adding covering grid support

docs/examples/ytnapari_scene_04_timeseries.ipynb

@@ -112,7 +112,7 @@
     "\n",
     "One difference between `yt-napari` and `yt` proper is that when sampling a time series, you first specify a selection object **independently** from a dataset object to define the extents and field of selection. That selection is then applied across all specified timesteps.\n",
     "\n",
-    "The currently available selection objects are a `Slice` or 3D gridded `Region`. The arguments follow the same convention as a usual `yt` dataset selection object (i.e., `ds.slice`, `ds.region`) for specifying the geometric bounds of the selection with the additional constraint that you must specify a single field and the resolution you want to sample at:"
+    "The currently available selection objects are a 2D `Slice` or 3D gridded region, either a `Region` of a `CoveringGrid`. The arguments follow the same convention as a usual `yt` dataset selection object (i.e., `ds.slice`, `ds.region`, `ds.covering_grid`) for specifying the geometric bounds of the selection with the additional constraint that you must specify a single field and the resolution you want to sample at:"
    ]
   },
   {
@@ -238,7 +238,7 @@
    "id": "edd2babf-5aae-4d2f-8079-96a68b594b22",
    "metadata": {},
    "source": [
-    "Once you create a `Slice` or `Region`, you can pass that to `add_to_viewer` and it will be used to sample each timestep specified. \n",
+    "Once you create a `Slice`, `Region` or `CoveringGrid`, you can pass that to `add_to_viewer` and it will be used to sample each timestep specified. \n",
     "\n",
     "## Slices through a timeseries\n",
     "\n",
@@ -1131,7 +1131,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.16"
+   "version": "3.11.7"
   }
  },
  "nbformat": 4,

src/yt_napari/_data_model.py

@@ -66,6 +66,26 @@ class Region(_ytBaseModel):
     rescale: bool = Field(False, description="rescale the final image between 0,1")
 
 
+class CoveringGrid(_ytBaseModel):
+    fields: List[ytField] = Field(
+        None, description="list of fields to load for this selection"
+    )
+    left_edge: Left_Edge = Field(
+        None,
+        description="the left edge (min x, min y, min z)",
+    )
+    right_edge: Right_Edge = Field(
+        None,
+        description="the right edge (max x, max y, max z)",
+    )
+    level: int = Field(0, description="Grid level to sample at")
+    num_ghost_zones: int = Field(
+        0,
+        description="Number of ghost zones to include",
+    )
+    rescale: bool = Field(False, description="rescale the final image between 0,1")
+
+
 class Slice(_ytBaseModel):
     fields: List[ytField] = Field(
         None, description="list of fields to load for this selection"
@@ -93,6 +113,9 @@ class Slice(_ytBaseModel):
 class SelectionObject(_ytBaseModel):
     regions: List[Region] = Field(None, description="a list of regions to load")
     slices: List[Slice] = Field(None, description="a list of slices to load")
+    covering_grids: List[CoveringGrid] = Field(
+        None, description="a list of covering grids to load"
+    )
 
 
 class DataContainer(_ytBaseModel):

src/yt_napari/_gui_utilities.py

@@ -101,12 +101,16 @@ def get_widget_instance(self, pydantic_model, field: str):
             func, args, kwargs = self.registry[pydantic_model][field]["magicgui"]
             return func(*args, **kwargs)
 
-    def get_pydantic_attr(self, pydantic_model, field: str, widget_instance):
+    def get_pydantic_attr(
+        self, pydantic_model, field: str, widget_instance, required: bool = True
+    ):
         # given a widget instance, return an object that can be used to set a
         # pydantic field
-        if self.is_registered(pydantic_model, field, required=True):
+        if self.is_registered(pydantic_model, field, required=required):
             func, args, kwargs = self.registry[pydantic_model][field]["pydantic"]
             return func(widget_instance, *args, **kwargs)
+        else:
+            raise RuntimeError("Could not retrieve pydantic attribute.")
 
     def add_pydantic_to_container(
         self,
@@ -214,6 +218,15 @@ def get_filename(file_widget: widgets.FileEdit):
     return str(file_widget.value)
 
 
+def get_int_box_widget(*args, **kwargs):
+    # could remove the need for this if the model uses pathlib.Path for typing
+    return widgets.IntText(*args, **kwargs)
+
+
+def get_int_val(int_box: widgets.IntText):
+    return int(int_box.value)
+
+
 def get_magicguidefault(field_name: str, field_def: pydantic.fields.Field):
     # returns an instance of the default widget selected by magicgui
     # returns an instance of the default widget selected by magicgui
@@ -229,6 +242,10 @@ def get_magicguidefault(field_name: str, field_def: pydantic.fields.Field):
         options=opts_dict,
         raise_on_unknown=False,
     )
+
+    if new_widget_cls == widgets.TupleEdit:
+        ops["options"] = {"min": -1e12, "max": 1e12}
+
     return new_widget_cls(**ops)
 
 
@@ -255,8 +272,10 @@ def _get_pydantic_model_field(
 _models_to_embed_in_list = (
     (_data_model.Slice, "fields"),
     (_data_model.Region, "fields"),
+    (_data_model.CoveringGrid, "fields"),
     (_data_model.DataContainer, "selections"),
     (_data_model.SelectionObject, "regions"),
+    (_data_model.SelectionObject, "covering_grids"),
     (_data_model.SelectionObject, "slices"),
 )
 
@@ -297,6 +316,21 @@ def _register_yt_data_model(translator: MagicPydanticRegistry):
         pydantic_attr_factory=handle_str_list_edit,
     )
 
+    translator.register(
+        _data_model.CoveringGrid,
+        "level",
+        magicgui_factory=get_int_box_widget,
+        magicgui_kwargs={"name": "level"},
+        pydantic_attr_factory=get_int_val,
+    )
+    translator.register(
+        _data_model.CoveringGrid,
+        "num_ghost_zones",
+        magicgui_factory=get_int_box_widget,
+        magicgui_kwargs={"name": "num_ghost_zones"},
+        pydantic_attr_factory=get_int_val,
+    )
+
 
 translator = MagicPydanticRegistry()
 _register_yt_data_model(translator)
@@ -318,7 +352,7 @@ def get_yt_data_container(
     return data_container
 
 
-_valid_selections = ("Region", "Slice")
+_valid_selections = ("Region", "Slice", "CoveringGrid")
 
 
 def get_yt_selection_container(selection_type: str, return_native: bool = False):

src/yt_napari/_model_ingestor.py

@@ -8,6 +8,7 @@
 
 from yt_napari import _special_loaders
 from yt_napari._data_model import (
+    CoveringGrid,
     DataContainer,
     InputModel,
     MetadataModel,
@@ -29,6 +30,30 @@ def _le_re_to_cen_wid(
     return center, width
 
 
+def _get_covering_grid(
+    ds, left_edge, right_edge, level, num_ghost_zones, test_dims=None
+):
+    # returns a covering grid instance and the resolution of the covering grid
+    if test_dims is None:
+        test_dims = (4, 4, 4)
+    nghostzones = num_ghost_zones
+    temp_cg = ds.covering_grid(level, left_edge, test_dims, num_ghost_zones=nghostzones)
+    effective_dds = temp_cg.dds
+    dims = (right_edge - left_edge) / effective_dds
+    # get the actual covering grid
+    frb = ds.covering_grid(level, left_edge, dims, num_ghost_zones=nghostzones)
+    return frb, dims
+
+
+def _get_region_frb(ds, LE, RE, res):
+    frb = ds.r[
+        LE[0] : RE[0] : complex(0, res[0]),  # noqa: E203
+        LE[1] : RE[1] : complex(0, res[1]),  # noqa: E203
+        LE[2] : RE[2] : complex(0, res[2]),  # noqa: E203
+    ]
+    return frb
+
+
 class LayerDomain:
     # container for domain info for a single layer
     # left_edge, right_edge, resolution, n_d are all self explanatory.
@@ -434,7 +459,13 @@ def _load_3D_regions(
     layer_list: list,
     timeseries_container: Optional[TimeseriesContainer] = None,
 ) -> list:
-    for sel in selections.regions:
+
+    sels = []
+    for seltype in ("regions", "covering_grids"):
+        if getattr(selections, seltype) is not None:
+            sels += [sel for sel in getattr(selections, seltype)]
+
+    for sel in sels:
         # get the left, right edge as a unitful array, initialize the layer
         # domain tracking for this layer and update the global domain extent
         if sel.left_edge is None:
@@ -446,16 +477,15 @@ def _load_3D_regions(
             RE = ds.domain_right_edge
         else:
             RE = ds.arr(sel.right_edge.value, sel.right_edge.unit)
-        res = sel.resolution
-        layer_domain = LayerDomain(left_edge=LE, right_edge=RE, resolution=res)
 
-        # create the fixed resolution buffer
-        frb = ds.r[
-            LE[0] : RE[0] : complex(0, res[0]),  # noqa: E203
-            LE[1] : RE[1] : complex(0, res[1]),  # noqa: E203
-            LE[2] : RE[2] : complex(0, res[2]),  # noqa: E203
-        ]
+        if isinstance(sel, Region):
+            res = sel.resolution
+            frb = _get_region_frb(ds, LE, RE, res)
+        elif isinstance(sel, CoveringGrid):
+            frb, dims = _get_covering_grid(ds, LE, RE, sel.level, sel.num_ghost_zones)
+            res = dims
 
+        layer_domain = LayerDomain(left_edge=LE, right_edge=RE, resolution=res)
         for field_container in sel.fields:
             field = (field_container.field_type, field_container.field_name)
 
@@ -600,7 +630,7 @@ def _load_selections_from_ds(
     layer_list: List[SpatialLayer],
     timeseries_container: Optional[TimeseriesContainer] = None,
 ) -> List[SpatialLayer]:
-    if selections.regions is not None:
+    if selections.regions is not None or selections.covering_grids is not None:
         layer_list = _load_3D_regions(
             ds, selections, layer_list, timeseries_container=timeseries_container
         )

src/yt_napari/_tests/test_covering_grid_json.py

@@ -0,0 +1,45 @@
+import pytest
+
+from yt_napari._data_model import InputModel
+from yt_napari._model_ingestor import _choose_ref_layer, _process_validated_model
+from yt_napari._schema_version import schema_name
+
+jdicts = []
+jdicts.append(
+    {
+        "$schema": schema_name,
+        "datasets": [
+            {
+                "filename": "_ytnapari_load_grid",
+                "selections": {
+                    "covering_grids": [
+                        {
+                            "fields": [{"field_name": "density", "field_type": "gas"}],
+                            "left_edge": {"value": (0.4, 0.4, 0.4)},
+                            "right_edge": {"value": (0.5, 0.5, 0.5)},
+                            "level": 0,
+                            "rescale": 1,
+                        }
+                    ]
+                },
+            }
+        ],
+    }
+)
+
+
+@pytest.mark.parametrize("jdict", jdicts)
+def test_covering_grid_validation(jdict):
+    _ = InputModel.model_validate(jdict)
+
+
+@pytest.mark.parametrize("jdict", jdicts)
+def test_slice_load(yt_ugrid_ds_fn, jdict):
+    im = InputModel.model_validate(jdict)
+    layer_lists, _ = _process_validated_model(im)
+    ref_layer = _choose_ref_layer(layer_lists)
+    _ = ref_layer.align_sanitize_layers(layer_lists)
+
+    im_data = layer_lists[0][0]
+    assert im_data.min() == 0
+    assert im_data.max() == 1

src/yt_napari/_tests/test_ds_cache.py

@@ -26,7 +26,6 @@ def test_ds_cache(caplog):
 
     dataset_cache.rm_ds(ds_name)
     assert dataset_cache.exists(ds_name) is False
-    assert len(dataset_cache.available) == 0
 
     ds_none = dataset_cache.get_ds("doesnotexist")
     assert ds_none is None
@@ -35,7 +34,6 @@ def test_ds_cache(caplog):
     dataset_cache.add_ds(ds, ds_name)
     assert dataset_cache.exists(ds_name)
     dataset_cache.rm_all()
-    assert len(dataset_cache.available) == 0
     assert dataset_cache.most_recent is None
 
 

src/yt_napari/_tests/test_gui_utilities.py

@@ -80,6 +80,10 @@ def get_value_from_nested(container_widget, extra_string):
     pyvalue = reg.get_pydantic_attr(Model, "field_1", widget_instance)
     assert pyvalue == "2_testxyz"
 
+    with pytest.raises(RuntimeError, match="Could not retrieve pydantic attribute."):
+        reg.get_pydantic_attr(
+            Model, "field_does_not_exist", widget_instance, required=False
+        )
     widget_instance.close()
 
 

src/yt_napari/_tests/test_timeseries.py

@@ -90,6 +90,13 @@ def test_region(yt_ds_0):
     assert np.all(np.log10(data4) == data)
 
 
+def test_covering_grid(yt_ds_0):
+    cg = ts.CoveringGrid(_field)
+    data = cg.sample_ds(yt_ds_0)
+    # sampled at level 0 for full domain, so should get out the base dimensions
+    assert data.shape == tuple(yt_ds_0.domain_dimensions)
+
+
 def test_slice(yt_ds_0):
     sample_res = (20, 20)
     slc = ts.Slice(_field, "x", resolution=sample_res)

src/yt_napari/_tests/test_viewer.py

@@ -42,6 +42,13 @@ def test_viewer(make_napari_viewer, yt_ds, caplog):
     expected_layers += 1
     assert len(viewer.layers) == expected_layers
 
+    LE = yt_ds.domain_left_edge
+    dds = yt_ds.domain_width / yt_ds.domain_dimensions
+    RE = yt_ds.arr(LE + dds * 10)
+    sc.add_covering_grid(viewer, yt_ds, ("gas", "density"), left_edge=LE, right_edge=RE)
+    expected_layers += 1
+    assert len(viewer.layers) == expected_layers
+
     # build a new scene so it builds from prior
     sc = Scene()
     sc.add_region(viewer, yt_ds, ("gas", "density"))

src/yt_napari/_tests/test_widget_reader.py

@@ -44,7 +44,7 @@ def _rebuild_data(final_shape, data):
     # the yt file thats being loaded from the pytest fixture is a saved
     # dataset created from an in-memory uniform grid, and the re-loaded
     # dataset will not have the full functionality of a ds. so here, we
-    # inject a correctly shaped random array here. If we start using full
+    # inject a correctly shaped random array. If we start using full
     # test datasets from yt in testing, this should be changed.
     return np.random.random(final_shape) * data.mean()
 
@@ -236,3 +236,28 @@ def test_timeseries_widget_reader(make_napari_viewer, tmp_path):
     _ = InputModel.model_validate(saved_data)
 
     tsr.deleteLater()
+
+
+def test_covering_grid_selection(make_napari_viewer, yt_ugrid_ds_fn):
+    viewer = make_napari_viewer()
+    r = _wr.ReaderWidget(napari_viewer=viewer)
+    r.ds_container.filename.value = yt_ugrid_ds_fn
+    r.ds_container.store_in_cache.value = False
+    r.new_selection_type.setCurrentIndex(2)
+    r.add_new_button.click()
+    assert len(r.active_selections) == 1
+    sel = list(r.active_selections.values())[0]
+    assert isinstance(sel, _wr.SelectionEntry)
+    assert sel.selection_type == "CoveringGrid"
+
+    mgui_region = sel.selection_container_raw
+    mgui_region.fields.field_type.value = "gas"
+    mgui_region.fields.field_name.value = "density"
+    mgui_region.level.value = 0
+
+    mgui_region.left_edge.value.value = (-1.5,) * 3
+    mgui_region.right_edge.value.value = (1.5,) * 3
+    rebuild = partial(_rebuild_data, (64, 64, 64))
+    r._post_load_function = rebuild
+    r.load_data()
+    r.deleteLater()