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- Dataset.plot.streamplot(*args, x=None, y=None, u=None, v=None, hue=None, hue_style=None, row=None, col=None, col_wrap=None, ax=None, figsize=None, size=None, aspect=None, sharex=True, sharey=True, add_guide=None, subplot_kws=None, cbar_kwargs=None, cbar_ax=None, cmap=None, vmin=None, vmax=None, norm=None, infer_intervals=None, center=None, robust=None, colors=None, extend=None, levels=None, **kwargs)[source]#
Plot streamlines of Dataset variables.
Wraps
matplotlib.pyplot.streamplot()
.- Parameters:
ds (Dataset)
x (
Hashable
orNone
, optional) – Variable name for x-axis.y (
Hashable
orNone
, optional) – Variable name for y-axis.u (
Hashable
orNone
, optional) – Variable name for the u velocity (in x direction).quiver/streamplot plots only.v (
Hashable
orNone
, optional) – Variable name for the v velocity (in y direction).quiver/streamplot plots only.hue (
Hashable
orNone
, optional) – Variable by which to color scatter points or arrows.hue_style (
{'continuous', 'discrete'}
orNone
, optional) – How to use thehue
variable:'continuous'
– continuous color scale(default for numerichue
variables)'discrete'
– a color for each unique value, using the default color cycle(default for non-numerichue
variables)
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.ax (
matplotlib axes object
orNone
, optional) – IfNone
, use the current axes. Not applicable when using facets.figsize (
Iterable[float]
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 ininches. Only used if asize
is provided.sharex (
bool
orNone
, optional) – If True all subplots share the same x-axis.sharey (
bool
orNone
, optional) – If True all subplots share the same y-axis.add_guide (
bool
orNone
, optional) – Add a guide that depends onhue_style
:'continuous'
– build a colorbar'discrete'
– build a legend
subplot_kws (
dict
orNone
, optional) – Dictionary of keyword arguments for Matplotlib subplots(seematplotlib.figure.Figure.add_subplot()
).Only applies to FacetGrid plotting.cbar_kwargs (
dict
, optional) – Dictionary of keyword arguments to pass to the colorbar(seematplotlib.figure.Figure.colorbar()
).cbar_ax (
matplotlib axes object
, optional) – Axes in which to draw the colorbar.cmap (matplotlib colormap name or
colormap
, optional) – The mapping from data values to color space. Either aMatplotlib colormap name or object. If not provided, this willbe either'viridis'
(if the function infers a sequentialdataset) or'RdBu_r'
(if the function infers a divergingdataset).See Choosing Colormaps in Matplotlibfor more information.If seaborn is installed,
cmap
may also be aseaborn color palette.Note: ifcmap
is a seaborn color palette,levels
must also be specified.vmin (
float
orNone
, optional) – Lower value to anchor the colormap, otherwise it is inferred from thedata 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 thesevalues are ignored.vmax (
float
orNone
, optional) – Upper value to anchor the colormap, otherwise it is inferred from thedata 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 thesevalues are ignored.norm (
matplotlib.colors.Normalize
, optional) – Ifnorm
hasvmin
orvmax
specified, the correspondingkwarg must beNone
.infer_intervals (
bool | None
) – If True the intervals are inferred.center (
float
, optional) – The value at which to center the colormap. Passing this value impliesuse of a diverging colormap. Setting it toFalse
prevents use of adiverging colormap.robust (
bool
, optional) – IfTrue
andvmin
orvmax
are absent, the colormap range iscomputed with 2nd and 98th percentiles instead of the extreme values.colors (
str
or array-like ofcolor-like
, optional) – A single color or a list of colors. Thelevels
argumentis required.extend (
{'neither', 'both', 'min', 'max'}
, optional) – How to draw arrows extending the colorbar beyond its limits. If notprovided,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 integeris provided, “nice” levels are chosen based on the data range: this canimply that the final number of levels is not exactly the expected one.Settingvmin
and/orvmax
withlevels=N
is equivalent tosettinglevels=np.linspace(vmin, vmax, N)
.**kwargs (optional) – Additional keyword arguments to wrapped Matplotlib function.
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