Removed jupyter notebook outputs

.gitignore

@@ -1,5 +1,2 @@
-__pycache__
-*/__pycache__
-*sublime*
-env/
 venv/
+__pycache__

data/SIM_001.csv

@@ -498,3 +498,4 @@
 23;24;20;-76;45;truck;truck;3537;ascending;country_road (separated);day;dry;car;120;continue
 25;35;23;-67;49;sportscar;truck;4248;flat;country_road (separated);day;rain;car;100;continue
 22,5;24,5;28,5;-175;36;car;car;1512;flat;country_road (separated);day;dry;truck;100;continue
+22,5;27,5;34,5;-68;40;truck;motorcycle;3285;flat;country_road (separated);day;rain;truck;120;continue

data/street_slope_sim.csv

@@ -1,4 +1,4 @@
 type_street_slope,  flat,   ascending,    decending
-flat,               1.0,    0.5,          0.6
+flat,               1.0,    0.3,          0.7
-ascending,          0.5,    1.0,          0.3
+ascending,          0.3,    1.0,          0.1
-decending,          0.6,    0.3,          1.0
+decending,          0.7,    0.1,          1.0

data/street_type_sim.csv

@@ -1,3 +1,3 @@
 type_street,                country_road (separated),   autobahn
-country_road (separated),   1.0,                        0.5
+country_road (separated),   1.0,                        0.3
-autobahn,                   0.5,                        1.0
+autobahn,                   0.3,                        1.0

data/time_type_sim.csv

@@ -1,5 +1,5 @@
 type_time,  night,  dusk,   day,    dawn
-night,      1.0,    0.5,    0.6,    0.8
+night,      1.0,    0.5,    0.2,    0.8
 dusk,       0.5,    1.0,    0.3,    0.5
-day,        0.6,    0.3,    1.0,    0.6
+day,        0.2,    0.3,    1.0,    0.6
 dawn,       0.8,    0.5,    0.6,    1.0

data/vehicle_type_sim.csv

@@ -1,5 +1,5 @@
 type_vehicle,   car,   motorcycle,    sportscar, truck
-car,            1.0,   0.5,           0.6,       0.8
+car,            1.0,   0.3,           0.6,       0.3
-motorcycle,     0.5,   1.0,           0.3,       0.5
+motorcycle,     0.3,   1.0,           0.9,       0.1
-sportscar,      0.6,   0.3,           1.0,       0.6
+sportscar,      0.6,   0.9,           1.0,       0.2
-truck,          0.8,   0.5,           0.6,       1.0
+truck,          0.3,   0.1,           0.2,       1.0

data/weather_type_sim.csv

@@ -1,5 +1,5 @@
 type_weather,   dry,    rain,   fog,    snow_ice
-dry,            1.0,    0.5,    0.6,    0.8
+dry,            1.0,    0.4,    0.2,    0.1
-rain,           0.5,    1.0,    0.3,    0.5
+rain,           0.4,    1.0,    0.8,    0.6
-fog,            0.6,    0.3,    1.0,    0.6
+fog,            0.2,    0.8,    1.0,    0.4
-snow_ice,       0.8,    0.5,    0.6,    1.0
+snow_ice,       0.1,    0.6,    0.4,    1.0

explore.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -13,7 +13,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -34,29 +34,9 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
+   "outputs": [],
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "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"
-     ]
-    },
-    {
-     "data": {
-      "text/plain": [
-       "[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",
-       " 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",
-       " 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'})]"
-      ]
-     },
-     "execution_count": 3,
-     "metadata": {},
-     "output_type": "execute_result"
-    }
-   ],
    "source": [
     "case_base = CaseBase.from_csv(\n",
     "    \"data/SIM_001.csv\",\n",
@@ -72,7 +52,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -97,6 +77,11 @@
     ")\n",
     "\n",
     "case_base.add_symbolic_sim(\n",
+    "    field = \"street_type\",\n",
+    "    similarity_matrix = create_similarity_matrix(\"data/street_type_sim.csv\", \"type_street\")\n",
+    ")\n",
+    "\n",
+    "case_base.add_symbolic_sim(\n",
     "    field = \"time\",\n",
     "    similarity_matrix = create_similarity_matrix(\"data/time_type_sim.csv\", \"type_time\")\n",
     ")\n",
@@ -109,53 +94,25 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": null,
    "metadata": {},
-   "outputs": [
+   "outputs": [],
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Your Query:\n",
-      "  - v = 28\n",
-      "  - v_left = 37\n",
-      "  - v_front = 22.5\n",
-      "  - d_left = -20\n",
-      "  - d_front = 51\n",
-      "  - radius_curve = 2000\n",
-      "  - speed_limit = 200\n",
-      "  - type_vehicle = motorcycle\n",
-      "  - type_left = motorcycle\n",
-      "  - type_front = motorcycle\n",
-      "\n",
-      "I recommend you this car:\n",
-      "Accelerated_lane_change\n",
-      "\n",
-      "Explanation:\n",
-      "  - v_left = 37.0 (similarity: 1.00)\n",
-      "  - v_front = 22.5 (similarity: 1.00)\n",
-      "  - d_left = -17.0 (similarity: 0.25)\n",
-      "  - d_front = 51.0 (similarity: 1.00)\n",
-      "  - radius_curve(m) = 3020.0 (similarity: 0.00)\n",
-      "  - speed_limit(km/h) = 120.0 (similarity: 0.01)\n",
-      "  - type_vehicle = car (similarity: 0.50)\n",
-      "  - type_left = truck (similarity: 0.50)\n",
-      "  - type_front = truck (similarity: 0.50)\n"
-     ]
-    }
-   ],
    "source": [
     "query = Query.from_problems(\n",
-    "    v = 28,\n",
+    "    v = 28.5,\n",
-    "    v_left = 37,\n",
+    "    v_left = 42.5,\n",
-    "    v_front = 22.5,\n",
+    "    v_front = 5,\n",
-    "    d_left = -20,\n",
+    "    d_left = -137,\n",
-    "    d_front = 51,\n",
+    "    d_front = 54,\n",
-    "    radius_curve = 2000,\n",
-    "    speed_limit = 200,\n",
-    "    type_vehicle = \"motorcycle\",\n",
     "    type_left = \"motorcycle\",\n",
-    "    type_front = \"motorcycle\",\n",
+    "    type_front = \"truck\",\n",
+    "    radius_curve = 2391,\n",
+    "    slope_street = \"flat\",\n",
+    "    street_type = \"country_road (separated)\",\n",
+    "    time = \"day\",\n",
+    "    weather = \"dry\",\n",
+    "    type_vehicle = \"car\",\n",
+    "    speed_limit = 100,\n",
     ")\n",
     "\n",
     "# sim_funcs: manhattan_sim, euclid_sim\n",
@@ -165,11 +122,15 @@
     "    v_front = euclid_sim,\n",
     "    d_left = euclid_sim,\n",
     "    d_front = euclid_sim,\n",
-    "    radius_curve = manhattan_sim,\n",
-    "    speed_limit = manhattan_sim,\n",
-    "    type_vehicle = symbolic_sim,\n",
     "    type_left = symbolic_sim,\n",
     "    type_front = symbolic_sim,\n",
+    "    radius_curve = euclid_sim,\n",
+    "    slope_street = symbolic_sim,\n",
+    "    street_type = symbolic_sim,\n",
+    "    time = symbolic_sim,\n",
+    "    weather = symbolic_sim,\n",
+    "    type_vehicle = symbolic_sim,\n",
+    "    speed_limit = euclid_sim,\n",
     ")\n",
     "\n",
     "print(\"Your Query:\")\n",
@@ -206,7 +167,7 @@
   "orig_nbformat": 4,
   "vscode": {
    "interpreter": {
-    "hash": "4c522f398908c053844cc48bcd755f88db468f52081f171c67c4d9e41e8d16a6"
+    "hash": "c6b11de3c41b7cafaa0ac1297b550056ae3875bbf0c337fa48ab4f33656fc527"
    }
   }
  },