def test_catchment_by_number(self):
expected = loaders.from_file('floodestimation/tests/data/17002.CD3')
self.db_session.add(expected)
result = CatchmentCollections(
self.db_session).catchment_by_number(17002)
self.assertIs(expected, result)
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_nearest_catchments(self):
subject_catchment = loaders.from_file(
'floodestimation/tests/data/17002.CD3')
catchments = CatchmentCollections(
self.db_session).nearest_qmed_catchments(subject_catchment)
result = [catchment.id for catchment in catchments]
expected = [17001, 10001, 10002]
self.assertEqual(expected, result)
def test_most_similar_catchments(self):
subject_catchment = loaders.from_file('floodestimation/tests/data/17002.CD3')
# Dummy similarity distance function
function = lambda c1, c2: abs(c2.descriptors.altbar - c1.descriptors.altbar)
catchments = CatchmentCollections(self.db_session).most_similar_catchments(subject_catchment, function)
result = [c.id for c in catchments]
expected = [10001, 10002]
self.assertEqual(expected, result)
def test_most_similar_catchments_excl_rejected_amax(self):
subject_catchment = loaders.from_file('floodestimation/tests/data/17002.CD3')
# Dummy similarity distance function
function = lambda c1, c2: abs(c2.descriptors.bfihost - c1.descriptors.bfihost)
catchments = CatchmentCollections(self.db_session).most_similar_catchments(subject_catchment, function,
records_limit=36)
result = [c.id for c in catchments]
expected = [10002, 10001]
self.assertEqual(expected, result)
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_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_l_cv_and_skew(self):
gauged_catchments = CatchmentCollections(self.db_session)
catchment = from_file('floodestimation/tests/data/37017.CD3')
analysis = GrowthCurveAnalysis(catchment, gauged_catchments)
var, skew = analysis._var_and_skew(catchment)
self.assertAlmostEqual(var, 0.2232, places=4)
self.assertAlmostEqual(skew, -0.0908, places=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_incl_subject_catchment(self):
# Subject catchment not in db
subject_catchment = loaders.from_file('floodestimation/tests/data/37017.CD3')
# Dummy similarity distance function
function = lambda c1, c2: abs(c2.descriptors.altbar - c1.descriptors.altbar)
catchments = CatchmentCollections(self.db_session).most_similar_catchments(subject_catchment, function,
include_subject_catchment='force')
result = [c.id for c in catchments]
expected = [37017, 10002, 10001]
self.assertEqual(expected, result)
self.assertEqual(catchments[0].similarity_dist, 0)
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_invalid_subj_catchment_option(self):
subject_catchment = loaders.from_file(
'floodestimation/tests/data/17002.CD3')
# Dummy similarity distance function
function = lambda c1, c2: abs(c2.descriptors.altbar - c1.descriptors.
altbar)
self.assertRaises(ValueError,
CatchmentCollections(
self.db_session).most_similar_catchments,
subject_catchment,
function,
include_subject_catchment='invalid')
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_incl_subject_catchment_updated(self):
# Subject catchment in db
subject_catchment = loaders.from_file('floodestimation/tests/data/201002.CD3')
subject_catchment.location = "Updated location name"
# Dummy similarity distance function
function = lambda c1, c2: abs(c2.descriptors.altbar - c1.descriptors.altbar)
catchments = CatchmentCollections(self.db_session).most_similar_catchments(subject_catchment, function,
include_subject_catchment='force')
result = [c.id for c in catchments]
expected = [201002, 10001, 10002]
self.assertEqual(expected, result)
self.assertEqual(catchments[0].location, "Updated location name")
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_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_single_site_gev(self):
gauged_catchments = CatchmentCollections(self.db_session)
catchment = from_file('floodestimation/tests/data/37017.CD3')
analysis = GrowthCurveAnalysis(catchment, gauged_catchments)
dist_func = analysis.growth_curve(method='single_site', distr='gev')
self.assertAlmostEqual(dist_func(0.5), 1)
def test_catchment_by_number_not_exist(self):
result = CatchmentCollections(
self.db_session, load_data='manual').catchment_by_number(99)
self.assertIsNone(result)
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_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_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_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_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_find_donors(self):
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 nrfa_qmed_catchments(db_session):
return db_session.query(Catchment).join(Descriptors).join(Catchment.amax_records). \
filter(Catchment.is_suitable_for_qmed,
Descriptors.centroid_ngr != None,
or_(Descriptors.urbext2000 < 0.03, Descriptors.urbext2000 == None)). \
group_by(Catchment). \
having(func.count(AmaxRecord.catchment_id) >= 10). \
all()
if __name__ == '__main__':
db_session = db.Session()
science_report_collections = ScienceReportCollections(db_session)
feh_catchments_collections = CatchmentCollections(db_session)
subject_catchments = science_report_collections.all_catchments()
print("Total number of catchments: {}".format(len(subject_catchments)))
with open('output.txt', mode='w') as output_file:
for i, catchment in enumerate(subject_catchments):
print(i, catchment.id)
#output = analyse_catchment(catchment, feh_catchments_collections)
output = analyse_catchment(catchment, science_report_collections)
output_file.write(
"{id}, {qmed_amax}, {qmed_descr}, {qmed_descr_idw}, {qmed_descr_first}, {qmed_descr_1999}, {qmed_descr_idw3}\n"
.format(**output))
db_session.close()
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])
from floodestimation.loaders import load_catchment
from floodestimation import db
from floodestimation.collections import CatchmentCollections
from floodestimation.analysis import QmedAnalysis
db_session = db.Session()
dee_catchment = load_catchment('nith_cds.cd3')
gauged_catchments = CatchmentCollections(db_session)
qmed_analysis = QmedAnalysis(dee_catchment, gauged_catchments)
print(qmed_analysis.qmed())
print(qmed_analysis.methods)
print(qmed_analysis.qmed_all_methods())
print(qmed_analysis.urban_adj_factor())
print(qmed_analysis.find_donor_catchments(5, 200.0))
qmed_analysis.idw_power = 1.5
print(qmed_analysis.idw_power)
donors = qmed_analysis.find_donor_catchments(5, 200.0)
for donor in donors:
Q = QmedAnalysis(donors[0], gauged_catchments)
print(donor, qmed_analysis._error_correlation(donor), Q.qmed_all_methods())
db_session.close()
def _load_data(self):
self.results['report_date'] = date.today()
self.results['catchment'] = self.catchment
self.gauged_catchments = CatchmentCollections(self.db_session,
load_data='manual')
def __init__(self, parent, p):
wx.Panel.__init__(self, parent)
self.p = p
db_session = db.Session()
self.gauged_catchments = CatchmentCollections(db_session)
self.qmed_analysis = QmedAnalysis(config.target_catchment,
self.gauged_catchments)
db_session.close()
self.qmed_method = 'best'
self.donor_search_criteria_refreshed = True
self.suggested_donors = None
self.adopted_donors = None
self.keep_rural = False
config.analysis.catchment.pot_records = None
self.adoptedQmed = '-'
self.calc_obs_amax_btn = wx.Button(self, -1, ' AMAX SERIES ')
self.calc_obs_amax_btn.Bind(wx.EVT_BUTTON, self.amax_area)
self.calc_obs_pot_btn = wx.Button(self, -1, ' POT SERIES ')
self.calc_obs_pot_btn.Bind(wx.EVT_BUTTON, self.pot_area)
self.refresh_calcs_btn = wx.Button(self, -1, ' REFRESH CALCS ')
self.qmed_notes = wx.TextCtrl(self,
-1,
"Notes on QMED",
size=(350, 150),
style=wx.TE_MULTILINE)
self.qmed_2008_label = wx.StaticText(self, -1, "QMED CDS 2008")
self.qmed_1999_label = wx.StaticText(self, -1, "QMED CDS 1999")
self.qmed_area_label = wx.StaticText(self, -1, "QMED AREA")
self.qmed_amax_label = wx.StaticText(self, -1, "QMED AMAX")
self.qmed_pot_label = wx.StaticText(self, -1, "QMED POT")
self.qmed_width_label = wx.StaticText(self, -1, "QMED Channel width")
self.user_qmed_label = wx.StaticText(self, -1, "User QMED")
self.selected_unadj_qmed_label = wx.StaticText(self, -1,
"Selected rural QMED")
self.station_search_distance_label = wx.StaticText(
self, -1, "Station search distance")
self.station_search_limit_label = wx.StaticText(
self, -1, "Station search limit")
self.idw_label = wx.StaticText(self, -1, "IDW")
self.selected_unadj_qmed = wx.TextCtrl(self,
-1,
"-",
style=wx.TE_READONLY)
self.qmed_cds2008 = wx.TextCtrl(self, -1, "-", style=wx.TE_READONLY)
self.qmed_cds1999 = wx.TextCtrl(self, -1, "-", style=wx.TE_READONLY)
self.qmed_areaOnly = wx.TextCtrl(self, -1, "-", style=wx.TE_READONLY)
self.qmed_obs_amax = wx.TextCtrl(self, -1, "-", style=wx.TE_READONLY)
self.qmed_obs_pot = wx.TextCtrl(self, -1, "-", style=wx.TE_READONLY)
self.qmed_geom = wx.TextCtrl(self, -1, "-", style=wx.TE_READONLY)
self.qmed_user = wx.TextCtrl(self, -1, "-")
self.rb1 = wx.RadioButton(self, -1, '', style=wx.RB_GROUP)
self.rb2 = wx.RadioButton(self, -1, '')
self.rb3 = wx.RadioButton(self, -1, '')
self.rb4 = wx.RadioButton(self, -1, '')
self.rb5 = wx.RadioButton(self, -1, '')
self.rb6 = wx.RadioButton(self, -1, '')
self.rb7 = wx.RadioButton(self, -1, '')
self.Bind(wx.EVT_RADIOBUTTON, self.SetVal, id=self.rb1.GetId())
self.Bind(wx.EVT_RADIOBUTTON, self.SetVal, id=self.rb2.GetId())
self.Bind(wx.EVT_RADIOBUTTON, self.SetVal, id=self.rb3.GetId())
self.Bind(wx.EVT_RADIOBUTTON, self.SetVal, id=self.rb4.GetId())
self.Bind(wx.EVT_RADIOBUTTON, self.SetVal, id=self.rb5.GetId())
self.Bind(wx.EVT_RADIOBUTTON, self.SetVal, id=self.rb6.GetId())
self.Bind(wx.EVT_RADIOBUTTON, self.SetVal, id=self.rb7.GetId())
self.station_search_distance = wx.TextCtrl(self, -1, "500.0")
self.station_limit = wx.TextCtrl(self, -1, "5")
self.idw_weight = wx.TextCtrl(self, -1, "3")
self.station_search_distance.Bind(wx.EVT_TEXT,
self.UpdateDonorCriteria)
self.station_limit.Bind(wx.EVT_TEXT, self.UpdateDonorCriteria)
#self.calcQMeds()
self.distance_decay_update = wx.RadioButton(self,
-1,
"Decaying with distance",
style=wx.RB_GROUP)
self.direct_transfer_update = wx.RadioButton(self, -1,
'Equal weighting')
self.dont_update = wx.RadioButton(self, -1, "Don't update")
#self.Bind(wx.EVT_RADIOBUTTON, self.SetUpdate, id=self.dont_update.GetId())
#self.Bind(wx.EVT_RADIOBUTTON, self.SetUpdate, id=self.distance_decay_update.GetId())
#self.Bind(wx.EVT_RADIOBUTTON, self.SetUpdate, id=self.direct_transfer_update.GetId())
self.local_qmed_adjustment_label = wx.StaticText(
self, -1, "Local QMED adjustment")
self.locally_adjusted_qmed_label = wx.StaticText(
self, -1, "Locally adjusted QMED")
self.locally_adjusted_qmed = wx.TextCtrl(self,
-1,
"-",
style=wx.TE_READONLY)
self.local_qmed_adjustment = wx.TextCtrl(self,
-1,
"-",
style=wx.TE_READONLY)
self.update_for_urb_chk = wx.CheckBox(self, -1,
'Update for urbanisation')
self.update_for_urb_chk.Bind(wx.EVT_CHECKBOX,
self.SetUrbanChk,
id=self.update_for_urb_chk.GetId())
self.urban_expansion_factor_label = wx.StaticText(
self, -1, "Urban expansion factor")
self.adjusted_urbext_label = wx.StaticText(self, -1, "Adjusted URBEXT")
self.urban_adjustment_factor_label = wx.StaticText(
self, -1, "Urban adjustment factor")
self.urban_expansion_factor = wx.TextCtrl(self,
-1,
"-",
style=wx.TE_READONLY)
self.adjusted_urbext = wx.TextCtrl(self, -1, "-", style=wx.TE_READONLY)
self.urban_adjustment_factor = wx.TextCtrl(self,
-1,
"-",
style=wx.TE_READONLY)
self.adopted_qmed_label = wx.StaticText(self, -1, "Adopted QMED")
self.adopted_qmed = wx.TextCtrl(self, -1, "-", style=wx.TE_READONLY)
sizer = wx.GridBagSizer(vgap=5, hgap=10)
sizer.Add(self.calc_obs_amax_btn, pos=(7, 3))
sizer.Add(self.calc_obs_pot_btn, pos=(7, 4))
sizer.Add(self.refresh_calcs_btn, pos=(0, 3))
sizer.Add(self.qmed_notes, pos=(1, 3), span=(5, 3))
sizer.Add(self.qmed_2008_label, pos=(0, 0))
sizer.Add(self.qmed_1999_label, pos=(1, 0))
sizer.Add(self.qmed_area_label, pos=(2, 0))
sizer.Add(self.qmed_amax_label, pos=(3, 0))
sizer.Add(self.qmed_pot_label, pos=(4, 0))
sizer.Add(self.qmed_width_label, pos=(5, 0))
sizer.Add(self.user_qmed_label, pos=(6, 0))
sizer.Add(self.selected_unadj_qmed_label, pos=(7, 0))
sizer.Add(self.qmed_cds2008, pos=(0, 1))
sizer.Add(self.qmed_cds1999, pos=(1, 1))
sizer.Add(self.qmed_areaOnly, pos=(2, 1))
sizer.Add(self.qmed_obs_amax, pos=(3, 1))
sizer.Add(self.qmed_obs_pot, pos=(4, 1))
sizer.Add(self.qmed_geom, pos=(5, 1))
sizer.Add(self.qmed_user, pos=(6, 1))
sizer.Add(self.selected_unadj_qmed, pos=(7, 1))
sizer.Add(self.rb1, pos=(0, 2))
sizer.Add(self.rb2, pos=(1, 2))
sizer.Add(self.rb3, pos=(2, 2))
sizer.Add(self.rb4, pos=(3, 2))
sizer.Add(self.rb5, pos=(4, 2))
sizer.Add(self.rb6, pos=(5, 2))
sizer.Add(self.rb7, pos=(6, 2))
self.table = wx.Panel(self, -1)
self.list = CheckListCtrl(self.table)
self.list.InsertColumn(0, 'STATION')
self.list.InsertColumn(1, 'DISTANCE')
self.list.InsertColumn(2, 'ADJUSTMENT FACTOR')
self.list.InsertColumn(3, 'ERROR CORRELATION')
self.list.InsertColumn(4, 'WEIGHT')
self.list.SetColumnWidth(0, 250)
self.list.SetColumnWidth(1, 100)
self.list.SetColumnWidth(2, 100)
self.list.SetColumnWidth(3, 100)
self.list.SetColumnWidth(4, 100)
sizer.Add(self.table, pos=(9, 0), span=(1, 6), flag=wx.EXPAND)
sizer.Add(self.station_search_distance_label, pos=(10, 0), span=(1, 1))
sizer.Add(self.station_search_distance, pos=(10, 1), span=(1, 1))
sizer.Add(self.station_search_limit_label, pos=(10, 2), span=(1, 1))
sizer.Add(self.station_limit, pos=(10, 3), span=(1, 1))
sizer.Add(self.idw_label, pos=(10, 4), span=(1, 1))
sizer.Add(self.idw_weight, pos=(10, 5), span=(1, 1))
sizer.Add(self.dont_update, pos=(11, 0), span=(1, 2))
sizer.Add(self.distance_decay_update, pos=(12, 0), span=(1, 2))
sizer.Add(self.direct_transfer_update, pos=(13, 0), span=(1, 2))
sizer.Add(self.local_qmed_adjustment_label, pos=(12, 2), span=(1, 1))
sizer.Add(self.local_qmed_adjustment, pos=(12, 3), span=(1, 1))
sizer.Add(self.locally_adjusted_qmed_label, pos=(13, 2), span=(1, 1))
sizer.Add(self.locally_adjusted_qmed, pos=(13, 3), span=(1, 1))
sizer.Add(self.update_for_urb_chk, pos=(15, 0), span=(1, 1))
sizer.Add(self.urban_expansion_factor, pos=(16, 1), span=(1, 1))
sizer.Add(self.adjusted_urbext, pos=(17, 1), span=(1, 1))
sizer.Add(self.urban_adjustment_factor, pos=(18, 1), span=(1, 1))
sizer.Add(self.urban_expansion_factor_label, pos=(16, 0), span=(1, 1))
sizer.Add(self.adjusted_urbext_label, pos=(17, 0), span=(1, 1))
sizer.Add(self.urban_adjustment_factor_label, pos=(18, 0), span=(1, 1))
sizer.Add(self.adopted_qmed_label, pos=(18, 4), span=(1, 1))
sizer.Add(self.adopted_qmed, pos=(18, 5), span=(1, 1))
# Assign actions to buttons
self.refresh_calcs_btn.Bind(wx.EVT_BUTTON, self.onRefresh)
border = wx.BoxSizer()
border.Add(sizer, 0, wx.ALL, 20)
self.SetSizerAndFit(border)
self.Fit()