def add_confidence(self, result, value, confidence_reached):
if confidence_reached:
detail = self.display_names["confidence_reached"]
else:
detail = self.display_names["confidence_not_reached"]
result.add_element(
SingleElement(self.display_names["confidence"],
"{}% ({})".format(value, detail)))
def add_test_suite(self, result, test_suite, descriptions):
# arrange attributes so the ones used in the descriptions goes first
sorted_columns = list(descriptions[0].keys())
sorted_columns.insert(0, PREDICTED_OUTCOME)
for column in test_suite.columns:
if column not in sorted_columns:
sorted_columns.append(column)
if PREDICTED_PROBABILITY in sorted_columns:
sorted_columns.remove(PREDICTED_PROBABILITY)
if OUTCOME in sorted_columns:
sorted_columns.remove(OUTCOME)
testing_suite = test_suite[sorted_columns]
testing_suite = testing_suite.rename(
columns={
PREDICTED_OUTCOME: self.display_names["predicted_outcome"]
})
column_names = list(testing_suite.columns)
data = testing_suite.values.tolist()
result.add_element(
TableElement(self.display_names["test_suite"], column_names, data))
result.add_element(
SingleElement(self.display_names["test_suite_total_cases"],
len(data)))
def add_maximum_acceptable_difference(self, result, value):
result.add_element(
SingleElement(self.display_names["maximum_acceptable_difference"],
value))
def add_percentage(self, result, proportion, error):
result.add_element(
SingleElement(
self.display_names["percentage"],
"({} ± {})%".format(round(proportion * 100, 2), error)))
def add_minimum_samples_amount(self, result, value):
result.add_element(
SingleElement(self.display_names["minimum_samples_amount"], value))
def add_decimals(self, result, value):
result.add_element(SingleElement(self.display_names["decimals"],
value))
if len(failing_cases) > 0:
column_names = [
"{} 1".format(self.display_names["individual"]),
"{} 2".format(self.display_names["individual"]),
self.display_names["individuals_distance"],
self.display_names["outcomes_distance"]
]
data = [[
case.individual1.name, case.individual2.name,
case.individuals_distance, case.outcomes_distance
] for case in failing_cases]
result.add_element(
TableElement(self.display_names["failing_cases_table"],
column_names, data))
result.add_element(
SingleElement(self.display_names["failing_cases"],
len(failing_cases)))
def add_probabilities_table(self, result, template, column_satisfies,
descriptions, probabilities_table):
row_descriptions = list()
for description in descriptions:
formatted_description = format_description(description)
row_descriptions.append(template.format(formatted_description))
column_names = list(probabilities_table[0].keys())
column_names.insert(0, "s")
data = [
list(round(value, 3) for value in dict_probabilities.values())
for dict_probabilities in probabilities_table
]
for i, row in enumerate(data):
row.insert(0, row_descriptions[i])