Hi, thanks for cool library, I especially enjoy using objects interface.
While using it I encountered a small issue when trying to customise tick labels using matplotlib formatter in combination with so.Est(). If I replace it with so.Agg() the issue disappears. I guess this has something to do with the fact that several variables use the same scale (y/ymin/ymax) and _view_interval is not initialised properly in that case?
import seaborn as sns
import seaborn.objects as so
import matplotlib as mpl
fmri = sns.load_dataset("fmri")
(
so.Plot(fmri, x="timepoint", y="signal", color="event")
.add(so.Band(), so.Est())
.scale(y=so.Continuous().label(mpl.ticker.PercentFormatter()))
)File ~/.pyenv/versions/miniforge3/lib/python3.9/site-packages/matplotlib/ticker.py:233, in Formatter.format_ticks(self, values)
231 """Return the tick labels for all the ticks at once."""
232 self.set_locs(values)
--> 233 return [self(value, i) for i, value in enumerate(values)]
File ~/.pyenv/versions/miniforge3/lib/python3.9/site-packages/matplotlib/ticker.py:233, in <listcomp>(.0)
231 """Return the tick labels for all the ticks at once."""
232 self.set_locs(values)
--> 233 return [self(value, i) for i, value in enumerate(values)]
File ~/.pyenv/versions/miniforge3/lib/python3.9/site-packages/matplotlib/ticker.py:1525, in PercentFormatter.__call__(self, x, pos)
1523 def __call__(self, x, pos=None):
1524 """Format the tick as a percentage with the appropriate scaling."""
-> 1525 ax_min, ax_max = self.axis.get_view_interval()
1526 display_range = abs(ax_max - ax_min)
1527 return self.fix_minus(self.format_pct(x, display_range))
File ~/.pyenv/versions/miniforge3/lib/python3.9/site-packages/seaborn/_core/scales.py:921, in PseudoAxis.get_view_interval(self)
920 def get_view_interval(self):
--> 921 return self._view_interval
AttributeError: 'PseudoAxis' object has no attribute '_view_interval'
Versions:
seaborn: 0.13.0
matplotlib: 3.6.2
Hi, thanks for cool library, I especially enjoy using objects interface.
While using it I encountered a small issue when trying to customise tick labels using matplotlib formatter in combination with
so.Est(). If I replace it withso.Agg()the issue disappears. I guess this has something to do with the fact that several variables use the same scale (y/ymin/ymax) and_view_intervalis not initialised properly in that case?Versions:
seaborn: 0.13.0
matplotlib: 3.6.2