Changeset 74b0495 in sasmodels


Ignore:
Timestamp:
Oct 10, 2017 1:39:39 PM (2 years ago)
Author:
Paul Kienzle <pkienzle@…>
Branches:
master, core_shell_microgels, costrafo411, magnetic_model, ticket-1257-vesicle-product, ticket_1156, ticket_1265_superball, ticket_822_more_unit_tests
Children:
09141ff
Parents:
b76191e
Message:

update oriented sesans and simultaneous fit examples

Files:
2 deleted
4 edited

Legend:

Unmodified
Added
Removed
  • example/oriented_usans.py

    r1cd24b4 r74b0495  
    66 
    77# Spherical particle data, not ellipsoids 
    8 sans, usans = load_data('../../sasview/sasview/test/1d_data/latex_smeared.xml') 
     8sans, usans = load_data('latex_smeared.xml', index='all') 
    99usans.qmin, usans.qmax = np.min(usans.x), np.max(usans.x) 
    1010usans.mask = (usans.x < 0.0) 
  • example/simul_fit.py

    r1a4d4c0 r74b0495  
    1 #!/usr/bin/env python 
    2 # -*- coding: utf-8 -*- 
    3  
    4 # To Sasview/documents/scripts 
    5  
    61from bumps.names import * 
    72from sasmodels.core import load_model 
     
    94from sasmodels.data import load_data, plot_data 
    105 
     6# latex data, same sample usans and sans 
     7# particles radius ~2300, uniform dispersity 
     8datasets = load_data('latex_smeared.xml', index='all') 
     9#[print(data) for data in datasets] 
    1110 
    12 """ IMPORT THE DATA USED """ 
    13 datafiles = ['latex_smeared_out_0.txt', 'latex_smeared_out_1.txt'] 
    14 datasets = [load_data(el) for el in datafiles] 
     11# A single sphere model to share between the datasets.  We will use 
     12# FreeVariables below to set the parameters that are independent between 
     13# the datasets. 
     14kernel = load_model('sphere') 
     15pars = dict(scale=0.01, background=0.0, sld=5.0, sld_solvent=0.0, radius=1500., 
     16            #radius_pd=0.1, radius_pd_n=35, 
     17            ) 
     18model = Model(kernel, **pars) 
    1519 
    16 for data in datasets: 
    17     data.qmin = 0.0 
    18     data.qmax = 10.0 
     20# radius and polydispersity (if any) are shared 
     21model.radius.range(0, inf) 
     22#model.radius_pd.range(0, 1) 
    1923 
    20 #sphere model 
    21 kernel = load_model('sphere', dtype="single") 
    22 pars = dict(scale=0.01, background=0.0, sld=1.0, sld_solvent=6.0, radius=1500.) 
    23 model = Model(kernel, **pars) 
    24 model.radius.range(0, inf) 
    25 #model.background.range(-inf, inf) 
    26 #model.scale.range(0, inf) 
    27 model.sld.range(-inf, inf) 
    28 model.sld_solvent.range(-inf, inf) 
     24# Contrast and dilution are the same for both measurements, but are not 
     25# separable with a single measurement (i.e., I(q) ~ F(q) contrast^2 Vf), 
     26# so fit one of scale, sld or solvent sld.  With absolute scaling from 
     27# data reduction, can use the same parameter for both datasets. 
     28model.scale.range(0, inf) 
     29#model.sld.range(-inf, inf) 
     30#model.sld_solvent.range(-inf, inf) 
    2931 
     32# Background is different for sans and usans so set it as a free variable 
     33# in the model. 
    3034free = FreeVariables( 
    31     names=[data.filename for data in datasets], 
     35    names=[data.run[0] for data in datasets], 
    3236    background=model.background, 
    33     scale=model.scale, 
    3437    ) 
    3538free.background.range(-inf, inf) 
    36 free.scale.range(0, inf) 
    3739 
    38 M = [Experiment(data=data, model=model) for data in datasets] 
     40# Note: can access the parameters for the individual models using 
     41# free.background[0] and free.background[1], setting constraints or 
     42# ranges as appropriate. 
     43 
     44# For more complex systems where different datasets require independent models, 
     45# separate models can be defined, with parameters tied together using 
     46# constraint expressions.  For example, the following could be used to fit 
     47# data set 1 to spheres and data set 2 to cylinders of the same volume: 
     48#    model1 = Model(load_model('sphere')) 
     49#    model2 = Model(load_model('cylinder')) 
     50#    model1.sld = model2.sld 
     51#    model1.sld_solvent = model2.sld_solvent 
     52#    model1.scale = model2.scale 
     53#    # set cylinders and spheres to the same volume 
     54#    model1.radius = (3/4*model2.radius**2*model2.length)**(1/3) 
     55#    model1.background.range(0, 2) 
     56#    model2.background.range(0, 2) 
     57 
     58# Setup the experiments, sharing the same model across all datasets. 
     59M = [Experiment(data=data, model=model, name=data.run[0]) for data in datasets] 
    3960 
    4061problem = FitProblem(M, freevars=free) 
    41  
    42 print(problem._parameters) 
  • sasmodels/bumps_model.py

    r3330bb4 r74b0495  
    133133    """ 
    134134    _cache = None # type: Dict[str, np.ndarray] 
    135     def __init__(self, data, model, cutoff=1e-5): 
     135    def __init__(self, data, model, cutoff=1e-5, name=None): 
    136136        # type: (Data, Model, float) -> None 
    137137        # remember inputs so we can inspect from outside 
     138        self.name = data.filename if name is None else name 
    138139        self.model = model 
    139140        self.cutoff = cutoff 
     
    204205        """ 
    205206        data, theory, resid = self._data, self.theory(), self.residuals() 
    206         plot_theory(data, theory, resid, view, Iq_calc=self.Iq_calc) 
     207        # TODO: hack to display oriented usans 2-D pattern 
     208        Iq_calc = self.Iq_calc if isinstance(self.Iq_calc, tuple) else None 
     209        plot_theory(data, theory, resid, view, Iq_calc=Iq_calc) 
    207210 
    208211    def simulate_data(self, noise=None): 
  • sasmodels/data.py

    r630156b r74b0495  
    4444    Data = Union["Data1D", "Data2D", "SesansData"] 
    4545 
    46 def load_data(filename): 
     46def load_data(filename, index=0): 
    4747    # type: (str) -> Data 
    4848    """ 
     
    5555        filename, indexstr = filename[:-1].split('[') 
    5656        index = int(indexstr) 
    57     else: 
    58         index = None 
    5957    datasets = loader.load(filename) 
    6058    if datasets is None: 
     
    6260    if not isinstance(datasets, list): 
    6361        datasets = [datasets] 
    64     if index is None and len(datasets) > 1: 
    65         raise ValueError("Need to specify filename[index] for multipart data") 
    66     data = datasets[index if index is not None else 0] 
    67     if hasattr(data, 'x'): 
    68         data.qmin, data.qmax = data.x.min(), data.x.max() 
    69         data.mask = (np.isnan(data.y) if data.y is not None 
    70                      else np.zeros_like(data.x, dtype='bool')) 
    71     elif hasattr(data, 'qx_data'): 
    72         data.mask = ~data.mask 
    73     return data 
     62    for data in datasets: 
     63        if hasattr(data, 'x'): 
     64            data.qmin, data.qmax = data.x.min(), data.x.max() 
     65            data.mask = (np.isnan(data.y) if data.y is not None 
     66                        else np.zeros_like(data.x, dtype='bool')) 
     67        elif hasattr(data, 'qx_data'): 
     68            data.mask = ~data.mask 
     69    return datasets[index] if index != 'all' else datasets 
    7470 
    7571 
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