---
license: mit
tags:
- gravitational-waves
- dingo
- waveforms
- sbi
pretty_name: DINGO-T1 25M waveform dataset
---

# DINGO-T1 waveform dataset — 25M (IMRPhenomXPHM, multibanded FD, SVD-200)

25,000,000 frequency-domain precessing-BBH waveforms generated with the `dingo` pipeline,
matching the DINGO-T1 (arXiv:2512.02968) data setup.

- **Approximant:** IMRPhenomXPHM (precession + higher modes), `f_ref = 20 Hz`
- **Domain:** `MultibandedFrequencyDomain`, f ∈ [20, 1810] Hz, base `δf = 0.125` → 1104 MFD bins
- **Compression:** whitening (`aLIGO_ZERO_DET_high_P_asd.txt`) + SVD basis size **200** per polarization
- **Intrinsic prior:** chirp_mass U(15,150) M☉, q U(0.125,1), |a₁|,|a₂| < 0.99 (precessing), isotropic angles
- **Sharding:** 5 files × 5M each — `dataset_part_0..4.hdf5`, ~31 GB/shard (~155 GB total).
  Each shard is a **self-contained** dingo `WaveformDataset` (same SVD basis + settings embedded).

## Files
- `dataset_part_{0..4}.hdf5` — the 5 shards (5M waveforms each)
- `svd.hdf5` — the shared SVD basis (also embedded in each shard)
- `settings.yaml` — exact generation settings

## Usage
Load any shard directly:
```python
from dingo.gw.dataset import WaveformDataset
wfd = WaveformDataset(file_name="dataset_part_0.hdf5")
```
Merge all 5 into a single training file (needs ~160 GB RAM):
```bash
dingo_merge_datasets --prefix dataset_part_ --num_parts 5 --out_file waveform_dataset.hdf5
```