def test_ghg_len_yearly(self):
idx = pd.date_range('20000101', '20550101', freq='d')
s = pd.Series(np.ones(len(idx)), index=idx)
ml = Model(s)
ml.freq = 'D'
v = ml.stats.ghg(key='observations', output='yearly')
assert len(v) == 55
def test_glg(self):
idx = pd.date_range('20000101', '20550101', freq='d')
s = pd.Series([x.month + x.day for x in idx], index=idx)
ml = Model(s)
ml.freq = 'D'
v = ml.stats.glg(key='observations')
assert v == 16.
def test_ghg(self):
idx = pd.to_datetime(['20160114', '20160115', '20160128', '20160214'])
s = pd.Series([10., 3., 30., 20], index=idx)
ml = Model(s)
ml.freq = 'D'
v = ml.stats.ghg(key='observations')
assert v == 20.
def test_ghg_linear(self):
idx = pd.to_datetime(['20160113', '20160115'])
s = pd.Series([0., 10.], index=idx)
ml = Model(s)
ml.freq = 'D'
v = ml.stats.ghg(key='observations', fill_method='linear')
assert v == 5.
def test_q_gvg_nan(self):
idx = pd.to_datetime(['20160820', '20160901', '20161120'])
s = pd.Series([0, 5, 10], index=idx)
ml = Model(s)
ml.freq = 'D'
v = ml.stats.q_gvg(key='observations')
assert np.isnan(v)
def test_q_gvg(self):
idx = pd.to_datetime(['20160320', '20160401', '20160420'])
s = pd.Series([0, 5, 10], index=idx)
ml = Model(s)
ml.freq = 'D'
v = ml.stats.q_gvg(key='observations')
assert v == 2.5
def test_q_gxg_nan(self):
idx = pd.date_range('20160101', freq='d', periods=3)
s = pd.Series([1, 3, np.nan], index=idx)
ml = Model(s)
ml.freq = 'D'
v = ml.stats.q_ghg(key='observations', q=.5)
assert v == 2.
def test_q_glg(self):
n = 101
idx = pd.date_range('20160101', freq='d', periods=n)
s = pd.Series(np.arange(n), index=idx)
ml = Model(s)
ml.freq = 'D'
v = ml.stats.q_glg(key='observations', q=.06)
assert v == 6.
def test_gvg(self):
idx = pd.to_datetime(['20170314', '20170328', '20170414', '20170428'])
s = pd.Series([1., 2., 3., 4], index=idx)
ml = Model(s)
ml.freq = 'D'
v = ml.stats.gvg(key='observations',
fill_method='linear',
output='mean')
assert v == 2.
def test_glg_fill_limit_null(self):
idx = pd.to_datetime(['20170101', '20170131', '20200101'])
s = pd.Series(np.ones(len(idx)), index=idx)
ml = Model(s)
ml.freq = 'D'
v = ml.stats.glg(key='observations',
fill_method='linear',
limit=10,
output='yearly')
assert v.count() == 0
def test_gvg_nan(self):
idx = pd.to_datetime(['20170228', '20170428', '20170429'])
s = pd.Series([1., 2., 3.], index=idx)
ml = Model(s)
ml.freq = 'D'
v = ml.stats.gvg(
key='observations',
fill_method=None,
output='mean',
)
assert np.isnan(v)
def test_q_gxg_series(self):
s = pd.read_csv('tests/data/hseries_gxg.csv', index_col=0, header=0,
parse_dates=True, dayfirst=True,
squeeze=True,)
ml = Model(s)
ml.freq = 'D'
ghg = ml.stats.q_ghg(key='observations')
glg = ml.stats.q_glg(key='observations')
gvg = ml.stats.q_gvg(key='observations')
print('\n')
print('calculated GXG\'s percentile method: \n')
print(('GHG: {ghg:.2f} m+NAP\n'
'GLG: {glg:.2f} m+NAP\n'
'GVG: {gvg:.2f} m+NAP\n').format(
ghg=ghg, glg=glg, gvg=gvg))
print('Menyanthes GXG\'s: \n')
print(('GHG: {ghg:.2f} m+NAP\n'
'GLG: {glg:.2f} m+NAP\n'
'GVG: {gvg:.2f} m+NAP\n').format(
ghg=-3.23, glg=-3.82, gvg=-3.43))