docs and option name

Author: nkanazawa1989

docs/tutorials/experiment_cloud_service.rst

@@ -19,9 +19,9 @@ experiment database.
 
     from qiskit_experiments.library.characterization import T1
     import numpy as np
-
+    
     t1_delays = np.arange(1e-6, 600e-6, 50e-6)
-
+    
     # Create an experiment for qubit 0,
     # setting the unit to microseconds,
     # with the specified time intervals
@@ -158,7 +158,7 @@ on by default at the experiment service level.
 .. jupyter-execute::
 
     exp = T1(qubit=0, delays=t1_delays)
-
+    
     t1_expdata = exp.run(backend=backend, shots=1000)
     t1_expdata.auto_save = True
     t1_expdata.block_for_results()
@@ -189,7 +189,7 @@ Tags and notes can be added to experiments to help identify specific experiments
 For example, an experiment can be tagged and made public with the following code.
 
 .. jupyter-execute::
-
+   
    t1_expdata.tags = ['tag1', 'tag2']
    t1_expdata.share_level = "public"
    t1_expdata.notes = "Example note."
@@ -201,7 +201,7 @@ These fields can also be updated in the web interface from the menu on the right
 
 .. |web_tags_share.png| image:: ./experiment_cloud_service/web_tags_share.png
 
-For more information about using the cloud database interface, please take a look at its `documentation <https://quantum-computing.ibm.com/lab/docs/iql/manage/experiments/>`__.
+For more information about using the cloud database interface, please take a look at its `documentation <https://quantum-computing.ibm.com/lab/docs/iql/manage/experiments/>`__. 
 
 Randomized Benchmarking experiment
 ----------------------------------
@@ -211,11 +211,11 @@ Let’s now do a standard RB experiment and save the results to ResultsDB.
 .. jupyter-execute::
 
     from qiskit_experiments.library import randomized_benchmarking as rb
-
+    
     lengths = list(range(1, 1000, 200))
     num_samples = 10
     seed = 1010
-
+    
     rb_exp = rb.StandardRB([0], lengths, num_samples=num_samples, seed=seed)
     rb_expdata = rb_exp.run(backend).block_for_results()
     rb_expdata.save()
@@ -242,15 +242,15 @@ Let’s do state tomography on a Hadamard state.
 
     from qiskit_experiments.library import StateTomography
     import qiskit
-
+    
     # Construct state by applying H gate
     qc_h = qiskit.QuantumCircuit(1)
     qc_h.h(0)
-
+    
     qstexp = StateTomography(qc_h)
     qst_expdata = qstexp.run(backend).block_for_results()
     qst_expdata.save()
-
+    
     for result in qst_expdata.analysis_results():
         print(result)
 
@@ -262,7 +262,7 @@ graphical interface, but the other analysis parameters are:
 .. image:: ./experiment_cloud_service/tomo_experiment.png
 
 |
-
+	   
 .. jupyter-execute::
 
     import qiskit.tools.jupyter

qiskit_experiments/curve_analysis/__init__.py

@@ -312,7 +312,7 @@ class AnalysisB(CurveAnalysis):
 compute custom quantities based on the raw fit parameters.
 See :ref:`curve_analysis_results` for details.
 Afterwards, the analysis draws several curves in the Matplotlib figure.
-User can set custom drawer to the option ``curve_plotter``.
+User can set custom drawer to the option ``curve_drawer``.
 The drawer defaults to the :class:`MplCurveDrawer`.
 Finally, it returns the list of created analysis results and Matplotlib figure.
 

qiskit_experiments/curve_analysis/base_curve_analysis.py

@@ -111,14 +111,14 @@ def parameters(self) -> List[str]:
     @property
     def drawer(self) -> BaseCurveDrawer:
         """A short-cut for curve drawer instance."""
-        return self._options.curve_plotter
+        return self._options.curve_drawer
 
     @classmethod
     def _default_options(cls) -> Options:
         """Return default analysis options.
 
         Analysis Options:
-            curve_plotter (BaseCurveDrawer): A curve drawer instance to visualize
+            curve_drawer (BaseCurveDrawer): A curve drawer instance to visualize
                 the analysis result.
             plot_raw_data (bool): Set ``True`` to draw processed data points,
                 dataset without formatting, on canvas. This is ``False`` by default.
@@ -156,7 +156,7 @@ def _default_options(cls) -> Options:
         """
         options = super()._default_options()
 
-        options.curve_plotter = MplCurveDrawer()
+        options.curve_drawer = MplCurveDrawer()
         options.plot_raw_data = False
         options.plot = True
         options.return_fit_parameters = True
@@ -173,7 +173,7 @@ def _default_options(cls) -> Options:
 
         # Set automatic validator for particular option values
         options.set_validator(field="data_processor", validator_value=DataProcessor)
-        options.set_validator(field="curve_plotter", validator_value=BaseCurveDrawer)
+        options.set_validator(field="curve_drawer", validator_value=BaseCurveDrawer)
 
         return options
 
@@ -187,23 +187,25 @@ def set_options(self, **fields):
             KeyError: When removed option ``curve_fitter`` is set.
         """
         # TODO remove this in Qiskit Experiments v0.4
-        if "curve_plotter" in fields and isinstance(fields["curve_plotter"], str):
-            plotter_str = fields["curve_plotter"]
+        if "curve_plotter" in fields:
             warnings.warn(
-                f"The curve plotter '{plotter_str}' has been deprecated. "
-                "The option is replaced with 'MplCurveDrawer' instance. "
+                f"The analysis option 'curve_plotter' has been deprecated. "
+                "The option is replaced with 'curve_drawer' that takes 'MplCurveDrawer' instance. "
                 "If this is a loaded analysis, please save this instance again to update option value. "
-                "This warning will be removed with backport in Qiskit Experiments 0.4.",
+                "The 'curve_plotter' argument along with this warning will be removed "
+                "in Qiskit Experiments 0.4.",
                 DeprecationWarning,
                 stacklevel=2,
             )
-            fields["curve_plotter"] = MplCurveDrawer()
+            del fields["curve_plotter"]
 
         if "curve_fitter" in fields:
             warnings.warn(
                 "Setting curve fitter to analysis options has been deprecated and "
                 "the option has been removed. The fitter setting is dropped. "
-                "Now you can directly override '_run_curve_fit' method to apply custom fitter.",
+                "Now you can directly override '_run_curve_fit' method to apply custom fitter. "
+                "The `curve_fitter` argument along with this warning will be removed "
+                "in Qiskit Experiments 0.4.",
                 DeprecationWarning,
                 stacklevel=2,
             )
@@ -217,7 +219,8 @@ def set_options(self, **fields):
                 f"Option(s) {deprecated} have been moved to draw_options and will be removed soon. "
                 "Use self.drawer.set_options instead. "
                 "If this is a loaded analysis, please save this instance again to update option value. "
-                "This warning will be removed with backport in Qiskit Experiments 0.4.",
+                "These arguments along with this warning will be removed "
+                "in Qiskit Experiments 0.4.",
                 DeprecationWarning,
                 stacklevel=2,
             )

qiskit_experiments/curve_analysis/curve_data.py

@@ -27,7 +27,7 @@
 class SeriesDef:
     """A dataclass to describe the definition of the curve.
 
-    Args:
+    Attributes:
         fit_func: A callable that defines the fit model of this curve. The argument names
             in the callable are parsed to create the fit parameter list, which will appear
             in the analysis results. The first argument should be ``x`` that represents
@@ -78,7 +78,7 @@ class CurveData:
     This dataset can consist of X, Y values from multiple series.
     To extract curve data of the particular series, :meth:`get_subset_of` can be used.
 
-    Args:
+    Attributes:
         x: X-values that experiment sweeps.
         y: Y-values that observed and processed by the data processor.
         y_err: Uncertainty of the Y-values which is created by the data processor.
@@ -130,7 +130,7 @@ def get_subset_of(self, index: Union[str, int]) -> "CurveData":
 class FitData:
     """A dataclass to store the outcome of the fitting.
 
-    Args:
+    Attributes:
         popt: List of optimal parameter values with uncertainties if available.
         popt_keys: List of parameter names being fit.
         pcov: Covariance matrix from the least square fitting.
@@ -182,7 +182,7 @@ def fitval(self, key: str) -> uncertainties.UFloat:
 class ParameterRepr:
     """Detailed description of fitting parameter.
 
-    Args:
+    Attributes:
         name: Original name of the fit parameter being defined in the fit model.
         repr: Optional. Human-readable parameter name shown in the analysis result and in the figure.
         unit: Optional. Physical unit of this parameter if applicable.

qiskit_experiments/curve_analysis/standard_analysis/error_amplification_analysis.py

@@ -106,7 +106,7 @@ def _default_options(cls):
                 considered as good. Defaults to :math:`\pi/2`.
         """
         default_options = super()._default_options()
-        default_options.curve_plotter.set_options(
+        default_options.curve_drawer.set_options(
             xlabel="Number of gates (n)",
             ylabel="Population",
             ylim=(0, 1.0),

qiskit_experiments/curve_analysis/standard_analysis/gaussian.py

@@ -71,7 +71,7 @@ class GaussianAnalysis(curve.CurveAnalysis):
     @classmethod
     def _default_options(cls) -> Options:
         options = super()._default_options()
-        options.curve_plotter.set_options(
+        options.curve_drawer.set_options(
             xlabel="Frequency",
             ylabel="Signal (arb. units)",
             xval_unit="Hz",

qiskit_experiments/curve_analysis/standard_analysis/resonance.py

@@ -71,7 +71,7 @@ class ResonanceAnalysis(curve.CurveAnalysis):
     @classmethod
     def _default_options(cls) -> Options:
         options = super()._default_options()
-        options.curve_plotter.set_options(
+        options.curve_drawer.set_options(
             xlabel="Frequency",
             ylabel="Signal (arb. units)",
             xval_unit="Hz",

qiskit_experiments/library/characterization/analysis/cr_hamiltonian_analysis.py

@@ -196,7 +196,7 @@ class CrossResonanceHamiltonianAnalysis(curve.CurveAnalysis):
     def _default_options(cls):
         """Return the default analysis options."""
         default_options = super()._default_options()
-        default_options.curve_plotter.set_options(
+        default_options.curve_drawer.set_options(
             subplots=(3, 1),
             xlabel="Flat top width",
             ylabel=[

qiskit_experiments/library/characterization/analysis/drag_analysis.py

@@ -120,7 +120,7 @@ def _default_options(cls):
         descriptions of analysis options.
         """
         default_options = super()._default_options()
-        default_options.curve_plotter.set_options(
+        default_options.curve_drawer.set_options(
             xlabel="Beta",
             ylabel="Signal (arb. units)",
         )

qiskit_experiments/library/characterization/analysis/ramsey_xy_analysis.py

@@ -95,7 +95,7 @@ def _default_options(cls):
         descriptions of analysis options.
         """
         default_options = super()._default_options()
-        default_options.curve_plotter.set_options(
+        default_options.curve_drawer.set_options(
             xlabel="Delay",
             ylabel="Signal (arb. units)",
             xval_unit="s",