<tool id="hardklor" name="Hardklor" version="2.30.1">
    <description>identification of features from mass spectra</description>
    <requirements>
        <requirement type="package" version="2.3.0">hardklor</requirement>
    </requirements>
    <stdio>
        <exit_code range="1:" level="fatal"/>
    </stdio>
    <command>python $__tool_directory__/hardklor.py "$ms1_in.extension" "$ms1_in"
    "$output" -charge_algo=$cdm -resolution=$res -centroided=$centroided -instrument=$instrument -algorithm=$algorithm -mincharge=$chMin 
    -maxcharge=$chMax -mslvl=$mslvl -correlation=$corr -depth=$depth -sensitivity=$sens -maxfeat=$maxfeat</command>
    <inputs>
	<param name="ms1_in" type="data" format="mzml" label="MS1 files with precursor spectra " />
        <param name="res" type="integer" value="60000" label="Spectral resolution at 400m/z" />
        <param name="centroided" type="select" display="radio" label="Centroided data?">
          <option value="0" selected="true">No</option>
          <option value="1">Yes</option>
        </param>
        <param name="instrument" type="select" label="Instrument" >
            <option value="Orbitrap" selected="true">Orbitrap</option>
            <option value="FTICR" >FTICR</option>
            <option value="TOF" >TOF</option>
            <option value="QIT" >Quadrupole ion trap</option>
        </param>
        <param name="mslvl" type="select" display="radio" label="MS level">
          <option value="0" >All</option>
          <option value="1" selected="true">MS1</option>
          <option value="2">MS2</option>
          <option value="3">MS3</option>
        </param>
        <param name="algorithm" type="select" label="Algorithm">
            <option value="Basic">Basic</option>
            <option value="Version1">Version 1</option>
            <option value="Version2" selected="true">Version 2</option>
        </param>
        <param name="cdm" type="select" label="Charge determination method">
            <option value="None">None</option>
            <option value="FFT">Fast Fourier Transform</option>
            <option value="Patterson">Patterson Algorithm</option>
            <option value="Quick" selected="true">Quick</option>
            <option value="Senko">Senko</option>
        </param>
        
        <param name="chMin" type="integer" value="1" label="Min charge state" />
        <param name="chMax" type="integer" value="5" label="Max charge state" />

        <param name="corr" type="float" value="0.95" label="Correlation threshold" />
        <param name="sens" type="integer" value="2" label="Sensitivity level" help="Ranges from 0 (min, fast) to 3 (max, slow)" />
        <param name="depth" type="integer" value="2" label="Depth of combinatorial analysis" 
help="Max number of overlapping features in any mz window. Keep as low as necessary for speed" />
        <param name="maxfeat" type="integer" value="12" label="Max nr. of features for mz-window to solve" />

<!--        <param name="sn" type="float" value="1" label="Signal to noise threshold" help="Must be >=0"  />
        <param name="snWin" type="float" optional="true" label="Dynamic signal to noise window length (m/z)" 
                help="For spectra with varying noise levels (not for Thermo data)"/>
        <param name="win" type="float" value="5.25" label="Max width of any set of peaks in a spectrum" /> -->
    </inputs>
    
    <outputs>
        <data format="hardklor" name="output" />
    </outputs>
    <tests>
        <test>
            <param name="ms1_in" value="ms1_spectra.mzml"/>
            <output name="output" file="hardklor_result.hk"/>
        </test>
    </tests>
    <help>
        Hardklör identifies peptide or protein-like features in mass spectra. It deconvolves overlapping ion signals and can be used on a variety of input formats. The output of Hardklör can be used by the Krönik tool which summarizes the peptide features over time in an LC-MS experiment.
    </help>
    <citations>
        <citation type="doi">10.1021/ac0700833</citation>
        <citation type="doi">10.1002/0471250953.bi1318s37</citation>
    </citations>
</tool>