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Build # 1704

Build Type

Pull #527

travis-ci

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web-flow

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<a href="https://github.com/fitbenchmarking/fitbenchmarking/commit/<a class=hub.com/fitbenchmarking/fitbenchmarking/commit/d20d397e47308d74a805885e123045ec7787a1bc">d20d397e4<a href="https://github.com/fitbenchmarking/fitbenchmarking/commit/d20d397e47308d74a805885e123045ec7787a1bc">">Merge </a><a class="double-link" href="https://github.com/fitbenchmarking/fitbenchmarking/commit/<a class="double-link" href="https://github.com/fitbenchmarking/fitbenchmarking/commit/d87218ed4274157725bf679b978198bd69263d40">d87218ed4</a>">d87218ed4</a><a href="https://github.com/fitbenchmarking/fitbenchmarking/commit/d20d397e47308d74a805885e123045ec7787a1bc"> into dcd2c1a37">dcd2c1a37</a>

Pull Request Pull Request #527: Algorithm type option

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20.93

/fitbenchmarking/core/fitting_benchmarking.py

"""
Main module of the tool, this holds the master function that calls
lower level functions to fit and benchmark a set of problems
for a certain fitting software.
"""

from __future__ import absolute_import, division, print_function

from fitbenchmarking.core.fitbenchmark_one_problem import fitbm_one_prob
from fitbenchmarking.parsing.parser_factory import parse_problem_file
from fitbenchmarking.jacobian.jacobian_factory import create_jacobian
from fitbenchmarking.utils import misc, output_grabber
from fitbenchmarking.utils.exceptions import NoResultsError
from fitbenchmarking.utils.log import get_logger

LOGGER = get_logger()


def fitbenchmark_group(group_name, options, data_dir):
    """
    Gather the user input and list of paths. Call benchmarking on these.

    :param group_name: is the name (label) for a group. E.g. the name for
                       the group of problems in "NIST/low_difficulty" may be
                       picked to be NIST_low_difficulty
    :type group_name: str
    :param options: dictionary containing software used in fitting
                    the problem, list of minimizers and location of
                    json file contain minimizers
    :type options: fitbenchmarking.utils.options.Options
    :param data_dir: full path of a directory that holds a group of problem
                     definition files
    :type date_dir: str

    :return: prob_results array of fitting results for the problem group,
             list of failed problems and dictionary of unselected minimizers
    :rtype: tuple(list, list, dict)
    """
    grabbed_output = output_grabber.OutputGrabber(options)

    # Extract problem definitions
    problem_group = misc.get_problem_files(data_dir)

    results = []

    failed_problems = []
    for i, p in enumerate(problem_group):
        with grabbed_output:
            parsed_problem = parse_problem_file(p, options)
        parsed_problem.correct_data()

        # Creates Jacobian class
        jacobian_cls = create_jacobian(options)
        jacobian = jacobian_cls(parsed_problem)

        # Making the Jacobian class part of the fitting problem. This will
        # eventually be extended to have Hessian information too.
        parsed_problem.jac = jacobian

        name = parsed_problem.name

        info_str = " Running data from: {} {}/{}".format(
            name, i + 1, len(problem_group))
        LOGGER.info('#' * (len(info_str) + 1))
        LOGGER.info(info_str)
        LOGGER.info('#' * (len(info_str) + 1))

        problem_results, problem_fails, unselected_minimzers = \
            fitbm_one_prob(problem=parsed_problem,
                           options=options)
        results.extend(problem_results)
        failed_problems.extend(problem_fails)

    for keys, minimzers in unselected_minimzers.items():
        minimizers_all = options.minimizers[keys]
        options.minimizers[keys] = list(set(minimizers_all) - set(minimzers))

    # options.minimizers = converge_minimizers
    # If the results are and empty list then this means that all minimizers
    # raise an exception and the tables will produce errors if they run.
    if results == []:
        message = "The current options set up meant that all minimizers set " \
                  "raised an exception. This is likely due to the " \
                  "`algorithm_type` set in the options. Please review " \
                  "current options setup and re-run FitBenmarking."
        raise NoResultsError(message)

    # Used to group elements in list by name
    results_dict = {}
    for problem_result in results:
        name = problem_result.name
        # group by name
        try:
            results_dict[name].append(problem_result)
        except KeyError:
            results_dict[name] = [problem_result]

    results = [results_dict[r] for r in
               sorted(results_dict.keys(), key=str.lower)]

    return results, failed_problems, unselected_minimzers

1	"""
2	Main module of the tool, this holds the master function that calls
3	lower level functions to fit and benchmark a set of problems
4	for a certain fitting software.
5	"""
6
7	from __future__ import absolute_import, division, print_function	1✔
8
9	from fitbenchmarking.core.fitbenchmark_one_problem import fitbm_one_prob	1✔
10	from fitbenchmarking.parsing.parser_factory import parse_problem_file	1✔
11	from fitbenchmarking.jacobian.jacobian_factory import create_jacobian	1✔
12	from fitbenchmarking.utils import misc, output_grabber	1✔
13	from fitbenchmarking.utils.exceptions import NoResultsError	1✔
14	from fitbenchmarking.utils.log import get_logger	1✔
15
16	LOGGER = get_logger()	1✔
17
18
19	def fitbenchmark_group(group_name, options, data_dir):	1✔
20	"""
21	Gather the user input and list of paths. Call benchmarking on these.
22
23	:param group_name: is the name (label) for a group. E.g. the name for
24	the group of problems in "NIST/low_difficulty" may be
25	picked to be NIST_low_difficulty
26	:type group_name: str
27	:param options: dictionary containing software used in fitting
28	the problem, list of minimizers and location of
29	json file contain minimizers
30	:type options: fitbenchmarking.utils.options.Options
31	:param data_dir: full path of a directory that holds a group of problem
32	definition files
33	:type date_dir: str
34
35	:return: prob_results array of fitting results for the problem group,
36	list of failed problems and dictionary of unselected minimizers
37	:rtype: tuple(list, list, dict)
38	"""
39	grabbed_output = output_grabber.OutputGrabber(options)	×
40
41	# Extract problem definitions
42	problem_group = misc.get_problem_files(data_dir)	×
43
44	results = []	×
45
46	failed_problems = []	×
47	for i, p in enumerate(problem_group):	×
48	with grabbed_output:	×
49	parsed_problem = parse_problem_file(p, options)	×
50	parsed_problem.correct_data()	×
51
52	# Creates Jacobian class
53	jacobian_cls = create_jacobian(options)	×
54	jacobian = jacobian_cls(parsed_problem)	×
55
56	# Making the Jacobian class part of the fitting problem. This will
57	# eventually be extended to have Hessian information too.
58	parsed_problem.jac = jacobian	×
59
60	name = parsed_problem.name	×
61
62	info_str = " Running data from: {} {}/{}".format(	×
63	name, i + 1, len(problem_group))
64	LOGGER.info('#' * (len(info_str) + 1))	×
65	LOGGER.info(info_str)	×
66	LOGGER.info('#' * (len(info_str) + 1))	×
67
68	problem_results, problem_fails, unselected_minimzers = \	×
69	fitbm_one_prob(problem=parsed_problem,
70	options=options)
71	results.extend(problem_results)	×
72	failed_problems.extend(problem_fails)	×
73
74	for keys, minimzers in unselected_minimzers.items():	×
75	minimizers_all = options.minimizers[keys]	×
76	options.minimizers[keys] = list(set(minimizers_all) - set(minimzers))	×
77
78	# options.minimizers = converge_minimizers
79	# If the results are and empty list then this means that all minimizers
80	# raise an exception and the tables will produce errors if they run.
81	if results == []:	×
82	message = "The current options set up meant that all minimizers set " \	×
83	"raised an exception. This is likely due to the " \
84	"`algorithm_type` set in the options. Please review " \
85	"current options setup and re-run FitBenmarking."
86	raise NoResultsError(message)	×
87
88	# Used to group elements in list by name
89	results_dict = {}	×
90	for problem_result in results:	×
91	name = problem_result.name	×
92	# group by name
93	try:	×
94	results_dict[name].append(problem_result)	×
95	except KeyError:	×
96	results_dict[name] = [problem_result]	×
97
98	results = [results_dict[r] for r in	×
99	sorted(results_dict.keys(), key=str.lower)]
100
101	return results, failed_problems, unselected_minimzers	×

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