ruby_compare.py

# -*- coding: utf-8 -*-
"""
Created on Mon May 13 16:59:05 2019

@author: Hezy
"""

import numpy as np
from pandas import read_csv
from scipy.special import wofz
from scipy.optimize import curve_fit
import matplotlib.pyplot as plt

# read data from csv file
data1 = read_csv(
    "20190515-afterN1.csv",
    skiprows=None,
    header=None,
    sep="\t",
    lineterminator="\n",
    names=["lambda", "intensity"],
)
data2 = read_csv(
    "20190515-afterN2.csv",
    skiprows=None,
    header=None,
    sep="\t",
    lineterminator="\n",
    names=["lambda", "intensity"],
)
x1 = data1.iloc[:, 0]
y1 = data1.iloc[:, 1]
x2 = data2.iloc[:, 0]
y2 = data2.iloc[:, 1]


def lorentz(x, gamma):
    return gamma / np.pi / (np.square(x) + np.square(gamma))


def gauss(x, sigma):
    return (np.exp(-np.square(x) / 2 / np.square(sigma))) / (sigma * np.sqrt(2 * np.pi))


def voigt(x, sigma, gamma):
    return np.real(wofz((x + 1j * gamma) / (sigma * np.sqrt(2)))) / (
        sigma * np.sqrt(2 * np.pi)
    )


def ruby(x, x1, s1, g1, a1, x2, s2, g2, a2, b):
    return b + a1 * voigt((x - x1), s1, g1) + a2 * voigt((x - x2), s2, g2)


"""
popt, pocv = curve_fit(ruby, x1, y1, p0=(692.2, 0.178, 0.1, 2689.0, 693.7, 0.247, 0.1, 6058.0, 90.4))
print(popt)
print(pocv)

yfit1 = ruby(x1, *popt)
ydif1 = yfit1 - y1

popt, pocv = curve_fit(ruby, x2, y2, p0=(692.2, 0.178, 0.1, 26890.0, 693.7, 0.247, 0.1, 60580.0, 90.4))
print(popt)
print(pocv)

yfit2 = ruby(x2, *popt)
ydif2 = yfit2 - y2
"""

# create figure
fig, ax = plt.subplots(figsize=(14, 8))
plt.plot(x1, y1, ".b", label="experiment")
# plt.plot(x1, yfit1, '-r', label='fit')
# plt.plot(x1, ydif1, '-g', label='difference')
plt.plot(x2, y2, ".r", label="experiment")
# plt.plot(x2, yfit2, '-r', label='fit')
# plt.plot(x2, ydif2, '-g', label='difference')


# arange figure
ax.grid(True)
ax.legend(loc="best")
ax.set_title("Ruby")
ax.set_xlabel("wavelength (nm)")
ax.set_ylabel("intesity (arb.)")

plt.show()