notes

Author: wpbonelli

flopy4/__init__.py

@@ -238,6 +238,7 @@ def init_tree(
     cls = type(self)
     spec = fields_dict(cls)
     dimensions = set()
+    coordinates = {}
     array_vars = {}
     scalar_vars = {}
     array_vals = {}
@@ -281,9 +282,18 @@ def _yield_arrays(spec, vals):
 
     array_vals = dict(list(_yield_arrays(spec=array_vars, vals=self.__dict__)))
 
+    # add coordinate arrays to the data tree
+    for dim in dimensions:
+        var = spec[dim]
+        coord = var.metadata.get("coord", None)
+        if coord:
+            value = np.arange(array_vals[dim][1].shape[0])
+            coordinates[coord] = value
+
     self.data = DataTree(
         Dataset(
-            array_vals,
+            data_vars=array_vals,
+            coords=coordinates,
             attrs={
                 n: v for n, v in scalar_vals.items() if n not in dimensions
             },

flopy4/mf6/__init__.py

@@ -43,7 +43,7 @@ class PeriodData:
         nstp: int = field(default=1)
         tsmult: float = field(default=1.0)
 
-    nper: int = field(default=1, metadata={"block": "dimensions"})
+    nper: int = field(default=1, metadata={"block": "dimensions", "dim": {"coord": "kper"}})
     perioddata: list[PeriodData] = field(
         default=Factory(list),
         metadata={"block": "perioddata", "dims": ("nper",)},

flopy4/mf6/gwf/dis.py

@@ -22,9 +22,9 @@ class Dis(Package):
     export_array_netcdf: bool = field(
         default=False, metadata={"block": "options"}
     )
-    nlay: int = field(default=1, metadata={"block": "dimensions"})
-    ncol: int = field(default=2, metadata={"block": "dimensions"})
-    nrow: int = field(default=2, metadata={"block": "dimensions"})
+    nlay: int = field(default=1, metadata={"block": "dimensions", "dim": {"coord": "k"}})
+    ncol: int = field(default=2, metadata={"block": "dimensions", "dim": {"coord": "i"}})
+    nrow: int = field(default=2, metadata={"block": "dimensions", "dim": {"coord": "j"}})
     delr: NDArray[np.floating] = field(
         default=1.0,
         metadata={"block": "griddata", "dims": ("ncol",)},

flopy4/todo.md

@@ -1,34 +1,23 @@
 # todo
 
-## perf
+- deduplicate data trees
 
-### memory
-
-Need to deduplicate data trees.
 Each component should get a view into the root (as far as it's aware) tree
 unless it's the root (i.e. simulation) itself, or it's not attached to any
 parent context, in which case it's the root of its own tree.
 
-### speed
-
-Need faster dimension resolution.
-We know the path from simulation to dis and tdis, no reason to search for it.
-
-## api
-
-### components
+- subcomponent accessors
 
 I think for access by name we want dict style e.g. `gwf["chd1"]`,
-like imod-python does it.
+like imod-python does it?
 
 By type, e.g. `gwf.chd`, where it's either a single component,
 or a dict by name (or auto-increment index) for multipackages?
 
-## docs
-
-Reproduce flopy3 quickstart.
-Keep it minimal, just show an equivalent with the prototype.
+- first class dimension support
 
-More detailed demo notebook.
-Compare/contrast implementations and different patterns in
-more detail.
+Right now array variables just declare their expected dimension. And the
+dimensions are looked up by unguided search across the data tree's vars,
+from the root down. Let variables declare themselves as dimensions? With
+optional coordinate arrays autogenerated in the right size and added to
+the dataset? And allow local vs global dimensions?