From 78c3b9ded033e0f5cb3c3663c33dae440dba16d6 Mon Sep 17 00:00:00 2001
From: Eliza Neights <eneights@gmail.com>
Date: Wed, 26 Feb 2025 14:40:01 -0500
Subject: [PATCH 01/31] Add polarization to point source response

---
 cosipy/response/FullDetectorResponse.py | 131 +++++++++++++++++++
 cosipy/response/PointSourceResponse.py  | 160 ++++++++++++++++++++++--
 2 files changed, 281 insertions(+), 10 deletions(-)

diff --git a/cosipy/response/FullDetectorResponse.py b/cosipy/response/FullDetectorResponse.py
index 14a775e7..811ad15a 100644
--- a/cosipy/response/FullDetectorResponse.py
+++ b/cosipy/response/FullDetectorResponse.py
@@ -684,6 +684,137 @@ def _open_rsp(cls, filename, Spectrumfile=None,norm="Linear" ,single_pixel = Fal
 
         return new
 
+    @staticmethod
+    def _write_h5(dr_area, filename):
+        """
+        Write a Histogram containing the response into a HDF5 file response format
+
+        Parameters
+        ----------
+        dr_area : Histogram,
+             Histogram containing the response matrix in unit of differential area
+
+         filename : str, :py:class:`~pathlib.Path`
+             Path to .h5 file
+        """
+
+        npix = dr_area.axes['NuLambda'].nbins
+        nside = HealpixBase(npix = npix).nside
+        has_polarization = "Pol" in dr_area.axes.labels
+        sparse = dr_area.is_sparse
+
+        f = h5.File(filename, mode='w')
+
+        drm = f.create_group('DRM')
+
+        # Header
+        drm.attrs['UNIT'] = 'cm2'
+
+        axis_description = {'Ei': "Initial simulated energy",
+                            'NuLambda': "Location of the simulated source in the spacecraft coordinates",
+                            'Pol': "Polarization angle",
+                            'Em': "Measured energy",
+                            'Phi': "Compton angle",
+                            'PsiChi': "Location in the Compton Data Space",
+                            'SigmaTau': "Electron recoil angle",
+                            'Dist': "Distance from first interaction"
+                            }
+
+        #keep the same dimension order of the data
+        axes_to_write = ['NuLambda', 'Ei']
+
+        if has_polarization:
+            axes_to_write += ['Pol']
+
+        axes_to_write += ['Em', 'Phi', 'PsiChi']
+
+        if sparse:
+            drm.attrs['SPARSE'] = True
+
+            # singletos. Save space in dense
+            axes_to_write += ['SigmaTau', 'Dist']
+        else:
+            drm.attrs['SPARSE'] = False
+
+        axes = drm.create_group('AXES', track_order=True)
+
+        for axis in dr_area.axes[axes_to_write]:
+
+            axis_dataset = axes.create_dataset(axis.label,
+                                               data=axis.edges)
+
+            if axis.label in ['NuLambda', 'PsiChi', 'SigmaTau']:
+
+                # HEALPix
+                axis_dataset.attrs['TYPE'] = 'healpix'
+
+                axis_dataset.attrs['NSIDE'] = nside
+
+                axis_dataset.attrs['SCHEME'] = 'ring'
+
+            else:
+
+                # 1D
+                axis_dataset.attrs['TYPE'] = axis.axis_scale
+
+                if axis.label in ['Ei', 'Em']:
+                    axis_dataset.attrs['UNIT'] = 'keV'
+                    axis_dataset.attrs['TYPE'] = 'log'
+                elif axis.label in ['Phi', 'Pol']:
+                    axis_dataset.attrs['UNIT'] = 'deg'
+                    axis_dataset.attrs['TYPE'] = 'linear'
+                elif axis.label in ['Dist']:
+                    axis_dataset.attrs['UNIT'] = 'cm'
+                    axis_dataset.attrs['TYPE'] = 'linear'
+                else:
+                    raise ValueError("Shouldn't happend")
+
+            axis_dataset.attrs['DESCRIPTION'] = axis_description[axis.label]
+
+        # sparse matrice
+        if sparse:
+
+            progress_bar = tqdm(total=npix, desc="Progress", unit="nbpixel")
+            # Contents. Sparse arrays
+            coords = drm.create_dataset('BIN_NUMBERS',
+                                        (npix,),
+                                        dtype=h5.vlen_dtype(int),
+                                        compression="gzip")
+
+            data = drm.create_dataset('CONTENTS',
+                                      (npix,),
+                                      dtype=h5.vlen_dtype(float),
+                                      compression="gzip")
+
+            for b in range(npix):
+                # print(f"{b}/{npix}")
+
+                pix_slice = dr_area[{'NuLambda': b}]
+
+                coords[b] = pix_slice.coords.flatten()
+                data[b] = pix_slice.data
+                progress_bar.update(1)
+
+            progress_bar.close()
+
+        # non sparseOk g
+        else:
+
+            if 'Pol' in axes_to_write:
+
+                data = drm.create_dataset('CONTENTS',
+                                          data=np.transpose(dr_area.contents, axes=[1, 0, 2, 3, 4, 5]),
+                                          compression="gzip")
+
+            else:
+
+                data = drm.create_dataset('CONTENTS',
+                                          data=np.transpose(dr_area.contents, axes=[1, 0, 2, 3, 4]),
+                                          compression="gzip")
+
+        # close the .h5 file in write mode in order to reopen it in read mode after
+        f.close()
+
     @property
     def is_sparse(self):
         return self._sparse
diff --git a/cosipy/response/PointSourceResponse.py b/cosipy/response/PointSourceResponse.py
index 310d27d9..55a3abff 100644
--- a/cosipy/response/PointSourceResponse.py
+++ b/cosipy/response/PointSourceResponse.py
@@ -1,14 +1,18 @@
-from histpy import Histogram, Axes, Axis
+from histpy import Histogram#, Axes, Axis
 
 import numpy as np
 import astropy.units as u
-from astropy.units import Quantity
-from scipy import integrate
+#from astropy.units import Quantity
+#from scipy import integrate
+from scoords import SpacecraftFrame, Attitude
 
-from threeML import DiracDelta, Constant, Line, Quadratic, Cubic, Quartic, StepFunction, StepFunctionUpper, Cosine_Prior, Uniform_prior, PhAbs, Gaussian
+#from threeML import DiracDelta, Constant, Line, Quadratic, Cubic, Quartic, StepFunction, StepFunctionUpper, Cosine_Prior, Uniform_prior, PhAbs, Gaussian
 
 from .functions import get_integrated_spectral_model
 
+import logging
+logger = logging.getLogger(__name__)
+
 class PointSourceResponse(Histogram):
     """
     Handles the multi-dimensional matrix that describes the expected
@@ -43,32 +47,168 @@ def photon_energy_axis(self):
         
         return self.axes['Ei']
        
-    def get_expectation(self, spectrum):
+    def get_expectation(self, spectrum, polarization_level=None, polarization_angle=None, scatt_map=None, convention=None):
         """
-        Convolve the response with a spectral hypothesis to obtain the expected
+        Convolve the response with a spectral (and optionally, polarization) hypothesis to obtain the expected
         excess counts from the source.
 
         Parameters
         ----------
         spectrum : :py:class:`threeML.Model`
             Spectral hypothesis.
+        polarization_level : float, optional
+            Polarization level (between 0 and 1).
+        polarization_angle : :py:class:`cosipy.polarization.polarization_angle.PolarizationAngle`, optional
+            Polarization angle. If in the spacecraft frame, the angle must have the same convention as the response.
+        scatt_map : :py:class:`cosipy.spacecraftfile.scatt_map.SpacecraftAttitudeMap`, optional
+            Spacecraft attitude map. Only needed for polarization angle provided in galactic reference frame.
+        convention : str, optional
+            Polarization angle convention of response ('RelativeX', 'RelativeY', or 'RelativeZ'). Only needed for polarization angle provided in galactic reference frame.
 
         Returns
         -------
         :py:class:`histpy.Histogram`
              Histogram with the expected counts on each analysis bin
         """
-        
+
+        if polarization_level == None:
+
+            if polarization_angle == None:
+
+                if 'Pol' in self.axes.labels:
+
+                    raise RuntimeError("Must include polarization in point source response if using polarization response")
+
+                else:
+
+                    contents = self.contents
+                    axes = self.axes[1:]
+
+            else:
+
+                raise RuntimeError("Must provide both polarization level and angle")
+
+        elif polarization_angle != None:
+
+            from cosipy.polarization.polarization_angle import PolarizationAngle
+            from cosipy.polarization.conventions import MEGAlibRelativeX, MEGAlibRelativeY, MEGAlibRelativeZ, IAUPolarizationConvention
+
+            if polarization_level > 1.0 or polarization_level < 0:
+
+                raise RuntimeError("Polarization level must be a fraction between 0 and 1")
+
+            elif not 'Pol' in self.axes.labels:
+                
+                raise RuntimeError("Response must have polarization angle axis to include polarization in point source response")
+
+            elif type(polarization_angle.convention.frame) == SpacecraftFrame:
+
+                logger.warning("The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!")
+
+                if polarization_angle.angle.deg == 180.:
+                    polarization_angle = PolarizationAngle(0. * u.deg, polarization_angle.skycoord, convention=polarization_angle.convention)
+
+                polarization_angle_components = []
+
+                for i in range(len(self.axes['Pol'].edges) - 1):
+
+                    polarization_angle_components.append(self.slice[{'Pol':slice(i,i+1)}].project('Ei', 'Em', 'Phi', 'PsiChi'))
+
+                    if polarization_angle.angle.deg >= self.axes['Pol'].edges.to_value(u.deg)[i] and polarization_angle.angle.deg < self.axes['Pol'].edges.to_value(u.deg)[i+1]:
+                        polarized_component = polarization_angle_components[i].contents
+
+                unpolarized_component = polarization_angle_components[0].contents
+
+                for i in range(len(polarization_angle_components) - 1):
+
+                    unpolarized_component += polarization_angle_components[i+1].contents
+
+                polarized_component /= np.sum(polarized_component.value)
+                unpolarized_component /= np.sum(unpolarized_component.value)
+
+                polarization_hist = (polarization_level * polarized_component) + ((1 - polarization_level) * unpolarized_component)
+                polarization_hist *= np.sum(self.contents) / np.sum(polarization_hist)
+
+                contents = polarization_hist
+                axes = self.project('Ei', 'Em', 'Phi', 'PsiChi').axes[1:]
+
+            elif type(scatt_map) != None and convention != None:
+
+                polarization_angle_components = np.empty(self.axes['Pol'].nbins, dtype=Histogram)
+
+                if polarization_angle.angle.deg == 180.:
+                    polarization_angle = PolarizationAngle(0. * u.deg, polarization_angle.skycoord, convention=polarization_angle.convention)
+
+                for i in range(len(self.axes['Pol'].edges) - 1):
+
+                    response_slice = self.slice[{'Pol':slice(i,i+1)}].project('Ei', 'Em', 'Phi', 'PsiChi')
+                    bin_center = (self.axes['Pol'].edges.to_value(u.deg)[i] + self.axes['Pol'].edges.to_value(u.deg)[i+1]) / 2
+
+                    for j, (pixels, exposure) in enumerate(zip(scatt_map.contents.coords.transpose(), scatt_map.contents.data)):
+
+                        attitude = Attitude.from_axes(x=scatt_map.axes['x'].pix2skycoord(pixels[0]), y=scatt_map.axes['y'].pix2skycoord(pixels[1]))
+
+                        if convention == 'RelativeX':
+                            this_convention = MEGAlibRelativeX(attitude=attitude)
+                        elif convention == 'RelativeY':
+                            this_convention = MEGAlibRelativeY(attitude=attitude)
+                        elif convention == 'RelativeZ':
+                            this_convention = MEGAlibRelativeZ(attitude=attitude)
+                        else:
+                            raise RuntimeError("Response convention must be 'RelativeX', 'RelativeY', or 'RelativeZ'")
+
+                        polarization_angle_bin_center = PolarizationAngle(bin_center * u.deg, polarization_angle.skycoord, convention=this_convention)
+
+                        polarization_angle_galactic = polarization_angle_bin_center.transform_to(polarization_angle.convention)
+
+                        if polarization_angle_galactic.angle.deg == 180.:
+                            polarization_angle_galactic = PolarizationAngle(0. * u.deg, polarization_angle_galactic.skycoord, convention=polarization_angle_galactic.convention)
+
+                        polarization_angle_index = np.max(np.where(polarization_angle_galactic.angle.deg >= self.axes['Pol'].edges.to_value(u.deg)))
+
+                        if hasattr(polarization_angle_components[polarization_angle_index], 'axes'):
+                            polarization_angle_components[polarization_angle_index] += response_slice * exposure / np.sum(scatt_map.project('x'))
+                        else:
+                            polarization_angle_components[polarization_angle_index] = response_slice * exposure / np.sum(scatt_map.project('x'))
+
+                for i in range(len(self.axes['Pol'].edges) - 1):
+
+                    if polarization_angle.angle.deg >= self.axes['Pol'].edges.to_value(u.deg)[i] and polarization_angle.angle.deg < self.axes['Pol'].edges.to_value(u.deg)[i+1]:
+                        polarized_component = polarization_angle_components[i].contents
+
+                unpolarized_component = polarization_angle_components[0].contents
+
+                for i in range(len(polarization_angle_components) - 1):
+
+                    unpolarized_component += polarization_angle_components[i+1].contents
+
+                polarized_component /= np.sum(polarized_component.value)
+                unpolarized_component /= np.sum(unpolarized_component.value)
+
+                polarization_hist = (polarization_level * polarized_component) + ((1 - polarization_level) * unpolarized_component)
+                polarization_hist *= np.sum(self.contents) / np.sum(polarization_hist)
+
+                contents = polarization_hist
+                axes = self.project('Ei', 'Em', 'Phi', 'PsiChi').axes[1:]
+
+            else:
+
+                raise RuntimeError("Scatt map and response convention must be provided to include polarization in galactic coordinates in point source response")
+
+        else:
+
+            raise RuntimeError("Must provide both polarization level and angle to include polarization in point source response")
+
         energy_axis = self.photon_energy_axis
 
         flux = get_integrated_spectral_model(spectrum, energy_axis)
         
-        expectation = np.tensordot(self.contents, flux.contents, axes = ([0], [0]))
+        expectation = np.tensordot(contents, flux.contents, axes=([0], [0]))
         
         # Note: np.tensordot loses unit if we use a sparse matrix as it input.
         if self.is_sparse:
             expectation *= self.unit * flux.unit
 
-        hist = Histogram(self.axes[1:], contents = expectation)
-        
+        hist = Histogram(axes, contents=expectation)
+
         return hist

From 2e5e3ca8d1f6573c42cd57af93a1bad304a35fbf Mon Sep 17 00:00:00 2001
From: Eliza Neights <eneights@gmail.com>
Date: Wed, 26 Feb 2025 16:58:36 -0500
Subject: [PATCH 02/31] Add error if expectation has units (Hiroki's
 suggestion)

---
 cosipy/threeml/COSILike.py | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/cosipy/threeml/COSILike.py b/cosipy/threeml/COSILike.py
index da3a508e..52ee8f9d 100644
--- a/cosipy/threeml/COSILike.py
+++ b/cosipy/threeml/COSILike.py
@@ -292,7 +292,10 @@ def get_log_like(self):
             logger.warning("Adding 1e-12 to each bin of the expectation to avoid log-likelihood = -inf.")
             self._printed_warning = True
         # This 1e-12 should be defined as a parameter in the near future (HY)
-        
+
+        if not expectation.contents.unit == u.dimensionless_unscaled:
+            raise RuntimeError("Expectation should be dimensionless, but has units of " + str(expectation.contents.unit) + ".")
+                         
         # Convert data into an arrary:
         data = self._data.contents
         

From 70c2fd04f235627099c94aab9df92b2d4db5c302 Mon Sep 17 00:00:00 2001
From: Eliza Neights <eneights@gmail.com>
Date: Thu, 27 Feb 2025 18:46:00 -0500
Subject: [PATCH 03/31] Add polarization fit in galactic coordinates

---
 cosipy/polarization/polarization_asad.py | 328 ++++++++++++++++-------
 1 file changed, 228 insertions(+), 100 deletions(-)

diff --git a/cosipy/polarization/polarization_asad.py b/cosipy/polarization/polarization_asad.py
index 4363bba7..02f3df1c 100644
--- a/cosipy/polarization/polarization_asad.py
+++ b/cosipy/polarization/polarization_asad.py
@@ -2,10 +2,11 @@
 from astropy.coordinates import Angle
 import astropy.units as u
 from astropy.stats import poisson_conf_interval
+from astropy.time import Time
 import matplotlib.pyplot as plt
 from scipy.optimize import curve_fit
 from cosipy.polarization.polarization_angle import PolarizationAngle
-from cosipy.polarization.conventions import MEGAlibRelativeX, IAUPolarizationConvention
+from cosipy.polarization.conventions import MEGAlibRelativeX, MEGAlibRelativeY, MEGAlibRelativeZ, IAUPolarizationConvention
 from cosipy.response import FullDetectorResponse
 from scoords import SpacecraftFrame
 
@@ -50,79 +51,125 @@ class PolarizationASAD():
         Source direction
     source_spectrum : astromodels.functions.functions_1D
         Spectrum of source
-    response_file : str or pathlib.Path
-        Path to detector response
+    asad_bin_edges : astropy.coordinates.angles.core.Angle
+        Bin edges for azimuthal scattering angle distribution
+    data : dict
+        Unbinned data
+    background : dict
+        Unbinned background model
     sc_orientation : cosipy.spacecraftfile.SpacecraftFile.SpacecraftFile
         Spacecraft orientation
+    response_file : str or pathlib.Path
+        Path to detector response
+    response_convention : str, optional
+        Polarization reference convention used in response ('RelativeX', 'RelativeY', or 'RelativeZ'). Default is 'RelativeX'
     fit_convention : cosipy.polarization.conventions.PolarizationConvention, optional
-        Polarization reference convention to use for fit. Default is RelativeX
+        Polarization reference convention to use for fit. Default is IAU convention
+    show_plots : bool, optional
+        Option to show plots. Default is False
     """
 
-    def __init__(self, source_vector, source_spectrum, response_file, sc_orientation, fit_convention=None):
-        
-        if fit_convention == None:
-            self._convention = MEGAlibRelativeX(attitude=source_vector.attitude)
-        else:
-            self._convention = fit_convention
+    def __init__(self, source_vector, source_spectrum, asad_bin_edges, data, background, sc_orientation, response_file, response_convention='RelativeX', fit_convention=IAUPolarizationConvention(), show_plots=False):
 
-        reference_vector = self._convention.get_basis(source_vector)[0] #px
+        if isinstance(fit_convention.frame, SpacecraftFrame) and not isinstance(source_vector.frame, SpacecraftFrame):
+            raise RuntimeError("To perform fit in spacecraft frame, source position must be provided in spacecraft frame.")
+        elif not isinstance(fit_convention.frame, SpacecraftFrame) and isinstance(source_vector.frame, SpacecraftFrame):
+            raise RuntimeError("To perform fit in galactic frame, source position must be provided in galactic frame.")
 
-        if isinstance(source_vector.frame, SpacecraftFrame):
-            self._source_vector = source_vector
-        else:
-            self._source_vector = source_vector.transform_to(SpacecraftFrame(attitude=source_vector.attitude))
-        
-        if isinstance(reference_vector.frame, SpacecraftFrame):
-            self._reference_vector = reference_vector
-        else:
-            self._reference_vector = reference_vector.transform_to(SpacecraftFrame(attitude=source_vector.attitude))
+        if ((isinstance(fit_convention, MEGAlibRelativeX) and response_convention != 'RelativeX') or 
+            (isinstance(fit_convention, MEGAlibRelativeY) and response_convention != 'RelativeY') or 
+            (isinstance(fit_convention, MEGAlibRelativeZ) and response_convention != 'RelativeZ')):
+            raise RuntimeError("If performing fit in spacecraft frame, fit convention must match convention of response.")
+
+        self._convention = fit_convention
+        self._response_convention = response_convention
+
+        self._source_vector = source_vector
+        self._spectrum = source_spectrum
+
+        self._data = data
+        self._background = background
+
+        self._asad_bin_edges = asad_bin_edges
+
+        self._reference_vector = self._convention.get_basis(source_vector)[0] #px
 
         self._source_vector_cartesian = [self._source_vector.cartesian.x.value,
                                          self._source_vector.cartesian.y.value, 
                                          self._source_vector.cartesian.z.value]
+
         self._reference_vector_cartesian = [self._reference_vector.cartesian.x.value, 
                                             self._reference_vector.cartesian.y.value, 
                                             self._reference_vector.cartesian.z.value]
-        
-        self._expectation, self._azimuthal_angle_bins = self.convolve_spectrum(source_spectrum, response_file, sc_orientation)
 
-        self._energy_range = [min(self.response.axes['Em'].edges.value), max(self.response.axes['Em'].edges.value)]
-        
-    def convolve_spectrum(self, spectrum, response_file, sc_orientation):
-        """
-        Convolve source spectrum with response and calculate azimuthal scattering angle bins.
 
-        Parameters
-        ----------
-        response_file : str or pathlib.Path
-            Path to detector response
-        sc_orientation : cosipy.spacecraftfile.SpacecraftFile.SpacecraftFile
-            Spacecraft orientation
+        self._response_file = response_file
+        self._response = FullDetectorResponse.open(response_file)
 
-        Returns
-        -------
-        expectation : cosipy.response.PointSourceResponse.PointSourceResponse
-            Expected counts in each bin of Compton data space
-        azimuthal_angle_bins : list
-            Centers of azimuthal scattering angle bins calculated from PsiChi bins in response
-        """
+        self._energy_range = [min(self._response.axes['Em'].edges.value), max(self._response.axes['Em'].edges.value)]
+
+        self._ori = sc_orientation
 
-        self.response = FullDetectorResponse.open(response_file)
+        self._asads = self.create_asads()
 
-        target_in_sc_frame = sc_orientation.get_target_in_sc_frame(target_name='source', target_coord=self._source_vector.transform_to('galactic'))
-        dwell_time_map = sc_orientation.get_dwell_map(response=response_file, src_path=target_in_sc_frame)
+        # Temporary workaround for empty bins in unpolarized ASAD
+        empty = np.where(self._asads['unpolarized']['counts'] == 0)[0]
+        for key in self._asads.keys():
+            if type(self._asads[key]['counts']) == dict:
+                for key_pol in self._asads[key]['counts'].keys():
+                    self._asads[key]['counts'][key_pol] = np.delete(self._asads[key]['counts'][key_pol], empty)
+                    self._asads[key]['uncertainties'][key_pol] = np.delete(self._asads[key]['uncertainties'][key_pol], empty, axis=1)
+            else:
+                self._asads[key]['counts'] = np.delete(self._asads[key]['counts'], empty)
+                self._asads[key]['uncertainties'] = np.delete(self._asads[key]['uncertainties'], empty, axis=1)
+        for index in sorted(empty, reverse=True):
+            del self._bins[index]
 
-        psr = self.response.get_point_source_response(exposure_map=dwell_time_map, coord=self._source_vector.transform_to('galactic'))
+        self._mu_100 = self.calculate_mu100(self._asads['polarized'], self._asads['unpolarized'], show_plots)
 
-        expectation = psr.get_expectation(spectrum)
+        if show_plots == True:
+            titles = {'source': 'Source ASAD', 'source & background': 'Source+background ASAD', 'background': 'Background ASAD', 'unpolarized': 'Unpolarized ASAD'}
+            for key in titles.keys():
+                self.plot_asad(self._asads[key]['counts'], self._asads[key]['uncertainties'], titles[key])
 
-        azimuthal_angle_bins = []
+        asad_corrected = self.correct_asad(self._asads['source'], self._asads['unpolarized'])
 
-        for i in range(expectation.axes['PsiChi'].nbins):
-            azimuthal_angle = self.calculate_azimuthal_scattering_angle(expectation.project(['PsiChi']).axes['PsiChi'].pix2ang(i)[0], expectation.project(['PsiChi']).axes['PsiChi'].pix2ang(i)[1])
-            azimuthal_angle_bins.append(azimuthal_angle)
+        self._asads['source (corrected)'] = asad_corrected
 
-        return expectation, azimuthal_angle_bins
+        self._mdp = self.calculate_mdp()
+
+        self._counts_corrected = asad_corrected['counts']
+
+        if isinstance(asad_corrected['uncertainties'], np.ndarray) and len(asad_corrected['uncertainties'].shape) == 2:
+            for i in range(len(asad_corrected['uncertainties'][0])):
+                if asad_corrected['uncertainties'][0][i] != asad_corrected['uncertainties'][1][i]:
+                    print('Warning: Uncertainty in at least one bin of ASAD is not Gaussian. Making error bars symmetric. Fit may not be accurate.')
+                    break
+            symmetric_sigma = []
+            for i in range(len(asad_corrected['uncertainties'][0])):
+                symmetric_sigma.append((asad_corrected['uncertainties'][0][i] + asad_corrected['uncertainties'][1][i]) / 2)
+            self._sigma = symmetric_sigma
+        else:
+            self._sigma = asad_corrected['uncertainties']
+
+    def calculate_mdp(self):
+        """
+        Calculate the minimum detectable polarization (MDP) of the source.
+        
+        Returns
+        -------
+        mdp : float
+            MDP of source
+        """
+
+        source_counts = np.sum(self._asads['source']['counts'])
+        background_counts = np.sum(self._asads['background (scaled)']['counts'])
+
+        mdp = 4.29 / self._mu_100['mu'] * np.sqrt(source_counts + background_counts) / source_counts
+
+        print('Minimum detectable polarization (MDP) of source: ' + str(round(mdp, 3)))
+
+        return mdp
 
     def calculate_azimuthal_scattering_angle(self, psi, chi):
         """
@@ -179,13 +226,58 @@ def calculate_azimuthal_scattering_angles(self, unbinned_data):
 
         azimuthal_angles = []
 
-        for i in range(len(unbinned_data['Psi local'])):
-            if unbinned_data['Energies'][i] >= self._energy_range[0] and unbinned_data['Energies'][i] <= self._energy_range[1]:
-                azimuthal_angle = self.calculate_azimuthal_scattering_angle(unbinned_data['Psi local'][i], unbinned_data['Chi local'][i])
-                azimuthal_angles.append(azimuthal_angle)
+        if isinstance(self._convention.frame, SpacecraftFrame):
+            for i in range(len(unbinned_data['Psi local'])):
+                if unbinned_data['Energies'][i] >= self._energy_range[0] and unbinned_data['Energies'][i] <= self._energy_range[1]:
+                    azimuthal_angle = self.calculate_azimuthal_scattering_angle(unbinned_data['Psi local'][i], unbinned_data['Chi local'][i])
+                    azimuthal_angles.append(azimuthal_angle)
+        else:
+            for i in range(len(unbinned_data['Psi galactic'])):
+                if unbinned_data['Energies'][i] >= self._energy_range[0] and unbinned_data['Energies'][i] <= self._energy_range[1]:
+                    azimuthal_angle = self.calculate_azimuthal_scattering_angle(unbinned_data['Psi galactic'][i], unbinned_data['Chi galactic'][i])
+                    azimuthal_angles.append(azimuthal_angle)
 
         return azimuthal_angles
 
+    def calculate_expectation(self, spectrum, polarization_level, polarization_angle):
+        """
+        Convolve source spectrum with response and calculate azimuthal scattering angle bins.
+
+        Parameters
+        ----------
+        spectrum : :py:class:`threeML.Model`
+            Spectral model.
+        polarization_level : float
+            Polarization level (between 0 and 1).
+        polarization_angle : :py:class:`cosipy.polarization.polarization_angle.PolarizationAngle`
+            Polarization angle. If in the spacecraft frame, the angle must have the same convention as the response.
+
+        Returns
+        -------
+        expectation : cosipy.response.PointSourceResponse.PointSourceResponse
+            Expected counts in each bin of Compton data space
+        azimuthal_angle_bins : list
+            Centers of azimuthal scattering angle bins calculated from PsiChi bins in response
+        """
+
+        if isinstance(self._convention.frame, SpacecraftFrame):
+            target_in_sc_frame = self._ori.get_target_in_sc_frame(target_name='source', target_coord=self._source_vector.transform_to('galactic'))
+            dwell_time_map = self._ori.get_dwell_map(response=self._response_file, src_path=target_in_sc_frame)
+            psr = self._response.get_point_source_response(exposure_map=dwell_time_map, coord=self._source_vector.transform_to('galactic'))
+            expectation = psr.get_expectation(spectrum, polarization_level, polarization_angle)
+        else:
+            scatt_map = self._ori.get_scatt_map(self._source_vector, nside=self._response.nside*2, coordsys='galactic')
+            psr = self._response.get_point_source_response(coord=self._source_vector, scatt_map=scatt_map)
+            expectation = psr.get_expectation(spectrum, polarization_level, polarization_angle, scatt_map, self._response_convention)
+
+        azimuthal_angle_bins = []
+
+        for i in range(expectation.axes['PsiChi'].nbins):
+            azimuthal_angle = self.calculate_azimuthal_scattering_angle(expectation.project(['PsiChi']).axes['PsiChi'].pix2ang(i)[0], expectation.project(['PsiChi']).axes['PsiChi'].pix2ang(i)[1])
+            azimuthal_angle_bins.append(azimuthal_angle)
+
+        return expectation, azimuthal_angle_bins
+
     def create_asad(self, azimuthal_angles, bins=20):
         """
         Create ASAD and calculate uncertainties.
@@ -218,7 +310,7 @@ def create_asad(self, azimuthal_angles, bins=20):
         asad = {'counts': counts, 'uncertainties': errors}
 
         return asad
-    
+
     def create_unpolarized_asad(self, bins=None):
         """
         Calculate the azimuthal scattering angles for all bins.
@@ -241,17 +333,19 @@ def create_unpolarized_asad(self, bins=None):
                 bin_edges = bins
         else:
             bin_edges = self._bin_edges
+
+        expectation, azimuthal_angle_bins = self.calculate_expectation(self._spectrum, 0, PolarizationAngle(Angle(0 * u.deg), self._source_vector, convention=self._convention))
         
         unpolarized_asad = []
 
         for i in range(len(bin_edges)-1):
             counts = 0
-            for j in range(self._expectation.project(['PsiChi']).nbins):
-                if self._azimuthal_angle_bins[j] >= bin_edges[i] and self._azimuthal_angle_bins[j] < bin_edges[i+1]:
-                    counts += self._expectation.project(['PsiChi'])[j]
+            for j in range(expectation.project(['PsiChi']).nbins):
+                if azimuthal_angle_bins[j] >= bin_edges[i] and azimuthal_angle_bins[j] < bin_edges[i+1]:
+                    counts += expectation.project(['PsiChi'])[j]
             unpolarized_asad.append(counts)
 
-        asad = {'counts': unpolarized_asad, 'uncertainties': calculate_uncertainties(unpolarized_asad)}
+        asad = {'counts': np.array(unpolarized_asad), 'uncertainties': calculate_uncertainties(unpolarized_asad)}
 
         return asad
     
@@ -280,20 +374,53 @@ def create_polarized_asads(self, bins=None):
         
         polarized_asads = {}
         polarized_asad_uncertainties = {}
-        for k in range(self._expectation.axes['Pol'].nbins):
+        for k in range(self._response.axes['Pol'].nbins):
             polarized_asads[k] = []
+            expectation, azimuthal_angle_bins = self.calculate_expectation(self._spectrum, 1, PolarizationAngle(Angle(self._response.axes['Pol'].centers.to_value(u.deg)[k] * u.deg), self._source_vector, convention=self._convention))
             for i in range(len(bin_edges)-1):
                 counts = 0
-                for j in range(self._expectation.project(['PsiChi']).nbins):
-                    if self._azimuthal_angle_bins[j] >= bin_edges[i] and self._azimuthal_angle_bins[j] < bin_edges[i+1]:
-                        counts += self._expectation.slice[{'Pol':slice(k,k+1)}].project(['PsiChi'])[j]
+                for j in range(self._response.axes['PsiChi'].nbins):
+                    if azimuthal_angle_bins[j] >= bin_edges[i] and azimuthal_angle_bins[j] < bin_edges[i+1]:
+                        counts += expectation.project(['PsiChi'])[j]
                 polarized_asads[k].append(counts)
+            polarized_asads[k] = np.array(polarized_asads[k])
             polarized_asad_uncertainties[k] = calculate_uncertainties(polarized_asads[k])
 
         asads = {'counts': polarized_asads, 'uncertainties': polarized_asad_uncertainties}
 
         return asads
 
+    def create_asads(self):
+        """
+        Create azimuthal scattering angle distributions from data, background model, and response.
+            
+        Returns
+        -------
+        asads : dict
+            Azimuthal scattering angle distributions (ASADs)
+        """
+
+        azimuthal_angles = {}
+        azimuthal_angles['source & background'] = self.calculate_azimuthal_scattering_angles(self._data)
+        azimuthal_angles['background'] = self.calculate_azimuthal_scattering_angles(self._background)
+
+        asads = {}
+        for key in azimuthal_angles.keys():
+            asads[key] = self.create_asad(azimuthal_angles[key], self._asad_bin_edges)
+
+        source_duration = np.max(self._data['TimeTags']) - np.min(self._data['TimeTags'])
+        background_duration = np.max(self._background['TimeTags']) - np.min(self._background['TimeTags'])
+
+        scaled_background_asad = (asads['background']['counts'] * source_duration / background_duration).astype(int)
+        source_asad = asads['source & background']['counts'] - scaled_background_asad
+
+        asads['source'] = {'counts': source_asad, 'uncertainties': calculate_uncertainties(source_asad)}
+        asads['unpolarized'] = self.create_unpolarized_asad()
+        asads['polarized'] = self.create_polarized_asads()
+        asads['background (scaled)'] = {'counts': scaled_background_asad, 'uncertainties': calculate_uncertainties(scaled_background_asad)}
+
+        return asads
+
     def asad_sinusoid(self, x, a, b, c):
         """
         Sinusoid to fit to ASAD.
@@ -452,7 +579,7 @@ def calculate_mu(self, counts_corrected, p0=None, bounds=(-np.inf, np.inf), sigm
 
         print('Modulation:', round(mu, 3), '+/-', round(mu_uncertainty, 3))
     
-        return modulation
+        return modulation, parameter_values
     
     def constant(self, x, a):
         """
@@ -473,7 +600,7 @@ def constant(self, x, a):
 
         return a
     
-    def calculate_mu100(self, polarized_asads, unpolarized_asad):
+    def calculate_mu100(self, polarized_asads, unpolarized_asad, show_plots=False):
         """
         Calculate the modulation (mu) of an 100% polarized source.
         
@@ -483,6 +610,8 @@ def calculate_mu100(self, polarized_asads, unpolarized_asad):
             Counts and Gaussian/Poisson errors in each azimuthal scattering angle bin for each polarization angle bin for 100% polarized source
         unpolarized_asad : list or np.array
             Counts and Gaussian/Poisson errors in each azimuthal scattering angle bin for unpolarized source
+        show_plots : bool, optional
+            Option to show plots. Default is False
             
         Returns
         -------
@@ -492,66 +621,59 @@ def calculate_mu100(self, polarized_asads, unpolarized_asad):
 
         mu_100_list = []
         mu_100_uncertainties = []
-        for i in range(self._expectation.axes['Pol'].nbins):
-            print('Polarization angle bin: ' + str(self._expectation.axes['Pol'].edges[i]) + ' to ' + str(self._expectation.axes['Pol'].edges[i+1]))
+        for i in range(self._response.axes['Pol'].nbins):
+            print('Polarization angle bin: ' + str(self._response.axes['Pol'].edges.to_value(u.deg)[i]) + ' to ' + str(self._response.axes['Pol'].edges.to_value(u.deg)[i+1]) + ' deg')
             asad_polarized = {'counts': polarized_asads['counts'][i], 'uncertainties': polarized_asads['uncertainties'][i]}
             asad_polarized_corrected = self.correct_asad(asad_polarized, unpolarized_asad)
-            mu_100 = self.calculate_mu(asad_polarized_corrected['counts'], bounds=([0, 0, 0], [np.inf,np.inf,np.pi]), sigma=asad_polarized_corrected['uncertainties'])
+            mu_100, coefficients = self.calculate_mu(asad_polarized_corrected['counts'], bounds=([0, 0, 0], [np.inf,np.inf,np.pi]), sigma=asad_polarized_corrected['uncertainties'])
+            fitted_angle = Angle(coefficients[2], unit=u.rad)
+            fitted_angle.wrap_at(180 * u.deg, inplace=True)
+            if fitted_angle.degree < 0:
+                fitted_angle += Angle(180, unit=u.deg)
+            print('Fitted angle: ' + str(fitted_angle.degree) + ' deg')
             mu_100_list.append(mu_100['mu'])
             mu_100_uncertainties.append(mu_100['uncertainty'])
-            self.plot_asad(asad_polarized_corrected['counts'], asad_polarized_corrected['uncertainties'], 'Corrected 100% Polarized ASAD', coefficients=self.fit(mu_100, asad_polarized_corrected['counts'], bounds=([0, 0, 0], [np.inf,np.inf,np.pi]), sigma=asad_polarized_corrected['uncertainties'])['best fit parameter values'])
+            if show_plots == True:
+                self.plot_asad(asad_polarized_corrected['counts'], asad_polarized_corrected['uncertainties'], 'Corrected 100% Polarized ASAD (' + str(int(self._response.axes['Pol'].centers[i].to_value(u.deg))) + ' deg)', coefficients=coefficients)
 
-        popt, pcov = curve_fit(self.constant, self._expectation.axes['Pol'].centers, mu_100_list, sigma=mu_100_uncertainties)
+        popt, pcov = curve_fit(self.constant, self._response.axes['Pol'].centers.to_value(u.deg), mu_100_list, sigma=mu_100_uncertainties)
         mu_100 = {'mu': popt[0], 'uncertainty': pcov[0][0]}
 
-        plt.scatter(self._expectation.axes['Pol'].centers, mu_100_list)
-        plt.errorbar(self._expectation.axes['Pol'].centers, mu_100_list, yerr=mu_100_uncertainties, linewidth=0, elinewidth=1)
-        plt.plot([0, 175], [mu_100['mu'], mu_100['mu']])
-        plt.xlabel('Polarization Angle (degrees)')
-        plt.ylabel('mu_100')
-        plt.show()
+        if show_plots == True:
+            plt.scatter(self._response.axes['Pol'].centers.to_value(u.deg), mu_100_list)
+            plt.errorbar(self._response.axes['Pol'].centers.to_value(u.deg), mu_100_list, yerr=mu_100_uncertainties, linewidth=0, elinewidth=1)
+            plt.plot([0, 175], [mu_100['mu'], mu_100['mu']])
+            plt.xlabel('Polarization Angle (degrees)')
+            plt.ylabel('mu_100')
+            plt.show()
 
         print('mu_100:', round(mu_100['mu'], 2))
 
         return mu_100
 
-    def fit(self, mu_100, counts_corrected, p0=None, bounds=(-np.inf, np.inf), sigma=None):
+    def fit(self, p0=None, bounds=([0, 0, 0], [np.inf,np.inf,np.pi]), show_plots=False):
         """
         Fit the polarization fraction and angle.
         
         Parameters
         ----------
-        mu_100 : dict
-            Modulation and uncertainty of a 100% polarized source
-        counts_corrected : list
-            Counts in each azimuthal scattering angle bin
-        p0 : list or np.array
+        p0 : list or np.array, optional
             Initial guess for parameter values
-        bounds : 2-tuple of float, list, or np.array
-            Lower & upper bounds on parameters
-        sigma : float, list, or np.array
-            Uncertainties for each azimuthal scattering angle bin
+        bounds : 2-tuple of float, list, or np.array, optional
+            Lower & upper bounds on parameters. Default is ([0, 0, 0], [np.inf,np.inf,np.pi])
+        show_plots : bool, optional
+            Option to show plots. Default is False
             
         Returns
         -------
         polarization : dict
-            Polarization fraction, polarization angle, and best fit parameter values for fitted sinusoid, and associated uncertainties
+            Polarization fraction, polarization angle in the IAU convention, and best fit parameter values for fitted sinusoid, and associated uncertainties
         """
 
-        if isinstance(sigma, np.ndarray) and len(sigma.shape) == 2:
-            for i in range(len(sigma[0])):
-                if sigma[0][i] != sigma[1][i]:
-                    print('Warning: Uncertainty in at least one bin of ASAD is not Gaussian. Making error bars symmetric. Fit may not be accurate.')
-                    break
-            symmetric_sigma = []
-            for i in range(len(sigma[0])):
-                symmetric_sigma.append((sigma[0][i] + sigma[1][i]) / 2)
-            sigma = symmetric_sigma
-
-        parameter_values, uncertainties = self.fit_asad(counts_corrected, p0, bounds, sigma)
+        parameter_values, uncertainties = self.fit_asad(self._counts_corrected, p0, bounds, self._sigma)
     
-        polarization_fraction = parameter_values[1] / (parameter_values[0] * mu_100['mu'])
-        polarization_fraction_uncertainty = polarization_fraction * np.sqrt((uncertainties[0]/parameter_values[0])**2 + (uncertainties[1]/parameter_values[1])**2 + (mu_100['uncertainty']/mu_100['mu'])**2)
+        polarization_fraction = parameter_values[1] / (parameter_values[0] * self._mu_100['mu'])
+        polarization_fraction_uncertainty = polarization_fraction * np.sqrt((uncertainties[0]/parameter_values[0])**2 + (uncertainties[1]/parameter_values[1])**2 + (self._mu_100['uncertainty']/self._mu_100['mu'])**2)
 
         polarization_angle = Angle(parameter_values[2], unit=u.rad)
         polarization_angle.wrap_at(180 * u.deg, inplace=True)
@@ -564,5 +686,11 @@ def fit(self, mu_100, counts_corrected, p0=None, bounds=(-np.inf, np.inf), sigma
     
         print('Best fit polarization fraction:', round(polarization_fraction, 3), '+/-', round(polarization_fraction_uncertainty, 3))
         print('Best fit polarization angle:', round(polarization_angle.angle.degree, 3), '+/-', round(polarization_angle_uncertainty.degree, 3))
+
+        if self._mdp > polarization['fraction']:
+            print('Polarization fraction is below MDP!', 'MDP:', round(self._mdp, 3))
+
+        if show_plots == True:
+            self.plot_asad(self._counts_corrected, self._asads['source (corrected)']['uncertainties'], 'Corrected Source ASAD', coefficients=polarization['best fit parameter values'])
         
         return polarization

From 1f1ae5896b0b0de3b01361170e6bd03769df4b8c Mon Sep 17 00:00:00 2001
From: Eliza Neights <eneights@gmail.com>
Date: Thu, 27 Feb 2025 18:48:48 -0500
Subject: [PATCH 04/31] Minor update

---
 cosipy/response/PointSourceResponse.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/cosipy/response/PointSourceResponse.py b/cosipy/response/PointSourceResponse.py
index 55a3abff..2860b394 100644
--- a/cosipy/response/PointSourceResponse.py
+++ b/cosipy/response/PointSourceResponse.py
@@ -142,7 +142,6 @@ def get_expectation(self, spectrum, polarization_level=None, polarization_angle=
                 for i in range(len(self.axes['Pol'].edges) - 1):
 
                     response_slice = self.slice[{'Pol':slice(i,i+1)}].project('Ei', 'Em', 'Phi', 'PsiChi')
-                    bin_center = (self.axes['Pol'].edges.to_value(u.deg)[i] + self.axes['Pol'].edges.to_value(u.deg)[i+1]) / 2
 
                     for j, (pixels, exposure) in enumerate(zip(scatt_map.contents.coords.transpose(), scatt_map.contents.data)):
 
@@ -157,7 +156,7 @@ def get_expectation(self, spectrum, polarization_level=None, polarization_angle=
                         else:
                             raise RuntimeError("Response convention must be 'RelativeX', 'RelativeY', or 'RelativeZ'")
 
-                        polarization_angle_bin_center = PolarizationAngle(bin_center * u.deg, polarization_angle.skycoord, convention=this_convention)
+                        polarization_angle_bin_center = PolarizationAngle(self.axes['Pol'].centers.to_value(u.deg)[i] * u.deg, polarization_angle.skycoord, convention=this_convention)
 
                         polarization_angle_galactic = polarization_angle_bin_center.transform_to(polarization_angle.convention)
 

From ad5c3d6841929120df4d150db08aa0f9d7df84ea Mon Sep 17 00:00:00 2001
From: Eliza Neights <eneights@gmail.com>
Date: Thu, 6 Mar 2025 11:35:55 -0500
Subject: [PATCH 05/31] Minor changes to point source response

---
 cosipy/response/PointSourceResponse.py | 6 ++----
 1 file changed, 2 insertions(+), 4 deletions(-)

diff --git a/cosipy/response/PointSourceResponse.py b/cosipy/response/PointSourceResponse.py
index 2860b394..6aa6e24f 100644
--- a/cosipy/response/PointSourceResponse.py
+++ b/cosipy/response/PointSourceResponse.py
@@ -139,7 +139,7 @@ def get_expectation(self, spectrum, polarization_level=None, polarization_angle=
                 if polarization_angle.angle.deg == 180.:
                     polarization_angle = PolarizationAngle(0. * u.deg, polarization_angle.skycoord, convention=polarization_angle.convention)
 
-                for i in range(len(self.axes['Pol'].edges) - 1):
+                for i in range(self.axes['Pol'].nbins):
 
                     response_slice = self.slice[{'Pol':slice(i,i+1)}].project('Ei', 'Em', 'Phi', 'PsiChi')
 
@@ -156,9 +156,7 @@ def get_expectation(self, spectrum, polarization_level=None, polarization_angle=
                         else:
                             raise RuntimeError("Response convention must be 'RelativeX', 'RelativeY', or 'RelativeZ'")
 
-                        polarization_angle_bin_center = PolarizationAngle(self.axes['Pol'].centers.to_value(u.deg)[i] * u.deg, polarization_angle.skycoord, convention=this_convention)
-
-                        polarization_angle_galactic = polarization_angle_bin_center.transform_to(polarization_angle.convention)
+                        polarization_angle_galactic = PolarizationAngle(self.axes['Pol'].centers.to_value(u.deg)[i] * u.deg, polarization_angle.skycoord, convention=this_convention).transform_to(polarization_angle.convention)
 
                         if polarization_angle_galactic.angle.deg == 180.:
                             polarization_angle_galactic = PolarizationAngle(0. * u.deg, polarization_angle_galactic.skycoord, convention=polarization_angle_galactic.convention)

From e975ff5fd6d4d97fb88bb708616a716c0dcdb899 Mon Sep 17 00:00:00 2001
From: Eliza Neights <eneights@gmail.com>
Date: Tue, 11 Mar 2025 10:48:47 -0400
Subject: [PATCH 06/31] Fix errors in azimuthal scattering angle calculation

---
 cosipy/polarization/polarization_asad.py | 47 ++++++++++++------------
 cosipy/response/PointSourceResponse.py   |  2 +-
 2 files changed, 24 insertions(+), 25 deletions(-)

diff --git a/cosipy/polarization/polarization_asad.py b/cosipy/polarization/polarization_asad.py
index 02f3df1c..98dd82f9 100644
--- a/cosipy/polarization/polarization_asad.py
+++ b/cosipy/polarization/polarization_asad.py
@@ -1,5 +1,5 @@
 import numpy as np
-from astropy.coordinates import Angle
+from astropy.coordinates import Angle, SkyCoord
 import astropy.units as u
 from astropy.stats import poisson_conf_interval
 from astropy.time import Time
@@ -73,8 +73,8 @@ def __init__(self, source_vector, source_spectrum, asad_bin_edges, data, backgro
 
         if isinstance(fit_convention.frame, SpacecraftFrame) and not isinstance(source_vector.frame, SpacecraftFrame):
             raise RuntimeError("To perform fit in spacecraft frame, source position must be provided in spacecraft frame.")
-        elif not isinstance(fit_convention.frame, SpacecraftFrame) and isinstance(source_vector.frame, SpacecraftFrame):
-            raise RuntimeError("To perform fit in galactic frame, source position must be provided in galactic frame.")
+        elif not isinstance(fit_convention.frame, SpacecraftFrame):
+            source_vector = source_vector.transform_to('icrs')
 
         if ((isinstance(fit_convention, MEGAlibRelativeX) and response_convention != 'RelativeX') or 
             (isinstance(fit_convention, MEGAlibRelativeY) and response_convention != 'RelativeY') or 
@@ -102,7 +102,6 @@ def __init__(self, source_vector, source_spectrum, asad_bin_edges, data, backgro
                                             self._reference_vector.cartesian.y.value, 
                                             self._reference_vector.cartesian.z.value]
 
-
         self._response_file = response_file
         self._response = FullDetectorResponse.open(response_file)
 
@@ -112,19 +111,6 @@ def __init__(self, source_vector, source_spectrum, asad_bin_edges, data, backgro
 
         self._asads = self.create_asads()
 
-        # Temporary workaround for empty bins in unpolarized ASAD
-        empty = np.where(self._asads['unpolarized']['counts'] == 0)[0]
-        for key in self._asads.keys():
-            if type(self._asads[key]['counts']) == dict:
-                for key_pol in self._asads[key]['counts'].keys():
-                    self._asads[key]['counts'][key_pol] = np.delete(self._asads[key]['counts'][key_pol], empty)
-                    self._asads[key]['uncertainties'][key_pol] = np.delete(self._asads[key]['uncertainties'][key_pol], empty, axis=1)
-            else:
-                self._asads[key]['counts'] = np.delete(self._asads[key]['counts'], empty)
-                self._asads[key]['uncertainties'] = np.delete(self._asads[key]['uncertainties'], empty, axis=1)
-        for index in sorted(empty, reverse=True):
-            del self._bins[index]
-
         self._mu_100 = self.calculate_mu100(self._asads['polarized'], self._asads['unpolarized'], show_plots)
 
         if show_plots == True:
@@ -234,7 +220,8 @@ def calculate_azimuthal_scattering_angles(self, unbinned_data):
         else:
             for i in range(len(unbinned_data['Psi galactic'])):
                 if unbinned_data['Energies'][i] >= self._energy_range[0] and unbinned_data['Energies'][i] <= self._energy_range[1]:
-                    azimuthal_angle = self.calculate_azimuthal_scattering_angle(unbinned_data['Psi galactic'][i], unbinned_data['Chi galactic'][i])
+                    psichi_skycoord = SkyCoord(l=unbinned_data['Chi galactic'][i], b=unbinned_data['Psi galactic'][i], frame='galactic', unit=u.deg).transform_to('icrs')
+                    azimuthal_angle = self.calculate_azimuthal_scattering_angle((np.pi/2) - psichi_skycoord.dec.rad, psichi_skycoord.ra.rad)
                     azimuthal_angles.append(azimuthal_angle)
 
         return azimuthal_angles
@@ -261,20 +248,29 @@ def calculate_expectation(self, spectrum, polarization_level, polarization_angle
         """
 
         if isinstance(self._convention.frame, SpacecraftFrame):
+            
             target_in_sc_frame = self._ori.get_target_in_sc_frame(target_name='source', target_coord=self._source_vector.transform_to('galactic'))
             dwell_time_map = self._ori.get_dwell_map(response=self._response_file, src_path=target_in_sc_frame)
             psr = self._response.get_point_source_response(exposure_map=dwell_time_map, coord=self._source_vector.transform_to('galactic'))
             expectation = psr.get_expectation(spectrum, polarization_level, polarization_angle)
+            
+            azimuthal_angle_bins = []
+
+            for i in range(expectation.axes['PsiChi'].nbins):
+                azimuthal_angle = self.calculate_azimuthal_scattering_angle(expectation.axes['PsiChi'].pix2ang(i)[0], expectation.axes['PsiChi'].pix2ang(i)[1])
+                azimuthal_angle_bins.append(azimuthal_angle)
+        
         else:
+            
             scatt_map = self._ori.get_scatt_map(self._source_vector, nside=self._response.nside*2, coordsys='galactic')
             psr = self._response.get_point_source_response(coord=self._source_vector, scatt_map=scatt_map)
             expectation = psr.get_expectation(spectrum, polarization_level, polarization_angle, scatt_map, self._response_convention)
 
-        azimuthal_angle_bins = []
+            azimuthal_angle_bins = []
 
-        for i in range(expectation.axes['PsiChi'].nbins):
-            azimuthal_angle = self.calculate_azimuthal_scattering_angle(expectation.project(['PsiChi']).axes['PsiChi'].pix2ang(i)[0], expectation.project(['PsiChi']).axes['PsiChi'].pix2ang(i)[1])
-            azimuthal_angle_bins.append(azimuthal_angle)
+            for i in range(expectation.axes['PsiChi'].nbins):
+                azimuthal_angle = self.calculate_azimuthal_scattering_angle((np.pi/2) - expectation.axes['PsiChi'].pix2skycoord(i).transform_to('icrs').dec.rad, expectation.axes['PsiChi'].pix2skycoord(i).transform_to('icrs').ra.rad)
+                azimuthal_angle_bins.append(azimuthal_angle)
 
         return expectation, azimuthal_angle_bins
 
@@ -630,7 +626,10 @@ def calculate_mu100(self, polarized_asads, unpolarized_asad, show_plots=False):
             fitted_angle.wrap_at(180 * u.deg, inplace=True)
             if fitted_angle.degree < 0:
                 fitted_angle += Angle(180, unit=u.deg)
-            print('Fitted angle: ' + str(fitted_angle.degree) + ' deg')
+            diff = fitted_angle.deg - self._response.axes['Pol'].centers.to_value(u.deg)[i]
+            if diff < 0:
+                diff = 180 - diff
+            print('Fitted angle: ' + str(fitted_angle.degree) + ' deg, difference:', diff)
             mu_100_list.append(mu_100['mu'])
             mu_100_uncertainties.append(mu_100['uncertainty'])
             if show_plots == True:
@@ -685,7 +684,7 @@ def fit(self, p0=None, bounds=([0, 0, 0], [np.inf,np.inf,np.pi]), show_plots=Fal
         polarization = {'fraction': polarization_fraction, 'angle': polarization_angle, 'fraction uncertainty': polarization_fraction_uncertainty, 'angle uncertainty': polarization_angle_uncertainty, 'best fit parameter values': parameter_values, 'best fit parameter uncertainties': uncertainties}
     
         print('Best fit polarization fraction:', round(polarization_fraction, 3), '+/-', round(polarization_fraction_uncertainty, 3))
-        print('Best fit polarization angle:', round(polarization_angle.angle.degree, 3), '+/-', round(polarization_angle_uncertainty.degree, 3))
+        print('Best fit polarization angle (IAU convention):', round(polarization_angle.angle.degree, 3), '+/-', round(polarization_angle_uncertainty.degree, 3))
 
         if self._mdp > polarization['fraction']:
             print('Polarization fraction is below MDP!', 'MDP:', round(self._mdp, 3))
diff --git a/cosipy/response/PointSourceResponse.py b/cosipy/response/PointSourceResponse.py
index 6aa6e24f..44fb0f9e 100644
--- a/cosipy/response/PointSourceResponse.py
+++ b/cosipy/response/PointSourceResponse.py
@@ -168,7 +168,7 @@ def get_expectation(self, spectrum, polarization_level=None, polarization_angle=
                         else:
                             polarization_angle_components[polarization_angle_index] = response_slice * exposure / np.sum(scatt_map.project('x'))
 
-                for i in range(len(self.axes['Pol'].edges) - 1):
+                for i in range(self.axes['Pol'].nbins):
 
                     if polarization_angle.angle.deg >= self.axes['Pol'].edges.to_value(u.deg)[i] and polarization_angle.angle.deg < self.axes['Pol'].edges.to_value(u.deg)[i+1]:
                         polarized_component = polarization_angle_components[i].contents

From d0a57e5fd398ce4287c00277a393ba7f1229e5bc Mon Sep 17 00:00:00 2001
From: Eliza Neights <eneights@gmail.com>
Date: Tue, 11 Mar 2025 15:07:01 -0400
Subject: [PATCH 07/31] Add from_scattering_direction() to polarization_angle

---
 cosipy/polarization/polarization_angle.py | 75 +++++++++++++++++++++++
 1 file changed, 75 insertions(+)

diff --git a/cosipy/polarization/polarization_angle.py b/cosipy/polarization/polarization_angle.py
index 07aa04ac..931cf7b6 100644
--- a/cosipy/polarization/polarization_angle.py
+++ b/cosipy/polarization/polarization_angle.py
@@ -100,4 +100,79 @@ def transform_to(self, convention, *args, **kwargs):
                                  self.skycoord,
                                  convention = convention2)
 
+    @classmethod
+    def from_scattering_direction(cls, psichi, source_coord, convention):
+        """
+        Calculate the azimuthal scattering angle of a scattered photon.
+        
+        Parameters
+        ----------
+        psichi : astropy.coordinates.SkyCoord
+            Scattered photon direction
+        source_coord : astropy.coordinates.SkyCoord
+            Source direction
+        convention :
+            cosipy.polarization.PolarizationConvention
+
+        Returns
+        -------
+        azimuthal_scattering_angle : cosipy.polarization.PolarizationAngle
+            Azimuthal scattering angle
+        """
+
+        if not psichi.frame.name == source_coord.frame.name:
+            raise RuntimeError('psichi and source_coord must have the same frame')
+
+        reference_coord = convention.get_basis(source_coord)[0]
+
+        source_vector_cartesian = [source_coord.cartesian.x.value,
+                                   source_coord.cartesian.y.value, 
+                                   source_coord.cartesian.z.value]
+
+        reference_vector_cartesian = [reference_coord.cartesian.x.value, 
+                                      reference_coord.cartesian.y.value,
+                                      reference_coord.cartesian.z.value]
+
+        if psichi.frame.name == 'spacecraftframe':
+
+            psi = (np.pi/2) - psichi.lat.rad
+            chi = psichi.lon.rad
+
+        elif psichi.frame.name == 'galactic':
+
+            psi = (np.pi/2) - psichi.b.rad
+            chi = psichi.l.rad
+
+        elif psichi.frame.name == 'icrs':
+
+            psi = (np.pi/2) - psichi.dec.rad
+            chi = psichi.ra.rad
+
+        else:
+            raise RuntimeError('Unsupported frame "' + psichi.frame.name + '"')
+
+        # Convert scattered photon vector from spherical to Cartesian coordinates
+        scattered_photon_vector = [np.sin(psi) * np.cos(chi), np.sin(psi) * np.sin(chi), np.cos(psi)]
+
+        # Project scattered photon vector onto plane perpendicular to source direction
+        d = np.dot(scattered_photon_vector, source_vector_cartesian) / np.dot(source_vector_cartesian, source_vector_cartesian)
+        projection = [scattered_photon_vector[0] - (d * source_vector_cartesian[0]), 
+                      scattered_photon_vector[1] - (d * source_vector_cartesian[1]), 
+                      scattered_photon_vector[2] - (d * source_vector_cartesian[2])]
+
+        # Calculate angle between scattered photon vector & reference vector on plane perpendicular to source direction
+        cross_product = np.cross(projection, reference_vector_cartesian)
+        if np.dot(source_vector_cartesian, cross_product) < 0:
+            sign = -1
+        else:
+            sign = 1
+        normalization = np.sqrt(np.dot(projection, projection)) * np.sqrt(np.dot(reference_vector_cartesian, reference_vector_cartesian))
+    
+        angle = Angle(sign * np.arccos(np.dot(projection, reference_vector_cartesian) / normalization), unit=u.rad)
+
+        azimuthal_scattering_angle = cls(angle, source_coord, convention=convention)
+
+        return azimuthal_scattering_angle
+
+
         

From d29b41bae7cd615c6aa4818a1f01aeefd1253802 Mon Sep 17 00:00:00 2001
From: Eliza Neights <eneights@gmail.com>
Date: Tue, 11 Mar 2025 15:18:57 -0400
Subject: [PATCH 08/31] Update polarization angle unit test

---
 tests/polarization/test_polarization_angle.py | 17 +++++++++++++++--
 1 file changed, 15 insertions(+), 2 deletions(-)

diff --git a/tests/polarization/test_polarization_angle.py b/tests/polarization/test_polarization_angle.py
index 4b6b3641..7877ce62 100644
--- a/tests/polarization/test_polarization_angle.py
+++ b/tests/polarization/test_polarization_angle.py
@@ -6,6 +6,7 @@
 import astropy.units as u
 from cosipy.polarization import OrthographicConvention, StereographicConvention
 from scoords import SpacecraftFrame, Attitude
+from cosipy.polarization.conventions import MEGAlibRelativeX, IAUPolarizationConvention
 
 # Define common test data
 source_direction = SkyCoord(ra = -36*u.deg, dec = 30*u.deg, frame = 'icrs')
@@ -35,5 +36,17 @@ def test_pa_transformation():
     
     assert np.isclose(pa2.angle, 165.46460289540*u.deg)
     
-    
-    
+def test_from_scattering_direction():
+
+    psichi = SkyCoord(lat=np.pi/8, lon=np.pi/6, unit=u.rad, frame=SpacecraftFrame(attitude = Attitude.identity()))
+    pa = PolarizationAngle.from_scattering_direction(psichi, source_direction.transform_to(SpacecraftFrame(attitude = Attitude.identity())), MEGAlibRelativeX(attitude = Attitude.identity()))
+
+    assert np.isclose(pa.angle, -134.186*u.deg)
+
+    pa2 = PolarizationAngle.from_scattering_direction(psichi.transform_to('galactic'), source_direction.transform_to('galactic'), IAUPolarizationConvention())
+
+    assert np.isclose(pa2.angle, 97.930*u.deg)
+
+    pa3 = PolarizationAngle.from_scattering_direction(psichi.transform_to('icrs'), source_direction, IAUPolarizationConvention())
+
+    assert np.isclose(pa3.angle, 80.349*u.deg)

From 8e566b7ee9916d1598c042fb96a37789d5d540b6 Mon Sep 17 00:00:00 2001
From: Eliza Neights <eneights@gmail.com>
Date: Tue, 11 Mar 2025 16:55:43 -0400
Subject: [PATCH 09/31] Remove calculate_uncertainties

---
 cosipy/polarization/__init__.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/cosipy/polarization/__init__.py b/cosipy/polarization/__init__.py
index cbd3de4f..08187a3b 100644
--- a/cosipy/polarization/__init__.py
+++ b/cosipy/polarization/__init__.py
@@ -1,3 +1,3 @@
-from .polarization_asad import PolarizationASAD, calculate_uncertainties
+from .polarization_asad import PolarizationASAD
 from .conventions import PolarizationConvention, OrthographicConvention, StereographicConvention, IAUPolarizationConvention
 from .polarization_angle import PolarizationAngle

From dbc2088298fa81bba306b85bf817a24a3e733ec3 Mon Sep 17 00:00:00 2001
From: Eliza Neights <eneights@gmail.com>
Date: Tue, 11 Mar 2025 17:27:01 -0400
Subject: [PATCH 10/31] Update uncertainty handling and change asad
 dictionaries to histograms

---
 cosipy/polarization/polarization_asad.py | 248 ++++++++---------------
 1 file changed, 80 insertions(+), 168 deletions(-)

diff --git a/cosipy/polarization/polarization_asad.py b/cosipy/polarization/polarization_asad.py
index 98dd82f9..9baa5387 100644
--- a/cosipy/polarization/polarization_asad.py
+++ b/cosipy/polarization/polarization_asad.py
@@ -9,37 +9,10 @@
 from cosipy.polarization.conventions import MEGAlibRelativeX, MEGAlibRelativeY, MEGAlibRelativeZ, IAUPolarizationConvention
 from cosipy.response import FullDetectorResponse
 from scoords import SpacecraftFrame
+from histpy import Histogram
 
-def calculate_uncertainties(counts):
-    """
-    Calculate the Poisson/Gaussian uncertainties for a list of binned counts.
-        
-    Parameters
-    ----------
-    counts : list
-        List of counts in each bin
-
-    Returns
-    -------
-    uncertainties : np.ndarray
-        Lower & upper uncertainties for each bin
-    """
-    
-    uncertainties_low = []
-    uncertainties_high = []
-    for i in range(len(counts)):
-        if counts[i] <= 5:
-            poisson_uncertainty = poisson_conf_interval(counts[i], interval="frequentist-confidence", sigma=1)
-            uncertainties_low.append(counts[i] - poisson_uncertainty[0])
-            uncertainties_high.append(poisson_uncertainty[1] - counts[i])
-        else:
-            gaussian_uncertainty = np.sqrt(counts[i])
-            uncertainties_low.append(gaussian_uncertainty)
-            uncertainties_high.append(gaussian_uncertainty)
-
-    uncertainties = np.array([uncertainties_low, uncertainties_high])
-        
-    return uncertainties
+import logging
+logger = logging.getLogger(__name__)
 
 class PolarizationASAD():
     """
@@ -109,35 +82,26 @@ def __init__(self, source_vector, source_spectrum, asad_bin_edges, data, backgro
 
         self._ori = sc_orientation
 
-        self._asads = self.create_asads()
+        self._asads, source_duration, background_duration = self.create_asads()
 
         self._mu_100 = self.calculate_mu100(self._asads['polarized'], self._asads['unpolarized'], show_plots)
 
         if show_plots == True:
             titles = {'source': 'Source ASAD', 'source & background': 'Source+background ASAD', 'background': 'Background ASAD', 'unpolarized': 'Unpolarized ASAD'}
             for key in titles.keys():
-                self.plot_asad(self._asads[key]['counts'], self._asads[key]['uncertainties'], titles[key])
+                if key == 'source & background' or key == 'background':
+                    self.plot_asad(self._asads[key].contents.data, titles[key], self._asads[key].bin_error[:])
+                elif key == 'source':
+                    self.plot_asad(self._asads[key].contents.data, titles[key], np.sqrt(self._asads['source & background'].bin_error[:]**2 + (self._asads['background'].bin_error[:] * source_duration / background_duration)**2))
+                else:
+                    self.plot_asad(self._asads[key].contents.data, titles[key])
 
-        asad_corrected = self.correct_asad(self._asads['source'], self._asads['unpolarized'])
+        asad_corrected, self._sigma = self.correct_asad(self._asads['source'], self._asads['unpolarized'], np.sqrt(self._asads['source & background'].bin_error[:]**2 + (self._asads['background'].bin_error[:] * source_duration / background_duration)**2))
 
         self._asads['source (corrected)'] = asad_corrected
 
         self._mdp = self.calculate_mdp()
 
-        self._counts_corrected = asad_corrected['counts']
-
-        if isinstance(asad_corrected['uncertainties'], np.ndarray) and len(asad_corrected['uncertainties'].shape) == 2:
-            for i in range(len(asad_corrected['uncertainties'][0])):
-                if asad_corrected['uncertainties'][0][i] != asad_corrected['uncertainties'][1][i]:
-                    print('Warning: Uncertainty in at least one bin of ASAD is not Gaussian. Making error bars symmetric. Fit may not be accurate.')
-                    break
-            symmetric_sigma = []
-            for i in range(len(asad_corrected['uncertainties'][0])):
-                symmetric_sigma.append((asad_corrected['uncertainties'][0][i] + asad_corrected['uncertainties'][1][i]) / 2)
-            self._sigma = symmetric_sigma
-        else:
-            self._sigma = asad_corrected['uncertainties']
-
     def calculate_mdp(self):
         """
         Calculate the minimum detectable polarization (MDP) of the source.
@@ -148,53 +112,15 @@ def calculate_mdp(self):
             MDP of source
         """
 
-        source_counts = np.sum(self._asads['source']['counts'])
-        background_counts = np.sum(self._asads['background (scaled)']['counts'])
+        source_counts = np.sum(self._asads['source'].contents.data)
+        background_counts = np.sum(self._asads['background (scaled)'].contents.data)
 
         mdp = 4.29 / self._mu_100['mu'] * np.sqrt(source_counts + background_counts) / source_counts
 
-        print('Minimum detectable polarization (MDP) of source: ' + str(round(mdp, 3)))
+        logger.info('Minimum detectable polarization (MDP) of source: ' + str(round(mdp, 3)))
 
         return mdp
 
-    def calculate_azimuthal_scattering_angle(self, psi, chi):
-        """
-        Calculate the azimuthal scattering angle of a scattered photon.
-        
-        Parameters
-        ----------
-        psi : float
-            Polar angle (radians) of scattered photon in local coordinates
-        chi : float
-            Azimuthal angle (radians) of scattered photon in local coordinates
-
-        Returns
-        -------
-        azimuthal_angle : astropy.coordinates.Angle
-            Azimuthal scattering angle defined with respect to given reference vector
-        """
-        
-        # Convert scattered photon vector from spherical to Cartesian coordinates
-        scattered_photon_vector = [np.sin(psi) * np.cos(chi), np.sin(psi) * np.sin(chi), np.cos(psi)]
-
-        # Project scattered photon vector onto plane perpendicular to source direction
-        d = np.dot(scattered_photon_vector, self._source_vector_cartesian) / np.dot(self._source_vector_cartesian, self._source_vector_cartesian)
-        projection = [scattered_photon_vector[0] - (d * self._source_vector_cartesian[0]), 
-                      scattered_photon_vector[1] - (d * self._source_vector_cartesian[1]), 
-                      scattered_photon_vector[2] - (d * self._source_vector_cartesian[2])]
-
-        # Calculate angle between scattered photon vector & reference vector on plane perpendicular to source direction
-        cross_product = np.cross(projection, self._reference_vector_cartesian)
-        if np.dot(self._source_vector_cartesian, cross_product) < 0:
-            sign = -1
-        else:
-            sign = 1
-        normalization = np.sqrt(np.dot(projection, projection)) * np.sqrt(np.dot(self._reference_vector_cartesian, self._reference_vector_cartesian))
-    
-        azimuthal_angle = Angle(sign * np.arccos(np.dot(projection, self._reference_vector_cartesian) / normalization), unit=u.rad)
-    
-        return azimuthal_angle
-
     def calculate_azimuthal_scattering_angles(self, unbinned_data):
         """
         Calculate the azimuthal scattering angles for all events in a dataset.
@@ -206,8 +132,8 @@ def calculate_azimuthal_scattering_angles(self, unbinned_data):
 
         Returns
         -------
-        azimuthal_angles : list
-            Azimuthal scattering angles. Each angle must be an astropy.coordinates.Angle object
+        azimuthal_angles : list of astropy.coordinates.Angle
+            Azimuthal scattering angles
         """
 
         azimuthal_angles = []
@@ -215,14 +141,15 @@ def calculate_azimuthal_scattering_angles(self, unbinned_data):
         if isinstance(self._convention.frame, SpacecraftFrame):
             for i in range(len(unbinned_data['Psi local'])):
                 if unbinned_data['Energies'][i] >= self._energy_range[0] and unbinned_data['Energies'][i] <= self._energy_range[1]:
-                    azimuthal_angle = self.calculate_azimuthal_scattering_angle(unbinned_data['Psi local'][i], unbinned_data['Chi local'][i])
-                    azimuthal_angles.append(azimuthal_angle)
+                    psichi = SkyCoord(lat=(np.pi/2) - unbinned_data['Psi local'][i], lon=unbinned_data['Chi local'][i], unit=u.rad, frame=self._convention.frame)
+                    azimuthal_angle = PolarizationAngle.from_scattering_direction(psichi, self._source_vector, self._convention)
+                    azimuthal_angles.append(azimuthal_angle.angle)
         else:
             for i in range(len(unbinned_data['Psi galactic'])):
                 if unbinned_data['Energies'][i] >= self._energy_range[0] and unbinned_data['Energies'][i] <= self._energy_range[1]:
-                    psichi_skycoord = SkyCoord(l=unbinned_data['Chi galactic'][i], b=unbinned_data['Psi galactic'][i], frame='galactic', unit=u.deg).transform_to('icrs')
-                    azimuthal_angle = self.calculate_azimuthal_scattering_angle((np.pi/2) - psichi_skycoord.dec.rad, psichi_skycoord.ra.rad)
-                    azimuthal_angles.append(azimuthal_angle)
+                    psichi = SkyCoord(l=unbinned_data['Chi galactic'][i], b=unbinned_data['Psi galactic'][i], frame='galactic', unit=u.deg).transform_to('icrs')
+                    azimuthal_angle = PolarizationAngle.from_scattering_direction(psichi, self._source_vector, self._convention)
+                    azimuthal_angles.append(azimuthal_angle.angle)
 
         return azimuthal_angles
 
@@ -257,8 +184,9 @@ def calculate_expectation(self, spectrum, polarization_level, polarization_angle
             azimuthal_angle_bins = []
 
             for i in range(expectation.axes['PsiChi'].nbins):
-                azimuthal_angle = self.calculate_azimuthal_scattering_angle(expectation.axes['PsiChi'].pix2ang(i)[0], expectation.axes['PsiChi'].pix2ang(i)[1])
-                azimuthal_angle_bins.append(azimuthal_angle)
+                psichi = SkyCoord(lat=(np.pi/2) - expectation.axes['PsiChi'].pix2ang(i)[0], lon=expectation.axes['PsiChi'].pix2ang(i)[1], unit=u.rad, frame=self._convention.frame)
+                azimuthal_angle = PolarizationAngle.from_scattering_direction(psichi, self._source_vector, self._convention)
+                azimuthal_angle_bins.append(azimuthal_angle.angle)
         
         else:
             
@@ -269,8 +197,9 @@ def calculate_expectation(self, spectrum, polarization_level, polarization_angle
             azimuthal_angle_bins = []
 
             for i in range(expectation.axes['PsiChi'].nbins):
-                azimuthal_angle = self.calculate_azimuthal_scattering_angle((np.pi/2) - expectation.axes['PsiChi'].pix2skycoord(i).transform_to('icrs').dec.rad, expectation.axes['PsiChi'].pix2skycoord(i).transform_to('icrs').ra.rad)
-                azimuthal_angle_bins.append(azimuthal_angle)
+                psichi = expectation.axes['PsiChi'].pix2skycoord(i)
+                azimuthal_angle = PolarizationAngle.from_scattering_direction(psichi, self._source_vector, self._convention)
+                azimuthal_angle_bins.append(azimuthal_angle.angle)
 
         return expectation, azimuthal_angle_bins
 
@@ -287,8 +216,8 @@ def create_asad(self, azimuthal_angles, bins=20):
 
         Returns
         -------
-        asad : dict
-            Counts and Gaussian/Poisson errors in each azimuthal scattering angle bin
+        asad : histpy.Histogram
+            Counts in each azimuthal scattering angle bin
         """
 
         if isinstance(bins, int):
@@ -297,13 +226,10 @@ def create_asad(self, azimuthal_angles, bins=20):
             bin_edges = bins
 
         counts, edges = np.histogram(azimuthal_angles, bins=bin_edges)
-        self._bin_edges = edges
-        self._bins = []
-        for i in range(len(self._bin_edges) - 1):
-            self._bins.append((self._bin_edges[i] + self._bin_edges[i+1]) / 2)
-        errors = calculate_uncertainties(counts)
 
-        asad = {'counts': counts, 'uncertainties': errors}
+        asad = Histogram(edges, contents=counts)
+        self._bin_edges = asad.axis.edges
+        self._bins = asad.axis.centers
 
         return asad
 
@@ -318,8 +244,8 @@ def create_unpolarized_asad(self, bins=None):
 
         Returns
         -------
-        asad : dict
-            Counts and Gaussian/Poisson errors in each azimuthal scattering angle bin
+        asad : histpy.Histogram
+            Counts in each azimuthal scattering angle bin
         """
 
         if not bins == None:
@@ -341,7 +267,7 @@ def create_unpolarized_asad(self, bins=None):
                     counts += expectation.project(['PsiChi'])[j]
             unpolarized_asad.append(counts)
 
-        asad = {'counts': np.array(unpolarized_asad), 'uncertainties': calculate_uncertainties(unpolarized_asad)}
+        asad = Histogram(bin_edges, contents=unpolarized_asad)
 
         return asad
     
@@ -356,8 +282,8 @@ def create_polarized_asads(self, bins=None):
 
         Returns
         -------
-        asads : dict
-            Counts and Gaussian/Poisson errors in each azimuthal scattering angle bin for each polarization angle bin
+        polarized_asads : dict of histpy.Histogram
+            Counts in each azimuthal scattering angle bin for each polarization angle bin
         """
 
         if not bins == None:
@@ -369,7 +295,6 @@ def create_polarized_asads(self, bins=None):
             bin_edges = self._bin_edges
         
         polarized_asads = {}
-        polarized_asad_uncertainties = {}
         for k in range(self._response.axes['Pol'].nbins):
             polarized_asads[k] = []
             expectation, azimuthal_angle_bins = self.calculate_expectation(self._spectrum, 1, PolarizationAngle(Angle(self._response.axes['Pol'].centers.to_value(u.deg)[k] * u.deg), self._source_vector, convention=self._convention))
@@ -379,12 +304,9 @@ def create_polarized_asads(self, bins=None):
                     if azimuthal_angle_bins[j] >= bin_edges[i] and azimuthal_angle_bins[j] < bin_edges[i+1]:
                         counts += expectation.project(['PsiChi'])[j]
                 polarized_asads[k].append(counts)
-            polarized_asads[k] = np.array(polarized_asads[k])
-            polarized_asad_uncertainties[k] = calculate_uncertainties(polarized_asads[k])
-
-        asads = {'counts': polarized_asads, 'uncertainties': polarized_asad_uncertainties}
+            polarized_asads[k] = Histogram(bin_edges, contents=polarized_asads[k])
 
-        return asads
+        return polarized_asads
 
     def create_asads(self):
         """
@@ -394,6 +316,10 @@ def create_asads(self):
         -------
         asads : dict
             Azimuthal scattering angle distributions (ASADs)
+        source_duration : float
+            Duration of source
+        background_duration : float
+            Duration of background
         """
 
         azimuthal_angles = {}
@@ -407,15 +333,15 @@ def create_asads(self):
         source_duration = np.max(self._data['TimeTags']) - np.min(self._data['TimeTags'])
         background_duration = np.max(self._background['TimeTags']) - np.min(self._background['TimeTags'])
 
-        scaled_background_asad = (asads['background']['counts'] * source_duration / background_duration).astype(int)
-        source_asad = asads['source & background']['counts'] - scaled_background_asad
+        scaled_background_asad = (asads['background'].contents.data * source_duration / background_duration).astype(int)
+        source_asad = asads['source & background'].contents.data - scaled_background_asad
 
-        asads['source'] = {'counts': source_asad, 'uncertainties': calculate_uncertainties(source_asad)}
+        asads['source'] = Histogram(asads['background'].axis.edges, contents=source_asad)
         asads['unpolarized'] = self.create_unpolarized_asad()
         asads['polarized'] = self.create_polarized_asads()
-        asads['background (scaled)'] = {'counts': scaled_background_asad, 'uncertainties': calculate_uncertainties(scaled_background_asad)}
+        asads['background (scaled)'] = Histogram(asads['background'].axis.edges, contents=scaled_background_asad)
 
-        return asads
+        return asads, source_duration, background_duration
 
     def asad_sinusoid(self, x, a, b, c):
         """
@@ -472,7 +398,7 @@ def fit_asad(self, counts, p0, bounds, sigma):
 
         return popt, uncertainties
     
-    def plot_asad(self, counts, error, title, coefficients=[]):
+    def plot_asad(self, counts, title, error=None, coefficients=[]):
         """
         Plot the ASAD.
         
@@ -480,16 +406,17 @@ def plot_asad(self, counts, error, title, coefficients=[]):
         ----------
         counts : list
             Counts in each azimuthal scattering angle bin
-        error : np.ndarray
-            Lower & upper uncertainties for each bin
         title : str
             Title of plot
+        error : float, list, or np.array
+            Uncertainties for each bin
         coefficients : list, optional
             Coefficients to plot fitted sinusoidal function
         """
 
         plt.scatter(Angle(self._bins).degree, counts)
-        plt.errorbar(Angle(self._bins).degree, counts, yerr=error, linewidth=0, elinewidth=1)
+        if not error is None:
+            plt.errorbar(Angle(self._bins).degree, counts, yerr=error, linewidth=0, elinewidth=1)
         plt.title(title)
         plt.xlabel('Azimuthal Scattering Angle (degrees)')
         
@@ -502,7 +429,7 @@ def plot_asad(self, counts, error, title, coefficients=[]):
 
         plt.show()
 
-    def correct_asad(self, data_asad, unpolarized_asad):
+    def correct_asad(self, data_asad, unpolarized_asad, data_asad_uncertainties=None):
         """
         Correct the ASAD using the ASAD of an unpolarized source.
         
@@ -515,25 +442,23 @@ def correct_asad(self, data_asad, unpolarized_asad):
             
         Returns
         -------
-        asad : dict
-            Normalized counts and uncertainties in each azimuthal scattering angle bin
+        asad : histpy.Histogram
+            Normalized counts in each azimuthal scattering angle bin
         """
     
         corrected = []
+        uncertainties = []
         for i in range(len(self._bins)):
-            corrected.append(data_asad['counts'][i] / np.sum(data_asad['counts']) / unpolarized_asad['counts'][i] * np.sum(unpolarized_asad['counts']))
-  
-        errors_low = []
-        errors_high = []
-        for i in range(len(self._bins)):
-            sigma_corrected_low = corrected[i] * np.sqrt(((data_asad['uncertainties'][0][i])/data_asad['counts'][i])**2 + ((unpolarized_asad['uncertainties'][0][i])/unpolarized_asad['counts'][i])**2)
-            sigma_corrected_high = corrected[i] * np.sqrt(((data_asad['uncertainties'][1][i])/data_asad['counts'][i])**2 + ((unpolarized_asad['uncertainties'][1][i])/unpolarized_asad['counts'][i])**2)
-            errors_low.append(sigma_corrected_low)
-            errors_high.append(sigma_corrected_high)
-
-        asad = {'counts': corrected, 'uncertainties': np.array([errors_low, errors_high])}
+            corrected.append(data_asad.contents.data[i] / np.sum(data_asad.contents.data) / unpolarized_asad.contents.data[i] * np.sum(unpolarized_asad.contents.data))
+            if not data_asad_uncertainties is None:
+                uncertainties.append(data_asad_uncertainties[i] / np.sum(data_asad.contents.data) / unpolarized_asad.contents.data[i] * np.sum(unpolarized_asad.contents.data))
+        
+        asad = Histogram(data_asad.axis.edges, contents=corrected)
 
-        return asad
+        if not data_asad_uncertainties is None:
+            return asad, uncertainties
+        else:
+            return asad
 
     def calculate_mu(self, counts_corrected, p0=None, bounds=(-np.inf, np.inf), sigma=None):
         """
@@ -556,16 +481,6 @@ def calculate_mu(self, counts_corrected, p0=None, bounds=(-np.inf, np.inf), sigm
             Modulation and uncertainty of fitted sinusoid
         """
 
-        if isinstance(sigma, np.ndarray) and len(sigma.shape) == 2:
-            for i in range(len(sigma[0])):
-                if sigma[0][i] != sigma[1][i]:
-                    print('Warning: Uncertainty in at least one bin of ASAD is not Gaussian. Making error bars symmetric. Fit may not be accurate.')
-                    break
-            symmetric_sigma = []
-            for i in range(len(sigma[0])):
-                symmetric_sigma.append((sigma[0][i] + sigma[1][i]) / 2)
-            sigma = symmetric_sigma
-
         parameter_values, uncertainties = self.fit_asad(counts_corrected, p0, bounds, sigma)
     
         mu = parameter_values[1] / parameter_values[0]
@@ -573,7 +488,7 @@ def calculate_mu(self, counts_corrected, p0=None, bounds=(-np.inf, np.inf), sigm
 
         modulation = {'mu': mu, 'uncertainty': mu_uncertainty}
 
-        print('Modulation:', round(mu, 3), '+/-', round(mu_uncertainty, 3))
+        logger.info('Modulation:', round(mu, 3), '+/-', round(mu_uncertainty, 3))
     
         return modulation, parameter_values
     
@@ -618,22 +533,19 @@ def calculate_mu100(self, polarized_asads, unpolarized_asad, show_plots=False):
         mu_100_list = []
         mu_100_uncertainties = []
         for i in range(self._response.axes['Pol'].nbins):
-            print('Polarization angle bin: ' + str(self._response.axes['Pol'].edges.to_value(u.deg)[i]) + ' to ' + str(self._response.axes['Pol'].edges.to_value(u.deg)[i+1]) + ' deg')
-            asad_polarized = {'counts': polarized_asads['counts'][i], 'uncertainties': polarized_asads['uncertainties'][i]}
-            asad_polarized_corrected = self.correct_asad(asad_polarized, unpolarized_asad)
-            mu_100, coefficients = self.calculate_mu(asad_polarized_corrected['counts'], bounds=([0, 0, 0], [np.inf,np.inf,np.pi]), sigma=asad_polarized_corrected['uncertainties'])
+            logger.info('Polarization angle bin: ' + str(self._response.axes['Pol'].edges.to_value(u.deg)[i]) + ' to ' + str(self._response.axes['Pol'].edges.to_value(u.deg)[i+1]) + ' deg')
+            #asad_polarized = {'counts': polarized_asads['counts'][i], 'uncertainties': polarized_asads['uncertainties'][i]}
+            asad_polarized_corrected = self.correct_asad(polarized_asads[i], unpolarized_asad)
+            mu_100, coefficients = self.calculate_mu(asad_polarized_corrected.contents.data, bounds=([0, 0, 0], [np.inf,np.inf,np.pi]))
             fitted_angle = Angle(coefficients[2], unit=u.rad)
             fitted_angle.wrap_at(180 * u.deg, inplace=True)
             if fitted_angle.degree < 0:
                 fitted_angle += Angle(180, unit=u.deg)
-            diff = fitted_angle.deg - self._response.axes['Pol'].centers.to_value(u.deg)[i]
-            if diff < 0:
-                diff = 180 - diff
-            print('Fitted angle: ' + str(fitted_angle.degree) + ' deg, difference:', diff)
+            logger.info('Fitted angle: ' + str(fitted_angle.degree) + ' deg')
             mu_100_list.append(mu_100['mu'])
             mu_100_uncertainties.append(mu_100['uncertainty'])
             if show_plots == True:
-                self.plot_asad(asad_polarized_corrected['counts'], asad_polarized_corrected['uncertainties'], 'Corrected 100% Polarized ASAD (' + str(int(self._response.axes['Pol'].centers[i].to_value(u.deg))) + ' deg)', coefficients=coefficients)
+                self.plot_asad(asad_polarized_corrected.contents.data, 'Corrected 100% Polarized ASAD (' + str(int(self._response.axes['Pol'].centers[i].to_value(u.deg))) + ' deg)', coefficients=coefficients)
 
         popt, pcov = curve_fit(self.constant, self._response.axes['Pol'].centers.to_value(u.deg), mu_100_list, sigma=mu_100_uncertainties)
         mu_100 = {'mu': popt[0], 'uncertainty': pcov[0][0]}
@@ -646,7 +558,7 @@ def calculate_mu100(self, polarized_asads, unpolarized_asad, show_plots=False):
             plt.ylabel('mu_100')
             plt.show()
 
-        print('mu_100:', round(mu_100['mu'], 2))
+        logger.info('mu_100:', round(mu_100['mu'], 2))
 
         return mu_100
 
@@ -669,7 +581,7 @@ def fit(self, p0=None, bounds=([0, 0, 0], [np.inf,np.inf,np.pi]), show_plots=Fal
             Polarization fraction, polarization angle in the IAU convention, and best fit parameter values for fitted sinusoid, and associated uncertainties
         """
 
-        parameter_values, uncertainties = self.fit_asad(self._counts_corrected, p0, bounds, self._sigma)
+        parameter_values, uncertainties = self.fit_asad(self._asads['source (corrected)'].contents.data, p0, bounds, self._sigma)
     
         polarization_fraction = parameter_values[1] / (parameter_values[0] * self._mu_100['mu'])
         polarization_fraction_uncertainty = polarization_fraction * np.sqrt((uncertainties[0]/parameter_values[0])**2 + (uncertainties[1]/parameter_values[1])**2 + (self._mu_100['uncertainty']/self._mu_100['mu'])**2)
@@ -683,13 +595,13 @@ def fit(self, p0=None, bounds=([0, 0, 0], [np.inf,np.inf,np.pi]), show_plots=Fal
 
         polarization = {'fraction': polarization_fraction, 'angle': polarization_angle, 'fraction uncertainty': polarization_fraction_uncertainty, 'angle uncertainty': polarization_angle_uncertainty, 'best fit parameter values': parameter_values, 'best fit parameter uncertainties': uncertainties}
     
-        print('Best fit polarization fraction:', round(polarization_fraction, 3), '+/-', round(polarization_fraction_uncertainty, 3))
-        print('Best fit polarization angle (IAU convention):', round(polarization_angle.angle.degree, 3), '+/-', round(polarization_angle_uncertainty.degree, 3))
+        logger.info('Best fit polarization fraction:', round(polarization_fraction, 3), '+/-', round(polarization_fraction_uncertainty, 3))
+        logger.info('Best fit polarization angle (IAU convention):', round(polarization_angle.angle.degree, 3), '+/-', round(polarization_angle_uncertainty.degree, 3))
 
         if self._mdp > polarization['fraction']:
-            print('Polarization fraction is below MDP!', 'MDP:', round(self._mdp, 3))
+            logger.info('Polarization fraction is below MDP!', 'MDP:', round(self._mdp, 3))
 
         if show_plots == True:
-            self.plot_asad(self._counts_corrected, self._asads['source (corrected)']['uncertainties'], 'Corrected Source ASAD', coefficients=polarization['best fit parameter values'])
+            self.plot_asad(self._asads['source (corrected)'].contents.data, 'Corrected Source ASAD', self._sigma, coefficients=polarization['best fit parameter values'])
         
         return polarization

From 39f52ec7c0571e906976be5e98d298acbcdbe207 Mon Sep 17 00:00:00 2001
From: Eliza Neights <eneights@gmail.com>
Date: Wed, 12 Mar 2025 10:55:20 -0400
Subject: [PATCH 11/31] Use nbins instead of edges

---
 cosipy/response/PointSourceResponse.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/cosipy/response/PointSourceResponse.py b/cosipy/response/PointSourceResponse.py
index 44fb0f9e..61ae0d6c 100644
--- a/cosipy/response/PointSourceResponse.py
+++ b/cosipy/response/PointSourceResponse.py
@@ -110,7 +110,7 @@ def get_expectation(self, spectrum, polarization_level=None, polarization_angle=
 
                 polarization_angle_components = []
 
-                for i in range(len(self.axes['Pol'].edges) - 1):
+                for i in range(self.axes['Pol'].nbins):
 
                     polarization_angle_components.append(self.slice[{'Pol':slice(i,i+1)}].project('Ei', 'Em', 'Phi', 'PsiChi'))
 

From 3e656b326275725deaad057b33291f279c68ebcc Mon Sep 17 00:00:00 2001
From: Eliza Neights <eneights@gmail.com>
Date: Wed, 12 Mar 2025 14:05:29 -0400
Subject: [PATCH 12/31] Add method to create ASAD from binned data

---
 cosipy/polarization/polarization_asad.py | 164 +++++++++++++++--------
 1 file changed, 111 insertions(+), 53 deletions(-)

diff --git a/cosipy/polarization/polarization_asad.py b/cosipy/polarization/polarization_asad.py
index 9baa5387..22663706 100644
--- a/cosipy/polarization/polarization_asad.py
+++ b/cosipy/polarization/polarization_asad.py
@@ -26,10 +26,10 @@ class PolarizationASAD():
         Spectrum of source
     asad_bin_edges : astropy.coordinates.angles.core.Angle
         Bin edges for azimuthal scattering angle distribution
-    data : dict
-        Unbinned data
-    background : dict
-        Unbinned background model
+    data : dict or cosipy.data_io.BinnedData
+        Binned or unbinned data
+    background : dict or cosipy.data_io.BinnedData
+        Binned or unbinned background model
     sc_orientation : cosipy.spacecraftfile.SpacecraftFile.SpacecraftFile
         Spacecraft orientation
     response_file : str or pathlib.Path
@@ -153,7 +153,7 @@ def calculate_azimuthal_scattering_angles(self, unbinned_data):
 
         return azimuthal_angles
 
-    def calculate_expectation(self, spectrum, polarization_level, polarization_angle):
+    def create_asad_from_response(self, spectrum, polarization_level, polarization_angle, bins=20):
         """
         Convolve source spectrum with response and calculate azimuthal scattering angle bins.
 
@@ -165,13 +165,13 @@ def calculate_expectation(self, spectrum, polarization_level, polarization_angle
             Polarization level (between 0 and 1).
         polarization_angle : :py:class:`cosipy.polarization.polarization_angle.PolarizationAngle`
             Polarization angle. If in the spacecraft frame, the angle must have the same convention as the response.
+        bins : int or astropy.units.quantity.Quantity, optional
+            Number of azimuthal scattering angle bins if int or array of edges of azimuthal scattering angle bins if Quantity
 
         Returns
         -------
-        expectation : cosipy.response.PointSourceResponse.PointSourceResponse
-            Expected counts in each bin of Compton data space
-        azimuthal_angle_bins : list
-            Centers of azimuthal scattering angle bins calculated from PsiChi bins in response
+        asad : histpy.Histogram
+            Counts in each azimuthal scattering angle bin
         """
 
         if isinstance(self._convention.frame, SpacecraftFrame):
@@ -197,22 +197,38 @@ def calculate_expectation(self, spectrum, polarization_level, polarization_angle
             azimuthal_angle_bins = []
 
             for i in range(expectation.axes['PsiChi'].nbins):
-                psichi = expectation.axes['PsiChi'].pix2skycoord(i)
+                psichi = expectation.axes['PsiChi'].pix2skycoord(i).transform_to('icrs')
                 azimuthal_angle = PolarizationAngle.from_scattering_direction(psichi, self._source_vector, self._convention)
                 azimuthal_angle_bins.append(azimuthal_angle.angle)
 
-        return expectation, azimuthal_angle_bins
+        if isinstance(bins, int):
+            bin_edges = Angle(np.linspace(-np.pi, np.pi, bins), unit=u.rad)
+        else:
+            bin_edges = bins
+
+        asad = []
 
-    def create_asad(self, azimuthal_angles, bins=20):
+        for i in range(len(bin_edges)-1):
+            counts = 0
+            for j in range(expectation.project(['PsiChi']).nbins):
+                if azimuthal_angle_bins[j] >= bin_edges[i] and azimuthal_angle_bins[j] < bin_edges[i+1]:
+                    counts += expectation.project(['PsiChi'])[j]
+            asad.append(counts)
+
+        asad = Histogram(bin_edges, contents=asad)
+
+        return asad
+
+    def bin_asad(self, azimuthal_angles, bins=20):
         """
-        Create ASAD and calculate uncertainties.
+        Bin list of azimuthal scattering angles into ASAD.
         
         Parameters
         ----------
         azimuthal_angles : list
-            Azimuthal scattering angles (radians)
-        bins : int or np.array, optional
-            Number of azimuthal scattering angle bins if int or edges of azimuthal scattering angle bins if np.array (radians)
+            Azimuthal scattering angles 
+        bins : int or astropy.units.quantity.Quantity, optional
+            Number of azimuthal scattering angle bins if int or array of edges of azimuthal scattering angle bins if Quantity
 
         Returns
         -------
@@ -233,14 +249,67 @@ def create_asad(self, azimuthal_angles, bins=20):
 
         return asad
 
+    def create_asad_from_binned_data(self, data, bins=20):
+        """
+        Create ASAD from binned data.
+        
+        Parameters
+        ----------
+        data : cosipy.data_io.BinnedData
+            Data binned in Compton data space
+        bins : int or astropy.units.quantity.Quantity, optional
+            Number of azimuthal scattering angle bins if int or array of edges of azimuthal scattering angle bins if Quantity
+
+        Returns
+        -------
+        asad : histpy.Histogram
+            Counts in each azimuthal scattering angle bin
+        """
+
+        if data.binned_data.axes['PsiChi'].coordsys.name == 'spacecraftframe':
+
+            azimuthal_angle_bins = []
+            for i in range(data.binned_data.axes['PsiChi'].nbins):
+                psichi = SkyCoord(lat=(np.pi/2) - data.binned_data.axes['PsiChi'].pix2ang(i)[0], lon=data.binned_data.axes['PsiChi'].pix2ang(i)[1], unit=u.rad, frame=self._convention.frame)
+                azimuthal_angle = PolarizationAngle.from_scattering_direction(psichi, self._source_vector, self._convention)
+                azimuthal_angle_bins.append(azimuthal_angle.angle)
+
+        else:
+
+            azimuthal_angle_bins = []
+            for i in range(data.binned_data.axes['PsiChi'].nbins):
+                psichi = data.binned_data.axes['PsiChi'].pix2skycoord(i).transform_to('icrs')
+                azimuthal_angle = PolarizationAngle.from_scattering_direction(psichi, self._source_vector, self._convention)
+                azimuthal_angle_bins.append(azimuthal_angle.angle)
+
+        if isinstance(bins, int):
+            bin_edges = Angle(np.linspace(-np.pi, np.pi, bins), unit=u.rad)
+        else:
+            bin_edges = bins
+
+        asad = []
+
+        for i in range(len(bin_edges)-1):
+            counts = 0
+            for j in range(data.binned_data.project(['PsiChi']).nbins):
+                if azimuthal_angle_bins[j] >= bin_edges[i] and azimuthal_angle_bins[j] < bin_edges[i+1]:
+                    counts += data.binned_data.project(['PsiChi'])[j]
+            asad.append(counts)
+
+        asad = Histogram(bin_edges, contents=asad)
+        self._bin_edges = asad.axis.edges
+        self._bins = asad.axis.centers
+
+        return asad
+
     def create_unpolarized_asad(self, bins=None):
         """
-        Calculate the azimuthal scattering angles for all bins.
+        Create unpolarized ASAD from response.
         
         Parameters
         ----------
-        bins : int or np.array, optional
-            Number of azimuthal scattering angle bins if int or edges of azimuthal scattering angle bins if np.array (radians)
+        bins : int or astropy.units.quantity.Quantity, optional
+            Number of azimuthal scattering angle bins if int or array of edges of azimuthal scattering angle bins if Quantity
 
         Returns
         -------
@@ -256,29 +325,18 @@ def create_unpolarized_asad(self, bins=None):
         else:
             bin_edges = self._bin_edges
 
-        expectation, azimuthal_angle_bins = self.calculate_expectation(self._spectrum, 0, PolarizationAngle(Angle(0 * u.deg), self._source_vector, convention=self._convention))
-        
-        unpolarized_asad = []
-
-        for i in range(len(bin_edges)-1):
-            counts = 0
-            for j in range(expectation.project(['PsiChi']).nbins):
-                if azimuthal_angle_bins[j] >= bin_edges[i] and azimuthal_angle_bins[j] < bin_edges[i+1]:
-                    counts += expectation.project(['PsiChi'])[j]
-            unpolarized_asad.append(counts)
-
-        asad = Histogram(bin_edges, contents=unpolarized_asad)
+        unpolarized_asad = self.create_asad_from_response(self._spectrum, 0, PolarizationAngle(Angle(0 * u.deg), self._source_vector, convention=self._convention), bins)
 
-        return asad
+        return unpolarized_asad
     
     def create_polarized_asads(self, bins=None):
         """
-        Calculate the azimuthal scattering angles for all bins.
+        Create 100% polarized ASADs for each polarization angle bin of response.
         
         Parameters
         ----------
-        bins : int or np.array, optional
-            Number of azimuthal scattering angle bins if int or edges of azimuthal scattering angle bins if np.array (radians)
+        bins : int or astropy.units.quantity.Quantity, optional
+            Number of azimuthal scattering angle bins if int or array of edges of azimuthal scattering angle bins if Quantity
 
         Returns
         -------
@@ -296,15 +354,7 @@ def create_polarized_asads(self, bins=None):
         
         polarized_asads = {}
         for k in range(self._response.axes['Pol'].nbins):
-            polarized_asads[k] = []
-            expectation, azimuthal_angle_bins = self.calculate_expectation(self._spectrum, 1, PolarizationAngle(Angle(self._response.axes['Pol'].centers.to_value(u.deg)[k] * u.deg), self._source_vector, convention=self._convention))
-            for i in range(len(bin_edges)-1):
-                counts = 0
-                for j in range(self._response.axes['PsiChi'].nbins):
-                    if azimuthal_angle_bins[j] >= bin_edges[i] and azimuthal_angle_bins[j] < bin_edges[i+1]:
-                        counts += expectation.project(['PsiChi'])[j]
-                polarized_asads[k].append(counts)
-            polarized_asads[k] = Histogram(bin_edges, contents=polarized_asads[k])
+            polarized_asads[k] = self.create_asad_from_response(self._spectrum, 1, PolarizationAngle(Angle(self._response.axes['Pol'].centers.to_value(u.deg)[k] * u.deg), self._source_vector, convention=self._convention), bins)
 
         return polarized_asads
 
@@ -323,22 +373,30 @@ def create_asads(self):
         """
 
         azimuthal_angles = {}
-        azimuthal_angles['source & background'] = self.calculate_azimuthal_scattering_angles(self._data)
-        azimuthal_angles['background'] = self.calculate_azimuthal_scattering_angles(self._background)
-
         asads = {}
-        for key in azimuthal_angles.keys():
-            asads[key] = self.create_asad(azimuthal_angles[key], self._asad_bin_edges)
 
-        source_duration = np.max(self._data['TimeTags']) - np.min(self._data['TimeTags'])
-        background_duration = np.max(self._background['TimeTags']) - np.min(self._background['TimeTags'])
+        if type(self._data) == dict:
+            azimuthal_angles['source & background'] = self.calculate_azimuthal_scattering_angles(self._data)
+            asads['source & background'] = self.bin_asad(azimuthal_angles['source & background'], self._asad_bin_edges)
+            source_duration = np.max(self._data['TimeTags']) - np.min(self._data['TimeTags'])
+        else:
+            asads['source & background'] = self.create_asad_from_binned_data(self._data, self._asad_bin_edges)
+            source_duration = (np.max(self._data.binned_data.axes['Time'].edges) - np.min(self._data.binned_data.axes['Time'].edges)).value
+
+        if type(self._background) == dict:
+            azimuthal_angles['background'] = self.calculate_azimuthal_scattering_angles(self._background)
+            asads['background'] = self.bin_asad(azimuthal_angles['background'], self._asad_bin_edges)
+            background_duration = np.max(self._background['TimeTags']) - np.min(self._background['TimeTags'])
+        else:
+            asads['background'] = self.create_asad_from_binned_data(self._background, self._asad_bin_edges)
+            background_duration = (np.max(self._background.binned_data.axes['Time'].edges) - np.min(self._background.binned_data.axes['Time'].edges)).value
 
         scaled_background_asad = (asads['background'].contents.data * source_duration / background_duration).astype(int)
         source_asad = asads['source & background'].contents.data - scaled_background_asad
 
         asads['source'] = Histogram(asads['background'].axis.edges, contents=source_asad)
-        asads['unpolarized'] = self.create_unpolarized_asad()
-        asads['polarized'] = self.create_polarized_asads()
+        asads['unpolarized'] = self.create_unpolarized_asad(self._bin_edges)
+        asads['polarized'] = self.create_polarized_asads(self._bin_edges)
         asads['background (scaled)'] = Histogram(asads['background'].axis.edges, contents=scaled_background_asad)
 
         return asads, source_duration, background_duration

From 7b4f39f274e54a624a78a0d9f773cfabbc3a2d0e Mon Sep 17 00:00:00 2001
From: Eliza Neights <eneights@gmail.com>
Date: Wed, 12 Mar 2025 21:01:49 -0400
Subject: [PATCH 13/31] Fix doctring

---
 cosipy/polarization/polarization_asad.py | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/cosipy/polarization/polarization_asad.py b/cosipy/polarization/polarization_asad.py
index 22663706..4b955bd7 100644
--- a/cosipy/polarization/polarization_asad.py
+++ b/cosipy/polarization/polarization_asad.py
@@ -537,6 +537,8 @@ def calculate_mu(self, counts_corrected, p0=None, bounds=(-np.inf, np.inf), sigm
         -------
         modulation : dict
             Modulation and uncertainty of fitted sinusoid
+        parameter_values : np.ndarray
+            Fitted parameter values
         """
 
         parameter_values, uncertainties = self.fit_asad(counts_corrected, p0, bounds, sigma)

From 4b8c138fe632fbb18bb23f9a4bc91b30757af55e Mon Sep 17 00:00:00 2001
From: Eliza Neights <eneights@gmail.com>
Date: Thu, 13 Mar 2025 17:10:06 -0400
Subject: [PATCH 14/31] Update tutorial notebook

---
 docs/tutorials/polarization/ASAD_method.ipynb | 738 +++++-------------
 1 file changed, 182 insertions(+), 556 deletions(-)

diff --git a/docs/tutorials/polarization/ASAD_method.ipynb b/docs/tutorials/polarization/ASAD_method.ipynb
index dc1340a1..42fecb49 100644
--- a/docs/tutorials/polarization/ASAD_method.ipynb
+++ b/docs/tutorials/polarization/ASAD_method.ipynb
@@ -5,7 +5,7 @@
    "id": "4e111ad9-5599-451c-83a5-f89a79b0dd42",
    "metadata": {},
    "source": [
-    "# Polarization example (GRB) - azimuthal scattering angle distribution (ASAD) method"
+    "# Polarization example - azimuthal scattering angle distribution (ASAD) method"
    ]
   },
   {
@@ -13,463 +13,221 @@
    "id": "f9b8addd-aaa4-488c-8041-385881689986",
    "metadata": {},
    "source": [
-    "This notebook fits the polarization fraction and angle of a GRB simulated using MEGAlib and combined with background. It's assumed that the start time, duration, localization, and spectrum of the GRB are already known. The GRB was simulated with 70% polarization at an angle of 110 degrees in the RelativeX convention, which corresponds to 83.015 degrees in the IAU convention.\n",
-    "\n",
-    "The data to run this notebook, including GRBs simulated on-axis, 10 degrees off-axis, and 20 degrees off-axis, can be found on the COSI Pipeline Google Drive: https://drive.google.com/drive/folders/1kCkqQv07APSSlexeuIgK2Jj7eqJzNNgQ. However, with the RelativeZ response, it is not possible to fit the on-axis GRB.\n",
-    "\n",
-    "Caveats/limitations:\n",
-    "- Currently, the source must be stationary with respect to the instrument, and the spacecraft must be stationary. The ability to fit the polarization of persistent sources will be added later. \n",
-    "- The background simulation is used as the background model, and its ASAD is subtracted from the source+background ASAD.   "
+    "This notebook fits the polarization fraction and angle of a Data Challenge 3 GRB (GRB 080802386) simulated using MEGAlib and combined with albedo photon background. It's assumed that the start time, duration, localization, and spectrum of the GRB are already known. The GRB was simulated with 80% polarization at an angle of 90 degrees in the IAU convention, and was 20 degrees off-axis. A detailed description of the ASAD method, which is the approach used here to fit the polarization, is available on the [Data Challenge repository](https://github.com/cositools/cosi-data-challenges/tree/main/polarization). "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": 9,
    "id": "26c12d83-7afc-4000-8b8f-d353e0b08d12",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Welcome to JupyROOT 6.28/02\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 PyGMO is not available                                                     \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=582139;file:///Users/eneights/opt/anaconda3/envs/cosipy-pr/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=777222;file:///Users/eneights/opt/anaconda3/envs/cosipy-pr/lib/python3.10/site-packages/threeML/minimizer/minimization.py#1369\u001b\\\u001b[2m1369\u001b[0m\u001b]8;;\u001b\\\n"
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-       "<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",
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-       "\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"
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-       "<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",
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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 Could not import plugin HAWCLike.py. Do you have the relative instrument        \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=126626;file:///Users/eneights/opt/anaconda3/envs/cosipy-pr/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=684220;file:///Users/eneights/opt/anaconda3/envs/cosipy-pr/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"
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-       "<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"
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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 Could not import plugin FermiLATLike.py. Do you have the relative instrument    \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=844329;file:///Users/eneights/opt/anaconda3/envs/cosipy-pr/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=222836;file:///Users/eneights/opt/anaconda3/envs/cosipy-pr/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"
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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\">01:03:49 </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:///Users/eneights/opt/anaconda3/envs/cosipy-pr/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:///Users/eneights/opt/anaconda3/envs/cosipy-pr/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",
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-       "\u001b[38;5;46m01:03:49\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=123326;file:///Users/eneights/opt/anaconda3/envs/cosipy-pr/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=545392;file:///Users/eneights/opt/anaconda3/envs/cosipy-pr/lib/python3.10/site-packages/threeML/utils/data_builders/fermi/lat_transient_builder.py#44\u001b\\\u001b[2m44\u001b[0m\u001b]8;;\u001b\\\n"
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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\"> Env. variable OMP_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:///Users/eneights/opt/anaconda3/envs/cosipy-pr/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:///Users/eneights/opt/anaconda3/envs/cosipy-pr/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"
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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 Env. variable OMP_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=451603;file:///Users/eneights/opt/anaconda3/envs/cosipy-pr/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=636257;file:///Users/eneights/opt/anaconda3/envs/cosipy-pr/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"
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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\"> 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:///Users/eneights/opt/anaconda3/envs/cosipy-pr/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:///Users/eneights/opt/anaconda3/envs/cosipy-pr/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"
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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 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=582927;file:///Users/eneights/opt/anaconda3/envs/cosipy-pr/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=991721;file:///Users/eneights/opt/anaconda3/envs/cosipy-pr/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"
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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\"> 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:///Users/eneights/opt/anaconda3/envs/cosipy-pr/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:///Users/eneights/opt/anaconda3/envs/cosipy-pr/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=828668;file:///Users/eneights/opt/anaconda3/envs/cosipy-pr/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=475847;file:///Users/eneights/opt/anaconda3/envs/cosipy-pr/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"
-    }
-   ],
+   "outputs": [],
    "source": [
     "from cosipy import UnBinnedData\n",
     "from cosipy.spacecraftfile import SpacecraftFile\n",
     "from cosipy.polarization.conventions import MEGAlibRelativeX, MEGAlibRelativeY, MEGAlibRelativeZ, IAUPolarizationConvention\n",
-    "from cosipy.polarization.polarization_asad import PolarizationASAD, calculate_uncertainties\n",
+    "from cosipy.polarization.polarization_asad import PolarizationASAD\n",
     "from cosipy.threeml.custom_functions import Band_Eflux\n",
     "from astropy.time import Time\n",
     "import numpy as np\n",
     "from astropy.coordinates import Angle, SkyCoord\n",
     "from astropy import units as u\n",
     "from scoords import SpacecraftFrame\n",
-    "from scipy.optimize import curve_fit"
+    "from cosipy.util import fetch_wasabi_file"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "ce33b697",
+   "id": "5a52ee92",
    "metadata": {},
    "source": [
-    "Read in the data (GRB+background), background simulation, and define the path to the detector response"
+    "### Download and read in data"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": 2,
-   "id": "ac0ad83d",
+   "cell_type": "markdown",
+   "id": "779bf315",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "analysis = UnBinnedData('/path/to/yaml/file') # e.g. grb.yaml\n",
-    "\n",
-    "analysis.select_data(unbinned_data='/path/to/data/file', output_name='/path/to/selected/data/file') # e.g. GRB_20_0.hdf5 & GRB_20_0_selected.hdf5\n",
-    "data = analysis.get_dict_from_hdf5('/path/to/selected/data/file') # e.g. GRB_20_0_selected.hdf5\n",
-    "background = analysis.get_dict_from_hdf5('/path/to/background/file') # e.g. background.hdf5\n",
-    "\n",
-    "response_file = '/path/to/response/file' # e.g. HEALPixO3_200to500keV_1ebins_12pbins_log_flat.binnedpolarization.11D_nside8.area.h5"
+    "This will download the files needed to run this notebook. If you have already downloaded these files, you can skip this."
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "2cc0300a",
+   "id": "597ad8ce",
    "metadata": {},
    "source": [
-    "Read in the orientation file. Here, the spacecraft is stationary, so we are only using the first attitude bin"
+    "Download the unbinned data (660.58 KB)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
-   "id": "ecb484f2",
+   "execution_count": null,
+   "id": "22688e16",
    "metadata": {},
    "outputs": [],
    "source": [
-    "sc_orientation = SpacecraftFile.parse_from_file('/path/to/ori/file') # e.g. ori.ori\n",
-    "sc_orientation = sc_orientation.source_interval(Time(analysis.tmin,format = 'unix'), Time(analysis.tmax,format = 'unix'))\n",
-    "\n",
-    "attitude = sc_orientation.get_attitude()[0]"
+    "fetch_wasabi_file('COSI-SMEX/cosipy_tutorials/polarization_fit/grb_background.fits.gz')"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "c6951d6c",
+   "id": "cf3fd48c",
    "metadata": {},
    "source": [
-    "Define the GRB spectrum. This is convolved with the response to calculate the ASADs of an unpolarized and 100% polarized source"
+    "Download the polarization response (1.35 GB). This needs to be unzipped before running the rest of the notebook"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
-   "id": "26cec39d",
+   "execution_count": null,
+   "id": "f37410bc",
    "metadata": {},
    "outputs": [],
    "source": [
-    "a = 10. * u.keV\n",
-    "b = 5000. * u.keV\n",
-    "alpha = 0.880\n",
-    "beta = -2.384\n",
-    "ebreak = 195.613 * u.keV\n",
-    "K = 10. / u.cm / u.cm / u.s\n",
-    "\n",
-    "spectrum = Band_Eflux(a = a.value,\n",
-    "                      b = b.value,\n",
-    "                      alpha = alpha,\n",
-    "                      beta = beta,\n",
-    "                      E0 = ebreak.value,\n",
-    "                      K = K.value)\n",
-    "\n",
-    "spectrum.a.unit = a.unit\n",
-    "spectrum.b.unit = b.unit\n",
-    "spectrum.E0.unit = ebreak.unit\n",
-    "spectrum.K.unit = K.unit"
+    "fetch_wasabi_file('COSI-SMEX/DC3/Responses/ResponseContinuum.o3.pol.e200_10000.b4.p12.s10396905069491.m441.filtered.nonsparse.binnedpolarization.11D_nside8.area.h5.gz')"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "39c52ea7",
+   "id": "75efff44",
    "metadata": {},
    "source": [
-    "Define the source position and polarization object"
+    "Download the orientation file (1.10 GB)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
-   "id": "41cbf55e",
+   "execution_count": null,
+   "id": "6a8cf7f0",
    "metadata": {},
    "outputs": [],
    "source": [
-    "source_direction = SkyCoord(0, 70, representation_type='spherical', frame=SpacecraftFrame(attitude=attitude), unit=u.deg)\n",
-    "\n",
-    "grb_polarization = PolarizationASAD(source_direction, spectrum, response_file, sc_orientation)"
+    "fetch_wasabi_file('COSI-SMEX/DC3/Data/Orientation/DC3_final_530km_3_month_with_slew_1sbins_GalacticEarth_SAA.ori')"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "eb4a7306",
+   "id": "ce33b697",
    "metadata": {},
    "source": [
-    "Calculate the azimuthal scattering angle for each photon in the data and background simulation"
+    "Read in the unbinned data, which is a GRB placed within albedo photon background. A time cut is done for the duration of the GRB to produce the GRB+background data to fit. The time intervals before and after the GRB are used to produce a background model. An energy cut is applied to both the data and background model to match the energy range of the detector response. Binned data can also be used for the ASAD method for both the data and background model."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
-   "id": "26df3de8",
+   "execution_count": null,
+   "id": "ac0ad83d",
    "metadata": {},
    "outputs": [],
    "source": [
-    "azimuthal_angles = {}\n",
-    "    \n",
-    "azimuthal_angles['grb & background'] = grb_polarization.calculate_azimuthal_scattering_angles(data)\n",
-    "azimuthal_angles['background'] = grb_polarization.calculate_azimuthal_scattering_angles(background)"
+    "grb_background = UnBinnedData('/path/to/yaml/file') # e.g. grb.yaml\n",
+    "grb_background.select_data_time(unbinned_data='/path/to/data/file', output_name='/path/to/time/selected/data/file') # e.g. grb_background.fits.gz & grb_background_source_interval.fits.gz\n",
+    "grb_background.select_data_energy(200., 10000., output_name='/path/to/time/energy/selected/data/file', unbinned_data='/path/to/time/selected/data/file') # e.g. grb_background_source_interval_energy_cut.fits.gz & grb_background_source_interval.fits.gz\n",
+    "data = grb_background.get_dict_from_fits('/path/to/time/energy/selected/data/file') # e.g. grb_background_source_interval_energy_cut.fits.gz\n",
+    "\n",
+    "background_before = UnBinnedData('/path/to/yaml/file') # e.g. background_before.yaml\n",
+    "background_before.select_data_time(unbinned_data='/path/to/data/file', output_name='/path/to/time/selected/background/file') # e.g. grb_background.fits.gz & background_before.fits.gz\n",
+    "background_before.select_data_energy(200., 10000., output_name='/path/to/time/energy/selected/background/file', unbinned_data='/path/to/time/selected/background/file') # e.g. background_before_energy_cut.fits.gz & background_before.fits.gz\n",
+    "background_1 = background_before.get_dict_from_fits('/path/to/time/energy/selected/background/file') # e.g. background_before_energy_cut.fits.gz\n",
+    "\n",
+    "background_after = UnBinnedData('/path/to/yaml/file') # e.g. background_after.yaml\n",
+    "background_after.select_data_time(unbinned_data='/path/to/data/file', output_name='/path/to/time/selected/background/file') # e.g. grb_background.fits.gz & background_after.fits.gz\n",
+    "background_before.select_data_energy(200., 10000., output_name='/path/to/time/energy/selected/background/file', unbinned_data='/path/to/time/selected/background/file') # e.g. background_after_energy_cut.fits.gz & background_after.fits.gz\n",
+    "background_2 = background_before.get_dict_from_fits('/path/to/time/energy/selected/background/file') # e.g. background_after_energy_cut.fits.gz\n",
+    "\n",
+    "background = [background_1, background_2]"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "b3417867",
+   "id": "b983b194",
    "metadata": {},
    "source": [
-    "Create an azimuthal scattering angle distribution (ASAD) each for the data and background simulation"
+    "Define the path to the detector response and read in the orientation file."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
-   "id": "641b46c1",
+   "execution_count": null,
+   "id": "36712258",
    "metadata": {},
    "outputs": [],
    "source": [
-    "bin_edges = Angle(np.linspace(-np.pi, np.pi, 18), unit=u.rad) # Define ASAD bins\n",
+    "response_file = '/path/to/response/file' # e.g. ResponseContinuum.o3.pol.e200_10000.b4.p12.s10396905069491.m441.filtered.nonsparse.binnedpolarization.11D_nside8.area.h5\n",
     "\n",
-    "asads = {}\n",
-    "for key in azimuthal_angles.keys():\n",
-    "    asads[key] = grb_polarization.create_asad(azimuthal_angles[key], bin_edges)"
+    "sc_orientation = SpacecraftFile.parse_from_file('/path/to/ori/file') # e.g. DC3_final_530km_3_month_with_slew_1sbins_GalacticEarth_SAA.ori\n",
+    "sc_orientation = sc_orientation.source_interval(Time(1835493492.2, format = 'unix'), Time(1835493492.8, format = 'unix'))"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "52e46d5e",
+   "id": "c6951d6c",
    "metadata": {},
    "source": [
-    "Calculate the ASAD of the GRB only by subtracting the background ASAD from the GRB+background ASAD"
+    "Define the GRB position and spectrum."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
-   "id": "6ff34198",
+   "execution_count": 15,
+   "id": "26cec39d",
    "metadata": {},
    "outputs": [],
    "source": [
-    "source_duration = analysis.tmax - analysis.tmin # Duration of GRB simulation\n",
-    "background_duration = np.max(background['TimeTags']) - np.min(background['TimeTags']) # Duration of background simulation\n",
+    "source_direction = SkyCoord(l=23.53, b=-53.44, frame='galactic', unit=u.deg)\n",
     "\n",
-    "background_asad_grb_duration = (asads['background']['counts'] * source_duration / background_duration).astype(int)\n",
-    "grb_asad = asads['grb & background']['counts'] - background_asad_grb_duration\n",
+    "a = 100. * u.keV\n",
+    "b = 10000. * u.keV\n",
+    "alpha = -0.7368949\n",
+    "beta = -2.095031\n",
+    "ebreak = 622.389 * u.keV\n",
+    "K = 300. / u.cm / u.cm / u.s\n",
     "\n",
-    "asads['grb'] = {'counts': grb_asad, 'uncertainties': calculate_uncertainties(grb_asad)}"
+    "spectrum = Band_Eflux(a = a.value,\n",
+    "                      b = b.value,\n",
+    "                      alpha = alpha,\n",
+    "                      beta = beta,\n",
+    "                      E0 = ebreak.value,\n",
+    "                      K = K.value)\n",
+    "\n",
+    "spectrum.a.unit = a.unit\n",
+    "spectrum.b.unit = b.unit\n",
+    "spectrum.E0.unit = ebreak.unit\n",
+    "spectrum.K.unit = K.unit"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "e3cda8c6",
+   "id": "bbb6ffe2",
    "metadata": {},
    "source": [
-    "Calculate the unpolarized and 100% polarized ASADs, and calculate the modulation of a 100% polarized source"
+    "### Polarization fit in ICRS frame"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "39c52ea7",
+   "metadata": {},
+   "source": [
+    "Define the azimuthal scattering angle bin edges, and create the polarization object. A number of steps are done when this object is created:\n",
+    "- Creates ASADs for the GRB+background data and background model, and subtracts the background ASAD from the GRB+background ASAD to produce an ASAD for the GRB only\n",
+    "- Convolves the GRB position and spectrum with the response to produce an unpolarized ASAD and 100% polarized ASADs for each polarization angle bin\n",
+    "- Corrects for instrumental effects by dividing the GRB only and 100% polarized ASADs by the unpolarized ASAD\n",
+    "- Fits a sinusoid to the 100% polarized ASADs to determine the $\\mu_{100}$, or the modulation of a 100% polarized source. This is used later on to convert the amplitude of the sinusoid fit to the GRB ASAD to a polarization fraction\n",
+    "\n",
+    "The ASADs are automatically calculated in the IAU convention."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
-   "id": "4cddef85",
+   "execution_count": 16,
+   "id": "41cbf55e",
    "metadata": {},
    "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Polarization angle bin: 0.0 deg to 15.0 deg\n",
-      "Modulation: 0.309 +/- 0.003\n",
-      "Best fit polarization fraction: 1.0 +/- 0.016\n",
-      "Best fit polarization angle: 160.234 +/- 0.3\n"
-     ]
-    },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -477,19 +235,9 @@
      "metadata": {},
      "output_type": "display_data"
     },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Polarization angle bin: 15.0 deg to 30.0 deg\n",
-      "Modulation: 0.31 +/- 0.004\n",
-      "Best fit polarization fraction: 1.0 +/- 0.018\n",
-      "Best fit polarization angle: 175.396 +/- 0.344\n"
-     ]
-    },
     {
      "data": {
-      "image/png": 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",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -497,19 +245,9 @@
      "metadata": {},
      "output_type": "display_data"
     },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Polarization angle bin: 30.0 deg to 45.0 deg\n",
-      "Modulation: 0.307 +/- 0.004\n",
-      "Best fit polarization fraction: 1.0 +/- 0.018\n",
-      "Best fit polarization angle: 10.124 +/- 0.367\n"
-     ]
-    },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -517,19 +255,9 @@
      "metadata": {},
      "output_type": "display_data"
     },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Polarization angle bin: 45.0 deg to 60.0 deg\n",
-      "Modulation: 0.309 +/- 0.004\n",
-      "Best fit polarization fraction: 1.0 +/- 0.017\n",
-      "Best fit polarization angle: 25.51 +/- 0.349\n"
-     ]
-    },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -537,19 +265,9 @@
      "metadata": {},
      "output_type": "display_data"
     },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Polarization angle bin: 60.0 deg to 75.0 deg\n",
-      "Modulation: 0.307 +/- 0.004\n",
-      "Best fit polarization fraction: 1.0 +/- 0.018\n",
-      "Best fit polarization angle: 40.702 +/- 0.364\n"
-     ]
-    },
     {
      "data": {
-      "image/png": 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",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -557,19 +275,9 @@
      "metadata": {},
      "output_type": "display_data"
     },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Polarization angle bin: 75.0 deg to 90.0 deg\n",
-      "Modulation: 0.312 +/- 0.004\n",
-      "Best fit polarization fraction: 1.0 +/- 0.017\n",
-      "Best fit polarization angle: 55.409 +/- 0.329\n"
-     ]
-    },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -577,19 +285,9 @@
      "metadata": {},
      "output_type": "display_data"
     },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Polarization angle bin: 90.0 deg to 105.0 deg\n",
-      "Modulation: 0.313 +/- 0.003\n",
-      "Best fit polarization fraction: 1.0 +/- 0.014\n",
-      "Best fit polarization angle: 70.287 +/- 0.271\n"
-     ]
-    },
     {
      "data": {
-      "image/png": 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",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -597,19 +295,9 @@
      "metadata": {},
      "output_type": "display_data"
     },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Polarization angle bin: 105.0 deg to 120.0 deg\n",
-      "Modulation: 0.312 +/- 0.003\n",
-      "Best fit polarization fraction: 1.0 +/- 0.016\n",
-      "Best fit polarization angle: 85.277 +/- 0.312\n"
-     ]
-    },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -617,19 +305,9 @@
      "metadata": {},
      "output_type": "display_data"
     },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Polarization angle bin: 120.0 deg to 135.0 deg\n",
-      "Modulation: 0.306 +/- 0.004\n",
-      "Best fit polarization fraction: 1.0 +/- 0.021\n",
-      "Best fit polarization angle: 100.21 +/- 0.429\n"
-     ]
-    },
     {
      "data": {
-      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -637,19 +315,9 @@
      "metadata": {},
      "output_type": "display_data"
     },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Polarization angle bin: 135.0 deg to 150.0 deg\n",
-      "Modulation: 0.309 +/- 0.004\n",
-      "Best fit polarization fraction: 1.0 +/- 0.018\n",
-      "Best fit polarization angle: 115.465 +/- 0.373\n"
-     ]
-    },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -657,19 +325,9 @@
      "metadata": {},
      "output_type": "display_data"
     },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Polarization angle bin: 150.0 deg to 165.0 deg\n",
-      "Modulation: 0.308 +/- 0.004\n",
-      "Best fit polarization fraction: 1.0 +/- 0.017\n",
-      "Best fit polarization angle: 130.659 +/- 0.332\n"
-     ]
-    },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -677,19 +335,9 @@
      "metadata": {},
      "output_type": "display_data"
     },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Polarization angle bin: 165.0 deg to 180.0 deg\n",
-      "Modulation: 0.309 +/- 0.004\n",
-      "Best fit polarization fraction: 1.0 +/- 0.019\n",
-      "Best fit polarization angle: 145.507 +/- 0.353\n"
-     ]
-    },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -699,7 +347,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -707,39 +355,9 @@
      "metadata": {},
      "output_type": "display_data"
     },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "mu_100: 0.31\n"
-     ]
-    }
-   ],
-   "source": [
-    "asads['unpolarized'] = grb_polarization.create_unpolarized_asad()\n",
-    "\n",
-    "asads['polarized'] = grb_polarization.create_polarized_asads()\n",
-    "\n",
-    "mu_100 = grb_polarization.calculate_mu100(asads['polarized'], asads['unpolarized'])"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "7fb2ffdb",
-   "metadata": {},
-   "source": [
-    "Plot the ASADs"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 11,
-   "id": "8fc63ee4",
-   "metadata": {},
-   "outputs": [
     {
      "data": {
-      "image/png": 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JJxsTDhEREbUCOp/TQkRERFQfTFqIiIhIFJi0EBERkSgwaSEiIiJRYNJCREREosCkhYiIiESBSQsRERGJApMWIiIiEgUmLURERCQKTFqIiIhIFJi0EBERkSgwaSEiIiJRYNJCREREosCkhYiIiESBSQsRERGJApMWIiIiEgUmLURERCQKTFqIiIhIFJi0EBERkSgwaSEiIiJRYNJCREREosCkhYiIiESBSQsRERGJApMWIiIiEgUmLURERCQKTFpaGLlcQHZqAQAgO7UAcrmg44iIiIhaBiNdB0D/uhGbiZiNiSjOLQMARIcn4PzO6xg00xOuPs46jo6IiEi32NNSDyV5ZTi7IwUleWVaO8eN2ExEfhuvTFgUinPLEPltPG7EZmrt3ERERGLQ4J6WkpISbN26FVeuXEFiYiKKioqwaNEijB8/Xq1uWloaVq1ahUuXLsHIyAiDBw9GWFgYbG1tVerJ5XJs3boVf/zxB3Jzc9GxY0fMmDEDo0ePbvSFNaWS/HLE/34NLv0dYdHWrMmPL5cLiNmYWGedmE2JcPF2gkRi0OTnJyIiEoMG97QUFBQgIiIC6enp6Nq1a631srKyMHfuXPzzzz8ICQnBc889h9OnT+ONN95AZWWlSt1169ZhzZo1GDBgAObPnw8nJyd88skniIyMbPgViVBmUq5aD8uDimVlyEzKbaaIiIiIWp4G97RIpVLs3LkTUqkUSUlJePnllzXW27x5M8rKyrB+/Xo4OTkBADw9PfHGG29g//79CAwMBABkZ2dj27ZtePrpp7Fw4UIAwBNPPIG5c+di9erVGDFiBAwNDRt7faJQml/epPWIiIj0UYN7WkxMTCCVSh9a79ixYxgyZIgyYQEAb29vdOrUCVFRUcqykydPoqqqCk8//bSyzMDAAJMmTUJ2djYSEhIaGqLomNuaNmk9IiIifaSVibjZ2dnIy8uDh4eH2jZPT0+kpKQof05JSYG5uTlcXFzU6im26zvnbnawtKt7royl1AzO3eyaKSIiIqKWRyu3PMtkMgDQ2CMjlUpRWFiIiooKmJiYQCaToW3btjAwMFCrBwA5OTkaz5GTk6M8DwCkp6c3VfjNTiIxwKCZnoj8Nr7WOoNe8OQkXCIiatW0krSUl9fMvTA2NlbbZmJioqxjYmKC8vLyh9bTZPfu3YiIiGiiiHXP1ccZoxZ4qazTAtT0sAx6geu0EBERaSVpMTWtmXvx4F1CAFBRUaFSx9TUtF71HhQYGAhfX1/lz+np6Vi8ePGjBa5jrj7OcPF2QnJUBqLDE+A7uwc8/Duxh4WIiAhaSloUQzv3D98oyGQy2NjYKHtSpFIp4uPjIQiCyhCRYl97e3uN57C3t691m5hJJAZwcGsDAHBwa8OEhYiI6P/TykRcBwcH2NraIjk5WW1bYmKiyvouXbt2RVlZmdqclCtXrii3ExEREWltGf/hw4fj1KlTuHv3rrLs7NmzyMjIgL+/v7Js6NChMDIyws6dO5VlgiBg165dcHBwQM+ePbUVIhEREYlIo4aHfvvtN9y7d085hBMdHY2srCwAwJQpU2BlZYUZM2bg6NGjWLBgAYKCglBaWootW7bAzc1NZcl/R0dHTJ06FVu2bEFVVRU8PT1x4sQJXLx4Ee+//77eLyxHRERE9dOopGXbtm3IzPz3AX7Hjx/H8ePHAQABAQGwsrKCk5MTVqxYgVWrVuGHH35QPnsoNDRUOZ9F4ZVXXoG1tTV2796NAwcOoGPHjnjvvfcwZsyYR7g0IiIi0ieNSlq2b99er3qurq5YtmzZQ+tJJBLMmDEDM2bMaEw4RERE1ApobU4LERERUVNi0kJERESiwKSFiIiIRIFJCxEREYkCkxYiIiISBSYtREREJApMWoiIiEgUmLQQERGRKDBpISIiIlFg0kJERESiwKSFiIiIRIFJCxEREYkCkxYiIiISBSYtREREJApMWoiIiEgUmLQQERGRKDBpISIiIlFg0kJERESiwKSFiIiIRIFJCxEREYkCkxYiIiISBSYtDyGXC8hOLQAAZKcWQC4XdBwRERFR62Sk6wBashuxmYjZmIji3DIAQHR4As7vvI5BMz3h6uOs4+iIiIhaF/a01OJGbCYiv41XJiwKxblliPw2HjdiM3UUGRERUevEpEUDuVxAzMbEOuvEbErkUBEREVEzYtKiQWZSrloPy4OKZWXITMptpoiIiIiISYsGpfnlTVqPiIiIHh2TFg3MbU2btB4RERE9Oq3ePZScnIx169bh8uXLEAQBPXr0wGuvvQZ3d3e1upcuXcKaNWtw9epVWFpawt/fHyEhIbCwsNBmiBo5d7ODpZ1ZnUNEllIzOHeza8aoiIiIWjet9bQkJycjNDQUt2/fRnBwMIKDg3Hr1i3MmzcPN2/eVKmbkpKChQsXoqysDGFhYZg4cSL27NmDDz/8UFvh1UkiMcCgmZ511hn0gickEoNmioiIiIi01tMSHh4OU1NTfP/992jTpg0AYMyYMXj++eexdu1aLF68WFl37dq1sLa2xooVK2BpaQkAaNeuHZYsWYLY2Fj4+PhoK8xaufo4Y9QCL5V1WoCaHpZBL2h3nRYLW1N4Te4KCw4/ERERKWmtp+XixYvw9vZWJiwAYG9vj759++L06dMoKSkBABQXFyMuLg4BAQHKhAUAxo4dC3Nzc0RFRWkrxIdy9XHGsytGwHd2DwCA7+weeHb5CK0vLGfR1gz9g9xh0dZMq+chIiISE60lLZWVlTAxMVErNzMzQ2VlJW7cuAEASE1NRXV1NTw8PFTqGRsbw93dHSkpKdoKsV4kEgM4uNUkXg5ubTgkREREpCNaGx7q1KkTrly5gurqahgaGgKoSWSuXLkCAMjOzgYAyGQyAIBUKlU7hlQqxYULFzQePycnR7kvAKSnpzdp/ERERNSyaC1pefrpp7Fs2TJ8+eWXmD59OuRyOTZu3KhMNCoqKgAA5eU1a50YGxurHcPExERZ70G7d+9GRESEdoInIiJq4UryypAYmQHPUZ1azXQCrSUtTz31FLKysrBlyxYcOHAAANCtWzdMmzYNmzZtgrm5OQDA1LRmsmllZaXaMSoqKjQOMQFAYGAgfH19lT+np6erTO4lIiLSZyX55Yj//Rpc+jsyaWkKISEheO6553Djxg1YWlqiS5cuWLt2LYCa4SPg32Gh+4d6FGQyGezt7TUe297evtZtREREpH+0viKutbU1evfujS5dugAA4uLi4ODggM6dOwMAXF1dYWhoiOTkZJX9KisrkZKSgq5du2o7RCIiIhKBZl3GPzIyEklJSZg6dSokkppTW1lZwdvbG4cOHVLeBg0ABw8eRGlpKfz9/ZszRCIiImqhtDY8dP78efz0008YMGAAbGxscOXKFezfvx8DBw5EUFCQSt05c+YgNDQUc+fORWBgILKysrBt2zYMGDAAAwcO1FaIREREJCJaS1ocHBwgkUiwZcsWlJaWwtnZGbNnz8azzz4LIyPV03p4eODrr7/GmjVrsHLlSlhYWGDixIl45ZVXtBUeERERiYzWkpYOHTpg2bJl9a7fu3dvrF69WlvhEBERkcg165wWIiIiosZi0kIoySvD2R0pKMkre3hlIiIiHWHSQsoFikryy3UdChERUa2YtBAREZEoMGkhIiIiUWDSQkRERKLApIWIiIhEgUkLERERiQKTFiIiIhIFJi1EREQkCkxaiKjBuCAhEekCkxYiajAuSEhEusCkhYiIiESBSQsRERGJApMWIiIiEgUmLURERCQKTFqIiIhIFJi0EBERkSgwaSEiIiJRYNJCREREosCkhYiIiESBSQsRERGJApMWIiIiEgUmLURERCQKTFrqwcLWFF6Tu8LC1lTXoRAREbVaTFrqwaKtGfoHucOirZmuQyEiIoJcLiA7tQAAkJ1aALlc0HFEzcNI1wEQERFR/d2IzUTMxkQU55YBAKLDE3B+53UMmukJVx9nHUenXexpISIiEokbsZmI/DZembAoFOeWIfLbeNyIzdRRZM2DSQsREZEIyOUCYjYm1lknZlOiXg8VaXV4KCMjA+Hh4bh06RIKCwvh5OSE0aNH47nnnoOZ2b/zQy5duoQ1a9bg6tWrsLS0hL+/P0JCQmBhYaHN8IiIiEQjMylXrYflQcWyMmQm5aJ9d2kzRdW8tJa03L17F6+88gqsrKzw9NNPw8bGBgkJCfjxxx+RnJyML774AgCQkpKChQsXwsXFBWFhYcjKysK2bdtw69YtLF26VFvhERERiUppfnmT1hMjrSUthw4dwr179/Ddd9/B1dUVABAYGAi5XI6DBw+iqKgI1tbWWLt2LaytrbFixQpYWloCANq1a4clS5YgNjYWPj4+2gqRiIhINMzruexGfeuJkdbmtBQXFwMA2rZtq1IulUohkUhgZGSE4uJixMXFISAgQJmwAMDYsWNhbm6OqKgobYVHREQkKs7d7GBpV/fSG5ZSMzh3s2umiJqf1pIWLy8vAMCXX36JlJQU3L17F5GRkdi1axemTJkCc3NzpKamorq6Gh4eHir7Ghsbw93dHSkpKdoKj4ioTiV5ZTi7IwUleXXPISBqLhKJAQbN9KyzzqAXPCGRGDRTRM1Pa8NDAwcOxOzZs7F582ZER0cry1944QWEhIQAAGQyGYCa3pcHSaVSXLhwodbj5+TkKPcHgPT09KYKvVV5cIEiOxcbvX7DE9VXSX454n+/Bpf+jlxYkloMVx9njFrgpbJOC1DTwzLoBf1fp0Wrdw+1a9cOffr0wfDhw2FjY4PTp09j8+bNsLOzw5QpU1BeXjNZyNjYWG1fExMTVFRU1Hrs3bt3IyIiQluhtwqteYEiIiKxcvVxhou3E5KjMhAdngDf2T3g4d+pVXzh1FrSEhkZiaVLl+Lnn3+Go6MjAGD48OEQBAE//PADRo8eDVPTmslClZWVavtXVFTAxMSk1uMHBgbC19dX+XN6ejoWL17cxFehvxQLFD1IsUDRqAVeTFyIiFooicQADm5tAAAObm1aRcICaHFOy86dO+Hu7q5MWBR8fX1RVlaGlJQU5bDQ/cM8CjKZDPb29rUe397eHh4eHsp/Li4uTXsBeowLFBER5+yQGGktacnLy4NcLlcrr6qqAgBUV1fD1dUVhoaGSE5OVqlTWVmJlJQUdO3aVVvhtWoNWaCIiPSTYs5OiR6v6UH6R2tJS6dOnZCSkoKMjAyV8sjISEgkEnTp0gVWVlbw9vbGoUOHUFJSoqxz8OBBlJaWwt/fX1vhtWpcoIiIiMRIa3NannvuOZw5cwZhYWGYPHkybGxscOrUKZw5cwZPPPGEcuhnzpw5CA0Nxdy5cxEYGKhcEXfAgAEYOHCgtsJr1bhAERERiZHWkpa+ffviu+++w4YNG7Bz504UFhaiXbt2CAkJwbRp05T1PDw88PXXX2PNmjVYuXIlLCwsMHHiRLzyyivaCq3VUyxQVNcQkb4vUEREROKj1Vueu3fvXq/nB/Xu3RurV6/WZih0H8UCRZruHlLQ9wWKqPF0sbZPSV4ZEiMz4DmqE9dMIWrFtDanhVo2xQJFDy4JbSk14+3OVKsbsZnYNu8oosMTANSs7bNt3lHciM3U6nk5aZSIAC33tFDL1poXKKKG49o+RKRr7Glp5VrrAkXUMFzbh4haAiYtRPRQXNuHiFoCJi1E9FBc24eIWgImLUT0UFzbh4haAiYtRPRQirV96sK1fYhI25i0ENFDKdb2qQvX9iEibWPSQkT1wrV9iEjXuE4LEdUb1/YhIl1iTwsRNQjX9iEiXWHSQkRERKLApIWIiIhEgUkLERERiQKTFiIiIhIFJi1EREQkCkxaiIiISBSYtBARtQAleWU4uyMFJXl1P02bqDVj0kJE1AKU5Jcj/vdrKOGTsolqxaSFiIiIRIFJCxEREYkCkxYiogfI5QKyUwsAANmpBZDLBR1HREQAH5hIRKTiRmwmYjYmoji3ZkJsdHgCzu+8jkEzPfkkayIdY08LEdH/dyM2E5HfxisTFoXi3DJEfhuPG7GZOoqMiAAmLUREAGqGhGI2JtZZJ2ZTIoeKiHSISQsREYDMpFy1HpYHFcvKkJmU20wRaQ/n7JBYcU4LERGA0nquj1Lfei0V5+zoDwtbU3hN7goLW1Ndh9Js2NNCRATAvJ6/+OtbryXinB39YtHWDP2D3GHR1kzXoTQbrfW0fP755zhw4ECt23/77Tc4ODgAAC5duoQ1a9bg6tWrsLS0hL+/P0JCQmBhYaGt8IiIVDh3s4OlnVmdQ0SWUjM4d7NrxqiaTn3n7Lh4O0EiMWimqIgaRmtJS2BgILy9vVXKBEHAsmXL4OzsrExYUlJSsHDhQri4uCAsLAxZWVnYtm0bbt26haVLl2orPCISiQfnX9i52Gjlj6pEYoBBMz0R+W18rXUGveAp2j/oDZmz0767tJmiImoYrSUtPXv2RM+ePVXKLl68iLKyMowZM0ZZtnbtWlhbW2PFihWwtLQEALRr1w5LlixBbGwsfHx8tBUiEbVwzT3/wtXHGaMWeKmcE6jpYRn0grjnfLSWOTuk35p1TsuRI0dgYGCA0aNHAwCKi4sRFxeHgIAAZcICAGPHjoW5uTmioqKaMzwiakF0Nf/C1ccZz64YAd/ZPQAAvrN74NnlI0SdsACtY84O6b9mS1qqqqoQFRWFnj17ol27dgCA1NRUVFdXw8PDQ6WusbEx3N3dkZKS0lzhEVELous1UyQSAzi4tQEAOLi1Ee2Q0P0Uc3bqIuY5O9Q6NFvSEhsbi4KCApWhIZlMBgCQStXHT6VSKXJycmo9Xk5ODpKTk5X/0tPTmz5oItKJ1rRmSnNRzNmpi5jn7FDr0GzrtBw5cgRGRkbw9/dXlpWX14ydGhsbq9U3MTFBRUVFrcfbvXs3IiIimjzO1qg13utPLRvnX2iHPs/ZodahWZKWkpISnDx5Ej4+PmjTpo2y3NS05o9kZWWl2j4VFRUwMTGp9ZiBgYHw9fVV/pyeno7Fixc3YdSth+Jef6KWgvMvtMfVxxku3k5IjspAdHgCfGf3gId/J/awkCg0S9Jy8uRJtbuGgH+HhRTDRPeTyWSwt7ev9Zj29vZ1bici8dL3NVN0TR/n7FDr0CxzWg4fPgxzc3OVnhEAcHV1haGhIZKTk1XKKysrkZKSgq5duzZHeETUwnD+BRFpovWkJT8/H3FxcRg2bBjMzFRnrltZWcHb2xuHDh1CSUmJsvzgwYMoLS1Vmf9CRK2LYv7Fg3e8WErNMGqBF+dfELVCWh8eioyMRHV1tdrQkMKcOXMQGhqKuXPnIjAwULki7oABAzBw4EBth0dELRjnXxDR/bTe03LkyBG0bdsW/fv317jdw8MDX3/9NUxNTbFy5Urs2bMHEydOxKeffqrt0IhIBDj/gogUtN7T8v333z+0Tu/evbF69Wpth0JEREQi1qzL+BORfuDaPkSkC822uBwR6Q+u7UNEusCeFtKJkrwynN2RgpK8updqJyIiUmDSQjpRkl+O+N+voYTLsBMRUT0xaSEi0jG5XEB2agEAIDu1QGtPryYSO85pISLSoRuxmSoPMIwOT8D5ndcxaCYfYEj0IPa0EBHpyI3YTER+G6/2jKXi3DJEfhuPG7GZOoqMSF1LmIvIpIWISAfkcgExGxPrrBOzKZFDRdRitIS5iExaiIh0IDMpt86nWANAsawMmUm5zRQRUcvHpIWISAdK6/lttb71iFoDJi1ERDpgXs/VhOtbj6g1YNJCpAUtYcIatWzO3exgaWdWZx1LqRmcu9k1U0RELR+TFiItaAkT1qhlk0gMMGimZ511Br3gyadaE92HSQsRkY64+jhj1AIvtR4XS6kZRi3w4jotRA/g4nJERDrk6uMMF28nJEdlIDo8Ab6ze8DDvxN7WIg0YE8LEZGOSSQGcHBrAwBwcGvDhIWoFkxaiIiISBSYtBAREZEoMGkhIiIiUWDSQkRERKLApIWISAMLW1N4Te4KC65IS9Ri8JZnIiINLNqaoX+Qu67DIKL7sKeFiIiIRIFJCxEREYkCkxYiolaIc3ZIjDinhYioFeKcHRIj9rQQERGRKDBpISIiIlFg0kJELR7nXxAR0AxzWpKTk7FhwwZcunQJFRUVaN++PZ588kkEBQUp61y6dAlr1qzB1atXYWlpCX9/f4SEhMDCwkLb4ZEOyOUCslMLAADZqQWwc7HhU22pTpx/QUSAlpOW2NhYLFq0CO7u7pg1axbMzc3xzz//IDs7W1knJSUFCxcuhIuLC8LCwpCVlYVt27bh1q1bWLp0qTbDIx24EZuJmI2JKM4tAwBEhyfg/M7rGDTTE64+zjqOjoiIWjKtJS3FxcX4/PPPMWjQIHz66aeQSDSPRK1duxbW1tZYsWIFLC0tAQDt2rXDkiVLEBsbCx8fH22FSM3sRmwmIr+NVysvzi1D5LfxGLXAi4kLERHVSmtzWo4cOYLc3FyEhIRAIpGgtLQUcrlcpU5xcTHi4uIQEBCgTFgAYOzYsTA3N0dUVJS2wqNmJpcLiNmYWGedmE2JkMuFZoqIiIjERms9LXFxcbC0tEROTg7+7//+DxkZGTA3N0dAQADCwsJgamqK1NRUVFdXw8PDQ2VfY2NjuLu7IyUlpdbj5+TkQCaTKX9OT0/X1qVQE8hMylUOCdWmWFaGzKRctO8ubaaoiIiaTkleGRIjM+A5qhMs2prpOhy9pLWk5datW6iursa7776LiRMn4uWXX8b58+fx22+/4d69e/jwww+VSYdUqv5HSiqV4sKFC7Uef/fu3YiIiNBW+NTESvPLm7QeEVFLU5Jfjvjfr8Glv6PeJS0t5QYKrSUtpaWlKCsrw1NPPYX58+cDAIYPH47Kykrs3r0bL730EsrLa/5AGRsbq+1vYmKCioqKWo8fGBgIX19f5c/p6elYvHhxE18FNRXzet6qWt96RETUPFrSDRRam9Nialrzx2fUqFEq5aNHjwYAJCQkKOtUVlaq7V9RUQETE5Naj29vbw8PDw/lPxcXl6YKnbTAuZsdLO3q/uZhKTWDcze7ZoqIiIgeRnEDxYPD+4obKG7EZjZrPFpLWhRDPnZ2qn+E2rZtCwAoKipS1rl/boqCTCaDvb29tsKjZiaRGGDQTM866wx6wZPrtRARtRAt8QYKrSUtism196/JAtRMoAUAW1tbuLq6wtDQEMnJySp1KisrkZKSgq5du2orPNIBVx9njFrgpdbjYik106vbnR8c+22OD3RJXhnO7khBSV7dk52JiOqrITdQNBetJS3+/v4AgL1796qU7927F4aGhvDy8oKVlRW8vb1x6NAhlJSUKOscPHgQpaWlymOQ/nD1ccazK0bAd3YPAIDv7B54dvkIvUlYbsRmYtu8o4gOTwBQM/a7bd5RrXehKiYAlnAiMxE1kZZ4A4XWJuI+/vjjmDBhAvbt24fq6mr07dsX58+fR1RUFGbMmKEc+pkzZw5CQ0Mxd+5cBAYGKlfEHTBgAAYOHKit8EiHJBIDOLi1AQA4uLXRmyEhLp5HRPqkJd5AodVl/N988004OTlh//79OHHiBJycnBAWFoZnnnlGWcfDwwNff/011qxZg5UrV8LCwgITJ07EK6+8os3QiJpUfcd+Xbyd9CZJIyL9priBoq4houa+gUKrSYuRkRFefPFFvPjii3XW6927N1avXq3NUIi0iovnEZG+UdxAoakHWaG5b6DQ2pwWotakJY79krhY2JrCa3JXWHCtImpBWtoNFFrtaSFqLVri2C+Ji0VbM/QPctd1GERqXH2c4eLthOSoDESHJ8B3dg94+HfSyVA3e1qImgAXzyMifdZSbqBg0kLUBLh4HhGR9jFpIWoiLW3sl4hI33BOC1ETakljv0RE+oY9LURNrKWM/RIR6RsmLURERCQKTFqIiIhIFJi0EBERkSgwaSEiIiJRYNJCREREosCkhYiIiESBSQsRERGJApMWIiIiEgUmLURERCQKTFqIiIgekVwuIDu1AACQnVoAuVzQcUT6ic8eIiIiegQ3YjMRszERxbllAIDo8ASc33kdg2Z68kGpTYw9LURERI10IzYTkd/GKxMWheLcMkR+G48bsZk6ikw/MWkhIiJqBLlcQMzGxDrrxGxK5FBRE2LSQiRyHEsn0o3MpFy1HpYHFcvKkJmU20wR6T/OaSESMY6lE+lOaX55k9ajh2NPC5FIcSydSLfMbU2btB49HJMWIhHiWDqR7jl3s4OlnVmddSylZnDuZtdMEek/Ji2kExa2pvCa3BUW/AbSKBxLJ9I9icQAg2Z61lln0AuekEgMmiki/cekhXTCoq0Z+ge5w6Jt3d9SSDOOpRO1DK4+zhi1wEutx8VSaoZRC7w4t6yJcSIukQhxLJ2o5XD1cYaLtxOSozIQHZ4A39k94OHfiT0sWsCeFiIR4lg6UcsikRjAwa0NAMDBrQ0TFi3RWk9LfHw85s+fr3Hb999/jx49eih/vnTpEtasWYOrV6/C0tIS/v7+CAkJgYWFhbbCIxI1xVh65LfxtdbhWDoRNaWWMBdR68NDU6ZMgaen6kSlDh06KP8/JSUFCxcuhIuLC8LCwpCVlYVt27bh1q1bWLp0qbbDIxItxVj6/eu0ADU9LINe4DotRNS0FHMRdUnrSUufPn0wYsSIWrevXbsW1tbWWLFiBSwtLQEA7dq1w5IlSxAbGwsfHx9th0gkWhxLJ6LWpFnmtJSUlKCqqkqtvLi4GHFxcQgICFAmLAAwduxYmJubIyoqqjnCIxI1jqUTUWuh9Z6WL774AqWlpTA0NETv3r3x2muvoVu3bgCA1NRUVFdXw8PDQ2UfY2NjuLu7IyUlRdvhEWlFSxj7JSLSN1pLWoyMjDB8+HAMGjQIbdq0QVpaGrZt24awsDCsXr0ajz/+OGQyGQBAKpWq7S+VSnHhwoVaj5+Tk6PcHwDS09Ob/iKIGqkljP0SEekbrSUtvXr1Qq9evZQ/Dx06FCNGjMCLL76ItWvX4quvvkJ5ec3CV8bGxmr7m5iYoKKiotbj7969GxEREU0eNxEREbVMzbq4XMeOHTF06FAcP34c1dXVMDWt6TqvrKxUq1tRUQETE5NajxUYGAhfX1/lz+np6Vi8eHHTB01EREQtQrOviOvo6IjKykqUlZUph4XuH+ZRkMlksLe3r/U49vb2dW4nIqKWoySvDImRGfAc1YmP76BGa/YVcW/fvg0TExOYm5vD1dUVhoaGSE5OVqlTWVmJlJQUdO3atbnDIyIiLSjJL0f879dQwudh0SPQWtKSn5+vVnbt2jVER0djwIABkEgksLKygre3Nw4dOoSSkhJlvYMHD6K0tBT+/v7aCo+IiIhERmvDQx9++CFMTU3Rs2dPtG3bFmlpadizZw/MzMzwyiuvKOvNmTMHoaGhmDt3LgIDA5Ur4g4YMAADBw7UVnhEREQkMlpLWvz8/HD48GFs374dxcXFsLW1xbBhwxAcHIyOHTsq63l4eODrr7/GmjVrsHLlSlhYWGDixIkqiQ0RERGR1pKWoKAgBAUF1atu7969sXr1am2FQkRERHqg2SfiEhERETUGkxYiIiISBSYtREREJApMWoiIiEgUmLQQERGRKDBpISIiIlFg0kJERESiwKSFiIiIRIFJCxEREYkCkxYiIiISBSYtRERETcDC1hRek7vCwtZU16HoLa09e4iIiKg1sWhrhv5B7roOQ6+xp4VahZK8MpzdkYKSvDJdh0JERI3EpIVahZL8csT/fg0l+eW6DoWIiBqJSQuRHuBYOhG1BpzTQqQHOJZORK0Be1qIiIhIFJi0EBGRVsnlArJTCwAA2akFkMsFrZ+Tk+/1E4eHiIhIa27EZiJmYyKKc2uSh+jwBJzfeR2DZnrC1cdZa+dVTL536e8Ii7ZmWjsPNS/2tBARkVbciM1E5LfxyoRFoTi3DJHfxuNGbKaOIiOxYtJCRERNTi4XELMxsc46MZsSm2WoiPQHkxYiImpymUm5aj0sDyqWlSEzKbeZIiJ9wKSFiIiaXGk9F3Ksbz0igEkLERFpgXk9Fzqsbz0igEkLERFpgXM3O1ja1X3XjqXUDM7d7JopItIHTFqIiKjJSSQGGDTTs846g17whERi0EwRkT5g0kJERFrh6uOMUQu81HpcLKVmGLXAS6vrtJB+4uJyRESkNa4+znDxdkJyVAaiwxPgO7sHPPw7sYeFGoU9LUREpFUSiQEc3NoAABzc2jBhoUZr1qRl48aNGDZsGGbNmqW27dKlSwgNDcWYMWMwadIkLF++HCUlJc0ZHhEREbVgzTY8lJWVhc2bN8Pc3FxtW0pKChYuXAgXFxeEhYUhKysL27Ztw61bt7B06dLmCpGIiIhasGZLWlavXo3u3btDLpejoKBAZdvatWthbW2NFStWwNLSEgDQrl07LFmyBLGxsfDx8WmuMImIiKiFapbhofPnz+PYsWOYO3eu2rbi4mLExcUhICBAmbAAwNixY2Fubo6oqKjmCJGIiIhaOK33tFRXV2P58uWYOHEiunTporY9NTUV1dXV8PDwUCk3NjaGu7s7UlJSNB43JycHMplM+XN6enrTBk5EREQtitaTll27duHu3bv45ptvNG5XJB5SqVRtm1QqxYULFzTut3v3bkRERDRZnKS/5HIB2ak1Q5LZqQWwc7Hh3QtERCKk1aSloKAAP/74I2bOnAlbW1uNdcrLax6WZWxsrLbNxMQEFRUVGvcLDAyEr6+v8uf09HQsXrz40YMmvXIjNhMxGxOVT5uNDk/A+Z3XMWimJxe2IiISGa0mLevXr4e1tTWmTJlSax1T05qHZVVWVqptq6iogImJicb97O3tYW9v3zSBkl66EZuJyG/j1cqLc8sQ+W08V+QkIhIZrU3EzcjIwJ49exAUFIScnBzcuXMHd+7cQUVFBaqqqnDnzh0UFhYqh4Xun5+iIJPJmJhQo8jlAmI2JtZZJ2ZTIuRyoZkiIiKiR6W1npacnBzI5XIsX74cy5cvV9v+7LPPIigoCC+99BIMDQ2RnJyMkSNHKrdXVlYiJSUF/v7+2gqR9FhmUq5ySKg2xbIyZCblon139flURCRenMemv7SWtLi6uuKzzz5TK1+/fj1KSkowb948tG/fHlZWVvD29sahQ4cwa9YsWFhYAAAOHjyI0tJSJi3UKKX55U1aj4jEgfPY9JvWkhZbW1v4+fmplf/6668AoLJtzpw5CA0Nxdy5cxEYGKhcEXfAgAEYOHCgtkIkPWZua9qk9Yio5eM8Nv3XIh6Y6OHhga+//hqmpqZYuXIl9uzZg4kTJ+LTTz/VdWgkUs7d7GBpZ1ZnHUupGZy72TVTRESkTZzH1jo02zL+CitWrNBY3rt3b6xevbqZoyF9JZEYYNBMT43fuhQGveDJcW4iPcF5bK1Di+hpIdIGVx9njFrgpdbjYik1YzcxkZ7hPLbWodl7Woiak6uPM1y8nZAclYHo8AT4zu4BD/9O7GEh0jOcx9Y6sKeF9J5EYgAHtzYAAAe3NkxYiPQQ57G1DkxaiIhI9BTz2OrCeWzix6SFiIj0Auex6T/OaSEiIr3BeWz6jT0tRESkdRa2pvCa3BUWzTARlvPY9Bd7WoiISOss2pqhf5C7rsMgkWNPCxEREYkCkxYiIiISBSYtREREJApMWoiIiEgUmLQQERGRKDBpISIiIlFg0kJERESiwKSFiIiIRIFJCxEREYkCkxYiIiISBSYtREREJApMWoiIiEgUmLQQERGRKDBpISIiIlFg0kKtgoWtKbwmd4WFramuQyEiokYy0nUARM3Boq0Z+ge56zoMIiJ6BOxpISIiIlFg0kJERESiwKSFiIj0Duex6SfOaSEiIr3DeWz6SWtJy40bN7BhwwYkJycjNzcXZmZmcHFxwbRp0+Dr66tSNy0tDatWrcKlS5dgZGSEwYMHIywsDLa2ttoKj4iIiERGa0lLZmYmSkpKMG7cONjb26OsrAzHjh3DokWL8OabbyIwMBAAkJWVhblz58LKygohISEoLS3F1q1bkZqaih9++AHGxsbaCpGIiIhERGtJy+DBgzF48GCVssmTJyMkJATbt29XJi2bN29GWVkZ1q9fDycnJwCAp6cn3njjDezfv19Zj4iIiFq3Zp2Ia2hoCEdHR9y7d09ZduzYMQwZMkSZsACAt7c3OnXqhKioqOYMj4iIiFowrU/ELS0tRXl5OYqLixEdHY0zZ87A398fAJCdnY28vDx4eHio7efp6YmYmBhth0dEREQiofWk5bvvvsPu3bsBABKJBMOGDcPChQsBADKZDAAglUrV9pNKpSgsLERFRQVMTEzUtufk5Cj3B4D09HRthE9EREQthNaTlqlTp2LEiBHIyclBVFQUqqurUVlZCQAoLy8HAI2TbRWJSnl5ucakZffu3YiIiNBe4ERERNSiaD1pcXFxgYuLCwBg3LhxeOONN/DOO+/ghx9+gKlpzaI/iiTmfhUVFQCgrPOgwMBAlVun09PTsXjx4qYOn4iIiFqIZl9cbsSIEfjqq6+QkZGhHBa6f5hHQSaTwcbGRmMvCwDY29vD3t5eq7ESERFRy9Hsy/grhoTu3bsHBwcH2NraIjk5Wa1eYmIiunbt2tzhERERUQultaQlLy9PrayqqgoHDx6EqakpHnvsMQDA8OHDcerUKdy9e1dZ7+zZs8jIyFDeZURERESkteGhr776CsXFxejTpw8cHBwgk8lw+PBh3Lx5E6GhobCwsAAAzJgxA0ePHsWCBQsQFBSE0tJSbNmyBW5ubhg/fry2wiMiIiKR0VrSMnLkSOzduxe7du1CQUEBLCws4OHhgVdffRVDhw5V1nNycsKKFSuwatUq/PDDD8pnD4WGhtY6n4WIiIhaHwNBEARdB9EUkpOTERISgnXr1mlcrI6IiIjErdnvHtIWxQRfLjJHREQkPi4uLjAzM6uzjt4kLZmZmQDAtVqIiIhEqD4jJXozPJSfn4/Y2Fi0a9dOtHNhFAvkvffee8oF+VojtsO/2BY12A7/Ylv8i21RQ1/aoVX1tNja2iIgIEDXYTQJFxcXzssB2+F+bIsabId/sS3+xbao0RraodkXlyMiIiJqDCYtREREJApMWloQqVSK4OBg5TOZWiu2w7/YFjXYDv9iW/yLbVGjNbWD3kzEJSIiIv3GnhYiIiISBSYtREREJApMWoiIiEgUmLQQERGRKOjN4nJikZOTgx07diAxMRFJSUkoLS3F8uXL4eXlpVZ33rx5OH/+vFq5j48PvvrqK5WyiooKhIeH49ChQygqKkKXLl0wZ84cDBgwQFuX8kga0g4AcOnSJaxZswZXr16FpaUl/P39ERISAgsLC5V6YmuH2uzfvx9ffPGFxm07d+5Uu0vg5MmT2LBhA9LT02Fra4sJEyZg5syZMDIS90dcX17PhoiPj8f8+fM1bvv+++/Ro0cP5c/1/VyIQUlJCbZu3YorV64gMTERRUVFWLRoEcaPH69WNy0tDatWrcKlS5dgZGSEwYMHIywsDLa2tir15HI5tm7dij/++AO5ubno2LEjZsyYgdGjRzfTVTVcfdvh888/x4EDB9T279y5MzZv3qxSJsZ2qI24f6OJUEZGBn755Rd07NgRbm5uSEhIqLO+g4MDXnnlFZUyTbe1ffHFFzh69CimTp2Kjh07Yv/+/XjrrbewfPly9O7du0mvoSk0pB1SUlKwcOFCuLi4ICwsDFlZWdi2bRtu3bqFpUuXqtQVWzs8zOzZs9GuXTuVMisrK5WfY2Ji8H//93/o27cv5s+fj9TUVGzcuBF5eXn4z3/+05zhNjl9ez0bYsqUKfD09FQp69Chg/L/G/K5EIOCggJERETAyckJXbt2RXx8vMZ6WVlZmDt3LqysrBASEoLS0lJs3boVqamp+OGHH2BsbKysu27dOvz888948skn0a1bN5w8eRKffPIJDAwMMGrUqOa6tAapbzsAgImJCd566y2VMktLS7V6YmyHWgnUrIqLi4WCggJBEAQhKipK8PPzE86dO6ex7ty5c4WZM2c+9JgJCQmCn5+f8MsvvyjLysrKhOeee0549dVXmybwJtaQdnjzzTeFSZMmCffu3VOW7dmzR/Dz8xPOnDmjLBNjO9Rm3759gp+fn5CYmPjQui+88ILw4osvCpWVlcqytWvXCsOGDRPS0tK0GaZW6dPr2RDnzp0T/Pz8hKioqDrr1fdzIRbl5eVCTk6OIAiCkJiYKPj5+Qn79u1Tq7ds2TJh9OjRQmZmprLs77//Fvz8/IRdu3Ypy7KysgR/f3/h66+/VpbJ5XIhNDRUmDx5slBVVaXFq2m8+rbDZ599JgQEBDz0eGJth9pwTkszs7CwgI2NTYP2qaqqQklJSa3bjx07BkNDQwQGBirLTE1NMXHiRCQkJODu3buNjldb6tsOxcXFiIuLQ0BAgMo3iLFjx8Lc3BxRUVHKMjG2Q32UlJSgurpa47a0tDSkpaXhySefVBkKevrppyEIAo4ePdpMUTY9fX09G6KkpARVVVVq5Q35XIiFiYlJvRZHO3bsGIYMGQInJydlmbe3Nzp16qRy3SdPnkRVVRWefvppZZmBgQEmTZqE7Ozsh/Zy60p920GhuroaxcXFtW4XazvUhsNDLVxGRgbGjh2LyspK2NnZ4YknnkBwcLDKH6iUlBR07NhRrVtQ0bV87do1lQ+4mKSmpqK6ulrtIWDGxsZwd3dHSkqKskwf22H+/PkoLS2FsbExBgwYgNDQUHTq1Em5/erVqwCg1j729vZwcHBQaR+x0cfXsyG++OILlJaWwtDQEL1798Zrr72Gbt26AWjY50KfZGdnIy8vT+NDAT09PRETE6P8OSUlBebm5mpPPVa8f1JSUkQ/xFhWVobx48ejrKwM1tbWGDVqFF599VWVOU361g5MWlqw9u3bw8vLC25ubigrK8PRo0exceNGZGRk4OOPP1bWk8lkGjNzRVlOTk6zxdzUZDIZAM3zeKRSKS5cuKBSV1/awdTUFOPHj4eXlxcsLS2RnJyM7du34/XXX8f69euVf6wf1j6K7WKkT69nQxgZGWH48OEYNGgQ2rRpg7S0NGzbtg1hYWFYvXo1Hn/88QZ9LvTJw667sLAQFRUVMDExgUwmQ9u2bWFgYKBWDxD/+0cqlWLatGl4/PHHIQgCzpw5gz/++APXr1/H8uXLlV9s9a0dmLQ8ArlcjsrKynrVNTExUXvTPMw777yj8vPYsWOxdOlS7NmzB88884zyLoLy8nKVyWf3n1OxXZu02Q6K2Gu7voqKCpW6umyH2jSmfUaOHImRI0cqy/38/ODj44O5c+di06ZNePPNNwFAef2Ka3zwWHUNK7Z0LfX11LZevXqhV69eyp+HDh2KESNG4MUXX8TatWvx1VdfNehzoU8edt2KOiYmJnr//nnwBo1Ro0ahU6dOWLduHY4dO6acYKtv7cCk5RFcuHCh1lsTH7Rp0ya17rnGePbZZ7Fnzx7ExcUpkxZTU1ONfxQVv7hMTU0f+bx10WY7KGKv7fru/2Ot63aoTVO1T+/evdG9e3ecPXtWWaa4fk1/pCoqKnR2zU2hpb6eutCxY0cMHToUx48fR3V1dYM+F/rkYdd9f53W+P555plnEB4ejri4OGXSom/twKTlEXTu3BmLFi2qV92mevqmo6MjAKCoqEjl2NnZ2Wp1FV2p9vb2TXLu2mizHRT1NQ1zyGQylWvTdTvUpinbx9HRETdv3lSrL5PJ1OZ3yGQytVtmxaSlvp664ujoiMrKSpSVlTXoc6FPHnbdNjY2yoRNKpUiPj4egiCo9O7q8/vH1NQUNjY2KCwsVJbpWzswaXkEUqlU48JH2nT79m0AUFlESXEvf3FxscqkxStXrii3a5M228HV1RWGhoZITk5WGS6prKxESkoK/P39lWW6bofaNGX73L59W+W1d3d3BwAkJyeje/fuyvKcnBxkZ2er3HkjNi319dSV27dvw8TEBObm5g36XOgTBwcH2NraIjk5WW1bYmKiynuia9eu+PPPP5Geno7HHntMWa7P75+SkhIUFBSo/X3Qp3bgLc8tVHFxsVqXvyAI2LhxIwCorAg6YsQIVFdXY/fu3cqyiooK7Nu3D927dxf1HRZWVlbw9vbGoUOHVOZnHDx4EKWlpSq/nPWpHfLz89XKTp8+jeTkZPj4+CjLXF1d0blzZ+zZs0fltug//vgDBgYGGD58eHOEqxX69Ho2hKbX/tq1a4iOjsaAAQMgkUga9LnQN8OHD8epU6dUbnk/e/YsMjIyVK576NChMDIyws6dO5VlgiBg165dcHBwQM+ePZs17qZUXl6ucb7aTz/9BEEQMHDgQGWZvrUDe1p04KeffgJQs8YGUPOL5uLFiwCAWbNmAai5lfXjjz/G6NGj0aFDB5SXl+PEiRO4dOkSnnzySZVb/rp37w5/f3+sXbsW+fn56NChAw4cOIDMzEy8/fbbzXtxDVCfdgCAOXPmIDQ0FHPnzkVgYKBy5c8BAwaofDjF2g6avPbaa3j88cfh4eEBS0tLXL16Ffv27YOjoyNeeOEFlbqvv/46Fi1ahP/85z8YNWoUUlNTsXPnTjzxxBMq36zERp9ez4b48MMPYWpqip49e6Jt27ZIS0vDnj17YGZmpjL5sr6fCzH57bffcO/ePeXQRXR0NLKysgDUrBBsZWWFGTNm4OjRo1iwYAGCgoJQWlqKLVu2wM3NTaVH09HREVOnTsWWLVtQVVUFT09PnDhxAhcvXsT7778PQ0NDnVxjfTysHYqKijB79myMHj0anTt3BgDExsYiJiYGAwcOxNChQ5XHEnM7aGIgCIKg6yBam2HDhtW67fjx4wBquoJ/+OEHJCYmIjc3FxKJBC4uLnjiiScQGBiodgdOeXm58hkt9+7dg5ubG+bMmaPyrbylqU87KFy8eFH5jBULCwv4+/vjlVdeUXvGihjbQZN169YhJiYGd+7cUc5hGDx4MIKDg2FnZ6dW/8SJE4iIiEB6ejratGmD8ePHq63nI0b68no2xI4dO3D48GH8888/KC4uhq2tLfr374/g4GB07NhRpW59Pxdi8cwzzyAzM1Pjtm3btikfaXHjxg21Zw+FhoaqfTbkcjl++eUX7N69GzKZDB07dsTzzz+PgIAArV/Lo3hYO1hZWWH58uVISEiATCaDXC5Hhw4dMGbMGDz33HNqn3uxtoMmTFqIiIhIFDinhYiIiESBSQsRERGJApMWIiIiEgUmLURERCQKTFqIiIhIFJi0EBERkSgwaSEiIiJRYNJCREREosCkhRps//79GDZsGPbv36/rUOolPj4ew4YNw48//qi1cwwbNgzz5s3T2vFbi2eeeQbPPPOMrsNo8X788UcMGzYM8fHxWj3P9u3bMXLkSNy5c6de9ZvjsyZmn376KaZOnYry8nJdhyJaTFpagf/9738YNmwYnnjiCbWHMOoLsf2xKygowJo1azBz5kyMGTMGY8aMwdSpU7FgwQJs2LABubm5zRLHwxLQefPm1fm4hdaktLQU48aNw7Bhw/D111/rOhytKyoqwsaNGzFhwgTl8vn0aIKDg5GTk4Nff/1V16GIlrgfTEIPVVJSgqioKBgYGKCwsBAnTpzAqFGjHumYfn5+6N69O6RSaRNF2bpkZWXh9ddfR1ZWFtzd3TF+/HhYW1tDJpPh8uXL2LBhA3r16qXxGUP67ptvvtF1CLWKiopCSUkJDAwMcOTIEYSGhsLU1FTXYWnN9u3bUVhYiGnTpuk6FL3RqVMn+Pr64pdffsGUKVNgbm6u65BEh0mLnvvrr79QWlqKZ555Bjt27MDevXsfOWmxsrKClZVVE0XY+vz444/IysrC7NmzVZ5mrXD9+vVW274dOnTQdQi12rt3LwwNDTF58mT8+uuvOH78OMaMGaPrsLSiqqoKf/75J3r16tWiXxMxCggIwPHjxxEZGYknnnhC1+GIDpMWPaf4RTt9+nRcv34d586dQ2ZmJpydnVXq/fjjj4iIiKj1OM7Ozti+fTuAmiGFL774AosWLVJ5FPywYcPQt29fvP/++/j+++/x999/o6KiAn369MGCBQvQvn17pKWlYe3atbhw4QKqqqrg4+ODhQsXqvQqxMfHY/78+QgODsZLL72kEsedO3fw7LPPYty4cXj33XeVP98fg4Km/ZOSkrB27VokJCRAIpGgX79+CAsLU+v+Pn78OKKiopCUlIScnBwYGRmhS5cuCAoKwogRI+pu9IdISEgAAEyePFnj9i5dumgsv337Nn7++Wf8/fffkMlksLS0xGOPPYbx48crX4fKykrs3r0bp06dQlpaGvLz82FpaYlevXph1qxZePzxx5XH+/zzz3HgwAEAwBdffIEvvvhC5frvb8v7/1/R9grXr1/Hpk2bcP78eRQWFkIqlcLX1xcvvvgi2rRpo6x3/2s3ffp0rFu3DhcuXEBhYaHyCb6KIT7Few349725fPly5OTkYMuWLbh58yasrKzg7++PV199Va3Ho6qqClu3bsWff/6JnJwcODg4YOLEiRg5ciSee+45tWt4mJs3b+LSpUsYMmSIyhcATUnL/e/fIUOG1Ov9BgDHjh3D5s2bcePGDVhaWsLX1xevvfYaZs+erdYmdanv61GX2NhYyGQyTJ8+XeP28vJybNiwAYcPH0ZBQQE6dOiAoKAgtadQ3+/27dvYtGkT/v77b+Tl5cHa2ho+Pj546aWX1H4fAQ1rD8V7eevWrTh+/Dj27t2L27dvY9SoUcrXOS8vD5s3b8apU6eQlZUFCwsL9OnTBy+99BLc3NzUzt+Q+hkZGdi8eTPi4+Mhk8lgZmYGR0dHeHl5Ye7cuTAwMFDWHTx4MMzMzHDgwAEmLY3ApEWPpaWlISEhAYMGDYKdnR3Gjh2Ls2fPYt++fWp/zL28vDQeIz09HVFRUfXuBi8qKkJoaCikUinGjh2LW7du4dSpU3jjjTfw+eefIywsDB4eHpgwYQKuXr2KY8eOobCwEMuXL2/UNVpZWSE4OBg7duwAAAQFBdV6TUlJSdiyZQu8vLwQGBiIlJQUnDhxAqmpqYiIiFC5xrVr18LIyAi9evWCVCpFfn4+oqOj8cEHH2D+/PmYMmVKo+IFoPzDkZGRge7du9drn4sXL+Ltt99GSUkJfHx8MGrUKBQVFSElJQU7duxQJi2FhYVYuXIlevfujUGDBsHa2hp37txBdHQ0zpw5g5UrV8LT0xNAzTDfvXv3cPLkSQwdOhRdu3ZVOWdwcDAOHDiAzMxMBAcHK8vd3d2V/3/y5El89NFHMDAwwNChQ+Ho6Ii0tDT8/vvviI2NxQ8//ABra2uV4/7zzz947bXX4ObmhnHjxqGwsBDGxsYPbQPFMX19fdGvXz+cOXMGv/32GwoKCvDBBx+o1P3yyy9x8OBBtG/fHpMmTUJlZSW2b9+Oy5cv16u9H7R3714AwNixY+Hk5IS+ffsiPj4et2/fRvv27TXu05D32969e/Hll1/C0tISY8eOhZWVFWJiYvDGG2+gqqoKRkb1+1XdmNdDk7NnzwIAevToobZNLpdj0aJFiIuLg5ubG0aPHo3CwkKsWrWq1t8jV65cwZtvvonS0lIMGTIEHTt2RGZmJg4fPowzZ87g+++/V2nHxrbHt99+iytXrmDw4MEYMmQI2rZtC6DmPTdv3jxkZ2djwIABGDp0KPLz83Hs2DH8/fff+Oabb1Q+iw2pn5OTg1deeQVlZWUYPHgwRo4cibKyMty6dQt//PEHXn/9dZV4jY2N8fjjjyMhIQGlpaUcImoogfTWypUrBT8/P+HIkSOCIAhCcXGxEBAQIAQFBQnV1dUP3T83N1eYOnWqMGrUKOHixYvK8n379gl+fn7Cvn37VOr7+fkJfn5+wsqVK1XKly1bJvj5+Qnjx48Xtm/friyXy+XCf//7X8HPz09ISkpSlp87d07w8/MTwsPD1WK6ffu24OfnJ3z22Wcq5VOnThWmTp2q8ToUx7u/LRQWL16ssfyff/5RO05xcbEwa9YsYfz48UJpaanatc+dO1fj+R+0Y8cOwc/PTwgMDBTCw8OFc+fOCffu3au1fnl5uTB58mRh+PDhQkxMjNr2u3fvqtTNyspSq5OamioEBAQICxcuVCmv7bVUmDt3ruDn56dxW35+vjBu3Dhh8uTJwp07d1S2HTlyRPDz8xO++eYbZZnitavttRUEza9jeHi48v2Tnp6uLC8rKxOmT58uDB8+XMjOzlaWx8XFCX5+fsJLL72k8jplZ2cLTz31lMb3T10qKyuFp556Shg/frxQVlYmCIIg7N27V/Dz8xPWrVunVr+h77fCwkIhICBACAgIEG7evKly3vnz5wt+fn61tsm5c+eUZQ19PeoSEhIiDB8+XCgvL1fbpnjPvPnmm0JVVZWy/Nq1a8LIkSPVXt/Kykph6tSpwtixY4Xk5GSVY124cEEYMWKE8Pbbbz9Se3z22WeCn5+fMHnyZCEzM1Mt5tdee00YMWKEcObMGZXymzdvCmPHjhVmzZrV6PqKz/P9v9sUCgoK1MoE4d/fzWfPntW4nWrHu4f0VFVVFQ4dOgRLS0sMHToUAGBhYQE/Pz/cvXsXcXFxde5fXl6Od999F5mZmXjnnXfQq1evep3X3Nwcc+bMUSlTzKFp06aNSk+IgYGBctv169frfW2N1adPH7X5PBMmTAAAJCYmqpRr+vZsYWGB8ePH4969e0hKSmp0HJMnT8a0adNw7949REREYP78+ZgwYQJmzpyJNWvWICcnR6X+yZMnkZ2djTFjxmDgwIFqx3N0dFT+v4mJCRwcHNTquLq6wsvLSzks1xQOHjyI4uJivPzyy2rd+6NGjcLjjz+OyMhItf3s7OzwwgsvNPh8QUFB6Ny5s/JnU1NTjBo1CnK5HMnJycryQ4cOAQBmzZoFMzMzZbm9vb3K+6++Tp8+jdzcXPj7+yt7R0aMGAEzMzPs378fcrlc4371fb+dPHkSpaWlmDBhAjp16qQsNzIyUvss1aWxr4cm2dnZsLKygomJido2xZDinDlzYGhoqCzv0qULAgIC1OqfOnUKmZmZmDZtmsrwJAD07t0bvr6+iImJQXFxMYBHa49p06bByclJpezq1au4fPkyxo4dCx8fH5VtnTp1whNPPIHU1FSkpqY2qr6Cpt5oGxsbjXEqeoCys7PrvB5Sx+EhPXXy5Enk5+dj4sSJKh+msWPH4tChQ9i7d6/aB1JBEAR8/vnnSEhIwIsvvojRo0fX+7wdO3ZU+UMBQHmXkZubm8rY7v3bHvxDrQ0eHh5qZYo/8Pfu3VMpz8vLw88//4yYmBjcvXtXbV2FR4nXwMAAr732GqZNm4aYmBhcuXIFSUlJuHr1KtLS0rB792589dVXyu5nxR+4AQMG1Ov4KSkp2LJlCy5evIjc3Fy1JCU/Px/29vaNjl9BMTfnypUr+Oeff9S2V1RUoKCgAPn5+bC1tVWWd+3atV7DQQ968A8e8G/Cdv/rd+3aNQA1fxAf1LNnzwaf988//wRQ89lRsLCwwNChQ3HkyBHExsZi0KBBavvV9/2mSNg1xdu9e3eVxKAujX09NCksLNSY/CriNTc313h9vXv3Vg6lPRjXzZs3Na7fkpubC7lcjoyMDHTr1u2R2kMx9Hm/K1euAKj5TGs6/82bN5X/dXNza3B9xbylb775BmfPnsXAgQPRt2/fWocNgX+TmYKCglrrkGZMWvTU/WPw9+vfvz8cHBwQHR2NwsJCjd8E1q9fj6ioKIwePRovvvhig85raWmpVqb4JVPXtqb69l8XCwuLWs9//7flwsJCvPzyy7h79y569eoFb29vWFlZQSKR4Nq1azh58iQqKysfOR5bW1uMGzcO48aNAwDIZDJ8++23OHbsGJYuXYoNGzYAgPIbaG1/RO536dIlLFy4EADg7e2Njh07Kq/75MmTuHbtWpPEDtTMXwKAnTt31lmvrKxM5WfFt8yGquv9c//rV1JSAolEonHSaUNvI8/JyUFsbCzat2+v9kd03LhxOHLkCPbt26cxaanv+03x+mpql9quQ5PGvh6amJqa1rqmU3Fxca3vRU3tq4jr8OHD9YrrUdpD0z6FhYUAanrMTp8+Xeu+paWljarfrl07fP/999iwYQNiYmIQFRUFAOjcuTNmz54Nf39/tX0VX4L0+ZZ5bWHSoofu3r2Lv//+GwDqXKX10KFDat3l+/fvx6ZNm9CrVy+88847Wo2zNoremOrqarVtil9o2rR3717cvXtX4y3JmzdvxsmTJ7VyXqlUivfeew+nT5/G9evXUVBQgDZt2ihvf65PV/KmTZtQUVGBVatWqf2RVXyDbCqKP8oREREa776ozYO9bU3NwsICcrkcBQUFaj0KDV20b//+/aiursbt27drXWQvOjq6Xr0XtVEkY3l5eWrbFNdRn4S1sa+HJm3atKn1/WZpaVlrD4Gm9lXE9b///Q9Dhgx56LkfpT00vbcUx6vvBPqG1gdqepE//fRTVFVVITk5GWfOnMGOHTvw0Ucfwd7eXm14XZEYNfY905pxToseOnDgAORyOXr37o2JEyeq/VN8s3+wG/f8+fP46quv0L59e3z22Wcax7Obg+LuBk1DMCkpKRr3kUgkGpOcxlB0rSvmAt3v4sWLTXKO2hgbG6t1fyu6vBWJaF1u374NGxsbtYSlrKwMV69eVasvkdT8Cqit7erarhi+UnT/txSKu6AuXbqktq0hdw8JgoB9+/YBAMaPH6/xs9SzZ09UVlYq59E0huIWd03xJiYm1vt93ZSvh5ubGyoqKnD37l21bV26dEFpaanKPCIFTZ+PhsbVVO2hoPj81Pf8Da1/PyMjI/To0QMvvfQS5s+fD0EQcOrUKbV6GRkZAPDIyWVrxKRFzyh+0RoYGODdd9/F22+/rfbv3XffRY8ePXD9+nXlhNKMjAy89957MDU1xf/+9z+dfgPo3LkzLCwslENYCrm5udi4caPGfWxsbFBQUNAkz/RQTGJ88Jfm4cOHERMT88jH37p1K9LT0zVu+/3331FaWorOnTsru8F9fX3h4OCAw4cPIzY2Vm2f+78ROzk5oaioCDdu3FCWVVdXY/Xq1cjPz1fbVzE8mJWVpTGeurZPmDABFhYWWLduncr5FMrKynSS0CjWTomIiFB5P8hkMuWt8fVx/vx5/PPPP+jTpw8WLVqk8bOk6I188AtAQwwdOhTm5ubYu3evylyUqqoqhIeH1/s4Tfl69O3bF4Dm3jnFkPP69etVEojr169rTN6GDh0KJycnbNu2DefPn1fbXlVVpZLsNFV7KHTv3h3du3dHZGSkxonIcrlcJa6G1k9OTtbYA6zoddL05e/KlSuQSqUqE42pfjg8pGfOnTuHO3fuPHQi2IQJE5CQkIC9e/eiW7duWLFiBQoLC+Ht7Y2//vpLrb6VlVWzPdvH2NgYU6ZMwaZNmzBnzhz4+vqitLQU0dHR6Nu3r8ZJhl5eXkhKSsJbb72F3r17w8jICH369FH+8m2IgIAA/PLLL1i+fDni4+Ph5OSEa9eu4dy5cxg2bBiOHz/+SNd36NAhrF69Gm5ubujevTvatm2LoqIiXLlyBVevXoWpqSn+85//KOubmJjg448/xn//+1/897//hY+PD7p27Yri4mJcu3YN5eXlyl/mU6ZMwd9//43Q0FD4+/vDxMQE58+fR05ODry8vNQesNejRw+Ymppix44dKCoqUiarimGxfv364ejRo3j//fcxcOBAmJiYoGvXrvD19YWtrS0+/PBDfPDBB3jppZfg4+ODzp07o7KyEpmZmTh//jx69uyJr7766pHaq6G8vb0xevRoHDlyBMHBwRg6dCgqKysRFRUFT09PnDp1StmDVBdFIqK440eTzp07o2fPnrh8+TKuXLlS73V37mdtbY2wsDAsXboUISEhGDlyJCwtLRETEwMTExPY29vXa0itKV+PoUOH4rvvvkNcXJzanAzFXJ4zZ85g9uzZGDhwIIqKihAZGYkBAwao9SyYmJjgk08+wVtvvYV58+ahX79+ykn5mZmZuHjxItq0aYPNmzc3aXvc74MPPsCCBQvw8ccfY8eOHXB3d4epqSmysrJw+fJlFBQU4MiRI42qf/DgQezevRt9+vRBhw4dYGFhgbS0NJw5cwY2NjZq759//vkHd+7cwaRJkxp0DVSDSYueUfyivX+lWk1GjhyJFStWIDIyEmFhYcpvpHFxcRpvh3Z2dm7WBxLOnj0bRkZG2Lt3L3bv3g1nZ2fMmjULQ4YMwbFjx9Tqz5o1C/fu3cOpU6dw8eJFVFdXIzg4uFFJi6OjI1asWIHvv/8ecXFxqK6uxuOPP45ly5YhKyvrkZOWd955B6dOncK5c+cQGxuLvLw8SCQSODk5YdKkSZg6daraN7CePXti/fr12Lx5M2JjY3H27FlYW1vjsccew1NPPaWsN2TIEHzyySfYvHkzDh8+DFNTU/Tr1w+fffaZxhWPbWxs8Mknn2DDhg34888/le8DRdLyxBNP4M6dO/jrr7/wyy+/oLq6GuPGjYOvry+AmtU9w8PDsWXLFpw9exZxcXEwMzODg4MDxo8fr/EW2Obw7rvvwsXFBfv27cPvv/8OBwcHTJ06Ff369cOpU6c0TpK9371793Ds2DGYm5tj+PDhddadMGECLl++jL179zYqaQGAJ598EtbW1ti0aRMOHDigXAH21VdfxdSpU+u9lH5TvR7t2rXDgAEDcPToUcyfP1+lt0AikeDzzz/Hhg0bcOTIEfz2229o3749wsLC0LFjR43DIZ6envjxxx+xZcsWxMTE4PLlyzA2Noa9vT38/PzUbg1vqvZQaN++PcLDw7Ft2zacOHEC+/fvh0QigVQqRZ8+fdRWuW5I/dGjR6OiogKXLl1CYmIiKisr4eDggKeeekrjLdiK3qjAwMAGXQPVMBAEQdB1EEREzeHPP//EkiVL8MYbb4jim+6tW7cwffp0+Pv74+OPP27Wc589exYLFy7Ee++9p7Pk80G6bI+mUFVVhenTp6Ndu3aNXgW8teOcFiLSOzKZDA9+H8vOzsbGjRthaGiIwYMH6ygyzYqKitRuMS4vL8eqVasA1Dxyobn1798fAwcOxMaNG2tdQE9bWmJ7NIUDBw7g7t27eP3113UdimhxeIiI9M7PP/+M06dPo0+fPrC1tUVWVhZOnTqFkpISvPjii2pd9rp2/vx5fPnllxgwYAAcHR1RUFCgfLhpv379MHLkSJ3ENW/ePBw+fBjZ2dnN2mYttT0elYGBAf773/9qXJiP6ofDQ0Skd86cOYNt27bh+vXrKCoqgomJCbp06YJJkyZpfDKzrmVkZCA8PByXL19W3uXVoUMH5VOpW9siZGwPqg2TFiIiIhIFzmkhIiIiUWDSQkRERKLApIWIiIhEgUkLERERiQKTFiIiIhIFJi1EREQkCkxaiIiISBSYtBAREZEoMGkhIiIiUfh/nSQ5XgfWvxIAAAAASUVORK5CYII=",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -749,7 +367,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -759,7 +377,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -769,7 +387,7 @@
     },
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -779,101 +397,113 @@
     }
    ],
    "source": [
-    "titles = {'grb': 'GRB ASAD', 'grb & background': 'GRB+background ASAD', 'background': 'Background ASAD', 'unpolarized': 'Unpolarized ASAD'}\n",
-    "for key in titles.keys():\n",
-    "    grb_polarization.plot_asad(asads[key]['counts'], asads[key]['uncertainties'], titles[key])"
+    "asad_bin_edges = Angle(np.linspace(-np.pi, np.pi, 17), unit=u.rad)\n",
+    "\n",
+    "grb_polarization = PolarizationASAD(source_direction, spectrum, asad_bin_edges, data, background, sc_orientation, response_file, response_convention='RelativeZ', show_plots=True)"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "539abbb2",
+   "id": "d4cb1625",
    "metadata": {},
    "source": [
-    "Divide the GRB ASAD by the unpolarized ASAD to correct for instrumental effects"
+    "Perform the fit in the ICRS frame. A sinusoid is fit to the GRB ASAD, and the amplitude and phase are used to determine the polarization fraction and angle, respectively. Because the polarization angles are distributed uniformly within the polarization angle bins of the response, and the bins are coarse, the $\\mu_{100}$ is underestimated, causing the fitted polarization fraction of the source to be overestimated."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
-   "id": "50e01dd4",
+   "execution_count": 19,
+   "id": "18ee6424",
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Best fit polarization fraction: 0.953 +/- 0.073\n",
+      "Minimum detectable polarization: 0.164\n",
+      "Best fit polarization angle (IAU convention): 87.668 +/- 1.987\n"
+     ]
+    }
+   ],
    "source": [
-    "asad_corrected = grb_polarization.correct_asad(asads['grb'], asads['unpolarized'])"
+    "polarization_icrs_fit = grb_polarization.fit(show_plots=True)\n",
+    "\n",
+    "print('Best fit polarization fraction:', round(polarization_icrs_fit['fraction'], 3), '+/-', round(polarization_icrs_fit['fraction uncertainty'], 3))\n",
+    "print('Minimum detectable polarization:', round(grb_polarization._mdp, 3))\n",
+    "print('Best fit polarization angle (IAU convention):', round(polarization_icrs_fit['angle'].angle.degree, 3), '+/-', round(polarization_icrs_fit['angle uncertainty'].degree, 3))\n"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "3275a6a6",
+   "id": "d98e8ebd",
    "metadata": {},
    "source": [
-    "Calculate the minimum detectable polarization (MDP) of the GRB "
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 13,
-   "id": "d79420fd",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "source_counts = np.sum(asads['grb']['counts'])\n",
-    "background_counts = np.sum(background_asad_grb_duration)\n",
-    "\n",
-    "mdp = 4.29 / mu_100['mu'] * np.sqrt(source_counts + background_counts) / source_counts"
+    "### Polarization fit in spacecraft coordinates"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "2ffedf1b",
+   "id": "971c406a",
    "metadata": {},
    "source": [
-    "Fit the polarization fraction and angle of the GRB"
+    "For short duration sources, such as this short GRB, the spacecraft does not move much, allowing the fit to also be done in spacecraft coordinates. This cell determines the spacecraft attitude at the beginning of the GRB and transform the source position to the spacecraft frame. Then, the polarization object is generated with the convention for the fit specified as the same convention used to generate the detector response, which is RelativeZ in this case. The ASADs are now generated in the spacecraft frame, instead of the ICRS frame as they were above.\n"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
-   "id": "2f180dd5",
+   "execution_count": null,
+   "id": "8e852aae",
    "metadata": {},
    "outputs": [
     {
-     "name": "stdout",
+     "name": "stderr",
      "output_type": "stream",
      "text": [
-      "Best fit polarization fraction: 0.88 +/- 0.183\n",
-      "Best fit polarization angle: 80.116 +/- 5.942\n",
-      "MDP: 0.451 \n",
-      "\n"
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n"
      ]
     }
    ],
    "source": [
-    "polarization = grb_polarization.fit(mu_100, asad_corrected['counts'], bounds=([0, 0, 0], [np.inf,np.inf,np.pi]), sigma=asad_corrected['uncertainties'])\n",
+    "attitude = sc_orientation.get_attitude()[0]\n",
+    "source_direction_local = source_direction.transform_to(SpacecraftFrame(attitude=attitude))\n",
     "\n",
-    "if mdp > polarization['fraction']:\n",
-    "    print('Polarization fraction is below MDP!', 'MDP:', round(mdp, 3))\n",
-    "else:\n",
-    "    print('MDP:', round(mdp, 3))"
+    "grb_polarization_local = PolarizationASAD(source_direction_local, spectrum, asad_bin_edges, data, background, sc_orientation, response_file, response_convention='RelativeZ', show_plots=True, fit_convention=MEGAlibRelativeZ(attitude=attitude))"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "f7f553e1",
+   "id": "66e73ecb",
    "metadata": {},
    "source": [
-    "Plot the corrected ASAD for the GRB with the best fit sinusoidal function"
+    "Perform the fit in spacecraft coordinates."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
-   "id": "c1f14711",
+   "execution_count": null,
+   "id": "b57eb337",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -883,20 +513,24 @@
     }
    ],
    "source": [
-    "grb_polarization.plot_asad(asad_corrected['counts'], asad_corrected['uncertainties'], 'Corrected ' + titles['grb'], coefficients=polarization['best fit parameter values'])"
+    "polarization_local_fit = grb_polarization_local.fit(show_plots=True)\n",
+    "\n",
+    "print('Best fit polarization fraction:', round(polarization_local_fit['fraction'], 3), '+/-', round(polarization_local_fit['fraction uncertainty'], 3))\n",
+    "print('Minimum detectable polarization:', round(grb_polarization_local._mdp, 3))\n",
+    "print('Best fit polarization angle (IAU convention):', round(polarization_local_fit['angle'].angle.degree, 3), '+/-', round(polarization_local_fit['angle uncertainty'].degree, 3))"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "57a5362a",
+   "id": "a98dc0bf",
    "metadata": {},
    "source": [
-    "Transform polarization angle to different conventions"
+    "The fitted polarization angle is always output in the IAU convention, but can easily be transformed to other conventions."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": null,
    "id": "7e456b61",
    "metadata": {},
    "outputs": [
@@ -904,32 +538,24 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "RelativeX: 107.101 degrees\n",
-      "RelativeY: 17.101 degrees\n",
-      "RelativeZ: 107.101 degrees\n",
-      "IAU: 80.116 degrees\n"
+      "RelativeX: 77.182 degrees\n",
+      "RelativeY: 167.182 degrees\n",
+      "RelativeZ: 77.182 degrees\n",
+      "IAU: 87.183 degrees\n"
      ]
     }
    ],
    "source": [
-    "print('RelativeX:', round(polarization['angle'].transform_to(MEGAlibRelativeX(attitude=attitude)).angle.degree, 3), 'degrees')\n",
-    "print('RelativeY:', round(polarization['angle'].transform_to(MEGAlibRelativeY(attitude=attitude)).angle.degree, 3), 'degrees')\n",
-    "print('RelativeZ:', round(polarization['angle'].transform_to(MEGAlibRelativeZ(attitude=attitude)).angle.degree, 3), 'degrees')\n",
-    "print('IAU:', round(polarization['angle'].transform_to(IAUPolarizationConvention()).angle.degree, 3), 'degrees')"
+    "print('RelativeX:', round(polarization_local_fit['angle'].transform_to(MEGAlibRelativeX(attitude=attitude)).angle.degree, 3), 'degrees')\n",
+    "print('RelativeY:', round(polarization_local_fit['angle'].transform_to(MEGAlibRelativeY(attitude=attitude)).angle.degree, 3), 'degrees')\n",
+    "print('RelativeZ:', round(polarization_local_fit['angle'].transform_to(MEGAlibRelativeZ(attitude=attitude)).angle.degree, 3), 'degrees')\n",
+    "print('IAU:', round(polarization_local_fit['angle'].transform_to(IAUPolarizationConvention()).angle.degree, 3), 'degrees')"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "ee9644fb",
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "cosipy-fork",
    "language": "python",
    "name": "python3"
   },

From 4df399c92553ba7807a0415e9ab738f6cd8a3f20 Mon Sep 17 00:00:00 2001
From: Eliza Neights <eneights@gmail.com>
Date: Thu, 13 Mar 2025 17:19:28 -0400
Subject: [PATCH 15/31] Fix tutorial notebook

---
 docs/tutorials/polarization/ASAD_method.ipynb | 201 +++++++++++++++++-
 1 file changed, 193 insertions(+), 8 deletions(-)

diff --git a/docs/tutorials/polarization/ASAD_method.ipynb b/docs/tutorials/polarization/ASAD_method.ipynb
index 42fecb49..8d855740 100644
--- a/docs/tutorials/polarization/ASAD_method.ipynb
+++ b/docs/tutorials/polarization/ASAD_method.ipynb
@@ -462,7 +462,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 20,
    "id": "8e852aae",
    "metadata": {},
    "outputs": [
@@ -470,6 +470,12 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
       "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
       "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
       "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
@@ -478,6 +484,176 @@
       "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
       "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n"
      ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 640x480 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
     }
    ],
    "source": [
@@ -497,19 +673,28 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 21,
    "id": "b57eb337",
    "metadata": {},
    "outputs": [
     {
      "data": {
-      "image/png": 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",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
      },
      "metadata": {},
      "output_type": "display_data"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Best fit polarization fraction: 0.91 +/- 0.07\n",
+      "Minimum detectable polarization: 0.181\n",
+      "Best fit polarization angle (IAU convention): 87.222 +/- 2.107\n"
+     ]
     }
    ],
    "source": [
@@ -530,7 +715,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 22,
    "id": "7e456b61",
    "metadata": {},
    "outputs": [
@@ -538,10 +723,10 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "RelativeX: 77.182 degrees\n",
-      "RelativeY: 167.182 degrees\n",
-      "RelativeZ: 77.182 degrees\n",
-      "IAU: 87.183 degrees\n"
+      "RelativeX: 77.219 degrees\n",
+      "RelativeY: 167.218 degrees\n",
+      "RelativeZ: 77.211 degrees\n",
+      "IAU: 87.222 degrees\n"
      ]
     }
    ],

From bac0abc4e4a6d39dfd1dd3197635f84862ad821d Mon Sep 17 00:00:00 2001
From: Eliza Neights <eneights@gmail.com>
Date: Fri, 14 Mar 2025 22:05:09 -0400
Subject: [PATCH 16/31] Update spacecraft coordinate unit test

---
 tests/polarization/test_polarization_asad.py | 138 ++-----------------
 1 file changed, 10 insertions(+), 128 deletions(-)

diff --git a/tests/polarization/test_polarization_asad.py b/tests/polarization/test_polarization_asad.py
index a946894f..9bfb30be 100644
--- a/tests/polarization/test_polarization_asad.py
+++ b/tests/polarization/test_polarization_asad.py
@@ -3,8 +3,8 @@
 from astropy import units as u
 from scoords import SpacecraftFrame
 
-from cosipy.polarization import PolarizationASAD, calculate_uncertainties
-from cosipy.polarization.conventions import IAUPolarizationConvention
+from cosipy.polarization import PolarizationASAD
+from cosipy.polarization.conventions import IAUPolarizationConvention, MEGAlibRelativeZ
 from cosipy.spacecraftfile import SpacecraftFile
 from cosipy import UnBinnedData
 from cosipy.threeml.custom_functions import Band_Eflux
@@ -12,7 +12,7 @@
 
 analysis = UnBinnedData(test_data.path / 'polarization_data.yaml')
 data = analysis.get_dict_from_hdf5(test_data.path / 'polarization_data.hdf5')
-response_path = test_data.path / 'test_polarization_response.h5'
+response_path = test_data.path / 'test_polarization_response_dense.h5'
 sc_orientation = SpacecraftFile.parse_from_file(test_data.path / 'polarization_ori.ori')
 attitude = sc_orientation.get_attitude()[0]
 
@@ -34,135 +34,17 @@
 spectrum.K.unit = K.unit
 
 source_direction = SkyCoord(0, 70, representation_type='spherical', frame=SpacecraftFrame(attitude=attitude), unit=u.deg)
-    
-polarization = PolarizationASAD(source_direction, spectrum, response_path, sc_orientation)
 
 bin_edges = Angle(np.linspace(-np.pi, np.pi, 10), unit=u.rad)
 
-def test_calculate_uncertainties():
+background = {'Psi local': [0, 0], 'Chi local': [0, 0], 'Psi galactic': [0, 0], 'Chi galactic': [0, 0], 'Energies': [300., 300.], 'TimeTags': [1., 2.]}
 
-    assert np.allclose(calculate_uncertainties([1, 2, 3, 5, 10, 50, 100, 1000, 1e4, 1e5]), 
-                        np.array([[0.82724622, 1.29181456, 1.63270469, 2.15969114, 3.16227766, 7.07106781, 10., 31.6227766, 100., 316.22776602], 
-                                  [2.29952656, 2.63785962, 2.91818583, 3.38247265, 3.16227766, 7.07106781, 10., 31.6227766, 100., 316.22776602]]))
-    
-def test_convolve_spectrum():
+def test_spacecraft_fit():
 
-    assert 'Pol' in polarization._expectation.axes.labels
+    polarization_spacecraft = PolarizationASAD(source_direction, spectrum, bin_edges, data, background, sc_orientation, response_path, response_convention='RelativeZ', show_plots=True, fit_convention=MEGAlibRelativeZ(attitude=attitude))
 
-    assert np.allclose(polarization._expectation.project('Em').contents[0], 7657.331992884072, atol=5.0)
+    polarization_fit_spacecraft = polarization_spacecraft.fit(show_plots=True)
 
-    assert np.allclose([polarization._azimuthal_angle_bins[5].rad, polarization._azimuthal_angle_bins[12].rad, 
-                        polarization._azimuthal_angle_bins[25].rad, polarization._azimuthal_angle_bins[40].rad], 
-                       [-3.083541411881164, -1.5707963267948966, 0.371190531909648, 0.9731904991340073])
-
-def test_calculate_azimuthal_scattering_angle():
-
-    assert np.allclose([polarization.calculate_azimuthal_scattering_angle(0, 0).rad, polarization.calculate_azimuthal_scattering_angle(np.pi/5, 0).rad,
-                        polarization.calculate_azimuthal_scattering_angle(np.pi/2, -np.pi/7).rad, polarization.calculate_azimuthal_scattering_angle(np.pi/3, 3*np.pi/2).rad],
-                        [1.5707963267948966, -1.5707963267948966, -1.097213841102146, 0.1949572818104049])
-    
-def test_polarization_asad_init():
-
-    source_direction_galactic = SkyCoord(0, 0, representation_type='spherical', frame='galactic', attitude=attitude, unit=u.deg)
-    polarization_iau = PolarizationASAD(source_direction_galactic, spectrum, response_path, sc_orientation, fit_convention=IAUPolarizationConvention())
-    
-def test_polarization_fit():
-
-    azimuthal_angles = polarization.calculate_azimuthal_scattering_angles(data)
-
-    assert np.allclose([azimuthal_angles[150].rad, azimuthal_angles[3275].rad, azimuthal_angles[5780].rad, azimuthal_angles[7050].rad], 
-                       [-0.14553958772561387, 2.848889133943549, -2.2494887481804238, 1.2037585274409062])
-
-    asad = polarization.create_asad(azimuthal_angles, bin_edges)
-
-    assert np.allclose([asad['counts'][0], asad['counts'][3], asad['counts'][6], asad['counts'][8]], [1114, 727, 587, 883])
-    
-    assert np.allclose([asad['uncertainties'][0][0], asad['uncertainties'][1][3], 
-                        asad['uncertainties'][0][6], asad['uncertainties'][1][8]], 
-                       [33.37663853655727, 26.962937525425527, 24.228082879171435, 29.715315916207253])
-    
-    asad_int_bins = polarization.create_asad(azimuthal_angles, 10)
-
-    assert np.allclose([asad_int_bins['counts'][0], asad_int_bins['counts'][3], asad_int_bins['counts'][6], asad_int_bins['counts'][8]], [1114, 727, 587, 883])
-    
-    assert np.allclose([asad_int_bins['uncertainties'][0][0], asad_int_bins['uncertainties'][1][3], 
-                        asad_int_bins['uncertainties'][0][6], asad_int_bins['uncertainties'][1][8]], 
-                       [33.37663853655727, 26.962937525425527, 24.228082879171435, 29.715315916207253])
-
-    asad_unpolarized = polarization.create_unpolarized_asad()
-
-    assert np.allclose([asad_unpolarized['counts'][0], asad_unpolarized['counts'][3], asad_unpolarized['counts'][6], asad_unpolarized['counts'][8]], 
-                       [932.4137328357068, 906.8283258620892, 794.565967927462, 999.309350107182])
-    
-    assert np.allclose([asad_unpolarized['uncertainties'][0][0], asad_unpolarized['uncertainties'][1][3], 
-                       asad_unpolarized['uncertainties'][0][6], asad_unpolarized['uncertainties'][1][8]], 
-                       [30.53545042791586, 30.11359038477626, 28.188046543303813, 31.61185458189984])
-    
-    asad_unpolarized_int_bins = polarization.create_unpolarized_asad(bins=10)
-
-    assert np.allclose([asad_unpolarized_int_bins['counts'][0], asad_unpolarized_int_bins['counts'][3], 
-                        asad_unpolarized_int_bins['counts'][6], asad_unpolarized_int_bins['counts'][8]], 
-                       [932.4137328357068, 906.8283258620892, 794.565967927462, 999.309350107182])
-    
-    assert np.allclose([asad_unpolarized_int_bins['uncertainties'][0][0], asad_unpolarized_int_bins['uncertainties'][1][3], 
-                       asad_unpolarized_int_bins['uncertainties'][0][6], asad_unpolarized_int_bins['uncertainties'][1][8]], 
-                       [30.53545042791586, 30.11359038477626, 28.188046543303813, 31.61185458189984])
-    
-    asad_unpolarized_bin_list = polarization.create_unpolarized_asad(bins=bin_edges)
-
-    assert np.allclose([asad_unpolarized_bin_list['counts'][0], asad_unpolarized_bin_list['counts'][3], 
-                        asad_unpolarized_bin_list['counts'][6], asad_unpolarized_bin_list['counts'][8]], 
-                       [932.4137328357068, 906.8283258620892, 794.565967927462, 999.309350107182])
-    
-    assert np.allclose([asad_unpolarized_bin_list['uncertainties'][0][0], asad_unpolarized_bin_list['uncertainties'][1][3], 
-                       asad_unpolarized_bin_list['uncertainties'][0][6], asad_unpolarized_bin_list['uncertainties'][1][8]], 
-                       [30.53545042791586, 30.11359038477626, 28.188046543303813, 31.61185458189984])
-    
-    asad_polarized = polarization.create_polarized_asads()
-    
-    assert np.allclose([asad_polarized['counts'][0][0], asad_polarized['counts'][1][3], asad_polarized['counts'][2][6], asad_polarized['counts'][3][8]], 
-                       [229.70809288956985, 231.350661957243, 197.93859480541153, 243.6223882118957])
-    
-    assert np.allclose([asad_polarized['uncertainties'][0][0][0], asad_polarized['uncertainties'][1][1][3], 
-                        asad_polarized['uncertainties'][2][0][6], asad_polarized['uncertainties'][3][1][8]], 
-                       [15.1561239401626, 15.210215710411308, 14.069065171695366, 15.608407612946802])
-    
-    asad_polarized_int_bins = polarization.create_polarized_asads(bins=10)
-    
-    assert np.allclose([asad_polarized_int_bins['counts'][0][0], asad_polarized_int_bins['counts'][1][3], 
-                        asad_polarized_int_bins['counts'][2][6], asad_polarized_int_bins['counts'][3][8]], 
-                       [229.70809288956985, 231.350661957243, 197.93859480541153, 243.6223882118957])
-    
-    assert np.allclose([asad_polarized_int_bins['uncertainties'][0][0][0], asad_polarized_int_bins['uncertainties'][1][1][3], 
-                        asad_polarized_int_bins['uncertainties'][2][0][6], asad_polarized_int_bins['uncertainties'][3][1][8]], 
-                       [15.1561239401626, 15.210215710411308, 14.069065171695366, 15.608407612946802])
-    
-    asad_polarized_bin_list = polarization.create_polarized_asads(bins=bin_edges)
-    
-    assert np.allclose([asad_polarized_bin_list['counts'][0][0], asad_polarized_bin_list['counts'][1][3], 
-                        asad_polarized_bin_list['counts'][2][6], asad_polarized_bin_list['counts'][3][8]], 
-                       [229.70809288956985, 231.350661957243, 197.93859480541153, 243.6223882118957])
-    
-    assert np.allclose([asad_polarized_bin_list['uncertainties'][0][0][0], asad_polarized_bin_list['uncertainties'][1][1][3], 
-                        asad_polarized_bin_list['uncertainties'][2][0][6], asad_polarized_bin_list['uncertainties'][3][1][8]], 
-                       [15.1561239401626, 15.210215710411308, 14.069065171695366, 15.608407612946802])
-
-    mu_100 = polarization.calculate_mu100(asad_polarized, asad_unpolarized)
-
-    assert np.allclose([mu_100['mu'], mu_100['uncertainty']], 
-                       [0.02068036893603115, 9.3940548992881e-07], atol=[0.01, 1e-7])
-    
-    asad_corrected = polarization.correct_asad(asad, asad_unpolarized)
-
-    assert np.allclose([asad_corrected['counts'][0], asad_corrected['counts'][3], asad_corrected['counts'][6], asad_corrected['counts'][8]], 
-                       [1.230972371153726, 0.826002019945234, 0.7611669401887197, 0.9104005858437615])
-    
-    assert np.allclose([asad_corrected['uncertainties'][0][0], asad_corrected['uncertainties'][1][3], 
-                        asad_corrected['uncertainties'][0][6], asad_corrected['uncertainties'][1][8]], 
-                       [0.05463841596540586, 0.04112013917034527, 0.04142682980425702, 0.04204822825061025])
-    
-    polarization_fit = polarization.fit(mu_100, asad_corrected['counts'], bounds=([0, 0, 0], [np.inf,np.inf,np.pi]), sigma=asad_corrected['uncertainties'])
-
-    assert np.allclose([polarization_fit['fraction'], polarization_fit['fraction uncertainty'], 
-                        polarization_fit['angle'].angle.rad, polarization_fit['angle uncertainty'].rad], 
-                       [15.270059610935844, 2.3931615504423474, 1.53994098472832, 0.07217196641713962], atol=[1.0, 0.5, 1.0, 0.1])
+    assert np.allclose([polarization_fit_spacecraft['fraction'], polarization_fit_spacecraft['fraction uncertainty'], 
+                        polarization_fit_spacecraft['angle'].angle.rad, polarization_fit_spacecraft['angle uncertainty'].rad],
+                        [13.73038868282377, 2.1295224814008353, 1.4851296518928818, 0.07562763316088744], atol=[1.0, 0.5, 1.0, 0.1])

From c3669043fdae61df604902be611bf18e5dd082ac Mon Sep 17 00:00:00 2001
From: Eliza Neights <eneights@gmail.com>
Date: Fri, 14 Mar 2025 22:21:17 -0400
Subject: [PATCH 17/31] Add unit test dense response

---
 .../test_polarization_response_dense.h5        | Bin 0 -> 578818 bytes
 1 file changed, 0 insertions(+), 0 deletions(-)
 create mode 100644 cosipy/test_data/test_polarization_response_dense.h5

diff --git a/cosipy/test_data/test_polarization_response_dense.h5 b/cosipy/test_data/test_polarization_response_dense.h5
new file mode 100644
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literal 0
HcmV?d00001


From 84976dfd039c2c6580ae4ab852e0d315c87d1911 Mon Sep 17 00:00:00 2001
From: Eliza Neights <eneights@gmail.com>
Date: Fri, 14 Mar 2025 23:15:29 -0400
Subject: [PATCH 18/31] Fix expectation unit check

---
 cosipy/threeml/COSILike.py | 9 ++++++---
 1 file changed, 6 insertions(+), 3 deletions(-)

diff --git a/cosipy/threeml/COSILike.py b/cosipy/threeml/COSILike.py
index 52ee8f9d..9fe79e84 100644
--- a/cosipy/threeml/COSILike.py
+++ b/cosipy/threeml/COSILike.py
@@ -162,6 +162,9 @@ def set_model(self, model):
             # Save expected counts for source:
             self._expected_counts[name] = copy.deepcopy(total_expectation)
 
+            if not total_expectation.unit == u.dimensionless_unscaled:
+                raise RuntimeError("Expectation should be dimensionless, but has units of " + str(expectation.contents.unit) + ".")
+
             # Need to check if self._signal type is dense (i.e. 'Quantity') or sparse (i.e. 'COO').
             if type(total_expectation.contents) == u.quantity.Quantity:
                 total_expectation = total_expectation.contents.value
@@ -237,6 +240,9 @@ def set_model(self, model):
             
             # Save expected counts for source:
             self._expected_counts[name] = copy.deepcopy(total_expectation)
+
+            if not total_expectation.unit == u.dimensionless_unscaled:
+                raise RuntimeError("Expectation should be dimensionless, but has units of " + str(expectation.contents.unit) + ".")
          
             # Need to check if self._signal type is dense (i.e. 'Quantity') or sparse (i.e. 'COO').
             if type(total_expectation.contents) == u.quantity.Quantity:
@@ -292,9 +298,6 @@ def get_log_like(self):
             logger.warning("Adding 1e-12 to each bin of the expectation to avoid log-likelihood = -inf.")
             self._printed_warning = True
         # This 1e-12 should be defined as a parameter in the near future (HY)
-
-        if not expectation.contents.unit == u.dimensionless_unscaled:
-            raise RuntimeError("Expectation should be dimensionless, but has units of " + str(expectation.contents.unit) + ".")
                          
         # Convert data into an arrary:
         data = self._data.contents

From bcbeec2e3bf9a6c0acef91a0f160702d6984e866 Mon Sep 17 00:00:00 2001
From: Eliza Neights <eneights@gmail.com>
Date: Fri, 14 Mar 2025 23:22:45 -0400
Subject: [PATCH 19/31] Move expectation test to PointSourceResponse

---
 cosipy/response/PointSourceResponse.py | 80 ++++++++++++++++++++------
 1 file changed, 61 insertions(+), 19 deletions(-)

diff --git a/cosipy/response/PointSourceResponse.py b/cosipy/response/PointSourceResponse.py
index 61ae0d6c..c2ad8c05 100644
--- a/cosipy/response/PointSourceResponse.py
+++ b/cosipy/response/PointSourceResponse.py
@@ -47,7 +47,7 @@ def photon_energy_axis(self):
         
         return self.axes['Ei']
        
-    def get_expectation(self, spectrum, polarization_level=None, polarization_angle=None, scatt_map=None, convention=None):
+    def get_expectation(self, spectrum, polarization_level=None, polarization_angle=None, scatt_map=None, convention=None, child_pa_bins=40):
         """
         Convolve the response with a spectral (and optionally, polarization) hypothesis to obtain the expected
         excess counts from the source.
@@ -143,30 +143,69 @@ def get_expectation(self, spectrum, polarization_level=None, polarization_angle=
 
                     response_slice = self.slice[{'Pol':slice(i,i+1)}].project('Ei', 'Em', 'Phi', 'PsiChi')
 
-                    for j, (pixels, exposure) in enumerate(zip(scatt_map.contents.coords.transpose(), scatt_map.contents.data)):
+                    if child_pa_bins is None:
 
-                        attitude = Attitude.from_axes(x=scatt_map.axes['x'].pix2skycoord(pixels[0]), y=scatt_map.axes['y'].pix2skycoord(pixels[1]))
+                        for j, (pixels, exposure) in enumerate(zip(scatt_map.contents.coords.transpose(), scatt_map.contents.data)):
 
-                        if convention == 'RelativeX':
-                            this_convention = MEGAlibRelativeX(attitude=attitude)
-                        elif convention == 'RelativeY':
-                            this_convention = MEGAlibRelativeY(attitude=attitude)
-                        elif convention == 'RelativeZ':
-                            this_convention = MEGAlibRelativeZ(attitude=attitude)
-                        else:
-                            raise RuntimeError("Response convention must be 'RelativeX', 'RelativeY', or 'RelativeZ'")
+                            attitude = Attitude.from_axes(x=scatt_map.axes['x'].pix2skycoord(pixels[0]), y=scatt_map.axes['y'].pix2skycoord(pixels[1]))
 
-                        polarization_angle_galactic = PolarizationAngle(self.axes['Pol'].centers.to_value(u.deg)[i] * u.deg, polarization_angle.skycoord, convention=this_convention).transform_to(polarization_angle.convention)
+                            if convention == 'RelativeX':
+                                this_convention = MEGAlibRelativeX(attitude=attitude)
+                            elif convention == 'RelativeY':
+                                this_convention = MEGAlibRelativeY(attitude=attitude)
+                            elif convention == 'RelativeZ':
+                                this_convention = MEGAlibRelativeZ(attitude=attitude)
+                            else:
+                                raise RuntimeError("Response convention must be 'RelativeX', 'RelativeY', or 'RelativeZ'")
 
-                        if polarization_angle_galactic.angle.deg == 180.:
-                            polarization_angle_galactic = PolarizationAngle(0. * u.deg, polarization_angle_galactic.skycoord, convention=polarization_angle_galactic.convention)
+                            polarization_angle_galactic = PolarizationAngle(self.axes['Pol'].centers.to_value(u.deg)[i] * u.deg, polarization_angle.skycoord, convention=this_convention).transform_to(polarization_angle.convention)
 
-                        polarization_angle_index = np.max(np.where(polarization_angle_galactic.angle.deg >= self.axes['Pol'].edges.to_value(u.deg)))
+                            if polarization_angle_galactic.angle.deg == 180.:
+                                polarization_angle_galactic = PolarizationAngle(0. * u.deg, polarization_angle_galactic.skycoord, convention=polarization_angle_galactic.convention)
 
-                        if hasattr(polarization_angle_components[polarization_angle_index], 'axes'):
-                            polarization_angle_components[polarization_angle_index] += response_slice * exposure / np.sum(scatt_map.project('x'))
-                        else:
-                            polarization_angle_components[polarization_angle_index] = response_slice * exposure / np.sum(scatt_map.project('x'))
+                            polarization_angle_index = np.max(np.where(polarization_angle_galactic.angle.deg >= self.axes['Pol'].edges.to_value(u.deg)))
+
+                            if hasattr(polarization_angle_components[polarization_angle_index], 'axes'):
+                                polarization_angle_components[polarization_angle_index] += response_slice * exposure / np.sum(scatt_map.project('x'))
+                            else:
+                                polarization_angle_components[polarization_angle_index] = response_slice * exposure / np.sum(scatt_map.project('x'))
+
+                    else:
+
+                        pol_edges = self.axes['Pol'].edges[i:i+2]
+
+                        child_pa_bin_size = (pol_edges[1] - pol_edges[0]) / child_pa_bins
+
+                        response_slice = response_slice / child_pa_bins
+
+                        for k in range(child_pa_bins):
+
+                            child_bin_center = pol_edges[0] + ((1 + (2*k)) * child_pa_bin_size / 2)
+
+                            for j, (pixels, exposure) in enumerate(zip(scatt_map.contents.coords.transpose(), scatt_map.contents.data)):
+
+                                attitude = Attitude.from_axes(x=scatt_map.axes['x'].pix2skycoord(pixels[0]), y=scatt_map.axes['y'].pix2skycoord(pixels[1]))
+
+                                if convention == 'RelativeX':
+                                    this_convention = MEGAlibRelativeX(attitude=attitude)
+                                elif convention == 'RelativeY':
+                                    this_convention = MEGAlibRelativeY(attitude=attitude)
+                                elif convention == 'RelativeZ':
+                                    this_convention = MEGAlibRelativeZ(attitude=attitude)
+                                else:
+                                    raise RuntimeError("Response convention must be 'RelativeX', 'RelativeY', or 'RelativeZ'")
+
+                                polarization_angle_galactic = PolarizationAngle(self.axes['Pol'].centers.to_value(u.deg)[i] * u.deg, polarization_angle.skycoord, convention=this_convention).transform_to(polarization_angle.convention)
+
+                                if polarization_angle_galactic.angle.deg == 180.:
+                                    polarization_angle_galactic = PolarizationAngle(0. * u.deg, polarization_angle_galactic.skycoord, convention=polarization_angle_galactic.convention)
+
+                                polarization_angle_index = np.max(np.where(polarization_angle_galactic.angle.deg >= self.axes['Pol'].edges.to_value(u.deg)))
+
+                                if hasattr(polarization_angle_components[polarization_angle_index], 'axes'):
+                                    polarization_angle_components[polarization_angle_index] += response_slice * exposure / np.sum(scatt_map.project('x'))
+                                else:
+                                    polarization_angle_components[polarization_angle_index] = response_slice * exposure / np.sum(scatt_map.project('x'))
 
                 for i in range(self.axes['Pol'].nbins):
 
@@ -208,4 +247,7 @@ def get_expectation(self, spectrum, polarization_level=None, polarization_angle=
 
         hist = Histogram(axes, contents=expectation)
 
+        if not hist.unit == u.dimensionless_unscaled:
+            raise RuntimeError("Expectation should be dimensionless, but has units of " + str(hist.unit) + ".")
+
         return hist

From 45ef074cdf27f76a59daf86e369593270c0978c9 Mon Sep 17 00:00:00 2001
From: Eliza Neights <eneights@gmail.com>
Date: Fri, 14 Mar 2025 23:23:56 -0400
Subject: [PATCH 20/31] Remove expectation check from COSILike

---
 cosipy/threeml/COSILike.py | 6 ------
 1 file changed, 6 deletions(-)

diff --git a/cosipy/threeml/COSILike.py b/cosipy/threeml/COSILike.py
index 9fe79e84..987b9aab 100644
--- a/cosipy/threeml/COSILike.py
+++ b/cosipy/threeml/COSILike.py
@@ -162,9 +162,6 @@ def set_model(self, model):
             # Save expected counts for source:
             self._expected_counts[name] = copy.deepcopy(total_expectation)
 
-            if not total_expectation.unit == u.dimensionless_unscaled:
-                raise RuntimeError("Expectation should be dimensionless, but has units of " + str(expectation.contents.unit) + ".")
-
             # Need to check if self._signal type is dense (i.e. 'Quantity') or sparse (i.e. 'COO').
             if type(total_expectation.contents) == u.quantity.Quantity:
                 total_expectation = total_expectation.contents.value
@@ -240,9 +237,6 @@ def set_model(self, model):
             
             # Save expected counts for source:
             self._expected_counts[name] = copy.deepcopy(total_expectation)
-
-            if not total_expectation.unit == u.dimensionless_unscaled:
-                raise RuntimeError("Expectation should be dimensionless, but has units of " + str(expectation.contents.unit) + ".")
          
             # Need to check if self._signal type is dense (i.e. 'Quantity') or sparse (i.e. 'COO').
             if type(total_expectation.contents) == u.quantity.Quantity:

From 47c9f628898f067177516b85c090ba5672803d31 Mon Sep 17 00:00:00 2001
From: Eliza Neights <eneights@gmail.com>
Date: Fri, 14 Mar 2025 23:25:48 -0400
Subject: [PATCH 21/31] Undo change to COSILike

---
 cosipy/threeml/COSILike.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/cosipy/threeml/COSILike.py b/cosipy/threeml/COSILike.py
index 987b9aab..da3a508e 100644
--- a/cosipy/threeml/COSILike.py
+++ b/cosipy/threeml/COSILike.py
@@ -292,7 +292,7 @@ def get_log_like(self):
             logger.warning("Adding 1e-12 to each bin of the expectation to avoid log-likelihood = -inf.")
             self._printed_warning = True
         # This 1e-12 should be defined as a parameter in the near future (HY)
-                         
+        
         # Convert data into an arrary:
         data = self._data.contents
         

From faf3be4732effc15de175d9fdc7e0813555bc8bb Mon Sep 17 00:00:00 2001
From: Eliza Neights <eneights@gmail.com>
Date: Fri, 14 Mar 2025 23:30:04 -0400
Subject: [PATCH 22/31] Add option to split PA bins into child bins when
 calculating ICRS frame polarization expectation

---
 cosipy/response/PointSourceResponse.py | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/cosipy/response/PointSourceResponse.py b/cosipy/response/PointSourceResponse.py
index c2ad8c05..0aee6041 100644
--- a/cosipy/response/PointSourceResponse.py
+++ b/cosipy/response/PointSourceResponse.py
@@ -47,7 +47,7 @@ def photon_energy_axis(self):
         
         return self.axes['Ei']
        
-    def get_expectation(self, spectrum, polarization_level=None, polarization_angle=None, scatt_map=None, convention=None, child_pa_bins=40):
+    def get_expectation(self, spectrum, polarization_level=None, polarization_angle=None, scatt_map=None, convention=None, child_pa_bins=None):
         """
         Convolve the response with a spectral (and optionally, polarization) hypothesis to obtain the expected
         excess counts from the source.
@@ -64,7 +64,9 @@ def get_expectation(self, spectrum, polarization_level=None, polarization_angle=
             Spacecraft attitude map. Only needed for polarization angle provided in galactic reference frame.
         convention : str, optional
             Polarization angle convention of response ('RelativeX', 'RelativeY', or 'RelativeZ'). Only needed for polarization angle provided in galactic reference frame.
-
+        child_pa_bins : int, optional
+            Number of child bins to convert spacecraft frame polarization angle bins into before transforming to ICRS frame
+        
         Returns
         -------
         :py:class:`histpy.Histogram`

From f97bba3867cc19a172a06d30681ae61d72772d91 Mon Sep 17 00:00:00 2001
From: Eliza Neights <eneights@gmail.com>
Date: Sat, 15 Mar 2025 01:28:39 -0400
Subject: [PATCH 23/31] Fix child bin PA

---
 cosipy/response/PointSourceResponse.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/cosipy/response/PointSourceResponse.py b/cosipy/response/PointSourceResponse.py
index 0aee6041..e6175836 100644
--- a/cosipy/response/PointSourceResponse.py
+++ b/cosipy/response/PointSourceResponse.py
@@ -47,7 +47,7 @@ def photon_energy_axis(self):
         
         return self.axes['Ei']
        
-    def get_expectation(self, spectrum, polarization_level=None, polarization_angle=None, scatt_map=None, convention=None, child_pa_bins=None):
+    def get_expectation(self, spectrum, polarization_level=None, polarization_angle=None, scatt_map=None, convention=None, child_pa_bins=40):
         """
         Convolve the response with a spectral (and optionally, polarization) hypothesis to obtain the expected
         excess counts from the source.
@@ -197,7 +197,7 @@ def get_expectation(self, spectrum, polarization_level=None, polarization_angle=
                                 else:
                                     raise RuntimeError("Response convention must be 'RelativeX', 'RelativeY', or 'RelativeZ'")
 
-                                polarization_angle_galactic = PolarizationAngle(self.axes['Pol'].centers.to_value(u.deg)[i] * u.deg, polarization_angle.skycoord, convention=this_convention).transform_to(polarization_angle.convention)
+                                polarization_angle_galactic = PolarizationAngle(child_bin_center.to_value(u.deg) * u.deg, polarization_angle.skycoord, convention=this_convention).transform_to(polarization_angle.convention)
 
                                 if polarization_angle_galactic.angle.deg == 180.:
                                     polarization_angle_galactic = PolarizationAngle(0. * u.deg, polarization_angle_galactic.skycoord, convention=polarization_angle_galactic.convention)

From 1fd17ac101680d079fa84412065e7b7332a19ad5 Mon Sep 17 00:00:00 2001
From: Eliza Neights <eneights@gmail.com>
Date: Sat, 15 Mar 2025 01:29:02 -0400
Subject: [PATCH 24/31] Fix default child_pa_bins

---
 cosipy/response/PointSourceResponse.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/cosipy/response/PointSourceResponse.py b/cosipy/response/PointSourceResponse.py
index e6175836..7cb2f788 100644
--- a/cosipy/response/PointSourceResponse.py
+++ b/cosipy/response/PointSourceResponse.py
@@ -47,7 +47,7 @@ def photon_energy_axis(self):
         
         return self.axes['Ei']
        
-    def get_expectation(self, spectrum, polarization_level=None, polarization_angle=None, scatt_map=None, convention=None, child_pa_bins=40):
+    def get_expectation(self, spectrum, polarization_level=None, polarization_angle=None, scatt_map=None, convention=None, child_pa_bins=None):
         """
         Convolve the response with a spectral (and optionally, polarization) hypothesis to obtain the expected
         excess counts from the source.

From b9cd566876049c89bac4f68d18fcbe162dd3eb4e Mon Sep 17 00:00:00 2001
From: Eliza Neights <eneights@gmail.com>
Date: Mon, 17 Mar 2025 11:58:28 -0400
Subject: [PATCH 25/31] Remove child pa bins

---
 cosipy/response/PointSourceResponse.py | 79 +++++++-------------------
 1 file changed, 19 insertions(+), 60 deletions(-)

diff --git a/cosipy/response/PointSourceResponse.py b/cosipy/response/PointSourceResponse.py
index 7cb2f788..f32a83dd 100644
--- a/cosipy/response/PointSourceResponse.py
+++ b/cosipy/response/PointSourceResponse.py
@@ -47,7 +47,7 @@ def photon_energy_axis(self):
         
         return self.axes['Ei']
        
-    def get_expectation(self, spectrum, polarization_level=None, polarization_angle=None, scatt_map=None, convention=None, child_pa_bins=None):
+    def get_expectation(self, spectrum, polarization_level=None, polarization_angle=None, scatt_map=None, convention=None):
         """
         Convolve the response with a spectral (and optionally, polarization) hypothesis to obtain the expected
         excess counts from the source.
@@ -64,8 +64,6 @@ def get_expectation(self, spectrum, polarization_level=None, polarization_angle=
             Spacecraft attitude map. Only needed for polarization angle provided in galactic reference frame.
         convention : str, optional
             Polarization angle convention of response ('RelativeX', 'RelativeY', or 'RelativeZ'). Only needed for polarization angle provided in galactic reference frame.
-        child_pa_bins : int, optional
-            Number of child bins to convert spacecraft frame polarization angle bins into before transforming to ICRS frame
         
         Returns
         -------
@@ -145,69 +143,30 @@ def get_expectation(self, spectrum, polarization_level=None, polarization_angle=
 
                     response_slice = self.slice[{'Pol':slice(i,i+1)}].project('Ei', 'Em', 'Phi', 'PsiChi')
 
-                    if child_pa_bins is None:
+                    for j, (pixels, exposure) in enumerate(zip(scatt_map.contents.coords.transpose(), scatt_map.contents.data)):
 
-                        for j, (pixels, exposure) in enumerate(zip(scatt_map.contents.coords.transpose(), scatt_map.contents.data)):
+                        attitude = Attitude.from_axes(x=scatt_map.axes['x'].pix2skycoord(pixels[0]), y=scatt_map.axes['y'].pix2skycoord(pixels[1]))
 
-                            attitude = Attitude.from_axes(x=scatt_map.axes['x'].pix2skycoord(pixels[0]), y=scatt_map.axes['y'].pix2skycoord(pixels[1]))
+                        if convention == 'RelativeX':
+                            this_convention = MEGAlibRelativeX(attitude=attitude)
+                        elif convention == 'RelativeY':
+                            this_convention = MEGAlibRelativeY(attitude=attitude)
+                        elif convention == 'RelativeZ':
+                            this_convention = MEGAlibRelativeZ(attitude=attitude)
+                        else:
+                            raise RuntimeError("Response convention must be 'RelativeX', 'RelativeY', or 'RelativeZ'")
 
-                            if convention == 'RelativeX':
-                                this_convention = MEGAlibRelativeX(attitude=attitude)
-                            elif convention == 'RelativeY':
-                                this_convention = MEGAlibRelativeY(attitude=attitude)
-                            elif convention == 'RelativeZ':
-                                this_convention = MEGAlibRelativeZ(attitude=attitude)
-                            else:
-                                raise RuntimeError("Response convention must be 'RelativeX', 'RelativeY', or 'RelativeZ'")
+                        polarization_angle_galactic = PolarizationAngle(self.axes['Pol'].centers.to_value(u.deg)[i] * u.deg, polarization_angle.skycoord, convention=this_convention).transform_to(polarization_angle.convention)
 
-                            polarization_angle_galactic = PolarizationAngle(self.axes['Pol'].centers.to_value(u.deg)[i] * u.deg, polarization_angle.skycoord, convention=this_convention).transform_to(polarization_angle.convention)
+                        if polarization_angle_galactic.angle.deg == 180.:
+                            polarization_angle_galactic = PolarizationAngle(0. * u.deg, polarization_angle_galactic.skycoord, convention=polarization_angle_galactic.convention)
 
-                            if polarization_angle_galactic.angle.deg == 180.:
-                                polarization_angle_galactic = PolarizationAngle(0. * u.deg, polarization_angle_galactic.skycoord, convention=polarization_angle_galactic.convention)
+                        polarization_angle_index = np.max(np.where(polarization_angle_galactic.angle.deg >= self.axes['Pol'].edges.to_value(u.deg)))
 
-                            polarization_angle_index = np.max(np.where(polarization_angle_galactic.angle.deg >= self.axes['Pol'].edges.to_value(u.deg)))
-
-                            if hasattr(polarization_angle_components[polarization_angle_index], 'axes'):
-                                polarization_angle_components[polarization_angle_index] += response_slice * exposure / np.sum(scatt_map.project('x'))
-                            else:
-                                polarization_angle_components[polarization_angle_index] = response_slice * exposure / np.sum(scatt_map.project('x'))
-
-                    else:
-
-                        pol_edges = self.axes['Pol'].edges[i:i+2]
-
-                        child_pa_bin_size = (pol_edges[1] - pol_edges[0]) / child_pa_bins
-
-                        response_slice = response_slice / child_pa_bins
-
-                        for k in range(child_pa_bins):
-
-                            child_bin_center = pol_edges[0] + ((1 + (2*k)) * child_pa_bin_size / 2)
-
-                            for j, (pixels, exposure) in enumerate(zip(scatt_map.contents.coords.transpose(), scatt_map.contents.data)):
-
-                                attitude = Attitude.from_axes(x=scatt_map.axes['x'].pix2skycoord(pixels[0]), y=scatt_map.axes['y'].pix2skycoord(pixels[1]))
-
-                                if convention == 'RelativeX':
-                                    this_convention = MEGAlibRelativeX(attitude=attitude)
-                                elif convention == 'RelativeY':
-                                    this_convention = MEGAlibRelativeY(attitude=attitude)
-                                elif convention == 'RelativeZ':
-                                    this_convention = MEGAlibRelativeZ(attitude=attitude)
-                                else:
-                                    raise RuntimeError("Response convention must be 'RelativeX', 'RelativeY', or 'RelativeZ'")
-
-                                polarization_angle_galactic = PolarizationAngle(child_bin_center.to_value(u.deg) * u.deg, polarization_angle.skycoord, convention=this_convention).transform_to(polarization_angle.convention)
-
-                                if polarization_angle_galactic.angle.deg == 180.:
-                                    polarization_angle_galactic = PolarizationAngle(0. * u.deg, polarization_angle_galactic.skycoord, convention=polarization_angle_galactic.convention)
-
-                                polarization_angle_index = np.max(np.where(polarization_angle_galactic.angle.deg >= self.axes['Pol'].edges.to_value(u.deg)))
-
-                                if hasattr(polarization_angle_components[polarization_angle_index], 'axes'):
-                                    polarization_angle_components[polarization_angle_index] += response_slice * exposure / np.sum(scatt_map.project('x'))
-                                else:
-                                    polarization_angle_components[polarization_angle_index] = response_slice * exposure / np.sum(scatt_map.project('x'))
+                        if hasattr(polarization_angle_components[polarization_angle_index], 'axes'):
+                            polarization_angle_components[polarization_angle_index] += response_slice * exposure / np.sum(scatt_map.project('x'))
+                        else:
+                            polarization_angle_components[polarization_angle_index] = response_slice * exposure / np.sum(scatt_map.project('x'))
 
                 for i in range(self.axes['Pol'].nbins):
 

From 497dc8e0f4fe1ef66fb921d03b64e8e4314eeb0b Mon Sep 17 00:00:00 2001
From: Eliza Neights <eneights@gmail.com>
Date: Mon, 17 Mar 2025 11:59:01 -0400
Subject: [PATCH 26/31] Fix unit test

---
 cosipy/test_data/polarization_ori.ori        |  4 ++--
 tests/polarization/test_polarization_asad.py | 10 ++++++++++
 2 files changed, 12 insertions(+), 2 deletions(-)

diff --git a/cosipy/test_data/polarization_ori.ori b/cosipy/test_data/polarization_ori.ori
index d7abfd12..8fa0ddff 100644
--- a/cosipy/test_data/polarization_ori.ori
+++ b/cosipy/test_data/polarization_ori.ori
@@ -1,4 +1,4 @@
 Type OrientationsGalactic 
-OG 0.0 73.14907746670937 41.85821768724895 16.85092253329064 221.85821768724895 0.0 0.0 0.0 15.0 
-OG 15.0 73.14907746670937 41.85821768724895 16.85092253329064 221.85821768724895 0.0 0.0 0.0 0.0
+OG 0.0 73.14907746670937 41.85821768724895 16.85092253329064 221.85821768724895 523.6546162516867 29.730094567937144 229.94497777814732 15.0 
+OG 15.0 73.14907746670937 41.85821768724895 16.85092253329064 221.85821768724895 523.6546162516867 29.730094567937144 229.94497777814732 0.0
 EN
diff --git a/tests/polarization/test_polarization_asad.py b/tests/polarization/test_polarization_asad.py
index 9bfb30be..a7a223e1 100644
--- a/tests/polarization/test_polarization_asad.py
+++ b/tests/polarization/test_polarization_asad.py
@@ -48,3 +48,13 @@ def test_spacecraft_fit():
     assert np.allclose([polarization_fit_spacecraft['fraction'], polarization_fit_spacecraft['fraction uncertainty'], 
                         polarization_fit_spacecraft['angle'].angle.rad, polarization_fit_spacecraft['angle uncertainty'].rad],
                         [13.73038868282377, 2.1295224814008353, 1.4851296518928818, 0.07562763316088744], atol=[1.0, 0.5, 1.0, 0.1])
+
+def test_icrs_fit():
+
+    polarization_icrs = PolarizationASAD(source_direction.transform_to('galactic'), spectrum, bin_edges, data, background, sc_orientation, response_path, response_convention='RelativeZ', show_plots=True)
+
+    polarization_fit_icrs = polarization_icrs.fit(show_plots=True)
+
+    assert np.allclose([polarization_fit_icrs['fraction'], polarization_fit_icrs['fraction uncertainty'], 
+                        polarization_fit_icrs['angle'].angle.rad, polarization_fit_icrs['angle uncertainty'].rad],
+                        [2.057120422245168, 0.6877456532374626, 1.4377475471600978, 0.13124860832618374], atol=[1.0, 0.5, 1.0, 0.1])

From 553f37f3a15033856dc9521044d1f8a4b64b1731 Mon Sep 17 00:00:00 2001
From: Eliza Neights <eneights@gmail.com>
Date: Mon, 17 Mar 2025 16:56:36 -0400
Subject: [PATCH 27/31] Allow for fit in spacecraft coordinates with position
 provided in other coordinates

---
 cosipy/polarization/polarization_asad.py | 4 +++-
 1 file changed, 3 insertions(+), 1 deletion(-)

diff --git a/cosipy/polarization/polarization_asad.py b/cosipy/polarization/polarization_asad.py
index f1d55701..4b16cbd1 100644
--- a/cosipy/polarization/polarization_asad.py
+++ b/cosipy/polarization/polarization_asad.py
@@ -45,7 +45,9 @@ class PolarizationASAD():
     def __init__(self, source_vector, source_spectrum, asad_bin_edges, data, background, sc_orientation, response_file, response_convention='RelativeX', fit_convention=IAUPolarizationConvention(), show_plots=False):
 
         if isinstance(fit_convention.frame, SpacecraftFrame) and not isinstance(source_vector.frame, SpacecraftFrame):
-            raise RuntimeError("To perform fit in spacecraft frame, source position must be provided in spacecraft frame.")
+            attitude = sc_orientation.get_attitude()[0]
+            source_vector = source_vector.transform_to(SpacecraftFrame(attitude=attitude))
+            logger.warning('The source direction is being converted to the spacecraft frame using the attitude at the first timestamp of the orientation.')
         elif not isinstance(fit_convention.frame, SpacecraftFrame):
             source_vector = source_vector.transform_to('icrs')
 

From 42614f4cf23fd695d6da5a55eae32928086ea4e1 Mon Sep 17 00:00:00 2001
From: Eliza Neights <eneights@gmail.com>
Date: Tue, 18 Mar 2025 11:05:15 -0400
Subject: [PATCH 28/31] Update ori file explannation in notebook

---
 docs/tutorials/polarization/ASAD_method.ipynb | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/tutorials/polarization/ASAD_method.ipynb b/docs/tutorials/polarization/ASAD_method.ipynb
index 8d855740..22d4bc63 100644
--- a/docs/tutorials/polarization/ASAD_method.ipynb
+++ b/docs/tutorials/polarization/ASAD_method.ipynb
@@ -144,7 +144,7 @@
    "id": "b983b194",
    "metadata": {},
    "source": [
-    "Define the path to the detector response and read in the orientation file."
+    "Define the path to the detector response and read in the orientation file. The orientation is cut down to the time interval of the source."
    ]
   },
   {

From 5ba201c19bc4a3d06d395404a6e39bb27f71e353 Mon Sep 17 00:00:00 2001
From: Eliza Neights <eneights@gmail.com>
Date: Tue, 18 Mar 2025 15:45:25 -0400
Subject: [PATCH 29/31] Add polarization fit

---
 cosipy/threeml/COSILike.py | 60 ++++++++++++++++++++++++++++++++++----
 1 file changed, 55 insertions(+), 5 deletions(-)

diff --git a/cosipy/threeml/COSILike.py b/cosipy/threeml/COSILike.py
index da3a508e..9ff367af 100644
--- a/cosipy/threeml/COSILike.py
+++ b/cosipy/threeml/COSILike.py
@@ -7,6 +7,8 @@
 from cosipy.response.FullDetectorResponse import FullDetectorResponse
 from cosipy.response.ExtendedSourceResponse import ExtendedSourceResponse
 from cosipy.image_deconvolution import AllSkyImageModel
+from cosipy.polarization.polarization_angle import PolarizationAngle
+from cosipy.polarization.conventions import IAUPolarizationConvention, MEGAlibRelativeX, MEGAlibRelativeY, MEGAlibRelativeZ
 
 from scoords import SpacecraftFrame, Attitude
 
@@ -63,9 +65,11 @@ class COSILike(PluginPrototype):
         Full path to precomputed point source response in Galactic coordinates
     earth_occ : bool, optional
         Option to include Earth occultation in fit (default is True).
+    response_pa_convention : str, optional
+        Polarization reference convention of response ('RelativeX', 'RelativeY', or 'RelativeZ'). Required if response contains polarization angle axis
     """
     def __init__(self, name, dr, data, bkg, sc_orientation, 
-                 nuisance_param=None, coordsys=None, precomputed_psr_file=None, earth_occ=True, **kwargs):
+                 nuisance_param=None, coordsys=None, precomputed_psr_file=None, earth_occ=True, response_pa_convention=None, **kwargs):
         
         # create the hash for the nuisance parameters. We have none for now.
         self._nuisance_parameters = collections.OrderedDict()
@@ -121,6 +125,22 @@ def __init__(self, name, dr, data, bkg, sc_orientation,
             logger.info("... loading the pre-computed image response ...")
             self.image_response = ExtendedSourceResponse.open(self.precomputed_psr_file)
             logger.info("--> done")
+
+        if 'Pol' in self._dr.axes.labels:
+            self._response_pa_convention = response_pa_convention
+            if self._coordsys == 'spacecraftframe':
+                if self._response_pa_convention == 'RelativeX':
+                    self._pa_convention = MEGAlibRelativeX(attitude=self._sc_orientation.get_attitude()[0])
+                elif self._response_pa_convention == 'RelativeY':
+                    self._pa_convention = MEGAlibRelativeY(attitude=self._sc_orientation.get_attitude()[0])
+                elif self._response_pa_convention == 'RelativeZ':
+                    self._pa_convention = MEGAlibRelativeZ(attitude=self._sc_orientation.get_attitude()[0])
+                else:
+                    raise RuntimeError("Response convention must be 'RelativeX', 'RelativeY', or 'RelativeZ'")
+            elif self._coordsys == 'galactic':
+                self._pa_convention = IAUPolarizationConvention()
+            else:
+                raise RuntimeError("Unknown coordinate system")
         
     def set_model(self, model):
         """
@@ -219,7 +239,7 @@ def set_model(self, model):
                     dwell_time_map = self._get_dwell_time_map(coord)
                     self._psr[name] = self._dr.get_point_source_response(exposure_map=dwell_time_map)
                 elif self._coordsys == 'galactic':
-                    scatt_map = self._get_scatt_map()
+                    scatt_map = self._get_scatt_map(coord)
                     self._psr[name] = self._dr.get_point_source_response(coord=coord, scatt_map=scatt_map)
                 else:
                     raise RuntimeError("Unknown coordinate system")
@@ -231,10 +251,40 @@ def set_model(self, model):
 
             # Convolve with spectrum
             # See also the Detector Response and Source Injector tutorials
-            spectrum = source.spectrum.main.shape
 
-            total_expectation = self._psr[name].get_expectation(spectrum)
-            
+            if hasattr(source.spectrum, 'main'):
+
+                spectrum = source.spectrum.main.shape
+                total_expectation = self._psr[name].get_expectation(spectrum)
+
+            else:
+
+                component_counter = 0
+
+                for item in source.spectrum.to_dict():
+
+                    spectrum = getattr(source.spectrum, item).shape
+
+                    if not 'Pol' in self._dr.axes.labels:
+                        this_expectation = self._psr[name].get_expectation(spectrum)
+                    else:
+                        polarization_level = source.components['grb'].polarization.degree.value / 100.
+                        polarization_angle = PolarizationAngle(coords.Angle(source.components['grb'].polarization.angle.value, unit=u.deg), source.position.sky_coord, convention=self._pa_convention)
+                        if self._coordsys == 'spacecraftframe':
+                            this_expectation = self._psr[name].get_expectation(spectrum, polarization_level, polarization_angle)
+                        elif self._coordsys == 'galactic':
+                            scatt_map = self._get_scatt_map(source.position.sky_coord)
+                            this_expectation = self._psr[name].get_expectation(spectrum, polarization_level, polarization_angle, scatt_map, self._response_pa_convention)
+                        else:
+                            raise RuntimeError("Unknown coordinate system")
+
+                    if component_counter == 0:
+                        total_expectation = this_expectation
+                    else:
+                        total_expectation += this_expectation
+                    
+                    component_counter += 1
+
             # Save expected counts for source:
             self._expected_counts[name] = copy.deepcopy(total_expectation)
          

From e495493b092a51372875574d7c6fae7f77c75ab0 Mon Sep 17 00:00:00 2001
From: Eliza Neights <eneights@gmail.com>
Date: Wed, 19 Mar 2025 12:40:06 -0400
Subject: [PATCH 30/31] Add MLM notebook

---
 .../{ => ASAD_method}/ASAD_method.ipynb       |    0
 .../background_after.yaml                     |   14 +
 .../background_before.yaml                    |   14 +
 .../maximum_likelihood_method/grb.yaml        |   14 +
 .../maximum_likelihood_method/mlm.ipynb       | 1031 +++++++++++++++++
 5 files changed, 1073 insertions(+)
 rename docs/tutorials/polarization/{ => ASAD_method}/ASAD_method.ipynb (100%)
 create mode 100644 docs/tutorials/polarization/maximum_likelihood_method/background_after.yaml
 create mode 100644 docs/tutorials/polarization/maximum_likelihood_method/background_before.yaml
 create mode 100644 docs/tutorials/polarization/maximum_likelihood_method/grb.yaml
 create mode 100644 docs/tutorials/polarization/maximum_likelihood_method/mlm.ipynb

diff --git a/docs/tutorials/polarization/ASAD_method.ipynb b/docs/tutorials/polarization/ASAD_method/ASAD_method.ipynb
similarity index 100%
rename from docs/tutorials/polarization/ASAD_method.ipynb
rename to docs/tutorials/polarization/ASAD_method/ASAD_method.ipynb
diff --git a/docs/tutorials/polarization/maximum_likelihood_method/background_after.yaml b/docs/tutorials/polarization/maximum_likelihood_method/background_after.yaml
new file mode 100644
index 00000000..9a34d763
--- /dev/null
+++ b/docs/tutorials/polarization/maximum_likelihood_method/background_after.yaml
@@ -0,0 +1,14 @@
+#----------#
+# Data I/O:
+
+data_file: "none" # full path
+ori_file: '/Users/eneights/work/COSI/data-challenges/data_challenge_4/data/orientations/DC3.ori'
+unbinned_output: 'fits' # 'fits' or 'hdf5'
+time_bins: 1 # time bin size in seconds. Takes int or list of bin edges. 
+energy_bins: [200., 500., 1000., 2000., 10000.] # Takes list. Needs to match response.
+phi_pix_size: 6 # binning of Compton scattering angle [deg]
+nside: 8 # healpix binning of psi chi local
+scheme: 'ring' # healpix binning of psi chi local
+tmin: 1835493502.8 # Min time cut in seconds.
+tmax: 1835493692. # Max time cut in seconds.
+#----------#
diff --git a/docs/tutorials/polarization/maximum_likelihood_method/background_before.yaml b/docs/tutorials/polarization/maximum_likelihood_method/background_before.yaml
new file mode 100644
index 00000000..9acae65c
--- /dev/null
+++ b/docs/tutorials/polarization/maximum_likelihood_method/background_before.yaml
@@ -0,0 +1,14 @@
+#----------#
+# Data I/O:
+
+data_file: "none" # full path
+ori_file: '/Users/eneights/work/COSI/data-challenges/data_challenge_4/data/orientations/DC3.ori'
+unbinned_output: 'fits' # 'fits' or 'hdf5'
+time_bins: 1 # time bin size in seconds. Takes int or list of bin edges. 
+energy_bins: [200., 500., 1000., 2000., 10000.] # Takes list. Needs to match response.
+phi_pix_size: 6 # binning of Compton scattering angle [deg]
+nside: 8 # healpix binning of psi chi local
+scheme: 'ring' # healpix binning of psi chi local
+tmin: 1835493292. # Min time cut in seconds.
+tmax: 1835493482.2 # Max time cut in seconds.
+#----------#
diff --git a/docs/tutorials/polarization/maximum_likelihood_method/grb.yaml b/docs/tutorials/polarization/maximum_likelihood_method/grb.yaml
new file mode 100644
index 00000000..f7310671
--- /dev/null
+++ b/docs/tutorials/polarization/maximum_likelihood_method/grb.yaml
@@ -0,0 +1,14 @@
+#----------#
+# Data I/O:
+
+data_file: "none" # full path
+ori_file: '/Users/eneights/work/COSI/data-challenges/data_challenge_4/data/orientations/DC3.ori'
+unbinned_output: 'fits' # 'fits' or 'hdf5'
+time_bins: 0.1 # time bin size in seconds. Takes int or list of bin edges. 
+energy_bins: [200., 500., 1000., 2000., 10000.] # Takes list. Needs to match response.
+phi_pix_size: 6 # binning of Compton scattering angle [deg]
+nside: 8 # healpix binning of psi chi local
+scheme: 'ring' # healpix binning of psi chi local
+tmin: 1835493492.2 # Min time cut in seconds.
+tmax: 1835493492.8 # Max time cut in seconds.
+#----------#
diff --git a/docs/tutorials/polarization/maximum_likelihood_method/mlm.ipynb b/docs/tutorials/polarization/maximum_likelihood_method/mlm.ipynb
new file mode 100644
index 00000000..9fe8cde4
--- /dev/null
+++ b/docs/tutorials/polarization/maximum_likelihood_method/mlm.ipynb
@@ -0,0 +1,1031 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "4e111ad9-5599-451c-83a5-f89a79b0dd42",
+   "metadata": {},
+   "source": [
+    "# Polarization example - Maximum likelihood method"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "f9b8addd-aaa4-488c-8041-385881689986",
+   "metadata": {},
+   "source": [
+    "This notebook fits the polarization fraction and angle of a Data Challenge 3 GRB (GRB 080802386) simulated using MEGAlib and combined with albedo photon background. It's assumed that the start time, duration, localization, and spectrum of the GRB are already known. The GRB was simulated with 80% polarization at an angle of 90 degrees in the IAU convention, and was 20 degrees off-axis. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "26c12d83-7afc-4000-8b8f-d353e0b08d12",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from cosipy import UnBinnedData, BinnedData, COSILike\n",
+    "from cosipy.spacecraftfile import SpacecraftFile\n",
+    "from cosipy.polarization.conventions import MEGAlibRelativeX, MEGAlibRelativeY, MEGAlibRelativeZ, IAUPolarizationConvention\n",
+    "from cosipy.threeml.custom_functions import Band_Eflux\n",
+    "from astropy.time import Time\n",
+    "import numpy as np\n",
+    "from astropy.coordinates import Angle, SkyCoord\n",
+    "from astropy import units as u\n",
+    "from cosipy.util import fetch_wasabi_file\n",
+    "from threeML import LinearPolarization, SpectralComponent, PointSource, Model, JointLikelihood, DataList\n",
+    "from astromodels import Parameter"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "5a52ee92",
+   "metadata": {},
+   "source": [
+    "### Read in data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ac0ad83d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "grb_background_local = UnBinnedData('grb.yaml')\n",
+    "grb_background_local.select_data_time(unbinned_data='/Users/eneights/work/COSI/data-challenges/data_challenge_4/data/simulations/polarization_tutorial_grb_background.fits.gz', output_name='grb_background_source_interval')\n",
+    "grb_background_local = BinnedData('grb.yaml')\n",
+    "grb_background_local.get_binned_data(unbinned_data='grb_background_source_interval.fits.gz', output_name='grb_background_binned_local', psichi_binning='local')\n",
+    "grb_background_local.load_binned_data_from_hdf5('grb_background_binned_local.hdf5')\n",
+    "\n",
+    "background_before_local = UnBinnedData('background_before.yaml')\n",
+    "background_before_local.select_data_time(unbinned_data='/Users/eneights/work/COSI/data-challenges/data_challenge_4/data/simulations/polarization_tutorial_grb_background.fits.gz', output_name='background_before')\n",
+    "background_before_local = BinnedData('background_before.yaml')\n",
+    "background_before_local.get_binned_data(unbinned_data='background_before.fits.gz', output_name='background_before_binned_local', psichi_binning='local')\n",
+    "background_before_local.load_binned_data_from_hdf5('background_before_binned_local.hdf5')\n",
+    "\n",
+    "background_after_local = UnBinnedData('background_after.yaml')\n",
+    "background_after_local.select_data_time(unbinned_data='/Users/eneights/work/COSI/data-challenges/data_challenge_4/data/simulations/polarization_tutorial_grb_background.fits.gz', output_name='background_after')\n",
+    "background_after_local = BinnedData('background_after.yaml')\n",
+    "background_after_local.get_binned_data(unbinned_data='background_after.fits.gz', output_name='background_after_binned_local', psichi_binning='local')\n",
+    "background_after_local.load_binned_data_from_hdf5('background_after_binned_local.hdf5')\n",
+    "\n",
+    "grb_background_galactic = BinnedData('grb.yaml')\n",
+    "grb_background_galactic.get_binned_data(unbinned_data='grb_background_source_interval.fits.gz', output_name='grb_background_binned_galactic', psichi_binning='galactic')\n",
+    "grb_background_galactic.load_binned_data_from_hdf5('grb_background_binned_galactic.hdf5')\n",
+    "\n",
+    "background_before_galactic = BinnedData('background_before.yaml')\n",
+    "background_before_galactic.get_binned_data(unbinned_data='background_before.fits.gz', output_name='background_before_binned_galactic', psichi_binning='galactic')\n",
+    "background_before_galactic.load_binned_data_from_hdf5('background_before_binned_galactic.hdf5')\n",
+    "\n",
+    "background_after_galactic = BinnedData('background_after.yaml')\n",
+    "background_after_galactic.get_binned_data(unbinned_data='background_after.fits.gz', output_name='background_after_binned_galactic', psichi_binning='galactic')\n",
+    "background_after_galactic.load_binned_data_from_hdf5('background_after_binned_galactic.hdf5')"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b983b194",
+   "metadata": {},
+   "source": [
+    "Define the path to the detector response and read in the orientation file. The orientation is cut down to the time interval of the source."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "36712258",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "response_file = '/Users/eneights/work/COSI/data-challenges/data_challenge_4/data/responses/ResponseContinuum.o3.pol.e200_10000.b4.p12.s10396905069491.m441.filtered.nonsparse.binnedpolarization.11D_nside8.area.h5'\n",
+    "\n",
+    "sc_orientation = SpacecraftFile.parse_from_file('/Users/eneights/work/COSI/data-challenges/data_challenge_4/data/orientations/DC3.ori')\n",
+    "sc_orientation = sc_orientation.source_interval(Time(1835493492.2, format = 'unix'), Time(1835493492.8, format = 'unix'))"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c6951d6c",
+   "metadata": {},
+   "source": [
+    "Define the GRB position and spectrum."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "26cec39d",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "source_direction = SkyCoord(l=23.53, b=-53.44, frame='galactic', unit=u.deg)\n",
+    "attitude = sc_orientation.get_attitude()[0]\n",
+    "\n",
+    "a = 100. * u.keV\n",
+    "b = 10000. * u.keV\n",
+    "alpha = -0.7368949\n",
+    "beta = -2.095031\n",
+    "ebreak = 622.389 * u.keV\n",
+    "K = 300. / u.cm / u.cm / u.s\n",
+    "\n",
+    "spectrum = Band_Eflux(a = a.value,\n",
+    "                      b = b.value,\n",
+    "                      alpha = alpha,\n",
+    "                      beta = beta,\n",
+    "                      E0 = ebreak.value,\n",
+    "                      K = K.value)\n",
+    "\n",
+    "spectrum.a.unit = a.unit\n",
+    "spectrum.b.unit = b.unit\n",
+    "spectrum.E0.unit = ebreak.unit\n",
+    "spectrum.K.unit = K.unit\n",
+    "\n",
+    "polarization = LinearPolarization(80, 80) # polarization degree, polarization angle (in same convention as response for data in local frame and IAU convention for data in galactic frame)\n",
+    "spectral_component = SpectralComponent('grb', spectrum, polarization)\n",
+    "\n",
+    "source = PointSource('source',                                                          # Name of source (arbitrary, but needs to be unique)\n",
+    "                     l = source_direction.l.deg,               # Longitude (deg)\n",
+    "                     b = source_direction.b.deg,               # Latitude (deg)\n",
+    "                     components = [spectral_component])                                 # Spectral model\n",
+    "\n",
+    "source.components['grb'].shape.K.fix = True\n",
+    "source.components['grb'].shape.E0.fix = True\n",
+    "source.components['grb'].shape.alpha.fix = True\n",
+    "source.components['grb'].shape.beta.fix = True\n",
+    "\n",
+    "model = Model(source)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "a393b0fc",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n"
+     ]
+    },
+    {
+     "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\">09:27:34 </span><span style=\"color: #00ffaf; text-decoration-color: #00ffaf\">INFO    </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> set the minimizer to minuit                                             </span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/classicMLE/joint_likelihood.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">joint_likelihood.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/classicMLE/joint_likelihood.py#1045\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1045</span></a>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[38;5;46m09:27:34\u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;49mINFO    \u001b[0m \u001b[1;38;5;251m set the minimizer to minuit                                            \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=740192;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/classicMLE/joint_likelihood.py\u001b\\\u001b[2mjoint_likelihood.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=359590;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/classicMLE/joint_likelihood.py#1045\u001b\\\u001b[2m1045\u001b[0m\u001b]8;;\u001b\\\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "bkg_par = Parameter(\"background_cosi\",                                                                          # background parameter\n",
+    "                    0.0016,                                                                                        # initial value of parameter\n",
+    "                    min_value=0,                                                                                # minimum value of parameter\n",
+    "                    max_value=1,                                                                                # maximum value of parameter\n",
+    "                    delta=1e-5,                                                                                 # initial step used by fitting engine\n",
+    "                    desc=\"Background parameter for cosi\")\n",
+    "\n",
+    "cosi = COSILike(\"cosi\",                                                                                         # COSI 3ML plugin\n",
+    "                dr = response_file,                                                                                        # detector response\n",
+    "                data = grb_background_local.binned_data.project('Em', 'Phi', 'PsiChi'),                                      # data (source+background)\n",
+    "                bkg = (background_before_local.binned_data.project('Em', 'Phi', 'PsiChi') + background_after_local.binned_data.project('Em', 'Phi', 'PsiChi')) * 0.0016,    # background model \n",
+    "                sc_orientation = sc_orientation,\n",
+    "                response_pa_convention = 'RelativeZ')\n",
+    "                #nuisance_param = bkg_par)\n",
+    "\n",
+    "plugins = DataList(cosi)\n",
+    "\n",
+    "like = JointLikelihood(model, plugins, verbose = False)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bbb6ffe2",
+   "metadata": {},
+   "source": [
+    "### Polarization fit in local frame"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "41cbf55e",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "Adding 1e-12 to each bin of the expectation to avoid log-likelihood = -inf.\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n",
+      "The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!\n"
+     ]
+    },
+    {
+     "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\">09:30:07 </span><span style=\"color: #af5fd7; text-decoration-color: #af5fd7\">WARNING </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> get_number_of_data_points not implemented, values for statistical        </span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/plugin_prototype.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">plugin_prototype.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/plugin_prototype.py#130\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">130</span></a>\n",
+       "<span style=\"color: #00ff00; text-decoration-color: #00ff00\">         </span>         <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">measurements such as AIC or BIC are unreliable                            </span><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">                       </span>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[38;5;46m09:30:07\u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;134mWARNING \u001b[0m \u001b[1;38;5;251m get_number_of_data_points not implemented, values for statistical       \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=970920;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/plugin_prototype.py\u001b\\\u001b[2mplugin_prototype.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=655372;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/plugin_prototype.py#130\u001b\\\u001b[2m130\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[38;5;46m         \u001b[0m         \u001b[1;38;5;251mmeasurements such as AIC or BIC are unreliable                           \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: #00ffaf; text-decoration-color: #00ffaf; font-weight: bold; text-decoration: underline\">Best fit values:</span>\n",
+       "\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[1;4;38;5;49mBest fit values:\u001b[0m\n",
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>result</th>\n",
+       "      <th>unit</th>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>parameter</th>\n",
+       "      <th></th>\n",
+       "      <th></th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>source.spectrum.grb.polarization.degree</th>\n",
+       "      <td>(6.0 +/- 0.6) x 10</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>source.spectrum.grb.polarization.angle</th>\n",
+       "      <td>(8.32 +/- 0.34) x 10</td>\n",
+       "      <td>deg</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                       result unit\n",
+       "parameter                                                         \n",
+       "source.spectrum.grb.polarization.degree    (6.0 +/- 0.6) x 10     \n",
+       "source.spectrum.grb.polarization.angle   (8.32 +/- 0.34) x 10  deg"
+      ]
+     },
+     "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\">\n",
+       "<span style=\"color: #00ffaf; text-decoration-color: #00ffaf; font-weight: bold; text-decoration: underline\">Correlation matrix:</span>\n",
+       "\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n",
+       "\u001b[1;4;38;5;49mCorrelation matrix:\u001b[0m\n",
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div><table id=\"table13729203104\">\n",
+       "<tr><td>1.00</td><td>-0.79</td></tr>\n",
+       "<tr><td>-0.79</td><td>1.00</td></tr>\n",
+       "</table></div>"
+      ],
+      "text/plain": [
+       " 1.00 -0.79\n",
+       "-0.79  1.00"
+      ]
+     },
+     "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\">\n",
+       "<span style=\"color: #00ffaf; text-decoration-color: #00ffaf; font-weight: bold; text-decoration: underline\">Values of -log(likelihood) at the minimum:</span>\n",
+       "\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n",
+       "\u001b[1;4;38;5;49mValues of -\u001b[0m\u001b[1;4;38;5;49mlog\u001b[0m\u001b[1;4;38;5;49m(\u001b[0m\u001b[1;4;38;5;49mlikelihood\u001b[0m\u001b[1;4;38;5;49m)\u001b[0m\u001b[1;4;38;5;49m at the minimum:\u001b[0m\n",
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>-log(likelihood)</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>cosi</th>\n",
+       "      <td>18747.564101</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>total</th>\n",
+       "      <td>18747.564101</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "       -log(likelihood)\n",
+       "cosi       18747.564101\n",
+       "total      18747.564101"
+      ]
+     },
+     "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\">\n",
+       "<span style=\"color: #00ffaf; text-decoration-color: #00ffaf; font-weight: bold; text-decoration: underline\">Values of statistical measures:</span>\n",
+       "\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\n",
+       "\u001b[1;4;38;5;49mValues of statistical measures:\u001b[0m\n",
+       "\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>statistical measures</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>AIC</th>\n",
+       "      <td>37493.128202</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>BIC</th>\n",
+       "      <td>37495.128202</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "     statistical measures\n",
+       "AIC          37493.128202\n",
+       "BIC          37495.128202"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "text/plain": [
+       "(                                             value  negative_error  \\\n",
+       " source.spectrum.grb.polarization.degree  60.304226       -6.271626   \n",
+       " source.spectrum.grb.polarization.angle   83.164307       -3.372013   \n",
+       " \n",
+       "                                          positive_error     error unit  \n",
+       " source.spectrum.grb.polarization.degree        6.140856  6.206241       \n",
+       " source.spectrum.grb.polarization.angle         3.432037  3.402025  deg  ,\n",
+       "        -log(likelihood)\n",
+       " cosi       18747.564101\n",
+       " total      18747.564101)"
+      ]
+     },
+     "execution_count": 30,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "like.fit()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "b6c3feed",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "spectrum = Band_Eflux(a = a.value,\n",
+    "                      b = b.value,\n",
+    "                      alpha = alpha,\n",
+    "                      beta = beta,\n",
+    "                      E0 = ebreak.value,\n",
+    "                      K = K.value)\n",
+    "\n",
+    "spectrum.a.unit = a.unit\n",
+    "spectrum.b.unit = b.unit\n",
+    "spectrum.E0.unit = ebreak.unit\n",
+    "spectrum.K.unit = K.unit\n",
+    "\n",
+    "polarization = LinearPolarization(80, 90) # convention of angle?? should be input into cosilike somewhere -- same as response for local frame, iau for galactic frame\n",
+    "spectral_component = SpectralComponent('grb', spectrum, polarization)\n",
+    "\n",
+    "source = PointSource('source',                                                          # Name of source (arbitrary, but needs to be unique)\n",
+    "                     l = source_direction.l.deg,               # Longitude (deg)\n",
+    "                     b = source_direction.b.deg,               # Latitude (deg)\n",
+    "                     components = [spectral_component])                                 # Spectral model\n",
+    "\n",
+    "source.components['grb'].shape.K.fix = True\n",
+    "source.components['grb'].shape.E0.fix = True\n",
+    "source.components['grb'].shape.alpha.fix = True\n",
+    "source.components['grb'].shape.beta.fix = True\n",
+    "\n",
+    "model = Model(source)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d98e8ebd",
+   "metadata": {},
+   "source": [
+    "### Polarization fit in ICRS coordinates"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "8e852aae",
+   "metadata": {},
+   "outputs": [
+    {
+     "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\">11:11:02 </span><span style=\"color: #00ffaf; text-decoration-color: #00ffaf\">INFO    </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> set the minimizer to minuit                                             </span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/classicMLE/joint_likelihood.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">joint_likelihood.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/classicMLE/joint_likelihood.py#1045\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">1045</span></a>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[38;5;46m11:11:02\u001b[0m\u001b[38;5;46m \u001b[0m\u001b[38;5;49mINFO    \u001b[0m \u001b[1;38;5;251m set the minimizer to minuit                                            \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=48516;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/classicMLE/joint_likelihood.py\u001b\\\u001b[2mjoint_likelihood.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=396566;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/classicMLE/joint_likelihood.py#1045\u001b\\\u001b[2m1045\u001b[0m\u001b]8;;\u001b\\\n"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Adding 1e-12 to each bin of the expectation to avoid log-likelihood = -inf.\n"
+     ]
+    },
+    {
+     "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\">12:25:23 </span><span style=\"color: #ff0000; text-decoration-color: #ff0000; font-weight: bold\">ERROR   </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> Last status:                                                             </span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">minuit_minimizer.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#166\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">166</span></a>\n",
+       "</pre>\n"
+      ],
+      "text/plain": [
+       "\u001b[38;5;46m12:25:23\u001b[0m\u001b[38;5;46m \u001b[0m\u001b[1;5;91mERROR   \u001b[0m \u001b[1;38;5;251m Last status:                                                            \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=182087;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\u001b\\\u001b[2mminuit_minimizer.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=867331;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#166\u001b\\\u001b[2m166\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\">         </span><span style=\"color: #ff0000; text-decoration-color: #ff0000; font-weight: bold\">ERROR   </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> ┌─────────────────────────────────────────────────────────────────────── </span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">minuit_minimizer.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#169\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">169</span></a>\n",
+       "<span style=\"color: #00ff00; text-decoration-color: #00ff00\">         </span>         <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">──┐                                                                       </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[1;5;91mERROR   \u001b[0m \u001b[1;38;5;251m ┌───────────────────────────────────────────────────────────────────────\u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=463832;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\u001b\\\u001b[2mminuit_minimizer.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=652850;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#169\u001b\\\u001b[2m169\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[38;5;46m         \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: #ff0000; text-decoration-color: #ff0000; font-weight: bold\">ERROR   </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> │                                Migrad                                  </span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">minuit_minimizer.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#169\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">169</span></a>\n",
+       "<span style=\"color: #00ff00; text-decoration-color: #00ff00\">         </span>         <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">│                                                                         </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[1;5;91mERROR   \u001b[0m \u001b[1;38;5;251m │                                Migrad                                 \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=803436;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\u001b\\\u001b[2mminuit_minimizer.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=532038;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#169\u001b\\\u001b[2m169\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[38;5;46m         \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: #ff0000; text-decoration-color: #ff0000; font-weight: bold\">ERROR   </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> ├──────────────────────────────────┬──────────────────────────────────── </span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">minuit_minimizer.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#169\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">169</span></a>\n",
+       "<span style=\"color: #00ff00; text-decoration-color: #00ff00\">         </span>         <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">──┤                                                                       </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[1;5;91mERROR   \u001b[0m \u001b[1;38;5;251m ├──────────────────────────────────┬────────────────────────────────────\u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=264800;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\u001b\\\u001b[2mminuit_minimizer.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=785176;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#169\u001b\\\u001b[2m169\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[38;5;46m         \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: #ff0000; text-decoration-color: #ff0000; font-weight: bold\">ERROR   </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> │ FCN = </span><span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0; font-weight: bold\">1.911e+04</span><span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">                  │             Nfcn = </span><span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0; font-weight: bold\">3445</span><span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">             </span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">minuit_minimizer.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#169\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">169</span></a>\n",
+       "<span style=\"color: #00ff00; text-decoration-color: #00ff00\">         </span>         <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">│                                                                         </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[1;5;91mERROR   \u001b[0m \u001b[1;38;5;251m │ FCN = \u001b[0m\u001b[1;37m1.911e+04\u001b[0m\u001b[1;38;5;251m                  │             Nfcn = \u001b[0m\u001b[1;37m3445\u001b[0m\u001b[1;38;5;251m            \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=151184;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\u001b\\\u001b[2mminuit_minimizer.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=287863;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#169\u001b\\\u001b[2m169\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[38;5;46m         \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: #ff0000; text-decoration-color: #ff0000; font-weight: bold\">ERROR   </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> │ EDM = </span><span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0; font-weight: bold\">1.4</span><span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> (Goal: </span><span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0; font-weight: bold\">0.0001</span><span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">)         │                                     </span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">minuit_minimizer.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#169\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">169</span></a>\n",
+       "<span style=\"color: #00ff00; text-decoration-color: #00ff00\">         </span>         <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">│                                                                         </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[1;5;91mERROR   \u001b[0m \u001b[1;38;5;251m │ EDM = \u001b[0m\u001b[1;37m1.4\u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b[1;38;5;251m(\u001b[0m\u001b[1;38;5;251mGoal: \u001b[0m\u001b[1;37m0.0001\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=833149;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\u001b\\\u001b[2mminuit_minimizer.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=8926;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#169\u001b\\\u001b[2m169\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[38;5;46m         \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: #ff0000; text-decoration-color: #ff0000; font-weight: bold\">ERROR   </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> ├──────────────────────────────────┼──────────────────────────────────── </span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">minuit_minimizer.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#169\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">169</span></a>\n",
+       "<span style=\"color: #00ff00; text-decoration-color: #00ff00\">         </span>         <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">──┤                                                                       </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[1;5;91mERROR   \u001b[0m \u001b[1;38;5;251m ├──────────────────────────────────┼────────────────────────────────────\u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=720300;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\u001b\\\u001b[2mminuit_minimizer.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=584454;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#169\u001b\\\u001b[2m169\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[38;5;46m         \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: #ff0000; text-decoration-color: #ff0000; font-weight: bold\">ERROR   </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> │         INVALID Minimum          │   ABOVE EDM threshold (goal x </span><span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0; font-weight: bold\">10</span><span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">)   </span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">minuit_minimizer.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#169\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">169</span></a>\n",
+       "<span style=\"color: #00ff00; text-decoration-color: #00ff00\">         </span>         <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">│                                                                         </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[1;5;91mERROR   \u001b[0m \u001b[1;38;5;251m │         INVALID Minimum          │   ABOVE EDM threshold \u001b[0m\u001b[1;38;5;251m(\u001b[0m\u001b[1;38;5;251mgoal x \u001b[0m\u001b[1;37m10\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=231629;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\u001b\\\u001b[2mminuit_minimizer.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=22241;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#169\u001b\\\u001b[2m169\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[38;5;46m         \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: #ff0000; text-decoration-color: #ff0000; font-weight: bold\">ERROR   </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> ├──────────────────────────────────┼──────────────────────────────────── </span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">minuit_minimizer.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#169\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">169</span></a>\n",
+       "<span style=\"color: #00ff00; text-decoration-color: #00ff00\">         </span>         <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">──┤                                                                       </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[1;5;91mERROR   \u001b[0m \u001b[1;38;5;251m ├──────────────────────────────────┼────────────────────────────────────\u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=305270;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\u001b\\\u001b[2mminuit_minimizer.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=559312;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#169\u001b\\\u001b[2m169\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[38;5;46m         \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: #ff0000; text-decoration-color: #ff0000; font-weight: bold\">ERROR   </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> │      No parameters at limit      │           Below call limit          </span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">minuit_minimizer.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#169\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">169</span></a>\n",
+       "<span style=\"color: #00ff00; text-decoration-color: #00ff00\">         </span>         <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">│                                                                         </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[1;5;91mERROR   \u001b[0m \u001b[1;38;5;251m │      No parameters at limit      │           Below call limit         \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=80144;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\u001b\\\u001b[2mminuit_minimizer.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=935977;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#169\u001b\\\u001b[2m169\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[38;5;46m         \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: #ff0000; text-decoration-color: #ff0000; font-weight: bold\">ERROR   </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> ├──────────────────────────────────┼──────────────────────────────────── </span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">minuit_minimizer.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#169\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">169</span></a>\n",
+       "<span style=\"color: #00ff00; text-decoration-color: #00ff00\">         </span>         <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">──┤                                                                       </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[1;5;91mERROR   \u001b[0m \u001b[1;38;5;251m ├──────────────────────────────────┼────────────────────────────────────\u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=37920;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\u001b\\\u001b[2mminuit_minimizer.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=17116;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#169\u001b\\\u001b[2m169\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[38;5;46m         \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: #ff0000; text-decoration-color: #ff0000; font-weight: bold\">ERROR   </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> │             Hesse ok             │         Covariance accurate         </span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">minuit_minimizer.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#169\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">169</span></a>\n",
+       "<span style=\"color: #00ff00; text-decoration-color: #00ff00\">         </span>         <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">│                                                                         </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[1;5;91mERROR   \u001b[0m \u001b[1;38;5;251m │             Hesse ok             │         Covariance accurate        \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=96448;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\u001b\\\u001b[2mminuit_minimizer.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=420348;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#169\u001b\\\u001b[2m169\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[38;5;46m         \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: #ff0000; text-decoration-color: #ff0000; font-weight: bold\">ERROR   </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> └──────────────────────────────────┴──────────────────────────────────── </span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">minuit_minimizer.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#169\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">169</span></a>\n",
+       "<span style=\"color: #00ff00; text-decoration-color: #00ff00\">         </span>         <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">──┘                                                                       </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[1;5;91mERROR   \u001b[0m \u001b[1;38;5;251m └──────────────────────────────────┴────────────────────────────────────\u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=348244;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\u001b\\\u001b[2mminuit_minimizer.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=848727;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#169\u001b\\\u001b[2m169\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[38;5;46m         \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: #ff0000; text-decoration-color: #ff0000; font-weight: bold\">ERROR   </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> ┌───┬─────────────────────────────────────────┬───────────┬───────────┬─ </span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">minuit_minimizer.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#174\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">174</span></a>\n",
+       "<span style=\"color: #00ff00; text-decoration-color: #00ff00\">         </span>         <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">───────────┬────────────┬─────────┬─────────┬───────┐                     </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[1;5;91mERROR   \u001b[0m \u001b[1;38;5;251m ┌───┬─────────────────────────────────────────┬───────────┬───────────┬─\u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=796559;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\u001b\\\u001b[2mminuit_minimizer.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=262290;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#174\u001b\\\u001b[2m174\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[38;5;46m         \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: #ff0000; text-decoration-color: #ff0000; font-weight: bold\">ERROR   </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> │   │ Name                                    │   Value   │ Hesse Err │  </span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">minuit_minimizer.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#174\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">174</span></a>\n",
+       "<span style=\"color: #00ff00; text-decoration-color: #00ff00\">         </span>         <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">Minos Err- │ Minos Err+ │ Limit-  │ Limit+  │ Fixed │                     </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[1;5;91mERROR   \u001b[0m \u001b[1;38;5;251m │   │ Name                                    │   Value   │ Hesse Err │ \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=28686;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\u001b\\\u001b[2mminuit_minimizer.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=50714;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#174\u001b\\\u001b[2m174\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[38;5;46m         \u001b[0m         \u001b[1;38;5;251mMinos Err- │ Minos Err+ │ Limit-  │ Limit+  │ Fixed │                    \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: #ff0000; text-decoration-color: #ff0000; font-weight: bold\">ERROR   </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> ├───┼─────────────────────────────────────────┼───────────┼───────────┼─ </span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">minuit_minimizer.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#174\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">174</span></a>\n",
+       "<span style=\"color: #00ff00; text-decoration-color: #00ff00\">         </span>         <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">───────────┼────────────┼─────────┼─────────┼───────┤                     </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[1;5;91mERROR   \u001b[0m \u001b[1;38;5;251m ├───┼─────────────────────────────────────────┼───────────┼───────────┼─\u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=268308;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\u001b\\\u001b[2mminuit_minimizer.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=455215;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#174\u001b\\\u001b[2m174\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[38;5;46m         \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: #ff0000; text-decoration-color: #ff0000; font-weight: bold\">ERROR   </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> │ </span><span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0; font-weight: bold\">0</span><span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> │ source_spectrum_grb_polarization_degree │   </span><span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0; font-weight: bold\">29.4</span><span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">    │    </span><span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0; font-weight: bold\">3.0</span><span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">    │  </span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">minuit_minimizer.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#174\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">174</span></a>\n",
+       "<span style=\"color: #00ff00; text-decoration-color: #00ff00\">         </span>         <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">│            │    </span><span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0; font-weight: bold\">0</span><span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">    │   </span><span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0; font-weight: bold\">100</span><span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">   │       │                                </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[1;5;91mERROR   \u001b[0m \u001b[1;38;5;251m │ \u001b[0m\u001b[1;37m0\u001b[0m\u001b[1;38;5;251m │ source_spectrum_grb_polarization_degree │   \u001b[0m\u001b[1;37m29.4\u001b[0m\u001b[1;38;5;251m    │    \u001b[0m\u001b[1;37m3.0\u001b[0m\u001b[1;38;5;251m    │ \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=423661;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\u001b\\\u001b[2mminuit_minimizer.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=423095;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#174\u001b\\\u001b[2m174\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[38;5;46m         \u001b[0m         \u001b[1;38;5;251m│            │    \u001b[0m\u001b[1;37m0\u001b[0m\u001b[1;38;5;251m    │   \u001b[0m\u001b[1;37m100\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: #ff0000; text-decoration-color: #ff0000; font-weight: bold\">ERROR   </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> │ </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\"> │ source_spectrum_grb_polarization_angle  │  </span><span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0; font-weight: bold\">89.9979</span><span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">  │  </span><span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0; font-weight: bold\">0.0014</span><span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">   │  </span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">minuit_minimizer.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#174\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">174</span></a>\n",
+       "<span style=\"color: #00ff00; text-decoration-color: #00ff00\">         </span>         <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">│            │    </span><span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0; font-weight: bold\">0</span><span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">    │   </span><span style=\"color: #c0c0c0; text-decoration-color: #c0c0c0; font-weight: bold\">180</span><span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">   │       │                                </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[1;5;91mERROR   \u001b[0m \u001b[1;38;5;251m │ \u001b[0m\u001b[1;37m1\u001b[0m\u001b[1;38;5;251m │ source_spectrum_grb_polarization_angle  │  \u001b[0m\u001b[1;37m89.9979\u001b[0m\u001b[1;38;5;251m  │  \u001b[0m\u001b[1;37m0.0014\u001b[0m\u001b[1;38;5;251m   │ \u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=454956;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\u001b\\\u001b[2mminuit_minimizer.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=360136;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#174\u001b\\\u001b[2m174\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[38;5;46m         \u001b[0m         \u001b[1;38;5;251m│            │    \u001b[0m\u001b[1;37m0\u001b[0m\u001b[1;38;5;251m    │   \u001b[0m\u001b[1;37m180\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: #ff0000; text-decoration-color: #ff0000; font-weight: bold\">ERROR   </span> <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\"> └───┴─────────────────────────────────────────┴───────────┴───────────┴─ </span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">minuit_minimizer.py</span></a><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">:</span><a href=\"file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#174\" target=\"_blank\"><span style=\"color: #7f7f7f; text-decoration-color: #7f7f7f\">174</span></a>\n",
+       "<span style=\"color: #00ff00; text-decoration-color: #00ff00\">         </span>         <span style=\"color: #c6c6c6; text-decoration-color: #c6c6c6; font-weight: bold\">───────────┴────────────┴─────────┴─────────┴───────┘                     </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[1;5;91mERROR   \u001b[0m \u001b[1;38;5;251m └───┴─────────────────────────────────────────┴───────────┴───────────┴─\u001b[0m\u001b[1;38;5;251m \u001b[0m\u001b]8;id=302610;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py\u001b\\\u001b[2mminuit_minimizer.py\u001b[0m\u001b]8;;\u001b\\\u001b[2m:\u001b[0m\u001b]8;id=204486;file:///Users/eneights/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py#174\u001b\\\u001b[2m174\u001b[0m\u001b]8;;\u001b\\\n",
+       "\u001b[38;5;46m         \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"
+    },
+    {
+     "ename": "FitFailed",
+     "evalue": "MIGRAD call failed. This is usually due to unconstrained parameters.",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mFitFailed\u001b[0m                                 Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[33], line 13\u001b[0m\n\u001b[1;32m      9\u001b[0m plugins_galactic \u001b[38;5;241m=\u001b[39m DataList(cosi_galactic)\n\u001b[1;32m     11\u001b[0m like_galactic \u001b[38;5;241m=\u001b[39m JointLikelihood(model, plugins_galactic, verbose \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;01mFalse\u001b[39;00m)\n\u001b[0;32m---> 13\u001b[0m \u001b[43mlike_galactic\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mfit\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n",
+      "File \u001b[0;32m~/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/classicMLE/joint_likelihood.py:327\u001b[0m, in \u001b[0;36mJointLikelihood.fit\u001b[0;34m(self, quiet, compute_covariance, n_samples)\u001b[0m\n\u001b[1;32m    323\u001b[0m \u001b[38;5;66;03m# Perform the fit, but first flush stdout (so if we have verbose=True the messages there will follow\u001b[39;00m\n\u001b[1;32m    324\u001b[0m \u001b[38;5;66;03m# what is already in the buffer)\u001b[39;00m\n\u001b[1;32m    325\u001b[0m sys\u001b[38;5;241m.\u001b[39mstdout\u001b[38;5;241m.\u001b[39mflush()\n\u001b[0;32m--> 327\u001b[0m xs, log_likelihood_minimum \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_minimizer\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mminimize\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m    328\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcompute_covar\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcompute_covariance\u001b[49m\n\u001b[1;32m    329\u001b[0m \u001b[43m\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    331\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m log_likelihood_minimum \u001b[38;5;241m==\u001b[39m minimization\u001b[38;5;241m.\u001b[39mFIT_FAILED:\n\u001b[1;32m    332\u001b[0m     log\u001b[38;5;241m.\u001b[39merror(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mThe fit failed to converge.\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n",
+      "File \u001b[0;32m~/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minimization.py:632\u001b[0m, in \u001b[0;36mMinimizer.minimize\u001b[0;34m(self, compute_covar)\u001b[0m\n\u001b[1;32m    628\u001b[0m \u001b[38;5;66;03m# Gather the best fit values from the minimizer and the covariance matrix (if provided)\u001b[39;00m\n\u001b[1;32m    630\u001b[0m \u001b[38;5;28;01mtry\u001b[39;00m:\n\u001b[0;32m--> 632\u001b[0m     internal_best_fit_values, function_minimum \u001b[38;5;241m=\u001b[39m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_minimize\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m    634\u001b[0m \u001b[38;5;28;01mexcept\u001b[39;00m FitFailed:\n\u001b[1;32m    636\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m\n",
+      "File \u001b[0;32m~/software/miniforge3/envs/cosipy-fork/lib/python3.10/site-packages/threeML/minimizer/minuit_minimizer.py:210\u001b[0m, in \u001b[0;36mMinuitMinimizer._minimize\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    206\u001b[0m \u001b[38;5;28;01mif\u001b[39;00m \u001b[38;5;129;01mnot\u001b[39;00m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mminuit\u001b[38;5;241m.\u001b[39mvalid:\n\u001b[1;32m    208\u001b[0m     \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39m_print_current_status()\n\u001b[0;32m--> 210\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m FitFailed(\n\u001b[1;32m    211\u001b[0m         \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mMIGRAD call failed. This is usually due to unconstrained parameters.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    212\u001b[0m     )\n\u001b[1;32m    214\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    215\u001b[0m \n\u001b[1;32m    216\u001b[0m     \u001b[38;5;66;03m# Gather the optimized values for all parameters from the internal\u001b[39;00m\n\u001b[1;32m    217\u001b[0m     \u001b[38;5;66;03m# iminuit dictionary\u001b[39;00m\n\u001b[1;32m    219\u001b[0m     best_fit_values \u001b[38;5;241m=\u001b[39m []\n",
+      "\u001b[0;31mFitFailed\u001b[0m: MIGRAD call failed. This is usually due to unconstrained parameters."
+     ]
+    }
+   ],
+   "source": [
+    "cosi_galactic = COSILike(\"cosi\",                                                                                         # COSI 3ML plugin\n",
+    "                dr = response_file,                                                                                        # detector response\n",
+    "                data = grb_background_galactic.binned_data.project('Em', 'Phi', 'PsiChi'),                                      # data (source+background)\n",
+    "                bkg = (background_before_galactic.binned_data.project('Em', 'Phi', 'PsiChi') + background_after_galactic.binned_data.project('Em', 'Phi', 'PsiChi')) * 0.0016,    # background model \n",
+    "                sc_orientation = sc_orientation,\n",
+    "                response_pa_convention = 'RelativeZ')\n",
+    "                #nuisance_param = bkg_par)\n",
+    "\n",
+    "plugins_galactic = DataList(cosi_galactic)\n",
+    "\n",
+    "like_galactic = JointLikelihood(model, plugins_galactic, verbose = False)\n",
+    "\n",
+    "like_galactic.fit()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "4b421e55",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "cosipy-fork",
+   "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": "3.10.0"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

From 8687ebaa7edd59f74c85638afeaf4b65f8a17975 Mon Sep 17 00:00:00 2001
From: Eliza Neights <eneights@gmail.com>
Date: Thu, 27 Mar 2025 14:16:25 -0400
Subject: [PATCH 31/31] Correct polarization angle rotation

---
 cosipy/polarization/polarization_angle.py |  40 ++---
 cosipy/response/FullDetectorResponse.py   | 197 ++++++----------------
 cosipy/response/PointSourceResponse.py    | 144 +++-------------
 cosipy/threeml/COSILike.py                |  12 +-
 4 files changed, 97 insertions(+), 296 deletions(-)

diff --git a/cosipy/polarization/polarization_angle.py b/cosipy/polarization/polarization_angle.py
index 931cf7b6..369be280 100644
--- a/cosipy/polarization/polarization_angle.py
+++ b/cosipy/polarization/polarization_angle.py
@@ -1,6 +1,7 @@
 import numpy as np
 from astropy.coordinates import SkyCoord, Angle
 import astropy.units as u
+from scoords import SpacecraftFrame
 
 from .conventions import PolarizationConvention
 
@@ -120,39 +121,30 @@ def from_scattering_direction(cls, psichi, source_coord, convention):
             Azimuthal scattering angle
         """
 
-        if not psichi.frame.name == source_coord.frame.name:
-            raise RuntimeError('psichi and source_coord must have the same frame')
+        if convention.frame.name == 'spacecraftframe':
 
-        reference_coord = convention.get_basis(source_coord)[0]
-
-        source_vector_cartesian = [source_coord.cartesian.x.value,
-                                   source_coord.cartesian.y.value, 
-                                   source_coord.cartesian.z.value]
-
-        reference_vector_cartesian = [reference_coord.cartesian.x.value, 
-                                      reference_coord.cartesian.y.value,
-                                      reference_coord.cartesian.z.value]
+            source_coord = source_coord.transform_to(SpacecraftFrame(attitude=source_coord.attitude))
+            psichi = psichi.transform_to(SpacecraftFrame(attitude=source_coord.attitude))
 
-        if psichi.frame.name == 'spacecraftframe':
+        elif convention.frame.name == 'icrs':
 
-            psi = (np.pi/2) - psichi.lat.rad
-            chi = psichi.lon.rad
+            source_coord = source_coord.transform_to('icrs')
+            psichi = psichi.transform_to('icrs')
 
-        elif psichi.frame.name == 'galactic':
+        elif convention.frame.name == 'galactic':
 
-            psi = (np.pi/2) - psichi.b.rad
-            chi = psichi.l.rad
+            source_coord = source_coord.transform_to('galactic')
+            psichi = psichi.transform_to('galactic')
 
-        elif psichi.frame.name == 'icrs':
+        else:
 
-            psi = (np.pi/2) - psichi.dec.rad
-            chi = psichi.ra.rad
+            raise RuntimeError('Unsupported polarization convention frame "' + convention.frame.name + '"')
 
-        else:
-            raise RuntimeError('Unsupported frame "' + psichi.frame.name + '"')
+        reference_coord = convention.get_basis(source_coord)[0]
 
-        # Convert scattered photon vector from spherical to Cartesian coordinates
-        scattered_photon_vector = [np.sin(psi) * np.cos(chi), np.sin(psi) * np.sin(chi), np.cos(psi)]
+        source_vector_cartesian = source_coord.cartesian.xyz.value
+        reference_vector_cartesian = reference_coord.cartesian.xyz.value
+        scattered_photon_vector = psichi.cartesian.xyz.value
 
         # Project scattered photon vector onto plane perpendicular to source direction
         d = np.dot(scattered_photon_vector, source_vector_cartesian) / np.dot(source_vector_cartesian, source_vector_cartesian)
diff --git a/cosipy/response/FullDetectorResponse.py b/cosipy/response/FullDetectorResponse.py
index 8a67c77e..b220a9b9 100644
--- a/cosipy/response/FullDetectorResponse.py
+++ b/cosipy/response/FullDetectorResponse.py
@@ -682,137 +682,6 @@ def _open_rsp(cls, filename, Spectrumfile=None,norm="Linear" ,single_pixel = Fal
 
         return new
 
-    @staticmethod
-    def _write_h5(dr_area, filename):
-        """
-        Write a Histogram containing the response into a HDF5 file response format
-
-        Parameters
-        ----------
-        dr_area : Histogram,
-             Histogram containing the response matrix in unit of differential area
-
-         filename : str, :py:class:`~pathlib.Path`
-             Path to .h5 file
-        """
-
-        npix = dr_area.axes['NuLambda'].nbins
-        nside = HealpixBase(npix = npix).nside
-        has_polarization = "Pol" in dr_area.axes.labels
-        sparse = dr_area.is_sparse
-
-        f = h5.File(filename, mode='w')
-
-        drm = f.create_group('DRM')
-
-        # Header
-        drm.attrs['UNIT'] = 'cm2'
-
-        axis_description = {'Ei': "Initial simulated energy",
-                            'NuLambda': "Location of the simulated source in the spacecraft coordinates",
-                            'Pol': "Polarization angle",
-                            'Em': "Measured energy",
-                            'Phi': "Compton angle",
-                            'PsiChi': "Location in the Compton Data Space",
-                            'SigmaTau': "Electron recoil angle",
-                            'Dist': "Distance from first interaction"
-                            }
-
-        #keep the same dimension order of the data
-        axes_to_write = ['NuLambda', 'Ei']
-
-        if has_polarization:
-            axes_to_write += ['Pol']
-
-        axes_to_write += ['Em', 'Phi', 'PsiChi']
-
-        if sparse:
-            drm.attrs['SPARSE'] = True
-
-            # singletos. Save space in dense
-            axes_to_write += ['SigmaTau', 'Dist']
-        else:
-            drm.attrs['SPARSE'] = False
-
-        axes = drm.create_group('AXES', track_order=True)
-
-        for axis in dr_area.axes[axes_to_write]:
-
-            axis_dataset = axes.create_dataset(axis.label,
-                                               data=axis.edges)
-
-            if axis.label in ['NuLambda', 'PsiChi', 'SigmaTau']:
-
-                # HEALPix
-                axis_dataset.attrs['TYPE'] = 'healpix'
-
-                axis_dataset.attrs['NSIDE'] = nside
-
-                axis_dataset.attrs['SCHEME'] = 'ring'
-
-            else:
-
-                # 1D
-                axis_dataset.attrs['TYPE'] = axis.axis_scale
-
-                if axis.label in ['Ei', 'Em']:
-                    axis_dataset.attrs['UNIT'] = 'keV'
-                    axis_dataset.attrs['TYPE'] = 'log'
-                elif axis.label in ['Phi', 'Pol']:
-                    axis_dataset.attrs['UNIT'] = 'deg'
-                    axis_dataset.attrs['TYPE'] = 'linear'
-                elif axis.label in ['Dist']:
-                    axis_dataset.attrs['UNIT'] = 'cm'
-                    axis_dataset.attrs['TYPE'] = 'linear'
-                else:
-                    raise ValueError("Shouldn't happend")
-
-            axis_dataset.attrs['DESCRIPTION'] = axis_description[axis.label]
-
-        # sparse matrice
-        if sparse:
-
-            progress_bar = tqdm(total=npix, desc="Progress", unit="nbpixel")
-            # Contents. Sparse arrays
-            coords = drm.create_dataset('BIN_NUMBERS',
-                                        (npix,),
-                                        dtype=h5.vlen_dtype(int),
-                                        compression="gzip")
-
-            data = drm.create_dataset('CONTENTS',
-                                      (npix,),
-                                      dtype=h5.vlen_dtype(float),
-                                      compression="gzip")
-
-            for b in range(npix):
-                # print(f"{b}/{npix}")
-
-                pix_slice = dr_area[{'NuLambda': b}]
-
-                coords[b] = pix_slice.coords.flatten()
-                data[b] = pix_slice.data
-                progress_bar.update(1)
-
-            progress_bar.close()
-
-        # non sparseOk g
-        else:
-
-            if 'Pol' in axes_to_write:
-
-                data = drm.create_dataset('CONTENTS',
-                                          data=np.transpose(dr_area.contents, axes=[1, 0, 2, 3, 4, 5]),
-                                          compression="gzip")
-
-            else:
-
-                data = drm.create_dataset('CONTENTS',
-                                          data=np.transpose(dr_area.contents, axes=[1, 0, 2, 3, 4]),
-                                          compression="gzip")
-
-        # close the .h5 file in write mode in order to reopen it in read mode after
-        f.close()
-
     @property
     def is_sparse(self):
         return self._sparse
@@ -941,7 +810,8 @@ def get_point_source_response(self,
                                   exposure_map = None,
                                   coord = None,
                                   scatt_map = None,
-                                  Earth_occ = True):
+                                  Earth_occ = True,
+                                  pol_convention = 'RelativeX'):
         """
         Convolve the all-sky detector response with exposure for a source at a given
         sky location.
@@ -961,6 +831,8 @@ def get_point_source_response(self,
             Option to include Earth occultation in the respeonce. 
             Default is True, in which case you can only pass one 
             coord, which must be the same as was used for the scatt map. 
+        pol_convention : str, optional
+            Polarization convention of response ('RelativeX', 'RelativeY', or 'RelativeZ') 
         
         Returns
         -------
@@ -1032,7 +904,7 @@ def get_point_source_response(self,
 
                 dr_pix.axes['PsiChi'].coordsys = SpacecraftFrame(attitude = att)
 
-                self._sum_rot_hist(dr_pix, psr, exposure)
+                self._sum_rot_hist(dr_pix, psr, exposure, coord, pol_convention)
 
             # Convert to PSR
             psr = tuple([PointSourceResponse(psr.axes[1:],
@@ -1216,14 +1088,14 @@ def merge_psr_to_extended_source_response(self, basename, coordsys = 'galactic',
         return extended_source_response
             
     @staticmethod
-    def _sum_rot_hist(h, h_new, exposure, axis = "PsiChi"):
+    def _sum_rot_hist(h, h_new, exposure, coord, pol_convention, axis = "PsiChi"):
         """
         Rotate a histogram with HealpixAxis h into the grid of h_new, and sum
         it up with the weight of exposure.
 
         Meant to rotate the PsiChi of a CDS from local to galactic
         """
-        
+
         axis_id = h.axes.label_to_index(axis)
 
         old_axes = h.axes
@@ -1235,11 +1107,35 @@ def _sum_rot_hist(h, h_new, exposure, axis = "PsiChi"):
         # Convolve
         # TODO: Change this to interpolation (pixels + weights)
         old_pixels = old_axis.find_bin(new_axis.pix2skycoord(np.arange(new_axis.nbins)))
+
+        if 'Pol' in h.axes.labels and h_new.axes[axis].coordsys.name == 'galactic' or h_new.axes[axis].coordsys.name == 'icrs':
+
+            from cosipy.polarization.polarization_angle import PolarizationAngle
+            from cosipy.polarization.conventions import IAUPolarizationConvention
+
+            pol_axis_id = h.axes.label_to_index('Pol')
+
+            old_pol_axis = h.axes[pol_axis_id]
+            new_pol_axis = h_new.axes[pol_axis_id]
+
+            old_pol_indices = []
+            for i in range(h_new.axes['Pol'].nbins):
+
+                pa = PolarizationAngle(h_new.axes['Pol'].centers.to_value(u.deg)[i] * u.deg, coord.transform_to('icrs'), convention=IAUPolarizationConvention())
+                pa_old = pa.transform_to(pol_convention, attitude=coord.attitude)
+
+                if pa_old.angle.deg == 180.:
+                    pa_old = PolarizationAngle(0. * u.deg, coord, convention=IAUPolarizationConvention())
+
+                old_pol_indices.append(old_pol_axis.find_bin(pa_old.angle))
+
+            old_pol_indices = np.array(old_pol_indices)
+
         # NOTE: there are some pixels that are duplicated, since the center 2 pixels
         # of the original grid can land within the boundaries of a single pixel
         # of the target grid. The following commented code fixes this, but it's slow, and
         # the effect is very small, so maybe not worth it
-        # nulambda_npix = h.axes['NuLamnda'].nbins    
+        # nulambda_npix = h.axes['NuLamnda'].nbins
         # new_norm = np.zeros(shape = nulambda_npix)
         # for p in old_pixels:
         #     h_slice = h[{axis:p}]
@@ -1251,14 +1147,29 @@ def _sum_rot_hist(h, h_new, exposure, axis = "PsiChi"):
 
             #h_new[{axis:new_pix}] += exposure * h[{axis: old_pix}] # * norm_corr
             # The following code does the same than the code above, but is faster
-            # However, it uses some internal functionality in histpy, which is bad practice
-            # TODO: change this in a future version. We might need to modify histpy so that
-            # this is not needed
-            
-            old_indices = tuple([slice(None)]*axis_id + [old_pix+1])
-            new_indices = tuple([slice(None)]*axis_id + [new_pix+1])
 
-            h_new._contents[new_indices] += exposure * h._contents[old_indices] # * norm_corr
+            if not 'Pol' in h.axes.labels:
+
+                old_index = (slice(None),)*axis_id + (old_pix,)
+                new_index = (slice(None),)*axis_id + (new_pix,)
+
+                h_new[new_index] += exposure * u.s * h[old_index] # * norm_corr
+
+            else:
+
+                for old_pol_bin,new_pol_bin in zip(old_pol_indices,range(new_pol_axis.nbins)):
+
+                    if pol_axis_id < axis_id:
+
+                        old_index = (slice(None),)*pol_axis_id + (old_pol_bin,) + (slice(None),)*(axis_id-pol_axis_id-1) + (old_pix,)
+                        new_index = (slice(None),)*pol_axis_id + (new_pol_bin,) + (slice(None),)*(axis_id-pol_axis_id-1) + (new_pix,)
+                
+                    else:
+
+                        old_index = (slice(None),)*axis_id + (old_pix,) + (slice(None),)*(pol_axis_id-axis_id-1) + (old_pol_bin,)
+                        new_index = (slice(None),)*axis_id + (new_pix,) + (slice(None),)*(pol_axis_id-axis_id-1) + (new_pol_bin,)
+
+                    h_new[new_index] += exposure * u.s * h[old_index] # * norm_corr
                         
 
     def __str__(self):
diff --git a/cosipy/response/PointSourceResponse.py b/cosipy/response/PointSourceResponse.py
index f32a83dd..56eaaef5 100644
--- a/cosipy/response/PointSourceResponse.py
+++ b/cosipy/response/PointSourceResponse.py
@@ -2,12 +2,8 @@
 
 import numpy as np
 import astropy.units as u
-#from astropy.units import Quantity
-#from scipy import integrate
 from scoords import SpacecraftFrame, Attitude
 
-#from threeML import DiracDelta, Constant, Line, Quadratic, Cubic, Quartic, StepFunction, StepFunctionUpper, Cosine_Prior, Uniform_prior, PhAbs, Gaussian
-
 from .functions import get_integrated_spectral_model
 
 import logging
@@ -47,7 +43,7 @@ def photon_energy_axis(self):
         
         return self.axes['Ei']
        
-    def get_expectation(self, spectrum, polarization_level=None, polarization_angle=None, scatt_map=None, convention=None):
+    def get_expectation(self, spectrum, polarization=None):
         """
         Convolve the response with a spectral (and optionally, polarization) hypothesis to obtain the expected
         excess counts from the source.
@@ -56,14 +52,8 @@ def get_expectation(self, spectrum, polarization_level=None, polarization_angle=
         ----------
         spectrum : :py:class:`threeML.Model`
             Spectral hypothesis.
-        polarization_level : float, optional
-            Polarization level (between 0 and 1).
-        polarization_angle : :py:class:`cosipy.polarization.polarization_angle.PolarizationAngle`, optional
-            Polarization angle. If in the spacecraft frame, the angle must have the same convention as the response.
-        scatt_map : :py:class:`cosipy.spacecraftfile.scatt_map.SpacecraftAttitudeMap`, optional
-            Spacecraft attitude map. Only needed for polarization angle provided in galactic reference frame.
-        convention : str, optional
-            Polarization angle convention of response ('RelativeX', 'RelativeY', or 'RelativeZ'). Only needed for polarization angle provided in galactic reference frame.
+        polarization : 'astromodels.core.polarization.LinearPolarization', optional
+            Polarization angle and degree. The angle is assumed to have same convention as point source response.
         
         Returns
         -------
@@ -71,130 +61,38 @@ def get_expectation(self, spectrum, polarization_level=None, polarization_angle=
              Histogram with the expected counts on each analysis bin
         """
 
-        if polarization_level == None:
-
-            if polarization_angle == None:
-
-                if 'Pol' in self.axes.labels:
-
-                    raise RuntimeError("Must include polarization in point source response if using polarization response")
-
-                else:
+        if polarization is None:
 
-                    contents = self.contents
-                    axes = self.axes[1:]
+            if 'Pol' in self.axes.labels:
 
-            else:
+                raise RuntimeError("Must include polarization in point source response if using polarization response")
 
-                raise RuntimeError("Must provide both polarization level and angle")
+            contents = self.contents
+            axes = self.axes[1:]
 
-        elif polarization_angle != None:
-
-            from cosipy.polarization.polarization_angle import PolarizationAngle
-            from cosipy.polarization.conventions import MEGAlibRelativeX, MEGAlibRelativeY, MEGAlibRelativeZ, IAUPolarizationConvention
-
-            if polarization_level > 1.0 or polarization_level < 0:
-
-                raise RuntimeError("Polarization level must be a fraction between 0 and 1")
+        else:
 
-            elif not 'Pol' in self.axes.labels:
+            if not 'Pol' in self.axes.labels:
                 
                 raise RuntimeError("Response must have polarization angle axis to include polarization in point source response")
 
-            elif type(polarization_angle.convention.frame) == SpacecraftFrame:
-
-                logger.warning("The response must have the same polarization convention as the provided polarization angle, or the result will be incorrect!")
-
-                if polarization_angle.angle.deg == 180.:
-                    polarization_angle = PolarizationAngle(0. * u.deg, polarization_angle.skycoord, convention=polarization_angle.convention)
-
-                polarization_angle_components = []
-
-                for i in range(self.axes['Pol'].nbins):
-
-                    polarization_angle_components.append(self.slice[{'Pol':slice(i,i+1)}].project('Ei', 'Em', 'Phi', 'PsiChi'))
-
-                    if polarization_angle.angle.deg >= self.axes['Pol'].edges.to_value(u.deg)[i] and polarization_angle.angle.deg < self.axes['Pol'].edges.to_value(u.deg)[i+1]:
-                        polarized_component = polarization_angle_components[i].contents
-
-                unpolarized_component = polarization_angle_components[0].contents
-
-                for i in range(len(polarization_angle_components) - 1):
-
-                    unpolarized_component += polarization_angle_components[i+1].contents
-
-                polarized_component /= np.sum(polarized_component.value)
-                unpolarized_component /= np.sum(unpolarized_component.value)
-
-                polarization_hist = (polarization_level * polarized_component) + ((1 - polarization_level) * unpolarized_component)
-                polarization_hist *= np.sum(self.contents) / np.sum(polarization_hist)
+            polarization_angle = polarization.angle.value
+            polarization_level = polarization.degree.value / 100.
 
-                contents = polarization_hist
-                axes = self.project('Ei', 'Em', 'Phi', 'PsiChi').axes[1:]
+            if polarization_angle == 180.:
+                polarization_angle = 0.
 
-            elif type(scatt_map) != None and convention != None:
+            unpolarized_weights = np.full(self.axes['Pol'].nbins, (1. - polarization_level) / self.axes['Pol'].nbins)
+            polarized_weights = np.zeros(self.axes['Pol'].nbins)
 
-                polarization_angle_components = np.empty(self.axes['Pol'].nbins, dtype=Histogram)
+            polarization_bin_index = self.axes['Pol'].find_bin(polarization_angle * u.deg)
+            polarized_weights[polarization_bin_index] = polarization_level
 
-                if polarization_angle.angle.deg == 180.:
-                    polarization_angle = PolarizationAngle(0. * u.deg, polarization_angle.skycoord, convention=polarization_angle.convention)
+            weights = unpolarized_weights + polarized_weights
 
-                for i in range(self.axes['Pol'].nbins):
-
-                    response_slice = self.slice[{'Pol':slice(i,i+1)}].project('Ei', 'Em', 'Phi', 'PsiChi')
-
-                    for j, (pixels, exposure) in enumerate(zip(scatt_map.contents.coords.transpose(), scatt_map.contents.data)):
-
-                        attitude = Attitude.from_axes(x=scatt_map.axes['x'].pix2skycoord(pixels[0]), y=scatt_map.axes['y'].pix2skycoord(pixels[1]))
-
-                        if convention == 'RelativeX':
-                            this_convention = MEGAlibRelativeX(attitude=attitude)
-                        elif convention == 'RelativeY':
-                            this_convention = MEGAlibRelativeY(attitude=attitude)
-                        elif convention == 'RelativeZ':
-                            this_convention = MEGAlibRelativeZ(attitude=attitude)
-                        else:
-                            raise RuntimeError("Response convention must be 'RelativeX', 'RelativeY', or 'RelativeZ'")
-
-                        polarization_angle_galactic = PolarizationAngle(self.axes['Pol'].centers.to_value(u.deg)[i] * u.deg, polarization_angle.skycoord, convention=this_convention).transform_to(polarization_angle.convention)
-
-                        if polarization_angle_galactic.angle.deg == 180.:
-                            polarization_angle_galactic = PolarizationAngle(0. * u.deg, polarization_angle_galactic.skycoord, convention=polarization_angle_galactic.convention)
-
-                        polarization_angle_index = np.max(np.where(polarization_angle_galactic.angle.deg >= self.axes['Pol'].edges.to_value(u.deg)))
-
-                        if hasattr(polarization_angle_components[polarization_angle_index], 'axes'):
-                            polarization_angle_components[polarization_angle_index] += response_slice * exposure / np.sum(scatt_map.project('x'))
-                        else:
-                            polarization_angle_components[polarization_angle_index] = response_slice * exposure / np.sum(scatt_map.project('x'))
-
-                for i in range(self.axes['Pol'].nbins):
-
-                    if polarization_angle.angle.deg >= self.axes['Pol'].edges.to_value(u.deg)[i] and polarization_angle.angle.deg < self.axes['Pol'].edges.to_value(u.deg)[i+1]:
-                        polarized_component = polarization_angle_components[i].contents
-
-                unpolarized_component = polarization_angle_components[0].contents
-
-                for i in range(len(polarization_angle_components) - 1):
-
-                    unpolarized_component += polarization_angle_components[i+1].contents
-
-                polarized_component /= np.sum(polarized_component.value)
-                unpolarized_component /= np.sum(unpolarized_component.value)
-
-                polarization_hist = (polarization_level * polarized_component) + ((1 - polarization_level) * unpolarized_component)
-                polarization_hist *= np.sum(self.contents) / np.sum(polarization_hist)
-
-                contents = polarization_hist
-                axes = self.project('Ei', 'Em', 'Phi', 'PsiChi').axes[1:]
-
-            else:
-
-                raise RuntimeError("Scatt map and response convention must be provided to include polarization in galactic coordinates in point source response")
-
-        else:
+            contents = np.tensordot(weights, self.contents, axes=([0], [self.axes.label_to_index('Pol')]))
 
-            raise RuntimeError("Must provide both polarization level and angle to include polarization in point source response")
+            axes = self.axes['Em', 'Phi', 'PsiChi']
 
         energy_axis = self.photon_energy_axis
 
diff --git a/cosipy/threeml/COSILike.py b/cosipy/threeml/COSILike.py
index 9ff367af..80536227 100644
--- a/cosipy/threeml/COSILike.py
+++ b/cosipy/threeml/COSILike.py
@@ -215,10 +215,10 @@ def set_model(self, model):
 
                     if self._coordsys == 'spacecraftframe':
                         dwell_time_map = self._get_dwell_time_map(coord)
-                        self._psr[name] = self._dr.get_point_source_response(exposure_map=dwell_time_map)
+                        self._psr[name] = self._dr.get_point_source_response(exposure_map=dwell_time_map, pol_convention=self._pa_convention)
                     elif self._coordsys == 'galactic':
                         scatt_map = self._get_scatt_map(coord)
-                        self._psr[name] = self._dr.get_point_source_response(coord=coord, scatt_map=scatt_map)
+                        self._psr[name] = self._dr.get_point_source_response(coord=coord, scatt_map=scatt_map, pol_convention=self._pa_convention)
                     else:
                         raise RuntimeError("Unknown coordinate system")
 
@@ -237,10 +237,10 @@ def set_model(self, model):
                 
                 if self._coordsys == 'spacecraftframe':
                     dwell_time_map = self._get_dwell_time_map(coord)
-                    self._psr[name] = self._dr.get_point_source_response(exposure_map=dwell_time_map)
+                    self._psr[name] = self._dr.get_point_source_response(exposure_map=dwell_time_map, pol_convention=self._pa_convention)
                 elif self._coordsys == 'galactic':
                     scatt_map = self._get_scatt_map(coord)
-                    self._psr[name] = self._dr.get_point_source_response(coord=coord, scatt_map=scatt_map)
+                    self._psr[name] = self._dr.get_point_source_response(coord=coord, scatt_map=scatt_map, pol_convention=self._pa_convention)
                 else:
                     raise RuntimeError("Unknown coordinate system")
 
@@ -271,10 +271,10 @@ def set_model(self, model):
                         polarization_level = source.components['grb'].polarization.degree.value / 100.
                         polarization_angle = PolarizationAngle(coords.Angle(source.components['grb'].polarization.angle.value, unit=u.deg), source.position.sky_coord, convention=self._pa_convention)
                         if self._coordsys == 'spacecraftframe':
-                            this_expectation = self._psr[name].get_expectation(spectrum, polarization_level, polarization_angle)
+                            this_expectation = self._psr[name].get_expectation(spectrum, source.components['grb'].polarization)
                         elif self._coordsys == 'galactic':
                             scatt_map = self._get_scatt_map(source.position.sky_coord)
-                            this_expectation = self._psr[name].get_expectation(spectrum, polarization_level, polarization_angle, scatt_map, self._response_pa_convention)
+                            this_expectation = self._psr[name].get_expectation(spectrum, source.components['grb'].polarization)
                         else:
                             raise RuntimeError("Unknown coordinate system")