{ "cells": [ { "cell_type": "markdown", "id": "9fe6c71f", "metadata": {}, "source": [ "# Stormpy Conversion\n", "Models can be converted back and forth between stormvogel and stormpy with ease using the `mapping` module.
\n", "This is useful, because this allows you to combine both APIs. For example, you could create a model in stormvogel becuase it has an easy API, do some model checking in stormpy, and then convert it back to display the results. (Note that there is also a direct model checking function available that uses stormpy behind the scenes.)" ] }, { "cell_type": "code", "execution_count": 1, "id": "3f961bed", "metadata": { "execution": { "iopub.execute_input": "2025-08-27T16:22:00.114063Z", "iopub.status.busy": "2025-08-27T16:22:00.113851Z", "iopub.status.idle": "2025-08-27T16:22:03.429648Z", "shell.execute_reply": "2025-08-27T16:22:03.429143Z" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "870853002a37449f9ae78bc6a2abd990", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Output()" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "\n", "function return_id_result(url, id, data) {\n", " fetch(url, {\n", " method: 'POST',\n", " body: JSON.stringify({\n", " 'id': id,\n", " 'data': data\n", " })\n", " })\n", " }\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "application/javascript": [ "return_id_result('http://127.0.0.1:8889', 'wBjAsYFZwXerUKBEjPYY', 'test message')" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" }, { "name": "stdout", "output_type": "stream", "text": [ "Test request failed. See 'Implementation details' in docs. Disable warning by use_server=False.\n" ] }, { "data": { "text/html": [ "\n", "\n", "\n", " \n", " Network\n", " \n", " \n", " \n", " \n", " \n", "
\n", " \n", " \n", " \n", "\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "from stormvogel import *\n", "stormvogel_model = examples.create_car_mdp()\n", "vis = show(stormvogel_model, layout=stormvogel.layout.Layout(\"layouts/car.json\"))" ] }, { "cell_type": "markdown", "id": "96845e4c", "metadata": {}, "source": [ "First, let's convert the stormvogel model to the same model in stormpy." ] }, { "cell_type": "code", "execution_count": 2, "id": "0ef7d39c", "metadata": { "execution": { "iopub.execute_input": "2025-08-27T16:22:03.437554Z", "iopub.status.busy": "2025-08-27T16:22:03.437371Z", "iopub.status.idle": "2025-08-27T16:22:03.441685Z", "shell.execute_reply": "2025-08-27T16:22:03.441267Z" } }, "outputs": [ { "name": "stdout", "output_type": "stream", "text": [ "-------------------------------------------------------------- \n", "Model type: \tMDP (sparse)\n", "States: \t5\n", "Transitions: \t9\n", "Choices: \t9\n", "Reward Models: none\n", "State Labels: \t6 labels\n", " * red light -> 2 item(s)\n", " * init -> 1 item(s)\n", " * accident -> 1 item(s)\n", " * green light -> 2 item(s)\n", " * moving -> 2 item(s)\n", " * still -> 2 item(s)\n", "Choice Labels: \t3 labels\n", " * accelerate -> 2 item(s)\n", " * brake -> 2 item(s)\n", " * wait -> 4 item(s)\n", "-------------------------------------------------------------- \n", "\n" ] } ], "source": [ "import stormvogel.stormpy_utils.mapping as mapping\n", "\n", "stormpy_model = mapping.stormvogel_to_stormpy(stormvogel_model)\n", "print(stormpy_model)" ] }, { "cell_type": "markdown", "id": "e5e12f7b", "metadata": {}, "source": [ "And now we convert it back." ] }, { "cell_type": "code", "execution_count": 3, "id": "83a5d6d8", "metadata": { "execution": { "iopub.execute_input": "2025-08-27T16:22:03.443112Z", "iopub.status.busy": "2025-08-27T16:22:03.442954Z", "iopub.status.idle": "2025-08-27T16:22:03.477052Z", "shell.execute_reply": "2025-08-27T16:22:03.476538Z" } }, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { "model_id": "8c8a1edec18b43258200c0b85f1a2920", "version_major": 2, "version_minor": 0 }, "text/plain": [ "Output()" ] }, "metadata": {}, "output_type": "display_data" }, { "data": { "text/html": [ "\n", "\n", "\n", " \n", " Network\n", " \n", " \n", " \n", " \n", " \n", "
\n", " \n", " \n", " \n", "\n" ], "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "stormvogel_model2 = mapping.stormpy_to_stormvogel(stormpy_model)\n", "vis = show(stormvogel_model2, layout=Layout(\"layouts/car.json\"))" ] }, { "cell_type": "markdown", "id": "3ddc912f", "metadata": {}, "source": [ "The result of the double conversion is equal to the original model." ] }, { "cell_type": "code", "execution_count": 4, "id": "88071789", "metadata": { "execution": { "iopub.execute_input": "2025-08-27T16:22:03.485616Z", "iopub.status.busy": "2025-08-27T16:22:03.485377Z", "iopub.status.idle": "2025-08-27T16:22:03.489321Z", "shell.execute_reply": "2025-08-27T16:22:03.488831Z" } }, "outputs": [ { "data": { "text/plain": [ "True" ] }, "execution_count": 4, "metadata": {}, "output_type": "execute_result" } ], "source": [ "stormvogel_model == stormvogel_model2" ] } ], "metadata": { "kernelspec": { "display_name": "Python 3 (ipykernel)", "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": "3.13.3" }, "widgets": { "application/vnd.jupyter.widget-state+json": { "state": { "035ea77068c241f782c4be3279e6ce8e": { "model_module": "@jupyter-widgets/base", "model_module_version": "2.0.0", "model_name": "LayoutModel", "state": { "_model_module": "@jupyter-widgets/base", "_model_module_version": "2.0.0", "_model_name": "LayoutModel", "_view_count": null, "_view_module": "@jupyter-widgets/base", "_view_module_version": "2.0.0", "_view_name": "LayoutView", "align_content": null, "align_items": null, "align_self": null, "border_bottom": null, "border_left": null, "border_right": null, "border_top": null, "bottom": null, "display": null, "flex": null, "flex_flow": null, "grid_area": null, "grid_auto_columns": null, "grid_auto_flow": null, 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