2022-03-11 16:14:48 +01:00
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"""
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Various useful utilities (duh)
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"""
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import numpy as np
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def sampled_time(sample_rate=1, start=0, end=1, offset=0):
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return offset + np.arange(start, end, 1/sample_rate)
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def rot_vector(phi1=0.12345):
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"""
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Return a unit vector rotated by phi radians.
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"""
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unit = np.array([
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phi1,
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phi1 - np.pi/2
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])
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return np.cos(unit)
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2022-03-24 17:29:04 +01:00
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def detect_edges(threshold, data, rising=True, falling=False):
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"""
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Detect rising/falling edges in data, returning the indices
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of the detected edges.
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https://stackoverflow.com/a/50365462
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"""
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mask = np.full(len(data), False)
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if rising:
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mask |= (data[:-1] < threshold) & (data[1:] > threshold)
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if falling:
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mask |= (data[:-1] > threshold) & (data[1:] < threshold)
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return np.flatnonzero(mask)+1
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