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testCorrelationMethods.py
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testCorrelationMethods.py
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"""
SPECTRA PROCESSING
Copyright (C) 2020 Josef Brandt, University of Gothenborg.
This program is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program, see COPYING.
If not, see <https://www.gnu.org/licenses/>.
"""
import numpy as np
from scipy.signal import gaussian
import matplotlib.pyplot as plt
from distort import *
from cythonModules.corrCoeff import sfec
from processing import normalizeIntensities
peakLength: int = 101
peak: np.ndarray = gaussian(peakLength, 7)
np.random.seed(42)
noisy: np.ndarray = normalizeIntensities(peak + np.random.rand(peakLength)*0.5)
offset: np.ndarray = peak + 0.4
tilted: np.ndarray = normalizeIntensities(peak + np.linspace(0, 0.4, peakLength))
bended: np.ndarray = normalizeIntensities(peak - gaussian(peakLength, 21)*0.5)
shifted: np.ndarray = np.zeros_like(peak)
shiftAmount = int(round(peakLength / 30))
shifted[shiftAmount:] = peak[:peakLength-shiftAmount]
for i, distorted in enumerate([noisy, offset, tilted, bended, shifted]):
plt.subplot(2, 3, i+1)
plt.plot(peak)
plt.plot(distorted)
corr_pearson = np.corrcoef(peak, distorted)[0, 1]
corr_sfec = sfec(peak, distorted)
plt.title(f'Pearson: {round(corr_pearson, 3)}, SFEC: {round(corr_sfec, 3)}')
plt.show()
plt.tight_layout()