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import numpy as np
from xypattern import Pattern
def gaussian(x, mu, a, sig):
return a * np.exp(-np.power(x - mu, 2.) / (2 * np.power(sig, 2.)))
def generate_peak_pattern(with_bkg=False):
x = np.arange(0, 24, 0.01)
y = np.zeros(x.shape)
peaks = [
[10, 3, 0.1],
[12, 4, 0.1],
[15, 6, 0.1],
]
for peak in peaks:
y += gaussian(x, peak[0], peak[1], peak[2])
y_bkg = x * 0.4 + 5.0
y_measurement = y + y_bkg
if with_bkg:
return Pattern(x, y_measurement), y_bkg
return Pattern(x, y_measurement)
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