# `ds2np`

Convert a URANIE DataServer object into a NumPy array.

```python
converter.ds2np(tds)
```

**Parameters:**

| Parameter | Type | Description |
|-----------|------|-------------|
| `tds` | `DataServer.TDataServer` | The DataServer object to convert. |

**Returns:**

| Type | Description |
|------|-------------|
| `numpy.ndarray` | A 2-D array with shape `(n_samples, n_attributes)`. |

## Example

```python
import numpy as np
from uratools import converter
from ROOT.URANIE import DataServer, Sampler

# Create a DataServer with samples
tds = DataServer.TDataServer("example", "Example")
tds.addAttribute(DataServer.TUniformDistribution("x1", 0.0, 10.0))
tds.addAttribute(DataServer.TUniformDistribution("x2", 0.0, 10.0))

# Generate samples using LHS
sam = Sampler.TSampling(tds, "lhs", 50)
sam.generateSample()

# Convert to NumPy for analysis
X = converter.ds2np(tds)

print(f"Shape: {X.shape}")  # (50, 2)
print(f"Mean:\n{np.mean(X, axis=0)}")
print(f"Std:\n{np.std(X, axis=0)}")
```

## Use Cases

- Extract DataServer results for analysis in Python (pandas, matplotlib, scikit-learn)

## Notes

- **Data preservation**: Only data values are preserved. Distribution metadata is lost during conversion.