def reset_time(self, extend_only=False):
'''
Args:
extend_only (bool) : will just extend the time in the segment and not reset it if set to true [do not use when composing wavoforms...].
Allings all segments togeter and sets the input time to 0,
e.g. ,
chan1 : waveform until 70 ns
chan2 : waveform until 140ns
-> totaltime will be 140 ns,
when you now as a new pulse (e.g. at time 0, it will actually occur at 140 ns in both blocks)
'''
n_channels = len(self.channels)
shape = list(self.shape)
time_data = np.empty([n_channels] + shape)
for i in range(len(self.channels)):
time_data[i] = upconvert_dimension(
getattr(self, self.channels[i]).total_time, shape)
times = np.amax(time_data, axis=0)
times, axis = reduce_arr(times)
if len(axis) == 0:
loop_obj = times
else:
loop_obj = lp.loop_obj(no_setpoints=True)
loop_obj.add_data(times, axis)
for i in self.channels:
segment = getattr(self, i)
segment.reset_time(loop_obj, False)
def reset_time(self, extend_only=False):
'''
Args:
extend_only (bool) : will just extend the time in the segment and not reset it if set to true [do not use when composing wavoforms...].
Allings all segments togeter and sets the input time to 0,
e.g. ,
chan1 : waveform until 70 ns
chan2 : waveform until 140ns
-> totaltime will be 140 ns,
when you now as a new pulse (e.g. at time 0, it will actually occur at 140 ns in both blocks)
'''
n_branches = len(self.branches)
n_channels = len(self.branches[0].channels)
shape = list(self.shape)
time_data = np.empty([n_branches * n_channels] + shape)
for ibranch, branch in enumerate(self.branches):
for ich, ch in enumerate(branch.channels):
time_data[ibranch * n_channels + ich] = upconvert_dimension(
branch[ch].total_time, shape)
times = np.amax(time_data, axis=0)
times, axis = reduce_arr(times)
logging.info(f'times {times}')
if len(axis) == 0:
loop_obj = times
else:
loop_obj = lp.loop_obj(no_setpoints=True)
loop_obj.add_data(times, axis)
for branch in self.branches:
for ch in branch.channels:
branch[ch].reset_time(loop_obj, False)
def total_time(self):
shape = list(self.shape)
n_branches = len(self.branches)
time_data = np.empty([n_branches] + shape)
for i, branch in enumerate(self.branches):
time_data[i] = upconvert_dimension(branch.total_time, shape)
times = np.amax(time_data, axis=0)
return times
def _start_time(self):
'''
get the total time that will be uploaded for this segment to the AWG
Returns:
times (np.ndarray) : numpy array with the total time (maximum of all the channels), for all the different loops executed.
'''
shape = list(self.shape)
n_channels = len(self.channels)
time_data = np.empty([n_channels] + shape)
for i in range(len(self.channels)):
time_data[i] = upconvert_dimension(
getattr(self, self.channels[i]).start_time, shape)
times = np.amax(time_data, axis=0)
return times
def total_time(self):
'''
get the total time that will be uploaded for this segment to the AWG
Returns:
times (np.ndarray) : numpy array with the total time (maximum of all the channels), for all the different loops executed.
'''
if self.render_mode and self._total_times is not None:
return self._total_times
shape = list(self.shape)
n_channels = len(self.channels)
time_data = np.empty([n_channels] + shape)
for i, channel in enumerate(self.channels):
time_data[i] = upconvert_dimension(self[channel].total_time, shape)
times = np.amax(time_data, axis=0)
if self.render_mode:
self._total_times = times
return times
