.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "examples\06-PyPoscar\plot_finding_defects_pyposcar.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code. .. rst-class:: sphx-glr-example-title .. _sphx_glr_examples_06-PyPoscar_plot_finding_defects_pyposcar.py: .. _ref_example_finding_defect: Finding defects in a POSCAR file ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ In this example, we'll demonstrate how to automatically find defects in a POSCAR file Let's get started! .. GENERATED FROM PYTHON SOURCE LINES 11-22 .. code-block:: Python import os from itertools import product import pyprocar.pyposcar as p import numpy as np import pyvista as pv from pyprocar.utils import ROOT data_dir=os.path.join(ROOT,'data','examples','PyPoscar','03-defects') # You do not need this. This is to ensure an image is rendered off screen when generating exmaple gallery. pv.OFF_SCREEN = True .. GENERATED FROM PYTHON SOURCE LINES 23-25 Utility function for creating GIF visualizations ++++++++++++++++++++++++++++++++++++++++++++++++ .. GENERATED FROM PYTHON SOURCE LINES 25-38 .. code-block:: Python def create_gif(atoms, labels, unit_cell, save_file): plotter = pv.Plotter() title = save_file.split(os.sep)[-1].split('.')[0] plotter.add_title(title) plotter.add_mesh(unit_cell.delaunay_3d().extract_feature_edges(), color='black', line_width=5, render_lines_as_tubes=True) plotter.add_point_labels(points=atoms.points, labels=labels, show_points=False, always_visible=True) plotter.add_mesh(atoms, scalars='atoms', point_size=30, render_points_as_spheres=True, show_scalar_bar=False) path = plotter.generate_orbital_path(n_points=36) plotter.open_gif(os.path.join(data_dir, save_file)) plotter.orbit_on_path(path, write_frames=True, viewup=[0, 0, 1], step=0.05) plotter.close() .. GENERATED FROM PYTHON SOURCE LINES 39-41 Finding defects ++++++++++++++++++++++++++++++++++++ .. GENERATED FROM PYTHON SOURCE LINES 41-83 .. code-block:: Python print('Loading an AGNR with a defect in it') a = p.poscar.Poscar(os.path.join(data_dir,"POSCAR-AGNR-defect.vasp"), verbose=False) a.parse() defects = p.defects.FindDefect(a) print('The defects are:') print(defects.all_defects) print('\n\nThe warning above indicates that there are two different types of defects') print('saving a file with the defects, defects.vasp') defects.write_defects(filename=os.path.join(data_dir,'defects.vasp')) print('Inspection of the file defects.vasp shows that the first type of defects are subtitutionals (0D), and the second are the AGRN edges (1D)') tmp_a = p.Poscar(os.path.join(data_dir, "POSCAR-AGNR-defect.vasp")) tmp_a.parse() # Convert positions to Cartesian coordinates for visualization atoms_before = pv.PolyData(np.dot(tmp_a.dpos, tmp_a.lat)) atoms_before['atoms'] = tmp_a.elm labels_before = [elm for elm, point in zip(tmp_a.elm, tmp_a.dpos)] # Define the unit cell using lattice vectors unit_cell_comb = list(product([0, 1], repeat=3)) unit_cell = np.array([comb[0]*tmp_a.lat[0] + comb[1]*tmp_a.lat[1] + comb[2]*tmp_a.lat[2] for comb in unit_cell_comb]) unit_cell_before = pv.PolyData(unit_cell) tmp_a = p.Poscar(os.path.join(data_dir, "defects.vasp")) tmp_a.parse() # Convert positions to Cartesian coordinates for visualization atoms_after = pv.PolyData(np.dot(tmp_a.dpos, tmp_a.lat)) atoms_after['atoms'] = tmp_a.elm labels_after = [elm for elm, point in zip(tmp_a.elm, tmp_a.dpos)] # Define the unit cell using lattice vectors unit_cell_comb = list(product([0, 1], repeat=3)) unit_cell = np.array([comb[0]*tmp_a.lat[0] + comb[1]*tmp_a.lat[1] + comb[2]*tmp_a.lat[2] for comb in unit_cell_comb]) unit_cell_after = pv.PolyData(unit_cell) create_gif(atoms=atoms_before, labels=labels_before, unit_cell=unit_cell_before, save_file='atoms_before_defect_finding.gif') create_gif(atoms=atoms_after, labels=labels_after, unit_cell=unit_cell_after, save_file='atoms_after_defect_finding.gif') .. rst-class:: sphx-glr-horizontal * .. image-sg:: /examples/06-PyPoscar/images/sphx_glr_plot_finding_defects_pyposcar_001.gif :alt: plot finding defects pyposcar :srcset: /examples/06-PyPoscar/images/sphx_glr_plot_finding_defects_pyposcar_001.gif :class: sphx-glr-multi-img * .. image-sg:: /examples/06-PyPoscar/images/sphx_glr_plot_finding_defects_pyposcar_002.gif :alt: plot finding defects pyposcar :srcset: /examples/06-PyPoscar/images/sphx_glr_plot_finding_defects_pyposcar_002.gif :class: sphx-glr-multi-img .. rst-class:: sphx-glr-script-out .. code-block:: none Loading an AGNR with a defect in it WARNING: in FindDefect.find_forgein_atoms() more than two sets of atoms were found. Cluster delimited by `minima`= [12 29] , `maxima=` [ 7 15 42] Only elements with less than 12 atoms are regarded as defects WARNING: in FindDefect.nearest_neighbors_environment() more than two sets of atoms were found. Cluster delimited by `minima`= [15 30] , `maxima=` [10 19 40] Only elements with environments less abundant than 15 are regarded as defects The defects are: [1, 2, 16, 17, 19, 20, 22, 25, 26, 27, 32, 33, 35, 36, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 62, 63, 64, 65] The warning above indicates that there are two different types of defects saving a file with the defects, defects.vasp Inspection of the file defects.vasp shows that the first type of defects are subtitutionals (0D), and the second are the AGRN edges (1D) .. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 9.326 seconds) .. _sphx_glr_download_examples_06-PyPoscar_plot_finding_defects_pyposcar.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_finding_defects_pyposcar.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_finding_defects_pyposcar.py ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_