def test_calc_all_weat_defaults(w2v_small):
weat_5_results_default = (calc_all_weat(w2v_small,
(5, )).iloc[0].to_dict())
weat_5_results = (calc_all_weat(w2v_small, (5, ),
filter_by='model',
with_pvalue=True,
pvalue_kwargs={
'method': 'exact'
}).iloc[0].to_dict())
assert_deep_almost_equal(weat_5_results_default, weat_5_results)
def calc_benchmark_scores(model, f_name):
with open('benchmark_weat.json') as data:
dict = json.load(data)
result = calc_all_weat(model,
weat_data=dict,
with_original_finding=True,
with_pvalue=True)
result.to_csv(f_name)
def test_calc_all_weat_index(w2v_small):
all_weat = calc_all_weat(w2v_small,
filter_by='model',
with_original_finding=True,
with_pvalue=True,
pvalue_kwargs={'method': 'approximate'})
for index in range(len(WEAT_DATA)):
single_weat = calc_all_weat(w2v_small,
weat_data=index,
filter_by='model',
with_original_finding=True,
with_pvalue=True,
pvalue_kwargs={'method': 'approximate'})
assert_deep_almost_equal(single_weat.iloc[0].to_dict(),
all_weat.iloc[index].to_dict(),
atol=0.01)
def test_calc_weat_pleasant_attribute(w2v_small):
# pylint: disable=line-too-long
pvalue_kwargs = {'method': 'approximate'}
result_v1 = calc_weat_pleasant_unpleasant_attribute(
w2v_small,
WEAT_DATA[1]['first_target'],
WEAT_DATA[1]['second_target'],
pvalue_kwargs=pvalue_kwargs)
result_v1['p'] = round(result_v1['p'], 4)
result_v1['d'] = round(result_v1['d'], 4)
result_v1['s'] = round(result_v1['s'], 4)
result_v2 = (calc_all_weat(w2v_small, (1, ),
pvalue_kwargs=pvalue_kwargs).iloc[0].to_dict())
assert_deep_almost_equal(result_v1, result_v2, atol=0.01)
def test_calc_all_weat(w2v_small):
calc_all_weat(w2v_small,
filter_by='model',
with_original_finding=True,
with_pvalue=True,
pvalue_kwargs={'method': 'approximate'})
