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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue732/v1.py
#! /usr/bin/env python # -*- coding: utf-8 -*- import os from lab.environments import LocalEnvironment, MaiaEnvironment from lab.reports import Attribute, arithmetic_mean, finite_sum, geometric_mean import common_setup from common_setup import IssueConfig, IssueExperiment DIR = os.path.dirname(os.path.abspath(__file__)) BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"] REVISIONS = ["issue732-base", "issue732-v1"] CONFIGS = [ IssueConfig( 'astar-inf', ['--search', 'astar(const(infinity))'], ), IssueConfig( 'astar-blind', ['--search', 'astar(blind())'], ), IssueConfig( 'debug-astar-inf', ['--search', 'astar(const(infinity))'], build_options=["debug32"], driver_options=["--build=debug32"], ), IssueConfig( 'debug-astar-blind', ['--search', 'astar(blind())'], build_options=["debug32"], driver_options=["--build=debug32"], ), ] SUITE = list(sorted(set(common_setup.DEFAULT_OPTIMAL_SUITE) | set(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_resource('sg_parser', 'sg-parser.py', dest='sg-parser.py') exp.add_command('sg-parser', ['{sg_parser}']) attributes = IssueExperiment.DEFAULT_TABLE_ATTRIBUTES + [ Attribute("sg_construction_time", functions=[finite_sum], min_wins=True), Attribute("sg_peak_mem_diff", functions=[finite_sum], min_wins=True), "error", "run_dir", ] exp.add_absolute_report_step(attributes=attributes) exp.run_steps()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue732/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')
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue732/v6-debug.py
#! /usr/bin/env python # -*- coding: utf-8 -*- import os from lab.environments import LocalEnvironment, BaselSlurmEnvironment from lab.reports import Attribute, finite_sum import common_setup from common_setup import IssueConfig, IssueExperiment DIR = os.path.dirname(os.path.abspath(__file__)) BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"] REVISIONS = ["issue732-base", "issue732-v6"] BUILDS = ["debug32", "release32"] CONFIGS = [ IssueConfig( "lama-first-{build}".format(**locals()), [], build_options=[build], driver_options=["--alias", "lama-first", "--build", build]) for build in BUILDS ] SUITE = set( common_setup.DEFAULT_OPTIMAL_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_resource('sg_parser', 'sg-parser.py', dest='sg-parser.py') exp.add_command('sg-parser', ['{sg_parser}']) attributes = IssueExperiment.DEFAULT_TABLE_ATTRIBUTES + [ Attribute("sg_construction_time", functions=[finite_sum], min_wins=True), Attribute("sg_peak_mem_diff", functions=[finite_sum], min_wins=True), ] exp.add_comparison_table_step(attributes=attributes) exp.run_steps()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue535/v7.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 = ["issue535-base", "issue535-v7"] CONFIGS = [ IssueConfig( "lazy-ff-pref-{pref_first}-randomize-{randomize}".format(**locals()), ["--heuristic", "hff=ff()", "--search", "lazy_greedy(hff, preferred_successors_first={pref_first}, randomize_successors={randomize}, preferred=hff)".format(**locals())]) for pref_first in [False, True] for randomize in [False, True] ] 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'] 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(relative=True, attributes=["total_time"]) exp()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue535/v4.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 = ["issue535-v3", "issue535-v4"] CONFIGS = [ IssueConfig( "lazy_greedy_ff", ["--heuristic", "h=ff()", "--search", "lazy_greedy(h, preferred=h)"]) ] 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'] 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(relative=True, attributes=["total_time"]) exp()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue535/v5.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 = ["issue535-base", "issue535-v5"] CONFIGS = [ IssueConfig( "{search}_ff".format(**locals()), ["--heuristic", "h=ff()", "--search", "{search}(h, preferred=h)".format(**locals())]) for search in ["lazy_greedy", "eager_greedy", "ehc"] ] + [ IssueConfig("lama-first", [], driver_options=["--alias", "lama-first"]) ] 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'] 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(relative=True, attributes=["total_time"]) exp()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue535/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))
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue535/v6.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 = ["issue535-base", "issue535-v6"] CONFIGS = [ IssueConfig( "ehc-ff-pref-{heuristic}-{preferred_usage}".format(**locals()), ["--heuristic", "hff=ff()", "--search", "ehc(hff, preferred={heuristic}, preferred_usage={preferred_usage})".format(**locals())]) for preferred_usage in ["RANK_PREFERRED_FIRST", "PRUNE_BY_PREFERRED"] for heuristic in ["add()", "hff"] ] 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'] 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(relative=True, attributes=["total_time"]) exp()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue535/v7-randomized.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 = ["issue535-base", "issue535-v7"] CONFIGS = [ IssueConfig( "lazy-ff-pref-{pref_first}-randomize-{randomize}-seed-{seed}".format(**locals()), ["--heuristic", "hff=ff()", "--random-seed", str(seed), "--search", "lazy_greedy(hff, preferred_successors_first={pref_first}, randomize_successors={randomize}, preferred=hff)".format(**locals())]) for pref_first in [True] for randomize in [True] for seed in [0, 1, 2] ] 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'] 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(relative=True, attributes=["total_time", "evaluations"]) exp()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue535/v1.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 = ["issue535-base", "issue535-v1"] CONFIGS = [ IssueConfig( "lazy_greedy_ff", ["--heuristic", "h=ff()", "--search", "lazy_greedy(h, preferred=h)"]) ] 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'] 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(relative=True, attributes=["total_time"]) exp()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue535/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')
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue535/v3.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 = ["issue535-v2", "issue535-v3"] CONFIGS = [ IssueConfig( "lazy_greedy_ff", ["--heuristic", "h=ff()", "--search", "lazy_greedy(h, preferred=h)"]) ] 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'] 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(relative=True, attributes=["total_time"]) exp()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue535/v2.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 = ["issue535-v1", "issue535-v2"] CONFIGS = [ IssueConfig( "lazy_greedy_ff", ["--heuristic", "h=ff()", "--search", "lazy_greedy(h, preferred=h)"]) ] 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'] 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(relative=True, attributes=["total_time"]) exp()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue555/issue555-v2.py
#! /usr/bin/env python # -*- coding: utf-8 -*- from downward import suites import common_setup REVS = ["issue555-base", "issue555-v2"] LIMITS = {"search_time": 1800} SUITE = suites.suite_optimal_with_ipc11() CONFIGS = { 'astar_h2': [ '--search', 'astar(hm(2))'], } exp = common_setup.IssueExperiment( search_revisions=REVS, configs=CONFIGS, suite=SUITE, limits=LIMITS, ) exp.add_comparison_table_step() exp()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue555/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", "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-%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 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))
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue555/issue555-v1.py
#! /usr/bin/env python # -*- coding: utf-8 -*- from downward import suites import common_setup REVS = ["issue555-base", "issue555-v1"] LIMITS = {"search_time": 1800} SUITE = suites.suite_optimal_with_ipc11() CONFIGS = { 'astar_h2': [ '--search', 'astar(hm(2))'], } exp = common_setup.IssueExperiment( search_revisions=REVS, configs=CONFIGS, suite=SUITE, limits=LIMITS, ) exp.add_comparison_table_step() exp()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue748/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 = ["issue748-base", "issue748-v1"] CONFIGS = [ IssueConfig('astar-blind', ['--search', 'astar(blind())']), IssueConfig('astar-lmcut', ['--search', 'astar(lmcut())']), ] SUITE = common_setup.DEFAULT_OPTIMAL_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 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()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue748/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)
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue748/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 = ["issue748-base", "issue748-v1"] CONFIGS = [ IssueConfig('lazy-greedy-blind', ['--search', 'lazy_greedy([blind()])']), IssueConfig('lama-first', [], driver_options=["--alias", "lama-first"]), IssueConfig('lwastar-ff', ["--heuristic", "h=ff()", "--search", "lazy_wastar([h],preferred=[h],w=5)"]), IssueConfig("ehc-ff", ["--search", "ehc(ff())"]), ] 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 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()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue748/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')
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makolon/hsr_isaac_tamp/hsr_tamp/downward/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))
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makolon/hsr_isaac_tamp/hsr_tamp/downward/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()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/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()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue585/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 = [] # TODO: this method adds all search parsers. See next method. def _add_runs(self): FastDownwardExperiment._add_runs(self) for run in self.runs: for parser in self.search_parsers: run.add_command(parser, [parser]) # TODO: copied adapted from downward/experiment. This method should # be removed when FastDownwardExperiment supports adding search parsers. def add_search_parser(self, path_to_parser): """ Invoke script at *path_to_parser* at the end of each search run. :: exp.add_search_parser('path/to/parser') """ if not os.path.isfile(path_to_parser): logging.critical('Parser %s could not be found.' % path_to_parser) if not os.access(path_to_parser, os.X_OK): logging.critical('Parser %s is not executable.' % path_to_parser) search_parser = 'search_parser%d' % len(self.search_parsers) self.add_resource(search_parser, path_to_parser) self.search_parsers.append(search_parser) 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 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: test this! 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_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))
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue585/v3-new-configs.py
#! /usr/bin/env python # -*- coding: utf-8 -*- from downward import suites from downward.experiment import FastDownwardExperiment from downward.reports.compare import CompareConfigsReport import common_setup REPO = common_setup.get_repo_base() REV_BASE = 'issue585-base' REV_V3 = 'issue585-v3' SUITE = suites.suite_optimal_with_ipc11() ALGORITHMS = { 'astar_cpdbs_genetic': (REV_V3, ['--search', 'astar(cpdbs(patterns=genetic()))']), 'astar_zopdbs_systematic': (REV_V3, ['--search', 'astar(zopdbs(patterns=systematic()))']), 'astar_zopdbs_hillclimbing': (REV_V3, ['--search', 'astar(zopdbs(patterns=hillclimbing()))']), 'astar_pho_genetic': (REV_V3, ['--search', 'astar(operatorcounting([pho_constraints(patterns=genetic())]))']), 'astar_pho_combo': (REV_V3, ['--search', 'astar(operatorcounting([pho_constraints(patterns=combo())]))']), } exp = common_setup.IssueExperiment( revisions=[], configs={}, suite=SUITE, ) for nick, (rev, cmd) in ALGORITHMS.items(): exp.add_algorithm(nick, REPO, rev, cmd) exp.add_absolute_report_step() exp()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue585/v1.py
#! /usr/bin/env python # -*- coding: utf-8 -*- from downward import suites from downward.experiment import FastDownwardExperiment from downward.reports.compare import CompareConfigsReport import common_setup REPO = common_setup.get_repo_base() REV_BASE = 'issue585-base' REV_V1 = 'issue585-v1' SUITE = ['gripper:prob01.pddl'] # suites.suite_optimal_with_ipc11() ALGORITHMS = { 'astar_pdb_base': (REV_BASE, ['--search', 'astar(pdb())']), 'astar_pdb_v1': (REV_V1, ['--search', 'astar(pdb())']), 'astar_cpdbs_base': (REV_BASE, ['--search', 'astar(cpdbs())']), 'astar_cpdbs_v1': (REV_V1, ['--search', 'astar(cpdbs())']), 'astar_cpdbs_systematic_base': (REV_BASE, ['--search', 'astar(cpdbs_systematic())']), 'astar_cpdbs_systematic_v1': (REV_V1, ['--search', 'astar(cpdbs(patterns=systematic()))']), 'astar_zopdbs_base': (REV_BASE, ['--search', 'astar(zopdbs())']), 'astar_zopdbs_v1': (REV_V1, ['--search', 'astar(zopdbs())']), 'astar_ipdb_base': (REV_BASE, ['--search', 'astar(ipdb())']), 'astar_ipdb_v1': (REV_V1, ['--search', 'astar(ipdb())']), 'astar_ipdb_alias': (REV_V1, ['--search', 'astar(cpdbs(patterns=hillclimbing()))']), 'astar_gapdb_base': (REV_BASE, ['--search', 'astar(gapdb())']), 'astar_gapdb_v1': (REV_V1, ['--search', 'astar(zopdbs(patterns=genetic()))']), 'astar_pho_systematic_base': (REV_BASE, ['--search', 'astar(operatorcounting([pho_constraints_systematic()]))']), 'astar_pho_systematic_v1': (REV_V1, ['--search', 'astar(operatorcounting([pho_constraints(patterns=systematic())]))']), 'astar_pho_hillclimbing_base': (REV_BASE, ['--search', 'astar(operatorcounting([pho_constraints_ipdb()]))']), 'astar_pho_hillclimbing_v1': (REV_V1, ['--search', 'astar(operatorcounting([pho_constraints(patterns=hillclimbing())]))']), } COMPARED_ALGORITHMS = [ ('astar_pdb_base', 'astar_pdb_v1', 'Diff (pdb)'), ('astar_cpdbs_base', 'astar_cpdbs_v1', 'Diff (cpdbs)'), ('astar_cpdbs_systematic_base', 'astar_cpdbs_systematic_v1', 'Diff (cpdbs_systematic)'), ('astar_zopdbs_base', 'astar_zopdbs_v1', 'Diff (zopdbs)'), ('astar_ipdb_base', 'astar_ipdb_v1', 'Diff (ipdb)'), ('astar_ipdb_v1', 'astar_ipdb_alias', 'Diff (ipdb_alias)'), ('astar_gapdb_base', 'astar_gapdb_v1', 'Diff (gapdb)'), ('astar_pho_systematic_base', 'astar_pho_systematic_v1', 'Diff (pho_systematic)'), ('astar_pho_hillclimbing_base', 'astar_pho_hillclimbing_v1', 'Diff (pho_hillclimbing)'), ] exp = common_setup.IssueExperiment( revisions=[], configs={}, suite=SUITE, ) for nick, (rev, cmd) in ALGORITHMS.items(): exp.add_algorithm(nick, REPO, rev, cmd) exp.add_report(CompareConfigsReport( COMPARED_ALGORITHMS, attributes=common_setup.IssueExperiment.DEFAULT_TABLE_ATTRIBUTES )) exp()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue585/v3-rest.py
#! /usr/bin/env python # -*- coding: utf-8 -*- from downward import suites from downward.experiment import FastDownwardExperiment from downward.reports.compare import CompareConfigsReport from relativescatter import RelativeScatterPlotReport import common_setup REPO = common_setup.get_repo_base() REV_BASE = 'issue585-base' REV_V3 = 'issue585-v3' SUITE = suites.suite_optimal_with_ipc11() ALGORITHMS = { 'astar_pdb_base': (REV_BASE, ['--search', 'astar(pdb())']), 'astar_pdb_v3': (REV_V3, ['--search', 'astar(pdb())']), 'astar_cpdbs_base': (REV_BASE, ['--search', 'astar(cpdbs())']), 'astar_cpdbs_v3': (REV_V3, ['--search', 'astar(cpdbs())']), 'astar_cpdbs_systematic_base': (REV_BASE, ['--search', 'astar(cpdbs_systematic())']), 'astar_cpdbs_systematic_v3': (REV_V3, ['--search', 'astar(cpdbs(patterns=systematic()))']), 'astar_zopdbs_base': (REV_BASE, ['--search', 'astar(zopdbs())']), 'astar_zopdbs_v3': (REV_V3, ['--search', 'astar(zopdbs())']), 'astar_pho_systematic_base': (REV_BASE, ['--search', 'astar(operatorcounting([pho_constraints_systematic()]))']), 'astar_pho_systematic_v3': (REV_V3, ['--search', 'astar(operatorcounting([pho_constraints(patterns=systematic())]))']), } COMPARED_ALGORITHMS = [ ('astar_pdb_base', 'astar_pdb_v3', 'Diff (pdb)'), ('astar_cpdbs_base', 'astar_cpdbs_v3', 'Diff (cpdbs)'), ('astar_cpdbs_systematic_base', 'astar_cpdbs_systematic_v3', 'Diff (cpdbs_systematic)'), ('astar_zopdbs_base', 'astar_zopdbs_v3', 'Diff (zopdbs)'), ('astar_pho_systematic_base', 'astar_pho_systematic_v3', 'Diff (pho_systematic)'), ] exp = common_setup.IssueExperiment( revisions=[], configs={}, suite=SUITE, ) for nick, (rev, cmd) in ALGORITHMS.items(): exp.add_algorithm(nick, REPO, rev, cmd) exp.add_report(CompareConfigsReport( COMPARED_ALGORITHMS, attributes=common_setup.IssueExperiment.DEFAULT_TABLE_ATTRIBUTES )) for c1, c2, _ in COMPARED_ALGORITHMS: exp.add_report( RelativeScatterPlotReport( attributes=["total_time"], filter_config=[c1, c2], get_category=lambda run1, run2: run1.get("domain"), ), outfile='issue585_%s_v3_total_time.png' % c1 ) exp()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue585/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')
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue585/v3.py
#! /usr/bin/env python # -*- coding: utf-8 -*- from downward import suites from downward.experiment import FastDownwardExperiment from downward.reports.compare import CompareConfigsReport from relativescatter import RelativeScatterPlotReport import common_setup REPO = common_setup.get_repo_base() REV_BASE = 'issue585-base' REV_V1 = 'issue585-v3' SUITE = suites.suite_optimal_with_ipc11() ALGORITHMS = { 'astar_ipdb_base': (REV_BASE, ['--search', 'astar(ipdb())']), 'astar_ipdb_v3': (REV_V1, ['--search', 'astar(ipdb())']), 'astar_gapdb_base': (REV_BASE, ['--search', 'astar(gapdb())']), 'astar_gapdb_v3': (REV_V1, ['--search', 'astar(zopdbs(patterns=genetic()))']), } COMPARED_ALGORITHMS = [ ('astar_ipdb_base', 'astar_ipdb_v3', 'Diff (ipdb)'), ('astar_gapdb_base', 'astar_gapdb_v3', 'Diff (gapdb)'), ] exp = common_setup.IssueExperiment( revisions=[], configs={}, suite=SUITE, ) for nick, (rev, cmd) in ALGORITHMS.items(): exp.add_algorithm(nick, REPO, rev, cmd) exp.add_report(CompareConfigsReport( COMPARED_ALGORITHMS, attributes=common_setup.IssueExperiment.DEFAULT_TABLE_ATTRIBUTES )) exp.add_report( RelativeScatterPlotReport( attributes=["total_time"], filter_config=["astar_ipdb_base", "astar_ipdb_v3"], get_category=lambda run1, run2: run1.get("domain"), ), outfile='issue585_ipdb_base_v3_total_time.png' ) exp.add_report( RelativeScatterPlotReport( attributes=["total_time"], filter_config=["astar_gapdb_base", "astar_gapdb_v3"], get_category=lambda run1, run2: run1.get("domain"), ), outfile='issue585_gapdb_base_v3_total_time.png' ) exp()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue585/v2.py
#! /usr/bin/env python # -*- coding: utf-8 -*- from downward import suites from downward.experiment import FastDownwardExperiment from downward.reports.compare import CompareConfigsReport import common_setup REPO = common_setup.get_repo_base() REV_BASE = 'issue585-base' REV_V1 = 'issue585-v2' SUITE = suites.suite_optimal_with_ipc11() ALGORITHMS = { 'astar_ipdb_base': (REV_BASE, ['--search', 'astar(ipdb())']), 'astar_ipdb_v2': (REV_V1, ['--search', 'astar(ipdb())']), } COMPARED_ALGORITHMS = [ ('astar_ipdb_base', 'astar_ipdb_v2', 'Diff (ipdb)'), ] exp = common_setup.IssueExperiment( revisions=[], configs={}, suite=SUITE, ) for nick, (rev, cmd) in ALGORITHMS.items(): exp.add_algorithm(nick, REPO, rev, cmd) exp.add_report(CompareConfigsReport( COMPARED_ALGORITHMS, attributes=common_setup.IssueExperiment.DEFAULT_TABLE_ATTRIBUTES )) exp()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue726/v1-opt.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 from relativescatter import RelativeScatterPlotReport DIR = os.path.dirname(os.path.abspath(__file__)) BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"] REVISIONS = ["issue726-base", "issue726-v1"] CONFIGS = [ IssueConfig("blind", ["--search", "astar(blind())"]), IssueConfig("lmcut", ["--search", "astar(lmcut())"]), ] 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_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", "lmcut"]: exp.add_report(RelativeScatterPlotReport( attributes=[attr], filter_algorithm=["issue726-%s-%s" % (rev1, config_nick), "issue726-%s-%s" % (rev2, config_nick)], get_category=lambda r1, r2: r1["domain"], ), outfile="issue726-%s-%s-%s-%s.png" % (config_nick, attr, rev1, rev2)) exp.run_steps()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue726/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)
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue726/v1-sat.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 from relativescatter import RelativeScatterPlotReport DIR = os.path.dirname(os.path.abspath(__file__)) BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"] REVISIONS = ["issue726-base", "issue726-v1"] CONFIGS = [ IssueConfig( "lama-first", [], driver_options=["--alias", "lama-first"]), IssueConfig( "lama", [], driver_options=["--alias", "seq-sat-lama-2011"]), IssueConfig("ehc_ff", ["--heuristic", "h=ff()", "--search", "ehc(h, preferred=h)"]), ] 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() exp.add_comparison_table_step() for attr in ["total_time", "search_time", "memory"]: for rev1, rev2 in [("base", "v1")]: for config_nick in ["lama-first", "ehc_ff"]: exp.add_report(RelativeScatterPlotReport( attributes=[attr], filter_algorithm=["issue726-%s-%s" % (rev1, config_nick), "issue726-%s-%s" % (rev2, config_nick)], get_category=lambda r1, r2: r1["domain"], ), outfile="issue726-%s-%s-%s-%s.png" % (config_nick, attr, rev1, rev2)) exp.run_steps()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue726/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')
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makolon/hsr_isaac_tamp/hsr_tamp/downward/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)
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makolon/hsr_isaac_tamp/hsr_tamp/downward/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()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/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()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/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()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/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')
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue803/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", "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)
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue803/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 = ["issue803-base", "issue803-v1"] if common_setup.is_test_run(): BUILDS = ["release32"] else: BUILDS = ["debug32", "release32", "debug64", "release64"] CONFIGS = [ IssueConfig( build + "-blind", ["--search", "astar(blind())"], build_options=[build], driver_options=["--build", build, "--overall-time-limit", "5m"]) for build in BUILDS ] 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_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() 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()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue803/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')
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makolon/hsr_isaac_tamp/hsr_tamp/downward/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()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/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)
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makolon/hsr_isaac_tamp/hsr_tamp/downward/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()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/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()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/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')
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makolon/hsr_isaac_tamp/hsr_tamp/downward/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()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue386/common_setup.py
# -*- coding: utf-8 -*- import os.path from lab.environments import MaiaEnvironment from lab.steps import Step from downward.checkouts import Translator, Preprocessor, Planner from downward.experiments import DownwardExperiment from downward.reports.compare import CompareRevisionsReport from downward.reports.scatter import ScatterPlotReport 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 filename of the main script, e.g. "/ham/spam/eggs.py" => "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. Found by searching upwards in the directory tree from the main script until a directory with a subdirectory named ".hg" is found.""" path = os.path.abspath(get_script_dir()) while True: if os.path.exists(os.path.join(path, ".hg")): return path path = os.path.dirname(path) class MyExperiment(DownwardExperiment): 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 = [ "total_time", "search_time", "memory", "expansions_until_last_jump", ] """Wrapper for DownwardExperiment with a few convenience features.""" def __init__(self, configs=None, grid_priority=None, path=None, repo=None, revisions=None, search_revisions=None, suite=None, **kwargs): """Create a DownwardExperiment with some convenience features. If "configs" is specified, it should be a dict of {nick: cmdline} pairs that sets the planner configurations to test. If "grid_priority" is specified and no environment is specifically requested in **kwargs, use the maia environment with the specified priority. If "path" is not specified, the experiment data path is derived automatically from the main script's filename. If "repo" is not specified, the repository base is derived automatically from the main script's path. 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. 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 experiments use the translator and preprocessor component of the first revision. If "suite" is specified, it should specify a problem suite. Options "combinations" (from the base class), "revisions" and "search_revisions" are mutually exclusive.""" if grid_priority is not None and "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() num_rev_opts_specified = ( int(revisions is not None) + int(search_revisions is not None) + int(kwargs.get("combinations") is not None)) if num_rev_opts_specified > 1: raise ValueError('must specify exactly one of "revisions", ' '"search_revisions" or "combinations"') # See add_comparison_table_step for more on this variable. self._HACK_revisions = revisions if revisions is not None: if not revisions: raise ValueError("revisions cannot be empty") combinations = [(Translator(repo, rev), Preprocessor(repo, rev), Planner(repo, rev)) for rev in revisions] kwargs["combinations"] = combinations if search_revisions is not None: if not search_revisions: raise ValueError("search_revisions cannot be empty") base_rev = search_revisions[0] translator = Translator(repo, base_rev) preprocessor = Preprocessor(repo, base_rev) combinations = [(translator, preprocessor, Planner(repo, rev)) for rev in search_revisions] kwargs["combinations"] = combinations DownwardExperiment.__init__(self, path=path, repo=repo, **kwargs) if configs is not None: for nick, config in configs.items(): self.add_config(nick, config) if suite is not None: self.add_suite(suite) self._report_prefix = get_experiment_name() def add_comparison_table_step(self, attributes=None): revisions = self._HACK_revisions if revisions is None: # TODO: It's not clear to me what a "revision" in the # overall context of the code really is, e.g. when keeping # the translator and preprocessor method fixed and only # changing the search component. It's also not really # clear to me how the interface of the Compare... reports # works and how to use it more generally. Hence the # present hack. # Ideally, this method should look at the table columns we # have (defined by planners and planner configurations), # pair them up in a suitable way, either controlled by a # convenience parameter or a more general grouping method, # and then use this to define which pairs go together. raise NotImplementedError( "only supported when specifying revisions in __init__") if attributes is None: attributes = self.DEFAULT_TABLE_ATTRIBUTES if len(revisions) == 2: report = CompareRevisionsReport(*revisions, attributes=attributes) self.add_report(report, outfile="%s-compare.html" % self._report_prefix) else: # HACK: assumes the first revision is the noe everything else is compared against for rev in revisions[1:]: report = CompareRevisionsReport(revisions[0], rev, attributes=attributes) self.add_report(report, outfile="%s-compare-%s.html" % (self._report_prefix, rev)) def add_scatter_plot_step(self, attributes=None): if attributes is None: attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES revisions = self._HACK_revisions if revisions is None: # TODO: See add_comparison_table_step. raise NotImplementedError( "only supported when specifying revisions in __init__") # HACK: assumes the first revision is the noe everything else is compared against for rev in revisions[1:]: # TODO: Should generalize this, too, by offering a general # grouping function and then comparing any pair of # settings in the same group. scatter_dir = os.path.join(self.eval_dir, "scatter") def make_scatter_plots(): configs = [conf[0] for conf in self.configs] for nick in configs: config_before = "%s-%s" % (revisions[0], nick) config_after = "%s-%s" % (rev, nick) for attribute in attributes: name = "%s-%s-%s" % (self._report_prefix, attribute, nick) report = ScatterPlotReport( filter_config=[config_before, config_after], attributes=[attribute], get_category=lambda run1, run2: run1["domain"], legend_location=(1.3, 0.5)) report(self.eval_dir, os.path.join(scatter_dir, rev, name)) self.add_step(Step("make-scatter-plots", make_scatter_plots))
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue386/exp3.py
#! /usr/bin/env python # -*- coding: utf-8 -*- from downward.suites import suite_optimal_with_ipc11 from downward.configs import default_configs_optimal import common_setup REVS = ["issue386-base", "issue386-v3"] CONFIGS = default_configs_optimal() # remove config that is disabled in this branch del CONFIGS['astar_selmax_lmcut_lmcount'] TEST_RUN = True if TEST_RUN: SUITE = "gripper:prob01.pddl" PRIORITY = None # "None" means local experiment else: SUITE = suite_optimal_with_ipc11() PRIORITY = 0 # number means maia experiment # TODO: I'd like to specify "search_revisions" (which uses the same # translator and preprocessor for everything) instead of "revisions" # here, but I can't seem to make this work with the REVS argument for # CompareRevisionsReport. exp = common_setup.MyExperiment( grid_priority=PRIORITY, revisions=REVS, configs=CONFIGS, suite=SUITE ) exp.add_comparison_table_step() exp.add_scatter_plot_step() exp()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue386/exp2.py
#! /usr/bin/env python # -*- coding: utf-8 -*- from downward.suites import suite_optimal_with_ipc11 from downward.configs import default_configs_optimal import common_setup REVS = ["issue386-base", "issue386-v2"] CONFIGS = default_configs_optimal() # remove config that is disabled in this branch del CONFIGS['astar_selmax_lmcut_lmcount'] TEST_RUN = True if TEST_RUN: SUITE = "gripper:prob01.pddl" PRIORITY = None # "None" means local experiment else: SUITE = suite_optimal_with_ipc11() PRIORITY = 0 # number means maia experiment # TODO: I'd like to specify "search_revisions" (which uses the same # translator and preprocessor for everything) instead of "revisions" # here, but I can't seem to make this work with the REVS argument for # CompareRevisionsReport. exp = common_setup.MyExperiment( grid_priority=PRIORITY, revisions=REVS, configs=CONFIGS, suite=SUITE ) exp.add_comparison_table_step() exp.add_scatter_plot_step() exp()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue386/exp1.py
#! /usr/bin/env python # -*- coding: utf-8 -*- from downward.suites import suite_optimal_with_ipc11 from downward.configs import default_configs_optimal import common_setup REVS = ["issue386-base", "issue386-v1"] CONFIGS = {'astar_ipdb': ['--search', 'astar(ipdb)']} # default_configs_optimal() TEST_RUN = True if TEST_RUN: SUITE = "gripper:prob01.pddl" PRIORITY = None # "None" means local experiment else: SUITE = suite_optimal_with_ipc11() PRIORITY = 0 # number means maia experiment # TODO: I'd like to specify "search_revisions" (which uses the same # translator and preprocessor for everything) instead of "revisions" # here, but I can't seem to make this work with the REVS argument for # CompareRevisionsReport. exp = common_setup.MyExperiment( grid_priority=PRIORITY, revisions=REVS, configs=CONFIGS, suite=SUITE ) exp.add_comparison_table_step() exp.add_scatter_plot_step() exp()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/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()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/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))
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makolon/hsr_isaac_tamp/hsr_tamp/downward/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()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/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')
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue682/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): """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, benchmarks_dir, suite, revisions=[], configs={}, grid_priority=None, path=None, test_suite=None, email=None, processes=None, **kwargs): """ 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(benchmarks_dir, 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))
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue682/suites.py
#! /usr/bin/env python # -*- coding: utf-8 -*- import argparse import textwrap HELP = "Convert suite name to list of domains or tasks." def suite_alternative_formulations(): return ['airport-adl', 'no-mprime', 'no-mystery'] def suite_ipc98_to_ipc04_adl(): return [ 'assembly', 'miconic-fulladl', 'miconic-simpleadl', 'optical-telegraphs', 'philosophers', 'psr-large', 'psr-middle', 'schedule', ] def suite_ipc98_to_ipc04_strips(): return [ 'airport', 'blocks', 'depot', 'driverlog', 'freecell', 'grid', 'gripper', 'logistics00', 'logistics98', 'miconic', 'movie', 'mprime', 'mystery', 'pipesworld-notankage', 'psr-small', 'satellite', 'zenotravel', ] def suite_ipc98_to_ipc04(): # All IPC1-4 domains, including the trivial Movie. return sorted(suite_ipc98_to_ipc04_adl() + suite_ipc98_to_ipc04_strips()) def suite_ipc06_adl(): return [ 'openstacks', 'pathways', 'trucks', ] def suite_ipc06_strips_compilations(): return [ 'openstacks-strips', 'pathways-noneg', 'trucks-strips', ] def suite_ipc06_strips(): return [ 'pipesworld-tankage', 'rovers', 'storage', 'tpp', ] def suite_ipc06(): return sorted(suite_ipc06_adl() + suite_ipc06_strips()) def suite_ipc08_common_strips(): return [ 'parcprinter-08-strips', 'pegsol-08-strips', 'scanalyzer-08-strips', ] def suite_ipc08_opt_adl(): return ['openstacks-opt08-adl'] def suite_ipc08_opt_strips(): return sorted(suite_ipc08_common_strips() + [ 'elevators-opt08-strips', 'openstacks-opt08-strips', 'sokoban-opt08-strips', 'transport-opt08-strips', 'woodworking-opt08-strips', ]) def suite_ipc08_opt(): return sorted(suite_ipc08_opt_strips() + suite_ipc08_opt_adl()) def suite_ipc08_sat_adl(): return ['openstacks-sat08-adl'] def suite_ipc08_sat_strips(): return sorted(suite_ipc08_common_strips() + [ # Note: cyber-security is missing. 'elevators-sat08-strips', 'openstacks-sat08-strips', 'sokoban-sat08-strips', 'transport-sat08-strips', 'woodworking-sat08-strips', ]) def suite_ipc08_sat(): return sorted(suite_ipc08_sat_strips() + suite_ipc08_sat_adl()) def suite_ipc08(): return sorted(set(suite_ipc08_opt() + suite_ipc08_sat())) def suite_ipc11_opt(): return [ 'barman-opt11-strips', 'elevators-opt11-strips', 'floortile-opt11-strips', 'nomystery-opt11-strips', 'openstacks-opt11-strips', 'parcprinter-opt11-strips', 'parking-opt11-strips', 'pegsol-opt11-strips', 'scanalyzer-opt11-strips', 'sokoban-opt11-strips', 'tidybot-opt11-strips', 'transport-opt11-strips', 'visitall-opt11-strips', 'woodworking-opt11-strips', ] def suite_ipc11_sat(): return [ 'barman-sat11-strips', 'elevators-sat11-strips', 'floortile-sat11-strips', 'nomystery-sat11-strips', 'openstacks-sat11-strips', 'parcprinter-sat11-strips', 'parking-sat11-strips', 'pegsol-sat11-strips', 'scanalyzer-sat11-strips', 'sokoban-sat11-strips', 'tidybot-sat11-strips', 'transport-sat11-strips', 'visitall-sat11-strips', 'woodworking-sat11-strips', ] def suite_ipc11(): return sorted(suite_ipc11_opt() + suite_ipc11_sat()) def suite_ipc14_agl_adl(): return [ 'cavediving-14-adl', 'citycar-sat14-adl', 'maintenance-sat14-adl', ] def suite_ipc14_agl_strips(): return [ 'barman-sat14-strips', 'childsnack-sat14-strips', 'floortile-sat14-strips', 'ged-sat14-strips', 'hiking-agl14-strips', 'openstacks-agl14-strips', 'parking-sat14-strips', 'tetris-sat14-strips', 'thoughtful-sat14-strips', 'transport-sat14-strips', 'visitall-sat14-strips', ] def suite_ipc14_agl(): return sorted(suite_ipc14_agl_adl() + suite_ipc14_agl_strips()) def suite_ipc14_mco_adl(): return [ 'cavediving-14-adl', 'citycar-sat14-adl', 'maintenance-sat14-adl', ] def suite_ipc14_mco_strips(): return [ 'barman-mco14-strips', 'childsnack-sat14-strips', 'floortile-sat14-strips', 'ged-sat14-strips', 'hiking-sat14-strips', 'openstacks-sat14-strips', 'parking-sat14-strips', 'tetris-sat14-strips', 'thoughtful-mco14-strips', 'transport-sat14-strips', 'visitall-sat14-strips', ] def suite_ipc14_mco(): return sorted(suite_ipc14_mco_adl() + suite_ipc14_mco_strips()) def suite_ipc14_opt_adl(): return [ 'cavediving-14-adl', 'citycar-opt14-adl', 'maintenance-opt14-adl', ] def suite_ipc14_opt_strips(): return [ 'barman-opt14-strips', 'childsnack-opt14-strips', 'floortile-opt14-strips', 'ged-opt14-strips', 'hiking-opt14-strips', 'openstacks-opt14-strips', 'parking-opt14-strips', 'tetris-opt14-strips', 'tidybot-opt14-strips', 'transport-opt14-strips', 'visitall-opt14-strips', ] def suite_ipc14_opt(): return sorted(suite_ipc14_opt_adl() + suite_ipc14_opt_strips()) def suite_ipc14_sat_adl(): return [ 'cavediving-14-adl', 'citycar-sat14-adl', 'maintenance-sat14-adl', ] def suite_ipc14_sat_strips(): return [ 'barman-sat14-strips', 'childsnack-sat14-strips', 'floortile-sat14-strips', 'ged-sat14-strips', 'hiking-sat14-strips', 'openstacks-sat14-strips', 'parking-sat14-strips', 'tetris-sat14-strips', 'thoughtful-sat14-strips', 'transport-sat14-strips', 'visitall-sat14-strips', ] def suite_ipc14_sat(): return sorted(suite_ipc14_sat_adl() + suite_ipc14_sat_strips()) def suite_ipc14(): return sorted(set( suite_ipc14_agl() + suite_ipc14_mco() + suite_ipc14_opt() + suite_ipc14_sat())) def suite_unsolvable(): return sorted( ['mystery:prob%02d.pddl' % index for index in [4, 5, 7, 8, 12, 16, 18, 21, 22, 23, 24]] + ['miconic-fulladl:f21-3.pddl', 'miconic-fulladl:f30-2.pddl']) def suite_optimal_adl(): return sorted( suite_ipc98_to_ipc04_adl() + suite_ipc06_adl() + suite_ipc08_opt_adl() + suite_ipc14_opt_adl()) def suite_optimal_strips(): return sorted( suite_ipc98_to_ipc04_strips() + suite_ipc06_strips() + suite_ipc06_strips_compilations() + suite_ipc08_opt_strips() + suite_ipc11_opt() + suite_ipc14_opt_strips()) def suite_optimal(): return sorted(suite_optimal_adl() + suite_optimal_strips()) def suite_satisficing_adl(): return sorted( suite_ipc98_to_ipc04_adl() + suite_ipc06_adl() + suite_ipc08_sat_adl() + suite_ipc14_sat_adl()) def suite_satisficing_strips(): return sorted( suite_ipc98_to_ipc04_strips() + suite_ipc06_strips() + suite_ipc06_strips_compilations() + suite_ipc08_sat_strips() + suite_ipc11_sat() + suite_ipc14_sat_strips()) def suite_satisficing(): return sorted(suite_satisficing_adl() + suite_satisficing_strips()) def suite_all(): return sorted( suite_ipc98_to_ipc04() + suite_ipc06() + suite_ipc06_strips_compilations() + suite_ipc08() + suite_ipc11() + suite_ipc14() + suite_alternative_formulations()) def parse_args(): parser = argparse.ArgumentParser() parser.add_argument("suite", help="suite name") return parser.parse_args() def main(): prefix = "suite_" suite_names = [ name[len(prefix):] for name in sorted(globals().keys()) if name.startswith(prefix)] parser = argparse.ArgumentParser(description=HELP) parser.add_argument("suite", choices=suite_names, help="suite name") parser.add_argument( "--width", default=72, type=int, help="output line width (default: %(default)s). Use 1 for single " "column.") args = parser.parse_args() suite_func = globals()[prefix + args.suite] print(textwrap.fill( str(suite_func()), width=args.width, break_long_words=False, break_on_hyphens=False)) if __name__ == "__main__": main()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue682/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) parser.add_pattern('actual_search_time', 'Actual search time: (.+)s \[t=.+s\]', required=False, type=float) 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) def check_proved_unsolvability(content, props): proved_unsolvability = False if props['coverage'] == 0: for line in content.splitlines(): if line == 'Completely explored state space -- no solution!': proved_unsolvability = True break props['proved_unsolvability'] = proved_unsolvability parser.add_function(check_proved_unsolvability) parser.parse()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue682/v1.py
#! /usr/bin/env python # -*- coding: utf-8 -*- import os import suites from lab.reports import Attribute, gm from common_setup import IssueConfig, IssueExperiment try: from relativescatter import RelativeScatterPlotReport matplotlib = True except ImportError: print 'matplotlib not availabe, scatter plots not available' matplotlib = False def main(revisions=None): benchmarks_dir=os.path.expanduser('~/repos/downward/benchmarks') suite=suites.suite_optimal_strips() configs = { 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('cggl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=cg_goal_level)),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']), 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-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('cggl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=cg_goal_level)),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,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-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('cggl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_precomputed(merge_tree=linear(variable_order=cg_goal_level)),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000))']), 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))']), } exp = IssueExperiment( benchmarks_dir=benchmarks_dir, suite=suite, revisions=revisions, configs=configs, test_suite=['depot:p01.pddl'], processes=4, email='[email protected]', ) exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py') exp.add_command('ms-parser', ['ms_parser']) # planner outcome attributes perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False) proved_unsolvability = Attribute('proved_unsolvability', absolute=True, min_wins=False) actual_search_time = Attribute('actual_search_time', absolute=False, min_wins=True, functions=[gm]) # m&s attributes ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[gm]) ms_atomic_construction_time = Attribute('ms_atomic_construction_time', absolute=False, min_wins=True, functions=[gm]) 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, proved_unsolvability, actual_search_time, 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() #if matplotlib: #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() main(revisions=['issue682-base', 'issue682-v1'])
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue682/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')
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue786/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", "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)
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue786/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 = ["issue786-base", "issue786-v1"] DRIVER_OPTIONS = ["--overall-time-limit", "5m"] CONFIGS = [ IssueConfig( "cegar", ["--search", "astar(cegar())"], driver_options=DRIVER_OPTIONS), IssueConfig( "ipdb", ["--search", "astar(ipdb())"], driver_options=DRIVER_OPTIONS) ] 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_absolute_report_step() exp.add_comparison_table_step() 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()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue786/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')
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue786/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 = ["issue786-v3-base", "issue786-v3"] DRIVER_OPTIONS = ["--overall-time-limit", "5m"] CONFIGS = [ IssueConfig( "diverse-potentials", ["--search", "astar(diverse_potentials())"], driver_options=DRIVER_OPTIONS), IssueConfig( "cegar", ["--search", "astar(cegar())"], driver_options=DRIVER_OPTIONS), IssueConfig( "ipdb", ["--search", "astar(ipdb())"], driver_options=DRIVER_OPTIONS) ] 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_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() 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()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue786/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 = ["issue786-v2-base", "issue786-v2"] DRIVER_OPTIONS = ["--overall-time-limit", "5m"] CONFIGS = [ IssueConfig( "diverse-potentials", ["--search", "astar(diverse_potentials())"], driver_options=DRIVER_OPTIONS), IssueConfig( "sample-potentials", ["--search", "astar(sample_based_potentials())"], driver_options=DRIVER_OPTIONS), IssueConfig( "ipdb", ["--search", "astar(ipdb())"], driver_options=DRIVER_OPTIONS) ] 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_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() 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()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue707/v4.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-v4"] 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()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/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()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/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()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue707/v2-compare.py
#! /usr/bin/env python # -*- coding: utf-8 -*- #! /usr/bin/env python # -*- coding: utf-8 -*- import os import subprocess from lab.environments import LocalEnvironment, MaiaEnvironment from lab.reports import Attribute, geometric_mean from downward.reports.compare import ComparativeReport from common_setup import IssueConfig, IssueExperiment, DEFAULT_OPTIMAL_SUITE, is_test_run BENCHMARKS_DIR=os.path.expanduser('~/repos/downward/benchmarks') REVISIONS = [] CONFIGS = [] 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_fetcher('data/issue707-v1-eval') exp.add_fetcher('data/issue707-v2-pruning-variants-eval') outfile = os.path.join( exp.eval_dir, "issue707-v1-v2-dfp-compare.html") exp.add_report(ComparativeReport(algorithm_pairs=[ ('%s-dfp-b50k' % 'issue707-v1', '%s-dfp-b50k-nopruneunreachable' % 'issue707-v2'), ('%s-dfp-b50k' % 'issue707-v1', '%s-dfp-b50k-nopruneirrelevant' % 'issue707-v2'), ('%s-dfp-b50k' % 'issue707-v1', '%s-dfp-b50k-noprune' % 'issue707-v2'), #('%s-dfp-f50k' % 'issue707-v1', '%s-dfp-f50k-nopruneunreachable' % 'issue707-v2'), #('%s-dfp-f50k' % 'issue707-v1', '%s-dfp-f50k-nopruneirrelevant' % 'issue707-v2'), #('%s-dfp-f50k' % 'issue707-v1', '%s-dfp-f50k-noprune' % 'issue707-v2'), #('%s-dfp-ginf' % 'issue707-v1', '%s-dfp-ginf-nopruneunreachable' % 'issue707-v2'), #('%s-dfp-ginf' % 'issue707-v1', '%s-dfp-ginf-nopruneirrelevant' % 'issue707-v2'), #('%s-dfp-ginf' % 'issue707-v1', '%s-dfp-ginf-noprune' % 'issue707-v2'), ],attributes=attributes),outfile=outfile) exp.add_step('publish-issue707-v1-v2-dfp-compare.html', subprocess.call, ['publish', outfile]) exp.run_steps()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/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)
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makolon/hsr_isaac_tamp/hsr_tamp/downward/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()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue707/v1.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", "issue707-v1"] CONFIGS = [ 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('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-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('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-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('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))']), ] 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()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/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')
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makolon/hsr_isaac_tamp/hsr_tamp/downward/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()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue604/v7.py
#! /usr/bin/env python # -*- coding: utf-8 -*- from downward import suites from lab.reports import Attribute, gm from common_setup import IssueConfig, IssueExperiment def main(revisions=None): suite = suites.suite_optimal_with_ipc11() configs = { IssueConfig('rl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']), #IssueConfig('cggl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('dfp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']), #IssueConfig('rl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('cggl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']), #IssueConfig('dfp-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']), #IssueConfig('rl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']), #IssueConfig('cggl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']), IssueConfig('dfp-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']), } exp = IssueExperiment( revisions=revisions, configs=configs, suite=suite, test_suite=['depot:pfile1'], processes=4, email='[email protected]', ) exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py') exp.add_command('ms-parser', ['ms_parser']) # planner outcome attributes 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) perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False) proved_unsolvability = Attribute('proved_unsolvability', absolute=True, min_wins=False) # m&s attributes ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[gm]) 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) ms_memory_delta = Attribute('ms_memory_delta', absolute=False, min_wins=True) extra_attributes = [ search_out_of_memory, search_out_of_time, perfect_heuristic, proved_unsolvability, ms_construction_time, ms_abstraction_constructed, ms_final_size, ms_out_of_memory, ms_out_of_time, ms_memory_delta, ] attributes = exp.DEFAULT_TABLE_ATTRIBUTES attributes.extend(extra_attributes) exp.add_comparison_table_step() exp() main(revisions=['issue604-v6', 'issue604-v7'])
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue604/v4.py
#! /usr/bin/env python # -*- coding: utf-8 -*- from downward import suites from lab.reports import Attribute, gm from common_setup import IssueConfig, IssueExperiment def main(revisions=None): suite = suites.suite_optimal_with_ipc11() configs = { IssueConfig('rl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('cggl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('dfp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('rl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('cggl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('dfp-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('rl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']), IssueConfig('cggl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']), IssueConfig('dfp-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']), } exp = IssueExperiment( revisions=revisions, configs=configs, suite=suite, test_suite=['depot:pfile1'], processes=4, email='[email protected]', ) exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py') exp.add_command('ms-parser', ['ms_parser']) # planner outcome attributes 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) perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False) proved_unsolvability = Attribute('proved_unsolvability', absolute=True, min_wins=False) # m&s attributes ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[gm]) 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) ms_memory_delta = Attribute('ms_memory_delta', absolute=False, min_wins=True) extra_attributes = [ search_out_of_memory, search_out_of_time, perfect_heuristic, proved_unsolvability, ms_construction_time, ms_abstraction_constructed, ms_final_size, ms_out_of_memory, ms_out_of_time, ms_memory_delta, ] attributes = exp.DEFAULT_TABLE_ATTRIBUTES attributes.extend(extra_attributes) exp.add_comparison_table_step() exp() main(revisions=['issue604-v3', 'issue604-v4'])
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue604/v5.py
#! /usr/bin/env python # -*- coding: utf-8 -*- from downward import suites from lab.reports import Attribute, gm from downward.reports.compare import CompareConfigsReport from common_setup import IssueConfig, IssueExperiment import os def main(revisions=None): suite = suites.suite_optimal_with_ipc11() configs = { IssueConfig('rl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('cggl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('dfp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('rl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('cggl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('dfp-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('rl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']), IssueConfig('cggl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']), IssueConfig('dfp-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']), } exp = IssueExperiment( revisions=revisions, configs=configs, suite=suite, test_suite=['depot:pfile1'], processes=4, email='[email protected]', ) exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py') exp.add_command('ms-parser', ['ms_parser']) # planner outcome attributes 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) perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False) proved_unsolvability = Attribute('proved_unsolvability', absolute=True, min_wins=False) # m&s attributes ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[gm]) 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) ms_memory_delta = Attribute('ms_memory_delta', absolute=False, min_wins=True) extra_attributes = [ search_out_of_memory, search_out_of_time, perfect_heuristic, proved_unsolvability, ms_construction_time, ms_abstraction_constructed, ms_final_size, ms_out_of_memory, ms_out_of_time, ms_memory_delta, ] attributes = exp.DEFAULT_TABLE_ATTRIBUTES attributes.extend(extra_attributes) exp.add_fetcher('data/issue604-v4-eval') exp.add_report(CompareConfigsReport(compared_configs=[ ('issue604-v3-rl-b50k', 'issue604-v5-rl-b50k'), ('issue604-v3-cggl-b50k', 'issue604-v5-cggl-b50k'), ('issue604-v3-dfp-b50k', 'issue604-v5-dfp-b50k'), ('issue604-v3-rl-ginf', 'issue604-v5-rl-ginf'), ('issue604-v3-cggl-ginf', 'issue604-v5-cggl-ginf'), ('issue604-v3-dfp-ginf', 'issue604-v5-dfp-ginf'), ('issue604-v3-rl-f50k', 'issue604-v5-rl-f50k'), ('issue604-v3-cggl-f50k', 'issue604-v5-cggl-f50k'), ('issue604-v3-dfp-f50k', 'issue604-v5-dfp-f50k'), ],attributes=attributes),outfile=os.path.join( exp.eval_dir, 'issue604-v3-v5-comparison.html')) exp.add_report(CompareConfigsReport(compared_configs=[ ('issue604-v4-rl-b50k', 'issue604-v5-rl-b50k'), ('issue604-v4-cggl-b50k', 'issue604-v5-cggl-b50k'), ('issue604-v4-dfp-b50k', 'issue604-v5-dfp-b50k'), ('issue604-v4-rl-ginf', 'issue604-v5-rl-ginf'), ('issue604-v4-cggl-ginf', 'issue604-v5-cggl-ginf'), ('issue604-v4-dfp-ginf', 'issue604-v5-dfp-ginf'), ('issue604-v4-rl-f50k', 'issue604-v5-rl-f50k'), ('issue604-v4-cggl-f50k', 'issue604-v5-cggl-f50k'), ('issue604-v4-dfp-f50k', 'issue604-v5-dfp-f50k'), ],attributes=attributes),outfile=os.path.join( exp.eval_dir, 'issue604-v4-v5-comparison.html')) exp() main(revisions=['issue604-v5'])
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue604/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=1, **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))
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue604/v6.py
#! /usr/bin/env python # -*- coding: utf-8 -*- from downward import suites from lab.reports import Attribute, gm from common_setup import IssueConfig, IssueExperiment def main(revisions=None): suite = suites.suite_optimal_with_ipc11() configs = { IssueConfig('rl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']), #IssueConfig('cggl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('dfp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']), #IssueConfig('rl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('cggl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']), #IssueConfig('dfp-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']), #IssueConfig('rl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']), #IssueConfig('cggl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']), IssueConfig('dfp-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']), } exp = IssueExperiment( revisions=revisions, configs=configs, suite=suite, test_suite=['depot:pfile1'], processes=4, email='[email protected]', ) exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py') exp.add_command('ms-parser', ['ms_parser']) # planner outcome attributes 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) perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False) proved_unsolvability = Attribute('proved_unsolvability', absolute=True, min_wins=False) # m&s attributes ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[gm]) 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) ms_memory_delta = Attribute('ms_memory_delta', absolute=False, min_wins=True) extra_attributes = [ search_out_of_memory, search_out_of_time, perfect_heuristic, proved_unsolvability, ms_construction_time, ms_abstraction_constructed, ms_final_size, ms_out_of_memory, ms_out_of_time, ms_memory_delta, ] attributes = exp.DEFAULT_TABLE_ATTRIBUTES attributes.extend(extra_attributes) exp.add_comparison_table_step() exp() main(revisions=['issue604-v5', 'issue604-v6'])
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue604/v7-base.py
#! /usr/bin/env python # -*- coding: utf-8 -*- from downward import suites from lab.reports import Attribute, gm from downward.reports.compare import CompareConfigsReport from common_setup import IssueConfig, IssueExperiment import os def main(revisions=[]): suite = suites.suite_optimal_with_ipc11() configs = { } exp = IssueExperiment( revisions=revisions, configs=configs, suite=suite, test_suite=['depot:pfile1'], processes=4, email='[email protected]', ) exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py') exp.add_command('ms-parser', ['ms_parser']) # planner outcome attributes 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) perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False) proved_unsolvability = Attribute('proved_unsolvability', absolute=True, min_wins=False) # m&s attributes ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[gm]) 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) ms_memory_delta = Attribute('ms_memory_delta', absolute=False, min_wins=True) extra_attributes = [ search_out_of_memory, search_out_of_time, perfect_heuristic, proved_unsolvability, ms_construction_time, ms_abstraction_constructed, ms_final_size, ms_out_of_memory, ms_out_of_time, ms_memory_delta, ] attributes = exp.DEFAULT_TABLE_ATTRIBUTES attributes.extend(extra_attributes) exp.add_fetcher('data/issue604-v1-eval',filter_config=[ 'issue604-base-rl-b50k', 'issue604-base-cggl-b50k', 'issue604-base-dfp-b50k', 'issue604-base-rl-ginf', 'issue604-base-cggl-ginf', 'issue604-base-dfp-ginf', 'issue604-base-rl-f50k', 'issue604-base-cggl-f50k', 'issue604-base-dfp-f50k', ]) exp.add_fetcher('data/issue604-v7-eval',filter_config=[ 'issue604-v7-rl-b50k', 'issue604-v7-cggl-b50k', 'issue604-v7-dfp-b50k', 'issue604-v7-rl-ginf', 'issue604-v7-cggl-ginf', 'issue604-v7-dfp-ginf', 'issue604-v7-rl-f50k', 'issue604-v7-cggl-f50k', 'issue604-v7-dfp-f50k', ]) exp.add_fetcher('data/issue604-v7-rest-eval',filter_config=[ 'issue604-v7-rl-b50k', 'issue604-v7-cggl-b50k', 'issue604-v7-dfp-b50k', 'issue604-v7-rl-ginf', 'issue604-v7-cggl-ginf', 'issue604-v7-dfp-ginf', 'issue604-v7-rl-f50k', 'issue604-v7-cggl-f50k', 'issue604-v7-dfp-f50k', ]) exp.add_report(CompareConfigsReport(compared_configs=[ ('issue604-base-rl-b50k', 'issue604-v7-rl-b50k'), ('issue604-base-cggl-b50k', 'issue604-v7-cggl-b50k'), ('issue604-base-dfp-b50k', 'issue604-v7-dfp-b50k'), ('issue604-base-rl-ginf', 'issue604-v7-rl-ginf'), ('issue604-base-cggl-ginf', 'issue604-v7-cggl-ginf'), ('issue604-base-dfp-ginf', 'issue604-v7-dfp-ginf'), ('issue604-base-rl-f50k', 'issue604-v7-rl-f50k'), ('issue604-base-cggl-f50k', 'issue604-v7-cggl-f50k'), ('issue604-base-dfp-f50k', 'issue604-v7-dfp-f50k'), ],attributes=attributes),outfile=os.path.join( exp.eval_dir, 'issue604-base-v7-comparison.html')) exp() main()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue604/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_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) def check_proved_unsolvability(content, props): proved_unsolvability = False if props['coverage'] == 0: for line in content.splitlines(): if line == 'Completely explored state space -- no solution!': proved_unsolvability = True break props['proved_unsolvability'] = proved_unsolvability parser.add_function(check_proved_unsolvability) parser.parse()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue604/v1.py
#! /usr/bin/env python # -*- coding: utf-8 -*- from downward import suites from lab.reports import Attribute, gm from common_setup import IssueConfig, IssueExperiment from relativescatter import RelativeScatterPlotReport def main(revisions=None): suite = suites.suite_optimal_with_ipc11() configs = { IssueConfig('rl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('cggl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('dfp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('rl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('cggl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('dfp-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('rl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']), IssueConfig('cggl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']), IssueConfig('dfp-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']), } exp = IssueExperiment( revisions=revisions, configs=configs, suite=suite, test_suite=['depot:pfile1'], processes=4, email='[email protected]', ) exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py') exp.add_command('ms-parser', ['ms_parser']) # planner outcome attributes perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False) proved_unsolvability = Attribute('proved_unsolvability', absolute=True, min_wins=False) actual_search_time = Attribute('actual_search_time', absolute=False, min_wins=True, functions=[gm]) # m&s attributes ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[gm]) 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, proved_unsolvability, actual_search_time, ms_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() exp.add_report( RelativeScatterPlotReport( attributes=["memory"], filter_config=["issue604-base-dfp-ginf", "issue604-v1-dfp-ginf"], get_category=lambda run1, run2: run1.get("domain"), ), outfile='issue604_base_v1_memory_dfp.png' ) exp.add_report( RelativeScatterPlotReport( attributes=["memory"], filter_config=["issue604-base-rl-ginf", "issue604-v1-rl-ginf"], get_category=lambda run1, run2: run1.get("domain"), ), outfile='issue604_base_v1_memory_rl.png' ) exp() main(revisions=['issue604-base', 'issue604-v1'])
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue604/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')
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue604/v3.py
#! /usr/bin/env python # -*- coding: utf-8 -*- from downward import suites from lab.reports import Attribute, gm from downward.reports.compare import CompareConfigsReport from common_setup import IssueConfig, IssueExperiment import os def main(revisions=None): suite = suites.suite_optimal_with_ipc11() configs = { IssueConfig('rl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('cggl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('dfp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('rl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('cggl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('dfp-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('rl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']), IssueConfig('cggl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']), IssueConfig('dfp-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']), } exp = IssueExperiment( revisions=revisions, configs=configs, suite=suite, test_suite=['depot:pfile1'], processes=4, email='[email protected]', ) exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py') exp.add_command('ms-parser', ['ms_parser']) # planner outcome attributes 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) perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False) proved_unsolvability = Attribute('proved_unsolvability', absolute=True, min_wins=False) # m&s attributes ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[gm]) 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) ms_memory_delta = Attribute('ms_memory_delta', absolute=False, min_wins=True) extra_attributes = [ search_out_of_memory, search_out_of_time, perfect_heuristic, proved_unsolvability, ms_construction_time, ms_abstraction_constructed, ms_final_size, ms_out_of_memory, ms_out_of_time, ms_memory_delta, ] attributes = exp.DEFAULT_TABLE_ATTRIBUTES attributes.extend(extra_attributes) exp.add_fetcher('data/issue604-v1-eval', filter_config=[ 'issue604-v1-rl-b50k', 'issue604-v1-cggl-b50k', 'issue604-v1-dfp-b50k', 'issue604-v1-rl-ginf', 'issue604-v1-cggl-ginf', 'issue604-v1-dfp-ginf', 'issue604-v1-rl-f50k', 'issue604-v1-cggl-f50k', 'issue604-v1-dfp-f50k', ]) exp.add_report(CompareConfigsReport(compared_configs=[ ('issue604-v1-rl-b50k', 'issue604-v3-rl-b50k'), ('issue604-v1-cggl-b50k', 'issue604-v3-cggl-b50k'), ('issue604-v1-dfp-b50k', 'issue604-v3-dfp-b50k'), ('issue604-v1-rl-ginf', 'issue604-v3-rl-ginf'), ('issue604-v1-cggl-ginf', 'issue604-v3-cggl-ginf'), ('issue604-v1-dfp-ginf', 'issue604-v3-dfp-ginf'), ('issue604-v1-rl-f50k', 'issue604-v3-rl-f50k'), ('issue604-v1-cggl-f50k', 'issue604-v3-cggl-f50k'), ('issue604-v1-dfp-f50k', 'issue604-v3-dfp-f50k'), ],attributes=attributes),outfile=os.path.join(exp.eval_dir, 'issue604-v1-v3-comparison.html')) exp() main(revisions=['issue604-v3'])
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue604/v2.py
#! /usr/bin/env python # -*- coding: utf-8 -*- from downward import suites from lab.reports import Attribute, gm from common_setup import IssueConfig, IssueExperiment def main(revisions=None): suite = suites.suite_optimal_with_ipc11() configs = { IssueConfig('rl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('cggl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('dfp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('rl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('cggl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('dfp-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('rl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']), IssueConfig('cggl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']), IssueConfig('dfp-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']), } exp = IssueExperiment( revisions=revisions, configs=configs, suite=suite, test_suite=['depot:pfile1'], processes=4, email='[email protected]', ) exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py') exp.add_command('ms-parser', ['ms_parser']) # planner outcome attributes 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) perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False) proved_unsolvability = Attribute('proved_unsolvability', absolute=True, min_wins=False) # m&s attributes ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[gm]) 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) ms_memory_delta = Attribute('ms_memory_delta', absolute=False, min_wins=True) extra_attributes = [ search_out_of_memory, search_out_of_time, perfect_heuristic, proved_unsolvability, ms_construction_time, ms_abstraction_constructed, ms_final_size, ms_out_of_memory, ms_out_of_time, ms_memory_delta, ] attributes = exp.DEFAULT_TABLE_ATTRIBUTES attributes.extend(extra_attributes) exp.add_comparison_table_step() exp() main(revisions=['issue604-v1', 'issue604-v2'])
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue604/v7-rest.py
#! /usr/bin/env python # -*- coding: utf-8 -*- from downward import suites from lab.reports import Attribute, gm from common_setup import IssueConfig, IssueExperiment def main(revisions=None): suite = suites.suite_optimal_with_ipc11() configs = { #IssueConfig('rl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('cggl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']), #IssueConfig('dfp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('rl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']), #IssueConfig('cggl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('dfp-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('rl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']), IssueConfig('cggl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']), #IssueConfig('dfp-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']), } exp = IssueExperiment( revisions=revisions, configs=configs, suite=suite, test_suite=['depot:pfile1'], processes=4, email='[email protected]', ) exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py') exp.add_command('ms-parser', ['ms_parser']) # planner outcome attributes 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) perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False) proved_unsolvability = Attribute('proved_unsolvability', absolute=True, min_wins=False) # m&s attributes ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[gm]) 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) ms_memory_delta = Attribute('ms_memory_delta', absolute=False, min_wins=True) extra_attributes = [ search_out_of_memory, search_out_of_time, perfect_heuristic, proved_unsolvability, ms_construction_time, ms_abstraction_constructed, ms_final_size, ms_out_of_memory, ms_out_of_time, ms_memory_delta, ] attributes = exp.DEFAULT_TABLE_ATTRIBUTES attributes.extend(extra_attributes) exp.add_comparison_table_step() exp() main(revisions=['issue604-v6', 'issue604-v7'])
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue655/base-v1.py
#! /usr/bin/env python # -*- coding: utf-8 -*- import os import suites from lab.reports import Attribute, gm from common_setup import IssueConfig, IssueExperiment try: from relativescatter import RelativeScatterPlotReport matplotlib = True except ImportError: print 'matplotlib not availabe, scatter plots not available' matplotlib = False def main(revisions=None): benchmarks_dir=os.path.expanduser('~/repos/downward/benchmarks') suite=suites.suite_optimal_strips() # dummy configs with correct names so that comparison report works configs = { IssueConfig('rl-b50k', []), IssueConfig('cggl-b50k', []), IssueConfig('dfp-b50k', []), IssueConfig('rl-ginf', []), IssueConfig('cggl-ginf', []), IssueConfig('dfp-ginf', []), IssueConfig('rl-f50k', []), IssueConfig('cggl-f50k', []), IssueConfig('dfp-f50k', []), } exp = IssueExperiment( benchmarks_dir=benchmarks_dir, suite=suite, revisions=revisions, configs=configs, test_suite=['depot:p01.pddl'], processes=4, email='[email protected]', ) exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py') exp.add_command('ms-parser', ['ms_parser']) # planner outcome attributes perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False) proved_unsolvability = Attribute('proved_unsolvability', absolute=True, min_wins=False) actual_search_time = Attribute('actual_search_time', absolute=False, min_wins=True, functions=[gm]) # m&s attributes ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[gm]) 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, proved_unsolvability, actual_search_time, ms_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_fetcher('data/issue655-base-eval') exp.add_fetcher('data/issue655-v1-eval') exp.add_comparison_table_step() if matplotlib: 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() main(revisions=['issue655-base', 'issue655-v1'])
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue655/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): """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, benchmarks_dir, suite, revisions=[], configs={}, grid_priority=None, path=None, test_suite=None, email=None, processes=None, **kwargs): """ 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(benchmarks_dir, 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))
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue655/base.py
#! /usr/bin/env python # -*- coding: utf-8 -*- import os import suites from lab.reports import Attribute, gm from common_setup import IssueConfig, IssueExperiment try: from relativescatter import RelativeScatterPlotReport matplotlib = True except ImportError: print 'matplotlib not availabe, scatter plots not available' matplotlib = False def main(revisions=None): benchmarks_dir=os.path.expanduser('~/repos/downward/benchmarks') suite=suites.suite_optimal_strips() configs = { IssueConfig('rl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('cggl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('dfp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('rl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('cggl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('dfp-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false)))']), IssueConfig('rl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']), IssueConfig('cggl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']), IssueConfig('dfp-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_fh(max_states=50000),label_reduction=exact(before_shrinking=false,before_merging=true)))']), } exp = IssueExperiment( benchmarks_dir=benchmarks_dir, suite=suite, revisions=revisions, configs=configs, test_suite=['depot:p01.pddl'], processes=4, email='[email protected]', ) exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py') exp.add_command('ms-parser', ['ms_parser']) # planner outcome attributes perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False) proved_unsolvability = Attribute('proved_unsolvability', absolute=True, min_wins=False) actual_search_time = Attribute('actual_search_time', absolute=False, min_wins=True, functions=[gm]) # m&s attributes ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[gm]) 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, proved_unsolvability, actual_search_time, ms_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() #if matplotlib: #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() main(revisions=['issue655-base'])
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue655/suites.py
#! /usr/bin/env python # -*- coding: utf-8 -*- import argparse import textwrap HELP = "Convert suite name to list of domains or tasks." def suite_alternative_formulations(): return ['airport-adl', 'no-mprime', 'no-mystery'] def suite_ipc98_to_ipc04_adl(): return [ 'assembly', 'miconic-fulladl', 'miconic-simpleadl', 'optical-telegraphs', 'philosophers', 'psr-large', 'psr-middle', 'schedule', ] def suite_ipc98_to_ipc04_strips(): return [ 'airport', 'blocks', 'depot', 'driverlog', 'freecell', 'grid', 'gripper', 'logistics00', 'logistics98', 'miconic', 'movie', 'mprime', 'mystery', 'pipesworld-notankage', 'psr-small', 'satellite', 'zenotravel', ] def suite_ipc98_to_ipc04(): # All IPC1-4 domains, including the trivial Movie. return sorted(suite_ipc98_to_ipc04_adl() + suite_ipc98_to_ipc04_strips()) def suite_ipc06_adl(): return [ 'openstacks', 'pathways', 'trucks', ] def suite_ipc06_strips_compilations(): return [ 'openstacks-strips', 'pathways-noneg', 'trucks-strips', ] def suite_ipc06_strips(): return [ 'pipesworld-tankage', 'rovers', 'storage', 'tpp', ] def suite_ipc06(): return sorted(suite_ipc06_adl() + suite_ipc06_strips()) def suite_ipc08_common_strips(): return [ 'parcprinter-08-strips', 'pegsol-08-strips', 'scanalyzer-08-strips', ] def suite_ipc08_opt_adl(): return ['openstacks-opt08-adl'] def suite_ipc08_opt_strips(): return sorted(suite_ipc08_common_strips() + [ 'elevators-opt08-strips', 'openstacks-opt08-strips', 'sokoban-opt08-strips', 'transport-opt08-strips', 'woodworking-opt08-strips', ]) def suite_ipc08_opt(): return sorted(suite_ipc08_opt_strips() + suite_ipc08_opt_adl()) def suite_ipc08_sat_adl(): return ['openstacks-sat08-adl'] def suite_ipc08_sat_strips(): return sorted(suite_ipc08_common_strips() + [ # Note: cyber-security is missing. 'elevators-sat08-strips', 'openstacks-sat08-strips', 'sokoban-sat08-strips', 'transport-sat08-strips', 'woodworking-sat08-strips', ]) def suite_ipc08_sat(): return sorted(suite_ipc08_sat_strips() + suite_ipc08_sat_adl()) def suite_ipc08(): return sorted(set(suite_ipc08_opt() + suite_ipc08_sat())) def suite_ipc11_opt(): return [ 'barman-opt11-strips', 'elevators-opt11-strips', 'floortile-opt11-strips', 'nomystery-opt11-strips', 'openstacks-opt11-strips', 'parcprinter-opt11-strips', 'parking-opt11-strips', 'pegsol-opt11-strips', 'scanalyzer-opt11-strips', 'sokoban-opt11-strips', 'tidybot-opt11-strips', 'transport-opt11-strips', 'visitall-opt11-strips', 'woodworking-opt11-strips', ] def suite_ipc11_sat(): return [ 'barman-sat11-strips', 'elevators-sat11-strips', 'floortile-sat11-strips', 'nomystery-sat11-strips', 'openstacks-sat11-strips', 'parcprinter-sat11-strips', 'parking-sat11-strips', 'pegsol-sat11-strips', 'scanalyzer-sat11-strips', 'sokoban-sat11-strips', 'tidybot-sat11-strips', 'transport-sat11-strips', 'visitall-sat11-strips', 'woodworking-sat11-strips', ] def suite_ipc11(): return sorted(suite_ipc11_opt() + suite_ipc11_sat()) def suite_ipc14_agl_adl(): return [ 'cavediving-14-adl', 'citycar-sat14-adl', 'maintenance-sat14-adl', ] def suite_ipc14_agl_strips(): return [ 'barman-sat14-strips', 'childsnack-sat14-strips', 'floortile-sat14-strips', 'ged-sat14-strips', 'hiking-agl14-strips', 'openstacks-agl14-strips', 'parking-sat14-strips', 'tetris-sat14-strips', 'thoughtful-sat14-strips', 'transport-sat14-strips', 'visitall-sat14-strips', ] def suite_ipc14_agl(): return sorted(suite_ipc14_agl_adl() + suite_ipc14_agl_strips()) def suite_ipc14_mco_adl(): return [ 'cavediving-14-adl', 'citycar-sat14-adl', 'maintenance-sat14-adl', ] def suite_ipc14_mco_strips(): return [ 'barman-mco14-strips', 'childsnack-sat14-strips', 'floortile-sat14-strips', 'ged-sat14-strips', 'hiking-sat14-strips', 'openstacks-sat14-strips', 'parking-sat14-strips', 'tetris-sat14-strips', 'thoughtful-mco14-strips', 'transport-sat14-strips', 'visitall-sat14-strips', ] def suite_ipc14_mco(): return sorted(suite_ipc14_mco_adl() + suite_ipc14_mco_strips()) def suite_ipc14_opt_adl(): return [ 'cavediving-14-adl', 'citycar-opt14-adl', 'maintenance-opt14-adl', ] def suite_ipc14_opt_strips(): return [ 'barman-opt14-strips', 'childsnack-opt14-strips', 'floortile-opt14-strips', 'ged-opt14-strips', 'hiking-opt14-strips', 'openstacks-opt14-strips', 'parking-opt14-strips', 'tetris-opt14-strips', 'tidybot-opt14-strips', 'transport-opt14-strips', 'visitall-opt14-strips', ] def suite_ipc14_opt(): return sorted(suite_ipc14_opt_adl() + suite_ipc14_opt_strips()) def suite_ipc14_sat_adl(): return [ 'cavediving-14-adl', 'citycar-sat14-adl', 'maintenance-sat14-adl', ] def suite_ipc14_sat_strips(): return [ 'barman-sat14-strips', 'childsnack-sat14-strips', 'floortile-sat14-strips', 'ged-sat14-strips', 'hiking-sat14-strips', 'openstacks-sat14-strips', 'parking-sat14-strips', 'tetris-sat14-strips', 'thoughtful-sat14-strips', 'transport-sat14-strips', 'visitall-sat14-strips', ] def suite_ipc14_sat(): return sorted(suite_ipc14_sat_adl() + suite_ipc14_sat_strips()) def suite_ipc14(): return sorted(set( suite_ipc14_agl() + suite_ipc14_mco() + suite_ipc14_opt() + suite_ipc14_sat())) def suite_unsolvable(): return sorted( ['mystery:prob%02d.pddl' % index for index in [4, 5, 7, 8, 12, 16, 18, 21, 22, 23, 24]] + ['miconic-fulladl:f21-3.pddl', 'miconic-fulladl:f30-2.pddl']) def suite_optimal_adl(): return sorted( suite_ipc98_to_ipc04_adl() + suite_ipc06_adl() + suite_ipc08_opt_adl() + suite_ipc14_opt_adl()) def suite_optimal_strips(): return sorted( suite_ipc98_to_ipc04_strips() + suite_ipc06_strips() + suite_ipc06_strips_compilations() + suite_ipc08_opt_strips() + suite_ipc11_opt() + suite_ipc14_opt_strips()) def suite_optimal(): return sorted(suite_optimal_adl() + suite_optimal_strips()) def suite_satisficing_adl(): return sorted( suite_ipc98_to_ipc04_adl() + suite_ipc06_adl() + suite_ipc08_sat_adl() + suite_ipc14_sat_adl()) def suite_satisficing_strips(): return sorted( suite_ipc98_to_ipc04_strips() + suite_ipc06_strips() + suite_ipc06_strips_compilations() + suite_ipc08_sat_strips() + suite_ipc11_sat() + suite_ipc14_sat_strips()) def suite_satisficing(): return sorted(suite_satisficing_adl() + suite_satisficing_strips()) def suite_all(): return sorted( suite_ipc98_to_ipc04() + suite_ipc06() + suite_ipc06_strips_compilations() + suite_ipc08() + suite_ipc11() + suite_ipc14() + suite_alternative_formulations()) def parse_args(): parser = argparse.ArgumentParser() parser.add_argument("suite", help="suite name") return parser.parse_args() def main(): prefix = "suite_" suite_names = [ name[len(prefix):] for name in sorted(globals().keys()) if name.startswith(prefix)] parser = argparse.ArgumentParser(description=HELP) parser.add_argument("suite", choices=suite_names, help="suite name") parser.add_argument( "--width", default=72, type=int, help="output line width (default: %(default)s). Use 1 for single " "column.") args = parser.parse_args() suite_func = globals()[prefix + args.suite] print(textwrap.fill( str(suite_func()), width=args.width, break_long_words=False, break_on_hyphens=False)) if __name__ == "__main__": main()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue655/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_memory_delta', 'Final peak memory increase of merge-and-shrink computation: (\d+) KB', required=False, type=int) parser.add_pattern('actual_search_time', 'Actual search time: (.+)s \[t=.+s\]', required=False, type=float) 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) def check_proved_unsolvability(content, props): proved_unsolvability = False if props['coverage'] == 0: for line in content.splitlines(): if line == 'Completely explored state space -- no solution!': proved_unsolvability = True break props['proved_unsolvability'] = proved_unsolvability parser.add_function(check_proved_unsolvability) parser.parse()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue655/v1.py
#! /usr/bin/env python # -*- coding: utf-8 -*- import os import suites from lab.reports import Attribute, gm from common_setup import IssueConfig, IssueExperiment try: from relativescatter import RelativeScatterPlotReport matplotlib = True except ImportError: print 'matplotlib not available, scatter plots not available' matplotlib = False def main(revisions=None): benchmarks_dir=os.path.expanduser('~/repos/downward/benchmarks') suite=suites.suite_optimal_strips() configs = { IssueConfig('rl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_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('cggl-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']), IssueConfig('dfp-b50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(greedy=false),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=50000,threshold_before_merge=1))']), IssueConfig('rl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_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('cggl-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1))']), IssueConfig('dfp-ginf', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(greedy=true),label_reduction=exact(before_shrinking=true,before_merging=false),max_states=infinity,threshold_before_merge=1))']), IssueConfig('rl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000))']), IssueConfig('cggl-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=cg_goal_level),shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000))']), IssueConfig('dfp-f50k', ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_fh(),label_reduction=exact(before_shrinking=false,before_merging=true),max_states=50000))']), } exp = IssueExperiment( benchmarks_dir=benchmarks_dir, suite=suite, revisions=revisions, configs=configs, test_suite=['depot:p01.pddl'], processes=4, email='[email protected]', ) exp.add_resource('ms_parser', 'ms-parser.py', dest='ms-parser.py') exp.add_command('ms-parser', ['ms_parser']) # planner outcome attributes perfect_heuristic = Attribute('perfect_heuristic', absolute=True, min_wins=False) proved_unsolvability = Attribute('proved_unsolvability', absolute=True, min_wins=False) actual_search_time = Attribute('actual_search_time', absolute=False, min_wins=True, functions=[gm]) # m&s attributes ms_construction_time = Attribute('ms_construction_time', absolute=False, min_wins=True, functions=[gm]) 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, proved_unsolvability, actual_search_time, ms_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() #if matplotlib: #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() main(revisions=['issue655-v1'])
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue655/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')
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue481/v1-lama.py
#! /usr/bin/env python # -*- coding: utf-8 -*- from downward import suites from common_setup import IssueConfig, IssueExperiment REVS = ["issue481-base", "issue481-v1"] SUITE = suites.suite_satisficing_with_ipc11() CONFIGS = [ IssueConfig("lama", [], driver_options=["--alias", "seq-sat-lama-2011"]), ] exp = IssueExperiment( revisions=REVS, configs=CONFIGS, suite=SUITE, email="[email protected]" ) exp.add_comparison_table_step() exp()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue481/v1-sat-test.py
#! /usr/bin/env python # -*- coding: utf-8 -*- from downward import suites from common_setup import IssueConfig, IssueExperiment REVS = ["issue481-base", "issue481-v1"] SUITE = suites.suite_satisficing_with_ipc11() CONFIGS = [ # Greedy (tests single and alternating open lists) IssueConfig("eager_greedy_ff", [ "--heuristic", "h=ff()", "--search", "eager_greedy(h, preferred=h)" ]), IssueConfig("lazy_greedy_ff", [ "--heuristic", "h=ff()", "--search", "lazy_greedy(h, preferred=h)" ]), # Epsilon Greedy IssueConfig("lazy_epsilon_greedy_ff", [ "--heuristic", "h=ff()", "--search", "lazy(epsilon_greedy(h))" ]), # Pareto IssueConfig("lazy_pareto_ff_cea", [ "--heuristic", "h1=ff()", "--heuristic", "h2=cea()", "--search", "lazy(pareto([h1, h2]))" ]), # Single Buckets IssueConfig("lazy_single_buckets_ff", [ "--heuristic", "h=ff()", "--search", "lazy(single_buckets(h))" ]), # Type based (from issue455) IssueConfig("ff-type-const", [ "--heuristic", "hff=ff(cost_type=one)", "--search", "lazy(alt([single(hff),single(hff, pref_only=true), type_based([const(1)])])," "preferred=[hff],cost_type=one)" ]), IssueConfig("lama-first", [ "--heuristic", "hlm,hff=lm_ff_syn(lm_rhw(reasonable_orders=true,lm_cost_type=one,cost_type=one))", "--search", "lazy(alt([single(hff),single(hff, pref_only=true), single(hlm), single(hlm, pref_only=true)])," "preferred=[hff,hlm],cost_type=one)" ]), IssueConfig("lama-first-types-ff-g", [ "--heuristic", "hlm,hff=lm_ff_syn(lm_rhw(reasonable_orders=true,lm_cost_type=one,cost_type=one))", "--search", "lazy(alt([single(hff),single(hff, pref_only=true), single(hlm), single(hlm, pref_only=true), type_based([hff, g()])])," "preferred=[hff,hlm],cost_type=one)" ]), ] exp = IssueExperiment( revisions=REVS, configs=CONFIGS, suite=SUITE, email="[email protected]" ) # Absolute report commented out because a comparison table is more useful for this issue. # (It's still in this file because someone might want to use it as a basis.) # Scatter plots commented out for now because I have no usable matplotlib available. # exp.add_absolute_report_step() exp.add_comparison_table_step() # exp.add_scatter_plot_step() exp()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue481/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 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, revisions, configs, suite, grid_priority=None, path=None, test_suite=None, email=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() 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 = 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 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(( "{rev1}-{config_nick}".format(**locals()), "{rev2}-{config_nick}".format(**locals()), "Diff ({config_nick})".format(**locals()))) report = CompareConfigsReport(compared_configs, **kwargs) outfile = os.path.join( self.eval_dir, "{name}-{rev1}-{rev2}-compare.html".format( name=self.name, **locals())) 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 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))
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue481/v1-opt-test.py
#! /usr/bin/env python # -*- coding: utf-8 -*- from downward import suites from common_setup import IssueConfig, IssueExperiment REVS = ["issue481-base", "issue481-v1"] SUITE = suites.suite_optimal_with_ipc11() CONFIGS = [ # Greedy (tests single and alternating open lists) IssueConfig("astar_lmcut", [ "--search", "astar(lmcut())" ]), ] exp = IssueExperiment( revisions=REVS, configs=CONFIGS, suite=SUITE, email="[email protected]" ) exp.add_comparison_table_step() exp()
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue627/v4.py
#! /usr/bin/env python # -*- coding: utf-8 -*- from downward import suites from common_setup_no_benchmarks import IssueConfig, IssueExperiment from relativescatter import RelativeScatterPlotReport def main(revisions=None): suite = suites.suite_optimal_with_ipc11() configs = { IssueConfig('astar-blind', ['--search', 'astar(blind())']), IssueConfig('astar-lmcut', ['--search', 'astar(lmcut())']), IssueConfig('astar-ipdb', ['--search', 'astar(ipdb())']), IssueConfig('astar-cegar-original', ['--search', 'astar(cegar(subtasks=[original()], max_states=10000, max_time=infinity))']), IssueConfig('astar-cegar-lm-goals', ['--search', 'astar(cegar(subtasks=[landmarks(),goals()], max_states=10000, max_time=infinity))']), } exp = IssueExperiment( benchmarks_dir="/infai/pommeren/projects/downward/benchmarks/", revisions=revisions, configs=configs, suite=suite, test_suite=['depot:pfile1'], processes=4, email='[email protected]', ) exp.add_comparison_table_step() for config in configs: exp.add_report( RelativeScatterPlotReport( attributes=["memory"], filter_config=["issue627-v3-base-%s" % config.nick, "issue627-v4-%s" % config.nick], get_category=lambda run1, run2: run1.get("domain"), ), outfile='issue627_base_v4_memory_%s.png' % config.nick ) exp.add_report( RelativeScatterPlotReport( attributes=["total_time"], filter_config=["issue627-v3-base-%s" % config.nick, "issue627-v4-%s" % config.nick], get_category=lambda run1, run2: run1.get("domain"), ), outfile='issue627_base_v4_total_time_%s.png' % config.nick ) exp() main(revisions=['issue627-v3-base', 'issue627-v4'])
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makolon/hsr_isaac_tamp/hsr_tamp/downward/experiments/issue627/v5.py
#! /usr/bin/env python # -*- coding: utf-8 -*- from downward import suites from common_setup_no_benchmarks import IssueConfig, IssueExperiment from relativescatter import RelativeScatterPlotReport def main(revisions=None): suite = suites.suite_optimal_with_ipc11() configs = { IssueConfig('astar-blind', ['--search', 'astar(blind())']), IssueConfig('astar-lmcut', ['--search', 'astar(lmcut())']), IssueConfig('astar-ipdb', ['--search', 'astar(ipdb())']), IssueConfig('astar-cegar-original', ['--search', 'astar(cegar(subtasks=[original()], max_states=10000, max_time=infinity))']), IssueConfig('astar-cegar-lm-goals', ['--search', 'astar(cegar(subtasks=[landmarks(),goals()], max_states=10000, max_time=infinity))']), } exp = IssueExperiment( benchmarks_dir="/infai/pommeren/projects/downward/benchmarks/", revisions=revisions, configs=configs, suite=suite, test_suite=['depot:pfile1'], processes=4, email='[email protected]', ) exp.add_comparison_table_step() for config in configs: exp.add_report( RelativeScatterPlotReport( attributes=["memory"], filter_config=["issue627-v3-base-%s" % config.nick, "issue627-v5-%s" % config.nick], get_category=lambda run1, run2: run1.get("domain"), ), outfile='issue627_base_v5_memory_%s.png' % config.nick ) exp.add_report( RelativeScatterPlotReport( attributes=["total_time"], filter_config=["issue627-v3-base-%s" % config.nick, "issue627-v5-%s" % config.nick], get_category=lambda run1, run2: run1.get("domain"), ), outfile='issue627_base_v5_total_time_%s.png' % config.nick ) exp() main(revisions=['issue627-v3-base', 'issue627-v5'])
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