diff --git a/src/pygama/pargen/AoE_cal.py b/src/pygama/pargen/AoE_cal.py index e3a853307..8d6d4c868 100644 --- a/src/pygama/pargen/AoE_cal.py +++ b/src/pygama/pargen/AoE_cal.py @@ -1552,24 +1552,15 @@ def get_aoe_cut_fit( log.error("A/E cut determination failed") self.low_cut_val = np.nan data[output_cut_param] = False - if self.dt_cut_param is not None and self.dt_cut_hard is True: - self.update_cal_dicts( - { - output_cut_param: { - "expression": f"({aoe_param}>a) & ({self.dt_cut_param})", - "parameters": {"a": self.low_cut_val}, - } - } - ) - else: - self.update_cal_dicts( - { - output_cut_param: { - "expression": f"({aoe_param}>a)", - "parameters": {"a": self.low_cut_val}, - } + + self.update_cal_dicts( + { + output_cut_param: { + "expression": f"({aoe_param}>a)", + "parameters": {"a": self.low_cut_val}, } - ) + } + ) def calculate_survival_fractions_sweep( self, @@ -1796,24 +1787,14 @@ def calibrate( df["AoE_Classifier"] < self.high_cut_val ) - if self.dt_cut_param is not None and self.dt_cut_hard is True: - self.update_cal_dicts( - { - "AoE_High_Side_Cut": { - "expression": f"(a>AoE_Classifier)& ({self.dt_cut_param})", - "parameters": {"a": self.high_cut_val}, - } - } - ) - else: - self.update_cal_dicts( - { - "AoE_High_Side_Cut": { - "expression": "(a>AoE_Classifier)", - "parameters": {"a": self.high_cut_val}, - } + self.update_cal_dicts( + { + "AoE_High_Side_Cut": { + "expression": "(a>AoE_Classifier)", + "parameters": {"a": self.high_cut_val}, } - ) + } + ) self.update_cal_dicts( { diff --git a/src/pygama/pargen/lq_cal.py b/src/pygama/pargen/lq_cal.py index 4df62276b..bf6f0daea 100644 --- a/src/pygama/pargen/lq_cal.py +++ b/src/pygama/pargen/lq_cal.py @@ -475,7 +475,7 @@ def drift_time_correction( self.update_cal_dicts( { - "LQ_Classifier": { + "LQ_Corrected": { "expression": f"{lq_param} - dt_eff*a - b", "parameters": {"a": self.dt_fit_pars[0], "b": self.dt_fit_pars[1]}, }