def plot_csq_trace(dat: DatHDF, cutoff: Optional[float] = None) -> Data1D:
plotter = OneD(dat=dat)
plotter.TEMPLATE = 'simple_white'
fig = plotter.figure(xlabel='CSQ Gate (mV)',
ylabel='Current (nA)',
title='CS current vs CSQ gate')
x = dat.Data.x
data = dat.Data.i_sense
if cutoff:
upper_lim = U.get_data_index(x, cutoff)
x, data = x[:upper_lim], data[:upper_lim]
fig.add_trace(plotter.trace(data=data, x=x))
fig.show()
return Data1D(x=x, data=data)
from dat_analysis.analysis_tools.general_fitting import FitInfo
from dat_analysis.dat_analysis.characters import DELTA
from dat_analysis.plotting.plotly.dat_plotting import OneD, TwoD
from dat_analysis.core_util import Data1D
from dat_analysis.analysis_tools.nrg import NRGParams, NrgUtil
import dat_analysis.useful_functions as U
from temp import get_avg_entropy_data, get_avg_i_sense_data, get_linear_theta, get_initial_params, get_2d_data
if TYPE_CHECKING:
from dat_analysis.dat_object.make_dat import DatHDF
p1d = OneD(dat=None)
p2d = TwoD(dat=None)
p1d.TEMPLATE = 'simple_white'
p2d.TEMPLATE = 'simple_white'
NRG_OCC_FIT_NAME = 'csq_forced_theta'
CSQ_DATNUM = 2197
class StrongGammaNoise:
def __init__(self, dat: DatHDF):
self.dat = dat
# The averaged data which does show some signal, but quite small given the number of repeats and duration
self.avg_data = get_avg_entropy_data(self.dat, lambda _: False,
CSQ_DATNUM)
self.avg_data.x = self.avg_data.x / 100 # Convert to real mV