1 | from bumps.names import * |
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2 | from sasmodels import core, bumps_model, sesans |
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3 | from sas.sascalc.dataloader.loader import Loader |
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4 | |
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5 | def get_bumps_model(model_name): |
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6 | kernel = core.load_model(model_name) |
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7 | model = bumps_model.Model(kernel) |
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8 | return model |
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9 | |
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10 | def sesans_fit(file, model, initial_vals={}, custom_params={}, param_range=[], acceptance_angle=None): |
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11 | """ |
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12 | |
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13 | @param file: SESANS file location |
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14 | @param model: Bumps model object or model name - can be model, model_1 * model_2, and/or model_1 + model_2 |
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15 | @param initial_vals: dictionary of {param_name : initial_value} |
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16 | @param custom_params: dictionary of {custom_parameter_name : Parameter() object} |
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17 | @param param_range: dictionary of {parameter_name : [minimum, maximum]} |
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18 | @param constraints: dictionary of {parameter_name : constraint} |
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19 | @return: FitProblem for Bumps usage |
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20 | """ |
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21 | initial_vals['background'] = 0.0 |
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22 | try: |
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23 | loader = Loader() |
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24 | data = loader.load(file) |
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25 | if data is None: raise IOError("Could not load file %r"%(file)) |
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26 | |
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27 | except: |
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28 | # If no loadable data file, generate random data |
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29 | SElength = np.linspace(0, 2400, 61) # [A] |
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30 | data = np.ones_like(SElength) |
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31 | err_data = np.ones_like(SElength)*0.03 |
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32 | |
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33 | class Sample: |
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34 | zacceptance = 0.1 # [A^-1] |
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35 | thickness = 0.2 # [cm] |
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36 | |
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37 | class SESANSData1D: |
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38 | #q_zmax = 0.23 # [A^-1] |
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39 | lam = 0.2 # [nm] |
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40 | x = SElength |
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41 | y = data |
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42 | dy = err_data |
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43 | sample = Sample() |
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44 | has_no_finite_acceptance = acceptance_angle is not None |
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45 | data = SESANSData1D() |
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46 | data.acceptance_angle = acceptance_angle |
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47 | |
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48 | data.has_no_finite_acceptance = acceptance_angle is not None |
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49 | radius = initial_vals.get("radius", 1000) |
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50 | data.Rmax = 30*radius # [A] |
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51 | |
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52 | if isinstance(model, basestring): |
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53 | model = get_bumps_model(model) |
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54 | |
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55 | # Load custom parameters, initial values and parameter ranges |
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56 | pars = model.parameters().copy() |
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57 | pars.update(custom_params) |
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58 | for k, v in custom_params.items(): |
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59 | if k not in pars: |
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60 | par_error("Can't set parameter %r in model"%k, pars) |
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61 | setattr(model, k, v) |
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62 | model._parameter_names.append(k) |
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63 | for k, v in initial_vals.items(): |
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64 | if k not in pars: |
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65 | par_error("Can't get parameter %r from model"%k, pars) |
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66 | param = pars[k] |
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67 | param.value = v |
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68 | for k, v in param_range.items(): |
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69 | if k not in pars: |
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70 | par_error("Can't set range on parameter %r in model"%k, pars) |
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71 | param = pars[k] |
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72 | param.range(*v) |
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73 | |
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74 | if False: # for future implementation |
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75 | M_sesans = bumps_model.Experiment(data=data, model=model) |
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76 | M_sans = bumps_model.Experiment(data=sans_data, model=model) |
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77 | problem = FitProblem([M_sesans, M_sans]) |
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78 | else: |
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79 | M_sesans = bumps_model.Experiment(data=data, model=model) |
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80 | problem = FitProblem(M_sesans) |
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81 | return problem |
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82 | |
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83 | |
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84 | def par_error(msg, pars): |
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85 | raise ValueError(msg+"\nAvailable parameters: %s"%", ".join(sorted(pars.keys()))) |
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