nanotune.fit.pinchofffit

class nanotune.fit.pinchofffit.PinchoffFit(run_id: int, db_name: str, db_folder: Optional[str] = None, gradient_percentile: float = 25, get_transition_from_fit: bool = False, **kwargs)

Bases: DataFit

Data fitting class for pinch-off curves.

gradient_percentile

percentage of the highest gradient of the traces, above which a portion of the trace is considered to be dropping, i.e. to be the transition interval.

get_transition_from_fit

whether to get transition interval from the fit. If not, filtered data is used.

property range_update_directives: List[str]

List of directives how nearby gates need to be adjusted. Depends on the signal strength of the trace.

find_fit() → None

Fits a pinchoff curve to a hyperbolic tangent and extracts transition voltages as well as interval.

compute_transition_interval() → None

Determines the transition interval based on a trace’s gradient, for all traces (readout methods) measured.

compute_transition_voltage() → None

Computes the transition voltage based in a trace’s gradient.

compute_initial_guess(readout_method: str = 'transport') → Tuple[Tuple[List[float], List[float]], List[float]]

Computes initial guess for fitting.

fit_function(v: ndarray[Any, dtype[float64]], params: List[float]) → ndarray[Any, dtype[float64]]

Function to fit pinch off curves.

Parameters

• v – voltage vector in V.

• params – parameter vector with the following entries: [amplitude, slope, shift, tanh sign].

Returns

np.array – tanh function values.

plot_fit(ax: Optional[Axes] = None, colorbar: Optional[Colorbar] = None, save_figures: bool = True, plot_gradient: Optional[bool] = True, plot_smooth: Optional[bool] = True, filename: Optional[str] = None, file_location: Optional[str] = None, plot_params: Optional[Dict[str, Union[str, float, int, bool, List[float]]]] = None, plot_format: str = 'png') → Tuple[Axes, Colorbar]

Plots the measurement including the fit, gradient and filtered trace.

plot_features(save_figures: bool = True, ax: Optional[Axes] = None, highlight_color: Optional[str] = 'indianred', fill_color: Optional[str] = 'indianred', fill_hatch: Optional[str] = None, filename: Optional[str] = None, file_location: Optional[str] = None, plot_params: Optional[Dict[str, Union[str, float, int, bool, List[float]]]] = None, plot_format: str = 'png') → Tuple[Axes, Colorbar]

Plots measurement, indicating some of the extracted features.