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Don't fallback to view limits when autoscale()ing no data. #15258

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Merged
merged 3 commits into from
Oct 2, 2019
Merged

Don't fallback to view limits when autoscale()ing no data. #15258

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84448ca
Don't fallback to view limits when autoscale()ing no data.
anntzer Sep 12, 2019
cf2ef39
Add an extra comment
jklymak Sep 13, 2019
63454db
Force autoscaling immediately after setting a scale.
anntzer Sep 13, 2019
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32 changes: 18 additions & 14 deletions lib/matplotlib/axes/_base.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2409,17 +2409,9 @@ def handle_single_axis(scale, autoscaleon, shared_axes, interval,
dl.extend(y_finite)

bb = mtransforms.BboxBase.union(dl)
# fall back on the viewlimits if this is not finite:
vl = None
if not np.isfinite(bb.intervalx).all():
vl = mtransforms.BboxBase.union([ax.viewLim for ax in shared])
bb.intervalx = vl.intervalx
if not np.isfinite(bb.intervaly).all():
if vl is None:
vl = mtransforms.BboxBase.union(
[ax.viewLim for ax in shared])
bb.intervaly = vl.intervaly
x0, x1 = getattr(bb, interval)
# If x0 and x1 are non finite, use the locator to figure out
# default limits.
locator = axis.get_major_locator()
x0, x1 = locator.nonsingular(x0, x1)

Expand Down Expand Up @@ -3260,20 +3252,26 @@ def set_xscale(self, value, **kwargs):
- `matplotlib.scale.SymmetricalLogScale`
- `matplotlib.scale.LogitScale`


Notes
-----
By default, Matplotlib supports the above mentioned scales.
Additionally, custom scales may be registered using
`matplotlib.scale.register_scale`. These scales can then also
be used here.
"""
old_default_lims = (self.xaxis.get_major_locator()
.nonsingular(-np.inf, np.inf))
g = self.get_shared_x_axes()
for ax in g.get_siblings(self):
ax.xaxis._set_scale(value, **kwargs)
ax._update_transScale()
ax.stale = True
self._request_autoscale_view(scaley=False)
new_default_lims = (self.xaxis.get_major_locator()
.nonsingular(-np.inf, np.inf))
if old_default_lims != new_default_lims:
# Force autoscaling now, to take advantage of the scale locator's
# nonsingular() before it possibly gets swapped out by the user.
self.autoscale_view(scaley=False)

@cbook._make_keyword_only("3.2", "minor")
def get_xticks(self, minor=False):
Expand Down Expand Up @@ -3645,20 +3643,26 @@ def set_yscale(self, value, **kwargs):
- `matplotlib.scale.SymmetricalLogScale`
- `matplotlib.scale.LogitScale`


Notes
-----
By default, Matplotlib supports the above mentioned scales.
Additionally, custom scales may be registered using
`matplotlib.scale.register_scale`. These scales can then also
be used here.
"""
old_default_lims = (self.yaxis.get_major_locator()
.nonsingular(-np.inf, np.inf))
g = self.get_shared_y_axes()
for ax in g.get_siblings(self):
ax.yaxis._set_scale(value, **kwargs)
ax._update_transScale()
ax.stale = True
self._request_autoscale_view(scalex=False)
new_default_lims = (self.yaxis.get_major_locator()
.nonsingular(-np.inf, np.inf))
if old_default_lims != new_default_lims:
# Force autoscaling now, to take advantage of the scale locator's
# nonsingular() before it possibly gets swapped out by the user.
self.autoscale_view(scalex=False)

@cbook._make_keyword_only("3.2", "minor")
def get_yticks(self, minor=False):
Expand Down
8 changes: 8 additions & 0 deletions lib/matplotlib/dates.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1118,6 +1118,10 @@ def nonsingular(self, vmin, vmax):
Given the proposed upper and lower extent, adjust the range
if it is too close to being singular (i.e. a range of ~0).
"""
if not np.isfinite(vmin) or not np.isfinite(vmax):
# Except if there is no data, then use 2000-2010 as default.
return (date2num(datetime.date(2000, 1, 1)),
date2num(datetime.date(2010, 1, 1)))
if vmax < vmin:
vmin, vmax = vmax, vmin
unit = self._get_unit()
Expand Down Expand Up @@ -1337,6 +1341,10 @@ def tick_values(self, vmin, vmax):
def nonsingular(self, vmin, vmax):
# whatever is thrown at us, we can scale the unit.
# But default nonsingular date plots at an ~4 year period.
if not np.isfinite(vmin) or not np.isfinite(vmax):
# Except if there is no data, then use 2000-2010 as default.
return (date2num(datetime.date(2000, 1, 1)),
date2num(datetime.date(2010, 1, 1)))
if vmax < vmin:
vmin, vmax = vmax, vmin
if vmin == vmax:
Expand Down
7 changes: 7 additions & 0 deletions lib/matplotlib/tests/test_axes.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2170,6 +2170,13 @@ def test_log_scales():
ax.set_xscale('log', basex=9.0)


def test_log_scales_no_data():
_, ax = plt.subplots()
ax.set(xscale="log", yscale="log")
ax.xaxis.set_major_locator(mticker.MultipleLocator(1))
assert ax.get_xlim() == ax.get_ylim() == (1, 10)


def test_log_scales_invalid():
fig = plt.figure()
ax = fig.add_subplot(1, 1, 1)
Expand Down
14 changes: 13 additions & 1 deletion lib/matplotlib/ticker.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1710,7 +1710,19 @@ def raise_if_exceeds(self, locs):
return locs

def nonsingular(self, v0, v1):
"""Expand a range as needed to avoid singularities."""
"""
Adjust a range as needed to avoid singularities.

This method gets called during autoscaling, with ``(v0, v1)`` set to
the data limits on the axes if the axes contains any data, or
``(-inf, +inf)`` if not.

- If ``v0 == v1`` (possibly up to some floating point slop), this
method returns an expanded interval around this value.
- If ``(v0, v1) == (-inf, +inf)``, this method returns appropriate
default view limits.
- Otherwise, ``(v0, v1)`` is returned without modification.
"""
return mtransforms.nonsingular(v0, v1, expander=.05)

def view_limits(self, vmin, vmax):
Expand Down