def test_vector_presenter_with_vector_data_contain_one_element_compare_with_reference_ignore_formatting(
self, mocker):
mock_write_scalar_res = mocker.patch(
'accuracy_checker.presenters.write_scalar_result'
) # type: MagicMock
result = EvaluationResult(
name='vector_metric',
metric_type='metric',
evaluated_value=[0.4],
reference_value=42,
abs_threshold=None,
rel_threshold=None,
meta={},
)
presenter = VectorPrintPresenter()
presenter.write_result(result, ignore_results_formatting=True)
mock_write_scalar_res.assert_called_once_with(
result.evaluated_value[0],
result.name,
result.abs_threshold,
result.rel_threshold, (2.0, 0.047619047619047616),
postfix=' ',
scale=1,
value_name=None,
result_format='{}')
def test_vector_presenter_with_vector_data_with_vector_scale(self, mocker):
mock_write_scalar_res = mocker.patch('accuracy_checker.presenters.write_scalar_result') # type: MagicMock
result = EvaluationResult(
name='scalar_metric',
metric_type='metric',
evaluated_value=[0.4, 0.6],
reference_value=None,
threshold=None,
meta={'names': ['class1', 'class2'], 'scale': [1, 2]}
)
presenter = VectorPrintPresenter()
presenter.write_result(result)
calls = [
call(
result.evaluated_value[0], result.name,
postfix='%', scale=result.meta['scale'][0], result_format='{:.2f}', value_name=result.meta['names'][0]
),
call(
result.evaluated_value[1], result.name, postfix='%',
scale=result.meta['scale'][1], result_format='{:.2f}', value_name=result.meta['names'][1]
),
call(
np.mean(np.multiply(result.evaluated_value, result.meta['scale'])), result.name, result.threshold,
None, result_format='{:.2f}', value_name='mean', postfix='%', scale=1
)
]
mock_write_scalar_res.assert_has_calls(calls)
def test_vector_presenter_with_scaler_data_compare_with_reference(
self, mocker):
mock_write_scalar_res = mocker.patch(
'accuracy_checker.presenters.write_scalar_result'
) # type: MagicMock
result = EvaluationResult(
name='scalar_metric',
metric_type='metric',
evaluated_value=0.4,
reference_value=42,
abs_threshold=None,
rel_threshold=None,
meta={},
)
presenter = VectorPrintPresenter()
presenter.write_result(result)
mock_write_scalar_res.assert_called_once_with(
result.evaluated_value,
result.name,
result.abs_threshold,
result.rel_threshold, (2.0, 0.047619047619047616),
postfix='%',
scale=100,
value_name=None,
result_format='{:.2f}')
def test_vector_presenter_with_vector_data_has_specific_format_with_ignore_formatting(self, mocker):
mock_write_scalar_res = mocker.patch('accuracy_checker.presenters.write_scalar_result') # type: MagicMock
result = EvaluationResult(
name='scalar_metric',
metric_type='metric',
evaluated_value=[0.4, 0.6],
reference_value=None,
threshold=None,
meta={'names': ['class1', 'class2'], 'scale': 0.5, 'postfix': 'km/h', 'data_format': '{:.4f}'}
)
presenter = VectorPrintPresenter()
presenter.write_result(result, ignore_results_formatting=True)
calls = [
call(
result.evaluated_value[0], result.name,
postfix=' ', scale=1, value_name=result.meta['names'][0], result_format='{}'
),
call(
result.evaluated_value[1], result.name,
postfix=' ', scale=1, value_name=result.meta['names'][1], result_format='{}'
),
call(
np.mean(np.multiply(result.evaluated_value, 1)), result.name, result.reference_value, result.threshold,
value_name='mean', postfix=' ', scale=1, result_format='{}'
)
]
mock_write_scalar_res.assert_has_calls(calls)
def test_vector_presenter_with_vector_data_contain_one_element(
self, mocker):
mock_write_scalar_res = mocker.patch(
'accuracy_checker.presenters.write_scalar_result'
) # type: MagicMock
result = EvaluationResult(name='scalar_metric',
metric_type='metric',
evaluated_value=[0.4],
reference_value=None,
abs_threshold=None,
rel_threshold=None,
meta={'names': ['prediction']},
profiling_file=None)
presenter = VectorPrintPresenter()
presenter.write_result(result)
mock_write_scalar_res.assert_called_once_with(
result.evaluated_value[0],
result.name,
None,
result.abs_threshold,
result.rel_threshold,
postfix='%',
scale=100,
value_name=result.meta['names'][0],
result_format='{:.2f}')
def test_vector_presenter_with_vector_data_with_scalar_postfix(
self, mocker):
mock_write_scalar_res = mocker.patch(
'accuracy_checker.presenters.write_scalar_result'
) # type: MagicMock
result = EvaluationResult(name='scalar_metric',
metric_type='metric',
evaluated_value=[0.4, 0.6],
reference_value=None,
abs_threshold=None,
rel_threshold=None,
meta={
'names': ['class1', 'class2'],
'postfix': '_'
},
profiling_file=None)
presenter = VectorPrintPresenter()
presenter.write_result(result)
calls = [
call(result.evaluated_value[0],
result.name,
None,
None,
None,
postfix=result.meta['postfix'],
scale=100,
value_name=result.meta['names'][0],
result_format='{:.2f}'),
call(result.evaluated_value[1],
result.name,
None,
None,
None,
postfix=result.meta['postfix'],
scale=100,
value_name=result.meta['names'][1],
result_format='{:.2f}'),
call(np.mean(np.multiply(result.evaluated_value, 100)),
result.name,
result.abs_threshold,
result.rel_threshold,
None,
value_name='mean',
postfix=result.meta['postfix'],
scale=1,
result_format='{:.2f}')
]
mock_write_scalar_res.assert_has_calls(calls)
def test_vector_presenter_with_vector_data_has_default_format_with_ignore_formatting_compare_with_ref(
self, mocker):
mock_write_scalar_res = mocker.patch(
'accuracy_checker.presenters.write_scalar_result'
) # type: MagicMock
result = EvaluationResult(name='vector_metric',
metric_type='metric',
evaluated_value=[0.4, 0.6],
reference_value=49,
abs_threshold=None,
rel_threshold=None,
meta={'names': ['class1', 'class2']},
profiling_file=None)
presenter = VectorPrintPresenter()
presenter.write_result(result, ignore_results_formatting=True)
calls = [
call(result.evaluated_value[0],
result.name,
None,
None,
None,
postfix=' ',
scale=1,
value_name=result.meta['names'][0],
result_format='{}'),
call(result.evaluated_value[1],
result.name,
None,
None,
None,
postfix=' ',
scale=1,
value_name=result.meta['names'][1],
result_format='{}'),
call(np.mean(np.multiply(result.evaluated_value, 1)),
result.name,
result.abs_threshold,
result.rel_threshold, (1.0, 0.02040816326530612),
value_name='mean',
postfix=' ',
scale=1,
result_format='{}')
]
mock_write_scalar_res.assert_has_calls(calls)
def test_vector_presenter_with_vector_data_with_one_element(self, mocker):
mock_write_scalar_res = mocker.patch(
'accuracy_checker.presenters.write_scalar_result'
) # type: MagicMock
res = EvaluationResult(name='scalar_metric',
evaluated_value=[0.4],
reference_value=None,
threshold=None,
meta={'names': ['prediction']})
presenter = VectorPrintPresenter()
presenter.write_result(res)
mock_write_scalar_res.assert_called_once_with(
res.evaluated_value,
res.name,
res.reference_value,
res.threshold,
postfix='%',
scale=100,
value_name=res.meta['names'][0])
def test_vector_presenter_with_scaler_data(self, mocker):
mock_write_scalar_res = mocker.patch(
'accuracy_checker.presenters.write_scalar_result'
) # type: MagicMock
res = EvaluationResult(
name='scalar_metric',
evaluated_value=0.4,
reference_value=None,
threshold=None,
meta={},
)
presenter = VectorPrintPresenter()
presenter.write_result(res)
mock_write_scalar_res.assert_called_once_with(
res.evaluated_value,
res.name,
res.reference_value,
res.threshold,
postfix='%',
scale=100,
value_name=None,
result_format='{:.2f}',
)
