comparison ml_visualization_ex.xml @ 16:a536d2736c2d draft

planemo upload for repository https://github.com/bgruening/galaxytools/tree/master/tools/sklearn commit 3c1e6c72303cfd8a5fd014734f18402b97f8ecb5

15:6fabdcde0214

            #elif $plotting_selection.plot_type == 'feature_importances'
            --estimator '$plotting_selection.infile_estimator'
            --infile1 '$plotting_selection.infile1'
            #elif $plotting_selection.plot_type == 'keras_plot_model'
            --model_config '$plotting_selection.infile_model_config'
            #end if
        ]]>
    </command>
    <configfiles>
        <inputs name="inputs" />

                <option value="pr_curve">2-class / multpi-label Precison Recall curve</option>
                <option value="roc_curve">2-class / multi-label Receiver Operating Characteristic (ROC) curve</option>
                <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>
            </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." />
                <param name="plot_std_err" type="boolean" truevalue="booltrue" falsevalue="boolfalse" optional="true" checked="false" label="Whether to plot standard error bar?" />
                <param name="title" type="text" value="" optional="true" label="Plot title" help="Optional. If change is desired." />

            </when>
            <when value="keras_plot_model">
                <param name="infile_model_config" type="data" format="json" label="Select the JSON dataset containing configuration for a neural network model" />
                <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>
        </conditional>
    </inputs>
    <outputs>
        <data name="output" format="html" from_work_dir="output" label="${plotting_selection.plot_type} plot on ${on_string}">

        </test>
        <test>
            <param name="plot_type" value="keras_plot_model" />
            <param name="infile_model_config" value="deepsear_1feature.json" ftype="json" />
            <output name="output" file="ml_vis05.png" compare="sim_size" delta="20000" />
        </test>
    </tests>
    <help>
        <![CDATA[
**What it does**

16:a536d2736c2d

            #elif $plotting_selection.plot_type == 'feature_importances'
            --estimator '$plotting_selection.infile_estimator'
            --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>
    <configfiles>
        <inputs name="inputs" />

                <option value="pr_curve">2-class / multpi-label Precison Recall curve</option>
                <option value="roc_curve">2-class / multi-label Receiver Operating Characteristic (ROC) curve</option>
                <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." />
                <param name="plot_std_err" type="boolean" truevalue="booltrue" falsevalue="boolfalse" optional="true" checked="false" label="Whether to plot standard error bar?" />
                <param name="title" type="text" value="" optional="true" label="Plot title" help="Optional. If change is desired." />

            </when>
            <when value="keras_plot_model">
                <param name="infile_model_config" type="data" format="json" label="Select the JSON dataset containing configuration for a neural network model" />
                <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>
        <data name="output" format="html" from_work_dir="output" label="${plotting_selection.plot_type} plot on ${on_string}">

        </test>
        <test>
            <param name="plot_type" value="keras_plot_model" />
            <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[
**What it does**