def __init__(self,
d,
theta,
A,
b,
Ahat=None,
bhat=None,
type='General',
name='Two-step Runge-Kutta Method'):
r"""
Initialize a 2-step Runge-Kutta method."""
d, A, b, Ahat, bhat = snp.normalize(d, A, b, Ahat, bhat)
self.s = max(np.shape(b))
self.d, self.theta, self.A, self.b = d, theta, A, b
self.Ahat, self.bhat = Ahat, bhat
#if type=='General': self.Ahat,self.bhat=Ahat,bhat
#elif type=='Type I':
# self.Ahat = np.zeros([self.s,self.s])
# self.bhat = np.zeros([self.s,1])
#elif type=='Type II':
# self.Ahat = np.zeros([self.s,self.s])
# self.Ahat[:,0]=Ahat
# self.bhat = np.zeros([self.s,1])
# self.bhat[0]=bhat
#else: raise Exception('Unrecognized type')
self.name = name
self.type = type
def __init__(self,
A=None,
At=None,
b=None,
bt=None,
alpha=None,
beta=None,
alphat=None,
betat=None,
name='downwind Runge-Kutta Method',
description=''):
r"""
Initialize a downwind Runge-Kutta method. The representation
uses the form and notation of [Ketcheson2010]_.
\\begin{align*}
y^n_i = & u^{n-1} + \\Delta t \\sum_{j=1}^{s}
(a_{ij} f(y_j^{n-1}) + \\tilde{a}_{ij} \\tilde{f}(y_j^n)) & (1\\le j \\le s) \\\\
\\end{align*}
"""
A, b, alpha, beta = snp.normalize(A, b, alpha, beta)
butchform = [x is not None for x in [A, At, b, bt]]
SOform = [x is not None for x in [alpha, alphat, beta, betat]]
if not ((all(butchform) and not (True in SOform)) or
((not (True in butchform)) and all(SOform))):
raise Exception("""To initialize a Runge-Kutta method,
you must provide either Butcher arrays or Shu-Osher arrays,
but not both.""")
if A is not None: #Initialize with Butcher arrays
# Check that number of stages is consistent
m = np.size(A, 0) # Number of stages
if m > 1:
if not np.all([np.size(A, 1), np.size(b)] == [m, m]):
raise Exception(
'Inconsistent dimensions of Butcher arrays')
else:
if not np.size(b) == 1:
raise Exception(
'Inconsistent dimensions of Butcher arrays')
elif alpha is not None: #Initialize with Shu-Osher arrays
A, At, b, bt = downwind_shu_osher_to_butcher(
alpha, alphat, beta, betat)
# Set Butcher arrays
if len(np.shape(A)) == 2:
self.A = A
self.At = At
else:
self.A = snp.array([A]) #Fix for 1-stage methods
self.At = snp.array([At])
self.b = b
self.bt = bt
self.c = np.sum(self.A, 1) - np.sum(self.At, 1)
self.name = name
self.info = description
self.underlying_method = rk.RungeKuttaMethod(self.A - self.At,
self.b - self.bt)
def __init__(
self,
A=None,
At=None,
b=None,
bt=None,
alpha=None,
beta=None,
alphat=None,
betat=None,
name="downwind Runge-Kutta Method",
description="",
):
r"""
Initialize a downwind Runge-Kutta method. The representation
uses the form and notation of [Ketcheson2010]_.
\\begin{align*}
y^n_i = & u^{n-1} + \\Delta t \\sum_{j=1}^{s}
(a_{ij} f(y_j^{n-1}) + \\tilde{a}_{ij} \\tilde{f}(y_j^n)) & (1\\le j \\le s) \\\\
\\end{align*}
"""
A, b, alpha, beta = snp.normalize(A, b, alpha, beta)
butchform = [x is not None for x in [A, At, b, bt]]
SOform = [x is not None for x in [alpha, alphat, beta, betat]]
if not ((all(butchform) and not (True in SOform)) or ((not (True in butchform)) and all(SOform))):
raise Exception(
"""To initialize a Runge-Kutta method,
you must provide either Butcher arrays or Shu-Osher arrays,
but not both."""
)
if A is not None: # Initialize with Butcher arrays
# Check that number of stages is consistent
m = np.size(A, 0) # Number of stages
if m > 1:
if not np.all([np.size(A, 1), np.size(b)] == [m, m]):
raise Exception("Inconsistent dimensions of Butcher arrays")
else:
if not np.size(b) == 1:
raise Exception("Inconsistent dimensions of Butcher arrays")
elif alpha is not None: # Initialize with Shu-Osher arrays
A, At, b, bt = downwind_shu_osher_to_butcher(alpha, alphat, beta, betat)
# Set Butcher arrays
if len(np.shape(A)) == 2:
self.A = A
self.At = At
else:
self.A = snp.array([A]) # Fix for 1-stage methods
self.At = snp.array([At])
self.b = b
self.bt = bt
self.c = np.sum(self.A, 1) - np.sum(self.At, 1)
self.name = name
self.info = description
self.underlying_method = rk.RungeKuttaMethod(self.A - self.At, self.b - self.bt)
def __init__(self,d,theta,A,b,Ahat=None,bhat=None,type='General',name='Two-step Runge-Kutta Method'):
r"""
Initialize a 2-step Runge-Kutta method."""
d,A,b,Ahat,bhat=snp.normalize(d,A,b,Ahat,bhat)
self.s = max(np.shape(b))
self.d,self.theta,self.A,self.b = d,theta,A,b
self.Ahat,self.bhat=Ahat,bhat
#if type=='General': self.Ahat,self.bhat=Ahat,bhat
#elif type=='Type I':
# self.Ahat = np.zeros([self.s,self.s])
# self.bhat = np.zeros([self.s,1])
#elif type=='Type II':
# self.Ahat = np.zeros([self.s,self.s])
# self.Ahat[:,0]=Ahat
# self.bhat = np.zeros([self.s,1])
# self.bhat[0]=bhat
#else: raise Exception('Unrecognized type')
self.name=name
self.type=type
