workflows/test_workflow.py

@@ -1,11 +1,11 @@
 import gtk
 from fluents import dataset, logger, plots, workflow
-#import geneontology
-#import gostat
+
 from scipy import array, randn, log, ones, newaxis
 import cPickle
 import networkx
 
+
 class TestWorkflow (workflow.Workflow):
 
     name = 'Test Workflow'
@@ -15,15 +15,14 @@ class TestWorkflow (workflow.Workflow):
     def __init__(self):
         workflow.Workflow.__init__(self)
 
-        load = workflow.Stage('load', 'Test Data')
-        load.add_task(TestDataTask)
-        load.add_task(TestPlot)
-        self.add_stage(load)
+        test_stage = workflow.Stage('test', 'Test Data')
+        test_stage.tasks.append(TestDataTask)
+        test_stage.tasks.append(TestPlot)
+        self.stages.append(test_stage)
 
         
 class TestDataTask(workflow.Task):  
     name = "Test data"
-
     def __init__(self, input):
         workflow.Task.__init__(self, input)
 
@@ -56,10 +55,10 @@ class TestPlot(workflow.Task):
         workflow.Task.__init__(self, input)
 
     def run(self):
-        logger.log('notice', 'Injecting foo test data')
-        x = randn(500,15)
-        X = dataset.Dataset(x)
-        ii = X.get_dim_name()
-        p = plots.ScatterPlot(X, X, ii[0], ii[0], '0_1', '0_2',name='scatter')
+        #logger.log('notice', 'Injecting % dataset') %self.input[0].get_name()
+        X = self.input[0]
+        ii = X.get_dim_name()[0]
+        ids = X.get_identifiers(ii, indices=[0,1])
+        p = plots.ScatterPlot(X, X, ii, ii, ids[0], ids[1],name='scatter')
         
         return [p]