visuals.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>index</th>\n",
       "      <th>value</th>\n",
       "      <th>model</th>\n",
       "      <th>metric</th>\n",
       "      <th>@k</th>\n",
       "      <th>threshold</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>0.000008</td>\n",
       "      <td>random</td>\n",
       "      <td>fittime</td>\n",
       "      <td>None</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>random</td>\n",
       "      <td>fittime</td>\n",
       "      <td>None</td>\n",
       "      <td>200</td>\n",
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       "      <td>0.000008</td>\n",
       "      <td>random</td>\n",
       "      <td>fittime</td>\n",
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       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>random</td>\n",
       "      <td>fittime</td>\n",
       "      <td>None</td>\n",
       "      <td>200</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>0.000007</td>\n",
       "      <td>random</td>\n",
       "      <td>fittime</td>\n",
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       "      <td>200</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>vae</td>\n",
       "      <td>hr</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
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       "    <tr>\n",
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       "      <td>45296</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>vae</td>\n",
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       "      <td>20</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>vae</td>\n",
       "      <td>hr</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
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       "    <tr>\n",
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       "      <td>0.000000</td>\n",
       "      <td>vae</td>\n",
       "      <td>hr</td>\n",
       "      <td>20</td>\n",
       "      <td>20</td>\n",
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       "      <td>0.000000</td>\n",
       "      <td>vae</td>\n",
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       "      <td>20</td>\n",
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       "  </tbody>\n",
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       "<p>1649589 rows × 6 columns</p>\n",
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      ],
      "text/plain": [
       "        index     value   model   metric    @k  threshold\n",
       "0           0  0.000008  random  fittime  None        200\n",
       "1           1  0.000007  random  fittime  None        200\n",
       "2           2  0.000008  random  fittime  None        200\n",
       "3           3  0.000007  random  fittime  None        200\n",
       "4           4  0.000007  random  fittime  None        200\n",
       "...       ...       ...     ...      ...   ...        ...\n",
       "669960  45295  0.000000     vae       hr    20         20\n",
       "669961  45296  0.000000     vae       hr    20         20\n",
       "669962  45297  0.000000     vae       hr    20         20\n",
       "669963  45298  0.000000     vae       hr    20         20\n",
       "669964  45299  0.000000     vae       hr    20         20\n",
       "\n",
       "[1649589 rows x 6 columns]"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "drop_unnamed = lambda x: x.loc[:, ~x.columns.str.contains(\".*Unnamed.*\")]\n",
    "\n",
    "\n",
    "def wide2tall(df, infer_model: bool = True):\n",
    "    df = drop_unnamed(df)\n",
    "    df = df.melt()\n",
    "    if infer_model:\n",
    "        df[[\"model\", \"metric\"]] = df.variable.str.split(\"_\", expand=True)\n",
    "        df[[\"metric\", \"@k\"]] = df.metric.str.split(\"@\", expand=True)\n",
    "    else:\n",
    "        df[[\"metric\", \"@k\"]] = df.variable.str.split(\"@\", expand=True)\n",
    "    df = df.drop(columns=[\"variable\"])\n",
    "    return df\n",
    "\n",
    "\n",
    "def read_data(threshold):\n",
    "\n",
    "    recs_df = pd.read_csv(f\"results/recres_{threshold}.csv\")\n",
    "    recs_df = wide2tall(recs_df)\n",
    "    loo_df = pd.read_csv(f\"results/loorecres_{threshold}.csv\")\n",
    "    loo_df = wide2tall(loo_df)\n",
    "    ndcg_df = pd.read_csv(f\"results/ndcg_recres_{threshold}.csv\")\n",
    "    ndcg_df = wide2tall(ndcg_df)\n",
    "    recs_df = pd.concat([recs_df, loo_df, ndcg_df])\n",
    "\n",
    "    rbm_df = pd.read_csv(f\"results/rbm_results_{threshold}.csv\")\n",
    "    rbm_df = wide2tall(rbm_df, False)\n",
    "    rbm_df[\"model\"] = \"rbm\"\n",
    "\n",
    "    vae_df = pd.read_csv(f\"results/vae_results_{threshold}.csv\")\n",
    "    vae_df = wide2tall(vae_df, False)\n",
    "    vae_df[\"model\"] = \"vae\"\n",
    "\n",
    "    df = pd.concat([recs_df, rbm_df, vae_df]).reset_index()\n",
    "    df[\"threshold\"] = threshold\n",
    "    return df\n",
    "\n",
    "\n",
    "df = pd.DataFrame()\n",
    "tmp = read_data(200)\n",
    "df = pd.concat([df, tmp])\n",
    "tmp = read_data(100)\n",
    "df = pd.concat([df, tmp])\n",
    "tmp = read_data(50)\n",
    "df = pd.concat([df, tmp])\n",
    "tmp = read_data(20)\n",
    "df = pd.concat([df, tmp])\n",
    "\n",
    "display(df)\n",
    "df.reset_index().to_feather(\"metrics2.feather\")\n",
    "# df = df.pivot(columns=['model', 'metric', '@k'], values='value')\n",
    "# # Data is now wide\n",
    "# df.columns = df.columns.to_flat_index().str.join(' ').str.replace('  ', '')\n",
    "# models = [\"random\", \"baseline\", \"svd\", \"knn\", \"normal\"]\n",
    "# grid = sns.FacetGrid()\n",
    "# for m in models:\n",
    "#     md = df.iloc[:, df.columns.get_level_values(0)==m]\n",
    "#     md = md.iloc[:, md.columns.get_level_values('metric')==\"p\"]\n",
    "#     sns.violinplot(md)\n",
    "#     #display(md.describe().loc[[\"mean\", 'std']])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "\n",
    "df = pd.read_feather(\"results/metrics.feather\")\n",
    "df = df.replace([\"p\", \"r\"], [\"precision\", \"recall\"])\n",
    "means = (\n",
    "    df.loc[df.threshold == 20, [\"metric\", \"model\", \"@k\", \"value\"]]\n",
    "    .groupby([\"model\", \"metric\", \"@k\"])\n",
    "    .mean()\n",
    ")\n",
    "means.T.stack(0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "sns.set_style(\"ticks\", {\"axes.grid\": True})\n",
    "for i in [20, 50, 100]:\n",
    "    data = df[\n",
    "        df.metric.isin([\"rmse\", \"mae\"])\n",
    "        & df.model.isin([\"vae\", \"rbm\", \"baseline\", \"svd\", \"knn\", \"normal\"])\n",
    "    ]\n",
    "    # data = data[data.threshold == i]\n",
    "    data = data.rename(\n",
    "        columns={\"metric\": \"metrika\", \"threshold\": \"granica\", \"value\": \"vrednost\"}\n",
    "    )\n",
    "    g = sns.catplot(\n",
    "        data=data,\n",
    "        kind=\"bar\",\n",
    "        y=\"vrednost\",\n",
    "        row=\"metrika\",\n",
    "        x=\"model\",\n",
    "        col=\"granica\",\n",
    "        aspect=0.7,\n",
    "    ).add_legend()\n",
    "    plt.yticks(np.arange(0, 1, 0.02))\n",
    "    g.set(ylim=(0, 0.2))\n",
    "    ticks = data[\"@k\"].unique()\n",
    "    # for ax in g.axes.flat:\n",
    "    #     ax.set(xticks=sorted(ticks))\n",
    "    # #g.fig.suptitle(\"Zavisnost metrika od kvaliteta podataka i duzine top-N liste\")\n",
    "    g.fig.savefig(f\"qwe_{i}.pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "\n",
    "remove_duplicate_columns = lambda df: df.loc[:, ~df.columns.duplicated()]\n",
    "\n",
    "\n",
    "def prep(df, metric, set):\n",
    "    df = df.rename(columns={\"Value\": \"vrednost\", \"Step\": \"epoha\"})\n",
    "    df[\"skup\"] = set\n",
    "    df[\"metrika\"] = metric\n",
    "    return df\n",
    "\n",
    "\n",
    "df = pd.DataFrame()\n",
    "\n",
    "tmp = pd.read_csv(\"csv/RBM-ndcg@100.csv\")\n",
    "tmp = prep(tmp, \"ndcg@100\", \"validacioni\")\n",
    "df = pd.concat([df, tmp])\n",
    "df = remove_duplicate_columns(df)\n",
    "\n",
    "tmp = pd.read_csv(\"csv/RBM-train-rmse.csv\")\n",
    "tmp = prep(tmp, \"RMSE\", \"trening\")\n",
    "df = pd.concat([df, tmp])\n",
    "df = remove_duplicate_columns(df)\n",
    "\n",
    "tmp = pd.read_csv(\"csv/RBM-train-mae.csv\")\n",
    "tmp = prep(tmp, \"MAE\", \"trening\")\n",
    "df = pd.concat([df, tmp])\n",
    "df = remove_duplicate_columns(df)\n",
    "\n",
    "tmp = pd.read_csv(\"csv/RBM-valid-rmse.csv\")\n",
    "tmp = prep(tmp, \"RMSE\", \"validacioni\")\n",
    "df = pd.concat([df, tmp])\n",
    "df = remove_duplicate_columns(df)\n",
    "\n",
    "tmp = pd.read_csv(\"csv/RBM-valid-mae.csv\")\n",
    "tmp = prep(tmp, \"MAE\", \"validacioni\")\n",
    "df = pd.concat([df, tmp])\n",
    "df = remove_duplicate_columns(df)\n",
    "df = df.reset_index()\n",
    "\n",
    "sns.set(style=\"ticks\")\n",
    "m = df.loc[(df.metrika == \"RMSE\") & (df.skup == \"validacioni\"), \"vrednost\"].min()\n",
    "g = sns.relplot(\n",
    "    data=df[df.metrika != \"ndcg@100\"],\n",
    "    kind=\"line\",\n",
    "    col=\"skup\",\n",
    "    hue=\"metrika\",\n",
    "    y=\"vrednost\",\n",
    "    x=\"epoha\",\n",
    ")\n",
    "g = g.refline(y=m)\n",
    "g.figure.savefig(\"RBM-RMSE-MAE.pdf\", backend=\"pdf\")\n",
    "\n",
    "plt.cla()\n",
    "plt.clf()\n",
    "\n",
    "ndcg_df = df[df.metrika == \"ndcg@100\"]\n",
    "g = sns.lineplot(ndcg_df, x=\"epoha\", y=\"vrednost\").set_ylabel(\"ndcg@100\")\n",
    "\n",
    "ndcg_max = ndcg_df.vrednost.max()\n",
    "ndcg_argmax = ndcg_df.vrednost.argmax()\n",
    "\n",
    "plt.axhline(y=ndcg_max, alpha=0.2, color=\"red\", dashes=[2, 2], label=ndcg_max)\n",
    "plt.axvline(x=ndcg_argmax, alpha=0.2, color=\"red\", dashes=[2, 2], label=ndcg_argmax)\n",
    "g.figure.savefig(\"RBM-ndcg.pdf\", backend=\"pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "import pandas as pd\n",
    "\n",
    "remove_duplicate_columns = lambda df: df.loc[:, ~df.columns.duplicated()]\n",
    "\n",
    "\n",
    "def prep(df, metric, set):\n",
    "    df = df.rename(columns={\"Value\": \"vrednost\", \"Step\": \"epoha\"})\n",
    "    df[\"skup\"] = set\n",
    "    df[\"metrika\"] = metric\n",
    "    return df\n",
    "\n",
    "\n",
    "df = pd.DataFrame()\n",
    "\n",
    "tmp = pd.read_csv(\"csv/VAE-valid-ndcg@100.csv\")\n",
    "tmp = prep(tmp, \"ndcg@100\", \"validacioni\")\n",
    "df = pd.concat([df, tmp])\n",
    "df = remove_duplicate_columns(df)\n",
    "\n",
    "tmp = pd.read_csv(\"csv/VAE-train-loss.csv\")\n",
    "tmp = prep(tmp, \"LOSS\", \"trening\")\n",
    "df = pd.concat([df, tmp])\n",
    "df = remove_duplicate_columns(df)\n",
    "\n",
    "sns.set(style=\"ticks\")\n",
    "m = df.loc[(df.metrika == \"ndcg\") & (df.skup == \"validacioni\"), \"vrednost\"].max()\n",
    "\n",
    "fig, ax = plt.subplots(1, 2, figsize=(9, 9))\n",
    "ax[0].set_box_aspect(1)\n",
    "ax[1].set_box_aspect(1)\n",
    "\n",
    "data = df[df.metrika == \"ndcg@100\"]\n",
    "sns.lineplot(data=data, x=\"epoha\", y=\"vrednost\", ax=ax[1])\n",
    "\n",
    "plt.axhline(\n",
    "    y=data.vrednost.max(),\n",
    "    alpha=0.4,\n",
    "    dashes=[3, 2],\n",
    "    color=\"red\",\n",
    ")\n",
    "plt.axvline(\n",
    "    x=data.vrednost.argmax(),\n",
    "    alpha=0.4,\n",
    "    dashes=[3, 2],\n",
    "    color=\"red\",\n",
    ")\n",
    "ax[1].set_ylabel(\"ndcg@100\")\n",
    "plt.savefig(\"VAE-ndcg.pdf\")\n",
    "\n",
    "\n",
    "data = df[df.metrika == \"LOSS\"]\n",
    "sns.lineplot(data=data, x=\"epoha\", y=\"vrednost\", ax=ax[0])\n",
    "ax[0].set_ylabel(\"ELBO\")\n",
    "fig.tight_layout(pad=1)\n",
    "plt.savefig(\"VAE-ndcg.pdf\", bbox_inches=\"tight\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<Figure size 640x480 with 0 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "df = pd.read_feather(\"results/metrics.feather\")\n",
    "df = df.replace([\"p\", \"r\"], [\"precision\", \"recall\"])\n",
    "\n",
    "df[\"@k\"] = df[\"@k\"].astype(float).fillna(0)\n",
    "\n",
    "means = (\n",
    "    df.loc[(df.threshold <= 100), [\"metric\", \"model\", \"@k\", \"value\", \"threshold\"]]\n",
    "    .groupby([\"threshold\", \"model\", \"metric\", \"@k\"], dropna=False)\n",
    "    .mean()\n",
    ")\n",
    "\n",
    "with pd.option_context(\"display.max_columns\", None, \"display.max_rows\", None,):\n",
    "    t = means.T.stack(1, dropna=False).T\n",
    "    t = t.reindex(index=[\"predtime\", \"fittime\", 'mae',  'rmse', 'arhr', \"hr\", \"ndcg\", \"precision\", \"recall\"], level='metric')\n",
    "    idx = pd.IndexSlice\n",
    "    t = t.loc[~t.index.get_level_values('metric').isin(['fittime', 'predtime'])]\n",
    "    cmap = sns.cm.vlag_r\n",
    "    \n",
    "    \n",
    "    y = [\"mae\", \"rmse\", \"arhr\", \"hr@1\", \"hr@5\", \"hr@10\", \"hr@20\", \"ndcg@10\", \"ndcg@100\", \"precision@10\", \"precision@20\", \"precision@50\", \"precision@100\",\"recall@10\", \"recall@20\", \"recall@50\", \"recall@100\",]\n",
    "    x = ['baseline', 'knn', 'normal', 'random', 'rbm', 'svd', 'vae']\n",
    "    g = sns.heatmap(t.loc[(100,)]-t.loc[(20,)], annot=True, fmt=\".3f\", cmap=cmap, vmin=-0.15, vmax=0.15, xticklabels=x, yticklabels=y)\n",
    "    g.set_ylabel(\"metrika\")\n",
    "    g.set_xlabel(\"model\")\n",
    "    plt.tight_layout()\n",
    "    plt.show()\n",
    "    plt.subplots_adjust(left=0.5)\n",
    "    g.figure.savefig(\"100-20metrics.pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "findfont: Font family ['normal'] not found. Falling back to DejaVu Sans.\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1648.89x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1648.89x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1648.89x1000 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib\n",
    "import numpy as np\n",
    "\n",
    "sns.set_style(\"ticks\", {\"axes.grid\": True})\n",
    "\n",
    "\n",
    "font = {\n",
    "    \"family\": \"normal\",\n",
    "    #'weight' : 'bold',\n",
    "    \"size\": 22,\n",
    "}\n",
    "\n",
    "matplotlib.rc(\"font\", **font)\n",
    "\n",
    "\n",
    "for i in [20, 50, 100]:\n",
    "    data = df[\n",
    "        df.metric.isin([\"hr\"])\n",
    "        & df.model.isin([\"vae\", \"rbm\", \"baseline\", \"svd\", \"knn\", \"normal\"])\n",
    "    ]\n",
    "    data = data.rename(\n",
    "        columns={\"metric\": \"metrika\", \"threshold\": \"granica\", \"value\": \"vrednost\"}\n",
    "    )\n",
    "    data = data[data.granica == i]\n",
    "    g = sns.catplot(\n",
    "        data=data,\n",
    "        kind=\"bar\",\n",
    "        y=\"vrednost\",\n",
    "        #col=\"metrika\",\n",
    "        col_wrap=2,\n",
    "        col=\"@k\",\n",
    "        x=\"model\",\n",
    "        aspect=1.6,\n",
    "    ).add_legend()\n",
    "    plt.yticks(np.arange(0, 1, 0.05))\n",
    "    g.set(ylim=(0, 0.5))\n",
    "    ticks = data[\"@k\"].unique()\n",
    "    g.add_legend()\n",
    "    g.set_ylabels(\"hr\")\n",
    "    g.fig.savefig(f\"hr_{i}.pdf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "model = \"svd\"\n",
    "metric = \"p@10\"\n",
    "drop_unnamed = lambda x: x.loc[:, ~x.columns.str.contains(\".*Unnamed.*\")]\n",
    "df1 = pd.read_csv(\"vae_complete.csv\")\n",
    "df1 = drop_unnamed(df1)\n",
    "df1 = df1.rename(columns={\"num_ratings2\": \"n_ratings\"})\n",
    "df1 = df1.drop(columns=[\"num_ratings1\"])\n",
    "df1 = df1.melt(id_vars=[\"n_ratings\"])\n",
    "df1[[\"metric\", \"@k\"]] = df1.variable.str.split(\"@\", expand=True)\n",
    "df1 = df1.drop(columns=[\"variable\"])\n",
    "df1[\"model\"] = \"vae\"\n",
    "\n",
    "df2 = pd.read_csv(\"recs_loo_complete.csv\")\n",
    "df2 = drop_unnamed(df2)\n",
    "df2 = df2.rename(columns={\"num_ratings2\": \"n_ratings\"})\n",
    "df2 = df2.melt(id_vars=[\"n_ratings\"])\n",
    "df2[[\"model\", \"metric\"]] = df2.variable.str.split(\"_\", expand=True)\n",
    "df2[[\"metric\", \"@k\"]] = df2.metric.str.split(\"@\", expand=True)\n",
    "df2 = df2.drop(columns=[\"variable\"])\n",
    "df2\n",
    "\n",
    "df4 = pd.read_csv(\"recs_rank_complete.csv\")\n",
    "df4 = drop_unnamed(df4)\n",
    "df4 = df4.rename(columns={\"svd_n_ratings1\": \"n_ratings\"})\n",
    "df4.drop(list(df4.filter(regex = 'ratings1')), axis = 1, inplace = True)\n",
    "df4 = df4.melt(id_vars=[\"n_ratings\"])\n",
    "df4[[\"model\", \"metric\"]] = df4.variable.str.split(\"_\", expand=True)\n",
    "df4[[\"metric\", \"@k\"]] = df4.metric.str.split(\"@\", expand=True)\n",
    "df4 = df4.drop(columns=['variable'])\n",
    "df4\n",
    "\n",
    "df3 = pd.read_csv(\"rbm_complete.csv\")\n",
    "df3 = df3.rename(columns={\"n_ratings3\": \"n_ratings\"})\n",
    "df3 = drop_unnamed(df3)\n",
    "df3 = df3.drop(columns=[\"n_ratings2\", \"n_ratings1\"])\n",
    "df3 = df3.melt(id_vars=[\"n_ratings\"])\n",
    "df3[\"model\"] = \"rbm\"\n",
    "df3[[\"metric\", \"@k\"]] = df3.variable.str.split(\"@\", expand=True)\n",
    "df3 = df3.drop(columns=\"variable\")\n",
    "df = pd.concat([df1, df2, df3, df4])\n",
    "\n",
    "df.reset_index().to_feather(\"res_with_num_ratings.feather\")\n",
    "df[[\"model\", \"metric\"]].drop_duplicates()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import seaborn as sns\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import matplotlib\n",
    "\n",
    "metric = 'arhr'\n",
    "k = None\n",
    "b = [20] + [10 * (2**x) for x in range(2, 8)]\n",
    "#b = np.arange(0,3000,200)\n",
    "\n",
    "sns.set_style(\"ticks\", {\"axes.grid\": True})\n",
    "\n",
    "df = pd.read_feather(\"res_with_num_ratings.feather\")\n",
    "df[\"@k\"].fillna(0,inplace=True)\n",
    "df['@k'] = df[\"@k\"].astype(int)\n",
    "#df[\"bins\"] = pd.cut(df.n_ratings, b)\n",
    "data = df[(df.model != \"random\") & (df.metric == f\"{metric}\")]\n",
    "\n",
    "if k != None:\n",
    "    data = data[data[\"@k\"] == k]\n",
    "\n",
    "data = data.reset_index()\n",
    "\n",
    "data = (\n",
    "    data.groupby([\"bins\", \"model\"])\n",
    "    .agg({\"value\": \"mean\"})\n",
    "    .reset_index(level=[0, 1])\n",
    "    .dropna()\n",
    "    .rename(columns={'value':f'{metric}', 'bins' : 'ocene'})\n",
    ")\n",
    "\n",
    "font = {\n",
    "    \"family\": \"normal\",\n",
    "    \"size\": 20,\n",
    "}\n",
    "\n",
    "matplotlib.rc(\"font\", **font)\n",
    "\n",
    "#sns.color_palette(\"rocket\", as_cmap=True)\n",
    "g = sns.catplot(\n",
    "    data=data,\n",
    "    kind=\"point\",\n",
    "    col=\"model\",\n",
    "    x=\"n_ratings\",\n",
    "    y=f\"{metric}\",\n",
    "    col_wrap=2,\n",
    "    aspect=2,\n",
    "    dodge=False,\n",
    "    hue = 'model',\n",
    ")\n",
    "\n",
    "g.set_xticklabels([f\"{b[i]}-{b[i+1]}\" for i in range(0,len(b)-1)], rotation=30)\n",
    "g.figure.savefig(\"coldStart_arhr.pdf\")\n",
    "# sns.barplot(data[f\"{model}_{metric}\"])"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "master",
   "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",
   "version": "3.8.10"
  },
  "orig_nbformat": 4,
  "vscode": {
   "interpreter": {
    "hash": "d455cf6aac0e24a365e2bb9047524329b9a2afd5e2a351689ff84ea1d2030951"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}