对比学习法增改

dpgen/data/Pnma/origin_backup.cif

@@ -0,0 +1,53 @@
+#------------------------------------------------------------------------------
+# CIF (Crystallographic Information File) for Li3YCl6
+# Data source: Table S1 from the provided image.
+# Rietveld refinement result of the neutron diffraction pattern for the 450 °C-annealed sample.
+#------------------------------------------------------------------------------
+
+data_Li3YCl6
+
+_chemical_name_systematic      'Lithium Yttrium Chloride'
+_chemical_formula_sum          'Li3 Y1 Cl6'
+_chemical_formula_structural   'Li3YCl6'
+
+_symmetry_space_group_name_H-M   'P n m a'
+_symmetry_Int_Tables_number      62
+_symmetry_cell_setting           orthorhombic
+
+loop_
+_symmetry_equiv_pos_as_xyz
+'x, y, z'
+'-x+1/2, y+1/2, -z+1/2'
+'-x, -y, -z'
+'x+1/2, -y+1/2, z+1/2'
+'-x, y+1/2, -z'
+'x-1/2, -y-1/2, z-1/2'
+'x, -y, z'
+'-x-1/2, y-1/2, -z-1/2'
+
+_cell_length_a                   12.92765(13)
+_cell_length_b                   11.19444(10)
+_cell_length_c                   6.04000(12)
+_cell_angle_alpha                90.0
+_cell_angle_beta                 90.0
+_cell_angle_gamma                90.0
+_cell_volume                     874.15
+_cell_formula_units_Z            4
+
+loop_
+_atom_site_label
+_atom_site_type_symbol
+_atom_site_fract_x
+_atom_site_fract_y
+_atom_site_fract_z
+_atom_site_occupancy
+_atom_site_Wyckoff_symbol
+_atom_site_U_iso_or_equiv
+Li1   Li   0.11730(7)   0.09640(7)   0.04860(10)   0.750(13)   8d   4.579(2)
+Li2   Li   0.13270(9)   0.07900(10)  0.48600(2)    0.750(19)   8d   9.554(4)
+Cl1   Cl   0.21726(7)   0.58920(7)   0.26362(11)   1.0         8d   0.797(17)
+Cl2   Cl   0.45948(8)   0.08259(8)   0.23831(13)   1.0         8d   1.548(2)
+Cl3   Cl   0.04505(10)  0.25000      0.74110(2)    1.0         4c   1.848(3)
+Cl4   Cl   0.20205(9)   0.25000      0.24970(2)    1.0         4c   0.561(2)
+Y1    Y    0.37529(10)  0.25000      0.01870(3)    1.0         4c   1.121(17)
+#------------------------------------------------------------------------------

dpgen/plus.py

@@ -0,0 +1,151 @@
+import random
+from typing import List
+from pymatgen.core import Structure
+from pymatgen.io.vasp import Poscar
+
+def _is_close_frac(z, target, tol=2e-2):
+    t = target % 1.0
+    return min(abs(z - t), abs(z - (t + 1)), abs(z - (t - 1))) < tol
+
+def make_model3_poscar_from_cif(cif_path: str,
+                                out_poscar: str = "POSCAR_model3_supercell",
+                                seed: int = 42,
+                                tol: float = 2e-2):
+    """
+    将 model3.cif 扩胞为 [[3,0,0],[2,4,0],[0,0,6]] 的2160原子超胞，并把部分占据位点(Y2=0.75, Y3=0.25, Li2=0.5)
+    显式有序化后写出 POSCAR。
+    """
+    random.seed(seed)
+
+    # 1) 读取 CIF
+    s = Structure.from_file(cif_path)
+
+    # 2) 扩胞（a_s=3a0, b_s=2a0+4b0, c_s=6c0）[1]
+    T = [[3, 0, 0],
+         [2, 4, 0],
+         [0, 0, 6]]
+    s.make_supercell(T)
+
+    # 3) 识别三类需取整的位点：Y2、Y3、Li2
+    y2_idx: List[int] = []
+    y3_idx: List[int] = []
+    li2_idx: List[int] = []
+
+    for i, site in enumerate(s.sites):
+        # 兼容不同版本pymatgen
+        try:
+            el = site.species.elements[0].symbol
+        except Exception:
+            ss = site.species_string
+            el = "Li" if ss.startswith("Li") else ("Y" if ss.startswith("Y") else ("Cl" if ss.startswith("Cl") else ss))
+        z = site.frac_coords[2]
+        if el == "Y":
+            if _is_close_frac(z, 0.488, tol):
+                y2_idx.append(i)
+            elif _is_close_frac(z, -0.065, tol) or _is_close_frac(z, 0.935, tol):
+                y3_idx.append(i)
+        elif el == "Li":
+            if _is_close_frac(z, 0.5, tol):
+                li2_idx.append(i)
+
+    def choose_keep(idxs, frac_keep):
+        n = len(idxs)
+        k = int(round(n * frac_keep))
+        if k < 0: k = 0
+        if k > n: k = n
+        keep = set(random.sample(idxs, k)) if 0 < k < n else set(idxs if k == n else [])
+        drop = [i for i in idxs if i not in keep]
+        return keep, drop
+
+    keep_y2, drop_y2 = choose_keep(y2_idx, 0.75)
+    keep_y3, drop_y3 = choose_keep(y3_idx, 0.25)
+    keep_li2, drop_li2 = choose_keep(li2_idx, 0.50)
+
+    # 4) 保留者占据设为1，其余删除
+    for i in keep_y2 | keep_y3:
+        s.replace(i, "Y")
+    for i in keep_li2:
+        s.replace(i, "Li")
+    to_remove = sorted(drop_y2 + drop_y3 + drop_li2, reverse=True)
+    for i in to_remove:
+        s.remove_sites([i])
+
+    # 5) 最终清理：消除任何残留的部分占据（防止 POSCAR 写出报错）
+    # 若有 site.is_ordered==False，则取该站位的“主要元素”替换为占据=1
+    for i, site in enumerate(s.sites):
+        if not site.is_ordered:
+            d = site.species.as_dict()  # {'Li': 0.5} 或 {'Li':0.5,'Y':0.5}
+            elem = max(d.items(), key=lambda kv: kv[1])[0]
+            s.replace(i, elem)
+
+    # 6) 排序并写出 POSCAR
+    order = {"Li": 0, "Y": 1, "Cl": 2}
+    s = s.get_sorted_structure(key=lambda site: order.get(site.species.elements[0].symbol, 99))
+    Poscar(s).write_file(out_poscar)
+
+    # 报告
+    comp = {k: int(v) for k, v in s.composition.as_dict().items()}
+    print(f"写出 {out_poscar}；总原子数 = {len(s)}")
+    print(f"Y2识别={len(y2_idx)}，Y3识别={len(y3_idx)}，Li2识别={len(li2_idx)}；组成={comp}")
+
+import random
+from typing import List
+from pymatgen.core import Structure
+from pymatgen.io.vasp import Poscar
+
+def make_pnma_poscar_from_cif(cif_path: str,
+                               out_poscar: str = "POSCAR_pnma_supercell",
+                               seed: int = 42,
+                               supercell=(3,3,6),
+                               tol: float = 1e-6):
+    """
+    读取 Pnma 的 CIF（如 origin.cif），扩胞到 2160 原子，并把部分占据的 Li 位点(0.75)显式取整后写出 POSCAR。
+    默认超胞尺度为(3,3,6)，体积放大因子=54，40原子/原胞×54=2160 [1][3]。
+    """
+    random.seed(seed)
+
+    s = Structure.from_file(cif_path)
+
+    # 扩胞；Pnma原胞已是正交，直接用对角放缩
+    s.make_supercell(supercell)
+
+    # 找出所有“部分占据的 Li”位点
+    partial_li_idx: List[int] = []
+    for i, site in enumerate(s.sites):
+        if not site.is_ordered:
+            d = site.species.as_dict()  # 例如 {'Li': 0.75}
+            # 只处理主要元素是Li且占据<1的位点
+            m_elem, m_occ = max(d.items(), key=lambda kv: kv[1])
+            if m_elem == "Li" and m_occ < 1 - tol:
+                partial_li_idx.append(i)
+
+    # 以占据0.75进行随机取整：保留75%，其余删除为“空位”
+    n = len(partial_li_idx)
+    k = int(round(n * 0.75))
+    keep = set(random.sample(partial_li_idx, k)) if 0 < k < n else set(partial_li_idx if k == n else [])
+    drop = sorted([i for i in partial_li_idx if i not in keep], reverse=True)
+
+    # 保留者设为占据=1；删除其余
+    for i in keep:
+        s.replace(i, "Li")
+    for i in drop:
+        s.remove_sites([i])
+
+    # 兜底：若仍有部分占据，强制取主要元素
+    for i, site in enumerate(s.sites):
+        if not site.is_ordered:
+            d = site.species.as_dict()
+            elem = max(d.items(), key=lambda kv: kv[1])[0]
+            s.replace(i, elem)
+
+    # 排序并写POSCAR
+    order = {"Li": 0, "Y": 1, "Cl": 2}
+    s = s.get_sorted_structure(key=lambda site: order.get(site.species.elements[0].symbol, 99))
+    Poscar(s).write_file(out_poscar)
+
+    comp = {k: int(v) for k, v in s.composition.as_dict().items()}
+    print(f"写出 {out_poscar}；总原子数 = {len(s)}；组成 = {comp}")
+
+if __name__=="__main__":
+    # make_model3_poscar_from_cif("data/P3ma/model3.cif","data/P3ma/supercell_model4.poscar")
+    make_pnma_poscar_from_cif("data/Pnma/origin.cif","data/Pnma/supercell_pnma.poscar",seed=42)