def test_resample(self):
times = pd.date_range('2000-01-01', freq='6H', periods=10)
array = DataArray(np.arange(10), [('time', times)])
actual = array.resample('6H', dim='time')
self.assertDataArrayIdentical(array, actual)
actual = array.resample('24H', dim='time')
expected = DataArray(array.to_series().resample('24H'))
self.assertDataArrayIdentical(expected, actual)
actual = array.resample('24H', dim='time', how=np.mean)
self.assertDataArrayIdentical(expected, actual)
with self.assertRaisesRegexp(ValueError, 'index must be monotonic'):
array[[2, 0, 1]].resample('1D', dim='time')
def test_resample_skipna(self):
times = pd.date_range('2000-01-01', freq='6H', periods=10)
array = DataArray(np.ones(10), [('time', times)])
array[1] = np.nan
actual = array.resample('1D', dim='time', skipna=False)
expected = DataArray([np.nan, 1, 1], [('time', times[::4])])
self.assertDataArrayIdentical(expected, actual)
def test_resample_upsampling(self):
times = pd.date_range('2000-01-01', freq='1D', periods=5)
array = DataArray(np.arange(5), [('time', times)])
expected_time = pd.date_range('2000-01-01', freq='12H', periods=9)
expected = array.reindex(time=expected_time)
for how in ['mean', 'median', 'sum', 'first', 'last', np.mean]:
actual = array.resample('12H', 'time', how=how)
self.assertDataArrayIdentical(expected, actual)
def test_resample_first(self):
times = pd.date_range('2000-01-01', freq='6H', periods=10)
array = DataArray(np.arange(10), [('time', times)])
actual = array.resample('1D', dim='time', how='first')
expected = DataArray([0, 4, 8], [('time', times[::4])])
self.assertDataArrayIdentical(expected, actual)
# verify that labels don't use the first value
actual = array.resample('24H', dim='time', how='first')
expected = DataArray(array.to_series().resample('24H', how='first'))
self.assertDataArrayIdentical(expected, actual)
# missing values
array = array.astype(float)
array[:2] = np.nan
actual = array.resample('1D', dim='time', how='first')
expected = DataArray([2, 4, 8], [('time', times[::4])])
self.assertDataArrayIdentical(expected, actual)
actual = array.resample('1D', dim='time', how='first', skipna=False)
expected = DataArray([np.nan, 4, 8], [('time', times[::4])])
self.assertDataArrayIdentical(expected, actual)
