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import numpy as np
from gatspy.periodic import LombScargleFast
np.random.seed(0)
t = 100 * np.random.rand(100)
dy = 0.1
y = np.sin(t) + dy * np.random.randn(100)
model = LombScargleFast().fit(t, y, dy)
model.optimizer.period_range = (6.3, 10)
print(model.best_period)
#6.2859733116463481
This happens when the low-frequency end of the grid is near a peak. It gets worse when the frequency becomes very small compared to the data range.
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