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.
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.
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.
Colormap
, default: rcParams["image.cmap"]
(default: 'viridis'
)
The Colormap instance or registered colormap name used to map scalar data to colors.
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.
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).
Colorizer
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.
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.
The alpha blending value, between 0 (transparent) and 1 (opaque).
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.
Whether to snap the mesh to pixel boundaries.
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.
matplotlib.collections.QuadMesh
If given, all parameters also accept a string s
, which is interpreted as data[s]
if s
is a key in data
.
Additionally, the following arguments are allowed. They are passed along to the QuadMesh
constructor:
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
.
matplotlib.pyplot.pcolormesh
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