replace openmatrix with h5py

.github/workflows/run-tests.yml

@@ -233,7 +233,7 @@ jobs:
           uv pip install "black==22.12.0" "coveralls>=4" \
                          "cytoolz==0.12.2" "dask>=2026" "isort>=5.12.0" \
                          "multimethod<2.0" "nbmake>=1.4.6" "numba>=0.57" \
-                         "numpy>=2,<3" "openmatrix==0.3.5.0" \
+                         "numpy>=2,<3" \
                          "pandera>=0.30" "pandas>=2,<3" "platformdirs>=3.2" \
                          "psutil>=5.9" "pyarrow>=11.0" "pydantic>=2.6,<3" "pypyr>=5.8" \
                          "tables>=3.9" "pytest>=7.2" "pytest-cov" "pytest-regressions" \

docs/walkthrough/loading-skims.ipynb

@@ -30,8 +30,8 @@
     "from pathlib import Path\n",
     "from tempfile import TemporaryDirectory\n",
     "\n",
+    "import h5py\n",
     "import numpy as np\n",
-    "import openmatrix\n",
     "import pandas as pd\n",
     "import xarray as xr\n",
     "\n",
@@ -132,7 +132,7 @@
    "source": [
     "## OMX: time period in matrix names\n",
     "\n",
-    "The openmatrix (OMX) standard defines a data format that stores two-dimensional matrix data. To represent a third dimension, one approach is to store a matrix for each time period and include the time period after a double underscore in the matrix name, such as `autotime__AM`."
+    "The Open Matrix (OMX) standard defines an HDF5 layout that stores two-dimensional matrix data. To represent a third dimension, one approach is to store a matrix for each time period and include the time period after a double underscore in the matrix name, such as `autotime__AM`."
    ]
   },
   {
@@ -143,15 +143,14 @@
    "outputs": [],
    "source": [
     "omx_path = data_directory / \"skims.omx\"\n",
-    "with openmatrix.open_file(omx_path, mode=\"w\") as omx_file:\n",
+    "with h5py.File(omx_path, mode=\"w\") as omx_file:\n",
     "    for timeperiod in timeperiods:\n",
-    "        omx_file.create_carray(\n",
-    "            \"/data\",\n",
-    "            f\"autotime__{timeperiod}\",\n",
-    "            obj=source_skims.autotime.sel(timeperiod=timeperiod).values,\n",
+    "        omx_file.create_dataset(\n",
+    "            f\"data/autotime__{timeperiod}\",\n",
+    "            data=source_skims.autotime.sel(timeperiod=timeperiod).values,\n",
     "        )\n",
-    "    omx_file.create_carray(\"/lookup\", \"taz\", obj=zones)\n",
-    "    omx_file.root._v_attrs.SHAPE = np.array([len(zones), len(zones)])"
+    "    omx_file.create_dataset(\"lookup/taz\", data=zones)\n",
+    "    omx_file.attrs[\"SHAPE\"] = np.array([len(zones), len(zones)])"
    ]
   },
   {

envs/development.yml

@@ -19,7 +19,6 @@ dependencies:
   - numba>=0.57
   - numexpr
   - numpy>=1.19,<2
-  - openmatrix
   - pandas>=1.2
   - pyarrow
   - pytest

envs/testing.yml

@@ -21,7 +21,6 @@ dependencies:
   - pytest-regressions
   - pytest-xdist
   - nbmake
-  - openmatrix
   - h5py
   - python-blosc2
   - hdf5plugin

pyproject.toml

@@ -92,7 +92,6 @@ testpaths = [
 dev = [
     "ipykernel>=6.31.0",
     "nbmake>=1.5.5",
-    "openmatrix>=0.3.5.0",
     "pytest>=8.4.2",
     "pytest-regressions>=2.8.3",
     "scipy>=1.13.1",