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Fix event weights in weighted reflectivity calculation #52

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Dec 5, 2024
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Fix event weights in weighted reflectivity calculation #52

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16 changes: 9 additions & 7 deletions reduction/lr_reduction/event_reduction.py
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Original file line number Diff line number Diff line change
Expand Up @@ -482,8 +482,8 @@ def specular_weighted(self, q_summing=True, bck_in_q=False):
"""
# Event weights for normalization
db_charge = self._ws_db.getRun().getProtonCharge()
wl_events = self._get_events(self._ws_db, self.norm_peak, self.norm_low_res)
wl_dist, wl_bins = np.histogram(wl_events, bins=60)
wl_events, wl_weights = self._get_events(self._ws_db, self.norm_peak, self.norm_low_res)
wl_dist, wl_bins = np.histogram(wl_events, bins=100, weights=wl_weights)
_bin_width = wl_bins[1:] - wl_bins[:-1]
wl_dist = wl_dist/db_charge/_bin_width
wl_middle = [(wl_bins[i+1]+wl_bins[i])/2.0 for i in range(len(wl_bins)-1)]
Expand Down Expand Up @@ -671,6 +671,7 @@ def _get_events(self, ws, peak, low_res):
Return an array of wavelengths for a given workspace.
"""
wl_events = np.asarray([])
wl_weights = np.asarray([])

for i in range(low_res[0], int(low_res[1]+1)):
for j in range(peak[0], int(peak[1]+1)):
Expand All @@ -685,8 +686,9 @@ def _get_events(self, ws, peak, low_res):
tofs = self.emission_time_correction(ws, tofs)
wl_list = tofs / self.constant
wl_events = np.concatenate((wl_events, wl_list))

return wl_events
weights = evt_list.getWeights()
wl_weights = np.concatenate((wl_weights, weights))
return wl_events, wl_weights

def off_specular(self, x_axis=None, x_min=-0.015, x_max=0.015, x_npts=50,
z_min=None, z_max=None, z_npts=-120, bck_in_q=None):
Expand Down Expand Up @@ -714,8 +716,8 @@ def off_specular(self, x_axis=None, x_min=-0.015, x_max=0.015, x_npts=50,
else:
qx_bins = np.logspace(np.log10(x_min), np.log10(x_max), num=np.abs(x_npts))

wl_events = self._get_events(self._ws_db, self.norm_peak, self.norm_low_res)
wl_dist, wl_bins = np.histogram(wl_events, bins=60)
wl_events, wl_weights = self._get_events(self._ws_db, self.norm_peak, self.norm_low_res)
wl_dist, wl_bins = np.histogram(wl_events, bins=100, weights=wl_weights)
wl_middle = [(wl_bins[i+1]+wl_bins[i])/2.0 for i in range(len(wl_bins)-1)]

_refl, _d_refl = self._off_specular(self._ws_sc, wl_dist, wl_middle, qx_bins, qz_bins,
Expand Down Expand Up @@ -767,7 +769,7 @@ def _off_specular(self, ws, wl_dist, wl_bins, x_bins, z_bins, peak_position, the
# Sign will depend on reflect up or down
ths_value = ws.getRun()['ths'].value[-1]
delta_theta_f *= np.sign(ths_value)
theta_f = theta + delta_theta_f
theta_f = theta - delta_theta_f

qz = k * (np.sin(theta_f) + np.sin(theta))
qz = np.fabs(qz)
Expand Down
2 changes: 1 addition & 1 deletion reduction/lr_reduction/workflow.py
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Original file line number Diff line number Diff line change
Expand Up @@ -44,7 +44,7 @@ def reduce(ws, template_file, output_dir, average_overlap=False,
# Call the reduction using the template
qz_mid, refl, d_refl, meta_data = template.process_from_template_ws(ws, template_data,
q_summing=q_summing,
tof_weighted=False,
tof_weighted=bck_in_q,
clean=q_summing,
bck_in_q=bck_in_q,
info=True)
Expand Down
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