scanpy.pl.StackedViolin.style
- StackedViolin.style(cmap='Blues', stripplot=False, jitter=False, jitter_size=1, linewidth=0.2, row_palette=None, scale='width', yticklabels=False, ylim=None, x_padding=0.5, y_padding=0.5)
Modifies plot visual parameters
- Parameters
- cmap :
Optional[str] (default:'Blues') String denoting matplotlib color map.
- stripplot :
Optional[bool] (default:False) Add a stripplot on top of the violin plot. See
stripplot().- jitter :
Union[float,bool,None] (default:False) Add jitter to the stripplot (only when stripplot is True) See
stripplot().- jitter_size :
Optional[int] (default:1) Size of the jitter points.
- linewidth :
Optional[float] (default:0.2) linewidth for the violin plots.
- row_palette :
Optional[str] (default:None) The row palette determines the colors to use for the stacked violins. The value should be a valid seaborn or matplotlib palette name (see
color_palette()). Alternatively, a single color name or hex value can be passed, e.g.'red'or'#cc33ff'.- scale :
Optional[Literal[‘area’, ‘count’, ‘width’]] (default:'width') The method used to scale the width of each violin. If ‘width’ (the default), each violin will have the same width. If ‘area’, each violin will have the same area. If ‘count’, a violin’s width corresponds to the number of observations.
- yticklabels :
Optional[bool] (default:False) Set to true to view the y tick labels.
- ylim :
Optional[Tuple[float,float]] (default:None) minimum and maximum values for the y-axis. If set. All rows will have the same y-axis range. Example: ylim=(0, 5)
- x_padding :
Optional[float] (default:0.5) Space between the plot left/right borders and the violins. A unit is the distance between the x ticks.
- y_padding :
Optional[float] (default:0.5) Space between the plot top/bottom borders and the violins. A unit is the distance between the y ticks.
- cmap :
- Returns
Examples
>>> adata = sc.datasets.pbmc68k_reduced() >>> markers = ['C1QA', 'PSAP', 'CD79A', 'CD79B', 'CST3', 'LYZ']
Change color map and turn off edges
>>> sc.pl.MatrixPlot(adata, markers, groupby='bulk_labels') ... .style(row_palette='Blues', linewidth=0).show()