Mercurial > repos > galaxyp > openms_mapaligneridentification
diff MapAlignerIdentification.xml @ 9:77b66c1c5415 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 21:29:16 +0000 |
| parents | 8434f070e939 |
| children |
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--- a/MapAlignerIdentification.xml Thu Dec 01 19:22:07 2022 +0000 +++ b/MapAlignerIdentification.xml Fri Jun 14 21:29:16 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="MapAlignerIdentification" name="MapAlignerIdentification" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="21.05"> - <description>Corrects retention time distortions between maps based on common peptide identifications.</description> + <description>Corrects retention time distortions between maps based on common peptide identifications</description> <macros> <token name="@EXECUTABLE@">MapAlignerIdentification</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 && @@ -31,11 +30,11 @@ #end if #if $design: mkdir design && - ln -s '$design' 'design/${re.sub("[^\w\-_]", "_", $design.element_identifier)}.$gxy2omsext($design.ext)' && + cp '$design' 'design/${re.sub("[^\w\-_]", "_", $design.element_identifier)}.$gxy2omsext($design.ext)' && #end if #if $reference.file: mkdir reference.file && - ln -s '$reference.file' 'reference.file/${re.sub("[^\w\-_]", "_", $reference.file.element_identifier)}.$gxy2omsext($reference.file.ext)' && + cp '$reference.file' 'reference.file/${re.sub("[^\w\-_]", "_", $reference.file.element_identifier)}.$gxy2omsext($reference.file.ext)' && #end if ## Main program call @@ -88,32 +87,32 @@ <option value="yes">Yes: process each dataset in an independent job</option> </param> <when value="no"> - <param argument="-in" type="data" format="consensusxml,featurexml,idxml,sqlite" multiple="true" optional="false" label="Input files to align (all must have the same file type)" help=" select consensusxml,featurexml,idxml,sqlite data sets(s)"/> + <param argument="-in" type="data" format="consensusxml,featurexml,idxml,sqlite" multiple="true" label="Input files to align (all must have the same file type)" help=" select consensusxml,featurexml,idxml,sqlite data sets(s)"/> </when> <when value="yes"> - <param argument="-in" type="data" format="consensusxml,featurexml,idxml,sqlite" multiple="false" optional="false" label="Input files to align (all must have the same file type)" help=" select consensusxml,featurexml,idxml,sqlite data sets(s)"/> + <param argument="-in" type="data" format="consensusxml,featurexml,idxml,sqlite" label="Input files to align (all must have the same file type)" help=" select consensusxml,featurexml,idxml,sqlite data sets(s)"/> </when> </conditional> <param argument="-design" type="data" format="tabular" optional="true" label="Input file containing the experimental design" help=" select tabular data sets(s)"/> <param argument="-store_original_rt" type="boolean" truevalue="true" falsevalue="false" checked="false" label="Store the original retention times (before transformation) as meta data in the output?" help=""/> <section name="reference" title="Options to define a reference file (use either 'file' or 'index', not both)" help="" expanded="false"> <param name="file" argument="-reference:file" type="data" format="consensusxml,featurexml,idxml,sqlite" optional="true" label="File to use as reference" help=" select consensusxml,featurexml,idxml,sqlite data sets(s)"/> - <param name="index" argument="-reference:index" type="integer" optional="true" min="0" value="0" label="Use one of the input files as reference ('1' for the first file, etc.)" help="If '0', no explicit reference is set - the algorithm will select a reference"/> + <param name="index" argument="-reference:index" type="integer" min="0" value="0" label="Use one of the input files as reference ('1' for the first file, etc.)" help="If '0', no explicit reference is set - the algorithm will select a reference"/> </section> <section name="algorithm" title="Algorithm parameters section" help="" expanded="false"> <param name="score_type" argument="-algorithm:score_type" type="text" optional="true" value="" label="Name of the score type to use for ranking and filtering (.oms input only)" help="If left empty, a score type is picked automatically"> <expand macro="list_string_san" name="score_type"/> </param> <param name="score_cutoff" argument="-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: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: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: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 > 1, the final value in seconds; if <= 1, taken as a fraction of the range of the reference RT scale"/> + <param name="min_score" argument="-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: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: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 > 1, the final value in seconds; if <= 1, taken as a fraction of the range of the reference RT scale"/> <param name="use_unassigned_peptides" argument="-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:use_feature_rt" type="boolean" truevalue="true" falsevalue="false" checked="false" 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: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=""/> </section> <section name="model" title="Options to control the modeling of retention time transformations from data" help="" expanded="false"> - <param name="type" argument="-model:type" type="select" optional="true" label="Type of model" help=""> + <param name="type" argument="-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> @@ -122,48 +121,48 @@ </param> <section name="linear" title="Parameters for 'linear' model" help="" expanded="false"> <param name="symmetric_regression" argument="-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="-model:linear:x_weight" type="select" optional="true" label="Weight x values" help=""> + <param name="x_weight" argument="-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="-model:linear:y_weight" type="select" optional="true" label="Weight y values" help=""> + <param name="y_weight" argument="-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="-model:linear:x_datum_min" type="float" optional="true" value="1e-15" label="Minimum x value" help=""/> - <param name="x_datum_max" argument="-model:linear:x_datum_max" type="float" optional="true" value="1000000000000000.0" label="Maximum x value" help=""/> - <param name="y_datum_min" argument="-model:linear:y_datum_min" type="float" optional="true" value="1e-15" label="Minimum y value" help=""/> - <param name="y_datum_max" argument="-model:linear:y_datum_max" type="float" optional="true" value="1000000000000000.0" label="Maximum y value" help=""/> + <param name="x_datum_min" argument="-model:linear:x_datum_min" type="float" value="1e-15" label="Minimum x value" help=""/> + <param name="x_datum_max" argument="-model:linear:x_datum_max" type="float" value="1000000000000000.0" label="Maximum x value" help=""/> + <param name="y_datum_min" argument="-model:linear:y_datum_min" type="float" value="1e-15" label="Minimum y value" help=""/> + <param name="y_datum_max" argument="-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="-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="-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="-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="-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="-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="-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="-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="-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="-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="-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="-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="-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="-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="-model:lowess:num_iterations" type="integer" min="0" value="3" label="Number of robustifying iterations for lowess fitting" help=""/> + <param name="delta" argument="-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="-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="-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="-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> @@ -171,13 +170,13 @@ </param> </section> <section name="interpolated" title="Parameters for 'interpolated' model" help="" expanded="false"> - <param name="interpolation_type" argument="-model:interpolated:interpolation_type" type="select" optional="true" label="Type of interpolation to apply" help=""> + <param name="interpolation_type" argument="-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="-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="-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> @@ -187,7 +186,7 @@ </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> @@ -213,7 +212,8 @@ <filter>OPTIONAL_OUTPUTS is not None and "ctd_out_FLAG" in OPTIONAL_OUTPUTS</filter> </data> </outputs> - <tests><!-- TOPP_MapAlignerIdentification_1 --> + <tests> + <!-- TOPP_MapAlignerIdentification_1 --> <test expect_num_outputs="2"> <section name="adv_opts"> <param name="force" value="false"/> @@ -241,8 +241,8 @@ <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"/> @@ -272,6 +272,9 @@ <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_MapAlignerIdentification_2 --> <test expect_num_outputs="2"> @@ -302,8 +305,8 @@ <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"/> @@ -333,6 +336,9 @@ <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_MapAlignerIdentification_3 --> <test expect_num_outputs="2"> @@ -362,8 +368,8 @@ <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"/> @@ -393,6 +399,9 @@ <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_MapAlignerIdentification_4 --> <test expect_num_outputs="2"> @@ -422,8 +431,8 @@ <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"/> @@ -453,6 +462,9 @@ <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_MapAlignerIdentification_5 --> <test expect_num_outputs="2"> @@ -482,8 +494,8 @@ <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"/> @@ -513,6 +525,9 @@ <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_MapAlignerIdentification_6 --> <test expect_num_outputs="2"> @@ -543,8 +558,8 @@ <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"/> @@ -574,6 +589,9 @@ <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_MapAlignerIdentification_7 --> <test expect_num_outputs="3"> @@ -582,7 +600,7 @@ <param name="test" value="true"/> </section> <conditional name="in_cond"> - <param name="in" value="MapAlignerIdentification_7_input1.idXML"/> + <param name="in" value="MapAlignerIdentification_7_input1_0.idXML"/> </conditional> <output_collection name="out" count="1"/> <output_collection name="trafo_out" count="1"/> @@ -605,8 +623,8 @@ <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"/> @@ -636,6 +654,9 @@ <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_MapAlignerIdentification_8 --> <test expect_num_outputs="3"> @@ -667,8 +688,8 @@ <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"/> @@ -698,11 +719,14 @@ <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[Corrects retention time distortions between maps based on common peptide identifications. -For more information, visit http://www.openms.de/doxygen/release/2.8.0/html/TOPP_MapAlignerIdentification.html]]></help> +For more information, visit https://openms.de/doxygen/release/3.1.0/html/TOPP_MapAlignerIdentification.html]]></help> <expand macro="references"/> </tool>