1 | """ |
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2 | Calculation thread for modeling |
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3 | """ |
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4 | |
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5 | import time |
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6 | import numpy |
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7 | import math |
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8 | from data_util.calcthread import CalcThread |
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9 | |
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10 | class Calc2D(CalcThread): |
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11 | """ |
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12 | Compute 2D model |
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13 | This calculation assumes a 2-fold symmetry of the model |
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14 | where points are computed for one half of the detector |
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15 | and I(qx, qy) = I(-qx, -qy) is assumed. |
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16 | """ |
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17 | def __init__(self, data, model, smearer, qmin, qmax, page_id, |
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18 | state=None, |
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19 | weight=None, |
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20 | fid=None, |
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21 | toggle_mode_on=False, |
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22 | completefn=None, |
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23 | updatefn=None, |
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24 | update_chisqr=True, |
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25 | source='model', |
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26 | yieldtime=0.04, |
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27 | worktime=0.04 |
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28 | ): |
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29 | CalcThread.__init__(self, completefn, updatefn, yieldtime, worktime) |
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30 | self.qmin = qmin |
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31 | self.qmax = qmax |
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32 | self.weight = weight |
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33 | self.fid = fid |
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34 | #self.qstep = qstep |
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35 | self.toggle_mode_on = toggle_mode_on |
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36 | self.data = data |
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37 | self.page_id = page_id |
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38 | self.state = None |
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39 | # the model on to calculate |
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40 | self.model = model |
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41 | self.smearer = smearer |
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42 | self.starttime = 0 |
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43 | self.update_chisqr = update_chisqr |
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44 | self.source = source |
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45 | |
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46 | def compute(self): |
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47 | """ |
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48 | Compute the data given a model function |
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49 | """ |
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50 | self.starttime = time.time() |
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51 | # Determine appropriate q range |
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52 | if self.qmin == None: |
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53 | self.qmin = 0 |
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54 | if self.qmax == None: |
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55 | if self.data != None: |
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56 | newx = math.pow(max(math.fabs(self.data.xmax), |
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57 | math.fabs(self.data.xmin)), 2) |
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58 | newy = math.pow(max(math.fabs(self.data.ymax), |
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59 | math.fabs(self.data.ymin)), 2) |
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60 | self.qmax = math.sqrt(newx + newy) |
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61 | |
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62 | if self.data is None: |
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63 | msg = "Compute Calc2D receive data = %s.\n" % str(self.data) |
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64 | raise ValueError, msg |
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65 | |
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66 | # Define matrix where data will be plotted |
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67 | radius = numpy.sqrt((self.data.qx_data * self.data.qx_data) + \ |
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68 | (self.data.qy_data * self.data.qy_data)) |
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69 | |
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70 | # For theory, qmax is based on 1d qmax |
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71 | # so that must be mulitified by sqrt(2) to get actual max for 2d |
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72 | index_model = (self.qmin <= radius) & (radius <= self.qmax) |
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73 | index_model = index_model & self.data.mask |
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74 | index_model = index_model & numpy.isfinite(self.data.data) |
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75 | |
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76 | if self.smearer is not None: |
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77 | # Set smearer w/ data, model and index. |
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78 | fn = self.smearer |
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79 | fn.set_model(self.model) |
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80 | fn.set_index(index_model) |
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81 | # Get necessary data from self.data and set the data for smearing |
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82 | fn.get_data() |
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83 | # Calculate smeared Intensity |
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84 | #(by Gaussian averaging): DataLoader/smearing2d/Smearer2D() |
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85 | value = fn.get_value() |
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86 | else: |
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87 | # calculation w/o smearing |
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88 | value = self.model.evalDistribution(\ |
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89 | [self.data.qx_data[index_model], |
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90 | self.data.qy_data[index_model]]) |
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91 | output = numpy.zeros(len(self.data.qx_data)) |
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92 | # output default is None |
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93 | # This method is to distinguish between masked |
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94 | #point(nan) and data point = 0. |
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95 | output = output / output |
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96 | # set value for self.mask==True, else still None to Plottools |
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97 | output[index_model] = value |
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98 | elapsed = time.time() - self.starttime |
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99 | self.complete(image=output, |
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100 | data=self.data, |
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101 | page_id=self.page_id, |
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102 | model=self.model, |
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103 | state=self.state, |
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104 | toggle_mode_on=self.toggle_mode_on, |
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105 | elapsed=elapsed, |
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106 | index=index_model, |
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107 | fid=self.fid, |
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108 | qmin=self.qmin, |
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109 | qmax=self.qmax, |
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110 | weight=self.weight, |
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111 | #qstep=self.qstep, |
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112 | update_chisqr=self.update_chisqr, |
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113 | source=self.source) |
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114 | |
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115 | |
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116 | class Calc1D(CalcThread): |
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117 | """ |
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118 | Compute 1D data |
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119 | """ |
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120 | def __init__(self, model, |
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121 | page_id, |
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122 | data, |
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123 | fid=None, |
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124 | qmin=None, |
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125 | qmax=None, |
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126 | weight=None, |
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127 | smearer=None, |
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128 | toggle_mode_on=False, |
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129 | state=None, |
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130 | completefn=None, |
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131 | update_chisqr=True, |
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132 | source='model', |
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133 | updatefn=None, |
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134 | yieldtime=0.01, |
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135 | worktime=0.01 |
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136 | ): |
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137 | """ |
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138 | """ |
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139 | CalcThread.__init__(self, completefn, |
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140 | updatefn, |
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141 | yieldtime, |
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142 | worktime) |
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143 | self.fid = fid |
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144 | self.data = data |
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145 | self.qmin = qmin |
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146 | self.qmax = qmax |
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147 | self.model = model |
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148 | self.weight = weight |
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149 | self.toggle_mode_on = toggle_mode_on |
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150 | self.state = state |
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151 | self.page_id = page_id |
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152 | self.smearer = smearer |
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153 | self.starttime = 0 |
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154 | self.update_chisqr = update_chisqr |
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155 | self.source = source |
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156 | self.out = None |
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157 | self.index = None |
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158 | |
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159 | def compute(self): |
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160 | """ |
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161 | Compute model 1d value given qmin , qmax , x value |
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162 | """ |
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163 | self.starttime = time.time() |
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164 | output = numpy.zeros((len(self.data.x))) |
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165 | index = (self.qmin <= self.data.x) & (self.data.x <= self.qmax) |
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166 | |
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167 | ##smearer the ouput of the plot |
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168 | if self.smearer is not None: |
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169 | first_bin, last_bin = self.smearer.get_bin_range(self.qmin, |
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170 | self.qmax) |
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171 | mask = self.data.x[first_bin:last_bin] |
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172 | output[first_bin:last_bin] = self.model.evalDistribution(mask) |
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173 | output = self.smearer(output, first_bin, last_bin) |
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174 | else: |
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175 | output[index] = self.model.evalDistribution(self.data.x[index]) |
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176 | |
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177 | elapsed = time.time() - self.starttime |
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178 | |
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179 | self.complete(x=self.data.x[index], y=output[index], |
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180 | page_id=self.page_id, |
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181 | state=self.state, |
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182 | weight=self.weight, |
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183 | fid=self.fid, |
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184 | toggle_mode_on=self.toggle_mode_on, |
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185 | elapsed=elapsed, index=index, model=self.model, |
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186 | data=self.data, |
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187 | update_chisqr=self.update_chisqr, |
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188 | source=self.source) |
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189 | |
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190 | def results(self): |
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191 | """ |
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192 | Send resuts of the computation |
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193 | """ |
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194 | return [self.out, self.index] |
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195 | |
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196 | """ |
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197 | Example: :: |
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198 | |
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199 | class CalcCommandline: |
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200 | def __init__(self, n=20000): |
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201 | #print thread.get_ident() |
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202 | from sans.models.CylinderModel import CylinderModel |
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203 | |
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204 | model = CylinderModel() |
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205 | |
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206 | |
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207 | print model.runXY([0.01, 0.02]) |
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208 | |
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209 | qmax = 0.01 |
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210 | qstep = 0.0001 |
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211 | self.done = False |
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212 | |
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213 | x = numpy.arange(-qmax, qmax+qstep*0.01, qstep) |
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214 | y = numpy.arange(-qmax, qmax+qstep*0.01, qstep) |
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215 | |
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216 | |
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217 | calc_thread_2D = Calc2D(x, y, None, model.clone(),None, |
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218 | -qmax, qmax,qstep, |
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219 | completefn=self.complete, |
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220 | updatefn=self.update , |
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221 | yieldtime=0.0) |
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222 | |
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223 | calc_thread_2D.queue() |
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224 | calc_thread_2D.ready(2.5) |
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225 | |
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226 | while not self.done: |
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227 | time.sleep(1) |
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228 | |
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229 | def update(self,output): |
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230 | print "update" |
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231 | |
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232 | def complete(self, image, data, model, elapsed, qmin, qmax,index, qstep ): |
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233 | print "complete" |
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234 | self.done = True |
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235 | |
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236 | if __name__ == "__main__": |
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237 | CalcCommandline() |
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238 | """ |
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