latents.data

Observation data containers for latent variable models.

Classes

ObsStatic	Store and manipulate views of observed static data.
ObsTimeSeries	Store and manipulate views of observed time series data.

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class ObsStatic(data: ndarray, dims: ndarray)

Store and manipulate views of observed static data.

Parameters:

datandarray of float, shape (y_dim, n_samples)

Observed data. Groups are stacked vertically. For example, if there are three groups with dimensionalities 2, 3, and 4, then data is a ndarray of shape (9, n_samples), and data[:2, :] contains the first group, data[2:5, :] contains the second group, and data[5:, :] contains the third group.

dimsndarray of int, shape (n_groups,)

Dimensionalities of each observed group.

Attributes:

datandarray of float, shape (y_dim, n_samples)

Observed data. Groups are stacked vertically.

dimsndarray of int, shape (n_groups,)

Dimensionalities of each observed group.

Raises:

TypeError

If data or dims is not a ndarray.

ValueError

If the sum of dims does not equal the number of rows in data.

Examples

Create observation data with two groups (3 and 2 dimensions):

>>> import numpy as np
>>> from latents.data import ObsStatic
>>> data = np.random.randn(5, 100)  # 5 total dims, 100 samples
>>> dims = np.array([3, 2])  # Group 1 has 3 dims, group 2 has 2
>>> Y = ObsStatic(data, dims)
>>> Y
ObsStatic(data.shape=(5, 100), dims=[3 2])

Access data for each group separately:

>>> groups = Y.get_groups()
>>> groups[0].shape  # First group
(3, 100)
>>> groups[1].shape  # Second group
(2, 100)

get_groups() → list[ndarray]

Return a list of views of the observed data, one for each group.

Returns:

list of ndarray

Views of the observed data, one per group, length n_groups.

class ObsTimeSeries

Store and manipulate views of observed time series data.

Stub for future implementation.

Raises:

NotImplementedError

Always raised; this class is a placeholder for future implementation.