def write(self, stream, prefix="", pretty=False):
"""Writes results in YAML format to a stream or
file.
Parameters
----------
stream : file-like object or string
A file-like object or a filename where results
should be written to.
prefix : string, optional
A string to use as a prefix for each line that
is written. (default: '')
pretty : bool, optional
Indicates whether or not certain recognized
attributes should be formatted for more
human-readable output. (default: False)
"""
with as_stream(stream) as stream:
attrs = vars(self)
names = sorted(list(attrs.keys()))
first = ('solution_status', 'termination_condition',
'objective', 'bound',
'absolute_gap', 'relative_gap',
'nodes', 'wall_time')
for cnt, name in enumerate(first):
if not hasattr(self, name):
continue
names.remove(name)
val = getattr(self, name)
if val is not None:
if pretty:
if name == 'wall_time':
val = time_format(val, digits=2)
elif name in ('objective','bound',
'absolute_gap','relative_gap'):
val = "%.7g" % (val)
if name in ("solution_status", "termination_condition"):
val = val.value
stream.write(prefix+'%s: %s\n'
% (name, val))
for name in names:
stream.write(prefix+'%s: %s\n'
% (name, getattr(self, name)))
def write(self, stream, prefix="", pretty=False):
# type: (Union[IO, str], str, bool) -> None
"""Writes results in YAML format to a stream or
file. Changing the parameter values from their
defaults may result in the output becoming
non-compatible with the YAML format.
Parameters
----------
stream : file-like object or string
A file-like object or a filename where results
should be written to.
prefix : string, optional
A string to use as a prefix for each line that
is written. (default: '')
pretty : bool, optional
Indicates whether or not certain recognized
attributes should be formatted for more
human-readable output. (default: False)
Example
-------
>>> import six
>>> import pybnb
>>> results = pybnb.SolverResults()
>>> results.best_node = pybnb.Node()
>>> results.best_node.objective = 123
>>> out = six.StringIO()
>>> # the best_node is serialized
>>> results.write(out)
>>> del results
>>> import yaml
>>> results_dict = yaml.safe_load(out.getvalue())
>>> # de-serialize the best_node
>>> best_node = pybnb.node.loads(results_dict['best_node'])
>>> assert best_node.objective == 123
"""
with as_stream(stream) as out:
attrs = vars(self)
names = sorted(list(attrs.keys()))
first = (
"solution_status",
"termination_condition",
"objective",
"bound",
"absolute_gap",
"relative_gap",
"nodes",
"wall_time",
"best_node",
)
for cnt, name in enumerate(first):
if not hasattr(self, name):
continue
names.remove(name)
val = getattr(self, name)
if val is not None:
if name in ("solution_status", "termination_condition"):
if type(val) in (SolutionStatus, TerminationCondition):
val = val.value
elif pretty:
if name == "wall_time":
val = time_format(val, digits=2)
elif name in (
"objective",
"bound",
"absolute_gap",
"relative_gap",
):
val = "%.7g" % (val)
elif name == "best_node":
assert isinstance(val, Node)
if val.objective is not None:
val = "Node(objective=%.7g)" % (val.objective)
else:
val = "Node(objective=None)"
else:
if name == "best_node":
val = dumps(val)
if not six.PY2:
val = base64.encodebytes(val).decode("ascii")
else:
val = base64.encodestring(val).decode("ascii")
val = "\n ".join(val.splitlines())
val = "!!binary |\n %s" % (val)
else:
val_ = "%r" % (val)
if type(val) is float:
if val_ == "inf":
val_ = ".inf"
elif val_ == "-inf":
val_ = "-.inf"
elif val_ == "nan":
val_ = ".nan"
val = val_
del val_
if pretty or (val is not None):
out.write(prefix + "%s: %s\n" % (name, val))
else:
assert val is None
out.write(prefix + "%s: null\n" % (name))
for name in names:
val = getattr(self, name)
if pretty:
out.write(prefix + "%s: %r\n" % (name, val))
else:
if val is None:
out.write(prefix + "%s: null\n" % (name))
else:
val_ = "%r" % (val)
if type(val) is float:
if val_ == "inf":
val_ = ".inf"
elif val_ == "-inf":
val_ = "-.inf"
elif val_ == "nan":
val_ = ".nan"
val = val_
del val_
out.write(prefix + "%s: %s\n" % (name, val))
def test_time_format(self):
assert time_format(None) == "<unknown>"
assert time_format(0.0) == "0.0 s"
assert time_format(0.0, align_unit=True) == "0.0 s "
assert time_format(0.0, digits=2) == "0.00 s"
assert time_format(24.9) == "24.9 s"
assert time_format(93.462, digits=3) == "1.558 m"
assert time_format(93.462, digits=4) == "1.5577 m"
assert time_format(93.462, digits=4, align_unit=True) == "1.5577 m "
assert time_format(5607.72, digits=3) == "1.558 h"
assert time_format(5607.72, digits=4) == "1.5577 h"
assert time_format(5607.72, digits=4, align_unit=True) == "1.5577 h "
assert time_format(134585.28, digits=3) == "1.558 d"
assert time_format(134585.28, digits=4) == "1.5577 d"
assert time_format(134585.28, digits=4, align_unit=True) == "1.5577 d "
assert time_format(0.23334, digits=1) == "233.3 ms"
assert time_format(0.23334, digits=2) == "233.34 ms"
assert time_format(0.00023334, digits=1) == "233.3 us"
assert time_format(0.00023334, digits=2) == "233.34 us"
assert time_format(0.0009999, digits=1) == "999.9 us"
assert time_format(0.00099999, digits=1) == "1.0 ms"
assert time_format(0.00099999, digits=2) == "999.99 us"
assert time_format(0.000999999, digits=2) == "1.00 ms"
assert time_format(0.000999999, digits=3) == "999.999 us"
assert time_format(0.0009999999, digits=3) == "1.000 ms"
assert time_format(0.0009999999, digits=4) == "999.9999 us"
assert time_format(0.00099999999, digits=4) == "1.0000 ms"
assert time_format(0.00099999999, digits=5) == "999.99999 us"
assert time_format(0.000999999999, digits=5) == "1.00000 ms"
assert time_format(0.000999999999, digits=6) == "999.999999 us"
def summarize_worker_statistics(stats, stream=sys.stdout):
"""Writes a summary of workers statistics to an
output stream.
Parameters
----------
stats : dict
A dictionary of worker statistics returned from
a call to :func:`collect_worker_statistics`.
stream : file-like object, or string, optional
A file-like object or a filename where results
should be written to. (default: ``sys.stdout``)
"""
import numpy
wall_time = numpy.array(stats['wall_time'],
dtype=float)
queue_time = numpy.array(stats['queue_time'],
dtype=float)
queue_count = numpy.array(stats['queue_call_count'],
dtype=int)
objective_time = numpy.array(stats['objective_time'],
dtype=float)
objective_count = numpy.array(stats['objective_call_count'],
dtype=int)
bound_time = numpy.array(stats['bound_time'],
dtype=float)
bound_count = numpy.array(stats['bound_call_count'],
dtype=int)
branch_time = numpy.array(stats['branch_time'],
dtype=float)
branch_count = numpy.array(stats['branch_call_count'],
dtype=int)
load_state_time = numpy.array(stats['load_state_time'],
dtype=float)
load_state_count = numpy.array(stats['load_state_call_count'],
dtype=int)
explored_nodes_count = numpy.array(stats['explored_nodes_count'],
dtype=int)
work_time = wall_time - queue_time
with as_stream(stream) as stream:
stream.write("Number of Workers: %6d\n"
% (len(wall_time)))
div = max(1.0,numpy.mean(explored_nodes_count))
numerator = numpy.max(explored_nodes_count) - \
numpy.min(explored_nodes_count)
if explored_nodes_count.sum() == 0:
stream.write("Load Imbalance: %6.2f%%\n"
% (0.0))
else:
stream.write("Load Imbalance: %6.2f%%\n"
% (numerator/div*100.0))
stream.write(" - min: %d\n" % (numpy.min(explored_nodes_count)))
stream.write(" - max: %d\n" % (numpy.max(explored_nodes_count)))
stream.write("Average Worker Timing:\n")
queue_count_str = "%d" % queue_count.sum()
tmp = "%"+str(len(queue_count_str))+"d"
bound_count_str = tmp % bound_count.sum()
objective_count_str = tmp % objective_count.sum()
branch_count_str = tmp % branch_count.sum()
load_state_count_str = tmp % load_state_count.sum()
div1 = numpy.copy(wall_time)
div1[div1 == 0] = 1
div2 = numpy.copy(queue_count)
div2[div2 == 0] = 1
stream.write(" - queue: %6.2f%% [avg time: %8s, count: %s]\n"
% (numpy.mean(queue_time/div1)*100.0,
time_format(numpy.mean(queue_time/div2),
align_unit=True),
queue_count_str))
div2 = numpy.copy(load_state_count)
div2[div2==0] = 1
stream.write(" - load_state:%6.2f%% [avg time: %8s, count: %s]\n"
% (numpy.mean((load_state_time/div1))*100.0,
time_format(numpy.mean(load_state_time/div2),
align_unit=True),
load_state_count_str))
div2 = numpy.copy(bound_count)
div2[div2==0] = 1
stream.write(" - bound: %6.2f%% [avg time: %8s, count: %s]\n"
% (numpy.mean((bound_time/div1))*100.0,
time_format(numpy.mean(bound_time/div2),
align_unit=True),
bound_count_str))
div2 = numpy.copy(objective_count)
div2[div2==0] = 1
stream.write(" - objective: %6.2f%% [avg time: %8s, count: %s]\n"
% (numpy.mean((objective_time/div1))*100.0,
time_format(numpy.mean(objective_time/div2),
align_unit=True),
objective_count_str))
div2 = numpy.copy(branch_count)
div2[div2==0] = 1
stream.write(" - branch: %6.2f%% [avg time: %8s, count: %s]\n"
% (numpy.mean((branch_time/div1))*100.0,
time_format(numpy.mean(branch_time/div2),
align_unit=True),
branch_count_str))
other_time = work_time - objective_time - bound_time - branch_time - load_state_time
div2 = numpy.copy(queue_count)
div2[div2 == 0] = 1
stream.write(" - other: %6.2f%% [avg time: %8s, count: %s]\n"
% (numpy.mean(other_time/div1)*100.0,
time_format(numpy.mean(other_time/div2),
align_unit=True),
queue_count_str))