[ff7119b] | 1 | """ |
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[aa4946b] | 2 | Wrap sasmodels for direct use by bumps. |
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[346bc88] | 3 | |
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| 4 | :class:`Model` is a wrapper for the sasmodels kernel which defines a |
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| 5 | bumps *Parameter* box for each kernel parameter. *Model* accepts keyword |
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| 6 | arguments to set the initial value for each parameter. |
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| 7 | |
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| 8 | :class:`Experiment` combines the *Model* function with a data file loaded by the |
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| 9 | sasview data loader. *Experiment* takes a *cutoff* parameter controlling |
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| 10 | how far the polydispersity integral extends. |
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| 11 | |
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[ff7119b] | 12 | """ |
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[aa4946b] | 13 | |
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[346bc88] | 14 | import warnings |
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[14de349] | 15 | |
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[aa4946b] | 16 | import numpy as np |
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| 17 | |
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[7cf2cfd] | 18 | from .data import plot_theory |
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| 19 | from .direct_model import DataMixin |
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[14de349] | 20 | |
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[346bc88] | 21 | # CRUFT: old style bumps wrapper which doesn't separate data and model |
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| 22 | def BumpsModel(data, model, cutoff=1e-5, **kw): |
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| 23 | warnings.warn("Use of BumpsModel is deprecated. Use bumps_model.Experiment instead.") |
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| 24 | model = Model(model, **kw) |
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| 25 | experiment = Experiment(data=data, model=model, cutoff=cutoff) |
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| 26 | for k in model._parameter_names: |
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| 27 | setattr(experiment, k, getattr(model, k)) |
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| 28 | return experiment |
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| 29 | |
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[ec7e360] | 30 | def create_parameters(model_info, **kwargs): |
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| 31 | # lazy import; this allows the doc builder and nosetests to run even |
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| 32 | # when bumps is not on the path. |
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| 33 | from bumps.names import Parameter |
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| 34 | |
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| 35 | partype = model_info['partype'] |
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| 36 | |
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| 37 | pars = {} |
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| 38 | for p in model_info['parameters']: |
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| 39 | name, default, limits = p[0], p[2], p[3] |
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| 40 | value = kwargs.pop(name, default) |
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| 41 | pars[name] = Parameter.default(value, name=name, limits=limits) |
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| 42 | for name in partype['pd-2d']: |
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| 43 | for xpart, xdefault, xlimits in [ |
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| 44 | ('_pd', 0., limits), |
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| 45 | ('_pd_n', 35., (0, 1000)), |
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| 46 | ('_pd_nsigma', 3., (0, 10)), |
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| 47 | ]: |
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| 48 | xname = name + xpart |
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| 49 | xvalue = kwargs.pop(xname, xdefault) |
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| 50 | pars[xname] = Parameter.default(xvalue, name=xname, limits=xlimits) |
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| 51 | |
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| 52 | pd_types = {} |
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| 53 | for name in partype['pd-2d']: |
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| 54 | xname = name + '_pd_type' |
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| 55 | xvalue = kwargs.pop(xname, 'gaussian') |
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| 56 | pd_types[xname] = xvalue |
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| 57 | |
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| 58 | if kwargs: # args not corresponding to parameters |
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| 59 | raise TypeError("unexpected parameters: %s" |
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| 60 | % (", ".join(sorted(kwargs.keys())))) |
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| 61 | |
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| 62 | return pars, pd_types |
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[346bc88] | 63 | |
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| 64 | class Model(object): |
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[ec7e360] | 65 | def __init__(self, model, **kwargs): |
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[7cf2cfd] | 66 | self._sasmodel = model |
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[ec7e360] | 67 | pars, pd_types = create_parameters(model.info, **kwargs) |
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| 68 | for k,v in pars.items(): |
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| 69 | setattr(self, k, v) |
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| 70 | for k,v in pd_types.items(): |
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| 71 | setattr(self, k, v) |
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| 72 | self._parameter_names = list(pars.keys()) |
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| 73 | self._pd_type_names = list(pd_types.keys()) |
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[346bc88] | 74 | |
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| 75 | def parameters(self): |
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| 76 | """ |
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| 77 | Return a dictionary of parameters |
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| 78 | """ |
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| 79 | return dict((k, getattr(self, k)) for k in self._parameter_names) |
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| 80 | |
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[ec7e360] | 81 | def state(self): |
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| 82 | pars = dict((k, getattr(self, k).value) for k in self._parameter_names) |
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| 83 | pars.update((k, getattr(self, k)) for k in self._pd_type_names) |
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| 84 | return pars |
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[7cf2cfd] | 85 | |
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| 86 | class Experiment(DataMixin): |
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[ff7119b] | 87 | """ |
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| 88 | Return a bumps wrapper for a SAS model. |
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| 89 | |
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| 90 | *data* is the data to be fitted. |
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| 91 | |
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[aa4946b] | 92 | *model* is the SAS model from :func:`core.load_model`. |
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[ff7119b] | 93 | |
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| 94 | *cutoff* is the integration cutoff, which avoids computing the |
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| 95 | the SAS model where the polydispersity weight is low. |
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| 96 | |
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| 97 | Model parameters can be initialized with additional keyword |
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| 98 | arguments, or by assigning to model.parameter_name.value. |
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| 99 | |
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| 100 | The resulting bumps model can be used directly in a FitProblem call. |
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| 101 | """ |
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[346bc88] | 102 | def __init__(self, data, model, cutoff=1e-5): |
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[14de349] | 103 | |
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[87985ca] | 104 | # remember inputs so we can inspect from outside |
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| 105 | self.model = model |
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[abb22f4] | 106 | self.cutoff = cutoff |
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[7cf2cfd] | 107 | self._interpret_data(data, model._sasmodel) |
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[14de349] | 108 | self.update() |
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| 109 | |
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| 110 | def update(self): |
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| 111 | self._cache = {} |
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| 112 | |
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| 113 | def numpoints(self): |
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[7e224c2] | 114 | """ |
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| 115 | Return the number of points |
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| 116 | """ |
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[3c56da87] | 117 | return len(self.Iq) |
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[14de349] | 118 | |
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| 119 | def parameters(self): |
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[7e224c2] | 120 | """ |
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[346bc88] | 121 | Return a dictionary of parameters |
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[7e224c2] | 122 | """ |
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[346bc88] | 123 | return self.model.parameters() |
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[14de349] | 124 | |
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| 125 | def theory(self): |
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| 126 | if 'theory' not in self._cache: |
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[ec7e360] | 127 | pars = self.model.state() |
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[7cf2cfd] | 128 | self._cache['theory'] = self._calc_theory(pars, cutoff=self.cutoff) |
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[14de349] | 129 | return self._cache['theory'] |
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| 130 | |
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| 131 | def residuals(self): |
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[9404dd3] | 132 | #if np.any(self.err ==0): print("zeros in err") |
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[346bc88] | 133 | return (self.theory() - self.Iq) / self.dIq |
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[14de349] | 134 | |
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| 135 | def nllf(self): |
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[3c56da87] | 136 | delta = self.residuals() |
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[9404dd3] | 137 | #if np.any(np.isnan(R)): print("NaN in residuals") |
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[3c56da87] | 138 | return 0.5 * np.sum(delta ** 2) |
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[14de349] | 139 | |
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[3c56da87] | 140 | #def __call__(self): |
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| 141 | # return 2 * self.nllf() / self.dof |
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[14de349] | 142 | |
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| 143 | def plot(self, view='log'): |
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[c97724e] | 144 | """ |
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| 145 | Plot the data and residuals. |
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| 146 | """ |
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[7cf2cfd] | 147 | data, theory, resid = self._data, self.theory(), self.residuals() |
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| 148 | plot_theory(data, theory, resid, view) |
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[c97724e] | 149 | |
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| 150 | def simulate_data(self, noise=None): |
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[7cf2cfd] | 151 | Iq = self.theory() |
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| 152 | self._set_data(Iq, noise) |
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[14de349] | 153 | |
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| 154 | def save(self, basename): |
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| 155 | pass |
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| 156 | |
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[abb22f4] | 157 | def __getstate__(self): |
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| 158 | # Can't pickle gpu functions, so instead make them lazy |
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| 159 | state = self.__dict__.copy() |
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[7cf2cfd] | 160 | state['_kernel'] = None |
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[abb22f4] | 161 | return state |
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| 162 | |
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| 163 | def __setstate__(self, state): |
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[3c56da87] | 164 | # pylint: disable=attribute-defined-outside-init |
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[abb22f4] | 165 | self.__dict__ = state |
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