demo_results_analysis.ipynb

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   "source": [
    "# Analysis of results"
   ]
  },
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   "source": [
    "# -- Libraries and defaults\n",
    "\n",
    "import os\n",
    "import pickle\n",
    "import numpy as np\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import arviz as az\n",
    "from functools import reduce\n",
    "from matplotlib.lines import Line2D\n",
    "\n",
    "np.set_printoptions(precision=4, suppress=True)\n",
    "pd.set_option(\"display.precision\", 4)\n",
    "pd.set_option(\"styler.format.precision\", 4)"
   ]
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   "source": [
    "# -- Global configuration\n",
    "\n",
    "DIR_EXPERIMENTS = \"experiments/\"\n",
    "SAVE_FIG = False  # Save format is .pdf\n",
    "DIR_SAVE = \"figures/\"\n",
    "COLORS = plt.get_cmap(\"tab10\")\n",
    "FONT_SIZE_LATEX = 15  # Font size for saved figures"
   ]
  },
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   "source": [
    "# -- Set matplotlib parameters\n",
    "\n",
    "plt.rc(\"axes\", prop_cycle=plt.cycler(\"color\", COLORS.colors))\n",
    "legend_fontsize = FONT_SIZE_LATEX - 2 if SAVE_FIG else None\n",
    "\n",
    "if SAVE_FIG:  # Mirror the style of a specific LaTeX document\n",
    "    plt.rcParams.update(\n",
    "        {\n",
    "            \"font.family\": \"serif\",\n",
    "            \"font.size\": FONT_SIZE_LATEX,\n",
    "            \"axes.linewidth\": 0.75,\n",
    "            \"text.usetex\": True,\n",
    "            \"pgf.rcfonts\": False,\n",
    "            \"pgf.texsystem\": \"pdflatex\",  # default is xetex\n",
    "            \"pgf.preamble\": \"\\n\".join(\n",
    "                [\n",
    "                    r\"\\renewcommand{\\rmdefault}{ptm}\",\n",
    "                    r\"\\renewcommand{\\sfdefault}{phv}\",\n",
    "                    r\"\\usepackage[T1]{fontenc}\",\n",
    "                    r\"\\usepackage[english]{babel}\",\n",
    "                    r\"\\usepackage{microtype}\",\n",
    "                    r\"\\makeatletter\\g@addto@macro\\bfseries{\\boldmath}\\makeatother\",  # bold math\n",
    "                ]\n",
    "            ),\n",
    "        }\n",
    "    )\n",
    "else:\n",
    "    plt.rcParams.update(plt.rcParamsDefault)\n",
    "    %matplotlib inline\n",
    "    plt.rcParams[\"figure.dpi\"] = 100"
   ]
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   "source": [
    "# -- Helper functions\n",
    "\n",
    "\n",
    "def get_name_table(dataname):\n",
    "    basename = os.path.basename(name)\n",
    "    basename_split = basename.split(\"_\")\n",
    "\n",
    "    if \"mixture\" in dataname:\n",
    "        model = \"mixture\"\n",
    "    elif \"gbm_\" in dataname:\n",
    "        model = \"gbm\"\n",
    "    elif \"gp_\" in dataname:\n",
    "        model = basename_split[5]\n",
    "    else:\n",
    "        model = basename_split[3]\n",
    "\n",
    "    if \"homoscedastic\" in dataname:\n",
    "        dataname_short = \"Homoscedastic\"\n",
    "    elif \"heteroscedastic\" in dataname:\n",
    "        dataname_short = \"Heteroscedastic\"\n",
    "    elif \"fractional\" in dataname:\n",
    "        dataname_short = \"fBM\"\n",
    "    elif \"brownian\" in dataname:\n",
    "        dataname_short = \"BM\"\n",
    "    elif \"exponential\" in dataname:\n",
    "        dataname_short = \"Sq. exp\"\n",
    "    elif \"ornstein_uhlenbeck\" in dataname:\n",
    "        dataname_short = \"O-U\"\n",
    "    elif \"gbm_rkhs\" in dataname:\n",
    "        dataname_short = \"GBM + RKHS\"\n",
    "    elif \"gbm_l2\" in dataname:\n",
    "        dataname_short = \"GBM + $L^2$\"\n",
    "    else:\n",
    "        dataname_short = model.capitalize()\n",
    "\n",
    "    return dataname_short\n",
    "\n",
    "\n",
    "def get_name_graph(dataname):\n",
    "    basename = os.path.basename(dataname)\n",
    "    basename_split = basename.split(\"_\")\n",
    "\n",
    "    if \"mixture\" in dataname:\n",
    "        model = \"mixture\"\n",
    "    elif \"gbm_\" in dataname:\n",
    "        model = \"gbm\"\n",
    "    elif \"gp_\" in dataname:\n",
    "        model = basename_split[5]\n",
    "    else:\n",
    "        model = basename_split[3]\n",
    "\n",
    "    real_data = False\n",
    "    if \"homoscedastic\" in dataname:\n",
    "        dataname_short = \"Homoscedastic\"\n",
    "    elif \"heteroscedastic\" in dataname:\n",
    "        dataname_short = \"Heteroscedastic\"\n",
    "    elif \"fractional\" in dataname:\n",
    "        dataname_short = \"Fractional Brownian\"\n",
    "    elif \"brownian\" in dataname:\n",
    "        dataname_short = \"Standard Brownian\"\n",
    "    elif \"exponential\" in dataname:\n",
    "        dataname_short = \"Gaussian\"\n",
    "    elif \"ornstein_uhlenbeck\" in dataname:\n",
    "        dataname_short = \"Ornstein-Uhlenbeck\"\n",
    "    elif \"gbm_rkhs\" in dataname:\n",
    "        dataname_short = \"GBM + RKHS\"\n",
    "    elif \"gbm_l2\" in dataname:\n",
    "        dataname_short = \"GBM + $L^2$\"\n",
    "    else:\n",
    "        dataname_short = model.capitalize()\n",
    "        real_data = True\n",
    "\n",
    "    if \"smoothing\" in basename:\n",
    "        dataname_short += \" - smooth\"\n",
    "    if \"p_free\" in basename:\n",
    "        dataname_short += \" (p free)\"\n",
    "\n",
    "    return dataname_short, real_data\n",
    "\n",
    "\n",
    "def separate_df(df, key):\n",
    "    df_bayesian = df[~df[\"Estimator\"].str.contains(\"\\+\")]\n",
    "    df_bayesian = df_bayesian.sort_values(key)\n",
    "    df_var_sel = df[df[\"Estimator\"].str.contains(\"\\+\")]\n",
    "    df_var_sel = df_var_sel.sort_values(key)\n",
    "\n",
    "    return df_bayesian, df_var_sel\n",
    "\n",
    "\n",
    "def get_size_latex(width, fraction=1, subplots=(1, 1)):\n",
    "    \"\"\"Set figure dimensions to avoid scaling in LaTeX.\n",
    "\n",
    "    [https://jwalton.info/Embed-Publication-Matplotlib-Latex/]\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    width: float or string\n",
    "            Document width in points, or string of predined document type\n",
    "    fraction: float, optional\n",
    "            Fraction of the width which you wish the figure to occupy\n",
    "    subplots: array-like, optional\n",
    "            The number of rows and columns of subplots.\n",
    "    Returns\n",
    "    -------\n",
    "    fig_dim: tuple\n",
    "            Dimensions of figure in inches\n",
    "    \"\"\"\n",
    "    if width == \"thesis\":\n",
    "        width_pt = 426.79135\n",
    "    elif width == \"beamer\":\n",
    "        width_pt = 307.28987\n",
    "    else:\n",
    "        width_pt = width\n",
    "\n",
    "    # Width of figure (in pts)\n",
    "    fig_width_pt = width_pt * fraction\n",
    "    # Convert from pt to inches\n",
    "    inches_per_pt = 1 / 72.27\n",
    "\n",
    "    # Golden ratio to set aesthetic figure height\n",
    "    # https://disq.us/p/2940ij3\n",
    "    golden_ratio = (5**0.5 - 1) / 2\n",
    "\n",
    "    # Figure width in inches\n",
    "    fig_width_in = fig_width_pt * inches_per_pt\n",
    "    # Figure height in inches\n",
    "    fig_height_in = fig_width_in * golden_ratio * (subplots[0] / subplots[1])\n",
    "\n",
    "    return (fig_width_in, fig_height_in)"
   ]
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   "cell_type": "markdown",
   "id": "4bcc7341",
   "metadata": {},
   "source": [
    "## Recovering the RKHS functional parameter"
   ]
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   "id": "adff505f",
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   "source": [
    "# -- Configuration\n",
    "\n",
    "DIR_TRACE = DIR_EXPERIMENTS + \"emcee_linear-3.idata\"  # emcee_linear-{3,4}.idata"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "7f4a1467",
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    "execution": {
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   "source": [
    "# -- Load data\n",
    "\n",
    "with open(DIR_TRACE, \"rb\") as file:\n",
    "    idata_emcee = pickle.load(file)\n",
    "    n_vars = len(idata_emcee.posterior[\"theta\"])"
   ]
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",
      "text/plain": [
       "<Figure size 1200x700 with 4 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# -- Plot density and trace evolution\n",
    "\n",
    "labeller = {\"β\": \"$b$\", \"τ\": \"$\\\\tau$\"} if SAVE_FIG else {\"β\": \"b\", \"τ\": \"τ\"}\n",
    "components = {0: \"First\", 1: \"Second\", 2: \"Third\", 3: \"Fourth\"}\n",
    "\n",
    "# Figure\n",
    "fig, axs = plt.subplots(2, 2, figsize=(12, 7))\n",
    "az.plot_trace(idata_emcee, var_names=[\"β\", \"τ\"], combined=True, axes=axs)\n",
    "plt.subplots_adjust(hspace=0.25)\n",
    "axs[0, 0].set_title(\"Approximate posterior density\")\n",
    "axs[0, 1].set_title(\"Trace evolution\")\n",
    "axs[1, 0].set_title(\"\")\n",
    "axs[1, 1].set_title(\"\")\n",
    "axs[0, 1].set_xlabel(\"Iterations\")\n",
    "axs[1, 1].set_xlabel(\"Iterations\")\n",
    "axs[1, 0].set_xlabel(labeller[\"τ\"])\n",
    "axs[0, 0].set_xlabel(labeller[\"β\"])\n",
    "axs[0, 1].set_ylabel(labeller[\"β\"])\n",
    "axs[1, 1].set_ylabel(labeller[\"τ\"])\n",
    "\n",
    "# Legend\n",
    "lines = [\n",
    "    Line2D([0], [0], label=components[i] + \" component\", color=COLORS(i))\n",
    "    for i in range(n_vars)\n",
    "]\n",
    "axs[1, 0].legend(\n",
    "    loc=\"lower center\",\n",
    "    handles=lines,\n",
    "    ncol=n_vars,\n",
    "    fancybox=True,\n",
    "    shadow=True,\n",
    "    fontsize=legend_fontsize,\n",
    "    bbox_to_anchor=(1.085, -0.45),\n",
    ")\n",
    "\n",
    "if SAVE_FIG:\n",
    "    plt.rcParams.update({\n",
    "        \"axes.labelsize\": FONT_SIZE_LATEX - 3,\n",
    "        \"xtick.labelsize\": FONT_SIZE_LATEX,\n",
    "        \"ytick.labelsize\": FONT_SIZE_LATEX,\n",
    "    })\n",
    "    plt.savefig(\n",
    "        DIR_SAVE + os.path.basename(DIR_TRACE).split(\".\")[0] + \".pdf\",\n",
    "        backend=\"pgf\",\n",
    "        bbox_inches=\"tight\",\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "34b742a2",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "## Dependence on parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "bc244ff2",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-21T17:00:47.209495Z",
     "start_time": "2022-09-21T17:00:47.200530Z"
    },
    "execution": {
     "iopub.execute_input": "2024-07-30T11:11:19.701256Z",
     "iopub.status.busy": "2024-07-30T11:11:19.700722Z",
     "iopub.status.idle": "2024-07-30T11:11:19.704734Z",
     "shell.execute_reply": "2024-07-30T11:11:19.704251Z",
     "shell.execute_reply.started": "2024-07-30T11:11:19.701209Z"
    },
    "hidden": true
   },
   "outputs": [],
   "source": [
    "# -- Configuration\n",
    "\n",
    "DIR_DEPENDENCE = DIR_EXPERIMENTS + \"mixture_dependence_acc_p.csv\"\n",
    "X_LABEL_DEPENDENCE = \"p\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "c8507a1c",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-21T17:00:47.227210Z",
     "start_time": "2022-09-21T17:00:47.211469Z"
    },
    "code_folding": [
     0
    ],
    "execution": {
     "iopub.execute_input": "2024-07-30T11:11:19.705714Z",
     "iopub.status.busy": "2024-07-30T11:11:19.705384Z",
     "iopub.status.idle": "2024-07-30T11:11:19.727914Z",
     "shell.execute_reply": "2024-07-30T11:11:19.727344Z",
     "shell.execute_reply.started": "2024-07-30T11:11:19.705694Z"
    },
    "hidden": true
   },
   "outputs": [],
   "source": [
    "# -- Read data\n",
    "\n",
    "df = pd.read_csv(DIR_DEPENDENCE)\n",
    "df_bayesian, df_var_sel = separate_df(df, X_LABEL_DEPENDENCE)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "f0de0340",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-21T17:00:48.140214Z",
     "start_time": "2022-09-21T17:00:47.229929Z"
    },
    "code_folding": [
     0
    ],
    "execution": {
     "iopub.execute_input": "2024-07-30T11:11:19.730470Z",
     "iopub.status.busy": "2024-07-30T11:11:19.730198Z",
     "iopub.status.idle": "2024-07-30T11:11:20.045573Z",
     "shell.execute_reply": "2024-07-30T11:11:20.044923Z",
     "shell.execute_reply.started": "2024-07-30T11:11:19.730450Z"
    },
    "hidden": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x350 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# -- Plot data\n",
    "\n",
    "SCORE = \"Acc\" if any(\"Acc\" in string for string in df.columns) else \"RMSE\"\n",
    "SCORE_STR = \"Accuracy\" if SCORE == \"Acc\" else SCORE\n",
    "FIGSIZE = (16, 5) if SAVE_FIG else (12, 3.5)\n",
    "\n",
    "fig, ax = plt.subplots(1, 2, figsize=FIGSIZE, sharey=True)\n",
    "for i, df in enumerate([df_bayesian, df_var_sel]):\n",
    "    ax[i].set_xlabel(X_LABEL_DEPENDENCE)\n",
    "    ax[i].set_ylabel(f\"{SCORE_STR}\")\n",
    "    for key, grp in df.groupby([\"Estimator\"]):\n",
    "        x, y = grp[X_LABEL_DEPENDENCE], grp[f\"Mean {SCORE}\"]\n",
    "        yerror = grp[f\"SD {SCORE}\"]\n",
    "        ax[i].plot(x, y, label=key[0], marker=\".\", markersize=10)\n",
    "        ax[i].fill_between(x, y - yerror, y + yerror, alpha=0.1)\n",
    "\n",
    "ax[0].legend(fontsize=legend_fontsize)\n",
    "ax[1].legend(loc=\"lower left\", fontsize=legend_fontsize)\n",
    "ax[1].tick_params(labelleft=True)\n",
    "\n",
    "if SAVE_FIG:\n",
    "    plt.savefig(\n",
    "        DIR_SAVE + os.path.basename(DIR_DEPENDENCE).split(\".\")[0] + \".pdf\",\n",
    "        backend=\"pgf\",\n",
    "        bbox_inches=\"tight\",\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0dc6d1ac",
   "metadata": {},
   "source": [
    "## CV results"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "d6bfe268",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-21T18:48:00.052500Z",
     "start_time": "2022-09-21T18:48:00.047231Z"
    },
    "code_folding": [],
    "execution": {
     "iopub.execute_input": "2024-07-30T11:11:20.046509Z",
     "iopub.status.busy": "2024-07-30T11:11:20.046279Z",
     "iopub.status.idle": "2024-07-30T11:11:20.050293Z",
     "shell.execute_reply": "2024-07-30T11:11:20.049773Z",
     "shell.execute_reply.started": "2024-07-30T11:11:20.046484Z"
    }
   },
   "outputs": [],
   "source": [
    "# -- Configuration\n",
    "\n",
    "KIND = \"linear\"  # 'linear' or 'logistic'\n",
    "METHOD = \"emcee\"\n",
    "SMOOTHING = False\n",
    "P_FREE = False\n",
    "DIR = DIR_EXPERIMENTS + \"out/\"\n",
    "SCORE_REG = \"RMSE\"  # 'RMSE' or 'rRMSE'\n",
    "\n",
    "KIND_STR = \"reg\" if KIND == \"linear\" else \"clf\"\n",
    "SCORE_STR = SCORE_REG if KIND == \"linear\" else \"Acc\"\n",
    "SCORE_STR_FULL = SCORE_REG if KIND == \"linear\" else \"Accuracy\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d4c426a2",
   "metadata": {},
   "source": [
    "### Data gathering"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "7a2eb886",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-21T18:48:02.111710Z",
     "start_time": "2022-09-21T18:48:02.080657Z"
    },
    "code_folding": [
     0
    ],
    "execution": {
     "iopub.execute_input": "2024-07-30T11:11:20.051334Z",
     "iopub.status.busy": "2024-07-30T11:11:20.050995Z",
     "iopub.status.idle": "2024-07-30T11:11:20.064926Z",
     "shell.execute_reply": "2024-07-30T11:11:20.064289Z",
     "shell.execute_reply.started": "2024-07-30T11:11:20.051312Z"
    }
   },
   "outputs": [],
   "source": [
    "# -- Data reading functions\n",
    "\n",
    "\n",
    "def get_filenames(*dirs, extension=\"csv\"):\n",
    "    rkhs = []\n",
    "    l2 = []\n",
    "    non_gp = []\n",
    "    real = []\n",
    "\n",
    "    dirs_lst = [d for d in dirs if d is not None]\n",
    "\n",
    "    for dirname in dirs_lst:\n",
    "        for file in os.listdir(dirname):\n",
    "            filename = file.split(\".\")[0]\n",
    "            ext = file.split(\".\")[1]\n",
    "\n",
    "            if SMOOTHING and \"smoothing\" not in filename:\n",
    "                continue\n",
    "            if not SMOOTHING and \"smoothing\" in filename:\n",
    "                continue\n",
    "\n",
    "            if P_FREE and \"p_free\" not in filename:\n",
    "                continue\n",
    "            if not P_FREE and \"p_free\" in filename:\n",
    "                continue\n",
    "\n",
    "            if METHOD in filename and KIND_STR in filename and ext == extension:\n",
    "                if KIND == \"linear\" and \"gbm\" in filename:\n",
    "                    non_gp += [dirname + filename]\n",
    "                elif KIND == \"logistic\" and \"mixture\" in filename:\n",
    "                    non_gp += [dirname + filename]\n",
    "                elif \"rkhs\" in filename:\n",
    "                    rkhs += [dirname + filename]\n",
    "                elif \"l2\" in filename:\n",
    "                    l2 += [dirname + filename]\n",
    "                else:\n",
    "                    real += [dirname + filename]\n",
    "\n",
    "    # Sort\n",
    "    for dataset in [rkhs, l2, non_gp, real]:\n",
    "        dataset.sort(key=lambda x: x.split(\"/\")[-1])\n",
    "\n",
    "    return rkhs, l2, non_gp, real"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "2d03ee7b",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-21T18:48:02.240178Z",
     "start_time": "2022-09-21T18:48:02.234047Z"
    },
    "code_folding": [],
    "execution": {
     "iopub.execute_input": "2024-07-30T11:11:20.065825Z",
     "iopub.status.busy": "2024-07-30T11:11:20.065640Z",
     "iopub.status.idle": "2024-07-30T11:11:20.078182Z",
     "shell.execute_reply": "2024-07-30T11:11:20.077577Z",
     "shell.execute_reply.started": "2024-07-30T11:11:20.065806Z"
    }
   },
   "outputs": [],
   "source": [
    "# -- Data reading\n",
    "\n",
    "rkhs, l2, non_gp, real = get_filenames(DIR)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "713b4d3b",
   "metadata": {
    "heading_collapsed": true
   },
   "source": [
    "### Score tables"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "bbcd08cd",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-21T17:00:48.191180Z",
     "start_time": "2022-09-21T17:00:48.184003Z"
    },
    "execution": {
     "iopub.execute_input": "2024-07-30T11:11:20.078974Z",
     "iopub.status.busy": "2024-07-30T11:11:20.078773Z",
     "iopub.status.idle": "2024-07-30T11:11:20.086924Z",
     "shell.execute_reply": "2024-07-30T11:11:20.086300Z",
     "shell.execute_reply.started": "2024-07-30T11:11:20.078955Z"
    },
    "hidden": true
   },
   "outputs": [],
   "source": [
    "# -- Table configuration\n",
    "\n",
    "PRINT_LATEX = False  # whether to print tables in Latex format\n",
    "dataname = \"l2\"  # 'rkhs', 'l2', 'non_gp' or 'real'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "dfd8634f",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-21T17:00:48.233717Z",
     "start_time": "2022-09-21T17:00:48.193854Z"
    },
    "code_folding": [
     0
    ],
    "execution": {
     "iopub.execute_input": "2024-07-30T11:11:20.087873Z",
     "iopub.status.busy": "2024-07-30T11:11:20.087669Z",
     "iopub.status.idle": "2024-07-30T11:11:20.114517Z",
     "shell.execute_reply": "2024-07-30T11:11:20.113661Z",
     "shell.execute_reply.started": "2024-07-30T11:11:20.087852Z"
    },
    "hidden": true
   },
   "outputs": [],
   "source": [
    "# -- Create tables\n",
    "\n",
    "dfs_bayesian = []\n",
    "dfs_var_sel = []\n",
    "\n",
    "if dataname == \"rkhs\":\n",
    "    data_all = rkhs\n",
    "elif dataname == \"l2\":\n",
    "    data_all = l2\n",
    "elif dataname == \"non_gp\":\n",
    "    data_all = non_gp\n",
    "else:\n",
    "    data_all = real\n",
    "\n",
    "for name in data_all:\n",
    "    kernel = get_name_table(name)\n",
    "    df = pd.read_csv(name + \".csv\")\n",
    "    score_lst = [f\"Mean {SCORE_STR}\", f\"SD {SCORE_STR}\"]\n",
    "\n",
    "    # Convert float to strings\n",
    "    df[score_lst] = df[score_lst].map(lambda x: \"{:.3f}\".format(x))\n",
    "\n",
    "    # Join Mean and SD\n",
    "    df[kernel] = df[score_lst[0]] + \" (\" + df[score_lst[1]] + \")\"\n",
    "    df = df[[\"Estimator\", kernel]]\n",
    "\n",
    "    df_bayesian, df_var_sel = separate_df(df, \"Estimator\")\n",
    "    dfs_bayesian.append(df_bayesian)\n",
    "    dfs_var_sel.append(df_var_sel)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "d3d72566",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-21T17:00:48.280077Z",
     "start_time": "2022-09-21T17:00:48.236205Z"
    },
    "code_folding": [
     0
    ],
    "execution": {
     "iopub.execute_input": "2024-07-30T11:11:20.115547Z",
     "iopub.status.busy": "2024-07-30T11:11:20.115333Z",
     "iopub.status.idle": "2024-07-30T11:11:20.181141Z",
     "shell.execute_reply": "2024-07-30T11:11:20.180550Z",
     "shell.execute_reply.started": "2024-07-30T11:11:20.115526Z"
    },
    "hidden": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--> Linear emcee L2 <--\n",
      "\n"
     ]
    },
    {
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       "      <td id=\"T_deecb_row5_col2\" class=\"data row5 col2\" >0.720 (0.031)</td>\n",
       "      <td id=\"T_deecb_row5_col3\" class=\"data row5 col3\" >0.716 (0.032)</td>\n",
       "      <td id=\"T_deecb_row5_col4\" class=\"data row5 col4\" >0.727 (0.031)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td id=\"T_deecb_row6_col0\" class=\"data row6 col0\" >pls+ridge</td>\n",
       "      <td id=\"T_deecb_row6_col1\" class=\"data row6 col1\" >0.719 (0.033)</td>\n",
       "      <td id=\"T_deecb_row6_col2\" class=\"data row6 col2\" >0.728 (0.046)</td>\n",
       "      <td id=\"T_deecb_row6_col3\" class=\"data row6 col3\" >0.720 (0.033)</td>\n",
       "      <td id=\"T_deecb_row6_col4\" class=\"data row6 col4\" >0.730 (0.031)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <td id=\"T_deecb_row7_col0\" class=\"data row7 col0\" >rmh+ridge</td>\n",
       "      <td id=\"T_deecb_row7_col1\" class=\"data row7 col1\" >0.753 (0.029)</td>\n",
       "      <td id=\"T_deecb_row7_col2\" class=\"data row7 col2\" >0.713 (0.030)</td>\n",
       "      <td id=\"T_deecb_row7_col3\" class=\"data row7 col3\" >0.791 (0.037)</td>\n",
       "      <td id=\"T_deecb_row7_col4\" class=\"data row7 col4\" >0.812 (0.027)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x774aa3331d30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# -- Show tables\n",
    "\n",
    "print(\n",
    "    \"--> \"\n",
    "    + KIND.capitalize()\n",
    "    + \" \"\n",
    "    + METHOD\n",
    "    + \" \"\n",
    "    + dataname.upper()\n",
    "    + (\" (smooth)\" if SMOOTHING else \"\")\n",
    "    + \" <--\\n\"\n",
    ")\n",
    "\n",
    "for dfs in [dfs_bayesian, dfs_var_sel]:\n",
    "    df_merge = reduce(lambda df1, df2: df1.merge(df2, on=\"Estimator\", how=\"inner\"), dfs)\n",
    "    if PRINT_LATEX:\n",
    "        print(df_merge.to_latex(index=False))\n",
    "    else:\n",
    "        display(df_merge.style.hide(axis='index'))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "09199b4b",
   "metadata": {},
   "source": [
    "### Score graphs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "7ff79585",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-30T11:11:20.182333Z",
     "iopub.status.busy": "2024-07-30T11:11:20.181985Z",
     "iopub.status.idle": "2024-07-30T11:11:20.314406Z",
     "shell.execute_reply": "2024-07-30T11:11:20.313825Z",
     "shell.execute_reply.started": "2024-07-30T11:11:20.182312Z"
    }
   },
   "outputs": [],
   "source": [
    "# -- Plotting functions\n",
    "\n",
    "\n",
    "def plot_df(df, ax=None, legend=False, limit=None):\n",
    "    if ax is None:\n",
    "        fig, ax = plt.subplots()\n",
    "    ax.margins(x=0.05)\n",
    "\n",
    "    estimator = df[\"Estimator\"].to_numpy(dtype=str)\n",
    "\n",
    "    # Quick fix for name\n",
    "    for i, name in enumerate(estimator):\n",
    "        if \"logistic\" in name:\n",
    "            estimator[i] = estimator[i].replace(\"+logistic\", \"+log\")\n",
    "\n",
    "    score = df[\"Mean \" + SCORE_STR].to_numpy()\n",
    "    sd = df[\"SD \" + SCORE_STR].to_numpy()\n",
    "    ours_idx = []\n",
    "\n",
    "    # Outliers\n",
    "    if KIND == \"linear\":\n",
    "        if limit is None:\n",
    "            q3, q1 = np.percentile(score + sd, [75, 25])\n",
    "            limit = q3 + 1.5 * (q3 - q1)  # IQR\n",
    "\n",
    "        outliers_idx = np.where(score > limit)[0]\n",
    "        outliers = estimator[outliers_idx]\n",
    "        symbol = \">\"\n",
    "    else:\n",
    "        if limit is None:\n",
    "            q3, q1 = np.percentile(score - sd, [75, 25])\n",
    "            limit = q1 - 1.5 * (q3 - q1)  # IQR\n",
    "        outliers_idx = np.where(score < limit)[0]\n",
    "        outliers = estimator[outliers_idx]\n",
    "        symbol = \"<\"\n",
    "\n",
    "    # Plot our models\n",
    "    all_outliers_ours = True\n",
    "    for idx, idx_where in enumerate(np.char.find(estimator, METHOD)):\n",
    "        if idx_where < 0:\n",
    "            continue\n",
    "        ours_idx.append(idx)\n",
    "\n",
    "        if estimator[idx] in outliers:\n",
    "            handles_ours_outliers = ax.plot(\n",
    "                limit, estimator[idx], symbol, color=COLORS(0), label=\"Our methods\"\n",
    "            )\n",
    "        else:\n",
    "            all_outliers_ours = False\n",
    "            handles_ours = ax.errorbar(\n",
    "                score[idx],\n",
    "                estimator[idx],\n",
    "                xerr=sd[idx],\n",
    "                color=COLORS(0),\n",
    "                ecolor=COLORS(0),\n",
    "                lw=1,\n",
    "                fmt=\"o\",\n",
    "                markersize=5,\n",
    "                label=\"Our methods\",\n",
    "            )\n",
    "\n",
    "    estimator_rest = np.delete(estimator, ours_idx)\n",
    "    score_rest = np.delete(score, ours_idx)\n",
    "    sd_rest = np.delete(sd, ours_idx)\n",
    "\n",
    "    # Plot comparison models\n",
    "    all_outliers_rest = True\n",
    "    for e, s, sdd in zip(estimator_rest, score_rest, sd_rest):\n",
    "        if e in outliers:\n",
    "            handles_rest_outliers = ax.plot(\n",
    "                limit, e, symbol, color=COLORS(1), label=\"Reference methods\"\n",
    "            )\n",
    "        else:\n",
    "            all_outliers_rest = False\n",
    "            handles_rest = ax.errorbar(\n",
    "                s,\n",
    "                e,\n",
    "                xerr=sdd,\n",
    "                color=COLORS(1),\n",
    "                ecolor=COLORS(1),\n",
    "                lw=1,\n",
    "                fmt=\"o\",\n",
    "                markersize=5,\n",
    "                label=\"Reference methods\",\n",
    "            )\n",
    "\n",
    "    if all_outliers_ours:\n",
    "        handles_ours = handles_ours_outliers\n",
    "    if all_outliers_rest:\n",
    "        handles_rest = handles_rest_outliers\n",
    "\n",
    "    handles = [handles_ours, handles_rest]\n",
    "\n",
    "    score_rest_no_outliers = np.delete(score, np.concatenate((outliers_idx, ours_idx)))\n",
    "    if len(score_rest_no_outliers) > 0:\n",
    "        handles_mean = ax.axvline(\n",
    "            x=score_rest_no_outliers.mean(),\n",
    "            color=COLORS(1),\n",
    "            ls=\"--\",\n",
    "            lw=1.3,\n",
    "            label=\"Mean of reference methods\",\n",
    "        )\n",
    "        handles += [handles_mean]\n",
    "\n",
    "    if legend:\n",
    "        ax.legend(handles=handles, bbox_to_anchor=(1, 1))\n",
    "\n",
    "    return handles\n",
    "\n",
    "\n",
    "def plot_data_all(\n",
    "    data,\n",
    "    data_type_name,\n",
    "    limit=None,\n",
    "    legend=True,\n",
    "    save=False,\n",
    "    figsize=[None, None],\n",
    "    bbox_legend=[None, None],\n",
    "):\n",
    "    n_data = len(data)\n",
    "    if limit is None:\n",
    "        limit = [(None, None)] * n_data\n",
    "\n",
    "    if figsize[0] is None:\n",
    "        figsize[0] = 2.5 * n_data\n",
    "    if figsize[1] is None:\n",
    "        figsize[1] = 7\n",
    "    if bbox_legend[0] is None:\n",
    "        if n_data == 2:\n",
    "            bbox_legend[0] = 1.15\n",
    "        elif n_data == 3:\n",
    "            bbox_legend[0] = 1.80\n",
    "        elif n_data == 4:\n",
    "            bbox_legend[0] = 2.45\n",
    "        else:\n",
    "            bbox_legend[0] = 1.0\n",
    "    if bbox_legend[1] is None:\n",
    "        bbox_legend[1] = -0.5\n",
    "\n",
    "    fig = plt.figure(figsize=figsize)\n",
    "    subfigs = fig.subfigures(nrows=1, ncols=n_data)\n",
    "    if n_data == 1:\n",
    "        subfigs = [subfigs]\n",
    "\n",
    "    for j, (dataname, l) in enumerate(zip(data, limit)):\n",
    "        df = pd.read_csv(dataname + \".csv\")\n",
    "        dataname_short, real_data = get_name_graph(dataname)\n",
    "\n",
    "        # Get different strategies and order by score\n",
    "        df_bayesian, df_var_sel = separate_df(df, \"Estimator\")\n",
    "\n",
    "        ##\n",
    "        # PLOT\n",
    "        ##\n",
    "\n",
    "        subfig = subfigs[j]\n",
    "        subfig.suptitle(dataname_short, fontweight=\"semibold\", y=0.96)\n",
    "        ax1, ax2 = subfig.subplots(nrows=2, ncols=1, sharex=True)\n",
    "\n",
    "        if j != 0 and j != n_data - 1:\n",
    "            ax1.set_yticks([])\n",
    "            ax2.set_yticks([])\n",
    "        if j != 0 and j == n_data - 1:\n",
    "            ax1.yaxis.tick_right()\n",
    "            ax2.yaxis.tick_right()\n",
    "\n",
    "        kind_title = \"Regression\" if KIND == \"linear\" else \"Classification\"\n",
    "        ax1.set_title(f\"{kind_title} methods\")\n",
    "        ax2.set_title(\"Two-stage methods\")\n",
    "        ax1.set_xlabel(SCORE_STR_FULL)\n",
    "        ax2.set_xlabel(SCORE_STR_FULL)\n",
    "        ax1.tick_params(labelbottom=True)\n",
    "        ax1.xaxis.set_major_locator(plt.MaxNLocator(4))\n",
    "        ax1.xaxis.set_major_formatter(plt.FormatStrFormatter(\"%0.2f\"))\n",
    "\n",
    "        _ = plot_df(df_bayesian, ax1, legend=False, limit=l[0])\n",
    "        handles = plot_df(df_var_sel, ax2, limit=l[1])\n",
    "\n",
    "        if legend and j == 0:\n",
    "            ax2.legend(\n",
    "                loc=\"lower center\",\n",
    "                handles=handles,\n",
    "                ncol=3,\n",
    "                fancybox=True,\n",
    "                shadow=True,\n",
    "                bbox_to_anchor=bbox_legend,\n",
    "            )\n",
    "\n",
    "        subfig.subplots_adjust(hspace=0.4)\n",
    "\n",
    "    if save:\n",
    "        filename_save = (\n",
    "            (\"reg_\" if KIND == \"linear\" else \"clf_\")\n",
    "            + METHOD\n",
    "            + \"_\"\n",
    "            + data_type_name\n",
    "            + (\"_p_free\" if \"p_free\" in dataname else \"\")\n",
    "            + (\"_smooth\" if \"smoothing\" in dataname else \"\")\n",
    "            + \".pdf\"\n",
    "        )\n",
    "        plt.rcParams.update({\n",
    "            \"legend.fontsize\": FONT_SIZE_LATEX,\n",
    "            \"axes.titlesize\": FONT_SIZE_LATEX - 1,\n",
    "            \"axes.labelsize\": FONT_SIZE_LATEX,\n",
    "            \"xtick.labelsize\": FONT_SIZE_LATEX,\n",
    "            \"ytick.labelsize\": FONT_SIZE_LATEX,\n",
    "        })\n",
    "        plt.savefig(DIR_SAVE + filename_save, bbox_inches=\"tight\", backend=\"pgf\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "b53df28c",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-30T11:11:20.315313Z",
     "iopub.status.busy": "2024-07-30T11:11:20.315114Z",
     "iopub.status.idle": "2024-07-30T11:11:20.336453Z",
     "shell.execute_reply": "2024-07-30T11:11:20.335741Z",
     "shell.execute_reply.started": "2024-07-30T11:11:20.315293Z"
    }
   },
   "outputs": [],
   "source": [
    "# -- Plot configuration\n",
    "\n",
    "dataname = \"l2\"\n",
    "LIMIT_EXPERIMENTS = True  # whether to use pre-defined limits for the plots\n",
    "bbox_legend = [None, None]\n",
    "height = 7"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "f36dcb73",
   "metadata": {
    "execution": {
     "iopub.execute_input": "2024-07-30T11:11:20.337397Z",
     "iopub.status.busy": "2024-07-30T11:11:20.337205Z",
     "iopub.status.idle": "2024-07-30T11:11:20.345922Z",
     "shell.execute_reply": "2024-07-30T11:11:20.345421Z",
     "shell.execute_reply.started": "2024-07-30T11:11:20.337376Z"
    }
   },
   "outputs": [],
   "source": [
    "# -- Data limits for plotting\n",
    "\n",
    "if LIMIT_EXPERIMENTS:\n",
    "    if KIND == \"linear\":\n",
    "        if dataname == \"rkhs\":\n",
    "            limit = [(None, None), (None, None), (None, None), (1, None)]\n",
    "        elif dataname == \"l2\":\n",
    "            limit = [(None, None), (None, None), (None, 0.90), (0.95, None)]\n",
    "        elif dataname == \"non_gp\":\n",
    "            limit = [(None, 0.9), (None, None)]\n",
    "        else:  # real\n",
    "            limit = [(None, None), (None, None), (8, 8)]\n",
    "    else:  # logistic\n",
    "        if dataname == \"rkhs\":\n",
    "            limit = [(None, None), (None, None), (None, None), (0.6, None)]\n",
    "        elif dataname == \"l2\":\n",
    "            limit = [(0.4, None), (None, None), (None, None), (None, None)]\n",
    "        elif dataname == \"non_gp\":\n",
    "            limit = [(None, None), (None, None)]\n",
    "        else:  # real\n",
    "            limit = [(None, None), (None, None), (None, None)]\n",
    "else:  # custom limits\n",
    "    limit = [(None, None), (None, None), (None, None), (None, None)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "0c31815c",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-21T18:49:26.334214Z",
     "start_time": "2022-09-21T18:49:24.734812Z"
    },
    "code_folding": [],
    "execution": {
     "iopub.execute_input": "2024-07-30T11:11:20.346904Z",
     "iopub.status.busy": "2024-07-30T11:11:20.346713Z",
     "iopub.status.idle": "2024-07-30T11:11:21.375222Z",
     "shell.execute_reply": "2024-07-30T11:11:21.374619Z",
     "shell.execute_reply.started": "2024-07-30T11:11:20.346880Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "--> Linear emcee L2 <--\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x700 with 8 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# -- Plot score graphs\n",
    "\n",
    "if dataname == \"rkhs\":\n",
    "    data_all = rkhs\n",
    "elif dataname == \"l2\":\n",
    "    data_all = l2\n",
    "elif dataname == \"non_gp\":\n",
    "    data_all = non_gp\n",
    "else:\n",
    "    data_all = real\n",
    "\n",
    "print(\n",
    "    \"--> \"\n",
    "    + KIND.capitalize()\n",
    "    + \" \"\n",
    "    + METHOD\n",
    "    + \" \"\n",
    "    + dataname.upper()\n",
    "    + (\" (smooth)\" if SMOOTHING else \"\")\n",
    "    + \" <--\"\n",
    ")\n",
    "\n",
    "plot_data_all(\n",
    "    data_all,\n",
    "    dataname,\n",
    "    limit=limit,\n",
    "    legend=True,\n",
    "    figsize=[None, height],  # Default width is 2.5*n_data\n",
    "    bbox_legend=bbox_legend,\n",
    "    save=SAVE_FIG,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a2906bf4",
   "metadata": {},
   "source": [
    "### CV data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "69c2d3c4",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-21T17:00:51.588272Z",
     "start_time": "2022-09-21T17:00:51.584074Z"
    },
    "execution": {
     "iopub.execute_input": "2024-07-30T11:11:21.376214Z",
     "iopub.status.busy": "2024-07-30T11:11:21.376006Z",
     "iopub.status.idle": "2024-07-30T11:11:21.379813Z",
     "shell.execute_reply": "2024-07-30T11:11:21.379252Z",
     "shell.execute_reply.started": "2024-07-30T11:11:21.376192Z"
    }
   },
   "outputs": [],
   "source": [
    "# -- Read data in .npz format\n",
    "\n",
    "rkhs, l2, non_gp, real = get_filenames(DIR, extension=\"npz\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "216da39d",
   "metadata": {
    "ExecuteTime": {
     "end_time": "2022-09-21T17:00:51.605721Z",
     "start_time": "2022-09-21T17:00:51.590951Z"
    },
    "execution": {
     "iopub.execute_input": "2024-07-30T11:11:21.380783Z",
     "iopub.status.busy": "2024-07-30T11:11:21.380467Z",
     "iopub.status.idle": "2024-07-30T11:11:21.463246Z",
     "shell.execute_reply": "2024-07-30T11:11:21.462599Z",
     "shell.execute_reply.started": "2024-07-30T11:11:21.380763Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Keys:\n",
      "score_ref_all\n",
      "score_bayesian_all\n",
      "score_var_sel_all\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "array([{'posterior_mean': array([[[-1.5637, -1.5622, -1.5345, -1.5332, -1.5424, -1.5591, -1.568 ],\n",
       "               [-0.9037, -0.8906, -0.949 , -0.9048, -0.9691, -0.973 , -1.0017],\n",
       "               [-0.9748, -0.8933, -0.9275, -0.9099, -1.1402, -0.9146, -0.9999],\n",
       "               [-0.8166, -0.8325, -0.8831, -0.8409, -0.9409, -0.9592, -0.9863],\n",
       "               [-0.9043, -0.7942, -0.813 , -0.7869, -0.7466, -0.7408, -1.3404],\n",
       "               [-0.8402, -0.8304, -0.8485, -0.8852, -0.8143, -0.8307, -0.8565],\n",
       "               [-0.8652, -0.7999, -0.7931, -0.8361, -0.7889, -0.7911, -0.8142],\n",
       "               [-0.8839, -0.8214, -0.8821, -0.9112, -0.8739, -0.8424, -0.8654],\n",
       "               [-1.118 , -0.8693, -0.834 , -0.8325, -0.8146, -0.8415, -1.497 ],\n",
       "               [-0.9441, -0.8679, -0.8102, -0.805 , -0.8263, -0.807 , -0.9726]],\n",
       "\n",
       "              [[-1.6068, -1.6044, -1.619 , -1.6175, -1.6266, -1.611 , -1.6155],\n",
       "               [-1.0408, -0.9877, -1.0512, -0.9893, -1.1387, -1.3514, -1.3532],\n",
       "               [-0.8617, -0.8446, -0.9118, -0.9124, -0.9534, -1.1998, -1.4134],\n",
       "               [-0.8381, -0.892 , -0.8597, -0.8722, -0.8553, -0.8205, -0.8527],\n",
       "               [-0.8707, -0.8948, -0.932 , -0.8503, -0.8852, -0.8694, -0.8634],\n",
       "               [-0.8919, -0.8552, -0.8476, -0.9282, -0.8564, -0.8592, -0.844 ],\n",
       "               [-0.9477, -0.9838, -0.9338, -0.9209, -0.8773, -0.9408, -0.8775],\n",
       "               [-0.9554, -0.8832, -0.9057, -0.9074, -0.8777, -0.8675, -0.835 ],\n",
       "               [-0.8755, -0.8589, -0.9289, -0.8497, -0.8541, -0.8152, -0.89  ],\n",
       "               [-0.8862, -0.9029, -1.1296, -0.8733, -0.8383, -0.8321, -0.9119]],\n",
       "\n",
       "              [[-1.4927, -1.5118, -1.4776, -1.479 , -1.4744, -1.4723, -1.5212],\n",
       "               [-0.7944, -0.8693, -0.8089, -0.8366, -0.852 , -0.8441, -1.0469],\n",
       "               [-0.6879, -0.6032, -0.6274, -0.5875, -0.6906, -0.6946, -0.8131],\n",
       "               [-0.7768, -0.8153, -0.8695, -0.8112, -0.8784, -0.8564, -0.8659],\n",
       "               [-0.6839, -0.7451, -0.7121, -0.8415, -0.671 , -0.7465, -0.8835],\n",
       "               [-0.6838, -0.7799, -0.6736, -0.6348, -0.7954, -1.115 , -0.6624],\n",
       "               [-0.7574, -0.8626, -0.9685, -0.8011, -0.7305, -0.7171, -0.7097],\n",
       "               [-0.8209, -0.9012, -0.9735, -0.8976, -0.6992, -0.7174, -0.7067],\n",
       "               [-0.8206, -1.0724, -0.7912, -0.7701, -0.7556, -0.744 , -0.7244],\n",
       "               [-0.8396, -0.7345, -0.7975, -0.7846, -0.7716, -0.7613, -0.8415]],\n",
       "\n",
       "              [[-1.5355, -1.4953, -1.4725, -1.5214, -1.6851, -1.5644, -1.5645],\n",
       "               [-0.8405, -0.8184, -0.8456, -0.831 , -0.8318, -1.0802, -0.8919],\n",
       "               [-0.7414, -0.7217, -0.7248, -0.7439, -0.9103, -0.8648, -0.8983],\n",
       "               [-0.8064, -0.7286, -0.7546, -0.7359, -0.7608, -0.8813, -0.9751],\n",
       "               [-0.7685, -0.8293, -0.7295, -0.795 , -0.718 , -0.7574, -0.7182],\n",
       "               [-0.7625, -0.7811, -0.7601, -0.6968, -0.7167, -0.7242, -0.7275],\n",
       "               [-0.7824, -0.8015, -0.7826, -0.7504, -0.7907, -0.7817, -0.7565],\n",
       "               [-0.8191, -0.7742, -0.6888, -0.7922, -0.6919, -0.7236, -0.7459],\n",
       "               [-0.7499, -0.8409, -0.7524, -0.7229, -0.7002, -0.6983, -0.9121],\n",
       "               [-0.7911, -0.976 , -0.9167, -0.8314, -0.7586, -1.0033, -1.142 ]],\n",
       "\n",
       "              [[-2.0191, -2.0958, -2.0442, -1.9579, -2.0378, -2.0977, -2.0419],\n",
       "               [-1.1015, -1.1375, -1.1295, -1.1616, -1.4029, -1.8053, -1.9259],\n",
       "               [-0.8259, -0.8538, -0.8431, -0.8668, -0.9675, -0.9762, -1.031 ],\n",
       "               [-0.8664, -0.8968, -0.9195, -0.9751, -1.1255, -1.3828, -1.4074],\n",
       "               [-0.7745, -0.833 , -0.8057, -0.8263, -0.7707, -0.8106, -0.8814],\n",
       "               [-0.9178, -0.8111, -1.0959, -0.9148, -1.0184, -1.0286, -1.0422],\n",
       "               [-0.8514, -0.8551, -0.815 , -0.845 , -0.8835, -0.8978, -0.9108],\n",
       "               [-1.0557, -0.9736, -0.9021, -0.9435, -0.9345, -1.0078, -1.0029],\n",
       "               [-0.9274, -0.8999, -0.8198, -0.8197, -0.8367, -0.8611, -0.9439],\n",
       "               [-0.8407, -0.9957, -0.818 , -0.7853, -0.8916, -0.8058, -0.8795]]]), 'mean': array([[[-1.9186, -2.1086, -1.5341, -1.5337, -1.9593, -1.9393, -2.8615],\n",
       "               [-0.9826, -0.8919, -1.292 , -1.0037, -1.7232, -1.7241, -1.5527],\n",
       "               [-2.8642, -1.7085, -0.9473, -0.883 , -3.4932, -1.6728, -0.895 ],\n",
       "               [-1.2652, -1.3199, -1.3547, -1.4375, -1.2362, -0.9898, -1.6294],\n",
       "               [-1.3331, -1.1926, -0.8469, -1.4137, -0.7706, -1.3762, -1.7565],\n",
       "               [-1.4957, -1.7698, -0.9524, -1.7607, -0.8008, -0.8194, -1.5753],\n",
       "               [-1.4702, -1.4239, -1.1991, -1.6072, -0.7829, -0.7955, -0.8494],\n",
       "               [-2.637 , -0.8826, -0.9256, -2.1013, -1.0814, -1.0339, -1.0471],\n",
       "               [-2.2984, -2.5062, -1.91  , -0.9916, -0.8294, -0.9663, -1.9448],\n",
       "               [-1.8941, -1.9803, -1.3562, -1.7172, -1.5676, -0.8833, -1.0057]],\n",
       "\n",
       "              [[-1.8094, -1.7896, -1.826 , -1.7978, -1.8056, -1.8014, -1.7796],\n",
       "               [-1.6072, -1.5151, -1.6041, -1.1013, -1.139 , -1.7605, -1.3532],\n",
       "               [-1.8166, -0.8929, -1.3356, -1.5559, -1.4316, -2.2189, -2.8236],\n",
       "               [-1.0989, -1.3042, -1.4903, -1.4405, -0.8605, -1.588 , -0.8555],\n",
       "               [-1.1871, -1.5593, -1.7193, -1.5024, -0.9027, -0.8816, -0.883 ],\n",
       "               [-0.9846, -1.1103, -1.02  , -1.6161, -0.8629, -1.3634, -0.8394],\n",
       "               [-1.6453, -2.3677, -1.0696, -1.5525, -0.8572, -1.5271, -0.9144],\n",
       "               [-3.6081, -1.8197, -1.6332, -1.2748, -1.3966, -0.8652, -1.004 ],\n",
       "               [-3.1096, -1.7424, -4.0297, -2.2217, -1.1077, -1.407 , -1.4784],\n",
       "               [-2.3407, -1.825 , -1.9311, -1.4185, -0.8883, -0.8177, -1.2202]],\n",
       "\n",
       "              [[-1.8763, -1.8346, -1.4764, -1.4762, -1.4764, -1.9645, -2.3845],\n",
       "               [-1.308 , -1.5229, -1.5434, -1.2127, -1.2321, -1.2209, -2.4508],\n",
       "               [-0.6691, -0.9075, -0.6127, -0.5857, -1.0777, -1.1692, -1.8221],\n",
       "               [-1.2516, -0.7872, -1.1844, -1.6334, -1.2616, -0.8562, -0.8907],\n",
       "               [-0.9572, -1.3455, -1.3471, -1.2268, -0.6825, -1.7534, -1.7603],\n",
       "               [-1.3206, -2.0299, -1.2245, -1.5843, -1.1249, -1.8658, -0.7181],\n",
       "               [-3.0445, -2.6923, -3.1132, -1.2307, -1.0963, -1.0928, -0.6655],\n",
       "               [-2.3314, -2.2353, -2.3973, -1.4218, -1.0014, -0.7658, -0.9015],\n",
       "               [-2.2342, -2.466 , -1.8555, -1.9629, -0.7592, -0.7867, -0.8624],\n",
       "               [-2.4127, -2.1258, -2.1318, -1.4109, -0.9131, -0.9324, -0.9315]],\n",
       "\n",
       "              [[-2.2847, -2.1334, -1.4735, -1.9465, -3.0252, -2.3308, -1.7959],\n",
       "               [-1.5546, -1.7173, -1.108 , -1.5275, -1.401 , -1.9418, -1.9068],\n",
       "               [-1.1445, -1.2573, -1.7911, -1.3356, -1.6365, -1.3192, -0.9398],\n",
       "               [-2.0436, -0.9375, -1.8535, -1.4792, -1.3754, -1.3411, -2.1407],\n",
       "               [-1.8034, -1.3603, -1.5677, -1.9723, -1.4533, -1.4965, -0.7917],\n",
       "               [-1.1575, -1.9292, -1.8354, -0.7416, -0.7403, -0.7497, -0.7545],\n",
       "               [-1.7609, -1.7361, -1.4872, -1.8154, -0.8693, -0.9814, -0.9033],\n",
       "               [-1.7254, -2.292 , -1.0731, -2.2118, -1.003 , -0.8241, -0.7852],\n",
       "               [-1.8279, -2.947 , -1.3196, -1.8941, -0.8573, -0.8039, -1.0189],\n",
       "               [-3.1598, -1.3704, -3.6267, -2.8984, -2.8072, -2.3189, -1.8511]],\n",
       "\n",
       "              [[-2.251 , -2.0985, -2.1957, -2.8772, -2.1956, -2.0974, -2.2016],\n",
       "               [-1.284 , -1.4944, -1.5067, -1.2688, -1.7637, -2.3596, -2.0644],\n",
       "               [-0.8617, -1.1785, -1.1671, -0.8601, -0.937 , -1.2304, -1.0298],\n",
       "               [-0.8875, -1.4154, -1.7982, -1.7741, -1.3146, -1.3795, -1.3972],\n",
       "               [-1.1689, -1.1672, -1.127 , -1.1311, -1.1726, -0.8662, -1.5571],\n",
       "               [-1.5448, -2.1295, -2.4021, -1.1802, -1.054 , -1.0757, -1.0954],\n",
       "               [-1.6557, -1.146 , -1.4816, -1.4328, -0.9282, -0.9312, -0.9586],\n",
       "               [-4.2762, -1.888 , -4.0245, -4.3469, -4.009 , -2.2059, -0.9456],\n",
       "               [-1.8241, -1.4801, -1.0136, -1.1082, -0.7976, -0.8896, -1.0854],\n",
       "               [-1.6801, -1.149 , -1.492 , -1.6637, -1.0803, -0.8596, -0.9234]]]), 'median': array([[[-1.5325, -1.5353, -1.5341, -1.5338, -1.5351, -1.5327, -1.5332],\n",
       "               [-0.8907, -0.892 , -0.8963, -0.895 , -0.9342, -0.9817, -1.0034],\n",
       "               [-0.8777, -0.8866, -0.8871, -0.8861, -0.8837, -0.8904, -0.8998],\n",
       "               [-0.7984, -0.796 , -0.8472, -0.812 , -0.8987, -0.9736, -0.9934],\n",
       "               [-0.7932, -0.7618, -0.7733, -0.8126, -0.7701, -0.7844, -0.7756],\n",
       "               [-0.8071, -0.809 , -0.8329, -0.7915, -0.7949, -0.8144, -0.809 ],\n",
       "               [-0.7996, -0.8505, -0.7895, -0.7967, -0.8344, -0.8114, -0.8206],\n",
       "               [-1.0818, -0.9624, -0.9675, -0.9809, -0.9776, -0.8486, -0.9775],\n",
       "               [-1.4929, -0.7959, -1.1308, -0.8048, -0.8288, -0.8236, -1.6917],\n",
       "               [-1.3026, -0.9456, -0.7467, -0.7474, -0.762 , -0.8431, -0.9836]],\n",
       "\n",
       "              [[-1.5959, -1.5954, -1.5956, -1.5944, -1.5948, -1.5945, -1.5947],\n",
       "               [-0.9469, -0.9448, -0.9478, -0.9683, -1.1395, -1.3193, -1.3579],\n",
       "               [-0.8632, -0.8412, -0.8441, -0.8651, -0.8902, -0.9541, -0.9844],\n",
       "               [-0.8548, -0.8365, -0.8416, -0.8628, -0.8506, -0.8507, -0.8666],\n",
       "               [-0.8665, -0.8642, -0.8789, -0.8309, -0.8792, -0.8912, -0.8595],\n",
       "               [-0.8551, -0.8248, -0.8273, -0.8491, -0.8582, -0.8559, -0.849 ],\n",
       "               [-1.0288, -1.2635, -1.0181, -0.9163, -0.855 , -0.887 , -0.8909],\n",
       "               [-2.0112, -1.0879, -0.9587, -0.9307, -0.8761, -0.8631, -0.9844],\n",
       "               [-3.559 , -0.8455, -4.4892, -1.0171, -0.8424, -0.8683, -0.8054],\n",
       "               [-0.9186, -0.912 , -1.4329, -1.2169, -0.9141, -0.8713, -1.0173]],\n",
       "\n",
       "              [[-1.4764, -1.4763, -1.4764, -1.4762, -1.4764, -1.4763, -1.4762],\n",
       "               [-0.8264, -0.8257, -0.8198, -0.8163, -0.8109, -0.8235, -0.8307],\n",
       "               [-0.5881, -0.5796, -0.5834, -0.5969, -0.6417, -0.7005, -0.7426],\n",
       "               [-0.7371, -0.7502, -0.9275, -0.8918, -0.8708, -0.8558, -0.8588],\n",
       "               [-0.6158, -0.6783, -0.6541, -0.6655, -0.6716, -0.7115, -0.7381],\n",
       "               [-0.7271, -0.7997, -0.6815, -0.7253, -0.9028, -0.792 , -0.6441],\n",
       "               [-1.2316, -1.1262, -0.7671, -0.7158, -0.6581, -0.6642, -0.6857],\n",
       "               [-1.0162, -0.9866, -0.988 , -0.7805, -0.9932, -0.7433, -0.8209],\n",
       "               [-0.9222, -0.9017, -0.7323, -0.7823, -0.8394, -0.7863, -0.706 ],\n",
       "               [-1.1848, -0.8266, -1.014 , -0.949 , -0.7994, -0.8204, -0.825 ]],\n",
       "\n",
       "              [[-1.4768, -1.4732, -1.4737, -1.4749, -1.4815, -1.4711, -1.4748],\n",
       "               [-0.8351, -0.8351, -0.8356, -0.8352, -0.8364, -0.8443, -0.8531],\n",
       "               [-0.7245, -0.6999, -0.7273, -0.7335, -0.809 , -0.8761, -0.9313],\n",
       "               [-0.7077, -0.7072, -0.7124, -0.7008, -0.7117, -0.7241, -0.7357],\n",
       "               [-0.7279, -0.7116, -0.6807, -0.7538, -0.7248, -0.7789, -0.7659],\n",
       "               [-0.7106, -0.7171, -0.6952, -0.7378, -0.7204, -0.7282, -0.7275],\n",
       "               [-1.3409, -1.0178, -1.2053, -0.7917, -0.8285, -0.8561, -0.8389],\n",
       "               [-0.8616, -0.8874, -0.762 , -0.8724, -1.0028, -0.7709, -0.7392],\n",
       "               [-0.9488, -1.1862, -0.95  , -0.8933, -0.7567, -0.798 , -0.88  ],\n",
       "               [-1.4226, -1.8055, -2.6797, -1.6037, -0.9515, -1.2697, -1.8897]],\n",
       "\n",
       "              [[-2.0966, -2.0977, -2.0979, -2.0962, -2.0994, -2.0962, -2.0969],\n",
       "               [-1.1146, -1.1231, -1.1236, -1.178 , -1.4944, -1.8977, -1.9912],\n",
       "               [-0.8447, -0.8543, -0.8526, -0.8716, -0.9684, -1.0249, -1.0282],\n",
       "               [-0.8889, -0.8823, -0.9123, -1.0002, -1.18  , -1.3773, -1.4344],\n",
       "               [-0.8285, -0.9069, -0.831 , -0.8925, -0.839 , -0.8215, -0.8581],\n",
       "               [-0.9475, -0.772 , -0.9303, -0.9185, -1.0151, -1.0502, -1.0606],\n",
       "               [-0.9055, -0.912 , -0.8363, -0.8955, -0.8933, -0.943 , -0.9498],\n",
       "               [-1.8044, -1.3136, -1.6184, -1.9293, -1.1973, -1.4313, -1.078 ],\n",
       "               [-0.8627, -1.1174, -1.1782, -0.9065, -0.9239, -0.8876, -1.0782],\n",
       "               [-0.8007, -0.8915, -0.8441, -0.8853, -0.9473, -0.8699, -0.9405]]]), 'mode': array([[[-1.527 , -1.5322, -1.5275, -1.5333, -1.5357, -1.5251, -1.5407],\n",
       "               [-0.884 , -0.895 , -0.8977, -0.9009, -0.9286, -0.9844, -1.0005],\n",
       "               [-0.8643, -0.8756, -0.88  , -0.9077, -0.9032, -0.8869, -0.8993],\n",
       "               [-0.8008, -0.8003, -0.9405, -0.817 , -0.9533, -0.9617, -0.9673],\n",
       "               [-0.8157, -0.7672, -0.8708, -0.7518, -0.787 , -0.7741, -0.7858],\n",
       "               [-0.802 , -0.764 , -0.8625, -0.7924, -0.7945, -0.8173, -0.8081],\n",
       "               [-0.9156, -0.8103, -0.8695, -0.8957, -0.8468, -0.7994, -0.8057],\n",
       "               [-0.9189, -0.8704, -1.118 , -0.9926, -1.0568, -0.877 , -0.9561],\n",
       "               [-1.594 , -1.046 , -2.1733, -1.0021, -0.8618, -0.8976, -1.4765],\n",
       "               [-1.9511, -0.9149, -1.1955, -0.8712, -0.7548, -0.8853, -0.9813]],\n",
       "\n",
       "              [[-1.6003, -1.5952, -1.597 , -1.5907, -1.5943, -1.5934, -1.5936],\n",
       "               [-0.9467, -0.9256, -0.9472, -0.9672, -1.1348, -1.3088, -1.3607],\n",
       "               [-0.8962, -0.8451, -0.8234, -0.8568, -0.8802, -0.928 , -0.9757],\n",
       "               [-0.8627, -0.8794, -0.8476, -0.8504, -0.8421, -0.8587, -0.8336],\n",
       "               [-0.8639, -0.849 , -0.8249, -0.8161, -0.8583, -0.8785, -0.843 ],\n",
       "               [-0.9206, -0.8543, -0.8547, -0.8666, -0.871 , -0.8675, -0.8645],\n",
       "               [-0.9934, -1.8906, -1.0718, -0.8934, -1.1446, -1.0573, -0.9007],\n",
       "               [-1.034 , -1.7894, -0.963 , -0.9721, -1.0018, -0.8541, -0.9319],\n",
       "               [-3.7193, -0.8343, -3.7331, -3.3054, -0.8656, -0.9895, -1.3332],\n",
       "               [-0.8211, -0.9165, -1.6134, -1.0153, -0.9134, -0.9141, -0.8721]],\n",
       "\n",
       "              [[-1.4766, -1.4763, -1.4775, -1.4767, -1.4762, -1.4766, -1.4766],\n",
       "               [-0.8306, -0.822 , -0.8137, -0.8145, -0.8041, -0.8215, -0.8274],\n",
       "               [-0.5951, -0.5871, -0.5758, -0.5877, -0.6401, -0.7016, -0.7586],\n",
       "               [-0.6704, -0.6837, -1.1004, -0.8601, -0.8644, -0.8503, -0.8558],\n",
       "               [-0.6538, -0.6757, -0.6963, -0.7304, -0.7068, -0.6915, -0.731 ],\n",
       "               [-0.825 , -0.6465, -0.6634, -0.7436, -1.3286, -0.8231, -0.6642],\n",
       "               [-1.4942, -0.8749, -0.8451, -0.8764, -0.6729, -0.6834, -0.7797],\n",
       "               [-1.085 , -0.94  , -1.02  , -0.8948, -0.9238, -1.1692, -0.7736],\n",
       "               [-0.8058, -0.971 , -0.8158, -0.692 , -0.7801, -0.7904, -0.7282],\n",
       "               [-1.033 , -0.7658, -0.9186, -0.7017, -0.7124, -0.7885, -0.7717]],\n",
       "\n",
       "              [[-1.4648, -1.4745, -1.4848, -1.4595, -1.4735, -1.466 , -1.494 ],\n",
       "               [-0.8356, -0.8358, -0.8353, -0.8355, -0.8361, -0.8446, -0.8526],\n",
       "               [-0.7137, -0.7015, -0.7067, -0.739 , -0.8013, -0.8709, -0.9136],\n",
       "               [-0.7357, -0.6966, -0.7352, -0.702 , -0.7101, -0.7215, -0.7227],\n",
       "               [-0.7295, -0.7032, -0.7096, -0.7689, -0.7841, -0.7842, -0.7264],\n",
       "               [-0.7488, -0.7206, -0.7133, -0.7132, -0.7166, -0.7145, -0.726 ],\n",
       "               [-1.7476, -1.4296, -1.4865, -0.8035, -0.8171, -0.8589, -0.6963],\n",
       "               [-0.7967, -0.9514, -0.7999, -1.0515, -1.0029, -0.8015, -0.8309],\n",
       "               [-1.2562, -1.7201, -0.8373, -0.7673, -0.8769, -0.9486, -1.0146],\n",
       "               [-0.7866, -1.083 , -1.463 , -4.0807, -4.324 , -1.2338, -3.2291]],\n",
       "\n",
       "              [[-2.1034, -2.0926, -2.1073, -2.0881, -2.1099, -2.092 , -2.1057],\n",
       "               [-1.1331, -1.1265, -1.1245, -1.2045, -1.4558, -1.8974, -1.9574],\n",
       "               [-0.8561, -0.8571, -0.8442, -0.8844, -0.9829, -1.0258, -1.0261],\n",
       "               [-0.9325, -0.895 , -0.9421, -1.0607, -1.1932, -1.3441, -1.4325],\n",
       "               [-0.8618, -1.098 , -0.8392, -1.0669, -0.9398, -0.7949, -0.8083],\n",
       "               [-0.9552, -0.891 , -0.9337, -0.9281, -0.9697, -0.9851, -0.9953],\n",
       "               [-1.0225, -0.8907, -0.7814, -0.8484, -0.9849, -1.01  , -1.0366],\n",
       "               [-1.243 , -0.8709, -6.4414, -5.3652, -6.5593, -3.9839, -1.206 ],\n",
       "               [-1.0302, -0.9646, -1.358 , -1.2825, -0.8318, -0.9269, -0.9911],\n",
       "               [-0.7612, -1.0025, -0.9994, -0.7903, -0.835 , -0.8552, -1.2821]]]), 'p': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], 'eta': [0.0001, 0.001, 0.01, 0.1, 1, 10, 100]},\n",
       "       {'posterior_mean': array([[[-1.7634, -1.751 , -1.7332, -1.7167, -1.7099, -1.7225, -1.7699],\n",
       "               [-1.0036, -0.9606, -0.9646, -0.9729, -0.9596, -1.1851, -1.517 ],\n",
       "               [-0.9095, -0.8728, -0.8278, -0.9518, -0.9647, -1.0465, -1.0567],\n",
       "               [-0.8481, -0.8742, -0.8479, -0.8259, -0.8744, -0.8916, -0.9227],\n",
       "               [-0.8404, -0.8159, -0.8423, -0.7836, -0.8202, -0.8488, -0.8669],\n",
       "               [-0.8898, -0.8718, -0.8623, -0.9114, -0.9056, -0.9421, -0.9693],\n",
       "               [-0.8761, -0.8576, -0.7942, -0.7897, -0.8184, -0.7863, -0.8395],\n",
       "               [-0.8844, -0.9669, -0.8816, -0.8542, -0.8401, -0.8882, -1.0219],\n",
       "               [-0.8991, -0.8186, -0.9328, -0.8523, -0.8303, -0.9027, -0.96  ],\n",
       "               [-1.024 , -0.8138, -0.9467, -0.8257, -0.8818, -0.8951, -1.0077]],\n",
       "\n",
       "              [[-1.746 , -1.7552, -1.7935, -1.7188, -1.7457, -1.7007, -1.6938],\n",
       "               [-1.0622, -1.0645, -1.0714, -1.0665, -1.2424, -1.4764, -1.5057],\n",
       "               [-0.8826, -0.9744, -0.9149, -0.9142, -1.0644, -1.1149, -1.1967],\n",
       "               [-0.9712, -0.9811, -0.9419, -0.9427, -1.0535, -0.9521, -1.1506],\n",
       "               [-0.8902, -0.9174, -0.9126, -0.923 , -0.9275, -0.9069, -1.1087],\n",
       "               [-0.904 , -0.9039, -0.9249, -0.9461, -0.8858, -0.8966, -0.9164],\n",
       "               [-0.9899, -0.9328, -0.8948, -0.9122, -0.8964, -0.9236, -1.0583],\n",
       "               [-1.0407, -1.0031, -0.9309, -0.9028, -0.9055, -0.9289, -0.9137],\n",
       "               [-0.8949, -0.9954, -0.9155, -0.9654, -0.9679, -0.9528, -1.1762],\n",
       "               [-0.959 , -1.0662, -0.9547, -0.9018, -0.9446, -1.0133, -1.4155]],\n",
       "\n",
       "              [[-1.2434, -1.4099, -1.2487, -1.2641, -1.2938, -1.268 , -1.311 ],\n",
       "               [-0.7581, -0.7969, -0.7962, -0.7871, -0.8495, -0.998 , -0.9522],\n",
       "               [-0.6164, -0.6212, -0.6415, -0.6199, -0.6303, -0.6204, -0.643 ],\n",
       "               [-0.6121, -0.633 , -0.6309, -0.626 , -0.6808, -0.5984, -0.6178],\n",
       "               [-0.6779, -0.7075, -0.721 , -0.6266, -0.6987, -0.7507, -0.7639],\n",
       "               [-0.6534, -0.6532, -0.6094, -0.5997, -0.6122, -0.616 , -0.6182],\n",
       "               [-0.6968, -0.6784, -0.6494, -0.5968, -0.603 , -0.6045, -0.6149],\n",
       "               [-0.7279, -0.6794, -0.6507, -0.6537, -0.6118, -0.6419, -0.7849],\n",
       "               [-0.6629, -0.6798, -0.6672, -0.612 , -0.6735, -0.8216, -0.6814],\n",
       "               [-0.6658, -0.6251, -0.6609, -0.6097, -0.5972, -0.6464, -0.7078]],\n",
       "\n",
       "              [[-1.4785, -1.5078, -1.4785, -1.4804, -1.4743, -1.4931, -1.4769],\n",
       "               [-0.7416, -0.857 , -0.8236, -0.7508, -1.0483, -1.0578, -1.1147],\n",
       "               [-0.5475, -0.7125, -0.556 , -0.6397, -0.8963, -1.0808, -1.1358],\n",
       "               [-0.4686, -0.5008, -0.4909, -0.4921, -0.5834, -0.8419, -1.039 ],\n",
       "               [-0.456 , -0.4949, -0.5211, -0.524 , -0.5386, -0.5477, -0.5453],\n",
       "               [-0.4544, -0.4873, -0.5392, -0.4957, -0.4784, -0.4822, -0.5329],\n",
       "               [-0.675 , -0.4647, -0.7453, -0.532 , -0.5533, -0.5531, -0.5781],\n",
       "               [-0.5491, -0.6534, -0.5232, -0.4973, -0.5128, -0.5564, -0.5555],\n",
       "               [-0.7597, -0.617 , -0.5132, -0.5397, -0.5329, -0.5247, -1.0588],\n",
       "               [-0.5675, -0.547 , -0.5033, -0.5089, -0.4762, -0.5293, -0.653 ]],\n",
       "\n",
       "              [[-1.7543, -1.7606, -1.7869, -1.7285, -1.8336, -1.7674, -1.7825],\n",
       "               [-1.1911, -1.0888, -1.2331, -1.251 , -1.3884, -1.6413, -1.7372],\n",
       "               [-0.8071, -0.8703, -0.8364, -0.8631, -0.8236, -0.7683, -1.0157],\n",
       "               [-0.9119, -0.8583, -0.8584, -0.8838, -1.0657, -1.3692, -1.4237],\n",
       "               [-0.8348, -0.851 , -0.8468, -0.8496, -0.8789, -0.9795, -0.8378],\n",
       "               [-1.0205, -0.7268, -0.7624, -0.7591, -0.9198, -0.7597, -0.7525],\n",
       "               [-0.8217, -0.7965, -0.9001, -0.7781, -0.7123, -0.7551, -0.7638],\n",
       "               [-0.8017, -0.8321, -0.8722, -0.8591, -0.7873, -0.8411, -0.7826],\n",
       "               [-0.9256, -0.8714, -0.8288, -0.8131, -0.8664, -0.8191, -0.9365],\n",
       "               [-0.9698, -0.792 , -0.8815, -0.7928, -0.712 , -0.7846, -0.9034]]]), 'mean': array([[[-2.5478, -2.2184, -2.1748, -2.4973, -1.7086, -2.113 , -2.0956],\n",
       "               [-1.0031, -1.2539, -0.9645, -0.9752, -0.957 , -1.9641, -1.6935],\n",
       "               [-1.3233, -2.7803, -1.2446, -1.6907, -1.5366, -1.0579, -1.6102],\n",
       "               [-1.2103, -2.1333, -1.1486, -1.2907, -1.298 , -1.3154, -1.4197],\n",
       "               [-1.9296, -1.1396, -1.1531, -1.2279, -0.8282, -0.8277, -0.899 ],\n",
       "               [-1.5468, -2.0832, -1.7239, -2.1467, -0.9949, -0.9862, -1.0097],\n",
       "               [-1.5575, -1.6578, -2.1301, -0.9855, -0.9585, -0.87  , -0.8231],\n",
       "               [-2.1986, -1.6564, -2.5992, -1.9767, -1.2747, -1.0511, -1.4102],\n",
       "               [-2.1424, -2.2963, -2.311 , -1.6229, -1.1084, -0.9826, -1.9325],\n",
       "               [-3.0326, -1.5249, -2.1004, -2.0367, -0.9702, -1.0001, -1.3246]],\n",
       "\n",
       "              [[-1.7459, -1.7478, -3.6604, -2.3367, -1.7571, -1.9954, -2.7603],\n",
       "               [-1.9778, -1.2969, -1.0882, -1.2182, -1.2428, -1.471 , -2.4902],\n",
       "               [-0.9411, -1.5703, -1.0924, -0.9079, -2.2358, -1.6693, -1.5221],\n",
       "               [-1.3558, -1.3322, -1.144 , -1.0195, -1.1167, -1.3766, -1.118 ],\n",
       "               [-1.194 , -1.8315, -1.8999, -1.8926, -0.9328, -1.3345, -1.3335],\n",
       "               [-1.0532, -1.2751, -2.0273, -1.9736, -1.9143, -0.9673, -0.9895],\n",
       "               [-2.6724, -1.5353, -2.3769, -0.991 , -1.3463, -0.9575, -1.2256],\n",
       "               [-2.7196, -2.4279, -2.1413, -0.9173, -0.9313, -0.9808, -0.9023],\n",
       "               [-1.1254, -1.8283, -1.9672, -1.5021, -1.2444, -1.771 , -1.2596],\n",
       "               [-1.8994, -2.2588, -1.3493, -1.3477, -1.8909, -1.4841, -1.8587]],\n",
       "\n",
       "              [[-1.247 , -2.2157, -1.2477, -1.8376, -1.6531, -1.6564, -2.0166],\n",
       "               [-1.3632, -1.2709, -0.9632, -0.9467, -1.3499, -1.8156, -0.9553],\n",
       "               [-0.6262, -1.6508, -1.2661, -1.2929, -1.256 , -1.2696, -0.6484],\n",
       "               [-1.3253, -0.7783, -0.9342, -1.3203, -1.2522, -1.3922, -0.6499],\n",
       "               [-0.7589, -2.3443, -1.3205, -1.0317, -1.0127, -1.0632, -1.032 ],\n",
       "               [-1.8792, -1.2988, -1.3211, -1.1875, -0.6204, -0.6298, -0.6334],\n",
       "               [-1.4118, -1.7491, -0.9768, -1.3524, -0.7634, -0.7336, -0.6623],\n",
       "               [-1.4309, -1.8854, -1.4584, -1.3411, -1.3503, -0.7585, -0.8951],\n",
       "               [-1.7613, -1.5186, -1.7404, -0.7101, -1.328 , -1.4636, -0.6609],\n",
       "               [-1.6996, -1.8946, -1.5819, -0.937 , -0.7282, -0.6463, -0.7439]],\n",
       "\n",
       "              [[-1.4819, -1.9211, -1.4774, -2.5032, -1.6456, -1.6534, -1.6435],\n",
       "               [-1.1151, -2.2816, -1.3912, -0.7674, -2.991 , -1.0529, -1.6262],\n",
       "               [-1.0283, -2.4848, -1.0656, -0.8382, -1.2276, -1.0802, -1.1418],\n",
       "               [-0.9455, -1.3041, -0.4963, -0.9353, -1.3777, -0.8128, -1.0242],\n",
       "               [-0.5689, -0.9527, -1.3484, -1.57  , -0.541 , -0.5438, -0.593 ],\n",
       "               [-1.6168, -1.6389, -1.4715, -0.9753, -0.5106, -0.5019, -0.785 ],\n",
       "               [-1.944 , -1.3518, -1.9238, -1.0622, -0.5923, -0.5631, -0.6204],\n",
       "               [-1.5054, -1.988 , -1.2083, -1.3749, -1.0466, -1.0153, -0.8185],\n",
       "               [-1.848 , -1.66  , -2.2633, -1.4312, -0.6298, -0.6717, -1.5978],\n",
       "               [-1.804 , -1.9019, -2.1182, -0.8189, -0.5815, -0.6368, -0.9173]],\n",
       "\n",
       "              [[-1.7592, -1.9184, -1.915 , -2.4733, -2.1314, -2.1706, -2.0745],\n",
       "               [-2.1862, -1.9079, -2.0628, -2.216 , -1.6167, -2.6093, -2.4482],\n",
       "               [-0.9755, -0.8217, -1.0058, -0.8228, -0.9176, -0.7557, -2.204 ],\n",
       "               [-1.0754, -1.8828, -1.1059, -0.8924, -1.0497, -1.6806, -1.4273],\n",
       "               [-1.2652, -1.2986, -1.4618, -1.8241, -1.4201, -1.8219, -0.8366],\n",
       "               [-1.7634, -0.9352, -1.8845, -0.926 , -1.62  , -0.7678, -0.7399],\n",
       "               [-4.1884, -1.2615, -4.5088, -3.8511, -1.691 , -0.7589, -0.7166],\n",
       "               [-1.519 , -1.2396, -2.1126, -0.8681, -0.8167, -0.9002, -0.818 ],\n",
       "               [-1.7862, -1.5817, -1.5775, -1.5244, -1.5033, -0.8221, -1.0575],\n",
       "               [-2.9374, -1.6426, -2.4708, -1.6819, -0.7443, -1.0594, -0.9753]]]), 'median': array([[[-1.7045, -1.7079, -1.7098, -1.7141, -1.7081, -1.7077, -1.7081],\n",
       "               [-0.9672, -0.9632, -0.9643, -0.9649, -0.9569, -0.987 , -1.0533],\n",
       "               [-0.9187, -0.978 , -0.8674, -0.9673, -1.0178, -1.0437, -1.0551],\n",
       "               [-0.8549, -0.8644, -0.8695, -0.8639, -0.864 , -0.8758, -0.8808],\n",
       "               [-0.8078, -0.8751, -0.9735, -0.8241, -0.8219, -0.8126, -0.874 ],\n",
       "               [-0.8901, -0.9195, -0.8278, -0.9329, -0.9766, -1.0101, -1.0112],\n",
       "               [-0.9587, -1.0473, -0.8607, -0.7587, -0.9548, -0.7756, -0.8047],\n",
       "               [-1.8685, -4.4276, -1.2685, -1.502 , -0.9881, -0.95  , -1.3021],\n",
       "               [-1.0052, -1.2582, -1.1231, -0.8702, -0.9877, -0.9769, -1.0563],\n",
       "               [-0.9559, -0.862 , -0.9114, -0.8393, -0.982 , -0.9551, -1.2297]],\n",
       "\n",
       "              [[-1.7453, -1.7483, -1.747 , -1.7467, -1.7485, -1.7466, -1.7486],\n",
       "               [-1.025 , -1.026 , -1.0254, -1.0495, -1.2433, -1.4701, -1.529 ],\n",
       "               [-0.9194, -0.9238, -0.9201, -0.9352, -1.0488, -1.1913, -1.2556],\n",
       "               [-0.9501, -0.9886, -0.9541, -0.9686, -0.9788, -0.9407, -0.9545],\n",
       "               [-0.9119, -0.9346, -0.9136, -0.9487, -0.958 , -0.932 , -0.9794],\n",
       "               [-0.9578, -0.9473, -0.9168, -0.9357, -0.8687, -0.9335, -0.9237],\n",
       "               [-0.9646, -0.9131, -0.8985, -0.9654, -0.9213, -0.9321, -1.2769],\n",
       "               [-0.969 , -1.1602, -0.903 , -0.9528, -0.9211, -0.978 , -0.9557],\n",
       "               [-0.9182, -1.0398, -1.7495, -0.9964, -7.2449, -0.9226, -1.2543],\n",
       "               [-1.4184, -0.9828, -0.9944, -0.9378, -1.3696, -1.1687, -1.5659]],\n",
       "\n",
       "              [[-1.2474, -1.2455, -1.2476, -1.2492, -1.2475, -1.2464, -1.2445],\n",
       "               [-0.8078, -0.808 , -0.8093, -0.8036, -0.8448, -0.9347, -0.9554],\n",
       "               [-0.6257, -0.6253, -0.6259, -0.6275, -0.6361, -0.6479, -0.652 ],\n",
       "               [-0.5961, -0.6002, -0.6091, -0.6255, -0.6175, -0.6154, -0.6166],\n",
       "               [-0.6111, -0.6364, -0.7924, -0.8558, -0.6909, -0.7361, -0.7379],\n",
       "               [-0.6023, -0.6078, -0.6276, -0.6226, -0.6191, -0.6238, -0.6264],\n",
       "               [-0.7459, -0.7796, -0.6672, -0.7208, -0.6149, -0.6125, -0.6146],\n",
       "               [-3.5251, -0.6883, -0.7137, -0.7479, -0.6651, -0.6319, -0.7934],\n",
       "               [-0.7463, -1.7331, -0.7113, -0.6056, -0.6513, -0.63  , -0.6815],\n",
       "               [-0.771 , -0.8536, -1.0319, -0.7152, -0.6496, -0.6497, -0.7282]],\n",
       "\n",
       "              [[-1.4821, -1.4811, -1.4772, -1.4801, -1.4808, -1.4823, -1.4789],\n",
       "               [-0.7599, -0.7592, -0.7618, -0.7608, -0.896 , -1.053 , -1.0982],\n",
       "               [-0.497 , -0.7607, -0.5028, -0.6299, -0.9097, -1.0946, -1.1427],\n",
       "               [-0.533 , -0.525 , -0.562 , -0.5104, -0.5759, -0.836 , -1.0147],\n",
       "               [-0.4774, -0.4617, -0.501 , -0.5654, -0.5684, -0.5334, -0.5424],\n",
       "               [-0.8296, -0.8452, -0.5107, -0.4689, -0.5157, -0.502 , -0.4993],\n",
       "               [-0.5376, -0.5844, -0.6845, -0.5923, -0.5663, -0.5787, -0.561 ],\n",
       "               [-0.7867, -0.8975, -1.1126, -0.9277, -0.5984, -0.7893, -0.6099],\n",
       "               [-4.2021, -0.8825, -1.4281, -0.8426, -0.6092, -0.5425, -1.3085],\n",
       "               [-1.3835, -1.0349, -0.9836, -0.5896, -0.5458, -0.5973, -0.7068]],\n",
       "\n",
       "              [[-1.7592, -1.7593, -1.7598, -1.7596, -1.7588, -1.7598, -1.7609],\n",
       "               [-1.0198, -0.9639, -1.0714, -1.0867, -1.3396, -1.6334, -1.6668],\n",
       "               [-0.7875, -0.7934, -0.7936, -0.7872, -0.778 , -0.7903, -0.8101],\n",
       "               [-0.8251, -0.7966, -0.8117, -0.9061, -0.999 , -1.455 , -1.4344],\n",
       "               [-0.8469, -0.8006, -0.8275, -0.8033, -0.8336, -0.8235, -0.8555],\n",
       "               [-0.8262, -0.7705, -0.8353, -0.813 , -0.7971, -0.8058, -0.7964],\n",
       "               [-1.185 , -0.892 , -2.3978, -1.0295, -1.0583, -0.7619, -0.7998],\n",
       "               [-0.8929, -1.1172, -0.6511, -0.853 , -0.8418, -0.9901, -0.8031],\n",
       "               [-1.2594, -0.8715, -0.7652, -0.927 , -0.851 , -0.9944, -0.8689],\n",
       "               [-1.6918, -0.9927, -0.9414, -0.8127, -0.839 , -0.9304, -0.85  ]]]), 'mode': array([[[ -1.714 ,  -1.7088,  -1.7085,  -1.7298,  -1.7074,  -1.7182,\n",
       "                 -1.7084],\n",
       "               [ -0.9607,  -0.972 ,  -0.9628,  -0.9705,  -0.9561,  -0.9821,\n",
       "                 -1.0561],\n",
       "               [ -0.8911,  -1.0978,  -0.8802,  -0.9207,  -1.0001,  -1.0458,\n",
       "                 -1.0615],\n",
       "               [ -0.8395,  -0.8859,  -0.9193,  -0.8755,  -0.883 ,  -0.9146,\n",
       "                 -0.8789],\n",
       "               [ -0.9165,  -0.8588,  -0.9784,  -0.8256,  -0.8166,  -0.8655,\n",
       "                 -0.8711],\n",
       "               [ -0.9482,  -1.3218,  -0.9891,  -1.3807,  -0.9568,  -0.9667,\n",
       "                 -0.9855],\n",
       "               [ -0.8822,  -0.8834,  -0.9549,  -0.7545,  -1.1951,  -0.7219,\n",
       "                 -0.817 ],\n",
       "               [ -0.9153,  -1.0368,  -1.8854,  -1.5869,  -1.1551,  -0.8657,\n",
       "                 -1.3158],\n",
       "               [ -1.0872,  -1.194 ,  -1.0437,  -0.9641,  -1.1502,  -0.9034,\n",
       "                 -1.2487],\n",
       "               [ -2.2437,  -0.9636,  -1.1654,  -0.9441,  -0.8655,  -0.9397,\n",
       "                 -1.0574]],\n",
       "\n",
       "              [[ -1.7387,  -1.7545,  -1.7441,  -1.7509,  -1.7489,  -1.7358,\n",
       "                 -1.7517],\n",
       "               [ -1.0273,  -1.0313,  -1.0276,  -1.0561,  -1.2522,  -1.4677,\n",
       "                 -1.5303],\n",
       "               [ -0.9173,  -0.9157,  -0.9239,  -0.9417,  -1.056 ,  -1.213 ,\n",
       "                 -1.2784],\n",
       "               [ -0.9577,  -1.0144,  -0.9433,  -0.9673,  -0.9781,  -0.9417,\n",
       "                 -0.9558],\n",
       "               [ -0.9635,  -0.9141,  -0.8946,  -0.9342,  -0.9753,  -0.9492,\n",
       "                 -0.9792],\n",
       "               [ -0.9383,  -0.9828,  -0.9859,  -0.9348,  -0.8724,  -0.9218,\n",
       "                 -0.9977],\n",
       "               [ -0.9787,  -1.0063,  -0.9077,  -0.9494,  -0.962 ,  -0.9482,\n",
       "                 -1.1397],\n",
       "               [ -0.9244,  -1.0279,  -0.9236,  -0.9763,  -0.9737,  -0.9355,\n",
       "                 -0.9541],\n",
       "               [ -0.9226,  -1.1169,  -1.8935,  -1.0491, -12.5468,  -1.0031,\n",
       "                 -1.155 ],\n",
       "               [ -1.1258,  -1.8596,  -0.9126,  -0.925 ,  -1.5464,  -1.2412,\n",
       "                 -1.3553]],\n",
       "\n",
       "              [[ -1.2476,  -1.2548,  -1.2336,  -1.2395,  -1.2478,  -1.2484,\n",
       "                 -1.2509],\n",
       "               [ -0.8096,  -0.8112,  -0.8138,  -0.8036,  -0.8485,  -0.935 ,\n",
       "                 -0.956 ],\n",
       "               [ -0.6293,  -0.6254,  -0.6253,  -0.631 ,  -0.6344,  -0.6496,\n",
       "                 -0.6515],\n",
       "               [ -0.641 ,  -0.6675,  -0.6275,  -0.6573,  -0.6528,  -0.6512,\n",
       "                 -0.671 ],\n",
       "               [ -0.6384,  -0.7323,  -0.6789,  -0.7873,  -0.8648,  -0.8943,\n",
       "                 -0.7633],\n",
       "               [ -0.5851,  -0.6108,  -0.6253,  -0.6199,  -0.6123,  -0.6241,\n",
       "                 -0.6282],\n",
       "               [ -0.7275,  -0.7447,  -0.7304,  -0.8149,  -0.6109,  -0.5904,\n",
       "                 -0.6585],\n",
       "               [ -0.7774,  -0.644 ,  -0.8376,  -0.7098,  -0.6715,  -0.699 ,\n",
       "                 -0.8049],\n",
       "               [ -0.7306,  -1.0443,  -0.8582,  -0.6852,  -0.7421,  -0.6766,\n",
       "                 -0.6957],\n",
       "               [ -0.9636,  -0.8694,  -1.048 ,  -0.8236,  -0.6581,  -1.0447,\n",
       "                 -1.171 ]],\n",
       "\n",
       "              [[ -1.489 ,  -1.4806,  -1.4799,  -1.506 ,  -1.4918,  -1.4687,\n",
       "                 -1.4866],\n",
       "               [ -0.7541,  -0.7434,  -0.7594,  -0.7605,  -0.8753,  -1.0522,\n",
       "                 -1.1029],\n",
       "               [ -0.5079,  -0.7703,  -0.5171,  -0.6481,  -0.8857,  -1.0743,\n",
       "                 -1.1344],\n",
       "               [ -0.6962,  -0.4477,  -0.5848,  -0.4902,  -0.5675,  -0.8117,\n",
       "                 -1.0225],\n",
       "               [ -0.5521,  -0.5215,  -0.4807,  -0.7711,  -0.647 ,  -0.6468,\n",
       "                 -0.6088],\n",
       "               [ -0.9136,  -0.5707,  -0.6837,  -0.5308,  -0.5154,  -0.4982,\n",
       "                 -0.4921],\n",
       "               [ -0.6004,  -0.637 ,  -0.645 ,  -0.5162,  -0.5378,  -0.5388,\n",
       "                 -0.5321],\n",
       "               [ -0.812 ,  -0.6096,  -1.4494,  -1.1143,  -0.5729,  -1.3829,\n",
       "                 -0.5851],\n",
       "               [ -7.9086,  -0.619 ,  -1.8693,  -0.7539,  -0.607 ,  -0.5837,\n",
       "                 -1.0308],\n",
       "               [ -0.9253,  -0.8297,  -0.8286,  -0.5249,  -0.6689,  -0.6069,\n",
       "                 -0.8288]],\n",
       "\n",
       "              [[ -1.7593,  -1.7527,  -1.7613,  -1.7628,  -1.7572,  -1.761 ,\n",
       "                 -1.767 ],\n",
       "               [ -0.9612,  -0.9467,  -0.9566,  -1.0188,  -1.3506,  -1.6426,\n",
       "                 -1.6601],\n",
       "               [ -0.7723,  -0.7658,  -0.7826,  -0.7836,  -0.7843,  -0.7885,\n",
       "                 -0.8147],\n",
       "               [ -0.8254,  -0.811 ,  -0.8263,  -0.8612,  -1.1198,  -1.3755,\n",
       "                 -1.4474],\n",
       "               [ -0.8065,  -0.835 ,  -0.8655,  -0.7908,  -0.9134,  -0.9247,\n",
       "                 -0.9256],\n",
       "               [ -0.9025,  -0.7146,  -0.7669,  -0.7507,  -0.7621,  -0.8043,\n",
       "                 -0.8186],\n",
       "               [ -4.0501,  -0.9257,  -3.7122,  -3.183 ,  -2.9967,  -0.7857,\n",
       "                 -1.1769],\n",
       "               [ -0.9877,  -0.9157,  -0.9907,  -0.8767,  -0.7793,  -0.863 ,\n",
       "                 -0.8165],\n",
       "               [ -1.1841,  -0.9847,  -1.0404,  -1.0268,  -0.81  ,  -1.0424,\n",
       "                 -0.7157],\n",
       "               [ -1.1607,  -0.9035,  -0.6629,  -0.6762,  -0.9742,  -1.3952,\n",
       "                 -1.1622]]]), 'p': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], 'eta': [0.0001, 0.001, 0.01, 0.1, 1, 10, 100]}                                                   ,\n",
       "       {'posterior_mean': array([[[-1.6827, -1.6737, -1.6598, -1.7349, -1.6807, -1.6716, -1.6965],\n",
       "               [-0.8999, -0.9414, -0.9093, -1.011 , -1.3529, -1.5424, -1.5363],\n",
       "               [-0.9908, -0.6572, -0.6723, -0.661 , -0.7287, -0.794 , -0.7528],\n",
       "               [-0.6716, -0.6509, -0.6662, -0.6519, -0.7069, -0.6448, -0.6435],\n",
       "               [-0.71  , -0.711 , -0.6603, -0.7232, -0.8314, -0.7486, -0.8451],\n",
       "               [-0.7655, -0.6577, -0.6722, -0.6631, -0.6672, -0.6605, -0.7418],\n",
       "               [-0.6981, -0.653 , -0.6645, -0.6518, -0.7468, -0.7148, -0.7385],\n",
       "               [-0.8085, -0.6923, -0.6822, -0.64  , -0.6401, -0.8136, -0.6501],\n",
       "               [-0.932 , -0.7333, -0.6905, -0.6525, -0.6745, -0.6738, -0.6345],\n",
       "               [-0.7048, -0.6886, -0.6609, -0.6378, -0.646 , -0.634 , -0.8713]],\n",
       "\n",
       "              [[-1.4105, -1.4433, -1.4418, -1.4197, -1.3554, -1.4079, -1.4149],\n",
       "               [-0.9401, -0.9881, -0.9661, -0.951 , -0.9734, -1.0653, -1.0837],\n",
       "               [-0.8284, -0.8012, -0.8284, -0.8478, -0.8823, -0.8749, -0.9126],\n",
       "               [-0.8129, -0.8513, -0.8075, -0.8169, -0.8364, -0.8879, -0.8932],\n",
       "               [-0.987 , -0.9767, -0.8163, -0.8208, -0.8233, -0.8712, -0.8927],\n",
       "               [-0.8031, -0.8417, -0.825 , -0.8331, -0.7987, -0.7952, -0.8   ],\n",
       "               [-0.8038, -0.8664, -0.8197, -0.833 , -0.8727, -0.8481, -0.8508],\n",
       "               [-0.8514, -0.8577, -0.8452, -0.8609, -0.9272, -0.7821, -0.8323],\n",
       "               [-0.8666, -0.9039, -0.8425, -0.8497, -0.8045, -0.8031, -1.2363],\n",
       "               [-0.7989, -0.8517, -0.8536, -0.8863, -0.9091, -0.8301, -1.42  ]],\n",
       "\n",
       "              [[-1.8523, -1.835 , -1.8265, -1.8237, -1.8241, -1.8333, -1.8729],\n",
       "               [-1.0817, -0.969 , -1.0084, -0.9341, -0.8664, -1.1306, -1.0328],\n",
       "               [-0.6801, -0.7456, -0.6929, -0.7009, -0.6934, -0.8075, -0.8064],\n",
       "               [-0.8327, -0.9095, -0.7631, -0.8039, -0.9817, -0.9816, -0.9509],\n",
       "               [-0.9239, -0.8686, -0.6807, -0.7029, -0.7569, -0.7781, -0.8423],\n",
       "               [-0.8913, -0.7921, -0.8742, -0.8974, -0.994 , -1.0739, -1.0648],\n",
       "               [-1.0218, -0.8129, -0.8248, -1.0407, -0.7979, -0.8938, -0.8986],\n",
       "               [-0.8451, -0.692 , -0.7464, -0.7294, -0.6674, -0.7092, -0.8519],\n",
       "               [-1.2672, -0.8063, -0.92  , -0.8403, -0.7349, -0.9237, -0.9059],\n",
       "               [-0.8425, -0.8337, -0.9169, -0.7985, -0.7447, -0.7214, -0.6507]],\n",
       "\n",
       "              [[-1.3056, -1.304 , -1.3634, -1.3178, -1.305 , -1.3122, -1.3031],\n",
       "               [-0.7745, -0.7449, -0.7871, -0.7379, -0.789 , -0.8251, -1.0134],\n",
       "               [-0.6376, -0.6603, -1.1778, -0.6703, -0.6978, -0.8557, -0.8047],\n",
       "               [-0.6639, -0.7172, -0.678 , -0.7224, -0.9463, -0.9802, -0.9818],\n",
       "               [-0.6826, -0.7845, -0.6719, -0.6466, -0.6504, -0.7039, -0.6996],\n",
       "               [-0.7569, -0.6798, -0.6575, -0.6779, -0.6629, -0.6695, -0.8037],\n",
       "               [-0.6452, -0.6364, -0.6523, -0.6462, -0.6432, -0.6356, -0.6331],\n",
       "               [-0.7583, -0.7717, -0.6705, -0.6844, -0.6811, -0.6735, -0.7096],\n",
       "               [-0.6555, -0.6618, -0.7023, -0.6842, -0.6775, -0.6449, -0.6403],\n",
       "               [-0.8593, -0.826 , -0.81  , -0.6101, -0.7208, -0.8323, -0.7556]],\n",
       "\n",
       "              [[-1.7961, -1.8851, -1.7228, -1.7441, -1.7233, -1.79  , -1.7965],\n",
       "               [-0.9491, -0.909 , -0.9233, -0.9153, -1.1257, -1.3412, -1.3551],\n",
       "               [-0.8622, -0.918 , -0.8607, -0.9425, -0.9897, -1.2595, -0.967 ],\n",
       "               [-1.0601, -1.5566, -0.9428, -0.9305, -0.864 , -0.9812, -0.9092],\n",
       "               [-0.961 , -0.9072, -0.9733, -0.934 , -0.9067, -0.9061, -0.9519],\n",
       "               [-0.9441, -0.9089, -0.9167, -1.0519, -0.8714, -0.8833, -0.8651],\n",
       "               [-0.9478, -0.9975, -1.0359, -0.92  , -0.8867, -0.8921, -1.0407],\n",
       "               [-0.8982, -0.9549, -0.9606, -0.8785, -0.8824, -0.863 , -0.8475],\n",
       "               [-0.9603, -0.9738, -1.1061, -0.8908, -0.8937, -0.8383, -0.8332],\n",
       "               [-0.9438, -1.02  , -0.8907, -0.947 , -0.7723, -0.7473, -0.9599]]]), 'mean': array([[[-1.6698, -1.6679, -1.9592, -1.9503, -2.5542, -1.9506, -2.1217],\n",
       "               [-1.1598, -1.9985, -1.6774, -1.3671, -2.0966, -2.2076, -2.0389],\n",
       "               [-1.6483, -0.6741, -1.1451, -0.648 , -1.6001, -0.8051, -0.761 ],\n",
       "               [-1.2033, -1.6244, -0.8559, -0.6747, -1.2195, -0.6454, -0.6376],\n",
       "               [-1.6175, -1.2843, -0.9277, -1.4333, -2.0681, -0.7614, -1.2865],\n",
       "               [-2.0642, -1.297 , -1.6337, -1.2278, -1.5805, -1.5994, -0.975 ],\n",
       "               [-1.094 , -1.8882, -1.1259, -0.8501, -0.8314, -0.9579, -0.7472],\n",
       "               [-2.1681, -1.5591, -1.8318, -0.7966, -0.6616, -0.7369, -0.6696],\n",
       "               [-1.6208, -1.6816, -1.9378, -0.6295, -0.6884, -1.4251, -0.6946],\n",
       "               [-1.8548, -1.3596, -1.8278, -0.7227, -0.7225, -0.6913, -1.0111]],\n",
       "\n",
       "              [[-1.8497, -1.442 , -1.4433, -1.8481, -2.0776, -1.8324, -1.8507],\n",
       "               [-1.1272, -1.3809, -1.6338, -1.0731, -1.6408, -1.9048, -2.3486],\n",
       "               [-0.8447, -1.4891, -1.5181, -1.1922, -1.5947, -0.859 , -1.6014],\n",
       "               [-2.2046, -1.9446, -0.9168, -1.575 , -1.8688, -0.8877, -1.547 ],\n",
       "               [-1.6065, -1.8044, -0.9226, -0.9504, -1.5573, -0.8612, -1.0158],\n",
       "               [-0.8678, -1.9215, -1.6838, -0.9461, -0.8054, -0.8115, -1.5216],\n",
       "               [-1.3257, -2.1013, -2.1686, -1.5924, -0.9136, -0.8804, -1.0608],\n",
       "               [-2.0577, -2.3402, -1.8477, -1.1563, -1.05  , -1.457 , -0.8582],\n",
       "               [-2.3843, -2.2241, -1.5813, -1.788 , -0.9089, -0.788 , -1.4827],\n",
       "               [-4.1391, -3.2253, -2.8744, -2.4469, -2.5874, -0.809 , -1.4243]],\n",
       "\n",
       "              [[-2.06  , -2.0399, -1.8225, -2.0463, -2.1429, -2.0938, -2.2889],\n",
       "               [-2.2278, -1.3409, -1.9395, -1.3645, -1.1186, -1.8784, -1.5801],\n",
       "               [-0.6872, -1.4348, -1.3557, -0.7554, -0.8667, -1.7389, -1.6977],\n",
       "               [-1.8541, -1.3787, -0.7572, -0.8456, -1.501 , -0.9757, -1.5171],\n",
       "               [-2.4836, -1.4848, -1.8223, -1.4283, -0.7511, -0.7335, -1.0915],\n",
       "               [-1.6233, -1.4426, -1.9379, -1.4402, -1.7522, -1.1462, -1.2638],\n",
       "               [-1.7545, -0.9958, -1.8399, -1.6143, -0.8684, -0.9422, -0.9439],\n",
       "               [-1.6951, -1.4447, -1.9336, -1.7884, -0.6479, -0.659 , -1.02  ],\n",
       "               [-2.1908, -1.5967, -1.5361, -1.4307, -1.1217, -1.0713, -1.0907],\n",
       "               [-1.8017, -2.0858, -1.5276, -2.0184, -0.8844, -0.7429, -0.6668]],\n",
       "\n",
       "              [[-1.5985, -1.6834, -2.1178, -1.5809, -1.6091, -1.7371, -2.4131],\n",
       "               [-1.0219, -1.2429, -1.6081, -0.7528, -0.7925, -1.0819, -2.9702],\n",
       "               [-1.3105, -1.4797, -1.4025, -1.591 , -1.1745, -1.2871, -1.2436],\n",
       "               [-2.1076, -1.5226, -1.5643, -1.6789, -2.4239, -1.2872, -1.8031],\n",
       "               [-1.2987, -1.2729, -1.8719, -0.933 , -0.6407, -1.7318, -1.0401],\n",
       "               [-2.3821, -1.9957, -1.4626, -0.7757, -0.6686, -0.6485, -1.1507],\n",
       "               [-1.887 , -1.835 , -1.7313, -0.676 , -0.74  , -0.655 , -0.6918],\n",
       "               [-2.4991, -2.1731, -2.2536, -1.3143, -0.7105, -0.6571, -0.7302],\n",
       "               [-1.6495, -1.7698, -1.2881, -1.3783, -1.2269, -0.7457, -0.6806],\n",
       "               [-2.1718, -2.1432, -1.906 , -1.4654, -0.7926, -0.9005, -0.8448]],\n",
       "\n",
       "              [[-2.3059, -3.231 , -1.9876, -1.9721, -1.7625, -2.0511, -2.2164],\n",
       "               [-1.5151, -1.2576, -1.5297, -0.9131, -1.3595, -1.5304, -1.5768],\n",
       "               [-1.0521, -1.1665, -1.5105, -1.1011, -1.371 , -1.8985, -0.9581],\n",
       "               [-2.0052, -2.748 , -1.6972, -1.467 , -0.8692, -0.9811, -0.9188],\n",
       "               [-1.2292, -1.6959, -1.64  , -1.5732, -0.9246, -0.9371, -0.9367],\n",
       "               [-1.8828, -1.7418, -1.7482, -1.8115, -0.9144, -0.9339, -0.886 ],\n",
       "               [-1.7181, -1.5212, -2.0379, -1.5727, -0.9136, -0.9278, -1.4844],\n",
       "               [-1.0218, -1.7893, -1.6505, -1.1706, -0.8996, -0.8899, -0.8411],\n",
       "               [-1.8842, -1.9391, -2.2368, -1.6252, -1.6348, -0.8406, -0.9065],\n",
       "               [-2.5027, -2.7394, -2.6929, -1.4663, -1.0711, -0.8551, -1.8395]]]), 'median': array([[[-1.668 , -1.6677, -1.6687, -1.6691, -1.6677, -1.668 , -1.6689],\n",
       "               [-0.9005, -0.9016, -0.911 , -0.9656, -1.2498, -1.504 , -1.5514],\n",
       "               [-0.67  , -0.665 , -0.6689, -0.6797, -0.7287, -0.8045, -0.852 ],\n",
       "               [-0.6427, -0.6355, -0.6533, -0.6315, -0.638 , -0.6409, -0.6388],\n",
       "               [-0.627 , -0.6831, -0.6659, -0.6957, -0.7394, -0.7698, -0.7566],\n",
       "               [-0.9443, -0.6567, -0.7023, -0.687 , -0.7423, -0.748 , -0.7753],\n",
       "               [-0.7062, -0.8248, -0.7306, -0.6522, -0.7636, -0.8003, -0.7302],\n",
       "               [-0.8036, -0.7864, -0.7158, -0.6602, -0.6572, -0.8571, -0.6733],\n",
       "               [-3.2894, -0.8577, -0.8279, -0.6638, -0.6913, -0.7378, -0.6462],\n",
       "               [-0.8603, -0.8045, -0.6818, -0.6995, -0.7545, -0.6717, -0.9573]],\n",
       "\n",
       "              [[-1.4424, -1.4418, -1.4434, -1.4429, -1.4402, -1.4414, -1.4421],\n",
       "               [-0.9918, -0.9906, -0.9902, -0.9925, -0.9984, -1.0043, -1.0088],\n",
       "               [-0.8111, -0.8099, -0.794 , -0.8201, -0.8247, -0.8499, -0.9153],\n",
       "               [-0.7845, -0.9372, -0.7765, -0.9346, -0.8653, -0.9052, -0.9281],\n",
       "               [-0.988 , -0.9033, -0.8208, -0.8101, -0.856 , -0.8615, -0.8802],\n",
       "               [-0.8317, -1.1218, -0.7957, -0.8112, -0.8228, -0.8175, -0.7758],\n",
       "               [-0.9562, -0.9128, -0.8776, -0.8236, -0.8381, -0.926 , -0.8369],\n",
       "               [-0.8256, -0.897 , -0.8985, -0.8281, -0.8739, -0.8892, -0.8489],\n",
       "               [-0.8388, -0.9037, -0.8797, -0.9437, -0.824 , -0.831 , -0.8938],\n",
       "               [-3.7786, -1.1563, -1.1582, -1.3186, -1.4358, -0.81  , -1.4735]],\n",
       "\n",
       "              [[-1.8237, -1.822 , -1.8224, -1.8211, -1.823 , -1.8214, -1.8237],\n",
       "               [-0.9653, -0.9599, -0.9623, -0.9655, -0.9872, -1.0276, -1.051 ],\n",
       "               [-0.6912, -0.6907, -0.6925, -0.703 , -0.7228, -0.7313, -0.7362],\n",
       "               [-0.7976, -0.7518, -0.7599, -0.7285, -0.979 , -0.9951, -0.9927],\n",
       "               [-0.9805, -0.8153, -0.6577, -0.723 , -0.7774, -0.7966, -0.8396],\n",
       "               [-0.9347, -1.0428, -0.8072, -0.9122, -0.9502, -1.093 , -1.1985],\n",
       "               [-1.2094, -0.6068, -0.8962, -0.9054, -0.7603, -0.867 , -0.8896],\n",
       "               [-0.8484, -0.6971, -0.6642, -0.7745, -0.7001, -0.6239, -0.8906],\n",
       "               [-0.6598, -0.9031, -0.6863, -0.8799, -0.8461, -0.9886, -0.8457],\n",
       "               [-0.8935, -0.9945, -0.9075, -0.7011, -0.7149, -0.7695, -0.6763]],\n",
       "\n",
       "              [[-1.331 , -1.329 , -1.3316, -1.3304, -1.3309, -1.3305, -1.3309],\n",
       "               [-0.7936, -0.7873, -0.7944, -0.7921, -0.7925, -0.7875, -0.7886],\n",
       "               [-0.6502, -0.6568, -0.6419, -0.6475, -0.6667, -0.8984, -0.7684],\n",
       "               [-1.0603, -0.6999, -0.6941, -0.7352, -1.5213, -0.9753, -1.0327],\n",
       "               [-0.6738, -0.6563, -0.6906, -0.6558, -0.6538, -0.6551, -0.6503],\n",
       "               [-0.8454, -0.753 , -0.6675, -0.7809, -0.735 , -0.7249, -0.7199],\n",
       "               [-0.6733, -0.8177, -0.682 , -0.7704, -0.72  , -0.6657, -0.6366],\n",
       "               [-0.8285, -0.8152, -0.6559, -0.7504, -0.6835, -0.7104, -0.7322],\n",
       "               [-1.1669, -0.7175, -0.9535, -0.8161, -0.6777, -0.7519, -0.7221],\n",
       "               [-1.1802, -2.0071, -0.8421, -0.7788, -0.8336, -0.8766, -0.7676]],\n",
       "\n",
       "              [[-1.6663, -1.6732, -1.6633, -1.6647, -1.6651, -1.667 , -1.6639],\n",
       "               [-0.9037, -0.9083, -0.9041, -0.9134, -1.075 , -1.2295, -1.2459],\n",
       "               [-0.8951, -0.9029, -0.8854, -0.8757, -0.8984, -0.9118, -0.9148],\n",
       "               [-0.9444, -0.9182, -0.9038, -0.8937, -0.8714, -0.9138, -0.909 ],\n",
       "               [-0.9451, -0.8907, -0.9204, -0.9516, -0.9295, -0.9268, -0.9101],\n",
       "               [-0.9837, -1.0791, -0.8561, -0.8817, -0.9215, -0.9266, -0.8999],\n",
       "               [-0.9339, -1.0703, -0.9729, -0.8729, -0.899 , -0.9382, -0.9124],\n",
       "               [-0.8194, -1.0355, -1.0491, -1.0111, -0.9454, -0.8919, -0.9223],\n",
       "               [-0.9427, -1.1338, -0.9423, -0.8432, -0.9199, -0.9123, -0.9408],\n",
       "               [-1.8084, -2.3665, -1.8285, -1.4786, -0.7546, -0.6941, -1.5575]]]), 'mode': array([[[ -1.6702,  -1.6664,  -1.6698,  -1.6699,  -1.6706,  -1.6665,\n",
       "                 -1.6719],\n",
       "               [ -0.8817,  -0.9046,  -0.9201,  -0.9624,  -1.2471,  -1.5111,\n",
       "                 -1.5518],\n",
       "               [ -0.6982,  -0.6817,  -0.6804,  -0.7065,  -0.7433,  -0.8024,\n",
       "                 -0.8409],\n",
       "               [ -0.6307,  -0.6238,  -0.648 ,  -0.6302,  -0.6367,  -0.639 ,\n",
       "                 -0.6428],\n",
       "               [ -0.6529,  -0.666 ,  -0.788 ,  -0.6763,  -0.7332,  -0.7427,\n",
       "                 -0.7495],\n",
       "               [ -0.8385,  -0.6724,  -0.6664,  -0.7208,  -0.6727,  -0.7079,\n",
       "                 -0.7761],\n",
       "               [ -0.9597,  -1.0424,  -0.9219,  -0.6415,  -0.8292,  -0.7659,\n",
       "                 -0.7899],\n",
       "               [ -0.652 ,  -1.0706,  -0.7377,  -0.6682,  -0.6851,  -0.8143,\n",
       "                 -0.6736],\n",
       "               [ -0.9971,  -0.9376,  -1.2678,  -0.7339,  -0.6825,  -0.8127,\n",
       "                 -0.7201],\n",
       "               [ -2.039 ,  -0.7743,  -0.6075,  -0.7288,  -0.6668,  -0.6335,\n",
       "                 -0.8931]],\n",
       "\n",
       "              [[ -1.4479,  -1.4314,  -1.4432,  -1.4478,  -1.4384,  -1.4432,\n",
       "                 -1.4405],\n",
       "               [ -0.9904,  -0.9992,  -0.9932,  -0.9928,  -0.9999,  -1.0035,\n",
       "                 -1.0106],\n",
       "               [ -0.7961,  -0.8098,  -0.7918,  -0.8022,  -0.8444,  -0.8608,\n",
       "                 -0.8874],\n",
       "               [ -0.8137,  -1.0279,  -0.8084,  -1.2372,  -0.8851,  -0.8888,\n",
       "                 -0.9145],\n",
       "               [ -1.3448,  -0.8113,  -0.8324,  -0.7943,  -0.8539,  -0.8613,\n",
       "                 -0.8875],\n",
       "               [ -0.7907,  -1.0262,  -0.9019,  -0.7805,  -0.7964,  -0.7909,\n",
       "                 -0.7726],\n",
       "               [ -0.9696,  -0.8022,  -0.9129,  -0.8172,  -0.7966,  -0.8881,\n",
       "                 -0.7886],\n",
       "               [ -1.0121,  -0.7408,  -1.0875,  -0.7837,  -0.8647,  -0.802 ,\n",
       "                 -0.8697],\n",
       "               [ -0.9417,  -0.9678,  -0.7472,  -0.9587,  -0.7676,  -0.8093,\n",
       "                 -0.9486],\n",
       "               [ -2.8455,  -0.9707,  -1.0619,  -0.8995,  -4.6905,  -0.7947,\n",
       "                 -1.8154]],\n",
       "\n",
       "              [[ -1.811 ,  -1.8312,  -1.8169,  -1.8224,  -1.8308,  -1.8158,\n",
       "                 -1.8288],\n",
       "               [ -0.9554,  -0.9615,  -0.963 ,  -0.9675,  -0.9855,  -1.0219,\n",
       "                 -1.053 ],\n",
       "               [ -0.695 ,  -0.6878,  -0.6924,  -0.7037,  -0.7266,  -0.7313,\n",
       "                 -0.7358],\n",
       "               [ -0.7954,  -0.8371,  -0.7658,  -0.941 ,  -1.0115,  -0.996 ,\n",
       "                 -0.9949],\n",
       "               [ -0.7859,  -0.9107,  -0.6984,  -0.7597,  -0.7873,  -0.7972,\n",
       "                 -0.8071],\n",
       "               [ -0.912 ,  -1.7701,  -1.1687,  -0.9545,  -1.0489,  -1.0989,\n",
       "                 -1.0935],\n",
       "               [ -1.2539,  -1.0839,  -0.838 ,  -1.0718,  -0.7445,  -0.8767,\n",
       "                 -0.8638],\n",
       "               [ -0.8673,  -0.7079,  -0.7722,  -0.6954,  -0.6575,  -0.7253,\n",
       "                 -0.8439],\n",
       "               [ -0.9777,  -0.9477,  -1.2688,  -1.2688,  -0.8267,  -1.0044,\n",
       "                 -0.8561],\n",
       "               [ -1.5447,  -1.5835,  -0.7995,  -0.821 ,  -0.9225,  -0.7791,\n",
       "                 -0.7946]],\n",
       "\n",
       "              [[ -1.3366,  -1.3288,  -1.3346,  -1.3371,  -1.3322,  -1.3366,\n",
       "                 -1.3315],\n",
       "               [ -0.7983,  -0.7898,  -0.8006,  -0.8068,  -0.7954,  -0.7887,\n",
       "                 -0.7875],\n",
       "               [ -0.6549,  -0.6558,  -0.6407,  -0.6515,  -0.6808,  -0.911 ,\n",
       "                 -0.8098],\n",
       "               [ -0.7489,  -0.684 ,  -0.694 ,  -0.7976, -10.9215,  -0.9994,\n",
       "                 -1.0373],\n",
       "               [ -0.7253,  -0.7065,  -0.7008,  -0.6624,  -0.6627,  -0.6602,\n",
       "                 -0.6637],\n",
       "               [ -0.8998,  -0.7429,  -1.0387,  -0.822 ,  -0.7798,  -0.9982,\n",
       "                 -1.0629],\n",
       "               [ -0.7925,  -1.0826,  -0.6894,  -0.637 ,  -0.6998,  -0.6448,\n",
       "                 -0.6082],\n",
       "               [ -0.9268,  -0.9835,  -0.7542,  -0.7231,  -0.7097,  -0.7223,\n",
       "                 -0.7315],\n",
       "               [ -1.1716,  -0.7791,  -1.1473,  -0.778 ,  -0.9433,  -0.6642,\n",
       "                 -0.6632],\n",
       "               [ -5.6749,  -1.4567,  -1.1772,  -0.8672,  -0.8845,  -0.8842,\n",
       "                 -0.7515]],\n",
       "\n",
       "              [[ -1.6675,  -1.6625,  -1.6503,  -1.6648,  -1.6518,  -1.6587,\n",
       "                 -1.6664],\n",
       "               [ -0.8924,  -0.9152,  -0.9135,  -0.9237,  -1.0943,  -1.2287,\n",
       "                 -1.2509],\n",
       "               [ -0.8723,  -0.8908,  -0.8724,  -0.8798,  -0.8877,  -0.9243,\n",
       "                 -0.9249],\n",
       "               [ -0.9012,  -0.9157,  -0.9548,  -0.8876,  -0.8715,  -0.9227,\n",
       "                 -0.9074],\n",
       "               [ -0.9511,  -1.0166,  -0.8696,  -0.9467,  -0.9151,  -0.9115,\n",
       "                 -0.9022],\n",
       "               [ -0.9934,  -0.9701,  -0.8257,  -0.9389,  -0.9054,  -0.8816,\n",
       "                 -0.9023],\n",
       "               [ -0.732 ,  -1.3034,  -0.8668,  -0.9011,  -0.8978,  -0.9036,\n",
       "                 -0.9217],\n",
       "               [ -1.1854,  -0.9154,  -1.3354,  -0.9188,  -0.8851,  -0.8731,\n",
       "                 -0.9354],\n",
       "               [ -0.8818,  -0.8168,  -0.9303,  -0.9328,  -0.9627,  -0.9543,\n",
       "                 -1.04  ],\n",
       "               [ -1.0949,  -2.1163,  -1.3924,  -1.1161,  -0.7018,  -0.7132,\n",
       "                 -1.2314]]]), 'p': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], 'eta': [0.0001, 0.001, 0.01, 0.1, 1, 10, 100]}                                                   ,\n",
       "       {'posterior_mean': array([[[-1.9193, -1.9212, -1.9239, -1.9142, -1.9145, -1.9216, -1.9161],\n",
       "               [-0.9494, -1.0267, -1.0034, -0.9636, -0.9373, -0.9956, -1.0019],\n",
       "               [-0.8819, -0.8921, -0.9007, -1.0599, -0.9812, -0.9238, -0.9496],\n",
       "               [-0.858 , -0.8356, -0.8485, -0.8615, -0.8843, -0.9181, -0.8952],\n",
       "               [-0.8228, -0.8869, -0.8317, -0.927 , -0.9085, -0.9046, -1.0447],\n",
       "               [-0.9039, -0.9625, -0.8817, -0.9158, -0.9434, -0.9555, -0.9504],\n",
       "               [-0.9765, -0.8638, -0.9558, -0.8779, -0.9199, -0.9514, -0.956 ],\n",
       "               [-0.8753, -0.8884, -0.8663, -0.8388, -0.8265, -0.8609, -0.8431],\n",
       "               [-0.9387, -0.8367, -0.8257, -0.8211, -0.8594, -0.8392, -0.824 ],\n",
       "               [-1.0759, -0.9709, -0.865 , -0.8101, -0.8709, -0.8849, -0.8403]],\n",
       "\n",
       "              [[-1.6288, -1.6194, -1.6207, -1.6686, -1.625 , -1.6261, -1.6417],\n",
       "               [-0.8201, -0.7492, -0.8006, -0.858 , -0.9541, -1.1141, -1.1815],\n",
       "               [-0.7262, -0.8274, -0.87  , -0.9126, -1.0908, -1.307 , -1.3454],\n",
       "               [-0.7042, -0.7473, -0.6915, -0.6848, -0.7831, -0.7032, -0.706 ],\n",
       "               [-0.6887, -0.6934, -0.711 , -0.8035, -0.702 , -0.7382, -0.7331],\n",
       "               [-0.7234, -0.7467, -0.7531, -0.7007, -0.728 , -0.7266, -0.7201],\n",
       "               [-0.6878, -0.7679, -0.694 , -0.6828, -0.7066, -0.7102, -0.7208],\n",
       "               [-0.7508, -0.745 , -0.6869, -0.6885, -0.7265, -0.7254, -0.8414],\n",
       "               [-0.7018, -0.7321, -0.7698, -0.7383, -0.7415, -0.8737, -0.7214],\n",
       "               [-0.6768, -0.6968, -0.7591, -0.7008, -0.7281, -0.7026, -0.772 ]],\n",
       "\n",
       "              [[-1.6223, -1.6839, -1.7056, -1.654 , -1.6781, -1.6805, -1.6767],\n",
       "               [-0.8626, -0.8725, -0.8077, -0.8867, -0.8891, -0.9229, -1.0008],\n",
       "               [-0.767 , -0.7491, -0.8319, -0.7517, -0.7978, -0.8699, -0.9229],\n",
       "               [-0.8006, -0.7711, -0.7056, -0.7319, -0.9557, -1.0458, -0.9995],\n",
       "               [-0.7636, -0.871 , -0.817 , -0.9565, -0.9728, -1.0364, -1.0124],\n",
       "               [-0.8204, -0.7432, -0.7667, -0.6935, -0.7117, -0.7245, -0.7231],\n",
       "               [-0.7678, -0.6609, -0.7508, -0.8103, -0.7036, -0.7912, -0.7151],\n",
       "               [-0.8157, -0.8624, -0.7868, -0.7638, -0.6818, -0.6643, -0.6812],\n",
       "               [-0.69  , -0.7264, -0.8432, -0.6968, -0.7744, -0.6785, -0.7226],\n",
       "               [-0.9117, -0.8853, -0.7569, -0.7128, -0.6813, -0.6582, -0.8628]],\n",
       "\n",
       "              [[-1.124 , -1.1754, -1.1263, -1.1678, -1.1356, -1.1342, -1.2491],\n",
       "               [-1.1312, -1.0265, -1.2528, -1.0705, -1.03  , -1.2398, -1.4651],\n",
       "               [-0.8718, -0.8634, -0.8862, -0.8592, -0.8639, -0.8262, -0.8205],\n",
       "               [-1.0978, -0.8529, -0.9522, -0.9171, -1.0058, -0.8541, -0.9657],\n",
       "               [-0.9598, -0.9366, -1.434 , -0.9671, -0.9039, -0.9891, -0.9684],\n",
       "               [-0.9798, -0.9128, -0.9088, -0.9292, -0.8868, -1.0256, -0.902 ],\n",
       "               [-0.8762, -0.8946, -0.8731, -0.8974, -0.8864, -0.8622, -0.8695],\n",
       "               [-1.0582, -1.0178, -0.9745, -0.8619, -0.9053, -0.9049, -0.8323],\n",
       "               [-0.9613, -0.8613, -0.8565, -0.8705, -0.893 , -0.8733, -0.9545],\n",
       "               [-1.03  , -1.0107, -1.0012, -0.9881, -0.8832, -0.8671, -0.9905]],\n",
       "\n",
       "              [[-1.66  , -1.736 , -1.6798, -1.6524, -1.6634, -1.6753, -1.7202],\n",
       "               [-1.0244, -1.0364, -1.0297, -1.0659, -1.2147, -1.4358, -1.4679],\n",
       "               [-0.9607, -0.8168, -0.9978, -0.928 , -1.0987, -1.1777, -1.1347],\n",
       "               [-0.824 , -0.8285, -0.8189, -0.8165, -0.8782, -0.9087, -0.9646],\n",
       "               [-0.7975, -0.7924, -0.8328, -0.8213, -0.8233, -0.846 , -0.8463],\n",
       "               [-0.8373, -0.7568, -0.8217, -0.7537, -0.7447, -0.7326, -0.7611],\n",
       "               [-0.8403, -0.8497, -0.7844, -0.773 , -0.7592, -0.7699, -0.8   ],\n",
       "               [-0.8611, -0.8368, -0.8811, -0.8345, -0.7668, -0.7527, -0.7826],\n",
       "               [-0.8413, -0.8461, -0.8211, -0.8199, -0.8065, -0.8125, -0.8701],\n",
       "               [-0.8071, -0.8313, -0.7821, -0.7639, -0.7377, -0.7445, -1.6075]]]), 'mean': array([[[-1.9449, -2.0442, -2.0189, -1.9434, -1.9415, -1.9424, -1.9444],\n",
       "               [-1.0457, -1.3156, -0.9282, -1.2075, -1.526 , -1.6535, -1.5175],\n",
       "               [-1.0345, -0.9303, -0.9335, -2.9134, -1.5528, -0.943 , -1.5716],\n",
       "               [-1.4741, -1.4506, -1.4743, -0.85  , -0.8829, -1.4373, -0.9179],\n",
       "               [-0.9194, -1.6507, -0.8336, -1.5033, -1.5557, -1.5673, -1.7011],\n",
       "               [-1.8499, -1.753 , -1.1728, -0.8119, -0.9625, -0.9689, -1.4176],\n",
       "               [-1.8487, -0.9863, -1.7316, -1.5117, -0.9128, -1.4296, -0.9723],\n",
       "               [-1.7246, -1.9318, -1.6389, -0.8542, -0.8413, -0.9152, -0.8363],\n",
       "               [-2.0263, -1.5817, -0.8821, -0.7955, -1.6622, -0.9131, -0.8391],\n",
       "               [-2.2253, -1.4488, -1.9367, -0.9639, -0.9428, -0.9154, -0.8944]],\n",
       "\n",
       "              [[-1.7231, -1.7312, -1.6243, -2.0902, -1.7047, -2.749 , -1.714 ],\n",
       "               [-1.542 , -1.4857, -0.9762, -1.0135, -1.5514, -1.6574, -1.1759],\n",
       "               [-0.9645, -1.1474, -1.627 , -1.0629, -1.342 , -1.3324, -1.5303],\n",
       "               [-1.4234, -1.3341, -0.8654, -0.6826, -2.7154, -0.7116, -1.0974],\n",
       "               [-1.1147, -1.207 , -1.1644, -2.8248, -0.6923, -0.7415, -0.7371],\n",
       "               [-1.1128, -1.3585, -2.097 , -1.8175, -0.7441, -0.7315, -0.7475],\n",
       "               [-1.745 , -1.5966, -1.5119, -1.1783, -0.7523, -0.7218, -0.7921],\n",
       "               [-2.0407, -1.4611, -1.7478, -1.1896, -0.9768, -0.9915, -1.264 ],\n",
       "               [-1.5673, -2.0367, -1.3354, -1.7066, -0.7863, -1.3665, -0.8463],\n",
       "               [-1.1963, -1.6879, -1.3165, -0.8271, -1.2444, -0.7045, -0.8362]],\n",
       "\n",
       "              [[-1.6212, -2.3026, -2.225 , -1.8688, -2.4197, -2.2372, -2.2314],\n",
       "               [-1.1951, -1.1371, -1.0072, -1.7371, -1.4174, -1.6909, -1.4405],\n",
       "               [-0.9312, -1.3878, -1.5322, -1.4401, -0.7954, -1.4041, -1.4494],\n",
       "               [-1.335 , -1.0878, -0.6794, -0.7044, -1.562 , -1.974 , -0.9524],\n",
       "               [-1.9884, -3.3688, -3.8005, -1.3335, -1.6493, -1.1295, -1.0261],\n",
       "               [-1.9845, -1.8587, -2.2025, -1.3964, -1.4287, -0.7506, -0.7693],\n",
       "               [-1.6929, -0.9262, -1.6014, -2.1777, -0.8557, -1.5572, -0.7681],\n",
       "               [-2.4549, -2.8294, -1.5863, -2.2724, -0.6867, -0.6479, -0.6806],\n",
       "               [-1.8386, -1.8169, -2.5358, -1.5259, -1.0131, -0.6587, -0.7904],\n",
       "               [-3.0955, -2.8167, -1.8513, -1.3501, -0.7395, -0.6637, -0.9697]],\n",
       "\n",
       "              [[-1.1246, -1.8106, -1.9118, -1.9963, -1.8348, -2.2673, -2.3953],\n",
       "               [-1.9234, -1.7924, -1.3314, -1.0691, -1.6917, -2.0677, -3.219 ],\n",
       "               [-0.9371, -1.6856, -1.2948, -1.0818, -0.8862, -1.6198, -0.8176],\n",
       "               [-2.1704, -1.9847, -1.7854, -1.59  , -1.1772, -0.8526, -1.7593],\n",
       "               [-1.048 , -2.1122, -2.5921, -1.6243, -0.9057, -1.5702, -0.9875],\n",
       "               [-2.121 , -1.9395, -1.4249, -1.9754, -0.8759, -1.22  , -0.909 ],\n",
       "               [-2.0262, -0.9451, -1.4454, -0.9413, -0.9617, -0.8962, -0.8995],\n",
       "               [-2.3925, -2.3504, -2.1428, -1.4255, -1.265 , -0.9418, -0.8866],\n",
       "               [-1.6788, -2.5786, -1.5852, -0.8861, -0.8627, -0.9036, -1.053 ],\n",
       "               [-2.0286, -2.8271, -2.0182, -2.1286, -0.893 , -0.9744, -1.2409]],\n",
       "\n",
       "              [[-1.8888, -3.4744, -1.9573, -1.9922, -1.6644, -1.9243, -2.9195],\n",
       "               [-1.5871, -1.5842, -1.2588, -1.3544, -1.5441, -1.6988, -1.9124],\n",
       "               [-1.12  , -1.3349, -2.1632, -1.1231, -1.0777, -1.6352, -1.8655],\n",
       "               [-2.0254, -0.8577, -1.4119, -1.3169, -0.8872, -1.4509, -1.2883],\n",
       "               [-1.8706, -1.6496, -1.4177, -2.5496, -0.8309, -0.8457, -0.8563],\n",
       "               [-1.5349, -1.533 , -1.5513, -1.9468, -0.7402, -0.7545, -0.7656],\n",
       "               [-1.1054, -2.0962, -1.443 , -1.2321, -0.7632, -0.7743, -0.8175],\n",
       "               [-2.6288, -1.9711, -2.3819, -3.2996, -1.4632, -0.8004, -1.1128],\n",
       "               [-2.1248, -2.0282, -1.6595, -1.7163, -1.322 , -0.8804, -0.9437],\n",
       "               [-1.4828, -1.7143, -1.4926, -1.5024, -0.8222, -0.8346, -1.8042]]]), 'median': array([[[-1.9295, -1.93  , -1.9298, -1.9307, -1.929 , -1.9303, -1.929 ],\n",
       "               [-0.9397, -0.9388, -0.9387, -0.942 , -0.9404, -0.9398, -0.9394],\n",
       "               [-0.9284, -0.9286, -0.948 , -0.9367, -0.939 , -0.9404, -0.9405],\n",
       "               [-0.8153, -0.82  , -0.8243, -0.8639, -0.8815, -0.8937, -0.9043],\n",
       "               [-0.8315, -0.8277, -0.8373, -0.8595, -0.9002, -0.9108, -0.9138],\n",
       "               [-0.8234, -1.0135, -0.7895, -0.9352, -0.9617, -0.9642, -0.9782],\n",
       "               [-0.98  , -0.8278, -0.8118, -0.9218, -0.9603, -0.956 , -0.9497],\n",
       "               [-1.0919, -0.9713, -0.8726, -0.915 , -0.8213, -0.9034, -0.848 ],\n",
       "               [-1.0043, -0.9018, -0.874 , -0.8718, -0.84  , -0.8574, -0.8251],\n",
       "               [-0.8709, -1.2731, -0.869 , -0.8442, -0.9251, -0.9183, -0.8644]],\n",
       "\n",
       "              [[-1.6233, -1.626 , -1.6242, -1.6199, -1.6233, -1.6209, -1.6196],\n",
       "               [-0.8217, -0.832 , -0.8347, -0.8528, -0.9907, -1.1418, -1.1751],\n",
       "               [-0.7375, -0.8382, -0.8116, -0.9115, -1.1565, -1.3206, -1.3255],\n",
       "               [-0.6837, -0.6827, -0.6723, -0.6824, -0.7085, -0.6951, -0.7034],\n",
       "               [-0.6569, -0.7113, -0.6676, -0.6676, -0.7021, -0.7176, -0.7044],\n",
       "               [-0.7135, -0.7463, -0.7272, -0.7927, -0.7524, -0.7331, -0.7078],\n",
       "               [-0.7678, -0.688 , -0.7266, -0.7958, -0.7185, -0.7321, -0.7555],\n",
       "               [-1.2357, -0.7861, -0.7545, -0.7115, -0.695 , -0.6851, -0.8685],\n",
       "               [-0.6996, -1.028 , -0.9865, -0.8154, -0.7325, -0.9642, -0.7203],\n",
       "               [-0.7515, -0.7471, -0.6498, -0.7538, -0.6897, -0.688 , -0.8345]],\n",
       "\n",
       "              [[-1.6205, -1.6242, -1.6264, -1.6251, -1.6264, -1.6224, -1.6251],\n",
       "               [-0.7868, -0.791 , -0.7877, -0.7899, -0.8296, -0.8912, -0.9173],\n",
       "               [-0.6528, -0.6616, -0.6468, -0.6721, -0.7202, -0.7833, -0.8382],\n",
       "               [-0.7933, -0.667 , -0.6831, -0.7284, -0.9019, -0.9418, -0.9559],\n",
       "               [-0.7919, -1.3227, -1.7037, -0.9092, -0.9709, -1.0431, -1.0357],\n",
       "               [-0.7695, -0.7505, -0.8477, -0.7328, -0.702 , -0.7466, -0.7605],\n",
       "               [-1.0642, -0.7634, -0.7929, -0.959 , -0.826 , -0.7213, -0.7575],\n",
       "               [-1.2272, -1.3055, -0.7227, -0.7031, -0.686 , -0.6391, -0.6827],\n",
       "               [-0.6788, -1.0994, -0.8645, -0.6708, -0.7203, -0.6129, -0.7668],\n",
       "               [-0.7417, -0.7696, -0.7815, -0.7643, -0.7194, -0.6472, -0.8362]],\n",
       "\n",
       "              [[-1.1245, -1.1242, -1.126 , -1.1242, -1.1235, -1.1243, -1.1247],\n",
       "               [-1.0621, -1.0587, -1.0638, -1.0618, -1.0593, -1.0823, -1.0996],\n",
       "               [-0.8728, -0.8752, -0.8739, -0.8497, -0.8137, -0.7974, -0.8004],\n",
       "               [-0.891 , -0.9688, -0.8394, -0.8696, -0.8476, -0.8419, -0.88  ],\n",
       "               [-0.9829, -0.9707, -0.9648, -0.913 , -0.9103, -0.9914, -0.9616],\n",
       "               [-0.9979, -0.9725, -0.9342, -0.9137, -0.8971, -0.8976, -0.9147],\n",
       "               [-1.0697, -0.9543, -1.0117, -0.9755, -0.9316, -0.873 , -0.8852],\n",
       "               [-1.1969, -1.1427, -1.36  , -0.9288, -1.0141, -0.9207, -0.9034],\n",
       "               [-1.2115, -1.9002, -1.1281, -0.8815, -0.8982, -0.9057, -0.8999],\n",
       "               [-1.3277, -1.262 , -1.374 , -0.9821, -0.9384, -0.9247, -0.9759]],\n",
       "\n",
       "              [[-1.6656, -1.6666, -1.6648, -1.6635, -1.6631, -1.6656, -1.6628],\n",
       "               [-1.018 , -1.0158, -1.0196, -1.0536, -1.2323, -1.4553, -1.5252],\n",
       "               [-0.9867, -0.8178, -1.0042, -0.9482, -1.1021, -1.1687, -1.1837],\n",
       "               [-0.7582, -0.7734, -0.7495, -0.7886, -0.8823, -0.9277, -0.9241],\n",
       "               [-0.7732, -0.7705, -0.785 , -0.7906, -0.8225, -0.838 , -0.8447],\n",
       "               [-0.7523, -0.799 , -0.7903, -0.7466, -0.7343, -0.7354, -0.7345],\n",
       "               [-0.9189, -0.7638, -0.7821, -0.7384, -0.7684, -0.7749, -0.8053],\n",
       "               [-3.0453, -1.1053, -0.9243, -1.3037, -0.816 , -0.7909, -0.8943],\n",
       "               [-0.9841, -0.9818, -0.8423, -0.9022, -0.9154, -0.8048, -0.9461],\n",
       "               [-1.1104, -1.1665, -0.8975, -0.7613, -0.7146, -0.758 , -1.7757]]]), 'mode': array([[[-1.927 , -1.9236, -1.9247, -1.9357, -1.9266, -1.935 , -1.9299],\n",
       "               [-0.9507, -0.9444, -0.9451, -0.9395, -0.9381, -0.9415, -0.9401],\n",
       "               [-1.057 , -0.966 , -0.876 , -0.945 , -0.9403, -0.9386, -0.9397],\n",
       "               [-0.8138, -0.8112, -0.8279, -0.862 , -0.8702, -0.9005, -0.9116],\n",
       "               [-0.8855, -0.825 , -0.8346, -0.8577, -0.8953, -0.9089, -0.9074],\n",
       "               [-0.878 , -0.8092, -0.8333, -0.9214, -0.9558, -0.961 , -0.976 ],\n",
       "               [-1.0247, -1.0183, -0.7901, -0.9306, -1.0285, -0.9975, -0.9893],\n",
       "               [-0.9816, -0.874 , -1.0051, -0.8439, -0.8016, -0.904 , -0.8483],\n",
       "               [-1.9825, -0.9876, -0.9583, -0.8333, -0.8305, -0.8614, -0.8133],\n",
       "               [-0.9453, -1.516 , -1.0151, -0.8639, -0.8934, -0.8967, -0.8941]],\n",
       "\n",
       "              [[-1.6243, -1.6496, -1.6252, -1.6183, -1.6301, -1.6235, -1.5938],\n",
       "               [-0.8246, -0.8377, -0.8325, -0.8435, -1.0134, -1.1407, -1.1645],\n",
       "               [-0.7365, -0.985 , -0.8049, -1.0133, -1.1013, -1.3208, -1.3353],\n",
       "               [-0.6813, -0.6846, -0.6854, -0.7355, -0.6951, -0.6946, -0.7027],\n",
       "               [-0.6611, -0.6719, -0.7064, -0.6825, -0.6855, -0.7187, -0.6939],\n",
       "               [-0.7125, -0.7752, -0.7295, -0.6871, -0.7154, -0.7173, -0.7005],\n",
       "               [-0.7842, -0.8952, -0.7547, -0.801 , -0.6816, -0.6901, -0.6858],\n",
       "               [-1.2201, -0.7748, -0.7034, -0.6885, -0.7504, -0.7678, -0.6953],\n",
       "               [-0.7002, -0.74  , -0.8337, -0.7737, -0.7674, -1.0133, -0.7703],\n",
       "               [-1.1092, -0.7695, -0.7081, -0.7211, -0.73  , -0.7207, -0.7639]],\n",
       "\n",
       "              [[-1.6209, -1.6138, -1.6182, -1.6224, -1.6339, -1.6146, -1.6241],\n",
       "               [-0.8001, -0.787 , -0.7816, -0.7836, -0.8137, -0.8903, -0.9183],\n",
       "               [-0.6351, -0.7296, -0.6394, -0.6584, -0.7322, -0.7808, -0.8328],\n",
       "               [-0.8625, -0.6926, -0.6741, -0.7204, -0.9463, -0.9658, -0.9863],\n",
       "               [-1.0365, -3.0099, -3.7112, -0.8983, -0.9578, -1.0473, -1.4933],\n",
       "               [-0.7917, -0.7649, -0.809 , -0.7977, -0.7362, -0.7573, -0.7374],\n",
       "               [-0.7129, -0.9076, -0.7391, -0.9059, -0.8187, -0.7343, -0.7566],\n",
       "               [-0.9851, -0.8056, -0.7625, -0.7355, -0.6947, -0.6614, -0.6399],\n",
       "               [-0.7556, -0.9243, -1.0124, -1.0356, -0.6917, -0.5821, -0.7407],\n",
       "               [-0.849 , -1.1468, -1.1175, -0.6827, -0.7294, -0.6039, -0.7976]],\n",
       "\n",
       "              [[-1.1271, -1.1257, -1.1244, -1.1285, -1.1214, -1.1254, -1.1247],\n",
       "               [-1.0764, -1.0701, -1.075 , -1.0657, -1.0575, -1.082 , -1.1101],\n",
       "               [-0.8749, -0.8684, -0.8792, -0.8563, -0.8122, -0.7978, -0.8016],\n",
       "               [-0.8758, -0.8857, -0.9379, -0.9124, -0.8613, -0.8936, -0.8455],\n",
       "               [-0.946 , -0.9495, -0.8618, -0.9109, -0.9356, -0.9451, -0.9405],\n",
       "               [-0.9907, -0.9226, -0.9449, -0.937 , -0.8944, -0.911 , -0.9078],\n",
       "               [-1.1881, -1.3437, -1.069 , -1.1104, -0.9371, -0.8743, -0.9063],\n",
       "               [-0.995 , -1.3259, -1.4935, -1.1122, -0.9598, -0.9632, -0.9226],\n",
       "               [-1.1767, -2.4819, -1.1419, -0.9606, -0.9666, -0.9612, -0.9623],\n",
       "               [-0.9118, -2.0622, -1.444 , -0.9521, -1.2995, -1.0771, -1.1048]],\n",
       "\n",
       "              [[-1.6635, -1.6701, -1.6633, -1.6701, -1.6572, -1.6684, -1.668 ],\n",
       "               [-1.0312, -1.004 , -1.0061, -1.0491, -1.2327, -1.4402, -1.51  ],\n",
       "               [-1.1846, -0.7964, -0.9958, -0.8859, -1.0906, -1.1734, -1.1769],\n",
       "               [-0.7616, -0.7669, -0.7839, -0.8113, -0.8638, -0.9191, -0.9234],\n",
       "               [-0.7913, -0.8522, -0.8303, -0.7838, -0.8164, -0.8275, -0.8368],\n",
       "               [-0.8523, -0.9822, -0.7896, -0.7472, -0.7305, -0.7495, -0.752 ],\n",
       "               [-0.8886, -0.7428, -0.8187, -0.7843, -0.7525, -0.7663, -0.8059],\n",
       "               [-2.6501, -1.2902, -1.4454, -3.9454, -0.8722, -0.7903, -1.1159],\n",
       "               [-0.8573, -0.9371, -0.8752, -0.8478, -0.8956, -0.8859, -0.911 ],\n",
       "               [-0.6975, -1.3833, -0.8238, -0.9281, -0.8705, -0.7763, -1.7169]]]), 'p': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], 'eta': [0.0001, 0.001, 0.01, 0.1, 1, 10, 100]},\n",
       "       {'posterior_mean': array([[[-1.5886, -1.5813, -1.5813, -1.5767, -1.5374, -1.5411, -1.5912],\n",
       "               [-1.0232, -1.1305, -1.0232, -1.0238, -1.204 , -1.4568, -1.3314],\n",
       "               [-0.8919, -0.9639, -0.8993, -0.9301, -0.9824, -1.0773, -0.9588],\n",
       "               [-0.9188, -0.9443, -0.9857, -0.8963, -0.9859, -1.2113, -0.9792],\n",
       "               [-0.8888, -0.9   , -0.8667, -0.9244, -0.9379, -0.9508, -1.8025],\n",
       "               [-0.9046, -0.9392, -1.011 , -0.8823, -0.9231, -0.9314, -0.9242],\n",
       "               [-0.8958, -0.9324, -0.9371, -0.8947, -0.888 , -0.9389, -0.8968],\n",
       "               [-0.9973, -0.9468, -0.9072, -0.9351, -0.862 , -0.8824, -0.9   ],\n",
       "               [-0.9088, -0.9037, -1.0127, -0.8744, -0.9032, -0.8685, -1.0025],\n",
       "               [-1.0454, -1.0796, -0.9182, -0.9125, -0.9978, -0.8895, -1.0341]],\n",
       "\n",
       "              [[-1.728 , -1.7292, -1.76  , -1.7273, -1.7389, -1.7674, -1.7359],\n",
       "               [-0.9117, -1.1126, -0.9507, -0.9507, -0.9836, -1.0533, -1.0411],\n",
       "               [-0.8336, -0.8493, -0.817 , -0.8054, -0.7668, -0.8236, -0.8834],\n",
       "               [-0.7095, -0.8036, -0.8859, -0.7193, -0.7543, -0.8223, -0.8272],\n",
       "               [-0.7243, -0.7476, -0.683 , -0.7242, -0.7665, -0.7627, -0.7668],\n",
       "               [-0.7727, -0.767 , -0.7333, -0.7431, -0.7537, -0.7587, -0.7651],\n",
       "               [-0.7038, -0.7284, -0.7308, -0.708 , -0.7118, -0.6902, -0.702 ],\n",
       "               [-0.6716, -0.7399, -0.7609, -1.0759, -0.7008, -0.7091, -0.6794],\n",
       "               [-0.7289, -0.8996, -0.7247, -0.6935, -0.7278, -0.7064, -0.7079],\n",
       "               [-0.7736, -0.8861, -0.8425, -0.7345, -0.7725, -0.8206, -0.6917]],\n",
       "\n",
       "              [[-1.8154, -1.7627, -1.7389, -1.7667, -1.7396, -1.745 , -1.7877],\n",
       "               [-1.0208, -0.992 , -1.0383, -1.0443, -0.9822, -0.979 , -1.0969],\n",
       "               [-0.8769, -0.8729, -0.8966, -0.917 , -1.0174, -1.0972, -1.1798],\n",
       "               [-0.8783, -0.9035, -0.8468, -0.8702, -0.8932, -0.9046, -1.1391],\n",
       "               [-1.0114, -0.9366, -0.8813, -0.8381, -0.84  , -0.9949, -0.8486],\n",
       "               [-0.8494, -0.8829, -0.9384, -0.8746, -0.8236, -0.8204, -0.8204],\n",
       "               [-0.9612, -0.9257, -1.021 , -0.9039, -0.9626, -0.986 , -1.0183],\n",
       "               [-0.8896, -1.0396, -0.9014, -0.953 , -0.8591, -0.8295, -0.8522],\n",
       "               [-0.9716, -0.896 , -0.9264, -0.8639, -0.8533, -0.8566, -0.8858],\n",
       "               [-1.0076, -0.8952, -0.9512, -0.9515, -0.8606, -0.8726, -1.7206]],\n",
       "\n",
       "              [[-1.6461, -1.6709, -1.6405, -1.6726, -1.6472, -1.725 , -1.6638],\n",
       "               [-0.752 , -0.7715, -0.7208, -0.7446, -0.8654, -1.2151, -1.0514],\n",
       "               [-0.522 , -0.5535, -0.4803, -0.505 , -0.4819, -0.5666, -0.5111],\n",
       "               [-0.5129, -0.644 , -0.5879, -0.5254, -0.6147, -0.6257, -0.7138],\n",
       "               [-0.5252, -0.5783, -0.5376, -0.625 , -0.6827, -0.6268, -0.671 ],\n",
       "               [-0.593 , -0.755 , -0.5875, -0.5024, -0.5218, -0.536 , -0.5359],\n",
       "               [-0.5727, -0.6545, -0.5814, -0.5711, -0.5448, -0.5442, -0.5514],\n",
       "               [-0.6574, -0.7152, -0.6994, -0.5   , -0.4704, -0.5249, -0.596 ],\n",
       "               [-0.7079, -0.5607, -0.535 , -0.6634, -0.6432, -0.5455, -0.72  ],\n",
       "               [-0.625 , -0.6486, -0.6616, -0.6249, -1.0288, -0.6011, -0.699 ]],\n",
       "\n",
       "              [[-1.3991, -1.47  , -1.467 , -1.4049, -1.5731, -1.4188, -1.3525],\n",
       "               [-0.9193, -0.7458, -0.7394, -0.7702, -1.0956, -1.399 , -1.4127],\n",
       "               [-0.5302, -0.5373, -0.5339, -0.5513, -0.5345, -0.5708, -0.5889],\n",
       "               [-0.5503, -0.6147, -0.5365, -0.5674, -0.7201, -0.6627, -1.0838],\n",
       "               [-0.565 , -0.6699, -0.7448, -0.5315, -0.541 , -0.5722, -0.5633],\n",
       "               [-0.6488, -0.5096, -0.5347, -0.524 , -0.5693, -0.6222, -0.603 ],\n",
       "               [-0.6606, -0.5523, -0.5401, -0.5446, -0.5423, -0.5768, -0.627 ],\n",
       "               [-0.5519, -0.5729, -0.5756, -0.5426, -0.5483, -0.5544, -0.573 ],\n",
       "               [-0.5328, -0.5423, -0.5727, -0.5519, -0.5888, -0.5674, -0.6536],\n",
       "               [-0.5573, -0.651 , -0.5365, -0.5268, -0.5337, -0.5742, -0.7424]]]), 'mean': array([[[-1.9875, -1.8405, -1.8359, -1.8364, -1.5307, -1.5366, -1.962 ],\n",
       "               [-1.396 , -1.6077, -1.665 , -1.4266, -1.8135, -1.9923, -1.7023],\n",
       "               [-1.186 , -1.8601, -1.1728, -0.9775, -1.3581, -1.9364, -1.3821],\n",
       "               [-1.5807, -1.8418, -2.4871, -0.9028, -1.2655, -1.9965, -1.3192],\n",
       "               [-1.9978, -0.875 , -1.5919, -1.8056, -1.8643, -1.0675, -2.0268],\n",
       "               [-1.6507, -1.0708, -1.8587, -0.9007, -1.3802, -1.0095, -0.9665],\n",
       "               [-2.244 , -1.6377, -2.126 , -1.8152, -0.9241, -1.5288, -0.8974],\n",
       "               [-1.8757, -1.902 , -1.2239, -0.9144, -0.8469, -0.9066, -1.0695],\n",
       "               [-1.9889, -1.7046, -1.4752, -0.8943, -1.0525, -0.8629, -0.9861],\n",
       "               [-2.4228, -2.2155, -1.7238, -1.4962, -1.3554, -0.9352, -1.2717]],\n",
       "\n",
       "              [[-1.7281, -2.0761, -2.1234, -1.7234, -2.0802, -1.9701, -1.9731],\n",
       "               [-1.5543, -1.3254, -1.625 , -1.3543, -1.4381, -1.5298, -1.4905],\n",
       "               [-0.9207, -1.0335, -0.8632, -0.9206, -1.238 , -0.9049, -0.8411],\n",
       "               [-1.3086, -1.2182, -1.168 , -1.7143, -0.8842, -0.9118, -1.3235],\n",
       "               [-1.4663, -1.4198, -1.6774, -0.8206, -1.4756, -0.7899, -0.8039],\n",
       "               [-1.4633, -1.5406, -1.5627, -1.272 , -1.28  , -0.7408, -0.7483],\n",
       "               [-0.7185, -1.4116, -1.4579, -1.3763, -0.7234, -0.6651, -0.7326],\n",
       "               [-1.3796, -1.1657, -1.5673, -1.6661, -0.6872, -1.2464, -0.6806],\n",
       "               [-3.1676, -2.3494, -1.5354, -1.1941, -1.2993, -0.7521, -0.7295],\n",
       "               [-1.9029, -3.6334, -3.4598, -2.1653, -1.5043, -0.7531, -0.8524]],\n",
       "\n",
       "              [[-1.8183, -1.9985, -2.0472, -2.024 , -2.0114, -2.0797, -1.9772],\n",
       "               [-1.4198, -1.5796, -1.7316, -2.4777, -1.5859, -1.2391, -1.7549],\n",
       "               [-0.856 , -1.6865, -1.1839, -0.9257, -1.9348, -1.6275, -1.1871],\n",
       "               [-1.2748, -1.0873, -1.5577, -0.849 , -1.6176, -1.5273, -1.8265],\n",
       "               [-2.0757, -2.0229, -2.119 , -1.2587, -0.8538, -1.7516, -0.8503],\n",
       "               [-0.9642, -2.1724, -1.9704, -1.8326, -0.8148, -0.8033, -0.8144],\n",
       "               [-2.4914, -2.1381, -2.0042, -1.8694, -1.195 , -0.9894, -1.2656],\n",
       "               [-1.7222, -2.9805, -2.2422, -2.342 , -0.8915, -0.8383, -0.8451],\n",
       "               [-2.6575, -1.9565, -2.1153, -0.9667, -0.8748, -0.8546, -0.8999],\n",
       "               [-2.4318, -1.8783, -2.6434, -1.9059, -0.8951, -0.876 , -1.6366]],\n",
       "\n",
       "              [[-1.6468, -2.4127, -1.6468, -2.4746, -1.6473, -2.7279, -2.4077],\n",
       "               [-1.6587, -1.6541, -1.7132, -0.8071, -0.7788, -3.3778, -2.2718],\n",
       "               [-1.2905, -0.6892, -0.4886, -0.535 , -0.4918, -1.4291, -0.5175],\n",
       "               [-0.5925, -1.3716, -0.697 , -0.5587, -0.6605, -1.5144, -1.519 ],\n",
       "               [-2.188 , -0.7449, -1.5189, -1.5505, -2.0988, -0.6854, -0.6843],\n",
       "               [-1.7588, -2.1774, -1.6265, -0.5029, -0.5276, -0.531 , -0.5383],\n",
       "               [-1.5148, -2.5428, -2.0178, -0.7751, -0.4915, -0.5134, -0.719 ],\n",
       "               [-2.4222, -3.6837, -2.4522, -0.7539, -0.4628, -0.5715, -0.9227],\n",
       "               [-1.8497, -1.9038, -1.8417, -1.066 , -0.8854, -0.5707, -1.1012],\n",
       "               [-2.0547, -1.4078, -2.514 , -1.1453, -2.618 , -0.6219, -0.9101]],\n",
       "\n",
       "              [[-1.4193, -1.4674, -1.4685, -2.0206, -1.567 , -1.6104, -1.9686],\n",
       "               [-1.3653, -1.3583, -1.1524, -1.1601, -1.1797, -1.4003, -1.2662],\n",
       "               [-0.572 , -0.5724, -0.8418, -1.0143, -0.8443, -0.5799, -0.5825],\n",
       "               [-1.1803, -0.836 , -0.7919, -0.9795, -1.5199, -0.6792, -1.7144],\n",
       "               [-1.1194, -1.9658, -1.0868, -1.5951, -1.4253, -0.593 , -0.5775],\n",
       "               [-1.8782, -1.2253, -1.5611, -0.5108, -0.5912, -0.7457, -0.6554],\n",
       "               [-1.8151, -1.3201, -1.4847, -0.8519, -0.615 , -0.6459, -0.748 ],\n",
       "               [-1.7466, -1.5593, -1.5119, -1.7027, -0.5718, -0.5614, -0.6222],\n",
       "               [-1.2908, -1.7877, -1.0348, -1.0312, -0.5919, -0.5717, -0.7153],\n",
       "               [-1.7899, -2.8179, -1.3354, -0.5272, -0.5856, -0.6361, -0.855 ]]]), 'median': array([[[-1.5401, -1.5324, -1.53  , -1.5318, -1.5302, -1.5362, -1.5339],\n",
       "               [-1.0201, -1.0225, -1.0179, -1.023 , -1.1218, -1.2387, -1.2446],\n",
       "               [-0.8952, -0.8998, -0.8958, -0.9006, -0.9232, -0.9392, -0.9385],\n",
       "               [-0.9062, -0.8575, -0.9586, -0.9051, -0.8445, -0.9554, -0.9715],\n",
       "               [-0.8784, -0.9141, -0.8807, -0.8522, -0.8329, -0.9915, -0.9437],\n",
       "               [-0.8824, -0.9296, -0.8983, -0.8818, -0.9365, -0.9752, -0.9813],\n",
       "               [-0.8887, -0.8959, -0.8838, -0.9406, -0.9179, -0.9245, -0.9289],\n",
       "               [-0.9194, -0.9202, -0.8979, -0.8998, -0.9127, -0.8908, -0.9891],\n",
       "               [-0.9287, -0.8979, -0.9485, -0.8659, -0.8533, -0.8464, -0.8719],\n",
       "               [-1.1393, -1.4163, -1.1768, -0.9468, -0.9266, -0.9637, -1.2641]],\n",
       "\n",
       "              [[-1.7286, -1.7217, -1.7265, -1.7248, -1.7218, -1.7226, -1.7214],\n",
       "               [-0.9174, -0.9188, -0.9217, -0.9351, -0.9745, -1.0142, -1.024 ],\n",
       "               [-0.8314, -0.8281, -0.8267, -0.8222, -0.8122, -0.8206, -0.8167],\n",
       "               [-0.7382, -0.7221, -0.8908, -0.7721, -0.8244, -0.8327, -0.8502],\n",
       "               [-0.7568, -0.7478, -0.7331, -0.7459, -0.7783, -0.8035, -0.776 ],\n",
       "               [-0.7633, -0.7967, -3.5375, -0.7377, -0.7575, -0.7644, -0.7946],\n",
       "               [-0.6927, -0.6678, -0.7298, -0.7276, -0.7674, -0.7103, -0.745 ],\n",
       "               [-0.7956, -0.8805, -0.7965, -0.73  , -0.7298, -0.7013, -0.6754],\n",
       "               [-1.0267, -0.817 , -0.8151, -0.7667, -0.6764, -0.7257, -0.7055],\n",
       "               [-0.8406, -1.1581, -1.7404, -0.8261, -0.7889, -0.7863, -0.893 ]],\n",
       "\n",
       "              [[-1.8198, -1.8196, -1.8182, -1.8217, -1.8168, -1.8192, -1.8228],\n",
       "               [-1.0044, -1.0008, -1.0051, -1.0006, -0.9811, -0.9763, -0.9812],\n",
       "               [-0.8307, -0.8824, -0.8529, -0.8731, -1.0232, -1.1488, -1.1896],\n",
       "               [-0.8102, -0.8898, -0.8383, -0.8542, -0.8839, -0.9423, -0.9703],\n",
       "               [-1.0913, -0.8883, -0.851 , -0.8329, -0.856 , -0.8408, -0.8497],\n",
       "               [-0.832 , -0.8396, -0.9291, -0.8287, -0.8154, -0.8192, -0.819 ],\n",
       "               [-1.0013, -0.8605, -0.9516, -1.0423, -1.1204, -0.9889, -1.1259],\n",
       "               [-0.9263, -0.8771, -0.9592, -0.9039, -0.949 , -0.859 , -0.8619],\n",
       "               [-1.2181, -0.8795, -1.1278, -0.83  , -0.8998, -0.8689, -0.9155],\n",
       "               [-0.9376, -1.0872, -1.1723, -1.1123, -0.8971, -0.9012, -1.7569]],\n",
       "\n",
       "              [[-1.6463, -1.6475, -1.6465, -1.6465, -1.647 , -1.6467, -1.6466],\n",
       "               [-0.6919, -0.7028, -0.6952, -0.7226, -0.8658, -1.0006, -1.0306],\n",
       "               [-0.5032, -0.4918, -0.4838, -0.4856, -0.4896, -0.5007, -0.5137],\n",
       "               [-0.5076, -0.5918, -0.5119, -0.5307, -0.6058, -0.7141, -0.7218],\n",
       "               [-0.929 , -0.4913, -0.5138, -0.5397, -0.6457, -0.6676, -0.7044],\n",
       "               [-0.5043, -0.5266, -0.5096, -0.5002, -0.5348, -0.5356, -0.5378],\n",
       "               [-0.7672, -0.9106, -0.618 , -0.6773, -0.4768, -0.5816, -0.6051],\n",
       "               [-0.6315, -1.1504, -0.6948, -0.4812, -0.4743, -0.5714, -0.8114],\n",
       "               [-0.8124, -0.7164, -0.8315, -1.0766, -0.9028, -0.5399, -0.9384],\n",
       "               [-1.1334, -1.6373, -0.7695, -0.6143, -1.0815, -0.6773, -0.9864]],\n",
       "\n",
       "              [[-1.4678, -1.4673, -1.4684, -1.4716, -1.4669, -1.4683, -1.4672],\n",
       "               [-0.8259, -0.7403, -0.7435, -0.7451, -1.0544, -1.3985, -1.4785],\n",
       "               [-0.5439, -0.5587, -0.5358, -0.5569, -0.5505, -0.5732, -0.5825],\n",
       "               [-0.5528, -0.6203, -0.5517, -0.5512, -0.5923, -0.6719, -0.6546],\n",
       "               [-0.5783, -0.6258, -0.5585, -0.5462, -0.5672, -0.6005, -0.6003],\n",
       "               [-0.5733, -0.5313, -0.5315, -0.5316, -0.5655, -0.7123, -0.5844],\n",
       "               [-0.6778, -0.6463, -0.6219, -0.6478, -0.5126, -0.558 , -0.6975],\n",
       "               [-0.6384, -0.7688, -0.7562, -0.6285, -0.5539, -0.5657, -0.5866],\n",
       "               [-0.693 , -0.5965, -0.6892, -0.5915, -0.5553, -0.577 , -0.6465],\n",
       "               [-0.6482, -0.798 , -0.7049, -0.5483, -0.5252, -0.5616, -0.874 ]]]), 'mode': array([[[-1.5137, -1.5307, -1.5311, -1.5166, -1.5302, -1.526 , -1.5367],\n",
       "               [-1.021 , -1.0189, -1.0165, -1.0177, -1.1128, -1.2318, -1.2486],\n",
       "               [-0.9109, -0.8963, -0.9024, -0.909 , -0.9258, -0.9449, -0.9402],\n",
       "               [-0.914 , -0.884 , -0.9176, -0.9313, -0.9096, -0.9588, -0.9909],\n",
       "               [-0.8901, -0.9425, -0.8769, -0.8508, -0.9968, -0.9691, -1.0555],\n",
       "               [-0.9012, -0.8553, -0.8685, -0.8826, -0.9552, -0.979 , -0.9805],\n",
       "               [-0.935 , -0.8722, -0.9261, -0.9167, -0.896 , -0.9344, -0.9263],\n",
       "               [-0.8962, -0.9162, -0.8905, -0.9013, -0.9145, -0.9116, -0.8947],\n",
       "               [-0.8715, -0.9194, -0.9447, -0.873 , -0.8857, -0.8611, -0.9082],\n",
       "               [-1.0823, -1.105 , -1.5839, -0.9211, -0.9109, -0.9152, -1.2282]],\n",
       "\n",
       "              [[-1.7303, -1.7383, -1.7375, -1.7156, -1.727 , -1.7224, -1.7259],\n",
       "               [-0.9153, -0.9217, -0.9123, -0.9372, -0.9743, -1.0113, -1.0156],\n",
       "               [-0.8321, -0.8324, -0.8669, -0.8186, -0.9086, -0.8055, -0.8078],\n",
       "               [-0.7307, -0.7462, -0.8259, -0.7476, -0.8978, -0.8388, -0.857 ],\n",
       "               [-0.7954, -0.7217, -0.7991, -0.7371, -0.7755, -0.8029, -0.8024],\n",
       "               [-0.794 , -0.8495, -0.818 , -0.7292, -0.7967, -0.8053, -0.7911],\n",
       "               [-0.8811, -0.6941, -0.7444, -0.7888, -0.8257, -0.6791, -0.7685],\n",
       "               [-0.8792, -0.8987, -1.1222, -0.7215, -0.7378, -0.7346, -0.7162],\n",
       "               [-1.3868, -0.8946, -0.9912, -1.0675, -0.7382, -0.7152, -0.7173],\n",
       "               [-2.2418, -1.5585, -4.6981, -1.0498, -5.6324, -0.8349, -4.4262]],\n",
       "\n",
       "              [[-1.8192, -1.8254, -1.8222, -1.8275, -1.8127, -1.8183, -1.8237],\n",
       "               [-0.9968, -0.9981, -1.0049, -0.999 , -0.9811, -0.976 , -0.9815],\n",
       "               [-0.8322, -0.8381, -0.8687, -0.8743, -1.0428, -1.1504, -1.1788],\n",
       "               [-0.8471, -0.8496, -0.8775, -0.8397, -0.8891, -0.939 , -0.9668],\n",
       "               [-0.8387, -0.8419, -0.8611, -0.8227, -0.8256, -0.8442, -0.8465],\n",
       "               [-0.9442, -0.905 , -0.83  , -0.8777, -0.8184, -0.8301, -0.8327],\n",
       "               [-0.9193, -1.2144, -0.9107, -0.8955, -1.0408, -1.0393, -1.2286],\n",
       "               [-1.0484, -1.0985, -1.1346, -1.0093, -0.9611, -1.0879, -0.9194],\n",
       "               [-1.0548, -0.9691, -0.8386, -0.9066, -0.884 , -0.8599, -0.8597],\n",
       "               [-1.1736, -1.5797, -1.9182, -1.1945, -0.88  , -0.8885, -1.938 ]],\n",
       "\n",
       "              [[-1.6449, -1.6464, -1.64  , -1.6476, -1.647 , -1.6523, -1.6511],\n",
       "               [-0.6801, -0.7073, -0.7039, -0.7181, -0.8834, -1.0006, -1.033 ],\n",
       "               [-0.4875, -0.4922, -0.4781, -0.475 , -0.4892, -0.4977, -0.5155],\n",
       "               [-0.534 , -0.5656, -0.5378, -0.5328, -0.5903, -0.7238, -0.7244],\n",
       "               [-0.5731, -0.543 , -0.5705, -0.6487, -0.6244, -0.6601, -0.7128],\n",
       "               [-0.5058, -0.5966, -0.4812, -0.4775, -0.5134, -0.5359, -0.5313],\n",
       "               [-0.7245, -0.6981, -0.5568, -0.7434, -0.6275, -0.5981, -0.7721],\n",
       "               [-1.0492, -1.4528, -2.8719, -0.5231, -0.6933, -0.5248, -1.0131],\n",
       "               [-1.0654, -1.1628, -0.7056, -1.2508, -0.9611, -0.5894, -1.1268],\n",
       "               [-1.0115, -2.2387, -0.9645, -0.709 , -1.0826, -0.8791, -1.1012]],\n",
       "\n",
       "              [[-1.4771, -1.463 , -1.4529, -1.4706, -1.4686, -1.4711, -1.4684],\n",
       "               [-0.8004, -0.7496, -0.7395, -0.7311, -1.0697, -1.3872, -1.4696],\n",
       "               [-0.5594, -0.5614, -0.5695, -0.5576, -0.5634, -0.5847, -0.5942],\n",
       "               [-0.5612, -0.9357, -0.5665, -0.5821, -0.6072, -0.6599, -0.6798],\n",
       "               [-0.5531, -0.5552, -0.5782, -0.5592, -0.5454, -0.5939, -0.591 ],\n",
       "               [-0.5324, -0.5374, -0.7942, -0.5398, -0.6308, -0.5803, -0.595 ],\n",
       "               [-0.8659, -0.6927, -0.7046, -0.6626, -0.5723, -0.5601, -0.6886],\n",
       "               [-0.6411, -0.826 , -0.7429, -0.6821, -0.5207, -0.5534, -0.5705],\n",
       "               [-0.7069, -0.7868, -1.1252, -0.6271, -0.6509, -0.5775, -0.6404],\n",
       "               [-0.5705, -0.7565, -0.6559, -0.5435, -0.5579, -0.5803, -0.8121]]]), 'p': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], 'eta': [0.0001, 0.001, 0.01, 0.1, 1, 10, 100]},\n",
       "       {'posterior_mean': array([[[-1.6907, -1.6647, -1.6438, -1.6227, -1.6167, -1.65  , -1.6616],\n",
       "               [-1.073 , -1.1086, -1.086 , -1.0794, -1.1549, -1.0853, -1.1359],\n",
       "               [-1.161 , -1.1943, -1.1408, -1.2073, -1.3393, -1.4483, -1.5107],\n",
       "               [-0.8893, -0.9214, -0.9012, -0.9225, -0.973 , -1.0219, -0.9955],\n",
       "               [-0.9004, -0.8787, -0.9135, -0.8923, -0.9591, -0.9689, -0.9522],\n",
       "               [-0.8844, -0.8991, -0.9009, -0.8585, -0.8899, -0.8953, -0.9004],\n",
       "               [-0.8953, -0.9169, -0.9635, -0.9127, -0.9052, -0.8966, -0.9243],\n",
       "               [-0.927 , -0.897 , -0.8982, -0.8497, -0.8616, -0.8629, -0.8593],\n",
       "               [-0.9014, -0.904 , -0.9392, -0.8925, -0.8943, -0.9108, -1.0076],\n",
       "               [-0.9589, -1.007 , -0.874 , -0.8526, -0.8483, -0.9424, -1.0765]],\n",
       "\n",
       "              [[-1.4957, -1.4961, -1.5076, -1.5162, -1.4938, -1.5349, -1.4822],\n",
       "               [-0.9267, -0.9211, -0.9351, -0.9538, -0.9327, -1.0493, -0.9889],\n",
       "               [-0.8467, -0.8924, -0.875 , -0.8937, -0.925 , -0.9286, -0.9075],\n",
       "               [-0.8518, -0.7515, -0.9167, -0.7687, -0.8711, -0.9346, -0.9401],\n",
       "               [-0.8185, -0.9334, -0.8676, -0.8153, -0.976 , -0.9509, -0.9687],\n",
       "               [-0.8219, -0.7613, -0.7533, -0.8534, -0.9087, -0.7545, -0.7556],\n",
       "               [-0.7613, -0.7721, -0.7538, -0.7196, -0.7508, -0.7832, -0.77  ],\n",
       "               [-0.7501, -0.9213, -0.7765, -0.7617, -0.7486, -0.7414, -0.7591],\n",
       "               [-0.7895, -0.7803, -0.8125, -0.7449, -0.7825, -0.7648, -0.852 ],\n",
       "               [-0.8001, -0.7598, -0.8029, -0.8143, -0.7722, -0.775 , -2.0849]],\n",
       "\n",
       "              [[-1.5996, -1.6176, -1.6194, -1.6077, -1.589 , -1.6026, -1.6712],\n",
       "               [-0.8138, -0.7936, -0.8124, -0.8068, -0.9788, -1.102 , -1.1884],\n",
       "               [-0.6953, -0.7594, -0.6153, -0.6299, -0.7416, -0.8846, -0.9144],\n",
       "               [-0.568 , -0.6296, -0.5978, -0.5925, -0.5834, -0.575 , -0.569 ],\n",
       "               [-0.5926, -0.6367, -0.6316, -0.6084, -0.6845, -0.816 , -1.1652],\n",
       "               [-0.6469, -0.8831, -0.6498, -0.6363, -0.5867, -0.5977, -0.6002],\n",
       "               [-0.8154, -0.7915, -0.7331, -0.7066, -0.7563, -0.7741, -0.7638],\n",
       "               [-0.6914, -0.6117, -0.6618, -0.6165, -0.5962, -0.624 , -1.0126],\n",
       "               [-0.8086, -0.7904, -0.7338, -0.7501, -0.6887, -0.6779, -1.548 ],\n",
       "               [-1.0616, -0.8848, -0.733 , -0.768 , -0.6184, -0.6539, -0.8768]],\n",
       "\n",
       "              [[-1.4317, -1.4023, -1.4384, -1.3911, -1.4251, -1.4191, -1.4271],\n",
       "               [-0.7722, -0.7359, -0.7433, -0.7254, -0.8205, -1.4506, -0.7968],\n",
       "               [-0.6471, -0.6722, -0.702 , -0.6452, -0.6883, -1.0386, -1.2628],\n",
       "               [-0.6459, -0.7687, -0.6355, -0.6402, -0.6899, -0.7007, -0.7179],\n",
       "               [-0.6776, -0.6969, -0.6978, -0.7043, -0.7811, -1.1862, -0.8237],\n",
       "               [-0.628 , -0.6667, -0.6452, -0.6255, -0.6774, -0.6379, -0.6321],\n",
       "               [-0.6708, -0.7673, -0.7925, -0.6634, -0.6419, -0.6367, -0.7944],\n",
       "               [-0.6277, -0.7006, -0.6426, -0.668 , -0.6269, -0.6334, -0.632 ],\n",
       "               [-0.7288, -0.7306, -0.7428, -0.7103, -0.9177, -0.6948, -0.7   ],\n",
       "               [-0.8198, -0.7355, -0.7792, -0.7275, -0.6752, -0.6677, -0.9503]],\n",
       "\n",
       "              [[-1.6528, -1.5527, -1.5304, -1.6092, -1.5688, -1.5714, -1.658 ],\n",
       "               [-0.9007, -0.9103, -0.9286, -0.95  , -1.2938, -1.435 , -1.4706],\n",
       "               [-0.8843, -0.8867, -0.8801, -0.9   , -0.8871, -0.9385, -0.943 ],\n",
       "               [-0.8682, -0.8669, -0.8622, -0.8631, -0.8418, -0.8833, -0.8016],\n",
       "               [-0.8983, -0.8803, -0.8823, -0.87  , -0.9153, -1.0222, -0.8479],\n",
       "               [-0.9226, -0.9442, -0.8928, -0.8992, -0.9049, -0.9092, -0.9116],\n",
       "               [-0.861 , -0.947 , -0.8771, -0.8747, -0.8946, -0.8783, -0.8814],\n",
       "               [-0.8798, -0.8883, -0.9341, -0.978 , -0.8908, -0.8967, -1.03  ],\n",
       "               [-0.8924, -0.8577, -0.9002, -0.8716, -0.9095, -0.9011, -0.9021],\n",
       "               [-0.9134, -0.8925, -0.9481, -0.9255, -0.8537, -0.8443, -1.4033]]]), 'mean': array([[[-1.8482, -1.6599, -1.7876, -1.8874, -2.436 , -1.8823, -1.6596],\n",
       "               [-1.0477, -1.2594, -1.2489, -1.0708, -1.7718, -1.381 , -1.7331],\n",
       "               [-1.384 , -1.958 , -1.4036, -1.6182, -1.53  , -1.68  , -1.7074],\n",
       "               [-1.436 , -0.9318, -0.8663, -1.2542, -0.954 , -1.3236, -0.9816],\n",
       "               [-0.9612, -1.0887, -1.7178, -1.2607, -0.9737, -1.271 , -1.0453],\n",
       "               [-1.7072, -1.6813, -0.8825, -1.541 , -0.8893, -0.9753, -0.8967],\n",
       "               [-1.1344, -1.3766, -1.826 , -1.5234, -1.2594, -1.2399, -0.9542],\n",
       "               [-1.0553, -1.7956, -1.4457, -1.1466, -0.8895, -0.878 , -0.8267],\n",
       "               [-1.4361, -1.4549, -1.6155, -1.3699, -0.9227, -0.9867, -0.9386],\n",
       "               [-1.9008, -2.4819, -1.4119, -1.3991, -1.0346, -1.1425, -1.147 ]],\n",
       "\n",
       "              [[-1.4949, -1.4937, -2.0261, -1.9071, -1.4962, -2.5989, -1.8528],\n",
       "               [-1.2075, -1.3687, -1.6782, -1.3377, -1.5297, -1.7562, -0.9852],\n",
       "               [-0.9471, -1.099 , -1.6103, -1.1519, -0.9271, -1.5342, -0.9103],\n",
       "               [-1.8384, -1.4874, -1.9449, -1.6173, -1.5531, -0.9436, -0.948 ],\n",
       "               [-1.8995, -1.5524, -1.7904, -0.8646, -1.0719, -0.9307, -0.9387],\n",
       "               [-1.4765, -1.1666, -1.6843, -1.1839, -1.547 , -0.7757, -0.7561],\n",
       "               [-1.4049, -2.0734, -1.7907, -1.5077, -0.7605, -0.767 , -0.7591],\n",
       "               [-1.6446, -1.8917, -1.602 , -1.5592, -0.9084, -0.7758, -0.789 ],\n",
       "               [-1.0009, -0.891 , -1.0892, -2.0278, -1.6923, -0.8226, -0.9505],\n",
       "               [-2.7749, -1.7413, -1.6577, -1.0164, -1.4534, -0.8413, -2.6292]],\n",
       "\n",
       "              [[-1.5955, -2.0895, -2.0065, -1.9221, -1.6961, -1.8823, -2.7352],\n",
       "               [-1.2519, -1.332 , -1.3909, -1.2116, -1.4113, -1.2989, -1.4331],\n",
       "               [-1.3229, -1.2701, -1.5995, -1.4737, -1.2762, -1.5822, -1.5528],\n",
       "               [-0.5669, -1.5038, -1.0237, -0.6058, -0.6125, -0.5904, -0.5908],\n",
       "               [-0.6723, -1.3626, -0.7858, -1.1833, -0.7045, -1.6541, -1.8387],\n",
       "               [-1.8081, -1.9304, -1.5599, -0.6521, -0.5943, -0.6264, -0.6318],\n",
       "               [-2.7567, -3.3142, -4.4036, -1.6585, -0.7363, -0.7618, -0.8628],\n",
       "               [-1.9593, -1.8145, -1.5817, -0.6793, -0.6238, -0.6845, -1.5715],\n",
       "               [-2.7829, -3.6294, -1.9257, -1.4614, -0.8786, -0.9227, -2.6335],\n",
       "               [-1.8974, -3.9852, -3.4793, -3.2802, -1.0773, -0.7438, -1.5192]],\n",
       "\n",
       "              [[-1.6204, -1.396 , -1.941 , -1.3949, -1.5715, -1.5517, -1.5928],\n",
       "               [-0.8103, -1.3422, -1.173 , -0.7224, -1.5776, -2.139 , -1.1386],\n",
       "               [-0.8092, -1.6788, -1.2503, -0.6911, -0.6808, -1.7216, -1.2793],\n",
       "               [-0.6649, -1.1176, -0.7341, -1.0651, -1.7007, -0.7468, -0.822 ],\n",
       "               [-1.2063, -1.2647, -1.5714, -1.5716, -0.9286, -1.7865, -0.8303],\n",
       "               [-1.2175, -1.2135, -1.1486, -0.8104, -1.2064, -0.7769, -0.9072],\n",
       "               [-1.3324, -1.7833, -1.9154, -0.6593, -1.1283, -0.6602, -0.8658],\n",
       "               [-1.1255, -1.6372, -1.2633, -1.4688, -0.6413, -0.6813, -0.6752],\n",
       "               [-1.4977, -1.7188, -1.5122, -1.4988, -1.2673, -0.8204, -0.7127],\n",
       "               [-1.863 , -1.1343, -1.617 , -1.5159, -0.811 , -0.9667, -1.122 ]],\n",
       "\n",
       "              [[-2.9544, -2.3524, -1.5362, -2.7237, -2.1057, -2.1589, -2.8554],\n",
       "               [-1.2231, -1.328 , -1.9591, -1.2368, -2.2705, -1.4362, -1.485 ],\n",
       "               [-1.1297, -0.9991, -1.4428, -1.0311, -0.8988, -1.5989, -1.6638],\n",
       "               [-1.1627, -1.5377, -1.1632, -2.0571, -0.8557, -1.5507, -1.5949],\n",
       "               [-1.307 , -1.9073, -0.992 , -0.8731, -1.5176, -1.8189, -0.8595],\n",
       "               [-1.5218, -1.1466, -1.6797, -0.9749, -0.9405, -0.9452, -0.9216],\n",
       "               [-1.4826, -1.6415, -1.1734, -2.084 , -0.8915, -0.9125, -0.8873],\n",
       "               [-1.6318, -1.4151, -1.7473, -1.1426, -0.8881, -0.9574, -1.1793],\n",
       "               [-2.4239, -1.6577, -1.7833, -1.8484, -0.9111, -0.9188, -1.0083],\n",
       "               [-1.001 , -1.8188, -2.6197, -1.6558, -0.8951, -0.9252, -2.1977]]]), 'median': array([[[-1.6611, -1.6597, -1.6598, -1.6585, -1.6583, -1.661 , -1.6601],\n",
       "               [-1.0834, -1.0849, -1.0844, -1.0854, -1.0873, -1.0805, -1.0787],\n",
       "               [-1.1495, -1.1608, -1.1603, -1.2193, -1.3545, -1.4935, -1.5347],\n",
       "               [-0.8603, -0.8688, -0.8764, -0.9332, -0.9531, -0.9807, -0.9837],\n",
       "               [-0.886 , -0.8856, -0.8691, -0.8904, -0.9226, -0.9282, -0.9409],\n",
       "               [-0.8642, -0.9337, -0.8093, -0.8726, -0.9375, -0.8996, -0.9186],\n",
       "               [-0.8491, -0.8615, -0.9047, -0.9855, -0.9259, -0.8795, -0.9467],\n",
       "               [-0.8089, -0.7712, -0.8783, -0.7777, -0.8673, -0.8724, -0.8477],\n",
       "               [-0.8149, -1.013 , -0.8576, -0.9095, -0.8043, -0.936 , -0.9564],\n",
       "               [-1.2949, -1.5488, -1.0275, -0.9991, -0.9567, -1.1171, -1.1066]],\n",
       "\n",
       "              [[-1.4946, -1.4938, -1.4955, -1.495 , -1.4972, -1.4978, -1.4933],\n",
       "               [-0.9494, -0.9452, -0.9469, -0.946 , -0.9438, -0.9447, -0.9516],\n",
       "               [-0.889 , -0.9076, -0.9232, -0.9384, -0.9273, -0.9125, -0.9095],\n",
       "               [-0.9686, -0.7553, -0.9536, -0.8035, -0.8719, -0.944 , -0.9506],\n",
       "               [-1.0455, -4.5062, -0.8827, -0.8076, -0.9307, -1.0123, -1.0241],\n",
       "               [-0.7732, -0.8508, -0.7804, -0.7511, -0.7557, -0.7856, -0.7708],\n",
       "               [-0.7569, -1.6349, -0.8215, -0.7393, -0.7891, -0.7705, -0.7435],\n",
       "               [-0.7142, -0.7856, -0.8602, -0.7421, -0.7498, -0.7689, -0.7344],\n",
       "               [-2.3211, -1.2438, -0.7774, -0.8904, -1.1555, -0.7955, -0.8771],\n",
       "               [-1.1372, -0.8444, -1.0351, -0.7862, -0.7805, -0.8471, -2.137 ]],\n",
       "\n",
       "              [[-1.5949, -1.5958, -1.5985, -1.5963, -1.5957, -1.5945, -1.596 ],\n",
       "               [-0.7866, -0.7852, -0.7865, -0.8076, -0.9424, -1.0877, -1.1264],\n",
       "               [-0.6426, -0.7763, -0.5593, -0.593 , -0.7218, -0.8018, -0.8241],\n",
       "               [-0.564 , -0.5946, -0.5901, -0.6088, -0.6052, -0.5636, -0.5623],\n",
       "               [-0.6087, -0.6157, -0.5645, -0.595 , -0.6759, -0.7015, -0.706 ],\n",
       "               [-0.5949, -0.568 , -0.6805, -0.608 , -0.5862, -0.585 , -0.5998],\n",
       "               [-0.8223, -0.7782, -3.0288, -0.7005, -0.7264, -0.7714, -0.9971],\n",
       "               [-0.9763, -0.662 , -0.7143, -0.6701, -0.5779, -0.7286, -0.7595],\n",
       "               [-0.7235, -3.9598, -0.7842, -0.9011, -0.8343, -0.722 , -1.9973],\n",
       "               [-2.616 , -3.2857, -2.8722, -1.0717, -0.5897, -0.6833, -1.3392]],\n",
       "\n",
       "              [[-1.3957, -1.3962, -1.396 , -1.395 , -1.3957, -1.3949, -1.3961],\n",
       "               [-0.7244, -0.726 , -0.7213, -0.7246, -0.7284, -0.7522, -0.7645],\n",
       "               [-0.6405, -0.635 , -0.6479, -0.6447, -0.6873, -0.8795, -1.0148],\n",
       "               [-0.6264, -0.8115, -0.6439, -0.6589, -0.6918, -0.733 , -0.8212],\n",
       "               [-0.7308, -0.6451, -0.6901, -0.7556, -0.8204, -0.8216, -0.8305],\n",
       "               [-0.6331, -0.6526, -0.6595, -0.8094, -0.6659, -0.6276, -0.8117],\n",
       "               [-0.7003, -0.7105, -0.6703, -0.6284, -0.6679, -0.6585, -0.9898],\n",
       "               [-0.7714, -0.7332, -0.6381, -0.6242, -0.6694, -0.6368, -0.7067],\n",
       "               [-0.9436, -0.6659, -0.8345, -0.8564, -0.8157, -0.7506, -0.7104],\n",
       "               [-0.9661, -0.6629, -5.3198, -0.9028, -0.7291, -0.7546, -0.9586]],\n",
       "\n",
       "              [[-1.5417, -1.5322, -1.5354, -1.5408, -1.5381, -1.541 , -1.5417],\n",
       "               [-0.8575, -0.8563, -0.8622, -0.9048, -1.1833, -1.4286, -1.4784],\n",
       "               [-0.8904, -0.885 , -0.9016, -0.8801, -0.8994, -0.9405, -0.9576],\n",
       "               [-0.8798, -0.8682, -0.879 , -0.8655, -0.8443, -0.8305, -0.8299],\n",
       "               [-0.8973, -0.8924, -0.8683, -0.8892, -0.8858, -0.8667, -0.8765],\n",
       "               [-0.9663, -0.9896, -0.9004, -0.8972, -0.9316, -0.9384, -0.9208],\n",
       "               [-0.9298, -1.1496, -0.9686, -0.8701, -0.914 , -0.9058, -0.8834],\n",
       "               [-2.7477, -1.1406, -0.9171, -0.9669, -0.907 , -0.9629, -0.98  ],\n",
       "               [-1.0101, -1.118 , -0.9158, -0.9697, -0.932 , -0.916 , -0.996 ],\n",
       "               [-0.8557, -1.1381, -1.3658, -1.0015, -0.8816, -0.9051, -1.2807]]]), 'mode': array([[[-1.6621, -1.654 , -1.6597, -1.6645, -1.6542, -1.6644, -1.6623],\n",
       "               [-1.0852, -1.0777, -1.0851, -1.0837, -1.0945, -1.0838, -1.0785],\n",
       "               [-1.1413, -1.1386, -1.1798, -1.1941, -1.3725, -1.4898, -1.5344],\n",
       "               [-0.858 , -0.8613, -0.8722, -0.8938, -0.9758, -0.9801, -0.9861],\n",
       "               [-0.9367, -0.8939, -0.8626, -0.8869, -0.8903, -0.9144, -0.9239],\n",
       "               [-0.9752, -0.8938, -0.8039, -0.912 , -0.9071, -0.8936, -0.9139],\n",
       "               [-0.8717, -0.864 , -0.9961, -0.9296, -0.9009, -0.8802, -0.9007],\n",
       "               [-0.7646, -0.8516, -0.8581, -0.9044, -0.8489, -0.9341, -0.7541],\n",
       "               [-0.8914, -0.8591, -0.8431, -0.7909, -0.8527, -0.8809, -0.9339],\n",
       "               [-1.1789, -1.668 , -1.5269, -0.8789, -0.8568, -1.003 , -1.1312]],\n",
       "\n",
       "              [[-1.4932, -1.4907, -1.4963, -1.4884, -1.4997, -1.4985, -1.4909],\n",
       "               [-0.9527, -0.949 , -0.9523, -0.9406, -0.9434, -0.9407, -0.9507],\n",
       "               [-0.9224, -0.9345, -0.9301, -0.9416, -0.9279, -0.9146, -0.9075],\n",
       "               [-0.7772, -0.7631, -1.0855, -0.8252, -0.8443, -0.9396, -0.9366],\n",
       "               [-1.0624, -1.9879, -0.8416, -0.8473, -1.0261, -0.9713, -0.9922],\n",
       "               [-0.8074, -0.9468, -0.9769, -0.7252, -0.7533, -0.7565, -0.76  ],\n",
       "               [-0.8728, -1.0881, -0.9882, -0.7288, -0.7841, -0.8293, -0.7374],\n",
       "               [-0.7804, -0.8246, -0.8874, -0.8006, -0.7536, -0.7516, -0.7494],\n",
       "               [-6.7177, -2.7914, -2.7537, -2.5743, -3.2368, -0.8579, -2.421 ],\n",
       "               [-2.4653, -1.1283, -0.9904, -0.7891, -0.7616, -1.0072, -1.8187]],\n",
       "\n",
       "              [[-1.5982, -1.5971, -1.6016, -1.5989, -1.5983, -1.5922, -1.5904],\n",
       "               [-0.7871, -0.7851, -0.7893, -0.8125, -0.9574, -1.0819, -1.1252],\n",
       "               [-0.6117, -0.803 , -0.5606, -0.5642, -0.6912, -0.7968, -0.8266],\n",
       "               [-0.68  , -0.6311, -0.6118, -0.6463, -0.5523, -0.5601, -0.5639],\n",
       "               [-0.5476, -0.62  , -0.6082, -0.6069, -0.6692, -0.7072, -0.726 ],\n",
       "               [-0.6377, -0.609 , -0.7603, -0.587 , -0.6025, -0.593 , -0.5996],\n",
       "               [-0.8007, -1.1807, -4.4815, -0.7176, -0.9104, -0.98  , -1.6082],\n",
       "               [-0.7062, -0.8631, -0.6971, -0.7511, -0.5828, -0.6449, -0.6613],\n",
       "               [-0.9849, -1.1722, -1.5463, -0.9809, -1.4436, -0.7438, -1.4263],\n",
       "               [-8.5241, -2.6584, -3.5442, -4.5615, -0.7257, -0.7655, -2.1794]],\n",
       "\n",
       "              [[-1.3957, -1.3935, -1.3871, -1.3926, -1.3959, -1.391 , -1.4009],\n",
       "               [-0.7234, -0.7237, -0.7214, -0.7268, -0.7189, -0.7427, -0.7663],\n",
       "               [-0.6413, -0.6478, -0.6322, -0.6541, -0.6893, -0.879 , -1.0013],\n",
       "               [-0.6441, -0.7139, -0.6766, -0.655 , -0.6973, -0.7329, -0.7472],\n",
       "               [-0.736 , -0.6596, -0.74  , -0.7   , -0.8131, -0.8266, -0.8267],\n",
       "               [-0.6345, -0.652 , -0.6463, -0.696 , -1.0311, -1.0603, -1.0085],\n",
       "               [-0.8277, -0.7511, -0.671 , -0.7106, -0.6713, -0.6836, -0.8234],\n",
       "               [-0.9792, -0.8097, -0.6634, -0.6674, -0.6815, -0.7525, -0.6969],\n",
       "               [-0.9308, -1.3687, -0.9952, -0.7815, -0.806 , -0.7607, -0.7624],\n",
       "               [-0.8438, -0.9811, -1.0176, -0.7956, -0.7111, -0.6805, -0.9246]],\n",
       "\n",
       "              [[-1.5345, -1.5307, -1.5233, -1.5353, -1.5343, -1.5609, -1.5439],\n",
       "               [-0.8492, -0.8589, -0.8644, -0.9096, -1.1723, -1.4291, -1.4763],\n",
       "               [-0.8843, -0.8756, -0.891 , -0.8739, -0.9116, -0.9461, -0.9703],\n",
       "               [-0.8736, -0.8584, -0.8854, -0.862 , -0.8599, -0.8497, -0.8542],\n",
       "               [-0.8948, -0.8809, -0.8861, -0.884 , -0.8628, -0.8436, -0.8687],\n",
       "               [-1.002 , -0.8701, -0.8652, -0.8762, -0.9206, -0.9017, -0.9053],\n",
       "               [-0.936 , -1.1073, -0.9717, -0.9245, -0.9167, -0.8971, -0.8736],\n",
       "               [-8.4772, -1.5938, -0.9771, -1.0075, -0.9225, -0.9212, -0.9433],\n",
       "               [-1.0678, -1.1747, -1.0449, -0.9504, -0.8851, -0.9092, -0.987 ],\n",
       "               [-1.1577, -1.0255, -1.3947, -0.9398, -0.8782, -0.8657, -0.9592]]]), 'p': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], 'eta': [0.0001, 0.001, 0.01, 0.1, 1, 10, 100]},\n",
       "       {'posterior_mean': array([[[-1.7178, -1.7304, -1.7286, -1.7091, -1.7377, -1.7406, -1.7664],\n",
       "               [-0.7449, -0.786 , -0.7616, -0.8514, -0.7788, -1.0692, -1.0006],\n",
       "               [-0.6737, -0.6762, -0.7774, -0.8139, -1.2124, -1.3332, -1.4254],\n",
       "               [-0.7231, -0.7111, -0.7122, -0.7273, -0.7434, -0.7638, -0.9972],\n",
       "               [-0.7487, -0.6705, -0.6645, -0.713 , -0.6763, -0.7124, -0.8086],\n",
       "               [-0.6721, -0.7756, -0.6518, -0.7365, -0.6977, -0.6825, -0.9334],\n",
       "               [-0.8083, -0.6784, -0.6794, -0.6467, -0.6594, -0.6791, -0.6702],\n",
       "               [-0.7294, -0.7158, -0.7251, -0.655 , -0.6141, -0.6177, -0.6084],\n",
       "               [-0.6928, -0.6573, -0.7193, -0.637 , -0.655 , -0.6555, -0.6697],\n",
       "               [-0.7466, -0.7427, -0.7515, -0.6745, -0.6972, -0.6805, -1.6483]],\n",
       "\n",
       "              [[-1.4172, -1.4012, -1.3961, -1.3846, -1.361 , -1.4097, -1.4532],\n",
       "               [-0.8609, -0.8336, -0.9381, -0.8474, -0.8932, -0.9115, -0.9525],\n",
       "               [-0.8229, -0.7868, -0.7815, -0.7682, -0.8441, -0.8509, -1.0155],\n",
       "               [-0.789 , -0.8226, -0.7982, -0.7868, -0.7756, -0.7776, -0.9289],\n",
       "               [-0.8231, -0.8094, -0.8611, -0.8561, -0.8923, -0.8549, -0.8437],\n",
       "               [-0.7943, -0.7715, -0.8469, -0.8065, -0.8368, -0.8129, -0.8239],\n",
       "               [-0.819 , -0.825 , -0.7835, -0.764 , -0.8599, -0.8388, -0.7507],\n",
       "               [-0.9157, -0.8511, -0.8668, -0.7872, -0.8376, -0.9991, -0.8675],\n",
       "               [-0.8455, -0.8073, -0.8302, -0.8395, -0.7631, -0.7596, -0.8281],\n",
       "               [-0.9232, -0.8276, -0.8402, -0.9114, -0.8381, -0.8955, -0.8954]],\n",
       "\n",
       "              [[-2.0214, -1.9945, -2.079 , -2.011 , -2.001 , -2.0007, -2.0694],\n",
       "               [-1.0825, -1.1377, -1.1066, -1.1027, -1.1828, -1.165 , -1.1635],\n",
       "               [-1.2009, -1.1685, -1.1131, -1.1071, -1.0957, -1.0878, -1.1631],\n",
       "               [-0.9919, -1.0323, -0.9449, -0.9647, -0.9184, -0.9501, -1.0608],\n",
       "               [-0.9359, -1.1971, -1.0027, -1.0281, -1.0377, -1.0632, -1.0561],\n",
       "               [-1.0329, -0.978 , -1.0243, -0.9194, -0.9817, -0.9426, -1.0509],\n",
       "               [-1.0608, -1.2335, -1.0555, -0.9331, -0.9402, -0.9015, -1.124 ],\n",
       "               [-0.9949, -1.0396, -0.9933, -1.0393, -0.9958, -1.0382, -1.2039],\n",
       "               [-1.0055, -1.2776, -0.9527, -0.8911, -0.9214, -0.9762, -0.948 ],\n",
       "               [-0.888 , -1.2252, -1.0989, -0.918 , -0.8856, -1.0498, -1.0303]],\n",
       "\n",
       "              [[-1.3584, -1.3578, -1.3468, -1.3739, -1.3351, -1.3564, -1.3524],\n",
       "               [-1.0217, -1.0426, -1.0134, -1.0608, -1.3434, -1.2456, -1.2343],\n",
       "               [-0.799 , -0.7774, -0.8009, -0.7677, -0.8705, -1.042 , -1.1157],\n",
       "               [-0.9047, -0.9061, -0.9068, -0.9006, -0.9818, -1.2032, -1.528 ],\n",
       "               [-0.7928, -0.8389, -0.8438, -0.8379, -0.8439, -0.848 , -0.8379],\n",
       "               [-0.8442, -0.8727, -0.8341, -0.7936, -0.7963, -0.8272, -0.9701],\n",
       "               [-0.8091, -0.9171, -0.8489, -0.8213, -0.8567, -0.8539, -0.8624],\n",
       "               [-0.7815, -0.8135, -0.8219, -0.8641, -0.8204, -0.8547, -0.9807],\n",
       "               [-0.9392, -0.8386, -0.8763, -0.8895, -0.9841, -0.9862, -1.0222],\n",
       "               [-0.9057, -0.8285, -0.7756, -0.8574, -0.8799, -0.8625, -0.9207]],\n",
       "\n",
       "              [[-1.2719, -1.2617, -1.2745, -1.2748, -1.2652, -1.2698, -1.4187],\n",
       "               [-0.9002, -0.8628, -0.8712, -0.8139, -0.9719, -1.1912, -1.1966],\n",
       "               [-0.7571, -0.765 , -0.6614, -0.6887, -0.8128, -0.6953, -1.2309],\n",
       "               [-0.6148, -0.6434, -0.6955, -0.6281, -0.7085, -0.7222, -0.725 ],\n",
       "               [-0.6576, -0.6397, -0.6916, -0.7939, -0.652 , -0.7906, -0.6899],\n",
       "               [-0.6603, -0.6256, -0.7378, -0.676 , -0.6002, -0.6211, -0.6589],\n",
       "               [-0.6477, -0.643 , -0.8076, -0.7613, -0.6679, -0.62  , -0.669 ],\n",
       "               [-0.695 , -0.6571, -0.7132, -0.6298, -0.7018, -0.7142, -0.7711],\n",
       "               [-0.6904, -0.7989, -0.8074, -0.5894, -0.5979, -0.6278, -0.7723],\n",
       "               [-0.7491, -0.7325, -0.6471, -0.7083, -0.6139, -0.7576, -1.3471]]]), 'mean': array([[[-2.7302, -1.7313, -1.7314, -2.1371, -2.3942, -2.396 , -2.0406],\n",
       "               [-1.1514, -1.3272, -1.0386, -1.812 , -1.6864, -2.9974, -2.9029],\n",
       "               [-1.5109, -1.3668, -1.1839, -0.8774, -1.7358, -1.719 , -1.4228],\n",
       "               [-1.3591, -0.9972, -1.4344, -1.6329, -1.5094, -0.8264, -2.5659],\n",
       "               [-1.8662, -1.6533, -1.4149, -1.4253, -0.7348, -1.4506, -1.3943],\n",
       "               [-0.8992, -1.7121, -0.5605, -1.8077, -1.6692, -0.7152, -1.5649],\n",
       "               [-1.7155, -1.4791, -1.4494, -1.3929, -1.4069, -0.6969, -0.6554],\n",
       "               [-2.4615, -1.8756, -2.0113, -1.7467, -0.572 , -0.6335, -0.6045],\n",
       "               [-1.9269, -1.403 , -1.8238, -0.5948, -0.656 , -0.6596, -0.6688],\n",
       "               [-3.8649, -3.4817, -2.9443, -1.6754, -0.7237, -0.7504, -2.0575]],\n",
       "\n",
       "              [[-2.4639, -1.8259, -1.8264, -1.8855, -1.3672, -2.3192, -2.29  ],\n",
       "               [-0.9957, -1.4694, -1.1319, -1.2499, -1.619 , -0.8931, -1.9333],\n",
       "               [-1.7101, -0.8766, -0.8203, -0.796 , -0.8692, -1.5371, -2.4172],\n",
       "               [-1.0622, -1.259 , -1.5867, -1.6126, -0.8074, -0.8049, -2.0516],\n",
       "               [-0.8822, -0.8908, -1.2384, -1.4955, -1.5144, -0.8582, -0.8519],\n",
       "               [-1.9801, -1.0166, -1.5813, -2.0945, -1.5432, -0.8181, -0.8447],\n",
       "               [-1.9619, -1.6446, -1.7481, -1.5778, -2.0263, -0.9442, -0.7783],\n",
       "               [-2.466 , -2.8097, -1.8733, -2.1713, -0.8709, -1.0042, -1.2153],\n",
       "               [-2.2856, -1.4373, -0.9692, -2.4426, -0.8325, -0.7602, -0.8732],\n",
       "               [-1.3808, -2.4906, -2.27  , -1.7118, -0.8769, -0.9252, -1.0077]],\n",
       "\n",
       "              [[-1.8874, -1.9943, -2.3513, -1.9446, -1.9951, -1.9949, -2.1152],\n",
       "               [-1.3047, -1.3486, -1.5166, -1.1076, -1.3044, -1.1665, -1.1625],\n",
       "               [-1.338 , -1.5735, -1.352 , -1.4403, -1.1108, -1.1112, -1.3676],\n",
       "               [-1.0336, -1.5265, -1.2974, -0.9435, -0.9177, -0.9478, -1.1382],\n",
       "               [-1.0067, -2.9319, -1.2713, -1.0202, -1.0723, -1.1749, -1.0662],\n",
       "               [-1.7067, -1.2203, -1.5211, -1.2868, -1.0404, -0.9288, -1.1153],\n",
       "               [-1.4043, -2.3124, -2.0964, -1.1363, -0.914 , -0.9618, -1.2269],\n",
       "               [-1.2987, -1.6165, -0.8423, -1.6969, -0.9472, -1.147 , -1.2161],\n",
       "               [-1.3681, -2.0418, -1.1168, -1.6715, -1.0024, -1.0123, -0.9744],\n",
       "               [-1.2962, -1.7529, -1.687 , -1.2224, -0.94  , -1.1043, -1.1134]],\n",
       "\n",
       "              [[-1.9082, -1.5643, -1.5525, -1.7874, -1.6386, -1.7368, -1.913 ],\n",
       "               [-1.2581, -1.2807, -1.6962, -1.1073, -1.6086, -1.6092, -1.2356],\n",
       "               [-0.8999, -1.0343, -1.3302, -0.9607, -1.2883, -1.0327, -1.5457],\n",
       "               [-1.3946, -1.279 , -1.6437, -1.127 , -1.4502, -1.6148, -1.5431],\n",
       "               [-1.8228, -0.858 , -1.8514, -1.5099, -0.8654, -0.868 , -0.8421],\n",
       "               [-1.0364, -1.3084, -1.4526, -1.6654, -1.2729, -1.3119, -1.6867],\n",
       "               [-1.3343, -1.8161, -1.3187, -1.4955, -1.4498, -0.9827, -0.9472],\n",
       "               [-1.8051, -1.8798, -2.1624, -1.5706, -1.5163, -1.0302, -1.0289],\n",
       "               [-1.22  , -1.4404, -1.6082, -0.8817, -1.1206, -1.043 , -1.048 ],\n",
       "               [-1.6512, -1.857 , -2.0233, -0.9103, -0.8601, -0.883 , -0.8226]],\n",
       "\n",
       "              [[-1.8767, -1.266 , -1.7294, -1.2645, -1.7714, -1.7473, -2.5019],\n",
       "               [-2.1275, -1.8749, -1.6143, -1.694 , -1.7746, -2.0693, -2.0168],\n",
       "               [-1.1773, -1.2786, -0.8779, -1.3329, -0.8398, -1.4516, -2.0467],\n",
       "               [-1.6991, -0.9166, -1.9688, -0.6293, -0.7666, -1.4795, -0.7095],\n",
       "               [-1.7019, -2.0769, -0.9428, -1.6369, -0.6539, -1.9154, -0.7195],\n",
       "               [-0.7441, -1.5396, -1.5654, -2.1405, -0.5877, -0.7394, -0.8107],\n",
       "               [-1.0449, -1.7677, -2.128 , -2.2298, -1.2877, -0.583 , -0.9435],\n",
       "               [-2.9273, -2.3646, -2.2323, -1.4941, -1.5084, -0.9172, -0.8479],\n",
       "               [-2.5348, -3.7134, -2.6601, -1.6202, -0.6797, -0.8886, -1.083 ],\n",
       "               [-2.5458, -2.6679, -0.8591, -1.8149, -0.6719, -0.7868, -1.4282]]]), 'median': array([[[-1.732 , -1.732 , -1.7317, -1.7303, -1.7304, -1.7323, -1.7311],\n",
       "               [-0.7729, -0.7766, -0.7772, -0.7752, -0.7691, -0.7629, -0.7656],\n",
       "               [-0.6495, -0.6586, -0.7122, -0.8438, -1.1363, -1.3872, -1.4219],\n",
       "               [-0.678 , -0.6719, -0.6385, -0.7137, -0.7479, -0.7566, -0.7445],\n",
       "               [-0.649 , -0.6826, -0.6691, -0.6904, -0.672 , -0.6962, -0.6724],\n",
       "               [-0.879 , -1.0085, -0.6395, -0.9062, -0.743 , -0.7332, -0.6995],\n",
       "               [-0.7659, -0.6878, -0.6032, -0.6289, -0.6447, -0.6806, -0.622 ],\n",
       "               [-0.8854, -0.6347, -0.7235, -0.6606, -0.6006, -0.6656, -0.6181],\n",
       "               [-0.7609, -0.691 , -0.7662, -0.6416, -0.5939, -0.6406, -0.6534],\n",
       "               [-2.0319, -1.3112, -1.4668, -0.6976, -0.7266, -0.7052, -1.6182]],\n",
       "\n",
       "              [[-1.3654, -1.3681, -1.3654, -1.3677, -1.3678, -1.3669, -1.3682],\n",
       "               [-0.8299, -0.8278, -0.8355, -0.8316, -0.8346, -0.8581, -0.8833],\n",
       "               [-0.7719, -0.7705, -0.7746, -0.7751, -0.8117, -0.8309, -0.8307],\n",
       "               [-0.7487, -0.787 , -0.7806, -0.7779, -0.7848, -0.779 , -0.7857],\n",
       "               [-0.8425, -0.8124, -0.8537, -0.8538, -0.8717, -0.8717, -0.8367],\n",
       "               [-0.7881, -0.7783, -0.7803, -0.8103, -0.8086, -0.819 , -0.8681],\n",
       "               [-0.7854, -0.9422, -0.7987, -0.7617, -0.7837, -0.8347, -0.8011],\n",
       "               [-1.2615, -1.4902, -0.9482, -0.8562, -0.879 , -1.0384, -0.8697],\n",
       "               [-0.8268, -0.7564, -0.9733, -0.838 , -0.7893, -0.7573, -0.829 ],\n",
       "               [-0.7739, -0.9242, -0.905 , -0.9435, -0.9213, -0.9013, -0.9939]],\n",
       "\n",
       "              [[-1.995 , -1.9948, -2.    , -1.9945, -1.9954, -1.9953, -1.9993],\n",
       "               [-1.0383, -1.0364, -1.043 , -1.062 , -1.1237, -1.1549, -1.1619],\n",
       "               [-1.0468, -1.0426, -1.0455, -1.0614, -1.0806, -1.0774, -1.0797],\n",
       "               [-0.9263, -0.951 , -0.9659, -0.9308, -0.9074, -0.921 , -0.9405],\n",
       "               [-0.9529, -1.0169, -0.9623, -0.9979, -1.0534, -1.0949, -1.0765],\n",
       "               [-0.8806, -1.0356, -0.9433, -0.9619, -0.9314, -0.9276, -0.9386],\n",
       "               [-1.2826, -1.0094, -1.3365, -0.9379, -0.9386, -1.0188, -1.0069],\n",
       "               [-0.8768, -1.0607, -0.9517, -1.0063, -0.9466, -1.021 , -1.4096],\n",
       "               [-1.1699, -8.341 , -0.8661, -0.8793, -0.9449, -0.9976, -0.9214],\n",
       "               [-0.9785, -1.2759, -1.0042, -0.9622, -0.922 , -1.0442, -1.0759]],\n",
       "\n",
       "              [[-1.3751, -1.3747, -1.3773, -1.3783, -1.3767, -1.3782, -1.376 ],\n",
       "               [-1.078 , -1.0732, -1.0693, -1.0854, -1.1365, -1.2021, -1.2358],\n",
       "               [-0.8123, -0.8227, -0.8114, -0.8027, -0.8656, -1.0441, -1.1663],\n",
       "               [-0.9934, -0.982 , -0.9952, -0.8749, -0.9257, -1.0989, -1.1369],\n",
       "               [-0.8664, -0.8506, -0.7926, -0.8708, -0.8757, -0.8066, -0.8053],\n",
       "               [-0.926 , -0.8699, -0.8252, -0.8318, -0.8419, -0.8511, -0.8498],\n",
       "               [-0.8344, -0.8834, -0.9467, -0.9178, -0.9319, -0.8563, -0.9379],\n",
       "               [-0.8401, -1.0075, -1.1413, -0.853 , -0.9857, -1.0325, -1.0458],\n",
       "               [-1.1082, -1.0177, -0.8781, -0.8673, -0.9976, -1.0439, -1.0227],\n",
       "               [-0.9941, -1.1085, -0.9451, -0.8768, -0.8421, -0.8606, -0.8844]],\n",
       "\n",
       "              [[-1.2702, -1.2647, -1.2665, -1.266 , -1.2677, -1.2687, -1.2808],\n",
       "               [-0.848 , -0.8532, -0.8515, -0.8671, -0.9971, -1.1617, -1.2061],\n",
       "               [-0.7906, -0.8083, -0.6744, -0.6779, -0.8363, -0.8748, -0.9178],\n",
       "               [-0.627 , -0.6506, -0.6582, -0.6386, -0.6835, -0.7054, -0.7229],\n",
       "               [-0.6501, -0.6778, -0.6057, -0.6177, -0.6497, -0.6582, -0.6922],\n",
       "               [-0.6966, -0.6098, -0.698 , -0.6411, -0.6605, -0.7147, -0.7381],\n",
       "               [-0.632 , -0.7516, -0.7697, -0.7484, -0.6446, -0.6381, -0.7977],\n",
       "               [-0.9627, -0.8722, -0.9056, -0.6793, -0.7075, -0.7485, -0.7882],\n",
       "               [-0.9572, -1.3074, -0.7577, -0.8046, -0.6451, -0.7255, -1.0706],\n",
       "               [-0.7589, -0.7631, -0.7145, -0.7224, -0.6329, -0.713 , -1.2781]]]), 'mode': array([[[ -1.7289,  -1.7474,  -1.7405,  -1.7399,  -1.7151,  -1.7317,\n",
       "                 -1.7258],\n",
       "               [ -0.7746,  -0.7814,  -0.7784,  -0.77  ,  -0.7641,  -0.763 ,\n",
       "                 -0.7733],\n",
       "               [ -0.68  ,  -0.6953,  -0.7039,  -0.9684,  -1.1134,  -1.3681,\n",
       "                 -1.3902],\n",
       "               [ -0.8232,  -0.6641,  -0.7826,  -0.7363,  -0.772 ,  -0.7551,\n",
       "                 -0.7497],\n",
       "               [ -0.6835,  -0.6979,  -0.7152,  -0.6802,  -0.6936,  -0.705 ,\n",
       "                 -0.6489],\n",
       "               [ -0.7294,  -0.931 ,  -0.6979,  -0.8628,  -0.7789,  -0.916 ,\n",
       "                 -0.7568],\n",
       "               [ -0.7776,  -0.8061,  -0.7805,  -0.6628,  -0.7111,  -0.7347,\n",
       "                 -0.641 ],\n",
       "               [ -0.7302,  -0.7111,  -0.8473,  -0.7261,  -0.7255,  -0.6231,\n",
       "                 -0.6199],\n",
       "               [ -0.7222,  -0.6952,  -0.6872,  -0.7172,  -0.634 ,  -0.6122,\n",
       "                 -0.7348],\n",
       "               [ -7.7515,  -4.795 ,  -4.4819,  -0.7584,  -0.9807,  -1.0113,\n",
       "                 -2.2755]],\n",
       "\n",
       "              [[ -1.3664,  -1.3484,  -1.3639,  -1.3628,  -1.3739,  -1.3681,\n",
       "                 -1.3568],\n",
       "               [ -0.8262,  -0.8367,  -0.8351,  -0.8247,  -0.847 ,  -0.8675,\n",
       "                 -0.8817],\n",
       "               [ -0.7765,  -0.7716,  -0.7696,  -0.7763,  -0.8111,  -0.835 ,\n",
       "                 -0.8281],\n",
       "               [ -0.7567,  -0.7795,  -0.7759,  -0.7701,  -0.7925,  -0.7798,\n",
       "                 -0.7957],\n",
       "               [ -0.8408,  -0.9047,  -0.8567,  -0.8743,  -0.886 ,  -0.882 ,\n",
       "                 -0.8791],\n",
       "               [ -0.7687,  -0.8091,  -0.7832,  -0.7786,  -0.8362,  -0.8629,\n",
       "                 -0.834 ],\n",
       "               [ -0.8357,  -0.8857,  -0.8256,  -0.805 ,  -0.781 ,  -0.8147,\n",
       "                 -0.7481],\n",
       "               [ -0.8867,  -1.5425,  -1.4274,  -0.7905,  -0.8749,  -1.1187,\n",
       "                 -0.9378],\n",
       "               [ -0.8822,  -0.846 ,  -0.9455,  -0.8741,  -0.7753,  -0.802 ,\n",
       "                 -0.8486],\n",
       "               [ -0.8494,  -0.9758,  -1.061 ,  -0.9578,  -0.9198,  -0.9338,\n",
       "                 -0.8216]],\n",
       "\n",
       "              [[ -1.9917,  -1.9943,  -2.0051,  -1.9857,  -2.0035,  -1.9933,\n",
       "                 -2.0032],\n",
       "               [ -1.0189,  -1.0284,  -1.0136,  -1.084 ,  -1.1309,  -1.1533,\n",
       "                 -1.1604],\n",
       "               [ -1.0334,  -0.9816,  -1.0291,  -1.0443,  -1.0956,  -1.065 ,\n",
       "                 -1.071 ],\n",
       "               [ -0.9509,  -0.9697,  -1.0213,  -0.9343,  -0.9097,  -0.923 ,\n",
       "                 -0.9565],\n",
       "               [ -0.9601,  -1.0332,  -0.9784,  -0.9825,  -1.052 ,  -1.0639,\n",
       "                 -1.0677],\n",
       "               [ -1.0494,  -1.0085,  -0.9342,  -0.9341,  -0.943 ,  -0.9293,\n",
       "                 -0.9114],\n",
       "               [ -1.0631,  -1.2506,  -1.0493,  -1.0086,  -1.004 ,  -1.0585,\n",
       "                 -1.0234],\n",
       "               [ -0.9583,  -0.9496,  -0.9476,  -0.9208,  -0.8975,  -1.0715,\n",
       "                 -1.2668],\n",
       "               [ -1.0779, -10.2663,  -0.9633,  -0.9163,  -0.9427,  -0.8811,\n",
       "                 -0.988 ],\n",
       "               [ -0.9074,  -1.2602,  -1.208 ,  -0.9127,  -0.9945,  -1.0886,\n",
       "                 -1.0039]],\n",
       "\n",
       "              [[ -1.3741,  -1.3825,  -1.3763,  -1.3852,  -1.3805,  -1.379 ,\n",
       "                 -1.3818],\n",
       "               [ -1.0861,  -1.0722,  -1.0759,  -1.0777,  -1.1372,  -1.2058,\n",
       "                 -1.2329],\n",
       "               [ -0.8531,  -0.8292,  -0.8319,  -0.8498,  -0.8576,  -1.0402,\n",
       "                 -1.1645],\n",
       "               [ -0.9175,  -1.1513,  -0.8628,  -0.8375,  -0.9061,  -1.0693,\n",
       "                 -1.0891],\n",
       "               [ -0.9253,  -0.8507,  -0.9155,  -0.8965,  -0.8782,  -0.8334,\n",
       "                 -0.8055],\n",
       "               [ -1.0862,  -0.9914,  -0.8227,  -0.8948,  -0.8872,  -0.9475,\n",
       "                 -0.8533],\n",
       "               [ -0.8545,  -0.9466,  -0.8618,  -0.9812,  -0.8515,  -0.8841,\n",
       "                 -0.9422],\n",
       "               [ -0.9316,  -0.9483,  -0.984 ,  -0.8984,  -1.2433,  -1.2405,\n",
       "                 -1.3937],\n",
       "               [ -1.3187,  -0.9182,  -0.8872,  -0.8883,  -1.0066,  -0.9991,\n",
       "                 -1.0206],\n",
       "               [ -0.8497,  -0.9892,  -1.1356,  -0.7997,  -0.7981,  -0.884 ,\n",
       "                 -0.8298]],\n",
       "\n",
       "              [[ -1.2524,  -1.2796,  -1.2799,  -1.272 ,  -1.2778,  -1.2549,\n",
       "                 -1.2794],\n",
       "               [ -0.849 ,  -0.8539,  -0.8554,  -0.8492,  -0.9982,  -1.162 ,\n",
       "                 -1.1933],\n",
       "               [ -0.8569,  -0.6577,  -0.6592,  -0.6962,  -0.8374,  -0.8383,\n",
       "                 -0.9078],\n",
       "               [ -0.6305,  -0.6519,  -0.5961,  -0.6343,  -0.6868,  -0.7209,\n",
       "                 -0.7271],\n",
       "               [ -0.6543,  -0.6676,  -0.6487,  -0.6386,  -0.6593,  -0.6604,\n",
       "                 -0.6944],\n",
       "               [ -0.6083,  -0.626 ,  -0.7721,  -0.6667,  -0.6432,  -0.6488,\n",
       "                 -0.697 ],\n",
       "               [ -0.6023,  -0.7549,  -0.8563,  -0.7803,  -0.6295,  -0.6123,\n",
       "                 -0.7499],\n",
       "               [ -1.0021,  -1.056 ,  -0.8255,  -0.6564,  -0.6981,  -0.6611,\n",
       "                 -0.7488],\n",
       "               [ -0.9409,  -0.8405,  -1.0487,  -0.6093,  -0.632 ,  -0.7218,\n",
       "                 -0.9605],\n",
       "               [ -1.2581,  -0.8232,  -0.968 ,  -0.7042,  -0.6456,  -0.8597,\n",
       "                 -1.2668]]]), 'p': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], 'eta': [0.0001, 0.001, 0.01, 0.1, 1, 10, 100]}                                                   ,\n",
       "       {'posterior_mean': array([[[-1.5146, -1.5006, -1.5169, -1.5445, -1.5125, -1.5195, -1.6179],\n",
       "               [-0.8336, -0.7644, -0.7806, -0.7864, -0.8027, -0.9942, -1.2718],\n",
       "               [-0.8929, -0.9462, -0.8814, -0.8486, -1.0482, -1.1642, -1.3411],\n",
       "               [-0.8377, -0.8443, -0.7852, -0.8372, -0.7595, -0.8396, -0.7511],\n",
       "               [-0.723 , -0.6976, -0.7891, -0.7448, -0.7167, -0.9595, -0.6929],\n",
       "               [-0.7982, -0.7744, -0.7864, -0.7523, -0.7404, -0.6858, -0.6823],\n",
       "               [-0.8789, -0.83  , -0.812 , -0.8192, -0.8936, -0.8068, -0.7501],\n",
       "               [-1.1544, -0.8986, -0.8775, -0.7147, -0.6909, -0.7066, -0.7194],\n",
       "               [-0.8806, -0.8914, -0.997 , -0.7655, -0.6852, -0.6591, -0.7256],\n",
       "               [-0.7689, -0.8639, -0.8223, -0.7532, -0.6951, -0.6871, -1.071 ]],\n",
       "\n",
       "              [[-1.3058, -1.3202, -1.3089, -1.3178, -1.3061, -1.333 , -1.3245],\n",
       "               [-0.8235, -0.7889, -0.7817, -0.8015, -0.8379, -0.8978, -0.9163],\n",
       "               [-0.614 , -0.7284, -0.7423, -0.7215, -0.7854, -0.8462, -0.8742],\n",
       "               [-0.6059, -0.6026, -0.6045, -0.5969, -0.594 , -0.5902, -0.6043],\n",
       "               [-0.6338, -0.6252, -0.6778, -0.6386, -0.5944, -0.7134, -0.716 ],\n",
       "               [-0.6952, -0.7517, -0.6805, -0.5829, -0.5762, -0.5819, -0.5863],\n",
       "               [-0.6646, -0.75  , -0.6275, -0.6527, -0.6165, -0.6142, -0.6607],\n",
       "               [-0.7149, -0.667 , -0.6402, -0.6459, -0.633 , -0.6356, -0.6895],\n",
       "               [-0.7173, -0.6508, -0.6921, -0.6535, -0.6425, -0.8294, -0.7643],\n",
       "               [-0.7668, -0.7007, -0.6807, -0.6728, -0.7378, -0.8238, -1.8157]],\n",
       "\n",
       "              [[-1.5691, -1.4992, -1.6035, -1.5113, -1.541 , -1.4694, -1.5505],\n",
       "               [-1.0536, -1.0909, -1.0432, -1.0871, -1.2923, -1.4075, -1.4446],\n",
       "               [-0.9701, -0.9452, -0.9433, -0.9036, -0.9368, -0.9167, -1.0147],\n",
       "               [-0.8393, -0.874 , -0.9138, -0.9127, -0.9711, -1.0083, -1.0528],\n",
       "               [-0.8354, -0.795 , -0.9005, -0.8317, -0.8124, -0.8168, -0.8514],\n",
       "               [-0.8666, -0.9416, -0.8666, -0.9311, -0.8732, -0.8978, -0.9399],\n",
       "               [-0.8694, -0.8   , -0.8931, -0.7633, -0.7457, -0.7292, -0.8206],\n",
       "               [-0.8489, -1.057 , -0.8321, -0.785 , -0.7491, -0.7921, -0.8214],\n",
       "               [-0.7991, -0.8483, -0.8203, -0.8388, -0.7691, -0.7399, -0.8305],\n",
       "               [-0.8394, -0.948 , -0.871 , -0.7663, -0.7407, -0.73  , -0.9358]],\n",
       "\n",
       "              [[-1.6171, -1.6233, -1.6759, -1.6483, -1.6436, -1.6259, -1.6417],\n",
       "               [-0.9195, -0.9348, -1.0146, -0.9793, -1.1967, -1.6127, -1.5764],\n",
       "               [-0.7174, -0.7105, -0.694 , -0.7391, -0.9197, -1.0105, -0.9724],\n",
       "               [-0.801 , -0.6897, -0.7188, -0.8028, -0.8725, -1.0119, -0.8069],\n",
       "               [-0.8221, -0.8567, -0.8511, -0.8823, -0.8292, -0.9395, -0.9398],\n",
       "               [-0.7041, -0.7598, -0.7118, -0.7861, -0.6808, -0.6923, -0.6853],\n",
       "               [-0.7964, -0.6838, -0.7417, -0.6928, -0.6998, -0.6754, -0.7091],\n",
       "               [-0.7483, -0.8247, -0.7535, -0.7207, -0.7107, -0.697 , -0.8664],\n",
       "               [-0.8938, -0.7052, -0.7179, -0.6934, -0.669 , -0.7652, -0.7604],\n",
       "               [-0.9212, -0.7996, -0.8713, -0.76  , -0.6778, -0.7234, -0.799 ]],\n",
       "\n",
       "              [[-1.3253, -1.3273, -1.3345, -1.3498, -1.3223, -1.3585, -1.3264],\n",
       "               [-0.8872, -0.9921, -0.8899, -0.9421, -1.1865, -1.2979, -1.4315],\n",
       "               [-0.8636, -0.782 , -0.8168, -0.7941, -0.9076, -0.9711, -0.9706],\n",
       "               [-0.7807, -0.7299, -0.7348, -0.7381, -0.7958, -1.1054, -0.8306],\n",
       "               [-0.7753, -0.8004, -0.7476, -0.7399, -0.8268, -0.7911, -1.0137],\n",
       "               [-0.7417, -0.8796, -0.7476, -0.7618, -0.7706, -0.8166, -0.8303],\n",
       "               [-0.7707, -0.7846, -0.8653, -0.7671, -0.7714, -0.7944, -0.7768],\n",
       "               [-0.7932, -0.9032, -0.8671, -0.8798, -0.7789, -0.9961, -0.968 ],\n",
       "               [-0.8054, -0.8118, -1.2313, -0.7634, -0.7513, -0.8404, -1.3835],\n",
       "               [-0.8083, -1.1209, -0.8881, -0.8397, -0.8637, -0.9841, -2.0369]]]), 'mean': array([[[-1.7298, -2.0692, -1.7717, -1.6535, -1.785 , -1.6509, -2.259 ],\n",
       "               [-1.5603, -1.9179, -1.4992, -0.7825, -0.8166, -2.1206, -2.7034],\n",
       "               [-1.996 , -1.0784, -1.2722, -0.9   , -1.3982, -1.1912, -1.5302],\n",
       "               [-1.7213, -2.257 , -1.445 , -1.3034, -0.7483, -1.2036, -0.7443],\n",
       "               [-0.8484, -1.562 , -1.7771, -0.8172, -0.7817, -1.1134, -0.7827],\n",
       "               [-0.9014, -1.1304, -1.2645, -1.5516, -1.1646, -0.7229, -0.7273],\n",
       "               [-2.2147, -1.4016, -1.7913, -0.8849, -1.2534, -0.7875, -0.7825],\n",
       "               [-3.6041, -1.9284, -2.8288, -1.1661, -0.7015, -0.7474, -0.7424],\n",
       "               [-3.0257, -2.2465, -2.5419, -1.2735, -1.2612, -0.7517, -0.8769],\n",
       "               [-2.3458, -2.5686, -2.0559, -1.7309, -0.7081, -0.9606, -1.219 ]],\n",
       "\n",
       "              [[-1.494 , -1.7703, -2.3035, -1.504 , -2.3173, -2.1712, -2.2735],\n",
       "               [-2.4313, -0.9211, -0.7846, -0.9401, -1.4887, -1.6229, -1.4149],\n",
       "               [-0.7849, -2.0731, -1.1194, -1.5256, -0.7937, -1.7914, -1.5287],\n",
       "               [-1.5168, -1.5369, -1.3703, -1.6607, -0.583 , -1.2668, -0.598 ],\n",
       "               [-1.4407, -1.3922, -1.8321, -1.7664, -0.6343, -1.0541, -1.4554],\n",
       "               [-0.895 , -1.3599, -1.3652, -1.4702, -0.5866, -0.5851, -0.5911],\n",
       "               [-2.0397, -1.6811, -1.5749, -0.7938, -0.7968, -0.6847, -1.0551],\n",
       "               [-2.0759, -1.193 , -1.4047, -1.0984, -1.4272, -0.6765, -0.8535],\n",
       "               [-1.7699, -3.2503, -1.6408, -0.8201, -0.6823, -0.8965, -0.7715],\n",
       "               [-2.2051, -2.0187, -1.7452, -1.7671, -1.0032, -1.2167, -2.1165]],\n",
       "\n",
       "              [[-1.5689, -1.977 , -1.8606, -1.9212, -1.8643, -2.9093, -2.0888],\n",
       "               [-1.3472, -1.9085, -1.9436, -1.0947, -1.2826, -1.8909, -2.2345],\n",
       "               [-1.3651, -1.4295, -0.9164, -0.9031, -0.9293, -1.5129, -1.4873],\n",
       "               [-1.5172, -1.0373, -0.8469, -1.4107, -1.4018, -1.3918, -1.7809],\n",
       "               [-2.1416, -0.8576, -1.9695, -1.3177, -0.8286, -0.8298, -1.5148],\n",
       "               [-2.1795, -2.0794, -1.7151, -2.1897, -0.8606, -0.8724, -0.9227],\n",
       "               [-1.3868, -1.5586, -1.7203, -0.7569, -0.746 , -1.1754, -0.9367],\n",
       "               [-1.6829, -3.1484, -0.9539, -1.8536, -1.3799, -0.8059, -0.8599],\n",
       "               [-1.9338, -2.5242, -2.3982, -1.7469, -0.788 , -0.7492, -0.9566],\n",
       "               [-2.0672, -2.4791, -1.3783, -1.2403, -0.76  , -0.7164, -1.2164]],\n",
       "\n",
       "              [[-2.1828, -2.1397, -3.4957, -2.1016, -2.1034, -2.1349, -2.522 ],\n",
       "               [-1.5888, -1.6206, -1.7618, -1.5771, -1.2323, -3.4073, -2.9426],\n",
       "               [-0.8267, -1.0899, -0.6737, -0.8586, -1.5754, -0.9638, -1.5113],\n",
       "               [-1.6493, -1.2136, -1.2039, -1.8483, -1.3326, -1.7133, -1.5394],\n",
       "               [-2.4225, -3.4441, -3.0774, -1.884 , -0.9825, -1.3989, -0.9392],\n",
       "               [-1.0681, -1.771 , -1.4548, -1.3228, -0.6606, -0.6685, -0.6688],\n",
       "               [-1.106 , -1.3401, -1.5359, -0.6964, -0.6901, -0.6974, -0.7858],\n",
       "               [-1.5812, -1.4069, -2.1895, -1.2433, -1.0714, -0.8001, -1.0736],\n",
       "               [-4.4734, -1.2782, -2.3714, -1.5577, -0.7033, -0.9977, -1.0432],\n",
       "               [-2.7372, -2.5509, -1.8684, -1.3277, -0.7949, -0.7427, -0.8865]],\n",
       "\n",
       "              [[-2.2105, -1.3328, -1.3318, -2.2364, -1.9171, -2.2673, -1.8624],\n",
       "               [-1.4536, -1.2682, -1.3582, -1.8612, -1.331 , -1.3432, -2.5202],\n",
       "               [-1.4697, -1.0022, -0.7942, -1.6903, -0.9263, -2.1733, -1.7069],\n",
       "               [-1.5779, -1.136 , -2.0062, -1.5519, -0.8348, -2.4129, -1.5565],\n",
       "               [-1.954 , -1.1413, -1.5297, -1.4687, -1.0467, -1.9749, -2.1305],\n",
       "               [-2.6585, -1.6557, -1.6598, -0.7518, -0.7704, -1.0097, -0.8345],\n",
       "               [-1.6122, -1.7414, -2.0938, -1.6484, -0.8018, -0.8021, -0.7902],\n",
       "               [-3.5684, -2.21  , -3.3898, -2.4098, -1.0832, -1.0528, -1.159 ],\n",
       "               [-1.7151, -1.9422, -2.3967, -0.7486, -0.7933, -0.8359, -2.1969],\n",
       "               [-3.7347, -3.7626, -2.1007, -1.1385, -0.7847, -0.8945, -3.1525]]]), 'median': array([[[-1.4726, -1.4709, -1.4721, -1.4734, -1.4724, -1.4736, -1.4731],\n",
       "               [-0.7498, -0.7477, -0.747 , -0.7482, -0.747 , -0.7469, -0.7464],\n",
       "               [-0.8177, -0.8361, -0.8244, -0.8411, -1.0262, -1.1914, -1.2293],\n",
       "               [-0.8049, -0.895 , -0.7882, -0.788 , -0.743 , -0.7579, -0.7353],\n",
       "               [-0.7355, -0.6902, -0.7876, -0.846 , -0.7808, -0.8989, -0.8533],\n",
       "               [-0.7476, -0.7589, -0.7744, -0.7402, -0.7821, -0.7134, -0.7115],\n",
       "               [-0.8583, -0.9512, -0.8015, -0.8969, -0.8709, -0.8034, -0.8098],\n",
       "               [-0.8971, -1.0938, -0.8707, -0.7089, -0.7257, -0.7132, -0.7703],\n",
       "               [-0.9698, -0.9211, -1.0861, -0.7773, -0.6979, -0.6867, -0.8171],\n",
       "               [-0.9088, -1.3481, -1.734 , -0.9084, -0.7077, -0.8129, -1.2026]],\n",
       "\n",
       "              [[-1.3457, -1.3481, -1.3464, -1.3469, -1.3444, -1.3451, -1.3447],\n",
       "               [-0.7792, -0.7809, -0.7806, -0.7912, -0.8528, -0.9177, -0.9363],\n",
       "               [-0.5986, -0.6303, -0.7688, -0.7912, -0.7997, -0.8285, -0.8449],\n",
       "               [-0.5926, -0.5825, -0.5837, -0.581 , -0.5868, -0.5938, -0.5971],\n",
       "               [-0.5983, -0.5775, -0.5713, -0.6046, -0.5946, -0.7549, -0.6379],\n",
       "               [-0.6184, -0.6534, -0.7   , -0.5714, -0.5799, -0.5803, -0.6006],\n",
       "               [-0.8853, -0.5886, -0.7518, -0.6317, -0.6161, -0.609 , -0.8931],\n",
       "               [-0.8238, -0.693 , -0.6423, -0.7593, -0.6805, -0.6506, -0.8248],\n",
       "               [-1.0857, -1.2272, -0.682 , -0.7069, -0.7477, -0.841 , -0.643 ],\n",
       "               [-0.8885, -0.8502, -0.6575, -0.5976, -0.7653, -1.1363, -1.7753]],\n",
       "\n",
       "              [[-1.569 , -1.5675, -1.5675, -1.5691, -1.5664, -1.565 , -1.5688],\n",
       "               [-1.0569, -1.0529, -1.0615, -1.0971, -1.2788, -1.4629, -1.5125],\n",
       "               [-0.9722, -0.9689, -0.9199, -0.935 , -0.9417, -0.9484, -0.9519],\n",
       "               [-0.8355, -0.8269, -0.8617, -0.8919, -0.957 , -1.021 , -1.0339],\n",
       "               [-3.3379, -0.8279, -0.8164, -0.8159, -0.8241, -0.8221, -0.8542],\n",
       "               [-0.9852, -1.1808, -0.84  , -0.8565, -0.8739, -0.874 , -0.9228],\n",
       "               [-0.8302, -0.719 , -0.7831, -0.7293, -0.7755, -0.7296, -0.7819],\n",
       "               [-0.9539, -1.0749, -0.7934, -0.82  , -0.7923, -0.8135, -0.8046],\n",
       "               [-1.1041, -0.9637, -0.8382, -0.7819, -0.7642, -0.7171, -0.8634],\n",
       "               [-0.9162, -1.5417, -0.9464, -0.7326, -0.764 , -0.7151, -1.0751]],\n",
       "\n",
       "              [[-1.6103, -1.6075, -1.6098, -1.6085, -1.6084, -1.6104, -1.609 ],\n",
       "               [-0.8378, -0.8426, -0.8537, -0.8968, -1.1904, -1.4485, -1.4941],\n",
       "               [-0.6735, -0.6801, -0.6854, -0.6996, -0.8882, -0.9309, -0.9348],\n",
       "               [-0.6992, -0.6699, -0.6708, -0.7984, -0.8525, -0.9562, -0.8584],\n",
       "               [-0.9686, -1.7748, -1.1603, -0.9063, -0.7816, -0.9474, -0.941 ],\n",
       "               [-0.716 , -0.9141, -0.6497, -0.6872, -0.6653, -0.6911, -0.6722],\n",
       "               [-0.8642, -0.6829, -0.717 , -0.73  , -0.7064, -0.6867, -0.7552],\n",
       "               [-0.9405, -0.7774, -0.7906, -0.7214, -0.7366, -0.7692, -0.9779],\n",
       "               [-0.8385, -0.671 , -0.9909, -0.7684, -0.7037, -0.8435, -0.872 ],\n",
       "               [-1.0444, -1.5731, -1.0919, -0.7667, -0.7671, -0.7185, -0.7987]],\n",
       "\n",
       "              [[-1.3317, -1.3329, -1.3318, -1.3318, -1.3318, -1.3325, -1.3321],\n",
       "               [-0.9625, -0.9637, -0.9644, -1.0013, -1.1714, -1.3481, -1.3847],\n",
       "               [-0.9854, -0.8413, -0.8431, -0.8483, -0.9098, -0.9134, -0.9139],\n",
       "               [-0.7778, -0.7351, -0.789 , -0.7821, -0.8294, -1.3289, -0.8624],\n",
       "               [-0.7413, -0.7532, -0.7514, -0.7455, -0.765 , -0.7731, -0.8078],\n",
       "               [-1.1124, -1.009 , -0.7667, -0.7713, -0.7634, -0.7554, -0.8408],\n",
       "               [-0.9674, -0.9032, -0.9521, -0.8018, -0.7961, -0.8201, -0.7862],\n",
       "               [-1.0934, -1.0486, -1.5525, -1.2386, -1.0972, -1.0254, -1.2285],\n",
       "               [-0.86  , -3.3501, -0.8685, -0.7547, -0.7658, -0.8101, -1.3126],\n",
       "               [-1.3125, -0.9516, -1.1977, -0.8345, -0.9646, -0.9387, -2.9666]]]), 'mode': array([[[ -1.4677,  -1.4593,  -1.4696,  -1.467 ,  -1.4632,  -1.4762,\n",
       "                 -1.4816],\n",
       "               [ -0.7571,  -0.7551,  -0.7357,  -0.7451,  -0.7461,  -0.7519,\n",
       "                 -0.7447],\n",
       "               [ -0.7949,  -0.7969,  -0.8257,  -0.8416,  -1.0262,  -1.1616,\n",
       "                 -1.1933],\n",
       "               [ -0.8873,  -0.8771,  -0.7719,  -0.7976,  -0.7339,  -0.7346,\n",
       "                 -0.7306],\n",
       "               [ -0.6847,  -0.7316,  -0.7984,  -0.8295,  -0.7728,  -0.9086,\n",
       "                 -0.812 ],\n",
       "               [ -0.7672,  -0.7667,  -0.6972,  -0.7423,  -0.728 ,  -0.7538,\n",
       "                 -0.7284],\n",
       "               [ -0.9224,  -1.2795,  -0.7859,  -1.0149,  -0.89  ,  -0.8006,\n",
       "                 -1.0189],\n",
       "               [ -0.7425,  -0.9259,  -0.8077,  -0.7112,  -0.7278,  -0.7155,\n",
       "                 -0.7518],\n",
       "               [ -0.6621,  -0.844 ,  -1.2026,  -0.9658,  -0.6844,  -0.6921,\n",
       "                 -0.7541],\n",
       "               [ -1.1825,  -1.0495,  -1.6952,  -0.8553,  -0.722 ,  -1.0021,\n",
       "                 -1.357 ]],\n",
       "\n",
       "              [[ -1.3333,  -1.3478,  -1.3435,  -1.3423,  -1.3328,  -1.3397,\n",
       "                 -1.3516],\n",
       "               [ -0.7773,  -0.7868,  -0.7821,  -0.7933,  -0.8503,  -0.9187,\n",
       "                 -0.9342],\n",
       "               [ -0.6127,  -0.7881,  -0.7636,  -0.791 ,  -0.7915,  -0.8299,\n",
       "                 -0.8432],\n",
       "               [ -0.6305,  -0.5886,  -0.6365,  -0.5865,  -0.5871,  -0.5955,\n",
       "                 -0.602 ],\n",
       "               [ -0.5953,  -0.5918,  -0.6005,  -0.6022,  -0.5952,  -0.7404,\n",
       "                 -0.636 ],\n",
       "               [ -0.6042,  -0.7771,  -0.7011,  -0.5985,  -0.5897,  -0.6009,\n",
       "                 -0.6321],\n",
       "               [ -0.6542,  -0.6097,  -0.7609,  -0.7889,  -0.6101,  -0.6397,\n",
       "                 -0.9229],\n",
       "               [ -0.8213,  -1.0045,  -0.7684,  -0.7169,  -0.6236,  -0.7574,\n",
       "                 -0.7497],\n",
       "               [ -2.5088,  -0.816 ,  -2.1098,  -0.6956,  -1.0883,  -0.825 ,\n",
       "                 -0.9639],\n",
       "               [ -0.86  ,  -0.845 ,  -0.8369,  -0.6111,  -0.9071,  -0.9319,\n",
       "                 -0.9953]],\n",
       "\n",
       "              [[ -1.5642,  -1.568 ,  -1.5736,  -1.5786,  -1.5699,  -1.5642,\n",
       "                 -1.5758],\n",
       "               [ -1.0477,  -1.037 ,  -1.0786,  -1.0978,  -1.284 ,  -1.4547,\n",
       "                 -1.5062],\n",
       "               [ -0.9548,  -0.9952,  -0.958 ,  -0.9355,  -0.948 ,  -0.9496,\n",
       "                 -0.9546],\n",
       "               [ -0.8347,  -0.8345,  -0.8748,  -0.8782,  -0.9589,  -1.0135,\n",
       "                 -1.0433],\n",
       "               [ -0.8332,  -0.8066,  -0.8698,  -0.8381,  -0.8245,  -0.8675,\n",
       "                 -0.8271],\n",
       "               [ -1.0293,  -1.5629,  -1.9095,  -0.8591,  -0.8769,  -0.895 ,\n",
       "                 -0.9947],\n",
       "               [ -0.8465,  -0.8774,  -0.7865,  -0.7255,  -0.7343,  -0.7404,\n",
       "                 -0.729 ],\n",
       "               [ -0.8376,  -1.    ,  -0.8361,  -0.8146,  -0.8098,  -0.829 ,\n",
       "                 -0.8313],\n",
       "               [ -0.8666,  -0.7795,  -0.8741,  -0.7322,  -0.7563,  -0.7477,\n",
       "                 -0.8887],\n",
       "               [ -0.8128,  -2.2068,  -1.022 ,  -0.7458,  -0.8747,  -0.7391,\n",
       "                 -0.7916]],\n",
       "\n",
       "              [[ -1.61  ,  -1.6061,  -1.609 ,  -1.6065,  -1.6104,  -1.6061,\n",
       "                 -1.6188],\n",
       "               [ -0.8374,  -0.8328,  -0.8349,  -0.8849,  -1.1975,  -1.4453,\n",
       "                 -1.4692],\n",
       "               [ -0.7214,  -0.7301,  -0.7178,  -0.6867,  -0.8676,  -0.9316,\n",
       "                 -0.9388],\n",
       "               [ -0.6724,  -0.6724,  -0.667 ,  -0.902 ,  -0.8426,  -0.949 ,\n",
       "                 -0.8414],\n",
       "               [ -0.9859,  -1.3672,  -1.0026,  -1.0327,  -5.4701,  -0.9521,\n",
       "                 -0.9453],\n",
       "               [ -0.764 ,  -0.6624,  -0.746 ,  -0.6802,  -0.67  ,  -0.8213,\n",
       "                 -0.8521],\n",
       "               [ -0.9524,  -0.7821,  -0.7603,  -0.7961,  -0.7334,  -0.7231,\n",
       "                 -0.7563],\n",
       "               [ -1.2844,  -0.9695,  -0.7167,  -0.7548,  -0.6913,  -0.7478,\n",
       "                 -0.8897],\n",
       "               [ -0.7625,  -0.7355,  -0.8483,  -0.8102,  -0.664 ,  -0.804 ,\n",
       "                 -1.0561],\n",
       "               [ -1.0626,  -0.8559,  -1.9658,  -0.8821,  -0.7635,  -0.8955,\n",
       "                 -0.9094]],\n",
       "\n",
       "              [[ -1.3333,  -1.3376,  -1.3317,  -1.3328,  -1.3314,  -1.3327,\n",
       "                 -1.3309],\n",
       "               [ -0.9779,  -0.9693,  -0.97  ,  -1.0038,  -1.1545,  -1.3524,\n",
       "                 -1.3933],\n",
       "               [ -1.1654,  -0.8473,  -0.8492,  -0.859 ,  -0.9452,  -0.9581,\n",
       "                 -0.9572],\n",
       "               [ -0.8079,  -0.8362,  -0.824 ,  -0.7902,  -0.8394,  -1.3214,\n",
       "                 -0.8767],\n",
       "               [ -0.7738,  -0.7529,  -0.7619,  -0.759 ,  -0.7992,  -0.8144,\n",
       "                 -0.8079],\n",
       "               [ -5.5348,  -2.0229,  -0.752 ,  -0.8394,  -0.7937,  -1.0077,\n",
       "                 -0.8622],\n",
       "               [ -0.7998,  -0.7831,  -0.8907,  -0.7897,  -0.8093,  -0.8132,\n",
       "                 -0.8131],\n",
       "               [ -4.3623,  -0.8026,  -3.4301,  -2.5978,  -2.2439,  -1.2573,\n",
       "                 -1.5934],\n",
       "               [ -0.9552, -10.0181,  -0.8129,  -0.7248,  -0.8232,  -0.7893,\n",
       "                 -1.2948],\n",
       "               [ -4.0901,  -2.6452,  -1.2172,  -0.9866,  -0.8965,  -0.9882,\n",
       "                 -8.3961]]]), 'p': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], 'eta': [0.0001, 0.001, 0.01, 0.1, 1, 10, 100]}                                                   ,\n",
       "       {'posterior_mean': array([[[-1.4357, -1.4373, -1.4411, -1.435 , -1.4339, -1.4325, -1.4344],\n",
       "               [-0.871 , -0.8359, -0.8504, -0.8766, -0.8463, -0.972 , -1.03  ],\n",
       "               [-0.7003, -0.7041, -0.7398, -0.7809, -0.9862, -1.017 , -1.1501],\n",
       "               [-0.8372, -0.6804, -0.6973, -0.7223, -0.7985, -0.8431, -0.8419],\n",
       "               [-0.6876, -0.6992, -0.7153, -0.6893, -0.6982, -0.7082, -0.7351],\n",
       "               [-0.6687, -0.6709, -0.6628, -0.6874, -0.7736, -0.7098, -0.7714],\n",
       "               [-0.7422, -0.71  , -0.7289, -0.7525, -0.6921, -0.6804, -0.72  ],\n",
       "               [-0.7091, -0.7552, -0.7126, -0.7199, -0.7767, -0.7255, -0.7889],\n",
       "               [-0.7018, -0.7655, -0.6936, -0.7293, -0.7588, -0.7428, -0.9712],\n",
       "               [-0.7919, -0.7815, -0.7214, -0.7055, -0.777 , -0.8943, -0.844 ]],\n",
       "\n",
       "              [[-1.5377, -1.5231, -1.5413, -1.6067, -1.5256, -1.5358, -1.4954],\n",
       "               [-0.8033, -0.8148, -0.8118, -0.779 , -0.8537, -1.0469, -1.0769],\n",
       "               [-0.6401, -0.6642, -0.7778, -0.7538, -1.0521, -1.1478, -1.151 ],\n",
       "               [-0.7717, -0.7666, -0.6824, -0.7111, -0.619 , -0.6474, -0.7308],\n",
       "               [-0.6148, -0.7134, -0.7203, -0.7609, -0.7433, -0.5835, -0.7934],\n",
       "               [-0.7029, -0.6732, -0.6665, -0.6585, -0.6672, -0.7272, -0.6642],\n",
       "               [-0.7205, -0.6853, -0.7818, -0.9083, -0.768 , -0.8362, -0.8199],\n",
       "               [-0.7368, -0.8312, -0.7467, -0.9644, -0.6361, -0.7617, -0.5942],\n",
       "               [-1.3614, -0.7678, -0.7073, -0.7237, -0.6974, -0.693 , -0.69  ],\n",
       "               [-0.7091, -0.9038, -0.6783, -0.6393, -0.6278, -0.8496, -0.8387]],\n",
       "\n",
       "              [[-1.8532, -1.9198, -1.8841, -1.9279, -1.9501, -1.9778, -1.9136],\n",
       "               [-1.3091, -1.2007, -1.1168, -1.1635, -1.185 , -1.3738, -1.478 ],\n",
       "               [-0.8769, -0.8321, -0.8659, -0.8181, -0.8961, -0.9023, -0.9542],\n",
       "               [-0.895 , -0.9503, -0.9239, -0.9283, -0.9967, -1.0594, -1.2276],\n",
       "               [-0.855 , -0.8917, -0.86  , -0.8854, -0.8658, -0.8871, -1.2277],\n",
       "               [-0.8913, -0.8341, -0.9081, -0.9305, -0.8774, -0.9123, -0.8551],\n",
       "               [-0.9187, -0.9429, -1.0122, -0.9794, -0.9476, -0.915 , -0.9482],\n",
       "               [-0.9965, -0.9505, -1.0894, -0.9073, -0.8861, -0.9675, -1.0955],\n",
       "               [-0.9857, -0.9341, -1.0197, -0.84  , -0.8187, -0.878 , -0.89  ],\n",
       "               [-1.0075, -0.8793, -0.9208, -0.8192, -0.9202, -0.8964, -1.0612]],\n",
       "\n",
       "              [[-1.3166, -1.3325, -1.279 , -1.2947, -1.3368, -1.3126, -1.3298],\n",
       "               [-1.2758, -1.3063, -1.2762, -1.1667, -1.3081, -1.3095, -1.3088],\n",
       "               [-0.6717, -0.646 , -0.6813, -0.6711, -0.7009, -0.7215, -0.7205],\n",
       "               [-0.6842, -0.7176, -0.6832, -0.6842, -0.7211, -0.7956, -1.7932],\n",
       "               [-0.6947, -0.6602, -0.7432, -0.6799, -0.683 , -0.7085, -0.6994],\n",
       "               [-0.673 , -0.6725, -0.6692, -0.6695, -0.6752, -0.6833, -0.6937],\n",
       "               [-0.6231, -0.6584, -0.6241, -0.6437, -0.6809, -0.6765, -0.7594],\n",
       "               [-0.6456, -0.7633, -0.6616, -0.7114, -0.694 , -0.7605, -0.7412],\n",
       "               [-0.6776, -0.6525, -0.6844, -0.6852, -0.6732, -0.6645, -0.7095],\n",
       "               [-0.673 , -0.6389, -0.6896, -0.7063, -0.6952, -0.7001, -0.856 ]],\n",
       "\n",
       "              [[-1.6415, -1.7072, -1.6496, -1.6412, -1.6415, -1.6781, -1.6659],\n",
       "               [-0.9304, -0.9632, -1.1192, -0.9767, -1.0325, -1.1097, -1.1444],\n",
       "               [-0.8169, -0.8148, -0.825 , -0.806 , -0.812 , -0.8129, -0.8045],\n",
       "               [-0.8401, -0.852 , -0.8283, -0.8318, -0.8815, -0.8808, -0.9103],\n",
       "               [-0.9504, -0.8232, -0.8798, -0.8918, -0.9694, -1.0504, -1.5119],\n",
       "               [-0.8609, -0.8764, -0.8515, -0.9051, -0.8057, -0.8051, -0.8195],\n",
       "               [-0.8211, -1.0029, -0.944 , -0.8401, -0.7763, -0.8471, -0.8438],\n",
       "               [-1.0576, -0.8794, -0.9358, -0.9091, -0.9231, -0.868 , -0.8558],\n",
       "               [-0.814 , -0.8956, -0.8014, -0.7842, -0.7969, -0.7569, -0.7553],\n",
       "               [-0.9357, -0.8359, -0.8207, -0.7848, -0.785 , -0.8333, -1.1066]]]), 'mean': array([[[-2.0601, -1.5914, -2.1604, -1.4827, -1.4898, -1.584 , -1.5306],\n",
       "               [-0.9435, -0.8865, -1.1126, -0.8724, -0.8842, -0.927 , -1.747 ],\n",
       "               [-1.0542, -0.8408, -1.2937, -1.5859, -1.0994, -1.7883, -2.1674],\n",
       "               [-2.2251, -1.94  , -1.4264, -1.4979, -1.4143, -1.502 , -1.2222],\n",
       "               [-1.1195, -0.753 , -1.4144, -1.0578, -0.6771, -0.6766, -0.7942],\n",
       "               [-1.1609, -1.6897, -1.6999, -1.1205, -1.1397, -0.9135, -1.0387],\n",
       "               [-2.0246, -2.0537, -1.4224, -1.1427, -0.6762, -0.7563, -0.7808],\n",
       "               [-0.9018, -1.3914, -1.5845, -0.9894, -0.7511, -0.9289, -0.8635],\n",
       "               [-3.3722, -2.0124, -3.1304, -2.3956, -0.8528, -0.8667, -1.2883],\n",
       "               [-1.6013, -1.3476, -1.676 , -0.8861, -1.1427, -0.9014, -1.0945]],\n",
       "\n",
       "              [[-1.5394, -1.9582, -1.5374, -2.0763, -1.954 , -2.2111, -2.2199],\n",
       "               [-1.2134, -0.9703, -0.9336, -1.3943, -1.4512, -1.0534, -1.1935],\n",
       "               [-1.1194, -1.526 , -1.7066, -0.9373, -1.0497, -1.6916, -1.8098],\n",
       "               [-1.3216, -1.3574, -0.7628, -1.4449, -0.6264, -1.2648, -1.7087],\n",
       "               [-1.4399, -1.6889, -1.6441, -1.4326, -0.7613, -2.5833, -0.8076],\n",
       "               [-1.7745, -1.417 , -1.3443, -0.674 , -0.6861, -1.3663, -0.7211],\n",
       "               [-1.4174, -1.6883, -2.3762, -1.5557, -1.5959, -1.6108, -0.8181],\n",
       "               [-1.7138, -2.1628, -0.9655, -0.9279, -0.7292, -1.3691, -0.7561],\n",
       "               [-3.565 , -1.8879, -1.1949, -1.6667, -1.3498, -1.3839, -0.7913],\n",
       "               [-2.0909, -2.1351, -1.3465, -1.2698, -0.6695, -1.3608, -0.9762]],\n",
       "\n",
       "              [[-1.8485, -2.7787, -2.239 , -2.4368, -2.812 , -4.1024, -2.5675],\n",
       "               [-2.3222, -1.7667, -1.4577, -1.9695, -1.8089, -1.3701, -2.0039],\n",
       "               [-1.12  , -0.8394, -0.8569, -1.9707, -0.8938, -0.9178, -0.9986],\n",
       "               [-1.8855, -1.3876, -2.6067, -1.1443, -1.7438, -1.0829, -1.8958],\n",
       "               [-1.0572, -1.9001, -1.6404, -1.9598, -0.8451, -0.9254, -1.9683],\n",
       "               [-1.9958, -1.5739, -1.4139, -1.6954, -0.8378, -0.9868, -0.8602],\n",
       "               [-1.9323, -2.4563, -1.7349, -2.3163, -1.7654, -0.9149, -0.9513],\n",
       "               [-2.5721, -2.4807, -1.7954, -1.6018, -0.94  , -1.2168, -1.1701],\n",
       "               [-2.6511, -1.6723, -2.4305, -1.0613, -1.881 , -0.8926, -0.9773],\n",
       "               [-2.1542, -3.4541, -4.5918, -4.2421, -1.9395, -1.2186, -0.9858]],\n",
       "\n",
       "              [[-1.6497, -1.3307, -1.9239, -1.708 , -1.3294, -1.7255, -1.6944],\n",
       "               [-1.4552, -1.2792, -1.3979, -2.0777, -1.7791, -1.329 , -1.3261],\n",
       "               [-0.6527, -1.1092, -1.0913, -0.6866, -0.7021, -1.4332, -0.7299],\n",
       "               [-0.6992, -1.1429, -0.8515, -1.2723, -0.791 , -0.846 , -2.1571],\n",
       "               [-1.5812, -1.1472, -1.739 , -1.7662, -0.6914, -1.2526, -0.7128],\n",
       "               [-1.5285, -1.5251, -1.072 , -0.7036, -0.6919, -0.6973, -0.6959],\n",
       "               [-1.5235, -1.7969, -1.8439, -1.4094, -0.9405, -1.3354, -0.7108],\n",
       "               [-1.796 , -2.3273, -1.1063, -2.1725, -1.2613, -0.8679, -2.0789],\n",
       "               [-1.2426, -1.1631, -2.6512, -0.7109, -0.6633, -0.6858, -0.7647],\n",
       "               [-2.3058, -2.1062, -1.3188, -0.8919, -0.687 , -0.7291, -1.0237]],\n",
       "\n",
       "              [[-2.0622, -2.3467, -2.4734, -2.0135, -1.6463, -2.1011, -1.9739],\n",
       "               [-0.9391, -1.5529, -1.6237, -1.2961, -1.1704, -1.1185, -1.4853],\n",
       "               [-1.1862, -0.9164, -0.8892, -0.822 , -0.8136, -0.8168, -0.8041],\n",
       "               [-1.3593, -1.3743, -1.3426, -1.3561, -1.4224, -0.8973, -0.9101],\n",
       "               [-1.7772, -1.4488, -1.5026, -1.6612, -1.5246, -1.0344, -1.3463],\n",
       "               [-1.7193, -2.1256, -3.5147, -3.7142, -2.6596, -0.8129, -0.8376],\n",
       "               [-4.282 , -1.8467, -3.9587, -4.0814, -3.9584, -3.1048, -1.2522],\n",
       "               [-2.319 , -1.6509, -1.7835, -1.7378, -1.1169, -0.888 , -0.944 ],\n",
       "               [-0.8466, -1.9146, -1.8179, -1.3188, -0.8281, -0.7923, -0.7126],\n",
       "               [-2.4177, -1.4548, -1.7277, -1.0723, -0.7636, -0.9954, -1.7199]]]), 'median': array([[[-1.433 , -1.4371, -1.4387, -1.4347, -1.4398, -1.4373, -1.439 ],\n",
       "               [-0.8855, -0.8836, -0.884 , -0.8865, -0.8819, -0.8814, -0.9055],\n",
       "               [-0.715 , -0.7096, -0.7943, -0.8106, -0.9982, -1.1395, -1.177 ],\n",
       "               [-0.8729, -0.7084, -0.7293, -0.7357, -0.8502, -0.9113, -0.932 ],\n",
       "               [-0.7111, -0.751 , -0.6971, -0.7442, -0.7195, -0.6996, -0.724 ],\n",
       "               [-0.8288, -0.8662, -0.735 , -0.6226, -0.7589, -0.7081, -0.7543],\n",
       "               [-0.9777, -0.9346, -1.0172, -0.8181, -0.6953, -0.6595, -0.7817],\n",
       "               [-0.8588, -1.007 , -0.7471, -0.7769, -0.8335, -0.7253, -0.9141],\n",
       "               [-0.8515, -1.2149, -1.1012, -0.7828, -0.8534, -1.1986, -1.2976],\n",
       "               [-0.6967, -0.7733, -1.1018, -0.7605, -0.8102, -0.8568, -0.8473]],\n",
       "\n",
       "              [[-1.5391, -1.535 , -1.5384, -1.5408, -1.538 , -1.5424, -1.5376],\n",
       "               [-0.8107, -0.8015, -0.8066, -0.8247, -0.9259, -1.0552, -1.0973],\n",
       "               [-0.6703, -0.6047, -0.7514, -0.7259, -1.0473, -1.1584, -1.1906],\n",
       "               [-0.6216, -0.6259, -0.6372, -0.6071, -0.5701, -0.5732, -0.6004],\n",
       "               [-0.8009, -0.8553, -0.6621, -0.6274, -0.7585, -0.7892, -0.7985],\n",
       "               [-0.6976, -0.7515, -0.599 , -0.6461, -0.6799, -0.6433, -0.6691],\n",
       "               [-0.7678, -0.8187, -0.8137, -0.987 , -0.7757, -0.8522, -0.8265],\n",
       "               [-0.6515, -0.657 , -0.7075, -0.6934, -0.7674, -0.7273, -0.7195],\n",
       "               [-0.7502, -3.3267, -0.6594, -0.72  , -0.7274, -0.7314, -0.6769],\n",
       "               [-0.9865, -0.8271, -0.7406, -0.6281, -0.7091, -0.7409, -0.8637]],\n",
       "\n",
       "              [[-1.8475, -1.8515, -1.8498, -1.8499, -1.8506, -1.8517, -1.8486],\n",
       "               [-1.1524, -1.155 , -1.1559, -1.1572, -1.228 , -1.3704, -1.4478],\n",
       "               [-0.8399, -0.8382, -0.8397, -0.8377, -0.8722, -0.9177, -0.9475],\n",
       "               [-0.8397, -0.8694, -0.8587, -0.906 , -1.0283, -1.0664, -1.0749],\n",
       "               [-0.8182, -0.8513, -0.8341, -0.8449, -0.8974, -0.9221, -1.0365],\n",
       "               [-0.8226, -0.8225, -0.8345, -0.8521, -0.9121, -0.9797, -0.8664],\n",
       "               [-0.9765, -1.0425, -0.9256, -0.8432, -1.0239, -0.9303, -1.0252],\n",
       "               [-1.0244, -1.0316, -1.1092, -0.98  , -0.9645, -1.0174, -1.2577],\n",
       "               [-0.8858, -1.1412, -1.1751, -1.0638, -0.8787, -0.907 , -0.9595],\n",
       "               [-2.2884, -1.2291, -1.6443, -1.3708, -0.9251, -0.8397, -0.9867]],\n",
       "\n",
       "              [[-1.3304, -1.3307, -1.331 , -1.3291, -1.3309, -1.3291, -1.3304],\n",
       "               [-1.3159, -1.316 , -1.3213, -1.2694, -1.3258, -1.3296, -1.3285],\n",
       "               [-0.6718, -0.6763, -0.6762, -0.6825, -0.7023, -0.7285, -0.7343],\n",
       "               [-0.6922, -0.7774, -0.7026, -0.7458, -0.8607, -0.8393, -0.879 ],\n",
       "               [-0.6764, -0.6552, -0.6204, -0.6576, -0.6892, -0.6664, -0.6935],\n",
       "               [-0.6618, -0.6717, -0.6901, -0.7043, -0.7011, -0.695 , -0.6917],\n",
       "               [-0.7277, -0.6208, -0.6348, -0.6388, -0.7215, -0.723 , -0.7704],\n",
       "               [-0.81  , -0.9418, -0.7233, -0.8769, -0.7536, -0.8377, -0.843 ],\n",
       "               [-0.6888, -0.7842, -0.8503, -0.6816, -0.6644, -0.6807, -0.7062],\n",
       "               [-0.8082, -0.9174, -0.7523, -0.7964, -0.6835, -0.6941, -0.9264]],\n",
       "\n",
       "              [[-1.648 , -1.6479, -1.6496, -1.6484, -1.6471, -1.6476, -1.6519],\n",
       "               [-0.9404, -0.9438, -0.9438, -0.952 , -1.0198, -1.1056, -1.1328],\n",
       "               [-0.8142, -0.8121, -0.8132, -0.8126, -0.8136, -0.817 , -0.8205],\n",
       "               [-0.813 , -0.8015, -0.8196, -0.8269, -0.8771, -0.9138, -0.9037],\n",
       "               [-0.8779, -0.8283, -0.8593, -0.8694, -0.974 , -1.0734, -1.1943],\n",
       "               [-1.0787, -1.2746, -1.099 , -1.4649, -1.2972, -0.8149, -0.8083],\n",
       "               [-1.9485, -1.2727, -1.149 , -1.746 , -1.7976, -1.3483, -1.053 ],\n",
       "               [-1.0249, -1.0264, -1.0215, -0.8517, -0.89  , -0.8751, -0.9383],\n",
       "               [-1.0706, -1.0096, -1.0366, -0.8069, -0.8745, -0.7946, -0.782 ],\n",
       "               [-1.4931, -1.2042, -0.8809, -0.9354, -0.7378, -0.9538, -1.5262]]]), 'mode': array([[[ -1.4474,  -1.4473,  -1.4318,  -1.4437,  -1.4408,  -1.4417,\n",
       "                 -1.444 ],\n",
       "               [ -0.8936,  -0.8894,  -0.8945,  -0.8892,  -0.8814,  -0.8876,\n",
       "                 -0.9035],\n",
       "               [ -0.7447,  -0.7234,  -0.7427,  -0.7844,  -1.0235,  -1.1626,\n",
       "                 -1.1714],\n",
       "               [ -0.7243,  -0.7739,  -0.7422,  -0.7089,  -0.8398,  -0.8974,\n",
       "                 -0.988 ],\n",
       "               [ -0.7401,  -0.7591,  -0.8879,  -0.7549,  -0.7424,  -0.672 ,\n",
       "                 -0.725 ],\n",
       "               [ -0.8472,  -0.8705,  -0.6458,  -0.6572,  -0.7221,  -0.7241,\n",
       "                 -0.7097],\n",
       "               [ -1.28  ,  -0.9026,  -1.0085,  -0.7984,  -0.7107,  -0.6506,\n",
       "                 -0.8093],\n",
       "               [ -0.7184,  -1.0912,  -0.8049,  -0.838 ,  -1.0739,  -1.2685,\n",
       "                 -0.8846],\n",
       "               [ -0.9982,  -1.0335,  -2.3325,  -1.7017,  -0.8795,  -1.1323,\n",
       "                 -1.3659],\n",
       "               [ -0.7316,  -1.0263,  -1.2602,  -0.7646,  -0.8341,  -0.8968,\n",
       "                 -0.8318]],\n",
       "\n",
       "              [[ -1.552 ,  -1.5382,  -1.543 ,  -1.5328,  -1.5307,  -1.5288,\n",
       "                 -1.5283],\n",
       "               [ -0.8043,  -0.7947,  -0.7931,  -0.8234,  -0.9197,  -1.0641,\n",
       "                 -1.0951],\n",
       "               [ -0.6131,  -0.6217,  -0.6231,  -0.6871,  -1.032 ,  -1.175 ,\n",
       "                 -1.1977],\n",
       "               [ -0.6875,  -0.6938,  -0.7208,  -0.6586,  -0.5624,  -0.5649,\n",
       "                 -0.6068],\n",
       "               [ -0.6359,  -0.6683,  -0.5784,  -0.6946,  -0.7433, -10.9031,\n",
       "                 -0.7982],\n",
       "               [ -0.6477,  -0.7389,  -0.5957,  -0.6   ,  -0.6319,  -0.6444,\n",
       "                 -0.6166],\n",
       "               [ -0.7784,  -0.9949,  -0.7692,  -0.8844,  -0.7638,  -0.8848,\n",
       "                 -0.8365],\n",
       "               [ -0.6458,  -0.8281,  -1.2518,  -0.7163,  -0.7265,  -0.7112,\n",
       "                 -0.8034],\n",
       "               [ -0.7258,  -0.7815,  -0.7555,  -0.9882,  -0.7228,  -0.6802,\n",
       "                 -0.6187],\n",
       "               [ -1.3207,  -0.8071,  -0.7482,  -0.6653,  -0.7995,  -0.7176,\n",
       "                 -0.8936]],\n",
       "\n",
       "              [[ -1.8422,  -1.8612,  -1.8427,  -1.8495,  -1.8522,  -1.8576,\n",
       "                 -1.8497],\n",
       "               [ -1.1429,  -1.1492,  -1.1701,  -1.1638,  -1.2551,  -1.3727,\n",
       "                 -1.4427],\n",
       "               [ -0.8349,  -0.8486,  -0.845 ,  -0.8304,  -0.8693,  -0.9205,\n",
       "                 -0.9481],\n",
       "               [ -0.8381,  -0.8618,  -0.8411,  -0.9002,  -1.0689,  -1.0725,\n",
       "                 -1.0756],\n",
       "               [ -0.8404,  -0.8131,  -0.8279,  -0.8635,  -0.8624,  -0.8778,\n",
       "                 -1.1066],\n",
       "               [ -0.8816,  -0.8156,  -0.9007,  -0.8755,  -0.9748,  -1.1972,\n",
       "                 -0.94  ],\n",
       "               [ -0.9663,  -1.1269,  -0.9425,  -0.9452,  -0.8786,  -0.92  ,\n",
       "                 -1.0298],\n",
       "               [ -1.0333,  -0.9778,  -0.9209,  -1.0563,  -0.9728,  -0.9294,\n",
       "                 -1.2439],\n",
       "               [ -0.915 ,  -1.1944,  -0.8902,  -1.0385,  -0.8909,  -0.9329,\n",
       "                 -0.9662],\n",
       "               [ -0.829 ,  -1.0382,  -3.7606,  -3.6244,  -1.0245,  -0.8399,\n",
       "                 -1.095 ]],\n",
       "\n",
       "              [[ -1.338 ,  -1.3269,  -1.3278,  -1.3294,  -1.3269,  -1.3284,\n",
       "                 -1.3313],\n",
       "               [ -1.3039,  -1.3033,  -1.3613,  -1.4397,  -1.3319,  -1.3426,\n",
       "                 -1.3518],\n",
       "               [ -0.6732,  -0.6727,  -0.6742,  -0.6799,  -0.7048,  -0.727 ,\n",
       "                 -0.7334],\n",
       "               [ -0.6996,  -0.8037,  -0.6998,  -0.7445,  -0.7757,  -0.8324,\n",
       "                 -0.8461],\n",
       "               [ -0.7174,  -0.6946,  -0.6751,  -0.6509,  -0.6923,  -0.6581,\n",
       "                 -0.6899],\n",
       "               [ -0.7167,  -0.6462,  -0.7983,  -0.619 ,  -0.6637,  -0.69  ,\n",
       "                 -0.6975],\n",
       "               [ -0.6584,  -0.7374,  -0.612 ,  -0.6537,  -0.7421,  -0.8215,\n",
       "                 -0.808 ],\n",
       "               [ -0.7079,  -0.8088,  -0.7436,  -0.892 ,  -0.7766,  -0.8259,\n",
       "                 -0.9958],\n",
       "               [ -0.6508,  -0.6917,  -0.8934,  -0.6341,  -0.6843,  -0.6653,\n",
       "                 -0.6592],\n",
       "               [ -0.6753,  -1.0491,  -0.6465,  -0.6976,  -0.6569,  -0.6716,\n",
       "                 -0.7368]],\n",
       "\n",
       "              [[ -1.6571,  -1.6516,  -1.654 ,  -1.6484,  -1.6547,  -1.6492,\n",
       "                 -1.6467],\n",
       "               [ -0.9409,  -0.9389,  -0.9582,  -0.9508,  -1.0157,  -1.112 ,\n",
       "                 -1.1336],\n",
       "               [ -0.8164,  -0.8217,  -0.8167,  -0.8158,  -0.8107,  -0.8168,\n",
       "                 -0.8241],\n",
       "               [ -0.8105,  -0.8038,  -0.8768,  -0.8268,  -0.85  ,  -0.8684,\n",
       "                 -0.9003],\n",
       "               [ -0.8292,  -0.9064,  -0.863 ,  -0.9061,  -1.0131,  -1.0599,\n",
       "                 -1.1715],\n",
       "               [ -1.1927,  -0.9918,  -4.2674,  -5.201 ,  -5.3958,  -0.8145,\n",
       "                 -0.8223],\n",
       "               [ -2.5833,  -1.0916,  -1.3402,  -5.1359,  -5.3376,  -4.0722,\n",
       "                 -1.3148],\n",
       "               [ -1.008 ,  -0.9248,  -0.9786,  -0.8535,  -0.8936,  -0.9583,\n",
       "                 -0.9744],\n",
       "               [ -1.0996,  -0.806 ,  -0.9298,  -0.8441,  -0.8079,  -0.8183,\n",
       "                 -0.839 ],\n",
       "               [ -2.3363,  -0.8737,  -0.9836,  -0.9494,  -0.8502,  -0.8739,\n",
       "                 -1.2679]]]), 'p': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], 'eta': [0.0001, 0.001, 0.01, 0.1, 1, 10, 100]}                                                   ,\n",
       "       {'posterior_mean': array([[[-1.7853, -1.7634, -1.797 , -1.8248, -1.7265, -1.7545, -1.6952],\n",
       "               [-1.012 , -0.9837, -0.9753, -0.9172, -0.9579, -0.9744, -0.9393],\n",
       "               [-1.0605, -0.9289, -0.9441, -1.0239, -1.341 , -1.4309, -1.652 ],\n",
       "               [-0.8087, -0.8033, -0.8211, -0.8071, -0.8004, -0.7986, -0.8032],\n",
       "               [-0.8268, -0.9141, -0.8215, -0.851 , -0.8319, -0.8685, -0.9322],\n",
       "               [-0.7936, -0.8133, -0.8364, -0.7721, -0.7666, -0.7624, -0.7753],\n",
       "               [-0.8072, -0.8777, -0.7983, -0.7963, -0.7887, -0.8099, -0.8046],\n",
       "               [-0.8631, -0.8115, -0.8648, -0.8205, -0.817 , -0.7853, -0.7791],\n",
       "               [-0.8357, -0.9565, -0.8216, -0.811 , -0.7815, -0.808 , -0.8866],\n",
       "               [-1.0095, -0.9754, -0.9028, -0.8529, -0.8335, -0.8383, -0.8318]],\n",
       "\n",
       "              [[-1.5298, -1.5228, -1.5274, -1.487 , -1.5258, -1.4988, -1.4957],\n",
       "               [-0.8038, -0.8058, -0.8279, -0.8137, -0.9671, -1.208 , -1.2768],\n",
       "               [-0.7378, -0.7887, -0.8369, -0.7766, -0.7417, -0.7356, -1.0878],\n",
       "               [-0.8434, -0.7975, -0.8211, -0.8325, -0.8654, -0.8973, -0.9041],\n",
       "               [-0.8448, -0.9114, -0.8121, -0.8294, -0.8238, -0.8688, -0.9784],\n",
       "               [-0.9938, -0.6881, -0.8686, -0.8392, -0.8464, -0.8329, -0.8562],\n",
       "               [-0.9902, -0.8544, -0.8037, -0.8474, -0.8766, -0.8361, -0.8322],\n",
       "               [-0.8058, -0.9013, -0.8252, -0.8509, -0.8565, -0.8414, -0.8414],\n",
       "               [-0.9077, -0.8169, -0.8293, -0.8611, -0.837 , -0.9043, -0.9124],\n",
       "               [-0.8146, -0.9428, -0.8293, -0.8084, -0.7612, -0.7864, -0.7092]],\n",
       "\n",
       "              [[-1.128 , -1.1816, -1.122 , -1.2783, -1.3254, -1.2073, -1.2447],\n",
       "               [-0.7624, -0.7589, -0.7631, -0.8595, -0.7605, -0.7704, -0.7824],\n",
       "               [-0.7476, -0.7238, -0.7559, -0.7628, -0.7551, -0.7977, -0.9712],\n",
       "               [-0.707 , -0.6941, -0.7177, -0.7426, -0.6983, -0.7066, -0.7221],\n",
       "               [-0.6996, -1.2278, -0.7103, -0.7236, -0.7265, -0.6969, -0.7856],\n",
       "               [-0.7257, -0.6806, -0.6892, -0.7088, -0.7208, -0.7117, -0.7213],\n",
       "               [-0.7252, -0.732 , -0.7038, -0.6961, -0.7046, -0.7259, -0.6883],\n",
       "               [-0.6923, -0.6926, -0.8691, -0.7173, -0.753 , -0.7264, -0.7956],\n",
       "               [-0.7307, -0.8588, -0.7682, -0.7287, -0.7006, -0.7168, -0.7057],\n",
       "               [-0.7674, -0.7718, -0.8351, -0.7136, -0.7112, -0.7024, -0.8438]],\n",
       "\n",
       "              [[-1.4244, -1.4226, -1.4113, -1.4114, -1.4324, -1.4444, -1.4159],\n",
       "               [-0.9766, -0.9296, -0.912 , -0.9709, -0.9193, -0.9986, -1.2617],\n",
       "               [-0.8363, -0.907 , -0.8571, -0.8534, -1.0772, -1.3568, -1.484 ],\n",
       "               [-0.9152, -0.933 , -0.8654, -0.8065, -0.8231, -0.9591, -1.0578],\n",
       "               [-0.7455, -0.7728, -0.7724, -0.7604, -0.7177, -0.7211, -0.9365],\n",
       "               [-0.692 , -0.7669, -0.7173, -0.7201, -0.7342, -0.7606, -0.7034],\n",
       "               [-0.8611, -0.9126, -0.7193, -0.9699, -0.7205, -0.7618, -0.73  ],\n",
       "               [-0.7678, -0.8454, -0.8792, -0.7901, -0.7624, -0.8386, -0.866 ],\n",
       "               [-0.7646, -0.9481, -0.768 , -0.674 , -0.7388, -0.7015, -0.7001],\n",
       "               [-0.7669, -0.7898, -0.8801, -0.7473, -0.7128, -0.7237, -1.0826]],\n",
       "\n",
       "              [[-1.9337, -1.902 , -1.8915, -1.8657, -1.8433, -1.8835, -1.9066],\n",
       "               [-1.064 , -1.1025, -0.977 , -1.0674, -1.3976, -1.5997, -1.9561],\n",
       "               [-0.7851, -0.786 , -0.8356, -1.0929, -1.0445, -1.2524, -1.2854],\n",
       "               [-0.6778, -0.6701, -0.6858, -0.695 , -0.7038, -0.7399, -0.7487],\n",
       "               [-0.6872, -0.6783, -0.6815, -0.6812, -0.7109, -0.7167, -0.7169],\n",
       "               [-0.6715, -0.8134, -0.7102, -0.7304, -0.7587, -0.8412, -0.838 ],\n",
       "               [-0.8148, -0.7913, -0.7196, -0.7413, -0.7177, -0.8519, -0.7491],\n",
       "               [-0.7446, -0.6673, -0.6842, -0.6779, -0.711 , -0.6811, -0.8423],\n",
       "               [-0.8152, -0.7827, -0.8735, -0.7816, -0.7133, -0.7551, -0.6944],\n",
       "               [-0.701 , -0.7137, -0.9411, -0.6632, -0.6867, -0.6946, -1.1547]]]), 'mean': array([[[-2.2298, -2.0154, -2.2968, -1.8212, -1.8987, -2.0545, -2.0477],\n",
       "               [-1.8392, -1.2758, -1.071 , -1.5113, -1.0719, -1.9255, -1.6144],\n",
       "               [-1.7287, -1.2364, -2.0816, -1.5459, -2.0483, -1.859 , -1.7456],\n",
       "               [-0.9249, -1.1575, -1.8265, -1.4458, -0.8194, -0.8225, -0.8223],\n",
       "               [-0.9527, -1.7875, -1.3899, -1.7549, -1.1109, -1.0094, -1.4706],\n",
       "               [-2.0762, -1.486 , -1.6014, -0.8258, -0.7913, -0.7995, -0.8296],\n",
       "               [-2.1231, -1.9264, -1.569 , -0.9498, -0.8182, -1.4436, -0.8328],\n",
       "               [-2.0744, -2.108 , -1.9931, -2.2737, -1.4151, -0.7867, -0.8163],\n",
       "               [-1.8094, -1.786 , -2.0704, -1.7915, -0.9458, -0.8801, -0.847 ],\n",
       "               [-3.2545, -1.9333, -1.9149, -1.397 , -1.1257, -0.9134, -0.8099]],\n",
       "\n",
       "              [[-1.9084, -1.8911, -1.5234, -1.9003, -1.5241, -1.8652, -2.2745],\n",
       "               [-1.5392, -0.9953, -1.3751, -1.517 , -1.4721, -2.2741, -1.9706],\n",
       "               [-0.8617, -0.8963, -0.9502, -0.7495, -1.4067, -0.7326, -1.794 ],\n",
       "               [-1.5853, -1.1173, -0.8237, -0.8684, -1.4365, -0.9682, -1.4829],\n",
       "               [-1.2246, -2.5389, -1.1555, -1.9127, -1.6564, -0.9696, -1.5689],\n",
       "               [-2.3864, -1.8622, -1.2396, -1.4812, -1.1323, -1.5634, -1.016 ],\n",
       "               [-2.1591, -2.1567, -1.432 , -1.1113, -0.87  , -0.8355, -0.8776],\n",
       "               [-1.8134, -1.722 , -1.5932, -1.4284, -1.5488, -0.8299, -0.8011],\n",
       "               [-1.6645, -1.1629, -1.3741, -1.4473, -0.9761, -1.0506, -1.2076],\n",
       "               [-2.1676, -2.3661, -2.0193, -1.535 , -1.0465, -0.9291, -0.8609]],\n",
       "\n",
       "              [[-1.122 , -1.581 , -1.1203, -1.9589, -2.4235, -1.6682, -1.6843],\n",
       "               [-1.2202, -1.5035, -1.1347, -0.9492, -0.7571, -0.7758, -1.2624],\n",
       "               [-1.1163, -0.8168, -0.8234, -0.7919, -1.361 , -1.3315, -2.3633],\n",
       "               [-0.8451, -1.061 , -1.725 , -0.8031, -0.7128, -0.7317, -1.5965],\n",
       "               [-0.8119, -1.8162, -1.369 , -1.8945, -1.6772, -0.693 , -0.768 ],\n",
       "               [-1.477 , -1.9299, -0.7987, -1.8411, -0.7578, -0.752 , -0.7724],\n",
       "               [-1.4117, -1.7082, -1.5473, -0.7782, -1.3245, -0.754 , -0.6847],\n",
       "               [-1.6743, -1.4031, -2.7908, -2.5173, -1.4429, -0.7565, -0.8165],\n",
       "               [-2.4024, -2.6476, -2.2803, -0.7736, -0.7406, -0.7064, -0.7167],\n",
       "               [-2.3281, -3.1467, -2.3249, -0.765 , -1.0234, -0.7321, -1.1583]],\n",
       "\n",
       "              [[-1.5277, -1.9208, -1.6941, -1.649 , -1.5176, -2.0842, -1.633 ],\n",
       "               [-1.4033, -0.9561, -1.446 , -1.5014, -0.9228, -1.2298, -2.4848],\n",
       "               [-1.7528, -1.1563, -0.8672, -0.8356, -1.3444, -1.6563, -1.8009],\n",
       "               [-2.0366, -1.9848, -1.9454, -0.9332, -0.8072, -1.2048, -1.5183],\n",
       "               [-2.2958, -1.2159, -1.7064, -1.9593, -0.7395, -0.7197, -1.0709],\n",
       "               [-1.4318, -1.9984, -0.8678, -0.813 , -0.9082, -0.7822, -0.7404],\n",
       "               [-2.2409, -1.7874, -2.1196, -1.33  , -0.7228, -1.1155, -0.7232],\n",
       "               [-4.5643, -2.4781, -5.0665, -3.7861, -1.0664, -0.8111, -0.8289],\n",
       "               [-1.8959, -2.7039, -2.2376, -2.1929, -0.829 , -0.6979, -0.7805],\n",
       "               [-1.7141, -2.1958, -2.0735, -0.8453, -0.8108, -0.7859, -1.0569]],\n",
       "\n",
       "              [[-1.9481, -2.6456, -1.9819, -2.1244, -1.852 , -1.9735, -2.2513],\n",
       "               [-1.8507, -1.9158, -1.6028, -1.5562, -1.6156, -1.7436, -2.6887],\n",
       "               [-1.2641, -1.823 , -2.434 , -1.2882, -1.1291, -1.569 , -1.7868],\n",
       "               [-0.7727, -0.8473, -1.2303, -0.6689, -1.2359, -0.7567, -0.7732],\n",
       "               [-1.3421, -1.2574, -0.7026, -1.1747, -0.7128, -0.7191, -0.7168],\n",
       "               [-1.3868, -1.4236, -1.233 , -0.7774, -0.8149, -1.3941, -0.9936],\n",
       "               [-1.1309, -1.4593, -1.0856, -0.8871, -0.7174, -1.2804, -0.7633],\n",
       "               [-1.2173, -1.6232, -1.4566, -1.3797, -0.7055, -1.3226, -0.9843],\n",
       "               [-1.6685, -1.3501, -1.7343, -1.7486, -0.7341, -0.7581, -0.798 ],\n",
       "               [-1.8246, -1.3211, -3.1281, -0.8248, -0.6819, -0.7484, -2.1656]]]), 'median': array([[[-1.8213, -1.8178, -1.8202, -1.8208, -1.8176, -1.8173, -1.8181],\n",
       "               [-0.9834, -0.9793, -0.9773, -0.975 , -0.9737, -0.9662, -0.9636],\n",
       "               [-1.056 , -0.8934, -0.9078, -1.0246, -1.3471, -1.6552, -1.7194],\n",
       "               [-0.8103, -0.7986, -1.0053, -0.822 , -0.8242, -0.8141, -0.8105],\n",
       "               [-0.8798, -0.9581, -0.8916, -0.9772, -0.845 , -0.8707, -0.8476],\n",
       "               [-0.8723, -0.905 , -0.786 , -0.7734, -0.7909, -0.7898, -0.8176],\n",
       "               [-1.032 , -0.933 , -0.783 , -0.8414, -0.8752, -0.8693, -0.8406],\n",
       "               [-1.232 , -0.9713, -1.0647, -0.8463, -0.8686, -0.8428, -0.8113],\n",
       "               [-0.9274, -1.1821, -0.9034, -0.9158, -0.8663, -0.8998, -0.792 ],\n",
       "               [-1.0303, -0.8378, -0.8188, -0.8933, -0.9656, -0.8411, -0.8004]],\n",
       "\n",
       "              [[-1.5205, -1.5219, -1.523 , -1.5254, -1.5244, -1.5227, -1.5232],\n",
       "               [-0.8058, -0.8027, -0.8072, -0.8302, -1.0473, -1.2678, -1.3151],\n",
       "               [-0.7257, -0.7491, -0.7244, -0.7509, -0.7127, -0.7324, -0.7644],\n",
       "               [-0.8215, -0.9085, -0.8201, -0.8273, -0.822 , -0.9247, -0.8318],\n",
       "               [-0.8005, -0.8353, -0.8357, -0.8262, -0.9097, -0.9101, -0.952 ],\n",
       "               [-0.8002, -0.8489, -1.0752, -0.8743, -1.0611, -0.848 , -0.8204],\n",
       "               [-1.0064, -0.9782, -0.9413, -1.15  , -0.8893, -0.843 , -0.8504],\n",
       "               [-0.8755, -1.3033, -0.825 , -0.8282, -0.8766, -0.8441, -0.8244],\n",
       "               [-0.9832, -0.8519, -1.0586, -0.8789, -0.9074, -1.0562, -1.1466],\n",
       "               [-0.7418, -1.1457, -0.7671, -0.7949, -0.9669, -0.8906, -0.7893]],\n",
       "\n",
       "              [[-1.1214, -1.1233, -1.1197, -1.1242, -1.1296, -1.1223, -1.1229],\n",
       "               [-0.7862, -0.7858, -0.7896, -0.7737, -0.7572, -0.7745, -0.7857],\n",
       "               [-0.7725, -0.7109, -0.7898, -0.8056, -0.7902, -0.798 , -0.801 ],\n",
       "               [-0.7168, -0.7328, -0.7147, -0.7149, -0.7126, -0.7316, -0.7336],\n",
       "               [-0.7505, -0.7393, -0.8661, -0.7199, -0.6996, -0.7172, -0.7573],\n",
       "               [-0.7549, -0.7203, -0.7162, -0.7484, -0.7647, -0.751 , -0.7728],\n",
       "               [-0.767 , -0.7264, -0.8019, -0.6852, -0.6983, -0.6941, -0.6744],\n",
       "               [-0.9314, -0.7948, -1.9798, -1.2135, -1.627 , -0.731 , -0.793 ],\n",
       "               [-0.6863, -0.7511, -0.7918, -0.7178, -0.7286, -0.6989, -0.7085],\n",
       "               [-0.7768, -0.7308, -1.1919, -0.7184, -1.039 , -0.7531, -1.1356]],\n",
       "\n",
       "              [[-1.378 , -1.3763, -1.3793, -1.3777, -1.3756, -1.3776, -1.3767],\n",
       "               [-0.9175, -0.9142, -0.9132, -0.9123, -0.9225, -0.9423, -0.9444],\n",
       "               [-0.8176, -0.8312, -0.8136, -0.8312, -0.9391, -1.2782, -1.4093],\n",
       "               [-0.8688, -0.8639, -0.7811, -0.8116, -0.8584, -0.9054, -0.9694],\n",
       "               [-0.7059, -0.7215, -0.7749, -0.7422, -0.748 , -0.6833, -0.7083],\n",
       "               [-0.6558, -0.6521, -0.7049, -0.7536, -0.7319, -0.7539, -0.6986],\n",
       "               [-0.9784, -7.6484, -0.8269, -0.7482, -0.7337, -0.7857, -0.7177],\n",
       "               [-1.7439, -0.9344, -1.0053, -1.0267, -0.7621, -0.8416, -0.8813],\n",
       "               [-0.7501, -0.7524, -0.7271, -0.6865, -0.7617, -0.7133, -0.7681],\n",
       "               [-0.7797, -0.8304, -1.7718, -0.7821, -0.7897, -0.6929, -0.9799]],\n",
       "\n",
       "              [[-1.8601, -1.8588, -1.8556, -1.8624, -1.8511, -1.8549, -1.8523],\n",
       "               [-0.9292, -0.9376, -0.9268, -0.9903, -1.3315, -1.5873, -1.6391],\n",
       "               [-0.773 , -0.7756, -1.1764, -0.9156, -1.0399, -1.2513, -1.2629],\n",
       "               [-0.6802, -0.6531, -0.6929, -0.7179, -0.7129, -0.7583, -0.7715],\n",
       "               [-0.6592, -0.7095, -0.7086, -0.6571, -0.7259, -0.7206, -0.7154],\n",
       "               [-0.7093, -0.8333, -0.7337, -0.7642, -0.7856, -0.8326, -0.7992],\n",
       "               [-0.9137, -0.8168, -0.8564, -0.8611, -0.7213, -0.7362, -0.7362],\n",
       "               [-0.7386, -1.0807, -0.8227, -0.9286, -0.6882, -0.72  , -0.8612],\n",
       "               [-1.0393, -0.848 , -0.8966, -0.9502, -0.728 , -0.751 , -0.7196],\n",
       "               [-1.2451, -0.8844, -1.0114, -0.7621, -0.6794, -0.7242, -1.3574]]]), 'mode': array([[[-1.8179, -1.8176, -1.828 , -1.8254, -1.7967, -1.8251, -1.8202],\n",
       "               [-0.987 , -0.9703, -0.9826, -0.9813, -0.981 , -0.968 , -0.9646],\n",
       "               [-0.9944, -0.8645, -0.9032, -1.0538, -1.3484, -1.704 , -1.7671],\n",
       "               [-0.8092, -0.7987, -0.8015, -0.8151, -0.8113, -0.8112, -0.8122],\n",
       "               [-0.8311, -0.8378, -0.7842, -0.8514, -0.8337, -0.8802, -0.8835],\n",
       "               [-0.8173, -0.8787, -0.8463, -0.8262, -0.8252, -0.8033, -0.7983],\n",
       "               [-0.9313, -1.0309, -0.9623, -0.8598, -0.8367, -0.8329, -0.8499],\n",
       "               [-1.0468, -0.8717, -1.0157, -0.8281, -0.8551, -0.8495, -0.8509],\n",
       "               [-0.9842, -1.1974, -0.7929, -0.9195, -0.8723, -0.8671, -0.8072],\n",
       "               [-0.9141, -1.0024, -0.93  , -1.0359, -0.8541, -0.836 , -0.839 ]],\n",
       "\n",
       "              [[-1.5236, -1.5157, -1.5204, -1.5361, -1.5273, -1.5226, -1.528 ],\n",
       "               [-0.7979, -0.8034, -0.8105, -0.8363, -1.0714, -1.2746, -1.3117],\n",
       "               [-0.7712, -0.7411, -0.7367, -0.7536, -0.7332, -0.7327, -0.7593],\n",
       "               [-0.8015, -1.0491, -0.9332, -0.8541, -0.8535, -0.8967, -0.8797],\n",
       "               [-0.7672, -0.9339, -0.8062, -0.8018, -0.8719, -0.8528, -0.8732],\n",
       "               [-0.8685, -0.8127, -0.9809, -0.8845, -1.1238, -0.8431, -0.7989],\n",
       "               [-1.4202, -0.8851, -0.803 , -1.1466, -0.8865, -0.8606, -0.8674],\n",
       "               [-0.9235, -1.0606, -1.1467, -0.9668, -0.8483, -0.8735, -0.8114],\n",
       "               [-0.9469, -0.9038, -0.8895, -0.9162, -0.9255, -0.9056, -0.9996],\n",
       "               [-1.3358, -1.4688, -0.992 , -0.9681, -0.9551, -0.8073, -0.7518]],\n",
       "\n",
       "              [[-1.1179, -1.1326, -1.1136, -1.1082, -1.1263, -1.122 , -1.1284],\n",
       "               [-0.7998, -0.7985, -0.7913, -0.7695, -0.7615, -0.7778, -0.7863],\n",
       "               [-0.8033, -0.7887, -0.7677, -0.8046, -0.7921, -0.782 , -0.785 ],\n",
       "               [-0.7313, -0.7162, -0.7122, -0.7197, -0.7128, -0.7166, -0.7054],\n",
       "               [-0.7393, -0.7235, -0.6747, -0.7195, -0.6937, -0.719 , -0.7454],\n",
       "               [-0.757 , -0.7359, -0.7746, -0.721 , -0.7698, -0.7913, -0.763 ],\n",
       "               [-0.955 , -1.1646, -0.6971, -0.7105, -0.6774, -0.7035, -0.6789],\n",
       "               [-0.942 , -1.0194, -1.3924, -5.0876, -0.8671, -0.8732, -1.1153],\n",
       "               [-0.9257, -0.7778, -0.8249, -0.7327, -0.6918, -0.7583, -0.6931],\n",
       "               [-0.9223, -1.0287, -1.1004, -1.0958, -1.3692, -0.7274, -1.2388]],\n",
       "\n",
       "              [[-1.3872, -1.3781, -1.3751, -1.3761, -1.3664, -1.38  , -1.3756],\n",
       "               [-0.925 , -0.9143, -0.905 , -0.9013, -0.924 , -0.9404, -0.943 ],\n",
       "               [-0.8423, -0.8426, -0.8047, -0.8426, -0.9096, -1.2612, -1.4047],\n",
       "               [-0.8786, -0.8939, -0.7686, -0.8433, -0.8462, -0.9375, -1.0605],\n",
       "               [-0.6909, -0.7042, -0.6857, -0.6915, -0.7541, -0.7026, -0.7272],\n",
       "               [-0.7067, -0.6566, -0.9841, -0.7215, -0.7173, -0.746 , -0.7074],\n",
       "               [-0.9398, -0.6001, -0.6708, -0.6954, -0.723 , -0.7817, -0.7234],\n",
       "               [-3.3478, -0.9157, -1.0068, -4.2205, -0.8026, -0.8696, -0.8993],\n",
       "               [-0.8795, -1.1052, -1.0209, -0.6844, -0.7397, -1.1288, -0.6901],\n",
       "               [-0.7956, -0.9442, -0.7025, -0.7547, -0.7037, -0.6476, -0.9124]],\n",
       "\n",
       "              [[-1.8555, -1.8503, -1.845 , -1.8564, -1.8651, -1.8477, -1.8486],\n",
       "               [-0.9158, -0.901 , -0.9054, -0.9885, -1.3183, -1.5575, -1.625 ],\n",
       "               [-0.8357, -0.7728, -0.9494, -0.9165, -1.0287, -1.251 , -1.2614],\n",
       "               [-0.7349, -0.7091, -0.7284, -0.7167, -0.7578, -0.7668, -0.7737],\n",
       "               [-0.6972, -0.7017, -0.7537, -0.6949, -0.7255, -0.7253, -0.7397],\n",
       "               [-0.7149, -0.8839, -0.8937, -0.7914, -0.8335, -0.818 , -0.8986],\n",
       "               [-0.8881, -0.7712, -0.7344, -0.8449, -0.8183, -0.8236, -0.8073],\n",
       "               [-0.8603, -0.8298, -0.8233, -0.7479, -0.7643, -0.6837, -0.7266],\n",
       "               [-2.2496, -0.8754, -0.986 , -0.7704, -0.8119, -0.8564, -0.764 ],\n",
       "               [-1.0705, -0.9763, -0.864 , -0.7382, -0.6825, -0.69  , -1.1484]]]), 'p': [1, 2, 3, 4, 5, 6, 7, 8, 9, 10], 'eta': [0.0001, 0.001, 0.01, 0.1, 1, 10, 100]}],\n",
       "      dtype=object)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# -- Example\n",
    "\n",
    "arr = np.load(rkhs[0] + \".npz\", allow_pickle=True)\n",
    "print(\"Keys:\")\n",
    "for a in arr.keys():\n",
    "    print(a)\n",
    "\n",
    "# Each row is a different repetition, inside the arrays are # n_splits x params_shape\n",
    "# e.g. for 5 folds, p in [2, 3] and eta in [0.01, 0.1], shape is (5, 2, 2).\n",
    "arr[\"score_bayesian_all\"]\n",
    "\n",
    "# There are also the parameter vectors (eta, p) and, in the case of INCLUDE_P,\n",
    "# the effective n_components used in each case."
   ]
  }
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