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Datasets:
Jrhoss
/
DrivaerML-PCTR

Tasks:
Other
Size:
100K<n<1M
ArXiv:
Tags:
CFD
aerodynamics
point-cloud
pytorch
fluid-dynamics
regression
License:
Dataset card Files
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 Community
Jrhoss commited on
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1 Parent(s): 0eb9119

Reorganize into train/val/test splits (80/10/10, seed=42) and fix README metadata

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  1. README.md +71 -13
  2. test/run_102/boundary_102.pt +3 -0
  3. test/run_111/boundary_111.pt +3 -0
  4. test/run_112/boundary_112.pt +3 -0
  5. test/run_113/boundary_113.pt +3 -0
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  31. test/run_392/boundary_392.pt +3 -0
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  50. test/run_82/boundary_82.pt +3 -0
README.md CHANGED
@@ -1,3 +1,25 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
  # DrivaerML-PCTR
2
 
3
  Processed version of [neashton/drivaerml](https://huggingface.co/datasets/neashton/drivaerml)
@@ -7,14 +29,39 @@ for use with the PCT-R (Point Cloud Transformer for Regression) model.
7
 
8
  Each `boundary_i.vtp` file (~500MB, ~8.8M cells) was processed as follows:
9
 
10
- 1. **Random sampling**: 100,000 cells per run, fixed seed `seed = run_id + 42`.
11
- 2. **Cell centres**: Coordinates are CFD cell centres — exact locations where OpenFOAM computed field values.
12
- 3. **Coordinate normalisation**: Local per-run, zero mean and unit std per axis. Stored in each file for unnormalisation.
13
- 4. **Target fields**: Raw, no normalisation. All 500 runs share identical CFD boundary conditions.
 
 
 
 
 
 
 
 
 
 
 
 
 
14
 
15
  ## File Structure
16
 
17
- Each run: `run_i/boundary_i.pt`
 
 
 
 
 
 
 
 
 
 
 
 
18
 
19
  ```python
20
  {
@@ -29,16 +76,27 @@ Each run: `run_i/boundary_i.pt`
29
 
30
  ## Target Field Order
31
 
32
- | Index | Field | Units | Description |
33
- |-------|-------|-------|-------------|
34
- | 0 | CpMeanTrim | [-] | Time-averaged static pressure coefficient |
35
- | 1 | pMeanTrim | [m²/s²] | Time-averaged kinematic pressure |
36
- | 2 | pPrime2MeanTrim | [m⁴/s⁴] | Time-averaged square of pressure fluctuations |
37
- | 3 | wallShearStressMeanTrim | [m²/s²] | Magnitude of time-averaged wall shear stress vector |
 
 
38
 
39
- ## Missing Runs
 
 
 
 
 
40
 
41
- `167, 211, 218, 221, 248, 282, 291, 295, 316, 325, 329, 364, 370, 376, 403, 473`
 
 
 
 
42
 
43
  ## Citation
44
 
 
1
+ ---
2
+ license: cc-by-sa-4.0
3
+ task_categories:
4
+ - other
5
+ tags:
6
+ - CFD
7
+ - aerodynamics
8
+ - point-cloud
9
+ - pytorch
10
+ - fluid-dynamics
11
+ - regression
12
+ size_categories:
13
+ - 100K<n<1M
14
+ splits:
15
+ train:
16
+ num_examples: 387
17
+ validation:
18
+ num_examples: 48
19
+ test:
20
+ num_examples: 49
21
+ ---
22
+
23
  # DrivaerML-PCTR
24
 
25
  Processed version of [neashton/drivaerml](https://huggingface.co/datasets/neashton/drivaerml)
 
29
 
30
  Each `boundary_i.vtp` file (~500MB, ~8.8M cells) was processed as follows:
31
 
32
+ 1. **Random sampling:** 100,000 cells per run, fixed seed `seed = run_id + 42`.
33
+ 2. **Cell centres:** Coordinates are CFD cell centres — exact locations where OpenFOAM computed field values.
34
+ 3. **Coordinate normalisation:** Local per-run, zero mean and unit std per axis. Stored in each file for unnormalisation.
35
+ 4. **Target fields:** Raw, no normalisation. All 500 runs share identical CFD boundary conditions.
36
+
37
+ ## Dataset Splits
38
+
39
+ The dataset is split **80/10/10** (train/val/test) using a random shuffle with `seed=42`.
40
+
41
+ | Split | Runs |
42
+ |------------|------|
43
+ | Train | 387 |
44
+ | Validation | 48 |
45
+ | Test | 49 |
46
+ | **Total** | **484** |
47
+
48
+ > **Missing runs:** `167, 211, 218, 221, 248, 282, 291, 295, 316, 325, 329, 364, 370, 376, 403, 473`
49
 
50
  ## File Structure
51
 
52
+ ```
53
+ train/
54
+ run_i/
55
+ boundary_i.pt
56
+ val/
57
+ run_i/
58
+ boundary_i.pt
59
+ test/
60
+ run_i/
61
+ boundary_i.pt
62
+ ```
63
+
64
+ Each `.pt` file contains:
65
 
66
  ```python
67
  {
 
76
 
77
  ## Target Field Order
78
 
79
+ | Index | Field | Units | Description |
80
+ |-------|------------------------|-----------|----------------------------------------------------------|
81
+ | 0 | `CpMeanTrim` | [-] | Time-averaged static pressure coefficient |
82
+ | 1 | `pMeanTrim` | [m²/s²] | Time-averaged kinematic pressure |
83
+ | 2 | `pPrime2MeanTrim` | [m⁴/s⁴] | Time-averaged square of pressure fluctuations |
84
+ | 3 | `wallShearStressMeanTrim` | [m²/s²] | Magnitude of time-averaged wall shear stress vector |
85
+
86
+ ## Loading the Dataset
87
 
88
+ ```python
89
+ from huggingface_hub import snapshot_download
90
+ import torch, os
91
+
92
+ # Download the full dataset
93
+ local_dir = snapshot_download(repo_id="Jrhoss/DrivaerML-PCTR", repo_type="dataset")
94
 
95
+ # Load a single run from the training split
96
+ data = torch.load(os.path.join(local_dir, "train", "run_1", "boundary_1.pt"))
97
+ print(data['coords'].shape) # [100000, 3]
98
+ print(data['targets'].shape) # [100000, 4]
99
+ ```
100
 
101
  ## Citation
102
 
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test/run_72/boundary_72.pt ADDED
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test/run_80/boundary_80.pt ADDED
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test/run_82/boundary_82.pt ADDED
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