def test_add_task_1(self):
'''Add tasks'''
to = TaskOrganizer()
for i, task in enumerate(self.tasks):
self.assertEquals(len(to.tasks), i)
to.add_task(task)
self.assertTrue(task in to.tasks)
self.assertEquals(len(to.tasks), i+1)
# adding same task doesn't do anything.
self.assertEquals(len(to.tasks), len(self.tasks))
to.add_task(self.tasks[0])
self.assertEquals(len(to.tasks), len(self.tasks))
def test_full_run(self):
to = TaskOrganizer()
for task in self.tasks:
to.add_task(task)
# batch one should be filtering and nothing else
results, skipped, impossible = to.pull_runnable_tasks()
pp = [task.plugin for task, info in results]
print '1', [p.name for p in pp]
self.assertTrue(self.dfp in pp)
self.assertTrue(self.efp in pp)
self.assertEquals(len(pp), 4) # 2 for each trial.
no_results, skipped, impossible = to.pull_runnable_tasks()
self.assertEquals(no_results, [])
for task, info in results:
return_fake_results(to, task)
# batch 2 should be detection and upsampling.
results, skipped, impossible = to.pull_runnable_tasks()
pp = [task.plugin for task, info in results]
print '2', [p.name for p in pp]
self.assertTrue(self.esrp in pp or self.esrp2 in pp)
self.assertTrue(self.sdp in pp)
self.assertEquals(len(pp), 4) # 2 for each trial.
no_results, skipped, impossible = to.pull_runnable_tasks()
self.assertEquals(no_results, [])
for task, info in results:
return_fake_results(to, task)
# batch 3 should more upsampling.
results, skipped, impossible = to.pull_runnable_tasks()
pp = [task.plugin for task, info in results]
print '3', [p.name for p in pp]
self.assertTrue(self.esrp in pp or self.esrp2 in pp)
self.assertEquals(len(pp), 2) # 2 for each trial.
no_results, skipped, impossible = to.pull_runnable_tasks()
self.assertEquals(no_results, [])
for task, info in results:
return_fake_results(to, task)
# batch 4 should be feature extraction.
results, skipped, impossible = to.pull_runnable_tasks()
pp = [task.plugin for task, info in results]
print '4', [p.name for p in pp]
self.assertTrue(self.fep in pp)
self.assertEquals(len(pp), 2) # 2 for each trial.
no_results, skipped, impossible = to.pull_runnable_tasks()
self.assertEquals(no_results, [])
for task, info in results:
return_fake_results(to, task)
# batch 5 should be clustering.
results, skipped, impossible = to.pull_runnable_tasks()
pp = [task.plugin for task, info in results]
print '5', [p.name for p in pp]
self.assertTrue(self.cp in pp)
self.assertEquals(len(pp), 1) # 1 for each trial. (pooling)
no_results, skipped, impossible = to.pull_runnable_tasks()
self.assertEquals(no_results, [])
for task, info in results:
return_fake_results(to, task)
# batch 6 should be clustering revision.
results, skipped, impossible = to.pull_runnable_tasks()
pp = [task.plugin for task, info in results]
print '6', [p.name for p in pp]
self.assertTrue(self.crp in pp)
self.assertEquals(len(pp), 1) # 1 for each trial. (pooling)
no_results, skipped, impossible = to.pull_runnable_tasks()
self.assertEquals(no_results, [])
for task, info in results:
return_fake_results(to, task)
# batch 7 should be summary plot stuff.
results, skipped, impossible = to.pull_runnable_tasks()
pp = [task.plugin for task, info in results]
print '7', [p.name for p in pp]
self.assertTrue(self.spp in pp)
self.assertEquals(len(pp), 2) # 2 for each trial.
no_results, skipped, impossible = to.pull_runnable_tasks()
self.assertEquals(no_results, [])
for task, info in results:
return_fake_results(to, task)
# all done
no_results, skipped, impossible = to.pull_runnable_tasks()
self.assertEquals(no_results, [])