Handling data (corneto.data)#

Simple datasets (Data and Sample)#

corneto.data.Data([samples])

A container for multiple labeled samples.

corneto.data.Sample([features])

A collection of unique features.

Modules#

corneto.data.util

Utility functions for data generation.

Data handling utilities for CORNETO#

This module provides the feature-aware data containers used by CORNETO’s methods and algorithms.

Classes#

  • Data: Main data container that maps sample IDs to samples

  • Sample: Container for feature objects and their metadata

  • Feature: A value and its graph mapping metadata

  • GraphData: A serializable graph and data bundle

Key Features#

  • Rich metadata support for data features

  • Flexible data import/export methods

  • Conversion between different data formats

  • Filtering and subsetting capabilities

  • Data manipulation and transformation utilities

Examples:#

Basic usage with Data and Sample classes:

>>> from corneto.data import Data
>>> dataset = Data.from_cdict({
...     "patient1": {
...         "treatment": {"value": "drugA", "mapping": "vertex", "dose": "high"}
...     }
... })
>>> print(dataset)
Data(n_samples=1, n_feats=[1])

>>> # Convert to dictionary format
>>> data_dict = dataset.to_dict()
>>> print(data_dict["patient1"]["features"][0]["value"])
drugA

Utilities#

The package also provides utility functions for generating random data:

>>> from corneto.data.util import generate_random_signalling_network
>>> # Generate a random signaling network
>>> network = generate_random_signalling_network(n=10, m=3, p_inhibitory=0.3)
>>> print(f"Generated network with {len(network)} edges")