diff main_macros.xml @ 3:cd3e98b58c1e draft

planemo upload for repository https://github.com/bgruening/galaxytools/tools/sklearn commit a349cb4673231f12344e418513a08691925565d9

--- a/main_macros.xml	Tue May 31 16:51:19 2016 -0400
+++ b/main_macros.xml	Fri Jun 03 13:55:59 2016 -0400
@@ -10,7 +10,7 @@
 
   <xml name="macro_stdio">
     <stdio>
-        <exit_code range="1:" level="fatal" description="Error occurred. Please check Tool Standard Error" />
+        <exit_code range="1:" level="fatal" description="Error occurred. Please check Tool Standard Error"/>
     </stdio>
   </xml>
 
@@ -23,7 +23,7 @@
             <option value="load">Load a model and predict</option>
         </param>
         <when value="load">
-            <param name="infile_model" type="data" format="@MODEL@" label="Models" help="Select a model file." />
+            <param name="infile_model" type="data" format="@MODEL@" label="Models" help="Select a model file."/>
             <param name="infile_data" type="data" format="@DATA@" label="Data (tabular)" help="Select the dataset you want to classify."/>
             <conditional name="prediction_options">
                 <param name="prediction_option" type="select" label="Select the type of prediction">
@@ -37,7 +37,7 @@
             </conditional>
         </when>
         <when value="train">
-            <param name="infile_train" type="data" format="@TRAIN@" label="Training samples (tabular)" />
+            <param name="infile_train" type="data" format="@TRAIN@" label="Training samples (tabular)"/>
             <conditional name="selected_algorithms">
                 <yield />
             </conditional>
@@ -52,7 +52,7 @@
             <option value="load">Load a model and predict</option>
         </param>
         <when value="load">
-            <param name="infile_model" type="data" format="@MODEL@" label="Models" help="Select a model file." />
+            <param name="infile_model" type="data" format="@MODEL@" label="Models" help="Select a model file."/>
             <param name="infile_data" type="data" format="@DATA@" label="Data (tabular)" help="Select the dataset you want to classify."/>
             <conditional name="prediction_options">
                 <param name="prediction_option" type="select" label="Select the type of prediction">
@@ -275,6 +275,10 @@
     </conditional>
   </xml>
 
+  <xml name="multitype_input" token_format="tabular" token_help="All datasets with tabular format are supporetd.">
+    <param name="infile_transform" type="data" format="@FORMAT@" label="Select a dataset to transform:" help="@HELP@"/>
+  </xml>
+
 
   <!--Advanced options-->
   <xml name="nn_advanced_options">
@@ -525,58 +529,64 @@
 
   <xml name="sparse_preprocessors">
     <param name="selected_pre_processor" type="select" label="Select a preprocessor:">
-      <option value="StandardScaler" selected="true">Standardize features by removing the mean and scaling to unit variance</option>
-      <option value="Binarizer">Binarize data</option>
-      <option value="Imputer">Complete missing values</option>
-      <option value="MaxAbsScaler">Scale features by their maximum absolute value</option>
-      <option value="Normalizer">Normalize samples individually to unit norm</option>
+      <option value="StandardScaler" selected="true">Standard Scaler (Standardizes features by removing the mean and scaling to unit variance)</option>
+      <option value="Binarizer">Binarizer (Binarizes data)</option>
+      <option value="Imputer">Imputer (Completes missing values)</option>
+      <option value="MaxAbsScaler">Max Abs Scaler (Scales features by their maximum absolute value)</option>
+      <option value="Normalizer">Normalizer (Normalizes samples individually to unit norm)</option>
       <yield/>
     </param>
   </xml>
 
   <xml name="sparse_preprocessor_options">
     <when value="Binarizer">
+        <expand macro="multitype_input" format="tabular,txt" help="Tabular and sparse datasets are supporetd."/>
         <section name="options" title="Advanced Options" expanded="False">
-            <param argument="copy" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Use a copy of data for precomputing binarization" help=" "/>
-            <param argument="threshold" type="float" optional="true" value="0.0" label="Threshold" help="Feature values below or equal to this are replaced by 0, above it by 1. Threshold may not be less than 0 for operations on sparse matrices. "/>
+          <param argument="copy" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Use a copy of data for precomputing binarization" help=" "/>
+          <param argument="threshold" type="float" optional="true" value="0.0" label="Threshold" help="Feature values below or equal to this are replaced by 0, above it by 1. Threshold may not be less than 0 for operations on sparse matrices. "/>
         </section>
     </when>
     <when value="Imputer">
-        <section name="options" title="Advanced Options" expanded="False">
-            <param argument="copy" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Use a copy of data for precomputing imputation" help=" "/>
-            <param argument="strategy" type="select" optional="true" label="Imputation strategy" help=" ">
-                <option value="mean" selected="true">Replace missing values using the mean along the axis</option>
-                <option value="median">Replace missing values using the median along the axis</option>
-                <option value="most_frequent">Replace missing using the most frequent value along the axis</option>
-            </param>
-            <param argument="missing_values" type="text" optional="true" value="NaN" label="Placeholder for missing values" help="For missing values encoded as numpy.nan, use the string value “NaN”"/>
-            <param argument="axis" type="select" optional="true" label="The axis along which to impute" help=" ">
-                <option value="0" selected="true">Impute along columns</option>
-                <option value="1">Impute along rows</option>
-            </param>
-        </section>
+      <expand macro="multitype_input" format="tabular,txt" help="Tabular and sparse datasets are supporetd."/>
+      <section name="options" title="Advanced Options" expanded="False">
+          <param argument="copy" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Use a copy of data for precomputing imputation" help=" "/>
+          <param argument="strategy" type="select" optional="true" label="Imputation strategy" help=" ">
+              <option value="mean" selected="true">Replace missing values using the mean along the axis</option>
+              <option value="median">Replace missing values using the median along the axis</option>
+              <option value="most_frequent">Replace missing using the most frequent value along the axis</option>
+          </param>
+          <param argument="missing_values" type="text" optional="true" value="NaN" label="Placeholder for missing values" help="For missing values encoded as numpy.nan, use the string value “NaN”"/>
+          <param argument="axis" type="boolean" optional="true" truevalue="1" falsevalue="0" label="Impute along axis = 1" help="If fasle, axis = 0 is selected for imputation. "/>
+          <!--param argument="axis" type="select" optional="true" label="The axis along which to impute" help=" ">
+              <option value="0" selected="true">Impute along columns</option>
+              <option value="1">Impute along rows</option>
+          </param-->
+      </section>
     </when>
     <when value="StandardScaler">
-        <section name="options" title="Advanced Options" expanded="False">
-            <param argument="copy" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Use a copy of data for performing inplace scaling" help=" "/>
-            <param argument="with_mean" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Center the data before scaling" help=" "/>
-            <param argument="with_std" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Scale the data to unit variance (or unit standard deviation)" help=" "/>
-        </section>
+      <expand macro="multitype_input"/>
+      <section name="options" title="Advanced Options" expanded="False">
+        <param argument="copy" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Use a copy of data for performing inplace scaling" help=" "/>
+        <param argument="with_mean" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Center the data before scaling" help=" "/>
+        <param argument="with_std" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Scale the data to unit variance (or unit standard deviation)" help=" "/>
+      </section>
     </when>
     <when value="MaxAbsScaler">
-        <section name="options" title="Advanced Options" expanded="False">
-            <param argument="copy" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Use a copy of data for precomputing scaling" help=" "/>
-        </section>
+      <expand macro="multitype_input" format="tabular,txt" help="Tabular and sparse datasets are supporetd."/>
+      <section name="options" title="Advanced Options" expanded="False">
+        <param argument="copy" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Use a copy of data for precomputing scaling" help=" "/>
+      </section>
     </when>
     <when value="Normalizer">
-        <section name="options" title="Advanced Options" expanded="False">
-            <param argument="norm" type="select" optional="true" label="The norm to use to normalize non zero samples" help=" ">
-                <option value="l1" selected="true">l1</option>
-                <option value="l2">l2</option>
-                <option value="max">max</option>
-                <param argument="copy" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Use a copy of data for precomputing row normalization" help=" "/>
-            </param>
-        </section>
+      <expand macro="multitype_input" format="tabular,txt" help="Tabular and sparse datasets are supporetd."/>
+      <section name="options" title="Advanced Options" expanded="False">
+        <param argument="norm" type="select" optional="true" label="The norm to use to normalize non zero samples" help=" ">
+          <option value="l1" selected="true">l1</option>
+          <option value="l2">l2</option>
+          <option value="max">max</option>
+          <param argument="copy" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolflase" checked="true" label="Use a copy of data for precomputing row normalization" help=" "/>
+        </param>
+      </section>
     </when>
     <yield/>
   </xml>