| 1 | # A sample of an experimental model function for Sum(Pmodel1,Pmodel2) |
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| 2 | import copy |
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| 3 | from sans.models.pluginmodel import Model1DPlugin |
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| 4 | |
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| 5 | """ |
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| 6 | ## ***************************************************************************** |
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| 7 | Please select the 'Compile' from the menubar after the modification and saving. |
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| 8 | Note that we recommend to save the file as a different file name. |
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| 9 | Otherwise, it could be removed in the future on re-installation of the SansView. |
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| 10 | ## ***************************************************************************** |
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| 11 | """ |
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| 12 | |
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| 13 | # Available model names for this sum model |
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| 14 | """ |
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| 15 | BCCrystalModel, BEPolyelectrolyte, BarBellModel, BinaryHSModel, BroadPeakModel, |
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| 16 | CSParallelepipedModel, CappedCylinderModel, CoreShellCylinderModel, |
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| 17 | CoreShellEllipsoidModel, CoreShellModel, CorrLengthModel, CylinderModel, |
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| 18 | DABModel, DebyeModel, EllipsoidModel, EllipticalCylinderModel, FCCrystalModel, |
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| 19 | FlexCylEllipXModel, FlexibleCylinderModel, FractalCoreShellModel, FractalModel, |
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| 20 | FuzzySphereModel, GaussLorentzGelModel, GuinierModel, GuinierPorodModel, |
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| 21 | HardsphereStructure, HayterMSAStructure, HollowCylinderModel, LamellarFFHGModel, |
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| 22 | LamellarModel, LamellarPCrystalModel, LamellarPSHGModel, LamellarPSModel, |
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| 23 | LineModel, LorentzModel, MultiShellModel, ParallelepipedModel, PeakGaussModel, |
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| 24 | PeakLorentzModel, PearlNecklaceModel, Poly_GaussCoil, PolymerExclVolume, |
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| 25 | PorodModel, PowerLawAbsModel, SCCrystalModel, SphereModel, SquareWellStructure, |
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| 26 | StackedDisksModel, StickyHSStructure, TeubnerStreyModel, TriaxialEllipsoidModel, |
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| 27 | TwoLorentzianModel, TwoPowerLawModel, VesicleModel |
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| 28 | """ |
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| 29 | ## This is same as the Easy Custom Sum(p1 + p2) |
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| 30 | # |
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| 31 | # Custom model = scale_factor * (P1 + P2) |
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| 32 | # |
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| 33 | ## User can REPLACE model names below two arrowed lines (two names per line) |
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| 34 | from sans.models.CylinderModel import CylinderModel as P1 #<======== |
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| 35 | from sans.models.PolymerExclVolume import PolymerExclVolume as P2 #<======== |
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| 36 | |
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| 37 | # If you want to add your custom model, change the filename to your custom model |
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| 38 | # FILE NAME without the extension(.py). And un-comment the line(ie., remove '#') |
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| 39 | |
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| 40 | # from filename import Model as P2 #<======== |
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| 41 | |
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| 42 | |
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| 43 | #####DO NOT CHANGE ANYTHING BELOW THIS LINE |
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| 44 | #####--------------------------------------------------------------------------- |
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| 45 | class Model(Model1DPlugin): |
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| 46 | """ |
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| 47 | Use for p1(Q)+p2(Q); |
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| 48 | Note: P(Q) refers to 'form factor' model. |
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| 49 | """ |
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| 50 | name = "sum_p1_p2" ## <----- FILE NAME (NAME OF THE MODEL) |
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| 51 | def __init__(self): |
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| 52 | Model1DPlugin.__init__(self, name=self.name) |
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| 53 | """ |
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| 54 | :param p_model1: a form factor, P(Q) |
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| 55 | :param p_model2: another form factor, P(Q) |
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| 56 | """ |
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| 57 | p_model1 = P1() |
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| 58 | p_model2 = P2() |
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| 59 | ## Setting model name model description |
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| 60 | self.description="" |
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| 61 | |
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| 62 | self.description = p_model1.name+"\n" |
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| 63 | self.description += p_model2.name+"\n" |
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| 64 | self.fill_description(p_model1, p_model2) |
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| 65 | |
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| 66 | ## Define parameters |
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| 67 | self.params = {} |
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| 68 | |
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| 69 | ## Parameter details [units, min, max] |
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| 70 | self.details = {} |
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| 71 | |
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| 72 | # non-fittable parameters |
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| 73 | self.non_fittable = p_model1.non_fittable |
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| 74 | self.non_fittable += p_model2.non_fittable |
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| 75 | |
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| 76 | ##models |
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| 77 | self.p_model1= p_model1 |
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| 78 | self.p_model2= p_model2 |
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| 79 | |
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| 80 | |
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| 81 | ## dispersion |
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| 82 | self._set_dispersion() |
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| 83 | ## Define parameters |
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| 84 | self._set_params() |
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| 85 | ## New parameter:Scaling factor |
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| 86 | self.params['scale_factor'] = 1 |
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| 87 | |
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| 88 | ## Parameter details [units, min, max] |
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| 89 | self._set_details() |
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| 90 | self.details['scale_factor'] = ['', None, None] |
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| 91 | |
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| 92 | |
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| 93 | #list of parameter that can be fitted |
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| 94 | self._set_fixed_params() |
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| 95 | ## parameters with orientation |
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| 96 | for item in self.p_model1.orientation_params: |
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| 97 | new_item = "p1_" + item |
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| 98 | if not new_item in self.orientation_params: |
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| 99 | self.orientation_params.append(new_item) |
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| 100 | |
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| 101 | for item in self.p_model2.orientation_params: |
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| 102 | new_item = "p2_" + item |
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| 103 | if not new_item in self.orientation_params: |
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| 104 | self.orientation_params.append(new_item) |
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| 105 | # get multiplicity if model provide it, else 1. |
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| 106 | try: |
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| 107 | multiplicity1 = p_model1.multiplicity |
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| 108 | try: |
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| 109 | multiplicity2 = p_model2.multiplicity |
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| 110 | except: |
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| 111 | multiplicity2 = 1 |
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| 112 | except: |
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| 113 | multiplicity1 = 1 |
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| 114 | multiplicity2 = 1 |
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| 115 | ## functional multiplicity of the model |
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| 116 | self.multiplicity1 = multiplicity1 |
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| 117 | self.multiplicity2 = multiplicity2 |
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| 118 | self.multiplicity_info = [] |
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| 119 | |
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| 120 | def _clone(self, obj): |
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| 121 | """ |
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| 122 | Internal utility function to copy the internal |
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| 123 | data members to a fresh copy. |
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| 124 | """ |
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| 125 | obj.params = copy.deepcopy(self.params) |
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| 126 | obj.description = copy.deepcopy(self.description) |
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| 127 | obj.details = copy.deepcopy(self.details) |
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| 128 | obj.dispersion = copy.deepcopy(self.dispersion) |
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| 129 | obj.p_model1 = self.p_model1.clone() |
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| 130 | obj.p_model2 = self.p_model2.clone() |
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| 131 | #obj = copy.deepcopy(self) |
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| 132 | return obj |
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| 133 | |
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| 134 | def _get_name(self, name1, name2): |
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| 135 | """ |
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| 136 | Get combined name from two model names |
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| 137 | """ |
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| 138 | p1_name = self._get_upper_name(name1) |
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| 139 | if not p1_name: |
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| 140 | p1_name = name1 |
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| 141 | name = p1_name |
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| 142 | name += "+" |
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| 143 | p2_name = self._get_upper_name(name2) |
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| 144 | if not p2_name: |
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| 145 | p2_name = name2 |
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| 146 | name += p2_name |
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| 147 | return name |
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| 148 | |
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| 149 | def _get_upper_name(self, name=None): |
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| 150 | """ |
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| 151 | Get uppercase string from model name |
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| 152 | """ |
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| 153 | if name == None: |
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| 154 | return "" |
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| 155 | upper_name = "" |
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| 156 | str_name = str(name) |
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| 157 | for index in range(len(str_name)): |
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| 158 | if str_name[index].isupper(): |
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| 159 | upper_name += str_name[index] |
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| 160 | return upper_name |
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| 161 | |
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| 162 | def _set_dispersion(self): |
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| 163 | """ |
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| 164 | combined the two models dispersions |
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| 165 | Polydispersion should not be applied to s_model |
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| 166 | """ |
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| 167 | ##set dispersion only from p_model |
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| 168 | for name , value in self.p_model1.dispersion.iteritems(): |
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| 169 | #if name.lower() not in self.p_model1.orientation_params: |
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| 170 | new_name = "p1_" + name |
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| 171 | self.dispersion[new_name]= value |
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| 172 | for name , value in self.p_model2.dispersion.iteritems(): |
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| 173 | #if name.lower() not in self.p_model2.orientation_params: |
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| 174 | new_name = "p2_" + name |
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| 175 | self.dispersion[new_name]= value |
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| 176 | |
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| 177 | def function(self, x=0.0): |
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| 178 | """ |
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| 179 | """ |
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| 180 | return 0 |
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| 181 | |
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| 182 | def getProfile(self): |
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| 183 | """ |
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| 184 | Get SLD profile of p_model if exists |
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| 185 | |
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| 186 | : return: (r, beta) where r is a list of radius of the transition points |
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| 187 | beta is a list of the corresponding SLD values |
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| 188 | : Note: This works only for func_shell# = 2 (exp function) |
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| 189 | and is not supporting for p2 |
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| 190 | """ |
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| 191 | try: |
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| 192 | x,y = self.p_model1.getProfile() |
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| 193 | except: |
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| 194 | x = None |
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| 195 | y = None |
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| 196 | |
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| 197 | return x, y |
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| 198 | |
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| 199 | def _set_params(self): |
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| 200 | """ |
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| 201 | Concatenate the parameters of the two models to create |
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| 202 | this model parameters |
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| 203 | """ |
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| 204 | |
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| 205 | for name , value in self.p_model1.params.iteritems(): |
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| 206 | # No 2D-supported |
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| 207 | #if name not in self.p_model1.orientation_params: |
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| 208 | new_name = "p1_" + name |
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| 209 | self.params[new_name]= value |
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| 210 | |
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| 211 | for name , value in self.p_model2.params.iteritems(): |
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| 212 | # No 2D-supported |
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| 213 | #if name not in self.p_model2.orientation_params: |
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| 214 | new_name = "p2_" + name |
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| 215 | self.params[new_name]= value |
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| 216 | |
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| 217 | # Set "scale" as initializing |
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| 218 | self._set_scale_factor() |
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| 219 | |
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| 220 | |
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| 221 | def _set_details(self): |
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| 222 | """ |
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| 223 | Concatenate details of the two models to create |
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| 224 | this model details |
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| 225 | """ |
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| 226 | for name ,detail in self.p_model1.details.iteritems(): |
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| 227 | new_name = "p1_" + name |
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| 228 | #if new_name not in self.orientation_params: |
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| 229 | self.details[new_name]= detail |
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| 230 | |
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| 231 | for name ,detail in self.p_model2.details.iteritems(): |
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| 232 | new_name = "p2_" + name |
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| 233 | #if new_name not in self.orientation_params: |
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| 234 | self.details[new_name]= detail |
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| 235 | |
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| 236 | def _set_scale_factor(self): |
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| 237 | """ |
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| 238 | Not implemented |
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| 239 | """ |
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| 240 | pass |
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| 241 | |
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| 242 | |
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| 243 | def setParam(self, name, value): |
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| 244 | """ |
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| 245 | Set the value of a model parameter |
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| 246 | |
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| 247 | :param name: name of the parameter |
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| 248 | :param value: value of the parameter |
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| 249 | """ |
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| 250 | # set param to p1+p2 model |
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| 251 | self._setParamHelper(name, value) |
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| 252 | |
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| 253 | ## setParam to p model |
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| 254 | model_pre = name.split('_', 1)[0] |
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| 255 | new_name = name.split('_', 1)[1] |
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| 256 | if model_pre == "p1": |
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| 257 | if new_name in self.p_model1.getParamList(): |
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| 258 | self.p_model1.setParam(new_name, value) |
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| 259 | elif model_pre == "p2": |
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| 260 | if new_name in self.p_model2.getParamList(): |
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| 261 | self.p_model2.setParam(new_name, value) |
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| 262 | elif name.lower() == 'scale_factor': |
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| 263 | self.params['scale_factor'] = value |
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| 264 | else: |
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| 265 | raise ValueError, "Model does not contain parameter %s" % name |
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| 266 | |
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| 267 | def getParam(self, name): |
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| 268 | """ |
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| 269 | Set the value of a model parameter |
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| 270 | |
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| 271 | :param name: name of the parameter |
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| 272 | |
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| 273 | """ |
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| 274 | # Look for dispersion parameters |
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| 275 | toks = name.split('.') |
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| 276 | if len(toks)==2: |
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| 277 | for item in self.dispersion.keys(): |
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| 278 | # 2D not supported |
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| 279 | if item.lower()==toks[0].lower():# and \ |
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| 280 | #item.lower() not in self.orientation_params \ |
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| 281 | #and toks[0].lower() not in self.orientation_params: |
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| 282 | for par in self.dispersion[item]: |
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| 283 | if par.lower() == toks[1].lower(): |
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| 284 | return self.dispersion[item][par] |
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| 285 | else: |
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| 286 | # Look for standard parameter |
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| 287 | for item in self.params.keys(): |
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| 288 | if item.lower()==name.lower():#and \ |
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| 289 | #item.lower() not in self.orientation_params \ |
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| 290 | #and toks[0].lower() not in self.orientation_params: |
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| 291 | return self.params[item] |
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| 292 | return |
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| 293 | #raise ValueError, "Model does not contain parameter %s" % name |
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| 294 | |
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| 295 | def _setParamHelper(self, name, value): |
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| 296 | """ |
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| 297 | Helper function to setparam |
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| 298 | """ |
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| 299 | # Look for dispersion parameters |
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| 300 | toks = name.split('.') |
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| 301 | if len(toks)== 2: |
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| 302 | for item in self.dispersion.keys(): |
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| 303 | if item.lower()== toks[0].lower():# and \ |
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| 304 | #item.lower() not in self.orientation_params: |
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| 305 | for par in self.dispersion[item]: |
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| 306 | if par.lower() == toks[1].lower():#and \ |
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| 307 | #item.lower() not in self.orientation_params: |
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| 308 | self.dispersion[item][par] = value |
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| 309 | return |
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| 310 | else: |
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| 311 | # Look for standard parameter |
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| 312 | for item in self.params.keys(): |
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| 313 | if item.lower()== name.lower():#and \ |
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| 314 | #item.lower() not in self.orientation_params: |
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| 315 | self.params[item] = value |
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| 316 | return |
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| 317 | |
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| 318 | raise ValueError, "Model does not contain parameter %s" % name |
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| 319 | |
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| 320 | |
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| 321 | def _set_fixed_params(self): |
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| 322 | """ |
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| 323 | fill the self.fixed list with the p_model fixed list |
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| 324 | """ |
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| 325 | for item in self.p_model1.fixed: |
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| 326 | new_item = "p1" + item |
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| 327 | self.fixed.append(new_item) |
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| 328 | for item in self.p_model2.fixed: |
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| 329 | new_item = "p2" + item |
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| 330 | self.fixed.append(new_item) |
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| 331 | |
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| 332 | self.fixed.sort() |
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| 333 | |
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| 334 | |
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| 335 | def run(self, x = 0.0): |
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| 336 | """ |
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| 337 | Evaluate the model |
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| 338 | |
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| 339 | :param x: input q-value (float or [float, float] as [r, theta]) |
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| 340 | :return: (scattering function value) |
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| 341 | """ |
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| 342 | self._set_scale_factor() |
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| 343 | return self.params['scale_factor'] * \ |
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| 344 | (self.p_model1.run(x) + self.p_model2.run(x)) |
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| 345 | |
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| 346 | def runXY(self, x = 0.0): |
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| 347 | """ |
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| 348 | Evaluate the model |
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| 349 | |
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| 350 | :param x: input q-value (float or [float, float] as [qx, qy]) |
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| 351 | :return: scattering function value |
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| 352 | """ |
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| 353 | self._set_scale_factor() |
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| 354 | return self.params['scale_factor'] * \ |
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| 355 | (self.p_model1.runXY(x) + self.p_model2.runXY(x)) |
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| 356 | |
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| 357 | ## Now (May27,10) directly uses the model eval function |
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| 358 | ## instead of the for-loop in Base Component. |
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| 359 | def evalDistribution(self, x = []): |
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| 360 | """ |
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| 361 | Evaluate the model in cartesian coordinates |
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| 362 | |
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| 363 | :param x: input q[], or [qx[], qy[]] |
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| 364 | :return: scattering function P(q[]) |
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| 365 | """ |
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| 366 | self._set_scale_factor() |
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| 367 | return self.params['scale_factor'] * \ |
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| 368 | (self.p_model1.evalDistribution(x) + \ |
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| 369 | self.p_model2.evalDistribution(x)) |
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| 370 | |
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| 371 | def set_dispersion(self, parameter, dispersion): |
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| 372 | """ |
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| 373 | Set the dispersion object for a model parameter |
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| 374 | |
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| 375 | :param parameter: name of the parameter [string] |
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| 376 | :dispersion: dispersion object of type DispersionModel |
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| 377 | """ |
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| 378 | value= None |
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| 379 | new_pre = parameter.split("_", 1)[0] |
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| 380 | new_parameter = parameter.split("_", 1)[1] |
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| 381 | try: |
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| 382 | if new_pre == 'p1' and \ |
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| 383 | new_parameter in self.p_model1.dispersion.keys(): |
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| 384 | value= self.p_model1.set_dispersion(new_parameter, dispersion) |
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| 385 | if new_pre == 'p2' and \ |
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| 386 | new_parameter in self.p_model2.dispersion.keys(): |
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| 387 | value= self.p_model2.set_dispersion(new_parameter, dispersion) |
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| 388 | self._set_dispersion() |
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| 389 | return value |
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| 390 | except: |
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| 391 | raise |
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| 392 | |
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| 393 | def fill_description(self, p_model1, p_model2): |
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| 394 | """ |
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| 395 | Fill the description for P(Q)+P(Q) |
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| 396 | """ |
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| 397 | description = "" |
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| 398 | description +="This model gives the summation of %s and %s.\n"% \ |
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| 399 | ( p_model1.name, p_model2.name ) |
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| 400 | self.description += description |
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| 401 | |
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| 402 | if __name__ == "__main__": |
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| 403 | m1= Model() |
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| 404 | #m1.setParam("p1_scale", 25) |
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| 405 | #m1.setParam("p1_length", 1000) |
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| 406 | #m1.setParam("p2_scale", 100) |
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| 407 | #m1.setParam("p2_rg", 100) |
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| 408 | out1 = m1.runXY(0.01) |
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| 409 | |
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| 410 | m2= Model() |
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| 411 | #m2.p_model1.setParam("scale", 25) |
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| 412 | #m2.p_model1.setParam("length", 1000) |
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| 413 | #m2.p_model2.setParam("scale", 100) |
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| 414 | #m2.p_model2.setParam("rg", 100) |
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| 415 | out2 = m2.p_model1.runXY(0.01) + m2.p_model2.runXY(0.01) |
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| 416 | print "Testing at Q = 0.01:" |
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| 417 | print out1, " = ", out2 |
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| 418 | if out1 == out2: |
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| 419 | print "===> Simple Test: Passed!" |
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| 420 | else: |
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| 421 | print "===> Simple Test: Failed!" |
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