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wpbonelliwpbonelli
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resolve conflicts
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3 files changed

+738
-800
lines changed

3 files changed

+738
-800
lines changed

‎flopy4/mf6/codec/writer/filters.py‎

Lines changed: 1 addition & 3 deletions
Original file line numberDiff line numberDiff line change
@@ -34,9 +34,7 @@ def field_type(value: Any) -> FieldType:
3434

3535

3636
def array_how(value: xr.DataArray) -> str:
37-
# TODO
38-
# - detect constant arrays?
39-
# - above certain size, use external?
37+
# TODO above certain size, use external?
4038
if value.max() == value.min():
4139
return "constant"
4240
return "internal"

‎flopy4/mf6/converter.py‎

Lines changed: 73 additions & 70 deletions
Original file line numberDiff line numberDiff line change
@@ -9,7 +9,6 @@
99
import xattree
1010
from attrs import define
1111
from cattrs import Converter
12-
from modflow_devtools.dfn.schema.block import block_sort_key
1312
from numpy.typing import NDArray
1413
from xattree import get_xatspec
1514

@@ -88,7 +87,7 @@ def _path_to_tuple(field_name: str, path_value: Path) -> tuple:
8887
return (field_name.upper(), "FILEOUT", str(path_value))
8988

9089

91-
def _user_dims(value, field_value):
90+
def _hack_spatial_dims(value, field_value):
9291
# terrible hack to convert flat nodes dimension to 3d structured dims.
9392
# long term solution for this is to use a custom xarray index. filters
9493
# should then have access to all dimensions needed.
@@ -162,15 +161,18 @@ def _get_binding_blocks(value: Component) -> dict[str, dict[str, list[tuple]]]:
162161
if block_name not in blocks:
163162
blocks[block_name] = {}
164163
blocks[block_name][name] = [
165-
_Binding.from_component(comp).to_tuple()
166-
for comp in child
167-
if comp is not None
164+
_Binding.from_component(comp).to_tuple() for comp in child if comp is not None
168165
]
169166
case _:
170167
raise ValueError(f"Unexpected child type: {type(child)}")
171168

172169
return blocks
173170

171+
172+
def _has_spatial_dims(value: xr.DataArray) -> bool:
173+
return any(dim in value.dims for dim in ["nlay", "nrow", "ncol", "nodes"])
174+
175+
174176
def unstructure_component(value: Component) -> dict[str, Any]:
175177
dfnspec = value.dfn
176178
xatspec = xattree.get_xatspec(type(value))
@@ -183,13 +185,13 @@ def unstructure_component(value: Component) -> dict[str, Any]:
183185

184186
for field_name in block.keys():
185187
# Skip child components that have been processed as bindings
186-
if isinstance(value, Context) and field_name in xatspec.children:
187-
child_spec = xatspec.children[field_name]
188-
if hasattr(child_spec, "metadata") and "block" in child_spec.metadata: # type: ignore
189-
if child_spec.metadata["block"] == block_name: # type: ignore
190-
continue
188+
if (
189+
isinstance(value, Context)
190+
and (child_spec := xatspec.children.get(field_name, None))
191+
and child_spec.metadata["block"] == block_name
192+
):
193+
continue
191194

192-
field_value = data[field_name]
193195
# convert:
194196
# - bools to keywords
195197
# - paths to records
@@ -198,73 +200,74 @@ def unstructure_component(value: Component) -> dict[str, Any]:
198200
# - xarray DataArrays with 'nper' dimension to kper-sliced datasets
199201
# (and split the period data into separate kper-indexed blocks)
200202
# - other values to their original form
201-
if isinstance(field_value, bool):
202-
if field_value: # only write if true
203-
blocks[block_name][field_name] = field_value
204-
if isinstance(field_value, Path):
205-
rec = _path_to_tuple(field_name, field_value)
206-
field_name = rec[0] # '_file' suffix dropped
207-
blocks[block_name][field_name] = rec
208-
elif isinstance(field_value, datetime):
209-
blocks[block_name][field_name] = field_value.isoformat()
210-
elif isinstance(field_value, xr.DataArray):
211-
if field_name == "auxiliary":
212-
blocks[block_name][field_name] = tuple(field_value.values.tolist())
213-
elif "nper" not in field_value.dims:
214-
blocks[block_name][field_name] = _user_dims(value, field_value)
215-
else:
216-
period_data = {}
217-
period_blocks = {}
218-
has_spatial_dims = any(
219-
dim in field_value.dims for dim in ["nlay", "nrow", "ncol", "nodes"]
220-
)
221-
if has_spatial_dims:
222-
field_value = _user_dims(value, field_value)
223-
224-
period_data[field_name] = {
225-
kper: field_value.isel(nper=kper)
226-
for kper in range(field_value.sizes["nper"])
227-
}
203+
match field_value := data[field_name]:
204+
case None:
205+
pass
206+
case bool():
207+
if field_value: # only write if true
208+
blocks[block_name][field_name] = field_value
209+
case Path():
210+
rec = _path_to_tuple(field_name, field_value)
211+
field_name = rec[0] # '_file' suffix dropped
212+
blocks[block_name][field_name] = rec
213+
case datetime():
214+
blocks[block_name][field_name] = field_value.isoformat()
215+
case xr.DataArray():
216+
if field_name == "auxiliary":
217+
blocks[block_name][field_name] = tuple(field_value.values.tolist())
218+
elif "nper" not in field_value.dims:
219+
blocks[block_name][field_name] = _hack_spatial_dims(value, field_value)
228220
else:
229-
if np.issubdtype(field_value.dtype, np.str_):
221+
period_data = {}
222+
period_blocks = {}
223+
if _has_spatial_dims(field_value):
224+
field_value = _hack_spatial_dims(value, field_value)
230225
period_data[field_name] = {
231-
kper: field_value[kper]
226+
kper: field_value.isel(nper=kper)
232227
for kper in range(field_value.sizes["nper"])
233-
if field_value[kper] is not None
234228
}
235229
else:
236-
if block_name not in period_data:
237-
period_data[block_name] = {}
238-
period_data[block_name][field_name] = field_value # type: ignore
239-
240-
dataset = xr.Dataset(period_data[block_name])
241-
_attach_field_metadata(dataset, type(value), list(period_data[block_name].keys())) # type: ignore
242-
blocks[block_name] = {block_name: dataset}
243-
del period_data[block_name]
244-
245-
for arr_name, periods in period_data.items():
246-
for kper, arr in periods.items():
247-
if isinstance(arr, xr.DataArray):
248-
max = arr.max()
249-
if max == arr.min() and max == FILL_DNODATA:
250-
# don't write empty period blocks unless
251-
# to intentionally reset data
252-
pass
230+
if np.issubdtype(field_value.dtype, np.str_):
231+
period_data[field_name] = {
232+
kper: field_value[kper]
233+
for kper in range(field_value.sizes["nper"])
234+
if field_value[kper] is not None
235+
}
236+
else:
237+
if block_name not in period_data:
238+
period_data[block_name] = {}
239+
period_data[block_name][field_name] = field_value # type: ignore
240+
241+
dataset = xr.Dataset(period_data[block_name])
242+
_attach_field_metadata(
243+
dataset, type(value), list(period_data[block_name].keys())
244+
) # type: ignore
245+
blocks[block_name] = {block_name: dataset}
246+
del period_data[block_name]
247+
248+
for arr_name, periods in period_data.items():
249+
for kper, arr in periods.items():
250+
if isinstance(arr, xr.DataArray):
251+
max = arr.max()
252+
if max == arr.min() and max == FILL_DNODATA:
253+
# don't write empty period blocks unless
254+
# to intentionally reset data
255+
pass
256+
else:
257+
if kper not in period_blocks:
258+
period_blocks[kper] = {}
259+
period_blocks[kper][arr_name] = arr
253260
else:
254261
if kper not in period_blocks:
255262
period_blocks[kper] = {}
256-
period_blocks[kper][arr_name] = arr
257-
else:
258-
if kper not in period_blocks:
259-
period_blocks[kper] = {}
260-
period_blocks[kper][arr_name] = arr.upper()
261-
262-
for kper, block in period_blocks.items():
263-
dataset = xr.Dataset(block)
264-
_attach_field_metadata(dataset, type(value), list(block.keys()))
265-
blocks[f"{block_name} {kper + 1}"] = {block_name: dataset}
266-
elif field_value is not None:
267-
blocks[block_name][field_name] = field_value
263+
period_blocks[kper][arr_name] = arr.upper()
264+
265+
for kper, block in period_blocks.items():
266+
dataset = xr.Dataset(block)
267+
_attach_field_metadata(dataset, type(value), list(block.keys()))
268+
blocks[f"{block_name} {kper + 1}"] = {block_name: dataset}
269+
case _:
270+
blocks[block_name][field_name] = field_value
268271

269272
# make sure options block always comes first
270273
# TODO: blocks should already be sorted here

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