<tool id="scanpy_plot" name="Plot" version="@TOOL_VERSION@+galaxy@VERSION_SUFFIX@" profile="@profile@">
    <description> with scanpy</description>
    <macros>
        <import>macros.xml</import>
    </macros>
    <expand macro="bio_tools"/>
    <expand macro="requirements"/>
    <stdio>
        <regex match="... storing" source="stderr" level="warning"/>
    </stdio>
    <expand macro="version_command"/>
    <command detect_errors="exit_code"><![CDATA[
@CMD@
      ]]></command>
    <configfiles>
        <configfile name="script_file"><![CDATA[
@CMD_imports@
@CMD_read_inputs@

sc.settings.figdir = '.'

#if $method.method == 'pl.scatter'

#if $method.type.type == 'xy':
x_field='$method.type.x'
y_field='$method.type.y'

#if $method.type.log:
if x_field in adata.obs or x_field in adata.var:
    if x_field in adata.obs:
        adata.obs[f"log_{x_field}"] = np.log10(adata.obs[x_field])
    elif x_field in adata.var:
        adata.var[f"log_{x_field}"] = np.log10(adata.var[x_field])
    x_field=f"log_{x_field}"

if y_field in adata.obs or y_field in adata.var:
    if y_field in adata.obs:
        adata.obs[f"log_{y_field}"] = np.log10(adata.obs[y_field])
    elif y_field in adata.var:
        adata.var[f"log_{y_field}"] = np.log10(adata.var[y_field])
    y_field=f"log_{y_field}"
#end if
#end if

sc.pl.scatter(
    @CMD_param_plot_inputs@
    #if $method.type.type == 'xy':
    x=x_field,
    y=y_field,
    #if $method.type.color
    color='$method.type.color',
    #end if
    #if str('$method.type.layers.use_layers') == 'true'
    layers=('$method.type.layers.layer_x', '$method.type.layers.layer_y', '$method.type.layers.layer_color'),
    #end if
    #else
    basis='$method.type.basis',
    #if $method.type.color
        #set $color = ([x.strip() for x in str($method.type.color).split(',')])
    color=$color,
    #end if
    #end if
    use_raw=$method.use_raw,
    sort_order=$method.sort_order,
    @CMD_params_groups@
    @CMD_params_pl_components@
    projection='$method.plot.projection',
    legend_loc='$method.plot.legend_loc',
    #if $method.plot.palette
    palette=['$method.plot.palette'],
    #end if
    #if $method.plot.color_map
    color_map='$method.plot.color_map',
    #end if
    @CMD_param_legend_fontsize@
    legend_fontweight='$method.plot.legend_fontweight',
    @CMD_param_title@
    @CMD_param_size@
    frameon=$method.plot.frameon)

#else if $method.method == 'pl.heatmap'
@CMD_var_names_header_check@
sc.pl.heatmap(
    @CMD_param_plot_inputs@
    #if $method.gene_symbols
    gene_symbols='$method.gene_symbols',
    #end if
    @CMD_params_inputs@
    @CMD_params_plots@
    @CMD_pl_heatmap@)

#else if $method.method == 'pl.dotplot'
@CMD_var_names_header_check@
sc.pl.dotplot(
    @CMD_param_plot_inputs@
    #if $method.gene_symbols
    gene_symbols='$method.gene_symbols',
    #end if
    @CMD_params_inputs@
    @CMD_params_plots@
    @CMD_pl_dotplot@)

#else if $method.method == 'pl.violin'
sc.pl.violin(
    @CMD_param_plot_inputs@
    #if $method.key_variables.type == "var_names"
        #set $key_list = adata.var_names
    #else if $method.key_variables.type == "obs"
        #set $key_list = adata.obs.select_dtypes(exclude=['category']).columns
    #else if $method.key_variables.type == "custom"
        #set $key_list=([x.strip() for x in str($method.key_variables.keys).split(',')])
    #end if
    keys=$key_list,
    #if $method.groupby
    groupby='$method.groupby',
    #end if
    log=$method.log,
    use_raw=$method.use_raw,
    @CMD_conditional_stripplot@
    multi_panel=$method.violin_plot.multi_panel.multi_panel,
    #if $method.violin_plot.multi_panel.multi_panel == "True" and str($method.violin_plot.multi_panel.width) != '' and str($method.violin_plot.multi_panel.height) != ''
    figsize=($method.violin_plot.multi_panel.width, $method.violin_plot.multi_panel.height),
    #end if
    scale='$method.violin_plot.scale',
    #if $method.xlabel
    xlabel='$method.xlabel',
    #end if
    #if str($method.rotation) != ''
    rotation=$method.rotation,
    #end if
    @CMD_params_seaborn_violinplot@)

#else if $method.method == 'pl.stacked_violin'
@CMD_var_names_header_check@
sc.pl.stacked_violin(
    @CMD_param_plot_inputs@
    #if $method.gene_symbols
    gene_symbols='$method.gene_symbols',
    #end if
    @CMD_params_inputs@
    @CMD_params_plots@
    @CMD_pl_stacked_violin@)

#else if $method.method == 'pl.matrixplot'
@CMD_var_names_header_check@
sc.pl.matrixplot(
    @CMD_param_plot_inputs@
    #if $method.gene_symbols
    gene_symbols='$method.gene_symbols',
    #end if
    @CMD_params_inputs@
    @CMD_params_plots@
    @CMD_pl_matrixplot@)

#else if $method.method == 'pl.clustermap'
sc.pl.clustermap(
    #if str($method.use_raw) == 'True'
    adata=adata.X,
    #else
    adata=adata,
    #end if
    show=False,
    #if $method.obs_keys
    obs_keys='$method.obs_keys',
    #end if
    use_raw=$method.use_raw,
    method='$method.seaborn_clustermap.method',
    metric='$method.seaborn_clustermap.metric',
    #if str($method.seaborn_clustermap.z_score) != 'None'
    z_score=$method.seaborn_clustermap.z_score,
    #end if
    #if str($method.seaborn_clustermap.standard_scale) != 'None'
    standard_scale=$method.seaborn_clustermap.standard_scale,
    #end if
    col_cluster=$method.seaborn_clustermap.col_cluster,
    row_cluster=$method.seaborn_clustermap.row_cluster).savefig(fname="output.$format")

#else if $method.method == 'pl.highest_expr_genes'
sc.pl.highest_expr_genes(
    @CMD_param_plot_inputs@
    n_top=$method.n_top,
    #if $method.gene_symbols
    gene_symbols='$method.gene_symbols',
    #end if
    #if $method.setseaborn_boxplot.color
    color='$method.setseaborn_boxplot.color',
    #end if
    #if $method.setseaborn_boxplot.palette
    palette='$method.setseaborn_boxplot.palette',
    #end if
    saturation=$method.setseaborn_boxplot.saturation)

#else if $method.method == 'pl.highly_variable_genes'
sc.pl.highly_variable_genes(
    adata_or_result=adata,
    log=$method.log,
    save='.$format',
    show=False,
    highly_variable_genes=$method.highly_variable_genes)

#else if $method.method == 'pl.pca'
sc.pl.pca(
    @CMD_param_plot_inputs@
    @CMD_param_color@
    use_raw=$method.use_raw,
    sort_order=$method.sort_order,
    @CMD_params_groups@
    @CMD_params_pl_components@
    @CMD_pl_attribute_section@
    @CMD_params_matplotlib_pyplot_scatter@)

#else if $method.method == 'pl.pca_loadings'
sc.pl.pca_loadings(
    @CMD_param_plot_inputs@
    #set $components = ([int(x.strip()) for x in str($method.components).split(',')])
    components=$components)

#else if $method.method == 'pl.pca_variance_ratio'
sc.pl.pca_variance_ratio(
    @CMD_param_plot_inputs@
    n_pcs=$method.n_pcs,
    log=$method.log)

#else if $method.method == 'pl.pca_overview'
sc.pl.pca_overview(
    @CMD_param_plot_inputs@
    @CMD_param_color@
    use_raw=$method.use_raw,
    sort_order=$method.sort_order,
    @CMD_params_groups@
    @CMD_params_pl_components@
    @CMD_pl_attribute_section@
    @CMD_params_matplotlib_pyplot_scatter@)

#else if $method.method == 'pl.tsne'
sc.pl.tsne(
    @CMD_param_plot_inputs@
    @CMD_param_color@
    use_raw=$method.use_raw,
    @CMD_pl_edges@
    arrows=$method.arrows,
    sort_order=$method.sort_order,
    @CMD_params_groups@
    @CMD_params_pl_components@
    @CMD_pl_attribute_section@
    @CMD_params_matplotlib_pyplot_scatter@)

#else if $method.method == 'pl.umap'
sc.pl.umap(
    @CMD_param_plot_inputs@
    @CMD_param_color@
    use_raw=$method.use_raw,
    @CMD_pl_edges@
    arrows=$method.arrows,
    sort_order=$method.sort_order,
    @CMD_params_groups@
    @CMD_params_pl_components@
    @CMD_pl_attribute_section@
    @CMD_params_matplotlib_pyplot_scatter@)

#else if $method.method == 'pl.diffmap'
sc.pl.diffmap(
    @CMD_param_plot_inputs@
    @CMD_param_color@
    use_raw=$method.use_raw,
    sort_order=$method.sort_order,
    @CMD_params_groups@
    @CMD_params_pl_components@
    @CMD_pl_attribute_section@
    @CMD_params_matplotlib_pyplot_scatter@)

#else if $method.method == 'pl.draw_graph'
sc.pl.draw_graph(
    @CMD_param_plot_inputs@
    @CMD_param_color@
    #if $method.gene_symbols
    gene_symbols='$method.gene_symbols',
    #end if
    use_raw=$method.use_raw,
    layout='$method.layout',
    edges=$method.edges.edges,
    #if str($method.edges.edges) == 'True'
    edges_width=$method.edges.edges_width,
    edges_color='$method.edges.edges_color',
    #end if
    arrows=$method.arrows,
    sort_order=$method.sort_order,
    @CMD_params_groups@
    @CMD_params_pl_components@
    @CMD_pl_attribute_section@
    @CMD_params_matplotlib_pyplot_scatter@)

#else if $method.method == 'pl.embedding_density'
sc.pl.embedding_density(
    @CMD_param_plot_inputs@
    basis='$method.basis',
    #if $method.key
    key='$method.key',
    #end if
    #if $method.groupby
    groupby='$method.groupby',
    #end if
    #if $method.group
    #set $group = ([x.strip() for x in str($method.group).split(',')])
    group=$group,
    #end if
    #if $method.color_map
    color_map='$method.color_map',
    #end if
    bg_dotsize=$method.bg_dotsize,
    fg_dotsize=$method.fg_dotsize,
    ncols=$method.ncols,
    wspace=$method.wspace,
    hspace=$method.hspace)

#else if $method.method == 'pl.dpt_groups_pseudotime'
sc.pl.dpt_groups_pseudotime(
    @CMD_param_plot_inputs@
    #if $method.color_map
    color_map='$method.color_map'
    #end if
    )

#else if $method.method == 'pl.dpt_timeseries'
sc.pl.dpt_timeseries(
    @CMD_param_plot_inputs@
    #if $method.heatmap.as_heatmap == "True"
        #if $method.heatmap.color_map
    color_map='$method.heatmap.color_map',
        #end if
    #end if
    as_heatmap=$method.heatmap.as_heatmap)

#else if $method.method == 'pl.paga'
sc.pl.paga(
    @CMD_param_plot_inputs@
    @CMD_params_pl_paga@)

#else if $method.method == 'pl.paga_compare'
sc.pl.paga_compare(
    @CMD_param_plot_inputs@
    @CMD_params_pl_paga@)

#else if $method.method == 'pl.paga_path'
sc.pl.paga_path(
    @CMD_param_plot_inputs@
    #set $nodes = ([int(x.strip()) for x in str($method.nodes).split(',')])
    nodes=$nodes,
    #set $keys=([x.strip() for x in str($method.keys).split(',')])
    keys=$keys,
    use_raw=$method.use_raw,
    #if $method.annotations
        #set $annotations=([x.strip() for x in str($method.annotations).split(',')])
    annotations=$annotations,
    #end if
    #if $method.color_map
    color_map='$method.color_map',
    #end if
    n_avg=$method.n_avg,
    #if $method.annotations
    groups_key='$method.groups_key',
    #end if
    as_heatmap=$method.as_heatmap,
    show_node_names=$method.show_node_names,
    show_colorbar=$method.show_colorbar,
    show_yticks=$method.show_yticks,
    normalize_to_zero_one=$method.normalize_to_zero_one)

#else if $method.method == 'pl.rank_genes_groups'
sc.pl.rank_genes_groups(
    @CMD_param_plot_inputs@
    @CMD_params_groups@
    n_genes=$method.n_genes,
    #if $method.gene_symbols
    gene_symbols='$method.gene_symbols',
    #end if
    fontsize=$method.fontsize,
    ncols=$method.ncols,
    sharey=$method.sharey)

#else if $method.method == 'pl.rank_genes_groups_violin'
sc.pl.rank_genes_groups_violin(
    @CMD_param_plot_inputs@
    @CMD_params_groups@
    #if $method.genes.select == 'n_genes'
    n_genes=$method.genes.n_genes,
    #else
        #set $gene_names = ([x.strip() for x in str($method.genes.gene_names).split(',')])
    gene_names=$gene_names,
    #end if
    #if $method.gene_symbols
    gene_symbols='$method.gene_symbols',
    #end if
    use_raw=$method.use_raw,
    split=$method.split,
    strip=$method.violin_plot.stripplot.stripplot,
    #if $method.violin_plot.stripplot.stripplot == "True"
    jitter=$method.violin_plot.stripplot.jitter.jitter,
        #if $method.violin_plot.stripplot.jitter.jitter == "True"
    size=$method.violin_plot.stripplot.jitter.size,
        #end if
    #end if
    scale='$method.violin_plot.scale')

#else if $method.method == 'pl.rank_genes_groups_dotplot'

@CMD_var_names_header_check@

sc.pl.rank_genes_groups_dotplot(
    @CMD_param_plot_inputs@
    #if $method.var_names.type == 'custom'
    #set $var_names = ([x.strip() for x in str($method.var_names.var_names).split(',')])
    var_names=$var_names,
    #else if $method.var_names.type == 'customfile'
    var_names={key: [v for v in list(value.values()) if pd.notna(v)] for key, value in pd.read_csv('$var_names', sep='\t', index_col=0, header=header).to_dict(orient='index').items()},
    #else
    n_genes=$method.n_genes,
    #end if
    #if $method.groupby != ''
    groupby='$method.groupby',
    #end if
    num_categories=$method.num_categories,
    #if $method.key != ''
    key='$method.key',
    #end if
    #if $method.gene_symbols
    gene_symbols='$method.gene_symbols',
    #end if
    @CMD_params_plots@
    @CMD_pl_dotplot@)

#else if $method.method == 'pl.rank_genes_groups_heatmap'
sc.pl.rank_genes_groups_heatmap(
    @CMD_param_plot_inputs@
    @CMD_pl_rank_genes_groups_ext@
    @CMD_params_plots@
    #if $method.gene_symbols
    gene_symbols='$method.gene_symbols',
    #end if
    @CMD_pl_heatmap@)

#else if $method.method == 'pl.rank_genes_groups_matrixplot'
sc.pl.rank_genes_groups_matrixplot(
    @CMD_param_plot_inputs@
    @CMD_pl_rank_genes_groups_ext@
    @CMD_params_plots@
    #if $method.gene_symbols
    gene_symbols='$method.gene_symbols',
    #end if
    @CMD_pl_matrixplot@)

#else if $method.method == 'pl.rank_genes_groups_stacked_violin'
sc.pl.rank_genes_groups_stacked_violin(
    @CMD_param_plot_inputs@
    @CMD_pl_rank_genes_groups_ext@
    @CMD_params_plots@
    #if $method.gene_symbols
    gene_symbols='$method.gene_symbols',
    #end if
    @CMD_pl_stacked_violin@)

#end if
]]></configfile>
    </configfiles>
    <inputs>
        <expand macro="inputs_anndata"/>
        <expand macro="param_plot_format"/>
        <conditional name="method">
            <param argument="method" type="select" label="Method used for plotting">
                <option value="pl.scatter">Generic: Scatter plot along observations or variables axes, using 'pl.scatter'</option>
                <option value="pl.heatmap">Generic: Heatmap of the expression values of set of genes, using 'pl.heatmap'</option>
                <option value="pl.dotplot">Generic: Makes a dot plot of the expression values, using 'pl.dotplot'</option>
                <option value="pl.violin">Generic: Violin plot, using 'pl.violin'</option>
                <option value="pl.stacked_violin">Generic: Stacked violin plots, using 'pl.stacked_violin'</option>
                <option value="pl.matrixplot">Generic: Heatmap of the mean expression values per cluster, using 'pl.matrixplot'</option>
                <option value="pl.clustermap">Generic: Hierarchically-clustered heatmap, using 'pl.clustermap'</option>
                <option value="pl.highest_expr_genes">Preprocessing: Plot the fraction of counts assigned to each gene over all cells, using 'pl.highest_expr_genes'</option>
                <!--<option value="pl.filter_genes_dispersion">Preprocessing: Plot dispersions versus means for genes, using 'pl.filter_genes_dispersion'</option>-->
                <option value="pl.highly_variable_genes">Preprocessing: Plot dispersions versus means for genes, using 'pl.highly_variable_genes'</option>
                <option value="pl.pca">PCA: Scatter plot in PCA coordinates, using 'pl.pca'</option>
                <option value="pl.pca_loadings">PCA: Rank genes according to contributions to PCs, using 'pl.pca_loadings'</option>
                <option value="pl.pca_variance_ratio">PCA: Scatter plot in PCA coordinates, using 'pl.pca_variance_ratio'</option>
                <option value="pl.pca_overview">PCA: Plot PCA results, using 'pl.pca_overview'</option>
                <option value="pl.tsne">Embeddings: Scatter plot in tSNE basis, using 'pl.tsne'</option>
                <option value="pl.umap">Embeddings: Scatter plot in UMAP basis, using 'pl.umap'</option>
                <option value="pl.diffmap">Embeddings: Scatter plot in Diffusion Map basis, using 'pl.diffmap'</option>
                <option value="pl.draw_graph">Embeddings: Scatter plot in graph-drawing basis, using 'pl.draw_graph'</option>
                <option value="pl.embedding_density">Embeddings: Plot the density of cells in an embedding (per condition), using 'pl.embedding_density'</option>
                <option value="pl.dpt_groups_pseudotime">Branching trajectories and pseudotime, clustering: Plot groups and pseudotime, using 'pl.dpt_groups_pseudotime'</option>
                <option value="pl.dpt_timeseries">Branching trajectories and pseudotime, clustering: Heatmap of pseudotime series, using 'pl.dpt_timeseries'</option>
                <option value="pl.paga">Branching trajectories and pseudotime, clustering: Plot the abstracted graph through thresholding low-connectivity edges, using 'pl.paga'</option>
                <option value="pl.paga_compare">Branching trajectories and pseudotime, clustering: Scatter and PAGA graph side-by-side, using 'pl.paga_compare'</option>
                <option value="pl.paga_path">Branching trajectories and pseudotime, clustering: Gene expression and annotation changes along paths, using 'pl.paga_path'</option>
                <option value="pl.rank_genes_groups">Marker genes: Plot ranking of genes using dotplot plot, using 'pl.rank_genes_groups'</option>
                <option value="pl.rank_genes_groups_violin">Marker genes: Plot ranking of genes as violin plot, using 'pl.rank_genes_groups_violin'</option>
                <option value="pl.rank_genes_groups_dotplot">Marker genes: Plot ranking of genes as dotplot plot, using 'pl.rank_genes_groups_dotplot'</option>
                <option value="pl.rank_genes_groups_heatmap">Marker genes: Plot ranking of genes as heatmap plot, using 'pl.rank_genes_groups_heatmap'</option>
                <option value="pl.rank_genes_groups_matrixplot">Marker genes: Plot ranking of genes as matrixplot plot, using 'pl.rank_genes_groups_matrixplot'</option>
                <option value="pl.rank_genes_groups_stacked_violin">Marker genes: Plot ranking of genes as stacked violin plot, using 'pl.rank_genes_groups_stacked_violin'</option>
            </param>
            <when value="pl.scatter">
                <conditional name="type">
                    <param name="type" type="select" label="Plotting tool that computed coordinates" help="">
                        <option value="xy">Using coordinates</option>
                        <option value="basis">Using tool that computes coordinates</option>
                    </param>
                    <when value="xy">
                        <param argument="x" type="text" value="" label="x coordinate" help="Index or key from either '.obs' or '.var'">
                            <expand macro="sanitize_query" />
                        </param>
                        <param argument="y" type="text" value="" label="y coordinate" help="Index or key from either '.obs' or '.var'">
                            <expand macro="sanitize_query" />
                        </param>
                        <expand macro="param_log"/>
                        <param argument="color" type="text" value="" label="Color by" help="Color points by single variable in `.obs` or `.var`">
                            <expand macro="sanitize_query" />
                        </param>
                        <conditional name="layers">
                            <param argument="use_layers" type="select" label="Use the layers attribute?">
                                <option value="true">Yes</option>
                                <option value="false" selected="true">No</option>
                            </param>
                            <when value="true">
                                <param argument="layer_x" type="text" value="" optional="true" label="Layers for x coordinate" help="Use the 'layers' attribute of 'adata' if present">
                                    <expand macro="sanitize_query" />
                                </param>
                                <param argument="layer_y" type="text" value="" optional="true" label="Layers for y coordinate" help="Use the 'layers' attribute of 'adata' if present">
                                    <expand macro="sanitize_query" />
                                </param>
                                <param argument="layer_color" type="text" value="" optional="true" label="Layers for color" help="Use the 'layers' attribute of 'adata' if present">
                                    <expand macro="sanitize_query" />
                                </param>
                            </when>
                            <when value="false"/>
                        </conditional>
                    </when>
                    <when value="basis">
                        <param argument="basis" type="select" label="Plotting tool that computes coordinates" help="">
                            <option value="pca">pca (need to run on 'tl.pca' output)</option>
                            <option value="tsne">tsne (need to run on 'tl.tsne' output)</option>
                            <option value="umap">umap (need to run on 'tl.umap' output)</option>
                            <option value="diffmap">diffmap (need to run on 'tl.diffmap' output)</option>
                            <option value="draw_graph_fr">draw_graph_fr (need to run on 'tl.draw_graph' output)</option>
                        </param>
                        <expand macro="param_color"/>
                    </when>
                </conditional>
                <expand macro="param_use_raw"/>
                <param argument="sort_order" type="boolean" truevalue="True" falsevalue="False" checked="true" label="Plot data points with higher values on top of others?" help="For continuous annotations used as color parameter"/>
                <expand macro="param_groups"/>
                <section name="plot" title="Plot attributes">
                    <expand macro="pl_components"/>
                    <expand macro="param_projection"/>
                    <expand macro="param_legend_loc"/>
                    <expand macro="param_legend_fontsize"/>
                    <expand macro="param_legend_fontweight"/>
                    <expand macro="param_color_map"/>
                    <expand macro="param_palette"/>
                    <expand macro="param_frameon"/>
                    <expand macro="param_size"/>
                    <expand macro="param_title"/>
                </section>
            </when>
            <when value="pl.heatmap">
                <expand macro="params_inputs"/>
                <expand macro="gene_symbols"/>
                <expand macro="params_plots"/>
                <expand macro="pl_heatmap"/>
            </when>
            <when value="pl.dotplot">
                <expand macro="params_inputs"/>
                <expand macro="gene_symbols"/>
                <expand macro="params_plots"/>
                <expand macro="pl_dotplot"/>
            </when>
            <when value="pl.violin">
                <conditional name="key_variables">
                    <param name="type" type="select" label="Keys for accessing variables">
                        <option value="var_names">All variables in '.var_names'</option>
                        <option value="obs">All fields in '.obs'</option>
                        <option value="custom">Subset of variables in 'adata.var_names' or fields of '.obs'</option>
                    </param>
                    <when value="var_names"/>
                    <when value="obs"/>
                    <when value="custom">
                        <param argument="keys" type="text" value="" label="Keys for accessing variables" help="One or a list of comma-separated index or key from '.var_names' or fields of '.obs'">
                            <expand macro="sanitize_query" />
                        </param>
                    </when>
                </conditional>
                <expand macro="param_groupby"/>
                <expand macro="param_log"/>
                <expand macro="param_use_raw"/>
                <section name="violin_plot" title="Violin plot attributes">
                    <expand macro="conditional_stripplot"/>
                    <conditional name="multi_panel">
                        <param argument="multi_panel" type="select" label="Display keys in multiple panels" help="Also when 'groupby is not provided">
                            <option value="True">Yes</option>
                            <option value="False" selected="true">No</option>
                        </param>
                        <when value="True">
                            <param argument="width" type="integer" min="0" value="" optional="true" label="Width of the figure" help=""/>
                            <param argument="height" type="integer" min="0" value="" optional="true" label="Height of the figure" help=""/>
                        </when>
                        <when value="False"/>
                    </conditional>
                    <expand macro="param_scale"/>
                </section>
                <param argument="xlabel" type="text" value="" optional="true" label="Label of the x axis" help="Defaults to 'groupby' if 'rotation' is 'None',    otherwise, no label is shown.">
                    <expand macro="sanitize_query" />
                </param>
                <param argument="rotation" type="float" value="" optional="true" label="Rotation of xtick labels" help=""/>
                <expand macro="seaborn_violinplot"/>
            </when>
            <when value="pl.stacked_violin">
                <expand macro="params_inputs"/>
                <expand macro="gene_symbols"/>
                <expand macro="params_plots"/>
                <expand macro="pl_stacked_violin"/>
            </when>
            <when value="pl.matrixplot">
                <expand macro="params_inputs"/>
                <expand macro="gene_symbols"/>
                <expand macro="params_plots"/>
                <expand macro="pl_matrixplot"/>
            </when>
            <when value="pl.clustermap">
                <param argument="obs_keys" type="text" value="" optional="true" label="Categorical annotation to plot with a different color map" help="Currently, only a single key is supported.">
                    <expand macro="sanitize_query" />
                </param>
                <expand macro="param_use_raw"/>
                <section name="seaborn_clustermap" title="Parameters for seaborn.clustermap">
                    <param name="method" type="select" label="Linkage method to use for calculating clusters" help="More details in https://docs.scipy.org/doc/scipy/reference/generated/scipy.cluster.hierarchy.linkage.html">
                        <option value="single">single: Nearest Point Algorithm</option>
                        <option value="complete">complete: Farthest Point Algorithm or Voor Hees Algorithm</option>
                        <option value="average">average: UPGMA algorithm</option>
                        <option value="weighted">weighted: WPGMA algorithm</option>
                        <option value="centroid">centroid: UPGMC algorithm</option>
                        <option value="median">median: WPGMC algorithm</option>
                        <option value="ward">ward: incremental algorithm</option>
                    </param>
                    <param name="metric" type="select" label="Distance metric to use for the data" help="See scipy.spatial.distance.pdist documentation for more options https://docs.scipy.org/doc/scipy/reference/generated/scipy.spatial.distance.pdist.html">
                        <expand macro="distance_metric_options"/>
                    </param>
                    <param name="z_score" type="select" label="Calculate z-scores for the rows or the columns?" help="Z scores are: z = (x - mean)/std, so values in each row (column) will get the mean of the row (column) subtracted, then divided by the standard deviation of the row (column). This ensures that each row (column) has mean of 0 and variance of 1.">
                        <option value="None">No Z-score</option>
                        <option value="0">Rows</option>
                        <option value="1">Columns</option>
                    </param>
                    <param name="standard_scale" type="select" label="Standardize a dimension?" help="It means for each row or column, subtract the minimum and divide each by its maximum.">
                        <option value="None">No standardization</option>
                        <option value="0">Rows</option>
                        <option value="1">Columns</option>
                    </param>
                    <param name="col_cluster" type="boolean" truevalue="True" falsevalue="False" checked="false" label="Cluster the columns?" help=""/>
                    <param name="row_cluster" type="boolean" truevalue="True" falsevalue="False" checked="false" label="Cluster the rows?" help=""/>
                </section>
            </when>
            <when value="pl.highly_variable_genes">
                <expand macro="param_log"/>
                <param argument="highly_variable_genes" type="boolean" truevalue="True" falsevalue="False" checked="true" label="Plot highly variable genes or gene subset?"/>
            </when>
            <when value="pl.highest_expr_genes">
                <param argument="n_top" type="integer" min="0" value="30" label="Number of top genes" help=""/>
                <param argument="gene_symbols" type="text" optional="true" label="Key for field in '.var' that stores gene symbols" help="Fill it if you do not want to use '.var_names'.">
                    <expand macro="sanitize_query" />
                </param>
                <section name="setseaborn_boxplot" title="Plot settings" expanded="false">
                    <param argument="color" type="text" value="" optional="true" label="Color for all of the elements, or seed for a gradient palette" help="">
                        <expand macro="sanitize_query" />
                    </param>
                    <param argument="palette" type="select" optional="true" label="Colors to use for the different levels of the hue variable" help="See https://seaborn.pydata.org/tutorial/color_palettes.html for more details.">
                        <expand macro="seaborn_color_palette_options"/>
                    </param>
                    <param argument="saturation" type="float" value="1" label="Proportion of the original saturation to draw colors at" help="Large patches often look better with slightly desaturated colors, but set this to 1 if you want the plot colors to perfectly match the input color spec."/>
                </section>
            </when>
            <when value="pl.pca">
                <expand macro="param_color"/>
                <expand macro="param_use_raw"/>
                <expand macro="param_sort_order"/>
                <expand macro="param_groups"/>
                <expand macro="pl_attribute_section"/>
                <expand macro="section_matplotlib_pyplot_scatter"/>
            </when>
            <when value="pl.pca_loadings">
                <param argument="components" type="text" value="1,2,3" label="List of comma-separated components" help="1, 2, 3 means first, second and third principal components">
                    <expand macro="sanitize_query" />
                </param>
            </when>
            <when value="pl.pca_variance_ratio">
                <param argument="n_pcs" type="integer" min="0" value="30" label="Number of PCs to show" help=""/>
                <expand macro="param_log"/>
            </when>
            <when value="pl.pca_overview">
                <expand macro="param_color"/>
                <expand macro="param_use_raw"/>
                <expand macro="param_sort_order"/>
                <expand macro="param_groups"/>
                <expand macro="pl_attribute_section"/>
                <expand macro="section_matplotlib_pyplot_scatter"/>
            </when>
            <when value="pl.tsne">
                <expand macro="param_color"/>
                <expand macro="param_use_raw"/>
                <expand macro="pl_edges"/>
                <expand macro="param_arrows"/>
                <expand macro="param_sort_order"/>
                <expand macro="param_groups"/>
                <expand macro="pl_attribute_section"/>
                <expand macro="section_matplotlib_pyplot_scatter"/>
            </when>
            <when value="pl.umap">
                <expand macro="param_color"/>
                <expand macro="param_use_raw"/>
                <expand macro="pl_edges"/>
                <expand macro="param_arrows"/>
                <expand macro="param_sort_order"/>
                <expand macro="param_groups"/>
                <expand macro="pl_attribute_section"/>
                <expand macro="section_matplotlib_pyplot_scatter"/>
            </when>
            <when value="pl.diffmap">
                <expand macro="param_color"/>
                <expand macro="param_use_raw"/>
                <expand macro="param_sort_order"/>
                <expand macro="param_groups"/>
                <expand macro="pl_attribute_section"/>
                <expand macro="section_matplotlib_pyplot_scatter"/>
            </when>
            <when value="pl.draw_graph">
                <expand macro="param_color"/>
                <expand macro="gene_symbols"/>
                <expand macro="param_use_raw"/>
                <param argument="layout" type="select" optional="false" label="Plotting layout" help="">
                    <expand macro="options_layout"/>
                </param>
                <expand macro="pl_edges"/>
                <expand macro="param_arrows"/>
                <expand macro="param_sort_order"/>
                <expand macro="param_groups"/>
                <expand macro="pl_attribute_section"/>
                <expand macro="section_matplotlib_pyplot_scatter"/>
            </when>
            <when value="pl.embedding_density">
                <param argument="basis" type="text" value="umap" label="The embedding over which the density was calculated." help="This embedded representation should be found in adata.obsm['X_[basis]']">
                    <expand macro="sanitize_query" />
                </param>
                <param argument="key" type="text" optional="true" value="" label="Name of the .obs covariate that contains the density estimates" help="Alternatively, pass _groupby_.">
                    <expand macro="sanitize_query" />
                </param>
                <param argument="groupby" type="text" optional="true" value="" label="Name of the condition used in tl.embedding_density" help="Alternatively, pass _key_.">
                    <expand macro="sanitize_query" />
                </param>
                <param argument="group" type="text" optional="all" value="" label="The category in the categorical observation annotation to be plotted" 
                    help="For example, 'G1' in the cell cycle 'phase' covariate. If multiple categories want to be plotted use a comma separated list">
                    <expand macro="sanitize_query" />
                </param>
                <expand macro="param_color_map"/>
                <param argument="bg_dotsize" type="integer" min="0" value="80" label="Dot size for background data points not in the group"/>
                <param argument="fg_dotsize" type="integer" min="0" value="180" label="Dot size for foreground data points in the group"/>
                <expand macro="param_ncols"/>
                <expand macro="param_wspace"/>
                <expand macro="param_hspace"/>
            </when>
            <when value="pl.dpt_groups_pseudotime">
                <expand macro="param_color_map"/>
            </when>
            <when value="pl.dpt_timeseries">
                <conditional name="heatmap">
                    <param argument="as_heatmap" type="select" label="Plot the timeseries as heatmap?" help="">
                        <option value="True">Yes</option>
                        <option value="False">No</option>
                    </param>
                    <when value="True">
                        <expand macro="param_color_map"/>
                    </when>
                    <when value="False" />
                </conditional>
            </when>
            <when value="pl.paga">
                <expand macro="inputs_paga"/>
            </when>
            <when value="pl.paga_compare">
                <expand macro="inputs_paga"/>
            </when>
            <when value="pl.paga_path">
                <param argument="nodes" type="text" value="" label="A path through nodes of the abstracted graph"
                       help="Each node is represented by its indice (within .categories) for the groups that have been used to run PAGA. Comma-separated">
                    <expand macro="sanitize_query" />
                </param>
                <param argument="keys" type="text" value="" label="Keys for accessing variables" help="One or a list of comma-separated index or key from '.var_names' or fields of '.obs'">
                    <expand macro="sanitize_query" />
                </param>
                <expand macro="param_use_raw"/>
                <param argument="annotations" type="text" value="" optional="true" label="Key to plot" help="Keys for obs, comma-separated">
                    <expand macro="sanitize_query" />
                </param>
                <expand macro="param_color_map"/>
                <param argument="n_avg" type="integer" value="1" label="Number of data points to include in computation of running average"/>
                <param argument="groups_key" type="text" value="" optional="true" label="Key of the grouping used to run PAGA" help="If not set, use uns/page/groups">
                    <expand macro="sanitize_query" />
                </param>
                <param argument="as_heatmap" type="boolean" truevalue="True" falsevalue="False" checked="true" label="Plot the timeseries as heatmap?" help="If not, annotations have no effect."/>
                <param argument="show_node_names" type="boolean" truevalue="True" falsevalue="False" checked="true" label="Plot the node names on the nodes bar?"/>
                <param argument="show_colorbar" type="boolean" truevalue="True" falsevalue="False" checked="true" label="Show the colorbar?"/>
                <param argument="show_yticks" type="boolean" truevalue="True" falsevalue="False" checked="true" label="Show the y ticks?"/>
                <param argument="normalize_to_zero_one" type="boolean" truevalue="True" falsevalue="False" checked="true" label="Shift and scale the running average to [0, 1] per gene?"/>
            </when>
            <when value="pl.rank_genes_groups">
                <expand macro="param_groups"/>
                <expand macro="param_n_genes"/>
                <expand macro="gene_symbols"/>
                <param argument="fontsize" type="integer" min="0" value="8" label="Font size for gene names"/>
                <expand macro="param_ncols"/>
                <param argument="sharey" type="boolean" truevalue="True" falsevalue="False" checked="true" label="Should the y-axis of each panels be shared?" help="If not, each panel has its own y-axis range"/>
            </when>
            <when value="pl.rank_genes_groups_violin">
                <expand macro="param_groups"/>
                <conditional name="genes">
                    <param argument="select" type="select" label="Which genes to plot?" help="">
                        <option value="n_genes">A number of genes</option>
                        <option value="gene_names">A custom list of genes</option>
                    </param>
                    <when value="n_genes">
                        <expand macro="param_n_genes"/>
                    </when>
                    <when value="gene_names">
                        <param argument="gene_names" type="text" value="" label="List of genes to plot" help="A list of comma-separated names">
                            <expand macro="sanitize_query" />
                        </param>
                    </when>
                </conditional>
                <expand macro="gene_symbols"/>
                <expand macro="param_use_raw"/>
                <param argument="split" type="boolean" truevalue="True" falsevalue="False" checked="true" label="Split the violins?"/>
                <section name="violin_plot" title="Violin plot attributes">
                    <expand macro="conditional_stripplot"/>
                    <expand macro="param_scale"/>
                </section>
            </when>
            <when value="pl.rank_genes_groups_dotplot">
                <expand macro="params_inputs"/>
                <expand macro="pl_rank_genes_groups_ext"/>
                <expand macro="params_plots"/>
                <expand macro="gene_symbols"/>
                <expand macro="pl_dotplot"/>
            </when>
            <when value="pl.rank_genes_groups_heatmap">
                <expand macro="pl_rank_genes_groups_ext"/>
                <expand macro="params_plots"/>
                <expand macro="gene_symbols"/>
                <expand macro="pl_heatmap"/>
            </when>
            <when value="pl.rank_genes_groups_matrixplot">
                <expand macro="pl_rank_genes_groups_ext"/>
                <expand macro="params_plots"/>
                <expand macro="gene_symbols"/>
                <expand macro="pl_matrixplot"/>
            </when>
            <when value="pl.rank_genes_groups_stacked_violin">
                <expand macro="pl_rank_genes_groups_ext"/>
                <expand macro="params_plots"/>
                <expand macro="gene_symbols"/>
                <expand macro="pl_stacked_violin"/>
            </when>
        </conditional>
        <expand macro="inputs_common_advanced"/>
    </inputs>
    <outputs>
        <data name="out_png" format="png" from_work_dir="*.png" label="PNG plot from ${tool.name} (${method.method}) on ${on_string}">
            <filter>format == 'png' and method['method'] != 'pl.rank_genes_groups_violin'</filter>
        </data>
        <collection name="collection_png" type="list" label="PNG plots from ${tool.name} (${method.method}) on ${on_string}">
            <discover_datasets pattern="rank_genes_groups_(?P&lt;designation&gt;.*).png" format="png"/>
            <filter>format == 'png' and method['method'] == 'pl.rank_genes_groups_violin'</filter>
        </collection>
        <data name="out_pdf" format="pdf" from_work_dir="*.pdf" label="PDF plot from ${tool.name} (${method.method}) on ${on_string}">
            <filter>format == 'pdf' and method['method'] != 'pl.rank_genes_groups_violin'</filter>
        </data>
        <collection name="collection_pdf" type="list" label="PDF plots from ${tool.name} (${method.method}) on ${on_string}">
            <discover_datasets pattern="rank_genes_groups_(?P&lt;designation&gt;.*).pdf" format="pdf"/>
            <filter>format == 'pdf' and method['method'] == 'pl.rank_genes_groups_violin'</filter>
        </collection>
        <data name="out_svg" format="svg" from_work_dir="*.svg" label="SVG plot from ${tool.name} (${method.method}) on ${on_string}">
            <filter>format == 'svg' and method['method'] != pl.rank_genes_groups_violin</filter>
        </data>
        <collection name="collection_svg" type="list" label="SVG plots from ${tool.name} (${method.method}) on ${on_string}">
            <discover_datasets pattern="rank_genes_groups_(?P&lt;designation&gt;.*).svg" format="svg"/>
            <filter>format == 'svg' and method['method'] == 'pl.rank_genes_groups_violin'</filter>
        </collection>
        <data name="hidden_output" format="txt" label="Log file" hidden="true" >
            <filter>advanced_common['show_log']</filter>
        </data>
    </outputs>
    <tests>
        <test expect_num_outputs="2">
            <!-- test 1: pl.scatter -->
            <param name="adata" value="pbmc68k_reduced.h5ad" />
            <param name="format" value="png"/>
            <conditional name="method">
                <param name="method" value="pl.scatter"/>
                <conditional name="type">
                    <param name="type" value="basis"/>
                    <param name="basis" value="umap"/>
                    <param name="color" value="HES4"/>
                </conditional>
                <param name="use_raw" value="True"/>
                <param name="sort_order" value="True"/>
                <section name="plot">
                    <param name="projection" value="2d"/>
                    <param name="legend_loc" value="right margin"/>
                    <param name="legend_fontsize" value="1"/>
                    <param name="legend_fontweight" value="normal"/>
                    <param name="color_map" value="inferno"/>
                    <param name="palette" value="inferno"/>
                    <param name="frameon" value="True"/>
                    <param name="size" value="1"/>
                </section>
            </conditional>
            <section name="advanced_common">
                <param name="show_log" value="true" />
            </section>
            <output name="hidden_output">
                <assert_contents>
                    <has_text_matching expression="sc.pl.scatter"/>
                    <has_text_matching expression="basis='umap'" />
                    <has_text_matching expression="color=\['HES4'\]"/>
                    <has_text_matching expression="use_raw=True"/>
                    <has_text_matching expression="sort_order=True"/>
                    <has_text_matching expression="projection='2d'"/>
                    <has_text_matching expression="legend_loc='right margin'"/>
                    <has_text_matching expression="legend_fontsize=1"/>
                    <has_text_matching expression="legend_fontweight='normal'"/>
                    <has_text_matching expression="color_map='inferno'"/>
                    <has_text_matching expression="frameon=True"/>
                    <has_text_matching expression="size=1.0"/>
                </assert_contents>
            </output>
            <output name="out_png" file="pl.scatter.umap.pbmc68k_reduced.png" ftype="png" compare="sim_size"/>
        </test>
        <test expect_num_outputs="2">
            <!-- test 2: pl.scatter -->
            <param name="adata" value="krumsiek11.h5ad" />
            <param name="format" value="png"/>
            <conditional name="method">
                <param name="method" value="pl.scatter"/>
                <conditional name="type">
                    <param name="type" value="xy"/>
                    <param name="x" value="EKLF"/>
                    <param name="y" value="Cebpa"/>
                    <conditional name="layers">
                        <param name="use_layers" value="false"/>
                    </conditional>
                </conditional>
                <param name="use_raw" value="False"/>
                <param name="sort_order" value="True"/>
                <section name="plot">
                    <param name="projection" value="2d"/>
                    <param name="legend_loc" value="right margin"/>
                    <param name="legend_fontsize" value="1"/>
                    <param name="legend_fontweight" value="normal"/>
                    <param name="palette" value="bwr"/>
                    <param name="frameon" value="False"/>
                    <param name="size" value="1"/>
                    <param name="title" value="A title"/>
                </section>
            </conditional>
            <section name="advanced_common">
                <param name="show_log" value="true" />
            </section>
            <output name="hidden_output">
                <assert_contents>
                    <has_text_matching expression="sc.pl.scatter"/>
                    <has_text_matching expression="x_field='EKLF'" />
                    <has_text_matching expression="y_field='Cebpa'"/>
                    <has_text_matching expression="use_raw=False"/>
                    <has_text_matching expression="sort_order=True"/>
                    <has_text_matching expression="projection='2d'"/>
                    <has_text_matching expression="legend_loc='right margin'"/>
                    <has_text_matching expression="legend_fontsize=1"/>
                    <has_text_matching expression="legend_fontweight='normal'"/>
                    <has_text_matching expression="frameon=False"/>
                    <has_text_matching expression="size=1.0"/>
                    <has_text_matching expression="title='A title'"/>
                </assert_contents>
            </output>
            <output name="out_png" file="pl.scatter.krumsiek11.png" ftype="png" compare="sim_size"/>
        </test>
        <test expect_num_outputs="2">
            <!-- test 3: pl.heatmap -->
            <param name="adata" value="krumsiek11.h5ad" />
            <param name="format" value="png"/>
            <conditional name="method">
                <param name="method" value="pl.heatmap"/>
                <conditional name="var_names">
                    <param name="type" value="all"/>
                </conditional>
                <param name="groupby" value="cell_type"/>
                <param name="num_categories" value="7"/>
                <param name="log" value="False"/>
                <param name="use_raw" value="False"/>
                <conditional name="figsize">
                    <param name="test" value="yes"/>
                    <param name="width" value="10" />
                    <param name="height" value="3"/>
                </conditional>
                <param name="dendrogram" value="True"/>
                <param name="swap_axes" value="True"/>
                <param name="show_gene_labels" value="False"/>
                <section name="matplotlib_pyplot_imshow">
                    <param name="cmap" value="YlGnBu"/>
                    <param name="interpolation" value="None"/>
                    <param name="origin" value="upper"/>
                </section>
            </conditional>
            <section name="advanced_common">
                <param name="show_log" value="true" />
            </section>
            <output name="hidden_output">
                <assert_contents>
                    <has_text_matching expression="sc.pl.heatmap"/>
                    <has_text_matching expression="var_names=adata.var_names" />
                    <has_text_matching expression="groupby='cell_type'"/>
                    <has_text_matching expression="log=False"/>
                    <has_text_matching expression="use_raw=False"/>
                    <has_text_matching expression="num_categories=7"/>
                    <has_text_matching expression="dendrogram=True"/>
                    <has_text_matching expression="figsize=\(10, 3\)"/>
                    <has_text_matching expression="swap_axes=True"/>
                    <has_text_matching expression="show_gene_labels=False"/>
                    <has_text_matching expression="cmap='YlGnBu'"/>
                    <has_text_matching expression="origin='upper'"/>
                </assert_contents>
            </output>
            <output name="out_png" file="pl.heatmap.krumsiek11.png" ftype="png" compare="sim_size"/>
        </test>
        <test expect_num_outputs="2">
          <!-- test 4: pl.heatmap with symbols -->
          <param name="adata" value="pp.filter_genes_dispersion.krumsiek11-seurat.h5ad" />
          <param name="format" value="png"/>
          <conditional name="method">
              <param name="method" value="pl.heatmap"/>
              <conditional name="var_names">
                  <param name="type" value="custom"/>
                  <param name="var_names" value="Fog1,EKLF,SCL"/>
              </conditional>
              <param name="groupby" value="cell_type"/>
              <param name="gene_symbols" value="symbol"/>
              <param name="num_categories" value="7"/>
              <param name="log" value="False"/>
              <param name="use_raw" value="False"/>
              <conditional name="figsize">
                  <param name="test" value="yes"/>
                  <param name="width" value="10" />
                  <param name="height" value="3"/>
              </conditional>
              <param name="dendrogram" value="True"/>
              <param name="swap_axes" value="True"/>
              <param name="show_gene_labels" value="True"/>
              <section name="matplotlib_pyplot_imshow">
                  <param name="cmap" value="YlGnBu"/>
                  <param name="interpolation" value="None"/>
                  <param name="origin" value="upper"/>
              </section>
          </conditional>
          <section name="advanced_common">
              <param name="show_log" value="true" />
          </section>
          <output name="hidden_output">
              <assert_contents>
                  <has_text_matching expression="sc.pl.heatmap"/>
                  <has_text_matching expression="gene_symbols='symbol'"/>
                  <has_text_matching expression="var_names=\['Fog1', 'EKLF', 'SCL'\]" />
                  <has_text_matching expression="groupby='cell_type'"/>
                  <has_text_matching expression="log=False"/>
                  <has_text_matching expression="use_raw=False"/>
                  <has_text_matching expression="num_categories=7"/>
                  <has_text_matching expression="dendrogram=True"/>
                  <has_text_matching expression="figsize=\(10, 3\)"/>
                  <has_text_matching expression="swap_axes=True"/>
                  <has_text_matching expression="show_gene_labels=True"/>
                  <has_text_matching expression="cmap='YlGnBu'"/>
                  <has_text_matching expression="origin='upper'"/>
              </assert_contents>
          </output>
        </test>
        <test expect_num_outputs="2">
            <!-- test 5: pl.dotplot -->
            <param name="adata" value="pbmc68k_reduced.h5ad" />
            <param name="format" value="png"/>
            <conditional name="method">
                <param name="method" value="pl.dotplot"/>
                <conditional name="var_names">
                    <param name="type" value="custom"/>
                    <param name="var_names" value="CD79A, MS4A1, CD8A, CD8B, LYZ, GNLY, NKG7, RP3-467N11.1, FCGR3A, FCER1A, CST3, POU2AF1, LINC00402"/>
                </conditional>
                <param name="groupby" value="louvain"/>
                <param name="num_categories" value="7"/>
                <param name="log" value="False"/>
                <param name="use_raw" value="False"/>
                <param name="dendrogram" value="True"/>
                <repeat name="var_group_positions">
                    <param name="start" value="0"/>
                    <param name="end" value="1"/>
                    <param name="label" value="B cells"/>
                </repeat>
                <repeat name="var_group_positions">
                    <param name="start" value="11"/>
                    <param name="end" value="12"/>
                    <param name="label" value="dendritic"/>
                </repeat>
                <conditional name="figsize">
                    <param name="test" value="no"/>
                </conditional>
                <param name="color_map" value="hot"/>
                <param name="dot_max" value="0.7"/>
                <param name="dot_min" value="0.1"/>
                <section name="matplotlib_pyplot_scatter">
                    <param name="linewidths" value="0" />
                    <param name="edgecolors" value="face"/>
                </section>
            </conditional>
            <section name="advanced_common">
                <param name="show_log" value="true" />
            </section>
            <output name="hidden_output">
                <assert_contents>
                    <has_text_matching expression="sc.pl.dotplot"/>
                    <has_text_matching expression="var_names=\['CD79A', 'MS4A1', 'CD8A', 'CD8B', 'LYZ', 'GNLY', 'NKG7', 'RP3-467N11.1', 'FCGR3A', 'FCER1A', 'CST3', 'POU2AF1', 'LINC00402'\]" />
                    <has_text_matching expression="groupby='louvain'"/>
                    <has_text_matching expression="log=False"/>
                    <has_text_matching expression="use_raw=False"/>
                    <has_text_matching expression="num_categories=7"/>
                    <has_text_matching expression="dendrogram=True"/>
                    <has_text_matching expression="var_group_positions=\[\(0, 1\), \(11, 12\)\]"/>
                    <has_text_matching expression="var_group_labels=\['B cells', 'dendritic'\]"/>
                    <has_text_matching expression="color_map='hot'"/>
                    <has_text_matching expression="dot_max=0.7"/>
                    <has_text_matching expression="dot_min=0.1"/>
                    <has_text_matching expression="lw=0.0"/>
                    <has_text_matching expression="ec='face'"/>
                </assert_contents>
            </output>
            <output name="out_png" file="pl.dotplot.krumsiek11.png" ftype="png" compare="sim_size"/>
        </test>
        <test expect_num_outputs="2">
          <!-- test 6: pl.dotplot with symbols -->
          <param name="adata" value="pp.filter_genes_dispersion.krumsiek11-seurat.h5ad" />
          <param name="format" value="png"/>
          <conditional name="method">
              <param name="method" value="pl.dotplot"/>
              <conditional name="var_names">
                  <param name="type" value="custom"/>
                  <param name="var_names" value="Fog1,EKLF,SCL"/>
              </conditional>
              <param name="groupby" value="cell_type"/>
              <param name="gene_symbols" value="symbol"/>
              <param name="num_categories" value="7"/>
              <param name="log" value="False"/>
              <param name="use_raw" value="False"/>
              <param name="dendrogram" value="True"/>
              <section name="matplotlib_pyplot_imshow">
                  <param name="cmap" value="YlGnBu"/>
                  <param name="interpolation" value="None"/>
                  <param name="origin" value="upper"/>
              </section>
          </conditional>
          <section name="advanced_common">
              <param name="show_log" value="true" />
          </section>
          <output name="hidden_output">
              <assert_contents>
                  <has_text_matching expression="sc.pl.dotplot"/>
                  <has_text_matching expression="gene_symbols='symbol'"/>
                  <has_text_matching expression="var_names=\['Fog1', 'EKLF', 'SCL'\]" />
                  <has_text_matching expression="groupby='cell_type'"/>
                  <has_text_matching expression="log=False"/>
                  <has_text_matching expression="use_raw=False"/>
                  <has_text_matching expression="num_categories=7"/>
                  <has_text_matching expression="dendrogram=True"/>
              </assert_contents>
          </output>
        </test>
        <test expect_num_outputs="2">
            <!-- test 7: pl.violin -->
            <param name="adata" value="pbmc68k_reduced.h5ad" />
            <param name="format" value="png"/>
            <conditional name="method">
                <param name="method" value="pl.violin"/>
                <conditional name="key_variables">
                    <param name="type" value="custom"/>
                    <param name="keys" value="n_genes, percent_mito, n_counts" />
                </conditional>
                <param name="log" value="False"/>
                <param name="use_raw" value="False"/>
                <section name="violin_plot">
                    <conditional name="stripplot">
                        <param name="stripplot" value="True"/>
                        <param name="jitter" value="True"/>
                        <param name="size" value="1"/>
                    </conditional>
                    <conditional name="multi_panel">
                        <param name="multi_panel" value="True"/>
                        <param name="width" value="20"/>
                        <param name="height" value="20"/>
                    </conditional>
                    <param name="scale" value="width"/>
                </section>
                <section name="seaborn_violinplot">
                    <param name="bw" value="scott"/>
                    <param name="linewidth" value="0"/>
                    <param name="color" value="AliceBlue"/>
                    <param name="palette" value="viridis"/>
                    <param name="saturation" value="0.75"/>
                </section>
            </conditional>
            <section name="advanced_common">
                <param name="show_log" value="true" />
            </section>
            <output name="hidden_output">
                <assert_contents>
                    <has_text_matching expression="sc.pl.violin"/>
                    <has_text_matching expression="keys=\['n_genes', 'percent_mito', 'n_counts'\]" />
                    <has_text_matching expression="log=False"/>
                    <has_text_matching expression="use_raw=False"/>
                    <has_text_matching expression="stripplot=True"/>
                    <has_text_matching expression="jitter=True"/>
                    <has_text_matching expression="size=1"/>
                    <has_text_matching expression="multi_panel=True"/>
                    <has_text_matching expression="figsize=\(20, 20\)"/>
                    <has_text_matching expression="scale='width'"/>
                    <has_text_matching expression="bw='scott'"/>
                    <has_text_matching expression="scale='width'"/>
                    <has_text_matching expression="linewidth=0.0"/>
                    <has_text_matching expression="color='AliceBlue'"/>
                    <has_text_matching expression="saturation=0.75"/>
                </assert_contents>
            </output>
            <output name="out_png" file="pl.violin.pbmc68k_reduced_custom.png" ftype="png" compare="sim_size"/>
        </test>
        <test expect_num_outputs="2">
            <!-- test 8: pl.stacked_violin -->
            <param name="adata" value="krumsiek11.h5ad" />
            <param name="format" value="png"/>
            <conditional name="method">
                <param name="method" value="pl.stacked_violin"/>
                <conditional name="var_names">
                    <param name="type" value="all"/>
                </conditional>
                <param name="groupby" value="cell_type"/>
                <param name="num_categories" value="7"/>
                <param name="log" value="False"/>
                <param name="use_raw" value="False"/>
                <param name="dendrogram" value="True"/>
                <conditional name="figsize">
                    <param name="test" value="no"/>
                </conditional>
                <param name="swap_axes" value="True"/>
                <section name="violin_plot">
                    <conditional name="stripplot">
                        <param name="stripplot" value="True"/>
                        <param name="jitter" value="True"/>
                        <param name="size" value="1"/>
                    </conditional>
                    <param name="scale" value="width"/>
                </section>
                <param name="row_palette" value="muted"/>
                <param name="standard_scale" value="None"/>
                <section name="seaborn_violinplot">
                    <param name="bw" value="scott"/>
                    <param name="linewidth" value="0"/>
                    <param name="color" value="AliceBlue"/>
                    <param name="saturation" value="0.75"/>
                </section>
            </conditional>
            <section name="advanced_common">
                <param name="show_log" value="true" />
            </section>
            <output name="hidden_output">
                <assert_contents>
                    <has_text_matching expression="sc.pl.stacked_violin"/>
                    <has_text_matching expression="groupby='cell_type'"/>
                    <has_text_matching expression="log=False"/>
                    <has_text_matching expression="use_raw=False"/>
                    <has_text_matching expression="num_categories=7"/>
                    <has_text_matching expression="dendrogram=True"/>
                    <has_text_matching expression="swap_axes=True"/>
                    <has_text_matching expression="stripplot=True"/>
                    <has_text_matching expression="jitter=True"/>
                    <has_text_matching expression="size=1"/>
                    <has_text_matching expression="scale='width'"/>
                    <has_text_matching expression="bw='scott'"/>
                    <has_text_matching expression="scale='width'"/>
                    <has_text_matching expression="linewidth=0.0"/>
                    <has_text_matching expression="color='AliceBlue'"/>
                    <has_text_matching expression="saturation=0.75"/>
                </assert_contents>
            </output>
            <output name="out_png" file="pl.stacked_violin.krumsiek11.png" ftype="png" compare="sim_size"/>
        </test>
        <test expect_num_outputs="2">
          <!-- test 9: pl.stacked_violin with symbols -->
          <param name="adata" value="pp.filter_genes_dispersion.krumsiek11-seurat.h5ad" />
          <param name="format" value="png"/>
          <conditional name="method">
              <param name="method" value="pl.stacked_violin"/>
              <conditional name="var_names">
                  <param name="type" value="custom"/>
                  <param name="var_names" value="Fog1,EKLF,SCL"/>
              </conditional>
              <param name="groupby" value="cell_type"/>
              <param name="gene_symbols" value="symbol"/>
              <param name="num_categories" value="7"/>
              <param name="log" value="False"/>
              <param name="use_raw" value="False"/>
              <param name="dendrogram" value="True"/>
              <param name="swap_axes" value="True"/>
          </conditional>
          <section name="advanced_common">
              <param name="show_log" value="true" />
          </section>
          <output name="hidden_output">
              <assert_contents>
                  <has_text_matching expression="sc.pl.stacked_violin"/>
                  <has_text_matching expression="gene_symbols='symbol'"/>
                  <has_text_matching expression="var_names=\['Fog1', 'EKLF', 'SCL'\]" />
                  <has_text_matching expression="groupby='cell_type'"/>
                  <has_text_matching expression="log=False"/>
                  <has_text_matching expression="use_raw=False"/>
                  <has_text_matching expression="num_categories=7"/>
                  <has_text_matching expression="dendrogram=True"/>
                  <has_text_matching expression="swap_axes=True"/>
              </assert_contents>
          </output>
        </test>
        <test expect_num_outputs="2">
            <!-- test 10: pl.matrixplot -->
            <param name="adata" value="krumsiek11.h5ad" />
            <param name="format" value="png"/>
            <conditional name="method">
                <param name="method" value="pl.matrixplot"/>
                <conditional name="var_names">
                    <param name="type" value="all"/>
                </conditional>
                <param name="groupby" value="cell_type"/>
                <param name="log" value="False"/>
                <param name="use_raw" value="False"/>
                <param name="num_categories" value="7"/>
                <param name="dendrogram" value="True"/>
                <conditional name="figsize">
                    <param name="test" value="no"/>
                </conditional>
                <param name="swap_axes" value="True"/>
                <section name="matplotlib_pyplot_pcolor">
                    <param name="cmap" value="viridis"/>
                    <param name="edgecolors" value="face"/>
                    <param name="snap" value="False"/>
                </section>
            </conditional>
            <section name="advanced_common">
                <param name="show_log" value="true" />
            </section>
            <output name="hidden_output">
                <assert_contents>
                    <has_text_matching expression="sc.pl.matrixplot"/>
                    <has_text_matching expression="var_names=adata.var_names" />
                    <has_text_matching expression="groupby='cell_type'"/>
                    <has_text_matching expression="log=False"/>
                    <has_text_matching expression="use_raw=False"/>
                    <has_text_matching expression="num_categories=7"/>
                    <has_text_matching expression="dendrogram=True"/>
                    <has_text_matching expression="swap_axes=True"/>
                    <has_text_matching expression="cmap='viridis'"/>
                    <has_text_matching expression="ec='face'"/>
                    <has_text_matching expression="snap=False"/>
                </assert_contents>
            </output>
            <output name="out_png" file="pl.matrixplot.krumsiek11.png" ftype="png" compare="sim_size"/>
        </test>
        <test expect_num_outputs="2">
          <!-- test 11: pl.matrixplot with symbols -->
          <param name="adata" value="pp.filter_genes_dispersion.krumsiek11-seurat.h5ad" />
          <param name="format" value="png"/>
          <conditional name="method">
              <param name="method" value="pl.matrixplot"/>
              <conditional name="var_names">
                  <param name="type" value="custom"/>
                  <param name="var_names" value="Fog1,EKLF,SCL"/>
              </conditional>
              <param name="groupby" value="cell_type"/>
              <param name="gene_symbols" value="symbol"/>
              <param name="num_categories" value="7"/>
              <param name="log" value="False"/>
              <param name="use_raw" value="False"/>
              <conditional name="figsize">
                  <param name="test" value="yes"/>
                  <param name="width" value="10" />
                  <param name="height" value="3"/>
              </conditional>
              <param name="dendrogram" value="True"/>
              <param name="swap_axes" value="False"/>
          </conditional>
          <section name="advanced_common">
              <param name="show_log" value="true" />
          </section>
          <output name="hidden_output">
              <assert_contents>
                  <has_text_matching expression="sc.pl.matrixplot"/>
                  <has_text_matching expression="gene_symbols='symbol'"/>
                  <has_text_matching expression="var_names=\['Fog1', 'EKLF', 'SCL'\]" />
                  <has_text_matching expression="groupby='cell_type'"/>
                  <has_text_matching expression="log=False"/>
                  <has_text_matching expression="use_raw=False"/>
                  <has_text_matching expression="num_categories=7"/>
                  <has_text_matching expression="dendrogram=True"/>
                  <has_text_matching expression="swap_axes=False"/>
              </assert_contents>
          </output>
        </test>
        <test expect_num_outputs="2">
            <!-- test 12: pl.clustermap -->
            <param name="adata" value="krumsiek11.h5ad" />
            <param name="format" value="png"/>
            <conditional name="method">
                <param name="method" value="pl.clustermap"/>
                <param name="use_raw" value="False"/>
                <section name="seaborn_clustermap">
                    <param name="method" value="single"/>
                    <param name="metric" value="euclidean"/>
                    <param name="z_score" value="None"/>
                    <param name="standard_scale" value="None"/>
                    <param name="col_cluster" value="False"/>
                    <param name="row_cluster" value="False"/>
                </section>
            </conditional>
            <section name="advanced_common">
                <param name="show_log" value="true" />
            </section>
            <output name="hidden_output">
                <assert_contents>
                    <has_text_matching expression="sc.pl.clustermap"/>
                    <has_text_matching expression="adata=adata" />
                    <has_text_matching expression="use_raw=False"/>
                    <has_text_matching expression="method='single'"/>
                    <has_text_matching expression="metric='euclidean'"/>
                    <has_text_matching expression="col_cluster=False"/>
                    <has_text_matching expression="row_cluster=False"/>
                </assert_contents>
            </output>
            <output name="out_png" file="pl.clustermap.krumsiek11.png" ftype="png" compare="sim_size"/>
        </test>
        <test expect_num_outputs="2">
            <!-- test 13: pl.highest_expr_genes -->
            <param name="adata" value="pp.filter_genes_dispersion.krumsiek11-seurat.h5ad" />
            <param name="format" value="png"/>
            <conditional name="method">
                <param name="method" value="pl.highest_expr_genes"/>
                <param name="n_top" value="30"/>
                <param name="gene_symbols" value="means"/>
                <section name="setseaborn_boxplot">
                    <param name="color" value="blue"/>
                    <param name="saturation" value="0.5"/>
                </section>
            </conditional>
            <section name="advanced_common">
                <param name="show_log" value="true" />
            </section>
            <output name="hidden_output">
                <assert_contents>
                    <has_text_matching expression="sc.pl.highest_expr_genes"/>
                    <has_text_matching expression="n_top=30" />
                    <has_text_matching expression="gene_symbols='means'" />
                    <has_text_matching expression="color='blue'"/>
                    <has_text_matching expression="saturation=0.5"/>
                </assert_contents>
            </output>
            <output name="out_png" file="pl.highest_expr_genes.filter_genes_dispersion.krumsiek11-seurat.png" ftype="png" compare="sim_size"/>
        </test>
        <test expect_num_outputs="2">
            <!-- test 14: pl.highly_variable_genes -->
            <param name="adata" value="pp.highly_variable_genes.seurat.blobs.h5ad" />
            <param name="format" value="png"/>
            <conditional name="method">
                <param name="method" value="pl.highly_variable_genes"/>
                <param name="log" value="false"/>
                <param name="highly_variable_genes" value="true"/>
            </conditional>
            <section name="advanced_common">
                <param name="show_log" value="true" />
            </section>
            <output name="hidden_output">
                <assert_contents>
                    <has_text_matching expression="sc.pl.highly_variable_genes"/>
                    <has_text_matching expression="adata_or_result=adata" />
                    <has_text_matching expression="log=False" />
                    <has_text_matching expression="highly_variable_genes=True"/>
                </assert_contents>
            </output>
            <output name="out_png" file="pl.highly_variable_genes.seurat.blobs.png" ftype="png" compare="sim_size"/>
        </test>
        <test expect_num_outputs="2">
            <!-- test 15: pl.pca -->
            <param name="adata" value="pbmc68k_reduced.h5ad" />
            <param name="format" value="pdf"/>
            <conditional name="method">
                <param name="method" value="pl.pca"/>
                <param name="color" value="CD3D,CD79A"/>
                <param name="use_raw" value="False"/>
                <param name="sort_order" value="True"/>
                <section name="plot">
                    <repeat name="components">
                        <param name="axis1" value="1"/>
                        <param name="axis2" value="2"/>
                    </repeat>
                    <repeat name="components">
                        <param name="axis1" value="1"/>
                        <param name="axis2" value="3"/>
                    </repeat>
                    <param name="projection" value="2d"/>
                    <param name="legend_loc" value="right margin"/>
                    <param name="legend_fontsize" value="1"/>
                    <param name="legend_fontweight" value="normal"/>
                    <param name="size" value="1"/>
                    <param name="palette" value="viridis"/>
                    <param name="frameon" value="True"/>
                    <param name="ncols" value="2"/>
                    <param name="wspace" value="0.1"/>
                    <param name="hspace" value="0.25"/>
                </section>
                <section name="matplotlib_pyplot_scatter">
                    <param name="linewidths" value="0"/>
                    <param name="edgecolors" value="face"/>
                </section>
            </conditional>
            <section name="advanced_common">
                <param name="show_log" value="true" />
            </section>
            <output name="hidden_output">
                <assert_contents>
                    <has_text_matching expression="sc.pl.pca"/>
                    <has_text_matching expression="save='.pdf'" />
                    <has_text_matching expression="color=\['CD3D', 'CD79A'\]" />
                    <has_text_matching expression="use_raw=False" />
                    <has_text_matching expression="sort_order=True" />
                    <has_text_matching expression="components=\['1,2', '1,3'\]" />
                    <has_text_matching expression="projection='2d'" />
                    <has_text_matching expression="legend_loc='right margin'" />
                    <has_text_matching expression="legend_fontsize=1" />
                    <has_text_matching expression="legend_fontweight='normal'" />
                    <has_text_matching expression="size=1.0" />
                    <has_text_matching expression="palette='viridis'" />
                    <has_text_matching expression="frameon=True" />
                    <has_text_matching expression="ncols=2" />
                    <has_text_matching expression="wspace=0.1" />
                    <has_text_matching expression="hspace=0.25" />
                    <has_text_matching expression="lw=0.0" />
                    <has_text_matching expression="ec='face'" />
                </assert_contents>
            </output>
            <output name="out_pdf" file="pl.pca.pbmc68k_reduced.CD3D_CD79A_components_2d.pdf" ftype="pdf" compare="sim_size"/>
        </test>
        <test expect_num_outputs="2">
            <!-- test 16: pl.pca_loadings -->
            <param name="adata" value="pp.pca.krumsiek11.h5ad" />
            <param name="format" value="png"/>
            <conditional name="method">
                <param name="method" value="pl.pca_loadings"/>
                <param name="components" value="1,2,3"/>
            </conditional>
            <section name="advanced_common">
                <param name="show_log" value="true" />
            </section>
            <output name="hidden_output">
                <assert_contents>
                    <has_text_matching expression="sc.pl.pca_loadings"/>
                    <has_text_matching expression="components=\[1, 2, 3\]" />
                </assert_contents>
            </output>
            <output name="out_png" file="pl.pca_loadings.pp.pca.krumsiek11.png" compare="sim_size"/>
        </test>
        <test expect_num_outputs="2">
            <!-- test 17: pl.pca_variance_ratio -->
            <param name="adata" value="pp.pca.krumsiek11.h5ad" />
            <param name="format" value="png"/>
            <conditional name="method">
                <param name="method" value="pl.pca_variance_ratio"/>
                <param name="n_pcs" value="5"/>
                <param name="log" value="False"/>
            </conditional>
            <section name="advanced_common">
                <param name="show_log" value="true" />
            </section>
            <output name="hidden_output">
                <assert_contents>
                    <has_text_matching expression="sc.pl.pca_variance_ratio"/>
                    <has_text_matching expression="n_pcs=5" />
                    <has_text_matching expression="log=False" />
                </assert_contents>
            </output>
            <output name="out_png" file="pl.pca_variance_ratio.pp.pca.krumsiek11.png" compare="sim_size"/>
        </test>
        <test expect_num_outputs="2">
            <!-- test 18: pl.pca_overview -->
            <param name="adata" value="pp.pca.krumsiek11.h5ad" />
            <param name="format" value="png"/>
            <conditional name="method">
                <param name="method" value="pl.pca_overview"/>
                <param name="use_raw" value="False"/>
                <param name="sort_order" value="True"/>
                <section name="plot">
                    <param name="projection" value="2d"/>
                    <param name="legend_loc" value="right margin"/>
                    <param name="legend_fontsize" value="1"/>
                    <param name="legend_fontweight" value="normal"/>
                    <param name="size" value="1"/>
                    <param name="palette" value="viridis"/>
                    <param name="frameon" value="True"/>
                    <param name="ncols" value="4"/>
                    <param name="wspace" value="0.1"/>
                    <param name="hspace" value="0.25"/>
                </section>
            </conditional>
            <section name="advanced_common">
                <param name="show_log" value="true" />
            </section>
            <output name="hidden_output">
                <assert_contents>
                    <has_text_matching expression="sc.pl.pca_overview"/>
                    <has_text_matching expression="use_raw=False"/>
                    <has_text_matching expression="sort_order=True"/>
                    <has_text_matching expression="projection='2d'"/>
                    <has_text_matching expression="legend_loc='right margin'"/>
                    <has_text_matching expression="legend_fontsize=1"/>
                    <has_text_matching expression="legend_fontweight='normal'"/>
                    <has_text_matching expression="size=1.0"/>
                    <has_text_matching expression="palette='viridis'"/>
                    <has_text_matching expression="frameon=True"/>
                    <has_text_matching expression="ncols=4"/>
                    <has_text_matching expression="wspace=0.1"/>
                    <has_text_matching expression="hspace=0.25"/>
                </assert_contents>
            </output>
            <output name="out_png" file="pl.pca_overview.pp.pca.krumsiek11.png" compare="sim_size"/>
        </test>
        <test expect_num_outputs="2">
            <!-- test 19: pl.tsne -->
            <param name="adata" value="tl.tsne.krumsiek11.h5ad" />
            <param name="format" value="png"/>
            <conditional name="method">
                <param name="method" value="pl.tsne"/>
                <param name="use_raw" value="False"/>
                <conditional name="edges">
                    <param name="edges" value="False" />
                </conditional>
                <param name="arrows" value="False" />
                <param name="sort_order" value="True"/>
                <section name="plot">
                    <param name="projection" value="2d"/>
                    <param name="legend_loc" value="right margin"/>
                    <param name="legend_fontsize" value="1"/>
                    <param name="legend_fontweight" value="normal"/>
                    <param name="palette" value="viridis"/>
                    <param name="frameon" value="True"/>
                    <param name="size" value="1"/>
                    <param name="ncols" value="4"/>
                    <param name="wspace" value="0.1"/>
                    <param name="hspace" value="0.25"/>
                </section>
                <section name="matplotlib_pyplot_scatter">
                    <param name="linewidths" value="0"/>
                    <param name="edgecolors" value="face"/>
                </section>
            </conditional>
            <section name="advanced_common">
                <param name="show_log" value="true" />
            </section>
            <output name="hidden_output">
                <assert_contents>
                    <has_text_matching expression="sc.pl.tsne"/>
                    <has_text_matching expression="use_raw=False"/>
                    <has_text_matching expression="edges=False"/>
                    <has_text_matching expression="arrows=False"/>
                    <has_text_matching expression="sort_order=True"/>
                    <has_text_matching expression="projection='2d'"/>
                    <has_text_matching expression="legend_loc='right margin'"/>
                    <has_text_matching expression="legend_fontsize=1"/>
                    <has_text_matching expression="legend_fontweight='normal'"/>
                    <has_text_matching expression="size=1.0"/>
                    <has_text_matching expression="palette='viridis'"/>
                    <has_text_matching expression="frameon=True"/>
                    <has_text_matching expression="ncols=4"/>
                    <has_text_matching expression="wspace=0.1"/>
                    <has_text_matching expression="hspace=0.25"/>
                    <has_text_matching expression="lw=0.0"/>
                    <has_text_matching expression="ec='face'"/>
                </assert_contents>
            </output>
            <output name="out_png" file="pl.tsne.krumsiek11.png" ftype="png" compare="sim_size"/>
        </test>
        <test expect_num_outputs="2">
            <!-- test 20: pl.umap -->
            <param name="adata" value="tl.umap.neighbors_umap_euclidean.recipe_weinreb17.paul15_subsample.h5ad" />
            <param name="format" value="png"/>
            <conditional name="method">
                <param name="method" value="pl.umap"/>
                <param name="color" value="paul15_clusters"/>
                <param name="use_raw" value="False"/>
                <conditional name="edges">
                    <param name="edges" value="True" />
                    <param name="edges_width" value="0.1" />
                    <param name="edges_color" value="AliceBlue"/>
                </conditional>
                <param name="arrows" value="False" />
                <section name="plot">
                    <param name="projection" value="2d"/>
                    <param name="legend_loc" value="right margin"/>
                    <param name="legend_fontsize" value="1"/>
                    <param name="legend_fontweight" value="normal"/>
                    <param name="size" value="1"/>
                    <param name="palette" value="viridis"/>
                    <param name="frameon" value="True"/>
                    <param name="ncols" value="4"/>
                    <param name="wspace" value="0.1"/>
                    <param name="hspace" value="0.25"/>
                </section>
                <section name="matplotlib_pyplot_scatter">
                    <param name="linewidths" value="0"/>
                    <param name="edgecolors" value="face"/>
                </section>
            </conditional>
            <section name="advanced_common">
                <param name="show_log" value="true" />
            </section>
            <output name="hidden_output">
                <assert_contents>
                    <has_text_matching expression="sc.pl.umap"/>
                    <has_text_matching expression="color=\['paul15_clusters'\]"/>
                    <has_text_matching expression="use_raw=False"/>
                    <has_text_matching expression="edges=True"/>
                    <has_text_matching expression="edges_width=0.1"/>
                    <has_text_matching expression="edges_color='AliceBlue'"/>
                    <has_text_matching expression="arrows=False"/>
                    <has_text_matching expression="sort_order=True"/>
                    <has_text_matching expression="projection='2d'"/>
                    <has_text_matching expression="legend_loc='right margin'"/>
                    <has_text_matching expression="legend_fontsize=1"/>
                    <has_text_matching expression="legend_fontweight='normal'"/>
                    <has_text_matching expression="size=1.0"/>
                    <has_text_matching expression="palette='viridis'"/>
                    <has_text_matching expression="frameon=True"/>
                    <has_text_matching expression="ncols=4"/>
                    <has_text_matching expression="wspace=0.1"/>
                    <has_text_matching expression="hspace=0.25"/>
                    <has_text_matching expression="lw=0.0"/>
                    <has_text_matching expression="ec='face'"/>
                </assert_contents>
            </output>
            <output name="out_png" file="pl.umap.neighbors_umap_euclidean.recipe_weinreb17.paul15_subsample.png" ftype="png" compare="sim_size"/>
        </test>
        <test expect_num_outputs="2">
            <!-- test 21: pl.diffmap -->
            <param name="adata" value="tl.diffmap.neighbors_gauss_braycurtis.recipe_weinreb17.paul15_subsample.h5ad" />
            <param name="format" value="png"/>
            <conditional name="method">
                <param name="method" value="pl.diffmap"/>
                <param name="color" value="paul15_clusters"/>
                <param name="use_raw" value="False"/>
                <param name="sort_order" value="True"/>
                <section name="plot">
                    <param name="projection" value="2d"/>
                    <param name="legend_loc" value="right margin"/>
                    <param name="legend_fontsize" value="1"/>
                    <param name="legend_fontweight" value="normal"/>
                    <param name="size" value="1"/>
                    <param name="palette" value="viridis"/>
                    <param name="frameon" value="True"/>
                    <param name="ncols" value="4"/>
                    <param name="wspace" value="0.1"/>
                    <param name="hspace" value="0.25"/>
                </section>
                <section name="matplotlib_pyplot_scatter">
                    <param name="linewidths" value="0"/>
                    <param name="edgecolors" value="face"/>
                </section>
            </conditional>
            <section name="advanced_common">
                <param name="show_log" value="true" />
            </section>
            <output name="hidden_output">
                <assert_contents>
                    <has_text_matching expression="sc.pl.diffmap"/>
                    <has_text_matching expression="color=\['paul15_clusters'\]"/>
                    <has_text_matching expression="use_raw=False"/>
                    <has_text_matching expression="sort_order=True"/>
                    <has_text_matching expression="projection='2d'"/>
                    <has_text_matching expression="legend_loc='right margin'"/>
                    <has_text_matching expression="legend_fontsize=1"/>
                    <has_text_matching expression="legend_fontweight='normal'"/>
                    <has_text_matching expression="size=1.0"/>
                    <has_text_matching expression="palette='viridis'"/>
                    <has_text_matching expression="frameon=True"/>
                    <has_text_matching expression="ncols=4"/>
                    <has_text_matching expression="wspace=0.1"/>
                    <has_text_matching expression="hspace=0.25"/>
                    <has_text_matching expression="lw=0.0"/>
                    <has_text_matching expression="ec='face'"/>
                </assert_contents>
            </output>
            <output name="out_png" file="pl.diffmap.neighbors_gauss_braycurtis.recipe_weinreb17.paul15_subsample.png" ftype="png" compare="sim_size"/>
        </test>
        <test expect_num_outputs="2">
            <!-- test 22: pl.draw_graph -->
            <param name="adata" value="tl.draw_graph.pp.neighbors_umap_euclidean.recipe_weinreb17.paul15_subsample.h5ad" />
            <param name="format" value="png"/>
            <conditional name="method">
                <param name="method" value="pl.draw_graph"/>
                <param name="use_raw" value="false"/>
                <param name="layout" value="fr"/>
                <conditional name="edges">
                    <param name="edges" value="True"/>
                    <param name="edges_width" value="0.1"/>
                    <param name="edges_color" value="Crimson"/>
                </conditional>
                <param name="arrows" value="false"/>
                <param name="sort_order" value="false"/>
                <section name="plot">
                    <param name="projection" value="2d"/>
                    <param name="legend_loc" value="right margin"/>
                    <param name="legend_fontweight" value="normal"/>
                    <param name="palette" value="viridis"/>
                    <param name="frameon" value="True"/>
                    <param name="ncols" value="4"/>
                    <param name="wspace" value="0.1"/>
                    <param name="hspace" value="0.25"/>
                </section>
                <section name="matplotlib_pyplot_scatter">
                    <param name="linewidths" value="0"/>
                    <param name="edgecolors" value="face"/>
                </section>
            </conditional>
            <section name="advanced_common">
                <param name="show_log" value="true" />
            </section>
            <output name="hidden_output">
                <assert_contents>
                    <has_text_matching expression="sc.pl.draw_graph"/>
                    <has_text_matching expression="use_raw=False"/>
                    <has_text_matching expression="edges=True"/>
                    <has_text_matching expression="edges_width=0.1"/>
                    <has_text_matching expression="edges_color='Crimson'"/>
                    <has_text_matching expression="arrows=False"/>
                    <has_text_matching expression="sort_order=False"/>
                    <has_text_matching expression="projection='2d'"/>
                    <has_text_matching expression="legend_loc='right margin'"/>
                    <has_text_matching expression="legend_fontweight='normal'"/>
                    <has_text_matching expression="palette='viridis'"/>
                    <has_text_matching expression="frameon=True"/>
                    <has_text_matching expression="ncols=4"/>
                    <has_text_matching expression="wspace=0.1"/>
                    <has_text_matching expression="hspace=0.25"/>
                    <has_text_matching expression="lw=0.0"/>
                    <has_text_matching expression="ec='face"/>
                </assert_contents>
            </output>
            <output name="out_png" file="pl.draw_graph.png" ftype="png" compare="sim_size"/>
        </test>
        <test expect_num_outputs="2">
            <!-- test 23: pl.embedding_density -->
            <param name="adata" value="tl.embedding_density.umap.pbmc68k_reduced.h5ad" />
            <param name="format" value="png"/>
            <conditional name="method">
                <param name="method" value="pl.embedding_density"/>
                <param name="basis" value="umap"/>
                <param name="key" value="umap_density_bulk_labels"/>
            </conditional>
            <section name="advanced_common">
                <param name="show_log" value="true" />
            </section>
            <output name="hidden_output">
                <assert_contents>
                    <has_text_matching expression="sc.pl.embedding_density"/>
                    <has_text_matching expression="basis='umap'" />
                    <has_text_matching expression="key='umap_density_bulk_labels'"/>
                </assert_contents>
            </output>
            <output name="out_png" file="pl.embedding_density.pbmc68k_reduced.png" ftype="png" compare="sim_size"/>
        </test>
        <test expect_num_outputs="2">
            <!-- test 24: pl.dpt_groups_pseudotime -->
            <param name="adata" value="tl.dpt.diffmap.neighbors_gauss_braycurtis.recipe_weinreb17.paul15_subsample.h5ad" />
            <param name="format" value="png"/>
            <conditional name="method">
                <param name="method" value="pl.dpt_groups_pseudotime"/>
                <param name="color_map" value="viridis"/>
            </conditional>
            <section name="advanced_common">
                <param name="show_log" value="true" />
            </section>
            <output name="hidden_output">
                <assert_contents>
                    <has_text_matching expression="sc.pl.dpt_groups_pseudotime"/>
                    <has_text_matching expression="color_map='viridis'"/>
                </assert_contents>
            </output>
            <output name="out_png" file="pl.dpt_groups_pseudotime.dpt.diffmap.neighbors_gauss_braycurtis.recipe_weinreb17.paul15_subsample.png" ftype="png" compare="sim_size"/>
        </test>
        <test expect_num_outputs="2">
            <!-- test 25: pl.dpt_timeseries -->
            <param name="adata" value="tl.dpt.diffmap.neighbors_gauss_braycurtis.recipe_weinreb17.paul15_subsample.h5ad" />
            <param name="format" value="png"/>
            <conditional name="method">
                <param name="method" value="pl.dpt_timeseries"/>
                <conditional name="heatmap">
                    <param name="as_heatmap" value="True"/>
                    <param name="color_map" value="viridis"/>
                </conditional>
            </conditional>
            <section name="advanced_common">
                <param name="show_log" value="true" />
            </section>
            <output name="hidden_output">
                <assert_contents>
                    <has_text_matching expression="sc.pl.dpt_timeseries"/>
                    <has_text_matching expression="color_map='viridis'"/>
                    <has_text_matching expression="as_heatmap=True"/>
                </assert_contents>
            </output>
            <output name="out_png" file="pl.dpt_timeseries.dpt.diffmap.neighbors_gauss_braycurtis.recipe_weinreb17.paul15_subsample.png" ftype="png" compare="sim_size"/>
        </test>
        <test expect_num_outputs="1">
             <!-- test 26: pl.paga -->
            <param name="adata" value="tl.paga.neighbors.paul15_gauss_braycurtis.h5ad" />
            <param name="format" value="png"/>
            <conditional name="method">
                <param name="method" value="pl.paga"/>
                <param name="threshold" value="0.01"/>
                <param name="color" value="louvain"/>
                <param name="layout" value="fr"/>
                <param name="random_state" value="0"/>
                <param name="solid_edges" value="connectivities"/>
                <param name="single_component" value="False"/>
                <param name="fontsize" value="1"/>
                <param name="node_size_scale" value="1.0"/>
                <param name="node_size_power" value="0.5"/>
                <param name="edge_width_scale" value="5"/>
                <param name="arrowsize" value="30"/>
                <param name="normalize_to_color" value="False"/>
                <param name="cmap" value="viridis"/>
                <param name="frameon" value="True"/>
            </conditional>
            <output name="out_png" file="pl.paga.paul15_gauss_braycurtis.png" ftype="png" compare="sim_size"/>
        </test>
        <test expect_num_outputs="1">
             <!-- test 27: pl.paga_compare -->
            <param name="adata" value="tl.paga.neighbors.paul15_gauss_braycurtis.h5ad" />
            <param name="format" value="png"/>
            <conditional name="method">
                <param name="method" value="pl.paga_compare"/>
                <param name="threshold" value="0.01"/>
                <param name="color" value="louvain"/>
                <param name="layout" value="fr"/>
                <param name="random_state" value="0"/>
                <param name="solid_edges" value="connectivities"/>
                <param name="single_component" value="False"/>
                <param name="fontsize" value="1"/>
                <param name="node_size_scale" value="1.0"/>
                <param name="node_size_power" value="0.5"/>
                <param name="edge_width_scale" value="5"/>
                <param name="arrowsize" value="30"/>
                <param name="normalize_to_color" value="False"/>
                <param name="cmap" value="viridis"/>
                <param name="frameon" value="True"/>
            </conditional>
            <output name="out_png" file="pl.paga_compare.paul15_gauss_braycurtis.png" ftype="png" compare="sim_size"/>
        </test>
        <!--<test expect_num_outputs="2">
             test pl.paga_path
        </test>-->
        <test expect_num_outputs="2">
            <!-- test 28: pl.rank_genes_groups -->
            <param name="adata" value="tl.rank_genes_groups.krumsiek11.h5ad" />
            <param name="format" value="png"/>
            <conditional name="method">
                <param name="method" value="pl.rank_genes_groups"/>
                <param name="gene_symbols" value="symbol"/>
                <param name="n_genes" value="10"/>
                <param name="fontsize" value="8"/>
                <param name="ncols" value="4"/>
                <param name="sharey" value="true"/>
            </conditional>
            <section name="advanced_common">
                <param name="show_log" value="true" />
            </section>
            <output name="hidden_output">
                <assert_contents>
                    <has_text_matching expression="sc.pl.rank_genes_groups"/>
                    <has_text_matching expression="n_genes=10"/>
                    <has_text_matching expression="fontsize=8"/>
                    <has_text_matching expression="ncols=4"/>
                    <has_text_matching expression="sharey=True"/>
                </assert_contents>
            </output>
            <output name="out_png" file="pl.rank_genes_groups.rank_genes_groups.krumsiek11.png" ftype="png" compare="sim_size"/>
        </test>
        <test expect_num_outputs="2">
            <!-- test 29: pl.rank_genes_groups_violin -->
            <param name="adata" value="tl.rank_genes_groups.krumsiek11.h5ad" />
            <param name="format" value="png"/>
            <conditional name="method">
                <param name="method" value="pl.rank_genes_groups_violin"/>
                <conditional name="genes">
                    <param name="select" value="n_genes"/>
                    <param name="n_genes" value="10"/>
                </conditional>
                <param name="use_raw" value="false"/>
                <param name="split" value="true"/>
                <section name="violin_plot">
                    <conditional name="stripplot">
                        <param name="stripplot" value="True"/>
                        <param name="jitter" value="True"/>
                        <param name="size" value="1"/>
                    </conditional>
                    <param name="scale" value="width"/>
                </section>
            </conditional>
            <section name="advanced_common">
                <param name="show_log" value="true" />
            </section>
            <output name="hidden_output">
                <assert_contents>
                    <has_text_matching expression="sc.pl.rank_genes_groups_violin"/>
                    <has_text_matching expression="n_genes=10"/>
                    <has_text_matching expression="use_raw=False"/>
                    <has_text_matching expression="split=True"/>
                    <has_text_matching expression="strip=True"/>
                    <has_text_matching expression="jitter=True"/>
                    <has_text_matching expression="size=1"/>
                    <has_text_matching expression="scale='width'"/>
                </assert_contents>
            </output>
            <output_collection name="collection_png">
                <element name="cell_type_Ery" file="pl.rank_genes_groups_violin.Ery.png" ftype="png" compare="sim_size"/>
                <element name="cell_type_Mk" file="pl.rank_genes_groups_violin.Mk.png" ftype="png" compare="sim_size"/>
                <element name="cell_type_Mo" file="pl.rank_genes_groups_violin.Mo.png" ftype="png" compare="sim_size"/>
                <element name="cell_type_Neu" file="pl.rank_genes_groups_violin.Neu.png" ftype="png" compare="sim_size"/>
                <element name="cell_type_progenitor" file="pl.rank_genes_groups_violin.progenitor.png" ftype="png" compare="sim_size"/>
            </output_collection>
        </test>
        <test expect_num_outputs="2">
            <!-- test 30: pl.rank_genes_groups_dotplot -->
            <param name="adata" value="tl.rank_genes_groups.krumsiek11.h5ad" />
            <param name="format" value="png"/>
            <conditional name="method">
                <param name="method" value="pl.rank_genes_groups_dotplot"/>
                <param name="gene_symbols" value="symbol"/>
                <param name="n_genes" value="10"/>
                <conditional name="var_names">
                  <param name="type" value="all"/>
                </conditional>
                <param name="log" value="False"/>
                <param name="use_raw" value="False"/>
                <param name="dendrogram" value="False"/>
                <param name="color_map" value="viridis"/>
                <section name="matplotlib_pyplot_scatter">
                    <param name="linewidths" value="0" />
                    <param name="edgecolors" value="face"/>
                </section>
            </conditional>
            <section name="advanced_common">
                <param name="show_log" value="true" />
            </section>
            <output name="hidden_output">
                <assert_contents>
                    <has_text_matching expression="sc.pl.rank_genes_groups_dotplot"/>
                    <has_text_matching expression="n_genes=10"/>
                    <has_text_matching expression="log=False"/>
                    <has_text_matching expression="use_raw=False"/>
                    <has_text_matching expression="dendrogram=False"/>
                    <has_text_matching expression="color_map='viridis'"/>
                    <has_text_matching expression="lw=0.0"/>
                    <has_text_matching expression="ec='face'"/>
                </assert_contents>
            </output>
            <output name="out_png" file="pl.rank_genes_groups_dotplot.rank_genes_groups.krumsiek11.png" ftype="png" compare="sim_size"/>
        </test>
        <test expect_num_outputs="2">
            <!-- test 31: pl.rank_genes_groups_heatmap -->
            <param name="adata" value="tl.rank_genes_groups.krumsiek11.h5ad" />
            <param name="format" value="png"/>
            <conditional name="method">
                <param name="method" value="pl.rank_genes_groups_heatmap"/>
                <param name="gene_symbols" value="symbol"/>
                <param name="n_genes" value="10"/>
                <param name="log" value="False"/>
                <param name="use_raw" value="False"/>
                <param name="dendrogram" value="False"/>
                <param name="swap_axes" value="False"/>
                <param name="show_gene_labels" value="False"/>
                <section name="matplotlib_pyplot_imshow">
                    <param name="cmap" value="viridis"/>
                    <param name="interpolation" value="None"/>
                    <param name="origin" value="upper"/>
                </section>
            </conditional>
            <section name="advanced_common">
                <param name="show_log" value="true" />
            </section>
            <output name="hidden_output">
                <assert_contents>
                    <has_text_matching expression="sc.pl.rank_genes_groups_heatmap"/>
                    <has_text_matching expression="n_genes=10"/>
                    <has_text_matching expression="log=False"/>
                    <has_text_matching expression="use_raw=False"/>
                    <has_text_matching expression="dendrogram=False"/>
                    <has_text_matching expression="swap_axes=False"/>
                    <has_text_matching expression="show_gene_labels=False"/>
                    <has_text_matching expression="cmap='viridis'"/>
                    <has_text_matching expression="origin='upper'"/>
                </assert_contents>
            </output>
            <output name="out_png" file="pl.rank_genes_groups_heatmap.rank_genes_groups.krumsiek11.png" ftype="png" compare="sim_size"/>
        </test>
        <test expect_num_outputs="2">
            <!-- test 32: pl.rank_genes_groups_matrixplot -->
            <param name="adata" value="tl.rank_genes_groups.krumsiek11.h5ad" />
            <param name="format" value="png"/>
            <conditional name="method">
                <param name="method" value="pl.rank_genes_groups_matrixplot"/>
                <param name="gene_symbols" value="symbol"/>
                <param name="n_genes" value="10"/>
                <param name="log" value="False"/>
                <param name="use_raw" value="False"/>
                <param name="dendrogram" value="False"/>
                <param name="swap_axes" value="False"/>
                <section name="matplotlib_pyplot_pcolor">
                    <param name="cmap" value="viridis"/>
                    <param name="edgecolors" value="face"/>
                    <param name="snap" value="False"/>
                </section>
            </conditional>
            <section name="advanced_common">
                <param name="show_log" value="true" />
            </section>
            <output name="hidden_output">
                <assert_contents>
                    <has_text_matching expression="sc.pl.rank_genes_groups_matrixplot"/>
                    <has_text_matching expression="n_genes=10"/>
                    <has_text_matching expression="log=False"/>
                    <has_text_matching expression="use_raw=False"/>
                    <has_text_matching expression="dendrogram=False"/>
                    <has_text_matching expression="swap_axes=False"/>
                    <has_text_matching expression="cmap='viridis'"/>
                    <has_text_matching expression="ec='face'"/>
                    <has_text_matching expression="snap=False"/>
                </assert_contents>
            </output>
            <output name="out_png" file="pl.rank_genes_groups_matrixplot.rank_genes_groups.krumsiek11.png" ftype="png" compare="sim_size"/>
        </test>
        <test expect_num_outputs="2">
            <!-- test 33: pl.rank_genes_groups_stacked_violin -->
            <param name="adata" value="tl.rank_genes_groups.krumsiek11.h5ad" />
            <param name="format" value="png"/>
            <conditional name="method">
                <param name="method" value="pl.rank_genes_groups_stacked_violin"/>
                <param name="gene_symbols" value="symbol"/>
                <param name="n_genes" value="10"/>
                <param name="log" value="False"/>
                <param name="use_raw" value="False"/>
                <param name="dendrogram" value="True"/>
                <param name="swap_axes" value="True"/>
                <section name="violin_plot">
                    <conditional name="stripplot">
                        <param name="stripplot" value="True"/>
                        <param name="jitter" value="True"/>
                        <param name="size" value="1"/>
                    </conditional>
                    <param name="scale" value="width"/>
                </section>
                <param name="row_palette" value="muted"/>
                <param name="standard_scale" value="None"/>
                <section name="seaborn_violinplot">
                    <param name="bw" value="scott"/>
                    <param name="linewidth" value="0"/>
                    <param name="color" value="AliceBlue"/>
                    <param name="palette" value="viridis"/>
                    <param name="saturation" value="0.75"/>
                </section>
            </conditional>
            <section name="advanced_common">
                <param name="show_log" value="true" />
            </section>
            <output name="hidden_output">
                <assert_contents>
                    <has_text_matching expression="sc.pl.rank_genes_groups_stacked_violin"/>
                    <has_text_matching expression="n_genes=10"/>
                    <has_text_matching expression="log=False"/>
                    <has_text_matching expression="use_raw=False"/>
                    <has_text_matching expression="dendrogram=True"/>
                    <has_text_matching expression="swap_axes=True"/>
                    <has_text_matching expression="stripplot=True"/>
                    <has_text_matching expression="jitter=True"/>
                    <has_text_matching expression="size=1"/>
                    <has_text_matching expression="scale='width'"/>
                    <has_text_matching expression="bw='scott'"/>
                    <has_text_matching expression="scale='width'"/>
                    <has_text_matching expression="linewidth=0.0"/>
                    <has_text_matching expression="color='AliceBlue'"/>
                    <has_text_matching expression="saturation=0.75"/>
                </assert_contents>
            </output>
            <output name="out_png" file="pl.rank_genes_groups_stacked_violin.rank_genes_groups.krumsiek11.png" ftype="png" compare="sim_size"/>
        </test>
        <test expect_num_outputs="2">
            <!-- test 34: pl.scatter log !-->
            <param name="adata" value="pbmc68k_reduced.h5ad" />
            <param name="format" value="png"/>
            <conditional name="method">
                <param name="method" value="pl.scatter"/>
                <conditional name="type">
                    <param name="type" value="xy"/>
                    <param name="x" value="n_genes"/>
                    <param name="y" value="n_counts"/>
                    <param name="log" value="True"/>
                    <conditional name="layers">
                        <param name="use_layers" value="false"/>
                    </conditional>
                </conditional>
                <param name="use_raw" value="False"/>
                <param name="sort_order" value="True"/>
                <section name="plot">
                    <param name="projection" value="2d"/>
                    <param name="legend_loc" value="right margin"/>
                    <param name="legend_fontsize" value="1"/>
                    <param name="legend_fontweight" value="normal"/>
                    <param name="palette" value="bwr"/>
                    <param name="frameon" value="False"/>
                    <param name="size" value="1"/>
                    <param name="title" value="A title"/>
                </section>
            </conditional>
            <section name="advanced_common">
                <param name="show_log" value="true" />
            </section>
            <output name="hidden_output">
                <assert_contents>
                    <has_text_matching expression="sc.pl.scatter"/>
                    <has_text_matching expression="use_raw=False"/>
                    <has_text_matching expression="sort_order=True"/>
                    <has_text_matching expression="projection='2d'"/>
                    <has_text_matching expression="legend_loc='right margin'"/>
                    <has_text_matching expression="legend_fontsize=1"/>
                    <has_text_matching expression="legend_fontweight='normal'"/>
                    <has_text_matching expression="frameon=False"/>
                    <has_text_matching expression="size=1.0"/>
                    <has_text_matching expression="title='A title'"/>
                </assert_contents>
            </output>
            <output name="out_png" file="pl.scatter.pbmc68k_reduced.png" ftype="png" compare="sim_size"/>
        </test>
        <test expect_num_outputs="2">
            <!-- test 35: pl.rank_genes_groups_dotplot with marker list -->
            <param name="adata" value="cosg.rank_genes_groups.newton-cg.pbmc68k_highly_reduced_1.h5ad" />
            <param name="format" value="png"/>
            <conditional name="method">
                <param name="method" value="pl.rank_genes_groups_dotplot"/>
                <conditional name="var_names">
                  <param name="type" value="customfile"/>
                  <param name="var_names" value="tl.rank_genes_groups.newton-cg.pbmc68k_highly_reduced_marker_1.tsv"/>
                </conditional>
                <param name="groupby" value="bulk_labels"/>
                <param name="log" value="False"/>
                <param name="use_raw" value="False"/>
                <param name="dendrogram" value="False"/>
                <param name="color_map" value="viridis"/>
                <section name="matplotlib_pyplot_scatter">
                    <param name="linewidths" value="0" />
                    <param name="edgecolors" value="face"/>
                </section>
            </conditional>
            <section name="advanced_common">
                <param name="show_log" value="true" />
            </section>
            <output name="hidden_output">
                <assert_contents>
                    <has_text_matching expression="sc.pl.rank_genes_groups_dotplot"/>
                    <has_text_matching expression="groupby='bulk_labels'"/>
                    <has_text_matching expression="log=False"/>
                    <has_text_matching expression="use_raw=False"/>
                    <has_text_matching expression="dendrogram=False"/>
                    <has_text_matching expression="color_map='viridis'"/>
                    <has_text_matching expression="lw=0.0"/>
                    <has_text_matching expression="ec='face'"/>
                </assert_contents>
            </output>
            <output name="out_png" file="pl.rank_genes_groups.newton-cg.pbmc68k_highly_reduced_marker_1.png" ftype="png" compare="sim_size"/>
        </test>
        <test expect_num_outputs="2">
            <!-- test 36: pl.rank_genes_groups_dotplot with marker list -->
            <param name="adata" value="cosg.rank_genes_groups.newton-cg.pbmc68k_highly_reduced_1.h5ad" />
            <param name="format" value="png"/>
            <conditional name="method">
                <param name="method" value="pl.rank_genes_groups_dotplot"/>
                <conditional name="var_names">
                  <param name="type" value="customfile"/>
                  <param name="var_names" value="tl.rank_genes_groups.newton-cg.pbmc68k_highly_reduced_marker_filtered_1.tsv"/>
                </conditional>
                <param name="groupby" value="bulk_labels"/>
                <param name="log" value="False"/>
                <param name="use_raw" value="False"/>
                <param name="dendrogram" value="False"/>
                <param name="color_map" value="viridis"/>
                <section name="matplotlib_pyplot_scatter">
                    <param name="linewidths" value="0" />
                    <param name="edgecolors" value="face"/>
                </section>
            </conditional>
            <section name="advanced_common">
                <param name="show_log" value="true" />
            </section>
            <output name="hidden_output">
                <assert_contents>
                    <has_text_matching expression="sc.pl.rank_genes_groups_dotplot"/>
                    <has_text_matching expression="groupby='bulk_labels'"/>
                    <has_text_matching expression="log=False"/>
                    <has_text_matching expression="use_raw=False"/>
                    <has_text_matching expression="dendrogram=False"/>
                    <has_text_matching expression="color_map='viridis'"/>
                    <has_text_matching expression="lw=0.0"/>
                    <has_text_matching expression="ec='face'"/>
                </assert_contents>
            </output>
            <output name="out_png" file="pl.rank_genes_groups.newton-cg.pbmc68k_highly_reduced_marker_filtered_1.png" ftype="png" compare="sim_size"/>
        </test>
    </tests>
    <help><![CDATA[
Generic: Scatter plot along observations or variables axes (`pl.scatter`)
=========================================================================

Color the plot using annotations of observations (`.obs`), variables
(`.var`) or expression of genes (`.var_names`).

More details on the `scanpy documentation
<https://scanpy.readthedocs.io/en/stable/api/scanpy.pl.scatter.html>`__

Generic: Heatmap of the expression values of set of genes (`pl.heatmap`)
========================================================================

If `groupby` is given, the heatmap is ordered by the respective group. For
example, a list of marker genes can be plotted, ordered by clustering. If
the `groupby` observation annotation is not categorical the observation
annotation is turned into a categorical by binning the data into the number
specified in `num_categories`.

More details on the `scanpy documentation
<https://scanpy.readthedocs.io/en/stable/api/scanpy.pl.heatmap.html>`__

Generic: Makes a dot plot of the expression values (`pl.dotplot`)
=================================================================

For each var_name and each `groupby` category a dot is plotted. Each dot
represents two values: mean expression within each category (visualized by
color) and fraction of cells expressing the var_name in the
category. (visualized by the size of the dot).  If groupby is not given, the
dotplot assumes that all data belongs to a single category. A gene is not
considered expressed if the expression value in the adata (or adata.raw) is
equal to zero.

For instance, for each marker gene, the mean value and the percentage of cells
expressing the gene can be visualized for each cluster.

More details on the `scanpy documentation
<https://scanpy.readthedocs.io/en/stable/api/scanpy.pl.dotplot.html>`__

Generic: Violin plot (`pl.violin`)
==================================

Wraps `seaborn.violinplot` for `anndata.AnnData`.

More details on the `scanpy documentation
<https://scanpy.readthedocs.io/en/stable/api/scanpy.pl.violin.html>`__

Generic: Stacked violin plots (`pl.stacked_violin`)
===================================================

Makes a compact image composed of individual violin plots (from `seaborn.violinplot`)
stacked on top of each other. Useful to visualize gene expression per cluster.

More details on the `scanpy documentation
<https://scanpy.readthedocs.io/en/stable/api/scanpy.pl.stacked_violin.html>`__

Generic: Heatmap of the mean expression values per cluster (`pl.matrixplot`)
============================================================================

Creates a heatmap of the mean expression values per cluster of each var_names

If groupby is not given, the matrixplot assumes that all data belongs to a single
category.

More details on the `scanpy documentation
<https://scanpy.readthedocs.io/en/stable/api/scanpy.pl.matrixplot.html>`__

Generic: Hierarchically-clustered heatmap (`pl.clustermap`)
===========================================================

Wraps `seaborn.clustermap
<https://seaborn.pydata.org/generated/seaborn.clustermap.html>`__ for
`anndata.AnnData`.

The returned object has a savefig() method that should be used if you want
to save the figure object without clipping the dendrograms.

To access the reordered row indices, use:
clustergrid.dendrogram_row.reordered_ind

Column indices, use: clustergrid.dendrogram_col.reordered_ind

More details on the `scanpy documentation
<https://scanpy.readthedocs.io/en/stable/api/scanpy.pl.clustermap.html>`__

Preprocessing: Plot the fraction of counts assigned to each gene over all cells (`pl.highest_expr_genes`)
=========================================================================================================

Computes, for each gene, the fraction of counts assigned to that gene within
a cell. The `n_top` genes with the highest mean fraction over all cells are
plotted as boxplots.

This plot is similar to the `scater` package function `plotHighestExprs(type= "highest-expression")`

More details on the `scanpy documentation
<https://scanpy.readthedocs.io/en/stable/api/generated/scanpy.pl.highest_expr_genes.html>`__

Preprocessing: Plot dispersions versus means for genes (`pl.highly_variable_genes`)
===================================================================================

It produces Supp. Fig. 5c of Zheng et al. (2017) and MeanVarPlot() of Seurat.

More details on the `scanpy documentation
<https://scanpy.readthedocs.io/en/stable/api/generated/scanpy.pl.highly_variable_genes.html>`__

PCA: Scatter plot in PCA coordinates (`pl.pca`)
===============================================

More details on the `scanpy documentation
<https://scanpy.readthedocs.io/en/stable/api/generated/scanpy.pl.pca.html>`__

PCA: Rank genes according to contributions to PCs (`pl.pca_loadings`)
=====================================================================

More details on the `scanpy documentation
<https://scanpy.readthedocs.io/en/stable/api/generated/scanpy.pl.pca_loadings.html>`__

PCA: Plot the variance ratio (`pl.pca_variance_ratio`)
======================================================

More details on the `scanpy documentation
<https://scanpy.readthedocs.io/en/stable/api/generated/scanpy.pl.pca_variance_ratio.html>`__

PCA: Plot PCA results (`pl.pca_overview`)
=========================================

The parameters are the ones of the scatter plot. Call pca_ranking separately
if you want to change the default settings.

More details on the `scanpy documentation
<https://scanpy.readthedocs.io/en/stable/api/generated/scanpy.pl.pca_overview.html>`__

Embedding: Scatter plot in tSNE basis (`pl.tsne`)
=================================================

More details on the `scanpy documentation
<https://scanpy.readthedocs.io/en/stable/api/generated/scanpy.pl.tsne.html>`__

Embeddings: Scatter plot in UMAP basis (`pl.umap`)
==================================================

More details on the `scanpy documentation
<https://scanpy.readthedocs.io/en/stable/api/generated/scanpy.pl.umap.html>`__

Embeddings: Scatter plot in Diffusion Map basis (`pl.diffmap`)
==============================================================

More details on the `scanpy documentation
<https://scanpy.readthedocs.io/en/stable/api/generated/scanpy.pl.diffmap.html>`__

Branching trajectories and pseudotime, clustering: Plot groups and pseudotime (`pl.dpt_groups_pseudotime`)
===========================================================================================================

More details on the `scanpy documentation
<https://scanpy.readthedocs.io/en/stable/api/generated/scanpy.pl.dpt_groups_pseudotime.html>`__

Branching trajectories and pseudotime, clustering: Heatmap of pseudotime series (`pl.dpt_timeseries`)
=====================================================================================================

More details on the `scanpy documentation
<https://scanpy.readthedocs.io/en/stable/api/generated/scanpy.pl.dpt_timeseries.html>`__


Branching trajectories and pseudotime, clustering: Plot the abstracted graph through thresholding low-connectivity edges (`pl.paga`)
====================================================================================================================================

This uses ForceAtlas2 or igraph's layout algorithms for most layouts.

When initializing the positions, note that - for some reason - igraph
mirrors coordinates along the x axis... that is, you should increase the
`maxiter` parameter by 1 if the layout is flipped.

More details on the `scanpy documentation
<https://scanpy.readthedocs.io/en/stable/api/generated/scanpy.pl.paga.html>`__


Branching trajectories and pseudotime, clustering: Scatter and PAGA graph side-by-side (`pl.paga_compare`)
==========================================================================================================

More details on the `scanpy documentation
<https://scanpy.readthedocs.io/en/stable/api/generated/scanpy.pl.paga_compare.html>`__

Branching trajectories and pseudotime, clustering: Gene expression and annotation changes along paths (`pl.paga_path`)
======================================================================================================================

More details on the `scanpy documentation
<https://scanpy.readthedocs.io/en/stable/api/generated/scanpy.pl.paga_path.html>`__

Marker genes: Plot ranking of genes using dotplot plot (`pl.rank_genes_groups`)
===============================================================================

More details on the `scanpy documentation
<https://scanpy.readthedocs.io/en/stable/api/generated/scanpy.pl.rank_genes_groups.html>`__

Marker genes: Plot ranking of genes as violin plot (`pl.rank_genes_groups_violin`)
==================================================================================

More details on the `scanpy documentation
<https://scanpy.readthedocs.io/en/stable/api/generated/scanpy.pl.rank_genes_groups_violin.html>`__

Marker genes: Plot ranking of genes as dotplot plot (`pl.rank_genes_groups_dotplot`)
====================================================================================

More details on the `scanpy documentation
<https://scanpy.readthedocs.io/en/stable/api/generated/scanpy.pl.rank_genes_groups_dotplot.html>`__

Marker genes: Plot ranking of genes as heatmap plot (`pl.rank_genes_groups_heatmap`)
====================================================================================

More details on the `scanpy documentation
<https://scanpy.readthedocs.io/en/stable/api/generated/scanpy.pl.rank_genes_groups_heatmap.html>`__

Marker genes: Plot ranking of genes as matrixplot plot (`pl.rank_genes_groups_matrixplot`)
==========================================================================================

More details on the `scanpy documentation
<https://scanpy.readthedocs.io/en/stable/api/generated/scanpy.pl.rank_genes_groups_matrixplot.html>`__

Marker genes: Plot ranking of genes as stacked violin plot (`pl.rank_genes_groups_stacked_violin`)
==================================================================================================

More details on the `scanpy documentation
<https://scanpy.readthedocs.io/en/stable/api/generated/scanpy.pl.rank_genes_groups_stacked_violin.html>`__
    ]]></help>
    <expand macro="citations"/>
</tool>