def __init__(self, core, config=None, label=None):
"""
Parameters
-----------
core: pyphs.Core
The core Port-Hamiltonian structure on wich the method is build.
config: dict or None
A dictionary of simulation parameters. If None, the standard
pyphs.config.simulations is used (the default is None).
keys and default values are
'fs': 48e3, # Sample rate (Hz)
'grad': 'discret', # In {'discret', 'theta', 'trapez'}
'theta': 0., # Theta-scheme for the structure
'split': True, # split implicit from explicit part
'maxit': 10, # Max number of iterations for NL solvers
"""
Method.__init__(self, core, config=config, label=label)
if VERBOSE >= 2:
print(' Build {}'.format('ijactempFll'))
self.setexpr('ijactempFll', self.jactempFll().inverse_LU())
if VERBOSE >= 2:
print(' Build {}'.format('ud_vl'))
ud_vl = matvecprod(-self.ijactempFll, self.Gl())
self.setexpr('ud_vl', list(ud_vl))
if VERBOSE >= 2:
print(' Build {}'.format('Fnl'))
temp = matvecprod(self.jactempFnll() * self.ijactempFll, self.Gl())
Fnl = list(types.matrix_types[0](self.Gnl()) -
types.matrix_types[0](temp))
if VERBOSE >= 2:
print(' Simplify {}'.format('jacFnlnl'))
jacFnlnl = simplify(self.jacGnlnl() - self.jactempFnll() *
self.ijactempFll * self.jacGlnl())
if VERBOSE >= 2:
print(' Inverse {}'.format('jacFnlnl'))
if jacFnlnl.shape == (0, 0):
ijacFnlnl = jacFnlnl
else:
ijacFnlnl = jacFnlnl.inv()
if VERBOSE >= 2:
print(' Build {} for Faust code generation'.format('ud_vnl'))
ud_vnl = list(
sympy.simplify(types.matrix_types[0](self.vnl()) -
types.matrix_types[0](
(matvecprod(ijacFnlnl, Fnl)))))
self.setexpr('ud_vnl', list(ud_vnl))
self.init_funcs()
def __init__(self, core, config=None, label=None):
"""
Parameters
-----------
core: pyphs.Core
The core Port-Hamiltonian structure on wich the method is build.
config: dict or None
A dictionary of simulation parameters. If None, the standard
pyphs.config.simulations is used (the default is None).
keys and default values are
'fs': 48e3, # Sample rate (Hz)
'grad': 'discret', # In {'discret', 'theta', 'trapez'}
'theta': 0., # Theta-scheme for the structure
'split': True, # split implicit from explicit part
'maxit': 10, # Max number of iterations for NL solvers
"""
Method.__init__(self, core, config=config, label=label)
if VERBOSE >= 2:
print(' Build {}'.format('ijactempFll'))
self.setexpr('ijactempFll', self.jactempFll().inverse_LU())
if VERBOSE >= 2:
print(' Build {}'.format('ud_vl'))
ud_vl = matvecprod(-self.ijactempFll, self.Gl())
self.setexpr('ud_vl', list(ud_vl))
if VERBOSE >= 2:
print(' Build {}'.format('Fnl'))
temp = matvecprod(self.jactempFnll()*self.ijactempFll, self.Gl())
Fnl = list(types.matrix_types[0](self.Gnl()) -
types.matrix_types[0](temp))
if VERBOSE >= 2:
print(' Simplify {}'.format('jacFnlnl'))
jacFnlnl = simplify(self.jacGnlnl() -
self.jactempFnll()*self.ijactempFll*self.jacGlnl())
if VERBOSE >= 2:
print(' Inverse {}'.format('jacFnlnl'))
if jacFnlnl.shape == (0, 0):
ijacFnlnl = jacFnlnl
else:
ijacFnlnl = jacFnlnl.inv()
if VERBOSE >= 2:
print(' Build {} for Faust code generation'.format('ud_vnl'))
ud_vnl = list(types.matrix_types[0](self.vnl()) -
types.matrix_types[0]((matvecprod(ijacFnlnl, Fnl))))
self.setexpr('ud_vnl', list(ud_vnl))
self.init_funcs()
def func():
v = geteval(method, 'v')
Mvv = geteval(method, 'Mvv')
Mvy = geteval(method, 'Mvy')
f = geteval(method, 'f')
u = geteval(method, 'u')
temp = [
sp.sympify(0),
] * len(geteval(method, 'v'))
temp = sumvecs(temp, matvecprod(method.I(''), v),
[-e for e in matvecprod(Mvv, f)],
[-e for e in matvecprod(Mvy, u)])
return temp
def func():
Fa = geteval(method, 'tempF' + a)
vl = geteval(method, 'vl')
JacFal = geteval(
method,
'jactempF' + a + 'l',
)
return sumvecs(Fa, [-e for e in matvecprod(JacFal, vl)])
def func():
v = geteval(method, 'v' + suffix)
Mvvl = geteval(method, 'Mv' + suffix + 'vl')
Mvvnl = geteval(method, 'Mv' + suffix + 'vnl')
Mvy = geteval(method, 'Mv' + suffix + 'y')
fl = geteval(method, 'fl')
fnl = geteval(method, 'fnl')
u = geteval(method, 'u')
temp = [
sp.sympify(0),
] * len(geteval(method, 'v' + suffix))
temp = sumvecs(temp, matvecprod(method.I(suffix), v),
[-e for e in matvecprod(Mvvl, fl)],
[-e for e in matvecprod(Mvvnl, fnl)],
[-e for e in matvecprod(Mvy, u)])
return temp
def func():
F = geteval(method, 'tempF')
vl = geteval(method, 'vl')
JacFl = jacobian(F, vl)
G = sumvecs(F, [-e for e in matvecprod(JacFl, vl)])
return list(G)
