Merge pull request matplotlib#24295 from anntzer/ua

timhoffm · web-flow · commit c8d16561b697 · 2022-10-30T00:11:53.000+02:00
Remove unnecessary np.{,as}array / astype calls.
diff --git a/examples/event_handling/path_editor.py b/examples/event_handling/path_editor.py
@@ -82,17 +82,12 @@ def get_ind_under_point(self, event):
         Return the index of the point closest to the event position or *None*
         if no point is within ``self.epsilon`` to the event position.
         """
-        # display coords
-        xy = np.asarray(self.pathpatch.get_path().vertices)
-        xyt = self.pathpatch.get_transform().transform(xy)
+        xy = self.pathpatch.get_path().vertices
+        xyt = self.pathpatch.get_transform().transform(xy)  # to display coords
         xt, yt = xyt[:, 0], xyt[:, 1]
         d = np.sqrt((xt - event.x)**2 + (yt - event.y)**2)
         ind = d.argmin()
-
-        if d[ind] >= self.epsilon:
-            ind = None
-
-        return ind
+        return ind if d[ind] < self.epsilon else None
 
     def on_draw(self, event):
         """Callback for draws."""
diff --git a/examples/subplots_axes_and_figures/secondary_axis.py b/examples/subplots_axes_and_figures/secondary_axis.py
@@ -59,7 +59,7 @@ def rad2deg(x):
 
 def one_over(x):
     """Vectorized 1/x, treating x==0 manually"""
-    x = np.array(x).astype(float)
+    x = np.array(x, float)
     near_zero = np.isclose(x, 0)
     x[near_zero] = np.inf
     x[~near_zero] = 1 / x[~near_zero]
diff --git a/examples/units/basic_units.py b/examples/units/basic_units.py
@@ -144,7 +144,7 @@ def __getattribute__(self, name):
         return object.__getattribute__(self, name)
 
     def __array__(self, dtype=object):
-        return np.asarray(self.value).astype(dtype)
+        return np.asarray(self.value, dtype)
 
     def __array_wrap__(self, array, context):
         return TaggedValue(array, self.unit)
diff --git a/lib/matplotlib/backend_bases.py b/lib/matplotlib/backend_bases.py
@@ -1464,7 +1464,7 @@ def on_pick(event):
             line = event.artist
             xdata, ydata = line.get_data()
             ind = event.ind
-            print('on pick line:', np.array([xdata[ind], ydata[ind]]).T)
+            print(f'on pick line: {xdata[ind]:.3f}, {ydata[ind]:.3f}')
 
         cid = fig.canvas.mpl_connect('pick_event', on_pick)
     """
diff --git a/lib/matplotlib/collections.py b/lib/matplotlib/collections.py
@@ -547,8 +547,8 @@ def set_offsets(self, offsets):
         if offsets.shape == (2,):  # Broadcast (2,) -> (1, 2) but nothing else.
             offsets = offsets[None, :]
         self._offsets = np.column_stack(
-            (np.asarray(self.convert_xunits(offsets[:, 0]), 'float'),
-             np.asarray(self.convert_yunits(offsets[:, 1]), 'float')))
+            (np.asarray(self.convert_xunits(offsets[:, 0]), float),
+             np.asarray(self.convert_yunits(offsets[:, 1]), float)))
         self.stale = True
 
     def get_offsets(self):
@@ -573,7 +573,7 @@ def set_linewidth(self, lw):
         if lw is None:
             lw = self._get_default_linewidth()
         # get the un-scaled/broadcast lw
-        self._us_lw = np.atleast_1d(np.asarray(lw))
+        self._us_lw = np.atleast_1d(lw)
 
         # scale all of the dash patterns.
         self._linewidths, self._linestyles = self._bcast_lwls(
diff --git a/lib/matplotlib/contour.py b/lib/matplotlib/contour.py
@@ -1144,7 +1144,7 @@ def _process_contour_level_args(self, args):
         if isinstance(levels_arg, Integral):
             self.levels = self._autolev(levels_arg)
         else:
-            self.levels = np.asarray(levels_arg).astype(np.float64)
+            self.levels = np.asarray(levels_arg, np.float64)
 
         if not self.filled:
             inside = (self.levels > self.zmin) & (self.levels < self.zmax)
diff --git a/lib/matplotlib/image.py b/lib/matplotlib/image.py
@@ -1701,7 +1701,7 @@ def _pil_png_to_float_array(pil_png):
     mode = pil_png.mode
     rawmode = pil_png.png.im_rawmode
     if rawmode == "1":  # Grayscale.
-        return np.asarray(pil_png).astype(np.float32)
+        return np.asarray(pil_png, np.float32)
     if rawmode == "L;2":  # Grayscale.
         return np.divide(pil_png, 2**2 - 1, dtype=np.float32)
     if rawmode == "L;4":  # Grayscale.
diff --git a/lib/matplotlib/patches.py b/lib/matplotlib/patches.py
@@ -1221,9 +1221,7 @@ def _recompute_path(self):
                 arc.codes, [connector, connector, Path.CLOSEPOLY]])
 
         # Shift and scale the wedge to the final location.
-        v *= self.r
-        v += np.asarray(self.center)
-        self._path = Path(v, c)
+        self._path = Path(v * self.r + self.center, c)
 
     def set_center(self, center):
         self._path = None
diff --git a/lib/matplotlib/sankey.py b/lib/matplotlib/sankey.py
@@ -434,10 +434,7 @@ def add(self, patchlabel='', flows=None, orientations=None, labels='',
         Sankey.finish
         """
         # Check and preprocess the arguments.
-        if flows is None:
-            flows = np.array([1.0, -1.0])
-        else:
-            flows = np.array(flows)
+        flows = np.array([1.0, -1.0]) if flows is None else np.array(flows)
         n = flows.shape[0]  # Number of flows
         if rotation is None:
             rotation = 0
diff --git a/lib/matplotlib/testing/compare.py b/lib/matplotlib/testing/compare.py
@@ -500,8 +500,8 @@ def save_diff_image(expected, actual, output):
     actual_image = _load_image(actual)
     actual_image, expected_image = crop_to_same(
         actual, actual_image, expected, expected_image)
-    expected_image = np.array(expected_image).astype(float)
-    actual_image = np.array(actual_image).astype(float)
+    expected_image = np.array(expected_image, float)
+    actual_image = np.array(actual_image, float)
     if expected_image.shape != actual_image.shape:
         raise ImageComparisonFailure(
             "Image sizes do not match expected size: {} "
diff --git a/lib/matplotlib/tests/test_axes.py b/lib/matplotlib/tests/test_axes.py
@@ -1499,7 +1499,7 @@ def test_arc_ellipse():
         [np.cos(rtheta), -np.sin(rtheta)],
         [np.sin(rtheta), np.cos(rtheta)]])
 
-    x, y = np.dot(R, np.array([x, y]))
+    x, y = np.dot(R, [x, y])
     x += xcenter
     y += ycenter
 
@@ -2097,7 +2097,7 @@ def test_hist_datetime_datasets():
 @pytest.mark.parametrize("bins_preprocess",
                          [mpl.dates.date2num,
                           lambda bins: bins,
-                          lambda bins: np.asarray(bins).astype('datetime64')],
+                          lambda bins: np.asarray(bins, 'datetime64')],
                          ids=['date2num', 'datetime.datetime',
                               'np.datetime64'])
 def test_hist_datetime_datasets_bins(bins_preprocess):
@@ -6409,7 +6409,7 @@ def test_pandas_pcolormesh(pd):
 
 def test_pandas_indexing_dates(pd):
     dates = np.arange('2005-02', '2005-03', dtype='datetime64[D]')
-    values = np.sin(np.array(range(len(dates))))
+    values = np.sin(range(len(dates)))
     df = pd.DataFrame({'dates': dates, 'values': values})
 
     ax = plt.gca()
diff --git a/lib/matplotlib/tests/test_collections.py b/lib/matplotlib/tests/test_collections.py
@@ -696,7 +696,7 @@ def test_pathcollection_legend_elements():
 
     h, l = sc.legend_elements(fmt="{x:g}")
     assert len(h) == 5
-    assert_array_equal(np.array(l).astype(float), np.arange(5))
+    assert l == ["0", "1", "2", "3", "4"]
     colors = np.array([line.get_color() for line in h])
     colors2 = sc.cmap(np.arange(5)/4)
     assert_array_equal(colors, colors2)
@@ -707,16 +707,14 @@ def test_pathcollection_legend_elements():
     l2 = ax.legend(h2, lab2, loc=2)
 
     h, l = sc.legend_elements(prop="sizes", alpha=0.5, color="red")
-    alpha = np.array([line.get_alpha() for line in h])
-    assert_array_equal(alpha, 0.5)
-    color = np.array([line.get_markerfacecolor() for line in h])
-    assert_array_equal(color, "red")
+    assert all(line.get_alpha() == 0.5 for line in h)
+    assert all(line.get_markerfacecolor() == "red" for line in h)
     l3 = ax.legend(h, l, loc=4)
 
     h, l = sc.legend_elements(prop="sizes", num=4, fmt="{x:.2f}",
                               func=lambda x: 2*x)
     actsizes = [line.get_markersize() for line in h]
-    labeledsizes = np.sqrt(np.array(l).astype(float)/2)
+    labeledsizes = np.sqrt(np.array(l, float) / 2)
     assert_array_almost_equal(actsizes, labeledsizes)
     l4 = ax.legend(h, l, loc=3)
 
@@ -727,7 +725,7 @@ def test_pathcollection_legend_elements():
 
     levels = [-1, 0, 55.4, 260]
     h6, lab6 = sc.legend_elements(num=levels, prop="sizes", fmt="{x:g}")
-    assert_array_equal(np.array(lab6).astype(float), levels[2:])
+    assert [float(l) for l in lab6] == levels[2:]
 
     for l in [l1, l2, l3, l4]:
         ax.add_artist(l)
diff --git a/lib/matplotlib/tests/test_colors.py b/lib/matplotlib/tests/test_colors.py
@@ -243,7 +243,7 @@ def test_colormap_invalid():
     # Test scalar representations
     assert_array_equal(cmap(-np.inf), cmap(0))
     assert_array_equal(cmap(np.inf), cmap(1.0))
-    assert_array_equal(cmap(np.nan), np.array([0., 0., 0., 0.]))
+    assert_array_equal(cmap(np.nan), [0., 0., 0., 0.])
 
 
 def test_colormap_return_types():
@@ -574,7 +574,7 @@ def test_Normalize():
     # i.e. 127-(-128) here).
     vals = np.array([-128, 127], dtype=np.int8)
     norm = mcolors.Normalize(vals.min(), vals.max())
-    assert_array_equal(np.asarray(norm(vals)), [0, 1])
+    assert_array_equal(norm(vals), [0, 1])
 
     # Don't lose precision on longdoubles (float128 on Linux):
     # for array inputs...
diff --git a/lib/matplotlib/tests/test_sankey.py b/lib/matplotlib/tests/test_sankey.py
@@ -1,5 +1,5 @@
 import pytest
-import numpy as np
+from numpy.testing import assert_allclose, assert_array_equal
 
 from matplotlib.sankey import Sankey
 from matplotlib.testing.decorators import check_figures_equal
@@ -67,28 +67,28 @@ def test_sankey2():
     s = Sankey(flows=[0.25, -0.25, 0.5, -0.5], labels=['Foo'],
                orientations=[-1], unit='Bar')
     sf = s.finish()
-    assert np.all(np.equal(np.array((0.25, -0.25, 0.5, -0.5)), sf[0].flows))
+    assert_array_equal(sf[0].flows, [0.25, -0.25, 0.5, -0.5])
     assert sf[0].angles == [1, 3, 1, 3]
     assert all([text.get_text()[0:3] == 'Foo' for text in sf[0].texts])
     assert all([text.get_text()[-3:] == 'Bar' for text in sf[0].texts])
     assert sf[0].text.get_text() == ''
-    assert np.allclose(np.array(((-1.375, -0.52011255),
-                                 (1.375, -0.75506044),
-                                 (-0.75, -0.41522509),
-                                 (0.75, -0.8599479))),
-                       sf[0].tips)
+    assert_allclose(sf[0].tips,
+                    [(-1.375, -0.52011255),
+                     (1.375, -0.75506044),
+                     (-0.75, -0.41522509),
+                     (0.75, -0.8599479)])
 
     s = Sankey(flows=[0.25, -0.25, 0, 0.5, -0.5], labels=['Foo'],
                orientations=[-1], unit='Bar')
     sf = s.finish()
-    assert np.all(np.equal(np.array((0.25, -0.25, 0, 0.5, -0.5)), sf[0].flows))
+    assert_array_equal(sf[0].flows, [0.25, -0.25, 0, 0.5, -0.5])
     assert sf[0].angles == [1, 3, None, 1, 3]
-    assert np.allclose(np.array(((-1.375, -0.52011255),
-                                 (1.375, -0.75506044),
-                                 (0, 0),
-                                 (-0.75, -0.41522509),
-                                 (0.75, -0.8599479))),
-                       sf[0].tips)
+    assert_allclose(sf[0].tips,
+                    [(-1.375, -0.52011255),
+                     (1.375, -0.75506044),
+                     (0, 0),
+                     (-0.75, -0.41522509),
+                     (0.75, -0.8599479)])
 
 
 @check_figures_equal(extensions=['png'])
diff --git a/lib/matplotlib/tests/test_transforms.py b/lib/matplotlib/tests/test_transforms.py
@@ -422,7 +422,7 @@ def test_pathc_extents_non_affine(self):
         ax = plt.axes()
         offset = mtransforms.Affine2D().translate(10, 10)
         na_offset = NonAffineForTest(mtransforms.Affine2D().translate(10, 10))
-        pth = Path(np.array([[0, 0], [0, 10], [10, 10], [10, 0]]))
+        pth = Path([[0, 0], [0, 10], [10, 10], [10, 0]])
         patch = mpatches.PathPatch(pth,
                                    transform=offset + na_offset + ax.transData)
         ax.add_patch(patch)
@@ -432,7 +432,7 @@ def test_pathc_extents_non_affine(self):
     def test_pathc_extents_affine(self):
         ax = plt.axes()
         offset = mtransforms.Affine2D().translate(10, 10)
-        pth = Path(np.array([[0, 0], [0, 10], [10, 10], [10, 0]]))
+        pth = Path([[0, 0], [0, 10], [10, 10], [10, 0]])
         patch = mpatches.PathPatch(pth, transform=offset + ax.transData)
         ax.add_patch(patch)
         expected_data_lim = np.array([[0., 0.], [10.,  10.]]) + 10
diff --git a/lib/matplotlib/tests/test_triangulation.py b/lib/matplotlib/tests/test_triangulation.py
@@ -944,8 +944,7 @@ def test_tritools():
     mask = np.array([False, False, True], dtype=bool)
     triang = mtri.Triangulation(x, y, triangles, mask=mask)
     analyser = mtri.TriAnalyzer(triang)
-    assert_array_almost_equal(analyser.scale_factors,
-                              np.array([1., 1./(1.+0.5*np.sqrt(3.))]))
+    assert_array_almost_equal(analyser.scale_factors, [1, 1/(1+3**.5/2)])
     assert_array_almost_equal(
         analyser.circle_ratios(rescale=False),
         np.ma.masked_array([0.5, 1./(1.+np.sqrt(2.)), np.nan], mask))
diff --git a/lib/matplotlib/transforms.py b/lib/matplotlib/transforms.py
@@ -925,7 +925,7 @@ def update_from_data_y(self, y, ignore=None):
            - When ``False``, include the existing bounds of the `Bbox`.
            - When ``None``, use the last value passed to :meth:`ignore`.
         """
-        y = np.array(y).ravel()
+        y = np.ravel(y)
         self.update_from_data_xy(np.column_stack([np.ones(y.size), y]),
                                  ignore=ignore, updatex=False)
 
diff --git a/lib/mpl_toolkits/mplot3d/axes3d.py b/lib/mpl_toolkits/mplot3d/axes3d.py
@@ -3207,7 +3207,7 @@ def _extract_errs(err, data, lomask, himask):
             invM = np.linalg.inv(self.get_proj())
         # elev=azim=roll=0 produces the Y-Z plane, so quiversize in 2D 'x' is
         # 'y' in 3D, hence the 1 index.
-        quiversize = np.dot(invM, np.array([quiversize, 0, 0, 0]))[1]
+        quiversize = np.dot(invM, [quiversize, 0, 0, 0])[1]
         # Quivers use a fixed 15-degree arrow head, so scale up the length so
         # that the size corresponds to the base. In other words, this constant
         # corresponds to the equation tan(15) = (base / 2) / (arrow length).
diff --git a/lib/mpl_toolkits/mplot3d/axis3d.py b/lib/mpl_toolkits/mplot3d/axis3d.py
@@ -164,8 +164,7 @@ def _init3d(self):
             antialiased=True)
 
         # Store dummy data in Polygon object
-        self.pane = mpatches.Polygon(
-            np.array([[0, 0], [0, 1]]), closed=False)
+        self.pane = mpatches.Polygon([[0, 0], [0, 1]], closed=False)
         self.set_pane_color(self._axinfo['color'])
 
         self.axes._set_artist_props(self.line)
diff --git a/lib/mpl_toolkits/tests/test_axes_grid1.py b/lib/mpl_toolkits/tests/test_axes_grid1.py
@@ -209,23 +209,22 @@ def test_inset_axes_complete():
     ins = inset_axes(ax, width=2., height=2., borderpad=0)
     fig.canvas.draw()
     assert_array_almost_equal(
-            ins.get_position().extents,
-            np.array(((0.9*figsize[0]-2.)/figsize[0],
-                      (0.9*figsize[1]-2.)/figsize[1], 0.9, 0.9)))
+        ins.get_position().extents,
+        [(0.9*figsize[0]-2.)/figsize[0], (0.9*figsize[1]-2.)/figsize[1],
+         0.9, 0.9])
 
     ins = inset_axes(ax, width="40%", height="30%", borderpad=0)
     fig.canvas.draw()
     assert_array_almost_equal(
-            ins.get_position().extents,
-            np.array((.9-.8*.4, .9-.8*.3, 0.9, 0.9)))
+        ins.get_position().extents, [.9-.8*.4, .9-.8*.3, 0.9, 0.9])
 
     ins = inset_axes(ax, width=1., height=1.2, bbox_to_anchor=(200, 100),
                      loc=3, borderpad=0)
     fig.canvas.draw()
     assert_array_almost_equal(
-            ins.get_position().extents,
-            np.array((200./dpi/figsize[0], 100./dpi/figsize[1],
-                     (200./dpi+1)/figsize[0], (100./dpi+1.2)/figsize[1])))
+        ins.get_position().extents,
+        [200/dpi/figsize[0], 100/dpi/figsize[1],
+         (200/dpi+1)/figsize[0], (100/dpi+1.2)/figsize[1]])
 
     ins1 = inset_axes(ax, width="35%", height="60%", loc=3, borderpad=1)
     ins2 = inset_axes(ax, width="100%", height="100%",
