def _calc_sampled_segments(self) -> Tuple[Sequence[TaborSegment], Sequence[int]]:
"""
Returns:
(segments, segment_lengths)
"""
time_array, segment_lengths = get_sample_times(self._parsed_program.waveforms, self._sample_rate)
if np.any(segment_lengths % 16 > 0) or np.any(segment_lengths < 192):
raise TaborException('At least one waveform has a length that is smaller 192 or not a multiple of 16')
segments = []
for i, waveform in enumerate(self._parsed_program.waveforms):
t = time_array[:segment_lengths[i]]
marker_time = t[::2]
segment_a = self._channel_data(waveform, t, 0)
segment_b = self._channel_data(waveform, t, 1)
assert (len(segment_a) == len(t))
assert (len(segment_b) == len(t))
marker_a = self._marker_data(waveform, marker_time, 0)
marker_b = self._marker_data(waveform, marker_time, 1)
segment = TaborSegment.from_sampled(ch_a=segment_a,
ch_b=segment_b,
marker_a=marker_a,
marker_b=marker_b)
segments.append(segment)
return segments, segment_lengths
def _sample_waveforms(self, waveforms: Sequence[Waveform]) -> List[Tuple[Tuple[numpy.ndarray, ...],
Tuple[numpy.ndarray, ...]]]:
sampled_waveforms = []
time_array, segment_lengths = get_sample_times(waveforms, self._sample_rate)
for waveform, segment_length in zip(waveforms, segment_lengths):
wf_time = time_array[:segment_length]
sampled_channels = []
for channel, trafo, amplitude, offset in zip(self._channels, self._voltage_transformations,
self._amplitudes, self._offsets):
if channel is None:
sampled_channels.append(self._sample_empty_channel(wf_time))
else:
sampled = waveform.get_sampled(channel, wf_time)
if trafo is not None:
sampled = trafo(sampled)
sampled = sampled - offset
sampled /= amplitude
sampled_channels.append(waveform.get_sampled(channel, wf_time))
sampled_markers = []
for marker in self._markers:
if marker is None:
sampled_markers.append(self._sample_empty_marker(wf_time))
else:
sampled_markers.append(waveform.get_sampled(marker, wf_time) != 0)
sampled_waveforms.append((tuple(sampled_channels), tuple(sampled_markers)))
return sampled_waveforms
def test_get_sample_times_single_wf(self):
sample_rate = TimeType(12, 10)
wf = DummyWaveform(duration=TimeType(40, 12))
expected_times = np.arange(4) / 1.2
times, n_samples = get_sample_times(wf, sample_rate_in_GHz=sample_rate)
np.testing.assert_equal(times, expected_times)
np.testing.assert_equal(n_samples, np.asarray(4))
def __init__(self, loop: Loop,
channels: Tuple[Optional[ChannelID], ...],
markers: Tuple[Optional[ChannelID], ...],
amplitudes: Tuple[float, ...],
offsets: Tuple[float, ...],
voltage_transformations: Tuple[Optional[Callable], ...],
sample_rate: TimeType):
assert len(channels) == len(amplitudes) == len(offsets) == len(voltage_transformations)
self._channels = tuple(channels)
self._markers = tuple(markers)
self._amplitudes = tuple(amplitudes)
self._offsets = tuple(offsets)
self._voltage_transformations = tuple(voltage_transformations)
self._sample_rate = sample_rate
self._loop = loop
self._waveforms = {node.waveform: None for node in loop.get_depth_first_iterator() if node.is_leaf()}
time_array, segment_lengths = get_sample_times(self._waveforms.keys(), sample_rate)
for waveform, segment_length in zip(self._waveforms.keys(), segment_lengths):
wf_time = time_array[:segment_length]
sampled_channels = []
for channel, trafo, amplitude, offset in zip(channels, voltage_transformations, amplitudes, offsets):
if channel is None:
sampled_channels.append(None)
else:
sampled = waveform.get_sampled(channel, wf_time)
if trafo:
sampled = trafo(sampled)
sampled = sampled - offset
sampled /= amplitude
sampled_channels.append(waveform.get_sampled(channel, wf_time))
sampled_markers = []
for marker in markers:
if marker is None:
sampled_markers.append(None)
else:
sampled_markers.append(waveform.get_sampled(marker, wf_time) != 0)
self._waveforms[waveform] = (tuple(sampled_channels), tuple(sampled_markers))
def test_get_sample_times(self):
sample_rate = TimeType.from_fraction(12, 10)
wf1 = DummyWaveform(duration=TimeType.from_fraction(20, 12))
wf2 = DummyWaveform(duration=TimeType.from_fraction(400000000001, 120000000000))
wf3 = DummyWaveform(duration=TimeType.from_fraction(1, 10**15))
expected_times = np.arange(4) / 1.2
times, n_samples = get_sample_times([wf1, wf2], sample_rate_in_GHz=sample_rate)
np.testing.assert_equal(expected_times, times)
np.testing.assert_equal(n_samples, np.asarray([2, 4]))
with self.assertRaises(AssertionError):
get_sample_times([], sample_rate_in_GHz=sample_rate)
with self.assertRaisesRegex(ValueError, "non integer length"):
get_sample_times([wf1, wf2], sample_rate_in_GHz=sample_rate, tolerance=0.)
with self.assertRaisesRegex(ValueError, "length <= zero"):
get_sample_times([wf1, wf3], sample_rate_in_GHz=sample_rate)
def parse_program(program: Loop,
channels: Tuple[Optional[ChannelID], ...],
markers: Tuple[Tuple[Optional[ChannelID], Optional[ChannelID]], ...],
sample_rate: TimeType,
amplitudes: Tuple[float, ...],
voltage_transformations: Tuple[Callable, ...],
offsets: Tuple[float, ...] = None) -> Tuple[Sequence[tek_awg.SequenceEntry],
Sequence[tek_awg.Waveform]]:
"""Convert the program into a sequence of sequence table entries and a sequence of waveforms that can be uploaded
to the device."""
assert program.depth() == 1, ("Invalid program depth: %d" % program.depth())
assert program.repetition_count == 1, ("Cannot repeat program a finite number of times (only once not %d)" %
program.repetition_count)
# For backward compatibility
# EDIT: I think this is not needed? (Simon)
if offsets is None:
offsets = (0.,) * len(amplitudes)
assert len(channels) == len(markers) == len(amplitudes) == len(voltage_transformations) == len(offsets)
sequencing_elements = []
ch_waveforms = {}
bin_waveforms = {}
sample_rate_in_GHz = sample_rate / 10**9
time_array, n_samples = get_sample_times([loop.waveform for loop in program],
sample_rate_in_GHz=sample_rate_in_GHz)
channel_wise_kwargs = [dict(voltage_to_uint16_kwargs=dict(output_amplitude=amplitude,
output_offset=offset,
resolution=14),
voltage_transformation=voltage_trafo)
for amplitude, offset, voltage_trafo in zip(amplitudes, offsets, voltage_transformations)]
# List of Tuple[positional channel tuple, set chs to sample]
channel_infos = [((channel, marker_1, marker_2), {channel, marker_1, marker_2} - {None})
for channel, (marker_1, marker_2) in zip(channels, markers)]
for n_sample, loop in zip(n_samples, program):
entries = []
for (positional_chs, chs_to_sample), kwargs in zip(channel_infos, channel_wise_kwargs):
if not chs_to_sample:
entries.append(n_sample)
bin_waveforms[n_sample] = None
else:
ch_waveform = loop.waveform.get_subset_for_channels(chs_to_sample)
if ch_waveform not in ch_waveforms:
bin_waveform = _make_binary_waveform(ch_waveform,
time_array[:n_sample],
*positional_chs, **kwargs)
if bin_waveform in bin_waveforms:
# use identical binary waveform already created to save memory
bin_waveform = ch_waveforms[bin_waveforms[bin_waveform]]
else:
bin_waveforms[bin_waveform] = ch_waveform
ch_waveforms[ch_waveform] = bin_waveform
entries.append(ch_waveforms[ch_waveform])
sequencing_elements.append(
tek_awg.SequenceEntry(entries=entries,
loop_count=loop.repetition_count)
)
return tuple(sequencing_elements), tuple(bin_waveforms.keys())