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import numpy as np
import matplotlib.pyplot as plt
import csv
class Efficiency(object):
"""
Object for undertaking the Efficiency Calibration of a detector.
Currently only plots the Efficiency versus Energy data and the fitted curve.
"""
def __init__(self,
path = 'Efficiency.csv'
):
self.path = path
self.rows = []
self.energy = []
self.efficiency = []
self.values = []
self.unc = []
self.x = []
self.y = []
self.space = np.linspace(1, 2700, 540)
self.z = []
self.fit = []
self.new_fit = []
def open(self):
"""
Reads the csv file.
"""
with open(self.path, newline='') as f:
reader = csv.reader(f)
self.rows = [r for r in reader]
def sort(self):
"""
Sorts the data.
"""
for i in self.rows:
self.energy.append(float(i[0]))
self.efficiency.append(([float(i[1]), float(i[2])]))
def unwrap_lst_unc(self):
"""
Separates data.
"""
for i in self.efficiency:
self.values.append(i[0])
self.unc.append(i[1])
def mutate(self):
"""
Mutates data and creates the fit function.
"""
for i in self.energy:
self.x.append(np.log(i/1460))
for i in self.values:
self.y.append(np.log(i))
self.z = np.polyfit(np.asarray(self.x), np.asarray(self.y), 4)
def normal(self, x):
return np.log(x/1460)
def func3(self, x):
return (self.z[0]*self.normal(x)**4)+(self.z[1]*self.normal(x)**3)+(self.z[2]*self.normal(x)**2)+(self.z[3]*self.normal(x))+(self.z[4])
def new_func(self, x):
return np.exp(func3(x))
def fitting(self):
"""
Fits the data.
"""
for i in self.space:
self.fit.append(self.func3(i))
for i in self.fit:
self.new_fit.append(np.exp(i))
def plotter(self):
"""
Plots the data and the fit.
"""
plt.title('Efficiency Curve')
plt.xlabel('Energy (keV)')
plt.ylabel('Efficiency')
plt.errorbar(self.energy, self.values, fmt=None, yerr=self.unc)
plt.plot(self.energy, self.values, 'ro')
plt.grid()
plt.plot(self.space, self.new_fit)
plt.legend(('Data Points', 'Fitted Curve'), loc='upper right')
plt.ylim(0, 0.002)
plt.show()
def main(self):
self.open()
self.sort()
self.unwrap_lst_unc()
self.mutate()
self.fitting()
self.plotter()
if __name__ == '__main__':
eff = Efficiency()
eff.main()
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