pygsti.data.freedataset.FreeformDataSet

pygsti.data.freedataset.FreeformDataSet#

class FreeformDataSet(circuits=None, circuit_indices=None)#

Bases: object

An association between Circuits and arbitrary data.

Parameters:

  • circuits (list of (tuples or Circuits), optional) – Each element is a tuple of operation labels or a Circuit object. Indices for these strings are assumed to ascend from 0. These indices must correspond to the time series of spam-label indices (above). Only specify this argument OR circuit_indices, not both.

  • circuit_indices (ordered dictionary, optional) – An OrderedDict with keys equal to circuits (tuples of operation labels) and values equal to integer indices associating a row/element of counts with the circuit. Only specify this argument OR circuits, not both.

Methods

__init__([circuits, circuit_indices])

copy()

Make a copy of this FreeformDataSet.

items()

Iterator over (circuit, info_dict) pairs.

keys()

Returns the circuits used as keys of this DataSet.

to_dataframe([pivot_valuename, pivot_value, ...])

Create a Pandas dataframe with the data from this free-form dataset.

values()

Iterator over info-dicts for each circuit.
copy()#

Make a copy of this FreeformDataSet.

Return type:

DataSet

items()#

Iterator over (circuit, info_dict) pairs.

Return type:

Iterator

keys()#

Returns the circuits used as keys of this DataSet.

Returns:

A list of Circuit objects which index the data counts within this data set.

Return type:

list

to_dataframe(pivot_valuename=None, pivot_value='Value', drop_columns=False)#

Create a Pandas dataframe with the data from this free-form dataset.

Parameters:

  • pivot_valuename (str, optional) – If not None, the resulting dataframe is pivoted using pivot_valuename as the column whose values name the pivoted table’s column names. If None and pivot_value is not None,`”ValueName”` is used.

  • pivot_value (str, optional) – If not None, the resulting dataframe is pivoted such that values of the pivot_value column are rearranged into new columns whose names are given by the values of the pivot_valuename column. If None and pivot_valuename is not None,`”Value”` is used.

  • drop_columns (bool or list, optional) – A list of column names to drop (prior to performing any pivot). If True appears in this list or is given directly, then all constant-valued columns are dropped as well. No columns are dropped when drop_columns == False.

Return type:

pandas.DataFrame

values()#

Iterator over info-dicts for each circuit.

Return type:

Iterator