Mercurial > repos > bgruening > ml_visualization_ex
diff ml_visualization_ex.xml @ 14:9c19cf3c4ea0 draft
planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 9981e25b00de29ed881b2229a173a8c812ded9bb
author | bgruening |
---|---|
date | Wed, 09 Aug 2023 13:08:43 +0000 |
parents | 6cf6f27547cb |
children | a536d2736c2d |
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--- a/ml_visualization_ex.xml Thu Aug 11 09:29:32 2022 +0000 +++ b/ml_visualization_ex.xml Wed Aug 09 13:08:43 2023 +0000 @@ -1,4 +1,4 @@ -<tool id="ml_visualization_ex" name="Machine Learning Visualization Extension" version="@VERSION@" profile="20.05"> +<tool id="ml_visualization_ex" name="Machine Learning Visualization Extension" version="@VERSION@" profile="@PROFILE@"> <description>includes several types of plotting for machine learning</description> <macros> <import>main_macros.xml</import> @@ -21,11 +21,6 @@ --infile1 '$plotting_selection.infile1' #elif $plotting_selection.plot_type == 'keras_plot_model' --model_config '$plotting_selection.infile_model_config' - #elif $plotting_selection.plot_type == 'classification_confusion_matrix' - --true_labels '$plotting_selection.infile_true' - --predicted_labels '$plotting_selection.infile_predicted' - --plot_color '$plotting_selection.plot_color' - --title '$plotting_selection.title' #end if ]]> </command> @@ -41,7 +36,6 @@ <option value="rfecv_gridscores">Number of features vs. Recursive Feature Elimination gridscores with corss-validation</option> <option value="feature_importances">Feature Importances plot</option> <option value="keras_plot_model">keras plot model - plot configuration of a neural network model</option> - <option value="classification_confusion_matrix">Confusion matrix for classes</option> </param> <when value="learning_curve"> <param name="infile1" type="data" format="tabular" label="Select the dataset containing values for plotting learning curve." help="This dataset should be the output of tool model_validation->learning_curve." /> @@ -85,7 +79,7 @@ </param> </when> <when value="feature_importances"> - <param name="infile_estimator" type="data" format="zip" label="Select the dataset containing fitted estimator/pipeline" /> + <param name="infile_estimator" type="data" format="h5mlm" label="Select the dataset containing fitted estimator/pipeline" /> <param name="infile1" type="data" format="tabular" label="Select the dataset containing feature names" help="Make sure the headers (first row) are feature names." /> <conditional name="column_selector_options"> <expand macro="samples_column_selector_options" multiple="true" /> @@ -102,32 +96,6 @@ <param name="title" type="hidden" value="" optional="true" label="Plot title" help="Optional. If change is desired." /> <param name="plot_format" type="hidden" value="png" label="The output format and library" /> </when> - - <when value="classification_confusion_matrix"> - <param name="infile_true" type="data" format="tabular" label="Select dataset containing true labels" /> - <param name="header_true" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolfalse" checked="false" label="Does the dataset contain header:" /> - <conditional name="column_selector_options_true"> - <expand macro="samples_column_selector_options" multiple="true" column_option="selected_column_selector_option" col_name="col1" infile="infile_true" /> - </conditional> - - <param name="infile_predicted" type="data" format="tabular" label="Select dataset containing predicted labels" /> - <param name="header_predicted" type="boolean" optional="true" truevalue="booltrue" falsevalue="boolfalse" checked="false" label="Does the dataset contain header:" /> - <param name="title" type="text" value="Confusion matrix between true and predicted labels" label="Plot title" /> - <param name="plot_format" type="hidden" value="png" label="The output format and library" /> - <param name="plot_color" type="select" label="Choose plot color"> - <option value="Greys">Greys</option> - <option value="Purples">Purples</option> - <option value="Blues">Blues</option> - <option value="Greens" selected="true">Greens</option> - <option value="Oranges">Oranges</option> - <option value="Reds">Reds</option> - <option value="Summer">Summer</option> - <option value="Autumn">Autumn</option> - <option value="RdYlGn">RdYlGn</option> - <option value="Spectral">Spectral</option> - <option value="winter">winter</option> - </param> - </when> </conditional> </inputs> <outputs> @@ -146,7 +114,7 @@ </test> <test> <param name="plot_type" value="feature_importances" /> - <param name="infile_estimator" value="best_estimator_.zip" ftype="zip" /> + <param name="infile_estimator" value="best_estimator_.h5mlm" ftype="h5mlm" /> <param name="infile1" value="regression_X.tabular" ftype="tabular" /> <param name="selected_column_selector_option" value="all_columns" /> <output name="output" file="ml_vis01.html" compare="sim_size" /> @@ -172,28 +140,6 @@ <param name="infile_model_config" value="deepsear_1feature.json" ftype="json" /> <output name="output" file="ml_vis05.png" compare="sim_size" delta="20000" /> </test> - <test> - <param name="plot_type" value="classification_confusion_matrix" /> - <param name="infile_true" value="ml_confusion_true.tabular" ftype="tabular" /> - <param name="header_true" value="False" /> - <param name="selected_column_selector_option" value="all_columns" /> - <param name="infile_predicted" value="ml_confusion_predicted.tabular" ftype="tabular" /> - <param name="header_predicted" value="False" /> - <param name="title" value="Confusion matrix" /> - <param name="plot_color" value="winter" /> - <output name="output" file="ml_confusion_viz.png" compare="sim_size" /> - </test> - <test> - <param name="plot_type" value="classification_confusion_matrix" /> - <param name="infile_true" value="true_header.tabular" ftype="tabular" /> - <param name="header_true" value="True" /> - <param name="selected_column_selector_option" value="all_columns" /> - <param name="infile_predicted" value="predicted_header.tabular" ftype="tabular" /> - <param name="header_predicted" value="True" /> - <param name="title" value="Confusion matrix" /> - <param name="plot_color" value="winter" /> - <output name="output" file="ml_confusion_viz.png" compare="sim_size" /> - </test> </tests> <help> <![CDATA[