xarray.DataArray.plot.imshow¶
-
DataArray.plot.
imshow
(x, y, **kwargs)¶ Image plot of 2d DataArray using matplotlib.pyplot
Wraps
matplotlib.pyplot.imshow()
While other plot methods require the DataArray to be strictly two-dimensional,
imshow
also accepts a 3D array where some dimension can be interpreted as RGB or RGBA color channels and allows this dimension to be specified via the kwargrgb=
.Unlike matplotlib, Xarray can apply
vmin
andvmax
to RGB or RGBA data, by applying a single scaling factor and offset to all bands. Passingrobust=True
infersvmin
andvmax
in the usual way.Note
This function needs uniformly spaced coordinates to properly label the axes. Call DataArray.plot() to check.
The pixels are centered on the coordinates values. Ie, if the coordinate value is 3.2 then the pixels for those coordinates will be centered on 3.2.
- Parameters
darray (
DataArray
) – Must be 2 dimensional, unless creating faceted plotsx (
string
, optional) – Coordinate for x axis. If None use darray.dims[1]y (
string
, optional) – Coordinate for y axis. If None use darray.dims[0]figsize (
tuple
, optional) – A tuple (width, height) of the figure in inches. Mutually exclusive withsize
andax
.aspect (scalar, optional) – Aspect ratio of plot, so that
aspect * size
gives the width in inches. Only used if asize
is provided.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
.ax (
matplotlib axes object
, optional) – Axis on which to plot this figure. By default, use the current axis. Mutually exclusive withsize
andfigsize
.row (
string
, optional) – If passed, make row faceted plots on this dimension namecol (
string
, optional) – If passed, make column faceted plots on this dimension namecol_wrap (
int
, optional) – Use together withcol
to wrap faceted plotsxscale, yscale (
'linear'
,'symlog'
,'log'
,'logit'
, optional) – Specifies scaling for the x- and y-axes respectivelyxticks, yticks (
Specify tick locations for x-
andy-axes
)xlim, ylim (
Specify x-
andy-axes limits
)xincrease (
None
,True
, orFalse
, optional) – Should the values on the x axes be increasing from left to right? if None, use the default for the matplotlib function.yincrease (
None
,True
, orFalse
, optional) – Should the values on the y axes be increasing from top to bottom? if None, use the default for the matplotlib function.add_colorbar (
bool
, optional) – Adds colorbar to axisadd_labels (
bool
, optional) – Use xarray metadata to label axesnorm (
matplotlib.colors.Normalize
instance, optional) – If thenorm
has vmin or vmax specified, the corresponding kwarg must be None.vmin, vmax (
floats
, optional) – Values to anchor the colormap, otherwise they are inferred from the data and other keyword arguments. When a diverging dataset is inferred, setting one of these values 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 (
:doc:matplotlib colormap name
orobject
, optional) – The mapping from data values to color space. If not provided, this will be either beviridis
(if the function infers a sequential dataset) orRdBu_r
(if the function infers a diverging dataset). When Seaborn is installed,cmap
may also be a seaborn color palette. Ifcmap
is seaborn color palette and the plot type is notcontour
orcontourf
,levels
must also be specified.colors (
discrete colors
toplot
, optional) – A single color or a list of colors. If the plot type is notcontour
orcontourf
, thelevels
argument is required.center (
float
, optional) – The value at which to center the colormap. Passing this value implies use of a diverging colormap. Setting it toFalse
prevents use of a diverging colormap.robust (
bool
, optional) – If True andvmin
orvmax
are 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, extend is inferred from vmin, vmax and the data limits.levels (
int
orlist-like object
, 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. Settingvmin
and/orvmax
withlevels=N
is equivalent to settinglevels=np.linspace(vmin, vmax, N)
.infer_intervals (
bool
, optional) – Only applies to pcolormesh. If True, the coordinate intervals are passed to pcolormesh. If False, 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.subplot_kws (
dict
, optional) – Dictionary of keyword arguments for matplotlib subplots. Only used for 2D and FacetGrid plots.cbar_ax (
matplotlib Axes
, optional) – Axes in which to draw the colorbar.cbar_kwargs (
dict
, optional) – Dictionary of keyword arguments to pass to the colorbar.**kwargs (optional) – Additional arguments to wrapped matplotlib function
- Returns
artist
– The same type of primitive artist that the wrapped matplotlib function returns