cytoflowgui.workflow.operations.kmeans#

class cytoflowgui.workflow.operations.kmeans.KMeansWorkflowOp[source]#

Bases: WorkflowOperation, KMeansOp

default_view(**kwargs)[source]#

Returns a diagnostic plot of the k-means clustering.

Returns:: IView
Return type:: an IView, call KMeans1DView.plot to see the diagnostic plot.

estimate(experiment)[source]#

Estimate the k-means clusters

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]#

Apply the KMeans clustering to the data.

Returns:

a new Experiment with one additional entry in Experiment.conditions named name, of type category. The new category has values name_1, name_2, etc to indicate which k-means cluster an event is a member of.

The new Experiment also has one new statistic called centers, which is a list of tuples encoding the centroids of each k-means cluster.

Return type:

Experiment

clear_estimate()[source]#

get_notebook_code(idx)[source]#

class cytoflowgui.workflow.operations.kmeans.KMeansWorkflowView[source]#

Bases: WorkflowByView

id = 'cytoflowgui.op_plugins.kmeans'#

friendly_id = 'KMeans'#

plot(experiment, **kwargs)[source]#: A default plot that passes current_plot as the plot name.

enum_plots(experiment)[source]#

get_notebook_code(idx)[source]#