Simplify log locator logic

dstansby · dstansby · commit ec9ecbc4abbd · 2022-12-01T09:55:42.000Z
diff --git a/lib/matplotlib/tests/test_ticker.py b/lib/matplotlib/tests/test_ticker.py
@@ -198,10 +198,10 @@ class TestLogLocator:
         'vmin, vmax, expected_ticks',
         (
             [1, 10, [1, 10]],
-            [0.9, 10.1, [1, 10]],
-            [0.9, 9, [1]],
-            [1.1, 11, [10]],
-            [0.5, 983, [1, 10, 100]]
+            [0.9, 10.1, [0.1, 1, 10, 100]],
+            [0.9, 9, [0.1, 1, 10]],
+            [1.1, 11, [1, 10, 100]],
+            [0.5, 983, [0.1, 1, 10, 100, 1000]]
         )
     )
     def test_tick_locs(self, vmin, vmax, expected_ticks):
@@ -210,13 +210,13 @@ def test_tick_locs(self, vmin, vmax, expected_ticks):
 
     def test_basic(self):
         loc = mticker.LogLocator(numticks=5)
-        test_value = np.array([1.00000000e-05, 1.00000000e-03, 1.00000000e-01,
+        test_value = np.array([1.00000000e-03, 1.00000000e-01,
                                1.00000000e+01, 1.00000000e+03, 1.00000000e+05,
-                               1.00000000e+07, 1.000000000e+09])
-        assert_almost_equal(loc.tick_values(0.001, 1.1e5), test_value)
+                               1.00000000e+07])
+        assert_almost_equal(loc.tick_values(1e-3, 1.1e5), test_value)
 
         loc = mticker.LogLocator(base=2)
-        test_value = np.array([0.5, 1., 2., 4., 8., 16., 32., 64., 128., 256.])
+        test_value = np.array([1., 2., 4., 8., 16., 32., 64., 128.])
         assert_almost_equal(loc.tick_values(1, 100), test_value)
 
     def test_invalid_lim_error(self):
diff --git a/lib/matplotlib/ticker.py b/lib/matplotlib/ticker.py
@@ -2408,8 +2408,10 @@ def tick_values(self, vmin, vmax):
         # whether we're a major or a minor locator.
         have_subs = len(subs) > 1 or (len(subs) == 1 and subs[0] != 1.0)
 
-        decades = np.arange(math.floor(log_vmin) - stride,
-                            math.ceil(log_vmax) + 2 * stride, stride)
+        # Return one tick below (or equal to) vmin,
+        # and one tick above (or equal to) vmax
+        decades = np.arange(math.floor(log_vmin),
+                            math.ceil(log_vmax) + stride, stride)
 
         if hasattr(self, '_transform'):
             ticklocs = self._transform.inverted().transform(decades)
