xarray.plot.imshow

xarray.plot.imshow(darray, x=None, y=None, ax=None, row=None, col=None, col_wrap=None, xincrease=True, yincrease=True, add_colorbar=True, add_labels=True, vmin=None, vmax=None, cmap=None, center=None, robust=False, extend=None, levels=None, colors=None, subplot_kws=None, **kwargs)

Image plot of 2d DataArray using matplotlib.pyplot

Wraps matplotlib.pyplot.imshow

..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 plots

x : 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]

ax : matplotlib axes object, optional

If None, uses the current axis

row : string, optional

If passed, make row faceted plots on this dimension name

col : string, optional

If passed, make column faceted plots on this dimension name

col_wrap : integer, optional

Use together with col to wrap faceted plots

xincrease : None, True, or False, 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, or False, 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 : Boolean, optional

Adds colorbar to axis

add_labels : Boolean, optional

Use xarray metadata to label axes

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 around center. 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 object, 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). When when Seaborn is installed, cmap may also be a seaborn color palette. If cmap is seaborn color palette and the plot type is not contour or contourf, levels must also be specified.

colors : discrete colors to plot, optional

A single color or a list of colors. If the plot type is not contour or contourf, the levels 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 to False prevents use of a diverging colormap.

robust : bool, optional

If True and vmin or vmax 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 or list-like object, optional

Split the colormap (cmap) into discrete color intervals.

subplot_kws : dict, optional

Dictionary of keyword arguments for matplotlib subplots. Only applies to FacetGrid plotting.

**kwargs : optional

Additional arguments to wrapped matplotlib function

Returns:

artist :

The same type of primitive artist that the wrapped matplotlib function returns