diff --git a/docs/getting_started/00_die.ipynb b/docs/getting_started/00_die.ipynb index d5d21b1..7c84273 100644 --- a/docs/getting_started/00_die.ipynb +++ b/docs/getting_started/00_die.ipynb @@ -1,13201 +1,13201 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# A simple die" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "import stormvogel.model\n", - "import stormvogel.visualization\n", - "import stormvogel.show\n", - "import stormvogel.mapping\n", - "import stormpy" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We will show off the API by creating a simple six-sided die." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": { - "scrolled": true - }, - "outputs": [ + "cells": [ + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# A simple die" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "import stormvogel.model\n", + "import stormvogel.visualization\n", + "import stormvogel.show\n", + "import stormvogel.mapping\n", + "import stormpy" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "We will show off the API by creating a simple six-sided die." + ] + }, { - "data": { - "text/html": [ - "\n", - " " + "cell_type": "code", + "execution_count": 2, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } ], - "text/plain": [ - "" + "source": [ + "# Create a new model with the name \"Die\"\n", + "dtmc = stormvogel.model.new_dtmc(\"Die\")\n", + "\n", + "init = dtmc.get_initial_state()\n", + "\n", + "# From the initial state, add the transition to 6 new states with probability 1/6th.\n", + "init.set_transitions(\n", + " [(1 / 6, dtmc.new_state(f\"rolled{i}\", {\"rolled\": i})) for i in range(1, 7)]\n", + ")\n", + "dtmc.add_self_loops()\n", + "import ipywidgets as widgets\n", + "import IPython.display as ipd\n", + "import logging\n", + "parent_logger = logging.getLogger(\"parent\")\n", + "parent_logger.setLevel(logging.DEBUG)\n", + "debug = widgets.Output()\n", + "\n", + "vis = stormvogel.show.show(dtmc, debug_output=debug, show_editor=False, name=\"die\")" ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# Create a new model with the name \"Die\"\n", - "dtmc = stormvogel.model.new_dtmc(\"Die\")\n", - "\n", - "init = dtmc.get_initial_state()\n", - "\n", - "# From the initial state, add the transition to 6 new states with probability 1/6th.\n", - "init.set_transitions(\n", - " [(1 / 6, dtmc.new_state(f\"rolled{i}\", {\"rolled\": i})) for i in range(1, 7)]\n", - ")\n", - "dtmc.add_self_loops()\n", - "import ipywidgets as widgets\n", - "import IPython.display as ipd\n", - "import logging\n", - "parent_logger = logging.getLogger(\"parent\")\n", - "parent_logger.setLevel(logging.DEBUG)\n", - "debug = widgets.Output()\n", - "\n", - "vis = stormvogel.show.show(dtmc, debug_output=debug, show_editor=False, name=\"die\")" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "stormpy_dtmc = stormvogel.mapping.stormvogel_to_stormpy(dtmc)" - ] - }, - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "We can perform DTMC evolution, although it is not very interesting for this particular model..." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ + }, { - "data": { - "image/png": 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", - "text/plain": [ - "
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a/docs/getting_started/01_study.ipynb +++ b/docs/getting_started/01_study.ipynb @@ -1,13310 +1,13310 @@ { - "cells": [ - { - "cell_type": "markdown", - "id": "31fda09b", - "metadata": {}, - "source": [ - "# The studying dilemma" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "id": "e924f3a4", - "metadata": {}, - "outputs": [], - "source": [ - "import stormvogel.model\n", - "from stormvogel.layout import Layout\n", - "from stormvogel.show import show\n", - "from stormvogel.model import EmptyAction" - ] - }, - { - "cell_type": "markdown", - "id": "0b09222b", - "metadata": {}, - "source": [ - "Let's create an MDP and add all states:" - ] - }, - { - "cell_type": "code", - "execution_count": 12, - "id": "1f2120a8", - "metadata": {}, - "outputs": [], - "source": [ - "mdp = stormvogel.model.new_mdp(\"Monty Hall\")\n", - "\n", - "init = mdp.get_initial_state()\n", - "study = mdp.action(\"study\")\n", - "not_study = mdp.action(\"don't study\")\n", - "\n", - "studied = mdp.new_state(\"studied\")\n", - "not_studied = mdp.new_state(\"didn't study\")\n", - "pass_test = mdp.new_state(\"pass test\")\n", - "fail_test = mdp.new_state(\"fail test\")\n", - "end = mdp.new_state(\"end\")" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "id": "1143b6c0", - "metadata": {}, - "outputs": [], - "source": [ - "init.set_transitions([\n", - " (study, studied),\n", - " (not_study, not_studied)\n", - "])" - ] - }, - { - "cell_type": "markdown", - "id": "1db64312", - "metadata": {}, - "source": [ - "If you studied, then there is a 90% chance that you pass the test." - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "id": "64bfb789", - "metadata": {}, - "outputs": [], - "source": [ - "studied.set_transitions([\n", - " (9/10, pass_test),\n", - " (1/10, fail_test)\n", - "])" - ] - }, - { - "cell_type": "markdown", - "id": "600839f5", - "metadata": {}, - "source": [ - "If you did not study, then there is only a 40% chance that you pass the test." - ] - }, - { - "cell_type": "code", - "execution_count": 15, - "id": "89d1d749", - "metadata": {}, - "outputs": [], - "source": [ - "not_studied.set_transitions([\n", - " (4/10, pass_test),\n", - " (6/10, fail_test)\n", - "])" - ] - }, - { - "cell_type": "markdown", - "id": "b0c4965f", - "metadata": {}, - "source": [ - "After the test, you are done" - ] - }, - { - "cell_type": "code", - "execution_count": 16, - "id": "2f8fb42e", - "metadata": {}, - "outputs": [], - "source": [ - "pass_test.set_transitions([(1, end)])\n", - "fail_test.set_transitions([(1, end)])" - ] - }, - { - "cell_type": "markdown", - "id": "14d7ab92", - "metadata": {}, - "source": [ - "We'll add some rewards for passing the test (nice!) and for not studying (had some free time)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "bfcbb7fa", - "metadata": {}, - "outputs": [], - "source": [ - "reward_model = mdp.add_rewards(\"R\")\n", - "reward_model.set_state_action_reward(pass_test, EmptyAction, 100)\n", - "reward_model.set_state_action_reward(fail_test, EmptyAction, 0)\n", - "reward_model.set_state_action_reward(not_studied, EmptyAction, 15)\n", - "reward_model.set_unset_rewards(0)" - ] - }, - { - "cell_type": "markdown", - "id": "797e09bb", - "metadata": {}, - "source": [ - "We'll decorate our model with a nice layout." - ] - }, - { - "cell_type": "code", - "execution_count": 18, - "id": "0df1511e-565d-45d0-93a8-adafbfaaaefa", - "metadata": { - "scrolled": true - }, - "outputs": [ + "cells": [ { - "data": { - "text/html": [ - "\n", - " " - ], - "text/plain": [ - "" + "cell_type": "markdown", + "id": "31fda09b", + "metadata": {}, + "source": [ + "# The studying dilemma" ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "vis = show(mdp, layout=Layout(\"layouts/pinkgreen.json\"), name=\"study\", show_editor=False)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "a9e68b97-49d8-47dc-8ba1-5d179bcecc52", - "metadata": {}, - 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"_model_module_version": "1.0.0", - "_model_name": "OutputModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/output", - "_view_module_version": "1.0.0", - "_view_name": "OutputView", - "layout": "IPY_MODEL_6e1a2c67fb444b3c8ef0160f2cca6ca2", - "msg_id": "", - "outputs": [ + }, + { + "cell_type": "code", + "execution_count": 11, + "id": "e924f3a4", + "metadata": {}, + "outputs": [], + "source": [ + "import stormvogel.model\n", + "from stormvogel.layout import Layout\n", + "from stormvogel.show import show\n", + "from stormvogel.model import EmptyAction" + ] + }, + { + "cell_type": "markdown", + "id": "0b09222b", + "metadata": {}, + "source": [ + "Let's create an MDP and add all states:" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "id": "1f2120a8", + "metadata": {}, + "outputs": [], + "source": [ + "mdp = stormvogel.model.new_mdp(\"Monty Hall\")\n", + "\n", + "init = mdp.get_initial_state()\n", + "study = mdp.action(\"study\")\n", + "not_study = mdp.action(\"don't study\")\n", + "\n", + "studied = mdp.new_state(\"studied\")\n", + "not_studied = mdp.new_state(\"didn't study\")\n", + "pass_test = mdp.new_state(\"pass test\")\n", + "fail_test = mdp.new_state(\"fail test\")\n", + "end = mdp.new_state(\"end\")" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "id": "1143b6c0", + "metadata": {}, + "outputs": [], + "source": [ + "init.set_transitions([\n", + " (study, studied),\n", + " (not_study, not_studied)\n", + "])" + ] + }, + { + "cell_type": "markdown", + "id": "1db64312", + "metadata": {}, + "source": [ + "If you studied, then there is a 90% chance that you pass the test." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "64bfb789", + "metadata": {}, + "outputs": [], + "source": [ + "studied.set_transitions([\n", + " (9/10, pass_test),\n", + " (1/10, fail_test)\n", + "])" + ] + }, + { + "cell_type": "markdown", + "id": "600839f5", + "metadata": {}, + "source": [ + "If you did not study, then there is only a 40% chance that you pass the test." + ] + }, + { + "cell_type": "code", + "execution_count": 15, + "id": "89d1d749", + "metadata": {}, + "outputs": [], + "source": [ + "not_studied.set_transitions([\n", + " (4/10, pass_test),\n", + " (6/10, fail_test)\n", + "])" + ] + }, + { + "cell_type": "markdown", + "id": "b0c4965f", + "metadata": {}, + "source": [ + "After the test, you are done" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "2f8fb42e", + "metadata": {}, + "outputs": [], + "source": [ + "pass_test.set_transitions([(1, end)])\n", + "fail_test.set_transitions([(1, end)])" + ] + }, + { + "cell_type": "markdown", + "id": "14d7ab92", + "metadata": {}, + "source": [ + "We'll add some rewards for passing the test (nice!) and for not studying (had some free time)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "bfcbb7fa", + "metadata": {}, + "outputs": [], + "source": [ + "reward_model = mdp.add_rewards(\"R\")\n", + "reward_model.set_state_action_reward(pass_test, EmptyAction, 100)\n", + "reward_model.set_state_action_reward(fail_test, EmptyAction, 0)\n", + "reward_model.set_state_action_reward(not_studied, EmptyAction, 15)\n", + "reward_model.set_unset_rewards(0)" + ] + }, + { + "cell_type": "markdown", + "id": "797e09bb", + "metadata": {}, + "source": [ + "We'll decorate our model with a nice layout." + ] + }, + { + "cell_type": "code", + "execution_count": 18, + "id": "0df1511e-565d-45d0-93a8-adafbfaaaefa", + "metadata": { + "scrolled": true + }, + "outputs": [ { - 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Whenever it gets hungry, it will go hunting and hopefully catch a prey. However, if it fails, it might starve to death..." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "7f3692d1-ad64-449d-809c-01ceb84e6bb4", - "metadata": {}, - "outputs": [ + "cells": [ { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "9990ef5a93aa41729419d45003428d66", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Output()" + "cell_type": "markdown", + "id": "9bdef9ae-fb41-4b72-924b-93077f182178", + "metadata": {}, + "source": [ + "# Naive value iteration, using a hungry lion\n", + "We start by creating a model of a lion. Whenever it gets hungry, it will go hunting and hopefully catch a prey. However, if it fails, it might starve to death..." ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from stormvogel.model import Model, ModelType, Branch, Transition\n", - "\n", - "lion = Model(name=\"lion\", model_type=ModelType.MDP)\n", - "init = lion.get_initial_state()\n", - "full = lion.new_state(\"full :D\")\n", - "satisfied = lion.new_state(\"satisfied :)\")\n", - "hungry = lion.new_state(\"hungry :(\")\n", - "starving = lion.new_state(\"starving :((\")\n", - "dead = lion.new_state(\"dead...\")\n", - "\n", - "hunt = lion.new_action(\"hunt >:D\")\n", - "rawr = lion.new_action(\"rawr\")\n", - "\n", - "init.set_transitions([(1, satisfied)])\n", - "\n", - "full.set_transitions(Transition({\n", - " hunt: Branch([\n", - " (0.5, satisfied),\n", - " (0.5, full),\n", - " ]),\n", - " rawr: Branch([\n", - " (0.9, full),\n", - " (0.1, satisfied)\n", - " ])\n", - "}))\n", - "\n", - "satisfied.set_transitions(Transition({\n", - " hunt: Branch([\n", - " (0.5, satisfied),\n", - " (0.3, full),\n", - " (0.2, hungry)\n", - " ]),\n", - " rawr: Branch([\n", - " (0.9, satisfied),\n", - " (0.1, hungry)\n", - " ])\n", - "}))\n", - "\n", - "hungry.set_transitions(Transition({\n", - " hunt: Branch([\n", - " (0.2, full),\n", - " (0.5, satisfied),\n", - " (0.1, hungry),\n", - " (0.2, starving)\n", - " ]),\n", - " rawr: Branch([\n", - " (0.9, hungry),\n", - " (0.1, starving)\n", - " ])\n", - "}))\n", - "\n", - "starving.set_transitions(Transition({\n", - " hunt: Branch([\n", - " (0.1, full),\n", - " (0.5, satisfied),\n", - " (0.2, hungry),\n", - " (0.2, dead)\n", - " ]),\n", - " rawr: Branch([\n", - " (0.9, starving),\n", - " (0.1, dead)\n", - " ])\n", - "}))\n", - "lion.add_self_loops()\n", - "\n", - "from stormvogel.show import show\n", - "from stormvogel.layout import Layout\n", - "vis = show(lion, layout=Layout(\"layouts/lion.json\"), name=\"lion\", show_editor=False)" - ] - }, - { - "cell_type": "markdown", - "id": "1c09fb4a-1fe9-4f76-982a-1eacd0b46a87", - "metadata": {}, - "source": [ - "Here we provide an implementation of naive value iteration using the model API." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "8807425f-1d69-4522-9077-b902c90bd0b2", - "metadata": {}, - "outputs": [], - "source": [ - "import stormvogel.model\n", - "\n", - "def naive_value_iteration(\n", - " model: stormvogel.model.Model, epsilon: float, target_state: stormvogel.model.State\n", - ") -> list[list[float]]:\n", - " \"\"\"Run naive value iteration. The result is a 2D list where result[n][m] is the probability to be in state m at step n.\n", - "\n", - " Args:\n", - " model (stormvogel.model.Model): Target model.\n", - " steps (int): Amount of steps.\n", - " target_state (stormvogel.model.State): Target state of the model.\n", - "\n", - " Returns:\n", - " list[list[float]]: The result is a 2D list where result[n][m] is the value of state m at iteration n.\n", - " \"\"\"\n", - " if epsilon <= 0:\n", - " RuntimeError(\"The algorithm will not terminate if epsilon is zero.\")\n", - "\n", - " # Create a dynamic matrix (list of lists) to store the result.\n", - " values_matrix = [[0 for state in model.get_states()]]\n", - " values_matrix[0][target_state.id] = 1\n", - "\n", - " terminate = False\n", - " while not terminate:\n", - " old_values = values_matrix[len(values_matrix) - 1]\n", - " new_values = [None for state in model.get_states()]\n", - " for sid, state in model.get_states().items():\n", - " transitions = model.get_transitions(state)\n", - " # Now we have to take a decision for an action.\n", - " actions = transitions.transition.keys()\n", - " action_values = {}\n", - " for action, branch in transitions.transition.items():\n", - " branch_value = sum([prob * old_values[state.id] for (prob, state) in branch.branch])\n", - " action_values[action] = branch_value\n", - " # We take the action with the highest value.\n", - " highest_value = max(action_values.values())\n", - " new_values[sid] = highest_value\n", - " values_matrix.append(new_values)\n", - " terminate = sum([abs(x-y) for (x, y) in zip(new_values, old_values)]) < epsilon\n", - " return values_matrix\n", - " " - ] - }, - { - "cell_type": "markdown", - "id": "46c998da-b579-4fc8-b385-7b1b07582359", - "metadata": {}, - "source": [ - "We apply naive value iteration on our lion model with 20 steps. Then we display the result of the as a heatmap, using matplotlib." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "a606dc3e-5d22-45a2-8234-30d3fe8b6bc5", - "metadata": {}, - "outputs": [ + }, { - "data": { - "image/png": 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", - "text/plain": [ - "
" + "cell_type": "code", + "execution_count": 5, + "id": "7f3692d1-ad64-449d-809c-01ceb84e6bb4", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "9990ef5a93aa41729419d45003428d66", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Output()" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from stormvogel.model import Model, ModelType, Branch, Transition\n", + "\n", + "lion = Model(name=\"lion\", model_type=ModelType.MDP)\n", + "init = lion.get_initial_state()\n", + "full = lion.new_state(\"full :D\")\n", + "satisfied = lion.new_state(\"satisfied :)\")\n", + "hungry = lion.new_state(\"hungry :(\")\n", + "starving = lion.new_state(\"starving :((\")\n", + "dead = lion.new_state(\"dead...\")\n", + "\n", + "hunt = lion.new_action(\"hunt >:D\")\n", + "rawr = lion.new_action(\"rawr\")\n", + "\n", + "init.set_transitions([(1, satisfied)])\n", + "\n", + "full.set_transitions(Transition({\n", + " hunt: Branch([\n", + " (0.5, satisfied),\n", + " (0.5, full),\n", + " ]),\n", + " rawr: Branch([\n", + " (0.9, full),\n", + " (0.1, satisfied)\n", + " ])\n", + "}))\n", + "\n", + "satisfied.set_transitions(Transition({\n", + " hunt: Branch([\n", + " (0.5, satisfied),\n", + " (0.3, full),\n", + " (0.2, hungry)\n", + " ]),\n", + " rawr: Branch([\n", + " (0.9, satisfied),\n", + " (0.1, hungry)\n", + " ])\n", + "}))\n", + "\n", + "hungry.set_transitions(Transition({\n", + " hunt: Branch([\n", + " (0.2, full),\n", + " (0.5, satisfied),\n", + " (0.1, hungry),\n", + " (0.2, starving)\n", + " ]),\n", + " rawr: Branch([\n", + " (0.9, hungry),\n", + " (0.1, starving)\n", + " ])\n", + "}))\n", + "\n", + "starving.set_transitions(Transition({\n", + " hunt: Branch([\n", + " (0.1, full),\n", + " (0.5, satisfied),\n", + " (0.2, hungry),\n", + " (0.2, dead)\n", + " ]),\n", + " rawr: Branch([\n", + " (0.9, starving),\n", + " (0.1, dead)\n", + " ])\n", + "}))\n", + "lion.add_self_loops()\n", + "\n", + "from stormvogel.show import show\n", + "from stormvogel.layout import Layout\n", + "vis = show(lion, layout=Layout(\"layouts/lion.json\"), name=\"lion\", show_editor=False)" ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import stormvogel.lib\n", - "res = naive_value_iteration(lion, 0.003, full)\n", - "labels = [s.labels[0] for s in lion.get_states().values()]\n", - "stormvogel.lib.display_value_iteration_result(res, 10, labels)" - ] - }, - { - "cell_type": "markdown", - "id": "dcbef4f2-78ae-4d2c-9587-9c96becf26b1", - "metadata": {}, - "source": [ - "Note that naive_value_iteration is also available under stormvogel.lib, in case you would like to use it later. However, this implementation is very inefficient so we recommend using the value iteration algorithms from stormpy if you want good performance." - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "12b57306-780c-4a40-898a-f3a95f7ff9eb", - "metadata": {}, - "outputs": [], - "source": [ - "import stormvogel.lib\n", - "res2 = stormvogel.lib.naive_value_iteration(lion, 0.003, full)\n", - "assert res == res2" - ] - } - ], - "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": "3.12.3" - }, - "widgets": { - "application/vnd.jupyter.widget-state+json": { - "state": { - "0a4470793a704b388de44c9e5f08cab8": { - "model_module": "@jupyter-widgets/output", - "model_module_version": "1.0.0", - 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"justify_content": null, - "justify_items": null, - "left": null, - "margin": null, - "max_height": null, - "max_width": null, - "min_height": null, - "min_width": null, - "object_fit": null, - "object_position": null, - "order": null, - "overflow": null, - "padding": null, - "right": null, - "top": null, - "visibility": null, - "width": null - } - }, - "c2b9fda9e1354d6ca57827715ca601ed": { - "model_module": "@jupyter-widgets/output", - "model_module_version": "1.0.0", - "model_name": "OutputModel", - "state": { - "_dom_classes": [], - "_model_module": "@jupyter-widgets/output", - "_model_module_version": "1.0.0", - "_model_name": "OutputModel", - "_view_count": null, - "_view_module": "@jupyter-widgets/output", - "_view_module_version": "1.0.0", - "_view_name": "OutputView", - "layout": "IPY_MODEL_52791b15670e460ba9fe9376b20cc3a8", - "msg_id": "", - "outputs": [ + }, + { + "cell_type": "markdown", + "id": "1c09fb4a-1fe9-4f76-982a-1eacd0b46a87", + "metadata": {}, + "source": [ + "Here we provide an implementation of naive value iteration using the model API." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "8807425f-1d69-4522-9077-b902c90bd0b2", + "metadata": {}, + "outputs": [], + "source": [ + "import stormvogel.model\n", + "\n", + "def naive_value_iteration(\n", + " model: stormvogel.model.Model, epsilon: float, target_state: stormvogel.model.State\n", + ") -> list[list[float]]:\n", + " \"\"\"Run naive value iteration. The result is a 2D list where result[n][m] is the probability to be in state m at step n.\n", + "\n", + " Args:\n", + " model (stormvogel.model.Model): Target model.\n", + " steps (int): Amount of steps.\n", + " target_state (stormvogel.model.State): Target state of the model.\n", + "\n", + " Returns:\n", + " list[list[float]]: The result is a 2D list where result[n][m] is the value of state m at iteration n.\n", + " \"\"\"\n", + " if epsilon <= 0:\n", + " RuntimeError(\"The algorithm will not terminate if epsilon is zero.\")\n", + "\n", + " # Create a dynamic matrix (list of lists) to store the result.\n", + " values_matrix = [[0 for state in model.get_states()]]\n", + " values_matrix[0][target_state.id] = 1\n", + "\n", + " terminate = False\n", + " while not terminate:\n", + " old_values = values_matrix[len(values_matrix) - 1]\n", + " new_values = [None for state in model.get_states()]\n", + " for sid, state in model.get_states().items():\n", + " transitions = model.get_transitions(state)\n", + " # Now we have to take a decision for an action.\n", + " actions = transitions.transition.keys()\n", + " action_values = {}\n", + " for action, branch in transitions.transition.items():\n", + " branch_value = sum([prob * old_values[state.id] for (prob, state) in branch.branch])\n", + " action_values[action] = branch_value\n", + " # We take the action with the highest value.\n", + " highest_value = max(action_values.values())\n", + " new_values[sid] = highest_value\n", + " values_matrix.append(new_values)\n", + " terminate = sum([abs(x-y) for (x, y) in zip(new_values, old_values)]) < epsilon\n", + " return values_matrix\n", + " " + ] + }, + { + "cell_type": "markdown", + "id": "46c998da-b579-4fc8-b385-7b1b07582359", + "metadata": {}, + "source": [ + "We apply naive value iteration on our lion model with 20 steps. Then we display the result of the as a heatmap, using matplotlib." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "a606dc3e-5d22-45a2-8234-30d3fe8b6bc5", + "metadata": {}, + "outputs": [ { - "data": { - "text/html": "\n ", - "text/plain": "" - }, - "metadata": {}, - "output_type": "display_data" + "data": { + "image/png": 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However, this implementation is very inefficient so we recommend using the value iteration algorithms from stormpy if you want good performance." + ] }, - "version_major": 2, - "version_minor": 0 - } - } - }, - "nbformat": 4, - "nbformat_minor": 5 + { + "cell_type": "code", + "execution_count": 8, + "id": "12b57306-780c-4a40-898a-f3a95f7ff9eb", + "metadata": {}, + "outputs": [], + "source": [ + "import stormvogel.lib\n", + "res2 = stormvogel.lib.naive_value_iteration(lion, 0.003, full)\n", + "assert res == res2" + ] + } + ], + "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": "3.12.3" + }, + "widgets": { + "application/vnd.jupyter.widget-state+json": { + "state": { + 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] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "2552891a-8d96-4c77-aa97-0a1ddf5bc02b", - "metadata": {}, - "outputs": [], - "source": [ - "from stormvogel import visualization, mapping, result, show\n", - "import stormpy" - ] - }, - { - "cell_type": "markdown", - "id": "2c278323", - "metadata": {}, - "source": [ - "Using the ``%%prism`` keyword, you can immediately tinker with PRISM programs in the notebooks. This example is the [NAND multiplexing case study from the PRISM website](https://www.prismmodelchecker.org/casestudies/nand.php). If you provide a variable name after the keyword, this variable will store your PRISM program after the execution of the cell." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "a00a5906-af87-4fb8-8f5f-ad5690129d33", - "metadata": {}, - "outputs": [ + "cells": [ { - "data": { - "text/plain": [ - "" + "cell_type": "markdown", + "id": "190cc3ba", + "metadata": {}, + "source": [ + "# Writing PRISM" ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "%%prism nand\n", - "dtmc\n", - "\n", - "const int N = 2; // number of inputs in each bundle\n", - "const int K = 2; // number of restorative stages\n", - "\n", - "const int M = 2*K+1; // total number of multiplexing units\n", - "\n", - "const double perr = 0.02; // probability nand works correctly\n", - "const double prob1 = 0.9; // probability initial inputs are stimulated\n", - "\n", - "module multiplex\n", - "\n", - "\tu : [1..M]; // number of stages\n", - "\tc : [0..N]; // counter (number of copies of the nand done)\n", - "\n", - "\ts : [0..4]; // local state\n", - "\t// 0 - initial state\n", - "\t// 1 - set x inputs\n", - "\t// 2 - set y inputs\n", - "\t// 3 - set outputs\n", - "\t// 4 - done\n", - "\n", - "\tz : [0..N]; // number of new outputs equal to 1\n", - "\tzx : [0..N]; // number of old outputs equal to 1\n", - "\tzy : [0..N]; // need second copy for y\n", - "\t// initially 9 since initially probability of stimulated state is 0.9\n", - "\n", - "\tx : [0..1]; // value of first input\n", - "\ty : [0..1]; // value of second input\n", - "\t\n", - "\t[] s=0 & (c (s'=1); // do next nand if have not done N yet\n", - "\t[] s=0 & (c=N) & (u (s'=1) & (zx'=z) & (zy'=z) & (z'=0) & (u'=u+1) & (c'=0); // move on to next u if not finished\n", - "\t[] s=0 & (c=N) & (u=M) -> (s'=4) & (zx'=0) & (zy'=0) & (x'=0) & (y'=0); // finished (so reset variables not needed to reduce state space)\n", - "\n", - "\t// choose x permute selection (have zx stimulated inputs)\n", - "\t// note only need y to be random\t\n", - "\t[] s=1 & u=1 -> prob1 : (x'=1) & (s'=2) + (1-prob1) : (x'=0) & (s'=2); // initially random\n", - "\t[] s=1 & u>1 & zx>0 -> (x'=1) & (s'=2) & (zx'=zx-1);\n", - "\t[] s=1 & u>1 & zx=0 -> (x'=0) & (s'=2);\n", - "\n", - "\t// choose x randomly from selection (have zy stimulated inputs)\n", - "\t[] s=2 & u=1 -> prob1 : (y'=1) & (s'=3) + (1-prob1) : (y'=0) & (s'=3); // initially random\n", - "\t[] s=2 & u>1 & zy<(N-c) & zy>0 -> zy/(N-c) : (y'=1) & (s'=3) & (zy'=zy-1) + 1-(zy/(N-c)) : (y'=0) & (s'=3);\n", - "\t[] s=2 & u>1 & zy=(N-c) & c 1 : (y'=1) & (s'=3) & (zy'=zy-1);\n", - "\t[] s=2 & u>1 & zy=0 -> 1 : (y'=0) & (s'=3);\n", - "\n", - "\t// use nand gate\n", - "\t[] s=3 & z (1-perr) : (z'=z+(1-x*y)) & (s'=0) & (c'=c+1) & (x'=0) & (y'=0) // not faulty\n", - "\t + perr : (z'=z+(x*y)) & (s'=0) & (c'=c+1) & (x'=0) & (y'=0); // von neumann fault\n", - "\t\n", - "\t[] s=4 -> (s'=s);\n", - "\t\n", - "endmodule\n", - "\n", - "// rewards: final value of gate\n", - "rewards\n", - "\t// [] s=0 & (c=N) & (u=M) : z/N;\n", - "\ts=0 & (c=N) & (u=M) : z/N;\n", - "endrewards\n", - "\n", - "label \"nextnand\" = s=0;\n", - "label \"selection\" = s=1;\n", - "label \"whichx\" = s=2;\n", - "label \"gate\" = s=3 & z 1 item(s)\n", - " * whichx -> 42 item(s)\n", - " * selection -> 39 item(s)\n", - " * nextnand -> 42 item(s)\n", - " * deadlock -> 0 item(s)\n", - " * target -> 1 item(s)\n", - " * gate -> 52 item(s)\n", - " * end -> 3 item(s)\n", - "Choice Labels: \tnone\n", - "-------------------------------------------------------------- \n", - "\n" - ] - } - ], - "source": [ - "print(nand_model)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "58dc3f9f", - "metadata": {}, - "outputs": [], - "source": [ - "stormpy_result = stormpy.model_checking(nand_model, prop[0])" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "7f568f16", - "metadata": {}, - "outputs": [ + "cell_type": "code", + "execution_count": 1, + "id": "2552891a-8d96-4c77-aa97-0a1ddf5bc02b", + "metadata": {}, + "outputs": [], + "source": [ + "from stormvogel import visualization, mapping, result, show\n", + "import stormpy" + ] + }, { - 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] - } - ], - "source": [ - "print(stormpy_result.get_values())" - ] - }, - { - "cell_type": "markdown", - "id": "f61dac88", - "metadata": {}, - "source": [ - "Let's visualize the model in an interactive graph :)" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "4b51450e", - "metadata": {}, - "outputs": [], - "source": [ - "stormvogel_model = mapping.stormpy_to_stormvogel(nand_model)\n", - "\n", - "stormvogel_result = result.convert_model_checking_result(stormvogel_model, stormpy_result)" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "59196c3e-aa2d-4fa6-abc7-b04bf3b5f1f4", - "metadata": {}, - "outputs": [ + "cell_type": "markdown", + "id": "2c278323", + "metadata": {}, + "source": [ + "Using the ``%%prism`` keyword, you can immediately tinker with PRISM programs in the notebooks. This example is the [NAND multiplexing case study from the PRISM website](https://www.prismmodelchecker.org/casestudies/nand.php). If you provide a variable name after the keyword, this variable will store your PRISM program after the execution of the cell." + ] + }, { - "data": { - "text/html": [ - "\n", - " " + "cell_type": "code", + "execution_count": 2, + "id": "a00a5906-af87-4fb8-8f5f-ad5690129d33", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } ], - "text/plain": [ - "" + "source": [ + "%%prism nand\n", + "dtmc\n", + "\n", + "const int N = 2; // number of inputs in each bundle\n", + "const int K = 2; // number of restorative stages\n", + "\n", + "const int M = 2*K+1; // total number of multiplexing units\n", + "\n", + "const double perr = 0.02; // probability nand works correctly\n", + "const double prob1 = 0.9; // probability initial inputs are stimulated\n", + "\n", + "module multiplex\n", + "\n", + "\tu : [1..M]; // number of stages\n", + "\tc : [0..N]; // counter (number of copies of the nand done)\n", + "\n", + "\ts : [0..4]; // local state\n", + "\t// 0 - initial state\n", + "\t// 1 - set x inputs\n", + "\t// 2 - set y inputs\n", + "\t// 3 - set outputs\n", + "\t// 4 - done\n", + "\n", + "\tz : [0..N]; // number of new outputs equal to 1\n", + "\tzx : [0..N]; // number of old outputs equal to 1\n", + "\tzy : [0..N]; // need second copy for y\n", + "\t// initially 9 since initially probability of stimulated state is 0.9\n", + "\n", + "\tx : [0..1]; // value of first input\n", + "\ty : [0..1]; // value of second input\n", + "\t\n", + "\t[] s=0 & (c (s'=1); // do next nand if have not done N yet\n", + "\t[] s=0 & (c=N) & (u (s'=1) & (zx'=z) & (zy'=z) & (z'=0) & (u'=u+1) & (c'=0); // move on to next u if not finished\n", + "\t[] s=0 & (c=N) & (u=M) -> (s'=4) & (zx'=0) & (zy'=0) & (x'=0) & (y'=0); // finished (so reset variables not needed to reduce state space)\n", + "\n", + "\t// choose x permute selection (have zx stimulated inputs)\n", + "\t// note only need y to be random\t\n", + "\t[] s=1 & u=1 -> prob1 : (x'=1) & (s'=2) + (1-prob1) : (x'=0) & (s'=2); // initially random\n", + "\t[] s=1 & u>1 & zx>0 -> (x'=1) & (s'=2) & (zx'=zx-1);\n", + "\t[] s=1 & u>1 & zx=0 -> (x'=0) & (s'=2);\n", + "\n", + "\t// choose x randomly from selection (have zy stimulated inputs)\n", + "\t[] s=2 & u=1 -> prob1 : (y'=1) & (s'=3) + (1-prob1) : (y'=0) & (s'=3); // initially random\n", + "\t[] s=2 & u>1 & zy<(N-c) & zy>0 -> zy/(N-c) : (y'=1) & (s'=3) & (zy'=zy-1) + 1-(zy/(N-c)) : (y'=0) & (s'=3);\n", + "\t[] s=2 & u>1 & zy=(N-c) & c 1 : (y'=1) & (s'=3) & (zy'=zy-1);\n", + "\t[] s=2 & u>1 & zy=0 -> 1 : (y'=0) & (s'=3);\n", + "\n", + "\t// use nand gate\n", + "\t[] s=3 & z (1-perr) : (z'=z+(1-x*y)) & (s'=0) & (c'=c+1) & (x'=0) & (y'=0) // not faulty\n", + "\t + perr : (z'=z+(x*y)) & (s'=0) & (c'=c+1) & (x'=0) & (y'=0); // von neumann fault\n", + "\t\n", + "\t[] s=4 -> (s'=s);\n", + "\t\n", + "endmodule\n", + "\n", + "// rewards: final value of gate\n", + "rewards\n", + "\t// [] s=0 & (c=N) & (u=M) : z/N;\n", + "\ts=0 & (c=N) & (u=M) : z/N;\n", + "endrewards\n", + "\n", + "label \"nextnand\" = s=0;\n", + "label \"selection\" = s=1;\n", + "label \"whichx\" = s=2;\n", + "label \"gate\" = s=3 & zFont" - 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"outputs": [ + }, + { + "cell_type": "markdown", + "id": "6fdae17c", + "metadata": {}, + "source": [ + "We now have a PRISM program, but that is not a Markov model yet, only a description. We can build this into a full model using stormpy:" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "049cb9f5-2e69-4092-982f-be446aee0012", + "metadata": {}, + "outputs": [], + "source": [ + "nand_model = stormpy.build_model(nand)" + ] + }, + { + "cell_type": "markdown", + "id": "7aa8ee57", + "metadata": {}, + "source": [ + "If we want to do model checking later, we need a property as well, such as:" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "336c76a2", + "metadata": {}, + "outputs": [], + "source": [ + "prop = stormpy.parse_properties(\"P=? [F \\\"target\\\"]\", nand)" + ] + }, + { + "cell_type": "markdown", + "id": "c67e37af", + "metadata": {}, + "source": [ + "We can print the model to get some basic information." + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "eb11837e-5c59-42d3-97ed-cedb76eca63c", + "metadata": {}, + "outputs": [ { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "4fe4981a477744c7ad088261177d0d2a", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": "VBox(children=(VBox(children=(Accordion(children=(VBox(children=(interactive(children=(IntSlider(value=1, desc…" - }, - "metadata": {}, - "output_type": "display_data" + "name": "stdout", + "output_type": "stream", + "text": [ + "-------------------------------------------------------------- \n", + "Model type: \tDTMC (sparse)\n", + "States: \t178\n", + "Transitions: \t243\n", + "Reward Models: (default)\n", + "State Labels: \t8 labels\n", + " * init -> 1 item(s)\n", + " * whichx -> 42 item(s)\n", + " * selection -> 39 item(s)\n", + " * nextnand -> 42 item(s)\n", + " * deadlock -> 0 item(s)\n", + " * target -> 1 item(s)\n", + " * gate -> 52 item(s)\n", + " * end -> 3 item(s)\n", + "Choice Labels: \tnone\n", + "-------------------------------------------------------------- \n", + "\n" + ] } - 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b/docs/getting_started/04_mdp.ipynb @@ -1,1650 +1,1650 @@ { - "cells": [ - { - "cell_type": "markdown", - "metadata": {}, - "source": [ - "# Example MDP" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "metadata": {}, - "outputs": [], - "source": [ - "from stormvogel import visualization, mapping, result, show\n", - "import stormpy" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "metadata": {}, - "outputs": [ + "cells": [ { - "data": { - "text/plain": [ - "" + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# Example MDP" ] - }, - "execution_count": 2, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "%%prism leader\n", - "// asynchronous leader election\n", - "// 4 processes\n", - "// gxn/dxp 29/01/01\n", - "\n", - "mdp\n", - "\n", - "const int N = 3; // number of processes\n", - "\n", - "//----------------------------------------------------------------------------------------------------------------------------\n", - "module process1\n", - "\t\n", - "\t// COUNTER\n", - "\tc1 : [0..3-1];\n", - "\t\n", - "\t// STATES\n", - "\ts1 : [0..4];\n", - "\t// 0 make choice\n", - "\t// 1 have not received neighbours choice\n", - "\t// 2 active\n", - "\t// 3 inactive\n", - "\t// 4 leader\n", - "\t\n", - "\t// PREFERENCE\n", - "\tp1 : [0..1];\n", - "\t\n", - "\t// VARIABLES FOR SENDING AND RECEIVING\n", - "\treceive1 : [0..2];\n", - "\t// not received anything\n", - "\t// received choice\n", - "\t// received counter\n", - "\tsent1 : [0..2];\n", - "\t// not send anything\n", - "\t// sent choice\n", - "\t// sent counter\n", - "\t\n", - "\t// pick value\n", - "\t[pick] (s1=0) -> 0.5 : (s1'=1) & (p1'=0) + 0.5 : (s1'=1) & (p1'=1);\n", - "\n", - "\t// send preference\n", - "\t[p12] (s1=1) & (sent1=0) -> (sent1'=1);\n", - "\t// receive preference\n", - "\t// stay active\n", - "\t[p31] (s1=1) & (receive1=0) & !( (p1=0) & (p3=1) ) -> (s1'=2) & (receive1'=1);\n", - "\t// become inactive\n", - "\t[p31] (s1=1) & (receive1=0) & (p1=0) & (p3=1) -> (s1'=3) & (receive1'=1);\n", - "\t\n", - "\t// send preference (can now reset preference)\n", - "\t[p12] (s1=2) & (sent1=0) -> (sent1'=1) & (p1'=0);\n", - "\t// send counter (already sent preference)\n", - "\t// not received counter yet\n", - "\t[c12] (s1=2) & (sent1=1) & (receive1=1) -> (sent1'=2);\n", - "\t// received counter (pick again)\n", - "\t[c12] (s1=2) & (sent1=1) & (receive1=2) -> (s1'=0) & (p1'=0) & (c1'=0) & (sent1'=0) & (receive1'=0);\n", - "\t\n", - "\t// receive counter and not sent yet (note in this case do not pass it on as will send own counter)\n", - "\t[c31] (s1=2) & (receive1=1) & (sent1<2) -> (receive1'=2);\n", - "\t// receive counter and sent counter\n", - "\t// only active process (decide)\n", - "\t[c31] (s1=2) & (receive1=1) & (sent1=2) & (c3=N-1) -> (s1'=4) & (p1'=0) & (c1'=0) & (sent1'=0) & (receive1'=0);\n", - "\t// other active process (pick again)\n", - "\t[c31] (s1=2) & (receive1=1) & (sent1=2) & (c3 (s1'=0) & (p1'=0) & (c1'=0) & (sent1'=0) & (receive1'=0);\n", - "\t\n", - "\t// send preference (must have received preference) and can now reset\n", - "\t[p12] (s1=3) & (receive1>0) & (sent1=0) -> (sent1'=1) & (p1'=0);\n", - "\t// send counter (must have received counter first) and can now reset\n", - "\t[c12] (s1=3) & (receive1=2) & (sent1=1) -> (s1'=3) & (p1'=0) & (c1'=0) & (sent1'=0) & (receive1'=0);\n", - "\t\n", - "\t// receive preference\n", - "\t[p31] (s1=3) & (receive1=0) -> (p1'=p3) & (receive1'=1);\n", - "\t// receive counter\n", - "\t[c31] (s1=3) & (receive1=1) & (c3 (c1'=c3+1) & (receive1'=2);\n", - "\t\t\n", - "\t// done\n", - "\t[done] (s1=4) -> (s1'=s1);\n", - "\t// add loop for processes who are inactive\n", - "\t[done] (s1=3) -> (s1'=s1);\n", - "\n", - "endmodule\n", - "\n", - "//----------------------------------------------------------------------------------------------------------------------------\n", - "\n", - "// construct further stations through renaming\n", - "module process2=process1[s1=s2,p1=p2,c1=c2,sent1=sent2,receive1=receive2,p12=p23,p31=p12,c12=c23,c31=c12,p3=p1,c3=c1] endmodule\n", - "module process3=process1[s1=s3,p1=p3,c1=c3,sent1=sent3,receive1=receive3,p12=p31,p31=p23,c12=c31,c31=c23,p3=p2,c3=c2] endmodule\n", - "\n", - "//----------------------------------------------------------------------------------------------------------------------------\n", - "rewards \"rounds\"\n", - " [c12] true : 1;\n", - "endrewards\n", - "\n", - "//----------------------------------------------------------------------------------------------------------------------------\n", - "formula leaders = (s1=4?1:0)+(s2=4?1:0)+(s3=4?1:0);\n", - "label \"elected\" = s1=4|s2=4|s3=4;\n" - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "metadata": {}, - "outputs": [], - "source": [ - "leader_model = stormpy.build_model(leader)\n", - "\n" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "metadata": {}, - "outputs": [ + }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "-------------------------------------------------------------- \n", - "Model type: \tMDP (sparse)\n", - "States: \t190\n", - "Transitions: \t323\n", - "Choices: \t316\n", - "Reward Models: rounds\n", - "State Labels: \t3 labels\n", - " * deadlock -> 3 item(s)\n", - " * init -> 1 item(s)\n", - " * elected -> 0 item(s)\n", - "Choice Labels: \tnone\n", - "-------------------------------------------------------------- \n", - "\n", - "['__class__', '__delattr__', '__dir__', '__doc__', '__eq__', '__format__', '__ge__', '__getattribute__', '__getstate__', '__gt__', '__hash__', '__init__', '__init_subclass__', '__le__', '__lt__', '__module__', '__ne__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__sizeof__', '__str__', '__subclasshook__', '_as_sparse_ctmc', '_as_sparse_dtmc', '_as_sparse_exact_dtmc', '_as_sparse_exact_mdp', '_as_sparse_imdp', '_as_sparse_ma', '_as_sparse_mdp', '_as_sparse_pctmc', '_as_sparse_pdtmc', '_as_sparse_pma', '_as_sparse_pmdp', '_as_sparse_pomdp', '_as_sparse_ppomdp', '_as_sparse_smg', '_as_symbolic_ctmc', '_as_symbolic_dtmc', '_as_symbolic_ma', '_as_symbolic_mdp', '_as_symbolic_pctmc', '_as_symbolic_pdtmc', '_as_symbolic_pma', '_as_symbolic_pmdp', 'add_reward_model', 'apply_scheduler', 'backward_transition_matrix', 'choice_labeling', 'choice_origins', 'get_choice_index', 'get_nr_available_actions', 'get_reward_model', 'has_choice_labeling', 'has_choice_origins', 'has_parameters', 'has_reward_model', 'has_state_valuations', 'initial_states', 'initial_states_as_bitvector', 'is_discrete_time_model', 'is_exact', 'is_nondeterministic_model', 'is_partially_observable', 'is_sink_state', 'is_sparse_model', 'is_symbolic_model', 'labeling', 'labels_state', 'model_type', 'nondeterministic_choice_indices', 'nr_choices', 'nr_states', 'nr_transitions', 'reduce_to_state_based_rewards', 'reward_models', 'set_initial_states', 'state_valuations', 'states', 'supports_parameters', 'supports_uncertainty', 'to_dot', 'transition_matrix']\n" - ] - } - ], - "source": [ - "print(leader_model)\n", - "\n", - "print(dir(leader_model))\n" - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "metadata": {}, - "outputs": [], - "source": [ - "prop = stormpy.parse_properties(\"Rmax=? [F \\\"elected\\\"]\", leader)" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "metadata": {}, - "outputs": [], - "source": [ - "stormpy_result = stormpy.model_checking(leader_model, prop[0], extract_scheduler=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "metadata": {}, - "outputs": [ + "cell_type": "code", + "execution_count": 1, + "metadata": {}, + "outputs": [], + "source": [ + "from stormvogel import visualization, mapping, result, show\n", + "import stormpy" + ] + }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "[inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf]\n" - ] - } - ], - "source": [ - "print(stormpy_result.get_values())" - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "metadata": {}, - "outputs": [ + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 2, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%%prism leader\n", + "// asynchronous leader election\n", + "// 4 processes\n", + "// gxn/dxp 29/01/01\n", + "\n", + "mdp\n", + "\n", + "const int N = 3; // number of processes\n", + "\n", + "//----------------------------------------------------------------------------------------------------------------------------\n", + "module process1\n", + "\t\n", + "\t// COUNTER\n", + "\tc1 : [0..3-1];\n", + "\t\n", + "\t// STATES\n", + "\ts1 : [0..4];\n", + "\t// 0 make choice\n", + "\t// 1 have not received neighbours choice\n", + "\t// 2 active\n", + "\t// 3 inactive\n", + "\t// 4 leader\n", + "\t\n", + "\t// PREFERENCE\n", + "\tp1 : [0..1];\n", + "\t\n", + "\t// VARIABLES FOR SENDING AND RECEIVING\n", + "\treceive1 : [0..2];\n", + "\t// not received anything\n", + "\t// received choice\n", + "\t// received counter\n", + "\tsent1 : [0..2];\n", + "\t// not send anything\n", + "\t// sent choice\n", + "\t// sent counter\n", + "\t\n", + "\t// pick value\n", + "\t[pick] (s1=0) -> 0.5 : (s1'=1) & (p1'=0) + 0.5 : (s1'=1) & (p1'=1);\n", + "\n", + "\t// send preference\n", + "\t[p12] (s1=1) & (sent1=0) -> (sent1'=1);\n", + "\t// receive preference\n", + "\t// stay active\n", + "\t[p31] (s1=1) & (receive1=0) & !( (p1=0) & (p3=1) ) -> (s1'=2) & (receive1'=1);\n", + "\t// become inactive\n", + "\t[p31] (s1=1) & (receive1=0) & (p1=0) & (p3=1) -> (s1'=3) & (receive1'=1);\n", + "\t\n", + "\t// send preference (can now reset preference)\n", + "\t[p12] (s1=2) & (sent1=0) -> (sent1'=1) & (p1'=0);\n", + "\t// send counter (already sent preference)\n", + "\t// not received counter yet\n", + "\t[c12] (s1=2) & (sent1=1) & (receive1=1) -> (sent1'=2);\n", + "\t// received counter (pick again)\n", + "\t[c12] (s1=2) & (sent1=1) & (receive1=2) -> (s1'=0) & (p1'=0) & (c1'=0) & (sent1'=0) & (receive1'=0);\n", + "\t\n", + "\t// receive counter and not sent yet (note in this case do not pass it on as will send own counter)\n", + "\t[c31] (s1=2) & (receive1=1) & (sent1<2) -> (receive1'=2);\n", + "\t// receive counter and sent counter\n", + "\t// only active process (decide)\n", + "\t[c31] (s1=2) & (receive1=1) & (sent1=2) & (c3=N-1) -> (s1'=4) & (p1'=0) & (c1'=0) & (sent1'=0) & (receive1'=0);\n", + "\t// other active process (pick again)\n", + "\t[c31] (s1=2) & (receive1=1) & (sent1=2) & (c3 (s1'=0) & (p1'=0) & (c1'=0) & (sent1'=0) & (receive1'=0);\n", + "\t\n", + "\t// send preference (must have received preference) and can now reset\n", + "\t[p12] (s1=3) & (receive1>0) & (sent1=0) -> (sent1'=1) & (p1'=0);\n", + "\t// send counter (must have received counter first) and can now reset\n", + "\t[c12] (s1=3) & (receive1=2) & (sent1=1) -> (s1'=3) & (p1'=0) & (c1'=0) & (sent1'=0) & (receive1'=0);\n", + "\t\n", + "\t// receive preference\n", + "\t[p31] (s1=3) & (receive1=0) -> (p1'=p3) & (receive1'=1);\n", + "\t// receive counter\n", + "\t[c31] (s1=3) & (receive1=1) & (c3 (c1'=c3+1) & (receive1'=2);\n", + "\t\t\n", + "\t// done\n", + "\t[done] (s1=4) -> (s1'=s1);\n", + "\t// add loop for processes who are inactive\n", + "\t[done] (s1=3) -> (s1'=s1);\n", + "\n", + "endmodule\n", + "\n", + "//----------------------------------------------------------------------------------------------------------------------------\n", + "\n", + "// construct further stations through renaming\n", + "module process2=process1[s1=s2,p1=p2,c1=c2,sent1=sent2,receive1=receive2,p12=p23,p31=p12,c12=c23,c31=c12,p3=p1,c3=c1] endmodule\n", + "module process3=process1[s1=s3,p1=p3,c1=c3,sent1=sent3,receive1=receive3,p12=p31,p31=p23,c12=c31,c31=c23,p3=p2,c3=c2] endmodule\n", + "\n", + "//----------------------------------------------------------------------------------------------------------------------------\n", + "rewards \"rounds\"\n", + " [c12] true : 1;\n", + "endrewards\n", + "\n", + "//----------------------------------------------------------------------------------------------------------------------------\n", + "formula leaders = (s1=4?1:0)+(s2=4?1:0)+(s3=4?1:0);\n", + "label \"elected\" = s1=4|s2=4|s3=4;\n" + ] + }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "-------------------------------------------------------------- \n", - "Model type: \tDTMC (sparse)\n", - "States: \t49\n", - "Transitions: \t56\n", - "Reward Models: rounds\n", - "State Labels: \t3 labels\n", - " * elected -> 0 item(s)\n", - " * init -> 1 item(s)\n", - " * deadlock -> 3 item(s)\n", - "Choice Labels: \tnone\n", - "-------------------------------------------------------------- \n", - "\n" - ] - } - ], - "source": [ - "scheduler = stormpy_result.scheduler\n", - "\n", - "print(leader_model.apply_scheduler(scheduler))" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "metadata": {}, - "outputs": [ + "cell_type": "code", + "execution_count": 3, + "metadata": {}, + "outputs": [], + "source": [ + "leader_model = stormpy.build_model(leader)\n", + "\n" + ] + }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "0 -> 0, 1 -> 0, 2 -> 0, 3 -> 0, 4 -> 0, 5 -> 0, 6 -> 0, 7 -> 0, 8 -> 0, 9 -> 0, 10 -> 0, 11 -> 0, 12 -> 0, 13 -> 0, 14 -> 0, 15 -> 0, 16 -> 0, 17 -> 0, 18 -> 0, 19 -> 0, 20 -> 0, 21 -> 0, 22 -> 0, 23 -> 0, 24 -> 0, 25 -> 0, 26 -> 0, 27 -> 0, 28 -> 0, 29 -> 0, 30 -> 0, 31 -> 0, 32 -> 0, 33 -> 0, 34 -> 0, 35 -> 0, 36 -> 0, 37 -> 0, 38 -> 0, 39 -> 0, 40 -> 0, 41 -> 0, 42 -> 0, 43 -> 0, 44 -> 0, 45 -> 0, 46 -> 0, 47 -> 0, 48 -> 0, 49 -> 0, 50 -> 0, 51 -> 0, 52 -> 0, 53 -> 0, 54 -> 0, 55 -> 0, 56 -> 0, 57 -> 0, 58 -> 0, 59 -> 0, 60 -> 0, 61 -> 0, 62 -> 0, 63 -> 0, 64 -> 0, 65 -> 0, 66 -> 0, 67 -> 0, 68 -> 0, 69 -> 0, 70 -> 0, 71 -> 0, 72 -> 0, 73 -> 0, 74 -> 0, 75 -> 0, 76 -> 0, 77 -> 0, 78 -> 0, 79 -> 0, 80 -> 0, 81 -> 0, 82 -> 0, 83 -> 0, 84 -> 0, 85 -> 0, 86 -> 0, 87 -> 0, 88 -> 0, 89 -> 0, 90 -> 0, 91 -> 0, 92 -> 0, 93 -> 0, 94 -> 0, 95 -> 0, 96 -> 0, 97 -> 0, 98 -> 0, 99 -> 0, 100 -> 0, 101 -> 0, 102 -> 0, 103 -> 0, 104 -> 0, 105 -> 0, 106 -> 0, 107 -> 0, 108 -> 0, 109 -> 0, 110 -> 0, 111 -> 0, 112 -> 0, 113 -> 0, 114 -> 0, 115 -> 0, 116 -> 0, 117 -> 0, 118 -> 0, 119 -> 0, 120 -> 0, 121 -> 0, 122 -> 0, 123 -> 0, 124 -> 0, 125 -> 0, 126 -> 0, 127 -> 0, 128 -> 0, 129 -> 0, 130 -> 0, 131 -> 0, 132 -> 0, 133 -> 0, 134 -> 0, 135 -> 0, 136 -> 0, 137 -> 0, 138 -> 0, 139 -> 0, 140 -> 0, 141 -> 0, 142 -> 0, 143 -> 0, 144 -> 0, 145 -> 0, 146 -> 0, 147 -> 0, 148 -> 0, 149 -> 0, 150 -> 0, 151 -> 0, 152 -> 0, 153 -> 0, 154 -> 0, 155 -> 0, 156 -> 0, 157 -> 0, 158 -> 0, 159 -> 0, 160 -> 0, 161 -> 0, 162 -> 0, 163 -> 0, 164 -> 0, 165 -> 0, 166 -> 0, 167 -> 0, 168 -> 0, 169 -> 0, 170 -> 0, 171 -> 0, 172 -> 0, 173 -> 0, 174 -> 0, 175 -> 0, 176 -> 0, 177 -> 0, 178 -> 0, 179 -> 0, 180 -> 0, 181 -> 0, 182 -> 0, 183 -> 0, 184 -> 0, 185 -> 0, 186 -> 0, 187 -> 0, 188 -> 0, 189 -> 0\n" - ] - } - ], - "source": [ - "scheduler_str = []\n", - "for state in leader_model.states:\n", - " choice = scheduler.get_choice(state)\n", - " action = choice.get_deterministic_choice()\n", - " scheduler_str.append(f\"{state} -> {action}\")\n", - "print(\", \".join(scheduler_str))" - ] - }, - { - "cell_type": "code", - "execution_count": 10, - "metadata": { - "scrolled": true - }, - "outputs": [], - "source": [ - "stormvogel_model = mapping.stormpy_to_stormvogel(leader_model)\n", - "\n", - "stormvogel_result = result.convert_model_checking_result(stormvogel_model, stormpy_result)" - ] - }, - { - "cell_type": "code", - "execution_count": 11, - "metadata": { - "scrolled": true - }, - "outputs": [ + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "-------------------------------------------------------------- \n", + "Model type: \tMDP (sparse)\n", + "States: \t190\n", + "Transitions: \t323\n", + "Choices: \t316\n", + "Reward Models: rounds\n", + "State Labels: \t3 labels\n", + " * deadlock -> 3 item(s)\n", + " * init -> 1 item(s)\n", + " * elected -> 0 item(s)\n", + "Choice Labels: \tnone\n", + "-------------------------------------------------------------- \n", + "\n", + "['__class__', '__delattr__', '__dir__', '__doc__', '__eq__', '__format__', '__ge__', '__getattribute__', '__getstate__', '__gt__', '__hash__', '__init__', '__init_subclass__', '__le__', '__lt__', '__module__', '__ne__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__sizeof__', '__str__', '__subclasshook__', '_as_sparse_ctmc', '_as_sparse_dtmc', '_as_sparse_exact_dtmc', '_as_sparse_exact_mdp', '_as_sparse_imdp', '_as_sparse_ma', '_as_sparse_mdp', '_as_sparse_pctmc', '_as_sparse_pdtmc', '_as_sparse_pma', '_as_sparse_pmdp', '_as_sparse_pomdp', '_as_sparse_ppomdp', '_as_sparse_smg', '_as_symbolic_ctmc', '_as_symbolic_dtmc', '_as_symbolic_ma', '_as_symbolic_mdp', '_as_symbolic_pctmc', '_as_symbolic_pdtmc', '_as_symbolic_pma', '_as_symbolic_pmdp', 'add_reward_model', 'apply_scheduler', 'backward_transition_matrix', 'choice_labeling', 'choice_origins', 'get_choice_index', 'get_nr_available_actions', 'get_reward_model', 'has_choice_labeling', 'has_choice_origins', 'has_parameters', 'has_reward_model', 'has_state_valuations', 'initial_states', 'initial_states_as_bitvector', 'is_discrete_time_model', 'is_exact', 'is_nondeterministic_model', 'is_partially_observable', 'is_sink_state', 'is_sparse_model', 'is_symbolic_model', 'labeling', 'labels_state', 'model_type', 'nondeterministic_choice_indices', 'nr_choices', 'nr_states', 'nr_transitions', 'reduce_to_state_based_rewards', 'reward_models', 'set_initial_states', 'state_valuations', 'states', 'supports_parameters', 'supports_uncertainty', 'to_dot', 'transition_matrix']\n" + ] + } + ], + "source": [ + "print(leader_model)\n", + "\n", + "print(dir(leader_model))\n" + ] + }, { - "data": { - "text/html": [ - "\n", - " " + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "prop = stormpy.parse_properties(\"Rmax=? [F \\\"elected\\\"]\", leader)" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "stormpy_result = stormpy.model_checking(leader_model, prop[0], extract_scheduler=True)" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "[inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf, inf]\n" + ] + } ], - "text/plain": [ - "" + "source": [ + "print(stormpy_result.get_values())" ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "import stormvogel.layout\n", - "\n", - "vis1 = show.show(stormvogel_model, stormvogel_result, layout=stormvogel.layout.EXPLORE(), show_editor=False, save_and_embed=True)" - ] - }, - { - "cell_type": "code", - "execution_count": 13, - "metadata": {}, - "outputs": [], - "source": [ - "induced_dtmc = stormvogel_result.generate_induced_dtmc()" - ] - }, - { - "cell_type": "code", - "execution_count": 14, - "metadata": {}, - "outputs": [ + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "-------------------------------------------------------------- \n", + "Model type: \tDTMC (sparse)\n", + "States: \t49\n", + "Transitions: \t56\n", + "Reward Models: rounds\n", + "State Labels: \t3 labels\n", + " * elected -> 0 item(s)\n", + " * init -> 1 item(s)\n", + " * deadlock -> 3 item(s)\n", + "Choice Labels: \tnone\n", + "-------------------------------------------------------------- \n", + "\n" + ] + } + ], + "source": [ + "scheduler = stormpy_result.scheduler\n", + "\n", + "print(leader_model.apply_scheduler(scheduler))" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "0 -> 0, 1 -> 0, 2 -> 0, 3 -> 0, 4 -> 0, 5 -> 0, 6 -> 0, 7 -> 0, 8 -> 0, 9 -> 0, 10 -> 0, 11 -> 0, 12 -> 0, 13 -> 0, 14 -> 0, 15 -> 0, 16 -> 0, 17 -> 0, 18 -> 0, 19 -> 0, 20 -> 0, 21 -> 0, 22 -> 0, 23 -> 0, 24 -> 0, 25 -> 0, 26 -> 0, 27 -> 0, 28 -> 0, 29 -> 0, 30 -> 0, 31 -> 0, 32 -> 0, 33 -> 0, 34 -> 0, 35 -> 0, 36 -> 0, 37 -> 0, 38 -> 0, 39 -> 0, 40 -> 0, 41 -> 0, 42 -> 0, 43 -> 0, 44 -> 0, 45 -> 0, 46 -> 0, 47 -> 0, 48 -> 0, 49 -> 0, 50 -> 0, 51 -> 0, 52 -> 0, 53 -> 0, 54 -> 0, 55 -> 0, 56 -> 0, 57 -> 0, 58 -> 0, 59 -> 0, 60 -> 0, 61 -> 0, 62 -> 0, 63 -> 0, 64 -> 0, 65 -> 0, 66 -> 0, 67 -> 0, 68 -> 0, 69 -> 0, 70 -> 0, 71 -> 0, 72 -> 0, 73 -> 0, 74 -> 0, 75 -> 0, 76 -> 0, 77 -> 0, 78 -> 0, 79 -> 0, 80 -> 0, 81 -> 0, 82 -> 0, 83 -> 0, 84 -> 0, 85 -> 0, 86 -> 0, 87 -> 0, 88 -> 0, 89 -> 0, 90 -> 0, 91 -> 0, 92 -> 0, 93 -> 0, 94 -> 0, 95 -> 0, 96 -> 0, 97 -> 0, 98 -> 0, 99 -> 0, 100 -> 0, 101 -> 0, 102 -> 0, 103 -> 0, 104 -> 0, 105 -> 0, 106 -> 0, 107 -> 0, 108 -> 0, 109 -> 0, 110 -> 0, 111 -> 0, 112 -> 0, 113 -> 0, 114 -> 0, 115 -> 0, 116 -> 0, 117 -> 0, 118 -> 0, 119 -> 0, 120 -> 0, 121 -> 0, 122 -> 0, 123 -> 0, 124 -> 0, 125 -> 0, 126 -> 0, 127 -> 0, 128 -> 0, 129 -> 0, 130 -> 0, 131 -> 0, 132 -> 0, 133 -> 0, 134 -> 0, 135 -> 0, 136 -> 0, 137 -> 0, 138 -> 0, 139 -> 0, 140 -> 0, 141 -> 0, 142 -> 0, 143 -> 0, 144 -> 0, 145 -> 0, 146 -> 0, 147 -> 0, 148 -> 0, 149 -> 0, 150 -> 0, 151 -> 0, 152 -> 0, 153 -> 0, 154 -> 0, 155 -> 0, 156 -> 0, 157 -> 0, 158 -> 0, 159 -> 0, 160 -> 0, 161 -> 0, 162 -> 0, 163 -> 0, 164 -> 0, 165 -> 0, 166 -> 0, 167 -> 0, 168 -> 0, 169 -> 0, 170 -> 0, 171 -> 0, 172 -> 0, 173 -> 0, 174 -> 0, 175 -> 0, 176 -> 0, 177 -> 0, 178 -> 0, 179 -> 0, 180 -> 0, 181 -> 0, 182 -> 0, 183 -> 0, 184 -> 0, 185 -> 0, 186 -> 0, 187 -> 0, 188 -> 0, 189 -> 0\n" + ] + } + ], + "source": [ + "scheduler_str = []\n", + "for state in leader_model.states:\n", + " choice = scheduler.get_choice(state)\n", + " action = choice.get_deterministic_choice()\n", + " scheduler_str.append(f\"{state} -> {action}\")\n", + "print(\", \".join(scheduler_str))" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": { + "scrolled": true + }, + "outputs": [], + "source": [ + "stormvogel_model = mapping.stormpy_to_stormvogel(leader_model)\n", + "\n", + "stormvogel_result = result.convert_model_checking_result(stormvogel_model, stormpy_result)" + ] + }, { - "data": { - "text/html": [ - "\n", - " " + "cell_type": "code", + "execution_count": 11, + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } ], - "text/plain": [ - "" + "source": [ + "import stormvogel.layout\n", + "\n", + "vis1 = show.show(stormvogel_model, stormvogel_result, layout=stormvogel.layout.EXPLORE(), show_editor=False, save_and_embed=True)" ] - }, - "metadata": {}, - "output_type": "display_data" + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [], + "source": [ + "induced_dtmc = stormvogel_result.generate_induced_dtmc()" + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "vis2 = show.show(induced_dtmc, layout=stormvogel.layout.EXPLORE(), show_editor=False, save_and_embed=True)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "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": "3.12.3" } - ], - "source": [ - "vis2 = show.show(induced_dtmc, layout=stormvogel.layout.EXPLORE(), show_editor=False, save_and_embed=True)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "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": "3.12.3" - } - }, - "nbformat": 4, - "nbformat_minor": 4 + "nbformat": 4, + "nbformat_minor": 4 } diff --git a/docs/getting_started/05_simulator.ipynb b/docs/getting_started/05_simulator.ipynb index f52ded4..25eb065 100644 --- a/docs/getting_started/05_simulator.ipynb +++ b/docs/getting_started/05_simulator.ipynb @@ -1,2923 +1,2923 @@ { - "cells": [ - { - "cell_type": "markdown", - "id": "a7245ed2", - "metadata": {}, - "source": [ - "# The simulator" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "a8ddc37c-66d2-43e4-8162-6be19a1d70a1", - "metadata": {}, - "outputs": [], - "source": [ - "from stormvogel.show import show\n", - "from stormvogel.layout import Layout\n", - "import stormvogel.model\n", - "import stormvogel.simulator" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "cab40f99-3460-4497-8b9f-3d669eee1e11", - "metadata": {}, - "outputs": [], - "source": [ - "# We create the monty hall mdp\n", - "mdp = stormvogel.model.new_mdp(\"Monty Hall\")\n", - "\n", - "init = mdp.get_initial_state()\n", - "\n", - "# first choose car position\n", - "init.set_transitions(\n", - " [(1 / 3, mdp.new_state(\"carchosen\", {\"car_pos\": i})) for i in range(3)]\n", - ")\n", - "\n", - "# we choose a door in each case\n", - "for s in mdp.get_states_with_label(\"carchosen\"):\n", - " s.set_transitions(\n", - " [\n", - " (\n", - " mdp.action(f\"open{i}\"),\n", - " mdp.new_state(\"open\", s.features | {\"chosen_pos\": i}),\n", - " )\n", - " for i in range(3)\n", - " ]\n", - " )\n", - "\n", - "# the other goat is revealed\n", - "for s in mdp.get_states_with_label(\"open\"):\n", - " car_pos = s.features[\"car_pos\"]\n", - " chosen_pos = s.features[\"chosen_pos\"]\n", - " other_pos = {0, 1, 2} - {car_pos, chosen_pos}\n", - " s.set_transitions(\n", - " [\n", - " (\n", - " 1 / len(other_pos),\n", - " mdp.new_state(\"goatrevealed\", s.features | {\"reveal_pos\": i}),\n", - " )\n", - " for i in other_pos\n", - " ]\n", - " )\n", - "\n", - "# we must choose whether we want to switch\n", - "for s in mdp.get_states_with_label(\"goatrevealed\"):\n", - " car_pos = s.features[\"car_pos\"]\n", - " chosen_pos = s.features[\"chosen_pos\"]\n", - " reveal_pos = s.features[\"reveal_pos\"]\n", - " other_pos = list({0, 1, 2} - {reveal_pos, chosen_pos})[0]\n", - " s.set_transitions(\n", - " [\n", - " (\n", - " mdp.action(\"stay\"),\n", - " mdp.new_state(\n", - " [\"done\"] + ([\"target\"] if chosen_pos == car_pos else []),\n", - " s.features | {\"chosen_pos\": chosen_pos},\n", - " ),\n", - " ),\n", - " (\n", - " mdp.action(\"switch\"),\n", - " mdp.new_state(\n", - " [\"done\"] + ([\"target\"] if other_pos == car_pos else []),\n", - " s.features | {\"chosen_pos\": other_pos},\n", - " ),\n", - " ),\n", - " ]\n", - " )\n", - "\n", - "# we add self loops to all states with no outgoing transitions\n", - "mdp.add_self_loops()" - ] - }, - { - "cell_type": "markdown", - "id": "d1f90374-dc85-4f31-b59f-aaf5e48a32f7", - "metadata": {}, - "source": [ - "We show what our mdp model looks like." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "c129cf62-40ca-4246-8718-5c859744e7f8", - "metadata": { - "scrolled": true - }, - "outputs": [ + "cells": [ + { + "cell_type": "markdown", + "id": "a7245ed2", + "metadata": {}, + "source": [ + "# The simulator" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "a8ddc37c-66d2-43e4-8162-6be19a1d70a1", + "metadata": {}, + "outputs": [], + "source": [ + "from stormvogel.show import show\n", + "from stormvogel.layout import Layout\n", + "import stormvogel.model\n", + "import stormvogel.simulator" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "cab40f99-3460-4497-8b9f-3d669eee1e11", + "metadata": {}, + "outputs": [], + "source": [ + "# We create the monty hall mdp\n", + "mdp = stormvogel.model.new_mdp(\"Monty Hall\")\n", + "\n", + "init = mdp.get_initial_state()\n", + "\n", + "# first choose car position\n", + "init.set_transitions(\n", + " [(1 / 3, mdp.new_state(\"carchosen\", {\"car_pos\": i})) for i in range(3)]\n", + ")\n", + "\n", + "# we choose a door in each case\n", + "for s in mdp.get_states_with_label(\"carchosen\"):\n", + " s.set_transitions(\n", + " [\n", + " (\n", + " mdp.action(f\"open{i}\"),\n", + " mdp.new_state(\"open\", s.features | {\"chosen_pos\": i}),\n", + " )\n", + " for i in range(3)\n", + " ]\n", + " )\n", + "\n", + "# the other goat is revealed\n", + "for s in mdp.get_states_with_label(\"open\"):\n", + " car_pos = s.features[\"car_pos\"]\n", + " chosen_pos = s.features[\"chosen_pos\"]\n", + " other_pos = {0, 1, 2} - {car_pos, chosen_pos}\n", + " s.set_transitions(\n", + " [\n", + " (\n", + " 1 / len(other_pos),\n", + " mdp.new_state(\"goatrevealed\", s.features | {\"reveal_pos\": i}),\n", + " )\n", + " for i in other_pos\n", + " ]\n", + " )\n", + "\n", + "# we must choose whether we want to switch\n", + "for s in mdp.get_states_with_label(\"goatrevealed\"):\n", + " car_pos = s.features[\"car_pos\"]\n", + " chosen_pos = s.features[\"chosen_pos\"]\n", + " reveal_pos = s.features[\"reveal_pos\"]\n", + " other_pos = list({0, 1, 2} - {reveal_pos, chosen_pos})[0]\n", + " s.set_transitions(\n", + " [\n", + " (\n", + " mdp.action(\"stay\"),\n", + " mdp.new_state(\n", + " [\"done\"] + ([\"target\"] if chosen_pos == car_pos else []),\n", + " s.features | {\"chosen_pos\": chosen_pos},\n", + " ),\n", + " ),\n", + " (\n", + " mdp.action(\"switch\"),\n", + " mdp.new_state(\n", + " [\"done\"] + ([\"target\"] if other_pos == car_pos else []),\n", + " s.features | {\"chosen_pos\": other_pos},\n", + " ),\n", + " ),\n", + " ]\n", + " )\n", + "\n", + "# we add self loops to all states with no outgoing transitions\n", + "mdp.add_self_loops()" + ] + }, + { + "cell_type": "markdown", + "id": "d1f90374-dc85-4f31-b59f-aaf5e48a32f7", + "metadata": {}, + "source": [ + "We show what our mdp model looks like." + ] + }, { - "data": { - "text/html": [ - "\n", - " " + "cell_type": "code", + "execution_count": 3, + "id": "c129cf62-40ca-4246-8718-5c859744e7f8", + "metadata": { + "scrolled": true + }, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } ], - "text/plain": [ - "" + "source": [ + "vis = show(mdp, layout=Layout(\"layouts/monty.json\"), save_and_embed=True)" ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "vis = show(mdp, layout=Layout(\"layouts/monty.json\"), save_and_embed=True)" - ] - }, - { - "cell_type": "markdown", - "id": "b5b2990c-65ed-4d7b-a4b8-f303843622e5", - "metadata": {}, - "source": [ - "We want to simulate this model. That is, we start at the initial state and then we walk through the model by choosing random actions.\n", - "\n", - "When we do this, we get a partial model as a result that contains everything we discovered during this walk. \n", - "\n", - "Try running this multiple times, and observe that sometimes we get to the target and sometimes we do not." - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "eb0fadc0-7bb6-4c1d-ae3e-9e16527726ab", - "metadata": {}, - "outputs": [ + }, + { + "cell_type": "markdown", + "id": "b5b2990c-65ed-4d7b-a4b8-f303843622e5", + "metadata": {}, + "source": [ + "We want to simulate this model. That is, we start at the initial state and then we walk through the model by choosing random actions.\n", + "\n", + "When we do this, we get a partial model as a result that contains everything we discovered during this walk. \n", + "\n", + "Try running this multiple times, and observe that sometimes we get to the target and sometimes we do not." + ] + }, { - "data": { - "text/html": [ - "\n", - " " + "cell_type": "code", + "execution_count": 4, + "id": "eb0fadc0-7bb6-4c1d-ae3e-9e16527726ab", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } ], - "text/plain": [ - "" + "source": [ + "# we can choose how many steps we take:\n", + "steps = 4\n", + "\n", + "# and we can specify a seed if we want:\n", + "seed = 12345676346\n", + "\n", + "# then we run the simulator:\n", + "partial_model = stormvogel.simulator.simulate(mdp, steps=steps, seed=seed)\n", + "# We could also provide a seed.\n", + "#partial_model = stormvogel.simulator.simulate(mdp, steps=steps, seed=seed)\n", + "\n", + "vis = show(partial_model, save_and_embed=True, layout=Layout(\"layouts/small_monty.json\"))" ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "# we can choose how many steps we take:\n", - "steps = 4\n", - "\n", - "# and we can specify a seed if we want:\n", - "seed = 12345676346\n", - "\n", - "# then we run the simulator:\n", - "partial_model = stormvogel.simulator.simulate(mdp, steps=steps, seed=seed)\n", - "# We could also provide a seed.\n", - "#partial_model = stormvogel.simulator.simulate(mdp, steps=steps, seed=seed)\n", - "\n", - "vis = show(partial_model, save_and_embed=True, layout=Layout(\"layouts/small_monty.json\"))" - ] - }, - { - "cell_type": "markdown", - "id": "49e3893d-bc35-4648-87eb-74a6a222ebf0", - "metadata": {}, - "source": [ - "We can also provide a scheduler (i.e. policy) which chooses what actions we should take at all time.\n", - "\n", - "In this case, we always take the first action, which means that we open door 0, and don't switch doors." - ] - }, - { - "cell_type": "code", - "execution_count": 5, - "id": "59ac1e34-866c-42c4-b19b-c2a15c830e2e", - "metadata": {}, - "outputs": [ + }, + { + "cell_type": "markdown", + "id": "49e3893d-bc35-4648-87eb-74a6a222ebf0", + "metadata": {}, + "source": [ + "We can also provide a scheduler (i.e. policy) which chooses what actions we should take at all time.\n", + "\n", + "In this case, we always take the first action, which means that we open door 0, and don't switch doors." + ] + }, { - "data": { - "text/html": [ - "\n", - " " + "cell_type": "code", + "execution_count": 5, + "id": "59ac1e34-866c-42c4-b19b-c2a15c830e2e", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } ], - "text/plain": [ - "" + "source": [ + "#it still chooses random actions but we can prevent this by providing a scheduler:\n", + "taken_actions = {}\n", + "for id, state in mdp.states.items():\n", + " taken_actions[id] = state.available_actions()[0]\n", + "scheduler = stormvogel.result.Scheduler(mdp, taken_actions)\n", + "\n", + "partial_model = stormvogel.simulator.simulate(mdp, steps=steps, scheduler=scheduler, seed=seed)\n", + "vis = show(partial_model, save_and_embed=True, layout=Layout(\"layouts/small_monty.json\"))" ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "#it still chooses random actions but we can prevent this by providing a scheduler:\n", - "taken_actions = {}\n", - "for id, state in mdp.states.items():\n", - " taken_actions[id] = state.available_actions()[0]\n", - "scheduler = stormvogel.result.Scheduler(mdp, taken_actions)\n", - "\n", - "partial_model = stormvogel.simulator.simulate(mdp, steps=steps, scheduler=scheduler, seed=seed)\n", - "vis = show(partial_model, save_and_embed=True, layout=Layout(\"layouts/small_monty.json\"))" - ] - }, - { - "cell_type": "markdown", - "id": "57a9b77d-4a75-42e4-8006-0bb11f2b345c", - "metadata": {}, - "source": [ - "We can highlight the scheduled states in the visualization of the entire model." - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "7e23fc38-b2af-4f02-b0a2-5d06151d2ca5", - "metadata": {}, - "outputs": [ + }, { - "data": { - "text/html": [ - "\n", - " " + "cell_type": "markdown", + "id": "57a9b77d-4a75-42e4-8006-0bb11f2b345c", + "metadata": {}, + "source": [ + "We can highlight the scheduled states in the visualization of the entire model." + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "7e23fc38-b2af-4f02-b0a2-5d06151d2ca5", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } ], - "text/plain": [ - "" + "source": [ + "vis = show(mdp, show_editor=True, layout=Layout(\"layouts/monty.json\"), scheduler=scheduler, save_and_embed=True)" ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "vis = show(mdp, show_editor=True, layout=Layout(\"layouts/monty.json\"), scheduler=scheduler, save_and_embed=True)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "191d5284-33b2-4ab3-8a1a-7c0c3334d250", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "markdown", - "id": "e4f388d8-d08b-40f5-a61b-1f5f29d004c9", - "metadata": {}, - "source": [ - "We can also get a path from the simulator function." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "34d0c293-d090-4e3d-9e80-4351f5fcba62", - "metadata": {}, - "outputs": [ + }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "initial state --(action: empty)--> state: 2 --(action: open0)--> state: 7 --(action: empty)--> state: 17 --(action: stay)--> state: 33\n" - ] - } - ], - "source": [ - "#we can also use another simulator function that returns a path instead of a partial model:\n", - "path = stormvogel.simulator.simulate_path(mdp, steps=4, scheduler=scheduler, seed=123456)\n", - "\n", - "print(path)" - ] - }, - { - "cell_type": "markdown", - "id": "1e0f6fea-6cd3-43e0-beea-84dc26eeca0b", - "metadata": {}, - "source": [ - "We can even visualize this path interactively! This works with any Path, not just a scheduler path. TODO." - ] - }, - { - "cell_type": "code", - "execution_count": 8, - "id": "afbb3234-99e4-49d0-b259-f598e895f600", - "metadata": {}, - "outputs": [ + "cell_type": "code", + "execution_count": null, + "id": "191d5284-33b2-4ab3-8a1a-7c0c3334d250", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "markdown", + "id": "e4f388d8-d08b-40f5-a61b-1f5f29d004c9", + "metadata": {}, + "source": [ + "We can also get a path from the simulator function." + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "34d0c293-d090-4e3d-9e80-4351f5fcba62", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "initial state --(action: empty)--> state: 2 --(action: open0)--> state: 7 --(action: empty)--> state: 17 --(action: stay)--> state: 33\n" + ] + } + ], + "source": [ + "#we can also use another simulator function that returns a path instead of a partial model:\n", + "path = stormvogel.simulator.simulate_path(mdp, steps=4, scheduler=scheduler, seed=123456)\n", + "\n", + "print(path)" + ] + }, + { + "cell_type": "markdown", + "id": "1e0f6fea-6cd3-43e0-beea-84dc26eeca0b", + "metadata": {}, + "source": [ + "We can even visualize this path interactively! This works with any Path, not just a scheduler path. TODO." + ] + }, { - "data": { - "text/html": [ - "\n", - " " + "cell_type": "code", + "execution_count": 8, + "id": "afbb3234-99e4-49d0-b259-f598e895f600", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "ename": "AttributeError", + "evalue": "'Visualization' object has no attribute 'show_path'", + "output_type": "error", + "traceback": [ + "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", + "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", + "Cell \u001b[0;32mIn[8], line 5\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtime\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m sleep\n\u001b[1;32m 4\u001b[0m vis \u001b[38;5;241m=\u001b[39m show(mdp, save_and_embed\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m, layout\u001b[38;5;241m=\u001b[39mLayout(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlayouts/monty.json\u001b[39m\u001b[38;5;124m\"\u001b[39m))\n\u001b[0;32m----> 5\u001b[0m \u001b[43mvis\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mshow_path\u001b[49m(path)\n\u001b[1;32m 6\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m state \u001b[38;5;129;01min\u001b[39;00m path:\n\u001b[1;32m 7\u001b[0m vis\u001b[38;5;241m.\u001b[39mhighlight_state(state, color\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mred\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", + "\u001b[0;31mAttributeError\u001b[0m: 'Visualization' object has no attribute 'show_path'" + ] + } ], - "text/plain": [ - "" + "source": [ + "from stormvogel.show import show\n", + "from time import sleep\n", + "\n", + "vis = show(mdp, save_and_embed=True, layout=Layout(\"layouts/monty.json\"))\n", + "vis.show_path(path)\n", + "for state in path:\n", + " vis.highlight_state(state, color=\"red\")\n", + " sleep(1)\n", + " # TODO should crash\n", + " " ] - }, - "metadata": {}, - "output_type": "display_data" }, { - "ename": "AttributeError", - "evalue": "'Visualization' object has no attribute 'show_path'", - "output_type": "error", - "traceback": [ - "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m", - "\u001b[0;31mAttributeError\u001b[0m Traceback (most recent call last)", - "Cell \u001b[0;32mIn[8], line 5\u001b[0m\n\u001b[1;32m 2\u001b[0m \u001b[38;5;28;01mfrom\u001b[39;00m \u001b[38;5;21;01mtime\u001b[39;00m \u001b[38;5;28;01mimport\u001b[39;00m sleep\n\u001b[1;32m 4\u001b[0m vis \u001b[38;5;241m=\u001b[39m show(mdp, save_and_embed\u001b[38;5;241m=\u001b[39m\u001b[38;5;28;01mTrue\u001b[39;00m, layout\u001b[38;5;241m=\u001b[39mLayout(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mlayouts/monty.json\u001b[39m\u001b[38;5;124m\"\u001b[39m))\n\u001b[0;32m----> 5\u001b[0m \u001b[43mvis\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mshow_path\u001b[49m(path)\n\u001b[1;32m 6\u001b[0m \u001b[38;5;28;01mfor\u001b[39;00m state \u001b[38;5;129;01min\u001b[39;00m path:\n\u001b[1;32m 7\u001b[0m vis\u001b[38;5;241m.\u001b[39mhighlight_state(state, color\u001b[38;5;241m=\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mred\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n", - "\u001b[0;31mAttributeError\u001b[0m: 'Visualization' object has no attribute 'show_path'" - ] + "cell_type": "code", + "execution_count": null, + "id": "0f6fe7f4-cc9e-4c1d-9850-3799ca47a903", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "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": "3.12.3" } - ], - "source": [ - "from stormvogel.show import show\n", - "from time import sleep\n", - "\n", - "vis = show(mdp, save_and_embed=True, layout=Layout(\"layouts/monty.json\"))\n", - "vis.show_path(path)\n", - "for state in path:\n", - " vis.highlight_state(state, color=\"red\")\n", - " sleep(1)\n", - " # TODO should crash\n", - " " - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "0f6fe7f4-cc9e-4c1d-9850-3799ca47a903", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "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": "3.12.3" - } - }, - "nbformat": 4, - "nbformat_minor": 5 + "nbformat": 4, + "nbformat_minor": 5 } diff --git a/docs/getting_started/07_pomdp.ipynb b/docs/getting_started/07_pomdp.ipynb index feb267f..299f9e5 100644 --- a/docs/getting_started/07_pomdp.ipynb +++ b/docs/getting_started/07_pomdp.ipynb @@ -1,335 +1,335 @@ { - "cells": [ - { - "cell_type": "code", - "execution_count": 1, - "id": "8013f1f2-f771-43b4-ba2a-c584d05d21b2", - "metadata": {}, - "outputs": [], - "source": [ - "import stormvogel.model\n", - "from stormvogel.layout import Layout\n", - "from stormvogel.show import show" - ] - }, - { - "cell_type": "markdown", - "id": "dbc502e0-a2f6-49c8-b9b1-638666906e27", - "metadata": {}, - "source": [ - "## What is a POMDP?\n", - "A Partially Observed MDP is an MDP where you do not know what state you are currently in.\n", - "You can obtain information about what state you might be in using Observations.\n", - "In a POMDP (every?) state has an Observation. The policy can use the current and previous observations for the decision making.\n", - "\n", - "The scenario is as follows:You are dropped in some city, but you are not sure which city. By walking and seeing landmarks, you learn where you are." - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "887c917f-6df3-4379-b1e0-9471d76b0180", - "metadata": {}, - "outputs": [ + "cells": [ + { + "cell_type": "code", + "execution_count": 1, + "id": "8013f1f2-f771-43b4-ba2a-c584d05d21b2", + "metadata": {}, + "outputs": [], + "source": [ + "import stormvogel.model\n", + "from stormvogel.layout import Layout\n", + "from stormvogel.show import show" + ] + }, + { + "cell_type": "markdown", + "id": "dbc502e0-a2f6-49c8-b9b1-638666906e27", + "metadata": {}, + "source": [ + "## What is a POMDP?\n", + "A Partially Observed MDP is an MDP where you do not know what state you are currently in.\n", + "You can obtain information about what state you might be in using Observations.\n", + "In a POMDP (every?) state has an Observation. The policy can use the current and previous observations for the decision making.\n", + "\n", + "The scenario is as follows:You are dropped in some city, but you are not sure which city. By walking and seeing landmarks, you learn where you are." + ] + }, { - "data": { - "text/html": [ - "\n", - " " + "cell_type": "code", + "execution_count": 2, + "id": "887c917f-6df3-4379-b1e0-9471d76b0180", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } ], - "text/plain": [ - "" + "source": [ + "pomdp = stormvogel.model.new_pomdp(create_initial_state=False)\n", + "\n", + "nijmegen = pomdp.new_state(\"nijmegen\")\n", + "eindhoven = pomdp.new_state(\"eindhoven\")\n", + "aachen = pomdp.new_state(\"aachen\")\n", + "cities = [nijmegen, eindhoven, aachen]\n", + "\n", + "saw_nijmegen = pomdp.new_state(\"saw nijmegen\")\n", + "saw_eindhoven = pomdp.new_state(\"saw eindhoven\")\n", + "saw_aachen = pomdp.new_state(\"saw aachen\")\n", + "saw_cities = [saw_nijmegen, saw_eindhoven, saw_aachen]\n", + "\n", + "walk = pomdp.new_action(\"walk\")\n", + "stay_put = pomdp.new_action(\"stay put\")\n", + "\n", + "for city, saw_city in zip(cities, saw_cities):\n", + " city.set_transitions([\n", + " (walk, saw_city),\n", + " (stay_put, city)\n", + " ])\n", + " saw_city.set_transitions([(1, city)])\n", + "\n", + "# We add an observation to the saw states. The observed states are marked with an O.\n", + "for saw_city in saw_cities:\n", + " saw_city.set_observation(saw_city.id)\n", + "\n", + "vis = show(pomdp, save_and_embed=True)" ] - }, - "metadata": {}, - "output_type": "display_data" + }, + { + "cell_type": "code", + "execution_count": null, + "id": "816a3bb7-449a-4f75-98b6-ea8ee3ff046f", + "metadata": {}, + "outputs": [], + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "235724b2-5f07-4f0f-a9c7-290d95a3781c", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "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": "3.12.3" } - ], - "source": [ - "pomdp = stormvogel.model.new_pomdp(create_initial_state=False)\n", - "\n", - "nijmegen = pomdp.new_state(\"nijmegen\")\n", - "eindhoven = pomdp.new_state(\"eindhoven\")\n", - "aachen = pomdp.new_state(\"aachen\")\n", - "cities = [nijmegen, eindhoven, aachen]\n", - "\n", - "saw_nijmegen = pomdp.new_state(\"saw nijmegen\")\n", - "saw_eindhoven = pomdp.new_state(\"saw eindhoven\")\n", - "saw_aachen = pomdp.new_state(\"saw aachen\")\n", - "saw_cities = [saw_nijmegen, saw_eindhoven, saw_aachen]\n", - "\n", - "walk = pomdp.new_action(\"walk\")\n", - "stay_put = pomdp.new_action(\"stay put\")\n", - "\n", - "for city, saw_city in zip(cities, saw_cities):\n", - " city.set_transitions([\n", - " (walk, saw_city),\n", - " (stay_put, city)\n", - " ])\n", - " saw_city.set_transitions([(1, city)])\n", - "\n", - "# We add an observation to the saw states. The observed states are marked with an O.\n", - "for saw_city in saw_cities:\n", - " saw_city.set_observation(saw_city.id)\n", - "\n", - "vis = show(pomdp, save_and_embed=True)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "816a3bb7-449a-4f75-98b6-ea8ee3ff046f", - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "235724b2-5f07-4f0f-a9c7-290d95a3781c", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "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": "3.12.3" - } - }, - "nbformat": 4, - "nbformat_minor": 5 + "nbformat": 4, + "nbformat_minor": 5 } diff --git a/docs/getting_started/08_pomdp-maze.ipynb b/docs/getting_started/08_pomdp-maze.ipynb index a2b2dd8..bfa2b68 100644 --- a/docs/getting_started/08_pomdp-maze.ipynb +++ b/docs/getting_started/08_pomdp-maze.ipynb @@ -1,900 +1,900 @@ { - "cells": [ - { - "cell_type": "markdown", - "id": "6ab964ed-c2a0-4979-beb1-b780cc47bc35", - "metadata": {}, - "source": [ - "# POMDP Mazes\n", - "In this notebook, we will show off the power of POMDPs using mazes.\n", - "The idea is that you start on some tile, without knowing which tile. You can walk in four directions. If you run into a wall, you observe this. Based on this you can determine where in the maze you are and escape." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "8a36e98c-af1c-46be-852c-a966558a92ab", - "metadata": {}, - "outputs": [], - "source": [ - "import stormvogel.model\n", - "from stormvogel.model import EmptyAction\n", - "from stormvogel.layout import Layout\n", - "from stormvogel.show import show" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "id": "2f4d4394-8a2a-424e-b16e-8ed202bdf493", - "metadata": {}, - "outputs": [], - "source": [ - "# HERE FOR DEVELOPMENT, MOVE TO LIB\n", - "import matplotlib\n", - "from matplotlib import pyplot as plt\n", - "\n", - "WALL_SYM = \"X\"\n", - "EMPTY_SYM = \".\"\n", - "EXIT_SYM = \"O\"\n", - "\n", - "def parse_level(level):\n", - " d = {EXIT_SYM: 2, WALL_SYM: 1, EMPTY_SYM: 0}\n", - " level_list = list(filter(lambda x: x != \"\", level.splitlines()))\n", - " level_list = list(map(\n", - " lambda x: list(map(lambda y: d[y], x)), \n", - " level_list))\n", - " width = len(level_list[0])\n", - " height = len(level_list)\n", - " return (level_list, width, height)\n", - "\n", - "\n", - "def show_grid(level, hor_size):\n", - " # https://stackoverflow.com/questions/19586828/drawing-grid-pattern-in-matplotlib\n", - " level_list, width, height = parse_level(level)\n", - " \n", - " # make a figure + axes\n", - " fig, ax = plt.subplots(1, 1, tight_layout=True)\n", - " fig.set_size_inches(hor_size, hor_size)\n", - " # make color map\n", - " my_cmap = matplotlib.colors.ListedColormap(['#8FCB9B', '#8F8073', '#0096FF'])\n", - " # draw the grid\n", - " for x in range(width + 1):\n", - " ax.axvline(x, lw=2, color='k', zorder=5)\n", - " for y in range(height + 1):\n", - " ax.axhline(y, lw=2, color='k', zorder=5)\n", - " \n", - " # draw the boxes\n", - " ax.imshow(level_list, interpolation='none', cmap=my_cmap, extent=[0, width, 0, height], zorder=0, )\n", - " # turn off the axis labels\n", - " ax.axis('off')\n", - "\n", - "END = 4\n", - "EXIT = 2\n", - "WALL = 1\n", - "WALKABLE = 0\n", - "OUT_OF_BOUNDS = -1\n", - "UNKNOWN = 3\n", - "\n", - "LEFT = \"←\"\n", - "RIGHT = \"→\"\n", - "UP = \"↑\"\n", - "DOWN = \"↓\"\n", - "\n", - "def out_of_bounds(x, y, width, height):\n", - " return x < 0 or y < 0 or x > width-1 or y > height -1\n", - "\n", - "def direction_result(x: int, y: int, direction: str, level_list: list, width: int, height: int):\n", - " d = {UP: (0,-1), RIGHT: (1,0), DOWN: (0,1), LEFT:(-1,0)}\n", - " res_x = x + d[direction][0]\n", - " res_y = y + d[direction][1]\n", - " if out_of_bounds(res_x,res_y,width,height):\n", - " return ((res_x,res_y), OUT_OF_BOUNDS)\n", - " if level_list[res_y][res_x] == WALL:\n", - " return ((x,y), WALL)\n", - " else:\n", - " return ((res_x, res_y), WALKABLE)\n", - "\n", - "def grid_world(level:list, position_scalar:int=200):\n", - " \"\"\"Create a grid world with an actor.\"\"\"\n", - " level_list, width, height = parse_level(level)\n", - " pomdp = stormvogel.model.new_pomdp(create_initial_state=False)\n", - " reward_model = pomdp.add_rewards(\"\")\n", - " \n", - " escaped = pomdp.new_state(\"escaped\")\n", - " escaped.set_observation(END)\n", - " #reward_model.set(escaped, 0)\n", - " \n", - " grid = [[None for x in range(width)] for y in range(height)]\n", - " for x in range(width):\n", - " for y in range(height):\n", - " if level_list[y][x] == WALKABLE:\n", - " grid[y][x] = pomdp.new_state([\"t\", f\"({x},{y})\"])\n", - " grid[y][x].set_observation(UNKNOWN)\n", - " #reward_model.set_state_action_reward(grid[y][x], -1)\n", - " if level_list[y][x] == EXIT:\n", - " grid[y][x] = pomdp.new_state([\"e\", f\"({x},{y})\"])\n", - " grid[y][x].set_observation(UNKNOWN)\n", - " #reward_model.set_state_action_reward(grid[y][x], 100)\n", - " grid[y][x].add_transitions([(1, escaped)])\n", - " dirs = {d: pomdp.new_action(d) for d in [UP, DOWN, LEFT, RIGHT]}\n", - " positions = {}\n", - " # Add movement\n", - " for x in range(width):\n", - " for y in range(height):\n", - " if level_list[y][x] == WALKABLE:\n", - " for d,action in dirs.items():\n", - " positions[str(grid[y][x].id)] = {\"x\": x * position_scalar, \"y\": y * position_scalar}\n", - " ((res_x, res_y), observation) = direction_result(x,y,d,level_list,width,height)\n", - "\n", - " \n", - " \n", - " if not observation == OUT_OF_BOUNDS:\n", - " took_dir = pomdp.new_state([d, f\"({x},{y})\"])\n", - " grid[y][x].add_transitions([(action, took_dir)])\n", - " #reward_model.set_state_action_reward(grid[y][x], action, -1)\n", - " # print(took_dir)\n", - " took_dir.add_transitions([(1, grid[res_y][res_x])])\n", - " reward_model.set_state_action_reward(took_dir, EmptyAction, -1)\n", - " took_dir.set_observation(observation)\n", - " pomdp.add_self_loops()\n", - " reward_model.set_unset_rewards(0)\n", - " return pomdp, positions" - ] - }, - { - "cell_type": "markdown", - "id": "6e428cc8-ed8b-4830-a1ae-eea45b663642", - "metadata": {}, - "source": [ - "First, we define a simple maze in ASSCI. 'X' are walls, '.' are walkable tiles, 'O' is the exit. We visualize it as a grid where walls are brown, walkable tiles are green, and the exit is blue." - ] - }, - { - "cell_type": "code", - "execution_count": 3, - "id": "ebdc5973-ff3f-4056-9593-511837966101", - "metadata": {}, - "outputs": [ + "cells": [ { - "data": { - "image/png": "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", - "text/plain": [ - "
" + "cell_type": "markdown", + "id": "6ab964ed-c2a0-4979-beb1-b780cc47bc35", + "metadata": {}, + "source": [ + "# POMDP Mazes\n", + "In this notebook, we will show off the power of POMDPs using mazes.\n", + "The idea is that you start on some tile, without knowing which tile. You can walk in four directions. If you run into a wall, you observe this. Based on this you can determine where in the maze you are and escape." ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "LEVEL =\"\"\"\n", - "XXXXX\n", - "X...X\n", - "XOX.X\n", - "XXXXX\n", - "\"\"\"\n", - "\n", - "show_grid(LEVEL, hor_size=4)" - ] - }, - { - "cell_type": "markdown", - "id": "150834b0-8bbf-4e10-bd76-9a53a6930524", - "metadata": {}, - "source": [ - "Now we create a POMDP from the level. Can you see how it corresponds to the maze?" - ] - }, - { - "cell_type": "code", - "execution_count": 4, - "id": "d0400922-7b90-43c5-a01e-cc051089521d", - "metadata": {}, - "outputs": [ + }, { - "data": { - "text/html": [ - "\n", - " " - ], - "text/plain": [ - "" + "cell_type": "code", + "execution_count": 1, + "id": "8a36e98c-af1c-46be-852c-a966558a92ab", + "metadata": {}, + "outputs": [], + "source": [ + "import stormvogel.model\n", + "from stormvogel.model import EmptyAction\n", + "from stormvogel.layout import Layout\n", + "from stormvogel.show import show" ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "pomdp, positions = grid_world(LEVEL)\n", - "\n", - "vis = show(pomdp, layout=Layout(\"layouts/grid.json\"), separate_labels=[\"t\", \"e\"], save_and_embed=True)" - ] - }, - { - "cell_type": "markdown", - "id": "a40aedf2-5973-4fb6-8bed-6146dd6db7ca", - "metadata": {}, - "source": [ - "Some things to keep in mind.\n", - "* The tiles in the grid that aren't walls have a state t,(x,y)\n", - "* From such a tile, you can try to go left, right, top or bottom (these are actions)\n", - "* After taking an action, you go to a state with an observation (symbol ⊙). After this you proceed to another tile state.\n", - " + If you try to go into a wall, you observe that you hit a wall (1)\n", - " + If you do not hit a wall, you observe this as well (0)\n", - "* Every state has a reward according to our reward model (euro sign). Solving the maze will give you 100 reward but taking a step will cost 1.\n", - "\n", - "For example, if you try to go left in tile (3,2), you observe that you hit a wall and you go back to (3,2). However, if you try to go up, you observe that you don't hit a wall and proceed to (3,1)." - ] - }, - { - "cell_type": "code", - "execution_count": 7, - "id": "8d5b0e8e-47db-4dfb-a533-a8181ec04751", - "metadata": {}, - "outputs": [ + }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "-------------------------------------------------------------- \n", - "Model type: \tPOMDP (sparse)\n", - "States: \t22\n", - "Transitions: \t34\n", - "Choices: \t34\n", - "Observations: \t5\n", - "Reward Models: (default)\n", - "State Labels: \t12 labels\n", - " * escaped -> 1 item(s)\n", - " * (1,2) -> 1 item(s)\n", - " * ↓ -> 4 item(s)\n", - " * (3,1) -> 5 item(s)\n", - " * (3,2) -> 5 item(s)\n", - " * (2,1) -> 5 item(s)\n", - " * ← -> 4 item(s)\n", - " * (1,1) -> 5 item(s)\n", - " * → -> 4 item(s)\n", - " * e -> 1 item(s)\n", - " * ↑ -> 4 item(s)\n", - " * t -> 4 item(s)\n", - "Choice Labels: \t4 labels\n", - " * → -> 4 item(s)\n", - " * ↓ -> 4 item(s)\n", - " * ↑ -> 4 item(s)\n", - " * ← -> 4 item(s)\n", - "-------------------------------------------------------------- \n", - "\n" - ] + "cell_type": "code", + "execution_count": 2, + "id": "2f4d4394-8a2a-424e-b16e-8ed202bdf493", + "metadata": {}, + "outputs": [], + "source": [ + "# HERE FOR DEVELOPMENT, MOVE TO LIB\n", + "import matplotlib\n", + "from matplotlib import pyplot as plt\n", + "\n", + "WALL_SYM = \"X\"\n", + "EMPTY_SYM = \".\"\n", + "EXIT_SYM = \"O\"\n", + "\n", + "def parse_level(level):\n", + " d = {EXIT_SYM: 2, WALL_SYM: 1, EMPTY_SYM: 0}\n", + " level_list = list(filter(lambda x: x != \"\", level.splitlines()))\n", + " level_list = list(map(\n", + " lambda x: list(map(lambda y: d[y], x)), \n", + " level_list))\n", + " width = len(level_list[0])\n", + " height = len(level_list)\n", + " return (level_list, width, height)\n", + "\n", + "\n", + "def show_grid(level, hor_size):\n", + " # https://stackoverflow.com/questions/19586828/drawing-grid-pattern-in-matplotlib\n", + " level_list, width, height = parse_level(level)\n", + " \n", + " # make a figure + axes\n", + " fig, ax = plt.subplots(1, 1, tight_layout=True)\n", + " fig.set_size_inches(hor_size, hor_size)\n", + " # make color map\n", + " my_cmap = matplotlib.colors.ListedColormap(['#8FCB9B', '#8F8073', '#0096FF'])\n", + " # draw the grid\n", + " for x in range(width + 1):\n", + " ax.axvline(x, lw=2, color='k', zorder=5)\n", + " for y in range(height + 1):\n", + " ax.axhline(y, lw=2, color='k', zorder=5)\n", + " \n", + " # draw the boxes\n", + " ax.imshow(level_list, interpolation='none', cmap=my_cmap, extent=[0, width, 0, height], zorder=0, )\n", + " # turn off the axis labels\n", + " ax.axis('off')\n", + "\n", + "END = 4\n", + "EXIT = 2\n", + "WALL = 1\n", + "WALKABLE = 0\n", + "OUT_OF_BOUNDS = -1\n", + "UNKNOWN = 3\n", + "\n", + "LEFT = \"\u2190\"\n", + "RIGHT = \"\u2192\"\n", + "UP = \"\u2191\"\n", + "DOWN = \"\u2193\"\n", + "\n", + "def out_of_bounds(x, y, width, height):\n", + " return x < 0 or y < 0 or x > width-1 or y > height -1\n", + "\n", + "def direction_result(x: int, y: int, direction: str, level_list: list, width: int, height: int):\n", + " d = {UP: (0,-1), RIGHT: (1,0), DOWN: (0,1), LEFT:(-1,0)}\n", + " res_x = x + d[direction][0]\n", + " res_y = y + d[direction][1]\n", + " if out_of_bounds(res_x,res_y,width,height):\n", + " return ((res_x,res_y), OUT_OF_BOUNDS)\n", + " if level_list[res_y][res_x] == WALL:\n", + " return ((x,y), WALL)\n", + " else:\n", + " return ((res_x, res_y), WALKABLE)\n", + "\n", + "def grid_world(level:list, position_scalar:int=200):\n", + " \"\"\"Create a grid world with an actor.\"\"\"\n", + " level_list, width, height = parse_level(level)\n", + " pomdp = stormvogel.model.new_pomdp(create_initial_state=False)\n", + " reward_model = pomdp.add_rewards(\"\")\n", + " \n", + " escaped = pomdp.new_state(\"escaped\")\n", + " escaped.set_observation(END)\n", + " #reward_model.set(escaped, 0)\n", + " \n", + " grid = [[None for x in range(width)] for y in range(height)]\n", + " for x in range(width):\n", + " for y in range(height):\n", + " if level_list[y][x] == WALKABLE:\n", + " grid[y][x] = pomdp.new_state([\"t\", f\"({x},{y})\"])\n", + " grid[y][x].set_observation(UNKNOWN)\n", + " #reward_model.set_state_action_reward(grid[y][x], -1)\n", + " if level_list[y][x] == EXIT:\n", + " grid[y][x] = pomdp.new_state([\"e\", f\"({x},{y})\"])\n", + " grid[y][x].set_observation(UNKNOWN)\n", + " #reward_model.set_state_action_reward(grid[y][x], 100)\n", + " grid[y][x].add_transitions([(1, escaped)])\n", + " dirs = {d: pomdp.new_action(d) for d in [UP, DOWN, LEFT, RIGHT]}\n", + " positions = {}\n", + " # Add movement\n", + " for x in range(width):\n", + " for y in range(height):\n", + " if level_list[y][x] == WALKABLE:\n", + " for d,action in dirs.items():\n", + " positions[str(grid[y][x].id)] = {\"x\": x * position_scalar, \"y\": y * position_scalar}\n", + " ((res_x, res_y), observation) = direction_result(x,y,d,level_list,width,height)\n", + "\n", + " \n", + " \n", + " if not observation == OUT_OF_BOUNDS:\n", + " took_dir = pomdp.new_state([d, f\"({x},{y})\"])\n", + " grid[y][x].add_transitions([(action, took_dir)])\n", + " #reward_model.set_state_action_reward(grid[y][x], action, -1)\n", + " # print(took_dir)\n", + " took_dir.add_transitions([(1, grid[res_y][res_x])])\n", + " reward_model.set_state_action_reward(took_dir, EmptyAction, -1)\n", + " took_dir.set_observation(observation)\n", + " pomdp.add_self_loops()\n", + " reward_model.set_unset_rewards(0)\n", + " return pomdp, positions" + ] }, { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "e082253a591e4b1aa4a6a1b8dd15b5d7", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Output()" + "cell_type": "markdown", + "id": "6e428cc8-ed8b-4830-a1ae-eea45b663642", + "metadata": {}, + "source": [ + "First, we define a simple maze in ASSCI. 'X' are walls, '.' are walkable tiles, 'O' is the exit. We visualize it as a grid where walls are brown, walkable tiles are green, and the exit is blue." ] - }, - "metadata": {}, - "output_type": "display_data" }, { - "data": { - "text/html": [ - "" + "cell_type": "code", + "execution_count": 3, + "id": "ebdc5973-ff3f-4056-9593-511837966101", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } ], - "text/plain": [ - "" + "source": [ + "LEVEL =\"\"\"\n", + "XXXXX\n", + "X...X\n", + "XOX.X\n", + "XXXXX\n", + "\"\"\"\n", + "\n", + "show_grid(LEVEL, hor_size=4)" + ] + }, + { + "cell_type": "markdown", + "id": "150834b0-8bbf-4e10-bd76-9a53a6930524", + "metadata": {}, + "source": [ + "Now we create a POMDP from the level. Can you see how it corresponds to the maze?" ] - }, - "metadata": {}, - "output_type": "display_data" }, { - "data": { - "text/html": [ - "" + "cell_type": "code", + "execution_count": 4, + "id": "d0400922-7b90-43c5-a01e-cc051089521d", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } ], - "text/plain": [ - "" + "source": [ + "pomdp, positions = grid_world(LEVEL)\n", + "\n", + "vis = show(pomdp, layout=Layout(\"layouts/grid.json\"), separate_labels=[\"t\", \"e\"], save_and_embed=True)" ] - }, - "metadata": {}, - "output_type": "display_data" }, { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "344d0554115e4dc381c93683abac404f", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Output()" + "cell_type": "markdown", + "id": "a40aedf2-5973-4fb6-8bed-6146dd6db7ca", + "metadata": {}, + "source": [ + "Some things to keep in mind.\n", + "* The tiles in the grid that aren't walls have a state t,(x,y)\n", + "* From such a tile, you can try to go left, right, top or bottom (these are actions)\n", + "* After taking an action, you go to a state with an observation (symbol \u2299). After this you proceed to another tile state.\n", + " + If you try to go into a wall, you observe that you hit a wall (1)\n", + " + If you do not hit a wall, you observe this as well (0)\n", + "* Every state has a reward according to our reward model (euro sign). Solving the maze will give you 100 reward but taking a step will cost 1.\n", + "\n", + "For example, if you try to go left in tile (3,2), you observe that you hit a wall and you go back to (3,2). However, if you try to go up, you observe that you don't hit a wall and proceed to (3,1)." ] - }, - "metadata": {}, - "output_type": "display_data" }, { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "5b90190eb6d74a98b10e97be81cb567e", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(Output(), Output()))" + "cell_type": "code", + "execution_count": 7, + "id": "8d5b0e8e-47db-4dfb-a533-a8181ec04751", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "-------------------------------------------------------------- \n", + "Model type: \tPOMDP (sparse)\n", + "States: \t22\n", + "Transitions: \t34\n", + "Choices: \t34\n", + "Observations: \t5\n", + "Reward Models: (default)\n", + "State Labels: \t12 labels\n", + " * escaped -> 1 item(s)\n", + " * (1,2) -> 1 item(s)\n", + " * \u2193 -> 4 item(s)\n", + " * (3,1) -> 5 item(s)\n", + " * (3,2) -> 5 item(s)\n", + " * (2,1) -> 5 item(s)\n", + " * \u2190 -> 4 item(s)\n", + " * (1,1) -> 5 item(s)\n", + " * \u2192 -> 4 item(s)\n", + " * e -> 1 item(s)\n", + " * \u2191 -> 4 item(s)\n", + " * t -> 4 item(s)\n", + "Choice Labels: \t4 labels\n", + " * \u2192 -> 4 item(s)\n", + " * \u2193 -> 4 item(s)\n", + " * \u2191 -> 4 item(s)\n", + " * \u2190 -> 4 item(s)\n", + "-------------------------------------------------------------- \n", + "\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "e082253a591e4b1aa4a6a1b8dd15b5d7", + "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": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "344d0554115e4dc381c93683abac404f", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Output()" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "5b90190eb6d74a98b10e97be81cb567e", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HBox(children=(Output(), Output()))" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "from stormvogel.mapping import stormvogel_to_stormpy, stormpy_to_stormvogel\n", + "\n", + "stormpy_model = stormvogel_to_stormpy(pomdp)\n", + "print(stormpy_model)\n", + "pomdp2 = stormpy_to_stormvogel(stormpy_model)\n", + "vis2 = show(pomdp2, layout=Layout(\"layouts/grid.json\"), separate_labels=[\"t\", \"e\"], show_editor=True)\n", + "\n", + "\n", + "# TODO use the stormvogel model checking instead!\n", + "# TODO fix the layout once we switch to sets for displaying labels" ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "from stormvogel.mapping import stormvogel_to_stormpy, stormpy_to_stormvogel\n", - "\n", - "stormpy_model = stormvogel_to_stormpy(pomdp)\n", - "print(stormpy_model)\n", - "pomdp2 = stormpy_to_stormvogel(stormpy_model)\n", - "vis2 = show(pomdp2, layout=Layout(\"layouts/grid.json\"), separate_labels=[\"t\", \"e\"], show_editor=True)\n", - "\n", - "\n", - "# TODO use the stormvogel model checking instead!\n", - "# TODO fix the layout once we switch to sets for displaying labels" - ] - }, - { - "cell_type": "code", - "execution_count": 6, - "id": "b1171d26-20f6-40e5-af57-721db56be040", - "metadata": {}, - "outputs": [ + }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "{Action(labels=frozenset()), Action(labels=frozenset({'↓'})), Action(labels=frozenset({'→'})), Action(labels=frozenset({'↑'})), Action(labels=frozenset({'←'}))}\n" - ] + "cell_type": "code", + "execution_count": 6, + "id": "b1171d26-20f6-40e5-af57-721db56be040", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{Action(labels=frozenset()), Action(labels=frozenset({'\u2193'})), Action(labels=frozenset({'\u2192'})), Action(labels=frozenset({'\u2191'})), Action(labels=frozenset({'\u2190'}))}\n" + ] + } + ], + "source": [ + "print(pomdp2.actions)\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "ea8bceb9-a0c5-49ee-9fb3-b03b0389fb9f", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "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": "3.12.3" } - ], - "source": [ - "print(pomdp2.actions)\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "ea8bceb9-a0c5-49ee-9fb3-b03b0389fb9f", - "metadata": {}, - "outputs": [], - "source": [] - } - ], - "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": "3.12.3" - } - }, - "nbformat": 4, - "nbformat_minor": 5 + "nbformat": 4, + "nbformat_minor": 5 } diff --git a/docs/getting_started/die.html b/docs/getting_started/die.html index f7df5a8..7cc9d70 100644 --- a/docs/getting_started/die.html +++ b/docs/getting_started/die.html @@ -15,18 +15,18 @@ ></script> <style type="text/css"> #mynetwork { - + width: 800px; height: 600px; border: 1px solid lightgray; - + } </style> </head> <body> <div id="mynetwork"></div> <script type="text/javascript"> - + var nodes = new vis.DataSet([{ id: 0, label: `init`, group: "states" }, { id: 1, label: `rolled1`, group: "states" }, { id: 2, label: `rolled2`, group: "states" }, @@ -207,4 +207,4 @@ " border:none !important; allowfullscreen webkitallowfullscreen mozallowfullscreen - > \ No newline at end of file + > diff --git a/docs/getting_started/layouts/pinkgreen.json b/docs/getting_started/layouts/pinkgreen.json index 9c72242..9df8db3 100644 --- a/docs/getting_started/layouts/pinkgreen.json +++ b/docs/getting_started/layouts/pinkgreen.json @@ -153,4 +153,4 @@ "resultSymbol": "\u2606", "show_rewards": true } -} \ No newline at end of file +} diff --git a/docs/getting_started/lion.html b/docs/getting_started/lion.html index 6b04aff..49a84a7 100644 --- a/docs/getting_started/lion.html +++ b/docs/getting_started/lion.html @@ -15,18 +15,18 @@ ></script> <style type="text/css"> #mynetwork { - + width: 687px; height: 519px; border: 1px solid lightgray; - + } </style> </head> <body> <div id="mynetwork"></div> <script type="text/javascript"> - + var nodes = new vis.DataSet([{ id: 0, label: `init`, group: "states", x: -253, y: -205 }, { id: 1, label: `full :D`, group: "states", x: 18, y: 193 }, { id: 2, label: `satisfied :)`, group: "states", x: -27, y: -59 }, @@ -346,4 +346,4 @@ " border:none !important; allowfullscreen webkitallowfullscreen mozallowfullscreen - > \ No newline at end of file + > diff --git a/docs/getting_started/model.html b/docs/getting_started/model.html index 7526086..45aaf4b 100644 --- a/docs/getting_started/model.html +++ b/docs/getting_started/model.html @@ -19,11 +19,11 @@ ></script> <style type="text/css"> #mynetwork { - + width: 800px; height: 600px; border: 1px solid lightgray; - + } </style> </head> @@ -31,7 +31,7 @@ <div id="mynetwork"></div> <script type="text/javascript"> <<<<<<< HEAD - + var nodes = new vis.DataSet([{ id: 0, label: `escaped ʘ 4`, group: "states", x: -297, y: 598 }, { id: 1, label: `t,(1,1) @@ -664,4 +664,4 @@ " border:none !important; allowfullscreen webkitallowfullscreen mozallowfullscreen - > \ No newline at end of file + > diff --git a/docs/getting_started/prism.html b/docs/getting_started/prism.html index 4b4a5af..8d3def1 100644 --- a/docs/getting_started/prism.html +++ b/docs/getting_started/prism.html @@ -15,18 +15,18 @@ ></script> <style type="text/css"> #mynetwork { - + width: 800px; height: 600px; border: 1px solid lightgray; - + } </style> </head> <body> <div id="mynetwork"></div> <script type="text/javascript"> - + var nodes = new vis.DataSet([{ id: 0, label: `nextnand,init € : 0.0 ☆ 113/152`, group: "states" }, @@ -965,4 +965,4 @@ " border:none !important; allowfullscreen webkitallowfullscreen mozallowfullscreen - > \ No newline at end of file + > diff --git a/docs/getting_started/study.html b/docs/getting_started/study.html index 8801a32..4e3c237 100644 --- a/docs/getting_started/study.html +++ b/docs/getting_started/study.html @@ -15,18 +15,18 @@ ></script> <style type="text/css"> #mynetwork { - + width: 800px; height: 600px; border: 1px solid lightgray; - + } </style> </head> <body> <div id="mynetwork"></div> <script type="text/javascript"> - + var nodes = new vis.DataSet([{ id: 0, label: `init`, group: "states", x: -15, y: -210 }, { id: 1, label: `studied`, group: "states", x: -83, y: -4 }, { id: 2, label: `didn't study`, group: "states", x: 72, y: -22 }, @@ -244,4 +244,4 @@ " border:none !important; allowfullscreen webkitallowfullscreen mozallowfullscreen - > \ No newline at end of file + > diff --git a/stormvogel/layout_editor.py b/stormvogel/layout_editor.py index 196bb51..30faba6 100644 --- a/stormvogel/layout_editor.py +++ b/stormvogel/layout_editor.py @@ -49,36 +49,36 @@ def __warn_failed_positions_save(self): If you cannot get the server to work, set stormvogel.communication_server.enable_server to false and re-run. This will speed up stormvogel and ignore this message, but it means that you cannot store positions in layout files. Please contact the stormvogel developpers if you keep running into issues.""") - + def set_current_vis_node_positions_in_layout(self): """Try to save the positions of the nodes in the graph to the layout. The user is informed if this fails.""" with self.debug_output: logging.debug(f"Status of vis {self.vis}") if self.vis is not None: - with self.output: - if stormvogel.communication_server.server is None: + with self.output: + if stormvogel.communication_server.server is None: + with self.debug_output: + logging.info( + "Node positions won't be saved because the server is disabled." + ) + with self.output: + print( + "Node positions won't be saved because the server is disabled." + ) + else: + try: + positions = self.vis.get_positions() with self.debug_output: - logging.info( - "Node positions won't be saved because the server is disabled." + logging.debug(positions) + self.layout.layout["positions"] = positions + except TimeoutError: + with self.debug_output: + logging.warning( + "Failed to save node positions in layout file." ) with self.output: - print( - "Node positions won't be saved because the server is disabled." - ) - else: - try: - positions = self.vis.get_positions() - with self.debug_output: - logging.debug(positions) - self.layout.layout["positions"] = positions - except TimeoutError: - with self.debug_output: - logging.warning( - "Failed to save node positions in layout file." - ) - with self.output: - self.__warn_failed_positions_save() + self.__warn_failed_positions_save() def process_save_button(self): if self.layout.layout["saving"]["save_button"]: diff --git a/stormvogel/show.py b/stormvogel/show.py index af4d7bf..1907eac 100644 --- a/stormvogel/show.py +++ b/stormvogel/show.py @@ -35,11 +35,10 @@ def show( """ if layout is None: layout = stormvogel.layout.DEFAULT() - do_init_server = ( # We only need to start the server if we want to have the layout editor. - show_editor - and stormvogel.communication_server.enable_server + do_init_server = ( # We only need to start the server if we want to have the layout editor. + show_editor and stormvogel.communication_server.enable_server ) - #do_display = not show_editor + # do_display = not show_editor vis = stormvogel.visualization.Visualization( model=model, name=name, @@ -52,14 +51,14 @@ def show( do_init_server=do_init_server, ) vis.show() - if show_editor: + if show_editor: e = stormvogel.layout_editor.LayoutEditor( layout, vis, do_display=False, debug_output=debug_output ) e.show() box = widgets.HBox(children=[vis.output, e.output]) ipd.display(box) - else: # Unfortunately, the sphinx docs only work if we save the html as a file and embed. + else: # Unfortunately, the sphinx docs only work if we save the html as a file and embed. iframe = vis.nt.generate_iframe() with open(name + ".html", "w") as f: f.write(iframe) diff --git a/stormvogel/visjs.py b/stormvogel/visjs.py index 09be351..680edb1 100644 --- a/stormvogel/visjs.py +++ b/stormvogel/visjs.py @@ -1,6 +1,5 @@ """Our own Python bindings to the vis.js library in JavaScript.""" -from typing import Tuple import IPython.display as ipd import ipywidgets as widgets import html @@ -12,9 +11,8 @@ import string import logging + spam: widgets.Output = widgets.Output() -from collections import namedtuple -Node = namedtuple("Node", "id label group") class Network(stormvogel.displayable.Displayable): @@ -29,7 +27,7 @@ def __init__( do_display: bool = True, debug_output: widgets.Output = widgets.Output(), do_init_server: bool = True, - positions: dict[str, dict[str, int]] | None = None + positions: dict[str, dict[str, int]] | None = None, ) -> None: """Display a visjs network using IPython. The network can display by itself or you can specify an Output widget in which it should be displayed. @@ -55,7 +53,7 @@ def __init__( self.server: stormvogel.communication_server.CommunicationServer = ( stormvogel.communication_server.initialize_server() ) - self.positions: dict[str, dict[str, int]] + self.positions: dict[str, dict[str, int]] if positions is None: self.positions = {} else: @@ -116,9 +114,7 @@ def add_node( if group is not None: current += f', group: "{group}"' if self.positions is not None and str(id) in self.positions: - current += ( - f', x: {self.positions[str(id)]["x"]}, y: {self.positions[str(id)]["y"]}' - ) + current += f', x: {self.positions[str(id)]["x"]}, y: {self.positions[str(id)]["y"]}' if self.new_nodes_hidden and id != self.initial_node_id: current += ", hidden: true" current += " },\n" diff --git a/stormvogel/visualization.py b/stormvogel/visualization.py index 2b71948..42f24e5 100644 --- a/stormvogel/visualization.py +++ b/stormvogel/visualization.py @@ -94,7 +94,7 @@ def __create_nt(self) -> None: debug_output=self.debug_output, do_display=False, do_init_server=self.do_init_server, - positions= self.layout.layout["positions"] + positions=self.layout.layout["positions"], ) def show(self) -> None: diff --git a/tests/saved_test_layout.json b/tests/saved_test_layout.json index c3802e7..ef74d4a 100644 --- a/tests/saved_test_layout.json +++ b/tests/saved_test_layout.json @@ -118,4 +118,4 @@ "init": { "color": "TEST_COLOR" } -} \ No newline at end of file +} diff --git a/tests/test_mapping.py b/tests/test_mapping.py index acf0fe9..f9b549b 100644 --- a/tests/test_mapping.py +++ b/tests/test_mapping.py @@ -139,6 +139,7 @@ def test_stormpy_to_stormvogel_and_back_mdp(): assert sparse_equal(stormpy_mdp, new_stormpy_mdp) + def test_stormvogel_to_stormpy_and_back_mdp(): # we test it for monty hall mdp stormvogel_mdp = examples.monty_hall.create_monty_hall_mdp() @@ -230,7 +231,6 @@ def test_stormpy_to_stormvogel_and_back_pomdp(): assert sparse_equal(stormpy_pomdp, new_stormpy_pomdp) - def test_stormvogel_to_stormpy_and_back_ma(): # we create a stormpy representation of an example ma stormvogel_ma = examples.simple_ma.create_simple_ma() @@ -254,4 +254,3 @@ def test_stormpy_to_stormvogel_and_back_ma(): # print(new_stormpy_ma) assert sparse_equal(stormpy_ma, new_stormpy_ma) - diff --git a/tests/test_simulator.py b/tests/test_simulator.py index 5d827d3..9d0d031 100644 --- a/tests/test_simulator.py +++ b/tests/test_simulator.py @@ -104,6 +104,7 @@ def scheduler(state: stormvogel.model.State) -> stormvogel.model.Action: assert partial_model == other_mdp + # TODO Pim could you also finish this test? :) # def test_simulate_path(): # # we make the nuclear fusion ctmc and run simulate path with it diff --git a/tests/test_visualization.py b/tests/test_visualization.py index 1a0cec9..f23fbd7 100644 --- a/tests/test_visualization.py +++ b/tests/test_visualization.py @@ -39,18 +39,15 @@ def test_show(mocker): debug_output=vis.debug_output, do_display=False, do_init_server=vis.do_init_server, - positions= vis.layout.layout["positions"] + positions=vis.layout.layout["positions"], ) - MockNetwork.add_node.assert_any_call( - 0, label="init", group="states" - ) # type: ignore - MockNetwork.add_node.assert_any_call( - 1, label="one", group="states" - ) # type: ignore + MockNetwork.add_node.assert_any_call(0, label="init", group="states") # type: ignore + MockNetwork.add_node.assert_any_call(1, label="one", group="states") # type: ignore assert MockNetwork.add_node.call_count == 2 MockNetwork.add_edge.assert_any_call(0, 1, label="1") assert MockNetwork.add_edge.call_count == 1 + def test_rewards(mocker): MockNetwork = boilerplate(mocker) model, one, init = simple_model() @@ -61,9 +58,7 @@ def test_rewards(mocker): model.get_rewards("HIHI").set_state_reward(one, 42) vis = Visualization(model=model) vis.show() - MockNetwork.add_node.assert_any_call( - 0, label="init", group="states" - ) # type: ignore + MockNetwork.add_node.assert_any_call(0, label="init", group="states") # type: ignore MockNetwork.add_node.assert_any_call( 1, label="one\n€\tLOL: 37\tHIHI: 42", group="states" ) # type: ignore @@ -80,12 +75,8 @@ def test_results_count(mocker): vis = Visualization(model=model, result=result) vis.show() RES_SYM = vis.layout.layout["state_properties"]["result_symbol"] - MockNetwork.add_node.assert_any_call( - 0, label=f"init\n{RES_SYM} 69", group="states" - ) # type: ignore - MockNetwork.add_node.assert_any_call( - 1, label=f"one\n{RES_SYM} 12", group="states" - ) # type: ignore + MockNetwork.add_node.assert_any_call(0, label=f"init\n{RES_SYM} 69", group="states") # type: ignore + MockNetwork.add_node.assert_any_call(1, label=f"one\n{RES_SYM} 12", group="states") # type: ignore assert result.values == {0: 69, 1: 12} assert MockNetwork.add_node.call_count == 2 @@ -105,9 +96,7 @@ def test_results_scheduler(mocker): result = Result(model, [1, 2], scheduler) vis = Visualization(model=model, result=result) vis.show() - MockNetwork.add_node.assert_any_call( - id=10000000001, label="BAD", group="actions" - ) + MockNetwork.add_node.assert_any_call(id=10000000001, label="BAD", group="actions") MockNetwork.add_node.assert_any_call( id=10000000000, label="GOOD", group="scheduled_actions" )