plotting - plotting utilities

Utilities for plotting.

bulkdgd.plotting.plots.plot_representations_time(df: DataFrame, output_file: str | None = None, config: dict[str, object] | None = None, **kwargs: dict[str, object] | None) → None

Plot the CPU/wall clock time spent in each epoch of each round of optimization when finding the representations for a set of samples (both for the full epoch and for the backward step performed in each epoch).

Parameters:

dfpandas.DataFrame

A data frame containing the time data. This data frame is produced as an output by the bulkdgd.core.model.BulkDGD.get_representations method.

output_filestr, optional

The file where the plot will be saved. If not provided, the plot will be generated but not saved.

configdict, optional

A dictionary containing the configuration for the plot’s aesthetics.

Alternatively, the options for the plot’s aesthetics can be provided using keyword arguments.

The available options can be found in the documentation.

If no configuration is provided, the default configuration (taken from the configs/plotting/lineplot.yaml file) will be used.

**kwargs

Additional keyword arguments representing options for the plot’s aesthetics.

The available options can be found in the documentation.

bulkdgd.plotting.plots.plot_dimensionality_reduction(dfs: list[DataFrame], output_file: str | None = None, config: dict[str, object] | None = None, max_plots_per_output: int = 9, columns: list[str] = ['C1', 'C2'], groups_column: str | None = None, groups: list[str] | None = None, plot_other_groups: bool = False, dfs_names: list[str] | None = None, **kwargs: dict[str, object] | None) → None

Plot the results of one or several dimensionality reduction analyses on a single figure (which may be split in multiple output files).

Parameters:

dfspandas.DataFrame

A list of data frames containing the results of the dimensionality reduction analyses.

The rows of each data frame should contain the data points, while the columns should contain the values of each data point’s projection along the principal components.

output_filestr, optional

The file where the plot will be saved. If not provided, the plot will be generated but not saved.

configdict, optional

A dictionary containing the configuration for the plot’s aesthetics.

Alternatively, the options for the plot’s aesthetics can be provided using keyword arguments.

The available options can be found in the documentation.

If no configuration is provided, the default configuration (taken from the configs/plotting/scatterplot.yaml file) will be used.

max_plots_per_outputint, 9

The maximum number of plots for each output file.

columnslist, ["PC1", "PC2"]

A list with the names of the two columns in each data frame that contain the values of the two dimensions of the projection’s space to be considered when plotting.

groups_columnstr, optional

The name of the column containing the labels of different groups of data points in the data frames, if any.

If provided, the data points will be colored according to the group they belong.

If not provided, the data points will be assumed to belong to one group.

groupslist, optional

A list of groups of interest.

If a list of groups is provided and plot_other_groups is False, only data points belonging to the groups of interest will be plotted.

If plot_other_groups is True, the other groups will be plotted according to the aesthetic specifications provided in the configuration.

plot_other_groupsbool, False

If a list of groups of interest if provided, set whether to plot data points belonging to the other groups according to the aesthetic specifications provided in the configuration (True) or not to plot the data points belonging to the other groups at all (False).

dfs_nameslist, optional

A list of names for the data frames passed. These names, if passed, will be used as the titles of the corresponding plots.

**kwargs

Additional keyword arguments representing options for the plot’s aesthetics.

The available options can be found in the documentation.

bulkdgd.plotting.plots.plot_enrichment_scores(df: DataFrame, groups_column: str, gene_set: str, gene_set_column: str = 'gene_set', num_genes_in_set_column: str = 'num_genes_in_set', num_genes_significant_column: str = 'num_genes_significant', e_score_column: str = 'e_score', groups: list[str] | None = None, config: dict[str, object] | None = None, output_file: str | None = None, **kwargs: dict[str, object] | None) → None

Plot the enrichment scores for sets of samples belonging to different groups.

Parameters:

dfpandas.DataFrame

A data frame containing the enrichment scores.

groups_columnstr

The name of the column containing the labels of different groups in the data frame.

gene_setstr

The name of the gene set for which the enrichment scores will be plotted.

gene_set_columnstr, "gene_set"

The name of the column containing the labels of the gene sets in the data frame.

num_genes_in_set_columnstr, "num_genes_in_set"

The name of the column containing the number of genes in each gene set in the data frame.

num_genes_significant_columnstr, "num_genes_significant"

The name of the column containing the number of significant genes in the data frame.

e_score_columnstr, "e_score"

The name of the column containing the enrichment scores in the data frame.

groupslist, optional

A list of groups of interest.

If a list of groups is provided, only the enrichment scores of the samples belonging to the groups of interest will be plotted.

If not provided, the enrichment scores of all the samples will be plotted.

configdict, optional

A dictionary containing the configuration for the plot’s aesthetics.

Alternatively, the options for the plot’s aesthetics can be provided using keyword arguments.

The available options can be found in the documentation.

output_filestr, optional

The file where the plot will be saved.

**kwargs

Additional keyword arguments representing options for the plot’s aesthetics.

The available options can be found in the documentation.

bulkdgd.plotting.plots.plot_rvalues(dfs: list[DataFrame] | DataFrame, genes: list[str], output_file: str | None = None, plot_type: str = 'histogram', config: dict[str, object] | None = None, max_plots_per_output: int = 9, categories: list[str] | None = None, **kwargs: dict[str, object] | None) → None

Plot the distribution of r-values for specific genes for one set of samples or two paired sets of samples (for instance, normal samples and cancer samples for the same tissue).

Parameters:

dfslist or pandas.DataFrame

One or two data frames containing the r-values values for one or two sets of samples.

The rows should contain the samples, while the columns should contain the r-values of the negative binomial distributions modeling the genes.

geneslist

A list of the names of the genes for which the r-values will be plotted.

output_filestr, optional

The file(s) where the plot(s) will be saved.

If multiple files need to be generated, the output file name will be constructed by appending a number to the name provided.

The format of the output file is inferred from its extension.

If not provided, the plot(s) will be generated but not saved.

plot_typestr, {"histogram", "histogram_dual, "histogram_overlap", "boxplot", "violinplot"}, "histogram"

The type of plot to generate. The available options are:

• "histogram": histograms of the r-values of the genes of interest for one set of samples.

• "histogram_bihist": bi-histograms showing the distributions of r-values of the genes of interest for two paired sets of samples.

• "histogram_overlap": two overlapping histograms showing the distribution of r-values of the genes of interest for two paired sets of samples.

• "boxplot": box plots showing the distributions of r-values of the genes of interest in either a set of samples or in two paired sets of samples (paired box plots).

• "violinplot": violin plots showing the distributions of r-values of the genes of interest in either a set of samples or in two paired sets of samples (paired violin plots).

configdict, optional

A dictionary containing the configuration for the plot’s aesthetics.

Alternatively, the options for the plot’s aesthetics can be provided using keyword arguments.

The available options can be found in the documentation.

max_plots_per_outputint, 9

The maximum number of plots for each output file.

categorieslist, optional

A list of two categories used when generating dual histograms or paired box plots or violin plots.

If provided, they are used to generate the legend of the plot.

**kwargs

Additional keyword arguments representing options for the plot’s aesthetics.

The available options can be found in the documentation.