Mercurial > repos > ecology > pampa_presabs

annotate CalculatePresAbs.xml @ 5:1ebb70b59037 draft default tip

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"planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 65ab5b6fe84871db0fe18244d805cea19a44e830"
author ecology
date Sat, 26 Jun 2021 07:19:36 +0000
parents 8d8aec182fb1
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1 <tool id="pampa_presabs" name="Calculate presence absence table" version="@VERSION@">
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2 <description>calculate presence absence table from observation data</description>
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3 <macros>
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4 <import>pampa_macros.xml</import>
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5 </macros>
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6 <expand macro="Pampa_requirements"/>
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7 <command detect_errors="exit_code"><![CDATA[
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8 Rscript
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9 '$__tool_directory__/FunctExeCalcPresAbsGalaxy.r'
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10 '$input'
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11 '$__tool_directory__/FunctPAMPAGalaxy.r'
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12 '$output_presabs'
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13 ]]>
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14 </command>
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15 <inputs>
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16 <expand macro="pampa_input_calculate"/>
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17 </inputs>
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18 <outputs>
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19 <data name="output_presabs" from_work_dir="TabPresAbs.tabular" format="tabular"/>
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20 </outputs>
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21 <tests>
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22 <test expect_num_outputs="1">
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23 <param name="input" value="ObservationsSansszcl_cropped.tabular"/>
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24 <output name="output_presabs" value="Presence_absence_table_sansszcl_cropped.tabular"/>
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25 </test>
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26 </tests>
1
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27 <edam_topics>
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28 <edam_topic>topic_0610</edam_topic>
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29 <edam_topic>topic_3050</edam_topic>
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30 </edam_topics>
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31 <help><![CDATA[
3
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32
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33 ====================================================
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34 Calculate presence absence table from abundance data
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35 ====================================================
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37 **What it does**
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38
c9dfe4e20a45 "planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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39 This tool from PAMPA toolsuite computes an abundance (max and standard deviation if SVR data) and presence absence table at finest aggregation possible from observation data
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41 |
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43 **Input description**
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44
c9dfe4e20a45 "planemo upload for repository https://github.com/ColineRoyaux/PAMPA-Galaxy commit 07f1028cc764f920b1e6419c151f04ab4e3600fa"
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45 A tabular file with observation data. Must at least contain three columns 'observation.unit'
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46 which associate year and location or 'year' and 'location', 'species.code' with species ID and 'number' for abundance.
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47
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48 +------------------+--------------+------------+
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49 | observation.unit | species.code | number |
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50 +==================+==============+============+
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51 | site_yearID | speciesID | 4 |
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52 +------------------+--------------+------------+
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53 | ... | ... | ... |
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54 +------------------+--------------+------------+
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56 OR
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58 +------+----------+--------------+------------+
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59 | year | location | species.code | number |
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60 +======+==========+==============+============+
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61 | 2000 |locationID| speciesID | 4 |
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62 +------+----------+--------------+------------+
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63 | ... | ... | ... | ... |
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64 +------+----------+--------------+------------+
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66 The data frame may also contain:
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67
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68 - 'size.class' field with 'G' representing big individuals in given species, 'M'middle-sized individuals and 'P' small individuals
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69 - 'rotation' field for STAVIRO data
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71 |
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73 **Output**
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76 A tabular file with presence/absence at finest aggregation available (per observation unit per species OR per observation unit per species per size class)
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79 |
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80
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81 **Source**
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82
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83 Derived from PAMPA scripts (https://wwz.ifremer.fr/pampa/Meth.-Outils/Outils) written by Yves Reecht.
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84
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85 ]]></help>
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86 <expand macro="pampa_bibref" />
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87 </tool>