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DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue499/relativescatter.py
|
# -*- coding: utf-8 -*-
#
# downward uses the lab package to conduct experiments with the
# Fast Downward planning system.
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
from collections import defaultdict
import os
from lab import tools
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows how a specific attribute in two
configurations. The attribute value in config 1 is shown on the
x-axis and the relation to the value in config 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['config'] == self.configs[0] and
run2['config'] == self.configs[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.configs[0], val1)
assert val2 > 0, (domain, problem, self.configs[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlots use log-scaling on the x-axis by default.
default_xscale = 'log'
if self.attribute and self.attribute in self.LINEAR:
default_xscale = 'linear'
PlotReport._set_scales(self, xscale or default_xscale, 'log')
| 4,690 | 35.937008 | 84 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/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()
| 1,489 | 30.702128 | 114 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/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()
| 1,682 | 33.346939 | 114 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/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)
| 14,171 | 35.715026 | 79 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/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')
| 3,875 | 35.566038 | 78 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue901/v2.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import itertools
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from downward.reports.compare import ComparativeReport
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
SCRIPT_NAME = os.path.splitext(os.path.basename(__file__))[0]
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue901-base", "issue901-v2"]
CONFIGS = [
IssueConfig("cegar-original-1M", ["--search", "astar(cegar(subtasks=[original()], max_transitions=1M, max_time=infinity))"]),
IssueConfig("cegar-lm-goals-1M", ["--search", "astar(cegar(subtasks=[landmarks(), goals()], max_transitions=1M, max_time=infinity))"]),
IssueConfig("cegar-original-900s", ["--search", "astar(cegar(subtasks=[original()], max_transitions=infinity, max_time=900))"]),
IssueConfig("cegar-lm-goals-900s", ["--search", "astar(cegar(subtasks=[landmarks(), goals()], max_transitions=infinity, max_time=900))"]),
]
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.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
REFINEMENT_ATTRIBUTES = [
"time_for_finding_traces",
"time_for_finding_flaws",
"time_for_splitting_states",
]
attributes = (
IssueExperiment.DEFAULT_TABLE_ATTRIBUTES +
["search_start_memory", "init_time", "time_analysis"] +
["total_" + attr for attr in REFINEMENT_ATTRIBUTES])
#exp.add_absolute_report_step(attributes=attributes)
exp.add_comparison_table_step(attributes=attributes)
exp.add_scatter_plot_step(relative=True, attributes=["search_time", "total_time"])
exp.run_steps()
| 2,320 | 34.166667 | 142 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue901/parser.py
|
#! /usr/bin/env python
import logging
import re
from lab.parser import Parser
class CommonParser(Parser):
def add_difference(self, diff, val1, val2):
def diff_func(content, props):
if props.get(val1) is None or props.get(val2) is None:
diff_val = None
else:
diff_val = props.get(val1) - props.get(val2)
props[diff] = diff_val
self.add_function(diff_func)
def _get_flags(self, flags_string):
flags = 0
for char in flags_string:
flags |= getattr(re, char)
return flags
def add_repeated_pattern(
self, name, regex, file="run.log", required=False, type=int,
flags=""):
def find_all_occurences(content, props):
matches = re.findall(regex, content, flags=self._get_flags(flags))
if required and not matches:
logging.error("Pattern {0} not found in file {1}".format(regex, file))
props[name] = [type(m) for m in matches]
self.add_function(find_all_occurences, file=file)
def add_pattern(self, name, regex, file="run.log", required=False, type=int, flags=""):
Parser.add_pattern(self, name, regex, file=file, required=required, type=type, flags=flags)
def add_bottom_up_pattern(self, name, regex, file="run.log", required=True, type=int, flags=""):
def search_from_bottom(content, props):
reversed_content = "\n".join(reversed(content.splitlines()))
match = re.search(regex, reversed_content, flags=self._get_flags(flags))
if required and not match:
logging.error("Pattern {0} not found in file {1}".format(regex, file))
if match:
props[name] = type(match.group(1))
self.add_function(search_from_bottom, file=file)
def no_search(content, props):
if "search_start_time" not in props:
error = props.get("error")
if error is not None and error != "incomplete-search-found-no-plan":
props["error"] = "no-search-due-to-" + error
REFINEMENT_ATTRIBUTES = [
("time_for_finding_traces", r"Time for finding abstract traces: (.+)s"),
("time_for_finding_flaws", r"Time for finding flaws: (.+)s"),
("time_for_splitting_states", r"Time for splitting states: (.+)s"),
]
def compute_total_times(content, props):
for attribute, pattern in REFINEMENT_ATTRIBUTES:
props["total_" + attribute] = sum(props[attribute])
def add_time_analysis(content, props):
init_time = props.get("init_time")
if not init_time:
return
parts = []
parts.append("{init_time:.2f}:".format(**props))
for attribute, pattern in REFINEMENT_ATTRIBUTES:
time = props["total_" + attribute]
relative_time = time / init_time
print time, type(time)
parts.append("{:.2f} ({:.2f})".format(time, relative_time))
props["time_analysis"] = " ".join(parts)
def main():
parser = CommonParser()
parser.add_pattern("search_start_time", r"\[g=0, 1 evaluated, 0 expanded, t=(.+)s, \d+ KB\]", type=float)
parser.add_pattern("search_start_memory", r"\[g=0, 1 evaluated, 0 expanded, t=.+s, (\d+) KB\]", type=int)
parser.add_pattern("init_time", r"Time for initializing additive Cartesian heuristic: (.+)s", type=float)
parser.add_pattern("cartesian_states", r"^Cartesian states: (\d+)\n", type=int)
for attribute, pattern in REFINEMENT_ATTRIBUTES:
parser.add_repeated_pattern(attribute, pattern, type=float, required=False)
parser.add_function(no_search)
parser.add_function(compute_total_times)
parser.add_function(add_time_analysis)
parser.parse()
if __name__ == "__main__":
main()
| 3,743 | 34.657143 | 109 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue901/v1.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import itertools
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from downward.reports.compare import ComparativeReport
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
SCRIPT_NAME = os.path.splitext(os.path.basename(__file__))[0]
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue901-base", "issue901-v1"]
CONFIGS = [
IssueConfig("cegar-original", ["--search", "astar(cegar(subtasks=[original()], max_transitions=1M, max_time=infinity))"]),
IssueConfig("cegar-lm-goals", ["--search", "astar(cegar(subtasks=[landmarks(), goals()], max_transitions=1M, max_time=infinity))"]),
]
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.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
REFINEMENT_ATTRIBUTES = [
"time_for_finding_traces",
"time_for_finding_flaws",
"time_for_splitting_states",
]
attributes = (
IssueExperiment.DEFAULT_TABLE_ATTRIBUTES +
["search_start_memory", "init_time", "time_analysis"] +
["total_" + attr for attr in REFINEMENT_ATTRIBUTES])
#exp.add_absolute_report_step(attributes=attributes)
exp.add_comparison_table_step(attributes=attributes)
exp.add_scatter_plot_step(relative=True, attributes=["search_time", "total_time"])
exp.run_steps()
| 2,038 | 30.859375 | 136 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue901/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import ComparativeReport
from downward.reports.scatter import ScatterPlotReport
from relativescatter import RelativeScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
DEFAULT_OPTIMAL_SUITE = [
'agricola-opt18-strips', 'airport', 'barman-opt11-strips',
'barman-opt14-strips', 'blocks', 'childsnack-opt14-strips',
'data-network-opt18-strips', 'depot', 'driverlog',
'elevators-opt08-strips', 'elevators-opt11-strips',
'floortile-opt11-strips', 'floortile-opt14-strips', 'freecell',
'ged-opt14-strips', 'grid', 'gripper', 'hiking-opt14-strips',
'logistics00', 'logistics98', 'miconic', 'movie', 'mprime',
'mystery', 'nomystery-opt11-strips', 'openstacks-opt08-strips',
'openstacks-opt11-strips', 'openstacks-opt14-strips',
'openstacks-strips', 'organic-synthesis-opt18-strips',
'organic-synthesis-split-opt18-strips', 'parcprinter-08-strips',
'parcprinter-opt11-strips', 'parking-opt11-strips',
'parking-opt14-strips', 'pathways-noneg', 'pegsol-08-strips',
'pegsol-opt11-strips', 'petri-net-alignment-opt18-strips',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-small', 'rovers',
'satellite', 'scanalyzer-08-strips', 'scanalyzer-opt11-strips',
'snake-opt18-strips', 'sokoban-opt08-strips',
'sokoban-opt11-strips', 'spider-opt18-strips', 'storage',
'termes-opt18-strips', 'tetris-opt14-strips',
'tidybot-opt11-strips', 'tidybot-opt14-strips', 'tpp',
'transport-opt08-strips', 'transport-opt11-strips',
'transport-opt14-strips', 'trucks-strips', 'visitall-opt11-strips',
'visitall-opt14-strips', 'woodworking-opt08-strips',
'woodworking-opt11-strips', 'zenotravel']
DEFAULT_SATISFICING_SUITE = [
'agricola-sat18-strips', 'airport', 'assembly',
'barman-sat11-strips', 'barman-sat14-strips', 'blocks',
'caldera-sat18-adl', 'caldera-split-sat18-adl', 'cavediving-14-adl',
'childsnack-sat14-strips', 'citycar-sat14-adl',
'data-network-sat18-strips', 'depot', 'driverlog',
'elevators-sat08-strips', 'elevators-sat11-strips',
'flashfill-sat18-adl', 'floortile-sat11-strips',
'floortile-sat14-strips', 'freecell', 'ged-sat14-strips', 'grid',
'gripper', 'hiking-sat14-strips', 'logistics00', 'logistics98',
'maintenance-sat14-adl', 'miconic', 'miconic-fulladl',
'miconic-simpleadl', 'movie', 'mprime', 'mystery',
'nomystery-sat11-strips', 'nurikabe-sat18-adl', 'openstacks',
'openstacks-sat08-adl', 'openstacks-sat08-strips',
'openstacks-sat11-strips', 'openstacks-sat14-strips',
'openstacks-strips', 'optical-telegraphs',
'organic-synthesis-sat18-strips',
'organic-synthesis-split-sat18-strips', 'parcprinter-08-strips',
'parcprinter-sat11-strips', 'parking-sat11-strips',
'parking-sat14-strips', 'pathways', 'pathways-noneg',
'pegsol-08-strips', 'pegsol-sat11-strips', 'philosophers',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-large',
'psr-middle', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-sat11-strips', 'schedule',
'settlers-sat18-adl', 'snake-sat18-strips', 'sokoban-sat08-strips',
'sokoban-sat11-strips', 'spider-sat18-strips', 'storage',
'termes-sat18-strips', 'tetris-sat14-strips',
'thoughtful-sat14-strips', 'tidybot-sat11-strips', 'tpp',
'transport-sat08-strips', 'transport-sat11-strips',
'transport-sat14-strips', 'trucks', 'trucks-strips',
'visitall-sat11-strips', 'visitall-sat14-strips',
'woodworking-sat08-strips', 'woodworking-sat11-strips',
'zenotravel']
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return node.endswith(".scicore.unibas.ch") or node.endswith(".cluster.bc2.ch")
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["depot:p01.pddl", "gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"planner_memory",
"planner_time",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, outfile=outfile)
self.add_step(
'publish-absolute-report', subprocess.call, ['publish', outfile])
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = ComparativeReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.%s" % (
self.name, rev1, rev2, report.output_format))
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
subprocess.call(["publish", outfile])
self.add_step("make-comparison-tables", make_comparison_tables)
self.add_step(
"publish-comparison-tables", publish_comparison_tables)
def add_scatter_plot_step(self, relative=False, attributes=None):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if relative:
report_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
report_class = ScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = get_algo_nick(rev1, config_nick)
algo2 = get_algo_nick(rev2, config_nick)
report = report_class(
filter_algorithm=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"])
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(step_name, make_scatter_plots)
| 14,743 | 36.42132 | 82 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue901/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(
axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows a relative comparison of two
algorithms with regard to the given attribute. The attribute value
of algorithm 1 is shown on the x-axis and the relation to the value
of algorithm 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['algorithm'] == self.algorithms[0] and
run2['algorithm'] == self.algorithms[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if not val1 or not val2:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.algorithms[0], val1)
assert val2 > 0, (domain, problem, self.algorithms[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlot uses log-scaling on the x-axis by default.
PlotReport._set_scales(
self, xscale or self.attribute.scale or 'log', 'log')
| 3,867 | 35.490566 | 78 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue596/main.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
from lab.reports import Attribute, gm
import common_setup
def main(revisions=None):
SUITE = suites.suite_optimal_with_ipc11()
B_CONFIGS = {
'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=label_reduction(before_shrinking=true,before_merging=false)))'],
'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=label_reduction(before_shrinking=true,before_merging=false)))'],
'dfp-b50k': ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,greedy=false),label_reduction=label_reduction(before_shrinking=true,before_merging=false)))'],
}
G_CONFIGS = {
'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=label_reduction(before_shrinking=true,before_merging=false)))'],
'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=label_reduction(before_shrinking=true,before_merging=false)))'],
'dfp-ginf': ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,greedy=true),label_reduction=label_reduction(before_shrinking=true,before_merging=false)))'],
}
F_CONFIGS = {
'rl-f50k': ['--search', 'astar(merge_and_shrink(merge_strategy=merge_linear(variable_order=reverse_level),shrink_strategy=shrink_fh(max_states=50000),label_reduction=label_reduction(before_shrinking=false,before_merging=true)))'],
'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=label_reduction(before_shrinking=false,before_merging=true)))'],
'dfp-f50k': ['--search', 'astar(merge_and_shrink(merge_strategy=merge_dfp,shrink_strategy=shrink_fh(max_states=50000),label_reduction=label_reduction(before_shrinking=false,before_merging=true)))'],
}
CONFIGS = dict(B_CONFIGS)
CONFIGS.update(G_CONFIGS)
CONFIGS.update(F_CONFIGS)
exp = common_setup.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(attributes=attributes)
exp()
| 4,428 | 57.276316 | 277 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue596/issue596-v1.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from main import main
main(revisions=["issue596-base", "issue596-v1"])
| 120 | 16.285714 | 48 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue596/ms-parser.py
|
#! /usr/bin/env python
from lab.parser import Parser
parser = Parser()
parser.add_pattern('actual_search_time', 'Actual search time: (.+)s \[.+s\]', required=False, type=float)
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)
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_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)
def check_planner_exit_reason(content, props):
ms_abstraction_constructed = props.get('ms_abstraction_constructed')
error = props.get('error')
if error != 'none' and error != 'timeout' and error != 'out-of-memory':
print 'error: %s' % error
return
# Check whether merge-and-shrink computation or search ran out of
# time or memory.
ms_out_of_time = False
ms_out_of_memory = False
search_out_of_time = False
search_out_of_memory = False
if ms_abstraction_constructed == False:
if error == 'timeout':
ms_out_of_time = True
elif error == 'out-of-memory':
ms_out_of_memory = True
elif ms_abstraction_constructed == True:
if error == 'timeout':
search_out_of_time = True
elif error == 'out-of-memory':
search_out_of_memory = True
props['ms_out_of_time'] = ms_out_of_time
props['ms_out_of_memory'] = ms_out_of_memory
props['search_out_of_time'] = search_out_of_time
props['search_out_of_memory'] = search_out_of_memory
parser.add_function(check_planner_exit_reason)
def check_perfect_heuristic(content, props):
plan_length = props.get('plan_length')
expansions = props.get('expansions')
if plan_length != None:
perfect_heuristic = False
if plan_length + 1 == expansions:
perfect_heuristic = True
props['perfect_heuristic'] = perfect_heuristic
parser.add_function(check_perfect_heuristic)
parser.parse()
| 2,646 | 35.763889 | 128 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue596/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.environments import LocalEnvironment, MaiaEnvironment
from lab.experiment import ARGPARSER
from lab.steps import Step
from downward.experiments.fast_downward_experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import CompareRevisionsReport
from downward.reports.scatter import ScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
def get_script():
"""Get file name of main script."""
import __main__
return __main__.__file__
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return ("cluster" in node or
node.startswith("gkigrid") or
node in ["habakuk", "turtur"])
def is_test_run():
return ARGS.test_run == "yes" or (ARGS.test_run == "auto" and
not is_running_on_cluster())
class IssueExperiment(FastDownwardExperiment):
"""Wrapper for FastDownwardExperiment with a few convenience features."""
DEFAULT_TEST_SUITE = "gripper:prob01.pddl"
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"plan_length",
]
def __init__(self, configs, revisions, suite, build_options=None,
driver_options=None, grid_priority=None,
test_suite=None, email=None, processes=1, **kwargs):
"""Create an FastDownwardExperiment with some convenience features.
All configs will be run on all revisions. Inherited options
*path*, *environment* and *cache_dir* from FastDownwardExperiment
are not supported and will be automatically set.
*configs* must be a non-empty dict of {nick: cmdline} pairs
that sets the planner configurations to test. nick will
automatically get the revision prepended, e.g.
'issue123-base-<nick>'::
IssueExperiment(configs={
"lmcut": ["--search", "astar(lmcut())"],
"ipdb": ["--search", "astar(ipdb())"]})
*revisions* must be a non-empty list of revisions, which
specify which planner versions to use in the experiment.
The same versions are used for translator, preprocessor
and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"])
*suite* sets the benchmarks for the experiment. It must be a
single string or a list of strings specifying domains or
tasks. The downward.suites module has many predefined
suites. ::
IssueExperiment(suite=["grid", "gripper:prob01.pddl"])
from downward import suites
IssueExperiment(suite=suites.suite_all())
IssueExperiment(suite=suites.suite_satisficing_with_ipc11())
IssueExperiment(suite=suites.suite_optimal())
Use *grid_priority* to set the job priority for cluster
experiments. It must be in the range [-1023, 0] where 0 is the
highest priority. By default the priority is 0. ::
IssueExperiment(grid_priority=-500)
Specify *test_suite* to set the benchmarks for experiment test
runs. By default the first gripper task is used.
IssueExperiment(test_suite=["depot:pfile1", "tpp:p01.pddl"])
"""
if is_test_run():
environment = LocalEnvironment(processes=processes)
suite = test_suite or self.DEFAULT_TEST_SUITE
elif "environment" not in kwargs:
environment = MaiaEnvironment(priority=grid_priority,
email=email)
FastDownwardExperiment.__init__(self, environment=environment,
**kwargs)
# Automatically deduce the downward repository from the file
repo = get_repo_base()
self.algorithm_nicks = []
self.revisions = revisions
for nick, cmdline in configs.items():
for rev in revisions:
algo_nick = '%s-%s' % (rev, nick)
self.add_algorithm(algo_nick, repo, rev, cmdline,
build_options, driver_options)
self.algorithm_nicks.append(algo_nick)
benchmarks_dir = os.path.join(repo, 'benchmarks')
self.add_suite(benchmarks_dir, suite)
self.search_parsers = []
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't
compare revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If
the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
# oufile is of the form <rev1>-<rev2>-...-<revn>.<format>
outfile = ''
for rev in self.revisions:
outfile += rev
outfile += '-'
outfile = outfile[:len(outfile)-1]
outfile += '.'
outfile += report.output_format
outfile = os.path.join(self.eval_dir, outfile)
self.add_report(report, outfile=outfile)
self.add_step(Step('publish-absolute-report', subprocess.call, ['publish', outfile]))
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revision triples. Each report pairs up the runs of the same
config and lists the two absolute attribute values and their
difference for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareRevisionsReport
class. If the keyword argument *attributes* is not
specified, a default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self.revisions, 2):
report = CompareRevisionsReport(rev1, rev2, **kwargs)
outfile = os.path.join(self.eval_dir,
"%s-%s-compare.html" %
(rev1, rev2))
report(self.eval_dir, outfile)
self.add_step(Step("make-comparison-tables", make_comparison_tables))
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self.revisions, 2):
outfile = os.path.join(self.eval_dir,
"%s-%s-compare.html" %
(rev1, rev2))
subprocess.call(['publish', outfile])
self.add_step(Step('publish-comparison-reports', publish_comparison_tables))
# TODO: this is copied from the old common_setup, but not tested
# with the new FastDownwardExperiment class!
def add_scatter_plot_step(self, attributes=None):
print 'This has not been tested with the new FastDownwardExperiment class!'
exit(0)
"""Add a step that creates scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revision pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
scatter_dir = os.path.join(self.eval_dir, "scatter")
def is_portfolio(config_nick):
return "fdss" in config_nick
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "%s-%s" % (rev1, config_nick)
algo2 = "%s-%s" % (rev2, config_nick)
report = ScatterPlotReport(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config_nick in self._config_nicks:
if is_portfolio(config_nick):
valid_attributes = [
attr for attr in attributes
if attr in self.PORTFOLIO_ATTRIBUTES]
else:
valid_attributes = attributes
for rev1, rev2 in itertools.combinations(
self.revision_nicks, 2):
for attribute in valid_attributes:
make_scatter_plot(config_nick, rev1, rev2, attribute)
self.add_step(Step("make-scatter-plots", make_scatter_plots))
| 11,089 | 35.843854 | 93 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue638/v1.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os, sys
from lab.environments import LocalEnvironment, MaiaEnvironment
from common_setup import IssueConfig, IssueExperiment, is_test_run
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue638-base", "issue638-v1"]
CONFIGS = [
IssueConfig(heuristic, ["--search", "astar({})".format(heuristic)])
for heuristic in [
"cpdbs(patterns=systematic(3), dominance_pruning=true)",
"cpdbs(patterns=systematic(4), dominance_pruning=true)",
"operatorcounting([pho_constraints(patterns=systematic(3))])",
"operatorcounting([pho_constraints(patterns=systematic(4))])",
]
]
sys.path.append(BENCHMARKS_DIR)
import suites
SUITE = suites.suite_optimal_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_command("parser", ["custom-parser.py"])
exp.add_comparison_table_step(
attributes=exp.DEFAULT_TABLE_ATTRIBUTES +
["num_sga_patterns", "num_interesting_patterns"])
exp.add_scatter_plot_step(attributes=["total_time"])
exp()
| 1,355 | 27.25 | 71 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue638/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab.steps import Step
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import CompareConfigsReport
from downward.reports.scatter import ScatterPlotReport
from relativescatter import RelativeScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return (
"cluster" in node or
node.startswith("gkigrid") or
node in ["habakuk", "turtur"])
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, outfile=outfile)
self.add_step(Step(
'publish-absolute-report', subprocess.call, ['publish', outfile]))
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = CompareConfigsReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.%s" % (
self.name, rev1, rev2, report.output_format))
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
subprocess.call(["publish", outfile])
self.add_step(Step("make-comparison-tables", make_comparison_tables))
self.add_step(Step(
"publish-comparison-tables", publish_comparison_tables))
def add_scatter_plot_step(self, relative=False, attributes=None):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if relative:
report_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
report_class = ScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "{}-{}".format(rev1, config_nick)
algo2 = "{}-{}".format(rev2, config_nick)
report = report_class(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(Step(step_name, make_scatter_plots))
| 11,446 | 33.068452 | 79 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue638/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(
axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows how a specific attribute in two
configurations. The attribute value in config 1 is shown on the
x-axis and the relation to the value in config 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['config'] == self.configs[0] and
run2['config'] == self.configs[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.configs[0], val1)
assert val2 > 0, (domain, problem, self.configs[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlots use log-scaling on the x-axis by default.
default_xscale = 'log'
if self.attribute and self.attribute in self.LINEAR:
default_xscale = 'linear'
PlotReport._set_scales(self, xscale or default_xscale, 'log')
| 3,921 | 35.654206 | 78 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue638/custom-parser.py
|
#! /usr/bin/env python
from lab.parser import Parser
class CustomParser(Parser):
def __init__(self):
Parser.__init__(self)
self.add_pattern(
"num_sga_patterns",
"Found (\d+) SGA patterns.",
required=False,
type=int)
self.add_pattern(
"num_interesting_patterns",
"Found (\d+) interesting patterns.",
required=False,
type=int)
if __name__ == "__main__":
parser = CustomParser()
print "Running custom parser"
parser.parse()
| 562 | 21.52 | 48 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue77/issue77-v4-opt.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import downward.suites
import common_setup
import configs
CONFIGS = configs.default_configs_optimal(ipc=False, extended=False)
print(sorted(CONFIGS.keys()))
print(len(CONFIGS))
SUITE = downward.suites.suite_optimal_with_ipc11()
exp = common_setup.IssueExperiment(
search_revisions=["issue77-v3", "issue77-v4"],
configs=CONFIGS,
suite=SUITE
)
exp.add_absolute_report_step()
exp.add_comparison_table_step()
# exp.add_scatter_plot_step()
exp()
| 512 | 18 | 68 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue77/issue77-v7-sat-eager.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import downward.suites
import common_setup
import configs
NICKS = [
'eager_greedy_alt_ff_cg', 'eager_greedy_ff', 'eager_greedy_ff_no_pref',
'eager_pareto_ff', 'eager_wa3_cg'
]
CONFIGS = {}
for nick in NICKS:
CONFIGS[nick] = configs.default_configs_satisficing(ipc=False, extended=True)[nick]
print(sorted(CONFIGS.keys()))
print(len(CONFIGS))
SUITE = downward.suites.suite_satisficing_with_ipc11()
exp = common_setup.IssueExperiment(
search_revisions=["issue77-v7-base", "issue77-v7"],
configs=CONFIGS,
suite=SUITE
)
exp.add_absolute_report_step()
exp.add_comparison_table_step()
# exp.add_scatter_plot_step()
exp()
| 697 | 20.8125 | 87 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue77/issue77-opt1.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import downward.configs
import downward.suites
# "ipc=False" skips portfolio configurations which we don't need to
# test here.
CONFIGS = downward.configs.default_configs_optimal(ipc=False, extended=True)
# pathmax is gone in this branch, remove it:
for key, value in list(CONFIGS.items()):
for pos, arg in enumerate(value):
if ", pathmax=false" in arg:
value[pos] = arg.replace(", pathmax=false", "")
# selmax is currently disabled
del CONFIGS["astar_selmax_lmcut_lmcount"]
SUITE = downward.suites.suite_optimal_with_ipc11()
import common_setup
exp = common_setup.IssueExperiment(
search_revisions=["issue77-base", "issue77-v2"],
configs=CONFIGS,
suite=SUITE
)
exp.add_absolute_report_step()
exp.add_comparison_table_step()
# exp.add_scatter_plot_step()
exp()
| 856 | 24.205882 | 76 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue77/relative_scatter.py
|
from collections import defaultdict
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport
EPSILON = 0.01
def get_relative_change(val1, val2):
"""
>>> get_relative_change(10, 0)
-999.0
>>> get_relative_change(10, 1)
-9.0
>>> get_relative_change(10, 5)
-1.0
>>> get_relative_change(10, 10)
0.0
>>> get_relative_change(10, 15)
0.5
>>> get_relative_change(10, 20)
1.0
>>> get_relative_change(10, 100)
9.0
>>> get_relative_change(0, 10)
999.0
>>> get_relative_change(0, 0)
0.0
"""
assert val1 >= 0, val1
assert val2 >= 0, val2
if val1 == 0:
val1 = EPSILON
if val2 == 0:
val2 = EPSILON
if val1 > val2:
return 1 - val1 / float(val2)
return val2 / float(val1) - 1
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows 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.
If the value for config 1 is v1 and the value for config 2 is v2,
the plot contains the point (v1, 1 - v1/v2) if v1 > v2 and the
point (v1, v2/v1 - 1) otherwise.
"""
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples.
categories = defaultdict(list)
self.ylim_bottom = 0
self.ylim_top = 0
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 = get_relative_change(val1, val2)
categories[category].append((x, y))
self.ylim_bottom = min(self.ylim_bottom, y)
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom *= 1.1
self.ylim_top *= 1.1
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, 'linear')
| 2,744 | 30.918605 | 72 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue77/issue77-v7-opt.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import downward.suites
import common_setup
import configs
CONFIGS = configs.default_configs_optimal(ipc=False, extended=False)
print(sorted(CONFIGS.keys()))
print(len(CONFIGS))
SUITE = downward.suites.suite_optimal_with_ipc11()
SCATTER_ATTRIBUTES = ["total_time"]
exp = common_setup.IssueExperiment(
search_revisions=["issue77-v7-base", "issue77-v7"],
configs=CONFIGS,
suite=SUITE
)
exp.add_absolute_report_step()
exp.add_comparison_table_step()
exp.add_scatter_plot_step(attributes=SCATTER_ATTRIBUTES, relative=True)
exp()
| 594 | 21.037037 | 71 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue77/issue77-sat1.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import downward.configs
import downward.suites
CONFIGS = downward.configs.default_configs_satisficing(extended=True)
# The following lines remove some configs that we don't currently
# support because the respective configurations are commented out
DISABLED = [
"seq_sat_fdss_1",
"seq_sat_fdss_2",
"seq_sat_lama_2011",
]
for key, value in list(CONFIGS.items()):
if key in DISABLED or key.startswith(("lazy", "iterated", "ehc")):
del CONFIGS[key]
else:
for pos, arg in enumerate(value):
if ", pathmax=false" in arg:
# pathmax is gone in this branch
value[pos] = arg.replace(", pathmax=false", "")
print(sorted(CONFIGS.keys()))
print(len(CONFIGS))
SUITE = downward.suites.suite_satisficing_with_ipc11()
import common_setup
exp = common_setup.IssueExperiment(
search_revisions=["issue77-base", "issue77-v1"],
configs=CONFIGS,
suite=SUITE
)
exp.add_absolute_report_step()
exp.add_comparison_table_step()
# exp.add_scatter_plot_step()
exp()
| 1,088 | 24.325581 | 70 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue77/issue77-v5-sat-lazy.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import downward.suites
import common_setup
import configs
CONFIGS = {}
INCLUDE = ("lazy", "lama")
EXCLUDE = ("lazy_greedy_add", "lazy_greedy_cea", "lazy_greedy_cg")
for key, value in configs.default_configs_satisficing(ipc=False, extended=True).items():
if any(x in key for x in INCLUDE) and not any(x in key for x in EXCLUDE):
CONFIGS[key] = value
print(sorted(CONFIGS.keys()))
print(len(CONFIGS))
SUITE = downward.suites.suite_satisficing_with_ipc11()
exp = common_setup.IssueExperiment(
search_revisions=["issue77-v5-base", "issue77-v5"],
configs=CONFIGS,
suite=SUITE
)
exp.add_absolute_report_step()
exp.add_comparison_table_step()
# exp.add_scatter_plot_step()
exp()
| 753 | 24.133333 | 88 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue77/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
from relative_scatter 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."""
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, relative=False):
"""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"])
Use `relative=True` to create relative scatter plots. ::
exp.add_scatter_plot_step(relative=True)
"""
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
if relative:
scatter_plot_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "relative-scatter")
else:
scatter_plot_class = ScatterPlotReport
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 = scatter_plot_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_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))
| 13,172 | 35.090411 | 79 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue77/issue77-v4-sat-eager.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import downward.suites
import common_setup
import configs
CONFIGS = configs.default_configs_satisficing(ipc=False, extended=False)
# The following lines remove some configs that we don't currently
# support.
DISABLED = [
]
for key, value in list(CONFIGS.items()):
if key in DISABLED or key.startswith(("lazy", "iterated", "ehc")):
del CONFIGS[key]
print(sorted(CONFIGS.keys()))
print(len(CONFIGS))
SUITE = downward.suites.suite_satisficing_with_ipc11()
exp = common_setup.IssueExperiment(
search_revisions=["issue77-v3", "issue77-v4"],
configs=CONFIGS,
suite=SUITE
)
exp.add_absolute_report_step()
exp.add_comparison_table_step()
# exp.add_scatter_plot_step()
exp()
| 750 | 20.457143 | 72 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue77/issue77-v6-sat-ehc.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import downward.suites
import common_setup
CONFIGS = {
"ehc_ff": [
"--search", "ehc(ff())"],
"ehc_add_pref": [
"--heuristic", "hadd=add()", "--search", "ehc(hadd, preferred=[hadd])"],
#"ehc_add_ff_pref": [
# "--search", "ehc(add(), preferred=[ff()],preferred_usage=RANK_PREFERRED_FIRST)"],
}
SUITE = downward.suites.suite_satisficing_with_ipc11()
exp = common_setup.IssueExperiment(
search_revisions=["issue77-v6-base", "issue77-v6"],
configs=CONFIGS,
suite=SUITE
)
exp.add_absolute_report_step()
exp.add_comparison_table_step()
# exp.add_scatter_plot_step()
exp()
| 669 | 22.103448 | 90 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue77/configs.py
|
def configs_optimal_core():
return {
# A*
"astar_blind": [
"--search",
"astar(blind)"],
"astar_h2": [
"--search",
"astar(hm(2))"],
"astar_ipdb": [
"--search",
"astar(ipdb)"],
"astar_lmcount_lm_merged_rhw_hm": [
"--search",
"astar(lmcount(lm_merged([lm_rhw(),lm_hm(m=1)]),admissible=true),mpd=true)"],
"astar_lmcut": [
"--search",
"astar(lmcut)"],
"astar_hmax": [
"--search",
"astar(hmax)"],
"astar_merge_and_shrink_bisim": [
"--search",
"astar(merge_and_shrink("
"merge_strategy=merge_linear(variable_order=reverse_level),"
"shrink_strategy=shrink_bisimulation(max_states=200000,greedy=false,"
"group_by_h=true)))"],
"astar_merge_and_shrink_greedy_bisim": [
"--search",
"astar(merge_and_shrink("
"merge_strategy=merge_linear(variable_order=reverse_level),"
"shrink_strategy=shrink_bisimulation(max_states=infinity,threshold=1,"
"greedy=true,group_by_h=false)))"],
"astar_merge_and_shrink_dfp_bisim": [
"--search",
"astar(merge_and_shrink(merge_strategy=merge_dfp,"
"shrink_strategy=shrink_bisimulation(max_states=50000,threshold=1,"
"greedy=false,group_by_h=true)))"],
#"astar_selmax_lmcut_lmcount": [
# "--search",
# "astar(selmax([lmcut(),lmcount(lm_merged([lm_hm(m=1),lm_rhw()]),"
# "admissible=true)],training_set=1000),mpd=true)"],
}
def configs_satisficing_core():
return {
# A*
"astar_goalcount": [
"--search",
"astar(goalcount)"],
# eager greedy
"eager_greedy_ff": [
"--heuristic",
"h=ff()",
"--search",
"eager_greedy(h, preferred=h)"],
"eager_greedy_add": [
"--heuristic",
"h=add()",
"--search",
"eager_greedy(h, preferred=h)"],
"eager_greedy_cg": [
"--heuristic",
"h=cg()",
"--search",
"eager_greedy(h, preferred=h)"],
"eager_greedy_cea": [
"--heuristic",
"h=cea()",
"--search",
"eager_greedy(h, preferred=h)"],
# lazy greedy
"lazy_greedy_ff": [
"--heuristic",
"h=ff()",
"--search",
"lazy_greedy(h, preferred=h)"],
"lazy_greedy_add": [
"--heuristic",
"h=add()",
"--search",
"lazy_greedy(h, preferred=h)"],
"lazy_greedy_cg": [
"--heuristic",
"h=cg()",
"--search",
"lazy_greedy(h, preferred=h)"],
}
def configs_optimal_ipc():
return {
"seq_opt_merge_and_shrink": ["ipc", "seq-opt-merge-and-shrink"],
"seq_opt_fdss_1": ["ipc", "seq-opt-fdss-1"],
"seq_opt_fdss_2": ["ipc", "seq-opt-fdss-2"],
}
def configs_satisficing_ipc():
return {
"seq_sat_lama_2011": ["ipc", "seq-sat-lama-2011"],
"seq_sat_fdss_1": ["ipc", "seq-sat-fdss-1"],
"seq_sat_fdss_2": ["ipc", "seq-sat-fdss-2"],
}
def configs_optimal_extended():
return {
# A*
"astar_lmcount_lm_merged_rhw_hm_no_order": [
"--search",
"astar(lmcount(lm_merged([lm_rhw(),lm_hm(m=1)]),admissible=true),mpd=true)"],
}
def configs_satisficing_extended():
return {
# eager greedy
"eager_greedy_alt_ff_cg": [
"--heuristic",
"hff=ff()",
"--heuristic",
"hcg=cg()",
"--search",
"eager_greedy(hff,hcg,preferred=[hff,hcg])"],
"eager_greedy_ff_no_pref": [
"--search",
"eager_greedy(ff())"],
# lazy greedy
"lazy_greedy_alt_cea_cg": [
"--heuristic",
"hcea=cea()",
"--heuristic",
"hcg=cg()",
"--search",
"lazy_greedy(hcea,hcg,preferred=[hcea,hcg])"],
"lazy_greedy_ff_no_pref": [
"--search",
"lazy_greedy(ff())"],
"lazy_greedy_cea": [
"--heuristic",
"h=cea()",
"--search",
"lazy_greedy(h, preferred=h)"],
# lazy wA*
"lazy_wa3_ff": [
"--heuristic",
"h=ff()",
"--search",
"lazy_wastar(h,w=3,preferred=h)"],
# eager wA*
"eager_wa3_cg": [
"--heuristic",
"h=cg()",
"--search",
"eager(single(sum([g(),weight(h,3)])),preferred=h)"],
# ehc
"ehc_ff": [
"--search",
"ehc(ff())"],
# iterated
"iterated_wa_ff": [
"--heuristic",
"h=ff()",
"--search",
"iterated([lazy_wastar(h,w=10), lazy_wastar(h,w=5), lazy_wastar(h,w=3),"
"lazy_wastar(h,w=2), lazy_wastar(h,w=1)])"],
# pareto open list
"eager_pareto_ff": [
"--heuristic",
"h=ff()",
"--search",
"eager(pareto([sum([g(), h]), h]), reopen_closed=true,"
"f_eval=sum([g(), h]))"],
# bucket-based open list
"eager_bucket_lmcut": [
"--heuristic",
"h=lmcut()",
"--search",
"eager(single_buckets(h), reopen_closed=true)"],
# LAMA's first iteration
"lama_first": [
"--if-unit-cost",
"--heuristic",
"hlm,hff=lm_ff_syn(lm_rhw(reasonable_orders=true))",
"--search",
"lazy_greedy([hff,hlm],preferred=[hff,hlm])",
"--if-non-unit-cost",
"--heuristic",
"hlm1,hff1=lm_ff_syn(lm_rhw(reasonable_orders=true,"
" lm_cost_type=one,cost_type=one))",
"--heuristic",
"hlm2,hff2=lm_ff_syn(lm_rhw(reasonable_orders=true,"
" lm_cost_type=plusone,cost_type=plusone))",
"--search",
"lazy_greedy([hff1,hlm1],preferred=[hff1,hlm1],"
" cost_type=one,reopen_closed=false)",
"--always"],
}
def default_configs_optimal(core=True, ipc=True, extended=False):
configs = {}
if core:
configs.update(configs_optimal_core())
if ipc:
configs.update(configs_optimal_ipc())
if extended:
configs.update(configs_optimal_extended())
return configs
def default_configs_satisficing(core=True, ipc=True, extended=False):
configs = {}
if core:
configs.update(configs_satisficing_core())
if ipc:
configs.update(configs_satisficing_ipc())
if extended:
configs.update(configs_satisficing_extended())
return configs
| 7,002 | 30.403587 | 89 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue77/issue77-v4-sat-lazy.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import downward.suites
import common_setup
import configs
CONFIGS = configs.default_configs_satisficing(ipc=False, extended=False)
DISABLED = [
]
for key, value in list(CONFIGS.items()):
if not key.startswith("lazy"):
del CONFIGS[key]
print(sorted(CONFIGS.keys()))
print(len(CONFIGS))
SUITE = downward.suites.suite_satisficing_with_ipc11()
exp = common_setup.IssueExperiment(
search_revisions=["issue77-base", "issue77-v4"],
configs=CONFIGS,
suite=SUITE
)
exp.add_absolute_report_step()
exp.add_comparison_table_step()
# exp.add_scatter_plot_step()
exp()
| 638 | 18.96875 | 72 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue77/issue77-sat2.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import common_setup
import downward.suites
# This experiment only tests the Lama-FF synergy, which sat1 did not
# test because it did not work in the issue77 branch.
CONFIGS = {
"synergy":
["--heuristic", "hlm,hff=lm_ff_syn(lm_rhw(reasonable_orders=true))",
"--search", "eager_greedy([hff,hlm],preferred=[hff,hlm])"],
}
SUITE = downward.suites.suite_satisficing_with_ipc11()
exp = common_setup.IssueExperiment(
search_revisions=["issue77-v3-base", "issue77-v3"],
configs=CONFIGS,
suite=SUITE
)
exp.add_absolute_report_step()
exp.add_comparison_table_step()
exp.add_scatter_plot_step()
exp()
| 684 | 24.37037 | 76 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue939/translator_additional_parser.py
|
#!/usr/bin/env python
import hashlib
from lab.parser import Parser
def add_hash_value(content, props):
props['translator_output_sas_hash'] = hashlib.sha512(str(content).encode('utf-8')).hexdigest()
parser = Parser()
parser.add_function(add_hash_value, file="output.sas")
parser.parse()
| 294 | 21.692308 | 98 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue939/base.py
|
#! /usr/bin/env python2
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
EXPNAME = common_setup.get_experiment_name()
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue939-base"]
CONFIGS = [
IssueConfig(
"translate-only",
[],
driver_options=["--translate"])
]
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]")
# This was generated by running "./suites.py all" in the benchmarks
# repository.
SUITE = [
'agricola-opt18-strips',
'agricola-sat18-strips',
'airport',
'airport-adl',
'assembly',
'barman-mco14-strips',
'barman-opt11-strips',
'barman-opt14-strips',
'barman-sat11-strips',
'barman-sat14-strips',
'blocks',
'caldera-opt18-adl',
'caldera-sat18-adl',
'caldera-split-opt18-adl',
'caldera-split-sat18-adl',
'cavediving-14-adl',
'childsnack-opt14-strips',
'childsnack-sat14-strips',
'citycar-opt14-adl',
'citycar-sat14-adl',
'data-network-opt18-strips',
'data-network-sat18-strips',
'depot',
'driverlog',
'elevators-opt08-strips',
'elevators-opt11-strips',
'elevators-sat08-strips',
'elevators-sat11-strips',
'flashfill-sat18-adl',
'floortile-opt11-strips',
'floortile-opt14-strips',
'floortile-sat11-strips',
'floortile-sat14-strips',
'freecell',
'ged-opt14-strips',
'ged-sat14-strips',
'grid',
'gripper',
'hiking-agl14-strips',
'hiking-opt14-strips',
'hiking-sat14-strips',
'logistics00',
'logistics98',
'maintenance-opt14-adl',
'maintenance-sat14-adl',
'miconic',
'miconic-fulladl',
'miconic-simpleadl',
'movie',
'mprime',
'mystery',
'no-mprime',
'no-mystery',
'nomystery-opt11-strips',
'nomystery-sat11-strips',
'nurikabe-opt18-adl',
'nurikabe-sat18-adl',
'openstacks',
'openstacks-agl14-strips',
'openstacks-opt08-adl',
'openstacks-opt08-strips',
'openstacks-opt11-strips',
'openstacks-opt14-strips',
'openstacks-sat08-adl',
'openstacks-sat08-strips',
'openstacks-sat11-strips',
'openstacks-sat14-strips',
'openstacks-strips',
'optical-telegraphs',
'organic-synthesis-opt18-strips',
'organic-synthesis-sat18-strips',
'organic-synthesis-split-opt18-strips',
'organic-synthesis-split-sat18-strips',
'parcprinter-08-strips',
'parcprinter-opt11-strips',
'parcprinter-sat11-strips',
'parking-opt11-strips',
'parking-opt14-strips',
'parking-sat11-strips',
'parking-sat14-strips',
'pathways',
'pathways-noneg',
'pegsol-08-strips',
'pegsol-opt11-strips',
'pegsol-sat11-strips',
'petri-net-alignment-opt18-strips',
'philosophers',
'pipesworld-notankage',
'pipesworld-tankage',
'psr-large',
'psr-middle',
'psr-small',
'rovers',
'satellite',
'scanalyzer-08-strips',
'scanalyzer-opt11-strips',
'scanalyzer-sat11-strips',
'schedule',
'settlers-opt18-adl',
'settlers-sat18-adl',
'snake-opt18-strips',
'snake-sat18-strips',
'sokoban-opt08-strips',
'sokoban-opt11-strips',
'sokoban-sat08-strips',
'sokoban-sat11-strips',
'spider-opt18-strips',
'spider-sat18-strips',
'storage',
'termes-opt18-strips',
'termes-sat18-strips',
'tetris-opt14-strips',
'tetris-sat14-strips',
'thoughtful-mco14-strips',
'thoughtful-sat14-strips',
'tidybot-opt11-strips',
'tidybot-opt14-strips',
'tidybot-sat11-strips',
'tpp',
'transport-opt08-strips',
'transport-opt11-strips',
'transport-opt14-strips',
'transport-sat08-strips',
'transport-sat11-strips',
'transport-sat14-strips',
'trucks',
'trucks-strips',
'visitall-opt11-strips',
'visitall-opt14-strips',
'visitall-sat11-strips',
'visitall-sat14-strips',
'woodworking-opt08-strips',
'woodworking-opt11-strips',
'woodworking-sat08-strips',
'woodworking-sat11-strips',
'zenotravel',
]
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=4)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser("translator_additional_parser.py")
del exp.commands['remove-output-sas']
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_parse_again_step()
exp.add_fetcher(name='fetch')
exp.run_steps()
| 4,843 | 24.361257 | 68 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue939/v1.py
|
#! /usr/bin/env python3
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
import common_setup
from common_setup import IssueConfig, IssueExperiment
EXPNAME = common_setup.get_experiment_name()
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue939-v1"]
CONFIGS = [
IssueConfig(
"translate-only",
[],
driver_options=["--translate"])
]
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]")
# This was generated by running "./suites.py all" in the benchmarks
# repository.
SUITE = [
'agricola-opt18-strips',
'agricola-sat18-strips',
'airport',
'airport-adl',
'assembly',
'barman-mco14-strips',
'barman-opt11-strips',
'barman-opt14-strips',
'barman-sat11-strips',
'barman-sat14-strips',
'blocks',
'caldera-opt18-adl',
'caldera-sat18-adl',
'caldera-split-opt18-adl',
'caldera-split-sat18-adl',
'cavediving-14-adl',
'childsnack-opt14-strips',
'childsnack-sat14-strips',
'citycar-opt14-adl',
'citycar-sat14-adl',
'data-network-opt18-strips',
'data-network-sat18-strips',
'depot',
'driverlog',
'elevators-opt08-strips',
'elevators-opt11-strips',
'elevators-sat08-strips',
'elevators-sat11-strips',
'flashfill-sat18-adl',
'floortile-opt11-strips',
'floortile-opt14-strips',
'floortile-sat11-strips',
'floortile-sat14-strips',
'freecell',
'ged-opt14-strips',
'ged-sat14-strips',
'grid',
'gripper',
'hiking-agl14-strips',
'hiking-opt14-strips',
'hiking-sat14-strips',
'logistics00',
'logistics98',
'maintenance-opt14-adl',
'maintenance-sat14-adl',
'miconic',
'miconic-fulladl',
'miconic-simpleadl',
'movie',
'mprime',
'mystery',
'no-mprime',
'no-mystery',
'nomystery-opt11-strips',
'nomystery-sat11-strips',
'nurikabe-opt18-adl',
'nurikabe-sat18-adl',
'openstacks',
'openstacks-agl14-strips',
'openstacks-opt08-adl',
'openstacks-opt08-strips',
'openstacks-opt11-strips',
'openstacks-opt14-strips',
'openstacks-sat08-adl',
'openstacks-sat08-strips',
'openstacks-sat11-strips',
'openstacks-sat14-strips',
'openstacks-strips',
'optical-telegraphs',
'organic-synthesis-opt18-strips',
'organic-synthesis-sat18-strips',
'organic-synthesis-split-opt18-strips',
'organic-synthesis-split-sat18-strips',
'parcprinter-08-strips',
'parcprinter-opt11-strips',
'parcprinter-sat11-strips',
'parking-opt11-strips',
'parking-opt14-strips',
'parking-sat11-strips',
'parking-sat14-strips',
'pathways',
'pathways-noneg',
'pegsol-08-strips',
'pegsol-opt11-strips',
'pegsol-sat11-strips',
'petri-net-alignment-opt18-strips',
'philosophers',
'pipesworld-notankage',
'pipesworld-tankage',
'psr-large',
'psr-middle',
'psr-small',
'rovers',
'satellite',
'scanalyzer-08-strips',
'scanalyzer-opt11-strips',
'scanalyzer-sat11-strips',
'schedule',
'settlers-opt18-adl',
'settlers-sat18-adl',
'snake-opt18-strips',
'snake-sat18-strips',
'sokoban-opt08-strips',
'sokoban-opt11-strips',
'sokoban-sat08-strips',
'sokoban-sat11-strips',
'spider-opt18-strips',
'spider-sat18-strips',
'storage',
'termes-opt18-strips',
'termes-sat18-strips',
'tetris-opt14-strips',
'tetris-sat14-strips',
'thoughtful-mco14-strips',
'thoughtful-sat14-strips',
'tidybot-opt11-strips',
'tidybot-opt14-strips',
'tidybot-sat11-strips',
'tpp',
'transport-opt08-strips',
'transport-opt11-strips',
'transport-opt14-strips',
'transport-sat08-strips',
'transport-sat11-strips',
'transport-sat14-strips',
'trucks',
'trucks-strips',
'visitall-opt11-strips',
'visitall-opt14-strips',
'visitall-sat11-strips',
'visitall-sat14-strips',
'woodworking-opt08-strips',
'woodworking-opt11-strips',
'woodworking-sat08-strips',
'woodworking-sat11-strips',
'zenotravel',
]
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=4)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser("translator_additional_parser.py")
del exp.commands['remove-output-sas']
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_parse_again_step()
exp.add_fetcher(name='fetch')
exp.run_steps()
| 4,841 | 24.350785 | 68 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue939/fetch.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from collections import defaultdict
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from lab.experiment import Experiment
from downward.reports import PlanningReport
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import ComparativeReport
import common_setup
DIR = os.path.dirname(os.path.abspath(__file__))
ENVIRONMENT = BaselSlurmEnvironment(
partition="infai_2",
email="[email protected]")
if common_setup.is_test_run():
ENVIRONMENT = LocalEnvironment(processes=4)
exp = Experiment()
class TranslatorDiffReport(PlanningReport):
def get_cell(self, run):
return ";".join(run.get(attr) for attr in self.attributes)
def get_text(self):
lines = []
for runs in self.problem_runs.values():
hashes = set([r.get("translator_output_sas_hash") for r in runs])
if len(hashes) > 1 or None in hashes:
lines.append(";".join([self.get_cell(r) for r in runs]))
return "\n".join(lines)
class SameValueFilters(object):
"""Ignore runs for a task where all algorithms have the same value."""
def __init__(self, attribute):
self._attribute = attribute
self._tasks_to_values = defaultdict(list)
def _get_task(self, run):
return (run['domain'], run['problem'])
def store_values(self, run):
value = run.get(self._attribute)
self._tasks_to_values[self._get_task(run)].append(value)
# Don't filter this run, yet.
return True
def filter_tasks_with_equal_values(self, run):
values = self._tasks_to_values[self._get_task(run)]
return len(set(values)) != 1
exp.add_fetcher(src='data/issue939-base-eval')
exp.add_fetcher(src='data/issue939-v1-eval', merge=True)
ATTRIBUTES = ["error", "run_dir", "translator_*", "translator_output_sas_hash"]
#exp.add_comparison_table_step(attributes=ATTRIBUTES)
same_value_filters = SameValueFilters("translator_output_sas_hash")
# exp.add_comparison_table_step(
# name="filtered",
# attributes=ATTRIBUTES,
# filter=[same_value_filters.store_values, same_value_filters.filter_tasks_with_equal_values])
exp.add_report(TranslatorDiffReport(
attributes=["domain", "problem", "algorithm", "run_dir"]
), outfile="different_output_sas.csv"
)
exp.add_report(AbsoluteReport(attributes=ATTRIBUTES))
exp.add_report(ComparativeReport([
('issue939-base-translate-only', 'issue939-v1-translate-only')
], attributes=ATTRIBUTES))
exp.run_steps()
| 2,598 | 29.576471 | 98 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue939/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import ComparativeReport
from downward.reports.scatter import ScatterPlotReport
from relativescatter import RelativeScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
DEFAULT_OPTIMAL_SUITE = [
'agricola-opt18-strips', 'airport', 'barman-opt11-strips',
'barman-opt14-strips', 'blocks', 'childsnack-opt14-strips',
'data-network-opt18-strips', 'depot', 'driverlog',
'elevators-opt08-strips', 'elevators-opt11-strips',
'floortile-opt11-strips', 'floortile-opt14-strips', 'freecell',
'ged-opt14-strips', 'grid', 'gripper', 'hiking-opt14-strips',
'logistics00', 'logistics98', 'miconic', 'movie', 'mprime',
'mystery', 'nomystery-opt11-strips', 'openstacks-opt08-strips',
'openstacks-opt11-strips', 'openstacks-opt14-strips',
'openstacks-strips', 'organic-synthesis-opt18-strips',
'organic-synthesis-split-opt18-strips', 'parcprinter-08-strips',
'parcprinter-opt11-strips', 'parking-opt11-strips',
'parking-opt14-strips', 'pathways-noneg', 'pegsol-08-strips',
'pegsol-opt11-strips', 'petri-net-alignment-opt18-strips',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-small', 'rovers',
'satellite', 'scanalyzer-08-strips', 'scanalyzer-opt11-strips',
'snake-opt18-strips', 'sokoban-opt08-strips',
'sokoban-opt11-strips', 'spider-opt18-strips', 'storage',
'termes-opt18-strips', 'tetris-opt14-strips',
'tidybot-opt11-strips', 'tidybot-opt14-strips', 'tpp',
'transport-opt08-strips', 'transport-opt11-strips',
'transport-opt14-strips', 'trucks-strips', 'visitall-opt11-strips',
'visitall-opt14-strips', 'woodworking-opt08-strips',
'woodworking-opt11-strips', 'zenotravel']
DEFAULT_SATISFICING_SUITE = [
'agricola-sat18-strips', 'airport', 'assembly',
'barman-sat11-strips', 'barman-sat14-strips', 'blocks',
'caldera-sat18-adl', 'caldera-split-sat18-adl', 'cavediving-14-adl',
'childsnack-sat14-strips', 'citycar-sat14-adl',
'data-network-sat18-strips', 'depot', 'driverlog',
'elevators-sat08-strips', 'elevators-sat11-strips',
'flashfill-sat18-adl', 'floortile-sat11-strips',
'floortile-sat14-strips', 'freecell', 'ged-sat14-strips', 'grid',
'gripper', 'hiking-sat14-strips', 'logistics00', 'logistics98',
'maintenance-sat14-adl', 'miconic', 'miconic-fulladl',
'miconic-simpleadl', 'movie', 'mprime', 'mystery',
'nomystery-sat11-strips', 'nurikabe-sat18-adl', 'openstacks',
'openstacks-sat08-adl', 'openstacks-sat08-strips',
'openstacks-sat11-strips', 'openstacks-sat14-strips',
'openstacks-strips', 'optical-telegraphs',
'organic-synthesis-sat18-strips',
'organic-synthesis-split-sat18-strips', 'parcprinter-08-strips',
'parcprinter-sat11-strips', 'parking-sat11-strips',
'parking-sat14-strips', 'pathways', 'pathways-noneg',
'pegsol-08-strips', 'pegsol-sat11-strips', 'philosophers',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-large',
'psr-middle', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-sat11-strips', 'schedule',
'settlers-sat18-adl', 'snake-sat18-strips', 'sokoban-sat08-strips',
'sokoban-sat11-strips', 'spider-sat18-strips', 'storage',
'termes-sat18-strips', 'tetris-sat14-strips',
'thoughtful-sat14-strips', 'tidybot-sat11-strips', 'tpp',
'transport-sat08-strips', 'transport-sat11-strips',
'transport-sat14-strips', 'trucks', 'trucks-strips',
'visitall-sat11-strips', 'visitall-sat14-strips',
'woodworking-sat08-strips', 'woodworking-sat11-strips',
'zenotravel']
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return node.endswith(".scicore.unibas.ch") or node.endswith(".cluster.bc2.ch")
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["depot:p01.pddl", "gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"planner_memory",
"planner_time",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, outfile=outfile)
self.add_step(
'publish-absolute-report', subprocess.call, ['publish', outfile])
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = ComparativeReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.%s" % (
self.name, rev1, rev2, report.output_format))
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
subprocess.call(["publish", outfile])
self.add_step("make-comparison-tables", make_comparison_tables)
self.add_step(
"publish-comparison-tables", publish_comparison_tables)
def add_scatter_plot_step(self, relative=False, attributes=None):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if relative:
report_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
report_class = ScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print("Make scatter plot for", name)
algo1 = get_algo_nick(rev1, config_nick)
algo2 = get_algo_nick(rev2, config_nick)
report = report_class(
filter_algorithm=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"])
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(step_name, make_scatter_plots)
| 14,744 | 36.423858 | 82 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue939/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(
axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows a relative comparison of two
algorithms with regard to the given attribute. The attribute value
of algorithm 1 is shown on the x-axis and the relation to the value
of algorithm 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['algorithm'] == self.algorithms[0] and
run2['algorithm'] == self.algorithms[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.algorithms[0], val1)
assert val2 > 0, (domain, problem, self.algorithms[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlot uses log-scaling on the x-axis by default.
PlotReport._set_scales(
self, xscale or self.attribute.scale or 'log', 'log')
| 3,875 | 35.566038 | 78 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue717/v2.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, MaiaEnvironment
from downward.reports.compare import ComparativeReport
from common_setup import IssueConfig, IssueExperiment, is_test_run
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue717-v2"]
CONFIGS = [
IssueConfig(
"lama-first-original", [], driver_options=["--alias", "lama-first"])
] + [
IssueConfig(
"lama-first-new", [], driver_options=["--alias", "lama-first-new"])
] + [
IssueConfig(
"lama-original", [], driver_options=["--alias", "seq-sat-lama-2011"])
] + [
IssueConfig(
"lama-new", [], driver_options=["--alias", "seq-sat-lama-2011-new"])
]
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=4)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_absolute_report_step()
algorithm_pairs = [
('issue717-v2-lama-first-original', 'issue717-v2-lama-first-new', 'Diff lama-first'),
('issue717-v2-lama-original', 'issue717-v2-lama-new', 'Diff lama')]
exp.add_report(ComparativeReport(
algorithm_pairs,
attributes=IssueExperiment.DEFAULT_TABLE_ATTRIBUTES))
exp.add_scatter_plot_step(attributes=["total_time", "memory"])
exp.run_steps()
| 2,981 | 36.746835 | 89 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue717/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 as CompareConfigsReport
from downward.reports.scatter import ScatterPlotReport
from relativescatter import RelativeScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return (
"cluster" in node or
node.startswith("gkigrid") or
node in ["habakuk", "turtur"])
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, outfile=outfile)
self.add_step(Step(
'publish-absolute-report', subprocess.call, ['publish', outfile]))
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = CompareConfigsReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.%s" % (
self.name, rev1, rev2, report.output_format))
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
subprocess.call(["publish", outfile])
self.add_step(Step("make-comparison-tables", make_comparison_tables))
self.add_step(Step(
"publish-comparison-tables", publish_comparison_tables))
def add_scatter_plot_step(self, relative=False, attributes=None):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if relative:
report_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
report_class = ScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "{}-{}".format(rev1, config_nick)
algo2 = "{}-{}".format(rev2, config_nick)
report = report_class(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(Step(step_name, make_scatter_plots))
| 11,467 | 33.130952 | 79 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue717/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(
axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows how a specific attribute in two
configurations. The attribute value in config 1 is shown on the
x-axis and the relation to the value in config 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['config'] == self.configs[0] and
run2['config'] == self.configs[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.configs[0], val1)
assert val2 > 0, (domain, problem, self.configs[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlots use log-scaling on the x-axis by default.
default_xscale = 'log'
if self.attribute and self.attribute in self.LINEAR:
default_xscale = 'linear'
PlotReport._set_scales(self, xscale or default_xscale, 'log')
| 3,921 | 35.654206 | 78 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue717/lama-synergy.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 = ["issue717-base"]
CONFIGS = [
IssueConfig(
"lama-first-original", [], driver_options=["--alias", "lama-first"])
] + [
IssueConfig(
"lama-first-new", [], driver_options=["--alias", "lama-first-new"])
]
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(attributes=["total_time", "memory"])
exp()
| 2,451 | 37.3125 | 76 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue905/parser.py
|
#! /usr/bin/env python
import logging
import re
from lab.parser import Parser
class CommonParser(Parser):
def add_difference(self, diff, val1, val2):
def diff_func(content, props):
if props.get(val1) is None or props.get(val2) is None:
diff_val = None
else:
diff_val = props.get(val1) - props.get(val2)
props[diff] = diff_val
self.add_function(diff_func)
def _get_flags(self, flags_string):
flags = 0
for char in flags_string:
flags |= getattr(re, char)
return flags
def add_repeated_pattern(
self, name, regex, file="run.log", required=False, type=int,
flags=""):
def find_all_occurences(content, props):
matches = re.findall(regex, content, flags=self._get_flags(flags))
if required and not matches:
logging.error("Pattern {0} not found in file {1}".format(regex, file))
props[name] = [type(m) for m in matches]
self.add_function(find_all_occurences, file=file)
def add_pattern(self, name, regex, file="run.log", required=False, type=int, flags=""):
Parser.add_pattern(self, name, regex, file=file, required=required, type=type, flags=flags)
def add_bottom_up_pattern(self, name, regex, file="run.log", required=True, type=int, flags=""):
def search_from_bottom(content, props):
reversed_content = "\n".join(reversed(content.splitlines()))
match = re.search(regex, reversed_content, flags=self._get_flags(flags))
if required and not match:
logging.error("Pattern {0} not found in file {1}".format(regex, file))
if match:
props[name] = type(match.group(1))
self.add_function(search_from_bottom, file=file)
def no_search(content, props):
if "search_start_time" not in props:
error = props.get("error")
if error is not None and error != "incomplete-search-found-no-plan":
props["error"] = "no-search-due-to-" + error
REFINEMENT_ATTRIBUTES = [
("time_for_finding_traces", r"Time for finding abstract traces: (.+)s"),
("time_for_finding_flaws", r"Time for finding flaws: (.+)s"),
("time_for_splitting_states", r"Time for splitting states: (.+)s"),
]
def compute_total_times(content, props):
for attribute, pattern in REFINEMENT_ATTRIBUTES:
props["total_" + attribute] = sum(props[attribute])
def add_time_analysis(content, props):
init_time = props.get("init_time")
if not init_time:
return
parts = []
parts.append("{init_time:.2f}:".format(**props))
for attribute, pattern in REFINEMENT_ATTRIBUTES:
time = props["total_" + attribute]
relative_time = time / init_time
print time, type(time)
parts.append("{:.2f} ({:.2f})".format(time, relative_time))
props["time_analysis"] = " ".join(parts)
def main():
parser = CommonParser()
parser.add_pattern("search_start_time", r"\[g=0, 1 evaluated, 0 expanded, t=(.+)s, \d+ KB\]", type=float)
parser.add_pattern("search_start_memory", r"\[g=0, 1 evaluated, 0 expanded, t=.+s, (\d+) KB\]", type=int)
parser.add_pattern("init_time", r"Time for initializing additive Cartesian heuristic: (.+)s", type=float)
parser.add_pattern("cartesian_states", r"^Cartesian states: (\d+)\n", type=int)
for attribute, pattern in REFINEMENT_ATTRIBUTES:
parser.add_repeated_pattern(attribute, pattern, type=float, required=False)
parser.add_function(no_search)
parser.add_function(compute_total_times)
parser.add_function(add_time_analysis)
parser.parse()
if __name__ == "__main__":
main()
| 3,743 | 34.657143 | 109 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue905/v1.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import itertools
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from downward.reports.compare import ComparativeReport
import common_setup
from common_setup import IssueConfig, IssueExperiment
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
SCRIPT_NAME = os.path.splitext(os.path.basename(__file__))[0]
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue905-base", "issue905-v1"]
CONFIGS = [
IssueConfig("cegar-original-1M", ["--search", "astar(cegar(subtasks=[original()], max_transitions=1M, max_time=infinity))"]),
IssueConfig("cegar-lm-goals-1M", ["--search", "astar(cegar(subtasks=[landmarks(), goals()], max_transitions=1M, max_time=infinity))"]),
IssueConfig("cegar-original-900s", ["--search", "astar(cegar(subtasks=[original()], max_transitions=infinity, max_time=900))"]),
IssueConfig("cegar-lm-goals-900s", ["--search", "astar(cegar(subtasks=[landmarks(), goals()], max_transitions=infinity, max_time=900))"]),
]
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.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser(os.path.join(DIR, "parser.py"))
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
REFINEMENT_ATTRIBUTES = [
"time_for_finding_traces",
"time_for_finding_flaws",
"time_for_splitting_states",
]
attributes = (
IssueExperiment.DEFAULT_TABLE_ATTRIBUTES +
["search_start_memory", "init_time", "time_analysis"] +
["total_" + attr for attr in REFINEMENT_ATTRIBUTES])
#exp.add_absolute_report_step(attributes=attributes)
exp.add_comparison_table_step(attributes=attributes)
exp.add_scatter_plot_step(relative=True, attributes=["init_time", "search_time", "total_time"])
exp.run_steps()
| 2,333 | 34.363636 | 142 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue905/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import ComparativeReport
from downward.reports.scatter import ScatterPlotReport
from relativescatter import RelativeScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
DEFAULT_OPTIMAL_SUITE = [
'agricola-opt18-strips', 'airport', 'barman-opt11-strips',
'barman-opt14-strips', 'blocks', 'childsnack-opt14-strips',
'data-network-opt18-strips', 'depot', 'driverlog',
'elevators-opt08-strips', 'elevators-opt11-strips',
'floortile-opt11-strips', 'floortile-opt14-strips', 'freecell',
'ged-opt14-strips', 'grid', 'gripper', 'hiking-opt14-strips',
'logistics00', 'logistics98', 'miconic', 'movie', 'mprime',
'mystery', 'nomystery-opt11-strips', 'openstacks-opt08-strips',
'openstacks-opt11-strips', 'openstacks-opt14-strips',
'openstacks-strips', 'organic-synthesis-opt18-strips',
'organic-synthesis-split-opt18-strips', 'parcprinter-08-strips',
'parcprinter-opt11-strips', 'parking-opt11-strips',
'parking-opt14-strips', 'pathways-noneg', 'pegsol-08-strips',
'pegsol-opt11-strips', 'petri-net-alignment-opt18-strips',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-small', 'rovers',
'satellite', 'scanalyzer-08-strips', 'scanalyzer-opt11-strips',
'snake-opt18-strips', 'sokoban-opt08-strips',
'sokoban-opt11-strips', 'spider-opt18-strips', 'storage',
'termes-opt18-strips', 'tetris-opt14-strips',
'tidybot-opt11-strips', 'tidybot-opt14-strips', 'tpp',
'transport-opt08-strips', 'transport-opt11-strips',
'transport-opt14-strips', 'trucks-strips', 'visitall-opt11-strips',
'visitall-opt14-strips', 'woodworking-opt08-strips',
'woodworking-opt11-strips', 'zenotravel']
DEFAULT_SATISFICING_SUITE = [
'agricola-sat18-strips', 'airport', 'assembly',
'barman-sat11-strips', 'barman-sat14-strips', 'blocks',
'caldera-sat18-adl', 'caldera-split-sat18-adl', 'cavediving-14-adl',
'childsnack-sat14-strips', 'citycar-sat14-adl',
'data-network-sat18-strips', 'depot', 'driverlog',
'elevators-sat08-strips', 'elevators-sat11-strips',
'flashfill-sat18-adl', 'floortile-sat11-strips',
'floortile-sat14-strips', 'freecell', 'ged-sat14-strips', 'grid',
'gripper', 'hiking-sat14-strips', 'logistics00', 'logistics98',
'maintenance-sat14-adl', 'miconic', 'miconic-fulladl',
'miconic-simpleadl', 'movie', 'mprime', 'mystery',
'nomystery-sat11-strips', 'nurikabe-sat18-adl', 'openstacks',
'openstacks-sat08-adl', 'openstacks-sat08-strips',
'openstacks-sat11-strips', 'openstacks-sat14-strips',
'openstacks-strips', 'optical-telegraphs',
'organic-synthesis-sat18-strips',
'organic-synthesis-split-sat18-strips', 'parcprinter-08-strips',
'parcprinter-sat11-strips', 'parking-sat11-strips',
'parking-sat14-strips', 'pathways', 'pathways-noneg',
'pegsol-08-strips', 'pegsol-sat11-strips', 'philosophers',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-large',
'psr-middle', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-sat11-strips', 'schedule',
'settlers-sat18-adl', 'snake-sat18-strips', 'sokoban-sat08-strips',
'sokoban-sat11-strips', 'spider-sat18-strips', 'storage',
'termes-sat18-strips', 'tetris-sat14-strips',
'thoughtful-sat14-strips', 'tidybot-sat11-strips', 'tpp',
'transport-sat08-strips', 'transport-sat11-strips',
'transport-sat14-strips', 'trucks', 'trucks-strips',
'visitall-sat11-strips', 'visitall-sat14-strips',
'woodworking-sat08-strips', 'woodworking-sat11-strips',
'zenotravel']
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return node.endswith(".scicore.unibas.ch") or node.endswith(".cluster.bc2.ch")
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["depot:p01.pddl", "gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"planner_memory",
"planner_time",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, outfile=outfile)
self.add_step(
'publish-absolute-report', subprocess.call, ['publish', outfile])
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = ComparativeReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.%s" % (
self.name, rev1, rev2, report.output_format))
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
subprocess.call(["publish", outfile])
self.add_step("make-comparison-tables", make_comparison_tables)
self.add_step(
"publish-comparison-tables", publish_comparison_tables)
def add_scatter_plot_step(self, relative=False, attributes=None):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if relative:
report_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
report_class = ScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = get_algo_nick(rev1, config_nick)
algo2 = get_algo_nick(rev2, config_nick)
report = report_class(
filter_algorithm=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"])
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(step_name, make_scatter_plots)
| 14,743 | 36.42132 | 82 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue905/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(
axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows a relative comparison of two
algorithms with regard to the given attribute. The attribute value
of algorithm 1 is shown on the x-axis and the relation to the value
of algorithm 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['algorithm'] == self.algorithms[0] and
run2['algorithm'] == self.algorithms[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if not val1 or not val2:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.algorithms[0], val1)
assert val2 > 0, (domain, problem, self.algorithms[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlot uses log-scaling on the x-axis by default.
PlotReport._set_scales(
self, xscale or self.attribute.scale or 'log', 'log')
| 3,867 | 35.490566 | 78 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue736/translator_additional_parser.py
|
#!/usr/bin/env python
import hashlib
from lab.parser import Parser
def add_hash_value(content, props):
props['translator_output_sas_xz_hash'] = hashlib.sha512(content).hexdigest()
parser = Parser()
parser.add_function(add_hash_value, file="output.sas.xz")
parser.parse()
| 279 | 20.538462 | 80 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue736/v1.py
|
#! /usr/bin/env python2
# -*- coding: utf-8 -*-
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from lab import tools
from downward.reports.compare import ComparativeReport
from downward.reports import PlanningReport
import common_setup
from common_setup import IssueConfig, IssueExperiment
DIR = os.path.dirname(os.path.abspath(__file__))
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue736-base", "issue736-v1"]
CONFIGS = [
IssueConfig(
"translate-only",
[],
driver_options=["--translate"])
]
SUITE = set(common_setup.DEFAULT_OPTIMAL_SUITE + common_setup.DEFAULT_SATISFICING_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,
)
del exp.commands["parse-search"]
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_resource("translator_additional_parser", "translator_additional_parser.py", dest="translator_additional_parser.py")
exp.add_command("translator_additional_parser", ["{translator_additional_parser}"])
class TranslatorDiffReport(PlanningReport):
def get_cell(self, run):
return ";".join(run.get(attr) for attr in self.attributes)
def get_text(self):
lines = []
for runs in self.problem_runs.values():
hashes = set([r.get("translator_output_sas_xz_hash") for r in runs])
if len(hashes) > 1 or None in hashes:
lines.append(";".join([self.get_cell(r) for r in runs]))
return "\n".join(lines)
exp.add_report(TranslatorDiffReport(
attributes=["domain", "problem", "algorithm", "run_dir"]
), outfile="different_output_sas.csv"
)
exp.run_steps()
| 1,887 | 29.451613 | 123 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue736/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import ComparativeReport
from downward.reports.scatter import ScatterPlotReport
from relativescatter import RelativeScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
DEFAULT_OPTIMAL_SUITE = [
'airport', 'barman-opt11-strips', 'barman-opt14-strips', 'blocks',
'childsnack-opt14-strips', 'depot', 'driverlog',
'elevators-opt08-strips', 'elevators-opt11-strips',
'floortile-opt11-strips', 'floortile-opt14-strips', 'freecell',
'ged-opt14-strips', 'grid', 'gripper', 'hiking-opt14-strips',
'logistics00', 'logistics98', 'miconic', 'movie', 'mprime',
'mystery', 'nomystery-opt11-strips', 'openstacks-opt08-strips',
'openstacks-opt11-strips', 'openstacks-opt14-strips',
'openstacks-strips', 'parcprinter-08-strips',
'parcprinter-opt11-strips', 'parking-opt11-strips',
'parking-opt14-strips', 'pathways-noneg', 'pegsol-08-strips',
'pegsol-opt11-strips', 'pipesworld-notankage',
'pipesworld-tankage', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-opt11-strips',
'sokoban-opt08-strips', 'sokoban-opt11-strips', 'storage',
'tetris-opt14-strips', 'tidybot-opt11-strips',
'tidybot-opt14-strips', 'tpp', 'transport-opt08-strips',
'transport-opt11-strips', 'transport-opt14-strips',
'trucks-strips', 'visitall-opt11-strips', 'visitall-opt14-strips',
'woodworking-opt08-strips', 'woodworking-opt11-strips',
'zenotravel']
DEFAULT_SATISFICING_SUITE = [
'airport', 'assembly', 'barman-sat11-strips',
'barman-sat14-strips', 'blocks', 'cavediving-14-adl',
'childsnack-sat14-strips', 'citycar-sat14-adl', 'depot',
'driverlog', 'elevators-sat08-strips', 'elevators-sat11-strips',
'floortile-sat11-strips', 'floortile-sat14-strips', 'freecell',
'ged-sat14-strips', 'grid', 'gripper', 'hiking-sat14-strips',
'logistics00', 'logistics98', 'maintenance-sat14-adl', 'miconic',
'miconic-fulladl', 'miconic-simpleadl', 'movie', 'mprime',
'mystery', 'nomystery-sat11-strips', 'openstacks',
'openstacks-sat08-adl', 'openstacks-sat08-strips',
'openstacks-sat11-strips', 'openstacks-sat14-strips',
'openstacks-strips', 'optical-telegraphs', 'parcprinter-08-strips',
'parcprinter-sat11-strips', 'parking-sat11-strips',
'parking-sat14-strips', 'pathways', 'pathways-noneg',
'pegsol-08-strips', 'pegsol-sat11-strips', 'philosophers',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-large',
'psr-middle', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-sat11-strips', 'schedule',
'sokoban-sat08-strips', 'sokoban-sat11-strips', 'storage',
'tetris-sat14-strips', 'thoughtful-sat14-strips',
'tidybot-sat11-strips', 'tpp', 'transport-sat08-strips',
'transport-sat11-strips', 'transport-sat14-strips', 'trucks',
'trucks-strips', 'visitall-sat11-strips', 'visitall-sat14-strips',
'woodworking-sat08-strips', 'woodworking-sat11-strips',
'zenotravel']
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return (
"cluster" in node or
node.startswith("gkigrid") or
node in ["habakuk", "turtur"])
def is_running_on_cluster_login_node():
return platform.node() == "login20.cluster.bc2.ch"
def can_publish():
return is_running_on_cluster_login_node() or not is_running_on_cluster()
def publish(report_file):
if can_publish():
subprocess.call(["publish", report_file])
else:
print "publishing reports is not supported on this node"
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, name="make-absolute-report", outfile=outfile)
self.add_step("publish-absolute-report", publish, outfile)
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def get_revision_pairs_and_files():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
yield (rev1, rev2, outfile)
def make_comparison_tables():
for rev1, rev2, outfile in get_revision_pairs_and_files():
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = ComparativeReport(compared_configs, **kwargs)
report(self.eval_dir, outfile)
def publish_comparison_tables():
for _, _, outfile in get_revision_pairs_and_files():
publish(outfile)
self.add_step("make-comparison-tables", make_comparison_tables)
self.add_step("publish-comparison-tables", publish_comparison_tables)
def add_scatter_plot_step(self, relative=False, attributes=None):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if relative:
report_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
report_class = ScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "{}-{}".format(rev1, config_nick)
algo2 = "{}-{}".format(rev2, config_nick)
report = report_class(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(step_name, make_scatter_plots)
| 14,462 | 35.24812 | 79 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue736/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(
axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows a relative comparison of two
algorithms with regard to the given attribute. The attribute value
of algorithm 1 is shown on the x-axis and the relation to the value
of algorithm 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['algorithm'] == self.algorithms[0] and
run2['algorithm'] == self.algorithms[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.algorithms[0], val1)
assert val2 > 0, (domain, problem, self.algorithms[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlot uses log-scaling on the x-axis by default.
PlotReport._set_scales(
self, xscale or self.attribute.scale or 'log', 'log')
| 3,875 | 35.566038 | 78 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue835/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 = ["issue835-base", "issue835-v1"]
CONFIGS = [
IssueConfig('lama-first', [], driver_options=['--alias', 'lama-first', '--overall-time-limit', '5m']),
]
SUITE = common_setup.DEFAULT_SATISFICING_SUITE
ENVIRONMENT = BaselSlurmEnvironment(email="[email protected]")
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=4)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
exp.add_comparison_table_step()
exp.run_steps()
| 1,214 | 26.613636 | 106 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue835/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import ComparativeReport
from downward.reports.scatter import ScatterPlotReport
from relativescatter import RelativeScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
DEFAULT_OPTIMAL_SUITE = [
'airport', 'barman-opt11-strips', 'barman-opt14-strips', 'blocks',
'childsnack-opt14-strips', 'depot', 'driverlog',
'elevators-opt08-strips', 'elevators-opt11-strips',
'floortile-opt11-strips', 'floortile-opt14-strips', 'freecell',
'ged-opt14-strips', 'grid', 'gripper', 'hiking-opt14-strips',
'logistics00', 'logistics98', 'miconic', 'movie', 'mprime',
'mystery', 'nomystery-opt11-strips', 'openstacks-opt08-strips',
'openstacks-opt11-strips', 'openstacks-opt14-strips',
'openstacks-strips', 'parcprinter-08-strips',
'parcprinter-opt11-strips', 'parking-opt11-strips',
'parking-opt14-strips', 'pathways-noneg', 'pegsol-08-strips',
'pegsol-opt11-strips', 'pipesworld-notankage',
'pipesworld-tankage', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-opt11-strips',
'sokoban-opt08-strips', 'sokoban-opt11-strips', 'storage',
'tetris-opt14-strips', 'tidybot-opt11-strips',
'tidybot-opt14-strips', 'tpp', 'transport-opt08-strips',
'transport-opt11-strips', 'transport-opt14-strips',
'trucks-strips', 'visitall-opt11-strips', 'visitall-opt14-strips',
'woodworking-opt08-strips', 'woodworking-opt11-strips',
'zenotravel']
DEFAULT_SATISFICING_SUITE = [
'airport', 'assembly', 'barman-sat11-strips',
'barman-sat14-strips', 'blocks', 'cavediving-14-adl',
'childsnack-sat14-strips', 'citycar-sat14-adl', 'depot',
'driverlog', 'elevators-sat08-strips', 'elevators-sat11-strips',
'floortile-sat11-strips', 'floortile-sat14-strips', 'freecell',
'ged-sat14-strips', 'grid', 'gripper', 'hiking-sat14-strips',
'logistics00', 'logistics98', 'maintenance-sat14-adl', 'miconic',
'miconic-fulladl', 'miconic-simpleadl', 'movie', 'mprime',
'mystery', 'nomystery-sat11-strips', 'openstacks',
'openstacks-sat08-adl', 'openstacks-sat08-strips',
'openstacks-sat11-strips', 'openstacks-sat14-strips',
'openstacks-strips', 'optical-telegraphs', 'parcprinter-08-strips',
'parcprinter-sat11-strips', 'parking-sat11-strips',
'parking-sat14-strips', 'pathways', 'pathways-noneg',
'pegsol-08-strips', 'pegsol-sat11-strips', 'philosophers',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-large',
'psr-middle', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-sat11-strips', 'schedule',
'sokoban-sat08-strips', 'sokoban-sat11-strips', 'storage',
'tetris-sat14-strips', 'thoughtful-sat14-strips',
'tidybot-sat11-strips', 'tpp', 'transport-sat08-strips',
'transport-sat11-strips', 'transport-sat14-strips', 'trucks',
'trucks-strips', 'visitall-sat11-strips', 'visitall-sat14-strips',
'woodworking-sat08-strips', 'woodworking-sat11-strips',
'zenotravel']
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return node.endswith(".scicore.unibas.ch") or node.endswith(".cluster.bc2.ch")
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["depot:p01.pddl", "gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, outfile=outfile)
self.add_step(
'publish-absolute-report', subprocess.call, ['publish', outfile])
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = ComparativeReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.%s" % (
self.name, rev1, rev2, report.output_format))
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
subprocess.call(["publish", outfile])
self.add_step("make-comparison-tables", make_comparison_tables)
self.add_step(
"publish-comparison-tables", publish_comparison_tables)
def add_scatter_plot_step(self, relative=False, attributes=None):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if relative:
report_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
report_class = ScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "{}-{}".format(rev1, config_nick)
algo2 = "{}-{}".format(rev2, config_nick)
report = report_class(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(step_name, make_scatter_plots)
| 14,153 | 35.955614 | 82 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue835/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(
axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows a relative comparison of two
algorithms with regard to the given attribute. The attribute value
of algorithm 1 is shown on the x-axis and the relation to the value
of algorithm 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['algorithm'] == self.algorithms[0] and
run2['algorithm'] == self.algorithms[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.algorithms[0], val1)
assert val2 > 0, (domain, problem, self.algorithms[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlot uses log-scaling on the x-axis by default.
PlotReport._set_scales(
self, xscale or self.attribute.scale or 'log', 'log')
| 3,875 | 35.566038 | 78 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue214/issue214.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward.suites import suite_optimal_with_ipc11
from downward.configs import default_configs_optimal
from downward.reports.scatter import ScatterPlotReport
import common_setup
REVS = ["issue214-base", "issue214-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
exp = common_setup.MyExperiment(
grid_priority=PRIORITY,
revisions=REVS,
configs=CONFIGS,
suite=SUITE,
parsers=['state_size_parser.py'],
)
exp.add_comparison_table_step(
attributes=common_setup.MyExperiment.DEFAULT_TABLE_ATTRIBUTES + ['bytes_per_state', 'variables', 'state_var_t_size']
)
exp.add_scatter_plot_step()
exp.add_report(ScatterPlotReport(
attributes=['bytes_per_state'],
filter_config_nick='astar_blind',
),
outfile='issue214_bytes_per_state.png')
for config_nick in ['astar_blind', 'astar_lmcut', 'astar_merge_and_shrink_bisim', 'astar_ipdb']:
for attr in ['memory', 'total_time']:
exp.add_report(ScatterPlotReport(
attributes=[attr],
filter_config_nick=config_nick,
),
outfile='issue214_%s_%s.png' % (attr, config_nick))
exp()
| 1,483 | 25.035088 | 120 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue214/issue214-v3-ipdb.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward.suites import suite_optimal_with_ipc11
from downward.configs import default_configs_optimal
from downward.reports.scatter import ScatterPlotReport
import common_setup
REVS = ["issue214-base", "issue214-v3"]
CONFIGS = {"ipdb": ["--search", "astar(ipdb())"]}
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
exp = common_setup.MyExperiment(
grid_priority=PRIORITY,
revisions=REVS,
configs=CONFIGS,
suite=SUITE,
parsers=['state_size_parser.py'],
)
exp.add_comparison_table_step(
attributes=common_setup.MyExperiment.DEFAULT_TABLE_ATTRIBUTES + ['bytes_per_state', 'variables', 'state_var_t_size']
)
exp()
| 864 | 22.378378 | 120 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue214/issue214-v5-sat.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
from downward.configs import default_configs_optimal
from downward.reports.scatter import ScatterPlotReport
import common_setup
REVS = ["issue214-base", "issue214-v5"]
CONFIGS = {"blind": ["--search", "astar(blind())"]}
TEST_RUN = False
if TEST_RUN:
SUITE = "gripper:prob01.pddl"
PRIORITY = None # "None" means local experiment
else:
SUITE = list(sorted(set(suites.suite_all()) - set(suites.suite_optimal_with_ipc11())))
PRIORITY = 0 # number means maia experiment
exp = common_setup.MyExperiment(
grid_priority=PRIORITY,
revisions=REVS,
configs=CONFIGS,
suite=SUITE,
parsers=['state_size_parser.py'],
)
exp.add_comparison_table_step(
attributes=common_setup.MyExperiment.DEFAULT_TABLE_ATTRIBUTES + ['bytes_per_state', 'variables', 'state_var_t_size']
)
exp()
| 894 | 23.189189 | 120 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue214/issue214-v5.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward.suites import suite_optimal_with_ipc11
from downward.configs import default_configs_optimal
from downward.reports.scatter import ScatterPlotReport
import common_setup
REVS = ["issue214-base", "issue214-v5"]
CONFIGS = {"blind": ["--search", "astar(blind())"]}
TEST_RUN = False
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
exp = common_setup.MyExperiment(
grid_priority=PRIORITY,
revisions=REVS,
configs=CONFIGS,
suite=SUITE,
parsers=['state_size_parser.py'],
)
exp.add_comparison_table_step(
attributes=common_setup.MyExperiment.DEFAULT_TABLE_ATTRIBUTES + ['bytes_per_state', 'variables', 'state_var_t_size']
)
exp()
| 867 | 22.459459 | 120 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue214/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, parsers=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.
If "parsers" is specified, it should be a list of paths to
parsers that should be run in addition to search_parser.py.
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
self._additional_parsers = parsers or []
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 _make_search_runs(self):
DownwardExperiment._make_search_runs(self)
for i, parser in enumerate(self._additional_parsers):
parser_alias = 'ADDITIONALPARSER%d' % i
self.add_resource(parser_alias, parser, os.path.basename(parser))
for run in self.runs:
run.require_resource(parser_alias)
run.add_command('additional-parser-%d' % i, [parser_alias])
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
report = CompareRevisionsReport(*revisions, attributes=attributes)
self.add_report(report, outfile="%s-compare.html" % self._report_prefix)
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__")
if len(revisions) != 2:
# TODO: Should generalize this, too, by offering a general
# grouping function and then comparing any pair of
# settings in the same group.
raise NotImplementedError("need two revisions")
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" % (revisions[1], 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, name))
self.add_step(Step("make-scatter-plots", make_scatter_plots))
| 9,190 | 37.456067 | 80 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue214/state_size_parser.py
|
#! /usr/bin/env python
from lab.parser import Parser
def calculate_old_state_size(content, props):
if 'bytes_per_state' not in props and 'preprocessor_variables' in props and 'state_var_t_size' in props:
props['bytes_per_state'] = props['preprocessor_variables'] * props['state_var_t_size']
class StateSizeParser(Parser):
def __init__(self):
Parser.__init__(self)
self.add_pattern('bytes_per_state', 'Bytes per state: (\d+)',
required=False, type=int)
self.add_pattern('state_var_t_size', 'Dispatcher selected state size (\d).',
required=False, type=int)
self.add_pattern('variables', 'Variables: (\d+)',
required=False, type=int)
self.add_function(calculate_old_state_size)
if __name__ == '__main__':
parser = StateSizeParser()
print 'Running state size parser'
parser.parse()
| 923 | 37.5 | 109 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue214/issue214-v4-ipdb.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward.suites import suite_optimal_with_ipc11
from downward.configs import default_configs_optimal
from downward.reports.scatter import ScatterPlotReport
import common_setup
REVS = ["issue214-base", "issue214-v4"]
CONFIGS = {"ipdb": ["--search", "astar(ipdb())"]}
TEST_RUN = False
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
exp = common_setup.MyExperiment(
grid_priority=PRIORITY,
revisions=REVS,
configs=CONFIGS,
suite=SUITE,
parsers=['state_size_parser.py'],
)
exp.add_comparison_table_step(
attributes=common_setup.MyExperiment.DEFAULT_TABLE_ATTRIBUTES + ['bytes_per_state', 'variables', 'state_var_t_size']
)
exp()
| 865 | 22.405405 | 120 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue214/issue214-sat.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward.suites import suite_satisficing_with_ipc11
from downward.configs import default_configs_satisficing
from downward.reports.scatter import ScatterPlotReport
import common_setup
REVS = ["issue214-base", "issue214-v2"]
CONFIGS = default_configs_satisficing()
TEST_RUN = True
if TEST_RUN:
SUITE = "gripper:prob01.pddl"
PRIORITY = None # "None" means local experiment
else:
SUITE = suite_satisficing_with_ipc11()
PRIORITY = 0 # number means maia experiment
exp = common_setup.MyExperiment(
grid_priority=PRIORITY,
revisions=REVS,
configs=CONFIGS,
suite=SUITE,
parsers=['state_size_parser.py'],
)
exp.add_comparison_table_step(
attributes=common_setup.MyExperiment.DEFAULT_TABLE_ATTRIBUTES + ['bytes_per_state', 'variables', 'state_var_t_size']
)
exp.add_scatter_plot_step()
exp.add_report(ScatterPlotReport(
attributes=['bytes_per_state'],
filter_config_nick='astar_blind',
),
outfile='issue214_sat_bytes_per_state.png')
for config_nick in ['lazy_greedy_ff', 'eager_greedy_cg', 'seq_sat_lama_2011']:
for attr in ['memory', 'total_time']:
exp.add_report(ScatterPlotReport(
attributes=[attr],
filter_config_nick=config_nick,
),
outfile='issue214_sat_%s_%s.png' % (attr, config_nick))
exp()
| 1,398 | 24.907407 | 120 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue914/v2.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import itertools
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from lab.reports import Attribute, geometric_mean
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__))
SCRIPT_NAME = os.path.splitext(os.path.basename(__file__))[0]
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue914-base", "issue914-v2"]
BUILDS = ["release"]
CONFIG_NICKS = [
('dfp-b50k-t900', ['--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,main_loop_max_time=900))']),
('rl-b50k-t900', ['--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,main_loop_max_time=900))']),
('sccs-dfp-b50k-t900', ['--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,main_loop_max_time=900))']),
]
CONFIGS = [
IssueConfig(
config_nick,
config,
build_options=[build],
driver_options=["--build", build])
for build in BUILDS
for config_nick, config in CONFIG_NICKS
]
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=4)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser('ms-parser.py')
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
# 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_atomic_fts_constructed = Attribute('ms_atomic_fts_constructed', absolute=True, min_wins=False)
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_atomic_fts_constructed,
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.run_steps()
| 4,058 | 42.180851 | 479 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue914/v4.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import itertools
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from lab.reports import Attribute, geometric_mean
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__))
SCRIPT_NAME = os.path.splitext(os.path.basename(__file__))[0]
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue914-base", "issue914-v4"]
BUILDS = ["release"]
CONFIG_NICKS = [
('dfp-b50k-t900', ['--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,main_loop_max_time=900))']),
('rl-b50k-t900', ['--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,main_loop_max_time=900))']),
('sccs-dfp-b50k-t900', ['--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,main_loop_max_time=900))']),
]
CONFIGS = [
IssueConfig(
config_nick,
config,
build_options=[build],
driver_options=["--build", build])
for build in BUILDS
for config_nick, config in CONFIG_NICKS
]
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=4)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser('ms-parser.py')
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
# 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_atomic_fts_constructed = Attribute('ms_atomic_fts_constructed', absolute=True, min_wins=False)
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)
ms_num_remaining_factors = Attribute('ms_num_remaining_factors', absolute=False, min_wins=False)
ms_num_factors_kept = Attribute('ms_num_factors_kept', absolute=False, min_wins=False)
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_atomic_fts_constructed,
ms_out_of_memory,
ms_out_of_time,
ms_memory_delta,
ms_num_remaining_factors,
ms_num_factors_kept,
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.run_steps()
| 4,396 | 42.97 | 479 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue914/v1.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import itertools
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from lab.reports import Attribute, geometric_mean
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__))
SCRIPT_NAME = os.path.splitext(os.path.basename(__file__))[0]
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue914-base", "issue914-v1"]
BUILDS = ["release"]
CONFIG_NICKS = [
('dfp-b50k-t900', ['--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,main_loop_max_time=900))']),
('rl-b50k-t900', ['--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,main_loop_max_time=900))']),
('sccs-dfp-b50k-t900', ['--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,main_loop_max_time=900))']),
]
CONFIGS = [
IssueConfig(
config_nick,
config,
build_options=[build],
driver_options=["--build", build])
for build in BUILDS
for config_nick, config in CONFIG_NICKS
]
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=4)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser('ms-parser.py')
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
# 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_atomic_fts_constructed = Attribute('ms_atomic_fts_constructed', absolute=True, min_wins=False)
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_atomic_fts_constructed,
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.run_steps()
| 4,058 | 42.180851 | 479 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue914/ms-parser.py
|
#! /usr/bin/env python
from lab.parser import Parser
parser = Parser()
parser.add_pattern('ms_construction_time', 'Merge-and-shrink algorithm runtime: (.+)s', required=False, type=float)
parser.add_pattern('ms_atomic_construction_time', 'M&S algorithm timer: (.+)s \(after computation of atomic factors\)', required=False, type=float)
parser.add_pattern('ms_memory_delta', 'Final peak memory increase of merge-and-shrink algorithm: (\d+) KB', required=False, type=int)
parser.add_pattern('ms_num_remaining_factors', 'Number of remaining factors: (\d+)', required=False, type=int)
parser.add_pattern('ms_num_factors_kept', 'Number of factors kept: (\d+)', 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_atomic_fts_constructed(content, props):
ms_atomic_construction_time = props.get('ms_atomic_construction_time')
ms_atomic_fts_constructed = False
if ms_atomic_construction_time is not None:
ms_atomic_fts_constructed = True
props['ms_atomic_fts_constructed'] = ms_atomic_fts_constructed
parser.add_function(check_atomic_fts_constructed)
def check_planner_exit_reason(content, props):
ms_abstraction_constructed = props.get('ms_abstraction_constructed')
error = props.get('error')
if error != 'success' and error != 'timeout' and error != 'out-of-memory':
print 'error: %s' % error
return
# Check whether merge-and-shrink computation or search ran out of
# time or memory.
ms_out_of_time = False
ms_out_of_memory = False
search_out_of_time = False
search_out_of_memory = False
if ms_abstraction_constructed == False:
if error == 'timeout':
ms_out_of_time = True
elif error == 'out-of-memory':
ms_out_of_memory = True
elif ms_abstraction_constructed == True:
if error == 'timeout':
search_out_of_time = True
elif error == 'out-of-memory':
search_out_of_memory = True
props['ms_out_of_time'] = ms_out_of_time
props['ms_out_of_memory'] = ms_out_of_memory
props['search_out_of_time'] = search_out_of_time
props['search_out_of_memory'] = search_out_of_memory
parser.add_function(check_planner_exit_reason)
def check_perfect_heuristic(content, props):
plan_length = props.get('plan_length')
expansions = props.get('expansions')
if plan_length != None:
perfect_heuristic = False
if plan_length + 1 == expansions:
perfect_heuristic = True
props['perfect_heuristic'] = perfect_heuristic
parser.add_function(check_perfect_heuristic)
parser.parse()
| 2,893 | 39.194444 | 147 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue914/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import ComparativeReport
from downward.reports.scatter import ScatterPlotReport
from relativescatter import RelativeScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
DEFAULT_OPTIMAL_SUITE = [
'agricola-opt18-strips', 'airport', 'barman-opt11-strips',
'barman-opt14-strips', 'blocks', 'childsnack-opt14-strips',
'data-network-opt18-strips', 'depot', 'driverlog',
'elevators-opt08-strips', 'elevators-opt11-strips',
'floortile-opt11-strips', 'floortile-opt14-strips', 'freecell',
'ged-opt14-strips', 'grid', 'gripper', 'hiking-opt14-strips',
'logistics00', 'logistics98', 'miconic', 'movie', 'mprime',
'mystery', 'nomystery-opt11-strips', 'openstacks-opt08-strips',
'openstacks-opt11-strips', 'openstacks-opt14-strips',
'openstacks-strips', 'organic-synthesis-opt18-strips',
'organic-synthesis-split-opt18-strips', 'parcprinter-08-strips',
'parcprinter-opt11-strips', 'parking-opt11-strips',
'parking-opt14-strips', 'pathways-noneg', 'pegsol-08-strips',
'pegsol-opt11-strips', 'petri-net-alignment-opt18-strips',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-small', 'rovers',
'satellite', 'scanalyzer-08-strips', 'scanalyzer-opt11-strips',
'snake-opt18-strips', 'sokoban-opt08-strips',
'sokoban-opt11-strips', 'spider-opt18-strips', 'storage',
'termes-opt18-strips', 'tetris-opt14-strips',
'tidybot-opt11-strips', 'tidybot-opt14-strips', 'tpp',
'transport-opt08-strips', 'transport-opt11-strips',
'transport-opt14-strips', 'trucks-strips', 'visitall-opt11-strips',
'visitall-opt14-strips', 'woodworking-opt08-strips',
'woodworking-opt11-strips', 'zenotravel']
DEFAULT_SATISFICING_SUITE = [
'agricola-sat18-strips', 'airport', 'assembly',
'barman-sat11-strips', 'barman-sat14-strips', 'blocks',
'caldera-sat18-adl', 'caldera-split-sat18-adl', 'cavediving-14-adl',
'childsnack-sat14-strips', 'citycar-sat14-adl',
'data-network-sat18-strips', 'depot', 'driverlog',
'elevators-sat08-strips', 'elevators-sat11-strips',
'flashfill-sat18-adl', 'floortile-sat11-strips',
'floortile-sat14-strips', 'freecell', 'ged-sat14-strips', 'grid',
'gripper', 'hiking-sat14-strips', 'logistics00', 'logistics98',
'maintenance-sat14-adl', 'miconic', 'miconic-fulladl',
'miconic-simpleadl', 'movie', 'mprime', 'mystery',
'nomystery-sat11-strips', 'nurikabe-sat18-adl', 'openstacks',
'openstacks-sat08-adl', 'openstacks-sat08-strips',
'openstacks-sat11-strips', 'openstacks-sat14-strips',
'openstacks-strips', 'optical-telegraphs',
'organic-synthesis-sat18-strips',
'organic-synthesis-split-sat18-strips', 'parcprinter-08-strips',
'parcprinter-sat11-strips', 'parking-sat11-strips',
'parking-sat14-strips', 'pathways', 'pathways-noneg',
'pegsol-08-strips', 'pegsol-sat11-strips', 'philosophers',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-large',
'psr-middle', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-sat11-strips', 'schedule',
'settlers-sat18-adl', 'snake-sat18-strips', 'sokoban-sat08-strips',
'sokoban-sat11-strips', 'spider-sat18-strips', 'storage',
'termes-sat18-strips', 'tetris-sat14-strips',
'thoughtful-sat14-strips', 'tidybot-sat11-strips', 'tpp',
'transport-sat08-strips', 'transport-sat11-strips',
'transport-sat14-strips', 'trucks', 'trucks-strips',
'visitall-sat11-strips', 'visitall-sat14-strips',
'woodworking-sat08-strips', 'woodworking-sat11-strips',
'zenotravel']
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return node.endswith(".scicore.unibas.ch") or node.endswith(".cluster.bc2.ch")
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["depot:p01.pddl", "gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"planner_memory",
"planner_time",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, outfile=outfile)
self.add_step(
'publish-absolute-report', subprocess.call, ['publish', outfile])
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = ComparativeReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.%s" % (
self.name, rev1, rev2, report.output_format))
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
subprocess.call(["publish", outfile])
self.add_step("make-comparison-tables", make_comparison_tables)
self.add_step(
"publish-comparison-tables", publish_comparison_tables)
def add_scatter_plot_step(self, relative=False, attributes=None):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if relative:
report_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
report_class = ScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print("Make scatter plot for", name)
algo1 = get_algo_nick(rev1, config_nick)
algo2 = get_algo_nick(rev2, config_nick)
report = report_class(
filter_algorithm=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"])
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(step_name, make_scatter_plots)
| 14,744 | 36.423858 | 82 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue914/v3.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import itertools
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from lab.reports import Attribute, geometric_mean
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__))
SCRIPT_NAME = os.path.splitext(os.path.basename(__file__))[0]
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue914-base", "issue914-v3"]
BUILDS = ["release"]
CONFIG_NICKS = [
('dfp-b50k-t900', ['--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,main_loop_max_time=900))']),
('rl-b50k-t900', ['--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,main_loop_max_time=900))']),
('sccs-dfp-b50k-t900', ['--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,main_loop_max_time=900))']),
]
CONFIGS = [
IssueConfig(
config_nick,
config,
build_options=[build],
driver_options=["--build", build])
for build in BUILDS
for config_nick, config in CONFIG_NICKS
]
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=4)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser('ms-parser.py')
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
# 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_atomic_fts_constructed = Attribute('ms_atomic_fts_constructed', absolute=True, min_wins=False)
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_atomic_fts_constructed,
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.run_steps()
| 4,058 | 42.180851 | 479 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue914/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(
axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows a relative comparison of two
algorithms with regard to the given attribute. The attribute value
of algorithm 1 is shown on the x-axis and the relation to the value
of algorithm 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['algorithm'] == self.algorithms[0] and
run2['algorithm'] == self.algorithms[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.algorithms[0], val1)
assert val2 > 0, (domain, problem, self.algorithms[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlot uses log-scaling on the x-axis by default.
PlotReport._set_scales(
self, xscale or self.attribute.scale or 'log', 'log')
| 3,875 | 35.566038 | 78 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue536/ipdb.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import suites
import common_setup
REVS = ["issue536-base", "issue536-v1", "issue536-v2"]
LIMITS = {"search_time": 1800}
SUITE = suites.suite_optimal_with_ipc11()
CONFIGS = {
"ipdb": ["--search", "astar(ipdb())"],
}
exp = common_setup.IssueExperiment(
search_revisions=REVS,
configs=CONFIGS,
suite=SUITE,
limits=LIMITS,
)
exp.add_absolute_report_step()
exp()
| 450 | 16.346154 | 54 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue536/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import sys
from lab.environments import LocalEnvironment, MaiaEnvironment
from lab.experiment import ARGPARSER
from lab.steps import Step
from downward.experiments import DownwardExperiment, _get_rev_nick
from downward.checkouts import Translator, Preprocessor, Planner
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import CompareRevisionsReport
from downward.reports.scatter import ScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
def get_script():
"""Get file name of main script."""
import __main__
return __main__.__file__
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return ("cluster" in node or
node.startswith("gkigrid") or
node in ["habakuk", "turtur"])
def is_test_run():
return ARGS.test_run == "yes" or (ARGS.test_run == "auto" and
not is_running_on_cluster())
class IssueExperiment(DownwardExperiment):
"""Wrapper for DownwardExperiment with a few convenience features."""
DEFAULT_TEST_SUITE = "gripper:prob01.pddl"
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, configs, suite, grid_priority=None, path=None,
repo=None, revisions=None, search_revisions=None,
test_suite=None, **kwargs):
"""Create a DownwardExperiment with some convenience features.
*configs* must be a non-empty dict of {nick: cmdline} pairs
that sets the planner configurations to test. ::
IssueExperiment(configs={
"lmcut": ["--search", "astar(lmcut())"],
"ipdb": ["--search", "astar(ipdb())"]})
*suite* sets the benchmarks for the experiment. It must be a
single string or a list of strings specifying domains or
tasks. The downward.suites module has many predefined
suites. ::
IssueExperiment(suite=["grid", "gripper:prob01.pddl"])
from downward import suites
IssueExperiment(suite=suites.suite_all())
IssueExperiment(suite=suites.suite_satisficing_with_ipc11())
IssueExperiment(suite=suites.suite_optimal())
Use *grid_priority* to set the job priority for cluster
experiments. It must be in the range [-1023, 0] where 0 is the
highest priority. By default the priority is 0. ::
IssueExperiment(grid_priority=-500)
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
If *repo* is specified, it must be the path to the root of a
local Fast Downward repository. If omitted, the repository
is derived automatically from the main script's path. Example::
script = /path/to/fd-repo/experiments/issue123/exp01.py -->
repo = /path/to/fd-repo
If *revisions* is specified, it should be a non-empty
list of revisions, which specify which planner versions to use
in the experiment. The same versions are used for translator,
preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"])
If *search_revisions* is specified, it should be a non-empty
list of revisions, which specify which search component
versions to use in the experiment. All runs use the
translator and preprocessor component of the first
revision. ::
IssueExperiment(search_revisions=["default", "issue123"])
If you really need to specify the (translator, preprocessor,
planner) triples manually, use the *combinations* parameter
from the base class (might be deprecated soon). The options
*revisions*, *search_revisions* and *combinations* can be
freely mixed, but at least one of them must be given.
Specify *test_suite* to set the benchmarks for experiment test
runs. By default the first gripper task is used.
IssueExperiment(test_suite=["depot:pfile1", "tpp:p01.pddl"])
"""
if is_test_run():
kwargs["environment"] = LocalEnvironment()
suite = test_suite or self.DEFAULT_TEST_SUITE
elif "environment" not in kwargs:
kwargs["environment"] = MaiaEnvironment(priority=grid_priority)
if path is None:
path = get_data_dir()
if repo is None:
repo = get_repo_base()
kwargs.setdefault("combinations", [])
if not any([revisions, search_revisions, kwargs["combinations"]]):
raise ValueError('At least one of "revisions", "search_revisions" '
'or "combinations" must be given')
if revisions:
kwargs["combinations"].extend([
(Translator(repo, rev),
Preprocessor(repo, rev),
Planner(repo, rev))
for rev in revisions])
if search_revisions:
base_rev = search_revisions[0]
# Use the same nick for all parts to get short revision nick.
kwargs["combinations"].extend([
(Translator(repo, base_rev, nick=rev),
Preprocessor(repo, base_rev, nick=rev),
Planner(repo, rev, nick=rev))
for rev in search_revisions])
DownwardExperiment.__init__(self, path=path, repo=repo, **kwargs)
self._config_nicks = []
for nick, config in configs.items():
self.add_config(nick, config)
self.add_suite(suite)
@property
def revision_nicks(self):
# TODO: Once the add_algorithm() API is available we should get
# rid of the call to _get_rev_nick() and avoid inspecting the
# list of combinations by setting and saving the algorithm nicks.
return [_get_rev_nick(*combo) for combo in self.combinations]
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_config(self, nick, config, timeout=None):
DownwardExperiment.add_config(self, nick, config, timeout=timeout)
self._config_nicks.append(nick)
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't
compare revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If
the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = get_experiment_name() + "." + report.output_format
self.add_report(report, outfile=outfile)
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revision triples. Each report pairs up the runs of the same
config and lists the two absolute attribute values and their
difference for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareRevisionsReport
class. If the keyword argument *attributes* is not
specified, a default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self.revision_nicks, 2):
report = CompareRevisionsReport(rev1, rev2, **kwargs)
outfile = os.path.join(self.eval_dir,
"%s-%s-%s-compare.html" %
(self.name, rev1, rev2))
report(self.eval_dir, outfile)
self.add_step(Step("make-comparison-tables", make_comparison_tables))
def add_scatter_plot_step(self, attributes=None):
"""Add a step that creates scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revision pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
scatter_dir = os.path.join(self.eval_dir, "scatter")
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "%s-%s" % (rev1, config_nick)
algo2 = "%s-%s" % (rev2, config_nick)
report = ScatterPlotReport(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config_nick in self._config_nicks:
for rev1, rev2 in itertools.combinations(
self.revision_nicks, 2):
for attribute in self.get_supported_attributes(
config_nick, attributes):
make_scatter_plot(config_nick, rev1, rev2, attribute)
self.add_step(Step("make-scatter-plots", make_scatter_plots))
| 12,856 | 34.913408 | 79 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue512/issue512.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from downward import configs, suites
import common_setup
SEARCH_REVS = ["issue512-base", "issue512-v1"]
LIMITS = {"search_time": 1800}
SUITE = suites.suite_satisficing_with_ipc11()
configs_satisficing_core = configs.configs_satisficing_core()
CONFIGS = {}
for name in ["eager_greedy_add", "eager_greedy_ff",
"lazy_greedy_add", "lazy_greedy_ff"]:
CONFIGS[name] = configs_satisficing_core[name]
CONFIGS["blind"] = ["--search", "astar(blind())"]
exp = common_setup.IssueExperiment(
revisions=SEARCH_REVS,
configs=CONFIGS,
suite=SUITE,
limits=LIMITS,
)
exp.add_search_parser("custom-parser.py")
attributes = attributes=exp.DEFAULT_TABLE_ATTRIBUTES + ["init_time"]
exp.add_absolute_report_step(attributes=attributes)
exp.add_comparison_table_step(attributes=attributes)
exp.add_report(common_setup.RegressionReport(
revision_nicks=exp.revision_nicks,
config_nicks=CONFIGS.keys(),
attributes=attributes))
exp()
| 1,010 | 25.605263 | 68 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue512/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.reports import Table
from lab.steps import Step
from downward.experiments import DownwardExperiment, _get_rev_nick
from downward.checkouts import Translator, Preprocessor, Planner
from downward.reports import PlanningReport
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"
# TODO: Add something about errors/exit codes.
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"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-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))
class RegressionReport(PlanningReport):
"""
Compare revisions for tasks on which the first revision performs
better than other revisions.
*revision_nicks* must be a list of revision_nicks, e.g.
["default", "issue123"].
*config_nicks* must be a list of configuration nicknames, e.g.
["eager_greedy_ff", "eager_greedy_add"].
*regression_attribute* is the attribute that we compare between
different revisions. It defaults to "coverage".
Example comparing search_time for tasks were we lose coverage::
exp.add_report(RegressionReport(revision_nicks=["default", "issue123"],
config_nicks=["eager_greedy_ff"],
regression_attribute="coverage",
attributes="search_time"))
"""
def __init__(self, revision_nicks, config_nicks,
regression_attribute="coverage", **kwargs):
PlanningReport.__init__(self, **kwargs)
assert revision_nicks
self.revision_nicks = revision_nicks
assert config_nicks
self.config_nicks = config_nicks
self.regression_attribute = regression_attribute
def get_markup(self):
tables = []
for (domain, problem) in self.problems:
for config_nick in self.config_nicks:
runs = [self.runs[(domain, problem, rev + "-" + config_nick)]
for rev in self.revision_nicks]
if any(runs[0][self.regression_attribute] >
runs[i][self.regression_attribute]
for i in range(1, len(self.revision_nicks))):
print "\"%s:%s\"," % (domain, problem)
table = Table()
for rev, run in zip(self.revision_nicks, runs):
for attr in self.attributes:
table.add_cell(rev, attr, run.get(attr))
table_name = ":".join((domain, problem, config_nick))
tables.append((table_name, table))
return "\n".join(name + "\n" + str(table) for name, table in tables)
| 14,920 | 36.3025 | 79 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue512/custom-parser.py
|
#! /usr/bin/env python
from lab.parser import Parser
class CustomParser(Parser):
def __init__(self):
Parser.__init__(self)
self.add_pattern(
"init_time",
"Best heuristic value: \d+ \[g=0, 1 evaluated, 0 expanded, t=(.+)s, \d+ KB\]",
required=True,
type=float)
if __name__ == "__main__":
parser = CustomParser()
print "Running custom parser"
parser.parse()
| 441 | 21.1 | 90 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue851/v2.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import itertools
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from lab.reports import Attribute, geometric_mean
from downward.reports.compare import ComparativeReport
import common_setup
from common_setup import IssueConfig, IssueExperiment
from generalscatter import GeneralScatterPlotReport
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
SCRIPT_NAME = os.path.splitext(os.path.basename(__file__))[0]
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue851-base-v2", "issue851-v2"]
BUILDS = ["release32"]
CONFIG_NICKS = [
('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))']),
# ('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))']),
# ('sbmiasm-b50k', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_bisimulation(greedy=false),merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[sf_miasm(shrink_strategy=shrink_bisimulation(greedy=false),max_states=50000,threshold_before_merge=1),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))']),
# ('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))']),
]
CONFIGS = [
IssueConfig(
config_nick,
config,
build_options=[build],
driver_options=["--build", build])
for build in BUILDS
for config_nick, config in CONFIG_NICKS
]
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=4)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser('ms-parser.py')
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
# 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_atomic_fts_constructed = Attribute('ms_atomic_fts_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_atomic_fts_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(attributes=[ms_atomic_construction_time])
for algo_nick in ['dfp-b50k']: # 'rl-b50k', 'sbmiasm-b50k', 'sccs-dfp-b50k']:
algo = "issue851-v2-{}".format(algo_nick)
exp.add_report(
GeneralScatterPlotReport(
x_algo = algo,
y_algo = algo,
x_attribute='ms_atomic_construction_time',
y_attribute='total_time',
filter_algorithm=[algo],
attributes=['total_time'],
get_category=lambda run1, run2: run1["domain"],
),
outfile='{}-total_time_vs_ms_atomic_construction_time.png'.format(algo),
)
exp.run_steps()
| 5,272 | 44.852174 | 514 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue851/v3-debug.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import itertools
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from lab.reports import Attribute, geometric_mean
from downward.reports.compare import ComparativeReport
import common_setup
from common_setup import IssueConfig, IssueExperiment
from generalscatter import GeneralScatterPlotReport
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
SCRIPT_NAME = os.path.splitext(os.path.basename(__file__))[0]
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue851-v3"]
BUILDS = ["debug32"]
CONFIG_NICKS = [
('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))']),
# ('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))']),
# ('sbmiasm-b50k', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_bisimulation(greedy=false),merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[sf_miasm(shrink_strategy=shrink_bisimulation(greedy=false),max_states=50000,threshold_before_merge=1),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))']),
# ('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))']),
]
CONFIGS = [
IssueConfig(
config_nick,
config,
build_options=[build],
driver_options=["--build", build])
for build in BUILDS
for config_nick, config in CONFIG_NICKS
]
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=4)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser('ms-parser.py')
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
# 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_atomic_fts_constructed = Attribute('ms_atomic_fts_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_atomic_fts_constructed,
ms_final_size,
ms_out_of_memory,
ms_out_of_time,
search_out_of_memory,
search_out_of_time,
]
attributes = exp.DEFAULT_TABLE_ATTRIBUTES
attributes.extend(extra_attributes)
exp.add_absolute_report_step(attributes=attributes)
exp.run_steps()
| 4,620 | 46.153061 | 514 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue851/v4.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import itertools
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from lab.reports import Attribute, geometric_mean
from downward.reports.compare import ComparativeReport
import common_setup
from common_setup import IssueConfig, IssueExperiment
from generalscatter import GeneralScatterPlotReport
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
SCRIPT_NAME = os.path.splitext(os.path.basename(__file__))[0]
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue851-base-v2", "issue851-v3", "issue851-v4"]
BUILDS = ["release32"]
CONFIG_NICKS = [
('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))']),
# ('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))']),
# ('sbmiasm-b50k', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_bisimulation(greedy=false),merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[sf_miasm(shrink_strategy=shrink_bisimulation(greedy=false),max_states=50000,threshold_before_merge=1),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))']),
# ('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))']),
]
CONFIGS = [
IssueConfig(
config_nick,
config,
build_options=[build],
driver_options=["--build", build])
for build in BUILDS
for config_nick, config in CONFIG_NICKS
]
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=4)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser('ms-parser.py')
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
# 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_atomic_fts_constructed = Attribute('ms_atomic_fts_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_atomic_fts_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(attributes=[ms_atomic_construction_time])
for algo_nick in ['dfp-b50k']: # 'rl-b50k', 'sbmiasm-b50k', 'sccs-dfp-b50k']:
algo = "issue851-v2-{}".format(algo_nick)
exp.add_report(
GeneralScatterPlotReport(
x_algo = algo,
y_algo = algo,
x_attribute='ms_atomic_construction_time',
y_attribute='total_time',
filter_algorithm=[algo],
attributes=['total_time'],
get_category=lambda run1, run2: run1["domain"],
),
outfile='{}-total_time_vs_ms_atomic_construction_time.png'.format(algo),
)
exp.run_steps()
| 5,287 | 44.982609 | 514 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue851/v1.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import itertools
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from lab.reports import Attribute, geometric_mean
from downward.reports.compare import ComparativeReport
import common_setup
from common_setup import IssueConfig, IssueExperiment
from generalscatter import GeneralScatterPlotReport
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
SCRIPT_NAME = os.path.splitext(os.path.basename(__file__))[0]
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue851-base", "issue851-v1"]
BUILDS = ["release32"]
CONFIG_NICKS = [
('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))']),
('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))']),
('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))']),
]
CONFIGS = [
IssueConfig(
config_nick,
config,
build_options=[build],
driver_options=["--build", build])
for build in BUILDS
for config_nick, config in CONFIG_NICKS
]
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=4)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser('ms-parser.py')
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
# 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_atomic_fts_constructed = Attribute('ms_atomic_fts_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_atomic_fts_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)
# TODO: remove this filter when re-running experiments
def check_atomic_fts_constructed(run):
ms_atomic_construction_time = run.get('ms_atomic_construction_time')
ms_atomic_fts_constructed = False
if ms_atomic_construction_time is not None:
ms_atomic_fts_constructed = True
run['ms_atomic_fts_constructed'] = ms_atomic_fts_constructed
return run
exp.add_comparison_table_step(attributes=attributes,filter=[check_atomic_fts_constructed])
exp.add_scatter_plot_step(attributes=[ms_atomic_construction_time])
for algo_nick in ['dfp-b50k', 'rl-b50k', 'sccs-dfp-b50k']:
algo = "issue851-v1-{}".format(algo_nick)
exp.add_report(
GeneralScatterPlotReport(
x_algo = algo,
y_algo = algo,
x_attribute='ms_atomic_construction_time',
y_attribute='total_time',
filter_algorithm=[algo],
attributes=['total_time'],
get_category=lambda run1, run2: run1["domain"],
),
outfile='{}-total_time_vs_ms_atomic_construction_time.png'.format(algo),
)
exp.run_steps()
| 5,144 | 40.829268 | 451 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue851/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', 'Merge-and-shrink algorithm runtime: (.+)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_atomic_fts_constructed(content, props):
ms_atomic_construction_time = props.get('ms_atomic_construction_time')
ms_atomic_fts_constructed = False
if ms_atomic_construction_time is not None:
ms_atomic_fts_constructed = True
props['ms_atomic_fts_constructed'] = ms_atomic_fts_constructed
parser.add_function(check_atomic_fts_constructed)
def check_planner_exit_reason(content, props):
ms_abstraction_constructed = props.get('ms_abstraction_constructed')
error = props.get('error')
if error != 'success' and error != 'timeout' and error != 'out-of-memory':
print 'error: %s' % error
return
# Check whether merge-and-shrink computation or search ran out of
# time or memory.
ms_out_of_time = False
ms_out_of_memory = False
search_out_of_time = False
search_out_of_memory = False
if ms_abstraction_constructed == False:
if error == 'timeout':
ms_out_of_time = True
elif error == 'out-of-memory':
ms_out_of_memory = True
elif ms_abstraction_constructed == True:
if error == 'timeout':
search_out_of_time = True
elif error == 'out-of-memory':
search_out_of_memory = True
props['ms_out_of_time'] = ms_out_of_time
props['ms_out_of_memory'] = ms_out_of_memory
props['search_out_of_time'] = search_out_of_time
props['search_out_of_memory'] = search_out_of_memory
parser.add_function(check_planner_exit_reason)
def check_perfect_heuristic(content, props):
plan_length = props.get('plan_length')
expansions = props.get('expansions')
if plan_length != None:
perfect_heuristic = False
if plan_length + 1 == expansions:
perfect_heuristic = True
props['perfect_heuristic'] = perfect_heuristic
parser.add_function(check_perfect_heuristic)
parser.parse()
| 2,776 | 38.112676 | 139 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue851/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import ComparativeReport
from downward.reports.scatter import ScatterPlotReport
from relativescatter import RelativeScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
DEFAULT_OPTIMAL_SUITE = [
'agricola-opt18-strips', 'airport', 'barman-opt11-strips',
'barman-opt14-strips', 'blocks', 'childsnack-opt14-strips',
'data-network-opt18-strips', 'depot', 'driverlog',
'elevators-opt08-strips', 'elevators-opt11-strips',
'floortile-opt11-strips', 'floortile-opt14-strips', 'freecell',
'ged-opt14-strips', 'grid', 'gripper', 'hiking-opt14-strips',
'logistics00', 'logistics98', 'miconic', 'movie', 'mprime',
'mystery', 'nomystery-opt11-strips', 'openstacks-opt08-strips',
'openstacks-opt11-strips', 'openstacks-opt14-strips',
'openstacks-strips', 'organic-synthesis-opt18-strips',
'organic-synthesis-split-opt18-strips', 'parcprinter-08-strips',
'parcprinter-opt11-strips', 'parking-opt11-strips',
'parking-opt14-strips', 'pathways-noneg', 'pegsol-08-strips',
'pegsol-opt11-strips', 'petri-net-alignment-opt18-strips',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-small', 'rovers',
'satellite', 'scanalyzer-08-strips', 'scanalyzer-opt11-strips',
'snake-opt18-strips', 'sokoban-opt08-strips',
'sokoban-opt11-strips', 'spider-opt18-strips', 'storage',
'termes-opt18-strips', 'tetris-opt14-strips',
'tidybot-opt11-strips', 'tidybot-opt14-strips', 'tpp',
'transport-opt08-strips', 'transport-opt11-strips',
'transport-opt14-strips', 'trucks-strips', 'visitall-opt11-strips',
'visitall-opt14-strips', 'woodworking-opt08-strips',
'woodworking-opt11-strips', 'zenotravel']
DEFAULT_SATISFICING_SUITE = [
'agricola-sat18-strips', 'airport', 'assembly',
'barman-sat11-strips', 'barman-sat14-strips', 'blocks',
'caldera-sat18-adl', 'caldera-split-sat18-adl', 'cavediving-14-adl',
'childsnack-sat14-strips', 'citycar-sat14-adl',
'data-network-sat18-strips', 'depot', 'driverlog',
'elevators-sat08-strips', 'elevators-sat11-strips',
'flashfill-sat18-adl', 'floortile-sat11-strips',
'floortile-sat14-strips', 'freecell', 'ged-sat14-strips', 'grid',
'gripper', 'hiking-sat14-strips', 'logistics00', 'logistics98',
'maintenance-sat14-adl', 'miconic', 'miconic-fulladl',
'miconic-simpleadl', 'movie', 'mprime', 'mystery',
'nomystery-sat11-strips', 'nurikabe-sat18-adl', 'openstacks',
'openstacks-sat08-adl', 'openstacks-sat08-strips',
'openstacks-sat11-strips', 'openstacks-sat14-strips',
'openstacks-strips', 'optical-telegraphs',
'organic-synthesis-sat18-strips',
'organic-synthesis-split-sat18-strips', 'parcprinter-08-strips',
'parcprinter-sat11-strips', 'parking-sat11-strips',
'parking-sat14-strips', 'pathways', 'pathways-noneg',
'pegsol-08-strips', 'pegsol-sat11-strips', 'philosophers',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-large',
'psr-middle', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-sat11-strips', 'schedule',
'settlers-sat18-adl', 'snake-sat18-strips', 'sokoban-sat08-strips',
'sokoban-sat11-strips', 'spider-sat18-strips', 'storage',
'termes-sat18-strips', 'tetris-sat14-strips',
'thoughtful-sat14-strips', 'tidybot-sat11-strips', 'tpp',
'transport-sat08-strips', 'transport-sat11-strips',
'transport-sat14-strips', 'trucks', 'trucks-strips',
'visitall-sat11-strips', 'visitall-sat14-strips',
'woodworking-sat08-strips', 'woodworking-sat11-strips',
'zenotravel']
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return node.endswith(".scicore.unibas.ch") or node.endswith(".cluster.bc2.ch")
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["depot:p01.pddl", "gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"planner_memory",
"planner_time",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, outfile=outfile)
self.add_step(
'publish-absolute-report', subprocess.call, ['publish', outfile])
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = ComparativeReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.%s" % (
self.name, rev1, rev2, report.output_format))
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
subprocess.call(["publish", outfile])
self.add_step("make-comparison-tables", make_comparison_tables)
self.add_step(
"publish-comparison-tables", publish_comparison_tables)
def add_scatter_plot_step(self, relative=False, attributes=None):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if relative:
report_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
report_class = ScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "{}-{}".format(rev1, config_nick)
algo2 = "{}-{}".format(rev2, config_nick)
report = report_class(
filter_algorithm=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
# legend_location=(1.3, 0.5),
)
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(step_name, make_scatter_plots)
| 14,809 | 36.39899 | 82 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue851/v3.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
import itertools
import os
from lab.environments import LocalEnvironment, BaselSlurmEnvironment
from lab.reports import Attribute, geometric_mean
from downward.reports.compare import ComparativeReport
import common_setup
from common_setup import IssueConfig, IssueExperiment
from generalscatter import GeneralScatterPlotReport
from relativescatter import RelativeScatterPlotReport
DIR = os.path.dirname(os.path.abspath(__file__))
SCRIPT_NAME = os.path.splitext(os.path.basename(__file__))[0]
BENCHMARKS_DIR = os.environ["DOWNWARD_BENCHMARKS"]
REVISIONS = ["issue851-base-v2", "issue851-v2", "issue851-v3"]
BUILDS = ["release32"]
CONFIG_NICKS = [
('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))']),
# ('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))']),
# ('sbmiasm-b50k', ['--search', 'astar(merge_and_shrink(shrink_strategy=shrink_bisimulation(greedy=false),merge_strategy=merge_stateless(merge_selector=score_based_filtering(scoring_functions=[sf_miasm(shrink_strategy=shrink_bisimulation(greedy=false),max_states=50000,threshold_before_merge=1),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))']),
# ('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))']),
]
CONFIGS = [
IssueConfig(
config_nick,
config,
build_options=[build],
driver_options=["--build", build])
for build in BUILDS
for config_nick, config in CONFIG_NICKS
]
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=4)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_parser('ms-parser.py')
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
# 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_atomic_fts_constructed = Attribute('ms_atomic_fts_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_atomic_fts_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(attributes=[ms_atomic_construction_time])
for algo_nick in ['dfp-b50k']: # 'rl-b50k', 'sbmiasm-b50k', 'sccs-dfp-b50k']:
algo = "issue851-v2-{}".format(algo_nick)
exp.add_report(
GeneralScatterPlotReport(
x_algo = algo,
y_algo = algo,
x_attribute='ms_atomic_construction_time',
y_attribute='total_time',
filter_algorithm=[algo],
attributes=['total_time'],
get_category=lambda run1, run2: run1["domain"],
),
outfile='{}-total_time_vs_ms_atomic_construction_time.png'.format(algo),
)
exp.run_steps()
| 5,287 | 44.982609 | 514 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue851/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(
axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows a relative comparison of two
algorithms with regard to the given attribute. The attribute value
of algorithm 1 is shown on the x-axis and the relation to the value
of algorithm 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['algorithm'] == self.algorithms[0] and
run2['algorithm'] == self.algorithms[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.algorithms[0], val1)
assert val2 > 0, (domain, problem, self.algorithms[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlot uses log-scaling on the x-axis by default.
PlotReport._set_scales(
self, xscale or self.attribute.scale or 'log', 'log')
| 3,875 | 35.566038 | 78 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue851/generalscatter.py
|
#! /usr/bin/env python
# -*- coding: utf-8 -*-
from collections import defaultdict
import logging
import math
import os
from lab import tools
from downward.reports.plot import MatplotlibPlot, Matplotlib, PgfPlots, \
PlotReport, MIN_AXIS
class ScatterMatplotlib(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':
# TODO: assert that both are linear or log
plot_size = max(report.x_missing_val * 1.01, report.y_missing_val * 1.01)
else:
plot_size = max(report.x_missing_val * 1.5, report.y_missing_val * 1.5)
# Plot a diagonal black line. Starting at (0,0) often raises errors.
axes.plot([0.001, plot_size], [0.001, plot_size], 'k')
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)
# axes.set_xlim(report.xlim_left, report.xlim_right)
# axes.set_ylim(report.ylim_bottom, report.ylim_top)
for axis in [axes.xaxis, axes.yaxis]:
# MatplotlibPlot.change_axis_formatter(
# axis, report.missing_val if report.show_missing else None)
MatplotlibPlot.change_axis_formatter(axes.xaxis,
report.x_missing_val if report.show_missing else None)
MatplotlibPlot.change_axis_formatter(axes.yaxis,
report.y_missing_val if report.show_missing else None)
return has_points
class ScatterPgfPlots(PgfPlots):
@classmethod
def _format_coord(cls, coord):
def format_value(v):
return str(v) if isinstance(v, int) else '%f' % v
return '(%s, %s)' % (format_value(coord[0]), format_value(coord[1]))
@classmethod
def _get_plot(cls, report):
lines = []
options = cls._get_axis_options(report)
lines.append('\\begin{axis}[%s]' % cls._format_options(options))
for category, coords in sorted(report.categories.items()):
plot = {'only marks': True}
lines.append(
'\\addplot+[%s] coordinates {\n%s\n};' % (
cls._format_options(plot),
' '.join(cls._format_coord(c) for c in coords)))
if category:
lines.append('\\addlegendentry{%s}' % category)
elif report.has_multiple_categories:
# None is treated as the default category if using multiple
# categories. Add a corresponding entry to the legend.
lines.append('\\addlegendentry{default}')
# Add black line.
start = min(report.min_x, report.min_y)
if report.xlim_left is not None:
start = min(start, report.xlim_left)
if report.ylim_bottom is not None:
start = min(start, report.ylim_bottom)
end = max(report.max_x, report.max_y)
if report.xlim_right:
end = max(end, report.xlim_right)
if report.ylim_top:
end = max(end, report.ylim_top)
if report.show_missing:
end = max(end, report.missing_val)
lines.append(
'\\addplot[color=black] coordinates {(%f, %f) (%d, %d)};' %
(start, start, end, end))
lines.append('\\end{axis}')
return lines
@classmethod
def _get_axis_options(cls, report):
opts = PgfPlots._get_axis_options(report)
# Add line for missing values.
for axis in ['x', 'y']:
opts['extra %s ticks' % axis] = report.missing_val
opts['extra %s tick style' % axis] = 'grid=major'
return opts
class GeneralScatterPlotReport(PlotReport):
"""
Generate a scatter plot for a specific attribute.
"""
def __init__(self, x_algo, y_algo, x_attribute, y_attribute, show_missing=True, get_category=None, **kwargs):
"""
See :class:`.PlotReport` for inherited arguments.
The keyword argument *attributes* must contain exactly one
attribute.
Use the *filter_algorithm* keyword argument to select exactly
two algorithms.
If only one of the two algorithms has a value for a run, only
add a coordinate if *show_missing* is True.
*get_category* can be a function that takes **two** runs
(dictionaries of properties) and returns a category name. This
name is used to group the points in the plot. If there is more
than one group, a legend is automatically added. Runs for which
this function returns None are shown in a default category and
are not contained in the legend. For example, to group by
domain:
>>> def domain_as_category(run1, run2):
... # run2['domain'] has the same value, because we always
... # compare two runs of the same problem.
... return run1['domain']
Example grouping by difficulty:
>>> def improvement(run1, run2):
... time1 = run1.get('search_time', 1800)
... time2 = run2.get('search_time', 1800)
... if time1 > time2:
... return 'better'
... if time1 == time2:
... return 'equal'
... return 'worse'
>>> from downward.experiment import FastDownwardExperiment
>>> exp = FastDownwardExperiment()
>>> exp.add_report(ScatterPlotReport(
... attributes=['search_time'],
... get_category=improvement))
Example comparing the number of expanded states for two
algorithms:
>>> exp.add_report(ScatterPlotReport(
... attributes=["expansions_until_last_jump"],
... filter_algorithm=["algorithm-1", "algorithm-2"],
... get_category=domain_as_category,
... format="png", # Use "tex" for pgfplots output.
... ),
... name="scatterplot-expansions")
"""
# If the size has not been set explicitly, make it a square.
matplotlib_options = kwargs.get('matplotlib_options', {})
matplotlib_options.setdefault('figure.figsize', [8, 8])
kwargs['matplotlib_options'] = matplotlib_options
PlotReport.__init__(self, **kwargs)
if not self.attribute:
logging.critical('ScatterPlotReport needs exactly one attribute')
# By default all values are in the same category.
self.get_category = get_category or (lambda run1, run2: None)
self.show_missing = show_missing
self.xlim_left = self.xlim_left or MIN_AXIS
self.ylim_bottom = self.ylim_bottom or MIN_AXIS
if self.output_format == 'tex':
self.writer = ScatterPgfPlots
else:
self.writer = ScatterMatplotlib
self.x_algo = x_algo
self.y_algo = y_algo
self.x_attribute = x_attribute
self.y_attribute = y_attribute
def _set_scales(self, xscale, yscale):
PlotReport._set_scales(self, xscale or self.attribute.scale or 'log', yscale)
if self.xscale != self.yscale:
logging.critical('Scatterplots must use the same scale on both axes.')
def _get_missing_val(self, max_value, scale):
"""
Separate the missing values by plotting them at (max_value * 10)
rounded to the next power of 10.
"""
assert max_value is not None
# HACK!
max_value = 1800
if scale == 'linear':
return max_value * 1.1
return int(10 ** math.ceil(math.log10(max_value)))
def _handle_none_values(self, X, Y, replacement_x, replacement_y):
assert len(X) == len(Y), (X, Y)
if self.show_missing:
return ([x if x is not None else replacement_x for x in X],
[y if y is not None else replacement_y for y in Y])
return zip(*[(x, y) for x, y in zip(X, Y) if x is not None and y is not None])
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
x_count = 0
y_count = 0
x_none_count = 0
y_none_count = 0
for (domain, problem), runs in self.problem_runs.items():
run1 = next((run for run in runs if run['algorithm'] == self.x_algo), None)
run2 = next((run for run in runs if run['algorithm'] == self.y_algo), None)
if run1 is None or run2 is None:
continue
assert (run1['algorithm'] == self.x_algo and
run2['algorithm'] == self.y_algo)
val1 = run1.get(self.x_attribute)
val2 = run2.get(self.y_attribute)
x_count += 1
y_count += 1
if val1 is None:
x_none_count += 1
if val2 is None:
y_none_count += 1
# print val1, val2
if val1 is None and val2 is None:
continue
category = self.get_category(run1, run2)
categories[category].append((val1, val2))
# print x_count, y_count
# print x_none_count, y_none_count
# print len(categories[None])
# print categories[None]
return categories
def _get_limit(self, varlist, limit_type):
assert limit_type == 'max' or limit_type == 'min'
varlist = [x for x in varlist if x is not None]
if(limit_type == 'max'):
return max(varlist)
else:
return min(varlist)
def _get_plot_size(self, missing_val, scale):
if scale == 'linear':
return missing_val * 1.01
else:
return missing_val * 1.25
def _prepare_categories(self, categories):
categories = PlotReport._prepare_categories(self, categories)
# Find max-value to fit plot and to draw missing values.
# self.missing_val = self._get_missing_val(max(self.max_x, self.max_y))
self.x_missing_val = self._get_missing_val(self.max_x, self.xscale)
self.y_missing_val = self._get_missing_val(self.max_y, self.yscale)
# print self.x_missing_val, self.y_missing_val
# set minima
self.xlim_left = self._get_limit([self.xlim_left, self.min_x],'min')
self.ylim_bottom = self._get_limit([self.ylim_bottom, self.min_y],'min')
# set maxima
x_plot_size = y_plot_size = None
if self.show_missing:
x_plot_size = self._get_plot_size(self.x_missing_val, self.xscale)
y_plot_size = self._get_plot_size(self.y_missing_val, self.yscale)
self.xlim_right = self._get_limit([self.xlim_right, self.max_x, x_plot_size], 'max')
self.ylim_top = self._get_limit([self.ylim_top, self.max_y, y_plot_size], 'max')
# self.diagonal_start = self.diagonal_end = None
# if self.show_diagonal:
# self.diagonal_start = max(self.xlim_left, self.ylim_bottom)
# self.diagonal_end = min(self.xlim_right, self.ylim_top)
new_categories = {}
for category, coords in categories.items():
X, Y = zip(*coords)
# X, Y = self._handle_none_values(X, Y, self.missing_val)
X, Y = self._handle_none_values(X, Y, self.x_missing_val, self.y_missing_val)
coords = zip(X, Y)
new_categories[category] = coords
# print len(new_categories[None])
# print new_categories[None]
return new_categories
def write(self):
if not (len(self.algorithms) == 1 and self.x_algo == self.algorithms[0] and self.y_algo == self.algorithms[0]):
logging.critical(
'Scatter plots need exactly 1 algorithm that must match x_algo and y_algo: %s, %s, %s' % (self.algorithms, self.x_algo, self.y_algo))
self.xlabel = self.xlabel or self.x_algo + ": " + self.x_attribute
self.ylabel = self.ylabel or self.y_algo + ": " + self.y_attribute
suffix = '.' + self.output_format
if not self.outfile.endswith(suffix):
self.outfile += suffix
tools.makedirs(os.path.dirname(self.outfile))
self._write_plot(self.runs.values(), self.outfile)
| 12,617 | 40.235294 | 149 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue776/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 = ["issue776-v2-base", "issue776-v2"]
CONFIGS = [
IssueConfig('lama-first', [], driver_options=['--alias', 'lama-first', '--overall-time-limit', '5m']),
IssueConfig('bjolp', [], driver_options=['--alias', 'seq-opt-bjolp', '--overall-time-limit', '5m']),
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(email="[email protected]")
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=4)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.SINGLE_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
exp.add_comparison_table_step()
exp.run_steps()
| 1,318 | 28.311111 | 106 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue776/v2-lama.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 = ["issue776-v2-base", "issue776-v2"]
CONFIGS = [
IssueConfig('lama', [], driver_options=['--alias', 'seq-sat-lama-2011', '--overall-time-limit', '5m']),
]
SUITE = common_setup.DEFAULT_SATISFICING_SUITE
ENVIRONMENT = BaselSlurmEnvironment(email="[email protected]")
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=4)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parser(exp.EXITCODE_PARSER)
exp.add_parser(exp.TRANSLATOR_PARSER)
exp.add_parser(exp.ANYTIME_SEARCH_PARSER)
exp.add_parser(exp.PLANNER_PARSER)
exp.add_step('build', exp.build)
exp.add_step('start', exp.start_runs)
exp.add_fetcher(name='fetch')
exp.add_comparison_table_step()
exp.run_steps()
| 1,219 | 26.727273 | 107 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue776/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 = ["issue776-base", "issue776-v1"]
CONFIGS = [
IssueConfig('lama', [], driver_options=['--alias', 'seq-sat-lama-2011']),
IssueConfig('lama-first', [], driver_options=['--alias', 'lama-first']),
IssueConfig('bjolp', [], driver_options=['--alias', 'seq-opt-bjolp']),
]
SUITE = common_setup.DEFAULT_OPTIMAL_SUITE
ENVIRONMENT = BaselSlurmEnvironment(email="[email protected]")
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=4)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_comparison_table_step()
exp.run_steps()
| 1,131 | 28.025641 | 77 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue776/common_setup.py
|
# -*- coding: utf-8 -*-
import itertools
import os
import platform
import subprocess
import sys
from lab.experiment import ARGPARSER
from lab import tools
from downward.experiment import FastDownwardExperiment
from downward.reports.absolute import AbsoluteReport
from downward.reports.compare import ComparativeReport
from downward.reports.scatter import ScatterPlotReport
from relativescatter import RelativeScatterPlotReport
def parse_args():
ARGPARSER.add_argument(
"--test",
choices=["yes", "no", "auto"],
default="auto",
dest="test_run",
help="test experiment locally on a small suite if --test=yes or "
"--test=auto and we are not on a cluster")
return ARGPARSER.parse_args()
ARGS = parse_args()
DEFAULT_OPTIMAL_SUITE = [
'airport', 'barman-opt11-strips', 'barman-opt14-strips', 'blocks',
'childsnack-opt14-strips', 'depot', 'driverlog',
'elevators-opt08-strips', 'elevators-opt11-strips',
'floortile-opt11-strips', 'floortile-opt14-strips', 'freecell',
'ged-opt14-strips', 'grid', 'gripper', 'hiking-opt14-strips',
'logistics00', 'logistics98', 'miconic', 'movie', 'mprime',
'mystery', 'nomystery-opt11-strips', 'openstacks-opt08-strips',
'openstacks-opt11-strips', 'openstacks-opt14-strips',
'openstacks-strips', 'parcprinter-08-strips',
'parcprinter-opt11-strips', 'parking-opt11-strips',
'parking-opt14-strips', 'pathways-noneg', 'pegsol-08-strips',
'pegsol-opt11-strips', 'pipesworld-notankage',
'pipesworld-tankage', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-opt11-strips',
'sokoban-opt08-strips', 'sokoban-opt11-strips', 'storage',
'tetris-opt14-strips', 'tidybot-opt11-strips',
'tidybot-opt14-strips', 'tpp', 'transport-opt08-strips',
'transport-opt11-strips', 'transport-opt14-strips',
'trucks-strips', 'visitall-opt11-strips', 'visitall-opt14-strips',
'woodworking-opt08-strips', 'woodworking-opt11-strips',
'zenotravel']
DEFAULT_SATISFICING_SUITE = [
'airport', 'assembly', 'barman-sat11-strips',
'barman-sat14-strips', 'blocks', 'cavediving-14-adl',
'childsnack-sat14-strips', 'citycar-sat14-adl', 'depot',
'driverlog', 'elevators-sat08-strips', 'elevators-sat11-strips',
'floortile-sat11-strips', 'floortile-sat14-strips', 'freecell',
'ged-sat14-strips', 'grid', 'gripper', 'hiking-sat14-strips',
'logistics00', 'logistics98', 'maintenance-sat14-adl', 'miconic',
'miconic-fulladl', 'miconic-simpleadl', 'movie', 'mprime',
'mystery', 'nomystery-sat11-strips', 'openstacks',
'openstacks-sat08-adl', 'openstacks-sat08-strips',
'openstacks-sat11-strips', 'openstacks-sat14-strips',
'openstacks-strips', 'optical-telegraphs', 'parcprinter-08-strips',
'parcprinter-sat11-strips', 'parking-sat11-strips',
'parking-sat14-strips', 'pathways', 'pathways-noneg',
'pegsol-08-strips', 'pegsol-sat11-strips', 'philosophers',
'pipesworld-notankage', 'pipesworld-tankage', 'psr-large',
'psr-middle', 'psr-small', 'rovers', 'satellite',
'scanalyzer-08-strips', 'scanalyzer-sat11-strips', 'schedule',
'sokoban-sat08-strips', 'sokoban-sat11-strips', 'storage',
'tetris-sat14-strips', 'thoughtful-sat14-strips',
'tidybot-sat11-strips', 'tpp', 'transport-sat08-strips',
'transport-sat11-strips', 'transport-sat14-strips', 'trucks',
'trucks-strips', 'visitall-sat11-strips', 'visitall-sat14-strips',
'woodworking-sat08-strips', 'woodworking-sat11-strips',
'zenotravel']
def get_script():
"""Get file name of main script."""
return tools.get_script_path()
def get_script_dir():
"""Get directory of main script.
Usually a relative directory (depends on how it was called by the user.)"""
return os.path.dirname(get_script())
def get_experiment_name():
"""Get name for experiment.
Derived from the absolute filename of the main script, e.g.
"/ham/spam/eggs.py" => "spam-eggs"."""
script = os.path.abspath(get_script())
script_dir = os.path.basename(os.path.dirname(script))
script_base = os.path.splitext(os.path.basename(script))[0]
return "%s-%s" % (script_dir, script_base)
def get_data_dir():
"""Get data dir for the experiment.
This is the subdirectory "data" of the directory containing
the main script."""
return os.path.join(get_script_dir(), "data", get_experiment_name())
def get_repo_base():
"""Get base directory of the repository, as an absolute path.
Search upwards in the directory tree from the main script until a
directory with a subdirectory named ".hg" is found.
Abort if the repo base cannot be found."""
path = os.path.abspath(get_script_dir())
while os.path.dirname(path) != path:
if os.path.exists(os.path.join(path, ".hg")):
return path
path = os.path.dirname(path)
sys.exit("repo base could not be found")
def is_running_on_cluster():
node = platform.node()
return node.endswith(".scicore.unibas.ch") or node.endswith(".cluster.bc2.ch")
def is_test_run():
return ARGS.test_run == "yes" or (
ARGS.test_run == "auto" and not is_running_on_cluster())
def get_algo_nick(revision, config_nick):
return "{revision}-{config_nick}".format(**locals())
class IssueConfig(object):
"""Hold information about a planner configuration.
See FastDownwardExperiment.add_algorithm() for documentation of the
constructor's options.
"""
def __init__(self, nick, component_options,
build_options=None, driver_options=None):
self.nick = nick
self.component_options = component_options
self.build_options = build_options
self.driver_options = driver_options
class IssueExperiment(FastDownwardExperiment):
"""Subclass of FastDownwardExperiment with some convenience features."""
DEFAULT_TEST_SUITE = ["depot:p01.pddl", "gripper:prob01.pddl"]
DEFAULT_TABLE_ATTRIBUTES = [
"cost",
"coverage",
"error",
"evaluations",
"expansions",
"expansions_until_last_jump",
"generated",
"memory",
"quality",
"run_dir",
"score_evaluations",
"score_expansions",
"score_generated",
"score_memory",
"score_search_time",
"score_total_time",
"search_time",
"total_time",
]
DEFAULT_SCATTER_PLOT_ATTRIBUTES = [
"evaluations",
"expansions",
"expansions_until_last_jump",
"initial_h_value",
"memory",
"search_time",
"total_time",
]
PORTFOLIO_ATTRIBUTES = [
"cost",
"coverage",
"error",
"plan_length",
"run_dir",
]
def __init__(self, revisions=None, configs=None, path=None, **kwargs):
"""
You can either specify both *revisions* and *configs* or none
of them. If they are omitted, you will need to call
exp.add_algorithm() manually.
If *revisions* is given, it must be a non-empty list of
revision identifiers, which specify which planner versions to
use in the experiment. The same versions are used for
translator, preprocessor and search. ::
IssueExperiment(revisions=["issue123", "4b3d581643"], ...)
If *configs* is given, it must be a non-empty list of
IssueConfig objects. ::
IssueExperiment(..., configs=[
IssueConfig("ff", ["--search", "eager_greedy(ff())"]),
IssueConfig(
"lama", [],
driver_options=["--alias", "seq-sat-lama-2011"]),
])
If *path* is specified, it must be the path to where the
experiment should be built (e.g.
/home/john/experiments/issue123/exp01/). If omitted, the
experiment path is derived automatically from the main
script's filename. Example::
script = experiments/issue123/exp01.py -->
path = experiments/issue123/data/issue123-exp01/
"""
path = path or get_data_dir()
FastDownwardExperiment.__init__(self, path=path, **kwargs)
if (revisions and not configs) or (not revisions and configs):
raise ValueError(
"please provide either both or none of revisions and configs")
for rev in revisions:
for config in configs:
self.add_algorithm(
get_algo_nick(rev, config.nick),
get_repo_base(),
rev,
config.component_options,
build_options=config.build_options,
driver_options=config.driver_options)
self._revisions = revisions
self._configs = configs
@classmethod
def _is_portfolio(cls, config_nick):
return "fdss" in config_nick
@classmethod
def get_supported_attributes(cls, config_nick, attributes):
if cls._is_portfolio(config_nick):
return [attr for attr in attributes
if attr in cls.PORTFOLIO_ATTRIBUTES]
return attributes
def add_absolute_report_step(self, **kwargs):
"""Add step that makes an absolute report.
Absolute reports are useful for experiments that don't compare
revisions.
The report is written to the experiment evaluation directory.
All *kwargs* will be passed to the AbsoluteReport class. If the
keyword argument *attributes* is not specified, a default list
of attributes is used. ::
exp.add_absolute_report_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
report = AbsoluteReport(**kwargs)
outfile = os.path.join(
self.eval_dir,
get_experiment_name() + "." + report.output_format)
self.add_report(report, outfile=outfile)
self.add_step(
'publish-absolute-report', subprocess.call, ['publish', outfile])
def add_comparison_table_step(self, **kwargs):
"""Add a step that makes pairwise revision comparisons.
Create comparative reports for all pairs of Fast Downward
revisions. Each report pairs up the runs of the same config and
lists the two absolute attribute values and their difference
for all attributes in kwargs["attributes"].
All *kwargs* will be passed to the CompareConfigsReport class.
If the keyword argument *attributes* is not specified, a
default list of attributes is used. ::
exp.add_comparison_table_step(attributes=["coverage"])
"""
kwargs.setdefault("attributes", self.DEFAULT_TABLE_ATTRIBUTES)
def make_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
compared_configs = []
for config in self._configs:
config_nick = config.nick
compared_configs.append(
("%s-%s" % (rev1, config_nick),
"%s-%s" % (rev2, config_nick),
"Diff (%s)" % config_nick))
report = ComparativeReport(compared_configs, **kwargs)
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.%s" % (
self.name, rev1, rev2, report.output_format))
report(self.eval_dir, outfile)
def publish_comparison_tables():
for rev1, rev2 in itertools.combinations(self._revisions, 2):
outfile = os.path.join(
self.eval_dir,
"%s-%s-%s-compare.html" % (self.name, rev1, rev2))
subprocess.call(["publish", outfile])
self.add_step("make-comparison-tables", make_comparison_tables)
self.add_step(
"publish-comparison-tables", publish_comparison_tables)
def add_scatter_plot_step(self, relative=False, attributes=None):
"""Add step creating (relative) scatter plots for all revision pairs.
Create a scatter plot for each combination of attribute,
configuration and revisions pair. If *attributes* is not
specified, a list of common scatter plot attributes is used.
For portfolios all attributes except "cost", "coverage" and
"plan_length" will be ignored. ::
exp.add_scatter_plot_step(attributes=["expansions"])
"""
if relative:
report_class = RelativeScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-relative")
step_name = "make-relative-scatter-plots"
else:
report_class = ScatterPlotReport
scatter_dir = os.path.join(self.eval_dir, "scatter-absolute")
step_name = "make-absolute-scatter-plots"
if attributes is None:
attributes = self.DEFAULT_SCATTER_PLOT_ATTRIBUTES
def make_scatter_plot(config_nick, rev1, rev2, attribute):
name = "-".join([self.name, rev1, rev2, attribute, config_nick])
print "Make scatter plot for", name
algo1 = "{}-{}".format(rev1, config_nick)
algo2 = "{}-{}".format(rev2, config_nick)
report = report_class(
filter_config=[algo1, algo2],
attributes=[attribute],
get_category=lambda run1, run2: run1["domain"],
legend_location=(1.3, 0.5))
report(
self.eval_dir,
os.path.join(scatter_dir, rev1 + "-" + rev2, name))
def make_scatter_plots():
for config in self._configs:
for rev1, rev2 in itertools.combinations(self._revisions, 2):
for attribute in self.get_supported_attributes(
config.nick, attributes):
make_scatter_plot(config.nick, rev1, rev2, attribute)
self.add_step(step_name, make_scatter_plots)
| 14,153 | 35.955614 | 82 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue776/relativescatter.py
|
# -*- coding: utf-8 -*-
from collections import defaultdict
from matplotlib import ticker
from downward.reports.scatter import ScatterPlotReport
from downward.reports.plot import PlotReport, Matplotlib, MatplotlibPlot
# TODO: handle outliers
# TODO: this is mostly copied from ScatterMatplotlib (scatter.py)
class RelativeScatterMatplotlib(Matplotlib):
@classmethod
def _plot(cls, report, axes, categories, styles):
# Display grid
axes.grid(b=True, linestyle='-', color='0.75')
has_points = False
# Generate the scatter plots
for category, coords in sorted(categories.items()):
X, Y = zip(*coords)
axes.scatter(X, Y, s=42, label=category, **styles[category])
if X and Y:
has_points = True
if report.xscale == 'linear' or report.yscale == 'linear':
plot_size = report.missing_val * 1.01
else:
plot_size = report.missing_val * 1.25
# make 5 ticks above and below 1
yticks = []
tick_step = report.ylim_top**(1/5.0)
for i in xrange(-5, 6):
yticks.append(tick_step**i)
axes.set_yticks(yticks)
axes.get_yaxis().set_major_formatter(ticker.ScalarFormatter())
axes.set_xlim(report.xlim_left or -1, report.xlim_right or plot_size)
axes.set_ylim(report.ylim_bottom or -1, report.ylim_top or plot_size)
for axis in [axes.xaxis, axes.yaxis]:
MatplotlibPlot.change_axis_formatter(
axis,
report.missing_val if report.show_missing else None)
return has_points
class RelativeScatterPlotReport(ScatterPlotReport):
"""
Generate a scatter plot that shows a relative comparison of two
algorithms with regard to the given attribute. The attribute value
of algorithm 1 is shown on the x-axis and the relation to the value
of algorithm 2 on the y-axis.
"""
def __init__(self, show_missing=True, get_category=None, **kwargs):
ScatterPlotReport.__init__(self, show_missing, get_category, **kwargs)
if self.output_format == 'tex':
raise "not supported"
else:
self.writer = RelativeScatterMatplotlib
def _fill_categories(self, runs):
# We discard the *runs* parameter.
# Map category names to value tuples
categories = defaultdict(list)
self.ylim_bottom = 2
self.ylim_top = 0.5
self.xlim_left = float("inf")
for (domain, problem), runs in self.problem_runs.items():
if len(runs) != 2:
continue
run1, run2 = runs
assert (run1['algorithm'] == self.algorithms[0] and
run2['algorithm'] == self.algorithms[1])
val1 = run1.get(self.attribute)
val2 = run2.get(self.attribute)
if val1 is None or val2 is None:
continue
category = self.get_category(run1, run2)
assert val1 > 0, (domain, problem, self.algorithms[0], val1)
assert val2 > 0, (domain, problem, self.algorithms[1], val2)
x = val1
y = val2 / float(val1)
categories[category].append((x, y))
self.ylim_top = max(self.ylim_top, y)
self.ylim_bottom = min(self.ylim_bottom, y)
self.xlim_left = min(self.xlim_left, x)
# center around 1
if self.ylim_bottom < 1:
self.ylim_top = max(self.ylim_top, 1 / float(self.ylim_bottom))
if self.ylim_top > 1:
self.ylim_bottom = min(self.ylim_bottom, 1 / float(self.ylim_top))
return categories
def _set_scales(self, xscale, yscale):
# ScatterPlot uses log-scaling on the x-axis by default.
PlotReport._set_scales(
self, xscale or self.attribute.scale or 'log', 'log')
| 3,875 | 35.566038 | 78 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue776/v1-lama-second.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 = ["issue776-base", "issue776-v1"]
CONFIGS = [
IssueConfig('lama-second', [
"--heuristic",
"hlm2=lama_synergy(lm_rhw(reasonable_orders=true,lm_cost_type=plusone),transform=adapt_costs(plusone))",
"--heuristic",
"hff2=ff_synergy(hlm2)",
"--search",
"lazy_greedy([hff2,hlm2],preferred=[hff2,hlm2],reopen_closed=false)"
]),
]
SUITE = [
'barman-opt11-strips', 'barman-sat11-strips', 'citycar-opt14-adl',
'citycar-sat14-adl', 'elevators-opt08-strips', 'elevators-opt11-strips',
'elevators-sat08-strips', 'elevators-sat11-strips',
'floortile-opt11-strips', 'floortile-opt14-strips',
'floortile-sat11-strips', 'floortile-sat14-strips', 'openstacks-opt08-adl',
'openstacks-sat08-adl', 'parcprinter-08-strips',
'parcprinter-opt11-strips', 'parking-opt11-strips', 'parking-opt14-strips',
'parking-sat11-strips', 'parking-sat14-strips', 'pegsol-08-strips',
'pegsol-opt11-strips', 'pegsol-sat11-strips', 'scanalyzer-08-strips',
'scanalyzer-opt11-strips', 'scanalyzer-sat11-strips',
'sokoban-opt08-strips', 'sokoban-opt11-strips', 'sokoban-sat08-strips',
'sokoban-sat11-strips', 'tetris-opt14-strips', 'tetris-sat14-strips',
'woodworking-opt08-strips', 'woodworking-opt11-strips',
'woodworking-sat08-strips', 'woodworking-sat11-strips'
]
ENVIRONMENT = BaselSlurmEnvironment(email="[email protected]",partition='infai_1')
if common_setup.is_test_run():
SUITE = IssueExperiment.DEFAULT_TEST_SUITE
ENVIRONMENT = LocalEnvironment(processes=4)
exp = IssueExperiment(
revisions=REVISIONS,
configs=CONFIGS,
environment=ENVIRONMENT,
)
exp.add_suite(BENCHMARKS_DIR, SUITE)
exp.add_parse_again_step()
exp.add_comparison_table_step()
exp.run_steps()
| 2,196 | 33.873016 | 112 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/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'])
| 4,337 | 60.971429 | 280 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/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'])
| 4,337 | 60.971429 | 280 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/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'])
| 4,341 | 61.028571 | 281 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/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'])
| 5,019 | 55.404494 | 280 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/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()
| 3,824 | 33.459459 | 107 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/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()
| 2,676 | 36.180556 | 135 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/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))
| 12,539 | 34.027933 | 83 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/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'])
| 5,392 | 55.768421 | 280 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/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'])
| 4,342 | 61.042857 | 280 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/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')
| 4,690 | 35.937008 | 84 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/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'])
| 5,780 | 57.393939 | 280 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/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'])
| 4,342 | 61.042857 | 280 |
py
|
DAAISy
|
DAAISy-main/dependencies/FD/experiments/issue696/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 = ["issue696-base", "issue696-v1"]
CONFIGS = [
IssueConfig(
"lazy_greedy_{}".format(heuristic),
["--heuristic", "h={}()".format(heuristic),
"--search", "lazy_greedy(h, preferred=h)"])
for heuristic in ["add", "cea", "cg", "ff"]
] + [
IssueConfig(
"ehc_{}".format(heuristic),
["--heuristic", "h={}()".format(heuristic),
"--search", "ehc(h, preferred=h)"])
for heuristic in ["ff"]
]
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(attributes=["total_time", "memory"])
exp()
| 2,671 | 37.171429 | 73 |
py
|
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