From 03139808bd462c601f4c6f7f329530cb0f317cad Mon Sep 17 00:00:00 2001
From: Robert Jordens <jordens@gmail.com>
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)