From d44b23752ccb5750c3d929eda6d6d51e4a2a2f53 Mon Sep 17 00:00:00 2001 From: YouGuessedMyName Date: Thu, 5 Dec 2024 16:55:45 +0100 Subject: [PATCH] linter --- docs/getting_started/die.html | 8 +- docs/getting_started/die.ipynb | 26368 ++++++++-------- docs/getting_started/layouts/grid.json | 2 +- docs/getting_started/layouts/monty.json | 2 +- docs/getting_started/layouts/small_monty.json | 2 +- docs/getting_started/lion.html | 8 +- docs/getting_started/model.html | 8 +- .../naive_value_iteration.ipynb | 2784 +- docs/getting_started/pomdp-maze.ipynb | 748 +- docs/getting_started/pomdp.ipynb | 640 +- docs/getting_started/simulator.ipynb | 4492 +-- docs/getting_started/study.html | 8 +- docs/getting_started/study.ipynb | 26214 +++++++-------- stormvogel/mapping.py | 6 +- stormvogel/model.py | 42 +- stormvogel/visualization.py | 30 +- tests/saved_test_layout.json | 2 +- tests/test_mapping.py | 1 + tests/test_model_methods.py | 2 +- tests/test_simulator.py | 6 - tests/test_visualization.py | 1 + 21 files changed, 30701 insertions(+), 30673 deletions(-) diff --git a/docs/getting_started/die.html b/docs/getting_started/die.html index a63ae3d..241f70d 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/die.ipynb b/docs/getting_started/die.ipynb index fd92708..b82e775 100644 --- a/docs/getting_started/die.ipynb +++ b/docs/getting_started/die.ipynb @@ -1,13194 +1,13194 @@ { - "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, save_and_embed=True, 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, save_and_embed=True, 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": 6, - "metadata": {}, - "outputs": [ + }, { - "data": { - "image/png": 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", - "text/plain": [ - "
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wgX72s5+d93xUVJRqa2u7PRQA4OJ1Keh2u10NDQ3nPV9ZWalBgwZ1eygAwMXrUtD//u//Xs8995zOnj0rSbLZbPrss880Z84cTZo0ya8DAgA6p0tBX7p0qTwejwYPHqyvv/5ad955p4YOHSqHw6Hnn3/e3zO2kZycrKysLN/jmJgYFRYWdmvNvLw830cZAEBv1aV3uYSEhGjr1q0qLS1VRUWFPB6P4uPjlZqa6u/5LPHGG29owYIFOnz4sM6ePavY2Fj9y7/8i376059aPRoAXFCXgr527VpNmTJFSUlJSkpK8j3f3Nys1157TVOnTu3SMM3NzQoMDOzSa/0pLCxMOTk5Gj58uAIDA/XWW28pPT1dgwcP1oQJE6weDwC+V5duuaSnp6u+vv6850+fPq309PROr5OcnKyMjAxlZWUpPDxcEyZM0Pbt2zVmzBjZ7XY5nU7NnTtX586d6/Sap06d0rRp0zRo0CAFBwdr/PjxqqioaLPPokWLFBERIYfDIbfbrcbGxvPmuv/++zVixAjdeOONyszM1MiRI7Vz585OzwEAl1qXP23RZjv/F9qPHTumkJCQi1przZo1CgwMVGlpqfLy8jRx4kSNHj1aFRUVWrFihVauXKmCgoJOrzd58mTV1dVp8+bN2rdvn+Lj45WSkuL7bdZ169YpLy9PCxYsUFlZmZxOp5YvX97uuW7btk2HDh3SuHHjLrhfU1OTGhoa2mwAcCld1C2X2267TTabTTabTSkpKQoI+P+Xt7S06MiRI/rRj350UQPExsZq8eLFkr65lRMdHa1ly5bJZrNp+PDhOn78uObMmaNnn31Wffq0/++fnTt3au/evaqrq5PdbpckLVmyRBs3btT69ev1xBNPqLCwUG63W263W5JUUFCgd95557yr9Pr6ekVFRampqUl9+/bV8uXL9cMf/vCCx164cKHy8/Mv6twBwJ8uKuhpaWmSpPLyck2YMEFBQUG+7wUGBiomJuai37aYkJDg+/rAgQNyuVxtrv6TkpLk8Xh07NgxXXfdde2u9e0PaAcOHNjm+a+//lpVVVW+Yzz55JNtvu9yufTuu++2ec7hcKi8vFwej0fbtm1Tdna2brjhBiUnJ3/vsefNm6fs7Gzf44aGBkVHR7c7LwD400UFPTc3V9I3bxWcMmVKm1/776oBAwZ0e41veTweOZ1OlZSUnPe90NDQi1qrT58+vo8FHjVqlA4cOKCFCxdeMOh2u933XwUAYIUuvcvlkUce8fcckqQRI0Zow4YNbe7Rl5aWyuFwaMiQIR2+Pj4+XrW1tQoICFBMTMwFj7Fnz54278TZvXt3h2u3traqqampcycCABbo0g9FW1patGTJEo0ZM0aRkZEKCwtrs3XVjBkzVFNTo1mzZungwYPatGmTcnNzlZ2d3eH9c0lKTU2Vy+VSWlqaiouLVV1drV27diknJ0dlZWWSpMzMTK1atUqrV69WZWWlcnNztX///jbrLFy4UFu3btWnn36qAwcOaOnSpXrllVf0k5/8pMvnBgA9rUtBz8/P13/8x39oypQpqq+vV3Z2th544AH16dNHeXl5XR4mKipKRUVF2rt3r+Li4vTkk0/K7XZr/vz5nXq9zWZTUVGRxo0bp/T0dN1000168MEHdfToUd+fxpsyZYqeeeYZzZ49WwkJCTp69KimT5/eZp0zZ85oxowZ+tu//VslJSVpw4YN+t3vfqdp06Z1+dwAoKd16S8W3XjjjfrlL3+pe+65x/fDw2+f2717t1599dWemLVX4S8WAfCHHv+LRbW1tbr11lslSUFBQb5fMvq7v/s7vf32211ZEgDQTV0K+pAhQ/T5559L+uZqvbi4WNI3n5POOz0AwBpdCvr999+vbdu2SZJmzZqlZ555RrGxsZo6daoee+wxvw4IAOicLt1D/2u7d+/Wrl27FBsbq3vvvdcfc/V63EMH4A8Xcw+9S+9D37Fjh+644w7fr/7ffvvtuv3223Xu3Dnt2LGj3c88AQD0jC7dcrnrrrt8H3b1XfX19brrrru6PRQA4OL59dMW//d//9evv8oPAOi8i7rl8sADD0j65hd4Hn300TbvaGlpadHHH3+sO+64w78TAgA65aKC/u1nnXu9XjkcDvXv39/3vcDAQN1+++16/PHH/TshAKBTLiroq1evliQNGjRIeXl5uvrqqyVJ1dXV2rhxo0aMGKHw8HD/TwkA6FCX7qF/9NFHWrt2raRv/uTb7bffrqVLlyotLU0rVqzw64AAgM7pctB/8IMfSJLWr1+viIgIHT16VGvXrtUvf/lLvw4IAOicLgX9q6++ksPhkCQVFxf7Pmnx9ttv19GjR/06IACgc7oU9KFDh2rjxo2qqanRli1bdPfdd0uS6urqOvxNJgBAz+hS0J999ln9/Oc/V0xMjMaOHSuXyyXpm6v12267za8DAgA6p8uf5VJbW6vPP/9ccXFxvr8mtHfvXgUHB2v48OF+HbI34rNcAPhDj3+WiyRFRkYqMjKyzXNjxozp6nIAgG7q0i0XAMDlh6ADgCEIOgAYgqADgCEIOgAYgqADgCEIOgAYgqADgCEIOgAYgqADgCEIOgAYgqADgCEIOgAYgqADgCEIOgAYgqADgCEIOgAYgqADgCEIOgAYgqADgCEIOgAYgqADgCEIOgAYgqADgCEIOgAYgqADgCF6XdCTk5OVlZXlexwTE6PCwsJurZmXl6dRo0Z1aw0AsFqvC/ql9tprr8lmsyktLc3qUQCgXZdV0Jubm60eoY3q6mr9/Oc/1w9+8AOrRwGADlka9OTkZGVkZCgrK0vh4eGaMGGCtm/frjFjxshut8vpdGru3Lk6d+5cp9c8deqUpk2bpkGDBik4OFjjx49XRUVFm30WLVqkiIgIORwOud1uNTY2nrdOS0uLHn74YeXn5+uGG27o9rkCQE+z/Ap9zZo1CgwMVGlpqfLy8jRx4kSNHj1aFRUVWrFihVauXKmCgoJOrzd58mTV1dVp8+bN2rdvn+Lj45WSkqKTJ09KktatW6e8vDwtWLBAZWVlcjqdWr58+XnrPPfccxo8eLDcbnenjtvU1KSGhoY2GwBcSgFWDxAbG6vFixdLktauXavo6GgtW7ZMNptNw4cP1/HjxzVnzhw9++yz6tOn/X//7Ny5U3v37lVdXZ3sdrskacmSJdq4caPWr1+vJ554QoWFhXK73b5QFxQU6J133mlzlb5z506tXLlS5eXlnT6PhQsXKj8//yLPHgD8x/Ir9ISEBN/XBw4ckMvlks1m8z2XlJQkj8ejY8eOdbhWRUWFPB6PBg4cqKCgIN925MgRVVVV+Y4xduzYNq9zuVy+r0+fPq2f/vSneumllxQeHt7p85g3b57q6+t9W01NTadfCwD+YPkV+oABA/y2lsfjkdPpVElJyXnfCw0N7dQaVVVVqq6u1r333ut7rrW1VZIUEBCgQ4cO6cYbbzzvdXa73fdfBQBgBcuD/l0jRozQhg0b5PV6fVfppaWlcjgcGjJkSIevj4+PV21trQICAhQTE3PBY+zZs0dTp071Pbd7927f18OHD9cnn3zS5jXz58/X6dOn9cILLyg6OroLZwYAPe+yCvqMGTNUWFioWbNmKSMjQ4cOHVJubq6ys7M7vH8uSampqXK5XEpLS9PixYt100036fjx43r77bd1//33KzExUZmZmXr00UeVmJiopKQk/f73v9f+/ft972Tp16+fbrnlljbrfnt1/9fPA8Dl5LIKelRUlIqKivT0008rLi5OYWFhcrvdmj9/fqdeb7PZVFRUpJycHKWnp+vEiROKjIzUuHHjFBERIUmaMmWKqqqqNHv2bDU2NmrSpEmaPn26tmzZ0pOnBgA9zub1er1WD2GihoYGhYSEqL8kW4d79z5PWT0AcIVokvQLSfX19QoODm53X8vf5QIA8A+CDgCGIOgAYAiCDgCGIOgAYAiCDgCGIOgAYAiCDgCGIOgAYAiCDgCGIOgAYAiCDgCGIOgAYAiCDgCGIOgAYAiCDgCGIOgAYAiCDgCGIOgAYAiCDgCGIOgAYAiCDgCGIOgAYAiCDgCGIOgAYAiCDgCGIOgAYAiCDgCGIOgAYAiCDgCGIOgAYAiCDgCGIOgAYAiCDgCGIOgAYAiCDgCGIOgAYAiCDgCGIOgAYAiCDgCGIOgAYAiCDgCGIOgAYIheF/Tk5GRlZWX5HsfExKiwsLBba+bl5WnUqFHdWgMArNbrgn4p/Pa3v5XNZmuz9evXz+qxAKBdAVYP8F3Nzc0KDAy0egxJUnBwsA4dOuR7bLPZLJwGADpm6RV6cnKyMjIylJWVpfDwcE2YMEHbt2/XmDFjZLfb5XQ6NXfuXJ07d67Ta546dUrTpk3ToEGDFBwcrPHjx6uioqLNPosWLVJERIQcDofcbrcaGxvPW8dmsykyMtK3RUREdPt8AaAnWX7LZc2aNQoMDFRpaany8vI0ceJEjR49WhUVFVqxYoVWrlypgoKCTq83efJk1dXVafPmzdq3b5/i4+OVkpKikydPSpLWrVunvLw8LViwQGVlZXI6nVq+fPl563g8Hl1//fWKjo7Wfffdp/3797d73KamJjU0NLTZAOBSsjzosbGxWrx4sYYNG6bi4mJFR0dr2bJlGj58uNLS0pSfn6+lS5eqtbW1w7V27typvXv36vXXX1diYqJiY2O1ZMkShYaGav369ZKkwsJCud1uud1uDRs2TAUFBbr55pvbrDNs2DCtWrVKmzZt0u9+9zu1trbqjjvu0LFjxy547IULFyokJMS3RUdHd+8fDABcJMuDnpCQ4Pv6wIEDcrlcbe5XJyUlyePxtBvTb1VUVMjj8WjgwIEKCgrybUeOHFFVVZXvGGPHjm3zOpfLdd7jqVOnatSoUbrzzjv1xhtvaNCgQXrxxRcveOx58+apvr7et9XU1HTq/AHAXyz/oeiAAQP8tpbH45HT6VRJScl53wsNDe3yuldddZVuu+02HT58+IL72O122e32Lh8DALrL8iv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a/docs/getting_started/layouts/grid.json +++ b/docs/getting_started/layouts/grid.json @@ -302,4 +302,4 @@ "width": 800, "height": 600, "physics": true -} \ No newline at end of file +} diff --git a/docs/getting_started/layouts/monty.json b/docs/getting_started/layouts/monty.json index 69c933a..03ee1f7 100644 --- a/docs/getting_started/layouts/monty.json +++ b/docs/getting_started/layouts/monty.json @@ -444,4 +444,4 @@ "width": 929, "height": 745, "physics": true -} \ No newline at end of file +} diff --git a/docs/getting_started/layouts/small_monty.json b/docs/getting_started/layouts/small_monty.json index f46ec23..9678ca9 100644 --- a/docs/getting_started/layouts/small_monty.json +++ b/docs/getting_started/layouts/small_monty.json @@ -136,4 +136,4 @@ "width": 575, "height": 148, "physics": true -} \ No newline at end of file +} diff --git a/docs/getting_started/lion.html b/docs/getting_started/lion.html index 30c0a9f..ae92044 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 f32e5c8..511a1da 100644 --- a/docs/getting_started/model.html +++ b/docs/getting_started/model.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: `nijmegen`, group: "states" }, { id: 1, label: `eindhoven`, group: "states" }, { id: 2, label: `aachen`, group: "states" }, @@ -218,4 +218,4 @@ " border:none !important; allowfullscreen webkitallowfullscreen mozallowfullscreen - > \ No newline at end of file + > diff --git a/docs/getting_started/naive_value_iteration.ipynb b/docs/getting_started/naive_value_iteration.ipynb index 270b37b..232cb40 100644 --- a/docs/getting_started/naive_value_iteration.ipynb +++ b/docs/getting_started/naive_value_iteration.ipynb @@ -1,1402 +1,1402 @@ { - "cells": [ - { - "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..." - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "id": "7f3692d1-ad64-449d-809c-01ceb84e6bb4", - "metadata": {}, - "outputs": [ + "cells": [ + { + "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..." + ] + }, { - "data": { - "text/html": [ - "\n", - " " + "cell_type": "code", + "execution_count": 1, + "id": "7f3692d1-ad64-449d-809c-01ceb84e6bb4", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " " + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + } ], - "text/plain": [ - "" + "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\", save_and_embed=True)" ] - }, - "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\", save_and_embed=True)" - ] - }, - { - "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": 2, - "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": 3, - "id": "a606dc3e-5d22-45a2-8234-30d3fe8b6bc5", - "metadata": {}, - "outputs": [ + }, { - "data": { - "image/png": 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", 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" + "cell_type": "markdown", + "id": "1c09fb4a-1fe9-4f76-982a-1eacd0b46a87", + "metadata": {}, + "source": [ + "Here we provide an implementation of naive value iteration using the model API." ] - }, - "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": 6, - "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": "3.11.2" - }, - "widgets": { - "application/vnd.jupyter.widget-state+json": { - "state": { - "0a4470793a704b388de44c9e5f08cab8": { - "model_module": "@jupyter-widgets/output", - "model_module_version": "1.0.0", - 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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": 3, + "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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null, + "grid_template_rows": null, + "height": null, + "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 + } + } + }, + "version_major": 2, + "version_minor": 0 + } + } + }, + "nbformat": 4, + "nbformat_minor": 5 } diff --git a/docs/getting_started/pomdp-maze.ipynb b/docs/getting_started/pomdp-maze.ipynb index daa5cdc..5971674 100644 --- a/docs/getting_started/pomdp-maze.ipynb +++ b/docs/getting_started/pomdp-maze.ipynb @@ -1,399 +1,399 @@ { - "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": 6, - "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": 7, - "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": 8, - "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": 9, - "id": "d0400922-7b90-43c5-a01e-cc051089521d", - "metadata": {}, - "outputs": [ + }, { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "a8f320e9dd724c2b8a5365445f84fa30", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Output()" + "cell_type": "code", + "execution_count": 6, + "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" }, { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "f0c470fd49be44aa9f75944c5f2cc558", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Output()" + "cell_type": "code", + "execution_count": 7, + "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" ] - }, - "metadata": {}, - "output_type": "display_data" }, { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "97583ad2f3474c4690aa05602a8e72c9", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(Output(), 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" - } - ], - "source": [ - "pomdp, positions = grid_world(LEVEL)\n", - "\n", - "vis = show(pomdp, layout=Layout(\"layouts/grid.json\"), separate_labels=[\"t\", \"e\"], show_editor=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": 5, - "id": "8d5b0e8e-47db-4dfb-a533-a8181ec04751", - "metadata": {}, - "outputs": [ + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "ebdc5973-ff3f-4056-9593-511837966101", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "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)" + ] + }, { - "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", - " * (1,2) -> 1 item(s)\n", - " * → -> 4 item(s)\n", - " * e -> 1 item(s)\n", - " * escaped -> 1 item(s)\n", - " * ↑ -> 4 item(s)\n", - " * t -> 4 item(s)\n", - " * ↓ -> 4 item(s)\n", - " * (3,1) -> 5 item(s)\n", - " * (3,2) -> 5 item(s)\n", - " * ← -> 4 item(s)\n", - " * (1,1) -> 5 item(s)\n", - " * (2,1) -> 5 item(s)\n", - "Choice Labels: \t0 labels\n", - "-------------------------------------------------------------- \n", - "\n" - ] + "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?" + ] }, { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "be72fa36268d4d918ba8707c62ab09a9", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Output()" + "cell_type": "code", + "execution_count": 9, + "id": "d0400922-7b90-43c5-a01e-cc051089521d", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "a8f320e9dd724c2b8a5365445f84fa30", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Output()" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "f0c470fd49be44aa9f75944c5f2cc558", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Output()" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "97583ad2f3474c4690aa05602a8e72c9", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HBox(children=(Output(), Output()))" + ] + }, + "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\"], show_editor=True)" ] - }, - "metadata": {}, - "output_type": "display_data" }, { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "ec58cba385aa471ab1ab61515bfcd49d", - "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": "ef0fe56a641d4ec2a77a8da76ea059a3", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(Output(), Output()))" + "cell_type": "code", + "execution_count": 5, + "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", + " * (1,2) -> 1 item(s)\n", + " * \u2192 -> 4 item(s)\n", + " * e -> 1 item(s)\n", + " * escaped -> 1 item(s)\n", + " * \u2191 -> 4 item(s)\n", + " * t -> 4 item(s)\n", + " * \u2193 -> 4 item(s)\n", + " * (3,1) -> 5 item(s)\n", + " * (3,2) -> 5 item(s)\n", + " * \u2190 -> 4 item(s)\n", + " * (1,1) -> 5 item(s)\n", + " * (2,1) -> 5 item(s)\n", + "Choice Labels: \t0 labels\n", + "-------------------------------------------------------------- \n", + "\n" + ] + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "be72fa36268d4d918ba8707c62ab09a9", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Output()" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "ec58cba385aa471ab1ab61515bfcd49d", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Output()" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "ef0fe56a641d4ec2a77a8da76ea059a3", + "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 stormpy to find the best policy/schedule, i.e. escape the maze as quickly as possible.\n", + "# Ask Pim or Linus for help?" ] - }, - "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 stormpy to find the best policy/schedule, i.e. escape the maze as quickly as possible.\n", - "# Ask Pim or Linus for help?" - ] - }, - { - "cell_type": "code", - "execution_count": 9, - "id": "b1171d26-20f6-40e5-af57-721db56be040", - "metadata": {}, - "outputs": [ + }, + { + "cell_type": "code", + "execution_count": 9, + "id": "b1171d26-20f6-40e5-af57-721db56be040", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{'0': Action(name='0', labels=frozenset()), '1': Action(name='1', labels=frozenset()), '2': Action(name='2', labels=frozenset()), '3': Action(name='3', labels=frozenset()), '4': Action(name='4', labels=frozenset()), '5': Action(name='5', labels=frozenset()), '6': Action(name='6', labels=frozenset()), '7': Action(name='7', labels=frozenset()), '8': Action(name='8', labels=frozenset()), '9': Action(name='9', labels=frozenset()), '10': Action(name='10', labels=frozenset()), '11': Action(name='11', labels=frozenset()), '12': Action(name='12', labels=frozenset()), '13': Action(name='13', labels=frozenset()), '14': Action(name='14', labels=frozenset()), '15': Action(name='15', labels=frozenset()), '16': Action(name='16', labels=frozenset()), '17': Action(name='17', labels=frozenset()), '18': Action(name='18', labels=frozenset()), '19': Action(name='19', labels=frozenset()), '20': Action(name='20', labels=frozenset()), '21': Action(name='21', labels=frozenset()), '22': Action(name='22', labels=frozenset()), '23': Action(name='23', labels=frozenset()), '24': Action(name='24', labels=frozenset()), '25': Action(name='25', labels=frozenset()), '26': Action(name='26', labels=frozenset()), '27': Action(name='27', labels=frozenset()), '28': Action(name='28', labels=frozenset()), '29': Action(name='29', labels=frozenset()), '30': Action(name='30', labels=frozenset()), '31': Action(name='31', labels=frozenset()), '32': Action(name='32', labels=frozenset()), '33': Action(name='33', labels=frozenset())}\n" + ] + } + ], + "source": [ + "print(pomdp2.actions)\n" + ] + }, { - "name": "stdout", - "output_type": "stream", - "text": [ - "{'0': Action(name='0', labels=frozenset()), '1': Action(name='1', labels=frozenset()), '2': Action(name='2', labels=frozenset()), '3': Action(name='3', labels=frozenset()), '4': Action(name='4', labels=frozenset()), '5': Action(name='5', labels=frozenset()), '6': Action(name='6', labels=frozenset()), '7': Action(name='7', labels=frozenset()), '8': Action(name='8', labels=frozenset()), '9': Action(name='9', labels=frozenset()), '10': Action(name='10', labels=frozenset()), '11': Action(name='11', labels=frozenset()), '12': Action(name='12', labels=frozenset()), '13': Action(name='13', labels=frozenset()), '14': Action(name='14', labels=frozenset()), '15': Action(name='15', labels=frozenset()), '16': Action(name='16', labels=frozenset()), '17': Action(name='17', labels=frozenset()), '18': Action(name='18', labels=frozenset()), '19': Action(name='19', labels=frozenset()), '20': Action(name='20', labels=frozenset()), '21': Action(name='21', labels=frozenset()), '22': Action(name='22', labels=frozenset()), '23': Action(name='23', labels=frozenset()), '24': Action(name='24', labels=frozenset()), '25': Action(name='25', labels=frozenset()), '26': Action(name='26', labels=frozenset()), '27': Action(name='27', labels=frozenset()), '28': Action(name='28', labels=frozenset()), '29': Action(name='29', labels=frozenset()), '30': Action(name='30', labels=frozenset()), '31': Action(name='31', labels=frozenset()), '32': Action(name='32', labels=frozenset()), '33': Action(name='33', labels=frozenset())}\n" - ] + "cell_type": "code", + "execution_count": null, + "id": "d7b41d4e-b9db-40fb-8aaf-cf3ce5e31cea", + "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": "3.11.2" } - ], - "source": [ - "print(pomdp2.actions)\n" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "id": "d7b41d4e-b9db-40fb-8aaf-cf3ce5e31cea", - "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": "3.11.2" - } - }, - "nbformat": 4, - "nbformat_minor": 5 + "nbformat": 4, + "nbformat_minor": 5 } diff --git a/docs/getting_started/pomdp.ipynb b/docs/getting_started/pomdp.ipynb index 8a144f1..e230406 100644 --- a/docs/getting_started/pomdp.ipynb +++ b/docs/getting_started/pomdp.ipynb @@ -1,327 +1,327 @@ { - "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": [ { - "data": { - "text/html": [ - "\n", - " " + "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": [ + { + "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": "b76ee6e4-156e-4a02-81b9-e150f5903df4", + "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": "3.11.2" } - ], - "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": "b76ee6e4-156e-4a02-81b9-e150f5903df4", - "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": "3.11.2" - } - }, - "nbformat": 4, - "nbformat_minor": 5 + "nbformat": 4, + "nbformat_minor": 5 } diff --git a/docs/getting_started/simulator.ipynb b/docs/getting_started/simulator.ipynb index 8dafe20..cf5ada7 100644 --- a/docs/getting_started/simulator.ipynb +++ b/docs/getting_started/simulator.ipynb @@ -1,2283 +1,2283 @@ { - "cells": [ - { - "cell_type": "markdown", - "id": "a7245ed2", - "metadata": {}, - "source": [ - "# The simulator" - ] - }, - { - "cell_type": "code", - "execution_count": 2, - "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": 3, - "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": 4, - "id": "c129cf62-40ca-4246-8718-5c859744e7f8", - "metadata": { - "scrolled": true - }, - "outputs": [ + "cells": [ { - "data": { - "text/html": [ - "\n", - " " - ], - "text/plain": [ - "" + "cell_type": "markdown", + "id": "a7245ed2", + "metadata": {}, + "source": [ + "# The simulator" ] - }, - "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": 8, - "id": "eb0fadc0-7bb6-4c1d-ae3e-9e16527726ab", - "metadata": {}, - "outputs": [ + }, { - "data": { - "text/html": [ - "\n", - " " - ], - "text/plain": [ - "" + "cell_type": "code", + "execution_count": 2, + "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" ] - }, - "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": 18, - "id": "59ac1e34-866c-42c4-b19b-c2a15c830e2e", - "metadata": {}, - "outputs": [ + }, { - "data": { - "text/html": [ - "\n", - " " - ], - "text/plain": [ - "" + "cell_type": "code", + "execution_count": 3, + "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()" ] - }, - "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": 19, - "id": "7e23fc38-b2af-4f02-b0a2-5d06151d2ca5", - "metadata": {}, - "outputs": [ + }, { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "5d046100f5854ee389f953275147271e", - "version_major": 2, - "version_minor": 0 + "cell_type": "markdown", + "id": "d1f90374-dc85-4f31-b59f-aaf5e48a32f7", + "metadata": {}, + "source": [ + "We show what our mdp model looks like." + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "c129cf62-40ca-4246-8718-5c859744e7f8", + "metadata": { + "scrolled": true }, - "text/plain": [ - "Output()" + "outputs": [ + { + "data": { + "text/html": [ + "\n", + " " + ], + "text/plain": [ + "" + ] + }, + "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." ] - }, - "metadata": {}, - "output_type": "display_data" }, { - "data": { - "text/html": [ - "" + "cell_type": "code", + "execution_count": 8, + "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" }, { - "data": { - "text/html": [ - "" + "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": 18, + "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" }, { - "data": { - "text/html": [ - "" + "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": 19, + "id": "7e23fc38-b2af-4f02-b0a2-5d06151d2ca5", + "metadata": {}, + "outputs": [ + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "5d046100f5854ee389f953275147271e", + "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": { + "text/html": [ + "" + ], + "text/plain": [ + "" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "ccd78354de7c4cab8f3e853b67f27b83", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "Output()" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "application/vnd.jupyter.widget-view+json": { + "model_id": "bfa42a087185484ea624cc0de7805b6c", + "version_major": 2, + "version_minor": 0 + }, + "text/plain": [ + "HBox(children=(Output(), Output()))" + ] + }, + "metadata": {}, + "output_type": "display_data" + } ], - "text/plain": [ - "" + "source": [ + "vis = show(mdp, show_editor=True, layout=Layout(\"layouts/monty.json\"), scheduler=scheduler)" ] - }, - "metadata": {}, - "output_type": "display_data" }, { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "ccd78354de7c4cab8f3e853b67f27b83", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Output()" + "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." ] - }, - "metadata": {}, - "output_type": "display_data" }, { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "bfa42a087185484ea624cc0de7805b6c", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "HBox(children=(Output(), Output()))" + "cell_type": "code", + "execution_count": 12, + "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)" ] - }, - "metadata": {}, - "output_type": "display_data" - } - ], - "source": [ - "vis = show(mdp, show_editor=True, layout=Layout(\"layouts/monty.json\"), scheduler=scheduler)" - ] - }, - { - "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": 12, - "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": 16, - "id": "afbb3234-99e4-49d0-b259-f598e895f600", - "metadata": {}, - "outputs": [ + "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": 16, + "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[16], 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[16], 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": "3.11.2" } - ], - "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": "3.11.2" - } - }, - "nbformat": 4, - "nbformat_minor": 5 + "nbformat": 4, + "nbformat_minor": 5 } diff --git a/docs/getting_started/study.html b/docs/getting_started/study.html index e3abc67..fd4bbe8 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: 5, y: -186 }, { id: 1, label: `studied`, group: "states", x: 98, y: 11 }, { id: 2, label: `didn't study @@ -247,4 +247,4 @@ " border:none !important; allowfullscreen webkitallowfullscreen mozallowfullscreen - > \ No newline at end of file + > diff --git a/docs/getting_started/study.ipynb b/docs/getting_started/study.ipynb index b6eb2e0..319ac1c 100644 --- a/docs/getting_started/study.ipynb +++ b/docs/getting_started/study.ipynb @@ -1,13130 +1,13130 @@ { - "cells": [ - { - "cell_type": "markdown", - "id": "31fda09b", - "metadata": {}, - "source": [ - "# The studying dilemma" - ] - }, - { - "cell_type": "code", - "execution_count": 1, - "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": 2, - "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": 3, - "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": 4, - "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": 5, - "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": 6, - "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": 8, - "id": "0df1511e-565d-45d0-93a8-adafbfaaaefa", - "metadata": { - "scrolled": true - }, - "outputs": [ + "cells": [ { - "data": { - "application/vnd.jupyter.widget-view+json": { - "model_id": "5ede64b2518440b9b728efa05babfc7d", - "version_major": 2, - "version_minor": 0 - }, - "text/plain": [ - "Output()" + "cell_type": "markdown", + "id": "31fda09b", + "metadata": {}, + "source": [ + "# The studying dilemma" ] - }, - "metadata": {}, - "output_type": "display_data" }, { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" + "cell_type": "code", + "execution_count": 1, + "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" ] - }, - "metadata": {}, - "output_type": "display_data" }, { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" + "cell_type": "markdown", + "id": "0b09222b", + "metadata": {}, + "source": [ + "Let's create an MDP and add all states:" ] - }, - "metadata": {}, - "output_type": "display_data" }, { - "data": { - "text/html": [ - "" - ], - "text/plain": [ - "" + "cell_type": "code", + "execution_count": 2, + "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\")" ] - 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Hashed by state id and Action. + """Rewards dict. Hashed by state id and Action. The function update_rewards can be called to update rewards. After this, rewards will correspond to intermediate_rewards. Note that in models without actions, EmptyAction will be used here.""" - def __init__(self, name: str, model: "Model", rewards: dict[Tuple[int, Action], Number]): + def __init__( + self, name: str, model: "Model", rewards: dict[Tuple[int, Action], Number] + ): self.name = name self.rewards = rewards self.model = model @@ -359,20 +361,22 @@ def __init__(self, name: str, model: "Model", rewards: dict[Tuple[int, Action], self.set_action_state = {} else: self.state_action_pair = None - - def set_from_rewards_vector(self, vector:list[Number]) -> None: + + def set_from_rewards_vector(self, vector: list[Number]) -> None: """Set the rewards of this model according to a stormpy rewards vector.""" combined_id = 0 self.rewards = dict() for s in self.model.states.values(): for a in s.available_actions(): - self.rewards[s.id,a] = vector[combined_id] + self.rewards[s.id, a] = vector[combined_id] combined_id += 1 def get_state_reward(self, state: State) -> Number: """Gets the reward at said state or state action pair""" if self.model.supports_actions(): - RuntimeError("This is a model with actions. Please call the get_action_state_reward(_at_id) function instead") + RuntimeError( + "This is a model with actions. Please call the get_action_state_reward(_at_id) function instead" + ) return self.rewards[state.id, EmptyAction] def get_state_action_reward(self, state: State, action: Action) -> Number | None: @@ -399,7 +403,13 @@ def set_state_reward(self, state: State, value: Number): else: self.rewards[state.id, EmptyAction] = value - def set_state_action_reward(self, state: State, action: Action, value: Number, auto_update_rewards:bool=True): + def set_state_action_reward( + self, + state: State, + action: Action, + value: Number, + auto_update_rewards: bool = True, + ): """sets the reward at said state action pair (in case of models with actions). If you disable auto_update_rewards, you will need to call update_intermediate_to""" if self.model.supports_actions(): @@ -411,15 +421,17 @@ def set_state_action_reward(self, state: State, action: Action, value: Number, a RuntimeError( "The model this rewardmodel belongs to does not support actions" ) - + def reward_vector(self) -> list[Number]: """Return the rewards in a stormpy format.""" vector = [] for s in self.model.states.values(): for a in s.available_actions(): - reward = self.rewards[s.id,a] + reward = self.rewards[s.id, a] if reward is None: - RuntimeError("A reward was not set. You might want to call set_unset_rewards.") + RuntimeError( + "A reward was not set. You might want to call set_unset_rewards." + ) vector.append(reward) return vector @@ -650,13 +662,17 @@ def add_markovian_state(self, markovian_state: State): else: raise RuntimeError("This model is not a MA") - def set_transitions(self, s: State, transitions: Transition | TransitionShorthand) -> None: + def set_transitions( + self, s: State, transitions: Transition | TransitionShorthand + ) -> None: """Set the transition from a state.""" if not isinstance(transitions, Transition): transitions = transition_from_shorthand(transitions) self.transitions[s.id] = transitions - def add_transitions(self, s: State, transitions: Transition | TransitionShorthand) -> None: + def add_transitions( + self, s: State, transitions: Transition | TransitionShorthand + ) -> None: """Add new transitions from a state to the model. If no transition currently exists, the result will be the same as set_transitions.""" if not isinstance(transitions, Transition): diff --git a/stormvogel/visualization.py b/stormvogel/visualization.py index c33b685..3889682 100644 --- a/stormvogel/visualization.py +++ b/stormvogel/visualization.py @@ -54,7 +54,7 @@ def __init__( model (Model): The stormvogel model to be displayed. name (str, optional): Internally used name. Will be randomly generated if left as None. result (Result, optional): Result corresponding to the model. - scheduler(Scheduler, optional): Scheduler. The scheduled states can be given a distinct layout. + scheduler(Scheduler, optional): Scheduler. The scheduled states can be given a distinct layout. If not set, then the scheduler from the result will be used. layout (Layout, optional): Layout used for the visualization. separate_labels (list[str], optional): Labels that should be edited separately according to the layout. @@ -76,7 +76,7 @@ def __init__( self.scheduler: stormvogel.result.Scheduler | None = scheduler # If a scheduler was not set explictely, but a result was set, then take the scheduler from the results. if self.scheduler is None: - if not self.result is None: + if self.result is not None: self.scheduler = self.result.scheduler self.layout: stormvogel.layout.Layout = layout self.separate_labels: set[str] = set(map(und, separate_labels)).union( @@ -177,8 +177,10 @@ def __add_transitions(self) -> None: ) if action.strict_eq(choice): group = "scheduled_actions" - - reward = self.__format_rewards(self.model.get_state_by_id(state_id), action) + + reward = self.__format_rewards( + self.model.get_state_by_id(state_id), action + ) # Add the action's node self.nt.add_node( @@ -215,7 +217,9 @@ def __format_probability(self, prob: stormvogel.model.Number) -> str: else: return str(round(float(prob), self.layout.layout["numbers"]["digits"])) - def __format_rewards(self, s: stormvogel.model.State, a: stormvogel.model.Action) -> str: + def __format_rewards( + self, s: stormvogel.model.State, a: stormvogel.model.Action + ) -> str: """Create a string that contains either the state exit reward (if actions are not supported) or the reward of taking this action from this state. (if actions ARE supported) Starts with newline""" @@ -228,15 +232,20 @@ def __format_rewards(self, s: stormvogel.model.State, a: stormvogel.model.Action reward = reward_model.get_state_action_reward(s, a) else: reward = reward_model.get_state_reward(s) - if not reward is None and not\ - (not self.layout.layout["state_properties"]["show_zero_rewards"] and reward == 0): + if reward is not None and not ( + not self.layout.layout["state_properties"]["show_zero_rewards"] + and reward == 0 + ): res += f"\t{reward_model.name}: {reward}" if res == EMPTY_RES: return "" return res def __format_result(self, s: stormvogel.model.State) -> str: - if self.result is None or not self.layout.layout["state_properties"]["show_results"]: + if ( + self.result is None + or not self.layout.layout["state_properties"]["show_results"] + ): return "" result_of_state = self.result.get_result_of_state(s) if result_of_state is None: @@ -249,7 +258,10 @@ def __format_result(self, s: stormvogel.model.State) -> str: ) def __format_observations(self, s: stormvogel.model.State) -> str: - if s.observation is None or not self.layout.layout["state_properties"]["show_observations"]: + if ( + s.observation is None + or not self.layout.layout["state_properties"]["show_observations"] + ): return "" else: return ( 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 dfde25d..9ccc604 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) + # TODO re-introduce this test once names are removed from actions # def test_stormvogel_to_stormpy_and_back_mdp(): # # we test it for monty hall mdp diff --git a/tests/test_model_methods.py b/tests/test_model_methods.py index 3cd3e03..4ab92e3 100644 --- a/tests/test_model_methods.py +++ b/tests/test_model_methods.py @@ -4,7 +4,6 @@ import examples.nuclear_fusion_ctmc import pytest from typing import cast -from stormvogel.model import EmptyAction def test_available_actions(): @@ -348,6 +347,7 @@ def test_get_state_action_reward(): assert rewardmodel.get_state_action_reward(state, action) == 5 + # TODO re-introduce this test once names are removed from actions. # def test_set_state_action_reward(): # # we create an mdp: diff --git a/tests/test_simulator.py b/tests/test_simulator.py index c2cf91f..95ede95 100644 --- a/tests/test_simulator.py +++ b/tests/test_simulator.py @@ -1,9 +1,3 @@ -import stormvogel.model -import examples.die -import examples.nuclear_fusion_ctmc -import stormvogel.simulator -from stormvogel.model import EmptyAction - # TODO re-introduce tests once action names are removed. # def test_simulate(): # # we make a die dtmc and run the simulator with it diff --git a/tests/test_visualization.py b/tests/test_visualization.py index c257bd7..6e7e36a 100644 --- a/tests/test_visualization.py +++ b/tests/test_visualization.py @@ -50,6 +50,7 @@ def test_show(mocker): MockNetwork.add_edge.assert_any_call(0, 1, label="1") assert MockNetwork.add_edge.call_count == 1 + # TODO re-introduce test once action names are removed. # def test_rewards(mocker): # MockNetwork = boilerplate(mocker)