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set_pickradius(pr)[source]
Set the pick radius used for containment tests. Parameters
prfloat
Pick radius, in points. | matplotlib.collections_api#matplotlib.collections.TriMesh.set_pickradius |
set_rasterized(rasterized)[source]
Force rasterized (bitmap) drawing for vector graphics output. Rasterized drawing is not supported by all artists. If you try to enable this on an artist that does not support it, the command has no effect and a warning will be issued. This setting is ignored for pixel-based output. ... | matplotlib.collections_api#matplotlib.collections.TriMesh.set_rasterized |
set_sketch_params(scale=None, length=None, randomness=None)[source]
Set the sketch parameters. Parameters
scalefloat, optional
The amplitude of the wiggle perpendicular to the source line, in pixels. If scale is None, or not provided, no sketch filter will be provided.
lengthfloat, optional
The length of th... | matplotlib.collections_api#matplotlib.collections.TriMesh.set_sketch_params |
set_snap(snap)[source]
Set the snapping behavior. Snapping aligns positions with the pixel grid, which results in clearer images. For example, if a black line of 1px width was defined at a position in between two pixels, the resulting image would contain the interpolated value of that line in the pixel grid, which wo... | matplotlib.collections_api#matplotlib.collections.TriMesh.set_snap |
set_transform(t)[source]
Set the artist transform. Parameters
tTransform | matplotlib.collections_api#matplotlib.collections.TriMesh.set_transform |
set_url(url)[source]
Set the url for the artist. Parameters
urlstr | matplotlib.collections_api#matplotlib.collections.TriMesh.set_url |
set_urls(urls)[source]
Parameters
urlslist of str or None
Notes URLs are currently only implemented by the SVG backend. They are ignored by all other backends. | matplotlib.collections_api#matplotlib.collections.TriMesh.set_urls |
set_visible(b)[source]
Set the artist's visibility. Parameters
bbool | matplotlib.collections_api#matplotlib.collections.TriMesh.set_visible |
set_zorder(level)[source]
Set the zorder for the artist. Artists with lower zorder values are drawn first. Parameters
levelfloat | matplotlib.collections_api#matplotlib.collections.TriMesh.set_zorder |
to_rgba(x, alpha=None, bytes=False, norm=True)[source]
Return a normalized rgba array corresponding to x. In the normal case, x is a 1D or 2D sequence of scalars, and the corresponding ndarray of rgba values will be returned, based on the norm and colormap set for this ScalarMappable. There is one special case, for h... | matplotlib.collections_api#matplotlib.collections.TriMesh.to_rgba |
update(props)[source]
Update this artist's properties from the dict props. Parameters
propsdict | matplotlib.collections_api#matplotlib.collections.TriMesh.update |
update_from(other)[source]
Copy properties from other to self. | matplotlib.collections_api#matplotlib.collections.TriMesh.update_from |
update_scalarmappable()[source]
Update colors from the scalar mappable array, if any. Assign colors to edges and faces based on the array and/or colors that were directly set, as appropriate. | matplotlib.collections_api#matplotlib.collections.TriMesh.update_scalarmappable |
zorder=0 | matplotlib.collections_api#matplotlib.collections.TriMesh.zorder |
matplotlib.colorbar Colorbars are a visualization of the mapping from scalar values to colors. In Matplotlib they are drawn into a dedicated Axes. Note Colorbars are typically created through Figure.colorbar or its pyplot wrapper pyplot.colorbar, which internally use Colorbar together with make_axes_gridspec (for Grid... | matplotlib.colorbar_api |
classmatplotlib.colorbar.Colorbar(ax, mappable=None, *, cmap=None, norm=None, alpha=None, values=None, boundaries=None, orientation='vertical', ticklocation='auto', extend=None, spacing='uniform', ticks=None, format=None, drawedges=False, filled=True, extendfrac=None, extendrect=False, label='')[source]
Bases: object... | matplotlib.colorbar_api#matplotlib.colorbar.Colorbar |
add_lines(*args, **kwargs)[source]
Draw lines on the colorbar. The lines are appended to the list lines. Parameters
levelsarray-like
The positions of the lines.
colorscolor or list of colors
Either a single color applying to all lines or one color value for each line.
linewidthsfloat or array-like
Eithe... | matplotlib.colorbar_api#matplotlib.colorbar.Colorbar.add_lines |
drag_pan(button, key, x, y)[source] | matplotlib.colorbar_api#matplotlib.colorbar.Colorbar.drag_pan |
draw_all()[source]
Calculate any free parameters based on the current cmap and norm, and do all the drawing. | matplotlib.colorbar_api#matplotlib.colorbar.Colorbar.draw_all |
get_ticks(minor=False)[source]
Return the ticks as a list of locations. Parameters
minorboolean, default: False
if True return the minor ticks. | matplotlib.colorbar_api#matplotlib.colorbar.Colorbar.get_ticks |
minorticks_off()[source]
Turn the minor ticks of the colorbar off. | matplotlib.colorbar_api#matplotlib.colorbar.Colorbar.minorticks_off |
minorticks_on()[source]
Turn on colorbar minor ticks. | matplotlib.colorbar_api#matplotlib.colorbar.Colorbar.minorticks_on |
n_rasterize=50 | matplotlib.colorbar_api#matplotlib.colorbar.Colorbar.n_rasterize |
remove()[source]
Remove this colorbar from the figure. If the colorbar was created with use_gridspec=True the previous gridspec is restored. | matplotlib.colorbar_api#matplotlib.colorbar.Colorbar.remove |
set_alpha(alpha)[source]
Set the transparency between 0 (transparent) and 1 (opaque). If an array is provided, alpha will be set to None to use the transparency values associated with the colormap. | matplotlib.colorbar_api#matplotlib.colorbar.Colorbar.set_alpha |
set_label(label, *, loc=None, **kwargs)[source]
Add a label to the long axis of the colorbar. Parameters
labelstr
The label text.
locstr, optional
The location of the label. For horizontal orientation one of {'left', 'center', 'right'} For vertical orientation one of {'bottom', 'center', 'top'} Defaults t... | matplotlib.colorbar_api#matplotlib.colorbar.Colorbar.set_label |
set_ticklabels(ticklabels, update_ticks=<deprecated parameter>, *, minor=False, **kwargs)[source]
Set tick labels. Discouraged The use of this method is discouraged, because of the dependency on tick positions. In most cases, you'll want to use set_ticks(positions, labels=labels) instead. If you are using this metho... | matplotlib.colorbar_api#matplotlib.colorbar.Colorbar.set_ticklabels |
set_ticks(ticks, update_ticks=<deprecated parameter>, labels=None, *, minor=False, **kwargs)[source]
Set tick locations. Parameters
tickslist of floats
List of tick locations.
labelslist of str, optional
List of tick labels. If not set, the labels show the data value.
minorbool, default: False
If False,... | matplotlib.colorbar_api#matplotlib.colorbar.Colorbar.set_ticks |
update_normal(mappable)[source]
Update solid patches, lines, etc. This is meant to be called when the norm of the image or contour plot to which this colorbar belongs changes. If the norm on the mappable is different than before, this resets the locator and formatter for the axis, so if these have been customized, th... | matplotlib.colorbar_api#matplotlib.colorbar.Colorbar.update_normal |
update_ticks()[source]
Setup the ticks and ticklabels. This should not be needed by users. | matplotlib.colorbar_api#matplotlib.colorbar.Colorbar.update_ticks |
matplotlib.colorbar.colorbar_factory(cax, mappable, **kwargs)[source]
[Deprecated] Create a colorbar on the given axes for the given mappable. Note This is a low-level function to turn an existing axes into a colorbar axes. Typically, you'll want to use colorbar instead, which automatically handles creation and plac... | matplotlib.colorbar_api#matplotlib.colorbar.colorbar_factory |
matplotlib.colorbar.ColorbarBase[source]
alias of matplotlib.colorbar.Colorbar | matplotlib.colorbar_api#matplotlib.colorbar.ColorbarBase |
classmatplotlib.colorbar.ColorbarPatch(ax, mappable=None, *, cmap=None, norm=None, alpha=None, values=None, boundaries=None, orientation='vertical', ticklocation='auto', extend=None, spacing='uniform', ticks=None, format=None, drawedges=False, filled=True, extendfrac=None, extendrect=False, label='')[source]
Bases: m... | matplotlib.colorbar_api#matplotlib.colorbar.ColorbarPatch |
matplotlib.colorbar.make_axes(parents, location=None, orientation=None, fraction=0.15, shrink=1.0, aspect=20, **kw)[source]
Create an Axes suitable for a colorbar. The axes is placed in the figure of the parents axes, by resizing and repositioning parents. Parameters
parentsAxes or list of Axes
The Axes to use ... | matplotlib.colorbar_api#matplotlib.colorbar.make_axes |
matplotlib.colorbar.make_axes_gridspec(parent, *, location=None, orientation=None, fraction=0.15, shrink=1.0, aspect=20, **kw)[source]
Create a SubplotBase suitable for a colorbar. The axes is placed in the figure of the parent axes, by resizing and repositioning parent. This function is similar to make_axes. Primary... | matplotlib.colorbar_api#matplotlib.colorbar.make_axes_gridspec |
matplotlib.colormaps[source]
Container for colormaps that are known to Matplotlib by name. Experimental While we expect the API to be final, we formally mark it as experimental for 3.5 because we want to keep the option to still adapt the API for 3.6 should the need arise. The universal registry instance is matplot... | matplotlib_configuration_api#matplotlib.colormaps |
matplotlib.colors Note The Color tutorials and examples demonstrate how to set colors and colormaps. You may want to read those instead. A module for converting numbers or color arguments to RGB or RGBA. RGB and RGBA are sequences of, respectively, 3 or 4 floats in the range 0-1. This module includes functions and cl... | matplotlib.colors_api |
matplotlib.colors.BoundaryNorm classmatplotlib.colors.BoundaryNorm(boundaries, ncolors, clip=False, *, extend='neither')[source]
Bases: matplotlib.colors.Normalize Generate a colormap index based on discrete intervals. Unlike Normalize or LogNorm, BoundaryNorm maps values to integers instead of to the interval 0-1.... | matplotlib._as_gen.matplotlib.colors.boundarynorm |
__call__(value, clip=None)[source]
Normalize value data in the [vmin, vmax] interval into the [0.0, 1.0] interval and return it. Parameters
value
Data to normalize.
clipbool
If None, defaults to self.clip (which defaults to False). Notes If not already initialized, self.vmin and self.vmax are initialized ... | matplotlib._as_gen.matplotlib.colors.boundarynorm#matplotlib.colors.BoundaryNorm.__call__ |
inverse(value)[source]
Raises
ValueError
BoundaryNorm is not invertible, so calling this method will always raise an error | matplotlib._as_gen.matplotlib.colors.boundarynorm#matplotlib.colors.BoundaryNorm.inverse |
matplotlib.colors.CenteredNorm classmatplotlib.colors.CenteredNorm(vcenter=0, halfrange=None, clip=False)[source]
Bases: matplotlib.colors.Normalize Normalize symmetrical data around a center (0 by default). Unlike TwoSlopeNorm, CenteredNorm applies an equal rate of change around the center. Useful when mapping sym... | matplotlib._as_gen.matplotlib.colors.centerednorm |
__call__(value, clip=None)[source]
Normalize value data in the [vmin, vmax] interval into the [0.0, 1.0] interval and return it. Parameters
value
Data to normalize.
clipbool
If None, defaults to self.clip (which defaults to False). Notes If not already initialized, self.vmin and self.vmax are initialized ... | matplotlib._as_gen.matplotlib.colors.centerednorm#matplotlib.colors.CenteredNorm.__call__ |
autoscale(A)[source]
Set halfrange to max(abs(A-vcenter)), then set vmin and vmax. | matplotlib._as_gen.matplotlib.colors.centerednorm#matplotlib.colors.CenteredNorm.autoscale |
autoscale_None(A)[source]
Set vmin and vmax. | matplotlib._as_gen.matplotlib.colors.centerednorm#matplotlib.colors.CenteredNorm.autoscale_None |
matplotlib.colors.Colormap classmatplotlib.colors.Colormap(name, N=256)[source]
Bases: object Baseclass for all scalar to RGBA mappings. Typically, Colormap instances are used to convert data values (floats) from the interval [0, 1] to the RGBA color that the respective Colormap represents. For scaling of data into... | matplotlib._as_gen.matplotlib.colors.colormap |
__call__(X, alpha=None, bytes=False)[source]
Parameters
Xfloat or int, ndarray or scalar
The data value(s) to convert to RGBA. For floats, X should be in the interval [0.0, 1.0] to return the RGBA values X*100 percent along the Colormap line. For integers, X should be in the interval [0, Colormap.N) to return R... | matplotlib._as_gen.matplotlib.colors.colormap#matplotlib.colors.Colormap.__call__ |
colorbar_extend
When this colormap exists on a scalar mappable and colorbar_extend is not False, colorbar creation will pick up colorbar_extend as the default value for the extend keyword in the matplotlib.colorbar.Colorbar constructor. | matplotlib._as_gen.matplotlib.colors.colormap#matplotlib.colors.Colormap.colorbar_extend |
copy()[source]
Return a copy of the colormap. | matplotlib._as_gen.matplotlib.colors.colormap#matplotlib.colors.Colormap.copy |
get_bad()[source]
Get the color for masked values. | matplotlib._as_gen.matplotlib.colors.colormap#matplotlib.colors.Colormap.get_bad |
get_over()[source]
Get the color for high out-of-range values. | matplotlib._as_gen.matplotlib.colors.colormap#matplotlib.colors.Colormap.get_over |
get_under()[source]
Get the color for low out-of-range values. | matplotlib._as_gen.matplotlib.colors.colormap#matplotlib.colors.Colormap.get_under |
is_gray()[source]
Return whether the colormap is grayscale. | matplotlib._as_gen.matplotlib.colors.colormap#matplotlib.colors.Colormap.is_gray |
reversed(name=None)[source]
Return a reversed instance of the Colormap. Note This function is not implemented for base class. Parameters
namestr, optional
The name for the reversed colormap. If it's None the name will be the name of the parent colormap + "_r". See also LinearSegmentedColormap.reversed
L... | matplotlib._as_gen.matplotlib.colors.colormap#matplotlib.colors.Colormap.reversed |
set_bad(color='k', alpha=None)[source]
Set the color for masked values. | matplotlib._as_gen.matplotlib.colors.colormap#matplotlib.colors.Colormap.set_bad |
set_extremes(*, bad=None, under=None, over=None)[source]
Set the colors for masked (bad) values and, when norm.clip =
False, low (under) and high (over) out-of-range values. | matplotlib._as_gen.matplotlib.colors.colormap#matplotlib.colors.Colormap.set_extremes |
set_over(color='k', alpha=None)[source]
Set the color for high out-of-range values. | matplotlib._as_gen.matplotlib.colors.colormap#matplotlib.colors.Colormap.set_over |
set_under(color='k', alpha=None)[source]
Set the color for low out-of-range values. | matplotlib._as_gen.matplotlib.colors.colormap#matplotlib.colors.Colormap.set_under |
with_extremes(*, bad=None, under=None, over=None)[source]
Return a copy of the colormap, for which the colors for masked (bad) values and, when norm.clip = False, low (under) and high (over) out-of-range values, have been set accordingly. | matplotlib._as_gen.matplotlib.colors.colormap#matplotlib.colors.Colormap.with_extremes |
matplotlib.colors.from_levels_and_colors matplotlib.colors.from_levels_and_colors(levels, colors, extend='neither')[source]
A helper routine to generate a cmap and a norm instance which behave similar to contourf's levels and colors arguments. Parameters
levelssequence of numbers
The quantization levels used ... | matplotlib._as_gen.matplotlib.colors.from_levels_and_colors |
matplotlib.colors.FuncNorm classmatplotlib.colors.FuncNorm(functions, vmin=None, vmax=None, clip=False)[source]
Bases: matplotlib.colors.FuncNorm Arbitrary normalization using functions for the forward and inverse. Parameters
functions(callable, callable)
two-tuple of the forward and inverse functions for the... | matplotlib._as_gen.matplotlib.colors.funcnorm |
__call__(value, clip=None)[source]
Normalize value data in the [vmin, vmax] interval into the [0.0, 1.0] interval and return it. Parameters
value
Data to normalize.
clipbool
If None, defaults to self.clip (which defaults to False). Notes If not already initialized, self.vmin and self.vmax are initialized ... | matplotlib._as_gen.matplotlib.colors.funcnorm#matplotlib.colors.FuncNorm.__call__ |
inverse(value)[source] | matplotlib._as_gen.matplotlib.colors.funcnorm#matplotlib.colors.FuncNorm.inverse |
matplotlib.colors.get_named_colors_mapping matplotlib.colors.get_named_colors_mapping()[source]
Return the global mapping of names to named colors. | matplotlib._as_gen.matplotlib.colors.get_named_colors_mapping |
matplotlib.colors.hsv_to_rgb matplotlib.colors.hsv_to_rgb(hsv)[source]
Convert hsv values to rgb. Parameters
hsv(..., 3) array-like
All values assumed to be in range [0, 1] Returns
(..., 3) ndarray
Colors converted to RGB values in range [0, 1]
Examples using matplotlib.colors.hsv_to_rgb
3D ... | matplotlib._as_gen.matplotlib.colors.hsv_to_rgb |
matplotlib.colors.is_color_like matplotlib.colors.is_color_like(c)[source]
Return whether c can be interpreted as an RGB(A) color. | matplotlib._as_gen.matplotlib.colors.is_color_like |
matplotlib.colors.LightSource classmatplotlib.colors.LightSource(azdeg=315, altdeg=45, hsv_min_val=0, hsv_max_val=1, hsv_min_sat=1, hsv_max_sat=0)[source]
Bases: object Create a light source coming from the specified azimuth and elevation. Angles are in degrees, with the azimuth measured clockwise from north and el... | matplotlib._as_gen.matplotlib.colors.lightsource |
blend_hsv(rgb, intensity, hsv_max_sat=None, hsv_max_val=None, hsv_min_val=None, hsv_min_sat=None)[source]
Take the input data array, convert to HSV values in the given colormap, then adjust those color values to give the impression of a shaded relief map with a specified light source. RGBA values are returned, which ... | matplotlib._as_gen.matplotlib.colors.lightsource#matplotlib.colors.LightSource.blend_hsv |
blend_overlay(rgb, intensity)[source]
Combine an rgb image with an intensity map using "overlay" blending. Parameters
rgbndarray
An MxNx3 RGB array of floats ranging from 0 to 1 (color image).
intensityndarray
An MxNx1 array of floats ranging from 0 to 1 (grayscale image). Returns
ndarray
An MxNx3 RGB... | matplotlib._as_gen.matplotlib.colors.lightsource#matplotlib.colors.LightSource.blend_overlay |
blend_soft_light(rgb, intensity)[source]
Combine an rgb image with an intensity map using "soft light" blending, using the "pegtop" formula. Parameters
rgbndarray
An MxNx3 RGB array of floats ranging from 0 to 1 (color image).
intensityndarray
An MxNx1 array of floats ranging from 0 to 1 (grayscale image). ... | matplotlib._as_gen.matplotlib.colors.lightsource#matplotlib.colors.LightSource.blend_soft_light |
hillshade(elevation, vert_exag=1, dx=1, dy=1, fraction=1.0)[source]
Calculate the illumination intensity for a surface using the defined azimuth and elevation for the light source. This computes the normal vectors for the surface, and then passes them on to shade_normals Parameters
elevation2D array-like
The he... | matplotlib._as_gen.matplotlib.colors.lightsource#matplotlib.colors.LightSource.hillshade |
shade(data, cmap, norm=None, blend_mode='overlay', vmin=None, vmax=None, vert_exag=1, dx=1, dy=1, fraction=1, **kwargs)[source]
Combine colormapped data values with an illumination intensity map (a.k.a. "hillshade") of the values. Parameters
data2D array-like
The height values used to generate a shaded map.
c... | matplotlib._as_gen.matplotlib.colors.lightsource#matplotlib.colors.LightSource.shade |
shade_normals(normals, fraction=1.0)[source]
Calculate the illumination intensity for the normal vectors of a surface using the defined azimuth and elevation for the light source. Imagine an artificial sun placed at infinity in some azimuth and elevation position illuminating our surface. The parts of the surface tha... | matplotlib._as_gen.matplotlib.colors.lightsource#matplotlib.colors.LightSource.shade_normals |
shade_rgb(rgb, elevation, fraction=1.0, blend_mode='hsv', vert_exag=1, dx=1, dy=1, **kwargs)[source]
Use this light source to adjust the colors of the rgb input array to give the impression of a shaded relief map with the given elevation. Parameters
rgbarray-like
An (M, N, 3) RGB array, assumed to be in the ran... | matplotlib._as_gen.matplotlib.colors.lightsource#matplotlib.colors.LightSource.shade_rgb |
matplotlib.colors.LinearSegmentedColormap classmatplotlib.colors.LinearSegmentedColormap(name, segmentdata, N=256, gamma=1.0)[source]
Bases: matplotlib.colors.Colormap Colormap objects based on lookup tables using linear segments. The lookup table is generated using linear interpolation for each primary color, with... | matplotlib._as_gen.matplotlib.colors.linearsegmentedcolormap |
staticfrom_list(name, colors, N=256, gamma=1.0)[source]
Create a LinearSegmentedColormap from a list of colors. Parameters
namestr
The name of the colormap.
colorsarray-like of colors or array-like of (value, color)
If only colors are given, they are equidistantly mapped from the range \([0, 1]\); i.e. 0 ma... | matplotlib._as_gen.matplotlib.colors.linearsegmentedcolormap#matplotlib.colors.LinearSegmentedColormap.from_list |
reversed(name=None)[source]
Return a reversed instance of the Colormap. Parameters
namestr, optional
The name for the reversed colormap. If it's None the name will be the name of the parent colormap + "_r". Returns
LinearSegmentedColormap
The reversed colormap. | matplotlib._as_gen.matplotlib.colors.linearsegmentedcolormap#matplotlib.colors.LinearSegmentedColormap.reversed |
set_gamma(gamma)[source]
Set a new gamma value and regenerate colormap. | matplotlib._as_gen.matplotlib.colors.linearsegmentedcolormap#matplotlib.colors.LinearSegmentedColormap.set_gamma |
matplotlib.colors.ListedColormap classmatplotlib.colors.ListedColormap(colors, name='from_list', N=None)[source]
Bases: matplotlib.colors.Colormap Colormap object generated from a list of colors. This may be most useful when indexing directly into a colormap, but it can also be used to generate special colormaps fo... | matplotlib._as_gen.matplotlib.colors.listedcolormap |
reversed(name=None)[source]
Return a reversed instance of the Colormap. Parameters
namestr, optional
The name for the reversed colormap. If it's None the name will be the name of the parent colormap + "_r". Returns
ListedColormap
A reversed instance of the colormap. | matplotlib._as_gen.matplotlib.colors.listedcolormap#matplotlib.colors.ListedColormap.reversed |
matplotlib.colors.LogNorm classmatplotlib.colors.LogNorm(vmin=None, vmax=None, clip=False)[source]
Bases: matplotlib.colors.LogNorm Normalize a given value to the 0-1 range on a log scale. Parameters
vmin, vmaxfloat or None
If vmin and/or vmax is not given, they are initialized from the minimum and maximum va... | matplotlib._as_gen.matplotlib.colors.lognorm |
__call__(value, clip=None)[source]
Normalize value data in the [vmin, vmax] interval into the [0.0, 1.0] interval and return it. Parameters
value
Data to normalize.
clipbool
If None, defaults to self.clip (which defaults to False). Notes If not already initialized, self.vmin and self.vmax are initialized ... | matplotlib._as_gen.matplotlib.colors.lognorm#matplotlib.colors.LogNorm.__call__ |
inverse(value)[source] | matplotlib._as_gen.matplotlib.colors.lognorm#matplotlib.colors.LogNorm.inverse |
matplotlib.colors.make_norm_from_scale matplotlib.colors.make_norm_from_scale(scale_cls, base_norm_cls=None, *, init=None)[source]
Decorator for building a Normalize subclass from a ScaleBase subclass. After @make_norm_from_scale(scale_cls)
class norm_cls(Normalize):
...
norm_cls is filled with methods so that... | matplotlib._as_gen.matplotlib.colors.make_norm_from_scale |
matplotlib.colors.NoNorm classmatplotlib.colors.NoNorm(vmin=None, vmax=None, clip=False)[source]
Bases: matplotlib.colors.Normalize Dummy replacement for Normalize, for the case where we want to use indices directly in a ScalarMappable. Parameters
vmin, vmaxfloat or None
If vmin and/or vmax is not given, they... | matplotlib._as_gen.matplotlib.colors.nonorm |
__call__(value, clip=None)[source]
Normalize value data in the [vmin, vmax] interval into the [0.0, 1.0] interval and return it. Parameters
value
Data to normalize.
clipbool
If None, defaults to self.clip (which defaults to False). Notes If not already initialized, self.vmin and self.vmax are initialized ... | matplotlib._as_gen.matplotlib.colors.nonorm#matplotlib.colors.NoNorm.__call__ |
inverse(value)[source] | matplotlib._as_gen.matplotlib.colors.nonorm#matplotlib.colors.NoNorm.inverse |
matplotlib.colors.Normalize classmatplotlib.colors.Normalize(vmin=None, vmax=None, clip=False)[source]
Bases: object A class which, when called, linearly normalizes data into the [0.0, 1.0] interval. Parameters
vmin, vmaxfloat or None
If vmin and/or vmax is not given, they are initialized from the minimum and... | matplotlib._as_gen.matplotlib.colors.normalize |
__call__(value, clip=None)[source]
Normalize value data in the [vmin, vmax] interval into the [0.0, 1.0] interval and return it. Parameters
value
Data to normalize.
clipbool
If None, defaults to self.clip (which defaults to False). Notes If not already initialized, self.vmin and self.vmax are initialized ... | matplotlib._as_gen.matplotlib.colors.normalize#matplotlib.colors.Normalize.__call__ |
autoscale(A)[source]
Set vmin, vmax to min, max of A. | matplotlib._as_gen.matplotlib.colors.normalize#matplotlib.colors.Normalize.autoscale |
autoscale_None(A)[source]
If vmin or vmax are not set, use the min/max of A to set them. | matplotlib._as_gen.matplotlib.colors.normalize#matplotlib.colors.Normalize.autoscale_None |
inverse(value)[source] | matplotlib._as_gen.matplotlib.colors.normalize#matplotlib.colors.Normalize.inverse |
staticprocess_value(value)[source]
Homogenize the input value for easy and efficient normalization. value can be a scalar or sequence. Returns
resultmasked array
Masked array with the same shape as value.
is_scalarbool
Whether value is a scalar. Notes Float dtypes are preserved; integer types with two b... | matplotlib._as_gen.matplotlib.colors.normalize#matplotlib.colors.Normalize.process_value |
scaled()[source]
Return whether vmin and vmax are set. | matplotlib._as_gen.matplotlib.colors.normalize#matplotlib.colors.Normalize.scaled |
matplotlib.colors.PowerNorm classmatplotlib.colors.PowerNorm(gamma, vmin=None, vmax=None, clip=False)[source]
Bases: matplotlib.colors.Normalize Linearly map a given value to the 0-1 range and then apply a power-law normalization over that range. Parameters
vmin, vmaxfloat or None
If vmin and/or vmax is not g... | matplotlib._as_gen.matplotlib.colors.powernorm |
__call__(value, clip=None)[source]
Normalize value data in the [vmin, vmax] interval into the [0.0, 1.0] interval and return it. Parameters
value
Data to normalize.
clipbool
If None, defaults to self.clip (which defaults to False). Notes If not already initialized, self.vmin and self.vmax are initialized ... | matplotlib._as_gen.matplotlib.colors.powernorm#matplotlib.colors.PowerNorm.__call__ |
inverse(value)[source] | matplotlib._as_gen.matplotlib.colors.powernorm#matplotlib.colors.PowerNorm.inverse |
matplotlib.colors.rgb_to_hsv matplotlib.colors.rgb_to_hsv(arr)[source]
Convert float rgb values (in the range [0, 1]), in a numpy array to hsv values. Parameters
arr(..., 3) array-like
All values must be in the range [0, 1] Returns
(..., 3) ndarray
Colors converted to hsv values in range [0, 1]
E... | matplotlib._as_gen.matplotlib.colors.rgb_to_hsv |
matplotlib.colors.same_color matplotlib.colors.same_color(c1, c2)[source]
Return whether the colors c1 and c2 are the same. c1, c2 can be single colors or lists/arrays of colors. | matplotlib._as_gen.matplotlib.colors.same_color |
matplotlib.colors.SymLogNorm classmatplotlib.colors.SymLogNorm(linthresh, linscale=1.0, vmin=None, vmax=None, clip=False, *, base=10)[source]
Bases: matplotlib.colors.SymLogNorm The symmetrical logarithmic scale is logarithmic in both the positive and negative directions from the origin. Since the values close to z... | matplotlib._as_gen.matplotlib.colors.symlognorm |
__call__(value, clip=None)[source]
Normalize value data in the [vmin, vmax] interval into the [0.0, 1.0] interval and return it. Parameters
value
Data to normalize.
clipbool
If None, defaults to self.clip (which defaults to False). Notes If not already initialized, self.vmin and self.vmax are initialized ... | matplotlib._as_gen.matplotlib.colors.symlognorm#matplotlib.colors.SymLogNorm.__call__ |
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