rename analysis -> descriptors and integrate with new feature settings

ciderpress/gpaw/atom_analysis_utils.py → ciderpress/gpaw/atom_descriptor_utils.py

@@ -389,7 +389,6 @@ def _get_paw_helper2(
         dydf_obg = dFdf_oag
     Nalpha = self.Nalpha
 
-    # TODO consts should be removed to make use of feat normalizers
     x_sig = np.zeros((nspin, nfeat, ngrid))
     dxdf_oig = np.zeros((norb, nfeat, ngrid))
     for s in range(nspin):
@@ -406,7 +405,7 @@ def _get_paw_helper2(
                 C_pg = self.C_aip[a, i_g].T
                 pa_g = C_pg[0] + dq0_g * (C_pg[1] + dq0_g * (C_pg[2] + dq0_g * C_pg[3]))
                 x_sig[s, i] += pa_g * y_sbg[s, a]
-            x_sig[s, i] *= ((self.consts[i, 1] + self.consts[-1, 1]) / 2) ** 1.5
+            # x_sig[s, i] *= ((self.consts[i, 1] + self.consts[-1, 1]) / 2) ** 1.5
     for o in range(norb):
         s = p_o[o][0]
         for i in range(nfeat):
@@ -425,7 +424,7 @@ def _get_paw_helper2(
                 dpa_g = 0.5 * (C_pg[1] + dq0_g * (2 * C_pg[2] + dq0_g * 3 * C_pg[3]))
                 dxdf_oig[o, i] += dpa_g * dadf_g * y_sbg[s, a]
                 dxdf_oig[o, i] += pa_g * dydf_obg[o, a]
-            dxdf_oig[o, i] *= ((self.consts[i, 1] + self.consts[-1, 1]) / 2) ** 1.5
+            # dxdf_oig[o, i] *= ((self.consts[i, 1] + self.consts[-1, 1]) / 2) ** 1.5
 
     return x_sig, dxdf_oig
 

ciderpress/gpaw/calculator.py

@@ -40,7 +40,7 @@ def get_cider_functional(
     _force_nonlocal=False,
 ):
     """
-    Initialize a CIDER surrogate hybrid exchange function of the form
+    Initialize a CIDER surrogate hybrid XC functional of the form
     E_xc = E_x^sl * (1 - xmix) + E_c^sl + xmix * E_x^CIDER
     where E_x^sl is given by the xkernel parameter, E_c^sl is given by the ckernel
     parameter, and E_x^CIDER is the ML exchange energy contains in mlfunc.
@@ -50,9 +50,9 @@ def get_cider_functional(
     but correctness is not guaranteed because the nonlocal features will
     not be correct due to the lack of core electrons.
 
-    NOTE: If the mlfunc is determined to be semi-local, all the
+    NOTE: If the mlfunc is determined to be semilocal, all the
     internal settings are ignored, and a simpler, more efficient
-    class is returned to evaluate the semi-local functional.
+    class is returned to evaluate the semilocal functional.
 
     Args:
         mlfunc (MappedXC, str): An ML functional object or a str
@@ -162,7 +162,7 @@ class is returned to evaluate the semi-local functional.
         msg = "Only implemented for b and d version, found {}"
         raise ValueError(msg.format(mlfunc.desc_version))
 
-    const_list = _get_const_list(mlfunc)
+    const_list = get_const_list(mlfunc.settings.nldf_settings)
     nexp = 4
 
     if use_paw:
@@ -299,19 +299,21 @@ def cider_functional_from_dict(d):
         else:
             # xc_params should have Nalpha, lambd, encut.
             # For PAW, it should also have pasdw_ovlp_fit, pasdw_store_funcs.
-            const_list = _get_const_list(mlfunc)
+            const_list = get_const_list(mlfunc.settings.nldf_settings)
             xc = cls(cider_kernel, nexp, const_list, **(d["xc_params"]))
     else:
         xc = cls(LibXC(d["name"]))
 
     return xc
 
 
-def _get_const_list(mlfunc):
-    settings = mlfunc.settings.nldf_settings
+def get_const_list(settings):
+    """
+    settings should be NLDFSettings object
+    """
     thetap = 2 * np.array(settings.theta_params)
     vvmul = thetap[0] / (2 * settings.feat_params[1][0])
-    fac_mul = thetap[2] if mlfunc.settings.sl_settings.level == "MGGA" else thetap[1]
+    fac_mul = thetap[2] if settings.sl_level == "MGGA" else thetap[1]
     consts = np.array([0.00, thetap[0], fac_mul, thetap[0] / 64]) / vvmul
     const_list = np.stack([0.5 * consts, 1.0 * consts, 2.0 * consts, consts * vvmul])
     return const_list

ciderpress/gpaw/cider_fft.py

@@ -1237,8 +1237,8 @@ def from_mlfunc(
 
 class CiderGGA(_CiderBase, GGA):
     def __init__(self, cider_kernel, nexp, consts, **kwargs):
-        if cider_kernel.mlfunc.desc_version != "d":
-            raise ValueError("Wrong mlfunc version")
+        if cider_kernel.mlfunc.settings.sl_settings.level != "GGA":
+            raise ValueError("CiderGGA only supports GGA functionals!")
         _CiderBase.__init__(self, cider_kernel, nexp, consts, **kwargs)
 
         GGA.__init__(self, LibXC("PBE"), stencil=2)
@@ -1335,9 +1335,8 @@ def integrate(a1_g, a2_g=None):
 
 class CiderMGGA(_CiderBase, MGGA):
     def __init__(self, cider_kernel, nexp, consts, **kwargs):
-
-        if cider_kernel.mlfunc.desc_version != "b":
-            raise ValueError("Wrong mlfunc version")
+        if cider_kernel.mlfunc.settings.sl_settings.level != "MGGA":
+            raise ValueError("CiderMGGA only supports MGGA functionals!")
         _CiderBase.__init__(self, cider_kernel, nexp, consts, **kwargs)
 
         MGGA.__init__(self, LibXC("PBE"), stencil=2)