Plots

tinytopics.plot

plot_loss(losses, figsize=(10, 8), dpi=300, title='Loss curve', color_palette=None, output_file=None)

Plot the loss curve over training epochs.

Parameters:

Name	Type	Description	Default
losses	Sequence[float]	List of loss values for each epoch.	required
figsize	tuple[int, int]	Plot size.	(10, 8)
dpi	int	Plot resolution.	300
title	str	Plot title.	'Loss curve'
color_palette	Sequence[str] | str | None	Custom color palette.	None
output_file	str | None	File path to save the plot. If None, displays the plot.	None

plot_structure(L_matrix, normalize_rows=False, figsize=(12, 6), dpi=300, title='Structure Plot', color_palette=None, output_file=None)

Structure plot for visualizing document-topic distributions.

Parameters:

Name	Type	Description	Default
L_matrix	ndarray	Document-topic distribution matrix.	required
normalize_rows	bool	If True, normalizes each row of L_matrix to sum to 1.	False
figsize	tuple[int, int]	Plot size.	(12, 6)
dpi	int	Plot resolution.	300
title	str	Plot title.	'Structure Plot'
color_palette	Sequence[str] | str | None	Custom color palette.	None
output_file	str | None	File path to save the plot. If None, displays the plot.	None

plot_top_terms(F_matrix, n_top_terms=10, term_names=None, figsize=(10, 8), dpi=300, title='Top Terms', color_palette=None, nrows=None, ncols=None, output_file=None)

Plot top terms for each topic in horizontal bar charts.

Parameters:

Name	Type	Description	Default
F_matrix	ndarray	Topic-term distribution matrix.	required
n_top_terms	int	Number of top terms to display per topic.	10
term_names	Sequence[str] | None	List of term names corresponding to indices.	None
figsize	tuple[int, int]	Plot size.	(10, 8)
dpi	int	Plot resolution.	300
title	str	Plot title.	'Top Terms'
color_palette	Sequence[str] | str | None	Custom color palette.	None
nrows	int | None	Number of rows in the subplot grid.	None
ncols	int | None	Number of columns in the subplot grid.	None
output_file	str | None	File path to save the plot. If None, displays the plot.	None