From dc75772cc0c0673ddb49f78a2d6e890d831e68da Mon Sep 17 00:00:00 2001
From: ShaunD137 <shaun.doherty@york.ac.uk>
Date: Fri, 10 Jul 2026 17:19:39 +0100
Subject: [PATCH 01/32] initial commit of voxel plotting

---
 src/sdf_xarray/dataarray_accessor.py | 163 +++++++++++++++++-
 src/sdf_xarray/plotting.py           | 240 ++++++++++++++++++++++++++-
 2 files changed, 388 insertions(+), 15 deletions(-)

diff --git a/src/sdf_xarray/dataarray_accessor.py b/src/sdf_xarray/dataarray_accessor.py
index 2377105..9abde5e 100644
--- a/src/sdf_xarray/dataarray_accessor.py
+++ b/src/sdf_xarray/dataarray_accessor.py
@@ -3,14 +3,46 @@
 from types import MethodType
 from typing import TYPE_CHECKING
 
+import numpy as np
 import xarray as xr
 from xarray.plot.accessor import DataArrayPlotAccessor
 
-from .plotting import animate, show
+from .plotting import animate, show, voxel_plot, _recover_vertex_coord
 
 if TYPE_CHECKING:
     from matplotlib.animation import FuncAnimation
 
+def _resize_ndarray(
+    arr: np.ndarray,
+    new_shape: tuple | list | np.ndarray,
+) -> np.ndarray:
+    """
+    Resizes a `numpy.ndarray` to another shape. The returned array must have the
+    same dimensionality as the input array.
+    Parameters
+    ----------
+    arr
+        The input array.
+    new_shape
+        The shape of the new `xarray.DataArray`, must be the same length as arr.shape.
+    """
+
+    from scipy.interpolate import RegularGridInterpolator  # noqa: PLC0415
+
+    if arr.ndim != len(new_shape):
+        raise ValueError(
+            f"The number of dimensions must match the input array. (original: {arr.ndim}, new: {len(new_shape)})"
+        )
+
+    old_grids = tuple(np.linspace(0, 1, size) for size in arr.shape)
+    new_grids = tuple(np.linspace(0, 1, size) for size in new_shape)
+    mesh = np.meshgrid(*new_grids, indexing="ij")
+    coords = np.stack(mesh, axis=-1)
+
+    return RegularGridInterpolator(old_grids, arr, bounds_error=False, fill_value=0)(
+        coords
+    )
+
 
 @xr.register_dataarray_accessor("epoch")
 class EpochAccessor:
@@ -35,18 +67,21 @@ def plot(self, *args, **kwargs) -> DataArrayPlotAccessor:
             Keyword arguments passed to `xarray.DataArray.plot`.
         """
         dims = self._obj.dims
-        is_not_2d_data = len(dims) != 2
-        is_time_dim_present = "time" in dims
-        is_x_or_y_specified_in_kwargs = "x" in kwargs or "y" in kwargs
 
-        if is_not_2d_data or is_time_dim_present or is_x_or_y_specified_in_kwargs:
+        if len(dims) == 1:
             return self._obj.plot(*args, **kwargs)
+        
+        elif len(dims) == 2:
+            updated_kwargs = dict(kwargs)
+            updated_kwargs.setdefault("x", dims[0])
+            updated_kwargs.setdefault("y", dims[1])
+            return self._obj.plot(*args, **updated_kwargs)
 
-        updated_kwargs = dict(kwargs)
-        updated_kwargs.setdefault("x", dims[0])
-        updated_kwargs.setdefault("y", dims[1])
+        elif len(dims) == 3:
+            return voxel_plot(self._obj, *args, **kwargs)
 
-        return self._obj.plot(*args, **updated_kwargs)
+        else:
+            return self._obj.plot(*args, **kwargs)
 
     def animate(self, *args, **kwargs) -> FuncAnimation:
         """Generate animations of Epoch data.
@@ -72,3 +107,113 @@ def animate(self, *args, **kwargs) -> FuncAnimation:
         anim.show = MethodType(show, anim)
 
         return anim
+
+
+    def resize(
+            self,
+            new_shape,
+        ) -> xr.DataArray:
+        """
+        Resizes a `xarray.DataArray` to another shape. The returned array must have the
+        same dimensionality as the input array.
+
+        Parameters
+        ----------
+        new_shape
+            The shape of the new `xarray.DataArray`, must be the same length as self.shape.
+        """
+
+        da = self._obj
+
+        # Create resized data and Dataset
+        data_resized = _resize_ndarray(da.values, new_shape)
+        da_resized = da.copy()
+        da_resized = xr.DataArray(
+            data=data_resized,
+            dims=da.dims,
+            attrs=da.attrs,
+        )
+
+        original_cell_size_da = []
+
+        # Resize coordinates and add to DataArray
+        for i in range(len(da_resized.dims)):
+            coord = list(da_resized.dims)[i]
+
+            if coord[-4:] == "_mid":
+                # If the coordinate is a midpoint coordinate, care must be taken to resize correctly
+                vertex_coord = _recover_vertex_coord(da[coord])
+                vertex_coord_resized = np.linspace(vertex_coord[0], vertex_coord[-1], new_shape[i]+1)
+                # Turn the vertex coord back into a midpoint coord
+                da_resized[coord] = ((np.roll(vertex_coord_resized, 1) + vertex_coord_resized)/2)[1:]
+            else:
+                # If not, the coordinate can be simply resized
+                coord_min = da[coord][0].values
+                coord_max = da[coord][-1].values
+                da_resized[coord] = np.linspace(coord_min, coord_max, new_shape[i])
+
+            da_resized[coord].attrs = da[coord].attrs
+
+            # Add original information as attributes 
+            if "original_shape" not in da.attrs:
+                da_resized[coord].attrs["original_size"] = da.shape[i]
+                original_cell_size = float((da[coord][1] - da[coord][0]).values)
+                original_cell_size_da.append(original_cell_size)
+                da_resized[coord].attrs["original_cell_size"] = original_cell_size
+        
+        if "original_shape" not in da.attrs:
+            da_resized.attrs["original_shape"] = da.shape
+            da_resized.attrs["original_cell_size"] = tuple(original_cell_size_da)
+
+        return da_resized
+
+
+    def limit(
+        self,
+        limits,
+        drop:bool = True,
+    ) -> xr.DataArray:
+        """
+        Drops values outside the specified limits.
+
+        Parameters
+        ----------
+        limits
+            Array-like list of limits.
+        drop
+            Bool specifying whether to drop the co-ordinates outside the limits (default = True).
+        """
+        da = self._obj
+        limits = list(limits)
+
+        # List of dimension names
+        dims = da.dims
+
+        original_lims_da = []
+        for i in range(len(dims)):
+            limits[i] = list(limits[i])
+
+            # Find the original limits of the dataarray
+            original_lims = (
+                float(da[dims[i]].values[0]),
+                float(da[dims[i]].values[-1])
+            )
+            original_lims_da.append(original_lims)
+            if "original_lims" not in da[dims[i]].attrs:
+                da[dims[i]].attrs["original_lims"] = original_lims
+
+            # If None is passed into limit, will assume the existing limit
+            if limits[i][0] == None:
+                limits[i][0]  = original_lims[0]
+            if limits[i][-1] == None:
+                limits[i][-1] = original_lims[1]
+
+            # Limit dataarray
+            da = da.where(
+                da[dims[i]] >= limits[i][0], drop = drop).where(
+                da[dims[i]] <= limits[i][1], drop = drop)
+            
+        if "original_lims" not in da.attrs:
+            da.attrs["original_lims"]  = tuple(original_lims_da)
+
+        return da
\ No newline at end of file
diff --git a/src/sdf_xarray/plotting.py b/src/sdf_xarray/plotting.py
index 723b6e4..e8cfd97 100644
--- a/src/sdf_xarray/plotting.py
+++ b/src/sdf_xarray/plotting.py
@@ -56,6 +56,47 @@ def get_frame_title(
     return f"{title_custom}{title_t_axis}{title_sdf}"
 
 
+def get_axis_label(dim: xr.DataArray):
+    label = f"{dim.long_name} [{dim.units}]"
+    return label
+
+
+def _recover_vertex_coord(w_mid):
+    # Takes a midpoint coordinate, returns a vertex coordinate
+    w_size = w_mid.size
+    dw = w_mid[1] - w_mid[0]
+    w = np.zeros(w_mid.size + 1)
+    w[:w_size] = w_mid - dw/2
+    w[w_size] = w[w_size-1] + dw
+    return w
+
+
+def shift_cmap(cmap, vmin, vmax, vcenter, N=1024):
+    """
+    Creates a new colourmap where the visual center of the original 
+    colourmap is shifted to a specific data value.
+    """
+    import matplotlib.pyplot as plt
+    import matplotlib.colors as mc
+
+    # get the original colourmap
+    if type(cmap) == str:
+        cmap = plt.get_cmap(cmap)
+    
+    midpoint = (vcenter - vmin) / (vmax - vmin)
+    lower_size = int(N * midpoint)
+    upper_size = N - lower_size
+    
+    bottom_colors = cmap(np.linspace(0.0, 0.5, lower_size))
+    top_colors = cmap(np.linspace(0.5, 1.0, upper_size))
+    new_colors = np.vstack((bottom_colors, top_colors))
+    
+    new_cmap = mc.ListedColormap(new_colors, name=f"shifted_{cmap.name}")
+
+    return new_cmap
+
+
+
 def calculate_window_boundaries(
     data: xr.DataArray,
     xlim: tuple[float, float] | None = None,
@@ -135,7 +176,142 @@ def _set_axes_labels(ax: plt.Axes, axis_kwargs: dict) -> None:
         ax.set_ylabel(axis_kwargs["ylabel"])
 
 
-def _setup_2d_plot(
+def voxel_plot(
+        da,
+        vmin = None,
+        vmax = None,
+        vcenter = None,
+        mask = None,
+        xlim = (None, None),
+        ylim = (None, None),
+        zlim = (None, None),
+        aspect = "equal",
+        elev = 30,
+        azim = -60,
+        cmap = "viridis",
+        cbar_scale = 0.9,
+    ):
+    """
+    Will take 3 dimensional data and plot it as voxels.
+
+    Parameters
+    ----------
+    da
+        DataArray to be plotted.
+    vmin
+        Minimum value. If `mask` is not stated, will be used to define the mask.
+    vmax
+        Maximum value. If `mask` is not stated, will be used to define the mask.
+    vcenter
+        Center value of the colourmap. Useful for diverging colourmaps with non-symetrical data.
+    mask
+        Array of bools specifing which cells to show. Must be same size as `da`
+    xlim, ylim, zlim
+        Sets the limits of the plot.
+    aspect
+        Aspect ratio of the plot. "equal", "auto" or list of floats. (default = "equal")
+    elev
+        Elevation angle in degrees. (default = 30)
+    azim
+        Azimithul angle in degrees. (default = -60)
+    cmap
+        Colourmap (default = "viridis")
+    cbar_scale
+        Vertical scale of the colorbar (default = 0.9)
+    """
+    import matplotlib.pyplot as plt
+
+    print("Warning! voxel plots can be extremely intensive!")
+
+    # Limit arrays based on axis limits
+    da = da.epoch.limit((xlim, ylim, zlim))
+
+    dims = da.dims
+
+    # Create W_Grid from W_Grid_mid coords
+    x = _recover_vertex_coord(da[dims[0]])
+    y = _recover_vertex_coord(da[dims[1]])
+    z = _recover_vertex_coord(da[dims[2]])
+
+    # Create mesh
+    x_mesh, y_mesh, z_mesh = np.meshgrid(x, y, z, indexing="ij")
+
+    if vmin == None:
+        vmin = np.min(da.values)
+    if vmax == None:
+        vmax = np.max(da.values)
+
+    # Mask out data
+    if mask == None:
+        mask = (da > vmin) * (da < vmax)
+
+    # Plot the data array
+    fig = plt.figure(figsize=(8, 6))
+    ax = fig.add_subplot(projection='3d')
+    ax.view_init(elev, azim)
+
+    # Set axis labels
+    ax.set_xlabel(get_axis_label(da[dims[0]]))
+    ax.set_ylabel(get_axis_label(da[dims[1]]))
+    ax.set_zlabel(get_axis_label(da[dims[2]]))
+
+    # Find axis limits
+    xlim = list(xlim)
+    ylim = list(ylim)
+    zlim = list(zlim)
+    if xlim[0] == None:
+        xlim[0] = x.min()
+    if xlim[1] == None:
+        xlim[1] = x.max()
+    if ylim[0] == None:
+        ylim[0] = y.min()
+    if ylim[1] == None:
+        ylim[1] = y.max()
+    if zlim[0] == None:
+        zlim[0] = z.min()
+    if zlim[1] == None:
+        zlim[1] = z.max()
+
+    # Set aspect ratio  of plot
+    if aspect == "equal":
+        x_aspect = 1
+        y_aspect = 1
+        z_aspect = 1
+    elif aspect == "auto":
+        x_aspect = xlim[1] - xlim[0]
+        y_aspect = ylim[1] - ylim[0]
+        z_aspect = zlim[1] - zlim[0]
+    else:
+        x_aspect, y_aspect, z_aspect = aspect
+    ax.set_box_aspect((x_aspect, y_aspect, z_aspect))
+
+    # Limit axis of plot
+    ax.set_xlim(xlim[0], xlim[1])
+    ax.set_ylim(ylim[0], ylim[1])
+    ax.set_zlim(zlim[0], zlim[1])
+
+    # Colour bar and colour map
+    if vcenter is not None:
+        cmap = shift_cmap(cmap, vmin, vmax, vcenter)
+    norm = plt.Normalize(vmin = vmin, vmax = vmax)
+    cmap = plt.get_cmap(cmap)
+    colours = cmap(norm(da))
+    
+    sm = plt.cm.ScalarMappable(cmap=cmap, norm=norm)
+    sm.set_array([])  # Required for the colorbar to function
+    cbar_label = get_axis_label(da)
+    fig.colorbar(sm, ax=ax, label=cbar_label, shrink = cbar_scale, aspect = 20*cbar_scale)
+
+    ax.voxels(
+        x_mesh, y_mesh, z_mesh,
+        mask,
+        facecolors = colours,
+    )
+
+    return fig, ax
+
+
+def _setup_line_plot(
     data: xr.DataArray,
     ax: plt.Axes,
     coord_names: list[str],
@@ -145,7 +321,7 @@ def _setup_2d_plot(
     max_percentile: float,
     t: str,
 ) -> tuple[float, float]:
-    """Setup 2D plot initialization."""
+    """Line animation initialization."""
 
     kwargs.setdefault("x", coord_names[0])
 
@@ -161,7 +337,43 @@ def _setup_2d_plot(
     return global_min, global_max
 
 
-def _setup_3d_plot(
+def _setup_pcolormesh_plot(
+    data: xr.DataArray,
+    ax: plt.Axes,
+    coord_names: list[str],
+    kwargs: dict,
+    kwargs_original: dict,
+    axis_kwargs: dict,
+    min_percentile: float,
+    max_percentile: float,
+    t: str,
+) -> None:
+    """pcolormesh animation initialization."""
+    import matplotlib.pyplot as plt  # noqa: PLC0415
+
+    if "norm" not in kwargs:
+        global_min, global_max = compute_global_limits(
+            data, min_percentile, max_percentile
+        )
+        kwargs["norm"] = plt.Normalize(vmin=global_min, vmax=global_max)
+
+    kwargs["add_colorbar"] = False
+    kwargs.setdefault("x", coord_names[0])
+    kwargs.setdefault("y", coord_names[1])
+
+    argmin_time = np.unravel_index(np.argmin(data.values), data.shape)[0]
+    plot = data.isel({t: argmin_time}).plot(ax=ax, **kwargs)
+    kwargs["cmap"] = plot.cmap
+
+    _set_axes_labels(ax, axis_kwargs)
+
+    if kwargs_original.get("add_colorbar", True):
+        long_name = data.attrs.get("long_name")
+        units = data.attrs.get("units")
+        fig = plot.get_figure()
+        fig.colorbar(plot, ax=ax, label=f"{long_name} [{units}]")
+
+def _setup_voxel_plot(
     data: xr.DataArray,
     ax: plt.Axes,
     coord_names: list[str],
@@ -172,7 +384,10 @@ def _setup_3d_plot(
     max_percentile: float,
     t: str,
 ) -> None:
-    """Setup 3D plot initialization."""
+    """
+    Voxel animation initialization.
+    NOTE: this function exists for completeness, voxel plots don't work in animations yet
+    """
     import matplotlib.pyplot as plt  # noqa: PLC0415
 
     if "norm" not in kwargs:
@@ -262,7 +477,7 @@ def _generate_animation(
 
     global_min = global_max = None
     if data.ndim == 2:
-        global_min, global_max = _setup_2d_plot(
+        global_min, global_max = _setup_line_plot(
             data=data,
             ax=ax,
             coord_names=coord_names,
@@ -273,7 +488,7 @@ def _generate_animation(
             t=t,
         )
     elif data.ndim == 3:
-        _setup_3d_plot(
+        _setup_pcolormesh_plot(
             data=data,
             ax=ax,
             coord_names=coord_names,
@@ -284,6 +499,19 @@ def _generate_animation(
             max_percentile=max_percentile,
             t=t,
         )
+    elif data.ndim == 4:
+        raise NotImplementedError("Voxel animations are not currently supported.")
+        # _setup_voxel_plot(
+        #     data=data,
+        #     ax=ax,
+        #     coord_names=coord_names,
+        #     kwargs=kwargs,
+        #     kwargs_original=kwargs_original,
+        #     axis_kwargs=axis_kwargs,
+        #     min_percentile=min_percentile,
+        #     max_percentile=max_percentile,
+        #     t=t,
+        # )
 
     ax.set_title(get_frame_title(data, 0, display_sdf_name, title, t))
 

From 26d20ce0c664576aacd394353159400162d1b748 Mon Sep 17 00:00:00 2001
From: JoelLucaAdams <joelucadams@gmail.com>
Date: Sat, 11 Jul 2026 13:18:39 +0100
Subject: [PATCH 02/32] Add missing scipy dependency to docs and tests

---
 pyproject.toml |   2 +
 uv.lock        | 141 +++++++++++++++++++++++++++++++++++++++++++++++++
 2 files changed, 143 insertions(+)

diff --git a/pyproject.toml b/pyproject.toml
index 33b9c35..039d3c9 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -69,6 +69,7 @@ docs = [
   "sphinx-design>=0.7.0",
   "pooch>=1.8.2",
   "tqdm",
+  "scipy",
 ]
 build = ["cibuildwheel[uv]"]
 lint = ["ruff"]
@@ -80,6 +81,7 @@ test = [
   "tqdm",
   "pint",
   "pint-xarray",
+  "scipy",
 ]
 
 [project.entry-points."xarray.backends"]
diff --git a/uv.lock b/uv.lock
index 99d7307..1a4d309 100644
--- a/uv.lock
+++ b/uv.lock
@@ -2246,6 +2246,134 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/c4/1c/1dbe51782c0e1e9cfce1d1004752672d2d4629ea46945d19d731ad772b3b/ruff-0.14.11-py3-none-win_arm64.whl", hash = "sha256:649fb6c9edd7f751db276ef42df1f3df41c38d67d199570ae2a7bd6cbc3590f0", size = 12938644, upload-time = "2026-01-08T19:11:50.027Z" },
 ]
 
+[[package]]
+name = "scipy"
+version = "1.17.1"
+source = { registry = "https://pypi.org/simple" }
+resolution-markers = [
+    "python_full_version < '3.12'",
+]
+dependencies = [
+    { name = "numpy", marker = "python_full_version < '3.12'" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/7a/97/5a3609c4f8d58b039179648e62dd220f89864f56f7357f5d4f45c29eb2cc/scipy-1.17.1.tar.gz", hash = "sha256:95d8e012d8cb8816c226aef832200b1d45109ed4464303e997c5b13122b297c0", size = 30573822, upload-time = "2026-02-23T00:26:24.851Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/df/75/b4ce781849931fef6fd529afa6b63711d5a733065722d0c3e2724af9e40a/scipy-1.17.1-cp311-cp311-macosx_10_14_x86_64.whl", hash = "sha256:1f95b894f13729334fb990162e911c9e5dc1ab390c58aa6cbecb389c5b5e28ec", size = 31613675, upload-time = "2026-02-23T00:16:00.13Z" },
+    { url = "https://files.pythonhosted.org/packages/f7/58/bccc2861b305abdd1b8663d6130c0b3d7cc22e8d86663edbc8401bfd40d4/scipy-1.17.1-cp311-cp311-macosx_12_0_arm64.whl", hash = "sha256:e18f12c6b0bc5a592ed23d3f7b891f68fd7f8241d69b7883769eb5d5dfb52696", size = 28162057, upload-time = "2026-02-23T00:16:09.456Z" },
+    { url = "https://files.pythonhosted.org/packages/6d/ee/18146b7757ed4976276b9c9819108adbc73c5aad636e5353e20746b73069/scipy-1.17.1-cp311-cp311-macosx_14_0_arm64.whl", hash = "sha256:a3472cfbca0a54177d0faa68f697d8ba4c80bbdc19908c3465556d9f7efce9ee", size = 20334032, upload-time = "2026-02-23T00:16:17.358Z" },
+    { url = "https://files.pythonhosted.org/packages/ec/e6/cef1cf3557f0c54954198554a10016b6a03b2ec9e22a4e1df734936bd99c/scipy-1.17.1-cp311-cp311-macosx_14_0_x86_64.whl", hash = "sha256:766e0dc5a616d026a3a1cffa379af959671729083882f50307e18175797b3dfd", size = 22709533, upload-time = "2026-02-23T00:16:25.791Z" },
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+    { url = "https://files.pythonhosted.org/packages/f8/a1/c7932f91909759b0267f75fdea34e91309f96b895757534b76a90b6b4344/scipy-1.18.0-cp314-cp314t-musllinux_1_2_aarch64.whl", hash = "sha256:1a4441f15d620578772a49e5ab48c0ee1f7a0220e387110283062729136b2553", size = 35699541, upload-time = "2026-06-19T15:01:31.968Z" },
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+    { url = "https://files.pythonhosted.org/packages/31/8e/f04c68e39919a010d34f2ee1367fd705b0a25a02f609d755f0bfbc0a15fc/scipy-1.18.0-cp314-cp314t-win_amd64.whl", hash = "sha256:e40baea28ae7f5475c779741e2d90b1247c78531207b49c7030e698ff81cee3f", size = 37365390, upload-time = "2026-06-19T15:01:38.091Z" },
+    { url = "https://files.pythonhosted.org/packages/d5/19/969dc072906c84dd0a3b05dcf57ea750936087d7873549e408b35cfc3f97/scipy-1.18.0-cp314-cp314t-win_arm64.whl", hash = "sha256:368e0a705903c466aa5f08eefb39e6b1b6b2d659e7352a31fd9e2438365be0f8", size = 25279661, upload-time = "2026-06-19T15:01:40.817Z" },
+]
+
 [[package]]
 name = "sdf-xarray"
 source = { editable = "." }
@@ -2281,6 +2409,8 @@ dev = [
     { name = "pooch" },
     { name = "pytest" },
     { name = "ruff" },
+    { name = "scipy", version = "1.17.1", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" },
+    { name = "scipy", version = "1.18.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" },
     { name = "sphinx" },
     { name = "sphinx-argparse-cli" },
     { name = "sphinx-autobuild" },
@@ -2299,6 +2429,8 @@ docs = [
     { name = "pint" },
     { name = "pint-xarray" },
     { name = "pooch" },
+    { name = "scipy", version = "1.17.1", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" },
+    { name = "scipy", version = "1.18.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" },
     { name = "sphinx" },
     { name = "sphinx-argparse-cli" },
     { name = "sphinx-autobuild" },
@@ -2316,8 +2448,12 @@ lint = [
 test = [
     { name = "dask", extra = ["complete"] },
     { name = "matplotlib" },
+    { name = "pint" },
+    { name = "pint-xarray" },
     { name = "pooch" },
     { name = "pytest" },
+    { name = "scipy", version = "1.17.1", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version < '3.12'" },
+    { name = "scipy", version = "1.18.0", source = { registry = "https://pypi.org/simple" }, marker = "python_full_version >= '3.12'" },
     { name = "tqdm" },
 ]
 
@@ -2347,6 +2483,7 @@ dev = [
     { name = "pooch", specifier = ">=1.8.2" },
     { name = "pytest", specifier = ">=3.3.0" },
     { name = "ruff" },
+    { name = "scipy" },
     { name = "sphinx", specifier = ">=5.3" },
     { name = "sphinx-argparse-cli", specifier = ">=1.10.0" },
     { name = "sphinx-autobuild", specifier = ">=2025.8.25" },
@@ -2365,6 +2502,7 @@ docs = [
     { name = "pint" },
     { name = "pint-xarray" },
     { name = "pooch", specifier = ">=1.8.2" },
+    { name = "scipy" },
     { name = "sphinx", specifier = ">=5.3" },
     { name = "sphinx-argparse-cli", specifier = ">=1.10.0" },
     { name = "sphinx-autobuild", specifier = ">=2025.8.25" },
@@ -2380,8 +2518,11 @@ lint = [{ name = "ruff" }]
 test = [
     { name = "dask", extras = ["complete"] },
     { name = "matplotlib" },
+    { name = "pint" },
+    { name = "pint-xarray" },
     { name = "pooch", specifier = ">=1.8.2" },
     { name = "pytest", specifier = ">=3.3.0" },
+    { name = "scipy" },
     { name = "tqdm" },
 ]
 

From 64da60b0c90f9195e3cbebbe3b3c4b97de7a6b58 Mon Sep 17 00:00:00 2001
From: JoelLucaAdams <joelucadams@gmail.com>
Date: Sat, 11 Jul 2026 13:31:22 +0100
Subject: [PATCH 03/32] make voxel plotting pass ruff check

---
 src/sdf_xarray/dataarray_accessor.py | 54 +++++++++--------
 src/sdf_xarray/plotting.py           | 89 ++++++++++++++--------------
 2 files changed, 72 insertions(+), 71 deletions(-)

diff --git a/src/sdf_xarray/dataarray_accessor.py b/src/sdf_xarray/dataarray_accessor.py
index 9abde5e..aba2c66 100644
--- a/src/sdf_xarray/dataarray_accessor.py
+++ b/src/sdf_xarray/dataarray_accessor.py
@@ -7,11 +7,12 @@
 import xarray as xr
 from xarray.plot.accessor import DataArrayPlotAccessor
 
-from .plotting import animate, show, voxel_plot, _recover_vertex_coord
+from .plotting import _recover_vertex_coord, animate, show, voxel_plot
 
 if TYPE_CHECKING:
     from matplotlib.animation import FuncAnimation
 
+
 def _resize_ndarray(
     arr: np.ndarray,
     new_shape: tuple | list | np.ndarray,
@@ -70,18 +71,17 @@ def plot(self, *args, **kwargs) -> DataArrayPlotAccessor:
 
         if len(dims) == 1:
             return self._obj.plot(*args, **kwargs)
-        
-        elif len(dims) == 2:
+
+        if len(dims) == 2:
             updated_kwargs = dict(kwargs)
             updated_kwargs.setdefault("x", dims[0])
             updated_kwargs.setdefault("y", dims[1])
             return self._obj.plot(*args, **updated_kwargs)
 
-        elif len(dims) == 3:
+        if len(dims) == 3:
             return voxel_plot(self._obj, *args, **kwargs)
 
-        else:
-            return self._obj.plot(*args, **kwargs)
+        return self._obj.plot(*args, **kwargs)
 
     def animate(self, *args, **kwargs) -> FuncAnimation:
         """Generate animations of Epoch data.
@@ -108,11 +108,10 @@ def animate(self, *args, **kwargs) -> FuncAnimation:
 
         return anim
 
-
     def resize(
-            self,
-            new_shape,
-        ) -> xr.DataArray:
+        self,
+        new_shape,
+    ) -> xr.DataArray:
         """
         Resizes a `xarray.DataArray` to another shape. The returned array must have the
         same dimensionality as the input array.
@@ -143,9 +142,13 @@ def resize(
             if coord[-4:] == "_mid":
                 # If the coordinate is a midpoint coordinate, care must be taken to resize correctly
                 vertex_coord = _recover_vertex_coord(da[coord])
-                vertex_coord_resized = np.linspace(vertex_coord[0], vertex_coord[-1], new_shape[i]+1)
+                vertex_coord_resized = np.linspace(
+                    vertex_coord[0], vertex_coord[-1], new_shape[i] + 1
+                )
                 # Turn the vertex coord back into a midpoint coord
-                da_resized[coord] = ((np.roll(vertex_coord_resized, 1) + vertex_coord_resized)/2)[1:]
+                da_resized[coord] = (
+                    (np.roll(vertex_coord_resized, 1) + vertex_coord_resized) / 2
+                )[1:]
             else:
                 # If not, the coordinate can be simply resized
                 coord_min = da[coord][0].values
@@ -154,24 +157,23 @@ def resize(
 
             da_resized[coord].attrs = da[coord].attrs
 
-            # Add original information as attributes 
+            # Add original information as attributes
             if "original_shape" not in da.attrs:
                 da_resized[coord].attrs["original_size"] = da.shape[i]
                 original_cell_size = float((da[coord][1] - da[coord][0]).values)
                 original_cell_size_da.append(original_cell_size)
                 da_resized[coord].attrs["original_cell_size"] = original_cell_size
-        
+
         if "original_shape" not in da.attrs:
             da_resized.attrs["original_shape"] = da.shape
             da_resized.attrs["original_cell_size"] = tuple(original_cell_size_da)
 
         return da_resized
 
-
     def limit(
         self,
         limits,
-        drop:bool = True,
+        drop: bool = True,
     ) -> xr.DataArray:
         """
         Drops values outside the specified limits.
@@ -196,24 +198,24 @@ def limit(
             # Find the original limits of the dataarray
             original_lims = (
                 float(da[dims[i]].values[0]),
-                float(da[dims[i]].values[-1])
+                float(da[dims[i]].values[-1]),
             )
             original_lims_da.append(original_lims)
             if "original_lims" not in da[dims[i]].attrs:
                 da[dims[i]].attrs["original_lims"] = original_lims
 
             # If None is passed into limit, will assume the existing limit
-            if limits[i][0] == None:
-                limits[i][0]  = original_lims[0]
-            if limits[i][-1] == None:
+            if limits[i][0] is None:
+                limits[i][0] = original_lims[0]
+            if limits[i][-1] is None:
                 limits[i][-1] = original_lims[1]
 
             # Limit dataarray
-            da = da.where(
-                da[dims[i]] >= limits[i][0], drop = drop).where(
-                da[dims[i]] <= limits[i][1], drop = drop)
-            
+            da = da.where(da[dims[i]] >= limits[i][0], drop=drop).where(
+                da[dims[i]] <= limits[i][1], drop=drop
+            )
+
         if "original_lims" not in da.attrs:
-            da.attrs["original_lims"]  = tuple(original_lims_da)
+            da.attrs["original_lims"] = tuple(original_lims_da)
 
-        return da
\ No newline at end of file
+        return da
diff --git a/src/sdf_xarray/plotting.py b/src/sdf_xarray/plotting.py
index e8cfd97..9c6f755 100644
--- a/src/sdf_xarray/plotting.py
+++ b/src/sdf_xarray/plotting.py
@@ -57,8 +57,7 @@ def get_frame_title(
 
 
 def get_axis_label(dim: xr.DataArray):
-    label = f"{dim.long_name} [{dim.units}]"
-    return label
+    return f"{dim.long_name} [{dim.units}]"
 
 
 def _recover_vertex_coord(w_mid):
@@ -66,35 +65,32 @@ def _recover_vertex_coord(w_mid):
     w_size = w_mid.size
     dw = w_mid[1] - w_mid[0]
     w = np.zeros(w_mid.size + 1)
-    w[:w_size] = w_mid - dw/2
-    w[w_size] = w[w_size-1] + dw
+    w[:w_size] = w_mid - dw / 2
+    w[w_size] = w[w_size - 1] + dw
     return w
 
 
 def shift_cmap(cmap, vmin, vmax, vcenter, N=1024):
     """
-    Creates a new colourmap where the visual center of the original 
+    Creates a new colourmap where the visual center of the original
     colourmap is shifted to a specific data value.
     """
-    import matplotlib.pyplot as plt
-    import matplotlib.colors as mc
+    import matplotlib.colors as mc  # noqa: PLC0415
+    import matplotlib.pyplot as plt  # noqa: PLC0415
 
     # get the original colourmap
-    if type(cmap) == str:
+    if type(cmap) is str:
         cmap = plt.get_cmap(cmap)
-    
+
     midpoint = (vcenter - vmin) / (vmax - vmin)
     lower_size = int(N * midpoint)
     upper_size = N - lower_size
-    
+
     bottom_colors = cmap(np.linspace(0.0, 0.5, lower_size))
     top_colors = cmap(np.linspace(0.5, 1.0, upper_size))
     new_colors = np.vstack((bottom_colors, top_colors))
-    
-    new_cmap = mc.ListedColormap(new_colors, name=f"shifted_{cmap.name}")
-
-    return new_cmap
 
+    return mc.ListedColormap(new_colors, name=f"shifted_{cmap.name}")
 
 
 def calculate_window_boundaries(
@@ -176,21 +172,21 @@ def _set_axes_labels(ax: plt.Axes, axis_kwargs: dict) -> None:
         ax.set_ylabel(axis_kwargs["ylabel"])
 
 
-def voxel_plot(
-        da,
-        vmin = None,
-        vmax = None,
-        vcenter = None,
-        mask = None,
-        xlim = (None, None),
-        ylim = (None, None),
-        zlim = (None, None),
-        aspect = "equal",
-        elev = 30,
-        azim = -60,
-        cmap = "viridis",
-        cbar_scale = 0.9,
-    ):
+def voxel_plot(  # noqa: PLR0912, PLR0915
+    da,
+    vmin=None,
+    vmax=None,
+    vcenter=None,
+    mask=None,
+    xlim=(None, None),
+    ylim=(None, None),
+    zlim=(None, None),
+    aspect="equal",
+    elev=30,
+    azim=-60,
+    cmap="viridis",
+    cbar_scale=0.9,
+):
     """
     Will take 3 dimensional data and plot it as voxels.
 
@@ -219,7 +215,7 @@ def voxel_plot(
     cbar_scale
         Vertical scale of the colorbar (default = 0.9)
     """
-    import matplotlib.pyplot as plt
+    import matplotlib.pyplot as plt  # noqa: PLC0415
 
     print("Warning! voxel plots can be extremely intensive!")
 
@@ -236,18 +232,18 @@ def voxel_plot(
     # Create mesh
     x_mesh, y_mesh, z_mesh = np.meshgrid(x, y, z, indexing="ij")
 
-    if vmin == None:
+    if vmin is None:
         vmin = np.min(da.values)
-    if vmax == None:
+    if vmax is None:
         vmax = np.max(da.values)
 
     # Mask out data
-    if mask == None:
+    if mask is None:
         mask = (da > vmin) * (da < vmax)
 
     # Plot the data array
     fig = plt.figure(figsize=(8, 6))
-    ax = fig.add_subplot(projection='3d')
+    ax = fig.add_subplot(projection="3d")
     ax.view_init(elev, azim)
 
     # Set axis labels
@@ -259,17 +255,17 @@ def voxel_plot(
     xlim = list(xlim)
     ylim = list(ylim)
     zlim = list(zlim)
-    if xlim[0] == None:
+    if xlim[0] is None:
         xlim[0] = x.min()
-    if xlim[1] == None:
+    if xlim[1] is None:
         xlim[1] = x.max()
-    if ylim[0] == None:
+    if ylim[0] is None:
         ylim[0] = y.min()
-    if ylim[1] == None:
+    if ylim[1] is None:
         ylim[1] = y.max()
-    if zlim[0] == None:
+    if zlim[0] is None:
         zlim[0] = z.min()
-    if zlim[1] == None:
+    if zlim[1] is None:
         zlim[1] = z.max()
 
     # Set aspect ratio  of plot
@@ -293,19 +289,21 @@ def voxel_plot(
     # Colour bar and colour map
     if vcenter is not None:
         cmap = shift_cmap(cmap, vmin, vmax, vcenter)
-    norm = plt.Normalize(vmin = vmin, vmax = vmax)
+    norm = plt.Normalize(vmin=vmin, vmax=vmax)
     cmap = plt.get_cmap(cmap)
     colours = cmap(norm(da))
-    
+
     sm = plt.cm.ScalarMappable(cmap=cmap, norm=norm)
     sm.set_array([])  # Required for the colorbar to function
     cbar_label = get_axis_label(da)
-    fig.colorbar(sm, ax=ax, label=cbar_label, shrink = cbar_scale, aspect = 20*cbar_scale)
+    fig.colorbar(sm, ax=ax, label=cbar_label, shrink=cbar_scale, aspect=20 * cbar_scale)
 
     ax.voxels(
-        x_mesh, y_mesh, z_mesh,
+        x_mesh,
+        y_mesh,
+        z_mesh,
         mask,
-        facecolors = colours,
+        facecolors=colours,
     )
 
     return fig, ax
@@ -373,6 +371,7 @@ def _setup_pcolormesh_plot(
         fig = plot.get_figure()
         fig.colorbar(plot, ax=ax, label=f"{long_name} [{units}]")
 
+
 def _setup_voxel_plot(
     data: xr.DataArray,
     ax: plt.Axes,

From fc398a39338b2f802f57a787e8e05a0677ba1706 Mon Sep 17 00:00:00 2001
From: Joel Adams <joelucadams@gmail.com>
Date: Tue, 14 Jul 2026 16:04:10 +0200
Subject: [PATCH 04/32] Add tests for voxel plot, resize and lims

---
 tests/test_epoch_dataarray_accessor.py | 240 +++++++++++++++++++++++++
 1 file changed, 240 insertions(+)

diff --git a/tests/test_epoch_dataarray_accessor.py b/tests/test_epoch_dataarray_accessor.py
index d9b6513..b76f992 100644
--- a/tests/test_epoch_dataarray_accessor.py
+++ b/tests/test_epoch_dataarray_accessor.py
@@ -7,7 +7,9 @@
 import pytest
 import xarray as xr
 from matplotlib.animation import PillowWriter
+from matplotlib.colors import ListedColormap
 from matplotlib.container import BarContainer
+from mpl_toolkits.mplot3d import Axes3D
 from packaging.version import Version
 
 import sdf_xarray as sdfxr
@@ -335,3 +337,241 @@ def test_epoch_plot_flips_axis_order_for_2d_data_but_not_when_time_dim_present(
         plot = ds["Derived_Number_Density_electron"].epoch.plot(ax=ax)
 
         assert type(plot[2]) is BarContainer
+
+
+def _make_3d_da(shape=(4, 5, 6)):
+    """Small synthetic 3-D DataArray with the metadata voxel_plot expects."""
+    nx, ny, nz = shape
+    rng = np.random.default_rng(42)
+    data = rng.uniform(0.0, 1.0, (nx, ny, nz)).astype(np.float64)
+    return xr.DataArray(
+        data,
+        dims=["X_Grid_mid", "Y_Grid_mid", "Z_Grid_mid"],
+        coords={
+            "X_Grid_mid": xr.Variable(
+                "X_Grid_mid",
+                np.linspace(0.0, 1e-5, nx),
+                attrs={"long_name": "X", "units": "m"},
+            ),
+            "Y_Grid_mid": xr.Variable(
+                "Y_Grid_mid",
+                np.linspace(0.0, 2e-5, ny),
+                attrs={"long_name": "Y", "units": "m"},
+            ),
+            "Z_Grid_mid": xr.Variable(
+                "Z_Grid_mid",
+                np.linspace(0.0, 3e-5, nz),
+                attrs={"long_name": "Z", "units": "m"},
+            ),
+        },
+        attrs={"long_name": "Test Density", "units": "1/m^3"},
+    )
+
+
+@pytest.fixture
+def close_figs():
+    yield
+    plt.close("all")
+
+
+def test_recover_vertex_coord_size():
+    mid = xr.DataArray(np.linspace(0.5, 4.5, 5))
+    vertex = sxp._recover_vertex_coord(mid)
+    assert vertex.size == mid.size + 1
+
+
+def test_recover_vertex_coord_values():
+    mid = xr.DataArray(np.array([0.5, 1.5, 2.5]))
+    vertex = sxp._recover_vertex_coord(mid)
+    np.testing.assert_allclose(vertex, [0.0, 1.0, 2.0, 3.0])
+
+
+def test_shift_cmap_returns_listed_colormap():
+    result = sxp.shift_cmap("RdBu", vmin=-1.0, vmax=1.0, vcenter=0.0)
+    assert isinstance(result, ListedColormap)
+
+
+def test_shift_cmap_total_colors():
+    result = sxp.shift_cmap("RdBu", vmin=-1.0, vmax=1.0, vcenter=0.0, N=100)
+    assert len(result.colors) == 100
+
+
+def test_shift_cmap_asymmetric_center():
+    result = sxp.shift_cmap("viridis", vmin=0.0, vmax=1.0, vcenter=0.25, N=200)
+    assert isinstance(result, ListedColormap)
+    assert len(result.colors) == 200
+
+
+def test_voxel_plot_returns_fig_and_ax(close_figs):
+    da = _make_3d_da()
+    fig, ax = sxp.voxel_plot(da)
+    assert isinstance(ax, Axes3D)
+
+
+def test_voxel_plot_axis_labels(close_figs):
+    da = _make_3d_da()
+    _, ax = sxp.voxel_plot(da)
+    assert ax.get_xlabel() == "X [m]"
+    assert ax.get_ylabel() == "Y [m]"
+    assert ax.get_zlabel() == "Z [m]"
+
+
+def test_voxel_plot_default_axis_limits(close_figs):
+    da = _make_3d_da()
+    _, ax = sxp.voxel_plot(da)
+    xlim = ax.get_xlim()
+    ylim = ax.get_ylim()
+    zlim = ax.get_zlim()
+    assert xlim[0] < xlim[1]
+    assert ylim[0] < ylim[1]
+    assert zlim[0] < zlim[1]
+
+
+def test_voxel_plot_with_xlim_ylim_zlim(close_figs):
+    da = _make_3d_da()
+    x0, x1 = 2e-6, 8e-6
+    y0, y1 = 2e-6, 1.8e-5
+    z0, z1 = 5e-6, 2.5e-5
+    _, ax = sxp.voxel_plot(da, xlim=(x0, x1), ylim=(y0, y1), zlim=(z0, z1))
+    assert ax.get_xlim() == pytest.approx((x0, x1), rel=0.1)
+    assert ax.get_ylim() == pytest.approx((y0, y1), rel=0.1)
+    assert ax.get_zlim() == pytest.approx((z0, z1), rel=0.1)
+
+
+def test_voxel_plot_with_explicit_vmin_vmax(close_figs):
+    da = _make_3d_da()
+    fig, ax = sxp.voxel_plot(da, vmin=0.2, vmax=0.8)
+    assert isinstance(ax, Axes3D)
+
+
+def test_voxel_plot_with_vcenter(close_figs):
+    da = _make_3d_da()
+    fig, ax = sxp.voxel_plot(da, cmap="RdBu", vcenter=1e-2)
+    assert isinstance(ax, Axes3D)
+
+
+def test_voxel_plot_with_custom_mask(close_figs):
+    da = _make_3d_da()
+    mask = da.values > 0.5
+    fig, ax = sxp.voxel_plot(da, mask=mask)
+    assert isinstance(ax, Axes3D)
+
+
+def test_voxel_plot_aspect_auto(close_figs):
+    da = _make_3d_da()
+    _, ax = sxp.voxel_plot(da, aspect="auto")
+    box = ax.get_box_aspect()
+    # voxel_plot uses vertex coords (half-cell beyond midpoints) for axis ranges;
+    # matplotlib normalizes the absolute values, so only ratios are stable
+    x_vert = sxp._recover_vertex_coord(da["X_Grid_mid"])
+    y_vert = sxp._recover_vertex_coord(da["Y_Grid_mid"])
+    z_vert = sxp._recover_vertex_coord(da["Z_Grid_mid"])
+    x_range = x_vert.max() - x_vert.min()
+    y_range = y_vert.max() - y_vert.min()
+    z_range = z_vert.max() - z_vert.min()
+    assert box[1] / box[0] == pytest.approx(y_range / x_range, rel=0.05)
+    assert box[2] / box[0] == pytest.approx(z_range / x_range, rel=0.05)
+
+
+def test_voxel_plot_aspect_custom_tuple(close_figs):
+    da = _make_3d_da()
+    _, ax = sxp.voxel_plot(da, aspect=(1.0, 2.0, 3.0))
+    box = ax.get_box_aspect()
+    assert box[1] / box[0] == pytest.approx(2.0, rel=0.01)
+    assert box[2] / box[0] == pytest.approx(3.0, rel=0.01)
+
+
+def test_epoch_plot_dispatches_to_voxel_for_3d_spatial_data(close_figs):
+    with xr.open_dataset(TEST_FILES_DIR_3D / "0001.sdf") as ds:
+        da = ds["Derived_Number_Density_Electron"].isel(
+            X_Grid_mid=slice(0, 4),
+            Y_Grid_mid=slice(0, 4),
+            Z_Grid_mid=slice(0, 4),
+        )
+        fig, ax = da.epoch.plot()
+        assert isinstance(ax, Axes3D)
+        assert ax.get_xlabel() == "X [m]"
+        assert ax.get_ylabel() == "Y [m]"
+        assert ax.get_zlabel() == "Z [m]"
+
+
+def test_resize_basic():
+    da = _make_3d_da(shape=(8, 10, 12))
+    da_small = da.epoch.resize((4, 5, 6))
+    assert da_small.shape == (4, 5, 6)
+    assert da_small.dims == da.dims
+
+
+def test_resize_stores_original_shape_attrs():
+    da = _make_3d_da(shape=(8, 10, 12))
+    da_small = da.epoch.resize((4, 5, 6))
+    assert da_small.attrs["original_shape"] == (8, 10, 12)
+
+
+def test_resize_coord_range_preserved():
+    da = _make_3d_da(shape=(8, 10, 12))
+    da_small = da.epoch.resize((4, 5, 6))
+    # For _mid coords, resize preserves the vertex (cell-edge) range rather than
+    # the midpoint values; check that the outer vertices are unchanged
+    orig_vertex = sxp._recover_vertex_coord(da["X_Grid_mid"])
+    new_vertex = sxp._recover_vertex_coord(da_small["X_Grid_mid"])
+    np.testing.assert_allclose(float(new_vertex[0]), float(orig_vertex[0]), rtol=1e-6)
+    np.testing.assert_allclose(float(new_vertex[-1]), float(orig_vertex[-1]), rtol=1e-6)
+
+
+def test_resize_wrong_ndim_raises():
+    da = _make_3d_da()
+    with pytest.raises(ValueError, match="dimensions"):
+        da.epoch.resize((4, 5))
+
+
+def test_resize_with_mid_coord():
+    da = _make_3d_da(shape=(6, 8, 10))
+    da_small = da.epoch.resize((3, 4, 5))
+    assert da_small.shape == (3, 4, 5)
+    for dim in da_small.dims:
+        assert da_small[dim].size == da_small.sizes[dim]
+
+
+def test_limit_reduces_coord_range():
+    da = _make_3d_da()
+    x_mid = 5e-6
+    da_lim = da.epoch.limit(((0.0, x_mid), (None, None), (None, None)))
+    assert float(da_lim["X_Grid_mid"][-1]) <= x_mid + 1e-7
+
+
+def test_limit_with_none_uses_existing_bounds():
+    da = _make_3d_da()
+    da_lim = da.epoch.limit(((None, None), (None, None), (None, None)))
+    assert da_lim.shape == da.shape
+
+
+def test_limit_stores_original_lims_on_coord():
+    da = _make_3d_da()
+    x_min = float(da["X_Grid_mid"][0])
+    x_max = float(da["X_Grid_mid"][-1])
+    da_lim = da.epoch.limit(((0.0, 5e-6), (None, None), (None, None)))
+    assert da_lim["X_Grid_mid"].attrs["original_lims"] == pytest.approx(
+        (x_min, x_max), rel=1e-6
+    )
+
+
+def test_limit_no_drop():
+    da = _make_3d_da()
+    da_lim = da.epoch.limit(((0.0, 5e-6), (None, None), (None, None)), drop=False)
+    assert da_lim.shape == da.shape
+    assert np.any(np.isnan(da_lim.values))
+
+
+def test_animate_raises_for_4d_data():
+    da = xr.DataArray(
+        np.zeros((3, 4, 5, 6)),
+        dims=["time", "X_Grid_mid", "Y_Grid_mid", "Z_Grid_mid"],
+        coords={
+            "time": xr.Variable(
+                "time", [1.0, 2.0, 3.0], attrs={"long_name": "Time", "units": "s"}
+            )
+        },
+    )
+    with pytest.raises(NotImplementedError, match="Voxel animations"):
+        da.epoch.animate()

From 0aa7ecdd003657210e49345a75729e9208c315f9 Mon Sep 17 00:00:00 2001
From: Joel Adams <joelucadams@gmail.com>
Date: Tue, 14 Jul 2026 16:04:30 +0200
Subject: [PATCH 05/32] rollback checks in plot for time and x and y

---
 src/sdf_xarray/dataarray_accessor.py | 8 +++++++-
 1 file changed, 7 insertions(+), 1 deletion(-)

diff --git a/src/sdf_xarray/dataarray_accessor.py b/src/sdf_xarray/dataarray_accessor.py
index aba2c66..6cf2a63 100644
--- a/src/sdf_xarray/dataarray_accessor.py
+++ b/src/sdf_xarray/dataarray_accessor.py
@@ -68,6 +68,8 @@ def plot(self, *args, **kwargs) -> DataArrayPlotAccessor:
             Keyword arguments passed to `xarray.DataArray.plot`.
         """
         dims = self._obj.dims
+        is_time_dim_present = "time" in dims
+        is_x_or_y_specified_in_kwargs = "x" in kwargs or "y" in kwargs
 
         if len(dims) == 1:
             return self._obj.plot(*args, **kwargs)
@@ -78,7 +80,11 @@ def plot(self, *args, **kwargs) -> DataArrayPlotAccessor:
             updated_kwargs.setdefault("y", dims[1])
             return self._obj.plot(*args, **updated_kwargs)
 
-        if len(dims) == 3:
+        if (
+            len(dims) == 3
+            and not is_time_dim_present
+            and not is_x_or_y_specified_in_kwargs
+        ):
             return voxel_plot(self._obj, *args, **kwargs)
 
         return self._obj.plot(*args, **kwargs)

From de3349be8006ad370c9392e63f493db76d9e0ea2 Mon Sep 17 00:00:00 2001
From: Joel Adams <joelucadams@gmail.com>
Date: Tue, 14 Jul 2026 17:15:47 +0200
Subject: [PATCH 06/32] Fix ruff linting on fixture tests

---
 tests/test_epoch_dataarray_accessor.py | 40 ++++++++++++++++----------
 1 file changed, 25 insertions(+), 15 deletions(-)

diff --git a/tests/test_epoch_dataarray_accessor.py b/tests/test_epoch_dataarray_accessor.py
index b76f992..6a2ee10 100644
--- a/tests/test_epoch_dataarray_accessor.py
+++ b/tests/test_epoch_dataarray_accessor.py
@@ -402,13 +402,15 @@ def test_shift_cmap_asymmetric_center():
     assert len(result.colors) == 200
 
 
-def test_voxel_plot_returns_fig_and_ax(close_figs):
+@pytest.mark.usefixtures("close_figs")
+def test_voxel_plot_returns_fig_and_ax():
     da = _make_3d_da()
-    fig, ax = sxp.voxel_plot(da)
+    _, ax = sxp.voxel_plot(da)
     assert isinstance(ax, Axes3D)
 
 
-def test_voxel_plot_axis_labels(close_figs):
+@pytest.mark.usefixtures("close_figs")
+def test_voxel_plot_axis_labels():
     da = _make_3d_da()
     _, ax = sxp.voxel_plot(da)
     assert ax.get_xlabel() == "X [m]"
@@ -416,7 +418,8 @@ def test_voxel_plot_axis_labels(close_figs):
     assert ax.get_zlabel() == "Z [m]"
 
 
-def test_voxel_plot_default_axis_limits(close_figs):
+@pytest.mark.usefixtures("close_figs")
+def test_voxel_plot_default_axis_limits():
     da = _make_3d_da()
     _, ax = sxp.voxel_plot(da)
     xlim = ax.get_xlim()
@@ -427,7 +430,8 @@ def test_voxel_plot_default_axis_limits(close_figs):
     assert zlim[0] < zlim[1]
 
 
-def test_voxel_plot_with_xlim_ylim_zlim(close_figs):
+@pytest.mark.usefixtures("close_figs")
+def test_voxel_plot_with_xlim_ylim_zlim():
     da = _make_3d_da()
     x0, x1 = 2e-6, 8e-6
     y0, y1 = 2e-6, 1.8e-5
@@ -438,26 +442,30 @@ def test_voxel_plot_with_xlim_ylim_zlim(close_figs):
     assert ax.get_zlim() == pytest.approx((z0, z1), rel=0.1)
 
 
-def test_voxel_plot_with_explicit_vmin_vmax(close_figs):
+@pytest.mark.usefixtures("close_figs")
+def test_voxel_plot_with_explicit_vmin_vmax():
     da = _make_3d_da()
-    fig, ax = sxp.voxel_plot(da, vmin=0.2, vmax=0.8)
+    _, ax = sxp.voxel_plot(da, vmin=0.2, vmax=0.8)
     assert isinstance(ax, Axes3D)
 
 
-def test_voxel_plot_with_vcenter(close_figs):
+@pytest.mark.usefixtures("close_figs")
+def test_voxel_plot_with_vcenter():
     da = _make_3d_da()
-    fig, ax = sxp.voxel_plot(da, cmap="RdBu", vcenter=1e-2)
+    _, ax = sxp.voxel_plot(da, cmap="RdBu", vcenter=1e-2)
     assert isinstance(ax, Axes3D)
 
 
-def test_voxel_plot_with_custom_mask(close_figs):
+@pytest.mark.usefixtures("close_figs")
+def test_voxel_plot_with_custom_mask():
     da = _make_3d_da()
     mask = da.values > 0.5
-    fig, ax = sxp.voxel_plot(da, mask=mask)
+    _, ax = sxp.voxel_plot(da, mask=mask)
     assert isinstance(ax, Axes3D)
 
 
-def test_voxel_plot_aspect_auto(close_figs):
+@pytest.mark.usefixtures("close_figs")
+def test_voxel_plot_aspect_auto():
     da = _make_3d_da()
     _, ax = sxp.voxel_plot(da, aspect="auto")
     box = ax.get_box_aspect()
@@ -473,7 +481,8 @@ def test_voxel_plot_aspect_auto(close_figs):
     assert box[2] / box[0] == pytest.approx(z_range / x_range, rel=0.05)
 
 
-def test_voxel_plot_aspect_custom_tuple(close_figs):
+@pytest.mark.usefixtures("close_figs")
+def test_voxel_plot_aspect_custom_tuple():
     da = _make_3d_da()
     _, ax = sxp.voxel_plot(da, aspect=(1.0, 2.0, 3.0))
     box = ax.get_box_aspect()
@@ -481,14 +490,15 @@ def test_voxel_plot_aspect_custom_tuple(close_figs):
     assert box[2] / box[0] == pytest.approx(3.0, rel=0.01)
 
 
-def test_epoch_plot_dispatches_to_voxel_for_3d_spatial_data(close_figs):
+@pytest.mark.usefixtures("close_figs")
+def test_epoch_plot_dispatches_to_voxel_for_3d_spatial_data():
     with xr.open_dataset(TEST_FILES_DIR_3D / "0001.sdf") as ds:
         da = ds["Derived_Number_Density_Electron"].isel(
             X_Grid_mid=slice(0, 4),
             Y_Grid_mid=slice(0, 4),
             Z_Grid_mid=slice(0, 4),
         )
-        fig, ax = da.epoch.plot()
+        _, ax = da.epoch.plot()
         assert isinstance(ax, Axes3D)
         assert ax.get_xlabel() == "X [m]"
         assert ax.get_ylabel() == "Y [m]"

From d6b687a95c888dbbbd33bf29e293d13a5c312579 Mon Sep 17 00:00:00 2001
From: Joel Adams <joelucadams@gmail.com>
Date: Tue, 14 Jul 2026 17:30:29 +0200
Subject: [PATCH 07/32] refactor voxel axes limits and setting aspect ratio

---
 src/sdf_xarray/plotting.py | 88 +++++++++++++++-----------------------
 1 file changed, 35 insertions(+), 53 deletions(-)

diff --git a/src/sdf_xarray/plotting.py b/src/sdf_xarray/plotting.py
index 9c6f755..57414f9 100644
--- a/src/sdf_xarray/plotting.py
+++ b/src/sdf_xarray/plotting.py
@@ -3,7 +3,7 @@
 import warnings
 from collections.abc import Callable
 from dataclasses import dataclass
-from typing import TYPE_CHECKING, Any
+from typing import TYPE_CHECKING, Any, Literal
 
 import numpy as np
 import xarray as xr
@@ -11,6 +11,8 @@
 if TYPE_CHECKING:
     import matplotlib.pyplot as plt
     from matplotlib.animation import FuncAnimation
+    from matplotlib.axes import Axes
+    from matplotlib.figure import Figure
 
 
 @dataclass
@@ -172,21 +174,22 @@ def _set_axes_labels(ax: plt.Axes, axis_kwargs: dict) -> None:
         ax.set_ylabel(axis_kwargs["ylabel"])
 
 
-def voxel_plot(  # noqa: PLR0912, PLR0915
-    da,
-    vmin=None,
-    vmax=None,
-    vcenter=None,
-    mask=None,
-    xlim=(None, None),
-    ylim=(None, None),
-    zlim=(None, None),
-    aspect="equal",
-    elev=30,
-    azim=-60,
-    cmap="viridis",
-    cbar_scale=0.9,
-):
+def voxel_plot(
+    da: xr.DataArray,
+    vmin: float | None = None,
+    vmax: float | None = None,
+    vcenter: float | None = None,
+    mask: list[bool] | None = None,
+    xlim: tuple[float | None, float | None] = (None, None),
+    ylim: tuple[float | None, float | None] = (None, None),
+    zlim: tuple[float | None, float | None] = (None, None),
+    aspect: Literal["equal"] | Literal["auto"] = "equal",
+    elev: int = 30,
+    azim: int = -60,
+    cmap: str = "viridis",
+    cbar_scale: float = 0.9,
+    **kwargs,
+) -> tuple[Figure, Axes]:
     """
     Will take 3 dimensional data and plot it as voxels.
 
@@ -251,40 +254,25 @@ def voxel_plot(  # noqa: PLR0912, PLR0915
     ax.set_ylabel(get_axis_label(da[dims[1]]))
     ax.set_zlabel(get_axis_label(da[dims[2]]))
 
-    # Find axis limits
-    xlim = list(xlim)
-    ylim = list(ylim)
-    zlim = list(zlim)
-    if xlim[0] is None:
-        xlim[0] = x.min()
-    if xlim[1] is None:
-        xlim[1] = x.max()
-    if ylim[0] is None:
-        ylim[0] = y.min()
-    if ylim[1] is None:
-        ylim[1] = y.max()
-    if zlim[0] is None:
-        zlim[0] = z.min()
-    if zlim[1] is None:
-        zlim[1] = z.max()
-
-    # Set aspect ratio  of plot
+    # Find and set axis limits
+    xlim, ylim, zlim = [
+        (data.min() if low is None else low, data.max() if high is None else high)
+        for (low, high), data in zip([xlim, ylim, zlim], [x, y, z])
+    ]
+
+    ax.set_xlim(xlim)
+    ax.set_ylim(ylim)
+    ax.set_zlim(zlim)
+
+    # Compute and set the box aspect ratio
     if aspect == "equal":
-        x_aspect = 1
-        y_aspect = 1
-        z_aspect = 1
+        box_aspect = (1, 1, 1)
     elif aspect == "auto":
-        x_aspect = xlim[1] - xlim[0]
-        y_aspect = ylim[1] - ylim[0]
-        z_aspect = zlim[1] - zlim[0]
+        box_aspect = (xlim[1] - xlim[0], ylim[1] - ylim[0], zlim[1] - zlim[0])
     else:
-        x_aspect, y_aspect, z_aspect = aspect
-    ax.set_box_aspect((x_aspect, y_aspect, z_aspect))
+        box_aspect = aspect
 
-    # Limit axis of plot
-    ax.set_xlim(xlim[0], xlim[1])
-    ax.set_ylim(ylim[0], ylim[1])
-    ax.set_zlim(zlim[0], zlim[1])
+    ax.set_box_aspect(box_aspect)
 
     # Colour bar and colour map
     if vcenter is not None:
@@ -298,13 +286,7 @@ def voxel_plot(  # noqa: PLR0912, PLR0915
     cbar_label = get_axis_label(da)
     fig.colorbar(sm, ax=ax, label=cbar_label, shrink=cbar_scale, aspect=20 * cbar_scale)
 
-    ax.voxels(
-        x_mesh,
-        y_mesh,
-        z_mesh,
-        mask,
-        facecolors=colours,
-    )
+    ax.voxels(x_mesh, y_mesh, z_mesh, mask, facecolors=colours, **kwargs)
 
     return fig, ax
 

From 7cef173439c4b263a431f6e5bec3579de8769103 Mon Sep 17 00:00:00 2001
From: Joel Adams <joelucadams@gmail.com>
Date: Tue, 14 Jul 2026 17:39:00 +0200
Subject: [PATCH 08/32] Improve docstring and types

---
 src/sdf_xarray/plotting.py | 34 ++++++++++++++++++++++++++++------
 1 file changed, 28 insertions(+), 6 deletions(-)

diff --git a/src/sdf_xarray/plotting.py b/src/sdf_xarray/plotting.py
index 57414f9..d029d1c 100644
--- a/src/sdf_xarray/plotting.py
+++ b/src/sdf_xarray/plotting.py
@@ -12,6 +12,7 @@
     import matplotlib.pyplot as plt
     from matplotlib.animation import FuncAnimation
     from matplotlib.axes import Axes
+    from matplotlib.colors import ListedColormap
     from matplotlib.figure import Figure
 
 
@@ -58,12 +59,13 @@ def get_frame_title(
     return f"{title_custom}{title_t_axis}{title_sdf}"
 
 
-def get_axis_label(dim: xr.DataArray):
+def get_axis_label(dim: xr.DataArray) -> str:
+    """Formats the axes label for a given dim in the form of ``dim.long_name [dim.units]``."""
     return f"{dim.long_name} [{dim.units}]"
 
 
-def _recover_vertex_coord(w_mid):
-    # Takes a midpoint coordinate, returns a vertex coordinate
+def _recover_vertex_coord(w_mid: xr.DataArray) -> np.ndarray:
+    """Takes a midpoint coordinate, returns a vertex coordinate."""
     w_size = w_mid.size
     dw = w_mid[1] - w_mid[0]
     w = np.zeros(w_mid.size + 1)
@@ -72,10 +74,30 @@ def _recover_vertex_coord(w_mid):
     return w
 
 
-def shift_cmap(cmap, vmin, vmax, vcenter, N=1024):
+def shift_cmap(
+    cmap: str, vmin: float, vmax: float, vcenter: float, N: int = 1024
+) -> ListedColormap:
     """
-    Creates a new colourmap where the visual center of the original
-    colourmap is shifted to a specific data value.
+    Create a new colormap where the visual center of the original
+    colormap is shifted to a specific data value.
+
+    Parameters
+    ----------
+    cmap : str or matplotlib.colors.Colormap
+        The name of the original colormap (e.g., 'viridis') or the colormap object itself.
+    vmin : float
+        The minimum value of your data range.
+    vmax : float
+        The maximum value of your data range.
+    vcenter : float
+        The data value that should map to the visual midpoint (0.5) of the colormap.
+    N : int, default 1024
+        The number of interpolation steps (color bins) in the new colormap.
+
+    Returns
+    -------
+    matplotlib.colors.ListedColormap
+        The newly constructed, shifted colormap.
     """
     import matplotlib.colors as mc  # noqa: PLC0415
     import matplotlib.pyplot as plt  # noqa: PLC0415

From 93c8b9e909cc7812322e87e8ad2e7da3958e7fca Mon Sep 17 00:00:00 2001
From: Joel Adams <joelucadams@gmail.com>
Date: Wed, 15 Jul 2026 12:36:46 +0200
Subject: [PATCH 09/32] change voxel plot warning to use `warnings.warn()`

---
 src/sdf_xarray/plotting.py | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/src/sdf_xarray/plotting.py b/src/sdf_xarray/plotting.py
index d029d1c..1f97a02 100644
--- a/src/sdf_xarray/plotting.py
+++ b/src/sdf_xarray/plotting.py
@@ -242,7 +242,10 @@ def voxel_plot(
     """
     import matplotlib.pyplot as plt  # noqa: PLC0415
 
-    print("Warning! voxel plots can be extremely intensive!")
+    warnings.warn(
+        "Voxel plots can be extremely computationally expensive and may take longer than expected to plot.",
+        stacklevel=2,
+    )
 
     # Limit arrays based on axis limits
     da = da.epoch.limit((xlim, ylim, zlim))

From 292e4752976da062c6699a8534c937340acc0b78 Mon Sep 17 00:00:00 2001
From: Joel Adams <joelucadams@gmail.com>
Date: Wed, 15 Jul 2026 13:57:55 +0200
Subject: [PATCH 10/32] update dataarray plot accessor to remove x or y check

---
 src/sdf_xarray/dataarray_accessor.py | 7 +------
 1 file changed, 1 insertion(+), 6 deletions(-)

diff --git a/src/sdf_xarray/dataarray_accessor.py b/src/sdf_xarray/dataarray_accessor.py
index 6cf2a63..d62c250 100644
--- a/src/sdf_xarray/dataarray_accessor.py
+++ b/src/sdf_xarray/dataarray_accessor.py
@@ -69,7 +69,6 @@ def plot(self, *args, **kwargs) -> DataArrayPlotAccessor:
         """
         dims = self._obj.dims
         is_time_dim_present = "time" in dims
-        is_x_or_y_specified_in_kwargs = "x" in kwargs or "y" in kwargs
 
         if len(dims) == 1:
             return self._obj.plot(*args, **kwargs)
@@ -80,11 +79,7 @@ def plot(self, *args, **kwargs) -> DataArrayPlotAccessor:
             updated_kwargs.setdefault("y", dims[1])
             return self._obj.plot(*args, **updated_kwargs)
 
-        if (
-            len(dims) == 3
-            and not is_time_dim_present
-            and not is_x_or_y_specified_in_kwargs
-        ):
+        if len(dims) == 3 and not is_time_dim_present:
             return voxel_plot(self._obj, *args, **kwargs)
 
         return self._obj.plot(*args, **kwargs)

From cc6fd44f5fc28c0824e67a732e1f851688998740 Mon Sep 17 00:00:00 2001
From: Joel Adams <joelucadams@gmail.com>
Date: Thu, 16 Jul 2026 11:38:02 +0200
Subject: [PATCH 11/32] Add global pytest filter for `userWarning` to ignore
 voxel plotting warning

---
 pyproject.toml | 6 ++++--
 1 file changed, 4 insertions(+), 2 deletions(-)

diff --git a/pyproject.toml b/pyproject.toml
index 039d3c9..94ab729 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -136,5 +136,7 @@ ignore = [
   "B9",      # flake8-bugbear opinionated warnings
   "PLR0913", # remove maximum number of arguments in a function
 ]
-exclude = ["**/_version.py"]
-# Auto-generated file
+exclude = ["**/_version.py"] # Auto-generated file
+
+[tool.pytest.ini_options]
+filterwarnings = ['ignore::UserWarning']

From 763f0420f0f6423c69155e89d7880e4243aa79aa Mon Sep 17 00:00:00 2001
From: Joel Adams <joelucadams@gmail.com>
Date: Fri, 17 Jul 2026 11:48:11 +0200
Subject: [PATCH 12/32] Update voxel_plot to accept user axes

---
 src/sdf_xarray/plotting.py             | 12 +++++++++---
 tests/test_epoch_dataarray_accessor.py |  8 ++++++++
 2 files changed, 17 insertions(+), 3 deletions(-)

diff --git a/src/sdf_xarray/plotting.py b/src/sdf_xarray/plotting.py
index 1f97a02..f643676 100644
--- a/src/sdf_xarray/plotting.py
+++ b/src/sdf_xarray/plotting.py
@@ -198,6 +198,7 @@ def _set_axes_labels(ax: plt.Axes, axis_kwargs: dict) -> None:
 
 def voxel_plot(
     da: xr.DataArray,
+    ax: plt.Axes | None = None,
     vmin: float | None = None,
     vmax: float | None = None,
     vcenter: float | None = None,
@@ -211,7 +212,7 @@ def voxel_plot(
     cmap: str = "viridis",
     cbar_scale: float = 0.9,
     **kwargs,
-) -> tuple[Figure, Axes]:
+) -> None:
     """
     Will take 3 dimensional data and plot it as voxels.
 
@@ -219,6 +220,8 @@ def voxel_plot(
     ----------
     da
         DataArray to be plotted.
+    ax
+        Matplotlib axes on which to plot.
     vmin
         Minimum value. If `mask` is not stated, will be used to define the mask.
     vmax
@@ -247,6 +250,11 @@ def voxel_plot(
         stacklevel=2,
     )
 
+    if ax is None:
+        fig, ax = plt.subplots(figsize=(8, 6), subplot_kw={"projection": "3d"})
+    else:
+        fig = ax.get_figure()
+
     # Limit arrays based on axis limits
     da = da.epoch.limit((xlim, ylim, zlim))
 
@@ -270,8 +278,6 @@ def voxel_plot(
         mask = (da > vmin) * (da < vmax)
 
     # Plot the data array
-    fig = plt.figure(figsize=(8, 6))
-    ax = fig.add_subplot(projection="3d")
     ax.view_init(elev, azim)
 
     # Set axis labels
diff --git a/tests/test_epoch_dataarray_accessor.py b/tests/test_epoch_dataarray_accessor.py
index 6a2ee10..667366f 100644
--- a/tests/test_epoch_dataarray_accessor.py
+++ b/tests/test_epoch_dataarray_accessor.py
@@ -409,6 +409,14 @@ def test_voxel_plot_returns_fig_and_ax():
     assert isinstance(ax, Axes3D)
 
 
+@pytest.mark.usefixtures("close_figs")
+def test_voxel_plot_accepts_axes():
+    da = _make_3d_da()
+    _, ax = plt.subplots(figsize=(8, 6), subplot_kw={"projection": "3d"})
+    sxp.voxel_plot(da, ax=ax)
+    assert isinstance(ax, Axes3D)
+
+
 @pytest.mark.usefixtures("close_figs")
 def test_voxel_plot_axis_labels():
     da = _make_3d_da()

From 822277552a78efb09cc2da1095e7bb2290f069be Mon Sep 17 00:00:00 2001
From: Joel Adams <joelucadams@gmail.com>
Date: Fri, 17 Jul 2026 11:50:54 +0200
Subject: [PATCH 13/32] Remove unused matplotlib imports

---
 src/sdf_xarray/plotting.py | 2 --
 1 file changed, 2 deletions(-)

diff --git a/src/sdf_xarray/plotting.py b/src/sdf_xarray/plotting.py
index f643676..29ba7fc 100644
--- a/src/sdf_xarray/plotting.py
+++ b/src/sdf_xarray/plotting.py
@@ -11,9 +11,7 @@
 if TYPE_CHECKING:
     import matplotlib.pyplot as plt
     from matplotlib.animation import FuncAnimation
-    from matplotlib.axes import Axes
     from matplotlib.colors import ListedColormap
-    from matplotlib.figure import Figure
 
 
 @dataclass

From 113430532db9558cdc8ce07d94cee7da9b2e8331 Mon Sep 17 00:00:00 2001
From: Joel Adams <joelucadams@gmail.com>
Date: Fri, 17 Jul 2026 12:24:20 +0200
Subject: [PATCH 14/32] Fix voxel_plot return type

---
 src/sdf_xarray/plotting.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/sdf_xarray/plotting.py b/src/sdf_xarray/plotting.py
index 29ba7fc..6522851 100644
--- a/src/sdf_xarray/plotting.py
+++ b/src/sdf_xarray/plotting.py
@@ -210,7 +210,7 @@ def voxel_plot(
     cmap: str = "viridis",
     cbar_scale: float = 0.9,
     **kwargs,
-) -> None:
+) -> tuple[plt.Figure, plt.Axes]:
     """
     Will take 3 dimensional data and plot it as voxels.
 
@@ -219,7 +219,7 @@ def voxel_plot(
     da
         DataArray to be plotted.
     ax
-        Matplotlib axes on which to plot.
+        Matplotlib axes on which to plot (This must use a 3d projection).
     vmin
         Minimum value. If `mask` is not stated, will be used to define the mask.
     vmax

From 90dcacc55c7c38febe96bc37d49dd7bd73e7585f Mon Sep 17 00:00:00 2001
From: Joel Adams <joelucadams@gmail.com>
Date: Fri, 17 Jul 2026 12:26:30 +0200
Subject: [PATCH 15/32] Make default mask inclusive of vmin and vmax

---
 src/sdf_xarray/plotting.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/sdf_xarray/plotting.py b/src/sdf_xarray/plotting.py
index 6522851..ea42088 100644
--- a/src/sdf_xarray/plotting.py
+++ b/src/sdf_xarray/plotting.py
@@ -273,7 +273,7 @@ def voxel_plot(
 
     # Mask out data
     if mask is None:
-        mask = (da > vmin) * (da < vmax)
+        mask = (da >= vmin) * (da <= vmax)
 
     # Plot the data array
     ax.view_init(elev, azim)

From fed1a5e7e548612b12788242ef9912374e4b6530 Mon Sep 17 00:00:00 2001
From: Joel Adams <joelucadams@gmail.com>
Date: Fri, 17 Jul 2026 12:30:56 +0200
Subject: [PATCH 16/32] Fix type hinting in voxel_plot

---
 src/sdf_xarray/plotting.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

diff --git a/src/sdf_xarray/plotting.py b/src/sdf_xarray/plotting.py
index ea42088..a384e8e 100644
--- a/src/sdf_xarray/plotting.py
+++ b/src/sdf_xarray/plotting.py
@@ -200,13 +200,13 @@ def voxel_plot(
     vmin: float | None = None,
     vmax: float | None = None,
     vcenter: float | None = None,
-    mask: list[bool] | None = None,
+    mask: np.ndarray[bool] | None = None,
     xlim: tuple[float | None, float | None] = (None, None),
     ylim: tuple[float | None, float | None] = (None, None),
     zlim: tuple[float | None, float | None] = (None, None),
-    aspect: Literal["equal"] | Literal["auto"] = "equal",
-    elev: int = 30,
-    azim: int = -60,
+    aspect: Literal["equal", "auto"] | tuple[float, float, float] = "equal",
+    elev: float = 30,
+    azim: float = -60,
     cmap: str = "viridis",
     cbar_scale: float = 0.9,
     **kwargs,

From a8bfaf3ebc342cc0a8e5e4508aa18637e3058741 Mon Sep 17 00:00:00 2001
From: ShaunD137 <shaun.doherty@york.ac.uk>
Date: Tue, 21 Jul 2026 09:30:11 +0100
Subject: [PATCH 17/32] remove time check in plot accessor

---
 src/sdf_xarray/dataarray_accessor.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

diff --git a/src/sdf_xarray/dataarray_accessor.py b/src/sdf_xarray/dataarray_accessor.py
index d62c250..aba2c66 100644
--- a/src/sdf_xarray/dataarray_accessor.py
+++ b/src/sdf_xarray/dataarray_accessor.py
@@ -68,7 +68,6 @@ def plot(self, *args, **kwargs) -> DataArrayPlotAccessor:
             Keyword arguments passed to `xarray.DataArray.plot`.
         """
         dims = self._obj.dims
-        is_time_dim_present = "time" in dims
 
         if len(dims) == 1:
             return self._obj.plot(*args, **kwargs)
@@ -79,7 +78,7 @@ def plot(self, *args, **kwargs) -> DataArrayPlotAccessor:
             updated_kwargs.setdefault("y", dims[1])
             return self._obj.plot(*args, **updated_kwargs)
 
-        if len(dims) == 3 and not is_time_dim_present:
+        if len(dims) == 3:
             return voxel_plot(self._obj, *args, **kwargs)
 
         return self._obj.plot(*args, **kwargs)

From 0f1adf5a097be0b0d4fd17b09606b095cccae2fa Mon Sep 17 00:00:00 2001
From: ShaunD137 <shaun.doherty@york.ac.uk>
Date: Wed, 22 Jul 2026 14:17:26 +0100
Subject: [PATCH 18/32] add optional histogram plot to plot accessor

---
 src/sdf_xarray/dataarray_accessor.py | 7 ++++++-
 1 file changed, 6 insertions(+), 1 deletion(-)

diff --git a/src/sdf_xarray/dataarray_accessor.py b/src/sdf_xarray/dataarray_accessor.py
index aba2c66..c330573 100644
--- a/src/sdf_xarray/dataarray_accessor.py
+++ b/src/sdf_xarray/dataarray_accessor.py
@@ -50,7 +50,7 @@ class EpochAccessor:
     def __init__(self, xarray_obj: xr.DataArray):
         self._obj = xarray_obj
 
-    def plot(self, *args, **kwargs) -> DataArrayPlotAccessor:
+    def plot(self, hist = False, *args, **kwargs) -> DataArrayPlotAccessor:
         """
         Builds upon `xarray.DataArray.plot` while changing some of its default behaviours.
 
@@ -62,6 +62,8 @@ def plot(self, *args, **kwargs) -> DataArrayPlotAccessor:
 
         Parameters
         ----------
+        hist
+            If `True`, will plot a histogram regardless of dimensionality (default = False).
         args
             Positional arguments passed to `xarray.DataArray.plot`.
         kwargs
@@ -69,6 +71,9 @@ def plot(self, *args, **kwargs) -> DataArrayPlotAccessor:
         """
         dims = self._obj.dims
 
+        if hist == True:
+            return self._obj.plot.hist(*args, **kwargs)
+
         if len(dims) == 1:
             return self._obj.plot(*args, **kwargs)
 

From e83b51d9aadb75985499d430a535ac7254d75802 Mon Sep 17 00:00:00 2001
From: ShaunD137 <shaun.doherty@york.ac.uk>
Date: Wed, 22 Jul 2026 14:46:08 +0100
Subject: [PATCH 19/32] remove now unnecessary tests

---
 tests/test_epoch_dataarray_accessor.py | 16 ----------------
 1 file changed, 16 deletions(-)

diff --git a/tests/test_epoch_dataarray_accessor.py b/tests/test_epoch_dataarray_accessor.py
index 667366f..50338d7 100644
--- a/tests/test_epoch_dataarray_accessor.py
+++ b/tests/test_epoch_dataarray_accessor.py
@@ -323,22 +323,6 @@ def test_epoch_plot_flips_axis_order_for_2d_data_with_additional_params(subplots
         assert ax.get_ylim() == pytest.approx((0.0, 0.5), abs=1e-2)
 
 
-def test_epoch_plot_flips_axis_order_for_2d_data_but_not_when_time_dim_present(
-    subplots,
-):
-    with xr.open_mfdataset(
-        TEST_FILES_DIR_2D_MW.glob("*.sdf"),
-        preprocess=SDFPreprocess(),
-        combine="nested",
-        compat="no_conflicts",
-        join="outer",
-    ) as ds:
-        _, ax = subplots
-        plot = ds["Derived_Number_Density_electron"].epoch.plot(ax=ax)
-
-        assert type(plot[2]) is BarContainer
-
-
 def _make_3d_da(shape=(4, 5, 6)):
     """Small synthetic 3-D DataArray with the metadata voxel_plot expects."""
     nx, ny, nz = shape

From 43f4e97a66e9827d1e26b0d79f9675c227ae9e9e Mon Sep 17 00:00:00 2001
From: ShaunD137 <shaun.doherty@york.ac.uk>
Date: Wed, 22 Jul 2026 14:46:40 +0100
Subject: [PATCH 20/32] documentation update

---
 docs/animation.md                    |  11 +++-
 docs/figures/voxel_plot_high_res.png | Bin 0 -> 212132 bytes
 docs/index.md                        |   1 +
 docs/plots.md                        |  91 +++++++++++++++++++++++++++
 docs/understanding_datasets.md       |  65 ++++++++++++++-----
 5 files changed, 149 insertions(+), 19 deletions(-)
 create mode 100644 docs/figures/voxel_plot_high_res.png
 create mode 100644 docs/plots.md

diff --git a/docs/animation.md b/docs/animation.md
index c512b4a..9e84580 100644
--- a/docs/animation.md
+++ b/docs/animation.md
@@ -35,9 +35,10 @@ resolved data has 2 dimensions.
 
 | Dimensions |      Plotting function        |        Notes          |
 | ---------- | ----------------------------- | --------------------- |
-|    `2`     | <inv:#xarray.plot.line>       |                       |
-|    `3`     | <inv:#xarray.plot.pcolormesh> |                       |
-|    `>3`    | <inv:#xarray.plot.hist>       | Not fully implemented |
+|     2      | <inv:#xarray.plot.line>       |                       |
+|     3      | <inv:#xarray.plot.pcolormesh> |                       |
+|     4      | <inv:#mpl_toolkits.mplot3d.axes3d.Axes3D.voxels>| WIP |
+|     >4     | <inv:#xarray.plot.hist>       | Not fully implemented |
 
 
 ### 1D simulation
@@ -103,6 +104,10 @@ anim.show()
 
 ### 3D simulation
 
+```{warning}
+[Voxel](./plots.md#voxel-plots) animations are not currently implemented. 
+```
+
 Opening a 3D simulation as a multi-file dataset and plotting it will
 return a <inv:#xarray.plot.hist>. However, this may not be
 desirable. We can plot a 3D simulation along a certain plane in the
diff --git a/docs/figures/voxel_plot_high_res.png b/docs/figures/voxel_plot_high_res.png
new file mode 100644
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CL5Y+A

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HcmV?d00001

diff --git a/docs/index.md b/docs/index.md
index 336ce52..8e21c71 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -21,6 +21,7 @@ why_sdf_xarray.md
 loading_data.md
 understanding_datasets.md
 unit_conversion.md
+plots.md
 animation.md
 ```
 
diff --git a/docs/plots.md b/docs/plots.md
new file mode 100644
index 0000000..56f7629
--- /dev/null
+++ b/docs/plots.md
@@ -0,0 +1,91 @@
+---
+file_format: mystnb
+kernelspec:
+  name: python3
+---
+
+# Plots
+
+You can plot datasets using
+[`xarray.DataArray.epoch.plot`](project:#sdf_xarray.dataarray_accessor.EpochAccessor.plot).
+This is a custom <project:#sdf_xarray> plotting routine that builds on top of
+<inv:#xarray.DataArray.plot>, so you keep the familiar <inv:#xarray> plotting
+behaviour while using <project:#sdf_xarray> conveniences (see 
+[here](project:#sdf_xarray.dataarray_accessor.EpochAccessor.plot) for details).
+Under the hood, plotting is still handled by <inv:#matplotlib>, which means you
+can use the full <inv:#matplotlib> API to customise your figure.
+
+| Dimensions | Base plotting function        |        Notes          |
+| ---------- | ----------------------------- | --------------------- |
+|     1      | <inv:#xarray.plot.line>       |                       |
+|     2      | <inv:#xarray.plot.pcolormesh> |                       |
+|     3      | <inv:#mpl_toolkits.mplot3d.axes3d.Axes3D.voxels>| Custom functionality built for <project:#sdf_xarray> |
+|     >3     | <inv:#xarray.plot.hist>       | Not fully implemented |
+
+## Line plots
+
+One dimensional data will be plotted as a line. Multiple lines can be easily
+plotted at the same time.
+
+```{code-cell} ipython3
+import sdf_xarray as sdfxr
+import matplotlib.pyplot as plt
+ds = sdfxr.open_dataset("tutorial_dataset_1d/0010.sdf")
+da_1 = ds["Derived_Number_Density_Electron"]
+da_2 = ds["Derived_Number_Density_Ion"]
+da_1.epoch.plot(label = "Electron")
+da_2.epoch.plot(label = "Ion")
+plt.legend()
+plt.show()
+```
+
+## Mesh plots
+
+Two dimensional data will be plotted as a mesh.
+
+```{code-cell} ipython3
+ds = sdfxr.open_dataset("tutorial_dataset_2d/0010.sdf")
+da = ds["Derived_Number_Density_Electron"]
+da.epoch.plot()
+```
+
+## Voxel plots
+
+Three dimensional data will be plotted using voxels. This behaviour is not native
+to <inv:#xarray>, it has been custom built specifically for this package.
+
+```bash
+ds = sdfxr.open_dataset("tutorial_dataset_3d/0000.sdf")
+da = ds["Derived_Number_Density"]
+da.epoch.plot(vmin = 1e27)
+```
+
+![voxel_plot_high_res](./figures/voxel_plot_high_res.png)
+
+```{warning}
+Voxel plots can be extremely computationally expensive and may take longer than
+expected to plot.
+```
+
+Because voxel plots are very expensive, even with relatively small data arrays,
+plotting can be sped up by using <project:#sdf_xarray.dataarray_accessor.EpochAccessor.resize>,
+which uses interpolation to reduce the resolution.
+
+```{code-cell} ipython3
+ds = sdfxr.open_dataset("tutorial_dataset_3d/0005.sdf")
+da = ds["Derived_Number_Density"]
+da_resized = da.epoch.resize((20, 20, 20))
+da_resized.epoch.plot(vmin = 1e27)
+```
+
+## Histograms
+
+When the data array has four or more dimensions (or is specified by the user), it will
+be plotted as a histogram.
+
+```{code-cell} ipython3
+ds = sdfxr.open_dataset("tutorial_dataset_3d/0005.sdf")
+da = ds["Derived_Number_Density"]
+
+da.epoch.plot(hist = True)
+```
\ No newline at end of file
diff --git a/docs/understanding_datasets.md b/docs/understanding_datasets.md
index d2c1914..c0d9956 100644
--- a/docs/understanding_datasets.md
+++ b/docs/understanding_datasets.md
@@ -29,23 +29,10 @@ ds = sdfxr.open_mfdataset("tutorial_dataset_1d/*.sdf")
 ds["Electric_Field_Ex"]
 ```
 
-## Plotting
+## Visulisation
 
-You can plot datasets using
-[`xarray.DataArray.epoch.plot`](project:#sdf_xarray.dataarray_accessor.EpochAccessor.plot).
-This is a custom <project:#sdf_xarray> plotting routine that builds on top of
-<inv:#xarray.DataArray.plot>, so you keep the familiar <inv:#xarray> plotting
-behaviour while using <project:#sdf_xarray> conveniences (see 
-[here](project:#sdf_xarray.dataarray_accessor.EpochAccessor.plot) for details).
-Under the hood, plotting is still handled by <inv:#matplotlib>, which means you
-can use the full <inv:#matplotlib> API to customise your figure.
-
-```{code-cell} ipython3
-# This is discretized in both space and time
-ds["Electric_Field_Ex"].epoch.plot()
-plt.title("Electric field along the x-axis")
-plt.show()
-```
+`sdf-xarray` has built-in plotting and animation functionality, more details can
+be found on [Plots](./plots.md) and [Animations](./animation.md).
 
 ## Dimension slicing
 
@@ -56,6 +43,7 @@ for easy indexing. To quickly determine the number of time steps available,
 you can check the size of the time dimension.
 
 ```{code-cell} ipython3
+ds = sdfxr.open_mfdataset("tutorial_dataset_1d/*.sdf")
 # This corresponds to the number of individual SDF files loaded
 print(f"There are a total of {ds['time'].size} time steps")
 
@@ -122,6 +110,51 @@ print(f"Total particle energy absorbed: {ds["Total_Particle_Energy_in_Simulation
 print(f"The laser absorption fraction: {ds["Laser_Absorption_Fraction_in_Simulation"][-1].values:.1f} %")
 ```
 
+## Limit
+
+The `.epoch` accessor, has the ability to "limit" data arrays. This is a helper
+function which applies <inv:#xarray.DataArray.where> to the upper and lower bounds
+of each dimension. You can use `None` to preserve the existing limit.
+
+```{code-cell} ipython3
+ds = sdfxr.open_dataset("tutorial_dataset_2d/0020.sdf")
+da = ds["Derived_Number_Density_Electron"]
+da.epoch.plot()
+print(f"Orignal shape: {da.shape}")
+plt.show()
+```
+
+```{code-cell} ipython3
+da_limit = da.epoch.limit(((-2e-6, 2e-6), (None, 0)))
+da_limit.epoch.plot()
+print(f"New shape: {da_limit.shape}")
+plt.show()
+```
+
+## Resize
+
+The data arrays can be interpolated with <project:#sdf_xarray.dataarray_accessor.EpochAccessor.resize>
+to either increase or decrease the resolution while mantaining the general structure.
+Decreasing the size may be useful to download large data from HPCs to local machines
+or ploting with [voxel plots](./plots.md#voxel-plots). Be aware that the original
+data will not be preserved.
+
+```{code-cell} ipython3
+ds = sdfxr.open_dataset("tutorial_dataset_2d/0020.sdf")
+da = ds["Derived_Number_Density_Electron"]
+
+da.epoch.plot()
+print(f"Orignal shape: {da.shape}")
+plt.show()
+```
+
+```{code-cell} ipython3
+da_resized = da.epoch.resize((50, 50))
+da_resized.epoch.plot()
+print(f"New shape: {da_resized.shape}")
+plt.show()
+```
+
 ## Visualisation on HPC Machines
 
 In many cases you will be running EPOCH simulations via a HPC cluster and your

From 5be1c6300c2ef9e714b1dd835c90c47063012dcd Mon Sep 17 00:00:00 2001
From: Joel Adams <joelucadams@gmail.com>
Date: Thu, 23 Jul 2026 10:17:18 +0200
Subject: [PATCH 21/32] Fix linting

---
 src/sdf_xarray/dataarray_accessor.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/src/sdf_xarray/dataarray_accessor.py b/src/sdf_xarray/dataarray_accessor.py
index c330573..7b7f790 100644
--- a/src/sdf_xarray/dataarray_accessor.py
+++ b/src/sdf_xarray/dataarray_accessor.py
@@ -50,7 +50,7 @@ class EpochAccessor:
     def __init__(self, xarray_obj: xr.DataArray):
         self._obj = xarray_obj
 
-    def plot(self, hist = False, *args, **kwargs) -> DataArrayPlotAccessor:
+    def plot(self, hist=False, *args, **kwargs) -> DataArrayPlotAccessor:
         """
         Builds upon `xarray.DataArray.plot` while changing some of its default behaviours.
 
@@ -71,7 +71,7 @@ def plot(self, hist = False, *args, **kwargs) -> DataArrayPlotAccessor:
         """
         dims = self._obj.dims
 
-        if hist == True:
+        if hist:
             return self._obj.plot.hist(*args, **kwargs)
 
         if len(dims) == 1:

From f7ebfce28ad3d1db668ae6f20c13d2473aa993aa Mon Sep 17 00:00:00 2001
From: Joel Adams <joelucadams@gmail.com>
Date: Thu, 23 Jul 2026 10:17:37 +0200
Subject: [PATCH 22/32] Remove unusued import from tests

---
 tests/test_epoch_dataarray_accessor.py | 1 -
 1 file changed, 1 deletion(-)

diff --git a/tests/test_epoch_dataarray_accessor.py b/tests/test_epoch_dataarray_accessor.py
index 50338d7..b889023 100644
--- a/tests/test_epoch_dataarray_accessor.py
+++ b/tests/test_epoch_dataarray_accessor.py
@@ -8,7 +8,6 @@
 import xarray as xr
 from matplotlib.animation import PillowWriter
 from matplotlib.colors import ListedColormap
-from matplotlib.container import BarContainer
 from mpl_toolkits.mplot3d import Axes3D
 from packaging.version import Version
 

From f812213c4e21ed93f17ec8699a781391d7b79cba Mon Sep 17 00:00:00 2001
From: Joel Adams <joelucadams@gmail.com>
Date: Thu, 23 Jul 2026 10:19:36 +0200
Subject: [PATCH 23/32] Fix backticks in plotting docstring

---
 src/sdf_xarray/dataarray_accessor.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/src/sdf_xarray/dataarray_accessor.py b/src/sdf_xarray/dataarray_accessor.py
index 7b7f790..819d8ba 100644
--- a/src/sdf_xarray/dataarray_accessor.py
+++ b/src/sdf_xarray/dataarray_accessor.py
@@ -63,7 +63,7 @@ def plot(self, hist=False, *args, **kwargs) -> DataArrayPlotAccessor:
         Parameters
         ----------
         hist
-            If `True`, will plot a histogram regardless of dimensionality (default = False).
+            If ``True``, will plot a histogram regardless of dimensionality (default = ``False``).
         args
             Positional arguments passed to `xarray.DataArray.plot`.
         kwargs

From ba158750cd88c352806ae1f22b8620e4baf7ceb1 Mon Sep 17 00:00:00 2001
From: Joel Adams <joelucadams@gmail.com>
Date: Thu, 23 Jul 2026 10:37:48 +0200
Subject: [PATCH 24/32] rename docs plots to plotting

---
 docs/index.md                  | 2 +-
 docs/{plots.md => plotting.md} | 8 ++++++--
 2 files changed, 7 insertions(+), 3 deletions(-)
 rename docs/{plots.md => plotting.md} (97%)

diff --git a/docs/index.md b/docs/index.md
index 8e21c71..8cdfb2b 100644
--- a/docs/index.md
+++ b/docs/index.md
@@ -21,7 +21,7 @@ why_sdf_xarray.md
 loading_data.md
 understanding_datasets.md
 unit_conversion.md
-plots.md
+plotting.md
 animation.md
 ```
 
diff --git a/docs/plots.md b/docs/plotting.md
similarity index 97%
rename from docs/plots.md
rename to docs/plotting.md
index 56f7629..847af17 100644
--- a/docs/plots.md
+++ b/docs/plotting.md
@@ -4,7 +4,7 @@ kernelspec:
   name: python3
 ---
 
-# Plots
+# Plotting
 
 You can plot datasets using
 [`xarray.DataArray.epoch.plot`](project:#sdf_xarray.dataarray_accessor.EpochAccessor.plot).
@@ -47,6 +47,7 @@ Two dimensional data will be plotted as a mesh.
 ds = sdfxr.open_dataset("tutorial_dataset_2d/0010.sdf")
 da = ds["Derived_Number_Density_Electron"]
 da.epoch.plot()
+plt.show()
 ```
 
 ## Voxel plots
@@ -54,10 +55,11 @@ da.epoch.plot()
 Three dimensional data will be plotted using voxels. This behaviour is not native
 to <inv:#xarray>, it has been custom built specifically for this package.
 
-```bash
+```python
 ds = sdfxr.open_dataset("tutorial_dataset_3d/0000.sdf")
 da = ds["Derived_Number_Density"]
 da.epoch.plot(vmin = 1e27)
+plt.show()
 ```
 
 ![voxel_plot_high_res](./figures/voxel_plot_high_res.png)
@@ -76,6 +78,7 @@ ds = sdfxr.open_dataset("tutorial_dataset_3d/0005.sdf")
 da = ds["Derived_Number_Density"]
 da_resized = da.epoch.resize((20, 20, 20))
 da_resized.epoch.plot(vmin = 1e27)
+plt.show()
 ```
 
 ## Histograms
@@ -88,4 +91,5 @@ ds = sdfxr.open_dataset("tutorial_dataset_3d/0005.sdf")
 da = ds["Derived_Number_Density"]
 
 da.epoch.plot(hist = True)
+plt.show()
 ```
\ No newline at end of file

From cc77c4ce74ebffcc5d877b7eab76b61cdb88ad1f Mon Sep 17 00:00:00 2001
From: Joel Adams <joelucadams@gmail.com>
Date: Thu, 23 Jul 2026 10:38:09 +0200
Subject: [PATCH 25/32] Fix plotting link in why_sdf_xarray

---
 docs/why_sdf_xarray.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/why_sdf_xarray.md b/docs/why_sdf_xarray.md
index 76bf3f9..58cecfb 100644
--- a/docs/why_sdf_xarray.md
+++ b/docs/why_sdf_xarray.md
@@ -7,7 +7,7 @@ There are several benefits to using this package over the [`sdf_helper`](https:/
 - [data to numpy and pandas](https://docs.xarray.dev/en/stable/user-guide/pandas.html) - Data can be easily converted to [numpy](https://www.numpy.org/) or [pandas](https://pandas.pydata.org/) if you prefer to work with raw data.
 - [data labelling](project:understanding_datasets.md) - All SDF files come with a bunch of information about them such as the `dimensions`, `units` and `name` of the variable. In <inv:#xarray> these are added to each variable making it much easier to read.
 - [lazy/partial loading](https://docs.xarray.dev/en/stable/internals/internal-design.html#lazy-loading) - This reduces the RAM requirements when loading large SDF files as we only load the actual array values when they are needed.
-- [plotting](project:understanding_datasets.md#plotting) - You can easily plot variables across several dimensions including time using built in <inv:#matplotlib> support.
+- [plotting](project:plotting.md) - You can easily plot variables across several dimensions including time using built in <inv:#matplotlib> support.
 - [animating](project:animation.md) - Visualise your data across time or slice through another dimension and make beautiful GIFs for your presentations.
 - [deck loading](loading-input-deck) - <project:#sdf_xarray> automatically loads in the associated `input.deck` utilised when creating the simulation so that you can access setup variables.
 - [easier unit conversion](project:unit_conversion.md) - Convert dimensions and variable units to other types with the help of [`pint`](https://pint.readthedocs.io/en/stable).

From 158f04d502f6f4d36982744f569bb06c61cbe397 Mon Sep 17 00:00:00 2001
From: Joel Adams <joelucadams@gmail.com>
Date: Thu, 23 Jul 2026 10:38:15 +0200
Subject: [PATCH 26/32] Fix spelling mistakes

---
 docs/understanding_datasets.md |  6 +++---
 src/sdf_xarray/plotting.py     | 12 ++++++------
 2 files changed, 9 insertions(+), 9 deletions(-)

diff --git a/docs/understanding_datasets.md b/docs/understanding_datasets.md
index c0d9956..fde4828 100644
--- a/docs/understanding_datasets.md
+++ b/docs/understanding_datasets.md
@@ -29,7 +29,7 @@ ds = sdfxr.open_mfdataset("tutorial_dataset_1d/*.sdf")
 ds["Electric_Field_Ex"]
 ```
 
-## Visulisation
+## Visualisation
 
 `sdf-xarray` has built-in plotting and animation functionality, more details can
 be found on [Plots](./plots.md) and [Animations](./animation.md).
@@ -54,7 +54,7 @@ print(f"The time at the 20th simulation step is {sim_time:.2e} s")
 
 You can select and extract a single simulation snapshot using the integer
 index of the time step with the <inv:#xarray.Dataset.isel> function. This can be
-done by passsing the index to the `time` parameter (e.g., `time=0` for
+done by passing the index to the `time` parameter (e.g., `time=0` for
 the first snapshot).
 
 ```{code-cell} ipython3
@@ -62,7 +62,7 @@ ds["Electric_Field_Ex"].isel(time=20)
 ```
 
 We can also use the <inv:#xarray.Dataset.sel> function if you wish to pass a
-value intead of an index.
+value instead of an index.
 
 ```{tip}
 If you know roughly what time you wish to select but not the exact value
diff --git a/src/sdf_xarray/plotting.py b/src/sdf_xarray/plotting.py
index a384e8e..79674f9 100644
--- a/src/sdf_xarray/plotting.py
+++ b/src/sdf_xarray/plotting.py
@@ -52,7 +52,7 @@ def get_frame_title(
     t_axis_units_formatted = f" [{t_axis_units}]" if t_axis_units else ""
     title_t_axis = f"{data[t].long_name} = {t_axis_value:.2e}{t_axis_units_formatted}"
 
-    # Adds sdf name to the title, if specifed
+    # Adds sdf name to the title, if specified
     title_sdf = f", {frame:04d}.sdf" if display_sdf_name else ""
     return f"{title_custom}{title_t_axis}{title_sdf}"
 
@@ -122,7 +122,7 @@ def calculate_window_boundaries(
     t: str = "time",
 ) -> np.ndarray:
     """Calculate the boundaries a moving window frame. If the user specifies xlim, this will
-    be used as the initial boundaries and the window will move along acordingly.
+    be used as the initial boundaries and the window will move along accordingly.
 
     Parameters
     ----------
@@ -153,7 +153,7 @@ def calculate_window_boundaries(
         window_boundaries[i, 0] = x_grid_non_nan[0] - x_half_cell
         window_boundaries[i, 1] = x_grid_non_nan[-1] + x_half_cell
 
-    # User's choice for initial window edge supercedes the one calculated
+    # User's choice for initial window edge supersedes the one calculated
     if xlim is not None:
         window_boundaries = window_boundaries + xlim - window_boundaries[0]
     return window_boundaries
@@ -225,9 +225,9 @@ def voxel_plot(
     vmax
         Maximum value. If `mask` is not stated, will be used to define the mask.
     vcenter
-        Center value of the colourmap. Useful for diverging colourmaps with non-symetrical data.
+        Center value of the colourmap. Useful for diverging colourmaps with non-symmetrical data.
     mask
-        Array of bools specifing which cells to show. Must be same size as `da`
+        Array of bools specifying which cells to show. Must be same size as ``da``
     xlim, ylim, zlim
         Sets the limits of the plot.
     aspect
@@ -235,7 +235,7 @@ def voxel_plot(
     elev
         Elevation angle in degrees. (default = 30)
     azim
-        Azimithul angle in degrees. (default = -60)
+        Azimuthal angle in degrees. (default = -60)
     cmap
         Colourmap (default = "viridis")
     cbar_scale

From c9df175ebc5fafdabd26656f2e7f8ff66a01f87d Mon Sep 17 00:00:00 2001
From: Joel Adams <joelucadams@gmail.com>
Date: Mon, 27 Jul 2026 11:16:16 +0100
Subject: [PATCH 27/32] Change name of resize accessor link in docs

---
 docs/plotting.md | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/docs/plotting.md b/docs/plotting.md
index 847af17..80f76c5 100644
--- a/docs/plotting.md
+++ b/docs/plotting.md
@@ -70,7 +70,7 @@ expected to plot.
 ```
 
 Because voxel plots are very expensive, even with relatively small data arrays,
-plotting can be sped up by using <project:#sdf_xarray.dataarray_accessor.EpochAccessor.resize>,
+plotting can be sped up by using [`xarray.DataArray.epoch.resize`](project:#sdf_xarray.dataarray_accessor.EpochAccessor.resize),
 which uses interpolation to reduce the resolution.
 
 ```{code-cell} ipython3

From 1621bbdc9a830eb422c0bc65b0c37851e8d3b793 Mon Sep 17 00:00:00 2001
From: Joel Adams <joelucadams@gmail.com>
Date: Mon, 27 Jul 2026 11:26:53 +0100
Subject: [PATCH 28/32] Fix new ruff rules

---
 pyproject.toml | 2 ++
 1 file changed, 2 insertions(+)

diff --git a/pyproject.toml b/pyproject.toml
index 94ab729..158f2c7 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -135,6 +135,8 @@ ignore = [
   "PLR2004", # magic-comparison
   "B9",      # flake8-bugbear opinionated warnings
   "PLR0913", # remove maximum number of arguments in a function
+  "PLR0917", # remove maximum number of positional arguments in a function
+  "BLE001",  # allow capturing of base exception
 ]
 exclude = ["**/_version.py"] # Auto-generated file
 

From ed2593c6ea54e3bc1704336b616a1a6c23834f09 Mon Sep 17 00:00:00 2001
From: Joel Adams <57064123+JoelLucaAdams@users.noreply.github.com>
Date: Tue, 28 Jul 2026 10:11:40 +0100
Subject: [PATCH 29/32] Apply suggestions from code review

Co-authored-by: Liam Pattinson <LiamPattinson@users.noreply.github.com>
---
 docs/understanding_datasets.md       | 2 +-
 src/sdf_xarray/dataarray_accessor.py | 2 +-
 src/sdf_xarray/plotting.py           | 2 +-
 3 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/docs/understanding_datasets.md b/docs/understanding_datasets.md
index fde4828..480452f 100644
--- a/docs/understanding_datasets.md
+++ b/docs/understanding_datasets.md
@@ -112,7 +112,7 @@ print(f"The laser absorption fraction: {ds["Laser_Absorption_Fraction_in_Simulat
 
 ## Limit
 
-The `.epoch` accessor, has the ability to "limit" data arrays. This is a helper
+The `.epoch` accessor has the ability to "limit" data arrays. This is a helper
 function which applies <inv:#xarray.DataArray.where> to the upper and lower bounds
 of each dimension. You can use `None` to preserve the existing limit.
 
diff --git a/src/sdf_xarray/dataarray_accessor.py b/src/sdf_xarray/dataarray_accessor.py
index 819d8ba..f9bf69c 100644
--- a/src/sdf_xarray/dataarray_accessor.py
+++ b/src/sdf_xarray/dataarray_accessor.py
@@ -144,7 +144,7 @@ def resize(
         for i in range(len(da_resized.dims)):
             coord = list(da_resized.dims)[i]
 
-            if coord[-4:] == "_mid":
+            if coord.endswith("_mid"):
                 # If the coordinate is a midpoint coordinate, care must be taken to resize correctly
                 vertex_coord = _recover_vertex_coord(da[coord])
                 vertex_coord_resized = np.linspace(
diff --git a/src/sdf_xarray/plotting.py b/src/sdf_xarray/plotting.py
index 79674f9..cf9dbc4 100644
--- a/src/sdf_xarray/plotting.py
+++ b/src/sdf_xarray/plotting.py
@@ -212,7 +212,7 @@ def voxel_plot(
     **kwargs,
 ) -> tuple[plt.Figure, plt.Axes]:
     """
-    Will take 3 dimensional data and plot it as voxels.
+    Plot 3-dimensional data as voxels.
 
     Parameters
     ----------

From 357d55c683ad6fea6302cbcf4d9579c5bf487353 Mon Sep 17 00:00:00 2001
From: Joel Adams <joelucadams@gmail.com>
Date: Tue, 28 Jul 2026 10:21:28 +0100
Subject: [PATCH 30/32] Fix broken internal plotting links in docs

---
 docs/animation.md              | 2 +-
 docs/understanding_datasets.md | 4 ++--
 2 files changed, 3 insertions(+), 3 deletions(-)

diff --git a/docs/animation.md b/docs/animation.md
index 9e84580..49cd723 100644
--- a/docs/animation.md
+++ b/docs/animation.md
@@ -105,7 +105,7 @@ anim.show()
 ### 3D simulation
 
 ```{warning}
-[Voxel](./plots.md#voxel-plots) animations are not currently implemented. 
+[Voxel](./plotting.md#voxel-plots) animations are not currently implemented. 
 ```
 
 Opening a 3D simulation as a multi-file dataset and plotting it will
diff --git a/docs/understanding_datasets.md b/docs/understanding_datasets.md
index 480452f..087731b 100644
--- a/docs/understanding_datasets.md
+++ b/docs/understanding_datasets.md
@@ -32,7 +32,7 @@ ds["Electric_Field_Ex"]
 ## Visualisation
 
 `sdf-xarray` has built-in plotting and animation functionality, more details can
-be found on [Plots](./plots.md) and [Animations](./animation.md).
+be found on [](./plotting.md) and [](./animation.md).
 
 ## Dimension slicing
 
@@ -136,7 +136,7 @@ plt.show()
 The data arrays can be interpolated with <project:#sdf_xarray.dataarray_accessor.EpochAccessor.resize>
 to either increase or decrease the resolution while mantaining the general structure.
 Decreasing the size may be useful to download large data from HPCs to local machines
-or ploting with [voxel plots](./plots.md#voxel-plots). Be aware that the original
+or ploting with [](./plotting.md#voxel-plots). Be aware that the original
 data will not be preserved.
 
 ```{code-cell} ipython3

From aec2cc96c58d5fa1d0a2dbb09b75bbd86f8bbbe3 Mon Sep 17 00:00:00 2001
From: Joel Adams <joelucadams@gmail.com>
Date: Tue, 28 Jul 2026 10:21:40 +0100
Subject: [PATCH 31/32] Remove types from `shift_cmap` docstring

---
 src/sdf_xarray/plotting.py | 11 +++++------
 1 file changed, 5 insertions(+), 6 deletions(-)

diff --git a/src/sdf_xarray/plotting.py b/src/sdf_xarray/plotting.py
index cf9dbc4..72a582c 100644
--- a/src/sdf_xarray/plotting.py
+++ b/src/sdf_xarray/plotting.py
@@ -81,20 +81,19 @@ def shift_cmap(
 
     Parameters
     ----------
-    cmap : str or matplotlib.colors.Colormap
+    cmap
         The name of the original colormap (e.g., 'viridis') or the colormap object itself.
-    vmin : float
+    vmin
         The minimum value of your data range.
-    vmax : float
+    vmax
         The maximum value of your data range.
-    vcenter : float
+    vcenter
         The data value that should map to the visual midpoint (0.5) of the colormap.
-    N : int, default 1024
+    N
         The number of interpolation steps (color bins) in the new colormap.
 
     Returns
     -------
-    matplotlib.colors.ListedColormap
         The newly constructed, shifted colormap.
     """
     import matplotlib.colors as mc  # noqa: PLC0415

From 71a282c6ed5f9cfeac5e252e1afc9c8dbda31dec Mon Sep 17 00:00:00 2001
From: Joel Adams <joelucadams@gmail.com>
Date: Tue, 28 Jul 2026 10:31:18 +0100
Subject: [PATCH 32/32] refactor dataarray tests to use auto close fig fixture
 with `autouse=True`

---
 tests/test_epoch_dataarray_accessor.py | 46 ++++++++------------------
 1 file changed, 14 insertions(+), 32 deletions(-)

diff --git a/tests/test_epoch_dataarray_accessor.py b/tests/test_epoch_dataarray_accessor.py
index b889023..4ec4249 100644
--- a/tests/test_epoch_dataarray_accessor.py
+++ b/tests/test_epoch_dataarray_accessor.py
@@ -26,11 +26,10 @@
 TEST_FILES_DIR_3D = download.fetch_dataset("test_files_3D")
 
 
-@pytest.fixture
-def subplots():
-    fig, ax = plt.subplots()
-    yield (fig, ax)
-    plt.close(fig)
+@pytest.fixture(autouse=True)
+def close_figs():
+    yield
+    plt.close("all")
 
 
 def test_animation_accessor():
@@ -246,21 +245,21 @@ def test_compute_global_limits_NaNs():
         assert result_max == pytest.approx(expected_result_max, abs=1e-1)
 
 
-def test_epoch_plot_simple_1d_dataset(subplots):
+def test_epoch_plot_simple_1d_dataset():
     with xr.open_mfdataset(
         TEST_FILES_DIR_1D.glob("*.sdf"),
         compat="no_conflicts",
         join="outer",
         preprocess=SDFPreprocess(),
     ) as ds:
-        _, ax = subplots
+        _, ax = plt.subplots()
         ds["Derived_Number_Density_electron"].isel(time=0).epoch.plot(ax=ax)
 
         assert len(ax.lines) == 1
         assert ax.get_xlabel() == "X [m]"
 
 
-def test_epoch_plot_simple_2d_dataset(subplots):
+def test_epoch_plot_simple_2d_dataset():
     with xr.open_mfdataset(
         TEST_FILES_DIR_2D_MW.glob("*.sdf"),
         preprocess=SDFPreprocess(),
@@ -268,7 +267,7 @@ def test_epoch_plot_simple_2d_dataset(subplots):
         compat="no_conflicts",
         join="outer",
     ) as ds:
-        _, ax = subplots
+        _, ax = plt.subplots()
         ds["Derived_Number_Density_electron"].isel(time=0).epoch.plot(ax=ax)
 
         assert len(ax.collections) > 0
@@ -276,9 +275,9 @@ def test_epoch_plot_simple_2d_dataset(subplots):
         assert ax.get_ylabel() == "Y [m]"
 
 
-def test_epoch_plot_simple_3d_dataset_slice(subplots):
+def test_epoch_plot_simple_3d_dataset_slice():
     with xr.open_dataset(TEST_FILES_DIR_3D / "0001.sdf") as ds:
-        _, ax = subplots
+        _, ax = plt.subplots()
         ds["Derived_Number_Density_Electron"].isel(Z_Grid_mid=0).epoch.plot(ax=ax)
 
         assert len(ax.collections) > 0
@@ -286,7 +285,7 @@ def test_epoch_plot_simple_3d_dataset_slice(subplots):
         assert ax.get_ylabel() == "Y [m]"
 
 
-def test_epoch_plot_flips_axis_order_for_2d_data(subplots):
+def test_epoch_plot_flips_axis_order_for_2d_data():
     with xr.open_mfdataset(
         TEST_FILES_DIR_2D_MW.glob("*.sdf"),
         preprocess=SDFPreprocess(),
@@ -294,14 +293,14 @@ def test_epoch_plot_flips_axis_order_for_2d_data(subplots):
         compat="no_conflicts",
         join="outer",
     ) as ds:
-        _, ax = subplots
+        _, ax = plt.subplots()
         ds["Derived_Number_Density_electron"].isel(time=0).epoch.plot(ax=ax)
 
         assert ax.get_xlabel() == "X [m]"
         assert ax.get_ylabel() == "Y [m]"
 
 
-def test_epoch_plot_flips_axis_order_for_2d_data_with_additional_params(subplots):
+def test_epoch_plot_flips_axis_order_for_2d_data_with_additional_params():
     with xr.open_mfdataset(
         TEST_FILES_DIR_2D_MW.glob("*.sdf"),
         preprocess=SDFPreprocess(),
@@ -309,7 +308,7 @@ def test_epoch_plot_flips_axis_order_for_2d_data_with_additional_params(subplots
         compat="no_conflicts",
         join="outer",
     ) as ds:
-        _, ax = subplots
+        _, ax = plt.subplots()
         ds["Derived_Number_Density_electron"].isel(time=0).epoch.plot(
             ax=ax,
             xlim=(0.5, 1.0),
@@ -351,12 +350,6 @@ def _make_3d_da(shape=(4, 5, 6)):
     )
 
 
-@pytest.fixture
-def close_figs():
-    yield
-    plt.close("all")
-
-
 def test_recover_vertex_coord_size():
     mid = xr.DataArray(np.linspace(0.5, 4.5, 5))
     vertex = sxp._recover_vertex_coord(mid)
@@ -385,14 +378,12 @@ def test_shift_cmap_asymmetric_center():
     assert len(result.colors) == 200
 
 
-@pytest.mark.usefixtures("close_figs")
 def test_voxel_plot_returns_fig_and_ax():
     da = _make_3d_da()
     _, ax = sxp.voxel_plot(da)
     assert isinstance(ax, Axes3D)
 
 
-@pytest.mark.usefixtures("close_figs")
 def test_voxel_plot_accepts_axes():
     da = _make_3d_da()
     _, ax = plt.subplots(figsize=(8, 6), subplot_kw={"projection": "3d"})
@@ -400,7 +391,6 @@ def test_voxel_plot_accepts_axes():
     assert isinstance(ax, Axes3D)
 
 
-@pytest.mark.usefixtures("close_figs")
 def test_voxel_plot_axis_labels():
     da = _make_3d_da()
     _, ax = sxp.voxel_plot(da)
@@ -409,7 +399,6 @@ def test_voxel_plot_axis_labels():
     assert ax.get_zlabel() == "Z [m]"
 
 
-@pytest.mark.usefixtures("close_figs")
 def test_voxel_plot_default_axis_limits():
     da = _make_3d_da()
     _, ax = sxp.voxel_plot(da)
@@ -421,7 +410,6 @@ def test_voxel_plot_default_axis_limits():
     assert zlim[0] < zlim[1]
 
 
-@pytest.mark.usefixtures("close_figs")
 def test_voxel_plot_with_xlim_ylim_zlim():
     da = _make_3d_da()
     x0, x1 = 2e-6, 8e-6
@@ -433,21 +421,18 @@ def test_voxel_plot_with_xlim_ylim_zlim():
     assert ax.get_zlim() == pytest.approx((z0, z1), rel=0.1)
 
 
-@pytest.mark.usefixtures("close_figs")
 def test_voxel_plot_with_explicit_vmin_vmax():
     da = _make_3d_da()
     _, ax = sxp.voxel_plot(da, vmin=0.2, vmax=0.8)
     assert isinstance(ax, Axes3D)
 
 
-@pytest.mark.usefixtures("close_figs")
 def test_voxel_plot_with_vcenter():
     da = _make_3d_da()
     _, ax = sxp.voxel_plot(da, cmap="RdBu", vcenter=1e-2)
     assert isinstance(ax, Axes3D)
 
 
-@pytest.mark.usefixtures("close_figs")
 def test_voxel_plot_with_custom_mask():
     da = _make_3d_da()
     mask = da.values > 0.5
@@ -455,7 +440,6 @@ def test_voxel_plot_with_custom_mask():
     assert isinstance(ax, Axes3D)
 
 
-@pytest.mark.usefixtures("close_figs")
 def test_voxel_plot_aspect_auto():
     da = _make_3d_da()
     _, ax = sxp.voxel_plot(da, aspect="auto")
@@ -472,7 +456,6 @@ def test_voxel_plot_aspect_auto():
     assert box[2] / box[0] == pytest.approx(z_range / x_range, rel=0.05)
 
 
-@pytest.mark.usefixtures("close_figs")
 def test_voxel_plot_aspect_custom_tuple():
     da = _make_3d_da()
     _, ax = sxp.voxel_plot(da, aspect=(1.0, 2.0, 3.0))
@@ -481,7 +464,6 @@ def test_voxel_plot_aspect_custom_tuple():
     assert box[2] / box[0] == pytest.approx(3.0, rel=0.01)
 
 
-@pytest.mark.usefixtures("close_figs")
 def test_epoch_plot_dispatches_to_voxel_for_3d_spatial_data():
     with xr.open_dataset(TEST_FILES_DIR_3D / "0001.sdf") as ds:
         da = ds["Derived_Number_Density_Electron"].isel(