T-test now works, and outputs a histogram as well as t-values and p-values.

fluents/workflow.py

@@ -241,8 +241,8 @@ class Options(dict):
     """
     def __init__(self, *args,**kw):
         dict.__init__(self, *args, **kw)
-        self['out_plots'] = None
+        self['out_plots'] = []
-        self['out_data'] = None
+        self['out_data'] = []
 	self['all_plots'] = []
 	self['all_data'] = []
 

workflows/gobrowser.py

@@ -2,7 +2,8 @@
 import gtk
 from fluents import dataset, logger, plots, workflow, fluents, project
 import geneontology
-from scipy import array, randn, log, ones, zeros
+#from scipy import array, randn, log, ones, zeros
+from scipy import *
 import networkx
 import re
 
@@ -339,6 +340,19 @@ class TTestOptionsDialog(workflow.OptionsDialog):
 	workflow.OptionsDialog.__init__(self, data, options,
                                         ['X', 'Categories'])
 
+        vb = gtk.VBox()
+        l = gtk.Label("Limit")
+        adj = gtk.Adjustment(0, 0.0, 1.0, 0.01, 1.0, 1.0)
+        sb = gtk.SpinButton(adj, 0.0, 2)
+        l.show()
+        sb.show()
+
+        vb.add(l)
+        vb.add(sb)
+        vb.show()
+        self.nb.insert_page(vb, gtk.Label("Limit"), -1)
+
+
 class TTestFunction(workflow.Function):
     def __init__(self):
         workflow.Function.__init__(self, 't-test', 't-test')
@@ -347,16 +361,55 @@ class TTestFunction(workflow.Function):
     def run(self, x, categories):
         self.show_gui(x, categories)
 
+        retval = []
+        m = x.asarray()
+        c = categories.asarray()
+
+        # Nonsmokers and current smokers
+        ns = m.take(nonzero(c[:,0]), 0)[0]
+        cs = m.take(nonzero(c[:,2]), 0)[0]
+
+        tscores = stats.ttest_ind(ns, cs)
+
+        print "Out data:", self.options['out_data']
+        tds = dataset.Dataset(tscores[0], [('gene_id', x['gene_id']), 
+                                           ('t', ['0'])],
+                              name='t-values')
+        if 't-value' in self.options['out_data']:
+            retval.append(tds)
+            
+        pds = dataset.Dataset(tscores[1], [('gene_id', x['gene_id']), 
+                                           ('p', ['0'])],
+                              name='p-values')
+        if 'p-value' in self.options['out_data']:
+            retval.append(pds)
+            
+        if ProbabilityHistogramPlot in self.options['out_plots']:
+            retval.append(ProbabilityHistogramPlot(pds))
+
+        return retval
+
     def show_gui(self, x, categories):
-        dlg = TTestOptionsDialog([x, categories], self.options)
+        dialog = TTestOptionsDialog([x, categories], self.options)
-        dlg.run()
+        response = dialog.run()
+        dialog.hide()
+        if response == gtk.RESPONSE_OK:
+            dialog.set_output()
+            return dialog.get_options()
+        else:
+            return options
 
 
 class TTestOptions(workflow.Options):
 
     def __init__(self):
         workflow.Options.__init__(self)
-        
+        self['all_plots'] = [(ProbabilityHistogramPlot, 'Histogram', True)]
+        self['all_data'] = [('t-value', 't-values', True),
+                            ('p-value', 'Probabilities', True),
+                            ('categories', 'Categories', False)]
+        self['out_data'] = ['t-value', 'p-value']
+
 
 class GOWeightOptions(workflow.Options):
     def __init__(self):
@@ -364,3 +417,9 @@ class GOWeightOptions(workflow.Options):
         self['similarity_threshold'] = 0.0
         self['rank_threshold'] = 0.0
 
+
+class ProbabilityHistogramPlot(plots.HistogramPlot):
+    def __init__(self, ds):
+        plots.HistogramPlot.__init__(self, ds, name="Confidence")
+
+

workflows/smalltest.py

@@ -52,6 +52,7 @@ class SmallTestWorkflow(workflow.Workflow):
         go = workflow.Stage('go', 'Gene Ontology')
         go.add_function(gobrowser.LoadGOFunction())
         go.add_function(gobrowser.GOWeightFunction())
+        go.add_function(gobrowser.TTestFunction())
         self.add_stage(go)
 
         # EXTRA PLOTS