Give _DummyAxis instances a __name__

efiring · efiring · commit d9bf0be16df6 · 2020-06-12T18:53:00.000-10:00
diff --git a/lib/matplotlib/tests/test_ticker.py b/lib/matplotlib/tests/test_ticker.py
@@ -510,6 +510,14 @@ class TestScalarFormatter:
         (True, (6, 6), (-1e5, 1e5), 6, False),
     ]
 
+    cursor_data = [
+        [0., "0.000"],
+        [0.0123, "0.012"],
+        [0.123, "0.123"],
+        [1.23,  "1.230"],
+        [12.3, "12.300"],
+    ]
+
     @pytest.mark.parametrize('unicode_minus, result',
                              [(True, "\N{MINUS SIGN}1"), (False, "-1")])
     def test_unicode_minus(self, unicode_minus, result):
@@ -556,15 +564,21 @@ def test_scilimits(self, sci_type, scilimits, lim, orderOfMag, fewticks):
         tmp_form.set_locs(ax.yaxis.get_majorticklocs())
         assert orderOfMag == tmp_form.orderOfMagnitude
 
-    def test_cursor_precision(self):
+    @pytest.mark.parametrize('data, expected', cursor_data)
+    def test_cursor_precision(self, data, expected):
         fig, ax = plt.subplots()
         ax.set_xlim(-1, 1)  # Pointing precision of 0.001.
         fmt = ax.xaxis.get_major_formatter().format_data_short
-        assert fmt(0.) == "0.000"
-        assert fmt(0.0123) == "0.012"
-        assert fmt(0.123) == "0.123"
-        assert fmt(1.23) == "1.230"
-        assert fmt(12.3) == "12.300"
+        assert fmt(data) == expected
+
+    @pytest.mark.parametrize('data, expected', cursor_data)
+    def test_cursor_dummy_axis(self, data, expected):
+        # Issue #17624
+        sf = mticker.ScalarFormatter()
+        sf.create_dummy_axis()
+        sf.set_bounds(0, 10)
+        fmt = sf.format_data_short
+        assert fmt(data) == expected
 
 
 class FakeAxis:
diff --git a/lib/matplotlib/ticker.py b/lib/matplotlib/ticker.py
@@ -198,6 +198,8 @@
 
 
 class _DummyAxis:
+    __name__ = "dummy"
+
     def __init__(self, minpos=0):
         self.dataLim = mtransforms.Bbox.unit()
         self.viewLim = mtransforms.Bbox.unit()
@@ -708,8 +710,8 @@ def format_data_short(self, value):
                         screen_xy + [[0, -1], [0, +1]])[:, 1]
                 delta = abs(neighbor_values - value).max()
             else:
-                # Rough approximation: no more than 1e4 pixels.
-                delta = self.axis.get_view_interval() / 1e4
+                # Rough approximation: no more than 1e4 divisions.
+                delta = np.diff(self.axis.get_view_interval()) / 1e4
             # If e.g. value = 45.67 and delta = 0.02, then we want to round to
             # 2 digits after the decimal point (floor(log10(0.02)) = -2);
             # 45.67 contributes 2 digits before the decimal point
