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
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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)
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Example output: