import os

from CertainTrust import Opinion
from vendors.debian.CSVReader import CSVReader

class Tests:
    @staticmethod
    def input_prediction_error_test(model):
        norm_param = 4

        model_filename = os.path.join(model.module_path, "models", "dummy_input_package_prediction_errorcompl.csv")
        model_set = model.gen_model_opinion_set(model_filename, 9, norm_param)

        system_filename = os.path.join(model.module_path, "inputs", "dummy_input_package_server.csv")
        system = CSVReader.read_csv_package_names(system_filename)

        # get system dict
        system_dict = dict()
        for key in system:
            print(key)
            new_key = model.unifySrcName(key)
            if new_key in model_set:
                system_dict[new_key] = model_set[new_key]

        print("Evaluating on: " + str(len(system_dict)) + " out of " + str(
            len(system)) + " packages, since they are not present in our model.")

        Tests.evaluate_expectation(system_dict, model, 9, norm_param)



    @staticmethod
    def evaluate_expectation(package_list, vendormodel, months, norm_val):
        """
        TODO:
        :param package_list: dictionary of opinions with names as key and opinion as value
        :param vendormodel: the vendor-model to compare the prediction with
        :return: TODO:
        """
        print("For normalization value = " + str(norm_val))
        # ANDed prediction
        system_and = Opinion._cum_and(list(package_list.values()))
        expectation = system_and.expectation_value()
        AND_prediction = (1 - expectation) * (norm_val * months * 30)

        # separate prediction
        sep_pred = 0
        for k in package_list:
            sep_pred = sep_pred + ((1 - package_list[k].expectation_value()) * (norm_val * months * 30))

        # src2month prediction gathering
        summ = 0
        for package in package_list:
            unified_package = vendormodel.unifySrcName(package)
            src2month = vendormodel.get_src2month()
            if unified_package in src2month:
                summ = summ + sum(src2month[package][-months - 3:-3])

        file_error = abs(summ - CSVReader.prediction_read) / summ
        print("Input file prediction = " + str(CSVReader.prediction_read) + ", ( error = " + str(file_error) + " )")

        sep_error = abs(summ - sep_pred) / summ
        print("Separate prediction = " + str(sep_pred) + ", ( error = " + str(sep_error) + " )")

        and_error = abs(summ - AND_prediction) / summ
        print("ANDed prediction = " + str(AND_prediction) + ", ( error = " + str(and_error) + " )")
        print("Src2month data = " + str(summ))