def setUp(self):
super(ReportGeneratorTest, self).setUp()
exact_set_lossless = simulator.SketchEstimatorConfig(
name='exact_set-infty-infty-lossless',
sketch_factory=exact_set.ExactSet.get_sketch_factory(),
estimator=exact_set.LosslessEstimator(),
sketch_noiser=None,
estimate_noiser=None)
exact_set_less_one = simulator.SketchEstimatorConfig(
name='exact_set-infty-infty-less_one',
sketch_factory=exact_set.ExactSet.get_sketch_factory(),
estimator=exact_set.LessOneEstimator(),
sketch_noiser=exact_set.AddRandomElementsNoiser(
num_random_elements=0, random_state=np.random.RandomState()),
estimate_noiser=None)
self.sketch_estimator_config_list = (exact_set_lossless,
exact_set_less_one)
self.evaluation_config = configs.EvaluationConfig(
name='test_evaluation',
num_runs=2,
scenario_config_list=[
configs.ScenarioConfig(
name='ind1',
set_generator_factory=(
set_generator.IndependentSetGenerator.
get_generator_factory_with_num_and_size(
universe_size=10, num_sets=5, set_size=1))),
configs.ScenarioConfig(
name='ind2',
set_generator_factory=(
set_generator.IndependentSetGenerator.
get_generator_factory_with_num_and_size(
universe_size=10, num_sets=5, set_size=1))),
])
self.evaluation_run_name = 'test_run'
def _run_evaluation_and_simulation(out_dir):
self.evaluator = evaluator.Evaluator(
evaluation_config=self.evaluation_config,
sketch_estimator_config_list=self.sketch_estimator_config_list,
run_name=self.evaluation_run_name,
out_dir=out_dir)
self.evaluator()
self.analyzer = analyzer.CardinalityEstimatorEvaluationAnalyzer(
out_dir=out_dir,
evaluation_directory=out_dir,
evaluation_run_name=self.evaluation_run_name,
evaluation_name=self.evaluation_config.name,
estimable_criteria_list=[(0.05, 0.95), (1.01, 0.9)])
self.analyzer()
self.run_evaluation_and_simulation = _run_evaluation_and_simulation
def setUp(self):
super(AnalyzerTest, self).setUp()
exact_set_lossless = configs.SketchEstimatorConfig(
name='exact_set_lossless',
sketch_factory=exact_set.ExactSet.get_sketch_factory(),
estimator=exact_set.LosslessEstimator(),
noiser=None)
exact_set_less_one = configs.SketchEstimatorConfig(
name='exact_set_less_one',
sketch_factory=exact_set.ExactSet.get_sketch_factory(),
estimator=exact_set.LessOneEstimator(),
noiser=exact_set.AddRandomElementsNoiser(
num_random_elements=0, random_state=np.random.RandomState()))
self.sketch_estimator_config_list = (exact_set_lossless,
exact_set_less_one)
self.evaluation_config = configs.EvaluationConfig(
name='test_evaluation',
num_runs=2,
scenario_config_list=[
configs.ScenarioConfig(
name='ind1',
set_generator_factory=(
set_generator.IndependentSetGenerator.
get_generator_factory(universe_size=10,
num_sets=5,
set_size=1))),
configs.ScenarioConfig(
name='ind2',
set_generator_factory=(
set_generator.IndependentSetGenerator.
get_generator_factory(universe_size=10,
num_sets=5,
set_size=1))),
])
self.run_name = 'test_run'
def _get_test_evaluator(out_dir):
return evaluator.Evaluator(
evaluation_config=self.evaluation_config,
sketch_estimator_config_list=self.sketch_estimator_config_list,
run_name=self.run_name,
out_dir=out_dir)
self.get_test_evaluator = _get_test_evaluator
def _get_test_analyzer(out_dir, evaluation_dir):
return analyzer.CardinalityEstimatorEvaluationAnalyzer(
out_dir=out_dir,
evaluation_directory=evaluation_dir,
evaluation_run_name=self.run_name,
evaluation_name=self.evaluation_config.name)
self.get_test_analyzer = _get_test_analyzer
def setUp(self):
super(FrequencyEstimatorEvaluationAnalyzerTest, self).setUp()
self.sketch_estimator_config_list = [
configs.SketchEstimatorConfig(
name=evaluation_configs.construct_sketch_estimator_config_name(
sketch_name='exact_multi_set',
sketch_config='10000',
estimator_name='lossless'),
sketch_factory=exact_set.ExactMultiSet.get_sketch_factory(),
estimator=exact_set.LosslessEstimator(),
max_frequency=2,
),
]
self.evaluation_config = configs.EvaluationConfig(
name='frequency_end_to_end_test',
num_runs=1,
scenario_config_list=[
configs.ScenarioConfig(
name='homogeneous',
set_generator_factory=(
frequency_set_generator.HomogeneousMultiSetGenerator.
get_generator_factory_with_num_and_size(
universe_size=100,
num_sets=3,
set_size=50,
freq_rates=[5] * 3,
freq_cap=8,
)))
])
self.run_name = 'test_run'
def setUp(self):
super(EvaluatorTest, self).setUp()
exact_set_lossless = simulator.SketchEstimatorConfig(
name='exact_set_lossless',
sketch_factory=exact_set.ExactSet.get_sketch_factory(),
estimator=exact_set.LosslessEstimator())
exact_set_less_one = simulator.SketchEstimatorConfig(
name='exact_set_less_one',
sketch_factory=exact_set.ExactSet.get_sketch_factory(),
estimator=exact_set.LessOneEstimator(),
sketch_noiser=exact_set.AddRandomElementsNoiser(
num_random_elements=0, random_state=np.random.RandomState()))
self.sketch_estimator_config_list = (exact_set_lossless,
exact_set_less_one)
self.evaluation_config = configs.EvaluationConfig(
name='test_evaluation',
num_runs=2,
scenario_config_list=[
configs.ScenarioConfig(
name='ind1',
set_generator_factory=(
set_generator.IndependentSetGenerator.
get_generator_factory_with_num_and_size(
universe_size=10, num_sets=2, set_size=5))),
configs.ScenarioConfig(
name='ind2',
set_generator_factory=(
set_generator.IndependentSetGenerator.
get_generator_factory_with_num_and_size(
universe_size=10, num_sets=2, set_size=5))),
])
self.run_name = 'test_run'
def _get_test_evaluator(out_dir, overwrite=False):
return evaluator.Evaluator(
evaluation_config=self.evaluation_config,
sketch_estimator_config_list=self.sketch_estimator_config_list,
run_name=self.run_name,
out_dir=out_dir,
overwrite=overwrite)
self.get_test_evaluator = _get_test_evaluator
def main(argv):
if len(argv) > 1:
raise app.UsageError('Too many command-line arguments.')
noiser_flip_probability = 1 / (1 + np.exp(FLAGS.noiser_epsilon))
universe_size = int(100 * FLAGS.sketch_size)
## config all decay rates
estimator_config_list = []
for a in FLAGS.exponential_bloom_filter_decay_rate:
estimator_config_exponential_bloom_filter = SketchEstimatorConfig(
name='exp_BF_' + str(int(a)),
sketch_factory=ExponentialBloomFilter.get_sketch_factory(
FLAGS.sketch_size, a),
estimator=FirstMomentEstimator(
method='exp',
denoiser=SurrealDenoiser(probability=noiser_flip_probability)),
sketch_noiser=BlipNoiser(FLAGS.noiser_epsilon))
estimator_config_list += [estimator_config_exponential_bloom_filter]
# config evaluation
scenario_config_list = []
for set_size_ratio in FLAGS.set_size_ratio:
set_size = int(set_size_ratio * FLAGS.sketch_size)
## list scenarios
scenario_config_list += [
configs.ScenarioConfig(
name=str(int(set_size_ratio)),
set_generator_factory=(set_generator.IndependentSetGenerator.
get_generator_factory_with_num_and_size(
universe_size=universe_size,
num_sets=FLAGS.number_of_sets,
set_size=set_size)))
]
evaluation_config = configs.EvaluationConfig(
name='3_vary_decay_rate_' + str(int(FLAGS.sketch_size / 1000)) + "k",
num_runs=FLAGS.number_of_trials,
scenario_config_list=scenario_config_list)
generate_results = evaluator.Evaluator(
evaluation_config=evaluation_config,
sketch_estimator_config_list=estimator_config_list,
run_name="eval_adbf_result",
out_dir=".",
workers=10)
generate_results()
def main(argv):
if len(argv) > 1:
raise app.UsageError('Too many command-line arguments.')
## config all decay rates
estimator_config_list = []
for sketch_size in FLAGS.sketch_size:
for epsilon in FLAGS.noiser_epsilon:
estimator_config_exponential_bloom_filter = SketchEstimatorConfig(
## flipping prob
name=str(int(sketch_size / 1000)) + "k_" + \
"{:.2f}".format(1 / (1 + np.exp(epsilon))),
sketch_factory=ExponentialBloomFilter.get_sketch_factory(
sketch_size, FLAGS.exponential_bloom_filter_decay_rate),
estimator=FirstMomentEstimator(
method='exp',
denoiser=SurrealDenoiser(epsilon)),
sketch_noiser=BlipNoiser(epsilon))
estimator_config_list += [
estimator_config_exponential_bloom_filter
]
# config evaluation
scenario_config_list = []
for universe_size in FLAGS.universe_size:
scenario_config_list += [
configs.ScenarioConfig(
name="{:.1f}".format(universe_size / 1000000),
set_generator_factory=(set_generator.IndependentSetGenerator.
get_generator_factory_with_num_and_size(
universe_size=universe_size,
num_sets=FLAGS.number_of_sets,
set_size=FLAGS.set_size)))
]
evaluation_config = configs.EvaluationConfig(
name='5_prediction',
num_runs=FLAGS.number_of_trials,
scenario_config_list=scenario_config_list)
generate_results = evaluator.Evaluator(
evaluation_config=evaluation_config,
sketch_estimator_config_list=estimator_config_list,
run_name="eval_adbf_result",
out_dir=".",
workers=10)
generate_results()
def main(argv):
if len(argv) > 1:
raise app.UsageError('Too many command-line arguments.')
noiser_flip_probability = 1 / (1 + np.exp(FLAGS.noiser_epsilon))
## list three adbf estimators
estimator_config_geometric_bloom_filter = SketchEstimatorConfig(
name='geo_BF',
sketch_factory=GeometricBloomFilter.get_sketch_factory(
FLAGS.sketch_size, FLAGS.geometric_bloom_filter_probability),
estimator=FirstMomentEstimator(
method='geo',
denoiser=SurrealDenoiser(
probability=noiser_flip_probability)),
sketch_noiser=BlipNoiser(FLAGS.noiser_epsilon))
estimator_config_logarithmic_bloom_filter = SketchEstimatorConfig(
name='log_BF',
sketch_factory=LogarithmicBloomFilter.get_sketch_factory(
FLAGS.sketch_size),
estimator=FirstMomentEstimator(
method='log',
denoiser=SurrealDenoiser(
probability=noiser_flip_probability)),
sketch_noiser=BlipNoiser(FLAGS.noiser_epsilon))
estimator_config_exponential_bloom_filter = SketchEstimatorConfig(
name='exp_BF',
sketch_factory=ExponentialBloomFilter.get_sketch_factory(
FLAGS.sketch_size, FLAGS.exponential_bloom_filter_decay_rate),
estimator=FirstMomentEstimator(
method='exp',
denoiser=SurrealDenoiser(
probability=noiser_flip_probability)),
sketch_noiser=BlipNoiser(FLAGS.noiser_epsilon))
estimator_config_list = [
estimator_config_geometric_bloom_filter,
estimator_config_logarithmic_bloom_filter,
estimator_config_exponential_bloom_filter,
]
# list scenarios of different set sizes
scenario_config_list = []
for set_size_ratio in FLAGS.set_size_ratio:
set_size = int(set_size_ratio * FLAGS.sketch_size)
scenario_config_list += [
configs.ScenarioConfig(
name="{:.1f}".format(set_size_ratio),
set_generator_factory=(
set_generator.IndependentSetGenerator
.get_generator_factory_with_num_and_size(
universe_size=FLAGS.universe_size,
num_sets=FLAGS.number_of_sets,
set_size=set_size)))
]
evaluation_config = configs.EvaluationConfig(
name='2_vary_set_size',
num_runs=FLAGS.number_of_trials,
scenario_config_list=scenario_config_list)
generate_results = evaluator.Evaluator(
evaluation_config=evaluation_config,
sketch_estimator_config_list=estimator_config_list,
run_name="eval_adbf_result",
out_dir=".",
workers=10)
generate_results()
def main(argv):
if len(argv) > 1:
raise app.UsageError('Too many command-line arguments.')
## list all estimators
estimator_config_list = []
for epsilon in FLAGS.noiser_epsilon:
## flipping prob
noiser_flip_probability = 1 / (1 + np.exp(epsilon))
# estimator_config_bloom_filter = SketchEstimatorConfig(
# name='unif_BF_' + "{:.2f}".format(noiser_flip_probability),
# sketch_factory=BloomFilter.get_sketch_factory(
# FLAGS.sketch_size, FLAGS.num_bloom_filter_hashes),
# estimator=UnionEstimator(),
# sketch_noiser=BlipNoiser(epsilon))
estimator_config_geometric_bloom_filter = SketchEstimatorConfig(
name='geo_BF_' + "{:.2f}".format(noiser_flip_probability),
sketch_factory=GeometricBloomFilter.get_sketch_factory(
FLAGS.sketch_size, FLAGS.geometric_bloom_filter_probability),
estimator=FirstMomentEstimator(method='geo',
denoiser=SurrealDenoiser(epsilon)),
sketch_noiser=BlipNoiser(epsilon))
estimator_config_logarithmic_bloom_filter = SketchEstimatorConfig(
name='log_BF_' + "{:.2f}".format(noiser_flip_probability),
sketch_factory=LogarithmicBloomFilter.get_sketch_factory(
FLAGS.sketch_size),
estimator=FirstMomentEstimator(method='log',
denoiser=SurrealDenoiser(epsilon)),
sketch_noiser=BlipNoiser(epsilon))
estimator_config_exponential_bloom_filter = SketchEstimatorConfig(
name='exp_BF_' + "{:.2f}".format(noiser_flip_probability),
sketch_factory=ExponentialBloomFilter.get_sketch_factory(
FLAGS.sketch_size, FLAGS.exponential_bloom_filter_decay_rate),
estimator=FirstMomentEstimator(method='exp',
denoiser=SurrealDenoiser(epsilon)),
sketch_noiser=BlipNoiser(epsilon))
estimator_config_list += [
# estimator_config_bloom_filter,
estimator_config_geometric_bloom_filter,
estimator_config_logarithmic_bloom_filter,
estimator_config_exponential_bloom_filter,
]
# config evaluation
evaluation_config = configs.EvaluationConfig(
name='1_vary_flip_prob',
num_runs=FLAGS.number_of_trials,
scenario_config_list=[
configs.ScenarioConfig(
name='independent',
set_generator_factory=(set_generator.IndependentSetGenerator.
get_generator_factory_with_num_and_size(
universe_size=FLAGS.universe_size,
num_sets=FLAGS.number_of_sets,
set_size=FLAGS.set_size)))
])
generate_results = evaluator.Evaluator(
evaluation_config=evaluation_config,
sketch_estimator_config_list=estimator_config_list,
run_name="eval_adbf_result",
out_dir=".",
workers=10)
generate_results()
