_are_validate_args(a, b, q, r, e, s, eq_type='care')

Essentially, it performs:

• a check whether the input is free of NaN and Infs

• a pass for the data through numpy.atleast_2d()

• squareness check of the relevant arrays

• shape consistency check of the arrays

• singularity check of the relevant arrays

• symmetricity check of the relevant matrices

• a check whether the regular or the generalized version is asked.

This function is used by solve_continuous_are and solve_discrete_are .

Parameters

a, b, q, r, e, s : array_like

Input data

eq_type : str

Accepted arguments are 'care' and 'dare'.

Returns

a, b, q, r, e, s : ndarray

Regularized input data

m, n : int

shape of the problem

r_or_c : type

Data type of the problem, returns float or complex

gen_or_not : bool

Type of the equation, True for generalized and False for regular ARE.

A helper function to validate the arguments supplied to the Riccati equation solvers. Any discrepancy found in the input matrices leads to a ValueError exception.

Examples

See :

Local connectivity graph

Hover to see nodes names; edges to Self not shown, Caped at 50 nodes.

Using a canvas is more power efficient and can get hundred of nodes ; but does not allow hyperlinks; , arrows or text (beyond on hover)

SVG is more flexible but power hungry; and does not scale well to 50 + nodes.

All aboves nodes referred to, (or are referred from) current nodes; Edges from Self to other have been omitted (or all nodes would be connected to the central node "self" which is not useful). Nodes are colored by the library they belong to, and scaled with the number of references pointing them

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GitHub : /scipy/linalg/_solvers.py#737
type: <class 'function'>
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