def _execute_metrics(self):
# Iterate over input GUI design files
for input_gui_design_file in self.input_gui_design_files[
len(self.results):]:
logger.info("Evaluating {}...".format(input_gui_design_file.name))
# Start total timer
start_time_total: float = time.time()
# Initialize GUI design results row
results_row = {}
results_row["filename"] = input_gui_design_file.name
results_row["evaluation_date"] = date.today().isoformat()
# Read GUI design image (PNG)
start_time: float = time.time()
gui_image_png_base64: str = utils.read_image(input_gui_design_file)
end_time: float = time.time()
results_row["read_image_time"] = round(end_time - start_time, 4)
# Iterate over AIM metrics
for metric in self._METRICS:
# Import metric module
metric_module = importlib.import_module("aim.metrics." +
metric)
# Execute metric
start_time: float = time.time()
metric_results: Optional[
List[Any]] = metric_module.Metric.execute_metric(
gui_image_png_base64)
end_time: float = time.time()
results_row[metric.partition("_")[0] + "_time"] = round(
end_time - start_time, 4)
# Iterate over metrics results
for index, metric_result in enumerate(metric_results):
if type(metric_result) is float:
results_row[metric.partition("_")[0] + "_result_" +
str(index + 1)] = round(metric_result, 4)
else:
results_row[metric.partition("_")[0] + "_result_" +
str(index + 1)] = metric_result
# End total timer
end_time_total: float = time.time()
results_row["total_evaluation_time"] = round(
end_time_total - start_time_total, 4)
# Append results
self.results.append(results_row)
# Precaution against crashes: save results after each GUI design
# evaluation instead of after completing all of them
self._save_results()
def test_contour_density_desktop(input_value: str,
expected_result: List[Any]) -> None:
"""
Test contour density (desktop GUIs).
Args:
input_value: GUI image file name
expected_result: Expected result (list of measures)
"""
# Build GUI image file path
gui_image_filepath: pathlib.Path = (pathlib.Path(DATA_TESTS_DIR) /
input_value)
# Read GUI image (PNG)
gui_image_png_base64: str = aim_utils.read_image(gui_image_filepath)
# Execute metric
result: Optional[List[Any]] = Metric4.execute_metric(gui_image_png_base64)
# Test result
if result is not None:
assert result[0] == expected_result[0]
