<tool id="pampa_glmsp" name="Compute GLM on population data" version="@VERSION@">
    <description>Compute a GLM of your choice on population data</description>
    <macros>
        <import>pampa_macros.xml</import>
    </macros>
    <expand macro="GLM_requirements"/>
    <command detect_errors="exit_code"><![CDATA[
        Rscript 
         '$__tool_directory__/FunctExeCalcGLMSpGalaxy.r' 
         '$input_metric'
         '$input_unitobs'
         '$varint'
         '$varrep'
         '$varrand'
         'species.code'
         #if $settings.advanced=='advanced' 
             $settings.distrib
             $settings.rdata
         #else
             'None'
             'false'
         #end if
         'unitSp'
         '$__tool_directory__/FunctPAMPAGalaxy.r' 
         '$output_summary'
         '$output_recap'
         #if $settings.advanced=='advanced'
             #if $settings.rdata=='true'
                 '$output_GLM'
             #end if
         #end if
    ]]>
    </command>
    <inputs>
        <expand macro="pampa_input_GLM"/>
        <expand macro="pampa_var_GLM"/>
        <conditional name="settings">
            <expand macro="pampa_advanced_params_select_GLM"/>
        </conditional>
    </inputs>
    <outputs>
        <data name="output_summary" from_work_dir="GLMSummary.tabular" format="tabular" label="GLM - Results from your population analysis on ${on_string}"/>
        <expand macro="pampa_output_GLM"/>
    </outputs>
    <tests>
        <test expect_num_outputs="4"> 
            <param name="input_metric" value="Presence_absence_table_sansszcl_cropped.tabular"/>
            <param name="input_unitobs" value="Unitobs.tabular"/>
            <param name="varint" value="4"/>
            <param name="varrep" value="year,site,habitat"/>
            <param name="varrand" value="site"/>
            <param name="advanced" value="advanced"/>
            <param name="distrib" value="None"/>
            <param name="rdata" value="true"/>
            <output name="output_summary">
                <assert_contents> 
                    <has_n_lines n="4"/>
                </assert_contents> 
            </output>
            <output name="output_recap">  
                <assert_contents> 
                    <has_n_lines n="606"/>
                </assert_contents> 
            </output>     
            <output name="output_rate">
                <assert_contents> 
                    <has_n_lines n="45"/>
                </assert_contents> 
            </output>
            <output_collection name="output_GLM"  type="list" count="3">
                <element name="GLM_Abalstel" ftype="Rdata">
                    <assert_contents> 
                        <has_size value="199219" delta="10000"/>
                    </assert_contents> 
                </element>
                <element name="GLM_Hemifasc" ftype="Rdata">
                    <assert_contents> 
                        <has_size value="202264" delta="10000"/>
                    </assert_contents> 
                </element>
                <element name="GLM_Zebrscop" ftype="Rdata">
                    <assert_contents> 
                        <has_size value="207311" delta="10000"/>
                    </assert_contents> 
                </element>
            </output_collection>
        </test>
    </tests>
    <edam_topics>
       <edam_topic>topic_0610</edam_topic>
       <edam_topic>topic_3050</edam_topic>
    </edam_topics>
    <help><![CDATA[
===============================================================
Compute GLM on population data with selected interest variables
===============================================================

**What it does**

This tool from PAMPA toolsuite computes Generalized Linear Models on population data. 

It allows user to choose composition of the model :

- Response variable among numeric or integer variables of the input file

- Explanatory variables among year, site and/or habitat

- Allocation of random effect on year and/or site

|

**Input description**

A tabular file with population data. Must at least contain three or four columns depending on the case : 

- ['year' and 'location'] or ['observation.unit'] 

- 'species.code'

- At least one population metric 

+----------------------+--------------+---------+---------+-----+       
|   observation.unit   | species.code | metric1 | metric2 | ... |            
+======================+==============+=========+=========+=====+        
|   year_locationID    | species code |    2    |   0.4   | ... |            
+----------------------+--------------+---------+---------+-----+        
|          ...         |      ...     |   ...   |   ...   | ... |       
+----------------------+--------------+---------+---------+-----+           

OR

+------+----------+--------------+---------+---------+-----+
| year | location | species.code | metric1 | metric2 | ... |
+======+==========+==============+=========+=========+=====+
| 2000 |locationID| species code |    2    |   0.4   | ... |
+------+----------+--------------+---------+---------+-----+
|  ... |    ...   |      ...     |   ...   |   ...   | ... |
+------+----------+--------------+---------+---------+-----+

The first input may be extracted from the 'Calculate presence absence' tool.

A tabular file with observation unit data which contains at least as much columns as used explanatory variables in addition with the 'observation.unit' column.

+-------------------+---------+--------+------------+-----+       
| observation.unit  |  site   |  year  |  habitat   | ... |            
+===================+=========+========+============+=====+        
|  year_locationID  | site ID |  2000  | habitatID  | ... |            
+-------------------+---------+--------+------------+-----+        
|        ...        |   ...   |   ...  |     ...    | ... |       
+-------------------+---------+--------+------------+-----+ 

The site may represent the same entity as the location or represent an aggregation of several locations.

|

**Output**

Three text files : 

- A first tabular file with GLM results. One analysis per species.

- A second text file with simple statistics on the whole dataset.

- A third text file with ratings of your analysis based on several criterias.

|

**Source**

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

  ]]></help>

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