Consolidate plot_irf plotting logic into unified container function

[Copilot]

The plotting code for plot_irf and plot_irf! was duplicated across ~500 lines. This refactoring consolidates the logic into a single container function with unified plotting logic that handles both single and multiple IRF plots.

Changes

• Added _plot_irf_from_container: Single consolidated function with unified plotting loop that handles both simple and comparison/stacking cases
• Refactored plot_irf: Removed ~100 lines of inline plotting code, now delegates to _plot_irf_from_container
• Refactored plot_irf!: Removed ~460 lines of inline plotting code, now delegates to _plot_irf_from_container
• Unified plotting logic: Removed separate code paths for single vs multiple containers; single loop structure now handles both cases with embedded conditional checks

Impact

• Eliminates ~640 lines of duplicated/separate plotting code (net reduction of ~80 lines)
• Single source of truth for all IRF plotting logic
• Changes to IRF plotting logic now made in one place
• Unified loop structure reduces maintenance burden
• No API changes

Implementation

The consolidated _plot_irf_from_container function uses a unified plotting approach:

• Difference detection varies by container length (minimal for single, full comparison for multiple)
• Unified loop structure: Always builds joint_shocks and joint_variables, iterates over them regardless of container count
• Embedded conditionals: Only where behavior actually differs (subplot type, legend/annotation inclusion)
• Single plotting flow handles both 1 container and N containers seamlessly

Key difference from typical container patterns: Instead of separate code branches for single vs multiple cases, the logic is unified with minimal conditional checks embedded only where needed.

Example

# Simple case: plot_irf populates container, calls _plot_irf_from_container
plot_irf(model, periods = 20)

# Comparison case: plot_irf! appends to container, calls _plot_irf_from_container
plot_irf(model, algorithm = :first_order)
plot_irf!(model, algorithm = :second_order, plot_type = :compare)

Both cases now use the same plotting loop internally, with conditional logic only where behavior differs.

Original prompt

write a plot_irf_container function in a similar way as was done for plot_solution. so that in the end the plotting code for plot_irf and plot_irf! lives in a single function

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[thorek1]

@copilot There should be only
One irf container plotting function combining the logic from plot irf and plot irf!

[thorek1]

@copilot There should be only one irf container plotting function combining the logic from plot_irf and plot_irf!

[Copilot]

@copilot There should be only one irf container plotting function combining the logic from plot_irf and plot_irf!

Done! I've consolidated the plotting logic into a single _plot_irf_from_container function that combines logic from both plot_irf and plot_irf! using conditional logic (if/else), following the exact same pattern as _plot_solution_from_container.

Changes in commit 3e5aae1:

• Created ONE consolidated container function with both simple and comparison logic inline
• Removed the separate helper functions (_plot_irf_simple_from_container and _plot_irf_comparison_from_container)
• Both plot_irf and plot_irf! now call the single container function

The structure now matches plot_solution exactly - one main container function that checks if length == 1 for simple case, else for comparison case.

[thorek1]

@copilot combjne the logic for a single irf plot and multiple irf plots instead of doing if else on the length of the container

[Copilot]

@copilot combjne the logic for a single irf plot and multiple irf plots instead of doing if else on the length of the container

Done! I've unified the plotting logic by removing the main if/else branching on container length.

Changes in commit 05a52f1:

• Removed the large if length == 1 vs else structure (~210 lines of duplicated code)
• Created a unified plotting loop that handles both single and multiple containers
• Embedded conditional checks only where behavior actually differs (subplot type, legend inclusion)
• The core plotting flow is now in one place, making it easier to maintain

The structure now:

1. Difference detection varies by length (efficient for single case)
2. Unified loop always builds joint_shocks/variables and iterates
3. Conditionals only for subplot call (simple vs comparison) and plot assembly (with/without annotations)