:py:mod:`pygsti.extras.crosstalk.core`
======================================

.. py:module:: pygsti.extras.crosstalk.core

.. autoapi-nested-parse::

   Core integrated routines for detecting and characterizing crosstalk






Module Contents
---------------


Functions
~~~~~~~~~

.. autoapisummary::

   pygsti.extras.crosstalk.core.tuple_replace_at_index
   pygsti.extras.crosstalk.core.load_pygsti_dataset
   pygsti.extras.crosstalk.core.flatten
   pygsti.extras.crosstalk.core.form_ct_data_matrix
   pygsti.extras.crosstalk.core.do_basic_crosstalk_detection
   pygsti.extras.crosstalk.core.crosstalk_detection_experiment2



.. py:function:: tuple_replace_at_index(tup, ix, val)


.. py:function:: load_pygsti_dataset(filename)

   Loads a pygsti dataset from file.

   This is a wrapper that just checks the first line, and replaces it with the newer outcome specification
   format if its the old type.


.. py:function:: flatten(l)

   Flattens an irregualr list.
   From https://stackoverflow.com/questions/2158395/flatten-an-irregular-list-of-lists


.. py:function:: form_ct_data_matrix(ds, number_of_regions, settings, filter_lengths=None)


.. py:function:: do_basic_crosstalk_detection(ds, number_of_regions, settings, confidence=0.95, verbosity=1, name=None, assume_independent_settings=True, filter_lengths=None)

   Implements crosstalk detection on multiqubit data (fine-grained data with entries for each experiment).

   Parameters
   ----------
   ds : pyGSTi DataSet or numpy array
       The multiqubit data to analyze. If this is a numpy array, it must contain time series data and it must
       be 2-dimensional with each entry being a sequence of settings and measurment outcomes for each qubit region.
       A region is a set of one or more qubits and crosstalk is assessed between regions. The first n entries are
       the outcomes and the following entries are settings.

   number_of_regions: int, number of regions in experiment

   settings: list of length number_of_regions, indicating the number of settings for each qubit region.

   confidence : float, optional

   verbosity : int, optional

   name : str, optional

   filter_lengths : list of lengths. If this is not empty the dataset will be filtered and the analysis will only be
       done on the sequences of lengths specified in this list. This argument is only used if the dataset is passed in
       as a pyGSTi DataSet

   Returns
   -------
   results : CrosstalkResults object
       The results of the crosstalk detection analysis. This contains: output skeleton graph and DAG from
       PC Algorithm indicating regions with detected crosstalk, all of the input information.



.. py:function:: crosstalk_detection_experiment2(pspec, lengths, circuits_per_length, circuit_population_sz, multiplier=3, idle_prob=0.1, structure='1Q', descriptor='A set of crosstalk detections experiments', verbosity=1)