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with env:
with rasterio.open(url) as src:
with rasterio.vrt.WarpedVRT(src, crs="epsg:4326") as vrt:
expected_shape = (vrt.width, vrt.height)
expected_crs = vrt.crs
expected_res = vrt.res
# Value of single pixel in center of image
lon, lat = vrt.xy(vrt.width // 2, vrt.height // 2)
expected_val = next(vrt.sample([(lon, lat)]))
with xr.open_rasterio(vrt) as da:
actual_shape = (da.sizes["x"], da.sizes["y"])
actual_crs = da.crs
actual_res = da.res
actual_val = da.sel(dict(x=lon, y=lat), method="nearest").data
assert_equal(actual_shape, expected_shape)
assert_equal(actual_crs, expected_crs)
assert_equal(actual_res, expected_res)
assert_equal(expected_val, actual_val)
def update_feature_test(cutout, red):
"""atlite should be able to overwrite a feature."""
red.data = cutout.data.drop_vars('influx_direct')
red.prepare('influx', overwrite=True)
assert_equal(red.data.influx_direct, cutout.data.influx_direct)
assert plotter._pltkwargs["nrows"] * plotter._pltkwargs["ncols"] >= len(
plotter.metrics
)
figsize = kwargs.get("figsize")
if figsize is not None:
assert plotter.figsize == figsize
train_batch_expected, train_epoch_expected = logger.to_xarray("train")
test_batch_expected, test_epoch_expected = logger.to_xarray("test")
train_batch_actual, train_epoch_actual = plotter.to_xarray("train")
test_batch_actual, test_epoch_actual = plotter.to_xarray("test")
assert_equal(train_batch_actual, train_batch_expected)
assert_equal(test_batch_actual, test_batch_expected)
assert_equal(train_epoch_actual, train_epoch_expected)
assert_equal(test_epoch_actual, test_epoch_expected)
def test_ButterwothFilter(self):
from xarray.testing import assert_equal
b_filter = ButterworthFilter(timeseries=self.base_eegs, freq_range=[58., 62.], filt_type='stop', order=4)
base_eegs_filtered_1 = b_filter.filter()
base_eegs_filtered_2 = self.base_eegs.filtered(freq_range=[58., 62.], filt_type='stop', order=4)
assert_equal(base_eegs_filtered_1, base_eegs_filtered_2)
with self.assertRaises(AssertionError):
assert_equal(base_eegs_filtered_1, self.base_eegs)
# Assert results match expectations
xr.testing.assert_allclose(deriv_x, truth_x)
assert deriv_x.metpy.units == truth_x.metpy.units
xr.testing.assert_allclose(deriv_y, truth_y)
assert deriv_y.metpy.units == truth_y.metpy.units
xr.testing.assert_allclose(deriv_p, truth_p)
assert deriv_p.metpy.units == truth_p.metpy.units
# Assert alternative specifications give same results (up to attribute differences)
xr.testing.assert_equal(deriv_x_alt1, deriv_x)
xr.testing.assert_equal(deriv_y_alt1, deriv_y)
xr.testing.assert_equal(deriv_p_alt1, deriv_p)
xr.testing.assert_equal(deriv_x_alt2, deriv_x)
xr.testing.assert_equal(deriv_y_alt2, deriv_y)
xr.testing.assert_equal(deriv_p_alt2, deriv_p)
def test_ButterwothFilter(self):
from xarray.testing import assert_equal
b_filter = ButterworthFilter(timeseries=self.base_eegs, freq_range=[58., 62.], filt_type='stop', order=4)
base_eegs_filtered_1 = b_filter.filter()
base_eegs_filtered_2 = self.base_eegs.filtered(freq_range=[58., 62.], filt_type='stop', order=4)
assert_equal(base_eegs_filtered_1, base_eegs_filtered_2)
with self.assertRaises(AssertionError):
assert_equal(base_eegs_filtered_1, self.base_eegs)
def test_xy_reversed_coords(ref):
cutout = Cutout(path="xy_r", module="era5", time=TIME,
x=slice(X1, X0), y = slice(Y1, Y0))
assert_equal(cutout.coords.to_dataset(), ref.coords.to_dataset())
coords=(('isobaric', test_da_xy['isobaric']),)
)
_, truth_p = xr.broadcast(test_da_xy, partial)
truth_p.coords['crs'] = test_da_xy['crs']
truth_p.attrs['units'] = 'kelvin / hectopascal'
# Assert results match expectations
xr.testing.assert_allclose(deriv_x, truth_x)
assert deriv_x.metpy.units == truth_x.metpy.units
xr.testing.assert_allclose(deriv_y, truth_y)
assert deriv_y.metpy.units == truth_y.metpy.units
xr.testing.assert_allclose(deriv_p, truth_p)
assert deriv_p.metpy.units == truth_p.metpy.units
# Assert alternative specifications give same results (up to attribute differences)
xr.testing.assert_equal(deriv_x_alt1, deriv_x)
xr.testing.assert_equal(deriv_y_alt1, deriv_y)
xr.testing.assert_equal(deriv_p_alt1, deriv_p)
xr.testing.assert_equal(deriv_x_alt2, deriv_x)
xr.testing.assert_equal(deriv_y_alt2, deriv_y)
xr.testing.assert_equal(deriv_p_alt2, deriv_p)
:meth:`as_quantity`.
"""
if not check_type:
a = Quantity(a)
b = Quantity(b)
if Quantity.CLASS == 'AttrSeries':
try:
a = a.sort_index()
b = b.sort_index()
except TypeError:
pass
assert_series_equal(a, b, check_dtype=False, **kwargs)
else:
import xarray.testing
xarray.testing.assert_equal(a, b, **kwargs)
# check attributes are equal
if check_attrs:
assert a.attrs == b.attrs
def test_mne_dataarray_conversions():
epochs = xarray_to_mne(original_data, original_meta, context_key, event_id)
after_conversion_data, after_conversion_meta = mne_to_xarray(epochs, context_key, event_id)
# assert that the passage in mne keeps the data unchanged
xr.testing.assert_equal(after_conversion_data, original_data)
assert original_meta == after_conversion_meta