forked from M-Labs/artiq
[WIP] wavesynth/interpolate: wavesynth programming tools
* interpolate(t, v) will generate the channel data subset of a wavesynth program * still broken
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import numpy as np
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from scipy.interpolate import splrep, splev
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def _round_times(times, sample_times=None):
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times = np.asanyarray(times)
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if sample_times is None:
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sample_times = np.rint(times)
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duration = np.diff(sample_times)
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sample_times = sample_times[:-1]
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assert np.all(duration >= 0)
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assert np.all(duration < (1 << 16))
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return times, sample_times, duration
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def _interpolate(time, data, sample_times, order=3):
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# FIXME: this does not ensure that the spline does not clip
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spline = splrep(time, data, k=order or 1)
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# FIXME: this could be faster but needs k knots outside t_eval
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# dv = np.array(spalde(t_eval, s))
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coeffs = np.array([splev(sample_times, spline, der=i, ext=0)
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for i in range(order + 1)]).T
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return coeffs
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def _zip_program(times, channels, target=):
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for tc in zip(times, *channels):
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yield {
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"duration": tc[0],
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"channel_data": tc[1:],
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}
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# FIXME: this does not handle:
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# `clear` (clearing the phase accumulator)
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# `silence` (stopping the dac clock)
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def interpolate_channels(times, data, sample_times=None, **kwargs):
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if len(times) == 1:
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return _zip_program(np.array([1]), data[:, :, None])
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data = np.asanyarray(data)
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assert len(times) == len(data)
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times, sample_times, duration = _round_times(times, sample_times)
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channel_coeff = [_interpolate(sample_times, i, **kwargs) for i in data.T]
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return _zip_program(duration, np.array(channel_coeff))
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# v = np.clip(v/self.max_out, -1, 1)
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