:gear: added matrix file generator

backend/db/data-generator/generate.ipynb

@@ -0,0 +1,176 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Scoring: ((107, 107), (1336, 1336))\n",
+      "10000\n",
+      "\n",
+      "Scoring: ((414, 107), (414, 414))\n",
+      "8616\n",
+      "\n",
+      "Scoring: ((414, 2056), (1648, 721))\n",
+      "5738\n",
+      "\n",
+      "Scoring: ((1648, 721), (107, 414))\n",
+      "6173\n",
+      "\n",
+      "Scoring: ((1336, 1648), (1028, 1648))\n",
+      "9924\n",
+      "\n",
+      "Scoring: ((107, 414), (721, 721))\n",
+      "8616\n"
+     ]
+    }
+   ],
+   "source": [
+    "import json\n",
+    "import copy\n",
+    "from itertools import product\n",
+    "from scipy import spatial\n",
+    "\n",
+    "config = {\n",
+    "    \"all_possible_responses\": [\n",
+    "        107, 414, 721, 1028, 1336, 1648, 2056\n",
+    "    ],\n",
+    "    \"aspect_size\": 2,\n",
+    "    \"magic\": 10000,\n",
+    "    \"write\": True,\n",
+    "    \"file\": \"test.js\",\n",
+    "    \"delimiter\": \"-\",\n",
+    "    \"version\": \"0.1.0\"\n",
+    "}\n",
+    "\n",
+    "def createPermutations(possibilities, size):\n",
+    "    return tuple(product(possibilities, repeat=size))\n",
+    "\n",
+    "\n",
+    "def getAspectFromSurveys(survey_a, survey_b, size):\n",
+    "    if (survey_a.__len__() < size | survey_b.__len__() < size):\n",
+    "        raise Exception(\"Surveys must both contain more items than size\")\n",
+    "\n",
+    "    def store(survey, length):\n",
+    "        col = []\n",
+    "        for i in range(size):\n",
+    "            val = survey.pop(0)\n",
+    "            col.append(val)\n",
+    "        return col\n",
+    "\n",
+    "    # Take the first <size> elements from the list\n",
+    "    col_a = tuple(store(survey_a, size))\n",
+    "    col_b = tuple(store(survey_b, size))\n",
+    "\n",
+    "    if (col_a.__len__() != size | col_b.__len__() != size ):\n",
+    "        raise Exception(\"No aspect values found in survey\")\n",
+    "\n",
+    "    return (col_a, col_b)\n",
+    "\n",
+    "\n",
+    "def scoreAspect(aspect_ab):\n",
+    "    a = aspect_ab[0]\n",
+    "    b = aspect_ab[1]\n",
+    "    return (1 - spatial.distance.cosine(a,b)) * config[\"magic\"]\n",
+    "\n",
+    "\n",
+    "def prescore_matrix_from(vals):\n",
+    "    m = {}\n",
+    "    for val in vals:\n",
+    "        m[val] = []\n",
+    "        for other_val in vals:\n",
+    "            score = scoreAspect((val, other_val))\n",
+    "            adjusted_score = round(score)\n",
+    "            m[val].append(adjusted_score)\n",
+    "    return m\n",
+    "\n",
+    "\n",
+    "def lookup_prescore_in(score_matrix, vals, aspect_ab):\n",
+    "    print(\"\\nScoring:\", aspect_ab)\n",
+    "    aspect_a, aspect_b = aspect_ab\n",
+    "    # Look-up using the index because\n",
+    "    # \n",
+    "    pos_b = vals.index(aspect_b)\n",
+    "    return score_matrix[aspect_a][pos_b]\n",
+    "\n",
+    "\n",
+    "# !: Mutates your input\n",
+    "def score_aspect(input_a, input_b, score_matrix, vals):\n",
+    "    aspect_ab = getAspectFromSurveys(input_a, input_b, config[\"aspect_size\"])\n",
+    "    return lookup_prescore_in(score_matrix, vals, aspect_ab)\n",
+    "\n",
+    "\n",
+    "def run():\n",
+    "    # Set the keys for the look-up\n",
+    "    xy_axis_vals = createPermutations(config[\"all_possible_responses\"], config[\"aspect_size\"])\n",
+    "    m = prescore_matrix_from(xy_axis_vals)\n",
+    "\n",
+    "    # Example:\n",
+    "    res = config[\"all_possible_responses\"]\n",
+    "    input_a = [\n",
+    "        res[0], res[0], # One aspect\n",
+    "        res[1], res[0],\n",
+    "        res[1], res[6],\n",
+    "        res[5], res[2],\n",
+    "        res[4], res[5],\n",
+    "        res[0], res[1],\n",
+    "    ]\n",
+    "    input_b = [\n",
+    "        res[4], res[4], # One aspect\n",
+    "        res[1], res[1],\n",
+    "        res[5], res[2],\n",
+    "        res[0], res[1],\n",
+    "        res[3], res[5],\n",
+    "        res[2], res[2],\n",
+    "    ]\n",
+    "    for i in range(round(input_a.__len__() / 2)):\n",
+    "        print(score_aspect(input_a, input_b, m, xy_axis_vals))\n",
+    "\n",
+    "\n",
+    "    if(config[\"write\"] == True):\n",
+    "        # Serializing json\n",
+    "        str_m = {}\n",
+    "        for key, value in m.items():\n",
+    "            delimiter = config[\"delimiter\"]\n",
+    "            str_key = delimiter.join([str(v) for v in key])\n",
+    "            str_m[str_key] = value\n",
+    "            str_m[\"_config\"] = config\n",
+    "        json_object = json.dumps(str_m, indent = 4)\n",
+    "        with open(config[\"file\"], \"w\") as file:\n",
+    "            # write to file\n",
+    "            file.write(json_object)\n",
+    "run()\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "interpreter": {
+   "hash": "a4118c1262ac97709ca0d199809af279fe9249120a4ac5f6c92359d01f3f0cd0"
+  },
+  "kernelspec": {
+   "display_name": "Python 3.7.10 64-bit ('base': conda)",
+   "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",
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+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}