cytoflowgui.workflow.operations.flowpeaks#

class cytoflowgui.workflow.operations.flowpeaks.FlowPeaksWorkflowOp[source]#

Bases: WorkflowOperation, FlowPeaksOp

default_view(**kwargs)[source]#

Returns a diagnostic plot of the Gaussian mixture model.

Parameters:

  • channels (List(Str)) – Which channels to plot? Must be contain either one or two channels.

  • scale (List({‘linear’, ‘log’, ‘logicle’})) – How to scale the channels before plotting them

  • density (bool) – Should we plot a scatterplot or the estimated density function?

Returns:

an IView, call plot to see the diagnostic plot.

Return type:

IView

estimate(experiment)[source]#

Estimate the k-means clusters, then hierarchically merge them.

Parameters:

  • experiment (Experiment) – The Experiment to use to estimate the k-means clusters

  • subset (str (default = None)) – A Python expression that specifies a subset of the data in experiment to use to parameterize the operation.

apply(experiment)[source]#

Assign events to a cluster.

Assigns each event to one of the k-means centroids from estimate, then groups together events in the same cluster hierarchy.

Parameters:

experiment (Experiment) – the Experiment to apply the gate to.

Returns:

A new Experiment with the gate applied to it. TODO - document the extra statistics

Return type:

Experiment

clear_estimate()[source]#
get_notebook_code(idx)[source]#
class cytoflowgui.workflow.operations.flowpeaks.FlowPeaksWorkflowView[source]#

Bases: WorkflowByView, By2DView

id = 'cytoflowgui.op_plugins.flowpeaks'#
friendly_id = 'FlowPeaks'#
plot(experiment, **kwargs)[source]#

A default plot that passes current_plot as the plot name.

get_notebook_code(idx)[source]#