def execute(self):
"""
Default behaviour is to copy the input array
derived classes need to overwrite this class with specific splines
"""
if not self.init_called:
self.initialize()
self.P = self.Pbase + self.spline(self.x, self.Cx, self.C)
self.dPds = curvature(np.array([self.x, self.P]).T)
def execute(self):
"""
Default behaviour is to copy the input array
derived classes need to overwrite this class with specific splines
"""
if not self.init_called:
self.initialize()
self.P = self.Pbase + self.spline(self.x, self.Cx, self.C)
self.dTds = curvature(np.array([self.x, self.P]).T)
def solve_nonlinear(self, params, unknowns, resids):
"""
update the spline
"""
C = params[self._name + '_C']
if not self._init_called:
self.set_spline(self.spline_options['spline_type'])
# self.Pbase = self.base_spline(self.s, self.xinit, self.Pinit)
self.spline.initialize(self.s, self.Cx, C)
self._P = self.spline(self.s, self.Cx, C)
P = self.Pinit + self._P * self.scaler
curv = curvature(np.array([self.s, P]).T)
unknowns[self._name] = P
unknowns[self._name + '_curv'] = curv
def solve_nonlinear(self, params, unknowns, resids):
"""
update the spline
"""
C = params[self._name + '_C']
if not self._init_called:
self.set_spline(self.spline_options['spline_type'])
# self.Pbase = self.base_spline(self.s, self.xinit, self.Pinit)
self.spline.initialize(self.s, self.Cx, C)
self._P = self.spline(self.s, self.Cx, C)
P = self.Pinit + self._P * self.scaler
curv = curvature(np.array([self.s, P]).T)
unknowns[self._name] = P
unknowns[self._name + '_curv'] = curv
def solve_nonlinear(self, params, unknowns, resids):
"""
update the spline
"""
C = params[self._name + "_C"]
if not self._init_called:
self.set_spline(self.spline_options["spline_type"])
self.spline.initialize(self.s[self._iCx0 : self._iCx1], self.Cx, C)
self._P = self.spline(self.s[self._iCx0 : self._iCx1], self.Cx, C)
_P = np.zeros(self.Pinit.shape[0])
_P[self._iCx0 : self._iCx1] = self._P
P = self.Pinit + _P * self.scaler
curv = curvature(np.array([self.s, P]).T)
unknowns[self._name] = P
unknowns[self._name + "_curv"] = curv
def computeLETE(self):
"""
computes the leading and trailing edge of the airfoil.
TE is computed as the mid-point between lower and upper TE points
LE is computed as the point with maximum distance from the TE.
"""
self.TE = np.array([np.average(self.points[[0, -1], 0]),
np.average(self.points[[0, -1], 1])])
res = minimize(self._sdist, (0.5), method='SLSQP', bounds=[(0, 1)])
self.sLE = res['x'][0]
xLE = self.spline[0](self.sLE)
yLE = self.spline[1](self.sLE)
self.LE = np.array([xLE, yLE])
self.curvLE = NaturalCubicSpline(self.s, curvature(self.points))(self.sLE)
self.chord = np.linalg.norm(self.LE-self.TE)
def solve_nonlinear(self, params, unknowns, resids):
"""
update the spline
"""
C = params[self._name + '_C']
if not self._init_called:
self.set_spline(self.spline_options['spline_type'])
self.spline.initialize(self.s[self._iCx0:self._iCx1], self.Cx, C)
self._P = self.spline(self.s[self._iCx0:self._iCx1], self.Cx, C)
_P = np.zeros(self.Pinit.shape[0])
_P[self._iCx0:self._iCx1] = self._P
P = self.Pinit + _P * self.scaler
curv = curvature(np.array([self.s, P]).T)
unknowns[self._name] = P
unknowns[self._name + '_curv'] = curv
def computeLETE(self):
"""
computes the leading and trailing edge of the airfoil.
TE is computed as the mid-point between lower and upper TE points
LE is computed as the point with maximum distance from the TE.
"""
self.TE = np.array([
np.average(self.points[[0, -1], 0]),
np.average(self.points[[0, -1], 1])
])
res = minimize(self._sdist, (0.5), method='SLSQP', bounds=[(0, 1)])
self.sLE = res['x'][0]
xLE = self.spline[0](self.sLE)
yLE = self.spline[1](self.sLE)
self.LE = np.array([xLE, yLE])
self.curvLE = NaturalCubicSpline(self.s,
curvature(self.points))(self.sLE)
