def test_best_method_pot(self):
catchment = Catchment("Aberdeen", "River Dee")
catchment.pot_dataset = PotDataset(start_date=date(1999, 1, 1), end_date=date(1999, 12, 31))
catchment.pot_dataset.pot_records = [PotRecord(date(1999, 1, 1), 2.0, 0.5),
PotRecord(date(1999, 12, 31), 1.0, 0.5)]
self.assertAlmostEqual(catchment.qmed(), 1.6696)
def test_record_start_end(self):
catchment = Catchment("Aberdeen", "River Dee")
catchment.amax_records = [AmaxRecord(date(1999, 12, 31), 3.0, 0.5),
AmaxRecord(date(2000, 12, 31), 2.0, 0.5),
AmaxRecord(date(2001, 12, 31), 1.0, 0.5)]
self.assertEqual(catchment.amax_records_start(), 1999)
self.assertEqual(catchment.amax_records_end(), 2001)
def test_pot_2_years(self):
catchment = Catchment("Aberdeen", "River Dee")
catchment.pot_dataset = PotDataset(start_date=date(1998, 1, 1), end_date=date(1999, 12, 31))
catchment.pot_dataset.pot_records = [PotRecord(date(1999, 1, 1), 3.0, 0.5),
PotRecord(date(1999, 2, 1), 2.0, 0.5),
PotRecord(date(1999, 12, 31), 1.0, 0.5)]
self.assertAlmostEqual(QmedAnalysis(catchment).qmed(method='pot_records'), 1.8789, 4)
def test_amax_long_records(self):
catchment = Catchment("Aberdeen", "River Dee")
catchment.amax_records = [AmaxRecord(date(1999, 12, 31), 5.0, 0.5),
AmaxRecord(date(2000, 12, 31), 1.0, 0.5),
AmaxRecord(date(2001, 12, 31), 4.0, 0.5),
AmaxRecord(date(2002, 12, 31), 2.0, 0.5),
AmaxRecord(date(2003, 12, 31), 3.0, 0.5)]
self.assertEqual(QmedAnalysis(catchment).qmed(method='amax_records'), 3)
def test_catchment_distance_no_country(self):
catchment_1 = Catchment("Aberdeen", "River Dee")
catchment_1.descriptors.centroid_ngr = Point(0, 0)
catchment_2 = Catchment("Dundee", "River Tay")
catchment_2.descriptors.centroid_ngr = Point(3000, 4000)
self.assertEqual(catchment_1.distance_to(catchment_2), 5)
def test_catchment_distance_no_country(self):
catchment_1 = Catchment("Aberdeen", "River Dee")
catchment_1.descriptors.centroid_ngr = Point(0, 0)
catchment_2 = Catchment("Dundee", "River Tay")
catchment_2.descriptors.centroid_ngr = Point(3000, 4000)
self.assertEqual(catchment_1.distance_to(catchment_2), 5)
def test_record_start_end(self):
catchment = Catchment("Aberdeen", "River Dee")
catchment.amax_records = [
AmaxRecord(date(1999, 12, 31), 3.0, 0.5),
AmaxRecord(date(2000, 12, 31), 2.0, 0.5),
AmaxRecord(date(2001, 12, 31), 1.0, 0.5)
]
self.assertEqual(catchment.amax_records_start(), 1999)
self.assertEqual(catchment.amax_records_end(), 2001)
def test_similarity_distance_incomplete_descriptors(self):
other_catchment = Catchment(location="Burn A", watercourse="Village B")
other_catchment.id = 999
other_catchment.is_suitable_for_pooling = True
self.db_session.add(other_catchment)
gauged_catchments = CatchmentCollections(self.db_session)
analysis = GrowthCurveAnalysis(self.catchment, gauged_catchments)
self.assertEqual(float('inf'), analysis._similarity_distance(self.catchment, other_catchment))
def test_descriptors_2008_urban_adjustment(self):
catchment = Catchment("Aberdeen", "River Dee")
catchment.descriptors = Descriptors(dtm_area=1,
bfihost=0.50,
sprhost=50,
saar=1000,
farl=1,
urbext2000=1)
self.assertAlmostEqual(QmedAnalysis(catchment, year=2000).urban_adj_factor(), 2.970205798, 4)
def test_catchment_distance_different_country(self):
catchment_1 = Catchment("Aberdeen", "River Dee")
catchment_1.descriptors.centroid_ngr = Point(0, 0)
catchment_2 = Catchment("Belfast")
catchment_2.descriptors.centroid_ngr = Point(3, 4)
catchment_2.country = 'ni'
self.assertEqual(catchment_1.distance_to(catchment_2), float('inf'))
def test_descriptors_1999_2(self):
catchment = Catchment("Aberdeen", "River Dee")
catchment.descriptors = Descriptors(dtm_area=2.345,
bfihost=0,
sprhost=100,
saar=2000,
farl=0.5,
urbext2000=0)
self.assertAlmostEqual(QmedAnalysis(catchment).qmed(method='descriptors_1999'), 0.3729, 4)
def test_add_catchment_with_amax(self):
catchment = Catchment("Aberdeen", "River Dee")
catchment.amax_records = [AmaxRecord(date(1999, 12, 31), 3.0, 0.5),
AmaxRecord(date(2000, 12, 31), 2.0, 0.5),
AmaxRecord(date(2001, 12, 31), 1.0, 0.5)]
self.db_session.add(catchment)
result = self.db_session.query(Catchment).filter_by(location="Aberdeen", watercourse="River Dee").one()
self.assertEqual(catchment, result)
self.assertEqual(catchment.amax_records, result.amax_records)
def test_descriptors_2008_1(self):
catchment = Catchment("Aberdeen", "River Dee")
catchment.descriptors = Descriptors(dtm_area=1,
bfihost=0.50,
sprhost=50,
saar=1000,
farl=1,
urbext2000=0)
self.assertAlmostEqual(QmedAnalysis(catchment).qmed(method='descriptors_2008'), 0.5907, 4)
def test_best_method_pot_over_amax(self):
catchment = Catchment("Aberdeen", "River Dee")
catchment.amax_records = [AmaxRecord(date(1999, 12, 31), 1.0, 0.5),
AmaxRecord(date(2000, 12, 31), 1.0, 0.5)]
catchment.pot_dataset = PotDataset(start_date=date(1998, 1, 1), end_date=date(1999, 12, 31))
catchment.pot_dataset.pot_records = [PotRecord(date(1999, 1, 1), 3.0, 0.5),
PotRecord(date(1999, 2, 1), 2.0, 0.5),
PotRecord(date(1999, 12, 31), 1.0, 0.5)]
self.assertAlmostEqual(catchment.qmed(), 1.8789, 4)
def test_best_method_descriptors(self):
catchment = Catchment("Aberdeen", "River Dee")
catchment.channel_width = 1
catchment.descriptors = Descriptors(dtm_area=1,
bfihost=0.50,
sprhost=50,
saar=1000,
farl=1,
urbext2000=0)
self.assertAlmostEqual(catchment.qmed(), 0.5907, 4)
def test_descriptors_2008_urban(self):
catchment = Catchment("Aberdeen", "River Dee")
catchment.descriptors = Descriptors(dtm_area=1,
bfihost=0.50,
sprhost=50,
saar=1000,
farl=1,
urbext2000=1)
self.assertAlmostEqual(QmedAnalysis(catchment, year=2000).qmed(method='descriptors_2008', as_rural=False),
1.7546, 4)
def test_similarity_distance_incomplete_descriptors(self):
other_catchment = Catchment(location="Burn A", watercourse="Village B")
other_catchment.id = 999
other_catchment.is_suitable_for_pooling = True
self.db_session.add(other_catchment)
gauged_catchments = CatchmentCollections(self.db_session)
analysis = GrowthCurveAnalysis(self.catchment, gauged_catchments)
self.assertEqual(
float('inf'),
analysis._similarity_distance(self.catchment, other_catchment))
def test_find_donors_exclude_urban(self):
other_catchment = Catchment(location="Burn A", watercourse="Village B")
other_catchment.id = 999
other_catchment.is_suitable_for_pooling = True
other_catchment.descriptors = Descriptors(urbext2000=0.031)
self.db_session.add(other_catchment)
gauged_catchments = CatchmentCollections(self.db_session)
analysis = GrowthCurveAnalysis(self.catchment, gauged_catchments)
analysis.find_donor_catchments()
donor_ids = [d.id for d in analysis.donor_catchments]
self.assertEqual([10002, 10001], donor_ids)
def test_add_catchment_with_amax(self):
catchment = Catchment("Aberdeen", "River Dee")
catchment.amax_records = [
AmaxRecord(date(1999, 12, 31), 3.0, 0.5),
AmaxRecord(date(2000, 12, 31), 2.0, 0.5),
AmaxRecord(date(2001, 12, 31), 1.0, 0.5)
]
self.db_session.add(catchment)
result = self.db_session.query(Catchment).filter_by(
location="Aberdeen", watercourse="River Dee").one()
self.assertEqual(catchment, result)
self.assertEqual(catchment.amax_records, result.amax_records)
def test_pot_records_by_month(self):
catchment = Catchment("Aberdeen", "River Dee")
catchment.pot_dataset = PotDataset(start_date=date(1998, 10, 1), end_date=date(2000, 1, 31))
catchment.pot_dataset.pot_records = [PotRecord(date(1999, 1, 1), 3.0, 0.5),
PotRecord(date(1999, 2, 1), 2.0, 0.5),
PotRecord(date(1999, 2, 15), 2.0, 0.5),
PotRecord(date(1999, 12, 31), 1.0, 0.5)]
analysis = QmedAnalysis(catchment)
records_by_month = analysis._pot_month_counts(catchment.pot_dataset)
expected = [2, 1, 1, 1, 1, 1, 1, 1, 1, 2, 2, 2]
result = [len(month) for month in records_by_month]
self.assertEqual(result, expected)
def test_find_donors_exclude_urban(self):
other_catchment = Catchment(location="Burn A", watercourse="Village B")
other_catchment.id = 999
other_catchment.is_suitable_for_pooling = True
other_catchment.descriptors = Descriptors(urbext2000=0.031)
self.db_session.add(other_catchment)
gauged_catchments = CatchmentCollections(self.db_session)
analysis = GrowthCurveAnalysis(self.catchment, gauged_catchments)
analysis.find_donor_catchments()
donor_ids = [d.id for d in analysis.donor_catchments]
self.assertEqual([10002, 10001], donor_ids)
def test_pot_complete_years(self):
catchment = Catchment("Aberdeen", "River Dee")
catchment.pot_dataset = PotDataset(start_date=date(1998, 10, 1), end_date=date(2000, 1, 31))
catchment.pot_dataset.pot_records = [PotRecord(date(1999, 1, 1), 3.0, 0.5),
PotRecord(date(1999, 2, 1), 2.0, 0.5),
PotRecord(date(1999, 2, 15), 2.0, 0.5),
PotRecord(date(1999, 12, 31), 1.0, 0.5)]
analysis = QmedAnalysis(catchment)
records, n = analysis._complete_pot_years(catchment.pot_dataset)
result = [record.date for record in records]
expected = [date(1999, 2, 1),
date(1999, 2, 15),
date(1999, 12, 31)]
self.assertEqual(result, expected)
def test_all(self):
catchment = Catchment("Aberdeen", "River Dee")
catchment.channel_width = 1
catchment.amax_records = [AmaxRecord(date(1999, 12, 31), 1.0, 0.5),
AmaxRecord(date(2000, 12, 31), 1.0, 0.5)]
catchment.descriptors = Descriptors(dtm_area=1,
bfihost=0.50,
sprhost=50,
saar=1000,
farl=1,
urbext2000=0)
qmeds = QmedAnalysis(catchment).qmed_all_methods()
self.assertEqual(qmeds['amax_records'], 1)
self.assertEqual(qmeds['channel_width'], 0.182)
self.assertEqual(qmeds['area'], 1.172)
self.assertAlmostEqual(qmeds['descriptors_1999'], 0.2671, 4)
def nearest_qmed_catchments(self,
subject_catchment,
limit=None,
dist_limit=500):
dist_sq = Catchment.distance_to(subject_catchment).label(
'dist_sq') # Distance squared, calculated using SQL
query = self.db_session.query(Catchment, dist_sq). \
join(Catchment.descriptors). \
filter(Catchment.id != subject_catchment.id, # Exclude subject catchment itself
Catchment.id.in_(self.catchment_ids),
Catchment.country == subject_catchment.country, # SQL dist method does not cover cross-boundary dist
# Within the distance limit
dist_sq <= dist_limit ** 2). \
group_by(Catchment). \
order_by(dist_sq)
if limit:
rows = query[
0:limit] # Each row is tuple of (catchment, distance squared)
else:
rows = query.all()
# Add real `dist` attribute to catchment list using previously calculated SQL dist squared
catchments = []
for row in rows:
catchment = row[0]
catchment.dist = sqrt(row[1])
catchments.append(catchment)
return catchments
def nearest_qmed_catchments(self, subject_catchment, limit=None, dist_limit=500):
dist_sq = Catchment.distance_to(subject_catchment).label('dist_sq') # Distance squared, calculated using SQL
query = self.db_session.query(Catchment, dist_sq). \
join(Catchment.descriptors). \
filter(Catchment.id != subject_catchment.id, # Exclude subject catchment itself
Catchment.id.in_(self.catchment_ids),
Catchment.country == subject_catchment.country, # SQL dist method does not cover cross-boundary dist
# Within the distance limit
dist_sq <= dist_limit ** 2). \
group_by(Catchment). \
order_by(dist_sq)
if limit:
rows = query[0:limit] # Each row is tuple of (catchment, distance squared)
else:
rows = query.all()
# Add real `dist` attribute to catchment list using previously calculated SQL dist squared
catchments = []
for row in rows:
catchment = row[0]
catchment.dist = sqrt(row[1])
catchments.append(catchment)
return catchments
def test_empty_db_tables(self):
db_session = db.Session()
db_session.add(Catchment(location="Aberdeen", watercourse="River Dee"))
db_session.commit()
db.empty_db_tables()
self.assertEqual(self.all_tables,
sorted(list(db.metadata.tables.keys())))
self.assertEqual(db_session.query(Catchment).count(), 0)
db_session.close()
def test_catchment_distance_different_country(self):
catchment_1 = Catchment("Aberdeen", "River Dee")
catchment_1.descriptors.centroid_ngr = Point(0, 0)
catchment_2 = Catchment("Belfast")
catchment_2.descriptors.centroid_ngr = Point(3, 4)
catchment_2.country = 'ni'
self.assertEqual(catchment_1.distance_to(catchment_2), float('inf'))
def setUpClass(cls):
settings.config['nrfa']['oh_json_url'] = \
'file:' + pathname2url(os.path.abspath('./floodestimation/fehdata_test.json'))
cls.db_session = db.Session()
cls.catchment = Catchment("Dundee", "River Tay")
cls.catchment.country = 'gb'
cls.catchment.descriptors = Descriptors(dtm_area=2.345,
bfihost=0.0,
sprhost=100,
saar=2000,
farl=0.5,
urbext2000=0,
fpext=0.2,
centroid_ngr=Point(
276125, 688424))
def test_best_method_order(self):
catchment = Catchment("Aberdeen", "River Dee")
catchment.channel_width = 1
catchment.amax_records = [AmaxRecord(date(1999, 12, 31), 1.0, 0.5),
AmaxRecord(date(2000, 12, 31), 1.0, 0.5)]
catchment.descriptors = Descriptors(dtm_area=1,
bfihost=0.50,
sprhost=50,
saar=1000,
farl=1)
self.assertEqual(catchment.qmed(), 1.0)
def test_best_method_area(self):
catchment = Catchment("Aberdeen", "River Dee")
catchment.descriptors = Descriptors(dtm_area=1)
self.assertEqual(catchment.qmed(), 1.172)
def __init__(self):
self.name = None
self.catchment = Catchment("River Town", "River Burn")
self.db_session = db.Session()
self.gauged_catchments = CatchmentCollections(self.db_session)
self.qmed = None
def test_channel_width_2(self):
catchment = Catchment("Aberdeen", "River Dee")
catchment.channel_width = 2.345
self.assertAlmostEqual(QmedAnalysis(catchment).qmed(method='channel_width'), 0.9839, 4)
def test_amax_rejected_record(self):
catchment = Catchment("Aberdeen", "River Dee")
catchment.amax_records = [AmaxRecord(date(1999, 12, 31), 2.0, 0.5),
AmaxRecord(date(2000, 12, 31), 1.0, 0.5),
AmaxRecord(date(2000, 12, 31), 99.0, 0.5, flag=2)]
self.assertEqual(QmedAnalysis(catchment).qmed(method='amax_records'), 1.5)
def test_channel_width_3(self):
catchment = Catchment("Aberdeen", "River Dee")
catchment.channel_width = 50
self.assertAlmostEqual(QmedAnalysis(catchment).qmed(method='channel_width'), 420.7576, 4)
def test_best_method_none(self):
catchment = Catchment("Aberdeen", "River Dee")
self.assertIsNone(catchment.qmed())
def test_best_method_channel_width(self):
catchment = Catchment("Aberdeen", "River Dee")
catchment.channel_width = 1
self.assertEqual(catchment.qmed(), 0.182)
def test_no_descriptors_1999(self):
catchment = Catchment("Aberdeen", "River Dee")
try:
QmedAnalysis(catchment).qmed(method='descriptors_1999')
except InsufficientDataError as e:
self.assertEqual(str(e), "Catchment `descriptors` attribute must be set first.")
def test_best_method_amax(self):
catchment = Catchment("Aberdeen", "River Dee")
catchment.amax_records = [AmaxRecord(date(1999, 12, 31), 1.0, 0.5),
AmaxRecord(date(2000, 12, 31), 1.0, 0.5)]
self.assertEqual(catchment.qmed(), 1.0)
def test_area_3(self):
catchment = Catchment("Aberdeen", "River Dee")
catchment.descriptors.dtm_area = 100
self.assertAlmostEqual(QmedAnalysis(catchment).qmed(method='area'), 81.2790, 4)
def test_area_2(self):
catchment = Catchment("Aberdeen", "River Dee")
catchment.descriptors.dtm_area = 2.345
self.assertAlmostEqual(QmedAnalysis(catchment).qmed(method='area'), 2.6946, 4)
class TestQmedDonor(unittest.TestCase):
catchment = Catchment("Dundee", "River Tay")
catchment.country = 'gb'
catchment.descriptors = Descriptors(dtm_area=2.345,
bfihost=1e-4,
sprhost=100,
saar=2000,
farl=0.5,
urbext2000=0,
centroid_ngr=Point(276125, 688424))
# QMED descr = 0.61732109
donor_catchment = Catchment("Aberdeen", "River Dee")
donor_catchment.country = 'gb'
donor_catchment.descriptors = Descriptors(dtm_area=1,
bfihost=0.50,
sprhost=50,
saar=1000,
farl=1,
urbext2000=0,
centroid_ngr=Point(276125, 688424))
donor_catchment.amax_records = [AmaxRecord(date(1999, 12, 31), 1.0, 0.5),
AmaxRecord(date(2000, 12, 31), 1.0, 0.5)]
# donor QMED descr = 0.59072777
# donor QMED amax = 1.0
@classmethod
def setUpClass(cls):
settings.config['nrfa']['oh_json_url'] = \
'file:' + pathname2url(os.path.abspath('./floodestimation/fehdata_test.json'))
cls.db_session = db.Session()
@classmethod
def tearDownClass(cls):
db.empty_db_tables()
def tearDown(self):
self.db_session.rollback()
def test_donor_adjustment_factor(self):
# 1.0/0.59072777 = 1.69282714
self.assertAlmostEqual(exp(QmedAnalysis(self.catchment).
_lnqmed_residual(self.donor_catchment)), 1.69282714)
def test_lnqmed_residual_one_donor(self):
# ln(1.0 / 0.59072777)
self.assertAlmostEqual(QmedAnalysis(self.catchment).
_lnqmed_residual(self.donor_catchment), 0.5264, 4)
def test_model_error_corr(self):
# because we're at zero distance, error correlation = 1
self.assertAlmostEqual(QmedAnalysis(self.catchment).
_model_error_corr(self.catchment, self.donor_catchment), 1)
def test_vector_b_one_donor(self):
assert_almost_equal(QmedAnalysis(self.catchment).
_vec_b([self.donor_catchment]), [0.1175])
def test_matrix_sigma_eta_one_donor(self):
result = QmedAnalysis(self.catchment)._matrix_sigma_eta([self.donor_catchment])
assert_almost_equal(result, [[0.1175]])
def test_beta_one_donor(self):
result = QmedAnalysis(self.catchment)._beta(self.donor_catchment)
self.assertAlmostEqual(result, 0.30242554)
def test_matrix_sigma_eps_one_donor(self):
# 4 * 0.30242554**2 / 2 = 0.18292242
result = QmedAnalysis(self.catchment)._matrix_sigma_eps([self.donor_catchment])
assert_almost_equal(result, [[0.18292242]])
def test_matrix_omega_one_donor(self):
# 0.1175 + 0.18292242 = 0.30042242
result = QmedAnalysis(self.catchment)._matrix_omega([self.donor_catchment])
assert_almost_equal(result, [[0.30042242]])
def test_vector_alpha_one_donor(self):
# 1/0.30042242 * 0.1175 = 0.39111595
result = QmedAnalysis(self.catchment)._vec_alpha([self.donor_catchment])
assert_almost_equal(result, [0.39111595])
def test_qmed_one_donor(self):
# 0.61732109 * 1.69282714**0.39111595 = 0.75844685
result = QmedAnalysis(self.catchment).qmed(method='descriptors', donor_catchments=[self.donor_catchment])
self.assertAlmostEqual(result, 0.75844685, places=4)
def test_distance_two_donors(self):
analysis = QmedAnalysis(self.catchment, CatchmentCollections(self.db_session), year=2000)
donors = analysis.find_donor_catchments()[0:2] # 17001, 10001
result = [d.distance_to(self.catchment) for d in donors]
assert_almost_equal(result, [5, 183.8515], decimal=4)
def test_lnqmed_residuals_two_donors(self):
analysis = QmedAnalysis(self.catchment, CatchmentCollections(self.db_session), year=2000)
donors = analysis.find_donor_catchments()[0:2] # 17001, 10001
qmed_amax = [QmedAnalysis(d).qmed() for d in donors]
qmed_descr =[QmedAnalysis(d, year=2000).qmed(method='descriptors') for d in donors]
assert_almost_equal(qmed_amax, [90.532, 50.18]) # not verified
assert_almost_equal(qmed_descr, [51.73180402, 48.70106637]) # not verified
result = [analysis._lnqmed_residual(d) for d in donors]
assert_almost_equal(result, [0.55963062, 0.02991561])
def test_model_error_corr_two_donors(self):
analysis = QmedAnalysis(self.catchment, CatchmentCollections(self.db_session), year=2000)
donors = analysis.find_donor_catchments()[0:2] # 17001, 10001
result = [analysis._model_error_corr(self.catchment, d) for d in donors]
assert_almost_equal(result, [0.352256808, 0.002198921])
def test_model_error_corr_between_two_donors(self):
analysis = QmedAnalysis(self.catchment, CatchmentCollections(self.db_session), year=2000)
donors = analysis.find_donor_catchments()[0:2] # 17001, 10001
dist = donors[0].distance_to(donors[1])
self.assertAlmostEqual(dist, 188.8487072) # not verified
result = analysis._model_error_corr(donors[0], donors[1])
self.assertAlmostEqual(result, 0.001908936)
def test_vector_b_two_donors(self):
analysis = QmedAnalysis(self.catchment, CatchmentCollections(self.db_session), year=2000)
donors = analysis.find_donor_catchments()[0:2] # 17001, 10001
# [0.352256808, 0.002198921] * 0.1175 = [0.041390175, 0.000258373]
result = analysis._vec_b(donors)
assert_almost_equal(result, [0.041390175, 0.000258373])
def test_matrix_sigma_eta_two_donors(self):
analysis = QmedAnalysis(self.catchment, CatchmentCollections(self.db_session), year=2000)
donors = analysis.find_donor_catchments()[0:2] # 17001, 10001
result = analysis._matrix_sigma_eta(donors)
# 0.1175 * 0.001908936 = 0.00022430
assert_almost_equal(result, [[0.1175, 0.00022430],
[0.00022430, 0.1175]])
def test_beta_two_donors(self):
analysis = QmedAnalysis(self.catchment, CatchmentCollections(self.db_session), year=2000)
donors = analysis.find_donor_catchments()[0:2] # 17001, 10001
result = [analysis._beta(d) for d in donors]
assert_almost_equal(result, [0.16351290, 0.20423656])
def test_lnqmed_corr(self):
analysis = QmedAnalysis(self.catchment, CatchmentCollections(self.db_session), year=2000)
donors = analysis.find_donor_catchments()[0:2] # 17001, 10001
results = analysis._lnqmed_corr(donors[0], donors[1])
self.assertAlmostEqual(results, 0.133632774)
def test_matrix_sigma_eps_two_donors(self):
analysis = QmedAnalysis(self.catchment, CatchmentCollections(self.db_session), year=2000)
donors = analysis.find_donor_catchments()[0:2] # 17001, 10001
record0 = [donors[0].amax_records_start(), donors[0].amax_records_end()]
record1 = [donors[1].amax_records_start(), donors[1].amax_records_end()]
self.assertEqual(record0, [1969, 2005]) # n=37
self.assertEqual(record1, [1939, 1984]) # n=46, 16 years overlapping
result = analysis._matrix_sigma_eps(donors)
# 4 * 0.16351290**2 / 37 = 0.00289043
# 4 * 0.16351290 * 0.20423656 * 16 / 37 / 46 * 0.133632774 = 0.00016781
# 4 * 0.20423656**2 / 46 = 0.00362718
assert_almost_equal(result, [[0.00289043, 0.00016781],
[0.00016781, 0.00362718]])
def test_matrix_omega_two_donors(self):
analysis = QmedAnalysis(self.catchment, CatchmentCollections(self.db_session), year=2000)
donors = analysis.find_donor_catchments()[0:2] # 17001, 10001
result = analysis._matrix_omega(donors)
assert_almost_equal(result, [[0.12039043, 0.00039211],
[0.00039211, 0.12112718]])
def test_vector_alpha_two_donors(self):
analysis = QmedAnalysis(self.catchment, CatchmentCollections(self.db_session), year=2000)
donors = analysis.find_donor_catchments()[0:2] # 17001, 10001
result = analysis._vec_alpha(donors)
assert_almost_equal(result, [0.34379622, 0.00102012]) # calculated in Excel
def test_qmed_two_donors(self):
analysis = QmedAnalysis(self.catchment, CatchmentCollections(self.db_session), year=2000)
donors = analysis.find_donor_catchments()[0:2] # 17001, 10001
result = analysis.qmed(method='descriptors', donor_catchments=donors)
# exp(ln(0.61732109) + 0.34379622 * 0.55963062 + 0.00102012 * 0.02991561) =
# exp(ln(0.61732109) + 0.192429411) = 0.748311028
self.assertAlmostEqual(result, 0.748311028, places=5)
def test_unsupported_method(self):
catchment = Catchment("Aberdeen", "River Dee")
try:
QmedAnalysis(catchment).qmed(method='abc')
except AttributeError as e:
self.assertEqual(str(e), "Method `abc` to estimate QMED does not exist.")
