From 4839dc7b58b6206f9be62a19824faf806c8b8e5b Mon Sep 17 00:00:00 2001
From: "Matthew W. Thompson" <mattwthompson@protonmail.com>
Date: Tue, 27 Oct 2026 12:09:52 -0500
Subject: [PATCH 01/18] Use thermo and energy errors in loss function

---
 examples/mvp/run.py | 23 ++++++++++++-----------
 1 file changed, 12 insertions(+), 11 deletions(-)

diff --git a/examples/mvp/run.py b/examples/mvp/run.py
index a402b58..b50ecec 100644
--- a/examples/mvp/run.py
+++ b/examples/mvp/run.py
@@ -19,7 +19,7 @@
 N_MOLECULES = 200
 INITIAL_FORCE_FIELD = "openff-2.3.0.offxml"
 
-MERGE_DATA = False
+MERGE_DATA = True
 
 
 def load_datasets(root: Path) -> tuple[Dataset, Dataset]:
@@ -85,19 +85,20 @@ def main(root: Path) -> None:
         # at end of loop for [1, ..., N_EPOCHS]?
         current_ff = trainable.to_force_field(theta)  # 287
 
-        # import json
-        # from tyff._serialization import load_tensor_force_field
+        import json
+
+        from tyff._serialization import load_tensor_force_field
 
         # sum(t.numel() for t in _pack_force_field(ref)[0] if t is not None)
         # is probably 208
 
-        # current_ff = load_tensor_force_field(
-        #     json.loads(
-        #         open(
-        #             'examples/mvp/EPOCH_0/simulations/reference_force_fields/reference.json'
-        #         ).read()
-        #     )
-        # )
+        thermo_ff = load_tensor_force_field(
+            json.loads(
+                open(
+                    f"examples/mvp/EPOCH_{epoch}/simulations/reference_force_fields/reference.json",
+                ).read()
+            )
+        )
 
         # no return value?
         simulate(
@@ -111,7 +112,7 @@ def main(root: Path) -> None:
 
         y_ref, _y_ref_std, y_pred, _y_pred_std = predict(
             dataset=thermo_data,
-            force_field=current_ff,
+            force_field=thermo_ff,
             epoch_dir=root / f"EPOCH_{epoch}",
         )
 

From 8f6befc7f92bdf720067abdb09cdfaa5e90a9132 Mon Sep 17 00:00:00 2001
From: "Matthew W. Thompson" <mattwthompson@protonmail.com>
Date: Tue, 27 Oct 2026 13:51:20 -0500
Subject: [PATCH 02/18] Start making weights for types of targets

---
 examples/mvp/run.py | 17 +++++++++++------
 1 file changed, 11 insertions(+), 6 deletions(-)

diff --git a/examples/mvp/run.py b/examples/mvp/run.py
index b50ecec..339e4a9 100644
--- a/examples/mvp/run.py
+++ b/examples/mvp/run.py
@@ -21,6 +21,14 @@
 
 MERGE_DATA = True
 
+# these weights should be exposed to the user in some sort of training config
+# probably a good phase II task
+COEFFICIENTS = {
+    "energy": 0.1,
+    "force": 0.01,
+    "thermo": 100_000.0,
+}
+
 
 def load_datasets(root: Path) -> tuple[Dataset, Dataset]:
     """Load datasets stored at data/*.tar.gz"""
@@ -124,13 +132,10 @@ def main(root: Path) -> None:
                 normalize=False,
             )
 
-            # the weights in front of each category of loss (energy, forces, and thermo)
-            # should be exposed to the user in some sort of training config
-            # probably a good phase II task
             loss = (
-                (energy_pred - energy_ref).square().mean()
-                + 0.1 * (forces_pred - forces_ref).square().mean()
-                + (y_pred - y_ref).square().mean()
+                COEFFICIENTS["energy"] * (energy_pred - energy_ref).square().mean()
+                + COEFFICIENTS["force"] * (forces_pred - forces_ref).square().mean()
+                + COEFFICIENTS["thermo"] * (y_pred - y_ref).square().mean()
             )
         else:
             loss = (y_pred - y_ref).square().mean()

From 8de767f196793d9fbcf45fb5b9a0a41291713037 Mon Sep 17 00:00:00 2001
From: "Matthew W. Thompson" <mattwthompson@protonmail.com>
Date: Wed, 4 Nov 2026 16:25:10 -0600
Subject: [PATCH 03/18] Refactor handling of "reference" force field

Co-authored-by: Lily Wang <31115101+lilyminium@users.noreply.github.com>
---
 examples/mvp/run.py        | 24 +++++----------
 tyff/compute/workflow.py   | 62 ++++++++++++++++----------------------
 tyff/targets/new_thermo.py | 13 ++++----
 3 files changed, 41 insertions(+), 58 deletions(-)

diff --git a/examples/mvp/run.py b/examples/mvp/run.py
index 339e4a9..04a18df 100644
--- a/examples/mvp/run.py
+++ b/examples/mvp/run.py
@@ -83,7 +83,10 @@ def main(root: Path) -> None:
         },
         attributes={},
     )
+    # these is the torch representation - the thing that is being optimized
     theta = trainable.to_values().requires_grad_(True)
+
+    # here's where the L-M optimizer could be put in - some scientific quesitons about which is better
     optimizer = Adam([theta], lr=0.01)
 
     # TODO: inner/outer loop, or any way of stepping through QM optimization
@@ -91,36 +94,25 @@ def main(root: Path) -> None:
     for epoch in range(N_EPOCHS):
         # maybe do this outside of loop for iteration 0, then
         # at end of loop for [1, ..., N_EPOCHS]?
-        current_ff = trainable.to_force_field(theta)  # 287
 
-        import json
-
-        from tyff._serialization import load_tensor_force_field
+        # current_ff is linked under the hood to theta - need to keep them linked to keep gradients together
+        current_ff = trainable.to_force_field(theta)  # 287
 
         # sum(t.numel() for t in _pack_force_field(ref)[0] if t is not None)
-        # is probably 208
-
-        thermo_ff = load_tensor_force_field(
-            json.loads(
-                open(
-                    f"examples/mvp/EPOCH_{epoch}/simulations/reference_force_fields/reference.json",
-                ).read()
-            )
-        )
 
         # no return value?
         simulate(
             force_field=current_ff,
             epoch_dir=root / f"EPOCH_{epoch}",
             thermo_data=thermo_data,
-            smirnoff_force_field=ForceField(INITIAL_FORCE_FIELD),
+            smirnoff_force_field=INITIAL_FORCE_FIELD,
             n_replicates=N_REPLICATES,
             n_molecules=N_MOLECULES,
         )
 
         y_ref, _y_ref_std, y_pred, _y_pred_std = predict(
             dataset=thermo_data,
-            force_field=thermo_ff,
+            force_field=current_ff,
             epoch_dir=root / f"EPOCH_{epoch}",
         )
 
@@ -162,7 +154,7 @@ def main(root: Path) -> None:
                 indent=4,
             )
 
-        # write out FF as SMIRNOFF force field
+        # update SMIRNOFF force field with new values from tensor FF
         convert_tensor_force_field(
             original_force_field=ForceField(INITIAL_FORCE_FIELD),
             tensor_force_field=updated_tensor_force_field,
diff --git a/tyff/compute/workflow.py b/tyff/compute/workflow.py
index a8990be..40175dd 100644
--- a/tyff/compute/workflow.py
+++ b/tyff/compute/workflow.py
@@ -162,11 +162,32 @@ def submit_target(
     def submit_dataset(
         self,
         dataset: datasets.Dataset,  # should be something that unpacks to DataEntry on iteration
+        tensor_force_field: tyff.TensorForceField,
         force_field: str,
         n_molecules: int,
         n_replicates: int = 3,
     ):
-        import openff.toolkit
+        """
+        Submit a dataset of targets for computation.
+
+        Parameters
+        ----------
+        dataset : datasets.Dataset
+            The dataset containing targets to be submitted.
+        tensor_force_field : tyff.TensorForceField
+            The tensor representation of the force field to be used.
+        force_field : str
+            The path to the reference force field.
+        n_molecules : int
+            The number of molecules to consider for each target.
+        n_replicates : int, optional
+            The number of replicates for each target, by default 3.
+
+        Returns
+        -------
+        list
+            A list of results from submitting each target.
+        """
 
         from tyff._serialization import dump_tensor_force_field
 
@@ -192,45 +213,16 @@ def submit_dataset(
             for smiles_ in target["smiles"]:
                 unique_smiles.add(smiles_)
 
-        # TODO: Probably drop this
-        (pathlib.Path(self.base_dir) / "interchanges").mkdir(exist_ok=True)
-
-        interchanges = list()
-
-        force_field_ = openff.toolkit.ForceField(force_field)
-        for index, unique_smiles_ in enumerate(sorted(unique_smiles)):
-            interchange = force_field_.create_interchange(
-                openff.toolkit.Molecule.from_mapped_smiles(unique_smiles_).to_topology()
-            )
-            interchanges.append(interchange)
-
-            with open(pathlib.Path(self.base_dir) / "interchanges" / f"interchange_{index}.json", "w") as f:
-                f.write(interchange.model_dump_json(indent=4))
-
-        self._reference_force_fields = pathlib.Path(self.base_dir) / "reference_force_fields"
-        self._reference_force_fields.mkdir(exist_ok=True)
-
-        assert self._reference_force_fields.exists()
-        assert self._reference_force_fields.is_dir()
-
-        logger.info(f"Made a path to store reference force fields at {self._reference_force_fields}")
-        # this is a "global"/reference force field composed from all unique molecules,
-        # don't think we're going to use the topologies here
-        reference_force_field, _tensor_topologies = tyff.converters.convert_interchange(interchanges)
-
-        # make sure this is not empty
-        assert len(reference_force_field.potentials) > 0
-
         logger.info(
             "Writing reference force field from path (which is probably outside of "
             f"this workflow's root): {force_field=}"
-            f"to path {self._reference_force_fields / 'reference.json'}"
+            f"to path {pathlib.Path(self.base_dir) / 'reference_force_field.json'}"
         )
 
         # dumps a JSON representation of the tensor representation of the SMIRNOFF force field
-        with open(self._reference_force_fields / "reference.json", "w") as f:
+        with open(pathlib.Path(self.base_dir) / "reference_force_field.json", "w") as f:
             json.dump(
-                dump_tensor_force_field(reference_force_field),
+                dump_tensor_force_field(tensor_force_field),
                 f,
                 indent=4,
             )
@@ -413,9 +405,7 @@ def _common_run(self, compute_config: BaseComputeConfig) -> tuple[dict[str, torc
         jacobian_future = create_jacobian(
             production_future=production_future,
             job_dir=job_dir,
-            # pathing here is weird, but there should only be one global reference
-            # force field for this workflow
-            reference_force_field_path=self._reference_force_fields / "reference.json",
+            reference_force_field_path=pathlib.Path(self.base_dir) / "reference_force_field.json",
         )
 
         return {"job_id": job_id, "future": jacobian_future}
diff --git a/tyff/targets/new_thermo.py b/tyff/targets/new_thermo.py
index 853c7bb..f2b3056 100644
--- a/tyff/targets/new_thermo.py
+++ b/tyff/targets/new_thermo.py
@@ -19,7 +19,7 @@ def simulate(
     force_field: tyff.TensorForceField,
     epoch_dir: Path,
     thermo_data: Dataset,
-    smirnoff_force_field: ForceField,
+    smirnoff_force_field: str,
     n_molecules: int,
     n_replicates: int,
 ) -> None:
@@ -36,8 +36,8 @@ def simulate(
         The directory for this epoch where simulation results will be stored.
     thermo_data : Dataset
         The dataset containing thermodynamic data for the simulation.
-    smirnoff_force_field : ForceField
-        The original SMIRNOFF force field corresponding to the tensor force field.
+    smirnoff_force_field : str
+        The path to the original SMIRNOFF force field corresponding to the tensor force field.
     n_molecules : int
         The number of molecules to simulate.
     n_replicates : int
@@ -50,14 +50,14 @@ def simulate(
 
     # write out this epoch's (tensor) force field as a SMIRNOFF force field
     current_smirnoff_force_field = convert_tensor_force_field(
-        original_force_field=smirnoff_force_field,
+        original_force_field=ForceField(smirnoff_force_field),
         tensor_force_field=force_field,
     )
 
     epoch_dir.mkdir(exist_ok=True)
 
     smirnoff_force_field_file = str(epoch_dir / "current_force_field.offxml")
-    current_smirnoff_force_field.to_file(smirnoff_force_field_file)
+    current_smirnoff_force_field.to_file(filename=smirnoff_force_field_file)
 
     with SimulationWorkflow(
         base_dir=str(epoch_dir / "simulations"),
@@ -65,7 +65,8 @@ def simulate(
     ) as workflow:
         workflow.submit_dataset(
             dataset=thermo_data,
-            force_field=smirnoff_force_field_file,
+            tensor_force_field=force_field,
+            force_field=smirnoff_force_field_file,  # possibly smoother to pass through openff.toolkit.ForceField
             n_molecules=n_molecules,
             n_replicates=n_replicates,
         )

From 47fe3ae884d3b17d53919e34465ee9382b9732c0 Mon Sep 17 00:00:00 2001
From: "Matthew W. Thompson" <mattwthompson@protonmail.com>
Date: Fri, 6 Nov 2026 10:25:00 -0600
Subject: [PATCH 04/18] Some fixes for pressure handling

---
 tyff/compute/_equilibrate.py | 2 +-
 tyff/compute/_jacobian.py    | 4 ++--
 tyff/compute/_produce.py     | 2 +-
 3 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/tyff/compute/_equilibrate.py b/tyff/compute/_equilibrate.py
index fed9387..58f42c8 100644
--- a/tyff/compute/_equilibrate.py
+++ b/tyff/compute/_equilibrate.py
@@ -142,7 +142,7 @@ def _run_equilibration(
             output_file=files["msgpack_trajectory"].filepath,
             report_interval=1000,
             beta=1.0 / (openmm.unit.MOLAR_GAS_CONSTANT_R * compute_config["temperature"] * openmm.unit.kelvin),
-            pressure=pressure if pressure is None else openmm.unit.kilopascal,
+            pressure=pressure if pressure is None else pressure * openmm.unit.kilopascal,
         )
     )
 
diff --git a/tyff/compute/_jacobian.py b/tyff/compute/_jacobian.py
index 2745a06..4c74c53 100644
--- a/tyff/compute/_jacobian.py
+++ b/tyff/compute/_jacobian.py
@@ -78,7 +78,7 @@ def _get_ensemble_average_and_jacobian(
         compute_config = BulkLiquid(**json.load(f))  # type: ignore[typeddict-item]
 
     temperature = compute_config["temperature"]  # kelvin, float
-    pressure = compute_config.get("pressure")  # atmosphere, float | None
+    pressure = compute_config.get("pressure")  # kPa, float | None
 
     interchanges = []
 
@@ -141,7 +141,7 @@ def _get_ensemble_average_and_jacobian(
         worker_force_field,
         frames_path,
         temperature * openmm.unit.kelvin,
-        None if pressure is None else pressure * openmm.unit.atmosphere,
+        None if pressure is None else pressure * openmm.unit.kilopascal,
     )
 
     # originally this was sorted(means),
diff --git a/tyff/compute/_produce.py b/tyff/compute/_produce.py
index e5903df..a69986e 100644
--- a/tyff/compute/_produce.py
+++ b/tyff/compute/_produce.py
@@ -138,7 +138,7 @@ def _run_production(
             output_file=files["msgpack_trajectory"].filepath,
             report_interval=1000,
             beta=1.0 / (openmm.unit.MOLAR_GAS_CONSTANT_R * compute_config["temperature"] * openmm.unit.kelvin),
-            pressure=pressure if pressure is None else openmm.unit.kilopascal,
+            pressure=pressure if pressure is None else pressure * openmm.unit.kilopascal,
         )
     )
 

From bf0c3cb993eca4546d8f9f23b8e136a1b08b906d Mon Sep 17 00:00:00 2001
From: "Matthew W. Thompson" <mattwthompson@protonmail.com>
Date: Fri, 6 Nov 2026 15:58:01 -0600
Subject: [PATCH 05/18] Add integration test with water at different
 temperatures

---
 tyff/_tests/compute/__init__.py               |  0
 tyff/_tests/conftest.py                       | 22 +++++++
 tyff/_tests/integration_tests/__init__.py     |  0
 .../compute/test_workflow.py                  | 58 +++++++++++++++++++
 4 files changed, 80 insertions(+)
 create mode 100644 tyff/_tests/compute/__init__.py
 create mode 100644 tyff/_tests/integration_tests/__init__.py
 create mode 100644 tyff/_tests/integration_tests/compute/test_workflow.py

diff --git a/tyff/_tests/compute/__init__.py b/tyff/_tests/compute/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/tyff/_tests/conftest.py b/tyff/_tests/conftest.py
index d959323..a60930c 100644
--- a/tyff/_tests/conftest.py
+++ b/tyff/_tests/conftest.py
@@ -24,6 +24,28 @@
 _E = openff.units.unit.elementary_charge
 
 
+def pytest_addoption(parser):
+    parser.addoption(
+        "--run-gpu",
+        action="store_true",
+        default=False,
+        help="run tests marked with @pytest.mark.gpu",
+    )
+
+
+def pytest_configure(config):
+    config.addinivalue_line("markers", "gpu: tests that require a GPU (skipped unless --run-gpu is given)")
+
+
+def pytest_collection_modifyitems(config, items):
+    if config.getoption("--run-gpu"):
+        return
+    skip_gpu = pytest.mark.skip(reason="need --run-gpu option to run")
+    for item in items:
+        if "gpu" in item.keywords:
+            item.add_marker(skip_gpu)
+
+
 @pytest.fixture
 def density_entry() -> DataEntry:
     return {
diff --git a/tyff/_tests/integration_tests/__init__.py b/tyff/_tests/integration_tests/__init__.py
new file mode 100644
index 0000000..e69de29
diff --git a/tyff/_tests/integration_tests/compute/test_workflow.py b/tyff/_tests/integration_tests/compute/test_workflow.py
new file mode 100644
index 0000000..ace58f2
--- /dev/null
+++ b/tyff/_tests/integration_tests/compute/test_workflow.py
@@ -0,0 +1,58 @@
+import json
+
+import pytest
+
+from tyff.compute.configs import local_config
+from tyff.compute.workflow import SimulationWorkflow
+from tyff.targets.thermo import create_dataset
+
+
+@pytest.mark.gpu
+def test_nonstandard_pressure(tmp_path):
+
+    dataset = create_dataset(
+        *[
+            {  # type: ignore
+                "id": "high_pressure_water",
+                "tag": "density",
+                "x": [1.0],
+                "smiles": ["O"],
+                "temperature": 298.15,
+                "pressure": val,
+                "value": 1.0,
+                "std": 0.01,
+                "units": "g/mL",
+                "source": "test_source",
+            }
+            for val in [101.325, 101325]
+        ]
+    )
+
+    with SimulationWorkflow(
+        base_dir=tmp_path,
+        parsl_config=local_config(),
+    ) as workflow:
+        workflow.submit_dataset(
+            dataset,
+            force_field="openff-2.3.0.offxml",
+            n_molecules=480,
+            n_replicates=1,
+        )
+
+        workflow.wait()
+
+        # hack - there needs to be a better way of grabbing results
+        job_dirs = [path for path in (tmp_path / "simulations").glob("*/") if not path.match("thermo_targets")]
+
+        results = dict()
+
+        for job_dir in job_dirs:
+            with open(job_dir / "compute_config.json") as f:
+                target_pressure = json.load(f)["pressure"]
+
+            with open(job_dir / "ensemble_averages.json") as f:
+                density = json.load(f)["density"]
+
+            results[target_pressure] = density
+
+        assert results[101325.0] > results[101.325]

From 027c51ea23c82ef8d2c2f6e60256d1665f31c578 Mon Sep 17 00:00:00 2001
From: "Matthew W. Thompson" <mattwthompson@protonmail.com>
Date: Fri, 6 Nov 2026 20:25:15 -0600
Subject: [PATCH 06/18] Add GPU-based test

---
 .github/workflows/gpu.yaml                    |   92 +
 pixi.lock                                     | 3572 +++++++++--------
 pixi.toml                                     |    1 +
 .../compute/test_workflow.py                  |    6 +-
 4 files changed, 1885 insertions(+), 1786 deletions(-)
 create mode 100644 .github/workflows/gpu.yaml

diff --git a/.github/workflows/gpu.yaml b/.github/workflows/gpu.yaml
new file mode 100644
index 0000000..72dd9ce
--- /dev/null
+++ b/.github/workflows/gpu.yaml
@@ -0,0 +1,92 @@
+name: GPU-enabled CI
+on:
+  workflow_dispatch:
+  pull_request:
+    branches:
+      - "main"
+
+concurrency:
+  # Specific group naming so CI is only cancelled
+  # within same PR or on merge to main
+  group: ${{ github.ref }}-${{ github.head_ref }}-${{ github.workflow }}
+  cancel-in-progress: true
+
+defaults:
+  run:
+    shell: bash -l {0}
+
+env:
+  OE_LICENSE: ${{ github.workspace }}/oe_license.txt
+
+jobs:
+  start-aws-runner:
+    runs-on: ubuntu-latest
+    permissions:
+      id-token: write
+      contents: read
+    outputs:
+      mapping: ${{ steps.aws-start.outputs.mapping }}
+    steps:
+      - name: Configure AWS credentials
+        uses: aws-actions/configure-aws-credentials@v6
+        with:
+          role-to-assume: arn:aws:iam::649715411074:role/gh-actions-runner-role
+          aws-region: us-east-1
+      - name: Create cloud runner
+        id: aws-start
+        uses: omsf/start-aws-gha-runner@v1.3.0
+        with:
+          aws_image_id: ami-0d5079d9be06933e5
+          aws_instance_type: g4dn.xlarge
+          # IAM default might be 5 GB?
+          aws_root_device_size: 125
+          aws_region_name: us-east-1
+          aws_home_dir: /home/ubuntu
+        env:
+          GH_PAT: ${{ secrets.GH_PAT }}
+  self-hosted-test:
+    name: GPU-based tests (env ${{ matrix.environment }})
+    runs-on: self-hosted
+    strategy:
+        fail-fast: true
+        matrix:
+          environment:
+            - hpc3  # re-using an otherwise generic CUDA environment
+    needs:
+      - start-aws-runner
+    steps:
+      - uses: actions/checkout@v7
+        with:
+          fetch-depth: 0
+
+      - name: Set up virtual environment
+        uses: prefix-dev/setup-pixi@v0.11.3
+        with:
+          environments: ${{ matrix.environment }}
+          frozen: true
+
+      - name: Run GPU-based tests
+        run: pixi run -e ${{ matrix.environment }} run_gpu_tests
+
+  stop-aws-runner:
+    runs-on: ubuntu-latest
+    permissions:
+        id-token: write
+        contents: read
+    needs:
+      - start-aws-runner
+      - self-hosted-test
+    if: ${{ always() }}
+    steps:
+      - name: Configure AWS credentials
+        uses: aws-actions/configure-aws-credentials@v6
+        with:
+          role-to-assume: arn:aws:iam::649715411074:role/gh-actions-runner-role
+          aws-region: us-east-1
+      - name: Stop instances
+        uses: omsf/stop-aws-gha-runner@v1.0.0
+        with:
+          instance_mapping: ${{ needs.start-aws-runner.outputs.mapping }}
+          aws_region_name: us-east-1
+        env:
+          GH_PAT: ${{ secrets.GH_PAT }}
diff --git a/pixi.lock b/pixi.lock
index 795d403..20e60cf 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -40,7 +40,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/azure-storage-common-cpp-12.13.0-ha7a2c86_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/azure-storage-files-datalake-cpp-12.14.0-h539c000_2.conda
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-  timestamp: 1792672483978
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-  md5: dd719c40c297d87fe93085248d2ff07b
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+  timestamp: 1793164688563
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+  md5: 08e015d6c335f0ba76d84a3195b57005
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   run_exports: {}
-  size: 3161654
-  timestamp: 1792672552740
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/fribidi-1.0.17-h7cc23a3_0.conda
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-  md5: f9d5302bca196ee87e62f393f2626562
+- conda: https://conda.anaconda.org/conda-forge/linux-64/fribidi-1.0.18-h7cc23a3_0.conda
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   - libgcc >=15
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-  timestamp: 1790011855888
+    - fribidi >=1.0.18,<2.0a0
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   timestamp: 1775243967708
-- conda: https://conda.anaconda.org/conda-forge/linux-64/hf-xet-1.7.0-py311h30674b1_0.conda
+- conda: https://conda.anaconda.org/conda-forge/linux-64/hf-xet-1.8.0-py311h30674b1_0.conda
   noarch: python
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+  md5: ca83380cfdb6f9f343e6925fc8ace96f
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-  - libgcc >=15
   - __glibc >=2.17,<3.0.a0
+  - libgcc >=15
   - _python_abi3_support 1.*
   - cpython >=3.11
   - openssl >=3.5.9,<4.0a0
@@ -6360,10 +6360,10 @@ packages:
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   license_family: APACHE
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-  - pkg:pypi/hf-xet?source=hash-mapping
+  - pkg:pypi/hf-xet?source=compressed-mapping
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/lcms2-2.19.1-h9073bf1_3.conda
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-  md5: 596464faa06e0b656b35416188ef9bba
+- conda: https://conda.anaconda.org/conda-forge/linux-64/lcms2-2.20-h9073bf1_0.conda
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   - libgcc >=15
-  - libjpeg-turbo >=3.2.0,<4.0a0
+  - libjpeg-turbo >=3.2.1,<4.0a0
   - libtiff >=4.7.2,<4.8.0a0
   license: MIT
   license_family: MIT
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-  size: 254292
-  timestamp: 1789051947923
+    - lcms2 >=2.20,<3.0a0
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 - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.46.1-default_hbd61a6d_103.conda
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/lerc-4.2.0-hdb68285_0.conda
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-  md5: fb9d356b1a57d6d54768be7ebd5fce09
+- conda: https://conda.anaconda.org/conda-forge/linux-64/lerc-4.3.0-he78707d_0.conda
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-  - libgcc >=14
-  - libstdcxx >=14
+  - libgcc >=15
+  - libstdcxx >=15
   license: Apache-2.0
   license_family: Apache
   purls: []
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-  size: 271158
-  timestamp: 1785036167977
+    - lerc >=4.3.0,<5.0a0
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 - conda: https://conda.anaconda.org/conda-forge/linux-64/libabseil-20250512.1-cxx17_hba17884_0.conda
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@@ -6643,21 +6643,21 @@ packages:
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/libaec-1.1.5-h088129d_0.conda
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-  md5: 86f7414544ae606282352fa1e116b41f
+- conda: https://conda.anaconda.org/conda-forge/linux-64/libaec-1.1.7-h659bb9a_0.conda
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   depends:
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-  - libgcc >=14
-  - libstdcxx >=14
+  - libgcc >=15
+  - libstdcxx >=15
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   license_family: BSD
   purls: []
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-  size: 36544
-  timestamp: 1769221884824
+    - libaec >=1.1.7,<2.0a0
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 - conda: https://conda.anaconda.org/conda-forge/linux-64/libarrow-20.0.0-hc7fa404_9_cpu.conda
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@@ -6862,18 +6862,18 @@ packages:
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/libblas-3.11.0-11_h4a7cf45_openblas.conda
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-  md5: b8cce1486f3c62f33291d6318c193d0d
+- conda: https://conda.anaconda.org/conda-forge/linux-64/libblas-3.11.0-12_h4a7cf45_openblas.conda
+  build_number: 12
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+  md5: d718330824f78deef9ca46fe62a33820
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   - libopenblas >=0.3.34,<1.0a0
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-  - libcblas   3.11.0   11*_openblas
-  - liblapack  3.11.0   11*_openblas
-  - liblapacke 3.11.0   11*_openblas
+  - blas 2.312   openblas
+  - libcblas   3.11.0   12*_openblas
+  - liblapack  3.11.0   12*_openblas
+  - liblapacke 3.11.0   12*_openblas
   - mkl <2027
   license: BSD-3-Clause
   license_family: BSD
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/libblas-3.11.0-11_h5875eb1_mkl.conda
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-  sha256: 3b9862430914d13ae264398340117f80b85720de308f6a80ad463588abe10358
-  md5: 8db4ae3941966215baa885eb004aded5
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+- conda: https://conda.anaconda.org/conda-forge/linux-64/libblas-3.11.0-12_h5875eb1_mkl.conda
+  build_number: 12
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+  md5: 6fc35ebced0ef56a112add45ed67afb4
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   constrains:
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-  - libcblas   3.11.0   11*_mkl
-  - liblapack  3.11.0   11*_mkl
-  - liblapacke 3.11.0   11*_mkl
+  - blas 2.312   mkl
+  - libcblas   3.11.0   12*_mkl
+  - liblapack  3.11.0   12*_mkl
+  - liblapacke 3.11.0   12*_mkl
   track_features:
   - blas_mkl
   - blas_mkl_2
@@ -6903,8 +6903,8 @@ packages:
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-  size: 18622
-  timestamp: 1789061051585
+  size: 18578
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/libbrotlicommon-1.1.0-hb03c661_4.conda
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-  md5: 1d29d2e33fe59954af82ef54a8af3fe1
+- conda: https://conda.anaconda.org/conda-forge/linux-64/libbrotlicommon-1.1.1-h39a168f_0.conda
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+  md5: e956fd8435e45c269c466c65992f15c1
   depends:
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-  - libgcc >=14
+  - libgcc >=15
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   license_family: MIT
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-  timestamp: 1756599354727
+    - libbrotlicommon >=1.1.1,<1.2.0a0
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 - conda: https://conda.anaconda.org/conda-forge/linux-64/libbrotlicommon-1.2.1-h39a168f_0.conda
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@@ -7025,21 +7025,21 @@ packages:
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   timestamp: 1792653685570
-- conda: https://conda.anaconda.org/conda-forge/linux-64/libbrotlidec-1.1.0-hb03c661_4.conda
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-  md5: 5cb5a1c9a94a78f5b23684bcb845338d
+- conda: https://conda.anaconda.org/conda-forge/linux-64/libbrotlidec-1.1.1-ha411449_0.conda
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+  md5: c79c71a4289c1915455445a5c7588e5d
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-  - libbrotlicommon 1.1.0 hb03c661_4
-  - libgcc >=14
+  - libbrotlicommon 1.1.1 h39a168f_0
+  - libgcc >=15
   license: MIT
   license_family: MIT
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+    - libbrotlidec >=1.1.1,<1.2.0a0
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 - conda: https://conda.anaconda.org/conda-forge/linux-64/libbrotlidec-1.2.1-ha411449_0.conda
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@@ -7055,21 +7055,21 @@ packages:
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   timestamp: 1792653694124
-- conda: https://conda.anaconda.org/conda-forge/linux-64/libbrotlienc-1.1.0-hb03c661_4.conda
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-  md5: 2e55011fa483edb8bfe3fd92e860cd79
+- conda: https://conda.anaconda.org/conda-forge/linux-64/libbrotlienc-1.1.1-h018ffa1_0.conda
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   depends:
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-  - libbrotlicommon 1.1.0 hb03c661_4
-  - libgcc >=14
+  - libbrotlicommon 1.1.1 h39a168f_0
+  - libgcc >=15
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   license_family: MIT
   purls: []
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-  timestamp: 1756599375485
+    - libbrotlienc >=1.1.1,<1.2.0a0
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 - conda: https://conda.anaconda.org/conda-forge/linux-64/libbrotlienc-1.2.1-h018ffa1_0.conda
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/libcblas-3.11.0-11_h0358290_openblas.conda
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-  md5: 73a248c30811075059b5aeda766c2624
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+  - libblas 3.11.0 12_h4a7cf45_openblas
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-  - blas 2.311   openblas
-  - liblapack  3.11.0   11*_openblas
-  - liblapacke 3.11.0   11*_openblas
+  - blas 2.312   openblas
+  - liblapack  3.11.0   12*_openblas
+  - liblapacke 3.11.0   12*_openblas
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/libcblas-3.11.0-11_hfef963f_mkl.conda
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-  depends:
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+  timestamp: 1793822078553
+- conda: https://conda.anaconda.org/conda-forge/linux-64/libcblas-3.11.0-12_hfef963f_mkl.conda
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+  md5: d3383e325cb626f18ee392c3dc77e666
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   constrains:
-  - blas 2.311   mkl
-  - liblapack  3.11.0   11*_mkl
-  - liblapacke 3.11.0   11*_mkl
+  - blas 2.312   mkl
+  - liblapack  3.11.0   12*_mkl
+  - liblapacke 3.11.0   12*_mkl
   track_features:
   - blas_mkl
   license: BSD-3-Clause
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   run_exports:
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-  size: 18250
-  timestamp: 1789061057597
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@@ -7157,15 +7157,15 @@ packages:
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/libclang-cpp23.1-23.1.4-default_h0acdd01_0.conda
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-  md5: fd31eb5c1d3fda66a4357c002c522445
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   - libzlib >=1.3.2,<2.0a0
+  - zstd >=1.5.7,<1.6.0a0
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+  - libclang-cpp23.1 ==23.1.4 default_h0acdd01_1
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   - libstdcxx >=15
   - libgcc >=15
-  - zstd >=1.5.7,<1.6.0a0
   - libzlib >=1.3.2,<2.0a0
+  - zstd >=1.5.7,<1.6.0a0
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-  timestamp: 1792647858417
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+  - cuda-version >=13.5,<13.6.0a0
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   - libstdcxx >=15
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   - libgcc >=15
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+  - expat 2.9.0.*
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   - libabseil >=20260107.1,<20260108.0a0
-  - libgcc >=14
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-  - libstdcxx >=14
-  - libzlib >=1.3.1,<2.0a0
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+  - libstdcxx >=15
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-  - liblapacke 3.11.0   11*_openblas
+  - blas 2.312   openblas
+  - libcblas   3.11.0   12*_openblas
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-  - libcblas   3.11.0   11*_mkl
-  - liblapacke 3.11.0   11*_mkl
+  - blas 2.312   mkl
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+  - liblapacke 3.11.0   12*_mkl
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+  - libexpat >=2.9.0,<3.0a0
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-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libblas-3.11.0-11_h51639a9_openblas.conda
-  build_number: 11
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-  md5: 364639b771dbb4ede335d965f55a23ac
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libblas-3.11.0-12_h51639a9_openblas.conda
+  build_number: 12
+  sha256: 7eb4c80f9a4c16ac056b8f3f9f2b594190fe80ab5f124dc8f7663bc03bd47ff3
+  md5: 590dfe955db6b9a73be378e15ab909dd
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   - libopenblas >=0.3.34,<1.0a0
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-  - libcblas   3.11.0   11*_openblas
-  - liblapack  3.11.0   11*_openblas
-  - liblapacke 3.11.0   11*_openblas
+  - blas 2.312   openblas
+  - libcblas   3.11.0   12*_openblas
+  - liblapack  3.11.0   12*_openblas
+  - liblapacke 3.11.0   12*_openblas
   - mkl <2027
   license: BSD-3-Clause
   license_family: BSD
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   run_exports:
     weak:
     - libblas >=3.11.0,<4.0a0
-  size: 18300
-  timestamp: 1789061064192
+  size: 18269
+  timestamp: 1793822033281
 - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libboost-1.82.0-h489e689_6.conda
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-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libbrotlicommon-1.1.0-h6caf38d_4.conda
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-  md5: 231cffe69d41716afe4525c5c1cc5ddd
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libbrotlicommon-1.1.1-h1dcdb26_0.conda
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+  md5: ac9939a473afe20219daca00c41e1f35
   depends:
   - __osx >=11.0
   license: MIT
@@ -16233,9 +16234,9 @@ packages:
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     weak:
-    - libbrotlicommon >=1.1.0,<1.2.0a0
-  size: 68938
-  timestamp: 1756599687687
+    - libbrotlicommon >=1.1.1,<1.2.0a0
+  size: 69388
+  timestamp: 1793084424718
 - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libbrotlicommon-1.2.1-h1dcdb26_0.conda
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   md5: 2d9c219a5fcbff3a79aad7d11ff219ce
@@ -16249,20 +16250,20 @@ packages:
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   size: 80086
   timestamp: 1792653671443
-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libbrotlidec-1.1.0-h6caf38d_4.conda
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-  md5: cb7e7fe96c9eee23a464afd57648d2cd
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libbrotlidec-1.1.1-h5295a6a_0.conda
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+  md5: 640aed44db6d7b82092175005bed3980
   depends:
   - __osx >=11.0
-  - libbrotlicommon 1.1.0 h6caf38d_4
+  - libbrotlicommon 1.1.1 h1dcdb26_0
   license: MIT
   license_family: MIT
   purls: []
   run_exports:
     weak:
-    - libbrotlidec >=1.1.0,<1.2.0a0
-  size: 29015
-  timestamp: 1756599708339
+    - libbrotlidec >=1.1.1,<1.2.0a0
+  size: 29753
+  timestamp: 1793084432456
 - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libbrotlidec-1.2.1-h5295a6a_0.conda
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   md5: bbcc3032ff8d7507c086725cef8deaa6
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   size: 30090
   timestamp: 1792653678773
-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libbrotlienc-1.1.0-h6caf38d_4.conda
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-  md5: 4ce5651ae5cd6eebc5899f9bfe0eac3c
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libbrotlienc-1.1.1-h2ddc9cb_0.conda
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+  md5: abdaeb333a9bba5d16f8ba77e4d6f685
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   - __osx >=11.0
-  - libbrotlicommon 1.1.0 h6caf38d_4
+  - libbrotlicommon 1.1.1 h1dcdb26_0
   license: MIT
   license_family: MIT
   purls: []
   run_exports:
     weak:
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-  size: 275791
-  timestamp: 1756599724058
+    - libbrotlienc >=1.1.1,<1.2.0a0
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+  timestamp: 1793084440768
 - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libbrotlienc-1.2.1-h2ddc9cb_0.conda
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   timestamp: 1792653686278
-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libcblas-3.11.0-11_hb0561ab_openblas.conda
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-  md5: 73bde7d713e790b3168707e02102e87b
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libcblas-3.11.0-12_hb0561ab_openblas.conda
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+  md5: e637f014922ab2ad169e57d06d15fea1
   depends:
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+  - libblas 3.11.0 12_h51639a9_openblas
   constrains:
-  - blas 2.311   openblas
-  - liblapack  3.11.0   11*_openblas
-  - liblapacke 3.11.0   11*_openblas
+  - blas 2.312   openblas
+  - liblapack  3.11.0   12*_openblas
+  - liblapacke 3.11.0   12*_openblas
   license: BSD-3-Clause
   license_family: BSD
   purls: []
   run_exports:
     weak:
     - libcblas >=3.11.0,<4.0a0
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-  timestamp: 1789061068736
+  size: 18222
+  timestamp: 1793822036912
 - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libclang-cpp18.1-18.1.8-default_hf3020a7_18.conda
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   md5: 4c5aaaf2f27ea600c899f64b01c9f1b0
@@ -16338,14 +16339,14 @@ packages:
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   size: 13335319
   timestamp: 1773505818840
-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libclang-cpp23.1-23.1.4-default_h8bbc02d_0.conda
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-  md5: 7a2d061f28f70200423f3e4da1056aea
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libclang-cpp23.1-23.1.4-default_h8bbc02d_1.conda
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+  md5: 6088a0f084aa42b5331154321145376b
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   - __osx >=11.0
-  - zstd >=1.5.7,<1.6.0a0
   - libzlib >=1.3.2,<2.0a0
+  - zstd >=1.5.7,<1.6.0a0
   - libxml2
   - libxml2-16 >=2.15.4
   - libllvm23 >=23.1.4,<23.2.0a0
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-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libclang13-23.1.4-default_h63627a2_0.conda
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-  md5: 47cd7f341d3fd4305c75700acc4c2858
+  size: 16607160
+  timestamp: 1793320051553
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libclang13-23.1.4-default_hde1afa0_1.conda
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+  md5: c5c4ba19bacb6c677e0e1403431ad163
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-  - libclang-cpp23.1 ==23.1.4 default_h8bbc02d_0
+  - libclang-cpp23.1 ==23.1.4 default_h8bbc02d_1
   - libcxx >=23.1.4
   - __osx >=11.0
-  - zstd >=1.5.7,<1.6.0a0
   - libzlib >=1.3.2,<2.0a0
+  - zstd >=1.5.7,<1.6.0a0
   - libxml2
   - libxml2-16 >=2.15.4
   - libllvm23 >=23.1.4,<23.2.0a0
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     weak:
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-  size: 10617013
-  timestamp: 1792647648570
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+  timestamp: 1793320051553
 - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libcrc32c-1.1.2-hbdafb3b_0.tar.bz2
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   md5: 32bd82a6a625ea6ce090a81c3d34edeb
@@ -16429,17 +16430,17 @@ packages:
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   timestamp: 1792014025908
-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libcxx-23.1.4-h55c6f16_2.conda
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-  md5: 08f01709cd5f8fd7af2c29e4e3ce1846
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libcxx-23.1.5-h55c6f16_0.conda
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+  md5: df8bd5c8eaa14aaa86806be695bda0b1
   depends:
   - __osx >=11.0
   license: Apache-2.0 WITH LLVM-exception
   license_family: Apache
   purls: []
   run_exports: {}
-  size: 577255
-  timestamp: 1792748855178
+  size: 577751
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 - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libdeflate-1.25-he7e0567_1.conda
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   md5: 78650d671cb56909bb3e5c13bce310f9
@@ -16495,19 +16496,19 @@ packages:
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   size: 369136
   timestamp: 1788870250682
-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libexpat-2.8.5-h6111c0a_0.conda
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-  md5: 5383c550b785bdaafcc4eaf638071a7c
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libexpat-2.9.0-h6111c0a_0.conda
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+  md5: f85a1fda9a2758a7aef2a7787d9c0203
   depends:
   - __osx >=11.0
   constrains:
-  - expat 2.8.5.*
+  - expat 2.9.0.*
   license: MIT
   license_family: MIT
   purls: []
   run_exports: {}
-  size: 69565
-  timestamp: 1790370026495
+  size: 69681
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 - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libffi-3.7.0-h47dc5ef_1.conda
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@@ -16713,30 +16714,30 @@ packages:
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   timestamp: 1761053602943
-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libgrpc-1.78.1-h3e3f78d_0.conda
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-  md5: 17b9e07ba9b46754a6953999a948dcf7
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libgrpc-1.78.2-h240aff3_0.conda
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+  - c-ares >=1.34.9,<2.0a0
   - libabseil * cxx17*
   - libabseil >=20260107.1,<20260108.0a0
-  - libcxx >=19
+  - libcxx >=21
   - libprotobuf >=6.33.5,<6.33.6.0a0
   - libre2-11 >=2025.11.5
-  - libzlib >=1.3.1,<2.0a0
-  - openssl >=3.5.5,<4.0a0
+  - libzlib >=1.3.2,<2.0a0
+  - openssl >=3.5.9,<4.0a0
   - re2
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+  - grpc-cpp =1.78.2
   license: Apache-2.0
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   purls: []
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-  timestamp: 1774012715207
+    - libgrpc >=1.78.2,<1.79.0a0
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+  timestamp: 1793878401892
 - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libharfbuzz-15.0.0-hcda0f7c_0.conda
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   timestamp: 1790118714457
-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libjpeg-turbo-3.2.0-h84a0fba_1.conda
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-  md5: b2f8c8e5a7651a1d7c05404c3a159517
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libjpeg-turbo-3.2.1-hb001647_0.conda
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+  md5: d420b10837f3b64259b1febf263b5f7a
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+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/liblapack-3.11.0-12_hd9741b5_openblas.conda
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+  - libblas 3.11.0 12_h51639a9_openblas
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-  - libcblas   3.11.0   11*_openblas
-  - liblapacke 3.11.0   11*_openblas
+  - blas 2.312   openblas
+  - libcblas   3.11.0   12*_openblas
+  - liblapacke 3.11.0   12*_openblas
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   purls: []
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-  timestamp: 1789061072707
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 - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libllvm18-18.1.8-default_h8e162e0_12.conda
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-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libllvm23-23.1.4-h759d1ac_1.conda
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-  timestamp: 1792564352724
+    - libllvm23 >=23.1.5,<23.2.0a0
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   md5: 8ab10323068b107661a4b9a4af84f3b5
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   timestamp: 1717671966211
-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libnghttp2-1.68.1-h435687b_1.conda
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   requires_python: '>=3.10'
+- pypi: https://files.pythonhosted.org/packages/db/fe/3388224bbb7d9e68ad0325af0164d05c3ae20a8cc78d5d91c218581911d9/notebook-7.6.5-py3-none-any.whl
+  name: notebook
+  version: 7.6.5
+  sha256: b27b4af6e410e7456cfffc6fb5a764dcfb7a331408907d483024d6ddb5ec05f2
+  requires_dist:
+  - jupyter-builder>=1.0.2,<2
+  - jupyter-server>=2.19.0,<3
+  - jupyterlab-server>=2.28.0,<3
+  - jupyterlab>=4.6.6,<4.7
+  - notebook-shim>=0.2,<0.3
+  - tornado>=6.2.0
+  - hatch ; extra == 'dev'
+  - pre-commit ; extra == 'dev'
+  - myst-parser ; extra == 'docs'
+  - nbsphinx ; extra == 'docs'
+  - pydata-sphinx-theme ; extra == 'docs'
+  - sphinx>=1.3.6 ; extra == 'docs'
+  - sphinxcontrib-github-alt ; extra == 'docs'
+  - sphinxcontrib-spelling ; extra == 'docs'
+  - ipykernel ; extra == 'test'
+  - jupyter-server[test]>=2.19.0,<3 ; extra == 'test'
+  - jupyterlab-server[test]>=2.28.0,<3 ; extra == 'test'
+  - nbval ; extra == 'test'
+  - pytest-console-scripts ; extra == 'test'
+  - pytest-timeout ; extra == 'test'
+  - pytest-tornasync ; extra == 'test'
+  - pytest>=7.0 ; extra == 'test'
+  - requests ; extra == 'test'
+  requires_python: '>=3.10'
 - pypi: https://files.pythonhosted.org/packages/dc/55/6467fde553886cb293e41538f3a8b4e4fd4688c6df242cf982162d8367fb/python_json_logger-4.2.0-py3-none-any.whl
   name: python-json-logger
   version: 4.2.0
@@ -21634,11 +21670,11 @@ packages:
   - pytest-timeout ; extra == 'test'
   - pytest<9 ; extra == 'test'
   requires_python: '>=3.10'
-- pypi: https://files.pythonhosted.org/packages/e8/7c/b8850a8e4ad29f64a827dd6c6902db4a9aa538fb2b9eef4e26084001a3bb/ruff-0.17.2-py3-none-macosx_11_0_arm64.whl
-  name: ruff
-  version: 0.17.2
-  sha256: 92a80d2f44584dabb0189b3a6c393e37e525e04942838482010575cb81945be7
-  requires_python: '>=3.7'
+- pypi: https://files.pythonhosted.org/packages/e8/10/4353eb86278f6a59aeb9fe2be4d979c20b110b4009fa455a3ea6467cf5cb/types_pyyaml-6.0.12.20261103-py3-none-any.whl
+  name: types-pyyaml
+  version: 6.0.12.20261103
+  sha256: 444654c61f635dab82c092a511aa96a0ce31164810784b9a37314e3e56532ac8
+  requires_python: '>=3.10'
 - pypi: https://files.pythonhosted.org/packages/e8/ea/47fbdc8f37410956fd445720e927589b1e2a47772c5f28109f0ce2fa26d9/pytest_mock-3.17.0-py3-none-any.whl
   name: pytest-mock
   version: 3.17.0
@@ -21751,24 +21787,6 @@ packages:
   - typing-extensions>=4 ; extra == 'optional'
   - google-re2>=1.1 ; extra == 're2'
   requires_python: '>=3.9'
-- pypi: https://files.pythonhosted.org/packages/f3/9e/bcc9af755425ad17790bf11d73c2ea7592914cf309ee1340997670f9d57a/mypy-2.4.0-cp312-cp312-manylinux2014_x86_64.manylinux_2_17_x86_64.manylinux_2_28_x86_64.whl
-  name: mypy
-  version: 2.4.0
-  sha256: 29eb0b9427a6b11b992e452f6cceb8af724f4dceb47e779d0b35e405e996ea5e
-  requires_dist:
-  - typing-extensions>=4.6.0 ; python_full_version < '3.15'
-  - typing-extensions>=4.14.0 ; python_full_version >= '3.15'
-  - mypy-extensions>=1.0.0
-  - pathspec>=1.0.0
-  - tomli>=1.1.0 ; python_full_version < '3.11'
-  - librt>=0.16.0 ; platform_python_implementation != 'PyPy'
-  - ast-serialize>=0.11.2,<1.0.0
-  - psutil>=4.0 ; extra == 'dmypy'
-  - setuptools>=50 ; extra == 'mypyc'
-  - lxml ; extra == 'reports'
-  - pip ; extra == 'install-types'
-  - orjson ; extra == 'faster-cache'
-  requires_python: '>=3.10'
 - pypi: https://files.pythonhosted.org/packages/f9/33/bd5b9137445ea4b680023eb0469b2bb969d61303dedb2aac6560ff3d14a1/notebook_shim-0.2.4-py3-none-any.whl
   name: notebook-shim
   version: 0.2.4
@@ -21797,19 +21815,3 @@ packages:
   version: 0.16.0
   sha256: 5bcc2c4726ced915b00de0c9856a4eeabfb3fddb93e10e0b8f735b7709358b6d
   requires_python: '>=3.9'
-- pypi: https://files.pythonhosted.org/packages/fe/66/bcab3b677b71ad286b4e607e3427499537c76e13ad2e22584ba7a7d9882c/markdown-3.11.2-py3-none-any.whl
-  name: markdown
-  version: 3.11.2
-  sha256: f80390747a2a0ff2ba54da074ce4f862f72a6685f608cd2637b646a6d83993f5
-  requires_dist:
-  - coverage ; extra == 'testing'
-  - pyyaml ; extra == 'testing'
-  - zensical==0.0.62 ; extra == 'docs'
-  - mdx-gh-links==0.4 ; extra == 'docs'
-  - mkdocstrings==1.0.6 ; extra == 'docs'
-  - mkdocstrings-python==1.16.8 ; extra == 'docs'
-  - pygments==2.21.0 ; extra == 'docs'
-  - pymdown-extensions==11.0.2 ; extra == 'docs'
-  - justhtml==3.11.2 ; extra == 'docs'
-  - ghp-import==2.1.0 ; extra == 'docs'
-  requires_python: '>=3.11'
diff --git a/pixi.toml b/pixi.toml
index 9946d87..61876f3 100644
--- a/pixi.toml
+++ b/pixi.toml
@@ -7,6 +7,7 @@ platforms = ["linux-64", "osx-arm64"]
 run_mvp = "python examples/mvp/run.py"
 run_mypy = "python -m mypy -p 'tyff'"
 run_tests = { cmd = "python -m pytest -n logical tyff/_tests", env = { OPENMM_DEFAULT_PLATFORM = "CPU" } }
+run_gpu_tests = { cmd = "python -m pytest -n 1 --run-gpu -m gpu tyff/_tests", env = { OPENMM_DEFAULT_PLATFORM = "GPU" } }
 dev_tests = { cmd = "python -m pytest -s -x --pdb --lf tyff/_tests", env = { OPENMM_DEFAULT_PLATFORM = "CPU" } }
 
 [dependencies]
diff --git a/tyff/_tests/integration_tests/compute/test_workflow.py b/tyff/_tests/integration_tests/compute/test_workflow.py
index ace58f2..2ab939f 100644
--- a/tyff/_tests/integration_tests/compute/test_workflow.py
+++ b/tyff/_tests/integration_tests/compute/test_workflow.py
@@ -48,11 +48,15 @@ def test_nonstandard_pressure(tmp_path):
 
         for job_dir in job_dirs:
             with open(job_dir / "compute_config.json") as f:
-                target_pressure = json.load(f)["pressure"]
+                compute_config = json.load(f)
+                target_pressure = compute_config["pressure"]
+
+                assert compute_config["temperature"] == 298.15
 
             with open(job_dir / "ensemble_averages.json") as f:
                 density = json.load(f)["density"]
 
             results[target_pressure] = density
 
+        # these should be ~1.04 and ~1.00, but certainly denser at higher pressure
         assert results[101325.0] > results[101.325]

From 619a32dedcac06a71f75912e7d593adda6be1989 Mon Sep 17 00:00:00 2001
From: "Matthew W. Thompson" <mattwthompson@protonmail.com>
Date: Sun, 8 Nov 2026 10:48:28 -0600
Subject: [PATCH 07/18] More safely recurse directories

---
 pixi.lock                                     | 340 +++++++++---------
 pixi.toml                                     |   2 +-
 .../compute/test_workflow.py                  |   9 +-
 3 files changed, 180 insertions(+), 171 deletions(-)

diff --git a/pixi.lock b/pixi.lock
index 20e60cf..0684087 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -46,7 +46,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/brotli-python-1.2.1-py313h2fc2bef_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_10.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/c-ares-1.34.9-hebe6cf0_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/c-blosc2-3.3.5-hea3f660_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/c-blosc2-3.5.0-hea3f660_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/cairo-1.18.6-h3c89d7e_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/cftime-1.6.5-py313h12b3e8d_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/charset-normalizer-3.5.2-h1114479_0.conda
@@ -95,7 +95,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libcrc32c-1.1.2-h9c3ff4c_0.tar.bz2
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libcufft-12.5.0.14-h393e864_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libcurl-8.23.0-ha042cf0_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libdeflate-1.25-hd45a770_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libdeflate-1.26-h351257e_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libedit-3.1.20260512-pl5321h373387f_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libev-4.33-h280c20c_3.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libevent-2.1.12-h5348a74_2.conda
@@ -118,7 +118,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/liblapack-3.11.0-12_h5e43f62_mkl.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/liblzma-5.8.3-hb03c661_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libmpdec-4.0.0-hb03c661_2.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libnetcdf-4.10.1-nompi_hf21f329_202.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libnetcdf-4.10.1-nompi_hf21f329_203.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libnghttp2-1.71.0-hc5e5977_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libntlm-1.8-hb9d3cd8_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libopentelemetry-cpp-1.26.0-h9692893_0.conda
@@ -137,7 +137,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-16.2.0-h934c35e_7.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libstdcxx-ng-16.2.0-hdf11a46_7.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libthrift-0.22.0-h64ffe93_3.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libtiff-4.7.2-hcc2c06a_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libtiff-4.7.2-h6d37cbf_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libtorch-2.12.0-cpu_mkl_h55d9b97_100.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libutf8proc-2.11.3-hfe17d71_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libuuid-2.42.4-hcfc3c73_1.conda
@@ -194,7 +194,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/pyarrow-core-20.0.0-py313he109ebe_2_cpu.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/pycairo-1.29.2-py313h0e1c009_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/pydantic-core-2.50.4-py313ha296275_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/pytables-3.11.1-py313h2e33612_6.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/pytables-3.11.1-py313h2e33612_7.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.13.18-hf47f18c_100_cp313.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/python-xxhash-3.7.0-py313h554d1e1_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/pytorch-2.12.0-cpu_mkl_py313_h5a856d5_100.conda
@@ -234,9 +234,9 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/noarch/bokeh-3.9.2-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/bson-0.5.10-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.10.23-hbd8a1cb_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/cachetools-7.3.0-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/cachetools-8.0.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/certifi-2026.10.23-pyhd8ed1ab_3.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/click-8.5.0-pyh5ded981_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/click-8.5.1-pyh5ded981_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/click-option-group-0.5.9-pyhcf101f3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/cloudpickle-3.1.2-pyhcf101f3_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/cmiles-base-0.1.6-pyhd8ed1ab_2.tar.bz2
@@ -463,10 +463,10 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/noarch/bokeh-3.9.2-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/bson-0.5.10-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/ca-certificates-2026.10.23-hbd8a1cb_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/cachetools-7.3.0-pyhd8ed1ab_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/cachetools-8.0.0-pyhd8ed1ab_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/certifi-2026.10.23-pyhd8ed1ab_3.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/charset-normalizer-3.5.1-pyhd8ed1ab_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/click-8.5.0-pyh5ded981_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/click-8.5.1-pyh5ded981_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/click-option-group-0.5.9-pyhcf101f3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/cloudpickle-3.1.2-pyhcf101f3_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/cpython-3.12.16-py312hd8ed1ab_0.conda
@@ -597,7 +597,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/osx-arm64/brotli-python-1.2.1-py312ha52686f_0.conda
       - conda: https://conda.anaconda.org/conda-forge/osx-arm64/bzip2-1.0.8-h4e30115_10.conda
       - conda: https://conda.anaconda.org/conda-forge/osx-arm64/c-ares-1.34.9-h74c22ad_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/osx-arm64/c-blosc2-3.3.5-h7c780c3_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/osx-arm64/c-blosc2-3.5.0-h7c780c3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/osx-arm64/cairo-1.18.6-h580cee5_0.conda
       - conda: https://conda.anaconda.org/conda-forge/osx-arm64/cftime-1.6.5-py312h23212ae_2.conda
       - conda: https://conda.anaconda.org/conda-forge/osx-arm64/contourpy-1.4.0-py312h67ba313_1.conda
@@ -643,7 +643,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libcrc32c-1.1.2-hbdafb3b_0.tar.bz2
       - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libcurl-8.23.0-h6651222_0.conda
       - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libcxx-23.1.5-h55c6f16_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libdeflate-1.25-he7e0567_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libdeflate-1.26-h72bfca4_0.conda
       - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libedit-3.1.20260512-pl5321h26f1114_0.conda
       - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libev-4.33-h1a92334_3.conda
       - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libevent-2.1.12-h4b5715a_2.conda
@@ -664,7 +664,7 @@ environments:
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       - conda: https://conda.anaconda.org/conda-forge/osx-arm64/liblapack-3.11.0-12_hd9741b5_openblas.conda
       - conda: https://conda.anaconda.org/conda-forge/osx-arm64/liblzma-5.8.3-h8088a28_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libnetcdf-4.10.1-nompi_hf6677ca_202.conda
+      - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libnetcdf-4.10.1-nompi_hf6677ca_203.conda
       - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libnghttp2-1.71.0-h29223de_0.conda
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       - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libopenblas-0.3.34-openmp_h5e6e99c_1.conda
@@ -682,7 +682,7 @@ environments:
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       - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libthrift-0.22.0-h3ffe37c_3.conda
-      - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libtiff-4.7.2-hf67920b_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libtiff-4.7.2-h87d37ca_2.conda
       - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libtorch-2.11.0-cpu_generic_h5d695db_1.conda
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@@ -733,7 +733,7 @@ environments:
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-      - conda: https://conda.anaconda.org/conda-forge/osx-arm64/pytables-3.11.1-py312h14fb2d0_6.conda
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@@ -5435,7 +5435,7 @@ packages:
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   license_family: MIT
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+  - pkg:pypi/brotli?source=hash-mapping
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-  md5: cca490d93e9ca32e2605d9141e189caa
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   license_family: BSD
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+  - pkg:pypi/cytoolz?source=compressed-mapping
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   license_family: BSD
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+  - pkg:pypi/cytoolz?source=compressed-mapping
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-  md5: 40f9b31aa9cf007789867df0decd0492
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+    - libdeflate >=1.26,<1.27.0a0
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/libnetcdf-4.10.1-nompi_hf21f329_202.conda
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-  md5: ba5cc8359007a234140c5575ee4c90a8
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@@ -8456,6 +8455,7 @@ packages:
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   - libstdcxx >=15
   license: BSD-3-Clause
+  license_family: BSD
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-  md5: 0907d876f460ebc941ae590338b6102f
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+  md5: 18023fe8fbec4f031ca88444572590e4
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   - __glibc >=2.17,<3.0.a0
-  - lerc >=4.2.0,<5.0a0
-  - libdeflate >=1.25,<1.26.0a0
+  - lerc >=4.3.0,<5.0a0
+  - libdeflate >=1.26,<1.27.0a0
   - libgcc >=15
-  - libjpeg-turbo >=3.2.0,<4.0a0
+  - libjpeg-turbo >=3.2.1,<4.0a0
   - liblzma >=5.8.3,<6.0a0
   - libstdcxx >=15
   - libwebp-base >=1.6.0,<2.0a0
@@ -8659,8 +8659,8 @@ packages:
   run_exports:
     weak:
     - libtiff >=4.7.2,<4.8.0a0
-  size: 459753
-  timestamp: 1787755584172
+  size: 459656
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 - conda: https://conda.anaconda.org/conda-forge/linux-64/libtorch-2.10.0-cpu_generic_h3f66b26_1.conda
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   md5: d6c6347d60da4b834d9b0d347093488e
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   - python_abi 3.12.* *_cp312
   license: MPL-2.0 AND Apache-2.0
   purls:
-  - pkg:pypi/ml-dtypes?source=compressed-mapping
+  - pkg:pypi/ml-dtypes?source=hash-mapping
   run_exports: {}
   size: 369809
   timestamp: 1792786261608
@@ -9426,7 +9426,7 @@ packages:
   license: Apache-2.0
   license_family: APACHE
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-  - pkg:pypi/multidict?source=compressed-mapping
+  - pkg:pypi/multidict?source=hash-mapping
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   size: 279916
   timestamp: 1793017848732
@@ -10851,14 +10851,14 @@ packages:
   run_exports: {}
   size: 1643123
   timestamp: 1784970418674
-- conda: https://conda.anaconda.org/conda-forge/linux-64/pytables-3.11.1-py312hbb427fd_6.conda
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-  md5: 0caa5752f83fb3a2edec9d8cb665f45b
+- conda: https://conda.anaconda.org/conda-forge/linux-64/pytables-3.11.1-py312hbb427fd_7.conda
+  sha256: 74da258b2dadfdfa74b66dfa7da7f3e220f0eec829ad367c985eb464ae64df40
+  md5: 9b4d8d6c42b428ad758e33509e37f16b
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-  - blosc >=1.21.6,<2.0a0
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   - bzip2 >=1.0.8,<2.0a0
-  - c-blosc2 >=3.3.4,<3.4.0a0
+  - c-blosc2 >=3.5.0,<3.6.0a0
   - hdf5 >=1.14.6,<1.14.7.0a0
   - libgcc >=15
   - libstdcxx >=15
@@ -10874,18 +10874,18 @@ packages:
   license: BSD-3-Clause
   license_family: BSD
   purls:
-  - pkg:pypi/tables?source=compressed-mapping
+  - pkg:pypi/tables?source=hash-mapping
   run_exports: {}
-  size: 1667028
-  timestamp: 1789139631310
-- conda: https://conda.anaconda.org/conda-forge/linux-64/pytables-3.11.1-py313h2e33612_6.conda
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+  size: 1668994
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+- conda: https://conda.anaconda.org/conda-forge/linux-64/pytables-3.11.1-py313h2e33612_7.conda
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+  md5: 3f9cf27c754fbfbbc6b1c177fe1b6290
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   - __glibc >=2.17,<3.0.a0
-  - blosc >=1.21.6,<2.0a0
+  - blosc >=1.21.7,<2.0a0
   - bzip2 >=1.0.8,<2.0a0
-  - c-blosc2 >=3.3.4,<3.4.0a0
+  - c-blosc2 >=3.5.0,<3.6.0a0
   - hdf5 >=1.14.6,<1.14.7.0a0
   - libgcc >=15
   - libstdcxx >=15
@@ -10901,10 +10901,10 @@ packages:
   license: BSD-3-Clause
   license_family: BSD
   purls:
-  - pkg:pypi/tables?source=compressed-mapping
+  - pkg:pypi/tables?source=hash-mapping
   run_exports: {}
-  size: 1680024
-  timestamp: 1789139641801
+  size: 1687271
+  timestamp: 1794044718101
 - conda: https://conda.anaconda.org/conda-forge/linux-64/python-3.12.15-h5f976f7_1_cpython.conda
   build_number: 1
   sha256: c9ef4af30139ad7d5e75ec6a740db8f2f5a7aa0bac5b626d7b77d206d742c369
@@ -11342,6 +11342,7 @@ packages:
   - reportlab
   - sqlalchemy
   license: BSD-3-Clause
+  license_family: BSD
   purls:
   - pkg:pypi/rdkit?source=hash-mapping
   run_exports: {}
@@ -11372,6 +11373,7 @@ packages:
   - reportlab
   - sqlalchemy
   license: BSD-3-Clause
+  license_family: BSD
   purls:
   - pkg:pypi/rdkit?source=hash-mapping
   run_exports: {}
@@ -11663,6 +11665,7 @@ packages:
   - libgcc >=15
   - python_abi 3.12.* *_cp312
   license: Apache-2.0
+  license_family: APACHE
   purls:
   - pkg:pypi/tornado?source=hash-mapping
   run_exports: {}
@@ -11677,6 +11680,7 @@ packages:
   - libgcc >=15
   - python_abi 3.13.* *_cp313
   license: Apache-2.0
+  license_family: APACHE
   purls:
   - pkg:pypi/tornado?source=compressed-mapping
   run_exports: {}
@@ -12297,9 +12301,9 @@ packages:
   run_exports: {}
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   timestamp: 1792772446739
-- conda: https://conda.anaconda.org/conda-forge/noarch/cachetools-7.3.0-pyhd8ed1ab_0.conda
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-  md5: 3bcfa89219c46a5b7c047eca5ece20bf
+- conda: https://conda.anaconda.org/conda-forge/noarch/cachetools-8.0.0-pyhd8ed1ab_0.conda
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+  md5: b629bd95e5995a70212e499122347d06
   depends:
   - python >=3.11
   license: MIT
@@ -12307,8 +12311,8 @@ packages:
   purls:
   - pkg:pypi/cachetools?source=hash-mapping
   run_exports: {}
-  size: 23687
-  timestamp: 1793927648766
+  size: 23093
+  timestamp: 1794078276129
 - conda: https://conda.anaconda.org/conda-forge/noarch/certifi-2026.10.23-pyhd8ed1ab_3.conda
   sha256: e17d21d2f133cae8eede0eef5a8acfa076b1999d00f11e714e1d18c2c8fd02c6
   md5: 6e761a5c8fd92be3a9fec46ade31b481
@@ -12333,9 +12337,9 @@ packages:
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-- conda: https://conda.anaconda.org/conda-forge/noarch/click-8.5.0-pyh5ded981_0.conda
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-  md5: dea5b13a211bbf99876deb980b408a66
+- conda: https://conda.anaconda.org/conda-forge/noarch/click-8.5.1-pyh5ded981_0.conda
+  sha256: f26981878e8ccdc82fc9025d25997aff119080486e5d089948cb718d428d8cb0
+  md5: d996564510ceb5744c225b93891316dc
   depends:
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   - python
@@ -12344,8 +12348,8 @@ packages:
   purls:
   - pkg:pypi/click?source=compressed-mapping
   run_exports: {}
-  size: 112341
-  timestamp: 1788802215348
+  size: 112921
+  timestamp: 1794046236533
 - conda: https://conda.anaconda.org/conda-forge/noarch/click-option-group-0.5.9-pyhcf101f3_0.conda
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   md5: d64dbb12cae6d209b7bd0587eaae3541
@@ -12633,7 +12637,7 @@ packages:
   license: BSD-3-Clause
   license_family: BSD
   purls:
-  - pkg:pypi/flexparser?source=compressed-mapping
+  - pkg:pypi/flexparser?source=hash-mapping
   run_exports: {}
   size: 30745
   timestamp: 1788605800152
@@ -15143,9 +15147,9 @@ packages:
     - c-blosc2 >=3.2.3,<3.3.0a0
   size: 291985
   timestamp: 1784174620114
-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/c-blosc2-3.3.5-h7c780c3_0.conda
-  sha256: 51f57c09f3ff9eeb3a17753c21de95c73c3ebc60add8c14bc4a4432e2649c1b8
-  md5: 327f552d4d4470eed5df46c59e39f9f1
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/c-blosc2-3.5.0-h7c780c3_0.conda
+  sha256: 05758b7b28fe6de67e27f0570b72dbfec89bb48232089c45ba315ddae2296cf8
+  md5: 74369a63e442b74b4902e76aae97b03a
   depends:
   - __osx >=11.0
   - libcxx >=21
@@ -15157,9 +15161,9 @@ packages:
   purls: []
   run_exports:
     weak:
-    - c-blosc2 >=3.3.5,<3.4.0a0
-  size: 297167
-  timestamp: 1790298008678
+    - c-blosc2 >=3.5.0,<3.6.0a0
+  size: 323158
+  timestamp: 1793835941005
 - conda: https://conda.anaconda.org/conda-forge/osx-arm64/cairo-1.18.0-hc6c324b_2.conda
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   md5: 6efeefcad878c15377f49f64e2cbf232
@@ -15217,7 +15221,7 @@ packages:
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   license_family: MIT
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-  - pkg:pypi/cffi?source=hash-mapping
+  - pkg:pypi/cffi?source=compressed-mapping
   run_exports: {}
   size: 289165
   timestamp: 1788485306633
@@ -15298,7 +15302,7 @@ packages:
   license: BSD-3-Clause
   license_family: BSD
   purls:
-  - pkg:pypi/cytoolz?source=hash-mapping
+  - pkg:pypi/cytoolz?source=compressed-mapping
   run_exports: {}
   size: 695392
   timestamp: 1791511337371
@@ -16441,9 +16445,9 @@ packages:
   run_exports: {}
   size: 577751
   timestamp: 1793848731635
-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libdeflate-1.25-he7e0567_1.conda
-  sha256: d896f4aa4ce4c590c2838678cb1917356fdb461d2a189991c0280c818c362172
-  md5: 78650d671cb56909bb3e5c13bce310f9
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libdeflate-1.26-h72bfca4_0.conda
+  sha256: f9c75ef67dbcc8e3c255d37e32948550bc8aa6752102c181686630b9ede96b8d
+  md5: 3f49c4c4ebcdb9fa285e5c73441063c1
   depends:
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   license: MIT
@@ -16451,9 +16455,9 @@ packages:
   purls: []
   run_exports:
     weak:
-    - libdeflate >=1.25,<1.26.0a0
-  size: 55727
-  timestamp: 1785909153744
+    - libdeflate >=1.26,<1.27.0a0
+  size: 55312
+  timestamp: 1787442891411
 - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libedit-3.1.20260512-pl5321h26f1114_0.conda
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   md5: ef2ab2462744ec6ba3a54c34dcc6a06e
@@ -16970,33 +16974,32 @@ packages:
     - libnetcdf >=4.10.1,<4.10.2.0a0
   size: 807359
   timestamp: 1783982087132
-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libnetcdf-4.10.1-nompi_hf6677ca_202.conda
-  build_number: 102
-  sha256: 3f4e175f4afb41eb74d6f0373fb3acdc9374b2728c9ed1d06f38ac073833e3e0
-  md5: 1accf60f93e7e9c8d1554cf774c730f0
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libnetcdf-4.10.1-nompi_hf6677ca_203.conda
+  build_number: 103
+  sha256: fb3fe46b0238731b8d6c81f3df96c1332631fd2638e2fd30c59739d05aee7a52
+  md5: 61b4c698f6d468542e8cc5304d54bed9
   depends:
   - libcxx >=21
   - __osx >=11.0
-  - libaec >=1.1.5,<2.0a0
-  - openssl >=3.5.9,<4.0a0
-  - hdf5 >=1.14.6,<1.14.7.0a0
-  - hdf4 >=4.2.15,<4.2.16.0a0
-  - libxml2
-  - libxml2-16 >=2.15.4
   - zstd >=1.5.7,<1.6.0a0
-  - blosc >=1.21.6,<2.0a0
+  - libaec >=1.1.7,<2.0a0
+  - blosc >=1.21.7,<2.0a0
+  - hdf4 >=4.2.15,<4.2.16.0a0
   - bzip2 >=1.0.8,<2.0a0
   - libzlib >=1.3.2,<2.0a0
-  - libzip >=1.12.1,<2.0a0
   - libcurl >=8.23.0,<9.0a0
+  - openssl >=3.5.9,<4.0a0
+  - libzip >=1.12.1,<2.0a0
+  - libxml2
+  - libxml2-16 >=2.15.4
+  - hdf5 >=1.14.6,<1.14.7.0a0
   license: MIT
-  license_family: MIT
   purls: []
   run_exports:
     weak:
     - libnetcdf >=4.10.1,<4.10.2.0a0
-  size: 826139
-  timestamp: 1792950580675
+  size: 826323
+  timestamp: 1794076089634
 - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libnetcdf-4.9.2-nompi_he469be0_114.conda
   sha256: aeac591ba859f9cf775993e8b7f21e50803405d41ef363dc4981d114e8df88a8
   md5: 8fd3ce6d910ed831c130c391c4364d3f
@@ -17496,15 +17499,15 @@ packages:
     - libthrift >=0.22.0,<0.22.1.0a0
   size: 322277
   timestamp: 1793150586884
-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libtiff-4.7.2-hf67920b_1.conda
-  sha256: 847d22a86ae28f66d3888702698254d25bb4eac3a0f64c1fabfb1842ac00be4c
-  md5: b6b191267455bf202af79f973690ed5d
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libtiff-4.7.2-h87d37ca_2.conda
+  sha256: 3c1cf481a60ed8598093641b3a41ee1a7bb78413029ec566a238927504e941bd
+  md5: ac0e529ed6020472c12f740602e58ab5
   depends:
   - __osx >=11.0
-  - lerc >=4.2.0,<5.0a0
+  - lerc >=4.3.0,<5.0a0
   - libcxx >=21
-  - libdeflate >=1.25,<1.26.0a0
-  - libjpeg-turbo >=3.2.0,<4.0a0
+  - libdeflate >=1.26,<1.27.0a0
+  - libjpeg-turbo >=3.2.1,<4.0a0
   - liblzma >=5.8.3,<6.0a0
   - libwebp-base >=1.6.0,<2.0a0
   - libzlib >=1.3.2,<2.0a0
@@ -17514,8 +17517,8 @@ packages:
   run_exports:
     weak:
     - libtiff >=4.7.2,<4.8.0a0
-  size: 380645
-  timestamp: 1787756067271
+  size: 380333
+  timestamp: 1794045696512
 - conda: https://conda.anaconda.org/conda-forge/osx-arm64/libtorch-2.10.0-cpu_generic_hc627905_1.conda
   sha256: c8c0f1141a0364690f914be3756f828a37a94c1f3fc08119cfe1fc0213ce69ce
   md5: b2b4a071ab5d82ecef50f4890853739a
@@ -17956,7 +17959,7 @@ packages:
   - numpy >=1.25,<3
   license: MPL-2.0 AND Apache-2.0
   purls:
-  - pkg:pypi/ml-dtypes?source=hash-mapping
+  - pkg:pypi/ml-dtypes?source=compressed-mapping
   run_exports: {}
   size: 246811
   timestamp: 1792786317299
@@ -18935,14 +18938,14 @@ packages:
   run_exports: {}
   size: 1771109
   timestamp: 1740640249078
-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/pytables-3.11.1-py312h14fb2d0_6.conda
-  sha256: 4a1d6f4f9acaa4e68940132c92980f8fc3e634c6141ec893bef222d9e390b31e
-  md5: 33eb025e2758072e89139d4e6e55cabf
+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/pytables-3.11.1-py312h14fb2d0_7.conda
+  sha256: dbbb7648d4a0a1b6581d195222631c173a06f052e6760e1a384c02fa3b5f58a9
+  md5: 0dd2063da25afe55c490390320b3a7a3
   depends:
   - __osx >=11.0
-  - blosc >=1.21.6,<2.0a0
+  - blosc >=1.21.7,<2.0a0
   - bzip2 >=1.0.8,<2.0a0
-  - c-blosc2 >=3.3.4,<3.4.0a0
+  - c-blosc2 >=3.5.0,<3.6.0a0
   - hdf5 >=1.14.6,<1.14.7.0a0
   - libcxx >=21
   - libzlib >=1.3.2,<2.0a0
@@ -18957,10 +18960,10 @@ packages:
   license: BSD-3-Clause
   license_family: BSD
   purls:
-  - pkg:pypi/tables?source=compressed-mapping
+  - pkg:pypi/tables?source=hash-mapping
   run_exports: {}
-  size: 1532615
-  timestamp: 1789139617084
+  size: 1530045
+  timestamp: 1794044657994
 - conda: https://conda.anaconda.org/conda-forge/osx-arm64/pytables-3.11.1-py312h4f4653e_5.conda
   sha256: 331621809e293900a77ecf1f1ca15bd8b9ef08794d44b64f0ca8bc0cf2f6d651
   md5: c9e305aba5a02811158661684dd486ae
@@ -19442,6 +19445,7 @@ packages:
   - __osx >=11.0
   - python_abi 3.12.* *_cp312
   license: Apache-2.0
+  license_family: APACHE
   purls:
   - pkg:pypi/tornado?source=hash-mapping
   run_exports: {}
diff --git a/pixi.toml b/pixi.toml
index 61876f3..a1b460b 100644
--- a/pixi.toml
+++ b/pixi.toml
@@ -7,7 +7,7 @@ platforms = ["linux-64", "osx-arm64"]
 run_mvp = "python examples/mvp/run.py"
 run_mypy = "python -m mypy -p 'tyff'"
 run_tests = { cmd = "python -m pytest -n logical tyff/_tests", env = { OPENMM_DEFAULT_PLATFORM = "CPU" } }
-run_gpu_tests = { cmd = "python -m pytest -n 1 --run-gpu -m gpu tyff/_tests", env = { OPENMM_DEFAULT_PLATFORM = "GPU" } }
+run_gpu_tests = { cmd = "python -m pytest -n 1 --run-gpu -m gpu tyff/_tests --color=no", env = { OPENMM_DEFAULT_PLATFORM = "GPU" } }
 dev_tests = { cmd = "python -m pytest -s -x --pdb --lf tyff/_tests", env = { OPENMM_DEFAULT_PLATFORM = "CPU" } }
 
 [dependencies]
diff --git a/tyff/_tests/integration_tests/compute/test_workflow.py b/tyff/_tests/integration_tests/compute/test_workflow.py
index 2ab939f..a6a78a4 100644
--- a/tyff/_tests/integration_tests/compute/test_workflow.py
+++ b/tyff/_tests/integration_tests/compute/test_workflow.py
@@ -42,7 +42,13 @@ def test_nonstandard_pressure(tmp_path):
         workflow.wait()
 
         # hack - there needs to be a better way of grabbing results
-        job_dirs = [path for path in (tmp_path / "simulations").glob("*/") if not path.match("thermo_targets")]
+        job_dirs = [
+            path
+            for path in (tmp_path).glob("*/")
+            if not path.match("thermo_targets")
+            and not path.match("reference_force_fields")
+            and not path.match("interchanges")
+        ]
 
         results = dict()
 
@@ -58,5 +64,4 @@ def test_nonstandard_pressure(tmp_path):
 
             results[target_pressure] = density
 
-        # these should be ~1.04 and ~1.00, but certainly denser at higher pressure
         assert results[101325.0] > results[101.325]

From 631986708b36ce54e38ccd963e51078e55bb4455 Mon Sep 17 00:00:00 2001
From: "Matthew W. Thompson" <mattwthompson@protonmail.com>
Date: Sun, 8 Nov 2026 15:38:51 -0600
Subject: [PATCH 08/18] Pin Pytest <9.2

---
 pixi.lock | 88 +++++++++++++++++++++++++------------------------------
 pixi.toml |  3 ++
 2 files changed, 43 insertions(+), 48 deletions(-)

diff --git a/pixi.lock b/pixi.lock
index 0684087..36e280a 100644
--- a/pixi.lock
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       - pypi: https://files.pythonhosted.org/packages/45/3c/b88167e2d6785c0e781ee5d498b07472aeb9b6765da3b19e7cc9e0813841/python_daemon-3.1.2-py3-none-any.whl
@@ -3551,10 +3560,8 @@ environments:
       - pypi: https://files.pythonhosted.org/packages/4b/76/6f8221eda15f28471c3887e5a75a62cd7338d20ac03e1e78a110a127d61e/sqlmodel-0.0.48-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/4d/dd/8bc67e7d5ffc1d88aa5af511189dfb76dc4e1e5b808fab186146ef2663e5/executing-2.3.0-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/4f/d3/a8b22fa575b297cd6e3e3b0155c7e25db170edf1c74783d6a31a2490b8d9/argon2_cffi-25.1.0-py3-none-any.whl
-      - pypi: https://files.pythonhosted.org/packages/51/39/1f5d8c8877a0fa327db959c19341d4be61660de1ab6b7391f9eb805bcd67/pytest-9.2.0-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/54/6f/84908cad2d6aa5144abcf7b42709fe4fdb459bc640ec7ac5786e7693dabc/prompt_toolkit-3.0.53-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/56/3d/c7dc9f35bc9e22cdb53679f844bee40fd5cff871862f60595869a433400d/debugpy-1.8.22-py2.py3-none-any.whl
-      - pypi: https://files.pythonhosted.org/packages/56/43/4ca9e49d27a1fcf6bece6f6aec0ea46bb9112489b93d4b688fb415457bdb/iniconfig-2.3.1-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/57/be/6a10d95bba71fd5f441dda01ae374ebcaeaa637a09f72b95e8cc59443958/setproctitle-1.3.8-cp312-cp312-macosx_11_0_arm64.whl
       - pypi: https://files.pythonhosted.org/packages/58/9d/40b6267367182187139a4000b82a3b287d84d745bccd808e75d916920e9d/bleach-6.4.0-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/59/6f/90230e26decc7cc8e11cea93ae45430b7a5539c50877ff270fa1b38d017e/symengine-0.15.0-cp311-abi3-macosx_11_0_arm64.whl
@@ -3565,7 +3572,6 @@ environments:
       - pypi: https://files.pythonhosted.org/packages/69/f0/842ff0c6ed2e9a4d027d32576813ef92c014f72743a3e745e0a9ce9df24b/jupyterlab-4.6.6-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/6a/9e/2064975477fdc887e47ad42157e214526dcad8f317a948dee17e1659a62f/terminado-0.18.1-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/6d/18/83376915176eb058cb86470eb7396388a13350b09a8f233a79303bbcbc5b/pure_eval-0.2.4-py3-none-any.whl
-      - pypi: https://files.pythonhosted.org/packages/71/46/17f022dd3e953bf20a04a028a21ec746d942f8d2af30fa0f124fa0e6a684/pygments-2.21.0-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/73/1d/ad4064bf12f4503bf61e65d74c93c523672776d25ee0a06aaf42ae09ef3f/vcs_versioning-2.6.0-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/77/c6/040cbc72480d789a5f40d63fb484d3106554c4dfa2d2b70ad5022057750f/webencodings-0.6.1-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/77/f5/21d2de20e8b8b0408f0681956ca2c69f1320a3848ac50e6e7f39c6159675/babel-2.18.0-py3-none-any.whl
@@ -3936,7 +3942,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/noarch/pygments-2.21.0-pyhcf101f3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pyparsing-3.3.3-pyh5ded981_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pysocks-1.7.1-pyha55dd90_7.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-9.2.0-pyhc364b38_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-9.1.1-pyhc364b38_2.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/python-constraint-1.4.0-pyhff2d567_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/python-dateutil-4.0.0-pyh5ded981_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/python-gil-3.12.16-hd8ed1ab_0.conda
@@ -4185,7 +4191,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/noarch/pymbar-core-4.2.0-pyhd8ed1ab_2.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pyparsing-3.3.2-pyhcf101f3_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/pysocks-1.7.1-pyha55dd90_7.conda
-      - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-9.2.0-pyhc364b38_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-9.1.1-pyhc364b38_2.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/python-constraint-1.4.0-pyhff2d567_1.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/python-dateutil-4.0.0-pyh5ded981_0.conda
       - conda: https://conda.anaconda.org/conda-forge/noarch/python-gil-3.12.16-hd8ed1ab_0.conda
@@ -13768,6 +13774,28 @@ packages:
   run_exports: {}
   size: 21085
   timestamp: 1733217331982
+- conda: https://conda.anaconda.org/conda-forge/noarch/pytest-9.1.1-pyhc364b38_2.conda
+  sha256: 430051d80765207a7d782b2b188230ba1489d35c6e75fd9903f76cb9fda4af16
+  md5: 64c98a12c4e23eb238bf66bbecafdf3c
+  depends:
+  - colorama
+  - pygments >=2.7.2
+  - python >=3.10
+  - iniconfig >=1.0.1
+  - packaging >=22
+  - pluggy >=1.5,<2
+  - tomli >=1
+  - exceptiongroup >=1
+  - python
+  constrains:
+  - pytest-faulthandler >=2
+  license: MIT
+  license_family: MIT
+  purls:
+  - pkg:pypi/pytest?source=hash-mapping
+  run_exports: {}
+  size: 306724
+  timestamp: 1782127176429
 - conda: https://conda.anaconda.org/conda-forge/noarch/pytest-9.2.0-pyhc364b38_1.conda
   sha256: a9cf3571e80a4e86992502068eb1d29a109e88345c39babf03b10450895056af
   md5: f0cfded84ced11a9dfb3790c4c1c0b63
@@ -20379,11 +20407,6 @@ packages:
   - ipykernel
   - ipywidgets
   - jupyterlab
-- pypi: https://files.pythonhosted.org/packages/40/9e/2b38731e0fc536806f16490e1a12d7f0dc2a1235aa8cc07bcc75416a7daa/pluggy-1.7.0-py3-none-any.whl
-  name: pluggy
-  version: 1.7.0
-  sha256: 7dd7b0d8832ba3cb632c306926ded123429211b83641b35dc5c41ad2d34f9bec
-  requires_python: '>=3.10'
 - pypi: https://files.pythonhosted.org/packages/41/09/5b161152e2d90f7b87f781c2e1267494aef9c32498df793f73ad0a0a494a/matplotlib_inline-0.2.2-py3-none-any.whl
   name: matplotlib-inline
   version: 0.2.2
@@ -20464,32 +20487,6 @@ packages:
   requires_dist:
   - argon2-cffi-bindings
   requires_python: '>=3.8'
-- pypi: https://files.pythonhosted.org/packages/51/39/1f5d8c8877a0fa327db959c19341d4be61660de1ab6b7391f9eb805bcd67/pytest-9.2.0-py3-none-any.whl
-  name: pytest
-  version: 9.2.0
-  sha256: 07acdcf88ec174f907dc01af70bf52d49b014bbab03faeeade31c96b18c2e588
-  requires_dist:
-  - colorama>=0.4 ; sys_platform == 'win32'
-  - exceptiongroup>=1 ; python_full_version < '3.11'
-  - iniconfig>=2
-  - packaging>=24
-  - pluggy>=1.6,<2
-  - pygments>=2.15
-  - tomli>=2 ; python_full_version < '3.11'
-  - argcomplete ; extra == 'dev'
-  - asynctest ; python_full_version < '3.11' and extra == 'dev'
-  - attrs>=23.1 ; extra == 'dev'
-  - coverage>=7.5 ; extra == 'dev'
-  - hypothesis>=6.75 ; extra == 'dev'
-  - mock ; extra == 'dev'
-  - numpy>=1.26 ; extra == 'dev'
-  - pexpect>=4.9 ; extra == 'dev'
-  - pytest-xdist>=3.5 ; extra == 'dev'
-  - pyyaml ; extra == 'dev'
-  - requests ; extra == 'dev'
-  - setuptools ; extra == 'dev'
-  - xmlschema ; extra == 'dev'
-  requires_python: '>=3.10'
 - pypi: https://files.pythonhosted.org/packages/54/6f/84908cad2d6aa5144abcf7b42709fe4fdb459bc640ec7ac5786e7693dabc/prompt_toolkit-3.0.53-py3-none-any.whl
   name: prompt-toolkit
   version: 3.0.53
@@ -20509,11 +20506,6 @@ packages:
   version: 1.8.22
   sha256: a9e9d3550e15ca479c59333e90845029190531f0cacfedab3b815a57bd913947
   requires_python: '>=3.10'
-- pypi: https://files.pythonhosted.org/packages/56/43/4ca9e49d27a1fcf6bece6f6aec0ea46bb9112489b93d4b688fb415457bdb/iniconfig-2.3.1-py3-none-any.whl
-  name: iniconfig
-  version: 2.3.1
-  sha256: 9121e2c1fdb355232495be3194c8dfe87ccc2d5dee45947b78e68f499790d7a7
-  requires_python: '>=3.10'
 - pypi: https://files.pythonhosted.org/packages/57/be/6a10d95bba71fd5f441dda01ae374ebcaeaa637a09f72b95e8cc59443958/setproctitle-1.3.8-cp312-cp312-macosx_11_0_arm64.whl
   name: setproctitle
   version: 1.3.8
diff --git a/pixi.toml b/pixi.toml
index a1b460b..7de913a 100644
--- a/pixi.toml
+++ b/pixi.toml
@@ -84,6 +84,9 @@ cuda-version = "==13.0"
 [feature.py312.dependencies]
 python = "3.12.*"
 
+[feature.test.dependencies]
+pytest = "<9.2"
+
 [feature.test.pypi-dependencies]
 pytest = "*"
 pytest-cov = "*"

From 5473dbfd7032cbc8128315edcbd4f07d3a12d07a Mon Sep 17 00:00:00 2001
From: "Matthew W. Thompson" <mattwthompson@protonmail.com>
Date: Sun, 8 Nov 2026 15:43:49 -0600
Subject: [PATCH 09/18] Drop GPU action for now

---
 .github/workflows/gpu.yaml | 92 --------------------------------------
 1 file changed, 92 deletions(-)
 delete mode 100644 .github/workflows/gpu.yaml

diff --git a/.github/workflows/gpu.yaml b/.github/workflows/gpu.yaml
deleted file mode 100644
index 72dd9ce..0000000
--- a/.github/workflows/gpu.yaml
+++ /dev/null
@@ -1,92 +0,0 @@
-name: GPU-enabled CI
-on:
-  workflow_dispatch:
-  pull_request:
-    branches:
-      - "main"
-
-concurrency:
-  # Specific group naming so CI is only cancelled
-  # within same PR or on merge to main
-  group: ${{ github.ref }}-${{ github.head_ref }}-${{ github.workflow }}
-  cancel-in-progress: true
-
-defaults:
-  run:
-    shell: bash -l {0}
-
-env:
-  OE_LICENSE: ${{ github.workspace }}/oe_license.txt
-
-jobs:
-  start-aws-runner:
-    runs-on: ubuntu-latest
-    permissions:
-      id-token: write
-      contents: read
-    outputs:
-      mapping: ${{ steps.aws-start.outputs.mapping }}
-    steps:
-      - name: Configure AWS credentials
-        uses: aws-actions/configure-aws-credentials@v6
-        with:
-          role-to-assume: arn:aws:iam::649715411074:role/gh-actions-runner-role
-          aws-region: us-east-1
-      - name: Create cloud runner
-        id: aws-start
-        uses: omsf/start-aws-gha-runner@v1.3.0
-        with:
-          aws_image_id: ami-0d5079d9be06933e5
-          aws_instance_type: g4dn.xlarge
-          # IAM default might be 5 GB?
-          aws_root_device_size: 125
-          aws_region_name: us-east-1
-          aws_home_dir: /home/ubuntu
-        env:
-          GH_PAT: ${{ secrets.GH_PAT }}
-  self-hosted-test:
-    name: GPU-based tests (env ${{ matrix.environment }})
-    runs-on: self-hosted
-    strategy:
-        fail-fast: true
-        matrix:
-          environment:
-            - hpc3  # re-using an otherwise generic CUDA environment
-    needs:
-      - start-aws-runner
-    steps:
-      - uses: actions/checkout@v7
-        with:
-          fetch-depth: 0
-
-      - name: Set up virtual environment
-        uses: prefix-dev/setup-pixi@v0.11.3
-        with:
-          environments: ${{ matrix.environment }}
-          frozen: true
-
-      - name: Run GPU-based tests
-        run: pixi run -e ${{ matrix.environment }} run_gpu_tests
-
-  stop-aws-runner:
-    runs-on: ubuntu-latest
-    permissions:
-        id-token: write
-        contents: read
-    needs:
-      - start-aws-runner
-      - self-hosted-test
-    if: ${{ always() }}
-    steps:
-      - name: Configure AWS credentials
-        uses: aws-actions/configure-aws-credentials@v6
-        with:
-          role-to-assume: arn:aws:iam::649715411074:role/gh-actions-runner-role
-          aws-region: us-east-1
-      - name: Stop instances
-        uses: omsf/stop-aws-gha-runner@v1.0.0
-        with:
-          instance_mapping: ${{ needs.start-aws-runner.outputs.mapping }}
-          aws_region_name: us-east-1
-        env:
-          GH_PAT: ${{ secrets.GH_PAT }}

From edf676d740c66aa84151328daa4b584e7bf4defd Mon Sep 17 00:00:00 2001
From: "Matthew W. Thompson" <mattwthompson@protonmail.com>
Date: Mon, 9 Nov 2026 20:05:20 -0600
Subject: [PATCH 10/18] Add dhvap calculations with tensor machinery

---
 examples/mvp/run.py                           |   7 +-
 pixi.lock                                     | 586 ++++++------------
 pixi.toml                                     |   2 +-
 .../compute/test_workflow.py                  | 106 ++--
 tyff/compute/_equilibrate.py                  |   2 +
 tyff/compute/_minimize.py                     |  11 +-
 tyff/compute/_openmm.py                       |  28 +
 tyff/compute/_produce.py                      |   8 +-
 tyff/compute/workflow.py                      |  46 +-
 tyff/targets/new_thermo.py                    | 126 +++-
 10 files changed, 445 insertions(+), 477 deletions(-)
 create mode 100644 tyff/compute/_openmm.py

diff --git a/examples/mvp/run.py b/examples/mvp/run.py
index 04a18df..4ad75b0 100644
--- a/examples/mvp/run.py
+++ b/examples/mvp/run.py
@@ -43,9 +43,6 @@ def load_datasets(root: Path) -> tuple[Dataset, Dataset]:
     thermo_data = Dataset.load_from_disk(root / "data/thermo")
     energy_data = Dataset.load_from_disk(root / "data/energy")
 
-    # temporary - need to go back and add dhmix, dhvap, etc.
-    thermo_data = thermo_data.filter(lambda x: x["tag"] == "density")
-
     logger.info(f"Loaded {len(thermo_data)} thermo entries and {len(energy_data)} energy entries")
 
     return thermo_data, energy_data
@@ -102,7 +99,7 @@ def main(root: Path) -> None:
 
         # no return value?
         simulate(
-            force_field=current_ff,
+            tensor_force_field=current_ff,
             epoch_dir=root / f"EPOCH_{epoch}",
             thermo_data=thermo_data,
             smirnoff_force_field=INITIAL_FORCE_FIELD,
@@ -112,7 +109,7 @@ def main(root: Path) -> None:
 
         y_ref, _y_ref_std, y_pred, _y_pred_std = predict(
             dataset=thermo_data,
-            force_field=current_ff,
+            tensor_force_field=current_ff,
             epoch_dir=root / f"EPOCH_{epoch}",
         )
 
diff --git a/pixi.lock b/pixi.lock
index 36e280a..e5a7c7a 100644
--- a/pixi.lock
+++ b/pixi.lock
@@ -2,13 +2,13 @@ version: 7
 platforms:
 - name: linux-64
   virtual-packages:
-  - __unix=0=0
+  - __unix=0
   - __linux=4.18
   - __glibc=2.28
   - __archspec=0=x86_64
 - name: osx-arm64
   virtual-packages:
-  - __unix=0=0
+  - __unix=0
   - __osx=13.0
   - __archspec=0=m1
 environments:
@@ -107,7 +107,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-16.2.0-h69a702a_7.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libgfortran-16.2.0-h69a702a_7.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libgfortran5-16.2.0-h6b99dfc_7.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libglib-2.90.0-h569388d_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libglib-2.90.1-h569388d_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libgoogle-cloud-3.3.0-h25dbb67_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libgoogle-cloud-storage-3.3.0-hdbdcf42_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libgrpc-1.78.2-hc7adcc0_0.conda
@@ -125,7 +125,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libopentelemetry-cpp-headers-1.26.0-ha770c72_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libparquet-20.0.0-h7376487_44_cpu.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libpng-1.6.59-h922cc85_0.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libpq-18.6-h3883810_3.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libpq-18.6-h3883810_4.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libprotobuf-6.33.5-h538a264_2.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libpsl-0.23.1-hd9e3e90_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libpython-3.13.18-hd51c5da_100_cp313.conda
@@ -143,7 +143,7 @@ environments:
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libuuid-2.42.4-hcfc3c73_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libuv-1.52.1-h280c20c_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libwebp-base-1.6.0-hd42ef1d_1.conda
-      - conda: https://conda.anaconda.org/conda-forge/linux-64/libxcb-1.17.0-hb83e432_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libxcb-1.17.0-hb83e432_3.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libxcrypt-4.4.38-h280c20c_0.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libxml2-16-2.15.4-hf3af7cc_1.conda
       - conda: https://conda.anaconda.org/conda-forge/linux-64/libxml2-2.15.4-h7df9aa5_1.conda
@@ -365,6 +365,7 @@ environments:
       - pypi: https://files.pythonhosted.org/packages/2c/62/e4721d8b8b9de685323717489a408521067a786cabc2b73ccd91aa9b9077/pyzmq-27.3.0-cp312-abi3-manylinux_2_26_x86_64.manylinux_2_28_x86_64.whl
       - pypi: https://files.pythonhosted.org/packages/2c/f7/021d590d52c1ac28e3290311776854c6a1c927fa3fb4b25ce74caf937a3d/mistune-3.4.0-py3-none-any.whl
       - pypi: https://files.pythonhosted.org/packages/2e/66/25cbb926e981a849d1cfcd36817fba6bfa5e9b6a2944c41230fe83ff25d2/jsonpointer-3.10-py3-none-any.whl
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/hdf5-2.1.0-nompi_hd4fcb43_104.conda
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/libglib-2.90.0-h569388d_0.conda
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-  md5: c85e9539551f1fd21104e518d940c244
+- conda: https://conda.anaconda.org/conda-forge/linux-64/libglib-2.90.1-h569388d_1.conda
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+  - libiconv >=1.18,<2.0a0
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+    - libglib >=2.90.1,<3.0a0
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/libnetcdf-4.10.0-nompi_he3e3c8e_205.conda
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/libpq-18.6-h3883810_3.conda
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+- conda: https://conda.anaconda.org/conda-forge/linux-64/libpq-18.6-h3883810_4.conda
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   - libstdcxx >=15
   - openldap >=2.6.13,<2.7.0a0
-  - openssl >=3.5.8,<4.0a0
+  - openssl >=3.5.9,<4.0a0
   license: PostgreSQL
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-  size: 2720456
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 - conda: https://conda.anaconda.org/conda-forge/linux-64/libprotobuf-6.31.1-hfb7daa7_5.conda
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/libxcb-1.17.0-hb83e432_2.conda
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-  md5: 61f0ffba9161cbb3a77722869b21e4bb
+- conda: https://conda.anaconda.org/conda-forge/linux-64/libxcb-1.17.0-hb83e432_3.conda
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-  size: 395120
-  timestamp: 1787885788278
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/netcdf4-1.7.4-nompi_py311h498b1eb_108.conda
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   noarch: python
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/pymol-open-source-3.1.0-py312h01792ee_8.conda
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-  md5: 80bbe43019e5cc74a03fc6983755dbb3
+- conda: https://conda.anaconda.org/conda-forge/linux-64/pymol-open-source-3.1.0-py312h49ac392_9.conda
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-  - libnetcdf >=4.10.0,<5.0a0
-  - libpng >=1.6.55,<1.7.0a0
-  - libstdcxx >=14
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+  - libnetcdf >=4.10.1,<5.0a0
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+  - numpy >=1.25,<3
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/pytables-3.11.1-py312h920095a_5.conda
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-- conda: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxxf86vm-1.1.7-hb03c661_0.conda
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+- conda: https://conda.anaconda.org/conda-forge/linux-64/xorg-libxxf86vm-1.1.7-h7cc23a3_1.conda
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-  - libgcc >=14
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+  - libgcc >=15
+  - xorg-libx11 >=1.8.14,<2.0a0
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   license: MIT
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-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libnetcdf-4.10.0-nompi_ha00b61a_205.conda
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-  license: MIT
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-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libxcb-1.17.0-hbffa61f_2.conda
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+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/libxcb-1.17.0-hbffa61f_3.conda
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-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/netcdf4-1.7.4-nompi_py311hfd37af6_108.conda
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-- conda: https://conda.anaconda.org/conda-forge/osx-arm64/pymol-open-source-3.1.0-py312h61dc058_8.conda
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+- conda: https://conda.anaconda.org/conda-forge/osx-arm64/pymol-open-source-3.1.0-py312h6b32e4a_9.conda
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   - pmw
   - pyqt
   - python >=3.12,<3.13.0a0
@@ -18898,8 +18718,8 @@ packages:
   purls:
   - pkg:pypi/pymol?source=hash-mapping
   run_exports: {}
-  size: 6214840
-  timestamp: 1774376549773
+  size: 6217669
+  timestamp: 1794255968614
 - conda: https://conda.anaconda.org/conda-forge/osx-arm64/pyqt-5.15.11-py312h6612b97_2.conda
   sha256: 5f307afa50b143e98344aa53d850d045fc12f788ab8afb02f81ee40dc47cfad8
   md5: 85165b0011b3f9dbe9af0a8cc908c027
@@ -19894,13 +19714,6 @@ packages:
   - pytest-jupyter[client]>=0.6.2 ; extra == 'test'
   - pytest-timeout ; extra == 'test'
   requires_python: '>=3.10'
-- pypi: https://files.pythonhosted.org/packages/10/b4/47e939285caad9a623d021512912ac08dc92a467ad075d179f43729d2934/pytest_randomly-5.0.0-py3-none-any.whl
-  name: pytest-randomly
-  version: 5.0.0
-  sha256: 8a0d4703115c0c25b38b6e129fc16b1947b9643ff26a41bc1d185d7e5a7689c1
-  requires_dist:
-  - pytest>=8
-  requires_python: '>=3.10'
 - pypi: https://files.pythonhosted.org/packages/10/cb/f2ad4230dc2eb1a74edf38f1a38b9b52277f75bef262d8908e60d957e13c/blinker-1.9.0-py3-none-any.whl
   name: blinker
   version: 1.9.0
@@ -20265,6 +20078,80 @@ packages:
   version: 7.36.2
   sha256: cbc70b17ee27e28894c7fee8bb04be1abead49e936bc70eb60052531eee2079e
   requires_python: '>=3.10'
+- pypi: https://files.pythonhosted.org/packages/32/85/a852e65a9ccb5ad88a289669bd303cec3d2ddb99f271b02c7add06a2b2b6/parsl-2026.11.9-py3-none-any.whl
+  name: parsl
+  version: 2026.11.9
+  sha256: 90c9f2ce67e25ac7b4b56af98ade6d4ffc55d5eed50373cd12723d6acbb7c1dd
+  requires_dist:
+  - pyzmq>=17.1.2
+  - typeguard>=4,<5
+  - typing-extensions>=4.6,<5
+  - dill
+  - tblib
+  - requests
+  - sortedcontainers
+  - psutil>=5.5.1
+  - setproctitle
+  - filelock>=3.13,<5
+  - sqlalchemy>=2,<2.1 ; extra == 'monitoring'
+  - pydot>=1.4.2 ; extra == 'visualization'
+  - networkx>=3.2,<3.3 ; extra == 'visualization'
+  - flask>=1.0.2 ; extra == 'visualization'
+  - flask-sqlalchemy ; extra == 'visualization'
+  - pandas>=2.2,<3 ; extra == 'visualization'
+  - plotly>=5.19,<7 ; extra == 'visualization'
+  - python-daemon ; extra == 'visualization'
+  - boto3 ; extra == 'aws'
+  - kubernetes ; extra == 'kubernetes'
+  - ipython<=8.6.0 ; extra == 'docs'
+  - nbsphinx ; extra == 'docs'
+  - sphinx>=7.4,<8 ; extra == 'docs'
+  - sphinx-rtd-theme ; extra == 'docs'
+  - google-auth ; extra == 'google-cloud'
+  - google-api-python-client ; extra == 'google-cloud'
+  - python-gssapi ; extra == 'gssapi'
+  - azure<=4 ; extra == 'azure'
+  - msrestazure ; extra == 'azure'
+  - work-queue ; extra == 'workqueue'
+  - pyyaml ; extra == 'flux'
+  - cffi ; extra == 'flux'
+  - jsonschema ; extra == 'flux'
+  - ensemble-launcher[hpc] ; extra == 'ensemble'
+  - proxystore ; extra == 'proxystore'
+  - radical-pilot==1.90 ; extra == 'radical-pilot'
+  - radical-utils==1.90 ; extra == 'radical-pilot'
+  - globus-compute-sdk>=2.34.0 ; extra == 'globus-compute'
+  - globus-sdk ; extra == 'globus-transfer'
+  - sqlalchemy>=2,<2.1 ; extra == 'all'
+  - pydot>=1.4.2 ; extra == 'all'
+  - networkx>=3.2,<3.3 ; extra == 'all'
+  - flask>=1.0.2 ; extra == 'all'
+  - flask-sqlalchemy ; extra == 'all'
+  - pandas>=2.2,<3 ; extra == 'all'
+  - plotly>=5.19,<7 ; extra == 'all'
+  - python-daemon ; extra == 'all'
+  - boto3 ; extra == 'all'
+  - kubernetes ; extra == 'all'
+  - ipython<=8.6.0 ; extra == 'all'
+  - nbsphinx ; extra == 'all'
+  - sphinx>=7.4,<8 ; extra == 'all'
+  - sphinx-rtd-theme ; extra == 'all'
+  - google-auth ; extra == 'all'
+  - google-api-python-client ; extra == 'all'
+  - python-gssapi ; extra == 'all'
+  - azure<=4 ; extra == 'all'
+  - msrestazure ; extra == 'all'
+  - work-queue ; extra == 'all'
+  - pyyaml ; extra == 'all'
+  - cffi ; extra == 'all'
+  - jsonschema ; extra == 'all'
+  - ensemble-launcher[hpc] ; extra == 'all'
+  - proxystore ; extra == 'all'
+  - radical-pilot==1.90 ; extra == 'all'
+  - radical-utils==1.90 ; extra == 'all'
+  - globus-compute-sdk>=2.34.0 ; extra == 'all'
+  - globus-sdk ; extra == 'all'
+  requires_python: '>=3.10.0'
 - pypi: https://files.pythonhosted.org/packages/33/ef/6d27fc118f58cb24886da413545a7efb0853d405fddbfd8b2d9ac09fbed4/jupyterlab_widgets-3.0.17-py3-none-any.whl
   name: jupyterlab-widgets
   version: 3.0.17
@@ -20567,6 +20454,13 @@ packages:
   version: 0.13.1
   sha256: 1b158f1c9e3a0d386913924c57995d6df78224868a4d0f215bdd41587c97b34a
   requires_python: '>=3.7'
+- pypi: https://files.pythonhosted.org/packages/67/ef/9979eae8db530930873d15fb16043ef6d72b5042f2636de4d85568eb3df4/pytest_randomly-5.1.0-py3-none-any.whl
+  name: pytest-randomly
+  version: 5.1.0
+  sha256: fb9004e6821422291087d0294fd62f45ff304094db11fbdff8f2fe1ed20764d8
+  requires_dist:
+  - pytest>=8
+  requires_python: '>=3.11'
 - pypi: https://files.pythonhosted.org/packages/69/90/f63fb5873511e014207a475e2bb4e8b2e570d655b00ac19a9a0ca0a385ee/jsonschema-4.26.0-py3-none-any.whl
   name: jsonschema
   version: 4.26.0
@@ -21468,78 +21362,6 @@ packages:
   - pytest-cache ; extra == 'devel'
   - validictory ; extra == 'devel'
   requires_python: '>=3.10'
-- pypi: https://files.pythonhosted.org/packages/d9/0e/7cd8f39c2c342d6f1037b7045cf41fe15b3558bad5497ff51ba1734df64b/parsl-2026.11.2-py3-none-any.whl
-  name: parsl
-  version: 2026.11.2
-  sha256: 347144b4360e6e633cd91e0f33914ff38ea5648d1b559d8d61a0a16698ac9c5e
-  requires_dist:
-  - pyzmq>=17.1.2
-  - typeguard>=4,<5
-  - typing-extensions>=4.6,<5
-  - dill
-  - tblib
-  - requests
-  - sortedcontainers
-  - psutil>=5.5.1
-  - setproctitle
-  - filelock>=3.13,<5
-  - sqlalchemy>=2,<2.1 ; extra == 'monitoring'
-  - pydot>=1.4.2 ; extra == 'visualization'
-  - networkx>=3.2,<3.3 ; extra == 'visualization'
-  - flask>=1.0.2 ; extra == 'visualization'
-  - flask-sqlalchemy ; extra == 'visualization'
-  - pandas>=2.2,<3 ; extra == 'visualization'
-  - plotly>=5.19,<7 ; extra == 'visualization'
-  - python-daemon ; extra == 'visualization'
-  - boto3 ; extra == 'aws'
-  - kubernetes ; extra == 'kubernetes'
-  - ipython<=8.6.0 ; extra == 'docs'
-  - nbsphinx ; extra == 'docs'
-  - sphinx>=7.4,<8 ; extra == 'docs'
-  - sphinx-rtd-theme ; extra == 'docs'
-  - google-auth ; extra == 'google-cloud'
-  - google-api-python-client ; extra == 'google-cloud'
-  - python-gssapi ; extra == 'gssapi'
-  - azure<=4 ; extra == 'azure'
-  - msrestazure ; extra == 'azure'
-  - work-queue ; extra == 'workqueue'
-  - pyyaml ; extra == 'flux'
-  - cffi ; extra == 'flux'
-  - jsonschema ; extra == 'flux'
-  - proxystore ; extra == 'proxystore'
-  - radical-pilot==1.90 ; extra == 'radical-pilot'
-  - radical-utils==1.90 ; extra == 'radical-pilot'
-  - globus-compute-sdk>=2.34.0 ; extra == 'globus-compute'
-  - globus-sdk ; extra == 'globus-transfer'
-  - sqlalchemy>=2,<2.1 ; extra == 'all'
-  - pydot>=1.4.2 ; extra == 'all'
-  - networkx>=3.2,<3.3 ; extra == 'all'
-  - flask>=1.0.2 ; extra == 'all'
-  - flask-sqlalchemy ; extra == 'all'
-  - pandas>=2.2,<3 ; extra == 'all'
-  - plotly>=5.19,<7 ; extra == 'all'
-  - python-daemon ; extra == 'all'
-  - boto3 ; extra == 'all'
-  - kubernetes ; extra == 'all'
-  - ipython<=8.6.0 ; extra == 'all'
-  - nbsphinx ; extra == 'all'
-  - sphinx>=7.4,<8 ; extra == 'all'
-  - sphinx-rtd-theme ; extra == 'all'
-  - google-auth ; extra == 'all'
-  - google-api-python-client ; extra == 'all'
-  - python-gssapi ; extra == 'all'
-  - azure<=4 ; extra == 'all'
-  - msrestazure ; extra == 'all'
-  - work-queue ; extra == 'all'
-  - pyyaml ; extra == 'all'
-  - cffi ; extra == 'all'
-  - jsonschema ; extra == 'all'
-  - proxystore ; extra == 'all'
-  - radical-pilot==1.90 ; extra == 'all'
-  - radical-utils==1.90 ; extra == 'all'
-  - globus-compute-sdk>=2.34.0 ; extra == 'all'
-  - globus-sdk ; extra == 'all'
-  requires_python: '>=3.10.0'
 - pypi: https://files.pythonhosted.org/packages/d9/0f/90088510d4758e0ee475ae1fc7f96e7bccd0e31f24107567075482b2fe9e/rdkit_stubs-0.8-py3-none-any.whl
   name: rdkit-stubs
   version: '0.8'
diff --git a/pixi.toml b/pixi.toml
index 7de913a..643c62c 100644
--- a/pixi.toml
+++ b/pixi.toml
@@ -7,7 +7,7 @@ platforms = ["linux-64", "osx-arm64"]
 run_mvp = "python examples/mvp/run.py"
 run_mypy = "python -m mypy -p 'tyff'"
 run_tests = { cmd = "python -m pytest -n logical tyff/_tests", env = { OPENMM_DEFAULT_PLATFORM = "CPU" } }
-run_gpu_tests = { cmd = "python -m pytest -n 1 --run-gpu -m gpu tyff/_tests --color=no", env = { OPENMM_DEFAULT_PLATFORM = "GPU" } }
+run_gpu_tests = { cmd = "python -m pytest -n 1 --run-gpu -m gpu tyff/_tests --color=no", env = { OPENMM_DEFAULT_PLATFORM = "OpenCL" } }
 dev_tests = { cmd = "python -m pytest -s -x --pdb --lf tyff/_tests", env = { OPENMM_DEFAULT_PLATFORM = "CPU" } }
 
 [dependencies]
diff --git a/tyff/_tests/integration_tests/compute/test_workflow.py b/tyff/_tests/integration_tests/compute/test_workflow.py
index a6a78a4..9600bc3 100644
--- a/tyff/_tests/integration_tests/compute/test_workflow.py
+++ b/tyff/_tests/integration_tests/compute/test_workflow.py
@@ -1,67 +1,57 @@
-import json
-
+import openff.toolkit
 import pytest
 
-from tyff.compute.configs import local_config
-from tyff.compute.workflow import SimulationWorkflow
+from tyff.converters.openff import topologies_for
+from tyff.targets.new_thermo import predict, simulate
 from tyff.targets.thermo import create_dataset
 
-
-@pytest.mark.gpu
-def test_nonstandard_pressure(tmp_path):
-
-    dataset = create_dataset(
-        *[
-            {  # type: ignore
-                "id": "high_pressure_water",
-                "tag": "density",
-                "x": [1.0],
-                "smiles": ["O"],
-                "temperature": 298.15,
-                "pressure": val,
-                "value": 1.0,
-                "std": 0.01,
-                "units": "g/mL",
-                "source": "test_source",
-            }
-            for val in [101.325, 101325]
-        ]
-    )
-
-    with SimulationWorkflow(
-        base_dir=tmp_path,
-        parsl_config=local_config(),
-    ) as workflow:
-        workflow.submit_dataset(
-            dataset,
-            force_field="openff-2.3.0.offxml",
-            n_molecules=480,
-            n_replicates=1,
+# this variable is magically detected by pytest, important that it is defined at module level
+pytestmark = pytest.mark.gpu
+
+
+class TestEnthalpyOfVaporization:
+    def test_enthalpy_of_vaporization(self, tmp_path):
+
+        dataset = create_dataset(
+            *[
+                {  # type: ignore
+                    "id": "methanol",
+                    "tag": "enthalpy_of_vaporization",
+                    "x": [1.0],
+                    "smiles": ["CO"],
+                    "temperature": 300.0,
+                    "pressure": 101.325,
+                    "value": 1.0,
+                    "std": 0.01,
+                    "units": "kJ/mol",
+                    "source": "test_source",
+                }
+            ]
         )
 
-        workflow.wait()
-
-        # hack - there needs to be a better way of grabbing results
-        job_dirs = [
-            path
-            for path in (tmp_path).glob("*/")
-            if not path.match("thermo_targets")
-            and not path.match("reference_force_fields")
-            and not path.match("interchanges")
-        ]
-
-        results = dict()
-
-        for job_dir in job_dirs:
-            with open(job_dir / "compute_config.json") as f:
-                compute_config = json.load(f)
-                target_pressure = compute_config["pressure"]
-
-                assert compute_config["temperature"] == 298.15
+        # I could be forgetting a cleaner way of going from SMIRNOFF + set[SMILES] -> TensorForceField,
+        # but this is clean enough
+        _topologies, tensor_force_field = topologies_for(
+            smiles_set={smiles for smiles_list in dataset["smiles"] for smiles in smiles_list},
+            smirnoff_force_field=openff.toolkit.ForceField("openff-2.3.0.offxml"),
+        )
 
-            with open(job_dir / "ensemble_averages.json") as f:
-                density = json.load(f)["density"]
+        simulate(
+            tensor_force_field=tensor_force_field,
+            epoch_dir=tmp_path,
+            thermo_data=dataset,
+            smirnoff_force_field="openff-2.3.0.offxml",
+            n_replicates=3,
+            n_molecules=360,
+        )
 
-            results[target_pressure] = density
+        _y_ref, _y_ref_std, _y_pred, _y_pred_std = predict(
+            dataset=dataset,
+            tensor_force_field=tensor_force_field,
+            epoch_dir=tmp_path,
+        )
 
-        assert results[101325.0] > results[101.325]
+        # ipdb> _y_ref, _y_ref_std, _y_pred, _y_pred_std
+        # (tensor([1.]), tensor([0.0100]), tensor([-67.6932],
+        #   dtype=torch.float64), tensor([0.8197], dtype=torch.float64)
+        # )
diff --git a/tyff/compute/_equilibrate.py b/tyff/compute/_equilibrate.py
index 58f42c8..6c7050a 100644
--- a/tyff/compute/_equilibrate.py
+++ b/tyff/compute/_equilibrate.py
@@ -10,6 +10,7 @@
     EquilibrationFiles,
     MinimizationFiles,
 )
+from tyff.compute._openmm import _get_platform
 from tyff.configs.liquid import BulkLiquid
 from tyff.exceptions import PressureNotDefinedError
 
@@ -71,6 +72,7 @@ def _run_equilibration(
         topology,
         system,
         integrator,
+        platform=_get_platform(logger),
     )
 
     try:
diff --git a/tyff/compute/_minimize.py b/tyff/compute/_minimize.py
index 201f2db..70a2812 100644
--- a/tyff/compute/_minimize.py
+++ b/tyff/compute/_minimize.py
@@ -6,6 +6,7 @@
 from parsl import File
 
 from tyff.compute._files import MinimizationFiles, PreparingFiles
+from tyff.compute._openmm import _get_platform
 from tyff.configs.liquid import BulkLiquid
 
 
@@ -56,14 +57,6 @@ def _minimize_energy(
         unique_molecules=molecules,
     )
 
-    try:
-        platform = openmm.Platform.getPlatformByName("CUDA")
-        logger.info("Trying to use CUDA platform ...")
-    except (openmm.OpenMMException, Exception) as error:
-        platform = openmm.Platform.getPlatformByName("CPU")
-        logger.info(f"Could not use CUDA platform because {error}")
-        logger.info("Trying to use CPU platform ...")
-
     simulation = openmm.app.Simulation(
         topology=topology.to_openmm(),
         system=system,
@@ -72,7 +65,7 @@ def _minimize_energy(
             1.0 / openmm.unit.picosecond,
             1.0 * openmm.unit.femtoseconds,  # TODO: This should be user input
         ),
-        platform=platform,
+        platform=_get_platform(logger),
     )
 
     simulation.context.setPositions(topology.get_positions().to_openmm())
diff --git a/tyff/compute/_openmm.py b/tyff/compute/_openmm.py
new file mode 100644
index 0000000..030228b
--- /dev/null
+++ b/tyff/compute/_openmm.py
@@ -0,0 +1,28 @@
+from __future__ import annotations
+
+import logging
+
+import openmm
+
+
+def _get_platform(logger: logging.Logger) -> openmm.Platform:
+    """
+    Get the OpenMM platform to use for minimization.
+
+    Returns
+    -------
+    openmm.Platform
+        The OpenMM platform to use for minimization.
+    """
+
+    for platform_name in ["CUDA", "OpenCL", "CPU"]:
+        try:
+            logger.info(f"Trying to use {platform_name} platform ...")
+            platform = openmm.Platform.getPlatformByName(platform_name)
+        except openmm.OpenMMException as error:
+            logger.info(f"Could not use {platform_name} platform because {error}")
+            continue
+
+        logger.info(f"Successfully requested platform {platform.getName()}")
+
+        return platform
diff --git a/tyff/compute/_produce.py b/tyff/compute/_produce.py
index a69986e..8666583 100644
--- a/tyff/compute/_produce.py
+++ b/tyff/compute/_produce.py
@@ -12,6 +12,7 @@
     EquilibrationFiles,
     ProductionFiles,
 )
+from tyff.compute._openmm import _get_platform
 from tyff.configs.liquid import BulkLiquid
 from tyff.exceptions import PressureNotDefinedError
 
@@ -67,6 +68,7 @@ def _run_production(
         topology,
         system,
         integrator,
+        platform=_get_platform(logger),
     )
 
     try:
@@ -144,11 +146,9 @@ def _run_production(
 
     logger.info("Running 100,000 steps of MD")
 
-    platform = simulation.context.getPlatform()
-    platform_name = platform.getName()
+    detected_platform = simulation.context.getPlatform().getName()
 
-    # Log or print the result
-    logger.info(f"Using OpenMM platform: {platform_name}")
+    logger.info(f"Using OpenMM platform: {detected_platform}")
 
     for index in range(10):
         logger.info(f"Running from step {index * 10_000} to step {(index + 1) * 10_000}")
diff --git a/tyff/compute/workflow.py b/tyff/compute/workflow.py
index 40175dd..57e2c1c 100644
--- a/tyff/compute/workflow.py
+++ b/tyff/compute/workflow.py
@@ -62,7 +62,19 @@ def __init__(self, base_dir: str, parsl_config: parsl.Config):
                     self._target_compute_mapping = loaded_mapping
         else:
             # initialize to empty dict otherwise
-            self._target_compute_mapping: dict[tuple[str, str, int, int], list[tuple[str, ...]]] = dict()
+            self._target_compute_mapping: dict[
+                tuple[
+                    str,  # target id
+                    str,  # target tag
+                    str,  # force field path
+                    int,  # n_molecules
+                    int,  # n_replicates
+                ],
+                list[  # len n_replicates
+                    # each job_dir in this replicate, i.e. 1 for density, 2 for dhvap, 3 for dhmix, etc.
+                    tuple[str, ...]
+                ],
+            ] = dict()
 
         # futures submitted via submit_target/submit_target_batch that haven't
         # been waited on yet; drained by wait()
@@ -136,6 +148,7 @@ def submit_target(
         self._target_compute_mapping[
             (
                 target_config["id"],  # this is unmodified from input data and therefore could look funky
+                target_config["tag"],  # this is unmodified from input data and therefore could look funky
                 force_field,
                 n_molecules,
                 n_replicates,
@@ -145,6 +158,7 @@ def submit_target(
             self._target_compute_mapping[
                 (
                     target_config["id"],
+                    target_config["tag"],
                     force_field,
                     n_molecules,
                     n_replicates,
@@ -244,7 +258,15 @@ def estimate_target(
         if target_config["tag"] == "density":
             # pull job ids for all replicates of this target/force field/n_molecules combination
             # TODO: other querying into jobs i.e. given a target and force field but any n_molecules
-            job_ids = self._target_compute_mapping[(target_config["id"], force_field, n_molecules, n_replicates)]
+            job_ids = self._target_compute_mapping[
+                (
+                    target_config["id"],
+                    target_config["tag"],
+                    force_field,
+                    n_molecules,
+                    n_replicates,
+                )
+            ]
 
             density_futures = [
                 run_density_analysis(
@@ -265,7 +287,15 @@ def estimate_target(
         elif target_config["tag"] == "enthalpy_of_vaporization":
             # pull job ids for all replicates of this target/force field/n_molecules combination
             # TODO: other querying into jobs i.e. given a target and force field but any n_molecules
-            job_ids = self._target_compute_mapping[(target_config["id"], force_field, n_molecules, n_replicates)]
+            job_ids = self._target_compute_mapping[
+                (
+                    target_config["id"],
+                    target_config["tag"],
+                    force_field,
+                    n_molecules,
+                    n_replicates,
+                )
+            ]
 
             dhvap_futures = [
                 # this function should separate the two job ids into gas and liquid,
@@ -288,6 +318,16 @@ def estimate_target(
         else:
             raise ValueError(f"Unknown target tag {target_config['tag']}")
 
+    def estimate_dataset(
+        self,
+        dataset: datasets.Dataset,  # should be something that unpacks to DataEntry on iteration
+        tensor_force_field: tyff.TensorForceField,
+        force_field: str,
+        n_molecules: int,
+        n_replicates: int = 3,
+    ):
+        raise NotImplementedError()
+
     def run(self, compute_configs: Sequence[BaseComputeConfig]):
         """Submit a batch and block until all complete."""
         pending = self._submit_compute_batch(compute_configs)
diff --git a/tyff/targets/new_thermo.py b/tyff/targets/new_thermo.py
index f2b3056..f00df05 100644
--- a/tyff/targets/new_thermo.py
+++ b/tyff/targets/new_thermo.py
@@ -4,6 +4,7 @@
 import torch
 from datasets import Dataset
 from openff.toolkit import ForceField
+from openff.units import unit
 
 import tyff
 import tyff.converters
@@ -16,7 +17,7 @@
 
 
 def simulate(
-    force_field: tyff.TensorForceField,
+    tensor_force_field: tyff.TensorForceField,
     epoch_dir: Path,
     thermo_data: Dataset,
     smirnoff_force_field: str,
@@ -30,14 +31,14 @@ def simulate(
 
     Parameters
     ----------
-    force_field : tyff.TensorForceField
-        The force field to be used in the simulation.
+    tensor_force_field : tyff.TensorForceField
+        The (tensor) force field to be used in the simulation.
     epoch_dir : Path
         The directory for this epoch where simulation results will be stored.
     thermo_data : Dataset
         The dataset containing thermodynamic data for the simulation.
     smirnoff_force_field : str
-        The path to the original SMIRNOFF force field corresponding to the tensor force field.
+        The path to the original (SMIRNOFF) force field corresponding to the tensor force field.
     n_molecules : int
         The number of molecules to simulate.
     n_replicates : int
@@ -51,7 +52,7 @@ def simulate(
     # write out this epoch's (tensor) force field as a SMIRNOFF force field
     current_smirnoff_force_field = convert_tensor_force_field(
         original_force_field=ForceField(smirnoff_force_field),
-        tensor_force_field=force_field,
+        tensor_force_field=tensor_force_field,
     )
 
     epoch_dir.mkdir(exist_ok=True)
@@ -65,7 +66,7 @@ def simulate(
     ) as workflow:
         workflow.submit_dataset(
             dataset=thermo_data,
-            tensor_force_field=force_field,
+            tensor_force_field=tensor_force_field,
             force_field=smirnoff_force_field_file,  # possibly smoother to pass through openff.toolkit.ForceField
             n_molecules=n_molecules,
             n_replicates=n_replicates,
@@ -83,6 +84,15 @@ def load_remote_observables(
     Load observables and attach to graph.
 
     Returns a mapping between job IDs and associated observables.
+
+    Parameters
+    ----------
+    force_field_per_epoch : tyff.TensorForceField
+        The tensor force field used for the simulations.
+    base_dir : Path
+        The base directory where simulation results are stored.
+    job_ids : list[str]
+        A 1-D list of job IDs corresponding to the simulations.
     """
     from tyff.mm._ops import _pack_force_field
 
@@ -132,13 +142,14 @@ def compute_properties(
     with open(epoch_dir / "simulations" / "target_job_map.json") as f:
         target_compute_mapping = {tuple(k): v for k, v in json.load(f)}
 
+    # TODO: Wrap this all up into SimulationWorkflow.estimate_dataset
     for entry in dataset:  # type: ignore
         entry: DataEntry
         if entry["tag"] == "density":
             # this lookup can be improved, but INITIAL_FORCE_FIELD
             # gets mutated by this point so it's not so straightforward
-            for as_submitted, job_ids in target_compute_mapping.items():
-                if as_submitted[0] == entry["id"]:
+            for (target_id, *_), job_ids in target_compute_mapping.items():
+                if target_id == entry["id"]:
                     break
 
             # this is set with an iteration variable - can we assume that
@@ -169,7 +180,91 @@ def compute_properties(
         elif entry["tag"] == "excess_molar_volume":
             raise NotImplementedError()
         elif entry["tag"] == "enthalpy_of_vaporization":
-            raise NotImplementedError()
+            for (target_id, *_), job_ids in target_compute_mapping.items():
+                if target_id == entry["id"]:
+                    break
+
+            values = list()
+
+            for job_ids_in_this_replicate in job_ids:
+                assert len(job_ids_in_this_replicate) == 2, (
+                    "Enthalpy of vaporization requires two jobs (gas and liquid)"
+                )
+                with (
+                    open(
+                        epoch_dir / "simulations" / job_ids_in_this_replicate[0] / "compute_config.json",
+                    ) as f0,
+                    open(epoch_dir / "simulations" / job_ids_in_this_replicate[1] / "compute_config.json") as f1,
+                ):
+                    compute_config0 = json.load(f0)
+                    compute_config1 = json.load(f1)
+
+                    if compute_config0["tag"] == "liquid" and compute_config1["tag"] == "gas":
+                        liquid_job_id = job_ids_in_this_replicate[0]
+                        liquid_config = compute_config0
+
+                        gas_job_id = job_ids_in_this_replicate[1]
+                        gas_config = compute_config1
+
+                    elif compute_config0["tag"] == "gas" and compute_config1["tag"] == "liquid":
+                        gas_job_id = job_ids_in_this_replicate[0]
+                        gas_config = compute_config0
+
+                        liquid_job_id = job_ids_in_this_replicate[1]
+                        liquid_config = compute_config1
+
+                    else:
+                        raise ValueError(
+                            f"Unexpected conmpute configs with tags {compute_config0['tag']} and "
+                            f"{compute_config1['tag']}"
+                        )
+
+                assert gas_config["temperature"] == liquid_config["temperature"], (
+                    "Gas and liquid temperatures must be the same for dHvap calculation"
+                )
+
+                # these are probably kcal/mol, not kJ
+                enthalpy_gas = observables[gas_job_id]["potential_energy"]
+                enthalpy_liquid = observables[liquid_job_id]["potential_energy"]
+
+                n_molecules = liquid_config["n_molecules"]
+
+                R = (1 * unit.avogadro_number * unit.boltzmann_constant).m_as("kJ/K")
+
+                print(
+                    f"Enthalpy of vaporization calculation: {enthalpy_gas=}, {enthalpy_liquid=}, "
+                    f"{n_molecules=}, {R=}, {gas_config['temperature']=}"
+                )
+
+                # Enthalpy of vaporization calculation:
+                #   enthalpy_gas=tensor(314.2987, dtype=torch.float64),
+                #   enthalpy_liquid=tensor(138130.4375, dtype=torch.float64),
+                #   n_molecules=360,
+                #   R=0.00831446261815324,
+                #   gas_config['temperature']=300.0
+                # Enthalpy of vaporization calculation:
+                #   enthalpy_gas=tensor(311.2487, dtype=torch.float64),
+                #   enthalpy_liquid=tensor(138186.0469, dtype=torch.float64),
+                #   n_molecules=360,
+                #   R=0.00831446261815324,
+                #   gas_config['temperature']=300.0
+                # Enthalpy of vaporization calculation:
+                #   enthalpy_gas=tensor(313.9513, dtype=torch.float64),
+                #   enthalpy_liquid=tensor(138701.0781, dtype=torch.float64),
+                #   n_molecules=360,
+                #   R=0.00831446261815324,
+                #   gas_config['temperature']=300.0
+
+                dhvap = enthalpy_gas - enthalpy_liquid / n_molecules + R * gas_config["temperature"]  # kJ/mol
+
+                values.append(dhvap)
+
+            # assume the types of observables are uniform across all these job IDs
+            types_of_observables = [*observables[job_ids[0][0]].keys()]
+
+            mean: dict[str, torch.Tensor] = {key: torch.stack(values).mean() for key in types_of_observables}
+            std: dict[str, torch.Tensor] = {key: torch.stack(values).std() for key in types_of_observables}
+
         else:
             raise ValueError(f"I do not know what to do with {entry['tag']}")
 
@@ -180,7 +275,7 @@ def compute_properties(
 
 def predict(
     dataset: Dataset,
-    force_field: tyff.TensorForceField,
+    tensor_force_field: tyff.TensorForceField,
     epoch_dir: Path,
 ) -> tuple[torch.Tensor, torch.Tensor, torch.Tensor, torch.Tensor]:
     # in order to get all of the (remote) observables for all simulations run from this
@@ -197,14 +292,15 @@ def predict(
     # and condense down to one value (dhvap) to be reported
     job_ids: list[str] = list()
 
-    for (target_id, _, _, _), these_job_ids in target_compute_mapping.items():
+    for (target_id, _target_tag, _, _, _), these_job_ids in target_compute_mapping.items():
         if target_id in this_datasets_ids:
             job_ids.extend(these_job_ids)
 
-    # see comment above
-    job_ids = [x[0] for x in job_ids]
-
-    attached_observables = load_remote_observables(force_field, epoch_dir, job_ids)
+    attached_observables = load_remote_observables(
+        force_field_per_epoch=tensor_force_field,
+        base_dir=epoch_dir,
+        job_ids=[x for sublist in job_ids for x in sublist],
+    )
 
     means_and_stds: list[tuple[dict[str, torch.Tensor], dict[str, torch.Tensor]]] = compute_properties(
         dataset=dataset,

From 299956ed6aaeab35ab9b151673b126b57d60dfc4 Mon Sep 17 00:00:00 2001
From: "Matthew W. Thompson" <mattwthompson@protonmail.com>
Date: Mon, 9 Nov 2026 20:43:18 -0600
Subject: [PATCH 11/18] Ensure use of kJ/mol

---
 .../compute/test_workflow.py                  | 15 ++++---
 tyff/targets/new_thermo.py                    | 40 +++++++++----------
 2 files changed, 26 insertions(+), 29 deletions(-)

diff --git a/tyff/_tests/integration_tests/compute/test_workflow.py b/tyff/_tests/integration_tests/compute/test_workflow.py
index 9600bc3..93157ea 100644
--- a/tyff/_tests/integration_tests/compute/test_workflow.py
+++ b/tyff/_tests/integration_tests/compute/test_workflow.py
@@ -29,8 +29,7 @@ def test_enthalpy_of_vaporization(self, tmp_path):
             ]
         )
 
-        # I could be forgetting a cleaner way of going from SMIRNOFF + set[SMILES] -> TensorForceField,
-        # but this is clean enough
+        # I could be forgetting a cleaner way of going from SMIRNOFF + set[SMILES] -> TensorForceField
         _topologies, tensor_force_field = topologies_for(
             smiles_set={smiles for smiles_list in dataset["smiles"] for smiles in smiles_list},
             smirnoff_force_field=openff.toolkit.ForceField("openff-2.3.0.offxml"),
@@ -41,8 +40,8 @@ def test_enthalpy_of_vaporization(self, tmp_path):
             epoch_dir=tmp_path,
             thermo_data=dataset,
             smirnoff_force_field="openff-2.3.0.offxml",
-            n_replicates=3,
-            n_molecules=360,
+            n_replicates=2,
+            n_molecules=240,
         )
 
         _y_ref, _y_ref_std, _y_pred, _y_pred_std = predict(
@@ -51,7 +50,7 @@ def test_enthalpy_of_vaporization(self, tmp_path):
             epoch_dir=tmp_path,
         )
 
-        # ipdb> _y_ref, _y_ref_std, _y_pred, _y_pred_std
-        # (tensor([1.]), tensor([0.0100]), tensor([-67.6932],
-        #   dtype=torch.float64), tensor([0.8197], dtype=torch.float64)
-        # )
+        # _y_ref=ttorch.tensor[1.]),
+        # _y_ref_std=tensor([0.0100]),
+        # _y_pred=tensor([-302.6861], dtype=torch.float64),
+        # _y_pred_std=tensor([2.9033], dtype=torch.float64)
diff --git a/tyff/targets/new_thermo.py b/tyff/targets/new_thermo.py
index f00df05..949e168 100644
--- a/tyff/targets/new_thermo.py
+++ b/tyff/targets/new_thermo.py
@@ -223,39 +223,37 @@ def compute_properties(
                     "Gas and liquid temperatures must be the same for dHvap calculation"
                 )
 
-                # these are probably kcal/mol, not kJ
-                enthalpy_gas = observables[gas_job_id]["potential_energy"]
-                enthalpy_liquid = observables[liquid_job_id]["potential_energy"]
+                kcal_to_kJ = 4.184
+
+                # these are stored in kcal/mol, so need to convert
+                gas_energy = observables[gas_job_id]["potential_energy"] * kcal_to_kJ
+                liquid_energy = observables[liquid_job_id]["potential_energy"] * kcal_to_kJ
 
                 n_molecules = liquid_config["n_molecules"]
 
+                # 0.00831446261815324
                 R = (1 * unit.avogadro_number * unit.boltzmann_constant).m_as("kJ/K")
 
                 print(
-                    f"Enthalpy of vaporization calculation: {enthalpy_gas=}, {enthalpy_liquid=}, "
+                    f"Enthalpy of vaporization calculation: {gas_energy=}, {liquid_energy=}, "
                     f"{n_molecules=}, {R=}, {gas_config['temperature']=}"
                 )
 
                 # Enthalpy of vaporization calculation:
-                #   enthalpy_gas=tensor(314.2987, dtype=torch.float64),
-                #   enthalpy_liquid=tensor(138130.4375, dtype=torch.float64),
-                #   n_molecules=360,
-                #   R=0.00831446261815324,
-                #   gas_config['temperature']=300.0
-                # Enthalpy of vaporization calculation:
-                #   enthalpy_gas=tensor(311.2487, dtype=torch.float64),
-                #   enthalpy_liquid=tensor(138186.0469, dtype=torch.float64),
-                #   n_molecules=360,
-                #   R=0.00831446261815324,
-                #   gas_config['temperature']=300.0
+                #     gas_energy=tensor(1308.0884, dtype=torch.float64),
+                #     liquid_energy=tensor(386691.8175, dtype=torch.float64),
+                #     n_molecules=240,
+                #     R=0.00831446261815324,
+                #     gas_config['temperature']=300.0
+                #
                 # Enthalpy of vaporization calculation:
-                #   enthalpy_gas=tensor(313.9513, dtype=torch.float64),
-                #   enthalpy_liquid=tensor(138701.0781, dtype=torch.float64),
-                #   n_molecules=360,
-                #   R=0.00831446261815324,
-                #   gas_config['temperature']=300.0
+                #     gas_energy=tensor(1300.6276, dtype=torch.float64),
+                #     liquid_energy=tensor(385886.6263, dtype=torch.float64),
+                #     n_molecules=240,
+                #     R=0.00831446261815324,
+                #     gas_config['temperature']=300.0
 
-                dhvap = enthalpy_gas - enthalpy_liquid / n_molecules + R * gas_config["temperature"]  # kJ/mol
+                dhvap = gas_energy - liquid_energy / n_molecules + R * gas_config["temperature"]  # kJ/mol
 
                 values.append(dhvap)
 

From eef338027747537632ff93aa6bf38d826d9443aa Mon Sep 17 00:00:00 2001
From: "Matthew W. Thompson" <mattwthompson@protonmail.com>
Date: Tue, 10 Nov 2026 11:06:52 -0600
Subject: [PATCH 12/18] Add enthalpy of mixing machinery

---
 .../compute/test_workflow.py                  | 64 ++++++++++++--
 tyff/compute/_equilibrate.py                  |  5 +-
 tyff/compute/_minimize.py                     |  5 +-
 tyff/compute/_produce.py                      |  5 +-
 tyff/targets/new_thermo.py                    | 88 +++++++++++++++++--
 5 files changed, 151 insertions(+), 16 deletions(-)

diff --git a/tyff/_tests/integration_tests/compute/test_workflow.py b/tyff/_tests/integration_tests/compute/test_workflow.py
index 93157ea..c9d278d 100644
--- a/tyff/_tests/integration_tests/compute/test_workflow.py
+++ b/tyff/_tests/integration_tests/compute/test_workflow.py
@@ -1,5 +1,8 @@
+from pathlib import Path
+
 import openff.toolkit
 import pytest
+import torch
 
 from tyff.converters.openff import topologies_for
 from tyff.targets.new_thermo import predict, simulate
@@ -8,6 +11,10 @@
 # this variable is magically detected by pytest, important that it is defined at module level
 pytestmark = pytest.mark.gpu
 
+# turn on to store simulation results in local path for debugging/iteration, otherwise (as in CI)
+# let pytest start everything fresh in a temporary directory
+USE_LOCAL_FILES = False
+
 
 class TestEnthalpyOfVaporization:
     def test_enthalpy_of_vaporization(self, tmp_path):
@@ -37,20 +44,63 @@ def test_enthalpy_of_vaporization(self, tmp_path):
 
         simulate(
             tensor_force_field=tensor_force_field,
-            epoch_dir=tmp_path,
+            epoch_dir=Path("vaporization") if USE_LOCAL_FILES else tmp_path,
             thermo_data=dataset,
             smirnoff_force_field="openff-2.3.0.offxml",
             n_replicates=2,
             n_molecules=240,
         )
 
-        _y_ref, _y_ref_std, _y_pred, _y_pred_std = predict(
+        y_ref, y_ref_std, y_pred, y_pred_std = predict(
             dataset=dataset,
             tensor_force_field=tensor_force_field,
-            epoch_dir=tmp_path,
+            epoch_dir=Path("vaporization") if USE_LOCAL_FILES else tmp_path,
         )
 
-        # _y_ref=ttorch.tensor[1.]),
-        # _y_ref_std=tensor([0.0100]),
-        # _y_pred=tensor([-302.6861], dtype=torch.float64),
-        # _y_pred_std=tensor([2.9033], dtype=torch.float64)
+        assert not torch.isnan(torch.stack([y_ref, y_ref_std, y_pred, y_pred_std])).any()
+
+
+class TestEnthalpyOfMixing:
+    def test_enthalpy_of_mixing(self, tmp_path):
+
+        dataset = create_dataset(
+            *[
+                {  # type: ignore
+                    "id": "foo",
+                    "tag": "enthalpy_of_mixing",
+                    "x": [0.8, 0.2],
+                    "smiles": ["O", "CCO"],
+                    "temperature": 300.0,
+                    "pressure": 101.325,
+                    "value": -5.0,
+                    "std": 1.0,
+                    "units": "kJ/mol",
+                    "source": "test_source",
+                }
+            ]
+        )
+
+        # I could be forgetting a cleaner way of going from SMIRNOFF + set[SMILES] -> TensorForceField
+        _topologies, tensor_force_field = topologies_for(
+            smiles_set={smiles for smiles_list in dataset["smiles"] for smiles in smiles_list},
+            smirnoff_force_field=openff.toolkit.ForceField("openff-2.3.0.offxml"),
+        )
+
+        simulate(
+            tensor_force_field=tensor_force_field,
+            epoch_dir=Path("mixing") if USE_LOCAL_FILES else tmp_path,
+            thermo_data=dataset,
+            smirnoff_force_field="openff-2.3.0.offxml",
+            n_replicates=3,
+            n_molecules=480,
+        )
+
+        y_ref, y_ref_std, y_pred, y_pred_std = predict(
+            dataset=dataset,
+            tensor_force_field=tensor_force_field,
+            epoch_dir=Path("mixing") if USE_LOCAL_FILES else tmp_path,
+        )
+
+        assert not torch.isnan(torch.stack([y_ref, y_ref_std, y_pred, y_pred_std])).any()
+
+        assert -10 < y_pred < 0
diff --git a/tyff/compute/_equilibrate.py b/tyff/compute/_equilibrate.py
index 6c7050a..642bb10 100644
--- a/tyff/compute/_equilibrate.py
+++ b/tyff/compute/_equilibrate.py
@@ -154,7 +154,10 @@ def _run_equilibration(
 
     logger.info(f"Using OpenMM platform: {detected_platform}")
 
-    simulation.step(10_000)
+    try:
+        simulation.step(10_000)
+    except openmm.OpenMMException as error:
+        raise RuntimeError(f"OpenMM crashed during equilibration in {job_dir=}") from error
 
     with open(files["topology"].filepath, "w") as f:
         openmm.app.PDBFile.writeFile(
diff --git a/tyff/compute/_minimize.py b/tyff/compute/_minimize.py
index 70a2812..7d642d0 100644
--- a/tyff/compute/_minimize.py
+++ b/tyff/compute/_minimize.py
@@ -76,7 +76,10 @@ def _minimize_energy(
 
     original_state = simulation.context.getState(energy=True)
 
-    simulation.minimizeEnergy()
+    try:
+        simulation.minimizeEnergy()
+    except openmm.OpenMMException as error:
+        raise RuntimeError(f"OpenMM crashed during minimization in {job_dir=}") from error
 
     final_state = simulation.context.getState(energy=True, positions=True)
 
diff --git a/tyff/compute/_produce.py b/tyff/compute/_produce.py
index 8666583..9da48f9 100644
--- a/tyff/compute/_produce.py
+++ b/tyff/compute/_produce.py
@@ -152,7 +152,10 @@ def _run_production(
 
     for index in range(10):
         logger.info(f"Running from step {index * 10_000} to step {(index + 1) * 10_000}")
-        simulation.step(10_000)
+        try:
+            simulation.step(10_000)
+        except openmm.OpenMMException as error:
+            raise RuntimeError(f"OpenMM crashed during production run in {job_dir=}") from error
 
     with open(files["topology"].filepath, "w") as f:
         openmm.app.PDBFile.writeFile(
diff --git a/tyff/targets/new_thermo.py b/tyff/targets/new_thermo.py
index 949e168..ffaec30 100644
--- a/tyff/targets/new_thermo.py
+++ b/tyff/targets/new_thermo.py
@@ -15,6 +15,8 @@
 from tyff.mm._ops import RemoteEnsembleAverage
 from tyff.targets.thermo import DataEntry
 
+KCAL_TO_KJ = 4.184
+
 
 def simulate(
     tensor_force_field: tyff.TensorForceField,
@@ -175,8 +177,84 @@ def compute_properties(
             raise NotImplementedError()
             # likely identical to density case
         elif entry["tag"] == "enthalpy_of_mixing":
-            raise NotImplementedError()
-            # figure out the three job IDs necessary from observables, calculate, etc
+            for (target_id, *_), job_ids in target_compute_mapping.items():
+                if target_id == entry["id"]:
+                    break
+
+            values = list()
+
+            for job_ids_in_this_replicate in job_ids:
+                assert len(job_ids_in_this_replicate) >= 3, (
+                    "Enthalpy of vaporization requires three or more jobs (pure and each component)"
+                )
+                with (
+                    open(
+                        epoch_dir / "simulations" / job_ids_in_this_replicate[0] / "compute_config.json",
+                    ) as f0,
+                    open(
+                        epoch_dir / "simulations" / job_ids_in_this_replicate[1] / "compute_config.json",
+                    ) as f1,
+                    open(
+                        epoch_dir / "simulations" / job_ids_in_this_replicate[2] / "compute_config.json",
+                    ) as f2,
+                ):
+                    compute_configs = [
+                        json.load(f0),
+                        json.load(f1),
+                        json.load(f2),
+                    ]
+
+                    mixture_config = next(d for d in compute_configs if len(d["smiles"]) == 2)
+
+                    mixture_job_id = job_ids_in_this_replicate[compute_configs.index(mixture_config)]
+
+                    # try to keep this flexible to ternary+ mixtures
+                    components = mixture_config["smiles"]
+                    x = mixture_config["x"]
+
+                    pure_configs = [
+                        next(d for d in compute_configs if d["smiles"] == [component_i]) for component_i in components
+                    ]
+
+                    component_job_ids = list()
+                    for component_i in components:
+                        component_job_id = next(
+                            job_ids_in_this_replicate[compute_configs.index(d)]
+                            for d in compute_configs
+                            if d["smiles"] == [component_i]
+                        )
+                        component_job_ids.append(component_job_id)
+
+                    # the provided job IDs should be represented by these variables, add several checks to make sure
+                    # parsing+bookkeepping is all lined up
+                    assert sorted([*component_job_ids, mixture_job_id]) == sorted(job_ids_in_this_replicate)
+
+                    assert len(component_job_ids) == len(pure_configs) == len(mixture_config["smiles"])
+
+                    for component_config in pure_configs:
+                        assert len(component_config["smiles"]) == len(component_config["x"]) == 1
+                        assert component_config["smiles"][0] in mixture_config["smiles"]
+
+                    mixture_energy = observables[mixture_job_id]["potential_energy"]
+
+                    component_energies = [
+                        observables[component_job_id]["potential_energy"] for component_job_id in component_job_ids
+                    ]
+                    component_n_molecules = [config["n_molecules"] for config in pure_configs]
+
+                    # this is kcal/mol because of what observables is computed as in tyff/mm/_ops.py
+                    dhmix = mixture_energy / mixture_config["n_molecules"] - sum(
+                        x_i * component_energy_i / n_i
+                        for x_i, component_energy_i, n_i in zip(x, component_energies, component_n_molecules)
+                    )
+
+                    values.append(dhmix * KCAL_TO_KJ)  # convert to kJ/mol
+
+            types_of_observables = [*observables[job_ids[0][0]].keys()]
+
+            mean: dict[str, torch.Tensor] = {key: torch.stack(values).mean() for key in types_of_observables}
+            std: dict[str, torch.Tensor] = {key: torch.stack(values).std() for key in types_of_observables}
+
         elif entry["tag"] == "excess_molar_volume":
             raise NotImplementedError()
         elif entry["tag"] == "enthalpy_of_vaporization":
@@ -223,11 +301,9 @@ def compute_properties(
                     "Gas and liquid temperatures must be the same for dHvap calculation"
                 )
 
-                kcal_to_kJ = 4.184
-
                 # these are stored in kcal/mol, so need to convert
-                gas_energy = observables[gas_job_id]["potential_energy"] * kcal_to_kJ
-                liquid_energy = observables[liquid_job_id]["potential_energy"] * kcal_to_kJ
+                gas_energy = observables[gas_job_id]["potential_energy"] * KCAL_TO_KJ
+                liquid_energy = observables[liquid_job_id]["potential_energy"] * KCAL_TO_KJ
 
                 n_molecules = liquid_config["n_molecules"]
 

From f5acd645d824e31184cc9793f00ea1bd335e6472 Mon Sep 17 00:00:00 2001
From: "Matthew W. Thompson" <mattwthompson@protonmail.com>
Date: Tue, 10 Nov 2026 11:53:55 -0600
Subject: [PATCH 13/18] Avoid using platforms if not available

For example: OpenCL is not available on most Linux runners, so it should be
skipped over when falling back through CUDA -> ... -> CPU platforms
---
 tyff/compute/_openmm.py | 8 +++++++-
 1 file changed, 7 insertions(+), 1 deletion(-)

diff --git a/tyff/compute/_openmm.py b/tyff/compute/_openmm.py
index 030228b..6555e2a 100644
--- a/tyff/compute/_openmm.py
+++ b/tyff/compute/_openmm.py
@@ -14,8 +14,12 @@ def _get_platform(logger: logging.Logger) -> openmm.Platform:
     openmm.Platform
         The OpenMM platform to use for minimization.
     """
-
+    available_platforms = [openmm.Platform.getPlatform(i).getName() for i in range(openmm.Platform.getNumPlatforms())]
     for platform_name in ["CUDA", "OpenCL", "CPU"]:
+        if platform_name not in available_platforms:
+            logger.info(f"Could not use {platform_name} platform because it is not detected as available")
+            continue
+
         try:
             logger.info(f"Trying to use {platform_name} platform ...")
             platform = openmm.Platform.getPlatformByName(platform_name)
@@ -26,3 +30,5 @@ def _get_platform(logger: logging.Logger) -> openmm.Platform:
         logger.info(f"Successfully requested platform {platform.getName()}")
 
         return platform
+
+    raise ValueError(f"Could not find a usable OpenMM platform. Available platforms: {available_platforms}")

From 226f8674486f74ea12c60dc841936137c9c23b0d Mon Sep 17 00:00:00 2001
From: "Matthew W. Thompson" <mattwthompson@protonmail.com>
Date: Wed, 11 Nov 2026 09:20:07 -0600
Subject: [PATCH 14/18] Update defaults in MVP to safely run water boxes

---
 examples/mvp/run.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/examples/mvp/run.py b/examples/mvp/run.py
index 4ad75b0..e8089c2 100644
--- a/examples/mvp/run.py
+++ b/examples/mvp/run.py
@@ -15,8 +15,8 @@
 from tyff.train import ParameterConfig, Trainable
 
 N_EPOCHS = 10
-N_REPLICATES = 2
-N_MOLECULES = 200
+N_REPLICATES = 1
+N_MOLECULES = 400
 INITIAL_FORCE_FIELD = "openff-2.3.0.offxml"
 
 MERGE_DATA = True

From 16d3c14287b644b9fa97675f5c472730fd578431 Mon Sep 17 00:00:00 2001
From: "Matthew W. Thompson" <mattwthompson@protonmail.com>
Date: Wed, 11 Nov 2026 09:21:11 -0600
Subject: [PATCH 15/18] Actually fix

---
 examples/mvp/run.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/examples/mvp/run.py b/examples/mvp/run.py
index e8089c2..0457dd0 100644
--- a/examples/mvp/run.py
+++ b/examples/mvp/run.py
@@ -16,7 +16,7 @@
 
 N_EPOCHS = 10
 N_REPLICATES = 1
-N_MOLECULES = 400
+N_MOLECULES = 480
 INITIAL_FORCE_FIELD = "openff-2.3.0.offxml"
 
 MERGE_DATA = True

From 559d208a3e90cc611bc3e59a297ad7f68eb91ecc Mon Sep 17 00:00:00 2001
From: "Matthew W. Thompson" <mattwthompson@protonmail.com>
Date: Wed, 11 Nov 2026 09:25:08 -0600
Subject: [PATCH 16/18] Load SMILES as mapped in compute apps

---
 tyff/_tests/integration_tests/compute/test_workflow.py | 2 ++
 tyff/compute/_minimize.py                              | 2 +-
 tyff/compute/_pack.py                                  | 2 +-
 3 files changed, 4 insertions(+), 2 deletions(-)

diff --git a/tyff/_tests/integration_tests/compute/test_workflow.py b/tyff/_tests/integration_tests/compute/test_workflow.py
index c9d278d..59e6eeb 100644
--- a/tyff/_tests/integration_tests/compute/test_workflow.py
+++ b/tyff/_tests/integration_tests/compute/test_workflow.py
@@ -59,6 +59,8 @@ def test_enthalpy_of_vaporization(self, tmp_path):
 
         assert not torch.isnan(torch.stack([y_ref, y_ref_std, y_pred, y_pred_std])).any()
 
+        # experimental value is around 36 kJ/mol, could get away with much smaller range
+        assert 30 < y_pred < 50
 
 class TestEnthalpyOfMixing:
     def test_enthalpy_of_mixing(self, tmp_path):
diff --git a/tyff/compute/_minimize.py b/tyff/compute/_minimize.py
index 7d642d0..9f24710 100644
--- a/tyff/compute/_minimize.py
+++ b/tyff/compute/_minimize.py
@@ -50,7 +50,7 @@ def _minimize_energy(
     # this should be in Kelvin
     temperature = compute_config["temperature"]
 
-    molecules = [Molecule.from_smiles(smiles) for smiles in compute_config["smiles"]]
+    molecules = [Molecule.from_mapped_smiles(smiles) for smiles in compute_config["smiles"]]
 
     topology = Topology.from_pdb(
         system_future["prepared_files"]["packed_topology"].filepath,
diff --git a/tyff/compute/_pack.py b/tyff/compute/_pack.py
index fddd166..976c55a 100644
--- a/tyff/compute/_pack.py
+++ b/tyff/compute/_pack.py
@@ -41,7 +41,7 @@ def _prepare_packed_topology(
     time.sleep(n_molecules * 0.001)
     packed_topology_file = f"{job_dir}/packed_topology.pdb"
 
-    molecules = [Molecule.from_smiles(smiles) for smiles in compute_config["smiles"]]
+    molecules = [Molecule.from_mapped_smiles(smiles) for smiles in compute_config["smiles"]]
 
     n_copies = [int(n_molecules * x) for x in compute_config["x"]]
 

From d24658da0c6ceb692198a6822b9f96c9c31d015e Mon Sep 17 00:00:00 2001
From: "Matthew W. Thompson" <mattwthompson@protonmail.com>
Date: Wed, 11 Nov 2026 09:54:44 -0600
Subject: [PATCH 17/18] Update dhmix/dhvap test

---
 .../integration_tests/compute/test_workflow.py | 18 ++++++++++--------
 1 file changed, 10 insertions(+), 8 deletions(-)

diff --git a/tyff/_tests/integration_tests/compute/test_workflow.py b/tyff/_tests/integration_tests/compute/test_workflow.py
index 59e6eeb..e607dae 100644
--- a/tyff/_tests/integration_tests/compute/test_workflow.py
+++ b/tyff/_tests/integration_tests/compute/test_workflow.py
@@ -28,8 +28,8 @@ def test_enthalpy_of_vaporization(self, tmp_path):
                     "smiles": ["CO"],
                     "temperature": 300.0,
                     "pressure": 101.325,
-                    "value": 1.0,
-                    "std": 0.01,
+                    "value": 38.3,
+                    "std": 0.01,  # arbitrary/unused
                     "units": "kJ/mol",
                     "source": "test_source",
                 }
@@ -59,8 +59,9 @@ def test_enthalpy_of_vaporization(self, tmp_path):
 
         assert not torch.isnan(torch.stack([y_ref, y_ref_std, y_pred, y_pred_std])).any()
 
-        # experimental value is around 36 kJ/mol, could get away with much smaller range
-        assert 30 < y_pred < 50
+        # experimental value is around 38 kJ/mol, could get away with much smaller range
+        assert 30 < y_pred < 50, f"{y_pred=} {y_ref=}, {y_pred_std=}, {y_ref_std=}"
+
 
 class TestEnthalpyOfMixing:
     def test_enthalpy_of_mixing(self, tmp_path):
@@ -72,10 +73,10 @@ def test_enthalpy_of_mixing(self, tmp_path):
                     "tag": "enthalpy_of_mixing",
                     "x": [0.8, 0.2],
                     "smiles": ["O", "CCO"],
-                    "temperature": 300.0,
+                    "temperature": 298.15,
                     "pressure": 101.325,
-                    "value": -5.0,
-                    "std": 1.0,
+                    "value": -0.765,
+                    "std": 0.01,  # arbitrary/unused
                     "units": "kJ/mol",
                     "source": "test_source",
                 }
@@ -105,4 +106,5 @@ def test_enthalpy_of_mixing(self, tmp_path):
 
         assert not torch.isnan(torch.stack([y_ref, y_ref_std, y_pred, y_pred_std])).any()
 
-        assert -10 < y_pred < 0
+        # experimental value is around -0.7 kJ/mol, but it should be negative (for all concentrations)
+        assert -1 < y_pred < 0, f"{y_pred=} {y_ref=}, {y_pred_std=}, {y_ref_std=}"

From 5a9ec9f7e60edd3954034562e9d85ab6921c9454 Mon Sep 17 00:00:00 2001
From: "Matthew W. Thompson" <mattwthompson@protonmail.com>
Date: Fri, 13 Nov 2026 10:54:53 -0600
Subject: [PATCH 18/18] Update lockfile

---
 pixi.lock | 21452 ++++++++++++++++++++++++++++++++++++++++++++++++++++
 pixi.toml |     3 -
 2 files changed, 21452 insertions(+), 3 deletions(-)
 create mode 100644 pixi.lock

diff --git a/pixi.lock b/pixi.lock
new file mode 100644
index 0000000..0f9e447
--- /dev/null
+++ b/pixi.lock
@@ -0,0 +1,21452 @@
+version: 7
+platforms:
+- name: linux-64
+  virtual-packages:
+  - __unix=0
+  - __linux=4.18
+  - __glibc=2.28
+  - __archspec=0=x86_64
+- name: osx-arm64
+  virtual-packages:
+  - __unix=0
+  - __osx=13.0
+  - __archspec=0=m1
+environments:
+  default:
+    channels:
+    - url: https://conda.anaconda.org/conda-forge/
+    indexes:
+    - https://pypi.org/simple
+    packages:
+      linux-64:
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/_openmp_mutex-4.5-8_kmp_llvm.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/aiohttp-3.14.5-py313h2af15c8_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/aws-c-auth-0.10.1-h2d2dd48_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/aws-c-cal-0.9.13-h2c9d079_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/aws-c-common-0.12.6-hb03c661_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/aws-c-compression-0.3.2-h8b1a151_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/aws-c-event-stream-0.6.0-h9b893ba_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/aws-c-http-0.10.12-h4bacb7b_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/aws-c-io-0.26.3-hb18f61d_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/aws-c-mqtt-0.15.2-he9ea9c5_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/aws-c-s3-0.11.5-h6d69fc9_5.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/aws-c-sdkutils-0.2.4-h8b1a151_4.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/aws-checksums-0.2.10-h8b1a151_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/aws-crt-cpp-0.37.4-h4c8aef7_3.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/aws-sdk-cpp-1.11.747-hc3785e1_3.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/azure-core-cpp-1.16.2-h206d751_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/azure-identity-cpp-1.13.3-hed0cdb0_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/azure-storage-blobs-cpp-12.16.0-hf824e48_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/azure-storage-common-cpp-12.13.0-ha7a2c86_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/azure-storage-files-datalake-cpp-12.14.0-h539c000_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/blosc-1.21.7-h3f4a69f_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/brotli-1.2.1-h505cf86_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/brotli-bin-1.2.1-h9908984_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/bzip2-1.0.8-hda65f42_10.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/c-ares-1.34.9-hebe6cf0_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/c-blosc2-3.6.1-hea3f660_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cairo-1.18.6-h3c89d7e_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cftime-1.6.5-py313h12b3e8d_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/charset-normalizer-3.5.2-h1114479_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/contourpy-1.4.0-py313h2551ef2_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cuda-nvrtc-13.5.37-h393e864_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cyrus-sasl-2.1.28-hac629b4_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/cytoolz-1.2.0-py313hd42f317_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/eigen-abi-5.0.1.80-hf414acd_3.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/flatbuffers-25.9.23-hb7d4c21_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/fmt-12.1.0-h76c4fd7_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/fontconfig-2.18.3-h4db4eae_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/fonttools-4.68.0-py313h6cd9899_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/freetype-2.14.3-ha770c72_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/fribidi-1.0.18-h7cc23a3_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/frozenlist-1.8.0-py313h7259b1b_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/gflags-2.3.1-hee9eb32_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/glog-0.7.1-hb7133d2_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/gmp-6.3.0-hfd2156b_3.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/gmpy2-2.3.2-py313ha4a6282_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/graphite2-1.3.15-h54a6638_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/greenlet-3.5.6-py313h901f96d_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/hdf4-4.2.15-h2a13503_7.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/hdf5-1.14.6-nompi_h19486de_110.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/hf-xet-1.8.0-py311h30674b1_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/icu-78.3-py310h44b86e0_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/jaxlib-0.10.2-cpu_py313hb5bfa57_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/keyutils-1.6.3-h7cc23a3_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/kiwisolver-1.5.1-py313h2551ef2_3.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/krb5-1.22.2-hbc21106_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/lcms2-2.20-h9073bf1_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/ld_impl_linux-64-2.46.1-default_hbd61a6d_103.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/lerc-4.3.0-he78707d_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libabseil-20260107.1-cxx17_h7b12aa8_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libaec-1.1.8-h659bb9a_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libarrow-20.0.0-hcf3e2a1_44_cpu.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libarrow-acero-20.0.0-h635bf11_44_cpu.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libarrow-dataset-20.0.0-h635bf11_44_cpu.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libarrow-substrait-20.0.0-hb4dd7c2_44_cpu.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libblas-3.11.0-12_h5875eb1_mkl.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libboost-1.90.0-h1101c1b_3.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libboost-python-1.90.0-py313hcc39c74_3.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libbrotlicommon-1.2.1-h39a168f_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libbrotlidec-1.2.1-ha411449_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libbrotlienc-1.2.1-h018ffa1_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcblas-3.11.0-12_hfef963f_mkl.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcrc32c-1.1.2-hee9eb32_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcufft-12.5.0.14-h393e864_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libcurl-8.23.0-ha042cf0_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libdeflate-1.26-h351257e_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libedit-3.1.20260512-pl5321h373387f_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libev-4.33-h280c20c_3.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libevent-2.1.12-h5348a74_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libexpat-2.9.0-hd2095e1_0.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libffi-3.7.0-h81df57d_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libfreetype-2.14.3-ha770c72_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libfreetype6-2.14.3-h5e6c136_2.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-16.2.0-ha9f2e26_7.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgcc-ng-16.2.0-h69a702a_7.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgfortran-16.2.0-h69a702a_7.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgfortran5-16.2.0-h6b99dfc_7.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libglib-2.90.1-hb382ddc_3.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgoogle-cloud-3.3.0-h25dbb67_1.conda
+      - conda: https://conda.anaconda.org/conda-forge/linux-64/libgoogle-cloud-storage-3.3.0-hdbdcf42_1.conda
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+  - doc8 ; extra == 'doc'
+  - sphinx>=7.0.0 ; extra == 'doc'
+  - sphinx-autobuild ; extra == 'doc'
+  - sphinx-autodoc-typehints ; extra == 'doc'
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+  - dateparser==1.* ; extra == 'test'
+  - pre-commit ; extra == 'test'
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+  - pytest-cov ; extra == 'test'
+  - pytest-mock ; extra == 'test'
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+  - littleutils ; extra == 'tests'
+  - cython ; extra == 'tests'
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+  requires_dist:
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+- pypi: https://files.pythonhosted.org/packages/fa/e8/0485850748dfdba9443f4151c7b2442cfa4987ba6cd871038eb5d6b8eca9/wcwidth-0.9.4-cp310-abi3-manylinux2014_x86_64.manylinux_2_17_x86_64.whl
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+  name: librt
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+  requires_python: '>=3.9'
+- pypi: https://files.pythonhosted.org/packages/fd/2e/36fc0941a40ef066dbc8abac41bbbefb41389f547c779aef832aea6b873d/types_pyyaml-6.0.12.20261113-py3-none-any.whl
+  name: types-pyyaml
+  version: 6.0.12.20261113
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diff --git a/pixi.toml b/pixi.toml
index 5bd9a08..4304b57 100644
--- a/pixi.toml
+++ b/pixi.toml
@@ -83,9 +83,6 @@ cuda-version = "==13.0"
 [feature.py312.dependencies]
 python = "3.12.*"
 
-[feature.test.dependencies]
-pytest = "<9.2"
-
 [feature.test.pypi-dependencies]
 pytest = ">=9.2"
 pytest-cov = "*"