def random_tmax_tmin_setup(length, tasmax_series, tasmin_series):
max_values = np.random.uniform(-20, 40, length)
min_values = []
for i in range(length):
min_values.append(np.random.uniform(-40, max_values[i]))
tasmax = tasmax_series(np.add(max_values, K2C))
tasmin = tasmin_series(np.add(min_values, K2C))
return tasmax, tasmin
def test_one_nan_day(self, tasmin_series):
a = np.zeros(365) + K2C + 5.0
a[2] -= 20
a[-1] = np.nan
ts = tasmin_series(a)
out = atmos.consecutive_frost_days(ts)
np.testing.assert_array_equal(out, [np.nan])
def test_convert_units_freeze_day(self, tasmin_series):
a = np.zeros(365) + 5.0
a[2:5] -= 20
a[6:10] -= 20
ts = tasmin_series(a)
ts.attrs['units'] = 'C'
out = atmos.consecutive_frost_days(ts)
np.testing.assert_array_equal(out, [4])
def test_uniform_freeze_thaw_cycles(self, tasmax_series, tasmin_series):
temp_values = np.zeros(365)
tasmax, tasmin = (
tasmax_series(temp_values + 5 + K2C),
tasmin_series(temp_values - 5 + K2C),
)
ft = xci.daily_freezethaw_cycles(tasmax, tasmin, freq="YS")
np.testing.assert_array_equal([np.sum(ft)], [365])
def test_1d(self, tasmax_series, tasmin_series):
tn1 = np.zeros(366)
tx1 = np.zeros(366)
tn1[:10] = np.array([20, 23, 23, 23, 23, 21, 23, 23, 23, 23])
tx1[:10] = np.array([29, 31, 31, 31, 29, 31, 31, 31, 31, 31])
tn = tasmin_series(tn1 + K2C, start="1/1/2000")
tx = tasmax_series(tx1 + K2C, start="1/1/2000")
tnC = tasmin_series(tn1, start="1/1/2000")
tnC.attrs["units"] = "C"
txC = tasmax_series(tx1, start="1/1/2000")
txC.attrs["units"] = "C"
hwf = atmos.heat_wave_max_length(tn,
tx,
thresh_tasmin="22 C",
thresh_tasmax="30 C")
hwfC = atmos.heat_wave_max_length(tnC,
txC,
thresh_tasmin="22 C",
thresh_tasmax="30 C")
np.testing.assert_array_equal(hwf, hwfC)
np.testing.assert_allclose(hwf.values[:1], 4)
hwf = atmos.heat_wave_max_length(tn,
tx,
thresh_tasmin="20 C",
thresh_tasmax="30 C",
window=4)
np.testing.assert_allclose(hwf.values[:1], 5)
# one long hw
hwf = atmos.heat_wave_max_length(tn,
tx,
thresh_tasmin="10 C",
thresh_tasmax="10 C")
np.testing.assert_allclose(hwf.values[:1], 10)
# no hw
hwf = atmos.heat_wave_max_length(tn,
tx,
thresh_tasmin="40 C",
thresh_tasmax="40 C")
np.testing.assert_allclose(hwf.values[:1], 0)
def test_season(self, tasmin_series):
ts = tasmin_series(np.zeros(360))
miss = checks.missing_any(ts, freq="YS", season="MAM")
np.testing.assert_equal(miss, [False])
miss = checks.missing_any(ts, freq="YS", season="JJA")
np.testing.assert_array_equal(miss, [True, True])
miss = checks.missing_any(ts, freq="YS", season="SON")
np.testing.assert_equal(miss, [False])
def test_1d(self, tasmax_series, tasmin_series):
tn1 = np.zeros(366)
tx1 = np.zeros(366)
tn1[:10] = np.array([20, 23, 23, 23, 23, 21, 23, 23, 23, 23])
tx1[:10] = np.array([29, 31, 31, 31, 29, 31, 31, 31, 31, 31])
tn = tasmin_series(tn1 + K2C, start='1/1/2000')
tx = tasmax_series(tx1 + K2C, start='1/1/2000')
tnC = tasmin_series(tn1, start='1/1/2000')
tnC.attrs['units'] = 'C'
txC = tasmax_series(tx1, start='1/1/2000')
txC.attrs['units'] = 'C'
hwf = atmos.heat_wave_max_length(tn,
tx,
thresh_tasmin='22 C',
thresh_tasmax='30 C')
hwfC = atmos.heat_wave_max_length(tnC,
txC,
thresh_tasmin='22 C',
thresh_tasmax='30 C')
np.testing.assert_array_equal(hwf, hwfC)
np.testing.assert_allclose(hwf.values[:1], 4)
hwf = atmos.heat_wave_max_length(tn,
tx,
thresh_tasmin='20 C',
thresh_tasmax='30 C',
window=4)
np.testing.assert_allclose(hwf.values[:1], 5)
# one long hw
hwf = atmos.heat_wave_max_length(tn,
tx,
thresh_tasmin='10 C',
thresh_tasmax='10 C')
np.testing.assert_allclose(hwf.values[:1], 10)
# no hw
hwf = atmos.heat_wave_max_length(tn,
tx,
thresh_tasmin='40 C',
thresh_tasmax='40 C')
np.testing.assert_allclose(hwf.values[:1], 0)
def test_1d(self, tasmax_series, tasmin_series):
tn = tasmin_series(np.asarray([20, 23, 23, 23, 23, 22, 23, 23, 23, 23]) + K2C)
tx = tasmax_series(np.asarray([29, 31, 31, 31, 29, 31, 31, 31, 31, 31]) + K2C)
wmmtf = xci.tx_tn_days_above(tn, tx)
np.testing.assert_allclose(wmmtf.values, [7])
wmmtf = xci.tx_tn_days_above(tn, tx, thresh_tasmax="50 C")
np.testing.assert_allclose(wmmtf.values, [0])
wmmtf = xci.tx_tn_days_above(tn, tx, thresh_tasmax="0 C", thresh_tasmin="0 C")
np.testing.assert_allclose(wmmtf.values, [10])
def test_nan_presence(self, tasmin_series):
i = 3650
A = 10.
tn = np.zeros(i) + K2C + A * np.sin(np.arange(i) / 365. * 2 * np.pi) + .1 * np.random.rand(i)
tn[10:20] -= 2
tn[9] = np.nan
tn = tasmin_series(tn)
tn10 = percentile_doy(tn, per=.1)
out = temp.cold_spell_duration_index(tn, tn10, freq='AS-JUL')
assert np.isnan(out[0])
def test_convert_units(self, tasmin_series):
i = 3650
A = 10.
tn = np.zeros(i) + A * np.sin(np.arange(i) / 365. * 2 * np.pi) + .1 * np.random.rand(i)
tn[10:20] -= 2
tn = tasmin_series(tn + K2C)
tn.attrs['units'] = 'C'
tn10 = percentile_doy(tn, per=.1)
out = temp.cold_spell_duration_index(tn, tn10, freq='AS-JUL')
assert out[0] == 10
def test_simple(self, tasmin_series):
a = np.zeros(365)
a[:6] -= [27, 28, 29, 30, 31, 32] # 2 above 30
mx = tasmin_series(a + K2C)
out = xci.tn_days_below(mx, thresh='-10 C')
np.testing.assert_array_equal(out[:1], [6])
np.testing.assert_array_equal(out[1:], [0])
out = xci.tn_days_below(mx, thresh='-30 C')
np.testing.assert_array_equal(out[:1], [2])
np.testing.assert_array_equal(out[1:], [0])
def test_simple(self, tasmin_series):
i = 3650
A = 10.
tn = np.zeros(i) + A * np.sin(
np.arange(i) / 365. * 2 * np.pi) + .1 * np.random.rand(i)
tn[10:20] -= 2
tn = tasmin_series(tn)
tn10 = percentile_doy(tn, per=.1)
out = xci.cold_spell_duration_index(tn, tn10, freq='YS')
assert out[0] == 10
assert out.units == 'days'
def test_convert_units(self, tasmin_series):
i = 3650
A = 10.0
tn = (np.zeros(i) + A * np.sin(np.arange(i) / 365.0 * 2 * np.pi) +
0.1 * np.random.rand(i))
tn[10:20] -= 2
tn = tasmin_series(tn + K2C)
tn.attrs["units"] = "C"
tn10 = percentile_doy(tn, per=0.1)
out = atmos.cold_spell_duration_index(tn, tn10, freq="AS-JUL")
assert out[0] == 10
def test_1d(self, tasmin_series):
a = np.zeros(35)
a[25:] = 23
da = tasmin_series(a + K2C)
wnf = xci.warm_night_frequency(da, freq='MS')
np.testing.assert_allclose(wnf.values, [6, 4])
wnf = xci.warm_night_frequency(da, freq='YS')
np.testing.assert_allclose(wnf.values, [10])
wnf = xci.warm_night_frequency(da, thresh='-1 C')
np.testing.assert_allclose(wnf.values, [35])
wnf = xci.warm_night_frequency(da, thresh='50 C')
np.testing.assert_allclose(wnf.values, [0])
def test_tn90p_simple(self, tasmin_series):
i = 366
tas = np.array(range(i))
tas = tasmin_series(tas, start='1/1/2000')
t90 = percentile_doy(tas, per=.1)
# create cold spell in june
tas[175:180] = 1
out = xci.tn90p(tas, t90, freq='MS')
assert out[0] == 30
assert out[1] == 29
assert out[5] == 25
def test_simple(self, tasmin_series, tasmax_series):
mn = np.zeros(365)
mx = np.zeros(365)
# 5 days in 1st month
mn[10:20] -= 1
mx[10:15] += 1
# 1 day in 2nd month
mn[40:44] += [1, 1, -1, -1]
mx[40:44] += [1, -1, 1, -1]
mn = tasmin_series(mn + K2C)
mx = tasmax_series(mx + K2C)
out = xci.daily_freezethaw_cycles(mx, mn, 'M')
np.testing.assert_array_equal(out[:2], [5, 1])
np.testing.assert_array_equal(out[2:], 0)
def test_1d(self, tasmax_series, tasmin_series):
tn = tasmin_series(np.asarray([20, 23, 23, 23, 23, 22, 23, 23, 23, 23]) + K2C)
tx = tasmax_series(np.asarray([29, 31, 31, 31, 29, 31, 31, 31, 31, 31]) + K2C)
# some hw
hwf = xci.heat_wave_frequency(
tn, tx, thresh_tasmin="22 C", thresh_tasmax="30 C"
)
np.testing.assert_allclose(hwf.values, 2)
hwf = xci.heat_wave_frequency(
tn, tx, thresh_tasmin="22 C", thresh_tasmax="30 C", window=4
)
np.testing.assert_allclose(hwf.values, 1)
# one long hw
hwf = xci.heat_wave_frequency(
tn, tx, thresh_tasmin="10 C", thresh_tasmax="10 C"
)
np.testing.assert_allclose(hwf.values, 1)
# no hw
hwf = xci.heat_wave_frequency(
tn, tx, thresh_tasmin="40 C", thresh_tasmax="40 C"
)
np.testing.assert_allclose(hwf.values, 0)
def static_tmax_tmin_setup(tasmax_series, tasmin_series):
max_values = np.add([22, 10, 35.2, 25.1, 18.9, 12, 16], K2C)
min_values = np.add([17, 3.5, 22.7, 16, 12.4, 7, 12], K2C)
tasmax = tasmax_series(max_values)
tasmin = tasmin_series(min_values)
return tasmax, tasmin
def test_to_period_end(self, tasmin_series):
a = np.zeros(365) + K2C + 5.0
a[2] -= 20
ts = tasmin_series(a)
miss = checks.missing_any(ts, freq="A-JUN")
np.testing.assert_equal(miss, [False])
