109 lines
3.3 KiB
Python
109 lines
3.3 KiB
Python
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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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Overview MPVs plot for BigBGO (AHBGOC) - adapted for DesignAnalysis folder
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Created on Thu May 2 13:21:02 2024
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@author: ava
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"""
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import matplotlib.pyplot as plt
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import sys
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import numpy as np
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import pandas as pd
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from pathlib import Path
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sys.path.append(str(Path(__file__).resolve().parents[1]))
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import plotstyle
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MODE = "slides" # "paper" oder "slides"
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MODE = "paper"
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plotstyle.set_style(MODE)
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# Fixed filenumbers without argparse
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filenumbers = [14, 16, 18, 20, 5, 7]
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files = []
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descr = []
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factors = []
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for num in filenumbers:
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if num == 14:
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files.append("2023-12-21-AHBGOC-14-langzeit")
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descr.append("two large diodes")
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factors.append(1.0)
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elif num == 16:
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files.append("2024-01-19-AHBGOC-rau-16_2weeks")
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descr.append("two large diodes, side roughened")
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factors.append(1.0)
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elif num == 18:
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files.append("2024-03-27-AHBGOC-six-18")
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descr.append("six small diodes, two preamps")
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factors.append(1.0)
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elif num == 20:
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files.append("2024-04-11-AHBGOC-six-20")
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descr.append("six small diodes, six preamps")
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factors.append(1.0)
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elif num == 22:
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files.append("2024-04-25-AHBGOC-six-vac-22")
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descr.append("six small diodes, six preamps, vacuum")
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factors.append(1.0)
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elif num == 5:
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files.append("2026-03-10-ahbgoa-test-5")
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descr.append("six small diodes, six preamps, dorn readout")
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factors.append(1/0.7)
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elif num == 7:
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files.append("2026-04-13-ahbgoa-test-7")
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descr.append("six small diodes, six preamps, dorn readout")
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factors.append(1/0.7)
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colors = ['tab:blue','tab:orange','tab:green','tab:red','tab:purple','tab:brown', 'tab:pink']
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energy = 'keV'
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f = 1.0
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energystr = energy + '$_{Si}$'
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plt.figure()
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ypos=[138,148,162,175,107,100]
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for i in range(len(files)):
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filename = "/home/asterix/ava/BGO/"+"fitparameters/" + files[i] + '_mpv_sums'
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data = pd.read_csv(filename+'.txt', sep='\s+')
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plt.errorbar(data['P'],data['mpv']*factors[i], data['err_mpv']*factors[i],
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fmt='o',capsize=5,ms=7,barsabove=True,color=colors[i], label=descr[i])
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values = data['mpv'] * factors[i]
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ma = max(values)
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mi = min(values)
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std = np.std(values)
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mean = np.mean(values)
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cv_percent = (std / mean) * 100 # Variationskoeffizient in Prozent
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plt.hlines(ma,1,16.5+i/4,ls=':', color=colors[i])
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plt.hlines(mi,1,16.5+i/4,ls=':', color=colors[i])
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plt.errorbar(16.5+i/4, ma-(ma-mi)/2,(ma-mi)/2,capsize=10,linewidth=2,color=colors[i])
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plt.fill_between([1,16.5+i/4], ma,mi,alpha = 0.1,color=colors[i])
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kw = dict(color=colors[i])
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#plt.text(17.5,ma-(ma-mi)/2-2/(2*i+1), "$\Delta$" + str(np.round(ma-mi,2)),kw)
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#plt.text(18,ypos[i], "$\Delta$" + str(np.round(ma-mi,2)),kw)
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plt.text(18, ypos[i], f"CV {cv_percent:.1f}\\%", kw, fontsize=24)
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# Title
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numberstr = ','.join(map(str, filenumbers))
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tit = f"Overview MPVs at different trigger positions"
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ylab = 'MPV [' + energystr + ']'
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xlab = 'Triggerposition'
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plt.legend(loc='upper right')
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plt.xticks([1,2,3,4,5,6,7,8,9,10,11,12,13,14, 15, 16, 17])
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#plt.title(tit)
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plt.ylabel(ylab)
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plt.xlabel(xlab)
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plt.ylim(100, 270)
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plt.xlim(0.8, 20)
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#plt.grid(True, which="both", ls="--", lw=0.5)
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# Save plot
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plotstyle.savefig("overview_position_dep", category="BGO")
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plt.show()
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