Projection plot

This visualization function can be launched from class DigitalCellSorter at the stage of post-processing.

From submodule VisualizationFunctions:

class VisualizationFunctions(dataName='dataName', saveDir='', matplotlibMode='Agg', safePlotting=True, verbose=1)[source]

Class of visualization functions for DigitalCellSorter

makeProjectionPlot(*args, **kwargs)[source]

Produce projection plot (2D layout) with a specified coloring scheme

Parameters:

Xprojection: 2D coordinates for each cell

cellClusterIndexLabel: cluster index for each cell

suffix: str

Text label to append to the figure name

colormap: cell coloring sequence, can be a dictionary or cm.colormap,

Default matplotlib.colors.LinearSegmentedColormap.jet

legend: boolean, Default True

Whether to print legend

labels: boolean, Default True

Whether to print labels

colorbar: boolean, Default False

Whether to show colorbar Use with non-numerical values will raise an error

fontsize: int, Default 10

Labels and legend font size

plotNaNs: boolean, Default True

Whether to plot NaN labels (in grey)

rightShift: float, Default 0.3

Fraction of space to leave on the right-hand side of the plot. This parameter is useful for adjusting legend overlap with data points.

dpi: int, Default 600

Resolution of the figure image

extension: str, Default ‘png’

Format of the figure file

Returns:

None

Usage:

DCS = DigitalCellSorter.DigitalCellSorter()

DCS.makeProjectionPlot(projection, cellClusterIndexLabel, suffix)

Example output:

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