`np2ds`¶

Convert a NumPy array into a URANIE DataServer object.

converter.np2ds(mat, attrib_names, name="", title="")

Parameters:

Parameter	Type	Description
`mat`	`numpy.ndarray`	Input array with shape `(n_samples, n_attributes)`. 1-D arrays are automatically reshaped to `(1, n_features)`.
`attrib_names`	`str`	Colon-separated attribute names, e.g., `"x1:x2:x3"`. Length must match `mat.shape[1]`.
`name`	`str`	Name for the DataServer object (optional, default: `""`).
`title`	`str`	Title for the DataServer object (optional, default: `""`).

Returns:

Type	Description
`DataServer.TDataServer`	A DataServer object with attributes populated from the array columns.

Example¶

import numpy as np
from uratools import converter

# Create data
X = np.random.randn(100, 3)

# Convert to DataServer
tds = converter.np2ds(X, "x1:x2:x3", name="samples", title="Random samples")

print(f"Patterns: {tds.getNPatterns()}")   # 100
print(f"Attributes: {tds.getNAttributes()}")  # 3

Use Cases¶

Prepare NumPy data for URANIE sampling workflows
Convert preprocessed data into URANIE format
Create DataServer objects from external data sources (CSV, HDF5, etc.)