sue_theta=None).demand.matrix))\n", "try:\n", " DTALiteTapModel().solve(low_cap_sc, Budget(iterations=5), RngBundle(0), Trace())\n", " raise AssertionError(\"expected a sub-0.1 capacity to be refused\")\n", "except ValueError as exc:\n", " print(f\"capacity < 0.1 refused : {exc}\"[:110] + \"…\")" ] }, { "cell_type": "markdown", "id": "f7d455ae", "metadata": {}, "source": [ "## Visualize\n", "\n", "The certified artifact is per-link flows on a road `Network` — the same\n", "artifact shape every static model here emits — so `tabench.viz` applies\n", "directly (adr-035's viz rule)." ] }, { "cell_type": "code", "execution_count": 6, "id": "0f17e175", "metadata": { "execution": { "iopub.execute_input": "2026-07-21T13:55:52.959302Z", "iopub.status.busy": "2026-07-21T13:55:52.958705Z", "iopub.status.idle": "2026-07-21T13:55:53.552853Z", "shell.execute_reply": "2026-07-21T13:55:53.552104Z" } }, "outputs": [ { "data": { "image/png": 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", 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", 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" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "display(viz.plot_network_flows(scenario.network, final.link_flows))\n", "display(viz.plot_flow_scatter((\"best-known UE\", oracle), {\"dtalite-tap\": final.link_flows}))" ] }, { "cell_type": "markdown", "id": "60049885", "metadata": {}, "source": [ "## Takeaways & pointers\n", "\n", "- **No mapping floor — the ceiling is line-search stall.** Because the\n", " compile map is the identity (verified by the adapter's own runtime A2\n", " gate), the certified gap here is honestly FW truncation, not a cost-model\n", " approximation — unlike `sumo-marouter`.\n", "- **`returncode == 0` proves nothing.** The engine exits 0 on corrupted or\n", " dropped input; success is defined by the read-back, which is why links are\n", " ALWAYS written sorted by node pair — verified live above across three\n", " permutations.\n", "- **The power-4 ladder, finally reachable by an external engine.** Sioux\n", " Falls' `power=4` links were unrepresentable in `sumo-marouter`'s linear\n", " class law; DTALite's per-link `vdf_beta` maps them exactly.\n", "- **Where next.** `spsa-sumo` ([04-spsa-sumo.ipynb](04-spsa-sumo.ipynb)) for a\n", " simulator-in-the-loop T2 estimator built on `sumo-marouter`; the full\n", " engine-hazard writeup (the `ExitMessage`/`getchar()` hang risk, the\n", " `lanes²` trap, the BIG-M mass gate) in\n", " [docs/design/adr-029-dtalite-tap.md](../../docs/design/adr-029-dtalite-tap.md)." ] } ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", "name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", "version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.10.12" }, "tabench": { "covers": [], "requires_extra": "dtalite", "track": "external", "unit": "dtalite-tap" } }, "nbformat": 4, "nbformat_minor": 5 }