Deprecate ListedColormap(..., N=...) parameter

Truncating or repeating the given colors to a specific value of N
is not within the scope of colormaps. Instead, users should
create an appropriate color list themselves and feed that to
ListedColormap.

Also the current behavior can be surprising: It may well be that
a given N was intended to truncate, but depending on the list, it
could repeat. Repeated colors in a colormap are dangerous / often
not intentended because they create an ambiguity in the color ->
value mapping.

Author: timhoffm

lib/matplotlib/cbook.py

@@ -1739,6 +1739,26 @@ def sanitize_sequence(data):
             else data)
 
 
+def _resize_sequence(seq, N):
+    """
+    Trim the given sequence to exactly N elements.
+
+    If there are more elements in the sequence, cut it.
+    If there are less elements in the sequence, repeat them.
+
+    Implementation detail: We maintain type stability for the output for
+    N <= len(seq). We simply return a list for N > len(seq); this was good
+    enough for the present use cases but is not a fixed design decision.
+    """
+    num_elements = len(seq)
+    if N == num_elements:
+        return seq
+    elif N < num_elements:
+        return seq[:N]
+    else:
+        return list(itertools.islice(itertools.cycle(seq), N))
+
+
 def normalize_kwargs(kw, alias_mapping=None):
     """
     Helper function to normalize kwarg inputs.

lib/matplotlib/cbook.pyi

@@ -14,6 +14,7 @@ from typing import (
     Generic,
     IO,
     Literal,
+    Sequence,
     TypeVar,
     overload,
 )
@@ -143,6 +144,7 @@ STEP_LOOKUP_MAP: dict[str, Callable]
 def index_of(y: float | ArrayLike) -> tuple[np.ndarray, np.ndarray]: ...
 def safe_first_element(obj: Collection[_T]) -> _T: ...
 def sanitize_sequence(data): ...
+def _resize_sequence(seq: Sequence, N: int) -> Sequence: ...
 def normalize_kwargs(
     kw: dict[str, Any],
     alias_mapping: dict[str, list[str]] | type[Artist] | Artist | None = ...,

lib/matplotlib/colors.py

@@ -1195,6 +1195,12 @@ def __init__(self, colors, name='from_list', N=None):
             self.colors = colors
             N = len(colors)
         else:
+            _api.warn_deprecated(
+                "3.11",
+                message="Passing 'N' to ListedColormap is deprecated since %(since)s "
+                        "and will be removed in %(removal)s. Please process the list "
+                        "of passed colors yourself if needed."
+            )
             if isinstance(colors, str):
                 self.colors = [colors] * N
             elif np.iterable(colors):
@@ -1259,7 +1265,7 @@ def reversed(self, name=None):
             name = self.name + "_r"
 
         colors_r = list(reversed(self.colors))
-        new_cmap = ListedColormap(colors_r, name=name, N=self.N)
+        new_cmap = ListedColormap(colors_r, name=name)
         # Reverse the over/under values too
         new_cmap._rgba_over = self._rgba_under
         new_cmap._rgba_under = self._rgba_over
@@ -1943,14 +1949,16 @@ def __getitem__(self, item):
             if origin_1_as_int > self.M-1:
                 origin_1_as_int = self.M-1
             one_d_lut = self._lut[:, origin_1_as_int]
-            new_cmap = ListedColormap(one_d_lut, name=f'{self.name}_0', N=self.N)
+            assert len(one_d_lut) == self.N  # temporary
+            new_cmap = ListedColormap(one_d_lut, name=f'{self.name}_0')
 
         elif item == 1:
             origin_0_as_int = int(self._origin[0]*self.N)
             if origin_0_as_int > self.N-1:
                 origin_0_as_int = self.N-1
             one_d_lut = self._lut[origin_0_as_int, :]
-            new_cmap = ListedColormap(one_d_lut, name=f'{self.name}_1', N=self.M)
+            assert len(one_d_lut) == self.M  # temporary
+            new_cmap = ListedColormap(one_d_lut, name=f'{self.name}_1')
         else:
             raise KeyError(f"only 0 or 1 are"
                            f" valid keys for BivarColormap, not {item!r}")

lib/matplotlib/contour.py

@@ -183,10 +183,14 @@ def clabel(self, levels=None, *,
             self.labelMappable = self
             self.labelCValueList = np.take(self.cvalues, self.labelIndiceList)
         else:
-            cmap = mcolors.ListedColormap(colors, N=len(self.labelLevelList))
-            self.labelCValueList = list(range(len(self.labelLevelList)))
-            self.labelMappable = cm.ScalarMappable(cmap=cmap,
-                                                   norm=mcolors.NoNorm())
+            # handling of explicit colors for labels:
+            # make labelCValueList contain integers [0, 1, 2, ...] and a cmap
+            # so that cmap(i) == colors[i]
+            num_levels = len(self.labelLevelList)
+            colors = cbook._resize_sequence(mcolors.to_rgba_array(colors), num_levels)
+            self.labelMappable = cm.ScalarMappable(
+                cmap=mcolors.ListedColormap(colors), norm=mcolors.NoNorm())
+            self.labelCValueList = list(range(num_levels))
 
         self.labelXYs = []
 
@@ -738,7 +742,8 @@ def __init__(self, ax, *args,
                 if self._extend_min:
                     i0 = 1
 
-            cmap = mcolors.ListedColormap(color_sequence[i0:None], N=ncolors)
+            cmap = mcolors.ListedColormap(
+                cbook._resize_sequence(color_sequence[i0:], ncolors))
 
             if use_set_under_over:
                 if self._extend_min:

lib/matplotlib/tests/test_cbook.py

@@ -463,6 +463,23 @@ def test_sanitize_sequence():
     assert k == cbook.sanitize_sequence(k)
 
 
+def test_resize_sequence():
+    a_list = [1, 2, 3]
+    arr = np.array([1, 2, 3])
+
+    # already same length: passthrough
+    assert cbook._resize_sequence(a_list, 3) is a_list
+    assert cbook._resize_sequence(arr, 3) is arr
+
+    # shortening
+    assert cbook._resize_sequence(a_list, 2) == [1, 2]
+    assert_array_equal(cbook._resize_sequence(arr, 2), [1, 2])
+
+    # extending
+    assert cbook._resize_sequence(a_list, 5) == [1, 2, 3, 1, 2]
+    assert_array_equal(cbook._resize_sequence(arr, 5), [1, 2, 3, 1, 2])
+
+
 fail_mapping: tuple[tuple[dict, dict], ...] = (
     ({'a': 1, 'b': 2}, {'alias_mapping': {'a': ['b']}}),
     ({'a': 1, 'b': 2}, {'alias_mapping': {'a': ['a', 'b']}}),

lib/matplotlib/tests/test_colors.py

@@ -1165,8 +1165,8 @@ def test_pandas_iterable(pd):
     # a single color
     lst = ['red', 'blue', 'green']
     s = pd.Series(lst)
-    cm1 = mcolors.ListedColormap(lst, N=5)
-    cm2 = mcolors.ListedColormap(s, N=5)
+    cm1 = mcolors.ListedColormap(lst)
+    cm2 = mcolors.ListedColormap(s)
     assert_array_equal(cm1.colors, cm2.colors)