package scipy

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package scipy
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Class type
type tag = [
  1. | `IterOpInv
]
type t = [ `IterOpInv | `Object ] Obj.t
val of_pyobject : Py.Object.t -> t
val to_pyobject : [> tag ] Obj.t -> Py.Object.t
val create : ?kwargs:(string * Py.Object.t) list -> Py.Object.t list -> t

IterOpInv: helper class to repeatedly solve A-sigma*M*x = b using an iterative method

val adjoint : [> tag ] Obj.t -> Py.Object.t

Hermitian adjoint.

Returns the Hermitian adjoint of self, aka the Hermitian conjugate or Hermitian transpose. For a complex matrix, the Hermitian adjoint is equal to the conjugate transpose.

Can be abbreviated self.H instead of self.adjoint().

Returns ------- A_H : LinearOperator Hermitian adjoint of self.

val dot : x:[> `Ndarray ] Np.Obj.t -> [> tag ] Obj.t -> [ `ArrayLike | `Ndarray | `Object ] Np.Obj.t

Matrix-matrix or matrix-vector multiplication.

Parameters ---------- x : array_like 1-d or 2-d array, representing a vector or matrix.

Returns ------- Ax : array 1-d or 2-d array (depending on the shape of x) that represents the result of applying this linear operator on x.

val matmat : x:Py.Object.t -> [> tag ] Obj.t -> Py.Object.t

Matrix-matrix multiplication.

Performs the operation y=A*X where A is an MxN linear operator and X dense N*K matrix or ndarray.

Parameters ---------- X : matrix, ndarray An array with shape (N,K).

Returns ------- Y : matrix, ndarray A matrix or ndarray with shape (M,K) depending on the type of the X argument.

Notes ----- This matmat wraps any user-specified matmat routine or overridden _matmat method to ensure that y has the correct type.

val matvec : x:Py.Object.t -> [> tag ] Obj.t -> Py.Object.t

Matrix-vector multiplication.

Performs the operation y=A*x where A is an MxN linear operator and x is a column vector or 1-d array.

Parameters ---------- x : matrix, ndarray An array with shape (N,) or (N,1).

Returns ------- y : matrix, ndarray A matrix or ndarray with shape (M,) or (M,1) depending on the type and shape of the x argument.

Notes ----- This matvec wraps the user-specified matvec routine or overridden _matvec method to ensure that y has the correct shape and type.

val rmatmat : x:Py.Object.t -> [> tag ] Obj.t -> Py.Object.t

Adjoint matrix-matrix multiplication.

Performs the operation y = A^H * x where A is an MxN linear operator and x is a column vector or 1-d array, or 2-d array. The default implementation defers to the adjoint.

Parameters ---------- X : matrix, ndarray A matrix or 2D array.

Returns ------- Y : matrix, ndarray A matrix or 2D array depending on the type of the input.

Notes ----- This rmatmat wraps the user-specified rmatmat routine.

val rmatvec : x:Py.Object.t -> [> tag ] Obj.t -> Py.Object.t

Adjoint matrix-vector multiplication.

Performs the operation y = A^H * x where A is an MxN linear operator and x is a column vector or 1-d array.

Parameters ---------- x : matrix, ndarray An array with shape (M,) or (M,1).

Returns ------- y : matrix, ndarray A matrix or ndarray with shape (N,) or (N,1) depending on the type and shape of the x argument.

Notes ----- This rmatvec wraps the user-specified rmatvec routine or overridden _rmatvec method to ensure that y has the correct shape and type.

val transpose : [> tag ] Obj.t -> Py.Object.t

Transpose this linear operator.

Returns a LinearOperator that represents the transpose of this one. Can be abbreviated self.T instead of self.transpose().

val to_string : t -> string

Print the object to a human-readable representation.

val show : t -> string

Print the object to a human-readable representation.

val pp : Stdlib.Format.formatter -> t -> unit

Pretty-print the object to a formatter.