Inherit center_time from peaklets (#102)

* Inherit `center_time` from `peaklets`

Following XENONnT/straxen#1503

* Debug for requirements installation

* Update version of plugin

.github/workflows/pytest.yml

@@ -28,7 +28,7 @@ jobs:
       fail-fast: false
       matrix:
         os: [ "ubuntu-latest" ]
-        python-version: [ "3.10", "3.11" ]
+        python-version: [ "3.11" ]
         test: [ "coveralls" ]
 
     steps:
@@ -47,12 +47,7 @@ jobs:
           python -m pip install --upgrade pip
           python -m pip install pytest coverage coveralls
 
-      - name: Install requirements for Python 3.10
-        if: matrix.python-version == '3.10'
-        run: pip install git+https://github.com/XENONnT/[email protected] --force-reinstall
-
-      - name: Install requirements for Python 3.11
-        if: matrix.python-version == '3.11'
+      - name: Install requirements
         run: pip install git+https://github.com/XENONnT/base_environment.git --force-reinstall
 
       - name: Install strax and straxen
@@ -85,10 +80,6 @@ jobs:
           SCADA_LOGIN_URL: ${{ secrets.SCADA_LOGIN_URL }}
           SCADA_PWD: ${{ secrets.SCADA_PWD }}
 
-      - name: Install requirements
-        run: |
-          pip install -r extra_requirements/requirements-tests.txt
-
       - name: Install Axidence
         run: |
           pip install .

axidence/plugins/pairing/peaks_paired.py

@@ -13,7 +13,7 @@
 
 
 class PeaksPaired(ExhaustPlugin, DownChunkingPlugin):
-    __version__ = "0.0.1"
+    __version__ = "0.0.2"
     depends_on = (
         "run_meta",
         "isolated_s1",
@@ -447,11 +447,13 @@ def shadow_matching(
             s2_group_index = np.hstack([group[1] for group in group_index_list]).astype(int)
             drift_time = np.hstack([group[2] for group in group_index_list]).astype(int)
             assert len(s1_group_index) == len(s2_group_index)
-        return paring_rate_full, (
-            s1["group_number"][s1_group_index],
-            s2["group_number"][s2_group_index],
-            drift_time,
-        )
+            return paring_rate_full, (
+                s1["group_number"][s1_group_index],
+                s2["group_number"][s2_group_index],
+                drift_time,
+            )
+        else:
+            return paring_rate_full
 
     def split_chunks(self, n_peaks):
         # divide results into chunks
@@ -509,6 +511,7 @@ def build_arrays(
             _array[0]["origin_center_time"] = s1["center_time"][s1_index]
             _array[0]["origin_n_competing"] = s1["n_competing"][s1_index]
             _array[0]["origin_group_type"] = 1
+            _array[0]["center_time"] = s1_center_time[i]
             _array[0]["time"] = s1_center_time[i] - (
                 s1["center_time"][s1_index] - s1["time"][s1_index]
             )
@@ -528,6 +531,9 @@ def build_arrays(
             _array[1:]["origin_center_time"] = s2_group_i["center_time"]
             _array[1:]["origin_n_competing"] = s2_group_i["n_competing"]
             _array[1:]["origin_group_type"] = 2
+            _array[1:]["center_time"] = s2_center_time[i] - (
+                s2_group_i["center_time"][s2_index] - s2_group_i["center_time"]
+            )
             _array[1:]["time"] = s2_center_time[i] - (
                 s2_group_i["center_time"][s2_index] - s2_group_i["time"]
             )