From 03139808bd462c601f4c6f7f329530cb0f317cad Mon Sep 17 00:00:00 2001 From: Robert Jordens Date: Mon, 23 Mar 2015 20:38:33 -0600 Subject: [PATCH] [WIP] wavesynth/interpolate: wavesynth programming tools * interpolate(t, v) will generate the channel data subset of a wavesynth program * still broken --- artiq/wavesynth/interpolate.py | 45 ++++++++++++++++++++++++++++++++++ 1 file changed, 45 insertions(+) create mode 100644 artiq/wavesynth/interpolate.py diff --git a/artiq/wavesynth/interpolate.py b/artiq/wavesynth/interpolate.py new file mode 100644 index 000000000..39cdf4bf0 --- /dev/null +++ b/artiq/wavesynth/interpolate.py @@ -0,0 +1,45 @@ +import numpy as np +from scipy.interpolate import splrep, splev + + +def _round_times(times, sample_times=None): + times = np.asanyarray(times) + if sample_times is None: + sample_times = np.rint(times) + duration = np.diff(sample_times) + sample_times = sample_times[:-1] + assert np.all(duration >= 0) + assert np.all(duration < (1 << 16)) + return times, sample_times, duration + + +def _interpolate(time, data, sample_times, order=3): + # FIXME: this does not ensure that the spline does not clip + spline = splrep(time, data, k=order or 1) + # FIXME: this could be faster but needs k knots outside t_eval + # dv = np.array(spalde(t_eval, s)) + coeffs = np.array([splev(sample_times, spline, der=i, ext=0) + for i in range(order + 1)]).T + return coeffs + + +def _zip_program(times, channels, target=): + for tc in zip(times, *channels): + yield { + "duration": tc[0], + "channel_data": tc[1:], + } +# FIXME: this does not handle: +# `clear` (clearing the phase accumulator) +# `silence` (stopping the dac clock) + + +def interpolate_channels(times, data, sample_times=None, **kwargs): + if len(times) == 1: + return _zip_program(np.array([1]), data[:, :, None]) + data = np.asanyarray(data) + assert len(times) == len(data) + times, sample_times, duration = _round_times(times, sample_times) + channel_coeff = [_interpolate(sample_times, i, **kwargs) for i in data.T] + return _zip_program(duration, np.array(channel_coeff)) + # v = np.clip(v/self.max_out, -1, 1)