1 | #pragma rtGlobals=1 // Use modern global access method. |
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2 | |
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3 | |
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4 | // Raspberry particles with polydisperse large sphere |
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5 | #include "Raspberry_v40" |
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6 | |
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7 | Proc PlotPolyRaspberry(num,qmin,qmax) |
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8 | Variable num=500, qmin=1e-5, qmax=0.7 |
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9 | Prompt num "Enter number of data points for model: " |
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10 | Prompt qmin "Enter minimum q-value (^-1) for model: " |
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11 | Prompt qmax "Enter maximum q-value (^-1) for model: " |
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12 | // |
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13 | Make/O/D/n=(num) xwave_PolyRaspberry, ywave_PolyRaspberry |
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14 | xwave_PolyRaspberry = alog(log(qmin) + x*((log(qmax)-log(qmin))/num)) |
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15 | Make/O/D coef_PolyRaspberry = {0.05,5000,0.1,-4e-7,0.005,100,0.4,3.5e-6,0,6.3e-6,0.0} |
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16 | make/o/t parameters_PolyRaspberry = {"vf Large","Radius Large (A)","pd Large Sphere","SLD Large sphere (A-2)","vf Small", "Radius Small (A)","surface coverage","SLD Small sphere (A-2)","delta","SLD solvent (A-2)","bkgd (cm-1)"} |
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17 | Edit parameters_PolyRaspberry, coef_PolyRaspberry |
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18 | |
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19 | Variable/G root:g_PolyRaspberry |
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20 | g_PolyRaspberry := PolyRaspberry(coef_PolyRaspberry, ywave_PolyRaspberry, xwave_PolyRaspberry) |
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21 | Display ywave_PolyRaspberry vs xwave_PolyRaspberry |
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22 | ModifyGraph marker=29, msize=2, mode=4 |
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23 | ModifyGraph log=1,grid=1,mirror=2 |
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24 | Label bottom "q (\\S-1\\M) " |
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25 | Label left "I(q) (cm\\S-1\\M)" |
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26 | AutoPositionWindow/M=1/R=$(WinName(0,1)) $WinName(0,2) |
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27 | |
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28 | AddModelToStrings("PolyRaspberry","coef_PolyRaspberry","parameters_PolyRaspberry","PolyRaspberry") |
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29 | // |
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30 | End |
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31 | |
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32 | |
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33 | Proc PlotSmearedPolyRaspberry(str) |
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34 | String str |
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35 | Prompt str,"Pick the data folder containing the resolution you want",popup,getAList(4) |
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36 | |
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37 | // if any of the resolution waves are missing => abort |
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38 | if(ResolutionWavesMissingDF(str)) //updated to NOT use global strings (in GaussUtils) |
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39 | Abort |
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40 | endif |
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41 | |
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42 | SetDataFolder $("root:"+str) |
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43 | |
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44 | // Setup parameter table for model function |
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45 | Make/O/D smear_coef_PolyRaspberry = {0.05,5000,0.1,-4e-7,0.005,100,0.4,3.5e-6,0,6.3e-6,0.0} |
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46 | make/o/t smear_parameters_PolyRaspberry = {"vf Large","Radius Large (A)","pd Large Sphere","SLD Large sphere (A-2)","vf Small", "Radius Small (A)","surface coverage","SLD Small sphere (A-2)","delta","SLD solvent (A-2)","bkgd (cm-1)"} |
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47 | Edit smear_parameters_PolyRaspberry,smear_coef_PolyRaspberry //display parameters in a table |
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48 | |
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49 | // output smeared intensity wave, dimensions are identical to experimental QSIG values |
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50 | // make extra copy of experimental q-values for easy plotting |
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51 | Duplicate/O $(str+"_q") smeared_PolyRaspberry,smeared_qvals |
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52 | SetScale d,0,0,"1/cm",smeared_PolyRaspberry |
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53 | |
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54 | Variable/G gs_PolyRaspberry=0 |
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55 | gs_PolyRaspberry := fSmearedPolyRaspberry(smear_coef_PolyRaspberry,smeared_PolyRaspberry,smeared_qvals) //this wrapper fills the STRUCT |
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56 | |
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57 | Display smeared_PolyRaspberry vs smeared_qvals |
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58 | ModifyGraph log=1,marker=29,msize=2,mode=4 |
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59 | Label bottom "q (\\S-1\\M)" |
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60 | Label left "I(q) (cm\\S-1\\M)" |
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61 | AutoPositionWindow/M=1/R=$(WinName(0,1)) $WinName(0,2) |
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62 | |
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63 | SetDataFolder root: |
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64 | AddModelToStrings("SmearedPolyRaspberry","smear_coef_PolyRaspberry","smear_parameters_PolyRaspberry","PolyRaspberry") |
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65 | End |
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66 | |
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67 | |
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68 | Function PolyRaspberry(cw,yw,xw) : FitFunc |
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69 | Wave cw,yw,xw |
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70 | |
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71 | #if exists("PolyRaspberryX") |
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72 | yw = PolyRaspberryX(cw,xw) |
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73 | #else |
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74 | yw = fPolyRaspberry(cw,xw) |
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75 | #endif |
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76 | return(0) |
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77 | End |
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78 | |
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79 | |
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80 | Function fPolyRaspberry(w,x) : FitFunc |
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81 | Wave w |
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82 | Variable x |
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83 | |
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84 | |
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85 | //Set up variables |
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86 | // variables are: |
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87 | //[0] volume fraction large spheres |
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88 | //[1] radius large sphere () |
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89 | //[2] polydispersity large sphere |
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90 | //[3] sld large sphere (-2) |
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91 | //[4] volume fraction small spheres |
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92 | //[5] fraction of small spheres at surface |
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93 | //[6] radius small sphere (A) |
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94 | //[7] sld small sphere |
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95 | //[8] small sphere penetration (A) |
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96 | //[9] sld solvent |
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97 | //[10] background (cm-1) |
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98 | |
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99 | Variable vfL,rL,pdL,sldL,vfS,rS,sldS,deltaS,delrhoL,delrhoS,bkg,sldSolv,qval,aSs,fSs |
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100 | vfL = w[0] |
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101 | rL = w[1] |
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102 | pdL = w[2] |
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103 | sldL = w[3] |
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104 | vfS = w[4] |
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105 | rS = w[5] |
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106 | aSs = w[6] |
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107 | sldS = w[7] |
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108 | deltaS = w[8] |
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109 | sldSolv = w[9] |
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110 | bkg = w[10] |
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111 | |
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112 | delrhoL = abs(sldL - sldSolv) |
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113 | delrhoS = abs(sldS - sldSolv) |
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114 | |
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115 | qval = x //rename the input q-value, purely for readability |
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116 | |
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117 | Variable f2 |
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118 | Variable va,vb,ii,zi,nord,yy,summ |
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119 | String weightStr,zStr |
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120 | |
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121 | Variable Np,VL,VS |
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122 | |
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123 | Variable sig = pdL*rL |
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124 | |
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125 | //select number of gauss points by setting nord=20 or76 points |
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126 | // nord = 20 |
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127 | nord = 76 |
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128 | |
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129 | weightStr = "gauss"+num2str(nord)+"wt" |
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130 | zStr = "gauss"+num2str(nord)+"z" |
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131 | |
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132 | if (WaveExists($weightStr) == 0) // wave reference is not valid, |
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133 | Make/D/N=(nord) $weightStr,$zStr |
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134 | Wave gauWt = $weightStr |
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135 | Wave gauZ = $zStr // wave references to pass |
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136 | if(nord==20) |
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137 | Make20GaussPoints(gauWt,gauZ) |
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138 | else |
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139 | Make76GaussPoints(gauWt,gauZ) |
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140 | endif |
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141 | else |
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142 | if(exists(weightStr) > 1) |
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143 | Abort "wave name is already in use" //executed only if name is in use elsewhere |
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144 | endif |
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145 | Wave gauWt = $weightStr |
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146 | Wave gauZ = $zStr // create the wave references |
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147 | endif |
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148 | |
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149 | // end points of integration |
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150 | // limits are technically 0-inf, but wisely choose interesting region of q where R() is nonzero |
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151 | // +/- 3 sigq catches 99.73% of distrubution |
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152 | // change limits (and spacing of zi) at each evaluation based on R() |
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153 | //integration from va to vb |
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154 | va = -4*sig + rL |
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155 | if (va< 4*rS) |
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156 | va=4*rS //to avoid numerical error when va<0 (-ve q-value) |
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157 | endif |
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158 | vb = 4*sig +rL |
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159 | |
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160 | //VL = 4*pi/3*rL^3 |
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161 | //VS = 4*pi/3*rS^3 |
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162 | //Np = vfS*fSs*VL/vfL/VS |
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163 | |
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164 | |
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165 | Make/O/N=9 rasp_temp |
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166 | rasp_temp[0] = w[0] |
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167 | rasp_temp[1] = w[1] |
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168 | rasp_temp[2] = delrhoL |
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169 | rasp_temp[3] = w[4] |
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170 | rasp_temp[4] = w[5] |
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171 | rasp_temp[5] = w[6] |
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172 | rasp_temp[6] = delrhoS |
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173 | rasp_temp[7] = w[8] |
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174 | rasp_temp[8] = w[9] |
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175 | rasp_temp[9] = Np |
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176 | |
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177 | summ = 0.0 // initialize integral |
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178 | for(ii=0;ii<nord;ii+=1) |
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179 | // calculate Gauss points on integration interval (r-value for evaluation) |
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180 | zi = ( gauZ[ii]*(vb-va) + vb + va )/2.0 |
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181 | rasp_temp[1] = zi |
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182 | //calculate scattering |
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183 | yy = gauWt[ii] * RaspGauss_distr(sig,rL,zi) * fRaspberryKernel(rasp_temp,qval) |
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184 | summ += yy //add to the running total of the quadrature |
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185 | endfor |
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186 | |
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187 | summ = (vb-va)/2.0*summ |
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188 | |
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189 | //Use average volume of oil droplet, so fraction of particles should be correct... |
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190 | VL = (4*pi/3*rL^3) *(1+3*pdL^2) |
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191 | VS = 4*pi/3*rS^3 |
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192 | |
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193 | //Using average volume of oil droplet, should get average Np... |
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194 | Np = aSs*4*(rS/(rL+deltaS))*VL/VS |
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195 | //Np = aSs*4*((rL+deltaS)/rS)^2 |
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196 | |
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197 | fSs = Np*vfL*VS/vfS/VL |
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198 | |
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199 | f2 = summ |
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200 | f2 += vfS*(1-fSs)*delrhoS^2*VS*fRaspBes(qval,rS)*fRaspBes(qval,rS) |
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201 | |
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202 | f2 *= 1e8 // [=] 1/cm |
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203 | |
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204 | return (f2+bkg) // Scale, then add in the background |
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205 | |
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206 | End |
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207 | |
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208 | Function RaspGauss_distr(sig,avg,pt) |
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209 | Variable sig,avg,pt |
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210 | |
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211 | Variable retval |
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212 | |
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213 | retval = (1/ ( sig*sqrt(2*Pi)) )*exp(-(avg-pt)^2/sig^2/2) |
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214 | return(retval) |
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215 | End |
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216 | |
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217 | |
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218 | /////////////////////////////////////////////////////////////// |
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219 | // smeared model calculation |
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220 | // |
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221 | // you don't need to do anything with this function, as long as |
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222 | // your Raspberry works correctly, you get the resolution-smeared |
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223 | // version for free. |
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224 | // |
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225 | // this is all there is to the smeared model calculation! |
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226 | Function SmearedPolyRaspberry(s) : FitFunc |
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227 | Struct ResSmearAAOStruct &s |
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228 | |
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229 | // the name of your unsmeared model (AAO) is the first argument |
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230 | Smear_Model_20(PolyRaspberry,s.coefW,s.xW,s.yW,s.resW) |
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231 | |
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232 | return(0) |
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233 | End |
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234 | |
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235 | /////////////////////////////////////////////////////////////// |
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236 | |
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237 | |
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238 | // nothing to change here |
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239 | // |
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240 | //wrapper to calculate the smeared model as an AAO-Struct |
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241 | // fills the struct and calls the ususal function with the STRUCT parameter |
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242 | // |
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243 | // used only for the dependency, not for fitting |
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244 | // |
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245 | Function fSmearedPolyRaspberry(coefW,yW,xW) |
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246 | Wave coefW,yW,xW |
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247 | |
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248 | String str = getWavesDataFolder(yW,0) |
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249 | String DF="root:"+str+":" |
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250 | |
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251 | WAVE resW = $(DF+str+"_res") |
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252 | |
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253 | STRUCT ResSmearAAOStruct fs |
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254 | WAVE fs.coefW = coefW |
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255 | WAVE fs.yW = yW |
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256 | WAVE fs.xW = xW |
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257 | WAVE fs.resW = resW |
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258 | |
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259 | Variable err |
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260 | err = SmearedPolyRaspberry(fs) |
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261 | |
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262 | return (0) |
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263 | End |
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264 | |
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265 | |
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266 | // plots the Gauss distribution based on the coefficient values |
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267 | // a static calculation, so re-run each time |
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268 | // |
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269 | Macro PlotRaspDistribution() |
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270 | |
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271 | variable pd,avg,zz,maxr,vf |
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272 | |
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273 | if(Exists("coef_pgs")!=1) |
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274 | abort "You need to plot the unsmeared model first to create the coefficient table" |
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275 | Endif |
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276 | pd=coef_PolyRaspberry[2] |
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277 | avg = coef_PolyRaspberry[1] |
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278 | vf = coef_PolyRaspberry[0] |
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279 | |
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280 | Variable vfL,rL,pdL,sldL,vfS,rS,sldS,deltaS,delrhoL,delrhoS,bkg,sldSolv,qval ,fSs |
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281 | |
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282 | vfL = coef_PolyRaspberry[0] |
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283 | rL = coef_PolyRaspberry[1] |
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284 | pdL = coef_PolyRaspberry[2] |
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285 | sldL = coef_PolyRaspberry[3] |
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286 | vfS = coef_PolyRaspberry[4] |
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287 | rS = coef_PolyRaspberry[5] |
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288 | aSs = coef_PolyRaspberry[6] |
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289 | sldS = coef_PolyRaspberry[7] |
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290 | deltaS = coef_PolyRaspberry[8] |
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291 | sldSolv = coef_PolyRaspberry[9] |
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292 | bkg = coef_PolyRaspberry[10] |
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293 | |
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294 | Make/O/D/N=1000 Rasp_distribution,Rasp_Vf,Rasp_Np,Rasp_VL |
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295 | maxr = avg*(1+10*pd) |
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296 | |
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297 | SetScale/I x, 0, maxr, Rasp_distribution |
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298 | Rasp_distribution = RaspGauss_distr(pd*avg,avg,x) |
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299 | Display Rasp_distribution |
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300 | |
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301 | End |
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