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| #!/usr/bin/env python3 | |
| # -*- coding: utf-8 -*- | |
| from abstractions import * | |
| import pickle | |
| import numpy as np | |
| class Monitor(object): | |
| def __init__(self, good_ref=None): | |
| # self.abs_type = abs_type | |
| self.good_ref = good_ref | |
| def set_reference(self, good_ref): | |
| self.good_ref = good_ref | |
| # def get_identity(self): | |
| # print("Monitor for network:" + self.netName + "class: " + str(self.classification) + "at layer " + str(self.location)) | |
| def make_verdicts(self, features): | |
| if len(self.good_ref): | |
| verdicts = ref_query(features, self.good_ref) | |
| else: | |
| raise RuntimeError("No reference exists!") | |
| return verdicts | |
| # def make_verdicts_delta(self, features, delta): | |
| # if len(self.good_ref): | |
| # verdicts = ref_query_delta(features, self.good_ref, delta) | |
| # else: | |
| # raise RuntimeError("No reference exists!") | |
| # return verdicts | |
| def ref_query(features, reference): | |
| query_results = [boxes_query(x, reference) for x in features] | |
| return query_results | |
| # def ref_query_delta(features, reference, delta): | |
| # query_results = [boxes_query_delta(x, reference, delta) for x in features] | |
| # return query_results | |
| # def query_infusion(in_good_ref, in_bad_ref): | |
| # if len(in_good_ref) == len(in_bad_ref): #0: acceptance (true, false), 1: rejection (false, true or false), 2: uncertainty (true, true) | |
| # verdicts = np.zeros(len(in_good_ref), dtype=int) | |
| # for i in range(len(in_good_ref)): | |
| # if not in_good_ref[i]: | |
| # verdicts[i] = 1 | |
| # elif in_bad_ref[i]: | |
| # verdicts[i] = 2 | |
| # return verdicts | |
| # else: | |
| # print("Error: IllegalArgument") | |