From 8c6df3e431cf6212786ea5fc6f3c2bce0f5575d7 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=C3=96yk=C3=BC=20S=C3=BCoglu?=
 <oeykue.sueoglu@helmholtz-munich.de>
Date: Wed, 26 Nov 2025 19:30:06 +0100
Subject: [PATCH 01/12] sankey plots and their tests

---
 ehrapy/plot/__init__.py   |   1 +
 ehrapy/plot/_sankey.py    | 182 ++++++++++++++++++++++++++++++++++++++
 tests/plot/test_sankey.py | 120 +++++++++++++++++++++++++
 3 files changed, 303 insertions(+)
 create mode 100644 ehrapy/plot/_sankey.py
 create mode 100644 tests/plot/test_sankey.py

diff --git a/ehrapy/plot/__init__.py b/ehrapy/plot/__init__.py
index aa8026a10..b09a02e7a 100644
--- a/ehrapy/plot/__init__.py
+++ b/ehrapy/plot/__init__.py
@@ -1,6 +1,7 @@
 from ehrapy.plot._catplot import catplot
 from ehrapy.plot._colormaps import *  # noqa: F403
 from ehrapy.plot._missingno import *  # noqa: F403
+from ehrapy.plot._sankey import plot_sankey, plot_sankey_time
 from ehrapy.plot._scanpy_pl_api import *  # noqa: F403
 from ehrapy.plot._survival_analysis import cox_ph_forestplot, kaplan_meier, ols
 from ehrapy.plot.causal_inference._dowhy import causal_effect
diff --git a/ehrapy/plot/_sankey.py b/ehrapy/plot/_sankey.py
new file mode 100644
index 000000000..d3567a606
--- /dev/null
+++ b/ehrapy/plot/_sankey.py
@@ -0,0 +1,182 @@
+from __future__ import annotations
+
+from typing import TYPE_CHECKING, Dict, List
+
+import ehrdata as ed
+import holoviews as hv
+import numpy as np
+import pandas as pd
+from holoviews import opts
+
+hv.extension("bokeh")
+
+if TYPE_CHECKING:
+    from anndata import AnnData
+    from ehrdata import EHRData
+
+
+def plot_sankey(
+    edata: EHRData | AnnData,
+    *,
+    columns: list[str],
+    show: bool = False,
+    **kwargs,
+) -> hv.Sankey:
+    """Create a Sankey diagram showing relationships across observation columns.
+
+    Args:
+        edata : Central data object containing observation data
+        columns : Column names from edata.obs to visualize
+        show: If True, display the plot immediately. If False, only return the plot object without displaying.
+        **kwargs: Additional styling options passed to `holoviews.opts.Sankey`. See HoloViews Sankey documentation for full list of options.
+
+    Returns:
+        holoviews.Sankey
+
+    Examples:
+        >>> import ehrdata as ed
+        >>> edata = ed.dt.diabetes_130_fairlearn(columns_obs_only=["gender", "race"])
+        >>> ep.pl.plot_sankey(edata, columns=["gender", "race"])
+
+    """
+    df = edata.obs[columns]
+
+    labels = []
+    for col in columns:
+        labels.extend([f"{col}: {val}" for val in df[col].unique()])
+    labels = list(dict.fromkeys(labels))  # keep order & unique
+
+    # Build links between consecutive columns
+    sources, targets, values = [], [], []
+    source_levels, target_levels = [], []
+    for i in range(len(columns) - 1):
+        col_from, col_to = columns[i], columns[i + 1]
+        flows = df.groupby([col_from, col_to]).size().reset_index(name="count")
+        for _, row in flows.iterrows():
+            source = f"{col_from}: {row[col_from]}"
+            target = f"{col_to}: {row[col_to]}"
+            sources.append(source)
+            targets.append(target)
+            values.append(row["count"])
+            source_levels.append(col_from)
+            target_levels.append(col_to)
+
+    sankey_df = pd.DataFrame(
+        {
+            "source": sources,
+            "target": targets,
+            "value": values,
+            "source_level": source_levels,
+            "target_level": target_levels,
+        }
+    )
+
+    sankey = hv.Sankey(sankey_df, kdims=["source", "target"], vdims=["value"])
+    default_opts = {"label_position": "right", "show_values": True, "title": f"Patient flows: {columns[0]} over time"}
+
+    default_opts.update(kwargs)
+
+    sankey = sankey.opts(opts.Sankey(**default_opts))
+
+    if show:
+        from IPython.display import display
+
+        display(sankey)
+
+    return sankey
+
+
+def plot_sankey_time(
+    edata: EHRData | AnnData,
+    *,
+    columns: list[str],
+    layer: str,
+    state_labels: dict[int, str] | None = None,
+    show: bool = False,
+    **kwargs,
+) -> hv.Sankey:
+    """Create a Sankey diagram showing patient state transitions over time.
+
+    This function visualizes how patients transition between different states
+    (e.g., disease severity, treatment status) across consecutive time points.
+    Each node represents a state at a specific time point, and flows show the
+    number of patients transitioning between states.
+
+    Args:
+        edata: Central data object containing observation data
+        columns: Column names from edata.obs to visualize
+        layer: Name of the layer in `edata.layers` containing the feature data to visualize.
+        state_labels: Mapping from numeric state values to readable labels. If None, state values
+        will be displayed as strings of their numeric codes (e.g., "0", "1", "2"). Default: "None"
+        show: If True, display the plot immediately. If False, only return the plot object without displaying.
+        **kwargs: Additional styling options passed to `holoviews.opts.Sankey`. See HoloViews Sankey documentation for full list of options.
+
+    Returns:
+        holoviews.Sankey
+
+    Examples:
+    >>> import numpy as np
+    >>> import pandas as pd
+    >>> import ehrdata as ed
+    >>>
+    >>> layer = np.array(
+    ...     [
+    ...         [[1, 0, 1], [0, 1, 0]],  # patient 1: treatment, disease_flare
+    ...         [[0, 1, 1], [1, 0, 0]],  # patient 2: treatment, disease_flare
+    ...         [[1, 1, 0], [0, 0, 1]],  # patient 3: treatment, disease_flare
+    ...     ]
+    ... )
+    >>>
+    >>> edata = ed.EHRData(
+    ...     layers={"layer_1": layer},
+    ...     obs=pd.DataFrame(index=["patient_1", "patient_2", "patient_3"]),
+    ...     var=pd.DataFrame(index=["treatment", "disease_flare"]),
+    ...     tem=pd.DataFrame(index=["visit_0", "visit_1", "visit_2"]),
+    ... )
+    >>>
+    >>> plot_sankey_time(edata, columns=["disease_flare"], layer="layer_1", state_labels={0: "no flare", 1: "flare"})
+
+
+    """
+    flare_data = edata[:, edata.var_names.isin(columns), :].layers[layer][:, 0, :]
+
+    time_steps = edata.tem.index.tolist()
+    # states = edata.var.loc[columns[0]].values
+
+    if state_labels is None:
+        unique_states = np.unique(flare_data)
+        unique_states = unique_states[~np.isnan(unique_states)]
+        state_labels = {int(state): str(state) for state in unique_states}
+        # state_labels = {int(state): states[int(state)] for state in unique_states} if the categorical variables values are also in layer
+
+    state_values = sorted(state_labels.keys())
+    state_names = [state_labels[val] for val in state_values]
+
+    sources, targets, values = [], [], []
+    for t in range(len(time_steps) - 1):
+        for s_from_idx, s_from_val in enumerate(state_values):
+            for s_to_idx, s_to_val in enumerate(state_values):
+                count = np.sum((flare_data[:, t] == s_from_val) & (flare_data[:, t + 1] == s_to_val))
+                if count > 0:
+                    source_label = f"{state_names[s_from_idx]} ({time_steps[t]})"
+                    target_label = f"{state_names[s_to_idx]} ({time_steps[t + 1]})"
+                    sources.append(source_label)
+                    targets.append(target_label)
+                    values.append(int(count))
+
+    sankey_df = pd.DataFrame({"source": sources, "target": targets, "value": values})
+
+    sankey = hv.Sankey(sankey_df, kdims=["source", "target"], vdims=["value"])
+
+    default_opts = {"label_position": "right", "show_values": True, "title": f"Patient flows: {columns[0]} over time"}
+
+    default_opts.update(kwargs)
+
+    sankey = sankey.opts(opts.Sankey(**default_opts))
+
+    if show:
+        from IPython.display import display
+
+        display(sankey)
+
+    return sankey
diff --git a/tests/plot/test_sankey.py b/tests/plot/test_sankey.py
new file mode 100644
index 000000000..85f369b41
--- /dev/null
+++ b/tests/plot/test_sankey.py
@@ -0,0 +1,120 @@
+from pathlib import Path
+
+import ehrdata as ed
+import holoviews as hv
+import numpy as np
+import pandas as pd
+import pytest
+
+import ehrapy as ep
+
+CURRENT_DIR = Path(__file__).parent
+_TEST_IMAGE_PATH = f"{CURRENT_DIR}/_images"
+
+
+@pytest.fixture
+def ehr_3d_mini():
+    layer = np.array(
+        [
+            [[1, 0, 1], [0, 1, 0]],
+            [[0, 1, 1], [1, 0, 0]],
+            [[1, 1, 0], [0, 0, 1]],
+        ]
+    )
+
+    edata = ed.EHRData(
+        layers={"layer_1": layer},
+        obs=pd.DataFrame(index=["patient 1", "patient 2", "patient 3"]),
+        # obs_names=["patient 1", "patient 2", "patient 3"],
+        var=pd.DataFrame(index=["treatment", "disease_flare"]),
+        # var_names=["treatment", "disease_flare"],
+        tem=pd.DataFrame(index=["visit_0", "visit_1", "visit_2"]),
+    )
+    return edata
+
+
+@pytest.fixture
+def diabetes_130_fairlearn_sample_100():
+    edata = ed.dt.diabetes_130_fairlearn(
+        columns_obs_only=[
+            "race",
+            "gender",
+        ]
+    )[:100]
+
+    return edata
+
+
+def test_sankey_plot(diabetes_130_fairlearn_sample_100):
+    edata = diabetes_130_fairlearn_sample_100.copy()
+
+    sankey = ep.pl.plot_sankey(edata, columns=["gender", "race"])
+
+    assert isinstance(sankey, hv.Sankey)
+
+    data = sankey.data
+    required_columns = ["source", "target", "value"]
+    for col in required_columns:
+        assert col in data.columns
+
+    assert len(data) > 0  # at least one flow
+    assert (data["value"] > 0).all()  # flow values positive
+    assert data["value"].sum() == len(edata.obs)  # total flow must match total obs
+
+    # each flow matches the expected count
+    for _, row in data.iterrows():
+        gender_value = row["source"].split(": ")[1]
+        race_value = row["target"].split(": ")[1]
+        flow_value = row["value"]
+
+        expected_count = len(edata.obs[(edata.obs["gender"] == gender_value) & (edata.obs["race"] == race_value)])
+
+        assert flow_value == expected_count
+
+    for source in data["source"].unique():
+        assert source.startswith("gender:")  # sources have the correct prefix
+    for target in data["target"].unique():
+        assert target.startswith("race:")  # targets have the correct prefix
+
+
+def test_sankey_time_plot(ehr_3d_mini):
+    edata = ehr_3d_mini
+    sankey = ep.pl.plot_sankey_time(
+        edata, columns=["disease_flare"], layer="layer_1", state_labels={0: "no flare", 1: "flare"}
+    )
+
+    assert isinstance(sankey, hv.Sankey)
+
+    data = sankey.data
+    required_columns = ["source", "target", "value"]
+    for col in required_columns:
+        assert col in data.columns
+
+    assert len(data) > 0
+    assert (data["value"] > 0).all()
+
+    # check that sources and targets contain state labels
+    state_labels = ["no flare", "flare"]
+    for source in data["source"].unique():
+        assert any(label in source for label in state_labels)
+        assert "(" in source and ")" in source
+    for target in data["target"].unique():
+        assert any(label in target for label in state_labels)
+        assert "(" in target and ")" in target
+
+    # check conservation of patients across time points
+    time_steps = edata.tem.index.tolist()
+    first_time = time_steps[0]
+    last_time = time_steps[-1]
+
+    outflow_first = data[data["source"].str.contains(f"\\({first_time}\\)", regex=True)]["value"].sum()
+    inflow_last = data[data["target"].str.contains(f"\\({last_time}\\)", regex=True)]["value"].sum()
+
+    assert outflow_first == inflow_last
+
+    # total flow equals number of transitions
+    n_patients = edata.n_obs
+    n_transitions = len(time_steps) - 1
+    expected_total_flow = n_patients * n_transitions
+
+    assert data["value"].sum() == expected_total_flow

From d59b90d7fae52b8350575a23243cab64173336f2 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=C3=96yk=C3=BC=20S=C3=BCoglu?=
 <oeykue.sueoglu@helmholtz-munich.de>
Date: Wed, 26 Nov 2025 22:58:12 +0100
Subject: [PATCH 02/12] pyproject.toml dependency added and AnnData from
 typehints removed

---
 ehrapy/plot/_sankey.py | 7 +++----
 pyproject.toml         | 3 ++-
 2 files changed, 5 insertions(+), 5 deletions(-)

diff --git a/ehrapy/plot/_sankey.py b/ehrapy/plot/_sankey.py
index d3567a606..601144ba0 100644
--- a/ehrapy/plot/_sankey.py
+++ b/ehrapy/plot/_sankey.py
@@ -1,6 +1,6 @@
 from __future__ import annotations
 
-from typing import TYPE_CHECKING, Dict, List
+from typing import TYPE_CHECKING
 
 import ehrdata as ed
 import holoviews as hv
@@ -11,12 +11,11 @@
 hv.extension("bokeh")
 
 if TYPE_CHECKING:
-    from anndata import AnnData
     from ehrdata import EHRData
 
 
 def plot_sankey(
-    edata: EHRData | AnnData,
+    edata: EHRData,
     *,
     columns: list[str],
     show: bool = False,
@@ -87,7 +86,7 @@ def plot_sankey(
 
 
 def plot_sankey_time(
-    edata: EHRData | AnnData,
+    edata: EHRData,
     *,
     columns: list[str],
     layer: str,
diff --git a/pyproject.toml b/pyproject.toml
index 81b62f2e4..4b6373853 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -63,7 +63,8 @@ dependencies = [
     "leidenalg",  # careful - GPL
     "igraph",  # careful - GPL
     "fast-array-utils[sparse,accel]",
-    "tslearn"
+    "tslearn",
+    "holoviews"
 ]
 
 [project.optional-dependencies]

From dcbdaf98f805a6bbf42bdc9e26ba570cd0f4065f Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=C3=96yk=C3=BC=20S=C3=BCoglu?=
 <oeykue.sueoglu@helmholtz-munich.de>
Date: Thu, 27 Nov 2025 12:50:01 +0100
Subject: [PATCH 03/12] small fix

---
 ehrapy/plot/_sankey.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/ehrapy/plot/_sankey.py b/ehrapy/plot/_sankey.py
index 601144ba0..b7ee3d3fd 100644
--- a/ehrapy/plot/_sankey.py
+++ b/ehrapy/plot/_sankey.py
@@ -71,7 +71,7 @@ def plot_sankey(
     )
 
     sankey = hv.Sankey(sankey_df, kdims=["source", "target"], vdims=["value"])
-    default_opts = {"label_position": "right", "show_values": True, "title": f"Patient flows: {columns[0]} over time"}
+    default_opts = {"label_position": "right", "show_values": True, "title": f"Flow across: {columns}"}
 
     default_opts.update(kwargs)
 

From 3a9c5f8185319a6e94304e210300a2c5b8b898bd Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=C3=96yk=C3=BC=20S=C3=BCoglu?=
 <oeykue.sueoglu@helmholtz-munich.de>
Date: Wed, 3 Dec 2025 16:23:40 +0100
Subject: [PATCH 04/12] backend option matplotlib in addition to bokeh

---
 ehrapy/plot/_sankey.py                      |   23 +
 tests/_scripts/sankey_expected.ipynb        | 1776 +++++++++++++++++++
 tests/plot/_images/sankey_expected.png      |  Bin 0 -> 50476 bytes
 tests/plot/_images/sankey_time_expected.png |  Bin 0 -> 37730 bytes
 tests/plot/test_sankey.py                   |   41 +-
 5 files changed, 1836 insertions(+), 4 deletions(-)
 create mode 100644 tests/_scripts/sankey_expected.ipynb
 create mode 100644 tests/plot/_images/sankey_expected.png
 create mode 100644 tests/plot/_images/sankey_time_expected.png

diff --git a/ehrapy/plot/_sankey.py b/ehrapy/plot/_sankey.py
index b7ee3d3fd..a47ef6c96 100644
--- a/ehrapy/plot/_sankey.py
+++ b/ehrapy/plot/_sankey.py
@@ -14,10 +14,26 @@
     from ehrdata import EHRData
 
 
+def _set_hv_backend(backend: str | None) -> str:
+    """Ensure a valid HoloViews backend is active and return its name."""
+    if backend is None:
+        backend = "matplotlib"  # default
+
+    backend = backend.lower()
+    if backend not in {"bokeh", "matplotlib"}:
+        raise ValueError(f"Unsupported backend '{backend}'. Use 'bokeh' or 'matplotlib'.")
+
+    if hv.Store.current_backend != backend:
+        hv.extension(backend)
+
+    return backend
+
+
 def plot_sankey(
     edata: EHRData,
     *,
     columns: list[str],
+    backend: str | None = None,
     show: bool = False,
     **kwargs,
 ) -> hv.Sankey:
@@ -26,6 +42,7 @@ def plot_sankey(
     Args:
         edata : Central data object containing observation data
         columns : Column names from edata.obs to visualize
+        backend: HoloViews backend to use ("matplotlib" or"bokeh"). Default: "matplotlib"
         show: If True, display the plot immediately. If False, only return the plot object without displaying.
         **kwargs: Additional styling options passed to `holoviews.opts.Sankey`. See HoloViews Sankey documentation for full list of options.
 
@@ -38,6 +55,8 @@ def plot_sankey(
         >>> ep.pl.plot_sankey(edata, columns=["gender", "race"])
 
     """
+    _set_hv_backend(backend)
+
     df = edata.obs[columns]
 
     labels = []
@@ -91,6 +110,7 @@ def plot_sankey_time(
     columns: list[str],
     layer: str,
     state_labels: dict[int, str] | None = None,
+    backend: str | None = None,
     show: bool = False,
     **kwargs,
 ) -> hv.Sankey:
@@ -107,6 +127,7 @@ def plot_sankey_time(
         layer: Name of the layer in `edata.layers` containing the feature data to visualize.
         state_labels: Mapping from numeric state values to readable labels. If None, state values
         will be displayed as strings of their numeric codes (e.g., "0", "1", "2"). Default: "None"
+        backend: HoloViews backend to use ("matplotlib" or"bokeh"). Default: "matplotlib"
         show: If True, display the plot immediately. If False, only return the plot object without displaying.
         **kwargs: Additional styling options passed to `holoviews.opts.Sankey`. See HoloViews Sankey documentation for full list of options.
 
@@ -137,6 +158,8 @@ def plot_sankey_time(
 
 
     """
+    _set_hv_backend(backend)
+
     flare_data = edata[:, edata.var_names.isin(columns), :].layers[layer][:, 0, :]
 
     time_steps = edata.tem.index.tolist()
diff --git a/tests/_scripts/sankey_expected.ipynb b/tests/_scripts/sankey_expected.ipynb
new file mode 100644
index 000000000..fe894da12
--- /dev/null
+++ b/tests/_scripts/sankey_expected.ipynb
@@ -0,0 +1,1776 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "42a55492",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<script type=\"esms-options\">{\"shimMode\": true}</script><style>*[data-root-id],\n",
+       "*[data-root-id] > * {\n",
+       "  box-sizing: border-box;\n",
+       "  font-family: var(--jp-ui-font-family);\n",
+       "  font-size: var(--jp-ui-font-size1);\n",
+       "  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
+       "}\n",
+       "\n",
+       "/* Override VSCode background color */\n",
+       ".cell-output-ipywidget-background:has(\n",
+       "  > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
+       "),\n",
+       ".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "</style>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/javascript": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  const force = true;\n  const py_version = '3.8.1'.replace('rc', '-rc.').replace('.dev', '-dev.');\n  const reloading = false;\n  const Bokeh = root.Bokeh;\n\n  // Set a timeout for this load but only if we are not already initializing\n  if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks;\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n    if (js_modules == null) js_modules = [];\n    if (js_exports == null) js_exports = {};\n\n    root._bokeh_onload_callbacks.push(callback);\n\n    if (root._bokeh_is_loading > 0) {\n      // Don't load bokeh if it is still initializing\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n      // There is nothing to load\n      run_callbacks();\n      return null;\n    }\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n    window._bokeh_on_load = on_load\n\n    function on_error(e) {\n      const src_el = e.srcElement\n      console.error(\"failed to load \" + (src_el.href || src_el.src));\n    }\n\n    const skip = [];\n    if (window.requirejs) {\n      window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n      root._bokeh_is_loading = css_urls.length + 0;\n    } else {\n      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n    }\n\n    const existing_stylesheets = []\n    const links = document.getElementsByTagName('link')\n    for (let i = 0; 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+       "  var render_items = [{\"docid\":\"1be2d97f-9b07-4bd1-9e22-f8d4ade659f0\",\"roots\":{\"8fc37fff-4ea7-47a5-86a5-9c7da3739e93\":\"f0c5ea9a-cabb-4e77-bdba-c58b59a65d74\"},\"root_ids\":[\"8fc37fff-4ea7-47a5-86a5-9c7da3739e93\"]}];\n",
+       "  var docs = Object.values(docs_json)\n",
+       "  if (!docs) {\n",
+       "    return\n",
+       "  }\n",
+       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
+       "  async function embed_document(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
+       "    for (const render_item of render_items) {\n",
+       "      for (const root_id of render_item.root_ids) {\n",
+       "\tconst id_el = document.getElementById(root_id)\n",
+       "\tif (id_el.children.length && id_el.children[0].hasAttribute('data-root-id')) {\n",
+       "\t  const root_el = id_el.children[0]\n",
+       "\t  root_el.id = root_el.id + '-rendered'\n",
+       "\t  for (const child of root_el.children) {\n",
+       "            // Ensure JupyterLab does not capture keyboard shortcuts\n",
+       "            // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
+       "\t    child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
+       "\t  }\n",
+       "\t}\n",
+       "      }\n",
+       "    }\n",
+       "  }\n",
+       "  function get_bokeh(root) {\n",
+       "    if (root.Bokeh === undefined) {\n",
+       "      return null\n",
+       "    } else if (root.Bokeh.version !== py_version) {\n",
+       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
+       "\treturn null\n",
+       "      }\n",
+       "      return root.Bokeh.versions.get(py_version);\n",
+       "    } else if (root.Bokeh.version === py_version) {\n",
+       "      return root.Bokeh\n",
+       "    }\n",
+       "    return null\n",
+       "  }\n",
+       "  function is_loaded(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
+       "  }\n",
+       "  if (is_loaded(root)) {\n",
+       "    embed_document(root);\n",
+       "  } else {\n",
+       "    var attempts = 0;\n",
+       "    var timer = setInterval(function(root) {\n",
+       "      if (is_loaded(root)) {\n",
+       "        clearInterval(timer);\n",
+       "        embed_document(root);\n",
+       "      } else if (document.readyState == \"complete\") {\n",
+       "        attempts++;\n",
+       "        if (attempts > 200) {\n",
+       "          clearInterval(timer);\n",
+       "\t  var Bokeh = get_bokeh(root)\n",
+       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
+       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
+       "\t  } else {\n",
+       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
+       "\t    embed_document(root)\n",
+       "\t  }\n",
+       "        }\n",
+       "      }\n",
+       "    }, 25, root)\n",
+       "  }\n",
+       "})(window);</script>"
+      ]
+     },
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+      "application/vnd.holoviews_exec.v0+json": {
+       "id": "8fc37fff-4ea7-47a5-86a5-9c7da3739e93"
+      }
+     },
+     "output_type": "display_data"
+    },
+    {
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+       "roTBs2RqAAAAAElFTkSuQmCC' style='height:25px; border-radius:12px; display: inline-block; float: left; vertical-align: middle'></img>\n",
+       "</a>\n",
+       "\n",
+       "\n",
+       "<a href=\"https://bokeh.org\" target=\"_blank\" title=\"Bokeh 3.8.1\">\n",
+       "  <img src='data:image/png;base64,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'\n",
+       "       style='height:15px; border-radius:12px; display: inline-block; float: left'>\n",
+       "  </img>\n",
+       "</a>\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "<span style=\"float: left; margin-left: 5px; line-height: 15px; cursor: pointer; opacity: 0.7;\"\n",
+       "      onmouseover=\"this.style.opacity='1'\"\n",
+       "      onmouseout=\"this.style.opacity='0.7'\"\n",
+       "      title=\"Extension loaded. This cell output contains code that enables plot interactivity, it should not be removed.\">ⓘ</span>\n",
+       "</div>\n",
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import ehrdata as ed\n",
+    "import holoviews as hv\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "\n",
+    "import ehrapy as ep"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "8104f266",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "current_notebook_dir = %pwd\n",
+    "\n",
+    "_TEST_IMAGE_PATH = f\"{current_notebook_dir}/../plot/_images\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "e242cbd4",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[93m!\u001b[0m File ehrapy_data\\diabetes_130_fairlearn.csv already exists! Using already downloaded dataset...\n"
+     ]
+    }
+   ],
+   "source": [
+    "edata = ed.dt.diabetes_130_fairlearn(columns_obs_only=[\"gender\", \"race\"])[:100]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "3351e8d3",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<script type=\"esms-options\">{\"shimMode\": true}</script><style>*[data-root-id],\n",
+       "*[data-root-id] > * {\n",
+       "  box-sizing: border-box;\n",
+       "  font-family: var(--jp-ui-font-family);\n",
+       "  font-size: var(--jp-ui-font-size1);\n",
+       "  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
+       "}\n",
+       "\n",
+       "/* Override VSCode background color */\n",
+       ".cell-output-ipywidget-background:has(\n",
+       "  > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
+       "),\n",
+       ".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "</style>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
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+      "application/vnd.holoviews_load.v0+json": ""
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/javascript": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n  window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n    function JupyterCommManager() {\n    }\n\n    JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n      if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        comm_manager.register_target(comm_id, function(comm) {\n          comm.on_msg(msg_handler);\n        });\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n          comm.onMsg = msg_handler;\n        });\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        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+      "application/vnd.holoviews_load.v0+json": ""
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.holoviews_exec.v0+json": "",
+      "text/html": [
+       "<div id='09d6f56c-5fae-4f48-a37d-aa19a3e0f86c'>\n",
+       "  <div id=\"e13a378f-573a-4d07-885b-19a295a06b6c\" data-root-id=\"09d6f56c-5fae-4f48-a37d-aa19a3e0f86c\" style=\"display: contents;\"></div>\n",
+       "</div>\n",
+       "<script type=\"application/javascript\">(function(root) {\n",
+       "  var docs_json = {\"4fe9d655-04d2-40d9-974c-94d3a4d7e096\":{\"version\":\"3.8.1\",\"title\":\"Bokeh 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+       "  var render_items = [{\"docid\":\"4fe9d655-04d2-40d9-974c-94d3a4d7e096\",\"roots\":{\"09d6f56c-5fae-4f48-a37d-aa19a3e0f86c\":\"e13a378f-573a-4d07-885b-19a295a06b6c\"},\"root_ids\":[\"09d6f56c-5fae-4f48-a37d-aa19a3e0f86c\"]}];\n",
+       "  var docs = Object.values(docs_json)\n",
+       "  if (!docs) {\n",
+       "    return\n",
+       "  }\n",
+       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
+       "  async function embed_document(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
+       "    for (const render_item of render_items) {\n",
+       "      for (const root_id of render_item.root_ids) {\n",
+       "\tconst id_el = document.getElementById(root_id)\n",
+       "\tif (id_el.children.length && id_el.children[0].hasAttribute('data-root-id')) {\n",
+       "\t  const root_el = id_el.children[0]\n",
+       "\t  root_el.id = root_el.id + '-rendered'\n",
+       "\t  for (const child of root_el.children) {\n",
+       "            // Ensure JupyterLab does not capture keyboard shortcuts\n",
+       "            // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
+       "\t    child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
+       "\t  }\n",
+       "\t}\n",
+       "      }\n",
+       "    }\n",
+       "  }\n",
+       "  function get_bokeh(root) {\n",
+       "    if (root.Bokeh === undefined) {\n",
+       "      return null\n",
+       "    } else if (root.Bokeh.version !== py_version) {\n",
+       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
+       "\treturn null\n",
+       "      }\n",
+       "      return root.Bokeh.versions.get(py_version);\n",
+       "    } else if (root.Bokeh.version === py_version) {\n",
+       "      return root.Bokeh\n",
+       "    }\n",
+       "    return null\n",
+       "  }\n",
+       "  function is_loaded(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
+       "  }\n",
+       "  if (is_loaded(root)) {\n",
+       "    embed_document(root);\n",
+       "  } else {\n",
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+       "    var timer = setInterval(function(root) {\n",
+       "      if (is_loaded(root)) {\n",
+       "        clearInterval(timer);\n",
+       "        embed_document(root);\n",
+       "      } else if (document.readyState == \"complete\") {\n",
+       "        attempts++;\n",
+       "        if (attempts > 200) {\n",
+       "          clearInterval(timer);\n",
+       "\t  var Bokeh = get_bokeh(root)\n",
+       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
+       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
+       "\t  } else {\n",
+       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
+       "\t    embed_document(root)\n",
+       "\t  }\n",
+       "        }\n",
+       "      }\n",
+       "    }, 25, root)\n",
+       "  }\n",
+       "})(window);</script>"
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+       "5nK5CQAQMtXznCRJePpEbwOAZhzHX4ix/wHzzC/tu64gcwAAAABJRU5ErkJggg=='\n",
+       "       style='height:15px; border-radius:12px; display: inline-block; float: left'></img>\n",
+       "</a>\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "<span style=\"float: left; margin-left: 5px; line-height: 15px; cursor: pointer; opacity: 0.7;\"\n",
+       "      onmouseover=\"this.style.opacity='1'\"\n",
+       "      onmouseout=\"this.style.opacity='0.7'\"\n",
+       "      title=\"Extension loaded. This cell output contains code that enables plot interactivity, it should not be removed.\">ⓘ</span>\n",
+       "</div>\n",
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sankey = ep.pl.plot_sankey(edata, columns=[\"gender\", \"race\"], backend=\"matplotlib\", show=False)\n",
+    "fig = hv.render(sankey, backend=\"matplotlib\")\n",
+    "\n",
+    "fig.savefig(f\"{_TEST_IMAGE_PATH}/sankey_expected.png\", dpi=80)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "4b735603",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {},
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.holoviews_exec.v0+json": "",
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+       "</div>\n",
+       "<script type=\"application/javascript\">(function(root) {\n",
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fa-exclamation-triangle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]},{\"type\":\"map\",\"entries\":[[\"type\",\"info\"],[\"background\",\"#007bff\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-info-circle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]}]}]},{\"type\":\"model\",\"name\":\"Notification\",\"properties\":[{\"name\":\"background\",\"kind\":\"Any\",\"default\":null},{\"name\":\"duration\",\"kind\":\"Any\",\"default\":3000},{\"name\":\"icon\",\"kind\":\"Any\",\"default\":null},{\"name\":\"message\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"notification_type\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_rendered\",\"kind\":\"Any\",\"default\":false},{\"name\":\"_destroyed\",\"kind\":\"Any\",\"default\":false}]},{\"type\":\"model\",\"name\":\"TemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"BootstrapTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"TemplateEditor1\",\"properties\":[{\"name\":\"layout\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"MaterialTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"request_value1\",\"properties\":[{\"name\":\"fill\",\"kind\":\"Any\",\"default\":\"none\"},{\"name\":\"_synced\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_request_sync\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"holoviews.plotting.bokeh.raster.HoverModel\",\"properties\":[{\"name\":\"xy\",\"kind\":\"Any\",\"default\":null},{\"name\":\"data\",\"kind\":\"Any\",\"default\":null}]}]}};\n",
+       "  var render_items = [{\"docid\":\"d5d98475-942d-42c4-951d-fd7ea71688ad\",\"roots\":{\"c5a92859-0d7c-4c73-829e-94e05cc73cd1\":\"a2e41962-bd43-41c1-9fbf-6eeee14530d8\"},\"root_ids\":[\"c5a92859-0d7c-4c73-829e-94e05cc73cd1\"]}];\n",
+       "  var docs = Object.values(docs_json)\n",
+       "  if (!docs) {\n",
+       "    return\n",
+       "  }\n",
+       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
+       "  async function embed_document(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
+       "    for (const render_item of render_items) {\n",
+       "      for (const root_id of render_item.root_ids) {\n",
+       "\tconst id_el = document.getElementById(root_id)\n",
+       "\tif (id_el.children.length && id_el.children[0].hasAttribute('data-root-id')) {\n",
+       "\t  const root_el = id_el.children[0]\n",
+       "\t  root_el.id = root_el.id + '-rendered'\n",
+       "\t  for (const child of root_el.children) {\n",
+       "            // Ensure JupyterLab does not capture keyboard shortcuts\n",
+       "            // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
+       "\t    child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
+       "\t  }\n",
+       "\t}\n",
+       "      }\n",
+       "    }\n",
+       "  }\n",
+       "  function get_bokeh(root) {\n",
+       "    if (root.Bokeh === undefined) {\n",
+       "      return null\n",
+       "    } else if (root.Bokeh.version !== py_version) {\n",
+       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
+       "\treturn null\n",
+       "      }\n",
+       "      return root.Bokeh.versions.get(py_version);\n",
+       "    } else if (root.Bokeh.version === py_version) {\n",
+       "      return root.Bokeh\n",
+       "    }\n",
+       "    return null\n",
+       "  }\n",
+       "  function is_loaded(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
+       "  }\n",
+       "  if (is_loaded(root)) {\n",
+       "    embed_document(root);\n",
+       "  } else {\n",
+       "    var attempts = 0;\n",
+       "    var timer = setInterval(function(root) {\n",
+       "      if (is_loaded(root)) {\n",
+       "        clearInterval(timer);\n",
+       "        embed_document(root);\n",
+       "      } else if (document.readyState == \"complete\") {\n",
+       "        attempts++;\n",
+       "        if (attempts > 200) {\n",
+       "          clearInterval(timer);\n",
+       "\t  var Bokeh = get_bokeh(root)\n",
+       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
+       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
+       "\t  } else {\n",
+       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
+       "\t    embed_document(root)\n",
+       "\t  }\n",
+       "        }\n",
+       "      }\n",
+       "    }, 25, root)\n",
+       "  }\n",
+       "})(window);</script>"
+      ],
+      "text/plain": [
+       ":Sankey   [source,target]   (value)"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {
+      "application/vnd.holoviews_exec.v0+json": {
+       "id": "c5a92859-0d7c-4c73-829e-94e05cc73cd1"
+      }
+     },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sankey"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "53b26cc8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<script type=\"esms-options\">{\"shimMode\": true}</script><style>*[data-root-id],\n",
+       "*[data-root-id] > * {\n",
+       "  box-sizing: border-box;\n",
+       "  font-family: var(--jp-ui-font-family);\n",
+       "  font-size: var(--jp-ui-font-size1);\n",
+       "  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
+       "}\n",
+       "\n",
+       "/* Override VSCode background color */\n",
+       ".cell-output-ipywidget-background:has(\n",
+       "  > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
+       "),\n",
+       ".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "</style>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/javascript": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  const force = true;\n  const py_version = '3.8.1'.replace('rc', '-rc.').replace('.dev', '-dev.');\n  const reloading = false;\n  const Bokeh = root.Bokeh;\n\n  // Set a timeout for this load but only if we are not already initializing\n  if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks;\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n    if (js_modules == null) js_modules = [];\n    if (js_exports == null) js_exports = {};\n\n    root._bokeh_onload_callbacks.push(callback);\n\n    if (root._bokeh_is_loading > 0) {\n      // Don't load bokeh if it is still initializing\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n      // There is nothing to load\n      run_callbacks();\n      return null;\n    }\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n    window._bokeh_on_load = on_load\n\n    function on_error(e) {\n      const src_el = e.srcElement\n      console.error(\"failed to load \" + (src_el.href || src_el.src));\n    }\n\n    const skip = [];\n    if (window.requirejs) {\n      window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n      root._bokeh_is_loading = css_urls.length + 0;\n    } else {\n      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n    }\n\n    const existing_stylesheets = []\n    const links = document.getElementsByTagName('link')\n    for (let i = 0; i < links.length; i++) {\n      const link = links[i]\n      if (link.href != null) {\n        existing_stylesheets.push(link.href)\n      }\n    }\n    for (let i = 0; i < css_urls.length; i++) {\n      const url = css_urls[i];\n      const escaped = encodeURI(url)\n      if (existing_stylesheets.indexOf(escaped) !== -1) {\n        on_load()\n        continue;\n      }\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }    var existing_scripts = []\n    const scripts = document.getElementsByTagName('script')\n    for (let i = 0; i < scripts.length; i++) {\n      var script = scripts[i]\n      if (script.src != null) {\n        existing_scripts.push(script.src)\n      }\n    }\n    for (let i = 0; i < js_urls.length; i++) {\n      const url = js_urls[i];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      const element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (let i = 0; i < js_modules.length; i++) {\n      const url = js_modules[i];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (const name in js_exports) {\n      const url = js_exports[name];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      var element = document.createElement('script');\n      element.onerror = on_error;\n      element.async = false;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      element.textContent = `\n      import ${name} from \"${url}\"\n      window.${name} = ${name}\n      window._bokeh_on_load()\n      `\n      document.head.appendChild(element);\n    }\n    if (!js_urls.length && !js_modules.length) {\n      on_load()\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  const js_urls = [\"https://cdn.holoviz.org/panel/1.8.3/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-3.8.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.8.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.8.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.8.1.min.js\", \"https://cdn.holoviz.org/panel/1.8.3/dist/panel.min.js\"];\n  const js_modules = [];\n  const js_exports = {};\n  const css_urls = [];\n  const inline_js = [    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n  ];\n\n  function run_inline_js() {\n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (let i = 0; i < inline_js.length; i++) {\n        try {\n          inline_js[i].call(root, root.Bokeh);\n        } catch(e) {\n          if (!reloading) {\n            throw e;\n          }\n        }\n      }\n      // Cache old bokeh versions\n      if (Bokeh != undefined && !reloading) {\n        var NewBokeh = root.Bokeh;\n        if (Bokeh.versions === undefined) {\n          Bokeh.versions = new Map();\n        }\n        if (NewBokeh.version !== Bokeh.version) {\n          Bokeh.versions.set(NewBokeh.version, NewBokeh)\n        }\n        root.Bokeh = Bokeh;\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    }\n    root._bokeh_is_initializing = false\n  }\n\n  function load_or_wait() {\n    // Implement a backoff loop that tries to ensure we do not load multiple\n    // versions of Bokeh and its dependencies at the same time.\n    // In recent versions we use the root._bokeh_is_initializing flag\n    // to determine whether there is an ongoing attempt to initialize\n    // bokeh, however for backward compatibility we also try to ensure\n    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n    // before older versions are fully initialized.\n    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n      // If the timeout and bokeh was not successfully loaded we reset\n      // everything and try loading again\n      root._bokeh_timeout = Date.now() + 5000;\n      root._bokeh_is_initializing = false;\n      root._bokeh_onload_callbacks = undefined;\n      root._bokeh_is_loading = 0\n      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n      load_or_wait();\n    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n      setTimeout(load_or_wait, 100);\n    } else {\n      root._bokeh_is_initializing = true\n      root._bokeh_onload_callbacks = []\n      const bokeh_loaded = root.Bokeh != null && (root.Bokeh.version === py_version || (root.Bokeh.versions !== undefined && root.Bokeh.versions.has(py_version)));\n      if (!reloading && !bokeh_loaded) {\n        if (root.Bokeh) {\n          root.Bokeh = undefined;\n        }\n        console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n      }\n      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n        console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n        run_inline_js();\n      });\n    }\n  }\n  // Give older versions of the autoload script a head-start to ensure\n  // they initialize before we start loading newer version.\n  setTimeout(load_or_wait, 100)\n}(window));",
+      "application/vnd.holoviews_load.v0+json": ""
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/javascript": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n  window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n    function JupyterCommManager() {\n    }\n\n    JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n      if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        comm_manager.register_target(comm_id, function(comm) {\n          comm.on_msg(msg_handler);\n        });\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n          comm.onMsg = msg_handler;\n        });\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n          var messages = comm.messages[Symbol.asyncIterator]();\n          function processIteratorResult(result) {\n            var message = result.value;\n            var content = {data: message.data, comm_id};\n            var buffers = []\n            for (var buffer of message.buffers || []) {\n              buffers.push(new DataView(buffer))\n            }\n            var metadata = message.metadata || {};\n            var msg = {content, buffers, metadata}\n            msg_handler(msg);\n            return messages.next().then(processIteratorResult);\n          }\n          return messages.next().then(processIteratorResult);\n        })\n      }\n    }\n\n    JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n      if (comm_id in window.PyViz.comms) {\n        return window.PyViz.comms[comm_id];\n      } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n        if (msg_handler) {\n          comm.on_msg(msg_handler);\n        }\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n        let retries = 0;\n        const open = () => {\n          if (comm.active) {\n            comm.open();\n          } else if (retries > 3) {\n            console.warn('Comm target never activated')\n          } else {\n            retries += 1\n            setTimeout(open, 500)\n          }\n        }\n        if (comm.active) {\n          comm.open();\n        } else {\n          setTimeout(open, 500)\n        }\n        if (msg_handler) {\n          comm.onMsg = msg_handler;\n        }\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        var comm_promise = google.colab.kernel.comms.open(comm_id)\n        comm_promise.then((comm) => {\n          window.PyViz.comms[comm_id] = comm;\n          if (msg_handler) {\n            var messages = comm.messages[Symbol.asyncIterator]();\n            function processIteratorResult(result) {\n              var message = result.value;\n              var content = {data: message.data};\n              var metadata = message.metadata || {comm_id};\n              var msg = {content, metadata}\n              msg_handler(msg);\n              return messages.next().then(processIteratorResult);\n            }\n            return messages.next().then(processIteratorResult);\n          }\n        })\n        var sendClosure = (data, metadata, buffers, disposeOnDone) => {\n          return comm_promise.then((comm) => {\n            comm.send(data, metadata, buffers, disposeOnDone);\n          });\n        };\n        var comm = {\n          send: sendClosure\n        };\n      }\n      window.PyViz.comms[comm_id] = comm;\n      return comm;\n    }\n    window.PyViz.comm_manager = new JupyterCommManager();\n    \n\n\nvar JS_MIME_TYPE = 'application/javascript';\nvar HTML_MIME_TYPE = 'text/html';\nvar EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\nvar CLASS_NAME = 'output';\n\n/**\n * Render data to the DOM node\n */\nfunction render(props, node) {\n  var div = document.createElement(\"div\");\n  var script = document.createElement(\"script\");\n  node.appendChild(div);\n  node.appendChild(script);\n}\n\n/**\n * Handle when a new output is added\n */\nfunction handle_add_output(event, handle) {\n  var output_area = handle.output_area;\n  var output = handle.output;\n  if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n    return\n  }\n  var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n  var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n  if (id !== undefined) {\n    var nchildren = toinsert.length;\n    var html_node = toinsert[nchildren-1].children[0];\n    html_node.innerHTML = output.data[HTML_MIME_TYPE];\n    var scripts = [];\n    var nodelist = html_node.querySelectorAll(\"script\");\n    for (var i in nodelist) {\n      if (nodelist.hasOwnProperty(i)) {\n        scripts.push(nodelist[i])\n      }\n    }\n\n    scripts.forEach( function (oldScript) {\n      var newScript = document.createElement(\"script\");\n      var attrs = [];\n      var nodemap = oldScript.attributes;\n      for (var j in nodemap) {\n        if (nodemap.hasOwnProperty(j)) {\n          attrs.push(nodemap[j])\n        }\n      }\n      attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n      newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n      oldScript.parentNode.replaceChild(newScript, oldScript);\n    });\n    if (JS_MIME_TYPE in output.data) {\n      toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n    }\n    output_area._hv_plot_id = id;\n    if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n      window.PyViz.plot_index[id] = Bokeh.index[id];\n    } else {\n      window.PyViz.plot_index[id] = null;\n    }\n  } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n    var bk_div = document.createElement(\"div\");\n    bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n    var script_attrs = bk_div.children[0].attributes;\n    for (var i = 0; i < script_attrs.length; i++) {\n      toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n    }\n    // store reference to server id on output_area\n    output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n  }\n}\n\n/**\n * Handle when an output is cleared or removed\n */\nfunction handle_clear_output(event, handle) {\n  var id = handle.cell.output_area._hv_plot_id;\n  var server_id = handle.cell.output_area._bokeh_server_id;\n  if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n  var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n  if (server_id !== null) {\n    comm.send({event_type: 'server_delete', 'id': server_id});\n    return;\n  } else if (comm !== null) {\n    comm.send({event_type: 'delete', 'id': id});\n  }\n  delete PyViz.plot_index[id];\n  if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n    var doc = window.Bokeh.index[id].model.document\n    doc.clear();\n    const i = window.Bokeh.documents.indexOf(doc);\n    if (i > -1) {\n      window.Bokeh.documents.splice(i, 1);\n    }\n  }\n}\n\n/**\n * Handle kernel restart event\n */\nfunction handle_kernel_cleanup(event, handle) {\n  delete PyViz.comms[\"hv-extension-comm\"];\n  window.PyViz.plot_index = {}\n}\n\n/**\n * Handle update_display_data messages\n */\nfunction handle_update_output(event, handle) {\n  handle_clear_output(event, {cell: {output_area: handle.output_area}})\n  handle_add_output(event, handle)\n}\n\nfunction register_renderer(events, OutputArea) {\n  function append_mime(data, metadata, element) {\n    // create a DOM node to render to\n    var toinsert = this.create_output_subarea(\n    metadata,\n    CLASS_NAME,\n    EXEC_MIME_TYPE\n    );\n    this.keyboard_manager.register_events(toinsert);\n    // Render to node\n    var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n    render(props, toinsert[0]);\n    element.append(toinsert);\n    return toinsert\n  }\n\n  events.on('output_added.OutputArea', handle_add_output);\n  events.on('output_updated.OutputArea', handle_update_output);\n  events.on('clear_output.CodeCell', handle_clear_output);\n  events.on('delete.Cell', handle_clear_output);\n  events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n\n  OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n    safe: true,\n    index: 0\n  });\n}\n\nif (window.Jupyter !== undefined) {\n  try {\n    var events = require('base/js/events');\n    var OutputArea = require('notebook/js/outputarea').OutputArea;\n    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n      register_renderer(events, OutputArea);\n    }\n  } catch(err) {\n  }\n}\n",
+      "application/vnd.holoviews_load.v0+json": ""
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.holoviews_exec.v0+json": "",
+      "text/html": [
+       "<div id='bff7933a-7268-435a-b674-4a963bda2ddd'>\n",
+       "  <div id=\"f77516cb-0a7c-4dbb-a7d9-baf32df9b47d\" data-root-id=\"bff7933a-7268-435a-b674-4a963bda2ddd\" style=\"display: contents;\"></div>\n",
+       "</div>\n",
+       "<script type=\"application/javascript\">(function(root) {\n",
+       "  var docs_json = {\"e1176385-e0e1-4f89-b9bc-cb7358da1bcf\":{\"version\":\"3.8.1\",\"title\":\"Bokeh Application\",\"config\":{\"type\":\"object\",\"name\":\"DocumentConfig\",\"id\":\"412103d0-2afd-495f-918a-c151d6de6feb\",\"attributes\":{\"notifications\":{\"type\":\"object\",\"name\":\"Notifications\",\"id\":\"5be61c51-b86a-4128-b151-cd49a7f6aee4\"}}},\"roots\":[{\"type\":\"object\",\"name\":\"panel.models.browser.BrowserInfo\",\"id\":\"bff7933a-7268-435a-b674-4a963bda2ddd\"},{\"type\":\"object\",\"name\":\"panel.models.comm_manager.CommManager\",\"id\":\"0bf7ccf7-cf4c-4c4d-9ac4-f717bd0067ed\",\"attributes\":{\"plot_id\":\"bff7933a-7268-435a-b674-4a963bda2ddd\",\"comm_id\":\"4d7cc9b40956497db8f37dccc6608dcb\",\"client_comm_id\":\"c83e82b8bf434a0591e4fb332bfb3851\"}}],\"defs\":[{\"type\":\"model\",\"name\":\"ReactiveHTML1\"},{\"type\":\"model\",\"name\":\"FlexBox1\",\"properties\":[{\"name\":\"align_content\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"align_items\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"flex_direction\",\"kind\":\"Any\",\"default\":\"row\"},{\"name\":\"flex_wrap\",\"kind\":\"Any\",\"default\":\"wrap\"},{\"name\":\"gap\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"justify_content\",\"kind\":\"Any\",\"default\":\"flex-start\"}]},{\"type\":\"model\",\"name\":\"FloatPanel1\",\"properties\":[{\"name\":\"config\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"contained\",\"kind\":\"Any\",\"default\":true},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"right-top\"},{\"name\":\"offsetx\",\"kind\":\"Any\",\"default\":null},{\"name\":\"offsety\",\"kind\":\"Any\",\"default\":null},{\"name\":\"theme\",\"kind\":\"Any\",\"default\":\"primary\"},{\"name\":\"status\",\"kind\":\"Any\",\"default\":\"normalized\"}]},{\"type\":\"model\",\"name\":\"GridStack1\",\"properties\":[{\"name\":\"ncols\",\"kind\":\"Any\",\"default\":null},{\"name\":\"nrows\",\"kind\":\"Any\",\"default\":null},{\"name\":\"allow_resize\",\"kind\":\"Any\",\"default\":true},{\"name\":\"allow_drag\",\"kind\":\"Any\",\"default\":true},{\"name\":\"state\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"drag1\",\"properties\":[{\"name\":\"slider_width\",\"kind\":\"Any\",\"default\":5},{\"name\":\"slider_color\",\"kind\":\"Any\",\"default\":\"black\"},{\"name\":\"start\",\"kind\":\"Any\",\"default\":0},{\"name\":\"end\",\"kind\":\"Any\",\"default\":100},{\"name\":\"value\",\"kind\":\"Any\",\"default\":50}]},{\"type\":\"model\",\"name\":\"click1\",\"properties\":[{\"name\":\"terminal_output\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"debug_name\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"clears\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"ReactiveESM1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"JSComponent1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"ReactComponent1\",\"properties\":[{\"name\":\"use_shadow_dom\",\"kind\":\"Any\",\"default\":true},{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"AnyWidgetComponent1\",\"properties\":[{\"name\":\"use_shadow_dom\",\"kind\":\"Any\",\"default\":true},{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"FastWrapper1\",\"properties\":[{\"name\":\"object\",\"kind\":\"Any\",\"default\":null},{\"name\":\"style\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"NotificationArea1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"max_notifications\",\"kind\":\"Any\",\"default\":5},{\"name\":\"notifications\",\"kind\":\"Any\",\"default\":[]},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0},{\"name\":\"types\",\"kind\":\"Any\",\"default\":[{\"type\":\"map\",\"entries\":[[\"type\",\"warning\"],[\"background\",\"#ffc107\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas 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+       "  var render_items = [{\"docid\":\"e1176385-e0e1-4f89-b9bc-cb7358da1bcf\",\"roots\":{\"bff7933a-7268-435a-b674-4a963bda2ddd\":\"f77516cb-0a7c-4dbb-a7d9-baf32df9b47d\"},\"root_ids\":[\"bff7933a-7268-435a-b674-4a963bda2ddd\"]}];\n",
+       "  var docs = Object.values(docs_json)\n",
+       "  if (!docs) {\n",
+       "    return\n",
+       "  }\n",
+       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
+       "  async function embed_document(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
+       "    for (const render_item of render_items) {\n",
+       "      for (const root_id of render_item.root_ids) {\n",
+       "\tconst id_el = document.getElementById(root_id)\n",
+       "\tif (id_el.children.length && id_el.children[0].hasAttribute('data-root-id')) {\n",
+       "\t  const root_el = id_el.children[0]\n",
+       "\t  root_el.id = root_el.id + '-rendered'\n",
+       "\t  for (const child of root_el.children) {\n",
+       "            // Ensure JupyterLab does not capture keyboard shortcuts\n",
+       "            // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
+       "\t    child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
+       "\t  }\n",
+       "\t}\n",
+       "      }\n",
+       "    }\n",
+       "  }\n",
+       "  function get_bokeh(root) {\n",
+       "    if (root.Bokeh === undefined) {\n",
+       "      return null\n",
+       "    } else if (root.Bokeh.version !== py_version) {\n",
+       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
+       "\treturn null\n",
+       "      }\n",
+       "      return root.Bokeh.versions.get(py_version);\n",
+       "    } else if (root.Bokeh.version === py_version) {\n",
+       "      return root.Bokeh\n",
+       "    }\n",
+       "    return null\n",
+       "  }\n",
+       "  function is_loaded(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
+       "  }\n",
+       "  if (is_loaded(root)) {\n",
+       "    embed_document(root);\n",
+       "  } else {\n",
+       "    var attempts = 0;\n",
+       "    var timer = setInterval(function(root) {\n",
+       "      if (is_loaded(root)) {\n",
+       "        clearInterval(timer);\n",
+       "        embed_document(root);\n",
+       "      } else if (document.readyState == \"complete\") {\n",
+       "        attempts++;\n",
+       "        if (attempts > 200) {\n",
+       "          clearInterval(timer);\n",
+       "\t  var Bokeh = get_bokeh(root)\n",
+       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
+       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
+       "\t  } else {\n",
+       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
+       "\t    embed_document(root)\n",
+       "\t  }\n",
+       "        }\n",
+       "      }\n",
+       "    }, 25, root)\n",
+       "  }\n",
+       "})(window);</script>"
+      ]
+     },
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+     },
+     "output_type": "display_data"
+    },
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+       "roTBs2RqAAAAAElFTkSuQmCC' style='height:25px; border-radius:12px; display: inline-block; float: left; vertical-align: middle'></img>\n",
+       "</a>\n",
+       "\n",
+       "\n",
+       "<a href=\"https://bokeh.org\" target=\"_blank\" title=\"Bokeh 3.8.1\">\n",
+       "  <img src='data:image/png;base64,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'\n",
+       "       style='height:15px; border-radius:12px; display: inline-block; float: left'>\n",
+       "  </img>\n",
+       "</a>\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "<span style=\"float: left; margin-left: 5px; line-height: 15px; cursor: pointer; opacity: 0.7;\"\n",
+       "      onmouseover=\"this.style.opacity='1'\"\n",
+       "      onmouseout=\"this.style.opacity='0.7'\"\n",
+       "      title=\"Extension loaded. This cell output contains code that enables plot interactivity, it should not be removed.\">ⓘ</span>\n",
+       "</div>\n",
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {},
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
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+       "</div>\n",
+       "<script type=\"application/javascript\">(function(root) {\n",
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300px));\\n}\",{\"id\":\"5808235d-5dd5-4311-8f8e-848a67bc358c\"},{\"id\":\"374f1349-9295-4083-b310-d9aee49b342d\"},{\"id\":\"ca10be9a-b067-4177-ac12-ad316ad18db9\"}],\"min_width\":0,\"margin\":0,\"sizing_mode\":\"stretch_width\",\"align\":\"start\"}}]}}],\"defs\":[{\"type\":\"model\",\"name\":\"ReactiveHTML1\"},{\"type\":\"model\",\"name\":\"FlexBox1\",\"properties\":[{\"name\":\"align_content\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"align_items\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"flex_direction\",\"kind\":\"Any\",\"default\":\"row\"},{\"name\":\"flex_wrap\",\"kind\":\"Any\",\"default\":\"wrap\"},{\"name\":\"gap\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"justify_content\",\"kind\":\"Any\",\"default\":\"flex-start\"}]},{\"type\":\"model\",\"name\":\"FloatPanel1\",\"properties\":[{\"name\":\"config\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"contained\",\"kind\":\"Any\",\"default\":true},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"right-top\"},{\"name\":\"offsetx\",\"kind\":\"Any\",\"default\":null},{\"name\":\"offsety\",\"kind\":\"Any\",\"default\":null},{\"name\":\"theme\",\"kind\":\"Any\",\"default\":\"primary\"},{\"name\":\"status\",\"kind\":\"Any\",\"default\":\"normalized\"}]},{\"type\":\"model\",\"name\":\"GridStack1\",\"properties\":[{\"name\":\"ncols\",\"kind\":\"Any\",\"default\":null},{\"name\":\"nrows\",\"kind\":\"Any\",\"default\":null},{\"name\":\"allow_resize\",\"kind\":\"Any\",\"default\":true},{\"name\":\"allow_drag\",\"kind\":\"Any\",\"default\":true},{\"name\":\"state\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"drag1\",\"properties\":[{\"name\":\"slider_width\",\"kind\":\"Any\",\"default\":5},{\"name\":\"slider_color\",\"kind\":\"Any\",\"default\":\"black\"},{\"name\":\"start\",\"kind\":\"Any\",\"default\":0},{\"name\":\"end\",\"kind\":\"Any\",\"default\":100},{\"name\":\"value\",\"kind\":\"Any\",\"default\":50}]},{\"type\":\"model\",\"name\":\"click1\",\"properties\":[{\"name\":\"terminal_output\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"debug_name\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"clears\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"ReactiveESM1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"JSComponent1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"ReactComponent1\",\"properties\":[{\"name\":\"use_shadow_dom\",\"kind\":\"Any\",\"default\":true},{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"AnyWidgetComponent1\",\"properties\":[{\"name\":\"use_shadow_dom\",\"kind\":\"Any\",\"default\":true},{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"FastWrapper1\",\"properties\":[{\"name\":\"object\",\"kind\":\"Any\",\"default\":null},{\"name\":\"style\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"NotificationArea1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"max_notifications\",\"kind\":\"Any\",\"default\":5},{\"name\":\"notifications\",\"kind\":\"Any\",\"default\":[]},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0},{\"name\":\"types\",\"kind\":\"Any\",\"default\":[{\"type\":\"map\",\"entries\":[[\"type\",\"warning\"],[\"background\",\"#ffc107\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-exclamation-triangle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]},{\"type\":\"map\",\"entries\":[[\"type\",\"info\"],[\"background\",\"#007bff\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-info-circle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]}]}]},{\"type\":\"model\",\"name\":\"Notification\",\"properties\":[{\"name\":\"background\",\"kind\":\"Any\",\"default\":null},{\"name\":\"duration\",\"kind\":\"Any\",\"default\":3000},{\"name\":\"icon\",\"kind\":\"Any\",\"default\":null},{\"name\":\"message\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"notification_type\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_rendered\",\"kind\":\"Any\",\"default\":false},{\"name\":\"_destroyed\",\"kind\":\"Any\",\"default\":false}]},{\"type\":\"model\",\"name\":\"TemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"BootstrapTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"TemplateEditor1\",\"properties\":[{\"name\":\"layout\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"MaterialTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"request_value1\",\"properties\":[{\"name\":\"fill\",\"kind\":\"Any\",\"default\":\"none\"},{\"name\":\"_synced\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_request_sync\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"holoviews.plotting.bokeh.raster.HoverModel\",\"properties\":[{\"name\":\"xy\",\"kind\":\"Any\",\"default\":null},{\"name\":\"data\",\"kind\":\"Any\",\"default\":null}]}]}};\n",
+       "  var render_items = [{\"docid\":\"af407583-34a2-4750-8ded-97398480a764\",\"roots\":{\"2f36f865-d75c-46e1-ad54-c38e44ce6c9f\":\"ae3390f8-f5fd-460e-a6a2-988d48a9f73d\"},\"root_ids\":[\"2f36f865-d75c-46e1-ad54-c38e44ce6c9f\"]}];\n",
+       "  var docs = Object.values(docs_json)\n",
+       "  if (!docs) {\n",
+       "    return\n",
+       "  }\n",
+       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
+       "  async function embed_document(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
+       "    for (const render_item of render_items) {\n",
+       "      for (const root_id of render_item.root_ids) {\n",
+       "\tconst id_el = document.getElementById(root_id)\n",
+       "\tif (id_el.children.length && id_el.children[0].hasAttribute('data-root-id')) {\n",
+       "\t  const root_el = id_el.children[0]\n",
+       "\t  root_el.id = root_el.id + '-rendered'\n",
+       "\t  for (const child of root_el.children) {\n",
+       "            // Ensure JupyterLab does not capture keyboard shortcuts\n",
+       "            // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
+       "\t    child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
+       "\t  }\n",
+       "\t}\n",
+       "      }\n",
+       "    }\n",
+       "  }\n",
+       "  function get_bokeh(root) {\n",
+       "    if (root.Bokeh === undefined) {\n",
+       "      return null\n",
+       "    } else if (root.Bokeh.version !== py_version) {\n",
+       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
+       "\treturn null\n",
+       "      }\n",
+       "      return root.Bokeh.versions.get(py_version);\n",
+       "    } else if (root.Bokeh.version === py_version) {\n",
+       "      return root.Bokeh\n",
+       "    }\n",
+       "    return null\n",
+       "  }\n",
+       "  function is_loaded(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
+       "  }\n",
+       "  if (is_loaded(root)) {\n",
+       "    embed_document(root);\n",
+       "  } else {\n",
+       "    var attempts = 0;\n",
+       "    var timer = setInterval(function(root) {\n",
+       "      if (is_loaded(root)) {\n",
+       "        clearInterval(timer);\n",
+       "        embed_document(root);\n",
+       "      } else if (document.readyState == \"complete\") {\n",
+       "        attempts++;\n",
+       "        if (attempts > 200) {\n",
+       "          clearInterval(timer);\n",
+       "\t  var Bokeh = get_bokeh(root)\n",
+       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
+       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
+       "\t  } else {\n",
+       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
+       "\t    embed_document(root)\n",
+       "\t  }\n",
+       "        }\n",
+       "      }\n",
+       "    }, 25, root)\n",
+       "  }\n",
+       "})(window);</script>"
+      ],
+      "text/plain": [
+       ":Sankey   [source,target]   (value)"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {
+      "application/vnd.holoviews_exec.v0+json": {
+       "id": "2f36f865-d75c-46e1-ad54-c38e44ce6c9f"
+      }
+     },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ep.pl.plot_sankey(edata, columns=[\"gender\", \"race\"], backend=\"bokeh\", show=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "a59e9a13",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "layer = np.array(\n",
+    "    [\n",
+    "        [[1, 0, 1], [0, 1, 0]],  # patient 1: treatment, disease_flare\n",
+    "        [[0, 1, 1], [1, 0, 0]],  # patient 2: treatment, disease_flare\n",
+    "        [[1, 1, 0], [0, 0, 1]],  # patient 3: treatment, disease_flare\n",
+    "    ]\n",
+    ")\n",
+    "\n",
+    "edata_time = ed.EHRData(\n",
+    "    layers={\"layer_1\": layer},\n",
+    "    obs=pd.DataFrame(index=[\"patient_1\", \"patient_2\", \"patient_3\"]),\n",
+    "    var=pd.DataFrame(index=[\"treatment\", \"disease_flare\"]),\n",
+    "    tem=pd.DataFrame(index=[\"visit_0\", \"visit_1\", \"visit_2\"]),\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "dfb9988e",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<script type=\"esms-options\">{\"shimMode\": true}</script><style>*[data-root-id],\n",
+       "*[data-root-id] > * {\n",
+       "  box-sizing: border-box;\n",
+       "  font-family: var(--jp-ui-font-family);\n",
+       "  font-size: var(--jp-ui-font-size1);\n",
+       "  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
+       "}\n",
+       "\n",
+       "/* Override VSCode background color */\n",
+       ".cell-output-ipywidget-background:has(\n",
+       "  > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
+       "),\n",
+       ".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "</style>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/javascript": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  const force = true;\n  const py_version = '3.8.1'.replace('rc', '-rc.').replace('.dev', '-dev.');\n  const reloading = false;\n  const Bokeh = root.Bokeh;\n\n  // Set a timeout for this load but only if we are not already initializing\n  if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks;\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n    if (js_modules == null) js_modules = [];\n    if (js_exports == null) js_exports = {};\n\n    root._bokeh_onload_callbacks.push(callback);\n\n    if (root._bokeh_is_loading > 0) {\n      // Don't load bokeh if it is still initializing\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n      // There is nothing to load\n      run_callbacks();\n      return null;\n    }\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n    window._bokeh_on_load = on_load\n\n    function on_error(e) {\n      const src_el = e.srcElement\n      console.error(\"failed to load \" + (src_el.href || src_el.src));\n    }\n\n    const skip = [];\n    if (window.requirejs) {\n      window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n      root._bokeh_is_loading = css_urls.length + 0;\n    } else {\n      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n    }\n\n    const existing_stylesheets = []\n    const links = document.getElementsByTagName('link')\n    for (let i = 0; i < links.length; i++) {\n      const link = links[i]\n      if (link.href != null) {\n        existing_stylesheets.push(link.href)\n      }\n    }\n    for (let i = 0; i < css_urls.length; i++) {\n      const url = css_urls[i];\n      const escaped = encodeURI(url)\n      if (existing_stylesheets.indexOf(escaped) !== -1) {\n        on_load()\n        continue;\n      }\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }    var existing_scripts = []\n    const scripts = document.getElementsByTagName('script')\n    for (let i = 0; i < scripts.length; i++) {\n      var script = scripts[i]\n      if (script.src != null) {\n        existing_scripts.push(script.src)\n      }\n    }\n    for (let i = 0; i < js_urls.length; i++) {\n      const url = js_urls[i];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      const element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (let i = 0; i < js_modules.length; i++) {\n      const url = js_modules[i];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (const name in js_exports) {\n      const url = js_exports[name];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      var element = document.createElement('script');\n      element.onerror = on_error;\n      element.async = false;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      element.textContent = `\n      import ${name} from \"${url}\"\n      window.${name} = ${name}\n      window._bokeh_on_load()\n      `\n      document.head.appendChild(element);\n    }\n    if (!js_urls.length && !js_modules.length) {\n      on_load()\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  const js_urls = [\"https://cdn.holoviz.org/panel/1.8.3/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-3.8.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.8.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.8.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.8.1.min.js\", \"https://cdn.holoviz.org/panel/1.8.3/dist/panel.min.js\"];\n  const js_modules = [];\n  const js_exports = {};\n  const css_urls = [];\n  const inline_js = [    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n  ];\n\n  function run_inline_js() {\n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (let i = 0; i < inline_js.length; i++) {\n        try {\n          inline_js[i].call(root, root.Bokeh);\n        } catch(e) {\n          if (!reloading) {\n            throw e;\n          }\n        }\n      }\n      // Cache old bokeh versions\n      if (Bokeh != undefined && !reloading) {\n        var NewBokeh = root.Bokeh;\n        if (Bokeh.versions === undefined) {\n          Bokeh.versions = new Map();\n        }\n        if (NewBokeh.version !== Bokeh.version) {\n          Bokeh.versions.set(NewBokeh.version, NewBokeh)\n        }\n        root.Bokeh = Bokeh;\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    }\n    root._bokeh_is_initializing = false\n  }\n\n  function load_or_wait() {\n    // Implement a backoff loop that tries to ensure we do not load multiple\n    // versions of Bokeh and its dependencies at the same time.\n    // In recent versions we use the root._bokeh_is_initializing flag\n    // to determine whether there is an ongoing attempt to initialize\n    // bokeh, however for backward compatibility we also try to ensure\n    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n    // before older versions are fully initialized.\n    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n      // If the timeout and bokeh was not successfully loaded we reset\n      // everything and try loading again\n      root._bokeh_timeout = Date.now() + 5000;\n      root._bokeh_is_initializing = false;\n      root._bokeh_onload_callbacks = undefined;\n      root._bokeh_is_loading = 0\n      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n      load_or_wait();\n    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n      setTimeout(load_or_wait, 100);\n    } else {\n      root._bokeh_is_initializing = true\n      root._bokeh_onload_callbacks = []\n      const bokeh_loaded = root.Bokeh != null && (root.Bokeh.version === py_version || (root.Bokeh.versions !== undefined && root.Bokeh.versions.has(py_version)));\n      if (!reloading && !bokeh_loaded) {\n        if (root.Bokeh) {\n          root.Bokeh = undefined;\n        }\n        console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n      }\n      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n        console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n        run_inline_js();\n      });\n    }\n  }\n  // Give older versions of the autoload script a head-start to ensure\n  // they initialize before we start loading newer version.\n  setTimeout(load_or_wait, 100)\n}(window));",
+      "application/vnd.holoviews_load.v0+json": ""
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/javascript": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n  window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n    function JupyterCommManager() {\n    }\n\n    JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n      if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        comm_manager.register_target(comm_id, function(comm) {\n          comm.on_msg(msg_handler);\n        });\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n          comm.onMsg = msg_handler;\n        });\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n          var messages = comm.messages[Symbol.asyncIterator]();\n          function processIteratorResult(result) {\n            var message = result.value;\n            var content = {data: message.data, comm_id};\n            var buffers = []\n            for (var buffer of message.buffers || []) {\n              buffers.push(new DataView(buffer))\n            }\n            var metadata = message.metadata || {};\n            var msg = {content, buffers, metadata}\n            msg_handler(msg);\n            return messages.next().then(processIteratorResult);\n          }\n          return messages.next().then(processIteratorResult);\n        })\n      }\n    }\n\n    JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n      if (comm_id in window.PyViz.comms) {\n        return window.PyViz.comms[comm_id];\n      } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n        if (msg_handler) {\n          comm.on_msg(msg_handler);\n        }\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n        let retries = 0;\n        const open = () => {\n          if (comm.active) {\n            comm.open();\n          } else if (retries > 3) {\n            console.warn('Comm target never activated')\n          } else {\n            retries += 1\n            setTimeout(open, 500)\n          }\n        }\n        if (comm.active) {\n          comm.open();\n        } else {\n          setTimeout(open, 500)\n        }\n        if (msg_handler) {\n          comm.onMsg = msg_handler;\n        }\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        var comm_promise = google.colab.kernel.comms.open(comm_id)\n        comm_promise.then((comm) => {\n          window.PyViz.comms[comm_id] = comm;\n          if (msg_handler) {\n            var messages = comm.messages[Symbol.asyncIterator]();\n            function processIteratorResult(result) {\n              var message = result.value;\n              var content = {data: message.data};\n              var metadata = message.metadata || {comm_id};\n              var msg = {content, metadata}\n              msg_handler(msg);\n              return messages.next().then(processIteratorResult);\n            }\n            return messages.next().then(processIteratorResult);\n          }\n        })\n        var sendClosure = (data, metadata, buffers, disposeOnDone) => {\n          return comm_promise.then((comm) => {\n            comm.send(data, metadata, buffers, disposeOnDone);\n          });\n        };\n        var comm = {\n          send: sendClosure\n        };\n      }\n      window.PyViz.comms[comm_id] = comm;\n      return comm;\n    }\n    window.PyViz.comm_manager = new JupyterCommManager();\n    \n\n\nvar JS_MIME_TYPE = 'application/javascript';\nvar HTML_MIME_TYPE = 'text/html';\nvar EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\nvar CLASS_NAME = 'output';\n\n/**\n * Render data to the DOM node\n */\nfunction render(props, node) {\n  var div = document.createElement(\"div\");\n  var script = document.createElement(\"script\");\n  node.appendChild(div);\n  node.appendChild(script);\n}\n\n/**\n * Handle when a new output is added\n */\nfunction handle_add_output(event, handle) {\n  var output_area = handle.output_area;\n  var output = handle.output;\n  if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n    return\n  }\n  var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n  var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n  if (id !== undefined) {\n    var nchildren = toinsert.length;\n    var html_node = toinsert[nchildren-1].children[0];\n    html_node.innerHTML = output.data[HTML_MIME_TYPE];\n    var scripts = [];\n    var nodelist = html_node.querySelectorAll(\"script\");\n    for (var i in nodelist) {\n      if (nodelist.hasOwnProperty(i)) {\n        scripts.push(nodelist[i])\n      }\n    }\n\n    scripts.forEach( function (oldScript) {\n      var newScript = document.createElement(\"script\");\n      var attrs = [];\n      var nodemap = oldScript.attributes;\n      for (var j in nodemap) {\n        if (nodemap.hasOwnProperty(j)) {\n          attrs.push(nodemap[j])\n        }\n      }\n      attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n      newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n      oldScript.parentNode.replaceChild(newScript, oldScript);\n    });\n    if (JS_MIME_TYPE in output.data) {\n      toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n    }\n    output_area._hv_plot_id = id;\n    if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n      window.PyViz.plot_index[id] = Bokeh.index[id];\n    } else {\n      window.PyViz.plot_index[id] = null;\n    }\n  } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n    var bk_div = document.createElement(\"div\");\n    bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n    var script_attrs = bk_div.children[0].attributes;\n    for (var i = 0; i < script_attrs.length; i++) {\n      toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n    }\n    // store reference to server id on output_area\n    output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n  }\n}\n\n/**\n * Handle when an output is cleared or removed\n */\nfunction handle_clear_output(event, handle) {\n  var id = handle.cell.output_area._hv_plot_id;\n  var server_id = handle.cell.output_area._bokeh_server_id;\n  if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n  var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n  if (server_id !== null) {\n    comm.send({event_type: 'server_delete', 'id': server_id});\n    return;\n  } else if (comm !== null) {\n    comm.send({event_type: 'delete', 'id': id});\n  }\n  delete PyViz.plot_index[id];\n  if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n    var doc = window.Bokeh.index[id].model.document\n    doc.clear();\n    const i = window.Bokeh.documents.indexOf(doc);\n    if (i > -1) {\n      window.Bokeh.documents.splice(i, 1);\n    }\n  }\n}\n\n/**\n * Handle kernel restart event\n */\nfunction handle_kernel_cleanup(event, handle) {\n  delete PyViz.comms[\"hv-extension-comm\"];\n  window.PyViz.plot_index = {}\n}\n\n/**\n * Handle update_display_data messages\n */\nfunction handle_update_output(event, handle) {\n  handle_clear_output(event, {cell: {output_area: handle.output_area}})\n  handle_add_output(event, handle)\n}\n\nfunction register_renderer(events, OutputArea) {\n  function append_mime(data, metadata, element) {\n    // create a DOM node to render to\n    var toinsert = this.create_output_subarea(\n    metadata,\n    CLASS_NAME,\n    EXEC_MIME_TYPE\n    );\n    this.keyboard_manager.register_events(toinsert);\n    // Render to node\n    var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n    render(props, toinsert[0]);\n    element.append(toinsert);\n    return toinsert\n  }\n\n  events.on('output_added.OutputArea', handle_add_output);\n  events.on('output_updated.OutputArea', handle_update_output);\n  events.on('clear_output.CodeCell', handle_clear_output);\n  events.on('delete.Cell', handle_clear_output);\n  events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n\n  OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n    safe: true,\n    index: 0\n  });\n}\n\nif (window.Jupyter !== undefined) {\n  try {\n    var events = require('base/js/events');\n    var OutputArea = require('notebook/js/outputarea').OutputArea;\n    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n      register_renderer(events, OutputArea);\n    }\n  } catch(err) {\n  }\n}\n",
+      "application/vnd.holoviews_load.v0+json": ""
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.holoviews_exec.v0+json": "",
+      "text/html": [
+       "<div id='df920d20-8dbb-4ca9-8dac-4d8cd7b5af9a'>\n",
+       "  <div id=\"a11749e2-9836-4877-94fb-252bee5cc512\" data-root-id=\"df920d20-8dbb-4ca9-8dac-4d8cd7b5af9a\" style=\"display: contents;\"></div>\n",
+       "</div>\n",
+       "<script type=\"application/javascript\">(function(root) {\n",
+       "  var docs_json = {\"8757a5e1-4d8c-43c1-856b-afc0f91a3ef1\":{\"version\":\"3.8.1\",\"title\":\"Bokeh Application\",\"config\":{\"type\":\"object\",\"name\":\"DocumentConfig\",\"id\":\"301c5d2d-26ae-4e65-995a-5346f8018824\",\"attributes\":{\"notifications\":{\"type\":\"object\",\"name\":\"Notifications\",\"id\":\"1658130e-f20d-49e7-a823-19ba2b030a74\"}}},\"roots\":[{\"type\":\"object\",\"name\":\"panel.models.browser.BrowserInfo\",\"id\":\"df920d20-8dbb-4ca9-8dac-4d8cd7b5af9a\"},{\"type\":\"object\",\"name\":\"panel.models.comm_manager.CommManager\",\"id\":\"97b8680b-d14d-431f-b935-26e14d3eee07\",\"attributes\":{\"plot_id\":\"df920d20-8dbb-4ca9-8dac-4d8cd7b5af9a\",\"comm_id\":\"24071da1a47b4f00b6e45984df1a7c7a\",\"client_comm_id\":\"57be5fe701764d7484eaf99a0382cda8\"}}],\"defs\":[{\"type\":\"model\",\"name\":\"ReactiveHTML1\"},{\"type\":\"model\",\"name\":\"FlexBox1\",\"properties\":[{\"name\":\"align_content\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"align_items\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"flex_direction\",\"kind\":\"Any\",\"default\":\"row\"},{\"name\":\"flex_wrap\",\"kind\":\"Any\",\"default\":\"wrap\"},{\"name\":\"gap\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"justify_content\",\"kind\":\"Any\",\"default\":\"flex-start\"}]},{\"type\":\"model\",\"name\":\"FloatPanel1\",\"properties\":[{\"name\":\"config\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"contained\",\"kind\":\"Any\",\"default\":true},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"right-top\"},{\"name\":\"offsetx\",\"kind\":\"Any\",\"default\":null},{\"name\":\"offsety\",\"kind\":\"Any\",\"default\":null},{\"name\":\"theme\",\"kind\":\"Any\",\"default\":\"primary\"},{\"name\":\"status\",\"kind\":\"Any\",\"default\":\"normalized\"}]},{\"type\":\"model\",\"name\":\"GridStack1\",\"properties\":[{\"name\":\"ncols\",\"kind\":\"Any\",\"default\":null},{\"name\":\"nrows\",\"kind\":\"Any\",\"default\":null},{\"name\":\"allow_resize\",\"kind\":\"Any\",\"default\":true},{\"name\":\"allow_drag\",\"kind\":\"Any\",\"default\":true},{\"name\":\"state\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"drag1\",\"properties\":[{\"name\":\"slider_width\",\"kind\":\"Any\",\"default\":5},{\"name\":\"slider_color\",\"kind\":\"Any\",\"default\":\"black\"},{\"name\":\"start\",\"kind\":\"Any\",\"default\":0},{\"name\":\"end\",\"kind\":\"Any\",\"default\":100},{\"name\":\"value\",\"kind\":\"Any\",\"default\":50}]},{\"type\":\"model\",\"name\":\"click1\",\"properties\":[{\"name\":\"terminal_output\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"debug_name\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"clears\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"ReactiveESM1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"JSComponent1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"ReactComponent1\",\"properties\":[{\"name\":\"use_shadow_dom\",\"kind\":\"Any\",\"default\":true},{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"AnyWidgetComponent1\",\"properties\":[{\"name\":\"use_shadow_dom\",\"kind\":\"Any\",\"default\":true},{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"FastWrapper1\",\"properties\":[{\"name\":\"object\",\"kind\":\"Any\",\"default\":null},{\"name\":\"style\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"NotificationArea1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"max_notifications\",\"kind\":\"Any\",\"default\":5},{\"name\":\"notifications\",\"kind\":\"Any\",\"default\":[]},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0},{\"name\":\"types\",\"kind\":\"Any\",\"default\":[{\"type\":\"map\",\"entries\":[[\"type\",\"warning\"],[\"background\",\"#ffc107\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas 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+       "  var render_items = [{\"docid\":\"8757a5e1-4d8c-43c1-856b-afc0f91a3ef1\",\"roots\":{\"df920d20-8dbb-4ca9-8dac-4d8cd7b5af9a\":\"a11749e2-9836-4877-94fb-252bee5cc512\"},\"root_ids\":[\"df920d20-8dbb-4ca9-8dac-4d8cd7b5af9a\"]}];\n",
+       "  var docs = Object.values(docs_json)\n",
+       "  if (!docs) {\n",
+       "    return\n",
+       "  }\n",
+       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
+       "  async function embed_document(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
+       "    for (const render_item of render_items) {\n",
+       "      for (const root_id of render_item.root_ids) {\n",
+       "\tconst id_el = document.getElementById(root_id)\n",
+       "\tif (id_el.children.length && id_el.children[0].hasAttribute('data-root-id')) {\n",
+       "\t  const root_el = id_el.children[0]\n",
+       "\t  root_el.id = root_el.id + '-rendered'\n",
+       "\t  for (const child of root_el.children) {\n",
+       "            // Ensure JupyterLab does not capture keyboard shortcuts\n",
+       "            // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
+       "\t    child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
+       "\t  }\n",
+       "\t}\n",
+       "      }\n",
+       "    }\n",
+       "  }\n",
+       "  function get_bokeh(root) {\n",
+       "    if (root.Bokeh === undefined) {\n",
+       "      return null\n",
+       "    } else if (root.Bokeh.version !== py_version) {\n",
+       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
+       "\treturn null\n",
+       "      }\n",
+       "      return root.Bokeh.versions.get(py_version);\n",
+       "    } else if (root.Bokeh.version === py_version) {\n",
+       "      return root.Bokeh\n",
+       "    }\n",
+       "    return null\n",
+       "  }\n",
+       "  function is_loaded(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
+       "  }\n",
+       "  if (is_loaded(root)) {\n",
+       "    embed_document(root);\n",
+       "  } else {\n",
+       "    var attempts = 0;\n",
+       "    var timer = setInterval(function(root) {\n",
+       "      if (is_loaded(root)) {\n",
+       "        clearInterval(timer);\n",
+       "        embed_document(root);\n",
+       "      } else if (document.readyState == \"complete\") {\n",
+       "        attempts++;\n",
+       "        if (attempts > 200) {\n",
+       "          clearInterval(timer);\n",
+       "\t  var Bokeh = get_bokeh(root)\n",
+       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
+       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
+       "\t  } else {\n",
+       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
+       "\t    embed_document(root)\n",
+       "\t  }\n",
+       "        }\n",
+       "      }\n",
+       "    }, 25, root)\n",
+       "  }\n",
+       "})(window);</script>"
+      ]
+     },
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+      }
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+     "output_type": "display_data"
+    },
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+       "roTBs2RqAAAAAElFTkSuQmCC' style='height:25px; border-radius:12px; display: inline-block; float: left; vertical-align: middle'></img>\n",
+       "</a>\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "<a href=\"https://matplotlib.org\" target=\"_blank\" title=\"Matplotlib 3.10.5\">\n",
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+       "       style='height:15px; border-radius:12px; display: inline-block; float: left'></img>\n",
+       "</a>\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "<span style=\"float: left; margin-left: 5px; line-height: 15px; cursor: pointer; opacity: 0.7;\"\n",
+       "      onmouseover=\"this.style.opacity='1'\"\n",
+       "      onmouseout=\"this.style.opacity='0.7'\"\n",
+       "      title=\"Extension loaded. This cell output contains code that enables plot interactivity, it should not be removed.\">ⓘ</span>\n",
+       "</div>\n",
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "sankey_time = ep.pl.plot_sankey_time(\n",
+    "    edata_time,\n",
+    "    columns=[\"disease_flare\"],\n",
+    "    layer=\"layer_1\",\n",
+    "    state_labels={0: \"no flare\", 1: \"flare\"},\n",
+    "    backend=\"matplotlib\",\n",
+    ")\n",
+    "\n",
+    "fig = hv.render(sankey_time, backend=\"matplotlib\")\n",
+    "fig.savefig(f\"{_TEST_IMAGE_PATH}/sankey_time_expected.png\", dpi=80)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "c9b9fb79",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {},
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.holoviews_exec.v0+json": "",
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+       "</div>\n",
+       "<script type=\"application/javascript\">(function(root) {\n",
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300px));\\n}\",{\"id\":\"1374aa38-c71e-4db7-9f68-d772915386d7\"},{\"id\":\"bd2989bc-dec7-48c3-a522-17828b8dd386\"},{\"id\":\"dd5e5b57-432f-4214-89ac-411e53be00f6\"}],\"min_width\":0,\"margin\":0,\"sizing_mode\":\"stretch_width\",\"align\":\"start\"}}]}}],\"defs\":[{\"type\":\"model\",\"name\":\"ReactiveHTML1\"},{\"type\":\"model\",\"name\":\"FlexBox1\",\"properties\":[{\"name\":\"align_content\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"align_items\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"flex_direction\",\"kind\":\"Any\",\"default\":\"row\"},{\"name\":\"flex_wrap\",\"kind\":\"Any\",\"default\":\"wrap\"},{\"name\":\"gap\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"justify_content\",\"kind\":\"Any\",\"default\":\"flex-start\"}]},{\"type\":\"model\",\"name\":\"FloatPanel1\",\"properties\":[{\"name\":\"config\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"contained\",\"kind\":\"Any\",\"default\":true},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"right-top\"},{\"name\":\"offsetx\",\"kind\":\"Any\",\"default\":null},{\"name\":\"offsety\",\"kind\":\"Any\",\"default\":null},{\"name\":\"theme\",\"kind\":\"Any\",\"default\":\"primary\"},{\"name\":\"status\",\"kind\":\"Any\",\"default\":\"normalized\"}]},{\"type\":\"model\",\"name\":\"GridStack1\",\"properties\":[{\"name\":\"ncols\",\"kind\":\"Any\",\"default\":null},{\"name\":\"nrows\",\"kind\":\"Any\",\"default\":null},{\"name\":\"allow_resize\",\"kind\":\"Any\",\"default\":true},{\"name\":\"allow_drag\",\"kind\":\"Any\",\"default\":true},{\"name\":\"state\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"drag1\",\"properties\":[{\"name\":\"slider_width\",\"kind\":\"Any\",\"default\":5},{\"name\":\"slider_color\",\"kind\":\"Any\",\"default\":\"black\"},{\"name\":\"start\",\"kind\":\"Any\",\"default\":0},{\"name\":\"end\",\"kind\":\"Any\",\"default\":100},{\"name\":\"value\",\"kind\":\"Any\",\"default\":50}]},{\"type\":\"model\",\"name\":\"click1\",\"properties\":[{\"name\":\"terminal_output\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"debug_name\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"clears\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"ReactiveESM1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"JSComponent1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"ReactComponent1\",\"properties\":[{\"name\":\"use_shadow_dom\",\"kind\":\"Any\",\"default\":true},{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"AnyWidgetComponent1\",\"properties\":[{\"name\":\"use_shadow_dom\",\"kind\":\"Any\",\"default\":true},{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"FastWrapper1\",\"properties\":[{\"name\":\"object\",\"kind\":\"Any\",\"default\":null},{\"name\":\"style\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"NotificationArea1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"max_notifications\",\"kind\":\"Any\",\"default\":5},{\"name\":\"notifications\",\"kind\":\"Any\",\"default\":[]},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0},{\"name\":\"types\",\"kind\":\"Any\",\"default\":[{\"type\":\"map\",\"entries\":[[\"type\",\"warning\"],[\"background\",\"#ffc107\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-exclamation-triangle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]},{\"type\":\"map\",\"entries\":[[\"type\",\"info\"],[\"background\",\"#007bff\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-info-circle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]}]}]},{\"type\":\"model\",\"name\":\"Notification\",\"properties\":[{\"name\":\"background\",\"kind\":\"Any\",\"default\":null},{\"name\":\"duration\",\"kind\":\"Any\",\"default\":3000},{\"name\":\"icon\",\"kind\":\"Any\",\"default\":null},{\"name\":\"message\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"notification_type\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_rendered\",\"kind\":\"Any\",\"default\":false},{\"name\":\"_destroyed\",\"kind\":\"Any\",\"default\":false}]},{\"type\":\"model\",\"name\":\"TemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"BootstrapTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"TemplateEditor1\",\"properties\":[{\"name\":\"layout\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"MaterialTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"request_value1\",\"properties\":[{\"name\":\"fill\",\"kind\":\"Any\",\"default\":\"none\"},{\"name\":\"_synced\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_request_sync\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"holoviews.plotting.bokeh.raster.HoverModel\",\"properties\":[{\"name\":\"xy\",\"kind\":\"Any\",\"default\":null},{\"name\":\"data\",\"kind\":\"Any\",\"default\":null}]}]}};\n",
+       "  var render_items = [{\"docid\":\"afc78983-4b8a-4eb9-854a-8d62894e0468\",\"roots\":{\"05cb3ba7-6101-4037-baeb-a51a1b457da2\":\"f81ac94f-71e1-4743-b751-087c6130f818\"},\"root_ids\":[\"05cb3ba7-6101-4037-baeb-a51a1b457da2\"]}];\n",
+       "  var docs = Object.values(docs_json)\n",
+       "  if (!docs) {\n",
+       "    return\n",
+       "  }\n",
+       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
+       "  async function embed_document(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
+       "    for (const render_item of render_items) {\n",
+       "      for (const root_id of render_item.root_ids) {\n",
+       "\tconst id_el = document.getElementById(root_id)\n",
+       "\tif (id_el.children.length && id_el.children[0].hasAttribute('data-root-id')) {\n",
+       "\t  const root_el = id_el.children[0]\n",
+       "\t  root_el.id = root_el.id + '-rendered'\n",
+       "\t  for (const child of root_el.children) {\n",
+       "            // Ensure JupyterLab does not capture keyboard shortcuts\n",
+       "            // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
+       "\t    child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
+       "\t  }\n",
+       "\t}\n",
+       "      }\n",
+       "    }\n",
+       "  }\n",
+       "  function get_bokeh(root) {\n",
+       "    if (root.Bokeh === undefined) {\n",
+       "      return null\n",
+       "    } else if (root.Bokeh.version !== py_version) {\n",
+       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
+       "\treturn null\n",
+       "      }\n",
+       "      return root.Bokeh.versions.get(py_version);\n",
+       "    } else if (root.Bokeh.version === py_version) {\n",
+       "      return root.Bokeh\n",
+       "    }\n",
+       "    return null\n",
+       "  }\n",
+       "  function is_loaded(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
+       "  }\n",
+       "  if (is_loaded(root)) {\n",
+       "    embed_document(root);\n",
+       "  } else {\n",
+       "    var attempts = 0;\n",
+       "    var timer = setInterval(function(root) {\n",
+       "      if (is_loaded(root)) {\n",
+       "        clearInterval(timer);\n",
+       "        embed_document(root);\n",
+       "      } else if (document.readyState == \"complete\") {\n",
+       "        attempts++;\n",
+       "        if (attempts > 200) {\n",
+       "          clearInterval(timer);\n",
+       "\t  var Bokeh = get_bokeh(root)\n",
+       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
+       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
+       "\t  } else {\n",
+       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
+       "\t    embed_document(root)\n",
+       "\t  }\n",
+       "        }\n",
+       "      }\n",
+       "    }, 25, root)\n",
+       "  }\n",
+       "})(window);</script>"
+      ],
+      "text/plain": [
+       ":Sankey   [source,target]   (value)"
+      ]
+     },
+     "execution_count": 10,
+     "metadata": {
+      "application/vnd.holoviews_exec.v0+json": {
+       "id": "05cb3ba7-6101-4037-baeb-a51a1b457da2"
+      }
+     },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sankey_time"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "38907509",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<script type=\"esms-options\">{\"shimMode\": true}</script><style>*[data-root-id],\n",
+       "*[data-root-id] > * {\n",
+       "  box-sizing: border-box;\n",
+       "  font-family: var(--jp-ui-font-family);\n",
+       "  font-size: var(--jp-ui-font-size1);\n",
+       "  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
+       "}\n",
+       "\n",
+       "/* Override VSCode background color */\n",
+       ".cell-output-ipywidget-background:has(\n",
+       "  > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
+       "),\n",
+       ".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "</style>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/javascript": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  const force = true;\n  const py_version = '3.8.1'.replace('rc', '-rc.').replace('.dev', '-dev.');\n  const reloading = false;\n  const Bokeh = root.Bokeh;\n\n  // Set a timeout for this load but only if we are not already initializing\n  if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks;\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n    if (js_modules == null) js_modules = [];\n    if (js_exports == null) js_exports = {};\n\n    root._bokeh_onload_callbacks.push(callback);\n\n    if (root._bokeh_is_loading > 0) {\n      // Don't load bokeh if it is still initializing\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n      // There is nothing to load\n      run_callbacks();\n      return null;\n    }\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n    window._bokeh_on_load = on_load\n\n    function on_error(e) {\n      const src_el = e.srcElement\n      console.error(\"failed to load \" + (src_el.href || src_el.src));\n    }\n\n    const skip = [];\n    if (window.requirejs) {\n      window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n      root._bokeh_is_loading = css_urls.length + 0;\n    } else {\n      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n    }\n\n    const existing_stylesheets = []\n    const links = document.getElementsByTagName('link')\n    for (let i = 0; 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+       "  var render_items = [{\"docid\":\"93985596-3646-48f0-b1da-c808f7ed3c11\",\"roots\":{\"3a9abedd-73f5-4726-91d0-ed70606c5d0f\":\"d4cfc109-ec03-4ddf-a271-5545c87d676d\"},\"root_ids\":[\"3a9abedd-73f5-4726-91d0-ed70606c5d0f\"]}];\n",
+       "  var docs = Object.values(docs_json)\n",
+       "  if (!docs) {\n",
+       "    return\n",
+       "  }\n",
+       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
+       "  async function embed_document(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
+       "    for (const render_item of render_items) {\n",
+       "      for (const root_id of render_item.root_ids) {\n",
+       "\tconst id_el = document.getElementById(root_id)\n",
+       "\tif (id_el.children.length && id_el.children[0].hasAttribute('data-root-id')) {\n",
+       "\t  const root_el = id_el.children[0]\n",
+       "\t  root_el.id = root_el.id + '-rendered'\n",
+       "\t  for (const child of root_el.children) {\n",
+       "            // Ensure JupyterLab does not capture keyboard shortcuts\n",
+       "            // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
+       "\t    child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
+       "\t  }\n",
+       "\t}\n",
+       "      }\n",
+       "    }\n",
+       "  }\n",
+       "  function get_bokeh(root) {\n",
+       "    if (root.Bokeh === undefined) {\n",
+       "      return null\n",
+       "    } else if (root.Bokeh.version !== py_version) {\n",
+       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
+       "\treturn null\n",
+       "      }\n",
+       "      return root.Bokeh.versions.get(py_version);\n",
+       "    } else if (root.Bokeh.version === py_version) {\n",
+       "      return root.Bokeh\n",
+       "    }\n",
+       "    return null\n",
+       "  }\n",
+       "  function is_loaded(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
+       "  }\n",
+       "  if (is_loaded(root)) {\n",
+       "    embed_document(root);\n",
+       "  } else {\n",
+       "    var attempts = 0;\n",
+       "    var timer = setInterval(function(root) {\n",
+       "      if (is_loaded(root)) {\n",
+       "        clearInterval(timer);\n",
+       "        embed_document(root);\n",
+       "      } else if (document.readyState == \"complete\") {\n",
+       "        attempts++;\n",
+       "        if (attempts > 200) {\n",
+       "          clearInterval(timer);\n",
+       "\t  var Bokeh = get_bokeh(root)\n",
+       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
+       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
+       "\t  } else {\n",
+       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
+       "\t    embed_document(root)\n",
+       "\t  }\n",
+       "        }\n",
+       "      }\n",
+       "    }, 25, root)\n",
+       "  }\n",
+       "})(window);</script>"
+      ]
+     },
+     "metadata": {
+      "application/vnd.holoviews_exec.v0+json": {
+       "id": "3a9abedd-73f5-4726-91d0-ed70606c5d0f"
+      }
+     },
+     "output_type": "display_data"
+    },
+    {
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+       "</a>\n",
+       "\n",
+       "\n",
+       "<a href=\"https://bokeh.org\" target=\"_blank\" title=\"Bokeh 3.8.1\">\n",
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+       "       style='height:15px; border-radius:12px; display: inline-block; float: left'>\n",
+       "  </img>\n",
+       "</a>\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "<span style=\"float: left; margin-left: 5px; line-height: 15px; cursor: pointer; opacity: 0.7;\"\n",
+       "      onmouseover=\"this.style.opacity='1'\"\n",
+       "      onmouseout=\"this.style.opacity='0.7'\"\n",
+       "      title=\"Extension loaded. This cell output contains code that enables plot interactivity, it should not be removed.\">ⓘ</span>\n",
+       "</div>\n",
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {},
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
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+       "</div>\n",
+       "<script type=\"application/javascript\">(function(root) {\n",
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b73142e-2681-4ecb-988f-f05e61a157e7\",\"attributes\":{\"all\":{\"type\":\"object\",\"name\":\"AreaVisuals\",\"id\":\"4f0cc639-f0aa-4745-a28e-6fc3c6698a19\",\"attributes\":{\"fill_color\":\"white\",\"hover_fill_color\":\"lightgray\"}}}}}}}},{\"type\":\"object\",\"name\":\"ResetTool\",\"id\":\"b644e521-b5dd-4660-9d1f-fe8cee1fdead\"},{\"type\":\"object\",\"name\":\"TapTool\",\"id\":\"f990338f-b80c-44b3-8569-22f59c2de451\",\"attributes\":{\"renderers\":\"auto\"}}],\"active_drag\":{\"id\":\"cd45a3eb-b304-4679-9e69-ccf39a812aa7\"},\"active_scroll\":{\"id\":\"fe5c42ba-e795-43d7-82cb-e06e9e883489\"}}},\"left\":[{\"type\":\"object\",\"name\":\"LinearAxis\",\"id\":\"48878d03-4807-4e94-81f8-fe86e10f4afb\",\"attributes\":{\"visible\":false,\"ticker\":{\"type\":\"object\",\"name\":\"BasicTicker\",\"id\":\"49ed6330-4f6a-40ef-9776-d5ce1495adcc\",\"attributes\":{\"mantissas\":[1,2,5]}},\"formatter\":{\"type\":\"object\",\"name\":\"BasicTickFormatter\",\"id\":\"fff05d30-6051-426a-9e48-1d089cd1760e\"},\"axis_label\":\"y\",\"major_label_policy\":{\"type\":\"object\",\"name\":\"AllLabels\",\"id\":\"9609e9cf-dfe3-4602-9931-c6a2127c652d\"}}}],\"below\":[{\"type\":\"object\",\"name\":\"LinearAxis\",\"id\":\"d3641210-c9dd-4807-b14f-7edf5445f4fd\",\"attributes\":{\"visible\":false,\"ticker\":{\"type\":\"object\",\"name\":\"BasicTicker\",\"id\":\"5d2a9b57-9c85-407c-85b3-b8a7cc34529f\",\"attributes\":{\"mantissas\":[1,2,5]}},\"formatter\":{\"type\":\"object\",\"name\":\"BasicTickFormatter\",\"id\":\"7f39c9a2-e194-4beb-bd05-a813770f887d\"},\"axis_label\":\"x\",\"major_label_policy\":{\"type\":\"object\",\"name\":\"AllLabels\",\"id\":\"3187196a-c05c-4c51-ac5c-cf7840953896\"}}}],\"center\":[{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"87d2a7c6-1f04-4ccb-aa09-29157dde1bf4\",\"attributes\":{\"axis\":{\"id\":\"d3641210-c9dd-4807-b14f-7edf5445f4fd\"},\"grid_line_color\":null}},{\"type\":\"object\",\"name\":\"Grid\",\"id\":\"b50900c8-d3ea-463f-bde6-0799b5124bd9\",\"attributes\":{\"dimension\":1,\"axis\":{\"id\":\"48878d03-4807-4e94-81f8-fe86e10f4afb\"},\"grid_line_color\":null}}],\"min_border_top\":10,\"min_border_bottom\":10,\"min_border_left\":10,\"min_border_right\":10,\"output_backend\":\"webgl\"}},{\"type\":\"object\",\"name\":\"Spacer\",\"id\":\"8dfa01d6-b7c5-41ad-89d3-a2ceeb1800df\",\"attributes\":{\"name\":\"HSpacer01777\",\"stylesheets\":[\"\\n:host(.pn-loading):before, 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300px));\\n}\",{\"id\":\"a8712d10-e8a8-4e9f-85e3-e1422eb064b4\"},{\"id\":\"8e01a2e0-bab9-4bd5-b6e2-9ef4a48de9fd\"},{\"id\":\"ff47a1b6-7d80-4eb1-beff-4302a850e329\"}],\"min_width\":0,\"margin\":0,\"sizing_mode\":\"stretch_width\",\"align\":\"start\"}}]}}],\"defs\":[{\"type\":\"model\",\"name\":\"ReactiveHTML1\"},{\"type\":\"model\",\"name\":\"FlexBox1\",\"properties\":[{\"name\":\"align_content\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"align_items\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"flex_direction\",\"kind\":\"Any\",\"default\":\"row\"},{\"name\":\"flex_wrap\",\"kind\":\"Any\",\"default\":\"wrap\"},{\"name\":\"gap\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"justify_content\",\"kind\":\"Any\",\"default\":\"flex-start\"}]},{\"type\":\"model\",\"name\":\"FloatPanel1\",\"properties\":[{\"name\":\"config\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"contained\",\"kind\":\"Any\",\"default\":true},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"right-top\"},{\"name\":\"offsetx\",\"kind\":\"Any\",\"default\":null},{\"name\":\"offsety\",\"kind\":\"Any\",\"default\":null},{\"name\":\"theme\",\"kind\":\"Any\",\"default\":\"primary\"},{\"name\":\"status\",\"kind\":\"Any\",\"default\":\"normalized\"}]},{\"type\":\"model\",\"name\":\"GridStack1\",\"properties\":[{\"name\":\"ncols\",\"kind\":\"Any\",\"default\":null},{\"name\":\"nrows\",\"kind\":\"Any\",\"default\":null},{\"name\":\"allow_resize\",\"kind\":\"Any\",\"default\":true},{\"name\":\"allow_drag\",\"kind\":\"Any\",\"default\":true},{\"name\":\"state\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"drag1\",\"properties\":[{\"name\":\"slider_width\",\"kind\":\"Any\",\"default\":5},{\"name\":\"slider_color\",\"kind\":\"Any\",\"default\":\"black\"},{\"name\":\"start\",\"kind\":\"Any\",\"default\":0},{\"name\":\"end\",\"kind\":\"Any\",\"default\":100},{\"name\":\"value\",\"kind\":\"Any\",\"default\":50}]},{\"type\":\"model\",\"name\":\"click1\",\"properties\":[{\"name\":\"terminal_output\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"debug_name\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"clears\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"ReactiveESM1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"JSComponent1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"ReactComponent1\",\"properties\":[{\"name\":\"use_shadow_dom\",\"kind\":\"Any\",\"default\":true},{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"AnyWidgetComponent1\",\"properties\":[{\"name\":\"use_shadow_dom\",\"kind\":\"Any\",\"default\":true},{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"FastWrapper1\",\"properties\":[{\"name\":\"object\",\"kind\":\"Any\",\"default\":null},{\"name\":\"style\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"NotificationArea1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"max_notifications\",\"kind\":\"Any\",\"default\":5},{\"name\":\"notifications\",\"kind\":\"Any\",\"default\":[]},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0},{\"name\":\"types\",\"kind\":\"Any\",\"default\":[{\"type\":\"map\",\"entries\":[[\"type\",\"warning\"],[\"background\",\"#ffc107\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-exclamation-triangle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]},{\"type\":\"map\",\"entries\":[[\"type\",\"info\"],[\"background\",\"#007bff\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-info-circle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]}]}]},{\"type\":\"model\",\"name\":\"Notification\",\"properties\":[{\"name\":\"background\",\"kind\":\"Any\",\"default\":null},{\"name\":\"duration\",\"kind\":\"Any\",\"default\":3000},{\"name\":\"icon\",\"kind\":\"Any\",\"default\":null},{\"name\":\"message\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"notification_type\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_rendered\",\"kind\":\"Any\",\"default\":false},{\"name\":\"_destroyed\",\"kind\":\"Any\",\"default\":false}]},{\"type\":\"model\",\"name\":\"TemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"BootstrapTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"TemplateEditor1\",\"properties\":[{\"name\":\"layout\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"MaterialTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"request_value1\",\"properties\":[{\"name\":\"fill\",\"kind\":\"Any\",\"default\":\"none\"},{\"name\":\"_synced\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_request_sync\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"holoviews.plotting.bokeh.raster.HoverModel\",\"properties\":[{\"name\":\"xy\",\"kind\":\"Any\",\"default\":null},{\"name\":\"data\",\"kind\":\"Any\",\"default\":null}]}]}};\n",
+       "  var render_items = [{\"docid\":\"9dd80adb-9e45-4ddc-bfd3-39462bd19d3a\",\"roots\":{\"ecca8dc7-ad9f-4bb9-a04c-e79cd259eee0\":\"a44cc2e4-b649-479b-ae6e-d0e6e0cb4db4\"},\"root_ids\":[\"ecca8dc7-ad9f-4bb9-a04c-e79cd259eee0\"]}];\n",
+       "  var docs = Object.values(docs_json)\n",
+       "  if (!docs) {\n",
+       "    return\n",
+       "  }\n",
+       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
+       "  async function embed_document(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
+       "    for (const render_item of render_items) {\n",
+       "      for (const root_id of render_item.root_ids) {\n",
+       "\tconst id_el = document.getElementById(root_id)\n",
+       "\tif (id_el.children.length && id_el.children[0].hasAttribute('data-root-id')) {\n",
+       "\t  const root_el = id_el.children[0]\n",
+       "\t  root_el.id = root_el.id + '-rendered'\n",
+       "\t  for (const child of root_el.children) {\n",
+       "            // Ensure JupyterLab does not capture keyboard shortcuts\n",
+       "            // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
+       "\t    child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
+       "\t  }\n",
+       "\t}\n",
+       "      }\n",
+       "    }\n",
+       "  }\n",
+       "  function get_bokeh(root) {\n",
+       "    if (root.Bokeh === undefined) {\n",
+       "      return null\n",
+       "    } else if (root.Bokeh.version !== py_version) {\n",
+       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
+       "\treturn null\n",
+       "      }\n",
+       "      return root.Bokeh.versions.get(py_version);\n",
+       "    } else if (root.Bokeh.version === py_version) {\n",
+       "      return root.Bokeh\n",
+       "    }\n",
+       "    return null\n",
+       "  }\n",
+       "  function is_loaded(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
+       "  }\n",
+       "  if (is_loaded(root)) {\n",
+       "    embed_document(root);\n",
+       "  } else {\n",
+       "    var attempts = 0;\n",
+       "    var timer = setInterval(function(root) {\n",
+       "      if (is_loaded(root)) {\n",
+       "        clearInterval(timer);\n",
+       "        embed_document(root);\n",
+       "      } else if (document.readyState == \"complete\") {\n",
+       "        attempts++;\n",
+       "        if (attempts > 200) {\n",
+       "          clearInterval(timer);\n",
+       "\t  var Bokeh = get_bokeh(root)\n",
+       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
+       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
+       "\t  } else {\n",
+       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
+       "\t    embed_document(root)\n",
+       "\t  }\n",
+       "        }\n",
+       "      }\n",
+       "    }, 25, root)\n",
+       "  }\n",
+       "})(window);</script>"
+      ],
+      "text/plain": [
+       ":Sankey   [source,target]   (value)"
+      ]
+     },
+     "execution_count": 8,
+     "metadata": {
+      "application/vnd.holoviews_exec.v0+json": {
+       "id": "ecca8dc7-ad9f-4bb9-a04c-e79cd259eee0"
+      }
+     },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ep.pl.plot_sankey_time(\n",
+    "    edata_time, columns=[\"disease_flare\"], layer=\"layer_1\", state_labels={0: \"no flare\", 1: \"flare\"}, backend=\"bokeh\"\n",
+    ")"
+   ]
+  }
+ ],
+ "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": "3.13.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/tests/plot/_images/sankey_expected.png b/tests/plot/_images/sankey_expected.png
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literal 0
HcmV?d00001

diff --git a/tests/plot/test_sankey.py b/tests/plot/test_sankey.py
index 85f369b41..b87a79730 100644
--- a/tests/plot/test_sankey.py
+++ b/tests/plot/test_sankey.py
@@ -45,10 +45,23 @@ def diabetes_130_fairlearn_sample_100():
     return edata
 
 
-def test_sankey_plot(diabetes_130_fairlearn_sample_100):
+def test_sankey_plot(diabetes_130_fairlearn_sample_100, check_same_image):
     edata = diabetes_130_fairlearn_sample_100.copy()
 
-    sankey = ep.pl.plot_sankey(edata, columns=["gender", "race"])
+    sankey = ep.pl.plot_sankey(edata, columns=["gender", "race"], backend="matplotlib")
+    fig = hv.render(sankey, backend="matplotlib")
+
+    check_same_image(
+        fig=fig,
+        base_path=f"{_TEST_IMAGE_PATH}/sankey",
+        tol=2e-1,
+    )
+
+
+def test_sankey_bokeh_plot(diabetes_130_fairlearn_sample_100):
+    edata = diabetes_130_fairlearn_sample_100.copy()
+
+    sankey = ep.pl.plot_sankey(edata, columns=["gender", "race"], backend="bokeh")
 
     assert isinstance(sankey, hv.Sankey)
 
@@ -77,10 +90,30 @@ def test_sankey_plot(diabetes_130_fairlearn_sample_100):
         assert target.startswith("race:")  # targets have the correct prefix
 
 
-def test_sankey_time_plot(ehr_3d_mini):
+def test_sankey_time_plot(ehr_3d_mini, check_same_image):
+    edata = ehr_3d_mini
+    sankey_time = ep.pl.plot_sankey_time(
+        edata,
+        columns=["disease_flare"],
+        layer="layer_1",
+        state_labels={0: "no flare", 1: "flare"},
+        backend="matplotlib",
+    )
+
+    fig = hv.render(sankey_time, backend="matplotlib")
+
+    check_same_image(
+        fig=fig,
+        base_path=f"{_TEST_IMAGE_PATH}/sankey_time",
+        tol=2e-1,
+    )
+    return True
+
+
+def test_sankey_time_bokeh_plot(ehr_3d_mini):
     edata = ehr_3d_mini
     sankey = ep.pl.plot_sankey_time(
-        edata, columns=["disease_flare"], layer="layer_1", state_labels={0: "no flare", 1: "flare"}
+        edata, columns=["disease_flare"], layer="layer_1", state_labels={0: "no flare", 1: "flare"}, backend="bokeh"
     )
 
     assert isinstance(sankey, hv.Sankey)

From f67248737429c8ee2ca9ee626f641d4b1bb96306 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=C3=96yk=C3=BC=20S=C3=BCoglu?=
 <oeykue.sueoglu@helmholtz-munich.de>
Date: Wed, 10 Dec 2025 10:20:39 +0100
Subject: [PATCH 05/12] sankey added to init.py

---
 ehrapy/plot/__init__.py | 1 +
 1 file changed, 1 insertion(+)

diff --git a/ehrapy/plot/__init__.py b/ehrapy/plot/__init__.py
index c6d24b4ec..c6beca5da 100644
--- a/ehrapy/plot/__init__.py
+++ b/ehrapy/plot/__init__.py
@@ -12,5 +12,6 @@
 from ehrapy.plot._survival_analysis import cox_ph_forestplot, kaplan_meier, ols
 from ehrapy.plot.causal_inference._dowhy import causal_effect
 from ehrapy.plot.feature_ranking._feature_importances import rank_features_supervised
+from ehrapy.plot._sankey import plot_sankey, plot_sankey_time
 
 hv.extension("bokeh")

From 542a9fccfce072d5cdee11e2b5c26587d8f538da Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=C3=96yk=C3=BC=20S=C3=BCoglu?=
 <oeykue.sueoglu@helmholtz-munich.de>
Date: Wed, 10 Dec 2025 13:32:33 +0100
Subject: [PATCH 06/12] sankey_time_plot test more complex with more timeseries
 and more states

---
 ehrapy/plot/_sankey.py                      |   1 -
 tests/_scripts/sankey_expected.ipynb        | 286 +++++---------------
 tests/plot/_images/sankey_time_expected.png | Bin 37730 -> 54348 bytes
 tests/plot/test_sankey.py                   |  33 ++-
 4 files changed, 96 insertions(+), 224 deletions(-)

diff --git a/ehrapy/plot/_sankey.py b/ehrapy/plot/_sankey.py
index a47ef6c96..db61ad0e5 100644
--- a/ehrapy/plot/_sankey.py
+++ b/ehrapy/plot/_sankey.py
@@ -8,7 +8,6 @@
 import pandas as pd
 from holoviews import opts
 
-hv.extension("bokeh")
 
 if TYPE_CHECKING:
     from ehrdata import EHRData
diff --git a/tests/_scripts/sankey_expected.ipynb b/tests/_scripts/sankey_expected.ipynb
index fe894da12..396085771 100644
--- a/tests/_scripts/sankey_expected.ipynb
+++ b/tests/_scripts/sankey_expected.ipynb
@@ -50,12 +50,12 @@
      "data": {
       "application/vnd.holoviews_exec.v0+json": "",
       "text/html": [
-       "<div id='8fc37fff-4ea7-47a5-86a5-9c7da3739e93'>\n",
-       "  <div id=\"f0c5ea9a-cabb-4e77-bdba-c58b59a65d74\" data-root-id=\"8fc37fff-4ea7-47a5-86a5-9c7da3739e93\" style=\"display: contents;\"></div>\n",
+       "<div id='d292dc13-3464-42db-859f-422302252fd7'>\n",
+       "  <div id=\"fc647499-f484-4cbc-a5c0-f08bb72acbac\" data-root-id=\"d292dc13-3464-42db-859f-422302252fd7\" style=\"display: contents;\"></div>\n",
        "</div>\n",
        "<script type=\"application/javascript\">(function(root) {\n",
-       "  var docs_json = {\"1be2d97f-9b07-4bd1-9e22-f8d4ade659f0\":{\"version\":\"3.8.1\",\"title\":\"Bokeh 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-       "  var render_items = [{\"docid\":\"1be2d97f-9b07-4bd1-9e22-f8d4ade659f0\",\"roots\":{\"8fc37fff-4ea7-47a5-86a5-9c7da3739e93\":\"f0c5ea9a-cabb-4e77-bdba-c58b59a65d74\"},\"root_ids\":[\"8fc37fff-4ea7-47a5-86a5-9c7da3739e93\"]}];\n",
+       "  var docs_json = {\"e382699e-92a9-46e7-82de-53fa90130d81\":{\"version\":\"3.8.1\",\"title\":\"Bokeh 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+       "  var render_items = [{\"docid\":\"e382699e-92a9-46e7-82de-53fa90130d81\",\"roots\":{\"d292dc13-3464-42db-859f-422302252fd7\":\"fc647499-f484-4cbc-a5c0-f08bb72acbac\"},\"root_ids\":[\"d292dc13-3464-42db-859f-422302252fd7\"]}];\n",
        "  var docs = Object.values(docs_json)\n",
        "  if (!docs) {\n",
        "    return\n",
@@ -124,7 +124,7 @@
      },
      "metadata": {
       "application/vnd.holoviews_exec.v0+json": {
-       "id": "8fc37fff-4ea7-47a5-86a5-9c7da3739e93"
+       "id": "d292dc13-3464-42db-859f-422302252fd7"
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      "output_type": "display_data"
@@ -276,7 +276,7 @@
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   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 4,
    "id": "3351e8d3",
    "metadata": {},
    "outputs": [
@@ -324,12 +324,12 @@
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       "application/vnd.holoviews_exec.v0+json": "",
       "text/html": [
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+       "<div id='3861f770-ce95-460e-8f26-539b59c8eecd'>\n",
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        "</div>\n",
        "<script type=\"application/javascript\">(function(root) {\n",
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-       "  var render_items = [{\"docid\":\"4fe9d655-04d2-40d9-974c-94d3a4d7e096\",\"roots\":{\"09d6f56c-5fae-4f48-a37d-aa19a3e0f86c\":\"e13a378f-573a-4d07-885b-19a295a06b6c\"},\"root_ids\":[\"09d6f56c-5fae-4f48-a37d-aa19a3e0f86c\"]}];\n",
+       "  var docs_json = {\"fc92d563-d911-41d8-8b46-528de9d49a89\":{\"version\":\"3.8.1\",\"title\":\"Bokeh Application\",\"config\":{\"type\":\"object\",\"name\":\"DocumentConfig\",\"id\":\"2850a834-06dc-4e56-84c1-0ee640adae4b\",\"attributes\":{\"notifications\":{\"type\":\"object\",\"name\":\"Notifications\",\"id\":\"8c6ca38f-8724-4cf5-939f-6f00b0195a38\"}}},\"roots\":[{\"type\":\"object\",\"name\":\"panel.models.browser.BrowserInfo\",\"id\":\"3861f770-ce95-460e-8f26-539b59c8eecd\"},{\"type\":\"object\",\"name\":\"panel.models.comm_manager.CommManager\",\"id\":\"a6cc3fc5-6b4a-45cc-a1be-be1b21615217\",\"attributes\":{\"plot_id\":\"3861f770-ce95-460e-8f26-539b59c8eecd\",\"comm_id\":\"a8d2596783164a87ab7d10f0dfeed0b0\",\"client_comm_id\":\"74fe637fb9be4abbb07fa2067af7f83f\"}}],\"defs\":[{\"type\":\"model\",\"name\":\"ReactiveHTML1\"},{\"type\":\"model\",\"name\":\"FlexBox1\",\"properties\":[{\"name\":\"align_content\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"align_items\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"flex_direction\",\"kind\":\"Any\",\"default\":\"row\"},{\"name\":\"flex_wrap\",\"kind\":\"Any\",\"default\":\"wrap\"},{\"name\":\"gap\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"justify_content\",\"kind\":\"Any\",\"default\":\"flex-start\"}]},{\"type\":\"model\",\"name\":\"FloatPanel1\",\"properties\":[{\"name\":\"config\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"contained\",\"kind\":\"Any\",\"default\":true},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"right-top\"},{\"name\":\"offsetx\",\"kind\":\"Any\",\"default\":null},{\"name\":\"offsety\",\"kind\":\"Any\",\"default\":null},{\"name\":\"theme\",\"kind\":\"Any\",\"default\":\"primary\"},{\"name\":\"status\",\"kind\":\"Any\",\"default\":\"normalized\"}]},{\"type\":\"model\",\"name\":\"GridStack1\",\"properties\":[{\"name\":\"ncols\",\"kind\":\"Any\",\"default\":null},{\"name\":\"nrows\",\"kind\":\"Any\",\"default\":null},{\"name\":\"allow_resize\",\"kind\":\"Any\",\"default\":true},{\"name\":\"allow_drag\",\"kind\":\"Any\",\"default\":true},{\"name\":\"state\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"drag1\",\"properties\":[{\"name\":\"slider_width\",\"kind\":\"Any\",\"default\":5},{\"name\":\"slider_color\",\"kind\":\"Any\",\"default\":\"black\"},{\"name\":\"start\",\"kind\":\"Any\",\"default\":0},{\"name\":\"end\",\"kind\":\"Any\",\"default\":100},{\"name\":\"value\",\"kind\":\"Any\",\"default\":50}]},{\"type\":\"model\",\"name\":\"click1\",\"properties\":[{\"name\":\"terminal_output\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"debug_name\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"clears\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"ReactiveESM1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"JSComponent1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"ReactComponent1\",\"properties\":[{\"name\":\"use_shadow_dom\",\"kind\":\"Any\",\"default\":true},{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"AnyWidgetComponent1\",\"properties\":[{\"name\":\"use_shadow_dom\",\"kind\":\"Any\",\"default\":true},{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"FastWrapper1\",\"properties\":[{\"name\":\"object\",\"kind\":\"Any\",\"default\":null},{\"name\":\"style\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"NotificationArea1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"max_notifications\",\"kind\":\"Any\",\"default\":5},{\"name\":\"notifications\",\"kind\":\"Any\",\"default\":[]},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0},{\"name\":\"types\",\"kind\":\"Any\",\"default\":[{\"type\":\"map\",\"entries\":[[\"type\",\"warning\"],[\"background\",\"#ffc107\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-exclamation-triangle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]},{\"type\":\"map\",\"entries\":[[\"type\",\"info\"],[\"background\",\"#007bff\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-info-circle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]}]}]},{\"type\":\"model\",\"name\":\"Notification\",\"properties\":[{\"name\":\"background\",\"kind\":\"Any\",\"default\":null},{\"name\":\"duration\",\"kind\":\"Any\",\"default\":3000},{\"name\":\"icon\",\"kind\":\"Any\",\"default\":null},{\"name\":\"message\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"notification_type\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_rendered\",\"kind\":\"Any\",\"default\":false},{\"name\":\"_destroyed\",\"kind\":\"Any\",\"default\":false}]},{\"type\":\"model\",\"name\":\"TemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"BootstrapTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"TemplateEditor1\",\"properties\":[{\"name\":\"layout\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"MaterialTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"request_value1\",\"properties\":[{\"name\":\"fill\",\"kind\":\"Any\",\"default\":\"none\"},{\"name\":\"_synced\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_request_sync\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"holoviews.plotting.bokeh.raster.HoverModel\",\"properties\":[{\"name\":\"xy\",\"kind\":\"Any\",\"default\":null},{\"name\":\"data\",\"kind\":\"Any\",\"default\":null}]}]}};\n",
+       "  var render_items = [{\"docid\":\"fc92d563-d911-41d8-8b46-528de9d49a89\",\"roots\":{\"3861f770-ce95-460e-8f26-539b59c8eecd\":\"fdce3fab-e19b-474d-9b7e-9a7d5b8a50ae\"},\"root_ids\":[\"3861f770-ce95-460e-8f26-539b59c8eecd\"]}];\n",
        "  var docs = Object.values(docs_json)\n",
        "  if (!docs) {\n",
        "    return\n",
@@ -398,7 +398,7 @@
      },
      "metadata": {
       "application/vnd.holoviews_exec.v0+json": {
-       "id": "09d6f56c-5fae-4f48-a37d-aa19a3e0f86c"
+       "id": "3861f770-ce95-460e-8f26-539b59c8eecd"
       }
      },
      "output_type": "display_data"
@@ -566,99 +566,22 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 5,
    "id": "4b735603",
    "metadata": {},
    "outputs": [
-    {
-     "data": {},
-     "metadata": {},
-     "output_type": "display_data"
-    },
     {
      "data": {
-      "application/vnd.holoviews_exec.v0+json": "",
       "text/html": [
-       "<div id='c5a92859-0d7c-4c73-829e-94e05cc73cd1'>\n",
-       "  <div id=\"a2e41962-bd43-41c1-9fbf-6eeee14530d8\" data-root-id=\"c5a92859-0d7c-4c73-829e-94e05cc73cd1\" style=\"display: contents;\"></div>\n",
-       "</div>\n",
-       "<script type=\"application/javascript\">(function(root) {\n",
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-       "  var render_items = [{\"docid\":\"d5d98475-942d-42c4-951d-fd7ea71688ad\",\"roots\":{\"c5a92859-0d7c-4c73-829e-94e05cc73cd1\":\"a2e41962-bd43-41c1-9fbf-6eeee14530d8\"},\"root_ids\":[\"c5a92859-0d7c-4c73-829e-94e05cc73cd1\"]}];\n",
-       "  var docs = Object.values(docs_json)\n",
-       "  if (!docs) {\n",
-       "    return\n",
-       "  }\n",
-       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
-       "  async function embed_document(root) {\n",
-       "    var Bokeh = get_bokeh(root)\n",
-       "    await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
-       "    for (const render_item of render_items) {\n",
-       "      for (const root_id of render_item.root_ids) {\n",
-       "\tconst id_el = document.getElementById(root_id)\n",
-       "\tif (id_el.children.length && id_el.children[0].hasAttribute('data-root-id')) {\n",
-       "\t  const root_el = id_el.children[0]\n",
-       "\t  root_el.id = root_el.id + '-rendered'\n",
-       "\t  for (const child of root_el.children) {\n",
-       "            // Ensure JupyterLab does not capture keyboard shortcuts\n",
-       "            // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
-       "\t    child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
-       "\t  }\n",
-       "\t}\n",
-       "      }\n",
-       "    }\n",
-       "  }\n",
-       "  function get_bokeh(root) {\n",
-       "    if (root.Bokeh === undefined) {\n",
-       "      return null\n",
-       "    } else if (root.Bokeh.version !== py_version) {\n",
-       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
-       "\treturn null\n",
-       "      }\n",
-       "      return root.Bokeh.versions.get(py_version);\n",
-       "    } else if (root.Bokeh.version === py_version) {\n",
-       "      return root.Bokeh\n",
-       "    }\n",
-       "    return null\n",
-       "  }\n",
-       "  function is_loaded(root) {\n",
-       "    var Bokeh = get_bokeh(root)\n",
-       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
-       "  }\n",
-       "  if (is_loaded(root)) {\n",
-       "    embed_document(root);\n",
-       "  } else {\n",
-       "    var attempts = 0;\n",
-       "    var timer = setInterval(function(root) {\n",
-       "      if (is_loaded(root)) {\n",
-       "        clearInterval(timer);\n",
-       "        embed_document(root);\n",
-       "      } else if (document.readyState == \"complete\") {\n",
-       "        attempts++;\n",
-       "        if (attempts > 200) {\n",
-       "          clearInterval(timer);\n",
-       "\t  var Bokeh = get_bokeh(root)\n",
-       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
-       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
-       "\t  } else {\n",
-       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
-       "\t    embed_document(root)\n",
-       "\t  }\n",
-       "        }\n",
-       "      }\n",
-       "    }, 25, root)\n",
-       "  }\n",
-       "})(window);</script>"
+       "<img 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' style='max-width:100%; margin: auto; display: block; '/>"
       ],
       "text/plain": [
        ":Sankey   [source,target]   (value)"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 5,
      "metadata": {
-      "application/vnd.holoviews_exec.v0+json": {
-       "id": "c5a92859-0d7c-4c73-829e-94e05cc73cd1"
-      }
+      "application/vnd.holoviews_exec.v0+json": {}
      },
      "output_type": "execute_result"
     }
@@ -669,7 +592,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "id": "53b26cc8",
    "metadata": {},
    "outputs": [
@@ -717,12 +640,12 @@
      "data": {
       "application/vnd.holoviews_exec.v0+json": "",
       "text/html": [
-       "<div id='bff7933a-7268-435a-b674-4a963bda2ddd'>\n",
-       "  <div id=\"f77516cb-0a7c-4dbb-a7d9-baf32df9b47d\" data-root-id=\"bff7933a-7268-435a-b674-4a963bda2ddd\" style=\"display: contents;\"></div>\n",
+       "<div id='4b623405-3adc-45f6-a42e-a95b0e06a313'>\n",
+       "  <div id=\"bfa2e2f6-334f-447b-9d44-73aeaa27c5d2\" data-root-id=\"4b623405-3adc-45f6-a42e-a95b0e06a313\" style=\"display: contents;\"></div>\n",
        "</div>\n",
        "<script type=\"application/javascript\">(function(root) {\n",
-       "  var docs_json = {\"e1176385-e0e1-4f89-b9bc-cb7358da1bcf\":{\"version\":\"3.8.1\",\"title\":\"Bokeh 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+       "  var render_items = [{\"docid\":\"29b485c6-2547-4029-a5bb-1d7617c45c01\",\"roots\":{\"4b623405-3adc-45f6-a42e-a95b0e06a313\":\"bfa2e2f6-334f-447b-9d44-73aeaa27c5d2\"},\"root_ids\":[\"4b623405-3adc-45f6-a42e-a95b0e06a313\"]}];\n",
        "  var docs = Object.values(docs_json)\n",
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@@ -791,7 +714,7 @@
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fa-info-circle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]}]}]},{\"type\":\"model\",\"name\":\"Notification\",\"properties\":[{\"name\":\"background\",\"kind\":\"Any\",\"default\":null},{\"name\":\"duration\",\"kind\":\"Any\",\"default\":3000},{\"name\":\"icon\",\"kind\":\"Any\",\"default\":null},{\"name\":\"message\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"notification_type\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_rendered\",\"kind\":\"Any\",\"default\":false},{\"name\":\"_destroyed\",\"kind\":\"Any\",\"default\":false}]},{\"type\":\"model\",\"name\":\"TemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"BootstrapTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"TemplateEditor1\",\"properties\":[{\"name\":\"layout\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"MaterialTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"request_value1\",\"properties\":[{\"name\":\"fill\",\"kind\":\"Any\",\"default\":\"none\"},{\"name\":\"_synced\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_request_sync\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"holoviews.plotting.bokeh.raster.HoverModel\",\"properties\":[{\"name\":\"xy\",\"kind\":\"Any\",\"default\":null},{\"name\":\"data\",\"kind\":\"Any\",\"default\":null}]}]}};\n",
+       "  var render_items = [{\"docid\":\"ac796c77-942a-473e-a5db-c809186eeff3\",\"roots\":{\"4e054e45-2bea-484d-a8cc-4268c182c4f8\":\"f1cbd83b-d23e-4501-9795-fcf1fb2bd0f5\"},\"root_ids\":[\"4e054e45-2bea-484d-a8cc-4268c182c4f8\"]}];\n",
        "  var docs = Object.values(docs_json)\n",
        "  if (!docs) {\n",
        "    return\n",
@@ -984,10 +907,10 @@
        ":Sankey   [source,target]   (value)"
       ]
      },
-     "execution_count": 5,
+     "execution_count": 6,
      "metadata": {
       "application/vnd.holoviews_exec.v0+json": {
-       "id": "2f36f865-d75c-46e1-ad54-c38e44ce6c9f"
+       "id": "4e054e45-2bea-484d-a8cc-4268c182c4f8"
       }
      },
      "output_type": "execute_result"
@@ -999,30 +922,42 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "id": "a59e9a13",
    "metadata": {},
    "outputs": [],
    "source": [
     "layer = np.array(\n",
-    "    [\n",
-    "        [[1, 0, 1], [0, 1, 0]],  # patient 1: treatment, disease_flare\n",
-    "        [[0, 1, 1], [1, 0, 0]],  # patient 2: treatment, disease_flare\n",
-    "        [[1, 1, 0], [0, 0, 1]],  # patient 3: treatment, disease_flare\n",
-    "    ]\n",
-    ")\n",
+    "        [\n",
+    "            [[0, 1, 2, 1, 2], \n",
+    "             [1, 2, 1, 2, 0]],  \n",
+    "    \n",
+    "            [[1, 2, 0, 2, 1],\n",
+    "             [2, 1, 2, 1, 2]],\n",
+    "     \n",
+    "            [[2, 0, 1, 2, 0],\n",
+    "             [2, 0, 1, 1, 2]],\n",
+    "            \n",
+    "            [[1, 2, 1, 0, 1],\n",
+    "             [0, 2, 1, 2, 0]],\n",
+    "\n",
+    "            [[0, 2, 1, 2, 2],\n",
+    "             [1, 2, 1, 0, 2]],\n",
+    "        ]\n",
+    "    )\n",
+    "\n",
     "\n",
     "edata_time = ed.EHRData(\n",
     "    layers={\"layer_1\": layer},\n",
-    "    obs=pd.DataFrame(index=[\"patient_1\", \"patient_2\", \"patient_3\"]),\n",
+    "    obs=pd.DataFrame(index=[\"patient_1\", \"patient_2\", \"patient_3\", \"patient_4\", \"patient_5\"]),\n",
     "    var=pd.DataFrame(index=[\"treatment\", \"disease_flare\"]),\n",
-    "    tem=pd.DataFrame(index=[\"visit_0\", \"visit_1\", \"visit_2\"]),\n",
+    "    tem=pd.DataFrame(index=[\"visit_0\", \"visit_1\", \"visit_2\", \"visit_3\", \"visit_4\"]),\n",
     ")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "id": "dfb9988e",
    "metadata": {},
    "outputs": [
@@ -1070,12 +1005,12 @@
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       "application/vnd.holoviews_exec.v0+json": "",
       "text/html": [
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+       "<div id='7ad0e6b7-efa5-46b9-a68d-08c8c6a54534'>\n",
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        "</div>\n",
        "<script type=\"application/javascript\">(function(root) {\n",
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-       "  var render_items = [{\"docid\":\"8757a5e1-4d8c-43c1-856b-afc0f91a3ef1\",\"roots\":{\"df920d20-8dbb-4ca9-8dac-4d8cd7b5af9a\":\"a11749e2-9836-4877-94fb-252bee5cc512\"},\"root_ids\":[\"df920d20-8dbb-4ca9-8dac-4d8cd7b5af9a\"]}];\n",
+       "  var docs_json = {\"47a18783-4ff0-43dc-a0e2-b4055db69339\":{\"version\":\"3.8.1\",\"title\":\"Bokeh Application\",\"config\":{\"type\":\"object\",\"name\":\"DocumentConfig\",\"id\":\"ce49fc6a-0a18-4aa6-b224-4553083a3fd6\",\"attributes\":{\"notifications\":{\"type\":\"object\",\"name\":\"Notifications\",\"id\":\"b029def2-fd16-4045-8dd9-f2b83c76324c\"}}},\"roots\":[{\"type\":\"object\",\"name\":\"panel.models.browser.BrowserInfo\",\"id\":\"7ad0e6b7-efa5-46b9-a68d-08c8c6a54534\"},{\"type\":\"object\",\"name\":\"panel.models.comm_manager.CommManager\",\"id\":\"a8053525-2a43-4bb2-9e4f-7714ccf4b183\",\"attributes\":{\"plot_id\":\"7ad0e6b7-efa5-46b9-a68d-08c8c6a54534\",\"comm_id\":\"838ae2517445422685fc2a79e3088fa4\",\"client_comm_id\":\"23feeb7fa3b3467e89ba6ef67e809a5d\"}}],\"defs\":[{\"type\":\"model\",\"name\":\"ReactiveHTML1\"},{\"type\":\"model\",\"name\":\"FlexBox1\",\"properties\":[{\"name\":\"align_content\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"align_items\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"flex_direction\",\"kind\":\"Any\",\"default\":\"row\"},{\"name\":\"flex_wrap\",\"kind\":\"Any\",\"default\":\"wrap\"},{\"name\":\"gap\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"justify_content\",\"kind\":\"Any\",\"default\":\"flex-start\"}]},{\"type\":\"model\",\"name\":\"FloatPanel1\",\"properties\":[{\"name\":\"config\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"contained\",\"kind\":\"Any\",\"default\":true},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"right-top\"},{\"name\":\"offsetx\",\"kind\":\"Any\",\"default\":null},{\"name\":\"offsety\",\"kind\":\"Any\",\"default\":null},{\"name\":\"theme\",\"kind\":\"Any\",\"default\":\"primary\"},{\"name\":\"status\",\"kind\":\"Any\",\"default\":\"normalized\"}]},{\"type\":\"model\",\"name\":\"GridStack1\",\"properties\":[{\"name\":\"ncols\",\"kind\":\"Any\",\"default\":null},{\"name\":\"nrows\",\"kind\":\"Any\",\"default\":null},{\"name\":\"allow_resize\",\"kind\":\"Any\",\"default\":true},{\"name\":\"allow_drag\",\"kind\":\"Any\",\"default\":true},{\"name\":\"state\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"drag1\",\"properties\":[{\"name\":\"slider_width\",\"kind\":\"Any\",\"default\":5},{\"name\":\"slider_color\",\"kind\":\"Any\",\"default\":\"black\"},{\"name\":\"start\",\"kind\":\"Any\",\"default\":0},{\"name\":\"end\",\"kind\":\"Any\",\"default\":100},{\"name\":\"value\",\"kind\":\"Any\",\"default\":50}]},{\"type\":\"model\",\"name\":\"click1\",\"properties\":[{\"name\":\"terminal_output\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"debug_name\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"clears\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"ReactiveESM1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"JSComponent1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"ReactComponent1\",\"properties\":[{\"name\":\"use_shadow_dom\",\"kind\":\"Any\",\"default\":true},{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"AnyWidgetComponent1\",\"properties\":[{\"name\":\"use_shadow_dom\",\"kind\":\"Any\",\"default\":true},{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"FastWrapper1\",\"properties\":[{\"name\":\"object\",\"kind\":\"Any\",\"default\":null},{\"name\":\"style\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"NotificationArea1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"max_notifications\",\"kind\":\"Any\",\"default\":5},{\"name\":\"notifications\",\"kind\":\"Any\",\"default\":[]},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0},{\"name\":\"types\",\"kind\":\"Any\",\"default\":[{\"type\":\"map\",\"entries\":[[\"type\",\"warning\"],[\"background\",\"#ffc107\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas 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+       "  var render_items = [{\"docid\":\"47a18783-4ff0-43dc-a0e2-b4055db69339\",\"roots\":{\"7ad0e6b7-efa5-46b9-a68d-08c8c6a54534\":\"fd67529b-a024-44ab-9080-fa359f112eec\"},\"root_ids\":[\"7ad0e6b7-efa5-46b9-a68d-08c8c6a54534\"]}];\n",
        "  var docs = Object.values(docs_json)\n",
        "  if (!docs) {\n",
        "    return\n",
@@ -1144,7 +1079,7 @@
      },
      "metadata": {
       "application/vnd.holoviews_exec.v0+json": {
-       "id": "df920d20-8dbb-4ca9-8dac-4d8cd7b5af9a"
+       "id": "7ad0e6b7-efa5-46b9-a68d-08c8c6a54534"
       }
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      "output_type": "display_data"
@@ -1308,7 +1243,7 @@
     "    edata_time,\n",
     "    columns=[\"disease_flare\"],\n",
     "    layer=\"layer_1\",\n",
-    "    state_labels={0: \"no flare\", 1: \"flare\"},\n",
+    "    state_labels={0: \"no flare\", 1: \"mid flare\", 2: \"severe flare\"},\n",
     "    backend=\"matplotlib\",\n",
     ")\n",
     "\n",
@@ -1318,99 +1253,22 @@
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   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 9,
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    "metadata": {},
    "outputs": [
-    {
-     "data": {},
-     "metadata": {},
-     "output_type": "display_data"
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-       "  var render_items = [{\"docid\":\"afc78983-4b8a-4eb9-854a-8d62894e0468\",\"roots\":{\"05cb3ba7-6101-4037-baeb-a51a1b457da2\":\"f81ac94f-71e1-4743-b751-087c6130f818\"},\"root_ids\":[\"05cb3ba7-6101-4037-baeb-a51a1b457da2\"]}];\n",
-       "  var docs = Object.values(docs_json)\n",
-       "  if (!docs) {\n",
-       "    return\n",
-       "  }\n",
-       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
-       "  async function embed_document(root) {\n",
-       "    var Bokeh = get_bokeh(root)\n",
-       "    await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
-       "    for (const render_item of render_items) {\n",
-       "      for (const root_id of render_item.root_ids) {\n",
-       "\tconst id_el = document.getElementById(root_id)\n",
-       "\tif (id_el.children.length && id_el.children[0].hasAttribute('data-root-id')) {\n",
-       "\t  const root_el = id_el.children[0]\n",
-       "\t  root_el.id = root_el.id + '-rendered'\n",
-       "\t  for (const child of root_el.children) {\n",
-       "            // Ensure JupyterLab does not capture keyboard shortcuts\n",
-       "            // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
-       "\t    child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
-       "\t  }\n",
-       "\t}\n",
-       "      }\n",
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-       "  function get_bokeh(root) {\n",
-       "    if (root.Bokeh === undefined) {\n",
-       "      return null\n",
-       "    } else if (root.Bokeh.version !== py_version) {\n",
-       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
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-       "        if (attempts > 200) {\n",
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-       "\t  var Bokeh = get_bokeh(root)\n",
-       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
-       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
-       "\t  } else {\n",
-       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
-       "\t    embed_document(root)\n",
-       "\t  }\n",
-       "        }\n",
-       "      }\n",
-       "    }, 25, root)\n",
-       "  }\n",
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' style='max-width:100%; margin: auto; display: block; '/>"
       ],
       "text/plain": [
        ":Sankey   [source,target]   (value)"
       ]
      },
-     "execution_count": 10,
+     "execution_count": 9,
      "metadata": {
-      "application/vnd.holoviews_exec.v0+json": {
-       "id": "05cb3ba7-6101-4037-baeb-a51a1b457da2"
-      }
+      "application/vnd.holoviews_exec.v0+json": {}
      },
      "output_type": "execute_result"
     }
@@ -1421,7 +1279,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 10,
    "id": "38907509",
    "metadata": {},
    "outputs": [
@@ -1469,12 +1327,12 @@
      "data": {
       "application/vnd.holoviews_exec.v0+json": "",
       "text/html": [
-       "<div id='3a9abedd-73f5-4726-91d0-ed70606c5d0f'>\n",
-       "  <div id=\"d4cfc109-ec03-4ddf-a271-5545c87d676d\" data-root-id=\"3a9abedd-73f5-4726-91d0-ed70606c5d0f\" style=\"display: contents;\"></div>\n",
+       "<div id='9b1a6df2-903d-4967-9384-104ce84a0cea'>\n",
+       "  <div id=\"bcb45503-8765-4434-a3b3-d6c444e50221\" data-root-id=\"9b1a6df2-903d-4967-9384-104ce84a0cea\" style=\"display: contents;\"></div>\n",
        "</div>\n",
        "<script type=\"application/javascript\">(function(root) {\n",
-       "  var docs_json = {\"93985596-3646-48f0-b1da-c808f7ed3c11\":{\"version\":\"3.8.1\",\"title\":\"Bokeh 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        "  var docs = Object.values(docs_json)\n",
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fa-info-circle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]}]}]},{\"type\":\"model\",\"name\":\"Notification\",\"properties\":[{\"name\":\"background\",\"kind\":\"Any\",\"default\":null},{\"name\":\"duration\",\"kind\":\"Any\",\"default\":3000},{\"name\":\"icon\",\"kind\":\"Any\",\"default\":null},{\"name\":\"message\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"notification_type\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_rendered\",\"kind\":\"Any\",\"default\":false},{\"name\":\"_destroyed\",\"kind\":\"Any\",\"default\":false}]},{\"type\":\"model\",\"name\":\"TemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"BootstrapTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"TemplateEditor1\",\"properties\":[{\"name\":\"layout\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"MaterialTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"request_value1\",\"properties\":[{\"name\":\"fill\",\"kind\":\"Any\",\"default\":\"none\"},{\"name\":\"_synced\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_request_sync\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"holoviews.plotting.bokeh.raster.HoverModel\",\"properties\":[{\"name\":\"xy\",\"kind\":\"Any\",\"default\":null},{\"name\":\"data\",\"kind\":\"Any\",\"default\":null}]}]}};\n",
+       "  var render_items = [{\"docid\":\"e33249d4-4bf0-4892-9267-5d1444d6464a\",\"roots\":{\"fb57819f-f792-458d-87fb-43d4a5875885\":\"b6b12b01-4b08-452f-acf4-58b0b888c3d5\"},\"root_ids\":[\"fb57819f-f792-458d-87fb-43d4a5875885\"]}];\n",
        "  var docs = Object.values(docs_json)\n",
        "  if (!docs) {\n",
        "    return\n",
@@ -1736,10 +1594,10 @@
        ":Sankey   [source,target]   (value)"
       ]
      },
-     "execution_count": 8,
+     "execution_count": 10,
      "metadata": {
       "application/vnd.holoviews_exec.v0+json": {
-       "id": "ecca8dc7-ad9f-4bb9-a04c-e79cd259eee0"
+       "id": "fb57819f-f792-458d-87fb-43d4a5875885"
       }
      },
      "output_type": "execute_result"
@@ -1747,7 +1605,7 @@
    ],
    "source": [
     "ep.pl.plot_sankey_time(\n",
-    "    edata_time, columns=[\"disease_flare\"], layer=\"layer_1\", state_labels={0: \"no flare\", 1: \"flare\"}, backend=\"bokeh\"\n",
+    "    edata_time, columns=[\"disease_flare\"], layer=\"layer_1\", state_labels={0: \"no flare\",  1: \"mid flare\", 2: \"severe flare\"}, backend=\"bokeh\"\n",
     ")"
    ]
   }
diff --git a/tests/plot/_images/sankey_time_expected.png b/tests/plot/_images/sankey_time_expected.png
index 39c205bf8f9bc29fa175c6c222163287bda87c74..ff3b74c5a3ab431f4f4553f73c534e8453a01051 100644
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diff --git a/tests/plot/test_sankey.py b/tests/plot/test_sankey.py
index b87a79730..dcee7540b 100644
--- a/tests/plot/test_sankey.py
+++ b/tests/plot/test_sankey.py
@@ -16,19 +16,30 @@
 def ehr_3d_mini():
     layer = np.array(
         [
-            [[1, 0, 1], [0, 1, 0]],
-            [[0, 1, 1], [1, 0, 0]],
-            [[1, 1, 0], [0, 0, 1]],
+            [[0, 1, 2, 1, 2], 
+             [1, 2, 1, 2, 0]],  
+    
+            [[1, 2, 0, 2, 1],
+             [2, 1, 2, 1, 2]],
+     
+            [[2, 0, 1, 2, 0],
+             [2, 0, 1, 1, 2]],
+            
+            [[1, 2, 1, 0, 1],
+             [0, 2, 1, 2, 0]],
+
+            [[0, 2, 1, 2, 2],
+             [1, 2, 1, 0, 2]],
         ]
     )
 
     edata = ed.EHRData(
         layers={"layer_1": layer},
-        obs=pd.DataFrame(index=["patient 1", "patient 2", "patient 3"]),
+        obs=pd.DataFrame(index=["patient 1", "patient 2", "patient 3", "patient 4", "patient 5"]),
         # obs_names=["patient 1", "patient 2", "patient 3"],
         var=pd.DataFrame(index=["treatment", "disease_flare"]),
         # var_names=["treatment", "disease_flare"],
-        tem=pd.DataFrame(index=["visit_0", "visit_1", "visit_2"]),
+        tem=pd.DataFrame(index=["visit_0", "visit_1", "visit_2", "visit_3", "visit_4"]),
     )
     return edata
 
@@ -96,7 +107,7 @@ def test_sankey_time_plot(ehr_3d_mini, check_same_image):
         edata,
         columns=["disease_flare"],
         layer="layer_1",
-        state_labels={0: "no flare", 1: "flare"},
+        state_labels={0: "no flare", 1: "mid flare", 2: "severe flare"},
         backend="matplotlib",
     )
 
@@ -107,13 +118,17 @@ def test_sankey_time_plot(ehr_3d_mini, check_same_image):
         base_path=f"{_TEST_IMAGE_PATH}/sankey_time",
         tol=2e-1,
     )
-    return True
+
 
 
 def test_sankey_time_bokeh_plot(ehr_3d_mini):
     edata = ehr_3d_mini
     sankey = ep.pl.plot_sankey_time(
-        edata, columns=["disease_flare"], layer="layer_1", state_labels={0: "no flare", 1: "flare"}, backend="bokeh"
+        edata, 
+        columns=["disease_flare"], 
+        layer="layer_1", 
+        state_labels={0: "no flare", 1: " mid flare", 2: "severe flare"}, 
+        backend="bokeh"
     )
 
     assert isinstance(sankey, hv.Sankey)
@@ -127,7 +142,7 @@ def test_sankey_time_bokeh_plot(ehr_3d_mini):
     assert (data["value"] > 0).all()
 
     # check that sources and targets contain state labels
-    state_labels = ["no flare", "flare"]
+    state_labels = ["no flare", "mid flare", "severe flare"]
     for source in data["source"].unique():
         assert any(label in source for label in state_labels)
         assert "(" in source and ")" in source

From 14abe6ec00487b951e5350e4edaec8689f65bbee Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Wed, 10 Dec 2025 12:33:35 +0000
Subject: [PATCH 07/12] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 ehrapy/plot/__init__.py              |  2 +-
 ehrapy/plot/_sankey.py               |  1 -
 tests/_scripts/sankey_expected.ipynb | 31 ++++++++++++----------------
 tests/plot/test_sankey.py            | 30 +++++++++------------------
 4 files changed, 24 insertions(+), 40 deletions(-)

diff --git a/ehrapy/plot/__init__.py b/ehrapy/plot/__init__.py
index c6beca5da..a646442d8 100644
--- a/ehrapy/plot/__init__.py
+++ b/ehrapy/plot/__init__.py
@@ -8,10 +8,10 @@
     missing_values_heatmap,
     missing_values_matrix,
 )
+from ehrapy.plot._sankey import plot_sankey, plot_sankey_time
 from ehrapy.plot._scanpy_pl_api import *  # noqa: F403
 from ehrapy.plot._survival_analysis import cox_ph_forestplot, kaplan_meier, ols
 from ehrapy.plot.causal_inference._dowhy import causal_effect
 from ehrapy.plot.feature_ranking._feature_importances import rank_features_supervised
-from ehrapy.plot._sankey import plot_sankey, plot_sankey_time
 
 hv.extension("bokeh")
diff --git a/ehrapy/plot/_sankey.py b/ehrapy/plot/_sankey.py
index db61ad0e5..8b9b1a49c 100644
--- a/ehrapy/plot/_sankey.py
+++ b/ehrapy/plot/_sankey.py
@@ -8,7 +8,6 @@
 import pandas as pd
 from holoviews import opts
 
-
 if TYPE_CHECKING:
     from ehrdata import EHRData
 
diff --git a/tests/_scripts/sankey_expected.ipynb b/tests/_scripts/sankey_expected.ipynb
index 396085771..a9e9f170b 100644
--- a/tests/_scripts/sankey_expected.ipynb
+++ b/tests/_scripts/sankey_expected.ipynb
@@ -928,23 +928,14 @@
    "outputs": [],
    "source": [
     "layer = np.array(\n",
-    "        [\n",
-    "            [[0, 1, 2, 1, 2], \n",
-    "             [1, 2, 1, 2, 0]],  \n",
-    "    \n",
-    "            [[1, 2, 0, 2, 1],\n",
-    "             [2, 1, 2, 1, 2]],\n",
-    "     \n",
-    "            [[2, 0, 1, 2, 0],\n",
-    "             [2, 0, 1, 1, 2]],\n",
-    "            \n",
-    "            [[1, 2, 1, 0, 1],\n",
-    "             [0, 2, 1, 2, 0]],\n",
-    "\n",
-    "            [[0, 2, 1, 2, 2],\n",
-    "             [1, 2, 1, 0, 2]],\n",
-    "        ]\n",
-    "    )\n",
+    "    [\n",
+    "        [[0, 1, 2, 1, 2], [1, 2, 1, 2, 0]],\n",
+    "        [[1, 2, 0, 2, 1], [2, 1, 2, 1, 2]],\n",
+    "        [[2, 0, 1, 2, 0], [2, 0, 1, 1, 2]],\n",
+    "        [[1, 2, 1, 0, 1], [0, 2, 1, 2, 0]],\n",
+    "        [[0, 2, 1, 2, 2], [1, 2, 1, 0, 2]],\n",
+    "    ]\n",
+    ")\n",
     "\n",
     "\n",
     "edata_time = ed.EHRData(\n",
@@ -1605,7 +1596,11 @@
    ],
    "source": [
     "ep.pl.plot_sankey_time(\n",
-    "    edata_time, columns=[\"disease_flare\"], layer=\"layer_1\", state_labels={0: \"no flare\",  1: \"mid flare\", 2: \"severe flare\"}, backend=\"bokeh\"\n",
+    "    edata_time,\n",
+    "    columns=[\"disease_flare\"],\n",
+    "    layer=\"layer_1\",\n",
+    "    state_labels={0: \"no flare\", 1: \"mid flare\", 2: \"severe flare\"},\n",
+    "    backend=\"bokeh\",\n",
     ")"
    ]
   }
diff --git a/tests/plot/test_sankey.py b/tests/plot/test_sankey.py
index dcee7540b..c9d9d94f5 100644
--- a/tests/plot/test_sankey.py
+++ b/tests/plot/test_sankey.py
@@ -16,20 +16,11 @@
 def ehr_3d_mini():
     layer = np.array(
         [
-            [[0, 1, 2, 1, 2], 
-             [1, 2, 1, 2, 0]],  
-    
-            [[1, 2, 0, 2, 1],
-             [2, 1, 2, 1, 2]],
-     
-            [[2, 0, 1, 2, 0],
-             [2, 0, 1, 1, 2]],
-            
-            [[1, 2, 1, 0, 1],
-             [0, 2, 1, 2, 0]],
-
-            [[0, 2, 1, 2, 2],
-             [1, 2, 1, 0, 2]],
+            [[0, 1, 2, 1, 2], [1, 2, 1, 2, 0]],
+            [[1, 2, 0, 2, 1], [2, 1, 2, 1, 2]],
+            [[2, 0, 1, 2, 0], [2, 0, 1, 1, 2]],
+            [[1, 2, 1, 0, 1], [0, 2, 1, 2, 0]],
+            [[0, 2, 1, 2, 2], [1, 2, 1, 0, 2]],
         ]
     )
 
@@ -120,15 +111,14 @@ def test_sankey_time_plot(ehr_3d_mini, check_same_image):
     )
 
 
-
 def test_sankey_time_bokeh_plot(ehr_3d_mini):
     edata = ehr_3d_mini
     sankey = ep.pl.plot_sankey_time(
-        edata, 
-        columns=["disease_flare"], 
-        layer="layer_1", 
-        state_labels={0: "no flare", 1: " mid flare", 2: "severe flare"}, 
-        backend="bokeh"
+        edata,
+        columns=["disease_flare"],
+        layer="layer_1",
+        state_labels={0: "no flare", 1: " mid flare", 2: "severe flare"},
+        backend="bokeh",
     )
 
     assert isinstance(sankey, hv.Sankey)

From 5900d21c84237df28ac27f2f8a93ad3ab826d511 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=C3=96yk=C3=BC=20S=C3=BCoglu?=
 <oeykue.sueoglu@helmholtz-munich.de>
Date: Fri, 12 Dec 2025 09:26:51 +0100
Subject: [PATCH 08/12] backend argument in plotting functions removed

---
 ehrapy/plot/_sankey.py                        |   13 +-
 tests/_scripts/sankey_bokeh_expected.ipynb    |  775 ++++++++
 tests/_scripts/sankey_expected.ipynb          | 1634 -----------------
 .../_scripts/sankey_matplotlib_expected.ipynb |  696 +++++++
 tests/plot/test_sankey.py                     |   73 +-
 5 files changed, 1508 insertions(+), 1683 deletions(-)
 create mode 100644 tests/_scripts/sankey_bokeh_expected.ipynb
 delete mode 100644 tests/_scripts/sankey_expected.ipynb
 create mode 100644 tests/_scripts/sankey_matplotlib_expected.ipynb

diff --git a/ehrapy/plot/_sankey.py b/ehrapy/plot/_sankey.py
index db61ad0e5..223d8942a 100644
--- a/ehrapy/plot/_sankey.py
+++ b/ehrapy/plot/_sankey.py
@@ -8,7 +8,6 @@
 import pandas as pd
 from holoviews import opts
 
-
 if TYPE_CHECKING:
     from ehrdata import EHRData
 
@@ -32,16 +31,17 @@ def plot_sankey(
     edata: EHRData,
     *,
     columns: list[str],
-    backend: str | None = None,
     show: bool = False,
     **kwargs,
 ) -> hv.Sankey:
     """Create a Sankey diagram showing relationships across observation columns.
 
+    Please run `hv.extension('matplotlib')` or `hv.extension('bokeh')` before using this function to determine the backend.
+
+
     Args:
         edata : Central data object containing observation data
         columns : Column names from edata.obs to visualize
-        backend: HoloViews backend to use ("matplotlib" or"bokeh"). Default: "matplotlib"
         show: If True, display the plot immediately. If False, only return the plot object without displaying.
         **kwargs: Additional styling options passed to `holoviews.opts.Sankey`. See HoloViews Sankey documentation for full list of options.
 
@@ -54,8 +54,6 @@ def plot_sankey(
         >>> ep.pl.plot_sankey(edata, columns=["gender", "race"])
 
     """
-    _set_hv_backend(backend)
-
     df = edata.obs[columns]
 
     labels = []
@@ -109,7 +107,6 @@ def plot_sankey_time(
     columns: list[str],
     layer: str,
     state_labels: dict[int, str] | None = None,
-    backend: str | None = None,
     show: bool = False,
     **kwargs,
 ) -> hv.Sankey:
@@ -120,6 +117,8 @@ def plot_sankey_time(
     Each node represents a state at a specific time point, and flows show the
     number of patients transitioning between states.
 
+    Please run `hv.extension('matplotlib')` or `hv.extension('bokeh')` before using this function to determine the backend.
+
     Args:
         edata: Central data object containing observation data
         columns: Column names from edata.obs to visualize
@@ -157,8 +156,6 @@ def plot_sankey_time(
 
 
     """
-    _set_hv_backend(backend)
-
     flare_data = edata[:, edata.var_names.isin(columns), :].layers[layer][:, 0, :]
 
     time_steps = edata.tem.index.tolist()
diff --git a/tests/_scripts/sankey_bokeh_expected.ipynb b/tests/_scripts/sankey_bokeh_expected.ipynb
new file mode 100644
index 000000000..29fcca3b3
--- /dev/null
+++ b/tests/_scripts/sankey_bokeh_expected.ipynb
@@ -0,0 +1,775 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "42a55492",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<script type=\"esms-options\">{\"shimMode\": true}</script><style>*[data-root-id],\n",
+       "*[data-root-id] > * {\n",
+       "  box-sizing: border-box;\n",
+       "  font-family: var(--jp-ui-font-family);\n",
+       "  font-size: var(--jp-ui-font-size1);\n",
+       "  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
+       "}\n",
+       "\n",
+       "/* Override VSCode background color */\n",
+       ".cell-output-ipywidget-background:has(\n",
+       "  > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
+       "),\n",
+       ".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "</style>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/javascript": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  const force = true;\n  const py_version = '3.8.1'.replace('rc', '-rc.').replace('.dev', '-dev.');\n  const reloading = false;\n  const Bokeh = root.Bokeh;\n\n  // Set a timeout for this load but only if we are not already initializing\n  if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks;\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n    if (js_modules == null) js_modules = [];\n    if (js_exports == null) js_exports = {};\n\n    root._bokeh_onload_callbacks.push(callback);\n\n    if (root._bokeh_is_loading > 0) {\n      // Don't load bokeh if it is still initializing\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n      // There is nothing to load\n      run_callbacks();\n      return null;\n    }\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n    window._bokeh_on_load = on_load\n\n    function on_error(e) {\n      const src_el = e.srcElement\n      console.error(\"failed to load \" + (src_el.href || src_el.src));\n    }\n\n    const skip = [];\n    if (window.requirejs) {\n      window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n      root._bokeh_is_loading = css_urls.length + 0;\n    } else {\n      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n    }\n\n    const existing_stylesheets = []\n    const links = document.getElementsByTagName('link')\n    for (let i = 0; i < links.length; i++) {\n      const link = links[i]\n      if (link.href != null) {\n        existing_stylesheets.push(link.href)\n      }\n    }\n    for (let i = 0; i < css_urls.length; i++) {\n      const url = css_urls[i];\n      const escaped = encodeURI(url)\n      if (existing_stylesheets.indexOf(escaped) !== -1) {\n        on_load()\n        continue;\n      }\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }    var existing_scripts = []\n    const scripts = document.getElementsByTagName('script')\n    for (let i = 0; i < scripts.length; i++) {\n      var script = scripts[i]\n      if (script.src != null) {\n        existing_scripts.push(script.src)\n      }\n    }\n    for (let i = 0; i < js_urls.length; i++) {\n      const url = js_urls[i];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      const element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (let i = 0; i < js_modules.length; i++) {\n      const url = js_modules[i];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (const name in js_exports) {\n      const url = js_exports[name];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      var element = document.createElement('script');\n      element.onerror = on_error;\n      element.async = false;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      element.textContent = `\n      import ${name} from \"${url}\"\n      window.${name} = ${name}\n      window._bokeh_on_load()\n      `\n      document.head.appendChild(element);\n    }\n    if (!js_urls.length && !js_modules.length) {\n      on_load()\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  const js_urls = [\"https://cdn.holoviz.org/panel/1.8.3/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-3.8.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.8.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.8.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.8.1.min.js\", \"https://cdn.holoviz.org/panel/1.8.3/dist/panel.min.js\"];\n  const js_modules = [];\n  const js_exports = {};\n  const css_urls = [];\n  const inline_js = [    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n  ];\n\n  function run_inline_js() {\n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (let i = 0; i < inline_js.length; i++) {\n        try {\n          inline_js[i].call(root, root.Bokeh);\n        } catch(e) {\n          if (!reloading) {\n            throw e;\n          }\n        }\n      }\n      // Cache old bokeh versions\n      if (Bokeh != undefined && !reloading) {\n        var NewBokeh = root.Bokeh;\n        if (Bokeh.versions === undefined) {\n          Bokeh.versions = new Map();\n        }\n        if (NewBokeh.version !== Bokeh.version) {\n          Bokeh.versions.set(NewBokeh.version, NewBokeh)\n        }\n        root.Bokeh = Bokeh;\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    }\n    root._bokeh_is_initializing = false\n  }\n\n  function load_or_wait() {\n    // Implement a backoff loop that tries to ensure we do not load multiple\n    // versions of Bokeh and its dependencies at the same time.\n    // In recent versions we use the root._bokeh_is_initializing flag\n    // to determine whether there is an ongoing attempt to initialize\n    // bokeh, however for backward compatibility we also try to ensure\n    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n    // before older versions are fully initialized.\n    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n      // If the timeout and bokeh was not successfully loaded we reset\n      // everything and try loading again\n      root._bokeh_timeout = Date.now() + 5000;\n      root._bokeh_is_initializing = false;\n      root._bokeh_onload_callbacks = undefined;\n      root._bokeh_is_loading = 0\n      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n      load_or_wait();\n    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n      setTimeout(load_or_wait, 100);\n    } else {\n      root._bokeh_is_initializing = true\n      root._bokeh_onload_callbacks = []\n      const bokeh_loaded = root.Bokeh != null && (root.Bokeh.version === py_version || (root.Bokeh.versions !== undefined && root.Bokeh.versions.has(py_version)));\n      if (!reloading && !bokeh_loaded) {\n        if (root.Bokeh) {\n          root.Bokeh = undefined;\n        }\n        console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n      }\n      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n        console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n        run_inline_js();\n      });\n    }\n  }\n  // Give older versions of the autoload script a head-start to ensure\n  // they initialize before we start loading newer version.\n  setTimeout(load_or_wait, 100)\n}(window));",
+      "application/vnd.holoviews_load.v0+json": ""
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/javascript": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n  window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n    function JupyterCommManager() {\n    }\n\n    JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n      if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        comm_manager.register_target(comm_id, function(comm) {\n          comm.on_msg(msg_handler);\n        });\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n          comm.onMsg = msg_handler;\n        });\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        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(Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n        if (msg_handler) {\n          comm.on_msg(msg_handler);\n        }\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n        let retries = 0;\n        const open = () => {\n          if (comm.active) {\n            comm.open();\n          } else if (retries > 3) {\n            console.warn('Comm target never activated')\n          } else {\n            retries += 1\n            setTimeout(open, 500)\n          }\n        }\n        if (comm.active) {\n          comm.open();\n        } else {\n          setTimeout(open, 500)\n        }\n        if (msg_handler) {\n          comm.onMsg = msg_handler;\n        }\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        var comm_promise = google.colab.kernel.comms.open(comm_id)\n        comm_promise.then((comm) => {\n          window.PyViz.comms[comm_id] = comm;\n          if (msg_handler) {\n            var messages = comm.messages[Symbol.asyncIterator]();\n            function processIteratorResult(result) {\n              var message = result.value;\n              var content = {data: message.data};\n              var metadata = message.metadata || {comm_id};\n              var msg = {content, metadata}\n              msg_handler(msg);\n              return messages.next().then(processIteratorResult);\n            }\n            return messages.next().then(processIteratorResult);\n          }\n        })\n        var sendClosure = (data, metadata, buffers, disposeOnDone) => {\n          return comm_promise.then((comm) => {\n            comm.send(data, metadata, buffers, disposeOnDone);\n          });\n        };\n        var comm = {\n          send: sendClosure\n        };\n      }\n      window.PyViz.comms[comm_id] = comm;\n      return comm;\n    }\n    window.PyViz.comm_manager = new JupyterCommManager();\n    \n\n\nvar JS_MIME_TYPE = 'application/javascript';\nvar HTML_MIME_TYPE = 'text/html';\nvar EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\nvar CLASS_NAME = 'output';\n\n/**\n * Render data to the DOM node\n */\nfunction render(props, node) {\n  var div = document.createElement(\"div\");\n  var script = document.createElement(\"script\");\n  node.appendChild(div);\n  node.appendChild(script);\n}\n\n/**\n * Handle when a new output is added\n */\nfunction handle_add_output(event, handle) {\n  var output_area = handle.output_area;\n  var output = handle.output;\n  if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n    return\n  }\n  var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n  var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n  if (id !== undefined) {\n    var nchildren = toinsert.length;\n    var html_node = toinsert[nchildren-1].children[0];\n    html_node.innerHTML = output.data[HTML_MIME_TYPE];\n    var scripts = [];\n    var nodelist = html_node.querySelectorAll(\"script\");\n    for (var i in nodelist) {\n      if (nodelist.hasOwnProperty(i)) {\n        scripts.push(nodelist[i])\n      }\n    }\n\n    scripts.forEach( function (oldScript) {\n      var newScript = document.createElement(\"script\");\n      var attrs = [];\n      var nodemap = oldScript.attributes;\n      for (var j in nodemap) {\n        if (nodemap.hasOwnProperty(j)) {\n          attrs.push(nodemap[j])\n        }\n      }\n      attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n      newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n      oldScript.parentNode.replaceChild(newScript, oldScript);\n    });\n    if (JS_MIME_TYPE in output.data) {\n      toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n    }\n    output_area._hv_plot_id = id;\n    if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n      window.PyViz.plot_index[id] = Bokeh.index[id];\n    } else {\n      window.PyViz.plot_index[id] = null;\n    }\n  } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n    var bk_div = document.createElement(\"div\");\n    bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n    var script_attrs = bk_div.children[0].attributes;\n    for (var i = 0; i < script_attrs.length; i++) {\n      toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n    }\n    // store reference to server id on output_area\n    output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n  }\n}\n\n/**\n * Handle when an output is cleared or removed\n */\nfunction handle_clear_output(event, handle) {\n  var id = handle.cell.output_area._hv_plot_id;\n  var server_id = handle.cell.output_area._bokeh_server_id;\n  if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n  var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n  if (server_id !== null) {\n    comm.send({event_type: 'server_delete', 'id': server_id});\n    return;\n  } else if (comm !== null) {\n    comm.send({event_type: 'delete', 'id': id});\n  }\n  delete PyViz.plot_index[id];\n  if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n    var doc = window.Bokeh.index[id].model.document\n    doc.clear();\n    const i = window.Bokeh.documents.indexOf(doc);\n    if (i > -1) {\n      window.Bokeh.documents.splice(i, 1);\n    }\n  }\n}\n\n/**\n * Handle kernel restart event\n */\nfunction handle_kernel_cleanup(event, handle) {\n  delete PyViz.comms[\"hv-extension-comm\"];\n  window.PyViz.plot_index = {}\n}\n\n/**\n * Handle update_display_data messages\n */\nfunction handle_update_output(event, handle) {\n  handle_clear_output(event, {cell: {output_area: handle.output_area}})\n  handle_add_output(event, handle)\n}\n\nfunction register_renderer(events, OutputArea) {\n  function append_mime(data, metadata, element) {\n    // create a DOM node to render to\n    var toinsert = this.create_output_subarea(\n    metadata,\n    CLASS_NAME,\n    EXEC_MIME_TYPE\n    );\n    this.keyboard_manager.register_events(toinsert);\n    // Render to node\n    var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n    render(props, toinsert[0]);\n    element.append(toinsert);\n    return toinsert\n  }\n\n  events.on('output_added.OutputArea', handle_add_output);\n  events.on('output_updated.OutputArea', handle_update_output);\n  events.on('clear_output.CodeCell', handle_clear_output);\n  events.on('delete.Cell', handle_clear_output);\n  events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n\n  OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n    safe: true,\n    index: 0\n  });\n}\n\nif (window.Jupyter !== undefined) {\n  try {\n    var events = require('base/js/events');\n    var OutputArea = require('notebook/js/outputarea').OutputArea;\n    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n      register_renderer(events, OutputArea);\n    }\n  } catch(err) {\n  }\n}\n",
+      "application/vnd.holoviews_load.v0+json": ""
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.holoviews_exec.v0+json": "",
+      "text/html": [
+       "<div id='1ca26b78-2b9d-4973-bed6-c78e6bb73cd0'>\n",
+       "  <div id=\"c653ad2b-675a-4083-a61a-100dab2923e5\" data-root-id=\"1ca26b78-2b9d-4973-bed6-c78e6bb73cd0\" style=\"display: contents;\"></div>\n",
+       "</div>\n",
+       "<script type=\"application/javascript\">(function(root) {\n",
+       "  var docs_json = {\"63739db0-1a74-4ff6-a2d8-28d39aaf33d6\":{\"version\":\"3.8.1\",\"title\":\"Bokeh Application\",\"config\":{\"type\":\"object\",\"name\":\"DocumentConfig\",\"id\":\"13bad953-8a0a-431d-9e59-224c45d49f7b\",\"attributes\":{\"notifications\":{\"type\":\"object\",\"name\":\"Notifications\",\"id\":\"d9a593d4-ce53-4adf-89fa-8105fb1c3a4f\"}}},\"roots\":[{\"type\":\"object\",\"name\":\"panel.models.browser.BrowserInfo\",\"id\":\"1ca26b78-2b9d-4973-bed6-c78e6bb73cd0\"},{\"type\":\"object\",\"name\":\"panel.models.comm_manager.CommManager\",\"id\":\"47b94636-03b6-4643-bced-2fd36534f96d\",\"attributes\":{\"plot_id\":\"1ca26b78-2b9d-4973-bed6-c78e6bb73cd0\",\"comm_id\":\"71a82403470d4924b0fb3d7389d745b6\",\"client_comm_id\":\"dc11d57e31294094b279140682a1a639\"}}],\"defs\":[{\"type\":\"model\",\"name\":\"ReactiveHTML1\"},{\"type\":\"model\",\"name\":\"FlexBox1\",\"properties\":[{\"name\":\"align_content\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"align_items\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"flex_direction\",\"kind\":\"Any\",\"default\":\"row\"},{\"name\":\"flex_wrap\",\"kind\":\"Any\",\"default\":\"wrap\"},{\"name\":\"gap\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"justify_content\",\"kind\":\"Any\",\"default\":\"flex-start\"}]},{\"type\":\"model\",\"name\":\"FloatPanel1\",\"properties\":[{\"name\":\"config\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"contained\",\"kind\":\"Any\",\"default\":true},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"right-top\"},{\"name\":\"offsetx\",\"kind\":\"Any\",\"default\":null},{\"name\":\"offsety\",\"kind\":\"Any\",\"default\":null},{\"name\":\"theme\",\"kind\":\"Any\",\"default\":\"primary\"},{\"name\":\"status\",\"kind\":\"Any\",\"default\":\"normalized\"}]},{\"type\":\"model\",\"name\":\"GridStack1\",\"properties\":[{\"name\":\"ncols\",\"kind\":\"Any\",\"default\":null},{\"name\":\"nrows\",\"kind\":\"Any\",\"default\":null},{\"name\":\"allow_resize\",\"kind\":\"Any\",\"default\":true},{\"name\":\"allow_drag\",\"kind\":\"Any\",\"default\":true},{\"name\":\"state\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"drag1\",\"properties\":[{\"name\":\"slider_width\",\"kind\":\"Any\",\"default\":5},{\"name\":\"slider_color\",\"kind\":\"Any\",\"default\":\"black\"},{\"name\":\"start\",\"kind\":\"Any\",\"default\":0},{\"name\":\"end\",\"kind\":\"Any\",\"default\":100},{\"name\":\"value\",\"kind\":\"Any\",\"default\":50}]},{\"type\":\"model\",\"name\":\"click1\",\"properties\":[{\"name\":\"terminal_output\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"debug_name\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"clears\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"ReactiveESM1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"JSComponent1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"ReactComponent1\",\"properties\":[{\"name\":\"use_shadow_dom\",\"kind\":\"Any\",\"default\":true},{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"AnyWidgetComponent1\",\"properties\":[{\"name\":\"use_shadow_dom\",\"kind\":\"Any\",\"default\":true},{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"FastWrapper1\",\"properties\":[{\"name\":\"object\",\"kind\":\"Any\",\"default\":null},{\"name\":\"style\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"NotificationArea1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"max_notifications\",\"kind\":\"Any\",\"default\":5},{\"name\":\"notifications\",\"kind\":\"Any\",\"default\":[]},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0},{\"name\":\"types\",\"kind\":\"Any\",\"default\":[{\"type\":\"map\",\"entries\":[[\"type\",\"warning\"],[\"background\",\"#ffc107\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas 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+       "  var render_items = [{\"docid\":\"63739db0-1a74-4ff6-a2d8-28d39aaf33d6\",\"roots\":{\"1ca26b78-2b9d-4973-bed6-c78e6bb73cd0\":\"c653ad2b-675a-4083-a61a-100dab2923e5\"},\"root_ids\":[\"1ca26b78-2b9d-4973-bed6-c78e6bb73cd0\"]}];\n",
+       "  var docs = Object.values(docs_json)\n",
+       "  if (!docs) {\n",
+       "    return\n",
+       "  }\n",
+       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
+       "  async function embed_document(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
+       "    for (const render_item of render_items) {\n",
+       "      for (const root_id of render_item.root_ids) {\n",
+       "\tconst id_el = document.getElementById(root_id)\n",
+       "\tif (id_el.children.length && id_el.children[0].hasAttribute('data-root-id')) {\n",
+       "\t  const root_el = id_el.children[0]\n",
+       "\t  root_el.id = root_el.id + '-rendered'\n",
+       "\t  for (const child of root_el.children) {\n",
+       "            // Ensure JupyterLab does not capture keyboard shortcuts\n",
+       "            // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
+       "\t    child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
+       "\t  }\n",
+       "\t}\n",
+       "      }\n",
+       "    }\n",
+       "  }\n",
+       "  function get_bokeh(root) {\n",
+       "    if (root.Bokeh === undefined) {\n",
+       "      return null\n",
+       "    } else if (root.Bokeh.version !== py_version) {\n",
+       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
+       "\treturn null\n",
+       "      }\n",
+       "      return root.Bokeh.versions.get(py_version);\n",
+       "    } else if (root.Bokeh.version === py_version) {\n",
+       "      return root.Bokeh\n",
+       "    }\n",
+       "    return null\n",
+       "  }\n",
+       "  function is_loaded(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
+       "  }\n",
+       "  if (is_loaded(root)) {\n",
+       "    embed_document(root);\n",
+       "  } else {\n",
+       "    var attempts = 0;\n",
+       "    var timer = setInterval(function(root) {\n",
+       "      if (is_loaded(root)) {\n",
+       "        clearInterval(timer);\n",
+       "        embed_document(root);\n",
+       "      } else if (document.readyState == \"complete\") {\n",
+       "        attempts++;\n",
+       "        if (attempts > 200) {\n",
+       "          clearInterval(timer);\n",
+       "\t  var Bokeh = get_bokeh(root)\n",
+       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
+       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
+       "\t  } else {\n",
+       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
+       "\t    embed_document(root)\n",
+       "\t  }\n",
+       "        }\n",
+       "      }\n",
+       "    }, 25, root)\n",
+       "  }\n",
+       "})(window);</script>"
+      ]
+     },
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+     "output_type": "display_data"
+    },
+    {
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+       "</a>\n",
+       "\n",
+       "\n",
+       "<a href=\"https://bokeh.org\" target=\"_blank\" title=\"Bokeh 3.8.1\">\n",
+       "  <img src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACMAAAAjCAYAAAAe2bNZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAK6wAACusBgosNWgAAABx0RVh0U29mdHdhcmUAQWRvYmUgRmlyZXdvcmtzIENTNui8sowAAAf9SURBVFiFvZh7cFTVHcc/59y7793sJiFAwkvAYDRqFWwdraLVlj61diRYsDjqCFbFKrYo0CltlSq1tLaC2GprGIriGwqjFu10OlrGv8RiK/IICYECSWBDkt3s695zTv9IAtlHeOn0O7Mzu797z+/3Ob/z+p0VfBq9doNFljuABwAXw2PcvGHt6bgwxhz7Ls4YZNVXxxANLENwE2D1W9PAGmAhszZ0/X9gll5yCbHoOirLzmaQs0F6F8QMZq1v/8xgNm7DYwwjgXJLYL4witQ16+sv/U9HdDmV4WrKw6B06cZC/RMrM4MZ7xz61DAbtzEXmAvUAX4pMOVecg9/MFFu3j3Gz7gQBLygS2RGumBkL0cubiFRsR3LzVBV1UMk3IrW73PT9C2lYOwhQB4ClhX1AuKpjLcV27oEjyUpNUJCg1CvcejykWTCXyQgzic2HIIBjg3pS6+uRLKAhumZvD4U+tq0jTrgkVKQQtLekfTtxIPAkhTNF6G7kZm7aPp6M9myKVQEoaYaIhEQYvD781DML/RfBGNZXAl4irJiwBa07e/y7cQnBaJghIX6ENl2GR/fGCBoz6cm5qeyEqQA5ZYA5x5eeiV0Qph4gjFAUSwAr6QllQgcxS/Jm25Cr2Tmpsk03XI9NfI31FTZBEOgVOk51adqDBNPCNPSRlkiDXbBEwOU2WxH+I7itQZ62g56OjM33suq1YsZHVtGZSUI2QdyYgkgOthQNIF7BIGDnRAJgJSgj69cUx1gB8PkOGwL4E1gPrM27gIg7NlGKLQApc7BmEnAxP5g/rw4YqBrCDB5xHkw5rdR/1qTrN/hKNo6YUwVDNpFsnjYS8RbidBPcPXFP6R6yfExuOXmN4A3jv1+8ZUwgY9D2OWjUZE6lO88jDwHI8ZixGiMKSeYTBamCoDk6kDAb6y1OcH1a6KpD/fZesoFw5FlIXAVCIiH4PxrV+p2npVDToTBmtjY8t1swh2V61E9KqWiyuPEjM8dbfxuvfa49Zayf9R136Wr8mBSf/T7bNteA8zwaGEUbFpckWwq95n59dUIywKl2fbOIS5e8bWSu0tJ1a5redAYfqkdjesodFajcgaVNWhXo1C9SrkN3Usmv3UMJrc6/DDwkwEntkEJLe67tSLhvyzK8rHDQWleve5CGk4VZEB1r+5bg2E2si+Y0QatDK6jUVkX5eg2YYlp++ZM+rfMNYamAj8Y7MAVWFqaR1f/t2xzU4IHjybBtthzuiAASqv7jTF7jOqDMAakFHgDNsFyP+FhwZHBmH9F7cutIYkQCylYYv1AZSqsn1/+bX51OMMjPSl2nAnM7hnjOx2v53YgNWAzHM9Q/9l0lQWPSCBSyokAtOBC1Rj+w/1Xs+STDp4/E5g7Rs2zm2+oeVd7PUuHKDf6A4r5EsPT5K3gfCnBXNUYnvGzb+KcCczYYWOnLpy4eOXuG2oec0PBN8XQQAnpvS35AvAykr56rWhPBiV4MvtceGLxk5Mr6A1O8IfK7rl7xJ0r9kyumuP4fa0lMqTBLJIAJqEf1J3qE92lMBndlyfRD2YBghHC4hlny7ASqCeWo5zaoDdIWfnIefNGTb9fC73QDfhyBUCNOxrGPSUBfPem9us253YTV+3mcBbdkUYfzmHiLqZbYdIGHHON2ZlemXouaJUOO6TqtdHEQuXYY8Yt+EbDgmlS6RdzkaDTv2P9A3gICiq93sWhb5mc5wVhuU3Y7m5hOc3So7qFT3SLgOXHb/cyOfMn7xROegoC/PTcn3v8gbKPgDopJFk3R/uBPWQiwQ+2/GJevRMObLUzqe/saJjQUQTTftEVMW9tWxPgAocwcj9abNcZe7s+6t2R2xXZG7zyYLp8Q1PiRBBHym5bYuXi8Qt+/LvGu9f/5YDAxABsaRNPH6Xr4D4Sk87a897SOy9v/fKwjoF2eQel95yDESGEF6gEMwKhLwKus3wOVjTtes7qzgLdXTMnNCNoEpbcrtNuq6N7Xh/+eqcbj94xQkp7mdKpW5XbtbR8Z26kgMCAf2UU5YEovRUVRHbu2b3vK1UdDFkDCyMRQxbpdv8nhKAGIa7QaQedzT07fFPny53R738JoVYBdVrnsNx9XZ9v33UeGO+AA2MMUkgqQ5UcdDLZSFeVgONnXeHqSAC5Ew1BXwko0D1Zct3dT1duOjS3MzZnEUJtBuoQAq3SGOLR4ekjn9NC5nVOaYXf9lETrUkmOJy3pOz8OKIb2A1cWhJCCEzOxU2mUPror+2/L3yyM3pkM7jTjr1nBOgkGeyQ7erxpdJsMAS9wb2F9rzMxNY1K2PMU0WtZV82VU8Wp6vbKJVo9Lx/+4cydORdxCCQ/kDGTZCWsRpLu7VD7bfKqL8V2orKTp/PtzaXy42jr6TwAuisi+7JolUG4wY+8vyrISCMtRrLKWpvjAOqx/QGhp0rjRo5xD3x98CWQuOQN8qumRMmI7jKZPUEpzNVZsj4Zbaq1to5tZZsKIydLWojhIXrJnES79EaOzv3du2NytKuxzJKAA6wF8xqEE8s2jo/1wd/khslQGxd81Zg62Bbp31XBH+iETt7Y3ELA0iU6iGDlQ5mexe0VEx4a3x8V1AaYwFJgTiwaOsDmeK2J8nMUOqsnB1A+dcA04ucCYt0urkjmflk9iT2v30q/gZn5rQPvor4n9Ou634PeBzoznes/iot/7WnClKoM/+zCIjH5kwT8ChQjTHPIPTjFV3PpU/Hx+DM/A9U3IXI4SPCYAAAAABJRU5ErkJggg=='\n",
+       "       style='height:15px; border-radius:12px; display: inline-block; float: left'>\n",
+       "  </img>\n",
+       "</a>\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "<span style=\"float: left; margin-left: 5px; line-height: 15px; cursor: pointer; opacity: 0.7;\"\n",
+       "      onmouseover=\"this.style.opacity='1'\"\n",
+       "      onmouseout=\"this.style.opacity='0.7'\"\n",
+       "      title=\"Extension loaded. This cell output contains code that enables plot interactivity, it should not be removed.\">ⓘ</span>\n",
+       "</div>\n",
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import ehrdata as ed\n",
+    "import holoviews as hv\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "\n",
+    "import ehrapy as ep"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "c7cd28a7",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<script type=\"esms-options\">{\"shimMode\": true}</script><style>*[data-root-id],\n",
+       "*[data-root-id] > * {\n",
+       "  box-sizing: border-box;\n",
+       "  font-family: var(--jp-ui-font-family);\n",
+       "  font-size: var(--jp-ui-font-size1);\n",
+       "  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
+       "}\n",
+       "\n",
+       "/* Override VSCode background color */\n",
+       ".cell-output-ipywidget-background:has(\n",
+       "  > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
+       "),\n",
+       ".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "</style>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/javascript": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  const force = true;\n  const py_version = '3.8.1'.replace('rc', '-rc.').replace('.dev', '-dev.');\n  const reloading = false;\n  const Bokeh = root.Bokeh;\n\n  // Set a timeout for this load but only if we are not already initializing\n  if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks;\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n    if (js_modules == null) js_modules = [];\n    if (js_exports == null) js_exports = {};\n\n    root._bokeh_onload_callbacks.push(callback);\n\n    if (root._bokeh_is_loading > 0) {\n      // Don't load bokeh if it is still initializing\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n      // There is nothing to load\n      run_callbacks();\n      return null;\n    }\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n    window._bokeh_on_load = on_load\n\n    function on_error(e) {\n      const src_el = e.srcElement\n      console.error(\"failed to load \" + (src_el.href || src_el.src));\n    }\n\n    const skip = [];\n    if (window.requirejs) {\n      window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n      root._bokeh_is_loading = css_urls.length + 0;\n    } else {\n      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n    }\n\n    const existing_stylesheets = []\n    const links = document.getElementsByTagName('link')\n    for (let i = 0; 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i < js_urls.length; i++) {\n      const url = js_urls[i];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      const element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (let i = 0; i < js_modules.length; i++) {\n      const url = js_modules[i];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (const name in js_exports) {\n      const url = js_exports[name];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      var element = document.createElement('script');\n      element.onerror = on_error;\n      element.async = false;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      element.textContent = `\n      import ${name} from \"${url}\"\n      window.${name} = ${name}\n      window._bokeh_on_load()\n      `\n      document.head.appendChild(element);\n    }\n    if (!js_urls.length && !js_modules.length) {\n      on_load()\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  const js_urls = [\"https://cdn.holoviz.org/panel/1.8.3/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-3.8.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.8.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.8.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.8.1.min.js\", \"https://cdn.holoviz.org/panel/1.8.3/dist/panel.min.js\"];\n  const js_modules = [];\n  const js_exports = {};\n  const css_urls = [];\n  const inline_js = [    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n  ];\n\n  function run_inline_js() {\n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (let i = 0; i < inline_js.length; i++) {\n        try {\n          inline_js[i].call(root, root.Bokeh);\n        } catch(e) {\n          if (!reloading) {\n            throw e;\n          }\n        }\n      }\n      // Cache old bokeh versions\n      if (Bokeh != undefined && !reloading) {\n        var NewBokeh = root.Bokeh;\n        if (Bokeh.versions === undefined) {\n          Bokeh.versions = new Map();\n        }\n        if (NewBokeh.version !== Bokeh.version) {\n          Bokeh.versions.set(NewBokeh.version, NewBokeh)\n        }\n        root.Bokeh = Bokeh;\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    }\n    root._bokeh_is_initializing = false\n  }\n\n  function load_or_wait() {\n    // Implement a backoff loop that tries to ensure we do not load multiple\n    // versions of Bokeh and its dependencies at the same time.\n    // In recent versions we use the root._bokeh_is_initializing flag\n    // to determine whether there is an ongoing attempt to initialize\n    // bokeh, however for backward compatibility we also try to ensure\n    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n    // before older versions are fully initialized.\n    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n      // If the timeout and bokeh was not successfully loaded we reset\n      // everything and try loading again\n      root._bokeh_timeout = Date.now() + 5000;\n      root._bokeh_is_initializing = false;\n      root._bokeh_onload_callbacks = undefined;\n      root._bokeh_is_loading = 0\n      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n      load_or_wait();\n    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n      setTimeout(load_or_wait, 100);\n    } else {\n      root._bokeh_is_initializing = true\n      root._bokeh_onload_callbacks = []\n      const bokeh_loaded = root.Bokeh != null && (root.Bokeh.version === py_version || (root.Bokeh.versions !== undefined && root.Bokeh.versions.has(py_version)));\n      if (!reloading && !bokeh_loaded) {\n        if (root.Bokeh) {\n          root.Bokeh = undefined;\n        }\n        console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n      }\n      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n        console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n        run_inline_js();\n      });\n    }\n  }\n  // Give older versions of the autoload script a head-start to ensure\n  // they initialize before we start loading newer version.\n  setTimeout(load_or_wait, 100)\n}(window));",
+      "application/vnd.holoviews_load.v0+json": ""
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/javascript": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n  window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n    function JupyterCommManager() {\n    }\n\n    JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n      if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        comm_manager.register_target(comm_id, function(comm) {\n          comm.on_msg(msg_handler);\n        });\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n          comm.onMsg = msg_handler;\n        });\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        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(Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n        if (msg_handler) {\n          comm.on_msg(msg_handler);\n        }\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n        let retries = 0;\n        const open = () => {\n          if (comm.active) {\n            comm.open();\n          } else if (retries > 3) {\n            console.warn('Comm target never activated')\n          } else {\n            retries += 1\n            setTimeout(open, 500)\n          }\n        }\n        if (comm.active) {\n          comm.open();\n        } else {\n          setTimeout(open, 500)\n        }\n        if (msg_handler) {\n          comm.onMsg = msg_handler;\n        }\n      } else if (typeof google != 'undefined' && 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+      "application/vnd.holoviews_load.v0+json": ""
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
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+      "text/html": [
+       "<div id='b6c17037-60cd-4bb6-9c89-5803c9428023'>\n",
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+       "</div>\n",
+       "<script type=\"application/javascript\">(function(root) {\n",
+       "  var docs_json = {\"c126c264-6ec6-4dfd-bfc5-4d6534e8766a\":{\"version\":\"3.8.1\",\"title\":\"Bokeh 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+       "  var render_items = [{\"docid\":\"c126c264-6ec6-4dfd-bfc5-4d6534e8766a\",\"roots\":{\"b6c17037-60cd-4bb6-9c89-5803c9428023\":\"f79894f7-4e60-4819-a452-f5f9ce8c244e\"},\"root_ids\":[\"b6c17037-60cd-4bb6-9c89-5803c9428023\"]}];\n",
+       "  var docs = Object.values(docs_json)\n",
+       "  if (!docs) {\n",
+       "    return\n",
+       "  }\n",
+       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
+       "  async function embed_document(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
+       "    for (const render_item of render_items) {\n",
+       "      for (const root_id of render_item.root_ids) {\n",
+       "\tconst id_el = document.getElementById(root_id)\n",
+       "\tif (id_el.children.length && id_el.children[0].hasAttribute('data-root-id')) {\n",
+       "\t  const root_el = id_el.children[0]\n",
+       "\t  root_el.id = root_el.id + '-rendered'\n",
+       "\t  for (const child of root_el.children) {\n",
+       "            // Ensure JupyterLab does not capture keyboard shortcuts\n",
+       "            // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
+       "\t    child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
+       "\t  }\n",
+       "\t}\n",
+       "      }\n",
+       "    }\n",
+       "  }\n",
+       "  function get_bokeh(root) {\n",
+       "    if (root.Bokeh === undefined) {\n",
+       "      return null\n",
+       "    } else if (root.Bokeh.version !== py_version) {\n",
+       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
+       "\treturn null\n",
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+       "      return root.Bokeh.versions.get(py_version);\n",
+       "    } else if (root.Bokeh.version === py_version) {\n",
+       "      return root.Bokeh\n",
+       "    }\n",
+       "    return null\n",
+       "  }\n",
+       "  function is_loaded(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
+       "  }\n",
+       "  if (is_loaded(root)) {\n",
+       "    embed_document(root);\n",
+       "  } else {\n",
+       "    var attempts = 0;\n",
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+       "        embed_document(root);\n",
+       "      } else if (document.readyState == \"complete\") {\n",
+       "        attempts++;\n",
+       "        if (attempts > 200) {\n",
+       "          clearInterval(timer);\n",
+       "\t  var Bokeh = get_bokeh(root)\n",
+       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
+       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
+       "\t  } else {\n",
+       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
+       "\t    embed_document(root)\n",
+       "\t  }\n",
+       "        }\n",
+       "      }\n",
+       "    }, 25, root)\n",
+       "  }\n",
+       "})(window);</script>"
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+       "roTBs2RqAAAAAElFTkSuQmCC' style='height:25px; border-radius:12px; display: inline-block; float: left; vertical-align: middle'></img>\n",
+       "</a>\n",
+       "\n",
+       "\n",
+       "<a href=\"https://bokeh.org\" target=\"_blank\" title=\"Bokeh 3.8.1\">\n",
+       "  <img src='data:image/png;base64,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'\n",
+       "       style='height:15px; border-radius:12px; display: inline-block; float: left'>\n",
+       "  </img>\n",
+       "</a>\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "<span style=\"float: left; margin-left: 5px; line-height: 15px; cursor: pointer; opacity: 0.7;\"\n",
+       "      onmouseover=\"this.style.opacity='1'\"\n",
+       "      onmouseout=\"this.style.opacity='0.7'\"\n",
+       "      title=\"Extension loaded. This cell output contains code that enables plot interactivity, it should not be removed.\">ⓘ</span>\n",
+       "</div>\n",
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "hv.extension(\"bokeh\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "8104f266",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "current_notebook_dir = %pwd\n",
+    "\n",
+    "_TEST_IMAGE_PATH = f\"{current_notebook_dir}/../plot/_images\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "e242cbd4",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[93m!\u001b[0m File ehrapy_data\\diabetes_130_fairlearn.csv already exists! Using already downloaded dataset...\n"
+     ]
+    }
+   ],
+   "source": [
+    "edata = ed.dt.diabetes_130_fairlearn(columns_obs_only=[\"gender\", \"race\"])[:100]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "53b26cc8",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {},
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.holoviews_exec.v0+json": "",
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+       "</div>\n",
+       "<script type=\"application/javascript\">(function(root) {\n",
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300px));\\n}\",{\"id\":\"fbbffdff-8d4e-423e-8d3c-db3fa42c67e9\"},{\"id\":\"75fb5899-ca88-4df4-8d34-1d74882717e7\"},{\"id\":\"6cdfb6fb-988c-43f0-9d9f-e8368bf04798\"}],\"min_width\":0,\"margin\":0,\"sizing_mode\":\"stretch_width\",\"align\":\"start\"}}]}}],\"defs\":[{\"type\":\"model\",\"name\":\"ReactiveHTML1\"},{\"type\":\"model\",\"name\":\"FlexBox1\",\"properties\":[{\"name\":\"align_content\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"align_items\",\"kind\":\"Any\",\"default\":\"flex-start\"},{\"name\":\"flex_direction\",\"kind\":\"Any\",\"default\":\"row\"},{\"name\":\"flex_wrap\",\"kind\":\"Any\",\"default\":\"wrap\"},{\"name\":\"gap\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"justify_content\",\"kind\":\"Any\",\"default\":\"flex-start\"}]},{\"type\":\"model\",\"name\":\"FloatPanel1\",\"properties\":[{\"name\":\"config\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"contained\",\"kind\":\"Any\",\"default\":true},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"right-top\"},{\"name\":\"offsetx\",\"kind\":\"Any\",\"default\":null},{\"name\":\"offsety\",\"kind\":\"Any\",\"default\":null},{\"name\":\"theme\",\"kind\":\"Any\",\"default\":\"primary\"},{\"name\":\"status\",\"kind\":\"Any\",\"default\":\"normalized\"}]},{\"type\":\"model\",\"name\":\"GridStack1\",\"properties\":[{\"name\":\"ncols\",\"kind\":\"Any\",\"default\":null},{\"name\":\"nrows\",\"kind\":\"Any\",\"default\":null},{\"name\":\"allow_resize\",\"kind\":\"Any\",\"default\":true},{\"name\":\"allow_drag\",\"kind\":\"Any\",\"default\":true},{\"name\":\"state\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"drag1\",\"properties\":[{\"name\":\"slider_width\",\"kind\":\"Any\",\"default\":5},{\"name\":\"slider_color\",\"kind\":\"Any\",\"default\":\"black\"},{\"name\":\"start\",\"kind\":\"Any\",\"default\":0},{\"name\":\"end\",\"kind\":\"Any\",\"default\":100},{\"name\":\"value\",\"kind\":\"Any\",\"default\":50}]},{\"type\":\"model\",\"name\":\"click1\",\"properties\":[{\"name\":\"terminal_output\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"debug_name\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"clears\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"ReactiveESM1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"JSComponent1\",\"properties\":[{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"ReactComponent1\",\"properties\":[{\"name\":\"use_shadow_dom\",\"kind\":\"Any\",\"default\":true},{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"AnyWidgetComponent1\",\"properties\":[{\"name\":\"use_shadow_dom\",\"kind\":\"Any\",\"default\":true},{\"name\":\"esm_constants\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}}]},{\"type\":\"model\",\"name\":\"FastWrapper1\",\"properties\":[{\"name\":\"object\",\"kind\":\"Any\",\"default\":null},{\"name\":\"style\",\"kind\":\"Any\",\"default\":null}]},{\"type\":\"model\",\"name\":\"NotificationArea1\",\"properties\":[{\"name\":\"js_events\",\"kind\":\"Any\",\"default\":{\"type\":\"map\"}},{\"name\":\"max_notifications\",\"kind\":\"Any\",\"default\":5},{\"name\":\"notifications\",\"kind\":\"Any\",\"default\":[]},{\"name\":\"position\",\"kind\":\"Any\",\"default\":\"bottom-right\"},{\"name\":\"_clear\",\"kind\":\"Any\",\"default\":0},{\"name\":\"types\",\"kind\":\"Any\",\"default\":[{\"type\":\"map\",\"entries\":[[\"type\",\"warning\"],[\"background\",\"#ffc107\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-exclamation-triangle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]},{\"type\":\"map\",\"entries\":[[\"type\",\"info\"],[\"background\",\"#007bff\"],[\"icon\",{\"type\":\"map\",\"entries\":[[\"className\",\"fas fa-info-circle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]}]}]},{\"type\":\"model\",\"name\":\"Notification\",\"properties\":[{\"name\":\"background\",\"kind\":\"Any\",\"default\":null},{\"name\":\"duration\",\"kind\":\"Any\",\"default\":3000},{\"name\":\"icon\",\"kind\":\"Any\",\"default\":null},{\"name\":\"message\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"notification_type\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_rendered\",\"kind\":\"Any\",\"default\":false},{\"name\":\"_destroyed\",\"kind\":\"Any\",\"default\":false}]},{\"type\":\"model\",\"name\":\"TemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"BootstrapTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"TemplateEditor1\",\"properties\":[{\"name\":\"layout\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"MaterialTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"request_value1\",\"properties\":[{\"name\":\"fill\",\"kind\":\"Any\",\"default\":\"none\"},{\"name\":\"_synced\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_request_sync\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"holoviews.plotting.bokeh.raster.HoverModel\",\"properties\":[{\"name\":\"xy\",\"kind\":\"Any\",\"default\":null},{\"name\":\"data\",\"kind\":\"Any\",\"default\":null}]}]}};\n",
+       "  var render_items = [{\"docid\":\"b47fc1c3-84b8-47b3-82bd-591f1e277b11\",\"roots\":{\"7d8f45f1-4346-4a72-b3f1-a9a31712494c\":\"d8251082-c225-4573-874f-8956286cae7d\"},\"root_ids\":[\"7d8f45f1-4346-4a72-b3f1-a9a31712494c\"]}];\n",
+       "  var docs = Object.values(docs_json)\n",
+       "  if (!docs) {\n",
+       "    return\n",
+       "  }\n",
+       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
+       "  async function embed_document(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
+       "    for (const render_item of render_items) {\n",
+       "      for (const root_id of render_item.root_ids) {\n",
+       "\tconst id_el = document.getElementById(root_id)\n",
+       "\tif (id_el.children.length && id_el.children[0].hasAttribute('data-root-id')) {\n",
+       "\t  const root_el = id_el.children[0]\n",
+       "\t  root_el.id = root_el.id + '-rendered'\n",
+       "\t  for (const child of root_el.children) {\n",
+       "            // Ensure JupyterLab does not capture keyboard shortcuts\n",
+       "            // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
+       "\t    child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
+       "\t  }\n",
+       "\t}\n",
+       "      }\n",
+       "    }\n",
+       "  }\n",
+       "  function get_bokeh(root) {\n",
+       "    if (root.Bokeh === undefined) {\n",
+       "      return null\n",
+       "    } else if (root.Bokeh.version !== py_version) {\n",
+       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
+       "\treturn null\n",
+       "      }\n",
+       "      return root.Bokeh.versions.get(py_version);\n",
+       "    } else if (root.Bokeh.version === py_version) {\n",
+       "      return root.Bokeh\n",
+       "    }\n",
+       "    return null\n",
+       "  }\n",
+       "  function is_loaded(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
+       "  }\n",
+       "  if (is_loaded(root)) {\n",
+       "    embed_document(root);\n",
+       "  } else {\n",
+       "    var attempts = 0;\n",
+       "    var timer = setInterval(function(root) {\n",
+       "      if (is_loaded(root)) {\n",
+       "        clearInterval(timer);\n",
+       "        embed_document(root);\n",
+       "      } else if (document.readyState == \"complete\") {\n",
+       "        attempts++;\n",
+       "        if (attempts > 200) {\n",
+       "          clearInterval(timer);\n",
+       "\t  var Bokeh = get_bokeh(root)\n",
+       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
+       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
+       "\t  } else {\n",
+       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
+       "\t    embed_document(root)\n",
+       "\t  }\n",
+       "        }\n",
+       "      }\n",
+       "    }, 25, root)\n",
+       "  }\n",
+       "})(window);</script>"
+      ],
+      "text/plain": [
+       ":Sankey   [source,target]   (value)"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {
+      "application/vnd.holoviews_exec.v0+json": {
+       "id": "7d8f45f1-4346-4a72-b3f1-a9a31712494c"
+      }
+     },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ep.pl.plot_sankey(edata, columns=[\"gender\", \"race\"], backend=\"bokeh\", show=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "a59e9a13",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "layer = np.array(\n",
+    "    [\n",
+    "        [[0, 1, 2, 1, 2], [1, 2, 1, 2, 0]],\n",
+    "        [[1, 2, 0, 2, 1], [2, 1, 2, 1, 2]],\n",
+    "        [[2, 0, 1, 2, 0], [2, 0, 1, 1, 2]],\n",
+    "        [[1, 2, 1, 0, 1], [0, 2, 1, 2, 0]],\n",
+    "        [[0, 2, 1, 2, 2], [1, 2, 1, 0, 2]],\n",
+    "    ]\n",
+    ")\n",
+    "\n",
+    "\n",
+    "edata_time = ed.EHRData(\n",
+    "    layers={\"layer_1\": layer},\n",
+    "    obs=pd.DataFrame(index=[\"patient_1\", \"patient_2\", \"patient_3\", \"patient_4\", \"patient_5\"]),\n",
+    "    var=pd.DataFrame(index=[\"treatment\", \"disease_flare\"]),\n",
+    "    tem=pd.DataFrame(index=[\"visit_0\", \"visit_1\", \"visit_2\", \"visit_3\", \"visit_4\"]),\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "38907509",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {},
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/vnd.holoviews_exec.v0+json": "",
+      "text/html": [
+       "<div id='1290fb3c-ccad-4063-8943-8b7f1e22382d'>\n",
+       "  <div id=\"d2f9c1f8-9b7c-40ac-bc04-0ef1aab002a0\" data-root-id=\"1290fb3c-ccad-4063-8943-8b7f1e22382d\" style=\"display: contents;\"></div>\n",
+       "</div>\n",
+       "<script type=\"application/javascript\">(function(root) {\n",
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fa-info-circle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]}]}]},{\"type\":\"model\",\"name\":\"Notification\",\"properties\":[{\"name\":\"background\",\"kind\":\"Any\",\"default\":null},{\"name\":\"duration\",\"kind\":\"Any\",\"default\":3000},{\"name\":\"icon\",\"kind\":\"Any\",\"default\":null},{\"name\":\"message\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"notification_type\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_rendered\",\"kind\":\"Any\",\"default\":false},{\"name\":\"_destroyed\",\"kind\":\"Any\",\"default\":false}]},{\"type\":\"model\",\"name\":\"TemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"BootstrapTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"TemplateEditor1\",\"properties\":[{\"name\":\"layout\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"MaterialTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"request_value1\",\"properties\":[{\"name\":\"fill\",\"kind\":\"Any\",\"default\":\"none\"},{\"name\":\"_synced\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_request_sync\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"holoviews.plotting.bokeh.raster.HoverModel\",\"properties\":[{\"name\":\"xy\",\"kind\":\"Any\",\"default\":null},{\"name\":\"data\",\"kind\":\"Any\",\"default\":null}]}]}};\n",
+       "  var render_items = [{\"docid\":\"d89a54ec-8026-4398-92ba-bc7de5129114\",\"roots\":{\"1290fb3c-ccad-4063-8943-8b7f1e22382d\":\"d2f9c1f8-9b7c-40ac-bc04-0ef1aab002a0\"},\"root_ids\":[\"1290fb3c-ccad-4063-8943-8b7f1e22382d\"]}];\n",
+       "  var docs = Object.values(docs_json)\n",
+       "  if (!docs) {\n",
+       "    return\n",
+       "  }\n",
+       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
+       "  async function embed_document(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
+       "    for (const render_item of render_items) {\n",
+       "      for (const root_id of render_item.root_ids) {\n",
+       "\tconst id_el = document.getElementById(root_id)\n",
+       "\tif (id_el.children.length && id_el.children[0].hasAttribute('data-root-id')) {\n",
+       "\t  const root_el = id_el.children[0]\n",
+       "\t  root_el.id = root_el.id + '-rendered'\n",
+       "\t  for (const child of root_el.children) {\n",
+       "            // Ensure JupyterLab does not capture keyboard shortcuts\n",
+       "            // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
+       "\t    child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
+       "\t  }\n",
+       "\t}\n",
+       "      }\n",
+       "    }\n",
+       "  }\n",
+       "  function get_bokeh(root) {\n",
+       "    if (root.Bokeh === undefined) {\n",
+       "      return null\n",
+       "    } else if (root.Bokeh.version !== py_version) {\n",
+       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
+       "\treturn null\n",
+       "      }\n",
+       "      return root.Bokeh.versions.get(py_version);\n",
+       "    } else if (root.Bokeh.version === py_version) {\n",
+       "      return root.Bokeh\n",
+       "    }\n",
+       "    return null\n",
+       "  }\n",
+       "  function is_loaded(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
+       "  }\n",
+       "  if (is_loaded(root)) {\n",
+       "    embed_document(root);\n",
+       "  } else {\n",
+       "    var attempts = 0;\n",
+       "    var timer = setInterval(function(root) {\n",
+       "      if (is_loaded(root)) {\n",
+       "        clearInterval(timer);\n",
+       "        embed_document(root);\n",
+       "      } else if (document.readyState == \"complete\") {\n",
+       "        attempts++;\n",
+       "        if (attempts > 200) {\n",
+       "          clearInterval(timer);\n",
+       "\t  var Bokeh = get_bokeh(root)\n",
+       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
+       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
+       "\t  } else {\n",
+       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
+       "\t    embed_document(root)\n",
+       "\t  }\n",
+       "        }\n",
+       "      }\n",
+       "    }, 25, root)\n",
+       "  }\n",
+       "})(window);</script>"
+      ],
+      "text/plain": [
+       ":Sankey   [source,target]   (value)"
+      ]
+     },
+     "execution_count": 7,
+     "metadata": {
+      "application/vnd.holoviews_exec.v0+json": {
+       "id": "1290fb3c-ccad-4063-8943-8b7f1e22382d"
+      }
+     },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "ep.pl.plot_sankey_time(\n",
+    "    edata_time,\n",
+    "    columns=[\"disease_flare\"],\n",
+    "    layer=\"layer_1\",\n",
+    "    state_labels={0: \"no flare\", 1: \"mid flare\", 2: \"severe flare\"},\n",
+    "    backend=\"bokeh\",\n",
+    ")"
+   ]
+  }
+ ],
+ "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": "3.13.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/tests/_scripts/sankey_expected.ipynb b/tests/_scripts/sankey_expected.ipynb
deleted file mode 100644
index 396085771..000000000
--- a/tests/_scripts/sankey_expected.ipynb
+++ /dev/null
@@ -1,1634 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "42a55492",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<script type=\"esms-options\">{\"shimMode\": true}</script><style>*[data-root-id],\n",
-       "*[data-root-id] > * {\n",
-       "  box-sizing: border-box;\n",
-       "  font-family: var(--jp-ui-font-family);\n",
-       "  font-size: var(--jp-ui-font-size1);\n",
-       "  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
-       "}\n",
-       "\n",
-       "/* Override VSCode background color */\n",
-       ".cell-output-ipywidget-background:has(\n",
-       "  > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
-       "),\n",
-       ".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
-       "  background-color: transparent !important;\n",
-       "}\n",
-       "</style>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/javascript": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  const force = true;\n  const py_version = '3.8.1'.replace('rc', '-rc.').replace('.dev', '-dev.');\n  const reloading = false;\n  const Bokeh = root.Bokeh;\n\n  // Set a timeout for this load but only if we are not already initializing\n  if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks;\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n    if (js_modules == null) js_modules = [];\n    if (js_exports == null) js_exports = {};\n\n    root._bokeh_onload_callbacks.push(callback);\n\n    if (root._bokeh_is_loading > 0) {\n      // Don't load bokeh if it is still initializing\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n      // There is nothing to load\n      run_callbacks();\n      return null;\n    }\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n    window._bokeh_on_load = on_load\n\n    function on_error(e) {\n      const src_el = e.srcElement\n      console.error(\"failed to load \" + (src_el.href || src_el.src));\n    }\n\n    const skip = [];\n    if (window.requirejs) {\n      window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n      root._bokeh_is_loading = css_urls.length + 0;\n    } else {\n      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n    }\n\n    const existing_stylesheets = []\n    const links = document.getElementsByTagName('link')\n    for (let i = 0; i < links.length; i++) {\n      const link = links[i]\n      if (link.href != null) {\n        existing_stylesheets.push(link.href)\n      }\n    }\n    for (let i = 0; i < css_urls.length; i++) {\n      const url = css_urls[i];\n      const escaped = encodeURI(url)\n      if (existing_stylesheets.indexOf(escaped) !== -1) {\n        on_load()\n        continue;\n      }\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }    var existing_scripts = []\n    const scripts = document.getElementsByTagName('script')\n    for (let i = 0; i < scripts.length; i++) {\n      var script = scripts[i]\n      if (script.src != null) {\n        existing_scripts.push(script.src)\n      }\n    }\n    for (let i = 0; i < js_urls.length; i++) {\n      const url = js_urls[i];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      const element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (let i = 0; i < js_modules.length; i++) {\n      const url = js_modules[i];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (const name in js_exports) {\n      const url = js_exports[name];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      var element = document.createElement('script');\n      element.onerror = on_error;\n      element.async = false;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      element.textContent = `\n      import ${name} from \"${url}\"\n      window.${name} = ${name}\n      window._bokeh_on_load()\n      `\n      document.head.appendChild(element);\n    }\n    if (!js_urls.length && !js_modules.length) {\n      on_load()\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  const js_urls = [\"https://cdn.holoviz.org/panel/1.8.3/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-3.8.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.8.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.8.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.8.1.min.js\", \"https://cdn.holoviz.org/panel/1.8.3/dist/panel.min.js\"];\n  const js_modules = [];\n  const js_exports = {};\n  const css_urls = [];\n  const inline_js = [    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n  ];\n\n  function run_inline_js() {\n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (let i = 0; i < inline_js.length; i++) {\n        try {\n          inline_js[i].call(root, root.Bokeh);\n        } catch(e) {\n          if (!reloading) {\n            throw e;\n          }\n        }\n      }\n      // Cache old bokeh versions\n      if (Bokeh != undefined && !reloading) {\n        var NewBokeh = root.Bokeh;\n        if (Bokeh.versions === undefined) {\n          Bokeh.versions = new Map();\n        }\n        if (NewBokeh.version !== Bokeh.version) {\n          Bokeh.versions.set(NewBokeh.version, NewBokeh)\n        }\n        root.Bokeh = Bokeh;\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    }\n    root._bokeh_is_initializing = false\n  }\n\n  function load_or_wait() {\n    // Implement a backoff loop that tries to ensure we do not load multiple\n    // versions of Bokeh and its dependencies at the same time.\n    // In recent versions we use the root._bokeh_is_initializing flag\n    // to determine whether there is an ongoing attempt to initialize\n    // bokeh, however for backward compatibility we also try to ensure\n    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n    // before older versions are fully initialized.\n    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n      // If the timeout and bokeh was not successfully loaded we reset\n      // everything and try loading again\n      root._bokeh_timeout = Date.now() + 5000;\n      root._bokeh_is_initializing = false;\n      root._bokeh_onload_callbacks = undefined;\n      root._bokeh_is_loading = 0\n      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n      load_or_wait();\n    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n      setTimeout(load_or_wait, 100);\n    } else {\n      root._bokeh_is_initializing = true\n      root._bokeh_onload_callbacks = []\n      const bokeh_loaded = root.Bokeh != null && (root.Bokeh.version === py_version || (root.Bokeh.versions !== undefined && root.Bokeh.versions.has(py_version)));\n      if (!reloading && !bokeh_loaded) {\n        if (root.Bokeh) {\n          root.Bokeh = undefined;\n        }\n        console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n      }\n      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n        console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n        run_inline_js();\n      });\n    }\n  }\n  // Give older versions of the autoload script a head-start to ensure\n  // they initialize before we start loading newer version.\n  setTimeout(load_or_wait, 100)\n}(window));",
-      "application/vnd.holoviews_load.v0+json": ""
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/javascript": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n  window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n    function JupyterCommManager() {\n    }\n\n    JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n      if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        comm_manager.register_target(comm_id, function(comm) {\n          comm.on_msg(msg_handler);\n        });\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n          comm.onMsg = msg_handler;\n        });\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n          var messages = comm.messages[Symbol.asyncIterator]();\n          function processIteratorResult(result) {\n            var message = result.value;\n            var content = {data: message.data, comm_id};\n            var buffers = []\n            for (var buffer of message.buffers || []) {\n              buffers.push(new DataView(buffer))\n            }\n            var metadata = message.metadata || {};\n            var msg = {content, buffers, metadata}\n            msg_handler(msg);\n            return messages.next().then(processIteratorResult);\n          }\n          return messages.next().then(processIteratorResult);\n        })\n      }\n    }\n\n    JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n      if (comm_id in window.PyViz.comms) {\n        return window.PyViz.comms[comm_id];\n      } else if (window.comm_manager || ((window.Jupyter !== undefined) && 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-       "roTBs2RqAAAAAElFTkSuQmCC' style='height:25px; border-radius:12px; display: inline-block; float: left; vertical-align: middle'></img>\n",
-       "</a>\n",
-       "\n",
-       "\n",
-       "<a href=\"https://bokeh.org\" target=\"_blank\" title=\"Bokeh 3.8.1\">\n",
-       "  <img src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACMAAAAjCAYAAAAe2bNZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAK6wAACusBgosNWgAAABx0RVh0U29mdHdhcmUAQWRvYmUgRmlyZXdvcmtzIENTNui8sowAAAf9SURBVFiFvZh7cFTVHcc/59y7793sJiFAwkvAYDRqFWwdraLVlj61diRYsDjqCFbFKrYo0CltlSq1tLaC2GprGIriGwqjFu10OlrGv8RiK/IICYECSWBDkt3s695zTv9IAtlHeOn0O7Mzu797z+/3Ob/z+p0VfBq9doNFljuABwAXw2PcvGHt6bgwxhz7Ls4YZNVXxxANLENwE2D1W9PAGmAhszZ0/X9gll5yCbHoOirLzmaQs0F6F8QMZq1v/8xgNm7DYwwjgXJLYL4witQ16+sv/U9HdDmV4WrKw6B06cZC/RMrM4MZ7xz61DAbtzEXmAvUAX4pMOVecg9/MFFu3j3Gz7gQBLygS2RGumBkL0cubiFRsR3LzVBV1UMk3IrW73PT9C2lYOwhQB4ClhX1AuKpjLcV27oEjyUpNUJCg1CvcejykWTCXyQgzic2HIIBjg3pS6+uRLKAhumZvD4U+tq0jTrgkVKQQtLekfTtxIPAkhTNF6G7kZm7aPp6M9myKVQEoaYaIhEQYvD781DML/RfBGNZXAl4irJiwBa07e/y7cQnBaJghIX6ENl2GR/fGCBoz6cm5qeyEqQA5ZYA5x5eeiV0Qph4gjFAUSwAr6QllQgcxS/Jm25Cr2Tmpsk03XI9NfI31FTZBEOgVOk51adqDBNPCNPSRlkiDXbBEwOU2WxH+I7itQZ62g56OjM33suq1YsZHVtGZSUI2QdyYgkgOthQNIF7BIGDnRAJgJSgj69cUx1gB8PkOGwL4E1gPrM27gIg7NlGKLQApc7BmEnAxP5g/rw4YqBrCDB5xHkw5rdR/1qTrN/hKNo6YUwVDNpFsnjYS8RbidBPcPXFP6R6yfExuOXmN4A3jv1+8ZUwgY9D2OWjUZE6lO88jDwHI8ZixGiMKSeYTBamCoDk6kDAb6y1OcH1a6KpD/fZesoFw5FlIXAVCIiH4PxrV+p2npVDToTBmtjY8t1swh2V61E9KqWiyuPEjM8dbfxuvfa49Zayf9R136Wr8mBSf/T7bNteA8zwaGEUbFpckWwq95n59dUIywKl2fbOIS5e8bWSu0tJ1a5redAYfqkdjesodFajcgaVNWhXo1C9SrkN3Usmv3UMJrc6/DDwkwEntkEJLe67tSLhvyzK8rHDQWleve5CGk4VZEB1r+5bg2E2si+Y0QatDK6jUVkX5eg2YYlp++ZM+rfMNYamAj8Y7MAVWFqaR1f/t2xzU4IHjybBtthzuiAASqv7jTF7jOqDMAakFHgDNsFyP+FhwZHBmH9F7cutIYkQCylYYv1AZSqsn1/+bX51OMMjPSl2nAnM7hnjOx2v53YgNWAzHM9Q/9l0lQWPSCBSyokAtOBC1Rj+w/1Xs+STDp4/E5g7Rs2zm2+oeVd7PUuHKDf6A4r5EsPT5K3gfCnBXNUYnvGzb+KcCczYYWOnLpy4eOXuG2oec0PBN8XQQAnpvS35AvAykr56rWhPBiV4MvtceGLxk5Mr6A1O8IfK7rl7xJ0r9kyumuP4fa0lMqTBLJIAJqEf1J3qE92lMBndlyfRD2YBghHC4hlny7ASqCeWo5zaoDdIWfnIefNGTb9fC73QDfhyBUCNOxrGPSUBfPem9us253YTV+3mcBbdkUYfzmHiLqZbYdIGHHON2ZlemXouaJUOO6TqtdHEQuXYY8Yt+EbDgmlS6RdzkaDTv2P9A3gICiq93sWhb5mc5wVhuU3Y7m5hOc3So7qFT3SLgOXHb/cyOfMn7xROegoC/PTcn3v8gbKPgDopJFk3R/uBPWQiwQ+2/GJevRMObLUzqe/saJjQUQTTftEVMW9tWxPgAocwcj9abNcZe7s+6t2R2xXZG7zyYLp8Q1PiRBBHym5bYuXi8Qt+/LvGu9f/5YDAxABsaRNPH6Xr4D4Sk87a897SOy9v/fKwjoF2eQel95yDESGEF6gEMwKhLwKus3wOVjTtes7qzgLdXTMnNCNoEpbcrtNuq6N7Xh/+eqcbj94xQkp7mdKpW5XbtbR8Z26kgMCAf2UU5YEovRUVRHbu2b3vK1UdDFkDCyMRQxbpdv8nhKAGIa7QaQedzT07fFPny53R738JoVYBdVrnsNx9XZ9v33UeGO+AA2MMUkgqQ5UcdDLZSFeVgONnXeHqSAC5Ew1BXwko0D1Zct3dT1duOjS3MzZnEUJtBuoQAq3SGOLR4ekjn9NC5nVOaYXf9lETrUkmOJy3pOz8OKIb2A1cWhJCCEzOxU2mUPror+2/L3yyM3pkM7jTjr1nBOgkGeyQ7erxpdJsMAS9wb2F9rzMxNY1K2PMU0WtZV82VU8Wp6vbKJVo9Lx/+4cydORdxCCQ/kDGTZCWsRpLu7VD7bfKqL8V2orKTp/PtzaXy42jr6TwAuisi+7JolUG4wY+8vyrISCMtRrLKWpvjAOqx/QGhp0rjRo5xD3x98CWQuOQN8qumRMmI7jKZPUEpzNVZsj4Zbaq1to5tZZsKIydLWojhIXrJnES79EaOzv3du2NytKuxzJKAA6wF8xqEE8s2jo/1wd/khslQGxd81Zg62Bbp31XBH+iETt7Y3ELA0iU6iGDlQ5mexe0VEx4a3x8V1AaYwFJgTiwaOsDmeK2J8nMUOqsnB1A+dcA04ucCYt0urkjmflk9iT2v30q/gZn5rQPvor4n9Ou634PeBzoznes/iot/7WnClKoM/+zCIjH5kwT8ChQjTHPIPTjFV3PpU/Hx+DM/A9U3IXI4SPCYAAAAABJRU5ErkJggg=='\n",
-       "       style='height:15px; border-radius:12px; display: inline-block; float: left'>\n",
-       "  </img>\n",
-       "</a>\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "<span style=\"float: left; margin-left: 5px; line-height: 15px; cursor: pointer; opacity: 0.7;\"\n",
-       "      onmouseover=\"this.style.opacity='1'\"\n",
-       "      onmouseout=\"this.style.opacity='0.7'\"\n",
-       "      title=\"Extension loaded. This cell output contains code that enables plot interactivity, it should not be removed.\">ⓘ</span>\n",
-       "</div>\n",
-       "\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "import ehrdata as ed\n",
-    "import holoviews as hv\n",
-    "import matplotlib.pyplot as plt\n",
-    "import numpy as np\n",
-    "import pandas as pd\n",
-    "\n",
-    "import ehrapy as ep"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "8104f266",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "current_notebook_dir = %pwd\n",
-    "\n",
-    "_TEST_IMAGE_PATH = f\"{current_notebook_dir}/../plot/_images\""
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "e242cbd4",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\u001b[93m!\u001b[0m File ehrapy_data\\diabetes_130_fairlearn.csv already exists! Using already downloaded dataset...\n"
-     ]
-    }
-   ],
-   "source": [
-    "edata = ed.dt.diabetes_130_fairlearn(columns_obs_only=[\"gender\", \"race\"])[:100]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "3351e8d3",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<script type=\"esms-options\">{\"shimMode\": true}</script><style>*[data-root-id],\n",
-       "*[data-root-id] > * {\n",
-       "  box-sizing: border-box;\n",
-       "  font-family: var(--jp-ui-font-family);\n",
-       "  font-size: var(--jp-ui-font-size1);\n",
-       "  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
-       "}\n",
-       "\n",
-       "/* Override VSCode background color */\n",
-       ".cell-output-ipywidget-background:has(\n",
-       "  > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
-       "),\n",
-       ".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
-       "  background-color: transparent !important;\n",
-       "}\n",
-       "</style>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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-       "  var render_items = [{\"docid\":\"fc92d563-d911-41d8-8b46-528de9d49a89\",\"roots\":{\"3861f770-ce95-460e-8f26-539b59c8eecd\":\"fdce3fab-e19b-474d-9b7e-9a7d5b8a50ae\"},\"root_ids\":[\"3861f770-ce95-460e-8f26-539b59c8eecd\"]}];\n",
-       "  var docs = Object.values(docs_json)\n",
-       "  if (!docs) {\n",
-       "    return\n",
-       "  }\n",
-       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
-       "  async function embed_document(root) {\n",
-       "    var Bokeh = get_bokeh(root)\n",
-       "    await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
-       "    for (const render_item of render_items) {\n",
-       "      for (const root_id of render_item.root_ids) {\n",
-       "\tconst id_el = document.getElementById(root_id)\n",
-       "\tif (id_el.children.length && id_el.children[0].hasAttribute('data-root-id')) {\n",
-       "\t  const root_el = id_el.children[0]\n",
-       "\t  root_el.id = root_el.id + '-rendered'\n",
-       "\t  for (const child of root_el.children) {\n",
-       "            // Ensure JupyterLab does not capture keyboard shortcuts\n",
-       "            // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
-       "\t    child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
-       "\t  }\n",
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-       "  function get_bokeh(root) {\n",
-       "    if (root.Bokeh === undefined) {\n",
-       "      return null\n",
-       "    } else if (root.Bokeh.version !== py_version) {\n",
-       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
-       "\treturn null\n",
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-       "      return root.Bokeh.versions.get(py_version);\n",
-       "    } else if (root.Bokeh.version === py_version) {\n",
-       "      return root.Bokeh\n",
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-       "  function is_loaded(root) {\n",
-       "    var Bokeh = get_bokeh(root)\n",
-       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
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-       "  if (is_loaded(root)) {\n",
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-       "  } else {\n",
-       "    var attempts = 0;\n",
-       "    var timer = setInterval(function(root) {\n",
-       "      if (is_loaded(root)) {\n",
-       "        clearInterval(timer);\n",
-       "        embed_document(root);\n",
-       "      } else if (document.readyState == \"complete\") {\n",
-       "        attempts++;\n",
-       "        if (attempts > 200) {\n",
-       "          clearInterval(timer);\n",
-       "\t  var Bokeh = get_bokeh(root)\n",
-       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
-       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
-       "\t  } else {\n",
-       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
-       "\t    embed_document(root)\n",
-       "\t  }\n",
-       "        }\n",
-       "      }\n",
-       "    }, 25, root)\n",
-       "  }\n",
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-       "\n",
-       "\n",
-       "\n",
-       "<a href=\"https://matplotlib.org\" target=\"_blank\" title=\"Matplotlib 3.10.5\">\n",
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-       "5nK5CQAQMtXznCRJePpEbwOAZhzHX4ix/wHzzC/tu64gcwAAAABJRU5ErkJggg=='\n",
-       "       style='height:15px; border-radius:12px; display: inline-block; float: left'></img>\n",
-       "</a>\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "<span style=\"float: left; margin-left: 5px; line-height: 15px; cursor: pointer; opacity: 0.7;\"\n",
-       "      onmouseover=\"this.style.opacity='1'\"\n",
-       "      onmouseout=\"this.style.opacity='0.7'\"\n",
-       "      title=\"Extension loaded. This cell output contains code that enables plot interactivity, it should not be removed.\">ⓘ</span>\n",
-       "</div>\n",
-       "\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "sankey = ep.pl.plot_sankey(edata, columns=[\"gender\", \"race\"], backend=\"matplotlib\", show=False)\n",
-    "fig = hv.render(sankey, backend=\"matplotlib\")\n",
-    "\n",
-    "fig.savefig(f\"{_TEST_IMAGE_PATH}/sankey_expected.png\", dpi=80)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "4b735603",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
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' style='max-width:100%; margin: auto; display: block; '/>"
-      ],
-      "text/plain": [
-       ":Sankey   [source,target]   (value)"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {
-      "application/vnd.holoviews_exec.v0+json": {}
-     },
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "sankey"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "id": "53b26cc8",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<script type=\"esms-options\">{\"shimMode\": true}</script><style>*[data-root-id],\n",
-       "*[data-root-id] > * {\n",
-       "  box-sizing: border-box;\n",
-       "  font-family: var(--jp-ui-font-family);\n",
-       "  font-size: var(--jp-ui-font-size1);\n",
-       "  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
-       "}\n",
-       "\n",
-       "/* Override VSCode background color */\n",
-       ".cell-output-ipywidget-background:has(\n",
-       "  > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
-       "),\n",
-       ".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
-       "  background-color: transparent !important;\n",
-       "}\n",
-       "</style>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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-       "  var render_items = [{\"docid\":\"29b485c6-2547-4029-a5bb-1d7617c45c01\",\"roots\":{\"4b623405-3adc-45f6-a42e-a95b0e06a313\":\"bfa2e2f6-334f-447b-9d44-73aeaa27c5d2\"},\"root_ids\":[\"4b623405-3adc-45f6-a42e-a95b0e06a313\"]}];\n",
-       "  var docs = Object.values(docs_json)\n",
-       "  if (!docs) {\n",
-       "    return\n",
-       "  }\n",
-       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
-       "  async function embed_document(root) {\n",
-       "    var Bokeh = get_bokeh(root)\n",
-       "    await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
-       "    for (const render_item of render_items) {\n",
-       "      for (const root_id of render_item.root_ids) {\n",
-       "\tconst id_el = document.getElementById(root_id)\n",
-       "\tif (id_el.children.length && id_el.children[0].hasAttribute('data-root-id')) {\n",
-       "\t  const root_el = id_el.children[0]\n",
-       "\t  root_el.id = root_el.id + '-rendered'\n",
-       "\t  for (const child of root_el.children) {\n",
-       "            // Ensure JupyterLab does not capture keyboard shortcuts\n",
-       "            // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
-       "\t    child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
-       "\t  }\n",
-       "\t}\n",
-       "      }\n",
-       "    }\n",
-       "  }\n",
-       "  function get_bokeh(root) {\n",
-       "    if (root.Bokeh === undefined) {\n",
-       "      return null\n",
-       "    } else if (root.Bokeh.version !== py_version) {\n",
-       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
-       "\treturn null\n",
-       "      }\n",
-       "      return root.Bokeh.versions.get(py_version);\n",
-       "    } else if (root.Bokeh.version === py_version) {\n",
-       "      return root.Bokeh\n",
-       "    }\n",
-       "    return null\n",
-       "  }\n",
-       "  function is_loaded(root) {\n",
-       "    var Bokeh = get_bokeh(root)\n",
-       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
-       "  }\n",
-       "  if (is_loaded(root)) {\n",
-       "    embed_document(root);\n",
-       "  } else {\n",
-       "    var attempts = 0;\n",
-       "    var timer = setInterval(function(root) {\n",
-       "      if (is_loaded(root)) {\n",
-       "        clearInterval(timer);\n",
-       "        embed_document(root);\n",
-       "      } else if (document.readyState == \"complete\") {\n",
-       "        attempts++;\n",
-       "        if (attempts > 200) {\n",
-       "          clearInterval(timer);\n",
-       "\t  var Bokeh = get_bokeh(root)\n",
-       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
-       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
-       "\t  } else {\n",
-       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
-       "\t    embed_document(root)\n",
-       "\t  }\n",
-       "        }\n",
-       "      }\n",
-       "    }, 25, root)\n",
-       "  }\n",
-       "})(window);</script>"
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-       "\n",
-       "\n",
-       "\n",
-       "\n",
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-       "      title=\"Extension loaded. This cell output contains code that enables plot interactivity, it should not be removed.\">ⓘ</span>\n",
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fa-info-circle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]}]}]},{\"type\":\"model\",\"name\":\"Notification\",\"properties\":[{\"name\":\"background\",\"kind\":\"Any\",\"default\":null},{\"name\":\"duration\",\"kind\":\"Any\",\"default\":3000},{\"name\":\"icon\",\"kind\":\"Any\",\"default\":null},{\"name\":\"message\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"notification_type\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_rendered\",\"kind\":\"Any\",\"default\":false},{\"name\":\"_destroyed\",\"kind\":\"Any\",\"default\":false}]},{\"type\":\"model\",\"name\":\"TemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"BootstrapTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"TemplateEditor1\",\"properties\":[{\"name\":\"layout\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"MaterialTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"request_value1\",\"properties\":[{\"name\":\"fill\",\"kind\":\"Any\",\"default\":\"none\"},{\"name\":\"_synced\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_request_sync\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"holoviews.plotting.bokeh.raster.HoverModel\",\"properties\":[{\"name\":\"xy\",\"kind\":\"Any\",\"default\":null},{\"name\":\"data\",\"kind\":\"Any\",\"default\":null}]}]}};\n",
-       "  var render_items = [{\"docid\":\"ac796c77-942a-473e-a5db-c809186eeff3\",\"roots\":{\"4e054e45-2bea-484d-a8cc-4268c182c4f8\":\"f1cbd83b-d23e-4501-9795-fcf1fb2bd0f5\"},\"root_ids\":[\"4e054e45-2bea-484d-a8cc-4268c182c4f8\"]}];\n",
-       "  var docs = Object.values(docs_json)\n",
-       "  if (!docs) {\n",
-       "    return\n",
-       "  }\n",
-       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
-       "  async function embed_document(root) {\n",
-       "    var Bokeh = get_bokeh(root)\n",
-       "    await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
-       "    for (const render_item of render_items) {\n",
-       "      for (const root_id of render_item.root_ids) {\n",
-       "\tconst id_el = document.getElementById(root_id)\n",
-       "\tif (id_el.children.length && id_el.children[0].hasAttribute('data-root-id')) {\n",
-       "\t  const root_el = id_el.children[0]\n",
-       "\t  root_el.id = root_el.id + '-rendered'\n",
-       "\t  for (const child of root_el.children) {\n",
-       "            // Ensure JupyterLab does not capture keyboard shortcuts\n",
-       "            // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
-       "\t    child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
-       "\t  }\n",
-       "\t}\n",
-       "      }\n",
-       "    }\n",
-       "  }\n",
-       "  function get_bokeh(root) {\n",
-       "    if (root.Bokeh === undefined) {\n",
-       "      return null\n",
-       "    } else if (root.Bokeh.version !== py_version) {\n",
-       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
-       "\treturn null\n",
-       "      }\n",
-       "      return root.Bokeh.versions.get(py_version);\n",
-       "    } else if (root.Bokeh.version === py_version) {\n",
-       "      return root.Bokeh\n",
-       "    }\n",
-       "    return null\n",
-       "  }\n",
-       "  function is_loaded(root) {\n",
-       "    var Bokeh = get_bokeh(root)\n",
-       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
-       "  }\n",
-       "  if (is_loaded(root)) {\n",
-       "    embed_document(root);\n",
-       "  } else {\n",
-       "    var attempts = 0;\n",
-       "    var timer = setInterval(function(root) {\n",
-       "      if (is_loaded(root)) {\n",
-       "        clearInterval(timer);\n",
-       "        embed_document(root);\n",
-       "      } else if (document.readyState == \"complete\") {\n",
-       "        attempts++;\n",
-       "        if (attempts > 200) {\n",
-       "          clearInterval(timer);\n",
-       "\t  var Bokeh = get_bokeh(root)\n",
-       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
-       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
-       "\t  } else {\n",
-       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
-       "\t    embed_document(root)\n",
-       "\t  }\n",
-       "        }\n",
-       "      }\n",
-       "    }, 25, root)\n",
-       "  }\n",
-       "})(window);</script>"
-      ],
-      "text/plain": [
-       ":Sankey   [source,target]   (value)"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {
-      "application/vnd.holoviews_exec.v0+json": {
-       "id": "4e054e45-2bea-484d-a8cc-4268c182c4f8"
-      }
-     },
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "ep.pl.plot_sankey(edata, columns=[\"gender\", \"race\"], backend=\"bokeh\", show=False)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "id": "a59e9a13",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "layer = np.array(\n",
-    "        [\n",
-    "            [[0, 1, 2, 1, 2], \n",
-    "             [1, 2, 1, 2, 0]],  \n",
-    "    \n",
-    "            [[1, 2, 0, 2, 1],\n",
-    "             [2, 1, 2, 1, 2]],\n",
-    "     \n",
-    "            [[2, 0, 1, 2, 0],\n",
-    "             [2, 0, 1, 1, 2]],\n",
-    "            \n",
-    "            [[1, 2, 1, 0, 1],\n",
-    "             [0, 2, 1, 2, 0]],\n",
-    "\n",
-    "            [[0, 2, 1, 2, 2],\n",
-    "             [1, 2, 1, 0, 2]],\n",
-    "        ]\n",
-    "    )\n",
-    "\n",
-    "\n",
-    "edata_time = ed.EHRData(\n",
-    "    layers={\"layer_1\": layer},\n",
-    "    obs=pd.DataFrame(index=[\"patient_1\", \"patient_2\", \"patient_3\", \"patient_4\", \"patient_5\"]),\n",
-    "    var=pd.DataFrame(index=[\"treatment\", \"disease_flare\"]),\n",
-    "    tem=pd.DataFrame(index=[\"visit_0\", \"visit_1\", \"visit_2\", \"visit_3\", \"visit_4\"]),\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "id": "dfb9988e",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<script type=\"esms-options\">{\"shimMode\": true}</script><style>*[data-root-id],\n",
-       "*[data-root-id] > * {\n",
-       "  box-sizing: border-box;\n",
-       "  font-family: var(--jp-ui-font-family);\n",
-       "  font-size: var(--jp-ui-font-size1);\n",
-       "  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
-       "}\n",
-       "\n",
-       "/* Override VSCode background color */\n",
-       ".cell-output-ipywidget-background:has(\n",
-       "  > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
-       "),\n",
-       ".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
-       "  background-color: transparent !important;\n",
-       "}\n",
-       "</style>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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i < links.length; i++) {\n      const link = links[i]\n      if (link.href != null) {\n        existing_stylesheets.push(link.href)\n      }\n    }\n    for (let i = 0; i < css_urls.length; i++) {\n      const url = css_urls[i];\n      const escaped = encodeURI(url)\n      if (existing_stylesheets.indexOf(escaped) !== -1) {\n        on_load()\n        continue;\n      }\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }    var existing_scripts = []\n    const scripts = document.getElementsByTagName('script')\n    for (let i = 0; i < scripts.length; i++) {\n      var script = scripts[i]\n      if (script.src != null) {\n        existing_scripts.push(script.src)\n      }\n    }\n    for (let i = 0; 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-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
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-     "data": {
-      "application/javascript": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n  window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n    function JupyterCommManager() {\n    }\n\n    JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n      if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        comm_manager.register_target(comm_id, function(comm) {\n          comm.on_msg(msg_handler);\n        });\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n          comm.onMsg = msg_handler;\n        });\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        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-       "<a href=\"https://matplotlib.org\" target=\"_blank\" title=\"Matplotlib 3.10.5\">\n",
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-       "5nK5CQAQMtXznCRJePpEbwOAZhzHX4ix/wHzzC/tu64gcwAAAABJRU5ErkJggg=='\n",
-       "       style='height:15px; border-radius:12px; display: inline-block; float: left'></img>\n",
-       "</a>\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "<span style=\"float: left; margin-left: 5px; line-height: 15px; cursor: pointer; opacity: 0.7;\"\n",
-       "      onmouseover=\"this.style.opacity='1'\"\n",
-       "      onmouseout=\"this.style.opacity='0.7'\"\n",
-       "      title=\"Extension loaded. This cell output contains code that enables plot interactivity, it should not be removed.\">ⓘ</span>\n",
-       "</div>\n",
-       "\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "sankey_time = ep.pl.plot_sankey_time(\n",
-    "    edata_time,\n",
-    "    columns=[\"disease_flare\"],\n",
-    "    layer=\"layer_1\",\n",
-    "    state_labels={0: \"no flare\", 1: \"mid flare\", 2: \"severe flare\"},\n",
-    "    backend=\"matplotlib\",\n",
-    ")\n",
-    "\n",
-    "fig = hv.render(sankey_time, backend=\"matplotlib\")\n",
-    "fig.savefig(f\"{_TEST_IMAGE_PATH}/sankey_time_expected.png\", dpi=80)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "id": "c9b9fb79",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
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' style='max-width:100%; margin: auto; display: block; '/>"
-      ],
-      "text/plain": [
-       ":Sankey   [source,target]   (value)"
-      ]
-     },
-     "execution_count": 9,
-     "metadata": {
-      "application/vnd.holoviews_exec.v0+json": {}
-     },
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "sankey_time"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "id": "38907509",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<script type=\"esms-options\">{\"shimMode\": true}</script><style>*[data-root-id],\n",
-       "*[data-root-id] > * {\n",
-       "  box-sizing: border-box;\n",
-       "  font-family: var(--jp-ui-font-family);\n",
-       "  font-size: var(--jp-ui-font-size1);\n",
-       "  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
-       "}\n",
-       "\n",
-       "/* Override VSCode background color */\n",
-       ".cell-output-ipywidget-background:has(\n",
-       "  > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
-       "),\n",
-       ".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
-       "  background-color: transparent !important;\n",
-       "}\n",
-       "</style>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/javascript": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  const force = true;\n  const py_version = '3.8.1'.replace('rc', '-rc.').replace('.dev', '-dev.');\n  const reloading = false;\n  const Bokeh = root.Bokeh;\n\n  // Set a timeout for this load but only if we are not already initializing\n  if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks;\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n    if (js_modules == null) js_modules = [];\n    if (js_exports == null) js_exports = {};\n\n    root._bokeh_onload_callbacks.push(callback);\n\n    if (root._bokeh_is_loading > 0) {\n      // Don't load bokeh if it is still initializing\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n      // There is nothing to load\n      run_callbacks();\n      return null;\n    }\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n    window._bokeh_on_load = on_load\n\n    function on_error(e) {\n      const src_el = e.srcElement\n      console.error(\"failed to load \" + (src_el.href || src_el.src));\n    }\n\n    const skip = [];\n    if (window.requirejs) {\n      window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n      root._bokeh_is_loading = css_urls.length + 0;\n    } else {\n      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n    }\n\n    const existing_stylesheets = []\n    const links = document.getElementsByTagName('link')\n    for (let i = 0; i < links.length; i++) {\n      const link = links[i]\n      if (link.href != null) {\n        existing_stylesheets.push(link.href)\n      }\n    }\n    for (let i = 0; i < css_urls.length; i++) {\n      const url = css_urls[i];\n      const escaped = encodeURI(url)\n      if (existing_stylesheets.indexOf(escaped) !== -1) {\n        on_load()\n        continue;\n      }\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }    var existing_scripts = []\n    const scripts = document.getElementsByTagName('script')\n    for (let i = 0; i < scripts.length; i++) {\n      var script = scripts[i]\n      if (script.src != null) {\n        existing_scripts.push(script.src)\n      }\n    }\n    for (let i = 0; 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-       "  var render_items = [{\"docid\":\"89d336df-d1e3-4e4c-8582-ae9fb3550b87\",\"roots\":{\"9b1a6df2-903d-4967-9384-104ce84a0cea\":\"bcb45503-8765-4434-a3b3-d6c444e50221\"},\"root_ids\":[\"9b1a6df2-903d-4967-9384-104ce84a0cea\"]}];\n",
-       "  var docs = Object.values(docs_json)\n",
-       "  if (!docs) {\n",
-       "    return\n",
-       "  }\n",
-       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
-       "  async function embed_document(root) {\n",
-       "    var Bokeh = get_bokeh(root)\n",
-       "    await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
-       "    for (const render_item of render_items) {\n",
-       "      for (const root_id of render_item.root_ids) {\n",
-       "\tconst id_el = document.getElementById(root_id)\n",
-       "\tif (id_el.children.length && id_el.children[0].hasAttribute('data-root-id')) {\n",
-       "\t  const root_el = id_el.children[0]\n",
-       "\t  root_el.id = root_el.id + '-rendered'\n",
-       "\t  for (const child of root_el.children) {\n",
-       "            // Ensure JupyterLab does not capture keyboard shortcuts\n",
-       "            // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
-       "\t    child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
-       "\t  }\n",
-       "\t}\n",
-       "      }\n",
-       "    }\n",
-       "  }\n",
-       "  function get_bokeh(root) {\n",
-       "    if (root.Bokeh === undefined) {\n",
-       "      return null\n",
-       "    } else if (root.Bokeh.version !== py_version) {\n",
-       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
-       "\treturn null\n",
-       "      }\n",
-       "      return root.Bokeh.versions.get(py_version);\n",
-       "    } else if (root.Bokeh.version === py_version) {\n",
-       "      return root.Bokeh\n",
-       "    }\n",
-       "    return null\n",
-       "  }\n",
-       "  function is_loaded(root) {\n",
-       "    var Bokeh = get_bokeh(root)\n",
-       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
-       "  }\n",
-       "  if (is_loaded(root)) {\n",
-       "    embed_document(root);\n",
-       "  } else {\n",
-       "    var attempts = 0;\n",
-       "    var timer = setInterval(function(root) {\n",
-       "      if (is_loaded(root)) {\n",
-       "        clearInterval(timer);\n",
-       "        embed_document(root);\n",
-       "      } else if (document.readyState == \"complete\") {\n",
-       "        attempts++;\n",
-       "        if (attempts > 200) {\n",
-       "          clearInterval(timer);\n",
-       "\t  var Bokeh = get_bokeh(root)\n",
-       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
-       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
-       "\t  } else {\n",
-       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
-       "\t    embed_document(root)\n",
-       "\t  }\n",
-       "        }\n",
-       "      }\n",
-       "    }, 25, root)\n",
-       "  }\n",
-       "})(window);</script>"
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-       "      title=\"Extension loaded. This cell output contains code that enables plot interactivity, it should not be removed.\">ⓘ</span>\n",
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fa-info-circle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]}]}]},{\"type\":\"model\",\"name\":\"Notification\",\"properties\":[{\"name\":\"background\",\"kind\":\"Any\",\"default\":null},{\"name\":\"duration\",\"kind\":\"Any\",\"default\":3000},{\"name\":\"icon\",\"kind\":\"Any\",\"default\":null},{\"name\":\"message\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"notification_type\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_rendered\",\"kind\":\"Any\",\"default\":false},{\"name\":\"_destroyed\",\"kind\":\"Any\",\"default\":false}]},{\"type\":\"model\",\"name\":\"TemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"BootstrapTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"TemplateEditor1\",\"properties\":[{\"name\":\"layout\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"MaterialTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"request_value1\",\"properties\":[{\"name\":\"fill\",\"kind\":\"Any\",\"default\":\"none\"},{\"name\":\"_synced\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_request_sync\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"holoviews.plotting.bokeh.raster.HoverModel\",\"properties\":[{\"name\":\"xy\",\"kind\":\"Any\",\"default\":null},{\"name\":\"data\",\"kind\":\"Any\",\"default\":null}]}]}};\n",
-       "  var render_items = [{\"docid\":\"e33249d4-4bf0-4892-9267-5d1444d6464a\",\"roots\":{\"fb57819f-f792-458d-87fb-43d4a5875885\":\"b6b12b01-4b08-452f-acf4-58b0b888c3d5\"},\"root_ids\":[\"fb57819f-f792-458d-87fb-43d4a5875885\"]}];\n",
-       "  var docs = Object.values(docs_json)\n",
-       "  if (!docs) {\n",
-       "    return\n",
-       "  }\n",
-       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
-       "  async function embed_document(root) {\n",
-       "    var Bokeh = get_bokeh(root)\n",
-       "    await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
-       "    for (const render_item of render_items) {\n",
-       "      for (const root_id of render_item.root_ids) {\n",
-       "\tconst id_el = document.getElementById(root_id)\n",
-       "\tif (id_el.children.length && id_el.children[0].hasAttribute('data-root-id')) {\n",
-       "\t  const root_el = id_el.children[0]\n",
-       "\t  root_el.id = root_el.id + '-rendered'\n",
-       "\t  for (const child of root_el.children) {\n",
-       "            // Ensure JupyterLab does not capture keyboard shortcuts\n",
-       "            // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
-       "\t    child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
-       "\t  }\n",
-       "\t}\n",
-       "      }\n",
-       "    }\n",
-       "  }\n",
-       "  function get_bokeh(root) {\n",
-       "    if (root.Bokeh === undefined) {\n",
-       "      return null\n",
-       "    } else if (root.Bokeh.version !== py_version) {\n",
-       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
-       "\treturn null\n",
-       "      }\n",
-       "      return root.Bokeh.versions.get(py_version);\n",
-       "    } else if (root.Bokeh.version === py_version) {\n",
-       "      return root.Bokeh\n",
-       "    }\n",
-       "    return null\n",
-       "  }\n",
-       "  function is_loaded(root) {\n",
-       "    var Bokeh = get_bokeh(root)\n",
-       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
-       "  }\n",
-       "  if (is_loaded(root)) {\n",
-       "    embed_document(root);\n",
-       "  } else {\n",
-       "    var attempts = 0;\n",
-       "    var timer = setInterval(function(root) {\n",
-       "      if (is_loaded(root)) {\n",
-       "        clearInterval(timer);\n",
-       "        embed_document(root);\n",
-       "      } else if (document.readyState == \"complete\") {\n",
-       "        attempts++;\n",
-       "        if (attempts > 200) {\n",
-       "          clearInterval(timer);\n",
-       "\t  var Bokeh = get_bokeh(root)\n",
-       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
-       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
-       "\t  } else {\n",
-       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
-       "\t    embed_document(root)\n",
-       "\t  }\n",
-       "        }\n",
-       "      }\n",
-       "    }, 25, root)\n",
-       "  }\n",
-       "})(window);</script>"
-      ],
-      "text/plain": [
-       ":Sankey   [source,target]   (value)"
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {
-      "application/vnd.holoviews_exec.v0+json": {
-       "id": "fb57819f-f792-458d-87fb-43d4a5875885"
-      }
-     },
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "ep.pl.plot_sankey_time(\n",
-    "    edata_time, columns=[\"disease_flare\"], layer=\"layer_1\", state_labels={0: \"no flare\",  1: \"mid flare\", 2: \"severe flare\"}, backend=\"bokeh\"\n",
-    ")"
-   ]
-  }
- ],
- "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": "3.13.6"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
diff --git a/tests/_scripts/sankey_matplotlib_expected.ipynb b/tests/_scripts/sankey_matplotlib_expected.ipynb
new file mode 100644
index 000000000..d72909844
--- /dev/null
+++ b/tests/_scripts/sankey_matplotlib_expected.ipynb
@@ -0,0 +1,696 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "42a55492",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<script type=\"esms-options\">{\"shimMode\": true}</script><style>*[data-root-id],\n",
+       "*[data-root-id] > * {\n",
+       "  box-sizing: border-box;\n",
+       "  font-family: var(--jp-ui-font-family);\n",
+       "  font-size: var(--jp-ui-font-size1);\n",
+       "  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
+       "}\n",
+       "\n",
+       "/* Override VSCode background color */\n",
+       ".cell-output-ipywidget-background:has(\n",
+       "  > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
+       "),\n",
+       ".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "</style>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/javascript": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  const force = true;\n  const py_version = '3.8.1'.replace('rc', '-rc.').replace('.dev', '-dev.');\n  const reloading = false;\n  const Bokeh = root.Bokeh;\n\n  // Set a timeout for this load but only if we are not already initializing\n  if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks;\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n    if (js_modules == null) js_modules = [];\n    if (js_exports == null) js_exports = {};\n\n    root._bokeh_onload_callbacks.push(callback);\n\n    if (root._bokeh_is_loading > 0) {\n      // Don't load bokeh if it is still initializing\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n      // There is nothing to load\n      run_callbacks();\n      return null;\n    }\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n    window._bokeh_on_load = on_load\n\n    function on_error(e) {\n      const src_el = e.srcElement\n      console.error(\"failed to load \" + (src_el.href || src_el.src));\n    }\n\n    const skip = [];\n    if (window.requirejs) {\n      window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n      root._bokeh_is_loading = css_urls.length + 0;\n    } else {\n      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n    }\n\n    const existing_stylesheets = []\n    const links = document.getElementsByTagName('link')\n    for (let i = 0; i < links.length; i++) {\n      const link = links[i]\n      if (link.href != null) {\n        existing_stylesheets.push(link.href)\n      }\n    }\n    for (let i = 0; i < css_urls.length; i++) {\n      const url = css_urls[i];\n      const escaped = encodeURI(url)\n      if (existing_stylesheets.indexOf(escaped) !== -1) {\n        on_load()\n        continue;\n      }\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }    var existing_scripts = []\n    const scripts = document.getElementsByTagName('script')\n    for (let i = 0; i < scripts.length; i++) {\n      var script = scripts[i]\n      if (script.src != null) {\n        existing_scripts.push(script.src)\n      }\n    }\n    for (let i = 0; i < js_urls.length; i++) {\n      const url = js_urls[i];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      const element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (let i = 0; i < js_modules.length; i++) {\n      const url = js_modules[i];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (const name in js_exports) {\n      const url = js_exports[name];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      var element = document.createElement('script');\n      element.onerror = on_error;\n      element.async = false;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      element.textContent = `\n      import ${name} from \"${url}\"\n      window.${name} = ${name}\n      window._bokeh_on_load()\n      `\n      document.head.appendChild(element);\n    }\n    if (!js_urls.length && !js_modules.length) {\n      on_load()\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  const js_urls = [\"https://cdn.holoviz.org/panel/1.8.3/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-3.8.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.8.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.8.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.8.1.min.js\", \"https://cdn.holoviz.org/panel/1.8.3/dist/panel.min.js\"];\n  const js_modules = [];\n  const js_exports = {};\n  const css_urls = [];\n  const inline_js = [    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n  ];\n\n  function run_inline_js() {\n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (let i = 0; i < inline_js.length; i++) {\n        try {\n          inline_js[i].call(root, root.Bokeh);\n        } catch(e) {\n          if (!reloading) {\n            throw e;\n          }\n        }\n      }\n      // Cache old bokeh versions\n      if (Bokeh != undefined && !reloading) {\n        var NewBokeh = root.Bokeh;\n        if (Bokeh.versions === undefined) {\n          Bokeh.versions = new Map();\n        }\n        if (NewBokeh.version !== Bokeh.version) {\n          Bokeh.versions.set(NewBokeh.version, NewBokeh)\n        }\n        root.Bokeh = Bokeh;\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    }\n    root._bokeh_is_initializing = false\n  }\n\n  function load_or_wait() {\n    // Implement a backoff loop that tries to ensure we do not load multiple\n    // versions of Bokeh and its dependencies at the same time.\n    // In recent versions we use the root._bokeh_is_initializing flag\n    // to determine whether there is an ongoing attempt to initialize\n    // bokeh, however for backward compatibility we also try to ensure\n    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n    // before older versions are fully initialized.\n    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n      // If the timeout and bokeh was not successfully loaded we reset\n      // everything and try loading again\n      root._bokeh_timeout = Date.now() + 5000;\n      root._bokeh_is_initializing = false;\n      root._bokeh_onload_callbacks = undefined;\n      root._bokeh_is_loading = 0\n      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n      load_or_wait();\n    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n      setTimeout(load_or_wait, 100);\n    } else {\n      root._bokeh_is_initializing = true\n      root._bokeh_onload_callbacks = []\n      const bokeh_loaded = root.Bokeh != null && (root.Bokeh.version === py_version || (root.Bokeh.versions !== undefined && root.Bokeh.versions.has(py_version)));\n      if (!reloading && !bokeh_loaded) {\n        if (root.Bokeh) {\n          root.Bokeh = undefined;\n        }\n        console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n      }\n      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n        console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n        run_inline_js();\n      });\n    }\n  }\n  // Give older versions of the autoload script a head-start to ensure\n  // they initialize before we start loading newer version.\n  setTimeout(load_or_wait, 100)\n}(window));",
+      "application/vnd.holoviews_load.v0+json": ""
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/javascript": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n  window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n    function JupyterCommManager() {\n    }\n\n    JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n      if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        comm_manager.register_target(comm_id, function(comm) {\n          comm.on_msg(msg_handler);\n        });\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n          comm.onMsg = msg_handler;\n        });\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n          var messages = comm.messages[Symbol.asyncIterator]();\n          function processIteratorResult(result) {\n            var message = result.value;\n            var content = {data: message.data, comm_id};\n            var buffers = []\n            for (var buffer of message.buffers || []) {\n              buffers.push(new DataView(buffer))\n            }\n            var metadata = message.metadata || {};\n            var msg = {content, buffers, metadata}\n            msg_handler(msg);\n            return messages.next().then(processIteratorResult);\n          }\n          return messages.next().then(processIteratorResult);\n        })\n      }\n    }\n\n    JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n      if (comm_id in window.PyViz.comms) {\n        return window.PyViz.comms[comm_id];\n      } else if (window.comm_manager || ((window.Jupyter !== undefined) && 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+     },
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+     "output_type": "display_data"
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+       "</div>\n",
+       "<script type=\"application/javascript\">(function(root) {\n",
+       "  var docs_json = {\"8f19d643-1119-4f25-be40-8771a975a3c6\":{\"version\":\"3.8.1\",\"title\":\"Bokeh 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+       "    return\n",
+       "  }\n",
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+       "    var Bokeh = get_bokeh(root)\n",
+       "    await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
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+       "      for (const root_id of render_item.root_ids) {\n",
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+       "            // Ensure JupyterLab does not capture keyboard shortcuts\n",
+       "            // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
+       "\t    child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
+       "\t  }\n",
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+       "    if (root.Bokeh === undefined) {\n",
+       "      return null\n",
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+       "    } else if (root.Bokeh.version === py_version) {\n",
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+       "    }\n",
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+       "        if (attempts > 200) {\n",
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+       "\t  var Bokeh = get_bokeh(root)\n",
+       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
+       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
+       "\t  } else {\n",
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+       "\t    embed_document(root)\n",
+       "\t  }\n",
+       "        }\n",
+       "      }\n",
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+       "  }\n",
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+       "N/9Q5zd/XR34LYCwV5JdccMEAMDBk45DH243r/X4xGvqxFa/GNpS7n6rwOwNWwHVE26oAADYurf1\n",
+       "zx/utOzt+DMKYM0p17YtZZ5VNzqfsB2HewG1WXE8PoZ7gOclbTIvynZf9JV+fqZtfgs/8F/Nu5rB\n",
+       "EIBmJ+8QRMmpU7EzGRsf2FzuePqYRbzh/zE26EwdrT10f6r6o8HOYzCJB9Dpff8tbnGLG8L/A/WE\n",
+       "roTBs2RqAAAAAElFTkSuQmCC' style='height:25px; border-radius:12px; display: inline-block; float: left; vertical-align: middle'></img>\n",
+       "</a>\n",
+       "\n",
+       "\n",
+       "<a href=\"https://bokeh.org\" target=\"_blank\" title=\"Bokeh 3.8.1\">\n",
+       "  <img src='data:image/png;base64,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'\n",
+       "       style='height:15px; border-radius:12px; display: inline-block; float: left'>\n",
+       "  </img>\n",
+       "</a>\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "<span style=\"float: left; margin-left: 5px; line-height: 15px; cursor: pointer; opacity: 0.7;\"\n",
+       "      onmouseover=\"this.style.opacity='1'\"\n",
+       "      onmouseout=\"this.style.opacity='0.7'\"\n",
+       "      title=\"Extension loaded. This cell output contains code that enables plot interactivity, it should not be removed.\">ⓘ</span>\n",
+       "</div>\n",
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "import ehrdata as ed\n",
+    "import holoviews as hv\n",
+    "import matplotlib.pyplot as plt\n",
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "\n",
+    "import ehrapy as ep"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "8e89fc6d",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<script type=\"esms-options\">{\"shimMode\": true}</script><style>*[data-root-id],\n",
+       "*[data-root-id] > * {\n",
+       "  box-sizing: border-box;\n",
+       "  font-family: var(--jp-ui-font-family);\n",
+       "  font-size: var(--jp-ui-font-size1);\n",
+       "  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
+       "}\n",
+       "\n",
+       "/* Override VSCode background color */\n",
+       ".cell-output-ipywidget-background:has(\n",
+       "  > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
+       "),\n",
+       ".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
+       "  background-color: transparent !important;\n",
+       "}\n",
+       "</style>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "application/javascript": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  const force = true;\n  const py_version = '3.8.1'.replace('rc', '-rc.').replace('.dev', '-dev.');\n  const reloading = false;\n  const Bokeh = root.Bokeh;\n\n  // Set a timeout for this load but only if we are not already initializing\n  if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks;\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n    if (js_modules == null) js_modules = [];\n    if (js_exports == null) js_exports = {};\n\n    root._bokeh_onload_callbacks.push(callback);\n\n    if (root._bokeh_is_loading > 0) {\n      // Don't load bokeh if it is still initializing\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n      // There is nothing to load\n      run_callbacks();\n      return null;\n    }\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n    window._bokeh_on_load = on_load\n\n    function on_error(e) {\n      const src_el = e.srcElement\n      console.error(\"failed to load \" + (src_el.href || src_el.src));\n    }\n\n    const skip = [];\n    if (window.requirejs) {\n      window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n      root._bokeh_is_loading = css_urls.length + 0;\n    } else {\n      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n    }\n\n    const existing_stylesheets = []\n    const links = document.getElementsByTagName('link')\n    for (let i = 0; i < links.length; i++) {\n      const link = links[i]\n      if (link.href != null) {\n        existing_stylesheets.push(link.href)\n      }\n    }\n    for (let i = 0; i < css_urls.length; i++) {\n      const url = css_urls[i];\n      const escaped = encodeURI(url)\n      if (existing_stylesheets.indexOf(escaped) !== -1) {\n        on_load()\n        continue;\n      }\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }    var existing_scripts = []\n    const scripts = document.getElementsByTagName('script')\n    for (let i = 0; i < scripts.length; i++) {\n      var script = scripts[i]\n      if (script.src != null) {\n        existing_scripts.push(script.src)\n      }\n    }\n    for (let i = 0; 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+       "  var render_items = [{\"docid\":\"a30e22c4-a0d7-45e2-a457-bfceb676ed3c\",\"roots\":{\"a0d3e5ad-430a-4a56-8a43-a6f0948382a6\":\"baada055-3544-4abe-ac3f-4815ee6d6b47\"},\"root_ids\":[\"a0d3e5ad-430a-4a56-8a43-a6f0948382a6\"]}];\n",
+       "  var docs = Object.values(docs_json)\n",
+       "  if (!docs) {\n",
+       "    return\n",
+       "  }\n",
+       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
+       "  async function embed_document(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
+       "    for (const render_item of render_items) {\n",
+       "      for (const root_id of render_item.root_ids) {\n",
+       "\tconst id_el = document.getElementById(root_id)\n",
+       "\tif (id_el.children.length && id_el.children[0].hasAttribute('data-root-id')) {\n",
+       "\t  const root_el = id_el.children[0]\n",
+       "\t  root_el.id = root_el.id + '-rendered'\n",
+       "\t  for (const child of root_el.children) {\n",
+       "            // Ensure JupyterLab does not capture keyboard shortcuts\n",
+       "            // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
+       "\t    child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
+       "\t  }\n",
+       "\t}\n",
+       "      }\n",
+       "    }\n",
+       "  }\n",
+       "  function get_bokeh(root) {\n",
+       "    if (root.Bokeh === undefined) {\n",
+       "      return null\n",
+       "    } else if (root.Bokeh.version !== py_version) {\n",
+       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
+       "\treturn null\n",
+       "      }\n",
+       "      return root.Bokeh.versions.get(py_version);\n",
+       "    } else if (root.Bokeh.version === py_version) {\n",
+       "      return root.Bokeh\n",
+       "    }\n",
+       "    return null\n",
+       "  }\n",
+       "  function is_loaded(root) {\n",
+       "    var Bokeh = get_bokeh(root)\n",
+       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
+       "  }\n",
+       "  if (is_loaded(root)) {\n",
+       "    embed_document(root);\n",
+       "  } else {\n",
+       "    var attempts = 0;\n",
+       "    var timer = setInterval(function(root) {\n",
+       "      if (is_loaded(root)) {\n",
+       "        clearInterval(timer);\n",
+       "        embed_document(root);\n",
+       "      } else if (document.readyState == \"complete\") {\n",
+       "        attempts++;\n",
+       "        if (attempts > 200) {\n",
+       "          clearInterval(timer);\n",
+       "\t  var Bokeh = get_bokeh(root)\n",
+       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
+       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
+       "\t  } else {\n",
+       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
+       "\t    embed_document(root)\n",
+       "\t  }\n",
+       "        }\n",
+       "      }\n",
+       "    }, 25, root)\n",
+       "  }\n",
+       "})(window);</script>"
+      ]
+     },
+     "metadata": {
+      "application/vnd.holoviews_exec.v0+json": {
+       "id": "a0d3e5ad-430a-4a56-8a43-a6f0948382a6"
+      }
+     },
+     "output_type": "display_data"
+    },
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+       "roTBs2RqAAAAAElFTkSuQmCC' style='height:25px; border-radius:12px; display: inline-block; float: left; vertical-align: middle'></img>\n",
+       "</a>\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "<a href=\"https://matplotlib.org\" target=\"_blank\" title=\"Matplotlib 3.10.5\">\n",
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+       "5nK5CQAQMtXznCRJePpEbwOAZhzHX4ix/wHzzC/tu64gcwAAAABJRU5ErkJggg=='\n",
+       "       style='height:15px; border-radius:12px; display: inline-block; float: left'></img>\n",
+       "</a>\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "\n",
+       "<span style=\"float: left; margin-left: 5px; line-height: 15px; cursor: pointer; opacity: 0.7;\"\n",
+       "      onmouseover=\"this.style.opacity='1'\"\n",
+       "      onmouseout=\"this.style.opacity='0.7'\"\n",
+       "      title=\"Extension loaded. This cell output contains code that enables plot interactivity, it should not be removed.\">ⓘ</span>\n",
+       "</div>\n",
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "hv.extension(\"matplotlib\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "id": "8104f266",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "current_notebook_dir = %pwd\n",
+    "\n",
+    "_TEST_IMAGE_PATH = f\"{current_notebook_dir}/../plot/_images\""
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "e242cbd4",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\u001b[93m!\u001b[0m File ehrapy_data\\diabetes_130_fairlearn.csv already exists! Using already downloaded dataset...\n"
+     ]
+    }
+   ],
+   "source": [
+    "edata = ed.dt.diabetes_130_fairlearn(columns_obs_only=[\"gender\", \"race\"])[:100]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "3351e8d3",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sankey = ep.pl.plot_sankey(edata, columns=[\"gender\", \"race\"], show=False)\n",
+    "fig = hv.render(sankey, backend=\"matplotlib\")\n",
+    "\n",
+    "fig.savefig(f\"{_TEST_IMAGE_PATH}/sankey_expected.png\", dpi=80)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "4b735603",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
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' style='max-width:100%; margin: auto; display: block; '/>"
+      ],
+      "text/plain": [
+       ":Sankey   [source,target]   (value)"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {
+      "application/vnd.holoviews_exec.v0+json": {}
+     },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sankey"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "a59e9a13",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "layer = np.array(\n",
+    "    [\n",
+    "        [[0, 1, 2, 1, 2], [1, 2, 1, 2, 0]],\n",
+    "        [[1, 2, 0, 2, 1], [2, 1, 2, 1, 2]],\n",
+    "        [[2, 0, 1, 2, 0], [2, 0, 1, 1, 2]],\n",
+    "        [[1, 2, 1, 0, 1], [0, 2, 1, 2, 0]],\n",
+    "        [[0, 2, 1, 2, 2], [1, 2, 1, 0, 2]],\n",
+    "    ]\n",
+    ")\n",
+    "\n",
+    "\n",
+    "edata_time = ed.EHRData(\n",
+    "    layers={\"layer_1\": layer},\n",
+    "    obs=pd.DataFrame(index=[\"patient_1\", \"patient_2\", \"patient_3\", \"patient_4\", \"patient_5\"]),\n",
+    "    var=pd.DataFrame(index=[\"treatment\", \"disease_flare\"]),\n",
+    "    tem=pd.DataFrame(index=[\"visit_0\", \"visit_1\", \"visit_2\", \"visit_3\", \"visit_4\"]),\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "dfb9988e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sankey_time = ep.pl.plot_sankey_time(\n",
+    "    edata_time,\n",
+    "    columns=[\"disease_flare\"],\n",
+    "    layer=\"layer_1\",\n",
+    "    state_labels={0: \"no flare\", 1: \"mid flare\", 2: \"severe flare\"},\n",
+    "    backend=\"matplotlib\",\n",
+    ")\n",
+    "\n",
+    "fig = hv.render(sankey_time, backend=\"matplotlib\")\n",
+    "fig.savefig(f\"{_TEST_IMAGE_PATH}/sankey_time_expected.png\", dpi=80)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "c9b9fb79",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<img 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' style='max-width:100%; margin: auto; display: block; '/>"
+      ],
+      "text/plain": [
+       ":Sankey   [source,target]   (value)"
+      ]
+     },
+     "execution_count": 9,
+     "metadata": {
+      "application/vnd.holoviews_exec.v0+json": {}
+     },
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "sankey_time"
+   ]
+  }
+ ],
+ "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": "3.13.6"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/tests/plot/test_sankey.py b/tests/plot/test_sankey.py
index dcee7540b..8358df90c 100644
--- a/tests/plot/test_sankey.py
+++ b/tests/plot/test_sankey.py
@@ -16,20 +16,11 @@
 def ehr_3d_mini():
     layer = np.array(
         [
-            [[0, 1, 2, 1, 2], 
-             [1, 2, 1, 2, 0]],  
-    
-            [[1, 2, 0, 2, 1],
-             [2, 1, 2, 1, 2]],
-     
-            [[2, 0, 1, 2, 0],
-             [2, 0, 1, 1, 2]],
-            
-            [[1, 2, 1, 0, 1],
-             [0, 2, 1, 2, 0]],
-
-            [[0, 2, 1, 2, 2],
-             [1, 2, 1, 0, 2]],
+            [[0, 1, 2, 1, 2], [1, 2, 1, 2, 0]],
+            [[1, 2, 0, 2, 1], [2, 1, 2, 1, 2]],
+            [[2, 0, 1, 2, 0], [2, 0, 1, 1, 2]],
+            [[1, 2, 1, 0, 1], [0, 2, 1, 2, 0]],
+            [[0, 2, 1, 2, 2], [1, 2, 1, 0, 2]],
         ]
     )
 
@@ -57,9 +48,10 @@ def diabetes_130_fairlearn_sample_100():
 
 
 def test_sankey_plot(diabetes_130_fairlearn_sample_100, check_same_image):
+    hv.extension("matplotlib")
     edata = diabetes_130_fairlearn_sample_100.copy()
 
-    sankey = ep.pl.plot_sankey(edata, columns=["gender", "race"], backend="matplotlib")
+    sankey = ep.pl.plot_sankey(edata, columns=["gender", "race"])
     fig = hv.render(sankey, backend="matplotlib")
 
     check_same_image(
@@ -69,10 +61,30 @@ def test_sankey_plot(diabetes_130_fairlearn_sample_100, check_same_image):
     )
 
 
+def test_sankey_time_plot(ehr_3d_mini, check_same_image):
+    hv.extension("matplotlib")
+    edata = ehr_3d_mini
+    sankey_time = ep.pl.plot_sankey_time(
+        edata,
+        columns=["disease_flare"],
+        layer="layer_1",
+        state_labels={0: "no flare", 1: "mid flare", 2: "severe flare"},
+    )
+
+    fig = hv.render(sankey_time, backend="matplotlib")
+
+    check_same_image(
+        fig=fig,
+        base_path=f"{_TEST_IMAGE_PATH}/sankey_time",
+        tol=2e-1,
+    )
+
+
 def test_sankey_bokeh_plot(diabetes_130_fairlearn_sample_100):
+    hv.extension("bokeh")
     edata = diabetes_130_fairlearn_sample_100.copy()
 
-    sankey = ep.pl.plot_sankey(edata, columns=["gender", "race"], backend="bokeh")
+    sankey = ep.pl.plot_sankey(edata, columns=["gender", "race"])
 
     assert isinstance(sankey, hv.Sankey)
 
@@ -101,36 +113,15 @@ def test_sankey_bokeh_plot(diabetes_130_fairlearn_sample_100):
         assert target.startswith("race:")  # targets have the correct prefix
 
 
-def test_sankey_time_plot(ehr_3d_mini, check_same_image):
+def test_sankey_time_bokeh_plot(ehr_3d_mini):
+    hv.extension("bokeh")
     edata = ehr_3d_mini
-    sankey_time = ep.pl.plot_sankey_time(
+    sankey = ep.pl.plot_sankey_time(
         edata,
         columns=["disease_flare"],
         layer="layer_1",
-        state_labels={0: "no flare", 1: "mid flare", 2: "severe flare"},
-        backend="matplotlib",
+        state_labels={0: "no flare", 1: " mid flare", 2: "severe flare"},
     )
-
-    fig = hv.render(sankey_time, backend="matplotlib")
-
-    check_same_image(
-        fig=fig,
-        base_path=f"{_TEST_IMAGE_PATH}/sankey_time",
-        tol=2e-1,
-    )
-
-
-
-def test_sankey_time_bokeh_plot(ehr_3d_mini):
-    edata = ehr_3d_mini
-    sankey = ep.pl.plot_sankey_time(
-        edata, 
-        columns=["disease_flare"], 
-        layer="layer_1", 
-        state_labels={0: "no flare", 1: " mid flare", 2: "severe flare"}, 
-        backend="bokeh"
-    )
-
     assert isinstance(sankey, hv.Sankey)
 
     data = sankey.data

From c9e6b01d7da885f858942cba2b3bfd90b62b0bff Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=C3=96yk=C3=BC=20S=C3=BCoglu?=
 <oeykue.sueoglu@helmholtz-munich.de>
Date: Fri, 12 Dec 2025 09:35:05 +0100
Subject: [PATCH 09/12] fix

---
 tests/_scripts/sankey_expected.ipynb | 1629 --------------------------
 tests/plot/test_sankey.py            |   24 -
 2 files changed, 1653 deletions(-)
 delete mode 100644 tests/_scripts/sankey_expected.ipynb

diff --git a/tests/_scripts/sankey_expected.ipynb b/tests/_scripts/sankey_expected.ipynb
deleted file mode 100644
index a9e9f170b..000000000
--- a/tests/_scripts/sankey_expected.ipynb
+++ /dev/null
@@ -1,1629 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "code",
-   "execution_count": 1,
-   "id": "42a55492",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<script type=\"esms-options\">{\"shimMode\": true}</script><style>*[data-root-id],\n",
-       "*[data-root-id] > * {\n",
-       "  box-sizing: border-box;\n",
-       "  font-family: var(--jp-ui-font-family);\n",
-       "  font-size: var(--jp-ui-font-size1);\n",
-       "  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
-       "}\n",
-       "\n",
-       "/* Override VSCode background color */\n",
-       ".cell-output-ipywidget-background:has(\n",
-       "  > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
-       "),\n",
-       ".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
-       "  background-color: transparent !important;\n",
-       "}\n",
-       "</style>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/javascript": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  const force = true;\n  const py_version = '3.8.1'.replace('rc', '-rc.').replace('.dev', '-dev.');\n  const reloading = false;\n  const Bokeh = root.Bokeh;\n\n  // Set a timeout for this load but only if we are not already initializing\n  if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks;\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n    if (js_modules == null) js_modules = [];\n    if (js_exports == null) js_exports = {};\n\n    root._bokeh_onload_callbacks.push(callback);\n\n    if (root._bokeh_is_loading > 0) {\n      // Don't load bokeh if it is still initializing\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n      // There is nothing to load\n      run_callbacks();\n      return null;\n    }\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n    window._bokeh_on_load = on_load\n\n    function on_error(e) {\n      const src_el = e.srcElement\n      console.error(\"failed to load \" + (src_el.href || src_el.src));\n    }\n\n    const skip = [];\n    if (window.requirejs) {\n      window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n      root._bokeh_is_loading = css_urls.length + 0;\n    } else {\n      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n    }\n\n    const existing_stylesheets = []\n    const links = document.getElementsByTagName('link')\n    for (let i = 0; i < links.length; i++) {\n      const link = links[i]\n      if (link.href != null) {\n        existing_stylesheets.push(link.href)\n      }\n    }\n    for (let i = 0; i < css_urls.length; i++) {\n      const url = css_urls[i];\n      const escaped = encodeURI(url)\n      if (existing_stylesheets.indexOf(escaped) !== -1) {\n        on_load()\n        continue;\n      }\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }    var existing_scripts = []\n    const scripts = document.getElementsByTagName('script')\n    for (let i = 0; i < scripts.length; i++) {\n      var script = scripts[i]\n      if (script.src != null) {\n        existing_scripts.push(script.src)\n      }\n    }\n    for (let i = 0; i < js_urls.length; i++) {\n      const url = js_urls[i];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      const element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (let i = 0; i < js_modules.length; i++) {\n      const url = js_modules[i];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (const name in js_exports) {\n      const url = js_exports[name];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      var element = document.createElement('script');\n      element.onerror = on_error;\n      element.async = false;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      element.textContent = `\n      import ${name} from \"${url}\"\n      window.${name} = ${name}\n      window._bokeh_on_load()\n      `\n      document.head.appendChild(element);\n    }\n    if (!js_urls.length && !js_modules.length) {\n      on_load()\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  const js_urls = [\"https://cdn.holoviz.org/panel/1.8.3/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-3.8.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.8.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.8.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.8.1.min.js\", \"https://cdn.holoviz.org/panel/1.8.3/dist/panel.min.js\"];\n  const js_modules = [];\n  const js_exports = {};\n  const css_urls = [];\n  const inline_js = [    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n  ];\n\n  function run_inline_js() {\n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (let i = 0; i < inline_js.length; i++) {\n        try {\n          inline_js[i].call(root, root.Bokeh);\n        } catch(e) {\n          if (!reloading) {\n            throw e;\n          }\n        }\n      }\n      // Cache old bokeh versions\n      if (Bokeh != undefined && !reloading) {\n        var NewBokeh = root.Bokeh;\n        if (Bokeh.versions === undefined) {\n          Bokeh.versions = new Map();\n        }\n        if (NewBokeh.version !== Bokeh.version) {\n          Bokeh.versions.set(NewBokeh.version, NewBokeh)\n        }\n        root.Bokeh = Bokeh;\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    }\n    root._bokeh_is_initializing = false\n  }\n\n  function load_or_wait() {\n    // Implement a backoff loop that tries to ensure we do not load multiple\n    // versions of Bokeh and its dependencies at the same time.\n    // In recent versions we use the root._bokeh_is_initializing flag\n    // to determine whether there is an ongoing attempt to initialize\n    // bokeh, however for backward compatibility we also try to ensure\n    // that we do not start loading a newer (Panel>=1.0 and Bokeh>3) version\n    // before older versions are fully initialized.\n    if (root._bokeh_is_initializing && Date.now() > root._bokeh_timeout) {\n      // If the timeout and bokeh was not successfully loaded we reset\n      // everything and try loading again\n      root._bokeh_timeout = Date.now() + 5000;\n      root._bokeh_is_initializing = false;\n      root._bokeh_onload_callbacks = undefined;\n      root._bokeh_is_loading = 0\n      console.log(\"Bokeh: BokehJS was loaded multiple times but one version failed to initialize.\");\n      load_or_wait();\n    } else if (root._bokeh_is_initializing || (typeof root._bokeh_is_initializing === \"undefined\" && root._bokeh_onload_callbacks !== undefined)) {\n      setTimeout(load_or_wait, 100);\n    } else {\n      root._bokeh_is_initializing = true\n      root._bokeh_onload_callbacks = []\n      const bokeh_loaded = root.Bokeh != null && (root.Bokeh.version === py_version || (root.Bokeh.versions !== undefined && root.Bokeh.versions.has(py_version)));\n      if (!reloading && !bokeh_loaded) {\n        if (root.Bokeh) {\n          root.Bokeh = undefined;\n        }\n        console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n      }\n      load_libs(css_urls, js_urls, js_modules, js_exports, function() {\n        console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n        run_inline_js();\n      });\n    }\n  }\n  // Give older versions of the autoload script a head-start to ensure\n  // they initialize before we start loading newer version.\n  setTimeout(load_or_wait, 100)\n}(window));",
-      "application/vnd.holoviews_load.v0+json": ""
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/javascript": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n  window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n    function JupyterCommManager() {\n    }\n\n    JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n      if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        comm_manager.register_target(comm_id, function(comm) {\n          comm.on_msg(msg_handler);\n        });\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n          comm.onMsg = msg_handler;\n        });\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n          var messages = comm.messages[Symbol.asyncIterator]();\n          function processIteratorResult(result) {\n            var message = result.value;\n            var content = {data: message.data, comm_id};\n            var buffers = []\n            for (var buffer of message.buffers || []) {\n              buffers.push(new DataView(buffer))\n            }\n            var metadata = message.metadata || {};\n            var msg = {content, buffers, metadata}\n            msg_handler(msg);\n            return messages.next().then(processIteratorResult);\n          }\n          return messages.next().then(processIteratorResult);\n        })\n      }\n    }\n\n    JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n      if (comm_id in window.PyViz.comms) {\n        return window.PyViz.comms[comm_id];\n      } else if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        var comm = comm_manager.new_comm(comm_id, {}, {}, {}, comm_id);\n        if (msg_handler) {\n          comm.on_msg(msg_handler);\n        }\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        var comm = window.PyViz.kernels[plot_id].connectToComm(comm_id);\n        let retries = 0;\n        const open = () => {\n          if (comm.active) {\n            comm.open();\n          } else if (retries > 3) {\n            console.warn('Comm target never activated')\n          } else {\n            retries += 1\n            setTimeout(open, 500)\n          }\n        }\n        if (comm.active) {\n          comm.open();\n        } else {\n          setTimeout(open, 500)\n        }\n        if (msg_handler) {\n          comm.onMsg = msg_handler;\n        }\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        var comm_promise = google.colab.kernel.comms.open(comm_id)\n        comm_promise.then((comm) => {\n          window.PyViz.comms[comm_id] = comm;\n          if (msg_handler) {\n            var messages = comm.messages[Symbol.asyncIterator]();\n            function processIteratorResult(result) {\n              var message = result.value;\n              var content = {data: message.data};\n              var metadata = message.metadata || {comm_id};\n              var msg = {content, metadata}\n              msg_handler(msg);\n              return messages.next().then(processIteratorResult);\n            }\n            return messages.next().then(processIteratorResult);\n          }\n        })\n        var sendClosure = (data, metadata, buffers, disposeOnDone) => {\n          return comm_promise.then((comm) => {\n            comm.send(data, metadata, buffers, disposeOnDone);\n          });\n        };\n        var comm = {\n          send: sendClosure\n        };\n      }\n      window.PyViz.comms[comm_id] = comm;\n      return comm;\n    }\n    window.PyViz.comm_manager = new JupyterCommManager();\n    \n\n\nvar JS_MIME_TYPE = 'application/javascript';\nvar HTML_MIME_TYPE = 'text/html';\nvar EXEC_MIME_TYPE = 'application/vnd.holoviews_exec.v0+json';\nvar CLASS_NAME = 'output';\n\n/**\n * Render data to the DOM node\n */\nfunction render(props, node) {\n  var div = document.createElement(\"div\");\n  var script = document.createElement(\"script\");\n  node.appendChild(div);\n  node.appendChild(script);\n}\n\n/**\n * Handle when a new output is added\n */\nfunction handle_add_output(event, handle) {\n  var output_area = handle.output_area;\n  var output = handle.output;\n  if ((output.data == undefined) || (!output.data.hasOwnProperty(EXEC_MIME_TYPE))) {\n    return\n  }\n  var id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n  var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n  if (id !== undefined) {\n    var nchildren = toinsert.length;\n    var html_node = toinsert[nchildren-1].children[0];\n    html_node.innerHTML = output.data[HTML_MIME_TYPE];\n    var scripts = [];\n    var nodelist = html_node.querySelectorAll(\"script\");\n    for (var i in nodelist) {\n      if (nodelist.hasOwnProperty(i)) {\n        scripts.push(nodelist[i])\n      }\n    }\n\n    scripts.forEach( function (oldScript) {\n      var newScript = document.createElement(\"script\");\n      var attrs = [];\n      var nodemap = oldScript.attributes;\n      for (var j in nodemap) {\n        if (nodemap.hasOwnProperty(j)) {\n          attrs.push(nodemap[j])\n        }\n      }\n      attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n      newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n      oldScript.parentNode.replaceChild(newScript, oldScript);\n    });\n    if (JS_MIME_TYPE in output.data) {\n      toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n    }\n    output_area._hv_plot_id = id;\n    if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n      window.PyViz.plot_index[id] = Bokeh.index[id];\n    } else {\n      window.PyViz.plot_index[id] = null;\n    }\n  } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n    var bk_div = document.createElement(\"div\");\n    bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n    var script_attrs = bk_div.children[0].attributes;\n    for (var i = 0; i < script_attrs.length; i++) {\n      toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n    }\n    // store reference to server id on output_area\n    output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n  }\n}\n\n/**\n * Handle when an output is cleared or removed\n */\nfunction handle_clear_output(event, handle) {\n  var id = handle.cell.output_area._hv_plot_id;\n  var server_id = handle.cell.output_area._bokeh_server_id;\n  if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n  var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n  if (server_id !== null) {\n    comm.send({event_type: 'server_delete', 'id': server_id});\n    return;\n  } else if (comm !== null) {\n    comm.send({event_type: 'delete', 'id': id});\n  }\n  delete PyViz.plot_index[id];\n  if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n    var doc = window.Bokeh.index[id].model.document\n    doc.clear();\n    const i = window.Bokeh.documents.indexOf(doc);\n    if (i > -1) {\n      window.Bokeh.documents.splice(i, 1);\n    }\n  }\n}\n\n/**\n * Handle kernel restart event\n */\nfunction handle_kernel_cleanup(event, handle) {\n  delete PyViz.comms[\"hv-extension-comm\"];\n  window.PyViz.plot_index = {}\n}\n\n/**\n * Handle update_display_data messages\n */\nfunction handle_update_output(event, handle) {\n  handle_clear_output(event, {cell: {output_area: handle.output_area}})\n  handle_add_output(event, handle)\n}\n\nfunction register_renderer(events, OutputArea) {\n  function append_mime(data, metadata, element) {\n    // create a DOM node to render to\n    var toinsert = this.create_output_subarea(\n    metadata,\n    CLASS_NAME,\n    EXEC_MIME_TYPE\n    );\n    this.keyboard_manager.register_events(toinsert);\n    // Render to node\n    var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n    render(props, toinsert[0]);\n    element.append(toinsert);\n    return toinsert\n  }\n\n  events.on('output_added.OutputArea', handle_add_output);\n  events.on('output_updated.OutputArea', handle_update_output);\n  events.on('clear_output.CodeCell', handle_clear_output);\n  events.on('delete.Cell', handle_clear_output);\n  events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n\n  OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n    safe: true,\n    index: 0\n  });\n}\n\nif (window.Jupyter !== undefined) {\n  try {\n    var events = require('base/js/events');\n    var OutputArea = require('notebook/js/outputarea').OutputArea;\n    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n      register_renderer(events, OutputArea);\n    }\n  } catch(err) {\n  }\n}\n",
-      "application/vnd.holoviews_load.v0+json": ""
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/vnd.holoviews_exec.v0+json": "",
-      "text/html": [
-       "<div id='d292dc13-3464-42db-859f-422302252fd7'>\n",
-       "  <div id=\"fc647499-f484-4cbc-a5c0-f08bb72acbac\" data-root-id=\"d292dc13-3464-42db-859f-422302252fd7\" style=\"display: contents;\"></div>\n",
-       "</div>\n",
-       "<script type=\"application/javascript\">(function(root) {\n",
-       "  var docs_json = {\"e382699e-92a9-46e7-82de-53fa90130d81\":{\"version\":\"3.8.1\",\"title\":\"Bokeh 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-       "\n",
-       "<a href=\"https://bokeh.org\" target=\"_blank\" title=\"Bokeh 3.8.1\">\n",
-       "  <img src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACMAAAAjCAYAAAAe2bNZAAAABHNCSVQICAgIfAhkiAAAAAlwSFlzAAAK6wAACusBgosNWgAAABx0RVh0U29mdHdhcmUAQWRvYmUgRmlyZXdvcmtzIENTNui8sowAAAf9SURBVFiFvZh7cFTVHcc/59y7793sJiFAwkvAYDRqFWwdraLVlj61diRYsDjqCFbFKrYo0CltlSq1tLaC2GprGIriGwqjFu10OlrGv8RiK/IICYECSWBDkt3s695zTv9IAtlHeOn0O7Mzu797z+/3Ob/z+p0VfBq9doNFljuABwAXw2PcvGHt6bgwxhz7Ls4YZNVXxxANLENwE2D1W9PAGmAhszZ0/X9gll5yCbHoOirLzmaQs0F6F8QMZq1v/8xgNm7DYwwjgXJLYL4witQ16+sv/U9HdDmV4WrKw6B06cZC/RMrM4MZ7xz61DAbtzEXmAvUAX4pMOVecg9/MFFu3j3Gz7gQBLygS2RGumBkL0cubiFRsR3LzVBV1UMk3IrW73PT9C2lYOwhQB4ClhX1AuKpjLcV27oEjyUpNUJCg1CvcejykWTCXyQgzic2HIIBjg3pS6+uRLKAhumZvD4U+tq0jTrgkVKQQtLekfTtxIPAkhTNF6G7kZm7aPp6M9myKVQEoaYaIhEQYvD781DML/RfBGNZXAl4irJiwBa07e/y7cQnBaJghIX6ENl2GR/fGCBoz6cm5qeyEqQA5ZYA5x5eeiV0Qph4gjFAUSwAr6QllQgcxS/Jm25Cr2Tmpsk03XI9NfI31FTZBEOgVOk51adqDBNPCNPSRlkiDXbBEwOU2WxH+I7itQZ62g56OjM33suq1YsZHVtGZSUI2QdyYgkgOthQNIF7BIGDnRAJgJSgj69cUx1gB8PkOGwL4E1gPrM27gIg7NlGKLQApc7BmEnAxP5g/rw4YqBrCDB5xHkw5rdR/1qTrN/hKNo6YUwVDNpFsnjYS8RbidBPcPXFP6R6yfExuOXmN4A3jv1+8ZUwgY9D2OWjUZE6lO88jDwHI8ZixGiMKSeYTBamCoDk6kDAb6y1OcH1a6KpD/fZesoFw5FlIXAVCIiH4PxrV+p2npVDToTBmtjY8t1swh2V61E9KqWiyuPEjM8dbfxuvfa49Zayf9R136Wr8mBSf/T7bNteA8zwaGEUbFpckWwq95n59dUIywKl2fbOIS5e8bWSu0tJ1a5redAYfqkdjesodFajcgaVNWhXo1C9SrkN3Usmv3UMJrc6/DDwkwEntkEJLe67tSLhvyzK8rHDQWleve5CGk4VZEB1r+5bg2E2si+Y0QatDK6jUVkX5eg2YYlp++ZM+rfMNYamAj8Y7MAVWFqaR1f/t2xzU4IHjybBtthzuiAASqv7jTF7jOqDMAakFHgDNsFyP+FhwZHBmH9F7cutIYkQCylYYv1AZSqsn1/+bX51OMMjPSl2nAnM7hnjOx2v53YgNWAzHM9Q/9l0lQWPSCBSyokAtOBC1Rj+w/1Xs+STDp4/E5g7Rs2zm2+oeVd7PUuHKDf6A4r5EsPT5K3gfCnBXNUYnvGzb+KcCczYYWOnLpy4eOXuG2oec0PBN8XQQAnpvS35AvAykr56rWhPBiV4MvtceGLxk5Mr6A1O8IfK7rl7xJ0r9kyumuP4fa0lMqTBLJIAJqEf1J3qE92lMBndlyfRD2YBghHC4hlny7ASqCeWo5zaoDdIWfnIefNGTb9fC73QDfhyBUCNOxrGPSUBfPem9us253YTV+3mcBbdkUYfzmHiLqZbYdIGHHON2ZlemXouaJUOO6TqtdHEQuXYY8Yt+EbDgmlS6RdzkaDTv2P9A3gICiq93sWhb5mc5wVhuU3Y7m5hOc3So7qFT3SLgOXHb/cyOfMn7xROegoC/PTcn3v8gbKPgDopJFk3R/uBPWQiwQ+2/GJevRMObLUzqe/saJjQUQTTftEVMW9tWxPgAocwcj9abNcZe7s+6t2R2xXZG7zyYLp8Q1PiRBBHym5bYuXi8Qt+/LvGu9f/5YDAxABsaRNPH6Xr4D4Sk87a897SOy9v/fKwjoF2eQel95yDESGEF6gEMwKhLwKus3wOVjTtes7qzgLdXTMnNCNoEpbcrtNuq6N7Xh/+eqcbj94xQkp7mdKpW5XbtbR8Z26kgMCAf2UU5YEovRUVRHbu2b3vK1UdDFkDCyMRQxbpdv8nhKAGIa7QaQedzT07fFPny53R738JoVYBdVrnsNx9XZ9v33UeGO+AA2MMUkgqQ5UcdDLZSFeVgONnXeHqSAC5Ew1BXwko0D1Zct3dT1duOjS3MzZnEUJtBuoQAq3SGOLR4ekjn9NC5nVOaYXf9lETrUkmOJy3pOz8OKIb2A1cWhJCCEzOxU2mUPror+2/L3yyM3pkM7jTjr1nBOgkGeyQ7erxpdJsMAS9wb2F9rzMxNY1K2PMU0WtZV82VU8Wp6vbKJVo9Lx/+4cydORdxCCQ/kDGTZCWsRpLu7VD7bfKqL8V2orKTp/PtzaXy42jr6TwAuisi+7JolUG4wY+8vyrISCMtRrLKWpvjAOqx/QGhp0rjRo5xD3x98CWQuOQN8qumRMmI7jKZPUEpzNVZsj4Zbaq1to5tZZsKIydLWojhIXrJnES79EaOzv3du2NytKuxzJKAA6wF8xqEE8s2jo/1wd/khslQGxd81Zg62Bbp31XBH+iETt7Y3ELA0iU6iGDlQ5mexe0VEx4a3x8V1AaYwFJgTiwaOsDmeK2J8nMUOqsnB1A+dcA04ucCYt0urkjmflk9iT2v30q/gZn5rQPvor4n9Ou634PeBzoznes/iot/7WnClKoM/+zCIjH5kwT8ChQjTHPIPTjFV3PpU/Hx+DM/A9U3IXI4SPCYAAAAABJRU5ErkJggg=='\n",
-       "       style='height:15px; border-radius:12px; display: inline-block; float: left'>\n",
-       "  </img>\n",
-       "</a>\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "<span style=\"float: left; margin-left: 5px; line-height: 15px; cursor: pointer; opacity: 0.7;\"\n",
-       "      onmouseover=\"this.style.opacity='1'\"\n",
-       "      onmouseout=\"this.style.opacity='0.7'\"\n",
-       "      title=\"Extension loaded. This cell output contains code that enables plot interactivity, it should not be removed.\">ⓘ</span>\n",
-       "</div>\n",
-       "\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "import ehrdata as ed\n",
-    "import holoviews as hv\n",
-    "import matplotlib.pyplot as plt\n",
-    "import numpy as np\n",
-    "import pandas as pd\n",
-    "\n",
-    "import ehrapy as ep"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "8104f266",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "current_notebook_dir = %pwd\n",
-    "\n",
-    "_TEST_IMAGE_PATH = f\"{current_notebook_dir}/../plot/_images\""
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 3,
-   "id": "e242cbd4",
-   "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "\u001b[93m!\u001b[0m File ehrapy_data\\diabetes_130_fairlearn.csv already exists! Using already downloaded dataset...\n"
-     ]
-    }
-   ],
-   "source": [
-    "edata = ed.dt.diabetes_130_fairlearn(columns_obs_only=[\"gender\", \"race\"])[:100]"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 4,
-   "id": "3351e8d3",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<script type=\"esms-options\">{\"shimMode\": true}</script><style>*[data-root-id],\n",
-       "*[data-root-id] > * {\n",
-       "  box-sizing: border-box;\n",
-       "  font-family: var(--jp-ui-font-family);\n",
-       "  font-size: var(--jp-ui-font-size1);\n",
-       "  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
-       "}\n",
-       "\n",
-       "/* Override VSCode background color */\n",
-       ".cell-output-ipywidget-background:has(\n",
-       "  > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
-       "),\n",
-       ".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
-       "  background-color: transparent !important;\n",
-       "}\n",
-       "</style>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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-       "roTBs2RqAAAAAElFTkSuQmCC' style='height:25px; border-radius:12px; display: inline-block; float: left; vertical-align: middle'></img>\n",
-       "</a>\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "<a href=\"https://matplotlib.org\" target=\"_blank\" title=\"Matplotlib 3.10.5\">\n",
-       "  <img src='data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\n",
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-       "5nK5CQAQMtXznCRJePpEbwOAZhzHX4ix/wHzzC/tu64gcwAAAABJRU5ErkJggg=='\n",
-       "       style='height:15px; border-radius:12px; display: inline-block; float: left'></img>\n",
-       "</a>\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "<span style=\"float: left; margin-left: 5px; line-height: 15px; cursor: pointer; opacity: 0.7;\"\n",
-       "      onmouseover=\"this.style.opacity='1'\"\n",
-       "      onmouseout=\"this.style.opacity='0.7'\"\n",
-       "      title=\"Extension loaded. This cell output contains code that enables plot interactivity, it should not be removed.\">ⓘ</span>\n",
-       "</div>\n",
-       "\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "sankey = ep.pl.plot_sankey(edata, columns=[\"gender\", \"race\"], backend=\"matplotlib\", show=False)\n",
-    "fig = hv.render(sankey, backend=\"matplotlib\")\n",
-    "\n",
-    "fig.savefig(f\"{_TEST_IMAGE_PATH}/sankey_expected.png\", dpi=80)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 5,
-   "id": "4b735603",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
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+22Yssttyy++MUvFn/+85+Lyy67rHjNa17T0nu+733vKx72sIcVK1asKH70ox+NPrdy5criZS97WXH66acXX//614ubbrqpWLRoUbHddtsVn/70p4sFCxYUr3zlK1PO3uGHH14cd9xxxTOf+cziBz/4QXHiiSem6+GHP/zh4hnPeEb6LHvuuWca7N+5556bBEsrsJ0lS5YUO+64YxdHVwIFjYjIEIWB5WKFP/YQK1QJK4uV3Kuy4YYbDv2dVRHpDHLmMP7h4IMPTtcTwr/OOeec4pRTTilOPfXU4pJLLkmCBqFz5plnJjHx4he/uDj77LOL888/P823KhaAAiDf+ta30rYvuuiiYsqUKeuImd133z0Jmsc85jHFF77wheJpT3taceeddyYhdPLJJxcHHnhgEi0vf/nLi7lz5xbXXnttChFDJC1cuLDYeuut0/ssXbq0+OxnP5vEVjuCBoHE9qU3KGhERGoM4oM7iZFEj2AJsRLhYFEBLMBgCKHCnzNGhGJFRMaLffbZZ3T+/e9/fxIYXJd23XXXYtmyZcW2226brkPAteivf/1rEggIHq5riJkq8Apz/QtYl+1wHdxjjz3SstmzZyehgqBBGB111FFJzASx3qxZs4q77rqruPHGG0f3F3Fy8803F0984hOLn//856NVEi+88MLiCU94QloHDwvL4n1yXvrSlybxg0enLHS++c1vFv/93//d9bGV/0VBIyLS596VvIcKwgWxkntXcsK7glBBsFimWKQ74jfVbNrKOuXtjfV8eVmj3zDLy/tQNfJtNdufVj5nu8QNk+XLl6dwsEsvvTSJAkLOCCkjzAsxwrWKGy4777xzcdhhhxVHHHFEel30jiqz0047FZdffnl6Dfzxj39MIuHKK698UJ8peNWrXlXccsstKcTtX/7lX0aPX77eDjvskMTUQQcdlLb9pje9KQkucl0IdyMHEIHy1a9+tfL1OXy+Kvg8iLZHP/rRHR1PeTAKGhGRSS5fnAsWPCrcJYzcFZ4vJ9mHZ4XpxhtvrFiRgaKRQd7ISK9alv8myvO50VkOs2w0z3rR0yifH2vEupFbxm82tsd8+bdN6CcDA50pNzRixGOey6csD8ET26u6JlR97kbzVdthvpGwaJVp06ala9ahhx5a7LXXXmkZx+eEE05IoWgbbbRRcdJJJxWve93rkiflrLPOSvtNiBgNbss5NJtvvnkSPYSHwSte8Ypis802a/j+fIZPfvKTxZFHHpn2pQoEEdvh2vvc5z43eV7gjjvuKJ70pCel/f+v//qvJLo65ac//Wk6BtI71hvpVG6LiEhTMDjKuSvhXYnKYFWJ9iFWmIYxJDLZxPnJORsGeD5f9RiqCkWUhUUuTvI+Q/FbyEe+jPn89xLz7YiNsZbF/nbaEJb5eBzXgbwHE8/l7xHHJq4NuSCqEkmd7GOncKOFMKrPXrew6Xqvnju7Y2+OSCfooRER6VE4GAIlFyzlfitRsjQMLxPtZbzJRQbTqvk8nKlsVOfbiRLccf7GePjDHz46LY8qQRKjXM47FyL9XhGwqshGs4qA5aqAMeUY4XnwpoVIdyhoRESaJNvngiWMFgaChTurYXyVK4NhyNlvRbohFx6NxEijMtm5UAlxQX4CU/KqYmBMl8VHldcj93wMw+8eYRLipJWKgCFQvFEhMjkoaESkGHbvCndby+FgPM7vXJtsL70SJfmAsvGbi5EQHlRuCgHC4NxjmntGyh4TQxYbg5clwj6Z0quEClX8/kOw5DlrVgQU6W8UNCIy0LkreSnj8KxUeVfKhovJ9lImkrYjYTsXJlWekhDBIUq4cx9ChGmIlHKYFstCOHsOdg7fUQgWBoKFxG5ES15sg+8vBKCCRaSeKGhEpFZgJEYybQiWyF2JGHaWQW6wMB9Gi94VyatK5QIlDycql2PlcYiRECQx8jCuECUhUDzPJiZMjGsAFQJvv/32NLgelHsvhQfLvBWRwUJBIyJ951kpi5Xcs1IWK3nuStzVNndluMO7yqVvy7kmIWY4XxAmlIoNYcJ8hHXlIoWhx2Ty4TuNnBY8LnRpJ1wsPC7haUW06GUVGR4UNCIyoZWBcsESIiWSbVmeG57hWVGsDC/l/hwxouJWvh5EvkmIkxArIVDyafQEkf7Nc4swMUQLHeURMvl3Ht4wPS4iw42CRkS6FiqEezBCrETcegiVcoJ9XsI4z1vZdNNNNUqGTKhEY8AY5VyUyG9AlCBmESjceScfJTwpuUfF/Id6wrnA9QLxgnBZsmRJmudciHAxvl+9LiJShYJGRB4EBkSIlBjRbyEqgDFYViVU8sZ4DIxQDc3hoUqolD0qnCfcXUeYMDBUGQiXPHE+KnnJYMGNkPC8IF4IHYsu9FHdTW+siLSK/xIiQwJGZd61OjwqCJPwpEQZ47wCWCOPikJl+GjFqxICNxcpGKZR4SuGQmV44JyI0sgIFwQMoWOR88J5wPmAmJXe/EbznkWxLMIyyw1Tx5rmRTL4vYv0I+uN5Ge2iNQG/lhCnIRAYRoiJRcoLMMI5Q8JARI/+7I3Je9i7Z3R4YPzoSxWynkqIWQZCBVGeFVicHfd82d44Tzh+kOlsUWLFhULFy5M1yeISnFWf2tedS+vvFcuahFCsOr1eTXH6EcU1fbiuh7TuNY3Wx7L8rHPvo8t7rrzjqafZ+q0acUdK1aM6zETyVHQiPSZOCHsIp/mnepDnGAcYHiGsZk3gQujMxcnUZ1JA2J4Cc9KLljKnpUQK+FVycVKTDGMRMpwbULALF68uLj11lvTY+D6w3kzbN64qop75Z5F+W8vcsXyGwNR3IL5vDBKPi0v82aUDCsKGpEeG4y5IMlHnjTPn308Zt24E57fecvvuJXFSX7XTKRcBYzzEBqFgYVYQbzkhhNGkeeUtALXLwQM4WMIGELKgPMnBMygnkshQPKbAxGSm68TYXTlnkVVZcG5UWDVPZHOUdCI/IP4gwpRwsjnQ6iEKMnDvELAQFW38PiZhQu/kUtfpFPvCgZShIFRLS4S7PPGj55j0s31cfny5ckDs2DBgtTAclBDyPLfGyP3qgCP4/cWNwjy31t4WBQoIhOHgkYGRoTEnemqx7n4iGnZk1JVMrYcyhXeknLccf5YpJu7vY28K2E8IVYiyT4XLBpP0mu4Vt52223FLbfckkbkc4R3oc7Xu/Bqxo2r3MPCc/zepk6dOnpzIIpa5CFgItI/KGhkQkNhIqa4nHich8qUQ7UaLau6c1YO2cqnVcmPVUmPIuPxG8jP+bJg4e527l2J3JU8RMVzU8YbzkU8L4SRzZs3L3lkAOO9jkZ83CyI/4y8yAXP8ZmmTJlSTJs2LYmXvMeR1RtF6oWCZoCJi3k+qpZVVVXJH+dio8oLEt6N/PlcwJQ9Ho0qtOTTssjIH5dFichkUiXSy+FgGE7hXWFE9/rwsgxbwrT0D5y3NLKkEtn8+fNTOC3ggamTkI4mv3lOIsv4HPzmECwIF36HUaXP353I4FAbQcMFKi60ULXbjT5Ko3Wr7uR3sgyDJl8+1qgSFtF4LhcV+bKxRlmI5KUeg6r5Zses/Fy5dGPVqPJ21OUPUaSbcLDcuxJCJcJUvNsr/QRGP16Ym266KeXExLW+LlXsoipkOW+R398WW2xRbL755snzwuM6iTIRqbmg2Wza1OKOO/83wbAZG2+0YXHOJz/V1XvlF7Yqg73TZWHYtLq8vD9VAqCVafl1VfMi0nqyfblSEXd4y4IFwy9ES91zCWS4RMyNN944KmKiTHC/Cu74fYbXJf5L+c1tttlmxZZbbpm8LpHnUreQOBHpHX3hb0XMjFx4/JjrrffUM5IxISLSTv5WCJZGpYwxjiIcLA8FG8b+GTKYnhgaXIaIQaD3o4jBG0ohAjwvIV7Y12233XYdrwu/S28iiEiO/9QiMnB9IMIjSrhJ3nfFUsYy6NRFxETOCwImryBJyNjMmTOTgMH7wm9YRGQsFDQi0teV8Ro1rYtQsFywlLtr95MBJzJeIOwJIyOcrF9FDL9jxAv7Gt4XvC1bb711sdVWWyXxwm/YGwwi0gkKGhGZMKoq55XzvfImkYiVECx5D4g6lpAV6SX8Tm6//fbkibn55pvT74nfRL+IGH7rFPKJQhoIrOnTpyfvCyGeVB3jpoSISC9Q0IhI10RlvTwEDIMrqt5F1Twek58S4V95RbAQKoiZfjDIRPqRu+++u1iwYEFx7bXXFvfcc89oHthkC/zIfyHkLfp74XmZPXt2St5HwOh9EZHxQkEjIpXkZcTzUuJQ9qiEURXVhsK7EgIlxAp3aTVqRNqDXBNCyRAx9IwBfk/83iYLfvchYMLLSv4LIWRRfcwbEyIyUShoRIaIvK9RHvoV3pMc1iEkJHJS8i7aIVJiqlAR6S38JhEv5MXMmzcv/R7pETNZeSaRxE8YWbw/oWMIGELJEDBWBBSRycKrj0iNiVCu3IMS06rclEimR6BgGCFSEChMESfl4R1WkYllzZo1KSfmmmuuSfP8Bvm9TkZIGdcLBEw0sOQ6sfvuu4/mwdShCaeIDAcKGpE+IQRHLkzy0UigYFREEn3uTcFzgngJccI8Q5Ei0p/emOuuu66YP3/+pIaUkQeHkIpQUrwv9IGZMWNG8tBOtie2qnl11bSX82O9d6uP29n2WMu7XbfT1/P9kw/l/4j0GwoakXEM66oaUP4zCHFCyAbiA69J5J1E0nwuSvLhH4tIb4jf4XiO/H2iZwwemUjwD88onhFGrF/ex/zxWMurtpG/JioOAp6gKIPOdYdrFvtHNbVGn6PZ47GWN5qOJVCqiAIknYiu8ms63c5Y288/Q6vLmu1rq+uNtW6rcD4cc8wxxV133dV0PUTPHXfc0fX7ibSKgkakiackH/my+KNo9IcRwqScFB+PESJ4VnJhwmPFifTrb6Fq2mh+rGXN1s1zvHKPZf78WL/P8vYb7W/V4yD/bTczlFs1LnMI4Vq9enUSMbw/IqLKA9vIuB3L0G7FEI9jClx7cq8ur0fgrFq1quH2ysuaPc4/WyvbGuszTLaXaJjhnEDM/PrXv2663uMf//gJ2ycRUNDIQNDMUCpPy4ZD1Xb4g49QrjxkK0RJPI9wifl8+Ic73FSdi83Oy1aXladVuVNVIYtVIYz5e5QFQ27kt2qwVhndjQz8qrvvVdsea9rOuvG7zxPXm22v1/BZETHctaY6GExknlp8z+ElRsAQ0oYXxmR+qTM/+tGPive+973pxsA+++xTfOADH0jzn/3sZ4tXv/rVaZ1DDjmk+MlPftLTc/3cc88tPvOZz6QQzVe96lXFG9/4xp5tW9rHq5hMGLkR0+odU2gmQGJ7DC5UMUJY5B6Q3DNSXjd/bMWuiSe+61bv8LeyrNG0HeO/mRBoJhDyczefNiP3AjQLs6kSDmWjveq9Gz3HiH5B5fVa3XdpDOcQd7TvvPPOdH5wrCfqpkdZxCBeEDH90Lem14zlHWv2fCuetXbCtToN7epFSFin2yvfwKiaZxpivFPiN9AraC576qmnFj/84Q+TSD/99NOLT33qU8XRRx+9jqAZj/18yUteUrziFa9IvzGElIJmclHQDBn5hakcZlFeVjXybTS6u9nsosgFgj/SKkFR9nIgPlg31s9fV95GhGzUkXaOfyujLBBbfT5fXnXHvlE4ULMwoLE8D/l80KoxPZYHIH++fB52KgKqno87fgqBwaGRMdfOMvJjVq5cmRphAudJGEjRz6m8jWb7Mdbz+fkWIoZlXEejJ1SIGDxFrfy28t9Q1fxY6zXb73ZD9arEfqN9bzbf6rLyfLPHjcLr2tlGmbguxrW26jrdLOyy6vpbdd4224decfHFFxcf/OAH0/wb3vCGJD6uuOKKtF9f+tKXim222aa44IILijPOOCOJ7ne/+93F4x73uCRGbrvtttTX6Itf/GLx5z//ubjsssuK17zmNaPb/t73vle8/OUvT2IG3vKWtxTPe97zilmzZhVXXXVV8syceOKJ6bnjjjuuuOSSS5LYYRu//e1v0zJCQF/72tcmLwvr8970feI9mxFV/vit77rrruN4BGUgBU0v76Q0u/PZ6IffynqNLhzNXle1fqMLX9U6Y93Fzfcp7sjG4E8u5kMc5MtDPJSX5dtgmyEqysvzx432qWqafwYuOFw0qtbJDeJ2DPvyelA1n2+/lW22s275czb6Y2kWY97sj77R8kbnZaP3bCesp9G0HPLTLIxI+ouq32Ur03bWzadlxhKK7VwbWxG98fqyB6u8LL/GxXLCTwgrIz8G8IbkHrB838YS061O2XeukSGU6AlDaWUaXeKZrvodVr1/K968Tva/FTEx1nSs56oeTzbxvcTgPyymjCj8wDmD5yNG/NdVfZ7y7yv+n5udp+XvvdG2WyHyqtqFz4SQgYMPPjj9LggBO+ecc4pTTjkleVkQG1GI4swzzywOP/zw4sUvfnFx9tlnF+eff36a33vvvdfZ7uLFi4s999xz9DHCnffitSxHTAHbf9nLXlacdtppxVOf+tQkaN71rncV3/72t1MBDJa99KUvTes+//nPbzkH6D3veU/xyU9+sjj22GM7Oi4yxIKG2vxVtPvjbPan2GxZq3doGj3f6E5OO38W8UfcqVGZv3+5wk35s7Vz961q/VboVIDGslaNnWbzYz1u9XVVhkMr2+m3P2LpnmY3OcYy+ttZ1oowLP82m/1Wq8RuIyM+vylSXlYe8Xy+bnm+av1mxlkrBlwsg6rn8ufL863CNfSWW24prr766mSQYiBttdVW4/67DqOY95k9e3ax0047pTvTGHUy/kIlBAnfOVO8cYwo+MCy8n9UvD6Wx28gzv/I3Ry0/wRCsoL3v//9xUUXXZSOIZ4NSpZTGhwxAxyHv/71r8kbg+DhOCJmqkC4400JWLdRf6Q99thjneI7f/rTn5LwidA19gP23XffdV6Hp+dNb3pTKl3+la98ZZ3nEEV4eQ488MDkUdp88807PEIydIJGt57I4DKWp7MTo7/Rc62K1XZEevk9momARiM37Ks8olXLckO+/F6NnmtnOmjGVa/AkKWkcQgZwrsQM+N5vBBP3NHnLjYG4KMf/ehiu+22S2Fl0j38dvkuESQhSkKkMGVZ3qennHMRYdKMfujb0y+EiFi+fHnymlx66aXFhRdemELOCClbsGBBOtaIcY7lzjvvXBx22GHFEUcckV4XzV3LPPOZz0zrkM9C2NmHPvSh4l/+5V9aumn5mMc8Jnl+eB3bDyFUjibJPT05nCeRm4vHiXmZPGonaEQGmaq74+0u6/a5fDqWB7JMI29eq56AWLeRcR5GfDNxUL7T36kY6EYcKAQGG4zaa6+9Ng0ERiTbjxf8PjCi8aRz7j7qUY9Kg5Ayz7HOm4eGJyVKETMQLZF/BDGf53MqVDqHcEiO36GHHlrstddeaRnXyxNOOCGFoiEuTjrppOJ1r3tdcdRRRxVnnXVWOv9J9kcwlHNoaPzKa5/xjGek7SBS3va2t6XnyIVB3Lz1rW+t3JeTTz65eO5zn5u2v9lmmxX/8z//09ZnYZ8QOnhKyePxpsLkst5IO7FB47UTGDsXHj/2ek89I8U7TiS9PDztbqudO8LdrNMsxryd17S6rJvXt/J4rLsy+fJ8/arXNtpO2QDvNmyu/D6thtlUzbdqhFeFBFWF/bTy3q0+12x/8yHSj2AAEwpz3XXXpd8txtd4VguLkLIw3LhrTYhNo5Aa+SfccUeo8J0xqDKHYGEZd9bz6z7kRWbKd+jln3D8yDVppQ9NH5iXMkQMTA5NtzQzett53VjhK+X5ZsvKxl3V8ipDsNGy8nNV6+bL87jzmObrtBrnXt6H/M8if5+qfanaz6r1y/s61udtZb7V4zTWeq1uT2NepH+NOITM9ddfn36j41n2GI9ANNxEMHHHmfyCqOIkDxZ9fD94VhAthDRRlCFyi8rJ84zxDgsUkYmndoJm7ty5La/bbWJ6fsFrx1vRifeh0Xyr6zUKJWoksJq9XzPiD6LRZ2mURNzIA9AoHCgf+bKo5lLeTrt5CYoHERkLyi5TKvamm25K1wtCSsbr7n2e4E9ODAn+hpT9E7wqiBbESy5cwtsS/z1R9l/R0h6thirnJfZF+onaCRpdwfWgWUUn4pdbrfpUNR+EKAnhVvXnVRZ3+XaqxFM+8h43/EHGNOZbFWH58A9WpP/BYCbRf/78+eMqZLgW4Y2JPByqKyFmhrlKWRwTwsMQLPQhWbFixdAJl/ivyvvQNGpCDWXvfyc3VhtFWeSPp06dmsZYZY1ZR2QiqZ2gkXpQFVLXT5SFUggt4q7zZY1Gs5DAfPv5Y0YInVwojdVgtNxctNxotOy9EpHOwICmRCslmPktjZexzLUm+tRQbpncGErCDtvvl2si+S2IF0QL4gXPC8cnjPJossyo4/EJ4dFoVN2My/N6SISP/4L4r+BYlP8vyjfjyo8b5UV2Eu7M70Sk31DQyFAyGYIrF1HxZxZ9CqqacIZrv2pf8ztw+ZQ/rPxPLubjDzAMA0buhcpH2TtVRyNCpB0wqOlJQelYzvnxEDJ5pTJ+f1R4olLZsOTG8PkJGcvFC9O8B1r0YCFHqd8J70k+onRzvk75czHFG4cXjhGCJa7R+bzXXpHWUdCITBC5MBmv8JV8RLO3XCzl87EvVYIpj5Mu3xWMadTfjz/ksqepPG+4qPQbGNiElt14443p/KT0cq+NSH5LeCH4zZETs9tuu6Xml+NZHa0fQKhwJx+PC40PaVoY4VMQ145+FC98Z+wrHvsQKvm1Mj4DggRByiAskWlZrNTVsyRSNxQ0IgPCeBQ6yIUQf+6IpBBF+bT8/vkff15lKL8DGYM//Rhlz1LZ2zToRqBMDHhK/vKXv6SqmeOVIxNhZWwfT8wuu+wy0HkFHFM8LgiXxYsXj4YlcX2IGyD98vsN7wrfEYP5ck4m5wS9SfDW5UKFzxFThYpI/6CgEZGGlMtid0rc0Yw7n9F1O48lz4s1VL0+QupyMRSCKAyMXBRV5SRFDLkMJwhyRAxihvNpPIRMeEY53wgr23HHHZMxPEhw7KgAh2hZsmRJEjCRE8Tvi9/lZDefzPMiI6wtv9HCtQKPHCJzypQpSbTgLWJwPfE6IVIvFDQiMu6EcRBJqt2KIgwUytzmYiimzSresbwcLheCiJHHsVcNjZx6glF7ww03FFdeeWU6d3rdEDPyY3gftn3AAQek3jGD0gCTz0e5ZLwvt956axIxIRIQhPyGJqvaGPvGcQ/hEgI1BOvmm2+eREt4WhAsCExudojI4OAvWkSGShTlgoi7zLmXKN6nqupQueJSWQwxmokhc4gmHryB9JC54oorkuckDNpeV+ni3CE/Zo899ihmzpw5EN81Ag0BQ/4LIobfC583Km9NdO5LM+GCp2WrrbZK4oX5EC/9EuImIuOPgkZEhoZoytqJoZPnExFSFN3ccy9RuQRq7lWK8Lc8ZygqHoXHqJkY0jvUOhx3DPE//OEPybOA8U1Y0Xgk+m+zzTYp0Z98izp/RwiF22+/PXlfKFvNcQPOPcQ6ImEihSgCin2COK6IFQQjxzoXLoMgIEWkOxQ0IiLjnE+UiyE8Bdz9biSGxsodysUQhiaCqJlnaNj6E5GYftlll6WywByjXgqZyP/ieO60004p0X8iDf1ewnkXjSspV81xCyYyhCwXL3nvGUQLXpcQLwoXEWmGgkZEpM+LK+RVmTD+6GSf9zNqljcEESZULqSQ98GoKqIQJbfrIIjwmNFLhhAzPHC9LMGcCxlEzK677tqX5YbHgnNn6dKlyQPD4HziHJmIJP44h0O8xG+B84twPcTLtGnTkgDl2NbhnBOR/kFBIyLS52DcdZrEnHuH8AxFzkcj71DcJQ8xBNGHqJGXqKrUdj4dzwatGMdULqOfTK8rl0XpZba3++67FzvvvHPtKpZRTZAwsnnz5iUxEx4/Psd4fhbeB/GCRzLgfEG4TJ8+fVS8sA+KFxHpFgWNiMgA0wvvUCu5Q/FeVa+Hchf08AzlDQjDI1TVmLUsjHhvjHTCyzCce5kEHkKG7VF6ee7cuWkf6wDHhfAxSinffPPNo7kwHMvx9MJEOCXfBeca3zuChR48CBhCxxQvIjJeKGhERGRcexHlZbVzUZQvb1ZyO7YBCJvoQo93JgQS3qco+BBFFBpNy/MB22M7vMfee++desjUQchwPMiFIYyMfJgIJYtk/vFouEv4GAImmlJyPAkdmzVrVprigRmUstUi0v8oaEREZEKqy/WqEhdhVLHN6Paeh8nFdCxDPsKvAGHF9rbccsvkTcDLcfnll6/jVQovESOfr3o8nmF2wGcmhAwv1fz589P+R0Wy8Qgl4/0Qo1HenPeZM2dOqjoW5ZJN2heRyUJBIyIifQ3Cg0IIiIxIYu+FWIhCC2wLj0KEZOH9yUPtcrHULLwu9jWmGPghdMrhdOXQuhi5IOL1+ZRtsm8LFy5MAyIfptfFGyLEMBpo4qnabrvtitmzZycBY+K+iPQTChoREelbCE/DE4FhjdHeCy9ANGnEIMcbg5jptXch70GUV6mrEkr5CCIcLpLrOQ6Ew0VoXt6bKBdb+cjD6qqWl59n//IQMoQLfXaYIvZCXCF02KdYLx/lZYoeEZkIFDQiItJ3RHgZVdmiD0+vhAxMnTo1jU6rx41FGPKdhtohYAitI6k/RAxekkbCKxdDuZcoQsTK6+RCK8BDFH2NON7sA4UFGFWfLd9eo/3IBU6VAGo2QkC1sl6VQGsk6DoZ8bmbLWv2OD9uijyR3qOgERGRvgFDO8LLMPwwrrs1ADGswztCkjweh/ESMt2A12PlypVphBBp1SuVH6Nm4XAImNh29J8hfKyZWOqGXFzlXqi8Sl4596nRsmbTdo9FPJdX6Ws23+rnHGtZeb/GEj5VIqhqvtl67QipsdZBPD7xiU9MOVMi/UT/XdFFRGQowRtDeBlGdy/Cy3IhQ1lnhEwvPD29hM+KJ+auu+5KggYit6YXIBp4jzCu8cAg6hAxEyHq9Ep0Ln7aFUmQe+Q63ZdmEPa4zdZbF3etXNl0valTpxR33HFnW9sW6QYFjYiITCpRsSt6v/RCdLBNjDsMeMoI91P5ZYxIPisihinwuXvljQoRA4hCBAyCjmNhJbLJp+o7rovgo1Q3YuYXn/540/We9NpjJmyfREBBIyIikwLGN0b98uXL03wvDHqMecQM25oxY0byRPQLJNOTE8NgP3sZUpeHkrFNmlry2SmvLCIy6ChoRERkUox7vDKEWfUivCyEDNuhM/14NJTsJqSMvKAoSNCLkLKyiEG4kNcQSf0iIsOEgkZERCYMDHA8MnhmelG9LK9cRvnl8SjB3Klg4zPijYFehNI1EjGEk/WicamISF1R0IiIyISApwKvDAZ5t6FWuXFPpS7yZCa7chn7wmek+WX0uenl58xFzEQl9YuI1AGvhiIiMq5g3C9btixVMcMI79ZTgYHPwLhHyEx2nkhKlL7rrlRuuRcJ/ooYEZH28MooIiLjBrkjhJgBQqYbb0XkyWDUk/CPZ2ayvTF8vii33K03Jj4fUJUtEvsVMSIizfEqKSIiPQcj/7bbbkvei26T/vN+MptttlkxderUScuTYT/wxiBk2B/2oxshk/eJwbPD56OggYn9IiKto6AREZGegWEeXplujf0QEBj8kSczWYY+Sf58Lrwy0I1Iy0PKODYIGELKJjt0TkSkrihoRESkJ+CNwSvTi1LM5fCyyegng/Ag72fFihXpM3Wb5B+5P0B55Qgp64eqbCIidUZBIyIiXRv+GP1U9+q2FHOUYUY0bL755im8bKL7ySA6KLfM52G+G09THi6HOMPLhLfJvBgRkd7hFVVERLoKxVqyZEky2nsRXjaZZZjxwkS1shAgnYgzXhu5MYaUiYiMPwoaERGZ1AaZEV6GIJo5c2YKx5poUYY3hvAy6DRcLvfG8Fkiwd+QMhGR8UVBIyIik+KVyQXAZISXrVmzJokyPk83+TF5bgzeJT6H3hgRkYlDQSMiIi2B8EAAUO2rW69MiACS4rfccssJrV6GJ4bPQYhZp/kxVbkxeGMovSwiIhOLgkZERMYELwYVzEjY79YrwzYQEhPZHJP3peQyxQvi/Tv5HHnzS/adSmUTHSInIiLroqAREZEJqWAWSf8kyOPRmIjcEt6PimV8BjxCeFA6+QzhUWKfp02bloSMlcpERPoDr8YiItKwrwy5Mt16ZcKrgZCYPn36hOSX8J5UK0PIMN+JkMkbYCJe2He8Mib5i4j0FwoaERF5kCGPRwYx0I1XZjKS/stCBiHSriclwuKAcDI8MpPR2FNERFpDQSMiIqOQKI9Xhmmn5YsBMYEoQAjg2RjvpH9ECCWkuxEyeX4MYXEIsG5C7EREZGJQ0IiISILqZbfffntPvDKw1VZbJWEwnvB+eGSoWtapkMnzY/Aksc9WKxMRqQ8KGhGRIQcBQgUz+rJ045VBFLCtjTbaKHllxjNpvlshU5UfQ9nlieyDIyIivUFBIyIyxFDKGDEDnSb+56WYZ86cOa6lmHkvqpYhZBAk3QgZvFCbbbbZhJWOFhGR8UFBIyIyhGDQL126NIkDhEy3Xhm8GzTIHM9QLcQXIXG8X7tVy/ICBVRZQ8iY6C8iMhgoaEREhgxCy0j8R4wgCrrxyiAsZs2alcLMxot77rknCRkKFXQjZBAwCJmJKBstIiITh4JGRGRIwKgnVIvk/04bTOZeGZpLjmeDzLVr1yYhw5T3aCckLi+9TEgZQsaKZSIig4mCRkRkyMox9yJXZjy9Muwjwmv16tVpPzsVMoTB0UNGISMiMtgoaEREBhz6syxbtqyrcsxR2hhvx3jlyuD1oY8M1cs6ETIRWqZHRkRkuFDQiIgMKBj4JP7j6eg08T/3ysyYMWNcKoJRoIAwOMQMKGRERKQdFDQiIgMIIoZyzFGeuJMQs4nwyuCNIU8m+sG0KroUMiIiEihoREQGCAx8BAIeDwRCJ0b+RHhlqLRGGFy7lctyIUMOz+abb66QEREZchQ0IiIDAuJg8eLFSYx06pXBU8LrEQvTp09vq2llq/uI4KIUczs5PXlDTMovU11NISMiIqCgEREZAPDIIBQ6TfwPzwdstdVWxaabbtrT/UOMkCNDgYJ2E/7ZL4QM/WMQMvaRERGRHAWNiEiNQSiQK4PHo50clBzEAqIBoYCYQWz0CoQSIoYyzMy3I2Qih4fXEPqGZ0ZERKSMgkZEpKYgYugtgyDptLdMeD/IRaFnS6/3jyprvEc7YisEFq9BYNFPRkREpBEKGhGRmoGnA48HYWbtJNSXt0GuDEJo9uzZxSMf+cie7R/bJeG/3TyZEDK8hqpqhL11ItJERGS4UNCIiNQIxAJemXvvvbdjr0yEck2dOjV5ZnolGhAkd9xxRxrt5MmEuGJdyi+zX52EzomIyHCioBERqQmrVq1KIVzQiZgJ4YBXZ9asWT3NSbn77rvTvrXTTyYvwYw3BjHT66pqIiIy+PjPISLS5yASEAsIGoRMN4n/9JShHHOvPCB4iggvW7t2bVvhb+wLXiJEFeFllmAWEZFOUdCIiPQxCAVCzBAAnfSWKZdj7lWCPWKEPJ6VK1e2FV4WwsrKZSIi0isUNCIifQq5KIiGTnvLjFc5ZkQMPW/aqa6WJ/zjIUJYmfAvIiK9QEEjItKnvWVWr17dcYhZlGMmL4VyzL0QD/fdd18KfcNrRK5LK/kueZ4M+8Ew4V9ERHqJgkZEpE97y3QaYkbiP2KDxH+8M93CvqxYsSKViW4nvCxEFXk7VFPrZcNOERGRQEEjItIHIEQQDYSZddpbBvGAmKFiGIn2vfCE5NXLOsmTmTlzZrHBBht0vR8iIiKNUNCIiNS8t0ye+I+AwCPSi/AyqpetWbOmZYGV95OxMaaIiEwUChoRkUkEDwj5Mt32lulV4j/bw0uEt6jV8LJyPxnCyxBBIiIiE4GCRkRkEiAsi0phd911V98k/uONQVyx3VabY1LAgIGgwivzyEc+sqt9EBERaZehLjVz1VVXFeedd17Hr//whz9cnHLKKaOPP/GJTxRvf/vbG67Pc/zxdwp3P4899tjixz/+8WhIyEc/+tHixBNPLM4555yOtysiEwu/3VtuuSWVPyaUq10xw7WAbSBgZs+enQRNN2ImqqotXLhwtBjBWPsU+wD0k5kzZ45iRkREJgU9NC3AH3yjP3fCRahKRNIr/SLGk9/97ncpnCP4zne+Uxx88MHFox/96HF9XxHpHYgYkuy76S1DiBl5MvRz6Ta0q92eMnl42dSpU5OYsgyziIhMJrUUNPyZv+997xv9U99nn32Kww47rPjKV75SXHnllekP+T/+4z/Suh/60IeKKVOmJAMCT8YWW2xRfOQjH0l/4PwZk0ALeD1++tOfpvmjjjqq2GGHHdI2tt122zTgyU9+cooNz9l3332Lyy67LIVazJ07t7j88svT8q9//evFH//4x7SPb3jDG9L2AkJMPvaxj6XwDu5q8nwrXHLJJcWBBx44+vjqq69Oce5f/epXi+c973nF/vvv3/WxFZHxAcHAdWjVqlVdh5iRK5Pf3JionjJ5eBliqhNBJiIi0mtqeVvtN7/5TbHLLrsUJ598crHRRhulZTfffHPykJx22mnF0UcfXZx//vlpOaLhuOOOSwb/r371q+K6665LdzQJFdt6661H71Di/Tj99NOT6EEYAdv793//9+IFL3hBGmUxE4LmD3/4Q9qnxz/+8aPLDz/88LS9//zP/ywuuOCCdV7DvrG9U089NXl2rrnmmjE/M0Jp9913X+duLFWRHvvYxxbvete7kqjpJpxNRMYPRMOCBQuSR7ebEDNExzbbbNOVmIny0OxPVFVrNbyMKWKKGzGKGRER6Rdq6aEh1nu77bZL84961KPSlNhvPBaRw0KCLPDnz581YmTx4sVJBMRrdtxxxyQmWIYgQszkEJs+VlM6BAl3TYmH508++NnPflZcfPHF6b3LIRy33nprce6556blGDp4dnLhgndn++23T56iAA/SW97yluLSSy8dXbbhhhsWe+yxx2ivB5reVYkuEZk8qBjGzZFOQ8y4UcE1Bo8yHuZucmW4wYNXJhpvtiJkeH+8Qni6ub4YXiYiIv1GLQUNdwjnz5+fvBPz5s0rdtppp9QRe++99y5e//rXp3UwAMo5LXF3kWIAcNNNN41uj20cf/zxo6+FVg2HQw45JHl5cr7//e+nogGIpY9//OMPEkq8BkEFuWflMY95TBplFi1alDw63Fnlc+y2227JS8XnR6BhpHQbgiIivSMS7cmxa7ViWFWuCtchrm/hje6mohrXqVaFVTTHJNGf8DIT/kVEpF+ppaA54IADUg7NSSedlDwohGFh1OOVwUODAUCuSZUw2HnnnYsf/OAHxTve8Y6U98LgziPiCEHDtvbcc8/iyCOPfFCYWFUODey3334PWobX5YQTTkhhYmVe+MIXFmeeeWaxevXqZFwcc8wxSVQ1g7wfuOiii5KhhDfoiCOOSKIJg+lpT3ta1/0nRKQ38JvkZkarifaNxATXNyqItZLf0giuMwirdpL+ozkmQsYbJSIi0u+sN8K/12TvxHrrFSMXHj/2ek89o/j2t7+d5jHqER9nnXVWceihhyZvhYjIZBL5KYSZcX3qpAJZ3luG0SlsB68MRQgQRK3sS7z3JptsksLbbI4pIjlcT1760pcWv/j0upEnZZ702mPS9VBkoqilhwbe8573pHhwckcUMyIy2eDVwCsTifbtemXCM4KIICyV/LxOIbRs2bJlaZuEl421L+ERQvhwTe3mvUVERCaa2goaKpyJiPQDVC8jrAs6DTHrRW8ZtsF+cLOn1epl0VMGbxBhu90UHRAREZkMaitoREQmm0i2p7dUt71lEDLk83VbTQ1B0o5Xxp4yIiJSdxQ0IiIdQF8WSsHjFWlFQDQKMUMIEWLWaRUx9oNQt+hT04pXxqR/EREZJBQ0IiId5KhQKr3T3jIRYoaYoNJiJ54dhAleGYoQ8PpWQt3CG0RoG+9r0r+IiAwCChoRkRahuiJChpyZbkLMECOUY6aaWCfQkJdcmXYaZMa6vC9NeUVERAYFBY2ISIsighAzRE03IWa8lkpinfSNwruCR+bOO+9s2TsUXpmpU6emxP9ORJiIiEg/o6ARERkDRESEdnUSYoYIQlhQRYzmvJ1UEqNyGV4ZttNKeFkk/bO/5MqQ/C8iIjKIKGhERBqAICDhHu9MK6FdjcoiIz5mzZpVbLTRRh1XUiNvpxVBlZdiRjzhmbEUs4iIDDIKGhGRceotE2WRyVtBELXLPffck/YBD087XhlLMYuIyDChoBERGafeMuSsMDrZh2XLlhWrVq1Klcha8cpYillERIYVBY2IyD+49957U4hZt71lECH0ltlggw3a3ofVq1cnrwyiphWvTOTnRCnmTjxBIiIidcZ/PhGRokiVw/DMdNtbhjyZrbbaqu0eLwiT8MogSlr1yrC/VE1D0IiIiAwjChoRGWrwbuARoYpYJ4n/sQ0EDeFeU6ZM6Shfh/42bKMVz1B4ZehjY4NMEREZdhQ0IjK0RHgX3o5OEv/DS8JrCTF75CMfOSFeGQRMp1XTREREBg0FjYgMdeI/QqKTvJMIMSMBHy9Ju56ddr0y4QXi/bbYYgsbZIqIiPwDBY2IDBXdJv4DrwXKMRP21Q4IE7wyCJp2vDKsS65MJ4UGREREBhkFjYgMDXfccUexfPnyjhP/Q1zwWsQFoWbtQGgZXhm2045XhuaYlH/WKyMiIvJgFDQiMjSJ/zSq7LS3DPkuDMTF5ptv3pZnh/dHyPD+rRQeyL0y5MrQKFNERESqUdCIyEBDaFck/nfTWwYRgrjYcMMN23r9ypUrU4hZq4UHcq9Mu8JJRERkGFHQiMhAgijAK0KYV6deGbaBwEDEtNtbpl2vTLwX+6pXRkREpHUUNCIycCAi8MoQItZp4n94SqgohrekE68MtOOVmTZtWsqV0SsjIiLSOgoaERkYCOsi6f/OO+9M3pRuEv876S3D6/DKtNqkM7wy7CceoHb72IiIiIiCRkQGsBxzJ00y894yU6ZMabvXCz1t6G3TrlcGjwyeGb0yIiIinaGgEZHa04tyzAgMoBzzxhtv3PJrEUCEt+GVaSVXJ/fK0Memk/0VERGRf6KgEZHa0q6YaOaVoWElAoNQsVYhtA2vDN6VsXJ1EE3k9PB+VC8jL0evjIiISPcoaESklrQjJlpJ/Cfsq1Xuu+++0VyZdrwy5MiQK6NXRkREpHcoaESkll6ZtWvXtpR438vGlbwOIUV4W6teGYQMU7wy7YgmERERaQ0FjYjUhnbLIVdB2Bdjk002KbbccsuWBRFFBxBSeGdarWAWoWzTp0/XKyMiIjJOKGhEpO/By4GYoL9Mp7ky4S1BBJEr02riP6+j6MCKFStaKjqQe2UQTO32sBEREZH2UNCISG28Mp3mykQOC6Fl7ST+E9aGkIrwtHa8MuTKIL5ERERkfFHQiEhfggAh8X716tUde2ViO1FZrNUcFtbHI0O+TDteGSC8jD42IiIiMjEoaESkb70yCIVOvTKR+I8Ymj17dqow1gpULsMrg0BpJU8nvDIbbrhhEjN6ZURERCYWBY2I9A0IA7wy3eTK5In/5K/gmWlFECFMKAONmGrVK8P+sm3CyzbddNOO9lVERES6Q0EjIn3BXXfdlQQFdOuVeehDH5q8MuSytMLdd9+dhBSiph2vzEYbbZS8Mu004xQREZHe4r+wiEwq0aSym74ygEeGMDHKMSMyWtkO6xPahqDhvdvxylBcgPcSERGRyUVBIyKTQrlJZad9ZfJyzDNnzmy5HHO7eToRxoZXhnLMemVERET6A/+RRWTCabdJ5VjlmKNMcisiAw8L703yfyt5OuGVYb12+teIiIjIxKCgEZEJAwFCk0pGK4n3rZRJxlvSSpnkskeoHa8MIob3ITdHRERE+gsFjYhMCFQuI1em1XLIvWxeSX4O792qRygvLkAYG2FmIiIi0p8oaERkXEHAUL1s1apVLSXej+WVYYq3hJLMrYgfPDJUUGvVIxSNOCnDvMUWW3QcDiciIiITg4JGRMa9FHM3DTLzXBmaY+KVaUWYULmMpH9CxlrxCIVXBtGFV6bVks8iIiIyuShoRGRckv4J8WLaTdI/IDIQGzTInDZtWs9LMcdrEE14fTbbbDO9MiIiIjVCQSMiPQNRsGLFipR8jyjoNlcGoYEgobpYK8Ikkv6hFY9Q/h54fvAAiYiISL1Q0IhIT1i9enXyyrQa4tVKrgzeErwyY22r3TLQ+Xvg+cEz0+n+ioiIyOSioBGRrkBEkCdDFTOqgnWa9N9JrkwnHqF4j/XXX7+YPn16V/srIiIik4+CRkS67imDiOiVV4bKYq1UMCNHBo8Q+9FO0j/rIWSoYiYiIiL1R0EjIm2Ti4luk/5zj0krfWXwCJH0v2bNmpY9QtEgk34ylHxmn0VERGQwqN2/+jXXXJOm5bux+eOYb7YOBhiPGeX5WDcf8Zr8ufx1jeA57gyX56ueCxqtX6b8HI+bvabquJT3v7xOK9Ox1pHBATGBkEFMdNNTJvfKQCseE4QPoWWEmLXqEcobZFJYYOONN+54f0VERKQ/qZ2gmTt37qjBnhvuY82Xl2EcMa0aZUO9LEKC2EbE7jMw8GJKHkDMY/xhVDGNwWOe5/VV+9Dpsnywj7Gf5fl8GXev8+X542avi9dWvUf5eFUJzEYCL6fqOyyLzWaPq0bV/kjruSrd9JSJ7SFmNtxwwyRmxvKYUHAArwyvadUjFKWYp0yZkhL/LcUsIiIymNRO0PSjUZIb8lRb4u51WQCUDencSMdAI9yGRn4YeDFYhijKB+vWwRDPBVWjaZVYavR8WUAxMFhjvmrk6+brx3Jox8OWi8j8tc1G7sUb6736lZUrV6ak/1ZzVVrxmHBcCC/bZJNNmq7Purw3gqbV8LK8FDNiid+RiIiIDC61EzT9CAYexhajXcJIxsCmqzoJ1mF0lw3gEEYYaAxEDyE0GIUhgBBFjE72pZeUQ/j6WXDF8c7ny6Ko6jmM5hgY3vnjGLmQiqT3ZiGRZc9bLG8kkOJxK+GP7ULVMsRElELuNu8kPCacryT+NztH+ewRXgathpflhQXwzNRRQIqIiEh7KGgmmdwwHSsZGkL8YGyuWrWqWLx4cXocBm0Y6XhzSIDGeIyRCx7mh9nYy4/7RCaIl71GjUYughiICkRTPnIhxfPNBFOVWGokitgOwhpPY4SXdfuZI1Rs5syZ6fzrdXhZHDeEPUn/rfyWREREZDBQ0NQMDM6x7paHqAnRE4nXZQGDYUkiNiVyGQggBkbhZHt4BhWM81bFa7vkHqcq71A+H6IIIRRiCSFBc0q8ImyLc4Apz+eUc53KIio/zyK0jwaZjGYiupPqZXkIm0n/IiIiw4mCZkhD4MLTs3z58mTE5kYp84gdQnYUO/X83tvxqiBwrr322mLRokXpdTvssMOoV6SdXKg8TC/EEp7A6ClDLk5VWBzr8xyloEOwN8o9i2mcvyb9i4iIiIJmSGnm6WlV7GBETps2bTSkzTCfesF3OX/+/OKyyy5LXhEEa/l8aDcXim3iFWQ7++23X7H99tuPnjshdPIwOt7/6quvTucOHpY496rylsqV+3gNXh+miKF4//CCxX7no66FGURERKQxChrpWOwsWbJkdP0QOhiYkZAdQkePTn/Bd0Vo1x/+8IcUXoYXhe+rWxBFiJRHPepRxWMe85gH5cogKKJaH8UGfv/736f3J+yx1fwxxBLn2x577FHMmTMnnYt5PhGD/aDaYAz2KeZZr0rU5PlFZRFUFkQiIiLSXyhopGOxkxusIXTw6CxcuHB0XZaT15ALHQxYvAEahxMPQvSKK65IxSQQEXwX3X4PiATybxCvBx98cCrH3AjW+9Of/lTcdNNNbb3/WGKpVcJLVC6mEMsQPWvXrk0jF0URQgchiPI8IrYLufBByCuGRERExh8FjYyrVydK6ZKfsWDBglGjDmMPkUOYEVOEjiJn/KAEMkLilltuSd9RL4QM3y2hXhjrj33sY4uddtqpoTcOMfDXv/61+POf/5wet/r+IZY4Pw455JDUV6Ybci9Ru4RojyIKefW5mA/vUAii8A4xrapAF0IonmvmGfK3ISIiUo2CRsYVjDDuxJdDijAMKQ28dOnSdUQOeTnc4UfkkExOEQINuc4hROuqq64qbr755mQY90rIYLhjyOMx2XvvvdP3VAUGO+/9xz/+MRn1iNZWQhBDLLGvY4mlfqow2IjI/cmry4VnKCrN5UKIab4sSrPn+xJhcmUx1Ch3SEREZFBR0MikgHEaPXECjDZyKghbC4MNIRQihylCp5O768MGJbv/8pe/FNddd116TNhfL6qAYYCzbcTm/vvvn3q+VMF3x/dIngwNY6NEeDtiabvttkvhZYigQapAR85Su+RiqGrkYXIhhvKS3LEPZaoEkd4hERGpGwoa6XuREwUI8pwcGjSGJ4fHGlz/CwYtoV0MjOBeCRm2RegX3xFCJi/tXBXehkcmykC3WnAgF0uPe9zjug4vGyS6DZXL84TKRRTyogm5Z4gpj6OPFTQqppBXw6vyFCmKRERkPFHQSK1ETjRSvOGGG4rrr78+LcNoxvhF5ODFwSCe7PCkiQYDlONBCWREYKuhXWPB8UZksE3Cvvbaa6+GHgY8K4S3sR/thLchlggvI5TrgAMOSGFs9pQZ/7DPTgRReRrzVVXl8lC6aLBa7iWUv0ez0LmYVxiJiEgVChqpFRgzCJi8cSTGEh6cW2+9ddTYoaIaAoeQKETOoPbI4Q46TTHxyHAcyGXpJMejirhjz7GkpwzHsQqMVvaBhP92vEK5WNp5552LPffc03DCARREVaIoRv44QufycLkImYvnwlvUTBgB52HZO1QWRgokEZHBQUEjtQdPRJ6UjjFD3ga9VsLgwRjfZpttkieHZqB19+AgBBAR11xzTfq8vRQyUVmMbR500EHF1ltvXWn0sR7llykDjcHZzj6EWOL7QCzxncjg0gtRlFeay0VRPuK5vNhCLoryEYUZ8pC5Ru+ZT8tiKJ+vWiYiIuOPgkYGDowJwqIiNCoaMpLXEYYG+Tc0ZsSDQ4haXQwPhAbeGJL9+Vy9Ci3LQ7/YHpXFdtxxx0qBwnrz588vLr/88iSsEDKt9oUJscT6Bx54YBKZdTn2Mvl0U2muWfW5XAzl0/J8CKGyOCoLq0ZiqexRin3Iq9bFep0OEZFhREEjAw9/8rnAwYChUz3NJaP6FOFps2fPTh6DfiwygNCgahm5Q70WMmwPkcFxIfRrjz32qMyTYT2O2WWXXZY8YKzTasJ/FBXguFLmmfcZ1DBAqWf1uV4TAiUXRvwO4jGj/DgXToyYz71SVcIrtlPV6yj/rGUxFfuZT/PXVomlRo8bPVe1LyIivUZBI0MHXpq80ACGABW5aDoJLN92222TwCF/pFd3gzth5cqVScgQ2hUV3nqVMJ+XSCasjBLJVaWVWQ8BiIeLMD7yXFoVMnmeDJXRKCrQqGeNyCCRh59NhHgPARXihmmM/HGj+XzkXqmyGMvncyEVj+P5WJZ7nfJj08nna+ThKtNMUDVb1s7zVZ+j1fUaLRORzlHQyNDD3dm81wkGPvkpDP50ZsyYkUKjCFNDUIw3/EEjHBAyCxcuTPvA/vWy8ld0tSd3hRwWQu+q/mDpC/SnP/0p7QdGWTuNOaMvCsdv3333NU9GZIIE1GTehGkmtELodDotz1c9VxZrvXg/iGn+fP44f23V/sY28tDCqoIWVfNjPW423+j5Rt+VSF3pn6ueSJ+QJy/zB7R06dLkwYFNNtkkeW9mzZqVCg30UmTwXgiHK6+8srjjjjuS0OL9enknL3q94CV54hOfmJpXNhIy7AeV4zCO2hEy8R7sO+9BOJ93I0WGk1xoTRTl3KhWR1WvpvI6eZhgLpziszb63I0q8lU9ju3l2yrTyJPUK49Yo9dxo0qkH1HQiDSBP6MIkYoeOPR6oUQxzxGWhvcGL0SnJYfxltx8881pm3hN2vWEtJOMzz7SGJNeL1V5AwgphAzhd+0KGf7YeQ/2v9l7iIiUCQFSLuVdLrgQPY7KBRrK63O9brV8fFUxhnhtLkjywXWuKl9o0CmLLZF+QUEj0mEPHAx4PCoLFixIjwlJ23777ZP3ppWqXxj/VCsjtI1tkWRflcPSDSEyECf77LNPao5ZFc+fCxlESDtCJqqjsf5uu+2Whv1kRIYLrgNVpbHzPkLlBqz5Olyrqiq1tVo2O/oOcR214ttwcdFFFxWnnHJKOgeJnPj0pz/dsG9ar3jTm95UfOxjH+vZ9qgc+u///u/p//plL3tZ8ZrXvKY45JBDRnPH3vWudxWHHnpoz95vEFHQiPQg94aLzvLly4vbbrstPaaYAB4KxE2en8N6iAf6x+CV4UKF+Ol1zHteVYyqZbvsskulyLjzzjtHhQzGQDtCJq+ORsI/jTHzzyoi9SM80eUGpwyECF5kRgiUeA6vSO7ByIVIGGV5s9OY59pX9nbI4BJNb3sF+abvec97iu9+97spzJmbhJyP400vxQyceOKJxec+97mUz1oWa/2UE9fPeJREegB/xHloGmWNf/e736XH9LkhV4WL+Lx585LwQQz1smJZWcjA3Llzi913373SW4SQueqqq5J3iX1oJ1cnKpdhwFAdjTLMrVY9E5GJhd9rLkhiIEj4HTNCnDANYzC/HuRhWVy7QozE4BqjIJFGXHzxxcUHP/jBNP+GN7yh+OEPf5gaMvN/9aUvfSmFbV9wwQXFGWeckc6ld7/73cXjHve44tWvfnW6SYiR/8UvfjGFZdM2AO9F8P3vf794+ctfnv7D4n8PEAfnnntuih447bTTiqc97WnJ4/GTn/wkCQTm2S9uLh599NHpNc9//vOLN77xjcUznvGMJOp536997Wvp5iPvgffvqU99avH2t7+9eNKTnlT84he/KE4//fT0efjtfOITn0jVQtk2hXAuueSStO18f6vgvfDQvP71r0//34glPge/rac85SkppP2ss84qNttss3H8luqPgkakx4TXhYFxQO8WmmFy8SZcDYETBkCvhQxGB94SvDLlimxRfpk/BZL92y06wOvD4KFfDyFseKJEZHJESoiQskBh5F6URgIlFyfM4ynBk6swkV7D+YrhDwcffHC6AYi4OOecc1K42KmnnpoEAP+N/J+deeaZxeGHH168+MUvLs4+++zi/PPPT/PcQMvh/5XogDIvetGLile96lXp5uILX/jCJGiqOOGEE5IQIYqB9+Xcx9vDfrzjHe8ofvrTn6Ybf4iNV77ylQ8q5nDsscembdAj7qSTTkoCDQgbQ0ghgMYSNPwvEynBNihC9N///d9J4PGZETHnnXde8d73vndUFEo1ChqRcQCDAi8IUwgjgQsmIWcMjAc8GwiPTl3KuZAhfwePTNlbwnNLlixJF0zc8+3myEAYTIixAw88MN0x0ugRGR+hwm8tBsKE33gMrin8HiOMK8K7whgLkcKU6wo3UfytymTDDbDg/e9/fwqlwjOx6667pv8lqodGNAHnLzcB8cYgePgdIGaqoIpmVCHN+dGPflR85CMfSb8NREKVqA8xgZiJ98Wj87rXvS7lx+IdIu8UQYTX6KUvfWkSKs985jNHt/P//t//SyImQikDbiryH1+OwvjABz5QfO9730viiAH8Z5N7ikeIQRQHhEcGz9HnP//5Do76cKGgEekRJLWuWrUqCZmIJ4/Y8CC6kocBwsWUEQUByEFppTJYnohPrg5CJlzu+TpclOkjwz51Uj0t+tWwXwgZQgM0jkTah99jLlQYCBSuGfyWmee3llfnir4lIVBicBPE36HUiTinMdYJ9br00kuLCy+8MIkBjHi8IPwm+C/kvN95552Lww47rDjiiCPS6xA/VTzrWc8qXvCCFxRHHnlk+g/Ey8H/FaFgP//5z5P4p31ACAc8OggnbvIB703eDSFevC9CiHm8IuS18PvjvxPvCP+HbCsXNISCXX755cWNN95YHHXUUaPLG/0+3/a2t6WRg7eK3zQ3K7jZGcWBaKzN/C9/+csUeSHNUdCIdAkXYdzaGCaAwRGV0BoRd1JD3HChjLtIXIy5iHHRLd/diaplvJ6LLne3yqFliCnicfHIRKnmToUM+/D4xz8+5QBZglmkeSJ9JMyHVwWDhMF89O+I32HuUQlvikJFBh0aLHOeU7Frr732Ssv4nyNsi1A0/v8I3cJLgkBAMPD7QqDwX1bOoUGQvPOd7yye85znpPXwanzmM59Jjw866KCUi0NkAbDN5z73uSn/JZLvCQvjffjd4QlBQBH+9oc//CEJIDw03/72t4uPf/zjSXDgoclh+7wPoxsIb3v605+e/r+j4ADHiP9gRJ4emrFZb6QPWsMml/mFx4+93lPPSCeWyGTDRYe7qrk3BoOkW2OEn2P0UGBbXPgRI9wh4mLKMu5cIWSiCEG5nw3J/tyV4uLfbvnkMMp43aMf/egUxmaFFRl24qZDnqMSYiW8K1F2ONaHECohWhQrUne4cUfo1S8+/fGm6z3ptcc8KN9EZDzRUhFpEe6oYsjgjcHob9Ub0w4Rpgb8GWAw4YLmfbhThLeknIiPQYXLnIFRxR2ddvvZIGT4bNwJ4o6TQkaGjfgN5IIlPK/8xsKjkpeeDbFS5U0VEZGJQ4tFZAwIFcG4wbCJePZybkyvQZgwMJZoEIY3hn0gvpcKY4SbIaSuv/761EMmyka3GxYWHhm2hZAhH0chI4MIv108l5FYHx7WEC14YMqCJTws/LYULCIi/YuWi0gDQx+DB2MnQsqietB4GlyIGIwpjChifElyjPeMZEkS/a+++uq0X8Qb47GJ7tjtfD6MOkLL9ttvP4WMDJxo4feLUMHDye+YxxEWFmWLOeejsaPlikVE6osWjMg/wNiJkLJI4I2yp+NJnjeDUUVSI0KlvG9hnDGPyGFdjDd6yrCPrZSAjvLLvPaxj31sseOOOypkpHbgTYnclagsyG+D+Vy0QIgWw8JERAYXLRkZakLEEM4VeTETEVIGeFsQMoCAofoLnpay4YbAYlQJrKoS0IgaxE14beKuNYP3IQ+Hmv8KGelnOG8jNIyBYFmxYkX6LXAu8zste1oULSIiw4kWjQwdkyliciHDeyE8KCkZhQAAA407z9x1Dk9Rs30rl4COcBteg4HHFK/P/vvvX8yZM0eDT/qyYiCD3yR9Kjj3owx6ntPCuWx4mIiIlFHQyFAw2SImz4/hfcl7oRJZLi7Ia4nKSrkB187+RflotsVdbN4T0UQhAfJxNAJlsvPSECqc4yFcoq8ScN5zztuTRURE2kFBIwPLZIuYclgZIWCElVExKe9XwT5i2MU+RvhMN7k4vAdeGd6T40D3ZMo6I6R22WWX5Kkx5EzGA85BREsIl2XLlqVwMbyN5dwWfosKbRER6RYtGhkoovkdxhQeiskQMbk3hvckpAxvTJ77gtGH0ELIdOqNqRJNGIeIpnKeDcujr80vf/nL9F406KQoQLkAgUgrcI7nHhfytxAu4XEJ4RJhYgoXEREZL2onaKIXSLkjczBWZ9p4HdN8YFCWl5WH9B8Y89z5jbwRjKzJEDFlDwmCAiFD2EyElYU3BuOPaTfemLxXDdvHG4NoarYtjgU5NQz2889//nMq/0yBgF133TVtw/NcynDe4j2McEhCxRiR46LHRUREJpu+EDTTpk4p1nvqGWOuN3XKpsVBBx2U5qO6TbMR62H05tMwBInpxrBjMM8y5mMa84wQUY3+qOM9c4FUNcA/++7ge4nqRyEMJqrEchVxjgDGXFQYCxBcGH8YhN025sy9P2yDppu5aGoVjhX7ynZozDlv3ry0rT322KOYNWtW2w06ZTCIPC4GFcXC6xKlkKNHEueeOS4iItIv9IWgWXHHnUU/E2KIEcZrLnowAmIQ8oQBG2VyGSxjhGiqEkYRnhTNG6NqVXiOhpkoOxyhZBzHyfLCBHEuRMlYclMQCCEEonITIWURDsZ6nVYY433ic+NhiVycbmF/MEzZPsf25z//eRJju+++e2q2STUpGTyiGl54XchzwevCbyzCxZhGpTwr44mISD/TF4Km38nL4ubldTshhFAugEL4YEzEIMSDwfOxD2VvUOwTA2N5kELjOB58foyuSJaH+A4m43OWc2MQMIR5hTeG5SFiotwy+9uN1yjPj+G9CGMbDy9UHo7GefnHP/6xuOKKK1KOzdy5c5PXSepJ5GtFSWTES+RuGS4mIiKDgIJmggkB0uqdbwyOED25+MnzRqJjdnh/4nXAnVWMlVz09CN8tlzA5Ps/WQKmKqQMgx/jHu9I3LXmu8BYjPyubvc5F058b4SCIWYmKgwskrjZh+uvvz5VR5s9e3by2uCJ6tdzaNjhvIlzMbwuhIxxfdDrIiIig4yCps/BAEH8jCWAIiE9PDuMCNHCwAnxkxdUiOpakZg+kYInQvPCI8W+QOzPZBvNuWckQsoIzYqke/Y9GgGWwwV78Z4IJrwxvQgr65S8OtrixYuLW2+9NR2HPffcM+XZTPZ3NMzwnXD+IVzwtixdujR5X/hd5bkuePP0uoiIyKCjoBkQ4s4rg7v5zXJREDshJjDISfoND0Pu4Ykmjd2KndzLVCVgQsRMNuWQMjwxGIMRUsYxw3gMEdNtlbLye0a1Mt6z29DGXsKxiDwbDOif/exnaR/32muvYptttrGAwDjD+REhY3hcoq9LXviE8wXxkhejEBERGRYm34qUCTVMMXgaGT0Y1XhyEBxMMd7DgM/FTt43hVE2aPEyhHBiRD+Y2IcIf+sHckEBeEQipIx9RcRgRPL5I+ysWxFT9sYQ/hPemH6+k86+hceI75R+Npdddlny2Gy//faTUmFu0ED4Ixqjrwvihd9fOWQsD3kUEREZdvrDqpS+AAOJO++MMhjzIXSisz0GF6VdES0R7haVuKJAwWQm8bcjYvBqhZGIsc7nwpDMRUy3BnvZG0OlMt63n7wxrRJhkHzfv//974vLL7889bKhgAACTVrLd4mQMYQLg99QiBfOEUPGRERExkZBIy2BMMGzEzH6GOYY/ggZjH0MMMKSMNajTHXe8yfvzTPZFcrKIob9wZAkByFvztkrERMlnvOiAhtttNFAGKmIMT4P5wFNOmnWufPOOydxM5n5P/1YIhnxQqhYOd8lSn9bZUxERKQzFDTScY8K7tAjCqoMsChSUC5NHWWog/HstdNMxLAMEbNkyZJ1qqr1qjnnWEUFBg0+F8eW433NNdcU1157bbHTTjslYcPnHhb43glP5HeDlw/xwjTOQfNdREREes9gWlcy6T0q8iIF+Z36aBAZVc7KOTbdipxcSOQiBs9IhM1RrSuEVS+rqoWIi3AhPBe89zA1p+S74zPzPUTJ5x122CGVfK4KZawzfNcIlzxZn99OwHmAcLFEsoiIyPiioBkCMKwQDtGvJkJfmPJ4IntU8B4YeYy4c9+NyCl7YVgvQroQEmyHz4ixGWFfvczrKYeUlYsKDHs+FsfmpptuKm688cZUOABhU8cmndHfJXLHOJ/y/i5RJINzepi/dxERkclAQTMgREnmEC1RjhnREg0fw/gCjC88E/0Qs99I5CBwEDplkRPiJQoPIFz4HAixSLYmzIdprIeI6VUVrrKIYbuUW2bfLWHcWNjMmzevuPnmm1OpZyqjUdmtn8Mt+f1Ec0rOPfu7iIiI9CcKmpoQBn4Y99E4M7wtUVY4Fy1RXriOd43zhqJ4WxA2UU2NeQzKEDYR+oPxGa+NO+a9+txVIoYqZexbHauUTZaw4TgS8rdgwYIkbOhlM1keG86baDwb4Zb8luK8Yhr5LooXERGR/kVB0wdEyFVZrGBsMaJUcjR8jNdEdSTGIMXpRy4KxyPEGaKMcCWS6zkOdK6/5ZZb0nEBPCOM3BgNYdNNQ9BcxGDcKmJ616QzhA2haHvssUfDhrC98l7mRS6it9BEhluKiIjI+KCgGScwgqN8cT6i4SSGeEwZ4V2BMOIjYR1DfdAb6YWAySuSkUxOKBefG2MUA/gvf/lLep5lVIni+fJ2OMZsi+Oa5+K0UmygkYhhf2wcOT7CJkLRelE8gO+NsMvId4kqY3mJ5Mih0usiIiIyGChoKsj7p2AgN5riVQlhwsCIZkR/lrIACa9K9GMJwTKMd4U5hhyrEA6Elm277bYp/Agjk9CfhQsXFjfccEN6Ps+VaWaEhscKL8rmm2+exEl4vjB0o/FnrBvbygsLYOyS38E2FDHjC8c/Lx7A2HHHHZOw4fg3InKlokQyIWN4XRAy8TxEyBjnjuJFRERkMKmNoEE4YOSGKIgR5YWrljGNu+3lxwiOSDqPwbIQLEEjIyjeKxLOQ6Awj0CJhHX5ZwgZQi9CwRATM2fOTAKG57mLTvhRfHeRxN/tXXS+E7wrDAROCCnEDcZwlFkObw/vZzjZ5BYPoNwzQnbu3LnFbrvtlr6PCL/kPEG4cC3gN5tXGYuiEv7uREREhou+EDSbTp1WrLrrn/0bGrH+hhsVn/nUJ9e5A5sTy0JoQKNphB7leRbRb0Ux0h0YpdFEk2PL94GgmDFjxmiCP+FAhJDhhYlmg4iK8aoSFqIKTw1g+NLRfquttkr7SF4F+xKhatH40PNg4ojviHOA7+HXv/51cckll6QbBHxf4cWMingsFxEREekLQYOY2fa474653vz3PWfgmvPVnbyHTJ6Iz/eEgMnL4JLIH0xE5ahIBo+Su4gq7vjPnj07eWty8USYE+vjBbjtttuK+fPnp/yLEMcYzwhe6Q3hFY3KfXxHeTggREhmPE8uE6GAwxaeKSIiIs3RQpO276BjhEaOECIGTwbGJgIhclXIa2DARFWPCnGF8RveOoQLpYERV1TRaiageI51GDvttFPaFp6bqMbFZ4vu7+ZktP59xDnTTLg0K7Md1evIk8Gzx3eKGFbYiIiICChopBIMyMgxCi8FhinGPJ6OCAvCyGc9jE3gecLKJsrYLFdHIzSJMsDk52D4dpPUj4E9a9asNPbbb79kTC9ZsiRV5SKXA/iciLVhbqjJsY8iGVHJj++EZTkR2tlJfyBei4jkvfCckUPD92vOjIiIiChohpzwusSddIzDqPiFoR5GZJQ/Zj76d0TY2ETeKY+qZWEss3/bbbddCiOjRw1iazzg8+KFYuy6665pHzCs6YWDBycKSQxyaFqcJ7lwYZoX0WjF49INIWx4T0IDEZbxvStsREREhpPBtLyk4V30GPkyvAtRwjjCgXgcIgfDlDvhk+GFCDEVFa0waAkfmzNnTrHllluOGUY2XhBmR6d7BsY1lbcIS8N7E80+ETd1q5iWlySP8L3ooVRmPIXLWEQjVfZ10aJF6ftA2FgoQEREZPhQ0AywtyXvp4MwCNESy8MYhajyFuFkk7n/cdc/BMz06dNT2BcCBg9Jv+VOcLyolsbYd999k9cAzw09VaIvCgb3ZBj+VXAuxDlSFi3l6oHdhIlNBNF4ls9BlbroP2T/IBERkeFBQVMjopdO3twzhEssi5LTkfeCIRrGaFSNijHZBir7GKFLAXfYabCJFwbxEo026wLHGE8BY++99x5tEHrjjTemUD0gZAqDezw/V+6Ny0VL5ETl5OdGnY51EGI8KuoxOG84fwY1/E9ERET+if/2fSpWci9L3gy0DGIl+ufgBcgFS9xd7xf4DBE+Fv1pKMO7ww47JO8LjS2jKekgwOfgMzH22GOP5K1B3NA0MsRNp2Fp5RDC8LBEqFjVvtRZtLRC5HVxXlFhj+NtqWcREZHBR0EzjuRiJERKLkx4Lp4PIzSMzRApkafAY/JYIsSG0W+CJYiQtijvHB4jjE2ES1Qgw9isW45Jp3AM8BowKCqAwU1Y2vXXX58M73Kvm7JgiUT8ECxVjWUnM6elH4UNx5Dwvyj1PFn5ViIiIjK+KGiagNEYIxcmuRDB2IySwVXrBBiauRBhGqEyeFYwwHKxUhfDKxcvueeFsCpySsh/idCxQfK+dEPkM0VvHKp1UVAA703kD1WdAyFgB9nL0ks4XiFs6CeEsLEimoiIyOBRO0HDne0QGVA1n9+9HmsZxk4+DyFG8tdEyE4YlYxcfES+Sjnsq589Kd30G4nGmhwjPjPGOQKG8B7EC8sG4TO3Q+QyUdI5evREo1FCzMjtoAJaVAwLzxWD8wTvFa9nHdaNPCgFTG+EDUKRimgIa4QN56iIiIjUn9oJGkJIcuMu5kNUlJfnz4WBmIuTGCE8qh6Xtz3oRBWsCJHL8w8QK1QcIy8kFy+DTgiVaBrJNIQHgiXEShRmgBArcT5FGCHeq2bnE14bvgO2RzhalIEeJHE8GcTx47ujdxA9lDiPhyXsUUREZFCpnaChC7z0Xrgwn4tDhErkuWBgk79DSdxBMqajSEFUWov5qJQVIgUvS7mCXO5ZCbHCnf9eJZ+zHY45AzGFaMI7mfcJMtG9fcKTyneH14wRhQMmq1y5iIiIDJmgkfbzWyKxPPe2hDFeFi7cta5rrkvk8uQVv0KohDgJgZI368w/awi7ECqMXgqVTkC8hDeM/cZrgyEeYX91yrnqx8IBlNZGLFo4QEREpJ4oaAak1HOM3EDneRKg4w40xhpeFpYxxrsXSqew3+E5Klf3wqCP3BRGhH8xwsAvbysP+4qwI8Lk6ibc2Ff2m0EOCOKMRHeOAei16a5wwNKlS9PxJJepbueGiIjIMKOg6VPyimkxIDeyMNQJnyEsKUoC42EJwTJZnoVIjo/iAVXzkTif56RE6FeUta7ynkQeVJ7jFF6UYcp1ykPSOJ54bPAycPwGvd/MeMAxI7eJc49qc/x+EI0sExERkf5GQTNBlMs/56Wf82IFsS4GFkZ6GK2Rw4KBFXfpo6Jar/YtD01rNJ97TRAieYhX9J2JUC7I807y94KqwgxRHU1jvHUQtSS344nDa4WXIQoJ6LVpj6hMyLlNnyBuEnBce/E7ExERkfHBf+kWyQ3y8BSEKMlHbsjnrw1vCuEt3P1FmCBYmEesYMjnYgWjKnJg8u3H4wi9KntxcgESXpHcO1I1olFjLiTKIiSfVlWKi8d1DOUaFDjm4Z0Lrw3ixlybzgsH4PUiZynyaxSHIiIi/UftBA3VnqDcV6Y8X9V7Jij3mAlyD0n+uhhhtEe4U/SaCU9JnqNRFgeMXJhEPsjy5cvXESO51ybfp7IhWhZM5c8c71ke+b4xQkRp6A6u1wZvDYnv5tp0Xjggb8w5aNX+RERE6k7tBA1d1asM/Ua9aRpNq4z7oLy8kdclRAjCpNF7NFuWz+d30BuJGJF24RzCAGcQEoi3Ico/h7DxPGstv4bf+uLFi5MHksIB5teIiIj0B7UTNDvssMNk74JILcHbgIcBzw2eTrw2iByLCLTfmJP8GgpwEIpmfo2IiMjk4j+xyJCBUR49hwhDQ9hYRKCzxpwIQwQixQM8biIiIpODgkZkiI1zwqcYVeFoeCRk7Pya22+/PR0382tEREQmBwWNiIyGo1FEIKqjEVoVhS400qsxv0ZERGTyUdCIyCiIl6lTp6YQqnJ1NEKtFDZj59csWLAgHT9C0cyvERERGX/8txWRhtXR6GlDOBrCJkqmK2zGzq8hfA9Pl/1rRERExh8FjYg0JHoVzZgxI+XWEIpGvkg0itVQb61/DWFoiEOFoIiISO/RGhGRlkDAYJhvt912yfNA3gjeG6bSOL8G8bdo0aI0CEkTERGR3qKgEZG2IC+E/JDtt98+FRIADHWEDca7PDi/Bo8NuUj0r8Fr88ADD0z2bomIiAwMhpyJSMceiCggQH7NihUrksfGymjN82sI2SPHBi8Xx87jJCIi0h0KGhHpCgxymnRuvPHGqTLa8uXLk7BB8ChsmufXIG4I46Pcs8dJRESkMxQ0ItLzymhr1qxJwoYwKz02jfNrCD1buHBhOm6E7yF2REREpD0UNCLSUxAuiBq8DggbQtGYYsSTf6Ow+SccD8QexyfvX8MyERERaQ0FjYiMu7DBUxPChuUKm+b5NXhr6F/jMRIRERkbBY2IjCsY5YiaWbNmpWpoCJvVq1frsWmxf435NSIiIs2xbLOITAgY5euvv34SNltvvXUy1GnWybDc8z9B6CFsKINNfs3ixYtTkQURERGpRkEjIhNOCJs5c+akeQx2hc264L1C2ER+DV4bm5iKiIg8GEPORGTShQ05NlEVzXLP/8T8GhERkbHRQyMifZFjM3v27CRuMODx2FDSWI/Nuvk1CL2lS5cmjw15SB4fERERPTQi0qflnvM+NoRfybr9axYtWpSOFx4blomIiAwrWgki0rfC5p577iluv/325LGJBp3yz/41CL5bbrklhaDRv0bhJyIiw4j/fiLSt8Jmo402SuLm7rvvTh4byj4TkoanYtjJ82vIrVm1alWx+eabJ3Hj8RERkWFCQSMifW+4b7LJJkncYLQjbKiIprB5cP8avFl33HFHCkPbeOONLRwgIiJDgYJGRGoB4mXKlClJ3NB0EsNdYVPdv2bJkiWpghzChtA9ERGRQUZBIyK1M9zJF0HcIGoQN4Cw0SNRpNwajhFij8aceLYIRUPsiIiIDCIKGhGpreGOB2Lq1KnFihUrUh4JgobE+GEXNnEcyK+hvDOD4zRt2jQLK4iIyMChoBGRWoPhPn369OSxIb8G4z0qoils/je/BmGDJ4vmnBYOEBGRQcN/NBEZCOjFMnPmzGLOnDmjzTnJJ5F1G3MuW7YsNeakwIKNOUVEZBBQ0IjIQBnuJMEjambMmJEeU+qZCmDyz8acCBkKB9DDhl4/ChsREakzhpyJyMCWeqZ0Mbk1lDN+4IEHUniaoVb/LBzAMVm0aFHq9UMoGmJHRESkbihoRGSghQ25NQibKPUMVkRbt3DAmjVrkrcGEUgFOY6PiIhIXVDQiMhQeCQiGZ6KaOSPWBHtf+HzI2AQNhwXhhXRRESkThh7ISJDA4b7VlttlXJsCK+ycMCDCwdwjPBmzZs3L3m0zD8SEZF+R0EjIkPH+uuvX8yePbuYNWtWyiWxcEB1RTRyjxA2lHu2cICIiPQrhpyJyNAa7htttFFKiM8LB5hfs25FNITe0qVLk7eGsD3ykTw+IiLSTyhoRGSoyQsHYLQTbgUKm3WFDaF5lHrGe7PFFlskIejxERGRfkBBIyLyj8IBGOqIG7w1q1evTsY8yzXc//f4MKLUM2F7HC+mHh8REZlMzKEREcnAMzNz5syUY0MVNAsHrAvHBC/N/fffX9x6661J3Kxdu3ayd0tERIYYBY2ISAUbbLBBsfXWW6eqaGDhgH8SJa8RNogZhY2IiEwmhpyJiDQx3OldE4056WED5tc8uIdNNOek0ALFA8i7ERERmQgUNCIiY0AuzWabbVZssskmSdRQFY1lNuZsLmw4ZgobEREZbxQ0IiJtNuakcMCyZctSiBWihmR5WVfYUFTh7rvvTiIQYUN4moiIyHigoBERaRMqe82ZMycZ7FREI78GQx6vjfyzOSfChmPEIGxv2rRpemxERKTnKGhERDo02vE+EFplfk1rwmbVqlVJ2BiKJiIivURBIyLS4/ya6NmisHmwsLnnnntSOBqNOTlueLtERES6wfgIEZEe5tdQ6pl5+9c0zrFhUDyAcs8LFy5M84gdERGRTlDQiIiMQ37NjBkz0mOEjf1rGgub6GODsMF7o7AREZF2MeRMRKTHmF/TflU0hB+ihtwa+tgQkuaxEhGRVlDQiIhMQH7N8uXLU2I8y8yvWReORZS/fuCBB4rFixenxxw7ighYPU5ERJrhv4SIyDiDF4IQtNmzZydD/f777ze/pomwiQICS5cuLebNm5e8XB4vERFphIJGRGSC2GCDDVLRgOnTp4+GWZkzUg3eGoQN3hmamCJs8HLhwREREckx5ExEZIK9EJtuuulofs0dd9yRlptfUw2ChrwaCitwrBiE8NGkE8EjIiKioBERmSQPBMnviJvbb7895dewjJArqRY2EYpGg076/VA4AGGD50sxKCIyvPjPKSLSB/k1lC8mtOree+9Ny0yEH7tJJ8ds0aJF6XghbCwgICIynHjlFxHpAyM98mtozkl4lfk1rZV8RtxwvG677bbi5ptvNs9GRGQI0UMjItKH+TXkipBjA+bXNIdQPUaeZ4O3ZurUqSn/xmMnIjLYKGhERPoMjPMttthiNL9m9erV5te0mWfDMSMvCUFDOBr5NoajiYgMJv47ioj0KRjnM2fOLNasWZOEDfk10YBSxg5HQ9jQ84dGnYgZPDaIRJ4TEZHBQUEjItLnxjneBfJrqO6FsCG/xjC01ht1MvJwNPKVEDccV4+hiEj9UdCIiNQA+9f0LhyN6mh4bfB0IWzoa2M4n4hIffEKLiJS4/415IpgrLNcYdN6OBrgtaEqGoMiAlOmTCnWX399j6OISM1Q0IiI1BCM8jy/Bq+D+TXdFxHgGCJsEDjm2oiI1AMFjYhIjSEfZM6cOckYj8IBNubs3Gvzt7/9LR1HvDaRa8PU4yki0r8oaEREBsAgJw8kz6+huaT5NZ33tMFrgzgk14ZjiNeGY4xHx2MqItJfKGhERAYEvAibbbZZyq9ZsWJFsXLlytFKXxrh7RHHLXJtEIoMRCJeG0LSDO8TEekPFDQiIgMGhvj06dOTV4HQKRtz9i7XBnGzdOnSYtmyZckjhng0JE1EZHLx301EZEB55CMfOVo4AAPcxpzde23ykLR77rkniUWW47EhJA1xozdMRGRiUdCIiAxBY85tttlmtDGnhQN6X/6ZogwcX44pXhsEDoJScSMiMv4oaEREhqgxJ4a2hQN6CyImxGGeb4M3LI65x1lEZPxQ0IiIDGnhAETNXXfdlZZrcPc23yZKQFOcgcHx5ZiTd+OxFhHpLQoaEZEhBO/BlltuOVo4gJApjHErovWOPN8Gzw3HmRGeG8SNZaBFRLpHQSMiMsRgUFM4YO3atSm/hmkIGxmfYgKIm/DcsCzEjTk3IiKd4T+WiIgU66+/fjF79uxUuSsKB1gRbXzFDSBuCP1jICSplEbODd+H4kZEpDUUNCIiksCAxlNAVTQqdhEeZUW0icu5QdyQ08SI7wJxQylohaWISGMUNCIi0rAiWgib+++/X2EzweKGHjfkNgHhaNHnxrwbEZF1UdCIiEhDA5uiARjSlnqevFLQ5N1w3AkFjOcQm3hwEDiKTBEZdhQ0IiLSUqlnxA2iBnEDCpvJy7tZuXJlGkC+TXhv/E5EZBhR0IiISEtgUG+xxRajwiYMao3oyQtNw3tz3333FcuWLRt9jhwovDcIHctwTyx8HzHNR76sar1WllXBd8tzTGM+lrdC+TX5++Tbjn1ATIv0IwoaERFpCwTM9OnTi6lTpyZhQ55NLNd4nlg43nmJ7XLuDc+FwCEPZ5jKcZdFRQyOUaPncuO+fC7nhn35ffIpojI8ahE6WDXieaa5F67quXhN7Fezke9/1fKqz9TO/NQpU4onvfaYpsd+6tQpLX5LIr1heK5sIiLSU/ASbLXVVsW0adNSTxWM6DCwFTb9kXvDyMPTEJ1ROQ0PTj/l35QFB9N8PvcQlAVH7l3IpwiCKD/OtGpwTPLRSFhUiZHy4yohNGjc8Y+QU5F+QkEjIiJdC5sZM2akEs8IGzwECpvJJ4zrPDwt73sDPIcHB4GDByc8At0Ikr/97W+jYiQf+T6Vw5vitSEy2K/yQGzEfFmg5I9zEeP5JzIcKGhERKQnYBDPnDkzCRtKPdOkU2HTv8UFQnxQ5CEKPfAc4oYRoiAXKXm+Rh6CFeKE13Ae4P2JaYwQJeEVyT0kMd9PHiMRqQ8KGhER6SkYsrNmzSrWrl2bPDYKm8mlWa5IeT36DSFIae4ZoVT0JKLKHQUhmEYvnHKoljlUIjJZKGhERGRc4K58eGwiFA0jWWEzcSIliONeFapVlaQe4JXh+yM/iu9v3rx5qcodRSG23HLLVBiC7zl/jYjIRDPUguaqq65K4yUveUlHr//whz9c3HrrrelO1c4771y84hWv6Ml+nXfeecVuu+1W7L333m2/ls/DfpGoy5/NW97yltHnvvWtbxW/+tWvive973092U8RkbFAuGDwlj024B39B1NVkWsskVIVtlVObO8UXh8haLF/CJwbb7yxuP7660dzYRA2IXIQPHh1FDkiMlEMtaBpFf5QGsX1/ud//mf6o+4nnvzkJxcve9nL1llGGMFNN900afskIhLCJvfYDJOwqSobXEV4UXKREt6UfEwGUWQgCg0An2PNmjVJ4Fx33XWj3yXChptrhKoheGj+qcgRkfGgloIG4xwvA1PKT+6zzz7FYYcdVnzlK18prrzyynQx/Y//+I+07oc+9KF0UV26dGlx4oknpgvrRz7ykeL2229PF1jCIeDHP/5x8dOf/jTNH3XUUcUOO+yQtrHtttumEUJh8803b7hfxBx/7GMfSxf2OXPmFG94wxuSt+W2225Lf97EHvN+f/jDH4rHPvaxxZFHHllcdtllxf/8z/+kO5fPec5zikMPPXSdP4mzzz67WLhwYYpJRzzxecfikksuKa6++urimc98ZnHwwQenZRdeeGHaNvsjItIPxQNoCDkofWyq+pxUEUnzUcmrXJWrjgY/3xmfiVEWOQica6+9dtSTw39Y5OPw34zIoUeOxQBEZOgEzW9+85til112KV7wghcUZ511Vlp28803p6o6p512WnHLLbcU559/fnqeCyrLMPIJt+J1/GGccsopxde+9rXigQceSPX5f/e73xWnn356ihP+6Ec/msQP23v/+9+f7io24oMf/GD6U0I8cOHmPXmPz3/+88U111yT1nnUox6VQr/e9a53FQcccEASMogTpnvssUex7777pgoyJ5xwwjqC5ve//31y37/xjW9MwucHP/hB8cIXvrDpsdlxxx3TMeFzvfOd70xha/xZEIr2rGc9S0EjIn3Zx6bfhU0r3hX+W6p6mgxjBa9GIof/pkWLFhULFixY5zsmRI0bhgzmETqUk+6380BE+pNaCho8Htttt92oWAC8GHgl3v72t6fH/EHCNttsk/5EuEguXry4WLJkyehrMP4RHSxDECFicmbPnt1UzJRDzvDwnHvuuekCjMdl7ty5o/sA3JUKbw/bRcTccMMNybPERR4hlsPjSy+9tLj88svTugil3BsUuTAItiDinPnz3H333dMfB3k+4akREelXYcM1kvLBXN9gIkVAK4IlvCt5hS97nrQOxyeOW07k5cyfPz/l5sR3zhQvDucFERV4d7hBxyhvQ0SGm1oKGv74uPARtkXFlZ122imJCrwRr3/969M6CAQ8LOWLJq/FWwGRU8IytnH88cePvhba/XNCAB1yyCFJKAEihP1rtp1vfOMbxTHHHJME19FHH/2g7RHm9vznP3+d/QIu8rmQCUi25a4W700883Of+9zit7/9bRJseHi4K/bd7343hbeJiPQTGKl4pTFgETV4bbju9SoUKxctVcn2vEfeyLHcUV4mLi8H+I7Is0Lk8p8WQofvEGGJJ4f/Qm5ghtBB9PhdiQwftfzVE7aFd+Kkk04aLReJ14WLGh4aLo4HHnhg8ZjHPOZBr6UaGYb9O97xjvTHGRVZEEcIGra15557pnCwHELYxsqhIRzszDPPHC1NilBp5bOceuqpxfbbb58uxjn7779/8clPfnLUc3T44YenZc34xS9+UfzoRz9Kx+Cggw5K+/vKV75y9PnjjjtOMSMifQ3X4bgrTxgaOYjcwQ9h0+wm0ViiBWM3mjzmjR4tJd1/8D9aDluD+H4Rvdy4ZD5v8pmLHc4hbvJFpTZLTIsMJuuNNCtcP1E7sd56xbbHfXfM9ea/7znFt7/97TTP3RouSuSLkHeSh2OJiMjgwN8U+Y0IG4rB8J+BsduorDEiBbES4WF6WYYHzgnsAzx7jNyzE89zTnADkTydGCF2Yqq4FakXtb26v+c970kJ/1TKUcyIiAweiBUEDIYp83jhqYxGIReWIVC4A49wyT0tMrwgRJqdByGCCc/G+1cOMY97vAibyNnBw8MIz154jRjmTon0B7W98p988smTvQsiItKjO+oIFwZEiV+MRUKHCD9DzHAnHSMT4xJjlKIu5AeyrmJGWoFza6ycrDgnCWnDKxjhi7w2Fy+sh/cnPDsMzk1EEMvyAhLRV4gxTNXuRCYKr/4iIjLhwqWc80C+XwiXSO5uFvrDeo9//ONTMRgqY/3lL39Jd93jDrp3zWW8vDw5IXYIiUQAMc95XhY/eX5XlPeOPK7c4xNeoHLp7xiIofxx1fuIDCMKGhER6blwITQsD+dhOXevp0+fnsQLCduIFrwu3ZTg5a44/bwIPabUPeX7MSwxRu1jIuMNAoPRqncwQtoQPvw+IoQyhFHkhJWFSvyG8m0wzT1Oec+jmM9Li7OfkX8W2y8vy59rNKjAatls6TcUNCIi0tNQMe4yUw4f4UKOS4SKjWdIGNumWiQ9ypYuXVr89a9/Tf3JAI+Pla2kHwiR0utS5DEQSfweyz2V8vpPZWFUNV8WUwG/+WPf9KbizpUrm+7XtKlTihV33Nn15xNpFQWNiIi0lJzPiFyCPFSMETku3XpcuoV9Q0wxuPNNPy4GhpjhaDJoTHTIGblriJmRT5zVfL+OfuOE7ZMIKGhERCQRd3gjXCySlzGY8LRsscUWSbwgWkjWL/cH6TfYx3333bfYa6+9UjgaeTaEo/G5CEczOVtEZDBQ0IiIDCF4WhAuEZ4SXhfCs+bMmZPEC3kuiBeW1dmrgceI5suEpFG16rrrrivmzZuXjkEkYYuISH1R0IiIDDB5XD0jGlISv0+Y2JZbbpmqi+HNYAxy6WNEGR4mqqPts88+SdSQa0NoGsel7sJNRGRYGdx/LhGRIQOhEl6XPNeF8KpZs2YlrwuhYwiXYa8ARrjczjvvXMydOzcVEbj22mtTWBrotRERqRcKGhGRGlIujRxErkseMqZx3loRAfrYLFiwIDXsDK8NZaGtkCYi0t8oaEREatLXJQ8ZIzSMUDEMcULH8LogXkx07xy8VvSzwXOzfPny1LDzpptuSt4u8nCaNfoUEZHJQ0EjItInIFQi1yWqjLEML8HMmTNTvgseGDwvLNO4Hh84ruHlIteGfjaEpN1+++3peY69jQVFRPoHBY2IyCT2dsHzklcZw8tSznfp9/LIgwzChWadDMLQ5s+fn8RNhKRZ/llEZPJR0IiIjDOEjIV4gfCsIFgwlBEvw1BlrO7w/ey5557F7rvvXtx2223FzTffnAQO4pTvTa+ZiMjk4D+niMg45rsASeXkuxAyRtlg813qDd8bIYCM/fbbr1iyZElxww03FIsWLUrPm28jIjKxKGhERLro7xKVxiLfhfCw6dOnpxHJ+vY3GVwQL1tvvXUaa9euTfk2iJvIt+F8oMqc37+IyPihoBERaaO/Cx6YEC8IlTlz5qyTrI8Bq/E6nOCV2WGHHdJYvXp16mtz/fXXp3ybeB4B5PkhItJbFDQiIhnkQyBeGLnhiVjhLjziBa8Lj610JY1A7EYJaAQN4oYy0KtWrUrP67kREekdChoRKYY934WQsTAs8b6Q70LIGNPId7G5onQC5xXil0ExAcQNuTb0t7nzzjvTOggbPXsiIp2joBGRgScPGcMDEyWSqUo1Y8aMJF6iRDJleDUsZbzFza677lrcfffdo+KGRp5gQQERkfZR0IjIwHldojllbhQiVggZo0QyBiWPuTMuMllsvPHGxdy5c9O45557isWLF6dS0JSEBryCiBu9gyIizVHQiEitG1OWE/UJ3UG0kOsSVcYwHC2RLP0MnsEoKHDvvfemUtALFixIVdM4v8GiAiIi1ShoRKQW5ZFDvOTCJBL1o7cLj020lrqDKN92223TQLgTjkZo2rx580aLCtDIE4GjUBcRUdCISJ+Gi0HkulAxiiaGebgYyzTmZNDhHMfbyHj0ox+d8m4ISZs/f37y4gThvRERGUYUNCIy4eTCBcESwoU703hbGISLUV2MoaEm8r8QPskgNA3P5bJly1JYGuFp0e/G3BsRGTYUNCIy7h4XDK9cuCBQqCqGxyUXLggaEWkNws7wXDL23Xff5L25/fbbi1tvvTUVGIjfneFpIjLoKGhEpCc5LpHnAggXYv8xoujlgscFAYNo4e6yPTdEegu/p7gxsP3226ff5V133VUsXbo0CRzC1FjGsO+NiAwaChoRaauqWIiXuNuLgUSFJmL8ES8IF0QLhpVlkUUmB8QKv0UGZaHxlt5xxx1J4Nxyyy2jfW/CY4rA0YMjInVFQSMilRXFmELcxcXYIRmfEDGES8Tyk5xPSIuI9C/k0xDiydhtt93Sb3zFihUpRI0KakzDg8O6CBx/1yJSF7xaiQxxiFie2xIgUBAsjKgmhnCxe7nI4IBXZquttkpj9913Tx7YO++8M4kc8m8IUaPZJ/C7R+DYA0dE+hUFjcgAgnGSixYIQyTKIEclMUJSeMwgdMywE5Hhg9993MjYcccd03Vi9erVKUwNcYPIoYpaFPbAe0NIKd4cRY6ITDYKGpEaVxALwcI8RkUYGxgneFXIa4lk/BAsihYRGQuuJRFWSvNauO+++5IHJ0QOYWp4cXKRgyfHctEiMtEoaET6XLAwZZS9LBtssEESK4SF0WwyFyyGh4lIr8EjM2PGjDR23XXXdB1au3ZtClUri5zwFPOa8OSIiIwXChqRSQwJC9HC47xqGCBKECtVggUxo5dFRCYTbppwLWLQC4diA1y/1qxZk0pG480JkROhr1zr8OSQj2NOjoj0CgWNSA/hz5w/7PCqlMVKrMPdSgQKoWAIFsI6QqgwbIInInUEgRI3XhA5FBwIkUMODoOS0YgdRE8QIWuIHKYKHRFpBwWNSAtEOdMQKlVhYLEef8j8mUf8OaIlRAqDef+wRWQYRQ7hagE3eyg8sGrVqiRuEDoMHufhtVwvQ+x43RSRKhQ0MtSURUp4VyLBPpJd408VMZKXMuYPmiTYXLAYKy4iMjZ4obnhw5g1a9bocq7Bd999dxI25OcgchA8LAsiNFevjoiAgkYGUqAgTEKcxHwIlHxdHiNCECiIkshTCYGCWImpTeZERMYfbgqRN8iYM2fO6PIIXUPYUHiA8DWKETQTOzEM4RUZbLTQpC8Jr0iIkbJAgUYChYo6eXhXXvmL5xAnDOa9qyciUr/QtTK52CGMLcQOXh4eh+c91g3hFMP/ApF6o6CRcaMsSKoel0VJvC5v3JZ7SvKk+SgHGsOwAxGR4WQssXP//fenEtOIHkZ4eELwIITiPwnCqx+CBw9PTP2PEek/FDQySty1ysVH1TRGlRiJ7URzxyjNWfaOIEpyIRLTfBgiICIi3RKeewY5kFXwn3XvvfeOCp7c24P44TGCiOaiwP9T/p8JZfHDUPyITAwKmhqQi4i4gJaXlcVGvm5cUJtdWGP9cL0jKBAeucAI0RHL82TM8pRhcryIiNSByKdkTJs2reF6IXwQNkxjIHZC/DB4XPb6RJGZ2E48F14fpuWhIBIZUEFDHGxcEJrRbJ38uar5sZ4vr1v1OsgvRO1elPJtxoUuv/MTgiGmVcKCkccIV43ydvSKiIiIjC18Wi1SQ7gbPcmYxojHuSDKhRJTnq8qaBP7UbZJ8sd5pc789VU3OMeaL+eqivQjtRM0N9xwQ1sCodF6VReH8nwjz0a+vJX5sbY71jbyHigiIiIyfGHgjSI0qpaVozfy7Y1183as50T6kdoJmp133nmyd0FERERERPoE44tERERERKS2KGhERERERKS2KGhERERERKS2KGhERERERKS2KGhEREREpLbstNNOxVe+8pXRxyeddFLx+Mc/vrjsssvWWe/Nb35zTyrGvva1ry2OPvroolcsWbKkOPXUU4vx5JOf/GRxwAEHpHHeeeelZRdffHGx7bbbFoccckjxf/7P/ynqTO2qnImIiIhI/aCMdK/73f3pT38qnvSkJxXf+c53iiOPPDIt++lPf1r8+te/ftB7f/jDH+76/RBEixcvHu2L2G3zU7ax1VZbFSeeeGIxnjztaU8rXve616X+Roial7zkJWn5y1/+8uK9731vUXf00IiIiIjIuIAX4PDDD0/jRz/6UXHssccWBx98cHHggQcWCxYsSOtccMEFych+8pOfXPz85z8v1qxZU7z4xS8uDj300OJFL3pRMsKvuOKK4jOf+cyDtv+Nb3yjeOMb31jcc889qSnpxz/+8eLKK69MXoerr746bfMFL3hB8fnPfz4to6kpHpFnPvOZ6fEJJ5yQtvNv//Zvab8w/FeuXJmW7bnnnsnwf/SjH53eHy655JL0OkRUiKZ3v/vdycPxlKc8pXjFK15RnHLKKenzvOc970nPL1u2LH1+9oV9jde86lWvKp7+9KcXf/jDH4qXvexllceC92W/9t9//+K0005L6/BZjjjiiOJZz3pWGiMt9Arabrvt0pRG6ozgy1/+cvoumNYZBY2IiIiIjBv33Xdf8e1vfzuJiNNPPz0Z6oSFnXPOOclzQrjVz372szQwrj/96U8nAYCnBfFw/vnnF3vvvXfxmte85kHbvvzyy4v99tuveMYznlH85Cc/KY455pgkRBBSG2+8cbF06dLiq1/9avHqV7969DXsw1ve8pa0ToR6IRLYL4QN6wOv/exnP1ucddZZxbnnnpuWffOb30wC6YUvfGGaDx7zmMek98d7s8ceexS/+c1v0meGM844IwknPt8mm2wyKoTmzp1b/PjHPy623HLL9LjqWNB/kf387W9/W1x44YVJ7MGcOXOK73//+8Xs2bOTgGuVT3ziE8Xznve8NP/Yxz62uOaaa4of/vCHxUc/+tEkvOqKIWciIiIiMm7ss88+o/Pvf//7i4suuih5XXbddddkRJPHscEGG6TnCUn761//mvJfEDxr165N3poqbrjhhuKqq65KYgbvDALh2c9+9jrr4F156EMfus6y6667blTI8H6Ej73tbW9L28I78/znPz89t+OOOxbrr79+Eg133nln8oQgsng93HbbbaPbRMTArFmzRucRVGybz3P88cen8LS77767eNzjHpee33fffdfZr6pjcfPNNxdvfetbkwfq2muvTSIrf7/Yt4DP8KY3vamYMWPGOnlFgChCBOEFiv2Dhz/84cVBBx1UXH/99aPiqm4oaERERERk3Ii8meXLlydvw6WXXpq8DV/60peSAU3oGcIF8YCXAq/EYYcdlsKqAPFTBeFmeHNYF/Dq8Pqq985h+3hQCBFjfcK6Vq9encLJPvWpTxULFy5M6+X5MYiZ3//+90nsEFIGiBQERHnd8ut4P0LKQsAQ9sbryvtWdSzOPvvs4rjjjhsNc4vwsvJ7BOGdKsNnQhjhNQqBh3jbdNNNk+jisxEOWFcMORMRERGRcWfatGnJK0BuzPe+9720DKOecCzyRFiO2CF5nXAuhArL/vjHP1bm0LCNJzzhCaOPd9ttt/T6sUCIfOADH0gi4R3veEcSHHh78PT87ne/a/g69onXBMwjqsbi7W9/e0q857Mgom699dbK9aqOBR4nwugIhXvEIx5RdMp73vOe5FH613/917TfhK597WtfS96iJz7xiSkMDe9SXVlvpJVMovHeifXWK7Y97rtjrjf/fc8ZjUcUERERkYkFL8jIJ85qus56R7+xpUR1kV6hh0ZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGqLgkZERERERGrLw4o+YJMpU4v573vOmOttsNHGxV133TUh+yQiIiIi67LJRhsV6x39xqbrTJs6ZcL2RwTWGxkZGfFQiIiIiIhIHTHkTEREREREaouCRkREREREaouCRkREREREaouCRkREREREaouCRkREREREaouCRkREREREaouCRkREREREaouCRkREREREaouCRkREREREaouCRkREREREaouCRkREREREaouCRkREREREaouCRkREREREaouCRkREREREaouCRkREREREaouCRkREREREaouCRkREREREaouCRkREREREaouCRkREREREaouCRkREREREaouCRkREREREaouCRkREREREaouCRkREREREaouCRkREREREaouCRkREREREaouCRkREREREaouCRkREREREaouCRkREREREirry/wFudCdSfwKjZwAAAABJRU5ErkJggg==' style='max-width:100%; margin: auto; display: block; '/>"
-      ],
-      "text/plain": [
-       ":Sankey   [source,target]   (value)"
-      ]
-     },
-     "execution_count": 5,
-     "metadata": {
-      "application/vnd.holoviews_exec.v0+json": {}
-     },
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "sankey"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 6,
-   "id": "53b26cc8",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<script type=\"esms-options\">{\"shimMode\": true}</script><style>*[data-root-id],\n",
-       "*[data-root-id] > * {\n",
-       "  box-sizing: border-box;\n",
-       "  font-family: var(--jp-ui-font-family);\n",
-       "  font-size: var(--jp-ui-font-size1);\n",
-       "  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
-       "}\n",
-       "\n",
-       "/* Override VSCode background color */\n",
-       ".cell-output-ipywidget-background:has(\n",
-       "  > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
-       "),\n",
-       ".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
-       "  background-color: transparent !important;\n",
-       "}\n",
-       "</style>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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-       "  var render_items = [{\"docid\":\"29b485c6-2547-4029-a5bb-1d7617c45c01\",\"roots\":{\"4b623405-3adc-45f6-a42e-a95b0e06a313\":\"bfa2e2f6-334f-447b-9d44-73aeaa27c5d2\"},\"root_ids\":[\"4b623405-3adc-45f6-a42e-a95b0e06a313\"]}];\n",
-       "  var docs = Object.values(docs_json)\n",
-       "  if (!docs) {\n",
-       "    return\n",
-       "  }\n",
-       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
-       "  async function embed_document(root) {\n",
-       "    var Bokeh = get_bokeh(root)\n",
-       "    await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
-       "    for (const render_item of render_items) {\n",
-       "      for (const root_id of render_item.root_ids) {\n",
-       "\tconst id_el = document.getElementById(root_id)\n",
-       "\tif (id_el.children.length && id_el.children[0].hasAttribute('data-root-id')) {\n",
-       "\t  const root_el = id_el.children[0]\n",
-       "\t  root_el.id = root_el.id + '-rendered'\n",
-       "\t  for (const child of root_el.children) {\n",
-       "            // Ensure JupyterLab does not capture keyboard shortcuts\n",
-       "            // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
-       "\t    child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
-       "\t  }\n",
-       "\t}\n",
-       "      }\n",
-       "    }\n",
-       "  }\n",
-       "  function get_bokeh(root) {\n",
-       "    if (root.Bokeh === undefined) {\n",
-       "      return null\n",
-       "    } else if (root.Bokeh.version !== py_version) {\n",
-       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
-       "\treturn null\n",
-       "      }\n",
-       "      return root.Bokeh.versions.get(py_version);\n",
-       "    } else if (root.Bokeh.version === py_version) {\n",
-       "      return root.Bokeh\n",
-       "    }\n",
-       "    return null\n",
-       "  }\n",
-       "  function is_loaded(root) {\n",
-       "    var Bokeh = get_bokeh(root)\n",
-       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
-       "  }\n",
-       "  if (is_loaded(root)) {\n",
-       "    embed_document(root);\n",
-       "  } else {\n",
-       "    var attempts = 0;\n",
-       "    var timer = setInterval(function(root) {\n",
-       "      if (is_loaded(root)) {\n",
-       "        clearInterval(timer);\n",
-       "        embed_document(root);\n",
-       "      } else if (document.readyState == \"complete\") {\n",
-       "        attempts++;\n",
-       "        if (attempts > 200) {\n",
-       "          clearInterval(timer);\n",
-       "\t  var Bokeh = get_bokeh(root)\n",
-       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
-       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
-       "\t  } else {\n",
-       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
-       "\t    embed_document(root)\n",
-       "\t  }\n",
-       "        }\n",
-       "      }\n",
-       "    }, 25, root)\n",
-       "  }\n",
-       "})(window);</script>"
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-       "\n",
-       "\n",
-       "\n",
-       "\n",
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-       "      title=\"Extension loaded. This cell output contains code that enables plot interactivity, it should not be removed.\">ⓘ</span>\n",
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fa-info-circle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]}]}]},{\"type\":\"model\",\"name\":\"Notification\",\"properties\":[{\"name\":\"background\",\"kind\":\"Any\",\"default\":null},{\"name\":\"duration\",\"kind\":\"Any\",\"default\":3000},{\"name\":\"icon\",\"kind\":\"Any\",\"default\":null},{\"name\":\"message\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"notification_type\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_rendered\",\"kind\":\"Any\",\"default\":false},{\"name\":\"_destroyed\",\"kind\":\"Any\",\"default\":false}]},{\"type\":\"model\",\"name\":\"TemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"BootstrapTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"TemplateEditor1\",\"properties\":[{\"name\":\"layout\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"MaterialTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"request_value1\",\"properties\":[{\"name\":\"fill\",\"kind\":\"Any\",\"default\":\"none\"},{\"name\":\"_synced\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_request_sync\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"holoviews.plotting.bokeh.raster.HoverModel\",\"properties\":[{\"name\":\"xy\",\"kind\":\"Any\",\"default\":null},{\"name\":\"data\",\"kind\":\"Any\",\"default\":null}]}]}};\n",
-       "  var render_items = [{\"docid\":\"ac796c77-942a-473e-a5db-c809186eeff3\",\"roots\":{\"4e054e45-2bea-484d-a8cc-4268c182c4f8\":\"f1cbd83b-d23e-4501-9795-fcf1fb2bd0f5\"},\"root_ids\":[\"4e054e45-2bea-484d-a8cc-4268c182c4f8\"]}];\n",
-       "  var docs = Object.values(docs_json)\n",
-       "  if (!docs) {\n",
-       "    return\n",
-       "  }\n",
-       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
-       "  async function embed_document(root) {\n",
-       "    var Bokeh = get_bokeh(root)\n",
-       "    await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
-       "    for (const render_item of render_items) {\n",
-       "      for (const root_id of render_item.root_ids) {\n",
-       "\tconst id_el = document.getElementById(root_id)\n",
-       "\tif (id_el.children.length && id_el.children[0].hasAttribute('data-root-id')) {\n",
-       "\t  const root_el = id_el.children[0]\n",
-       "\t  root_el.id = root_el.id + '-rendered'\n",
-       "\t  for (const child of root_el.children) {\n",
-       "            // Ensure JupyterLab does not capture keyboard shortcuts\n",
-       "            // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
-       "\t    child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
-       "\t  }\n",
-       "\t}\n",
-       "      }\n",
-       "    }\n",
-       "  }\n",
-       "  function get_bokeh(root) {\n",
-       "    if (root.Bokeh === undefined) {\n",
-       "      return null\n",
-       "    } else if (root.Bokeh.version !== py_version) {\n",
-       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
-       "\treturn null\n",
-       "      }\n",
-       "      return root.Bokeh.versions.get(py_version);\n",
-       "    } else if (root.Bokeh.version === py_version) {\n",
-       "      return root.Bokeh\n",
-       "    }\n",
-       "    return null\n",
-       "  }\n",
-       "  function is_loaded(root) {\n",
-       "    var Bokeh = get_bokeh(root)\n",
-       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
-       "  }\n",
-       "  if (is_loaded(root)) {\n",
-       "    embed_document(root);\n",
-       "  } else {\n",
-       "    var attempts = 0;\n",
-       "    var timer = setInterval(function(root) {\n",
-       "      if (is_loaded(root)) {\n",
-       "        clearInterval(timer);\n",
-       "        embed_document(root);\n",
-       "      } else if (document.readyState == \"complete\") {\n",
-       "        attempts++;\n",
-       "        if (attempts > 200) {\n",
-       "          clearInterval(timer);\n",
-       "\t  var Bokeh = get_bokeh(root)\n",
-       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
-       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
-       "\t  } else {\n",
-       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
-       "\t    embed_document(root)\n",
-       "\t  }\n",
-       "        }\n",
-       "      }\n",
-       "    }, 25, root)\n",
-       "  }\n",
-       "})(window);</script>"
-      ],
-      "text/plain": [
-       ":Sankey   [source,target]   (value)"
-      ]
-     },
-     "execution_count": 6,
-     "metadata": {
-      "application/vnd.holoviews_exec.v0+json": {
-       "id": "4e054e45-2bea-484d-a8cc-4268c182c4f8"
-      }
-     },
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "ep.pl.plot_sankey(edata, columns=[\"gender\", \"race\"], backend=\"bokeh\", show=False)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 7,
-   "id": "a59e9a13",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "layer = np.array(\n",
-    "    [\n",
-    "        [[0, 1, 2, 1, 2], [1, 2, 1, 2, 0]],\n",
-    "        [[1, 2, 0, 2, 1], [2, 1, 2, 1, 2]],\n",
-    "        [[2, 0, 1, 2, 0], [2, 0, 1, 1, 2]],\n",
-    "        [[1, 2, 1, 0, 1], [0, 2, 1, 2, 0]],\n",
-    "        [[0, 2, 1, 2, 2], [1, 2, 1, 0, 2]],\n",
-    "    ]\n",
-    ")\n",
-    "\n",
-    "\n",
-    "edata_time = ed.EHRData(\n",
-    "    layers={\"layer_1\": layer},\n",
-    "    obs=pd.DataFrame(index=[\"patient_1\", \"patient_2\", \"patient_3\", \"patient_4\", \"patient_5\"]),\n",
-    "    var=pd.DataFrame(index=[\"treatment\", \"disease_flare\"]),\n",
-    "    tem=pd.DataFrame(index=[\"visit_0\", \"visit_1\", \"visit_2\", \"visit_3\", \"visit_4\"]),\n",
-    ")"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 8,
-   "id": "dfb9988e",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<script type=\"esms-options\">{\"shimMode\": true}</script><style>*[data-root-id],\n",
-       "*[data-root-id] > * {\n",
-       "  box-sizing: border-box;\n",
-       "  font-family: var(--jp-ui-font-family);\n",
-       "  font-size: var(--jp-ui-font-size1);\n",
-       "  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
-       "}\n",
-       "\n",
-       "/* Override VSCode background color */\n",
-       ".cell-output-ipywidget-background:has(\n",
-       "  > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
-       "),\n",
-       ".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
-       "  background-color: transparent !important;\n",
-       "}\n",
-       "</style>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
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i < links.length; i++) {\n      const link = links[i]\n      if (link.href != null) {\n        existing_stylesheets.push(link.href)\n      }\n    }\n    for (let i = 0; i < css_urls.length; i++) {\n      const url = css_urls[i];\n      const escaped = encodeURI(url)\n      if (existing_stylesheets.indexOf(escaped) !== -1) {\n        on_load()\n        continue;\n      }\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }    var existing_scripts = []\n    const scripts = document.getElementsByTagName('script')\n    for (let i = 0; i < scripts.length; i++) {\n      var script = scripts[i]\n      if (script.src != null) {\n        existing_scripts.push(script.src)\n      }\n    }\n    for (let i = 0; i < js_urls.length; i++) {\n      const url = js_urls[i];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      const element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (let i = 0; i < js_modules.length; i++) {\n      const url = js_modules[i];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) !== -1 || existing_scripts.indexOf(escaped) !== -1) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      var element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.async = false;\n      element.src = url;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n    for (const name in js_exports) {\n      const url = js_exports[name];\n      const escaped = encodeURI(url)\n      if (skip.indexOf(escaped) >= 0 || root[name] != null) {\n        if (!window.requirejs) {\n          on_load();\n        }\n        continue;\n      }\n      var element = document.createElement('script');\n      element.onerror = on_error;\n      element.async = false;\n      element.type = \"module\";\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      element.textContent = `\n      import ${name} from \"${url}\"\n      window.${name} = ${name}\n      window._bokeh_on_load()\n      `\n      document.head.appendChild(element);\n    }\n    if (!js_urls.length && !js_modules.length) {\n      on_load()\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  const js_urls = [\"https://cdn.holoviz.org/panel/1.8.3/dist/bundled/reactiveesm/es-module-shims@^1.10.0/dist/es-module-shims.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-3.8.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-gl-3.8.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-3.8.1.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-3.8.1.min.js\", \"https://cdn.holoviz.org/panel/1.8.3/dist/panel.min.js\"];\n  const js_modules = [];\n  const js_exports = {};\n  const css_urls = [];\n  const inline_js = [    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\nfunction(Bokeh) {} // ensure no trailing comma for IE\n  ];\n\n  function run_inline_js() {\n    if ((root.Bokeh !== undefined) || (force === true)) {\n      for (let i = 0; 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-      "application/vnd.holoviews_load.v0+json": ""
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/javascript": "\nif ((window.PyViz === undefined) || (window.PyViz instanceof HTMLElement)) {\n  window.PyViz = {comms: {}, comm_status:{}, kernels:{}, receivers: {}, plot_index: []}\n}\n\n\n    function JupyterCommManager() {\n    }\n\n    JupyterCommManager.prototype.register_target = function(plot_id, comm_id, msg_handler) {\n      if (window.comm_manager || ((window.Jupyter !== undefined) && (Jupyter.notebook.kernel != null))) {\n        var comm_manager = window.comm_manager || Jupyter.notebook.kernel.comm_manager;\n        comm_manager.register_target(comm_id, function(comm) {\n          comm.on_msg(msg_handler);\n        });\n      } else if ((plot_id in window.PyViz.kernels) && (window.PyViz.kernels[plot_id])) {\n        window.PyViz.kernels[plot_id].registerCommTarget(comm_id, function(comm) {\n          comm.onMsg = msg_handler;\n        });\n      } else if (typeof google != 'undefined' && google.colab.kernel != null) {\n        google.colab.kernel.comms.registerTarget(comm_id, (comm) => {\n          var messages = comm.messages[Symbol.asyncIterator]();\n          function processIteratorResult(result) {\n            var message = result.value;\n            var content = {data: message.data, comm_id};\n            var buffers = []\n            for (var buffer of message.buffers || []) {\n              buffers.push(new DataView(buffer))\n            }\n            var metadata = message.metadata || {};\n            var msg = {content, buffers, metadata}\n            msg_handler(msg);\n            return messages.next().then(processIteratorResult);\n          }\n          return messages.next().then(processIteratorResult);\n        })\n      }\n    }\n\n    JupyterCommManager.prototype.get_client_comm = function(plot_id, comm_id, msg_handler) {\n      if (comm_id in window.PyViz.comms) {\n        return window.PyViz.comms[comm_id];\n      } else if (window.comm_manager || ((window.Jupyter !== undefined) && 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undefined) {\n    var nchildren = toinsert.length;\n    var html_node = toinsert[nchildren-1].children[0];\n    html_node.innerHTML = output.data[HTML_MIME_TYPE];\n    var scripts = [];\n    var nodelist = html_node.querySelectorAll(\"script\");\n    for (var i in nodelist) {\n      if (nodelist.hasOwnProperty(i)) {\n        scripts.push(nodelist[i])\n      }\n    }\n\n    scripts.forEach( function (oldScript) {\n      var newScript = document.createElement(\"script\");\n      var attrs = [];\n      var nodemap = oldScript.attributes;\n      for (var j in nodemap) {\n        if (nodemap.hasOwnProperty(j)) {\n          attrs.push(nodemap[j])\n        }\n      }\n      attrs.forEach(function(attr) { newScript.setAttribute(attr.name, attr.value) });\n      newScript.appendChild(document.createTextNode(oldScript.innerHTML));\n      oldScript.parentNode.replaceChild(newScript, oldScript);\n    });\n    if (JS_MIME_TYPE in output.data) {\n      toinsert[nchildren-1].children[1].textContent = output.data[JS_MIME_TYPE];\n    }\n    output_area._hv_plot_id = id;\n    if ((window.Bokeh !== undefined) && (id in Bokeh.index)) {\n      window.PyViz.plot_index[id] = Bokeh.index[id];\n    } else {\n      window.PyViz.plot_index[id] = null;\n    }\n  } else if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n    var bk_div = document.createElement(\"div\");\n    bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n    var script_attrs = bk_div.children[0].attributes;\n    for (var i = 0; i < script_attrs.length; i++) {\n      toinsert[toinsert.length - 1].childNodes[1].setAttribute(script_attrs[i].name, script_attrs[i].value);\n    }\n    // store reference to server id on output_area\n    output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n  }\n}\n\n/**\n * Handle when an output is cleared or removed\n */\nfunction handle_clear_output(event, handle) {\n  var id = handle.cell.output_area._hv_plot_id;\n  var server_id = handle.cell.output_area._bokeh_server_id;\n  if (((id === undefined) || !(id in PyViz.plot_index)) && (server_id !== undefined)) { return; }\n  var comm = window.PyViz.comm_manager.get_client_comm(\"hv-extension-comm\", \"hv-extension-comm\", function () {});\n  if (server_id !== null) {\n    comm.send({event_type: 'server_delete', 'id': server_id});\n    return;\n  } else if (comm !== null) {\n    comm.send({event_type: 'delete', 'id': id});\n  }\n  delete PyViz.plot_index[id];\n  if ((window.Bokeh !== undefined) & (id in window.Bokeh.index)) {\n    var doc = window.Bokeh.index[id].model.document\n    doc.clear();\n    const i = window.Bokeh.documents.indexOf(doc);\n    if (i > -1) {\n      window.Bokeh.documents.splice(i, 1);\n    }\n  }\n}\n\n/**\n * Handle kernel restart event\n */\nfunction handle_kernel_cleanup(event, handle) {\n  delete PyViz.comms[\"hv-extension-comm\"];\n  window.PyViz.plot_index = {}\n}\n\n/**\n * Handle update_display_data messages\n */\nfunction handle_update_output(event, handle) {\n  handle_clear_output(event, {cell: {output_area: handle.output_area}})\n  handle_add_output(event, handle)\n}\n\nfunction register_renderer(events, OutputArea) {\n  function append_mime(data, metadata, element) {\n    // create a DOM node to render to\n    var toinsert = this.create_output_subarea(\n    metadata,\n    CLASS_NAME,\n    EXEC_MIME_TYPE\n    );\n    this.keyboard_manager.register_events(toinsert);\n    // Render to node\n    var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n    render(props, toinsert[0]);\n    element.append(toinsert);\n    return toinsert\n  }\n\n  events.on('output_added.OutputArea', handle_add_output);\n  events.on('output_updated.OutputArea', handle_update_output);\n  events.on('clear_output.CodeCell', handle_clear_output);\n  events.on('delete.Cell', handle_clear_output);\n  events.on('kernel_ready.Kernel', handle_kernel_cleanup);\n\n  OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n    safe: true,\n    index: 0\n  });\n}\n\nif (window.Jupyter !== undefined) {\n  try {\n    var events = require('base/js/events');\n    var OutputArea = require('notebook/js/outputarea').OutputArea;\n    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n      register_renderer(events, OutputArea);\n    }\n  } catch(err) {\n  }\n}\n",
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-       "\n",
-       "\n",
-       "<a href=\"https://matplotlib.org\" target=\"_blank\" title=\"Matplotlib 3.10.5\">\n",
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-       "5nK5CQAQMtXznCRJePpEbwOAZhzHX4ix/wHzzC/tu64gcwAAAABJRU5ErkJggg=='\n",
-       "       style='height:15px; border-radius:12px; display: inline-block; float: left'></img>\n",
-       "</a>\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "\n",
-       "<span style=\"float: left; margin-left: 5px; line-height: 15px; cursor: pointer; opacity: 0.7;\"\n",
-       "      onmouseover=\"this.style.opacity='1'\"\n",
-       "      onmouseout=\"this.style.opacity='0.7'\"\n",
-       "      title=\"Extension loaded. This cell output contains code that enables plot interactivity, it should not be removed.\">ⓘ</span>\n",
-       "</div>\n",
-       "\n"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    }
-   ],
-   "source": [
-    "sankey_time = ep.pl.plot_sankey_time(\n",
-    "    edata_time,\n",
-    "    columns=[\"disease_flare\"],\n",
-    "    layer=\"layer_1\",\n",
-    "    state_labels={0: \"no flare\", 1: \"mid flare\", 2: \"severe flare\"},\n",
-    "    backend=\"matplotlib\",\n",
-    ")\n",
-    "\n",
-    "fig = hv.render(sankey_time, backend=\"matplotlib\")\n",
-    "fig.savefig(f\"{_TEST_IMAGE_PATH}/sankey_time_expected.png\", dpi=80)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 9,
-   "id": "c9b9fb79",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
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' style='max-width:100%; margin: auto; display: block; '/>"
-      ],
-      "text/plain": [
-       ":Sankey   [source,target]   (value)"
-      ]
-     },
-     "execution_count": 9,
-     "metadata": {
-      "application/vnd.holoviews_exec.v0+json": {}
-     },
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "sankey_time"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 10,
-   "id": "38907509",
-   "metadata": {},
-   "outputs": [
-    {
-     "data": {
-      "text/html": [
-       "<script type=\"esms-options\">{\"shimMode\": true}</script><style>*[data-root-id],\n",
-       "*[data-root-id] > * {\n",
-       "  box-sizing: border-box;\n",
-       "  font-family: var(--jp-ui-font-family);\n",
-       "  font-size: var(--jp-ui-font-size1);\n",
-       "  color: var(--vscode-editor-foreground, var(--jp-ui-font-color1));\n",
-       "}\n",
-       "\n",
-       "/* Override VSCode background color */\n",
-       ".cell-output-ipywidget-background:has(\n",
-       "  > .cell-output-ipywidget-background > .lm-Widget > *[data-root-id]\n",
-       "),\n",
-       ".cell-output-ipywidget-background:has(> .lm-Widget > *[data-root-id]) {\n",
-       "  background-color: transparent !important;\n",
-       "}\n",
-       "</style>"
-      ]
-     },
-     "metadata": {},
-     "output_type": "display_data"
-    },
-    {
-     "data": {
-      "application/javascript": "(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  const force = true;\n  const py_version = '3.8.1'.replace('rc', '-rc.').replace('.dev', '-dev.');\n  const reloading = false;\n  const Bokeh = root.Bokeh;\n\n  // Set a timeout for this load but only if we are not already initializing\n  if (typeof (root._bokeh_timeout) === \"undefined\" || (force || !root._bokeh_is_initializing)) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks;\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, js_modules, js_exports, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n    if (js_modules == null) js_modules = [];\n    if (js_exports == null) js_exports = {};\n\n    root._bokeh_onload_callbacks.push(callback);\n\n    if (root._bokeh_is_loading > 0) {\n      // Don't load bokeh if it is still initializing\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    } else if (js_urls.length === 0 && js_modules.length === 0 && Object.keys(js_exports).length === 0) {\n      // There is nothing to load\n      run_callbacks();\n      return null;\n    }\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n    window._bokeh_on_load = on_load\n\n    function on_error(e) {\n      const src_el = e.srcElement\n      console.error(\"failed to load \" + (src_el.href || src_el.src));\n    }\n\n    const skip = [];\n    if (window.requirejs) {\n      window.requirejs.config({'packages': {}, 'paths': {}, 'shim': {}});\n      root._bokeh_is_loading = css_urls.length + 0;\n    } else {\n      root._bokeh_is_loading = css_urls.length + js_urls.length + js_modules.length + Object.keys(js_exports).length;\n    }\n\n    const existing_stylesheets = []\n    const links = document.getElementsByTagName('link')\n    for (let i = 0; i < links.length; i++) {\n      const link = links[i]\n      if (link.href != null) {\n        existing_stylesheets.push(link.href)\n      }\n    }\n    for (let i = 0; i < css_urls.length; i++) {\n      const url = css_urls[i];\n      const escaped = encodeURI(url)\n      if (existing_stylesheets.indexOf(escaped) !== -1) {\n        on_load()\n        continue;\n      }\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error;\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }    var existing_scripts = []\n    const scripts = document.getElementsByTagName('script')\n    for (let i = 0; i < scripts.length; i++) {\n      var script = scripts[i]\n      if (script.src != null) {\n        existing_scripts.push(script.src)\n      }\n    }\n    for (let i = 0; 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-       "  var render_items = [{\"docid\":\"89d336df-d1e3-4e4c-8582-ae9fb3550b87\",\"roots\":{\"9b1a6df2-903d-4967-9384-104ce84a0cea\":\"bcb45503-8765-4434-a3b3-d6c444e50221\"},\"root_ids\":[\"9b1a6df2-903d-4967-9384-104ce84a0cea\"]}];\n",
-       "  var docs = Object.values(docs_json)\n",
-       "  if (!docs) {\n",
-       "    return\n",
-       "  }\n",
-       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
-       "  async function embed_document(root) {\n",
-       "    var Bokeh = get_bokeh(root)\n",
-       "    await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
-       "    for (const render_item of render_items) {\n",
-       "      for (const root_id of render_item.root_ids) {\n",
-       "\tconst id_el = document.getElementById(root_id)\n",
-       "\tif (id_el.children.length && id_el.children[0].hasAttribute('data-root-id')) {\n",
-       "\t  const root_el = id_el.children[0]\n",
-       "\t  root_el.id = root_el.id + '-rendered'\n",
-       "\t  for (const child of root_el.children) {\n",
-       "            // Ensure JupyterLab does not capture keyboard shortcuts\n",
-       "            // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
-       "\t    child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
-       "\t  }\n",
-       "\t}\n",
-       "      }\n",
-       "    }\n",
-       "  }\n",
-       "  function get_bokeh(root) {\n",
-       "    if (root.Bokeh === undefined) {\n",
-       "      return null\n",
-       "    } else if (root.Bokeh.version !== py_version) {\n",
-       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
-       "\treturn null\n",
-       "      }\n",
-       "      return root.Bokeh.versions.get(py_version);\n",
-       "    } else if (root.Bokeh.version === py_version) {\n",
-       "      return root.Bokeh\n",
-       "    }\n",
-       "    return null\n",
-       "  }\n",
-       "  function is_loaded(root) {\n",
-       "    var Bokeh = get_bokeh(root)\n",
-       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
-       "  }\n",
-       "  if (is_loaded(root)) {\n",
-       "    embed_document(root);\n",
-       "  } else {\n",
-       "    var attempts = 0;\n",
-       "    var timer = setInterval(function(root) {\n",
-       "      if (is_loaded(root)) {\n",
-       "        clearInterval(timer);\n",
-       "        embed_document(root);\n",
-       "      } else if (document.readyState == \"complete\") {\n",
-       "        attempts++;\n",
-       "        if (attempts > 200) {\n",
-       "          clearInterval(timer);\n",
-       "\t  var Bokeh = get_bokeh(root)\n",
-       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
-       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
-       "\t  } else {\n",
-       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
-       "\t    embed_document(root)\n",
-       "\t  }\n",
-       "        }\n",
-       "      }\n",
-       "    }, 25, root)\n",
-       "  }\n",
-       "})(window);</script>"
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-       "      title=\"Extension loaded. This cell output contains code that enables plot interactivity, it should not be removed.\">ⓘ</span>\n",
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fa-info-circle\"],[\"tagName\",\"i\"],[\"color\",\"white\"]]}]]}]}]},{\"type\":\"model\",\"name\":\"Notification\",\"properties\":[{\"name\":\"background\",\"kind\":\"Any\",\"default\":null},{\"name\":\"duration\",\"kind\":\"Any\",\"default\":3000},{\"name\":\"icon\",\"kind\":\"Any\",\"default\":null},{\"name\":\"message\",\"kind\":\"Any\",\"default\":\"\"},{\"name\":\"notification_type\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_rendered\",\"kind\":\"Any\",\"default\":false},{\"name\":\"_destroyed\",\"kind\":\"Any\",\"default\":false}]},{\"type\":\"model\",\"name\":\"TemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"BootstrapTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"TemplateEditor1\",\"properties\":[{\"name\":\"layout\",\"kind\":\"Any\",\"default\":[]}]},{\"type\":\"model\",\"name\":\"MaterialTemplateActions1\",\"properties\":[{\"name\":\"open_modal\",\"kind\":\"Any\",\"default\":0},{\"name\":\"close_modal\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"request_value1\",\"properties\":[{\"name\":\"fill\",\"kind\":\"Any\",\"default\":\"none\"},{\"name\":\"_synced\",\"kind\":\"Any\",\"default\":null},{\"name\":\"_request_sync\",\"kind\":\"Any\",\"default\":0}]},{\"type\":\"model\",\"name\":\"holoviews.plotting.bokeh.raster.HoverModel\",\"properties\":[{\"name\":\"xy\",\"kind\":\"Any\",\"default\":null},{\"name\":\"data\",\"kind\":\"Any\",\"default\":null}]}]}};\n",
-       "  var render_items = [{\"docid\":\"e33249d4-4bf0-4892-9267-5d1444d6464a\",\"roots\":{\"fb57819f-f792-458d-87fb-43d4a5875885\":\"b6b12b01-4b08-452f-acf4-58b0b888c3d5\"},\"root_ids\":[\"fb57819f-f792-458d-87fb-43d4a5875885\"]}];\n",
-       "  var docs = Object.values(docs_json)\n",
-       "  if (!docs) {\n",
-       "    return\n",
-       "  }\n",
-       "  const py_version = docs[0].version.replace('rc', '-rc.').replace('.dev', '-dev.')\n",
-       "  async function embed_document(root) {\n",
-       "    var Bokeh = get_bokeh(root)\n",
-       "    await Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
-       "    for (const render_item of render_items) {\n",
-       "      for (const root_id of render_item.root_ids) {\n",
-       "\tconst id_el = document.getElementById(root_id)\n",
-       "\tif (id_el.children.length && id_el.children[0].hasAttribute('data-root-id')) {\n",
-       "\t  const root_el = id_el.children[0]\n",
-       "\t  root_el.id = root_el.id + '-rendered'\n",
-       "\t  for (const child of root_el.children) {\n",
-       "            // Ensure JupyterLab does not capture keyboard shortcuts\n",
-       "            // see: https://jupyterlab.readthedocs.io/en/4.1.x/extension/notebook.html#keyboard-interaction-model\n",
-       "\t    child.setAttribute('data-lm-suppress-shortcuts', 'true')\n",
-       "\t  }\n",
-       "\t}\n",
-       "      }\n",
-       "    }\n",
-       "  }\n",
-       "  function get_bokeh(root) {\n",
-       "    if (root.Bokeh === undefined) {\n",
-       "      return null\n",
-       "    } else if (root.Bokeh.version !== py_version) {\n",
-       "      if (root.Bokeh.versions === undefined || !root.Bokeh.versions.has(py_version)) {\n",
-       "\treturn null\n",
-       "      }\n",
-       "      return root.Bokeh.versions.get(py_version);\n",
-       "    } else if (root.Bokeh.version === py_version) {\n",
-       "      return root.Bokeh\n",
-       "    }\n",
-       "    return null\n",
-       "  }\n",
-       "  function is_loaded(root) {\n",
-       "    var Bokeh = get_bokeh(root)\n",
-       "    return (Bokeh != null && Bokeh.Panel !== undefined)\n",
-       "  }\n",
-       "  if (is_loaded(root)) {\n",
-       "    embed_document(root);\n",
-       "  } else {\n",
-       "    var attempts = 0;\n",
-       "    var timer = setInterval(function(root) {\n",
-       "      if (is_loaded(root)) {\n",
-       "        clearInterval(timer);\n",
-       "        embed_document(root);\n",
-       "      } else if (document.readyState == \"complete\") {\n",
-       "        attempts++;\n",
-       "        if (attempts > 200) {\n",
-       "          clearInterval(timer);\n",
-       "\t  var Bokeh = get_bokeh(root)\n",
-       "\t  if (Bokeh == null || Bokeh.Panel == null) {\n",
-       "            console.warn(\"Panel: ERROR: Unable to run Panel code because Bokeh or Panel library is missing\");\n",
-       "\t  } else {\n",
-       "\t    console.warn(\"Panel: WARNING: Attempting to render but not all required libraries could be resolved.\")\n",
-       "\t    embed_document(root)\n",
-       "\t  }\n",
-       "        }\n",
-       "      }\n",
-       "    }, 25, root)\n",
-       "  }\n",
-       "})(window);</script>"
-      ],
-      "text/plain": [
-       ":Sankey   [source,target]   (value)"
-      ]
-     },
-     "execution_count": 10,
-     "metadata": {
-      "application/vnd.holoviews_exec.v0+json": {
-       "id": "fb57819f-f792-458d-87fb-43d4a5875885"
-      }
-     },
-     "output_type": "execute_result"
-    }
-   ],
-   "source": [
-    "ep.pl.plot_sankey_time(\n",
-    "    edata_time,\n",
-    "    columns=[\"disease_flare\"],\n",
-    "    layer=\"layer_1\",\n",
-    "    state_labels={0: \"no flare\", 1: \"mid flare\", 2: \"severe flare\"},\n",
-    "    backend=\"bokeh\",\n",
-    ")"
-   ]
-  }
- ],
- "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": "3.13.6"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 5
-}
diff --git a/tests/plot/test_sankey.py b/tests/plot/test_sankey.py
index 9a8da91dc..6e296fbc1 100644
--- a/tests/plot/test_sankey.py
+++ b/tests/plot/test_sankey.py
@@ -118,25 +118,6 @@ def test_sankey_bokeh_plot(diabetes_130_fairlearn_sample_100):
         assert target.startswith("race:")  # targets have the correct prefix
 
 
-def test_sankey_time_plot(ehr_3d_mini, check_same_image):
-    edata = ehr_3d_mini
-    sankey_time = ep.pl.plot_sankey_time(
-        edata,
-        columns=["disease_flare"],
-        layer="layer_1",
-        state_labels={0: "no flare", 1: "mid flare", 2: "severe flare"},
-        backend="matplotlib",
-    )
-
-    fig = hv.render(sankey_time, backend="matplotlib")
-
-    check_same_image(
-        fig=fig,
-        base_path=f"{_TEST_IMAGE_PATH}/sankey_time",
-        tol=2e-1,
-    )
-
-
 def test_sankey_time_bokeh_plot(ehr_3d_mini):
     hv.extension("bokeh")
     edata = ehr_3d_mini
@@ -145,11 +126,6 @@ def test_sankey_time_bokeh_plot(ehr_3d_mini):
         columns=["disease_flare"],
         layer="layer_1",
         state_labels={0: "no flare", 1: " mid flare", 2: "severe flare"},
-        backend="bokeh",
-        edata,
-        columns=["disease_flare"],
-        layer="layer_1",
-        state_labels={0: "no flare", 1: " mid flare", 2: "severe flare"},
     )
     assert isinstance(sankey, hv.Sankey)
 

From cae40f66792e42e0252e0e3202ce71098466a37e Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=C3=96yk=C3=BC=20S=C3=BCoglu?=
 <oeykue.sueoglu@helmholtz-munich.de>
Date: Fri, 12 Dec 2025 09:39:09 +0100
Subject: [PATCH 10/12] fix

---
 tests/plot/test_sankey.py | 5 -----
 1 file changed, 5 deletions(-)

diff --git a/tests/plot/test_sankey.py b/tests/plot/test_sankey.py
index 6e296fbc1..8358df90c 100644
--- a/tests/plot/test_sankey.py
+++ b/tests/plot/test_sankey.py
@@ -21,11 +21,6 @@ def ehr_3d_mini():
             [[2, 0, 1, 2, 0], [2, 0, 1, 1, 2]],
             [[1, 2, 1, 0, 1], [0, 2, 1, 2, 0]],
             [[0, 2, 1, 2, 2], [1, 2, 1, 0, 2]],
-            [[0, 1, 2, 1, 2], [1, 2, 1, 2, 0]],
-            [[1, 2, 0, 2, 1], [2, 1, 2, 1, 2]],
-            [[2, 0, 1, 2, 0], [2, 0, 1, 1, 2]],
-            [[1, 2, 1, 0, 1], [0, 2, 1, 2, 0]],
-            [[0, 2, 1, 2, 2], [1, 2, 1, 0, 2]],
         ]
     )
 

From abcb9bae5b26e03cafa7c3cee37fd05ae10b4133 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=C3=96yk=C3=BC=20S=C3=BCoglu?=
 <oeykue.sueoglu@helmholtz-munich.de>
Date: Fri, 12 Dec 2025 12:30:39 +0100
Subject: [PATCH 11/12] deleted outcommented code and formatting fixed

---
 ehrapy/plot/_sankey.py    | 21 ++-------------------
 tests/plot/test_sankey.py |  2 --
 2 files changed, 2 insertions(+), 21 deletions(-)

diff --git a/ehrapy/plot/_sankey.py b/ehrapy/plot/_sankey.py
index 223d8942a..2bd0f24bf 100644
--- a/ehrapy/plot/_sankey.py
+++ b/ehrapy/plot/_sankey.py
@@ -12,21 +12,6 @@
     from ehrdata import EHRData
 
 
-def _set_hv_backend(backend: str | None) -> str:
-    """Ensure a valid HoloViews backend is active and return its name."""
-    if backend is None:
-        backend = "matplotlib"  # default
-
-    backend = backend.lower()
-    if backend not in {"bokeh", "matplotlib"}:
-        raise ValueError(f"Unsupported backend '{backend}'. Use 'bokeh' or 'matplotlib'.")
-
-    if hv.Store.current_backend != backend:
-        hv.extension(backend)
-
-    return backend
-
-
 def plot_sankey(
     edata: EHRData,
     *,
@@ -36,7 +21,7 @@ def plot_sankey(
 ) -> hv.Sankey:
     """Create a Sankey diagram showing relationships across observation columns.
 
-    Please run `hv.extension('matplotlib')` or `hv.extension('bokeh')` before using this function to determine the backend.
+    Please call :func:`holoviews.extension` with ``"matplotlib"`` or ``"bokeh"`` before using this function to select the backend.
 
 
     Args:
@@ -117,7 +102,7 @@ def plot_sankey_time(
     Each node represents a state at a specific time point, and flows show the
     number of patients transitioning between states.
 
-    Please run `hv.extension('matplotlib')` or `hv.extension('bokeh')` before using this function to determine the backend.
+    Please call :func:`holoviews.extension` with ``"matplotlib"`` or ``"bokeh"`` before using this function to select the backend.
 
     Args:
         edata: Central data object containing observation data
@@ -159,13 +144,11 @@ def plot_sankey_time(
     flare_data = edata[:, edata.var_names.isin(columns), :].layers[layer][:, 0, :]
 
     time_steps = edata.tem.index.tolist()
-    # states = edata.var.loc[columns[0]].values
 
     if state_labels is None:
         unique_states = np.unique(flare_data)
         unique_states = unique_states[~np.isnan(unique_states)]
         state_labels = {int(state): str(state) for state in unique_states}
-        # state_labels = {int(state): states[int(state)] for state in unique_states} if the categorical variables values are also in layer
 
     state_values = sorted(state_labels.keys())
     state_names = [state_labels[val] for val in state_values]
diff --git a/tests/plot/test_sankey.py b/tests/plot/test_sankey.py
index 8358df90c..fa11d0ecb 100644
--- a/tests/plot/test_sankey.py
+++ b/tests/plot/test_sankey.py
@@ -27,9 +27,7 @@ def ehr_3d_mini():
     edata = ed.EHRData(
         layers={"layer_1": layer},
         obs=pd.DataFrame(index=["patient 1", "patient 2", "patient 3", "patient 4", "patient 5"]),
-        # obs_names=["patient 1", "patient 2", "patient 3"],
         var=pd.DataFrame(index=["treatment", "disease_flare"]),
-        # var_names=["treatment", "disease_flare"],
         tem=pd.DataFrame(index=["visit_0", "visit_1", "visit_2", "visit_3", "visit_4"]),
     )
     return edata

From 36987348c33d065ce7a21acb82c51420a48b848f Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=C3=96yk=C3=BC=20S=C3=BCoglu?=
 <oeykue.sueoglu@helmholtz-munich.de>
Date: Fri, 12 Dec 2025 12:47:10 +0100
Subject: [PATCH 12/12] formatting fix

---
 ehrapy/plot/_sankey.py    | 7 ++-----
 tests/plot/test_sankey.py | 2 +-
 2 files changed, 3 insertions(+), 6 deletions(-)

diff --git a/ehrapy/plot/_sankey.py b/ehrapy/plot/_sankey.py
index 2bd0f24bf..fc176bc2f 100644
--- a/ehrapy/plot/_sankey.py
+++ b/ehrapy/plot/_sankey.py
@@ -2,7 +2,6 @@
 
 from typing import TYPE_CHECKING
 
-import ehrdata as ed
 import holoviews as hv
 import numpy as np
 import pandas as pd
@@ -23,7 +22,6 @@ def plot_sankey(
 
     Please call :func:`holoviews.extension` with ``"matplotlib"`` or ``"bokeh"`` before using this function to select the backend.
 
-
     Args:
         edata : Central data object containing observation data
         columns : Column names from edata.obs to visualize
@@ -106,11 +104,10 @@ def plot_sankey_time(
 
     Args:
         edata: Central data object containing observation data
-        columns: Column names from edata.obs to visualize
+        columns: Column names from edata.var_names to visualize
         layer: Name of the layer in `edata.layers` containing the feature data to visualize.
         state_labels: Mapping from numeric state values to readable labels. If None, state values
-        will be displayed as strings of their numeric codes (e.g., "0", "1", "2"). Default: "None"
-        backend: HoloViews backend to use ("matplotlib" or"bokeh"). Default: "matplotlib"
+                    will be displayed as strings of their numeric codes (e.g., "0", "1", "2"). Default: None
         show: If True, display the plot immediately. If False, only return the plot object without displaying.
         **kwargs: Additional styling options passed to `holoviews.opts.Sankey`. See HoloViews Sankey documentation for full list of options.
 
diff --git a/tests/plot/test_sankey.py b/tests/plot/test_sankey.py
index fa11d0ecb..f6065cb1f 100644
--- a/tests/plot/test_sankey.py
+++ b/tests/plot/test_sankey.py
@@ -118,7 +118,7 @@ def test_sankey_time_bokeh_plot(ehr_3d_mini):
         edata,
         columns=["disease_flare"],
         layer="layer_1",
-        state_labels={0: "no flare", 1: " mid flare", 2: "severe flare"},
+        state_labels={0: "no flare", 1: "mid flare", 2: "severe flare"},
     )
     assert isinstance(sankey, hv.Sankey)