Format according to preview ruff rules

Author: briling

qstack/basis_opt/opt.py

@@ -43,7 +43,6 @@ def energy(x):
             E += qbbt.energy_mol(newbasis, m)
         return E
 
-
     def gradient(x):
         """Compute total loss function (fitting error) and gradient for given exponents.
 
@@ -76,7 +75,6 @@ def gradient(x):
         dE_dx = dE_da * exponents
         return E, dE_dx
 
-
     def gradient_only(x):
         """Compute only the gradient of the loss function (wrapper for optimization algorithms).
 
@@ -88,7 +86,6 @@ def gradient_only(x):
         """
         return gradient(x)[1]
 
-
     def read_bases(basis_files):
         """Read basis set definitions from files or dicts.
 
@@ -117,7 +114,6 @@ def read_bases(basis_files):
                 basis.update(i)
         return basis
 
-
     def make_bf_start():
         """Create basis function index bounds for each element.
 
@@ -131,7 +127,6 @@ def make_bf_start():
             bf_bounds[q] = [start, start+nbf[i]]
         return bf_bounds
 
-
     def make_moldata(fname):
         """Create molecular data dictionary from file or dict.
 

qstack/constants.py

@@ -3,10 +3,13 @@
 https://physics.nist.gov/cuu/Constants/
 https://physics.nist.gov/cuu/Constants/Table/allascii.txt
 """
+import math
+
+
 # Constants
 SPEED_LIGHT = 299792458.0
 PLANCK = 6.62607004e-34
-HBAR = PLANCK/(2*3.141592653589793)
+HBAR = PLANCK/(2*math.pi)
 FUND_CHARGE = 1.6021766208e-19
 MOL_NA = 6.022140857e23
 MASS_E = 9.10938356e-31
@@ -20,4 +23,4 @@
 BOHR2ANGS = 0.52917721092  # Angstroms
 HARTREE2J = HBAR**2/(MASS_E*(BOHR2ANGS*1e-10)**2)
 HARTREE2EV = 27.21138602
-AU2DEBYE = FUND_CHARGE * BOHR2ANGS*1e-10 / DEBYE # 2.541746
+AU2DEBYE = FUND_CHARGE * BOHR2ANGS*1e-10 / DEBYE  # 2.541746

qstack/equio.py

@@ -28,7 +28,6 @@
 _molid_name = 'mol_id'
 
 
-
 def _get_llist(mol):
     """Get list of angular momentum quantum numbers for basis functions of each element of a molecule.
 
@@ -50,7 +49,7 @@ def _get_tsize(tensor):
     Returns:
         int: Total size of the tensor (total number of elements).
     """
-    return sum([np.prod(tensor.block(key).values.shape) for key in tensor.keys])
+    return sum(np.prod(tensor.block(key).values.shape) for key in tensor.keys)
 
 
 def _labels_to_array(labels):
@@ -120,19 +119,19 @@ def vector_to_tensormap(mol, c):
         if llists[q]==sorted(llists[q]):
             for l in set(llists[q]):
                 msize = 2*l+1
-                nsize = blocks[(l,q)].shape[-1]
+                nsize = blocks[l,q].shape[-1]
                 cslice = c[i(nsize*msize)].reshape(nsize,msize).T
                 if l==1:  # for l=1, the pyscf order is x,y,z (1,-1,0)
                     cslice = cslice[pyscf2gpr_l1_order]
-                blocks[(l,q)][iq[q],:,:] = cslice
+                blocks[l,q][iq[q],:,:] = cslice
         else:
             il = dict.fromkeys(range(max(llists[q]) + 1), 0)
             for l in llists[q]:
                 msize = 2*l+1
                 cslice = c[i(msize)]
                 if l==1:  # for l=1, the pyscf order is x,y,z (1,-1,0)
                     cslice = cslice[pyscf2gpr_l1_order]
-                blocks[(l,q)][iq[q],:,il[l]] = cslice
+                blocks[l,q][iq[q],:,il[l]] = cslice
                 il[l] += 1
         iq[q] += 1
 
@@ -256,7 +255,7 @@ def matrix_to_tensormap(mol, dm):
                         dmslice = np.transpose(dmslice, axes=[1,3,0,2]).reshape(msize1,msize2,-1)
                         block = tensor_blocks[tm_label_vals.index((l1,l2,q1,q2))]
                         at_p = block.samples.position((iat1,iat2))
-                        blocks[(l1,l2,q1,q2)][at_p,:,:,:] = dmslice
+                        blocks[l1,l2,q1,q2][at_p,:,:,:] = dmslice
                     iq2[q2] += 1
             iq1[q1] += 1
     else:
@@ -275,7 +274,7 @@ def matrix_to_tensormap(mol, dm):
                         block = tensor_blocks[tm_label_vals.index((l1, l2, q1, q2))]
                         at_p = block.samples.position((iat1, iat2))
                         n_p = block.properties.position((il1[l1], il2[l2]))
-                        blocks[(l1,l2,q1,q2)][at_p,:,:,n_p] = dmslice
+                        blocks[l1,l2,q1,q2][at_p,:,:,n_p] = dmslice
                         il2[l2] += 1
                     iq2[q2] += 1
                 il1[l1] += 1
@@ -486,7 +485,7 @@ def split(tensor):
                 continue
             sampleidx = [t[0] for t in samples]
             samplelbl = [t[1] for t in samples]
-            #sampleidx = [block.samples.position(lbl) for lbl in samplelbl]
+            # sampleidx = [block.samples.position(lbl) for lbl in samplelbl]
 
             blocks[key] = block.values[sampleidx]
             block_samp_labels[key] = metatensor.Labels(tensor.sample_names[1:], np.array(samplelbl)[:,1:])

qstack/fields/dm.py

@@ -103,4 +103,3 @@ def sphericalize_density_matrix(mol, dm):
                         spherical_dm[idx+m,jdx+m] = trace / msize
 
     return spherical_dm
-

qstack/fields/dori.py

@@ -44,7 +44,7 @@ def eval_rho_dm(mol, ao, dm, deriv=2):
         if deriv==2:
             DM_dAO_dr_i = 2 * _dot_ao_dm(mol, dAO_dr[i], dm, None, None, None)
             for j in range(i, 3):
-                d2rho_dr2[i,j] = _contract_rho(dAO_dr[j], DM_dAO_dr_i) + 2.0*np.einsum('ip,ip->i', d2AO_dr2[triu_idx[(i,j)]], DM_AO)
+                d2rho_dr2[i,j] = _contract_rho(dAO_dr[j], DM_dAO_dr_i) + 2.0*np.einsum('ip,ip->i', d2AO_dr2[triu_idx[i,j]], DM_AO)
                 d2rho_dr2[j,i] = d2rho_dr2[i,j]
 
     if deriv==1:

qstack/fields/excited.py

@@ -120,7 +120,7 @@ def exciton_properties_dm(mol, hole, part):
     dist = np.linalg.norm(hole_r-part_r)
     hole_extent = np.sqrt(hole_r2-hole_r@hole_r)
     part_extent = np.sqrt(part_r2-part_r@part_r)
-    return(dist, hole_extent, part_extent)
+    return dist, hole_extent, part_extent
 
 
 def exciton_properties(mol, hole, part):

qstack/mathutils/wigner.py

@@ -56,7 +56,7 @@ def get_polynom_Y(l, m):
     r = Symbol('r', nonnegative=True)
     expr = real_Y_correct_phase(l,m, theta, phi) * r**l
     expr = expand(expr, func=True)
-    expr = expr.rewrite(sp.cos)#.simplify().trigsimp()
+    expr = expr.rewrite(sp.cos)  # .simplify().trigsimp()
     expr = expand_trig(expr)
     expr = cancel(expr)
     expr = expr.subs({r: sp.sqrt(x*x+y*y+z*z), phi: sp.atan2(y,x), theta: sp.atan2(sp.sqrt(x*x+y*y),z)})
@@ -139,7 +139,6 @@ def compute_wigner(lmax):
             # rotated spherical harmonic
             Y_rot[l][m] = Y[l][m].subs({x: x1, y:y1, z:z1}).subs({x1:xx*x+xy*y+xz*z, y1:yx*x+yy*y+yz*z, z1:zx*x+zy*y+zz*z})
 
-
     D = [zeros(2*l+1,2*l+1) for l in range(lmax+1)]
     integrals_xyz_dict = {}
     for l in range(lmax+1):
@@ -159,4 +158,3 @@ def compute_wigner(lmax):
 
     D = compute_wigner(lmax)
     print_wigner(D)
-

qstack/mathutils/xyz_integrals_float.py

@@ -70,4 +70,3 @@ def trinomial(k1, k2, k3):
 if __name__ == "__main__":
     k,n,m = map(int, sys.argv[1:4])
     print(f"{xyz(k,n,m):.15f} π")
-

qstack/orcaio.py

@@ -91,7 +91,6 @@ def read_density(mol, basename, directory='./', version=500, openshell=False, re
     else:
         dm = np.fromfile(path[0], offset=8, count=mol.nao*mol.nao*nspin).reshape((nspin,mol.nao,mol.nao))
 
-
     is_def2 = 'def2' in pyscf.gto.basis._format_basis_name(mol.basis)
     has_3d = np.any([21 <= pyscf.data.elements.charge(q) <= 30 for q in mol.elements])
     if is_def2 and has_3d:
@@ -277,4 +276,3 @@ def read_gbw(mol, fname, reorder_dest='pyscf', sort_l=True):
     if reorder_dest is not None:
         reorder_coeff_inplace(c, mol, reorder_dest, ls if (ls and sort_l) else None)
     return c, e, occ
-

qstack/qml/b2r2.py

@@ -177,7 +177,7 @@ def get_b2r2_a_molecular(ncharges, coords, elements,
             coords_b = coords[j]
             R = np.linalg.norm(coords_b - coords_a)
             if R < rcut:
-                twobodyrep[bag_idx[(ncharge_a, ncharge_b)]] += get_gaussian(grid, R)
+                twobodyrep[bag_idx[ncharge_a, ncharge_b]] += get_gaussian(grid, R)
 
     twobodyrep = 2.0*np.concatenate(twobodyrep)
     return twobodyrep