<tool id="pampa_communitymetrics" name="Calculate community metrics" version="@VERSION@">
    <description>calculate community metrics from abundance data</description>
    <macros>
        <import>pampa_macros.xml</import>
    </macros>
    <expand macro="Pampa_requirements"/>
    <command detect_errors="exit_code"><![CDATA[
        Rscript 
         '$__tool_directory__/FunctExeCalcCommIndexesGalaxy.r' 
         '$input'
         '$indexes'
         '$__tool_directory__/FunctPAMPAGalaxy.r' 
         '$output_community'
    ]]>
    </command>
    <inputs>
        <expand macro="pampa_input_calculate"/>
        <param name="indexes" type="select" label="Choose the community metrics you want to compute" help="Presence/absence, Species richness, Simpson and Shannon index are systematically computed." multiple="true">
            <option selected="true" value="all">All</option>
            <option value="simpson.l">1-Simpson</option>
            <option value="pielou">Pielou</option>
            <option value="hill">Hill</option>
        </param>
    </inputs>
    <outputs>
        <data name="output_community" from_work_dir="TabCommunityIndexes.tabular" format="tabular"/>
    </outputs>
    <tests>
        <test expect_num_outputs="1"> 
            <param name="input" value="ObservationsSansszcl_cropped.tabular"/>
            <param name="indexes" value="all"/>
            <output name="output_community" value="Community_metrics_cropped.tabular"/>
        </test>
    </tests>
    <edam_topics>
       <edam_topic>topic_0610</edam_topic>
       <edam_topic>topic_3050</edam_topic>
    </edam_topics>
    <help><![CDATA[
===============================================
Calculate community metrics from abundance data
===============================================

**What it does**

This tool from PAMPA toolsuite computes community metrics from abundance data:

- Species richness / alpha diversity
- Shannon index
- Simpson index
- Pielou index
- Hill index

|

**Input description**

A tabular file with observation data. Must at least contain three columns 'observation.unit'
which associate year and location or 'year' and 'location', 'species.code' with species ID and 'number' for abundance.

+------------------+--------------+------------+
| observation.unit | species.code |   number   |
+==================+==============+============+
|   site_yearID    |   speciesID  |      4     |
+------------------+--------------+------------+
|        ...       |      ...     |     ...    |
+------------------+--------------+------------+

OR

+------+----------+--------------+------------+
| year | location | species.code |   number   |
+======+==========+==============+============+
| 2000 |locationID|   speciesID  |      4     |
+------+----------+--------------+------------+
|  ... |    ...   |      ...     |     ...    |
+------+----------+--------------+------------+

The data frame may also contain: 

- 'size.class' field with 'G' representing big individuals in given species, 'M' middle-sized individuals and 'P' small individuals
- 'rotation' field for STAVIRO data

|

**Output**

A  tabular file with every metrics selected computed per observation unit

|

**Source**

Derived from PAMPA scripts (https://wwz.ifremer.fr/pampa/Meth.-Outils/Outils) written by Yves Reecht.

  ]]></help>

  <expand macro="pampa_bibref" />
</tool>