diff --git a/lib/matplotlib/axes/_base.py b/lib/matplotlib/axes/_base.py
index edddd7a7f8a5..95a052461ac4 100644
--- a/lib/matplotlib/axes/_base.py
+++ b/lib/matplotlib/axes/_base.py
@@ -2185,6 +2185,10 @@ def autoscale(self, enable=True, axis='both', tight=None):
if axis in ['y', 'both']:
self._autoscaleYon = bool(enable)
scaley = self._autoscaleYon
+ if tight and scalex:
+ self._xmargin = 0
+ if tight and scaley:
+ self._ymargin = 0
self.autoscale_view(tight=tight, scalex=scalex, scaley=scaley)
def autoscale_view(self, tight=None, scalex=True, scaley=True):
@@ -2194,6 +2198,14 @@ def autoscale_view(self, tight=None, scalex=True, scaley=True):
setting *scaley* to *False*. The autoscaling preserves any
axis direction reversal that has already been done.
+ If *tight* is *False*, the axis major locator will be used
+ to expand the view limits if rcParams['axes.autolimit_mode']
+ is 'round_numbers'. Note that any margins that are in effect
+ will be applied first, regardless of whether *tight* is
+ *True* or *False*. Specifying *tight* as *True* or *False*
+ saves the setting as a private attribute of the Axes; specifying
+ it as *None* (the default) applies the previously saved value.
+
The data limits are not updated automatically when artist data are
changed after the artist has been added to an Axes instance. In that
case, use :meth:`matplotlib.axes.Axes.relim` prior to calling
@@ -2246,52 +2258,56 @@ def autoscale_view(self, tight=None, scalex=True, scaley=True):
def handle_single_axis(scale, autoscaleon, shared_axes, interval,
minpos, axis, margin, do_lower_margin,
do_upper_margin, set_bound):
- if scale and autoscaleon:
- shared = shared_axes.get_siblings(self)
- dl = [ax.dataLim for ax in shared]
- # ignore non-finite data limits if good limits exist
- finite_dl = [d for d in dl if np.isfinite(d).all()]
- if len(finite_dl):
- dl = finite_dl
-
- bb = mtransforms.BboxBase.union(dl)
- x0, x1 = getattr(bb, interval)
- locator = axis.get_major_locator()
- try:
- # e.g., DateLocator has its own nonsingular()
- x0, x1 = locator.nonsingular(x0, x1)
- except AttributeError:
- # Default nonsingular for, e.g., MaxNLocator
- x0, x1 = mtransforms.nonsingular(
- x0, x1, increasing=False, expander=0.05)
-
- if margin > 0 and (do_lower_margin or do_upper_margin):
- if axis.get_scale() == 'linear':
- delta = (x1 - x0) * margin
- if do_lower_margin:
- x0 -= delta
- if do_upper_margin:
- x1 += delta
- else:
- # If we have a non-linear scale, we need to
- # add the margin in figure space and then
- # transform back
- minpos = getattr(bb, minpos)
- transform = axis.get_transform()
- inverse_trans = transform.inverted()
- x0, x1 = axis._scale.limit_range_for_scale(
- x0, x1, minpos)
- x0t, x1t = transform.transform([x0, x1])
- delta = (x1t - x0t) * margin
- if do_lower_margin:
- x0t -= delta
- if do_upper_margin:
- x1t += delta
- x0, x1 = inverse_trans.transform([x0t, x1t])
-
- if not _tight:
- x0, x1 = locator.view_limits(x0, x1)
- set_bound(x0, x1)
+
+ if not (scale and autoscaleon):
+ return # nothing to do...
+
+ shared = shared_axes.get_siblings(self)
+ dl = [ax.dataLim for ax in shared]
+ # ignore non-finite data limits if good limits exist
+ finite_dl = [d for d in dl if np.isfinite(d).all()]
+ if len(finite_dl):
+ dl = finite_dl
+
+ bb = mtransforms.BboxBase.union(dl)
+ x0, x1 = getattr(bb, interval)
+ locator = axis.get_major_locator()
+ try:
+ # e.g., DateLocator has its own nonsingular()
+ x0, x1 = locator.nonsingular(x0, x1)
+ except AttributeError:
+ # Default nonsingular for, e.g., MaxNLocator
+ x0, x1 = mtransforms.nonsingular(
+ x0, x1, increasing=False, expander=0.05)
+
+ if margin > 0 and (do_lower_margin or do_upper_margin):
+ if axis.get_scale() == 'linear':
+ delta = (x1 - x0) * margin
+ if do_lower_margin:
+ x0 -= delta
+ if do_upper_margin:
+ x1 += delta
+ else:
+ # If we have a non-linear scale, we need to
+ # add the margin in figure space and then
+ # transform back
+ minpos = getattr(bb, minpos)
+ transform = axis.get_transform()
+ inverse_trans = transform.inverted()
+ x0, x1 = axis._scale.limit_range_for_scale(
+ x0, x1, minpos)
+ x0t, x1t = transform.transform([x0, x1])
+ delta = (x1t - x0t) * margin
+ if do_lower_margin:
+ x0t -= delta
+ if do_upper_margin:
+ x1t += delta
+ x0, x1 = inverse_trans.transform([x0t, x1t])
+
+ if not _tight:
+ x0, x1 = locator.view_limits(x0, x1)
+ set_bound(x0, x1)
+ # End of definition of internal function 'handle_single_axis'.
handle_single_axis(
scalex, self._autoscaleXon, self._shared_x_axes,
diff --git a/lib/matplotlib/tests/test_axes.py b/lib/matplotlib/tests/test_axes.py
index 29ed50eaf6e3..0bcbaa492b45 100644
--- a/lib/matplotlib/tests/test_axes.py
+++ b/lib/matplotlib/tests/test_axes.py
@@ -167,6 +167,16 @@ def test_autoscale_tiny_range():
ax[i].plot([0, 1], [1, 1 + y1])
+@cleanup(style='default')
+def test_autoscale_tight():
+ fig, ax = plt.subplots(1, 1)
+ ax.plot([1, 2, 3, 4])
+ ax.autoscale(enable=True, axis='x', tight=False)
+ ax.autoscale(enable=True, axis='y', tight=True)
+ assert_allclose(ax.get_xlim(), (-0.15, 3.15))
+ assert_allclose(ax.get_ylim(), (1.0, 4.0))
+
+
@image_comparison(baseline_images=['offset_points'],
remove_text=True)
def test_basic_annotate():
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