From 4ef3d93a53dc16b86791321c21608db4c2c9a75c Mon Sep 17 00:00:00 2001 From: Marnix Date: Wed, 11 Dec 2024 13:44:49 +0100 Subject: [PATCH 1/7] Test some ways to unstructure xarray data --- test/test_cattrs.py | 58 +++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 58 insertions(+) create mode 100644 test/test_cattrs.py diff --git a/test/test_cattrs.py b/test/test_cattrs.py new file mode 100644 index 0000000..e95a769 --- /dev/null +++ b/test/test_cattrs.py @@ -0,0 +1,58 @@ +import numpy as np +import xarray as xr +from attrs import define, field +from cattrs import Converter, unstructure +from numpy.typing import NDArray + + +@define +class Foo: + x: NDArray[np.float32] = field() + + +@define +class Bar: + x: xr.DataArray = field() + + +@define +class Baz: + x: xr.DataTree = field() + + +def test_unstructure_numpy_array(): + np_arr = np.array([1.0, 2.0, 3.0]) + f = Foo(x=np_arr) + f_dict = unstructure(f) + + # We expect that the default unstructure functionality keeps the numpy array as is. + # This helps when finally converting the dictionary to MF6 input files. + assert np_arr is f_dict["x"] + + +def test_unstructure_xarray(): + x_arr = xr.DataArray([1, 2, 3]) + f = Bar(x=x_arr) + f_dict = unstructure(f) + + # We expect that the default unstructure functionality keeps the xarray as is. + # This helps when finally converting the dictionary to MF6 input files. + assert x_arr is f_dict["x"] + + +def test_unstructure_xarray_tree_to_ascii(): + x_arr = xr.DataArray([1, 2, 3]) + x_set = xr.Dataset({"x": x_arr}) + x_tree = xr.DataTree(x_set) + f = Baz(x=x_tree) + + converter = Converter() + converter.register_unstructure_hook( + Baz, lambda b: " ".join(b.x["x"].data.astype(str)) + ) + f_dict = converter.unstructure(f) + + # The data is formatted in ascii format. + # The whole string will be in memory when doing this, + # duplicating the data. + assert f_dict == "1 2 3" From 938d9022e4948aeb0e5ad93cbc33d88b1348d8b6 Mon Sep 17 00:00:00 2001 From: Marnix Date: Thu, 12 Dec 2024 18:01:42 +0100 Subject: [PATCH 2/7] Add dask and io to xarray optional dependencies --- pixi.lock | 1348 +++++++++++++++++++++++++++++++++++++++++++++++- pyproject.toml | 8 +- 2 files changed, 1350 insertions(+), 6 deletions(-) diff --git a/pixi.lock b/pixi.lock index 89afd55..3ec3ef6 100644 --- a/pixi.lock +++ b/pixi.lock @@ -29,30 +29,65 @@ environments: - 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conda: https://conda.anaconda.org/conda-forge/linux-64/xz-5.6.3-hbcc6ac9_1.conda sha256: 9cef529dcff25222427c9d90b9fc376888a59e138794b4336bbcd3331a5eea22 md5: 62aae173382a8aae284726353c6a6a24 @@ -8200,6 +9518,32 @@ packages: purls: [] size: 63898 timestamp: 1733407936888 +- pypi: https://files.pythonhosted.org/packages/ed/c9/142095e654c2b97133ff71df60979422717b29738b08bc8a1709a5d5e0d0/zarr-2.18.3-py3-none-any.whl + name: zarr + version: 2.18.3 + sha256: b1f7dfd2496f436745cdd4c7bcf8d3b4bc1dceef5fdd0d589c87130d842496dd + requires_dist: + - asciitree + - numpy>=1.24 + - numcodecs>=0.10.0 + - fasteners ; sys_platform != 'emscripten' + - sphinx ; extra == 'docs' + - sphinx-automodapi ; extra == 'docs' + - sphinx-design ; extra == 'docs' + - sphinx-issues ; extra == 'docs' + - sphinx-copybutton ; extra == 'docs' + - pydata-sphinx-theme ; extra == 'docs' + - numpydoc ; extra == 'docs' + - numcodecs[msgpack] ; extra == 'docs' + - notebook ; extra == 'jupyter' + - ipytree>=0.2.2 ; extra == 'jupyter' + - ipywidgets>=8.0.0 ; extra == 'jupyter' + requires_python: '>=3.10' +- pypi: https://files.pythonhosted.org/packages/80/ab/11a76c1e2126084fde2639514f24e6111b789b0bfa4fc6264a8975c7e1f1/zict-3.0.0-py2.py3-none-any.whl + name: zict + version: 3.0.0 + sha256: 5796e36bd0e0cc8cf0fbc1ace6a68912611c1dbd74750a3f3026b9b9d6a327ae + requires_python: '>=3.8' - pypi: https://files.pythonhosted.org/packages/b7/1a/7e4798e9339adc931158c9d69ecc34f5e6791489d469f5e50ec15e35f458/zipp-3.21.0-py3-none-any.whl name: zipp version: 3.21.0 diff --git a/pyproject.toml b/pyproject.toml index 17a7251..d196f86 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -34,16 +34,16 @@ classifiers = [ ] requires-python = ">=3.11" dependencies = [ - "attrs", # todo: bounds? - "cattrs", # todo: bounds? + "attrs", # todo: bounds? + "cattrs", # todo: bounds? "flopy>=3.7.0", "Jinja2>=3.0", - "lark", # todo: bounds? + "lark", # todo: bounds? "numpy>=1.20.3", "pandas>=2.0.0", "toml>=0.10", "networkx>=3.4.2,<4", - "xarray>=2024.11.0,<2025", + "xarray[parallel,io]>=2024.11.0,<2025", "scipy>=1.14.1,<2", ] dynamic = ["version"] From e0fde777e8e0f912594e5661ae48b40903edb651 Mon Sep 17 00:00:00 2001 From: Marnix Date: Thu, 12 Dec 2024 18:02:01 +0100 Subject: [PATCH 3/7] Test how to read/write dask arrays --- test/test_dask_xarray.py | 55 ++++++++++++++++++++++++++++++++++++++++ 1 file changed, 55 insertions(+) create mode 100644 test/test_dask_xarray.py diff --git a/test/test_dask_xarray.py b/test/test_dask_xarray.py new file mode 100644 index 0000000..1112709 --- /dev/null +++ b/test/test_dask_xarray.py @@ -0,0 +1,55 @@ +import numpy as np +import xarray as xr + +# These tests show how we could use a chunked and lazy dask array +# to read a netcdf file. +# In this case we want to write the data to a single file, +# so we need to ensure that the data is sequential and in the right order. +# We can't use xr.map_blocks, because it is a parallel operation. +# Instead we need to loop over the blocks and compute them one by one. (test 2) + + +def test_netcdf_with_map_blocks(): + data = xr.DataArray(range(1, 1_000), dims=("x",)) + nc_path = "test/data/test.nc" + data.to_netcdf(nc_path) + data.close() + data = xr.open_dataarray(nc_path, chunks={"x": 100}) + + output_file = [] + + # Option 1: this works, but all blocks are still loaded into memory. + # That's because we need to return the block. + # And that data is then collected and returned by compute(). + # Even if we don't use it. + # And because it's going in parallel, we don't have control of the order. + def append_to_output_file(block): + output_file.append(block.data) + return block + + result = data.map_blocks( + append_to_output_file, + template=data, + ) + + result.compute() + assert len(output_file) == 10 + + +def test_netcdf_with_dask_map_blocks(): + data = xr.DataArray(range(1, 1_000), dims=("x",)) + nc_path = "test/data/test.nc" + data.to_netcdf(nc_path) + data.close() + data = xr.open_dataarray(nc_path, chunks={"x": 100}) + + output_file = [] + + # Option 2 is easier. + # We simply loop over the raw dask blocks and compute them one by one. + for block in data.data.blocks: + block_data = block.compute() + output_file.append(block_data) + + assert len(output_file) == 10 + assert np.all(np.equal(output_file[0], range(1, 101))) From fb44fe6801f6ffb1819c1c457d383a655c98d89a Mon Sep 17 00:00:00 2001 From: Marnix Date: Thu, 12 Dec 2024 18:05:50 +0100 Subject: [PATCH 4/7] Fix linting --- test/test_cattrs.py | 6 ++++-- 1 file changed, 4 insertions(+), 2 deletions(-) diff --git a/test/test_cattrs.py b/test/test_cattrs.py index e95a769..5d96f90 100644 --- a/test/test_cattrs.py +++ b/test/test_cattrs.py @@ -25,7 +25,8 @@ def test_unstructure_numpy_array(): f = Foo(x=np_arr) f_dict = unstructure(f) - # We expect that the default unstructure functionality keeps the numpy array as is. + # We expect that the default unstructure functionality keeps + # the numpy array as is. # This helps when finally converting the dictionary to MF6 input files. assert np_arr is f_dict["x"] @@ -35,7 +36,8 @@ def test_unstructure_xarray(): f = Bar(x=x_arr) f_dict = unstructure(f) - # We expect that the default unstructure functionality keeps the xarray as is. + # We expect that the default unstructure functionality keeps + # the xarray as is. # This helps when finally converting the dictionary to MF6 input files. assert x_arr is f_dict["x"] From fa21d422be6698321cc68c4c930ac58068562cad Mon Sep 17 00:00:00 2001 From: Marnix Date: Fri, 13 Dec 2024 08:11:21 +0100 Subject: [PATCH 5/7] Add test that shows that we need an unstructure_hook for DataTree This is the simplest way to keep DataTree object the original. Otherwise it would return a copy of some sort. --- test/test_cattrs.py | 16 ++++++++++++++++ 1 file changed, 16 insertions(+) diff --git a/test/test_cattrs.py b/test/test_cattrs.py index 5d96f90..68f6747 100644 --- a/test/test_cattrs.py +++ b/test/test_cattrs.py @@ -58,3 +58,19 @@ def test_unstructure_xarray_tree_to_ascii(): # The whole string will be in memory when doing this, # duplicating the data. assert f_dict == "1 2 3" + + +def test_unstructure_xarray_tree(): + x_arr = xr.DataArray([1, 2, 3]) + x_set = xr.Dataset({"x": x_arr}) + x_tree = xr.DataTree(x_set) + f = Baz(x=x_tree) + + converter = Converter() + converter.register_unstructure_hook(xr.DataTree, lambda v: v) + f_dict = converter.unstructure(f) + + # We expect that the default unstructure functionality keeps + # the xarray as is. + # This helps when finally converting the dictionary to MF6 input files. + assert x_tree is f_dict["x"] From f14ed4519c056dd1230fdbcc417f154c102fc769 Mon Sep 17 00:00:00 2001 From: Marnix Date: Fri, 13 Dec 2024 08:18:52 +0100 Subject: [PATCH 6/7] Use temp paths in the test --- test/test_dask_xarray.py | 8 ++++---- 1 file changed, 4 insertions(+), 4 deletions(-) diff --git a/test/test_dask_xarray.py b/test/test_dask_xarray.py index 1112709..f03c06e 100644 --- a/test/test_dask_xarray.py +++ b/test/test_dask_xarray.py @@ -9,9 +9,9 @@ # Instead we need to loop over the blocks and compute them one by one. (test 2) -def test_netcdf_with_map_blocks(): +def test_netcdf_with_map_blocks(tmp_path): data = xr.DataArray(range(1, 1_000), dims=("x",)) - nc_path = "test/data/test.nc" + nc_path = tmp_path / "test_netcdf_with_map_blocks.nc" data.to_netcdf(nc_path) data.close() data = xr.open_dataarray(nc_path, chunks={"x": 100}) @@ -36,9 +36,9 @@ def append_to_output_file(block): assert len(output_file) == 10 -def test_netcdf_with_dask_map_blocks(): +def test_netcdf_with_dask_map_blocks(tmp_path): data = xr.DataArray(range(1, 1_000), dims=("x",)) - nc_path = "test/data/test.nc" + nc_path = tmp_path / "test_netcdf_with_dask_map_blocks.nc" data.to_netcdf(nc_path) data.close() data = xr.open_dataarray(nc_path, chunks={"x": 100}) From 2be53fad8853322bf59901dafa121273e56e0566 Mon Sep 17 00:00:00 2001 From: Marnix Date: Mon, 16 Dec 2024 08:44:11 +0100 Subject: [PATCH 7/7] Test that shows default unstructure behavior --- test/test_cattrs.py | 13 +++++++++++++ 1 file changed, 13 insertions(+) diff --git a/test/test_cattrs.py b/test/test_cattrs.py index 68f6747..74fd620 100644 --- a/test/test_cattrs.py +++ b/test/test_cattrs.py @@ -74,3 +74,16 @@ def test_unstructure_xarray_tree(): # the xarray as is. # This helps when finally converting the dictionary to MF6 input files. assert x_tree is f_dict["x"] + + +def test_unstructure_xarray_tree_no_hook(): + x_arr = xr.DataArray([1, 2, 3]) + x_set = xr.Dataset({"x": x_arr}) + x_tree = xr.DataTree(x_set) + f = Baz(x=x_tree) + + f_dict = unstructure(f) + + # Unfortunately the default converter seems to make a copy of the DataTree + # and doesn't keep the original reference. + assert x_tree is not f_dict["x"]