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jonathanjdenneyjonathanjdenney
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reimplemented fstar diagram
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‎pymatgen/analysis/fstar/fstar.py‎

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"""
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This module implements an f* coordinate and diagram generator.
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For information about f* diagrams, see the following publications:
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Yin, L. et al. Extending the limits of powder diffraction analysis: diffraction parameter space, occupancy defects, and
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atomic form factors. Rev. Sci. Instrum. 89, 093002 (2018). 10.1063/1.5044555
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Yin, L. et al.Thermodynamics of Antisite Defects in Layered NMC Cathodes: Systematic Insights from High-Precision Powder
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Diffraction Analyses Chem. Mater 2020 32 (3), 1002-1010. 10.1021/acs.chemmater.9b03646
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"""
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import os
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import numpy as np
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import pandas as pd
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from pymatgen.symmetry.analyzer import SpacegroupAnalyzer
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import plotly.express as px
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# Load in the form factors
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with open(os.path.join(os.path.dirname(__file__),
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"xray_factors_2.csv")) as f:
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X_RAY_SCATTER_DF = pd.read_csv(f)
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# from https://it.iucr.org/Cb/ch6o1v0001/ table 6.1.1.4
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with open(os.path.join(os.path.dirname(__file__),
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"neutron_factors.csv")) as f:
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NEUTRON_SCATTER_DF = pd.read_csv(f)
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# from http://www.ccp14.ac.uk/ccp/web-mirrors/neutrons/n-scatter/n-lengths/LIST~1.HTM
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class FStarDiagram:
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"""
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Take a list of structure objects and/or cifs and use them to generate an f* phase diagram.
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"""
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def __init__(self, structures, scattering_type='X-ray_simple', custom_scatter=None):
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"""
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Initialize the f* diagram generator with the list of structures and scattering type.
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Args:
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structures(list): List of structure objects to use in the diagram. These must be symmetrized structure
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objects.
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scattering_type(str): Type of scattering to use in the f* calculation. Defaults to 'X-ray_simple'
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which uses the atomic number as the scattering factor. 'X-ray' and 'Neutron' are built in scattering
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types which use X-ray and neutron scattering factors, respectively. 'Custom' allows the user to
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supplement their own calculation with any set of scattering factors.
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custom_scatter(function): when using custom scattering set this equal to a global varialble that is equal
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to the custom scattering function.
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"""
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self._structures = [SpacegroupAnalyzer(structure).get_symmetrized_structure() for structure in
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structures]
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self._scatter = scattering_type
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self._custscat = custom_scatter
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self._equiv_inds = [struct.equivalent_indices for struct in self._structures]
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self.site_labels = self.get_site_labels()
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self.coords = self.get_fstar_coords()
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self.plot = px.scatter_ternary(data_frame=self.coords, a=self.site_labels[0], b=self.site_labels[1],
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c=self.site_labels[2])
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print("The labels for this structure's unique sites are")
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print(self.site_labels)
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def edit_fstar_diagram(self, combine_list=False, plot_list=False, **kwargs):
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"""
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Edit the plot of the f* diagram using plotly express.
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Args:
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combine_list(list): This is a list of lists which indicates what unique sites need to be combined to make
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the plot ternary.
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plot_list(list): This is a list that indicates what unique sites or combined sites to plot and what order to
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plot them in.
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kwargs: use this to add any other arguments from scatter_ternary .
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"""
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if combine_list:
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for combo in combine_list:
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self.coords[str(combo)] = sum([self.coords[site] for site in combo])
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if str(combo) not in self.site_labels:
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self.site_labels.append(str(combo))
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if plot_list:
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self.plot = px.scatter_ternary(data_frame=self.coords, a=plot_list[0], b=plot_list[1], c=plot_list[2],
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**kwargs)
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else:
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self.plot = px.scatter_ternary(data_frame=self.coords, a=self.site_labels[0], b=self.site_labels[1],
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c=self.site_labels[2], **kwargs)
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def get_site_labels(self):
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"""
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Generates unique site labels based on composition, order, and symetry equivalence in the structure object.
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Ex:
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Structure Summary
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Lattice
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abc : 2.851 2.851 14.275
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angles : 90.0 90.0 119.99999999999999
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volume : 100.48498759501827
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A : 2.851 0.0 1.745734012184552e-16
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B : -1.4254999999999998 2.4690384261894347 1.745734012184552e-16
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C : 0.0 0.0 14.275
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PeriodicSite: Li:0.990, Ni:0.010 (0.0000, 0.0000, 0.0000) [0.0000, 0.0000, 0.0000]
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PeriodicSite: Li:0.990, Ni:0.010 (1.4255, 0.8230, 4.7583) [0.6667, 0.3333, 0.3333]
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PeriodicSite: Li:0.990, Ni:0.010 (-0.0000, 1.6460, 9.5167) [0.3333, 0.6667, 0.6667]
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PeriodicSite: Li:0.010, Mn:0.333, Co:0.333, Ni:0.323 (0.0000, 0.0000, 7.1375) [0.0000, 0.0000, 0.5000]
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PeriodicSite: Li:0.010, Mn:0.333, Co:0.333, Ni:0.323 (1.4255, 0.8230, 11.8958) [0.6667, 0.3333, 0.8333]
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PeriodicSite: Li:0.010, Mn:0.333, Co:0.333, Ni:0.323 (-0.0000, 1.6460, 2.3792) [0.3333, 0.6667, 0.1667]
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PeriodicSite: O (0.0000, 0.0000, 3.5688) [0.0000, 0.0000, 0.2500]
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PeriodicSite: O (0.0000, 0.0000, 10.7063) [0.0000, 0.0000, 0.7500]
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PeriodicSite: O (1.4255, 0.8230, 8.3270) [0.6667, 0.3333, 0.5833]
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PeriodicSite: O (1.4255, 0.8230, 1.1895) [0.6667, 0.3333, 0.0833]
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PeriodicSite: O (-0.0000, 1.6460, 13.0855) [0.3333, 0.6667, 0.9167]
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PeriodicSite: O (-0.0000, 1.6460, 5.9480) [0.3333, 0.6667, 0.4167]
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results in
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labels - ['[0. 0. 0.]Li', '[0. 0. 0.5]Co', '[0. 0. 0.25]O']
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'[0. 0. 0.]Li' - PeriodicSite: Li:0.990, Ni:0.010 (0.0000, 0.0000, 0.0000) [0.0000, 0.0000, 0.0000]
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'[0. 0. 0.5]Co' - PeriodicSite: Li:0.010, Mn:0.333, Co:0.333, Ni:0.323
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(0.0000, 0.0000, 7.1375) [0.0000, 0.0000, 0.5000]
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'[0. 0. 0.25]O' - PeriodicSite: O (0.0000, 0.0000, 3.5688) [0.0000, 0.0000, 0.2500]
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"""
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site_labels_fin = []
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for ind1, struct in enumerate(self._equiv_inds):
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site_labels = []
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for ind2, site in enumerate(struct):
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label = str(self._structures[ind1][site[0]].frac_coords) + \
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[str(sp) for sp, occ in self._structures[ind1][site[0]].species.items()][0]
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if label not in site_labels:
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site_labels.append(label)
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if len(site_labels) > len(site_labels_fin):
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site_labels_fin = site_labels
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return site_labels_fin
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def get_fstar_coords(self):
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"""
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Calculate the f* coordinates for the list of structures.
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"""
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fstar_df_full = pd.DataFrame(columns=self.site_labels)
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for ind1, struct in enumerate(self._equiv_inds):
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fstar_df = pd.DataFrame(columns=self.site_labels, data=[[0.0 for i in self.site_labels]])
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for ind2, site in enumerate(struct):
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occ_f_list = []
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mult = len(site)
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site_frac_coord = str(self._structures[ind1][site[0]].frac_coords)
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column = [label for label in self.site_labels if site_frac_coord in label]
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elements_and_occupancies = self._structures[ind1][site[0]].species.items()
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for sp, occ in elements_and_occupancies:
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if self._scatter == 'X-ray_simple':
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f_occ = sp.Z * occ
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if self._scatter == 'X-ray':
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for i, n in enumerate(X_RAY_SCATTER_DF['atom'].values):
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if hasattr(sp, "element"):
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if n == str(sp.element):
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f_occ = round(
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sum([X_RAY_SCATTER_DF.loc[i]['a1'], X_RAY_SCATTER_DF.loc[i]['a2'],
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X_RAY_SCATTER_DF.loc[i]['a3'],
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X_RAY_SCATTER_DF.loc[i]['a4'], X_RAY_SCATTER_DF.loc[i]['c']]), 0) * occ
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break
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else:
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continue
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else:
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if n == str(sp):
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f_occ = round(
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sum([X_RAY_SCATTER_DF.loc[i]['a1'], X_RAY_SCATTER_DF.loc[i]['a2'],
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X_RAY_SCATTER_DF.loc[i]['a3'],
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X_RAY_SCATTER_DF.loc[i]['a4'], X_RAY_SCATTER_DF.loc[i]['c']]), 0) * occ
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break
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else:
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continue
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if self._scatter == 'Neutron':
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for i, n in enumerate(NEUTRON_SCATTER_DF['Isotope'].values):
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if hasattr(sp, "element"):
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if n == str(sp.element):
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f_occ = float(NEUTRON_SCATTER_DF.loc[i]['Coh b']) * occ
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break
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else:
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continue
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else:
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if n == str(sp):
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f_occ = float(NEUTRON_SCATTER_DF.loc[i]['Coh b']) * occ
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break
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else:
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continue
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if self._scatter == 'Custom':
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if hasattr(sp, "element"):
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f_occ = self._custscat(str(sp.element), occ, ind1, ind2)
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else:
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f_occ = self._custscat(str(sp), occ, ind1, ind2)
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occ_f_list.append(f_occ)
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fstar = np.absolute(mult * sum(occ_f_list))
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fstar_df.loc[0][column[0]] = round(float(fstar), 4)
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tot = sum(sum(list(fstar_df.values)))
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fstar_df = pd.DataFrame(columns=self.site_labels, data=[fs / tot for fs in list(fstar_df.values)])
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fstar_df_full = pd.concat([fstar_df_full, fstar_df], ignore_index=True)
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return fstar_df_full

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