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How to use pareto_key method in hypothesis

Best Python code snippet using hypothesis

test_pareto.py

Source:test_pareto.py

1# This file is part of Hypothesis, which may be found at2# https://github.com/HypothesisWorks/hypothesis/3#4# Most of this work is copyright (C) 2013-2020 David R. MacIver5# (david@drmaciver.com), but it contains contributions by others. See6# CONTRIBUTING.rst for a full list of people who may hold copyright, and7# consult the git log if you need to determine who owns an individual8# contribution.9#10# This Source Code Form is subject to the terms of the Mozilla Public License,11# v. 2.0. If a copy of the MPL was not distributed with this file, You can12# obtain one at https://mozilla.org/MPL/2.0/.13#14# END HEADER15import pytest16from hypothesis import HealthCheck, Phase, settings17from hypothesis.database import InMemoryExampleDatabase18from hypothesis.internal.compat import int_to_bytes19from hypothesis.internal.conjecture.data import Status20from hypothesis.internal.conjecture.engine import ConjectureRunner, RunIsComplete21from hypothesis.internal.entropy import deterministic_PRNG22def test_pareto_front_contains_different_interesting_reasons():23    with deterministic_PRNG():24        def test(data):25            data.mark_interesting(data.draw_bits(4))26        runner = ConjectureRunner(27            test,28            settings=settings(29                max_examples=5000,30                database=InMemoryExampleDatabase(),31                suppress_health_check=HealthCheck.all(),32            ),33            database_key=b"stuff",34        )35        runner.run()36        assert len(runner.pareto_front) == 2 ** 437def test_database_contains_only_pareto_front():38    with deterministic_PRNG():39        def test(data):40            data.target_observations["1"] = data.draw_bits(4)41            data.draw_bits(64)42            data.target_observations["2"] = data.draw_bits(8)43        db = InMemoryExampleDatabase()44        runner = ConjectureRunner(45            test,46            settings=settings(47                max_examples=500, database=db, suppress_health_check=HealthCheck.all()48            ),49            database_key=b"stuff",50        )51        runner.run()52        assert len(runner.pareto_front) <= 50053        for v in runner.pareto_front:54            assert v.status >= Status.VALID55        assert len(db.data) == 156        (values,) = db.data.values()57        values = set(values)58        assert len(values) == len(runner.pareto_front)59        for data in runner.pareto_front:60            assert data.buffer in values61            assert data in runner.pareto_front62        for k in values:63            assert runner.cached_test_function(k) in runner.pareto_front64def test_clears_defunct_pareto_front():65    with deterministic_PRNG():66        def test(data):67            data.draw_bits(8)68            data.draw_bits(8)69        db = InMemoryExampleDatabase()70        runner = ConjectureRunner(71            test,72            settings=settings(73                max_examples=10000,74                database=db,75                suppress_health_check=HealthCheck.all(),76                phases=[Phase.reuse],77            ),78            database_key=b"stuff",79        )80        for i in range(256):81            db.save(runner.pareto_key, bytes([i, 0]))82        runner.run()83        assert len(list(db.fetch(runner.pareto_key))) == 184def test_down_samples_the_pareto_front():85    with deterministic_PRNG():86        def test(data):87            data.draw_bits(8)88            data.draw_bits(8)89        db = InMemoryExampleDatabase()90        runner = ConjectureRunner(91            test,92            settings=settings(93                max_examples=1000,94                database=db,95                suppress_health_check=HealthCheck.all(),96                phases=[Phase.reuse],97            ),98            database_key=b"stuff",99        )100        for i in range(10000):101            db.save(runner.pareto_key, int_to_bytes(i, 2))102        with pytest.raises(RunIsComplete):103            runner.reuse_existing_examples()104        assert runner.valid_examples == 1000105def test_stops_loading_pareto_front_if_interesting():106    with deterministic_PRNG():107        def test(data):108            data.draw_bits(8)109            data.draw_bits(8)110            data.mark_interesting()111        db = InMemoryExampleDatabase()112        runner = ConjectureRunner(113            test,114            settings=settings(115                max_examples=1000,116                database=db,117                suppress_health_check=HealthCheck.all(),118                phases=[Phase.reuse],119            ),120            database_key=b"stuff",121        )122        for i in range(10000):123            db.save(runner.pareto_key, int_to_bytes(i, 2))124        runner.reuse_existing_examples()125        assert runner.call_count == 1126def test_uses_tags_in_calculating_pareto_front():127    with deterministic_PRNG():128        def test(data):129            if data.draw_bits(1):130                data.start_example(11)131                data.draw_bits(8)132                data.stop_example()133        runner = ConjectureRunner(134            test,135            settings=settings(max_examples=10, database=InMemoryExampleDatabase()),136            database_key=b"stuff",137        )138        runner.run()139        assert len(runner.pareto_front) == 2140def test_optimises_the_pareto_front():141    def test(data):142        count = 0143        while data.draw_bits(8):144            count += 1145        data.target_observations[""] = min(count, 5)146    runner = ConjectureRunner(147        test,148        settings=settings(max_examples=10000, database=InMemoryExampleDatabase()),149        database_key=b"stuff",150    )151    runner.cached_test_function([255] * 20 + [0])152    runner.pareto_optimise()153    assert len(runner.pareto_front) == 6154    for i, data in enumerate(runner.pareto_front):155        assert list(data.buffer) == [1] * i + [0]156def test_does_not_optimise_the_pareto_front_if_interesting():157    def test(data):158        n = data.draw_bits(8)159        data.target_observations[""] = n160        if n == 255:161            data.mark_interesting()162    runner = ConjectureRunner(163        test,164        settings=settings(max_examples=10000, database=InMemoryExampleDatabase()),165        database_key=b"stuff",166    )167    runner.cached_test_function([0])168    runner.pareto_optimise = None169    runner.optimise_targets()170    assert runner.interesting_examples171def test_stops_optimising_once_interesting():172    hi = 2 ** 16 - 1173    def test(data):174        n = data.draw_bits(16)175        data.target_observations[""] = n176        if n < hi:177            data.mark_interesting()178    runner = ConjectureRunner(179        test,180        settings=settings(max_examples=10000, database=InMemoryExampleDatabase()),181        database_key=b"stuff",182    )183    data = runner.cached_test_function([255] * 2)184    assert data.status == Status.VALID185    runner.pareto_optimise()186    assert runner.call_count <= 20...

extract_predicted_pareto_frontier.py

Source:extract_predicted_pareto_frontier.py

1from __future__ import division2from non_dominated_sort import non_dominated_sort3import os4import csv5lessismore = {}6lessismore["results_SS-L/"] = [False, False]7lessismore["results_SS-H/"] = [False, False]8lessismore["results_SS-B/"] = [False, False]9lessismore["results_SS-J/"] = [False, True]10lessismore["results_SS-D/"] = [False, True]11lessismore["results_SS-E/"] = [False, True]12lessismore["results_SS-I/"] = [False, True]13lessismore["results_SS-K/"] = [False, True]14lessismore["results_SS-A/"] = [False, True]15lessismore["results_SS-C/"] = [False, True]16lessismore["results_SS-G/"] = [False, True]17lessismore["results_SS-F/"] = [False, True]18ePAL_data_folder = "./Data/"19raw_data_folder = "../Data/"20pareto_data_folder = "./Data/"21result_folders = [f+'/' for f in os.listdir(ePAL_data_folder) if '.md' not in f]22print result_folders23for result_folder in result_folders:24    print "--- " * 1025    print result_folder26    # generate a dict to assign objective values27    objective_dict = {}28    raw_filename = raw_data_folder + result_folder.replace('results_', '').replace('/', '')  + '.csv'29    assert(os.path.isfile(raw_filename) is True), "Something is wrong"30    # Read content of the raw files from raw_data_folder31    content = open(raw_filename).readlines()32    duplicate_count = 033    for i, line in enumerate(content):34        if i == 0: continue  # Skip the first line which contains headers35        line_values = map(float, [v for v in line.strip().split(',')])36        independent_values = map(int, line_values[:-2])  # Since we only consider problems with two objectives37        dependent_values = line_values[-2:]  # Since we only consider problems with two objectives38        assert(len(independent_values) + len(dependent_values) == len(line_values)), "Something is wrong"39        independent_key = ",".join(map(str, independent_values))40        if independent_key in objective_dict.keys(): duplicate_count += 141        objective_dict[independent_key] = dependent_values42    # find the objective scores of the pareto front extracted by epal43    pareto_files = [pareto_data_folder + result_folder + f for f in os.listdir(pareto_data_folder + result_folder) if "prediction_error" not in f and 'stop' not in f and ".csv" in f]44    for pareto_file in pareto_files:45        print ". ",pareto_file46        pareto_content = open(pareto_file).readlines()47        assert(len(content) >= len(pareto_content)), "Something is wrong"48        predicted_pareto_front = []49        # Finding objective values for the evaluated solutions returned by ePAL50        for pc in pareto_content:51            pc_value = map(int, map(float, pc.strip().split(';')))52            pareto_key = ",".join(map(str, pc_value))53            predicted_pareto_front.append(objective_dict[pareto_key])54        assert(len(predicted_pareto_front) == len(pareto_content)), "Something is wrong"55    #56        nd_pf_indexes = non_dominated_sort(predicted_pareto_front, lessismore[result_folder])57        nd_pf = sorted([predicted_pareto_front[index] for index in nd_pf_indexes], key=lambda x:x[1], reverse=True)58        # Store Predicted Pareto Data59        pf_store_filename = "./Predicted_Frontier/" +  "/".join(pareto_file.split('/')[2:])60        intermediate_folders = "/".join(pf_store_filename.split('/')[:-1]) + "/"61        try:62            os.makedirs(intermediate_folders)63        except:64            pass65        with open(pf_store_filename, "wb") as f:66            writer = csv.writer(f)...

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