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1 <tool id="kpca1" name="Kernel Principal Component Analysis" version="1.1.0">
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2 <description> </description>
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3 <expand macro="requirements" />
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4 <macros>
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5 <import>statistic_tools_macros.xml</import>
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6 </macros>
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7 <command interpreter="python">
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8 kpca.py
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9 --input=$input1
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10 --output1=$out_file1
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11 --output2=$out_file2
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12 --var_cols=$var_cols
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13 --kernel=$kernelChoice.kernel
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14 --features=$features
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15 #if $kernelChoice.kernel == "rbfdot" or $kernelChoice.kernel == "anovadot":
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16 --sigma=$kernelChoice.sigma
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17 --degree="None"
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18 --scale="None"
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19 --offset="None"
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20 --order="None"
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21 #elif $kernelChoice.kernel == "polydot":
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22 --sigma="None"
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23 --degree=$kernelChoice.degree
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24 --scale=$kernelChoice.scale
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25 --offset=$kernelChoice.offset
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26 --order="None"
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27 #elif $kernelChoice.kernel == "tanhdot":
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28 --sigma="None"
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29 --degree="None"
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30 --scale=$kernelChoice.scale
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31 --offset=$kernelChoice.offset
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32 --order="None"
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33 #elif $kernelChoice.kernel == "besseldot":
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34 --sigma=$kernelChoice.sigma
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35 --degree=$kernelChoice.degree
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36 --scale="None"
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37 --offset="None"
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38 --order=$kernelChoice.order
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39 #elif $kernelChoice.kernel == "anovadot":
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40 --sigma=$kernelChoice.sigma
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41 --degree=$kernelChoice.degree
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42 --scale="None"
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43 --offset="None"
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44 --order="None"
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45 #else:
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46 --sigma="None"
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47 --degree="None"
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48 --scale="None"
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49 --offset="None"
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50 --order="None"
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51 #end if
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52 </command>
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53 <inputs>
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54 <param format="tabular" name="input1" type="data" label="Select data" help="Dataset missing? See TIP below."/>
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55 <param name="var_cols" label="Select columns containing input variables " type="data_column" data_ref="input1" numerical="True" multiple="true" >
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56 <validator type="no_options" message="Please select at least one column."/>
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57 </param>
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58 <param name="features" size="10" type="integer" value="2" label="Number of principal components to return" help="To return all, enter 0"/>
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59 <conditional name="kernelChoice">
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60 <param name="kernel" type="select" label="Kernel function">
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61 <option value="rbfdot" selected="true">Gaussian Radial Basis Function</option>
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62 <option value="polydot">Polynomial</option>
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63 <option value="vanilladot">Linear</option>
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64 <option value="tanhdot">Hyperbolic</option>
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65 <option value="laplacedot">Laplacian</option>
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66 <option value="besseldot">Bessel</option>
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67 <option value="anovadot">ANOVA Radial Basis Function</option>
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68 <option value="splinedot">Spline</option>
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69 </param>
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70 <when value="vanilladot" />
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71 <when value="splinedot" />
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72 <when value="rbfdot">
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73 <param name="sigma" size="10" type="float" value="1" label="sigma (inverse kernel width)" />
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74 </when>
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75 <when value="laplacedot">
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76 <param name="sigma" size="10" type="float" value="1" label="sigma (inverse kernel width)" />
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77 </when>
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78 <when value="polydot">
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79 <param name="degree" size="10" type="integer" value="1" label="degree" />
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80 <param name="scale" size="10" type="integer" value="1" label="scale" />
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81 <param name="offset" size="10" type="integer" value="1" label="offset" />
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82 </when>
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83 <when value="tanhdot">
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84 <param name="scale" size="10" type="integer" value="1" label="scale" />
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85 <param name="offset" size="10" type="integer" value="1" label="offset" />
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86 </when>
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87 <when value="besseldot">
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88 <param name="sigma" size="10" type="integer" value="1" label="sigma" />
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89 <param name="order" size="10" type="integer" value="1" label="order" />
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90 <param name="degree" size="10" type="integer" value="1" label="degree" />
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91 </when>
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92 <when value="anovadot">
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93 <param name="sigma" size="10" type="integer" value="1" label="sigma" />
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94 <param name="degree" size="10" type="integer" value="1" label="degree" />
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95 </when>
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96 </conditional>
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97 </inputs>
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98 <outputs>
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99 <data format="input" name="out_file1" metadata_source="input1" />
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100 <data format="pdf" name="out_file2" />
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101 </outputs>
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102 <tests>
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103 <test>
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104 <param name="input1" value="iris.tabular"/>
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105 <param name="var_cols" value="1,2,3,4"/>
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106 <param name="kernel" value="polydot"/>
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107 <param name="features" value="2"/>
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108 <param name="offset" value="0"/>
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109 <param name="scale" value="1"/>
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110 <param name="degree" value="2"/>
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111 <output name="out_file1" file="kpca_out1.tabular"/>
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112 <output name="out_file2" file="kpca_out2.pdf"/>
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113 </test>
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114 </tests>
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115 <help>
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116
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117
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118 .. class:: infomark
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119
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120 **TIP:** If your data is not TAB delimited, use *Edit Datasets->Convert characters*
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121
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122 -----
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123
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124 .. class:: infomark
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125
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126 **What it does**
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127
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128 This tool uses functions from 'kernlab' library from R statistical package to perform Kernel Principal Component Analysis (kPCA) on the input data. It outputs two files, one containing the summary statistics of the performed kPCA, and the other containing a scatterplot matrix of rotated values reported by kPCA.
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129
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130 *Alexandros Karatzoglou, Alex Smola, Kurt Hornik, Achim Zeileis (2004). kernlab - An S4 Package for Kernel Methods in R. Journal of Statistical Software 11(9), 1-20. URL http://www.jstatsoft.org/v11/i09/*
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131
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132 -----
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133
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134 .. class:: warningmark
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135
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136 **Note**
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137
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138 This tool currently treats all variables as continuous numeric variables. Running the tool on categorical variables might result in incorrect results. Rows containing non-numeric (or missing) data in any of the chosen columns will be skipped from the analysis.
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139
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140 </help>
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141 </tool>
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