KMatrix

class glotaran.builtin.megacomplexes.decay.k_matrix.KMatrix(*, label: str, matrix: dict[tuple[str, str], Parameter | str])

Bases: ModelItem

A K-Matrix represents a first order differental system.

Method generated by attrs for class KMatrix.

Attributes Summary

matrix
label

Methods Summary

a_matrix	The A matrix of the KMatrix.
a_matrix_as_markdown	Returns the A Matrix as markdown formatted table.
a_matrix_general	The A matrix of the KMatrix for a general model.
a_matrix_sequential	The A matrix of the KMatrix for a sequential model.
combine	Creates a combined matrix.
eigen	Returns the eigenvalues and eigenvectors of the k matrix.
empty	Creates an empty K-Matrix.
full	The full representation of the KMatrix as numpy array.
involved_compartments	A list of all compartments in the Matrix.
is_sequential	Returns true in the KMatrix represents an unibranched model.
matrix_as_markdown	Returns the KMatrix as markdown formatted table.
rates	The resulting rates of the matrix.
reduced	The reduced representation of the KMatrix as numpy array.

Methods Documentation

a_matrix(compartments: list[str], initial_concentration: ndarray) → ndarray

The A matrix of the KMatrix.

Parameters:

initial_concentration – The initial concentration.

a_matrix_as_markdown(compartments: list[str], initial_concentration: ndarray) → MarkdownStr

Returns the A Matrix as markdown formatted table.

Parameters:

initial_concentration – The initial concentration.

a_matrix_general(compartments: list[str], initial_concentration: ndarray) → ndarray

The A matrix of the KMatrix for a general model.

Parameters:

initial_concentration – The initial concentration.

a_matrix_sequential(compartments: list[str]) → ndarray

The A matrix of the KMatrix for a sequential model.

Parameters:

initial_concentration – The initial concentration.

combine(k_matrix: KMatrix) → KMatrix

Creates a combined matrix.

When combining k-matrices km1 and km2 (km1.combine(km2)), entries in km1 will be overwritten by corresponding entries in km2.

Parameters:

k_matrix – KMatrix to combine with.

Returns:

The combined KMatrix.

Return type:

combined

eigen(compartments: list[str]) → tuple[ndarray, ndarray]

Returns the eigenvalues and eigenvectors of the k matrix.

Parameters:

compartments – The compartment order.

classmethod empty(label: str, compartments: list[str]) → KMatrix

Creates an empty K-Matrix. Useful for combining.

Parameters:

• label – Label of the K-Matrix

• compartments – A list of all compartments in the model.

full(compartments: list[str]) → ndarray

The full representation of the KMatrix as numpy array.

Parameters:

compartments – The compartment order.

involved_compartments() → list[str]

A list of all compartments in the Matrix.

is_sequential(compartments: list[str], initial_concentration: ndarray) → bool

Returns true in the KMatrix represents an unibranched model.

Parameters:

initial_concentration – The initial concentration.

label: str

matrix: dict[tuple[str, str], Parameter | str]

matrix_as_markdown(compartments: list[str] | None = None, fill_parameters: bool = False) → MarkdownStr

Returns the KMatrix as markdown formatted table.

Parameters:

• compartments – (default = None) An optional list defining the desired order of compartments.

• fill_parameters (bool) – (default = False) If true, the entries will be filled with the actual parameter values instead of labels.

rates(compartments: list[str], initial_concentration: ndarray) → ndarray

The resulting rates of the matrix.

By definition, the eigenvalues of the compartmental model are negative and the rates are the negatives of the eigenvalues, thus the eigenvalues need to be multiplied with -1 to get rates with the correct sign.

Parameters:

• compartments (list[str]) – Names of compartment used to order the matrix.

• initial_concentration (np.ndarray) – The initial concentration.

reduced(compartments: list[str]) → ndarray

The reduced representation of the KMatrix as numpy array.

Parameters:

compartments – The compartment order.