bsfit.nodes.cirpy.data.VonMises¶

class bsfit.nodes.cirpy.data.VonMises(p: bool)[source]¶

Bases: object

Von Mises class

__init__(p: bool)[source]¶

instantiate von mises

\[V(x,u,k) = e^{k.cos(x-u)}/(2\pi.besseli(0,k))\]

Parameters: p (bool) – True (for probability) or False (for function)

Methods

`__init__`(p)	instantiate von mises
`get`(v_x, v_u, v_k)	generate von Mises functions or probability densities

get(v_x: numpy.array, v_u: numpy.array, v_k: list)[source]¶

generate von Mises functions or probability densities

Parameters

v_x (np.array) – von mises’ support space
v_u (np.array) – von mises’ mean
v_k (list) – von mises’ concentration

Usage:

v_x = np.arange(0,360,1)
v_u = np.array([0,90,180,270])
v_k = [2.7, 2.7, 2.7, 2.7]
von_mises = VonMises(p=True)
von_mises = von_mises.get(v_x, v_u, v_k)

Returns: von mises functions or probability densities
Return type: (np.ndarray)