diff --git a/cluster_experiments/power_config.py b/cluster_experiments/power_config.py
index 81bd29b6..049cdedf 100644
--- a/cluster_experiments/power_config.py
+++ b/cluster_experiments/power_config.py
@@ -79,6 +79,7 @@ class PowerConfig:
 
     # optional mappings
     cupac_model: str = ""
+    comparison_col: str = ""
 
     # Shared
     target_col: str = "target"
diff --git a/cluster_experiments/random_splitter.py b/cluster_experiments/random_splitter.py
index f14a15fb..68512a38 100644
--- a/cluster_experiments/random_splitter.py
+++ b/cluster_experiments/random_splitter.py
@@ -481,3 +481,43 @@ def from_config(cls, config) -> "StratifiedSwitchbackSplitter":
             splitter_weights=config.splitter_weights,
             washover=washover_cls.from_config(config),
         )
+
+
+class ClusteredSteppedWedge(ClusteredSplitter):
+    """Normally used for gradual rollouts, where the treatment is rolled out in batches."""
+
+    def __init__(self, rollout_df: pd.DataFrame, cluster_cols: List[str]):
+        """rollout df should have a column 'rollout_date' and a column 'perc_cities'"""
+        super().__init__(cluster_cols)
+        self.rollout_df = rollout_df
+
+    def assign_treatment_df(
+        self,
+        df: pd.DataFrame,
+    ) -> pd.DataFrame:
+        """
+        Takes a df, randomizes treatments and adds the treatment column to the dataframe
+
+        Arguments:
+            df: dataframe to assign treatments to
+        """
+        df = df.copy()
+
+        # raise error if any nulls in cluster_cols
+        if df[self.cluster_cols].isnull().values.any():
+            raise ValueError(
+                f"Null values found in cluster_cols: {self.cluster_cols}. "
+                "Please remove nulls before running the splitter."
+            )
+
+        clusters_df = df.loc[:, self.cluster_cols].drop_duplicates()
+        clusters_df[self.treatment_col] = self.sample_treatment(clusters_df)
+        df = df.merge(clusters_df, on=self.cluster_cols, how="left")
+
+        # once we know the treatment cities, we need to stablish a roll out strategy. 2 inputs, rollout date and n cities.
+
+        df = df.merge(self.rollout_df, on=["cluster"], how="left")
+        # replace all 1 by treatment
+
+        df["treatment"] = np.where(df["date"] >= df["rollout_date"], 1, 0)
+        return df
diff --git a/docs/plot_calendars.ipynb b/docs/plot_calendars.ipynb
new file mode 100644
index 00000000..5554325c
--- /dev/null
+++ b/docs/plot_calendars.ipynb
@@ -0,0 +1,447 @@
+{
+    "cells": [
+        {
+            "attachments": {},
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "This notebook shows the visualizations of different calendars that can be generated with switchback splitters"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 1,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "from cluster_experiments import PowerAnalysis\n",
+                "import pandas as pd\n",
+                "import numpy as np\n",
+                "from plotnine import ggplot, geom_tile, element_text, element_blank, theme, labs, facet_wrap, aes, theme_set, theme_minimal\n",
+                "# Remove warnings\n",
+                "import warnings\n",
+                "warnings.filterwarnings('ignore')\n",
+                "\n",
+                "np.random.seed(42)\n",
+                "\n",
+                "theme_set(theme_minimal())"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 2,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "def plot_calendar(splitter, df, calendar_name):\n",
+                "    treatments = splitter.assign_treatment_df(df)\n",
+                "    \n",
+                "    treatment_df = (\n",
+                "        treatments\n",
+                "        .loc[:, [\"city\", \"treatment\", \"time\"]]\n",
+                "        .drop_duplicates()\n",
+                "    )\n",
+                "    # Convert time column to datetime format and extract week and day\n",
+                "    treatment_df['time'] = pd.to_datetime(treatment_df['time'])\n",
+                "    treatment_df['week'] = treatment_df['time'].dt.isocalendar().week.astype(str)\n",
+                "    treatment_df['day'] = treatment_df['time'].dt.dayofweek.astype(str)\n",
+                "    # day of week with format number + name\n",
+                "    treatment_df['day_of_week'] = treatment_df['day'] + ' - ' + treatment_df['time'].dt.day_name()\n",
+                "\n",
+                "    return (ggplot(treatment_df, aes(x='day_of_week', y='week', fill='treatment'))\n",
+                "            + geom_tile()\n",
+                "            + facet_wrap('city', nrow=2)\n",
+                "            + labs(title=f'Switchback calendar in different cities, using {calendar_name}', x='Day', y='Week')\n",
+                "            + theme(axis_text_x=element_text(angle=90, vjust=1.0),\n",
+                "                    axis_text_y=element_text(size=8),\n",
+                "                    strip_background=element_blank(),\n",
+                "                    strip_text=element_text(size=10)))\n",
+                "\n",
+                "\n",
+                "        "
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 3,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# Define data with random dates\n",
+                "df_raw = pd.DataFrame(\n",
+                "    {   \n",
+                "        \"time\": pd.date_range(\"2021-03-01\", \"2021-03-15\", freq=\"1min\")[\n",
+                "            np.random.randint(14 * 24 * 60, size=14 * 24 * 60)\n",
+                "        ],\n",
+                "        \"y\": np.random.randn(14 * 24 * 60),\n",
+                "    }\n",
+                ").assign(\n",
+                "    day_of_week=lambda df: df.time.dt.dayofweek,\n",
+                "    hour_of_day=lambda df: df.time.dt.hour,\n",
+                "    week=lambda df: df.time.dt.isocalendar().week,\n",
+                ")\n",
+                "df = pd.concat([df_raw.assign(city=city) for city in (\"TGN\", \"NYC\", \"LON\", \"REU\")])"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 4,
+            "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>time</th>\n",
+                            "      <th>y</th>\n",
+                            "      <th>day_of_week</th>\n",
+                            "      <th>hour_of_day</th>\n",
+                            "      <th>week</th>\n",
+                            "      <th>city</th>\n",
+                            "    </tr>\n",
+                            "  </thead>\n",
+                            "  <tbody>\n",
+                            "    <tr>\n",
+                            "      <th>0</th>\n",
+                            "      <td>2021-03-11 23:15:00</td>\n",
+                            "      <td>0.827658</td>\n",
+                            "      <td>3</td>\n",
+                            "      <td>23</td>\n",
+                            "      <td>10</td>\n",
+                            "      <td>TGN</td>\n",
+                            "    </tr>\n",
+                            "    <tr>\n",
+                            "      <th>1</th>\n",
+                            "      <td>2021-03-01 14:20:00</td>\n",
+                            "      <td>0.843550</td>\n",
+                            "      <td>0</td>\n",
+                            "      <td>14</td>\n",
+                            "      <td>9</td>\n",
+                            "      <td>TGN</td>\n",
+                            "    </tr>\n",
+                            "    <tr>\n",
+                            "      <th>2</th>\n",
+                            "      <td>2021-03-04 17:50:00</td>\n",
+                            "      <td>0.306790</td>\n",
+                            "      <td>3</td>\n",
+                            "      <td>17</td>\n",
+                            "      <td>9</td>\n",
+                            "      <td>TGN</td>\n",
+                            "    </tr>\n",
+                            "    <tr>\n",
+                            "      <th>3</th>\n",
+                            "      <td>2021-03-09 07:24:00</td>\n",
+                            "      <td>-2.133119</td>\n",
+                            "      <td>1</td>\n",
+                            "      <td>7</td>\n",
+                            "      <td>10</td>\n",
+                            "      <td>TGN</td>\n",
+                            "    </tr>\n",
+                            "    <tr>\n",
+                            "      <th>4</th>\n",
+                            "      <td>2021-03-08 20:04:00</td>\n",
+                            "      <td>-1.026710</td>\n",
+                            "      <td>0</td>\n",
+                            "      <td>20</td>\n",
+                            "      <td>10</td>\n",
+                            "      <td>TGN</td>\n",
+                            "    </tr>\n",
+                            "  </tbody>\n",
+                            "</table>\n",
+                            "</div>"
+                        ],
+                        "text/plain": [
+                            "                 time         y  day_of_week  hour_of_day  week city\n",
+                            "0 2021-03-11 23:15:00  0.827658            3           23    10  TGN\n",
+                            "1 2021-03-01 14:20:00  0.843550            0           14     9  TGN\n",
+                            "2 2021-03-04 17:50:00  0.306790            3           17     9  TGN\n",
+                            "3 2021-03-09 07:24:00 -2.133119            1            7    10  TGN\n",
+                            "4 2021-03-08 20:04:00 -1.026710            0           20    10  TGN"
+                        ]
+                    },
+                    "execution_count": 4,
+                    "metadata": {},
+                    "output_type": "execute_result"
+                }
+            ],
+            "source": [
+                "# We have data of 2-weeks in 4 cities\n",
+                "df.head()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 5,
+            "metadata": {},
+            "outputs": [
+                {
+                    "data": {
+                        "image/png": 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",
+                        "text/plain": [
+                            "<Figure size 640x480 with 4 Axes>"
+                        ]
+                    },
+                    "metadata": {
+                        "needs_background": "light"
+                    },
+                    "output_type": "display_data"
+                },
+                {
+                    "data": {
+                        "text/plain": [
+                            "<ggplot: (310936046)>"
+                        ]
+                    },
+                    "execution_count": 5,
+                    "metadata": {},
+                    "output_type": "execute_result"
+                }
+            ],
+            "source": [
+                "# Completely random calendar\n",
+                "config = {\n",
+                "    \"time_col\": \"time\",\n",
+                "    \"switch_frequency\": \"1d\",\n",
+                "    \"perturbator\": \"uniform\",\n",
+                "    \"analysis\": \"ols_clustered\",\n",
+                "    \"splitter\": \"switchback\",\n",
+                "    \"cluster_cols\": [\"time\", \"city\"],\n",
+                "    \"target_col\": \"y\",\n",
+                "}\n",
+                "\n",
+                "power = PowerAnalysis.from_dict(config)\n",
+                "\n",
+                "plot_calendar(power.splitter, df, \"random calendar\")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 6,
+            "metadata": {},
+            "outputs": [
+                {
+                    "data": {
+                        "image/png": 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",
+                        "text/plain": [
+                            "<Figure size 640x480 with 4 Axes>"
+                        ]
+                    },
+                    "metadata": {
+                        "needs_background": "light"
+                    },
+                    "output_type": "display_data"
+                },
+                {
+                    "data": {
+                        "text/plain": [
+                            "<ggplot: (311115590)>"
+                        ]
+                    },
+                    "execution_count": 6,
+                    "metadata": {},
+                    "output_type": "execute_result"
+                }
+            ],
+            "source": [
+                "# Balanced calendar\n",
+                "config = {\n",
+                "    \"time_col\": \"time\",\n",
+                "    \"switch_frequency\": \"1d\",\n",
+                "    \"perturbator\": \"uniform\",\n",
+                "    \"analysis\": \"ols_clustered\",\n",
+                "    \"splitter\": \"switchback_balance\",\n",
+                "    \"cluster_cols\": [\"time\", \"city\"],\n",
+                "    \"target_col\": \"y\",\n",
+                "}\n",
+                "\n",
+                "power = PowerAnalysis.from_dict(config)\n",
+                "\n",
+                "plot_calendar(power.splitter, df, \"balanced Calendar\")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 7,
+            "metadata": {},
+            "outputs": [
+                {
+                    "data": {
+                        "image/png": 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",
+                        "text/plain": [
+                            "<Figure size 640x480 with 4 Axes>"
+                        ]
+                    },
+                    "metadata": {
+                        "needs_background": "light"
+                    },
+                    "output_type": "display_data"
+                },
+                {
+                    "data": {
+                        "text/plain": [
+                            "<ggplot: (311223354)>"
+                        ]
+                    },
+                    "execution_count": 7,
+                    "metadata": {},
+                    "output_type": "execute_result"
+                }
+            ],
+            "source": [
+                "# Stratified - city level\n",
+                "config = {\n",
+                "    \"time_col\": \"time\",\n",
+                "    \"switch_frequency\": \"1d\",\n",
+                "    \"perturbator\": \"uniform\",\n",
+                "    \"analysis\": \"ols_clustered\",\n",
+                "    \"splitter\": \"switchback_stratified\",\n",
+                "    \"cluster_cols\": [\"time\", \"city\"],\n",
+                "    \"strata_cols\": [\"city\"],\n",
+                "    \"target_col\": \"y\",\n",
+                "}\n",
+                "\n",
+                "power = PowerAnalysis.from_dict(config)\n",
+                "\n",
+                "plot_calendar(power.splitter, df, \"stratified calendar (city level)\")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 8,
+            "metadata": {},
+            "outputs": [
+                {
+                    "data": {
+                        "image/png": 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",
+                        "text/plain": [
+                            "<Figure size 640x480 with 4 Axes>"
+                        ]
+                    },
+                    "metadata": {
+                        "needs_background": "light"
+                    },
+                    "output_type": "display_data"
+                },
+                {
+                    "data": {
+                        "text/plain": [
+                            "<ggplot: (311217083)>"
+                        ]
+                    },
+                    "execution_count": 8,
+                    "metadata": {},
+                    "output_type": "execute_result"
+                }
+            ],
+            "source": [
+                "# Stratified - city + week level\n",
+                "config = {\n",
+                "    \"time_col\": \"time\",\n",
+                "    \"switch_frequency\": \"1d\",\n",
+                "    \"perturbator\": \"uniform\",\n",
+                "    \"analysis\": \"ols_clustered\",\n",
+                "    \"splitter\": \"switchback_stratified\",\n",
+                "    \"cluster_cols\": [\"time\", \"city\"],\n",
+                "    \"strata_cols\": [\"week\", \"city\"],\n",
+                "    \"target_col\": \"y\",\n",
+                "}\n",
+                "\n",
+                "power = PowerAnalysis.from_dict(config)\n",
+                "\n",
+                "plot_calendar(power.splitter, df, \"stratified calendar (week + city level)\")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 9,
+            "metadata": {},
+            "outputs": [
+                {
+                    "data": {
+                        "image/png": 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",
+                        "text/plain": [
+                            "<Figure size 640x480 with 4 Axes>"
+                        ]
+                    },
+                    "metadata": {
+                        "needs_background": "light"
+                    },
+                    "output_type": "display_data"
+                },
+                {
+                    "data": {
+                        "text/plain": [
+                            "<ggplot: (311416839)>"
+                        ]
+                    },
+                    "execution_count": 9,
+                    "metadata": {},
+                    "output_type": "execute_result"
+                }
+            ],
+            "source": [
+                "# Stratified - city + day of week level\n",
+                "config = {\n",
+                "    \"time_col\": \"time\",\n",
+                "    \"switch_frequency\": \"1d\",\n",
+                "    \"perturbator\": \"uniform\",\n",
+                "    \"analysis\": \"ols_clustered\",\n",
+                "    \"splitter\": \"switchback_stratified\",\n",
+                "    \"cluster_cols\": [\"time\", \"city\"],\n",
+                "    \"strata_cols\": [\"day_of_week\", \"city\"],\n",
+                "    \"target_col\": \"y\",\n",
+                "}\n",
+                "\n",
+                "power = PowerAnalysis.from_dict(config)\n",
+                "\n",
+                "plot_calendar(power.splitter, df, \"stratified calendar (day of week + city level)\")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": null,
+            "metadata": {},
+            "outputs": [],
+            "source": []
+        }
+    ],
+    "metadata": {
+        "kernelspec": {
+            "display_name": "venv",
+            "language": "python",
+            "name": "python3"
+        },
+        "language_info": {
+            "codemirror_mode": {
+                "name": "ipython",
+                "version": 3
+            },
+            "file_extension": ".py",
+            "mimetype": "text/x-python",
+            "name": "python",
+            "nbconvert_exporter": "python",
+            "pygments_lexer": "ipython3",
+            "version": "3.8.6"
+        },
+        "orig_nbformat": 4
+    },
+    "nbformat": 4,
+    "nbformat_minor": 2
+}
diff --git a/docs/plot_calendars_hours.ipynb b/docs/plot_calendars_hours.ipynb
new file mode 100644
index 00000000..a0d1428b
--- /dev/null
+++ b/docs/plot_calendars_hours.ipynb
@@ -0,0 +1,509 @@
+{
+    "cells": [
+        {
+            "attachments": {},
+            "cell_type": "markdown",
+            "metadata": {},
+            "source": [
+                "This notebook shows the visualizations of different calendars that can be generated with switchback splitters"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 1,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "from cluster_experiments import PowerAnalysis\n",
+                "import pandas as pd\n",
+                "import numpy as np\n",
+                "import plotnine as pn\n",
+                "# Remove warnings\n",
+                "import warnings\n",
+                "warnings.filterwarnings('ignore')\n",
+                "\n",
+                "np.random.seed(42)\n",
+                "\n",
+                "pn.theme_set(pn.theme_minimal())"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 2,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "def plot_calendar(splitter, df, calendar_name):\n",
+                "    treatments = splitter.assign_treatment_df(df)\n",
+                "    \n",
+                "    treatment_df = (\n",
+                "        treatments\n",
+                "        .loc[:, [\"city\", \"treatment\", \"time\"]]\n",
+                "        .drop_duplicates()\n",
+                "    )\n",
+                "    # Convert time column to datetime format and extract week and day\n",
+                "    treatment_df['week_number'] = treatment_df['time'].dt.isocalendar().week.astype(int).astype(str)\n",
+                "    treatment_df['week_number_num'] = treatment_df['time'].dt.isocalendar().week\n",
+                "    # add time with the week set to the minimum week number\n",
+                "    treatment_df['time_in_week'] = treatment_df['time'] - pd.to_timedelta(treatment_df['week_number_num'], unit='W') + pd.to_timedelta(treatment_df['week_number_num'].min(), unit='W')\n",
+                "\n",
+                "    # Custom date formatter function\n",
+                "    def custom_date_formatter(dates):\n",
+                "        return [date.strftime('%a %H:%M') for date in dates]\n",
+                "\n",
+                "    # Create the plot\n",
+                "    plot = (\n",
+                "        pn.ggplot(treatment_df, pn.aes(x='time_in_week', y='week_number', fill='treatment'))\n",
+                "        + pn.geom_tile()\n",
+                "        + pn.theme_minimal()\n",
+                "        + pn.labs(\n",
+                "            title=f\"Treatment assignment using {calendar_name}\",\n",
+                "            x=\"Time since start of week\",\n",
+                "            y=\"Week number\",\n",
+                "            fill=\"Treatment\"\n",
+                "        )\n",
+                "        + pn.facet_wrap('~city')\n",
+                "        + pn.scale_x_datetime(labels=custom_date_formatter)\n",
+                "        # vertical labels\n",
+                "        + pn.theme(axis_text_x=pn.element_text(angle=90, vjust=1.0))\n",
+                "    )\n",
+                "\n",
+                "    # Display the plot\n",
+                "    return plot"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 3,
+            "metadata": {},
+            "outputs": [],
+            "source": [
+                "# Define data with random dates\n",
+                "df_raw = pd.DataFrame(\n",
+                "    {   \n",
+                "        \"time\": pd.date_range(\"2021-03-01\", \"2021-03-15\", freq=\"1s\")[\n",
+                "            np.random.randint(14 * 24 * 60 * 60, size=14 * 24 * 60 * 60)\n",
+                "        ],\n",
+                "        \"y\": np.random.randn(14 * 24 * 60 * 60),\n",
+                "    }\n",
+                ").assign(\n",
+                "    day_of_week=lambda df: df.time.dt.dayofweek,\n",
+                "    hour_of_day=lambda df: df.time.dt.hour,\n",
+                "    hour_4h=lambda df: df.time.dt.hour // 4,\n",
+                "    week=lambda df: df.time.dt.isocalendar().week,\n",
+                ")\n",
+                "df = pd.concat([df_raw.assign(city=city) for city in (\"TGN\", \"NYC\", \"LON\", \"REU\")])"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 4,
+            "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>time</th>\n",
+                            "      <th>y</th>\n",
+                            "      <th>day_of_week</th>\n",
+                            "      <th>hour_of_day</th>\n",
+                            "      <th>hour_4h</th>\n",
+                            "      <th>week</th>\n",
+                            "      <th>city</th>\n",
+                            "    </tr>\n",
+                            "  </thead>\n",
+                            "  <tbody>\n",
+                            "    <tr>\n",
+                            "      <th>0</th>\n",
+                            "      <td>2021-03-02 09:52:38</td>\n",
+                            "      <td>0.328784</td>\n",
+                            "      <td>1</td>\n",
+                            "      <td>9</td>\n",
+                            "      <td>2</td>\n",
+                            "      <td>9</td>\n",
+                            "      <td>TGN</td>\n",
+                            "    </tr>\n",
+                            "    <tr>\n",
+                            "      <th>1</th>\n",
+                            "      <td>2021-03-08 18:25:55</td>\n",
+                            "      <td>0.489899</td>\n",
+                            "      <td>0</td>\n",
+                            "      <td>18</td>\n",
+                            "      <td>4</td>\n",
+                            "      <td>10</td>\n",
+                            "      <td>TGN</td>\n",
+                            "    </tr>\n",
+                            "    <tr>\n",
+                            "      <th>2</th>\n",
+                            "      <td>2021-03-02 12:38:52</td>\n",
+                            "      <td>-0.559446</td>\n",
+                            "      <td>1</td>\n",
+                            "      <td>12</td>\n",
+                            "      <td>3</td>\n",
+                            "      <td>9</td>\n",
+                            "      <td>TGN</td>\n",
+                            "    </tr>\n",
+                            "    <tr>\n",
+                            "      <th>3</th>\n",
+                            "      <td>2021-03-03 23:59:38</td>\n",
+                            "      <td>1.644260</td>\n",
+                            "      <td>2</td>\n",
+                            "      <td>23</td>\n",
+                            "      <td>5</td>\n",
+                            "      <td>9</td>\n",
+                            "      <td>TGN</td>\n",
+                            "    </tr>\n",
+                            "    <tr>\n",
+                            "      <th>4</th>\n",
+                            "      <td>2021-03-02 06:37:48</td>\n",
+                            "      <td>-0.418535</td>\n",
+                            "      <td>1</td>\n",
+                            "      <td>6</td>\n",
+                            "      <td>1</td>\n",
+                            "      <td>9</td>\n",
+                            "      <td>TGN</td>\n",
+                            "    </tr>\n",
+                            "  </tbody>\n",
+                            "</table>\n",
+                            "</div>"
+                        ],
+                        "text/plain": [
+                            "                 time         y  day_of_week  hour_of_day  hour_4h  week city\n",
+                            "0 2021-03-02 09:52:38  0.328784            1            9        2     9  TGN\n",
+                            "1 2021-03-08 18:25:55  0.489899            0           18        4    10  TGN\n",
+                            "2 2021-03-02 12:38:52 -0.559446            1           12        3     9  TGN\n",
+                            "3 2021-03-03 23:59:38  1.644260            2           23        5     9  TGN\n",
+                            "4 2021-03-02 06:37:48 -0.418535            1            6        1     9  TGN"
+                        ]
+                    },
+                    "execution_count": 4,
+                    "metadata": {},
+                    "output_type": "execute_result"
+                }
+            ],
+            "source": [
+                "# We have data of 2-weeks in 4 cities\n",
+                "df.head()"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 5,
+            "metadata": {},
+            "outputs": [
+                {
+                    "data": {
+                        "image/png": 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",
+                        "text/plain": [
+                            "<Figure size 640x480 with 4 Axes>"
+                        ]
+                    },
+                    "metadata": {
+                        "needs_background": "light"
+                    },
+                    "output_type": "display_data"
+                },
+                {
+                    "data": {
+                        "text/plain": [
+                            "<ggplot: (304288799)>"
+                        ]
+                    },
+                    "execution_count": 5,
+                    "metadata": {},
+                    "output_type": "execute_result"
+                }
+            ],
+            "source": [
+                "# Completely random calendar\n",
+                "from datetime import timedelta\n",
+                "\n",
+                "\n",
+                "config = {\n",
+                "    \"time_col\": \"time\",\n",
+                "    \"switch_frequency\": \"4h\",\n",
+                "    \"perturbator\": \"uniform\",\n",
+                "    \"analysis\": \"ols_clustered\",\n",
+                "    \"splitter\": \"switchback\",\n",
+                "    \"cluster_cols\": [\"time\", \"city\"],\n",
+                "    \"target_col\": \"y\",\n",
+                "    \"washover\": \"constant_washover\",\n",
+                "    \"washover_time_delta\": timedelta(hours=2),\n",
+                "}\n",
+                "\n",
+                "power = PowerAnalysis.from_dict(config)\n",
+                "\n",
+                "plot_calendar(power.splitter, df, \"random calendar\")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 6,
+            "metadata": {},
+            "outputs": [
+                {
+                    "data": {
+                        "image/png": 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",
+                        "text/plain": [
+                            "<Figure size 640x480 with 4 Axes>"
+                        ]
+                    },
+                    "metadata": {
+                        "needs_background": "light"
+                    },
+                    "output_type": "display_data"
+                },
+                {
+                    "data": {
+                        "text/plain": [
+                            "<ggplot: (304498911)>"
+                        ]
+                    },
+                    "execution_count": 6,
+                    "metadata": {},
+                    "output_type": "execute_result"
+                }
+            ],
+            "source": [
+                "# Balanced calendar\n",
+                "config = {\n",
+                "    \"time_col\": \"time\",\n",
+                "    \"switch_frequency\": \"4h\",\n",
+                "    \"perturbator\": \"uniform\",\n",
+                "    \"analysis\": \"ols_clustered\",\n",
+                "    \"splitter\": \"switchback_balance\",\n",
+                "    \"cluster_cols\": [\"time\", \"city\"],\n",
+                "    \"target_col\": \"y\",\n",
+                "}\n",
+                "\n",
+                "power = PowerAnalysis.from_dict(config)\n",
+                "\n",
+                "plot_calendar(power.splitter, df, \"balanced Calendar\")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 7,
+            "metadata": {},
+            "outputs": [
+                {
+                    "data": {
+                        "image/png": 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",
+                        "text/plain": [
+                            "<Figure size 640x480 with 4 Axes>"
+                        ]
+                    },
+                    "metadata": {
+                        "needs_background": "light"
+                    },
+                    "output_type": "display_data"
+                },
+                {
+                    "data": {
+                        "text/plain": [
+                            "<ggplot: (304646891)>"
+                        ]
+                    },
+                    "execution_count": 7,
+                    "metadata": {},
+                    "output_type": "execute_result"
+                }
+            ],
+            "source": [
+                "# Stratified - city level\n",
+                "config = {\n",
+                "    \"time_col\": \"time\",\n",
+                "    \"switch_frequency\": \"4h\",\n",
+                "    \"perturbator\": \"uniform\",\n",
+                "    \"analysis\": \"ols_clustered\",\n",
+                "    \"splitter\": \"switchback_stratified\",\n",
+                "    \"cluster_cols\": [\"time\", \"city\"],\n",
+                "    \"strata_cols\": [\"city\"],\n",
+                "    \"target_col\": \"y\",\n",
+                "}\n",
+                "\n",
+                "power = PowerAnalysis.from_dict(config)\n",
+                "\n",
+                "plot_calendar(power.splitter, df, \"stratified calendar (city level)\")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 8,
+            "metadata": {},
+            "outputs": [
+                {
+                    "data": {
+                        "image/png": 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",
+                        "text/plain": [
+                            "<Figure size 640x480 with 4 Axes>"
+                        ]
+                    },
+                    "metadata": {
+                        "needs_background": "light"
+                    },
+                    "output_type": "display_data"
+                },
+                {
+                    "data": {
+                        "text/plain": [
+                            "<ggplot: (304292286)>"
+                        ]
+                    },
+                    "execution_count": 8,
+                    "metadata": {},
+                    "output_type": "execute_result"
+                }
+            ],
+            "source": [
+                "# Stratified - city + week level\n",
+                "config = {\n",
+                "    \"time_col\": \"time\",\n",
+                "    \"switch_frequency\": \"4h\",\n",
+                "    \"perturbator\": \"uniform\",\n",
+                "    \"analysis\": \"ols_clustered\",\n",
+                "    \"splitter\": \"switchback_stratified\",\n",
+                "    \"cluster_cols\": [\"time\", \"city\"],\n",
+                "    \"strata_cols\": [\"week\", \"city\"],\n",
+                "    \"target_col\": \"y\",\n",
+                "}\n",
+                "\n",
+                "power = PowerAnalysis.from_dict(config)\n",
+                "\n",
+                "plot_calendar(power.splitter, df, \"stratified calendar (week + city level)\")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 9,
+            "metadata": {},
+            "outputs": [
+                {
+                    "data": {
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",
+                        "text/plain": [
+                            "<Figure size 640x480 with 4 Axes>"
+                        ]
+                    },
+                    "metadata": {
+                        "needs_background": "light"
+                    },
+                    "output_type": "display_data"
+                },
+                {
+                    "data": {
+                        "text/plain": [
+                            "<ggplot: (304915270)>"
+                        ]
+                    },
+                    "execution_count": 9,
+                    "metadata": {},
+                    "output_type": "execute_result"
+                }
+            ],
+            "source": [
+                "# Stratified - city + day of week level\n",
+                "config = {\n",
+                "    \"time_col\": \"time\",\n",
+                "    \"switch_frequency\": \"4h\",\n",
+                "    \"perturbator\": \"uniform\",\n",
+                "    \"analysis\": \"ols_clustered\",\n",
+                "    \"splitter\": \"switchback_stratified\",\n",
+                "    \"cluster_cols\": [\"time\", \"city\"],\n",
+                "    \"strata_cols\": [\"day_of_week\", \"city\"],\n",
+                "    \"target_col\": \"y\",\n",
+                "}\n",
+                "\n",
+                "power = PowerAnalysis.from_dict(config)\n",
+                "\n",
+                "plot_calendar(power.splitter, df, \"stratified calendar (day of week + city level)\")"
+            ]
+        },
+        {
+            "cell_type": "code",
+            "execution_count": 10,
+            "metadata": {},
+            "outputs": [
+                {
+                    "data": {
+                        "image/png": 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kq56f7fm+uIme43yVPvB3WLW8I4FnVldoO15AvlMw612eyv9Uv/frKce55Kv79wUe1PuhQaSUbiOfjD0xItasknes0o4HHtm17Xckr99vASJiO/JAIkcCq/XUoQvIFzX+q5p3qPOELmuT7wK8GXhDSumtg+7zyN2iNunJa71q8sa904Y8nn02dd1pqurvaSz7vbQ9+eTua6m6Gt5lUfX7f1g5f0wpDTr8eqddnpNSOqJn8tfIdyR2qfbVitiZ3MY+3rNtrqLr7mBX+q0pP0fZ6VLZaUed7pPd7ehc8mibL+mpI6+s8hykHdFnn3e6h63bZ9q0rq197Eq+m/X+1OeuS1q5u3hfIJ/fdu4Id9rRK4FzU0onDbvAFfhOW1z9XtizqIXkc+Ojusq1Iu17JleR70YObFRBz+XdJ1eVTaqfJ5Jv7/X+7E6+4nFH38PI/XJPJd+SvLpr3g3JX9rDmErTH3bqlHHaSUM17a5d/29b/f58n7JfRv7ivXuf5fRb9pU9y14hkfvPfy0iriRXxCuq8rymmmVjgJTS38ldjJ4GTEXuj/65iOjtC/nBqrzfAa6I3Bf8zRHRb726bUr+kji7d0J1UOu3DZghvXOy0W/7zLSfZtu3vftwS/rXv86JQu+6DlvGUTmSfJL6TuDqyM8x7F+dUAxqkHXZqvrdb1/+k6UB9PKsaF3q59x+idXB8vMRMUU+sHbqf+cW+7j68m9DPpa+mP5166ksW6/uQ+4+1e+B1Rm7kPbJE/KdllnNwXYaVbvZlNzNZto6V+15WnePQY95PfrWn+Xod0LX6Xffbx/9ue9ChvsOO5j8Hbh7V9oe5O32nQHKvBVwZdVOe3UuYNynz7RBnUA+zj8q8rNZj67STiCfsDwpche7HYCfV4ESLP3ufBf969D9WFp/hj5PqHyEfGL5mpTSZ4dcrxf2yeegatoZfabds88yZjLI93/nmNt7kYmUuw9dx8rtNxiuDdyN3C7P6lOeRK7rG9O/rQ1iRdrRHhHxe5ZtR53jQ792tBG5O1+n2+fu5Iuyg44s3K/uAezdJ/3tAyxv4OP1sKrzux8BL4qlz0w+jXzM/uIKLnao77SU0vnk7q3P7wQskbvHPRn4Tkqpc+F7Rdv3TIJ80Xtgo3qm58Y+aZ0A62TyrbCZXA4QEf9Nvr32W3J/xovJFR6qK0ZDlum2FZjW/cXXye/d5D74/fQGenQd+Gdb9tCqK/Mnk788P03uQ3sdOeLfnXwgv2MbpZQWRcSh5L72TyBfOfrfiPguudtKSimdHxEPJH9p7VjN93HgAxHxrJTSyStT5j5m2yf9ts9M8w+6nNXId4Zme5Cx90A/bBmHMVtjXaZtVifIz4yI7clXWB5Pvqq5T0TsnVL6xAD5jXJdljHHdWna8aS6YnQ8+cr1QeT+51eT1/FZ5G0zrpcvd/L5Fiv+JTMSc7Sd5kW7GfaY19G52zKgK6vlzcVFqaG+w1JKp0fEGcArI+KD5GDhMcAnU73PpXScUP1+KvmkeC3ghJTS3yLi4ir9SvKdqRO7PtdZz4OY/rxSx0098w50ntDlWPJ32lsi4gcppanZV2UZxzP9Yeink09wX8L0Z52W90xYt9nawaB6vycG/t7oMkwbmFci4k3kO78nkJ/rnSI/o7kG8EOmt/ljyftoD/KdqWeQB9Ka9dnFHv0ejv9Jtbyv9qTPdFF3nA4mH89fQO4SuQe5C9niFVzeinynLSY/+7Mz+c7yy6rlHNpnucO275lsTL5zPrBRBT39XE7u0rFxSumE5cwL+aGom4EndX9pVZFsvysMQ0V7K6BzpeTmAcs/rGHL/xTywASvTCl9pXtCROzR7wPVFYGDgYMjP5y8mBzJP4ncTYHqNvJPqh8ij6bxW/JzCDvMUJbLyFdd7987IfLIM1sx82AG43QueZudlOZ++PQVqX+dbXIXpr87ZivyQWvZTPIDfmcARMTG5If5DoiIg2a4czCszgG8377cjHzCOZAB69KKttsHkbuFfCCl9N6ecvb7whrl8eE88onyOgMeG84Hto6Itfrsswf0+0AfnePRQ5n5RBKG304z5TWKdnMZuevrtHWOiLXJV4S7u5kNfcwbVkrp9oj4K7krWK/OleUHMH1ktwf2mX/Y7zDIx+cvkE+6nlmlDdQlpyrf/SPi7lXX327bdc2zQlJKZ0dEm6VBTzul1LkjfCJLgx5YGiBB112GAdrHsOcJHT8jb6cfACdHxI7V991yVXfGlrk7FhGbV3+ekkY/ZHVnn0yrQ9XV8g1Zdr9dVU27S+oabry6wr4Z+Xi0Mi4nt8t+5Ykq/Wr6XOQdUHc76r2zM1M7ugj4r+5uYBGxbZ95SSktiYivkC8I3p+lAxh8bdAC9qt7VW++C1bw/K/7eD3rIA8zFWk5039Afh5mj4j4PnlAiO/060o3oGG/0yB3YTuI3KXtCJbut5O65lnR9j1NRGxFjmGm3SGdzbiuhHb6LB4OPCgiXt5vnp6uL7eRd3RvGd/TJw3ySfcou7McT77is3f0Hwp5jVi5oTGHLX/nCtIyV02rE8udetI2jKX9sAGoTl46w1betZrvbn3y+Sv5AdsZr3xW+/Z7wHYR8ayeya9nOSPFjNFXyScb7+43cQW7XnV0nj8YZh+eU/1+ak85XkL+8upOm3a7t+pCegH5iuucbOOU0mXk/rbPjK7haSvvHHQ5Q9SlFdluMHP9X0B+wLXXiuazXCmP8vUD4Nkxw7DTPXXraHL3i//tmWc3+p9s9/Nj8hfIXtF/SOzOMXLY7dTPSNpNddz4LvlZnJ16Ju/F0ucqOgY+5q2kk4Ct+qzXj8n1d8+qz3sn/7Xp/4K8Yb/DIA+6cD15FMuXAienlM6ZYd5eR3ct/w6Rh4p9Efl5sRU54ep2Innwgeey7N2cE8gnrC8E/plS6u669Afyickr+52oRnY3WKHzhDuklE4h31XemPz82aBtqW6/J58cvjTyKKjdOhcqurs39v3eAN7KHJzTVfvgWHIA/byeyS8mX4w4eojn5HodS24Xb4uIO3USq/On1/eZv9PuV+uaN1i6bfr5Ivmk/T3kERGPSilds4LlnQtHke9OvaffeWIs/zmxG6r5+n5/VT2KvkTucvox8rOTg14s6be8Yb/TqLqwfZs8GuMLyN9lh3XXk5Vp3308pvr9swHnB8Z7pwfyl+ZjgcXVl9wvyF8i9yQfrG4i9wGEXEmeB/w88vsxgtyt5wEsHdq226/IB9UPkE+ubiePhPPvPvMOLaV0Y0S8lPwl/deqq9jZ5JPN+5CH/30nK347cdjyn0K+OvWJKuK9iNwdYg/yF8zDuuZ9MvDFyENzn0OOtB9AHjq2zdKrcsdHxPXkW48Xk59T2o18grb/csr/bvL+OToiDiZvm0eSrzicx/jrWj+fJtezRZHfL/Jj8lWzLcj1ciuW9q8e1unkffbu6g7Mv4ELU0q/nuUzJ5D7NX8g8gACfyMPLVqQt1l3oLpv5GFNv08e6ec/5Dt0zwK+n/oMr7sS3kw+8ftFRHyepUNWP5Tc9gb5shu0Lv2q+v2RiPg6+cr4WSmlaf3Je5xN7lL19qrb05/JD8i/hnwlsffLYUX2zzBeSx6G8ycRcURXfvci76PfsvQhz4+TTw4/WZ2wn05uj7uT2+5yHzavjkevIJ/o/jEiOkNWb0yuFz8kX3Ubdjv1M8p2sy+5+8m3IqIznP6jyW3gfJY9bgxzzFsZ3ySffD2H3F0DyIMNRMQ7yENBn159B9xK7gLVrxvTsN9hpJRuiIjDycPCwnAnLl+tyvL6yO8BOp6lQ1YH+XmXlb3jeSK528p9WbZ7yonk48K25JE875BSStWFnJ8CZ1Tb4kzy8W1LcsB6GEsf2h/mPGEZKaXfRsQO5LvLJ0fEU1NKfZ8TmS9SSrdFxOvId2xPr74/LyPf6XsWeT92DyjwDfLzeF+M3IX4UnKbfxgz1KsVsA85qPpGddJ7JkuHrP4HM1wAGUTVHfIT5AsFp0TEN8gX7l5F7rq2Wc9HjiI/s3V8RHyb/F2yc/WZmfK4KCKOJwf7sBIBwFxIKbUj4o3kO7l/ro4dF5Kfa3wG+Tvhu7Ms4lfk7sWfj4jjyKOW/TqldGHXPF8iB3kvA/6W8vD0K2OY77SOxVX+XyAfDw7rs9wVbt89nkP+HhrujlFa8eH7dqhWanFP+kn0Gea1a/o65Aca/0DuZ3oD+WTvcLqGKa7m7ZwE3EQ+CHyd3DfzIqYPy7gp+WrIVeQdk6iGm5ypTF3rsLDPtJk+c3/yjv0H+QvvcvLOPwDYomu+xQw3rOSM5Z9lW25H7mZxFbnSnEY+WVjUs/73Jr9b4s/kB9FvrLb5Z4DNu5b3KvIDcZ0+s5eRR0F7fk++yyy/Z9t8j3yl8vpqWduRx+L/y/K2QZphiMIV3E99P0N+SO515IPI9VXdurDa9s+frRxd0xbSZyhI8u3cv1T1YlrbmGEf3qfahzeQn084rtqOy6xXtT5HsnRo02vJd+reTr4FPeN6L2f7zbQvH02+gnIjuRvDt8gnuVcCPxhgvQaqS9W8byffsVrSvc1n2s5dn7sn+QTg0mo//oF8zBhq/8y0r2epW4vp07bJAceHyBctbq7251/JXwC9w3NuRu5ucVW1jU8hH+j7LnuW7bw9+eraZdV6tcmB0PYrsp1m2XajbDfbkK/+Xlct+8fk0b6mbX8GPObNtp8G3K5/It9l6TftxdX0W8j1+5PkQKZfHRr4O6zrMw+ulnUlPa9HGKDca1fb4pyqfFeTj8mPGLQeL2f5C6qyJWBBn22WgFfM8NnNyQHj+V1l+xP5eY0H9Mw70HkCMx/ntyF/R18OPHQF9n+nrm457Gdnq+uzbXfyMfe4arvcUu3D9wBr9Zn34eTj6U1VW/hGtW+m1SsG/C6aYX99qarjS8jHli8Am/WZd8b6PMOyg3w392/k49aF1bp2hnNf2DXvauTviHPJx9U2eUCpjWdbN/JxIZEvog29D/ssr+9xbchlPIV8Qeqqah//varTW3XNcxLTj3urkQOjS1h6B3lhn+UfXU3be8hyzVQnB/5O69qvF1ZlmLE+MHj73rLfdic/N3gTeQTAofZBVAuQRiLys0NXAKellJ65vPk1f1VdUC4DDk4pvW5580urqojYmXwC8ciU0uljzvv+5BOLA1NKbxln3lJTVD0jfgi8KaX0mbrLMw4RcST5LtjmKaVBBwNY5UTEO8l3jO6bUhpmYJHxPdOj5ov+49W/gfwg5vFjLo5WQvQfJ3/f6rf7Uo2WUjqG3B1red16R+GN5KubtXbJkVZxbyTfRRh4AINVWeT3e+1CHsCgyQHPhuQ7fwcMG/DA/HjOQs1xRkT8ktztajXysMrPI1+1nFdD+Wpm1d25f1R9rf9Cfov408kjSv2M2UcLkxohpbTjuPKKPKLbc8nvrHk1+cRl2ruyJM2sejZ2R/LzxM8kd3+6ut5SjVZEPIrcJf515POuD9dbotFK+UXOKzwgkd3bNGci4gByP9p7kvuWt8knyO9Pc/ugvUaoGhnni+QXiC0gXxy5iPxA6QEpv4Fe0hypRuC7kPyc0onkYbnn6qF0aSJUg1j8jPzsyTHA65r+fVUNDPIy8vNB700pTcSdrRVl0CNJkiSp0XymR5IkSVKjGfRIkiRJajSDHkmSJEmNZtAjSZIkqdEMeiRJkiQ1mkGPJEmSpEYz6JEkSZLUaAY9kiRJkhrNoEeSJElSoxn0SJIkSWo0gx5JkiRJjWbQI0mSJKnR1qi7AJImT6vVOgk4st1uH9yTvhnwYeBZwJ2Bc4GPt9vtw7vmWQy8HHhqu90+sUpbG7gJuHe73b5oDKsgaUBVe3888IB2u31ulXZ/4K/AW4GFwMPa7faSatr6wJ+Bd7bb7SNardau1XzbATcCfwE+0W63vzfmVZG0CvNOj6R5odVqbQScAqwOPATYGNgXOLDVar2pZ/argA+Os3ySVsq1wAf6pH8KuB54T1faR4HfVgHPm4D/Az4JbFb9fADYaZSFldQ83umRNF+8mXy35mXtdvv2Ku37rVbrjcAXWq3Woe12+7oq/WvA81qt1k7tdvvYGsoqaTgHAW9ttVoPbbfbv+8kttvt21ut1iuA01ut1tHARsDzgO1ardYG5Isbr2y329/qWtaJ1Y8kDcw7PZLmi6cD3+kKeDq+DawLPKYr7WbgfcD+rVbL45g0//0L+AxwQO+EqsvbImAx8CXgDe12+1LgscDawNFjK6WkxvJkQdJ8sQkw1ZtY9fO/opre7VBgTeAloy+apDnwMeCRrVbriX2mfRq4FTi73W4fWaXdFbii86yPJK0Mgx5J88UVwILexFartSY54LmiO73dbv+H/BzA+4C1xlFASSuu3W5fA3wE+FCfabeTByg4qyv5SmCT6hggSSvFoEfSfHEC8D99uqs9j/ysz2l9PnMUeVCDV4+4bJLmxkHAlsBzBpj3VHJX1p1HWSBJk8GBDCTVZY1qqOmOg4CXAoe1Wq13kO/sPI38HMB7uwYxuEO73U6tVmsf4OvjKLCkldNut29qtVrvZ4DRF9vt9nWtVuvdwGdbrdbtwI/IF0AeD7yk3W7vMdrSSmoS7/RIqstB5BOYzs/RwOOqaX8CriE/9PzWdrv9yZkW0m63j2fZLjGS5rcvA1cPMmO73f40sCfwNuBS4J/kQQ+OHVHZJDVUpJTqLoMkSZIkjYx3eiRJkiQ1mkGPJEmSpEYz6JEkSZLUaAY9kiRJkhrNoEeSJElSoxn0aKJMTU3daWpqatHU1NSdhv3skiVLNluyZMmiJUuWbDbuvM2/3vwned3nQ/4rmOcGU1NTaWpqaoMV+fySJUu2X7JkSVqyZMn2k5b/JK/7pOdf97pLo2TQo0lzJ2C/6vewNqs+u0InfiuZt/nXm/8kr/t8yF+SpJVi0CNJkiSp0Qx6JEmSJDWaQY8kSZKkRjPokSRJktRoBj2SJEmSGs2gR5IkSVKjRUqp7jJII7fbWedNq+j7f3zfgT+/79v2n5Y2zOcHXeYwxpX/ym6nYZY56HYexbabaZmDzlv3OvWzsmWayaBlPXK7rQPyuzuAa4ENFyxYcN3AGa2A8xbutlJfasPUg2E+P6iVrRsrW84617OJ5uN2HtW+23rxkTHOti4Nyzs9kiRJkhrNoEeSJElSoxn0SJIkSWo0gx5JkiRJjWbQI0mSJKnRDHokSZIkNZpBjyRJkqRGM+iRJEmS1GgGPZIkSZIazaBHkiRJUqMZ9EiSJElqNIMeSZIkSY1m0CNJkiSp0Qx6JEmSJDWaQY8kSZKkRjPokSRJktRoBj2SJEmSGs2gR5IkSVKjGfRIkiRJajSDHkmSJEmNZtAjSZIkqdEMeiRJkiQ1mkGPJEmSpEYz6JEkSZLUaAY9kiRJkhrNoEeSJElSoxn0SJIkSWo0gx5JkiRJjWbQI0mSJKnRDHokSZIkNZpBjyRJkqRGM+iRJEmS1Ghr1F0ANU9RFPcFPgc8ErgWeH9Zll+ut1SSJEmaVN7p0ZwqimINoAR+AWwC7AJ8oiiKJ9VaMEmSJE0sgx7NtfsBWwIHlGX5n7IsfwccA+xea6kkSZI0sQx6NNei+ulNe3ANZZEkSZJ8pkdz7hzgEuC9RVF8EHgosDPwr1pLJUmSpIll0KM5VZblkqIo/hv4DDBFDoIWA9vNdV5TU1N3Au4018uVNDempqY2qP5cv/N7amqq77wLFiy4boDlSJqnqna63LYOs7d3aVQMejTnyrL8M7Bj5/+iKI4EfjWCrN4F7DeC5UqaG9f2/H/JLPP2doudbTmS5p/udjpbW4fZ27s0EgY9mnNFUTwYOA+4DXghOQB6/Qiy+hDwyQHn9aRJGr8Nq9/rk0+CNgeuX4nlDMK2LtVjQ1a+rUsjY9CjUXgh8BpgLeC3wNPKsrxyrjNZsGDBLcAtA8181Xlznb2k5eh0Yenq5nL9inRrGeYztnSpHgsWLLhuZdu6NEoGPZpzZVm+i9z1TJIkSaqdQ1ZLkiRJajSDHkmSJEmNZtAjSZIkqdEMeiRJkiQ1mkGPJEmSpEYz6JEkSZLUaAY9kiRJkhrNoEeSJElSoxn0SJIkSWo0gx5JkiRJjWbQI0mSJKnRDHokSZIkNZpBjyRJkqRGM+iRJEmS1GgGPZIkSZIazaBHkiRJUqMZ9EiSJElqNIMeSZIkSY1m0CNJkiSp0Qx6JEmSJDWaQY8kSZKkRjPokSRJktRoBj2SJEmSGs2gR5IkSVKjGfRIkiRJajSDHkmSJEmNZtAjSZIkqdEMeiRJkiQ1mkGPJEmSpEYz6JEkSZLUaAY9kiRJkhrNoEeSJElSoxn0SJIkSWo0gx5JkiRJjWbQI0mSJKnR1qi7ANI47P/xfael7fu2/cf2+UGXOYxx5b+y22mYZQ66nUex7WZa5qDz1r1O/axsmWYycFkXHznwMufKqNrFoMsdZ90c9PP9zMf1bKL5uJ1Hte/G39ql4XinR5IkSVKjGfRIkiRJajSDHkmSJEmNZtAjSZIkqdEMeiRJkiQ1mkGPJEmSpEYz6JEkSZLUaAY9kiRJkhrNoEeSJElSoxn0SJIkSWo0gx5JkiRJjWbQI0mSJKnRDHokSZIkNZpBjyRJkqRGM+iRJEmS1GgGPZIkSZIazaBHkiRJUqMZ9EiSJElqNIMeSZIkSY1m0CNJkiSp0Qx6JEmSJDWaQY8kSZKkRjPokSRJktRoBj2SJEmSGs2gR5IkSVKjGfRIkiRJajSDHkmSJEmNZtAjSZIkqdEMeiRJkiQ1mkGPJEmSpEYz6JEkSZLUaAY9kiRJkhptjboLoFVPURR7AguBBwHHlGW5W9e07YAvAQ8GLgL2LMvypzUUU5IkSQK806MVMwXsD3yxO7EoijWB7wElsDHwPuCYoig2HXsJJUmSpIpBj4ZWluXRZVkeC1zRM2kHYF3gw2VZ3lKW5TeBs4Bdx1tCSZIkaSmDHs2l7YAzy7K8vSvtD1W6JEmSVAuDHs2l9YBretKuAdYfe0kkSZKkigMZaC7dAGzYk7YhcP0oMpuamroTcKdRLFvSypuamtqg+rNz4WP9qampvvMuWLDgugGWI2meqtrpcts6zN7epVEx6NFcOgt4R1EUq3V1cXsI8I0R5fcuYL8RLVvSyru25/9LZpk3hliOpPmnu53O1tZh9vYujYRBj4ZWFMUa5LqzBrBaURRrA7cBJwE3AW8viuJAoCAPa73LiIryIeCTA87rSZM0fp07v+uTT4I2Z8Xu/PbeQZ6NbV2qx4asfFuXRsagRytiX5a9w7IrcFhZlguLoijI7+nZj/yenl3KsrxsFIVYsGDBLcAtg8x73igKIGlWnS4sXd1crl+Rbi1DfeYqW7tUhwULFly3sm1dGiWDHg2tLMtFwKIZpp0JPGqMxZEkSZJm5ehtkiRJkhrNoKfBImLtiCgj4ol1l0WSJEmqi0FPg6WUbgaeBKxed1kkSZKkuhj0NN+PgafXXQhJkiSpLg5k0HyHAodExPrAD4BLgdQ9Q0rpjDoKJkmSJI2DQU/zfb/6/b/VT3fAE9X/dn+TJElSYxn0NN+T6y6AJEmSVCeDnoZLKf287jJIkiRJdTLomRARsS3wcGAL4CsppX9FxNbApSml6+stnSRJkjQ6Bj0NFxHrAl8CXgDcTh6x70fAv4APARcCb6+tgJIkSdKIOWR1830ceArwTGAD8uAFHT8AnlFHoSRJkqRx8U5P8z0P2Dul9OOI6B2l7SJgy7GXSJIkSRoj7/Q033rAP2eYdudxFkSSJEmqg0FP8/0J+J8Zpj0b+O0YyyJJkiSNnd3bmu8DwHerAQ2OIr+M9JER8UJgd+BZdRZOkiRJGjXv9DRcSuk4YDfg8cCx5IEMPk8eze3FKaUT6yudJEmSNHre6ZkAKaVvA9+OiG2ATYCrUkpn11wsSZIkaSwMeiZISulc4Ny6yyFJkiSNk93bJkBEPDAivh4R50XEv6vfh0fEA+sumyRJkjRq3ulpuIh4NnA0cAn5mZ5LgbsDOwFnRMQu1XM/kiRJUiMZ9DTfx4AfATunlG7vJEbE3sB3q+kGPZIkSWosu7c1372B/+sOeACq/z9XTZckSZIay6Cn+f7EzIHNvYGzxlgWSZIkaezs3tZ8rweOjIgbgWNTStdGxIbAzsBbgRfWWjpJkiRpxAx6GigirgdSV9JawFeAr0TEEmDNKn0JcCKwwXhLKEmSNHoRkZY/F69IKS0eYRl2AhaklD4/qjxWxnwv31wx6GmmT7Bs0CNJkjSJHtPz/2nAQcARXWnnj7gMOwEPB+ZrULET87t8c8Kgp4FSSovqLoMkSVLdUkq/6v4/IgAu7k3vmWedlNJNoy6bxsuBDCRJkjSRImJRRNwQEY+MiNMi4mby89BExLYR8d2IuLZ6uftxEXGfns+/NSJOr+a5LCK+HxHbdE1fDLwceGBEpOpncWdaRJwVEU+NiD9FxE0R8fOI2DIi7hIR34qI6yLi/Ih4QZ+yPzsifl197vKI+L+IuHPX9B2q/J4WEUdExPUR8feIePsg5Wsa7/RMgIjYDdgV2AJYu3d6SunBYy+UJEnS/LAWubvbgcA+wJURsRVwKnmU24XA7cC7gRMj4n4ppVuqz24OfBb4O/kZ6dcCp0bENimlq4APAHcD7g+8uPrM5V1534P8WMIHyc9afwb4OnAjcDLwRWAP4PCI+FVK6e8AEfE84JvAocB+wGbAh4GNgd161u9g4GvkQax2Aj4SEX9KKf1ogPI1hkFPw0XEAcA7gd8B5wK31lsiSZKkeWVN4N0ppW92EiLiMOAq4GkppZurtFOBC4BXUj3/klJ6c9dnVgd+AlwGPA/4Qkrp/Ii4HLjXDF3q7gI8KaX052oZC8jPHH0kpfSBKu10YBdywPLpyH30Pg58M6X0qq78/wn8ICI+0Fle5TudRx8i4kTg2VX5fjRA+RrDoKf5dgfem1Lav+6CSJIkzVPH9fz/dOBI4D8R0Tlfvhr4PfCIzkwR8Wjy3ZLtyQFMxzYMZqonQDm3+n1CJyGldE1EXEbusdNZ9r2AvbrKBvBz8h2phwPdy/xx17JSRPyVfIdqovhMz2T4dd0FkCRJmqduTCnd0JO2CbAXuctZ988TqIKPiLgnOaBYHXgN8DhyQHQZfR4nmME1Pf/fOkt6Z5mbVL+P6SnbjVVZtuj57GzLmhje6Wm+LwEvIt9ulSRJ0rL6vebjKvLdn37DOF9f/X4GsB6wS0rpGoDqzstd+nxmLl1V/d6T/he2p0ac/yrJoKf53kPu/3kK+UWk1/RMTymlA8deKkmSpPnrBGA74PcppdtmmGcdcsC0pCvt+Uw/v57rOytnA5cAW6WUPjcHy5uIOz8GPc33FPJQhOsz/QVdkBurQY8kSdJS+wGnA8dHxBeAS8kjrT0J+EVK6RvAT6t5D42IQ4AHAm9l+gXmvwK7R8QLgb8BV6SULlrRglXP5bwFOKIaovo44N/k53yeDeyTUjp3tmWMsnzzVaTU746emiIizgbawBuBc1NKS5bzkUabmpraALgW2HDBggXXDfPZJUuWbE8eBe9ha6655hnjzNv8681/ktd9PuS/Ilb1dba+m38d+de97uMQEQnYO6X08er/RcDbUkrr9Zn3vsD+wI7kbmz/JA8j/dGu0dZeCiwCFgB/IJ9vHQV8P6W0ZzXPBsAhwNOAuwKHpZQWVu/DeXhKabuuPHcAfgY8IqX02670i7qXWaU9jTyM9sOrpIuAHwEfSCldO8uyjgU2SintMFv5lrsxVzHe6Wm+LYA39IwMIkmSNHFSStHz/yJy0NJv3r8B014K2jPP18jvwOm2Zc881wEv7PPZhX3STgKiT/qWfdJ+wizPbM+yrJ0GKV/TOHpb8/0SuF/dhZAkSZLq4p2e5tsHOCwibiU/lHdN7wzVG4MlSZKkRjLoab7Tq98H039IRshjukuSJEmNZNDTfLszc7AjSZIkNZ5BT8OllBbXXQZJkqQ6nLdwt5Fc+N168ZHTBgjQ/OaQ1ZIkSWokgx51eKen4SLiQpbTvS2ltNWYiiNJkiSNnUFP832X6UHPxuQ3Cgdw9NhLJEmSJI2RQU/DpZT26pceEWsBxwIXjrM8kiRJ0rj5ctIJlVK6FfgssHfdZZEkSWqKiDg2Im6NiLvVXRYtZdAz2TYB1q+7EJIkSU0QEZsCzwauB15cc3HUxe5tDRcRu/RJXgvYFtgT+Ol4SyRJktRYLwHOAw4DXgF8qtbS6A4GPc337RnSl5AHMXjDGMsiSZLUZK8ADge+DhwQEdunlM6ouUzCoGcS3LtP2s3AZcmXNEmSJM2JiHg48EDg6ymlf0TEyeQgyKBnHjDoabiU0t/rLoMkSdIEeAXwy5TSRdX/XwM+GhFvSyndUl+xBAY9EyEiVgceBWwOrN07PaX01bEXSpIkqSEi4k7AC4E7RcS/quQ1gLsABXBUXWVTZtDTcBGxPfnZnS3ILyPtlQCDHkmSpBW3E3mgqAcBN3alf5x8B8igp2YGPc33f8C1wMuBvwC31lscCVqt1knAo4H/ALcApwNvbLfb57ZarR3Iowre2POxl7fb7e+0Wq3FwL/a7fY7e5aZgG3b7fbZIy6+pOVotVo3dP27DnnwnP9U/x/QbrcPaLVamwKLgOcCGwNXAr8FPtFut0+tlnMRsBGwVbvdvqpKewZwcLvd3nLkKyIN7hXAV1NKF3QnRsSBwK8jYkFKaaqeogkMeibBA4FdU0o/r7sgUo+92u32wa1Wa13gEOArwOOraZe12+171Fc0SSuj3W6v1/m71Wr9ihykLO5KuwtwGvB74KnA34B1gWcAzwFO7VrcbcA7qh9pXkopPWOG9N/h+fa84E5ovnOBDeouhDSTdrt9Y6vVOhL4Vt1lkTQ2bwZuAl7Qbrdvq9JuIL9mofdVCx8F3tNqtT7dbre9Ui5phaxWdwE0cm8G3hUR96+7IFI/rVZrffJbq8+ruyySxuZpwNFdAc9s/gh8F3jPaIskqcm809N8nwXuAZwVEVPANT3TU0rp/429VBJ8stVqfYR8J/J8YOeuaZu2Wq1reuZ/TLvd/uu4CidppDYB7rhr02q1Hg38iHwx9qo+z+u8F/hTq9X6+NhKKKlRDHqa73fkEdqk+eYt1TM9WwM/AO4LnFlNm+2ZniXAmt0JrVZrza5pkua/K4AFnX/a7favgI2qgUyO7J253W6f32q1DgPeT373iSQNxaCn4VJKC+sugzSbdrt9XqvVehPw5Var9cMBPnIx8NCetK2A24F/zHX5JI3EicBOrVZrUbvdvn3Az3yA/JzqH0dXLElN5TM9kmrXbrd/CFwKvGaA2Y8Cnt5qtZ7TarXWaLVadwU+BHyn3W47JLu0avgksD7wjVardd9Wq7Vaq9VaB3jkTB9ot9v/JHfZfvuYyiipQQx6JM0XHyEPSbsO+ZmeG3p+3ghQvYfneeQ+/leQr/peyWABk6R5oN1uXwk8hvyc6c+A64Gzye/v2mWWj34UWH3U5ZPUPJGSj3tIkiRJai7v9EiSJElqNAcykCRJUiPtdtZ5I+nSdOR2W8colqvR8U5Pw0XEK2aZFhFxyDjLI0mSJI2bQU/zHRwRu/YmRkQAXwV2G3+RJEmSpPEx6Gm+1wJfjYhndxIiYnXgW8BzgKfXVTBJkiRpHAx6Gi6ldCj5nQZHRcSTI2It4LvADsBTUkq/rrN84zY1NbXB1NRUmpqa2mDYzy5ZsmT7JUuWpCVLlmw/7rzNv978J3nd50P+deRZ9zpb381/Eve9NEoOZDABUkoHRcR65GDnTOA+wJNTSmfVWzJJkiRp9LzT00ARcZfeH+AQ4AhgG2BnYKprmiRJklZCRJwUETdHxA0RcX1E/DYinlR3uZR5p6eZrgBmGqIxgF/2pPl2a0mSpJW3V0rp4IhYDXglcExEbJpS+k/dBZt0Bj3NtDszBz2SJEkaoZTS7RHxdeALwALg4pqLNPEMehoopbS47jJIkiRNqmqk3JeTg52pmosjDHomRkRsDGwHbAH8MKV0dUSsDdyaUrq93tJJkiQ1wicj4sPA2tX/u9u1bX5wIIOGi4jVIuIA4B/Az4GvAfeuJh8NvKeuskmSJDXMW1JKGwHrAI8CPh4R/1VvkQQQKfnoR5NFxP7AG4G9gROBc4GHp5TOiIjXAq9KKT28zjKOw25nnTetou//8X2nzbfv2/bv+/l+8w5jpuXOdT51G3Q9ZzLMPpnrz6/q276fYepzv3lXdptsvfjIgPzuDuBaYMMFCxZct1ILXY5+bX0Yo2jrMy1zXHWz7nY56DJnWu4o2ubK7qeVbUMru+9XZjuNat9tvfjIGGdbH9TKHhNmcuR2W0dvWkScBByZUjq4K+0o4F8ppTeMohwanHd6mm8hsE9K6RDgwp5p55Pf2SNJkqQ5FBEPAJ4A+F7EecCgp/nuCvx1hmmrA2uOsSySJElN9qnqPT03AD8Avlj9qGYOZNB85wJPI3dt67UDXn2QJElaaSmlHeoug2Zm0NN8BwJfjIglwLertM0j4jHkZ30W1lUwSZIkaRwMehoupbQ4Iu4CLAL2qZKPBf4N7JtS+lZNRZMkSZLGwqBnAqSUPhkRXwAeR37G5yrgtJTStfWWTJIkSRo9g54JkVK6ATi+7nJIkiRJ4+bobRMgIjaJiA9HxIkRcU5EPLBKf1NEPLru8kmSJEmjZNDTcBGxPfA3YDfgEmBr4E7V5Bbw5pqKJkmSJI2F3dua70DgNOC/gQS8tGvar4EX1FEoSZKkUTtyu62j7jJofjDoab5HALuklJZExOo90y4HNq2hTJIkSdLY2L2t+f4NbDDDtHsCV46xLJIkSdLYGfQ03/HAvhFx1660FBHrAG8CflBPsSRJkqTxMOhpvneQ7/T8DfgW+bme/YG/kN/Zs299RZMkSZJGz6Cn4VJKbeAhwEHAZsD55GDn68DDU0qX1Vc6SZIkafQcyKCBIuJtwC+A36WU/pNSugbYr/qRJEmSJopBTzN9pPp9c0T8FvglOQg6LaV0bX3FkiRJksbPoKeZNgEeCzyu+nkz8C7g9oj4CzkIOgX4ZUrp77WVUpIkSRoDg54GSildDRxX/RARawAPIwdAjwV2Al5TTWunlO5ZT0klSZKk0TPomQAppf8AvwZ+HRFHAo8HXgo8C2jVWTZJkiRp1Ax6GiwiAngwS+/wPI78QtJ/AqcBewOn1lZASZIkaQwMehooIvYjBzmPBtYB/kgObt4FnJpSurjG4kmSJEljZdDTTPsB/wYWA59OKZ1Xb3EkSZKk+vhy0mZ6E/B94L+BcyLioog4IiL2jIjtI8L9LkmSpInhnZ4GSikdBBwEEBFbsPSZnlcAB5Lf33M6ucvbqSmlH9RVVkmSJGnUDHoaLqX0D+DI6oeIuDN59LY9gXdWs1kPJEmS1Fie7E6AiNgQeAxLX1b6CODOwO3An2ssmiRJkjRyBj0NFBH3YekQ1Y8DtiU/v3UTcDrwaeCXwGkppWvrKqckSZI0DgY9zfS36vflwCnkUdx+CfyuelGpJEmSNDEMeprplcApKaVz6y6IJEmSVDeDngZKKR1adxkkSZKk+cL3tUiSJElqNIMeSZIkSY1m9zbNuaIo7gt8DngkcC3w/rIsv1xvqSRJkjSpvNOjOVUUxRpACfwC2ATYBfhEURRPqrVgkiRJmlgGPZpr9wO2BA4oy/I/ZVn+DjgG2L3WUkmSJGliGfRorkX105v24BrKIkmSJPlMj+bcOcAlwHuLovgg8FBgZ+Bfc53R1NTUBnO9TElzp6uNrt/5PTU11XfeBQsWXDfAciTNU1U7XW5bh9nbuzQqBj2aU2VZLimK4r+BzwBT5CBoMbDdCLK7dgTLlDR3etvoJbPM23uHeLblSJp/utvpbG0dZm/v0kgY9GjOlWX5Z2DHzv9FURwJ/GoEWW04xLyeNEnj12mj65NPgjYHrl+J5QzCti7VY0NWvq1LI2PQozlXFMWDgfOA24AXkgOg1891PkPdHr/qvLnOXtJydNpoVzeX61ekW4ttXZr/FixYcN3KtnVplBzIQKPwQvKVniuBhcDTyrK8stYSSZIkaWJ5p0dzrizLdwHvqrsckiRJEninR5IkSVLDGfRIkiRJajSDHkmSJEmNZtAjSZIkqdEMeiRJkiQ1mkGPJEmSpEYz6JEkSZLUaAY9kiRJkhrNoEeSJElSoxn0SJIkSWo0gx5JkiRJjWbQI0mSJKnRDHokSZIkNZpBjyRJkqRGM+iRJEmS1GgGPZIkSZIazaBHkiRJUqMZ9EiSJElqNIMeSZIkSY1m0CNJkiSp0Qx6JEmSJDWaQY8kSZKkRjPokSRJktRoBj2SJEmSGs2gR5IkSVKjGfRIkiRJajSDHkmSJEmNZtAjSZIkqdEMeiRJkiQ1mkGPJEmSpEYz6JEkSZLUaAY9kiRJkhrNoEeSJElSoxn0SJIkSWq0NeougDQO+39832lp+75t/4Hmm2nelc1/FPnUbdD1nMkw+2SuP7+qb/t+hqnPg7aRYRy5Up9eMaOogyub/0zLHFfdrLtdDrrMmZY7ira5svtpZdvQyu77ldlOo9p3dbR3aRje6ZEkSZLUaAY9kiRJkhrNoEeSJElSoxn0SJIkSWo0gx5JkiRJjWbQI0mSJKnRDHokSZIkNZpBjyRJkqRGM+iRJEmS1GgGPZIkSZIazaBHkiRJUqMZ9EiSJElqNIMeSZIkSY1m0CNJkiSp0Qx6JEmSJDWaQY8kSZKkRjPokSRJktRoBj2SJEmSGs2gR5IkSVKjGfRIkiRJajSDHkmSJEmNZtAjSZIkqdEMeiRJkiQ1mkGPJEmSpEYz6JEkSZLUaAY9kiRJkhrNoEeSJElSoxn0SJIkSWo0gx5JkiRJjWbQI0mSJKnRDHokSZIkNZpBjyRJkqRGM+iRJEmS1Ghr1F0ArXqKotgTWAg8CDimLMvduqZtB3wJeDBwEbBnWZY/raGYkiRJEuCdHq2YKWB/4IvdiUVRrAl8DyiBjYH3AccURbHp2EsoSZIkVQx6NLSyLI8uy/JY4IqeSTsA6wIfLsvylrIsvwmcBew63hJKkiRJSxn0aC5tB5xZluXtXWl/qNIlSZKkWvhMj+bSesA1PWnXAPcaRWZTU1MbjGK5kuZGVxtdv/N7amqq77wLFiy4boDlSJqnqna63LYOs7d3aVQMejSXbgA27EnbELh+RPldO6LlSpobvW30klnmjSGWI2n+6W6ns7V1mL29SyNh0KO5dBbwjqIoVuvq4vYQ4Bsjyq83wJqNJ03S+HXa6Prkk6DNWbGLILZ1af7bkJVv69LIGPRoaEVRrEGuO2sAqxVFsTZwG3AScBPw9qIoDgQK8rDWu4yiHMPcHj9vFAWQNKtOG+3q5nL9inRrsa1L89+CBQuuW9m2Lo2SAxloRexLDm7eTR6Z7Sbgi2VZLiEHOjuTn+V5P7BLWZaX1VROSZIkyTs9Gl5ZlouARTNMOxN41BiLI0mSJM3KOz2SJEmSGs2gR5IkSVKjGfRIkiRJajSDHkmSJEmNZtAjSZIkqdEMeiRJkiQ1mkGPJEmSpEYz6JEkSZLUaAY9kiRJkhrNoEeSJElSoxn0SJIkSWo0gx5JkiRJjWbQI0mSJKnRDHokSZIkNZpBjyRJkqRGM+iRJEmS1GgGPZIkSZIazaBHkiRJUqMZ9EiSJElqNIMeSZIkSY1m0CNJkiSp0Qx6JEmSJDWaQY8kSZKkRjPokSRJktRoBj2SJEmSGs2gR5IkSVKjGfRIkiRJajSDHkmSJEmNZtAjSZIkqdEMeiRJkiQ1mkGPJEmSpEYz6JEkSZLUaAY9kiRJkhrNoEeSJElSo0VKqe4ySGMzNTW1AXAtsOGCBQuuG+azS5Ys2R74HfCwNddc84xx5m3+9eY/yes+H/JfEav6Olvfzb+O/Oted2mUvNMjSZIkqdEMeiRJkiQ1mkGPJEmSpEYz6JEkSZLUaAY9kiRJkhrNoEeSJElSoxn0SJIkSWo039MjSZIkqdG80yNJkiSp0Qx6JEmSJDWaQY8kSZKkRjPokSRJktRoBj2SJEmSGs2gR5IkSVKjGfRIkiRJajSDHkmSJEmNZtAjSZIkqdEMeiRJkiQ1mkGPJEmSpEYz6JEkSZLUaAY9kiRJkhrNoEeSJElSoxn0SJIkSWo0gx5JkiRJjWbQI0mSJKnRDHokSZIkNZpBjyRJkqRGM+iRNFJFUUz0cWbS11+TZZLr+ySvu7QqiJRS3WWQRqIoiv8Cdge2A9YHrgfOAr5cluWPJyD/TYBd++R/VFmWV4w479ewdN3XBm5m6bp/YZR5V/nXtu5V/rWuf1c57ka1/mVZXj6mPGup93W2t0lu61X+E9ve6173rnKMva1X+dZa96VhGPSokYqieBOwD/BF4A/ANcCGwEOAVwEHlGV5UIPzfzJwDPnLpzf/7YCdy7I8aUR5HwDsAny8J++HAm8BjinL8t2jyLvKv7Z1r/Kve/3XBN4PvAK4GxBAAi4HvgLsV5blkhHlXUu9r7O9TXJbr/Kvu75P8rGutrZe5V9r3ZeGtUbdBZBGZG9gx7Isz+pJ/05RFN8EjgdGeTCuO/+DgFeXZfmt3glFUewKfA544IjyfhWwfVmWl/Sk/64oiuOBM4CRnQhQ77pD/ev/OWBb4CVMPxF7TzX91SPKu656X2d7m+S2DvXX90k+1tXZ1qH+ui8NxaBHTbUBcOEM0y6qpjc5/3uTr372811g8QjzXhO4aYZpNzH6406d6w71r/+uwFZlWV7dlXYlcEJRFGcA5zO6E6G66n2d7W2S2zrUX98n+VhXZ1uH+uu+NBSDHjXVj4DDi6LYpyzLv3YSi6LYFvgg8MOG5/8ncveKj/SZthdw5gjz/iZwXFEU7wP+yLJdHt4DHDnCvKHedYf6138J+WTj6j7TNgD+M8K866r3dba3SW7rUH99n+RjXZ1tHeqv+9JQDHrUVHuQb+3/viiKAK4lfwkk4NvAnhOQf1kUxV7kL/1ryF/GDyJfgSxGmPcbgP3I/bwXkNc5gDZwGPC+EeYN9a471L/+hwAnFkXxSab3s38z8H8jzLuuel9ne5vktg711/dJPtbV2dah/rovDcWBDNRoRVGsC2wDrAfcAJxbluWNk5B/URRrAE8m92fv5H8WcFJZlqO+Atgpw0advMuyvGYceVb51r7uVTk2op71fxWwkPwgd/f6Ly7L8ktjyL+Wel9ze5votl6VYyMmtL1PaluvylDr96w0KIMeNV5dQ3nOl/zrUhTF+sD9WTqM6V/Lsryh3lKNj+tf2xC6tbW3SW3rMNn1fZLXvWOS675WHQY9aqSuoTx3BzZh/EN51pp/VYa63peyIbnbxS7ArSztcrEW8B3gdWVZXjuq/Ksy1PnOltrXvyrHtiy7/meWZXn2iPOspd7X2d4mua1Xedde3yf5WFeVY+xtvcq39rovDcO3B6upPgc8HngxcHfyl9Cm5KE9H1dNb2z+1fsTvgr8jdznfHfgvcC5wGFFUbxhhNl/ifzl94CyLNcry3LzsizXJ3c9iWr6yNS87lD/+t+zKIpfkYfL7V7/M4qiOK0oii1GmH1d9b7O9jbJbR3qr++TfKyrs61D/d+z0lAcyEBNVfdQnnXnX+f7E/4L2Kwsy393J5ZleV5RFHsAUyPKt6Pud0fUvf5fBk4FntrdxaYoivXID1YfCjx1RHnXVe/rbG+T3Nah/vo+yce6Ots61F/3paF4p0dN1RnKs59xDOVZd/51vj/hOmDrGaZtTe5+MUp1vzui7vV/DPCu3mcKqv/3AR49wrzrqvd1trdJbutQf32f5GNdnW0d6q/70lC806Omqnsoz7rzr/P9CR8mX+k7lOnr/gpg0QjzhvrfHVH3+v+L3OXkxD7THgdcOsK866r3dba3SW7rUH99n+RjXZ1tHeqv+9JQHMhAjVX3UJ515l89YPs54HnkvuXT3p8wygdsi6J4GvBy+q/7CaPKt8q71nWvylDn+j+P3K3lh0w/EXkm8IqyLL8zwvxrqfc1t7eJbetVGSa2vU9yW6/KUPuQ2dKgDHqkBpvk9ydM+LpvS364uPdE5PBxjOqk8Zvk+g6Tu/62dWlwBj2SJEmSGs2BDNR4RVH8oU/amROU/2f7pH1+THlf1SftunHkXeVV27pXedW9/psPkjaivP/QJ23k9b7O9jbJbb3Kq+76PsnHutraepXXH/qkja3uS4Mw6NEk+EiftA9NUP4xYNooPLdP2rPGlDfUu+5Q//r/qU/aX8aUd131vs72NsltHeqv75N8rKuzrUP9dV9aLru3SVJDFUWxRVmW/1hemqRVm21dWj6DHjVa9ZDndsD65HcmnNU9rGnT86/KcLdO/mVZXj6mPNckvxRvmXUHTijLcsk4ylCVY+zrXuU7L9a/LnXV+zrb26S29SrfeVHfJ/lYV6f5UPelQRj0qJGKorgn8C3g/5HfCn0NeSjP+wB/BJ4/yitg8yD/NYH3k98VsWmVnIDLga8A+43qC7koigcDJbn77J9Yuu4Prsrw3LIsR9bXu851r/Kvdf2rMmxCflt674nYUWVZXjHCfGup93W2t0lu61X+E9ve6173qgy1tPUq71rrvjQsX06qpvoycCrw1O63VRdFsR7wPvK7DZ7a4Pw/B2wLvIRl39/wUOA91fRXjyjvLwKfLsvywN4JRVHsBXwJeNSI8oZ61x1qXv+iKJ4MHEM+8fkDcDF5/V8EHFAUxc5lWZ40ouzrqvd1trdJbusw2e19kts61F/3paEY9KipHgM8pyzLW7oTy7K8oSiKfYArG57/rsBWZVle3ZV2Jfnt4WeQr8qN6kTggcC0UZQqnyO/JX2U6lx3qH/9DwJeXZblt3onFEWxa1WGB44o77rqfZ3tbZLbOtRf3yf5WFdnW4f66740FEdvU1P9C3j8DNMeB1za8PyXkN9K3s8GwH9GmPeFwPNnmLYrcMEI84Z61x3qX/97k6/+9vNdYMsR5l1Xva+zvU1yW4f66/skH+vqbOtQf92XhuKdHjXVO4Fji6L4Ict2eXgI8Exy/+8m538IcGJRFJ/sk/+bgf8bYd57ktf9TX3yvi+w0wjzhnrXHepf/z8Bb6H/ELJ7AaN8xqCuel9ne5vktg711/dJPtbV2dah/rovDcWBDNRY1YgyLyY/4LkecAO57/PhZVmePQH5vwpY2Cf/xWVZfmnEed8F2KVP3keXZTntJX4jyL+2da/yr239i6LYjvxw9Trkk55ryCciDwJuAoqyLP88wvxrqfd1trdJbutV/hPb3ie5rVdlqLXuS8Mw6JGkhimKYg3gyeT+/N0nIieVZTnq7k6SxsS2Lg3OoEeNVedQnvMh/6oMve9POHNMV54fALyc6et+WFmWY3lLeF3rXuVd+/rXpcbhsuscundi23qVd+31fZKPdXWaD3VfGpRBjxqpz1Ce17C0r/F2wEiH8pwH+df53pIXkIdyLZm+7s9lhtGG5jD/ut+bUuv6V2X4L2B3pp+IfLksyx+PMN9a6n2d7W2S23qV/8S297rXvSpDLW29yrvWui8Ny4EM1FR1D+VZd/51vj/hAPJL+X7eO6EoiicCi8knKaNS97sjal3/6qHqfcgnY0ex7InIYUVRHFCW5UEjyr6uel9ne5vktg6T3d4nua1D/XVfGopBj5pqeUN5Lm54/nW+P+HuwGkzTPtNNX2U6n53RN3rvzewY1mWZ/Wkf6coim8Cx5NPVkahrnpfZ3ub5LYO9df3ST7W1dnWof66Lw3F9/SoqTpDefazF6MfyrPu/Ot8f8IpwCeKoljm3RnV/x+tpo9S3e+OqHv9NyC/P6Sfi5j5nSZzoa56X2d7m+S2DvXX90k+1tXZ1qH+ui8NxTs9aqo9gLIoir2YYSjPhudf5/sTXgl8A7i8KIq/d+V9L+B0YLcR5g31vzui7vX/EXB4URT7lGX5105i9aD3B4EfjjDvuup9ne1tkts61F/fJ/lYV2dbh/rrvjQUBzJQY1VDee7A9PcHjGUoz3mQf93vDtm6N++yLM8bdb5V3rW/O6Ku9S+KYkNyX/rnAQFcS77im4BvA3uWZXntCPOvpd7X2d4mva1XZZjY9j6pbb0qQ611XxqGQY8kNVBRFOsC27D0ROTcsixvrLdUkuaabV0ajEGPJEmSpEZzIANJkiRJjWbQI0mSJKnRDHqkMSiKYvOiKB5ddzk0PkVRHDZD+qHjLovGx7Y+eWzr0qrBIavVaEVRbAF8ANie/JDnHcqy3GoM+beAI4FHAP8B1qveVP30siz3GFGe7x1kvrIs3z+K/LvKcSF5FKF+eY9k2xdFsV9Zlu+r/j5gpvnKstxnFPn32Bl4eZ/0sQ7jWhTFXZhe9y8ecZ61tLs62/skt/WqLJPc3ie2rVf51vo9Kw3KoEdNdwT55XX7AXWMZnMI8DPgycDlVdoJwMdGmOe2XX+vRf7iPRP4O3BP8jsUyhHm3/Hanv83A/YEDh9hnvfoyW/siqJ4dfXnGl1/d9yHpfVg1OXYEfgKsDl5ONuOBKw+4uzrand1tvdJbuswge3dtn6Hur9npYEY9Kjp/h/w5BrfF/Bo4L/LsrytKIoEUJbl1UVRbDSqDMuyfGHn76rbxSvLsvxqV9pLgR1HlX9XOY7vTSuK4kTgO8CnRpTn66p8VgMOBn5fluWto8hrFp3tv1bX35BPQC4FFo6pHP8HHAgcxvhPROpqd3W294lt61VZJrG929azur9npYEY9KjpfgvcF/jr8mYckSuBBcA/OglFUWwFTI0p/52Y/kbyI4DPMr4v5G5XAfcbdSZlWd5eFMWJZVmut/y55zzvJwMURfHhsizfOe78u2wKfLosyzreS1BXu6uzvdvWp2t0e7et36Hu71lpIAY9arpfAj+oHij9V/eEsiy/MIb8DwGOLopiX2C1oiieCBxAfov2OPwD2I188tOxK3DJqDPu091jXfKbw08Zdd6V04uieFBZlmeOKb9ldJ8EFUWxJl3dTsZ0NfpbwHMZX/embnW1uzrb+8S2dZjs9j7hbR3q/56VBmLQo6Z7AnARuZ99twSM/GBcluUni6JYAnwSWJPcBeNg4POjzrvyBuDYoijeDFxM7ue/DfnB21F7Yc//NwA/JXfDGIdTgR8WRfFV8jMOd1wFHccXcVEUm5O7nTyRnod7GU8/+7sA3yyK4jSmn4i8aMR519XuamvvE97WYYLb+4S3daj5e1YaVKRU191QSeNQjejzbHLXmynguLIsr6q3VKNXFMXPZpiUyrJ8yhjyPw64FvgIcDL5xOC9wPFlWX5xDPnvN9O0zohXapZJbetQb3u3rUurBoMeNV7V3eDxQIvc1eOUsiyXjCnvJ840rSzLk8dRhqocmwObl2X5q3HlWeW7Hvlqc+8wpiNb96IoirIs6+rm0V2OK4EtyrK8sSiKa8qy3Kgoio2B08qyvH/d5Ru1utpdjflOdFuv8p7I9j7pbR3q/Z6VBmX3NjVaURT3A44D1iF3+dgCuKUoimeXZXn2GIrwzZ7/70Lu730F+WrsSNXx7pCuvF9Efs7hdpYdUSgx2nU/HNigqxwXl2V5zxHmN5P/ALdVf19TFMWmwHXkk4KRq/MkvK52V3N7n9i2XuU/ye19Ytt6lX/d37PSQAx61HSfI7+/4ENlWaaiKAJ4Z5U+jmGbl3l3RHU17P3kPufjUMe7Qzo+ArysLMtjxpBXt+j5f/0x59/xa3JXo6OB44GjgJvIIx2NQ50n4XW1u9ra+4S3dZjs9j7JbR1q/p6VBrVa3QWQRmx74KOdoTyr3x8DHlpHYarb/e8F3jOmLB8NvK96f8Id7w4BNhpD3usA3x1DPr16++zW1Yf3xcCJ1d97kU9A/wiM48FiyrLcrPuH3OXoE+QT8VGrq93Nm/Y+YW0dJru9T3Jbh3nU7qTZeKdHTXcp+cB7elfaQ4DLailN9v/IozuNQ53vDjmY/Jb2cY1e1bFmURR7sPQK8J16h9Mdx+htZVle3/X3TcAHRp3nbMqyXFIUxXvJoywdPOLs6mp38629T0pbhwlu7xPe1mH+tTupL4MeNd2HgeOr9wdcBGxJflHfW0eZaVEU7yzL8sPVEKLdVx7XBe4P7DvK/LuM9d0hPesbwMOKongb04dRfewo8q/8mmWvsP6G6W9LH9lJUFEUzwCuK8vy1Or/+wBfBbYjD6u7sCzLS0eV/3KM6yS8lnZXR76T2tbB9m5bv0Nd7V0aikGPGq0sy8OKovg7ufvBM4E28D9lWZ404qz3IX8RHMKyJ0I3AH8sy/K8EecPzPzukLIsR3UiNI6rirMqy3KHmovwfuDNXf9/EbiefGL2KnK3j5eNuhB1noTX1e5qyndS2zrY3ie+rUOt37PSUByyWhqBoiiuL8uyrgfoKYri8+SHmn9eluVYuxh0rnyPM8/5pCiKq4C7V11MNgH+CWxVluU/qlGdzijLcvMxlOPlPUljPQmfFJPc1qv8J7a929alVYt3etRIvX26+xlxP+81iqJ4KdNHFurO/6sjzH998oOsraIozgFOIp8YnVSW5eWzfXAOdK58T6pg6fC1jwIuKcvyHwBlWV5WFMWG4yhEWZaHjSOfbnW1u5rb+yS3dZjs9j6xbR1qb3fS0Ax61FQHA38j32bvdzIy0uc6yN1L/neW6Ync93skyrJ8KdzxIPOTgCeSh5S9V3Vi9LOyLF8/ouxnPPmbEGeSu7ccXv3+SWdCURRbANeMMvM+zxlsBXyN8TxnUFe7q7O9T3Jbh8lu75Pc1qH+71lpKAY9aqrPAM8HbgEWA8eUZXnrGPO/sSzLx4wxv77KsrwAuAA4tOpu8RJgb/IoS6M6Ear7ynfd3gl8v+p2dDPQ/RD3C4BTRpx/73MGX2J8zxnU1e7qbO+T3NZhstv7JLd1qP97VhqKQY8aqSzLvapRhJ5NHkXm00VRHAMcWpblb2ot3JgURXEP8pXfzs/6wC+A9wGjfEt3rVe+61aW5alFUdwL2AY4t3s4W+B7wBEjLsLW5BGsqJ4zeAJLnzM4HThjVBnX1e4mvb3X2NZhgtv7JLd1sN1p1eNABpoI1RfC24G3AE8d9agy8+Dh5nPIJyM/I5/0/KK6EjyOvK8ry3KDceSl6YqiuBq4a1mWtxdF8Wzgs2VZ3rtr+tjq5rjbXR35TnJbr/K3vddkPrX1Kr9a2rs0KO/0qNGKorgTsBP5KtRDye+sOGvU+dZ5ElT5J/Ag4F7Vz9+LomiXZXlLvcXSGNT6nEGVTy3tro58beuqUe1tvcqrlvYuDcugR41UFMVjgJcDu5Af6DwEOK4syyW1FmxMyrLcoSiKtcgjCj0JeDf5xYF/IV8NPrksyx+NKPtJfrB5PqjtOYO62t0kt/ea2zrY3utU6zNFk9zutGqye5saqSiK24FzgK8Dfd9dMWlDaRZFsS7wOuBtwKZlWa5ec5E0IkVRrE+f5wyKorgfcH1ZllMjyreWdmd7X5ZtfXLU1darPGx3WqV4p0dNdTL5AdodZ5je+KE0i6JYE3gkSx9ufiz5quxp5Hd5qKGqk5/f9Uk/Z8RZ19XuJrq929YnV41tHSa83WnV450eqYGKovgpubvL7eRuBycBPwd+U5blf2osmqQ5ZFuXpMF4p0dqpuPJb0o/vSzL25Y3s6RVlm1dkgbgnR5JkiRJjbZa3QWQJEmSpFEy6JEkSZLUaAY9kiRJkhrNoEeSJElSoxn0SJpoEZEG+FkYESdFxPfrLu9sImKHqrwPr7ssg6rKvM8IlrswIl40x8t8UUT8LSKWRMQf5nLZc2VVqKeSVAeHrJY06R7T8/9pwEHAEV1p5wO/Aeb7kMBnkNfnr3UXZAg7AG8DDpjj5S4EbmDZ/bjCImI94CvAN6plXzcXy5UkjYdBj6SJllL6Vff/EQFwcW86cPnYCrWCUkrXAb3lnigRsU5K6aYRLHpL4E7A11JKp4xg+ZKkEbJ7myQNoLfbUEQsiogbIuKhEXFaRNwUEWdU/68dEf8XEVdHxCURsVef5T0mIn4aEf+OiGsj4oiI2HQ5ZVgzIj4WERdHxC0R8c+I+F5EbFhNn9a9rfr/7VV5L42IKyLi0Ii4c8+yWxHx1WqemyLi7Ih4U888CyPiTxFxc0S0I+KDEbH6csq8eUR8q1ruzRFxYUQc2NmGwH7Anbu6Ep5UTbt/RBwZEf+IiBsj4i8R8daIWK1r2Vt2dT/8YkRcCfymWsaTgGd3LXfRLGVcLSL2jYiLqu16dkS8pmv6IuDM6t8TZ1teRJwfER/o+v9/qvk/1pX2X1Xa3brSnh0Rv662/eVV/endRxtFxOer/X5LRPwuIp6+nO2/TkQcFxEXRMRWs80rSU3mnR5JWnFrAocBBwKXAh8BjgZOAS4Dng/8N3BgRPwmpXQq5IAHOAn4AfAC4M7A/sB3md7drtu7gNcC7wD+DGwCPJ18B2I2ewK/AF4ObAN8rCrvO6vy3JXcrQ/g3cAFwH2B+3QWEBFvAT5aretbgW2BDwKrd5Yzg68CC4A3VnneE+gEZV8CNgdeBDylSut0G2sB5wBfB64HHgK8D1iv+t3tQ8BxwAvJF/MuBg4HbiR3nQO4ZJYyfgx4E3kfnAo8Bzg4ItZMKX22Kuf51bq8ntyNcKblnQw8sev/JwE390k7O6V0OUBEPA/4JnAoOQjcDPgwsDGwWzXPWsBPgLuT91EbeAlwXERsn1I6kx5Vl7zvVct7QkqpPcs2kKRmSyn5448//vhT/QAJeFuf9JOA73f9v6ia95ldac+p0o7sSludfLJ/YFfaz8mBUXSlPQC4HXjWLGX7PvCdWabvUOX/8J71+XXPfIuB87r+/yD5xHzLGZa7PjnwOKAn/bXkwOKus5TpBuANs0xfBNywnH0S5It0+wBTXelbVuv3w+Xtr1mWvQlwK/ChnvQjyIHr6tX/D6ny2mE5y3sFcBNwp+r/P5CfEVsCrFel/RI4pGvdLgKO6FnOM6r68MCu5S4BHtAz36+Ab/WuNzlg+lWV/6Z1tSd//PHHn/nyY/c2SVpxtwMndv1/bvX7hE5CSuk28l2CLQAiYl3gccBRwOoRsUZErFF99h/AI2bJ7wzgWVVXtUd0d/Vajp/0/P8X8h2Wjh2Bn6aULprh848l32E5qlPeqswnAOsA2y2nzG+LiNdFxNYDlpeqi+D7IuI84BbyCf8Hgc2qOxjdjht0uX08inzH7qie9G8CdyPfGRvGycDawCMjYiPgQcDnyHewHhcRa5P38cnV/NsA9wK+1bNtf06uX527Yk8nd7E7t2e+nzC9zmwC/Kz6+8kppcuGXAdJahyDHklacTellG7t+r/z9zU9891KPhGGfAV+dXI3sSU9P/ekCo5m8EFyF7qXk0eT+1dE7BeRR1+YRb/ydHeJuyswNcvnN6l+n9FT3r9V6bOV+QXkwPCDwN+q52V2WU55Ia/n3sAXgWeRT+z3r6at3TPvpQMsbyYbz7CMzv93GWZhKaXzyV3Pngg8HrgspXQ2+e7OE4FHA2uxNOjpbNtjWHbb3kiuJ1t0zfdQpteZfZm+/bcB/h/wjZTS1cOUX5Kaymd6JGm8riF3kzoAOLbP9Ctm+mBK6RZyd7BF1V2T3av/LwC+thJlupL83M1Mrqp+70K+G9Xrwpk+mFL6J7B7RLwKeBj5JP2bEXG/lNIFs+S5K7kL2Ec6CRHx7JmymWU5y9NZt03JwUrH3XumD6PzXM+G5GepOmk7k+9a/T2l1NmOneXvCfy6z7Kmuub7E/DKAfI/lXwX7pMRcWVK6fCh10CSGsagR5LGKKX074g4Ddg2pbTvSiznPGCfapSxbVeyWCeQu6DdM6V0cZ/pp5HvPGyeUjpmRTJIKd0OnB4R+wIFsDU5WOu969SxDkvvnFGNErfbEFl2312bzW/Id0x2BX7flf588jM95/b70HKcTB4c4a7kwQkgd1c7gNzD4uSuec8mD4qwVUrpc7Ms8wTyHa+plNJsd+UASCl9KiLWARZHxM0ppW8PvxqS1BwGPZI0fnsDP42IbwJHAleTn7F5GnBoSumkfh+KiGOB35FPzv8NPJfcPeunK1meA4GXASdXwy1fAGwFbJNSekdK6ZqIeC/w0YjYnPyw/G3VPP8N/E9K6cY+5d0QOJ58F+occreuN5Dvdp1RzfZXYI1qeOxTgetSSueQn1XZIyL+Qr779b8sf5S6bn8FXh4RzwX+yQzBQkrpiog4CNg7Im4mP/z/LPKIcm+onska1snkZ6AeRh6AAPI+u4U8Ot9XuvJP1ch4R1RDVB9H3rf3Ap4N7JNSOpc8ctxrgJMi4uPkYGwjcpe3tVJK7+qzbh+qAp8jqsDn+73zSNKkMOiRpDFLKZ0aEY8nD718KDkYuIT87Mt5s3z0FPIdiLeSj9/nAC9OKZ0wy2cGKc+VEfE48tDPHwXWJY8o9vmueT4REW3gLeTAZQl5gIbv03VHpsfN5Ifv30B+Xukm4LfA01NKnW5836vyeRe5i9nJ5FHo3gAcTB757EbyiHPHkJ/xGcRHyXeTvkoODt5H7grYz97kQOxV5O53FwGvTSkdMmBey0gp/SUiLic/k3NWlXZbRJxCHpXt5J75j4qIa8hDUb+kSr4I+BHVs0UppVsi4inVOrybPAz1FeRg6vPMIKX03irw+XZEPGdl64okraoipZXpCi1JkiRJ85ujt0mSJElqNIMeSZIkSY1m0CNJkiSp0Qx6JEmSJDWaQY8kSZKkRjPokSRJktRoBj2SJEmSGs2gR5IkSVKjGfRIkiRJajSDHkmSJEmNZtAjSZIkqdEMeiRJkiQ12v8HlyTuAD391VIAAAAASUVORK5CYII=",
+                        "text/plain": [
+                            "<Figure size 640x480 with 4 Axes>"
+                        ]
+                    },
+                    "metadata": {
+                        "needs_background": "light"
+                    },
+                    "output_type": "display_data"
+                },
+                {
+                    "data": {
+                        "text/plain": [
+                            "<ggplot: (305061328)>"
+                        ]
+                    },
+                    "execution_count": 10,
+                    "metadata": {},
+                    "output_type": "execute_result"
+                }
+            ],
+            "source": [
+                "# Stratified - city + day of week + hour of day level\n",
+                "config = {\n",
+                "    \"time_col\": \"time\",\n",
+                "    \"switch_frequency\": \"4h\",\n",
+                "    \"perturbator\": \"uniform\",\n",
+                "    \"analysis\": \"ols_clustered\",\n",
+                "    \"splitter\": \"switchback_stratified\",\n",
+                "    \"cluster_cols\": [\"time\", \"city\"],\n",
+                "    \"strata_cols\": [\"day_of_week\", \"hour_4h\", \"city\"],\n",
+                "    \"target_col\": \"y\",\n",
+                "}\n",
+                "\n",
+                "power = PowerAnalysis.from_dict(config)\n",
+                "\n",
+                "plot_calendar(power.splitter, df, \"stratified calendar (day of week + hour of day + city level)\")"
+            ]
+        }
+    ],
+    "metadata": {
+        "kernelspec": {
+            "display_name": "venv",
+            "language": "python",
+            "name": "python3"
+        },
+        "language_info": {
+            "codemirror_mode": {
+                "name": "ipython",
+                "version": 3
+            },
+            "file_extension": ".py",
+            "mimetype": "text/x-python",
+            "name": "python",
+            "nbconvert_exporter": "python",
+            "pygments_lexer": "ipython3",
+            "version": "3.8.6"
+        },
+        "orig_nbformat": 4
+    },
+    "nbformat": 4,
+    "nbformat_minor": 2
+}
diff --git a/mkdocs.yml b/mkdocs.yml
index d89a1bd2..20c703d0 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -11,7 +11,10 @@ nav:
     - Index: index.md
   - Cupac example: cupac_example.ipynb
   - Custom classes: create_custom_classes.ipynb
-  - Stratified switchback: switchback.ipynb
+  - Switchback:
+      - Stratified switchback: switchback.ipynb
+      - Switchback calendar visualization: plot_calendars.ipynb
+      - Visualization - 4-hour switches: plot_calendars_hours.ipynb
   - Multiple treatments: multivariate.ipynb
   - AA test clustered: aa_test.ipynb
   - Paired T test: paired_ttest.ipynb
@@ -22,6 +25,7 @@ nav:
       - Pre experiment outcome model: api/cupac_model.md
       - Power config: api/power_config.md
       - Power analysis: api/power_analysis.md
+      - Washover: api/washover.md
 plugins:
   - mkdocstrings:
       watch:
diff --git a/setup.py b/setup.py
index 3f961f14..5e8a9671 100644
--- a/setup.py
+++ b/setup.py
@@ -38,6 +38,8 @@
     "mkdocstrings==0.18.0",
     "jinja2<3.1.0",
     "mkdocs-jupyter==0.22.0",
+    "plotnine==0.8.0",
+    "matplotlib==3.4.3",
 ]
 
 dev_packages = test_packages + util_packages + docs_packages