Mercurial > repos > tduigou > icfree_calibrator
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planemo upload for repository https://github.com/brsynth/icfree-ml commit 89b220357cba84350590ce79306440e78df97be5-dirty
author | tduigou |
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date | Fri, 22 Nov 2024 11:37:49 +0000 |
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children | 64294f757d70 |
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<tool id="icfree_calibrator" name="iCFree calibrator" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" license="MIT"> <description>Calculate yield based on fluorescence data and optionally apply calibration</description> <macros> <import>macros.xml</import> </macros> <expand macro="requirements"/> <command detect_errors="exit_code"><![CDATA[ cp '$initial_data_file' 'initial_data.csv' && cp '$sampling_file' 'sampling.csv' && cp '$ref_file' 'reference.csv' && python -m icfree.learner.extractor --initial_data_file 'initial_data.csv' --sampling_file 'sampling.csv' --output_file 'extractor.csv' #if str($adv.num_samples) != '' --num_samples '$adv.num_samples' #end if #if str($adv.num_replicates) != '' --num_replicates '$adv.num_replicates' #end if && python -m icfree.learner.calibrator --output 'calibrated.csv' --plot '$output_graph' --jove_plus '$jove_plus' --jove_minus '$jove_minus' --r2_limit '$adv.r2_limit' #if str($adv.num_control_points) != '' --num_control_points '$adv.num_control_points' #end if #if str($adv.num_samples) != '' --num '$adv.num_samples' #end if 'extractor.csv' 'reference.csv' && mv 'calibrated.csv' '$output_calibrated' ]]></command> <inputs> <param name="initial_data_file" type="data" format="csv" label="Initial file" help="Initial file"/> <param name="sampling_file" type="data" format="csv" label="Sampling file" help="Sampling file"/> <param name="ref_file" type="data" format="csv" label="Reference input file" help="Reference input file"/> <param argument="jove_plus" type="integer" label="Line number for Jove+ (1-based index)" help="Line number for Jove+ (1-based index)" /> <param argument="jove_minus" type="integer" label="Line number for Jove- (1-based index)" help="Line number for Jove- (1-based index)" /> <section name="adv" title="Advanced Options" expanded="false"> <param argument="num_samples" type="integer" optional="true" label="Number of samples" help="Number of samples" /> <!-- Extractor --> <param argument="num_replicates" type="integer" optional="true" label="Number of replicates" help="Number of replicates." /> <!-- Calibrator --> <param argument="r2_limit" type="float" value="0.8" label="R-squared limit for the regression" help="R-squared limit for the regression" /> <param argument="num_control_points" type="integer" optional="true" label="Number of control points to select" help="Number of control points to select" /> </section> </inputs> <outputs> <data name="output_calibrated" format="csv" label="${tool.name} - Calibrated yields" /> <data name="output_graph" format="png" label="${tool.name} - Graph" /> </outputs> <tests> <test expect_num_outputs="2"> <!-- python -m icfree.learner.extractor -initial_data_file calibrator.input.initial_data.csv -sampling_file calibrator.input.sampling.csv -output_file calibrator.extractor_output.1.csv --> <!-- python -m icfree.learner.calibrator -output calibrator.output.calibrated.1.csv -jove_plus 3 -jove_minus 2 -plot calibrator.output.1.png calibrator.output.extractor.1.csv calibrator.input.ref.csv --> <param name="initial_data_file" value="calibrator.input.initial_data.csv" /> <param name="sampling_file" value="calibrator.input.sampling.csv" /> <param name="ref_file" value="calibrator.input.ref.csv" /> <param name="jove_plus" value="3" /> <param name="jove_minus" value="2" /> <output name="output_calibrated" ftype="csv"> <assert_contents> <has_n_lines n="343" /> </assert_contents> </output> <output name="calibrator_graph" ftype="png" > <assert_contents> <has_size value="62000" delta="2000" /> </assert_contents> </output> </test> <test expect_num_outputs="2"> <!-- python -m icfree.learner.extractor -initial_data_file calibrator.input.initial_data.csv -sampling_file calibrator.input.sampling.tsv -output_file calibrator.output.extractor.2.csv -num_samples 20 -num_replicates 3 --> <!-- python -m icfree.learner.calibrator -plot calibrator.output.2.png -output calibrator.output.2.csv -jove_plus 4 -jove_minus 3 -r2_limit 0.9 -num 20 -num_control_points 4 calibrator.output.extractor.2.csv calibrator.input.ref.csv --> <param name="initial_data_file" value="calibrator.input.initial_data.csv" /> <param name="sampling_file" value="calibrator.input.sampling.csv" /> <param name="ref_file" value="calibrator.input.ref.csv" /> <param name="num_samples" value="20" /> <param name="num_replicates" value="3" /> <param name="r2_limit" value="0.9" /> <param name="num_control_points" value="4" /> <param name="jove_plus" value="4" /> <param name="jove_minus" value="3" /> <output name="output_calibrated" ftype="csv"> <assert_contents> <has_n_lines n="21" /> </assert_contents> </output> <output name="calibrator_graph" ftype="png" > <assert_contents> <has_size value="45000" delta="1000" /> </assert_contents> </output> </test> </tests> <help><![CDATA[ Calibrator ========== Calculate yield based on fluorescence data and apply calibration. ]]></help> <expand macro="creator"/> <expand macro="citation"/> </tool>