Merge pull request #98 from XENONnT/add_s2_pattern_map

Add s2 pattern map schema

xedocs/schemas/corrections/__init__.py

@@ -22,5 +22,6 @@
 from .som_network import *
 from .hotspot_veto_cut import *
 from .photoionization_strength import *
+from .s2_pattern_maps import *
 from .s1_pattern_maps import *
 from .z_bias import *

xedocs/schemas/corrections/s2_pattern_map.py

@@ -0,0 +1,22 @@
+"""
+
+The pattern likelihood cut defined in SR0 was defined with a data-driven S2 map and a Gaussian 
+smeared likelihood definition, using the Tensorflow framework. The data-driven S2 map is trained 
+using a neural network, using S2 optical Monte Carlo simulation as an initial guess, to best-fit 
+event_area_per_channel. Details can be found in the SR0 note. As the SR0 method relied on trainable 
+parameters for each PMT the S2 pattern likelihood needs to be retrained to reflect the changed PMT list in SR1.
+
+SR0 S2 pattern map note
+https://xe1t-wiki.lngs.infn.it/doku.php?id=shenyang:s2_pattern_likelihood (Shenyang)
+
+SR1 S2 pattern map note
+https://xe1t-wiki.lngs.infn.it/doku.php?id=xenon:xenon1t:jacques:nt_sr1_s2pl (Jacques)
+
+
+"""
+
+from .base_references import BaseMap
+
+
+class S2PatternMap(BaseMap):
+    _ALIAS = "s2_pattern_maps"

xedocs/schemas/corrections/s2_pattern_maps.py

@@ -0,0 +1,22 @@
+"""
+
+The pattern likelihood cut defined in SR0 was defined with a data-driven S2 map and a Gaussian 
+smeared likelihood definition, using the Tensorflow framework. The data-driven S2 map is trained 
+using a neural network, using S2 optical Monte Carlo simulation as an initial guess, to best-fit 
+event_area_per_channel. Details can be found in the SR0 note. As the SR0 method relied on trainable 
+parameters for each PMT the S2 pattern likelihood needs to be retrained to reflect the changed PMT list in SR1.
+
+SR0 S2 pattern map note
+https://xe1t-wiki.lngs.infn.it/doku.php?id=shenyang:s2_pattern_likelihood (Shenyang)
+
+SR1 S2 pattern map note
+https://xe1t-wiki.lngs.infn.it/doku.php?id=xenon:xenon1t:jacques:nt_sr1_s2pl (Jacques)
+
+
+"""
+
+from .base_references import BaseMap
+
+
+class S2PatternMap(BaseMap):
+    _ALIAS = "s2_pattern_maps"