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Uptade fix number of levels with log contour #29137

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Uptade fix number of levels with log contour #29137

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27 changes: 21 additions & 6 deletions lib/matplotlib/contour.py
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Original file line number Diff line number Diff line change
Expand Up @@ -960,13 +960,12 @@
label.set_color(self.labelMappable.to_rgba(cv))
super().changed()

def _autolev(self, N):
def _autolev(self, N, *, using_default):
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I think this extra argument is not necessary.

The only place where this is passed it is simply a N is not None (on the input side, but the effect is the same)

So even if the variable is useful, it can be computed internally.

However, even further, the difference between LogLocator() and LogLocator(numticks=N) when N is None is nothing, therefore you can just pass it as a kwarg.

Haven't fully thought through the last portion (adjustments if levels are still insufficient) and if there may need to be at least a if N is not None in there potentially, but not sure yet.

"""
Select contour levels to span the data.

The target number of levels, *N*, is used only when the
scale is not log and default locator is used.

locator is not set and the scale is log or the default
locator is used.

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lib/matplotlib/contour.py#L967-L968 

Added lines #L967 - L968 were not covered by tests
We need two more levels for filled contours than for
line contours, because for the latter we need to specify
the lower and upper boundary of each range. For example,
Expand All @@ -976,7 +975,12 @@
"""
if self.locator is None:
if self.logscale:
self.locator = ticker.LogLocator()
if using_default:
# Let log locator choose instead of using hard coded value
# set in self._process_contour_level_args()
self.locator = ticker.LogLocator()
else:
self.locator = ticker.LogLocator(numticks=N)
else:
self.locator = ticker.MaxNLocator(N + 1, min_n_ticks=1)

Expand All @@ -993,14 +997,25 @@
i0 = under[-1] if len(under) else 0
over = np.nonzero(lev > self.zmax)[0]
i1 = over[0] + 1 if len(over) else len(lev)

if self.extend in ('min', 'both'):
i0 += 1
if self.extend in ('max', 'both'):
i1 -= 1

# Ensure at least 3 levels and handle log scale specifically
if i1 - i0 < 3:
i0, i1 = 0, len(lev)

# Handle log scale adjustments if levels are still insufficient
if self.logscale and len(lev) < N:
self.locator = ticker.LogLocator(numticks=N+1)
lev = self.locator.tick_values(self.zmin, self.zmax)
under = np.nonzero(lev < self.zmin)[0]
i0 = under[-1] if len(under) else 0
over = np.nonzero(lev > self.zmax)[0]

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i1 = over[0] + 1 if len(over) else len(lev)

return lev[i0:i1]

def _process_contour_level_args(self, args, z_dtype):
Expand All @@ -1020,7 +1035,7 @@
else:
levels_arg = self.levels
if isinstance(levels_arg, Integral):
self.levels = self._autolev(levels_arg)
self.levels = self._autolev(levels_arg, using_default=self.levels is None)
else:
self.levels = np.asarray(levels_arg, np.float64)
if self.filled and len(self.levels) < 2:
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