Merge pull request #244 from Jammy2211/feature/plot-improvements-5

Plot improvements: DPI config, Delaunay aspect ratio, tick rounding, source vmax

Author: Jammy2211

autoarray/config/visualize/general.yaml

@@ -1,5 +1,6 @@
 general:
   backend: default                      # The matplotlib backend used for visualization. `default` uses the system default, can specify specific backend (e.g. TKAgg, Qt5Agg, WXAgg).
+  dpi: 150                              # Resolution in dots per inch used when saving figures. Lower values reduce file size (e.g. 150 gives ~50% smaller files than 300 with negligible quality loss for diagnostic subplots).
   imshow_origin: upper                  # The `origin` input of `imshow`, determining if pixel values are ascending or descending on the y-axis.
   log10_min_value: 1.0e-4               # If negative values are being plotted on a log10 scale, values below this value are rounded up to it (e.g. to remove negative values).
   log10_max_value: 1.0e99               # If positive values are being plotted on a log10 scale, values above this value are rounded down to it.

autoarray/inversion/plot/inversion_plots.py

@@ -116,13 +116,18 @@ def _recon_array():
 
     # panels 4-5: source reconstruction zoomed / unzoomed
     pixel_values = inversion.reconstruction_dict[mapper]
+    try:
+        recon_vmax = float(np.max(np.asarray(_recon_array())))
+    except Exception:
+        recon_vmax = None
     plot_mapper(
         mapper,
         solution_vector=pixel_values,
         ax=axes[4],
-        title="Source Reconstruction",
+        title="Source Plane (Zoom)",
         colormap=colormap,
         use_log10=use_log10,
+        vmax=recon_vmax,
         zoom_to_brightest=True,
         mesh_grid=mesh_grid,
         lines=lines,
@@ -131,9 +136,10 @@ def _recon_array():
         mapper,
         solution_vector=pixel_values,
         ax=axes[5],
-        title="Source Reconstruction (Unzoomed)",
+        title="Source Plane (No Zoom)",
         colormap=colormap,
         use_log10=use_log10,
+        vmax=recon_vmax,
         zoom_to_brightest=False,
         mesh_grid=mesh_grid,
         lines=lines,
@@ -316,7 +322,7 @@ def subplot_mappings(
         mapper,
         solution_vector=pixel_values,
         ax=axes[2],
-        title="Source Reconstruction",
+        title="Source Plane (Zoom)",
         colormap=colormap,
         use_log10=use_log10,
         zoom_to_brightest=True,
@@ -327,7 +333,7 @@ def subplot_mappings(
         mapper,
         solution_vector=pixel_values,
         ax=axes[3],
-        title="Source Reconstruction (Unzoomed)",
+        title="Source Plane (No Zoom)",
         colormap=colormap,
         use_log10=use_log10,
         zoom_to_brightest=False,

autoarray/inversion/plot/mapper_plots.py

@@ -18,6 +18,8 @@ def plot_mapper(
     output_format: str = "png",
     colormap=None,
     use_log10: bool = False,
+    vmin=None,
+    vmax=None,
     mesh_grid=None,
     lines=None,
     line_colors=None,
@@ -63,6 +65,8 @@ def plot_mapper(
             title=title,
             colormap=colormap,
             use_log10=use_log10,
+            vmin=vmin,
+            vmax=vmax,
             zoom_to_brightest=zoom_to_brightest,
             lines=numpy_lines(lines),
             line_colors=line_colors,

autoarray/plot/inversion.py

@@ -119,7 +119,7 @@ def plot_inversion_reconstruction(
     elif isinstance(
         mapper.interpolator, (InterpolatorDelaunay, InterpolatorKNearestNeighbor)
     ):
-        _plot_delaunay(ax, pixel_values, mapper, norm, colormap, is_subplot=is_subplot)
+        _plot_delaunay(ax, pixel_values, mapper, norm, colormap, extent, is_subplot=is_subplot)
 
     # --- overlays --------------------------------------------------------------
     if lines is not None:
@@ -230,7 +230,7 @@ def _plot_rectangular(ax, pixel_values, mapper, norm, colormap, extent, is_subpl
         _apply_colorbar(im, ax, is_subplot=is_subplot)
 
 
-def _plot_delaunay(ax, pixel_values, mapper, norm, colormap, is_subplot=False):
+def _plot_delaunay(ax, pixel_values, mapper, norm, colormap, extent, is_subplot=False):
     """Render a Delaunay or KNN pixelization reconstruction onto *ax*.
 
     Uses ``ax.tripcolor`` with Gouraud shading so that the reconstructed
@@ -252,10 +252,19 @@ def _plot_delaunay(ax, pixel_values, mapper, norm, colormap, is_subplot=False):
         ``None`` for automatic scaling.
     colormap
         Matplotlib colormap name.
+    extent
+        ``[xmin, xmax, ymin, ymax]`` spatial extent; used to set the axes
+        aspect ratio to match rectangular pixelization plots.
     is_subplot
         When ``True`` uses ``labelsize_subplot`` from config for the colorbar
         tick labels (matches the behaviour of :func:`~autoarray.plot.array.plot_array`).
     """
+    xmin, xmax, ymin, ymax = extent
+    x_range = abs(xmax - xmin)
+    y_range = abs(ymax - ymin)
+    box_aspect = (x_range / y_range) if y_range > 0 else 1.0
+    ax.set_aspect(box_aspect, adjustable="box")
+
     mesh_grid = mapper.source_plane_mesh_grid
 
     if hasattr(mesh_grid, "array"):

autoarray/plot/utils.py

@@ -419,7 +419,7 @@ def save_figure(
     path: str,
     filename: str,
     format: str = "png",
-    dpi: int = 300,
+    dpi: Optional[int] = None,
     structure=None,
 ) -> None:
     """
@@ -448,6 +448,10 @@ def save_figure(
         of ``fig.savefig``. Callers do not need to pass this; ``plot_array``
         supplies it automatically from the input array.
     """
+    if dpi is None:
+        from autoconf import conf
+        dpi = int(conf.instance["visualize"]["general"]["general"]["dpi"])
+
     if path:
         os.makedirs(path, exist_ok=True)
         formats = format if isinstance(format, (list, tuple)) else [format]
@@ -717,11 +721,20 @@ def _inward_ticks(lo: float, hi: float, factor: float, n: int) -> np.ndarray:
 
 
 def _round_ticks(values: np.ndarray, sig: int = 2) -> np.ndarray:
-    """Round *values* to *sig* significant figures."""
+    """Round *values* to *sig* significant figures.
+
+    After rounding, values smaller than 1e-10 of the overall tick scale are
+    clamped to zero so that floating-point noise (e.g. 1e-16 centre ticks on
+    symmetric extents) does not appear as scientific notation in labels.
+    """
     with np.errstate(divide="ignore", invalid="ignore"):
         nonzero = np.where(values != 0, np.abs(values), 1.0)
         mags = np.where(values != 0, 10 ** (sig - 1 - np.floor(np.log10(nonzero))), 1.0)
-    return np.round(values * mags) / mags
+    rounded = np.round(values * mags) / mags
+    scale = float(np.max(np.abs(rounded))) if len(rounded) > 0 else 1.0
+    if scale > 0:
+        rounded[np.abs(rounded) < scale * 1e-10] = 0.0
+    return rounded
 
 
 def _arcsec_labels(ticks) -> List[str]: