def test_distance_func_with_kwarg_works(tmpdir, sample_config):
sample_config['DYESCORE_DATA_DIR'] = tmpdir.strpath
ds = DyeScore(write_config_file(tmpdir, sample_config))
random_array = np.random.rand(5, 2)
snippet_ids = ['0', '1', '2', '3', '4'] # 0 index for sanity :D
data = xr.DataArray(random_array,
coords={
'snippet': snippet_ids,
'symbol': ['window.navigator', 'canvas.context'],
},
dims=('snippet', 'symbol'))
f = ds.dye_score_data_file('snippets')
data.to_dataset(name='data').to_zarr(store=ds.get_zarr_store(f))
# Run Test
dye_snippets = ['2']
weights = [0.4, 0.6]
kwargs = dict(w=weights)
result_file = ds.compute_distances_for_dye_snippets(
dye_snippets, distance_function='cosine', override=True, **kwargs)
# Check Results
results = xr.open_zarr(store=ds.get_zarr_store(result_file))['data']
assert results.shape == (5, 1)
for s in snippet_ids:
actual_result = results.sel(snippet=s, dye_snippet='2').values
expected_result = cosine(random_array[2],
random_array[int(s)],
w=weights)
assert actual_result == expected_result
def test_data_validation_with_invalid_file(tmpdir, sample_config):
# Set-up invalid data file and save config
data_file = os.path.join(tmpdir, 'data.csv')
df = pd.DataFrame({'a': [1, 2, 3]})
df.to_csv(data_file)
sample_config['INPUT_PARQUET_LOCATION'] = data_file
config_file = write_config_file(tmpdir, sample_config)
ds = DyeScore(config_file)
# Test
with pytest.raises(ArrowIOError):
ds.validate_input_data()
def test_data_validation_with_valid_file(tmpdir, sample_config):
# Set-up valid data file and save config
data_file = os.path.join(tmpdir, 'data.parquet')
daskify(
pd.DataFrame({
'top_level_url': ['a', 'b'],
'document_url': ['a', 'b'],
'script_url': ['c', 'd'],
'symbol': ['e', 'f'],
'func_name': ['g', 'h']
})).to_parquet(data_file)
sample_config['INPUT_PARQUET_LOCATION'] = data_file
config_file = write_config_file(tmpdir, sample_config)
ds = DyeScore(config_file)
# Test
assert ds.validate_input_data() is True
def test_passing_unavailable_string_fails(tmpdir, sample_config):
# Setup
sample_config['DYESCORE_DATA_DIR'] = tmpdir.strpath
ds = DyeScore(write_config_file(tmpdir, sample_config))
random_array = np.random.rand(5, 2)
snippet_ids = ['0', '1', '2', '3', '4']
data = xr.DataArray(random_array,
coords={
'snippet': snippet_ids,
'symbol': ['window.navigator', 'canvas.context'],
},
dims=('snippet', 'symbol'))
f = ds.dye_score_data_file('snippets')
data.to_dataset(name='data').to_zarr(store=ds.get_zarr_store(f))
# Run Test
with pytest.raises(KeyError):
ds.compute_distances_for_dye_snippets(
['2'],
override=True,
distance_function='euclidean',
)