Creates interactive visualizations for semantic analysis results including similarity heatmaps, dimensionality reduction plots, and clustering visualizations.
Usage
plot_semantic_viz(
analysis_result = NULL,
plot_type = "similarity",
data_labels = NULL,
color_by = NULL,
height = 600,
width = 800,
title = NULL,
coords = NULL,
clusters = NULL,
hover_text = NULL,
hover_config = NULL,
cluster_colors = NULL
)Arguments
- analysis_result
A list containing semantic analysis results from functions like semantic_similarity_analysis(), semantic_document_clustering(), or reduce_dimensions().
- plot_type
Type of visualization: "similarity" for heatmap, "dimensionality_reduction" for scatter plot, or "clustering" for cluster visualization (default: "similarity").
- data_labels
Optional character vector of labels for data points (default: NULL).
- color_by
Optional variable to color points by in scatter plots (default: NULL).
- height
The height of the resulting Plotly plot, in pixels (default: 600).
- width
The width of the resulting Plotly plot, in pixels (default: 800).
- title
Optional custom title for the plot (default: NULL).
- coords
Optional pre-computed coordinates for dimensionality reduction plots (default: NULL).
- clusters
Optional cluster assignments vector (default: NULL).
- hover_text
Optional custom hover text for points (default: NULL).
- hover_config
Optional hover configuration list (default: NULL).
- cluster_colors
Optional color palette for clusters (default: NULL).
Examples
if (interactive()) {
texts <- c("machine learning", "deep learning", "artificial intelligence")
result <- semantic_similarity_analysis(texts)
plot <- plot_semantic_viz(result, plot_type = "similarity")
print(plot)
}