51 lines
1.6 KiB
Python
51 lines
1.6 KiB
Python
import gtk
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from fluents import dataset, logger, plots, workflow
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#import geneontology
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#import gostat
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from scipy import array, randn, log, ones
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import cPickle
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import networkx
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class TestWorkflow (workflow.Workflow):
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name = 'Test Workflow'
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ident = 'test'
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description = 'This workflow currently serves as a general testing workflow.'
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def __init__(self):
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workflow.Workflow.__init__(self)
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load = workflow.Stage('load', 'Test Data')
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load.add_task(TestDataTask)
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self.add_stage(load)
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class TestDataTask(workflow.Task):
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name = "Test data"
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def __init__(self, input):
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workflow.Task.__init__(self, input)
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def run(self):
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logger.log('notice', 'Injecting foo test data')
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x = randn(500,15)
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X = dataset.Dataset(x)
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p = plots.ScatterPlot(X, X, 'rows', 'rows', '0_1', '0_2',name='scatter')
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# p2 = plots.ScatterMarkerPlot(X, X, 'rows', 'rows', '0_1', '0_2',name='marker')
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graph = networkx.XGraph()
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for x in 'ABCDEF':
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for y in 'ADE':
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graph.add_edge(x, y, 3)
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ds = dataset.GraphDataset(array(networkx.adj_matrix(graph)))
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ds_plot = plots.NetworkPlot(ds)
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cds = dataset.CategoryDataset(ones([3, 3]))
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ds_scatter = plots.ScatterMarkerPlot(ds, ds,
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'rows_0', 'rows_0',
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'0_1', '0_2')
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lp = plots.LineViewPlot(X,major_axis=0)
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vp = plots.VennPlot()
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self.datasets = [p]
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return [X, ds, p, ds_plot, ds_scatter, p2, cds, lp, vp]
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