Datasets:

MIGRATE
/

Surfdisp96-Roccastrada-10k-2025

@@ -1,6 +1,6 @@
 ---
 license: cc-by-sa-4.0
-pretty_name: sd96-roccastrada-10m
 task_categories:
 - other
 language:
@@ -14,102 +14,162 @@ tags:
 - inverse-problem
 size_categories:
 - 10K<n<100K
 ---
-## Dataset Overview
-The dataset contains seismic models and their corresponding dispersion curves generated using the SurfDisp96 simulation. Each sample in the dataset includes:
-1. A seismic velocity model with parameters like shear wave velocities, depths, and layer thicknesses
-2. Three dispersion curves for different period ranges (low, middle, and high)
-## Prior
-This dataset was generated with the Roccastrada prior:
-| Parameter | Value    | Description                               |
-|-----------|----------|-------------------------------------------|
-| Vs        | 0.5, 4.0 | Range of shear velocities (km/s)          |
-| z         | 0.0, 5.0 | Min and max depth (km) of Voronoi kernels |
-| layers    | 2, 20    | Min/max of the number of layers           |
-| vpvs      | 1.3      | Ratio VP/VS                               |
-| mohoest   | null     | Add a mohoest layer ?                     |
-| mantle    | null     |                                           |
-| thickmin  | 0.1      | Layer minimum thickness                   |
-| lvz       | null     | Low velocity zone                         |
-| hvz       | null     | High velocity zone                        |
-## Column Descriptions
-| Column Name | Data Type | Description | Possible Values |
-|-------------|-----------|-------------|----------------|
 | **Model Parameters** |
-| `vs` | List[float32] | Shear wave velocities for each layer in km/s | Typically 0.5-5.0 km/s, depends on prior |
-| `z` | List[float32] | Depths of layer middle points (middle points between layer boundaries) in km | Depends on the prior configuration, typically 0-15 km |
-| `h` | List[float32] | Layer thicknesses in km | Depends on the prior configuration |
-| `z_disc` | List[float32] | Depths of discontinuities (changes in Vs) in km | Depends on the prior configuration |
-| `vp` | List[float32] | P-wave velocities for each layer in km/s | Typically 1.5-8.5 km/s (depends on prior) |
-| `vpvs` | float | VP/VS ratio (ratio of P-wave to S-wave velocity) | Typically 1.7-1.9 (depends on prior) |
-| `nlayers` | int | Number of layers in the model | Depends on the prior configuration |
-| `velmap_vs` | List[float32] | Shear wave velocity profile transformed from the Voronoi model to a layered model | Typically 0.5-5.0 km/s |
-| `velmap_z` | List[float32] | Corresponding depths for the layered model | Typically 0-15 km with 60 evenly spaced points |
 | **Low Range Dispersion Curve** |
-| `L_disp_x` | List[float32] | Periods (T) in seconds for the low range dispersion curve | Defined by `low_range` parameter, typically 0.1-1.0 s |
-| `L_disp_y` | List[float32] | Corresponding velocities in km/s for the low range dispersion curve | Typically 0.5-3.0 km/s |
-| `L_wave_type` | string | Type of seismic wave for the low range dispersion curve | "Rayleigh" or "Love" |
-| `L_velocity_type` | string | Type of velocity measurement for the low range dispersion curve | "group" or "phase" |
 | **Middle Range Dispersion Curve** |
-| `M_disp_x` | List[float32] | Periods (T) in seconds for the middle range dispersion curve | Defined by `middle_range` parameter, typically 1.0-10.0 s |
-| `M_disp_y` | List[float32] | Corresponding velocities in km/s for the middle range dispersion curve | Typically 1.0-3.5 km/s |
-| `M_wave_type` | string | Type of seismic wave for the middle range dispersion curve | "Rayleigh" or "Love" |
-| `M_velocity_type` | string | Type of velocity measurement for the middle range dispersion curve | "group" or "phase" |
 | **High Range Dispersion Curve** |
-| `H_disp_x` | List[float32] | Periods (T) in seconds for the high range dispersion curve | Defined by `high_range` parameter, typically 10.0-40.0 s |
-| `H_disp_y` | List[float32] | Corresponding velocities in km/s for the high range dispersion curve | Typically 2.0-4.0 km/s |
-| `H_wave_type` | string | Type of seismic wave for the high range dispersion curve | "Rayleigh" or "Love" |
-| `H_velocity_type` | string | Type of velocity measurement for the high range dispersion curve | "group" or "phase" |
-## Notes
-1. All numerical arrays are stored as lists of float32 values to optimize storage space.
-2. The dispersion curves represent the relationship between period (T) and velocity (v) for seismic waves.
-3. The low, middle, and high ranges refer to different period ranges for the dispersion curves, allowing for multi-scale analysis of the seismic model.
-4. The wave type is typically "Rayleigh" for surface waves.
-5. The velocity type is typically "group" for group velocity dispersion curves.
-6. The exact ranges for periods depend on the `low_range`, `middle_range`, and `high_range` parameters provided to the `generate_dataset_surfdisp96` function.
-7. The number of points in each dispersion curve is determined by the `length` parameter.
-8. If `variable_grid` is set to True, the periods may not be evenly spaced, with the minimum difference between consecutive periods defined by the third element of the range tuples.
-## Usage Example
-This dataset can be used for various seismic inversion tasks, such as:
-1. Inferring subsurface velocity structures from observed dispersion curves
-2. Training machine learning models to predict dispersion curves from velocity models (forward problem)
-3. Training machine learning models to predict velocity models from dispersion curves (inverse problem)
-4. Studying the sensitivity of dispersion curves to changes in velocity model parameters
-## Sample Visualization
-The dataset includes a visualization of a sample model and its dispersion curves. You can find this visualization in the `sample_plot.png` file in the dataset directory.
 ![Sample Plot](sample_plot.png)
-## Generation Steps
-The dataset was generated using the following commands:
 ```bash
-python3 migrate/cli/main.py generate-dataset-surfdisp96 --name Surfdisp96-Roccastrada-10m --pretty-name sd96-roccastrada-10m --description "This dataset contains synthetic seismic models and their corresponding Rayleigh-wave dispersion curves generated using forward modeling with the Roccastrada priors. It is designed for benchmarking inversion algorithms and training machine learning models in geophysics." license-name "other" --created-by "" --prior-file /datadisk/Projets/RECHERCHES/Recherches/MIGRATE/reps/migrate/conf/priors/roccastrada_prior.yaml --output-dir "/datadisk/Projets/RECHERCHES/Recherches/MIGRATE/reps/migrate/data/seismic/Dispsurf96-Roccastrada-10k" --n-samples 10000 --samples-per-shard 1000 --length 108 --test-ratio 0.2 --fold (2, 5, 10) --seed 43 --low-range 1.0,5.0 --middle-range 1.0,15.0 --high-range 1.0,30.0
 ```
-## Download Instructions
-You can download the dataset via the 🤗 Hub CLI:
-```bash
-huggingface-cli download dataset <repo-id> --local-dir ./seismic-dataset
-```
-Or use `datasets` in Python:
-```python
-from datasets import load_dataset
-ds = load_dataset('<repo-id>', split='train')
-```

 ---
 license: cc-by-sa-4.0
+pretty_name: sd96-roccastrada-10k
 task_categories:
 - other
 language:
 - inverse-problem
 size_categories:
 - 10K<n<100K
+format: parquet
+creation_date: "2025-09-16 15:39:27"
+created_by: "Nils Schaetti"
+organization: "DMML – Data Mining and Machine Learning Group, Haute École de Gestion de Genève (HES-SO)"
+contact: "nils.schaetti@hesge.ch"
+citation: |
+  Schaetti, N. (2025). *MIGRATE Synthetic Seismic Dataset – Surfdisp96-Roccastrada-10m*.
+  DMML – Data Mining and Machine Learning Group, Haute École de Gestion de Genève (HES-SO).
+  Licensed under CC BY-SA 4.0.
 ---
+# 🧠 Dataset Overview
+The **Surfdisp96-Roccastrada-10m** dataset contains **synthetic seismic velocity models** and their corresponding **Rayleigh-wave dispersion curves**, generated using the **SurfDisp96** simulator with **Roccastrada priors**.
+It is designed for benchmarking **seismic inversion algorithms** and for training **machine-learning models** in geophysics.
+Each sample includes:
+1. A **seismic velocity model** with shear-wave velocities, depths and layer thicknesses
+2. Three **dispersion curves** covering low, middle and high period ranges
+# 🔢 Priors Configuration (Roccastrada)
+| Parameter | Value | Description |
+|-----------|--------|-------------|
+| `vs` | [0.5, 4.0] | Range of shear-wave velocities (km/s) |
+| `z` | [0.0, 5.0] | Depth range (km) |
+| `layers` | [2, 20] | Minimum and maximum number of layers |
+| `vpvs` | 1.3 | P/S velocity ratio |
+| `mohoest` | null | Estimated Moho depth (unused) |
+| `mantle` | null | Mantle properties (unused) |
+| `thickmin` | 0.1 | Minimum layer thickness (km) |
+| `lvz` | null | Low-velocity zone (not used) |
+| `hvz` | null | High-velocity zone (not used) |
+# ⚙️ Generation Parameters
+| Parameter | Value | Description |
+|------------|--------|-------------|
+| `seed` | 43 | Random seed for reproducibility |
+| `random_generator` | numpy.default_rng | Random number generator backend |
+| `n_samples` | 10 000 | Total synthetic models |
+| `samples_per_shard` | 1 000 | Number of samples per Parquet shard |
+| `n_shards` | 10 | Total number of shards |
+| `source` | sample_model + forward | Data generation process |
+| `dispersion_curve_length` | 108 | Number of points per dispersion curve |
+| `folds` | 2-fold, 5-fold, 10-fold | Available cross-validation splits |
+| `fold_file` | folds.json | JSON file defining the folds |
+# 🧩 Feature Schema
+| Feature | Type | Description |
+|----------|------|-------------|
+| `vs` | list<float32> | Shear-wave velocities (km/s), one per layer |
+| `z` | list<float32> | Depths of layer boundaries (km) |
+| `vpvs` | float32 | Vp/Vs ratio |
+| `disp_x` | list<float32> | Period values (s), length = 108 |
+| `disp_y` | list<float32> | Corresponding velocities (km/s), length = 108 |
+| `wave_type` | string | Type of surface wave (Rayleigh / Love) |
+| `velocity_type` | string | Velocity measurement type (group / phase) |
+# 📊 Column Descriptions
+| Column Name | Data Type | Description | Typical Values |
+|--------------|-----------|--------------|----------------|
 | **Model Parameters** |
+| `vs` | list<float32> | Shear-wave velocities (km/s) | 0.5–5.0 |
+| `z` | list<float32> | Layer-center depths (km) | 0–15 |
+| `h` | list<float32> | Layer thicknesses (km) | depends on prior |
+| `z_disc` | list<float32> | Discontinuity depths (km) | depends on prior |
+| `vp` | list<float32> | P-wave velocities (km/s) | 1.5–8.5 |
+| `vpvs` | float32 | Vp/Vs ratio | 1.3 |
+| `nlayers` | int | Number of layers | 2–20 |
+| `velmap_vs` | list<float32> | Interpolated Vs profile (60 points) | 0.5–5.0 |
+| `velmap_z` | list<float32> | Depth grid for `velmap_vs` | 0–15 km |
 | **Low Range Dispersion Curve** |
+| `L_disp_x` | list<float32> | Periods (s) | 0.1–1.0 |
+| `L_disp_y` | list<float32> | Velocities (km/s) | 0.5–3.0 |
+| `L_wave_type` | string | Wave type | Rayleigh / Love |
+| `L_velocity_type` | string | Velocity type | group / phase |
 | **Middle Range Dispersion Curve** |
+| `M_disp_x` | list<float32> | Periods (s) | 1.0–10.0 |
+| `M_disp_y` | list<float32> | Velocities (km/s) | 1.0–3.5 |
+| `M_wave_type` | string | Wave type | Rayleigh / Love |
+| `M_velocity_type` | string | Velocity type | group / phase |
 | **High Range Dispersion Curve** |
+| `H_disp_x` | list<float32> | Periods (s) | 10.0–40.0 |
+| `H_disp_y` | list<float32> | Velocities (km/s) | 2.0–4.0 |
+| `H_wave_type` | string | Wave type | Rayleigh / Love |
+| `H_velocity_type` | string | Velocity type | group / phase |
+# 🧭 Notes
+1. All arrays are stored as `float32` to reduce storage size.
+2. Dispersion curves represent the relationship between **period (T)** and **velocity (v)** for seismic surface waves.
+3. Low, middle and high ranges enable **multi-scale analysis** of the subsurface structure.
+4. Default wave type = “Rayleigh”, velocity type = “group”.
+5. Period ranges and grid spacing depend on generation parameters (`low_range`, `middle_range`, `high_range`, `variable_grid`).
+6. Folds allow robust cross-validation (2, 5, 10 folds).
+# 🧮 Usage Example
+### With 🤗 Datasets
+```python
+from datasets import load_dataset
+ds = load_dataset("nils-schaetti/sd96-roccastrada-10m", split="train")
+print(ds[0]["vs"])  # Access shear-wave velocity model
+````
+### Via CLI
+```bash
+huggingface-cli download dataset nils-schaetti/sd96-roccastrada-10m --local-dir ./sd96-roccastrada-10m
+```
+# 🖼️ Sample Visualization
+A sample model and its three dispersion curves are illustrated in **sample_plot.png** within the dataset directory.
 ![Sample Plot](sample_plot.png)
+# ⚙️ Generation Command
 ```bash
+python3 migrate/cli/main.py generate-dataset-surfdisp96 \
+  --name Surfdisp96-Roccastrada-10m \
+  --pretty-name sd96-roccastrada-10m \
+  --description "This dataset contains synthetic seismic models and their corresponding Rayleigh-wave dispersion curves generated using forward modeling with the Roccastrada priors. It is designed for benchmarking inversion algorithms and training machine learning models in geophysics." \
+  --license-name "CC BY-SA 4.0" \
+  --created-by "Nils Schaetti" \
+  --prior-file conf/priors/roccastrada_prior.yaml \
+  --output-dir data/seismic/Dispsurf96-Roccastrada-10k \
+  --n-samples 10000 \
+  --samples-per-shard 1000 \
+  --length 108 \
+  --test-ratio 0.2 \
+  --folds 2 5 10 \
+  --seed 43 \
+  --low-range 1.0 5.0 \
+  --middle-range 1.0 15.0 \
+  --high-range 1.0 30.0
 ```
+# 🧾 License
+This dataset is released under the **Creative Commons Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)** license.
+© 2025 Nils Schaetti
+DMML – Data Mining and Machine Learning Group
+Haute École de Gestion de Genève (HES-SO)
+📧 [nils.schaetti@hesge.ch](mailto:nils.schaetti@hesge.ch)
+You are free to use, share, and adapt this dataset for any purpose, including commercial use, provided that you:
+* **Attribute** the creator (Nils Schaetti, DMML Group, HEG Genève)
+* **Share-alike** any derivative work under the same license (CC BY-SA 4.0)
+[![License: CC BY-SA 4.0](https://licensebuttons.net/l/by-sa/4.0/88x31.png)](https://creativecommons.org/licenses/by-sa/4.0/)