from itertools import product
import io
import numpy as np
import warnings
import numpy.core.numeric as nx
try:
DRMAA_AVAILABLE = True
import drmaa
except(RuntimeError):
DRMAA_AVAILABLE = False
[docs]def list_param_combinations(param_ranges):
"""
Create a list of all parameter combinations from a dictionary specifying
desired parameter values as lists.
Example:
>>> param_ranges = {'a': [1], 'b': [2, 3]}
>>> list_param_combinations(param_ranges)
[{'a': 1, 'b': 2}, {'a': 1, 'b': 3}]
Additionally, this function is robust in case values are not lists:
>>> param_ranges = {'a': 1, 'b': [2, 3]}
>>> list_param_combinations(param_ranges)
[{'a': 1, 'b': 2}, {'a': 1, 'b': 3}]
"""
# Convert non-list values to single-element lists
# This is required to make sure product work.
for key in param_ranges:
if not isinstance(param_ranges[key], list):
param_ranges[key] = [param_ranges[key]]
return [dict(zip(param_ranges, v)) for v in
product(*param_ranges.values())]
[docs]def get_command_from_result(script, result, debug=False):
"""
Return the command that is needed to obtain a certain result.
Args:
params (dict): Dictionary containing parameter: value pairs.
debug (bool): Whether the command should include the debugging
template.
"""
if not debug:
command = "python waf --run \"" + script + " " + " ".join(
['--%s=%s' % (param, value) for param, value in
result['params'].items()]) + "\""
else:
command = "python waf --run " + script + " --command-template=\"" +\
"gdb --args %s " + " ".join(['--%s=%s' % (param, value) for
param, value in
result['params'].items()]) + "\""
return command
[docs]def constant_array_parser(result):
"""
Dummy parser, used for testing purposes.
"""
return [0, 1, 2, 3]
[docs]def automatic_parser(result, dtypes={}, converters={}):
"""
Try and automatically convert strings formatted as tables into nested
list structures.
Under the hood, this function essentially applies the genfromtxt function
to all files in the output, and passes it the additional kwargs.
Args:
result (dict): the result to parse.
dtypes (dict): a dictionary containing the dtype specification to perform
parsing for each available filename. See the numpy genfromtxt
documentation for more details on how to format these.
"""
np.seterr(all='raise')
parsed = {}
# By default, if dtype is None, the order Numpy tries to convert a string
# to a value is: bool, int, float. We don't like this, since it would give
# us a mixture of integers and doubles in the output, if any integers
# existed in the data. So, we modify the StringMapper's default mapper to
# skip the int check and directly convert numbers to floats.
oldmapper = np.lib._iotools.StringConverter._mapper
np.lib._iotools.StringConverter._mapper = [(nx.bool_, np.lib._iotools.str2bool, False),
(nx.floating, float, nx.nan),
(nx.complexfloating, complex, nx.nan + 0j),
(nx.longdouble, nx.longdouble, nx.nan)]
for filename, contents in result['output'].items():
if dtypes.get(filename) is None:
dtypes[filename] = None
if converters.get(filename) is None:
converters[filename] = None
with warnings.catch_warnings():
warnings.simplefilter("ignore")
parsed[filename] = np.genfromtxt(io.StringIO(contents),
dtype=dtypes[filename],
converters=converters[filename]
).tolist()
# Here we restore the original mapper, so no side-effects remain.
np.lib._iotools.StringConverter._mapper = oldmapper
return parsed
[docs]def stdout_automatic_parser(result):
"""
Try and automatically convert strings formatted as tables into a matrix.
Under the hood, this function essentially applies the genfromtxt function
to the stdout.
Args:
result (dict): the result to parse.
"""
np.seterr(all='raise')
parsed = {}
# By default, if dtype is None, the order Numpy tries to convert a string
# to a value is: bool, int, float. We don't like this, since it would give
# us a mixture of integers and doubles in the output, if any integers
# existed in the data. So, we modify the StringMapper's default mapper to
# skip the int check and directly convert numbers to floats.
oldmapper = np.lib._iotools.StringConverter._mapper
np.lib._iotools.StringConverter._mapper = [(nx.bool_, np.lib._iotools.str2bool, False),
(nx.floating, float, nx.nan),
(nx.complexfloating, complex, nx.nan + 0j),
(nx.longdouble, nx.longdouble, nx.nan)]
file_contents = result['output']['stdout']
with warnings.catch_warnings():
warnings.simplefilter("ignore")
parsed = np.genfromtxt(io.StringIO(file_contents))
# Here we restore the original mapper, so no side-effects remain.
np.lib._iotools.StringConverter._mapper = oldmapper
return parsed