xarray.DataArray.plot.pcolormesh#
- DataArray.plot.pcolormesh(*args, x=None, y=None, figsize=None, size=None, aspect=None, ax=None, row=None, col=None, col_wrap=None, xincrease=True, yincrease=True, add_colorbar=None, add_labels=True, vmin=None, vmax=None, cmap=None, center=None, robust=False, extend=None, levels=None, infer_intervals=None, colors=None, subplot_kws=None, cbar_ax=None, cbar_kwargs=None, xscale=None, yscale=None, xticks=None, yticks=None, xlim=None, ylim=None, norm=None, **kwargs)[source]#
Pseudocolor plot of 2D DataArray.
Wraps
matplotlib.pyplot.pcolormesh().- Parameters:
darray (
DataArray) – Must be two-dimensional, unless creating faceted plots.x (
HashableorNone, optional) – Coordinate for x axis. IfNone, usedarray.dims[1].y (
HashableorNone, optional) – Coordinate for y axis. IfNone, usedarray.dims[0].figsize (
IterableorfloatorNone, optional) – A tuple (width, height) of the figure in inches. Mutually exclusive withsizeandax.size (scalar, optional) – If provided, create a new figure for the plot with the given size: height (in inches) of each plot. See also:
aspect.aspect (
"auto","equal", scalar orNone, optional) – Aspect ratio of plot, so thataspect * sizegives the width in inches. Only used if asizeis provided.ax (
matplotlib axes object, optional) – Axes on which to plot. By default, use the current axes. Mutually exclusive withsizeandfigsize.row (
HashableorNone, optional) – If passed, make row faceted plots on this dimension name.col (
HashableorNone, optional) – If passed, make column faceted plots on this dimension name.col_wrap (
int, optional) – Use together withcolto wrap faceted plots.xincrease (
None,True, orFalse, optional) – Should the values on the x axis be increasing from left to right? IfNone, use the default for the Matplotlib function.yincrease (
None,True, orFalse, optional) – Should the values on the y axis be increasing from top to bottom? IfNone, use the default for the Matplotlib function.add_colorbar (
bool, optional) – Add colorbar to axes.add_labels (
bool, optional) – Use xarray metadata to label axes.vmin (
floatorNone, optional) – Lower value to anchor the colormap, otherwise it is inferred from the data and other keyword arguments. When a diverging dataset is inferred, setting vmin or vmax will fix the other by symmetry aroundcenter. Setting both values prevents use of a diverging colormap. If discrete levels are provided as an explicit list, both of these values are ignored.vmax (
floatorNone, optional) – Upper value to anchor the colormap, otherwise it is inferred from the data and other keyword arguments. When a diverging dataset is inferred, setting vmin or vmax will fix the other by symmetry aroundcenter. Setting both values prevents use of a diverging colormap. If discrete levels are provided as an explicit list, both of these values are ignored.cmap (matplotlib colormap name or
colormap, optional) – The mapping from data values to color space. If not provided, this will be either be'viridis'(if the function infers a sequential dataset) or'RdBu_r'(if the function infers a diverging dataset). See Choosing Colormaps in Matplotlib for more information. If seaborn is installed,cmapmay also be a seaborn color palette. Note: ifcmapis a seaborn color palette and the plot type is not'contour'or'contourf',levelsmust also be specified.center (
floatorFalse, optional) – The value at which to center the colormap. Passing this value implies use of a diverging colormap. Setting it toFalseprevents use of a diverging colormap.robust (
bool, optional) – IfTrueandvminorvmaxare absent, the colormap range is computed with 2nd and 98th percentiles instead of the extreme values.extend (
{'neither', 'both', 'min', 'max'}, optional) – How to draw arrows extending the colorbar beyond its limits. If not provided,extendis inferred fromvmin,vmaxand the data limits.levels (
intor array-like, optional) – Split the colormap (cmap) into discrete color intervals. If an integer is provided, “nice” levels are chosen based on the data range: this can imply that the final number of levels is not exactly the expected one. Settingvminand/orvmaxwithlevels=Nis equivalent to settinglevels=np.linspace(vmin, vmax, N).infer_intervals (
bool, optional) – Only applies to pcolormesh. IfTrue, the coordinate intervals are passed to pcolormesh. IfFalse, the original coordinates are used (this can be useful for certain map projections). The default is to always infer intervals, unless the mesh is irregular and plotted on a map projection.colors (
stror array-like ofcolor-like, optional) – A single color or a sequence of colors. If the plot type is not'contour'or'contourf', thelevelsargument is required.subplot_kws (
dict, optional) – Dictionary of keyword arguments for Matplotlib subplots. Only used for 2D and faceted plots. (seematplotlib.figure.Figure.add_subplot()).cbar_ax (
matplotlib axes object, optional) – Axes in which to draw the colorbar.cbar_kwargs (
dict, optional) – Dictionary of keyword arguments to pass to the colorbar (seematplotlib.figure.Figure.colorbar()).xscale (
{'linear', 'symlog', 'log', 'logit'}orNone, optional) – Specifies scaling for the x-axes.yscale (
{'linear', 'symlog', 'log', 'logit'}orNone, optional) – Specifies scaling for the y-axes.xticks (
ArrayLikeorNone, optional) – Specify tick locations for x-axes.yticks (
ArrayLikeorNone, optional) – Specify tick locations for y-axes.xlim (
tuple[float,float]orNone, optional) – Specify x-axes limits.ylim (
tuple[float,float]orNone, optional) – Specify y-axes limits.norm (
matplotlib.colors.Normalize, optional) – Ifnormhasvminorvmaxspecified, the corresponding kwarg must beNone.**kwargs (optional) – Additional keyword arguments to wrapped Matplotlib function.
- Returns:
artist– The same type of primitive artist that the wrapped Matplotlib function returns.