diff --git a/PeakOTron.py b/PeakOTron.py
index 0a60dd4ace8b5598b4d7247eabdbfa873daf0127..886a24cc9ae6a6cb0f2fe5724687047e405d7787 100644
--- a/PeakOTron.py
+++ b/PeakOTron.py
@@ -279,14 +279,15 @@ class PeakOTron:
"r_fast":None,
"tgate":None,
"pedestal":None,
+ "truncate":False,
"n_bootstrap": 1000,
"n_bootstrap_kde":100,
"bw":None,
"peak_dist_factor":0.8,
"peak_width_factor":0.5,
"peak_ppf":0.95,
- "prominence": 0.0,
- "min_n_peak_evts": 100,
+ "peak_prominence": 0.0,
+ "peak_min_n_evts": 100,
"kernel_kde":"gaussian",
"bandwidth_kde":"ISJ",
"ppf_mainfit":1 - 1e-6,
@@ -1294,14 +1295,15 @@ class PeakOTron:
peak_dist_factor,
peak_width_factor,
peak_ppf,
+ peak_prominence,
+ peak_min_n_evts,
+ truncate,
pedestal,
- prominence,
bin_method,
n_bootstrap,
n_bootstrap_kde,
bandwidth_kde,
- kernel_kde,
- min_n_peak_evts):
+ kernel_kde):
self.scaler = RobustScaler()
@@ -1412,33 +1414,47 @@ class PeakOTron:
est_gain_lin = abs(f_lin_kde_s(est_gain) - f_lin_kde_s(0))
- peaks, properties = find_peaks(y_kde_s,
- distance=peak_dist_factor*est_gain_lin,
- prominence=prominence
- )
-
-
+ limit_s = pedestal_s - 0.5*est_gain
+ limit = limit_s*self.scaler.scale_[0] + self.scaler.center_[0]
+ if(truncate):
+
+ cond_limit = (x>limit)
+ cond_limit_s = (x_s>limit_s)
+ cond_limit_kde_s = (x_kde_s>limit_s)
- if(len(peaks)<3):
- if(self._verbose):
- print("Not enough peaks found with distance criterion to fit. Removing distance criterion and finding all peaks...")
+ x = x[cond_limit]
+ y = y[cond_limit]
+ y_err = y_err[cond_limit]
- peaks, properties = find_peaks(y_kde_s,
- prominence=prominence
- )
+ x_s = x_s[cond_limit_s]
+ y_s = y_s[cond_limit_s]
+ y_err_s = y_err_s[cond_limit_s]
+ x_kde_s = x_kde_s[cond_limit_kde_s]
+ y_kde_s = y_kde_s[cond_limit_kde_s]
+ y_kde_err_s = y_kde_err_s[cond_limit_kde_s]
- limit_s = pedestal_s - 0.5*est_gain
- limit = pedestal - 0.5*est_gain*self.scaler.scale_[0]
- cond_limit_s = (x_kde_s[peaks]>limit_s)
- if(sum(cond_limit_s)<3):
if(self._verbose):
- print("No peaks observed above pedestal - gain/2. Continuing without thresholding...")
- else:
- peaks = peaks[cond_limit_s]
-
+ print("Truncated distributions to only fit PH > pedestal - statistical gain/2 ...")
+
+
+
+ peaks, properties = find_peaks(y_kde_s,
+ distance=peak_dist_factor*est_gain_lin,
+ prominence=peak_prominence
+ )
+
+
+
+
+ if(len(peaks)<3):
+ print("Not enough peaks found with current distance criterion to fit. Setting fit fail status and continuing..")
+ self._failed=True
+ return
+
+
x_peaks_s = x_kde_s[peaks]
@@ -1471,16 +1487,16 @@ class PeakOTron:
N_evt_peak = len(self.SelectRange(data_s, x_peak-x_width/2, x_peak+x_width/2))
- if(x_i>peak_threshold and N_evt_peak<min_n_peak_evts):
+ if(x_i>peak_threshold and N_evt_peak<peak_min_n_evts):
if(self._verbose):
print("Peak {:d} has {:d} events. Less than event threshold {:d}. Ignoring...".format(x_i,
N_evt_peak,
- min_n_peak_evts))
+ peak_min_n_evts))
else:
if(self._verbose):
print("Peak {:d} has {:d} events. Adding...".format(x_i,
N_evt_peak,
- min_n_peak_evts))
+ peak_min_n_evts))
self._peak_data["x_peak_s"].append(x_peak)
self._peak_data["y_peak_s"].append(y_peak)
@@ -1498,7 +1514,7 @@ class PeakOTron:
self._peak_data["x_width_s"] = np.asarray(self._peak_data["x_width_s"])
if(n_valid_peaks<3):
- print("Minimum 3 peaks covering a threshold {0} events required. Too few events in peaks to proceed. Setting fit fail status and continuing...".format(min_n_peak_evts))
+ print("Minimum 3 peaks covering a threshold {0} events required. Too few events in peaks to proceed. Setting fit fail status and continuing...".format(peak_min_n_evts))
self._failed = True
return
@@ -2001,8 +2017,9 @@ class PeakOTron:
peak_dist_factor,
peak_width_factor,
peak_ppf,
- prominence,
- min_n_peak_evts,
+ peak_prominence,
+ peak_min_n_evts,
+ truncate,
kernel_kde,
bandwidth_kde,
ppf_mainfit,
@@ -2021,19 +2038,21 @@ class PeakOTron:
if(self._verbose):
print("Getting histogram and peak values...")
- self.GetHistAndPeaks(data,
+ self.GetHistAndPeaks(
+ data,
bw,
peak_dist_factor,
peak_width_factor,
peak_ppf,
+ peak_prominence,
+ peak_min_n_evts,
+ truncate,
pedestal,
- prominence,
bin_method,
n_bootstrap,
n_bootstrap_kde,
bandwidth_kde,
- kernel_kde,
- min_n_peak_evts)
+ kernel_kde)
if(not self._failed):
if(self._verbose):