# Training Data (Unit-Corrected)

This directory contains molecular data with **corrected units** ready for DCMnet/PhysnetJax training.

## Data Corrections Applied

### 1. Atomic Coordinates (R)
- **Original**: Angstroms (verified)
- **Status**: ✓ Correct
- **Units**: Angstrom (ASE standard)

### 2. Energies (E)
- **Original**: Hartree
- **Converted**: eV (ASE standard)
- **Factor**: ×27.211386

### 3. Forces (F)
- **Original**: Hartree/Bohr
- **Converted**: eV/Angstrom (ASE standard)
- **Factor**: ×51.42208

## Data Splits

- **Train**: 5600 samples (80%)
- **Valid**: 700 samples (10%)
- **Test**: 701 samples (10%)
- **Seed**: 42 (reproducible)

## Files

### Energy, Forces, and Dipoles
- `energies_forces_dipoles_train.npz`
- `energies_forces_dipoles_valid.npz`
- `energies_forces_dipoles_test.npz`

Each contains:
- `R`: Atomic coordinates [Angstrom]
- `Z`: Atomic numbers [int]
- `N`: Number of atoms [int]
- `E`: Energies [eV] ← CONVERTED from Hartree
- `F`: Forces [eV/Angstrom] ← CONVERTED from Hartree/Bohr
- `Dxyz`: Dipole moments [e·Å] ← CONVERTED from Debye

## Units Summary (ASE Standard)

| Property | Unit | Status |
|----------|------|--------|
| R (coordinates) | Angstrom | ✓ Correct |
| E (energy) | eV | ✓ Converted |
| F (forces) | eV/Angstrom | ✓ Converted |
| Dxyz (dipoles) | e·Å | ✓ Converted from Debye |

## Usage

```python
import numpy as np

# Load training data
train_props = np.load('energies_forces_dipoles_train.npz')

# All units are ASE-standard - ready to use!
R = train_props['R']  # Angstroms
E = train_props['E']  # eV
F = train_props['F']  # eV/Angstrom
Dxyz = train_props['Dxyz']  # e·Å (converted from Debye)

Generated by: mmml.cli.fix_and_split