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Fix two bugs in new S1 AFT and pattern likelihood calculations #183

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merged 3 commits into from
Dec 19, 2017
Merged

Fix two bugs in new S1 AFT and pattern likelihood calculations #183

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ded03f5
Fix bugs in event indexing and PMT selection
pdeperio Dec 19, 2017
16fe89a
Increment version
pdeperio Dec 19, 2017
48544ed
Fix version oops
pdeperio Dec 19, 2017
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42 changes: 22 additions & 20 deletions hax/treemakers/posrec.py
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Original file line number Diff line number Diff line change
Expand Up @@ -34,7 +34,7 @@ class PositionReconstruction(TreeMaker):
- s1_area_upper_injection_fraction: s1 area fraction near Rn220 injection points (near PMT 131)
- s1_area_lower_injection_fraction: s1 area fraction near Rn220 injection points (near PMT 243)
"""
__version__ = '0.16'
__version__ = '0.17'
extra_branches = ['peaks.area_per_channel[260]',
'peaks.hits_per_channel[260]',
'peaks.n_saturated_per_channel[260]',
Expand Down Expand Up @@ -175,10 +175,10 @@ def extract_data(self, event):
self.nn_tensorflow,
self.loaded_tfnn_model_json_name)

e = event.event_number
event_num = event.event_number

try:
i = self.indices.index(e)
event_index = self.indices.index(event_num)
except Exception:
return event_data

Expand All @@ -189,8 +189,8 @@ def extract_data(self, event):
# Position reconstruction based on NN from TensorFlow
s2apc = np.array(list(s2.area_per_channel))
s2apc_clean = []
for i, s2_t in enumerate(s2apc):
if i not in self.list_bad_pmts and i < self.ntop_pmts:
for ipmt, s2_t in enumerate(s2apc):
if ipmt not in self.list_bad_pmts and ipmt < self.ntop_pmts:
s2apc_clean.append(s2_t)
s2apc_clean = np.asarray(s2apc_clean)
s2apc_clean_norm = s2apc_clean / s2apc_clean.sum()
Expand Down Expand Up @@ -218,7 +218,7 @@ def extract_data(self, event):
size_top = s1.area * s1.area_fraction_top
size_tot = s1.area

aft = self.s1_aft_map.get_value(self.x[i], self.y[i], self.z[i])
aft = self.s1_aft_map.get_value(self.x[event_index], self.y[event_index], self.z[event_index])
event_data['s1_area_fraction_top_probability_hax'] = binom_test_pax(size_top, size_tot, aft)

# Now do s1_pattern_fit
Expand All @@ -232,38 +232,40 @@ def extract_data(self, event):
confused_s1_channels.append(a)

try:

# Create PMT array of booleans for use in likelihood calculation
is_pmt_in = np.ones(len(self.tpc_channels), dtype=bool) # Default True
is_pmt_in[confused_s1_channels] = False # Ignore saturated channels

event_data['s1_pattern_fit_hax'] = self.pattern_fitter.compute_gof(
(self.x[i], self.y[i], self.z[i]),
(self.x[event_index], self.y[event_index], self.z[event_index]),
apc[self.tpc_channels],
pmt_selection=np.setdiff1d(self.tpc_channels,
confused_s1_channels),
pmt_selection=is_pmt_in,
statistic=self.statistic)

event_data['s1_pattern_fit_hits_hax'] = self.pattern_fitter.compute_gof(
(self.x[i], self.y[i], self.z[i]),
(self.x[event_index], self.y[event_index], self.z[event_index]),
hpc[self.tpc_channels],
pmt_selection=np.setdiff1d(self.tpc_channels,
confused_s1_channels),
pmt_selection=is_pmt_in,
statistic=self.statistic)

pmts_bottom = np.setdiff1d(self.tpc_channels, confused_s1_channels)
pmts_bottom[self.pax_config['DEFAULT']['channels_top']] = 0
# Switch to bottom PMTs only
is_pmt_in[self.pax_config['DEFAULT']['channels_top']] = False

event_data['s1_pattern_fit_bottom_hax'] = self.pattern_fitter.compute_gof(
(self.x[i], self.y[i], self.z[i]),
(self.x[event_index], self.y[event_index], self.z[event_index]),
apc[self.tpc_channels],
pmt_selection=pmts_bottom,
pmt_selection=is_pmt_in,
statistic=self.statistic)

event_data['s1_pattern_fit_bottom_hits_hax'] = self.pattern_fitter.compute_gof(
(self.x[i], self.y[i], self.z[i]),
(self.x[event_index], self.y[event_index], self.z[event_index]),
hpc[self.tpc_channels],
pmt_selection=pmts_bottom,
pmt_selection=is_pmt_in,
statistic=self.statistic)

except exceptions.CoordinateOutOfRangeException as E:
except exceptions.CoordinateOutOfRangeException as _:
# pax does this too. happens when event out of TPC (usually z)
log.error(E)
return event_data

return event_data