Fix matplotlib typing (quantumlib#6290)

* Fix matplotlib typing

matplotlib 3.8.0 was released this week and included typing hints.
This fixes the resulting CI breakages.

* Fix issues.

* formatting

* Change to seaborn v0_8

Author: dstrain115

Diff for: cirq/contrib/svg/svg.py

@@ -2,12 +2,14 @@
 from typing import TYPE_CHECKING, List, Tuple, cast, Dict
 
 import matplotlib.textpath
+import matplotlib.font_manager
+
 
 if TYPE_CHECKING:
     import cirq
 
 QBLUE = '#1967d2'
-FONT = "Arial"
+FONT = matplotlib.font_manager.FontProperties(family="Arial")
 EMPTY_MOMENT_COLWIDTH = float(21)  # assumed default column width
 
 

Diff for: cirq/devices/named_topologies.py

@@ -74,7 +74,7 @@ def _node_and_coordinates(
 
 
 def draw_gridlike(
-    graph: nx.Graph, ax: plt.Axes = None, tilted: bool = True, **kwargs
+    graph: nx.Graph, ax: Optional[plt.Axes] = None, tilted: bool = True, **kwargs
 ) -> Dict[Any, Tuple[int, int]]:
     """Draw a grid-like graph using Matplotlib.
 

Diff for: cirq/experiments/qubit_characterizations.py

@@ -15,13 +15,13 @@
 import dataclasses
 import itertools
 
-from typing import Any, Iterator, List, Optional, Sequence, Tuple, TYPE_CHECKING
+from typing import Any, cast, Iterator, List, Optional, Sequence, Tuple, TYPE_CHECKING
 import numpy as np
 
 from matplotlib import pyplot as plt
 
 # this is for older systems with matplotlib <3.2 otherwise 3d projections fail
-from mpl_toolkits import mplot3d  # pylint: disable=unused-import
+from mpl_toolkits import mplot3d
 from cirq import circuits, ops, protocols
 
 if TYPE_CHECKING:
@@ -89,8 +89,9 @@ def plot(self, ax: Optional[plt.Axes] = None, **plot_kwargs: Any) -> plt.Axes:
         """
         show_plot = not ax
         if not ax:
-            fig, ax = plt.subplots(1, 1, figsize=(8, 8))
-        ax.set_ylim([0, 1])
+            fig, ax = plt.subplots(1, 1, figsize=(8, 8))  # pragma: no cover
+            ax = cast(plt.Axes, ax)  # pragma: no cover
+        ax.set_ylim((0.0, 1.0))  # pragma: no cover
         ax.plot(self._num_cfds_seq, self._gnd_state_probs, 'ro-', **plot_kwargs)
         ax.set_xlabel(r"Number of Cliffords")
         ax.set_ylabel('Ground State Probability')
@@ -541,7 +542,7 @@ def _find_inv_matrix(mat: np.ndarray, mat_sequence: np.ndarray) -> int:
 def _matrix_bar_plot(
     mat: np.ndarray,
     z_label: str,
-    ax: plt.Axes,
+    ax: mplot3d.axes3d.Axes3D,
     kets: Optional[Sequence[str]] = None,
     title: Optional[str] = None,
     ylim: Tuple[int, int] = (-1, 1),

Diff for: cirq/linalg/decompositions.py

@@ -20,6 +20,7 @@
 from typing import (
     Any,
     Callable,
+    cast,
     Iterable,
     List,
     Optional,
@@ -33,7 +34,7 @@
 import matplotlib.pyplot as plt
 
 # this is for older systems with matplotlib <3.2 otherwise 3d projections fail
-from mpl_toolkits import mplot3d  # pylint: disable=unused-import
+from mpl_toolkits import mplot3d
 import numpy as np
 
 from cirq import value, protocols
@@ -554,7 +555,7 @@ def scatter_plot_normalized_kak_interaction_coefficients(
     interactions: Iterable[Union[np.ndarray, 'cirq.SupportsUnitary', 'KakDecomposition']],
     *,
     include_frame: bool = True,
-    ax: Optional[plt.Axes] = None,
+    ax: Optional[mplot3d.axes3d.Axes3D] = None,
     **kwargs,
 ):
     r"""Plots the interaction coefficients of many two-qubit operations.
@@ -633,13 +634,13 @@ def scatter_plot_normalized_kak_interaction_coefficients(
     show_plot = not ax
     if not ax:
         fig = plt.figure()
-        ax = fig.add_subplot(1, 1, 1, projection='3d')
+        ax = cast(mplot3d.axes3d.Axes3D, fig.add_subplot(1, 1, 1, projection='3d'))
 
     def coord_transform(
         pts: Union[List[Tuple[int, int, int]], np.ndarray]
-    ) -> Tuple[Iterable[float], Iterable[float], Iterable[float]]:
+    ) -> Tuple[np.ndarray, np.ndarray, np.ndarray]:
         if len(pts) == 0:
-            return [], [], []
+            return np.array([]), np.array([]), np.array([])
         xs, ys, zs = np.transpose(pts)
         return xs, zs, ys
 

Diff for: cirq/vis/heatmap.py

@@ -15,6 +15,7 @@
 from dataclasses import astuple, dataclass
 from typing import (
     Any,
+    cast,
     Dict,
     List,
     Mapping,
@@ -217,7 +218,7 @@ def _plot_colorbar(
         )
         position = self._config['colorbar_position']
         orien = 'vertical' if position in ('left', 'right') else 'horizontal'
-        colorbar = ax.figure.colorbar(
+        colorbar = cast(plt.Figure, ax.figure).colorbar(
             mappable, colorbar_ax, ax, orientation=orien, **self._config.get("colorbar_options", {})
         )
         colorbar_ax.tick_params(axis='y', direction='out')
@@ -230,15 +231,15 @@ def _write_annotations(
         ax: plt.Axes,
     ) -> None:
         """Writes annotations to the center of cells. Internal."""
-        for (center, annotation), facecolor in zip(centers_and_annot, collection.get_facecolors()):
+        for (center, annotation), facecolor in zip(centers_and_annot, collection.get_facecolor()):
             # Calculate the center of the cell, assuming that it is a square
             # centered at (x=col, y=row).
             if not annotation:
                 continue
             x, y = center
-            face_luminance = vis_utils.relative_luminance(facecolor)
+            face_luminance = vis_utils.relative_luminance(facecolor)  # type: ignore
             text_color = 'black' if face_luminance > 0.4 else 'white'
-            text_kwargs = dict(color=text_color, ha="center", va="center")
+            text_kwargs: Dict[str, Any] = dict(color=text_color, ha="center", va="center")
             text_kwargs.update(self._config.get('annotation_text_kwargs', {}))
             ax.text(x, y, annotation, **text_kwargs)
 
@@ -295,6 +296,7 @@ def plot(
         show_plot = not ax
         if not ax:
             fig, ax = plt.subplots(figsize=(8, 8))
+            ax = cast(plt.Axes, ax)
         original_config = copy.deepcopy(self._config)
         self.update_config(**kwargs)
         collection = self._plot_on_axis(ax)
@@ -381,6 +383,7 @@ def plot(
         show_plot = not ax
         if not ax:
             fig, ax = plt.subplots(figsize=(8, 8))
+            ax = cast(plt.Axes, ax)
         original_config = copy.deepcopy(self._config)
         self.update_config(**kwargs)
         qubits = set([q for qubits in self._value_map.keys() for q in qubits])

Diff for: cirq/vis/heatmap_test.py

@@ -34,6 +34,14 @@ def ax():
     return figure.add_subplot(111)
 
 
+def test_default_ax():
+    row_col_list = ((0, 5), (8, 1), (7, 0), (13, 5), (1, 6), (3, 2), (2, 8))
+    test_value_map = {
+        grid_qubit.GridQubit(row, col): np.random.random() for (row, col) in row_col_list
+    }
+    _, _ = heatmap.Heatmap(test_value_map).plot()
+
+
 @pytest.mark.parametrize('tuple_keys', [True, False])
 def test_cells_positions(ax, tuple_keys):
     row_col_list = ((0, 5), (8, 1), (7, 0), (13, 5), (1, 6), (3, 2), (2, 8))
@@ -61,6 +69,8 @@ def test_two_qubit_heatmap(ax):
     title = "Two Qubit Interaction Heatmap"
     heatmap.TwoQubitInteractionHeatmap(value_map, title=title).plot(ax)
     assert ax.get_title() == title
+    # Test default axis
+    heatmap.TwoQubitInteractionHeatmap(value_map, title=title).plot()
 
 
 def test_invalid_args():

Diff for: cirq/vis/histogram.py

@@ -100,9 +100,9 @@ def integrated_histogram(
     plot_options.update(kwargs)
 
     if cdf_on_x:
-        ax.step(bin_values, parameter_values, **plot_options)
+        ax.step(bin_values, parameter_values, **plot_options)  # type: ignore
     else:
-        ax.step(parameter_values, bin_values, **plot_options)
+        ax.step(parameter_values, bin_values, **plot_options)  # type: ignore
 
     set_semilog = ax.semilogy if cdf_on_x else ax.semilogx
     set_lim = ax.set_xlim if cdf_on_x else ax.set_ylim
@@ -128,15 +128,15 @@ def integrated_histogram(
 
     if median_line:
         set_line(
-            np.median(float_data),
+            float(np.median(float_data)),
             linestyle='--',
             color=plot_options['color'],
             alpha=0.5,
             label=median_label,
         )
     if mean_line:
         set_line(
-            np.mean(float_data),
+            float(np.mean(float_data)),
             linestyle='-.',
             color=plot_options['color'],
             alpha=0.5,

Diff for: cirq/vis/state_histogram.py

@@ -14,7 +14,7 @@
 
 """Tool to visualize the results of a study."""
 
-from typing import Union, Optional, Sequence, SupportsFloat
+from typing import cast, Optional, Sequence, SupportsFloat, Union
 import collections
 import numpy as np
 import matplotlib.pyplot as plt
@@ -51,13 +51,13 @@ def get_state_histogram(result: 'result.Result') -> np.ndarray:
 
 def plot_state_histogram(
     data: Union['result.Result', collections.Counter, Sequence[SupportsFloat]],
-    ax: Optional['plt.Axis'] = None,
+    ax: Optional[plt.Axes] = None,
     *,
     tick_label: Optional[Sequence[str]] = None,
     xlabel: Optional[str] = 'qubit state',
     ylabel: Optional[str] = 'result count',
     title: Optional[str] = 'Result State Histogram',
-) -> 'plt.Axis':
+) -> plt.Axes:
     """Plot the state histogram from either a single result with repetitions or
        a histogram computed using `result.histogram()` or a flattened histogram
        of measurement results computed using `get_state_histogram`.
@@ -87,6 +87,7 @@ def plot_state_histogram(
     show_fig = not ax
     if not ax:
         fig, ax = plt.subplots(1, 1)
+        ax = cast(plt.Axes, ax)
     if isinstance(data, result.Result):
         values = get_state_histogram(data)
     elif isinstance(data, collections.Counter):
@@ -96,9 +97,12 @@ def plot_state_histogram(
     if tick_label is None:
         tick_label = [str(i) for i in range(len(values))]
     ax.bar(np.arange(len(values)), values, tick_label=tick_label)
-    ax.set_xlabel(xlabel)
-    ax.set_ylabel(ylabel)
-    ax.set_title(title)
+    if xlabel:
+        ax.set_xlabel(xlabel)
+    if ylabel:
+        ax.set_ylabel(ylabel)
+    if title:
+        ax.set_title(title)
     if show_fig:
         fig.show()
     return ax

Diff for: cirq/vis/state_histogram_test.py

@@ -78,6 +78,8 @@ def test_plot_state_histogram_result():
     for r1, r2 in zip(ax1.get_children(), ax2.get_children()):
         if isinstance(r1, mpl.patches.Rectangle) and isinstance(r2, mpl.patches.Rectangle):
             assert str(r1) == str(r2)
+    # Test default axis
+    state_histogram.plot_state_histogram(expected_values)
 
 
 @pytest.mark.usefixtures('closefigures')