Update docstrings

Co-authored-by: Daniel J. Egger <[email protected]>
Co-authored-by: Naoki Kanazawa <[email protected]>

Author: 3 people

qiskit_experiments/curve_analysis/__init__.py

@@ -318,8 +318,8 @@ 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 plotter to the option ``plotter``.
-The plotter defaults to the :class:`CurvePlotter`.
+Users can set a custom plotter in :class:`CurveAnalysis` classes, to customize
+figures, by setting the :attr:`~CurveAnalysis.plotter` attribute.
 Finally, it returns the list of created analysis results and Matplotlib figure.
 
 

qiskit_experiments/curve_analysis/composite_curve_analysis.py

@@ -352,14 +352,14 @@ def _run_analysis(
                             params=fit_data.ufloat_params,
                         )
                         y_mean = unp.nominal_values(y_data_with_uncertainty)
-                        # Draw fit line
+                        # Add fit line data
                         self.plotter.set_series_data(
                             model._name + f"_{analysis.name}",
                             x_interp=interp_x,
                             y_mean=y_mean,
                         )
                         if fit_data.covar is not None:
-                            # Draw confidence intervals with different n_sigma
+                            # Add confidence interval data
                             sigmas = unp.std_devs(y_data_with_uncertainty)
                             if np.isfinite(sigmas).all():
                                 self.plotter.set_series_data(model._name, sigmas=sigmas)

qiskit_experiments/curve_analysis/curve_analysis.py

@@ -558,14 +558,14 @@ def _run_analysis(
                         params=fit_data.ufloat_params,
                     )
                     y_mean = unp.nominal_values(y_data_with_uncertainty)
-                    # Draw fit line
+                    # Add fit line data
                     self.plotter.set_series_data(
                         model._name,
                         x_interp=interp_x,
                         y_mean=y_mean,
                     )
                     if fit_data.covar is not None:
-                        # Draw confidence intervals with different n_sigma
+                        # Add confidence interval data
                         sigmas = unp.std_devs(y_data_with_uncertainty)
                         if np.isfinite(sigmas).all():
                             self.plotter.set_series_data(

qiskit_experiments/visualization/__init__.py

@@ -54,7 +54,6 @@
 
     BaseDrawer
     MplDrawer
-    LegacyCurveCompatDrawer
 
 Plotting Style
 ==============

qiskit_experiments/visualization/drawers/base_drawer.py

@@ -52,8 +52,7 @@ class BaseDrawer(ABC):
 
     draw_line
 
-        This method plots a line from provided X and Y values. This method is typically called with
-        interpolated x and y values from a curve-fit.
+        This method plots a line from provided X and Y values.
 
     draw_filled_y_area
 
@@ -70,18 +69,16 @@ class BaseDrawer(ABC):
     draw_text_box
 
         This method draws a text-box on the canvas, which is a rectangular region containing some text.
-        This method is typically called with a list of analysis results and reduced chi-squared values
-        from a curve-fit.
 
     Options and Figure Options
     ==========================
 
     Drawers have both :attr:`options` and :attr:`figure_options` available to set parameters that define
-    how to drawer and what is drawn. :class:`BasePlotter` is similar in that it also has ``options`` and
-    ``figure_options`. The former contains class-specific variables that define how an instance behaves.
-    The latter contains figure-specific variables that typically contain values that are drawn on the
-    canvas, such as text. For details on the difference between the two sets of options, see the
-    documentation for :class:`BasePlotter`.
+    how to draw and what is drawn, respectively. :class:`BasePlotter` is similar in that it also has
+    ``options`` and ``figure_options`. The former contains class-specific variables that define how an
+    instance behaves. The latter contains figure-specific variables that typically contain values that
+    are drawn on the canvas, such as text. For details on the difference between the two sets of options,
+    see the documentation for :class:`BasePlotter`.
 
     .. note::
         If a drawer instance is used with a plotter, then there is the potential for any figure-option
@@ -337,11 +334,11 @@ def draw_line(
         legend: bool = False,
         **options,
     ):
-        """Draw fit line.
+        """Draw a line.
 
         Args:
             x_data: X values.
-            y_data: Fit Y values.
+            y_data: Y values.
             name: Name of this series.
             label: Optional legend label to override ``name`` and ``series_params``.
             legend: Whether the drawn area must have a legend entry. Defaults to False.

qiskit_experiments/visualization/plotters/base_plotter.py

@@ -115,7 +115,7 @@ def __init__(self, drawer: BaseDrawer):
         """
         # Data to be plotted, such as scatter points, interpolated fits, and confidence intervals
         self._series_data: Dict[str, Dict[str, Any]] = {}
-        # Data for figure-wide drawing, unrelated to series data, such as text or fit reports.
+        # Data that isn't directly associated with a single series, such as text or fit reports.
         self._figure_data: Dict[str, Any] = {}
 
         # Options for the plotter