def _makefm(self, params):
zdot = self.x[self.dim:]
OhmP = tn.subs(self._Ohm, zip(self.z, self._P))
OhmI = tn.subs(self._dPsi, zip(self.q, OhmP))
zz = self._P
zzdot = np.dot(self._dP, zdot)
out = -tn.einsum('i,ijk,k', zzdot, self.dMzz, zzdot) \
+ tn.einsum('i,ikj,k', zzdot, self.dMzz, zzdot) / 2
out = np.dot(self.Mzzi, out + self.dVzz)
out = out - tn.einsum('ijk,j,k', tn.diff(self._dP, self.z), zdot, zdot)
out = out + matmult(OhmI, self.Mqi, self.u)
# in general, there should be a subs here
out = matmult(self._dPi, out)
out = np.concatenate((zdot, out))
out = tn.SymExpr(tn.subs(out, self.ztox))
out.callable(*params)
return out
def _makefm(self, params):
zdot = self.x[self.dim:]
OhmP = tn.subs(self._Ohm, zip(self.z, self._P))
OhmI = tn.subs(self._dPsi, zip(self.q, OhmP))
zz = self._P
zzdot = np.dot(self._dP, zdot)
out = -tn.einsum('i,ijk,k', zzdot, self.dMzz, zzdot) \
+ tn.einsum('i,ikj,k', zzdot, self.dMzz, zzdot) / 2
out = np.dot(self.Mzzi, out + self.dVzz)
out = out - tn.einsum('ijk,j,k',
tn.diff(self._dP, self.z), zdot, zdot)
out = out + matmult(OhmI, self.Mqi, self.u)
# in general, there should be a subs here
out = matmult(self._dPi, out)
out = np.concatenate((zdot, out))
out = tn.SymExpr(tn.subs(out, self.ztox))
out.callable(*params)
return out
def _makefp(self, params):
zdot = self.x[self.dim:]
out = np.concatenate((
zdot,
np.dot(
self.Mzi, -tn.einsum('i,ijk,k', zdot, self.dMz, zdot) +
tn.einsum('i,ikl,k', zdot, self.dMz, zdot) / 2 + self.dVz) +
matmult(
tn.subs(self._dPsi, self.qtoz),
self.Mqi, # here we might need subs
self.u)))
out = tn.SymExpr(tn.subs(out, self.ztox))
out.callable(*params)
return out
def _makefp(self, params):
zdot = self.x[self.dim:]
out = np.concatenate((zdot,
np.dot(self.Mzi,
- tn.einsum(
'i,ijk,k', zdot, self.dMz, zdot)
+ tn.einsum(
'i,ikl,k', zdot, self.dMz, zdot) / 2
+ self.dVz)
+ matmult(
tn.subs(self._dPsi, self.qtoz),
self.Mqi, # here we might need subs
self.u)
))
out = tn.SymExpr(tn.subs(out, self.ztox))
out.callable(*params)
return out
from nlsymb import np, sym, matmult, tensor
import nlsymb.tensor as tn
from sympy import Symbol as S
if __name__ == "__main__":
x1 = S('x1')
x2 = S('x2')
x = np.array([x1, x2])
f = np.array([x[0], x[1]**2, 3 * x[0] + x[1]])
print f
print tn.subs(f, {x1: 2.0, x2: 3.0})
print tn.eval(f, x, [2.0, 3.0])
A = tn.diff(f, x)
print A
print A[0, 1]
Anum = tn.eval(A, x, [2, 3])
print Anum[0, 1]
g = np.dot(A, x)
print g
g = tn.einsum('ij,j', A, x)
print g
from nlsymb import np, sym, matmult, tensor
import nlsymb.tensor as tn
from sympy import Symbol as S
if __name__ == "__main__":
x1 = S('x1')
x2 = S('x2')
x = np.array([x1, x2])
f = np.array([x[0], x[1]**2, 3*x[0]+x[1]])
print f
print tn.subs(f, {x1:2.0, x2:3.0})
print tn.eval(f, x, [2.0, 3.0])
A = tn.diff(f, x)
print A
print A[0, 1]
Anum = tn.eval(A, x, [2,3])
print Anum[0,1]
g = np.dot(A, x)
print g
g = tn.einsum('ij,j', A, x)
print g
