Remove deprecated code for 0.7 (qiskit-community#1452)

Removes code scheduled for removal in 0.7. For analysis results,
`dataframe` is still set to `False` by default as `True` is a breaking
change.

docs/conf.py

@@ -213,7 +213,6 @@ def setup(app):
 # Should come up with better way to address this
 
 from qiskit_experiments.curve_analysis import ParameterRepr
-from qiskit_experiments.curve_analysis import SeriesDef
 
 
 def maybe_skip_member(app, what, name, obj, skip, options):
@@ -227,9 +226,6 @@ def maybe_skip_member(app, what, name, obj, skip, options):
         "y",
         "y_err",
         "name",
-        "filter_kwargs",
-        "fit_func",
-        "signature",
         "artifact_id",
         "artifact_data",
         "device_components",
@@ -239,10 +235,6 @@ def maybe_skip_member(app, what, name, obj, skip, options):
     skip_members = [
         ParameterRepr.repr,
         ParameterRepr.unit,
-        SeriesDef.plot_color,
-        SeriesDef.plot_symbol,
-        SeriesDef.model_description,
-        SeriesDef.canvas,
     ]
     if not skip:
         return (name in skip_names or obj in skip_members) and what == "attribute"

docs/howtos/artifacts.rst

@@ -36,7 +36,7 @@ artifacts as a list of :class:`.ArtifactData` objects accessed by :meth:`.Experi
     backend = AerSimulator.from_backend(FakePerth())
     exp1 = T1(physical_qubits=[0], delays=np.arange(1e-6, 6e-4, 5e-5))
     exp2 = T1(physical_qubits=[1], delays=np.arange(1e-6, 6e-4, 5e-5))
-    data = ParallelExperiment([exp1, exp2], flatten_results=True).run(backend).block_for_results()
+    data = ParallelExperiment([exp1, exp2]).run(backend).block_for_results()
     data.artifacts()
 
 Artifacts can be accessed using either the artifact ID, which has to be unique in each

docs/manuals/verification/quantum_volume.rst

@@ -158,7 +158,7 @@ Extracting the maximum Quantum Volume.
 .. jupyter-execute::
 
     qv_values = [
-        batch_expdata.child_data(i).analysis_results("quantum_volume").value
+        batch_expdata.analysis_results("quantum_volume")[i].value
         for i in range(batch_exp.num_experiments)
     ]
 
@@ -169,10 +169,9 @@ Extracting the maximum Quantum Volume.
 
     for i in range(batch_exp.num_experiments):
         print(f"\nComponent experiment {i}")
-        sub_data = batch_expdata.child_data(i)
-        display(sub_data.figure(0))
-        for result in sub_data.analysis_results():
-            print(result)
+        display(batch_expdata.figure(i))
+    for result in batch_expdata.analysis_results():
+        print(result)
 
 References
 ----------

docs/manuals/verification/randomized_benchmarking.rst

@@ -182,8 +182,7 @@ The EPGs of two-qubit RB are analyzed with the corrected EPC if available.
         [
             StandardRB((qubit,), lengths_1_qubit, num_samples=num_samples, seed=seed)
             for qubit in qubits
-        ],
-        flatten_results=True,
+        ]
     )
     expdata_1q = single_exps.run(backend).block_for_results()
 

docs/tutorials/curve_analysis.rst

@@ -343,7 +343,7 @@ For example, :class:`.StarkRamseyXYAmpScanAnalysis` defines four `series`
 labels in its ``data_subfit_map`` option (``Xpos``, ``Ypos``, ``Xneg``,
 ``Yneg``) but only two models (``FREQpos``, ``FREQneg``) whose names do not
 match the series labels.
-It does this by overriding the ``CurveData._format_data()`` method and adding
+It does this by overriding the ``CurveAnalysis._format_data()`` method and adding
 its own series to the :class:`.ScatterTable` with series labels to match its
 fit model names (by combining ``Xpos``  and ``Ypos`` series data into a
 ``FREQpos`` series and similary for the series with names ending with ``neg``).
@@ -400,11 +400,6 @@ See the :doc:`Artifacts how-to </howtos/artifacts>` for more information.
 Curve Analysis workflow
 -----------------------
 
-.. warning::
-
-    :class:`CurveData` dataclass is replaced with :class:`.ScatterTable` dataframe.
-    This class will be deprecated and removed in the future release.
-
 Typically curve analysis performs fitting as follows.
 This workflow is defined in the method :meth:`CurveAnalysis._run_analysis`.
 
@@ -534,9 +529,9 @@ one can get the list of parameters with the :attr:`CurveAnalysis.parameters`. Ea
 boundary value can be a tuple of floats representing minimum and maximum values.
 
 Apart from user provided guesses, the analysis can systematically generate those values
-with the method :meth:`_generate_fit_guesses`, which is called with the :class:`CurveData`
-dataclass. If the analysis contains multiple model definitions, we can get the subset
-of curve data with :meth:`.CurveData.get_subset_of` using the name of the series. A
+with the method :meth:`_generate_fit_guesses`, which is called with the :class:`.ScatterTable`
+class. If the analysis contains multiple model definitions, we can get the subset
+of curve data with :meth:`.ScatterTable.get_subset_of` using the name of the series. A
 developer can implement the algorithm to generate initial guesses and boundaries by
 using this curve data object, which will be provided to the fitter. Note that there are
 several common initial guess estimators available in :mod:`curve_analysis.guess`.

docs/tutorials/getting_started.rst

@@ -384,7 +384,7 @@ simultaneously on the same device:
 
     child_exp1 = T1(physical_qubits=(2,), delays=delays)
     child_exp2 = StandardRB(physical_qubits=(3,1), lengths=np.arange(1,100,10), num_samples=2)
-    parallel_exp = ParallelExperiment([child_exp1, child_exp2], flatten_results=False)
+    parallel_exp = ParallelExperiment([child_exp1, child_exp2])
 
 Note that when the transpile and run options are set for a composite experiment, the
 child experiments's options are also set to the same options recursively. Let's examine
@@ -437,35 +437,19 @@ arbitrarily to make complex composite experiments.
 Viewing child experiment data
 -----------------------------
 
-The experiment data returned from a composite experiment contains individual analysis
-results for each child experiment that can be accessed using
-:meth:`~.ExperimentData.child_data`. By default, the parent data object does not contain
-analysis results.
+The experiment data returned from a composite experiment contains analysis
+results for each child experiment in the parent experiment.
 
 .. note::
 
-    This behavior will be updated in Qiskit Experiments 0.7.
     By default, all analysis results will be stored in the parent data object,
-    and you need to explicitly set ``flatten_results=False`` to generate child data objects.
-
-.. jupyter-execute::
-
-    parallel_data = parallel_exp.run(backend, seed_simulator=101).block_for_results()
-
-    for i, sub_data in enumerate(parallel_data.child_data()):
-        print("Component experiment",i)
-        display(sub_data.figure(0))
-        for result in sub_data.analysis_results():
-            print(result)
-
-If you want the parent data object to contain the analysis results instead, you can set
-the ``flatten_results`` flag to true to flatten the results of all component experiments
-into one level:
+    and you need to explicitly set ``flatten_results=False`` to generate child
+    data objects in the legacy format.
 
 .. jupyter-execute::
 
     parallel_exp = ParallelExperiment(
-        [T1(physical_qubits=(i,), delays=delays) for i in range(2)], flatten_results=True
+        [T1(physical_qubits=(i,), delays=delays) for i in range(2)]
     )
     parallel_data = parallel_exp.run(backend, seed_simulator=101).block_for_results()
 

qiskit_experiments/curve_analysis/__init__.py

@@ -40,21 +40,10 @@
     :toctree: ../stubs/
 
     ScatterTable
-    SeriesDef
-    CurveData
     CurveFitResult
     ParameterRepr
     FitOptions
 
-Visualization
-=============
-
-.. autosummary::
-    :toctree: ../stubs/
-
-    BaseCurveDrawer
-    MplCurveDrawer
-
 Standard Analysis Library
 =========================
 
@@ -120,18 +109,14 @@
 from .composite_curve_analysis import CompositeCurveAnalysis
 from .scatter_table import ScatterTable
 from .curve_data import (
-    CurveData,
     CurveFitResult,
-    FitData,
     FitOptions,
     ParameterRepr,
-    SeriesDef,
 )
 from .curve_fit import (
     process_curve_data,
     process_multi_curve_data,
 )
-from .visualization import BaseCurveDrawer, MplCurveDrawer
 from . import guess
 from . import fit_function
 from . import utils
@@ -146,6 +131,3 @@
     ErrorAmplificationAnalysis,
     BlochTrajectoryAnalysis,
 )
-
-# deprecated
-from .visualization import plot_curve_fit, plot_errorbar, plot_scatter, FitResultPlotters

qiskit_experiments/curve_analysis/base_curve_analysis.py

@@ -14,14 +14,11 @@
 Base class of curve analysis.
 """
 
-import warnings
 from abc import ABC, abstractmethod
 from typing import Dict, List, Union
 
 import lmfit
 
-from qiskit.utils.deprecation import deprecate_func
-
 from qiskit_experiments.data_processing import DataProcessor
 from qiskit_experiments.data_processing.processor_library import get_processor
 from qiskit_experiments.framework import (
@@ -31,10 +28,8 @@
     Options,
 )
 from qiskit_experiments.visualization import (
-    BaseDrawer,
     BasePlotter,
     CurvePlotter,
-    LegacyCurveCompatDrawer,
     MplDrawer,
 )
 
@@ -130,20 +125,6 @@ def plotter(self) -> BasePlotter:
         """A short-cut to the curve plotter instance."""
         return self._options.plotter
 
-    @property
-    @deprecate_func(
-        since="0.5",
-        additional_msg="Use `plotter` from the new visualization module.",
-        removal_timeline="after 0.6",
-        package_name="qiskit-experiments",
-    )
-    def drawer(self) -> BaseDrawer:
-        """A short-cut for curve drawer instance, if set. ``None`` otherwise."""
-        if isinstance(self.plotter.drawer, LegacyCurveCompatDrawer):
-            return self.plotter.drawer._curve_drawer
-        else:
-            return None
-
     @classmethod
     def _default_options(cls) -> Options:
         """Return default analysis options.
@@ -159,8 +140,6 @@ def _default_options(cls) -> Options:
                 not create a figure. This overrides the behavior of ``generate_figures``.
             return_fit_parameters (bool): (Deprecated) Set ``True`` to return all fit model parameters
                 with details of the fit outcome. Default to ``False``.
-            return_data_points (bool): (Deprecated) Set ``True`` to include in the analysis result
-                the formatted data points given to the fitter. Default to ``False``.
             data_processor (Callable): A callback function to format experiment data.
                 This can be a :class:`.DataProcessor`
                 instance that defines the `self.__call__` method.
@@ -211,7 +190,6 @@ def _default_options(cls) -> Options:
         options.plot_raw_data = False
         options.plot_residuals = False
         options.return_fit_parameters = True
-        options.return_data_points = False
         options.data_processor = None
         options.normalization = False
         options.average_method = "shots_weighted"
@@ -405,20 +383,3 @@ def _initialize(
         if not data_processor.is_trained:
             data_processor.train(data=experiment_data.data())
         self.set_options(data_processor=data_processor)
-
-        # Check if a model contains legacy data mapping option.
-        data_subfit_map = {}
-        for model in self.models:
-            if "data_sort_key" in model.opts:
-                data_subfit_map[model._name] = model.opts["data_sort_key"]
-                del model.opts["data_sort_key"]
-        if data_subfit_map:
-            warnings.warn(
-                "Setting 'data_sort_key' to an LMFIT model constructor is no longer "
-                "valid configuration of the model. "
-                "Use 'data_subfit_map' option in the analysis options. "
-                "This warning will be dropped in v0.6 along with the support for the "
-                "'data_sort_key' in the LMFIT model options.",
-                DeprecationWarning,
-            )
-            self.set_options(data_subfit_map=data_subfit_map)

qiskit_experiments/curve_analysis/composite_curve_analysis.py

@@ -22,19 +22,15 @@
 import numpy as np
 import pandas as pd
 
-from qiskit.utils.deprecation import deprecate_func
-
 from qiskit_experiments.framework import (
     AnalysisResultData,
     BaseAnalysis,
     ExperimentData,
     Options,
 )
 from qiskit_experiments.visualization import (
-    BaseDrawer,
     BasePlotter,
     CurvePlotter,
-    LegacyCurveCompatDrawer,
     MplDrawer,
 )
 
@@ -76,7 +72,6 @@ class CompositeCurveAnalysis(BaseAnalysis):
             for qi in (0, 1):
                 analysis = curve.OscillationAnalysis(name=f"init{qi}")
                 analysis.set_options(
-                    return_fit_parameters=["freq"],
                     filter_data={"init_state": qi},
                 )
             analysis = CompositeCurveAnalysis(analyses=analyses)
@@ -147,20 +142,6 @@ def plotter(self) -> BasePlotter:
         """A short-cut to the plotter instance."""
         return self._options.plotter
 
-    @property
-    @deprecate_func(
-        since="0.5",
-        additional_msg="Use `plotter` from the new visualization module instead.",
-        removal_timeline="after 0.6",
-        package_name="qiskit-experiments",
-    )
-    def drawer(self) -> BaseDrawer:
-        """A short-cut for curve drawer instance, if set. ``None`` otherwise."""
-        if hasattr(self._options, "curve_drawer"):
-            return self._options.curve_drawer
-        else:
-            return None
-
     def analyses(
         self, index: Optional[Union[str, int]] = None
     ) -> Union[BaseCurveAnalysis, List[BaseCurveAnalysis]]:
@@ -273,8 +254,6 @@ def _default_options(cls) -> Options:
                 This is ``True`` by default.
             return_fit_parameters (bool): (Deprecated) Set ``True`` to return all fit model parameters
                 with details of the fit outcome. Default to ``False``.
-            return_data_points (bool): (Deprecated) Set ``True`` to include in the analysis result
-                the formatted data points given to the fitter. Default to ``False``.
             extra (Dict[str, Any]): A dictionary that is appended to all database entries
                 as extra information.
         """
@@ -283,7 +262,6 @@ def _default_options(cls) -> Options:
             plotter=CurvePlotter(MplDrawer()),
             plot=True,
             return_fit_parameters=False,
-            return_data_points=False,
             extra={},
         )
 
@@ -293,27 +271,6 @@ def _default_options(cls) -> Options:
         return options
 
     def set_options(self, **fields):
-        # TODO remove this in Qiskit Experiments 0.6
-        if "curve_drawer" in fields:
-            warnings.warn(
-                "The option 'curve_drawer' is replaced with 'plotter'. "
-                "This option will be removed in Qiskit Experiments 0.6.",
-                DeprecationWarning,
-                stacklevel=2,
-            )
-            # Set the plotter drawer to `curve_drawer`. If `curve_drawer` is the right type, set it
-            # directly. If not, wrap it in a compatibility drawer.
-            if isinstance(fields["curve_drawer"], BaseDrawer):
-                plotter = self.options.plotter
-                plotter.drawer = fields.pop("curve_drawer")
-                fields["plotter"] = plotter
-            else:
-                drawer = fields["curve_drawer"]
-                compat_drawer = LegacyCurveCompatDrawer(drawer)
-                plotter = self.options.plotter
-                plotter.drawer = compat_drawer
-                fields["plotter"] = plotter
-
         for field in fields:
             if not hasattr(self.options, field):
                 warnings.warn(
@@ -349,10 +306,7 @@ def _run_analysis(
             metadata = analysis.options.extra
             metadata["group"] = analysis.name
             analysis.set_options(
-                plot=False,
-                extra=metadata,
-                return_fit_parameters=self.options.return_fit_parameters,
-                return_data_points=self.options.return_data_points,
+                plot=False, extra=metadata, return_fit_parameters=self.options.return_fit_parameters
             )
             results, _ = analysis._run_analysis(experiment_data)
             for res in results: