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comparison kcca.xml @ 1:2e7bc1bb2dbe draft default tip

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author iuc
date Fri, 09 Jan 2015 12:56:07 -0500
parents ffcdde989859
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0:ffcdde989859 1:2e7bc1bb2dbe
3 <expand macro="requirements" /> 3 <expand macro="requirements" />
4 <macros> 4 <macros>
5 <import>statistic_tools_macros.xml</import> 5 <import>statistic_tools_macros.xml</import>
6 </macros> 6 </macros>
7 <command interpreter="python"> 7 <command interpreter="python">
8 kcca.py 8 <![CDATA[
9 kcca.py
9 --input=$input1 10 --input=$input1
10 --output1=$out_file1 11 --output1=$out_file1
11 --x_cols=$x_cols 12 --x_cols=$x_cols
12 --y_cols=$y_cols 13 --y_cols=$y_cols
13 --kernel=$kernelChoice.kernel 14 --kernel=$kernelChoice.kernel
47 --degree="None" 48 --degree="None"
48 --scale="None" 49 --scale="None"
49 --offset="None" 50 --offset="None"
50 --order="None" 51 --order="None"
51 #end if 52 #end if
53 ]]>
52 </command> 54 </command>
53 <inputs> 55 <inputs>
54 <param format="tabular" name="input1" type="data" label="Select data" help="Dataset missing? See TIP below."/> 56 <param format="tabular" name="input1" type="data" label="Select data" help="Dataset missing? See TIP below."/>
55 <param name="x_cols" label="Select columns containing X variables " type="data_column" data_ref="input1" numerical="True" multiple="true" > 57 <param name="x_cols" label="Select columns containing X variables " type="data_column" data_ref="input1" numerical="True" multiple="true" >
56 <validator type="no_options" message="Please select at least one column."/> 58 <validator type="no_options" message="Please select at least one column."/>
94 </when> 96 </when>
95 <when value="anovadot"> 97 <when value="anovadot">
96 <param name="sigma" size="10" type="float" value="1" label="sigma" /> 98 <param name="sigma" size="10" type="float" value="1" label="sigma" />
97 <param name="degree" size="10" type="float" value="1" label="degree" /> 99 <param name="degree" size="10" type="float" value="1" label="degree" />
98 </when> 100 </when>
99 </conditional> 101 </conditional>
100 </inputs> 102 </inputs>
101 <outputs> 103 <outputs>
102 <data format="input" name="out_file1" metadata_source="input1" /> 104 <data format="input" name="out_file1" metadata_source="input1" />
103 </outputs> 105 </outputs>
104 <tests> 106 <tests>
121 <param name="sigma" value="0.5"/> 123 <param name="sigma" value="0.5"/>
122 <output name="out_file1" file="kcca_out2.tabular" compare="re_match"/> 124 <output name="out_file1" file="kcca_out2.tabular" compare="re_match"/>
123 </test> 125 </test>
124 </tests> 126 </tests>
125 <help> 127 <help>
128 <![CDATA[
126 129
127 130
128 .. class:: infomark 131 .. class:: infomark
129 132
130 **TIP:** If your data is not TAB delimited, use *Edit Datasets-&gt;Convert characters* 133 **TIP:** If your data is not TAB delimited, use *Edit Datasets->Convert characters*
131 134
132 ----- 135 -----
133 136
134 .. class:: infomark 137 .. class:: infomark
135 138
136 **What it does** 139 **What it does**
137 140
138 This tool uses functions from 'kernlab' library from R statistical package to perform Kernel Canonical Correlation Analysis (kCCA) on the input data. 141 This tool uses functions from 'kernlab' library from R statistical package to perform Kernel Canonical Correlation Analysis (kCCA) on the input data.
139 142
140 *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/* 143 *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/*
141 144
142 ----- 145 -----
143 146
145 148
146 **Note** 149 **Note**
147 150
148 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. 151 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.
149 152
153 ]]>
150 </help> 154 </help>
151 </tool> 155 </tool>