use pyscf convention for nuc_grad_method

Author: jeanwsr

examples/dh/03-relaxed-dm.py

@@ -40,6 +40,6 @@
 # 3. Relaxed DM (AO basis)
 rdm1_ao = mf_g.make_rdm1_relaxed(ao_repr=True)
 
-# 4. .dipole() method uses relaxed DM internally
-dip = mf.dipole()
+# 4. .dipole() method on Gradients uses relaxed DM internally
+dip = mf_g.dipole()
 print(f"Dipole (via .dipole):   {np.linalg.norm(dip):.6f} a.u.")

pyscf/dh/grad/dfdh.py

@@ -343,10 +343,9 @@ def _add_dispersion_gradient(self, grad_contrib):
 
 class Gradients(RDFDH, RDHRespMixin, GradientMixin):
 
-    def __init__(self, mol: gto.Mole, *args, skip_construct=False, **kwargs):
-        if not skip_construct:
-            super(Gradients, self).__init__(mol, *args, **kwargs)
-        # results
+    def __init__(self, method):
+        self.__dict__.update(method.__dict__)
+        self._base = method
         self.grad_jk = NotImplemented
         self.grad_gga = NotImplemented
         self.grad_pt2 = NotImplemented

pyscf/dh/grad/udfdh.py

@@ -25,7 +25,7 @@
 from pyscf.dh.dhutil import calc_batch_size, gen_batch, gen_shl_batch, tot_size, timing, as_scanner_grad
 from pyscf.dh.grad.dfdh import get_H_1_ao, get_S_1_ao, generator_L_1, kernel, GradientMixin
 # pyscf import
-from pyscf import gto, lib, df
+from pyscf import lib, df
 from pyscf.df.grad.rhf import _int3c_wrapper as int3c_wrapper
 # other import
 import numpy as np
@@ -118,10 +118,9 @@ def get_gradient_jk(dfobj: df.DF, C, D, D_r, Y_mo, cx, cx_n, max_memory=2000):
 
 class Gradients(UDFDH, UDHRespMixin, GradientMixin):
 
-    def __init__(self, mol: gto.Mole, *args, skip_construct=False, **kwargs):
-        if not skip_construct:
-            super(Gradients, self).__init__(mol, *args, **kwargs)
-        # results
+    def __init__(self, method):
+        self.__dict__.update(method.__dict__)
+        self._base = method
         self.grad_jk = NotImplemented
         self.grad_gga = NotImplemented
         self.grad_pt2 = NotImplemented

pyscf/dh/polar/rdfdh.py

@@ -24,7 +24,7 @@
 from pyscf.dh.resp import RDHRespMixin
 from pyscf.dh.dhutil import gen_batch, get_rho_from_dm_gga, restricted_biorthogonalize, hermi_sum_last2dim
 from pyscf.dh.xccode import xc_equal
-from pyscf import gto, lib
+from pyscf import lib
 import numpy as np
 
 einsum = lib.einsum
@@ -92,9 +92,9 @@ def _rks_gga_wv2(rho0, rho1, rho2, fxc, kxc, weight):
 
 class Polar(RDFDH, RDHRespMixin):
 
-    def __init__(self, mol: gto.Mole, *args, skip_construct=False, **kwargs):
-        if not skip_construct:
-            super(Polar, self).__init__(mol, *args, **kwargs)
+    def __init__(self, method):
+        self.__dict__.update(method.__dict__)
+        self._base = method
         self.pol_scf = NotImplemented
         self.pol_corr = NotImplemented
         self.pol_tot = NotImplemented

pyscf/dh/polar/udfdh.py

@@ -26,7 +26,7 @@
 from pyscf.dh.dhutil import gen_batch, get_rho_from_dm_gga, tot_size, hermi_sum_last2dim
 from pyscf.dh.xccode import xc_equal
 # pyscf import
-from pyscf import gto, lib, dft
+from pyscf import lib, dft
 from pyscf.dft.numint import _scale_ao
 from pyscf.lib.numpy_helper import ANTIHERMI
 # other import
@@ -138,9 +138,9 @@ def nprop(self):
             self.prepare_H_1()
         return self.tensors["H_1_ao"].shape[0]
 
-    def __init__(self, mol: gto.Mole, *args, skip_construct=False, **kwargs):
-        if not skip_construct:
-            super(Polar, self).__init__(mol, *args, **kwargs)
+    def __init__(self, method):
+        self.__dict__.update(method.__dict__)
+        self._base = method
         self.pol_scf = NotImplemented
         self.pol_corr = NotImplemented
         self.pol_tot = NotImplemented

pyscf/dh/rdfdh.py

@@ -172,15 +172,11 @@ def build(sI, t_ijab, g_ijab):
 
     def nuc_grad_method(self):
         from pyscf.dh.grad.dfdh import Gradients
-        self.__class__ = Gradients
-        Gradients.__init__(self, self.mol, skip_construct=True)
-        return self
+        return Gradients(self)
 
     def polar_method(self):
         from pyscf.dh.polar.rdfdh import Polar
-        self.__class__ = Polar
-        Polar.__init__(self, self.mol, skip_construct=True)
-        return self
+        return Polar(self)
 
     energy_elec_pt2 = energy_elec_pt2
     energy_elec_mp2 = energy_elec_mp2_ajz

pyscf/dh/udfdh.py

@@ -219,19 +219,13 @@ def prepare_pt2(self, dump_t_ijab=True, fast_trans=True):
 
         return self
 
-    @timing
-    # A REALLY DIRTY WAY transform to son class https://stackoverflow.com/questions/7078134/
     def nuc_grad_method(self):
         from pyscf.dh.grad.udfdh import Gradients
-        self.__class__ = Gradients
-        Gradients.__init__(self, self.mol, skip_construct=True)
-        return self
+        return Gradients(self)
 
     def polar_method(self):
         from pyscf.dh.polar.udfdh import Polar
-        self.__class__ = Polar
-        Polar.__init__(self, self.mol, skip_construct=True)
-        return self
+        return Polar(self)
 
     energy_elec_pt2 = energy_elec_pt2
     energy_elec_mp2 = energy_elec_ump2_ajz