1 | |
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2 | import numpy as np |
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3 | |
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4 | # TODO: turn ModelInfo into a proper class |
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5 | ModelInfo = dict |
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6 | |
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7 | MAX_PD = 4 |
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8 | |
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9 | COMMON_PARAMETERS = [ |
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10 | ["scale", "", 1, [0, np.inf], "", "Source intensity"], |
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11 | ["background", "1/cm", 1e-3, [0, np.inf], "", "Source background"], |
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12 | ] |
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13 | assert (len(COMMON_PARAMETERS) == 2 |
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14 | and COMMON_PARAMETERS[0][0]=="scale" |
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15 | and COMMON_PARAMETERS[1][0]=="background"), "don't change common parameters" |
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16 | # assumptions about common parameters exist throughout the code, such as: |
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17 | # (1) kernel functions Iq, Iqxy, form_volume, ... don't see them |
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18 | # (2) kernel drivers assume scale is par[0] and background is par[1] |
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19 | # (3) mixture models drop the background on components and replace the scale |
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20 | # with a scale that varies from [-inf, inf] |
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21 | # (4) product models drop the background and reassign scale |
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22 | # and maybe other places. |
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23 | # Note that scale and background cannot be coordinated parameters whose value |
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24 | # depends on the some polydisperse parameter with the current implementation |
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25 | |
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26 | def make_parameter_table(pars): |
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27 | processed = [] |
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28 | for p in pars: |
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29 | if not isinstance(p, list) or len(p) != 6: |
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30 | raise ValueError("Parameter should be [name, units, default, limits, type, desc], but got %r" |
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31 | %str(p)) |
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32 | processed.append(parse_parameter(*p)) |
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33 | partable = ParameterTable(processed) |
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34 | return partable |
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35 | |
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36 | def parse_parameter(name, units='', default=None, |
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37 | limits=(-np.inf, np.inf), type='', description=''): |
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38 | # Parameter is a user facing class. Do robust type checking. |
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39 | if not isstr(name): |
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40 | raise ValueError("expected string for parameter name %r"%name) |
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41 | if not isstr(units): |
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42 | raise ValueError("expected units to be a string for %s"%name) |
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43 | # if limits is a list of strings, then this is a choice list |
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44 | # field, and limits are 1 to length of string list |
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45 | if isinstance(limits, list) and all(isstr(k) for k in limits): |
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46 | choices = limits |
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47 | limits = [0, len(choices)-1] |
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48 | else: |
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49 | choices = [] |
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50 | # TODO: maybe allow limits of None for (-inf, inf) |
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51 | try: |
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52 | low, high = limits |
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53 | if not isinstance(low, (int, float)): |
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54 | raise TypeError("low is not numeric") |
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55 | if not isinstance(high, (int, float)): |
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56 | raise TypeError("high is not numeric") |
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57 | if low >= high: |
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58 | raise ValueError("require low < high") |
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59 | except: |
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60 | raise ValueError("invalid limits %s for %s"%(limits, name)) |
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61 | |
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62 | if not isinstance(default, (int, float)): |
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63 | raise ValueError("expected default %r to be a number for %s" |
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64 | % (default, name)) |
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65 | if default < low or default > high: |
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66 | raise ValueError("default value %r not in range for %s" |
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67 | % (default, name)) |
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68 | |
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69 | if type not in ("volume", "orientation", "sld", "magnetic", ""): |
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70 | raise ValueError("unexpected type %r for %s" % (type, name)) |
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71 | |
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72 | if not isstr(description): |
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73 | raise ValueError("expected description to be a string") |
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74 | |
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75 | |
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76 | # Parameter id for name[n] does not include [n] |
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77 | if "[" in name: |
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78 | if not name.endswith(']'): |
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79 | raise ValueError("Expected name[len] for vector parameter %s"%name) |
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80 | pid, ref = name[:-1].split('[', 1) |
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81 | ref = ref.strip() |
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82 | else: |
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83 | pid, ref = name, None |
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84 | |
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85 | |
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86 | # automatically identify sld types |
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87 | if type=='' and (pid.startswith('sld') or pid.endswith('sld')): |
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88 | type = 'sld' |
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89 | |
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90 | # Check if using a vector definition, name[k], as the parameter name |
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91 | if ref: |
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92 | if ref == '': |
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93 | raise ValueError("Need to specify vector length for %s"%name) |
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94 | try: |
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95 | length = int(ref) |
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96 | control = None |
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97 | except: |
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98 | length = None |
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99 | control = ref |
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100 | else: |
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101 | length = 1 |
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102 | control = None |
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103 | |
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104 | # Build the parameter |
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105 | parameter = Parameter(name=name, units=units, default=default, |
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106 | limits=limits, type=type, description=description) |
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107 | |
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108 | # TODO: need better control over whether a parameter is polydisperse |
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109 | parameter.polydisperse = type in ('orientation', 'volume') |
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110 | parameter.relative_pd = type in ('volume') |
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111 | parameter.choices = choices |
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112 | parameter.length = length |
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113 | parameter.length_control = control |
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114 | |
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115 | return parameter |
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116 | |
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117 | |
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118 | def set_demo(model_info, demo): |
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119 | """ |
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120 | Assign demo parameters to model_info['demo'] |
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121 | |
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122 | If demo is not defined, then use defaults. |
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123 | |
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124 | If demo is defined, override defaults with value from demo. |
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125 | |
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126 | If demo references vector fields, such as thickness[n], then support |
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127 | different ways of assigning the demo values, including assigning a |
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128 | specific value (e.g., thickness3=50.0), assigning a new value to all |
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129 | (e.g., thickness=50.0) or assigning values using list notation. |
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130 | """ |
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131 | partable = model_info['parameters'] |
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132 | if demo is None: |
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133 | result = partable.defaults |
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134 | else: |
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135 | pars = dict((p.id, p) for p in partable.kernel_parameters) |
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136 | result = partable.defaults.copy() |
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137 | vectors = dict((name,value) for name,value in demo.items() |
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138 | if name in pars and pars[name].length > 1) |
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139 | if vectors: |
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140 | scalars = dict((name, value) for name, value in demo.items() |
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141 | if name not in pars or pars[name].length == 1) |
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142 | for name, value in vectors.items(): |
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143 | if np.isscalar(value): |
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144 | # support for the form |
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145 | # demo(thickness=0, thickness2=50) |
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146 | for k in pars[name].length: |
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147 | key = name+str(k) |
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148 | if key not in scalars: |
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149 | scalars[key] = vectors |
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150 | else: |
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151 | # supoprt for the form |
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152 | # demo(thickness=[20,10,3]) |
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153 | for (k,v) in enumerate(value): |
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154 | scalars[name+str(k)] = v |
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155 | result.update(scalars) |
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156 | else: |
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157 | result.update(demo) |
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158 | |
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159 | model_info['demo'] = result |
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160 | |
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161 | class Parameter(object): |
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162 | """ |
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163 | The available kernel parameters are defined as a list, with each parameter |
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164 | defined as a sublist with the following elements: |
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165 | |
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166 | *name* is the name that will be used in the call to the kernel |
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167 | function and the name that will be displayed to the user. Names |
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168 | should be lower case, with words separated by underscore. If |
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169 | acronyms are used, the whole acronym should be upper case. |
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170 | |
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171 | *units* should be one of *degrees* for angles, *Ang* for lengths, |
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172 | *1e-6/Ang^2* for SLDs. |
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173 | |
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174 | *default value* will be the initial value for the model when it |
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175 | is selected, or when an initial value is not otherwise specified. |
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176 | |
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177 | *limits = [lb, ub]* are the hard limits on the parameter value, used to |
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178 | limit the polydispersity density function. In the fit, the parameter limits |
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179 | given to the fit are the limits on the central value of the parameter. |
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180 | If there is polydispersity, it will evaluate parameter values outside |
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181 | the fit limits, but not outside the hard limits specified in the model. |
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182 | If there are no limits, use +/-inf imported from numpy. |
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183 | |
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184 | *type* indicates how the parameter will be used. "volume" parameters |
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185 | will be used in all functions. "orientation" parameters will be used |
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186 | in *Iqxy* and *Imagnetic*. "magnetic* parameters will be used in |
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187 | *Imagnetic* only. If *type* is the empty string, the parameter will |
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188 | be used in all of *Iq*, *Iqxy* and *Imagnetic*. "sld" parameters |
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189 | can automatically be promoted to magnetic parameters, each of which |
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190 | will have a magnitude and a direction, which may be different from |
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191 | other sld parameters. |
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192 | |
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193 | *description* is a short description of the parameter. This will |
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194 | be displayed in the parameter table and used as a tool tip for the |
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195 | parameter value in the user interface. |
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196 | |
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197 | Additional values can be set after the parameter is created: |
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198 | |
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199 | *length* is the length of the field if it is a vector field |
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200 | *length_control* is the parameter which sets the vector length |
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201 | *is_control* is True if the parameter is a control parameter for a vector |
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202 | *polydisperse* is true if the parameter accepts a polydispersity |
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203 | *relative_pd* is true if that polydispersity is relative |
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204 | |
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205 | In the usual process these values are set by :func:`make_parameter_table` |
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206 | and :func:`parse_parameter` therein. |
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207 | """ |
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208 | def __init__(self, name, units='', default=None, limits=(-np.inf, np.inf), |
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209 | type='', description=''): |
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210 | self.id = name.split('[')[0].strip() |
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211 | self.name = name |
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212 | self.units = units |
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213 | self.default = default |
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214 | self.limits = limits |
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215 | self.type = type |
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216 | self.description = description |
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217 | |
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218 | # Length and length_control will be filled in once the complete |
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219 | # parameter table is available. |
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220 | self.length = 1 |
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221 | self.length_control = None |
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222 | self.is_control = False |
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223 | |
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224 | # TODO: need better control over whether a parameter is polydisperse |
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225 | self.polydisperse = False |
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226 | self.relative_pd = False |
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227 | |
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228 | # choices are also set externally. |
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229 | self.choices = [] |
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230 | |
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231 | def as_definition(self): |
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232 | """ |
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233 | Declare space for the variable in a parameter structure. |
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234 | |
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235 | For example, the parameter thickness with length 3 will |
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236 | return "double thickness[3];", with no spaces before and |
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237 | no new line character afterward. |
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238 | """ |
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239 | if self.length == 1: |
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240 | return "double %s;"%self.id |
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241 | else: |
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242 | return "double %s[%d];"%(self.id, self.length) |
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243 | |
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244 | def as_function_argument(self): |
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245 | """ |
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246 | Declare the variable as a function argument. |
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247 | |
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248 | For example, the parameter thickness with length 3 will |
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249 | return "double *thickness", with no spaces before and |
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250 | no comma afterward. |
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251 | """ |
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252 | if self.length == 1: |
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253 | return "double %s"%self.id |
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254 | else: |
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255 | return "double *%s"%self.id |
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256 | |
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257 | def as_call_reference(self, prefix=""): |
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258 | # Note: if the parameter is a struct type, then we will need to use |
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259 | # &prefix+id. For scalars and vectors we can just use prefix+id. |
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260 | return prefix + self.id |
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261 | |
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262 | def __str__(self): |
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263 | return "<%s>"%self.name |
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264 | |
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265 | def __repr__(self): |
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266 | return "P<%s>"%self.name |
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267 | |
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268 | |
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269 | class ParameterTable(object): |
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270 | """ |
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271 | ParameterTable manages the list of available parameters. |
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272 | |
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273 | There are a couple of complications which mean that the list of parameters |
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274 | for the kernel differs from the list of parameters that the user sees. |
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275 | |
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276 | (1) Common parameters. Scale and background are implicit to every model, |
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277 | but are not passed to the kernel. |
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278 | |
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279 | (2) Vector parameters. Vector parameters are passed to the kernel as a |
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280 | pointer to an array, e.g., thick[], but they are seen by the user as n |
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281 | separate parameters thick1, thick2, ... |
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282 | |
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283 | Therefore, the parameter table is organized by how it is expected to be |
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284 | used. The following information is needed to set up the kernel functions: |
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285 | |
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286 | * *kernel_parameters* is the list of parameters in the kernel parameter |
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287 | table, with vector parameter p declared as p[]. |
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288 | |
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289 | * *iq_parameters* is the list of parameters to the Iq(q, ...) function, |
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290 | with vector parameter p sent as p[]. |
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291 | |
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292 | * *iqxy_parameters* is the list of parameters to the Iqxy(qx, qy, ...) |
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293 | function, with vector parameter p sent as p[]. |
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294 | |
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295 | * *form_volume_parameters* is the list of parameters to the form_volume(...) |
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296 | function, with vector parameter p sent as p[]. |
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297 | |
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298 | Problem details, which sets up the polydispersity loops, requires the |
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299 | following: |
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300 | |
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301 | * *theta_offset* is the offset of the theta parameter in the kernel parameter |
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302 | table, with vector parameters counted as n individual parameters |
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303 | p1, p2, ..., or offset is -1 if there is no theta parameter. |
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304 | |
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305 | * *max_pd* is the maximum number of polydisperse parameters, with vector |
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306 | parameters counted as n individual parameters p1, p2, ... Note that |
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307 | this number is limited to sasmodels.modelinfo.MAX_PD. |
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308 | |
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309 | * *npars* is the total number of parameters to the kernel, with vector |
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310 | parameters counted as n individual parameters p1, p2, ... |
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311 | |
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312 | * *call_parameters* is the complete list of parameters to the kernel, |
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313 | including scale and background, with vector parameters recorded as |
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314 | individual parameters p1, p2, ... |
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315 | |
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316 | * *active_1d* is the set of names that may be polydisperse for 1d data |
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317 | |
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318 | * *active_2d* is the set of names that may be polydisperse for 2d data |
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319 | |
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320 | User parameters are the set of parameters visible to the user, including |
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321 | the scale and background parameters that the kernel does not see. User |
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322 | parameters don't use vector notation, and instead use p1, p2, ... |
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323 | |
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324 | * *control_parameters* is the |
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325 | |
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326 | """ |
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327 | # scale and background are implicit parameters |
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328 | COMMON = [Parameter(*p) for p in COMMON_PARAMETERS] |
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329 | |
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330 | def __init__(self, parameters): |
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331 | self.kernel_parameters = parameters |
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332 | self._set_vector_lengths() |
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333 | self._make_call_parameter_list() |
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334 | self._categorize_parameters() |
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335 | self._set_defaults() |
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336 | #self._name_table= dict((p.id, p) for p in parameters) |
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337 | |
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338 | def _set_vector_lengths(self): |
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339 | # Sort out the length of the vector parameters such as thickness[n] |
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340 | for p in self.kernel_parameters: |
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341 | if p.length_control: |
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342 | for ref in self.kernel_parameters: |
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343 | if ref.id == p.length_control: |
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344 | break |
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345 | else: |
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346 | raise ValueError("no reference variable %r for %s" |
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347 | % (p.length_control, p.name)) |
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348 | ref.is_control = True |
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349 | low, high = ref.limits |
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350 | if int(low) != low or int(high) != high or low<0 or high>20: |
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351 | raise ValueError("expected limits on %s to be within [0, 20]" |
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352 | % ref.name) |
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353 | p.length = high |
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354 | |
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355 | def _set_defaults(self): |
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356 | # Construct default values, including vector defaults |
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357 | defaults = {} |
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358 | for p in self.call_parameters: |
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359 | if p.length == 1: |
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360 | defaults[p.id] = p.default |
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361 | else: |
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362 | for k in range(1, p.length+1): |
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363 | defaults["%s%d"%(p.id, k)] = p.default |
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364 | self.defaults = defaults |
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365 | |
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366 | def _make_call_parameter_list(self): |
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367 | full_list = self.COMMON[:] |
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368 | for p in self.kernel_parameters: |
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369 | if p.length == 1: |
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370 | full_list.append(p) |
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371 | else: |
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372 | for k in range(1, p.length+1): |
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373 | pk = Parameter(p.id+str(k), p.units, p.default, |
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374 | p.limits, p.type, p.description) |
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375 | pk.polydisperse = p.polydisperse |
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376 | pk.relative_pd = p.relative_pd |
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377 | full_list.append(pk) |
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378 | self.call_parameters = full_list |
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379 | |
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380 | """ # Suppress these for now until we see how they are used |
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381 | def __getitem__(self, k): |
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382 | if isinstance(k, (int, slice)): |
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383 | return self.parameters[k] |
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384 | else: |
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385 | return self._name_table[k] |
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386 | |
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387 | def __contains__(self, key): |
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388 | return key in self._name_table |
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389 | |
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390 | def __iter__(self): |
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391 | return iter(self.expanded_parameters) |
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392 | """ |
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393 | |
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394 | def _categorize_parameters(self): |
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395 | # Set the kernel parameters. Assumes background and scale are the |
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396 | # first two parameters in the parameter list, but these are not sent |
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397 | # to the underlying kernel functions. |
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398 | self.iq_parameters = [p for p in self.kernel_parameters |
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399 | if p.type not in ('orientation', 'magnetic')] |
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400 | self.iqxy_parameters = [p for p in self.kernel_parameters |
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401 | if p.type != 'magnetic'] |
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402 | self.form_volume_parameters = [p for p in self.kernel_parameters |
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403 | if p.type == 'volume'] |
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404 | |
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405 | # Theta offset |
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406 | offset = 0 |
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407 | for p in self.kernel_parameters: |
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408 | if p.name == 'theta': |
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409 | self.theta_offset = offset |
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410 | break |
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411 | offset += p.length |
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412 | else: |
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413 | self.theta_offset = -1 |
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414 | |
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415 | # number of polydisperse parameters |
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416 | num_pd = sum(p.length for p in self.kernel_parameters if p.polydisperse) |
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417 | # Don't use more polydisperse parameters than are available in the model |
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418 | # Note: we can do polydispersity on arbitrary parameters, so it is not |
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419 | # clear that this is a good idea; it does however make the poly_details |
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420 | # code easier to write, so we will leave it in for now. |
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421 | self.max_pd = min(num_pd, MAX_PD) |
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422 | |
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423 | self.npars = sum(p.length for p in self.kernel_parameters) |
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424 | |
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425 | # true if has 2D parameters |
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426 | self.has_2d = any(p.type in ('orientation', 'magnetic') |
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427 | for p in self.kernel_parameters) |
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428 | |
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429 | self.pd_1d = set(p.name for p in self.call_parameters |
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430 | if p.polydisperse and p.type not in ('orientation', 'magnetic')) |
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431 | self.pd_2d = set(p.name for p in self.call_parameters |
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432 | if p.polydisperse and p.type != 'magnetic') |
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433 | |
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434 | def user_parameters(self, pars={}, is2d=True): |
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435 | """ |
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436 | Return the list of parameters for the given data type. |
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437 | |
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438 | Vector parameters are expanded as in place. If multiple parameters |
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439 | share the same vector length, then the parameters will be interleaved |
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440 | in the result. The control parameters come first. For example, |
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441 | if the parameter table is ordered as:: |
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442 | |
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443 | sld_core |
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444 | sld_shell[num_shells] |
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445 | sld_solvent |
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446 | thickness[num_shells] |
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447 | num_shells |
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448 | |
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449 | and *pars[num_shells]=2* then the returned list will be:: |
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450 | |
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451 | num_shells |
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452 | scale |
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453 | background |
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454 | sld_core |
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455 | sld_shell1 |
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456 | thickness1 |
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457 | sld_shell2 |
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458 | thickness2 |
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459 | sld_solvent |
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460 | |
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461 | Note that shell/thickness pairs are grouped together in the result |
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462 | even though they were not grouped in the incoming table. The control |
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463 | parameter is always returned first since the GUI will want to set it |
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464 | early, and rerender the table when it is changed. |
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465 | """ |
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466 | control = [p for p in self.kernel_parameters if p.is_control] |
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467 | |
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468 | # Gather entries such as name[n] into groups of the same n |
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469 | dependent = dict((p.id, []) for p in control) |
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470 | for p in self.kernel_parameters: |
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471 | if p.length_control is not None: |
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472 | dependent[p.length_control].append(p) |
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473 | |
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474 | # Gather entries such as name[4] into groups of the same length |
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475 | fixed = {} |
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476 | for p in self.kernel_parameters: |
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477 | if p.length > 1 and p.length_control is None: |
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478 | fixed.setdefault(p.length, []).append(p) |
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479 | |
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480 | # Using the call_parameters table, we already have expanded forms |
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481 | # for each of the vector parameters; put them in a lookup table |
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482 | expanded_pars = dict((p.name, p) for p in self.call_parameters) |
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483 | |
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484 | # Gather the user parameters in order |
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485 | result = control + self.COMMON |
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486 | for p in self.kernel_parameters: |
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487 | if not is2d and p.type in ('orientation', 'magnetic'): |
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488 | pass |
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489 | elif p.is_control: |
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490 | pass # already added |
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491 | elif p.length_control is not None: |
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492 | table = dependent.get(p.length_control, []) |
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493 | if table: |
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494 | # look up length from incoming parameters |
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495 | table_length = int(pars.get(p.length_control, p.length)) |
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496 | del dependent[p.length_control] # first entry seen |
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497 | for k in range(1, table_length+1): |
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498 | for entry in table: |
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499 | result.append(expanded_pars[entry.id+str(k)]) |
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500 | else: |
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501 | pass # already processed all entries |
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502 | elif p.length > 1: |
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503 | table = fixed.get(p.length, []) |
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504 | if table: |
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505 | table_length = p.length |
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506 | del fixed[p.length] |
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507 | for k in range(1, table_length+1): |
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508 | for entry in table: |
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509 | result.append(expanded_pars[entry.id+str(k)]) |
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510 | else: |
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511 | pass # already processed all entries |
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512 | else: |
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513 | result.append(p) |
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514 | |
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515 | return result |
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516 | |
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517 | |
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518 | |
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519 | def isstr(x): |
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520 | # TODO: 2-3 compatible tests for str, including unicode strings |
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521 | return isinstance(x, str) |
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522 | |
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