DistanceToSelectionFunction
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@ -297,6 +297,42 @@ class GOWeightDialog(gtk.Dialog):
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options['rank_threshold'] = self._rank_spin.get_value()
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class DistanceToSelectionFunction(workflow.Function):
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def __init__(self):
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workflow.Function.__init__(self, 'dist-to-sel', 'Dist. to Selection')
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self.options = DistanceToSelectionOptions()
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def run(self, similarities, selection):
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self.show_gui(similarities, self.options)
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retval = []
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dims = similarities.get_dim_name()
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if dims[0] != "_%s" %dims[1] and dims[1] != "_%s" %dims[0]:
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logger.log('warning', 'Are you sure this is a similarity matrix?')
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dim = dims[0]
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print "dim", dim
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print "selection", selection[dim]
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print "indices", similarities.get_indices(dim, selection[dim])
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indices = similarities.get_indices(dim, selection[dim])
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m = apply_along_axis(max, 1, similarities.asarray().take(indices, 1))
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retval.append(dataset.Dataset(m, [(dim, similarities[dim]),
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("_dummy", '0')]))
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return retval
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def show_gui(self, similarities, options, edit=True):
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dialog = DistanceToSelectionOptionsDialog([similarities], self.options)
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response = dialog.run()
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dialog.hide()
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if response == gtk.RESPONSE_OK:
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dialog.set_output()
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return dialog.get_options()
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else:
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return options
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class GOWeightFunction(workflow.Function):
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def __init__(self):
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workflow.Function.__init__(self, 'load-go-ann', 'GO Influence')
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@ -334,6 +370,11 @@ class GOWeightFunction(workflow.Function):
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return options
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class DistanceToSelectionOptionsDialog(workflow.OptionsDialog):
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def __init__(self, data, options):
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workflow.OptionsDialog.__init__(self, data, options, ['X'])
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class TTestOptionsDialog(workflow.OptionsDialog):
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def __init__(self, data, options):
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@ -373,13 +414,13 @@ class TTestFunction(workflow.Function):
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print "Out data:", self.options['out_data']
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tds = dataset.Dataset(tscores[0], [('gene_id', x['gene_id']),
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('t', ['0'])],
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('_t', ['0'])],
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name='t-values')
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if 't-value' in self.options['out_data']:
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retval.append(tds)
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pds = dataset.Dataset(tscores[1], [('gene_id', x['gene_id']),
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('p', ['0'])],
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('_p', ['0'])],
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name='p-values')
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if 'p-value' in self.options['out_data']:
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retval.append(pds)
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@ -387,6 +428,14 @@ class TTestFunction(workflow.Function):
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if ProbabilityHistogramPlot in self.options['out_plots']:
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retval.append(ProbabilityHistogramPlot(pds))
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if VolcanoPlot in self.options['out_plots']:
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fc = apply_along_axis(mean, 0, ns) / apply_along_axis(mean, 0, cs)
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fcds = dataset.Dataset(fc, [('gene_id', x['gene_id']),
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('_dummy', ['0'])],
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name="Fold change")
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retval.append(VolcanoPlot(fcds, pds, 'gene_id'))
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return retval
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def show_gui(self, x, categories):
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@ -404,13 +453,20 @@ class TTestOptions(workflow.Options):
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def __init__(self):
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workflow.Options.__init__(self)
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self['all_plots'] = [(ProbabilityHistogramPlot, 'Histogram', True)]
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self['all_plots'] = [(ProbabilityHistogramPlot, 'Histogram', True),
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(VolcanoPlot, 'Histogram', True)]
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self['all_data'] = [('t-value', 't-values', True),
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('p-value', 'Probabilities', True),
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('categories', 'Categories', False)]
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self['out_data'] = ['t-value', 'p-value']
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class DistanceToSelectionOptions(workflow.Options):
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def __init__(self):
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workflow.Options.__init__(self)
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self['all_data'] = [('mindist', 'Minimum distance', True)]
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class GOWeightOptions(workflow.Options):
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def __init__(self):
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workflow.Options.__init__(self)
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@ -420,6 +476,13 @@ class GOWeightOptions(workflow.Options):
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class ProbabilityHistogramPlot(plots.HistogramPlot):
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def __init__(self, ds):
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plots.HistogramPlot.__init__(self, ds, name="Confidence")
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plots.HistogramPlot.__init__(self, ds, name="Confidence", bins=50)
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class VolcanoPlot(plots.ScatterPlot):
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def __init__(self, fold_ds, p_ds, dim, **kw):
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plots.ScatterPlot.__init__(self, fold_ds, p_ds, 'gene_id', '_dummy',
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'0', '0',
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name="Volcano plot",
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sel_dim_2='_p', **kw)
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