<tool id="picrust_predict_metagenomes" name="Predict Metagenome" version="@WRAPPER_VERSION@.0">
    <description>based on the abundance of OTUs and a functional database</description>
    <macros>
        <import>macros.xml</import>
    </macros>
    <expand macro="requirements"/>
    <expand macro="version_command"/>
    <command detect_errors="aggressive"><![CDATA[
        predict_metagenomes.py
            -i '$input_data'
            -o tempbiom
            -c '$gg.precalc'
            $normalize_by_otu
            $normalize_by_function
            #if $accuracy_metrics:
                -a $out_summary
            #end if

            @OUTPUT_CONVERSION_COMMANDS@
    ]]></command>
    <inputs>
        <param name="input_data" type="data" format="biom1,h5" label="Input biom file that is output of normalize_by_copy_number.py"/>
        <expand macro="otu-reference-precalculated"/>
        <expand macro="biom_format_select_no_json"/>
        <param argument="normalize_by_function" type="boolean" truevalue="--normalize_by_function" falsevalue="" checked="false" label="Normalize by function?"
               help="Normalizes the predicted functional abundances by dividing each abundance by the sum of functional abundances in the sample. Total sum of abundances for each sample will equal 1"/>
        <param argument="normalize_by_otu" type="boolean" truevalue="--normalize_by_otu" falsevalue="" checked="false" label="Normalize by OTU?"
               help="Normalizes the predicted functional abundances by dividing each abundance by the sum of OTUs in the sample. Note: total sum of abundances for each sample will NOT equal 1"/>
        <param argument="accuracy_metrics" type="boolean" truevalue="T" falsevalue="F" checked="false" label="Calculate accuracy metrics"
               help="requires that per-genome accuracy metrics were calculated during genome prediction (predict_traits tool) (e.g. there are NSTI values in the genome biom file metadata)"/>
    </inputs>
    <outputs>
        <expand macro="biom_output"/>
        <data name="out_summary" format="tabular">
           <filter>accuracy_metrics</filter>
       </data>
    </outputs>
    <tests>
       <test> <!-- test with accuracy metrics and normalizations -->
            <param name="input_data" value="otu_table_for_custom_trait_table.biom"/>
            <param name="source" value="hist"/>
            <param name="precalc" value="custom_trait_table.tab"/>
            <param name="output_type" value="tsv"/>
            <param name="accuracy_metrics" value="T"/>
            <param name="normalize_by_function" value="--normalize_by_function"/>
            <param name="normalize_by_otu" value="--normalize_by_otu"/>
            <output name="out_biom" ftype="tabular">
                <assert_contents>
                    <has_text text="trait2"/>
                    <has_text text="Sample4"/>
                </assert_contents>
            </output>
            <output name="out_summary" ftype="tabular">
                <assert_contents>
                    <has_line_matching expression="#Sample\tMetric\tValue"/>
                    <has_text text="NSTI"/>
                    <has_text text="Sample4"/>
                </assert_contents>
            </output>
        </test>
    </tests>
    <help>
<![CDATA[
@PICRUST_OVERVIEW@

**Command Documentation**

This module produces a 'virtual' metagenome of functional abundances for each sample in the given OTU table. Choose either the KEGG Ortholog (KO), Clusters of Orthologous Genes (COG), or non-coding and other structured RNA (Rfam) precalculated files.

**Input file:** This should be a normalized OTU table populated by the output of the PICRUSt Normalize by Copy Number module.

Make sure that you specify an appropriate functional database for this command (usually the ko, cog, or rfam v13_5 database).

]]>
    </help>
    <expand macro="citations"/>
</tool>