1732

pending completion

Build # 1732

Build Type

Pull #552

travis-ci

Committed by

web-flow

Commit Message

<a href="https://github.com/fitbenchmarking/fitbenchmarking/commit/<a class=hub.com/fitbenchmarking/fitbenchmarking/commit/5e94f074ea6dc8bc794ddb47ffa252d46ed59228">5e94f074e<a href="https://github.com/fitbenchmarking/fitbenchmarking/commit/5e94f074ea6dc8bc794ddb47ffa252d46ed59228">">Merge </a><a class="double-link" href="https://github.com/fitbenchmarking/fitbenchmarking/commit/<a class="double-link" href="https://github.com/fitbenchmarking/fitbenchmarking/commit/5b91ca9538393c55ef19fc94bbd844953d41e949">5b91ca953</a>">5b91ca953</a><a href="https://github.com/fitbenchmarking/fitbenchmarking/commit/5e94f074ea6dc8bc794ddb47ffa252d46ed59228"> into 7c300e071">7c300e071</a>

Pull Request Pull Request #552: Enabling comparison of multiple jacobians

Run Details

118 of 118 new or added lines in 13 files covered. (100.0%)

1929 of 2411 relevant lines covered (80.01%)

0.8 hits per line

Source File
Press 'n' to go to next uncovered line, 'b' for previous

86.67

/fitbenchmarking/controllers/minuit_controller.py

"""
Implements a controller for the CERN pacakage Minuit
https://seal.web.cern.ch/seal/snapshot/work-packages/mathlibs/minuit/
using the iminuit python interface
http://iminuit.readthedocs.org
"""
from iminuit import Minuit
import numpy as np

from fitbenchmarking.controllers.base_controller import Controller


class MinuitController(Controller):
    """
    Controller for the Minuit fitting software
    """

    def __init__(self, problem):
        """
        Initializes variable used for temporary storage.

        :param problem: Problem to fit
        :type problem: FittingProblem
        """
        super(MinuitController, self).__init__(problem)
        self._popt = None
        self._initial_step = None
        self._minuit_problem = None
        self.algorithm_check = {
            'all': ['minuit'],
            'ls': [None],
            'deriv_free': [None],
            'general': ['minuit']}

    def jacobian_information(self):
        """
        Minuit does not requires Jacobian information
        """
        has_jacobian = False
        jacobian_list = []
        return has_jacobian, jacobian_list

    def setup(self):
        """
        Setup for Minuit
        """
        # minuit requires an initial step size.
        # The docs say
        # "A good guess is a fraction of the initial
        #  fit parameter value, e.g. 10%
        #  (be careful when applying this rule-of-thumb
        #  when the initial parameter value is zero "
        self._initial_step = 0.1 * np.array(self.initial_params)
        # set small steps to something sensible(?)
        self._initial_step[self._initial_step < 1e-12] = 1e-12
        self._minuit_problem = Minuit.from_array_func(self.problem.eval_r_norm,
                                                      self.initial_params,
                                                      error=self._initial_step,
                                                      errordef=1)

    def fit(self):
        """
        Run problem with Minuit
        """
        self._minuit_problem.migrad()  # run optimizer
        self._status = 0 if self._minuit_problem.migrad_ok() else 1

    def cleanup(self):
        """
        Convert the result to a numpy array and populate the variables results
        will be read from
        """
        fmin = self._minuit_problem.get_fmin()
        if self._status == 0:
            self.flag = 0
        elif fmin.has_reached_call_limit:
            self.flag = 1
        else:
            self.flag = 2

        self._popt = self._minuit_problem.np_values()
        self.final_params = self._popt

1	"""
2	Implements a controller for the CERN pacakage Minuit
3	https://seal.web.cern.ch/seal/snapshot/work-packages/mathlibs/minuit/
4	using the iminuit python interface
5	http://iminuit.readthedocs.org
6	"""
7	from iminuit import Minuit	1✔
8	import numpy as np	1✔
9
10	from fitbenchmarking.controllers.base_controller import Controller	1✔
11
12
13	class MinuitController(Controller):	1✔
14	"""
15	Controller for the Minuit fitting software
16	"""
17
18	def __init__(self, problem):	1✔
19	"""
20	Initializes variable used for temporary storage.
21
22	:param problem: Problem to fit
23	:type problem: FittingProblem
24	"""
25	super(MinuitController, self).__init__(problem)	1✔
26	self._popt = None	1✔
27	self._initial_step = None	1✔
28	self._minuit_problem = None	1✔
29	self.algorithm_check = {	1✔
30	'all': ['minuit'],
31	'ls': [None],
32	'deriv_free': [None],
33	'general': ['minuit']}
34
35	def jacobian_information(self):	1✔
36	"""
37	Minuit does not requires Jacobian information
38	"""
39	has_jacobian = False	×
40	jacobian_list = []	×
41	return has_jacobian, jacobian_list	×
42
43	def setup(self):	1✔
44	"""
45	Setup for Minuit
46	"""
47	# minuit requires an initial step size.
48	# The docs say
49	# "A good guess is a fraction of the initial
50	# fit parameter value, e.g. 10%
51	# (be careful when applying this rule-of-thumb
52	# when the initial parameter value is zero "
53	self._initial_step = 0.1 * np.array(self.initial_params)	1✔
54	# set small steps to something sensible(?)
55	self._initial_step[self._initial_step < 1e-12] = 1e-12	1✔
56	self._minuit_problem = Minuit.from_array_func(self.problem.eval_r_norm,	1✔
57	self.initial_params,
58	error=self._initial_step,
59	errordef=1)
60
61	def fit(self):	1✔
62	"""
63	Run problem with Minuit
64	"""
65	self._minuit_problem.migrad() # run optimizer	1✔
66	self._status = 0 if self._minuit_problem.migrad_ok() else 1	1✔
67
68	def cleanup(self):	1✔
69	"""
70	Convert the result to a numpy array and populate the variables results
71	will be read from
72	"""
73	fmin = self._minuit_problem.get_fmin()	1✔
74	if self._status == 0:	1✔
75	self.flag = 0	1✔
76	elif fmin.has_reached_call_limit:	1✔
77	self.flag = 1	×
78	else:
79	self.flag = 2	1✔
80
81	self._popt = self._minuit_problem.np_values()	1✔
82	self.final_params = self._popt	1✔

fitbenchmarking / fitbenchmarking / 1732

Source File Press 'n' to go to next uncovered line, 'b' for previous

Source File
Press 'n' to go to next uncovered line, 'b' for previous