def test_get_LDC_2d():
a = np.random.rand(8760, 4)
a = make_timeseries(a, freq='h')
b = get_LDC(a)
assert np.isclose(np.nansum(b[1]), np.nansum(a))
# check monotonicity
assert np.all(np.diff(b[1].sum(1)) < 0)
def test_get_LDC_not_annual():
a = np.random.rand(10000)
a = make_timeseries(a, freq='h')
b = get_LDC(a)
assert np.isclose(b[1].sum(), a.sum())
#check monotonicity
assert np.all(np.diff(b[1]) < 0)
def test_get_stats():
a = np.ones(8760)
a = make_timeseries(a, freq='h')
b = get_load_stats(a)
assert a.sum() == b.loc['Sum'].squeeze()
assert np.asarray(b.loc['Ramps (98%)'])[0] == (0,0)
assert np.isclose(0, b.loc['Trend'].squeeze())
assert 1 == b.loc['Load Factor (peakiness)'].squeeze()
def test_disag_hourly_to_minutes(self):
x = np.arange(0, 8760)
y = (np.cos(2 * np.pi / 8759 * x) * 50 + 100)
y = make_timeseries(y, freq='h')
disag_profile = np.random.rand(60)
y_disag = disag_upsample(y, disag_profile, to_offset='t')
assert np.isclose(np.sum(y_disag),
np.sum(y)) # <= 0.001 #FIXME: np test equality
assert len(y_disag) == 8760 * 60
def test_disag_daily_to_hourly(self):
x = np.arange(0, 365)
y = (np.cos(2 * np.pi / 364 * x) * 50 + 100)
y = make_timeseries(y, freq='d')
disag_profile = np.random.rand(24)
y_disag = disag_upsample(y, disag_profile)
assert np.isclose(np.sum(y_disag),
np.sum(y)) # <= 0.001 #FIXME: np test equality
assert len(y_disag) == 8760
def test_reshape_multiannual_dataframe():
a = np.random.rand(8760*2)
a = pd.DataFrame(make_timeseries(a, year=2019, freq='h'))
b = reshape_timeseries(a, x='dayofyear', y='hour', aggfunc='sum')
assert b.shape == (24,365)
assert np.isclose(b.sum().sum(), a.sum())
def test_ndarray_h(self):
a = np.random.rand(8760)
b = make_timeseries(a)
assert isinstance(b, pd.Series)
assert sum(a) == sum(b)
def test_multiannual_timeseries(self):
a = np.random.rand(8760*2)
b = make_timeseries(a, freq='h')
assert isinstance(b, pd.Series)
assert sum(a) == sum(b)
def test_empty_frame_to_indexed_empty(self):
b = make_timeseries(freq='H', length=8760)
assert isinstance(b, pd.Series) and len(b) == 8760
def test_2d_ndarray(self):
a = np.random.rand(8760,5)
b = make_timeseries(a)
assert type(b) == pd.DataFrame
def test_pddataframe_2d(self):
a = pd.DataFrame(np.random.rand(35040,3))
b = make_timeseries(a)
assert type(b) == pd.DataFrame
def test_pddataframe(self):
a = pd.DataFrame(np.random.rand(8760))
b = make_timeseries(a)
assert type(b) == pd.DataFrame
def test_pdseries(self):
a = pd.Series(np.random.rand(8760))
b = make_timeseries(a)
assert isinstance(b, pd.Series)
assert sum(a) == sum(b)
def test_ndarray_x(self):
a = np.random.rand(8730)
b = make_timeseries(a, freq='H')
assert isinstance(b, pd.Series)
assert sum(a) == sum(b)
def test_reshape_multiannual():
a = np.random.rand(8760 * 2)
a = make_timeseries(a, freq='h')
b = reshape_timeseries(a, x='dayofyear', y='hour', aggfunc='sum')
assert b.shape == (24, 365)
assert np.isclose(b.sum().sum(), a.sum())
def test_empty_frame(self):
a = np.array([])
b = make_timeseries(a, freq='H')
assert type(b) == pd.Series and len(b)==0
def test_get_stats_df():
a = np.ones(8760)
a = make_timeseries(a, freq='h').to_frame()
b = get_load_stats(a)
assert a.sum().sum() == b.loc['Sum'].squeeze()
def test_countweekend_days_per_month():
a = make_timeseries(year=2015, length=8760, freq='h')
b = countweekend_days_per_month(a.resample('d').mean())
assert len(b) == 12
assert sum(b) == 104 #weekend days in 2015
