, basis=None, vkey='velocity', density=2, smooth=None, min_mass=None, cutoff_perc=None, arrow_color=None, arrow_size=1, arrow_style='-|>', max_length=4, integration_direction='both', linewidth=None, n_neighbors=None, recompute=None, color=None, use_raw=None, layer=None, color_map=None, colorbar=True, palette=None, size=None, alpha=0.3, perc=None, X=None, V=None, X_grid=None, V_grid=None, sort_order=True, groups=None, components=None, legend_loc='on data', legend_fontsize=None, legend_fontweight=None, xlabel=None, ylabel=None, title=None, fontsize=None, figsize=None, dpi=None, frameon=None, show=None, save=None, ax=None, ncols=None, **kwargs)

Stream plot of velocities on the embedding.

adata : AnnData

Annotated data matrix.

density : float (default: 2)

Controls the closeness of streamlines. When density = 2 (default), the domain is divided into a 60x60 grid, whereas density linearly scales this grid. Each cell in the grid can have, at most, one traversing streamline. For different densities in each direction, use a tuple (density_x, density_y).

smooth : bool or int (default: None)

Multiplication factor for scale in Gaussian kernel around grid point.

min_mass : float (default: 1)

Minimum threshold for mass to be shown. It can range between 0 (all velocities) and 5 (large velocities only).

cutoff_perc : float (default: None)

If set, mask small velocities below a percentile threshold (between 0 and 100).

linewidth : float (default: 1)

Line width for streamplot.

arrow_color : str or 2D array (default: ‘k’)

The streamline color. If given an array, it must have the same shape as u and v.

arrow_size : float (default: 1)

Scaling factor for the arrow size.

arrow_style : str (default: ‘-|>’)

Arrow style specification, ‘-|>’ or ‘->’.

max_length : float (default: 4)

Maximum length of streamline in axes coordinates.

integration_direction : str (default: ‘both’)

Integrate the streamline in ‘forward’, ‘backward’ or ‘both’ directions.

n_neighbors : int (default: None)

Number of neighbors to consider around grid point.

X : np.ndarray (default: None)

Embedding coordinates. Using adata.obsm[‘X_umap’] per default.

V : np.ndarray (default: None)

Embedding velocity coordinates. Using adata.obsm[‘velocity_umap’] per default.

basis : str or list of str (default: None)

Key for embedding. If not specified, use ‘umap’, ‘tsne’ or ‘pca’ (ordered by preference).

vkey : str or list of str (default: None)

Key for velocity / steady-state ratio to be visualized.

color : str, list of str or None (default: None)

Key for annotations of observations/cells or variables/genes

use_raw : bool (default: None)

Use raw attribute of adata if present.

layer : str, list of str or None (default: None)

Specify the layer for color.

color_map : str (default: matplotlib.rcParams[‘image.cmap’])

String denoting matplotlib color map.

colorbar : bool (default: False)

Whether to show colorbar.

palette : list of str (default: None)

Colors to use for plotting groups (categorical annotation).

size : float (default: 5)

Point size.

alpha : float (default: 1)

Set blending - 0 transparent to 1 opaque.


Scaling factor for the width of occurring lines.

linecolor : str ir list of str (default: ‘k’)

Color of lines from velocity fits, linear fits and polynomial fits

perc : tuple, e.g. [2,98] (default: None)

Specify percentile for continuous coloring.

groups : str or list of str (default: all groups)

Restrict to a few categories in categorical observation annotation. Multiple categories can be passed as list with [‘cluster_1’, ‘cluster_3’], or as string with ‘cluster_1, cluster_3’.

sort_order : bool (default: True)

For continuous annotations used as color parameter, plot data points with higher values on top of others.

components : str or list of str (default: ‘1,2’)

For instance, [‘1,2’, ‘2,3’].

projection : {'2d', '3d'} (default: '2d')

Projection of plot.

legend_loc : str (default: 'none')

Location of legend, either ‘on data’, ‘right margin’ or valid keywords for matplotlib.legend.

legend_fontsize : int (default: None)

Legend font size.

legend_fontweight : {‘normal’, ‘bold’, …} (default: None)

Legend font weight. A numeric value in range 0-1000 or a string. Defaults to ‘bold’ if legend_loc = ‘on data’, otherwise to ‘normal’. Available are [‘light’, ‘normal’, ‘medium’, ‘semibold’, ‘bold’, ‘heavy’, ‘black’].

legend_fontoutline : float (default: None)

Line width of the legend font outline in pt. Draws a white outline using the path effect withStroke.

legend_align_text : bool or str (default: None)

Aligns the positions of the legend texts. Set the axis along which the best alignment should be determined. This can be ‘y’ or True (vertically), ‘x’ (horizontally), or ‘xy’ (best alignment in both directions).

right_margin : float or list of float (default: None)

Adjust the width of the space right of each plotting panel.

left_margin : float or list of float (default: None)

Adjust the width of the space left of each plotting panel.

xlabel : str (default: None)

Label of x-axis.

ylabel : str (default: None)

Label of y-axis.

title : str (default: None)

Provide title for panels either as, e.g. [“title1”, “title2”, …].

fontsize : float (default: None)

Label font size.

figsize : tuple (default: (7,5))

Figure size.

xlim : tuple, e.g. [0,1] or None (default: None)

Restrict x-limits of the axis.

ylim : tuple, e.g. [0,1] or None (default: None)

Restrict y-limits of the axis.

add_density : bool or str or None (default: None)

Whether to show density of values along x and y axes. Color of the density plot can also be passed as str.

add_assignments : bool or str or None (default: None)

Whether to add assignments to the model curve. Color of the assignments can also be passed as str.

add_linfit : bool or str or None (default: None)

Whether to add linear regression fit to the data points. Color of the line can also be passed as str. Fitting with or without an intercept by passing ‘intercept’ or ‘no_intercept’. A colored regression line with intercept is obtained with ‘intercept, blue’.

add_polyfit : bool or str or int or None (default: None)

Whether to add polynomial fit to the data points. Color of the polyfit plot can also be passed as str. The degree of the polynomial fit can be passed as int (default is 2 for quadratic fit). Fitting with or without an intercept by passing ‘intercept’ or ‘no_intercept’. A colored regression line with intercept is obtained with ‘intercept, blue’.

add_rug : str or None (default: None)

If categorical observation annotation (e.g. ‘clusters’) is given, a rugplot is attached to the x-axis showing the data membership to each of the categories.

add_text : str (default: None)

Text to be added to the plot, passed as str.

add_text_pos : tuple, e.g. [0.05, 0.95] (defaut: [0.05, 0.95])

Text position. Default is [0.05, 0.95], positioning the text at top right corner.

add_margin : float (default: None)

A value between [-1, 1] to add (positive) and reduce (negative) figure margins.

add_outline : bool or str (default: False)

Whether to show an outline around scatter plot dots. Alternatively a string of cluster names can be passed, e.g. ‘cluster_1, clusters_3’.

outline_width : tuple type scalar or None (default: (0.3, 0.05))

Width of the inner and outer outline

outline_color : tuple of type str or None (default: (‘black’, ‘white’))

Inner and outer matplotlib color of the outline

n_convolve : int or None (default: None)

If int is given, data is smoothed by convolution along the x-axis with kernel size n_convolve.


Whether to convolve/average the color values over the nearest neighbors. If int, it specifies number of neighbors.

normalize_data : bool (default: None)

Whether to rescale values for x, y to [0,1].

rescale_color : tuple (default: None)

Boundaries for color rescaling, e.g. [0, 1], setting min/max values of the colorbar.

color_gradients : str or np.ndarray (default: None)

Key for .obsm or array with color gradients by categories.

dpi : int (default: 80)

Figure dpi.

frameon : bool (default: True)

Draw a frame around the scatter plot.

ncols : int (default: None)

Number of panels per row.

nrows : int (default: None)

Number of panels per column.

wspace : float (default: None)

Adjust the width of the space between multiple panels.

hspace : float (default: None)

Adjust the height of the space between multiple panels.

show : bool, optional (default: None)

Show the plot, do not return axis.

save : bool or str, optional (default: None)

If True or a str, save the figure. A string is appended to the default filename. Infer the filetype if ending on {‘.pdf’, ‘.png’, ‘.svg’}.

ax : matplotlib.Axes, optional (default: None)

A matplotlib axes object. Only works if plotting a single component.


matplotlib.Axis if show==False