Add readout plotting tools

cirq-core/cirq/experiments/single_qubit_readout_calibration.py

@@ -18,6 +18,10 @@
 
 import sympy
 import numpy as np
+import matplotlib.pyplot as plt
+import cirq.vis.heatmap as cirq_heatmap
+import cirq.vis.histogram as cirq_histogram
+from cirq.devices import grid_qubit
 from cirq import circuits, ops, study
 
 if TYPE_CHECKING:
@@ -51,6 +55,111 @@ def _json_dict_(self) -> Dict[str, Any]:
             'timestamp': self.timestamp,
         }
 
+    def plot_heatmap(
+        self,
+        axs: Optional[tuple[plt.Axes, plt.Axes]] = None,
+        annotation_format: str = '0.1%',
+        **plot_kwargs: Any,
+    ) -> tuple[plt.Axes, plt.Axes]:
+        """Plot a heatmap of the readout errors. If qubits are not cirq.GridQubits, throws an error.
+
+        Args:
+            axs: a tuple of the plt.Axes to plot on. If not given, a new figure is created,
+                plotted on, and shown.
+            annotation_format: The format string for the numbers in the heatmap.
+            **plot_kwargs: Arguments to be passed to 'cirq.Heatmap.plot()'.
+        Returns:
+            The two plt.Axes containing the plot.
+        """
+
+        if axs is None:
+            _, axs = plt.subplots(1, 2, dpi=200, facecolor='white', figsize=(12, 4))
+
+        for ax, title, data in zip(
+            axs,
+            ['$|0\\rangle$ errors', '$|1\\rangle$ errors'],
+            [self.zero_state_errors, self.one_state_errors],
+        ):
+            data_with_grid_qubit_keys = {}
+            for qubit in data:
+                assert type(qubit) == grid_qubit.GridQubit, "qubits must be cirq.GridQubits"
+                data_with_grid_qubit_keys[qubit] = data[qubit]  # just for typecheck
+            _, _ = cirq_heatmap.Heatmap(data_with_grid_qubit_keys).plot(
+                ax, annotation_format=annotation_format, title=title, **plot_kwargs
+            )
+        return axs[0], axs[1]
+
+    def plot_integrated_histogram(
+        self,
+        ax: Optional[plt.Axes] = None,
+        cdf_on_x: bool = False,
+        axis_label: str = 'Readout error rate',
+        semilog: bool = True,
+        median_line: bool = True,
+        median_label: Optional[str] = 'median',
+        mean_line: bool = False,
+        mean_label: Optional[str] = 'mean',
+        show_zero: bool = False,
+        title: Optional[str] = None,
+        **kwargs,
+    ) -> plt.Axes:
+        """Plot the readout errors using cirq.integrated_histogram().
+
+        Args:
+            ax: The axis to plot on. If None, we generate one.
+            cdf_on_x: If True, flip the axes compared the above example.
+            axis_label: Label for x axis (y-axis if cdf_on_x is True).
+            semilog: If True, force the x-axis to be logarithmic.
+            median_line: If True, draw a vertical line on the median value.
+            median_label: If drawing median line, optional label for it.
+            mean_line: If True, draw a vertical line on the mean value.
+            mean_label: If drawing mean line, optional label for it.
+            title: Title of the plot. If None, we assign "N={len(data)}".
+            show_zero: If True, moves the step plot up by one unit by prepending 0
+                to the data.
+            **kwargs: Kwargs to forward to `ax.step()`. Some examples are
+                color: Color of the line.
+                linestyle: Linestyle to use for the plot.
+                lw: linewidth for integrated histogram.
+                ms: marker size for a histogram trace.
+        Returns:
+            The axis that was plotted on.
+        """
+
+        ax = cirq_histogram.integrated_histogram(
+            data=self.zero_state_errors,
+            ax=ax,
+            cdf_on_x=cdf_on_x,
+            semilog=semilog,
+            median_line=median_line,
+            median_label=median_label,
+            mean_line=mean_line,
+            mean_label=mean_label,
+            show_zero=show_zero,
+            color='C0',
+            label='$|0\\rangle$ errors',
+            **kwargs,
+        )
+        ax = cirq_histogram.integrated_histogram(
+            data=self.one_state_errors,
+            ax=ax,
+            cdf_on_x=cdf_on_x,
+            axis_label=axis_label,
+            semilog=semilog,
+            median_line=median_line,
+            median_label=median_label,
+            mean_line=mean_line,
+            mean_label=mean_label,
+            show_zero=show_zero,
+            title=title,
+            color='C1',
+            label='$|1\\rangle$ errors',
+            **kwargs,
+        )
+        ax.legend(loc='best')
+        ax.set_ylabel('Percentile')
+        return ax
+
     @classmethod
     def _from_json_dict_(
         cls, zero_state_errors, one_state_errors, repetitions, timestamp, **kwargs

cirq-core/cirq/experiments/single_qubit_readout_calibration_test.py

@@ -87,7 +87,7 @@ def test_estimate_single_qubit_readout_errors_with_noise():
 
 
 def test_estimate_parallel_readout_errors_no_noise():
-    qubits = cirq.LineQubit.range(10)
+    qubits = [cirq.GridQubit(i, 0) for i in range(10)]
     sampler = cirq.Simulator()
     repetitions = 1000
     result = cirq.estimate_parallel_single_qubit_readout_errors(
@@ -97,6 +97,8 @@ def test_estimate_parallel_readout_errors_no_noise():
     assert result.one_state_errors == {q: 0 for q in qubits}
     assert result.repetitions == repetitions
     assert isinstance(result.timestamp, float)
+    _ = result.plot_integrated_histogram()
+    _, _ = result.plot_heatmap()
 
 
 def test_estimate_parallel_readout_errors_all_zeros():