|
78 | 78 |
|
79 | 79 | import matplotlib as mpl |
80 | 80 | import numpy as np |
81 | | -from matplotlib import cbook, docstring, scale |
| 81 | +from matplotlib import cbook, scale |
82 | 82 | from ._color_data import BASE_COLORS, TABLEAU_COLORS, CSS4_COLORS, XKCD_COLORS |
83 | 83 |
|
84 | 84 |
|
@@ -479,13 +479,6 @@ def _create_lookup_table(N, data, gamma=1.0): |
479 | 479 | return np.clip(lut, 0.0, 1.0) |
480 | 480 |
|
481 | 481 |
|
482 | | -@cbook.deprecated("3.2", |
483 | | - addendum='This is not considered public API any longer.') |
484 | | -@docstring.copy(_create_lookup_table) |
485 | | -def makeMappingArray(N, data, gamma=1.0): |
486 | | - return _create_lookup_table(N, data, gamma) |
487 | | - |
488 | | - |
489 | 482 | def _warn_if_global_cmap_modified(cmap): |
490 | 483 | if getattr(cmap, '_global', False): |
491 | 484 | cbook.warn_deprecated( |
@@ -763,9 +756,6 @@ def __init__(self, name, segmentdata, N=256, gamma=1.0): |
763 | 756 | LinearSegmentedColormap.from_list |
764 | 757 | Static method; factory function for generating a smoothly-varying |
765 | 758 | LinearSegmentedColormap. |
766 | | -
|
767 | | - makeMappingArray |
768 | | - For information about making a mapping array. |
769 | 759 | """ |
770 | 760 | # True only if all colors in map are identical; needed for contouring. |
771 | 761 | self.monochrome = False |
@@ -1185,11 +1175,6 @@ def __call__(self, value, clip=None): |
1185 | 1175 | return result |
1186 | 1176 |
|
1187 | 1177 |
|
1188 | | -@cbook.deprecation.deprecated('3.2', alternative='TwoSlopeNorm') |
1189 | | -class DivergingNorm(TwoSlopeNorm): |
1190 | | - ... |
1191 | | - |
1192 | | - |
1193 | 1178 | def _make_norm_from_scale(scale_cls, base_norm_cls=None, *, init=None): |
1194 | 1179 | """ |
1195 | 1180 | Decorator for building a `.Normalize` subclass from a `.Scale` subclass. |
|
0 commit comments