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Cluster estimation integration test #251
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2e1f340
Nearly completed test (with an unusual error)
RohanKatreddy ebc8470
wrote cluster estimation worker integration test
RohanKatreddy 8bd2fd7
Nearly completed test (with an unusual error)
RohanKatreddy 86456bc
wrote cluster estimation worker integration test
RohanKatreddy cc322ea
Merge branch 'cluster-estimation-integration-test' of github.com:UWAR…
RohanKatreddy 9f67587
Added review changes: type checking, created constants, and import st…
RohanKatreddy b37c965
review changes: corrected expected type of output_results
RohanKatreddy 5f1dcba
review changes: made type checking more dynamic and refactored to rem…
RohanKatreddy 2778d80
Final review change
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,154 @@ | ||
| """ | ||
| Test cluster_estimation_worker process. | ||
| """ | ||
|
|
||
| import time | ||
| import multiprocessing as mp | ||
| from typing import List | ||
|
|
||
| import numpy as np | ||
|
|
||
| from utilities.workers import queue_proxy_wrapper, worker_controller | ||
| from modules.cluster_estimation.cluster_estimation_worker import cluster_estimation_worker | ||
| from modules.detection_in_world import DetectionInWorld | ||
| from modules.object_in_world import ObjectInWorld | ||
|
|
||
| MIN_ACTIVATION_THRESHOLD = 3 | ||
| MIN_NEW_POINTS_TO_RUN = 0 | ||
| MAX_NUM_COMPONENTS = 3 | ||
| RANDOM_STATE = 0 | ||
|
|
||
|
|
||
| def test_cluster_estimation_worker() -> int: | ||
| """ | ||
| Integration test for cluster estimation worker. | ||
| """ | ||
|
|
||
| # Worker and controller setup. | ||
| controller = worker_controller.WorkerController() | ||
|
|
||
| mp_manager = mp.Manager() | ||
| input_queue = queue_proxy_wrapper.QueueProxyWrapper(mp_manager) | ||
| output_queue = queue_proxy_wrapper.QueueProxyWrapper(mp_manager) | ||
|
|
||
| worker_process = mp.Process( | ||
| target=cluster_estimation_worker, | ||
| args=( | ||
| MIN_ACTIVATION_THRESHOLD, | ||
| MIN_NEW_POINTS_TO_RUN, | ||
| MAX_NUM_COMPONENTS, | ||
| RANDOM_STATE, | ||
| input_queue, | ||
| output_queue, | ||
| controller, | ||
| ), | ||
| ) | ||
|
|
||
| # Second test set: 1 clusters | ||
| test_data_1 = [ | ||
| # Landing pad 1 | ||
| DetectionInWorld.create( | ||
| np.array([[1, 1], [1, 2], [2, 2], [2, 1]]), np.array([1.5, 1.5]), 1, 0.9 | ||
| )[1], | ||
| DetectionInWorld.create( | ||
| np.array([[1, 1], [1, 2], [2, 2], [2, 1]]), np.array([1.5, 1.5]), 1, 0.9 | ||
| )[1], | ||
| DetectionInWorld.create( | ||
| np.array([[1, 1], [1, 2], [2, 2], [2, 1]]), np.array([1.5, 1.5]), 1, 0.9 | ||
| )[1], | ||
| DetectionInWorld.create( | ||
| np.array([[1, 1], [1, 2], [2, 2], [2, 1]]), np.array([1.5, 1.5]), 1, 0.9 | ||
| )[1], | ||
| DetectionInWorld.create( | ||
| np.array([[1, 1], [1, 2], [2, 2], [2, 1]]), np.array([1.5, 1.5]), 1, 0.9 | ||
| )[1], | ||
| ] | ||
|
|
||
| # First test set: 2 clusters | ||
| test_data_2 = [ | ||
| # Landing pad 1 | ||
| DetectionInWorld.create( | ||
| np.array([[1, 1], [1, 2], [2, 2], [2, 1]]), np.array([1.5, 1.5]), 1, 0.9 | ||
| )[1], | ||
| DetectionInWorld.create( | ||
| np.array([[1, 1], [1, 2], [2, 2], [2, 1]]), np.array([1.5, 1.5]), 1, 0.9 | ||
| )[1], | ||
| DetectionInWorld.create( | ||
| np.array([[1, 1], [1, 2], [2, 2], [2, 1]]), np.array([1.5, 1.5]), 1, 0.9 | ||
| )[1], | ||
| DetectionInWorld.create( | ||
| np.array([[1, 1], [1, 2], [2, 2], [2, 1]]), np.array([1.5, 1.5]), 1, 0.9 | ||
| )[1], | ||
| DetectionInWorld.create( | ||
| np.array([[1, 1], [1, 2], [2, 2], [2, 1]]), np.array([1.5, 1.5]), 1, 0.9 | ||
| )[1], | ||
| # Landing pad 2 | ||
| DetectionInWorld.create( | ||
| np.array([[10, 10], [10, 11], [11, 11], [11, 10]]), np.array([10.5, 10.5]), 1, 0.9 | ||
| )[1], | ||
| DetectionInWorld.create( | ||
| np.array([[10.1, 10.1], [10.1, 11.1], [11.1, 11.1], [11.1, 10.1]]), | ||
| np.array([10.6, 10.6]), | ||
| 1, | ||
| 0.92, | ||
| )[1], | ||
| DetectionInWorld.create( | ||
| np.array([[9.9, 9.9], [9.9, 10.9], [10.9, 10.9], [10.9, 9.9]]), | ||
| np.array([10.4, 10.4]), | ||
| 1, | ||
| 0.88, | ||
| )[1], | ||
| DetectionInWorld.create( | ||
| np.array([[10.2, 10.2], [10.2, 11.2], [11.2, 11.2], [11.2, 10.2]]), | ||
| np.array([10.7, 10.7]), | ||
| 1, | ||
| 0.95, | ||
| )[1], | ||
| DetectionInWorld.create( | ||
| np.array([[10.3, 10.3], [10.3, 11.3], [11.3, 11.3], [11.3, 10.3]]), | ||
| np.array([10.8, 10.8]), | ||
| 1, | ||
| 0.93, | ||
| )[1], | ||
| ] | ||
|
|
||
| # Testing with test_data_1 (1 cluster) | ||
|
|
||
| input_queue.queue.put(test_data_1) | ||
| worker_process.start() | ||
| time.sleep(1) | ||
|
|
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| output_results: List[DetectionInWorld] = output_queue.queue.get() | ||
|
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||
| assert output_results is not None | ||
| assert isinstance(output_results, list) | ||
| assert len(output_results) == 1 | ||
| assert all(isinstance(obj, ObjectInWorld) for obj in output_results) | ||
|
|
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| time.sleep(1) | ||
|
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| # Testing with test_data_2 (2 clusters) | ||
|
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| input_queue.queue.put(test_data_2) | ||
| time.sleep(1) | ||
|
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| output_results: List[DetectionInWorld] = output_queue.queue.get() | ||
|
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| assert output_results is not None | ||
| assert isinstance(output_results, list) | ||
| assert len(output_results) == 2 | ||
| assert all(isinstance(obj, ObjectInWorld) for obj in output_results) | ||
|
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| controller.request_exit() | ||
| input_queue.queue.put(None) | ||
| worker_process.join() | ||
|
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| return 0 | ||
|
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|
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| if __name__ == "__main__": | ||
| result_main = test_cluster_estimation_worker() | ||
| if result_main < 0: | ||
| print(f"ERROR: Status code: {result_main}") | ||
|
|
||
| print("Done!") | ||
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It might be better to create a loop where you extract each list from the queue and check whether they are the types youre expecting. You'd remove the len(output_results) assertion and just wrap the other ones inside the loop, exiting if they fail. I would probably try to do this with test_data_1 as well.