Plot System Overview

This page summarizes all plotting components used in the application. It includes 1D fits, multi-1D fits, 2D surface fits, confidence bands, residuals, MCMC diagnostics, and model comparison.

Global Plot Architecture

1. 1D Fit Plots (`plot.py`)

These are methods or utilities used for plotting raw 1D data, fitted curves, residuals, and confidence intervals.

Function / Method	Description	Location
`PlotWidget.plot_data(df)`	Plots raw 1D data (X, Y)	`plot.py`
`PlotWidget.plot_fit(x, y)`	Plots fitted curve on top of data	`plot.py`
`PlotAnalysis.toggle_residuals_plot()`	Toggles residuals plot (Y - fit)	`plot_analysis.py`
`PlotAnalysis.toggle_confidence_band()`	Toggles display of confidence intervals	`plot_analysis.py`

2. Multi-1D Fit (Fit per Y) (`plot2d.py`)

Plots used when performing a fit Z = f(X, Y_fixed) for multiple Y values.

Function	Description	Location
`plot_multi1d_data(ax, canvas, x, y, z, pw)`	Plots raw grouped data	`plot2d.py`
`plot_multi1d_fit(ax, canvas, fits, pw)`	Overlays fitted curves Z=f(X,Y_fixed)	`plot2d.py`
`PlotAnalysis.toggle_confidence_band()`	Confidence bands over Y slices	`plot_analysis.py`
`PlotAnalysis.toggle_residuals_plot()` (mode: multi 1D)	Residual plots per Y	`plot_analysis.py`

3. 2D Surface Fit (`plot2d.py`)

Used for true 2D fits where Z = f(X, Y), showing surface and contour.

Function	Description	Location
`plot_2d_series(x, y, z, strategy)`	Raw Z data as scatter grouped by strategy	`plot2d.py`
`plot_2d_surface_fit(ax, canvas, x, y, z, fit, pw)`	Fitted surface + 3D view + contour	`plot2d.py`
`PlotAnalysis.plot_conf_interval_2d()`	Confidence region for surface fit	`plot_analysis.py`

4. MCMC Diagnostic Plots (`mcmc_plot.py`)

Generated after a successful fit with emcee.

Function / Method	Description	Location
`MCMCPlot.show_mcmc_results(...)`	Dispatches the diagnostic plots	`mcmc_plot.py`
`MCMCPlot.plot_walkers(...)`	Shows evolution of walker chains per param	`mcmc_plot.py`
`MCMCPlot.plot_corner(...)`	Displays parameter correlations (corner)	`mcmc_plot.py`
`MCMCPlot.plot_autocorrelation(...)`	Autocorrelation of each parameter chain	`mcmc_plot.py`
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5. Comparison Plot (`fit_comparison.py`)

Plots used in comparison mode to overlay stored fits.

Function / Method	Description	Location
`FitComparisonManager.redraw_comparison_plot()`	Rebuilds the fit overlay plot	`fit_comparison.py`
`FitComparisonManager.create_comparison_plot()`	Initializes the matplotlib canvas	`fit_comparison.py`

6. Manual Fit Mode

In manual mode (sliders), the same plot functions are reused.

Function / Method	Description	Location
`PlotWidget.plot_data(df)`	Raw data (X, Y)	`plot.py`
`PlotWidget.plot_fit(x, y)`	Manual fit preview from sliders	`plot.py`

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Plot System Overview

Global Plot Architecture

1. 1D Fit Plots (plot.py)

2. Multi-1D Fit (Fit per Y) (plot2d.py)

3. 2D Surface Fit (plot2d.py)