CHANGE position colorbar

.gitignore

@@ -15,6 +15,7 @@ requirements.txt
 leckstrom.py
 leckstrom.pdf
 leckstrom.txt
+/T_calib
 
  ---> Python
 # Byte-compiled / optimized / DLL files

T_landau_sums.py

@@ -0,0 +1,118 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Tue Jun 11 13:46:53 2024
+
+@author: ava
+"""
+
+import argparse
+import sys
+import matplotlib.pyplot as plt
+import pandas as pd
+import numpy as np
+from scipy import special
+from scipy import constants
+from scipy.optimize import curve_fit
+import os.path
+from fit_functions import lan
+from fit_functions import mips
+from fit_functions import find_par
+from fit_functions import find_par_new
+
+
+parser = argparse.ArgumentParser(description="This script plots and fits histograms for Tranges")
+parser.add_argument("Tranges", type = str,nargs='+', help="temperature ranges to do script for [n60,n50,n40,...,40]")
+
+args = parser.parse_args()
+
+keV = True
+factor = 1/0.00362
+plt.figure(figsize=(17,12))
+
+labels = ['40','30','20','10','0','n10','n20','n30','n40','n50','n60']
+# params = [] #[[950,192,25,55,200]]+9*[[]]+[[770,440,45,58,1700]]
+# area = []
+# for i in range(11):
+#     a = 250+(490-270)/10*i
+#     b = 650 + (950-650)/10*i
+#     area.append([int(a),int(b)])
+#     par = np.array([950,192,25,55,200]) + (np.array([770,440,45,58,1700]) - np.array([950,192,25,55,200]))/10*i
+#     paradd = [int(x) for x in par]
+#     params.append(paradd)
+    
+params = [[950, 192, 25, 55, 200], [932, 216, 27, 55, 350], [914, 241, 29, 55, 500], [896, 266, 31, 55, 650], [878, 291, 33, 56, 800], [860, 316, 35, 56, 950], [842, 340, 37, 56, 1100], [824, 365, 39, 57, 1250], [806, 390, 41, 57, 1400], [788, 415, 43, 57, 1550], [770, 440, 45, 58, 1700]]
+area = [[250, 650], [272, 680], [294, 710], [316, 740], [338, 770], [360, 800], [382, 830], [404, 860], [426, 890], [448, 920], [470, 950]]
+
+fitparams = {'T': [], 'mpv': [], 'err_mpv':[]}
+
+for i in range(len(args.Tranges)):
+
+    data = pd.read_csv("histograms/2024-Tcalib-AHBGOC_"+args.Tranges[i]+'x_sum_muon.hist', sep = '\s+', skiprows=0)
+    
+    Itime = None
+    f = "histograms/2024-Tcalib-AHBGOC_"+args.Tranges[i]+"x_sum_muon.hist"
+    while len(f) > 0:
+        if os.path.isfile(f+'.Itime'):
+            Itime = int(pd.read_csv(f+'.Itime', sep = '\s+', skiprows=0, names = ['time'])['time'][0])
+            f=''
+        else:
+            f=f[:-1]
+            
+            
+    pos = labels.index(args.Tranges[i])
+    startparams = params[pos]
+    a,b = area[pos]
+    factor=1.0
+    #factor = 1/0.00362
+    energy = 'keV'
+    #signal = '$e^{-}_{ph}$'
+    resV = 0.838214/2
+    #plt.axvline(data[energy][a])
+    #plt.axvline(data[energy][b])
+
+    for ch in ['sum']:   
+        sig = np.power(data[ch]+1, 0.5) 
+        par, cov = curve_fit(lan, data[energy][a:b], data[ch][a:b], startparams, sigma = sig[a:b], absolute_sigma=True)
+       
+        print(par)
+        perr = np.sqrt(np.diag(cov))
+        print(perr)
+        
+        fitparams['T'].append(args.Tranges[i])
+        fitparams['mpv'].append(par[1])
+        fitparams['err_mpv'].append(perr[1])
+    
+        if not Itime==None:
+            plt.step(data[energy]*factor, np.multiply(data[ch], 3600/resV/Itime/factor), label=args.Tranges[i]+' ; $e$ = ('+ str(round(par[1]*factor,1)) + '$\pm$' +str(round((perr[1]*factor+0.05),1))+')'+energy)
+            plt.plot(data[energy][a:b]*factor, np.multiply(lan(data[energy], *par), 3600/resV/Itime/factor)[a:b], 'k--') 
+        else:
+            plt.step(data[energy]*factor, data[ch]/factor, label=ch)
+            #+' ; $e$ = ('+ str(int(round(par[1]*factor,-1))) + '$\pm$' +str(int(round(perr[1]*factor+4.9,-1)))+')'+signal)
+            #plt.plot(data[energy][a:b]*factor, lan(data[energy]*par)[a:b]/factor, 'k--') 
+
+        frame = pd.DataFrame(fitparams)
+        frame.to_csv('T_calib/'+'fitparams_landau_sums_keV', sep = ' ', index = False)
+
+fs = 15
+ylab = 'counts [1/h/$e^{-}_{ph}$]'
+xlab = 'signal [$e^{-}_{ph}$]'
+ylab = 'counts [1/h/keV$_{Si}$]'
+xlab = 'signal [keV$_{Si}$]'
+plt.plot(0, 0,'k--', linewidth=1, label = 'landau_fit')
+plt.legend(fontsize = fs)
+plt.xticks(fontsize=fs)
+plt.yticks(fontsize=fs)
+plt.title("Landau fit for BGO-sums at different temperatures", fontsize = fs+10, pad = 15)
+
+plt.yscale('log')
+plt.ylabel(ylab, fontsize = fs+5)
+plt.xlabel(xlab, fontsize=fs+5)
+#plt.ylim(5,100) #1
+plt.ylim(1.1/factor,100/factor) #2
+#plt.ylim(0.9,50) #3
+plt.xlim(100*factor,900*factor) 
+
+#plt.show()
+plt.savefig('T_calib/landau_sums')
+plt.savefig('T_calib/landau_sums.pdf')

make_Tcalibs.py

@@ -0,0 +1,52 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Tue Jun 11 11:33:02 2024
+
+@author: ava
+
+Explaination:
+    Executes selected evaluation scripts for all temperature ranges
+"""
+import sys
+import argparse
+import subprocess as sub
+
+parser = argparse.ArgumentParser(description="This script parses EI-data for 2024-Tcalib... and returns all histogramms")
+parser.add_argument("Tranges", type = str,nargs='+', help="temperature ranges to do script for [n60,n50,n40,...,40]")
+parser.add_argument("-v", "--verbose", choices = ['0','1','2'], help = "when zero only emit serious error messages; when one also emit warnings, when two emit informational messages")
+parser.add_argument('-muon', action='store_true', help = "makes histogramm of muon signals with AHBGOx.py")  # on/off flag
+parser.add_argument('-sum', action='store_true', help = "makes histogramm of BGO-diodes and sum with 'AHBGOx.py'")  # on/off flag
+parser.add_argument('-dau', action='store_true', help = "makes dau-file with 'AHBGOx.py'")  # on/off flag
+parser.add_argument('-Itime', action='store_true', help = "makes .Itime-data with 'AHBGOx.py'")  # on/off flag
+#parser.add_argument('-x', action='store_true', help = "makes histogramm of BGO-diodes and sum with 'AHBGOx.py'")  # on/off flag
+#parser.add_argument('-zero', action='store_true', help = "changes values to 0°C (use only with '-x')")  # on/off flag
+#parser.add_argument('-histfit', action='store_true', help = "fits and plots curves from -vertical with histfit_vertical.py")  # on/off flag
+
+args = parser.parse_args()
+
+if args.verbose == None:
+     verbosity = 1
+else:
+     verbosity = args.verbose
+if verbosity == 2:
+     sys.stderr.write("--verbostiy = '" + str(args.verbose)+"'\n")
+     sys.stderr.write("--filepath = '" + str(args.file)+"'\n")
+    
+filepath = "T_calib/2024-Tcalib-AHBGOC_"
+name = filepath.split("/")[-1]
+
+options=[]
+if args.muon:
+    options.append("-muon")
+if args.sum:
+    options.append("-sum")
+if args.dau:
+    options = ["-dau"]
+if args.Itime:
+    options = ["-Itime"]
+
+for i in range(len(args.Tranges)):
+    sub.run(["python3","AHBGOx.py", filepath+args.Tranges[i]+".EI"]+options)
+
+    

vacmonitor-2d.py

@@ -0,0 +1,136 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""
+Created on Wed May 29 13:54:06 2024
+
+@author: Ava Pohley
+"""
+import argparse
+import sys
+import matplotlib.pyplot as plt
+import datetime as dt
+from datetime import datetime
+import pandas as pd
+import numpy as np
+import os.path
+import matplotlib.dates as mdates
+
+
+def main():
+    
+    parser = argparse.ArgumentParser(description="This script plots temperatures and pressures of given data ending on '.dau' or '.vac'")
+    parser.add_argument("-v", "--verbose", choices = ['0','1','2'], help = "when zero only emit serious error messages; when one also emit warnings, when two emit informational messages")
+    parser.add_argument("files", type=str, nargs='+', help="files were data is stored in")
+    parser.add_argument("-t", "--title", type = str, help="title to use in plot; if not given a standard title will be chosen")
+    parser.add_argument("-e", "--export", type = str, nargs='+', help = "first: filepath were figure shall be exported to (if f, filepath of histdata will be chosen with filepath_plot) \n second:format (png,pdf,...)")
+    #parser.add_argument("-l", "--limits", type=str, nargs='+',help = "limits of plot in order xmin,xmax, ymin,ymax,")
+
+    args = parser.parse_args()
+
+    if args.verbose == None:
+        verbosity = 1
+    else:
+        verbosity = args.verbose
+    
+    if verbosity == 2:
+        sys.stderr.write("--verbostiy = '" + str(args.verbose)+"'\n")
+        sys.stderr.write("--files = '" + str(args.filepath)+"'\n")
+        sys.stderr.write("--title = '" + str(args.title)+"'\n")
+        sys.stderr.write("--export = '" + str(args.export) +"'\n")
+        #sys.stderr.write("--limits = '" + str(args.limits) +"'\n")
+
+    fig, ax = plt.subplots()
+    fig.figsize=(20,15)
+    
+    secondax=0
+    cbar = None
+    ax2 = ax.twinx()
+    used_labels=[]
+    
+    for file in args.files:
+        path,end = file.split('.')
+        
+        if end == 'dau':
+            if secondax == 0:
+                secondax = 1
+            if 'AHBGO' in file:
+                names = ['$T_{BGO}$']
+                data = pd.read_csv(file, sep="\s+",names=['time']+names,skiprows=1, on_bad_lines='skip')
+                colors = ['tab:blue']
+            else:
+                names = ['T1','T2','T3','T4']
+                #time, I,T1,T2,T3,T4 = np.genfromtxt(file,dtype=np.dtype(str),delimiter=' ',usecols=(0,1,2,3,4,5),unpack=True,invalid_raise=False)
+                data = pd.read_csv(file, sep=' ',names=['time','I']+names, on_bad_lines='skip')
+                for n in names:
+                    data[n] = T(data.loc[:, n])
+                colors = ['tab:orange','tab:green','tab:red','tab:purple']
+            
+            time=[]
+            for t in data['time']: time.append(pd.to_datetime(datetime.fromtimestamp(t))) 
+            
+            for i in range(len(names)):
+                label = names[i]
+                if label in used_labels:
+                    label = ""
+                else: used_labels.append(label)
+                ax2.plot(time,data[names[i]], color=colors[i],label = label)
+   
+                
+        elif end == '2dhist':
+            count = True
+            names = ['time', 'mV', 'counts']
+            data = pd.read_csv(file, sep = "\s+", skiprows=1, names = names)
+            time=[]
+            for t in data['time']: time.append(pd.to_datetime(datetime.fromtimestamp(t))) 
+            
+            plot = ax.scatter(time, data['mV'], c=data['counts'], norm = 'log', vmin=0.5, vmax = 100)
+            if cbar == None:
+                cbar = plt.colorbar(plot, orientation = 'vertical',location ='left', shrink = 0.95, pad = 0.1)
+
+
+    if count:
+        layout(ax,ax2,secondax,cbar)
+        
+        if args.export == None:
+            plt.show()
+        else:
+            if args.export[0] == 'f1':
+                name = 'plots/vacmon_' + args.files[0].split('/')[-1].split('.')[0]
+            else:
+                name = args.export[0]
+            if len(args.export)>1:
+                    end = '.' + args.export[1]
+            else:
+                    end=''
+            plt.savefig(name+end)
+            
+    else: 
+        print('no valid file')
+
+def T(x):
+    return np.divide(np.subtract(x,1000), 3.85)      
+
+def layout(ax,ax2,secondax,cbar):
+    fs=20
+    if not cbar == None:
+        ax2.margins(x=0)
+        ax.margins(y=0)
+        ax.tick_params(axis='x', labelsize=fs-3)
+        cbar.set_label('counts', fontsize = fs+5)
+        cbar.ax.tick_params(labelsize=fs)
+        ax.tick_params(axis='y', labelsize=fs)    
+        ax.set_ylabel("signal [mV]", fontsize = fs)
+    if secondax > 0:
+        ax2.set_ylabel("T [°C]", fontsize = fs)
+        ax2.legend(fontsize=fs-2,loc = 'upper left')
+        ax2.tick_params(axis='x', labelsize=fs-3)
+        ax2.tick_params(axis='y', labelsize=fs)       
+    
+    plt.xticks(fontsize=fs)
+    plt.title("vacmonitor-2d.py", fontsize = fs+2)
+   
+    plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%H:%M\n%m-%d\n%Y'))
+        
+        
+main()
+  

vacmonitor.py

@@ -43,6 +43,8 @@ def main():
     fig.figsize=(20,15)
     
     secondax=0
+    ax2 = None
+    used_labels=[]
     
     for file in args.files:
         path,end = file.split('.')
@@ -66,7 +68,11 @@ def main():
             for t in data['time']: time.append(pd.to_datetime(datetime.fromtimestamp(t))) 
             
             for i in range(len(names)):
-                ax.plot(time,data[names[i]], color=colors[i],label = names[i])
+                label = names[i]
+                if label in used_labels:
+                    label = ""
+                else: used_labels.append(label)
+                ax.plot(time,data[names[i]], color=colors[i],label = label)
    
                 
         elif 'vac' in end:
@@ -84,7 +90,11 @@ def main():
                 time.append(pd.to_datetime(datetime.fromtimestamp(int(t.split(' ')[1])))) 
            
             for i in range(len(names)):
-                ax2.plot(time,data[names[i]], color=colors[i],label = names[i])
+                label = names[i]
+                if label in used_labels:
+                    label = ""
+                else: used_labels.append(label)
+                ax2.plot(time,data[names[i]], color=colors[i],label = label)
         
 
     if secondax > 0:
@@ -126,7 +136,7 @@ def layout(ax,ax2,secondax):
     plt.xticks(fontsize=fs)
     plt.title("vacmonitor.py", fontsize = fs+2)
    
-    plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%H:%M\n%d.Okt\n%Y'))
+    plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%H:%M\n%m-%d\n%Y'))
         
         
 main()