Create Scenario Plots (Matplotlib)

Python/matplotlib wrapper for creating visualizations from MINTe results. This function calls the underlying Python minte.create_scenario_plots() function and returns matplotlib figure objects.

Note: For native R plotting with ggplot2, use plot_prevalence() or plot_cases() instead, which provide the same functionality using R's ggplot2 graphics system.

Usage

create_scenario_plots_mpl(
  results,
  output_dir = NULL,
  plot_type = "both",
  predictor = NULL,
  window_size = 14L,
  plot_tight = FALSE,
  figsize_combined = c(12, 8),
  figsize_individual = c(10, 6),
  dpi = 300L
)

Arguments

results

A data frame of results (e.g., from results$prevalence).

output_dir

Character. Directory to save plots. If NULL, plots are returned but not saved.

plot_type

Character. Type of plot: "individual", "combined", or "both".

predictor

Character. Predictor type ("prevalence" or "cases"). Auto-detected if NULL.

window_size

Integer. Days per timestep. Default 14.

plot_tight

Logical. Use tight y-axis scaling. Default FALSE.

figsize_combined

Numeric vector of length 2. Figure size for combined plot.

figsize_individual

Numeric vector of length 2. Figure size for individual plots.

dpi

Integer. DPI for saved figures. Default 300.

Value

A list of matplotlib figure objects (Python objects). These can be saved to files but are not directly viewable in R graphics devices.

See also

• plot_prevalence() for native R/ggplot2 prevalence plots

• plot_cases() for native R/ggplot2 cases plots

Examples

if (FALSE) { # \dontrun{
results <- run_minter_scenarios(...)
# Save matplotlib plots to files
plots <- create_scenario_plots_mpl(
  results$prevalence,
  output_dir = "plots/",
  plot_type = "both"
)

# For interactive R plotting, use the native functions instead:
p <- plot_prevalence(results)
print(p)
} # }