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Build # 1621

Build Type

Pull #539

travis-ci

Committed by

web-flow

Commit Message

<a href="https://github.com/fitbenchmarking/fitbenchmarking/commit/<a class=hub.com/fitbenchmarking/fitbenchmarking/commit/2b42579b6e88872ee3b1747b946f0b5841e3839f">2b42579b6<a href="https://github.com/fitbenchmarking/fitbenchmarking/commit/2b42579b6e88872ee3b1747b946f0b5841e3839f">">Merge </a><a class="double-link" href="https://github.com/fitbenchmarking/fitbenchmarking/commit/<a class="double-link" href="https://github.com/fitbenchmarking/fitbenchmarking/commit/9c39aa6aff80af1bb271c5dc608d5118273f1533">9c39aa6af</a>">9c39aa6af</a><a href="https://github.com/fitbenchmarking/fitbenchmarking/commit/2b42579b6e88872ee3b1747b946f0b5841e3839f"> into 5d00e88fd">5d00e88fd</a>

Pull Request Pull Request #539: Changing name of sasview controller to bumps

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93.02

/fitbenchmarking/controllers/bumps_controller.py

"""
Implements a controller for the SasView fitting software.
"""

from bumps.fitters import fit as bumpsFit
from bumps.names import Curve, FitProblem

import numpy as np

from fitbenchmarking.controllers.base_controller import Controller


class BumpsController(Controller):
    """
    Controller for the Sasview fitting software.

    Sasview requires a model to fit.
    Setup creates a model with the correct function.
    """

    def __init__(self, problem):
        """
        Extract param names for function setup

        :param problem: Problem to fit
        :type problem: FittingProblem
        """
        super(BumpsController, self).__init__(problem)

        self._param_names = self.problem.param_names

        self._func_wrapper = None
        self._fit_problem = None
        self._bumps_result = None

    def setup(self):
        """
        Setup problem ready to run with SasView.

        Creates a Sasview FitProblem for calling in fit()
        """
        # Bumps fails with the *args notation
        param_name_str = ', '.join(self._param_names)
        wrapper = "def fitFunction(x, {}):\n".format(param_name_str)
        wrapper += "    return func(x, {})".format(param_name_str)

        exec_dict = {'func': self.problem.function}
        exec(wrapper, exec_dict)

        model = exec_dict['fitFunction']

        # Remove any function attribute. BinWidth is the only attribute in all
        # FitBenchmark (Mantid) problems.
        param_dict = {name: value
                      for name, value
                      in zip(self._param_names, self.initial_params)}

        # Create a Function Wrapper for the problem function. The type of the
        # Function Wrapper is acceptable by Bumps.
        func_wrapper = Curve(fn=model,
                             x=self.data_x,
                             y=self.data_y,
                             dy=self.data_e,
                             **param_dict)

        # Set a range for each parameter
        val_ranges = self.problem.value_ranges
        for name in self._param_names:
            min_val = -np.inf
            max_val = np.inf
            if val_ranges is not None and name in val_ranges:
                min_val = val_ranges[name][0]
                max_val = val_ranges[name][1]
            func_wrapper.__dict__[name].range(min_val, max_val)

        # Create a Problem Wrapper. The type of the Problem Wrapper is
        # acceptable by Bumps fitting.
        self._func_wrapper = func_wrapper
        self._fit_problem = FitProblem(func_wrapper)
        if self.minimizer == "lm-bumps":
            self.minimizer = "lm"

    def fit(self):
        """
        Run problem with SasView.
        """
        result = bumpsFit(self._fit_problem, method=self.minimizer)

        self._bumps_result = result
        self._status = self._bumps_result.status

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

        self.final_params = self._bumps_result.x

1	"""
2	Implements a controller for the SasView fitting software.
3	"""
4
5	from bumps.fitters import fit as bumpsFit	1✔
6	from bumps.names import Curve, FitProblem	1✔
7
8	import numpy as np	1✔
9
10	from fitbenchmarking.controllers.base_controller import Controller	1✔
11
12
13	class BumpsController(Controller):	1✔
14	"""
15	Controller for the Sasview fitting software.
16
17	Sasview requires a model to fit.
18	Setup creates a model with the correct function.
19	"""
20
21	def __init__(self, problem):	1✔
22	"""
23	Extract param names for function setup
24
25	:param problem: Problem to fit
26	:type problem: FittingProblem
27	"""
28	super(BumpsController, self).__init__(problem)	1✔
29
30	self._param_names = self.problem.param_names	1✔
31
32	self._func_wrapper = None	1✔
33	self._fit_problem = None	1✔
34	self._bumps_result = None	1✔
35
36	def setup(self):	1✔
37	"""
38	Setup problem ready to run with SasView.
39
40	Creates a Sasview FitProblem for calling in fit()
41	"""
42	# Bumps fails with the *args notation
43	param_name_str = ', '.join(self._param_names)	1✔
44	wrapper = "def fitFunction(x, {}):\n".format(param_name_str)	1✔
45	wrapper += " return func(x, {})".format(param_name_str)	1✔
46
47	exec_dict = {'func': self.problem.function}	1✔
48	exec(wrapper, exec_dict)	1✔
49
50	model = exec_dict['fitFunction']	1✔
51
52	# Remove any function attribute. BinWidth is the only attribute in all
53	# FitBenchmark (Mantid) problems.
54	param_dict = {name: value	1✔
55	for name, value
56	in zip(self._param_names, self.initial_params)}
57
58	# Create a Function Wrapper for the problem function. The type of the
59	# Function Wrapper is acceptable by Bumps.
60	func_wrapper = Curve(fn=model,	1✔
61	x=self.data_x,
62	y=self.data_y,
63	dy=self.data_e,
64	**param_dict)
65
66	# Set a range for each parameter
67	val_ranges = self.problem.value_ranges	1✔
68	for name in self._param_names:	1✔
69	min_val = -np.inf	1✔
70	max_val = np.inf	1✔
71	if val_ranges is not None and name in val_ranges:	1✔
72	min_val = val_ranges[name][0]	×
73	max_val = val_ranges[name][1]	×
74	func_wrapper.__dict__[name].range(min_val, max_val)	1✔
75
76	# Create a Problem Wrapper. The type of the Problem Wrapper is
77	# acceptable by Bumps fitting.
78	self._func_wrapper = func_wrapper	1✔
79	self._fit_problem = FitProblem(func_wrapper)	1✔
80	if self.minimizer == "lm-bumps":	1✔
81	self.minimizer = "lm"	×
82
83	def fit(self):	1✔
84	"""
85	Run problem with SasView.
86	"""
87	result = bumpsFit(self._fit_problem, method=self.minimizer)	1✔
88
89	self._bumps_result = result	1✔
90	self._status = self._bumps_result.status	1✔
91
92	def cleanup(self):	1✔
93	"""
94	Convert the result to a numpy array and populate the variables results
95	will be read from.
96	"""
97	if self._status == 0:	1✔
98	self.flag = 0	1✔
99	elif self._status == 2:	1✔
100	self.flag = 1	1✔
101	else:
102	self.flag = 2	1✔
103
104	self.final_params = self._bumps_result.x	1✔

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