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SAN_BENIGNO_s__10.ipynb 126 KiB
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Marco Mazzolini's avatar
working version with snow+snow related runoff.
Marco Mazzolini committed
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  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9155f273",
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "a4=compute_anomalies(climatologies4, predictions4)\n",
    "a4['split']=predictions4.split\n",
    "plot_anomalies(a4)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "4869891d",
   "metadata": {},
   "source": [
    "# COMPARE RESULTS"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9bf593c1",
   "metadata": {},
   "outputs": [],
   "source": [
    "results = pd.concat([r2_PCA180,r2_PCA36,r2_STATS,r2_TPE],axis=1)\n",
    "results.columns=['A) PCA(180)','B) PCA(36)','C) TPE_STATS','D) TPE_AVG']\n",
    "results.iloc[1:].plot.bar()\n",
    "plt.title('R^2 RESULTS COMPARISON')\n",
    "plt.ylabel('r^2 [/]')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "42d0f057",
   "metadata": {},
   "outputs": [],
   "source": [
    "r2_TPE_an = evaluate_prediction(a4)\n",
    "r2_STATS_an= evaluate_prediction(a3)\n",
    "r2_PCA36_an = evaluate_prediction(a2)\n",
    "r2_PCA180_an = evaluate_prediction(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "734b6a0b",
   "metadata": {},
   "outputs": [],
   "source": [
    "results = pd.concat([r2_PCA180_an,r2_PCA36_an,r2_STATS_an,r2_TPE_an],axis=1)\n",
    "results.columns=['A) PCA(180)','B) PCA(36)','C) TPE_STATS','D) TPE_AVG']\n",
    "results.iloc[1:].plot.bar()\n",
    "plt.title('R^2 RESULTS COMPARISON')\n",
    "plt.ylabel('r^2 [/]')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "175d81f4",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "8434ad71",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f933ff24",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5d12673a",
   "metadata": {},
   "outputs": [],
   "source": [
    "results = pd.concat([r2_PCA180,r2_PCA36,r2_STATS],axis=1)\n",
    "results.columns=['A) PCA(180)','B) PCA(36)','C) TPE_STATS']\n",
    "results.iloc[1:].plot.bar()\n",
    "plt.title('R^2 RESULTS COMPARISON')\n",
    "plt.ylabel('r^2 [/]')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "79e276ec",
   "metadata": {},
   "outputs": [],
   "source": [
    "#r2_TPE_an = evaluate_prediction(a4)\n",
    "r2_STATS_an= evaluate_prediction(a3)\n",
    "r2_PCA36_an = evaluate_prediction(a2)\n",
    "r2_PCA180_an = evaluate_prediction(a)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "c3e39799",
   "metadata": {},
   "outputs": [],
   "source": [
    "results = pd.concat([r2_PCA180_an,r2_PCA36_an,r2_STATS_an],axis=1)\n",
    "results.columns=['A) PCA(180)','B) PCA(36)','C) TPE_STATS']\n",
    "results.iloc[1:].plot.bar()\n",
    "plt.title('R^2 RESULTS COMPARISON')\n",
    "plt.ylabel('r^2 [/]')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5eacb987",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "1ef98b15",
   "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",
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