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Simplify test_combine_echodata_combined_append #1

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Aug 15, 2023
Merged

Simplify test_combine_echodata_combined_append #1

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2 changes: 1 addition & 1 deletion echopype/echodata/combine.py
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Original file line number Diff line number Diff line change
Expand Up @@ -654,7 +654,7 @@ def _get_prov_attrs(
Parameters
----------
ds : xr.Dataset
The provenance dataset to get attributes from
The Provenance group dataset to get attributes from
is_combined: bool
The flag to indicate if it's combined

Expand Down
77 changes: 33 additions & 44 deletions echopype/tests/echodata/test_echodata_combine.py
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Original file line number Diff line number Diff line change
Expand Up @@ -234,7 +234,8 @@ def attr_time_to_dt(time_str):


def _check_prov_ds(prov_ds, eds):
"""Checks the provenance dataset against original echodata object"""
"""Checks the Provenance dataset against source_filenames variable
and global attributes in the original echodata object"""
for i in range(prov_ds.dims["echodata_filename"]):
ed_ds = eds[i]
one_ds = prov_ds.isel(echodata_filename=i, filenames=i)
Expand All @@ -246,12 +247,12 @@ def _check_prov_ds(prov_ds, eds):
)
else:
ed_group = value.attrs.get("echodata_group")
group_attrs = ed_ds[ed_group].attrs
expected_val = group_attrs[key]
expected_val = ed_ds[ed_group].attrs[key]
if not isinstance(expected_val, str):
expected_val = str(expected_val)
assert str(value.values) == expected_val


@pytest.mark.parametrize("test_param", [
"single",
"multi",
Expand Down Expand Up @@ -283,15 +284,16 @@ def test_combine_echodata_combined_append(ek60_multi_test_data, test_param, sona
combined_ed = echopype.combine_echodata(eds[:2])
combined_ed.to_zarr(first_zarr, overwrite=True)

def _check_prov_ds_and_dims(sel_comb_ed, n_val_expected):
prov_ds = sel_comb_ed["Provenance"]
for _, n_val in prov_ds.dims.items():
assert n_val == n_val_expected
_check_prov_ds(prov_ds, eds)

# Checks for Provenance group
prov_ds = combined_ed["Provenance"]
for _, n_val in prov_ds.dims.items():
# Both dims of filenames and echodata filename
# should be 2 at this point
assert n_val == 2

_check_prov_ds(prov_ds, eds)

# Both dims of filenames and echodata filename should be 2
expected_n_vals = 2
_check_prov_ds_and_dims(combined_ed, expected_n_vals)

# Second combined file
combined_ed_other = echopype.combine_echodata(eds[2:])
Expand All @@ -301,59 +303,46 @@ def test_combine_echodata_combined_append(ek60_multi_test_data, test_param, sona
combined_ed_other = echopype.open_converted(second_zarr)

# Set expected values for Provenance
expected_n_vals = 4
if test_param == "single":
data_inputs = [combined_ed, eds[2]]
expected_n_vals = 3
elif test_param == "multi":
data_inputs = [combined_ed, eds[2], eds[3]]
expected_n_vals = 4
else:
data_inputs = [combined_ed, combined_ed_other]
combined_ed2 = echopype.combine_echodata(
data_inputs
)
expected_n_vals = 4

combined_ed2 = echopype.combine_echodata(data_inputs)

# Verify that combined objects are all EchoData objects
assert isinstance(combined_ed, EchoData)
assert isinstance(combined_ed_other, EchoData)
assert isinstance(combined_ed2, EchoData)

# Ensure that they're from the same file source
assert eds[0]['Provenance'].source_filenames[0].values == combined_ed['Provenance'].source_filenames[0].values
assert eds[1]['Provenance'].source_filenames[0].values == combined_ed['Provenance'].source_filenames[1].values
assert eds[2]['Provenance'].source_filenames[0].values == combined_ed2['Provenance'].source_filenames[2].values
if test_param != "single":
assert eds[3]['Provenance'].source_filenames[0].values == combined_ed2['Provenance'].source_filenames[3].values
group_path = "Provenance"
for i in range(4):
ds_i = eds[i][group_path]
select_comb_ds = combined_ed[group_path] if i < 2 else combined_ed2[group_path]
if i < 3 or (i == 3 and test_param != "single"):
assert ds_i.source_filenames[0].values == select_comb_ds.source_filenames[i].values

# Check beam_group1. Should be exactly same xr dataset
group_path = "Sonar/Beam_group1"
ds0 = eds[0][group_path]
filt_ds0 = combined_ed[group_path].sel(ping_time=ds0.ping_time)
assert filt_ds0.identical(ds0) is True

ds1 = eds[1][group_path]
filt_ds1 = combined_ed[group_path].sel(ping_time=ds1.ping_time)
assert filt_ds1.identical(ds1) is True

ds2 = eds[2][group_path]
filt_ds2 = combined_ed2[group_path].sel(ping_time=ds2.ping_time)
assert filt_ds2.identical(ds2) is True

if test_param != "single":
ds3 = eds[3][group_path]
filt_ds3 = combined_ed2[group_path].sel(ping_time=ds3.ping_time)
assert filt_ds3.identical(ds3) is True
for i in range(4):
ds_i = eds[i][group_path]
select_comb_ds = combined_ed[group_path] if i < 2 else combined_ed2[group_path]
if i < 3 or (i == 3 and test_param != "single"):
filt_ds_i = select_comb_ds.sel(ping_time=ds_i.ping_time)
assert filt_ds_i.identical(ds_i) is True

filt_combined = combined_ed2[group_path].sel(ping_time=combined_ed[group_path].ping_time)
assert filt_combined.identical(combined_ed[group_path])
assert filt_combined.identical(combined_ed[group_path]) is True

# Checks for Provenance group
prov_ds = combined_ed2["Provenance"]
for _, n_val in prov_ds.dims.items():
# Both dims of filenames and echodata filename
# should be expected_n_vals at this point
assert n_val == expected_n_vals

_check_prov_ds(prov_ds, eds)
# Both dims of filenames and echodata filename should be expected_n_vals
_check_prov_ds_and_dims(combined_ed2, expected_n_vals)


def test_combine_echodata_channel_selection():
Expand Down
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