Add Gaussian noise 3D transform and augmentation

conf/data_module/augmentations/ts_3d_jitter.yaml

@@ -0,0 +1,6 @@
+
+_target_: chemtorch.components.augmentation.TS3DJitterAugmentation
+jitter:
+  _target_: chemtorch.components.transform.TS3DJitterTransform
+  sigma: 0.1
+  clip: 0.5

conf/experiment/dimereaction_ts_sensitivity.yaml

@@ -0,0 +1,48 @@
+# @package _global_
+defaults:
+  - /data_module/data_pipeline: rdb7_fwd_xyz
+  - /data_module/representation: reaction_3d_graph
+  - /data_module/dataloader_factory: pyg_dataloader
+  - /data_module/transform/ts_3d_jitter@data_module.transform.test.ts_3d_jitter
+  - /model: dimereaction
+  - /routine: regression
+  - /props/label_mean@props.label_mean
+  - /props/label_std@props.label_std
+  - _self_
+
+# LOGGING (Weight and Biases)
+log: true
+project_name: chemtorch
+group_name: dimereaction_ts_sensitivity
+run_name: dimereaction
+
+# Prediction and checkpoint saving
+save_dir: experiment/dimereaction_ts_sensitivity/${run_name}/seed_${seed}_${now:%Y-%m-%d_%H-%M-%S}
+save_predictions_for: all
+predictions_save_dir: ${save_dir}/predictions
+trainer.enable_checkpointing: true
+trainer.checkpoint_callback.dirpath: ${save_dir}/checkpoints
+
+# INITIALIZATION
+seed: 0
+
+tasks:
+  - fit
+  - test
+
+trainer:
+  max_epochs: 100
+
+# HYPERPARAMETERS
+routine:
+  optimizer:
+    lr: 0.0020537287319414765
+    weight_decay: 2.5493166021321106e-05
+data_module:
+  dataloader:
+    batch_size: 32
+
+model:
+  hidden_channels: 128
+  num_blocks: 4
+  cutoff: 5.528600558772409

conf/experiment/dimereaction_ts_sensitivity_augmented.yaml

@@ -0,0 +1,7 @@
+# @package _global_
+defaults:
+  - dimereaction_ts_sensitivity
+  - /data_module/augmentations/ts_3d_jitter@data_module.augmentations.ts_3d_jitter
+  - _self_
+
+run_name: dimereaction_augmented

src/chemtorch/components/augmentation/ts_3d_jitter.py

@@ -0,0 +1,35 @@
+from typing import List, Optional
+import torch
+from torch._tensor import Tensor
+
+from chemtorch.components.transform.graph_transform.ts_3d_jitter import TS3DJitterTransform
+
+try:
+    # Python ≥ 3.12
+    from typing import override  # type: ignore
+except ImportError:
+    # Python < 3.12
+    from typing_extensions import override  # type: ignore
+
+from chemtorch.components.augmentation.abstract_augmentation import AbstractAugmentation
+from chemtorch.components.representation.graph.reaction_3d_graph import Reaction3DData
+
+
+class TS3DJitterAugmentation(AbstractAugmentation[Reaction3DData]):
+    """
+    Apply Gaussian noise to the 3D coordinates of the transition state.
+    """
+
+    def __init__(self, jitter: TS3DJitterTransform, num_augmentations: int = 1):
+        self.jitter = jitter
+        self.num_augmentations = num_augmentations
+
+    @override
+    def _augment(self, obj: Reaction3DData, label: Optional[Tensor] = None) -> List[tuple[Reaction3DData, Optional[Tensor]]]:
+        augmented_list = []
+
+        for _ in range(self.num_augmentations):
+            augmented_data = self.jitter(obj.clone())
+            augmented_list.append((augmented_data, label))
+
+        return augmented_list

src/chemtorch/components/transform/graph_transform/__init__.py

@@ -1,2 +1,3 @@
 from .dummy import DummyNodeTransform
 from .randomwalkpe import RandomWalkPETransform
+from .ts_3d_jitter import TS3DJitterTransform

src/chemtorch/components/transform/graph_transform/ts_3d_jitter.py

@@ -0,0 +1,42 @@
+import torch
+
+try:
+    # Python ≥ 3.12
+    from typing import override  # type: ignore
+except ImportError:
+    # Python < 3.12
+    from typing_extensions import override  # type: ignore
+
+from chemtorch.components.representation.graph.reaction_3d_graph import Reaction3DData
+from chemtorch.components.transform.abstract_transform import AbstractTransform
+
+
+class TS3DJitterTransform(AbstractTransform[Reaction3DData]):
+    """
+    Apply Gaussian noise to the 3D coordinates of the transition state.
+
+    The noise is sampled from a normal distribution with mean 0 and standard deviation defined by `sigma`.
+    The noise is clipped to the range [-clip, clip] to prevent excessive perturbations.
+    """
+
+    def __init__(self, sigma: float = 0.1, clip: float = 0.5):
+        self.sigma = sigma
+        self.clip = clip
+
+    def _make_jitter(self, pos: torch.Tensor) -> torch.Tensor:
+        return torch.clamp(
+            torch.randn_like(pos) * self.sigma, -self.clip, self.clip
+        )
+
+    @override
+    def __call__(self, obj: Reaction3DData, **kwargs) -> Reaction3DData:
+        def _make_jitter(pos: torch.Tensor) -> torch.Tensor:
+            return torch.clamp(
+                torch.randn_like(pos) * self.sigma, -self.clip, self.clip
+            )
+
+        ts_jitter = _make_jitter(obj.pos_ts)
+
+        obj.pos_ts += ts_jitter
+
+        return obj

test/test_integration/fixtures/baselines.yaml

@@ -0,0 +1,55 @@
+# Reference baseline values for saved config tests
+# 
+# This file defines expected validation losses and test configuration for each model.
+# Timeout values fallback to presets.py defaults (PRECOMPUTE_TIMEOUT=30s, DEFAULT_TIMEOUT=60s)
+# Only specify timeout values when they differ from defaults.
+
+# Configuration defaults
+defaults:
+  tolerance: 1.1e-5  # Tolerance for prediction comparisons
+
+# Model-specific baselines
+models:
+  atom_han:
+    val_loss:
+      epoch_1: 1.34
+      epoch_3: 1.39
+    timeout:
+      precompute: 10
+      per_epoch: 60
+    reference_predictions:
+      epoch_1: "rdb7_subsample_0.01_atom_han_seed_0_epoch_1.csv"
+      epoch_3: "rdb7_subsample_0.01_atom_han_seed_0_epoch_3.csv"
+
+  cgr_dmpnn:
+    val_loss:
+      epoch_1: 1.36
+      epoch_3: 1.49
+    timeout:
+      precompute: 10
+      per_epoch: 120
+    reference_predictions:
+      epoch_1: "rdb7_subsample_0.01_cgr_dmpnn_seed_0_epoch_1.csv"
+      epoch_3: "rdb7_subsample_0.01_cgr_dmpnn_seed_0_epoch_3.csv"
+
+  drfp_mlp:
+    val_loss:
+      epoch_1: 1.30
+      epoch_3: 1.34
+    timeout:
+      precompute: 30
+      per_epoch: 30
+    reference_predictions:
+      epoch_1: "rdb7_subsample_0.01_drfp_mlp_seed_0_epoch_1.csv"
+      epoch_3: "rdb7_subsample_0.01_drfp_mlp_seed_0_epoch_3.csv"
+
+  dimereaction:
+    val_loss:
+      epoch_1: 1.37
+      epoch_3: 1.16
+    timeout:
+      precompute: 20
+      per_epoch: 80
+    reference_predictions:
+      epoch_1: "rdb7_subsample_0.01_dimereaction_seed_0_epoch_1.csv"
+      epoch_3: "rdb7_subsample_0.01_dimereaction_seed_0_epoch_3.csv"

test/test_integration/fixtures/ref_preds/rdb7_subsample_0.01_atom_han_seed_0_epoch_1.csv

@@ -0,0 +1,13 @@
+label,smiles,prediction
+92.62519,[C:1]1([H:7])([H:8])[C@:2]2([H:9])[C:3]([H:10])([H:11])[C:4]([H:12])([H:13])[C:5]([H:14])([H:15])[C@:6]12[H:16]>>[C:1]1([H:7])([H:8])[C@:2]([C:3]([C:4]([H:12])([H:13])[H:14])([H:10])[H:11])([H:9])[C@:6]1([C:5][H:15])[H:16],81.07571
+90.15481,[C:1]([C:2]([C:3]1([O:4][H:12])[C:5]([H:13])([H:14])[C:6]1([H:15])[H:16])([H:10])[H:11])([H:7])([H:8])[H:9]>>[C:1]([C:2]([C:6]([C:5]([C:3][O:4][H:12])([H:13])[H:14])([H:15])[H:16])([H:10])[H:11])([H:7])([H:8])[H:9],81.091736
+75.21907,[C:1]([C:2]1([O:3][H:10])[C:4]([H:11])([H:12])[O:5][C:6]1([H:13])[H:14])([H:7])([H:8])[H:9]>>[C:1]([C:2](=[O:3])[C:4]([O:5][C:6]([H:10])([H:13])[H:14])([H:11])[H:12])([H:7])([H:8])[H:9],81.06443
+47.00517,[N:1]([c:2]1[n:3][c:4]([O:5][H:10])[c:6]([H:11])[n:7]1[H:12])([H:8])[H:9]>>[N:1]([C@@:2]1([H:12])[N:3]=[C:4]([O:5][H:10])[C:6]([H:11])=[N:7]1)([H:8])[H:9],81.176216
+86.62878,[C:1]1([H:7])([H:8])[N:2]([H:9])[C@:3]1([C@@:4]1([H:11])[C:5]([H:12])([H:13])[N:6]1[H:14])[H:10]>>[C:1](=[N:2][H:9])([H:7])[H:8].[C:3]([C@@:4]1([H:11])[C:5]([H:12])([H:13])[N:6]1[H:14])[H:10],81.20128
+114.48725,[C:1](#[C:2][c:3]1[c:4]([H:9])[n:5]([H:10])[n:6][c:7]1[H:11])[H:8]>>[C+:1]#[C:2][C:3]1=[C:4]([H:9])[N:5]([H:10])[N-:6][C:7]1([H:8])[H:11],81.16353
+67.50583,[O:1]([C@@:2]1([H:8])[C:3]([H:9])([H:10])[C:4]([H:11])([H:12])[C@:5]1([O:6][H:14])[H:13])[H:7]>>[C:2]1([H:8])=[C:3]([H:9])[C:4]([H:11])([H:12])[C@:5]1([O:6][H:14])[H:13].[O:1]([H:7])[H:10],81.120895
+76.88764,[C:1]([N:2]([C:3](=[O:4])[H:10])[C:5](=[O:6])[H:11])([H:7])([H:8])[H:9]>>[C-:3]#[O+:4].[C:1]([N:2]([C:5](=[O:6])[H:11])[H:10])([H:7])([H:8])[H:9],81.04735
+136.10961,[O:1]=[C:2]1[C:3]([H:8])([H:9])[C:4]([C:6]#[N:7])([H:10])[C:5]1([H:11])[H:12]>>[O:1]=[C:6]=[N:7][C:4]1([H:10])[C:3]([H:8])([H:9])[C:2][C:5]1([H:11])[H:12],81.06836
+99.43027,[N:1]#[C:2][C@@:3]1([H:7])[C:4]([H:8])([H:9])[C:5]([H:10])([H:11])[N:6]1[H:12]>>[N:1]#[C:2][C@@:3]1([H:7])[C-:4]([H:9])[N+:6]1([C:5]([H:8])([H:10])[H:11])[H:12],81.16888
+54.73362,[C:1]([C@@:2]([O:3][H:11])([C@@:4]1([H:12])[C:5]([H:13])([H:14])[O:6]1)[H:10])([H:7])([H:8])[H:9]>>[C:1]([C@@:2]1([H:10])[O:3][C@@:4]1([C:5]([O:6][H:11])([H:13])[H:14])[H:12])([H:7])([H:8])[H:9],81.1118
+115.48569,[C:1]([C:2]([c:3]1[c:4]([H:13])[n:5]([H:14])[n:6][n:7]1)([H:11])[H:12])([H:8])([H:9])[H:10]>>[C:1]([C:2]([C:4](=[C:3]=[N:7][N:6]=[N:5][H:14])[H:13])([H:11])[H:12])([H:8])([H:9])[H:10],81.07801

test/test_integration/fixtures/ref_preds/rdb7_subsample_0.01_atom_han_seed_0_epoch_3.csv

@@ -0,0 +1,13 @@
+label,smiles,prediction
+92.62519,[C:1]1([H:7])([H:8])[C@:2]2([H:9])[C:3]([H:10])([H:11])[C:4]([H:12])([H:13])[C:5]([H:14])([H:15])[C@:6]12[H:16]>>[C:1]1([H:7])([H:8])[C@:2]([C:3]([C:4]([H:12])([H:13])[H:14])([H:10])[H:11])([H:9])[C@:6]1([C:5][H:15])[H:16],82.991585
+90.15481,[C:1]([C:2]([C:3]1([O:4][H:12])[C:5]([H:13])([H:14])[C:6]1([H:15])[H:16])([H:10])[H:11])([H:7])([H:8])[H:9]>>[C:1]([C:2]([C:6]([C:5]([C:3][O:4][H:12])([H:13])[H:14])([H:15])[H:16])([H:10])[H:11])([H:7])([H:8])[H:9],82.98281
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+47.00517,[N:1]([c:2]1[n:3][c:4]([O:5][H:10])[c:6]([H:11])[n:7]1[H:12])([H:8])[H:9]>>[N:1]([C@@:2]1([H:12])[N:3]=[C:4]([O:5][H:10])[C:6]([H:11])=[N:7]1)([H:8])[H:9],82.400604
+86.62878,[C:1]1([H:7])([H:8])[N:2]([H:9])[C@:3]1([C@@:4]1([H:11])[C:5]([H:12])([H:13])[N:6]1[H:14])[H:10]>>[C:1](=[N:2][H:9])([H:7])[H:8].[C:3]([C@@:4]1([H:11])[C:5]([H:12])([H:13])[N:6]1[H:14])[H:10],82.82114
+114.48725,[C:1](#[C:2][c:3]1[c:4]([H:9])[n:5]([H:10])[n:6][c:7]1[H:11])[H:8]>>[C+:1]#[C:2][C:3]1=[C:4]([H:9])[N:5]([H:10])[N-:6][C:7]1([H:8])[H:11],82.331924
+67.50583,[O:1]([C@@:2]1([H:8])[C:3]([H:9])([H:10])[C:4]([H:11])([H:12])[C@:5]1([O:6][H:14])[H:13])[H:7]>>[C:2]1([H:8])=[C:3]([H:9])[C:4]([H:11])([H:12])[C@:5]1([O:6][H:14])[H:13].[O:1]([H:7])[H:10],82.748215
+76.88764,[C:1]([N:2]([C:3](=[O:4])[H:10])[C:5](=[O:6])[H:11])([H:7])([H:8])[H:9]>>[C-:3]#[O+:4].[C:1]([N:2]([C:5](=[O:6])[H:11])[H:10])([H:7])([H:8])[H:9],82.253746
+136.10961,[O:1]=[C:2]1[C:3]([H:8])([H:9])[C:4]([C:6]#[N:7])([H:10])[C:5]1([H:11])[H:12]>>[O:1]=[C:6]=[N:7][C:4]1([H:10])[C:3]([H:8])([H:9])[C:2][C:5]1([H:11])[H:12],82.3757
+99.43027,[N:1]#[C:2][C@@:3]1([H:7])[C:4]([H:8])([H:9])[C:5]([H:10])([H:11])[N:6]1[H:12]>>[N:1]#[C:2][C@@:3]1([H:7])[C-:4]([H:9])[N+:6]1([C:5]([H:8])([H:10])[H:11])[H:12],82.64329
+54.73362,[C:1]([C@@:2]([O:3][H:11])([C@@:4]1([H:12])[C:5]([H:13])([H:14])[O:6]1)[H:10])([H:7])([H:8])[H:9]>>[C:1]([C@@:2]1([H:10])[O:3][C@@:4]1([C:5]([O:6][H:11])([H:13])[H:14])[H:12])([H:7])([H:8])[H:9],82.747314
+115.48569,[C:1]([C:2]([c:3]1[c:4]([H:13])[n:5]([H:14])[n:6][n:7]1)([H:11])[H:12])([H:8])([H:9])[H:10]>>[C:1]([C:2]([C:4](=[C:3]=[N:7][N:6]=[N:5][H:14])[H:13])([H:11])[H:12])([H:8])([H:9])[H:10],82.515076

test/test_integration/fixtures/ref_preds/rdb7_subsample_0.01_cgr_dmpnn_seed_0_epoch_1.csv

@@ -0,0 +1,13 @@
+label,smiles,prediction
+92.62519,[C:1]1([H:7])([H:8])[C@:2]2([H:9])[C:3]([H:10])([H:11])[C:4]([H:12])([H:13])[C:5]([H:14])([H:15])[C@:6]12[H:16]>>[C:1]1([H:7])([H:8])[C@:2]([C:3]([C:4]([H:12])([H:13])[H:14])([H:10])[H:11])([H:9])[C@:6]1([C:5][H:15])[H:16],81.62593
+90.15481,[C:1]([C:2]([C:3]1([O:4][H:12])[C:5]([H:13])([H:14])[C:6]1([H:15])[H:16])([H:10])[H:11])([H:7])([H:8])[H:9]>>[C:1]([C:2]([C:6]([C:5]([C:3][O:4][H:12])([H:13])[H:14])([H:15])[H:16])([H:10])[H:11])([H:7])([H:8])[H:9],81.555855
+75.21907,[C:1]([C:2]1([O:3][H:10])[C:4]([H:11])([H:12])[O:5][C:6]1([H:13])[H:14])([H:7])([H:8])[H:9]>>[C:1]([C:2](=[O:3])[C:4]([O:5][C:6]([H:10])([H:13])[H:14])([H:11])[H:12])([H:7])([H:8])[H:9],81.62833
+47.00517,[N:1]([c:2]1[n:3][c:4]([O:5][H:10])[c:6]([H:11])[n:7]1[H:12])([H:8])[H:9]>>[N:1]([C@@:2]1([H:12])[N:3]=[C:4]([O:5][H:10])[C:6]([H:11])=[N:7]1)([H:8])[H:9],81.32265
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+114.48725,[C:1](#[C:2][c:3]1[c:4]([H:9])[n:5]([H:10])[n:6][c:7]1[H:11])[H:8]>>[C+:1]#[C:2][C:3]1=[C:4]([H:9])[N:5]([H:10])[N-:6][C:7]1([H:8])[H:11],81.442276
+67.50583,[O:1]([C@@:2]1([H:8])[C:3]([H:9])([H:10])[C:4]([H:11])([H:12])[C@:5]1([O:6][H:14])[H:13])[H:7]>>[C:2]1([H:8])=[C:3]([H:9])[C:4]([H:11])([H:12])[C@:5]1([O:6][H:14])[H:13].[O:1]([H:7])[H:10],81.47074
+76.88764,[C:1]([N:2]([C:3](=[O:4])[H:10])[C:5](=[O:6])[H:11])([H:7])([H:8])[H:9]>>[C-:3]#[O+:4].[C:1]([N:2]([C:5](=[O:6])[H:11])[H:10])([H:7])([H:8])[H:9],81.21686
+136.10961,[O:1]=[C:2]1[C:3]([H:8])([H:9])[C:4]([C:6]#[N:7])([H:10])[C:5]1([H:11])[H:12]>>[O:1]=[C:6]=[N:7][C:4]1([H:10])[C:3]([H:8])([H:9])[C:2][C:5]1([H:11])[H:12],81.4186
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test/test_integration/fixtures/ref_preds/rdb7_subsample_0.01_cgr_dmpnn_seed_0_epoch_3.csv

@@ -0,0 +1,13 @@
+label,smiles,prediction
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test/test_integration/fixtures/ref_preds/rdb7_subsample_0.01_dimereaction_seed_0_epoch_1.csv

@@ -0,0 +1,13 @@
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