diff --git a/cosipy/__init__.py b/cosipy/__init__.py
index 694c1476c..7767e31b2 100644
--- a/cosipy/__init__.py
+++ b/cosipy/__init__.py
@@ -24,4 +24,5 @@
 
 from .background_estimation import LineBackgroundEstimation
 from .background_estimation import ContinuumEstimation
+from .background_estimation import TransientBackgroundEstimation
 
diff --git a/cosipy/background_estimation/TransientBackgroundEstimation.py b/cosipy/background_estimation/TransientBackgroundEstimation.py
new file mode 100644
index 000000000..1340b314b
--- /dev/null
+++ b/cosipy/background_estimation/TransientBackgroundEstimation.py
@@ -0,0 +1,267 @@
+from histpy import Histogram
+import numpy as np
+import matplotlib.pyplot as plt
+import itertools
+import copy
+
+class TransientBackgroundEstimation:
+    
+    """
+    Estimate transient background using a Histogram that
+    includes a 'Time' axis.
+    
+    The estimated background preserves all axes instead of
+    projecting to `Time` axis.
+    
+    YS: now it can support one background windows before
+    and after the burst. More than one window on each siede 
+    needs further tests.
+    
+    YS: now it assumes only one burst per data.
+    
+    YS: The burst window can be recoginized by Bayesian blocks
+    automatically in the future. I have the code but I need to 
+    do more tests before adding it.
+    
+    """
+    
+    def __init__(self, data):
+        
+        """
+        Initialize the instance if a transient background.
+        
+        Parameters
+        ----------
+        data : histpy.histogram.Histogram
+            The histogram containing both signal and background components.
+            Must include an axis labeled 'Time'.
+        """
+        
+        # check if input is histogram object
+        if not isinstance(data, Histogram):
+            raise TypeError(
+                "`data` must be a histpy.histogram.Histogram, \
+                got {type(data).__name__}."
+            )
+            
+        self._data = data
+                    
+        self._axes_labels = list(self._data.axes.labels)
+        
+        # check if the data has Time axis
+        if not "Time" in self._axes_labels:
+            raise ValueError(
+                "A 'Time' axis must be present for backrgound estimation \
+                of transients."
+            )
+        
+        # check if the Time axis is at index 0
+        time_axis_index = self._axes_labels.index("Time")
+        if time_axis_index != 0:
+            raise ValueError(
+                f"The `Time` axis must have index of 0, but you have \
+                index of {time_axis_index}."
+            )
+                
+        # All the time tags
+        self._timetags = self._data.axes["Time"].edges.value
+        
+        # max and min time tages
+        self._timetag_min = self._timetags.min()
+        self._timetag_max = self._timetags.max()
+        
+        #full data duration
+        self._full_duration = self._timetag_max - self._timetag_min
+        
+        # initialize the background window
+        # the background window is defined by the start and end time tags
+        # such as [[1,2], [3,4], [5,6]]
+        self._bkg_windows = []
+        
+        # initialize the burst window
+        # I use plural windows to avoid API changes after supporting multiple windows
+        self._burst_windows = []
+        
+        
+    def slice_by_timetags(self, start, end):
+        
+        """
+        It slice the data by timetags.
+        
+        Parameters
+        ----------
+        timetag_start : float
+            The start of the time slicing
+        timetag_end : float
+            The end of the time slicing
+            
+        Returns
+        -------
+        sliced_data : histpy.histogram.Histogram
+            The sliced data by time tags.
+        """
+        
+        if start >= end:
+            raise ValueError(
+                "`start` must be smaller than `end`."
+            )
+            
+        if start < self._timetag_min or end > self._timetag_max:
+            raise ValueError(
+                f"`start` and `end` must be within \
+                [{self._timetag_min}, {self._timetag_max}]."
+                )
+            
+        # find the indices of the starting and ending time tags
+        start_idx = np.searchsorted(self._timetags, start, side='right')
+        end_idx = np.searchsorted(self._timetags, end, side='left')
+        
+        # slice data by time tag indices
+        sliced_data = self._data.slice[start_idx:end_idx,:]
+        
+        return sliced_data
+    
+    def add_bkg_windows(self, *timetags):
+        
+        """
+        Define bkg windows using their timetags
+        
+        Parameters
+        ----------
+        timetages : list
+            The star and end time tags of the background windows
+        """
+        
+        for i in timetags:
+            
+            self._bkg_windows += [i]
+        
+        return
+    
+    @property
+    def bkg_windows(self):
+        return self._bkg_windows
+    
+    @property
+    def bkg_durations(self):
+        return [j-i for (i,j) in self._bkg_windows]
+    
+    def add_burst_windows(self, *timetags):
+        
+        if len(timetags) > 1:
+            
+            raise ValueError(
+                "Only one burst windows is supported now"
+            )
+            
+        for i in timetags:
+            
+            if i[0] >= i[1]:
+                
+                raise ValueError(
+                    "`start` must be smaller than `end`."
+                )
+            
+            self._burst_windows += [i]
+        
+        return
+    
+    @property
+    def burst_durations(self):
+        return [j-i for (i,j) in self._burst_windows]
+
+    @property
+    def burst_windows(self): 
+        # I use plural windows to avoid API changes after supporting multiple windows
+        return self._burst_windows
+    
+
+    def plot_lightcurve(self, burst_windows = False, bkg_windows = False,
+                        plot_limits = None):
+        
+        colors = itertools.cycle(plt.rcParams["axes.prop_cycle"].by_key()["color"])
+
+        fig, ax = plt.subplots(figsize=(16,8), sharex=False, nrows=1) ##sharex=True
+
+        plt.tick_params(axis="both", which="both", labelleft=True, labelright=False, labelbottom=True, labeltop=False, labelsize = 15)
+
+        ax.step(self._timetags[:-1], self._data.project("Time")[:].todense(), where='post', label='Light curve')
+        
+        #ax.ticklabel_format(axis='x', style='plain', useOffset=True, useMathText=True)
+        
+        if plot_limits is not None:
+            
+            ax.set_xlim(plot_limits)
+            
+        if burst_windows:
+            for idx, (t0, t1) in enumerate(self._burst_windows):
+                ax.axvspan(xmin=t0, xmax=t1, alpha=0.3, color=next(colors), label=f"Burst window")
+            
+        if bkg_windows:
+            for idx, (t0, t1) in enumerate(self._bkg_windows):  
+                ax.axvspan(xmin=t0, xmax=t1, alpha=0.3, color=next(colors), label=f"Background window {idx}")
+
+        ax.set_ylabel("Counts [ph]")
+        ax.set_xlabel("Time [s]")
+        
+        plt.legend(fontsize = 15)
+        
+        return
+    
+    
+    def make_background_model(self, scaling = "duration", save_path = None):
+        
+        """
+        
+        Parameters
+        ----------
+        scaling : str
+            The scaling method: duration or fitting.
+            `duration` scales the background counts by the duration ratio  
+            between the burst and background windows. 
+            `fitting` will fit the background windows before and after the
+            burst to get the fitted background counts during the burst. It
+            will be supported later.
+            
+        """
+        
+        if not self._bkg_windows:
+            raise ValueError(
+                "Please define background windows first."
+            )
+            
+        if not self._burst_windows:
+            raise ValueError(
+                "Please define burst window first."
+            )
+            
+        bkgs = []
+        
+        for (t0, t1) in self._bkg_windows:
+            sliced_bkg = self.slice_by_timetags(t0, t1)
+            bkgs += [sliced_bkg]
+            
+        # add all backgrounds
+        total_bkg = copy.deepcopy(bkgs[0]).project_out("Time")
+        for i in bkgs[1:]:
+            total_bkg = total_bkg + i.project_out("Time")
+            
+        unit_bkg = total_bkg/(np.sum(self.bkg_durations))
+            
+        if scaling == "duration":
+            bkg_model = self.burst_durations[0]*unit_bkg
+        
+        elif scaling == "fitting":
+            raise NotImplementedError(
+                "The scaling by fitting the background before and after the burst \
+                is not implemented yet!"
+            )
+        else:
+            raise ValueError(
+                "Please use `duration` or `fitting` for scaling method"
+            )
+            
+        if save_path is not None:
+            bkg_model.write(save_path)
+        
+        return bkg_model
diff --git a/cosipy/background_estimation/__init__.py b/cosipy/background_estimation/__init__.py
index ee2ba6813..7bed92eec 100644
--- a/cosipy/background_estimation/__init__.py
+++ b/cosipy/background_estimation/__init__.py
@@ -1,3 +1,4 @@
 from .LineBackgroundEstimation import LineBackgroundEstimation
 from .ContinuumEstimation import ContinuumEstimation
+from .TransientBackgroundEstimation import TransientBackgroundEstimation
 from .free_norm_threeml_binned_bkg import *
diff --git a/cosipy/test_data/GRB_bn110605183_with_bkg.hdf5 b/cosipy/test_data/GRB_bn110605183_with_bkg.hdf5
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diff --git a/docs/tutorials/background_estimation/tranisent_background/GRB_bn110605183_with_bkg.hdf5 b/docs/tutorials/background_estimation/tranisent_background/GRB_bn110605183_with_bkg.hdf5
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diff --git a/docs/tutorials/background_estimation/tranisent_background/Transient_background_example.ipynb b/docs/tutorials/background_estimation/tranisent_background/Transient_background_example.ipynb
new file mode 100644
index 000000000..fb2d3919e
--- /dev/null
+++ b/docs/tutorials/background_estimation/tranisent_background/Transient_background_example.ipynb
@@ -0,0 +1,692 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "7793101d-312a-404b-9ff1-6fb7a32b0914",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## Transient Background Modeling in CDS\n",
+    "\n",
+    "This notebook demonstrates a background-modeling method for transients. Traditionally, one models the background by fitting the light curve before and after the burst. However, that approach only uses the count information after projecting to the `Time` axis. `cosipy` operates in Compton Data Space (CDS), so the background must be modeled in CDS as well. We therefore need a different approach that preserves the multi-dimensional structure of the data.\n",
+    "\n",
+    "### Overview\n",
+    "\n",
+    "The general idea is the same:\n",
+    "\n",
+    "1. Define background windows before and after the burst.\n",
+    "2. Sum the data in those background windows and scale the result to the burst interval.\n",
+    "\n",
+    "We provide two scaling methods: `duration` and `fitting`.\n",
+    "\n",
+    "### Scaling Methods\n",
+    "\n",
+    "#### `duration`\n",
+    "\n",
+    "1. Convert the summed background model into a unit-rate background (i.e., a 1 s background).\n",
+    "2. Multiply by the burst duration so the expected total counts scale to the burst interval.\n",
+    "\n",
+    "#### `fitting`\n",
+    "**This will be supported in the future.**\n",
+    "\n",
+    "1. Fit the burst background level in a light curve using the background windows.\n",
+    "2. Use the fitted result to estimate the number of background counts in the burst interval.\n",
+    "3. Scale the summed background model to match the fitted counts.\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "4e8581d7-558c-405a-af36-f5b8eccaa424",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/io/package_data.py:4: UserWarning: pkg_resources is deprecated as an API. See https://setuptools.pypa.io/en/latest/pkg_resources.html. The pkg_resources package is slated for removal as early as 2025-11-30. Refrain from using this package or pin to Setuptools<81.\n",
+      "  import pkg_resources\n"
+     ]
+    },
+    {
+     "data": {
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+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #00ff00; text-decoration-color: #00ff00\">         </span><span style=\"color: #af5fd7; text-decoration-color: #af5fd7\">WARNING </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> but are inform you about optional packages that can be installed                  </span><a href=\"file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/__init__.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">__init__.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/__init__.py#41\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">41</span></a>\n",
+       "</pre>\n"
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+       "\u001b[38;5;46m        \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m but are inform you about optional packages that can be installed                 \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=631489;file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=297654;file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/__init__.py#41\u001b\\\u001b[2m41\u001b[0m\u001b]8;;\u001b\\\n"
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+     "output_type": "display_data"
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+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #00ff00; text-decoration-color: #00ff00\">         </span><span style=\"color: #af5fd7; text-decoration-color: #af5fd7\">WARNING </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> </span><span style=\"color: #800000; text-decoration-color: #800000; font-weight: bold\"> to disable these messages, turn off start_warning in your config file</span><span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">            </span><a href=\"file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/__init__.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">__init__.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/__init__.py#44\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">44</span></a>\n",
+       "</pre>\n"
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+      "text/html": [
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+       "</pre>\n"
+      ],
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+       "\u001b[38;5;46m        \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m no display variable set. using backend for graphics without display \u001b[0m\u001b[1;38;5;251m(\u001b[0m\u001b[1;38;5;251magg\u001b[0m\u001b[1;38;5;251m)\u001b[0m\u001b[1;38;5;251m        \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=56791;file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=243834;file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/__init__.py#50\u001b\\\u001b[2m50\u001b[0m\u001b]8;;\u001b\\\n"
+      ]
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+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #00ff00; text-decoration-color: #00ff00\">22:21:09 </span><span style=\"color: #af5fd7; text-decoration-color: #af5fd7\">WARNING </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> ROOT minimizer not available                                                </span><a href=\"file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/minimizer/minimization.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">minimization.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/minimizer/minimization.py#1345\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1345</span></a>\n",
+       "</pre>\n"
+      ],
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+      ]
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+     "metadata": {},
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+     "data": {
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+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #00ff00; text-decoration-color: #00ff00\">         </span><span style=\"color: #af5fd7; text-decoration-color: #af5fd7\">WARNING </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> Multinest minimizer not available                                           </span><a href=\"file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/minimizer/minimization.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">minimization.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/minimizer/minimization.py#1357\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1357</span></a>\n",
+       "</pre>\n"
+      ],
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+      ]
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+     "metadata": {},
+     "output_type": "display_data"
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+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #00ff00; text-decoration-color: #00ff00\">         </span><span style=\"color: #af5fd7; text-decoration-color: #af5fd7\">WARNING </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> PyGMO is not available                                                      </span><a href=\"file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/minimizer/minimization.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">minimization.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/minimizer/minimization.py#1369\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1369</span></a>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[38;5;46m        \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m PyGMO is not available                                                     \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=966337;file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/minimizer/minimization.py\u001b\\\u001b[2mminimization.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=44696;file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/minimizer/minimization.py#1369\u001b\\\u001b[2m1369\u001b[0m\u001b]8;;\u001b\\\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #00ff00; text-decoration-color: #00ff00\">22:21:10 </span><span style=\"color: #af5fd7; text-decoration-color: #af5fd7\">WARNING </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> The cthreeML package is not installed. You will not be able to use plugins which  </span><a href=\"file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/__init__.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">__init__.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/__init__.py#94\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">94</span></a>\n",
+       "<span style=\"color: #00ff00; text-decoration-color: #00ff00\">         </span>         <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">require the C/C++ interface (currently HAWC)                                       </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">              </span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[38;5;46m22:21:10\u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m The cthreeML package is not installed. You will not be able to use plugins which \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=732039;file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=44431;file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/__init__.py#94\u001b\\\u001b[2m94\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[38;5;46m         \u001b[0m         \u001b[1;38;5;251mrequire the C/C++ interface \u001b[0m\u001b[1;38;5;251m(\u001b[0m\u001b[1;38;5;251mcurrently HAWC\u001b[0m\u001b[1;38;5;251m)\u001b[0m\u001b[1;38;5;251m                                      \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m              \u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #00ff00; text-decoration-color: #00ff00\">         </span><span style=\"color: #af5fd7; text-decoration-color: #af5fd7\">WARNING </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> Could not import plugin FermiLATLike.py. Do you have the relative instrument     </span><a href=\"file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/__init__.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">__init__.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/__init__.py#144\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">144</span></a>\n",
+       "<span style=\"color: #00ff00; text-decoration-color: #00ff00\">         </span>         <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">software installed and configured?                                                </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[38;5;46m        \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Could not import plugin FermiLATLike.py. Do you have the relative instrument    \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=291878;file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=198214;file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/__init__.py#144\u001b\\\u001b[2m144\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[38;5;46m         \u001b[0m         \u001b[1;38;5;251msoftware installed and configured?                                               \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m               \u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #00ff00; text-decoration-color: #00ff00\">         </span><span style=\"color: #af5fd7; text-decoration-color: #af5fd7\">WARNING </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> Could not import plugin HAWCLike.py. Do you have the relative instrument         </span><a href=\"file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/__init__.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">__init__.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/__init__.py#144\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">144</span></a>\n",
+       "<span style=\"color: #00ff00; text-decoration-color: #00ff00\">         </span>         <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">software installed and configured?                                                </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[38;5;46m        \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Could not import plugin HAWCLike.py. Do you have the relative instrument        \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=617541;file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=83956;file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/__init__.py#144\u001b\\\u001b[2m144\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[38;5;46m         \u001b[0m         \u001b[1;38;5;251msoftware installed and configured?                                               \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m               \u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #00ff00; text-decoration-color: #00ff00\">22:21:11 </span><span style=\"color: #af5fd7; text-decoration-color: #af5fd7\">WARNING </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> No fermitools installed                                              </span><a href=\"file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/utils/data_builders/fermi/lat_transient_builder.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">lat_transient_builder.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/utils/data_builders/fermi/lat_transient_builder.py#44\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">44</span></a>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[38;5;46m22:21:11\u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m No fermitools installed                                             \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=301673;file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/utils/data_builders/fermi/lat_transient_builder.py\u001b\\\u001b[2mlat_transient_builder.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=793142;file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/utils/data_builders/fermi/lat_transient_builder.py#44\u001b\\\u001b[2m44\u001b[0m\u001b]8;;\u001b\\\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #00ff00; text-decoration-color: #00ff00\">22:21:11 </span><span style=\"color: #af5fd7; text-decoration-color: #af5fd7\">WARNING </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> Env. variable MKL_NUM_THREADS is not set. Please set it to </span><span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0; font-weight: bold\">1</span><span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> for optimal         </span><a href=\"file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/__init__.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">__init__.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/__init__.py#387\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">387</span></a>\n",
+       "<span style=\"color: #00ff00; text-decoration-color: #00ff00\">         </span>         <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">performances in 3ML                                                               </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[38;5;46m22:21:11\u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Env. variable MKL_NUM_THREADS is not set. Please set it to \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m for optimal        \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=534420;file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=4047;file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/__init__.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[38;5;46m         \u001b[0m         \u001b[1;38;5;251mperformances in 3ML                                                              \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m               \u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #00ff00; text-decoration-color: #00ff00\">         </span><span style=\"color: #af5fd7; text-decoration-color: #af5fd7\">WARNING </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> Env. variable NUMEXPR_NUM_THREADS is not set. Please set it to </span><span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0; font-weight: bold\">1</span><span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> for optimal     </span><a href=\"file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/__init__.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">__init__.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/__init__.py#387\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">387</span></a>\n",
+       "<span style=\"color: #00ff00; text-decoration-color: #00ff00\">         </span>         <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">performances in 3ML                                                               </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">               </span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[38;5;46m        \u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m Env. variable NUMEXPR_NUM_THREADS is not set. Please set it to \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m for optimal    \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=650082;file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/__init__.py\u001b\\\u001b[2m__init__.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=732364;file:///home/sheng2/Applications/conda_envs/cosipy_yong_dev/lib/python3.10/site-packages/threeML/__init__.py#387\u001b\\\u001b[2m387\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[38;5;46m         \u001b[0m         \u001b[1;38;5;251mperformances in 3ML                                                              \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[2m               \u001b[0m\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from pathlib import Path\n",
+    "from histpy import Histogram\n",
+    "from cosipy import TransientBackgroundEstimation\n",
+    "import matplotlib.pyplot as plt"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b937a9e4-05d4-4055-b86d-8599241a0739",
+   "metadata": {},
+   "source": [
+    "## Load and examine data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "6d8d767c-f840-4dd3-860f-1865f7078110",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "data_dir = Path(\"\")  # Current directory by default. Modify if you want a different path"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "9bd49ee1-d39e-4ec6-8543-8e0da0619f79",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# Read the data\n",
+    "\n",
+    "file_name = \"GRB_bn110605183_with_bkg.hdf5\"\n",
+    "\n",
+    "data = Histogram.open(data_dir / file_name)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "e8a4a251-89c1-496c-ad3e-068bf84112ba",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# initialize background estimator\n",
+    "\n",
+    "estimator = TransientBackgroundEstimation(data)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "b74a32d9-6f8b-4022-b8c5-10c76d1ee077",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1600x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# view the full light curve\n",
+    "%matplotlib inline\n",
+    "estimator.plot_lightcurve()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "81c8d604-3d9e-462e-93b4-1a80a728ef9d",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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mpiZnnXVWgzU+//KXv+SGG25osrG23XbbJMmrr776ia/93ve+lyT5zne+k5deeqnBsVWrVuX//b//V/+5ffv22W+//bJo0aL87Gc/q2+vqanJ2Wefnddff70x5dc79thjU1JSkjvuuGODr8gnyT777JNDDz00Tz/9dE4//fR88MEH65zzl7/8JX/4wx82qZ7NzWvyAAAAADSrfffdd4PHTj755Jx88skbPP4f//Efefzxx/Nf//VfGTBgQA444IAsWbIkf/rTn/Jv//Zv+elPf7rOjvGNseOOO2bPPfdMRUVF9t577+y+++5p27ZtxowZs8Ed3OuccMIJqaioyA033JBPf/rT2W+//bL99ttn/vz5mTZtWvr3759p06bVn3/hhRfm85//fL71rW9l4sSJ6dOnT6ZOnZoVK1bkxBNPzG233dbo+9hhhx1y4IEH5oknnsgrr7ySAQMGbPDr/+tf/zqHHXZYbrzxxtxxxx0ZNmxYtt122yxdujQvvfRS3nzzzZx11lk57LDDGl3P5iYMBVq9uc/Oz9RJswu68dDKxdbyBAAAKJTnnntug8f+WdDWq1evTJkyJT/4wQ/y3//93/mv//qv7Lzzzrnmmmty1FFH5ac//Wl69uzZJHXeddddOeecc/Lkk09m6tSpWbt2bfr16/dPw9Akuf766/PZz342N954Y55//vn8+c9/ztZbb50DDjgg3/jGNxqc+9nPfjb33ntvLrnkkrzwwgvp1KlTPvvZz+aqq67K+PHjN/k+jjvuuDzxxBP1v96QrbfeOlOmTMkvfvGL/O53v8uLL76YKVOmZJtttsnOO++cM888M8ccc8wm17M5ldTW1tY2dxFbildffTXf/OY384tf/CKDBw9u7nKgaNz53Sey9O3lm2Wsbtt2ytj/e1BB+q7bQKljj8Jt0gQAADSPVatW5fXXX89OO+30sbt907R+97vf5Stf+UpOOeWU3HTTTc1dTlFrKc+AmaFAq1c3I7Sk5MPd3gulXYfSjBg7sGD9AwAA0DhTp07NZz7zmQZt06ZNyznnnJMk+epXv9ocZdECCUOBLUZ5dzMqAQAAitHIkSPTp0+f7LbbbunatWtef/31+tfYzzjjjIwcObK5S6SFEIYCAAAA0Kqdd955efDBB1NRUZElS5akc+fOOeigg3LyySd/7JqYFB9hKAAAAACt2kUXXZSLLrqoucugFWjT3AUAAAAAAGwOwlAAAAAAoCgIQwEAAACAoiAMBQAAANhMamtrm7sEaBYt5XtfGAoAAABQYKWlH+5hXVVV1cyVQPOo+96vexaaizAUAAAAoMBKS0vTqVOnLFq0KGvWrGnucmCzWrNmTRYtWpROnTo1exjavKMDAAAAFIlevXrlzTffzOuvv55u3bqlvLw8bdu2TUlJSXOXBk2utrY2a9asycqVK7N06dKsXbs2ffv2be6yhKEAAAAAm0PHjh2z00475b333svixYuzcOHC5i4JCq5t27bp2LFjtt5667Rv3765yxGGAgAAAGwu7du3T79+/VJbW5vVq1dn7dq1zV0SFEybNm3Srl27FjX7WRgKAAAAsJmVlJS0iFlyUGxsoAQAAAAAFAUzQ4GCmvvs/EydNDurV9UUbIyVi6sK1jcAAACw5RCGAgU1ddLsLH17+WYZq10HP9IAAACADZMcAAVVNyO0pCQp715WsHHadSjNiLEDC9Y/AAAA0PoJQ6HIFfo19rpX2Mu7l+XYnx5SkDEAAAAANoYwFIrc5nqN3SvsAAAAQHOTTkCR2xyvsXuFHQAAAGgJhKFAEq+xAwAAAFu+Ns1dAAAAAADA5iAMBQAAAACKgjAUAAAAACgKwlAAAAAAoCgIQwEAAACAoiAMBQAAAACKgjAUAAAAACgKwlAAAAAAoCgIQwEAAACAoiAMBQAAAACKgjAUAAAAACgKwlAAAAAAoCgIQwEAAACAoiAMBQAAAACKgjAUAAAAACgKwlAAAAAAoCgIQwEAAACAoiAMBQAAAACKgjAUAAAAACgKwlAAAAAAoCgIQwEAAACAoiAMBQAAAACKgjAUAAAAACgKwlAAAAAAoCgIQwEAAACAoiAMBQAAAACKQmlzFwBAQysXV+WOM/5UsP7bdSjNiLEDs9M+fQs2BgAAALREwlCAFqJdh9IkVamtTVYsqirgSFWpuHO2MBQAAICiIwwFaCFGjB2YijtnZ/WqmoKNsXLxh2FrIccAAACAlkoYCtBC7LRP34LP1rzjjD8VeNYpAAAAtFw2UAIAAAAAioIwFAAAAAAoCsJQAAAAAKAoCEMBAAAAgKIgDAUAAAAAioIwFAAAAAAoCsJQAAAAAKAoCEMBAAAAgKIgDAUAAAAAioIwFAAAAAAoCsJQAAAAAKAoCEMBAAAAgKIgDAUAAAAAikJpcxewPhMnTsxLL72UuXPnZsmSJamurk6PHj0ybNiwHHPMMRkwYMB6r5s8eXLuueeezJs3L6WlpfnUpz6VE044IUOGDNngWNOnT8+ECRMyc+bM1NTUpH///jnqqKNy2GGHFer2AAAAAIBm0CLD0F//+tdZuXJlBgwYkJ133jlJ8sYbb+Shhx7KI488kssvvzz7779/g2uuv/76TJo0KWVlZdlrr71SXV2dioqKVFRU5NJLL82BBx64zjiPPfZYLrnkkqxduzZDhw5Nt27dMnXq1FxxxRWZM2dOTj/99M1yvwAAAABA4bXIMPSKK67IoEGDUlZW1qD9nnvuybXXXpurr746kyZNSmnph+VXVFRk0qRJ6datW2688cZsv/32SZIZM2bkrLPOypVXXplhw4alS5cu9X198MEHueqqq7JmzZpcdtllOfjgg5MkixYtyumnn56JEydm//33z/DhwzfTXQMAAAAAhdQi1wwdMmTIOkFokhx55JHZbrvtsmjRosybN6++feLEiUmS448/vj4ITZI99tgjY8aMSWVlZR544IEGfd1///1Zvnx5DjjggPogNEl69OiRU089tUG/AAAAAEDr1yLD0I/Ttm3bJKmfFVpVVZUXX3wxSTJq1Kh1zq9rmzJlSoP2Z555ZoPX7Lfffmnfvn0qKipSVVXVRJUDAAAAAM2pVYWhDz30UN58883069cv/fr1S5L87W9/S3V1dbbaaqtsvfXW61wzaNCgJMmcOXMatNd9rjv+Ue3atcvOO++c6urqvPXWW019GwAAAABAM2iRa4bW+e1vf5vXX389q1atyrx58/L666+nV69eueiii+pniL777rtJkt69e6+3j/Ly8nTu3DnLli3LihUr0rFjxyxfvjyVlZUfe13v3r0za9asvPPOOxvcvR4AAAAAaD1adBj65z//OVOnTq3/3KdPn5x//vkZPHhwfdvKlSuTJB06dNhgP+Xl5amsrKwPQ+uuSbLetUk/2t+KFSs22O/ChQvz/vvv13/+6DqmAAAAAEDL0qLD0GuvvTZJsmzZssydOze33XZbzjzzzJx88sk54YQTmrm65N5778348eObuwwAAAAAYCO06DC0TpcuXTJ06NBcffXVOfXUU3PLLbdkr732ym677Zby8vIkyapVqzZ4fd1M0I4dOyZJ/TXJhxsw1W3G9FF1/dVdsz5jxozJyJEj6z/Pmzcvl19++Se4MwAAAABgc2kVYWid0tLSHHLIIXn11VczZcqU7Lbbbtlmm22SJAsWLFjvNStXrkxlZWW6dOlSH2x26tQpnTt3TmVlZRYsWJBOnTqtc11df3369NlgPb169UqvXr029bYAAAAAgM2gVe0mnyTdunVLkixZsiRJssMOO6R9+/ZZsmTJegPR1157LUnW2QSp7nPd8Y+qqanJ3Llz0759+/pd6wEAAACA1q3VhaHTpk1Lkmy77bZJPtwAafjw4UmSRx99dJ3zH3vssSTJ/vvv36B9v/32a3D8o6ZMmZLq6uqMGDFigxssAQAAAACtS4sLQ6dPn57nnnsua9eubdBeU1OTu+66K3/84x9TVlaWQw45pP7Y0UcfnSS5/fbb8+abb9a3z5gxI/fdd186d+6cww8/vEF/RxxxRDp16pSnnnoqjz/+eH374sWLc9NNNzXoFwAAAABo/VrcmqFvvfVWrrzyynTr1i2DBw9O165ds3Tp0sydOzfvv/9+2rdvn/POO69+rdAkGTFiRL785S9n0qRJOemkkzJixIisXr06FRUVSZLzzjsvXbp0aTBO165dc+655+biiy/OhRdemGHDhqVbt26pqKhIZWVlxo0bVz/jFAAAAABo/VpcGDp06NAcf/zxmTZtWubMmZOlS5emXbt26dOnT0aNGpUvfelL613H88wzz8zAgQNz9913p6KiIqWlpRkxYkROOOGEDBkyZL1jjRo1KjfccEMmTJiQl19+OTU1Ndlxxx1z5JFHZvTo0YW+VQAAAABgM2pxYei2226bb37zm426dvTo0Z84xBwyZEiuueaaRo0HAAAAALQeLW7NUAAAAACAQhCGAgAAAABFQRgKAAAAABQFYSgAAAAAUBSEoQAAAABAURCGAgAAAABFQRgKAAAAABQFYSgAAAAAUBSEoQAAAABAURCGAgAAAABFQRgKAAAAABQFYSgAAAAAUBSEoQAAAABAURCGAgAAAABFQRgKAAAAABQFYSgAAAAAUBSEoQAAAABAURCGAgAAAABFQRgKAAAAABQFYSgAAAAAUBSEoQAAAABAURCGAgAAAABFQRgKAAAAABQFYSgAAAAAUBSEoQAAAABAURCGAgAAAABFQRgKAAAAABQFYSgAAAAAUBSEoQAAAABAURCGAgAAAABFQRgKAAAAABQFYSgAAAAAUBSEoQAAAABAURCGAgAAAABFQRgKAAAAABQFYSgAAAAAUBSEoQAAAABAURCGAgAAAABFQRgKAAAAABQFYSgAAAAAUBSEoQAAAABAURCGAgAAAABFQRgKAAAAABQFYSgAAAAAUBSEoQAAAABAURCGAgAAAABFQRgKAAAAABQFYSgAAAAAUBSEoQAAAABAURCGAgAAAABFQRgKAAAAABQFYSgAAAAAUBSEoQAAAABAURCGAgAAAABFQRgKAAAAABQFYSgAAAAAUBSEoQAAAABAURCGAgAAAABFQRgKAAAAABQFYSgAAAAAUBSEoQAAAABAURCGAgAAAABFQRgKAAAAABQFYSgAAAAAUBSEoQAAAABAURCGAgAAAABFQRgKAAAAABQFYSgAAAAAUBSEoQAAAABAURCGAgAAAABFQRgKAAAAABQFYSgAAAAAUBSEoQAAAABAURCGAgAAAABFQRgKAAAAABSF0uYuANiwuc/Oz9RJs7N6VU3Bxli5uKpgfQMAAAC0JC0uDF21alWef/75PP3005k+fXrefffdtGnTJtttt10OPvjgjBs3Lh07dmxwza233prx48dvsM9jjz02p5xyynqPTZ8+PRMmTMjMmTNTU1OT/v3756ijjsphhx3WlLcFjTJ10uwsfXv5ZhmrXYcW9+MAAAAAoEm1uPTj4YcfztVXX50k6d+/f0aOHJnly5dnxowZufXWW/Pwww/nhhtuSPfu3de5dsiQIdluu+3WaR88ePB6x3rsscdyySWXZO3atRk6dGi6deuWqVOn5oorrsicOXNy+umnN+3NwSdUNyO0pCQp715WsHHadSjNiLEDC9Y/AAAAQEvQ4sLQtm3b5l/+5V8yduzY7LjjjvXtCxcuzLnnnpvZs2fnhhtuyIUXXrjOtUcccURGjx69UeN88MEHueqqq7JmzZpcdtllOfjgg5MkixYtyumnn56JEydm//33z/Dhw5vkvmBTlHcvy7E/PaS5ywAAAABo1VrcBkqjR4/OOeec0yAITZJevXrl29/+dpLkiSeeyOrVqzdpnPvvvz/Lly/PAQccUB+EJkmPHj1y6qmnJkkmTpy4SWMAAAAAAC1HiwtDP84uu+ySJKmurs7SpUs3qa9nnnkmSTJq1Kh1ju23335p3759KioqUlVlcxkAAAAA2BK0uNfkP87bb7+dJCktLU3Xrl3XOf7CCy9k9uzZqa6uTu/evbPvvvtucL3QOXPmJEkGDRq0zrF27dpl5513zqxZs/LWW29lwIABTXgXAAAAAEBzaFVh6KRJk5Ike++9d9q3b7/O8YceeqjB51tuuSUHH3xwzjvvvAY70C9fvjyVlZVJkt69e693rN69e2fWrFl55513NhiGLly4MO+//37953nz5n2yGwIAAAAANptWE4Y+88wzeeCBB1JaWpqTTz65wbF+/frltNNOy7777pttttkmy5Yty1/+8pfcfPPNefzxx7N27dr88Ic/rD9/5cqV9b8uK1v/Dt0dOnRIkqxYsWKDNd17770ZP378JtwVAAAAALC5tIowdN68ebn88stTW1ubU089tX7t0Dqf+9znGnwuLy/PoYcemuHDh+frX/96nnzyybz88svZfffdm7SuMWPGZOTIkevUCQAAAAC0PC1+A6UFCxbknHPOybJlyzJu3LiMHTt2o6/t1atXRo8enSR57rnn6tvLy8vrf72hDZJWrVqVJA1er19f/4MHD67/r3///htdGwAAAACwebXoMPSDDz7I2WefnXfeeSdf+MIXcvrpp3/iPvr165ckDdb27NSpUzp37pzkw7B1fera+/Tp84nHBAAAAABanhYbhq5YsSLnnHNO3njjjRx00EE555xzUlJS8on7WbZsWZKGs0GT1G+K9Nprr61zTU1NTebOnZv27dvXh6kAAAAAQOvWIsPQ6urqnH/++XnllVey995756KLLkrbtm0/cT+1tbV58sknkySDBg1qcGy//fZLkjz22GPrXDdlypRUV1dnxIgRG9xgCQAAAABoXVpcGLpmzZpccskleeGFF7Lnnnvm8ssvT7t27TZ4/pIlS3L33Xevs+v7ihUr8qMf/SgzZ85Mjx49ctBBBzU4fsQRR6RTp0556qmn8vjjj9e3L168ODfddFOS5Oijj27COwMAAAAAmlOL203+7rvvrp/N2a1bt/z4xz9e73mnnXZattpqq6xcuTI/+clP8p//+Z/Zdddd07NnzyxZsiSzZ8/O0qVL07lz51x22WXp0KFDg+u7du2ac889NxdffHEuvPDCDBs2LN26dUtFRUUqKyszbty4DB8+vOD3CwAAAABsHi0uDK1b4zNJfSi6Pl//+tez1VZbpVu3bjn22GMzc+bMvPXWW3n55ZfTpk2b9O3bN4cddljGjRuX3r17r7ePUaNG5YYbbsiECRPy8ssvp6amJjvuuGOOPPLI+l3oAQAAAIAtQ4sLQ7/xjW/kG9/4xkaf37Fjx5xyyimNHm/IkCG55pprGn09AAAAANA6tLg1QwEAAAAACkEYCgAAAAAUBWEoAAAAAFAUhKEAAAAAQFEQhgIAAAAARUEYCgAAAAAUBWEoAAAAAFAUhKEAAAAAQFEQhgIAAAAARUEYCgAAAAAUBWEoAAAAAFAUhKEAAAAAQFEQhgIAAAAARUEYCgAAAAAUBWEoAAAAAFAUhKEAAAAAQFEQhgIAAAAARUEYCgAAAAAUBWEoAAAAAFAUhKEAAAAAQFEQhgIAAAAARUEYCgAAAAAUBWEoAAAAAFAUhKEAAAAAQFEQhgIAAAAARUEYCgAAAAAUBWEoAAAAAFAUhKEAAAAAQFEQhgIAAAAARUEYCgAAAAAUBWEoAAAAAFAUhKEAAAAAQFEQhgIAAAAARUEYCgAAAAAUBWEoAAAAAFAUhKEAAAAAQFEQhgIAAAAARUEYCgAAAAAUBWEoAAAAAFAUhKEAAAAAQFEQhgIAAAAARUEYCgAAAAAUhdKNOendd9/d5IE6d+6cTp06bXI/AAAAAACNsVFh6Lhx41JSUrJJA33ta1/L1772tU3qAwAAAACgsTYqDE2SAQMGZJdddvnEA9TW1uahhx76xNcBAAAAADSljQ5DDzzwwEbP7BSGAgAAAADNbaM2UOrevXvKy8sbPcimXg8AAAAAsKk2ambof/3Xf23SIJt6PQAAAADAptqomaEAAAAAAK2dMBQAAAAAKAobvYHSP1q9enWefPLJzJo1K5WVlVm7du16z/ve977X6OIAAAAAAJpKo8LQd955J9/5znfy9ttvp7a2doPnlZSUCEMBAAAAgBahUWHoDTfckL///e/53Oc+l8MPPzy9e/dO27Ztm7o2AAAAAIAm06gw9MUXX8xnPvOZXHDBBU1dDwAAAABAQTRqA6W1a9dm4MCBTV0LAAAAAEDBNCoM/dSnPpV58+Y1dS0AAAAAAAXTqDD03/7t3/LCCy/ksccea+JyAAAAAAAKY6PWDB0/fvw6bcOHD8/FF1+coUOHZtCgQenUqdM655SUlOTEE0/c5CIBAAAAADbVRoWhv/rVrzZ4bNq0aZk2bdp6jwlDAQAAAICWYqPC0Ouuu67QdQAAAAAAFNRGhaHDhg0rcBkAAAAAAIXVqA2UAAAAAABam42aGbohTzzxRCZPnpzZs2dn+fLl6dSpUwYNGpTRo0fnwAMPbKoaAQAAAAA2WaPC0Jqamlx22WV5/PHHU1tbm7Zt26Zr165ZtGhRnn766UyZMiUHH3xwfvCDH6S0dJPyVgAAAACAJtGopPI3v/lNHnvssQwdOjTf/OY3s/vuu6dNmzZZu3ZtZsyYkV/84hd5/PHHs/POO9tNHgAAAABoERq1ZuiDDz6YHXbYIT/+8Y8zZMiQtGnzYTdt2rTJnnvumWuvvTb9+vXLgw8+2KTFAgAAAAA0VqPC0Pfffz/777//Bl+BLy0tzciRI/P+++9vUnEAAAAAAE2lUWHo1ltvnZUrV37sOStXrsw222zTqKIAAAAAAJpao8LQI444Io8++mgWLly43uMLFizIo48+miOOOGKTigMAAAAAaCqN2kDpf/2v/5Xp06fn5JNPzpe//OXsueee6d69exYvXpyXXnopkyZNypAhQzJq1Ki8++67Da41WxQAAAAAaA6NCkOPOeaYlJSUpLa2Nr/85S/XOV5bW5spU6ZkypQpDdpLSkry6KOPNq5SAAAAAIBN0Kgw9POf/3xKSkqauhYAAAAAgIJpVBh6/vnnN3UdAAAAAAAF1agNlAAAAAAAWhthKAAAAABQFDbqNflTTz01RxxxRA4//PBGDfJJrl+1alWef/75PP3005k+fXrefffdtGnTJtttt10OPvjgjBs3Lh07dlzvtZMnT84999yTefPmpbS0NJ/61KdywgknZMiQIRscb/r06ZkwYUJmzpyZmpqa9O/fP0cddVQOO+ywRt0rAAAAANAybdTM0JkzZ2bBggWNHuSTXP/www/nggsuyIMPPpg2bdpk5MiR2XPPPTN//vzceuut+T//5/9k8eLF61x3/fXX58orr8zrr7+ez3zmM9ltt91SUVGRM888M08++eR6x3rsscdy5pln5s9//nMGDBiQvffeO2+99VauuOKK/OxnP2v0/QIAAAAALc9Gb6D04osvNnqQT7LzfNu2bfMv//IvGTt2bHbcccf69oULF+bcc8/N7Nmzc8MNN+TCCy+sP1ZRUZFJkyalW7duufHGG7P99tsnSWbMmJGzzjorV155ZYYNG5YuXbrUX/PBBx/kqquuypo1a3LZZZfl4IMPTpIsWrQop59+eiZOnJj9998/w4cPb/R9AwAAAAAtx0aHodOmTcu0adMKWMqHRo8endGjR6/T3qtXr3z729/OaaedlieeeCKrV69Ou3btkiQTJ05Mkhx//PH1QWiS7LHHHhkzZkzuuuuuPPDAAznmmGPqj91///1Zvnx5DjjggPogNEl69OiRU089Nd///vczceJEYSgAAAAAbCE2Kgy97rrrNnmgPn36bHIfu+yyS5Kkuro6S5cuTa9evVJVVVU/a3XUqFHrXDNq1KjcddddmTJlSoMw9JlnntngNfvtt1/at2+fioqKVFVVpaysbJNrBwAAAACa10aFocOGDStwGRvn7bffTpKUlpama9euSZK//e1vqa6uzlZbbZWtt956nWsGDRqUJJkzZ06D9rrPdcc/ql27dtl5550za9asvPXWWxkwYECT3gcAAAAAsPlt1AZKLcWkSZOSJHvvvXfat2+fJHn33XeTJL17917vNeXl5encuXOWLVuWFStWJEmWL1+eysrKj72urv2dd95puhsAAAAAAJrNRq8Z2tyeeeaZPPDAAyktLc3JJ59c375y5cokSYcOHTZ4bXl5eSorK7NixYp07Nix/pokG3wFvq6/ugB1fRYuXJj333+//vO8efM27mYAAAAAgM2uVYSh8+bNy+WXX57a2tqceuqp9WuHNrd7770348ePb+4yAAAAAICN0OLD0AULFuScc87JsmXLMm7cuIwdO7bB8fLy8iTJqlWrNthH3UzQjh07NrgmSaqqqlJauu6Xoa6/umvWZ8yYMRk5cmT957rQFgAAAABoeVp0GPrBBx/k7LPPzjvvvJMvfOELOf3009c5Z5tttknyYWi6PitXrkxlZWW6dOlSH2x26tQpnTt3TmVlZRYsWJBOnTqtc11df3369Nlgfb169UqvXr0+8X0BAAAAAJtfi91AacWKFTnnnHPyxhtv5KCDDso555yTkpKSdc7bYYcd0r59+yxZsmS9gehrr72WJOvsCF/3ue74R9XU1GTu3Llp3759+vXr1xS3AwAAAAA0sxYZhlZXV+f888/PK6+8kr333jsXXXRR2rZtu95zy8rKMnz48CTJo48+us7xxx57LEmy//77N2jfb7/9Ghz/qClTpqS6ujojRozY4AZLAAAAAEDr0qgwdM6cOXnggQeyfPny+raqqqr86Ec/ylFHHZWvfOUr+e///u9GFbRmzZpccskleeGFF7Lnnnvm8ssvT7t27T72mqOPPjpJcvvtt+fNN9+sb58xY0buu+++dO7cOYcffniDa4444oh06tQpTz31VB5//PH69sWLF+emm25q0C8AAAAA0Po1as3QCRMmZPr06fnCF75Q3/bzn/889957b8rLy7N06dJce+212XbbbbPXXnt9or7vvvvuPPnkk0mSbt265cc//vF6zzvttNOy1VZbJUlGjBiRL3/5y5k0aVJOOumkjBgxIqtXr05FRUWS5LzzzkuXLl0aXN+1a9ece+65ufjii3PhhRdm2LBh6datWyoqKlJZWZlx48bVzzgFAAAAAFq/RoWhr7zySoYPH16/hmdNTU0mT56c3XbbLdddd12WLVuWk08+OZMmTfrEYeiyZcvqf10Xiq7P17/+9fowNEnOPPPMDBw4MHfffXcqKipSWlqaESNG5IQTTsiQIUPW28eoUaNyww03ZMKECXn55ZdTU1OTHXfcMUceeWRGjx79ieoGAAAAAFq2RoWhS5cuzdZbb13/edasWVm+fHn+9V//NWVlZSkrK8vIkSPz7LPPfuK+v/GNb+Qb3/hGY8rK6NGjP3GIOWTIkFxzzTWNGg8AAAAAaD0atWZo27Zts3r16vrP06ZNS0lJSYPXyrt165alS5dueoUAAAAAAE2gUTND+/TpkxdffLH+86OPPpq+ffumT58+9W0LFixIt27dNr1CAFqNuc/Oz9RJs7N6VU1Bx2nXoTQjxg7MTvv0Leg4AAAAbFkaFYZ+7nOfy0033ZR/+7d/S7t27TJnzpwcf/zxDc6ZO3du+vXr1yRFAtA6TJ00O0vfXr4ZRqpKxZ2zhaEAAAB8Io0KQ4866qi88sorefzxx1NbW5t99903X/3qV+uPv/766/nrX//a6LU/AWid6maElpQk5d3LCjLGysVVqa1NwWefAgAAsOVpVBjavn37XHLJJVm+fHlKSkrSsWPHBse7d++eW265pcFr8wAUj/LuZTn2p4cUpO87zvhTViyqKkjfAAAAbNkatYHStGnT8u6776ZTp07rBKFJstVWW6VLly7561//uskFAgAAAAA0hUaFod/61rcyefLkjz3noYceyre+9a3GdA8AAAAA0OQaFYbW1tZu1DklJSWN6R4AAAAAoMk1KgzdGG+99VY6depUqO4BAAAAAD6Rjd5A6T/+4z8afH7yySfzzjvvrHPemjVr8t577+Wll17KPvvss+kVAgAAAAA0gY0OQz+6RmhJSUn++te/bnCDpJKSkuy6664544wzNr1CAAAAAIAmsNFh6MSJE5N8uBboMccck7Fjx+bLX/7yOue1adMmXbp0SXl5edNVCQAAAACwiTY6DO3Tp0/9r7/3ve9l0KBBDdoAaD1WLq7KHWf8qSD9AgAAQEu10WHoR40ePbqp6wBgM2jXoTRJVWprkxWLChdcfjgOAAAAtCyb9LfVmTNnZtasWamsrMzatWvXOV5SUpITTzxxU4YAoAmNGDswFXfOzupVNQUbo12H0owYO7Bg/QMAAEBjNSoM/eCDD3L++ednxowZqa2t3eB5wlCAlmWnffpmp336NncZAAAA0CwaFYb+9Kc/zfTp0zNs2LAcdthh2XrrrdO2bdumrg0AAAAAoMk0Kgx95plnsttuu+UnP/lJSkpKmromAAAAAIAm16YxF1VVVWXo0KGCUAAAAACg1WhUGLrLLrvknXfeaepaAAAAAAAKplFh6Ne+9rU8/fTTefnll5u6HgAAAACAgmjUmqGLFi3KvvvumzPPPDOHHnpoBg4cmE6dOq333MMOO2yTCgQAAAAAaAqNCkOvvPLKlJSUpLa2NpMnT87kyZPXWT+0trY2JSUlwlAAAAAAoEVoVBj6ve99r6nrAAAAAAAoqEaFoaNHj27qOgAAAAAACqpRGygBAAAAALQ2jZoZ+u677270udtss01jhgAAAAAAaFKNCkPHjRu3zoZJ61NSUpJHH320MUMAAAAAADSpRoWhn//859cbhlZWVmbOnDmZP39+hg0blj59+mxygQAAAAAATaFRYej555+/wWO1tbX53e9+l9/+9rc599xzG10YAAAAAEBTavINlEpKSvKVr3wlO+20U2688cam7h4AAAAAoFEKtpv84MGD88ILLxSqewAAAACAT6RgYejf//73rFmzplDdAwAAAAB8Io1aM3RD1q5dmwULFuQPf/hDnn766Xz6059uyu4BAAAAABqtUWHowQcfvN7d5OvU1tamS5cuOf300xtdGAAAAABAU2pUGDp06ND1hqElJSXp0qVLdt1113zhC19I9+7dN7lAAAAAAICm0Kgw9Prrr2/qOqDVmfvs/EydNDurV9UUbIyVi6sK1jcAAABAsWnSNUOhmEydNDtL316+WcZq18GjCgAAALCpNjlhmT59embPnp0VK1akY8eOGThwYIYMGdIUtUGLVjcjtKQkKe9eVrBx2nUozYixAwvWP7RWKxdX5Y4z/lSw/uuevZ326VuwMQAAANi8Gh2GTp8+Pf/xH/+Rv//970k+3DSpbh3Rfv365Xvf+1722GOPpqkSWrDy7mU59qeHNHcZUDQ+nCldldraZMWiQi4lUZWKO2cLQwEAALYgjQpDX3/99Xz3u9/NqlWrMmLEiAwfPjw9e/bMokWL8uKLL+b555/Pd7/73dx8883Zcccdm7hkAIrZiLEDU3Fn4dfrra1NQccAAABg82tUGDp+/PisXr06V199dfbZZ58Gx4477rg899xzOe+88zJ+/PhcfPHFTVEnACRJdtqnb8Fna95xxp8KPOsUAACA5tCmMRdNmzYto0aNWicIrbPPPvtk1KhRefHFFzepOAAAAACAptKoMHT58uXp2/fjZ+X07ds3y5dvnp22AQAAAAD+mUaFoT179szLL7/8sefMnDkzPXv2bFRRAAAAAABNrVFh6MiRIzNt2rT88pe/TFVVwzXVqqqqcuutt+bFF1/MAQcc0CRFAgAAAABsqkZtoHTiiSfmmWeeya9//evce++92W233dK9e/csXrw4s2bNypIlS7LtttvmxBNPbOp6AQAAAAAapVFhaLdu3XLTTTfl5ptvziOPPJJnn322/lj79u0zevTonHLKKenatWuTFQoAAAAAsCkaFYYmyVZbbZXvfe97+e53v5t58+ZlxYoV6dixY/r375/S0kZ3CwAAAABQEJucWpaWlmbAgAFNUQsAAAAAQMF8og2UJkyYkJ///OepqanZ4DmrV6/Oz3/+8/z617/e5OIAAAAAAJrKRoehFRUVufXWW9O1a9ePfQ2+Xbt26datW375y1/mhRdeaJIiAQAAAAA21UaHoQ899FC6dOmSo4466p+ee+SRR6ZLly6ZPHnyJhUHAAAAANBUNjoMnTFjRj7zmc+kffv2//Tc9u3bZ8SIEZk+ffomFQcAAAAA0FQ2OgxduHBhtt12243uuG/fvnn//fcbVRQAAAAAQFPb6DC0TZs2H7tx0j+qqalJmzafaH8mAAAAAICC2ei0smfPnnn99dc3uuPXX389vXr1alRRAAAAAABNbaPD0D333DMvvPBC5s+f/0/PnT9/fl544YUMHTp0k4oDAAAAAGgqGx2GHnnkkampqcmFF16YJUuWbPC8pUuX5qKLLsqaNWvyr//6r01RIwAAAADAJivd2BMHDx6csWPH5s4778wJJ5yQf/3Xf83w4cPTu3fvJB9usDR16tTcd999WbJkScaNG5fBgwcXrHAAAAAAgE9io8PQJDn99NPTvn37/Pa3v83tt9+e22+/vcHx2tratGnTJl/96ldz8sknN2mhAAAAAACb4hOFoSUlJfk//+f/5PDDD8+DDz6YGTNmZNGiRUmSHj16ZMiQIRk9enS22267ghQLAAAAANBYnygMrbPddtvlm9/8ZlPXAgAAAABQMBu9gRIAAAAAQGsmDAUAAAAAioIwFAAAAAAoCsJQAAAAAKAoCEMBAAAAgKIgDAUAAAAAioIwFAAAAAAoCsJQAAAAAKAoCEMBAAAAgKIgDAUAAAAAioIwFAAAAAAoCsJQAAAAAKAoCEMBAAAAgKJQ2twFrM+rr76a559/Pq+88kpmzZqVBQsWJEmeeOKJ9Z5/6623Zvz48Rvs79hjj80pp5yy3mPTp0/PhAkTMnPmzNTU1KR///456qijcthhh23yfQAAAAAALUeLDENvu+22PPXUU5/4uiFDhmS77bZbp33w4MHrPf+xxx7LJZdckrVr12bo0KHp1q1bpk6dmiuuuCJz5szJ6aef/olrAAAAAABaphYZhu6+++4ZMGBAdt111+y66645+uijU11d/U+vO+KIIzJ69OiNGuODDz7IVVddlTVr1uSyyy7LwQcfnCRZtGhRTj/99EycODH7779/hg8fvkn3AgAAAAC0DC0yDD3uuOMKPsb999+f5cuX54ADDqgPQpOkR48eOfXUU/P9738/EydOFIYCAAAAwBaiaDdQeuaZZ5Iko0aNWufYfvvtl/bt26eioiJVVVWbuTIAAAAAoBBa5MzQxnrhhRcye/bsVFdXp3fv3tl33303uF7onDlzkiSDBg1a51i7du2y8847Z9asWXnrrbcyYMCAgtYNAAAAABTeFhWGPvTQQw0+33LLLTn44INz3nnnpWPHjvXty5cvT2VlZZKkd+/e6+2rd+/emTVrVt55550NhqELFy7M+++/X/953rx5m3oLAAAAAECBbBFhaL9+/XLaaadl3333zTbbbJNly5blL3/5S26++eY8/vjjWbt2bX74wx/Wn79y5cr6X5eVla23zw4dOiRJVqxYscFx77333owfP75pbgIAAAAAKKgtIgz93Oc+1+BzeXl5Dj300AwfPjxf//rX8+STT+bll1/O7rvv3qTjjhkzJiNHjqz/PG/evFx++eVNOgYAAAAA0DS26A2UevXqldGjRydJnnvuufr28vLy+l9vaIOkVatWJUmD1+vX1//gwYPr/+vfv39TlA0AAAAAFMAWHYYmH75Cn6TB2p6dOnVK586dkyQLFixY73V17X369ClwhQAAAADA5rDFh6HLli1L0nA2aJL6TZFee+21da6pqanJ3Llz0759+/owFQAAAABo3bboMLS2tjZPPvlkkmTQoEENju23335Jkscee2yd66ZMmZLq6uqMGDFigxssAQAAAACtS6sPQ5csWZK77757nV3fV6xYkR/96EeZOXNmevTokYMOOqjB8SOOOCKdOnXKU089lccff7y+ffHixbnpppuSJEcffXThbwAAAAAA2Cxa5G7yzzzzTG677bb6z6tXr06SnHLKKfVtJ554Yvbbb7+sXLkyP/nJT/Kf//mf2XXXXdOzZ88sWbIks2fPztKlS9O5c+dcdtll6dChQ4MxunbtmnPPPTcXX3xxLrzwwgwbNizdunVLRUVFKisrM27cuAwfPnzz3DAAAAAAUHAtMgxdsmRJZs6cuU77R9uWLFmSJOnWrVuOPfbYzJw5M2+99VZefvnltGnTJn379s1hhx2WcePGpXfv3usdZ9SoUbnhhhsyYcKEvPzyy6mpqcmOO+6YI488sn4XegAAAABgy9Aiw9DRo0dvdBjZsWPHBjNGP6khQ4bkmmuuafT1AAAAAEDr0OrXDAUAAAAA2BjCUAAAAACgKAhDAQAAAICiIAwFAAAAAIqCMBQAAAAAKArCUAAAAACgKAhDAQAAAICiIAwFAAAAAIqCMBQAAAAAKArCUAAAAACgKAhDAQAAAICiIAwFAAAAAIqCMBQAAAAAKArCUAAAAACgKAhDAQAAAICiIAwFAAAAAIqCMBQAAAAAKArCUAAAAACgKAhDAQAAAICiIAwFAAAAAIqCMBQAAAAAKArCUAAAAACgKAhDAQAAAICiIAwFAAAAAIpCaXMXAAAUxtxn52fqpNlZvaqmYGO061CaEWMHZqd9+hZsDAAAgKYiDAWALdTUSbOz9O3lBR6lKhV3zhaGAgAArYIwFAC2UHUzQktKkvLuZU3e/8rFVamtTUFnngIAADQlYSgAbOHKu5fl2J8e0uT93nHGn7JiUVWT9wsAAFAoNlACAAAAAIqCMBQAAAAAKApekweAZrA5dnpfubj1v8K+Ob5OSdKuQ2lGjB1oI6iP4fcCAIAtgTAUAJrB5tnp/UPtOrTe/91vvq9TVSrunC2A+xh+LwAA2BK03r8dAUArVuid3uvUzbJrrTbH12nl4qrU1qbgMx5bO78XAABsCYShANCMCrXT+5amkF+nO874U1Ysav1LCmwufi8AAGjNbKAEAAAAABQFYSgAAAAAUBSEoQAAAABAURCGAgAAAABFQRgKAAAAABQFu8kDACRZubgqd5zxp4L1365DaUaMHZid9ulbkP7nPjs/UyfNzupVNQXpf+Viu7wDAND6CUMBgKLWrkNpkqrU1iYrFhUy8KtKxZ2zCxaGTp00O0vfXl6Qvj/qw68XAAC0Tv40CwAUtRFjB6bizsLNqEw+nFVZW5uCjlHXd0lJUt69rCBj1M1uBQCA1koYCgAUtZ326Vuw2Zp17jjjTwWedfo/yruX5difHrJZxgIAgNbGBkoAAAAAQFEQhgIAAAAARUEYCgAAAAAUBWEoAAAAAFAUhKEAAAAAQFEQhgIAAAAARUEYCgAAAAAUBWEoAAAAAFAUhKEAAAAAQFEQhgIAAAAARUEYCgAAAAAUBWEoAAAAAFAUhKEAAAAAQFEobe4CoBDmPjs/UyfNzupVNQUbY+XiqoL1DQAAAEDTE4ayRZo6aXaWvr18s4zVroPHCAAAAKA1kOKwRaqbEVpSkpR3LyvYOO06lGbE2IEF6x8AAACApiMMZYtW3r0sx/70kOYuAwAAAIAWwAZKAAAAAEBREIYCAAAAAEVBGAoAAAAAFAVrhgLABqxcXJU7zvhTwfqm+PieAgCA5iUMBYB/0K5DaZKq1NYmKxYVNmD6cCy2dL6nAACgZfCnZQD4ByPGDkzFnbOzelVNQcdp16E0I8YOLOgYtAy+pwAAoGUQhgLAP9hpn77ZaZ++zV0GWxDfUwAA0DLYQAkAAAAAKArCUAAAAACgKAhDAQAAAICiIAwFAAAAAIqCMBQAAAAAKArCUAAAAACgKAhDAQAAAICiIAwFAAAAAIpCaXMXsD6vvvpqnn/++bzyyiuZNWtWFixYkCR54oknPva6yZMn55577sm8efNSWlqaT33qUznhhBMyZMiQDV4zffr0TJgwITNnzkxNTU369++fo446KocddliT3hMAAAAA0LxaZBh622235amnnvpE11x//fWZNGlSysrKstdee6W6ujoVFRWpqKjIpZdemgMPPHCdax577LFccsklWbt2bYYOHZpu3bpl6tSpueKKKzJnzpycfvrpTXVLAABspJWLq3LHGX8qWP/tOpRmxNiB2WmfvgUbAwCAlqlFhqG77757BgwYkF133TW77rprjj766FRXV2/w/IqKikyaNCndunXLjTfemO233z5JMmPGjJx11lm58sorM2zYsHTp0qX+mg8++CBXXXVV1qxZk8suuywHH3xwkmTRokU5/fTTM3HixOy///4ZPnx4YW8WAIAkH4aUSVVqa5MVi6oKOFJVKu6cLQwFAChCLTIMPe644z7R+RMnTkySHH/88fVBaJLsscceGTNmTO6666488MADOeaYY+qP3X///Vm+fHkOOOCA+iA0SXr06JFTTz013//+9zNx4kRhKADAZjJi7MBU3Dk7q1fVFGyMlYs/DFsLOQYAAC1XiwxDP4mqqqq8+OKLSZJRo0atc3zUqFG56667MmXKlAZh6DPPPLPBa/bbb7+0b98+FRUVqaqqSllZWUFqBwDgf+y0T9+Cz9a844w/FXjWKQAALVmr303+b3/7W6qrq7PVVltl6623Xuf4oEGDkiRz5sxp0F73ue74R7Vr1y4777xzqqur89ZbbxWgagAAAABgc2v1Yei7776bJOndu/d6j5eXl6dz585ZtmxZVqxYkSRZvnx5KisrP/a6uvZ33nmnqUsGAAAAAJpBq39NfuXKlUmSDh06bPCc8vLyVFZWZsWKFenYsWP9NUk2+Ap8XX91Aer6LFy4MO+//37953nz5n2i2gFgS1DInb9XLvY6MwAA0HRafRjanO69996MHz++ucsAgGax+Xb+rhsLAABg07T6v1mUl5cnSVatWrXBc+pmgnbs2LHBNcmHGzCVlq77Zajrr+6a9RkzZkxGjhxZ/3nevHm5/PLLP0H1ANB6bY6dv5MPg9ARYwcWdAwAAKA4tPowdJtttkmSLFiwYL3HV65cmcrKynTp0qU+2OzUqVM6d+6cysrKLFiwIJ06dVrnurr++vTps8Gxe/XqlV69em3qLQBAq7Q5dv4GAABoSq1+A6Uddtgh7du3z5IlS9YbiL722mtJkgEDBjRor/tcd/yjampqMnfu3LRv3z79+vUrQNUAAAAAwObW6sPQsrKyDB8+PEny6KOPrnP8scceS5Lsv//+Ddr322+/Bsc/asqUKamurs6IESM2uMESAAAAANC6tPowNEmOPvroJMntt9+eN998s759xowZue+++9K5c+ccfvjhDa454ogj0qlTpzz11FN5/PHH69sXL16cm266qUG/AAAAAEDr1yLXDH3mmWdy22231X9evXp1kuSUU06pbzvxxBPrZ3eOGDEiX/7ylzNp0qScdNJJGTFiRFavXp2KiookyXnnnZcuXbo0GKNr164599xzc/HFF+fCCy/MsGHD0q1bt1RUVKSysjLjxo2rn3EKAAAAALR+LTIMXbJkSWbOnLlO+0fblixZ0uDYmWeemYEDB+buu+9ORUVFSktLM2LEiJxwwgkZMmTIescZNWpUbrjhhkyYMCEvv/xyampqsuOOO+bII4/M6NGjm/SeAAAAAIDm1SLD0NGjRzcqjGzMdUOGDMk111zziccCAAAAAFqXLWLNUAAAAACAf0YYCgAAAAAUBWEoAAAAAFAUhKEAAAAAQFEQhgIAAAAARUEYCgAAAAAUBWEoAAAAAFAUhKEAAAAAQFEQhgIAAAAARUEYCgAAAAAUBWEoAAAAAFAUhKEAAAAAQFEQhgIAAAAARUEYCgAAAAAUBWEoAAAAAFAUhKEAAAAAQFEQhgIAAAAARUEYCgAAAAAUBWEoAAAAAFAUhKEAAAAAQFEQhgIAAAAARaG0uQvYEv3hqucztePfC9Z/uw6lGTF2YHbap2/BxgAAAACALY0wtABWfbA6K1ZVFXCEqlTcOVsYCgAAAACfgDC0AEpKko49ygrS98rFVamtTVavqilI/wAAAACwpRKGFkBZl3Y59qeHFKTvO874U1YsKuSsUwAAAADYMglDAQCAzW7us/MzddLsgr/xZL19AOCjhKEAAMBmN3XS7Cx9e/lmGMl6+wDA/xCGAgAAm13djNCSkqS8u/X2AdjybY63IrwR8c8JQwEAgGZT3r3MevsAFIXN81aENyL+GWEoAAAAABRYod+K8EbExhGGAgAAAMBmUqi3IrwRsXHaNHcBAAAAAACbgzAUAAAAACgKwlAAAAAAoCgIQwEAAACAoiAMBQAAAACKgjAUAAAAACgKwlAAAAAAoCgIQwEAAACAoiAMBQAAAACKQmlzFwAAAFBIKxdX5Y4z/lSw/tt1KM2IsQOz0z59CzYGANA0hKEAAMAWqV2H0iRVqa1NViyqKuBIVam4c7YwFABaAWEoAACwRRoxdmAq7pyd1atqCjbGysUfhq2FHAMAaDrCUAAAYIu00z59Cz5b844z/lTgWacAQFOygRIAAAAAUBTMDAUAgFZm7rPzM3VSYV//tikQALAlEoYCAEArM3XS7Cx9e3mBR7EpEACw5RGGAgBAK1M3I7SkJCnvXtbk/dsUCABar5WLq3LHGX8qWP+t/e0RYSgAALRS5d3LcuxPD2nyfm0KBACtT7sOpUk+/AfNwv5/vHW/PSIMBQCg6JgxAQBsaUaMHZiKOwu7pviW8PaIMBQAgKJhxgQAsKXaaZ++Bf+zx5bw9ogwFACAomHGBDSPuc/Oz9RJhX32ErOyAfjnhKEAABQNMyageUydNDtL316+GUYyKxuAjycMBQAA2ETWof14dTNCS0o+3PirEMzKBmBjCEMBAAAaaXOuQ/vIddPSsccrBel9c4Wt5d3LcuxPDylI32ZlA7AxhKEAAACNtDnWof1owFe4sM/r5QAUB2EoAABAI22OdWhff25+QQNXr5cDUEyEoQAAAC1YoQNXr5cDUEyEoQAAAGwxCr2Z1ebQ2jfMYuPNfXZ+pk4q7FIbvp+gIWEoAAAArd7m28xqc7CGa7GYOml2lr69vMCj+H6CjxKGAgAA0Optjs2sNoe6NVw/mL+8YDNczRRsOeq+X0tKkvLuZU3evzWBYV3CUAAAAFq9zbGZ1eZw53efyNK3lxd4hquZgi1NefeyHPvTQ5q8X2sCw7qEoQAAANBCFHqG65YyU3BzrLWZmEW7MTbX78WWYOViwXRLIAwFAACAFqLQM1y3lJmCm2etzcQs2n9u8/1ebDk+XOOY5uKrDwAAALQqhV5rM9lyZtEW2ub4vdiS1M02pvkIQ9nsNscUelPPAQAANmzl4qqCbdCUbL7Xywu11may5cyi3VwK+XtBcZn77PzsvG/hfnYIQ9nsNucUelPPAQAA/seHf0eqKvAGTYnXy4HGmjpptjCULcvmmkJv6jkAwKYp5Mwxb/K0PH6/i0OhN2hKvF4ObJpC/+wQhtJsTKEHAGiZNt/MMW/ytAR+v4tLoTdoSrxeDrRs/k8EAAA0sDlmjiXe5Gkp/H4DUEyEoQAAQAObY+YYLYffbwCKiTAUAAAAANhorXmdaWFoAZSW+bICAAAAsGXZnOtMF4rUrgA+9dntm7sEAACaWWueMQHA//DzHP7H5lpnupCEoQWw7R69mrsEAACaiZ25AbYMfp7DuraEdaa3mKftzDPPzLRp0zZ4/Jprrsk+++yzTvvkyZNzzz33ZN68eSktLc2nPvWpnHDCCRkyZEgBqwUAYEtlZ26ALYOf57Bl2mLC0DoHH3xwysvL12nv1Wvd2ZrXX399Jk2alLKysuy1116prq5ORUVFKioqcumll+bAAw/cHCUDALAF2RJmTADg5zlsqba4MPS0005L377//IdVRUVFJk2alG7duuXGG2/M9tt/uM7njBkzctZZZ+XKK6/MsGHD0qVLl0KXDAAAAABsBm2au4DmMnHixCTJ8ccfXx+EJskee+yRMWPGpLKyMg888EBzlQcAAAAANLGiDEOrqqry4osvJklGjRq1zvG6tilTpmzGqgAAAACAQtriXpN/4IEH8sEHH6SkpCTbb799DjzwwGyzzTYNzvnb3/6W6urqbLXVVtl6663X6WPQoEFJkjlz5myWmgEAAACAwtviwtAJEyY0+HzjjTfmxBNPzIknnljf9u677yZJevfuvd4+ysvL07lz5yxbtiwrVqxIx44dC1cwAAAAALBZbDFh6NChQ3PEEUdkjz32SM+ePfPee+/lsccey4QJE3LLLbekY8eOGTt2bJJk5cqVSZIOHTpssL/y8vJUVlZ+bBi6cOHCvP/++/Wf582b14R3BAAAALDpVi6uyh1n/KlgfUNrssWEoSeddFKDz9tvv32OP/74DB48ON/97nfzq1/9KmPGjElZWVmTjXnvvfdm/PjxTdYfAAAAQFNp16E0SVVqa5MViwobWn44FrR8W/x36t57751dd901s2bNysyZMzN8+PCUl5cnSVatWrXB6+pmj37cK/JjxozJyJEj6z/Pmzcvl19+eRNVDgAAANB4I8YOTMWds7N6VU1Bx2nXoTQjxg4s6BjQVLb4MDRJ+vXrl1mzZtW/0l63odKCBQvWe/7KlStTWVmZLl26fGwY2qtXr/Tq1avpCwYAAADYRDvt0zc77dO3ucuAFqVNcxewOSxbtizJ/6wRusMOO6R9+/ZZsmTJegPR1157LUkyYMCAzVckAAAAAFBQW3wYumTJkrz00ktJkkGDBiVJysrKMnz48CTJo48+us41jz32WJJk//333zxFAgAAAAAFt0WEodOnT8+TTz6ZNWvWNGifP39+LrjggqxcuTIjR47M1ltvXX/s6KOPTpLcfvvtefPNN+vbZ8yYkfvuuy+dO3fO4YcfvnluAAAAAAAouC1izdC33norV155ZXr06JFBgwalc+fOeffdd/Pqq6+muro6O+20U/6//+//a3DNiBEj8uUvfzmTJk3KSSedlBEjRmT16tWpqKhIkpx33nnp0qVLc9xOs5v77PxMnVS4BZZXLi7sDnYAAAA0v5WLq3LHGX8qWN8AjbFFhKG77bZbvvjFL2bmzJmZNWtWli1blvLy8gwcODCjRo3KF7/4xZSVla1z3ZlnnpmBAwfm7rvvTkVFRUpLSzNixIiccMIJGTJkSDPcScswddLsLH17ecHHaddhi/j2AwAA4CM+/LteVWprkxWLChta+nsl8EltET81dtxxx3znO99p1LWjR4/O6NGjm7ii1q1uRmhJSVLefd0QuSm061CaEWMHFqRvAAAAms+IsQNTcWfh3jas4++VQGNsEWEohVHevSzH/vSQ5i4DAACAVmSnffpmp336NncZAOslDG2lrL0CAAAAAJ+MMLSVsfYKAAAAADSOtKuVsfYKAAAAADSOMLSVsfYKAAAAADROm+YuAAAAAABgcxCGAgAAAABFQRgKAAAAABQFYSgAAAAAUBSEoQAAAABAURCGAgAAAABFQRgKAAAAABQFYSgAAAAAUBSEoQAAAABAURCGAgAAAABFQRgKAAAAABQFYSgAAAAAUBSEoQAAAABAURCGAgAAAABFQRgKAAAAABQFYSgAAAAAUBSEoQAAAABAURCGAgAAAABFQRgKAAAAABQFYSgAAAAAUBSEoQAAAABAURCGAgAAAABFQRgKAAAAABQFYSgAAAAAUBSEoQAAAABAURCGAgAAAABFQRgKAAAAABQFYSgAAAAAUBSEoQAAAABAURCGAgAAAABFobS5C9iSVFVVJUnmzZvXzJUAAAAAQOvVv3//dOjQocn7FYY2odmzZydJLr/88mauBAAAAABar2uuuSb77LNPk/crDG1C/fv3T5Kce+652WWXXZq5GqApzZs3L5dffnm+//3v1z/rwJbB8w1bLs83bLk837Dlqnu+y8vLC9K/MLQJdenSJUmyyy67ZPDgwc1cDVAI/fv393zDFsrzDVsuzzdsuTzfsOUqKysrSL82UAIAAAAAioIwFAAAAAAoCsLQJtSzZ8987WtfS8+ePZu7FKCJeb5hy+X5hi2X5xu2XJ5v2HIV+vkuqa2trS1IzwAAAAAALYiZoQAAAABAURCGAgAAAABFQRgKAAAAABSF0uYuYEtQVVWVX//613nkkUfy3nvvpUuXLtlnn31y0kknpXfv3s1dHvAxXn311Tz//PN55ZVXMmvWrCxYsCBJ8sQTT3zsdZMnT84999yTefPmpbS0NJ/61KdywgknZMiQIZujbOCfWLVqVZ5//vk8/fTTmT59et599920adMm2223XQ4++OCMGzcuHTt2XO+1nm9o+SZOnJiXXnopc+fOzZIlS1JdXZ0ePXpk2LBhOeaYYzJgwID1Xuf5htZn6dKlOf7447NkyZJst912+e1vf7vBcz3j0LKdeeaZmTZt2gaPX3PNNdlnn33WaW/qZ9sGSpuoqqoq3/rWt/Lyyy+nZ8+e2XPPPfPOO+/klVdeyVZbbZWbb7452267bXOXCWzA+eefn6eeemqd9o8LQ6+//vpMmjQpZWVl2WuvvVJdXZ2pU6cmSS699NIceOCBBasX2Dj3339/rr766iRJ//79s/POO2f58uWZMWNGVqxYkR122CE33HBDunfv3uA6zze0Dv/yL/+SlStXZsCAAenVq1eS5I033sibb76Z0tLSXH755dl///0bXOP5htbpiiuuyEMPPZTa2tqPDUM949Dy1YWhBx98cMrLy9c5fvTRR6/zD5qFeLaFoZvoF7/4RW6//fbsvvvu+dGPflQ/y2TixIn52c9+lmHDhuX6669v5iqBDfnNb36TVatWZdddd82uu+6ao48+OtXV1RsMQysqKvKd73wn3bp1y4033pjtt98+STJjxoycddZZKSsry8SJE9OlS5fNeRvAP5g8eXJmzJiRsWPHZscdd6xvX7hwYc4999zMnj07n/3sZ3PhhRfWH/N8Q+sxffr0DBo0KGVlZQ3a77nnnlx77bXp0aNHJk2alNLSD1+E83xD6zR16tR8+9vfzr/8y7/kvvvu22AY6hmH1qEuDJ04cWL69u37T88v1LNtzdBNsHr16txzzz1Jkm9/+9sNXrerS7OnTZuWV199tblKBP6J4447LieddFJGjhyZnj17/tPzJ06cmCQ5/vjj638QJ8kee+yRMWPGpLKyMg888EDB6gU2zujRo3POOec0CEKTpFevXvn2t7+d5MMZ4KtXr64/5vmG1mPIkCHrBKFJcuSRR2a77bbLokWLMm/evPp2zze0PlVVVfm///f/Zscdd8wxxxzzsed6xmHLVKhnWxi6CaZPn57Kyspst912GTRo0DrHR40alSR5+umnN3NlQCFUVVXlxRdfTPI/z/dH1bVNmTJlM1YFfFK77LJLkqS6ujpLly5N4vmGLUnbtm2TpH5WqOcbWqdf/epXefvtt3P22WfXP8/r4xmHLVMhn20bKG2Cv/71r0my3iD0o+1z5szZbDUBhfO3v/0t1dXV2WqrrbL11luvc9wzD63D22+/neTDoKRr165JPN+wpXjooYfy5ptvpl+/funXr18Szze0RnPmzMnEiRMzevToDB06NPPnz9/guZ5xaH0eeOCBfPDBBykpKcn222+fAw88MNtss02Dcwr5bAtDN8F7772XJBvcMb6u/d13391sNQGFU/csb+iZLy8vT+fOnbNs2bKsWLFigztVA81r0qRJSZK999477du3T+L5htbqt7/9bV5//fWsWrUq8+bNy+uvv55evXrloosuqp8h6vmG1mXt2rW56qqr0rlz55x66qn/9HzPOLQ+EyZMaPD5xhtvzIknnpgTTzyxvq2Qz7YwdBOsXLkySda7XlGSdOjQIUmyYsWKzVYTUDh1z3zds70+5eXlqays9ActaKGeeeaZPPDAAyktLc3JJ59c3+75htbpz3/+c/2OsknSp0+fnH/++Rk8eHB9m+cbWpe77rors2bNynnnnZdu3br90/M949B6DB06NEcccUT22GOP9OzZM++9914ee+yxTJgwIbfccks6duyYsWPHJinssy0MBQCKwrx583L55ZentrY2p556av3aoUDrde211yZJli1blrlz5+a2227LmWeemZNPPjknnHBCM1cHfFLvvvtufvnLX2bYsGEZPXp0c5cDNLGTTjqpweftt98+xx9/fAYPHpzvfve7+dWvfpUxY8ZscNJhU7GB0iYoLy9P8uGiruuzatWqJPEvT7CFqHvm657t9an71yvPPbQsCxYsyDnnnJNly5Zl3Lhx9f/iXMfzDa1bly5dMnTo0Fx99dUZPHhwbrnllrzyyitJPN/Qmlx77bWpqanJ2WefvdHXeMah9dt7772z6667prKyMjNnzkxS2GfbzNBNULeA64IFC9Z7vK79HxeBBVqnumd5Q8/8ypUrU1lZmS5duviDFrQgH3zwQc4+++y88847+cIXvpDTTz99nXM837BlKC0tzSGHHJJXX301U6ZMyW677eb5hlZkypQp6dy5c370ox81aK+urk7y4XN85plnJkkuuuii9OzZ0zMOW4h+/fpl1qxZef/995MU9s/nwtBNUPd63Wuvvbbe43XtAwYM2Gw1AYWzww47pH379lmyZEkWLFiwzkLOnnloeVasWJFzzjknb7zxRg466KCcc845KSkpWec8zzdsOerWGFyyZEkSzze0NpWVlZk2bdp6j1VXV9cfqwtIPeOwZVi2bFmS/1kjtJDPttfkN8GQIUPSuXPn/P3vf8/s2bPXOf7YY48lSUaOHLmZKwMKoaysLMOHD0+SPProo+scr3vm999//81ZFrAB1dXVOf/88/PKK69k7733brC79D/yfMOWoy4o2XbbbZN4vqE1eeKJJ9b738SJE5Mk2223XX1b3759k3jGYUuwZMmSvPTSS0mSQYMGJSnssy0M3QTt2rXLkUcemeTDtU3q1ipIkokTJ2bOnDkZNmxYg90sgdbt6KOPTpLcfvvtefPNN+vbZ8yYkfvuuy+dO3fO4Ycf3lzlAf9/a9asySWXXJIXXnghe+65Zy6//PK0a9fuY6/xfEPrMH369Dz33HNZu3Ztg/aamprcdddd+eMf/5iysrIccsgh9cc837Bl84xDyzd9+vQ8+eSTWbNmTYP2+fPn54ILLsjKlSszcuTI+iUpk8I92yW1tbW1jbwP8uHmSWeddVZmzpyZnj17Zs8998y7776bmTNnZquttsrNN99c/6/SQMvzzDPP5Lbbbqv//Morr6S2tjaf+tSn6ttOPPHE7LfffvWfr7/++kyaNCkdOnTIiBEjsnr16lRUVCRJLr300hx44IGb7waA9brzzjtzww03JEkOPPDAdOrUab3nnXbaadlqq63qP3u+oeWbPHlyrrzyynTr1i2DBw9O165ds3Tp0sydOzfvv/9+2rdvn/PPP79BGJp4vqE1mz9/fo4++uhst912+e1vf7veczzj0LLV/f+7R48eGTRoUDp37px33303r776aqqrq7PTTjvlJz/5Sbp3797gukI828LQJlBVVZVf//rXefjhh/Pee++lS5cu2WeffXLSSSc1SLSBlqfuB/LHOe+88zJ69Oh1rrv77rszb968lJaWZvfdd88JJ5yQIUOGFLJcYCPdeuutGT9+/D89b+LEifWv2dXxfEPL9vbbb+eBBx7ItGnT8vbbb2fp0qVp165d+vTpk09/+tP50pe+lH79+q33Ws83tE4bE4YmnnFoyd54443cfffdmTlzZt57770sW7Ys5eXl6d+/f0aNGpUvfvGLKSsrW++1Tf1sC0MBAAAAgKJgzVAAAAAAoCgIQwEAAACAoiAMBQAAAACKgjAUAAAAACgKwlAAAAAAoCgIQwEAAACAoiAMBQAAAACKgjAUAAAAACgKpc1dAAAAAAAUysKFCzNp0qS88sormTVrVlauXJnrrrsuw4cP3+g+Kioqcvvtt2fu3LlZs2ZN+vXrly996Uv5/Oc/v8FrXnrppZxxxhlJknvvvTdbbbVV/bG//e1v+e///u/MnDkzs2fPTnV1dSZOnJi+ffuu009VVVXuvPPOPPTQQ3nnnXfSpUuX7LHHHvn617+enXbaqcG5zz//fMaPH5/XXnst7dq1y2c+85mcdtpp6+13xYoVue222/Loo4/m/fffT7du3bL77rvnggsuSIcOHdZ7T1dffXXuv//+7Lfffrnqqqs25ku3XnfddVfuueeezJ8/P926dcshhxySk046KeXl5Y3uc2OZGQoAQLM788wzc9BBBzV3Gf/U5MmTc9BBB9X/d/HFFzeqn5tvvrlBP7feemvTFgoA1HvzzTdzxx13ZMGCBdl5550/8fVPPfVUzj777KxevTpf+9rXcvLJJ6esrCw//OEP8/vf/36916xduzbXXXfdBsO9l19+OXfddVdWrFiR/v37f+z4l112WW655ZYMHz48Z511VsaMGZO//OUvOfXUU/POO+/UnzdlypScc845Wb16df7t3/4tRx99dKZNm5YzzjgjS5YsadBnZWVlzjjjjDz44IP57Gc/m+985zv50pe+lOrq6qxevXq9dcyaNSuTJ09O+/btP7bef+amm27Kddddl5133jlnnnlmDj744Nx11135/ve/v0n9biwzQwEAaFKfNNR84oknClRJ4RxwwAHZZZddGvUXqiQZMWJE2rdvn3feeSd/+MMfmrg6ACguZ555Zvr06ZPzzz9/vccHDx6c+++/P127ds1jjz2WCy+88BP1f/fdd6dnz575yU9+Uh8EjhkzJscff3wmT56ccePGrXPNfffdl/feey+HH354Jk2atM7xkSNH5sEHH0zHjh3z29/+NrNnz17v2AsWLMgTTzyRY445Jqeddlp9+5577plvfetbeeKJJ+rHv/nmm9O3b9/87Gc/S7t27erHOfnkk/PrX/+6fpZqkvz85z/PO++8k1/+8pfZdttt69uPO+649dZRW1ub6667Lp///Ofzwgsv/LMv2QYtXLgwv//97/P5z38+F1xwQX17v379ct111+Xpp5/OyJEjG93/xhCGAgDQpL72ta+t0zZp0qRUVlau91iSXHDBBVm1alVhC2tCBx54YEaPHt3o60eMGJERI0bkxRdfFIYCQIF17Nhxk65fsWJFunTp0mBGZGlpabp167be8z/44IP88pe/zDe+8Y0sXrx4ved07dp1o8dOku7duzdo79mzZ5KkrKysfsw33ngjX/nKV+qD0CTZZZdd0r9///zpT3+qD0OXLVuWBx98MF/60pey7bbbZvXq1amtrf3YGZ8PPfRQXn/99Vx++eU59dRT13vO2rVrM2nSpNx///15++2306lTpxxwwAE55ZRT0qVLlyQfzohds2ZNDjnkkAbX/u///b9z3XXX5ZFHHhGGAgDQunzjG99Yp+0Pf/hDKisr13ssSbbZZptClwUA0CjDhg3LHXfckV/+8pc57LDDUlJSkocffjivvvrqepfM+eUvf5kePXpkzJgxue222zZp7O222y69e/fOxIkTs8MOO2TgwIFZuHBh/SzQulCxuro6yf+Eox9VVlaW119/Pe+//3569uyZ6dOnp7q6Ov369csPfvCDPPXUU1m7dm123333fPvb387AgQMbXL9ixYrcfPPN+epXv1ofwq7P//2//zeTJ0/OF77whXzpS1/K/Pnzc88992T27Nm58cYbU1paWv8K/j/WWbdG6Wuvvdb4L9ZGEoYCANDszjzzzEybNq3BK/OTJ0/OlVdemfPOOy9du3bNhAkTMnfu3HTp0iVf+MIX8o1vfCNt2rTJ5MmT8/vf/z5vvvlmttpqq3zpS1/KV77ylXXGqK2tzYMPPpgHHnigfvODHXfcMV/84hdz+OGHN8l9LFy4ML/5zW/y7LPPZsGCBWnfvn169OiRYcOG5ZRTTknnzp2bZBwAYPM58cQTM3/+/Nx+++2ZMGFCkg/Du0svvTQHHnhgg3PnzJmT++67L1dddVXatm27yWOXlpbmsssuy2WXXZbzzjuvvn3w4MG58cYb62dc9ujRI507d8706dMbXL906dLMmzcvyYd/TunZs2feeuutJB++Kr/tttvm/PPPz/LlyzN+/Ph861vfym233ZZevXrV9zF+/PiUlZWtdzmAOi+99FLuv//+/OAHP8ihhx5a3/7pT3863/3ud/Poo4/m0EMPzfbbb58kmT59ej796U83uD75cFmAQhOGAgDQoj3xxBN5/vnnc+CBB2bIkCF55plnMmHChNTW1qZz586ZMGFCDjjggAwbNixPPPFEbrrppnTv3j2HHXZYfR+1tbW57LLL8vDDD6dfv3757Gc/m3bt2uX555/PVVddlTfeeCOnn376JtW5atWqnH766XnnnXey11575aCDDsrq1aszf/78/PGPf8wxxxwjDAWATVRTU5PKysp12lavXr3OJkFdu3ZNmzabvnd4u3btsv3222fUqFE56KCDsmbNmtx33325/PLL8+Mf/zi77757/bnXXXdd9tlnn+y9996bPG6dLl26ZJdddsmoUaPyqU99Kn//+9/zm9/8JhdddFF+9KMfpaysLG3atMmYMWNyxx135D//8z/zhS98IStWrMhNN91UPxuzqqoqSbJy5cr6vq+99tr6ZQQGDhyYU089Nffcc0+++c1vJvlw86lJkyblwgsv/NjX6B999NF07tw5e+21V4Pfh0GDBqW8vDwvvvhiDj300AwePDif+tSncscdd6R3794ZPnx45s2blx//+McpLS2tn+FaSMJQAABatOeeey4/+9nPsttuuyX58DX8r3zlK7nzzjvTsWPH3HLLLfUL/x9zzDE59thj87vf/a5BGHr//ffn4Ycfzhe+8IV897vfTWnph38MXr16dX7wgx9k4sSJ+exnP5vBgwc3us6pU6dm/vz5GTt2bP793/+9wbEVK1bUjwkANN706dNz1llnrdM+Y8aMPPLIIw3aJk6cmL59+27ymD/5yU8yc+bM/PKXv6wPVw855JCccMIJuf766/Of//mfSZJHHnkkM2bM2ORX4z+qsrIy//7v/55jjjkmxxxzTH37rrvumjPPPDOTJ0/OF7/4xSTJSSedlKVLl+a3v/1tfvOb3yRJ9tprrxx++OH57//+7/qd7etCzZEjRzZYT3X33XdP3759M2PGjPq266+/PnvssUdGjRr1sXW+9dZbqayszJgxY9Z7/KNrp1522WW5+OKL8x//8R9JkrZt22bcuHGZNm1a3nzzzY38yjSeP5EBANCife5zn6sPQpMPN0HYb7/98uCDD+bYY49tsAPqNttskyFDhuQvf/lLampq6gPIu+++O+Xl5fn2t7/dIJRs165dvvnNb2bKlCl5+OGHNykMrbO+tbo2deMGAOBDu+yyS3784x83aPvZz36WHj16rLNMTo8ePTZ5vNWrV+eBBx7Iscce22CWaWlpafbZZ5/cc889Wb16ddq1a5ebbropo0aNSmlpaebPn58k9bNY33vvvdTU1DR4/XxjPP7441m0aNE6mwoNGzYsnTp1yvTp0+vD0Hbt2uXcc8/NN7/5zbz55pvp0aNHtt9++1x66aVp06ZNtttuuySpr+EfN2Wqa6ureerUqXnuuedy+eWX199PkqxZsyZVVVWZP39+unbtmk6dOqW2tjbdu3fPD37wg/Xex1ZbbVX/6969e+dnP/tZ3nzzzSxatCj9+vVLz549c+SRR6Zfv36f6OvTGMJQAABatF122WWdtrrF+zd0bM2aNVm8eHF69+6dVatWZe7cuenVq1f9LImPWrNmTZLkb3/72ybVOXTo0PTs2TO/+c1v8te//jX7779/hg0blv79+6ekpGST+gYAPtSlS5eMGDFinbaePXuu094Uli5dmjVr1tT/eeGj1qxZk7Vr12bt2rVJPgw8H3744Tz88MPrnHvyySdnl112ya233vqJxq+bUVk3Rp3a2tqsXbt2vXX16NGjPghes2ZNXnzxxey22271/zhb94+/CxcuXOfahQsXZocddqi/nyT5/ve/v855CxYsyNFHH50zzjgj48aNy7bbbpupU6dmyJAh6/2H4fXZfvvt69cQfeONN/L+++9n9OjRG3XtphCGAgDQonXq1GmdtroNCT7uWE1NTZJk2bJlqa2tzYIFCzJ+/PgNjrNq1apNqrNz5865+eabc8stt2TKlCl59tlnkyRbb711jjvuuBx55JGb1D8AUHjvvvtuVq1alf79+yf5cKZk586d8+STT+akk05Ku3btkny4BM7TTz+dHXbYoT78++EPf7hOf4888kj+9Kc/5YILLkjv3r0/cT11MyUfeeSRfOMb36hvf+qpp7Jy5cp1dn7/R7/73e/y/vvvN1haYIcddsguu+ySp576/7V3dyFN9mEcx3+zFzS0EIVN0EpziVpUtl4g9CAaEeY8qIMIfEFQRFYe2Ik7iAjCgxFSBkYmNPBES5EoS1EyeSzQQCXUA4leEOnloEhhVDI7iN08Sy2b6+nJfT9HG/vv/l/3Dn+7/9f1jz58+GA8tTkwMKC3b9/q2LFjkr4NP1rontxutywWiwoKCpSSkiLpW9uA9vZ2eTwelZWVBayfnZ2V1+s1hj19z+fzqb6+XpGRkcrPz//JL7J8hKEAAABY0fyBaVpamhoaGn7rXmazWS6XSz6fT8+ePdPg4KBaW1tVW1urmJgYHTp06LfuDwAAFubv4/nixQtJUmdnpzHBvKioyFh34cIFDQ8Pq6+vT9K3P1lPnDih69evq7y8XIcPH5bP59Pdu3f17t27gKcmv58sL0kTExOSpH379gUcFZ+ZmVFra6skGT0629raFB0drejoaCOQPHDggJKTk+XxePTmzRtjgFJbW5vi4uKUm5trXLOrq0sPHz7Ujh07FBUVpSdPnujBgwc6evTovJ6fTqdTVVVVcjqdcjgcmpmZUUtLi5KSkoxA0mw2y2w2z7unuro6xcbGBtzvzp075XA41NTUpImJCe3Zs0erV6/W5OSkent7dfr0aaOGS5cu6fPnz7JarZqdnVV3d7fGx8flcrkW3C/UCEMBAACwoq1bt06bNm3Sy5cvNT09vehTCaEUEREhq9Uqq9WqzMxMnTp1Sv39/YShAAD8IY2NjQHvOzo6jNf/DkMXUlhYqISEBN26dUs3btzQly9ftGXLFp0/f/6ng4UWMz09Pa+m5uZmSZLFYjHC0DVr1ujKlSvyeDx6/Pixenp6FBUVpezsbJWWlgYErImJifr48aM8Ho8+ffqkjRs3qqqqasGhRllZWXK73WpsbNS1a9cUGRmp7OxslZeXB93r/MyZM0pLS9Pt27fV0NCgVatWyWKxyG63a9u2bca6rVu36ubNm+ru7pbJZFJ6erpqa2uVlZUV1L6/ijAUAAAAK97x48d18eJFud1uVVdXG9NU/aampmQymZY1cfb58+fasGHDvGEN/l5f/smtAAAgtC5fvvzTNf4nPYO9lt1ul91u/6W6JKmkpCTgeLtfQkLCkmuKiYmR0+mU0+n84bqMjAzV1dUtuTabzRZUn9WWlpZFP8vLy1NeXt4Pv3/kyJH/pDfoYghDAQAAsOI5HA6Njo7q/v37evr0qWw2m+Li4vT+/Xu9evVKY2NjOnv27LLC0MHBQdXX12v79u1KSkrS+vXrNTU1pf7+fq1du5aeoQAAAP8DhKEAAABY8Uwmk1wul/bv3687d+7o0aNH8nq9io2NVWJioioqKrR79+5l7bF37169fv1aIyMj6uvrk9frVXx8vA4ePKiTJ09q8+bNobkZAAAABM00Nzc396eLAAAAAP4G9+7dU01Njaqrq0NyvGtoaEiVlZUqLi5e8AgdAAAAQiviTxcAAAAA/G1qamqUk5Ojc+fOBfX9q1evKicnR5WVlaEtDAAAAD/EMXkAAABgiVJTU1VcXGy8T0lJCeo6NpstYKDSrl27llsaAAAAloBj8gAAAAAAAADCAsfkAQAAAAAAAIQFwlAAAAAAAAAAYYEwFAAAAAAAAEBYIAwFAAAAAAAAEBYIQwEAAAAAAACEBcJQAAAAAAAAAGGBMBQAAAAAAABAWCAMBQAAAAAAABAWCEMBAAAAAAAAhIWvGMM9qrh1w4IAAAAASUVORK5CYII=",
+      "text/plain": [
+       "<Figure size 1600x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# You can zoom in the light curve by using `plot_limts` parameters\n",
+    "estimator.plot_lightcurve(plot_limits = [1.841896e9 + 400, 1.841896e9+450])"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "88a11256-b1b5-423b-85fe-67759865547a",
+   "metadata": {},
+   "source": [
+    "## Define Burst Window\n",
+    "\n",
+    "You can estimate the burst window by the zoom-in light curve.\n",
+    "\n",
+    "The burst windows can be recognized by Bayesian blocks. It will be implemented in future updates."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "d6284e86-bf47-4400-a07e-b87ddf8783e1",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# add a burst window\n",
+    "\n",
+    "estimator.add_burst_windows([1.8418964e9+4, 1.8418964e9+48])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "28476cd0-5558-4cbb-bf50-4d6d58e80848",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1600x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# plot the light curve with the burst window\n",
+    "estimator.plot_lightcurve(burst_windows=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "70e65823-f435-43bb-ac7f-dc9c804937d8",
+   "metadata": {},
+   "source": [
+    "## Define Background Windows\n",
+    "\n",
+    "You can define the background windows like you did for the burst window."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "8a0efa69-dfcb-435e-b317-7ddfe0012c3c",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "estimator.add_bkg_windows([1.841896e9+200, 1.841896e9+300], [1.841896e9+500, 1.841896e9+600])"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "ce286352-62b4-48fd-9773-52d7c221466b",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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+      "text/plain": [
+       "<Figure size 1600x800 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "estimator.plot_lightcurve(burst_windows=True, bkg_windows=True)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ac4a43f9-86a9-4585-b6a7-2565983abd4d",
+   "metadata": {},
+   "source": [
+    "## Make the background model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "29fabcdf-d375-4731-a35d-bf58bdd450e2",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# It only supports scaling by duratiom now.\n",
+    "\n",
+    "bkg_model = estimator.make_background_model(scaling = \"duration\", save_path = data_dir / \"bkg_model.hdf5\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "be0a39a6-11f5-49dc-8993-5433aeb546c6",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Could not determine default ax_kw['coord']. WCSAxes do not support intricsic coordinates <SpacecraftFrame Frame (attitude=None, obstime=None, location=None)>. Fallling back to plotting onto ICRS coodinates\n",
+      "Failed to transform from 'spacecraftframe' to 'icrs'. Rasterizing in 'spacecraftframe' frame. ERROR: Spacecraft coordinates need attitude to transform from ICRS\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'Background model (PsiChi)')"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 600x600 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "bkg_model.project(\"PsiChi\").plot()\n",
+    "plt.title(\"Background model (PsiChi)\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "616185b1-4a2a-4ec8-b418-477048c665d0",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## Compare with the true background"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "4c38b2fd-02eb-40f1-b148-09d50d122a11",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Could not determine default ax_kw['coord']. WCSAxes do not support intricsic coordinates <SpacecraftFrame Frame (attitude=None, obstime=None, location=None)>. Fallling back to plotting onto ICRS coodinates\n",
+      "Failed to transform from 'spacecraftframe' to 'icrs'. Rasterizing in 'spacecraftframe' frame. ERROR: Spacecraft coordinates need attitude to transform from ICRS\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'Real background (PsiChi)')"
+      ]
+     },
+     "execution_count": 14,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 600x600 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "bkg_true = Histogram.open(\"True_GRB_bn110605183_background.hdf5\")\n",
+    "bkg_true.project(\"PsiChi\").plot()\n",
+    "plt.title(\"Real background (PsiChi)\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "4e3cb43b-ce78-4fde-96c8-def03e8df178",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Could not determine default ax_kw['coord']. WCSAxes do not support intricsic coordinates <SpacecraftFrame Frame (attitude=None, obstime=None, location=None)>. Fallling back to plotting onto ICRS coodinates\n",
+      "Failed to transform from 'spacecraftframe' to 'icrs'. Rasterizing in 'spacecraftframe' frame. ERROR: Spacecraft coordinates need attitude to transform from ICRS\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "Text(0.5, 1.0, 'Real background (PsiChi)')"
+      ]
+     },
+     "execution_count": 15,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 600x600 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "bkg_diff = bkg_true.project(\"PsiChi\") - bkg_model.project(\"PsiChi\")\n",
+    "\n",
+    "bkg_diff.plot()\n",
+    "plt.title(\"Real background (PsiChi)\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "984e96c2-fcc8-4ce5-9d58-edeea65ec62f",
+   "metadata": {},
+   "source": [
+    "The difference map is centered around $0$ with variations up to $\\pm5$"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "c559331b-5e86-4ae4-b90a-685d256230ab",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "cosipy_yong_dev",
+   "language": "python",
+   "name": "cosipy_yong_dev"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.10.19"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/docs/tutorials/background_estimation/tranisent_background/True_GRB_bn110605183_background.hdf5 b/docs/tutorials/background_estimation/tranisent_background/True_GRB_bn110605183_background.hdf5
new file mode 100644
index 000000000..a0a77cab7
Binary files /dev/null and b/docs/tutorials/background_estimation/tranisent_background/True_GRB_bn110605183_background.hdf5 differ
diff --git a/tests/background_estimation/test_transient_background_estimation.py b/tests/background_estimation/test_transient_background_estimation.py
new file mode 100644
index 000000000..d4daf8ab1
--- /dev/null
+++ b/tests/background_estimation/test_transient_background_estimation.py
@@ -0,0 +1,193 @@
+from histpy import Histogram
+from cosipy import TransientBackgroundEstimation, test_data
+import numpy as np
+import pytest
+from pathlib import Path
+
+
+def test_transient_background():
+    
+    bkg_file = test_data.path / "GRB_bn110605183_with_bkg.hdf5"
+    
+    data = Histogram.open(bkg_file)
+    
+    estimator = TransientBackgroundEstimation(data)
+    
+    estimator.plot_lightcurve(plot_limits = [1.841896e9 + 400, 1.841896e9+450])
+    
+    # only one burst window error
+    with pytest.raises(ValueError):
+        estimator.add_burst_windows([1.8418964e9+4, 1.8418964e9+48], [1.8418964e9+4, 1.8418964e9+48])
+        
+    # burst window start > end error 
+    with pytest.raises(ValueError):
+        estimator.add_burst_windows([1.8418964e9+48, 1.8418964e9+4])
+    
+    estimator.add_burst_windows([1.8418964e9+4, 1.8418964e9+48])
+    
+    estimator.add_bkg_windows([1.841896e9+200, 1.841896e9+300], [1.841896e9+500, 1.841896e9+600])
+    
+    estimator.plot_lightcurve(burst_windows=True, bkg_windows=True)
+    
+    # error for currently unsupported scaling by fitting
+    with pytest.raises(NotImplementedError):
+        
+        _ = estimator.make_background_model(scaling = "fitting")
+        
+    # error for scaling method other than duration and fitting
+    with pytest.raises(ValueError):
+        
+        _ = estimator.make_background_model(scaling = "test")
+    
+    save_path = Path("")/"test_data.hdf5"
+    
+    bkg_model = estimator.make_background_model(save_path = save_path)
+ 
+    save_path.unlink()
+    
+    psichi_array = np.array([4.62, 3.52, 3.96, 3.52, 5.06, 3.74, 2.86, 3.08, 2.86, 3.08, 3.52,
+                               2.2 , 4.84, 4.62, 3.52, 3.08, 4.18, 3.52, 3.74, 2.86, 2.64, 3.52,
+                               4.4 , 5.06, 4.62, 3.96, 2.2 , 3.08, 3.52, 3.74, 4.62, 3.08, 3.52,
+                               5.5 , 3.08, 2.42, 3.08, 4.4 , 4.62, 2.64, 1.98, 5.06, 4.62, 2.64,
+                               2.64, 3.52, 4.62, 7.26, 4.18, 2.86, 1.76, 3.08, 5.72, 4.4 , 3.74,
+                               3.96, 5.06, 4.18, 4.18, 1.54, 3.08, 5.94, 2.86, 3.96, 4.84, 2.2 ,
+                               3.74, 2.2 , 5.06, 1.98, 2.64, 5.28, 1.76, 4.84, 3.52, 3.08, 3.74,
+                               2.2 , 2.86, 4.84, 4.62, 2.42, 3.74, 5.28, 1.76, 3.74, 3.08, 2.42,
+                               1.76, 4.18, 2.64, 2.2 , 5.06, 2.64, 5.94, 3.96, 5.5 , 1.98, 2.42,
+                               2.86, 4.84, 2.86, 5.06, 4.62, 1.98, 2.42, 4.62, 1.76, 3.08, 3.08,
+                               2.42, 3.52, 5.06, 4.84, 3.96, 1.76, 2.42, 2.64, 2.64, 1.98, 2.2 ,
+                               1.98, 4.62, 2.42, 3.08, 3.52, 4.62, 2.42, 3.3 , 1.98, 4.84, 5.06,
+                               2.42, 3.74, 2.42, 2.2 , 2.42, 4.4 , 5.06, 2.64, 4.18, 4.62, 3.08,
+                               1.76, 3.52, 5.06, 3.74, 4.62, 4.84, 2.64, 3.96, 3.3 , 1.76, 3.3 ,
+                               3.08, 2.64, 4.4 , 3.08, 3.74, 4.62, 0.88, 3.08, 3.3 , 5.5 , 2.86,
+                               3.52, 4.18, 2.86, 0.44, 3.96, 3.96, 4.62, 4.4 , 3.52, 4.4 , 3.08,
+                               2.86, 3.96, 3.74, 2.64, 3.08, 5.06, 1.98, 1.98, 2.64, 2.2 , 4.4 ,
+                               2.42, 3.96, 4.4 , 5.28, 2.2 , 1.54, 2.64, 5.06, 3.3 , 2.86, 4.62,
+                               4.62, 1.76, 2.86, 4.18, 5.06, 3.08, 3.08, 4.18, 3.3 , 3.3 , 1.32,
+                               3.96, 4.4 , 4.62, 4.84, 2.64, 2.64, 3.3 , 0.88, 3.3 , 5.28, 3.52,
+                               4.84, 3.96, 4.18, 2.86, 1.1 , 3.52, 3.74, 2.64, 3.96, 4.18, 3.52,
+                               2.42, 0.44, 2.2 , 3.3 , 3.08, 3.3 , 2.42, 3.96, 3.52, 1.76, 5.06,
+                               4.4 , 2.2 , 2.42, 3.74, 1.98, 2.42, 2.64, 4.18, 3.74, 1.76, 3.96,
+                               4.62, 4.84, 2.2 , 1.98, 2.86, 3.52, 2.42, 4.4 , 2.86, 3.96, 2.2 ,
+                               0.88, 3.3 , 3.96, 3.74, 3.08, 3.08, 4.62, 4.84, 0.88, 4.4 , 3.74,
+                               5.06, 3.96, 2.2 , 3.08, 5.06, 0.88, 4.62, 4.62, 5.06, 5.28, 3.08,
+                               3.96, 1.98, 1.76, 2.86, 3.96, 3.96, 5.28, 3.96, 3.96, 2.2 , 2.2 ,
+                               3.3 , 3.96, 4.4 , 3.96, 4.84, 4.18, 3.3 , 4.18, 3.74, 4.18, 2.64,
+                               3.3 , 6.6 , 3.74, 2.64, 2.2 , 4.84, 4.4 , 3.96, 3.52, 5.5 , 3.3 ,
+                               1.54, 3.74, 2.64, 4.18, 4.4 , 2.86, 6.16, 3.96, 3.3 , 2.64, 6.16,
+                               5.06, 2.2 , 2.64, 3.3 , 4.62, 3.08, 1.76, 4.18, 4.18, 3.96, 3.96,
+                               4.62, 5.06, 3.3 , 2.86, 4.62, 2.86, 4.84, 4.84, 4.62, 6.16, 4.4 ,
+                               2.64, 4.18, 4.62, 3.08, 4.4 , 4.62, 5.72, 3.96, 1.54, 5.06, 4.62,
+                               2.42, 5.06, 5.06, 2.86, 3.08, 1.54, 5.06, 5.28, 7.04, 5.72, 4.84,
+                               5.5 , 5.28, 3.52, 5.5 , 4.84, 4.18, 4.18, 7.48, 5.5 , 5.06, 4.84,
+                               4.84, 6.6 , 6.38, 3.96, 5.94, 4.18, 3.74, 5.06, 4.84, 7.04, 3.52,
+                               3.74, 5.94, 4.62, 4.18, 1.98, 4.62, 5.94, 2.64, 6.82, 3.52, 5.06,
+                               2.86, 1.54, 4.84, 3.08, 3.08, 5.72, 3.74, 3.74, 3.3 , 0.44, 6.16,
+                               5.28, 2.86, 4.62, 3.52, 5.72, 3.96, 1.98, 3.96, 5.5 , 5.28, 5.28,
+                               5.28, 4.84, 2.86, 2.42, 3.74, 3.96, 3.08, 3.52, 4.18, 4.4 , 3.52,
+                               3.74, 3.52, 5.06, 4.18, 4.62, 3.74, 4.62, 2.2 , 2.42, 5.06, 3.74,
+                               3.96, 3.96, 5.06, 2.42, 1.76, 2.64, 1.76, 3.96, 2.42, 3.52, 3.74,
+                               4.62, 2.2 , 1.1 , 2.64, 4.18, 5.72, 2.86, 1.76, 4.84, 3.3 , 0.88,
+                               2.64, 2.86, 2.42, 4.62, 4.4 , 4.18, 3.74, 1.32, 2.2 , 4.18, 3.74,
+                               4.18, 4.18, 3.52, 3.74, 1.32, 3.08, 3.96, 3.52, 2.64, 2.86, 4.18,
+                               4.18, 1.54, 3.52, 6.38, 1.98, 3.3 , 3.08, 5.06, 2.64, 1.54, 2.42,
+                               3.96, 1.98, 3.08, 2.64, 4.4 , 3.52, 1.32, 4.18, 3.96, 1.54, 3.74,
+                               3.96, 3.08, 0.44, 2.42, 3.96, 3.96, 2.42, 2.64, 4.18, 3.96, 1.98,
+                               1.1 , 2.42, 2.64, 3.52, 3.74, 1.54, 2.2 , 2.64, 1.32, 3.52, 3.3 ,
+                               4.18, 2.86, 5.28, 3.74, 3.96, 0.44, 3.52, 3.3 , 3.96, 3.52, 4.4 ,
+                               3.96, 2.64, 0.66, 4.18, 4.62, 4.4 , 4.62, 4.4 , 3.52, 3.74, 2.64,
+                               3.96, 3.52, 1.32, 1.54, 3.3 , 3.08, 1.32, 2.86, 3.52, 2.64, 3.3 ,
+                               1.98, 5.28, 2.42, 2.64, 2.2 , 3.74, 3.3 , 2.42, 3.3 , 3.08, 3.08,
+                               1.98, 1.76, 3.52, 3.08, 2.64, 3.3 , 4.4 , 1.98, 2.86, 2.2 , 2.42,
+                               2.2 , 1.76, 3.52, 3.52, 1.76, 2.42, 1.1 , 1.76, 3.74, 3.3 , 3.08,
+                               2.86, 4.84, 4.18, 1.76, 2.42, 4.18, 3.74, 5.94, 4.62, 3.3 , 1.98,
+                               1.76, 3.3 , 4.84, 3.3 , 5.28, 3.08, 3.74, 4.18, 2.42, 2.2 , 3.08,
+                               2.42, 1.54, 3.52, 3.52, 0.66, 1.1 , 3.3 , 2.64, 1.32, 2.86, 3.74,
+                               2.64, 1.98, 3.08, 3.3 , 4.84, 3.52, 2.2 , 3.52, 3.08, 1.1 , 2.42,
+                               3.96, 4.62, 4.18, 2.64, 3.74, 4.62, 1.76, 1.98, 2.2 , 3.74, 3.74,
+                               2.42, 3.96, 0.88, 2.64, 3.96, 2.2 , 2.86, 3.08, 2.86, 2.2 , 1.76,
+                               3.08, 3.08, 5.94, 2.42, 3.52, 0.88, 0.88, 3.74, 3.08, 4.18, 1.76,
+                               2.64, 1.98, 2.2 , 3.52, 1.98, 3.74, 2.64, 1.1 , 2.86, 3.74, 2.64,
+                               4.18, 3.08, 1.98, 2.2 , 5.28, 2.42, 3.3 , 1.98, 1.32, 2.42, 5.28,
+                               1.76, 5.06, 2.2 , 1.54, 2.86, 2.64, 4.4 , 3.96, 2.42, 3.52, 2.86,
+                               3.96, 1.98, 3.3 , 3.52, 4.4 , 5.28, 2.42, 2.42, 1.76, 2.64, 3.08,
+                               2.64, 1.76, 3.08, 2.42, 1.32, 1.32, 2.86, 3.52, 2.64, 2.2 , 2.64,
+                               3.3 , 1.32, 1.98, 1.76, 2.86, 1.76, 1.76, 3.08, 3.74, 2.86, 4.62,
+                               5.94, 2.86, 1.98, 4.84, 2.86, 3.08, 4.18, 3.3 , 3.3 , 2.2 , 3.96,
+                               2.42, 2.86, 1.54, 2.42, 2.42, 1.54, 2.2 , 2.64, 1.98])
+    
+    assert np.allclose(bkg_model.project("PsiChi").contents.todense(),psichi_array)
+    
+    assert np.allclose([44.0], estimator.burst_durations)
+    
+    assert np.allclose([[1841896404.0, 1841896448.0]], estimator.burst_windows)
+    
+    assert np.allclose([[1841896200.0, 1841896300.0], [1841896500.0, 1841896600.0]], estimator.bkg_windows)
+    
+    assert np.allclose([100.0, 100.0], estimator.bkg_durations)
+    
+def test_data_type_error():
+    
+    data = np.array([10])
+
+    with pytest.raises(TypeError):
+        
+        estimator = TransientBackgroundEstimation(data)
+        
+        
+def test_window_error():
+    
+    bkg_file = test_data.path / "GRB_bn110605183_with_bkg.hdf5"
+    
+    data = Histogram.open(bkg_file)
+    
+    estimator = TransientBackgroundEstimation(data)
+    
+    # making background error when the background window not defined
+    with pytest.raises(ValueError):
+        
+        _ = estimator.make_background_model()
+        
+    estimator.add_bkg_windows([1.841896e9+200, 1.841896e9+300], [1.841896e9+500, 1.841896e9+600])
+    
+    # making background error when the burst window not defined
+    with pytest.raises(ValueError):
+        
+        _ = estimator.make_background_model()
+        
+def test_Time_axis_error():
+    
+    bkg_file = test_data.path / "GRB_bn110605183_with_bkg_no_time_axis.hdf5"  
+    data = Histogram.open(bkg_file)
+    
+    # error when there is no Time axis in the data
+    with pytest.raises(ValueError):
+        
+        estimator = TransientBackgroundEstimation(data)
+        
+    bkg_file = test_data.path / "GRB_bn110605183_with_bkg_time_axis_idx_not_zero.hdf5"
+    data = Histogram.open(bkg_file)
+    
+    # error when there is the Time axis doesn't have index of 0
+    with pytest.raises(ValueError):
+        
+        estimator = TransientBackgroundEstimation(data)
+        
+        
+def test_slice_timetage_error():
+    
+    bkg_file = test_data.path / "GRB_bn110605183_with_bkg.hdf5"
+    
+    data = Histogram.open(bkg_file)
+    
+    estimator = TransientBackgroundEstimation(data)
+    
+    # error when slicing window start > end
+    with pytest.raises(ValueError):
+        
+        estimator.slice_by_timetags(1.8418964e9+48, 1.8418964e9+4)
+        
+    # error when the scaling start is smaller than the minumum time tag
+    with pytest.raises(ValueError):
+        
+        estimator.slice_by_timetags(1841896154.0-10, 1.8418964e9+48)
\ No newline at end of file