Removed jupyter notebook outputs
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@ -2,7 +2,7 @@
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 6,
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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@ -13,7 +13,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 7,
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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@ -34,29 +34,9 @@
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},
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{
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"cell_type": "code",
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"execution_count": 8,
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"CaseBase(cases=499, fields=[('v', 'v_left', 'v_front', 'd_left', 'd_front', 'type_left', 'type_front', 'radius_curve(m)', 'slope_street', 'street_type', 'time', 'weather', 'type_vehicle', 'speed_limit(km/h)'), 'action'])\n"
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]
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},
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{
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"data": {
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"text/plain": [
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"[Case(problem={'v_left': 36.5, 'v_front': 23.0, 'd_left': -56.0, 'd_front': 45.0, 'type_left': 'sportscar', 'type_front': 'truck', 'radius_curve(m)': 2237.0, 'slope_street': 'flat', 'street_type': 'country_road (separated)', 'time': 'night', 'weather': 'dry', 'type_vehicle': 'car', 'speed_limit(km/h)': 100.0}, solution={'action': 'continue'}),\n",
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" Case(problem={'v_left': 32.0, 'v_front': 28.0, 'd_left': -114.0, 'd_front': 44.0, 'type_left': 'motorcycle', 'type_front': 'car', 'radius_curve(m)': 3891.0, 'slope_street': 'ascending', 'street_type': 'autobahn', 'time': 'night', 'weather': 'dry', 'type_vehicle': 'truck', 'speed_limit(km/h)': 250.0}, solution={'action': 'continue'}),\n",
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" Case(problem={'v_left': 43.0, 'v_front': 31.5, 'd_left': -98.0, 'd_front': 60.0, 'type_left': 'truck', 'type_front': 'car', 'radius_curve(m)': 1720.0, 'slope_street': 'flat', 'street_type': 'autobahn', 'time': 'dusk', 'weather': 'rain', 'type_vehicle': 'car', 'speed_limit(km/h)': 130.0}, solution={'action': 'continue'})]"
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]
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},
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"execution_count": 8,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"outputs": [],
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"source": [
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"case_base = CaseBase.from_csv(\n",
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" \"data/SIM_001.csv\",\n",
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@ -72,7 +52,7 @@
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},
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{
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"cell_type": "code",
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"execution_count": 12,
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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@ -114,65 +94,25 @@
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},
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{
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"cell_type": "code",
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"execution_count": 13,
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"execution_count": null,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"Your Query:\n",
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" - v = 22.5\n",
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" - v_left = 27.5\n",
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" - v_front = 34.5\n",
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" - d_left = -68\n",
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" - d_front = 40\n",
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" - type_left = truck\n",
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" - type_front = motorcycle\n",
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" - radius_curve = 3285\n",
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" - slope_street = flat\n",
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" - street_type = country_road (separated)\n",
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" - time = day\n",
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" - weather = rain\n",
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" - type_vehicle = motorcycle\n",
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" - speed_limit = 120\n",
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"\n",
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"I recommend you this car:\n",
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"Continue\n",
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"\n",
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"Explanation:\n",
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" - v_left = 33.0 (similarity: 0.15)\n",
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" - v_front = 34.5 (similarity: 1.00)\n",
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" - d_left = -120.0 (similarity: 0.02)\n",
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" - d_front = 38.0 (similarity: 0.33)\n",
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" - type_left = car (similarity: 0.80)\n",
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" - type_front = motorcycle (similarity: 1.00)\n",
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" - radius_curve(m) = 3606.0 (similarity: 0.00)\n",
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" - slope_street = flat (similarity: 1.00)\n",
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" - street_type = country_road (separated) (similarity: 1.00)\n",
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" - time = day (similarity: 1.00)\n",
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" - weather = rain (similarity: 1.00)\n",
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" - type_vehicle = truck (similarity: 0.50)\n",
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" - speed_limit(km/h) = 120.0 (similarity: 1.00)\n"
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]
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}
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],
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"outputs": [],
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"source": [
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"query = Query.from_problems(\n",
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" v = 22.5,\n",
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" v_left = 27.5,\n",
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" v_front = 34.5,\n",
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" d_left = -68,\n",
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" d_front = 40,\n",
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" type_left = \"truck\",\n",
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" type_front = \"motorcycle\",\n",
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" radius_curve = 3285,\n",
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" v = 28.5,\n",
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" v_left = 42.5,\n",
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" v_front = 5,\n",
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" d_left = -137,\n",
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" d_front = 54,\n",
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" type_left = \"motorcycle\",\n",
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" type_front = \"truck\",\n",
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" radius_curve = 2391,\n",
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" slope_street = \"flat\",\n",
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" street_type = \"country_road (separated)\",\n",
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" time = \"day\",\n",
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" weather = \"rain\",\n",
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" type_vehicle = \"motorcycle\",\n",
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" speed_limit = 120,\n",
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" weather = \"dry\",\n",
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" type_vehicle = \"car\",\n",
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" speed_limit = 100,\n",
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")\n",
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"\n",
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"# sim_funcs: manhattan_sim, euclid_sim\n",
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@ -227,7 +167,7 @@
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"orig_nbformat": 4,
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"vscode": {
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"interpreter": {
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"hash": "a5aa7fe267f107423dffd85abeeed3bf0e097b37494d32919cbe32f80338e7f6"
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"hash": "c6b11de3c41b7cafaa0ac1297b550056ae3875bbf0c337fa48ab4f33656fc527"
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}
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}
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},
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