Fix ProgressMeter usage and delay plot generation

ChrisRackauckas · claude · ChrisRackauckas · commit cb3ac54eb589 · 2025-08-07T20:00:40.000-04:00
- Fix ProgressMeter.update\! to use 'desc' parameter instead of 'description' - Remove make_plot parameter from autotune_setup - Move plot generation from autotune_setup to plot(results) method - Remove plot uploading from GitHub sharing (plots not shared anymore) - Simplify AutotuneResults struct to only contain results_df and sysinfo - Update documentation to reflect on-demand plot generation 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <noreply@anthropic.com>
diff --git a/lib/LinearSolveAutotune/README.md b/lib/LinearSolveAutotune/README.md
@@ -26,7 +26,7 @@ share_results(results)
 - **Multi-size Testing**: Flexible size categories from small to very large matrices
 - **Element Type Support**: Tests with Float32, Float64, ComplexF32, ComplexF64
 - **GPU Support**: Automatically detects and benchmarks GPU algorithms if available
-- **Performance Visualization**: Creates plots showing algorithm performance
+- **Performance Visualization**: Generate plots on demand with `plot(results)`
 - **Community Sharing**: Optional telemetry to help improve algorithm selection
 
 ## Size Categories
@@ -135,7 +135,6 @@ If you prefer using a token:
 ```julia
 autotune_setup(;
     sizes = [:small, :medium, :large],
-    make_plot = true,
     set_preferences = true,
     samples = 5,
     seconds = 0.5,
@@ -146,15 +145,14 @@ autotune_setup(;
 
 **Parameters:**
 - `sizes`: Vector of size categories to test
-- `make_plot`: Generate performance plots
 - `set_preferences`: Update LinearSolve preferences
 - `samples`: Number of benchmark samples per test
 - `seconds`: Maximum time per benchmark
 - `eltypes`: Element types to benchmark
 - `skip_missing_algs`: Continue if algorithms are missing
 
 **Returns:**
-- `results`: AutotuneResults object containing benchmark data, system info, and plots
+- `results`: AutotuneResults object containing benchmark data and system info
 
 ### `share_results`
 
diff --git a/lib/LinearSolveAutotune/src/LinearSolveAutotune.jl b/lib/LinearSolveAutotune/src/LinearSolveAutotune.jl
@@ -38,7 +38,6 @@ include("preferences.jl")
 struct AutotuneResults
     results_df::DataFrame
     sysinfo::Dict
-    plots::Union{Nothing, Dict}
 end
 
 # Display method for AutotuneResults
@@ -91,14 +90,17 @@ end
 
 # Plot method for AutotuneResults
 function Plots.plot(results::AutotuneResults; kwargs...)
-    if results.plots === nothing || isempty(results.plots)
-        @warn "No plots available in results. Run autotune_setup with make_plot=true"
+    # Generate plots from the results data
+    plots_dict = create_benchmark_plots(results.results_df)
+    
+    if plots_dict === nothing || isempty(plots_dict)
+        @warn "No data available for plotting"
         return nothing
     end
     
     # Create a composite plot from all element type plots
     plot_list = []
-    for (eltype_name, p) in results.plots
+    for (eltype_name, p) in plots_dict
         push!(plot_list, p)
     end
     
@@ -121,7 +123,6 @@ end
 """
     autotune_setup(; 
         sizes = [:small, :medium, :large],
-        make_plot::Bool = true,
         set_preferences::Bool = true,
         samples::Int = 5,
         seconds::Float64 = 0.5,
@@ -138,7 +139,6 @@ Run a comprehensive benchmark of all available LU factorization methods and opti
 # Arguments
 
   - `sizes = [:small, :medium, :large]`: Size categories to test. Options: :small (5-20), :medium (20-300), :large (300-1000), :big (10000-100000)
-  - `make_plot::Bool = true`: Generate performance plots for each element type
   - `set_preferences::Bool = true`: Update LinearSolve preferences with optimal algorithms
   - `samples::Int = 5`: Number of benchmark samples per algorithm/size
   - `seconds::Float64 = 0.5`: Maximum time per benchmark
@@ -170,14 +170,13 @@ share_results(results)
 """
 function autotune_setup(;
         sizes = [:small, :medium, :large],
-        make_plot::Bool = true,
         set_preferences::Bool = true,
         samples::Int = 5,
         seconds::Float64 = 0.5,
         eltypes = (Float32, Float64, ComplexF32, ComplexF64),
         skip_missing_algs::Bool = false)
     @info "Starting LinearSolve.jl autotune setup..."
-    @info "Configuration: sizes=$sizes, make_plot=$make_plot, set_preferences=$set_preferences"
+    @info "Configuration: sizes=$sizes, set_preferences=$set_preferences"
     @info "Element types to benchmark: $(join(eltypes, ", "))"
 
     # Get system information
@@ -243,23 +242,12 @@ function autotune_setup(;
         set_algorithm_preferences(categories)
     end
 
-    # Create plots if requested
-    plots_dict = nothing
-    plot_files = nothing
-    if make_plot
-        @info "Creating performance plots..."
-        plots_dict = create_benchmark_plots(results_df)
-        if !isempty(plots_dict)
-            plot_files = save_benchmark_plots(plots_dict)
-        end
-    end
-
     @info "Autotune setup completed!"
 
     sysinfo = get_detailed_system_info()
 
     # Return AutotuneResults object
-    return AutotuneResults(results_df, sysinfo, plots_dict)
+    return AutotuneResults(results_df, sysinfo)
 end
 
 """
@@ -305,7 +293,6 @@ function share_results(results::AutotuneResults)
     # Extract from AutotuneResults
     results_df = results.results_df
     sysinfo = results.sysinfo
-    plots_dict = results.plots
     
     # Get system info
     system_info = sysinfo
@@ -342,14 +329,8 @@ function share_results(results::AutotuneResults)
     # Format results
     markdown_content = format_results_for_github(results_df, system_info, categories)
     
-    # Process plots if available
-    plot_files = nothing
-    if plots_dict !== nothing && !isempty(plots_dict)
-        plot_files = save_benchmark_plots(plots_dict)
-    end
-    
-    # Upload to GitHub
-    upload_to_github(markdown_content, plot_files, github_auth, results_df, system_info, categories)
+    # Upload to GitHub (without plots)
+    upload_to_github(markdown_content, nothing, github_auth, results_df, system_info, categories)
     
     @info "✅ Thank you for contributing to the LinearSolve.jl community!"
 end
diff --git a/lib/LinearSolveAutotune/src/benchmarking.jl b/lib/LinearSolveAutotune/src/benchmarking.jl
@@ -120,7 +120,7 @@ function benchmark_algorithms(matrix_sizes, algorithms, alg_names, eltypes;
                 for (alg, name) in zip(compatible_algs, compatible_names)
                     # Update progress description
                     ProgressMeter.update!(progress, 
-                        description="Benchmarking $name on $(n)×$(n) $eltype matrix: ")
+                        desc="Benchmarking $name on $(n)×$(n) $eltype matrix: ")
                     
                     gflops = 0.0
                     success = true
diff --git a/lib/LinearSolveAutotune/src/telemetry.jl b/lib/LinearSolveAutotune/src/telemetry.jl
@@ -245,12 +245,13 @@ function format_detailed_results_markdown(df::DataFrame)
 end
 
 """
-    upload_to_github(content::String, plot_files::Union{Nothing, Tuple, Dict}, auth_info::Tuple,
+    upload_to_github(content::String, plot_files, auth_info::Tuple,
                      results_df::DataFrame, system_info::Dict, categories::Dict)
 
 Create a GitHub issue with benchmark results for community data collection.
+Note: plot_files parameter is kept for compatibility but not used.
 """
-function upload_to_github(content::String, plot_files::Union{Nothing, Tuple, Dict}, auth_info::Tuple,
+function upload_to_github(content::String, plot_files, auth_info::Tuple,
                          results_df::DataFrame, system_info::Dict, categories::Dict)
     
     auth_method, auth_data = auth_info
@@ -272,61 +273,14 @@ function upload_to_github(content::String, plot_files::Union{Nothing, Tuple, Dic
         target_repo = "SciML/LinearSolve.jl"
         issue_number = 669  # The existing issue for collecting autotune results
         
-        # First, upload plots to a gist if available
-        gist_url = nothing
-        raw_urls = Dict{String, String}()
-        plot_links = ""
-        
-        if plot_files !== nothing
-            @info "📊 Uploading plots to GitHub Gist..."
-            
-            # Get element type for labeling
-            eltype_str = if !isempty(results_df)
-                unique_eltypes = unique(results_df.eltype)
-                join(unique_eltypes, ", ")
-            else
-                "Mixed"
-            end
-            
-            if auth_method == :gh_cli
-                gist_url, raw_urls = upload_plots_to_gist_gh(plot_files, eltype_str)
-            elseif auth_method == :token
-                gist_url, raw_urls = upload_plots_to_gist(plot_files, auth_data, eltype_str)
-            end
-            
-            if gist_url !== nothing
-                # Add plot links section to the content
-                plot_links = """
-                
-                ### 📊 Benchmark Plots
-                
-                View all plots in the gist: [Benchmark Plots Gist]($gist_url)
-                
-                """
-                
-                # Embed PNG images directly in the markdown if we have raw URLs
-                for (name, url) in raw_urls
-                    if endswith(name, ".png")
-                        plot_links *= """
-                        #### $name
-                        ![$(name)]($url)
-                        
-                        """
-                    end
-                end
-                
-                plot_links *= "---\n"
-            end
-        end
-        
         # Construct comment body
         cpu_name = get(system_info, "cpu_name", "unknown")
         os_name = get(system_info, "os", "unknown")
         timestamp = Dates.format(Dates.now(), "yyyy-mm-dd HH:MM")
         
         comment_body = """
         ## Benchmark Results: $cpu_name on $os_name ($timestamp)
-        $plot_links
+        
         $content
 
         ---
@@ -350,9 +304,6 @@ function upload_to_github(content::String, plot_files::Union{Nothing, Tuple, Dic
 
         if issue_url !== nothing
             @info "✅ Successfully added benchmark results to issue: $issue_url"
-            if gist_url !== nothing
-                @info "📊 Plots available at: $gist_url"
-            end
             @info "🔗 Your benchmark data has been shared with the LinearSolve.jl community!"
             @info "💡 View all community benchmark data: https://github.com/SciML/LinearSolve.jl/issues/669"
         else
