def _plot(self, axes_list, data=None):
"""
Plot 1: self.data['tau'], the list of times specified for a given experiment, verses self.data['counts'], the data
received for each time
Plot 2: the pulse sequence performed at the current time (or if plotted statically, the last pulse sequence
performed
Args:
axes_list: list of axes to write plots to (uses first 2)
data (optional) dataset to plot (dictionary that contains keys counts, tau), if not provided use self.data
"""
# if self.scripts['find_nv'].is_running: #self.scripts['find_nv'].data['maximum_point']:
# # self.scripts['find_nv'].plot(axes_list)
# self.scripts['find_nv']._plot(axes_list)
# self._plot_refresh = True
# else:
if data is None:
data = self.data
if 'counts' in data.keys():
# The following does not work for pulsedelays; you need to comment out the 'if' for it to work.
# if counts != []:
# plot_1d_simple_timetrace_ns(axes_list[0], data['tau'], [data['counts'])
# print('plotting with tau values: ', data['tau'])
plot_1d_simple_timetrace_ns(axes_list[0], data['tau'], [data['counts']])
plot_pulses(axes_list[1], self.pulse_sequences[self.sequence_index])
def _plot_validate(self, axes_list):
"""
Preview pulse sequence by plotting first and last sequence to plots 1 and 0, respectively
Args:
axes_list: List containing axes to plot to
Returns:
"""
axis0 = axes_list[0]
axis1 = axes_list[1]
pulse_sequences, tau_list, _ = self.create_pulse_sequences(
logging=False)
# if pulse_sequences[0]:
if pulse_sequences:
plot_pulses(axis0, pulse_sequences[0])
axis0.set_title(
'Pulse Visualization for Minimum tau (tau = {:f} ns)'.format(
tau_list[0]))
plot_pulses(axis1, pulse_sequences[-1])
axis1.set_title(
'Pulse Visualization for Maximum tau (tau = {:f} ns)'.format(
tau_list[-1]))
else:
print('no pulse sequences passed validation!!!')
def _plot(self, axes_list, data=None):
"""
Plot 1: self.data['tau'], the list of times specified for a given experiment, verses self.data['counts'], the data
received for each time
Plot 2: the pulse sequence performed at the current time (or if plotted statically, the last pulse sequence
performed
Args:
axes_list: list of axes to write plots to (uses first 2)
data (optional) dataset to plot (dictionary that contains keys counts, tau), if not provided use self.data
"""
# if self.scripts['find_nv'].is_running: #self.scripts['find_nv'].data['maximum_point']:
# # self.scripts['find_nv'].plot(axes_list)
# self.scripts['find_nv']._plot(axes_list)
# self._plot_refresh = True
# else:
if data is None:
data = self.data
if 'counts' in data.keys():
# The following does not work for pulsedelays; you need to comment out the 'if' for it to work.
# if counts != []:
# plot_1d_simple_timetrace_ns(axes_list[0], data['tau'], [data['counts'])
# print('plotting with tau values: ', data['tau'])
plot_1d_simple_timetrace_ns(axes_list[0], data['tau'],
[data['counts']])
plot_pulses(axes_list[1],
self.pulse_sequences[self.sequence_index])
def _plot(self, axes_list, data=None):
"""
Very similar to plot for PulseBlasterBaseScript but here deals with case where first plot has counts=[], using
PulseBlasterBaseScript plot leads to errors
Plot 1: self.data['tau'], the list of times specified for a given experiment, verses self.data['counts'], the data
received for each time
Plot 2: the pulse sequence performed at the current time (or if plotted statically, the last pulse sequence
performed
Args:
axes_list: list of axes to write plots to (uses first 2)
data (optional) dataset to plot (dictionary that contains keys counts, tau), if not provided use self.data
"""
if data is None:
data = self.data
counts = data['counts']
x_data = data['tau']
axis1 = axes_list[0]
plot_1d_simple_timetrace_ns(axis1, x_data, [counts])
axis2 = axes_list[1]
plot_pulses(axis2, self.pulse_sequences[self.sequence_index])
def _plot(self, axes_list, data=None):
"""
Very similar to plot for PulseBlasterBaseScript but here deals with case where first plot has counts=[], using
PulseBlasterBaseScript plot leads to errors
Plot 1: self.data['tau'], the list of times specified for a given experiment, verses self.data['counts'], the data
received for each time
Plot 2: the pulse sequence performed at the current time (or if plotted statically, the last pulse sequence
performed
Args:
axes_list: list of axes to write plots to (uses first 2)
data (optional) dataset to plot (dictionary that contains keys counts, tau), if not provided use self.data
"""
if data is None:
data = self.data
counts = data['counts']
x_data = data['tau']
axis1 = axes_list[0]
plot_1d_simple_timetrace_ns(axis1, x_data, [counts])
axis2 = axes_list[1]
plot_pulses(axis2, self.pulse_sequences[self.sequence_index])
def _plot(self, axes_list, data=None):
'''
Plot 1: self.data['tau'], the list of times specified for a given experiment, verses self.data['counts'], the data
received for each time
Plot 2: the pulse sequence performed at the current time (or if plotted statically, the last pulse sequence
performed
Args:
axes_list: list of axes to write plots to (uses first 2)
data (optional) dataset to plot, if not provided use self.data
'''
if data is None:
data = self.data
mw_frequencies = data['mw_frequencies']
esr_counts = data['esr_counts']
axis1 = axes_list[0]
if not esr_counts == []:
counts = esr_counts
plot_esr(axis1, mw_frequencies[0:len(counts)], counts)
axis1.hold(False)
axis2 = axes_list[1]
plot_pulses(axis2, self.pulse_sequences[0])
def _plot(self, axes_list, data = None):
'''
Plot 1: self.data['tau'], the list of times specified for a given experiment, verses self.data['counts'], the data
received for each time
Plot 2: the pulse sequence performed at the current time (or if plotted statically, the last pulse sequence
performed
Args:
axes_list: list of axes to write plots to (uses first 2)
data (optional) dataset to plot, if not provided use self.data
'''
if data is None:
data = self.data
mw_frequencies = data['mw_frequencies']
esr_counts = data['esr_counts']
axis1 = axes_list[0]
if not esr_counts == []:
counts = esr_counts
plot_esr(axis1, mw_frequencies[0:len(counts)], counts)
axis1.hold(False)
axis2 = axes_list[1]
plot_pulses(axis2, self.pulse_sequences[0])
def _plot_validate(self, axes_list):
"""
Preview pulse sequence by plotting first and last sequence to plots 1 and 0, respectively
Args:
axes_list: List containing axes to plot to
Returns:
"""
axis0 = axes_list[0]
axis1 = axes_list[1]
pulse_sequences, tau_list, _ = self.create_pulse_sequences(logging=False)
# if pulse_sequences[0]:
if pulse_sequences:
plot_pulses(axis0, pulse_sequences[0])
axis0.set_title('Pulse Visualization for Minimum tau (tau = {:f} ns)'.format(tau_list[0]))
plot_pulses(axis1, pulse_sequences[-1])
axis1.set_title('Pulse Visualization for Maximum tau (tau = {:f} ns)'.format(tau_list[-1]))
else:
print('no pulse sequences passed validation!!!')
def _plot(self, axes_list, data=None):
'''
Plot 1: self.data['tau'], the list of times specified for a given experiment, verses self.data['counts'], the data
received for each time
Plot 2: the pulse sequence performed at the current time (or if plotted statically, the last pulse sequence
performed
Args:
axes_list: list of axes to write plots to (uses first 2)
data (optional) dataset to plot (dictionary that contains keys counts_for_mw, mw_power_values), if not provided use self.data
'''
if data is None:
data = self.data
counts = data['counts_for_mw']
x_data = data['mw_power_values']
axis1 = axes_list[0]
if not counts == []:
plot_1d_simple_timetrace_ns(axis1,
x_data, [counts],
x_label='microwave power (dBm)')
axis2 = axes_list[1]
plot_pulses(axis2, self.pulse_sequences[self.sequence_index])