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Fix specifying number of levels with log contour #27576

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Merged
merged 8 commits into from
Apr 30, 2025
Merged

Fix specifying number of levels with log contour #27576

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12ce07f
Fix specifying number of levels with log contour
dstansby Dec 28, 2023
d307114
Fix log contours when using default levels
dstansby Dec 28, 2023
d6a445e
Update test
dstansby Jan 10, 2024
917bc62
PEP8 fix
dstansby Mar 24, 2025
0eadaf0
Clean up contour level logic
dstansby Apr 8, 2025
b4fc4d3
Factor out logic to set default locator
dstansby Apr 9, 2025
47b2ca0
Rename locator setting method
dstansby Apr 13, 2025
8c0775e
Move parameter description
dstansby Apr 30, 2025
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4 changes: 4 additions & 0 deletions doc/users/next_whats_new/log_contour_levels.rst
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Original file line number Diff line number Diff line change
@@ -0,0 +1,4 @@
Maximum levels on log-scaled contour plots are now respected
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
When plotting contours with a log norm, passing an integer value to the ``levels``
argument to cap the maximum number of contour levels now works as intended.
52 changes: 31 additions & 21 deletions lib/matplotlib/contour.py
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Original file line number Diff line number Diff line change
Expand Up @@ -964,12 +964,29 @@ def changed(self):
label.set_color(self.labelMappable.to_rgba(cv))
super().changed()

def _autolev(self, N):
def _ensure_locator_exists(self, N):
"""
Select contour levels to span the data.
Set a locator on this ContourSet if it's not already set.

The target number of levels, *N*, is used only when the
scale is not log and default locator is used.
Parameters
----------
N : int or None
If *N* is an int, it is used as the target number of levels.
Otherwise when *N* is None, a reasonable default is chosen;
for logscales the LogLocator chooses, N=7 is the default
otherwise.
"""
if self.locator is None:
if self.logscale:
self.locator = ticker.LogLocator(numticks=N)
else:
if N is None:
N = 7 # Hard coded default
self.locator = ticker.MaxNLocator(N + 1, min_n_ticks=1)

def _autolev(self):
"""
Select contour levels to span the data.

We need two more levels for filled contours than for
line contours, because for the latter we need to specify
Expand All @@ -978,12 +995,6 @@ def _autolev(self, N):
one contour line, but two filled regions, and therefore
three levels to provide boundaries for both regions.
"""
if self.locator is None:
if self.logscale:
self.locator = ticker.LogLocator()
else:
self.locator = ticker.MaxNLocator(N + 1, min_n_ticks=1)

lev = self.locator.tick_values(self.zmin, self.zmax)

try:
Expand Down Expand Up @@ -1011,22 +1022,21 @@ def _process_contour_level_args(self, args, z_dtype):
"""
Determine the contour levels and store in self.levels.
"""
if self.levels is None:
levels_arg = self.levels
if levels_arg is None:
if args:
# Set if levels manually provided
levels_arg = args[0]
Comment on lines 1027 to 1029
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@timhoffm timhoffm Apr 9, 2025 •
edited
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This could still be made clearer / the current code is still convoluted (but possibly better as a followup PR to not make too many changes and complicate review)

args is not the original args but stripped from leading [X, Y], Z. Effectively it can only be empty or contain a single element that contains levels passed positionally (which is supported, but a bit cumbersome to write out as a signature because the optional [X, Y] require to absorb all positional parameters in *args and we therefore have to reunite a possible positional level from args with the possible kwarg level.

The current implementation also has the surprising side effect that you can do contour(Z, levels1, levels=levels2) and the positional levels1 is sliently ignored.

The only use of args here is to pass on a possible positional level. We can push the logic out of the function and unite the positional and kwarg paths of levels in the caller _contour_args - where it belongs logically.

I think eventually we should also make levels kw-only. contour(Z, 5) or contour(X, Y, Z, [-1, 0, 1]) are not very readable anyway.

elif np.issubdtype(z_dtype, bool):
if self.filled:
levels_arg = [0, .5, 1]
else:
levels_arg = [.5]
else:
levels_arg = 7 # Default, hard-wired.
else:
levels_arg = self.levels
if isinstance(levels_arg, Integral):
self.levels = self._autolev(levels_arg)
# Set default values for bool data types
levels_arg = [0, .5, 1] if self.filled else [.5]

if isinstance(levels_arg, Integral) or levels_arg is None:
self._ensure_locator_exists(levels_arg)
self.levels = self._autolev()
else:
self.levels = np.asarray(levels_arg, np.float64)

if self.filled and len(self.levels) < 2:
raise ValueError("Filled contours require at least 2 levels.")
if len(self.levels) > 1 and np.min(np.diff(self.levels)) <= 0.0:
Expand Down
15 changes: 15 additions & 0 deletions lib/matplotlib/tests/test_contour.py
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Original file line number Diff line number Diff line change
Expand Up @@ -214,6 +214,21 @@ def test_log_locator_levels():
assert_array_almost_equal(cb.ax.get_yticks(), c.levels)


@pytest.mark.parametrize("n_levels", [2, 3, 4, 5, 6])
def test_lognorm_levels(n_levels):
x, y = np.mgrid[1:10:0.1, 1:10:0.1]
data = np.abs(np.sin(x)*np.exp(y))

fig, ax = plt.subplots()
im = ax.contour(x, y, data, norm=LogNorm(), levels=n_levels)
fig.colorbar(im, ax=ax)

levels = im.levels
visible_levels = levels[(levels <= data.max()) & (levels >= data.min())]
# levels parameter promises "no more than n+1 "nice" contour levels "
assert len(visible_levels) <= n_levels + 1


@image_comparison(['contour_datetime_axis.png'], style='mpl20')
def test_contour_datetime_axis():
fig = plt.figure()
Expand Down
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