Add new plotting module for experiment and analysis figures

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 drawer to the option ``curve_drawer``.
-The drawer defaults to the :class:`MplCurveDrawer`.
+User can set custom plotter to the option ``plotter``.
+The plotter defaults to the :class:`CurvePlotter`.
 Finally, it returns the list of created analysis results and Matplotlib figure.
 
 
@@ -481,15 +481,6 @@ def _create_analysis_results(self, fit_data, quality, **metadata):
     ParameterRepr
     FitOptions
 
-Visualization
-=============
-
-.. autosummary::
-    :toctree: ../stubs/
-
-    BaseCurveDrawer
-    MplCurveDrawer
-
 Standard Analysis Library
 =========================
 
@@ -565,7 +556,6 @@ def _create_analysis_results(self, fit_data, quality, **metadata):
     process_curve_data,
     process_multi_curve_data,
 )
-from .visualization import BaseCurveDrawer, MplCurveDrawer
 from . import guess
 from . import fit_function
 from . import utils
@@ -580,6 +570,3 @@ def _create_analysis_results(self, fit_data, quality, **metadata):
     ErrorAmplificationAnalysis,
     BlochTrajectoryAnalysis,
 )
-
-# deprecated
-from .visualization import plot_curve_fit, plot_errorbar, plot_scatter, FitResultPlotters

qiskit_experiments/curve_analysis/base_curve_analysis.py

@@ -23,8 +23,8 @@
 from qiskit_experiments.data_processing import DataProcessor
 from qiskit_experiments.data_processing.processor_library import get_processor
 from qiskit_experiments.framework import BaseAnalysis, AnalysisResultData, Options, ExperimentData
+from qiskit_experiments.visualization import MplDrawer, BasePlotter, CurvePlotter
 from .curve_data import CurveData, ParameterRepr, CurveFitResult
-from .visualization import MplCurveDrawer, BaseCurveDrawer
 
 PARAMS_ENTRY_PREFIX = "@Parameters_"
 DATA_ENTRY_PREFIX = "@Data_"
@@ -113,16 +113,16 @@ def models(self) -> List[lmfit.Model]:
         """Return fit models."""
 
     @property
-    def drawer(self) -> BaseCurveDrawer:
-        """A short-cut for curve drawer instance."""
-        return self._options.curve_drawer
+    def plotter(self) -> BasePlotter:
+        """A short-cut for curve plotter instance."""
+        return self._options.plotter
 
     @classmethod
     def _default_options(cls) -> Options:
         """Return default analysis options.
 
         Analysis Options:
-            curve_drawer (BaseCurveDrawer): A curve drawer instance to visualize
+            plotter (BasePlotter): A curve plotter 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.
@@ -168,7 +168,7 @@ def _default_options(cls) -> Options:
         """
         options = super()._default_options()
 
-        options.curve_drawer = MplCurveDrawer()
+        options.plotter = CurvePlotter(MplDrawer())
         options.plot_raw_data = False
         options.plot = True
         options.return_fit_parameters = True
@@ -187,7 +187,7 @@ 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_drawer", validator_value=BaseCurveDrawer)
+        options.set_validator(field="plotter", validator_value=BasePlotter)
 
         return options
 

qiskit_experiments/curve_analysis/composite_curve_analysis.py

@@ -22,10 +22,10 @@
 from uncertainties import unumpy as unp, UFloat
 
 from qiskit_experiments.framework import BaseAnalysis, ExperimentData, AnalysisResultData, Options
+from qiskit_experiments.visualization import MplDrawer, CurvePlotter, BasePlotter
 from .base_curve_analysis import BaseCurveAnalysis, PARAMS_ENTRY_PREFIX
 from .curve_data import CurveFitResult
 from .utils import analysis_result_to_repr, eval_with_uncertainties
-from .visualization import MplCurveDrawer, BaseCurveDrawer
 
 
 class CompositeCurveAnalysis(BaseAnalysis):
@@ -124,9 +124,9 @@ def models(self) -> Dict[str, List[lmfit.Model]]:
         return models
 
     @property
-    def drawer(self) -> BaseCurveDrawer:
-        """A short-cut for curve drawer instance."""
-        return self._options.curve_drawer
+    def plotter(self) -> BasePlotter:
+        """A short-cut for plotter instance."""
+        return self._options.plotter
 
     def analyses(
         self, index: Optional[Union[str, int]] = None
@@ -187,7 +187,7 @@ def _default_options(cls) -> Options:
         """Default analysis options.
 
         Analysis Options:
-            curve_drawer (BaseCurveDrawer): A curve drawer instance to visualize
+            plotter (BasePlotter): A plotter instance to visualize
                 the analysis result.
             plot (bool): Set ``True`` to create figure for fit result.
                 This is ``True`` by default.
@@ -200,15 +200,15 @@ def _default_options(cls) -> Options:
         """
         options = super()._default_options()
         options.update_options(
-            curve_drawer=MplCurveDrawer(),
+            plotter=CurvePlotter(MplDrawer()),
             plot=True,
             return_fit_parameters=True,
             return_data_points=False,
             extra={},
         )
 
         # Set automatic validator for particular option values
-        options.set_validator(field="curve_drawer", validator_value=BaseCurveDrawer)
+        options.set_validator(field="plotter", validator_value=BasePlotter)
 
         return options
 
@@ -232,10 +232,6 @@ def _run_analysis(
 
         analysis_results = []
 
-        # Initialize canvas
-        if self.options.plot:
-            self.drawer.initialize_canvas()
-
         fit_dataset = {}
         for analysis in self._analyses:
             analysis._initialize(experiment_data)
@@ -251,22 +247,22 @@ def _run_analysis(
             if self.options.plot and analysis.options.plot_raw_data:
                 for model in analysis.models:
                     sub_data = processed_data.get_subset_of(model._name)
-                    self.drawer.draw_raw_data(
-                        x_data=sub_data.x,
-                        y_data=sub_data.y,
-                        name=model._name + f"_{analysis.name}",
+                    self.plotter.set_series_data(
+                        model._name + f"_{analysis.name}",
+                        x=sub_data.x,
+                        y=sub_data.y,
                     )
 
             # Format data
             formatted_data = analysis._format_data(processed_data)
             if self.options.plot:
                 for model in analysis.models:
                     sub_data = formatted_data.get_subset_of(model._name)
-                    self.drawer.draw_formatted_data(
-                        x_data=sub_data.x,
-                        y_data=sub_data.y,
-                        y_err_data=sub_data.y_err,
-                        name=model._name + f"_{analysis.name}",
+                    self.plotter.set_series_data(
+                        model._name + f"_{analysis.name}",
+                        x_formatted=sub_data.x,
+                        y_formatted=sub_data.y,
+                        y_formatted_err=sub_data.y_err,
                     )
 
             # Run fitting
@@ -310,23 +306,16 @@ def _run_analysis(
                         )
                         y_mean = unp.nominal_values(y_data_with_uncertainty)
                         # Draw fit line
-                        self.drawer.draw_fit_line(
-                            x_data=interp_x,
-                            y_data=y_mean,
-                            name=model._name + f"_{analysis.name}",
+                        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
                             sigmas = unp.std_devs(y_data_with_uncertainty)
                             if np.isfinite(sigmas).all():
-                                for n_sigma, alpha in self.drawer.options.plot_sigma:
-                                    self.drawer.draw_confidence_interval(
-                                        x_data=interp_x,
-                                        y_ub=y_mean + n_sigma * sigmas,
-                                        y_lb=y_mean - n_sigma * sigmas,
-                                        name=model._name + f"_{analysis.name}",
-                                        alpha=alpha,
-                                    )
+                                self.plotter.set_series_data(model._name, sigmas=sigmas)
 
             # Add raw data points
             if self.options.return_data_points:
@@ -355,10 +344,8 @@ def _run_analysis(
             for group, fit_data in fit_dataset.items():
                 chisqs.append(r"reduced-$\chi^2$ = " + f"{fit_data.reduced_chisq: .4g} ({group})")
             report += "\n".join(chisqs)
-            self.drawer.draw_fit_report(description=report)
+            self.plotter.set_figure_data(report_text=report)
 
-            # Finalize canvas
-            self.drawer.format_canvas()
-            return analysis_results, [self.drawer.figure]
+            return analysis_results, [self.plotter.figure()]
 
         return analysis_results, []

qiskit_experiments/curve_analysis/curve_analysis.py

@@ -140,7 +140,7 @@ def __init__(
             )
             # pylint: disable=no-member
             models = []
-            plot_options = {}
+            series_params = {}
             for series_def in self.__series__:
                 models.append(
                     lmfit.Model(
@@ -149,12 +149,12 @@ def __init__(
                         data_sort_key=series_def.filter_kwargs,
                     )
                 )
-                plot_options[series_def.name] = {
+                series_params[series_def.name] = {
                     "color": series_def.plot_color,
                     "symbol": series_def.plot_symbol,
                     "canvas": series_def.canvas,
                 }
-            self.drawer.set_options(plot_options=plot_options)
+            self.plotter.set_plot_options(series_params=series_params)
 
         self._models = models or []
         self._name = name or self.__class__.__name__
@@ -467,10 +467,6 @@ def _run_analysis(
         self._initialize(experiment_data)
         analysis_results = []
 
-        # Initialize canvas
-        if self.options.plot:
-            self.drawer.initialize_canvas()
-
         # Run data processing
         processed_data = self._run_data_processing(
             raw_data=experiment_data.data(),
@@ -480,10 +476,10 @@ def _run_analysis(
         if self.options.plot and self.options.plot_raw_data:
             for model in self._models:
                 sub_data = processed_data.get_subset_of(model._name)
-                self.drawer.draw_raw_data(
-                    x_data=sub_data.x,
-                    y_data=sub_data.y,
-                    name=model._name,
+                self.plotter.set_series_data(
+                    model._name,
+                    x=sub_data.x,
+                    y=sub_data.y,
                 )
         # for backward compatibility, will be removed in 0.4.
         self.__processed_data_set["raw_data"] = processed_data
@@ -493,11 +489,11 @@ def _run_analysis(
         if self.options.plot:
             for model in self._models:
                 sub_data = formatted_data.get_subset_of(model._name)
-                self.drawer.draw_formatted_data(
-                    x_data=sub_data.x,
-                    y_data=sub_data.y,
-                    y_err_data=sub_data.y_err,
-                    name=model._name,
+                self.plotter.set_series_data(
+                    model._name,
+                    x_formatted=sub_data.x,
+                    y_formatted=sub_data.y,
+                    y_formatted_err=sub_data.y_err,
                 )
         # for backward compatibility, will be removed in 0.4.
         self.__processed_data_set["fit_ready"] = formatted_data
@@ -562,31 +558,27 @@ def _run_analysis(
                     )
                     y_mean = unp.nominal_values(y_data_with_uncertainty)
                     # Draw fit line
-                    self.drawer.draw_fit_line(
-                        x_data=interp_x,
-                        y_data=y_mean,
-                        name=model._name,
+                    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
                         sigmas = unp.std_devs(y_data_with_uncertainty)
                         if np.isfinite(sigmas).all():
-                            for n_sigma, alpha in self.drawer.options.plot_sigma:
-                                self.drawer.draw_confidence_interval(
-                                    x_data=interp_x,
-                                    y_ub=y_mean + n_sigma * sigmas,
-                                    y_lb=y_mean - n_sigma * sigmas,
-                                    name=model._name,
-                                    alpha=alpha,
-                                )
+                            self.plotter.set_series_data(
+                                model._name,
+                                sigmas=sigmas,
+                            )
 
                 # Write fitting report
                 report_description = ""
                 for res in analysis_results:
                     if isinstance(res.value, (float, UFloat)):
                         report_description += f"{analysis_result_to_repr(res)}\n"
                 report_description += r"reduced-$\chi^2$ = " + f"{fit_data.reduced_chisq: .4g}"
-                self.drawer.draw_fit_report(description=report_description)
+                self.plotter.set_figure_data(report_text=report_description)
 
         # Add raw data points
         if self.options.return_data_points:
@@ -596,8 +588,7 @@ def _run_analysis(
 
         # Finalize plot
         if self.options.plot:
-            self.drawer.format_canvas()
-            return analysis_results, [self.drawer.figure]
+            return analysis_results, [self.plotter.figure()]
 
         return analysis_results, []
 

qiskit_experiments/curve_analysis/standard_analysis/bloch_trajectory.py

@@ -138,7 +138,7 @@ def _default_options(cls):
             input_key="counts",
             data_actions=[dp.Probability("1"), dp.BasisExpectationValue()],
         )
-        default_options.curve_drawer.set_options(
+        default_options.plotter.set_plot_options(
             xlabel="Flat top width",
             ylabel="Pauli expectation values",
             xval_unit="s",

qiskit_experiments/curve_analysis/standard_analysis/error_amplification_analysis.py

@@ -105,7 +105,7 @@ def _default_options(cls):
                 considered as good. Defaults to :math:`\pi/2`.
         """
         default_options = super()._default_options()
-        default_options.curve_drawer.set_options(
+        default_options.plotter.set_plot_options(
             xlabel="Number of gates (n)",
             ylabel="Population",
             ylim=(0, 1.0),

qiskit_experiments/curve_analysis/standard_analysis/gaussian.py

@@ -76,7 +76,7 @@ def __init__(
     @classmethod
     def _default_options(cls) -> Options:
         options = super()._default_options()
-        options.curve_drawer.set_options(
+        options.plotter.set_plot_options(
             xlabel="Frequency",
             ylabel="Signal (arb. units)",
             xval_unit="Hz",

qiskit_experiments/curve_analysis/standard_analysis/resonance.py

@@ -76,7 +76,7 @@ def __init__(
     @classmethod
     def _default_options(cls) -> Options:
         options = super()._default_options()
-        options.curve_drawer.set_options(
+        options.plotter.set_plot_options(
             xlabel="Frequency",
             ylabel="Signal (arb. units)",
             xval_unit="Hz",