matplotlib · SharadhNaidu · May 18, 2026 · May 19, 2026 · Jun 5, 2026 · Jun 5, 2026
diff --git a/lib/matplotlib/path.py b/lib/matplotlib/path.py
@@ -978,6 +978,11 @@ def arc(cls, theta1, theta2, n=None, is_wedge=False):
         That is, if *theta2* > *theta1* + 360, the arc will be from *theta1* to
         *theta2* - 360 and not a full circle plus some extra overlap.
 
+        As a special case, if the span *theta2* - *theta1* is within
+        floating-point tolerance of a whole number of turns, a complete circle
+        is drawn rather than collapsing a delta of 360*n plus a tiny rounding
+        error to a near-empty arc (matplotlib issues #20388 and #26972).
+
         If *n* is provided, it is the number of spline segments to make.
         If *n* is not provided, the number of spline segments is
         determined based on the delta between *theta1* and *theta2*.
@@ -989,11 +994,17 @@ def arc(cls, theta1, theta2, n=None, is_wedge=False):
         halfpi = np.pi * 0.5
 
         eta1 = theta1
-        eta2 = theta2 - 360 * np.floor((theta2 - theta1) / 360)
-        # Ensure 2pi range is not flattened to 0 due to floating-point errors,
-        # but don't try to expand existing 0 range.
-        if theta2 != theta1 and eta2 <= eta1:
-            eta2 += 360
+        n_turns = (theta2 - theta1) / 360
+        # If the requested span is within floating-point tolerance of a whole
+        # number of turns, draw a complete circle.  Otherwise unwrap *theta2*
+        # to the shortest arc within 360 degrees.  Snapping near-integer
+        # windings here avoids the edge case where a delta of 360*n plus a
+        # tiny rounding error would otherwise collapse to a near-empty arc.
+        if (theta2 != theta1 and round(n_turns) >= 1
+                and abs(n_turns - round(n_turns)) < 1e-9):
+            eta2 = theta1 + 360
+        else:
+            eta2 = theta2 - 360 * np.floor(n_turns)
         eta1, eta2 = np.deg2rad([eta1, eta2])
 
         # number of curve segments to make

diff --git a/lib/matplotlib/tests/test_path.py b/lib/matplotlib/tests/test_path.py
@@ -511,6 +511,27 @@ def test_full_arc(offset):
     np.testing.assert_allclose(maxs, 1)
 
 
+@pytest.mark.parametrize('theta2', [360 + 1e-9, 720, 720 + 1e-9, 360 * 5])
+def test_arc_full_circle_snap(theta2):
+    # A span that is within floating-point tolerance of a whole number of
+    # turns must draw a complete circle, not collapse to a near-empty arc.
+    # This is the floating-point edge case behind gh-20388 and gh-26972.
+    full = Path.arc(0, 360)
+    snapped = Path.arc(0, theta2)
+    assert len(snapped.vertices) == len(full.vertices)
+    np.testing.assert_allclose(np.min(snapped.vertices, axis=0), -1, atol=1e-12)
+    np.testing.assert_allclose(np.max(snapped.vertices, axis=0), 1, atol=1e-12)
+
+
+def test_arc_unwrap_partial_turn():
+    # A span comfortably more than a whole number of turns (not near-integer)
+    # is still unwrapped to the equivalent shortest arc within 360 degrees.
+    np.testing.assert_allclose(Path.arc(0, 410).vertices,
+                               Path.arc(0, 50).vertices)
+    np.testing.assert_allclose(Path.arc(0, 540).vertices,
+                               Path.arc(0, 180).vertices)
+
+
 def test_disjoint_zero_length_segment():
     this_path = Path(
         np.array([

diff --git a/lib/matplotlib/tests/test_polar.py b/lib/matplotlib/tests/test_polar.py
@@ -5,6 +5,7 @@
 import pytest
 
 import matplotlib as mpl
+from matplotlib.path import Path
 from matplotlib.projections.polar import RadialLocator
 from matplotlib import pyplot as plt
 from matplotlib.testing.decorators import image_comparison, check_figures_equal
@@ -328,6 +329,56 @@ def test_polar_gridlines():
     assert ax.yaxis.majorTicks[0].gridline.get_alpha() == .2
 
 
+@pytest.mark.parametrize('span_deg', [359.999999, 360.0,
+                                      360 - 1e-9, 720.0])
+def test_polar_transform_constant_r_arc(span_deg):
+    # PolarTransform's chunking boundary used to disagree with Path.arc's
+    # angle-unwrap step, so an angular delta of nearly-but-not-exactly
+    # 360 degrees collapsed to a near-empty arc. Apply the transform to
+    # a constant-r path of varying angular span and check that the
+    # result remains a non-degenerate circle.
+    fig, ax = plt.subplots(subplot_kw={'projection': 'polar'})
+    fig.canvas.draw()
+    r = 1.0
+    path = Path([(0.0, r), (np.deg2rad(span_deg), r)],
+                [Path.MOVETO, Path.LINETO])
+    path._interpolation_steps = 100
+    out = ax.transProjection.transform_path_non_affine(path)
+    spread = np.ptp(out.vertices, axis=0)
+    assert spread.min() > r * 1.5, (
+        f"transformed arc collapsed for span={span_deg}: spread={spread}")
+
+
+@pytest.mark.parametrize('angle', [10, 20, 30, 45, 90, 110])
+def test_polar_inverted_theta_outer_spine(angle):
+    # With set_theta_direction(-1) and certain values of
+    # set_theta_zero_location offset, the polar outer spine used to
+    # collapse to a near-empty arc.
+    fig, ax = plt.subplots(subplot_kw={'projection': 'polar'})
+    ax.set_theta_direction(-1)
+    ax.set_theta_zero_location("N", angle)
+    fig.canvas.draw()
+    spine = ax.spines['polar']
+    tpath = spine.get_transform().transform_path(spine.get_path())
+    spread = np.ptp(tpath.vertices, axis=0)
+    assert spread.min() > 50, (
+        f"outer spine collapsed for angle={angle}: spread={spread}")
+
+
+@pytest.mark.parametrize('offset', [1.0, np.pi / 2, np.pi, 1.570796327])
+def test_polar_theta_offset_outer_spine(offset):
+    # set_theta_offset used to remove the outer spine outline; same
+    # floating-point root cause as the inverted-theta case above.
+    fig, ax = plt.subplots(subplot_kw={'projection': 'polar'})
+    ax.set_theta_offset(offset)
+    fig.canvas.draw()
+    spine = ax.spines['polar']
+    tpath = spine.get_transform().transform_path(spine.get_path())
+    spread = np.ptp(tpath.vertices, axis=0)
+    assert spread.min() > 50, (
+        f"outer spine collapsed for theta_offset={offset}: spread={spread}")
+
+
 def test_get_tightbbox_polar():
     fig, ax = plt.subplots(subplot_kw={'projection': 'polar'})
     fig.canvas.draw()