accelerated unit test

gpu4pyscf/df/tests/test_df_ecp.py

@@ -51,11 +51,19 @@ def run_dft(xc):
     e_dft = mf.kernel()
     return e_dft
 
+def _make_mf():
+    mf = rks.RKS(mol, xc=xc).density_fit(auxbasis=auxbasis)
+    mf.conv_tol = 1e-12
+    mf.grids.level = grids_level
+    mf.verbose = 1
+    mf.kernel()
+    return mf
+
 def _check_grad(grid_response=False, tol=1e-5):
     mf = rks.RKS(mol, xc=xc).density_fit(auxbasis=auxbasis)
     mf.grids.level = grids_level
     mf.conv_tol = 1e-12
-    e_tot = mf.kernel()
+    mf.kernel()
     g = mf.nuc_grad_method()
     g.auxbasis_response = True
     g.grid_response = grid_response
@@ -85,22 +93,14 @@ def _check_grad(grid_response=False, tol=1e-5):
             mol.set_geom_(coords, unit='Bohr')
             grad_fd[i,j] = (e0-e1)/2.0/eps
     grad_fd = np.array(grad_fd).reshape(-1,3)
-    print('finite difference gradient:')
-    print(grad_fd)
-    print('difference between analytical and finite difference gradient:', np.linalg.norm(g_analy - grad_fd))
+    print('norm of analytical - finite difference gradient:', np.linalg.norm(g_analy - grad_fd))
     assert(np.linalg.norm(g_analy - grad_fd) < tol)
 
 
-def _check_dft_hessian(disp=None, ix=0, iy=0, tol=1e-3):
-    pmol = mol.copy()
+def _check_dft_hessian(mf, h, ix=0, iy=0, tol=1e-3):
+    pmol = mf.mol.copy()
     pmol.build()
 
-    mf = rks.RKS(pmol, xc=xc).density_fit(auxbasis=auxbasis)
-    mf.conv_tol = 1e-12
-    mf.grids.level = grids_level
-    mf.verbose = 1
-    mf.kernel()
-
     g = mf.nuc_grad_method()
     g.auxbasis_response = True
     g.kernel()
@@ -112,31 +112,19 @@ def _check_dft_hessian(disp=None, ix=0, iy=0, tol=1e-3):
     pmol.set_geom_(coords + v, unit='Bohr')
     pmol.build()
     _, g0 = g_scanner(pmol)
-    
+
     pmol.set_geom_(coords - v, unit='Bohr')
     pmol.build()
     _, g1 = g_scanner(pmol)
-    
+
     h_fd = (g0 - g1)/2.0/eps
     pmol.set_geom_(coords, unit='Bohr')
     pmol.build()
 
-    mf = rks.RKS(pmol, xc=xc, disp=disp).density_fit(auxbasis=auxbasis)
-    mf.grids.level = grids_level
-    mf.kernel()
-    hobj = mf.Hessian()
-    hobj.set(auxbasis_response=2)
-    hobj.verbose=0
-    h = hobj.kernel()
-
-    print(f"analytical Hessian H({ix},{iy})")
-    print(h[ix,:,iy,:])
-    print(f"finite different Hessian H({ix},{iy})")
-    print(h_fd)
-    print('Norm of diff', np.linalg.norm(h[ix,:,iy,:] - h_fd))
+    print(f'Norm of finite difference - analytical Hessian({ix},{iy})', np.linalg.norm(h[ix,:,iy,:] - h_fd))
     assert(np.linalg.norm(h[ix,:,iy,:] - h_fd) < tol)
 
-class KnownValues(unittest.TestCase):    
+class KnownValues(unittest.TestCase):
     def test_rks_scf(self):
         mf = rks.RKS(mol, xc=xc).density_fit(auxbasis=auxbasis)
         mf.conv_tol = 1e-12
@@ -145,10 +133,16 @@ def test_rks_scf(self):
 
     def test_rks_gradient(self):
         _check_grad()
-    
+
     def test_rks_hessian(self):
-        _check_dft_hessian(ix=0, iy=0)
-        _check_dft_hessian(ix=0, iy=1)
+        mf = _make_mf()
+        hobj = mf.Hessian()
+        hobj.set(auxbasis_response=2)
+        hobj.verbose=0
+        h = hobj.kernel()
+
+        _check_dft_hessian(mf, h, ix=0, iy=0)
+        _check_dft_hessian(mf, h, ix=0, iy=1)
 
 if __name__ == "__main__":
     print("Full Tests for DF ECP")

gpu4pyscf/df/tests/test_df_hessian.py

@@ -42,19 +42,29 @@ def tearDownModule():
     global mol
     del mol
 
-def _check_rhf_hessian(ix=0, iy=0, tol=1e-3):
-    pmol = mol.copy()
-    pmol.build()
-
-    mf = scf.RHF(pmol).density_fit(auxbasis='ccpvtz-jkfit')
+def _make_rhf():
+    mf = scf.RHF(mol).density_fit(auxbasis='ccpvtz-jkfit')
+    mf.conv_tol = 1e-12
+    mf.kernel()
+    return mf
+
+def _make_rks(xc, disp=None):
+    mf = dft.rks.RKS(mol, xc=xc).density_fit(auxbasis=auxbasis0)
     mf.conv_tol = 1e-12
+    mf.disp = disp
+    mf.grids.level = grids_level
+    mf.verbose = 1
     mf.kernel()
+    return mf
+
+def _check_rhf_hessian(mf, h, ix=0, iy=0, tol=1e-3):
+    pmol = mf.mol.copy()
+    pmol.build()
+
     g = mf.nuc_grad_method()
     g.kernel()
     g_scanner = g.as_scanner()
-    hobj = mf.Hessian()
-    hobj.set(auxbasis_response=2)
-
+
     coords = pmol.atom_coords()
     v = np.zeros_like(coords)
     v[ix,iy] = eps
@@ -67,25 +77,13 @@ def _check_rhf_hessian(ix=0, iy=0, tol=1e-3):
     _, g1 = g_scanner(pmol)
     h_fd = (g0 - g1)/2.0/eps
 
-    pmol.set_geom_(coords, unit='Bohr')
-    h = hobj.kernel()
-    print(f"analytical Hessian H({ix},{iy})")
-    print(h[ix,:,iy,:])
-    print(f"finite different Hessian H({ix},{iy})")
-    print(h_fd)
-    print('Norm of diff', np.linalg.norm(h[ix,:,iy,:] - h_fd))
+    print(f'Norm of analytical - finite difference Hessian H({ix},{iy})', np.linalg.norm(h[ix,:,iy,:] - h_fd))
     assert(np.linalg.norm(h[ix,:,iy,:] - h_fd) < tol)
 
-def _check_dft_hessian(xc=xc0, disp=None, ix=0, iy=0, tol=1e-3):
-    pmol = mol.copy()
+def _check_dft_hessian(mf, h, ix=0, iy=0, tol=1e-3):
+    pmol = mf.mol.copy()
     pmol.build()
 
-    mf = dft.rks.RKS(pmol, xc=xc, disp=disp).density_fit(auxbasis=auxbasis0)
-    mf.conv_tol = 1e-12
-    mf.grids.level = grids_level
-    mf.verbose = 1
-    mf.kernel()
-
     g = mf.nuc_grad_method()
     g.auxbasis_response = True
     g.kernel()
@@ -101,57 +99,67 @@ def _check_dft_hessian(xc=xc0, disp=None, ix=0, iy=0, tol=1e-3):
     pmol.set_geom_(coords - v, unit='Bohr')
     pmol.build()
     _, g1 = g_scanner(pmol)
-    
+
     h_fd = (g0 - g1)/2.0/eps
-    pmol.set_geom_(coords, unit='Bohr')
-    pmol.build()
 
-    mf = dft.rks.RKS(pmol, xc=xc, disp=disp).density_fit(auxbasis=auxbasis0)
-    mf.grids.level = grids_level
-    mf.kernel()
-    hobj = mf.Hessian()
-    hobj.set(auxbasis_response=2)
-    hobj.verbose=0
-    h = hobj.kernel()
-
-    print(f"analytical Hessian H({ix},{iy})")
-    print(h[ix,:,iy,:])
-    print(f"finite different Hessian H({ix},{iy})")
-    print(h_fd)
-    print('Norm of diff', np.linalg.norm(h[ix,:,iy,:] - h_fd))
+    print(f'Norm of analytical - finite difference Hessian H({ix},{iy})', np.linalg.norm(h[ix,:,iy,:] - h_fd))
     assert(np.linalg.norm(h[ix,:,iy,:] - h_fd) < tol)
-    
+
 class KnownValues(unittest.TestCase):
     def test_hessian_rhf(self):
         print('-----testing DF RHF Hessian----')
-        _check_rhf_hessian(ix=0, iy=0)
-        _check_rhf_hessian(ix=0, iy=1)
-
+        mf = _make_rhf()
+        hobj = mf.Hessian()
+        hobj.set(auxbasis_response=2)
+        h = hobj.kernel()
+        _check_rhf_hessian(mf, h, ix=0, iy=0)
+        _check_rhf_hessian(mf, h, ix=0, iy=1)
+
     def test_hessian_lda(self):
         print('-----testing DF LDA Hessian----')
-        _check_dft_hessian(xc='LDA', disp=None, ix=0,iy=0)
-        _check_dft_hessian(xc='LDA', disp=None, ix=0,iy=1)
-
+        mf = _make_rks('LDA')
+        hobj = mf.Hessian()
+        hobj.set(auxbasis_response=2)
+        h = hobj.kernel()
+        _check_dft_hessian(mf, h, ix=0,iy=0)
+        _check_dft_hessian(mf, h, ix=0,iy=1)
+
     def test_hessian_gga(self):
         print('-----testing DF PBE Hessian----')
-        _check_dft_hessian(xc='PBE', disp=None, ix=0,iy=0)
-        _check_dft_hessian(xc='PBE', disp=None, ix=0,iy=1)
-
+        mf = _make_rks('PBE')
+        hobj = mf.Hessian()
+        hobj.set(auxbasis_response=2)
+        h = hobj.kernel()
+        _check_dft_hessian(mf, h, ix=0,iy=0)
+        _check_dft_hessian(mf, h, ix=0,iy=1)
+
     def test_hessian_hybrid(self):
         print('-----testing DF B3LYP Hessian----')
-        _check_dft_hessian(xc='B3LYP', disp=None, ix=0,iy=0)
-        _check_dft_hessian(xc='B3LYP', disp=None, ix=0,iy=1)
+        mf = _make_rks('b3lyp')
+        hobj = mf.Hessian()
+        hobj.set(auxbasis_response=2)
+        h = hobj.kernel()
+        _check_dft_hessian(mf, h, ix=0,iy=0)
+        _check_dft_hessian(mf, h, ix=0,iy=1)
 
     def test_hessian_mgga(self):
         print('-----testing DF M06 Hessian----')
-        _check_dft_hessian(xc='m06', disp=None, ix=0,iy=0)
-        _check_dft_hessian(xc='m06', disp=None, ix=0,iy=1)
-
+        mf = _make_rks('m06')
+        hobj = mf.Hessian()
+        hobj.set(auxbasis_response=2)
+        h = hobj.kernel()
+        _check_dft_hessian(mf, h, ix=0,iy=0)
+        _check_dft_hessian(mf, h, ix=0,iy=1)
+
     def test_hessian_rsh(self):
         print('-----testing DF wb97 Hessian----')
-        _check_dft_hessian(xc='wb97', disp=None, ix=0,iy=0)
-        _check_dft_hessian(xc='wb97', disp=None, ix=0,iy=1)
-
+        mf = _make_rks('wb97')
+        hobj = mf.Hessian()
+        hobj.set(auxbasis_response=2)
+        h = hobj.kernel()
+        _check_dft_hessian(mf, h, ix=0,iy=0)
+        _check_dft_hessian(mf, h, ix=0,iy=1)
+
     def test_hessian_D3(self):
         pmol = mol.copy()
         pmol.build()
@@ -161,11 +169,11 @@ def test_hessian_D3(self):
         mf.grids.level = grids_level
         mf.verbose = 1
         mf.kernel()
-        
+
         hobj = mf.Hessian()
         hobj.set(auxbasis_response=2)
         hobj.verbose=0
-        h = hobj.kernel()
+        hobj.kernel()
 
     def test_hessian_D4(self):
         pmol = mol.copy()
@@ -180,7 +188,7 @@ def test_hessian_D4(self):
         hobj = mf.Hessian()
         hobj.set(auxbasis_response=2)
         hobj.verbose=0
-        h = hobj.kernel()
+        hobj.kernel()
 
 if __name__ == "__main__":
     print("Full Tests for DF Hessian")

gpu4pyscf/solvent/hessian/pcm.py

@@ -193,7 +193,7 @@ def pcm_vmat_scanner(mol):
     pcmobj.reset(pmol)
     return vmat
 
-'''
+"""
 def analytic_grad_vmat(pcmobj, mo_coeff, mo_occ, atmlst=None, verbose=None):
     '''
     dv_solv / da
@@ -221,7 +221,7 @@ def analytic_grad_vmat(pcmobj, mo_coeff, mo_occ, atmlst=None, verbose=None):
     t1 = log.timer_debug1('computing solvent grad veff', *t1)
     pcmobj.reset(pmol)
     return vmat
-'''
+"""
 def make_hess_object(hess_method):
     '''
     return solvent hessian object

gpu4pyscf/solvent/tests/test_pcm_hessian.py

@@ -54,7 +54,7 @@ def _make_mf(method='C-PCM'):
     return mf
 
 def _check_hessian(mf, h, ix=0, iy=0):
-    pmol = mol.copy()
+    pmol = mf.mol.copy()
     pmol.build()
 
     g = mf.nuc_grad_method()
@@ -81,7 +81,6 @@ def _check_hessian(mf, h, ix=0, iy=0):
     assert(np.linalg.norm(h[ix,:,iy,:] - h_fd) < tol)
 
 class KnownValues(unittest.TestCase):
-
     def test_hess_cpcm(self):
         mf = _make_mf(method='C-PCM')
         hobj = mf.Hessian()