def test_clearsky_cache_key(self):
cs = csd.Clearsky()
target_datetime = datetime(2010, 6, 19, 22, 15)
config = read_configuration_file(config_test.DUMMY_TEST_CFG_PATH)
key = cs._generate_cache_key(target_datetime,
config.stations[Station.BND])
self.assertEqual(key, "40.0519;-88.3731;230.00;2010-06-19 22:15:00")
def __init__(
self,
metadata: Callable[[], Iterable[Metadata]],
image_reader: image.ImageReader,
config: DataloaderConfig = DataloaderConfig(),
):
"""Load the config with the image_reader from the metadata."""
self.metadata = metadata
self.image_reader = image_reader
self.config = config
enable_clearsky_caching = False
if config.precompute_clearsky:
enable_clearsky_caching = True
self.csd = csd.Clearsky(enable_caching=enable_clearsky_caching)
if config.precompute_clearsky:
self.csd._precompute_clearsky_values(config.target_datetimes,
config.stations)
self.ok = 0
self.skipped = 0
self._readers = {
Feature.image: self._read_image,
Feature.target_ghi: self._read_target,
Feature.metadata: self._read_metadata,
Feature.target_cloud: self._read_cloudiness,
}
def test_clearsky_prediction_function(self):
target_datetime = datetime(2010, 6, 19, 22, 15)
config = read_configuration_file(config_test.DUMMY_TEST_CFG_PATH)
preditions = csd.Clearsky().calculate_clearsky_values(
config.stations[Station.BND], target_datetime)
self.assertCloseTo(preditions[csd.CSMDOffset.GHI_T], 471.675670)
self.assertCloseTo(preditions[csd.CSMDOffset.GHI_T_1h], 280.165857)
self.assertCloseTo(preditions[csd.CSMDOffset.GHI_T_3h], 0.397029)
self.assertCloseTo(preditions[csd.CSMDOffset.GHI_T_6h], 0.0)
def test_clearsky_prediction_uncached_performance(self):
target_datetime = datetime(2010, 6, 19, 22, 15)
config = read_configuration_file(config_test.DUMMY_TEST_CFG_PATH)
start_time = time.time()
iterations = 100
for i in range(0, iterations):
csd.Clearsky(clear_cache=True).calculate_clearsky_values(
config.stations[Station.BND], target_datetime)
delta = time.time() - start_time
iterations_per_seconde = iterations / delta
self.assertLess(delta, 4) # 3.59s on i5 8600k
self.assertGreater(iterations_per_seconde, 25) # 27.57 IPS. Too slow!
def test_clearsky_prediction_cached_performance(self):
target_datetime = datetime(2010, 6, 19, 22, 15)
config = read_configuration_file(config_test.DUMMY_TEST_CFG_PATH)
start_time = time.time()
iterations = 1000
cs = csd.Clearsky()
for i in range(0, iterations):
cs.calculate_clearsky_values(config.stations[Station.BND],
target_datetime)
delta = time.time() - start_time
iterations_per_seconde = iterations / delta
self.assertLess(delta, 0.1) # 0.058s on i5 8600k
self.assertGreater(iterations_per_seconde, 25) # 17 196 IPS. Ok!
def test_precompute(self):
meta_config = config.read_configuration_file(
"tests/data/samples/train_config_raphael.json")
target_datetimes = pd.Series(meta_config.target_datetimes)
stations = meta_config.stations
clearsky = csd.Clearsky()
clearsky._precompute_clearsky_values(target_datetimes, stations)
self.assertCloseTo(
clearsky.cache["40.0519;-88.3731;230.00;2015-01-04 19:15:00"][0],
414.271049)
self.assertCloseTo(
clearsky.cache["40.0519;-88.3731;230.00;2014-07-10 00:15:00"][0],
98.633557)