Source code for dakotathon.utils
#! /usr/bin/env python
"""Helper functions for processing Dakota parameter and results files."""
import os
import subprocess
import re
import yaml
import numpy as np
import collections
[docs]def is_dakota_installed():
"""Check whether Dakota is installed and in the execution path.
Returns
-------
bool
True if Dakota is callable.
"""
try:
subprocess.check_call(["dakota", "--version"])
except (subprocess.CalledProcessError, OSError):
return False
else:
return True
[docs]def which(prog, env=None):
"""Call the OS `which` function.
Parameters
----------
prog : str
The command name.
env : str, optional
An environment variable.
Returns
-------
The path to the command, or None if the command is not found.
"""
prog = os.environ.get(env or prog.upper(), prog)
try:
prog = subprocess.check_output(
["/usr/bin/which", prog], stderr=open("/dev/null", "w")
).strip()
except subprocess.CalledProcessError:
return None
else:
return prog
[docs]def which_dakota():
"""Locate the Dakota executable.
Returns
-------
The path to the Dakota executable, or None if Dakota is not found.
"""
return which("dakota")
[docs]def add_dyld_library_path():
"""Add the `DYLD_LIBRARY_PATH` environment variable for Dakota."""
try:
dakota_exe = which_dakota()
dakota_dir = os.path.dirname(os.path.dirname(dakota_exe))
os.environ["DYLD_LIBRARY_PATH"] = (
os.path.join(dakota_dir, "bin")
+ os.path.pathsep
+ os.path.join(dakota_dir, "lib")
)
except (AttributeError, TypeError):
return None
[docs]def get_response_descriptors(params_file):
"""Extract response descriptors from a Dakota parameters file.
Parameters
----------
params_file : str
The path to a Dakota parameters file.
Returns
-------
list
A list of response descriptors for the Dakota experiment.
"""
labels = []
try:
with open(params_file, "r") as fp:
for line in fp:
if re.search("ASV_", line):
labels.append("".join(re.findall(":(\S+)", line)))
except IOError:
return None
else:
return labels
[docs]def get_attributes(obj):
"""Get and format the attributes of an object.
Parameters
----------
section
An object that has attributes.
Returns
-------
dict
The object's attributes.
"""
attrs = obj.__dict__.copy()
for key in attrs:
if key.startswith("_"):
new_key = key.lstrip("_")
attrs[new_key] = attrs.pop(key)
return attrs
[docs]def get_configuration_file(params_file):
"""Extract the configuration filepath from a Dakota parameters file.
Parameters
----------
params_file : str
The path to a Dakota parameters file.
Returns
-------
str
The path to the configuration file for the Dakota experiment.
"""
with open(params_file, "r") as fp:
for line in fp:
if re.search("AC_1", line):
return line.split("AC_1")[0].strip()
[docs]def deserialize(config_file):
"""Load settings from a YAML configuration file.
Returns
-------
dict
Configuration settings in a dict.
"""
with open(config_file, "r") as fp:
return yaml.safe_load(fp)
[docs]def compute_statistic(statistic, array):
"""Compute the statistic used in a Dakota response function.
Parameters
----------
statistic : str
A string with the name of the statistic to compute ('mean',
'median', etc.).
array : array_like
An array data structure, such as a numpy array.
Returns
-------
float
The value of the computed statistic.
"""
return np.__getattribute__(statistic)(array)
[docs]def write_results(results_file, values, labels):
"""Write a Dakota results file from a set of input values.
Parameters
----------
results_file : str
The path to a Dakota results file.
values : array_like
A list or array of numeric values.
labels : str
A list of labels to attach to the values.
"""
arr_values = np.asarray(values)
arr_labels = np.asarray(labels)
results = np.column_stack((arr_values, arr_labels))
np.savetxt(results_file, results, delimiter="\t", fmt="%s")
[docs]def to_iterable(x):
"""Get an iterable version of an input.
Parameters
----------
x
Anything.
Returns
-------
If the input isn't iterable, or is a string, then a tuple; else,
the input.
Notes
-----
Courtesy http://stackoverflow.com/a/6711233/1563298
"""
if isinstance(x, collections.Iterable) and not isinstance(x, str):
return x
else:
return (x,)
