Lines Matching refs:quadrature

8 User Q-functions describe the action of the $D$ operator at quadrature points
11 Since the Q-functions are invoked at every quadrature point, efficiency is
20 is the basis operator, and $D$ represents multiplication by quadrature weights
42 "data context" pointer, a number of quadrature points, and two arrays of arrays,
46 function evaluated at each quadrature point. The second input array is `qdata`,
58 nodal points to quadrature points, and `CEED_EVAL_NONE` indicates that the
59 `qdata` is already precomputed at quadrature points, and no interpolation is
84 quadrature points. The next three arguments are specifications of the input and
95 array. The first dimension is always equal to the number of quadrature points.
97 number of quadrature points, but in more sophisticated examples (e.g. the [apply
99 matrices at each quadrature point. After providing all of the array
109 transformation Jacobian, and $w$ is the quadrature weight.
147 this array stores the gradient of the trial function at each quadrature point.
148 Therefore, at each quadrature point, `du` stores a vector of length `dim`, and
151 each quadrature point. This means that the output array `dv` also has shape
155 \det(J) J^{-\intercal} J^{-1}$ evaluated at every quadrature point. In order to
179 Then, the gradient of $u$ at the given quadrature point is loaded as a