def test_eval_mat(self):
cell, grids = make_grids(30)
numpy.random.seed(10)
nao = 10
ngrids = 500
rho = numpy.random.random((6, ngrids))
vxc = numpy.random.random((4, ngrids))
weight = numpy.random.random(ngrids)
ao = (numpy.random.random((10, ngrids, nao)) + numpy.random.random(
(10, ngrids, nao)) * 1j)
mat0 = numpy.einsum('pi,p,pj->ij', ao[0].conj(), weight * vxc[0],
ao[0])
mat1 = numint.eval_mat(cell, ao[0], weight, rho, vxc, xctype='LDA')
self.assertTrue(numpy.allclose(mat0, mat1))
vrho, vsigma = vxc[:2]
wv = weight * vsigma * 2
mat0 = numpy.einsum('pi,p,pj->ij', ao[0].conj(), weight * vrho, ao[0])
mat0 += numpy.einsum(
'pi,p,pj->ij', ao[0].conj(), rho[1] * wv, ao[1]) + numpy.einsum(
'pi,p,pj->ij', ao[1].conj(), rho[1] * wv, ao[0])
mat0 += numpy.einsum(
'pi,p,pj->ij', ao[0].conj(), rho[2] * wv, ao[2]) + numpy.einsum(
'pi,p,pj->ij', ao[2].conj(), rho[2] * wv, ao[0])
mat0 += numpy.einsum(
'pi,p,pj->ij', ao[0].conj(), rho[3] * wv, ao[3]) + numpy.einsum(
'pi,p,pj->ij', ao[3].conj(), rho[3] * wv, ao[0])
mat1 = numint.eval_mat(cell, ao, weight, rho, vxc, xctype='GGA')
self.assertTrue(numpy.allclose(mat0, mat1))
def test_eval_mat(self):
cell, grids = make_grids([61]*3)
numpy.random.seed(10)
nao = 10
ngrids = 500
rho = numpy.random.random((6,ngrids))
vxc = numpy.random.random((4,ngrids))
weight = numpy.random.random(ngrids)
ao =(numpy.random.random((10,ngrids,nao)) +
numpy.random.random((10,ngrids,nao))*1j)
mat0 = numpy.einsum('pi,p,pj->ij', ao[0].conj(), weight*vxc[0], ao[0])
mat1 = numint.eval_mat(cell, ao[0], weight, rho, vxc, xctype='LDA')
self.assertTrue(numpy.allclose(mat0, mat1))
vrho, vsigma = vxc[:2]
wv = weight * vsigma * 2
mat0 = numpy.einsum('pi,p,pj->ij', ao[0].conj(), weight*vrho, ao[0])
mat0 += numpy.einsum('pi,p,pj->ij', ao[0].conj(), rho[1]*wv, ao[1]) + numpy.einsum('pi,p,pj->ij', ao[1].conj(), rho[1]*wv, ao[0])
mat0 += numpy.einsum('pi,p,pj->ij', ao[0].conj(), rho[2]*wv, ao[2]) + numpy.einsum('pi,p,pj->ij', ao[2].conj(), rho[2]*wv, ao[0])
mat0 += numpy.einsum('pi,p,pj->ij', ao[0].conj(), rho[3]*wv, ao[3]) + numpy.einsum('pi,p,pj->ij', ao[3].conj(), rho[3]*wv, ao[0])
mat1 = numint.eval_mat(cell, ao, weight, rho, vxc, xctype='GGA')
self.assertTrue(numpy.allclose(mat0, mat1))
mat1 = numint.eval_mat(cell, ao, weight, rho, vxc, xctype='MGGA')
self.assertAlmostEqual(finger(mat1), -106.84965223363503+50.089526939523154j, 7)
mat1 = numint.eval_mat(cell, ao[0], weight, rho, vxc, xctype='LDA')
self.assertAlmostEqual(finger(mat1), 10.483493302918024+3.5590312220458227j, 7)
def test_eval_mat(self):
cell, grids = make_grids(30)
ng = grids.weights.size
np.random.seed(1)
rho = np.random.random(ng)
rho *= 1/np.linalg.norm(rho)
vrho = np.random.random(ng)
ao1 = numint.eval_ao(cell, grids.coords)
mat1 = numint.eval_mat(cell, ao1, grids.weights, rho, vrho)
w = np.arange(mat1.size) * .01
self.assertAlmostEqual(np.dot(w,mat1.ravel()), (.14777107967912118+0j), 8)
def test_eval_mat(self):
cell, grids = make_grids([61]*3)
ng = grids.weights.size
np.random.seed(1)
rho = np.random.random(ng)
rho *= 1/np.linalg.norm(rho)
vrho = np.random.random(ng)
ao1 = numint.eval_ao(cell, grids.coords)
mat1 = numint.eval_mat(cell, ao1, grids.weights, rho, vrho)
w = np.arange(mat1.size) * .01
self.assertAlmostEqual(np.dot(w,mat1.ravel()), (.14777107967912118+0j), 8)
def test_eval_mat1(self):
cell, grids = make_grids([61] * 3)
numpy.random.seed(10)
nao = 10
ngrids = 500
rho = numpy.random.random((6, ngrids))
vxc = numpy.random.random((4, ngrids))
weight = numpy.random.random(ngrids)
ao = (numpy.random.random((10, ngrids, nao)) + numpy.random.random(
(10, ngrids, nao)) * 1j)
mat0 = numpy.einsum('pi,p,pj->ij', ao[0].conj(), weight * vxc[0],
ao[0])
mat1 = numint.eval_mat(cell, ao[0], weight, rho, vxc, xctype='LDA')
self.assertAlmostEqual(abs(mat0 - mat1).max(), 0, 12)
vrho, vsigma = vxc[:2]
wv = weight * vsigma * 2
mat0 = numpy.einsum('pi,p,pj->ij', ao[0].conj(), weight * vrho, ao[0])
mat0 += numpy.einsum(
'pi,p,pj->ij', ao[0].conj(), rho[1] * wv, ao[1]) + numpy.einsum(
'pi,p,pj->ij', ao[1].conj(), rho[1] * wv, ao[0])
mat0 += numpy.einsum(
'pi,p,pj->ij', ao[0].conj(), rho[2] * wv, ao[2]) + numpy.einsum(
'pi,p,pj->ij', ao[2].conj(), rho[2] * wv, ao[0])
mat0 += numpy.einsum(
'pi,p,pj->ij', ao[0].conj(), rho[3] * wv, ao[3]) + numpy.einsum(
'pi,p,pj->ij', ao[3].conj(), rho[3] * wv, ao[0])
mat1 = numint.eval_mat(cell, ao, weight, rho, vxc, xctype='GGA')
self.assertAlmostEqual(abs(mat0 - mat1).max(), 0, 11)
mat1 = numint.eval_mat(cell, ao, weight, rho, vxc, xctype='MGGA')
self.assertAlmostEqual(lib.fp(mat1),
-160.191390949408 + 21.478570186344374j, 7)
mat1 = numint.eval_mat(cell, ao[0], weight, rho, vxc, xctype='LDA')
self.assertAlmostEqual(lib.fp(mat1),
10.483493302918024 + 3.5590312220458227j, 7)
def test_eval_mat(self):
cell, grids = make_grids(30)
numpy.random.seed(10)
nao = 10
ngrids = 500
rho = numpy.random.random((6,ngrids))
vxc = numpy.random.random((4,ngrids))
weight = numpy.random.random(ngrids)
ao =(numpy.random.random((10,ngrids,nao)) +
numpy.random.random((10,ngrids,nao))*1j)
mat0 = numpy.einsum('pi,p,pj->ij', ao[0].conj(), weight*vxc[0], ao[0])
mat1 = numint.eval_mat(cell, ao[0], weight, rho, vxc, xctype='LDA')
self.assertTrue(numpy.allclose(mat0, mat1))
vrho, vsigma = vxc[:2]
wv = weight * vsigma * 2
mat0 = numpy.einsum('pi,p,pj->ij', ao[0].conj(), weight*vrho, ao[0])
mat0 += numpy.einsum('pi,p,pj->ij', ao[0].conj(), rho[1]*wv, ao[1]) + numpy.einsum('pi,p,pj->ij', ao[1].conj(), rho[1]*wv, ao[0])
mat0 += numpy.einsum('pi,p,pj->ij', ao[0].conj(), rho[2]*wv, ao[2]) + numpy.einsum('pi,p,pj->ij', ao[2].conj(), rho[2]*wv, ao[0])
mat0 += numpy.einsum('pi,p,pj->ij', ao[0].conj(), rho[3]*wv, ao[3]) + numpy.einsum('pi,p,pj->ij', ao[3].conj(), rho[3]*wv, ao[0])
mat1 = numint.eval_mat(cell, ao, weight, rho, vxc, xctype='GGA')
self.assertTrue(numpy.allclose(mat0, mat1))
