diff MapAlignerTreeGuided.xml @ 5:37d1f970c572 draft default tip

planemo upload for repository https://github.com/galaxyproteomics/tools-galaxyp/tree/master/tools/openms commit 5c080b1e2b99f1c88f4557e9fec8c45c9d23b906
author galaxyp
date Fri, 14 Jun 2024 21:36:22 +0000
parents 502c7e321ba5
children
line wrap: on
line diff
--- a/MapAlignerTreeGuided.xml	Thu Dec 01 19:24:51 2022 +0000
+++ b/MapAlignerTreeGuided.xml	Fri Jun 14 21:36:22 2024 +0000
@@ -1,8 +1,7 @@
-<?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 CTDConverter.-->
 <!--Proposed Tool Section: [Map Alignment]-->
 <tool id="MapAlignerTreeGuided" name="MapAlignerTreeGuided" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="21.05">
-  <description>Tree guided correction of retention time distortions between maps.</description>
+  <description>Tree guided correction of retention time distortions between maps</description>
   <macros>
     <token name="@EXECUTABLE@">MapAlignerTreeGuided</token>
     <import>macros.xml</import>
@@ -17,9 +16,9 @@
 mkdir in_cond.in &&
 #if $in_cond.in_select == "no"
 mkdir ${' '.join(["'in_cond.in/%s'" % (i) for i, f in enumerate($in_cond.in) if f])} && 
-${' '.join(["ln -s '%s' 'in_cond.in/%s/%s.%s' && " % (f, i, re.sub('[^\w\-_]', '_', f.element_identifier), $gxy2omsext(f.ext)) for i, f in enumerate($in_cond.in) if f])}
+${' '.join(["cp '%s' 'in_cond.in/%s/%s.%s' && " % (f, i, re.sub('[^\w\-_]', '_', f.element_identifier), $gxy2omsext(f.ext)) for i, f in enumerate($in_cond.in) if f])}
 #else
-ln -s '$in_cond.in' 'in_cond.in/${re.sub("[^\w\-_]", "_", $in_cond.in.element_identifier)}.$gxy2omsext($in_cond.in.ext)' &&
+cp '$in_cond.in' 'in_cond.in/${re.sub("[^\w\-_]", "_", $in_cond.in.element_identifier)}.$gxy2omsext($in_cond.in.ext)' &&
 #end if
 #if "out_FLAG" in str($OPTIONAL_OUTPUTS).split(',')
   mkdir out &&
@@ -75,14 +74,14 @@
         <option value="yes">Yes: process each dataset in an independent job</option>
       </param>
       <when value="no">
-        <param argument="-in" type="data" format="featurexml" multiple="true" optional="false" label="Input files to align (all must have the same file type)" help=" select featurexml data sets(s)"/>
+        <param argument="-in" type="data" format="featurexml" multiple="true" label="Input files to align (all must have the same file type)" help=" select featurexml data sets(s)"/>
       </when>
       <when value="yes">
-        <param argument="-in" type="data" format="featurexml" multiple="false" optional="false" label="Input files to align (all must have the same file type)" help=" select featurexml data sets(s)"/>
+        <param argument="-in" type="data" format="featurexml" label="Input files to align (all must have the same file type)" help=" select featurexml data sets(s)"/>
       </when>
     </conditional>
     <section name="algorithm" title="Algorithm parameters section" help="" expanded="false">
-      <param name="model_type" argument="-algorithm:model_type" type="select" optional="true" label="Options to control the modeling of retention time transformations from data" help="">
+      <param name="model_type" argument="-algorithm:model_type" type="select" label="Options to control the modeling of retention time transformations from data" help="">
         <option value="linear">linear</option>
         <option value="b_spline" selected="true">b_spline</option>
         <option value="lowess">lowess</option>
@@ -90,7 +89,7 @@
         <expand macro="list_string_san" name="model_type"/>
       </param>
       <section name="model" title="" help="" expanded="false">
-        <param name="type" argument="-algorithm:model:type" type="select" optional="true" label="Type of model" help="">
+        <param name="type" argument="-algorithm:model:type" type="select" label="Type of model" help="">
           <option value="linear">linear</option>
           <option value="b_spline" selected="true">b_spline</option>
           <option value="lowess">lowess</option>
@@ -99,48 +98,48 @@
         </param>
         <section name="linear" title="Parameters for 'linear' model" help="" expanded="false">
           <param name="symmetric_regression" argument="-algorithm:model:linear:symmetric_regression" type="boolean" truevalue="true" falsevalue="false" checked="false" label="Perform linear regression on 'y - x' vs" help="'y + x', instead of on 'y' vs. 'x'"/>
-          <param name="x_weight" argument="-algorithm:model:linear:x_weight" type="select" optional="true" label="Weight x values" help="">
+          <param name="x_weight" argument="-algorithm:model:linear:x_weight" type="select" label="Weight x values" help="">
             <option value="1/x">1/x</option>
             <option value="1/x2">1/x2</option>
             <option value="ln(x)">ln(x)</option>
-            <option value=""></option>
+            <option value="x" selected="true">x</option>
             <expand macro="list_string_san" name="x_weight"/>
           </param>
-          <param name="y_weight" argument="-algorithm:model:linear:y_weight" type="select" optional="true" label="Weight y values" help="">
+          <param name="y_weight" argument="-algorithm:model:linear:y_weight" type="select" label="Weight y values" help="">
             <option value="1/y">1/y</option>
             <option value="1/y2">1/y2</option>
             <option value="ln(y)">ln(y)</option>
-            <option value=""></option>
+            <option value="y" selected="true">y</option>
             <expand macro="list_string_san" name="y_weight"/>
           </param>
-          <param name="x_datum_min" argument="-algorithm:model:linear:x_datum_min" type="float" optional="true" value="1e-15" label="Minimum x value" help=""/>
-          <param name="x_datum_max" argument="-algorithm:model:linear:x_datum_max" type="float" optional="true" value="1000000000000000.0" label="Maximum x value" help=""/>
-          <param name="y_datum_min" argument="-algorithm:model:linear:y_datum_min" type="float" optional="true" value="1e-15" label="Minimum y value" help=""/>
-          <param name="y_datum_max" argument="-algorithm:model:linear:y_datum_max" type="float" optional="true" value="1000000000000000.0" label="Maximum y value" help=""/>
+          <param name="x_datum_min" argument="-algorithm:model:linear:x_datum_min" type="float" value="1e-15" label="Minimum x value" help=""/>
+          <param name="x_datum_max" argument="-algorithm:model:linear:x_datum_max" type="float" value="1000000000000000.0" label="Maximum x value" help=""/>
+          <param name="y_datum_min" argument="-algorithm:model:linear:y_datum_min" type="float" value="1e-15" label="Minimum y value" help=""/>
+          <param name="y_datum_max" argument="-algorithm:model:linear:y_datum_max" type="float" value="1000000000000000.0" label="Maximum y value" help=""/>
         </section>
         <section name="b_spline" title="Parameters for 'b_spline' model" help="" expanded="false">
-          <param name="wavelength" argument="-algorithm:model:b_spline:wavelength" type="float" optional="true" min="0.0" value="0.0" label="Determines the amount of smoothing by setting the number of nodes for the B-spline" help="The number is chosen so that the spline approximates a low-pass filter with this cutoff wavelength. The wavelength is given in the same units as the data; a higher value means more smoothing. '0' sets the number of nodes to twice the number of input points"/>
-          <param name="num_nodes" argument="-algorithm:model:b_spline:num_nodes" type="integer" optional="true" min="0" value="5" label="Number of nodes for B-spline fitting" help="Overrides 'wavelength' if set (to two or greater). A lower value means more smoothing"/>
-          <param name="extrapolate" argument="-algorithm:model:b_spline:extrapolate" type="select" optional="true" label="Method to use for extrapolation beyond the original data range" help="'linear': Linear extrapolation using the slope of the B-spline at the corresponding endpoint. 'b_spline': Use the B-spline (as for interpolation). 'constant': Use the constant value of the B-spline at the corresponding endpoint. 'global_linear': Use a linear fit through the data (which will most probably introduce discontinuities at the ends of the data range)">
+          <param name="wavelength" argument="-algorithm:model:b_spline:wavelength" type="float" min="0.0" value="0.0" label="Determines the amount of smoothing by setting the number of nodes for the B-spline" help="The number is chosen so that the spline approximates a low-pass filter with this cutoff wavelength. The wavelength is given in the same units as the data; a higher value means more smoothing. '0' sets the number of nodes to twice the number of input points"/>
+          <param name="num_nodes" argument="-algorithm:model:b_spline:num_nodes" type="integer" min="0" value="5" label="Number of nodes for B-spline fitting" help="Overrides 'wavelength' if set (to two or greater). A lower value means more smoothing"/>
+          <param name="extrapolate" argument="-algorithm:model:b_spline:extrapolate" type="select" label="Method to use for extrapolation beyond the original data range" help="'linear': Linear extrapolation using the slope of the B-spline at the corresponding endpoint. 'b_spline': Use the B-spline (as for interpolation). 'constant': Use the constant value of the B-spline at the corresponding endpoint. 'global_linear': Use a linear fit through the data (which will most probably introduce discontinuities at the ends of the data range)">
             <option value="linear" selected="true">linear</option>
             <option value="b_spline">b_spline</option>
             <option value="constant">constant</option>
             <option value="global_linear">global_linear</option>
             <expand macro="list_string_san" name="extrapolate"/>
           </param>
-          <param name="boundary_condition" argument="-algorithm:model:b_spline:boundary_condition" type="integer" optional="true" min="0" max="2" value="2" label="Boundary condition at B-spline endpoints: 0 (value zero), 1 (first derivative zero) or 2 (second derivative zero)" help=""/>
+          <param name="boundary_condition" argument="-algorithm:model:b_spline:boundary_condition" type="integer" min="0" max="2" value="2" label="Boundary condition at B-spline endpoints: 0 (value zero), 1 (first derivative zero) or 2 (second derivative zero)" help=""/>
         </section>
         <section name="lowess" title="Parameters for 'lowess' model" help="" expanded="false">
-          <param name="span" argument="-algorithm:model:lowess:span" type="float" optional="true" min="0.0" max="1.0" value="0.666666666666667" label="Fraction of datapoints (f) to use for each local regression (determines the amount of smoothing)" help="Choosing this parameter in the range .2 to .8 usually results in a good fit"/>
-          <param name="num_iterations" argument="-algorithm:model:lowess:num_iterations" type="integer" optional="true" min="0" value="3" label="Number of robustifying iterations for lowess fitting" help=""/>
-          <param name="delta" argument="-algorithm:model:lowess:delta" type="float" optional="true" value="-1.0" label="Nonnegative parameter which may be used to save computations (recommended value is 0.01 of the range of the input" help="e.g. for data ranging from 1000 seconds to 2000 seconds, it could be set to 10). Setting a negative value will automatically do this"/>
-          <param name="interpolation_type" argument="-algorithm:model:lowess:interpolation_type" type="select" optional="true" label="Method to use for interpolation between datapoints computed by lowess" help="'linear': Linear interpolation. 'cspline': Use the cubic spline for interpolation. 'akima': Use an akima spline for interpolation">
+          <param name="span" argument="-algorithm:model:lowess:span" type="float" min="0.0" max="1.0" value="0.666666666666667" label="Fraction of datapoints (f) to use for each local regression (determines the amount of smoothing)" help="Choosing this parameter in the range .2 to .8 usually results in a good fit"/>
+          <param name="num_iterations" argument="-algorithm:model:lowess:num_iterations" type="integer" min="0" value="3" label="Number of robustifying iterations for lowess fitting" help=""/>
+          <param name="delta" argument="-algorithm:model:lowess:delta" type="float" value="-1.0" label="Nonnegative parameter which may be used to save computations (recommended value is 0.01 of the range of the input" help="e.g. for data ranging from 1000 seconds to 2000 seconds, it could be set to 10). Setting a negative value will automatically do this"/>
+          <param name="interpolation_type" argument="-algorithm:model:lowess:interpolation_type" type="select" label="Method to use for interpolation between datapoints computed by lowess" help="'linear': Linear interpolation. 'cspline': Use the cubic spline for interpolation. 'akima': Use an akima spline for interpolation">
             <option value="linear">linear</option>
             <option value="cspline" selected="true">cspline</option>
             <option value="akima">akima</option>
             <expand macro="list_string_san" name="interpolation_type"/>
           </param>
-          <param name="extrapolation_type" argument="-algorithm:model:lowess:extrapolation_type" type="select" optional="true" label="Method to use for extrapolation outside the data range" help="'two-point-linear': Uses a line through the first and last point to extrapolate. 'four-point-linear': Uses a line through the first and second point to extrapolate in front and and a line through the last and second-to-last point in the end. 'global-linear': Uses a linear regression to fit a line through all data points and use it for interpolation">
+          <param name="extrapolation_type" argument="-algorithm:model:lowess:extrapolation_type" type="select" label="Method to use for extrapolation outside the data range" help="'two-point-linear': Uses a line through the first and last point to extrapolate. 'four-point-linear': Uses a line through the first and second point to extrapolate in front and and a line through the last and second-to-last point in the end. 'global-linear': Uses a linear regression to fit a line through all data points and use it for interpolation">
             <option value="two-point-linear">two-point-linear</option>
             <option value="four-point-linear" selected="true">four-point-linear</option>
             <option value="global-linear">global-linear</option>
@@ -148,13 +147,13 @@
           </param>
         </section>
         <section name="interpolated" title="Parameters for 'interpolated' model" help="" expanded="false">
-          <param name="interpolation_type" argument="-algorithm:model:interpolated:interpolation_type" type="select" optional="true" label="Type of interpolation to apply" help="">
+          <param name="interpolation_type" argument="-algorithm:model:interpolated:interpolation_type" type="select" label="Type of interpolation to apply" help="">
             <option value="linear">linear</option>
             <option value="cspline" selected="true">cspline</option>
             <option value="akima">akima</option>
             <expand macro="list_string_san" name="interpolation_type"/>
           </param>
-          <param name="extrapolation_type" argument="-algorithm:model:interpolated:extrapolation_type" type="select" optional="true" label="Type of extrapolation to apply: two-point-linear: use the first and last data point to build a single linear model, four-point-linear: build two linear models on both ends using the first two / last two points, global-linear: use all points to build a single linear model" help="Note that global-linear may not be continuous at the border">
+          <param name="extrapolation_type" argument="-algorithm:model:interpolated:extrapolation_type" type="select" label="Type of extrapolation to apply: two-point-linear: use the first and last data point to build a single linear model, four-point-linear: build two linear models on both ends using the first two / last two points, global-linear: use all points to build a single linear model" help="Note that global-linear may not be continuous at the border">
             <option value="two-point-linear" selected="true">two-point-linear</option>
             <option value="four-point-linear">four-point-linear</option>
             <option value="global-linear">global-linear</option>
@@ -167,9 +166,9 @@
           <expand macro="list_string_san" name="score_type"/>
         </param>
         <param name="score_cutoff" argument="-algorithm:align_algorithm:score_cutoff" type="boolean" truevalue="true" falsevalue="false" checked="false" label="Use only IDs above a score cut-off (parameter 'min_score') for alignment?" help=""/>
-        <param name="min_score" argument="-algorithm:align_algorithm:min_score" type="float" optional="true" value="0.05" label="If 'score_cutoff' is 'true': Minimum score for an ID to be considered" help="Unless you have very few runs or identifications, increase this value to focus on more informative peptides"/>
-        <param name="min_run_occur" argument="-algorithm:align_algorithm:min_run_occur" type="integer" optional="true" min="2" value="2" label="Minimum number of runs (incl" help="reference, if any) in which a peptide must occur to be used for the alignment.. Unless you have very few runs or identifications, increase this value to focus on more informative peptides"/>
-        <param name="max_rt_shift" argument="-algorithm:align_algorithm:max_rt_shift" type="float" optional="true" min="0.0" value="0.5" label="Maximum realistic RT difference for a peptide (median per run vs" help="reference). Peptides with higher shifts (outliers) are not used to compute the alignment.. If 0, no limit (disable filter); if &gt; 1, the final value in seconds; if &lt;= 1, taken as a fraction of the range of the reference RT scale"/>
+        <param name="min_score" argument="-algorithm:align_algorithm:min_score" type="float" value="0.05" label="If 'score_cutoff' is 'true': Minimum score for an ID to be considered" help="Unless you have very few runs or identifications, increase this value to focus on more informative peptides"/>
+        <param name="min_run_occur" argument="-algorithm:align_algorithm:min_run_occur" type="integer" min="2" value="2" label="Minimum number of runs (incl" help="reference, if any) in which a peptide must occur to be used for the alignment.. Unless you have very few runs or identifications, increase this value to focus on more informative peptides"/>
+        <param name="max_rt_shift" argument="-algorithm:align_algorithm:max_rt_shift" type="float" min="0.0" value="0.5" label="Maximum realistic RT difference for a peptide (median per run vs" help="reference). Peptides with higher shifts (outliers) are not used to compute the alignment.. If 0, no limit (disable filter); if &gt; 1, the final value in seconds; if &lt;= 1, taken as a fraction of the range of the reference RT scale"/>
         <param name="use_unassigned_peptides" argument="-algorithm:align_algorithm:use_unassigned_peptides" type="boolean" truevalue="true" falsevalue="false" checked="true" label="Should unassigned peptide identifications be used when computing an alignment of feature or consensus maps" help="If 'false', only peptide IDs assigned to features will be used"/>
         <param name="use_feature_rt" argument="-algorithm:align_algorithm:use_feature_rt" type="boolean" truevalue="true" falsevalue="false" checked="true" label="When aligning feature or consensus maps, don't use the retention time of a peptide identification directly; instead, use the retention time of the centroid of the feature (apex of the elution profile) that the peptide was matched to" help="If different identifications are matched to one feature, only the peptide closest to the centroid in RT is used.. Precludes 'use_unassigned_peptides'"/>
         <param name="use_adducts" argument="-algorithm:align_algorithm:use_adducts" type="boolean" truevalue="true" falsevalue="false" checked="true" label="If IDs contain adducts, treat differently adducted variants of the same molecule as different" help=""/>
@@ -177,7 +176,7 @@
     </section>
     <expand macro="adv_opts_macro">
       <param argument="-force" type="boolean" truevalue="true" falsevalue="false" checked="false" label="Overrides tool-specific checks" help=""/>
-      <param argument="-test" type="hidden" optional="true" value="False" label="Enables the test mode (needed for internal use only)" help="">
+      <param argument="-test" type="hidden" value="False" label="Enables the test mode (needed for internal use only)" help="" optional="true">
         <expand macro="list_string_san" name="test"/>
       </param>
     </expand>
@@ -203,7 +202,8 @@
       <filter>OPTIONAL_OUTPUTS is not None and "ctd_out_FLAG" in OPTIONAL_OUTPUTS</filter>
     </data>
   </outputs>
-  <tests><!-- TOPP_MapAlignerTreeGuided_1 -->
+  <tests>
+    <!-- TOPP_MapAlignerTreeGuided_1 -->
     <test expect_num_outputs="2">
       <section name="adv_opts">
         <param name="force" value="false"/>
@@ -219,8 +219,8 @@
           <param name="type" value="b_spline"/>
           <section name="linear">
             <param name="symmetric_regression" value="false"/>
-            <param name="x_weight"/>
-            <param name="y_weight"/>
+            <param name="x_weight" value="x"/>
+            <param name="y_weight" value="y"/>
             <param name="x_datum_min" value="1e-15"/>
             <param name="x_datum_max" value="1000000000000000.0"/>
             <param name="y_datum_min" value="1e-15"/>
@@ -261,6 +261,9 @@
           <is_valid_xml/>
         </assert_contents>
       </output>
+      <assert_stdout>
+        <has_text_matching expression="@EXECUTABLE@ took .* \(wall\), .* \(CPU\), .* \(system\), .* \(user\)(; Peak Memory Usage: 32 MB)?."/>
+      </assert_stdout>
     </test>
     <!-- TOPP_MapAlignerTreeGuided_2 -->
     <test expect_num_outputs="2">
@@ -278,8 +281,8 @@
           <param name="type" value="b_spline"/>
           <section name="linear">
             <param name="symmetric_regression" value="false"/>
-            <param name="x_weight"/>
-            <param name="y_weight"/>
+            <param name="x_weight" value="x"/>
+            <param name="y_weight" value="y"/>
             <param name="x_datum_min" value="1e-15"/>
             <param name="x_datum_max" value="1000000000000000.0"/>
             <param name="y_datum_min" value="1e-15"/>
@@ -320,6 +323,9 @@
           <is_valid_xml/>
         </assert_contents>
       </output>
+      <assert_stdout>
+        <has_text_matching expression="@EXECUTABLE@ took .* \(wall\), .* \(CPU\), .* \(system\), .* \(user\)(; Peak Memory Usage: 32 MB)?."/>
+      </assert_stdout>
     </test>
     <!-- TOPP_MapAlignerTreeGuided_3 -->
     <test expect_num_outputs="2">
@@ -337,8 +343,8 @@
           <param name="type" value="b_spline"/>
           <section name="linear">
             <param name="symmetric_regression" value="false"/>
-            <param name="x_weight"/>
-            <param name="y_weight"/>
+            <param name="x_weight" value="x"/>
+            <param name="y_weight" value="y"/>
             <param name="x_datum_min" value="1e-15"/>
             <param name="x_datum_max" value="1000000000000000.0"/>
             <param name="y_datum_min" value="1e-15"/>
@@ -379,11 +385,14 @@
           <is_valid_xml/>
         </assert_contents>
       </output>
+      <assert_stdout>
+        <has_text_matching expression="@EXECUTABLE@ took .* \(wall\), .* \(CPU\), .* \(system\), .* \(user\)(; Peak Memory Usage: 32 MB)?."/>
+      </assert_stdout>
     </test>
   </tests>
   <help><![CDATA[Tree guided correction of retention time distortions between maps.
 
 
-For more information, visit http://www.openms.de/doxygen/release/2.8.0/html/TOPP_MapAlignerTreeGuided.html]]></help>
+For more information, visit https://openms.de/doxygen/release/3.1.0/html/TOPP_MapAlignerTreeGuided.html]]></help>
   <expand macro="references"/>
 </tool>