Delete example.py

example.py

-
-import os
-import sys
-import numpy as np
-import pandas as pd
-from PeakOTron import PeakOTron
-from joblib import dump
-import time
-
-print("--------------------")
-print('EXAMPLE SIPM CALIBRATION RUN')
-print("--------------------")
-
-
-out_dict = {}
-files_to_fit = []
-
-## Find all histograms in directory 
-for root, dirs, files in os.walk("./data/hamamatsu_pcb6/Light"):
-     
-        for file in files:
-            
-            if file.endswith(".txt"):
-                files_to_fit.append([file, os.path.join(root, file)])
-                
-
-## Print files.
-print("Files to fit:")
-for i, (file, _) in enumerate(files_to_fit):
-    print('File {0}: {1}'.format(i, file))
-    
-    
-    
-SiPM = "PM1125NS_SBO"
-
-
-## Loop thorough files
-for i, (file, path) in enumerate(files_to_fit):
-    items = file.split('_')
-
-    V = float(items[2].replace('V', '').replace('p', '.'))
-
-    print("\n\n")
-    print("===============================================================")
-    print("FIT {:d} - {:s}".format(i, file))
-    print("===============================================================")
-    print("\n\n")
-        
-
-    ## Load files. 
-    data = np.loadtxt(path, skiprows=8)
-
-    ## Create a PeakOTron Fit Object. 
-    f_data = PeakOTron(verbose=True)
-
-    ## Perform fit. 
-    time_start = time.time()
-    f_data.Fit(data, 
-          tau=21.953,  #SLOW PULSE COMPONENT TIME CONSTANT (ns)
-          t_gate=104, #GATE LENGTH (ns)
-          t_0 = 64, #INTEGRATION TIME BEFORE GATE (ns)               
-          tau_R=21.953,
-          truncate_nG=0.333
-              
-    ) #BINNING RULE "knuth", "freedman", "scott" - use bw= #### to override. it is still required for DCR calculation. 
-    time_end = time.time()
-    print("\n")
-    print("Fit took {:3.3f} s".format(time_end - time_start))
-    print("\n")
-
-    f_data.PlotFit(xlabel="ADC", display=False, save_directory="./Results/{0}_fit.png".format(os.path.splitext(file)[0]))
-    
-
-    
-    dump(f_data, "./Results/{0}".format(os.path.splitext(file)[0]))
-    
-    
-    
-    fit_out = {}
-    fit_val, fit_err = f_data.GetFitResults()
-    for key, val in fit_val.items():
-        print("{:s} : {:3.3E}".format(key, val))
-    
-    fit_out["SiPM"] = SiPM
-    fit_out["V"] = V
-
-    for key, value in fit_err.items():
-        fit_out["d_{:s}".format(key)] = value
-
-    fit_out.update(fit_val)
-    out_dict.update()
-    if out_dict == {}:
-        for key in fit_out.keys():
-            out_dict[key] = []
-
-    for key in fit_out.keys():
-        out_dict[key].append(fit_out[key])
-
-    print("===============================================================")
-    print("\n\n")
-        
-
-
-
-df = pd.DataFrame.from_dict(out_dict)
-df.to_csv("./fit_results_{:s}.csv".format(SiPM))