108 lines
4.2 KiB
Python
108 lines
4.2 KiB
Python
import unittest
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import yaml
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import sys
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import os
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import pandas as pd
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from snakemake.io import expand
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class RapidsTests(unittest.TestCase):
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unittest.TestLoader.sortTestMethodsUsing = lambda self, a, b: (a < b) - (a > b)
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def generate_sensor_file_lists(self):
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# Go through the configs and select those sensors with COMPUTE = True.
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# Also get TIME_SEGMENTS, then create expected
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# files. Return dictionary with list of file paths of expected and
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# actual files for each sensor listed in the config file. Added for Travis.
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# Initialize string of file path for both expected and actual metric values
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segment = self.configs['TIME_SEGMENTS']['TYPE'].lower()
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act_str = "data/processed/features/{pid}/{sensor_key}.csv"
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exp_str = "tests/data/processed/features/"+segment+"/{pid}/{sensor_key}.csv"
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# Build list of sensors to be tested.
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sensors = []
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for sensor in self.configs:
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if "PROVIDERS" in self.configs[sensor] and self.configs[sensor]["PROVIDERS"] is not None:
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for provider in self.configs[sensor]["PROVIDERS"]:
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if self.configs[sensor]["PROVIDERS"][provider]["COMPUTE"]:
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sensors.append(sensor.lower())
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act_file_list = expand(act_str,pid=self.configs["PIDS"],sensor_key = sensors)
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exp_file_list = expand(exp_str, pid=self.configs["PIDS"],sensor_key = sensors)
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sensor_file_lists = list(zip(act_file_list,exp_file_list))
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return sensor_file_lists
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def test_sensors_files_exist(self):
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# Loop through the file_list dictionary and check if the files exist.
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file_lists = self.generate_sensor_file_lists()
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for each in file_lists:
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print("Checking if the output file exists: {}".format(each[0]))
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print(os.path.exists( each[0]))
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self.assertEqual(os.path.exists( each[0]), 1)
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def test_sensors_features_calculations(self):
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sensor_file_list = self.generate_sensor_file_lists()
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for act_result, exp_result in sensor_file_list:
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df_act = pd.read_csv(act_result)
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df_exp = pd.read_csv(exp_result)
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if df_act.empty:
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print(act_result)
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print("Checking if the output file is empty: {}".format(exp_result))
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self.assertTrue(df_exp.empty)
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else:
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# The order in which the columns varies from time to time so
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# the columns are sorted before doing the comparision
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print("Comparing {} and {}".format(act_result, exp_result))
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df_exp = df_exp.reindex(sorted(df_exp.columns), axis=1)
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df_act = df_act.reindex(sorted(df_act.columns), axis=1)
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pd.testing.assert_frame_equal(df_exp, df_act, obj=df_exp)
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class TestFrequency(RapidsTests):
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@classmethod
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def setUpClass(cls):
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# Runs once to Setup env
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# global configs
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with open(r'tests/settings/frequency_config.yaml') as file:
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cls.configs = yaml.full_load(file)
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class TestPeriodic(RapidsTests):
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@classmethod
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def setUpClass(cls):
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# Runs once to Setup env
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# global configs
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with open(r'tests/settings/periodic_config.yaml') as file:
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cls.configs = yaml.full_load(file)
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class TestEvent(RapidsTests):
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@classmethod
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def setUpClass(cls):
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# Runs once to Setup env
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# global configs
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with open(r'tests/settings/event_config.yaml') as file:
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cls.configs = yaml.full_load(file)
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def run_some_tests(test_type):
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# Run only the tests in the specified classes
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if test_type == "frequency":
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test_class = TestFrequency
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elif test_type == "periodic":
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test_class = TestPeriodic
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elif test_type == "event":
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test_class = TestEvent
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else:
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raise ValueError("Only frequency, periodic, and event are valid arguments")
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loader = unittest.TestLoader()
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suite = loader.loadTestsFromTestCase(test_class)
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big_suite = unittest.TestSuite(suite)
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runner = unittest.TextTestRunner()
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results = runner.run(big_suite)
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if __name__ == '__main__':
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run_some_tests(sys.argv[1]) |