def test_build_waveform_multi_channel_vectorized(self):
ppt = PointPulseTemplate([('t1', 'A'), ('t2', 0., 'hold'),
('t1+t2', 'B+C', 'linear')], [0, 'A'],
measurements=[('M', 'n', 1), ('L', 'n', 1)])
parameters = {
't1': 0.1,
't2': 1.,
'A': np.ones(2),
'B': np.arange(2),
'C': 19.,
'n': 0.2
}
wf = ppt.build_waveform(parameters=parameters,
channel_mapping={
0: 1,
'A': 'A'
})
expected_1 = PointWaveform(1,
[(0, 1., HoldInterpolationStrategy()),
(0.1, 1., HoldInterpolationStrategy()),
(1., 0., HoldInterpolationStrategy()),
(1.1, 19., LinearInterpolationStrategy())])
expected_A = PointWaveform('A',
[(0, 1., HoldInterpolationStrategy()),
(0.1, 1., HoldInterpolationStrategy()),
(1., 0., HoldInterpolationStrategy()),
(1.1, 20., LinearInterpolationStrategy())])
self.assertEqual(wf.defined_channels, {1, 'A'})
self.assertEqual(wf._sub_waveforms[0].defined_channels, {1})
self.assertEqual(wf._sub_waveforms[0], expected_1)
self.assertEqual(wf._sub_waveforms[1].defined_channels, {'A'})
self.assertEqual(wf._sub_waveforms[1], expected_A)
def test_build_waveform_multi_channel(self):
table = TablePulseTemplate(
{
0: [(0, 0), ('foo', 'v', 'linear'), ('bar', 0, 'jump')],
3: [(0, 1), ('bar+foo', 0, 'linear')]
},
parameter_constraints=['foo>1'],
measurements=[('M', 'b', 'l'), ('N', 1, 2)])
parameters = {'v': 2.3, 'foo': 1, 'bar': 4, 'b': 2, 'l': 1}
channel_mapping = {0: 'ch', 3: 'oh'}
with self.assertRaises(ParameterConstraintViolation):
table.build_waveform(parameters=parameters,
channel_mapping=channel_mapping)
parameters['foo'] = 1.1
waveform = table.build_waveform(parameters=parameters,
channel_mapping=channel_mapping)
self.assertIsInstance(waveform, MultiChannelWaveform)
expected_waveforms = [
TableWaveform.from_table(
'ch', ((0, 0, HoldInterpolationStrategy()),
(1.1, 2.3, LinearInterpolationStrategy()),
(4, 0, JumpInterpolationStrategy()),
(5.1, 0, HoldInterpolationStrategy()))),
TableWaveform.from_table(
'oh', ((0, 1, HoldInterpolationStrategy()),
(5.1, 0, LinearInterpolationStrategy()))),
]
self.assertEqual(waveform._sub_waveforms, tuple(expected_waveforms))
def test_validate_input_duplicate_removal(self):
validated = TableWaveform._validate_input([TableWaveformEntry(0.0, 0.2, HoldInterpolationStrategy()),
TableWaveformEntry(0.1, 0.2, LinearInterpolationStrategy()),
TableWaveformEntry(0.1, 0.3, JumpInterpolationStrategy()),
TableWaveformEntry(0.1, 0.3, HoldInterpolationStrategy()),
TableWaveformEntry(0.2, 0.3, LinearInterpolationStrategy()),
TableWaveformEntry(0.3, 0.3, JumpInterpolationStrategy())])
self.assertEqual(validated, (TableWaveformEntry(0.0, 0.2, HoldInterpolationStrategy()),
TableWaveformEntry(0.1, 0.2, LinearInterpolationStrategy()),
TableWaveformEntry(0.1, 0.3, HoldInterpolationStrategy()),
TableWaveformEntry(0.3, 0.3, JumpInterpolationStrategy())))
def test_get_entries_auto_insert(self) -> None:
table = TablePulseTemplate({0: [('foo', 'v', 'linear'),
('bar', 0, 'jump')],
1: [(0, 3, 'linear'),
('bar+foo', 2, 'linear')]})
instantiated_entries = table.get_entries_instantiated({'v': 2.3, 'foo': 1, 'bar': 4})
self.assertEqual({0: [(0, 2.3, HoldInterpolationStrategy()),
(1, 2.3, LinearInterpolationStrategy()),
(4, 0, JumpInterpolationStrategy()),
(5, 0, HoldInterpolationStrategy())],
1: [(0, 3, LinearInterpolationStrategy()),
(5, 2, LinearInterpolationStrategy())]}, instantiated_entries)
def test_from_entry_list(self):
entries = {
0: [(0, 9, HoldInterpolationStrategy()),
(1, 2, HoldInterpolationStrategy()),
(4, 1, LinearInterpolationStrategy())],
1: [(0, 8, HoldInterpolationStrategy()),
(1, 1, HoldInterpolationStrategy()),
(4, 2, LinearInterpolationStrategy())],
2: [(0, 7, HoldInterpolationStrategy()),
(1, 3, HoldInterpolationStrategy()),
(4, 3, LinearInterpolationStrategy())]
}
tpt = TablePulseTemplate.from_entry_list([(0, 9, 8, 7),
(1, 2, 1, 3, 'hold'),
(4, 1, 2, 3, 'linear')],
identifier='tpt')
self.assertEqual(tpt.entries, entries)
self.assertEqual(tpt.identifier, 'tpt')
tpt = TablePulseTemplate.from_entry_list([(0, 9, 8, 7, 'hold'),
(1, 2, 1, 3, 'hold'),
(4, 1, 2, 3, 'linear')],
identifier='tpt2')
self.assertEqual(tpt.entries, entries)
entries = {k: entries[i] for k, i in zip('ABC', [0, 1, 2])}
tpt = TablePulseTemplate.from_entry_list([(0, 9, 8, 7),
(1, 2, 1, 3, 'hold'),
(4, 1, 2, 3, 'linear')],
identifier='tpt3',
channel_names=['A', 'B', 'C'])
self.assertEqual(tpt.entries, entries)
self.assertEqual(tpt.identifier, 'tpt3')
entries = {
0: [(0, 9, HoldInterpolationStrategy()),
(1, 2, HoldInterpolationStrategy()),
(4, 1, HoldInterpolationStrategy())],
1: [(0, 8, HoldInterpolationStrategy()),
(1, 1, HoldInterpolationStrategy()),
(4, 2, HoldInterpolationStrategy())],
2: [(0, 7, HoldInterpolationStrategy()),
(1, 3, HoldInterpolationStrategy()),
(4, 3, HoldInterpolationStrategy())]
}
tpt = TablePulseTemplate.from_entry_list([(0, 9, 8, 7), (1, 2, 1, 3),
(4, 1, 2, 3)],
identifier='tpt4')
self.assertEqual(tpt.entries, entries)
def test_linear_interpolation(self):
start = (-1, -1)
end = (3, 3)
t = np.arange(-1, 4, dtype=float)
strat = LinearInterpolationStrategy()
result = strat(start, end, t)
self.assertTrue(all(t == result))
def test_build_waveform_time_type(self):
from qupulse.utils.types import TimeType
table = TablePulseTemplate({0: [(0, 0),
('foo', 'v', 'linear'),
('bar', 0, 'jump')]},
parameter_constraints=['foo>1'],
measurements=[('M', 'b', 'l'),
('N', 1, 2)])
parameters = {'v': 2.3,
'foo': TimeType.from_float(1.), 'bar': TimeType.from_float(4),
'b': TimeType.from_float(2), 'l': TimeType.from_float(1)}
channel_mapping = {0: 'ch'}
with self.assertRaises(ParameterConstraintViolation):
table.build_waveform(parameters=parameters,
channel_mapping=channel_mapping)
parameters['foo'] = TimeType.from_float(1.1)
waveform = table.build_waveform(parameters=parameters,
channel_mapping=channel_mapping)
self.assertIsInstance(waveform, TableWaveform)
self.assertEqual(waveform._table,
((0, 0, HoldInterpolationStrategy()),
(TimeType.from_float(1.1), 2.3, LinearInterpolationStrategy()),
(4, 0, JumpInterpolationStrategy())))
self.assertEqual(waveform._channel_id,
'ch')
def test_build_waveform_single_channel(self):
table = TablePulseTemplate({0: [(0, 0),
('foo', 'v', 'linear'),
('bar', 0, 'jump')]},
parameter_constraints=['foo>1'],
measurements=[('M', 'b', 'l'),
('N', 1, 2)])
parameters = {'v': 2.3, 'foo': 1, 'bar': 4, 'b': 2, 'l': 1}
channel_mapping = {0: 'ch'}
with self.assertRaises(ParameterConstraintViolation):
table.build_waveform(parameters=parameters,
channel_mapping=channel_mapping)
parameters['foo'] = 1.1
waveform = table.build_waveform(parameters=parameters,
channel_mapping=channel_mapping)
self.assertIsInstance(waveform, TableWaveform)
self.assertEqual(waveform._table,
((0, 0, HoldInterpolationStrategy()),
(1.1, 2.3, LinearInterpolationStrategy()),
(4, 0, JumpInterpolationStrategy())))
self.assertEqual(waveform._channel_id,
'ch')
def test_from_table(self):
expected = ConstantWaveform(0.1, 0.2, 'A')
for interp in (HoldInterpolationStrategy(), JumpInterpolationStrategy(), LinearInterpolationStrategy()):
wf = TableWaveform.from_table('A',
[TableWaveformEntry(0.0, 0.2, interp),
TableWaveformEntry(0.1, 0.2, interp)])
self.assertEqual(expected, wf)
def test_known_interpolation_strategies(self):
strategies = [("linear", LinearInterpolationStrategy()),
("hold", HoldInterpolationStrategy()),
("jump", JumpInterpolationStrategy())]
for strat_name, strat_val in strategies:
entry = TableEntry('a', Expression('b'), strat_name)
self.assertEqual(entry.t, Expression('a'))
self.assertEqual(entry.v, Expression('b'))
self.assertEqual(entry.interp, strat_val)
def test_repr_str(self):
#Test hash
strategies = {
LinearInterpolationStrategy():
("linear", "<Linear Interpolation>"),
HoldInterpolationStrategy(): ("hold", "<Hold Interpolation>"),
JumpInterpolationStrategy(): ("jump", "<Jump Interpolation>")
}
for strategy in strategies:
repr_ = strategies[strategy][1]
str_ = strategies[strategy][0]
self.assertEqual(repr(strategy), repr_)
self.assertEqual(str(strategy), str_)
self.assertTrue(
LinearInterpolationStrategy() != HoldInterpolationStrategy())
self.assertTrue(
LinearInterpolationStrategy() != JumpInterpolationStrategy())
self.assertTrue(
JumpInterpolationStrategy() != HoldInterpolationStrategy())
def test_build_waveform_single_channel_with_measurements(self):
ppt = PointPulseTemplate([('t1', 'A'),
('t2', 0., 'hold'),
('t1+t2', 'B+C', 'linear')], [0], measurements=[('M', 'n', 1), ('L', 'n', 1)])
parameters = {'t1': 0.1, 't2': 1., 'A': 1., 'B': 2., 'C': 19., 'n': 0.2}
wf = ppt.build_waveform(parameters=parameters, channel_mapping={0: 1})
expected = PointWaveform(1, [(0, 1., HoldInterpolationStrategy()),
(0.1, 1., HoldInterpolationStrategy()),
(1., 0., HoldInterpolationStrategy()),
(1.1, 21., LinearInterpolationStrategy())])
self.assertEqual(wf, expected)
def test_build_waveform_multi_channel(self):
table = TablePulseTemplate({0: [(0, 0),
('foo', 'v', 'linear'),
('bar', 0, 'jump')],
3: [(0, 1),
('bar+foo', 0, 'linear')]},
parameter_constraints=['foo>1'],
measurements=[('M', 'b', 'l'),
('N', 1, 2)])
parameters = {'v': 2.3, 'foo': 1, 'bar': 4, 'b': 2, 'l': 1}
channel_mapping = {0: 'ch', 3: 'oh'}
with self.assertRaises(ParameterConstraintViolation):
table.build_waveform(parameters=parameters,
channel_mapping=channel_mapping)
parameters['foo'] = 1.1
waveform = table.build_waveform(parameters=parameters,
channel_mapping=channel_mapping)
self.assertIsInstance(waveform, MultiChannelWaveform)
self.assertEqual(len(waveform._sub_waveforms), 2)
channels = {'oh', 'ch'}
for wf in waveform._sub_waveforms:
self.assertIsInstance(wf, TableWaveform)
self.assertIn(wf._channel_id, channels)
channels.remove(wf._channel_id)
if wf.defined_channels == {'ch'}:
self.assertEqual(wf._table,
((0, 0, HoldInterpolationStrategy()),
(1.1, 2.3, LinearInterpolationStrategy()),
(4, 0, JumpInterpolationStrategy()),
(5.1, 0, HoldInterpolationStrategy())))
elif wf.defined_channels == {'oh'}:
self.assertEqual(wf._table,
((0, 1, HoldInterpolationStrategy()),
(5.1, 0, LinearInterpolationStrategy())))
def test_build_waveform_single_channel(self):
ppt = PointPulseTemplate([('t1', 'A'), ('t2', 0., 'hold'),
('t1+t2', 'B+C', 'linear')], [0])
parameters = {'t1': 0.1, 't2': 1., 'A': 1., 'B': 2., 'C': 19.}
wf = ppt.build_waveform(parameters=parameters, channel_mapping={0: 1})
expected = PointWaveform.from_table(
1, [(0, 1., HoldInterpolationStrategy()),
(0.1, 1., HoldInterpolationStrategy()),
(1., 0., HoldInterpolationStrategy()),
(1.1, 21., LinearInterpolationStrategy())])
self.assertIsInstance(wf, PointWaveform)
self.assertEqual(wf, expected)
class TablePulseTemplate(AtomicPulseTemplate, ParameterConstrainer):
"""The TablePulseTemplate class implements pulses described by a table with time, voltage and interpolation strategy
inputs. The interpolation strategy describes how the voltage between the entries is interpolated(see also
InterpolationStrategy.) It can define multiple channels of which each has a separate table. If they do not have the
same length the shorter channels are extended to the longest duration.
If the time entries of all channels are equal it is more convenient to use the :paramrefPointPulseTemplate`."""
interpolation_strategies = {
'linear': LinearInterpolationStrategy(),
'hold': HoldInterpolationStrategy(),
'jump': JumpInterpolationStrategy(),
'default': HoldInterpolationStrategy()
}
def __init__(self,
entries: Dict[ChannelID, Sequence[EntryInInit]],
identifier: Optional[str] = None,
*,
parameter_constraints: Optional[List[Union[
str, ParameterConstraint]]] = None,
measurements: Optional[List[MeasurementDeclaration]] = None,
consistency_check: bool = True,
registry: PulseRegistryType = None) -> None:
"""
Construct a `TablePulseTemplate` from a dict which maps channels to their entries. By default the consistency
of the provided entries is checked. There are two static functions for convenience construction: from_array and
from_entry_list.
Args:
entries: A dictionary that maps channel ids to a list of entries. An entry is a
(time, voltage[, interpolation strategy]) tuple or a TableEntry
identifier: Used for serialization
parameter_constraints: Constraint list that is forwarded to the ParameterConstrainer superclass
measurements: Measurement declaration list that is forwarded to the MeasurementDefiner superclass
consistency_check: If True the consistency of the times will be checked on construction as far as possible
"""
AtomicPulseTemplate.__init__(self,
identifier=identifier,
measurements=measurements)
ParameterConstrainer.__init__(
self, parameter_constraints=parameter_constraints)
if not entries:
raise ValueError(
"Cannot construct an empty TablePulseTemplate (no entries given). There is currently no "
"specific reason for this. Please submit an issue if you need this 'feature'."
)
self._entries = dict((ch, list()) for ch in entries.keys())
for channel, channel_entries in entries.items():
if len(channel_entries) == 0:
raise ValueError('Channel {} is empty'.format(channel))
for entry in channel_entries:
self._add_entry(channel, TableEntry(*entry))
self._duration = self.calculate_duration()
self._table_parameters = set(
var for channel_entries in self.entries.values()
for entry in channel_entries
for var in itertools.chain(entry.t.variables, entry.v.variables
)) | self.constrained_parameters
if self.duration == 0:
warnings.warn(
'Table pulse template with duration 0 on construction.',
category=ZeroDurationTablePulseTemplate)
if consistency_check:
# perform a simple consistency check. All inequalities with more than one free variable are ignored as the
# sympy solver does not support them
# collect all conditions
inequalities = [eq.sympified_expression for eq in self._parameter_constraints] +\
[sympy.Le(previous_entry.t.underlying_expression, entry.t.underlying_expression)
for channel_entries in self._entries.values()
for previous_entry, entry in zip(channel_entries, channel_entries[1:])]
# test if any condition is already dissatisfied
if any(
isinstance(eq, BooleanAtom) and bool(eq) is False
for eq in inequalities):
raise ValueError(
'Table pulse template has impossible parametrization')
# filter conditions that are inequalities with one free variable and test if the solution set is empty
inequalities = [
eq for eq in inequalities
if isinstance(eq, sympy.Rel) and len(eq.free_symbols) == 1
]
if not sympy.reduce_inequalities(inequalities):
raise ValueError(
'Table pulse template has impossible parametrization')
self._register(registry=registry)
def _add_entry(self, channel, new_entry: TableEntry) -> None:
ch_entries = self._entries[channel]
# comparisons with Expression can yield None -> use 'is True' and 'is False'
if (new_entry.t < 0) is True:
raise ValueError(
'Time parameter number {} of channel {} is negative.'.format(
len(ch_entries), channel))
for previous_entry in ch_entries:
if (new_entry.t < previous_entry.t) is True:
raise ValueError(
'Time parameter number {} of channel {} is smaller than a previous one'
.format(len(ch_entries), channel))
self._entries[channel].append(new_entry)
@property
def entries(self) -> Dict[ChannelID, List[TableEntry]]:
return self._entries
def get_entries_instantiated(self, parameters: Dict[str, numbers.Real]) \
-> Dict[ChannelID, List[TableWaveformEntry]]:
"""Compute an instantiated list of the table's entries.
Args:
parameters (Dict(str -> Parameter)): A mapping of parameter names to Parameter objects.
Returns:
(float, float)-list of all table entries with concrete values provided by the given
parameters.
"""
if not (self.table_parameters <= set(parameters.keys())):
raise ParameterNotProvidedException(
(self.table_parameters - set(parameters.keys())).pop())
instantiated_entries = dict(
) # type: Dict[ChannelID,List[TableWaveformEntry]]
for channel, channel_entries in self._entries.items():
instantiated = [
entry.instantiate(parameters) for entry in channel_entries
]
# Add (0, v) entry if wf starts at finite time
if instantiated[0].t > 0:
instantiated.insert(
0,
TableWaveformEntry(
0, instantiated[0].v,
TablePulseTemplate.interpolation_strategies['hold']))
instantiated_entries[channel] = instantiated
duration = max(instantiated[-1].t
for instantiated in instantiated_entries.values())
# ensure that all channels have equal duration
for channel, instantiated in instantiated_entries.items():
final_entry = instantiated[-1]
if final_entry.t < duration:
instantiated.append(
TableWaveformEntry(
duration, final_entry.v,
TablePulseTemplate.interpolation_strategies['hold']))
instantiated_entries[channel] = instantiated
return instantiated_entries
@property
def table_parameters(self) -> Set[str]:
return self._table_parameters
@property
def parameter_names(self) -> Set[str]:
return self.table_parameters | self.measurement_parameters | self.constrained_parameters
@property
def duration(self) -> ExpressionScalar:
return self._duration
def calculate_duration(self) -> ExpressionScalar:
duration_expressions = [
entries[-1].t for entries in self._entries.values()
]
duration_expression = sympy.Max(*(expr.sympified_expression
for expr in duration_expressions))
return ExpressionScalar(duration_expression)
@property
def defined_channels(self) -> Set[ChannelID]:
return set(self._entries.keys())
def get_serialization_data(self,
serializer: Optional[Serializer] = None
) -> Dict[str, Any]:
data = super().get_serialization_data(serializer)
if serializer: # compatibility to old serialization routines, deprecated
data = dict()
local_data = dict(
entries=dict(
(channel,
[entry.get_serialization_data() for entry in channel_entries])
for channel, channel_entries in self.entries.items()),
parameter_constraints=[str(c) for c in self.parameter_constraints],
measurements=self.measurement_declarations)
data.update(**local_data)
return data
def build_waveform(
self, parameters: Dict[str, numbers.Real],
channel_mapping: Dict[ChannelID, Optional[ChannelID]]
) -> Optional[Union[TableWaveform, MultiChannelWaveform]]:
self.validate_parameter_constraints(parameters, volatile=set())
if all(channel_mapping[channel] is None
for channel in self.defined_channels):
return None
instantiated = [(channel_mapping[channel], instantiated_channel)
for channel, instantiated_channel in
self.get_entries_instantiated(parameters).items()
if channel_mapping[channel] is not None]
if self.duration.evaluate_numeric(**parameters) == 0:
return None
waveforms = [
TableWaveform(*ch_instantiated) for ch_instantiated in instantiated
]
if len(waveforms) == 1:
return waveforms.pop()
else:
return MultiChannelWaveform(waveforms)
@staticmethod
def from_array(times: np.ndarray, voltages: np.ndarray,
channels: List[ChannelID]) -> 'TablePulseTemplate':
"""Static constructor to build a TablePulse from numpy arrays.
Args:
times: 1D numpy array with time values
voltages: 1D or 2D numpy array with voltage values
channels: channels to define
Returns:
TablePulseTemplate with the given values, hold interpolation everywhere and no free
parameters.
"""
if times.ndim == 0 or voltages.ndim == 0:
raise ValueError('Zero dimensional input is not accepted.')
if times.ndim > 2 or voltages.ndim > 2:
raise ValueError(
'Three or higher dimensional input is not accepted.')
if times.ndim == 2 and times.shape[0] != len(channels):
raise ValueError(
'First dimension of times must be equal to the number of channels'
)
if voltages.ndim == 2 and voltages.shape[0] != len(channels):
raise ValueError(
'First dimension of voltages must be equal to the number of channels'
)
if voltages.shape[-1] != times.shape[-1]:
ValueError('Different number of entries for times and voltages')
return TablePulseTemplate(
dict((channel,
list(
zip(times if times.ndim == 1 else times[i, :],
voltages if voltages.ndim == 1 else voltages[i, :])))
for i, channel in enumerate(channels)))
@staticmethod
def from_entry_list(entry_list: List[Tuple],
channel_names: Optional[List[ChannelID]] = None,
**kwargs) -> 'TablePulseTemplate':
"""Static constructor for a TablePulseTemplate where all channel's entries share the same times.
:param entry_list: List of tuples of the form (t, v_1, ..., v_N[, interp])
:param channel_names: Optional list of channel identifiers to use. Default is [0, ..., N-1]
:param kwargs: Forwarded to TablePulseTemplate constructor
:return: TablePulseTemplate with
"""
# TODO: Better doc string
def is_valid_interpolation_strategy(inter):
return inter in TablePulseTemplate.interpolation_strategies or isinstance(
inter, InterpolationStrategy)
# determine number of channels
max_len = max(len(data) for data in entry_list)
min_len = min(len(data) for data in entry_list)
if max_len - min_len > 1:
raise ValueError(
'There are entries of contradicting lengths: {}'.format(
set(len(t) for t in entry_list)))
elif max_len - min_len == 1:
num_chan = min_len - 1
else:
# figure out whether all last entries are interpolation strategies
if all(
is_valid_interpolation_strategy(interp)
for *data, interp in entry_list):
num_chan = min_len - 2
else:
num_chan = min_len - 1
# insert default interpolation strategy key
entry_list = [(t, *data, interp) if len(data) == num_chan else
(t, *data, interp, 'default')
for t, *data, interp in entry_list]
for *_, last_voltage, _ in entry_list:
if last_voltage in TablePulseTemplate.interpolation_strategies:
warnings.warn(
'{} is also an interpolation strategy name but handled as a voltage. Is it intended?'
.format(last_voltage), AmbiguousTablePulseEntry)
if channel_names is None:
channel_names = list(range(num_chan))
elif len(channel_names) != num_chan:
raise ValueError(
'Number of channel identifiers does not correspond to the number of channels.'
)
parsed = {channel_name: [] for channel_name in channel_names}
for time, *voltages, interp in entry_list:
for channel_name, volt in zip(channel_names, voltages):
parsed[channel_name].append((time, volt, interp))
return TablePulseTemplate(parsed, **kwargs)
@property
def integral(self) -> Dict[ChannelID, ExpressionScalar]:
expressions = dict()
for channel, channel_entries in self._entries.items():
pre_entry = TableEntry(0, channel_entries[0].v, None)
post_entry = TableEntry(self.duration, channel_entries[-1].v,
'hold')
channel_entries = [pre_entry] + channel_entries + [post_entry]
expressions[channel] = TableEntry._sequence_integral(
channel_entries, lambda v: v.sympified_expression)
return expressions
def _as_expression(self) -> Dict[ChannelID, ExpressionScalar]:
expressions = dict()
for channel, channel_entries in self._entries.items():
pre_value = channel_entries[0].v.sympified_expression
post_value = channel_entries[-1].v.sympified_expression
expressions[channel] = TableEntry._sequence_as_expression(
channel_entries,
lambda v: v.sympified_expression,
t=self._AS_EXPRESSION_TIME,
pre_value=pre_value,
post_value=post_value)
return expressions