model comparison plot 3.ipynb

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   "cell_type": "code",
   "execution_count": 2,
   "id": "8add6620",
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   "source": [
    "%run SAT_help_functions.ipynb\n",
    "\n",
    "datasets = ['Dutilh2013', 'Dutilh2019', 'Evans2017', 'Lerche2017', 'Rae2014', 'Wagenmakers2008']\n",
    "dataset_names = ['Dutilh 2013', 'Dutilh 2019', 'Evans 2017', 'Lerche 2017', 'Rae 2014', 'Wagenmakers 2008']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "a8a6f1ca",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "0e3cf31b",
   "metadata": {},
   "source": [
    "## Using function to plot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "c6366f7e",
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "\n",
    "def BIC_to_likelihood(BIC, k, n):\n",
    "    x = np.exp((-BIC+k*np.log(n))/2)\n",
    "    if x < np.log(2.2E-308):\n",
    "        return 2.2E-308\n",
    "    if x > np.log(1.7E+308):\n",
    "        return 1.7E+308\n",
    "    return x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "id": "aa6a9076",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"Parameter Estimates/DDM2v2a2c2terresultWagenmakers2008.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "id": "0ec1f97e",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_n = pd.read_csv(\"Parameter Estimates/n_Wagenmakers2008.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "id": "145307fd",
   "metadata": {},
   "outputs": [],
   "source": [
    "df[\"n\"] = df_n[\"N\"]\n",
    "df[\"k\"] = [len(df.columns)-5]*len(df)\n",
    "df[\"ll\"] = df[\"BIC\"] - df[\"k\"]*np.log(df[\"n\"])\n",
    "\n",
    "BIC = np.array(df.groupby('Participant')['ll'].sum() + df.groupby('Participant')['k'].mean()*np.log(df.groupby('Participant')['n'].sum()))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f946ced7",
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   "outputs": [],
   "source": []
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       "               k\n",
       "Participant     \n",
       "1            8.0\n",
       "3            8.0\n",
       "4            8.0\n",
       "5            8.0\n",
       "6            8.0\n",
       "7            8.0\n",
       "8            8.0\n",
       "9            8.0\n",
       "10           8.0\n",
       "11           8.0\n",
       "12           8.0\n",
       "13           8.0\n",
       "14           8.0\n",
       "15           8.0\n",
       "16           8.0\n",
       "17           8.0"
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       "      <th></th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Drift Rate Speed</th>\n",
       "      <th>Drift Rate Accuracy</th>\n",
       "      <th>BSpeed</th>\n",
       "      <th>BAcc</th>\n",
       "      <th>Collapse Speed</th>\n",
       "      <th>Collapse Accuracy</th>\n",
       "      <th>Non-decision Time Speed</th>\n",
       "      <th>Non-decision Time Accuracy</th>\n",
       "      <th>BIC</th>\n",
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       "      <td>2.402747</td>\n",
       "      <td>2.310603</td>\n",
       "      <td>0.503449</td>\n",
       "      <td>0.599552</td>\n",
       "      <td>0.466667</td>\n",
       "      <td>0.085711</td>\n",
       "      <td>0.377105</td>\n",
       "      <td>0.379175</td>\n",
       "      <td>-131.605080</td>\n",
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       "      <td>8</td>\n",
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       "      <td>0</td>\n",
       "      <td>0.893472</td>\n",
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       "      <td>0.546061</td>\n",
       "      <td>0.537191</td>\n",
       "      <td>0.289474</td>\n",
       "      <td>0.068181</td>\n",
       "      <td>0.346250</td>\n",
       "      <td>0.399448</td>\n",
       "      <td>-13.165765</td>\n",
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       "      <td>0.503030</td>\n",
       "      <td>0.000208</td>\n",
       "      <td>0.081876</td>\n",
       "      <td>0.344316</td>\n",
       "      <td>0.393658</td>\n",
       "      <td>-160.678389</td>\n",
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       "      <td>8</td>\n",
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       "      <td>2.542635</td>\n",
       "      <td>0.560067</td>\n",
       "      <td>0.666177</td>\n",
       "      <td>0.081395</td>\n",
       "      <td>0.460524</td>\n",
       "      <td>0.357555</td>\n",
       "      <td>0.354519</td>\n",
       "      <td>-164.218917</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>148</td>\n",
       "      <td>8</td>\n",
       "      <td>-204.196615</td>\n",
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       "      <td>2.402917</td>\n",
       "      <td>0.813833</td>\n",
       "      <td>0.927307</td>\n",
       "      <td>0.826087</td>\n",
       "      <td>0.133394</td>\n",
       "      <td>0.311746</td>\n",
       "      <td>0.406767</td>\n",
       "      <td>-204.242102</td>\n",
       "      <td>2</td>\n",
       "      <td>17</td>\n",
       "      <td>309</td>\n",
       "      <td>8</td>\n",
       "      <td>-250.108832</td>\n",
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       "      <th>92</th>\n",
       "      <td>0</td>\n",
       "      <td>1.741959</td>\n",
       "      <td>1.688959</td>\n",
       "      <td>0.572304</td>\n",
       "      <td>0.704000</td>\n",
       "      <td>0.145410</td>\n",
       "      <td>0.000081</td>\n",
       "      <td>0.331606</td>\n",
       "      <td>0.464750</td>\n",
       "      <td>7.393102</td>\n",
       "      <td>3</td>\n",
       "      <td>17</td>\n",
       "      <td>306</td>\n",
       "      <td>8</td>\n",
       "      <td>-38.395579</td>\n",
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       "      <td>0</td>\n",
       "      <td>2.097835</td>\n",
       "      <td>2.617806</td>\n",
       "      <td>0.750649</td>\n",
       "      <td>1.076347</td>\n",
       "      <td>0.515152</td>\n",
       "      <td>0.217062</td>\n",
       "      <td>0.317224</td>\n",
       "      <td>0.410499</td>\n",
       "      <td>-139.688114</td>\n",
       "      <td>4</td>\n",
       "      <td>17</td>\n",
       "      <td>305</td>\n",
       "      <td>8</td>\n",
       "      <td>-185.450608</td>\n",
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       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>0</td>\n",
       "      <td>2.344213</td>\n",
       "      <td>2.208976</td>\n",
       "      <td>0.824453</td>\n",
       "      <td>0.952635</td>\n",
       "      <td>0.800000</td>\n",
       "      <td>0.225000</td>\n",
       "      <td>0.320416</td>\n",
       "      <td>0.414808</td>\n",
       "      <td>-147.625200</td>\n",
       "      <td>5</td>\n",
       "      <td>17</td>\n",
       "      <td>301</td>\n",
       "      <td>8</td>\n",
       "      <td>-193.282082</td>\n",
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       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>0</td>\n",
       "      <td>2.099490</td>\n",
       "      <td>2.204830</td>\n",
       "      <td>1.094247</td>\n",
       "      <td>1.374779</td>\n",
       "      <td>0.944444</td>\n",
       "      <td>0.500000</td>\n",
       "      <td>0.241287</td>\n",
       "      <td>0.309254</td>\n",
       "      <td>-55.436520</td>\n",
       "      <td>6</td>\n",
       "      <td>17</td>\n",
       "      <td>299</td>\n",
       "      <td>8</td>\n",
       "      <td>-101.040068</td>\n",
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      "text/plain": [
       "    Unnamed: 0  Drift Rate Speed  Drift Rate Accuracy    BSpeed      BAcc  \\\n",
       "0            0          3.004488             3.550522  0.516220  0.569945   \n",
       "1            0          2.402747             2.310603  0.503449  0.599552   \n",
       "2            0          0.893472             1.762489  0.546061  0.537191   \n",
       "3            0          2.336344             2.847524  0.500203  0.503030   \n",
       "4            0          3.127804             2.542635  0.560067  0.666177   \n",
       "..         ...               ...                  ...       ...       ...   \n",
       "91           0          2.473551             2.402917  0.813833  0.927307   \n",
       "92           0          1.741959             1.688959  0.572304  0.704000   \n",
       "93           0          2.097835             2.617806  0.750649  1.076347   \n",
       "94           0          2.344213             2.208976  0.824453  0.952635   \n",
       "95           0          2.099490             2.204830  1.094247  1.374779   \n",
       "\n",
       "    Collapse Speed  Collapse Accuracy  Non-decision Time Speed  \\\n",
       "0         0.000000           0.636364                 0.357856   \n",
       "1         0.466667           0.085711                 0.377105   \n",
       "2         0.289474           0.068181                 0.346250   \n",
       "3         0.000208           0.081876                 0.344316   \n",
       "4         0.081395           0.460524                 0.357555   \n",
       "..             ...                ...                      ...   \n",
       "91        0.826087           0.133394                 0.311746   \n",
       "92        0.145410           0.000081                 0.331606   \n",
       "93        0.515152           0.217062                 0.317224   \n",
       "94        0.800000           0.225000                 0.320416   \n",
       "95        0.944444           0.500000                 0.241287   \n",
       "\n",
       "    Non-decision Time Accuracy         BIC  Frequency  Participant    n  k  \\\n",
       "0                     0.377005 -258.758052          1            1  156  8   \n",
       "1                     0.379175 -131.605080          2            1  150  8   \n",
       "2                     0.399448  -13.165765          3            1  157  8   \n",
       "3                     0.393658 -160.678389          4            1  147  8   \n",
       "4                     0.354519 -164.218917          5            1  148  8   \n",
       "..                         ...         ...        ...          ...  ... ..   \n",
       "91                    0.406767 -204.242102          2           17  309  8   \n",
       "92                    0.464750    7.393102          3           17  306  8   \n",
       "93                    0.410499 -139.688114          4           17  305  8   \n",
       "94                    0.414808 -147.625200          5           17  301  8   \n",
       "95                    0.309254  -55.436520          6           17  299  8   \n",
       "\n",
       "            ll  \n",
       "0  -299.156900  \n",
       "1  -171.690162  \n",
       "2   -53.615731  \n",
       "3  -200.601849  \n",
       "4  -204.196615  \n",
       "..         ...  \n",
       "91 -250.108832  \n",
       "92  -38.395579  \n",
       "93 -185.450608  \n",
       "94 -193.282082  \n",
       "95 -101.040068  \n",
       "\n",
       "[96 rows x 15 columns]"
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     "data": {
      "text/plain": [
       "<Axes: xlabel='Frequency', ylabel='Boundary Separation Speed'>"
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     "execution_count": 10,
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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(df, x = \"Frequency\", y = \"Boundary Separation Speed\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "32718408",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Frequency', ylabel='Boundary Separation Accuracy'>"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(df, x = \"Frequency\", y = \"Boundary Separation Accuracy\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f0d552b2",
   "metadata": {},
   "outputs": [],
   "source": [
    "df = pd.read_csv(\"Parameter Estimates/OUM2v2k2terresultWagenmakers2008.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3bc42ca7",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Axes: xlabel='Frequency', ylabel='Boundary Separation'>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.barplot(df, x = \"Frequency\", y = \"Boundary Separation\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "id": "aabb283c",
   "metadata": {},
   "outputs": [],
   "source": [
    "def BIC_to_exp(BIC):\n",
    "    return np.exp(-BIC/2)\n",
    "def BIC_to_likelihood(BIC, k, n):\n",
    "    return np.exp((-BIC+k*np.log(n))/2)\n",
    "#dataset = \"Dutilh2019\"\n",
    "#models = [\"DDM2v2c2ter\",\"OUM2v2k2ter\"] \n",
    "#sortby = \"OUM2v2k2ter\"\n",
    "def plot_BIC_comparison(ax,dataset, models, sortby = \"OUM2v2k2ter\"):\n",
    "\n",
    "    BIC_all = pd.DataFrame(columns = models)\n",
    "    for model in models:\n",
    "        if dataset==\"Wagenmakers2008\":\n",
    "            BIC_all[model] = pd.DataFrame(np.array(pd.read_csv(\"Parameter Estimates/\"+model+\"resultWagenmakers2008.csv\").groupby('Participant')[['BIC']].mean()), columns = [\"BIC\"])\n",
    "        else:\n",
    "            if model == \"DDM2v1sv2a2ter\" or model == \"DDMfull\":\n",
    "                bic_dir = \"/Users/wangjiashun/Desktop/Reserach on SAT/datasets/transformed/\"+model+\"_\"\n",
    "                BIC_all[model] = pd.read_csv(bic_dir+dataset+\".csv\").astype('float64')[['BIC']]                \n",
    "            else:\n",
    "                BIC_all[model] = pd.read_csv(\"Parameter Estimates/\"+model+\"result\"+dataset+\".csv\").astype('float64')[['BIC']]\n",
    "    # solving the numerical issue\n",
    "    for i in range(len(BIC_all)):\n",
    "        tmp_max = np.max(np.array(BIC_all.loc[[i]]))\n",
    "        tmp_min = np.min(np.array(BIC_all.loc[[i]]))\n",
    "        np_max = -np.log(2.2E-308)/2 # 354\n",
    "        np_min = -np.log(1.7E+308)/2 # -354\n",
    "\n",
    "        if tmp_max > np_max and tmp_min < np_min:\n",
    "            for model in models:\n",
    "                if BIC_all.loc[i,model] > np_max:\n",
    "                    BIC_all.loc[i,model] = np_max\n",
    "                if BIC_all.loc[i,model] < np_min:\n",
    "                    BIC_all.loc[i,model] = np_min\n",
    "\n",
    "        elif tmp_max > np_max and tmp_min > np_min:\n",
    "            dif_max = tmp_max-np_max\n",
    "            BIC_all.loc[[i]] -= dif_max\n",
    "        elif tmp_min < np_min and tmp_max < np_max:\n",
    "            dif_min = tmp_min - np_min\n",
    "            BIC_all.loc[[i]] -= dif_min\n",
    "\n",
    "    for model in models:\n",
    "        BIC_all[model] = BIC_to_exp(BIC_all[model])\n",
    "\n",
    "    BIC_all[\"Sum\"] = BIC_all.sum(axis = 1)\n",
    "\n",
    "    for model in models:\n",
    "        BIC_all[model] = BIC_all[model]/BIC_all[\"Sum\"]\n",
    "\n",
    "    BIC_all = BIC_all.drop(labels = 'Sum',axis = 1)\n",
    "    BIC_all = BIC_all.sort_values(by = sortby, axis = 0)\n",
    "    BIC_all = BIC_all.reset_index(drop=True)\n",
    "    BIC_all.index += 1\n",
    "    if models==[\"DDM2v2a2ter\",\"OUM2v2k2ter\"]:\n",
    "        color=[\"#ff7f0e\", \"#1f77b4\"]\n",
    "    elif models==[\"OUM2v2a2ter\",\"OUM2v2k2ter\"]:\n",
    "        color=[\"#a1c9f4\",'#1f77b4']\n",
    "    elif models == [\"OUM2v2a2k2ter\",\"OUM2v2k2ter\",\"OUM2k2ter\"]:\n",
    "        color=[\"#a1c9f4\",'#699ADD','#1f77b4'] #3179C6 88BDDF\n",
    "    else:\n",
    "        color=[\"#F29A2E\", \"#1f77b4\"]\n",
    "        \n",
    "    return BIC_all.plot(ax = ax, kind='bar', title = dataset, legend =False, stacked=True, width=1,edgecolor='black'\n",
    "                        ,color=color)\n",
    "\n",
    "# DDM vs OUMk    [\"#ff7f0e\", \"#1f77b4\"]\n",
    "\n",
    "# OUMa vs OUMk   [\"#a1c9f4\",'#1f77b4']\n",
    "\n",
    "# DDMc vs OUMk   [\"#F29A2E\", \"#1f77b4\"]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e99272be",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_all_datasets(models, labels, sortby, xlabelsize=15, titlesize = 20, figsize=(18, 12)):\n",
    "    figure, axes = plt.subplots(2,3,figsize=figsize)\n",
    "    plot_BIC_comparison(ax = axes[0,0],dataset = \"Dutilh2013\", models = models, sortby = sortby)\n",
    "    plot_BIC_comparison(ax = axes[0,1],dataset = \"Dutilh2019\", models = models, sortby = sortby) # float 128 issue\n",
    "    plot_BIC_comparison(ax = axes[0,2],dataset = \"Evans2017\", models = models, sortby = sortby)\n",
    "    plot_BIC_comparison(ax = axes[1,0],dataset = \"Lerche2017\", models = models, sortby = sortby)\n",
    "    plot_BIC_comparison(ax = axes[1,1],dataset = \"Rae2014\", models = models, sortby = sortby)\n",
    "    plot_BIC_comparison(ax = axes[1,2],dataset = \"Wagenmakers2008\", models = models, sortby = sortby) # float 128 issue\n",
    "    \n",
    "    axes[0,0].set_title(\"Dutilh2013\",fontsize = titlesize)\n",
    "    axes[0,1].set_title(\"Dutilh2019\",fontsize = titlesize)\n",
    "    axes[0,2].set_title(\"Evans2017\",fontsize = titlesize)\n",
    "    axes[1,0].set_title(\"Lerche2017\",fontsize = titlesize)\n",
    "    axes[1,1].set_title(\"Rae2014\",fontsize = titlesize)\n",
    "    axes[1,2].set_title(\"Wagenmakers2008\",fontsize = titlesize)\n",
    "    axes[1,0].set_xlabel(\"Participants\", fontsize = xlabelsize)\n",
    "    axes[1,1].set_xlabel(\"Participants\", fontsize = xlabelsize)\n",
    "    axes[1,2].set_xlabel(\"Participants\", fontsize = xlabelsize)\n",
    "\n",
    "    axes[0,2].legend(labels = labels, loc='upper left', bbox_to_anchor=(1.03, 1))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "a8c5c1f5",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_all_datasets_flat(models, labels, sortby, xlabelsize=15, titlesize = 20, figsize=(30, 4)):\n",
    "    sns.set_style(\"whitegrid\", {'axes.grid' : False})\n",
    "    figure, axes = plt.subplots(1,6,figsize=figsize)\n",
    "    for i in range(6):\n",
    "        plot_BIC_comparison(ax = axes[i],dataset = datasets[i], models = models, sortby = sortby)\n",
    "        axes[i].set_title(dataset_names[i],fontsize = titlesize, fontweight='bold', fontname='Arial')\n",
    "        axes[i].set_xlabel(\"Participants\", fontsize = xlabelsize, fontname='Arial')\n",
    "        axes[i].set_ylim(0,1)\n",
    "        axes[i].tick_params(axis='both', which='major', labelsize=7)\n",
    "    axes[0].set_ylabel('Model Weight', fontsize=xlabelsize, fontname='Arial')\n",
    "    axes[5].legend(labels = labels, loc='upper left', bbox_to_anchor=(1.03, 1),fontsize=10)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d29987d7",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "2aeed7ae",
   "metadata": {},
   "outputs": [
    {
     "data": {
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jdfr06QLHzsnJ0dGjR/2+XeXIkSMFPkHz+uuvKykpSSNHjtQll1wS9HnJ6y89PV0VKlTQ7bffroMHD2r48OGW1x845zSWWHEaY6y4iT1WnMQkK25ilRWnMcyK09hmxWnMs+ImFloJd2GXm9gZjNN4asdprLVSmMXkwYSKzVbcxOxgvFhE4TTGW3GziD2Q03wAzlnFh0mTJlle9zMyMmyv6VbXa7tr8aRJkyyvsd9++62k4NdPu2tj6dKlba97dte0yy67zPJ6tXPnzhKxMKowC+luuOEGy/eYXZ7dvXt3y9zaLp+2y6Fvu+02y5y5TJkylnmyXW5slw+fOnXKMgeOi4uzzHnt8twePXpY5rbGGB0/flyVK1fWM888I+n3T0OfOXNGTz/9tObNm6e1a9fqX//6l+bMmeMrSKSmpmrt2rWqVKmSDh8+rCpVquj48eM6c+aM4uPjtXnzZtWvX19fffWVGjZsqK+//lqxsbGKiYlRzZo1NXnyZH377beaP3++JkyYoPT0dFWsWFEHDhzQkSNHlJ6ersOHD6ts2bI6c+aMsrKydPDgQVWpUkW//fabTpw4odjYWJ05c0ZxcXEhXy9TpkwpsFg3nNfLhAkTdPLkScvXS5UqVTx7veS/l0JBdvcXDRs2DHnv4PT+INQ9QKg830kOHypPd5KHO8m1neTSTvLlUDmxk3zXaU4bziI4KXTu6SSvDJU7hsoPncwTOZkjCjU/5GReyMl8UKi5ICfXrVDzP07mfZzM94Sa63Eyx2MXD/PYxcW88VvFxjxxcXGWMTL/c2sVKxcvXqycnBzLeAlnnMxNeV3j8Kq+EYm6htc1DadzMl4suM7/3HpVx4jEB/GdzF94WbeIRM3Cy1pFpOoUXsSs/H15Ebuk0PEL4Qu35hEo3BpIIC9qIoHCqZEE8qJmkl+49ZNgwq2pBAq3xhLIi5pLIK8/XB9uTSaQFzWa/MKt1wTyqn4TqLD1nEDh1ncAuODFbyuf67Kyssz777/vt23WrFnm+PHjxXL8NWvWmNGjR5vhw4ebF154wXzyyScF2sybN69YxhJM165dzalTp/y2ZWRkmK5du/pty8nJMb179zbbt28P2eff//53k5OT4/v3sGHDzLhx40xSUlKBY2dmZhpjjJk9e7bvON26dSvQZ0pKinnhhRdMVlaW6dOnT9Dj3nrrrWbPnj3m/vvvN+np6cYYYzIzMwucS69evczPP/9snnjiCbNnzx5jjDE//fRTgXbGGN+Yc3JyzMKFC83gwYNNhw4dTI8ePfzaJSYmmpMnT5pff/3V/PnPfzanTp0yWVlZBc7ltttuMydPnjTGGHP06FFz++23+x6f3+LFi01CQoJJTk42Q4cONcnJyeavf/2rWbJkSYExrlmzxqxduzboc5LnnXfeMQkJCebw4cPGmN/fF0OGDDH16tXzazdv3jzTqVMnk5ub69t25513mqlTpwbtd/Xq1ebee+8N+tzlSUlJMcnJyeYvf/mLSUlJMSdOnDB/+ctffP/neTZt2mQSExPNgAEDTMOGDU1iYqJp166dWb16tV87q///Q4cO+f177ty55uabbzYDBgwwzz77rOncubPp3r27eeutt/zavfvuu6Z9+/ZmyJAhplOnTmbJkiVmwoQJ5uWXXy5wjLS0NJOYmGgSExNNnz59fH/fsGFDgbabN282X331leXzYowxn376qWnfvr05ePCgb9vo0aML/L+g5Il07PGKkxhmJZKxzStOY6QVN7EzGKfx1I6bWGvFSQy24jQ2W3ETs4NxGsftOI3xVpzG/mDc5AMoOkV1Tbe6xhbV9dPummZ3vbK7FoW6xlhdP+yuDXbve7v3tN171ep92LZtW9v3mFWebZdbO8mng+XQdjmzXZ5slxvb5cN2OXConNcqz7XLbVeuXGk6d+7s91rq06eP+fDDD33/3rZtm/nHP/5hunTp4ts2b94889xzz5k+ffqYyZMnmxMnTpjWrVubZcuWmV27dpk77rjDJCYmmjp16phmzZqZxMREs3nzZnPHHXcEfV6MMWbFihUmMTHRDB061EyZMsW0atXKdOzY0SxevNgsX77ctG3b1nTv3t107NjRfPnllyYlJcW8/fbbZtGiRaZTp06+18t9993n6vWSd78S7PWS/3lx8noZP368GTx4sGnXrp1JSUkx6enpvtfLxo0bTWJiornrrrv8Xi+rVq1yfC8F7xXn/UGoHL648nQnubSTfDlUTuw037XLaZ3krE7y0lC5p5O8MlTu6CQ/DDVP5GSOyOn8kN28kJP5oFBzQU6uW6Hmf5zM+zid77Gb63Eyx+MkHuYJFheNsY+NeexiZB67WGmMfbxE8YvEPFM01zW8ijHGOJt7iUQdw+l8iJf1CyfzF17WLSJRs/CyVhGpOoUXMSuP17HLGOv4hbPf2VITcSOc+kkwZ0NNxa1wazCBwq3JBPKiRpOfF/WaQOHUbwKFW88JFG59B4BzLC5EkQsskNjdDO7fv99RMLYrnuTnpJCSX6iFbCkpKX4FFqsbQ7tiSyA3N4g33XRTgRvE6dOn+7WzukEcN26cX7tNmzaZ7t27m+uuu86MHz/ebNmyxZw5c8Y88MADBdr16NHD9OnTx+9GPVi7Ll26mN69e/u169+/f9B2+fs7dOiQ7XHnz59v3nzzzaDHDWy7Zs2akH22bNnSjB8/3mzfvj3oOX/xxReOzzn/cbds2WL27dsXtF3Hjh1NgwYNfBOkwY5rjDFHjhwxI0eONCkpKWb9+vWmdevWplOnTiYtLS1ou9TUVLNlyxbToUMHk5CQUKDd4cOHHbUDEBluYqQVp7EzGKfx1I7bWGvFyWLyYJzGZituYnYwXiyicBrjrTiN/cE4zQcAJ0Jd06yuV0WxMMru2lDYhVF271Wr9+GwYcMs32N2ebZdbm2XT9vl0HY5s12ebJcb2+XDdjmwXc5rl+fa5bbBHpe/z1GjRpnU1FSzefNm0759+6B9bt68ucDjRo4caf773/+a9evXm/bt2/v2WY3lyy+/LLAv2ONSUlJ8x8ufn2dlZZmtW7eatLQ007dvX5OVlRX0NfmPf/zD798nTpzwFUPz9uUV/86cOeP3uLzian6//PKLqVOnTtBj5ebmFnhcbm6u2bVrV4FxBvYdOE7AS05z6VD5cqic2E2+a5XTOslZneSloXJPJ3llqNwxVH7oZJ7IyRxRqPkhJ/NCTuaDQs0FOZkDCjX/42Tex8l8T6i5HidzPHbxMH8bq7gYeJzA2Bh4nGAxMo9drAy2P1gfQKR4FWOMcTb3Eok6htP5EC/rF07mL7ysW0SiZuFlrSJSdQovYlYer2JXXju7+AUAwXhRgwkUTk0mkBc1mvy8qtcEKmz9JlC49ZxA4dZ3ADjH4kIUi6ysLLNlyxaTlpZmtm7d6lsxn9/QoUMt/wSTv3iSJ9i3u+UvpBgTutj/yy+/mGnTpoU6pZD95ebmmp07d5q0tDSzffv2oOfsZDxWtmzZYvbv3x903+HDh81XX31ljh49aowxQQtSPXr0MLt27TLbtm0ziYmJZvny5caYgpMFPXr0MDt37nTULlh/gZ+s8Pq4bvssjnMubDtjjBkwYICZM2eOmTBhgmnRooXZs2ePOXDggOndu3eh282dO9fX7scffwzaDkDkOImRVtzGzmCcxlM7bmOtFbcx2Irb4zuN2V4cywm7GG/FSewPxk2MApywuqaFul7ZXYucXGOcXD/yP87qfe/mPR34Xg32PrR7j9nlnHa5tdd9OtnndZ92uWyofVa5bTh9erHPzVjyn0P+fY0bNzYtWrQwbdq0Ma1btzYNGjQwbdq0MW3atCmwr379+qZ169aW++we53WfTscJFIVQubTTfDlUTuwm33Wa0wbrI1Re6jb3tMor7XLHUPmhkzkTJ3NERXkcN228OI6TcTiZxwnVxskcj1fHCbePYG0Cx+t0bguIFK9ijDHO5l4iUcdwMh/idf0i1PyFl3P4kahZeFkziFSdwqs4kNfOi9jlph0ABAqnBhPIi5pMIC9qNPl5Va8J5FX9JlC44wunvgPAuVKR/llmnP2GDRtmue/555/3/b1t27YaM2aMnnzyybD6bNSoketjB2uXty1UO6f9BWsnSS+88IKnfTptV7p0aV1xxRWSpEmTJqlfv36qXLmyYmJi/B5TunRpVa9e3VG7YP0FKuxx+/fvH7Sd2z6L45wL206STp48qcTEREnSpk2bVLVqVUkq0NZNuy5duvjaXX755UHbAYgMN/EiGDex0+3x88fTwvbh5BycxuDiPL6bxzuN40U5hnAe7yZGAaHYvRbtrld2j5s9e7ZnY4iEvXv3Wr7H7HJOu9za7n1rl0OHepyX4wy1zy6XDbXPKrcNp08v9rkZS/5zyL/v3Xff1ahRo5ScnKx69eopKSlJ06ZNkyTt2rWrxO8DvOYkB3KSL4fKiZ0cJ1ROW9g+AtuEyj29OE6o/NDJnImTOSK3xwk2L+Qkly3K88nfR6hxOJnHCdXGyRyPV8cJt49gbQLH63RuC4gEr2JMqL7y5l4iUcdwekwv6xdO2ng5hx+JmoWXNYNI1Sm8igN57byIXW7aAUB+4c69Bwq3JhPIixqN0/4Kc77h1m+c9JcnGvoDYI3FhShybdu21ejRo/XUU0/ZtmvXrp02bNigI0eOqEOHDp706aadk0TA6+NG8tgXXHCBXnnlFQ0YMECVK1fWuHHjNGjQIJ06dSoq27300ktB20XTGMNtJ0kXX3yxRo0apUceeUSpqamSpLfeeksVKlQo0nYAIsNNvAjGTewsiuN70Ue4N+NeHD+S4/dqDIV9vJsYBYRi91ps1qyZ5fXq+PHjlo8Ltc/q/Rctfe7fv9/yPdawYcMi35c/hy6O4znd16RJE8sctXz58ufsvurVq2vs2LF69tlnVadOHb8i2dmwD/CakxzISb4cqh8nxwmVEzrtIxqOEyo/dJI/etHGybxQURynqPpwMj8Tqo0XfZS04wCR4lWMcdp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      "text/plain": [
       "<Figure size 3000x400 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "models = [\"DDM2v2a2ter\",\"OUM2v2k2ter\"] \n",
    "labels = [\"Threshold DDM\",\"Self-excitation OUM\"] \n",
    "plot_all_datasets_flat(models, labels, sortby = \"OUM2v2k2ter\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "3f1fc7b8",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3000x400 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "models = [\"OUM2v2a2ter\",\"OUM2v2k2ter\"] \n",
    "labels = [\"Threshold OUM\",\"Self-excitation OUM\"] \n",
    "sortby = \"OUM2v2k2ter\"\n",
    "plot_all_datasets_flat(models, labels, sortby = \"OUM2v2k2ter\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "3b921c0f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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dOqaHZanx33//acaMGdq6davCw8OVN29eNW7cWAMGDHC5cyBxdKhEjz76qGm5YMGCKl26tI4dOyYp4YHclStXVKBAAUkyjTwVEBCgevXqGctlypRRmTJl9Ndff0lKGOnqxo0bCggIMNp0795d169fN5bz5ct31+kOJKlx48bau3evIiIidO7cOVWoUMG0PekxJfFwD8BdkTucl11zR9KpqD09PU0FJ5LUu3dvffzxx8bohevXr6e4EIBLTp06pTZt2hjL5cqV0/fff++wre2orm+//bapmPr8+fNasGCBfvvtN124cEG3bt1Sjhw5lD9/flWtWlW9evWye6NeMuea+vXra968eQoNDdXs2bO1fft2Xbp0SYGBgWrQoIH69++vhx9+2GF8J06c0OLFi7Vv3z5duHBBt2/flre3t4oWLaqaNWvq6aefNuUqZ5w4ccI0dWSDBg2MwsJE9evXN+W8sLAw4+etW7ea2gYHB5uW27ZtaxQXJrZPeq1fsmSJPvjgA9M+zuaQ5Fy+fFnjx483ljt37mx01gJAcrZs2aJly5bp4MGDunbtmnLmzKkKFSqodevW6tixo3H/kdSoUaO0atUqSVJQUJDWrl2rqVOnavXq1YqMjFTBggU1ZMgQ/e9//zP2uX79uhYtWqRff/1VZ8+e1c2bN5UzZ06VLVtWbdu2VefOnR2ey1ZcXJyWLFmilStX6tSpU/Ly8lKlSpX09NNPq2XLlsnuFxUVpUWLFmndunU6c+aMYmNjlT9/ftWuXVtPP/20qlSp4vLvLum9iJeXl+leQkoYUSNXrly6du2apIT7oEQ3btwwjT5TtmxZ4wGZlNDX5O/vr5s3b0oy37ck7p/4UCzRveYRSfrggw8UEREhKeGhOCNvAEgLQUFBypMnjzFLh5RQzGzbBxQREaH58+dr+/btOnv2rKKiouTh4aF8+fKpYsWK6tatW7KjuErSP//8o6+++krbtm3Tf//9Jw8PDxUtWlSNGjVS7969VbBgQZfiPn/+vHENlxJeQLIdWdD2+3bSe4bdu3cbL7tKCX10SUcta9u2rVFcKCXcMyQtLty0aZOGDh1qOn5qr/Xjxo0zfRYA6a9WrVqmaVIPHDiQbHGhl5eXypUrZ/QZ79u3T7Gxscb348Tnj4lKlSqlvHnzGsvR0dFasWKF1q1bp7/++kvXr1+XxWJRrly59NBDD6lNmzbq1q1bsiPG3rx5U1999ZXWrVun8+fPy8/PT4888ogGDRqkChUq6PHHHzf6yJN7PnDlyhXNmzdPmzZtMqaXLVSokOrVq6devXqpVKlSDs+dtD9nxIgRGjx4sEJCQjR//nwdOHBAN27cUOHChdWyZUv17dtXuXPnNu2/e/du9erVy1j+5ptvVLZsWWNUunPnzsnf319169bVkCFDjGL448ePa+bMmdq9e7du3bqlYsWK6fHHH1efPn3k5eXlMNY9e/Zo6dKlOnjwoC5evKiYmBj5+PioSJEiqlu3rvr166dChQo53Dc5a9euNQ1Q4+bmpo8//litWrUytUtNjrP93Xz99de6fv26pk6dqtOnTysgIEB16tTRJ598Iinh72Dp0qX69ddfdfLkSd24cUNubm7KkyePypcvr3bt2qldu3Zyc3Nz6TNm5n1TSv13np6eatmypb7++mtJCTNf7d69W82aNZMku89pO1uMp6enPDw8jOJCnv8D2RfFhcgyGjRooKJFixrFHdevX9cff/yRqo7LrOT333/X4MGDTUUV//77r5YvX641a9Zo3rx5Dh8yJmfevHkKDw/XxYsXdfHiRYdJ2LZQL/HtgbCwMNPNcalSpWSxWExtkxaIWK1W/f3336pRo4axPemIU9WrV9fUqVP12GOPOR1/njx5lCdPHkkJbxVevnxZ27ZtM02J5uXlxRvfAJxC7nBOds0dSWMKDAy0u1H19vZWwYIF9e+//0qSLl26pMuXL5s6jQAgJQ899JBq1qypffv2SUoopvvrr79UpkwZu7aJU4BICdefpKO27tixQ0OGDLGbPvHWrVs6d+6czp07px9//FGvv/66evbsmWJMmzdv1osvvqioqChj3cWLF7V69Wr9+OOPmjVrlt3DuSVLlui9994zTV8sSZGRkfrzzz/1559/asWKFXrrrbfUtWvXu/xW/k+9evW0Z88eI384ur7euHHDtJyYPyQZuSGRbSe57e/Ztn3S/JEjRw69/PLLunbtmqZNm+b0Z7D10UcfGTH7+/vrpZdeSvWxANz/oqOjNXr0aFMOkBIKlbdv367t27dr8eLFmjlz5l2LMV577TXTaBTnzp0z7RMSEqJhw4bZTdsbERGhXbt2adeuXVq2bJlmz56d4vfdqKgo9e7dW7///rux7tatW9q5c6d27typPn36GKPIJvXXX39p4MCBxr1VotDQUIWGhmrVqlXq06ePXnnlFbv7gZT88ssvRh65ceOG3b6xsbGmnGebR5LmAttph93d3VW6dGljhJqrV6/q4sWLxktStqOmN23aVCNGjLinPqfff/9da9euNZZHjBjhcHpOAHDVxYsX7XJA4vUs0fHjx/Xcc88ZBc6J4uLidOHCBV24cEHr169X37599eqrr9qd48cff9To0aNNUxBLCfdBiS8rTZgwQa1bt3Y67uLFi+vAgQMKCwvTxYsX5e3tbdfGlXsG22u97T1D0ikfbbm7u6tfv34KCgoyjebkjNWrV2vz5s2SEu49WrZsaZf/AaS9WrVqafny5cbywYMHTS9yJi0urFmzpmrXrm0UF0ZGRurYsWOqWrWqJOnQoUOmYyedEvnGjRt69tlndeTIEbsYwsPDFR4erpCQEK1du1Zz5861K5w7c+aM+vTpY/qufPv2ba1bt06bN2/Whx9+eNfPmtz3/VOnTunUqVNavny5XnvtNVOhW3I+/fRTTZ8+3fR998yZM5o9e7bWrl2rpUuXpnh/Eh4ertdff910Tb19+7bWrl2rX3/9VQsXLtTJkyf1+uuvG1PTSwnX7KlTp2rHjh2aN2+eXSHmjBkz9PHHH9ud7+bNm0b/1KpVq/Tll1+anh+k5MCBAxo9erRp3dixY+0KC9Mqx23ZskVffvml8bJtRESE8fdw7tw5Pfvss3b3TFLC85t///1Xmzdv1qpVqzRjxgzlyJHDqc8oZe59k6u5+K+//jKKC0uVKqWAgAAj18+fP1+VKlVSrVq1dOXKFX366aemuDt37uzEbwNAVuRayTSQzhK/ACayHb46Oxo4cKBdwUaiqKgojR071qXjeXh4qFChQqpatapatGhh9+Xi0KFDxtsuklSsWDHjC8aZM2dMbR11RtuuO3v2rF2b/Pnza9y4cVqyZEmK08TczcyZM9WoUSONHj3a+NLh6+urzz77TEWLFk31cQE8WMgdd5ddc4evr6/xc0REhKkjI5HtG+UMqw882E6ePOnUv6RsRzT64Ycf7I67f/9+09vvwcHB8vf3l5Tw1vnIkSPtCgttxcfHa/z48UZBtCNnzpzRiBEjTJ1uSUVHR2vs2LGmDsPjx4/r3XfftSsstBUXF6e33nrLYUd6SgICAlS6dGnVr19fZcuWtdtuO21L0rfp75ZDbJdt20sJU7m0bNlS3333nVMd7Ck5efKkVq9ebSw/99xzFKQDSNG4cePuWlhw7Ngx9evXzzTqkq3EIvOk8uXLpzp16khKeODVv39/uweNto4ePaoXXnghxTZTpkwxFRba+uqrr0wjhEsJDxeTe0iWyGq1as6cOZoxY0aK57fl6empokWLqkaNGnYjqEsJo48n/Z7vSh6RZLzAmsjRvUiJEiU0ZcoUffHFF8qZM6dL8dtK+nJsUFCQafQsAHCF1WpVTEyMrly5oj179mjo0KGKi4sztpctW9bURx4dHa3hw4fbFRY6MmfOHO3fv9+07rffftNLL71kV3SR1K1btzRy5MgU84gjPj4+KlmypOrUqWPXTyfZ3zMkva+427Xe29vbVEARGhpqGl09Ud26dbV06VK9+OKLLo8WFRYWZpoOefjw4SpZsqRLxwCQOrbTFicdfe3UqVOm0dnq169vN7PN7t27He5re+z33nvPqf6QPXv2aO7cuaZ1UVFRGjBgQLLflaOjo/Xqq6+aRmW19ffff2vAgAEpft+PjY3V+++/b5re1pHvvvtOn3/+ud2LNIn++ecfhwV+SY0aNSrZYu3IyEgNGjRIo0ePdtgfLyUUSiYtCpUS8szdzislFBqOGjXqru2khFmkhgwZYrrXGjhwoHr06GF37rTKcbNmzbLLM+3atZMkvfjiiyneMyXasWOH6b7BGZl13xQXF2fq8/T19bV7USCl/jtvb2/T9OTh4eHq06ePqlWrpqZNm2rlypWSEgocR48ezVTlQDbGyIXIUmzforh06VKaHXvixIm6deuW2rZta6wrUKCA5s2bZ/ycHiIjI9W2bVt17dpVOXPm1ObNmzV9+nSjo+DPP//UyZMnjSGm78WdO3f03nvvmdYlfQMjpTcEEyUt5HC0z6RJk9SwYcNkh7t2xT///GNazpEjhz799NMUp20AAFvkjnuTlXNHmTJljKma4+Li9PPPP+uJJ54wtm/ZssWuACe5okwAD4ak1+uUnDhxwvi5TZs2ev/99xUZGSkpYYTCkSNHmgqxbQsOO3XqZPy8dOlSU6Fzq1at1KtXL/n5+encuXOaMmWK0ekWFxenPXv2mK5lSSUWHrZo0UI9evRQzpw5tXbtWtM0YOfPn9eJEyeMaYLWrl1regg5YMAANWnSRAEBAbp48aIWLFhgTG8SFxenL7/80qnOXmesX79eW7ZsMZZ9fHzUpEkTY/luOcQ2fyROz5KoXr16WrdunWkql3sxY8YMo4PY29tbTz/9dJocF8D9KSQkxJjWWEoYSXvYsGGqVq2awsLCNGPGDOMB5Z9//qn58+ebHqo48uyzz+rxxx/X2bNndfnyZWOkj7feesv0IKxChQoaNGiQihUrpqNHj2ry5MnGg8iQkBBt3LhRzZs3d3iOyMhIlSxZUoMHD1bZsmV17tw5ffjhh6aXidatW2ca7X3y5Mmm6SNr1aql/v37K1++fNq7d6+mTZtmXNM///xzderUyeWpzBy5cuWK3UM3V+9FbNcl3cfb21uzZ89Wo0aNXC40cWTnzp2mYp1nn3022WnzAMCRpIUAKXFzc7Mbpennn382FVDXqVNHgwYNUp48efTff/9p+vTpphdud+/ebYwKFR8fr3HjxpmKJbp06aL27dvLw8NDP/30kxYtWiSr1ar4+Hi9+eabdgWBqXXw4EGtWLHCWLZYLKbRppztd0q8X4uLi1NUVJTxslfZsmW1evVqVahQIdUxvvHGG0Z/UtWqVfXcc89p+vTpqT4eAOcVK1ZMhQoVMooIT58+revXrytnzpymUQulhFmMKlasaJreNSQkRP3795dkP+hA4siF//77r77//ntjfZEiRfTqq6+qVKlSunHjhlasWGEq6Nu9e7cGDhxoLC9cuNB0/fXy8tLQoUPVuHFjXblyRV999ZW2b99uTPvqyNtvv216KbVZs2bq0aOHAgICtGXLFs2ePdvY/4MPPlCrVq0cjgQrJRR2ubu767nnnlOLFi0UFxenmTNnmqa63bhxY7KxSAkj1xUrVkwjRoxQmTJl9Pvvv2v8+PFGnkgslKxTp46ef/55eXl56fPPPzf9n2zcuFFPPfWUsTxr1izjZ4vFokGDBql58+aKj4/X0aNHjWctiZ8hLCwsxdEVb968qeeff950n9KxY0fT9MhS+uS4SpUq6ZVXXpGHh4fWrFmjhg0b6tSpU6aXtGrXrq3nnntORYoUUXR0tLZv364ZM2YYBYBLlizR0KFD7/nlJil975uioqJMvztnnv/Y9t8NGDBAVqtVM2bMcPjytcVi0YQJE9S+fXu7bQCyD4oLkaXYflGyTYb3wtEoSZ6enmlSmJGSxx9/3JTwK1WqpNDQUNOIGWfPnr3nOBLfXEz65dnPz0/PPfecsWyb0D087C8Btp2itkUbrkyBfDe2xYV37txRv3791KlTJ7377rsO4wMAW+SO1MvquaNNmzamjp233npL165dU7Vq1XT8+HF99NFHdvskN9oXACTH19dXbdu2NR54XbhwQXv37jXepI2NjTV1OhYtWlT16tUzlhs2bCgPDw8dP35cV69e1dSpU43rYoUKFRQXF6eRI0ca7VN6k11KKJCcOnWqsVy5cmWdOnVKv/76q7Hu/PnzRnFh0qJqPz8/DRo0yOj0K1eunOrXr68xY8aoYMGCevjhh+/poVtSiW+FJ9WjRw/lzp3bWL5bDrFdTnxgmCjxM6aFsLAw/fTTT8Zyx44d7d7aBoCklixZYlr+/PPPjdxQpUoV1atXT48//rhRGL58+fIUiwvr1q1rFIokLew7fvy49u3bZyyXLFlSy5YtM6bQqlSpknLnzq2hQ4dKShgR/O+//062uDBnzpxavHixMbpEhQoVlCtXLvXu3dtok/Th6I0bN0xF9KVLl9a8efOMF4OqVKmiYsWKaciQIZIS8uK3335rLKfWjRs31L9/f4WGhhrrihQpYpom617vRby8vByO+pFaSUexCQwMZEovAOkif/78evfdd+1G56pQoYJGjx6tEydO6MyZM5o+fboCAgIkJXxvzp07t7p27Wq0T3rfsX37dtOoRJ07dzaN1FerVi1ZLBYtWLBAUsKI33v27Lnn0YWOHz+uAQMGmEZaat26tWl6RWeu9bbrkhYXBgUF3VOMK1euNF6Y8vLy0vjx4ykcBzLYI488YowWbrVadfDgQTVu3NhUyBYQEKBKlSrJ3d1dtWvXNqYx37t3r+Li4uTm5mYq/CpatKjRt+/l5aV33nlHx48f1/HjxzVy5EjT9a1WrVpav3698T3Stt8m6QtHkvTuu+/qf//7n7Fcr149PfvsswoJCXH4+U6ePGnaVr9+fdNo4NWqVVPOnDk1fvx4SQmFfz///LPpHLbGjh1remFy2rRpatq0qa5cuSIpYbafxCJNR3LkyKEFCxYYI+RWqFBBO3bsMPU9lS5dWnPmzDHuCz766CM1bNjQ2J50VEkpoU+oevXqOnHihEqUKKERI0YY26pWrarjx49r6dKlxrqUigvj4+P10ksvmUZXbNy4sd0gCVLa5zg3Nzd98sknKl68uKT/K1K1fe7UpUsX0z1ZtWrVlCdPHp04cUJlypTRww8/7NK0yMlJ7/sm2+cpnp6eTu+bVKVKlVSgQAGHI8lbrVa99tprunDhggYNGmS3HUD2QOUOshTbIZzvNrVXduBoNIwKFSqYCkRsK/xddefOHQ0bNsw0aogkjR49Wvny5bunY6en3r1766WXXlJERIQ+//xz4+3vlStXymKx6IMPPsjkCAFkB+SO1MkOuaNp06aqV6+edu3aJSnhM7/77rsp7kMHMIDU6NKli2k0jR9++MHoZNy+fbvROSsljFqYdFTDqlWrOpz6KyYmRocPHza9OS4pxSlapIRRkGzVqlXL1MGbtAivUqVKpvWtWrVS69at1aBBA9WoUUOBgYGaOHFiiud01datWzVs2DDTtDQlS5Y0Cl+yom+++cb0HaFnz56ZGA2A7CDpFGv58+e3e/jk7++vBg0a6Ntvv5WUME1jSg/Ikhtd13Zarg4dOtg9hGratKnmzp2r8uXL37UwulWrVnbTVlWsWNG0nPReYt++faaijxYtWtiNON60aVN5enoa7fbs2ZNiDHdz5coV9evXzzQ1ncVi0XvvvZcmD+DSw4ULF7R9+3Zj+cknn0x2NBkASI02bdooODhYzZo1c3h9KVOmjKkoL1F8fLyOHz+uX375xbQ+6X1H0pwmOc5JrVq1MgovpIT8dC/FhUePHlWfPn1MU4AGBgZqzJgxqT5mWgsLCzOKeSRp8ODBevjhhzMxIuDBVLNmTaO4UEoYgbBhw4ama1edOnWMft8GDRoYxYWRkZE6evSofHx8TMVftWrVMn7OmzevnnzySYfnDg0NNX3Hk8zXz6tXr+r06dPGcv78+e1GX3N3d1f//v2TLS60vQa3adPGrk2rVq1M16M9e/YkW1zo6+trKiaXEgZgqFy5sqkPKioqKtniwoYNGxqFhYlKlSpl6nvq2LGj6b4gX758CgwMNK7rtgVtLVq0UIsWLezOdfPmTe3Zs8duGuakfUq2fv75Z9N2Ly8vTZkyxWHRXFrnuKpVqxqFhUmVLl1aOXLkMOIaO3asNmzYoEcffVS1a9dWqVKlTCM5poXsct+0fPlyvfHGG5ISChtHjBihRo0a6cKFC5o6dapOnjyp+Ph4ffzxxwoKCjKmmQaQvVBciCzFdqSKxDfvXGFbZJLZHN2M2g4pnHQaM1dFRkbq+eeft/vS2q1bN7svyz4+PqZlRwU4tutshzpOS0mnTKtdu7Zat25tvPG/cuVK9e/fX6VKlUq38wO4P5A7XJddcofFYtHUqVPVv39/0w10ooIFCyooKMj0QNbRsP0AHhxJpzt2RfXq1fXwww/r77//lpTQiTl27Fh5enqaRnNyc3NTx44dHR7jzp072rZtm3bv3q2DBw/q+PHjDjtK75ZzHE0BnCtXLtNy0hzQoUMHLV26VEePHpUkYyrkBQsWyGKxqEyZMqpXr57atGmjmjVrpnhuZ/zyyy968cUXTYUouXLl0rRp0+xyhu1DUdvcZZs/0vManrRAv0yZMuk+CjGA7O3mzZu6fPmysXzp0iWnprL8+++/ky0uTG6K96QjUEiO7wU8PT3tRrBKjqP9bb+fJ73+Jh3lQ5K++OILffHFFymeIzFfpsalS5f03HPP6a+//jKtHzlypGkkFOnueUTKuH6s1atXm6YLSzqlJwA468cff9SdO3d0/vx5zZkzRwcOHDC27du3T717975r4XJsbKx+++037d69W/v379exY8ccjiCU9L7D9lrft2/fu8Z6L9f6vXv3auDAgaZCHy8vL33yySfKnz+/qW1mXuvHjh1rjARfsWJFY2pVABnLtsjrwIEDOnLkiGmmhqTfhW2/F+/evVuBgYGmdYmjzdk6cuSIduzYob179+ro0aOmKXcTJb1+2o7OV65cObm5udntk3Rkclu21+Bx48Zp3LhxybaXUr4GFytWzGGRnW3fUUqDMDga9dW2T8fR81kfHx+juDC5/q2IiAht2rRJe/fu1aFDh3Tq1CnT9+hEjtYlsu1Pi46O1g8//KAePXrYtU3rHJfcfZu/v7+GDRtmzKYUExOj9evXa/369ZKkPHnyqHbt2mrWrJlatWpl9/t0VUbdN93r858LFy7o7bffNpb79etnjOhfsWJF1apVS8HBwcZ3gmnTpqlt27amF7cBZA/22Q/IRJcuXTItpzRyUnJfWrLaiFWJw/MnZTuqUmqLWm7cuKG+ffvaFYd07NhRb731ll1724d1tm+VSPZDGaemSCc1vL29TW8qWK1WY6QqAEgJucM12S135MmTR0uWLNGrr76qcuXKKUeOHMqdO7c6deqkb775xjT9piS7jiQAcFaXLl2Mn69evart27crKipKGzduNNbXq1fP7s1uSVqwYIEaNmyoIUOGaMGCBTp48KDu3LkjX19fl6f2dXQNdTQlSaLEqWx69Ohh95DNarXqzz//1IIFC/TUU0/pqaeesiticcUPP/ygkSNH2hUWzpkzx+EoKrb5zDaH2L4g4Cj/pYXjx4+bOpsdvUkPAEnZXp+clfQBqK3kvqfanuteR6BwVKjt6OFjotSMiG47JZiz/vvvPz3zzDN2D8gGDx6sgQMH2rW3zQuOimcyqh9rw4YNxs+FCxdO8QEyACSndOnSqlixooKDg7Vw4ULTyFphYWHq06ePDh06lOz+P/74o5o2bap+/fpp9uzZ2rNnj6KiopQjRw7TiOa2MvJav2vXLvXr18+usHDatGmqV6+eXfu73TNI5lzp7u6eJsWFK1eu1NatW43l/v376+zZszp58qROnjxpGr1eSngZ4OTJk7p48eI9nxuAWdmyZU2FcYcPHzZNiSwlTCWc6OGHH1aBAgWM5ZCQELtrp23B4h9//KGOHTuqc+fOmjJlirZs2aLw8HC5ubmpXLlyyRaC2V4/k3spMqXvoGl9DU7uXCn1HdlydB21LZp09FkdFVYmunXrlsaNG6fGjRtrzJgxWrlypf7++2/Fx8crf/789zyN/bRp0xz+LtP692tbpJlU//79NWnSJJUsWdJuW0REhNatW6fXXntNTZs2Nb2s7KqMvG/y9fU1Ffo58/wn6fm+/fZb0/O1pP2rUsLznWbNmhnLp06dspt6HED2wMiFyFKOHz9uWk6poy65QpC7TTOW0dJresaoqCj179/fmEo40dNPP61x48Y5rPi3HcY5IiLCro3tWzrJvaGRWnFxcbp06ZIKFSpkt832rcVr166l6bkB3J/IHc7LrrnDy8tLffv2dfjWYdLiUovFwkhUAFKtQ4cOmjx5slE4t379et25c8fUqdapUye7/ZYuXar333/fWK5Vq5bat2+vGjVqqEyZMgoJCVHv3r2djiM1OcDf31/jxo3TK6+8oh07dmj79u36/fffdfLkSVMx+r59+9SvXz/98MMPdlNe3s3PP/+s1157zfT2c758+TRnzpxkCyiLFy9umjrTNockHRVMksPO2bSQOF1SIooLAdyNbYFf8eLF7zqan6RkRy2U7EeTSGT70C61xRyJXM0jtnH16dPH7oGQrdSMMhEeHq7evXvrzJkzpvUvvfSSMbKFraxwLyIlPNw7duyYsdy8efM0PweAB4+Xl5cmT56sxx9/3CiMiIqK0ogRI/T999/bFY9s2bJFL774ovH9vly5curcubNq1aqlcuXK6b///kv2e65tXps6depdR+RNTQHfnj179Pzzz5vuoXx9fTV9+nRTYVBSd7vW37p1y1TUULx48RSLW5xl+9LtyJEjU2z/7LPPSkp4OXfChAn3fH4A/8disahmzZrGvfvVq1e1fPlyY3uBAgXs+nzr16+v7777TlLCaKmFCxc2tuXLl08PPfSQsRwWFqZnn33WGHEvb9686tatm+rWravKlSvL399fjz32mMOiKtuiw+ReQkrpO7zt9+3Ro0ercePGybaXlGKfTVo8O3DmOurqtXbMmDFau3atsfzEE0+oWbNmqlatmooWLapPP/1Un3/+udPH8/b2VosWLYwpsyMiIvTFF1/opZdeMrVL6xx3txEH27dvr/bt2+vIkSPasmWLdu/ercOHD5ty1dWrV/XKK68oX758yea/5GT0fZOHh4eKFCmiCxcuSEoo1oyOjjb9Ddrum7T/zrYA0vZZv6N1//33n8M6AQBZG8WFyDKOHz+us2fPGss5c+ZU1apVjWXbNy4cfYG7fft2im+J3y/i4uL0wgsv2BWH9O/fXy+//HKy+xUpUkQ+Pj7GF+TTp0/LarWaOoVPnTpl/GyxWBxOp5Man3zyib7//nv9999/io2N1aZNm+xGfTl//rxpOU+ePGlybgD3L3KH87Jj7pASOpHDwsIUFhamsmXLmkYqjI2N1Z9//mkslyhRIt1GvQJw/0t8k3bdunWSEh7eRUdHG9tz5syp4OBgu/2SdoxWqlRJCxcuNHX0puYN6tS4deuWrl69qhYtWhgPFW/cuKFdu3bpww8/NEbuO3PmjPbu3etS5+bvv/+ul19+2VRYWKhQIc2bN8/hNDmJknbmS9LJkydNU7ckzR+S46k800LSAkdfX19VrFgxXc4D4P6RK1cuBQQEGA8JL126pKCgILv7i7/++kv58uWzG03bkeRGD7R9EHT8+HE9/vjjpnVWq1WDBw9W/vz5Vbp0aZUrV87h6E+pUaxYMdPy9evX7R7e3rlzR6dPn9ZDDz3kcnG6lJCjBgwYYHpAZrFY9MYbbzic2iyRbRy2ecNqtZqOGRgYaBrFJq3s3bvXtJx0pDEAuBeFCxfWq6++apoe859//tGkSZP0zjvvmNrOmDHDKCzMnz+/li1bZiqASGnUXdtrfUxMjN019tKlS4qKikp18d7Jkyc1aNAgU3FOQECAZs+erRo1aiS7n20cJ0+eNC3bXvsdjZgOIPurVauW6cXApM8LHfVfNGjQwCgujIyMNE1za/td7euvvzYKCyXpyy+/tOsXSK7vxvY55vHjxxUfH293nUxp1Fnba3BUVJTdte/69eu6dOmSSpQokeKo41nV6dOnTYWFPXv21NixY01tXOkf8/T01Keffqq6desqJCTEGDV2/vz5evrpp03FpGmd4+72+4+Pj9eFCxdUoUIFVa5cWUOGDFFsbKyOHTumBQsWGCMWWq1WrVy50qX+t8y6b3rooYeM4kKr1apTp06ZXiQ+ffq06XhJ++9sp7C+cOGCXTy204snNwIogKyNaZGRJURHR+uDDz4wrevevbupw9L2TT3bRCYljC5yN0m/NGS1aTCd9emnn2rLli2mdf369UuxOERK+OxJO5+vXr2qnTt3Gstnz541vWFQo0aNNJtOJkeOHDp//rzxO1+2bJlp+7Vr1+yGiKazFkBKyB2uyY65Y/Xq1apevbpatWqlXr16afXq1abta9euNXWet23bNk3OC+DB1blzZ+Pn8PBw/fjjj8Zy27Zt7d6GjoiIME2L5efnZ/cG+U8//ZRO0SZ0zPbr10/NmjVTjRo11KVLF1NnbUBAgFq2bKmmTZvaxe2sixcvatiwYaapkPPnz69FixalWFgoJXT2J5X09ynZ5+AmTZo4HZcrknbylytXLk1GOgFwf7NYLKap1G7fvq2FCxea2ly5ckVdu3ZVvXr11KhRI/Xv3990rXR0TEfq1KljWv7+++/tHrzt2LFDmzZt0rJly/TBBx9o1qxZrn6kZNWsWdOUu9auXat///3X1GbVqlXq0KGDatSooTZt2mjevHkunWPs2LE6evSoad24ceNSfEAmJYw6U7ZsWWP52LFjpnu6Xbt2mUaJudsIMKl14MAB0zJF6gDSUteuXVW7dm3TuuXLl+vgwYOmdUln7vD29ra7N7H9rp2Uba6ZO3eu6cUhSRo/fryCg4NVs2ZNderUSbt27XL6M0RFRWnw4MGml3d9fX311VdfpVhYKEn16tUzfT//5ZdfTH1vGXXPACBzpfQ80FFxVkoFW7ZTItvOfGQ77e327duTHXwgMDDQVCgVHh6u77//3tQmNjZWM2fOTDYe22v8kiVL7L7vz549W23btlX16tXVvn17U6FedmD7Ow4MDDQtR0VF6ddff3X6eK1bt1aTJk3k7e2toUOHGuvv3LmjqVOnmtqmdY5L7r5t+vTpat++vapXr64WLVrol19+MbZ5eHioatWqdjMvudL/JmXefZNt/13Svsy4uDht2rTJWM6RI4fq1q1rLNtOd71kyRLT8pUrV0z/976+vuky2jyA9Jf9St+RrSV96ywuLk43b97UiRMntHjxYtPIQ4GBgerVq5dpX19fXxUsWFBhYWGSEkbc+Pjjj/X888/LYrHoxx9/tHubzxEfHx+jECE8PFzr16+Xn5+f8uTJk+x0XlnJqVOnNHv2bNO6smXLqmPHjnZv9SVK+nb9448/bnr756233tK4cePk7e2tiRMnmqZN69ChQ5rF/cQTT2jatGlGR/uXX36p2NhYBQcHKzw8XJ988onpzaEGDRowtSUASeSOtJBdc0fdunXl5uam+Ph4SQmjgwUEBKhSpUrau3evJk+ebLT19fVV165d0+zcALKn5K5pjjgagapx48YqVKiQ8UZt0s7IpIWHiby8vGSxWIzrYEhIiD788EO1bdtWERERWrx4sd2UvCkVnrjK399f169fN94uTpw6pV+/fipZsqSioqL0+++/65tvvjHt58oIgR9++KGuXLliWjd48GBFR0c7/H0HBAQYbz9XrlxZpUqVMjo09+/frw8//FDt2rVTSEiI6eWiQoUKmTon08qlS5dMDwkqVaqU5ucAkD2EhobajargSGJ+6Nq1q+kaPmnSJIWHh6t58+a6c+eOPv74Y2Pqq0uXLqlOnTp2ecUZ5cqVU82aNbVv3z5JCdO29ezZU0OGDFHRokV17NgxTZkyxbSPo5yUWnnz5lXz5s2Nh2O3bt1St27d9MILL6hs2bI6evSoJk6cKCnhwempU6dc6q/ZuXOnMZVZooYNG6pu3brJ5u2kx3/88cdNn//ll1/WqFGjdPv2bb377rum/dLyXiSppCN/+Pv78zAMQJqyWCx6++231aFDB+NewWq16p133tGKFSuMwrscOXIYowKGhoZq9OjRevrpp3Xr1i2tXr1aq1atMh036X1H06ZNlT9/fl26dEmS9Mcff+iZZ55R//79lT9/fv30009GIcutW7d0+vTpu04pmdQXX3xhN31jr1695Ofn5/Ba7+PjoyJFikhKGEG+QYMG2r59u6SEkRvHjBmjnj176s8//9RXX31l7Ofr66uWLVs6HVdKJkyYkOL0xp999pmmTZtmLG/cuNFudCwAaady5crKkSOHw+/rtoVPklSwYEGVLl3a4TXGtpjPthj7hRde0MiRI+Xn56etW7earjOSTLNYSFKnTp00adIkY/mNN97QxYsX1bhxY4WHh2vWrFnGd3lHKlWqpEqVKhlFYxcvXlTXrl01dOhQBQUF6bffftOcOXMkJVy7//rrL5euwVmB7e94zpw5yp8/v6pUqaK///5bs2fPNs1AJaXcP5Z09MAuXbpo7ty5Rt/S999/r2effdZ44Se9c1yi3Llz68SJE8bymDFjdP78edWuXVteXl46ffq03TMYV0bbzcz7ptatW2vKlCnG/8ncuXNVokQJlS1bVosWLTL6HSWpRYsWptmjgoODTS/iLVq0SG5ubmrTpo2uXLmijz/+2FRMGxwcnKrR8AFkPooLkaGcGVHIzc1NH330kfLnz2+3rUWLFvr666+N5RkzZuiLL76QJKPwIOkXCEeCgoL0xx9/SEp4WJj4xsOLL76YLQpEvvzyS7s3Lv7880+1a9cu2X2S3vi2a9dOCxcuNN66PnfunPr162e3T9myZdWlS5c0i7to0aI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      "text/plain": [
       "<Figure size 3000x400 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "models = [\"DDM2v2a2Weibull2ter\",\"OUM2v2k2ter\"] \n",
    "labels = [\"CBM\",\"Self-excitation OUM\"] \n",
    "sortby = \"OUM2v2k2ter\"\n",
    "plot_all_datasets_flat(models, labels, sortby = \"OUM2v2k2ter\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "5e422e07",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "markdown",
   "id": "2453cc2a",
   "metadata": {},
   "source": [
    "## Supplementary materials"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "4246c6ad",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3000x400 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "models = [\"DDM2a2ter\",\"OUM2k2ter\"] \n",
    "labels = [\"DDM2a2ter\",\"OUM2k2ter\"] \n",
    "plot_all_datasets_flat(models, labels, sortby = \"OUM2k2ter\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "7e558f64",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3000x400 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "models = [\"OUM2v2a2k2ter\",\"OUM2v2k2ter\",\"OUM2k2ter\"] \n",
    "labels = [\"Full OUM\",\"Self-excitation OUM\",\"OUM2k2ter\"] \n",
    "plot_all_datasets_flat(models, labels, sortby = \"OUM2k2ter\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "656e6aba",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3000x400 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "models = [\"OUM2v2a2k2ter\",\"OUM2v2k2ter\"] \n",
    "labels = [\"Full OUM\",\"Self-excitation OUM\"] \n",
    "plot_all_datasets_flat(models, labels, sortby = \"OUM2v2k2ter\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "618d608c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3000x400 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "models = [\"OUM2v2k2ter\",\"OUM2k2ter\"] \n",
    "labels = [\"OUM2v2k2ter\",\"OUM2k2ter\"] \n",
    "plot_all_datasets_flat(models, labels, sortby = \"OUM2v2k2ter\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "6ac8ad23",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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apOrVq0tSgeTo8ssv19ixY/X888+rTp06lsnToUOH1LdvXx05ckSffPKJOnTooPHjx6tKlSoF2pYpU0ZVqlRRmTJlVL9+fUlSjRo1CrSrUKGCRowYoa+//lqvvfaaDhw4oObNm6t69erq0aOHv92f//xnDRs2TJmZmTrnnHOUnJysypUrq2rVqgH9XXjhhRoxYoRatGihpUuXqm7dulqxYoXOOeecAud2ejH41VdfBf15SCoQ8CJVyOZ1EZsUuQvElJQUTZs2TZUqVfI/lpaWpn79+gX8Xtq3b6+DBw/q3HPPDfgZ+Xw+ff755/7Hli9frunTp0uSRo8erSeffFLPP/+8jDEBryM5OVkff/yxDh48qJ49e2rFihWKjY1Vr169An4nn376qY4ePaqWLVtKOpOg7tu3z/LnI525EHj77bdVoUIFZWZm6o477gj4vWzbtk3PPvus+vTpo6lTp+qcc85RTk6OunfvHvB7qVevnnr37q377rtP11xzjbp166a6desWOF9KSoo++ugjpaenq1u3bvriiy8UFxenXr16BbSbPHmypk2bprJly+ro0aN6+umn9cYbb+if//ynpk2bFtB29uzZeu+99xQXF+d/7PTp0+rVq1dAceHDDz+sffv2qUaNGgE/Y5/PF/Ae+Omnn/znmDZtmu6//37997//LfB7gXtOY4kVpzHGitPYY8VpTLLiJlZZcRrDrDiNbVacxjwrbmKhlXAXTN3EzmCcxlM7TmOtFTfF5ME4jc1W3MTsYJzGcTtOY7wVN0Xs+TnNB+CcVXzYv3+/5bx/8cUXW87pdvO13Vx84MAByznWbv60mxtjYmJs5z27OS1vLpnfunXrSkRhVGEK6Y4eParp06cHfY+9/PLLlnn2+eefb5lb2+XTlSpVCplDB8uZc3JyLPNku9zYLh/+4YcfLHPgnJwcy5x3zpw5lnluVlaWZW47Y8YMffrppzpy5Ii6du2q5cuXS5L69OkjY4y2bt2qXr16yRijsmXLBizYStLSpUs1depU/8+yT58+8vl86tq1q/r27au3335bPp9PvXr1Uvfu3XXFFVfo6aef1gsvvKC4uDjddtttat68uSpUqKBZs2Zp3rx5OnnypDp37qwlS5ZIkvr27avZs2frnXfekc/n06lTp/TQQw9p4sSJ/nFazcml4e8F9uyuL6ZNmxby2sHJ9YGTa4BQeb6THD5Unu4kD3eSazvJpZ3ky6FyYif5bqic1osiOCl07ukkrwyVO4bKD52sEzlZIwq1PuRmXchuPSjUWpCTeSvU+o+TdR8n6z2h1nqcrPHYxcNcBw4cCBkXpeCxMfdvPjU11TJG5rKLlZJs4yWccbI25eUeh5f7G5HY1/B6T8PpmowXBde5vNzHiMQH8Z2sX3i5bxHJPQsv9ioitU/hRczK5VXskpzHLxReuHse+YW7B5JfuHsi+YW7R5KfF3smeYW7fxJMuHsq+YW7x5KfF3su+Xn94fpw92Ty82KPJq9w92vyC3f/Jr9w93PyC3d/B4BzZ2VxYdu2bbVhwwYdPnxY7du3t2w3atQoffjhh/4k9/LLL9fkyZP1n//8J6DdhRdeqFGjRunRRx9VSkqKJOndd98NuPjJVa5cOT333HOaMWOGcnJygp73008/VVpamn788Ud/H1WqVNHgwYMLtL3hhhv04IMPqk6dOho0aJBatGihFStW+D8RkSv3NTRu3FiNGzfWkSNHtH79ev38888B7V5++WUtW7ZM8fHxqlixot566y35fL4Cn0gZNWqUZsyYoSVLlqh27dq67bbb9O2332rs2LEFxuj0YnDq1Kn6/vvv1axZswJ95A/GkS5k86qITYrcBWJ2drbKlAmcAmJiYhQTExPw2HvvvacBAwZo0qRJOu+88yx/JsYY5eTkKCYmRo888oieeOIJvfrqqwWS8ZycHJUtW1bx8fF6+OGHFRsbq5ycnAKf3HnjjTeUnJysEydO6KGHHrJNeo4ePaq9e/fq/PPPD/gbOH36dIHX99tvv6lGjRo6cOCAqlevrt9//71Afz6fT9ddd50+/PBDLVq0SMnJydq+fbvOPfdcvf/++wE/w9jYWPl8PmVnZys7O9u/6ZnX8ePHlZ2d7f/3gQMHVLFiRZ08ebLAubOzs3XkyJGAb1c5fPhwgU/QvPnmm+rbt69Gjhypiy66KOjPJbe/tLQ0VapUSbfffrsOHjyo4cOHW84/cM5pLLHiNMZYcRN7rDiJSVbcxCorTmOYFaexzYrTmGfFTSy0Em5hl5vYGYzTeGrHaay1Uphi8mBCxWYrbmJ2MF4UUTiN8VbcFLHn5zQfgHNW8WHixImW8356errtnG41X9vNxRMnTrScY7///ntJwedPu7kxLi7Odt6zm9MuueQSy/lq586dJaIwqjCFdNdff73le8wuz+7evbtlbm2XT9vl0F26dLHMmcuWLWuZJ9vlxnb58IkTJyxz4NjYWMuc1y7P7dGjh2Vua4zRsWPHVKVKFT333HOSznwa+tSpU3r22Wc1e/ZsrVmzRk8++aRmzpzp35BISUnRmjVrdN555yk1NVUXXHCBjh07plOnTqlixYravHmzGjRooG+++UYJCQn69ttvFRMTI5/Pp5o1a2rSpEn6/vvvNWfOHE2YMEFpaWmqXLmyDhw4oMOHDystLU2pqakqV66cTp06pczMTB08eFAXXHCB/vjjDx0/flwxMTE6deqUYmNjQ/69TJ48uUCxbjh/LxMmTFBGRobl38sFF1zg2d9L3mspFGR3fZGQkBDy2sHp9UGoa4BQeb6THD5Unu4kD3eSazvJpZ3ky6FyYif5rtOcNpwiOCl07ukkrwyVO4bKD52sEzlZIwq1PuRkXcjJelCotSAn81ao9R8n6z5O1ntCrfU4WeOxi4e57OJi7vitYmOu2NhYyxiZ92drFSsXLlyo7Oxsy3gJZ5ysTXm9x+HV/kYk9jW83tNwuibjRcF13p+tV/sYkfggvpP1Cy/3LSKxZ+HlXkWk9im8iFl5+/Iidkmh4xfCF+6eR37h7oHk58WeSH7h7JHk58WeSV7h7p8EE+6eSn7h7rHk58WeS35ef7g+3D2Z/LzYo8kr3P2a/Lzav8mvsPs5+YW7vwPABS/urXy2y8zMNB9//HHAY9OnTzfHjh0rlvOvXr3ajB492gwfPty89NJL5vPPPy/QZvbs2cUylmC6detmTpw4EfBYenq66datW8Bj2dnZpnfv3mb79u0h+/zHP/5hsrOz/f8eNmyYGTdunOnbt2+Bc58+fdoYY8yMGTP857ntttsK9JmcnGxeeuklk5mZafr06RP0vLfeeqvZs2ePeeCBB0xaWpoxxpjTp08XeC29evUyv/76q3nqqafMnj17jDHG/PLLLwXaGWP8Y87Ozjbz5883gwcPNu3btzc9evQIaJeYmGgyMjLM77//bv7617+aEydOmMzMzAKvpUuXLiYjI8MYY8yRI0fM7bff7n9+XgsXLjSdOnUySUlJZujQoSYpKcncfPPNZtGiRQXGuHr1arNmzZqgP5NcH3zwgenUqZNJTU01xpx5XwwZMsTUq1cvoN3s2bNNx44dTU5Ojv+xu+66y0yZMiVov6tWrTL33Xdf0J9druTkZJOUlGT+9re/meTkZHP8+HHzt7/9zf87z7Vp0yaTmJhoBgwYYBISEkxiYqJp27atWbVqVUA7q9//oUOHAv49a9Ysc9NNN5kBAwaY559/3nTu3Nl0797dvPvuuwHtPvzwQ9OuXTszZMgQ07FjR7No0SIzYcIE8+qrrxY4x/r1601iYqJJTEw0ffr08f//hg0bCrTdvHmz+eabbyx/LsYY88UXX5h27dqZgwcP+h8bPXp0gd8LSp5Ixx6vOIlhViIZ27ziNEZacRM7g3EaT+24ibVWnMRgK05jsxU3MTsYp3HcjtMYb8Vp7A/GTT6AolNUc7rVHFtU86fdnGY3X9nNRaHmGKv5w25usHvf272n7d6rVu/DNm3a2L7HrPJsu9zaST4dLIe2y5nt8mS73NguH7bLgUPlvFZ5rl1uu2LFCtO5c+eAv6U+ffqYuXPn+v+9bds2889//tN07drV/9js2bPNCy+8YPr06WMmTZpkjh8/blq1amWWLFlidu3aZe644w6TmJho6tSpY5o2bWoSExPN5s2bzR133BH052KMMcuXLzeJiYlm6NChZvLkyaZly5amQ4cOZuHChWbp0qWmTZs2pnv37qZDhw7m66+/NsnJyea9994zCxYsMB07dvT/vdx///2u/l5yr1eC/b3k/bk4+XsZP368GTx4sGnbtq1JTk42aWlp/r+XjRs3msTERHP33XcH/L2sXLnS8bUUvFec1wehcvjiytOd5NJO8uVQObHTfNcup3WSszrJS0Plnk7yylC5o5P8MNQ6kZM1IqfrQ3brQk7Wg0KtBTmZt0Kt/zhZ93G63mO31uNkjcdJPMwVLC4aYx8bc9nFyFx2sdIY+3iJ4heJdaZo3tfwKsYY42ztJRL7GE7XQ7zcv3CyfuHlvkUk9iy83KuI1D6FFzErl9exyxjr+IXSr7TsibgRzv5JMKVhT8WtcPdg8gt3TyY/L/Zo8vJivya/cPZv8gt3Pye/cPd3ADhHcSGKXP4NEruLwf379zsKxnabJ3k52UjJK1QhW3JycsAGi9WFod1mS35uLhBvvPHGAheI77zzTkA7qwvEcePGBbTbtGmT6d69u7n22mvN+PHjzZYtW8ypU6fMgw8+WKBdjx49TJ8+fQIu1IO169q1q+ndu3dAuzvvvDNou7z9HTp0yPa8c+bMMW+//XbQ8+Zvu3r16pB9tmjRwowfP95s37496Gv+6quvHL/mvOfdsmWL2bdvX9B2HTp0MA0bNvQvkAY7rzHGHD582IwcOdIkJyebdevWmVatWpmOHTua9evXB22XkpJitmzZYtq3b286depUoF1qaqqjdgAiw02MtOI0dgbjNJ7acRtrrTgpJg/GaWy24iZmB+NFEYXTGG/FaewPxmk+ADgRak6zmq+KojDKbm4obGGU3XvV6n04bNgwy/eYXZ5tl1vb5dN2ObRdzmyXJ9vlxnb5sF0ObJfz2uW5drltsOfl7XPUqFEmJSXFbN682bRr1y5on5s3by7wvJEjR5r//ve/Zt26daZdu3b+Y1Zj+frrrwscC/a85ORk//ny5ueZmZlm69atZv369aZfv34mMzMz6N/kP//5z4B/Hz9+3L8Zmnssd/Pv1KlTAc/L3VzN67fffjN16tQJeq6cnJwCz8vJyTG7du0qMM78fecfJ+Alp7l0qHw5VE7sJt+1ymmd5KxO8tJQuaeTvDJU7hgqP3SyTuRkjSjU+pCTdSEn60Gh1oKcrAGFWv9xsu7jZL0n1FqPkzUeu3iYt41VXMx/nvyxMf95gsXIXHaxMtjxYH0AkeJVjDHG2dpLJPYxnK6HeLl/4WT9wst9i0jsWXi5VxGpfQovYlYur2JXbju7+AUAwXixB5NfOHsy+XmxR5OXV/s1+RV2/ya/cPdz8gt3fweAcxQXolhkZmaaLVu2mPXr15utW7f6K+bzGjp0qOV/weTdPMkV7Nvd8m6kGBN6s/+3334zU6dODfWSQvaXk5Njdu7cadavX2+2b98e9DU7GY+VLVu2mP379wc9lpqaar755htz5MgRY4wJuiHVo0cPs2vXLrNt2zaTmJholi5daowpuFjQo0cPs3PnTkftgvWX/5MVXp/XbZ/F8ZoL284YYwYMGGBmzpxpJkyYYJo3b2727NljDhw4YHr37l3odrNmzfK3+/nnn4O2AxA5TmKkFbexMxin8dSO21hrxW0MtuL2/E5jthfncsIuxltxEvuDcROjACes5rRQ85XdXORkjnEyf+R9ntX73s17Ov97Ndj70O49Zpdz2uXWXvfp5JjXfdrlsqGOWeW24fTpxTE3Y8n7GvIeu+aaa0zz5s1N69atTatWrUzDhg1N69atTevWrQsca9CggWnVqpXlMbvned2n03ECRSFULu00Xw6VE7vJd53mtMH6CJWXus09rfJKu9wxVH7oZM3EyRpRUZ7HTRsvzuNkHE7WcUK1cbLG49V5wu0jWJv843W6tgVEilcxxhhnay+R2Mdwsh7i9f5FqPULL9fwI7Fn4eWeQaT2KbyKA7ntvIhdbtoBQH7h7MHk58WeTH5e7NHk5dV+TX5e7d/kF+74wtnfAeBcmUjflhml37BhwyyPvfjii/7/b9OmjcaMGaOnn346rD4bNWrk+tzB2uU+Fqqd0/6CtZOkl156ydM+nbaLi4vTZZddJkmaOHGi+vfvrypVqsjn8wU8Jy4uTpdffrmjdsH6y6+w573zzjuDtnPbZ3G85sK2k6SMjAwlJiZKkjZt2qTq1atLUoG2btp17drV3+7SSy8N2g5AZLiJF8G4iZ1uz583nha2DyevwWkMLs7zu3m+0zhelGMI5/luYhQQit3fot18Zfe8GTNmeDaGSNi7d6/le8wu57TLre3et3Y5dKjneTnOUMfsctlQx6xy23D69OKYm7HkfQ15j3344YcaNWqUkpKSVK9ePfXt21dTp06VJO3atavEHwO85iQHcpIvh8qJnZwnVE5b2D7ytwmVe3pxnlD5oZM1EydrRG7PE2xdyEkuW5SvJ28focbhZB0nVBsnazxenSfcPoK1yT9ep2tbQCR4FWNC9ZW79hKJfQyn5/Ry/8JJGy/X8COxZ+HlnkGk9im8igO57byIXW7aAUBe4a695xfunkx+XuzROO2vMK833P0bJ/3liob+AFijuBBFrk2bNho9erSeeeYZ23Zt27bVhg0bdPjwYbVv396TPt20c5IIeH3eSJ67atWqeu211zRgwABVqVJF48aN06BBg3TixImobPfKK68EbRdNYwy3nSRdeOGFGjVqlB599FGlpKRIkt59911VqlSpSNsBiAw38SIYN7GzKM7vRR/hXox7cf5Ijt+rMRT2+W5iFBCK3d9i06ZNLeerY8eOWT4v1DGr91+09Ll//37L91hCQkKRH8ubQxfH+Zwea9y4sWWOWqFChbP22OWXX66xY8fq+eefV506dQI2yUrDMcBrTnIgJ/lyqH6cnCdUTui0j2g4T6j80En+6EUbJ+tCRXGeourDyfpMqDZe9FHSzgNEilcxxmlfkdjHiNZzernmHok9i5I0fqt2XsWBSPQFAPl5sQeSV7h7Mvl5Pb6i6M/LYspof70AbET6qxNxdhg5cqSZP39+RPqM9naROvepU6fMu+++a9LT0/2P/fLLL+app54qUe1KwhjdvJbMzEzz8ccfBzw2ffp0c+zYsSJtByByiiJGFvf5w+3jbH9+JMfgJkYBThT2b9HueSX5mN177Gw+Zpejns3H8j9mdXuv0nAM8IpXuXSofpycpzj6KI7zhMoPneSPXrQpSedx0oeT+T9UGy/6KGnnASLJy/Uar2KA1+2i8ZxerrlHYp0/Wvty086rOBCJvgAgmEjvwYTi9fjoD0BR8BljTKQLHAEAAAAAAAAAAAAAAAAAQPSIifQAAAAAAAAAAAAAAAAAAABAdKG4EAAAAAAAAAAAAAAAAAAABKC4EAAAAAAAAAAAAAAAAAAABKC4ECXGzJkzVbt27QL/1a1bV40aNVLHjh31wgsv6ODBg0Vy/pycHM2YMUO///57gTGNHTvWdX9r165V7dq19eijj3o5TE/t3btXs2bNivQwAKDQiB3Fj9gBAAAAAAAAAIA32OcofuxzAEAgigtR4tSpU0dJSUn+/+677z717NlTlSpV0ltvvaXbbrtNf/zxh+fnfeSRR/TUU0/p5MmT/sfq1q2rpKQk/fWvf3Xd38UXX6ykpCS1a9fOy2F6ZsuWLerUqZNWrlwZ6aEAQNiIHcWD2AGgpGOxtvixWAugpCN2FD9iB4CSjLhR/IgbAEoL9jmKB/scAFBQmUgPAHCrbt26uv/++4Mee+yxx/Txxx/rtdde07PPPuvpeYNdzNetW1d169YtVH+XXHKJ5euIBkePHtXp06cjPQwA8ASxo3gQOwCUFnXq1FHbtm39/zbG6MSJE1q/fr3eeustLVy4UB988IEuuOACT8/7yCOPaN68eVq4cKH/sdzF2iZNmrjuL3extnbt2l4O0zNbtmzRP/7xD7Vv316JiYmRHg4AhIXYUTyIHQBKC+JG8SBuAChN2OcoHuxzAEBBFBeiVBk4cKA+/vhjffHFF5EeCgCghCB2AADyY7G2eLBYC6A0IXYUD2IHgNKCuFE8iBsAzhbscwAAihK3RUap8pe//EWSdPjwYf9jP/zwgx599FHddNNNql+/vho1aqSuXbtq8uTJysnJ8bfbt2+fateurWeffVbjx4/Xtddeq2uuuUYPPvigateurXXr1kmS2rVrp9atW0uyvl1AWlqaXnnlFXXs2FENGzbUjTfeqCFDhmjHjh3+NsFuFzB06FDVrl1be/fu1QsvvKDmzZurUaNG6tGjhxYsWBD0NS9cuFB33323rrvuOtWrV0/XXnut+vXrpyVLlgS0yx3r/Pnz9dFHH6lr165q2LChmjVrpkceeUR79+4NGEe/fv0kSXPmzFHt2rU1c+ZMSVJGRoZGjx6tzp07KyEhQU2aNFHfvn01b948h78lAIguxA5iBwC4MXDgQElisRYA4BixAwDgBnEDAOAW+xzscwBAUeKbC1Gq7N69W5J04YUXSpJWrFihgQMHqnz58mrbtq3OP/98/fbbb1q8eLFGjhypgwcP6rHHHgvoY8GCBTp58qQSExN15MgRdejQQVdccYVmzZql/fv3q2/fvrrkkkssx3DkyBH17NlTu3btUr169dSzZ08dOnRI8+fP14oVKzRt2jRdeeWVtq9jyJAh2r17t2655RZlZWVp4cKFeuCBB/S///u/GjBggL/dq6++quTkZF166aXq1KmTypUrp+3bt2vZsmVau3atUlJSdNNNNwX0PXHiRG3evFlt2rRRixYttHbtWs2dO1fr16/XvHnzVLFiRf/tGGbNmqVatWqpXbt2/k8uDho0SKtXr9b111+vli1bKi0tTQsWLNCQIUN0/Phx9ejRw9HvCgCiBbGD2AEAblgt1k6ZMkXr16/XwYMHFRcXp/j4eN16663q37+/YmLOfK5v3759atOmjXr37q0qVarorbfeUnZ2tm644QbNnz/f31+7du108cUXa8mSJZo5c6aGDRumgQMHasiQIf42aWlpmjhxohYsWKD9+/frvPPO0zXXXKOkpCTVrFlT0pnF2n79+qlz5856+eWXJZ1ZJJ01a5YWL16sqVOnau7cuTpx4oRq1aqlu+66S+3bty/wmhcuXKjp06frxx9/1LFjx1ShQgXVrVtX/fv39y8qS/KPddy4cUpPT9fUqVO1c+dOlS9fXtdff70eeughVa9ePWAc0pnF2jlz5ujFF1/U3//+d2VkZOg///mPli5dqr1796pMmTKqW7euevXqpU6dOnnyewSA4kTsIHYAgBvEDeIGALjFPgf7HABQlCguRKmRlZWlV155RZLUoUMHSdLIkSMlSdOnT1eNGjX8bbdv365bbrlFs2bNKpA4HTx4UBMnTtQNN9zgf6xt27Zat26dP3GKj4+3HMeYMWO0a9cu3XXXXXrsscfk8/kkSR07dtTgwYM1duxYTZgwwfa17NmzRzNnztSll14qSbr33nvVvXt3vfLKK2rfvr2qV6+ugwcPKiUlRTVr1tRHH32k8uXL+5//3nvv6emnn9asWbMKJE5btmzRu+++q4SEBElSTk6O7rjjDq1bt06ff/65br31VrVt21aVK1fWrFmzVLt2bf9tDX766SetXr1at956q1566SV/nwMGDFDHjh01efJkEicAJQqxg9gBAG6xWMtiLQC4RewgdgCAG8QN4gYAuME+B/scAFDUKC5EibN582a99tpr/n8bY3T48GGtWrVKu3fv1pVXXqmBAwfKGKMHH3xQWVlZAUmTJF1xxRU6//zz9ccffxTo/3/+5390/fXXF2psp0+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      "text/plain": [
       "<Figure size 3000x400 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "models = [\"OUM2v2a2k2ter\",\"OUM2k2ter\"] \n",
    "labels = [\"Full OUM\",\"Self-excitation OUM\"] \n",
    "plot_all_datasets_flat(models, labels, sortby = \"OUM2k2ter\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "8835017c",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 3000x400 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "models = [\"DDM2v2a2c2ter\",\"OUM2v2k2ter\"] \n",
    "labels = [\"Linear CBM\",\"Full OUM\"] \n",
    "plot_all_datasets_flat(models, labels, sortby = \"OUM2v2k2ter\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "1c7f6f4d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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9zQ8//GCeffZZc/DgQWOMMd9//32BdsYY35izs7PNsmXLzJAhQ0yHDh1Mz54987WLj483GRkZ5scffzS//e1vzfnz501mZmaB59K1a1eTkZFhjDHm9OnT5r777vM9Pq8VK1aYzp07m6FDh5rhw4eboUOHmt///vdm5cqVBca4ceNGs2nTpoCvSa7//ve/pnPnziY1NdUY89PnYtiwYaZ+/fr52i1atMh06tTJ5OTk+LYNGDDAzJw5M2C/GzZsMA8//HDA1y5XYmKiGTp0qPnd735nEhMTzblz58zvfvc73988144dO0x8fLwZOHCgiY2NNfHx8aZdu3Zmw4YN+dpZ/f1PnjyZ79/Jycnm7rvvNgMHDjQvvvii6dKli+nRo4eZPXt2vnYLFiww7du3N8OGDTOdOnUyK1euNFOmTDGvvfZagWNs3brVxMfHm/j4eNO3b1/f/2/btq1A2507d5rPP//c8nUxxpiPP/7YtG/f3pw4ccK3bezYsQX+Lih7Qh17vOIkhlkJZWzzitMYacVN7AzEaTy14ybWWnESg604jc1W3MTsQJzGcTtOY7wVp7E/EDf5AIpPcZ3Trc6xxXX+tDun2Z2v7M5Fwc4xVucPu3OD3efe7jNt91m1+hzGxcXZfsas8my73NpJPh0oh7bLme3yZLvc2C4ftsuBg+W8VnmuXW67bt0606VLl3zvpb59+5olS5b4/r17927z5z//2XTr1s23bdGiReall14yffv2NdOnTzfnzp0zbdq0MatWrTL79+83999/v4mPjzd169Y1zZo1M/Hx8Wbnzp3m/vvvD/i6GGPM2rVrTXx8vBk+fLiZMWOGufPOO03Hjh3NihUrzOrVq01cXJzp0aOH6dixo/nss89MYmKieeedd8zy5ctNp06dfO+XRx55xNX7Jfd6JdD7Je/r4uT9MnnyZDNkyBDTrl07k5iYaNLS0nzvl+3bt5v4+Hjz4IMP5nu/rF+/3vG1FLxXktcHwXL4ksrTneTSTvLlYDmx03zXLqd1krM6yUuD5Z5O8spguaOT/DDYPJGTOSKn80N280JO5oOCzQU5OW8Fm/9xMu/jdL7Hbq7HyRyPk3iYK1BcNMY+Nuayi5G57GKlMfbxEiUvFPNMpbmu4VWMMcbZ3Eso6hhO50O8rF84mb/wsm4RipqFl7WKUNUpvIhZubyOXcZYxy+Ev3CpibhRlPpJIOFQU3GrqDUYf0WtyfjzokaTlxf1Gn9Fqd/4K2o9x19R6ztASWBRHoqdf2HB7iLqyJEjjoKYXdEhLycFiLyCLQBLTEzMV5iwuqCyK1L4c3NhdddddxW4sHr77bfztbO6sJo4cWK+djt27DA9evQwt99+u5k8ebJJSUkxFy9eNI8++miBdj179jR9+/bNd4EbqF23bt1Mnz598rV74IEHArbL29/Jkydtj7t48WLz1ltvBTyuf9uNGzcG7bNly5Zm8uTJZs+ePQGf86effur4Oec9bkpKijl8+HDAdh07djSNGjXyTSwGOq4xxpw6dcqMHj3aJCYmmi1btpg2bdqYTp06ma1btwZsl5SUZFJSUkyHDh1M586dC7RLTU111A5AaLiJkVacxs5AnMZTO25jrRUni7ADcRqbrbiJ2YF4sfjAaYy34jT2B+I0HwCcCHZOszpfFceCIrtzQ2EXFNl9Vq0+hyNGjLD8jNnl2Xa5tV0+bZdD2+XMdnmyXW5slw/b5cB2Oa9dnmuX2wZ6XN4+x4wZY5KSkszOnTtN+/btA/a5c+fOAo8bPXq0+c9//mO2bNli2rdv79tnNZbPPvuswL5Aj0tMTPQdL29+npmZaXbt2mW2bt1q+vXrZzIzMwO+J//85z/n+/e5c+d8RcTcfblFs4sXL+Z7XG5RMq+jR4+aunXrBjxWTk5Ogcfl5OSY/fv3Fxinf9/+4wS85DSXDpYvB8uJ3eS7Vjmtk5zVSV4aLPd0klcGyx2D5YdO5omczBEFmx9yMi/kZD4o2FyQkzmgYPM/TuZ9nMz3BJvrcTLHYxcP87axiov+x/GPjf7HCRQjc9nFykD7A/UBhIpXMcYYZ3MvoahjOJ0P8bJ+4WT+wsu6RShqFl7WKkJVp/AiZuXyKnbltrOLXwAQiBc1GH9Fqcn486JGk5dX9Rp/ha3f+CtqPcdfUes7QElgUR5KRGZmpklJSTFbt241u3bt8q3Qzmv48OGW/wWSt+iQK9DdxPIWIIwJXiQ/evSomTVrVrCnFLS/nJwcs2/fPrN161azZ8+egM/ZyXispKSkmCNHjgTcl5qaaj7//HNz+vRpY4wJWMjp2bOn2b9/v9m9e7eJj483q1evNsYUvMju2bOn2bdvn6N2gfrzX8nv9XHd9lkSz7mw7YwxZuDAgWbhwoVmypQppkWLFubgwYPm2LFjpk+fPoVul5yc7Gv33XffBWwHIHScxEgrbmNnIE7jqR23sdaK2xhsxe3xncZsL47lhF2Mt+Ik9gfiJkYBTlid04Kdr+zORU7OMU7OH3kfZ/W5d/OZ9v+sBvoc2n3G7HJOu9za6z6d7PO6T7tcNtg+q9y2KH16sc/NWPI+h7z7brvtNtOiRQvTtm1b06ZNG9OoUSPTtm1b07Zt2wL7GjZsaNq0aWO5z+5xXvfpdJxAcQiWSzvNl4PlxG7yXac5baA+guWlbnNPq7zSLncMlh86mTNxMkdUnMdx08aL4zgZh5N5nGBtnMzxeHWcovYRqI3/eJ3ObQGh4lWMMcbZ3Eso6hhO5kO8rl8Em7/wcg4/FDULL2sGoapTeBUHctt5EbvctAMAf0Wpwfjzoibjz4saTV5e1Wv8eVW/8VfU8RWlvgOUhHKh/vlchL8RI0ZY7sv7m/JxcXEaN26cnnvuuSL12bhxY9fHDtQud1uwdk77C9ROkl555RVP+3TaLjo6WjfffLMkadq0aerfv7+qVaumiIiIfI+Jjo7WLbfc4qhdoP78Ffa4DzzwQMB2bvssiedc2HaSlJGRofj4eEnSjh07VKNGDUkq0NZNu27duvna3XTTTQHbAQgNN/EiEDex0+3x88bTwvbh5Dk4jcEleXw3j3cax4tzDEV5vJsYBQRj9160O1/ZPW7+/PmejSEUDh06ZPkZs8s57XJru8+tXQ4d7HFejjPYPrtcNtg+q9y2KH16sc/NWPI+h7z7FixYoDFjxmjo0KGqX7++EhISNGvWLEnS/v37y/w+wGtOciAn+XKwnNjJcYLltIXtw79NsNzTi+MEyw+dzJk4mSNye5xA80JOctnifD55+wg2DifzOMHaOJnj8eo4Re0jUBv/8Tqd2wJCwasYE6yv3LmXUNQxnB7Ty/qFkzZezuGHombhZc0gVHUKr+JAbjsvYpebdgCQV1Hn3v0VtSbjz4sajdP+CvN8i1q/cdJfrtLQH1AcWJSHYhcXF6exY8fqX//6l227du3aadu2bTp16pQ6dOjgSZ9u2jkJoF4fN5THrl69uiZNmqSBAweqWrVqmjhxogYPHqzz58+XynYTJkwI2K40jbGo7STpuuuu05gxY/Tkk08qKSlJkjR79mxVqVKlWNsBCA038SIQN7GzOI7vRR9FvYj14vihHL9XYyjs493EKCAYu/dis2bNLM9XZ8+etXxcsH1Wn7/S0ueRI0csP2OxsbHFvi9vDl0Sx3O6r0mTJpY5aqVKlS7bfbfccovGjx+vF198UXXr1s1XXAqHfYDXnORATvLlYP04OU6wnNBpH6XhOMHyQyf5oxdtnMwLFcdxiqsPJ/Mzwdp40UdZOw4QKl7FGKd9haKOUVqP6eWceyhqFmVp/FbtvIoDoegLAPx5UQPJq6g1GX9ej684+vNyEWJpf75AsQj1rfpweRg9erRZtmxZSPos7e1CdeyLFy+a2bNnm/T0dN+277//3jz77LNlql1ZGKOb55KZmWnee++9fNvmzZtnzp49W6ztAIROccTIkj5+Ufu43B8fyjG4iVGAE4V9L9o9rizvs/uMXc777HLUy3mf/zarn2EKh32AV7zKpYP14+Q4JdFHSRwnWH7oJH/0ok1ZOo6TPpyc/4O18aKPsnYcIJS8nK/xKgZ43a40HtPLOfdQzPOX1r7ctPMqDoSiLwAIJNQ1mGC8Hh/9AaVLhDHGhHphIAAAAAAAAAAAAAAAAAAA4SAy1AMAAAAAAAAAAAAAAAAAACBcsCgPAAAAAAAAAAAAAAAAAACPsCgPAAAAAAAAAAAAAAAAAACPsCgPZcbChQtVp06dAv/Vq1dPjRs3VqdOnfTSSy/pxIkTxXL8nJwczZ8/Xz/++GOBMY0fP951f5s3b1adOnX05JNPejlMTx06dEjJycmhHgYAFBqxo+QROwAAAAAAAAAA8AZ1jpJHnQOAV1iUhzKnbt26Gjp0qO+/hx9+WL169VKVKlX05ptv6t5779Xx48c9P+4TTzyhZ599VhcuXPBtq1evnoYOHarf/va3rvu74YYbNHToULVv397LYXomJSVFnTt31vr160M9FAAoMmJHySB2ACjrmOQseUxyAijriB0lj9gBoCwjbpQ84gaAcEGdo2RQ5wDgpXKhHgDgVr169fTII48E3PfUU0/pvffe06RJk/T88897etxAF8H16tVTvXr1CtXfjTfeaPk8SoMzZ87o0qVLoR4GAHiC2FEyiB0AwkXdunXVrl0737+NMTp//ry2bt2qN998UytWrNB///tfXXPNNZ4e94knntDSpUu1YsUK37bcSc6mTZu67i93krNOnTpeDtMzKSkp+tOf/qQOHTooPj4+1MMBgCIhdpQMYgeAcEHcKBnEDQDhhDpHyaDOAcBLLMpDWBk0aJDee+89ffzxx6EeCgCgjCB2AAD8MclZMpjkBBBOiB0lg9gBIFwQN0oGcQPA5YI6BwCUTvx8LcLKL3/5S0nSqVOnfNu+/vprPfnkk7r77rvVoEEDNW7cWN26ddOMGTOUk5Pja3f48GHVqVNHzz//vCZPnqzbb79dt912mx599FHVqVNHW7ZskSS1b99ebdu2lWR9W/e0tDRNmDBBnTp1UqNGjXTXXXdp2LBh2rt3r69NoNu6Dx8+XHXq1NGhQ4f00ksvqUWLFmrcuLF69uyp5cuXB3zOK1as0IMPPqg77rhD9evX1+23365+/fpp1apV+drljnXZsmV699131a1bNzVq1EjNmzfXE088oUOHDuUbR79+/SRJixcvVp06dbRw4UJJUkZGhsaOHasuXbooNjZWTZs2VUJCgpYuXerwrwQApQuxg9gBAG4MGjRIkpjkBAA4RuwAALhB3AAAuEWdgzoHgNKJO+UhrBw4cECSdN1110mS1q1bp0GDBqlixYpq166drr76ah09elQffvihRo8erRMnTuipp57K18fy5ct14cIFxcfH6/Tp0+rYsaNuvfVWJScn68iRI0pISNCNN95oOYbTp0+rV69e2r9/v+rXr69evXrp5MmTWrZsmdatW6c5c+boV7/6le3zGDZsmA4cOKA//OEPysrK0ooVK/TXv/5Vf/vb3zRw4EBfu9dee02JiYm66aab1LlzZ1WoUEF79uzRmjVrtHnzZiUlJenuu+/O1/e0adO0c+dOxcXFqWXLltq8ebOWLFmirVu3aunSpapcubLvtvnJycmqXbu22rdv7/um3ODBg7Vx40a1atVKd955p9LS0rR8+XINGzZM586dU8+ePR39rQCgtCB2EDsAwA2rSc6ZM2dq69atOnHihKKjoxUTE6N77rlH/fv3V2TkT9+HO3z4sOLi4tSnTx9Vq1ZNb775prKzs9W6dWstW7bM11/79u11ww03aNWqVVq4cKFGjBihQYMGadiwYb42aWlpmjZtmpYvX64jR47oqquu0m233aahQ4eqVq1akn6a5OzXr5+6dOmiV199VdJPk4vJycn68MMPNWvWLC1ZskTnz59X7dq1NWDAAHXo0KHAc16xYoXmzZunb775RmfPnlWlSpVUr1499e/f3zcZK8k31okTJyo9PV2zZs3Svn37VLFiRbVq1UqPPfaYatSokW8c0k+TnIsXL9bLL7+sP/7xj8rIyNC///1vrV69WocOHVK5cuVUr1499e7dW507d/bk7wgAJYnYQewAADeIG8QNAHCLOgd1DgClE4vyEDaysrI0YcIESVLHjh0lSaNHj5YkzZs3TzVr1vS13bNnj/7whz8oOTm5QMJx4sQJTZs2Ta1bt/Zta9eunbZs2eJLOGJiYizHMW7cOO3fv18DBgzQU089pYiICElSp06dNGTIEI0fP15TpkyxfS4HDx7UwoULddNNN0mSHnroIfXo0UMTJkxQhw4dVKNGDZ04cUJJSUmqVauW3n33XVWsWNH3+HfeeUfPPfeckpOTCyQcKSkpmj17tmJjYyVJOTk5uv/++7VlyxZ99NFHuueee9SuXTtVrVpVycnJqlOnju/2899++602btyoe+65R6+88oqvz4EDB6pTp06aMWMGCQeAMoXYQewAALeY5GSSEwDcInYQOwDADeIGcQMA3KDOQZ0DQOnFojyUOTt37tSkSZN8/zbG6NSpU9qwYYMOHDigX/3qVxo0aJCMMXr00UeVlZWVL9mQpFtvvVVXX321jh8/XqD/n/3sZ2rVqlWhxnbp0iW9//77uuqqq/T444/7kg3pp6Rl6NChuvbaa4P2M2DAAF+yIUk1atTQgAED9Oqrr2rJkiV6+OGHVa5cOY0ZM0bXX399vmRDkpo3by5JSk1NLdB3y5YtfcmGJEVGRiouLk5btmzR4cOHbceVeyvjffv2KTU1VdWqVfON74MPPtA111wT9LkBQCgQO4gdAOAFJjmZ5AQAt4gdxA4AcIO4QdwAACvUOahzACh7WJSHMiclJUUpKSm+f0dGRqpy5cqKiYnRI488ov79+6tKlSqS5Psm1PHjx7V7924dOnRIBw4c0JdffqmTJ09KkrKzsxUVFeXr78Ybb8yXKLhx6NAhpaWl6c4771R0dHSB/bkXfcHccccdBbblJgnffPONJOnKK6/U73//e0k/fXNu7969Onz4sPbu3avPPvtM0k/PzZ9/8iVJVatWlfRTwmSnTp06atq0qbZu3ao777xTTZo0UcuWLdW6dWvfN8wAoDQidhA7AMANJjmZ5AQAt4gdxA4AcIO4QdwAALeoc1DnAFD2sCgPZU58fLxGjRrlqO3evXs1evRorV27VsYYSdINN9ygpk2b6ttvv9WZM2d823NVqFCh0GM7ffq0pP8fwAsr97b0eeVeCJ49e9a3bfXq1Ro3bpx27dolSYqKilKtWrVUv3597dmzp8Bzk6Ty5csX2JabYAVq72/atGmaOXOmlixZok2bNmnTpk0aO3asbr75Zj399NO66667nD1JAChBxA5iBwC4wSQnk5wA4Baxg9gBAG4QN4gbAOAWdQ7qHADKHhblIWxlZGSof//+OnnypB566CHFxcWpZs2avgvZli1ben7MypUrS5LOnTtnOaZKlSoF7efChQsFtuUmGrnf2vryyy81ePBgVa1aVS+88IIaN26smJgYlS9fXnv37tV7771X2Kdhq2LFiho8eLAGDx6so0ePatOmTfrwww+1cuVKDRkyRMuWLdONN95YLMcGgOJG7CB2AIDEJCeTnADgHrGD2AEAbhA3iBsAUFyoc1DnAFB6sCgPYWvDhg06duyYevbsqWHDhuXbl5qa6rvluZMLNKdq1qyp8uXL6+uvvy7wzTRJ6tu3rw4ePKg1a9bY9vP5558rJiYm37Zt27ZJkn7zm99IkhYvXqzs7Gw9++yz+sMf/pCv7Z49eyQV7bkF+hbdjh07tGzZMnXs2FGxsbG67rrr1K1bN3Xr1k0jRozQwoULtX37dhIOAGUWsYPYAQBuMMnJJCcAuEXsIHYAgBvEDeIGALhFnYM6B4DSIzLUAwCKS+43wb7//vt82y9evKhnn31WOTk5kqSsrCxH/eXepj0zM9OyTfny5dW5c2edPHlSiYmJ+fatXr1a33zzjWJjY30XtVamTJmiEydO+P793Xffadq0aapcubLvVu5Wz++HH37QuHHjXD23QMqV+2nNbt7nm5aWppkzZ2rSpEm+10/6KbE5cuSIJKlGjRqFPiYAhBqxg9gBAG7kTnLee++9GjZsmBo1auQrjpXUJKe/vn37qmnTpkpPT7ft5/PPPy+wzW6Ss0ePHvrVr37luyNFcU5yjho1Sjt27JAk3yTn5MmT9cc//lGZmZnavn17oY8JAKFG7CB2AIAbxA3iBgC4RZ2DOgeA0oM75SFsNWnSRDfffLM++eQT9enTR40bN9bZs2e1Zs0aHT9+XFdddZVOnTql06dPq2LFikH7u/766yVJzz//vJo1a6ahQ4cGbPf3v/9d27dvV2JiojZs2KDGjRvrhx9+0IoVK/Tzn/9czz33XNBjnThxQl27dlVcXJwyMzO1YsUKnT9/Xi+//LLv9u6///3vNXPmTE2YMEFff/21brrpJn3//fdatWqVypUrp+joaN9t5gsj9/muXbtWo0ePVlxcnFq0aKG7775bq1evVpcuXdSiRQtFRUVp06ZN2rlzpzp06KDY2NhCHxMAQo3YQewAADfcTHLmTmDacTPJuWjRIiUmJuqvf/2rb1/uJGerVq0cTXK2aNFCV199taTSN8n57bff6vXXX1dk5E/fJWSSE0C4IHYQOwDADeIGcQMA3KLOQZ0DQOnBojyErYoVK2rGjBkaN26cPv30U3355Zf6xS9+oYYNG+rBBx/Uxo0bNXHiRH388ce67777gvY3aNAg7d27V9u3b9euXbvUv3//gO2qVaum+fPnKykpSStWrNCsWbNUpUoVderUSY8++qij29a+8MILWr9+vZYvX67s7GzFxsZq0KBBuv32231t6tSpo5kzZ+q1117Tpk2btHbtWl1//fW655579PDDD2v48OHauHGj9u7dq1q1ajl+3XJdf/31euKJJ/TGG2/o7bffVsWKFdW0aVNNmDBBb7/9thYvXqzk5GRlZWXplltu0YgRI9SnTx/XxwGA0oTYQewAADeY5GSSEwDcInYQOwDADeIGcQMA3KLOQZ0DQCliAJQaf//7303t2rXN+vXrQz0UAEAZQewAAO+8++67pnbt2ubvf/+748ccPnzYPP7446Z169amYcOGJi4uzgwZMsRs27bNJCYmmtq1a5vZs2cbY4w5dOiQqV27tunVq1fAvg4ePGh69uxpGjRoYJo1a2bOnTvnG9O4cePytT116pQZNWqUadu2ralfv75p3ry5efzxx813333na7Np0yZTu3Zt88QTT/i25caNpUuXmpEjR5pmzZqZJk2amAEDBpgtW7YUGNOnn35qEhISTLNmzUxsbKzp1KmT+cc//mF++OEHc//995vatWubPXv25Hv9/Mdqty8pKcnccccdpkGDBmbixInGGGMyMjLM1KlTTZcuXUyTJk3Mb37zG9OtWzczc+ZMc+nSJSd/FgAoMcQOYgcAuEHcIG4AAAqizgEgXEUYY0yoFwYC+Mnw4cOVnJysmTNnqkWLFqEeDgCgDCB2AADcIG4AANwidgAA3CBuAADcInYACFeRoR4AAAAAAAAAAAAAAAAAAADhgkV5AAAAAAAAAAAAAAAAAAB4hEV5QCkyatQo7dq1i9vyAgAcI3YAAAAAAAAAAICyijoHgHAVYYwxoR4EAAAAAAAAAAAAAAAAAADhgDvlAQAAAAAAAAAAAAAAAADgERblAQAAAAAAAAAAAAAAAADgERblAQAAAAAAAAAAAAAAAADgERblAQAAAAAAAAAAAAAAAADgERblAQAAAAAAAAAAAAAAAADgERblAQAAAAAAAAAAAAAAAADgERblAQAAAAAAAAAAAAAAAADgERblAQAAAAAAAAAAAAAAAADgkf8HCGMjgoEAk7IAAAAASUVORK5CYII=",
      "text/plain": [
       "<Figure size 3000x400 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "models = [\"DDM2v2a2c2ter\",\"OUM2v2a2k2ter\"] \n",
    "labels = [\"Linear CBM\",\"Full OUM\"] \n",
    "plot_all_datasets_flat(models, labels, sortby = \"OUM2v2a2k2ter\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "id": "6b33488d",
   "metadata": {},
   "outputs": [],
   "source": [
    "pal = sns.color_palette()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 98,
   "id": "68bc4c12",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'#1f77b4'"
      ]
     },
     "execution_count": 98,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pal.as_hex()[0]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 141,
   "id": "101f81e0",
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_Weibull(t,a=2,a_prime=1.5,lam=1,k=3):\n",
    "    first = 1-np.exp(-(t/lam)**k)\n",
    "    second = a - a_prime\n",
    "    return (a - first*second)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 144,
   "id": "6f6a7434",
   "metadata": {},
   "outputs": [],
   "source": [
    "def plot_boundary(ax,dataset):\n",
    "    \n",
    "    if ax is None:\n",
    "        ax = plt.gca()\n",
    "    T_dur = 1.5\n",
    "    \n",
    "    t = np.arange(0,5,0.01)\n",
    "    param = pd.read_csv(\"Parameter Estimates/DDM2v2a2Weibull2terresult\"+dataset+\".csv\")             \n",
    "    param_mean = param.mean(axis=0)\n",
    "    a_speed = get_Weibull(t,a=param_mean[\"Boundary Separation Speed\"],\n",
    "                           a_prime=param_mean[\"aprimeSpeed\"],\n",
    "                           lam=param_mean[\"lamSpeed\"],k=3)\n",
    "    a_acc = get_Weibull(t,a=param_mean[\"Boundary Separation Accuracy\"],\n",
    "                           a_prime=param_mean[\"aprimeAcc\"],\n",
    "                           lam=param_mean[\"lamAcc\"],k=3)\n",
    "    #['#1f77b4', '#ff7f0e'\n",
    "    ax.plot(t, a_speed, color=\"#1f77b4\")\n",
    "    ax.plot(t, a_acc, color=\"#ff7f0e\")\n",
    "    ax.plot(t, -a_speed, color=\"#1f77b4\")\n",
    "    ax.plot(t, -a_acc, color=\"#ff7f0e\")\n",
    "    ax.tick_params(left = False, bottom = False, labelleft = False, labelbottom = False)\n",
    "    ax.axis('off')\n",
    "\n",
    "    t_max = next(a[0] for a in enumerate(a_acc) if a[1]-param_mean[\"aprimeAcc\"] < 0.001)\n",
    "    ax.set_xlim(0,t[t_max])\n",
    "\n",
    "    #ax.legend([\"Boundary (Speed)\", \"Boundary (Accuracy)\"])\n",
    "    \n",
    "    #return ax\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 145,
   "id": "cc192588",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 2800x400 with 6 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "def plot_all_boundaries(xlabelsize=15, titlesize = 20, figsize=(28, 4)):\n",
    "    sns.set_style(\"whitegrid\", {'axes.grid' : False})\n",
    "    figure, axes = plt.subplots(1,6,figsize=figsize)\n",
    "    for i in range(6):\n",
    "        plot_boundary(ax = axes[i],dataset = datasets[i])\n",
    "        axes[i].set_title(\"\")\n",
    "        #axes[i].set_title(dataset_names[i],fontsize = titlesize, fontweight='bold', fontname='Arial')\n",
    "        #axes[i].set_xlabel(\"Time\", fontsize = xlabelsize, fontname='Arial')\n",
    "        #axes[i].set_xlim(0,t_max)\n",
    "        #axes[i].set_ylim(0,3.5)\n",
    "        axes[i].set_ylabel(\"Boundaries\")\n",
    "        axes[i].tick_params(axis='both', which='major', labelsize=7)\n",
    "        \n",
    "    axes[0].text(x=-0.1, y=-0.5,s=\"Boundaries\",size=20, rotation = \"vertical\")\n",
    "\n",
    "    axes[5].legend(labels =[\"Speed\", \"Accuracy\"], loc='upper left', bbox_to_anchor=(1.03, 1),fontsize=10)\n",
    "plot_all_boundaries()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f844b550",
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 147,
   "id": "d4565c75",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Unnamed: 0.1</th>\n",
       "      <th>Unnamed: 0</th>\n",
       "      <th>Participant</th>\n",
       "      <th>Block</th>\n",
       "      <th>Practice</th>\n",
       "      <th>Cond</th>\n",
       "      <th>Stimulus</th>\n",
       "      <th>Frequency</th>\n",
       "      <th>Response</th>\n",
       "      <th>Time</th>\n",
       "      <th>Censor</th>\n",
       "      <th>Correct</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>0</td>\n",
       "      <td>894</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>Accuracy</td>\n",
       "      <td>5798</td>\n",
       "      <td>5</td>\n",
       "      <td>1</td>\n",
       "      <td>0.734</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>895</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>Accuracy</td>\n",
       "      <td>6554</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.536</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>2</td>\n",
       "      <td>896</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>Accuracy</td>\n",
       "      <td>1177</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.514</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>3</td>\n",
       "      <td>897</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>Accuracy</td>\n",
       "      <td>4796</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0.466</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>4</td>\n",
       "      <td>898</td>\n",
       "      <td>1</td>\n",
       "      <td>10</td>\n",
       "      <td>0</td>\n",
       "      <td>Accuracy</td>\n",
       "      <td>1299</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.446</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22020</th>\n",
       "      <td>22020</td>\n",
       "      <td>32027</td>\n",
       "      <td>17</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>Accuracy</td>\n",
       "      <td>3232</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>0.637</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22021</th>\n",
       "      <td>22021</td>\n",
       "      <td>32028</td>\n",
       "      <td>17</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>Accuracy</td>\n",
       "      <td>4696</td>\n",
       "      <td>4</td>\n",
       "      <td>0</td>\n",
       "      <td>0.584</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22022</th>\n",
       "      <td>22022</td>\n",
       "      <td>32029</td>\n",
       "      <td>17</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>Accuracy</td>\n",
       "      <td>2574</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>0.824</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22023</th>\n",
       "      <td>22023</td>\n",
       "      <td>32030</td>\n",
       "      <td>17</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>Accuracy</td>\n",
       "      <td>6334</td>\n",
       "      <td>6</td>\n",
       "      <td>0</td>\n",
       "      <td>0.739</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22024</th>\n",
       "      <td>22024</td>\n",
       "      <td>32031</td>\n",
       "      <td>17</td>\n",
       "      <td>20</td>\n",
       "      <td>0</td>\n",
       "      <td>Accuracy</td>\n",
       "      <td>1195</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>0.708</td>\n",
       "      <td>0.0</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>22025 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "       Unnamed: 0.1  Unnamed: 0  Participant  Block  Practice      Cond  \\\n",
       "0                 0         894            1     10         0  Accuracy   \n",
       "1                 1         895            1     10         0  Accuracy   \n",
       "2                 2         896            1     10         0  Accuracy   \n",
       "3                 3         897            1     10         0  Accuracy   \n",
       "4                 4         898            1     10         0  Accuracy   \n",
       "...             ...         ...          ...    ...       ...       ...   \n",
       "22020         22020       32027           17     20         0  Accuracy   \n",
       "22021         22021       32028           17     20         0  Accuracy   \n",
       "22022         22022       32029           17     20         0  Accuracy   \n",
       "22023         22023       32030           17     20         0  Accuracy   \n",
       "22024         22024       32031           17     20         0  Accuracy   \n",
       "\n",
       "       Stimulus  Frequency  Response   Time  Censor  Correct  \n",
       "0          5798          5         1  0.734     0.0        0  \n",
       "1          6554          6         0  0.536     0.0        1  \n",
       "2          1177          1         1  0.514     0.0        1  \n",
       "3          4796          4         0  0.466     0.0        1  \n",
       "4          1299          1         1  0.446     0.0        1  \n",
       "...         ...        ...       ...    ...     ...      ...  \n",
       "22020      3232          3         1  0.637     0.0        1  \n",
       "22021      4696          4         0  0.584     0.0        1  \n",
       "22022      2574          2         1  0.824     0.0        1  \n",
       "22023      6334          6         0  0.739     0.0        1  \n",
       "22024      1195          1         1  0.708     0.0        1  \n",
       "\n",
       "[22025 rows x 12 columns]"
      ]
     },
     "execution_count": 147,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Frequencies = [1,  2, 3,  4,  5,  6]\n",
    "participants = [1,  3,  4,  5,  6,  7,  8,  9, 10, 11, 12, 13, 14, 15, 16, 17]\n",
    "df = pd.read_csv(\"/Users/wangjiashun/Desktop/Reserach on SAT/datasets/transformed/Wagenmakers2008/SpeedAccData_new.csv\")\n",
    "df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 149,
   "id": "643b59ae",
   "metadata": {},
   "outputs": [],
   "source": [
    "save_dif = \"/Users/wangjiashun/Desktop/Reserach on SAT/datasets/transformed/Wagenmakers2008/dataByFreq/\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 154,
   "id": "f15d68b7",
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in Frequencies:\n",
    "    for j in range(len(participants)):\n",
    "        d = df[df[\"Frequency\"]==i]\n",
    "        d = d[d[\"Participant\"]==participants[j]]\n",
    "        d.to_csv(save_dif+\"Freq\"+str(i)+\"/sub\"+str(j+1)+\".csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "83b1d592",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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