matplotlib.pyplot.pcolormesh — Matplotlib 3.10.3 documentation (original) (raw)

matplotlib.pyplot.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:

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 theNotes 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"]](../../users/explain/customizing.html?highlight=image.cmap#matplotlibrc-sample) (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:

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:

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"]](../../users/explain/customizing.html?highlight=pcolor.shading#matplotlibrc-sample) (default: 'auto'). Possible values:

See pcolormesh grids and shadingfor 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:

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, pcolormeshreturns 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 inpcolor 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 inpcolormesh, which is not available with pcolor.

Examples using matplotlib.pyplot.pcolormesh#