MNT: convert tests and internal usage way from using mpl.cm.get_cmap

Author: tacaswell

lib/matplotlib/cm.py

@@ -269,7 +269,7 @@ def get_cmap(name=None, lut=None):
     if lut is None:
         return _colormaps[name]
     else:
-        return _colormaps[name].resample(lut)
+        return _colormaps[name].resampled(lut)
 
 
 def unregister_cmap(name):
@@ -550,8 +550,8 @@ def set_cmap(self, cmap):
         cmap : `.Colormap` or str or None
         """
         in_init = self.cmap is None
-        cmap = get_cmap(cmap)
-        self.cmap = cmap
+
+        self.cmap = _ensure_cmap(cmap)
         if not in_init:
             self.changed()  # Things are not set up properly yet.
 
@@ -663,3 +663,26 @@ def changed(self):
     *vmin*/*vmax* when a *norm* instance is given (but using a `str` *norm*
     name together with *vmin*/*vmax* is acceptable).""",
 )
+
+
+def _ensure_cmap(cmap):
+    """
+    Ensure that we have a `.Colormap` object.
+
+    Parameters
+    ----------
+    cmap : None, str, Colormap
+
+        - if a `Colormap`, return it
+        - if a string, look it up in mpl.colormaps
+        - if None, look up the default color map in mpl.colormaps
+
+    Returns
+    -------
+    Colormap
+    """
+    if isinstance(cmap, colors.Colormap):
+        return cmap
+    return mpl.colormaps[
+        cmap if cmap is not None else mpl.rcParams['image.cmap']
+    ]

lib/matplotlib/pyplot.py

@@ -2084,7 +2084,7 @@ def set_cmap(cmap):
     matplotlib.cm.register_cmap
     matplotlib.cm.get_cmap
     """
-    cmap = cm.get_cmap(cmap)
+    cmap = colormaps[cmap]
 
     rc('image', cmap=cmap.name)
     im = gci()

lib/matplotlib/streamplot.py

@@ -187,7 +187,7 @@ def streamplot(axes, x, y, u, v, density=1, linewidth=None, color=None,
     if use_multicolor_lines:
         if norm is None:
             norm = mcolors.Normalize(color.min(), color.max())
-        cmap = cm.get_cmap(cmap)
+        cmap = cm._ensure_cmap(cmap)
 
     streamlines = []
     arrows = []

lib/matplotlib/tests/test_artist.py

@@ -5,7 +5,6 @@
 
 import pytest
 
-from matplotlib import cm
 import matplotlib.colors as mcolors
 import matplotlib.pyplot as plt
 import matplotlib.patches as mpatches
@@ -14,6 +13,7 @@
 import matplotlib.transforms as mtransforms
 import matplotlib.collections as mcollections
 import matplotlib.artist as martist
+import matplotlib as mpl
 from matplotlib.testing.decorators import check_figures_equal, image_comparison
 
 
@@ -415,7 +415,7 @@ def test_format_cursor_data_BoundaryNorm():
     # map range -1..1 to 0..256 in 0.01 steps
     fig, ax = plt.subplots()
     fig.suptitle("-1..1 to 0..256 in 0.01")
-    cmap = cm.get_cmap('RdBu_r', 200)
+    cmap = mpl.colormaps['RdBu_r'].resampled(200)
     norm = mcolors.BoundaryNorm(np.linspace(-1, 1, 200), 200)
     img = ax.imshow(X, cmap=cmap, norm=norm)
 
@@ -439,7 +439,7 @@ def test_format_cursor_data_BoundaryNorm():
     # map range -1..1 to 0..256 in 0.01 steps
     fig, ax = plt.subplots()
     fig.suptitle("-1..1 to 0..256 in 0.001")
-    cmap = cm.get_cmap('RdBu_r', 2000)
+    cmap = mpl.colormaps['RdBu_r'].resampled(2000)
     norm = mcolors.BoundaryNorm(np.linspace(-1, 1, 2000), 2000)
     img = ax.imshow(X, cmap=cmap, norm=norm)
 

lib/matplotlib/tests/test_axes.py

@@ -1220,7 +1220,7 @@ def test_pcolormesh_alpha():
     Qy = Y + np.sin(X)
     Z = np.hypot(X, Y) / 5
     Z = (Z - Z.min()) / Z.ptp()
-    vir = plt.get_cmap("viridis", 16)
+    vir = mpl.colormaps["viridis"].resampled(16)
     # make another colormap with varying alpha
     colors = vir(np.arange(16))
     colors[:, 3] = 0.5 + 0.5*np.sin(np.arange(16))
@@ -2250,7 +2250,7 @@ def test_contour_hatching():
     x, y, z = contour_dat()
     fig, ax = plt.subplots()
     ax.contourf(x, y, z, 7, hatches=['/', '\\', '//', '-'],
-                cmap=plt.get_cmap('gray'),
+                cmap=mpl.colormaps['gray'],
                 extend='both', alpha=0.5)
 
 
@@ -2260,7 +2260,7 @@ def test_contour_colorbar():
 
     fig, ax = plt.subplots()
     cs = ax.contourf(x, y, z, levels=np.arange(-1.8, 1.801, 0.2),
-                     cmap=plt.get_cmap('RdBu'),
+                     cmap=mpl.colormaps['RdBu'],
                      vmin=-0.6,
                      vmax=0.6,
                      extend='both')
@@ -2444,7 +2444,7 @@ def test_scatter_edgecolor_RGB(self):
     @check_figures_equal(extensions=["png"])
     def test_scatter_invalid_color(self, fig_test, fig_ref):
         ax = fig_test.subplots()
-        cmap = plt.get_cmap("viridis", 16)
+        cmap = mpl.colormaps["viridis"].resampled(16)
         cmap.set_bad("k", 1)
         # Set a nonuniform size to prevent the last call to `scatter` (plotting
         # the invalid points separately in fig_ref) from using the marker
@@ -2453,15 +2453,15 @@ def test_scatter_invalid_color(self, fig_test, fig_ref):
                    c=[1, np.nan, 2, np.nan], s=[1, 2, 3, 4],
                    cmap=cmap, plotnonfinite=True)
         ax = fig_ref.subplots()
-        cmap = plt.get_cmap("viridis", 16)
+        cmap = mpl.colormaps["viridis"].resampled(16)
         ax.scatter([0, 2], [0, 2], c=[1, 2], s=[1, 3], cmap=cmap)
         ax.scatter([1, 3], [1, 3], s=[2, 4], color="k")
 
     @check_figures_equal(extensions=["png"])
     def test_scatter_no_invalid_color(self, fig_test, fig_ref):
         # With plotnonfinite=False we plot only 2 points.
         ax = fig_test.subplots()
-        cmap = plt.get_cmap("viridis", 16)
+        cmap = mpl.colormaps["viridis"].resampled(16)
         cmap.set_bad("k", 1)
         ax.scatter(range(4), range(4),
                    c=[1, np.nan, 2, np.nan], s=[1, 2, 3, 4],

lib/matplotlib/tests/test_collections.py

@@ -955,7 +955,7 @@ def test_quadmesh_set_array():
 def test_quadmesh_vmin_vmax():
     # test when vmin/vmax on the norm changes, the quadmesh gets updated
     fig, ax = plt.subplots()
-    cmap = mpl.cm.get_cmap('plasma')
+    cmap = mpl.colormaps['plasma']
     norm = mpl.colors.Normalize(vmin=0, vmax=1)
     coll = ax.pcolormesh([[1]], cmap=cmap, norm=norm)
     fig.canvas.draw()

lib/matplotlib/tests/test_colorbar.py

@@ -3,6 +3,7 @@
 
 from matplotlib import cm
 import matplotlib.colors as mcolors
+import matplotlib as mpl
 
 from matplotlib import rc_context
 from matplotlib.testing.decorators import image_comparison
@@ -24,7 +25,7 @@ def _get_cmap_norms():
     colorbar_extension_length.
     """
     # Create a colormap and specify the levels it represents.
-    cmap = cm.get_cmap("RdBu", lut=5)
+    cmap = mpl.colormaps["RdBu"].resampled(5)
     clevs = [-5., -2.5, -.5, .5, 1.5, 3.5]
     # Define norms for the colormaps.
     norms = dict()
@@ -132,8 +133,8 @@ def test_colorbar_extension_inverted_axis(orientation, extend, expected):
     """Test extension color with an inverted axis"""
     data = np.arange(12).reshape(3, 4)
     fig, ax = plt.subplots()
-    cmap = plt.get_cmap("viridis").with_extremes(under=(0, 0, 0, 1),
-                                                 over=(1, 1, 1, 1))
+    cmap = mpl.colormaps["viridis"].with_extremes(under=(0, 0, 0, 1),
+                                                  over=(1, 1, 1, 1))
     im = ax.imshow(data, cmap=cmap)
     cbar = fig.colorbar(im, orientation=orientation, extend=extend)
     if orientation == "horizontal":
@@ -268,7 +269,7 @@ def test_colorbar_single_scatter():
     plt.figure()
     x = y = [0]
     z = [50]
-    cmap = plt.get_cmap('jet', 16)
+    cmap = mpl.colormaps['jet'].resampled(16)
     cs = plt.scatter(x, y, z, c=z, cmap=cmap)
     plt.colorbar(cs)
 
@@ -326,7 +327,7 @@ def test_colorbar_closed_patch():
     ax4 = fig.add_axes([0.05, 0.25, 0.9, 0.1])
     ax5 = fig.add_axes([0.05, 0.05, 0.9, 0.1])
 
-    cmap = cm.get_cmap("RdBu", lut=5)
+    cmap = mpl.colormaps["RdBu"].resampled(5)
 
     im = ax1.pcolormesh(np.linspace(0, 10, 16).reshape((4, 4)), cmap=cmap)
 
@@ -957,7 +958,7 @@ def test_colorbar_extend_drawedges():
         fig.subplots_adjust(left=0.05, bottom=0.05, right=0.95, top=0.95)
 
         for ax, (extend, coloroffset, res) in zip(axs, params):
-            cmap = plt.get_cmap("viridis")
+            cmap = mpl.colormaps["viridis"]
             bounds = np.arange(5)
             nb_colors = len(bounds) + coloroffset
             colors = cmap(np.linspace(100, 255, nb_colors).astype(int))
@@ -980,7 +981,7 @@ def test_colorbar_extend_drawedges():
 
 def test_negative_boundarynorm():
     fig, ax = plt.subplots(figsize=(1, 3))
-    cmap = plt.get_cmap("viridis")
+    cmap = mpl.colormaps["viridis"]
 
     clevs = np.arange(-94, -85)
     norm = BoundaryNorm(clevs, cmap.N)
@@ -1016,7 +1017,7 @@ def test_nonorm():
     fig.subplots_adjust(bottom=0.5)
 
     norm = NoNorm(vmin=min(data), vmax=max(data))
-    cmap = cm.get_cmap("viridis", len(data))
+    cmap = mpl.colormaps["viridis"].resampled(len(data))
     mappable = cm.ScalarMappable(norm=norm, cmap=cmap)
     cbar = fig.colorbar(mappable, cax=ax, orientation="horizontal")
 

lib/matplotlib/tests/test_colors.py

@@ -12,6 +12,7 @@
 
 from matplotlib import cbook, cm, cycler
 import matplotlib
+import matplotlib as mpl
 import matplotlib.colors as mcolors
 import matplotlib.colorbar as mcolorbar
 import matplotlib.pyplot as plt
@@ -29,9 +30,9 @@ def test_create_lookup_table(N, result):
     assert_array_almost_equal(mcolors._create_lookup_table(N, data), result)
 
 
-def test_resample():
+def test_resampled():
     """
-    GitHub issue #6025 pointed to incorrect ListedColormap.resample;
+    GitHub issue #6025 pointed to incorrect ListedColormap.resampled;
     here we test the method for LinearSegmentedColormap as well.
     """
     n = 101
@@ -47,8 +48,8 @@ def test_resample():
         cmap.set_under('r')
         cmap.set_over('g')
         cmap.set_bad('b')
-    lsc3 = lsc.resample(3)
-    lc3 = lc.resample(3)
+    lsc3 = lsc.resampled(3)
+    lc3 = lc.resampled(3)
     expected = np.array([[0.0, 0.2, 1.0, 0.7],
                          [0.5, 0.2, 0.5, 0.7],
                          [1.0, 0.2, 0.0, 0.7]], float)
@@ -127,7 +128,7 @@ def test_colormap_copy():
 
 
 def test_colormap_equals():
-    cmap = plt.get_cmap("plasma")
+    cmap = mpl.colormaps["plasma"]
     cm_copy = cmap.copy()
     # different object id's
     assert cm_copy is not cmap
@@ -155,7 +156,7 @@ def test_colormap_endian():
     mapping of 1.0 when input from a non-native-byteorder
     array.
     """
-    cmap = cm.get_cmap("jet")
+    cmap = mpl.colormaps["jet"]
     # Test under, over, and invalid along with values 0 and 1.
     a = [-0.5, 0, 0.5, 1, 1.5, np.nan]
     for dt in ["f2", "f4", "f8"]:
@@ -170,7 +171,7 @@ def test_colormap_invalid():
     rather than bad. This tests to make sure all invalid values
     (-inf, nan, inf) are mapped respectively to (under, bad, over).
     """
-    cmap = cm.get_cmap("plasma")
+    cmap = mpl.colormaps["plasma"]
     x = np.array([-np.inf, -1, 0, np.nan, .7, 2, np.inf])
 
     expected = np.array([[0.050383, 0.029803, 0.527975, 1.],
@@ -203,7 +204,7 @@ def test_colormap_return_types():
     Make sure that tuples are returned for scalar input and
     that the proper shapes are returned for ndarrays.
     """
-    cmap = cm.get_cmap("plasma")
+    cmap = mpl.colormaps["plasma"]
     # Test return types and shapes
     # scalar input needs to return a tuple of length 4
     assert isinstance(cmap(0.5), tuple)
@@ -318,7 +319,7 @@ def test_BoundaryNorm():
 
     # Testing extend keyword, with interpolation (large cmap)
     bounds = [1, 2, 3]
-    cmap = cm.get_cmap('viridis')
+    cmap = mpl.colormaps['viridis']
     mynorm = mcolors.BoundaryNorm(bounds, cmap.N, extend='both')
     refnorm = mcolors.BoundaryNorm([0] + bounds + [4], cmap.N)
     x = np.random.randn(100) * 10 + 2
@@ -789,7 +790,7 @@ def test_boundarynorm_and_colorbarbase():
 
     # Set the colormap and bounds
     bounds = [-1, 2, 5, 7, 12, 15]
-    cmap = cm.get_cmap('viridis')
+    cmap = mpl.colormaps['viridis']
 
     # Default behavior
     norm = mcolors.BoundaryNorm(bounds, cmap.N)
@@ -1134,13 +1135,13 @@ def test_pandas_iterable(pd):
     assert_array_equal(cm1.colors, cm2.colors)
 
 
-@pytest.mark.parametrize('name', sorted(plt.colormaps()))
+@pytest.mark.parametrize('name', sorted(mpl.colormaps()))
 def test_colormap_reversing(name):
     """
     Check the generated _lut data of a colormap and corresponding reversed
     colormap if they are almost the same.
     """
-    cmap = plt.get_cmap(name)
+    cmap = mpl.colormaps[name]
     cmap_r = cmap.reversed()
     if not cmap_r._isinit:
         cmap._init()
@@ -1307,7 +1308,7 @@ def test_hex_shorthand_notation():
 
 
 def test_repr_png():
-    cmap = plt.get_cmap('viridis')
+    cmap = mpl.colormaps['viridis']
     png = cmap._repr_png_()
     assert len(png) > 0
     img = Image.open(BytesIO(png))
@@ -1320,7 +1321,7 @@ def test_repr_png():
 
 
 def test_repr_html():
-    cmap = plt.get_cmap('viridis')
+    cmap = mpl.colormaps['viridis']
     html = cmap._repr_html_()
     assert len(html) > 0
     png = cmap._repr_png_()
@@ -1331,15 +1332,15 @@ def test_repr_html():
 
 
 def test_get_under_over_bad():
-    cmap = plt.get_cmap('viridis')
+    cmap = mpl.colormaps['viridis']
     assert_array_equal(cmap.get_under(), cmap(-np.inf))
     assert_array_equal(cmap.get_over(), cmap(np.inf))
     assert_array_equal(cmap.get_bad(), cmap(np.nan))
 
 
 @pytest.mark.parametrize('kind', ('over', 'under', 'bad'))
 def test_non_mutable_get_values(kind):
-    cmap = copy.copy(plt.get_cmap('viridis'))
+    cmap = copy.copy(mpl.colormaps['viridis'])
     init_value = getattr(cmap, f'get_{kind}')()
     getattr(cmap, f'set_{kind}')('k')
     black_value = getattr(cmap, f'get_{kind}')()
@@ -1348,7 +1349,7 @@ def test_non_mutable_get_values(kind):
 
 
 def test_colormap_alpha_array():
-    cmap = plt.get_cmap('viridis')
+    cmap = mpl.colormaps['viridis']
     vals = [-1, 0.5, 2]  # under, valid, over
     with pytest.raises(ValueError, match="alpha is array-like but"):
         cmap(vals, alpha=[1, 1, 1, 1])
@@ -1360,7 +1361,7 @@ def test_colormap_alpha_array():
 
 
 def test_colormap_bad_data_with_alpha():
-    cmap = plt.get_cmap('viridis')
+    cmap = mpl.colormaps['viridis']
     c = cmap(np.nan, alpha=0.5)
     assert c == (0, 0, 0, 0)
     c = cmap([0.5, np.nan], alpha=0.5)