Data fitting

Base class

The abstract DataFit class is the base for all fitting classes. Its main purpose is to establish the presence of find_fit and plot_fit methods, as well as the range_update_directives attribute required by Tuningstages.

The find_fit method extracts features and determines the transport regime, i.e. open, closed or intermediate. Its implementation needs to update self._features with the extracted features. In case of a closed or open regime, the range_update_directives list is populated with suggestions on how voltages need to be adjusted, e.g. more positive or negative. The plot_fit method should display a plot with important features shown.

It also provides a method to save extracted features to metadata. Specifically, the following code is used for this:

nt.set_database(self.db_name, db_folder=self.db_folder)
ds = qc.load_by_run_spec(captured_run_id=self.qc_run_id)
try:
    nt_meta = json.loads(ds.get_metadata(nt.meta_tag))
except (RuntimeError, TypeError, OperationalError):
    nt_meta = {}
nt_meta["features"] = self.features
ds.add_metadata(nt.meta_tag, json.dumps(nt_meta))

More details about the features extracted for each measurement can be found in Pinchoff, Dot fit and Coulomb oscillation fit.

• Pinchoff
• Dot fit
• Coulomb oscillation fit