Mercurial > repos > galaxyp > openms_ptmodel
view PTModel.xml @ 1:30ccca244091 draft
planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/openms commit 9a14ed1f2d3c9abdfb080251b3419dd9e0c52a14
author | galaxyp |
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date | Wed, 09 Aug 2017 09:21:36 -0400 |
parents | 2b34b435c177 |
children | a174f62788b7 |
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<?xml version='1.0' encoding='UTF-8'?> <!--This is a configuration file for the integration of a tools into Galaxy (https://galaxyproject.org/). This file was automatically generated using CTD2Galaxy.--> <!--Proposed Tool Section: [Peptide property prediction]--> <tool id="PTModel" name="PTModel" version="2.2.0"> <description>Trains a model for the prediction of proteotypic peptides from a training set.</description> <macros> <token name="@EXECUTABLE@">PTModel</token> <import>macros.xml</import> </macros> <expand macro="references"/> <expand macro="stdio"/> <expand macro="requirements"/> <command>PTModel #if $param_in_positive: -in_positive $param_in_positive #end if #if $param_in_negative: -in_negative $param_in_negative #end if #if $param_out: -out $param_out #end if #if $param_c: -c $param_c #end if #if $param_svm_type: -svm_type #if " " in str($param_svm_type): "$param_svm_type" #else $param_svm_type #end if #end if #if $param_nu: -nu $param_nu #end if #if $param_kernel_type: -kernel_type #if " " in str($param_kernel_type): "$param_kernel_type" #else $param_kernel_type #end if #end if #if $param_degree: -degree $param_degree #end if #if $param_border_length: -border_length $param_border_length #end if #if $param_k_mer_length: -k_mer_length $param_k_mer_length #end if #if $param_sigma: -sigma $param_sigma #end if #if $param_max_positive_count: -max_positive_count $param_max_positive_count #end if #if $param_max_negative_count: -max_negative_count $param_max_negative_count #end if #if $param_redundant: -redundant #end if #if $param_additive_cv: -additive_cv #end if #if $param_cv_skip_cv: -cv:skip_cv #end if #if $param_cv_number_of_runs: -cv:number_of_runs $param_cv_number_of_runs #end if #if $param_cv_number_of_partitions: -cv:number_of_partitions $param_cv_number_of_partitions #end if #if $param_cv_degree_start: -cv:degree_start $param_cv_degree_start #end if #if $param_cv_degree_step_size: -cv:degree_step_size $param_cv_degree_step_size #end if #if $param_cv_degree_stop: -cv:degree_stop $param_cv_degree_stop #end if #if $param_cv_c_start: -cv:c_start $param_cv_c_start #end if #if $param_cv_c_step_size: -cv:c_step_size $param_cv_c_step_size #end if #if $param_cv_c_stop: -cv:c_stop $param_cv_c_stop #end if #if $param_cv_nu_start: -cv:nu_start $param_cv_nu_start #end if #if $param_cv_nu_step_size: -cv:nu_step_size $param_cv_nu_step_size #end if #if $param_cv_nu_stop: -cv:nu_stop $param_cv_nu_stop #end if #if $param_cv_sigma_start: -cv:sigma_start $param_cv_sigma_start #end if #if $param_cv_sigma_step_size: -cv:sigma_step_size $param_cv_sigma_step_size #end if #if $param_cv_sigma_stop: -cv:sigma_stop $param_cv_sigma_stop #end if #if $adv_opts.adv_opts_selector=='advanced': #if $adv_opts.param_force: -force #end if #end if </command> <inputs> <param name="param_in_positive" type="data" format="idxml" optional="False" label="input file with positive examples" help="(-in_positive) "/> <param name="param_in_negative" type="data" format="idxml" optional="False" label="input file with negative examples" help="(-in_negative) "/> <param name="param_c" type="float" value="1.0" label="the penalty parameter of the svm" help="(-c) "/> <param name="param_svm_type" display="radio" type="select" optional="False" value="C_SVC" label="the type of the svm (NU_SVC or C_SVC)" help="(-svm_type) "> <option value="NU_SVC">NU_SVC</option> <option value="C_SVC" selected="true">C_SVC</option> </param> <param name="param_nu" type="float" min="0.0" max="1.0" optional="True" value="0.5" label="the nu parameter [0..1] of the svm (for nu-SVR)" help="(-nu) "/> <param name="param_kernel_type" display="radio" type="select" optional="False" value="OLIGO" label="the kernel type of the svm" help="(-kernel_type) "> <option value="LINEAR">LINEAR</option> <option value="RBF">RBF</option> <option value="POLY">POLY</option> <option value="OLIGO" selected="true">OLIGO</option> </param> <param name="param_degree" type="integer" min="1" optional="True" value="1" label="the degree parameter of the kernel function of the svm (POLY kernel)" help="(-degree) "/> <param name="param_border_length" type="integer" min="1" optional="True" value="22" label="length of the POBK" help="(-border_length) "/> <param name="param_k_mer_length" type="integer" min="1" optional="True" value="1" label="k_mer length of the POBK" help="(-k_mer_length) "/> <param name="param_sigma" type="float" value="5.0" label="sigma of the POBK" help="(-sigma) "/> <param name="param_max_positive_count" type="integer" min="1" optional="True" value="1000" label="quantity of positive samples for training (randomly chosen if smaller than available quantity)" help="(-max_positive_count) "/> <param name="param_max_negative_count" type="integer" min="1" optional="True" value="1000" label="quantity of positive samples for training (randomly chosen if smaller than available quantity)" help="(-max_negative_count) "/> <param name="param_redundant" display="radio" type="boolean" truevalue="-redundant" falsevalue="" checked="false" optional="True" label="if the input sets are redundant and the redundant peptides should occur more than once in the training set, this flag has to be set" help="(-redundant) "/> <param name="param_additive_cv" display="radio" type="boolean" truevalue="-additive_cv" falsevalue="" checked="false" optional="True" label="if the step sizes should be interpreted additively (otherwise the actual value is multiplied with the step size to get the new value" help="(-additive_cv) "/> <param name="param_cv_skip_cv" display="radio" type="boolean" truevalue="-cv:skip_cv" falsevalue="" checked="false" optional="True" label="Has to be set if the cv should be skipped and the model should just be trained with the specified parameters" help="(-skip_cv) "/> <param name="param_cv_number_of_runs" type="integer" min="1" optional="True" value="10" label="number of runs for the CV" help="(-number_of_runs) "/> <param name="param_cv_number_of_partitions" type="integer" min="2" optional="True" value="10" label="number of CV partitions" help="(-number_of_partitions) "/> <param name="param_cv_degree_start" type="integer" min="1" optional="True" value="1" label="starting point of degree" help="(-degree_start) "/> <param name="param_cv_degree_step_size" type="integer" value="2" label="step size point of degree" help="(-degree_step_size) "/> <param name="param_cv_degree_stop" type="integer" value="4" label="stopping point of degree" help="(-degree_stop) "/> <param name="param_cv_c_start" type="float" value="1.0" label="starting point of c" help="(-c_start) "/> <param name="param_cv_c_step_size" type="float" value="100.0" label="step size of c" help="(-c_step_size) "/> <param name="param_cv_c_stop" type="float" value="1000.0" label="stopping point of c" help="(-c_stop) "/> <param name="param_cv_nu_start" type="float" min="0.0" max="1.0" optional="True" value="0.1" label="starting point of nu" help="(-nu_start) "/> <param name="param_cv_nu_step_size" type="float" value="1.3" label="step size of nu" help="(-nu_step_size) "/> <param name="param_cv_nu_stop" type="float" min="0.0" max="1.0" optional="True" value="0.9" label="stopping point of nu" help="(-nu_stop) "/> <param name="param_cv_sigma_start" type="float" value="1.0" label="starting point of sigma" help="(-sigma_start) "/> <param name="param_cv_sigma_step_size" type="float" value="1.3" label="step size of sigma" help="(-sigma_step_size) "/> <param name="param_cv_sigma_stop" type="float" value="15.0" label="stopping point of sigma" help="(-sigma_stop) "/> <expand macro="advanced_options"> <param name="param_force" display="radio" type="boolean" truevalue="-force" falsevalue="" checked="false" optional="True" label="Overwrite tool specific checks" help="(-force) "/> </expand> </inputs> <outputs> <data name="param_out" format="txt"/> </outputs> <help>Trains a model for the prediction of proteotypic peptides from a training set. For more information, visit http://ftp.mi.fu-berlin.de/OpenMS/release-documentation/html/TOPP_PTModel.html</help> </tool>