docs: rewrite docs/api plot.rst for the functional API; drop dead data.rst entries

docs/api/data.rst

@@ -5,8 +5,7 @@ Data Structures
 2D Data Structures
 ------------------
 
-Two-dimensional data structures store and mask 2D arrays containing data (e.g. images) and
-grids of (y,x) Cartesian coordinates.
+Two-dimensional data structures store and mask 2D arrays containing data (e.g. images).
 
 .. currentmodule:: autocti
 
@@ -17,8 +16,6 @@ grids of (y,x) Cartesian coordinates.
 
    Mask2D
    Array2D
-   Grid2D
-   Grid2DIrregular
 
 Charge Injection Imaging
 ------------------------
@@ -36,8 +33,7 @@ For charge injection datasets taken with a CCD (or similar imaging device).
 1D Data Structures
 ------------------
 
-One-dimensional data structures store and mask 1D arrays containing data (e.g. 1D CTI datasets
-images) and grids of (y,x) Cartesian coordinates.
+One-dimensional data structures store and mask 1D arrays containing data (e.g. 1D CTI datasets).
 
 .. autosummary::
    :toctree: _autosummary
@@ -47,7 +43,6 @@ images) and grids of (y,x) Cartesian coordinates.
    Mask1D
    Array1D
    ArrayIrregular
-   Grid1D
 
 Dataset 1D
 ----------
@@ -58,6 +53,5 @@ For 1D datasets.
    :toctree: generated/
 
    Dataset1D
-   LayoutDataset1D
-   SettingsDataset1D
+   Layout1D
    SimulatorDataset1D

docs/api/plot.rst

@@ -2,133 +2,129 @@
 Plotting
 ========
 
-**PyAutoCTI** custom visualization library.
+Create figures and subplots of **PyAutoCTI** datasets, fits and non-linear search results.
 
-Step-by-step Juypter notebook guides illustrating all objects listed on this page are
-provided on the `autocti_workspace: plot tutorials <https://github.com/Jammy2211/autocti_workspace/tree/release/notebooks/plot>`_ and
-it is strongly recommended you use those to learn plot customization.
+The plotting API is **functional**: import ``autocti.plot`` and call a plot function directly, passing it the
+dataset or fit to plot. There are no ``Plotter`` classes to configure first.
+
+.. code-block:: python
+
+   import autocti.plot as aplt
+
+   aplt.subplot_imaging_ci(dataset=dataset)
+   aplt.subplot_fit_ci(fit=fit, output_path="output", output_format="png")
+
+By default a figure is shown interactively. Pass ``output_path`` and ``output_format`` (e.g. ``"png"`` or
+``"pdf"``) to write it to disk instead.
 
 **Examples / Tutorials:**
 
-- `autocti_workspace: plot tutorials <https://github.com/Jammy2211/autocti_workspace/tree/release/notebooks/plot>`_
+- `autocti_workspace: plot tutorials <https://github.com/PyAutoLabs/autocti_workspace/tree/main/notebooks/plot>`_
 
-Plotters [aplt]
----------------
+Dataset 1D [aplt]
+-----------------
 
-Create figures and subplots showing quantities of standard **PyAutoCTI** objects.
+Plot a one-dimensional CTI dataset (``Dataset1D``) and its fit (``FitDataset1D``).
 
 .. currentmodule:: autocti.plot
 
+**Dataset:**
+
 .. autosummary::
    :toctree: _autosummary
-   :template: custom-class-template.rst
-   :recursive:
 
-    Array2DPlotter
-    Array1DPlotter
-    YX1DPlotter
-    Dataset1DPlotter
-    FitDataset1DPlotter
-    ImagingCIPlotter
-    FitImagingCIPlotter
-    MultiFigurePlotter
-    MultiYX1DPlotter
-
-Non-linear Search Plotters [aplt]
----------------------------------
+   figure_dataset_1d_data
+   subplot_dataset_1d
+   subplot_dataset_1d_list
 
-Create figures and subplots of non-linear search specific visualization of every search algorithm supported
-by **PyAutoCTI**.
-
-.. currentmodule:: autocti.plot
+**Fit:**
 
 .. autosummary::
    :toctree: _autosummary
-   :template: custom-class-template.rst
-   :recursive:
 
-   NestPlotter
-   MCMCPlotter
-   MLEPlotter
+   figure_fit_dataset_1d
+   subplot_fit_dataset_1d
+   subplot_fit_dataset_1d_list
+   fits_fit_dataset_1d
 
-Plot Customization [aplt]
--------------------------
+Charge Injection Imaging [aplt]
+-------------------------------
 
-Customize figures created via ``Plotter`` objects, including changing ``matplotlib`` settings and adding
-visuals to figures.
+Plot charge injection imaging (``ImagingCI``) and its fit (``FitImagingCI``), either the whole frame or one
+region of it (e.g. the parallel FPR or EPER).
 
-.. currentmodule:: autocti.plot
+**Dataset:**
 
 .. autosummary::
    :toctree: _autosummary
-   :template: custom-class-template.rst
-   :recursive:
 
-   MatPlot1D
-   MatPlot2D
-   Include1D
-   Include2D
-   Visuals1D
-   Visuals2D
+   figure_imaging_ci_data_region
+   figure_pre_cti_data_residual_map
+   subplot_imaging_ci
+   subplot_imaging_ci_region
+   subplot_imaging_ci_data_binned
+   subplot_imaging_ci_list
+   subplot_imaging_ci_data_region_list
 
-Matplot Lib Wrappers [aplt]
----------------------------
+**Fit:**
 
-Wrappers for every ``matplotlib`` function used by a ``Plotter``, allowing for detailed customization of
-every figure and subplot.
+.. autosummary::
+   :toctree: _autosummary
 
-.. currentmodule:: autocti.plot
+   figure_fit_ci_region
+   subplot_fit_ci
+   subplot_fit_ci_region
+   subplot_noise_scaling_map_dict
+   subplot_fit_ci_list
+   subplot_fit_ci_region_list
+   fits_fit_ci
+
+General Plot Functions [aplt]
+-----------------------------
 
-**Matplotlib Wrapper Base Objects:**
+Lower-level functions the plots above are built from, for plotting any array or (y,x) line yourself.
 
 .. autosummary::
    :toctree: _autosummary
-   :template: custom-class-template.rst
-   :recursive:
 
-   Units
-   Figure
-   Axis
-   Cmap
-   Colorbar
-   ColorbarTickParams
-   TickParams
-   YTicks
-   XTicks
-   Title
-   YLabel
-   XLabel
-   Legend
-   Output
-
-**Matplotlib Wrapper 1D Objects:**
+   plot_array
+   plot_yx
+   plot_cti_1d
+   subplot_save
+
+Non-linear Search Plots [aplt]
+------------------------------
+
+Plots of a completed non-linear search, re-exported from **PyAutoFit**. Pass them the ``Samples`` of a fit.
 
 .. autosummary::
    :toctree: _autosummary
-   :template: custom-class-template.rst
-   :recursive:
 
-   YXPlot
+   corner_cornerpy
+   corner_anesthetic
+   subplot_parameters
+   log_likelihood_vs_iteration
+
+Figure Output [aplt]
+--------------------
+
+The shared helper that shows a figure or writes it to ``path/filename.format``:
+
+.. autosummary::
+   :toctree: _autosummary
+
+   output_figure
+
+Visualization During a Fit [aplt]
+---------------------------------
 
-**Matplotlib Wrapper 2D Objects:**
+The classes a model-fit uses to write its on-the-fly visualization. You do not normally create these
+yourself; the ``Analysis`` classes do.
 
 .. autosummary::
    :toctree: _autosummary
    :template: custom-class-template.rst
    :recursive:
 
-   ArrayOverlay
-   GridScatter
-   GridPlot
-   VectorYXQuiver
-   PatchOverlay
-   VoronoiDrawer
-   OriginScatter
-   MaskScatter
-   BorderScatter
-   PositionsScatter
-   IndexScatter
-   MeshGridScatter
-   ParallelOverscanPlot
-   SerialPrescanPlot
-   SerialOverscanPlot
+   PlotterDataset1D
+   PlotterImagingCI