Merge branch 'master' into fix_urllib3

.github/workflows/code_style.yml

@@ -19,7 +19,7 @@ jobs:
         run: |
              bash .github/scripts/pre_pyflakes.sh
       - name: Set up Python
-        uses: actions/setup-python@v4.5.0
+        uses: actions/setup-python@v4.6.0
         with:
           python-version: 3.8
       - name: patch reviewdog

.github/workflows/pypi_install.yml

@@ -13,7 +13,7 @@ jobs:
     steps:
       # Setup steps
       - name: Setup python
-        uses: actions/setup-python@v4.5.0
+        uses: actions/setup-python@v4.6.0
         with:
           python-version: '3.8'
 

.github/workflows/pytest.yml

@@ -50,7 +50,7 @@ jobs:
         uses: actions/checkout@v3
 
       - name: Setup python
-        uses: actions/setup-python@v4.5.0
+        uses: actions/setup-python@v4.6.0
         with:
           python-version: ${{ matrix.python-version }}
 

.github/workflows/test_install.yml

@@ -23,7 +23,7 @@ jobs:
         python-version: [3.8]
     steps:
       - name: Setup python
-        uses: actions/setup-python@v4.5.0
+        uses: actions/setup-python@v4.6.0
         with:
           python-version: ${{ matrix.python-version }}
       - name: Checkout repo

HISTORY.md

@@ -1,6 +1,5 @@
 v2.0.7 / 2023-04-25
 -------------------
-## What's Changed
 * Bootstrax target removal after failures by @cfuselli in https://github.com/XENONnT/straxen/pull/1145
 * reforming _raw_path and _processed_path by @FaroutYLq in https://github.com/XENONnT/straxen/pull/1149
 * Adding correction of Z position due to non-uniform drift velocity by @terliuk in https://github.com/XENONnT/straxen/pull/1148
@@ -10,7 +9,7 @@ v2.0.7 / 2023-04-25
 * Use zstd as compressor of peaks by @dachengx in https://github.com/XENONnT/straxen/pull/1154
 * Bump sphinx from 5.3.0 to 6.2.0 in /extra_requirements by @dependabot in https://github.com/XENONnT/straxen/pull/1161
 
-## New Contributors
+New Contributors
 * @cfuselli made their first contribution in https://github.com/XENONnT/straxen/pull/1145
 * @matteoguida made their first contribution in https://github.com/XENONnT/straxen/pull/1146
 * @hmdyt made their first contribution in https://github.com/XENONnT/straxen/pull/1159
@@ -20,12 +19,11 @@ v2.0.7 / 2023-04-25
 
 v2.0.6 / 2023-03-08
 -------------------
-## What's Changed
 * Bump supercharge/mongodb-github-action from 1.8.0 to 1.9.0 by @dependabot in https://github.com/XENONnT/straxen/pull/1140
 * Small patches to restrax module by @JoranAngevaare in https://github.com/XENONnT/straxen/pull/1143, d04a3428c52c159577b61af2a28ddd0af5652027, 602b807291211f083c8f54df6768b8198fbf6b55
 * Ms events by @michaweiss89 and @HenningSE in https://github.com/XENONnT/straxen/pull/1080
 
-## New Contributors
+New Contributors
 * @michaweiss89 made their first contribution in https://github.com/XENONnT/straxen/pull/1080
 
 **Full Changelog**: https://github.com/XENONnT/straxen/compare/v2.0.5...v2.0.6
@@ -36,7 +34,6 @@ Notes:
 
 v2.0.5 / 2023-02-24
 -------------------
-## What's Changed
 * fix xedocs for testing by @JoranAngevaare in https://github.com/XENONnT/straxen/pull/1139
 * Restart python style guide by @JoranAngevaare in https://github.com/XENONnT/straxen/pull/1138
 * Decrease number of chunks by @JoranAngevaare in https://github.com/XENONnT/straxen/pull/1123
@@ -983,7 +980,7 @@ patches and fixes:
 - Bugfix in clean_up_empty_records (#210)
 
 
-0.10.0 / 2020-08-187
+0.10.0 / 2020-08-18
 --------------------
 - Neutron-veto integration (#86)
 - Processing for high energy channels (#161, #176)

requirements.txt

@@ -12,6 +12,6 @@ numpy
 packaging
 pymongo<4.0.0
 requests
-strax>=1.4.0
+strax>=1.5.0
 utilix>=0.5.3
 xedocs

straxen/plugins/events/event_basics.py

@@ -19,7 +19,7 @@ class EventBasics(strax.Plugin):
     alternative S2 is selected as the largest S2 other than main S2
     in the time window [main S1 time, main S1 time + max drift time].
     """
-    __version__ = '1.3.1'
+    __version__ = '1.3.2'
 
     depends_on = ('events',
                   'peak_basics',
@@ -76,6 +76,17 @@ def infer_dtype(self):
 
         dtype += self._get_si_dtypes(self.peak_properties)
 
+        dtype += [
+            (f's1_max_diff', np.int32,
+             f'Main S1 largest time difference between apexes of hits [ns]'),
+            (f'alt_s1_max_diff', np.int32,
+             f'Alternate S1 largest time difference between apexes of hits [ns]'),
+            (f's1_min_diff', np.int32,
+             f'Main S1 smallest time difference between apexes of hits [ns]'),
+            (f'alt_s1_min_diff', np.int32,
+             f'Alternate S1 smallest time difference between apexes of hits [ns]'),
+        ]
+
         dtype += [
             (f's2_x', np.float32,
              f'Main S2 reconstructed X position, uncorrected [cm]'),
@@ -253,7 +264,9 @@ def fill_result_i(self, event, peaks):
             # Largest index 0 -> main sx, 1 -> alt sx
             for largest_index, main_or_alt in enumerate(['s', 'alt_s']):
                 peak_properties_to_save = [name for name, _, _ in self.peak_properties]
-                if s_i == 2:
+                if s_i == 1:
+                    peak_properties_to_save += ['max_diff', 'min_diff']
+                elif s_i == 2:
                     peak_properties_to_save += ['x', 'y']
                     peak_properties_to_save += self.posrec_save
                 field_names = [f'{main_or_alt}{s_i}_{name}' for name in peak_properties_to_save]

straxen/plugins/merged_s2s/merged_s2s.py

@@ -15,7 +15,7 @@ class MergedS2s(strax.OverlapWindowPlugin):
     Merge together peaklets if peak finding favours that they would
     form a single peak instead.
     """
-    __version__ = '1.0.0'
+    __version__ = '1.0.1'
 
     depends_on = ('peaklets', 'peaklet_classification', 'lone_hits')
     data_kind = 'merged_s2s'
@@ -133,7 +133,8 @@ def compute(self, peaklets, lone_hits):
     @numba.njit(cache=True, nogil=True)
     def get_merge_instructions(
             peaklet_starts, peaklet_ends, areas, types,
-            gap_thresholds, max_duration, max_gap, max_area):
+            gap_thresholds, max_duration, max_gap, max_area,
+            sort_kind='mergesort'):
         """
         Finding the group of peaklets to merge. To do this start with the
         smallest gaps and keep merging until the new, merged S2 has such a
@@ -149,7 +150,7 @@ def get_merge_instructions(
         peaklet_start_index = np.arange(len(peaklet_starts))
         peaklet_end_index = np.arange(len(peaklet_starts))
 
-        for gap_i in np.argsort(peaklet_gaps):
+        for gap_i in np.argsort(peaklet_gaps, kind=sort_kind):
             start_idx = peaklet_start_index[gap_i]
             inclusive_end_idx = peaklet_end_index[gap_i + 1]
             sum_area = np.sum(areas[start_idx:inclusive_end_idx + 1])

straxen/plugins/peaklets/peaklets.py

@@ -3,6 +3,7 @@
 import strax
 from immutabledict import immutabledict
 from strax.processing.general import _touching_windows
+from strax.dtypes import DIGITAL_SUM_WAVEFORM_CHANNEL
 import straxen
 
 
@@ -37,7 +38,7 @@ class Peaklets(strax.Plugin):
     parallel = 'process'
     compressor = 'zstd'
 
-    __version__ = '1.0.2'
+    __version__ = '1.1.0'
 
     peaklet_gap_threshold = straxen.URLConfig(
         default=700, infer_type=False,
@@ -230,7 +231,7 @@ def compute(self, records, start, end):
         del hits
 
         hitlets['time'] -= (hitlets['left'] - hitlets['left_integration']) * hitlets['dt']
-        hitlets['length'] = (hitlets['right_integration'] - hitlets['left_integration'])
+        hitlets['length'] = hitlets['right_integration'] - hitlets['left_integration']
         hitlets = strax.sort_by_time(hitlets)
         rlinks = strax.record_links(records)
 
@@ -289,15 +290,16 @@ def compute(self, records, start, end):
         peaklet_max_times = (
             peaklets['time']
             + np.argmax(peaklets['data'], axis=1) * peaklets['dt'])
-        tight_coincidence_channel = get_tight_coin(
+        peaklets['tight_coincidence'] = get_tight_coin(
             sorted_hit_max_times,
             sorted_hit_channels,
             peaklet_max_times,
             self.tight_coincidence_window_left,
             self.tight_coincidence_window_right,
             self.channel_range)
 
-        peaklets['tight_coincidence'] = tight_coincidence_channel
+        # Add max and min time difference between apexes of hits
+        self.add_hit_features(hitlets, hit_max_times, peaklets)
 
         if self.diagnose_sorting and len(r):
             assert np.diff(r['time']).min(initial=1) >= 0, "Records not sorted"
@@ -314,6 +316,16 @@ def compute(self, records, start, end):
         if n_top_pmts_if_digitize_top <= 0:
             peaklets = drop_data_top_field(peaklets, self.dtype_for('peaklets'))
 
+        # Check channel of peaklets
+        peaklets_unique_channel = np.unique(peaklets['channel'])
+        if (peaklets_unique_channel == DIGITAL_SUM_WAVEFORM_CHANNEL).sum() > 1:
+            raise ValueError(
+                f'Found channel number of peaklets other than {DIGITAL_SUM_WAVEFORM_CHANNEL}')
+        # Check tight_coincidence
+        if not np.all(peaklets['n_hits'] >= peaklets['tight_coincidence']):
+            raise ValueError(
+                f'Found n_hits less than tight_coincidence')
+
         return dict(peaklets=peaklets,
                     lone_hits=lone_hits)
 
@@ -368,6 +380,31 @@ def create_outside_peaks_region(peaklets, start, end):
         outside_peaks[-1]['endtime'] = end
         return outside_peaks
 
+    @staticmethod
+    def add_hit_features(hitlets, hit_max_times, peaklets):
+        """
+        Create hits timing features
+        :param hitlets_max: hitlets with only max height time.
+        :param peaklets: Peaklets for which intervals should be computed.
+        :return: array of peaklet_timing dtype.
+        """
+        hits_w_max = np.zeros(
+            len(hitlets),
+            strax.merged_dtype(
+                [np.dtype([('max_time', np.int64)]), np.dtype(strax.time_fields)]))
+        hits_w_max['time'] = hitlets['time']
+        hits_w_max['endtime'] = strax.endtime(hitlets)
+        hits_w_max['max_time'] = hit_max_times
+        split_hits = strax.split_by_containment(hits_w_max, peaklets)
+        for peaklet, h_max in zip(peaklets, split_hits):
+            max_time_diff = np.diff(np.sort(h_max['max_time']))
+            if len(max_time_diff) > 0:
+                peaklet['max_diff'] = max_time_diff.max()
+                peaklet['min_diff'] = max_time_diff.min()
+            else:
+                peaklet['max_diff'] = -1
+                peaklet['min_diff'] = -1
+
 def drop_data_top_field(peaklets, goal_dtype, _name_function= '_drop_data_top_field'):
     """Return peaklets without the data_top field"""
     peaklets_without_top_field = np.zeros(len(peaklets), dtype=goal_dtype)

straxen/plugins/peaks/peak_basics.py

@@ -14,7 +14,7 @@ class PeakBasics(strax.Plugin):
     arrays.
     NB: This plugin can therefore be loaded as a pandas DataFrame.
     """
-    __version__ = "0.1.3"
+    __version__ = '0.1.4'
     parallel = True
     depends_on = ('peaks',)
     provides = 'peak_basics'
@@ -53,7 +53,11 @@ class PeakBasics(strax.Plugin):
         (('Number of PMTs with hits within tight range of mean',
           'tight_coincidence'), np.int16),
         (('Classification of the peak(let)',
-          'type'), np.int8)
+          'type'), np.int8),
+        (('Largest time difference between apexes of hits inside peak [ns]',
+          'max_diff'), np.int32),
+        (('Smallest time difference between apexes of hits inside peak [ns]',
+          'min_diff'), np.int32),
     ]
 
     n_top_pmts = straxen.URLConfig(default=straxen.n_top_pmts, infer_type=False,
@@ -68,7 +72,8 @@ class PeakBasics(strax.Plugin):
     def compute(self, peaks):
         p = peaks
         r = np.zeros(len(p), self.dtype)
-        for q in 'time length dt area type'.split():
+        needed_fields = 'time length dt area type max_diff min_diff'
+        for q in needed_fields.split():
             r[q] = p[q]
         r['endtime'] = p['time'] + p['dt'] * p['length']
         r['n_channels'] = (p['area_per_channel'] > 0).sum(axis=1)