matplotlib.axes.Axes.pcolormesh#

Axes.pcolormesh(*args, alpha=None, norm=None, cmap=None, vmin=None, vmax=None, colorizer=None, shading=None, antialiased=False, data=None, **kwargs)[source]#

Create a pseudocolor plot with a non-regular rectangular grid.

Call signature:

pcolormesh([X, Y,] C, /, **kwargs)

X and Y can be used to specify the corners of the quadrilaterals.

The arguments X, Y, C are positional-only.

Hint

pcolormesh is similar to pcolor. It is much faster and preferred in most cases. For a detailed discussion on the differences see Differences between pcolor() and pcolormesh().

Parameters:

Carray-like

The mesh data. Supported array shapes are:

(M, N) or M*N: a mesh with scalar data. The values are mapped to colors using normalization and a colormap. See parameters norm, cmap, vmin, vmax.
(M, N, 3): an image with RGB values (0-1 float or 0-255 int).
(M, N, 4): an image with RGBA values (0-1 float or 0-255 int), i.e. including transparency.

The first two dimensions (M, N) define the rows and columns of the mesh data.

X, Yarray-like, optional

The coordinates of the corners of quadrilaterals of a pcolormesh:

(X[i+1, j], Y[i+1, j])       (X[i+1, j+1], Y[i+1, j+1])
                      ●╶───╴●
                      │     │
                      ●╶───╴●
    (X[i, j], Y[i, j])       (X[i, j+1], Y[i, j+1])

Note that the column index corresponds to the x-coordinate, and the row index corresponds to y. For details, see the Notes section below.

If shading='flat' the dimensions of X and Y should be one greater than those of C, and the quadrilateral is colored due to the value at C[i, j]. If X, Y and C have equal dimensions, a warning will be raised and the last row and column of C will be ignored.

If shading='nearest' or 'gouraud', the dimensions of X and Y should be the same as those of C (if not, a ValueError will be raised). For 'nearest' the color C[i, j] is centered on (X[i, j], Y[i, j]). For 'gouraud', a smooth interpolation is carried out between the quadrilateral corners.

If X and/or Y are 1-D arrays or column vectors they will be expanded as needed into the appropriate 2D arrays, making a rectangular grid.

cmapstr or Colormap, default: rcParams["image.cmap"] (default: 'viridis')

The Colormap instance or registered colormap name used to map scalar data to colors.

normstr or Normalize, optional

The normalization method used to scale scalar data to the [0, 1] range before mapping to colors using cmap. By default, a linear scaling is used, mapping the lowest value to 0 and the highest to 1.

If given, this can be one of the following:

An instance of Normalize or one of its subclasses (see Colormap normalization).
A scale name, i.e. one of "linear", "log", "symlog", "logit", etc. For a list of available scales, call matplotlib.scale.get_scale_names(). In that case, a suitable Normalize subclass is dynamically generated and instantiated.

vmin, vmaxfloat, optional

When using scalar data and no explicit norm, vmin and vmax define the data range that the colormap covers. By default, the colormap covers the complete value range of the supplied data. It is an error to use vmin/vmax when a norm instance is given (but using a str norm name together with vmin/vmax is acceptable).

colorizerColorizer or None, default: None

The Colorizer object used to map color to data. If None, a Colorizer object is created from a norm and cmap.

edgecolors{'none', None, 'face', color, color sequence}, optional

The color of the edges. Defaults to 'none'. Possible values:

'none' or '': No edge.
None: rcParams["patch.edgecolor"] (default: 'black') will be used. Note that currently rcParams["patch.force_edgecolor"] (default: False) has to be True for this to work.
'face': Use the adjacent face color.
A color or sequence of colors will set the edge color.

The singular form edgecolor works as an alias.

alphafloat, default: None

The alpha blending value, between 0 (transparent) and 1 (opaque).

shading{'flat', 'nearest', 'gouraud', 'auto'}, optional

The fill style for the quadrilateral; defaults to rcParams["pcolor.shading"] (default: 'auto'). Possible values:

'flat': A solid color is used for each quad. The color of the quad (i, j), (i+1, j), (i, j+1), (i+1, j+1) is given by C[i, j]. The dimensions of X and Y should be one greater than those of C; if they are the same as C, then a deprecation warning is raised, and the last row and column of C are dropped.
'nearest': Each grid point will have a color centered on it, extending halfway between the adjacent grid centers. The dimensions of X and Y must be the same as C.
'gouraud': Each quad will be Gouraud shaded: The color of the corners (i', j') are given by C[i', j']. The color values of the area in between is interpolated from the corner values. The dimensions of X and Y must be the same as C. When Gouraud shading is used, edgecolors is ignored.
'auto': Choose 'flat' if dimensions of X and Y are one larger than C. Choose 'nearest' if dimensions are the same.

See pcolormesh grids and shading for more description.

snapbool, default: False

Whether to snap the mesh to pixel boundaries.

rasterizedbool, optional

Rasterize the pcolormesh when drawing vector graphics. This can speed up rendering and produce smaller files for large data sets. See also Rasterization for vector graphics.

Returns:

matplotlib.collections.QuadMesh

Other Parameters:

dataindexable object, optional

If given, all parameters also accept a string s, which is interpreted as data[s] if s is a key in data.

**kwargs

Additionally, the following arguments are allowed. They are passed along to the QuadMesh constructor:

Property	Description
`agg_filter`	a filter function, which takes a (m, n, 3) float array and a dpi value, and returns a (m, n, 3) array and two offsets from the bottom left corner of the image
`alpha`	array-like or float or None
`animated`	bool
`antialiased` or `aa` or `antialiaseds`	bool or list of bools
`array`	array-like
`capstyle`	`CapStyle` or {'butt', 'projecting', 'round'}
`clim`	(vmin: float, vmax: float)
`clip_box`	`BboxBase` or None
`clip_on`	bool
`clip_path`	Patch or (Path, Transform) or None
`cmap`	`Colormap` or str or None
`color`	color or list of RGBA tuples
`edgecolor` or `ec` or `edgecolors`	color or list of color or 'face'
`facecolor` or `facecolors` or `fc`	color or list of color
`figure`	`Figure` or `SubFigure`
`gid`	str
`hatch`	{'/', '\', '\|', '-', '+', 'x', 'o', 'O', '.', '*'}
`hatch_linewidth`	unknown
`in_layout`	bool
`joinstyle`	`JoinStyle` or {'miter', 'round', 'bevel'}
`label`	object
`linestyle` or `dashes` or `linestyles` or `ls`	str or tuple or list thereof
`linewidth` or `linewidths` or `lw`	float or list of floats
`mouseover`	bool
`norm`	`Normalize` or str or None
`offset_transform` or `transOffset`	`Transform`
`offsets`	(N, 2) or (2,) array-like
`path_effects`	list of `AbstractPathEffect`
`picker`	None or bool or float or callable
`pickradius`	float
`rasterized`	bool
`sketch_params`	(scale: float, length: float, randomness: float)
`snap`	bool or None
`transform`	`Transform`
`url`	str
`urls`	list of str or None
`visible`	bool
`zorder`	float

See also

pcolor: An alternative implementation with slightly different features. For a detailed discussion on the differences see Differences between pcolor() and pcolormesh().
imshow: If X and Y are each equidistant, imshow can be a faster alternative.

Notes

Masked arrays

C may be a masked array. If C[i, j] is masked, the corresponding quadrilateral will be transparent. Masking of X and Y is not supported. Use pcolor if you need this functionality.

Grid orientation

The grid orientation follows the standard matrix convention: An array C with shape (nrows, ncolumns) is plotted with the column number as X and the row number as Y.

Differences between pcolor() and pcolormesh()

Both methods are used to create a pseudocolor plot of a 2D array using quadrilaterals.

The main difference lies in the created object and internal data handling: While pcolor returns a PolyQuadMesh, pcolormesh returns a QuadMesh. The latter is more specialized for the given purpose and thus is faster. It should almost always be preferred.

There is also a slight difference in the handling of masked arrays. Both pcolor and pcolormesh support masked arrays for C. However, only pcolor supports masked arrays for X and Y. The reason lies in the internal handling of the masked values. pcolor leaves out the respective polygons from the PolyQuadMesh. pcolormesh sets the facecolor of the masked elements to transparent. You can see the difference when using edgecolors. While all edges are drawn irrespective of masking in a QuadMesh, the edge between two adjacent masked quadrilaterals in pcolor is not drawn as the corresponding polygons do not exist in the PolyQuadMesh. Because PolyQuadMesh draws each individual polygon, it also supports applying hatches and linestyles to the collection.

Another difference is the support of Gouraud shading in pcolormesh, which is not available with pcolor.

Examples using `matplotlib.axes.Axes.pcolormesh`#

pcolor images

pcolormesh grids and shading

pcolormesh

QuadMesh Demo

Time Series Histogram

Rasterization for vector graphics

pcolormesh(X, Y, Z)

Creating Colormaps in Matplotlib

Colormap normalization

matplotlib.axes.Axes.pcolormesh#

Examples using matplotlib.axes.Axes.pcolormesh#

Examples using `matplotlib.axes.Axes.pcolormesh`#