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DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue707/v3-pruning-variants.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, MaiaEnvironment
from lab.reports import Attribute, geometric_mean
from common_setup import IssueConfig, IssueExperiment, DEFAULT_OPTIMAL_SUITE, is_test_run
BENCHMARKS_DIR=os.path.expanduser('~/repos/downward/benchmarks')
REVISIONS = ["issue707-v3"]
CONFIGS = [
IssueConfig('rl-b50k-nopruneunreachable', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1,prune_unreachable_states=false))']),
IssueConfig('dfp-b50k-nopruneunreachable', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1,prune_unreachable_states=false))']),
IssueConfig('sccs-dfp-b50k-nopruneunreachable', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_bisimulation(greedy=false),merge_strategy=merge_sccs(order_of_sccs=topological,merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order(atomic_ts_order=reverse_level,product_ts_order=new_to_old,atomic_before_product=false)])),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1,prune_unreachable_states=false))']),
IssueConfig('rl-ginf-nopruneunreachable', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1,prune_unreachable_states=false))']),
IssueConfig('dfp-ginf-nopruneunreachable', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1,prune_unreachable_states=false))']),
IssueConfig('sccs-dfp-ginf-nopruneunreachable', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_bisimulation(greedy=true),merge_strategy=merge_sccs(order_of_sccs=topological,merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order(atomic_ts_order=reverse_level,product_ts_order=new_to_old,atomic_before_product=false)])),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1,prune_unreachable_states=false))']),
IssueConfig('rl-f50k-nopruneunreachable', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000,prune_unreachable_states=false))']),
IssueConfig('dfp-f50k-nopruneunreachable', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000,prune_unreachable_states=false))']),
IssueConfig('sccs-dfp-f50k-nopruneunreachable', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_fh(),merge_strategy=merge_sccs(order_of_sccs=topological,merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order(atomic_ts_order=reverse_level,product_ts_order=new_to_old,atomic_before_product=false)])),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,prune_unreachable_states=false))']),
IssueConfig('rl-b50k-nopruneirrelevant', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1,prune_irrelevant_states=false))']),
IssueConfig('dfp-b50k-nopruneirrelevant', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1,prune_irrelevant_states=false))']),
IssueConfig('sccs-dfp-b50k-nopruneirrelevant', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_bisimulation(greedy=false),merge_strategy=merge_sccs(order_of_sccs=topological,merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order(atomic_ts_order=reverse_level,product_ts_order=new_to_old,atomic_before_product=false)])),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1,prune_irrelevant_states=false))']),
IssueConfig('rl-ginf-nopruneirrelevant', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1,prune_irrelevant_states=false))']),
IssueConfig('dfp-ginf-nopruneirrelevant', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1,prune_irrelevant_states=false))']),
IssueConfig('sccs-dfp-ginf-nopruneirrelevant', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_bisimulation(greedy=true),merge_strategy=merge_sccs(order_of_sccs=topological,merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order(atomic_ts_order=reverse_level,product_ts_order=new_to_old,atomic_before_product=false)])),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1,prune_irrelevant_states=false))']),
IssueConfig('rl-f50k-nopruneirrelevant', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000,prune_irrelevant_states=false))']),
IssueConfig('dfp-f50k-nopruneirrelevant', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000,prune_irrelevant_states=false))']),
IssueConfig('sccs-dfp-f50k-nopruneirrelevant', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_fh(),merge_strategy=merge_sccs(order_of_sccs=topological,merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order(atomic_ts_order=reverse_level,product_ts_order=new_to_old,atomic_before_product=false)])),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,prune_irrelevant_states=false))']),
IssueConfig('rl-b50k-noprune', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1,prune_unreachable_states=false,prune_irrelevant_states=false))']),
IssueConfig('dfp-b50k-noprune', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1,prune_unreachable_states=false,prune_irrelevant_states=false))']),
IssueConfig('sccs-dfp-b50k-noprune', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_bisimulation(greedy=false),merge_strategy=merge_sccs(order_of_sccs=topological,merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order(atomic_ts_order=reverse_level,product_ts_order=new_to_old,atomic_before_product=false)])),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1,prune_unreachable_states=false,prune_irrelevant_states=false))']),
IssueConfig('rl-ginf-noprune', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1,prune_unreachable_states=false,prune_irrelevant_states=false))']),
IssueConfig('dfp-ginf-noprune', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1,prune_unreachable_states=false,prune_irrelevant_states=false))']),
IssueConfig('sccs-dfp-ginf-noprune', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_bisimulation(greedy=true),merge_strategy=merge_sccs(order_of_sccs=topological,merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order(atomic_ts_order=reverse_level,product_ts_order=new_to_old,atomic_before_product=false)])),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1,prune_unreachable_states=false,prune_irrelevant_states=false))']),
IssueConfig('rl-f50k-noprune', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000,prune_unreachable_states=false,prune_irrelevant_states=false))']),
IssueConfig('dfp-f50k-noprune', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000,prune_unreachable_states=false,prune_irrelevant_states=false))']),
IssueConfig('sccs-dfp-f50k-noprune', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_fh(),merge_strategy=merge_sccs(order_of_sccs=topological,merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order(atomic_ts_order=reverse_level,product_ts_order=new_to_old,atomic_before_product=false)])),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,prune_unreachable_states=false,prune_irrelevant_states=false))']),
]
SUITE = DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = MaiaEnvironment(
priority=-100, email='[email protected]')
if is_test_run():
SUITE = ['depot:p01.pddl', 'depot:p02.pddl', 'parcprinter-opt11-strips:p01.pddl', 'parcprinter-opt11-strips:p02.pddl', 'mystery:prob07.pddl']
ENVIRONMENT = LocalEnvironment(processes=4)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py')
exp.add_command('ms-parser', ['{ms_parser}'])
exp.add_suite(BENCHMARKS_DIR, SUITE)
# planner outcome attributes
perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False)
# m&s attributes
ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[geometric_mean])
ms_atomic_construction_time = Attribute('ms_atomic_construction_time', absolute=False, min_wins=True, functions=[geometric_mean])
ms_abstraction_constructed = Attribute('ms_abstraction_constructed', absolute=True, min_wins=False)
ms_final_size = Attribute('ms_final_size', absolute=False, min_wins=True)
ms_out_of_memory = Attribute('ms_out_of_memory', absolute=True, min_wins=True)
ms_out_of_time = Attribute('ms_out_of_time', absolute=True, min_wins=True)
search_out_of_memory = Attribute('search_out_of_memory', absolute=True, min_wins=True)
search_out_of_time = Attribute('search_out_of_time', absolute=True, min_wins=True)
extra_attributes = [
perfect_heuristic,
ms_construction_time,
ms_atomic_construction_time,
ms_abstraction_constructed,
ms_final_size,
ms_out_of_memory,
ms_out_of_time,
search_out_of_memory,
search_out_of_time,
]
attributes = exp.DEFAULT_TABLE_ATTRIBUTES
attributes.extend(extra_attributes)
exp.add_absolute_report_step(attributes=attributes)
exp.run_steps()
| 13,476 | 140.863158 | 533 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue707/v2-pruning-variants.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, MaiaEnvironment
from lab.reports import Attribute, geometric_mean
from common_setup import IssueConfig, IssueExperiment, DEFAULT_OPTIMAL_SUITE, is_test_run
BENCHMARKS_DIR=os.path.expanduser('~/repos/downward/benchmarks')
REVISIONS = ["issue707-v2"]
CONFIGS = [
IssueConfig('rl-b50k-nopruneunreachable', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1,prune_unreachable_states=false))']),
IssueConfig('dfp-b50k-nopruneunreachable', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1,prune_unreachable_states=false))']),
IssueConfig('rl-ginf-nopruneunreachable', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1,prune_unreachable_states=false))']),
IssueConfig('dfp-ginf-nopruneunreachable', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1,prune_unreachable_states=false))']),
IssueConfig('rl-f50k-nopruneunreachable', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000,prune_unreachable_states=false))']),
IssueConfig('dfp-f50k-nopruneunreachable', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000,prune_unreachable_states=false))']),
IssueConfig('rl-b50k-nopruneirrelevant', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1,prune_irrelevant_states=false))']),
IssueConfig('dfp-b50k-nopruneirrelevant', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1,prune_irrelevant_states=false))']),
IssueConfig('rl-ginf-nopruneirrelevant', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1,prune_irrelevant_states=false))']),
IssueConfig('dfp-ginf-nopruneirrelevant', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1,prune_irrelevant_states=false))']),
IssueConfig('rl-f50k-nopruneirrelevant', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000,prune_irrelevant_states=false))']),
IssueConfig('dfp-f50k-nopruneirrelevant', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000,prune_irrelevant_states=false))']),
IssueConfig('rl-b50k-noprune', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1,prune_unreachable_states=false,prune_irrelevant_states=false))']),
IssueConfig('dfp-b50k-noprune', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1,prune_unreachable_states=false,prune_irrelevant_states=false))']),
IssueConfig('rl-ginf-noprune', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1,prune_unreachable_states=false,prune_irrelevant_states=false))']),
IssueConfig('dfp-ginf-noprune', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1,prune_unreachable_states=false,prune_irrelevant_states=false))']),
IssueConfig('rl-f50k-noprune', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000,prune_unreachable_states=false,prune_irrelevant_states=false))']),
IssueConfig('dfp-f50k-noprune', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000,prune_unreachable_states=false,prune_irrelevant_states=false))']),
]
SUITE = DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = MaiaEnvironment(
priority=0, email='[email protected]')
if is_test_run():
SUITE = ['depot:p01.pddl', 'depot:p02.pddl', 'parcprinter-opt11-strips:p01.pddl', 'parcprinter-opt11-strips:p02.pddl', 'mystery:prob07.pddl']
ENVIRONMENT = LocalEnvironment(processes=4)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py')
exp.add_command('ms-parser', ['{ms_parser}'])
exp.add_suite(BENCHMARKS_DIR, SUITE)
# planner outcome attributes
perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False)
# m&s attributes
ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[geometric_mean])
ms_atomic_construction_time = Attribute('ms_atomic_construction_time', absolute=False, min_wins=True, functions=[geometric_mean])
ms_abstraction_constructed = Attribute('ms_abstraction_constructed', absolute=True, min_wins=False)
ms_final_size = Attribute('ms_final_size', absolute=False, min_wins=True)
ms_out_of_memory = Attribute('ms_out_of_memory', absolute=True, min_wins=True)
ms_out_of_time = Attribute('ms_out_of_time', absolute=True, min_wins=True)
search_out_of_memory = Attribute('search_out_of_memory', absolute=True, min_wins=True)
search_out_of_time = Attribute('search_out_of_time', absolute=True, min_wins=True)
extra_attributes = [
perfect_heuristic,
ms_construction_time,
ms_atomic_construction_time,
ms_abstraction_constructed,
ms_final_size,
ms_out_of_memory,
ms_out_of_time,
search_out_of_memory,
search_out_of_time,
]
attributes = exp.DEFAULT_TABLE_ATTRIBUTES
attributes.extend(extra_attributes)
exp.add_absolute_report_step(attributes=attributes)
exp.run_steps()
| 8,940 | 102.965116 | 420 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue707/ms-parser.py
|
#! /usr/bin/env python
from lab.parser import Parser
parser = Parser()
parser.add_pattern('ms_final_size', 'Final transition system size: (\d+)', required=False, type=int)
parser.add_pattern('ms_construction_time', 'Done initializing merge-and-shrink heuristic \[(.+)s\]', required=False, type=float)
parser.add_pattern('ms_atomic_construction_time', 't=(.+)s \(after computation of atomic transition systems\)', required=False, type=float)
parser.add_pattern('ms_memory_delta', 'Final peak memory increase of merge-and-shrink computation: (\d+) KB', required=False, type=int)
def check_ms_constructed(content, props):
ms_construction_time = props.get('ms_construction_time')
abstraction_constructed = False
if ms_construction_time is not None:
abstraction_constructed = True
props['ms_abstraction_constructed'] = abstraction_constructed
parser.add_function(check_ms_constructed)
def check_planner_exit_reason(content, props):
ms_abstraction_constructed = props.get('ms_abstraction_constructed')
error = props.get('error')
if error != 'none' and error != 'timeout' and error != 'out-of-memory':
print 'error: %s' % error
return
# Check whether merge-and-shrink computation or search ran out of
# time or memory.
ms_out_of_time = False
ms_out_of_memory = False
search_out_of_time = False
search_out_of_memory = False
if ms_abstraction_constructed == False:
if error == 'timeout':
ms_out_of_time = True
elif error == 'out-of-memory':
ms_out_of_memory = True
elif ms_abstraction_constructed == True:
if error == 'timeout':
search_out_of_time = True
elif error == 'out-of-memory':
search_out_of_memory = True
props['ms_out_of_time'] = ms_out_of_time
props['ms_out_of_memory'] = ms_out_of_memory
props['search_out_of_time'] = search_out_of_time
props['search_out_of_memory'] = search_out_of_memory
parser.add_function(check_planner_exit_reason)
def check_perfect_heuristic(content, props):
plan_length = props.get('plan_length')
expansions = props.get('expansions')
if plan_length != None:
perfect_heuristic = False
if plan_length + 1 == expansions:
perfect_heuristic = True
props['perfect_heuristic'] = perfect_heuristic
parser.add_function(check_perfect_heuristic)
parser.parse()
| 2,415 | 37.967742 | 139 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue707/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import ComparativeReport
from downward.reports.scatter import ScatterPlotReport
try:
from relativescatter import RelativeScatterPlotReport
matplotlib = True
except ImportError:
print 'matplotlib not availabe, scatter plots not available'
matplotlib = False
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
DEFAULT_OPTIMAL_SUITE = [
'airport', 'barman-opt11-strips', 'barman-opt14-strips', 'blocks',
'childsnack-opt14-strips', 'depot', 'driverlog',
'elevators-opt08-strips', 'elevators-opt11-strips',
'floortile-opt11-strips', 'floortile-opt14-strips', 'freecell',
'ged-opt14-strips', 'grid', 'gripper', 'hiking-opt14-strips',
'logistics00', 'logistics98', 'miconic', 'movie', 'mprime',
'mystery', 'nomystery-opt11-strips', 'openstacks-opt08-strips',
'openstacks-opt11-strips', 'openstacks-opt14-strips',
'openstacks-strips', 'parcprinter-08-strips',
'parcprinter-opt11-strips', 'parking-opt11-strips',
'parking-opt14-strips', 'pathways-noneg', 'pegsol-08-strips',
'pegsol-opt11-strips', 'pipesworld-notankage',
'pipesworld-tankage', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-opt11-strips',
'sokoban-opt08-strips', 'sokoban-opt11-strips', 'storage',
'tetris-opt14-strips', 'tidybot-opt11-strips',
'tidybot-opt14-strips', 'tpp', 'transport-opt08-strips',
'transport-opt11-strips', 'transport-opt14-strips',
'trucks-strips', 'visitall-opt11-strips', 'visitall-opt14-strips',
'woodworking-opt08-strips', 'woodworking-opt11-strips',
'zenotravel']
DEFAULT_SATISFICING_SUITE = [
'airport', 'assembly', 'barman-sat11-strips',
'barman-sat14-strips', 'blocks', 'cavediving-14-adl',
'childsnack-sat14-strips', 'citycar-sat14-adl', 'depot',
'driverlog', 'elevators-sat08-strips', 'elevators-sat11-strips',
'floortile-sat11-strips', 'floortile-sat14-strips', 'freecell',
'ged-sat14-strips', 'grid', 'gripper', 'hiking-sat14-strips',
'logistics00', 'logistics98', 'maintenance-sat14-adl', 'miconic',
'miconic-fulladl', 'miconic-simpleadl', 'movie', 'mprime',
'mystery', 'nomystery-sat11-strips', 'openstacks',
'openstacks-sat08-adl', 'openstacks-sat08-strips',
'openstacks-sat11-strips', 'openstacks-sat14-strips',
'openstacks-strips', 'optical-telegraphs', 'parcprinter-08-strips',
'parcprinter-sat11-strips', 'parking-sat11-strips',
'parking-sat14-strips', 'pathways', 'pathways-noneg',
'pegsol-08-strips', 'pegsol-sat11-strips', 'philosophers',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-large',
'psr-middle', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-sat11-strips', 'schedule',
'sokoban-sat08-strips', 'sokoban-sat11-strips', 'storage',
'tetris-sat14-strips', 'thoughtful-sat14-strips',
'tidybot-sat11-strips', 'tpp', 'transport-sat08-strips',
'transport-sat11-strips', 'transport-sat14-strips', 'trucks',
'trucks-strips', 'visitall-sat11-strips', 'visitall-sat14-strips',
'woodworking-sat08-strips', 'woodworking-sat11-strips',
'zenotravel']
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return (
"cluster" in node or
node.startswith("gkigrid") or
node in ["habakuk", "turtur"])
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
"unsolvable",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, outfile=outfile)
self.add_step(
'publish-absolute-report', subprocess.call, ['publish', outfile])
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = ComparativeReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.%s" % (
self.name, rev1, rev2, report.output_format))
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
subprocess.call(["publish", outfile])
self.add_step("make-comparison-tables", make_comparison_tables)
self.add_step(
"publish-comparison-tables", publish_comparison_tables)
def add_scatter_plot_step(self, relative=False, attributes=None):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if matplotlib:
if relative:
report_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
report_class = ScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "{}-{}".format(rev1, config_nick)
algo2 = "{}-{}".format(rev2, config_nick)
report = report_class(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(step_name, make_scatter_plots)
| 14,475 | 35.834606 | 81 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue707/v5-debug.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, MaiaEnvironment
from lab.reports import Attribute, geometric_mean
from common_setup import IssueConfig, IssueExperiment, DEFAULT_OPTIMAL_SUITE, is_test_run
BENCHMARKS_DIR=os.path.expanduser('~/repos/downward/benchmarks')
REVISIONS = ["issue707-base-v2", "issue707-v5"]
CONFIGS = [
IssueConfig('dfp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))'],build_options=['--debug'], driver_options=['--debug', '--search-time-limit', '60s']),
IssueConfig('rl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))'],build_options=['--debug'], driver_options=['--debug', '--search-time-limit', '60s']),
IssueConfig('sccs-dfp-b50k', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_bisimulation(greedy=false),merge_strategy=merge_sccs(order_of_sccs=topological,merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order(atomic_ts_order=reverse_level,product_ts_order=new_to_old,atomic_before_product=false)])),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))'],build_options=['--debug'], driver_options=['--debug', '--search-time-limit', '60s']),
IssueConfig('dfp-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1))'],build_options=['--debug'], driver_options=['--debug', '--search-time-limit', '60s']),
IssueConfig('rl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1))'],build_options=['--debug'], driver_options=['--debug', '--search-time-limit', '60s']),
IssueConfig('sccs-dfp-ginf', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_bisimulation(greedy=true),merge_strategy=merge_sccs(order_of_sccs=topological,merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order(atomic_ts_order=reverse_level,product_ts_order=new_to_old,atomic_before_product=false)])),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1))'],build_options=['--debug'], driver_options=['--debug', '--search-time-limit', '60s']),
IssueConfig('dfp-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000))'],build_options=['--debug'], driver_options=['--debug', '--search-time-limit', '60s']),
IssueConfig('rl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000))'],build_options=['--debug'], driver_options=['--debug', '--search-time-limit', '60s']),
IssueConfig('sccs-dfp-f50k', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_fh(),merge_strategy=merge_sccs(order_of_sccs=topological,merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order(atomic_ts_order=reverse_level,product_ts_order=new_to_old,atomic_before_product=false)])),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000))'],build_options=['--debug'], driver_options=['--debug', '--search-time-limit', '60s']),
]
SUITE = DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = MaiaEnvironment(
priority=0, email='[email protected]')
if is_test_run():
SUITE = ['depot:p01.pddl', 'depot:p02.pddl', 'parcprinter-opt11-strips:p01.pddl', 'parcprinter-opt11-strips:p02.pddl', 'mystery:prob07.pddl']
ENVIRONMENT = LocalEnvironment(processes=4)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py')
exp.add_command('ms-parser', ['{ms_parser}'])
exp.add_suite(BENCHMARKS_DIR, SUITE)
# planner outcome attributes
perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False)
# m&s attributes
ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[geometric_mean])
ms_atomic_construction_time = Attribute('ms_atomic_construction_time', absolute=False, min_wins=True, functions=[geometric_mean])
ms_abstraction_constructed = Attribute('ms_abstraction_constructed', absolute=True, min_wins=False)
ms_final_size = Attribute('ms_final_size', absolute=False, min_wins=True)
ms_out_of_memory = Attribute('ms_out_of_memory', absolute=True, min_wins=True)
ms_out_of_time = Attribute('ms_out_of_time', absolute=True, min_wins=True)
search_out_of_memory = Attribute('search_out_of_memory', absolute=True, min_wins=True)
search_out_of_time = Attribute('search_out_of_time', absolute=True, min_wins=True)
extra_attributes = [
perfect_heuristic,
ms_construction_time,
ms_atomic_construction_time,
ms_abstraction_constructed,
ms_final_size,
ms_out_of_memory,
ms_out_of_time,
search_out_of_memory,
search_out_of_time,
]
attributes = exp.DEFAULT_TABLE_ATTRIBUTES
attributes.extend(extra_attributes)
exp.add_comparison_table_step(attributes=attributes)
exp.add_scatter_plot_step()
exp.run_steps()
| 6,259 | 82.466667 | 548 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue707/v3.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, MaiaEnvironment
from lab.reports import Attribute, geometric_mean
from common_setup import IssueConfig, IssueExperiment, DEFAULT_OPTIMAL_SUITE, is_test_run
BENCHMARKS_DIR=os.path.expanduser('~/repos/downward/benchmarks')
REVISIONS = ["issue707-base-v2", "issue707-v3"]
CONFIGS = [
IssueConfig('dfp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('rl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('sccs-dfp-b50k', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_bisimulation(greedy=false),merge_strategy=merge_sccs(order_of_sccs=topological,merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order(atomic_ts_order=reverse_level,product_ts_order=new_to_old,atomic_before_product=false)])),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1))']),
IssueConfig('rl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1))']),
IssueConfig('sccs-dfp-ginf', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_bisimulation(greedy=true),merge_strategy=merge_sccs(order_of_sccs=topological,merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order(atomic_ts_order=reverse_level,product_ts_order=new_to_old,atomic_before_product=false)])),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1))']),
IssueConfig('dfp-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000))']),
IssueConfig('rl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000))']),
IssueConfig('sccs-dfp-f50k', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_fh(),merge_strategy=merge_sccs(order_of_sccs=topological,merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order(atomic_ts_order=reverse_level,product_ts_order=new_to_old,atomic_before_product=false)])),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000))']),
]
SUITE = DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = MaiaEnvironment(
priority=-100, email='[email protected]')
if is_test_run():
SUITE = ['depot:p01.pddl', 'depot:p02.pddl', 'parcprinter-opt11-strips:p01.pddl', 'parcprinter-opt11-strips:p02.pddl', 'mystery:prob07.pddl']
ENVIRONMENT = LocalEnvironment(processes=4)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py')
exp.add_command('ms-parser', ['{ms_parser}'])
exp.add_suite(BENCHMARKS_DIR, SUITE)
# planner outcome attributes
perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False)
# m&s attributes
ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[geometric_mean])
ms_atomic_construction_time = Attribute('ms_atomic_construction_time', absolute=False, min_wins=True, functions=[geometric_mean])
ms_abstraction_constructed = Attribute('ms_abstraction_constructed', absolute=True, min_wins=False)
ms_final_size = Attribute('ms_final_size', absolute=False, min_wins=True)
ms_out_of_memory = Attribute('ms_out_of_memory', absolute=True, min_wins=True)
ms_out_of_time = Attribute('ms_out_of_time', absolute=True, min_wins=True)
search_out_of_memory = Attribute('search_out_of_memory', absolute=True, min_wins=True)
search_out_of_time = Attribute('search_out_of_time', absolute=True, min_wins=True)
extra_attributes = [
perfect_heuristic,
ms_construction_time,
ms_atomic_construction_time,
ms_abstraction_constructed,
ms_final_size,
ms_out_of_memory,
ms_out_of_time,
search_out_of_memory,
search_out_of_time,
]
attributes = exp.DEFAULT_TABLE_ATTRIBUTES
attributes.extend(extra_attributes)
exp.add_comparison_table_step(attributes=attributes)
exp.add_scatter_plot_step()
exp.run_steps()
| 5,554 | 70.217949 | 464 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue707/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(
axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows a relative comparison of two
algorithms with regard to the given attribute. The attribute value
of algorithm 1 is shown on the x-axis and the relation to the value
of algorithm 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['algorithm'] == self.algorithms[0] and
run2['algorithm'] == self.algorithms[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.algorithms[0], val1)
assert val2 > 0, (domain, problem, self.algorithms[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlot uses log-scaling on the x-axis by default.
PlotReport._set_scales(
self, xscale or self.attribute.scale or 'log', 'log')
| 3,875 | 35.566038 | 78 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue707/v5.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, MaiaEnvironment
from lab.reports import Attribute, geometric_mean
from common_setup import IssueConfig, IssueExperiment, DEFAULT_OPTIMAL_SUITE, is_test_run
BENCHMARKS_DIR=os.path.expanduser('~/repos/downward/benchmarks')
REVISIONS = ["issue707-base-v2", "issue707-v5"]
CONFIGS = [
IssueConfig('dfp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('rl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('sccs-dfp-b50k', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_bisimulation(greedy=false),merge_strategy=merge_sccs(order_of_sccs=topological,merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order(atomic_ts_order=reverse_level,product_ts_order=new_to_old,atomic_before_product=false)])),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']),
IssueConfig('dfp-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1))']),
IssueConfig('rl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1))']),
IssueConfig('sccs-dfp-ginf', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_bisimulation(greedy=true),merge_strategy=merge_sccs(order_of_sccs=topological,merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order(atomic_ts_order=reverse_level,product_ts_order=new_to_old,atomic_before_product=false)])),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1))']),
IssueConfig('dfp-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000))']),
IssueConfig('rl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000))']),
IssueConfig('sccs-dfp-f50k', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_fh(),merge_strategy=merge_sccs(order_of_sccs=topological,merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order(atomic_ts_order=reverse_level,product_ts_order=new_to_old,atomic_before_product=false)])),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000))']),
]
SUITE = DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = MaiaEnvironment(
priority=0, email='[email protected]')
if is_test_run():
SUITE = ['depot:p01.pddl', 'depot:p02.pddl', 'parcprinter-opt11-strips:p01.pddl', 'parcprinter-opt11-strips:p02.pddl', 'mystery:prob07.pddl']
ENVIRONMENT = LocalEnvironment(processes=4)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py')
exp.add_command('ms-parser', ['{ms_parser}'])
exp.add_suite(BENCHMARKS_DIR, SUITE)
# planner outcome attributes
perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False)
# m&s attributes
ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[geometric_mean])
ms_atomic_construction_time = Attribute('ms_atomic_construction_time', absolute=False, min_wins=True, functions=[geometric_mean])
ms_abstraction_constructed = Attribute('ms_abstraction_constructed', absolute=True, min_wins=False)
ms_final_size = Attribute('ms_final_size', absolute=False, min_wins=True)
ms_out_of_memory = Attribute('ms_out_of_memory', absolute=True, min_wins=True)
ms_out_of_time = Attribute('ms_out_of_time', absolute=True, min_wins=True)
search_out_of_memory = Attribute('search_out_of_memory', absolute=True, min_wins=True)
search_out_of_time = Attribute('search_out_of_time', absolute=True, min_wins=True)
extra_attributes = [
perfect_heuristic,
ms_construction_time,
ms_atomic_construction_time,
ms_abstraction_constructed,
ms_final_size,
ms_out_of_memory,
ms_out_of_time,
search_out_of_memory,
search_out_of_time,
]
attributes = exp.DEFAULT_TABLE_ATTRIBUTES
attributes.extend(extra_attributes)
exp.add_comparison_table_step(attributes=attributes)
exp.add_scatter_plot_step()
exp.run_steps()
| 5,503 | 72.386667 | 464 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue707/v1-pruning-variants.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, MaiaEnvironment
from lab.reports import Attribute, geometric_mean
from common_setup import IssueConfig, IssueExperiment, DEFAULT_OPTIMAL_SUITE, is_test_run
BENCHMARKS_DIR=os.path.expanduser('~/repos/downward/benchmarks')
REVISIONS = ["issue707-v1"]
CONFIGS = [
IssueConfig('rl-b50k-pruneinit', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1,prune_unreachable_states=false))']),
IssueConfig('dfp-b50k-pruneinit', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1,prune_unreachable_states=false))']),
IssueConfig('rl-ginf-pruneinit', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1,prune_unreachable_states=false))']),
IssueConfig('dfp-ginf-pruneinit', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1,prune_unreachable_states=false))']),
IssueConfig('rl-f50k-pruneinit', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000,prune_unreachable_states=false))']),
IssueConfig('dfp-f50k-pruneinit', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000,prune_unreachable_states=false))']),
IssueConfig('rl-b50k-prunegoal', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1,prune_irrelevant_states=false))']),
IssueConfig('dfp-b50k-prunegoal', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1,prune_irrelevant_states=false))']),
IssueConfig('rl-ginf-prunegoal', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1,prune_irrelevant_states=false))']),
IssueConfig('dfp-ginf-prunegoal', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1,prune_irrelevant_states=false))']),
IssueConfig('rl-f50k-prunegoal', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000,prune_irrelevant_states=false))']),
IssueConfig('dfp-f50k-prunegoal', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000,prune_irrelevant_states=false))']),
IssueConfig('rl-b50k-noprune', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1,prune_unreachable_states=false,prune_irrelevant_states=false))']),
IssueConfig('dfp-b50k-noprune', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1,prune_unreachable_states=false,prune_irrelevant_states=false))']),
IssueConfig('rl-ginf-noprune', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1,prune_unreachable_states=false,prune_irrelevant_states=false))']),
IssueConfig('dfp-ginf-noprune', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1,prune_unreachable_states=false,prune_irrelevant_states=false))']),
IssueConfig('rl-f50k-noprune', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=reverse_level)),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000,prune_unreachable_states=false,prune_irrelevant_states=false))']),
IssueConfig('dfp-f50k-noprune', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[goal_relevance,dfp,total_order])),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000,prune_unreachable_states=false,prune_irrelevant_states=false))']),
]
SUITE = DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = MaiaEnvironment(
priority=0, email='[email protected]')
if is_test_run():
SUITE = ['depot:p01.pddl', 'depot:p02.pddl', 'parcprinter-opt11-strips:p01.pddl', 'parcprinter-opt11-strips:p02.pddl', 'mystery:prob07.pddl']
ENVIRONMENT = LocalEnvironment(processes=4)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py')
exp.add_command('ms-parser', ['{ms_parser}'])
exp.add_suite(BENCHMARKS_DIR, SUITE)
# planner outcome attributes
perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False)
# m&s attributes
ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[geometric_mean])
ms_atomic_construction_time = Attribute('ms_atomic_construction_time', absolute=False, min_wins=True, functions=[geometric_mean])
ms_abstraction_constructed = Attribute('ms_abstraction_constructed', absolute=True, min_wins=False)
ms_final_size = Attribute('ms_final_size', absolute=False, min_wins=True)
ms_out_of_memory = Attribute('ms_out_of_memory', absolute=True, min_wins=True)
ms_out_of_time = Attribute('ms_out_of_time', absolute=True, min_wins=True)
search_out_of_memory = Attribute('search_out_of_memory', absolute=True, min_wins=True)
search_out_of_time = Attribute('search_out_of_time', absolute=True, min_wins=True)
extra_attributes = [
perfect_heuristic,
ms_construction_time,
ms_atomic_construction_time,
ms_abstraction_constructed,
ms_final_size,
ms_out_of_memory,
ms_out_of_time,
search_out_of_memory,
search_out_of_time,
]
attributes = exp.DEFAULT_TABLE_ATTRIBUTES
attributes.extend(extra_attributes)
exp.add_absolute_report_step(attributes=attributes)
exp.run_steps()
| 8,838 | 101.77907 | 420 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue694/v2-opt.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import itertools
import os
from lab.environments import LocalEnvironment, MaiaEnvironment
from downward.reports.compare import ComparativeReport
import common_setup
from common_setup import IssueConfig, IssueExperiment, RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue694-v2-base", "issue694-v2"]
BUILDS = ["release32", "release64"]
SEARCHES = [
("blind", "astar(blind())"),
("lmcut", "astar(lmcut())"),
]
CONFIGS = [
IssueConfig(
"{nick}-{build}".format(**locals()),
["--search", search],
build_options=[build],
driver_options=["--build", build])
for nick, search in SEARCHES
for build in BUILDS
]
ATTRIBUTES = [
"coverage", "error", "expansions_until_last_jump", "memory",
"score_memory", "total_time", "score_total_time",
"int_hash_set_load_factor", "int_hash_set_resizes"]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = MaiaEnvironment(
priority=0, email="[email protected]")
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_command('run-custom-parser', [os.path.join(DIR, 'custom-parser.py')])
exp.add_comparison_table_step(attributes=ATTRIBUTES)
for relative in [False, True]:
exp.add_scatter_plot_step(relative=relative, attributes=["memory", "total_time"])
exp.run_steps()
| 1,644 | 28.375 | 85 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue694/v1-opt.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import itertools
import os
from lab.environments import LocalEnvironment, MaiaEnvironment
from downward.reports.compare import ComparativeReport
import common_setup
from common_setup import IssueConfig, IssueExperiment, RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue694-v1-base", "issue694-v1"]
BUILDS = ["release32", "release64"]
SEARCHES = [
("blind", "astar(blind())"),
("lmcut", "astar(lmcut())"),
]
CONFIGS = [
IssueConfig(
"{nick}-{build}".format(**locals()),
["--search", search],
build_options=[build],
driver_options=["--build", build])
for nick, search in SEARCHES
for build in BUILDS
]
ATTRIBUTES = [
"coverage", "error", "expansions_until_last_jump", "memory",
"score_memory", "total_time", "score_total_time",
"int_hash_set_load_factor", "int_hash_set_resizes"]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = MaiaEnvironment(
priority=0, email="[email protected]")
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_command('run-custom-parser', [os.path.join(DIR, 'custom-parser.py')])
exp.add_comparison_table_step(attributes=ATTRIBUTES)
for relative in [False, True]:
exp.add_scatter_plot_step(relative=relative, attributes=["memory", "total_time"])
exp.run_steps()
| 1,644 | 28.375 | 85 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue694/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab.steps import Step
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import ComparativeReport
from downward.reports.scatter import ScatterPlotReport
from relativescatter import RelativeScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
DEFAULT_OPTIMAL_SUITE = [
'airport', 'barman-opt11-strips', 'barman-opt14-strips', 'blocks',
'childsnack-opt14-strips', 'depot', 'driverlog',
'elevators-opt08-strips', 'elevators-opt11-strips',
'floortile-opt11-strips', 'floortile-opt14-strips', 'freecell',
'ged-opt14-strips', 'grid', 'gripper', 'hiking-opt14-strips',
'logistics00', 'logistics98', 'miconic', 'movie', 'mprime',
'mystery', 'nomystery-opt11-strips', 'openstacks-opt08-strips',
'openstacks-opt11-strips', 'openstacks-opt14-strips',
'openstacks-strips', 'parcprinter-08-strips',
'parcprinter-opt11-strips', 'parking-opt11-strips',
'parking-opt14-strips', 'pathways-noneg', 'pegsol-08-strips',
'pegsol-opt11-strips', 'pipesworld-notankage',
'pipesworld-tankage', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-opt11-strips',
'sokoban-opt08-strips', 'sokoban-opt11-strips', 'storage',
'tetris-opt14-strips', 'tidybot-opt11-strips',
'tidybot-opt14-strips', 'tpp', 'transport-opt08-strips',
'transport-opt11-strips', 'transport-opt14-strips',
'trucks-strips', 'visitall-opt11-strips', 'visitall-opt14-strips',
'woodworking-opt08-strips', 'woodworking-opt11-strips',
'zenotravel']
DEFAULT_SATISFICING_SUITE = [
'airport', 'assembly', 'barman-sat11-strips',
'barman-sat14-strips', 'blocks', 'cavediving-14-adl',
'childsnack-sat14-strips', 'citycar-sat14-adl', 'depot',
'driverlog', 'elevators-sat08-strips', 'elevators-sat11-strips',
'floortile-sat11-strips', 'floortile-sat14-strips', 'freecell',
'ged-sat14-strips', 'grid', 'gripper', 'hiking-sat14-strips',
'logistics00', 'logistics98', 'maintenance-sat14-adl', 'miconic',
'miconic-fulladl', 'miconic-simpleadl', 'movie', 'mprime',
'mystery', 'nomystery-sat11-strips', 'openstacks',
'openstacks-sat08-adl', 'openstacks-sat08-strips',
'openstacks-sat11-strips', 'openstacks-sat14-strips',
'openstacks-strips', 'optical-telegraphs', 'parcprinter-08-strips',
'parcprinter-sat11-strips', 'parking-sat11-strips',
'parking-sat14-strips', 'pathways', 'pathways-noneg',
'pegsol-08-strips', 'pegsol-sat11-strips', 'philosophers',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-large',
'psr-middle', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-sat11-strips', 'schedule',
'sokoban-sat08-strips', 'sokoban-sat11-strips', 'storage',
'tetris-sat14-strips', 'thoughtful-sat14-strips',
'tidybot-sat11-strips', 'tpp', 'transport-sat08-strips',
'transport-sat11-strips', 'transport-sat14-strips', 'trucks',
'trucks-strips', 'visitall-sat11-strips', 'visitall-sat14-strips',
'woodworking-sat08-strips', 'woodworking-sat11-strips',
'zenotravel']
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return (
"cluster" in node or
node.startswith("gkigrid") or
node in ["habakuk", "turtur"])
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, outfile=outfile)
self.add_step(
'publish-absolute-report', subprocess.call, ['publish', outfile])
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = ComparativeReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.%s" % (
self.name, rev1, rev2, report.output_format))
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
subprocess.call(["publish", outfile])
self.add_step("make-comparison-tables", make_comparison_tables)
self.add_step(
"publish-comparison-tables", publish_comparison_tables)
def add_scatter_plot_step(self, relative=False, attributes=None):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if relative:
report_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
report_class = ScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "{}-{}".format(rev1, config_nick)
algo2 = "{}-{}".format(rev2, config_nick)
report = report_class(
filter_algorithm=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"])
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(step_name, make_scatter_plots)
| 14,157 | 35.678756 | 79 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue694/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(
axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows a relative comparison of two
algorithms with regard to the given attribute. The attribute value
of algorithm 1 is shown on the x-axis and the relation to the value
of algorithm 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['algorithm'] == self.algorithms[0] and
run2['algorithm'] == self.algorithms[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.algorithms[0], val1)
assert val2 > 0, (domain, problem, self.algorithms[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlot uses log-scaling on the x-axis by default.
PlotReport._set_scales(
self, xscale or self.attribute.scale or 'log', 'log')
| 3,875 | 35.566038 | 78 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue694/v3-opt.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from downward.reports.compare import ComparativeReport
import common_setup
from common_setup import IssueConfig, IssueExperiment, RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue694-v2", "issue694-v3"]
BUILDS = ["release32", "release64"]
SEARCHES = [
("blind", "astar(blind())"),
]
CONFIGS = [
IssueConfig(
"{nick}-{build}".format(**locals()),
["--search", search],
build_options=[build],
driver_options=["--build", build])
for nick, search in SEARCHES
for build in BUILDS
]
ATTRIBUTES = [
"coverage", "error", "expansions_until_last_jump", "memory",
"score_memory", "total_time", "score_total_time",
"int_hash_set_load_factor", "int_hash_set_resizes"]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(email="[email protected]")
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_command('run-custom-parser', [os.path.join(DIR, 'custom-parser.py')])
exp.add_comparison_table_step(attributes=ATTRIBUTES)
for relative in [False, True]:
exp.add_scatter_plot_step(relative=relative, attributes=["memory", "total_time"])
exp.run_steps()
| 1,584 | 28.90566 | 85 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue694/custom-parser.py
|
#! /usr/bin/env python
from lab.parser import Parser
def main():
parser = Parser()
parser.add_pattern(
"int_hash_set_load_factor",
"Int hash set load factor: \d+/\d+ = (.+)",
required=False,
type=float)
parser.add_pattern(
"int_hash_set_resizes",
"Int hash set resizes: (\d+)",
required=False,
type=int)
print "Running custom parser"
parser.parse()
main()
| 444 | 19.227273 | 51 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue883/parser.py
|
#! /usr/bin/env python
import logging
import re
from lab.parser import Parser
class CommonParser(Parser):
def add_difference(self, diff, val1, val2):
def diff_func(content, props):
if props.get(val1) is None or props.get(val2) is None:
diff_val = None
else:
diff_val = props.get(val1) - props.get(val2)
props[diff] = diff_val
self.add_function(diff_func)
def _get_flags(self, flags_string):
flags = 0
for char in flags_string:
flags |= getattr(re, char)
return flags
def add_repeated_pattern(
self, name, regex, file="run.log", required=False, type=int,
flags=""):
def find_all_occurences(content, props):
matches = re.findall(regex, content, flags=self._get_flags(flags))
if required and not matches:
logging.error("Pattern {0} not found in file {1}".format(regex, file))
props[name] = [type(m) for m in matches]
self.add_function(find_all_occurences, file=file)
def add_pattern(self, name, regex, file="run.log", required=False, type=int, flags=""):
Parser.add_pattern(self, name, regex, file=file, required=required, type=type, flags=flags)
def add_bottom_up_pattern(self, name, regex, file="run.log", required=True, type=int, flags=""):
def search_from_bottom(content, props):
reversed_content = "\n".join(reversed(content.splitlines()))
match = re.search(regex, reversed_content, flags=self._get_flags(flags))
if required and not match:
logging.error("Pattern {0} not found in file {1}".format(regex, file))
if match:
props[name] = type(match.group(1))
self.add_function(search_from_bottom, file=file)
def no_search(content, props):
if "search_start_time" not in props:
error = props.get("error")
if error is not None and error != "incomplete-search-found-no-plan":
props["error"] = "no-search-due-to-" + error
REFINEMENT_ATTRIBUTES = [
("time_for_finding_traces", r"Time for finding abstract traces: (.+)s"),
("time_for_finding_flaws", r"Time for finding flaws: (.+)s"),
("time_for_splitting_states", r"Time for splitting states: (.+)s"),
]
def compute_total_times(content, props):
for attribute, pattern in REFINEMENT_ATTRIBUTES:
props["total_" + attribute] = sum(props[attribute])
def add_time_analysis(content, props):
init_time = props.get("init_time")
if not init_time:
return
parts = []
parts.append("{init_time:.2f}:".format(**props))
for attribute, pattern in REFINEMENT_ATTRIBUTES:
time = props["total_" + attribute]
relative_time = time / init_time
print time, type(time)
parts.append("{:.2f} ({:.2f})".format(time, relative_time))
props["time_analysis"] = " ".join(parts)
def main():
parser = CommonParser()
parser.add_pattern("search_start_time", r"\[g=0, 1 evaluated, 0 expanded, t=(.+)s, \d+ KB\]", type=float)
parser.add_pattern("search_start_memory", r"\[g=0, 1 evaluated, 0 expanded, t=.+s, (\d+) KB\]", type=int)
parser.add_pattern("init_time", r"Time for initializing additive Cartesian heuristic: (.+)s", type=float)
parser.add_pattern("cartesian_states", r"^Cartesian states: (\d+)\n", type=int)
for attribute, pattern in REFINEMENT_ATTRIBUTES:
parser.add_repeated_pattern(attribute, pattern, type=float, required=False)
parser.add_function(no_search)
parser.add_function(compute_total_times)
parser.add_function(add_time_analysis)
parser.parse()
if __name__ == "__main__":
main()
| 3,743 | 34.657143 | 109 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue883/v1.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
BUILD = "release64"
REVISIONS = ["issue883-base", "issue883-v1"]
DRIVER_OPTIONS = ["--build", BUILD]
CONFIGS = [
IssueConfig(
nick + "-" + max_transitions_nick,
config,
build_options=[BUILD],
driver_options=DRIVER_OPTIONS)
for max_transitions_nick, max_transitions in [("1M", 1000000), ("2M", 2000000)]
for nick, config in [
("cegar-original", ["--search", "astar(cegar(subtasks=[original()], max_transitions={max_transitions}))".format(**locals())]),
("cegar-landmarks-goals", ["--search", "astar(cegar(max_transitions={max_transitions}))".format(**locals())]),
]
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = [
#"depot:p02.pddl",
"gripper:prob01.pddl"]
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
#exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
REFINEMENT_ATTRIBUTES = [
"time_for_finding_traces",
"time_for_finding_flaws",
"time_for_splitting_states",
]
attributes = (
IssueExperiment.DEFAULT_TABLE_ATTRIBUTES +
["search_start_memory", "init_time", "time_analysis"] +
REFINEMENT_ATTRIBUTES +
["total_" + attr for attr in REFINEMENT_ATTRIBUTES])
#exp.add_absolute_report_step(attributes=attributes)
exp.add_comparison_table_step(attributes=attributes)
if len(REVISIONS) == 2:
for attribute in ["init_time", "expansions_until_last_jump", "total_time_for_splitting_states", "total_time_for_finding_traces"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain")),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS))
exp.run_steps()
| 2,794 | 33.085366 | 134 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue883/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import ComparativeReport
from downward.reports.scatter import ScatterPlotReport
from relativescatter import RelativeScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
DEFAULT_OPTIMAL_SUITE = [
'agricola-opt18-strips', 'airport', 'barman-opt11-strips',
'barman-opt14-strips', 'blocks', 'childsnack-opt14-strips',
'data-network-opt18-strips', 'depot', 'driverlog',
'elevators-opt08-strips', 'elevators-opt11-strips',
'floortile-opt11-strips', 'floortile-opt14-strips', 'freecell',
'ged-opt14-strips', 'grid', 'gripper', 'hiking-opt14-strips',
'logistics00', 'logistics98', 'miconic', 'movie', 'mprime',
'mystery', 'nomystery-opt11-strips', 'openstacks-opt08-strips',
'openstacks-opt11-strips', 'openstacks-opt14-strips',
'openstacks-strips', 'organic-synthesis-opt18-strips',
'organic-synthesis-split-opt18-strips', 'parcprinter-08-strips',
'parcprinter-opt11-strips', 'parking-opt11-strips',
'parking-opt14-strips', 'pathways-noneg', 'pegsol-08-strips',
'pegsol-opt11-strips', 'petri-net-alignment-opt18-strips',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-small', 'rovers',
'satellite', 'scanalyzer-08-strips', 'scanalyzer-opt11-strips',
'snake-opt18-strips', 'sokoban-opt08-strips',
'sokoban-opt11-strips', 'spider-opt18-strips', 'storage',
'termes-opt18-strips', 'tetris-opt14-strips',
'tidybot-opt11-strips', 'tidybot-opt14-strips', 'tpp',
'transport-opt08-strips', 'transport-opt11-strips',
'transport-opt14-strips', 'trucks-strips', 'visitall-opt11-strips',
'visitall-opt14-strips', 'woodworking-opt08-strips',
'woodworking-opt11-strips', 'zenotravel']
DEFAULT_SATISFICING_SUITE = [
'agricola-sat18-strips', 'airport', 'assembly',
'barman-sat11-strips', 'barman-sat14-strips', 'blocks',
'caldera-sat18-adl', 'caldera-split-sat18-adl', 'cavediving-14-adl',
'childsnack-sat14-strips', 'citycar-sat14-adl',
'data-network-sat18-strips', 'depot', 'driverlog',
'elevators-sat08-strips', 'elevators-sat11-strips',
'flashfill-sat18-adl', 'floortile-sat11-strips',
'floortile-sat14-strips', 'freecell', 'ged-sat14-strips', 'grid',
'gripper', 'hiking-sat14-strips', 'logistics00', 'logistics98',
'maintenance-sat14-adl', 'miconic', 'miconic-fulladl',
'miconic-simpleadl', 'movie', 'mprime', 'mystery',
'nomystery-sat11-strips', 'nurikabe-sat18-adl', 'openstacks',
'openstacks-sat08-adl', 'openstacks-sat08-strips',
'openstacks-sat11-strips', 'openstacks-sat14-strips',
'openstacks-strips', 'optical-telegraphs',
'organic-synthesis-sat18-strips',
'organic-synthesis-split-sat18-strips', 'parcprinter-08-strips',
'parcprinter-sat11-strips', 'parking-sat11-strips',
'parking-sat14-strips', 'pathways', 'pathways-noneg',
'pegsol-08-strips', 'pegsol-sat11-strips', 'philosophers',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-large',
'psr-middle', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-sat11-strips', 'schedule',
'settlers-sat18-adl', 'snake-sat18-strips', 'sokoban-sat08-strips',
'sokoban-sat11-strips', 'spider-sat18-strips', 'storage',
'termes-sat18-strips', 'tetris-sat14-strips',
'thoughtful-sat14-strips', 'tidybot-sat11-strips', 'tpp',
'transport-sat08-strips', 'transport-sat11-strips',
'transport-sat14-strips', 'trucks', 'trucks-strips',
'visitall-sat11-strips', 'visitall-sat14-strips',
'woodworking-sat08-strips', 'woodworking-sat11-strips',
'zenotravel']
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return node.endswith(".scicore.unibas.ch") or node.endswith(".cluster.bc2.ch")
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["depot:p01.pddl", "gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"planner_memory",
"planner_time",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, outfile=outfile)
self.add_step(
'publish-absolute-report', subprocess.call, ['publish', outfile])
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = ComparativeReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.%s" % (
self.name, rev1, rev2, report.output_format))
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
subprocess.call(["publish", outfile])
self.add_step("make-comparison-tables", make_comparison_tables)
self.add_step(
"publish-comparison-tables", publish_comparison_tables)
def add_scatter_plot_step(self, relative=False, attributes=None):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if relative:
report_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
report_class = ScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "{}-{}".format(rev1, config_nick)
algo2 = "{}-{}".format(rev2, config_nick)
report = report_class(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(step_name, make_scatter_plots)
| 14,786 | 36.435443 | 82 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue883/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(
axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows a relative comparison of two
algorithms with regard to the given attribute. The attribute value
of algorithm 1 is shown on the x-axis and the relation to the value
of algorithm 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['algorithm'] == self.algorithms[0] and
run2['algorithm'] == self.algorithms[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if not val1 or not val2:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.algorithms[0], val1)
assert val2 > 0, (domain, problem, self.algorithms[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlot uses log-scaling on the x-axis by default.
PlotReport._set_scales(
self, xscale or self.attribute.scale or 'log', 'log')
| 3,867 | 35.490566 | 78 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue549/main.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
from lab.reports import Attribute, gm
import common_setup
def main(revisions=None):
SUITE = suites.suite_satisficing_with_ipc11()
CONFIGS = {
'cea': ['--search', 'eager_greedy(cea())'],
'cg': ['--search', 'eager_greedy(cg())'],
'lmcount': ['--search', 'eager_greedy(lmcount(lm_rhw()))'],
}
exp = common_setup.IssueExperiment(
revisions=revisions,
configs=CONFIGS,
suite=SUITE,
test_suite=['depot:pfile1'],
processes=4,
email='[email protected]',
grid_priority=-10,
)
attributes = exp.DEFAULT_TABLE_ATTRIBUTES
attributes.append('landmarks')
attributes.append('landmarks_generation_time')
exp.add_comparison_table_step(attributes=attributes)
exp()
| 853 | 22.081081 | 67 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue549/issue549-v3.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from main import main
main(revisions=["issue549-base", "issue549-v3"])
| 120 | 16.285714 | 48 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue549/issue549-v1.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from main import main
main(revisions=["issue549-base", "issue549-v1"])
| 120 | 16.285714 | 48 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue549/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.environments import LocalEnvironment, MaiaEnvironment
from lab.experiment import ARGPARSER
from lab.steps import Step
from downward.experiments.fast_downward_experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import CompareRevisionsReport
from downward.reports.scatter import ScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
def get_script():
"""Get file name of main script."""
import __main__
return __main__.__file__
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return ("cluster" in node or
node.startswith("gkigrid") or
node in ["habakuk", "turtur"])
def is_test_run():
return ARGS.test_run == "yes" or (ARGS.test_run == "auto" and
not is_running_on_cluster())
class IssueExperiment(FastDownwardExperiment):
"""Wrapper for FastDownwardExperiment with a few convenience features."""
DEFAULT_TEST_SUITE = "gripper:prob01.pddl"
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"plan_length",
]
def __init__(self, configs, revisions, suite, build_options=None,
driver_options=None, grid_priority=None,
test_suite=None, email=None, processes=1, **kwargs):
"""Create an FastDownwardExperiment with some convenience features.
All configs will be run on all revisions. Inherited options
*path*, *environment* and *cache_dir* from FastDownwardExperiment
are not supported and will be automatically set.
*configs* must be a non-empty dict of {nick: cmdline} pairs
that sets the planner configurations to test. nick will
automatically get the revision prepended, e.g.
'issue123-base-<nick>'::
IssueExperiment(configs={
"lmcut": ["--search", "astar(lmcut())"],
"ipdb": ["--search", "astar(ipdb())"]})
*revisions* must be a non-empty list of revisions, which
specify which planner versions to use in the experiment.
The same versions are used for translator, preprocessor
and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"])
*suite* sets the benchmarks for the experiment. It must be a
single string or a list of strings specifying domains or
tasks. The downward.suites module has many predefined
suites. ::
IssueExperiment(suite=["grid", "gripper:prob01.pddl"])
from downward import suites
IssueExperiment(suite=suites.suite_all())
IssueExperiment(suite=suites.suite_satisficing_with_ipc11())
IssueExperiment(suite=suites.suite_optimal())
Use *grid_priority* to set the job priority for cluster
experiments. It must be in the range [-1023, 0] where 0 is the
highest priority. By default the priority is 0. ::
IssueExperiment(grid_priority=-500)
Specify *test_suite* to set the benchmarks for experiment test
runs. By default the first gripper task is used.
IssueExperiment(test_suite=["depot:pfile1", "tpp:p01.pddl"])
"""
if is_test_run():
environment = LocalEnvironment(processes=processes)
suite = test_suite or self.DEFAULT_TEST_SUITE
elif "environment" not in kwargs:
environment = MaiaEnvironment(priority=grid_priority,
email=email)
FastDownwardExperiment.__init__(self, environment=environment,
**kwargs)
# Automatically deduce the downward repository from the file
repo = get_repo_base()
self.algorithm_nicks = []
self.revisions = revisions
for nick, cmdline in configs.items():
for rev in revisions:
algo_nick = '%s-%s' % (rev, nick)
self.add_algorithm(algo_nick, repo, rev, cmdline,
build_options, driver_options)
self.algorithm_nicks.append(algo_nick)
benchmarks_dir = os.path.join(repo, 'benchmarks')
self.add_suite(benchmarks_dir, suite)
self.search_parsers = []
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't
compare revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If
the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
# oufile is of the form <rev1>-<rev2>-...-<revn>.<format>
outfile = ''
for rev in self.revisions:
outfile += rev
outfile += '-'
outfile = outfile[:len(outfile)-1]
outfile += '.'
outfile += report.output_format
outfile = os.path.join(self.eval_dir, outfile)
self.add_report(report, outfile=outfile)
self.add_step(Step('publish-absolute-report', subprocess.call, ['publish', outfile]))
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revision triples. Each report pairs up the runs of the same
config and lists the two absolute attribute values and their
difference for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareRevisionsReport
class. If the keyword argument *attributes* is not
specified, a default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self.revisions, 2):
report = CompareRevisionsReport(rev1, rev2, **kwargs)
outfile = os.path.join(self.eval_dir,
"%s-%s-compare.html" %
(rev1, rev2))
report(self.eval_dir, outfile)
self.add_step(Step("make-comparison-tables", make_comparison_tables))
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self.revisions, 2):
outfile = os.path.join(self.eval_dir,
"%s-%s-compare.html" %
(rev1, rev2))
subprocess.call(['publish', outfile])
self.add_step(Step('publish-comparison-reports', publish_comparison_tables))
# TODO: this is copied from the old common_setup, but not tested
# with the new FastDownwardExperiment class!
def add_scatter_plot_step(self, attributes=None):
print 'This has not been tested with the new FastDownwardExperiment class!'
exit(0)
"""Add a step that creates scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revision pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
scatter_dir = os.path.join(self.eval_dir, "scatter")
def is_portfolio(config_nick):
return "fdss" in config_nick
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "%s-%s" % (rev1, config_nick)
algo2 = "%s-%s" % (rev2, config_nick)
report = ScatterPlotReport(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config_nick in self._config_nicks:
if is_portfolio(config_nick):
valid_attributes = [
attr for attr in attributes
if attr in self.PORTFOLIO_ATTRIBUTES]
else:
valid_attributes = attributes
for rev1, rev2 in itertools.combinations(
self.revision_nicks, 2):
for attribute in valid_attributes:
make_scatter_plot(config_nick, rev1, rev2, attribute)
self.add_step(Step("make-scatter-plots", make_scatter_plots))
| 11,089 | 35.843854 | 93 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue560/issue560.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
from relativescatter import RelativeScatterPlotReport
import common_setup
REVS = ["issue560-base", "issue560-v1"]
SUITE = suites.suite_all()
# We are only interested in the preprocessing here and will only run the first steps of the experiment.
CONFIGS = {
"astar_blind": [
"--search",
"astar(blind())"],
}
exp = common_setup.IssueExperiment(
search_revisions=REVS,
configs=CONFIGS,
suite=SUITE,
)
exp.add_report(
RelativeScatterPlotReport(
attributes=["preprocess_wall_clock_time"],
get_category=lambda run1, run2: run1.get("domain"),
),
outfile='issue560_base_v1_preprocess_wall_clock_time.png'
)
exp.add_absolute_report_step(attributes=["preprocess_wall_clock_time"])
exp()
| 824 | 21.916667 | 103 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue560/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import sys
from lab.environments import LocalEnvironment, MaiaEnvironment
from lab.experiment import ARGPARSER
from lab.steps import Step
from downward.experiments import DownwardExperiment, _get_rev_nick
from downward.checkouts import Translator, Preprocessor, Planner
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import CompareRevisionsReport
from downward.reports.scatter import ScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
def get_script():
"""Get file name of main script."""
import __main__
return __main__.__file__
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return ("cluster" in node or
node.startswith("gkigrid") or
node in ["habakuk", "turtur"])
def is_test_run():
return ARGS.test_run == "yes" or (ARGS.test_run == "auto" and
not is_running_on_cluster())
class IssueExperiment(DownwardExperiment):
"""Wrapper for DownwardExperiment with a few convenience features."""
DEFAULT_TEST_SUITE = "gripper:prob01.pddl"
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, configs, suite, grid_priority=None, path=None,
repo=None, revisions=None, search_revisions=None,
test_suite=None, **kwargs):
"""Create a DownwardExperiment with some convenience features.
*configs* must be a non-empty dict of {nick: cmdline} pairs
that sets the planner configurations to test. ::
IssueExperiment(configs={
"lmcut": ["--search", "astar(lmcut())"],
"ipdb": ["--search", "astar(ipdb())"]})
*suite* sets the benchmarks for the experiment. It must be a
single string or a list of strings specifying domains or
tasks. The downward.suites module has many predefined
suites. ::
IssueExperiment(suite=["grid", "gripper:prob01.pddl"])
from downward import suites
IssueExperiment(suite=suites.suite_all())
IssueExperiment(suite=suites.suite_satisficing_with_ipc11())
IssueExperiment(suite=suites.suite_optimal())
Use *grid_priority* to set the job priority for cluster
experiments. It must be in the range [-1023, 0] where 0 is the
highest priority. By default the priority is 0. ::
IssueExperiment(grid_priority=-500)
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
If *repo* is specified, it must be the path to the root of a
local Fast Downward repository. If omitted, the repository
is derived automatically from the main script's path. Example::
script = /path/to/fd-repo/experiments/issue123/exp01.py -->
repo = /path/to/fd-repo
If *revisions* is specified, it should be a non-empty
list of revisions, which specify which planner versions to use
in the experiment. The same versions are used for translator,
preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"])
If *search_revisions* is specified, it should be a non-empty
list of revisions, which specify which search component
versions to use in the experiment. All runs use the
translator and preprocessor component of the first
revision. ::
IssueExperiment(search_revisions=["default", "issue123"])
If you really need to specify the (translator, preprocessor,
planner) triples manually, use the *combinations* parameter
from the base class (might be deprecated soon). The options
*revisions*, *search_revisions* and *combinations* can be
freely mixed, but at least one of them must be given.
Specify *test_suite* to set the benchmarks for experiment test
runs. By default the first gripper task is used.
IssueExperiment(test_suite=["depot:pfile1", "tpp:p01.pddl"])
"""
if is_test_run():
kwargs["environment"] = LocalEnvironment()
suite = test_suite or self.DEFAULT_TEST_SUITE
elif "environment" not in kwargs:
kwargs["environment"] = MaiaEnvironment(priority=grid_priority)
if path is None:
path = get_data_dir()
if repo is None:
repo = get_repo_base()
kwargs.setdefault("combinations", [])
if not any([revisions, search_revisions, kwargs["combinations"]]):
raise ValueError('At least one of "revisions", "search_revisions" '
'or "combinations" must be given')
if revisions:
kwargs["combinations"].extend([
(Translator(repo, rev),
Preprocessor(repo, rev),
Planner(repo, rev))
for rev in revisions])
if search_revisions:
base_rev = search_revisions[0]
# Use the same nick for all parts to get short revision nick.
kwargs["combinations"].extend([
(Translator(repo, base_rev, nick=rev),
Preprocessor(repo, base_rev, nick=rev),
Planner(repo, rev, nick=rev))
for rev in search_revisions])
DownwardExperiment.__init__(self, path=path, repo=repo, **kwargs)
self._config_nicks = []
for nick, config in configs.items():
self.add_config(nick, config)
self.add_suite(suite)
@property
def revision_nicks(self):
# TODO: Once the add_algorithm() API is available we should get
# rid of the call to _get_rev_nick() and avoid inspecting the
# list of combinations by setting and saving the algorithm nicks.
return [_get_rev_nick(*combo) for combo in self.combinations]
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_config(self, nick, config, timeout=None):
DownwardExperiment.add_config(self, nick, config, timeout=timeout)
self._config_nicks.append(nick)
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't
compare revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If
the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = get_experiment_name() + "." + report.output_format
self.add_report(report, outfile=outfile)
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revision triples. Each report pairs up the runs of the same
config and lists the two absolute attribute values and their
difference for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareRevisionsReport
class. If the keyword argument *attributes* is not
specified, a default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self.revision_nicks, 2):
report = CompareRevisionsReport(rev1, rev2, **kwargs)
outfile = os.path.join(self.eval_dir,
"%s-%s-%s-compare.html" %
(self.name, rev1, rev2))
report(self.eval_dir, outfile)
self.add_step(Step("make-comparison-tables", make_comparison_tables))
def add_scatter_plot_step(self, attributes=None):
"""Add a step that creates scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revision pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
scatter_dir = os.path.join(self.eval_dir, "scatter")
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "%s-%s" % (rev1, config_nick)
algo2 = "%s-%s" % (rev2, config_nick)
report = ScatterPlotReport(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config_nick in self._config_nicks:
for rev1, rev2 in itertools.combinations(
self.revision_nicks, 2):
for attribute in self.get_supported_attributes(
config_nick, attributes):
make_scatter_plot(config_nick, rev1, rev2, attribute)
self.add_step(Step("make-scatter-plots", make_scatter_plots))
| 12,856 | 34.913408 | 79 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue560/relativescatter.py
|
# -*- coding: utf-8 -*-
#
# downward uses the lab package to conduct experiments with the
# Fast Downward planning system.
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
from collections import defaultdict
import os
from lab import tools
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows how a specific attribute in two
configurations. The attribute value in config 1 is shown on the
x-axis and the relation to the value in config 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['config'] == self.configs[0] and
run2['config'] == self.configs[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.configs[0], val1)
assert val2 > 0, (domain, problem, self.configs[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlots use log-scaling on the x-axis by default.
default_xscale = 'log'
if self.attribute and self.attribute in self.LINEAR:
default_xscale = 'linear'
PlotReport._set_scales(self, xscale or default_xscale, 'log')
| 4,690 | 35.937008 | 84 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue925/v1.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
from itertools import combinations
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
# These revisions are all tag experimental branches off the same revision.
# we only need different tags so lab creates separate build directories in the build cache.
# We then manually recompile the code in the build cache with the correct settings.
REVISIONS = ["issue925-cplex12.8-static", "issue925-cplex12.8-dynamic", "issue925-cplex12.9-static", "issue925-cplex12.9-dynamic"]
CONFIGS = [
IssueConfig("opcount-seq-lmcut", ["--search", "astar(operatorcounting([state_equation_constraints(), lmcut_constraints()]))"]),
IssueConfig("diverse-potentials", ["--search", "astar(diverse_potentials())"]),
IssueConfig("optimal-lmcount", ["--search", "astar(lmcount(lm_merged([lm_rhw(),lm_hm(m=1)]), admissible=true, optimal=true))"]),
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(email="[email protected]")
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=4)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
exp.add_comparison_table_step()
for r1, r2 in combinations(REVISIONS, 2):
for nick in ["opcount-seq-lmcut", "diverse-potentials", "optimal-lmcount"]:
exp.add_report(RelativeScatterPlotReport(
attributes=["total_time"],
filter_algorithm=["%s-%s" % (r, nick) for r in [r1, r2]],
get_category=lambda run1, run2: run1["domain"]),
outfile="issue925-v1-total-time-%s-%s-%s.png" % (r1, r2, nick))
exp.run_steps()
| 2,243 | 37.689655 | 132 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue925/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import ComparativeReport
from downward.reports.scatter import ScatterPlotReport
from relativescatter import RelativeScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
DEFAULT_OPTIMAL_SUITE = [
'airport', 'barman-opt11-strips', 'barman-opt14-strips', 'blocks',
'childsnack-opt14-strips', 'depot', 'driverlog',
'elevators-opt08-strips', 'elevators-opt11-strips',
'floortile-opt11-strips', 'floortile-opt14-strips', 'freecell',
'ged-opt14-strips', 'grid', 'gripper', 'hiking-opt14-strips',
'logistics00', 'logistics98', 'miconic', 'movie', 'mprime',
'mystery', 'nomystery-opt11-strips', 'openstacks-opt08-strips',
'openstacks-opt11-strips', 'openstacks-opt14-strips',
'openstacks-strips', 'parcprinter-08-strips',
'parcprinter-opt11-strips', 'parking-opt11-strips',
'parking-opt14-strips', 'pathways-noneg', 'pegsol-08-strips',
'pegsol-opt11-strips', 'pipesworld-notankage',
'pipesworld-tankage', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-opt11-strips',
'sokoban-opt08-strips', 'sokoban-opt11-strips', 'storage',
'tetris-opt14-strips', 'tidybot-opt11-strips',
'tidybot-opt14-strips', 'tpp', 'transport-opt08-strips',
'transport-opt11-strips', 'transport-opt14-strips',
'trucks-strips', 'visitall-opt11-strips', 'visitall-opt14-strips',
'woodworking-opt08-strips', 'woodworking-opt11-strips',
'zenotravel']
DEFAULT_SATISFICING_SUITE = [
'airport', 'assembly', 'barman-sat11-strips',
'barman-sat14-strips', 'blocks', 'cavediving-14-adl',
'childsnack-sat14-strips', 'citycar-sat14-adl', 'depot',
'driverlog', 'elevators-sat08-strips', 'elevators-sat11-strips',
'floortile-sat11-strips', 'floortile-sat14-strips', 'freecell',
'ged-sat14-strips', 'grid', 'gripper', 'hiking-sat14-strips',
'logistics00', 'logistics98', 'maintenance-sat14-adl', 'miconic',
'miconic-fulladl', 'miconic-simpleadl', 'movie', 'mprime',
'mystery', 'nomystery-sat11-strips', 'openstacks',
'openstacks-sat08-adl', 'openstacks-sat08-strips',
'openstacks-sat11-strips', 'openstacks-sat14-strips',
'openstacks-strips', 'optical-telegraphs', 'parcprinter-08-strips',
'parcprinter-sat11-strips', 'parking-sat11-strips',
'parking-sat14-strips', 'pathways', 'pathways-noneg',
'pegsol-08-strips', 'pegsol-sat11-strips', 'philosophers',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-large',
'psr-middle', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-sat11-strips', 'schedule',
'sokoban-sat08-strips', 'sokoban-sat11-strips', 'storage',
'tetris-sat14-strips', 'thoughtful-sat14-strips',
'tidybot-sat11-strips', 'tpp', 'transport-sat08-strips',
'transport-sat11-strips', 'transport-sat14-strips', 'trucks',
'trucks-strips', 'visitall-sat11-strips', 'visitall-sat14-strips',
'woodworking-sat08-strips', 'woodworking-sat11-strips',
'zenotravel']
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return node.endswith(".scicore.unibas.ch") or node.endswith(".cluster.bc2.ch")
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["depot:p01.pddl", "gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, outfile=outfile)
self.add_step(
'publish-absolute-report', subprocess.call, ['publish', outfile])
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = ComparativeReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.%s" % (
self.name, rev1, rev2, report.output_format))
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
subprocess.call(["publish", outfile])
self.add_step("make-comparison-tables", make_comparison_tables)
self.add_step(
"publish-comparison-tables", publish_comparison_tables)
def add_scatter_plot_step(self, relative=False, attributes=None):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if relative:
report_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
report_class = ScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "{}-{}".format(rev1, config_nick)
algo2 = "{}-{}".format(rev2, config_nick)
report = report_class(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(step_name, make_scatter_plots)
| 14,153 | 35.955614 | 82 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue925/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(
axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows a relative comparison of two
algorithms with regard to the given attribute. The attribute value
of algorithm 1 is shown on the x-axis and the relation to the value
of algorithm 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['algorithm'] == self.algorithms[0] and
run2['algorithm'] == self.algorithms[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.algorithms[0], val1)
assert val2 > 0, (domain, problem, self.algorithms[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlot uses log-scaling on the x-axis by default.
PlotReport._set_scales(
self, xscale or self.attribute.scale or 'log', 'log')
| 3,875 | 35.566038 | 78 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue591/v1-opt.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, MaiaEnvironment
from common_setup import IssueConfig, IssueExperiment, is_test_run
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue591-base", "issue591-v1"]
CONFIGS = [
IssueConfig(heuristic, ["--search", "astar({})".format(heuristic)])
for heuristic in [
"blind()", "cegar(max_states=10000)", "hm()", "lmcut()", "hmax()"]
]
SUITE = [
'barman-opt14-strips', 'cavediving-14-adl', 'childsnack-opt14-strips',
'citycar-opt14-adl', 'floortile-opt14-strips', 'ged-opt14-strips',
'hiking-opt14-strips', 'maintenance-opt14-adl',
'openstacks-opt14-strips', 'parking-opt14-strips',
'tetris-opt14-strips', 'tidybot-opt14-strips', 'transport-opt14-strips',
'visitall-opt14-strips']
ENVIRONMENT = MaiaEnvironment(
priority=0, email="[email protected]")
if is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_absolute_report_step()
exp.add_comparison_table_step()
exp.add_scatter_plot_step(attributes=["total_time"])
exp()
| 1,297 | 28.5 | 76 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue591/v1-sat.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, MaiaEnvironment
from common_setup import IssueConfig, IssueExperiment, is_test_run
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue591-base", "issue591-v1"]
CONFIGS = [
IssueConfig(
"lazy_greedy_{}".format(heuristic),
["--heuristic", "h={}()".format(heuristic),
"--search", "lazy_greedy(h, preferred=h)"])
for heuristic in ["add", "cea", "cg", "ff"]
]
SUITE = [
'barman-sat14-strips', 'cavediving-14-adl', 'childsnack-sat14-strips',
'citycar-sat14-adl', 'floortile-sat14-strips', 'ged-sat14-strips',
'hiking-sat14-strips', 'maintenance-sat14-adl',
'openstacks-sat14-strips', 'parking-sat14-strips',
'tetris-sat14-strips', 'thoughtful-sat14-strips',
'transport-sat14-strips', 'visitall-sat14-strips']
ENVIRONMENT = MaiaEnvironment(
priority=0, email="[email protected]")
if is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_absolute_report_step()
exp.add_comparison_table_step()
exp.add_scatter_plot_step(attributes=["total_time"])
exp()
| 1,344 | 28.23913 | 74 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue591/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab.steps import Step
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import CompareConfigsReport
from downward.reports.scatter import ScatterPlotReport
from relativescatter import RelativeScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return (
"cluster" in node or
node.startswith("gkigrid") or
node in ["habakuk", "turtur"])
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, outfile=outfile)
self.add_step(Step(
'publish-absolute-report', subprocess.call, ['publish', outfile]))
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = CompareConfigsReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.%s" % (
self.name, rev1, rev2, report.output_format))
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
subprocess.call(["publish", outfile])
self.add_step(Step("make-comparison-tables", make_comparison_tables))
self.add_step(Step(
"publish-comparison-tables", publish_comparison_tables))
def add_scatter_plot_step(self, relative=False, attributes=None):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if relative:
report_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
report_class = ScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "{}-{}".format(rev1, config_nick)
algo2 = "{}-{}".format(rev2, config_nick)
report = report_class(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(Step(step_name, make_scatter_plots))
| 11,446 | 33.068452 | 79 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue591/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(
axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows how a specific attribute in two
configurations. The attribute value in config 1 is shown on the
x-axis and the relation to the value in config 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['config'] == self.configs[0] and
run2['config'] == self.configs[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.configs[0], val1)
assert val2 > 0, (domain, problem, self.configs[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlots use log-scaling on the x-axis by default.
default_xscale = 'log'
if self.attribute and self.attribute in self.LINEAR:
default_xscale = 'linear'
PlotReport._set_scales(self, xscale or default_xscale, 'log')
| 3,921 | 35.654206 | 78 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue919/translator_additional_parser.py
|
#!/usr/bin/env python
import hashlib
from lab.parser import Parser
def add_hash_value(content, props):
props['translator_output_sas_hash'] = hashlib.sha512(content).hexdigest()
parser = Parser()
parser.add_function(add_hash_value, file="output.sas")
parser.parse()
| 273 | 20.076923 | 77 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue919/v1.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from collections import defaultdict
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from lab import tools
from downward.reports.compare import ComparativeReport
from downward.reports import PlanningReport
import common_setup
from common_setup import IssueConfig, IssueExperiment
EXPNAME = common_setup.get_experiment_name()
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue919-base", "issue919-v1"]
CONFIGS = [
IssueConfig(
"translate-only",
[],
driver_options=["--translate"])
]
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
# This was generated by running "./suites.py all" in the benchmarks
# repository.
SUITE = [
'agricola-opt18-strips',
'agricola-sat18-strips',
'airport',
'airport-adl',
'assembly',
'barman-mco14-strips',
'barman-opt11-strips',
'barman-opt14-strips',
'barman-sat11-strips',
'barman-sat14-strips',
'blocks',
'caldera-opt18-adl',
'caldera-sat18-adl',
'caldera-split-opt18-adl',
'caldera-split-sat18-adl',
'cavediving-14-adl',
'childsnack-opt14-strips',
'childsnack-sat14-strips',
'citycar-opt14-adl',
'citycar-sat14-adl',
'data-network-opt18-strips',
'data-network-sat18-strips',
'depot',
'driverlog',
'elevators-opt08-strips',
'elevators-opt11-strips',
'elevators-sat08-strips',
'elevators-sat11-strips',
'flashfill-sat18-adl',
'floortile-opt11-strips',
'floortile-opt14-strips',
'floortile-sat11-strips',
'floortile-sat14-strips',
'freecell',
'ged-opt14-strips',
'ged-sat14-strips',
'grid',
'gripper',
'hiking-agl14-strips',
'hiking-opt14-strips',
'hiking-sat14-strips',
'logistics00',
'logistics98',
'maintenance-opt14-adl',
'maintenance-sat14-adl',
'miconic',
'miconic-fulladl',
'miconic-simpleadl',
'movie',
'mprime',
'mystery',
'no-mprime',
'no-mystery',
'nomystery-opt11-strips',
'nomystery-sat11-strips',
'nurikabe-opt18-adl',
'nurikabe-sat18-adl',
'openstacks',
'openstacks-agl14-strips',
'openstacks-opt08-adl',
'openstacks-opt08-strips',
'openstacks-opt11-strips',
'openstacks-opt14-strips',
'openstacks-sat08-adl',
'openstacks-sat08-strips',
'openstacks-sat11-strips',
'openstacks-sat14-strips',
'openstacks-strips',
'optical-telegraphs',
'organic-synthesis-opt18-strips',
'organic-synthesis-sat18-strips',
'organic-synthesis-split-opt18-strips',
'organic-synthesis-split-sat18-strips',
'parcprinter-08-strips',
'parcprinter-opt11-strips',
'parcprinter-sat11-strips',
'parking-opt11-strips',
'parking-opt14-strips',
'parking-sat11-strips',
'parking-sat14-strips',
'pathways',
'pathways-noneg',
'pegsol-08-strips',
'pegsol-opt11-strips',
'pegsol-sat11-strips',
'petri-net-alignment-opt18-strips',
'philosophers',
'pipesworld-notankage',
'pipesworld-tankage',
'psr-large',
'psr-middle',
'psr-small',
'rovers',
'satellite',
'scanalyzer-08-strips',
'scanalyzer-opt11-strips',
'scanalyzer-sat11-strips',
'schedule',
'settlers-opt18-adl',
'settlers-sat18-adl',
'snake-opt18-strips',
'snake-sat18-strips',
'sokoban-opt08-strips',
'sokoban-opt11-strips',
'sokoban-sat08-strips',
'sokoban-sat11-strips',
'spider-opt18-strips',
'spider-sat18-strips',
'storage',
'termes-opt18-strips',
'termes-sat18-strips',
'tetris-opt14-strips',
'tetris-sat14-strips',
'thoughtful-mco14-strips',
'thoughtful-sat14-strips',
'tidybot-opt11-strips',
'tidybot-opt14-strips',
'tidybot-sat11-strips',
'tpp',
'transport-opt08-strips',
'transport-opt11-strips',
'transport-opt14-strips',
'transport-sat08-strips',
'transport-sat11-strips',
'transport-sat14-strips',
'trucks',
'trucks-strips',
'visitall-opt11-strips',
'visitall-opt14-strips',
'visitall-sat11-strips',
'visitall-sat14-strips',
'woodworking-opt08-strips',
'woodworking-opt11-strips',
'woodworking-sat08-strips',
'woodworking-sat11-strips',
'zenotravel',
]
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser("translator_additional_parser.py")
del exp.commands['remove-output-sas']
class TranslatorDiffReport(PlanningReport):
def get_cell(self, run):
return ";".join(run.get(attr) for attr in self.attributes)
def get_text(self):
lines = []
for runs in self.problem_runs.values():
hashes = set([r.get("translator_output_sas_hash") for r in runs])
if len(hashes) > 1 or None in hashes:
lines.append(";".join([self.get_cell(r) for r in runs]))
return "\n".join(lines)
class SameValueFilters(object):
"""Ignore runs for a task where all algorithms have the same value."""
def __init__(self, attribute):
self._attribute = attribute
self._tasks_to_values = defaultdict(list)
def _get_task(self, run):
return (run['domain'], run['problem'])
def store_values(self, run):
value = run.get(self._attribute)
self._tasks_to_values[self._get_task(run)].append(value)
# Don't filter this run, yet.
return True
def filter_tasks_with_equal_values(self, run):
values = self._tasks_to_values[self._get_task(run)]
return len(set(values)) != 1
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
ATTRIBUTES = ["error", "run_dir", "translator_*", "translator_output_sas_hash"]
# exp.add_absolute_report_step(
# outfile=os.path.join(exp.eval_dir, "{EXPNAME}.html".format(**locals())),
# attributes=ATTRIBUTES)
exp.add_comparison_table_step(
attributes=ATTRIBUTES)
same_value_filters = SameValueFilters("translator_output_sas_hash")
# exp.add_absolute_report_step(
# outfile=os.path.join(exp.eval_dir, "{EXPNAME}-filtered.html".format(**locals())),
# attributes=ATTRIBUTES,
# filter=[same_value_filters.store_values, same_value_filters.filter_tasks_with_equal_values])
exp.add_comparison_table_step(
suffix="filtered",
attributes=ATTRIBUTES,
filter=[same_value_filters.store_values, same_value_filters.filter_tasks_with_equal_values])
exp.add_report(TranslatorDiffReport(
attributes=["domain", "problem", "algorithm", "run_dir"]
), outfile="different_output_sas.csv"
)
exp.run_steps()
| 7,065 | 27.37751 | 97 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue919/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import ComparativeReport
from downward.reports.scatter import ScatterPlotReport
from relativescatter import RelativeScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
DEFAULT_OPTIMAL_SUITE = [
'agricola-opt18-strips', 'airport', 'barman-opt11-strips',
'barman-opt14-strips', 'blocks', 'childsnack-opt14-strips',
'data-network-opt18-strips', 'depot', 'driverlog',
'elevators-opt08-strips', 'elevators-opt11-strips',
'floortile-opt11-strips', 'floortile-opt14-strips', 'freecell',
'ged-opt14-strips', 'grid', 'gripper', 'hiking-opt14-strips',
'logistics00', 'logistics98', 'miconic', 'movie', 'mprime',
'mystery', 'nomystery-opt11-strips', 'openstacks-opt08-strips',
'openstacks-opt11-strips', 'openstacks-opt14-strips',
'openstacks-strips', 'organic-synthesis-opt18-strips',
'organic-synthesis-split-opt18-strips', 'parcprinter-08-strips',
'parcprinter-opt11-strips', 'parking-opt11-strips',
'parking-opt14-strips', 'pathways-noneg', 'pegsol-08-strips',
'pegsol-opt11-strips', 'petri-net-alignment-opt18-strips',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-small', 'rovers',
'satellite', 'scanalyzer-08-strips', 'scanalyzer-opt11-strips',
'snake-opt18-strips', 'sokoban-opt08-strips',
'sokoban-opt11-strips', 'spider-opt18-strips', 'storage',
'termes-opt18-strips', 'tetris-opt14-strips',
'tidybot-opt11-strips', 'tidybot-opt14-strips', 'tpp',
'transport-opt08-strips', 'transport-opt11-strips',
'transport-opt14-strips', 'trucks-strips', 'visitall-opt11-strips',
'visitall-opt14-strips', 'woodworking-opt08-strips',
'woodworking-opt11-strips', 'zenotravel']
DEFAULT_SATISFICING_SUITE = [
'agricola-sat18-strips', 'airport', 'assembly',
'barman-sat11-strips', 'barman-sat14-strips', 'blocks',
'caldera-sat18-adl', 'caldera-split-sat18-adl', 'cavediving-14-adl',
'childsnack-sat14-strips', 'citycar-sat14-adl',
'data-network-sat18-strips', 'depot', 'driverlog',
'elevators-sat08-strips', 'elevators-sat11-strips',
'flashfill-sat18-adl', 'floortile-sat11-strips',
'floortile-sat14-strips', 'freecell', 'ged-sat14-strips', 'grid',
'gripper', 'hiking-sat14-strips', 'logistics00', 'logistics98',
'maintenance-sat14-adl', 'miconic', 'miconic-fulladl',
'miconic-simpleadl', 'movie', 'mprime', 'mystery',
'nomystery-sat11-strips', 'nurikabe-sat18-adl', 'openstacks',
'openstacks-sat08-adl', 'openstacks-sat08-strips',
'openstacks-sat11-strips', 'openstacks-sat14-strips',
'openstacks-strips', 'optical-telegraphs',
'organic-synthesis-sat18-strips',
'organic-synthesis-split-sat18-strips', 'parcprinter-08-strips',
'parcprinter-sat11-strips', 'parking-sat11-strips',
'parking-sat14-strips', 'pathways', 'pathways-noneg',
'pegsol-08-strips', 'pegsol-sat11-strips', 'philosophers',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-large',
'psr-middle', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-sat11-strips', 'schedule',
'settlers-sat18-adl', 'snake-sat18-strips', 'sokoban-sat08-strips',
'sokoban-sat11-strips', 'spider-sat18-strips', 'storage',
'termes-sat18-strips', 'tetris-sat14-strips',
'thoughtful-sat14-strips', 'tidybot-sat11-strips', 'tpp',
'transport-sat08-strips', 'transport-sat11-strips',
'transport-sat14-strips', 'trucks', 'trucks-strips',
'visitall-sat11-strips', 'visitall-sat14-strips',
'woodworking-sat08-strips', 'woodworking-sat11-strips',
'zenotravel']
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return node.endswith(".scicore.unibas.ch") or node.endswith(".cluster.bc2.ch")
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["depot:p01.pddl", "gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"planner_memory",
"planner_time",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, outfile=None, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = outfile or os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, outfile=outfile)
self.add_step(
'publish-' + os.path.basename(outfile), subprocess.call, ['publish', outfile])
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
Use *suffix* to denote a step name and filename suffix if you
want to add multiple different comparison table steps.
All *kwargs* except *suffix* will be passed to the
CompareConfigsReport class. If the keyword argument
*attributes* is not specified, a default list of attributes is
used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
suffix = kwargs.pop("suffix", "")
if suffix:
suffix = "-" + suffix
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = ComparativeReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare%s.%s" % (
self.name, rev1, rev2, suffix, report.output_format))
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare%s.html" % (self.name, rev1, rev2, suffix))
subprocess.call(["publish", outfile])
self.add_step("make-comparison-tables%s" % suffix, make_comparison_tables)
self.add_step(
"publish-comparison-tables%s" % suffix, publish_comparison_tables)
def add_scatter_plot_step(self, relative=False, attributes=None):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if relative:
report_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
report_class = ScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "{}-{}".format(rev1, config_nick)
algo2 = "{}-{}".format(rev2, config_nick)
report = report_class(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(step_name, make_scatter_plots)
| 15,119 | 36.61194 | 90 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue919/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(
axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows a relative comparison of two
algorithms with regard to the given attribute. The attribute value
of algorithm 1 is shown on the x-axis and the relation to the value
of algorithm 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['algorithm'] == self.algorithms[0] and
run2['algorithm'] == self.algorithms[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.algorithms[0], val1)
assert val2 > 0, (domain, problem, self.algorithms[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlot uses log-scaling on the x-axis by default.
PlotReport._set_scales(
self, xscale or self.attribute.scale or 'log', 'log')
| 3,875 | 35.566038 | 78 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue774/v2-sat.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue774-v2-base", "issue774-v2"]
CONFIGS = [
IssueConfig("blind", ["--search", "astar(blind())"]),
IssueConfig("ehc_ff", ["--heuristic", "h=ff()", "--search", "ehc(h, preferred=[h])"]),
IssueConfig(
"lama-first",
[],
driver_options=["--alias", "lama-first"]),
]
SUITE = common_setup.DEFAULT_SATISFICING_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_absolute_report_step()
exp.add_comparison_table_step()
for attr in ["total_time", "search_time", "memory"]:
for rev1, rev2 in [("v2-base", "v2")]:
for config_nick in ["blind", "ehc_ff", "lama-first"]:
exp.add_report(RelativeScatterPlotReport(
attributes=[attr],
filter_algorithm=["issue774-%s-%s" % (rev1, config_nick),
"issue774-%s-%s" % (rev2, config_nick)],
get_category=lambda r1, r2: r1["domain"],
),
outfile="issue774-%s-%s-%s-%s.png" % (config_nick, attr, rev1, rev2))
exp.run_steps()
| 1,742 | 30.125 | 90 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue774/v1-sat.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue774-base", "issue774-v1"]
CONFIGS = [
IssueConfig("blind", ["--search", "astar(blind())"]),
IssueConfig("ehc_ff", ["--heuristic", "h=ff()", "--search", "ehc(h, preferred=[h])"]),
IssueConfig(
"lama-first",
[],
driver_options=["--alias", "lama-first"]),
]
SUITE = common_setup.DEFAULT_SATISFICING_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_absolute_report_step()
exp.add_comparison_table_step()
for attr in ["total_time", "search_time", "memory"]:
for rev1, rev2 in [("base", "v1")]:
for config_nick in ["blind", "ehc_ff", "lama-first"]:
exp.add_report(RelativeScatterPlotReport(
attributes=[attr],
filter_algorithm=["issue774-%s-%s" % (rev1, config_nick),
"issue774-%s-%s" % (rev2, config_nick)],
get_category=lambda r1, r2: r1["domain"],
),
outfile="issue774-%s-%s-%s-%s.png" % (config_nick, attr, rev1, rev2))
exp.run_steps()
| 1,736 | 30.017857 | 90 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue774/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import ComparativeReport
from downward.reports.scatter import ScatterPlotReport
from relativescatter import RelativeScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
DEFAULT_OPTIMAL_SUITE = [
'airport', 'barman-opt11-strips', 'barman-opt14-strips', 'blocks',
'childsnack-opt14-strips', 'depot', 'driverlog',
'elevators-opt08-strips', 'elevators-opt11-strips',
'floortile-opt11-strips', 'floortile-opt14-strips', 'freecell',
'ged-opt14-strips', 'grid', 'gripper', 'hiking-opt14-strips',
'logistics00', 'logistics98', 'miconic', 'movie', 'mprime',
'mystery', 'nomystery-opt11-strips', 'openstacks-opt08-strips',
'openstacks-opt11-strips', 'openstacks-opt14-strips',
'openstacks-strips', 'parcprinter-08-strips',
'parcprinter-opt11-strips', 'parking-opt11-strips',
'parking-opt14-strips', 'pathways-noneg', 'pegsol-08-strips',
'pegsol-opt11-strips', 'pipesworld-notankage',
'pipesworld-tankage', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-opt11-strips',
'sokoban-opt08-strips', 'sokoban-opt11-strips', 'storage',
'tetris-opt14-strips', 'tidybot-opt11-strips',
'tidybot-opt14-strips', 'tpp', 'transport-opt08-strips',
'transport-opt11-strips', 'transport-opt14-strips',
'trucks-strips', 'visitall-opt11-strips', 'visitall-opt14-strips',
'woodworking-opt08-strips', 'woodworking-opt11-strips',
'zenotravel']
DEFAULT_SATISFICING_SUITE = [
'airport', 'assembly', 'barman-sat11-strips',
'barman-sat14-strips', 'blocks', 'cavediving-14-adl',
'childsnack-sat14-strips', 'citycar-sat14-adl', 'depot',
'driverlog', 'elevators-sat08-strips', 'elevators-sat11-strips',
'floortile-sat11-strips', 'floortile-sat14-strips', 'freecell',
'ged-sat14-strips', 'grid', 'gripper', 'hiking-sat14-strips',
'logistics00', 'logistics98', 'maintenance-sat14-adl', 'miconic',
'miconic-fulladl', 'miconic-simpleadl', 'movie', 'mprime',
'mystery', 'nomystery-sat11-strips', 'openstacks',
'openstacks-sat08-adl', 'openstacks-sat08-strips',
'openstacks-sat11-strips', 'openstacks-sat14-strips',
'openstacks-strips', 'optical-telegraphs', 'parcprinter-08-strips',
'parcprinter-sat11-strips', 'parking-sat11-strips',
'parking-sat14-strips', 'pathways', 'pathways-noneg',
'pegsol-08-strips', 'pegsol-sat11-strips', 'philosophers',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-large',
'psr-middle', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-sat11-strips', 'schedule',
'sokoban-sat08-strips', 'sokoban-sat11-strips', 'storage',
'tetris-sat14-strips', 'thoughtful-sat14-strips',
'tidybot-sat11-strips', 'tpp', 'transport-sat08-strips',
'transport-sat11-strips', 'transport-sat14-strips', 'trucks',
'trucks-strips', 'visitall-sat11-strips', 'visitall-sat14-strips',
'woodworking-sat08-strips', 'woodworking-sat11-strips',
'zenotravel']
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return (
node == "login-infai.scicore.unibas.ch" or
node.endswith(".cluster.bc2.ch") or
"cluster" in node or
node.startswith("gkigrid") or
node in ["habakuk", "turtur"])
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, outfile=outfile)
self.add_step(
'publish-absolute-report', subprocess.call, ['publish', outfile])
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = ComparativeReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.%s" % (
self.name, rev1, rev2, report.output_format))
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
subprocess.call(["publish", outfile])
self.add_step("make-comparison-tables", make_comparison_tables)
self.add_step(
"publish-comparison-tables", publish_comparison_tables)
def add_scatter_plot_step(self, relative=False, attributes=None):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if relative:
report_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
report_class = ScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "{}-{}".format(rev1, config_nick)
algo2 = "{}-{}".format(rev2, config_nick)
report = report_class(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(step_name, make_scatter_plots)
| 14,266 | 35.770619 | 79 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue774/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(
axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows a relative comparison of two
algorithms with regard to the given attribute. The attribute value
of algorithm 1 is shown on the x-axis and the relation to the value
of algorithm 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['algorithm'] == self.algorithms[0] and
run2['algorithm'] == self.algorithms[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.algorithms[0], val1)
assert val2 > 0, (domain, problem, self.algorithms[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlot uses log-scaling on the x-axis by default.
PlotReport._set_scales(
self, xscale or self.attribute.scale or 'log', 'log')
| 3,875 | 35.566038 | 78 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue422/issue422.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
import common_setup
exp = common_setup.IssueExperiment(
search_revisions=["issue422-base", "issue422-v1"],
configs={"lmcut": ["--search", "astar(lmcut())"]},
suite=suites.suite_optimal_with_ipc11(),
)
exp.add_absolute_report_step()
exp.add_comparison_table_step()
exp.add_scatter_plot_step()
exp()
| 394 | 19.789474 | 54 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue422/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import sys
from lab.environments import LocalEnvironment, MaiaEnvironment
from lab.experiment import ARGPARSER
from lab.steps import Step
from downward.experiments import DownwardExperiment, _get_rev_nick
from downward.checkouts import Translator, Preprocessor, Planner
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import CompareRevisionsReport
from downward.reports.scatter import ScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
def get_script():
"""Get file name of main script."""
import __main__
return __main__.__file__
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return (node.endswith("cluster") or
node.startswith("gkigrid") or
node in ["habakuk", "turtur"])
def is_test_run():
return ARGS.test_run == "yes" or (ARGS.test_run == "auto" and
not is_running_on_cluster())
class IssueExperiment(DownwardExperiment):
"""Wrapper for DownwardExperiment with a few convenience features."""
DEFAULT_TEST_SUITE = "gripper:prob01.pddl"
# TODO: Once we have reference results, we should add "quality".
# TODO: Add something about errors/exit codes.
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"plan_length",
]
def __init__(self, configs, suite, grid_priority=None, path=None,
repo=None, revisions=None, search_revisions=None,
test_suite=None, **kwargs):
"""Create a DownwardExperiment with some convenience features.
*configs* must be a non-empty dict of {nick: cmdline} pairs
that sets the planner configurations to test. ::
IssueExperiment(configs={
"lmcut": ["--search", "astar(lmcut())"],
"ipdb": ["--search", "astar(ipdb())"]})
*suite* sets the benchmarks for the experiment. It must be a
single string or a list of strings specifying domains or
tasks. The downward.suites module has many predefined
suites. ::
IssueExperiment(suite=["grid", "gripper:prob01.pddl"])
from downward import suites
IssueExperiment(suite=suites.suite_all())
IssueExperiment(suite=suites.suite_satisficing_with_ipc11())
IssueExperiment(suite=suites.suite_optimal())
Use *grid_priority* to set the job priority for cluster
experiments. It must be in the range [-1023, 0] where 0 is the
highest priority. By default the priority is 0. ::
IssueExperiment(grid_priority=-500)
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
If *repo* is specified, it must be the path to the root of a
local Fast Downward repository. If omitted, the repository
is derived automatically from the main script's path. Example::
script = /path/to/fd-repo/experiments/issue123/exp01.py -->
repo = /path/to/fd-repo
If *revisions* is specified, it should be a non-empty
list of revisions, which specify which planner versions to use
in the experiment. The same versions are used for translator,
preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"])
If *search_revisions* is specified, it should be a non-empty
list of revisions, which specify which search component
versions to use in the experiment. All runs use the
translator and preprocessor component of the first
revision. ::
IssueExperiment(search_revisions=["default", "issue123"])
If you really need to specify the (translator, preprocessor,
planner) triples manually, use the *combinations* parameter
from the base class (might be deprecated soon). The options
*revisions*, *search_revisions* and *combinations* can be
freely mixed, but at least one of them must be given.
Specify *test_suite* to set the benchmarks for experiment test
runs. By default the first gripper task is used.
IssueExperiment(test_suite=["depot:pfile1", "tpp:p01.pddl"])
"""
if is_test_run():
kwargs["environment"] = LocalEnvironment()
suite = test_suite or self.DEFAULT_TEST_SUITE
elif "environment" not in kwargs:
kwargs["environment"] = MaiaEnvironment(priority=grid_priority)
if path is None:
path = get_data_dir()
if repo is None:
repo = get_repo_base()
kwargs.setdefault("combinations", [])
if not any([revisions, search_revisions, kwargs["combinations"]]):
raise ValueError('At least one of "revisions", "search_revisions" '
'or "combinations" must be given')
if revisions:
kwargs["combinations"].extend([
(Translator(repo, rev),
Preprocessor(repo, rev),
Planner(repo, rev))
for rev in revisions])
if search_revisions:
base_rev = search_revisions[0]
# Use the same nick for all parts to get short revision nick.
kwargs["combinations"].extend([
(Translator(repo, base_rev, nick=rev),
Preprocessor(repo, base_rev, nick=rev),
Planner(repo, rev, nick=rev))
for rev in search_revisions])
DownwardExperiment.__init__(self, path=path, repo=repo, **kwargs)
self._config_nicks = []
for nick, config in configs.items():
self.add_config(nick, config)
self.add_suite(suite)
@property
def revision_nicks(self):
# TODO: Once the add_algorithm() API is available we should get
# rid of the call to _get_rev_nick() and avoid inspecting the
# list of combinations by setting and saving the algorithm nicks.
return [_get_rev_nick(*combo) for combo in self.combinations]
def add_config(self, nick, config, timeout=None):
DownwardExperiment.add_config(self, nick, config, timeout=timeout)
self._config_nicks.append(nick)
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't
compare revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If
the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = get_experiment_name() + "." + report.output_format
self.add_report(report, outfile=outfile)
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revision triples. Each report pairs up the runs of the same
config and lists the two absolute attribute values and their
difference for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareRevisionsReport
class. If the keyword argument *attributes* is not
specified, a default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self.revision_nicks, 2):
report = CompareRevisionsReport(rev1, rev2, **kwargs)
outfile = os.path.join(self.eval_dir,
"%s-%s-compare.html" % (rev1, rev2))
report(self.eval_dir, outfile)
self.add_step(Step("make-comparison-tables", make_comparison_tables))
def add_scatter_plot_step(self, attributes=None):
"""Add a step that creates scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revision pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
scatter_dir = os.path.join(self.eval_dir, "scatter")
def is_portfolio(config_nick):
return "fdss" in config_nick
def make_scatter_plots():
for config_nick in self._config_nicks:
for rev1, rev2 in itertools.combinations(
self.revision_nicks, 2):
algo1 = "%s-%s" % (rev1, config_nick)
algo2 = "%s-%s" % (rev2, config_nick)
if is_portfolio(config_nick):
valid_attributes = [
attr for attr in attributes
if attr in self.PORTFOLIO_ATTRIBUTES]
else:
valid_attributes = attributes
for attribute in valid_attributes:
name = "-".join([rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
report = ScatterPlotReport(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(self.eval_dir, os.path.join(scatter_dir, name))
self.add_step(Step("make-scatter-plots", make_scatter_plots))
| 12,734 | 35.594828 | 79 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue731/v4-sat.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue731-base", "issue731-v4"]
BUILDS = ["release32"]
SEARCHES = [
("ff_lazy", ["--heuristic", "h=ff()", "--search", "lazy_greedy([h], preferred=[h])"]),
("cea_lazy", ["--heuristic", "h=cea()", "--search", "lazy_greedy([h], preferred=[h])"]),
("type_based", ["--heuristic", "h=ff()", "--search", "eager(alt([type_based([h, g()])]))"]),
("zhu_givan", [
"--heuristic", "hlm=lmcount(lm_zg())",
"--search", """lazy_greedy([hlm], preferred=[hlm])"""]),
]
CONFIGS = [
IssueConfig(
"{nick}-{build}".format(**locals()),
search,
build_options=[build],
driver_options=["--build", build])
for nick, search in SEARCHES
for build in BUILDS
] + [
IssueConfig(
"lama-first-{build}".format(**locals()),
[],
build_options=[build],
driver_options=["--build", build, "--alias", "lama-first"])
for build in BUILDS
]
SUITE = common_setup.DEFAULT_SATISFICING_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
priority=0, email="[email protected]")
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_comparison_table_step()
exp.run_steps()
| 1,678 | 28.45614 | 96 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue731/v4-opt.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue731-base", "issue731-v4"]
BUILDS = ["release32"]
SEARCHES = [
("blind", "astar(blind())"),
("divpot", "astar(diverse_potentials())"),
("cegar", "astar(cegar())"),
("systematic2", "astar(cpdbs(systematic(2)))"),
("ipdb", "astar(ipdb())"),
]
CONFIGS = [
IssueConfig(
"{nick}-{build}".format(**locals()),
["--search", search],
build_options=[build],
driver_options=["--build", build])
for nick, search in SEARCHES
for build in BUILDS
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
priority=0, email="[email protected]")
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_comparison_table_step()
exp.run_steps()
| 1,264 | 24.816327 | 68 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue731/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import ComparativeReport
from downward.reports.scatter import ScatterPlotReport
from relativescatter import RelativeScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
DEFAULT_OPTIMAL_SUITE = [
'airport', 'barman-opt11-strips', 'barman-opt14-strips', 'blocks',
'childsnack-opt14-strips', 'depot', 'driverlog',
'elevators-opt08-strips', 'elevators-opt11-strips',
'floortile-opt11-strips', 'floortile-opt14-strips', 'freecell',
'ged-opt14-strips', 'grid', 'gripper', 'hiking-opt14-strips',
'logistics00', 'logistics98', 'miconic', 'movie', 'mprime',
'mystery', 'nomystery-opt11-strips', 'openstacks-opt08-strips',
'openstacks-opt11-strips', 'openstacks-opt14-strips',
'openstacks-strips', 'parcprinter-08-strips',
'parcprinter-opt11-strips', 'parking-opt11-strips',
'parking-opt14-strips', 'pathways-noneg', 'pegsol-08-strips',
'pegsol-opt11-strips', 'pipesworld-notankage',
'pipesworld-tankage', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-opt11-strips',
'sokoban-opt08-strips', 'sokoban-opt11-strips', 'storage',
'tetris-opt14-strips', 'tidybot-opt11-strips',
'tidybot-opt14-strips', 'tpp', 'transport-opt08-strips',
'transport-opt11-strips', 'transport-opt14-strips',
'trucks-strips', 'visitall-opt11-strips', 'visitall-opt14-strips',
'woodworking-opt08-strips', 'woodworking-opt11-strips',
'zenotravel']
DEFAULT_SATISFICING_SUITE = [
'airport', 'assembly', 'barman-sat11-strips',
'barman-sat14-strips', 'blocks', 'cavediving-14-adl',
'childsnack-sat14-strips', 'citycar-sat14-adl', 'depot',
'driverlog', 'elevators-sat08-strips', 'elevators-sat11-strips',
'floortile-sat11-strips', 'floortile-sat14-strips', 'freecell',
'ged-sat14-strips', 'grid', 'gripper', 'hiking-sat14-strips',
'logistics00', 'logistics98', 'maintenance-sat14-adl', 'miconic',
'miconic-fulladl', 'miconic-simpleadl', 'movie', 'mprime',
'mystery', 'nomystery-sat11-strips', 'openstacks',
'openstacks-sat08-adl', 'openstacks-sat08-strips',
'openstacks-sat11-strips', 'openstacks-sat14-strips',
'openstacks-strips', 'optical-telegraphs', 'parcprinter-08-strips',
'parcprinter-sat11-strips', 'parking-sat11-strips',
'parking-sat14-strips', 'pathways', 'pathways-noneg',
'pegsol-08-strips', 'pegsol-sat11-strips', 'philosophers',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-large',
'psr-middle', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-sat11-strips', 'schedule',
'sokoban-sat08-strips', 'sokoban-sat11-strips', 'storage',
'tetris-sat14-strips', 'thoughtful-sat14-strips',
'tidybot-sat11-strips', 'tpp', 'transport-sat08-strips',
'transport-sat11-strips', 'transport-sat14-strips', 'trucks',
'trucks-strips', 'visitall-sat11-strips', 'visitall-sat14-strips',
'woodworking-sat08-strips', 'woodworking-sat11-strips',
'zenotravel']
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return (
"cluster" in node or
node.startswith("gkigrid") or
node in ["habakuk", "turtur"])
def is_running_on_cluster_login_node():
return platform.node() == "login20.cluster.bc2.ch"
def can_publish():
return is_running_on_cluster_login_node() or not is_running_on_cluster()
def publish(report_file):
if can_publish():
subprocess.call(["publish", report_file])
else:
print "publishing reports is not supported on this node"
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, name="make-absolute-report", outfile=outfile)
self.add_step("publish-absolute-report", publish, outfile)
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def get_revision_pairs_and_files():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
yield (rev1, rev2, outfile)
def make_comparison_tables():
for rev1, rev2, outfile in get_revision_pairs_and_files():
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = ComparativeReport(compared_configs, **kwargs)
report(self.eval_dir, outfile)
def publish_comparison_tables():
for _, _, outfile in get_revision_pairs_and_files():
publish(outfile)
self.add_step("make-comparison-tables", make_comparison_tables)
self.add_step("publish-comparison-tables", publish_comparison_tables)
def add_scatter_plot_step(self, relative=False, attributes=None):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if relative:
report_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
report_class = ScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "{}-{}".format(rev1, config_nick)
algo2 = "{}-{}".format(rev2, config_nick)
report = report_class(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(step_name, make_scatter_plots)
| 14,462 | 35.24812 | 79 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue731/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(
axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows a relative comparison of two
algorithms with regard to the given attribute. The attribute value
of algorithm 1 is shown on the x-axis and the relation to the value
of algorithm 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['algorithm'] == self.algorithms[0] and
run2['algorithm'] == self.algorithms[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.algorithms[0], val1)
assert val2 > 0, (domain, problem, self.algorithms[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlot uses log-scaling on the x-axis by default.
PlotReport._set_scales(
self, xscale or self.attribute.scale or 'log', 'log')
| 3,875 | 35.566038 | 78 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue731/v5-opt.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import itertools
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from downward.reports.compare import ComparativeReport
import common_setup
from common_setup import IssueConfig, IssueExperiment
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue731-v5-base", "issue731-v5"]
BUILDS = ["release32", "release64"]
SEARCHES = [
("blind", "astar(blind())"),
("systematic2", "astar(cpdbs(systematic(2)))"),
("ipdb", "astar(ipdb())"),
]
CONFIGS = [
IssueConfig(
"{nick}-{build}".format(**locals()),
["--search", search],
build_options=[build],
driver_options=["--build", build])
for nick, search in SEARCHES
for build in BUILDS
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
email="[email protected]")
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_comparison_table_step()
# Compare builds.
for build1, build2 in itertools.combinations(BUILDS, 2):
for rev in REVISIONS:
algorithm_pairs = [
("{rev}-{config_nick}-{build1}".format(**locals()),
"{rev}-{config_nick}-{build2}".format(**locals()),
"Diff ({config_nick}-{rev})".format(**locals()))
for config_nick, search in SEARCHES]
exp.add_report(
ComparativeReport(
algorithm_pairs,
attributes=IssueExperiment.DEFAULT_TABLE_ATTRIBUTES),
name="issue731-{build1}-vs-{build2}-{rev}".format(**locals()))
exp.run_steps()
| 1,863 | 28.125 | 74 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue740/out_sas.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import common
# We want to test both NOT specifying the -sas-file option AND specifying the default "output.sas" value.
# The result should be the same in both cases
common.generate_experiments(common.generate_configs((None, "output.sas")))
| 289 | 35.25 | 105 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue740/foobar_sas.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import common
common.generate_experiments(common.generate_configs(["foobar.sas"]))
| 132 | 18 | 68 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue740/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import ComparativeReport
from downward.reports.scatter import ScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
DEFAULT_OPTIMAL_SUITE = [
'airport', 'barman-opt11-strips', 'barman-opt14-strips', 'blocks',
'childsnack-opt14-strips', 'depot', 'driverlog',
'elevators-opt08-strips', 'elevators-opt11-strips',
'floortile-opt11-strips', 'floortile-opt14-strips', 'freecell',
'ged-opt14-strips', 'grid', 'gripper', 'hiking-opt14-strips',
'logistics00', 'logistics98', 'miconic', 'movie', 'mprime',
'mystery', 'nomystery-opt11-strips', 'openstacks-opt08-strips',
'openstacks-opt11-strips', 'openstacks-opt14-strips',
'openstacks-strips', 'parcprinter-08-strips',
'parcprinter-opt11-strips', 'parking-opt11-strips',
'parking-opt14-strips', 'pathways-noneg', 'pegsol-08-strips',
'pegsol-opt11-strips', 'pipesworld-notankage',
'pipesworld-tankage', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-opt11-strips',
'sokoban-opt08-strips', 'sokoban-opt11-strips', 'storage',
'tetris-opt14-strips', 'tidybot-opt11-strips',
'tidybot-opt14-strips', 'tpp', 'transport-opt08-strips',
'transport-opt11-strips', 'transport-opt14-strips',
'trucks-strips', 'visitall-opt11-strips', 'visitall-opt14-strips',
'woodworking-opt08-strips', 'woodworking-opt11-strips',
'zenotravel']
DEFAULT_SATISFICING_SUITE = [
'airport', 'assembly', 'barman-sat11-strips',
'barman-sat14-strips', 'blocks', 'cavediving-14-adl',
'childsnack-sat14-strips', 'citycar-sat14-adl', 'depot',
'driverlog', 'elevators-sat08-strips', 'elevators-sat11-strips',
'floortile-sat11-strips', 'floortile-sat14-strips', 'freecell',
'ged-sat14-strips', 'grid', 'gripper', 'hiking-sat14-strips',
'logistics00', 'logistics98', 'maintenance-sat14-adl', 'miconic',
'miconic-fulladl', 'miconic-simpleadl', 'movie', 'mprime',
'mystery', 'nomystery-sat11-strips', 'openstacks',
'openstacks-sat08-adl', 'openstacks-sat08-strips',
'openstacks-sat11-strips', 'openstacks-sat14-strips',
'openstacks-strips', 'optical-telegraphs', 'parcprinter-08-strips',
'parcprinter-sat11-strips', 'parking-sat11-strips',
'parking-sat14-strips', 'pathways', 'pathways-noneg',
'pegsol-08-strips', 'pegsol-sat11-strips', 'philosophers',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-large',
'psr-middle', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-sat11-strips', 'schedule',
'sokoban-sat08-strips', 'sokoban-sat11-strips', 'storage',
'tetris-sat14-strips', 'thoughtful-sat14-strips',
'tidybot-sat11-strips', 'tpp', 'transport-sat08-strips',
'transport-sat11-strips', 'transport-sat14-strips', 'trucks',
'trucks-strips', 'visitall-sat11-strips', 'visitall-sat14-strips',
'woodworking-sat08-strips', 'woodworking-sat11-strips',
'zenotravel']
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return (
"cluster" in node or
node.startswith("gkigrid") or
node in ["habakuk", "turtur"])
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, outfile=outfile)
self.add_step(
'publish-absolute-report', subprocess.call, ['publish', outfile])
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = ComparativeReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.%s" % (
self.name, rev1, rev2, report.output_format))
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
subprocess.call(["publish", outfile])
self.add_step("make-comparison-tables", make_comparison_tables)
self.add_step(
"publish-comparison-tables", publish_comparison_tables)
def add_scatter_plot_step(self, relative=False, attributes=None):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if relative:
from relativescatter import RelativeScatterPlotReport
report_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
report_class = ScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "{}-{}".format(rev1, config_nick)
algo2 = "{}-{}".format(rev2, config_nick)
report = report_class(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(step_name, make_scatter_plots)
| 14,182 | 35.838961 | 79 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue740/common.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["8e0b8e1f6edc"]
EXPORTS = ["PYTHONPATH", "PATH", "DOWNWARD_BENCHMARKS"]
def generate_configs(sas_filenames):
configs = []
for sas_file in sas_filenames:
common_driver_options = [] if sas_file is None else ["--sas-file", sas_file]
configs += [
IssueConfig('lazy-greedy-blind-{}'.format(sas_file), ['--search', 'lazy_greedy([blind()])'],
driver_options=common_driver_options + []),
IssueConfig('lama-first-{}'.format(sas_file), [],
driver_options=common_driver_options + ["--alias", "lama-first"]),
IssueConfig("seq_sat_fdss_1-{}".format(sas_file), [],
driver_options=common_driver_options + ["--alias", "seq-sat-fdss-1"]),
IssueConfig("seq_sat_fdss_-{}".format(sas_file), [],
driver_options=common_driver_options + ["--portfolio", "driver/portfolios/seq_sat_fdss_2.py",
"--overall-time-limit", "20s"]),
IssueConfig('translate-only-{}'.format(sas_file), [],
driver_options=['--translate'] + common_driver_options),
]
return configs
def generate_experiments(configs):
SUITE = ["gripper:prob01.pddl",
"blocks:probBLOCKS-5-0.pddl",
"visitall-sat11-strips:problem12.pddl",
"airport:p01-airport1-p1.pddl"]
ENVIRONMENT = BaselSlurmEnvironment(email="[email protected]", export=EXPORTS)
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=2)
exp = IssueExperiment(
revisions=REVISIONS,
configs=configs,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_absolute_report_step()
exp.run_steps()
| 2,196 | 33.328125 | 117 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue773/v1-opt.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue773-base", "issue773-v1"]
CONFIGS = [
IssueConfig('lmcut-sss-min-pruning-ratio', ['--search', 'astar(lmcut(), pruning=stubborn_sets_simple(min_pruning_ratio=0.2))']),
IssueConfig('lmcut-sss', ['--search', 'astar(lmcut(), pruning=stubborn_sets_simple())']),
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_1",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
#exp.add_absolute_report_step()
exp.add_comparison_table_step()
for attribute in ["total_time"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain"),
),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS)
)
exp.run_steps()
| 1,617 | 31.36 | 132 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue773/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import ComparativeReport
from downward.reports.scatter import ScatterPlotReport
from relativescatter import RelativeScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
DEFAULT_OPTIMAL_SUITE = [
'airport', 'barman-opt11-strips', 'barman-opt14-strips', 'blocks',
'childsnack-opt14-strips', 'depot', 'driverlog',
'elevators-opt08-strips', 'elevators-opt11-strips',
'floortile-opt11-strips', 'floortile-opt14-strips', 'freecell',
'ged-opt14-strips', 'grid', 'gripper', 'hiking-opt14-strips',
'logistics00', 'logistics98', 'miconic', 'movie', 'mprime',
'mystery', 'nomystery-opt11-strips', 'openstacks-opt08-strips',
'openstacks-opt11-strips', 'openstacks-opt14-strips',
'openstacks-strips', 'parcprinter-08-strips',
'parcprinter-opt11-strips', 'parking-opt11-strips',
'parking-opt14-strips', 'pathways-noneg', 'pegsol-08-strips',
'pegsol-opt11-strips', 'pipesworld-notankage',
'pipesworld-tankage', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-opt11-strips',
'sokoban-opt08-strips', 'sokoban-opt11-strips', 'storage',
'tetris-opt14-strips', 'tidybot-opt11-strips',
'tidybot-opt14-strips', 'tpp', 'transport-opt08-strips',
'transport-opt11-strips', 'transport-opt14-strips',
'trucks-strips', 'visitall-opt11-strips', 'visitall-opt14-strips',
'woodworking-opt08-strips', 'woodworking-opt11-strips',
'zenotravel']
DEFAULT_SATISFICING_SUITE = [
'airport', 'assembly', 'barman-sat11-strips',
'barman-sat14-strips', 'blocks', 'cavediving-14-adl',
'childsnack-sat14-strips', 'citycar-sat14-adl', 'depot',
'driverlog', 'elevators-sat08-strips', 'elevators-sat11-strips',
'floortile-sat11-strips', 'floortile-sat14-strips', 'freecell',
'ged-sat14-strips', 'grid', 'gripper', 'hiking-sat14-strips',
'logistics00', 'logistics98', 'maintenance-sat14-adl', 'miconic',
'miconic-fulladl', 'miconic-simpleadl', 'movie', 'mprime',
'mystery', 'nomystery-sat11-strips', 'openstacks',
'openstacks-sat08-adl', 'openstacks-sat08-strips',
'openstacks-sat11-strips', 'openstacks-sat14-strips',
'openstacks-strips', 'optical-telegraphs', 'parcprinter-08-strips',
'parcprinter-sat11-strips', 'parking-sat11-strips',
'parking-sat14-strips', 'pathways', 'pathways-noneg',
'pegsol-08-strips', 'pegsol-sat11-strips', 'philosophers',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-large',
'psr-middle', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-sat11-strips', 'schedule',
'sokoban-sat08-strips', 'sokoban-sat11-strips', 'storage',
'tetris-sat14-strips', 'thoughtful-sat14-strips',
'tidybot-sat11-strips', 'tpp', 'transport-sat08-strips',
'transport-sat11-strips', 'transport-sat14-strips', 'trucks',
'trucks-strips', 'visitall-sat11-strips', 'visitall-sat14-strips',
'woodworking-sat08-strips', 'woodworking-sat11-strips',
'zenotravel']
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return node.endswith(".scicore.unibas.ch") or node.endswith(".cluster.bc2.ch")
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["depot:p01.pddl", "gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, outfile=outfile)
self.add_step(
'publish-absolute-report', subprocess.call, ['publish', outfile])
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = ComparativeReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.%s" % (
self.name, rev1, rev2, report.output_format))
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
subprocess.call(["publish", outfile])
self.add_step("make-comparison-tables", make_comparison_tables)
self.add_step(
"publish-comparison-tables", publish_comparison_tables)
def add_scatter_plot_step(self, relative=False, attributes=None):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if relative:
report_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
report_class = ScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "{}-{}".format(rev1, config_nick)
algo2 = "{}-{}".format(rev2, config_nick)
report = report_class(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(step_name, make_scatter_plots)
| 14,153 | 35.955614 | 82 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue773/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(
axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows a relative comparison of two
algorithms with regard to the given attribute. The attribute value
of algorithm 1 is shown on the x-axis and the relation to the value
of algorithm 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['algorithm'] == self.algorithms[0] and
run2['algorithm'] == self.algorithms[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.algorithms[0], val1)
assert val2 > 0, (domain, problem, self.algorithms[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlot uses log-scaling on the x-axis by default.
PlotReport._set_scales(
self, xscale or self.attribute.scale or 'log', 'log')
| 3,875 | 35.566038 | 78 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue714/v1-portfolios.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, MaiaEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue714-base", "issue714-v1"]
CONFIGS = [
IssueConfig(alias, [], driver_options=["--alias", alias])
for alias in [
"seq-sat-fdss-1", "seq-sat-fdss-2", "seq-sat-fdss-2014",
"seq-sat-fd-autotune-1", "seq-sat-fd-autotune-2"]
]
SUITE = common_setup.DEFAULT_SATISFICING_SUITE
ENVIRONMENT = MaiaEnvironment(
priority=0, email="[email protected]")
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_absolute_report_step(attributes=IssueExperiment.PORTFOLIO_ATTRIBUTES)
exp.add_comparison_table_step(attributes=IssueExperiment.PORTFOLIO_ATTRIBUTES)
exp.run_steps()
| 1,128 | 27.948718 | 78 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue714/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import ComparativeReport
from downward.reports.scatter import ScatterPlotReport
from relativescatter import RelativeScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
DEFAULT_OPTIMAL_SUITE = [
'airport', 'barman-opt11-strips', 'barman-opt14-strips', 'blocks',
'childsnack-opt14-strips', 'depot', 'driverlog',
'elevators-opt08-strips', 'elevators-opt11-strips',
'floortile-opt11-strips', 'floortile-opt14-strips', 'freecell',
'ged-opt14-strips', 'grid', 'gripper', 'hiking-opt14-strips',
'logistics00', 'logistics98', 'miconic', 'movie', 'mprime',
'mystery', 'nomystery-opt11-strips', 'openstacks-opt08-strips',
'openstacks-opt11-strips', 'openstacks-opt14-strips',
'openstacks-strips', 'parcprinter-08-strips',
'parcprinter-opt11-strips', 'parking-opt11-strips',
'parking-opt14-strips', 'pathways-noneg', 'pegsol-08-strips',
'pegsol-opt11-strips', 'pipesworld-notankage',
'pipesworld-tankage', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-opt11-strips',
'sokoban-opt08-strips', 'sokoban-opt11-strips', 'storage',
'tetris-opt14-strips', 'tidybot-opt11-strips',
'tidybot-opt14-strips', 'tpp', 'transport-opt08-strips',
'transport-opt11-strips', 'transport-opt14-strips',
'trucks-strips', 'visitall-opt11-strips', 'visitall-opt14-strips',
'woodworking-opt08-strips', 'woodworking-opt11-strips',
'zenotravel']
DEFAULT_SATISFICING_SUITE = [
'airport', 'assembly', 'barman-sat11-strips',
'barman-sat14-strips', 'blocks', 'cavediving-14-adl',
'childsnack-sat14-strips', 'citycar-sat14-adl', 'depot',
'driverlog', 'elevators-sat08-strips', 'elevators-sat11-strips',
'floortile-sat11-strips', 'floortile-sat14-strips', 'freecell',
'ged-sat14-strips', 'grid', 'gripper', 'hiking-sat14-strips',
'logistics00', 'logistics98', 'maintenance-sat14-adl', 'miconic',
'miconic-fulladl', 'miconic-simpleadl', 'movie', 'mprime',
'mystery', 'nomystery-sat11-strips', 'openstacks',
'openstacks-sat08-adl', 'openstacks-sat08-strips',
'openstacks-sat11-strips', 'openstacks-sat14-strips',
'openstacks-strips', 'optical-telegraphs', 'parcprinter-08-strips',
'parcprinter-sat11-strips', 'parking-sat11-strips',
'parking-sat14-strips', 'pathways', 'pathways-noneg',
'pegsol-08-strips', 'pegsol-sat11-strips', 'philosophers',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-large',
'psr-middle', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-sat11-strips', 'schedule',
'sokoban-sat08-strips', 'sokoban-sat11-strips', 'storage',
'tetris-sat14-strips', 'thoughtful-sat14-strips',
'tidybot-sat11-strips', 'tpp', 'transport-sat08-strips',
'transport-sat11-strips', 'transport-sat14-strips', 'trucks',
'trucks-strips', 'visitall-sat11-strips', 'visitall-sat14-strips',
'woodworking-sat08-strips', 'woodworking-sat11-strips',
'zenotravel']
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return (
"cluster" in node or
node.startswith("gkigrid") or
node in ["habakuk", "turtur"])
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, outfile=outfile)
self.add_step(
'publish-absolute-report', subprocess.call, ['publish', outfile])
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = ComparativeReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.%s" % (
self.name, rev1, rev2, report.output_format))
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
subprocess.call(["publish", outfile])
self.add_step("make-comparison-tables", make_comparison_tables)
self.add_step(
"publish-comparison-tables", publish_comparison_tables)
def add_scatter_plot_step(self, relative=False, attributes=None):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if relative:
report_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
report_class = ScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "{}-{}".format(rev1, config_nick)
algo2 = "{}-{}".format(rev2, config_nick)
report = report_class(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(step_name, make_scatter_plots)
| 14,171 | 35.715026 | 79 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue714/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(
axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows a relative comparison of two
algorithms with regard to the given attribute. The attribute value
of algorithm 1 is shown on the x-axis and the relation to the value
of algorithm 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['algorithm'] == self.algorithms[0] and
run2['algorithm'] == self.algorithms[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.algorithms[0], val1)
assert val2 > 0, (domain, problem, self.algorithms[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlot uses log-scaling on the x-axis by default.
PlotReport._set_scales(
self, xscale or self.attribute.scale or 'log', 'log')
| 3,875 | 35.566038 | 78 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue714/v1-configs.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import itertools
import os
from lab.environments import LocalEnvironment, MaiaEnvironment
from downward.reports import compare
import common_setup
from common_setup import IssueConfig, IssueExperiment
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
SUITE = common_setup.DEFAULT_SATISFICING_SUITE
ENVIRONMENT = MaiaEnvironment(
priority=0, email="[email protected]")
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=[],
configs=[],
environment=ENVIRONMENT,
)
compared_algorithms = []
for search in ["eager_greedy", "lazy_greedy"]:
for h1, h2 in itertools.permutations(["cea", "cg", "ff"], 2):
rev = "issue714-base"
config_nick = "-".join([search, h1, h2])
algo1 = common_setup.get_algo_nick(rev, config_nick)
exp.add_algorithm(
algo1,
common_setup.get_repo_base(),
rev,
[
"--heuristic", "h{h1}={h1}".format(**locals()),
"--heuristic", "h{h2}={h2}".format(**locals()),
"--search", "{search}(h{h1}, h{h2}, preferred=[h{h1},h{h2}])".format(**locals())],
driver_options=["--search-time-limit", "1m"])
rev = "issue714-v1"
config_nick = "-".join([search, h1, h2])
algo2 = common_setup.get_algo_nick(rev, config_nick)
exp.add_algorithm(
algo2,
common_setup.get_repo_base(),
rev,
[
"--heuristic", "h{h1}={h1}".format(**locals()),
"--heuristic", "h{h2}={h2}".format(**locals()),
"--search", "{search}([h{h1},h{h2}], preferred=[h{h1},h{h2}])".format(**locals())],
driver_options=["--search-time-limit", "1m"])
compared_algorithms.append([algo1, algo2, "Diff ({config_nick})".format(**locals())])
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_absolute_report_step()
exp.add_report(compare.ComparativeReport(
compared_algorithms,
attributes=IssueExperiment.DEFAULT_TABLE_ATTRIBUTES),
name=common_setup.get_experiment_name() + "-comparison")
exp.run_steps()
| 2,299 | 31.857143 | 99 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue578/v1.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from downward.reports.compare import ComparativeReport
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue578-v1"]
CONFIGS = [
IssueConfig('cpdbs-hc900', ['--search', 'astar(cpdbs(patterns=hillclimbing(max_time=900)))']),
IssueConfig('cpdbs-hc900-dp30', ['--search', 'astar(cpdbs(patterns=hillclimbing(max_time=900),dominance_pruning_max_time=30))']),
IssueConfig('cpdbs-hc900-dp60', ['--search', 'astar(cpdbs(patterns=hillclimbing(max_time=900),dominance_pruning_max_time=60))']),
IssueConfig('cpdbs-hc900-dp300', ['--search', 'astar(cpdbs(patterns=hillclimbing(max_time=900),dominance_pruning_max_time=300))']),
IssueConfig('cpdbs-sys2', ['--search', 'astar(cpdbs(patterns=systematic(2)))']),
IssueConfig('cpdbs-sys2-dp30', ['--search', 'astar(cpdbs(patterns=systematic(2),dominance_pruning_max_time=30))']),
IssueConfig('cpdbs-sys2-dp60', ['--search', 'astar(cpdbs(patterns=systematic(2),dominance_pruning_max_time=60))']),
IssueConfig('cpdbs-sys2-dp300', ['--search', 'astar(cpdbs(patterns=systematic(2),dominance_pruning_max_time=300))']),
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(email="[email protected]")
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_resource("custom_parser", "custom-parser.py")
exp.add_command("run-custom-parser", ["{custom_parser}"])
exp.add_suite(BENCHMARKS_DIR, SUITE)
attributes = exp.DEFAULT_TABLE_ATTRIBUTES
attributes.extend([
"dominance_pruning_failed",
"dominance_pruning_time",
"dominance_pruning_pruned_subsets",
"dominance_pruning_pruned_pdbs",
"pdb_collection_construction_time",
])
exp.add_fetcher('data/issue578-v1-more-configs-eval')
exp.add_absolute_report_step(attributes=attributes)
#exp.add_comparison_table_step()
exp.run_steps()
| 2,298 | 39.333333 | 135 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue578/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import ComparativeReport
from downward.reports.scatter import ScatterPlotReport
from relativescatter import RelativeScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
DEFAULT_OPTIMAL_SUITE = [
'airport', 'barman-opt11-strips', 'barman-opt14-strips', 'blocks',
'childsnack-opt14-strips', 'depot', 'driverlog',
'elevators-opt08-strips', 'elevators-opt11-strips',
'floortile-opt11-strips', 'floortile-opt14-strips', 'freecell',
'ged-opt14-strips', 'grid', 'gripper', 'hiking-opt14-strips',
'logistics00', 'logistics98', 'miconic', 'movie', 'mprime',
'mystery', 'nomystery-opt11-strips', 'openstacks-opt08-strips',
'openstacks-opt11-strips', 'openstacks-opt14-strips',
'openstacks-strips', 'parcprinter-08-strips',
'parcprinter-opt11-strips', 'parking-opt11-strips',
'parking-opt14-strips', 'pathways-noneg', 'pegsol-08-strips',
'pegsol-opt11-strips', 'pipesworld-notankage',
'pipesworld-tankage', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-opt11-strips',
'sokoban-opt08-strips', 'sokoban-opt11-strips', 'storage',
'tetris-opt14-strips', 'tidybot-opt11-strips',
'tidybot-opt14-strips', 'tpp', 'transport-opt08-strips',
'transport-opt11-strips', 'transport-opt14-strips',
'trucks-strips', 'visitall-opt11-strips', 'visitall-opt14-strips',
'woodworking-opt08-strips', 'woodworking-opt11-strips',
'zenotravel']
DEFAULT_SATISFICING_SUITE = [
'airport', 'assembly', 'barman-sat11-strips',
'barman-sat14-strips', 'blocks', 'cavediving-14-adl',
'childsnack-sat14-strips', 'citycar-sat14-adl', 'depot',
'driverlog', 'elevators-sat08-strips', 'elevators-sat11-strips',
'floortile-sat11-strips', 'floortile-sat14-strips', 'freecell',
'ged-sat14-strips', 'grid', 'gripper', 'hiking-sat14-strips',
'logistics00', 'logistics98', 'maintenance-sat14-adl', 'miconic',
'miconic-fulladl', 'miconic-simpleadl', 'movie', 'mprime',
'mystery', 'nomystery-sat11-strips', 'openstacks',
'openstacks-sat08-adl', 'openstacks-sat08-strips',
'openstacks-sat11-strips', 'openstacks-sat14-strips',
'openstacks-strips', 'optical-telegraphs', 'parcprinter-08-strips',
'parcprinter-sat11-strips', 'parking-sat11-strips',
'parking-sat14-strips', 'pathways', 'pathways-noneg',
'pegsol-08-strips', 'pegsol-sat11-strips', 'philosophers',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-large',
'psr-middle', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-sat11-strips', 'schedule',
'sokoban-sat08-strips', 'sokoban-sat11-strips', 'storage',
'tetris-sat14-strips', 'thoughtful-sat14-strips',
'tidybot-sat11-strips', 'tpp', 'transport-sat08-strips',
'transport-sat11-strips', 'transport-sat14-strips', 'trucks',
'trucks-strips', 'visitall-sat11-strips', 'visitall-sat14-strips',
'woodworking-sat08-strips', 'woodworking-sat11-strips',
'zenotravel']
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return (
"cluster" in node or
node.startswith("gkigrid") or
node in ["habakuk", "turtur"])
def is_running_on_cluster_login_node():
return platform.node() == "login20.cluster.bc2.ch"
def can_publish():
return is_running_on_cluster_login_node() or not is_running_on_cluster()
def publish(report_file):
if can_publish():
subprocess.call(["publish", report_file])
else:
print "publishing reports is not supported on this node"
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, name="make-absolute-report", outfile=outfile)
self.add_step("publish-absolute-report", publish, outfile)
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def get_revision_pairs_and_files():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
yield (rev1, rev2, outfile)
def make_comparison_tables():
for rev1, rev2, outfile in get_revision_pairs_and_files():
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = ComparativeReport(compared_configs, **kwargs)
report(self.eval_dir, outfile)
def publish_comparison_tables():
for _, _, outfile in get_revision_pairs_and_files():
publish(outfile)
self.add_step("make-comparison-tables", make_comparison_tables)
self.add_step("publish-comparison-tables", publish_comparison_tables)
def add_scatter_plot_step(self, relative=False, attributes=None):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if relative:
report_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
report_class = ScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "{}-{}".format(rev1, config_nick)
algo2 = "{}-{}".format(rev2, config_nick)
report = report_class(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(step_name, make_scatter_plots)
| 14,462 | 35.24812 | 79 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue578/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(
axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows a relative comparison of two
algorithms with regard to the given attribute. The attribute value
of algorithm 1 is shown on the x-axis and the relation to the value
of algorithm 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['algorithm'] == self.algorithms[0] and
run2['algorithm'] == self.algorithms[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.algorithms[0], val1)
assert val2 > 0, (domain, problem, self.algorithms[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlot uses log-scaling on the x-axis by default.
PlotReport._set_scales(
self, xscale or self.attribute.scale or 'log', 'log')
| 3,875 | 35.566038 | 78 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue578/custom-parser.py
|
#! /usr/bin/env python
from lab.parser import Parser
def add_dominance_pruning_failed(content, props):
if "dominance_pruning=False" in content:
failed = False
elif "pdb_collection_construction_time" not in props:
failed = False
else:
failed = "dominance_pruning_time" not in props
props["dominance_pruning_failed"] = int(failed)
def main():
print "Running custom parser"
parser = Parser()
parser.add_pattern(
"pdb_collection_construction_time", "^PDB collection construction time: (.+)s$", type=float, flags="M", required=False)
parser.add_pattern(
"dominance_pruning_time", "^Dominance pruning took (.+)s$", type=float, flags="M", required=False)
parser.add_pattern(
"dominance_pruning_pruned_subsets", "Pruned (\d+) of \d+ maximal additive subsets", type=int, required=False)
parser.add_pattern(
"dominance_pruning_pruned_pdbs", "Pruned (\d+) of \d+ PDBs", type=int, required=False)
parser.add_function(add_dominance_pruning_failed)
parser.parse()
main()
| 1,069 | 31.424242 | 127 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue578/v1-more-configs.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from downward.reports.compare import ComparativeReport
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue578-v1"]
CONFIGS = [
IssueConfig('cpdbs-sys2-dp500', ['--search', 'astar(cpdbs(patterns=systematic(2),dominance_pruning_max_time=500))']),
IssueConfig('cpdbs-sys2-dp700', ['--search', 'astar(cpdbs(patterns=systematic(2),dominance_pruning_max_time=700))']),
IssueConfig('cpdbs-sys2-dp900', ['--search', 'astar(cpdbs(patterns=systematic(2),dominance_pruning_max_time=900))']),
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(email="[email protected]")
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_resource("custom_parser", "custom-parser.py")
exp.add_command("run-custom-parser", ["{custom_parser}"])
exp.add_suite(BENCHMARKS_DIR, SUITE)
attributes = exp.DEFAULT_TABLE_ATTRIBUTES
attributes.extend([
"dominance_pruning_failed",
"dominance_pruning_time",
"dominance_pruning_pruned_subsets",
"dominance_pruning_pruned_pdbs",
"pdb_collection_construction_time",
])
exp.add_absolute_report_step(attributes=attributes)
#exp.add_comparison_table_step()
exp.run_steps()
| 1,659 | 32.2 | 121 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue486/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import sys
from lab.environments import LocalEnvironment, MaiaEnvironment
from lab.experiment import ARGPARSER
from lab.steps import Step
from downward.experiments import DownwardExperiment, _get_rev_nick
from downward.checkouts import Translator, Preprocessor, Planner
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import CompareRevisionsReport
from downward.reports.scatter import ScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
def get_script():
"""Get file name of main script."""
import __main__
return __main__.__file__
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return (node.endswith("cluster.bc2.ch") or
node.startswith("gkigrid") or
node in ["habakuk", "turtur"])
def is_test_run():
return ARGS.test_run == "yes" or (ARGS.test_run == "auto" and
not is_running_on_cluster())
class IssueExperiment(DownwardExperiment):
"""Wrapper for DownwardExperiment with a few convenience features."""
DEFAULT_TEST_SUITE = "gripper:prob01.pddl"
# TODO: Once we have reference results, we should add "quality".
# TODO: Add something about errors/exit codes.
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"plan_length",
]
def __init__(self, configs, suite, grid_priority=None, path=None,
repo=None, revisions=None, search_revisions=None,
test_suite=None, **kwargs):
"""Create a DownwardExperiment with some convenience features.
*configs* must be a non-empty dict of {nick: cmdline} pairs
that sets the planner configurations to test. ::
IssueExperiment(configs={
"lmcut": ["--search", "astar(lmcut())"],
"ipdb": ["--search", "astar(ipdb())"]})
*suite* sets the benchmarks for the experiment. It must be a
single string or a list of strings specifying domains or
tasks. The downward.suites module has many predefined
suites. ::
IssueExperiment(suite=["grid", "gripper:prob01.pddl"])
from downward import suites
IssueExperiment(suite=suites.suite_all())
IssueExperiment(suite=suites.suite_satisficing_with_ipc11())
IssueExperiment(suite=suites.suite_optimal())
Use *grid_priority* to set the job priority for cluster
experiments. It must be in the range [-1023, 0] where 0 is the
highest priority. By default the priority is 0. ::
IssueExperiment(grid_priority=-500)
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
If *repo* is specified, it must be the path to the root of a
local Fast Downward repository. If omitted, the repository
is derived automatically from the main script's path. Example::
script = /path/to/fd-repo/experiments/issue123/exp01.py -->
repo = /path/to/fd-repo
If *revisions* is specified, it should be a non-empty
list of revisions, which specify which planner versions to use
in the experiment. The same versions are used for translator,
preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"])
If *search_revisions* is specified, it should be a non-empty
list of revisions, which specify which search component
versions to use in the experiment. All runs use the
translator and preprocessor component of the first
revision. ::
IssueExperiment(search_revisions=["default", "issue123"])
If you really need to specify the (translator, preprocessor,
planner) triples manually, use the *combinations* parameter
from the base class (might be deprecated soon). The options
*revisions*, *search_revisions* and *combinations* can be
freely mixed, but at least one of them must be given.
Specify *test_suite* to set the benchmarks for experiment test
runs. By default the first gripper task is used.
IssueExperiment(test_suite=["depot:pfile1", "tpp:p01.pddl"])
"""
if is_test_run():
kwargs["environment"] = LocalEnvironment()
suite = test_suite or self.DEFAULT_TEST_SUITE
elif "environment" not in kwargs:
kwargs["environment"] = MaiaEnvironment(priority=grid_priority)
if path is None:
path = get_data_dir()
if repo is None:
repo = get_repo_base()
kwargs.setdefault("combinations", [])
if not any([revisions, search_revisions, kwargs["combinations"]]):
raise ValueError('At least one of "revisions", "search_revisions" '
'or "combinations" must be given')
if revisions:
kwargs["combinations"].extend([
(Translator(repo, rev),
Preprocessor(repo, rev),
Planner(repo, rev))
for rev in revisions])
if search_revisions:
base_rev = search_revisions[0]
# Use the same nick for all parts to get short revision nick.
kwargs["combinations"].extend([
(Translator(repo, base_rev, nick=rev),
Preprocessor(repo, base_rev, nick=rev),
Planner(repo, rev, nick=rev))
for rev in search_revisions])
DownwardExperiment.__init__(self, path=path, repo=repo, **kwargs)
self._config_nicks = []
for nick, config in configs.items():
self.add_config(nick, config)
self.add_suite(suite)
@property
def revision_nicks(self):
# TODO: Once the add_algorithm() API is available we should get
# rid of the call to _get_rev_nick() and avoid inspecting the
# list of combinations by setting and saving the algorithm nicks.
return [_get_rev_nick(*combo) for combo in self.combinations]
def add_config(self, nick, config, timeout=None):
DownwardExperiment.add_config(self, nick, config, timeout=timeout)
self._config_nicks.append(nick)
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't
compare revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If
the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = get_experiment_name() + "." + report.output_format
self.add_report(report, outfile=outfile)
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revision triples. Each report pairs up the runs of the same
config and lists the two absolute attribute values and their
difference for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareRevisionsReport
class. If the keyword argument *attributes* is not
specified, a default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self.revision_nicks, 2):
report = CompareRevisionsReport(rev1, rev2, **kwargs)
outfile = os.path.join(self.eval_dir,
"%s-%s-compare.html" % (rev1, rev2))
report(self.eval_dir, outfile)
self.add_step(Step("make-comparison-tables", make_comparison_tables))
def add_scatter_plot_step(self, attributes=None):
"""Add a step that creates scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revision pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
scatter_dir = os.path.join(self.eval_dir, "scatter")
def is_portfolio(config_nick):
return "fdss" in config_nick
def make_scatter_plots():
for config_nick in self._config_nicks:
for rev1, rev2 in itertools.combinations(
self.revision_nicks, 2):
algo1 = "%s-%s" % (rev1, config_nick)
algo2 = "%s-%s" % (rev2, config_nick)
if is_portfolio(config_nick):
valid_attributes = [
attr for attr in attributes
if attr in self.PORTFOLIO_ATTRIBUTES]
else:
valid_attributes = attributes
for attribute in valid_attributes:
name = "-".join([rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
report = ScatterPlotReport(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(self.eval_dir, os.path.join(scatter_dir, name))
self.add_step(Step("make-scatter-plots", make_scatter_plots))
| 12,741 | 35.614943 | 79 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue486/issue486.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
import common_setup
CONFIGS = {
'astar_ipdb': [
'--search',
'astar(ipdb())'],
'astar_pdb': [
'--search',
'astar(pdb())'],
'astar_gapdb': [
'--search',
'astar(gapdb())'],
}
exp = common_setup.IssueExperiment(
search_revisions=["issue486-base", "issue486-v1"],
configs=CONFIGS,
suite=suites.suite_optimal_with_ipc11(),
)
exp.add_comparison_table_step()
exp()
| 550 | 18 | 54 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue462/issue462-sat.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites, configs
from downward.reports.compare import CompareConfigsReport
import common_setup
REVISIONS = ["issue462-base", "issue462-v1"]
exp = common_setup.IssueExperiment(
search_revisions=REVISIONS,
configs=configs.default_configs_satisficing(),
suite=suites.suite_satisficing_with_ipc11(),
limits={"search_time": 300}
)
exp.add_absolute_report_step()
exp.add_comparison_table_step()
def grouped_configs_to_compare(config_nicks):
grouped_configs = []
for config_nick in config_nicks:
col_names = ['%s-%s' % (r, config_nick) for r in REVISIONS]
grouped_configs.append((col_names[0], col_names[1],
'Diff - %s' % config_nick))
return grouped_configs
exp.add_report(CompareConfigsReport(
compared_configs=grouped_configs_to_compare(configs.configs_satisficing_core()),
attributes=common_setup.IssueExperiment.DEFAULT_TABLE_ATTRIBUTES,
),
outfile="issue462-sat-compare-core-configs.html"
)
def add_first_run_search_time(run):
if run.get("search_time_all", []):
run["first_run_search_time"] = run["search_time_all"][0]
return run
exp.add_report(CompareConfigsReport(
compared_configs=grouped_configs_to_compare(configs.configs_satisficing_ipc()),
attributes=common_setup.IssueExperiment.DEFAULT_TABLE_ATTRIBUTES + ["first_run_search_time"],
filter=add_first_run_search_time,
),
outfile="issue462-sat-compare-portfolio-configs.html"
)
exp.add_scatter_plot_step()
exp()
| 1,700 | 32.352941 | 113 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue462/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import sys
from lab.environments import LocalEnvironment, MaiaEnvironment
from lab.experiment import ARGPARSER
from lab.steps import Step
from downward.experiments import DownwardExperiment, _get_rev_nick
from downward.checkouts import Translator, Preprocessor, Planner
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import CompareRevisionsReport
from downward.reports.scatter import ScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
def get_script():
"""Get file name of main script."""
import __main__
return __main__.__file__
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return (node.endswith("cluster.bc2.ch") or
node.startswith("gkigrid") or
node in ["habakuk", "turtur"])
def is_test_run():
return ARGS.test_run == "yes" or (ARGS.test_run == "auto" and
not is_running_on_cluster())
class IssueExperiment(DownwardExperiment):
"""Wrapper for DownwardExperiment with a few convenience features."""
DEFAULT_TEST_SUITE = "gripper:prob01.pddl"
# TODO: Once we have reference results, we should add "quality".
# TODO: Add something about errors/exit codes.
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"plan_length",
]
def __init__(self, configs, suite, grid_priority=None, path=None,
repo=None, revisions=None, search_revisions=None,
test_suite=None, **kwargs):
"""Create a DownwardExperiment with some convenience features.
*configs* must be a non-empty dict of {nick: cmdline} pairs
that sets the planner configurations to test. ::
IssueExperiment(configs={
"lmcut": ["--search", "astar(lmcut())"],
"ipdb": ["--search", "astar(ipdb())"]})
*suite* sets the benchmarks for the experiment. It must be a
single string or a list of strings specifying domains or
tasks. The downward.suites module has many predefined
suites. ::
IssueExperiment(suite=["grid", "gripper:prob01.pddl"])
from downward import suites
IssueExperiment(suite=suites.suite_all())
IssueExperiment(suite=suites.suite_satisficing_with_ipc11())
IssueExperiment(suite=suites.suite_optimal())
Use *grid_priority* to set the job priority for cluster
experiments. It must be in the range [-1023, 0] where 0 is the
highest priority. By default the priority is 0. ::
IssueExperiment(grid_priority=-500)
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
If *repo* is specified, it must be the path to the root of a
local Fast Downward repository. If omitted, the repository
is derived automatically from the main script's path. Example::
script = /path/to/fd-repo/experiments/issue123/exp01.py -->
repo = /path/to/fd-repo
If *revisions* is specified, it should be a non-empty
list of revisions, which specify which planner versions to use
in the experiment. The same versions are used for translator,
preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"])
If *search_revisions* is specified, it should be a non-empty
list of revisions, which specify which search component
versions to use in the experiment. All runs use the
translator and preprocessor component of the first
revision. ::
IssueExperiment(search_revisions=["default", "issue123"])
If you really need to specify the (translator, preprocessor,
planner) triples manually, use the *combinations* parameter
from the base class (might be deprecated soon). The options
*revisions*, *search_revisions* and *combinations* can be
freely mixed, but at least one of them must be given.
Specify *test_suite* to set the benchmarks for experiment test
runs. By default the first gripper task is used.
IssueExperiment(test_suite=["depot:pfile1", "tpp:p01.pddl"])
"""
if is_test_run():
kwargs["environment"] = LocalEnvironment()
suite = test_suite or self.DEFAULT_TEST_SUITE
elif "environment" not in kwargs:
kwargs["environment"] = MaiaEnvironment(priority=grid_priority)
if path is None:
path = get_data_dir()
if repo is None:
repo = get_repo_base()
kwargs.setdefault("combinations", [])
if not any([revisions, search_revisions, kwargs["combinations"]]):
raise ValueError('At least one of "revisions", "search_revisions" '
'or "combinations" must be given')
if revisions:
kwargs["combinations"].extend([
(Translator(repo, rev),
Preprocessor(repo, rev),
Planner(repo, rev))
for rev in revisions])
if search_revisions:
base_rev = search_revisions[0]
# Use the same nick for all parts to get short revision nick.
kwargs["combinations"].extend([
(Translator(repo, base_rev, nick=rev),
Preprocessor(repo, base_rev, nick=rev),
Planner(repo, rev, nick=rev))
for rev in search_revisions])
DownwardExperiment.__init__(self, path=path, repo=repo, **kwargs)
self._config_nicks = []
for nick, config in configs.items():
self.add_config(nick, config)
self.add_suite(suite)
@property
def revision_nicks(self):
# TODO: Once the add_algorithm() API is available we should get
# rid of the call to _get_rev_nick() and avoid inspecting the
# list of combinations by setting and saving the algorithm nicks.
return [_get_rev_nick(*combo) for combo in self.combinations]
def add_config(self, nick, config, timeout=None):
DownwardExperiment.add_config(self, nick, config, timeout=timeout)
self._config_nicks.append(nick)
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't
compare revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If
the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = get_experiment_name() + "." + report.output_format
self.add_report(report, outfile=outfile)
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revision triples. Each report pairs up the runs of the same
config and lists the two absolute attribute values and their
difference for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareRevisionsReport
class. If the keyword argument *attributes* is not
specified, a default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self.revision_nicks, 2):
report = CompareRevisionsReport(rev1, rev2, **kwargs)
outfile = os.path.join(self.eval_dir,
"%s-%s-compare.html" % (rev1, rev2))
report(self.eval_dir, outfile)
self.add_step(Step("make-comparison-tables", make_comparison_tables))
def add_scatter_plot_step(self, attributes=None):
"""Add a step that creates scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revision pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
scatter_dir = os.path.join(self.eval_dir, "scatter")
def is_portfolio(config_nick):
return "fdss" in config_nick
def make_scatter_plots():
for config_nick in self._config_nicks:
for rev1, rev2 in itertools.combinations(
self.revision_nicks, 2):
algo1 = "%s-%s" % (rev1, config_nick)
algo2 = "%s-%s" % (rev2, config_nick)
if is_portfolio(config_nick):
valid_attributes = [
attr for attr in attributes
if attr in self.PORTFOLIO_ATTRIBUTES]
else:
valid_attributes = attributes
for attribute in valid_attributes:
name = "-".join([rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
report = ScatterPlotReport(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(self.eval_dir, os.path.join(scatter_dir, name))
self.add_step(Step("make-scatter-plots", make_scatter_plots))
| 12,741 | 35.614943 | 79 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue462/issue462-opt.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites, configs
from downward.reports.compare import CompareConfigsReport
import common_setup
REVISIONS = ["issue462-base", "issue462-v1"]
CONFIGS = configs.default_configs_optimal()
# remove config that is disabled in this branch
del CONFIGS['astar_selmax_lmcut_lmcount']
exp = common_setup.IssueExperiment(
search_revisions=REVISIONS,
configs=CONFIGS,
suite=suites.suite_optimal_with_ipc11(),
limits={"search_time": 300}
)
exp.add_absolute_report_step()
exp.add_comparison_table_step()
def grouped_configs_to_compare(config_nicks):
grouped_configs = []
for config_nick in config_nicks:
col_names = ['%s-%s' % (r, config_nick) for r in REVISIONS]
grouped_configs.append((col_names[0], col_names[1],
'Diff - %s' % config_nick))
return grouped_configs
exp.add_report(CompareConfigsReport(
compared_configs=grouped_configs_to_compare(configs.configs_optimal_core()),
attributes=common_setup.IssueExperiment.DEFAULT_TABLE_ATTRIBUTES,
),
outfile="issue462-opt-compare-core-configs.html"
)
def add_first_run_search_time(run):
if run.get("search_time_all", []):
run["first_run_search_time"] = run["search_time_all"][0]
return run
exp.add_report(CompareConfigsReport(
compared_configs=grouped_configs_to_compare(configs.configs_optimal_ipc()),
attributes=common_setup.IssueExperiment.DEFAULT_TABLE_ATTRIBUTES + ["first_run_search_time"],
filter=add_first_run_search_time,
),
outfile="issue462-opt-compare-portfolio-configs.html"
)
exp.add_scatter_plot_step()
exp()
| 1,793 | 31.618182 | 113 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue198/v2-opt.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue198-v2-base", "issue198-v2"]
CONFIGS = [
IssueConfig('astar_blind', ['--search', 'astar(blind)']),
IssueConfig('seq-opt-bjolp', [], driver_options=["--alias", "seq-opt-bjolp"]),
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
exp.add_parse_again_step()
#exp.add_absolute_report_step()
exp.add_comparison_table_step()
for attribute in ["total_time"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain"),
),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS)
)
exp.run_steps()
| 1,821 | 28.868852 | 93 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue198/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import ComparativeReport
from downward.reports.scatter import ScatterPlotReport
from relativescatter import RelativeScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
DEFAULT_OPTIMAL_SUITE = [
'airport', 'barman-opt11-strips', 'barman-opt14-strips', 'blocks',
'childsnack-opt14-strips', 'depot', 'driverlog',
'elevators-opt08-strips', 'elevators-opt11-strips',
'floortile-opt11-strips', 'floortile-opt14-strips', 'freecell',
'ged-opt14-strips', 'grid', 'gripper', 'hiking-opt14-strips',
'logistics00', 'logistics98', 'miconic', 'movie', 'mprime',
'mystery', 'nomystery-opt11-strips', 'openstacks-opt08-strips',
'openstacks-opt11-strips', 'openstacks-opt14-strips',
'openstacks-strips', 'parcprinter-08-strips',
'parcprinter-opt11-strips', 'parking-opt11-strips',
'parking-opt14-strips', 'pathways-noneg', 'pegsol-08-strips',
'pegsol-opt11-strips', 'pipesworld-notankage',
'pipesworld-tankage', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-opt11-strips',
'sokoban-opt08-strips', 'sokoban-opt11-strips', 'storage',
'tetris-opt14-strips', 'tidybot-opt11-strips',
'tidybot-opt14-strips', 'tpp', 'transport-opt08-strips',
'transport-opt11-strips', 'transport-opt14-strips',
'trucks-strips', 'visitall-opt11-strips', 'visitall-opt14-strips',
'woodworking-opt08-strips', 'woodworking-opt11-strips',
'zenotravel']
DEFAULT_SATISFICING_SUITE = [
'airport', 'assembly', 'barman-sat11-strips',
'barman-sat14-strips', 'blocks', 'cavediving-14-adl',
'childsnack-sat14-strips', 'citycar-sat14-adl', 'depot',
'driverlog', 'elevators-sat08-strips', 'elevators-sat11-strips',
'floortile-sat11-strips', 'floortile-sat14-strips', 'freecell',
'ged-sat14-strips', 'grid', 'gripper', 'hiking-sat14-strips',
'logistics00', 'logistics98', 'maintenance-sat14-adl', 'miconic',
'miconic-fulladl', 'miconic-simpleadl', 'movie', 'mprime',
'mystery', 'nomystery-sat11-strips', 'openstacks',
'openstacks-sat08-adl', 'openstacks-sat08-strips',
'openstacks-sat11-strips', 'openstacks-sat14-strips',
'openstacks-strips', 'optical-telegraphs', 'parcprinter-08-strips',
'parcprinter-sat11-strips', 'parking-sat11-strips',
'parking-sat14-strips', 'pathways', 'pathways-noneg',
'pegsol-08-strips', 'pegsol-sat11-strips', 'philosophers',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-large',
'psr-middle', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-sat11-strips', 'schedule',
'sokoban-sat08-strips', 'sokoban-sat11-strips', 'storage',
'tetris-sat14-strips', 'thoughtful-sat14-strips',
'tidybot-sat11-strips', 'tpp', 'transport-sat08-strips',
'transport-sat11-strips', 'transport-sat14-strips', 'trucks',
'trucks-strips', 'visitall-sat11-strips', 'visitall-sat14-strips',
'woodworking-sat08-strips', 'woodworking-sat11-strips',
'zenotravel']
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return node.endswith(".scicore.unibas.ch") or node.endswith(".cluster.bc2.ch")
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["depot:p01.pddl", "gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, outfile=outfile)
self.add_step(
'publish-absolute-report', subprocess.call, ['publish', outfile])
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = ComparativeReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.%s" % (
self.name, rev1, rev2, report.output_format))
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
subprocess.call(["publish", outfile])
self.add_step("make-comparison-tables", make_comparison_tables)
self.add_step(
"publish-comparison-tables", publish_comparison_tables)
def add_scatter_plot_step(self, relative=False, attributes=None):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if relative:
report_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
report_class = ScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "{}-{}".format(rev1, config_nick)
algo2 = "{}-{}".format(rev2, config_nick)
report = report_class(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(step_name, make_scatter_plots)
| 14,153 | 35.955614 | 82 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue198/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(
axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows a relative comparison of two
algorithms with regard to the given attribute. The attribute value
of algorithm 1 is shown on the x-axis and the relation to the value
of algorithm 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['algorithm'] == self.algorithms[0] and
run2['algorithm'] == self.algorithms[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.algorithms[0], val1)
assert val2 > 0, (domain, problem, self.algorithms[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlot uses log-scaling on the x-axis by default.
PlotReport._set_scales(
self, xscale or self.attribute.scale or 'log', 'log')
| 3,875 | 35.566038 | 78 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue814/v15.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue814-v13", "issue814-v14", "issue814-v15"]
if common_setup.is_test_run():
BUILDS = ["release64"]
else:
BUILDS = ["release32", "release64"]
CONFIGS = [
IssueConfig(
build + "-{heuristic}".format(**locals()),
["--evaluator", "h={heuristic}()".format(**locals()),
"--search", "lazy_greedy([h])"],
build_options=[build],
driver_options=["--build", build, "--overall-time-limit", "30m"])
for build in BUILDS
for heuristic in ["ff"]
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
#exp.add_absolute_report_step()
exp.add_comparison_table_step(
attributes=IssueExperiment.DEFAULT_TABLE_ATTRIBUTES +
["simplify_before", "simplify_after", "simplify_time"])
for attribute in ["memory", "total_time"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain")),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS))
exp.run_steps()
| 2,244 | 30.619718 | 94 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue814/v2.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue814-v1", "issue814-v2"]
if common_setup.is_test_run():
BUILDS = ["release32"]
else:
BUILDS = ["debug64", "release32", "release64"]
CONFIGS = [
IssueConfig(
build + "-{heuristic}".format(**locals()),
["--evaluator", "h={heuristic}()".format(**locals()), "--search", "lazy_greedy([h],preferred=[h])"],
build_options=[build],
driver_options=["--build", build, "--overall-time-limit", "30m"])
for build in BUILDS
for heuristic in ["add", "ff"]
]
SUITE = common_setup.DEFAULT_SATISFICING_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
#exp.add_absolute_report_step()
exp.add_comparison_table_step(
attributes=IssueExperiment.DEFAULT_TABLE_ATTRIBUTES +
["simplify_before", "simplify_after", "simplify_time"])
for attribute in ["memory", "total_time"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain")),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS))
exp.run_steps()
| 2,253 | 31.2 | 108 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue814/align-hmax.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue814-v14", "issue814-v16"]
if common_setup.is_test_run():
BUILDS = ["release64"]
else:
BUILDS = ["release32", "release64"]
CONFIGS = [
IssueConfig(
build + "-{heuristic}".format(**locals()),
["--evaluator", "h={heuristic}()".format(**locals()),
"--search", "astar(h)"],
build_options=[build],
driver_options=["--build", build, "--overall-time-limit", "30m"])
for build in BUILDS
for heuristic in ["hmax"]
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_1",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
#exp.add_absolute_report_step()
exp.add_comparison_table_step(
attributes=IssueExperiment.DEFAULT_TABLE_ATTRIBUTES +
["simplify_before", "simplify_after", "simplify_time"])
for attribute in ["memory", "total_time"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain")),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS))
exp.run_steps()
| 2,222 | 30.309859 | 94 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue814/parser.py
|
#! /usr/bin/env python
"""
========================================================================
Simplifying 29928 unary operators... done! [17292 unary operators]
time to simplify: 0.022623s
========================================================================
=> Here we want to extract 29928 (simplify_before), 17292 (simplify_after) and
0.022623s (simplify_time).
"""
import re
from lab.parser import Parser
print 'Running custom parser'
parser = Parser()
parser.add_pattern('simplify_before', r'^Simplifying (\d+) unary operators\.\.\. done! \[\d+ unary operators\]$', type=int)
parser.add_pattern('simplify_after', r'^Simplifying \d+ unary operators\.\.\. done! \[(\d+) unary operators\]$', type=int)
parser.add_pattern('simplify_time', r'^time to simplify: (.+)s$', type=float)
parser.parse()
| 812 | 32.875 | 123 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue814/v16-hmax.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue814-v15", "issue814-v16"]
if common_setup.is_test_run():
BUILDS = ["release64"]
else:
BUILDS = ["release32", "release64"]
CONFIGS = [
IssueConfig(
build + "-{heuristic}".format(**locals()),
["--evaluator", "h={heuristic}()".format(**locals()),
"--search", "astar(h)"],
build_options=[build],
driver_options=["--build", build, "--overall-time-limit", "30m"])
for build in BUILDS
for heuristic in ["hmax"]
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_1",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
#exp.add_absolute_report_step()
exp.add_comparison_table_step(
attributes=IssueExperiment.DEFAULT_TABLE_ATTRIBUTES +
["simplify_before", "simplify_after", "simplify_time"])
for attribute in ["memory", "total_time"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain")),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS))
exp.run_steps()
| 2,222 | 30.309859 | 94 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue814/v11-base-hmax-30min.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue814-base", "issue814-v11"]
if common_setup.is_test_run():
BUILDS = ["release32"]
else:
BUILDS = ["debug64", "release32", "release64"]
CONFIGS = [
IssueConfig(
build + "-{heuristic}".format(**locals()),
["--evaluator", "h={heuristic}()".format(**locals()),
"--search", "astar(h)"],
build_options=[build],
driver_options=["--build", build, "--overall-time-limit", "30m"])
for build in BUILDS
for heuristic in ["hmax"]
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
#exp.add_absolute_report_step()
exp.add_comparison_table_step(
attributes=IssueExperiment.DEFAULT_TABLE_ATTRIBUTES +
["simplify_before", "simplify_after", "simplify_time"])
for attribute in ["memory", "total_time"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain")),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS))
exp.run_steps()
| 2,234 | 30.478873 | 94 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue814/v4.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue814-base", "issue814-v4"]
if common_setup.is_test_run():
BUILDS = ["release32"]
else:
BUILDS = ["debug64", "release32", "release64"]
CONFIGS = [
IssueConfig(
build + "-{heuristic}".format(**locals()),
["--evaluator", "h={heuristic}()".format(**locals()), "--search", "lazy_greedy([h],preferred=[h])"],
build_options=[build],
driver_options=["--build", build, "--overall-time-limit", "5m"])
for build in BUILDS
for heuristic in ["add", "ff"]
]
SUITE = common_setup.DEFAULT_SATISFICING_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
#exp.add_absolute_report_step()
exp.add_comparison_table_step(
attributes=IssueExperiment.DEFAULT_TABLE_ATTRIBUTES +
["simplify_before", "simplify_after", "simplify_time"])
for attribute in ["memory", "total_time"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain")),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS))
exp.run_steps()
| 2,254 | 31.214286 | 108 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue814/v1.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue814-base", "issue814-v1"]
if common_setup.is_test_run():
BUILDS = ["release32"]
else:
BUILDS = ["debug64", "release32", "release64"]
CONFIGS = [
IssueConfig(
build + "-{heuristic}".format(**locals()),
["--evaluator", "h={heuristic}()".format(**locals()), "--search", "lazy_greedy([h],preferred=[h])"],
build_options=[build],
driver_options=["--build", build, "--overall-time-limit", "30m"])
for build in BUILDS
for heuristic in ["add", "ff"]
]
SUITE = common_setup.DEFAULT_SATISFICING_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
#exp.add_absolute_report_step()
exp.add_comparison_table_step(
attributes=IssueExperiment.DEFAULT_TABLE_ATTRIBUTES +
["simplify_before", "simplify_after", "simplify_time"])
for attribute in ["memory", "total_time"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain")),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS))
exp.run_steps()
| 2,255 | 31.228571 | 108 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue814/v13.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue814-v12", "issue814-v13"]
if common_setup.is_test_run():
BUILDS = ["release64"]
else:
BUILDS = ["release32", "release64"]
CONFIGS = [
IssueConfig(
build + "-{heuristic}".format(**locals()),
["--evaluator", "h={heuristic}()".format(**locals()),
"--search", "lazy_greedy([h])"],
build_options=[build],
driver_options=["--build", build, "--overall-time-limit", "30m"])
for build in BUILDS
for heuristic in ["add", "ff"]
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
#exp.add_absolute_report_step()
exp.add_comparison_table_step(
attributes=IssueExperiment.DEFAULT_TABLE_ATTRIBUTES +
["simplify_before", "simplify_after", "simplify_time"])
for attribute in ["memory", "total_time"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain")),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS))
exp.run_steps()
| 2,235 | 30.492958 | 94 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue814/v15-hadd.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue814-v13", "issue814-v14", "issue814-v15"]
if common_setup.is_test_run():
BUILDS = ["release64"]
else:
BUILDS = ["release32", "release64"]
CONFIGS = [
IssueConfig(
build + "-{heuristic}".format(**locals()),
["--evaluator", "h={heuristic}()".format(**locals()),
"--search", "lazy_greedy([h])"],
build_options=[build],
driver_options=["--build", build, "--overall-time-limit", "30m"])
for build in BUILDS
for heuristic in ["add"]
]
SUITE = common_setup.DEFAULT_SATISFICING_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
#exp.add_absolute_report_step()
exp.add_comparison_table_step(
attributes=IssueExperiment.DEFAULT_TABLE_ATTRIBUTES +
["simplify_before", "simplify_after", "simplify_time"])
for attribute in ["memory", "total_time"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain")),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS))
exp.run_steps()
| 2,249 | 30.690141 | 94 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue814/v1_7_10.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
"""This experiment is only here for completeness because it was referred
to on the tracker. Don't use it as given here: the different experiments
that are aggregated here used different timeouts, so the results will be
misleading."""
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue814-base", "issue814-v1", "issue814-v7", "issue814-v10"]
if common_setup.is_test_run():
BUILDS = ["release32"]
else:
BUILDS = ["debug64", "release32", "release64"]
CONFIGS = [
IssueConfig(
build + "-{heuristic}".format(**locals()),
["--evaluator", "h={heuristic}()".format(**locals()), "--search", "lazy_greedy([h],preferred=[h])"],
build_options=[build],
driver_options=["--build", build, "--overall-time-limit", "30m"])
for build in BUILDS
for heuristic in ["add", "ff"]
]
SUITE = common_setup.DEFAULT_SATISFICING_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
## The following steps are to actually run the experiment.
# exp.add_step('build', exp.build)
# exp.add_step('start', exp.start_runs)
# exp.add_fetcher(name='fetch')
## Alternatively, the following steps fetch the results from the other experiments.
exp.add_fetcher('data/issue814-v1-eval')
exp.add_fetcher('data/issue814-v7-eval')
exp.add_fetcher('data/issue814-v10-eval')
exp.add_absolute_report_step()
exp.add_comparison_table_step(
attributes=IssueExperiment.DEFAULT_TABLE_ATTRIBUTES +
["simplify_before", "simplify_after", "simplify_time"])
for attribute in ["memory", "total_time"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain")),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS))
exp.run_steps()
| 2,794 | 33.506173 | 108 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue814/v17-sat.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue814-v12-base", "issue814-v16", "issue814-v17"]
if common_setup.is_test_run():
BUILDS = ["release64"]
else:
BUILDS = ["release32", "release64"]
CONFIGS = [
IssueConfig(
build + "-{heuristic}".format(**locals()),
["--evaluator", "h={heuristic}()".format(**locals()),
"--search", "lazy_greedy([h])"],
build_options=[build],
driver_options=["--build", build, "--overall-time-limit", "30m"])
for build in BUILDS
for heuristic in ["add", "ff"]
]
SUITE = common_setup.DEFAULT_SATISFICING_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
#exp.add_absolute_report_step()
exp.add_comparison_table_step(
attributes=IssueExperiment.DEFAULT_TABLE_ATTRIBUTES +
["simplify_before", "simplify_after", "simplify_time"])
for attribute in ["memory", "total_time"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain")),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS))
exp.run_steps()
| 2,260 | 30.84507 | 94 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue814/align-sat.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue814-v14", "issue814-v16"]
if common_setup.is_test_run():
BUILDS = ["release64"]
else:
BUILDS = ["release32", "release64"]
CONFIGS = [
IssueConfig(
build + "-{heuristic}".format(**locals()),
["--evaluator", "h={heuristic}()".format(**locals()),
"--search", "lazy_greedy([h])"],
build_options=[build],
driver_options=["--build", build, "--overall-time-limit", "30m"])
for build in BUILDS
for heuristic in ["add", "ff"]
]
SUITE = common_setup.DEFAULT_SATISFICING_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
#exp.add_absolute_report_step()
exp.add_comparison_table_step(
attributes=IssueExperiment.DEFAULT_TABLE_ATTRIBUTES +
["simplify_before", "simplify_after", "simplify_time"])
for attribute in ["memory", "total_time"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain")),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS))
exp.run_steps()
| 2,239 | 30.549296 | 94 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue814/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import ComparativeReport
from downward.reports.scatter import ScatterPlotReport
from relativescatter import RelativeScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
DEFAULT_OPTIMAL_SUITE = [
'agricola-opt18-strips', 'airport', 'barman-opt11-strips',
'barman-opt14-strips', 'blocks', 'childsnack-opt14-strips',
'data-network-opt18-strips', 'depot', 'driverlog',
'elevators-opt08-strips', 'elevators-opt11-strips',
'floortile-opt11-strips', 'floortile-opt14-strips', 'freecell',
'ged-opt14-strips', 'grid', 'gripper', 'hiking-opt14-strips',
'logistics00', 'logistics98', 'miconic', 'movie', 'mprime',
'mystery', 'nomystery-opt11-strips', 'openstacks-opt08-strips',
'openstacks-opt11-strips', 'openstacks-opt14-strips',
'openstacks-strips', 'organic-synthesis-opt18-strips',
'organic-synthesis-split-opt18-strips', 'parcprinter-08-strips',
'parcprinter-opt11-strips', 'parking-opt11-strips',
'parking-opt14-strips', 'pathways-noneg', 'pegsol-08-strips',
'pegsol-opt11-strips', 'petri-net-alignment-opt18-strips',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-small', 'rovers',
'satellite', 'scanalyzer-08-strips', 'scanalyzer-opt11-strips',
'snake-opt18-strips', 'sokoban-opt08-strips',
'sokoban-opt11-strips', 'spider-opt18-strips', 'storage',
'termes-opt18-strips', 'tetris-opt14-strips',
'tidybot-opt11-strips', 'tidybot-opt14-strips', 'tpp',
'transport-opt08-strips', 'transport-opt11-strips',
'transport-opt14-strips', 'trucks-strips', 'visitall-opt11-strips',
'visitall-opt14-strips', 'woodworking-opt08-strips',
'woodworking-opt11-strips', 'zenotravel']
DEFAULT_SATISFICING_SUITE = [
'agricola-sat18-strips', 'airport', 'assembly',
'barman-sat11-strips', 'barman-sat14-strips', 'blocks',
'caldera-sat18-adl', 'caldera-split-sat18-adl', 'cavediving-14-adl',
'childsnack-sat14-strips', 'citycar-sat14-adl',
'data-network-sat18-strips', 'depot', 'driverlog',
'elevators-sat08-strips', 'elevators-sat11-strips',
'flashfill-sat18-adl', 'floortile-sat11-strips',
'floortile-sat14-strips', 'freecell', 'ged-sat14-strips', 'grid',
'gripper', 'hiking-sat14-strips', 'logistics00', 'logistics98',
'maintenance-sat14-adl', 'miconic', 'miconic-fulladl',
'miconic-simpleadl', 'movie', 'mprime', 'mystery',
'nomystery-sat11-strips', 'nurikabe-sat18-adl', 'openstacks',
'openstacks-sat08-adl', 'openstacks-sat08-strips',
'openstacks-sat11-strips', 'openstacks-sat14-strips',
'openstacks-strips', 'optical-telegraphs',
'organic-synthesis-sat18-strips',
'organic-synthesis-split-sat18-strips', 'parcprinter-08-strips',
'parcprinter-sat11-strips', 'parking-sat11-strips',
'parking-sat14-strips', 'pathways', 'pathways-noneg',
'pegsol-08-strips', 'pegsol-sat11-strips', 'philosophers',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-large',
'psr-middle', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-sat11-strips', 'schedule',
'settlers-sat18-adl', 'snake-sat18-strips', 'sokoban-sat08-strips',
'sokoban-sat11-strips', 'spider-sat18-strips', 'storage',
'termes-sat18-strips', 'tetris-sat14-strips',
'thoughtful-sat14-strips', 'tidybot-sat11-strips', 'tpp',
'transport-sat08-strips', 'transport-sat11-strips',
'transport-sat14-strips', 'trucks', 'trucks-strips',
'visitall-sat11-strips', 'visitall-sat14-strips',
'woodworking-sat08-strips', 'woodworking-sat11-strips',
'zenotravel']
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return node.endswith(".scicore.unibas.ch") or node.endswith(".cluster.bc2.ch")
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["depot:p01.pddl", "gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"planner_memory",
"planner_time",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, outfile=outfile)
self.add_step(
'publish-absolute-report', subprocess.call, ['publish', outfile])
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = ComparativeReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.%s" % (
self.name, rev1, rev2, report.output_format))
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
subprocess.call(["publish", outfile])
self.add_step("make-comparison-tables", make_comparison_tables)
self.add_step(
"publish-comparison-tables", publish_comparison_tables)
def add_scatter_plot_step(self, relative=False, attributes=None):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if relative:
report_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
report_class = ScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "{}-{}".format(rev1, config_nick)
algo2 = "{}-{}".format(rev2, config_nick)
report = report_class(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(step_name, make_scatter_plots)
| 14,786 | 36.435443 | 82 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue814/v15-hmax.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue814-v13", "issue814-v14", "issue814-v15"]
if common_setup.is_test_run():
BUILDS = ["release64"]
else:
BUILDS = ["release32", "release64"]
CONFIGS = [
IssueConfig(
build + "-{heuristic}".format(**locals()),
["--evaluator", "h={heuristic}()".format(**locals()),
"--search", "astar(h)"],
build_options=[build],
driver_options=["--build", build, "--overall-time-limit", "30m"])
for build in BUILDS
for heuristic in ["hmax"]
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
#exp.add_absolute_report_step()
exp.add_comparison_table_step(
attributes=IssueExperiment.DEFAULT_TABLE_ATTRIBUTES +
["simplify_before", "simplify_after", "simplify_time"])
for attribute in ["memory", "total_time"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain")),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS))
exp.run_steps()
| 2,238 | 30.535211 | 94 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue814/v17-hmax.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue814-v12-base", "issue814-v16", "issue814-v17"]
if common_setup.is_test_run():
BUILDS = ["release64"]
else:
BUILDS = ["release32", "release64"]
CONFIGS = [
IssueConfig(
build + "-{heuristic}".format(**locals()),
["--evaluator", "h={heuristic}()".format(**locals()),
"--search", "astar(h)"],
build_options=[build],
driver_options=["--build", build, "--overall-time-limit", "30m"])
for build in BUILDS
for heuristic in ["hmax"]
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_1",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
#exp.add_absolute_report_step()
exp.add_comparison_table_step(
attributes=IssueExperiment.DEFAULT_TABLE_ATTRIBUTES +
["simplify_before", "simplify_after", "simplify_time"])
for attribute in ["memory", "total_time"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain")),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS))
exp.run_steps()
| 2,243 | 30.605634 | 94 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue814/v9.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue814-v8", "issue814-v9"]
if common_setup.is_test_run():
BUILDS = ["release32"]
else:
BUILDS = ["debug64", "release32", "release64"]
CONFIGS = [
IssueConfig(
build + "-{heuristic}".format(**locals()),
["--evaluator", "h={heuristic}()".format(**locals()), "--search", "lazy_greedy([h],preferred=[h])"],
build_options=[build],
driver_options=["--build", build, "--overall-time-limit", "5m"])
for build in BUILDS
for heuristic in ["add", "ff"]
]
SUITE = common_setup.DEFAULT_SATISFICING_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
#exp.add_absolute_report_step()
exp.add_comparison_table_step(
attributes=IssueExperiment.DEFAULT_TABLE_ATTRIBUTES +
["simplify_before", "simplify_after", "simplify_time"])
for attribute in ["memory", "total_time"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain")),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS))
exp.run_steps()
| 2,252 | 31.185714 | 108 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue814/v10.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue814-v9", "issue814-v10"]
if common_setup.is_test_run():
BUILDS = ["release32"]
else:
BUILDS = ["debug64", "release32", "release64"]
CONFIGS = [
IssueConfig(
build + "-{heuristic}".format(**locals()),
["--evaluator", "h={heuristic}()".format(**locals()), "--search", "lazy_greedy([h],preferred=[h])"],
build_options=[build],
driver_options=["--build", build, "--overall-time-limit", "5m"])
for build in BUILDS
for heuristic in ["add", "ff"]
]
SUITE = common_setup.DEFAULT_SATISFICING_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
#exp.add_absolute_report_step()
exp.add_comparison_table_step(
attributes=IssueExperiment.DEFAULT_TABLE_ATTRIBUTES +
["simplify_before", "simplify_after", "simplify_time"])
for attribute in ["memory", "total_time"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain")),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS))
exp.run_steps()
| 2,253 | 31.2 | 108 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue814/v3.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue814-v2", "issue814-v3"]
if common_setup.is_test_run():
BUILDS = ["release32"]
else:
BUILDS = ["debug64", "release32", "release64"]
CONFIGS = [
IssueConfig(
build + "-{heuristic}".format(**locals()),
["--evaluator", "h={heuristic}()".format(**locals()), "--search", "lazy_greedy([h],preferred=[h])"],
build_options=[build],
driver_options=["--build", build, "--overall-time-limit", "5m"])
for build in BUILDS
for heuristic in ["add", "ff"]
]
SUITE = common_setup.DEFAULT_SATISFICING_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
#exp.add_absolute_report_step()
exp.add_comparison_table_step(
attributes=IssueExperiment.DEFAULT_TABLE_ATTRIBUTES +
["simplify_before", "simplify_after", "simplify_time"])
for attribute in ["memory", "total_time"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain")),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS))
exp.run_steps()
| 2,252 | 31.185714 | 108 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue814/v6.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue814-v5", "issue814-v6"]
if common_setup.is_test_run():
BUILDS = ["release32"]
else:
BUILDS = ["debug64", "release32", "release64"]
CONFIGS = [
IssueConfig(
build + "-{heuristic}".format(**locals()),
["--evaluator", "h={heuristic}()".format(**locals()), "--search", "lazy_greedy([h],preferred=[h])"],
build_options=[build],
driver_options=["--build", build, "--overall-time-limit", "5m"])
for build in BUILDS
for heuristic in ["add", "ff"]
]
SUITE = common_setup.DEFAULT_SATISFICING_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
#exp.add_absolute_report_step()
exp.add_comparison_table_step(
attributes=IssueExperiment.DEFAULT_TABLE_ATTRIBUTES +
["simplify_before", "simplify_after", "simplify_time"])
for attribute in ["memory", "total_time"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain")),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS))
exp.run_steps()
| 2,252 | 31.185714 | 108 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue814/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(
axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows a relative comparison of two
algorithms with regard to the given attribute. The attribute value
of algorithm 1 is shown on the x-axis and the relation to the value
of algorithm 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['algorithm'] == self.algorithms[0] and
run2['algorithm'] == self.algorithms[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.algorithms[0], val1)
assert val2 > 0, (domain, problem, self.algorithms[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlot uses log-scaling on the x-axis by default.
PlotReport._set_scales(
self, xscale or self.attribute.scale or 'log', 'log')
| 3,875 | 35.566038 | 78 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue814/v5.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue814-v4", "issue814-v5"]
if common_setup.is_test_run():
BUILDS = ["release32"]
else:
BUILDS = ["debug64", "release32", "release64"]
CONFIGS = [
IssueConfig(
build + "-{heuristic}".format(**locals()),
["--evaluator", "h={heuristic}()".format(**locals()), "--search", "lazy_greedy([h],preferred=[h])"],
build_options=[build],
driver_options=["--build", build, "--overall-time-limit", "5m"])
for build in BUILDS
for heuristic in ["add", "ff"]
]
SUITE = common_setup.DEFAULT_SATISFICING_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
#exp.add_absolute_report_step()
exp.add_comparison_table_step(
attributes=IssueExperiment.DEFAULT_TABLE_ATTRIBUTES +
["simplify_before", "simplify_after", "simplify_time"])
for attribute in ["memory", "total_time"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain")),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS))
exp.run_steps()
| 2,252 | 31.185714 | 108 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue814/v16-sat.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue814-v15", "issue814-v16"]
if common_setup.is_test_run():
BUILDS = ["release64"]
else:
BUILDS = ["release32", "release64"]
CONFIGS = [
IssueConfig(
build + "-{heuristic}".format(**locals()),
["--evaluator", "h={heuristic}()".format(**locals()),
"--search", "lazy_greedy([h])"],
build_options=[build],
driver_options=["--build", build, "--overall-time-limit", "30m"])
for build in BUILDS
for heuristic in ["add", "ff"]
]
SUITE = common_setup.DEFAULT_SATISFICING_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
#exp.add_absolute_report_step()
exp.add_comparison_table_step(
attributes=IssueExperiment.DEFAULT_TABLE_ATTRIBUTES +
["simplify_before", "simplify_after", "simplify_time"])
for attribute in ["memory", "total_time"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain")),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS))
exp.run_steps()
| 2,239 | 30.549296 | 94 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue814/v10-base-30min.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue814-base", "issue814-v10"]
if common_setup.is_test_run():
BUILDS = ["release32"]
else:
BUILDS = ["debug64", "release32", "release64"]
CONFIGS = [
IssueConfig(
build + "-{heuristic}".format(**locals()),
["--evaluator", "h={heuristic}()".format(**locals()), "--search", "lazy_greedy([h],preferred=[h])"],
build_options=[build],
driver_options=["--build", build, "--overall-time-limit", "30m"])
for build in BUILDS
for heuristic in ["add", "ff"]
]
SUITE = common_setup.DEFAULT_SATISFICING_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
#exp.add_absolute_report_step()
exp.add_comparison_table_step(
attributes=IssueExperiment.DEFAULT_TABLE_ATTRIBUTES +
["simplify_before", "simplify_after", "simplify_time"])
for attribute in ["memory", "total_time"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain")),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS))
exp.run_steps()
| 2,256 | 31.242857 | 108 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue814/v8.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue814-v7", "issue814-v8"]
if common_setup.is_test_run():
BUILDS = ["release32"]
else:
BUILDS = ["debug64", "release32", "release64"]
CONFIGS = [
IssueConfig(
build + "-{heuristic}".format(**locals()),
["--evaluator", "h={heuristic}()".format(**locals()), "--search", "lazy_greedy([h],preferred=[h])"],
build_options=[build],
driver_options=["--build", build, "--overall-time-limit", "5m"])
for build in BUILDS
for heuristic in ["add", "ff"]
]
SUITE = common_setup.DEFAULT_SATISFICING_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
#exp.add_absolute_report_step()
exp.add_comparison_table_step(
attributes=IssueExperiment.DEFAULT_TABLE_ATTRIBUTES +
["simplify_before", "simplify_after", "simplify_time"])
for attribute in ["memory", "total_time"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain")),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS))
exp.run_steps()
| 2,252 | 31.185714 | 108 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue814/v7.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue814-v6", "issue814-v7"]
if common_setup.is_test_run():
BUILDS = ["release32"]
else:
BUILDS = ["debug64", "release32", "release64"]
CONFIGS = [
IssueConfig(
build + "-{heuristic}".format(**locals()),
["--evaluator", "h={heuristic}()".format(**locals()), "--search", "lazy_greedy([h],preferred=[h])"],
build_options=[build],
driver_options=["--build", build, "--overall-time-limit", "5m"])
for build in BUILDS
for heuristic in ["add", "ff"]
]
SUITE = common_setup.DEFAULT_SATISFICING_SUITE
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]",
export=["PATH", "DOWNWARD_BENCHMARKS"])
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=1)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
#exp.add_absolute_report_step()
exp.add_comparison_table_step(
attributes=IssueExperiment.DEFAULT_TABLE_ATTRIBUTES +
["simplify_before", "simplify_after", "simplify_time"])
for attribute in ["memory", "total_time"]:
for config in CONFIGS:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_algorithm=["{}-{}".format(rev, config.nick) for rev in REVISIONS],
get_category=lambda run1, run2: run1.get("domain")),
outfile="{}-{}-{}-{}-{}.png".format(exp.name, attribute, config.nick, *REVISIONS))
exp.run_steps()
| 2,252 | 31.185714 | 108 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue621/v1.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
configs = [
IssueConfig(
"cegar-10K-original",
["--search", "astar(cegar(subtasks=[original()],max_states=10000,max_time=infinity))"]),
]
revisions = ["issue621-base", "issue621-v1"]
exp = IssueExperiment(
revisions=revisions,
configs=configs,
suite=suites.suite_optimal_with_ipc11(),
test_suite=["depot:pfile1"],
email="[email protected]",
)
exp.add_comparison_table_step()
for attribute in ["memory", "total_time"]:
for config in configs:
exp.add_report(
RelativeScatterPlotReport(
attributes=[attribute],
filter_config=["{}-{}".format(rev, config.nick) for rev in revisions],
get_category=lambda run1, run2: run1.get("domain"),
),
outfile="{}-{}-{}.png".format(exp.name, attribute, config.nick)
)
exp()
| 1,067 | 25.7 | 96 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue621/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.environments import LocalEnvironment, MaiaEnvironment
from lab.experiment import ARGPARSER
from lab.steps import Step
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import CompareConfigsReport
from downward.reports.scatter import ScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return (
"cluster" in node or
node.startswith("gkigrid") or
node in ["habakuk", "turtur"])
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Wrapper for FastDownwardExperiment with a few convenience features."""
DEFAULT_TEST_SUITE = "gripper:prob01.pddl"
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, suite, revisions=[], configs={}, grid_priority=None,
path=None, test_suite=None, email=None, processes=None,
**kwargs):
"""Create a DownwardExperiment with some convenience features.
If *revisions* is specified, it should be a non-empty
list of revisions, which specify which planner versions to use
in the experiment. The same versions are used for translator,
preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
*configs* must be a non-empty list of IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
*suite* sets the benchmarks for the experiment. It must be a
single string or a list of strings specifying domains or
tasks. The downward.suites module has many predefined
suites. ::
IssueExperiment(..., suite=["grid", "gripper:prob01.pddl"])
from downward import suites
IssueExperiment(..., suite=suites.suite_all())
IssueExperiment(..., suite=suites.suite_satisficing_with_ipc11())
IssueExperiment(..., suite=suites.suite_optimal())
Use *grid_priority* to set the job priority for cluster
experiments. It must be in the range [-1023, 0] where 0 is the
highest priority. By default the priority is 0. ::
IssueExperiment(..., grid_priority=-500)
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
Specify *test_suite* to set the benchmarks for experiment test
runs. By default the first gripper task is used.
IssueExperiment(..., test_suite=["depot:pfile1", "tpp:p01.pddl"])
If *email* is specified, it should be an email address. This
email address will be notified upon completion of the experiments
if it is run on the cluster.
"""
if is_test_run():
kwargs["environment"] = LocalEnvironment(processes=processes)
suite = test_suite or self.DEFAULT_TEST_SUITE
elif "environment" not in kwargs:
kwargs["environment"] = MaiaEnvironment(
priority=grid_priority, email=email)
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
repo = get_repo_base()
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
repo,
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self.add_suite(os.path.join(repo, "benchmarks"), suite)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't
compare revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If
the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(self.eval_dir,
get_experiment_name() + "." +
report.output_format)
self.add_report(report, outfile=outfile)
self.add_step(Step('publish-absolute-report',
subprocess.call,
['publish', outfile]))
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = CompareConfigsReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare" % (self.name, rev1, rev2)
+ "." + report.output_format)
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare" % (self.name, rev1, rev2)
+ ".html")
subprocess.call(['publish', outfile])
self.add_step(Step("make-comparison-tables", make_comparison_tables))
self.add_step(Step("publish-comparison-tables", publish_comparison_tables))
def add_scatter_plot_step(self, attributes=None):
"""Add a step that creates scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
scatter_dir = os.path.join(self.eval_dir, "scatter")
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "%s-%s" % (rev1, config_nick)
algo2 = "%s-%s" % (rev2, config_nick)
report = ScatterPlotReport(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(Step("make-scatter-plots", make_scatter_plots))
| 12,542 | 34.036313 | 83 |
py
|
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