|
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 |
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@@ -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(
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@@ -763,9 +756,6 @@ def __init__(self, name, segmentdata, N=256, gamma=1.0):
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763 | 756 | LinearSegmentedColormap.from_list
|
764 | 757 | Static method; factory function for generating a smoothly-varying
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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.
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771 | 761 | self.monochrome = False
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@@ -1185,11 +1175,6 @@ def __call__(self, value, clip=None):
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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.
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|
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