pygeo/parameterization/DVGeo.py
def computeDVJacobian(self, config=None):
        """
        return J_temp for a given config
        """
        # These routines are not recursive. They compute the derivatives at this level and
        # pass information down one level for the next pass call from the routine above

        # This is going to be DENSE in general
        J_attach = self._attachedPtJacobian(config=config)

        # Compute local normal jacobian
        J_spanwiselocal = self._spanwiselocalDVJacobian(config=config)

        # Compute local normal jacobian
        J_sectionlocal = self._sectionlocalDVJacobian(config=config)

        # This is the sparse jacobian for the local DVs that affect
        # Control points directly.
        J_local = self._localDVJacobian(config=config)

        # this is the jacobian from accumulated derivative dependence from parent to child
        J_casc = self._cascadedDVJacobian(config=config)

        J_temp = None

        # add them together
        if J_attach is not None:
            J_temp = sparse.lil_matrix(J_attach)

        if J_spanwiselocal is not None:
            if J_temp is None:
                J_temp = sparse.lil_matrix(J_spanwiselocal)
            else:
                J_temp += J_spanwiselocal

        if J_sectionlocal is not None:
            if J_temp is None:
                J_temp = sparse.lil_matrix(J_sectionlocal)
            else:
                J_temp += J_sectionlocal

        if J_local is not None:
            if J_temp is None:
                J_temp = sparse.lil_matrix(J_local)
            else:
                J_temp += J_local

        if J_casc is not None:
            if J_temp is None:
                J_temp = sparse.lil_matrix(J_casc)
            else:
                J_temp += J_casc

        return J_temp

        return J_temp for a given config
        
return J_temp for a given config
return J_temp for a given config
def computeDVJacobian(self, config=None):
        J_attach = self._attachedPtJacobian(config=config)
        J_spanwiselocal = self._spanwiselocalDVJacobian(config=config)
        J_sectionlocal = self._sectionlocalDVJacobian(config=config)
        J_local = self._localDVJacobian(config=config)
        J_casc = self._cascadedDVJacobian(config=config)
        J_temp = None
        if J_attach is not None:
            J_temp = sparse.lil_matrix(J_attach)
        if J_spanwiselocal is not None:
            if J_temp is None:
                J_temp = sparse.lil_matrix(J_spanwiselocal)
            else:
                J_temp += J_spanwiselocal
        if J_sectionlocal is not None:
            if J_temp is None:
                J_temp = sparse.lil_matrix(J_sectionlocal)
            else:
                J_temp += J_sectionlocal
        if J_local is not None:
            if J_temp is None:
                J_temp = sparse.lil_matrix(J_local)
            else:
                J_temp += J_local
        if J_casc is not None:
            if J_temp is None:
                J_temp = sparse.lil_matrix(J_casc)
            else:
                J_temp += J_casc
        return J_temp
def computeDVJacobian ( self , config = None ) : J_attach = self . _attachedPtJacobian ( config = config ) J_spanwiselocal = self . _spanwiselocalDVJacobian ( config = config ) J_sectionlocal = self . _sectionlocalDVJacobian ( config = config ) J_local = self . _localDVJacobian ( config = config ) J_casc = self . _cascadedDVJacobian ( config = config ) J_temp = None if J_attach is not None : J_temp = sparse . lil_matrix ( J_attach ) if J_spanwiselocal is not None : if J_temp is None : J_temp = sparse . lil_matrix ( J_spanwiselocal ) else : J_temp += J_spanwiselocal if J_sectionlocal is not None : if J_temp is None : J_temp = sparse . lil_matrix ( J_sectionlocal ) else : J_temp += J_sectionlocal if J_local is not None : if J_temp is None : J_temp = sparse . lil_matrix ( J_local ) else : J_temp += J_local if J_casc is not None : if J_temp is None : J_temp = sparse . lil_matrix ( J_casc ) else : J_temp += J_casc return J_temp
return J_temp for a given config
return J_temp for a given config
"""
        return J_temp for a given config
        """ # These routines are not recursive. They compute the derivatives at this level and # pass information down one level for the next pass call from the routine above # This is going to be DENSE in general # Compute local normal jacobian # Compute local normal jacobian # This is the sparse jacobian for the local DVs that affect # Control points directly. # this is the jacobian from accumulated derivative dependence from parent to child # add them together
self
config