scvelo.pl.velocity_embedding_stream

scvelo.pl.velocity_embedding_stream(adata, basis=None, vkey='velocity', density=None, smooth=None, min_mass=None, cutoff_perc=None, arrow_color=None, 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=True, save=None, ax=None, ncols=None, **kwargs)

Stream plot of velocities on the embedding.

Parameters:
adata : AnnData

Annotated data matrix.

vkey : str or None (default: None)

Key for annotations of observations/cells or variables/genes.

density : float (default: 1)

Amount of velocities to show - 0 none to 1 all

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 (range between 0 and 100).

linewidth : float (default: 1)

Line width for streamplot.

n_neighbors : int (default: None)

Number of neighbors to consider around grid point.

X : np.ndarray (default: None)

Embedding grid point coordinates

V : np.ndarray (default: None)

Embedding grid velocity coordinates

basis : str (default=’umap’)

Key for embedding.

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.

linewidth

Scaling factor for the width of occurring lines.

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

Specify percentile for continuous coloring.

sort_order : bool (default: True)

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

groups : str (default: all groups)

Restrict to a few categories in categorical observation annotation.

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. Defaults to ‘bold’ if legend_loc = ‘on data’, otherwise to ‘normal’. Available are [‘light’, ‘normal’, ‘medium’, ‘semibold’, ‘bold’, ‘heavy’, ‘black’].

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.

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

Whether to show density of counts attached to the x and y axes. Color of the plot can also be given as str.

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

Whether to show assignments to the model curve. Color of the assignments can also be given as str.

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

Whether to show linear fit to the data. Color of the plot can also be given as str.

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

Whether to show polynomial fit to ???. Color of the polyfit plot can also be given as str. If int is given, determines the degree of the polynomial fit (else the degree defaults to 2).

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 distribution of data membership to each of the categories.

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.

smooth

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

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.

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.

Returns:

matplotlib.Axis if show==False