reservoirpy.mat_gen.orthogonal#

reservoirpy.mat_gen.orthogonal = <reservoirpy.mat_gen.Initializer (_orthogonal) object>[source]#

Create a random orthogonal matrix, drawn from the O(N) Haar distribution (the only uniform distribution on O(N)).

Note that the connectivity parameter in the Reservoir node has no effect with an orthogonal matrix initializer.

Parameters:

  • *shape ((int, int), optional) – Shape (row, columns) of the array. Must be a square matrix, i.e. row == columns.

  • sr (float, optional) – If defined, then will rescale the spectral radius of the matrix to this value.

  • input_scaling (float or array, optional) – If defined, then will rescale the matrix using this coefficient or array of coefficients.

  • dtype (numpy.dtype, default to numpy.float64) – A Numpy numerical type.

  • seed (optional) – Random generator seed. Default to the global value set with reservoirpy.set_seed().

  • **kwargs (optional) – This argument is kept for compatibility reasons. This is not used.

Returns:

If a shape is given to the initializer, then returns a matrix. Else, returns a function partially initialized with the given keyword parameters, which can be called with a shape and returns a matrix.

Return type:

numpy array or callable