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interface_connection/__init__.py

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+
+from .latmatcher_interface import compute_supercell, compute_supercell_a, compute_supercell_b

interface_connection/latmatcher_interface.py

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+
+
+from backend.latmathcher.plots import plot_atom_list
+from backend.latmathcher import atoms_to_greed
+from backend.latmathcher import PipelineLatMatch
+from backend.db_utils.utils import structure_ato_list
+from backend.db_utils.parse_c2db import from_c2db_structure, read_c2db_json
+from backend.db_utils.structure_database import DBInstance
+
+
+import matplotlib.pyplot as plt
+import matplotlib.patches as patches
+import os
+import shutil
+import numpy as np
+import periodictable
+import ast
+
+def get_atomic_number(element_symbol):
+    # Find the element in the periodic table and return its atomic number
+    element = getattr(periodictable, element_symbol)
+    return element.number
+
+
+def compute_supercell_a(file_material_a, file_material_b, file_source_a, file_source_b, max_angle, max_strain):
+
+
+    #
+    ip = "test_ip"  # get_client_ip(response)
+
+    db_latmatcher_path = "/Users/voicutomut/Documents/GitHub/BespokeMaterials/DB/LatMatcher"
+    new_directory = db_latmatcher_path + "/{}__ma{}__ms{}_on{}".format(ip, max_angle, max_strain,
+                                                                       len(os.listdir(db_latmatcher_path)))
+    if not os.path.exists(new_directory):
+        os.makedirs(new_directory)
+    path_to_move = new_directory
+
+    file1 = process_file(file_material_a, path_to_move+"/")
+    file2 = process_file(file_material_b, path_to_move+"/")
+
+
+    if file_source_a == "c2db.json":
+        A_structure = from_c2db_structure(read_c2db_json(file1))
+        A_cell=A_structure["cell"]
+    if file_source_b == "c2db.json":
+        B_structure = from_c2db_structure(read_c2db_json(file2))
+        B_cell=B_structure["cell"]
+
+
+
+    if file_source_a == ".xyz":
+        A_structure = extract_from_xyz(file1)
+        A_cell = A_structure["cell"]
+    if file_source_b == ".xyz":
+        B_structure = extract_from_xyz(file2)
+        B_cell=B_structure["cell"]
+
+
+    if file_source_a == "bespoke.json":
+        A_structure = extract_from_bespoke(file1)
+        A_cell = A_structure["cell"]
+    if file_source_b == "bespoke.json":
+        B_structure = extract_from_bespoke(file2)
+        B_cell=B_structure["cell"]
+
+
+    super_xyz, min_supercel= compute_supercell(A_cell, B_cell, A_structure, B_structure )
+    rez=min_supercel.rez
+
+    # Write the new file:
+    name = "solution"
+    file12 = path_to_move + "/" + name + ".xyz"
+
+    xyz_content = "{"+"'lattice_vectors':{}".format(np.array2string(min_supercel.get_new_structure()['lattice_vectors'],
+                                                                  separator=', ',
+                                                                   max_line_width=np.inf).replace("\n"," "))+"}\n\n"
+
+    xyz_content += f"{len(super_xyz)}\n\n"
+    xyz_content += "\n".join([f"{atom[0]} {' '.join(map(str, atom[1]))}" for atom in super_xyz])
+
+    # Write the content to a file
+    with open(file12, 'w') as file:
+        file.write(xyz_content)
+
+
+    plot=plot_supercel(super_xyz, min_supercel)
+    return file12, str(rez[0]), str((rez[1], rez[2])),plot
+
+def compute_supercell_b():
+    pass
+
+def compute_supercell(A_cell, B_cell,A_structure,B_structure ):
+
+    min_supercel = PipelineLatMatch(A_cell, B_cell, Aatoms3D=structure_ato_list(A_structure),
+                                    Batoms3D=structure_ato_list(B_structure), dim=(10, 10), optimize_angle=True,
+                                    optimize_strain=True)
+
+    new_structure = min_supercel.get_new_structure()
+    super_xyz = structure_ato_list(new_structure)
+    return super_xyz,    min_supercel
+
+
+
+
+def  plot_supercel(super_xyz, min_supercel):
+    fig = plt.figure()
+    new_structure=min_supercel.get_new_structure()
+    super_a = [super_xyz[i] for i in range(len(new_structure["host_guest"])) if
+               new_structure["host_guest"][i] == "host"]
+    super_b = [super_xyz[i] for i in range(len(new_structure["host_guest"])) if
+               new_structure["host_guest"][i] == "guest"]
+
+    atoms = atoms_to_greed(super_a, lat_v=min_supercel.sc_vec3, dim=(10, 10, 0))
+    plot_atom_list(atoms, marker=".")
+    atoms = atoms_to_greed(super_b, lat_v=min_supercel.sc_vec3, dim=(10, 10, 0))
+    plot_atom_list(atoms, marker="*")
+
+    x = [0.0, min_supercel.sc_vec3[0][0], min_supercel.sc_vec3[0][0] + min_supercel.sc_vec3[0][1],
+         min_supercel.sc_vec3[0][1], 0.0]
+    y = [0.0, min_supercel.sc_vec3[1][0], min_supercel.sc_vec3[1][0] + min_supercel.sc_vec3[1][1],
+         min_supercel.sc_vec3[1][1], 0.0]
+    plt.gca().add_patch(patches.Polygon(xy=list(zip(x, y)), fill=True, alpha=0.4, color="green"))
+    plt.ylim(-15, 15)
+    plt.xlim(-15, 15)
+    return fig
+
+
+
+# Utility tools for working with files
+def file_json(file_path):
+    file = file_path.split("/")[-1]
+    ext = file.split(".")[-1]
+    if ext == "json":
+        return True
+    else:
+        return False
+
+
+def get_file_name(file_path):
+    file = file_path.split("/")[-1]
+    file_name = file.split(".")[-2]
+    return file_name
+
+
+def process_file(fileobj, path_to_move):
+    file_path = path_to_move + os.path.basename(fileobj.name)
+    shutil.copyfile(fileobj.name, file_path)
+    return file_path
+
+
+def extract_from_xyz(file):
+
+    structure={'cell':[], 'atoms':[],
+               'positions':[],
+               "pbc":[ True,  True, False] }
+
+    with open(file, 'r') as xyz_file:
+        lines = xyz_file.readlines()[4:]  # Skipping the first two line
+
+    with open(file, 'r') as xyz_file:
+        dict_string = xyz_file.readlines()[:1][0]
+        print(dict_string)
+
+
+    lattice = ast.literal_eval(dict_string)['lattice_vectors']
+
+
+    structure["cell"]=np.array([[lattice[0][0], lattice[0][1], 0],
+                                [lattice[1][0], lattice[1][1], 0],
+                                [0,0,1]])
+
+
+    atom_xyz=np.array([line.split()[1:4] for line in lines], dtype=float)
+
+    atomic_symbols = []
+    for line in lines:
+        atomic_symbols.append(line.split()[0])
+    structure['atoms']=[get_atomic_number(element_symbol) for element_symbol  in atomic_symbols]
+
+    structure['positions']=atom_xyz
+
+
+
+    return structure
+
+
+def extract_from_bespoke(file):
+    read_element = DBInstance().from_json_file(file)
+    structure = read_element.structure
+    structure["cell"]=np.array(structure["cell"])
+    return structure