Forest plot

Creating forest plots from contrast objects.

forest_plot

 forest_plot (contrasts:List, selected_indices:Optional[List]=None,
              contrast_type:str='delta2', xticklabels:Optional[List]=None,
              effect_size:str='mean_diff', contrast_labels:List[str]=None,
              ylabel:str='value',
              plot_elements_to_extract:Optional[List]=None, title:str='ΔΔ
              Forest', custom_palette:Union[dict,list,str,NoneType]=None,
              fontsize:int=20, violin_kwargs:Optional[dict]=None,
              marker_size:int=20, ci_line_width:float=2.5,
              zero_line_width:int=1, remove_spines:bool=True,
              ax:Optional[matplotlib.axes._axes.Axes]=None,
              additional_plotting_kwargs:Optional[dict]=None,
              rotation_for_xlabels:int=45, alpha_violin_plot:float=0.4,
              horizontal:bool=False)

Custom function that generates a forest plot from given contrast objects, suitable for a range of data analysis types, including those from packages like DABEST-python.

	Type	Default	Details
contrasts	List		List of contrast objects.
selected_indices	Optional[List]	None	Indices of specific contrasts to plot, if not plotting all.
contrast_type	str	delta2
xticklabels	Optional[List]	None	Custom labels for the x-axis ticks.
effect_size	str	mean_diff	Type of effect size to plot (e.g., ‘mean_diff’, ‘median_diff’).
contrast_labels	List[str]	None	Labels for each contrast.
ylabel	str	value	Label for the y-axis, describing the plotted data or effect size.
plot_elements_to_extract	Optional[List]	None	Elements to extract for detailed plot customization.
title	str	ΔΔ Forest	Plot title, summarizing the visualized data.
custom_palette	Optional[Union[dict, list, str]]	None	Custom color palette for the plot.
fontsize	int	20	Font size for text elements in the plot.
violin_kwargs	Optional[dict]	None	Additional arguments for violin plot customization.
marker_size	int	20	Marker size for plotting mean differences or effect sizes.
ci_line_width	float	2.5	Width of confidence interval lines.
zero_line_width	int	1	Width of the line indicating zero effect size.
remove_spines	bool	True	If True, removes top and right plot spines.
ax	Optional[plt.Axes]	None	Matplotlib Axes object for the plot; creates new if None. additional_plotting_kwargs : Optional[dict], default=None Further customization arguments for the plot.
additional_plotting_kwargs	Optional[dict]	None
rotation_for_xlabels	int	45	Rotation angle for x-axis labels, improving readability.
alpha_violin_plot	float	0.4	Transparency level for violin plots.
horizontal	bool	False	New argument for horizontal orientation
Returns	plt.Figure		The matplotlib figure object with the generated forest plot.

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extract_plot_data

 extract_plot_data (contrast_plot_data, contrast_type)

Extracts bootstrap, difference, and confidence intervals based on contrast labels.

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load_plot_data

 load_plot_data (contrasts:List, effect_size:str='mean_diff',
                 contrast_type:str='delta2')

Loads plot data based on specified effect size and contrast type.

	Type	Default	Details
contrasts	List		List of contrast objects.
effect_size	str	mean_diff
contrast_type	str	delta2
Returns	List