1 | |
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2 | Examples for event biasing |
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3 | -------------------------- |
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4 | |
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5 | This directory includes example applications to demonstrate the usage of |
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6 | different variance reduction techniques supported in Geant4, or possible |
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7 | from the user applications. |
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8 | |
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9 | |
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10 | General remark to variance reduction |
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11 | ------------------------------------ |
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12 | The tools provided for importance sampling (or geometrical splitting and |
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13 | Russian roulette) and for the weight window technique require the user to |
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14 | have a good understanding of the physics in the problem. This is because |
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15 | the user has to decide which particle types have to be biased, define the |
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16 | cells (physical volumes, replicas) and assign importances or weight |
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17 | windows to that cells. If this is not done properly it can not be |
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18 | expected that the results describe a real experiment. The examples given |
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19 | here only demonstrate how to use the tools technically. They don't intend |
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20 | to produce physical correct results. |
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21 | |
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22 | General remark to scoring |
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23 | ------------------------- |
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24 | A interface G4VScorer is provided for the user. The user may create his |
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25 | own class to perform the desired scoring. The user defined class |
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26 | therefore should inherit from the interface G4VScorer. |
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27 | An example of an implementation of a scorer is G4Scorer |
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28 | which may be found in source/event. |
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29 | The scoring in these examples is done with a G4Scorer. |
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30 | The variance reduction techniques and scoring do not support all options |
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31 | of the Geant4 geometry. It only supports physical volumes and simple |
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32 | replicas. |
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33 | To identify a physical volume (or replica) objects of the class |
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34 | G4GeometryCell are used. Scoring is done according to these |
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35 | cells and importance values or the weight windows may be assigned to |
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36 | them. |
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37 | When scoring is done in a parallel geometry special action has to be taken |
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38 | to prevent counting of "collisions" with boundaries of the mass geometry |
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39 | as interactions. This is differently handled when scoring is done in the |
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40 | mass geometry. |
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41 | |
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42 | --> G4GeometryCell of the parallel geometry must not share boundaries with |
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43 | the world volume! <-- |
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44 | |
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45 | Known problems |
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46 | -------------- |
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47 | In the following scenario it can happen that a particle is not |
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48 | biased and it's weight is therefore not changed even if it crosses |
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49 | a boundary where biasing should happen. |
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50 | Importance and weight window sampling create particles on boundaries |
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51 | between volumes. If the GPIL method of a physical process returns |
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52 | 0 as step length for a particle on a boundary and if the PostStepDoIt of |
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53 | that process changes the direction of the particle to go back in the |
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54 | former volume the biasing won't be invoked. |
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55 | This will produce particles with weights that do not correspondent to the |
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56 | importance of the current volumes. |
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57 | |
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58 | Further information: |
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59 | -------------------- |
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60 | Short description of importance sampling and scoring: |
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61 | http://cern.ch/geant4/working_groups/geometry/biasing/Sampling.html |
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62 | |
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63 | Example B01 |
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64 | =========== |
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65 | |
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66 | The example uses importance sampling or the weight window technique |
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67 | according to an input parameter. It uses scoring in both cases. |
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68 | Importance values or weight windows are defined according to the mass |
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69 | geometry. In this example the weight window technique is configured such |
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70 | that it behaves equivalent to importance sampling: The window is actually |
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71 | not a window but simply the inverse of the importance value and only |
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72 | one energy region is used that covers all energies in the problem. |
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73 | The user may change the weight window configuration by changing the |
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74 | initialization of the weight window algorithm in example,cc. |
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75 | Different energy bounds for the weight window technique may be specified |
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76 | in B01DetectorConstruction. |
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77 | |
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78 | The executable takes one optional argument: 0 or 1. Without argument or |
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79 | with argument: 0, the importance sampling is applied with argument: 1, |
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80 | the weight window technique is applied. |
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81 | |
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82 | |
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83 | Example B02 |
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84 | =========== |
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85 | |
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86 | This example uses a parallel geometry to define G4GeometryCell objects |
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87 | for scoring and importance sampling. In addition it customizes |
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88 | the scoring. In this example one scorer creates a histogram. |
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89 | |
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90 | Compiling and running |
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91 | --------------------- |
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92 | Can be compiled and executed on a RedHat-7.3 system with gcc-3.2.3 |
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93 | compiler and the tcsh shell. |
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94 | To compile this example you need AIDA 3.2.1 installed. To link |
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95 | and run it you need a AIDA compliant analysis package. The |
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96 | GNUmakefile of this example shows how to use AIDA through PI as |
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97 | analysis interface. |
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98 | Histograms are saved in HBOOK format. It can be displayed with PAW or |
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99 | compatible packages. |
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100 | You need to set the following variables in your environment: |
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101 | "G4ANALYSIS_USE" |
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102 | "PI_BASE_DIR" (where PI has been installed) |
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103 | Finally, source the script setupPI.csh. |
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104 | |
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105 | Now you should be able to run gmake and to run exampleB02. |
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106 | |
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107 | The example stores the plot in the file b02.hbook. |
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108 | To look at the histogram using lizard you also may use PI 1.2.1 |
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109 | http://cern.ch/PI. |
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110 | |
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111 | |
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112 | Example B03 |
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113 | =========== |
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114 | |
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115 | This example uses Geant4 and in particular importance sampling and |
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116 | scoring through python. It creates a simple histogram. It's meant |
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117 | to demonstrate how to use a customized scorer and importance sampling |
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118 | in combination with a scripting language, python. |
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119 | Geant4 code is executed from a python session. Therefore, swig is used |
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120 | to create python shadow classes and to generate the code necessary to |
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121 | use the Geant4 libraries from a python session. |
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122 | It can be built and run using PI: http://cern.ch/PI. |
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123 | At the end a histogram called "trackentering.hbook" is created and can be |
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124 | displayed using standard packages (such as PAW). |
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125 | |
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126 | Building, compiling and running |
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127 | ------------------------------- |
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128 | |
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129 | You need to set the following variables in your environment: |
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130 | "G4ANALYSIS_USE" |
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131 | "PI_BASE_DIR" (where PI has been installed) |
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132 | "SWIG_BASE_DIR" (where SWIG 1.3.15 has been installed) |
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133 | Finally source the script setupPI.csh. |
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134 | |
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135 | You may run gmake now. |
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136 | You should be able to execute the file B03RunApplication.py from your |
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137 | shell or from a lizard session now. |
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138 | |
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139 | At the moment the plotting is not available using a python script, but |
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140 | it is planned in future releases. A histogram is created and later displayed |
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141 | using standard analysis packages. |
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142 | |
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143 | To clean all the added files, just type gmake clean_all. |
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144 | |
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145 | Files in B03; |
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146 | B03Application.py: Is a example class utilizing importance sampling |
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147 | and scoring using python. |
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148 | B03RunApplication.py: Is a python script running the example. |
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149 | It may be executed from the shell or in a python session. |
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150 | B03App.py: Is created by swig using swig. |
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