xarray.plot.contourf#
- xarray.plot.contourf(darray, *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]#
Filled contour plot of 2D DataArray.
Wraps
matplotlib.pyplot.contourf()
.- Parameters
darray (
DataArray
) – Must be two-dimensional, unless creating faceted plots.x (
Hashable
orNone
, optional) – Coordinate for x axis. IfNone
, usedarray.dims[1]
.y (
Hashable
orNone
, optional) – Coordinate for y axis. IfNone
, usedarray.dims[0]
.figsize (
Iterable
orfloat
orNone
, optional) – A tuple (width, height) of the figure in inches. Mutually exclusive withsize
andax
.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 * size
gives the width in inches. Only used if asize
is provided.ax (
matplotlib axes object
, optional) – Axes on which to plot. By default, use the current axes. Mutually exclusive withsize
andfigsize
.row (
Hashable
orNone
, optional) – If passed, make row faceted plots on this dimension name.col (
Hashable
orNone
, optional) – If passed, make column faceted plots on this dimension name.col_wrap (
int
, optional) – Use together withcol
to 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 (
float
orNone
, 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 (
float
orNone
, 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,
cmap
may also be a seaborn color palette. Note: ifcmap
is a seaborn color palette and the plot type is not'contour'
or'contourf'
,levels
must also be specified.center (
float
orFalse
, 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) – IfTrue
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 fromvmin
,vmax
and the data limits.levels (
int
or 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. Settingvmin
and/orvmax
withlevels=N
is 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 (
str
or array-like ofcolor-like
, optional) – A single color or a sequence of colors. If the plot type is not'contour'
or'contourf'
, thelevels
argument 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 (
ArrayLike
orNone
, optional) – Specify tick locations for x-axes.yticks (
ArrayLike
orNone
, 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) – Ifnorm
hasvmin
orvmax
specified, 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.