fmda/results_summary.ipynb

   1 {
   2  "cells": [
   3   {
   4    "cell_type": "code",
   5    "execution_count": null,
   6    "id": "af683b2e-8e70-403c-ab28-1cfdc314b4d5",
   7    "metadata": {},
   8    "outputs": [],
   9    "source": [
  10     "import pandas as pd\n",
  11     "from data_funcs import from_json\n",
  12     "import matplotlib.pyplot as plt"
  13    ]
  14   },
  15   {
  16    "cell_type": "code",
  17    "execution_count": null,
  18    "id": "365b3157-b5db-4cd1-8095-4f847f24d682",
  19    "metadata": {
  20     "scrolled": true
  21    },
  22    "outputs": [],
  23    "source": [
  24     "rnn = from_json(\"rnn_errs.json\")\n",
  25     "kf = from_json(\"kf_errs.json\")"
  26    ]
  27   },
  28   {
  29    "cell_type": "code",
  30    "execution_count": null,
  31    "id": "e4faafed-6678-4164-a6e3-649d01fd63c7",
  32    "metadata": {},
  33    "outputs": [],
  34    "source": [
  35     "# Remove \"filename\" key\n",
  36     "del rnn['filename']\n",
  37     "del kf['filename']"
  38    ]
  39   },
  40   {
  41    "cell_type": "code",
  42    "execution_count": null,
  43    "id": "19b9744c-a4db-4aab-a054-e402269b9f4d",
  44    "metadata": {},
  45    "outputs": [],
  46    "source": [
  47     "# Prepare lists to store the extracted values\n",
  48     "cases = []\n",
  49     "predictions = []\n",
  50     "\n",
  51     "# Iterate through the dictionary to extract the needed values\n",
  52     "for key, value in rnn.items():\n",
  53     "    cases.append(value['case'])\n",
  54     "    predictions.append(value['errs']['prediction'])\n",
  55     "\n",
  56     "# Create the DataFrame\n",
  57     "df1 = pd.DataFrame({\n",
  58     "    'case': cases,\n",
  59     "    'prediction': predictions\n",
  60     "})\n"
  61    ]
  62   },
  63   {
  64    "cell_type": "code",
  65    "execution_count": null,
  66    "id": "0b961e18-47c9-40a9-9b63-178d7fad27e4",
  67    "metadata": {},
  68    "outputs": [],
  69    "source": [
  70     "df1"
  71    ]
  72   },
  73   {
  74    "cell_type": "code",
  75    "execution_count": null,
  76    "id": "690b32ea-4a80-4a44-a7e6-6dd9453041dc",
  77    "metadata": {},
  78    "outputs": [],
  79    "source": [
  80     "df2 = pd.DataFrame.from_dict(kf).transpose()\n",
  81     "df2.head()"
  82    ]
  83   },
  84   {
  85    "cell_type": "code",
  86    "execution_count": null,
  87    "id": "6c5b2084-879d-4fb9-a25f-a57c3d239dde",
  88    "metadata": {},
  89    "outputs": [],
  90    "source": [
  91     "plt.hist(df1.prediction, label = \"RNN\")\n",
  92     "plt.hist(df2.errs, label = \"KF\")\n",
  93     "plt.legend()"
  94    ]
  95   },
  96   {
  97    "cell_type": "code",
  98    "execution_count": null,
  99    "id": "403c87cb-85c1-4059-9d9c-087d0fd33f9b",
 100    "metadata": {},
 101    "outputs": [],
 102    "source": [
 103     "print(df1.prediction.mean())\n",
 104     "print(df1.prediction.median())"
 105    ]
 106   },
 107   {
 108    "cell_type": "code",
 109    "execution_count": null,
 110    "id": "0a36faff-9b98-4a80-b464-0973909d5e8f",
 111    "metadata": {},
 112    "outputs": [],
 113    "source": [
 114     "print(df2.errs.mean())\n",
 115     "print(df2.errs.median())"
 116    ]
 117   },
 118   {
 119    "cell_type": "code",
 120    "execution_count": null,
 121    "id": "4355db09-2232-4526-ba96-42da4cd44ce3",
 122    "metadata": {},
 123    "outputs": [],
 124    "source": []
 125   },
 126   {
 127    "cell_type": "code",
 128    "execution_count": null,
 129    "id": "5b7a4469-ad9a-4b6a-8982-31873d39e43d",
 130    "metadata": {},
 131    "outputs": [],
 132    "source": []
 133   }
 134  ],
 135  "metadata": {
 136   "kernelspec": {
 137    "display_name": "Python 3 (ipykernel)",
 138    "language": "python",
 139    "name": "python3"
 140   },
 141   "language_info": {
 142    "codemirror_mode": {
 143     "name": "ipython",
 144     "version": 3
 145    },
 146    "file_extension": ".py",
 147    "mimetype": "text/x-python",
 148    "name": "python",
 149    "nbconvert_exporter": "python",
 150    "pygments_lexer": "ipython3",
 151    "version": "3.12.5"
 152   }
 153  },
 154  "nbformat": 4,
 155  "nbformat_minor": 5
 156 }