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def pcolormesh(*args: 'ArrayLike', alpha: 'float | None' = None, norm: 'str | Normalize | None' = None, cmap: 'str | Colormap | None' = None, vmin: 'float | None' = None, vmax: 'float | None' = None, colorizer: 'Colorizer | None' = None, shading: "Literal['flat', 'nearest', 'gouraud', 'auto'] | None" = None, antialiased: 'bool' = False, data=None, **kwargs) -> 'QuadMesh'
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::
`~.Axes.pcolormesh` is similar to `~.Axes.pcolor`. It is much faster
and preferred in most cases. For a detailed discussion on the
differences see :ref:`Differences between pcolor() and pcolormesh()
<differences-pcolor-pcolormesh>`.
Parameters
----------
C : array-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, Y : array-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
:ref:`Notes <axes-pcolormesh-grid-orientation>` 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.
cmap : str or `~matplotlib.colors.Colormap`, default: :rc:`image.cmap`
The Colormap instance or registered colormap name used to map scalar data
to colors.
norm : str or `~matplotlib.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 :ref:`colormapnorms`).
- 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, vmax : float, 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).
colorizer : `~matplotlib.colorizer.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*.
edgecolors : {'none', None, 'face', color, color sequence}, optional
The color of the edges. Defaults to 'none'. Possible values:
- 'none' or '': No edge.
- *None*: :rc:`patch.edgecolor` will be used. Note that currently
:rc:`patch.force_edgecolor` 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.
alpha : float, 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
:rc:`pcolor.shading`. 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 :doc:`/gallery/images_contours_and_fields/pcolormesh_grids`
for more description.
snap : bool, default: False
Whether to snap the mesh to pixel boundaries.
rasterized : bool, optional
Rasterize the pcolormesh when drawing vector graphics. This can
speed up rendering and produce smaller files for large data sets.
See also :doc:`/gallery/misc/rasterization_demo`.
Returns
-------
`matplotlib.collections.QuadMesh`
Other Parameters
----------------
data : indexable 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 `~matplotlib.collections.QuadMesh` constructor:
Properties:
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 scalar 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: `~matplotlib.transforms.BboxBase` or None
clip_on: bool
clip_path: Patch or (Path, Transform) or None
cmap: `.Colormap` or str or None
color: :mpltype:`color` or list of RGBA tuples
edgecolor or ec or edgecolors: :mpltype:`color` or list of :mpltype:`color` or 'face'
facecolor or facecolors or fc: :mpltype:`color` or list of :mpltype:`color`
figure: `~matplotlib.figure.Figure` or `~matplotlib.figure.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: `~matplotlib.transforms.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
:ref:`Differences between pcolor() and pcolormesh()
<differences-pcolor-pcolormesh>`.
imshow : If *X* and *Y* are each equidistant, `~.Axes.imshow` can be a
faster alternative.
Notes
-----
.. note::
This is the :ref:`pyplot wrapper <pyplot_interface>` for `.axes.Axes.pcolormesh`.
**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 `~.Axes.pcolor` if you need this functionality.
.. _axes-pcolormesh-grid-orientation:
**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-pcolor-pcolormesh:
**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 `~.Axes.pcolor` returns a `.PolyQuadMesh`, `~.Axes.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 `~.Axes.pcolor` and `~.Axes.pcolormesh` support masked arrays
for *C*. However, only `~.Axes.pcolor` supports masked arrays for *X*
and *Y*. The reason lies in the internal handling of the masked values.
`~.Axes.pcolor` leaves out the respective polygons from the
PolyQuadMesh. `~.Axes.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
`~.Axes.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
`~.Axes.pcolormesh`, which is not available with `~.Axes.pcolor`.
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