1 | from sans.fit.AbstractFitEngine import Model |
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2 | |
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3 | class FitProblem: |
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4 | """ |
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5 | FitProblem class allows to link a model with the new name created in _on_model, |
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6 | a name theory created with that model and the data fitted with the model. |
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7 | FitProblem is mostly used as value of the dictionary by fitting module. |
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8 | """ |
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9 | |
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10 | def __init__(self): |
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11 | |
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12 | """ |
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13 | @ self.data :is the data selected to perform the fit |
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14 | @ self.theory_name: the name of the theory created with self.model |
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15 | @ self.model_list: is a list containing a model as first element |
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16 | and its name assign example [lineModel, M0] |
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17 | """ |
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18 | self.fit_data=None |
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19 | self.theory_name=None |
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20 | self.model_list=[] |
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21 | self.schedule=0 |
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22 | self.list_param=[] |
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23 | self.name_per_page=None |
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24 | self.smearer= None |
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25 | self.plotted_data=None |
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26 | |
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27 | def set_smearer(self, smearer): |
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28 | self.smearer= smearer |
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29 | #print "smeaerer in fitproblem",self.smearer |
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30 | def get_smearer(self): |
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31 | return self.smearer |
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32 | |
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33 | def save_model_name(self, name): |
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34 | self.name_per_page= name |
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35 | |
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36 | |
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37 | def get_name(self): |
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38 | return self.name_per_page |
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39 | |
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40 | def set_model(self,model,name): |
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41 | """ |
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42 | associates each model with its new created name |
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43 | @param model: model selected |
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44 | @param name: name created for model |
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45 | """ |
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46 | self.model_list=[model,name] |
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47 | |
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48 | |
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49 | def add_plotted_data(self,data): |
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50 | """ |
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51 | save a copy of the data select to fit |
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52 | @param data: data selected |
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53 | """ |
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54 | self.plotted_data = data |
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55 | def add_fit_data(self,data): |
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56 | """ |
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57 | save a copy of the data select to fit |
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58 | @param data: data selected |
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59 | """ |
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60 | self.fit_data = data |
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61 | |
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62 | def get_model(self): |
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63 | """ @return: saved model """ |
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64 | #print "fitproblem",self.model_list |
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65 | return self.model_list |
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66 | |
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67 | def get_plotted_data(self): |
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68 | """ @return: list of data dList""" |
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69 | return self.plotted_data |
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70 | |
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71 | |
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72 | def get_fit_data(self): |
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73 | return self.fit_data |
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74 | |
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75 | |
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76 | def get_theory(self): |
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77 | """ @return the name of theory for plotting purpose""" |
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78 | return self.theory_name |
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79 | |
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80 | |
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81 | def set_theory(self,name): |
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82 | """ |
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83 | Set theory name |
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84 | @param name: name of the theory |
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85 | """ |
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86 | self.theory_name = name |
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87 | |
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88 | |
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89 | def set_model_param(self,name,value): |
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90 | """ |
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91 | set the value of a given parameter of this model |
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92 | @param name: name of the given parameter |
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93 | @param value: value of that parameter |
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94 | """ |
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95 | #print "fitproblem",name,value |
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96 | #self.model_list[0].setParam(name,value) |
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97 | self.list_param.append([name,value]) |
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98 | def get_model_param(self): |
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99 | """ |
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100 | set the value of a given parameter of this model |
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101 | @param name: name of the given parameter |
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102 | @param value: value of that parameter |
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103 | """ |
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104 | #print self.param_name, self.param_value |
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105 | #self.model_list[0].setParam(name,value) |
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106 | return self.list_param |
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107 | |
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108 | def reset_model(self,model): |
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109 | """ |
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110 | reset a model when parameter has changed |
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111 | @param value: new model |
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112 | """ |
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113 | #print "fitproblem : reset model" |
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114 | self.model_list[0]=model |
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115 | |
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116 | def schedule_tofit(self, schedule=0): |
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117 | """ |
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118 | set schedule to true to decide if this fit must be performed |
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119 | """ |
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120 | self.schedule=schedule |
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121 | |
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122 | def get_scheduled(self): |
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123 | """ return true or false if a problem as being schedule for fitting""" |
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124 | return self.schedule |
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125 | def clear_model_param(self): |
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126 | """ |
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127 | clear constraint info |
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128 | """ |
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129 | self.list_param=[] |
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