fix cuts (now have coincidence and ROI), corrected drift-time of cent…

…re, and fixed bug in drift map implementation

flamedisx/lz/lz.py

@@ -72,7 +72,7 @@ class LZSource:
     path_s1_acc_curve = 'sr1/cS1_acceptance_curve.pkl'
     path_s2_acc_curve = 'sr1/cS2_acceptance_curve.pkl'
 
-    def __init__(self, *args, ignore_maps=False, ignore_acc=False, cap_upper_cs1=False, **kwargs):
+    def __init__(self, *args, ignore_maps=False, ignore_acc_maps=False, cap_upper_cs1=False, **kwargs):
         super().__init__(*args, **kwargs)
 
         self.cap_upper_cs1 = cap_upper_cs1
@@ -91,9 +91,9 @@ def __init__(self, *args, ignore_maps=False, ignore_acc=False, cap_upper_cs1=Fal
         self.S2_min = config.getfloat('NEST', 'S2_min_config') * (1 + self.double_pe_fraction)  # phd to phe
         self.cS2_max = config.getfloat('NEST', 'cS2_max_config') * (1 + self.double_pe_fraction)  # phd to phe
 
-        if ignore_acc:
+        if ignore_acc_maps:
             print("ignoring acceptances")
-            self.ignore_acceptances = True
+            self.ignore_acceptances_maps = True
 
             self.cs1_acc_domain = None
             self.log10_cs2_acc_domain = None
@@ -177,7 +177,7 @@ def s1_acceptance(self, s1, cs1, cs1_acc_curve):
                               tf.zeros_like(s1, dtype=fd.float_type()))  # if false
 
         # multiplying by efficiency curve
-        if not self.ignore_acceptances:
+        if not self.ignore_acceptances_maps:
             acceptance *= cs1_acc_curve
 
         return acceptance
@@ -191,7 +191,7 @@ def s2_acceptance(self, s2, cs2, cs2_acc_curve,
                               tf.zeros_like(s2, dtype=fd.float_type()))  # if false
 
         # multiplying by efficiency curve
-        if not self.ignore_acceptances:
+        if not self.ignore_acceptances_maps:
             acceptance *= cs2_acc_curve
 
         # We will insert the FV acceptance here
@@ -296,7 +296,7 @@ def add_extra_columns(self, d):
             accept_lower_drift_time = np.where(drift_time_us > 71., 1., 0.)
             accept_radial = np.where(radius_cm < boundaryR, 1., 0.)
 
-            d['fv_acceptance'] = accept_upper_drift_time * accept_lower_drift_time * accept_radial
+            d['fv_acceptance'] =np.ones_like(accept_upper_drift_time * accept_lower_drift_time * accept_radial)
 
         if 'resistor_acceptance' not in d.columns:
             x = d['x'].values
@@ -311,7 +311,7 @@ def add_extra_columns(self, d):
             not_inside_res1 = np.where(np.sqrt( (x-res1X)*(x-res1X) + (y-res1Y)*(y-res1Y) ) < res1R, 0., 1.)
             not_inside_res2 = np.where(np.sqrt( (x-res2X)*(x-res2X) + (y-res2Y)*(y-res2Y) ) < res2R, 0., 1.)
 
-            d['resistor_acceptance'] = not_inside_res1 * not_inside_res2
+            d['resistor_acceptance'] = np.ones_like(not_inside_res1 * not_inside_res2)
 
         if 'timestamp_acceptance' not in d.columns:
             t_start = pd.to_datetime('2021-12-23T09:37:51')
@@ -322,7 +322,7 @@ def add_extra_columns(self, d):
             not_inside_window1 = np.where((days_since_start >= 25.5) & (days_since_start <= 33.), 0., 1.)
             not_inside_window2 = np.where((days_since_start >= 90.) & (days_since_start <= 93.5), 0., 1.)
 
-            d['timestamp_acceptance'] = not_inside_window1 * not_inside_window2
+            d['timestamp_acceptance'] =np.ones_like( not_inside_window1 * not_inside_window2)
 
 
 ##

flamedisx/nest/config/lz_SR3.ini

@@ -6,13 +6,13 @@ pressure_config = 1.86 ; bar
 drift_field_config = 96.5 ; V/cm
 gas_field_config = 8.301178 ; kV/cm
 
-radius_config = 67.3 ; cm not sure what to do here
+radius_config = 72.8 ; cm not sure what to do here
 ;grab from core cuts
 dt_min_config = 71000. ; ns
 dt_max_config = 1030000. ; ns
 
 z_topDrift_config = 146.1 ; cm
-dt_cntr_config = 462500. ; ns
+dt_cntr_config = 517927 ; ns old: 462500.
 
 g1_config = 0.1122 ; MADE FLOATABLE INSTEAD
 elife_config = 9000000. ; ns

flamedisx/nest/lxe_blocks/energy_spectrum.py

@@ -209,7 +209,7 @@ def validate_fix_truth(self, d):
             else:
                 raise ValueError("When fixing position, give (x, y, z), "
                                  "or (r, theta, z).")
-            data=apply_drift_map(data,self.drift_map,None,self.z_topDrift, self.drift_velocity)
+            d=apply_drift_map(d,self.drift_map,None,self.z_topDrift, self.drift_velocity)
         elif 'event_time' not in d and 'energy' not in d:
             # Neither position, time, nor energy given
             raise ValueError(f"Dict should contain at least ['x', 'y', 'z'] "