sdeint/wiener.py
def Jkpw(dW, h, n=5):
    """matrix J approximating repeated Stratonovich integrals for each of N
    time intervals, based on the method of Kloeden, Platen and Wright (1992).

    Args:
      dW (array of shape (N, m)): giving m independent Weiner increments for
        each time step N. (You can make this array using sdeint.deltaW())
      h (float): the time step size
      n (int, optional): how many terms to take in the series expansion

    Returns:
      (A, J) where
        A: array of shape (N, m, m) giving the Levy areas that were used.
        J: array of shape (N, m, m) giving an m x m matrix of repeated
        Stratonovich integral values for each of the N time intervals.
    """
    m = dW.shape[1]
    A, I = Ikpw(dW, h, n)
    J = I + 0.5*h*np.eye(m).reshape((1, m, m))
    return (A, J)
matrix J approximating repeated Stratonovich integrals for each of N
    time intervals, based on the method of Kloeden, Platen and Wright (1992).

    Args:
      dW (array of shape (N, m)): giving m independent Weiner increments for
        each time step N. (You can make this array using sdeint.deltaW())
      h (float): the time step size
      n (int, optional): how many terms to take in the series expansion

    Returns:
      (A, J) where
        A: array of shape (N, m, m) giving the Levy areas that were used.
        J: array of shape (N, m, m) giving an m x m matrix of repeated
        Stratonovich integral values for each of the N time intervals.
    
matrix J approximating repeated Stratonovich integrals for each of N
time intervals, based on the method of Kloeden, Platen and Wright (1992).
matrix J approximating repeated Stratonovich integrals for each of N time intervals based on the method of Kloeden Platen and Wright ( 1992 ) .
def Jkpw(dW, h, n=5):
    m = dW.shape[1]
    A, I = Ikpw(dW, h, n)
    J = I + 0.5*h*np.eye(m).reshape((1, m, m))
    return (A, J)
def Jkpw ( dW , h , n = 5 ) : m = dW . shape [ 1 ] A , I = Ikpw ( dW , h , n ) J = I + 0.5 * h * np . eye ( m ) . reshape ( ( 1 , m , m ) ) return ( A , J )
matrix J approximating repeated Stratonovich integrals for each of N
time intervals, based on the method of Kloeden, Platen and Wright (1992).
matrix J approximating repeated Stratonovich integrals for each of N time intervals based on the method of Kloeden Platen and Wright ( 1992 ) .
"""matrix J approximating repeated Stratonovich integrals for each of N
    time intervals, based on the method of Kloeden, Platen and Wright (1992).

    Args:
      dW (array of shape (N, m)): giving m independent Weiner increments for
        each time step N. (You can make this array using sdeint.deltaW())
      h (float): the time step size
      n (int, optional): how many terms to take in the series expansion

    Returns:
      (A, J) where
        A: array of shape (N, m, m) giving the Levy areas that were used.
        J: array of shape (N, m, m) giving an m x m matrix of repeated
        Stratonovich integral values for each of the N time intervals.
    """
(A, J) where
A: array of shape (N, m, m) giving the Levy areas that were used.
J: array of shape (N, m, m) giving an m x m matrix of repeated
Stratonovich integral values for each of the N time intervals.
( A J ) where A : array of shape ( N m m ) giving the Levy areas that were used . J : array of shape ( N m m ) giving an m x m matrix of repeated Stratonovich integral values for each of the N time intervals .
dW
giving m independent Weiner increments for
each time step N. (You can make this array using sdeint.deltaW())
giving m independent Weiner increments for each time step N . ( You can make this array using sdeint . deltaW () )
h
the time step size
the time step size
n
None