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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 | |
| from ase.io import read | |
| from CifFile import ReadCif | |
| import matplotlib.pyplot as plt | |
| import matplotlib.patches as patches | |
| import os | |
| import shutil | |
| import numpy as np | |
| import periodictable | |
| import ast | |
| def create_directory(directory_path): | |
| if not os.path.exists(directory_path): | |
| os.makedirs(directory_path) | |
| print(f"Directory '{directory_path}' created successfully.") | |
| else: | |
| print(f"Directory '{directory_path}' already exists.") | |
| 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 = "DB/LatMatcher" | |
| create_directory("DB") | |
| create_directory("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+"/") | |
| file_source_a="."+file1.split(".")[-1] | |
| file_source_b = "."+file2.split(".")[-1] | |
| print("fa, fb:",file_source_a, file_source_b) | |
| 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 = f"{len(super_xyz)}\n" | |
| xyz_content +="Lattice=\"{}\"".format(np.array2string(min_supercel.get_new_structure()['lattice_vectors'], | |
| separator=', ', | |
| max_line_width=np.inf).replace("\n"," ").replace("[","").replace("]","").replace(",",""))+" pbc=\"T T F\""+"\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() | |
| atoms = atoms_to_greed(super_xyz, 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(-10, 20) | |
| # 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] } | |
| atoms = read(file) | |
| lattice_vectors = atoms.cell | |
| atom_symbols = atoms.get_chemical_symbols() | |
| positions = atoms.get_positions() | |
| structure["cell"] = np.array([[lattice_vectors[0][0], lattice_vectors[0][1], 0], | |
| [lattice_vectors[1][0], lattice_vectors[1][1], 0], | |
| [0,0,1]]) | |
| structure['atoms'] = [get_atomic_number(element_symbol) for element_symbol in atom_symbols] | |
| structure['positions'] = positions | |
| print(structure) | |
| 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 |