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, [])