Lines Matching refs:nx
47 nx = nelem + 1
51 x = ceed.Vector(nx)
52 x_array = np.zeros(nx)
53 for i in range(nx):
54 x_array[i] = i / (nx - 1.0)
62 indx = np.zeros(nx * 2, dtype="int32")
63 for i in range(nx):
66 rx = ceed.ElemRestriction(nelem, 2, 1, 1, nx, indx,
136 nx = nelem + 1
140 x = ceed.Vector(nx)
141 x_array = np.zeros(nx, dtype=ceed.scalar_type())
142 for i in range(nx):
143 x_array[i] = i / (nx - 1.0)
151 indx = np.zeros(nx * 2, dtype="int32")
152 for i in range(nx):
155 rx = ceed.ElemRestriction(nelem, 2, 1, 1, nx, indx,
226 nx = nelem + 1
230 x = ceed.Vector(nx)
231 x_array = np.zeros(nx, dtype=ceed.scalar_type())
232 for i in range(nx):
233 x_array[i] = i / (nx - 1.0)
241 indx = np.zeros(nx * 2, dtype="int32")
242 for i in range(nx):
245 rx = ceed.ElemRestriction(nelem, 2, 1, 1, nx, indx,
323 nx = nelem + 1
327 x = ceed.Vector(nx)
328 x_array = np.zeros(nx, dtype=ceed.scalar_type())
329 for i in range(nx):
330 x_array[i] = i / (nx - 1.0)
338 indx = np.zeros(nx * 2, dtype="int32")
339 for i in range(nx):
342 rx = ceed.ElemRestriction(nelem, 2, 1, 1, nx, indx,
412 nx = nelem + 1
419 indx = np.zeros(nx * 2, dtype="int32")
420 for i in range(nx):
423 rx = ceed.ElemRestriction(nelem, 2, 1, 1, nx, indx,
487 nx = nelem + 1
491 x = ceed.Vector(nx)
492 x_array = np.zeros(nx, dtype=ceed.scalar_type())
493 for i in range(nx):
494 x_array[i] = i / (nx - 1.0)
502 indx = np.zeros(nx * 2, dtype="int32")
503 for i in range(nx):
506 rx = ceed.ElemRestriction(nelem, 2, 1, 1, nx, indx,
589 nx, ny = 3, 2
590 ndofs = (nx * 2 + 1) * (ny * 2 + 1)
597 x_array[i] = (1. / (nx * 2)) * (i % (nx * 2 + 1))
598 x_array[i + ndofs] = (1. / (ny * 2)) * (i / (nx * 2 + 1))
608 col = i % nx
609 row = i // nx
610 offset = col * 2 + row * (nx * 2 + 1) * 2
696 nx, ny = 3, 2
697 ndofs = (nx * 2 + 1) * (ny * 2 + 1)
704 x_array[i] = (1. / (nx * 2)) * (i % (nx * 2 + 1))
705 x_array[i + ndofs] = (1. / (ny * 2)) * (i / (nx * 2 + 1))
715 col = i % nx
716 row = i // nx
717 offset = col * 2 + row * (nx * 2 + 1) * 2
803 nx, ny = 3, 3
806 ndofs = (nx * 2 + 1) * (ny * 2 + 1)
813 for j in range(nx * 2 + 1):
815 x_array[i + j * (ny * 2 + 1) + ndofs] = j / (2 * nx)
828 col = i % nx
829 row = i // nx
830 offset = col * 2 + row * (nx * 2 + 1) * 2
979 nx, ny = 3, 3
982 ndofs = (nx * 2 + 1) * (ny * 2 + 1)
989 for j in range(nx * 2 + 1):
991 x_array[i + j * (ny * 2 + 1) + ndofs] = j / (2 * nx)
1004 col = i % nx
1005 row = i // nx
1006 offset = col * 2 + row * (nx * 2 + 1) * 2
1156 nx, ny = 3, 3
1159 ndofs = (nx * 2 + 1) * (ny * 2 + 1)
1171 col = i % nx
1172 row = i // nx
1173 offset = col * 2 + row * (nx * 2 + 1) * 2
1328 nx, ny = 3, 3
1331 ndofs = (nx * 2 + 1) * (ny * 2 + 1)
1338 for j in range(nx * 2 + 1):
1340 x_array[i + j * (ny * 2 + 1) + ndofs] = j / (2 * nx)
1353 col = i % nx
1354 row = i // nx
1355 offset = col * 2 + row * (nx * 2 + 1) * 2
1519 nx = 3
1521 ndofs = (nx * 2 + 1) * (ny * 2 + 1)
1527 for i in range(nx * 2 + 1):
1529 x_array[i + j * (nx * 2 + 1) + 0 * ndofs] = i / (2 * nx)
1530 x_array[i + j * (nx * 2 + 1) + 1 * ndofs] = j / (2 * ny)
1540 col = i % nx
1541 row = i // nx
1542 offset = col * (p - 1) + row * (nx * 2 + 1) * (p - 1)
1545 indx[p * (p * i + k) + j] = offset + k * (nx * 2 + 1) + j
1575 nx = nelem + 1
1580 x = ceed.Vector(nx)
1581 x_array = np.zeros(nx, dtype=ceed.scalar_type())
1582 for i in range(nx):
1583 x_array[i] = i / (nx - 1.0)
1593 indx = np.zeros(nx * 2, dtype="int32")
1594 for i in range(nx):
1597 rx = ceed.ElemRestriction(nelem, 2, 1, 1, nx, indx,
1711 nx = nelem + 1
1716 x = ceed.Vector(nx)
1717 x_array = np.zeros(nx, dtype=ceed.scalar_type())
1718 for i in range(nx):
1719 x_array[i] = i / (nx - 1.0)
1729 indx = np.zeros(nx * 2, dtype="int32")
1730 for i in range(nx):
1733 rx = ceed.ElemRestriction(nelem, 2, 1, 1, nx, indx,
1849 nx = nelem + 1
1854 x = ceed.Vector(nx)
1855 x_array = np.zeros(nx, dtype=ceed.scalar_type())
1856 for i in range(nx):
1857 x_array[i] = i / (nx - 1.0)
1867 indx = np.zeros(nx * 2, dtype="int32")
1868 for i in range(nx):
1871 rx = ceed.ElemRestriction(nelem, 2, 1, 1, nx, indx,