def __init__(self, dimNames, data, m):
"""Initialise a uniform profile.
Args:
dimNames: see function
data (DataContainer) - DataContainer with
- magnitude (Av0)
- grid
m (real) - power for H/H0
"""
FunctionBase.__init__(self, dimNames)
self.m = m
self.data = data
self.H0 = self.data.v('grid', 'low', 'z', x=0) - self.data.v(
'grid', 'high', 'z', x=0)
# change grid to remove z dimension
self.data.data['grid'] = copy.copy(self.data.data['grid'])
self.data.data['grid']['dimensions'] = dimNames
if 'f' in dimNames:
self.data.data['grid']['axis'] = copy.copy(
self.data.data['grid']['axis'])
lenf = self.data.data['grid']['axis']['f'].shape[-1]
self.data.data['grid']['axis']['f'] = self.data.data['grid'][
'axis']['f'].reshape(1, lenf)
self.data.data['grid']['contraction'] = np.asarray([[0, 0], [0,
0]])
return
def __init__(self, dimNames, data):
FunctionBase.__init__(self, dimNames)
self.C0 = float(data.v('C0'))
# call checkVariables method of FunctionBase to make sure that the input is correct
FunctionBase.checkVariables(self, ('C0', self.C0))
return
def __init__(self, dimNames, data):
FunctionBase.__init__(self, dimNames)
self.L = float(data.v('L'))
self.C1 = np.array(data.v('C1'))
self.C2 = np.array(data.v('C2'))
FunctionBase.checkVariables(self, ('L', self.L), ('C1', self.C1), ('C2', self.C2))
return
def __init__(self, dimNames, data):
FunctionBase.__init__(self, dimNames)
self.L = float(data.v('L'))
self.C0 = float(data.v('C0'))
self.CL = float(data.v('CL'))
FunctionBase.checkVariables(self, ('C0', self.C0), ('CL', self.CL),
('L', self.L))
return
def __init__(self, dimNames, data):
FunctionBase.__init__(self, dimNames)
self.L = float(data.v('L'))
self.alpha = float(data.v('alpha'))
self.beta = float(data.v('beta'))
self.gamma = float(data.v('gamma'))
self.xc = float(data.v('xc'))
self.xl = float(data.v('xl'))
FunctionBase.checkVariables(self, ('alpha', self.alpha),
('beta', self.beta), ('xc', self.xc),
('xl', self.xl), ('L', self.L))
return
def __init__(self, dimNames, data):
FunctionBase.__init__(self, dimNames)
self.L = float(data.v('L'))
self.C0 = data.v('C0')
self.C1 = data.v('C1')
self.xc = float(data.v('xc'))
self.xl = float(data.v('xl'))
# call checkVariables method of FunctionBase to make sure that the input is correct
FunctionBase.checkVariables(self, ('C0', self.C0), ('C1', self.C1),
('xc', self.xc), ('xl', self.xl),
('L', self.L))
return
def __init__(self, dimNames, data):
FunctionBase.__init__(self, dimNames)
self.L = float(data.v('L'))
self.C = np.array(data.v('C'))
self.XL = float(np.array(data.v('XL')))
FunctionBase.checkVariables(self, ('C', self.C), ('XL', self.XL),
('L', self.L))
# coefficients for the linear function
self.C_lin = np.asarray([
np.polyval(np.polyder(self.C), self.XL),
np.polyval(self.C, self.XL)
])
return
def __init__(self, dimNames, data, m):
"""Initialise a uniform profile with x dependency via H/H0
Args:
dimNames: see function
data (DataContainer) - DataContainer with
- magnitude (Av0)
- grid
m (real) - power for H/H0
"""
FunctionBase.__init__(self, dimNames)
self.m = m
self.data = data
self.H0 = self.data.v('grid', 'low', 'z', x=0) - self.data.v('grid', 'high', 'z', x=0)
return
def __init__(self, dimNames, data, m):
"""Initialise a parabolic profile.
Args:
dimNames: see function
coef (complex array) - needs to be a real/complex array in shape (x,1,f) (length of x may be 1)
data (DataContainer) - DataContainer with
- roughness (z0*)
- roughness (zs*)
- magnitude (coef)
- grid
m (real) - power for H/H0
"""
FunctionBase.__init__(self, dimNames)
self.data = data
self.m = m
self.H0 = self.data.v('grid', 'low', 'z', x=0) - self.data.v(
'grid', 'high', 'z', x=0)
return
def __init__(self, input):
self.__input = input
FunctionBase.__init__(self, ['x', 'f'])
return
def __init__(self, dimNames, data):
FunctionBase.__init__(self, dimNames)
self.H = data
return
def __init__(self, dimNames, data):
FunctionBase.__init__(self, dimNames)
self.L = float(data.v('L'))
self.C = np.array(ny.toList(data.v('C')))
FunctionBase.checkVariables(self, ('C', self.C), ('L', self.L))
return