def test_wrong_value(self):
check_words_example = {
'sun': 1,
'cloud': 2,
'fsdf': 'ewerwr',
'shower': 4,
'thunderstorm': 5,
'fog': 6,
'snow': 7,
}
with self.assertRaises(ValueError):
processor = Word2ClassPreprocessor(check_words_example)
def test_call(self):
check_words_example = {
'sun': 1,
'cloud': 2,
'rain': 3,
'shower': 4,
'thunderstorm': 5,
'fog': 6,
'snow': 7,
}
test_sentence = "great thunderstorm and clouing wind"
processor = Word2ClassPreprocessor(check_words_example)
self.assertEqual(processor(test_sentence), 5)
def test_none_len(self):
with self.assertRaises(IndexError):
processor = Word2ClassPreprocessor({})
def test_wrong_type(self):
with self.assertRaises(TypeError):
processor = Word2ClassPreprocessor(None)
MONGO_DB = 'weather_db_test'
CHECK_WORDS = {
'sun': 1,
'cloud': 2,
'rain': 3,
'shower': 4,
'thunderstorm': 5,
'fog': 6,
'snow': 7,
}
KEY_MAP = {
't_min': (('temperature', 'min'), ),
't_max': (('temperature', 'max'), ),
'class': (('description', ), (Word2ClassPreprocessor(CHECK_WORDS), )),
}
class TestPredModel(unittest.TestCase):
def test_to_vector(self):
s: pandas.Series = pandas.Series(data=[3, 4, 5, 6, 7, 8, 1, 2, 3, 4])
vec = to_vector(s)
self.assertEqual(vec.shape, (len(s), 1))
def test_normalization(self):
vec = numpy.array([2, 2]).reshape((2, 1))
no = reverse_norma(vec)
for v in no:
self.assertEqual(v, 0.5)
key_map_object = {
'temperature_max': (('temperature', 'max'), ),
'temperature_min': (('temperature', 'min'), ),
'feels_temperature_max': (('feels_temperature', 'max'), ),
'feels_temperature_min': (('feels_temperature', 'min'), ),
'pressure_max': (('pressure', 'max'), ),
'pressure_min': (('pressure', 'min'), ),
'humidity_max': (('humidity', 'max'), ),
'humidity_min': (('humidity', 'min'), ),
'precipitation_max': (('precipitation', 'max'), ),
'precipitation_min': (('precipitation', 'min'), ),
'wind_direction_max': (('wind_direction', 'max'), ),
'wind_direction_min': (('wind_direction', 'min'), ),
'wind_speed_max': (('wind_speed', 'max'), ),
'wind_speed_min': (('wind_speed', 'min'), ),
'class': (('description', ), (Word2ClassPreprocessor(
retrieve_check_words(CHECK_WORDS_COLLECTION)), ))
}
if not args.city:
print(
'City name is empty. Please, Honorable Sir, provide it or pass to command line argument --city'
)
elif not args.country:
print(
'Country name is empty. Please, Honorable Sir, provide it or pass to command line argument --country'
)
else:
if args.script.upper() == 'REDUCE':
reduce(args.city, args.country, args.max, args.limit,
key_map_object)
elif args.script.upper() == 'PRODUCE':