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lib/matplotlib
- colorizer.pyi
- colorizer.py
- colors.pyi
- colors.py
- tests
  - baseline_images/test_colors
    - test_norm_protocol.png
  - test_colors.py

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`‎lib/matplotlib/colorizer.py‎`

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+1-1Lines changed: 1 addition & 1 deletion

Original file line number	Diff line number	Diff line change
`@@ -90,7 +90,7 @@ def norm(self):`
`90`	`90`
`91`	`91`	`@norm.setter`
`92`	`92`	`def norm(self, norm):`
`93`		`- _api.check_isinstance((colors.Normalize, str, None), norm=norm)`
	`93`	`+ _api.check_isinstance((colors.Norm, str, None), norm=norm)`
`94`	`94`	`if norm is None:`
`95`	`95`	`norm = colors.Normalize()`
`96`	`96`	`elif isinstance(norm, str):`

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`‎lib/matplotlib/colorizer.pyi‎`

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+7-7Lines changed: 7 additions & 7 deletions

Original file line number	Diff line number	Diff line change
`@@ -10,12 +10,12 @@ class Colorizer:`
`10`	`10`	`def __init__(`
`11`	`11`	`self,`
`12`	`12`	`cmap: str \| colors.Colormap \| None = ...,`
`13`		`- norm: str \| colors.Normalize \| None = ...,`
	`13`	`+ norm: str \| colors.Norm \| None = ...,`
`14`	`14`	`) -> None: ...`
`15`	`15`	`@property`
`16`		`- def norm(self) -> colors.Normalize: ...`
	`16`	`+ def norm(self) -> colors.Norm: ...`
`17`	`17`	`@norm.setter`
`18`		`- def norm(self, norm: colors.Normalize \| str \| None) -> None: ...`
	`18`	`+ def norm(self, norm: colors.Norm \| str \| None) -> None: ...`
`19`	`19`	`def to_rgba(`
`20`	`20`	`self,`
`21`	`21`	`x: np.ndarray,`
`@@ -63,18 +63,18 @@ class _ColorizerInterface:`
`63`	`63`	`def get_cmap(self) -> colors.Colormap: ...`
`64`	`64`	`def set_cmap(self, cmap: str \| colors.Colormap) -> None: ...`
`65`	`65`	`@property`
`66`		`- def norm(self) -> colors.Normalize: ...`
	`66`	`+ def norm(self) -> colors.Norm: ...`
`67`	`67`	`@norm.setter`
`68`		`- def norm(self, norm: colors.Normalize \| str \| None) -> None: ...`
`69`		`- def set_norm(self, norm: colors.Normalize \| str \| None) -> None: ...`
	`68`	`+ def norm(self, norm: colors.Norm \| str \| None) -> None: ...`
	`69`	`+ def set_norm(self, norm: colors.Norm \| str \| None) -> None: ...`
`70`	`70`	`def autoscale(self) -> None: ...`
`71`	`71`	`def autoscale_None(self) -> None: ...`
`72`	`72`
`73`	`73`
`74`	`74`	`class _ScalarMappable(_ColorizerInterface):`
`75`	`75`	`def __init__(`
`76`	`76`	`self,`
`77`		`- norm: colors.Normalize \| None = ...,`
	`77`	`+ norm: colors.Norm \| None = ...,`
`78`	`78`	`cmap: str \| colors.Colormap \| None = ...,`
`79`	`79`	`*,`
`80`	`80`	`colorizer: Colorizer \| None = ...,`

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`‎lib/matplotlib/colors.py‎`

Copy file name to clipboardExpand all lines: lib/matplotlib/colors.py

+79Lines changed: 79 additions & 0 deletions

Original file line number	Diff line number	Diff line change
`@@ -41,6 +41,7 @@`
`41`	`41`
`42`	`42`	`import base64`
`43`	`43`	`from collections.abc import Sequence, Mapping`
	`44`	`+from typing import Protocol, runtime_checkable`
`44`	`45`	`import functools`
`45`	`46`	`import importlib`
`46`	`47`	`import inspect`
`@@ -2257,6 +2258,84 @@ def _init(self):`
`2257`	`2258`	`self._isinit = True`
`2258`	`2259`
`2259`	`2260`
	`2261`	`+@runtime_checkable`
	`2262`	`+class Norm(Protocol):`
	`2263`	`+`
	`2264`	`+ @property`
	`2265`	`+ def vmin(self):`
	`2266`	`+ """Lower limit of the input data interval; maps to 0."""`
	`2267`	`+ ...`
	`2268`	`+`
	`2269`	`+`
	`2270`	`+ @property`
	`2271`	`+ def vmax(self):`
	`2272`	`+ """Upper limit of the input data interval; maps to 1."""`
	`2273`	`+ ...`
	`2274`	`+`
	`2275`	`+ @property`
	`2276`	`+ def clip(self):`
	`2277`	`+ """`
	`2278`	+ Determines the behavior for mapping values outside the range ``[vmin, vmax]``.
	`2279`	`+`
	`2280`	+ See the clip parameter in `.Normalize`.
	`2281`	`+ """`
	`2282`	`+ ...`
	`2283`	`+`
	`2284`	`+ def _changed(self):`
	`2285`	`+ """`
	`2286`	`+ Call this whenever the norm is changed to notify all the`
	`2287`	`+ callback listeners to the 'changed' signal.`
	`2288`	`+ """`
	`2289`	`+ ...`
	`2290`	`+`
	`2291`	`+`
	`2292`	`+ def __call__(self, value, clip=None):`
	`2293`	`+ """`
	`2294`	`+ Normalize the data and return the normalized data.`
	`2295`	`+`
	`2296`	`+ Parameters`
	`2297`	`+ ----------`
	`2298`	`+ value`
	`2299`	`+ Data to normalize.`
	`2300`	`+ clip : bool, optional`
	`2301`	+ See the description of the parameter clip in `.Normalize`.
	`2302`	`+`
	`2303`	+ If ``None``, defaults to ``self.clip`` (which defaults to
	`2304`	+ ``False``).
	`2305`	`+`
	`2306`	`+ Notes`
	`2307`	`+ -----`
	`2308`	+ If not already initialized, ``self.vmin`` and ``self.vmax`` are
	`2309`	+ initialized using ``self.autoscale_None(value)``.
	`2310`	`+ """`
	`2311`	`+ ...`
	`2312`	`+`
	`2313`	`+ def inverse(self, value):`
	`2314`	`+ """`
	`2315`	`+ Maps the normalized value (i.e., index in the colormap) back to image`
	`2316`	`+ data value.`
	`2317`	`+`
	`2318`	`+ Parameters`
	`2319`	`+ ----------`
	`2320`	`+ value`
	`2321`	`+ Normalized value.`
	`2322`	`+ """`
	`2323`	`+ ...`
	`2324`	`+`
	`2325`	`+`
	`2326`	`+ def autoscale(self, A):`
	`2327`	`+ """Set vmin, vmax to min, max of A."""`
	`2328`	`+ ...`
	`2329`	`+`
	`2330`	`+ def autoscale_None(self, A):`
	`2331`	`+ """If vmin or vmax are not set, use the min/max of A to set them."""`
	`2332`	`+ ...`
	`2333`	`+`
	`2334`	`+ def scaled(self):`
	`2335`	`+ """Return whether vmin and vmax are both set."""`
	`2336`	`+ ...`
	`2337`	`+`
	`2338`	`+`
`2260`	`2339`	`class Normalize:`
`2261`	`2340`	`"""`
`2262`	`2341`	`A class which, when called, maps values within the interval`

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`‎lib/matplotlib/colors.pyi‎`

Copy file name to clipboardExpand all lines: lib/matplotlib/colors.pyi

+26-1Lines changed: 26 additions & 1 deletion

Original file line number	Diff line number	Diff line change
`@@ -2,7 +2,7 @@ from collections.abc import Callable, Iterable, Iterator, Mapping, Sequence`
`2`	`2`	`from matplotlib import cbook, scale`
`3`	`3`	`import re`
`4`	`4`
`5`		`-from typing import Any, Literal, overload`
	`5`	`+from typing import Any, Literal, overload, Protocol, runtime_checkable`
`6`	`6`	`from .typing import ColorType`
`7`	`7`
`8`	`8`	`import numpy as np`
`@@ -249,6 +249,31 @@ class BivarColormapFromImage(BivarColormap):`
`249`	`249`	`origin: Sequence[float] = ..., name: str = ...`
`250`	`250`	`) -> None: ...`
`251`	`251`
	`252`	`+@runtime_checkable`
	`253`	`+class Norm(Protocol):`
	`254`	`+ callbacks: cbook.CallbackRegistry`
	`255`	`+ @property`
	`256`	`+ def vmin(self) -> float \| None: ...`
	`257`	`+ @property`
	`258`	`+ def vmax(self) -> float \| None: ...`
	`259`	`+ @property`
	`260`	`+ def clip(self) -> bool: ...`
	`261`	`+ @overload`
	`262`	`+ def __call__(self, value: float, clip: bool \| None = ...) -> float: ...`
	`263`	`+ @overload`
	`264`	`+ def __call__(self, value: np.ndarray, clip: bool \| None = ...) -> np.ma.MaskedArray: ...`
	`265`	`+ @overload`
	`266`	`+ def __call__(self, value: ArrayLike, clip: bool \| None = ...) -> ArrayLike: ...`
	`267`	`+ @overload`
	`268`	`+ def inverse(self, value: float) -> float: ...`
	`269`	`+ @overload`
	`270`	`+ def inverse(self, value: np.ndarray) -> np.ma.MaskedArray: ...`
	`271`	`+ @overload`
	`272`	`+ def inverse(self, value: ArrayLike) -> ArrayLike: ...`
	`273`	`+ def autoscale(self, A: ArrayLike) -> None: ...`
	`274`	`+ def autoscale_None(self, A: ArrayLike) -> None: ...`
	`275`	`+ def scaled(self) -> bool: ...`
	`276`	`+`
`252`	`277`	`class Normalize:`
`253`	`278`	`callbacks: cbook.CallbackRegistry`
`254`	`279`	`def __init__(`

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`‎lib/matplotlib/tests/baseline_images/test_colors/test_norm_protocol.png‎`

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`‎lib/matplotlib/tests/test_colors.py‎`

Copy file name to clipboardExpand all lines: lib/matplotlib/tests/test_colors.py

+51-1Lines changed: 51 additions & 1 deletion

Original file line number	Diff line number	Diff line change
`@@ -19,7 +19,8 @@`
`19`	`19`	`import matplotlib.pyplot as plt`
`20`	`20`	`import matplotlib.scale as mscale`
`21`	`21`	`from matplotlib.rcsetup import cycler`
`22`		`-from matplotlib.testing.decorators import image_comparison, check_figures_equal`
	`22`	`+from matplotlib.testing.decorators import (image_comparison, check_figures_equal,`
	`23`	`+ remove_ticks_and_titles)`
`23`	`24`	`from matplotlib.colors import is_color_like, to_rgba_array, ListedColormap`
`24`	`25`
`25`	`26`
`@@ -1829,3 +1830,52 @@ def test_LinearSegmentedColormap_from_list_value_color_tuple():`
`1829`	`1830`	`cmap([value for value, _ in value_color_tuples]),`
`1830`	`1831`	`to_rgba_array([color for _, color in value_color_tuples]),`
`1831`	`1832`	`)`
	`1833`	`+`
	`1834`	`+`
	`1835`	`+@image_comparison(['test_norm_protocol.png'])`
	`1836`	`+def test_norm_protocol():`
	`1837`	`+ class CustomHalfNorm:`
	`1838`	`+ def __init__(self):`
	`1839`	`+ self.callbacks = mpl.cbook.CallbackRegistry(signals=["changed"])`
	`1840`	`+`
	`1841`	`+ @property`
	`1842`	`+ def vmin(self):`
	`1843`	`+ return 0`
	`1844`	`+`
	`1845`	`+ @property`
	`1846`	`+ def vmax(self):`
	`1847`	`+ return 1`
	`1848`	`+`
	`1849`	`+ @property`
	`1850`	`+ def clip(self):`
	`1851`	`+ return False`
	`1852`	`+`
	`1853`	`+ def _changed(self):`
	`1854`	`+ self.callbacks.process('changed')`
	`1855`	`+`
	`1856`	`+ def __call__(self, value, clip=None):`
	`1857`	`+ return value/2`
	`1858`	`+`
	`1859`	`+ def inverse(self, value):`
	`1860`	`+ return value`
	`1861`	`+`
	`1862`	`+`
	`1863`	`+ def autoscale(self, A):`
	`1864`	`+ pass`
	`1865`	`+`
	`1866`	`+ def autoscale_None(self, A):`
	`1867`	`+ pass`
	`1868`	`+`
	`1869`	`+ def scaled(self):`
	`1870`	`+ return True`
	`1871`	`+`
	`1872`	`+ fig, axes = plt.subplots(2,2)`
	`1873`	`+`
	`1874`	`+ r = np.linspace(-1, 3, 16*16).reshape((16,16))`
	`1875`	`+ norm = CustomHalfNorm()`
	`1876`	`+ colorizer = mpl.colorizer.Colorizer(cmap='viridis', norm=norm)`
	`1877`	`+ c = axes[0,0].imshow(r, colorizer=colorizer)`
	`1878`	`+ axes[0,1].pcolor(r, colorizer=colorizer)`
	`1879`	`+ axes[1,0].contour(r, colorizer=colorizer)`
	`1880`	`+ axes[1,1].contourf(r, colorizer=colorizer)`
	`1881`	`+ remove_ticks_and_titles(fig)`

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