From 89a9da1e7a9b6524ada2d26146317e6ddc69b2b3 Mon Sep 17 00:00:00 2001 From: Shyue Ping Ong Date: Mon, 24 Jun 2024 11:37:59 -0700 Subject: [PATCH] Update docs. --- docs/_modules/index.html | 17 +- .../analysis/diffusion/aimd/clustering.html | 85 ++-- .../analysis/diffusion/aimd/pathway.html | 130 +++--- .../pymatgen/analysis/diffusion/aimd/rdf.html | 142 +++---- .../diffusion/aimd/tests/test_clustering.html | 42 +- .../diffusion/aimd/tests/test_pathway.html | 67 +-- .../diffusion/aimd/tests/test_rdf.html | 35 +- .../diffusion/aimd/tests/test_van_hove.html | 104 +++-- .../analysis/diffusion/aimd/van_hove.html | 198 ++++----- .../pymatgen/analysis/diffusion/analyzer.html | 353 ++++++++-------- .../diffusion/neb/full_path_mapper.html | 397 +++++++++--------- .../pymatgen/analysis/diffusion/neb/io.html | 56 ++- .../analysis/diffusion/neb/pathfinder.html | 384 +++++++++-------- .../diffusion/neb/periodic_dijkstra.html | 69 +-- .../neb/tests/test_full_path_mapper.html | 160 +++++-- 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Navigation

  • modules |
    • -
  • pymatgen-diffusion 2023.8.15 documentation »
    • +
  • pymatgen-diffusion 2024.6.10 documentation »
  • Overview: module code
    • @@ -68,7 +68,6 @@

    All modules for which code is available

  • pymatgen.analysis.diffusion.utils.parse_entries
  • pymatgen.analysis.diffusion.utils.supercells
  • pymatgen.analysis.diffusion.utils.tests.test_edge_data_from_sc
    • -
  • pymatgen.analysis.diffusion.utils.tests.test_maggma
  • pymatgen.analysis.diffusion.utils.tests.test_parse_entries
    • @@ -82,7 +81,7 @@

    All modules for which code is available

  • Documentation overview
    • - + diff --git a/docs/_modules/pymatgen/analysis/diffusion/aimd/clustering.html b/docs/_modules/pymatgen/analysis/diffusion/aimd/clustering.html index a402652..123f2b2 100644 --- a/docs/_modules/pymatgen/analysis/diffusion/aimd/clustering.html +++ b/docs/_modules/pymatgen/analysis/diffusion/aimd/clustering.html @@ -1,15 +1,15 @@ - + - pymatgen.analysis.diffusion.aimd.clustering — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.aimd.clustering — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -34,7 +34,7 @@

    Navigation

  • modules |
    • -
  • pymatgen-diffusion 2023.8.15 documentation »
    • +
  • pymatgen-diffusion 2024.6.10 documentation »
  • Module code »
  • pymatgen.analysis.diffusion.aimd.clustering
    • @@ -46,14 +46,12 @@

    Navigation

    Source code for pymatgen.analysis.diffusion.aimd.clustering

    -# Copyright (c) Materials Virtual Lab.
-# Distributed under the terms of the BSD License.
-
-"""
+"""
 This module implements clustering algorithms to determine centroids, with
 adaption for periodic boundary conditions. This can be used, for example, to
 determine likely atomic positions from MD trajectories.
 """
+
 from __future__ import annotations
 
 import random
@@ -71,10 +69,10 @@ 
    Source code for pymatgen.analysis.diffusion.aimd.clustering
    __date__ = "3/18/15"
 
 
-
    [docs]class Kmeans:
-    """
-    Simple kmeans clustering.
-    """
+
    
+[docs]
+class Kmeans:
+    """Simple kmeans clustering."""
 
     def __init__(self, max_iterations: int = 1000):
         """
@@ -83,7 +81,9 @@ 
    Source code for pymatgen.analysis.diffusion.aimd.clustering
            """
         self.max_iterations = max_iterations
 
-
    [docs]    def cluster(self, points, k, initial_centroids=None):
+
    
+[docs]
+    def cluster(self, points, k, initial_centroids=None):
         """
         Args:
             points (ndarray): Data points as a mxn ndarray, where m is the
@@ -122,7 +122,10 @@ 
    Source code for pymatgen.analysis.diffusion.aimd.clustering
    # We can get the labels too by calling getLabels(dataSet, centroids)
         return centroids, labels, ss
    
 
-
    [docs]    @staticmethod
+
+
    
+[docs]
+    @staticmethod
     def get_labels(points, centroids):
         """
         For each element in the dataset, chose the closest centroid.
@@ -136,7 +139,10 @@ 
    Source code for pymatgen.analysis.diffusion.aimd.clustering
    min_dists = np.min(dists, axis=1)
         return np.where(dists == min_dists[:, None])[1], np.sum(min_dists**2)
    
 
-
    [docs]    @staticmethod
+
+
    
+[docs]
+    @staticmethod
     def get_centroids(points, labels, k, centroids):
         """
         Each centroid is the geometric mean of the points that
@@ -159,7 +165,10 @@ 
    Source code for pymatgen.analysis.diffusion.aimd.clustering
    centroids.append(get_random_centroid(points))
         return np.array(centroids)
    
 
-
    [docs]    def should_stop(self, old_centroids, centroids, iterations):
+
+
    
+[docs]
+    def should_stop(self, old_centroids, centroids, iterations):
         """
         Check for stopping conditions.
 
@@ -173,10 +182,14 @@ 
    Source code for pymatgen.analysis.diffusion.aimd.clustering
    return True
         if old_centroids is None:
             return False
-        return np.allclose(old_centroids, centroids)
    
+        return np.allclose(old_centroids, centroids)
    
+
    
 
 
-
    [docs]class KmeansPBC(Kmeans):
+
+
    
+[docs]
+class KmeansPBC(Kmeans):
     """
     A version of KMeans that work with PBC. Distance metrics have to change,
     as well as new centroid determination. The points supplied should be
@@ -192,7 +205,9 @@ 
    Source code for pymatgen.analysis.diffusion.aimd.clustering
    self.lattice = lattice
         self.max_iterations = max_iterations
 
-
    [docs]    def get_labels(self, points, centroids):
+
    
+[docs]
+    def get_labels(self, points, centroids):
         """
         For each element in the dataset, chose the closest centroid.
         Make that centroid the element's label.
@@ -205,7 +220,10 @@ 
    Source code for pymatgen.analysis.diffusion.aimd.clustering
    min_dists = np.min(dists, axis=1)
         return np.where(dists == min_dists[:, None])[1], np.sum(min_dists**2)
    
 
-
    [docs]    def get_centroids(self, points, labels, k, centroids):
+
+
    
+[docs]
+    def get_centroids(self, points, labels, k, centroids):
         """
         Each centroid is the geometric mean of the points that
         have that centroid's label. Important: If a centroid is empty (no
@@ -237,7 +255,10 @@ 
    Source code for pymatgen.analysis.diffusion.aimd.clustering
    new_centroids.append(c)
         return np.array(new_centroids)
    
 
-
    [docs]    def should_stop(self, old_centroids, centroids, iterations):
+
+
    
+[docs]
+    def should_stop(self, old_centroids, centroids, iterations):
         """
         Check for stopping conditions.
 
@@ -254,10 +275,14 @@ 
    Source code for pymatgen.analysis.diffusion.aimd.clustering
    return all(
             np.allclose(pbc_diff(c1, c2), [0, 0, 0])
             for c1, c2 in zip(old_centroids, centroids)
-        )
    
+        )
    
+
    
 
 
-
    [docs]def get_random_centroid(points):
+
+
    
+[docs]
+def get_random_centroid(points):
     """
     Generate a random centroid based on points.
 
@@ -270,7 +295,10 @@ 
    Source code for pymatgen.analysis.diffusion.aimd.clustering
    return np.array([random.uniform(mind[i], maxd[i]) for i in range(n)])
    
 
 
-
    [docs]def get_random_centroids(points, k):
+
+
    
+[docs]
+def get_random_centroids(points, k):
     """
     Generate k random centroids based on points.
 
@@ -282,6 +310,7 @@ 
    Source code for pymatgen.analysis.diffusion.aimd.clustering
    for _i in range(k):
         centroids.append(get_random_centroid(points))
     return np.array(centroids)
    
+
    @@ -296,7 +325,7 @@

    Source code for pymatgen.analysis.diffusion.aimd.clustering

    +
    diff --git a/docs/_modules/pymatgen/analysis/diffusion/aimd/pathway.html b/docs/_modules/pymatgen/analysis/diffusion/aimd/pathway.html index 1f98fbb..54d2535 100644 --- a/docs/_modules/pymatgen/analysis/diffusion/aimd/pathway.html +++ b/docs/_modules/pymatgen/analysis/diffusion/aimd/pathway.html @@ -1,15 +1,15 @@ - + - pymatgen.analysis.diffusion.aimd.pathway — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.aimd.pathway — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -34,7 +34,7 @@

    Navigation

  • modules |
    • -
  • pymatgen-diffusion 2023.8.15 documentation »
    • +
  • pymatgen-diffusion 2024.6.10 documentation »
  • Module code »
  • pymatgen.analysis.diffusion.aimd.pathway
    • @@ -46,12 +46,8 @@

    Navigation

    Source code for pymatgen.analysis.diffusion.aimd.pathway

    -# Copyright (c) Materials Virtual Lab.
-# Distributed under the terms of the BSD License.
+"""Algorithms for diffusion pathway analysis."""
 
-"""
- Algorithms for diffusion pathway analysis
-"""
 from __future__ import annotations
 
 import itertools
@@ -62,8 +58,12 @@ 
    Source code for pymatgen.analysis.diffusion.aimd.pathway
    from scipy.spatial.distance import squareform
 
 
-
    [docs]class ProbabilityDensityAnalysis:
+
    
+[docs]
+class ProbabilityDensityAnalysis:
     r"""
+    Probability density analysis class.
+
     Compute the time-averaged probability density distribution of selected
     species on a "uniform" (in terms of fractional coordinates) 3-D grid.
     Note that \int_{\Omega}d^3rP(r) = 1
@@ -78,6 +78,7 @@ 
    Source code for pymatgen.analysis.diffusion.aimd.pathway
    def __init__(self, structure, trajectories, interval=0.5, species=("Li", "Na")):
         """
         Initialization.
+
         Args:
             structure (Structure): crystal structure
             trajectories (numpy array): ionic trajectories of the structure
@@ -88,7 +89,6 @@ 
    Source code for pymatgen.analysis.diffusion.aimd.pathway
                    (in Angstrom)
             species(list of str): list of species that are of interest
         """
-
         # initial settings
         trajectories = np.array(trajectories)
 
@@ -97,9 +97,7 @@ 
    Source code for pymatgen.analysis.diffusion.aimd.pathway
    assert np.all(trajectories >= 0)
         assert np.all(trajectories <= 1)
 
-        indices = [
-            j for j, site in enumerate(structure) if site.specie.symbol in species
-        ]
+        indices = [j for j, site in enumerate(structure) if site.specie.symbol in species]
         lattice = structure.lattice
         frac_interval = [interval / length for length in lattice.abc]
         nsteps = len(trajectories)
@@ -133,35 +131,20 @@ 
    Source code for pymatgen.analysis.diffusion.aimd.pathway
    for i in range(3):
                     next_i[i] = corner_i[i] + 1 if corner_i[i] < lens[i] - 1 else 0
 
-                agrid = (
-                    np.array([corner_i[0], next_i[0]])[:, None]
-                    * np.array([1, 0, 0])[None, :]
-                )
-                bgrid = (
-                    np.array([corner_i[1], next_i[1]])[:, None]
-                    * np.array([0, 1, 0])[None, :]
-                )
-                cgrid = (
-                    np.array([corner_i[2], next_i[2]])[:, None]
-                    * np.array([0, 0, 1])[None, :]
-                )
+                agrid = np.array([corner_i[0], next_i[0]])[:, None] * np.array([1, 0, 0])[None, :]
+                bgrid = np.array([corner_i[1], next_i[1]])[:, None] * np.array([0, 1, 0])[None, :]
+                cgrid = np.array([corner_i[2], next_i[2]])[:, None] * np.array([0, 0, 1])[None, :]
 
-                grid_indices = (
-                    agrid[:, None, None] + bgrid[None, :, None] + cgrid[None, None, :]
-                )
+                grid_indices = agrid[:, None, None] + bgrid[None, :, None] + cgrid[None, None, :]
                 grid_indices = grid_indices.reshape(8, 3)
 
                 mini_grid = [grid[indx[0], indx[1], indx[2]] for indx in grid_indices]
                 dist_matrix = lattice.get_all_distances(mini_grid, fcoord)
-                indx = np.where(dist_matrix == np.min(dist_matrix, axis=0)[None, :])[0][
-                    0
-                ]
+                indx = np.where(dist_matrix == np.min(dist_matrix, axis=0)[None, :])[0][0]
 
                 # 3-index label mapping to single index
                 min_indx = (
-                    grid_indices[indx][0] * len(rb) * len(rc)
-                    + grid_indices[indx][1] * len(rc)
-                    + grid_indices[indx][2]
+                    grid_indices[indx][0] * len(rb) * len(rc) + grid_indices[indx][1] * len(rc) + grid_indices[indx][2]
                 )
 
                 # make sure the index does not go out of bound.
@@ -182,10 +165,10 @@ 
    Source code for pymatgen.analysis.diffusion.aimd.pathway
    self.species = species
         self.stable_sites = None
 
-
    [docs]    @classmethod
-    def from_diffusion_analyzer(
-        cls, diffusion_analyzer, interval=0.5, species=("Li", "Na")
-    ):
+
    
+[docs]
+    @classmethod
+    def from_diffusion_analyzer(cls, diffusion_analyzer, interval=0.5, species=("Li", "Na")):
         """
         Create a ProbabilityDensityAnalysis from a diffusion_analyzer object.
 
@@ -204,11 +187,12 @@ 
    Source code for pymatgen.analysis.diffusion.aimd.pathway
    trajectories = np.array(trajectories)
 
-        return ProbabilityDensityAnalysis(
-            structure, trajectories, interval=interval, species=species
-        )
    
+        return ProbabilityDensityAnalysis(structure, trajectories, interval=interval, species=species)
    
+
 
-
    [docs]    def generate_stable_sites(self, p_ratio=0.25, d_cutoff=1.0):
+
    
+[docs]
+    def generate_stable_sites(self, p_ratio=0.25, d_cutoff=1.0):
         """
         Obtain a set of low-energy sites from probability density function with
         given probability threshold 'p_ratio'. The set of grid points with
@@ -227,7 +211,6 @@ 
    Source code for pymatgen.analysis.diffusion.aimd.pathway
                The set of stable sites is stored in the `stable_sites` attribute
             as a Nx3 numpy array.
         """
-
         # Set of grid points with high probability density.
         grid_fcoords = []
         indices = np.where(self.Pr > self.Pr.max() * p_ratio)
@@ -279,24 +262,28 @@ 
    Source code for pymatgen.analysis.diffusion.aimd.pathway
    self.stable_sites = np.array(stable_sites)
    
 
-
    [docs]    def get_full_structure(self):
+
+
    
+[docs]
+    def get_full_structure(self):
         """
         Generate the structure with the low-energy sites included. In the end, a
         pymatgen Structure object will be returned.
         """
-
         full_structure = self.structure.copy()
         for fcoord in self.stable_sites:
             full_structure.append("X", fcoord)
 
         return full_structure
    
 
-
    [docs]    def to_chgcar(self, filename="CHGCAR.vasp"):
+
+
    
+[docs]
+    def to_chgcar(self, filename="CHGCAR.vasp"):
         """
         Save the probability density distribution in the format of CHGCAR,
         which can be visualized by VESTA.
         """
-
         count = 1
         VolinAu = self.structure.lattice.volume / 0.5291772083**3
         syms = [site.specie.symbol for site in self.structure]
@@ -333,10 +320,14 @@ 
    Source code for pymatgen.analysis.diffusion.aimd.pathway
    f.write("\n")
                         count += 1
 
-        f.close()
    
+        f.close()
    
+
    
+
 
 
-
    [docs]class SiteOccupancyAnalyzer:
+
    
+[docs]
+class SiteOccupancyAnalyzer:
     """
     A class that analyzes the site occupancy of given species using MD trajectories.
     The occupancy of a site is determined based on the shortest distance scheme.
@@ -367,20 +358,15 @@ 
    Source code for pymatgen.analysis.diffusion.aimd.pathway
                    simulation. Note that the coordinates are fractional.
             species(list of str): list of species that are of interest.
         """
-
         lattice = structure.lattice
         coords_ref = np.array(coords_ref)
         trajectories = np.array(trajectories)
         count = Counter()
 
-        indices = [
-            i for i, site in enumerate(structure) if site.specie.symbol in species
-        ]
+        indices = [i for i, site in enumerate(structure) if site.specie.symbol in species]
 
         for it in range(len(trajectories)):
-            dist_matrix = lattice.get_all_distances(
-                coords_ref, trajectories[it, indices, :]
-            )
+            dist_matrix = lattice.get_all_distances(coords_ref, trajectories[it, indices, :])
             labels = np.where(dist_matrix == np.min(dist_matrix, axis=0)[None, :])[0]
             count.update(labels)
 
@@ -397,16 +383,17 @@ 
    Source code for pymatgen.analysis.diffusion.aimd.pathway
    self.nsteps = len(trajectories)
         self.site_occ = site_occ
 
-
    [docs]    def get_average_site_occupancy(self, indices):
-        """
-        Get the average site occupancy over a subset of reference sites.
-        """
+
    
+[docs]
+    def get_average_site_occupancy(self, indices):
+        """Get the average site occupancy over a subset of reference sites."""
         return np.sum(self.site_occ[indices]) / len(indices)
    
 
-
    [docs]    @classmethod
-    def from_diffusion_analyzer(
-        cls, coords_ref, diffusion_analyzer, species=("Li", "Na")
-    ):
+
+
    
+[docs]
+    @classmethod
+    def from_diffusion_analyzer(cls, coords_ref, diffusion_analyzer, species=("Li", "Na")):
         """
         Create a SiteOccupancyAnalyzer object using a diffusion_analyzer object.
 
@@ -417,7 +404,6 @@ 
    Source code for pymatgen.analysis.diffusion.aimd.pathway
                    pymatgen.analysis.diffusion_analyzer.DiffusionAnalyzer object
             species(list of str): list of species that are of interest.
         """
-
         trajectories = []
 
         # Initial structure.
@@ -427,7 +413,9 @@ 
    Source code for pymatgen.analysis.diffusion.aimd.pathway
    for s in diffusion_analyzer.get_drift_corrected_structures():
             trajectories.append(s.frac_coords)
 
-        return SiteOccupancyAnalyzer(structure, coords_ref, trajectories, species)
    
+        return SiteOccupancyAnalyzer(structure, coords_ref, trajectories, species)
    
+
    
+
    @@ -442,7 +430,7 @@

    Source code for pymatgen.analysis.diffusion.aimd.pathway

    +
    diff --git a/docs/_modules/pymatgen/analysis/diffusion/aimd/rdf.html b/docs/_modules/pymatgen/analysis/diffusion/aimd/rdf.html index 908ab60..2cc3af8 100644 --- a/docs/_modules/pymatgen/analysis/diffusion/aimd/rdf.html +++ b/docs/_modules/pymatgen/analysis/diffusion/aimd/rdf.html @@ -1,15 +1,15 @@ - + - pymatgen.analysis.diffusion.aimd.rdf — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.aimd.rdf — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -34,7 +34,7 @@

    Navigation

  • modules |
    • -
  • pymatgen-diffusion 2023.8.15 documentation »
    • +
  • pymatgen-diffusion 2024.6.10 documentation »
  • Module code »
  • pymatgen.analysis.diffusion.aimd.rdf
    • @@ -49,9 +49,8 @@

    Source code for pymatgen.analysis.diffusion.aimd.rdf

    # Copyright (c) Materials Virtual Lab. # Distributed under the terms of the BSD License. -""" -RDF implementation. -""" +"""RDF implementation.""" + from __future__ import annotations from collections import Counter @@ -68,7 +67,9 @@

    Source code for pymatgen.analysis.diffusion.aimd.rdf

    from pymatgen.util.plotting import pretty_plot -
    [docs]class RadialDistributionFunction: +
    +[docs] +class RadialDistributionFunction: """ Calculate the average radial distribution function for a given set of structures. @@ -99,7 +100,6 @@

    Source code for pymatgen.analysis.diffusion.aimd.rdf

    reference_indices ([int]): set this option along with 'indices' parameter to compute radial distribution function. """ - if ngrid < 2: raise ValueError("ngrid should be greater than 1!") if sigma <= 0: @@ -142,11 +142,7 @@

    Source code for pymatgen.analysis.diffusion.aimd.rdf

    self.rho = rho # This is the average density for fcoords, ref_fcoords, latt in zip(fcoords_list, ref_fcoords_list, lattices): - dcf = ( - fcoords[:, None, None, :] - + images[None, None, :, :] - - ref_fcoords[None, :, None, :] - ) + dcf = fcoords[:, None, None, :] + images[None, None, :, :] - ref_fcoords[None, :, None, :] dcc = latt.get_cartesian_coords(dcf) d2 = np.sum(dcc**2, axis=3) dists = [ @@ -176,18 +172,14 @@

    Source code for pymatgen.analysis.diffusion.aimd.rdf

    ) # additional dr factor renormalises overlapping gaussians. - raw_rdf[indx] += ( - dn / float(len(reference_indices)) / ff / rho / len(fcoords_list) - ) + raw_rdf[indx] += dn / float(len(reference_indices)) / ff / rho / len(fcoords_list) self.structures = structures self.cell_range = cell_range self.rmax = rmax self.ngrid = ngrid self.species = {structures[0][i].species_string for i in indices} - self.reference_species = { - structures[0][i].species_string for i in reference_indices - } + self.reference_species = {structures[0][i].species_string for i in reference_indices} self.indices = indices self.reference_indices = reference_indices self.dr = dr @@ -200,7 +192,9 @@

    Source code for pymatgen.analysis.diffusion.aimd.rdf

    self.peak_r = [self.interval[i] for i in self.peak_indices] self.peak_rdf = [self.rdf[i] for i in self.peak_indices] -
    [docs] @classmethod +
    +[docs] + @classmethod def from_species( cls, structures: list, @@ -229,15 +223,9 @@

    Source code for pymatgen.analysis.diffusion.aimd.rdf

    eg: species=["H"], reference_species=["O"] to compute O-H pair distribution in a water MD simulation. """ - indices = [ - j for j, site in enumerate(structures[0]) if site.specie.symbol in species - ] + indices = [j for j, site in enumerate(structures[0]) if site.specie.symbol in species] if reference_species: - reference_indices = [ - j - for j, site in enumerate(structures[0]) - if site.specie.symbol in reference_species - ] + reference_indices = [j for j, site in enumerate(structures[0]) if site.specie.symbol in reference_species] if len(reference_indices) < 1: raise ValueError("Given reference species are not in the structure!") @@ -254,26 +242,22 @@

    Source code for pymatgen.analysis.diffusion.aimd.rdf

    reference_indices=reference_indices, )
    + @property def coordination_number(self): """ - returns running coordination number + returns running coordination number. Returns: numpy array """ # Note: The average density from all input structures is used here. intervals = np.append(self.interval, self.interval[-1] + self.dr) - return np.cumsum( - self.raw_rdf - * self.rho - * 4.0 - / 3.0 - * np.pi - * (intervals[1:] ** 3 - intervals[:-1] ** 3) - ) + return np.cumsum(self.raw_rdf * self.rho * 4.0 / 3.0 * np.pi * (intervals[1:] ** 3 - intervals[:-1] ** 3)) -
    [docs] def get_rdf_plot( +
    +[docs] + def get_rdf_plot( self, label: str | None = None, xlim: tuple = (0.0, 8.0), @@ -289,7 +273,6 @@

    Source code for pymatgen.analysis.diffusion.aimd.rdf

    ylim (list): Set the y limits of the current axes. loc_peak (bool): Label peaks if True. """ - if label is None: symbol_list = [e.symbol for e in self.structures[0].composition] symbol_list = [symbol for symbol in symbol_list if symbol in self.species] @@ -312,8 +295,8 @@

    Source code for pymatgen.analysis.diffusion.aimd.rdf

    label="Peaks", ) - plt.xlabel("$r$ ($\\rm\\AA$)") - plt.ylabel("$g(r)$") + plt.set_xlabel("$r$ ($\\rm\\AA$)") + plt.set_ylabel("$g(r)$") plt.legend(loc="upper right", fontsize=36) plt.xlim(xlim[0], xlim[1]) plt.ylim(ylim[0], ylim[1]) @@ -321,7 +304,10 @@

    Source code for pymatgen.analysis.diffusion.aimd.rdf

    return plt
    -
    [docs] def export_rdf(self, filename: str): + +
    +[docs] + def export_rdf(self, filename: str): """ Output RDF data to a csv file. @@ -340,13 +326,15 @@

    Source code for pymatgen.analysis.diffusion.aimd.rdf

    for r, gr in zip(self.interval, self.rdf): f.write(delimiter.join([str(v) for v in [r, gr]])) - f.write("\n")
    + f.write("\n")
    +
    -
    [docs]class RadialDistributionFunctionFast: - """ - Fast radial distribution analysis. - """ + +
    +[docs] +class RadialDistributionFunctionFast: + """Fast radial distribution analysis.""" def __init__( self, @@ -414,9 +402,7 @@

    Source code for pymatgen.analysis.diffusion.aimd.rdf

    self.neighbor_elements = [elements[i] for i in self.neighbor_indices] self.density = [{}] * len(self.structures) # type: list[dict] - self.natoms = [ - i.composition.to_data_dict["unit_cell_composition"] for i in self.structures - ] + self.natoms = [i.composition.to_data_dict["unit_cell_composition"] for i in self.structures] for s_index, natoms in enumerate(self.natoms): for i, j in natoms.items(): @@ -429,23 +415,24 @@

    Source code for pymatgen.analysis.diffusion.aimd.rdf

    def _dist_to_counts(self, d): """ - Convert a distance array for counts in the bin + Convert a distance array for counts in the bin. Args: d: (1D np.array) + Returns: 1D array of counts in the bins centered on self.r """ counts = np.zeros((self.ngrid,)) - indices = np.array( - np.floor((d - self.rmin + 0.5 * self.dr) / self.dr), dtype=int - ) + indices = np.array(np.floor((d - self.rmin + 0.5 * self.dr) / self.dr), dtype=int) unique, val_counts = np.unique(indices, return_counts=True) counts[unique] = val_counts return counts -
    [docs] def get_rdf( +
    +[docs] + def get_rdf( self, ref_species: str | list[str], species: str | list[str], @@ -458,27 +445,26 @@

    Source code for pymatgen.analysis.diffusion.aimd.rdf

    species (list of species or just single specie str): the species that we are interested in. The rdfs are calculated on these species. is_average (bool): whether to take the average over - all structures + all structures. Returns: (x, rdf) x is the radial points, and rdf is the rdf value. """ if self.n_jobs > 1: all_rdfs = Parallel(n_jobs=self.n_jobs)( - self.get_one_rdf(ref_species, species, i) - for i in range(self.n_structures) + self.get_one_rdf(ref_species, species, i) for i in range(self.n_structures) ) all_rdfs = [i[1] for i in all_rdfs] else: - all_rdfs = [ - self.get_one_rdf(ref_species, species, i)[1] - for i in range(self.n_structures) - ] + all_rdfs = [self.get_one_rdf(ref_species, species, i)[1] for i in range(self.n_structures)] if is_average: all_rdfs = np.mean(all_rdfs, axis=0) return self.r, all_rdfs
    -
    [docs] def get_one_rdf( + +
    +[docs] + def get_one_rdf( self, ref_species: str | list[str], species: str | list[str], @@ -486,7 +472,7 @@

    Source code for pymatgen.analysis.diffusion.aimd.rdf

    ): """ Get the RDF for one structure, indicated by the index of the structure - in all structures + in all structures. Args: ref_species (list of species or just single specie str): the reference species. @@ -521,9 +507,12 @@

    Source code for pymatgen.analysis.diffusion.aimd.rdf

    rdf_temp = gaussian_filter1d(rdf_temp, self.sigma) return self.r, rdf_temp
    -
    [docs] def get_coordination_number(self, ref_species, species, is_average=True): + +
    +[docs] + def get_coordination_number(self, ref_species, species, is_average=True): """ - returns running coordination number + returns running coordination number. Args: ref_species (list of species or just single specie str): the reference species. @@ -540,18 +529,17 @@

    Source code for pymatgen.analysis.diffusion.aimd.rdf

    if isinstance(species, str): species = [species] density = [sum(i[j] for j in species) for i in self.density] - cn = [ - np.cumsum(rdf * density[i] * 4.0 * np.pi * self.r**2 * self.dr) - for i, rdf in enumerate(all_rdf) - ] + cn = [np.cumsum(rdf * density[i] * 4.0 * np.pi * self.r**2 * self.dr) for i, rdf in enumerate(all_rdf)] if is_average: cn = np.mean(cn, axis=0) - return self.r, cn
    + return self.r, cn
    +
    + def _get_neighbor_list(structure, r) -> tuple: """ - Thin wrapper to enable parallel calculations + Thin wrapper to enable parallel calculations. Args: structure (pymatgen Structure): pymatgen structure @@ -575,7 +563,7 @@

    Source code for pymatgen.analysis.diffusion.aimd.rdf

    +
    diff --git a/docs/_modules/pymatgen/analysis/diffusion/aimd/tests/test_clustering.html b/docs/_modules/pymatgen/analysis/diffusion/aimd/tests/test_clustering.html index c8085f9..a1c952b 100644 --- a/docs/_modules/pymatgen/analysis/diffusion/aimd/tests/test_clustering.html +++ b/docs/_modules/pymatgen/analysis/diffusion/aimd/tests/test_clustering.html @@ -1,15 +1,15 @@ - + - pymatgen.analysis.diffusion.aimd.tests.test_clustering — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.aimd.tests.test_clustering — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -34,7 +34,7 @@

    Navigation

  • modules |
    • -
  • pymatgen-diffusion 2023.8.15 documentation »
    • +
  • pymatgen-diffusion 2024.6.10 documentation »
  • Module code »
  • pymatgen.analysis.diffusion.aimd.tests.test_clustering
    • @@ -61,8 +61,12 @@

    Source code for pymatgen.analysis.diffusion.aimd.tests.test_clustering

    < from pymatgen.util.coord import pbc_diff -
    [docs]class KmeansTest(unittest.TestCase): -
    [docs] def test_cluster(self): +
    +[docs] +class KmeansTest(unittest.TestCase): +
    +[docs] + def test_cluster(self): data = np.random.uniform(size=(10, 5)) data = list(data) d2 = np.random.uniform(size=(10, 5)) + ([5] * 5) @@ -82,11 +86,17 @@

    Source code for pymatgen.analysis.diffusion.aimd.tests.test_clustering

    < if np.allclose(c1, a): same = True break - assert same
    + assert same
    +
    + -
    [docs]class KmeansPBCTest(unittest.TestCase): -
    [docs] def test_cluster(self): +
    +[docs] +class KmeansPBCTest(unittest.TestCase): +
    +[docs] + def test_cluster(self): lattice = Lattice.cubic(4) pts = [] @@ -105,11 +115,9 @@

    Source code for pymatgen.analysis.diffusion.aimd.tests.test_clustering

    < if np.allclose(pbc_diff(c1, c2), [0, 0, 0], atol=0.1): found = True break - assert found
    - + assert found
    +
    -if __name__ == "__main__": - unittest.main()
    @@ -124,7 +132,7 @@

    Source code for pymatgen.analysis.diffusion.aimd.tests.test_clustering

    < - +
    diff --git a/docs/_modules/pymatgen/analysis/diffusion/aimd/tests/test_pathway.html b/docs/_modules/pymatgen/analysis/diffusion/aimd/tests/test_pathway.html index bee999e..38e3702 100644 --- a/docs/_modules/pymatgen/analysis/diffusion/aimd/tests/test_pathway.html +++ b/docs/_modules/pymatgen/analysis/diffusion/aimd/tests/test_pathway.html @@ -1,15 +1,15 @@ - + - pymatgen.analysis.diffusion.aimd.tests.test_pathway — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.aimd.tests.test_pathway — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -34,7 +34,7 @@

    Navigation

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  • pymatgen.analysis.diffusion.aimd.tests.test_pathway
    • @@ -59,10 +59,7 @@

    Source code for pymatgen.analysis.diffusion.aimd.tests.test_pathway

    import numpy as np -from pymatgen.analysis.diffusion.aimd.pathway import ( - ProbabilityDensityAnalysis, - SiteOccupancyAnalyzer, -) +from pymatgen.analysis.diffusion.aimd.pathway import ProbabilityDensityAnalysis, SiteOccupancyAnalyzer from pymatgen.analysis.diffusion.analyzer import DiffusionAnalyzer from pymatgen.core import Structure from pymatgen.io.vasp import Chgcar @@ -70,8 +67,12 @@

    Source code for pymatgen.analysis.diffusion.aimd.tests.test_pathway

    tests_dir = os.path.dirname(os.path.abspath(__file__)) -
    [docs]class ProbabilityDensityTest(unittest.TestCase): -
    [docs] def test_probability(self): +
    +[docs] +class ProbabilityDensityTest(unittest.TestCase): +
    +[docs] + def test_probability(self): traj_file = os.path.join(tests_dir, "cNa3PS4_trajectories.npy") struc_file = os.path.join(tests_dir, "cNa3PS4.cif") @@ -87,7 +88,10 @@

    Source code for pymatgen.analysis.diffusion.aimd.tests.test_pathway

    self.assertAlmostEqual(pda.Pr.min(), 0.0, 12) self.assertAlmostEqual(Pr_tot, 1.0, 12)
    -
    [docs] def test_probability_classmethod(self): + +
    +[docs] + def test_probability_classmethod(self): file = os.path.join(tests_dir, "cNa3PS4_pda.json") data = json.load(open(file)) diff_analyzer = DiffusionAnalyzer.from_dict(data) @@ -103,7 +107,10 @@

    Source code for pymatgen.analysis.diffusion.aimd.tests.test_pathway

    self.assertAlmostEqual(pda.Pr.min(), 0.0, 12) self.assertAlmostEqual(Pr_tot, 1.0, 12)
    -
    [docs] def test_generate_stable_sites(self): + +
    +[docs] + def test_generate_stable_sites(self): file = os.path.join(tests_dir, "cNa3PS4_pda.json") data = json.load(open(file)) diff_analyzer = DiffusionAnalyzer.from_dict(data) @@ -124,7 +131,10 @@

    Source code for pymatgen.analysis.diffusion.aimd.tests.test_pathway

    assert s.composition["X"] == 50 self.assertAlmostEqual(s[177].frac_coords[2], 0.57446809)
    -
    [docs] def test_to_chgcar(self): + +
    +[docs] + def test_to_chgcar(self): file = os.path.join(tests_dir, "cNa3PS4_pda.json") data = json.load(open(file)) diff_analyzer = DiffusionAnalyzer.from_dict(data) @@ -136,11 +146,17 @@

    Source code for pymatgen.analysis.diffusion.aimd.tests.test_pathway

    pda.to_chgcar("CHGCAR.PDA") chgcar = Chgcar.from_file("CHGCAR.PDA") assert pda.structure.species == chgcar.structure.species - os.remove("CHGCAR.PDA")
    + os.remove("CHGCAR.PDA")
    +
    + -
    [docs]class SiteOccupancyTest(unittest.TestCase): -
    [docs] def test_site_occupancy(self): +
    +[docs] +class SiteOccupancyTest(unittest.TestCase): +
    +[docs] + def test_site_occupancy(self): traj_file = os.path.join(tests_dir, "cNa3PS4_trajectories.npy") struc_file = os.path.join(tests_dir, "cNa3PS4.cif") @@ -159,7 +175,10 @@

    Source code for pymatgen.analysis.diffusion.aimd.tests.test_pathway

    self.assertAlmostEqual(site_occ[15], 0.875, 12) assert len(coords_ref) == 48
    -
    [docs] def test_site_occupancy_classmethod(self): + +
    +[docs] + def test_site_occupancy_classmethod(self): file = os.path.join(tests_dir, "cNa3PS4_pda.json") data = json.load(open(file)) diff_analyzer = DiffusionAnalyzer.from_dict(data) @@ -175,11 +194,9 @@

    Source code for pymatgen.analysis.diffusion.aimd.tests.test_pathway

    self.assertAlmostEqual(np.sum(site_occ), len(coords_ref), 12) self.assertAlmostEqual(site_occ[1], 0.98, 12) self.assertAlmostEqual(site_occ[26], 0.97, 12) - assert len(coords_ref) == 48
    - + assert len(coords_ref) == 48
    +
    -if __name__ == "__main__": - unittest.main()
    @@ -194,7 +211,7 @@

    Source code for pymatgen.analysis.diffusion.aimd.tests.test_pathway

    - +
    diff --git a/docs/_modules/pymatgen/analysis/diffusion/aimd/tests/test_rdf.html b/docs/_modules/pymatgen/analysis/diffusion/aimd/tests/test_rdf.html index c7409af..7e18b3a 100644 --- a/docs/_modules/pymatgen/analysis/diffusion/aimd/tests/test_rdf.html +++ b/docs/_modules/pymatgen/analysis/diffusion/aimd/tests/test_rdf.html @@ -1,15 +1,15 @@ - + - pymatgen.analysis.diffusion.aimd.tests.test_rdf — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.aimd.tests.test_rdf — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -34,7 +34,7 @@

    Navigation

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  • pymatgen.analysis.diffusion.aimd.tests.test_rdf
    • @@ -60,8 +60,12 @@

    Source code for pymatgen.analysis.diffusion.aimd.tests.test_rdf

    tests_dir = os.path.dirname(os.path.abspath(__file__)) -
    [docs]class RDFTest(unittest.TestCase): -
    [docs] def test_rdf(self): +
    +[docs] +class RDFTest(unittest.TestCase): +
    +[docs] + def test_rdf(self): # Parse the DiffusionAnalyzer object from json file directly obj = loadfn(os.path.join(tests_dir, "cNa3PS4_pda.json")) @@ -81,7 +85,10 @@

    Source code for pymatgen.analysis.diffusion.aimd.tests.test_rdf

    self.assertAlmostEqual(r[np.argmax(s_na_rdf)], 2.9000, 4)
    -
    [docs] def test_rdf_coordination_number(self): + +
    +[docs] + def test_rdf_coordination_number(self): # create a simple cubic lattice coords = np.array([[0.5, 0.5, 0.5]]) atom_list = ["S"] @@ -92,11 +99,9 @@

    Source code for pymatgen.analysis.diffusion.aimd.tests.test_rdf

    rdf = RadialDistributionFunctionFast( structures=[structure], rmax=5.0, sigma=0.01, ngrid=500 ) - assert np.round(rdf.get_coordination_number("S", "S")[1][110], 2) == 6.0
    - + assert np.round(rdf.get_coordination_number("S", "S")[1][110], 2) == 6.0
    +
    -if __name__ == "__main__": - unittest.main()
    @@ -111,7 +116,7 @@

    Source code for pymatgen.analysis.diffusion.aimd.tests.test_rdf

    - +
    diff --git a/docs/_modules/pymatgen/analysis/diffusion/aimd/tests/test_van_hove.html b/docs/_modules/pymatgen/analysis/diffusion/aimd/tests/test_van_hove.html index d5e70ac..c2ce69d 100644 --- a/docs/_modules/pymatgen/analysis/diffusion/aimd/tests/test_van_hove.html +++ b/docs/_modules/pymatgen/analysis/diffusion/aimd/tests/test_van_hove.html @@ -1,15 +1,15 @@ - + - pymatgen.analysis.diffusion.aimd.tests.test_van_hove — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.aimd.tests.test_van_hove — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -34,7 +34,7 @@

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  • pymatgen.analysis.diffusion.aimd.tests.test_van_hove
    • @@ -61,20 +61,21 @@

    Source code for pymatgen.analysis.diffusion.aimd.tests.test_van_hove

    import matplotlib as mpl import numpy as np +import pytest from monty.serialization import loadfn -from pymatgen.analysis.diffusion.aimd.van_hove import ( - EvolutionAnalyzer, - RadialDistributionFunction, - VanHoveAnalysis, -) +from pymatgen.analysis.diffusion.aimd.van_hove import EvolutionAnalyzer, RadialDistributionFunction, VanHoveAnalysis mpl.use("pdf") tests_dir = os.path.dirname(os.path.abspath(__file__)) -
    [docs]class VanHoveTest(unittest.TestCase): -
    [docs] def test_van_hove(self): +
    +[docs] +class VanHoveTest(unittest.TestCase): +
    +[docs] + def test_van_hove(self): # Parse the DiffusionAnalyzer object from json file directly obj = loadfn(os.path.join(tests_dir, "cNa3PS4_pda.json")) @@ -91,11 +92,17 @@

    Source code for pymatgen.analysis.diffusion.aimd.tests.test_van_hove

    check = np.shape(vh.gsrt) == (20, 101) and np.shape(vh.gdrt) == (20, 101) assert check self.assertAlmostEqual(vh.gsrt[0, 0], 3.98942280401, 10) - self.assertAlmostEqual(vh.gdrt[10, 0], 9.68574868168, 10)
    + self.assertAlmostEqual(vh.gdrt[10, 0], 9.68574868168, 10)
    +
    + -
    [docs]class RDFTest(unittest.TestCase): -
    [docs] def test_rdf(self): +
    +[docs] +class RDFTest(unittest.TestCase): +
    +[docs] + def test_rdf(self): # Parse the DiffusionAnalyzer object from json file directly obj = loadfn(os.path.join(tests_dir, "cNa3PS4_pda.json")) @@ -165,7 +172,10 @@

    Source code for pymatgen.analysis.diffusion.aimd.tests.test_van_hove

    self.assertAlmostEqual(obj_1.rho, obj_2.rho) self.assertAlmostEqual(obj_1.rdf[0], obj_2.rdf[0])
    -
    [docs] def test_rdf_coordination_number(self): + +
    +[docs] + def test_rdf_coordination_number(self): # create a simple cubic lattice coords = np.array([[0.5, 0.5, 0.5]]) atom_list = ["S"] @@ -178,7 +188,10 @@

    Source code for pymatgen.analysis.diffusion.aimd.tests.test_van_hove

    ) assert rdf.coordination_number[100] == 6.0
    -
    [docs] def test_rdf_two_species_coordination_number(self): + +
    +[docs] + def test_rdf_two_species_coordination_number(self): # create a structure with interpenetrating simple cubic lattice coords = np.array([[0.0, 0.0, 0.0], [0.5, 0.5, 0.5]]) atom_list = ["S", "Zn"] @@ -196,7 +209,10 @@

    Source code for pymatgen.analysis.diffusion.aimd.tests.test_van_hove

    ) assert rdf.coordination_number[100] == 8.0
    -
    [docs] def setUp(self): + +
    +[docs] + def setUp(self): coords = np.array([[0.5, 0.5, 0.5]]) atom_list = ["S"] lattice = Lattice.from_parameters( @@ -204,33 +220,51 @@

    Source code for pymatgen.analysis.diffusion.aimd.tests.test_van_hove

    ) self.structure = Structure(lattice, atom_list, coords)
    -
    [docs] def test_raises_valueerror_if_ngrid_is_less_than_2(self): - with self.assertRaises(ValueError): + +
    +[docs] + def test_raises_valueerror_if_ngrid_is_less_than_2(self): + with pytest.raises(ValueError): RadialDistributionFunction.from_species( structures=[self.structure], ngrid=1 )
    -
    [docs] def test_raises_ValueError_if_sigma_is_not_positive(self): - with self.assertRaises(ValueError): + +
    +[docs] + def test_raises_ValueError_if_sigma_is_not_positive(self): + with pytest.raises(ValueError): RadialDistributionFunction.from_species( structures=[self.structure], sigma=0 )
    -
    [docs] def test_raises_ValueError_if_species_not_in_structure(self): - with self.assertRaises(ValueError): + +
    +[docs] + def test_raises_ValueError_if_species_not_in_structure(self): + with pytest.raises(ValueError): RadialDistributionFunction.from_species( structures=[self.structure], species=["Cl"] )
    -
    [docs] def test_raises_ValueError_if_reference_species_not_in_structure(self): - with self.assertRaises(ValueError): + +
    +[docs] + def test_raises_ValueError_if_reference_species_not_in_structure(self): + with pytest.raises(ValueError): RadialDistributionFunction.from_species( structures=[self.structure], species=["S"], reference_species=["Cl"] - )
    + )
    +
    + -
    [docs]class EvolutionAnalyzerTest(unittest.TestCase): -
    [docs] def test_get_df(self): +
    +[docs] +class EvolutionAnalyzerTest(unittest.TestCase): +
    +[docs] + def test_get_df(self): # Parse the DiffusionAnalyzer object from json file directly obj = loadfn(os.path.join(tests_dir, "cNa3PS4_pda.json")) @@ -248,11 +282,9 @@

    Source code for pymatgen.analysis.diffusion.aimd.tests.test_van_hove

    and ("Na", "Na") in eva.pairs ) assert check - self.assertAlmostEqual(max(np.array(rdf)[0]), 1.772465, 4)
    - + self.assertAlmostEqual(max(np.array(rdf)[0]), 1.772465, 4)
    +
    -if __name__ == "__main__": - unittest.main()
    @@ -267,7 +299,7 @@

    Source code for pymatgen.analysis.diffusion.aimd.tests.test_van_hove

    - +
    diff --git a/docs/_modules/pymatgen/analysis/diffusion/aimd/van_hove.html b/docs/_modules/pymatgen/analysis/diffusion/aimd/van_hove.html index 3071330..90947ef 100644 --- a/docs/_modules/pymatgen/analysis/diffusion/aimd/van_hove.html +++ b/docs/_modules/pymatgen/analysis/diffusion/aimd/van_hove.html @@ -1,15 +1,15 @@ - + - pymatgen.analysis.diffusion.aimd.van_hove — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.aimd.van_hove — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -34,7 +34,7 @@

    Navigation

  • modules |
    • -
  • pymatgen-diffusion 2023.8.15 documentation »
    • +
  • pymatgen-diffusion 2024.6.10 documentation »
  • Module code »
  • pymatgen.analysis.diffusion.aimd.van_hove
    • @@ -49,9 +49,8 @@

    Source code for pymatgen.analysis.diffusion.aimd.van_hove

    # Copyright (c) Materials Virtual Lab. # Distributed under the terms of the BSD License. -""" -Van Hove analysis for correlations. -""" +"""Van Hove analysis for correlations.""" + from __future__ import annotations import itertools @@ -76,16 +75,18 @@

    Source code for pymatgen.analysis.diffusion.aimd.van_hove

    __date__ = "Aug 9, 2017" -
    [docs]class VanHoveAnalysis: +
    +[docs] +class VanHoveAnalysis: """ - Class for van Hove function analysis. In particular, self-part (Gs) and - distinct-part (Gd) of the van Hove correlation function G(r,t) - for given species and given structure are computed. If you use this class, - please consider citing the following paper: - - Zhu, Z.; Chu, I.-H.; Deng, Z. and Ong, S. P. "Role of Na+ Interstitials - and Dopants in Enhancing the Na+ Conductivity of the Cubic Na3PS4 - Superionic Conductor". Chem. Mater. (2015), 27, pp 8318-8325 + Class for van Hove function analysis. + + In particular, self-part (Gs) and distinct-part (Gd) of the van Hove correlation function G(r,t) for given species + and given structure are computed. If you use this class, please consider citing the following paper:: + + Zhu, Z.; Chu, I.-H.; Deng, Z. and Ong, S. P. "Role of Na+ Interstitials + and Dopants in Enhancing the Na+ Conductivity of the Cubic Na3PS4 + Superionic Conductor". Chem. Mater. (2015), 27, pp 8318-8325 """ def __init__( @@ -125,7 +126,6 @@

    Source code for pymatgen.analysis.diffusion.aimd.van_hove

    will be selected for the analysis. If this is given, "species" parameter will be ignored. """ - # initial check if step_skip <= 0: raise ValueError("skip_step should be >=1!") @@ -151,17 +151,11 @@

    Source code for pymatgen.analysis.diffusion.aimd.van_hove

    structure = diffusion_analyzer.structure if indices is None: - indices = [ - j for j, site in enumerate(structure) if site.specie.symbol in species - ] + indices = [j for j, site in enumerate(structure) if site.specie.symbol in species] ref_indices = indices if reference_species: - ref_indices = [ - j - for j, site in enumerate(structure) - if site.specie.symbol in reference_species - ] + ref_indices = [j for j, site in enumerate(structure) if site.specie.symbol in reference_species] rho = float(len(indices)) / lattice.volume @@ -186,11 +180,7 @@

    Source code for pymatgen.analysis.diffusion.aimd.van_hove

    tracking_ions = np.array(tracking_ions) # type: ignore ref_ions = np.array(ref_ions) # type: ignore - gaussians = ( - norm.pdf(interval[:, None], interval[None, :], sigma) - / float(avg_nsteps) - / float(len(ref_indices)) - ) + gaussians = norm.pdf(interval[:, None], interval[None, :], sigma) / float(avg_nsteps) / float(len(ref_indices)) # calculate self part of van Hove function image = np.array([0, 0, 0]) @@ -199,15 +189,11 @@

    Source code for pymatgen.analysis.diffusion.aimd.van_hove

    it0 = min(it * step_skip, ntsteps) for it1 in range(avg_nsteps): dists = [ - lattice.get_distance_and_image( - tracking_ions[it1][u], tracking_ions[it0 + it1][u], jimage=image - )[0] + lattice.get_distance_and_image(tracking_ions[it1][u], tracking_ions[it0 + it1][u], jimage=image)[0] for u in range(len(indices)) ] - r_indices = [ - int(dist / dr) for dist in filter(lambda e: e < rmax, dists) - ] + r_indices = [int(dist / dr) for dist in filter(lambda e: e < rmax, dists)] dns.update(r_indices) # type: ignore for indx, dn in dns.most_common(ngrid): @@ -245,9 +231,7 @@

    Source code for pymatgen.analysis.diffusion.aimd.van_hove

    if u != v or j != indx0 ] - r_indices = [ - int(dist / dr) for dist in filter(lambda e: e < rmax, dists) - ] + r_indices = [int(dist / dr) for dist in filter(lambda e: e < rmax, dists)] dns.update(r_indices) for indx, dn in dns.most_common(ngrid): @@ -264,12 +248,13 @@

    Source code for pymatgen.analysis.diffusion.aimd.van_hove

    # time interval (in ps) in gsrt and gdrt. self.timeskip = self.obj.time_step * self.obj.step_skip * step_skip / 1000.0 -
    [docs] def get_3d_plot(self, figsize: tuple = (12, 8), mode: str = "distinct"): +
    +[docs] + def get_3d_plot(self, figsize: tuple = (12, 8), mode: str = "distinct"): """ Plot 3D self-part or distinct-part of van Hove function, which is specified by the input argument 'type'. """ - assert mode in ["distinct", "self"] if mode == "distinct": @@ -277,17 +262,13 @@

    Source code for pymatgen.analysis.diffusion.aimd.van_hove

    vmax = 4.0 cb_ticks = [0, 1, 2, 3, 4] cb_label = "$G_d$($t$,$r$)" - elif mode == "self": + else: grt = self.gsrt.copy() vmax = 1.0 cb_ticks = [0, 1] cb_label = r"4$\pi r^2G_s$($t$,$r$)" - y = ( - np.arange(np.shape(grt)[1]) - * self.interval[-1] - / float(len(self.interval) - 1) - ) + y = np.arange(np.shape(grt)[1]) * self.interval[-1] / float(len(self.interval) - 1) x = np.arange(np.shape(grt)[0]) * self.timeskip X, Y = np.meshgrid(x, y, indexing="ij") @@ -300,8 +281,8 @@

    Source code for pymatgen.analysis.diffusion.aimd.van_hove

    labelsize = int(figsize[0] * 3) plt.pcolor(X, Y, grt, cmap="jet", vmin=grt.min(), vmax=vmax) - plt.xlabel("Time (ps)", size=labelsize) - plt.ylabel(r"$r$ ($\AA$)", size=labelsize) + plt.set_xlabel("Time (ps)", size=labelsize) + plt.set_ylabel(r"$r$ ($\AA$)", size=labelsize) plt.axis([x.min(), x.max(), y.min(), y.max()]) cbar = plt.colorbar(ticks=cb_ticks) @@ -311,8 +292,14 @@

    Source code for pymatgen.analysis.diffusion.aimd.van_hove

    return plt
    -
    [docs] def get_1d_plot( - self, mode: str = "distinct", times: list = [0.0], colors: list | None = None + +
    +[docs] + def get_1d_plot( + self, + mode: str = "distinct", + times: list | None = None, + colors: list | None = None, ): """ Plot the van Hove function at given r or t. @@ -324,6 +311,8 @@

    Source code for pymatgen.analysis.diffusion.aimd.van_hove

    colors (list strings/tuples): Additional color settings. If not set, seaborn.color_plaette("Set1", 10) will be used. """ + if times is None: + times = [0.0] if colors is None: import seaborn as sns @@ -336,7 +325,7 @@

    Source code for pymatgen.analysis.diffusion.aimd.van_hove

    grt = self.gdrt.copy() ylabel = "$G_d$($t$,$r$)" ylim = [-0.005, 4.0] - elif mode == "self": + else: grt = self.gsrt.copy() ylabel = r"4$\pi r^2G_s$($t$,$r$)" ylim = [-0.005, 1.0] @@ -348,28 +337,26 @@

    Source code for pymatgen.analysis.diffusion.aimd.van_hove

    index = min(index, np.shape(grt)[0] - 1) new_time = index * self.timeskip label = str(new_time) + " ps" - plt.plot( - self.interval, grt[index], color=colors[i], label=label, linewidth=4.0 - ) + plt.plot(self.interval, grt[index], color=colors[i], label=label, linewidth=4.0) - plt.xlabel(r"$r$ ($\AA$)") - plt.ylabel(ylabel) + plt.set_xlabel(r"$r$ ($\AA$)") + plt.set_ylabel(ylabel) plt.legend(loc="upper right", fontsize=36) plt.xlim(0.0, self.interval[-1] - 1.0) plt.ylim(ylim[0], ylim[1]) plt.tight_layout() - return plt
    + return plt
    +
    -
    [docs]class EvolutionAnalyzer: - """ - Analyze the evolution of structures during AIMD simulations. - """ - def __init__( - self, structures: list, rmax: float = 10, step: int = 1, time_step: int = 2 - ): +
    +[docs] +class EvolutionAnalyzer: + """Analyze the evolution of structures during AIMD simulations.""" + + def __init__(self, structures: list, rmax: float = 10, step: int = 1, time_step: int = 2): """ Initialization the EvolutionAnalyzer from MD simulations. From the structures obtained from MD simulations, we can analyze the structure @@ -397,7 +384,9 @@

    Source code for pymatgen.analysis.diffusion.aimd.van_hove

    self.step = step self.time_step = time_step -
    [docs] @staticmethod +
    +[docs] + @staticmethod def get_pairs(structure: Structure): """ Get all element pairs in a structure. @@ -413,7 +402,10 @@

    Source code for pymatgen.analysis.diffusion.aimd.van_hove

    return list(pairs)
    -
    [docs] @staticmethod + +
    +[docs] + @staticmethod def rdf(structure: Structure, pair: tuple, ngrid: int = 101, rmax: float = 10): """ Process rdf from a given structure and pair. @@ -438,7 +430,10 @@

    Source code for pymatgen.analysis.diffusion.aimd.van_hove

    return r.rdf
    -
    [docs] @staticmethod + +
    +[docs] + @staticmethod def atom_dist( structure: Structure, specie: str, @@ -461,9 +456,9 @@

    Source code for pymatgen.analysis.diffusion.aimd.van_hove

    density (np.array): atomic concentration along one direction. """ if direction in ["a", "b", "c"]: - l = getattr(structure.lattice, direction) + latt_len = getattr(structure.lattice, direction) ind = ["a", "b", "c"].index(direction) - assert window <= l, "Window range exceeds valid bounds!" + assert window <= latt_len, "Window range exceeds valid bounds!" else: raise ValueError("Choose from a, b and c!") @@ -471,21 +466,20 @@

    Source code for pymatgen.analysis.diffusion.aimd.van_hove

    atom_total = structure.composition[specie] density = [] - for i in np.linspace(0, l - window, ngrid): + for i in np.linspace(0, latt_len - window, ngrid): atoms = [] for j in [-1, 0, 1]: - temp = [ - s - for s in atom_list - if i - window < s.coords[ind] % l + l * j < i + window - ] + temp = [s for s in atom_list if i - window < s.coords[ind] % latt_len + latt_len * j < i + window] atoms.extend(temp) density.append(len(atoms) / atom_total) return np.array(density)
    -
    [docs] def get_df(self, func: Callable, save_csv: str | None = None, **kwargs): + +
    +[docs] + def get_df(self, func: Callable, save_csv: str | None = None, **kwargs): """ Get the data frame for a given pair. This step would be very slow if there are hundreds or more structures to parse. @@ -502,6 +496,7 @@

    Source code for pymatgen.analysis.diffusion.aimd.van_hove

    df = EvolutionAnalyzer.get_df( func=EvolutionAnalyzer.atom_dist, specie="Na") save_csv (str): save pandas DataFrame to csv. + **kwargs: Pass-through to func. Returns: pandas.DataFrame object: index is the radial distance in Angstrom, @@ -524,7 +519,10 @@

    Source code for pymatgen.analysis.diffusion.aimd.van_hove

    return df
    -
    [docs] @staticmethod + +
    +[docs] + @staticmethod def get_min_dist(df: pd.DataFrame, tol: float = 1e-10): """ Get the shortest pair distance from the given DataFrame. @@ -544,7 +542,10 @@

    Source code for pymatgen.analysis.diffusion.aimd.van_hove

    return float(col) raise RuntimeError("Getting min dist failed.")
    -
    [docs] @staticmethod + +
    +[docs] + @staticmethod def plot_evolution_from_data( df: pd.DataFrame, x_label: str | None = None, @@ -557,7 +558,6 @@

    Source code for pymatgen.analysis.diffusion.aimd.van_hove

    implement in the future. Args: - df (pandas.DataFrame): input DataFrame object, index is the radial distance in Angstrom, and column is the time step in ps. x_label (str): x label @@ -593,15 +593,18 @@

    Source code for pymatgen.analysis.diffusion.aimd.van_hove

    plt.xticks(rotation="horizontal") - plt.xlabel(x_label, fontsize=30) - plt.ylabel("Time (ps)", fontsize=30) + plt.set_xlabel(x_label, fontsize=30) + plt.set_ylabel("Time (ps)", fontsize=30) plt.yticks(rotation="horizontal") plt.tight_layout() return plt
    -
    [docs] def plot_rdf_evolution( + +
    +[docs] + def plot_rdf_evolution( self, pair: tuple, cmap=plt.cm.plasma, # pylint: disable=E1101 @@ -616,17 +619,19 @@

    Source code for pymatgen.analysis.diffusion.aimd.van_hove

    cmocean.cm.thermal is recommended df (DataFrame): external data, index is the radial distance in Angstrom, and column is the time step in ps. + Returns: matplotlib.axes._subplots.AxesSubplot object """ if df is None: df = self.get_df(func=EvolutionAnalyzer.rdf, pair=pair) x_label, cb_label = f"$r$ ({pair[0]}-{pair[1]}) ($\\rm\\AA$)", "$g(r)$" - return self.plot_evolution_from_data( - df=df, x_label=x_label, cb_label=cb_label, cmap=cmap - )
    + return self.plot_evolution_from_data(df=df, x_label=x_label, cb_label=cb_label, cmap=cmap)
    + -
    [docs] def plot_atomic_evolution( +
    +[docs] + def plot_atomic_evolution( self, specie: str, direction: str = "c", @@ -642,20 +647,19 @@

    Source code for pymatgen.analysis.diffusion.aimd.van_hove

    cmap (color map): the color map used in heat map. df (DataFrame): external data, index is the atomic distance in Angstrom, and column is the time step in ps. + Returns: matplotlib.axes._subplots.AxesSubplot object """ if df is None: - df = self.get_df( - func=EvolutionAnalyzer.atom_dist, specie=specie, direction=direction - ) + df = self.get_df(func=EvolutionAnalyzer.atom_dist, specie=specie, direction=direction) x_label, cb_label = ( f"Atomic distribution along {direction}", "Probability", ) - return self.plot_evolution_from_data( - df=df, x_label=x_label, cb_label=cb_label, cmap=cmap - )
    + return self.plot_evolution_from_data(df=df, x_label=x_label, cb_label=cb_label, cmap=cmap)
    +
    +
    @@ -670,7 +674,7 @@

    Source code for pymatgen.analysis.diffusion.aimd.van_hove

    +
    diff --git a/docs/_modules/pymatgen/analysis/diffusion/analyzer.html b/docs/_modules/pymatgen/analysis/diffusion/analyzer.html index 68cc543..eb71b2b 100644 --- a/docs/_modules/pymatgen/analysis/diffusion/analyzer.html +++ b/docs/_modules/pymatgen/analysis/diffusion/analyzer.html @@ -1,15 +1,15 @@ - + - pymatgen.analysis.diffusion.analyzer — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.analyzer — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -34,7 +34,7 @@

    Navigation

  • modules |
    • -
  • pymatgen-diffusion 2023.8.15 documentation »
    • +
  • pymatgen-diffusion 2024.6.10 documentation »
  • Module code »
  • pymatgen.analysis.diffusion.analyzer
    • @@ -46,12 +46,9 @@

    Navigation

    Source code for pymatgen.analysis.diffusion.analyzer

    -# Copyright (c) Pymatgen Development Team.
-# Distributed under the terms of the MIT License.
+"""A module to perform diffusion analyses.
 
-"""
-A module to perform diffusion analyses (e.g. calculating diffusivity from
-mean square displacements etc.). If you use this module, please consider
+For example, calculating diffusivity from mean square displacements etc.). If you use this module, please consider
 citing the following papers::
 
     Ong, S. P., Mo, Y., Richards, W. D., Miara, L., Lee, H. S., & Ceder, G.
@@ -64,6 +61,7 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
        Li10GeP2S12 Lithium Super Ionic Conductor Material. Chemistry of Materials,
     24(1), 15-17. doi:10.1021/cm203303y
 """
+
 from __future__ import annotations
 
 import multiprocessing
@@ -73,10 +71,7 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
    import scipy.constants as const
 from monty.json import MSONable
 
-from pymatgen.analysis.structure_matcher import (
-    OrderDisorderElementComparator,
-    StructureMatcher,
-)
+from pymatgen.analysis.structure_matcher import OrderDisorderElementComparator, StructureMatcher
 from pymatgen.core.periodic_table import get_el_sp
 from pymatgen.core.structure import Structure
 from pymatgen.io.vasp.outputs import Vasprun
@@ -90,7 +85,9 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
    __date__ = "5/2/13"
 
 
-
    [docs]class DiffusionAnalyzer(MSONable):
+
    
+[docs]
+class DiffusionAnalyzer(MSONable):
     """
     Class for performing diffusion analysis.
 
@@ -311,9 +308,7 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
    max_dt = min(len(indices) * nsteps // self.min_obs, nsteps)
                 if min_dt >= max_dt:
                     raise ValueError("Not enough data to calculate diffusivity")
-                timesteps = np.arange(
-                    min_dt, max_dt, max(int((max_dt - min_dt) / 200), 1)
-                )
+                timesteps = np.arange(min_dt, max_dt, max(int((max_dt - min_dt) / 200), 1))
 
             dt = timesteps * self.time_step * self.step_skip
 
@@ -328,7 +323,7 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
    # calculate regional msd and number of diffusing specie in those regions
             msd_c_range = np.zeros_like(dt, dtype=np.double)
             msd_c_range_components = np.zeros((*dt.shape, 3))
-
+            indices_c_range = []
             for i, n in enumerate(timesteps):
                 if not smoothed:
                     dx = dc[:, i : i + 1, :]
@@ -348,50 +343,38 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
    # Get regional msd
                 if c_ranges:
-                    indices_c_range = []
                     if not c_range_include_edge:
                         for index in indices:
                             if any(
-                                lower < structures[i][index].c < upper
-                                and lower < structures[i + 1][index].c < upper
+                                lower < structures[i][index].c < upper and lower < structures[i + 1][index].c < upper
                                 for (lower, upper) in c_ranges
                             ):
                                 indices_c_range.append(index)
                     else:
                         for index in indices:
                             if any(
-                                lower <= structures[i][index].c <= upper
-                                or lower <= structures[i + 1][index].c <= upper
+                                lower <= structures[i][index].c <= upper or lower <= structures[i + 1][index].c <= upper
                                 for (lower, upper) in c_ranges
                             ):
                                 indices_c_range.append(index)
                     msd_c_range[i] = np.average(sq_disp_ions[:, i][indices_c_range])
-                    msd_c_range_components[i] = np.average(
-                        dcomponents[indices_c_range] ** 2, axis=(0, 1)
-                    )
+                    msd_c_range_components[i] = np.average(dcomponents[indices_c_range] ** 2, axis=(0, 1))
 
                 # Get mscd
                 sq_chg_disp = np.sum(dx[indices, :, :], axis=0) ** 2
                 mscd[i] = np.average(np.sum(sq_chg_disp, axis=1), axis=0) / len(indices)
 
-            conv_factor = get_conversion_factor(
-                self.structure, self.specie, self.temperature
-            )
-            self.diffusivity, self.diffusivity_std_dev = get_diffusivity_from_msd(
-                msd, dt, smoothed
-            )
+            conv_factor = get_conversion_factor(self.structure, self.specie, self.temperature)
+            self.diffusivity, self.diffusivity_std_dev = get_diffusivity_from_msd(msd, dt, smoothed)
             (
                 self.chg_diffusivity,
                 self.chg_diffusivity_std_dev,
             ) = get_diffusivity_from_msd(mscd, dt, smoothed)
             diffusivity_components = np.zeros(3)
             diffusivity_components_std_dev = np.zeros(3)
-            for i in range(3):
-                diffusivity_components[i], diffusivity_components_std_dev[i] = (
-                    np.array(
-                        get_diffusivity_from_msd(msd_components[:, i], dt, smoothed)
-                    )
-                    * 3
+            for j in range(3):
+                diffusivity_components[j], diffusivity_components_std_dev[j] = (
+                    np.array(get_diffusivity_from_msd(msd_components[:, j], dt, smoothed)) * 3
                 )
             self.diffusivity_components = diffusivity_components
             self.diffusivity_components_std_dev = diffusivity_components_std_dev
@@ -401,9 +384,7 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
    self.chg_conductivity = self.chg_diffusivity * conv_factor
             self.chg_conductivity_std_dev = self.chg_diffusivity_std_dev * conv_factor
             self.conductivity_components = self.diffusivity_components * conv_factor
-            self.conductivity_components_std_dev = (
-                self.diffusivity_components_std_dev * conv_factor
-            )
+            self.conductivity_components_std_dev = self.diffusivity_components_std_dev * conv_factor
 
             if c_ranges:
                 (
@@ -412,42 +393,23 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
    ) = get_diffusivity_from_msd(msd_c_range, dt, smoothed)
                 diffusivity_c_range_components = np.zeros(3)
                 diffusivity_c_range_components_std_dev = np.zeros(3)
-                (
-                    diffusivity_c_range_components[i],
-                    diffusivity_c_range_components_std_dev[i],
-                ) = (
-                    np.array(
-                        get_diffusivity_from_msd(
-                            msd_c_range_components[:, i], dt, smoothed
-                        )
-                    )
-                    * 3
-                )
+                for j in range(3):
+                    (
+                        diffusivity_c_range_components[j],
+                        diffusivity_c_range_components_std_dev[j],
+                    ) = np.array(get_diffusivity_from_msd(msd_c_range_components[:, j], dt, smoothed)) * 3
 
                 self.diffusivity_c_range_components = diffusivity_c_range_components
-                self.diffusivity_c_range_components_std_dev = (
-                    diffusivity_c_range_components_std_dev
-                )
+                self.diffusivity_c_range_components_std_dev = diffusivity_c_range_components_std_dev
 
-                n_specie_c_range = np.average([len(i) for i in indices_c_range])
-                vol_c_range = np.sum(
-                    [
-                        max(min(upper, 1), 0) - max(min(lower, 1), 0)
-                        for (upper, lower) in c_ranges
-                    ]
-                )
+                n_specie_c_range = np.average([len(j) for j in indices_c_range])
+                vol_c_range = np.sum([max(min(upper, 1), 0) - max(min(lower, 1), 0) for (upper, lower) in c_ranges])
                 n_density_c_range = n_specie_c_range / vol_c_range
                 conv_factor_c_range = conv_factor / len(indices) * n_density_c_range
 
-                self.conductivity_c_range = (
-                    self.diffusivity_c_range * conv_factor_c_range
-                )
-                self.conductivity_c_range_std_dev = (
-                    self.diffusivity_c_range_std_dev * conv_factor_c_range
-                )
-                self.conductivity_c_range_components = (
-                    self.diffusivity_c_range_components * conv_factor_c_range
-                )
+                self.conductivity_c_range = self.diffusivity_c_range * conv_factor_c_range
+                self.conductivity_c_range_std_dev = self.diffusivity_c_range_std_dev * conv_factor_c_range
+                self.conductivity_c_range_components = self.diffusivity_c_range_components * conv_factor_c_range
                 self.conductivity_c_range_components_std_dev = (
                     self.diffusivity_c_range_components_std_dev * conv_factor_c_range
                 )
@@ -456,9 +418,7 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
    self.drift = drift
             self.corrected_displacements = dc
             self.max_ion_displacements = np.max(np.sum(dc**2, axis=-1) ** 0.5, axis=1)
-            self.max_framework_displacement = np.max(
-                self.max_ion_displacements[framework_indices]
-            )
+            self.max_framework_displacement = np.max(self.max_ion_displacements[framework_indices])
             self.msd = msd
             self.mscd = mscd
             self.haven_ratio = self.diffusivity / self.chg_diffusivity
@@ -468,14 +428,18 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
    self.indices = indices
             self.framework_indices = framework_indices
 
-
    [docs]    def get_drift_corrected_structures(self, start=None, stop=None, step=None):
+
    
+[docs]
+    def get_drift_corrected_structures(self, start=None, stop=None, step=None):
         """
         Returns an iterator for the drift-corrected structures. Use of
         iterator is to reduce memory usage as # of structures in MD can be
         huge. You don't often need all the structures all at once.
 
         Args:
-            start, stop, step (int): applies a start/stop/step to the iterator.
+            start(int): Applies a start to the iterator.
+            stop (int): Applies a stop to the iterator.
+            step (int): Applies a step to the iterator.
                 Faster than applying it after generation, as it reduces the
                 number of structures created.
         """
@@ -493,14 +457,17 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
    coords_are_cartesian=True,
             )
    
 
-
    [docs]    def get_summary_dict(self, include_msd_t=False, include_mscd_t=False):
+
+
    
+[docs]
+    def get_summary_dict(self, include_msd_t=False, include_mscd_t=False):
         """
         Provides a summary of diffusion information.
 
         Args:
             include_msd_t (bool): Whether to include mean square displace and
                 time data with the data.
-            include_msd_t (bool): Whether to include mean square charge displace and
+            include_mscd_t (bool): Whether to include mean square charge displace and
                 time data with the data.
 
         Returns:
@@ -533,7 +500,10 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
    d["mscd"] = self.mscd.tolist()
         return d
    
 
-
    [docs]    def get_framework_rms_plot(self, plt=None, granularity=200, matching_s=None):
+
+
    
+[docs]
+    def get_framework_rms_plot(self, granularity=200, matching_s=None):
         """
         Get the plot of rms framework displacement vs time. Useful for checking
         for melting, especially if framework atoms can move via paddle-wheel
@@ -541,23 +511,20 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
            but doesn't constitute melting).
 
         Args:
-            plt (matplotlib.pyplot): If plt is supplied, changes will be made
-                to an existing plot. Otherwise, a new plot will be created.
             granularity (int): Number of structures to match
             matching_s (Structure): Optionally match to a disordered structure
                 instead of the first structure in the analyzer. Required when
                 a secondary mobile ion is present.
+
         Notes:
             The method doesn't apply to NPT-AIMD simulation analysis.
         """
         from pymatgen.util.plotting import pretty_plot
 
         if self.lattices is not None and len(self.lattices) > 1:
-            warnings.warn(
-                "Note the method doesn't apply to NPT-AIMD simulation analysis!"
-            )
+            warnings.warn("Note the method doesn't apply to NPT-AIMD simulation analysis!")
 
-        plt = pretty_plot(12, 8, plt=plt)
+        plt = pretty_plot(12, 8)
         step = (self.corrected_displacements.shape[1] - 1) // (granularity - 1)
         f = (matching_s or self.structure).copy()
         f.remove_species([self.specie])
@@ -586,12 +553,15 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
    plt.plot(plot_dt, rms[:, 0], label="RMS")
         plt.plot(plot_dt, rms[:, 1], label="max")
         plt.legend(loc="best")
-        plt.xlabel(f"Timestep ({unit})")
-        plt.ylabel("normalized distance")
+        plt.set_xlabel(f"Timestep ({unit})")
+        plt.set_ylabel("normalized distance")
         plt.tight_layout()
         return plt
    
 
-
    [docs]    def get_msd_plot(self, plt=None, mode="specie"):
+
+
    
+[docs]
+    def get_msd_plot(self, mode="specie"):
         """
         Get the plot of the smoothed msd vs time graph. Useful for
         checking convergence. This can be written to an image file.
@@ -605,7 +575,7 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
            """
         from pymatgen.util.plotting import pretty_plot
 
-        plt = pretty_plot(12, 8, plt=plt)
+        plt = pretty_plot(12, 8)
         if np.max(self.dt) > 100000:
             plot_dt = self.dt / 1000
             unit = "ps"
@@ -615,9 +585,7 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
    if mode == "species":
             for sp in sorted(self.structure.composition.keys()):
-                indices = [
-                    i for i, site in enumerate(self.structure) if site.specie == sp
-                ]
+                indices = [i for i, site in enumerate(self.structure) if site.specie == sp]
                 sd = np.average(self.sq_disp_ions[indices, :], axis=0)
                 plt.plot(plot_dt, sd, label=str(sp))
             plt.legend(loc=2, prop={"size": 20})
@@ -637,15 +605,18 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
    plt.plot(plot_dt, self.msd_components[:, 2], "b")
             plt.legend(["Overall", "a", "b", "c"], loc=2, prop={"size": 20})
 
-        plt.xlabel(f"Timestep ({unit})")
+        plt.set_xlabel(f"Timestep ({unit})")
         if mode == "mscd":
-            plt.ylabel("MSCD ($\\AA^2$)")
+            plt.set_ylabel("MSCD ($\\AA^2$)")
         else:
-            plt.ylabel("MSD ($\\AA^2$)")
+            plt.set_ylabel("MSD ($\\AA^2$)")
         plt.tight_layout()
         return plt
    
 
-
    [docs]    def plot_msd(self, mode="default"):
+
+
    
+[docs]
+    def plot_msd(self, mode="default"):
         """
         Plot the smoothed msd vs time graph. Useful for checking convergence.
 
@@ -658,7 +629,10 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
            """
         self.get_msd_plot(mode=mode).show()
    
 
-
    [docs]    def export_msdt(self, filename):
+
+
    
+[docs]
+    def export_msdt(self, filename):
         """
         Writes MSD data to a csv file that can be easily plotted in other
         software.
@@ -675,13 +649,14 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
    f.write("# ")
             f.write(delimiter.join(["t", "MSD", "MSD_a", "MSD_b", "MSD_c", "MSCD"]))
             f.write("\n")
-            for dt, msd, msdc, mscd in zip(
-                self.dt, self.msd, self.msd_components, self.mscd
-            ):
+            for dt, msd, msdc, mscd in zip(self.dt, self.msd, self.msd_components, self.mscd):
                 f.write(delimiter.join([str(v) for v in [dt, msd, *list(msdc), mscd]]))
                 f.write("\n")
    
 
-
    [docs]    @classmethod
+
+
    
+[docs]
+    @classmethod
     def from_structures(
         cls,
         structures,
@@ -718,21 +693,20 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
                    typically need to supply both variables. This stipulates the
                 initial structure from which the current set of displacements
                 are computed.
-            \\*\\*kwargs: kwargs supported by the :class:`DiffusionAnalyzer`_.
+            **kwargs: kwargs supported by the :class:`DiffusionAnalyzer`_.
                 Examples include smoothed, min_obs, avg_nsteps.
         """
-        p, l = [], []
-        for i, s in enumerate(structures):
-            if i == 0:
-                structure = s
+        p, lattices = [], []
+        structure = structures[0]
+        for s in structures:
             p.append(np.array(s.frac_coords)[:, None])
-            l.append(s.lattice.matrix)
+            lattices.append(s.lattice.matrix)
         if initial_structure is not None:
             p.insert(0, np.array(initial_structure.frac_coords)[:, None])
-            l.insert(0, initial_structure.lattice.matrix)
+            lattices.insert(0, initial_structure.lattice.matrix)
         else:
             p.insert(0, p[0])
-            l.insert(0, l[0])
+            lattices.insert(0, lattices[0])
 
         p = np.concatenate(p, axis=1)
         dp = p[:, 1:] - p[:, :-1]
@@ -740,11 +714,11 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
    f_disp = np.cumsum(dp, axis=1)
         c_disp = []
         for i in f_disp:
-            c_disp.append([np.dot(d, m) for d, m in zip(i, l[1:])])
+            c_disp.append([np.dot(d, m) for d, m in zip(i, lattices[1:])])
         disp = np.array(c_disp)
 
         # If is NVT-AIMD, clear lattice data.
-        l = np.array([l[0]]) if np.array_equal(l[0], l[-1]) else np.array(l)
+        lattices = np.array([lattices[0]]) if np.array_equal(lattices[0], lattices[-1]) else np.array(lattices)
         if initial_disp is not None:
             disp += initial_disp[:, None, :]
 
@@ -755,14 +729,15 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
    temperature,
             time_step,
             step_skip=step_skip,
-            lattices=l,
+            lattices=lattices,
             **kwargs,
         )
    
 
-
    [docs]    @classmethod
-    def from_vaspruns(
-        cls, vaspruns, specie, initial_disp=None, initial_structure=None, **kwargs
-    ):
+
+
    
+[docs]
+    @classmethod
+    def from_vaspruns(cls, vaspruns, specie, initial_disp=None, initial_structure=None, **kwargs):
         r"""
         Convenient constructor that takes in a list of Vasprun objects to
         perform diffusion analysis.
@@ -783,22 +758,20 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
                    typically need to supply both variables. This stipulates the
                 initial stricture from which the current set of displacements
                 are computed.
-            \\*\\*kwargs: kwargs supported by the :class:`DiffusionAnalyzer`_.
+            **kwargs: kwargs supported by the :class:`DiffusionAnalyzer`_.
                 Examples include smoothed, min_obs, avg_nsteps.
         """
 
         def get_structures(vaspruns):
+            step_skip = vaspruns[0].ionic_step_skip or 1
+            final_structure = vaspruns[0].initial_structure
+            temperature = vaspruns[0].parameters["TEEND"]
+            time_step = vaspruns[0].parameters["POTIM"]
             for i, vr in enumerate(vaspruns):
                 if i == 0:
-                    step_skip = vr.ionic_step_skip or 1
-                    final_structure = vr.initial_structure
-                    temperature = vr.parameters["TEEND"]
-                    time_step = vr.parameters["POTIM"]
                     yield step_skip, temperature, time_step
                 # check that the runs are continuous
-                fdist = pbc_diff(
-                    vr.initial_structure.frac_coords, final_structure.frac_coords
-                )
+                fdist = pbc_diff(vr.initial_structure.frac_coords, final_structure.frac_coords)
                 if np.any(fdist > 0.001):
                     raise ValueError("initial and final structures do not match.")
                 final_structure = vr.final_structure
@@ -821,7 +794,10 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
    **kwargs,
         )
    
 
-
    [docs]    @classmethod
+
+
    
+[docs]
+    @classmethod
     def from_files(
         cls,
         filepaths,
@@ -864,7 +840,7 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
                    typically need to supply both variables. This stipulates the
                 initial structure from which the current set of displacements
                 are computed.
-            \\*\\*kwargs: kwargs supported by the :class:`DiffusionAnalyzer`_.
+            **kwargs: kwargs supported by the :class:`DiffusionAnalyzer`_.
                 Examples include smoothed, min_obs, avg_nsteps.
         """
         if ncores is not None and len(filepaths) > 1:
@@ -894,10 +870,11 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
    **kwargs,
         )
    
 
-
    [docs]    def as_dict(self):
-        """
-        Returns: MSONable dict
-        """
+
+
    
+[docs]
+    def as_dict(self):
+        """Returns: MSONable dict."""
         return {
             "@module": self.__class__.__module__,
             "@class": self.__class__.__name__,
@@ -913,11 +890,14 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
    "lattices": self.lattices.tolist(),
         }
    
 
-
    [docs]    @classmethod
+
+
    
+[docs]
+    @classmethod
     def from_dict(cls, d):
         """
         Args:
-            d (dict): Dict representation
+            d (dict): Dict representation.
 
         Returns: DiffusionAnalyzer
         """
@@ -933,10 +913,14 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
    smoothed=d.get("smoothed", "max"),
             avg_nsteps=d.get("avg_nsteps", 1000),
             lattices=np.array(d.get("lattices", [d["structure"]["lattice"]["matrix"]])),
-        )
    
+        )
    
+
    
+
 
 
-
    [docs]def get_conversion_factor(structure, species, temperature):
+
    
+[docs]
+def get_conversion_factor(structure, species, temperature):
     """
     Conversion factor to convert between cm^2/s diffusivity measurements and
     mS/cm conductivity measurements based on number of atoms of diffusing
@@ -954,36 +938,26 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
            Conductivity (in mS/cm) = Conversion Factor * Diffusivity (in cm^2/s)
     """
     df_sp = get_el_sp(species)
-    z = (
-        df_sp.oxi_state
-        if hasattr(df_sp, "oxi_state")
-        else df_sp.full_electronic_structure[-1][2]
-    )
+    z = df_sp.oxi_state if hasattr(df_sp, "oxi_state") else df_sp.full_electronic_structure[-1][2]
 
     n = structure.composition[species]
 
     vol = structure.volume * 1e-24  # units cm^3
-    return (
-        1000
-        * n
-        / (vol * const.N_A)
-        * z**2
-        * (const.N_A * const.e) ** 2
-        / (const.R * temperature)
-    )
    
+    return 1000 * n / (vol * const.N_A) * z**2 * (const.N_A * const.e) ** 2 / (const.R * temperature)
    
+
 
 
 def _get_vasprun(args):
-    """
-    Internal method to support multiprocessing.
-    """
+    """Internal method to support multiprocessing."""
     return Vasprun(args[0], ionic_step_skip=args[1], parse_dos=False, parse_eigen=False)
 
 
-
    [docs]def fit_arrhenius(temps, diffusivities):
+
    
+[docs]
+def fit_arrhenius(temps, diffusivities):
     """
-    Returns Ea, c, standard error of Ea from the Arrhenius fit:
-        D = c * exp(-Ea/kT)
+    Returns Ea, c, standard error of Ea from the Arrhenius fit.
+        D = c * exp(-Ea/kT).
 
     Args:
         temps ([float]): A sequence of temperatures. units: K
@@ -997,17 +971,16 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
    w, res, _, _ = np.linalg.lstsq(a, logd, rcond=None)
     w = np.array(w)
     n = len(temps)
-    std_Ea = (
-        (res[0] / (n - 2) / (n * np.var(t_1))) ** 0.5 * const.k / const.e
-        if n > 2
-        else None
-    )
+    std_Ea = (res[0] / (n - 2) / (n * np.var(t_1))) ** 0.5 * const.k / const.e if n > 2 else None
     return -w[0] * const.k / const.e, np.exp(w[1]), std_Ea
    
 
 
-
    [docs]def get_diffusivity_from_msd(msd, dt, smoothed="max"):
+
+
    
+[docs]
+def get_diffusivity_from_msd(msd, dt, smoothed="max"):
     """
-    Returns diffusivity and standard deviation of diffusivity given by:
+    Returns diffusivity and standard deviation of diffusivity.
 
         D = 1 / 2dt * <mean square displacement>
 
@@ -1021,17 +994,17 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
            msd ([float]): A sequence of mean square displacements. units: Å^2
         dt ([float]): A sequence of time steps corresponding to MSD. units: fs
         smoothed (str): Whether to smooth the MSD, and what mode to smooth.
-                Supported modes are:
-
-                i. "max", which tries to use the maximum #
-                   of data points for each time origin, subject to a
-                   minimum # of observations given by min_obs, and then
-                   weights the observations based on the variance
-                   accordingly. This is the default.
-                ii. "constant", in which each timestep is averaged over
-                    the number of time_steps given by min_steps.
-                iii. None / False / any other false-like quantity. No
-                   smoothing.
+            Supported modes are::
+
+            i. "max", which tries to use the maximum #
+               of data points for each time origin, subject to a
+               minimum # of observations given by min_obs, and then
+               weights the observations based on the variance
+               accordingly. This is the default.
+            ii. "constant", in which each timestep is averaged over
+                the number of time_steps given by min_steps.
+            iii. None / False / any other false-like quantity. No
+               smoothing.
     """
 
     def weighted_lstsq(a, b):
@@ -1066,9 +1039,12 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
    return diffusivity, diffusivity_std_dev
    
 
 
-
    [docs]def get_extrapolated_diffusivity(temps, diffusivities, new_temp):
+
+
    
+[docs]
+def get_extrapolated_diffusivity(temps, diffusivities, new_temp):
     """
-    Returns (Arrhenius) extrapolated diffusivity at new_temp
+    Returns (Arrhenius) extrapolated diffusivity at new_temp.
 
     Args:
         temps ([float]): A sequence of temperatures. units: K
@@ -1083,7 +1059,10 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
    return c * np.exp(-Ea / (const.k / const.e * new_temp))
    
 
 
-
    [docs]def get_extrapolated_conductivity(temps, diffusivities, new_temp, structure, species):
+
+
    
+[docs]
+def get_extrapolated_conductivity(temps, diffusivities, new_temp, structure, species):
     """
     Returns extrapolated mS/cm conductivity.
 
@@ -1098,12 +1077,15 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
        Returns:
         (float) Conductivity at extrapolated temp in mS/cm.
     """
-    return get_extrapolated_diffusivity(
-        temps, diffusivities, new_temp
-    ) * get_conversion_factor(structure, species, new_temp)
    
+    return get_extrapolated_diffusivity(temps, diffusivities, new_temp) * get_conversion_factor(
+        structure, species, new_temp
+    )
    
 
 
-
    [docs]def get_arrhenius_plot(temps, diffusivities, diffusivity_errors=None, **kwargs):
+
+
    
+[docs]
+def get_arrhenius_plot(temps, diffusivities, diffusivity_errors=None, **kwargs):
     r"""
     Returns an Arrhenius plot.
 
@@ -1113,7 +1095,7 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
                from DiffusionAnalyzer.diffusivity).
         diffusivity_errors ([float]): A sequence of errors for the
             diffusivities. If None, no error bar is plotted.
-        \\*\\*kwargs:
+        **kwargs:
             Any keyword args supported by matplotlib.pyplot.plot.
 
     Returns:
@@ -1151,10 +1133,11 @@ 
    Source code for pymatgen.analysis.diffusion.analyzer
    fontsize=30,
         transform=plt.axes().transAxes,
     )
-    plt.ylabel("D (cm$^2$/s)")
-    plt.xlabel("1000/T (K$^{-1}$)")
+    plt.set_ylabel("D (cm$^2$/s)")
+    plt.set_xlabel("1000/T (K$^{-1}$)")
     plt.tight_layout()
     return plt
    
+
    @@ -1169,7 +1152,7 @@

    Source code for pymatgen.analysis.diffusion.analyzer

    +
    diff --git a/docs/_modules/pymatgen/analysis/diffusion/neb/full_path_mapper.html b/docs/_modules/pymatgen/analysis/diffusion/neb/full_path_mapper.html index d73603f..7ad2d64 100644 --- a/docs/_modules/pymatgen/analysis/diffusion/neb/full_path_mapper.html +++ b/docs/_modules/pymatgen/analysis/diffusion/neb/full_path_mapper.html @@ -1,15 +1,15 @@ - + - pymatgen.analysis.diffusion.neb.full_path_mapper — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.neb.full_path_mapper — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -34,7 +34,7 @@

    Navigation

  • modules |
    • -
  • pymatgen-diffusion 2023.8.15 documentation »
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  • pymatgen-diffusion 2024.6.10 documentation »
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  • pymatgen.analysis.diffusion.neb.full_path_mapper
    • @@ -46,11 +46,8 @@

    Navigation

    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper

    -# Copyright (c) Materials Virtual Lab.
-# Distributed under the terms of the BSD License.
-"""
-Migraiton Graph Analysis
-"""
+"""Migration Graph Analysis."""
+
 from __future__ import annotations
 
 __author__ = "Jimmy Shen"
@@ -69,15 +66,8 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    import numpy as np
 from monty.json import MSONable
 
-from pymatgen.analysis.diffusion.neb.pathfinder import (
-    ChgcarPotential,
-    MigrationHop,
-    NEBPathfinder,
-)
-from pymatgen.analysis.diffusion.neb.periodic_dijkstra import (
-    get_optimal_pathway_rev,
-    periodic_dijkstra,
-)
+from pymatgen.analysis.diffusion.neb.pathfinder import ChgcarPotential, MigrationHop, NEBPathfinder
+from pymatgen.analysis.diffusion.neb.periodic_dijkstra import get_optimal_pathway_rev, periodic_dijkstra
 from pymatgen.analysis.diffusion.utils.parse_entries import process_entries
 from pymatgen.analysis.graphs import StructureGraph
 from pymatgen.analysis.local_env import MinimumDistanceNN, NearNeighbors
@@ -92,9 +82,12 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    logger = logging.getLogger(__name__)
 
 
-
    [docs]def generic_groupby(list_in: list, comp: Callable = operator.eq):
+
    
+[docs]
+def generic_groupby(list_in: list, comp: Callable = operator.eq):
     """
-    Group a list of unsortable objects
+    Group a list of unsortable objects.
+
     Args:
         list_in: A list of generic objects
         comp: (Default value = operator.eq) The comparator
@@ -118,7 +111,10 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    return list_out
    
 
 
-
    [docs]class MigrationGraph(MSONable):
+
+
    
+[docs]
+class MigrationGraph(MSONable):
     """
     A python object for handling the migratrion graph of a given base
     structure and mobile specie sites within that base structure.
@@ -141,6 +137,7 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
            connecting all sites as specified by the migration graph.
         The sites are decorated with Migration graph objects and then grouped
         together based on their equivalence.
+
         Args:
             structure: Structure with base framework and mobile sites.
              When used with structure_is_base = True, only the base framework
@@ -166,22 +163,16 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    @property
     def only_sites(self) -> Structure:
-        """
-        A structure that only contains the migrating species
-        """
+        """A structure that only contains the migrating species."""
         return self.m_graph.structure
 
     @property
     def host_structure(self) -> Structure:
-        """
-        A structure that only contains the non-migrating species
-        """
+        """A structure that only contains the non-migrating species."""
         host_struct = self.structure.copy()
         rm_sites = set()
         for isite in self.only_sites:
-            neighbors_ = host_struct.get_neighbors_in_shell(
-                isite.coords, r=0.0, dr=0.05, include_index=True
-            )
+            neighbors_ = host_struct.get_neighbors_in_shell(isite.coords, r=0.0, dr=0.05, include_index=True)
             if len(neighbors_) == 0:
                 continue
             for n_ in neighbors_:
@@ -191,9 +182,7 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    @property
     def symm_structure(self) -> SymmetrizedStructure:
-        """
-        The symmetrized structure with the present item's symprec value
-        """
+        """The symmetrized structure with the present item's symprec value."""
         a = SpacegroupAnalyzer(self.structure, symprec=self.symprec)
         sym_struct = a.get_symmetrized_structure()
         if not isinstance(sym_struct, SymmetrizedStructure):
@@ -202,9 +191,7 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    @property
     def unique_hops(self):
-        """
-        The unique hops dictionary keyed by the hop label
-        """
+        """The unique hops dictionary keyed by the hop label."""
         # reversed so that the first instance represents the group of distinct hops
         ihop_data = list(reversed(list(self.m_graph.graph.edges(data=True))))
         for u, v, d in ihop_data:
@@ -213,14 +200,16 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    d["hop_distance"] = d["hop"].length
         return {d["hop_label"]: d for u, v, d in ihop_data}
 
-
    [docs]    @classmethod
-    def with_base_structure(
-        cls, base_structure: Structure, m_graph: StructureGraph, **kwargs
-    ) -> MigrationGraph:
+
    
+[docs]
+    @classmethod
+    def with_base_structure(cls, base_structure: Structure, m_graph: StructureGraph, **kwargs) -> MigrationGraph:
         """
         Args:
-            base_structure: base framework structure that does not contain any
-             migrating sites.
+            base_structure: base framework structure that does not contain any migrating sites.
+            m_graph: The StructureGraph object that defines the migration network.
+            **kwargs: Passthrough for kwargs.
+
         Returns:
             A constructed MigrationGraph object
         """
@@ -228,16 +217,22 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    structure = Structure.from_sites(sites)
         return cls(structure=structure, m_graph=m_graph, **kwargs)
    
 
-
    [docs]    @classmethod
+
+
    
+[docs]
+    @classmethod
     def with_local_env_strategy(
         cls, structure: Structure, migrating_specie: str, nn: NearNeighbors, **kwargs
     ) -> MigrationGraph:
         """
         Using a specific nn strategy to get the connectivity graph between all the migrating ion sites.
+
         Args:
             structure: Input structure that contains all sites.
             migrating_specie: The specie that migrates. E.g. "Li".
             nn: The specific local environment object used to connect the migrating ion sites.
+            **kwargs: Passthrough for kwargs.
+
         Returns:
             A constructed MigrationGraph object
         """
@@ -245,16 +240,24 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    migration_graph = StructureGraph.with_local_env_strategy(only_sites, nn)
         return cls(structure=structure, m_graph=migration_graph, **kwargs)
    
 
-
    [docs]    @classmethod
+
+
    
+[docs]
+    @classmethod
     def with_distance(
         cls, structure: Structure, migrating_specie: str, max_distance: float, **kwargs
     ) -> MigrationGraph:
         """
         Using a specific nn strategy to get the connectivity graph between all the migrating ion sites.
+
         Args:
+            structure: Input structure that contains all sites.
+            migrating_specie: The specie that migrates. E.g. "Li".
             max_distance: Maximum length of NEB path in the unit
                 of Angstrom. Defaults to None, which means you are setting the
                 value to the min cutoff until finding 1D or >1D percolating paths.
+            **kwargs: Passthrough for kwargs.
+
         Returns:
             A constructed MigrationGraph object
         """
@@ -265,7 +268,10 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    )
         return cls(structure=structure, m_graph=migration_graph, **kwargs)
    
 
-
    [docs]    @staticmethod
+
+
    
+[docs]
+    @staticmethod
     def get_structure_from_entries(
         entries: list[ComputedStructureEntry],
         migrating_ion_entry: ComputedEntry,
@@ -278,12 +284,13 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
            Args:
             entries: list of entries, must contain a mixture of inserted and empty structures.
             migrating_ion_entry: The metallic phase of the working ion, used to calculate insertion energies.
+            **kwargs: Passthrough for kwargs.
 
         Additional Kwargs:
             symprec:  symmetry parameter for SpacegroupAnalyzer
             ltol: Fractional length tolerance for StructureMatcher
             stol: Site tolerance for StructureMatcher
-            angle_tol: Angle tolerance fro StructureMatcher and SpacegroupAnalyzer
+            angle_tol: Angle tolerance for StructureMatcher and SpacegroupAnalyzer
             only_single_cat: If True, only use single cation insertions so the
             site energy is more accurate use_strict_tol: halve the ltol and
             stol parameter for more strict matching.
@@ -339,13 +346,14 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    res.append(struct)
         return res
    
 
+
     def _get_pos_and_migration_hop(self, u, v, w):
         """
         insert a single MigrationHop object on a graph edge
         Args:
           u (int): index of initial node
           v (int): index of final node
-          w (int): index for multiple edges that share the same two nodes
+          w (int): index for multiple edges that share the same two nodes.
         """
         edge = self.m_graph.graph[u][v][w]
         i_site = self.only_sites.sites[u]
@@ -360,30 +368,23 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    edge["ipos_cart"] = np.dot(i_site.frac_coords, self.only_sites.lattice.matrix)
         edge["epos_cart"] = np.dot(e_site.frac_coords, self.only_sites.lattice.matrix)
 
-        edge["hop"] = MigrationHop(
-            i_site, e_site, self.symm_structure, symprec=self.symprec
-        )
+        edge["hop"] = MigrationHop(i_site, e_site, self.symm_structure, symprec=self.symprec)
 
     def _populate_edges_with_migration_hops(self):
-        """
-        Populate the edges with the data for the Migration Paths
-        """
+        """Populate the edges with the data for the Migration Paths."""
         list(starmap(self._get_pos_and_migration_hop, self.m_graph.graph.edges))
 
     def _group_and_label_hops(self):
-        """
-        Group the MigrationHop objects together and label all the symmetrically equlivaelnt hops with the same label
-        """
+        """Group the MigrationHop objects together and label all the symmetrically equlivaelnt hops with the same label."""
         hops = list(nx.get_edge_attributes(self.m_graph.graph, "hop").items())
         labs = generic_groupby(hops, comp=lambda x, y: x[1] == y[1])
-        new_attr = {
-            g_index: {"hop_label": labs[edge_index]}
-            for edge_index, (g_index, _) in enumerate(hops)
-        }
+        new_attr = {g_index: {"hop_label": labs[edge_index]} for edge_index, (g_index, _) in enumerate(hops)}
         nx.set_edge_attributes(self.m_graph.graph, new_attr)
         return new_attr
 
-
    [docs]    def add_data_to_similar_edges(
+
    
+[docs]
+    def add_data_to_similar_edges(
         self,
         target_label: int | str,
         data: dict,
@@ -395,61 +396,63 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
                target_label: The edge uniqueness label are adding data
             data: The data to passed to the different edges
             m_hop: If the data is an array, and m_hop is set, it uses the reference migration path to
-            determine whether the data needs to be flipped so that 0-->1 is different from 1-->0
+            determine whether the data needs to be flipped so that 0-->1 is different from 1-->0.
         """
-
         for _u, _v, d in self.m_graph.graph.edges(data=True):
             if d["hop_label"] == target_label:
                 d.update(data)
-                if m_hop is not None:
-                    # Try to override the data.
-                    if not m_hop.symm_structure.spacegroup.are_symmetrically_equivalent(
-                        [m_hop.isite], [d["hop"].isite]
-                    ):
-                        # "The data going to this edge needs to be flipped"
-                        for k in data:
-                            if isinstance(data[k], (np.ndarray, np.generic)):
-                                raise Warning(
-                                    "The data provided will only be flipped "
-                                    "if it a list"
-                                )
-                            if not isinstance(data[k], list):
-                                continue
-                            d[k] = d[k][::-1]  # flip the data in the array
    
-
-
    [docs]    def assign_cost_to_graph(self, cost_keys=["hop_distance"]):
+                # Try to override the data.
+                if m_hop is not None and not m_hop.symm_structure.spacegroup.are_symmetrically_equivalent(
+                    [m_hop.isite], [d["hop"].isite]
+                ):
+                    # "The data going to this edge needs to be flipped"
+                    for k in data:
+                        if isinstance(data[k], (np.ndarray, np.generic)):
+                            raise Warning("The data provided will only be flipped if it a list")
+                        if not isinstance(data[k], list):
+                            continue
+                        d[k] = d[k][::-1]  # flip the data in the array
    
+
+
+
    
+[docs]
+    def assign_cost_to_graph(self, cost_keys=None):
         """
         Read the data dict on each add and populate a cost key
         Args:
             cost_keys: a list of keys for data on each edge.
-                The SC Graph is decorated with a "cost" key that is the product of the different keys here
+                The SC Graph is decorated with a "cost" key that is the product of the different keys here.
         """
+        if cost_keys is None:
+            cost_keys = ["hop_distance"]
         for k, v in self.unique_hops.items():
             cost_val = np.prod([v[ik] for ik in cost_keys])
             self.add_data_to_similar_edges(k, {"cost": cost_val})
    
 
-
    [docs]    def get_path(self, max_val=100000, flip_hops=True):
+
+
    
+[docs]
+    def get_path(self, max_val=100000, flip_hops=True):
         """
         obtain a pathway through the material using hops that are in the current graph
         Basic idea:
             Get an endpoint p1 in the graph that is outside the current unit cell
             Ask the graph for a pathway that connects to p1 from either within the (0,0,0) cell
             or any other neighboring UC not containing p1.
+
         Args:
             max_val: Filter the graph by a cost
             flip_hops: If true, hops in paths returned will be flipped so
                 isites and esites match to form a coherent path.
                 If false, hops will retain their original orientation
                 from the migration graph.
+
         Returns:
             Generator for list of Dicts:
             Each dict contains the information of a hop
         """
-
         if len(self.unique_hops) != len(self.unique_hops):
-            logger.error(
-                f"There are {len(self.unique_hops)} SC hops but {len(self.unique_hops)} UC hops in {self}"
-            )
+            logger.error(f"There are {len(self.unique_hops)} SC hops but {len(self.unique_hops)} UC hops in {self}")
 
         # for u, v, k, d in self.m_graph.graph.edges(data=True, keys=True):
         for u in self.m_graph.graph.nodes():
@@ -463,9 +466,7 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    for tmp_u, tmp_v, tmp_k in cut_edges:
                 path_graph.remove_edge(tmp_u, tmp_v, key=tmp_k)
             # populate the entire graph with multiple images
-            best_ans, path_parent = periodic_dijkstra(
-                path_graph, sources={u}, weight="cost", max_image=2
-            )
+            best_ans, path_parent = periodic_dijkstra(path_graph, sources={u}, weight="cost", max_image=2)
             # find a way to a u site that is not in the (0,0,0) image
             all_paths = []
             for idx, jimage in path_parent:
@@ -488,9 +489,7 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    # displacement +/- (jimage1 - jimage2) is present on of of the edges
                 # Note: there should only ever be one valid to_jimage for a u->v pair
                 i1_, i2_ = sorted((idx1, idx2))
-                all_edge_data = [
-                    *path_graph.get_edge_data(i1_, i2_, default={}).items()
-                ]
+                all_edge_data = [*path_graph.get_edge_data(i1_, i2_, default={}).items()]
                 image_diff = np.subtract(jimage2, jimage1)
                 found_ = 0
                 for _k, tmp_d in all_edge_data:
@@ -504,9 +503,18 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    else:
                 yield u, path_hops
    
 
-
    [docs]    def get_summary_dict(self, added_keys: list[str] | None = None) -> dict:
+
+
    
+[docs]
+    def get_summary_dict(self, added_keys: list[str] | None = None) -> dict:
         """
-        Dictionary format, for saving to database
+        Dictionary format, for saving to database.
+
+        Args:
+            added_keys: a list of keys for data on each edge.
+
+        Returns:
+            Dict.
         """
         hops = []
         keys = ["hop_label", "to_jimage", "ipos", "epos", "ipos_cart", "epos_cart"]
@@ -525,8 +533,8 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    unique_hops = []
         for d in self.unique_hops.values():
-            new_hop["iindex"] = d["iindex"]
-            new_hop["eindex"] = d["eindex"]
+            new_hop["iindex"] = d["iindex"]  # type: ignore
+            new_hop["eindex"] = d["eindex"]  # type: ignore
             unique_hops.append(get_keys(d))
 
         unique_hops = sorted(unique_hops, key=lambda x: x["hop_label"])
@@ -537,13 +545,15 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    migrating_specie=list(self.only_sites.composition.as_dict().keys()),
             hops=hops,
             unique_hops=unique_hops,
-        )
    
+        )
    
+
    
 
 
-
    [docs]class ChargeBarrierGraph(MigrationGraph):
-    """
-    A Migration graph with additional charge density analysis on the charge density of the host material
-    """
+
+
    
+[docs]
+class ChargeBarrierGraph(MigrationGraph):
+    """A Migration graph with additional charge density analysis on the charge density of the host material."""
 
     def __init__(
         self,
@@ -555,13 +565,15 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    ):
         """
         Construct the MigrationGraph object using a VolumetricData object.
-        The graph is constructure using the structure, and cost values are assigned based on charge density analysis.
+        The graph is constructed using the structure, and cost values are assigned based on charge density analysis.
+
         Args:
+            structure (Structure): Input structure.
+            m_graph (StructureGraph): Input structure graph.
             potential_field: Input VolumetricData object that describes the field does
                 not have to contains all the metastable sites.
-            migrating_specie (Specie-like): The specie that migrates. E.g.,
-                "Li".
-            symprec (float): Symmetry precision to determine equivalence.
+            potential_data_key (str): Key for potential data.
+            **kwargs: Passthru for kwargs.
         """
         self.potential_field = potential_field
         self.potential_data_key = potential_data_key
@@ -569,18 +581,11 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    self._setup_grids()
 
     def _setup_grids(self):
-        """Populate the internal varialbes used for defining the grid points in the charge density analysis"""
-
+        """Populate the internal variables used for defining the grid points in the charge density analysis."""
         # set up the grid
-        aa = np.linspace(
-            0, 1, len(self.potential_field.get_axis_grid(0)), endpoint=False
-        )
-        bb = np.linspace(
-            0, 1, len(self.potential_field.get_axis_grid(1)), endpoint=False
-        )
-        cc = np.linspace(
-            0, 1, len(self.potential_field.get_axis_grid(2)), endpoint=False
-        )
+        aa = np.linspace(0, 1, len(self.potential_field.get_axis_grid(0)), endpoint=False)
+        bb = np.linspace(0, 1, len(self.potential_field.get_axis_grid(1)), endpoint=False)
+        cc = np.linspace(0, 1, len(self.potential_field.get_axis_grid(2)), endpoint=False)
         # move the grid points to the center
         aa, bb, dd = map(_shift_grid, [aa, bb, cc])
 
@@ -599,20 +604,14 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    def _dist_mat(self, pos_frac):
         # return a matrix that contains the distances to pos_frac
-        aa = np.linspace(
-            0, 1, len(self.potential_field.get_axis_grid(0)), endpoint=False
-        )
-        bb = np.linspace(
-            0, 1, len(self.potential_field.get_axis_grid(1)), endpoint=False
-        )
-        cc = np.linspace(
-            0, 1, len(self.potential_field.get_axis_grid(2)), endpoint=False
-        )
+        aa = np.linspace(0, 1, len(self.potential_field.get_axis_grid(0)), endpoint=False)
+        bb = np.linspace(0, 1, len(self.potential_field.get_axis_grid(1)), endpoint=False)
+        cc = np.linspace(0, 1, len(self.potential_field.get_axis_grid(2)), endpoint=False)
         aa, bb, cc = map(_shift_grid, [aa, bb, cc])
         AA, BB, CC = np.meshgrid(aa, bb, cc, indexing="ij")
         dist_from_pos = self.potential_field.structure.lattice.get_all_distances(
-            fcoords1=np.vstack([AA.flatten(), BB.flatten(), CC.flatten()]).T,
-            fcoords2=pos_frac,
+            np.vstack([AA.flatten(), BB.flatten(), CC.flatten()]).T,
+            pos_frac,
         )
         return dist_from_pos.reshape(AA.shape)
 
@@ -627,15 +626,9 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    mid_struct = self.potential_field.structure.copy()
 
         # the moving ion is always inserted on the zero index
-        start_struct.insert(
-            0, migration_hop.isite.species_string, ipos, properties=dict(magmom=0)
-        )
-        end_struct.insert(
-            0, migration_hop.isite.species_string, epos, properties=dict(magmom=0)
-        )
-        mid_struct.insert(
-            0, migration_hop.isite.species_string, mpos, properties=dict(magmom=0)
-        )
+        start_struct.insert(0, migration_hop.isite.species_string, ipos, properties=dict(magmom=0))
+        end_struct.insert(0, migration_hop.isite.species_string, epos, properties=dict(magmom=0))
+        mid_struct.insert(0, migration_hop.isite.species_string, mpos, properties=dict(magmom=0))
 
         chgpot = ChgcarPotential(self.potential_field, normalize=False)
         return NEBPathfinder(
@@ -647,10 +640,8 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    mid_struct=mid_struct,
         )
 
-    def _get_avg_chg_at_max(
-        self, migration_hop, radius=None, chg_along_path=False, output_positions=False
-    ):
-        """obtain the maximum average charge along the path
+    def _get_avg_chg_at_max(self, migration_hop, radius=None, chg_along_path=False, output_positions=False):
+        """Obtain the maximum average charge along the path
         Args:
             migration_hop (MigrationHop): MigrationPath object that represents a given hop
             radius (float, optional): radius of sphere to perform the average.
@@ -661,12 +652,12 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
                output_positions (bool, optional): If True, also return the entire list of average
                     charges along the path for plotting.
                     Defaults to False.
+
         Returns:
             [float]: maximum of the charge density, (optional: entire list of charge density)
         """
-        if radius is None:
-            rr = self._tube_radius
-        if rr <= 0:
+        rr = radius or self._tube_radius
+        if rr <= 0:  # type: ignore
             raise ValueError("The integration radius must be positive.")
 
         npf = self._get_pathfinder_from_hop(migration_hop)
@@ -676,9 +667,7 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    for ict in centers:
             dist_mat = self._dist_mat(ict)
             mask = dist_mat < rr
-            vol_sphere = self.potential_field.structure.volume * (
-                mask.sum() / self.potential_field.ngridpts
-            )
+            vol_sphere = self.potential_field.structure.volume * (mask.sum() / self.potential_field.ngridpts)
             avg_chg.append(
                 np.sum(self.potential_field.data[self.potential_data_key] * mask)
                 / self.potential_field.ngridpts
@@ -695,17 +684,16 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
            Calculate the amount of charge that a migrating ion has to move through in order to complete a hop
         Args:
             migration_hop: MigrationHop object that represents a given hop
-            mask_file_seedname(string): seedname for output of the migration path masks (for debugging and
-                visualization) (Default value = None)
+            mask_file_seedname(string): seed name for output of the migration path masks (for debugging and
+                visualization) (Default value = None).
+
         Returns:
             float: The total charge density in a tube that connects two sites of a given edges of the graph
         """
         try:
-            self._tube_radius
+            _ = self._tube_radius
         except NameError:
-            logger.warning(
-                "The radius of the tubes for charge analysis need to be defined first."
-            )
+            logger.warning("The radius of the tubes for charge analysis need to be defined first.")
         ipos = migration_hop.isite.frac_coords
         epos = migration_hop.esite.frac_coords
 
@@ -713,15 +701,10 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    cart_epos = np.dot(epos, self.potential_field.structure.lattice.matrix)
         pbc_mask = np.zeros(self._uc_grid_shape, dtype=bool).flatten()
         for img in self._images:
-            grid_pos = np.dot(
-                self._fcoords + img, self.potential_field.structure.lattice.matrix
-            )
-            proj_on_line = np.dot(grid_pos - cart_ipos, cart_epos - cart_ipos) / (
-                np.linalg.norm(cart_epos - cart_ipos)
-            )
+            grid_pos = np.dot(self._fcoords + img, self.potential_field.structure.lattice.matrix)
+            proj_on_line = np.dot(grid_pos - cart_ipos, cart_epos - cart_ipos) / (np.linalg.norm(cart_epos - cart_ipos))
             dist_to_line = np.linalg.norm(
-                np.cross(grid_pos - cart_ipos, cart_epos - cart_ipos)
-                / (np.linalg.norm(cart_epos - cart_ipos)),
+                np.cross(grid_pos - cart_ipos, cart_epos - cart_ipos) / (np.linalg.norm(cart_epos - cart_ipos)),
                 axis=-1,
             )
 
@@ -753,7 +736,9 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    / self.potential_field.structure.volume
         )
 
-
    [docs]    def populate_edges_with_chg_density_info(self, tube_radius=1):
+
    
+[docs]
+    def populate_edges_with_chg_density_info(self, tube_radius=1):
         """
         Args:
             tube_radius: Tube radius.
@@ -769,8 +754,7 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    v["hop"], chg_along_path=True, output_positions=True
             )
             images = [
-                {"position": ifrac, "average_charge": ichg}
-                for ifrac, ichg in zip(frac_coords_list, avg_chg_list)
+                {"position": ifrac, "average_charge": ichg} for ifrac, ichg in zip(frac_coords_list, avg_chg_list)
             ]
             v.update(
                 dict(
@@ -781,11 +765,14 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    )
             self.add_data_to_similar_edges(k, {"max_avg_chg": max_chg})
    
 
-
    [docs]    def get_least_chg_path(self):
+
+
    
+[docs]
+    def get_least_chg_path(self):
         """
         obtain an intercolating pathway through the material that has the least amount of charge
         Returns:
-            list of hops
+            list of hops.
         """
         min_chg = 100000000
         min_path = []
@@ -799,22 +786,26 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    min_path = path
         return min_path
    
 
-
    [docs]    def get_summary_dict(self, add_keys: list[str] | None = None):
-        """
-        Dictionary format, for saving to database
-        """
+
+
    
+[docs]
+    def get_summary_dict(self, add_keys: list[str] | None = None):
+        """Dictionary format, for saving to database."""
         a_keys = ["max_avg_chg", "chg_total"]
         if add_keys is not None:
             a_keys += add_keys
-        return super().get_summary_dict(added_keys=a_keys)
    
+        return super().get_summary_dict(added_keys=a_keys)
    
+
    
+
 
 
 # Utility functions
-
    [docs]def get_only_sites_from_structure(
-    structure: Structure, migrating_specie: str
-) -> Structure:
+
    
+[docs]
+def get_only_sites_from_structure(structure: Structure, migrating_specie: str) -> Structure:
     """
     Get a copy of the structure with only the migrating sites.
+
     Args:
         structure: The full_structure that contains all the sites
         migrating_specie: The name of migrating species
@@ -830,35 +821,34 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    return Structure.from_sites(migrating_ion_sites)
    
 
 
+
 def _shift_grid(vv):
     """
     Move the grid points by half a step so that they sit in the center
     Args:
-        vv: equally space grid points in 1-D
+        vv: equally space grid points in 1-D.
     """
     step = vv[1] - vv[0]
     return vv + step / 2.0
 
 
-
    [docs]def get_hop_site_sequence(
-    hop_list: list[dict], start_u: int | str, key: str | None = None
-) -> list:
+
    
+[docs]
+def get_hop_site_sequence(hop_list: list[dict], start_u: int | str, key: str | None = None) -> list:
     """
     Read in a list of hop dictionaries and print the sequence of sites (and relevant property values if any).
+
     Args:
         hop_list: a list of the data on a sequence of hops
         start_u: the site index of the starting sites
         key (optional): property to track in a hop (e.g.: "hop_distance")
+
     Returns:
         String representation of the hop sequence (and property values if any)
     """
     hops = iter(hop_list)
     ihop = next(hops)
-    site_seq = (
-        [ihop["eindex"], ihop["iindex"]]
-        if ihop["eindex"] == start_u
-        else [ihop["iindex"], ihop["eindex"]]
-    )
+    site_seq = [ihop["eindex"], ihop["iindex"]] if ihop["eindex"] == start_u else [ihop["iindex"], ihop["eindex"]]
 
     for ihop in hops:
         if ihop["iindex"] == site_seq[-1]:
@@ -878,7 +868,10 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    return site_seq
    
 
 
-
    [docs]def order_path(hop_list: list[dict], start_u: int | str) -> list[dict]:
+
+
    
+[docs]
+def order_path(hop_list: list[dict], start_u: int | str) -> list[dict]:
     """
     Takes a list of hop dictionaries and flips hops (switches isite and esite)
     as needed to form a coherent path / sequence of sites according to
@@ -886,6 +879,7 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
        For example if hop_list = [{iindex:0, eindex:1, etc.}, {iindex:0, eindex:1, etc.}]
     then the output is [{iindex:0, eindex:1, etc.}, {iindex:1, eindex:0, etc.}] so that
     the following hop iindex matches the previous hop's eindex.
+
     Args:
         hop_list: a list of the data on a sequence of hops
         start_u: the site index of the starting sites
@@ -934,6 +928,7 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    return ordered_path
    
 
 
+
 """
 Note the current pathway algorithm no longer needs supercells but the following
 functions might still be useful for other applications
@@ -948,10 +943,10 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    # Utility Functions for comparing UC and SC hops
 
 
-
    [docs]def almost(a, b):
-    """
-    return true if the values are almost equal
-    """
+
    
+[docs]
+def almost(a, b):
+    """Return true if the values are almost equal."""
     SMALL_VAL = 1e-4
     try:
         return all(almost(i, j) for i, j in zip(list(a), list(b)))
@@ -961,18 +956,22 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    raise NotImplementedError
    
 
 
-
    [docs]def check_uc_hop(sc_hop, uc_hop):
+
+
    
+[docs]
+def check_uc_hop(sc_hop, uc_hop):
     """
     See if hop in the 2X2X2 supercell and a unit cell hop
-    are equilvalent under lattice translation
+    are equivalent under lattice translation.
+
     Args:
         sc_hop: MigrationHop object form pymatgen-diffusion.
         uc_hop: MigrationHop object form pymatgen-diffusion.
+
     Return:
-        image vector of lenght 3
+        image vector of length 3
         Is the UC hop flip of the SC hop
     """
-
     directions = np.array(
         [
             [0, 0, 0],
@@ -1006,12 +1005,17 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    return None
    
 
 
-
    [docs]def map_hop_sc2uc(sc_hop: MigrationHop, mg: MigrationGraph):
+
+
    
+[docs]
+def map_hop_sc2uc(sc_hop: MigrationHop, mg: MigrationGraph):
     """
     Map a given hop in the SC onto the UC.
+
     Args:
         sc_hop: MigrationHop object form pymatgen-diffusion.
         mg: MigrationGraph object from pymatgen-diffusion.
+
     Note:
         For now assume that the SC is exactly 2x2x2 of the UC.
         Can add in the parsing of different SC's later
@@ -1032,6 +1036,7 @@ 
    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper
    hop_label=d["hop_label"],
             )
     raise AssertionError("Looking for a SC hop without a matching UC hop")
    
+
    @@ -1046,7 +1051,7 @@

    Source code for pymatgen.analysis.diffusion.neb.full_path_mapper

    - +
    diff --git a/docs/_modules/pymatgen/analysis/diffusion/neb/io.html b/docs/_modules/pymatgen/analysis/diffusion/neb/io.html index 178a184..1a17fb4 100644 --- a/docs/_modules/pymatgen/analysis/diffusion/neb/io.html +++ b/docs/_modules/pymatgen/analysis/diffusion/neb/io.html @@ -1,15 +1,15 @@ - + - pymatgen.analysis.diffusion.neb.io — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.neb.io — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -34,7 +34,7 @@

    Navigation

  • modules |
    • -
  • pymatgen-diffusion 2023.8.15 documentation »
    • +
  • pymatgen-diffusion 2024.6.10 documentation »
  • Module code »
  • pymatgen.analysis.diffusion.neb.io
    • @@ -49,9 +49,8 @@

    Source code for pymatgen.analysis.diffusion.neb.io

    # Copyright (c) Materials Virtual Lab. # Distributed under the terms of the BSD License. -""" -Generate input fiels for NEB calculations. -""" +"""Generate input fields for NEB calculations.""" + from __future__ import annotations import copy @@ -62,16 +61,16 @@

    Source code for pymatgen.analysis.diffusion.neb.io

    __author__ = "Austen" -
    [docs]class MVLCINEBEndPointSet(MITRelaxSet): - """ - Class for writing NEB end points relaxation inputs. - """ +
    +[docs] +class MVLCINEBEndPointSet(MITRelaxSet): + """Class for writing NEB end points relaxation inputs.""" def __init__(self, structure, **kwargs): r""" Args: structure: Structure - \*\*kwargs: Keyword args supported by VaspInputSets. + **kwargs: Keyword args supported by VaspInputSets. """ user_incar_settings = kwargs.get("user_incar_settings", {}) defaults = { @@ -92,18 +91,21 @@

    Source code for pymatgen.analysis.diffusion.neb.io

    super().__init__(structure, **kwargs)
    -
    [docs]class MVLCINEBSet(MITNEBSet): + +
    +[docs] +class MVLCINEBSet(MITNEBSet): """ MAVRL-tested settings for CI-NEB calculations. Note that these parameters requires the VTST modification of VASP from the Henkelman group. See - http://theory.cm.utexas.edu/vtsttools/ + http://theory.cm.utexas.edu/vtsttools/. """ def __init__(self, structures, **kwargs): r""" Args: - structure: Structure - \*\*kwargs: Keyword args supported by VaspInputSets. + structures: Input structures. + **kwargs: Keyword args supported by VaspInputSets. """ user_incar_settings = kwargs.get("user_incar_settings", {}) @@ -133,7 +135,10 @@

    Source code for pymatgen.analysis.diffusion.neb.io

    super().__init__(structures, **kwargs)
    -
    [docs]def get_endpoints_from_index(structure, site_indices): + +
    +[docs] +def get_endpoints_from_index(structure, site_indices): """ This class reads in one perfect structure and the two endpoint structures are generated using site_indices. @@ -146,7 +151,6 @@

    Source code for pymatgen.analysis.diffusion.neb.io

    endpoints (list of Structure): a two-element list of two endpoints Structure object. """ - if len(site_indices) != 2 or len(set(site_indices)) != 2: raise ValueError("Invalid indices!") if structure[site_indices[0]].specie != structure[site_indices[1]].specie: @@ -173,13 +177,18 @@

    Source code for pymatgen.analysis.diffusion.neb.io

    return [s_0, s_1]
    -
    [docs]def get_endpoint_dist(ep_0, ep_1): + +
    +[docs] +def get_endpoint_dist(ep_0, ep_1): """ Calculate a list of site distances between two endpoints, assuming periodic boundary conditions. + Args: ep_0 (Structure): the first endpoint structure. ep_1 (Structure): the second endpoint structure. + Returns: dist (list): a list of distances between two structures. """ @@ -195,6 +204,7 @@

    Source code for pymatgen.analysis.diffusion.neb.io

    distances.append(d) return distances
    +
    @@ -209,7 +219,7 @@

    Source code for pymatgen.analysis.diffusion.neb.io

    +
    diff --git a/docs/_modules/pymatgen/analysis/diffusion/neb/pathfinder.html b/docs/_modules/pymatgen/analysis/diffusion/neb/pathfinder.html index 847f1d7..8b2f0bf 100644 --- a/docs/_modules/pymatgen/analysis/diffusion/neb/pathfinder.html +++ b/docs/_modules/pymatgen/analysis/diffusion/neb/pathfinder.html @@ -1,15 +1,15 @@ - + - pymatgen.analysis.diffusion.neb.pathfinder — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.neb.pathfinder — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -34,7 +34,7 @@

    Navigation

  • modules |
    • -
  • pymatgen-diffusion 2023.8.15 documentation »
    • +
  • pymatgen-diffusion 2024.6.10 documentation »
  • Module code »
  • pymatgen.analysis.diffusion.neb.pathfinder
    • @@ -49,9 +49,8 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    # Copyright (c) Materials Virtual Lab. # Distributed under the terms of the BSD License. -""" -Algorithms for NEB migration path analysis. -""" +"""Algorithms for NEB migration path analysis.""" + from __future__ import annotations import itertools @@ -67,10 +66,7 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    from monty.json import MSONable from scipy.interpolate import interp1d -from pymatgen.analysis.diffusion.utils.supercells import ( - get_sc_fromstruct, - get_start_end_structures, -) +from pymatgen.analysis.diffusion.utils.supercells import get_sc_fromstruct, get_start_end_structures from pymatgen.core import PeriodicSite, Site, Structure from pymatgen.core.periodic_table import get_el_sp from pymatgen.io.vasp.inputs import Poscar @@ -84,7 +80,9 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    # TODO: (1) ipython notebook example files, unittests -
    [docs]class IDPPSolver: +
    +[docs] +class IDPPSolver: """ A solver using image dependent pair potential (IDPP) algo to get an improved initial NEB path. For more details about this algo, please refer to @@ -99,7 +97,6 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    structures (list of pmg_structure) : Initial guess of the NEB path (including initial and final end-point structures). """ - latt = structures[0].lattice natoms = structures[0].num_sites nimages = len(structures) - 2 @@ -130,9 +127,7 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    weights = np.zeros_like(target_dists, dtype=np.float64) for ni in range(nimages): avg_dist = (target_dists[ni] + structures[ni + 1].distance_matrix) / 2.0 - weights[ni] = 1.0 / ( - avg_dist**4 + np.eye(natoms, dtype=np.float64) * 1e-8 - ) + weights[ni] = 1.0 / (avg_dist**4 + np.eye(natoms, dtype=np.float64) * 1e-8) for ni, i in itertools.product(range(nimages + 2), range(natoms)): frac_coords = structures[ni][i].frac_coords @@ -140,22 +135,20 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    if ni not in [0, nimages + 1]: for j in range(i + 1, natoms): - img = latt.get_distance_and_image( - frac_coords, structures[ni][j].frac_coords - )[1] + img = latt.get_distance_and_image(frac_coords, structures[ni][j].frac_coords)[1] translations[ni - 1, i, j] = latt.get_cartesian_coords(img) translations[ni - 1, j, i] = -latt.get_cartesian_coords(img) - self.init_coords = np.array(init_coords).reshape( - nimages + 2, natoms, 3 - ) # pylint: disable=E1121 + self.init_coords = np.array(init_coords).reshape(nimages + 2, natoms, 3) # pylint: disable=E1121 self.translations = translations self.weights = weights self.structures = structures self.target_dists = target_dists self.nimages = nimages -
    [docs] def run( +
    +[docs] + def run( self, maxiter=1000, tol=1e-5, @@ -191,7 +184,6 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    Returns: [Structure] Complete IDPP path (including end-point structures) """ - coords = self.init_coords.copy() old_funcs = np.zeros((self.nimages,), dtype=np.float64) idpp_structures = [self.structures[0]] @@ -200,9 +192,7 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    indices = list(range(len(self.structures[0]))) else: species = [get_el_sp(sp) for sp in species] - indices = [ - i for i, site in enumerate(self.structures[0]) if site.specie in species - ] + indices = [i for i, site in enumerate(self.structures[0]) if site.specie in species] if len(indices) == 0: raise ValueError("The given species are not in the system!") @@ -212,15 +202,11 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    # Get the sets of objective functions, true and total force # matrices. funcs, true_forces = self._get_funcs_and_forces(coords) - tot_forces = self._get_total_forces( - coords, true_forces, spring_const=spring_const - ) + tot_forces = self._get_total_forces(coords, true_forces, spring_const=spring_const) # Each atom is allowed to move up to max_disp disp_mat = step_size * tot_forces[:, indices, :] - disp_mat = np.where( - np.abs(disp_mat) > max_disp, np.sign(disp_mat) * max_disp, disp_mat - ) + disp_mat = np.where(np.abs(disp_mat) > max_disp, np.sign(disp_mat) * max_disp, disp_mat) coords[1 : (self.nimages + 1), indices] += disp_mat max_force = np.abs(tot_forces[:, indices, :]).max() @@ -232,9 +218,7 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    old_funcs = funcs else: - warnings.warn( - "Maximum iteration number is reached without convergence!", UserWarning - ) + warnings.warn("Maximum iteration number is reached without convergence!", UserWarning) for ni in range(self.nimages): # generate the improved image structure @@ -257,9 +241,16 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    return idpp_structures
    -
    [docs] @classmethod + +
    +[docs] + @classmethod def from_endpoints( - cls, endpoints, nimages=5, sort_tol=1.0, interpolate_lattices=False + cls, + endpoints, + nimages: int = 5, + sort_tol: float = 1.0, + interpolate_lattices: bool = False, ): """ A class method that starts with end-point structures instead. The @@ -272,6 +263,7 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    sort_tol (float): Distance tolerance (in Angstrom) used to match the atomic indices between start and end structures. Need to increase the value in some cases. + interpolate_lattices (bool): Whether to interpolate lattices between the start and end structures. """ try: images = endpoints[0].interpolate( @@ -283,8 +275,7 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    except Exception as e: if "Unable to reliably match structures " in str(e): warnings.warn( - "Auto sorting is turned off because it is unable" - " to match the end-point structures!", + "Auto sorting is turned off because it is unable" " to match the end-point structures!", UserWarning, ) images = endpoints[0].interpolate( @@ -298,10 +289,11 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    return IDPPSolver(images)
    + def _get_funcs_and_forces(self, x): """ Calculate the set of objective functions as well as their gradients, - i.e. "effective true forces" + i.e. "effective true forces". """ funcs = [] funcs_prime = [] @@ -314,11 +306,7 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    vec = [x[ni + 1, i] - x[ni + 1] - trans[ni, i] for i in range(natoms)] trial_dist = np.linalg.norm(vec, axis=2) - aux = ( - (trial_dist - target_dists[ni]) - * weights[ni] - / (trial_dist + np.eye(natoms, dtype=np.float64)) - ) + aux = (trial_dist - target_dists[ni]) * weights[ni] / (trial_dist + np.eye(natoms, dtype=np.float64)) # Objective function func = np.sum((trial_dist - target_dists[ni]) ** 2 * weights[ni]) @@ -331,15 +319,19 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    return 0.5 * np.array(funcs), -2 * np.array(funcs_prime) -
    [docs] @staticmethod +
    +[docs] + @staticmethod def get_unit_vector(vec): """ Calculate the unit vector of a vector. + Args: vec: Vector. """ return vec / np.sqrt(np.sum(vec**2))
    + def _get_total_forces(self, x, true_forces, spring_const): """ Calculate the total force on each image structure, which is equal to @@ -347,7 +339,6 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    tangent. Note that the spring force is the modified version in the literature (e.g. Henkelman et al., J. Chem. Phys. 113, 9901 (2000)). """ - total_forces = [] natoms = np.shape(true_forces)[1] @@ -360,24 +351,21 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    tangent = self.get_unit_vector(tangent) # Spring force - spring_force = ( - spring_const * (np.linalg.norm(vec1) - np.linalg.norm(vec2)) * tangent - ) + spring_force = spring_const * (np.linalg.norm(vec1) - np.linalg.norm(vec2)) * tangent # Total force flat_ft = true_forces[ni - 1].copy().flatten() - total_force = true_forces[ni - 1] + ( - spring_force - np.dot(flat_ft, tangent) * tangent - ).reshape(natoms, 3) + total_force = true_forces[ni - 1] + (spring_force - np.dot(flat_ft, tangent) * tangent).reshape(natoms, 3) total_forces.append(total_force) return np.array(total_forces)
    -
    [docs]class MigrationHop(MSONable): - """ - A convenience container representing a migration path. - """ + +
    +[docs] +class MigrationHop(MSONable): + """A convenience container representing a migration path.""" def __init__( self, @@ -392,8 +380,9 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    isite: Initial site esite: End site symm_structure: SymmetrizedStructure - host_symm_struct: SymmetrizedStructure of the host structure, used to for its spacegroup - symprec: used to determine equivalence + host_symm_struct: SymmetrizedStructure of the host structure, used to for + its spacegroup + symprec: used to determine equivalence. """ self.isite = isite self.esite = esite @@ -402,11 +391,13 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    self.symm_structure = symm_structure self.host_symm_struct = host_symm_struct self.symprec = symprec - self.msite = PeriodicSite( - esite.specie, (isite.frac_coords + esite.frac_coords) / 2, esite.lattice - ) + self.msite = PeriodicSite(esite.specie, (isite.frac_coords + esite.frac_coords) / 2, esite.lattice) - sg = self.host_symm_struct.spacegroup if host_symm_struct else self.symm_structure.spacegroup # type: ignore + sg = ( + self.host_symm_struct.spacegroup # type: ignore[union-attr] + if host_symm_struct + else self.symm_structure.spacegroup # type: ignore[union-attr] + ) for i, sites in enumerate(self.symm_structure.equivalent_sites): if sg.are_symmetrically_equivalent([isite], [sites[0]]): self.iindex = i @@ -434,24 +425,21 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    break if self.iindex is None: - raise RuntimeError( - f"No symmetrically equivalent site was found for {isite}" - ) + raise RuntimeError(f"No symmetrically equivalent site was found for {isite}") if self.eindex is None: - raise RuntimeError( - f"No symmetrically equivalent site was found for {esite}" - ) + raise RuntimeError(f"No symmetrically equivalent site was found for {esite}") def __repr__(self): ifc = self.isite.frac_coords efc = self.esite.frac_coords + wyk_symbols = self.symm_structure.wyckoff_symbols return ( f"Path of {self.length:.4f} A from {self.isite.specie} " f"[{ifc[0]:.3f}, {ifc[1]:.3f}, {ifc[2]:.3f}] " - f"(ind: {self.iindex}, Wyckoff: {self.symm_structure.wyckoff_symbols[self.iindex]}) " + f"(ind: {self.iindex}, Wyckoff: {wyk_symbols[self.iindex]}) " f"to {self.esite.specie} " f"[{efc[0]:.3f}, {efc[1]:.3f}, {efc[2]:.3f}] " - f"(ind: {self.eindex}, Wyckoff: {self.symm_structure.wyckoff_symbols[self.eindex]})" + f"(ind: {self.eindex}, Wyckoff: {wyk_symbols[self.eindex]})" ) @property @@ -481,7 +469,9 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    self.symprec, ) -
    [docs] def get_structures(self, nimages=5, vac_mode=True, idpp=False, **idpp_kwargs): +
    +[docs] + def get_structures(self, nimages=5, vac_mode=True, idpp=False, **idpp_kwargs): r""" Generate structures for NEB calculation. @@ -502,27 +492,19 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    idpp (bool): Defaults to False. If True, the generated structures will be run through the IDPPSolver to generate a better guess for the minimum energy path. - \*\*idpp_kwargs: Passthrough kwargs for the IDPPSolver.run. + **idpp_kwargs: Passthrough kwargs for the IDPPSolver.run. Returns: [Structure] Note that the first site of each structure is always the migrating ion. This makes it easier to perform subsequent analysis. """ - migrating_specie_sites, other_sites = self._split_migrating_and_other_sites( - vac_mode - ) + migrating_specie_sites, other_sites = self._split_migrating_and_other_sites(vac_mode) - start_structure = Structure.from_sites( - [self.isite, *migrating_specie_sites, *other_sites] - ) - end_structure = Structure.from_sites( - [self.esite, *migrating_specie_sites, *other_sites] - ) + start_structure = Structure.from_sites([self.isite, *migrating_specie_sites, *other_sites]) + end_structure = Structure.from_sites([self.esite, *migrating_specie_sites, *other_sites]) - structures = start_structure.interpolate( - end_structure, nimages=nimages + 1, pbc=False - ) + structures = start_structure.interpolate(end_structure, nimages=nimages + 1, pbc=False) if idpp: solver = IDPPSolver(structures) @@ -530,6 +512,7 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    return structures
    + def _split_migrating_and_other_sites(self, vac_mode): migrating_specie_sites = [] other_sites = [] @@ -537,10 +520,7 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    if site.specie != self.isite.specie: other_sites.append(site) else: - if ( - self.isite.distance(site) <= 1e-8 - or self.esite.distance(site) <= 1e-8 - ): + if self.isite.distance(site) <= 1e-8 or self.esite.distance(site) <= 1e-8: migrating_specie_sites.append(site) continue @@ -548,7 +528,9 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    other_sites.append(site) return migrating_specie_sites, other_sites -
    [docs] def get_sc_structures( +
    +[docs] + def get_sc_structures( self, vac_mode: bool, min_atoms: int = 80, @@ -557,7 +539,8 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    tol: float = 1e-5, ) -> tuple[Structure, Structure, Structure]: """ - Construct supercells that represents the start and end positions for migration analysis. + Construct supercells that represents the start and end positions for migration + analysis. Args: vac_mode: If true simulate vacancy diffusion. @@ -573,9 +556,7 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    If in vacancy mode, the base structure is the fully intercalated structure """ - migrating_specie_sites, other_sites = self._split_migrating_and_other_sites( - vac_mode - ) + migrating_specie_sites, other_sites = self._split_migrating_and_other_sites(vac_mode) if vac_mode: base_struct = Structure.from_sites(other_sites + migrating_specie_sites) else: @@ -596,22 +577,29 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    ) return start_struct, end_struct, base_sc
    -
    [docs] def write_path(self, fname, **kwargs): + +
    +[docs] + def write_path(self, fname, **kwargs): r""" Write the path to a file for easy viewing. Args: fname (str): File name. - \*\*kwargs: Kwargs supported by NEBPath.get_structures. + **kwargs: Kwargs supported by NEBPath.get_structures. """ sites = [] for st in self.get_structures(**kwargs): sites.extend(st) st = Structure.from_sites(sites) - st.to(filename=fname)
    + st.to(filename=fname)
    +
    + -
    [docs]class DistinctPathFinder: +
    +[docs] +class DistinctPathFinder: """ Determines symmetrically distinct paths between existing sites. The path info can then be used to set up either vacancy or interstitial @@ -684,7 +672,9 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    else: self.max_path_length = max_path_length -
    [docs] def get_paths(self): +
    +[docs] + def get_paths(self): """ Returns: [MigrationHop] All distinct migration paths. @@ -693,16 +683,17 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    for sites in self.symm_structure.equivalent_sites: if sites[0].specie == self.migrating_specie: site0 = sites[0] - for nn in self.symm_structure.get_neighbors( - site0, r=round(self.max_path_length, 3) + 0.01 - ): + for nn in self.symm_structure.get_neighbors(site0, r=round(self.max_path_length, 3) + 0.01): if nn.specie == self.migrating_specie: path = MigrationHop(site0, nn, self.symm_structure) paths.add(path) return sorted(paths, key=lambda p: p.length)
    -
    [docs] def write_all_paths(self, fname, nimages=5, **kwargs): + +
    +[docs] + def write_all_paths(self, fname, nimages=5, **kwargs): r""" Write a file containing all paths, using hydrogen as a placeholder for the images. H is chosen as it is the smallest atom. This is extremely @@ -711,22 +702,24 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    Args: fname (str): Filename nimages (int): Number of images per path. - \*\*kwargs: Passthrough kwargs to path.get_structures. + **kwargs: Passthrough kwargs to path.get_structures. """ sites = [] for p in self.get_paths(): - structures = p.get_structures( - nimages=nimages, species=[self.migrating_specie], **kwargs - ) + structures = p.get_structures(nimages=nimages, species=[self.migrating_specie], **kwargs) sites.append(structures[0][0]) sites.append(structures[-1][0]) for s in structures[1:-1]: sites.append(PeriodicSite("H", s[0].frac_coords, s.lattice)) - sites.extend(structures[0].sites[1:]) - Structure.from_sites(sites).to(filename=fname)
    + sites.extend(structures[0].sites[1:]) # type: ignore + Structure.from_sites(sites).to(filename=fname)
    +
    + -
    [docs]class NEBPathfinder: +
    +[docs] +class NEBPathfinder: """ General pathfinder for interpolating between two structures, where the interpolating path is calculated with the elastic band method with @@ -740,17 +733,17 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    Ceder, The Journal of Chemical Physics 145 (7), 074112 """ - def __init__( - self, start_struct, end_struct, relax_sites, v, n_images=20, mid_struct=None - ): + def __init__(self, start_struct, end_struct, relax_sites, v, n_images=20, mid_struct=None): """ Args: - start_struct, end_struct: Endpoint structures to interpolate + start_struct: Starting structure + end_struct: End structure to interpolate relax_sites: List of site indices whose interpolation paths should be relaxed v: Static potential field to use for the elastic band relaxation n_images: Number of interpolation images to generate - mid_struct: (optional) additional structure between the start and end structures to help. + mid_struct: (optional) additional structure between the start and end + structures to help. """ self.__s1 = start_struct self.__s2 = end_struct @@ -761,7 +754,9 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    self.__images = None self.interpolate() -
    [docs] def interpolate(self): +
    +[docs] + def interpolate(self): """ Finds a set of n_images from self.s1 to self.s2, where all sites except for the ones given in relax_sites, the interpolation is linear (as in @@ -773,20 +768,15 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    The final number of images will still be n_images. """ if self.__mid is not None: - # to make arithmetic easier we will do the interpolation in two parts with n images each - # then just take every other image at the end, this results in exactly n images - images_0 = self.__s1.interpolate( - self.__mid, nimages=self.__n_images, interpolate_lattices=False - )[:-1] - images_1 = self.__mid.interpolate( - self.__s2, nimages=self.__n_images, interpolate_lattices=False - ) + # to make arithmetic easier we will do the interpolation in two parts with n + # images each then just take every other image at the end, this results in + # exactly n images + images_0 = self.__s1.interpolate(self.__mid, nimages=self.__n_images, interpolate_lattices=False)[:-1] + images_1 = self.__mid.interpolate(self.__s2, nimages=self.__n_images, interpolate_lattices=False) images = images_0 + images_1 images = images[::2] else: - images = self.__s1.interpolate( - self.__s2, nimages=self.__n_images, interpolate_lattices=False - ) + images = self.__s1.interpolate(self.__s2, nimages=self.__n_images, interpolate_lattices=False) for site_i in self.__relax_sites: start_f = images[0].sites[site_i].frac_coords end_f = images[-1].sites[site_i].frac_coords @@ -805,13 +795,13 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    for image_i, image in enumerate(images): image.translate_sites( site_i, - NEBPathfinder.__d2f(path[image_i], self.__v) - - image.sites[site_i].frac_coords, + NEBPathfinder.__d2f(path[image_i], self.__v) - image.sites[site_i].frac_coords, frac_coords=True, to_unit_cell=True, ) self.__images = images
    + @property def images(self): """ @@ -820,10 +810,15 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    """ return self.__images -
    [docs] def plot_images(self, outfile): +
    +[docs] + def plot_images(self, outfile): """ - Generates a POSCAR with the calculated diffusion path with respect to the first endpoint. - :param outfile: Output file for the POSCAR. + Generates a POSCAR with the calculated diffusion path with respect to the first + endpoint. + + Args: + outfile: Output file for the POSCAR. """ sum_struct = self.__images[0].sites for image in self.__images: @@ -841,7 +836,10 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    p = Poscar(sum_struct) p.write_file(outfile)
    -
    [docs] @staticmethod + +
    +[docs] + @staticmethod def string_relax( start, end, @@ -894,11 +892,7 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    # logger.debug(f"Getting path from {start} to {end} (coords wrt V grid)") # Set parameters - dr = ( - np.array([1 / V.shape[0], 1 / V.shape[1], 1 / V.shape[2]]) - if not dr - else np.array(dr, dtype=float) - ) + dr = np.array([1 / V.shape[0], 1 / V.shape[1], 1 / V.shape[2]]) if not dr else np.array(dr, dtype=float) keff = k * dr * n_images h0 = h @@ -925,25 +919,18 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    dV = np.gradient(V) # Evolve string - for step in range(0, max_iter): + for step in range(max_iter): # Gradually decay step size to prevent oscillations - h = ( - h0 * np.exp(-2 * (step - min_iter) / max_iter) - if step > min_iter - else h0 - ) + h = h0 * np.exp(-2 * (step - min_iter) / max_iter) if step > min_iter else h0 # Calculate forces acting on string d = V.shape s0 = s.copy() # store copy for endpoint fixing below (fixes GH 2732) edV = np.array( [ [ - dV[0][int(pt[0]) % d[0]][int(pt[1]) % d[1]][int(pt[2]) % d[2]] - / dr[0], - dV[1][int(pt[0]) % d[0]][int(pt[1]) % d[1]][int(pt[2]) % d[2]] - / dr[0], - dV[2][int(pt[0]) % d[0]][int(pt[1]) % d[1]][int(pt[2]) % d[2]] - / dr[0], + dV[0][int(pt[0]) % d[0]][int(pt[1]) % d[1]][int(pt[2]) % d[2]] / dr[0], + dV[1][int(pt[0]) % d[0]][int(pt[1]) % d[1]][int(pt[2]) % d[2]] / dr[0], + dV[2][int(pt[0]) % d[0]][int(pt[1]) % d[1]][int(pt[2]) % d[2]] / dr[0], ] for pt in s ] @@ -957,16 +944,8 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    ds_plus[0] = ds_plus[0] - ds_plus[0] ds_minus[-1] = ds_minus[-1] - ds_minus[-1] Fpot = edV - Fel = ( - keff - * (la.norm(ds_plus) - la.norm(ds0_plus)) - * (ds_plus / la.norm(ds_plus)) - ) - Fel += ( - keff - * (la.norm(ds_minus) - la.norm(ds0_minus)) - * (ds_minus / la.norm(ds_minus)) - ) + Fel = keff * (la.norm(ds_plus) - la.norm(ds0_plus)) * (ds_plus / la.norm(ds_plus)) + Fel += keff * (la.norm(ds_minus) - la.norm(ds0_minus)) * (ds_minus / la.norm(ds_minus)) s -= h * (Fpot + Fel) # Fix endpoints @@ -984,9 +963,7 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    tol = la.norm((s - s0) * dr) / n_images / h if tol > 1e10: - raise ValueError( - "Pathfinding failed, path diverged! Consider reducing h to avoid divergence." - ) + raise ValueError("Pathfinding failed, path diverged! Consider reducing h to avoid " "divergence.") if step > min_iter and tol < max_tol: logger.debug(f"Converged at {step=}") @@ -996,6 +973,7 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    logger.debug(f"{step=} - ds = {tol}") return s
    + @staticmethod def __f2d(frac_coords, v): """ @@ -1020,7 +998,10 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    )
    -
    [docs]class StaticPotential: + +
    +[docs] +class StaticPotential: """ Defines a general static potential for diffusion calculations. Implements grid-rescaling and smearing for the potential grid. Also provides a @@ -1035,16 +1016,24 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    self.__v = pot self.__s = struct -
    [docs] def get_v(self): +
    +[docs] + def get_v(self): """Returns the potential.""" return self.__v
    -
    [docs] def normalize(self): + +
    +[docs] + def normalize(self): """Sets the potential range 0 to 1.""" self.__v = self.__v - np.amin(self.__v) self.__v = self.__v / np.amax(self.__v)
    -
    [docs] def rescale_field(self, new_dim): + +
    +[docs] + def rescale_field(self, new_dim): """ Changes the discretization of the potential field by linear interpolation. This is necessary if the potential field @@ -1057,27 +1046,23 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    """ v_dim = self.__v.shape padded_v = np.lib.pad(self.__v, ((0, 1), (0, 1), (0, 1)), mode="wrap") - ogrid_list = np.array( - [ - list(c) - for c in list(np.ndindex(v_dim[0] + 1, v_dim[1] + 1, v_dim[2] + 1)) - ] - ) - v_ogrid = padded_v.reshape( - ((v_dim[0] + 1) * (v_dim[1] + 1) * (v_dim[2] + 1), -1) - ) + ogrid_list = np.array([list(c) for c in list(np.ndindex(v_dim[0] + 1, v_dim[1] + 1, v_dim[2] + 1))]) + v_ogrid = padded_v.reshape(((v_dim[0] + 1) * (v_dim[1] + 1) * (v_dim[2] + 1), -1)) ngrid_a, ngrid_b, ngrid_c = np.mgrid[ 0 : v_dim[0] : v_dim[0] / new_dim[0], 0 : v_dim[1] : v_dim[1] / new_dim[1], 0 : v_dim[2] : v_dim[2] / new_dim[2], ] - v_ngrid = scipy.interpolate.griddata( - ogrid_list, v_ogrid, (ngrid_a, ngrid_b, ngrid_c), method="linear" - ).reshape((new_dim[0], new_dim[1], new_dim[2])) + v_ngrid = scipy.interpolate.griddata(ogrid_list, v_ogrid, (ngrid_a, ngrid_b, ngrid_c), method="linear").reshape( + (new_dim[0], new_dim[1], new_dim[2]) + ) self.__v = v_ngrid
    -
    [docs] def gaussian_smear(self, r): + +
    +[docs] + def gaussian_smear(self, r): """ Applies an isotropic Gaussian smear of width (standard deviation) r to the potential field. This is necessary to avoid finding paths through @@ -1111,9 +1096,9 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    for g_b in np.arange(-2 * r_disc[1], 2 * r_disc[1] + 1, 1): for g_c in np.arange(-2 * r_disc[2], 2 * r_disc[2] + 1, 1): g = np.array([g_a / v_dim[0], g_b / v_dim[1], g_c / v_dim[2]]).T - gauss_dist[int(g_a + r_disc[0])][int(g_b + r_disc[1])][ - int(g_c + r_disc[2]) - ] = (la.norm(np.dot(self.__s.lattice.matrix, g)) / r) + gauss_dist[int(g_a + r_disc[0])][int(g_b + r_disc[1])][int(g_c + r_disc[2])] = ( + la.norm(np.dot(self.__s.lattice.matrix, g)) / r + ) gauss = scipy.stats.norm.pdf(gauss_dist) gauss = gauss / np.sum(gauss, dtype=float) padded_v = np.pad( @@ -1122,10 +1107,14 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    mode="wrap", ) smeared_v = scipy.signal.convolve(padded_v, gauss, mode="valid") - self.__v = smeared_v
    + self.__v = smeared_v
    +
    + -
    [docs]class ChgcarPotential(StaticPotential): +
    +[docs] +class ChgcarPotential(StaticPotential): """Implements a potential field based on the charge density output from VASP.""" def __init__(self, chgcar, smear=False, normalize=True): @@ -1146,7 +1135,10 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    self.normalize()
    -
    [docs]class FreeVolumePotential(StaticPotential): + +
    +[docs] +class FreeVolumePotential(StaticPotential): """ Implements a potential field based on geometric distances from atoms in the structure - basically, the potential @@ -1177,15 +1169,16 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    for b_d in np.arange(0, dim[1], 1): for c_d in np.arange(0, dim[2], 1): coords_f = np.array([a_d / dim[0], b_d / dim[1], c_d / dim[2]]) - d_f = sorted( - s.get_sites_in_sphere(coords_f, s.lattice.a), key=lambda x: x[1] - )[0][1] + d_f = sorted(s.get_sites_in_sphere(coords_f, s.lattice.a), key=lambda x: x[1])[0][1] # logger.debug(d_f) gauss_dist[int(a_d)][int(b_d)][int(c_d)] = d_f / r return scipy.stats.norm.pdf(gauss_dist)
    -
    [docs]class MixedPotential(StaticPotential): + +
    +[docs] +class MixedPotential(StaticPotential): """Implements a potential that is a weighted sum of some other potentials.""" def __init__(self, potentials, coefficients, smear=False, normalize=True): @@ -1206,6 +1199,7 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    self.gaussian_smear(2) if normalize: self.normalize()
    +
    @@ -1220,7 +1214,7 @@

    Source code for pymatgen.analysis.diffusion.neb.pathfinder

    +
    diff --git a/docs/_modules/pymatgen/analysis/diffusion/neb/periodic_dijkstra.html b/docs/_modules/pymatgen/analysis/diffusion/neb/periodic_dijkstra.html index 7ce7d0d..4b1ce7c 100644 --- a/docs/_modules/pymatgen/analysis/diffusion/neb/periodic_dijkstra.html +++ b/docs/_modules/pymatgen/analysis/diffusion/neb/periodic_dijkstra.html @@ -1,15 +1,15 @@ - + - pymatgen.analysis.diffusion.neb.periodic_dijkstra — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.neb.periodic_dijkstra — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -34,7 +34,7 @@

    Navigation

  • modules |
    • -
  • pymatgen-diffusion 2023.8.15 documentation »
    • +
  • pymatgen-diffusion 2024.6.10 documentation »
  • Module code »
  • pymatgen.analysis.diffusion.neb.periodic_dijkstra
    • @@ -48,9 +48,9 @@

    Navigation

    Source code for pymatgen.analysis.diffusion.neb.periodic_dijkstra

     # Copyright (c) Materials Virtual Lab.
 # Distributed under the terms of the BSD License.
-"""
-Dijkstra's path search on a graph where the nodes are on a periodic graph
-"""
+"""Dijkstra's path search on a graph where the nodes are on a periodic graph."""
+
+from __future__ import annotations
 
 __author__ = "Jimmy Shen"
 __copyright__ = "Copyright 2021, The Materials Project"
@@ -61,18 +61,25 @@ 
    Source code for pymatgen.analysis.diffusion.neb.periodic_dijkstra
    import heapq
 import math
 from collections import defaultdict
-from typing import Callable, Dict, Set
+from typing import TYPE_CHECKING, Callable
 
 import numpy as np
-from networkx.classes.graph import Graph
-from pymatgen.analysis.graphs import StructureGraph
 
+if TYPE_CHECKING:
+    from networkx.classes.graph import Graph
+
+    from pymatgen.analysis.graphs import StructureGraph
 
-def _get_adjacency_with_images(G: Graph) -> Dict:
+
+def _get_adjacency_with_images(G: Graph) -> dict:
     """
     Return an adjacency dictionary with properly oriented "to_image" values.
     Note: the current implementation assumes that the original
     "to_jimage" value always corresponds to a an edge u -> v where u <= v.
+
+    Args:
+        G (pymatgen.analysis.graphs.StructureGraph): Structure graph.
+
     Returns:
         dict: Nested dictionary with [start][end][edge_key][data_field]
     """
@@ -96,13 +103,15 @@ 
    Source code for pymatgen.analysis.diffusion.neb.periodic_dijkstra
    # Make sure all the to_jimages are pointing in the correct direction
     for u, value1 in p_graph.items():
         for v, value2 in value1.items():
-            for k, d in value2.items():
+            for d in value2.values():
                 if u > v:
                     d["to_jimage"] = tuple(np.multiply(-1, d["to_jimage"]))
     return p_graph
 
 
-
    [docs]def periodic_dijkstra(
+
    
+[docs]
+def periodic_dijkstra(
     G: Graph,
     sources: set,
     weight: str = "weight",
@@ -118,16 +127,16 @@ 
    Source code for pymatgen.analysis.diffusion.neb.periodic_dijkstra
            G (Graph): The graph object with additional "to_jimage" fields to
                 indicate edges across periodic images.
         sources (set): the index of the source node
-        target (int, optional): The index of of target node, if None populate all nodes. Defaults to None.
+        weight: the weight of the edges.
         max_image (int, optional): Defaults to 3.
         target_reached (callable, optional): A function of (site_index, jimage) used to check
             for stop iteration. This function is always called on the top of heap so it might miss the optimal path but
             often can find a "good enough" path very quickly.
+
     Returns:
         best_ans: a dictionary of the best cost found to periodic node keyed by (site_index, jimage)
         path_parent: dictionary of optimal path parent for each node given in index-image pairs.
     """
-
     conn_dict = _get_adjacency_with_images(G.to_undirected())
 
     # use a default dict since we don't know how far out to search
@@ -144,7 +153,7 @@ 
    Source code for pymatgen.analysis.diffusion.neb.periodic_dijkstra
    if min_val < best_ans[(cur_idx, cur_image)]:
             best_ans[(cur_idx, cur_image)] = min_val
         for next_node, keyed_data in conn_dict[cur_idx].items():
-            for k, d in keyed_data.items():
+            for d in keyed_data.values():
                 # get the node index, image pair
                 new_image = tuple(np.add(cur_image, d["to_jimage"]))
                 next_index_pair = (next_node, new_image)
@@ -162,9 +171,12 @@ 
    Source code for pymatgen.analysis.diffusion.neb.periodic_dijkstra
    return best_ans, path_parent
    
 
 
-
    [docs]def periodic_dijkstra_on_sgraph(
+
+
    
+[docs]
+def periodic_dijkstra_on_sgraph(
     sgraph: StructureGraph,
-    sources: Set,
+    sources: set,
     weight: str = "weight",
     max_image: int = 1,
     target_reached: Callable = lambda idx, jimage: False,
@@ -177,11 +189,12 @@ 
    Source code for pymatgen.analysis.diffusion.neb.periodic_dijkstra
        Args:
         sgraph (Graph): The StructureGraph object used for path searching
         sources (set): the index of the source node
-        target (int, optional): The index of of target node, if None populate all nodes. Defaults to None.
+        weight: the weight of the edges.
         max_image (int, optional): Defaults to 3.
         target_reached (callable, optional): A function of (site_index, jimage) used to check
             for stop iteration. This function is always called on the top of heap so it might miss the optimal path but
             often can find a "good enough" path very quickly.
+
     Returns:
         best_ans: a dictionary of the best cost found to periodic node keyed by (site_index, jimage)
         path_parent: dictionary of optimal path parent for each node given in index-image pairs.
@@ -197,15 +210,17 @@ 
    Source code for pymatgen.analysis.diffusion.neb.periodic_dijkstra
    return best_ans, path_parent
    
 
 
-
    [docs]def get_optimal_pathway_rev(path_parent: dict, leaf_node: tuple):
-    """
-    follow a leaf node all the way up to source.
-    """
+
+
    
+[docs]
+def get_optimal_pathway_rev(path_parent: dict, leaf_node: tuple):
+    """Follow a leaf node all the way up to source."""
     cur = leaf_node
     while cur in path_parent:
         yield cur
         cur = path_parent[cur]
     yield cur
    
+
    @@ -220,7 +235,7 @@

    Source code for pymatgen.analysis.diffusion.neb.periodic_dijkstra

    - +
    diff --git a/docs/_modules/pymatgen/analysis/diffusion/neb/tests/test_full_path_mapper.html b/docs/_modules/pymatgen/analysis/diffusion/neb/tests/test_full_path_mapper.html index a7232a5..fd34c1c 100644 --- a/docs/_modules/pymatgen/analysis/diffusion/neb/tests/test_full_path_mapper.html +++ b/docs/_modules/pymatgen/analysis/diffusion/neb/tests/test_full_path_mapper.html @@ -1,15 +1,15 @@ - + - pymatgen.analysis.diffusion.neb.tests.test_full_path_mapper — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.neb.tests.test_full_path_mapper — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -34,7 +34,7 @@

    Navigation

  • modules |
    • -
  • pymatgen-diffusion 2023.8.15 documentation »
    • +
  • pymatgen-diffusion 2024.6.10 documentation »
  • Module code »
  • pymatgen.analysis.diffusion.neb.tests.test_full_path_mapper
    • @@ -74,14 +74,21 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_full_path_mapper< __date__ = "April 10, 2019" -
    [docs]class MigrationGraphSimpleTest(unittest.TestCase): -
    [docs] def setUp(self): +
    +[docs] +class MigrationGraphSimpleTest(unittest.TestCase): +
    +[docs] + def setUp(self): struct = Structure.from_file(f"{dir_path}/full_path_files/MnO2_full_Li.vasp") self.fpm = MigrationGraph.with_distance( structure=struct, migrating_specie="Li", max_distance=4 )
    -
    [docs] def test_get_pos_and_migration_hop(self): + +
    +[docs] + def test_get_pos_and_migration_hop(self): """ Make sure that we can populate the graph with MigrationHop Objects """ @@ -90,14 +97,23 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_full_path_mapper< self.fpm.m_graph.graph[0][1][1]["hop"].length, 3.571248, 4 )

    -
    [docs] def test_get_summary_dict(self): + +
    +[docs] + def test_get_summary_dict(self): summary_dict = self.fpm.get_summary_dict() - assert "hop_label", summary_dict["hops"][0] - assert "hop_label", summary_dict["unique_hops"][0]
    + assert "hop_label" in summary_dict["hops"][0] + assert "hop_label" in summary_dict["unique_hops"][0]
    +
    + -
    [docs]class MigrationGraphFromEntriesTest(unittest.TestCase): -
    [docs] def setUp(self): +
    +[docs] +class MigrationGraphFromEntriesTest(unittest.TestCase): +
    +[docs] + def setUp(self): self.test_ents_MOF = loadfn( f"{dir_path}/full_path_files/Mn6O5F7_cat_migration.json" ) @@ -111,7 +127,10 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_full_path_mapper< migrating_ion_entry=self.li_ent, )[0]

    -
    [docs] def test_m_graph_from_entries_failed(self): + +
    +[docs] + def test_m_graph_from_entries_failed(self): # only base s_list = MigrationGraph.get_structure_from_entries( entries=[self.test_ents_MOF["ent_base"]], @@ -125,30 +144,44 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_full_path_mapper< ) assert len(s_list) == 0

    -
    [docs] def test_m_graph_construction(self): + +
    +[docs] + def test_m_graph_construction(self): assert self.full_struct.composition["Li"] == 8 mg = MigrationGraph.with_distance( self.full_struct, migrating_specie="Li", max_distance=4.0 ) - assert len(mg.m_graph.structure) == 8
    + assert len(mg.m_graph.structure) == 8
    +
    -
    [docs]class MigrationGraphComplexTest(unittest.TestCase): -
    [docs] def setUp(self): + +
    +[docs] +class MigrationGraphComplexTest(unittest.TestCase): +
    +[docs] + def setUp(self): struct = Structure.from_file(f"{dir_path}/full_path_files/MnO2_full_Li.vasp") self.fpm_li = MigrationGraph.with_distance( structure=struct, migrating_specie="Li", max_distance=4 ) - # Particularity difficult pathfinding since both the starting and ending positions are outside the unit cell + # Particularity difficult path finding since both the starting and ending + # positions are outside the unit cell struct = Structure.from_file(f"{dir_path}/full_path_files/Mg_2atom.vasp") self.fpm_mg = MigrationGraph.with_distance( structure=struct, migrating_specie="Mg", max_distance=2 )
    -
    [docs] def test_group_and_label_hops(self): + +
    +[docs] + def test_group_and_label_hops(self): """ - Check that the set of end points in a group of similiarly labeled hops are all the same + Check that the set of end points in a group of similarly labeled hops are all + the same. """ edge_labs = np.array( [d["hop_label"] for u, v, d in self.fpm_li.m_graph.graph.edges(data=True)] @@ -169,9 +202,12 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_full_path_mapper< for end_point_labels in sub_set: assert sorted(end_point_labels) == sorted(sub_set[0])

    -
    [docs] def test_unique_hops_dict(self): + +
    +[docs] + def test_unique_hops_dict(self): """ - Check that the unique hops are inequilvalent + Check that the unique hops are inequivalent """ unique_list = [v for k, v in self.fpm_li.unique_hops.items()] all_pairs = [ @@ -183,7 +219,10 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_full_path_mapper< for migration_hop in all_pairs: assert migration_hop[0]["hop"] != migration_hop[1]["hop"]

    -
    [docs] def test_add_data_to_similar_edges(self): + +
    +[docs] + def test_add_data_to_similar_edges(self): # passing normal data self.fpm_li.add_data_to_similar_edges(0, {"key0": "data"}) for _u, _v, d in self.fpm_li.m_graph.graph.edges(data=True): @@ -212,7 +251,10 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_full_path_mapper< if d["hop_label"] == 2: assert d["key2"] == [3, 2, 1]

    -
    [docs] def test_assign_cost_to_graph(self): + +
    +[docs] + def test_assign_cost_to_graph(self): self.fpm_li.assign_cost_to_graph() # use 'hop_distance' for _u, _v, d in self.fpm_li.m_graph.graph.edges(data=True): self.assertAlmostEqual(d["cost"], d["hop_distance"], 4) @@ -221,7 +263,10 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_full_path_mapper< for _u, _v, d in self.fpm_li.m_graph.graph.edges(data=True): self.assertAlmostEqual(d["cost"], d["hop_distance"] ** 2, 4)

    -
    [docs] def test_periodic_dijkstra(self): + +
    +[docs] + def test_periodic_dijkstra(self): self.fpm_li.assign_cost_to_graph() # use 'hop_distance' # test the connection graph @@ -237,7 +282,10 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_full_path_mapper< ] assert neg_image in opposite_connections

    -
    [docs] def test_get_path(self): + +
    +[docs] + def test_get_path(self): self.fpm_li.assign_cost_to_graph() # use 'hop_distance' paths = [*self.fpm_li.get_path(flip_hops=False)] p_strings = { @@ -263,7 +311,10 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_full_path_mapper< } assert "1->0->1" in p_strings

    -
    [docs] def test_get_key_in_path(self): + +
    +[docs] + def test_get_key_in_path(self): self.fpm_li.assign_cost_to_graph() # use 'hop_distance' paths = [*self.fpm_li.get_path(flip_hops=False)] hop_seq_info = [ @@ -282,13 +333,19 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_full_path_mapper< assert distances == hop_seq_info[u][1] print(distances, hop_seq_info[u][1])

    -
    [docs] def test_not_matching_first(self): + +
    +[docs] + def test_not_matching_first(self): structure = Structure.from_file(f"{dir_path}/pathfinder_files/Li6MnO4.json") fpm_lmo = MigrationGraph.with_distance(structure, "Li", max_distance=4) for _u, _v, d in fpm_lmo.m_graph.graph.edges(data=True): assert d["hop"].eindex in {0, 1}
    -
    [docs] def test_order_path(self): + +
    +[docs] + def test_order_path(self): # add list data to migration graph - to test if list data is flipped for n, hop_d in self.fpm_li.unique_hops.items(): data = {"data": [hop_d["iindex"], hop_d["eindex"]]} @@ -307,11 +364,17 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_full_path_mapper< for h, ord_h in zip(hop_list, ordered): if h["iindex"] != ord_h["iindex"]: # check only if hop was flipped assert h["data"][0] == ord_h["data"][-1] - assert h["data"][-1] == ord_h["data"][0]

    + assert h["data"][-1] == ord_h["data"][0]
    +
    + -
    [docs]class ChargeBarrierGraphTest(unittest.TestCase): -
    [docs] def setUp(self): +
    +[docs] +class ChargeBarrierGraphTest(unittest.TestCase): +
    +[docs] + def setUp(self): self.full_sites_MOF = loadfn( f"{dir_path}/full_path_files/LixMn6O5F7_full_sites.json" ) @@ -327,9 +390,12 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_full_path_mapper< ) self.cbg._tube_radius = 10000

    -
    [docs] def test_integration(self): + +
    +[docs] + def test_integration(self): """ - Sanity check: for a long enough diagonaly hop, if we turn the radius of the tube way up, it should cover the entire unit cell + Sanity check: for a long enough diagonally hop, if we turn the radius of the tube way up, it should cover the entire unit cell """ total_chg_per_vol = ( self.cbg.potential_field.data["total"].sum() @@ -363,7 +429,10 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_full_path_mapper< 3, )

    -
    [docs] def test_populate_edges_with_chg_density_info(self): + +
    +[docs] + def test_populate_edges_with_chg_density_info(self): """ Test that all of the sites with similar lengths have similar charge densities, this will not always be true, but it valid in this Mn6O5F7 @@ -382,14 +451,15 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_full_path_mapper< if 1.05 > length / prv[0] > 0.95: self.assertAlmostEqual(chg, prv[1], 3)

    -
    [docs] def test_get_summary_dict(self): - summary_dict = self.cbg.get_summary_dict() - assert "chg_total", summary_dict["hops"][0] - assert "chg_total", summary_dict["unique_hops"][0]
    +
    +[docs] + def test_get_summary_dict(self): + summary_dict = self.cbg.get_summary_dict() + assert "chg_total", summary_dict["hops"][0] # noqa: PLW0129 + assert "chg_total", summary_dict["unique_hops"][0] # noqa: PLW0129
    +
    -if __name__ == "__main__": - unittest.main()
    @@ -404,7 +474,7 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_full_path_mapper< - +

    diff --git a/docs/_modules/pymatgen/analysis/diffusion/neb/tests/test_io.html b/docs/_modules/pymatgen/analysis/diffusion/neb/tests/test_io.html index e16f5de..e72bfdb 100644 --- a/docs/_modules/pymatgen/analysis/diffusion/neb/tests/test_io.html +++ b/docs/_modules/pymatgen/analysis/diffusion/neb/tests/test_io.html @@ -1,15 +1,15 @@ - + - pymatgen.analysis.diffusion.neb.tests.test_io — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.neb.tests.test_io — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -34,7 +34,7 @@

    Navigation

  • modules |
    • -
  • pymatgen-diffusion 2023.8.15 documentation »
    • +
  • pymatgen-diffusion 2024.6.10 documentation »
  • Module code »
  • pymatgen.analysis.diffusion.neb.tests.test_io
    • @@ -64,17 +64,24 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_io

    test_dir = os.path.join(os.path.abspath(os.path.dirname(__file__))) -
    [docs]def get_path(path_str, dirname="./"): +
    +[docs] +def get_path(path_str, dirname="./"): cwd = os.path.abspath(os.path.dirname(__file__)) return os.path.join(cwd, dirname, path_str)
    -
    [docs]class MVLCINEBEndPointSetTest(unittest.TestCase): + +
    +[docs] +class MVLCINEBEndPointSetTest(unittest.TestCase): endpoint = Structure.from_file(get_path("POSCAR0", dirname="io_files")) -
    [docs] def test_incar(self): +
    +[docs] + def test_incar(self): m = MVLCINEBEndPointSet(self.endpoint) - incar_string = m.incar.get_string(sort_keys=True, pretty=True) + incar_string = m.incar.get_str(sort_keys=True, pretty=True) incar_expect = """ALGO = Fast EDIFF = 5e-05 EDIFFG = -0.02 @@ -86,6 +93,7 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_io

    ISPIN = 2 ISYM = 0 LCHARG = False +LDAU = False LMAXMIX = 4 LORBIT = 11 LREAL = Auto @@ -98,7 +106,10 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_io

    SIGMA = 0.05""" assert incar_string == incar_expect
    -
    [docs] def test_incar_user_setting(self): + +
    +[docs] + def test_incar_user_setting(self): user_incar_settings = { "ALGO": "Normal", "EDIFFG": -0.05, @@ -107,7 +118,7 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_io

    "NSW": 100, } m = MVLCINEBEndPointSet(self.endpoint, user_incar_settings=user_incar_settings) - incar_string = m.incar.get_string(sort_keys=True) + incar_string = m.incar.get_str(sort_keys=True) incar_expect = """ALGO = Normal EDIFF = 5e-05 EDIFFG = -0.05 @@ -119,6 +130,7 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_io

    ISPIN = 2 ISYM = 0 LCHARG = False +LDAU = False LMAXMIX = 4 LORBIT = 11 LREAL = Auto @@ -131,19 +143,22 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_io

    NSW = 100 PREC = Accurate SIGMA = 0.05""" - assert incar_string.strip() == incar_expect.strip()
    + assert incar_string.strip() == incar_expect.strip()
    +
    -
    [docs]class MVLCINEBSetTest(unittest.TestCase): - structures = [ - Structure.from_file(get_path("POSCAR" + str(i), dirname="io_files")) - for i in range(3) - ] -
    [docs] def test_incar(self): +
    +[docs] +class MVLCINEBSetTest(unittest.TestCase): + structures = [Structure.from_file(get_path("POSCAR" + str(i), dirname="io_files")) for i in range(3)] + +
    +[docs] + def test_incar(self): m = MVLCINEBSet(self.structures) - incar_string = m.incar.get_string(sort_keys=True) + incar_string = m.incar.get_str(sort_keys=True) incar_expect = """ALGO = Fast EDIFF = 5e-05 EDIFFG = -0.02 @@ -159,6 +174,7 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_io

    ISYM = 0 LCHARG = False LCLIMB = True +LDAU = False LMAXMIX = 4 LORBIT = 0 LREAL = Auto @@ -173,10 +189,13 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_io

    SPRING = -5""" assert incar_string.strip() == incar_expect.strip()
    -
    [docs] def test_incar_user_setting(self): + +
    +[docs] + def test_incar_user_setting(self): user_incar_settings = {"IOPT": 3, "EDIFFG": -0.05, "NPAR": 4, "ISIF": 3} m = MVLCINEBSet(self.structures, user_incar_settings=user_incar_settings) - incar_string = m.incar.get_string(sort_keys=True, pretty=True) + incar_string = m.incar.get_str(sort_keys=True, pretty=True) incar_expect = """ALGO = Fast EDIFF = 5e-05 EDIFFG = -0.05 @@ -192,6 +211,7 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_io

    ISYM = 0 LCHARG = False LCLIMB = True +LDAU = False LMAXMIX = 4 LORBIT = 0 LREAL = Auto @@ -205,43 +225,44 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_io

    PREC = Accurate SIGMA = 0.05 SPRING = -5""" - assert incar_string.strip() == incar_expect.strip()
    + assert incar_string.strip() == incar_expect.strip()
    +
    + -
    [docs]class UtilityTest(unittest.TestCase): +
    +[docs] +class UtilityTest(unittest.TestCase): """ Unit test for outside methods in io.py """ structure = Structure.from_file(get_path("POSCAR", dirname="io_files")) -
    [docs] def test_get_endpoints_from_index(self): - endpoints = get_endpoints_from_index( - structure=self.structure, site_indices=[0, 1] - ) +
    +[docs] + def test_get_endpoints_from_index(self): + endpoints = get_endpoints_from_index(structure=self.structure, site_indices=[0, 1]) ep_0 = endpoints[0].as_dict() ep_1 = endpoints[1].as_dict() - ep_0_expect = Structure.from_file( - get_path("POSCAR_ep0", dirname="io_files") - ).as_dict() - ep_1_expect = Structure.from_file( - get_path("POSCAR_ep1", dirname="io_files") - ).as_dict() + ep_0_expect = Structure.from_file(get_path("POSCAR_ep0", dirname="io_files")).as_dict() + ep_1_expect = Structure.from_file(get_path("POSCAR_ep1", dirname="io_files")).as_dict() assert ep_0 == ep_0_expect assert ep_1 == ep_1_expect
    -
    [docs] def test_get_endpoint_dist(self): + +
    +[docs] + def test_get_endpoint_dist(self): ep0 = Structure.from_file(get_path("POSCAR_ep0", dirname="io_files")) ep1 = Structure.from_file(get_path("POSCAR_ep1", dirname="io_files")) distances = get_endpoint_dist(ep0, ep1) self.assertAlmostEqual(max(distances), 6.3461081051543893, 7) - assert min(distances) == 0.0
    - + assert min(distances) == 0.0
    +
    -if __name__ == "__main__": - unittest.main()
    @@ -256,7 +277,7 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_io

    - +
    diff --git a/docs/_modules/pymatgen/analysis/diffusion/neb/tests/test_pathfinder.html b/docs/_modules/pymatgen/analysis/diffusion/neb/tests/test_pathfinder.html index f5cb264..5782f0f 100644 --- a/docs/_modules/pymatgen/analysis/diffusion/neb/tests/test_pathfinder.html +++ b/docs/_modules/pymatgen/analysis/diffusion/neb/tests/test_pathfinder.html @@ -1,15 +1,15 @@ - + - pymatgen.analysis.diffusion.neb.tests.test_pathfinder — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.neb.tests.test_pathfinder — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -34,7 +34,7 @@

    Navigation

  • modules |
    • -
  • pymatgen-diffusion 2023.8.15 documentation »
    • +
  • pymatgen-diffusion 2024.6.10 documentation »
  • Module code »
  • pymatgen.analysis.diffusion.neb.tests.test_pathfinder
    • @@ -57,11 +57,7 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_pathfinder

    import numpy as np from pymatgen.analysis.diffusion.neb.full_path_mapper import MigrationGraph -from pymatgen.analysis.diffusion.neb.pathfinder import ( - DistinctPathFinder, - IDPPSolver, - MigrationHop, -) +from pymatgen.analysis.diffusion.neb.pathfinder import DistinctPathFinder, IDPPSolver, MigrationHop from pymatgen.analysis.diffusion.utils.supercells import get_start_end_structures from pymatgen.core import Composition, PeriodicSite, Structure from pymatgen.symmetry.analyzer import SpacegroupAnalyzer @@ -72,18 +68,25 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_pathfinder

    __date__ = "March 14, 2017" -
    [docs]def get_path(path_str, dirname="./"): +
    +[docs] +def get_path(path_str, dirname="./"): cwd = os.path.abspath(os.path.dirname(__file__)) return os.path.join(cwd, dirname, path_str)
    -
    [docs]class IDPPSolverTest(unittest.TestCase): + +
    +[docs] +class IDPPSolverTest(unittest.TestCase): init_struct = Structure.from_file(get_path("CONTCAR-0", dirname="pathfinder_files")) final_struct = Structure.from_file( get_path("CONTCAR-1", dirname="pathfinder_files") ) -
    [docs] def test_idpp_from_ep(self): +
    +[docs] + def test_idpp_from_ep(self): obj = IDPPSolver.from_endpoints( [self.init_struct, self.final_struct], nimages=3, sort_tol=1.0 ) @@ -115,7 +118,10 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_pathfinder

    new_path[4][47].frac_coords, np.array([0.59767531, 0.12640952, 0.37745006]) )
    -
    [docs] def test_idpp_from_ep_diff_latt(self): + +
    +[docs] + def test_idpp_from_ep_diff_latt(self): # This is the same test as test_idpp_from_ep where we want to interpolate # different lattices. @@ -213,7 +219,10 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_pathfinder

    ), )
    -
    [docs] def test_idpp(self): + +
    +[docs] + def test_idpp(self): images = self.init_struct.interpolate( self.final_struct, nimages=4, autosort_tol=1.0 ) @@ -238,11 +247,17 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_pathfinder

    ) assert np.allclose( new_path[4][47].frac_coords, np.array([0.59767531, 0.12640952, 0.37745006]) - )
    + )
    +
    -
    [docs]class DistinctPathFinderTest(PymatgenTest): -
    [docs] def test_get_paths(self): + +
    +[docs] +class DistinctPathFinderTest(PymatgenTest): +
    +[docs] + def test_get_paths(self): s = self.get_structure("LiFePO4") # Only one path in LiFePO4 with 4 A. p = DistinctPathFinder(s, "Li", max_path_length=4) @@ -287,16 +302,25 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_pathfinder

    for f in glob.glob("pathfindertest_*.cif"): os.remove(f)
    -
    [docs] def test_max_path_length(self): + +
    +[docs] + def test_max_path_length(self): s = Structure.from_file(get_path("LYPS.cif", dirname="pathfinder_files")) dp1 = DistinctPathFinder(s, "Li", perc_mode="1d") self.assertAlmostEqual(dp1.max_path_length, 4.11375354207, 7) dp2 = DistinctPathFinder(s, "Li", 5, perc_mode="1d") - self.assertAlmostEqual(dp2.max_path_length, 5.0, 7)
    + self.assertAlmostEqual(dp2.max_path_length, 5.0, 7)
    +
    + -
    [docs]class MigrationHopTest(PymatgenTest): -
    [docs] def setUp(self): +
    +[docs] +class MigrationHopTest(PymatgenTest): +
    +[docs] + def setUp(self): self.lifepo = self.get_structure("LiFePO4") m_graph = MigrationGraph.with_distance( self.lifepo, max_distance=4.0, migrating_specie="Li" @@ -309,11 +333,17 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_pathfinder

    symm_structure = a.get_symmetrized_structure() self.m_hop = MigrationHop(i_site, e_site, symm_structure)
    -
    [docs] def test_msonable(self): + +
    +[docs] + def test_msonable(self): hop_dict = self.m_hop.as_dict() - assert type(hop_dict) == dict
    + assert isinstance(hop_dict, dict)
    + -
    [docs] def test_get_start_end_structs_from_hop(self): +
    +[docs] + def test_get_start_end_structs_from_hop(self): dist_ref = self.m_hop.length base = self.lifepo.copy() base.remove_species(["Li"]) @@ -328,7 +358,10 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_pathfinder

    end_site = next(filter(lambda x: x.species_string == "Li", end.sites)) self.assertAlmostEqual(start_site.distance(end_site), dist_ref, 3)
    -
    [docs] def test_get_start_end_structs_from_hop_vac(self): + +
    +[docs] + def test_get_start_end_structs_from_hop_vac(self): dist_ref = self.m_hop.length start, end, b_sc = get_start_end_structures( self.m_hop.isite, @@ -351,7 +384,10 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_pathfinder

    end.remove_sites(s2) self.assertAlmostEqual(start.sites[0].distance(end.sites[0]), dist_ref, 3)
    -
    [docs] def test_get_sc_structures(self): + +
    +[docs] + def test_get_sc_structures(self): dist_ref = self.m_hop.length start, end, b_sc = self.m_hop.get_sc_structures(vac_mode=False) start_site = next(filter(lambda x: x.species_string == "Li", start.sites)) @@ -360,14 +396,15 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_pathfinder

    assert b_sc.composition == Composition("Fe24 P24 O96") self.assertAlmostEqual(start_site.distance(end_site), dist_ref, 3)
    -
    [docs] def test_get_sc_structures_vacmode(self): + +
    +[docs] + def test_get_sc_structures_vacmode(self): start, end, b_sc = self.m_hop.get_sc_structures(vac_mode=True) assert start.composition == end.composition == Composition("Li23 Fe24 P24 O96") - assert b_sc.composition == Composition("Li24 Fe24 P24 O96")
    - + assert b_sc.composition == Composition("Li24 Fe24 P24 O96")
    +
    -if __name__ == "__main__": - unittest.main()
    @@ -382,7 +419,7 @@

    Source code for pymatgen.analysis.diffusion.neb.tests.test_pathfinder

    - +
    diff --git a/docs/_modules/pymatgen/analysis/diffusion/tests/test_analyzer.html b/docs/_modules/pymatgen/analysis/diffusion/tests/test_analyzer.html index 08c7665..3dcb23a 100644 --- a/docs/_modules/pymatgen/analysis/diffusion/tests/test_analyzer.html +++ b/docs/_modules/pymatgen/analysis/diffusion/tests/test_analyzer.html @@ -1,15 +1,15 @@ - + - pymatgen.analysis.diffusion.tests.test_analyzer — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.tests.test_analyzer — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -34,7 +34,7 @@

    Navigation

  • modules |
    • -
  • pymatgen-diffusion 2023.8.15 documentation »
    • +
  • pymatgen-diffusion 2024.6.10 documentation »
  • Module code »
  • pymatgen.analysis.diffusion.tests.test_analyzer
    • @@ -59,11 +59,7 @@

    Source code for pymatgen.analysis.diffusion.tests.test_analyzer

    import pytest import scipy.constants as const -from pymatgen.analysis.diffusion.analyzer import ( - DiffusionAnalyzer, - fit_arrhenius, - get_conversion_factor, -) +from pymatgen.analysis.diffusion.analyzer import DiffusionAnalyzer, fit_arrhenius, get_conversion_factor from pymatgen.core.lattice import Lattice from pymatgen.core.structure import Structure from pymatgen.util.testing import PymatgenTest @@ -71,15 +67,22 @@

    Source code for pymatgen.analysis.diffusion.tests.test_analyzer

    module_dir = os.path.dirname(os.path.abspath(__file__)) -
    [docs]class FuncTest(PymatgenTest): -
    [docs] def test_get_conversion_factor(self): +
    +[docs] +class FuncTest(PymatgenTest): +
    +[docs] + def test_get_conversion_factor(self): s = PymatgenTest.get_structure("LiFePO4") # large tolerance because scipy constants changed between 0.16.1 and 0.17 self.assertAlmostEqual( 41370704.343540139, get_conversion_factor(s, "Li", 600), delta=20 )
    -
    [docs] def test_fit_arrhenius(self): + +
    +[docs] + def test_fit_arrhenius(self): Ea = 0.5 k = const.k / const.e c = 12 @@ -95,11 +98,17 @@

    Source code for pymatgen.analysis.diffusion.tests.test_analyzer

    r2 = fit_arrhenius([1, 2], [10, 10]) self.assertAlmostEqual(r2[0], 0) self.assertAlmostEqual(r2[1], 10) - assert r2[2] is None
    + assert r2[2] is None
    +
    + -
    [docs]class DiffusionAnalyzerTest(PymatgenTest): -
    [docs] def test_init(self): +
    +[docs] +class DiffusionAnalyzerTest(PymatgenTest): +
    +[docs] + def test_init(self): # Diffusion vasprun.xmls are rather large. We are only going to use a # very small preprocessed run for testing. Note that the results are # unreliable for short runs. @@ -253,7 +262,7 @@

    Source code for pymatgen.analysis.diffusion.tests.test_analyzer

    self.assertAlmostEqual(d.chg_conductivity, 1.06440821953e-09, 4) # Can't average over 2000 steps because this is a 1000-step run. - self.assertRaises( + self.assertRaises( # noqa: PT027 ValueError, DiffusionAnalyzer, d.structure, @@ -290,7 +299,10 @@

    Source code for pymatgen.analysis.diffusion.tests.test_analyzer

    assert data[:, -1] == pytest.approx(d.mscd) os.remove("test.csv")
    -
    [docs] def test_init_npt(self): + +
    +[docs] + def test_init_npt(self): # Diffusion vasprun.xmls are rather large. We are only going to use a # very small preprocessed run for testing. Note that the results are # unreliable for short runs. @@ -475,7 +487,7 @@

    Source code for pymatgen.analysis.diffusion.tests.test_analyzer

    self.assertAlmostEqual(d.chg_conductivity, 554.5240271992852, 6) # Can't average over 2000 steps because this is a 1000-step run. - self.assertRaises( + self.assertRaises( # noqa: PT027 ValueError, DiffusionAnalyzer, d.structure, @@ -514,7 +526,10 @@

    Source code for pymatgen.analysis.diffusion.tests.test_analyzer

    assert data[:, -1] == pytest.approx(d.mscd) os.remove("test.csv")
    -
    [docs] def test_from_structure_NPT(self): + +
    +[docs] + def test_from_structure_NPT(self): coords1 = np.array([[0.0, 0.0, 0.0], [0.5, 0.5, 0.5]]) coords2 = np.array([[0.0, 0.0, 0.0], [0.6, 0.6, 0.6]]) coords3 = np.array([[0.0, 0.0, 0.0], [0.7, 0.7, 0.7]]) @@ -541,7 +556,9 @@

    Source code for pymatgen.analysis.diffusion.tests.test_analyzer

    ) assert d.disp[1] == pytest.approx( np.array([[0.0, 0.0, 0.0], [0.21, 0.21, 0.21], [0.40, 0.40, 0.40]]) - )
    + )
    +
    +
    @@ -556,7 +573,7 @@

    Source code for pymatgen.analysis.diffusion.tests.test_analyzer

    - +
    diff --git a/docs/_modules/pymatgen/analysis/diffusion/tests/test_pathfinder.html b/docs/_modules/pymatgen/analysis/diffusion/tests/test_pathfinder.html index 5788e44..86616df 100644 --- a/docs/_modules/pymatgen/analysis/diffusion/tests/test_pathfinder.html +++ b/docs/_modules/pymatgen/analysis/diffusion/tests/test_pathfinder.html @@ -1,15 +1,15 @@ - + - pymatgen.analysis.diffusion.tests.test_pathfinder — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.tests.test_pathfinder — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -34,7 +34,7 @@

    Navigation

  • modules |
    • -
  • pymatgen-diffusion 2023.8.15 documentation »
    • +
  • pymatgen-diffusion 2024.6.10 documentation »
  • Module code »
  • pymatgen.analysis.diffusion.tests.test_pathfinder
    • @@ -57,14 +57,20 @@

    Source code for pymatgen.analysis.diffusion.tests.test_pathfinder

    module_dir = os.path.dirname(os.path.abspath(__file__)) -
    [docs]class PathfinderTest(PymatgenTest): -
    [docs] def test_mhop_msonable(self): +
    +[docs] +class PathfinderTest(PymatgenTest): +
    +[docs] + def test_mhop_msonable(self): file_path = os.path.join(module_dir, "migration_graph_spinel_MgMn2O4.json") spinel_mg = loadfn(file_path) hop = spinel_mg.unique_hops[0]["hop"] hop_dict = hop.as_dict() - assert type(hop_dict) == dict
    + assert isinstance(hop_dict, dict)
    +
    +
    @@ -79,7 +85,7 @@

    Source code for pymatgen.analysis.diffusion.tests.test_pathfinder

    - +
    diff --git a/docs/_modules/pymatgen/analysis/diffusion/utils/edge_data_from_sc.html b/docs/_modules/pymatgen/analysis/diffusion/utils/edge_data_from_sc.html index ae83adf..0d5fa99 100644 --- a/docs/_modules/pymatgen/analysis/diffusion/utils/edge_data_from_sc.html +++ b/docs/_modules/pymatgen/analysis/diffusion/utils/edge_data_from_sc.html @@ -1,15 +1,15 @@ - + - pymatgen.analysis.diffusion.utils.edge_data_from_sc — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.utils.edge_data_from_sc — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -34,7 +34,7 @@

    Navigation

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    • -
  • pymatgen-diffusion 2023.8.15 documentation »
    • +
  • pymatgen-diffusion 2024.6.10 documentation »
  • Module code »
  • pymatgen.analysis.diffusion.utils.edge_data_from_sc
    • @@ -49,9 +49,8 @@

    Source code for pymatgen.analysis.diffusion.utils.edge_data_from_sc

    # Copyright (c) Materials Virtual Lab. # Distributed under the terms of the BSD License. -""" -Function to add edge data to MigrationGraph through 2 SC structures -""" +"""Function to add edge data to MigrationGraph through 2 SC structures.""" + from __future__ import annotations __author__ = "Haoming Li" @@ -64,13 +63,8 @@

    Source code for pymatgen.analysis.diffusion.utils.edge_data_from_sc

    import numpy as np -from pymatgen.analysis.diffusion.neb.full_path_mapper import ( - MigrationGraph, - MigrationHop, -) -from pymatgen.analysis.diffusion.utils.parse_entries import ( - get_matched_structure_mapping, -) +from pymatgen.analysis.diffusion.neb.full_path_mapper import MigrationGraph, MigrationHop +from pymatgen.analysis.diffusion.utils.parse_entries import get_matched_structure_mapping from pymatgen.analysis.structure_matcher import StructureMatcher from pymatgen.core.structure import PeriodicSite, Structure from pymatgen.symmetry.analyzer import SpacegroupAnalyzer @@ -78,7 +72,9 @@

    Source code for pymatgen.analysis.diffusion.utils.edge_data_from_sc

    logger = logging.getLogger(__name__) -
    [docs]def add_edge_data_from_sc( +
    +[docs] +def add_edge_data_from_sc( mg: MigrationGraph, i_sc: Structure, e_sc: Structure, @@ -87,15 +83,17 @@

    Source code for pymatgen.analysis.diffusion.utils.edge_data_from_sc

    use_host_sg: bool = True, ) -> None: """ - Add a data entry and key to edges within FullPathMapper object with the same hop_label. - These hops are equivalent by symmetry to the 2 positions given in the supercell structures. + Add a data entry and key to edges within FullPathMapper object with the same + hop_label. These hops are equivalent by symmetry to the 2 positions given in the + supercell structures. Args: + mg: MigrationGraph object. i_sc: Supercell structure containing working ion at initial position e_sc: Supercell structure containing working ion at ending position data_array: The data to be added to the edges key: Key of the edge attribute to be added - use_host_sg: Flag t whether or not to use the host structure's spacegroup to initiate MigrationHop + use_host_sg: Flag whether to use the host structure's spacegroup to initiate MigrationHop Returns: None @@ -104,30 +102,29 @@

    Source code for pymatgen.analysis.diffusion.utils.edge_data_from_sc

    i_wi = [x for x in i_sc.sites if x.species_string == wi] e_wi = [x for x in e_sc.sites if x.species_string == wi] if len(i_wi) != 1 or len(e_wi) != 1: - raise ValueError( - "The number of working ions in each supercell structure should be one" - ) + raise ValueError("The number of working ions in each supercell structure should be one") isite, esite = i_wi[0], e_wi[0] uhop_index, mh_from_sc = get_unique_hop(mg, i_sc, isite, esite, use_host_sg) add_dict = {key: data_array} - mg.add_data_to_similar_edges( - target_label=uhop_index, data=add_dict, m_hop=mh_from_sc - )
    + mg.add_data_to_similar_edges(target_label=uhop_index, data=add_dict, m_hop=mh_from_sc)
    -
    [docs]def get_uc_pos( + +
    +[docs] +def get_uc_pos( isite: PeriodicSite, esite: PeriodicSite, uc: Structure, sc: Structure, sm: StructureMatcher, ) -> tuple[PeriodicSite, PeriodicSite, PeriodicSite]: - """Take positions in the supercel and transform into the unitcell positions + """Take positions in the supercell and transform into the unit cell positions. Args: isite: initial site in the SC esite: ending site in the SC - uc: Unit Cell structre + uc: Unit Cell structure sc: Super Cell structure sm: StructureMatcher object with the working ion ignored @@ -136,10 +133,7 @@

    Source code for pymatgen.analysis.diffusion.utils.edge_data_from_sc

    """ mapping = get_matched_structure_mapping(base=uc, inserted=sc, sm=sm) if mapping is None: - raise ValueError( - "Cannot obtain inverse mapping, consider lowering tolerances " - "in StructureMatcher" - ) + raise ValueError("Cannot obtain inverse mapping, consider lowering tolerances " "in StructureMatcher") sc_m, total_t = mapping sc_ipos = isite.frac_coords sc_ipos_t = sc_ipos - total_t @@ -172,19 +166,20 @@

    Source code for pymatgen.analysis.diffusion.utils.edge_data_from_sc

    return p0, p1, p2
    + def _get_first_close_site(frac_coord, structure, stol=0.1): for site in structure.sites: - dist, image = structure.lattice.get_distance_and_image( - frac_coord, site.frac_coords - ) + dist, image = structure.lattice.get_distance_and_image(frac_coord, site.frac_coords) if dist < stol: return np.add(site.frac_coords, image) return frac_coord -
    [docs]def mh_eq(mh1, mh2): +
    +[docs] +def mh_eq(mh1, mh2): """ - Allow for symmetric matching of MigrationPath objects with variable precession + Allow for symmetric matching of MigrationPath objects with variable precession. Args: mh1: MigrationHop object @@ -197,35 +192,33 @@

    Source code for pymatgen.analysis.diffusion.utils.edge_data_from_sc

    return mh1 == mh2
    -
    [docs]def get_unique_hop( + +
    +[docs] +def get_unique_hop( mg: MigrationGraph, sc: Structure, isite: PeriodicSite, esite: PeriodicSite, use_host_sg: bool = True, ) -> tuple[int, MigrationHop]: - """Get the unique hop label that correspond to two end positions in the SC + """Get the unique hop label that correspond to two end positions in the SC. Args: mg: Object containing the migration analysis sc: Structure of the supercell used for the NEB calculation isite: Initial position in the supercell esite: Final position in the supercell - use_host_sg: Flag t whether or not to use the host structure's spacegroup to initiate MigrationHop + use_host_sg: Flag t whether or not to use the host structure's spacegroup to + initiate MigrationHop Returns: - The index of the unique hop, the MigrationHop object trasformed from the SC + The index of the unique hop, the MigrationHop object transformed from the SC """ - sm = StructureMatcher( - ignored_species=[ - next(iter(mg.m_graph.graph.edges(data=True)))[2]["hop"].isite.specie.name - ] - ) + sm = StructureMatcher(ignored_species=[next(iter(mg.m_graph.graph.edges(data=True)))[2]["hop"].isite.specie.name]) uc_isite, uc_msite, uc_esite = get_uc_pos(isite, esite, mg.symm_structure, sc, sm) if use_host_sg: - base_ss = SpacegroupAnalyzer( - mg.host_structure, symprec=mg.symprec - ).get_symmetrized_structure() + base_ss = SpacegroupAnalyzer(mg.host_structure, symprec=mg.symprec).get_symmetrized_structure() mh_from_sc = MigrationHop( uc_isite, uc_esite, @@ -234,9 +227,7 @@

    Source code for pymatgen.analysis.diffusion.utils.edge_data_from_sc

    symprec=mg.symprec, ) else: - mh_from_sc = MigrationHop( - uc_isite, uc_esite, symm_structure=mg.symm_structure, symprec=mg.symprec - ) + mh_from_sc = MigrationHop(uc_isite, uc_esite, symm_structure=mg.symm_structure, symprec=mg.symprec) result = [] for k, v in mg.unique_hops.items(): # tolerance may be changed here @@ -248,10 +239,9 @@

    Source code for pymatgen.analysis.diffusion.utils.edge_data_from_sc

    if len(result) == 0: raise ValueError("No matches between UC and SC") - assert mg.symm_structure.spacegroup.are_symmetrically_equivalent( - [uc_msite], [mh_from_sc.msite] - ) + assert mg.symm_structure.spacegroup.are_symmetrically_equivalent([uc_msite], [mh_from_sc.msite]) return result[0], mh_from_sc
    +
    @@ -266,7 +256,7 @@

    Source code for pymatgen.analysis.diffusion.utils.edge_data_from_sc

    - +
    diff --git a/docs/_modules/pymatgen/analysis/diffusion/utils/maggma.html b/docs/_modules/pymatgen/analysis/diffusion/utils/maggma.html index b754539..cab8098 100644 --- a/docs/_modules/pymatgen/analysis/diffusion/utils/maggma.html +++ b/docs/_modules/pymatgen/analysis/diffusion/utils/maggma.html @@ -1,15 +1,15 @@ - + - pymatgen.analysis.diffusion.utils.maggma — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.utils.maggma — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -34,7 +34,7 @@

    Navigation

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    • -
  • pymatgen-diffusion 2023.8.15 documentation »
    • +
  • pymatgen-diffusion 2024.6.10 documentation »
  • Module code »
  • pymatgen.analysis.diffusion.utils.maggma
    • @@ -51,8 +51,9 @@

    Source code for pymatgen.analysis.diffusion.utils.maggma

    """ Functions for querying Materials Project style MongoStores that contains cathode materials The functions are isolated from the rest of the package so -that the rest of the package will not depend on Maggma +that the rest of the package will not depend on Maggma. """ + from __future__ import annotations __author__ = "Jimmy Shen" @@ -74,7 +75,9 @@

    Source code for pymatgen.analysis.diffusion.utils.maggma

    logger.setLevel(logging.INFO) -
    [docs]def get_entries_from_dbs( +
    +[docs] +def get_entries_from_dbs( structure_group_store: MongoStore, material_store: MongoStore, migrating_ion: str, @@ -87,12 +90,11 @@

    Source code for pymatgen.analysis.diffusion.utils.maggma

    Args: structure_group_store: Electrode documents one per each similar group of insertion materials, can also use any db that contains a - material_store: Material documenets one per each similar structure ( + material_store: Material documents one per each similar structure ( multiple tasks) migrating_ion: The name of the migrating ion - material_ids list with topotactic structures + material_id: Material id """ - with structure_group_store as store: sg_doc = store.query_one({structure_group_store.key: material_id}) ignored_species = migrating_ion @@ -113,6 +115,7 @@

    Source code for pymatgen.analysis.diffusion.utils.maggma

    base_entries.append(entry) return base_entries, inserted_entries
    +
    @@ -127,7 +130,7 @@

    Source code for pymatgen.analysis.diffusion.utils.maggma

    +
    diff --git a/docs/_modules/pymatgen/analysis/diffusion/utils/parse_entries.html b/docs/_modules/pymatgen/analysis/diffusion/utils/parse_entries.html index b0de48c..277924d 100644 --- a/docs/_modules/pymatgen/analysis/diffusion/utils/parse_entries.html +++ b/docs/_modules/pymatgen/analysis/diffusion/utils/parse_entries.html @@ -1,15 +1,15 @@ - + - pymatgen.analysis.diffusion.utils.parse_entries — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.utils.parse_entries — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -34,7 +34,7 @@

    Navigation

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  • pymatgen-diffusion 2023.8.15 documentation »
    • +
  • pymatgen-diffusion 2024.6.10 documentation »
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  • pymatgen.analysis.diffusion.utils.parse_entries
    • @@ -49,9 +49,8 @@

    Source code for pymatgen.analysis.diffusion.utils.parse_entries

    # Copyright (c) Materials Virtual Lab. # Distributed under the terms of the BSD License. -""" -Functions for combining many ComputedEntry objects into MigrationGraph objects. -""" +"""Functions for combining many ComputedEntry objects into MigrationGraph objects.""" + from __future__ import annotations import logging @@ -82,7 +81,9 @@

    Source code for pymatgen.analysis.diffusion.utils.parse_entries

    logger.setLevel(logging.INFO) -
    [docs]def process_entries( +
    +[docs] +def process_entries( base_entries: list[ComputedStructureEntry], inserted_entries: list[ComputedStructureEntry], migrating_ion_entry: ComputedEntry, @@ -92,25 +93,28 @@

    Source code for pymatgen.analysis.diffusion.utils.parse_entries

    angle_tol: float = 5.0, ) -> list[dict]: """ - Process a list of base entries and inserted entries to create input for migration path analysis Each inserted - entries can be mapped to more than one base entry. Return groups of structures decorated with the working ions - to indicate the metastable sites, ranked by the number of working ion sites (highest number is the first). + Process a list of base entries and inserted entries to create input for migration + path analysis Each inserted entries can be mapped to more than one base entry. + Return groups of structures decorated with the working ions to indicate the + metastable sites, ranked by the number of working ion sites (highest number is the + first). Args: - base_entries: Full list of base entires - inserted_entries: Full list of inserted entires - migrating_ion_entry: The metallic phase of the working ion, used to calculate insertion energies. + base_entries: Full list of base entries + inserted_entries: Full list of inserted entries + migrating_ion_entry: The metallic phase of the working ion, used to calculate + insertion energies. symprec: symmetry parameter for SpacegroupAnalyzer ltol: Fractional length tolerance for StructureMatcher stol: Site tolerance for StructureMatcher - angle_tol: Angle tolerance fro StructureMatcher and SpacegroupAnalyzer + angle_tol: Angle tolerance for StructureMatcher and SpacegroupAnalyzer only_single_cat: If True, only use single cation insertions so the site energy is more accurate use_strict_tol: halve the ltol and stol parameter for more strict matching. Returns: - list: List of dictionaries that each contain - {'base' : Structure Object of host, 'inserted' : Structure object of all inserted sites} + list: List of dictionaries that each contain {'base': Structure Object of host, + 'inserted': Structure object of all inserted sites} """ working_ion = str(migrating_ion_entry.composition.elements[0]) sm_no_wion = StructureMatcher( @@ -124,23 +128,16 @@

    Source code for pymatgen.analysis.diffusion.utils.parse_entries

    # grouping of inserted structures with base structures all_sga = [ - SpacegroupAnalyzer( - itr_base_ent.structure, symprec=symprec, angle_tolerance=angle_tol - ) + SpacegroupAnalyzer(itr_base_ent.structure, symprec=symprec, angle_tolerance=angle_tol) for itr_base_ent in base_entries ] entries_with_num_symmetry_ops = [ - (ient, len(all_sga[itr_ent].get_space_group_operations())) - for itr_ent, ient in enumerate(base_entries) + (ient, len(all_sga[itr_ent].get_space_group_operations())) for itr_ent, ient in enumerate(base_entries) ] - entries_with_num_symmetry_ops = sorted( - entries_with_num_symmetry_ops, key=lambda x: x[0].energy_per_atom - ) - entries_with_num_symmetry_ops = sorted( - entries_with_num_symmetry_ops, key=lambda x: x[1], reverse=True - ) + entries_with_num_symmetry_ops = sorted(entries_with_num_symmetry_ops, key=lambda x: x[0].energy_per_atom) + entries_with_num_symmetry_ops = sorted(entries_with_num_symmetry_ops, key=lambda x: x[1], reverse=True) entries_with_num_symmetry_ops = sorted( entries_with_num_symmetry_ops, key=lambda x: x[0].structure.num_sites, @@ -170,14 +167,13 @@

    Source code for pymatgen.analysis.diffusion.utils.parse_entries

    struct_wo_sym_ops = _filter_and_merge(mapped_cell.get_sorted_structure()) if struct_wo_sym_ops is None: logger.warning( - f"No meta-stable sites were found during symmetry mapping for base {base_ent.entry_id}." - "Consider playing with the various tolerances (ltol, stol, angle_tol)." + f"No meta-stable sites were found during symmetry mapping for base " + f"{base_ent.entry_id}. Consider playing with the various tolerances " + "(ltol, stol, angle_tol)." ) continue - struct_sym = get_sym_migration_ion_sites( - base_ent.structure, struct_wo_sym_ops, working_ion - ) + struct_sym = get_sym_migration_ion_sites(base_ent.structure, struct_wo_sym_ops, working_ion) results.append( { "base": base_ent.structure, @@ -186,14 +182,13 @@

    Source code for pymatgen.analysis.diffusion.utils.parse_entries

    ) results = filter(lambda x: len(x["inserted"]) != 0, results) # type: ignore - return sorted( - results, key=lambda x: x["inserted"].composition[working_ion], reverse=True - )
    + return sorted(results, key=lambda x: x["inserted"].composition[working_ion], reverse=True)
    + -
    [docs]def get_matched_structure_mapping( - base: Structure, inserted: Structure, sm: StructureMatcher -): +
    +[docs] +def get_matched_structure_mapping(base: Structure, inserted: Structure, sm: StructureMatcher): """ Get the mapping from the inserted structure onto the base structure, assuming that the inserted structure sans the working ion is some kind @@ -211,9 +206,7 @@

    Source code for pymatgen.analysis.diffusion.utils.parse_entries

    s1, s2 = sm._process_species([base, inserted]) fu, _ = sm._get_supercell_size(s1, s2) try: - val, dist, sc_m, total_t, mapping = sm._strict_match( - s1, s2, fu=fu, s1_supercell=True - ) + val, dist, sc_m, total_t, mapping = sm._strict_match(s1, s2, fu=fu, s1_supercell=True) except TypeError: return None sc = s1 * sc_m @@ -221,17 +214,21 @@

    Source code for pymatgen.analysis.diffusion.utils.parse_entries

    return sc_m, total_t
    -
    [docs]def get_inserted_on_base( + +
    +[docs] +def get_inserted_on_base( base_ent: ComputedStructureEntry, inserted_ent: ComputedStructureEntry, migrating_ion_entry: ComputedEntry, sm: StructureMatcher, ) -> Structure | None: """ - For a structured-matched pair of base and inserted entries, map all of the Li positions in the inserted entry to - positions in the base entry and return a new structure where all the sites are decorated with the insertion - energy. Since the calculation of the insertion energy needs the energy of the metallic working ion, - a `migrating_ion_entry` must also be provided. + For a structured-matched pair of base and inserted entries, map all of the Li + positions in the inserted entry to positions in the base entry and return a new + structure where all the sites are decorated with the insertion energy. Since the + calculation of the insertion energy needs the energy of the metallic working ion, a + `migrating_ion_entry` must also be provided. Args: base_ent: The entry for the host structure @@ -242,9 +239,7 @@

    Source code for pymatgen.analysis.diffusion.utils.parse_entries

    Returns: List of entries for each working ion in the list of """ - mapped_result = get_matched_structure_mapping( - base_ent.structure, inserted_ent.structure, sm - ) + mapped_result = get_matched_structure_mapping(base_ent.structure, inserted_ent.structure, sm) if mapped_result is None: return None @@ -267,7 +262,10 @@

    Source code for pymatgen.analysis.diffusion.utils.parse_entries

    return new_struct
    -
    [docs]def get_sym_migration_ion_sites( + +
    +[docs] +def get_sym_migration_ion_sites( base_struct: Structure, inserted_struct: Structure, migrating_ion: str, @@ -275,13 +273,14 @@

    Source code for pymatgen.analysis.diffusion.utils.parse_entries

    angle_tol: float = 5.0, ) -> Structure: """ - Take one inserted entry then map out all symmetry equivalent copies of the cation sites in base entry. - Each site is decorated with the insertion energy calculated from the base and inserted entries. + Take one inserted entry then map out all symmetry equivalent copies of the cation + sites in base entry. Each site is decorated with the insertion energy calculated + from the base and inserted entries. Args: - inserted_entry: entry that contains cation - base_struct_entry: the entry containing the base structure - migrating_ion_entry: the name of the migrating species + base_struct: the base structure. + inserted_struct: inserted structure. + migrating_ion: Ion that migrates. symprec: the symprec tolerance for the space group analysis angle_tol: the angle tolerance for the space group analysis @@ -302,7 +301,7 @@

    Source code for pymatgen.analysis.diffusion.utils.parse_entries

    sym_migration_struct = Structure.from_sites(sym_migration_ion_sites) for op in sa.get_space_group_operations(): struct_tmp = sym_migration_struct.copy() - struct_tmp.apply_operation(symmop=op, fractional=True) + struct_tmp.apply_operation(op, fractional=True) for isite in struct_tmp.sites: if isite.species_string == wi_: sym_migration_struct.insert( @@ -314,24 +313,22 @@

    Source code for pymatgen.analysis.diffusion.utils.parse_entries

    # must clean up as you go or the number of sites explodes if len(sym_migration_struct) > 1: - sym_migration_struct.merge_sites( - tol=SITE_MERGE_R, mode="average" - ) # keeps removing duplicates + sym_migration_struct.merge_sites(tol=SITE_MERGE_R, mode="average") # keeps removing duplicates return sym_migration_struct
    + def _filter_and_merge(inserted_structure: Structure) -> Structure | None: """ - For each site in a structure, split it into a migration sublattice where all sites contain the "insertion_energy" - property and a host lattice. For each site in the migration sublattice if there is collision with the host sites, - remove the migration site. Finally merge all the migration sites. + For each site in a structure, split it into a migration sublattice where all sites + contain the "insertion_energy" property and a host lattice. For each site in the + migration sublattice if there is collision with the host sites, remove the migration + site. Finally merge all the migration sites. """ migration_sites = [] base_sites = [] for i_site in inserted_structure: - if "insertion_energy" in i_site.properties and isinstance( - i_site.properties["insertion_energy"], float - ): + if "insertion_energy" in i_site.properties and isinstance(i_site.properties["insertion_energy"], float): migration_sites.append(i_site) else: base_sites.append(i_site) @@ -350,7 +347,9 @@

    Source code for pymatgen.analysis.diffusion.utils.parse_entries

    return res -
    [docs]def get_insertion_energy( +
    +[docs] +def get_insertion_energy( base_entry: ComputedStructureEntry, inserted_entry: ComputedStructureEntry, migrating_ion_entry: ComputedEntry, @@ -362,9 +361,11 @@

    Source code for pymatgen.analysis.diffusion.utils.parse_entries

    inserted_entry: The entry for the inserted structure migrating_ion_entry: The entry for the metallic phase of the working ion Returns: - The insertion energy defined as (E[inserted] - (E[Base] + n * E[working_ion]))/(n) + float: insertion energy defined as + (E[inserted] - (E[Base] + n * E[working_ion])) / n Where n is the number of working ions and E[inserted]. - Additionally, and E[base] and E[inserted] are for structures of the same size (sans working ion) + Additionally, and E[base] and E[inserted] are for structures of the same size + (sans working ion). """ wi_ = str(migrating_ion_entry.composition.elements[0]) comp_inserted_no_wi = inserted_entry.composition.as_dict() @@ -378,6 +379,7 @@

    Source code for pymatgen.analysis.diffusion.utils.parse_entries

    n_wi = inserted_entry.composition[wi_] return (e_insert - (e_base + n_wi * e_wi)) / n_wi
    +
    @@ -392,7 +394,7 @@

    Source code for pymatgen.analysis.diffusion.utils.parse_entries

    - +
    diff --git a/docs/_modules/pymatgen/analysis/diffusion/utils/supercells.html b/docs/_modules/pymatgen/analysis/diffusion/utils/supercells.html index a8a7a25..8a2a506 100644 --- a/docs/_modules/pymatgen/analysis/diffusion/utils/supercells.html +++ b/docs/_modules/pymatgen/analysis/diffusion/utils/supercells.html @@ -1,15 +1,15 @@ - + - pymatgen.analysis.diffusion.utils.supercells — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.utils.supercells — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -34,7 +34,7 @@

    Navigation

  • modules |
    • -
  • pymatgen-diffusion 2023.8.15 documentation »
    • +
  • pymatgen-diffusion 2024.6.10 documentation »
  • Module code »
  • pymatgen.analysis.diffusion.utils.supercells
    • @@ -46,11 +46,8 @@

    Navigation

    Source code for pymatgen.analysis.diffusion.utils.supercells

    -# Copyright (c) Materials Virtual Lab.
-# Distributed under the terms of the BSD License.
-"""
-Functions for creating supercells for NEB calculations
-"""
+"""Functions for creating supercells for NEB calculations."""
+
 from __future__ import annotations
 
 import logging
@@ -60,9 +57,7 @@ 
    Source code for pymatgen.analysis.diffusion.utils.supercells
    # from ase.build import find_optimal_cell_shape, get_deviation_from_optimal_cell_shape
 # from pymatgen.io.ase import AseAtomsAdaptor
 from pymatgen.core import PeriodicSite, Structure
-from pymatgen.transformations.advanced_transformations import (
-    CubicSupercellTransformation,
-)
+from pymatgen.transformations.advanced_transformations import CubicSupercellTransformation
 
 __author__ = "Jimmy Shen"
 __copyright__ = "Copyright 2019, The Materials Project"
@@ -72,10 +67,12 @@ 
    Source code for pymatgen.analysis.diffusion.utils.supercells
    logger = logging.getLogger(__name__)
 
-# Helper functions for MigraionHop.get_sc_struture
+# Helper functions for MigrationHop.get_sc_struture
 
 
-
    [docs]def get_sc_fromstruct(
+
    
+[docs]
+def get_sc_fromstruct(
     base_struct: Structure,
     min_atoms: int = 80,
     max_atoms: int = 240,
@@ -105,6 +102,7 @@ 
    Source code for pymatgen.analysis.diffusion.utils.supercells
    return struct_sc
    
 
 
+
 def _get_sc_from_struct_pmg(
     base_struct: Structure,
     min_atoms: int = 80,
@@ -112,7 +110,7 @@ 
    Source code for pymatgen.analysis.diffusion.utils.supercells
    min_length: float = 10.0,
 ) -> list[list[int]] | None:
     """
-    Generate the best supercell from a unitcell using the pymatgen CubicSupercellTransformation
+    Generate the best supercell from a unitcell using the pymatgen CubicSupercellTransformation.
 
     Args:
         base_struct: structure of the unit cell
@@ -124,9 +122,7 @@ 
    Source code for pymatgen.analysis.diffusion.utils.supercells
            3x3 matrix: supercell matrix
 
     """
-    cst = CubicSupercellTransformation(
-        min_atoms=min_atoms, max_atoms=max_atoms, min_length=min_length
-    )
+    cst = CubicSupercellTransformation(min_atoms=min_atoms, max_atoms=max_atoms, min_length=min_length)
 
     try:
         cst.apply_transformation(base_struct)
@@ -135,54 +131,9 @@ 
    Source code for pymatgen.analysis.diffusion.utils.supercells
    return cst.transformation_matrix
 
 
-# Something is broken with how ASE generates supercells
-# now many calls to `find_optimal_cell_shape` results in
-# `Failed to find a transformation matrix`
-# So remove this funtionality now in favour of decreasing the max_length
-#
-# def _get_sc_from_struct_ase(
-#     base_struct: Structure, min_atoms: int=80, max_atoms: int=240
-# ) -> List[List[int]]:
-#     """generate the best supercell from a unitcell using ASE's method, is slower but more exhaustive
-#
-#     Args:
-#         base_struct (pymatgen.Structure): unit cell
-#         min_atoms (int, optional): Minimum number of atoms in the desired supercell. Defaults to 80.
-#
-#     Returns:
-#         3x3 matrix: supercell matrix
-#     """
-#
-#     num_cells_min = int(np.ceil(min_atoms / base_struct.num_sites))
-#     num_cells_max = int(np.ceil(max_atoms / base_struct.num_sites))
-#
-#     atoms = AseAtomsAdaptor().get_atoms(base_struct)
-#     res = []
-#     for icell in range(num_cells_min, num_cells_max):
-#         if icell % 2 != 0 and icell % 3 != 0:
-#             continue  # cells with many factors are more likely to be square
-#         logger.info(f"Getting cell shape {icell} x unit cell")
-#         sc_mat = find_optimal_cell_shape(atoms.cell, icell, "sc")
-#         if sc_mat is None:
-#             continue
-#         deviation = get_deviation_from_optimal_cell_shape(np.dot(sc_mat, atoms.cell))
-#         dd = {"deviation": deviation, "P1": sc_mat}
-#         # base_struct_sc.to('poscar', f'/Users/lik/Desktop/enpoints_{base_struct_sc.num_sites}.vasp')
-#         res.append(dd)
-#         if deviation < 0.3:
-#             logger.debug("Found good cell")
-#             return sc_mat
-#
-#     else:
-#         best_case = min(res, key=lambda x: x["deviation"])
-#     logger.warning(
-#         f"Could not find case with deviation from cubic was less than 0.3 using the ASE cubic supercell finder \
-#         \nThe best one had a deviation of {best_case['deviation']}"
-#     )
-#     return best_case["P1"]
-
-
-
    [docs]def get_start_end_structures(
+
    
+[docs]
+def get_start_end_structures(
     isite: PeriodicSite,
     esite: PeriodicSite,
     base_struct: Structure,
@@ -195,10 +146,14 @@ 
    Source code for pymatgen.analysis.diffusion.utils.supercells
        Obtain the starting and terminating structures in a supercell for NEB calculations.
 
     Args:
+        isite: Initial site index.
+        esite: End site index.
         hop: object presenting the migration event
         base_struct: unit cell representation of the structure
         sc_mat: supercell transformation to create the simulation cell for the NEB calc
-        tol: toleranace for identifying isite/esite within base_struct
+        vac_mode: Vacuum mode.
+        debug: debug mode.
+        tol: toleranace for identifying isite/esite within base_struct.
 
     Returns:
         initial structure, final structure, empty structure all in the supercell
@@ -240,22 +195,13 @@ 
    Source code for pymatgen.analysis.diffusion.utils.supercells
    if debug:
             icart = base_sc.lattice.get_cartesian_coords(ipos_sc)
             ecart = base_sc.lattice.get_cartesian_coords(epos_sc)
-            assert (
-                abs(
-                    np.linalg.norm(icart - ecart)
-                    - np.linalg.norm(isite.coords - esite.coords)
-                )
-                < 1e-5
-            )
-        i_ref_ = PeriodicSite(
-            species=esite.species_string, coords=ipos_sc, lattice=base_sc.lattice
-        )
-        e_ref_ = PeriodicSite(
-            species=esite.species_string, coords=epos_sc, lattice=base_sc.lattice
-        )
+            assert abs(np.linalg.norm(icart - ecart) - np.linalg.norm(isite.coords - esite.coords)) < 1e-5
+        i_ref_ = PeriodicSite(species=esite.species_string, coords=ipos_sc, lattice=base_sc.lattice)
+        e_ref_ = PeriodicSite(species=esite.species_string, coords=epos_sc, lattice=base_sc.lattice)
         start_struct = remove_site_at_pos(start_struct, e_ref_, tol)
         end_struct = remove_site_at_pos(end_struct, i_ref_, tol)
     return start_struct, end_struct, base_sc
    
+
    @@ -270,7 +216,7 @@

    Source code for pymatgen.analysis.diffusion.utils.supercells

    - +
    diff --git a/docs/_modules/pymatgen/analysis/diffusion/utils/tests/test_edge_data_from_sc.html b/docs/_modules/pymatgen/analysis/diffusion/utils/tests/test_edge_data_from_sc.html index 26238d4..f85ed3b 100644 --- a/docs/_modules/pymatgen/analysis/diffusion/utils/tests/test_edge_data_from_sc.html +++ b/docs/_modules/pymatgen/analysis/diffusion/utils/tests/test_edge_data_from_sc.html @@ -1,15 +1,15 @@ - + - pymatgen.analysis.diffusion.utils.tests.test_edge_data_from_sc — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.utils.tests.test_edge_data_from_sc — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -34,7 +34,7 @@

    Navigation

  • modules |
    • -
  • pymatgen-diffusion 2023.8.15 documentation »
    • +
  • pymatgen-diffusion 2024.6.10 documentation »
  • Module code »
  • pymatgen.analysis.diffusion.utils.tests.test_edge_data_from_sc
    • @@ -56,11 +56,7 @@

    Source code for pymatgen.analysis.diffusion.utils.tests.test_edge_data_from_ import pytest from pymatgen.analysis.diffusion.neb.full_path_mapper import MigrationGraph -from pymatgen.analysis.diffusion.utils.edge_data_from_sc import ( - add_edge_data_from_sc, - get_uc_pos, - get_unique_hop, -) +from pymatgen.analysis.diffusion.utils.edge_data_from_sc import add_edge_data_from_sc, get_uc_pos, get_unique_hop from pymatgen.analysis.structure_matcher import StructureMatcher from pymatgen.core.structure import PeriodicSite, Structure @@ -86,7 +82,9 @@

    Source code for pymatgen.analysis.diffusion.utils.tests.test_edge_data_from_ ) -
    [docs]def test_add_edge_data_from_sc(): +
    +[docs] +def test_add_edge_data_from_sc(): errors = [] test_key = "test_key" @@ -113,10 +111,13 @@

    Source code for pymatgen.analysis.diffusion.utils.tests.test_edge_data_from_ if not all(i == hop_labels[0] for i in hop_labels): errors.append("Not all data are added to the same unique hop") - assert not errors, "errors occured:\n" + "\n".join(errors)

    + assert not errors, "errors occurred:\n" + "\n".join(errors)
    + -
    [docs]def test_get_uc_pos(): +
    +[docs] +def test_get_uc_pos(): errors = [] # set up parameters to initiate get_uc_pos @@ -159,10 +160,13 @@

    Source code for pymatgen.analysis.diffusion.utils.tests.test_edge_data_from_ if not test_p2.__eq__(p2): errors.append("Ending site does not match") - assert not errors, "errors occured:\n" + "\n".join(errors)

    + assert not errors, "errors occurred:\n" + "\n".join(errors)
    -
    [docs]def test_get_unique_hop_host(): + +
    +[docs] +def test_get_unique_hop_host(): results = get_unique_hop( mg_Mg, mg_input_struct_i, @@ -173,8 +177,11 @@

    Source code for pymatgen.analysis.diffusion.utils.tests.test_edge_data_from_ assert results[0] == 2

    -
    [docs]def test_get_unique_host_nonhost(): - with pytest.raises(Exception) as exc_info: + +
    +[docs] +def test_get_unique_host_nonhost(): + with pytest.raises(RuntimeError) as exc_info: get_unique_hop( mg_Mg, mg_input_struct_i, @@ -182,8 +189,12 @@

    Source code for pymatgen.analysis.diffusion.utils.tests.test_edge_data_from_ mg_input_struct_e[0], use_host_sg=False, ) - expected_exception = "No symmetrically equivalent site was found for [0.53593472 2.8352428 4.54752366] Mg" - assert exc_info.value.args[0] == expected_exception

    + + assert exc_info.value.args[0] == ( + "No symmetrically equivalent site was found for [0.53593472 " + "2.8352428 4.54752366] Mg" + )
    +
    @@ -198,7 +209,7 @@

    Source code for pymatgen.analysis.diffusion.utils.tests.test_edge_data_from_ - +

    diff --git a/docs/_modules/pymatgen/analysis/diffusion/utils/tests/test_parse_entries.html b/docs/_modules/pymatgen/analysis/diffusion/utils/tests/test_parse_entries.html index 56eb80b..f655f4e 100644 --- a/docs/_modules/pymatgen/analysis/diffusion/utils/tests/test_parse_entries.html +++ b/docs/_modules/pymatgen/analysis/diffusion/utils/tests/test_parse_entries.html @@ -1,15 +1,15 @@ - + - pymatgen.analysis.diffusion.utils.tests.test_parse_entries — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.utils.tests.test_parse_entries — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -34,7 +34,7 @@

    Navigation

  • modules |
    • -
  • pymatgen-diffusion 2023.8.15 documentation »
    • +
  • pymatgen-diffusion 2024.6.10 documentation »
  • Module code »
  • pymatgen.analysis.diffusion.utils.tests.test_parse_entries
    • @@ -74,8 +74,12 @@

    Source code for pymatgen.analysis.diffusion.utils.tests.test_parse_entries__date__ = "April 10, 2019" -
    [docs]class ParseEntriesTest(unittest.TestCase): -
    [docs] def setUp(self): +
    +[docs] +class ParseEntriesTest(unittest.TestCase): +
    +[docs] + def setUp(self): d = loadfn(f"{dir_path}/parse_entry_test_vars.json") struct_uc = d["struct_uc"] self.li_ent = d["li_ent"] @@ -107,6 +111,7 @@

    Source code for pymatgen.analysis.diffusion.utils.tests.test_parse_entriesself.base, self.inserted_2Li, self.li_ent, self.sm )

    + def _is_valid_inserted_ent(self, mapped_struct): res = True for isite in mapped_struct.sites: @@ -118,7 +123,9 @@

    Source code for pymatgen.analysis.diffusion.utils.tests.test_parse_entriesreturn False return res -
    [docs] def test_get_inserted_on_base(self): +
    +[docs] + def test_get_inserted_on_base(self): mapped_struct = get_inserted_on_base( self.base, self.inserted_1Li1, self.li_ent, self.sm ) @@ -135,7 +142,10 @@

    Source code for pymatgen.analysis.diffusion.utils.tests.test_parse_entriesassert self._is_valid_inserted_ent(mapped_struct) assert mapped_struct[0].properties["insertion_energy"] == 4.0

    -
    [docs] def test_process_ents(self): + +
    +[docs] + def test_process_ents(self): base_2_ent = ComputedStructureEntry( structure=self.base.structure * [[1, 1, 0], [1, -1, 0], [0, 0, 2]], energy=self.base.energy * 4, @@ -150,7 +160,10 @@

    Source code for pymatgen.analysis.diffusion.utils.tests.test_parse_entriesif i_insert_site.species_string == "Li": assert i_insert_site.properties["insertion_energy"] == 4

    -
    [docs] def test_filter_and_merge(self): + +
    +[docs] + def test_filter_and_merge(self): combined_struct = Structure.from_sites( self.struct_inserted_1Li1.sites + self.struct_inserted_1Li2.sites @@ -161,7 +174,10 @@

    Source code for pymatgen.analysis.diffusion.utils.tests.test_parse_entriesif i_insert_site.species_string == "Li": assert i_insert_site.properties["insertion_energy"] in {4.5, 5.5}

    -
    [docs] def test_get_insertion_energy(self): + +
    +[docs] + def test_get_insertion_energy(self): insert_energy = get_insertion_energy(self.base, self.inserted_1Li1, self.li_ent) basex2_ = ComputedStructureEntry( structure=self.base.structure * [1, 1, 2], energy=self.base.energy * 2 @@ -172,7 +188,10 @@

    Source code for pymatgen.analysis.diffusion.utils.tests.test_parse_entriesinsert_energy = get_insertion_energy(self.base, self.inserted_2Li, self.li_ent) self.assertAlmostEqual(insert_energy, 4)

    -
    [docs] def test_get_all_sym_sites(self): + +
    +[docs] + def test_get_all_sym_sites(self): struct11 = get_sym_migration_ion_sites( self.base.structure, self.inserted_1Li1.structure, migrating_ion="Li" ) @@ -184,11 +203,9 @@

    Source code for pymatgen.analysis.diffusion.utils.tests.test_parse_entriesstruct22 = get_sym_migration_ion_sites( self.base.structure, self.inserted_2Li.structure, migrating_ion="Li" ) - assert struct22.composition["Li"] == 8

    - + assert struct22.composition["Li"] == 8
    +
    -if __name__ == "__main__": - unittest.main()
    @@ -203,7 +220,7 @@

    Source code for pymatgen.analysis.diffusion.utils.tests.test_parse_entries - +

    diff --git a/docs/_static/basic.css b/docs/_static/basic.css index cfc60b8..f316efc 100644 --- a/docs/_static/basic.css +++ b/docs/_static/basic.css @@ -4,7 +4,7 @@ * * Sphinx stylesheet -- basic theme. * - * :copyright: Copyright 2007-2023 by the Sphinx team, see AUTHORS. + * :copyright: Copyright 2007-2024 by the Sphinx team, see AUTHORS. * :license: BSD, see LICENSE for details. * */ @@ -237,6 +237,10 @@ a.headerlink { visibility: hidden; } +a:visited { + color: #551A8B; +} + h1:hover > a.headerlink, h2:hover > a.headerlink, h3:hover > a.headerlink, diff --git a/docs/_static/doctools.js b/docs/_static/doctools.js index d06a71d..4d67807 100644 --- a/docs/_static/doctools.js +++ b/docs/_static/doctools.js @@ -4,7 +4,7 @@ * * Base JavaScript utilities for all Sphinx HTML documentation. * - * :copyright: Copyright 2007-2023 by the Sphinx team, see AUTHORS. + * :copyright: Copyright 2007-2024 by the Sphinx team, see AUTHORS. * :license: BSD, see LICENSE for details. * */ diff --git a/docs/_static/documentation_options.js b/docs/_static/documentation_options.js index a81e935..13e0e86 100644 --- a/docs/_static/documentation_options.js +++ b/docs/_static/documentation_options.js @@ -1,6 +1,5 @@ -var DOCUMENTATION_OPTIONS = { - URL_ROOT: document.getElementById("documentation_options").getAttribute('data-url_root'), - VERSION: '2023.8.15', +const DOCUMENTATION_OPTIONS = { + VERSION: '2024.6.10', LANGUAGE: 'en', COLLAPSE_INDEX: false, BUILDER: 'html', diff --git a/docs/_static/language_data.js b/docs/_static/language_data.js index 250f566..367b8ed 100644 --- a/docs/_static/language_data.js +++ b/docs/_static/language_data.js @@ -5,7 +5,7 @@ * This script contains the language-specific data used by searchtools.js, * namely the list of stopwords, stemmer, scorer and splitter. * - * :copyright: Copyright 2007-2023 by the Sphinx team, see AUTHORS. + * :copyright: Copyright 2007-2024 by the Sphinx team, see AUTHORS. * :license: BSD, see LICENSE for details. * */ @@ -13,7 +13,7 @@ var stopwords = ["a", "and", "are", "as", "at", "be", "but", "by", "for", "if", "in", "into", "is", "it", "near", "no", "not", "of", "on", "or", "such", "that", "the", "their", "then", "there", "these", "they", "this", "to", "was", "will", "with"]; -/* Non-minified version is copied as a separate JS file, is available */ +/* Non-minified version is copied as a separate JS file, if available */ /** * Porter Stemmer diff --git a/docs/_static/searchtools.js b/docs/_static/searchtools.js index 97d56a7..92da3f8 100644 --- a/docs/_static/searchtools.js +++ b/docs/_static/searchtools.js @@ -4,7 +4,7 @@ * * Sphinx JavaScript utilities for the full-text search. * - * :copyright: Copyright 2007-2023 by the Sphinx team, see AUTHORS. + * :copyright: Copyright 2007-2024 by the Sphinx team, see AUTHORS. * :license: BSD, see LICENSE for details. * */ @@ -57,12 +57,12 @@ const _removeChildren = (element) => { const _escapeRegExp = (string) => string.replace(/[.*+\-?^${}()|[\]\\]/g, "\\$&"); // $& means the whole matched string -const _displayItem = (item, searchTerms) => { +const _displayItem = (item, searchTerms, highlightTerms) => { const docBuilder = DOCUMENTATION_OPTIONS.BUILDER; - const docUrlRoot = DOCUMENTATION_OPTIONS.URL_ROOT; const docFileSuffix = DOCUMENTATION_OPTIONS.FILE_SUFFIX; const docLinkSuffix = DOCUMENTATION_OPTIONS.LINK_SUFFIX; const showSearchSummary = DOCUMENTATION_OPTIONS.SHOW_SEARCH_SUMMARY; + const contentRoot = document.documentElement.dataset.content_root; const [docName, title, anchor, descr, score, _filename] = item; @@ -75,28 +75,35 @@ const _displayItem = (item, searchTerms) => { if (dirname.match(/\/index\/$/)) dirname = dirname.substring(0, dirname.length - 6); else if (dirname === "index/") dirname = ""; - requestUrl = docUrlRoot + dirname; + requestUrl = contentRoot + dirname; linkUrl = requestUrl; } else { // normal html builders - requestUrl = docUrlRoot + docName + docFileSuffix; + requestUrl = contentRoot + docName + docFileSuffix; linkUrl = docName + docLinkSuffix; } let linkEl = listItem.appendChild(document.createElement("a")); linkEl.href = linkUrl + anchor; linkEl.dataset.score = score; linkEl.innerHTML = title; - if (descr) + if (descr) { listItem.appendChild(document.createElement("span")).innerHTML = " (" + descr + ")"; + // highlight search terms in the description + if (SPHINX_HIGHLIGHT_ENABLED) // set in sphinx_highlight.js + highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted")); + } else if (showSearchSummary) fetch(requestUrl) .then((responseData) => responseData.text()) .then((data) => { if (data) listItem.appendChild( - Search.makeSearchSummary(data, searchTerms) + Search.makeSearchSummary(data, searchTerms, anchor) ); + // highlight search terms in the summary + if (SPHINX_HIGHLIGHT_ENABLED) // set in sphinx_highlight.js + highlightTerms.forEach((term) => _highlightText(listItem, term, "highlighted")); }); Search.output.appendChild(listItem); }; @@ -109,26 +116,43 @@ const _finishSearch = (resultCount) => { ); else Search.status.innerText = _( - `Search finished, found ${resultCount} page(s) matching the search query.` - ); + "Search finished, found ${resultCount} page(s) matching the search query." + ).replace('${resultCount}', resultCount); }; const _displayNextItem = ( results, resultCount, - searchTerms + searchTerms, + highlightTerms, ) => { // results left, load the summary and display it // this is intended to be dynamic (don't sub resultsCount) if (results.length) { - _displayItem(results.pop(), searchTerms); + _displayItem(results.pop(), searchTerms, highlightTerms); setTimeout( - () => _displayNextItem(results, resultCount, searchTerms), + () => _displayNextItem(results, resultCount, searchTerms, highlightTerms), 5 ); } // search finished, update title and status message else _finishSearch(resultCount); }; +// Helper function used by query() to order search results. +// Each input is an array of [docname, title, anchor, descr, score, filename]. +// Order the results by score (in opposite order of appearance, since the +// `_displayNextItem` function uses pop() to retrieve items) and then alphabetically. +const _orderResultsByScoreThenName = (a, b) => { + const leftScore = a[4]; + const rightScore = b[4]; + if (leftScore === rightScore) { + // same score: sort alphabetically + const leftTitle = a[1].toLowerCase(); + const rightTitle = b[1].toLowerCase(); + if (leftTitle === rightTitle) return 0; + return leftTitle > rightTitle ? -1 : 1; // inverted is intentional + } + return leftScore > rightScore ? 1 : -1; +}; /** * Default splitQuery function. Can be overridden in ``sphinx.search`` with a @@ -152,13 +176,26 @@ const Search = { _queued_query: null, _pulse_status: -1, - htmlToText: (htmlString) => { + htmlToText: (htmlString, anchor) => { const htmlElement = new DOMParser().parseFromString(htmlString, 'text/html'); - htmlElement.querySelectorAll(".headerlink").forEach((el) => { el.remove() }); + for (const removalQuery of [".headerlinks", "script", "style"]) { + htmlElement.querySelectorAll(removalQuery).forEach((el) => { el.remove() }); + } + if (anchor) { + const anchorContent = htmlElement.querySelector(`[role="main"] ${anchor}`); + if (anchorContent) return anchorContent.textContent; + + console.warn( + `Anchored content block not found. Sphinx search tries to obtain it via DOM query '[role=main] ${anchor}'. Check your theme or template.` + ); + } + + // if anchor not specified or not found, fall back to main content const docContent = htmlElement.querySelector('[role="main"]'); - if (docContent !== undefined) return docContent.textContent; + if (docContent) return docContent.textContent; + console.warn( - "Content block not found. Sphinx search tries to obtain it via '[role=main]'. Could you check your theme or template." + "Content block not found. Sphinx search tries to obtain it via DOM query '[role=main]'. Check your theme or template." ); return ""; }, @@ -231,16 +268,7 @@ const Search = { else Search.deferQuery(query); }, - /** - * execute search (requires search index to be loaded) - */ - query: (query) => { - const filenames = Search._index.filenames; - const docNames = Search._index.docnames; - const titles = Search._index.titles; - const allTitles = Search._index.alltitles; - const indexEntries = Search._index.indexentries; - + _parseQuery: (query) => { // stem the search terms and add them to the correct list const stemmer = new Stemmer(); const searchTerms = new Set(); @@ -276,16 +304,32 @@ const Search = { // console.info("required: ", [...searchTerms]); // console.info("excluded: ", [...excludedTerms]); - // array of [docname, title, anchor, descr, score, filename] - let results = []; + return [query, searchTerms, excludedTerms, highlightTerms, objectTerms]; + }, + + /** + * execute search (requires search index to be loaded) + */ + _performSearch: (query, searchTerms, excludedTerms, highlightTerms, objectTerms) => { + const filenames = Search._index.filenames; + const docNames = Search._index.docnames; + const titles = Search._index.titles; + const allTitles = Search._index.alltitles; + const indexEntries = Search._index.indexentries; + + // Collect multiple result groups to be sorted separately and then ordered. + // Each is an array of [docname, title, anchor, descr, score, filename]. + const normalResults = []; + const nonMainIndexResults = []; + _removeChildren(document.getElementById("search-progress")); - const queryLower = query.toLowerCase(); + const queryLower = query.toLowerCase().trim(); for (const [title, foundTitles] of Object.entries(allTitles)) { - if (title.toLowerCase().includes(queryLower) && (queryLower.length >= title.length/2)) { + if (title.toLowerCase().trim().includes(queryLower) && (queryLower.length >= title.length/2)) { for (const [file, id] of foundTitles) { let score = Math.round(100 * queryLower.length / title.length) - results.push([ + normalResults.push([ docNames[file], titles[file] !== title ? `${titles[file]} > ${title}` : title, id !== null ? "#" + id : "", @@ -300,46 +344,47 @@ const Search = { // search for explicit entries in index directives for (const [entry, foundEntries] of Object.entries(indexEntries)) { if (entry.includes(queryLower) && (queryLower.length >= entry.length/2)) { - for (const [file, id] of foundEntries) { - let score = Math.round(100 * queryLower.length / entry.length) - results.push([ + for (const [file, id, isMain] of foundEntries) { + const score = Math.round(100 * queryLower.length / entry.length); + const result = [ docNames[file], titles[file], id ? "#" + id : "", null, score, filenames[file], - ]); + ]; + if (isMain) { + normalResults.push(result); + } else { + nonMainIndexResults.push(result); + } } } } // lookup as object objectTerms.forEach((term) => - results.push(...Search.performObjectSearch(term, objectTerms)) + normalResults.push(...Search.performObjectSearch(term, objectTerms)) ); // lookup as search terms in fulltext - results.push(...Search.performTermsSearch(searchTerms, excludedTerms)); + normalResults.push(...Search.performTermsSearch(searchTerms, excludedTerms)); // let the scorer override scores with a custom scoring function - if (Scorer.score) results.forEach((item) => (item[4] = Scorer.score(item))); - - // now sort the results by score (in opposite order of appearance, since the - // display function below uses pop() to retrieve items) and then - // alphabetically - results.sort((a, b) => { - const leftScore = a[4]; - const rightScore = b[4]; - if (leftScore === rightScore) { - // same score: sort alphabetically - const leftTitle = a[1].toLowerCase(); - const rightTitle = b[1].toLowerCase(); - if (leftTitle === rightTitle) return 0; - return leftTitle > rightTitle ? -1 : 1; // inverted is intentional - } - return leftScore > rightScore ? 1 : -1; - }); + if (Scorer.score) { + normalResults.forEach((item) => (item[4] = Scorer.score(item))); + nonMainIndexResults.forEach((item) => (item[4] = Scorer.score(item))); + } + + // Sort each group of results by score and then alphabetically by name. + normalResults.sort(_orderResultsByScoreThenName); + nonMainIndexResults.sort(_orderResultsByScoreThenName); + + // Combine the result groups in (reverse) order. + // Non-main index entries are typically arbitrary cross-references, + // so display them after other results. + let results = [...nonMainIndexResults, ...normalResults]; // remove duplicate search results // note the reversing of results, so that in the case of duplicates, the highest-scoring entry is kept @@ -353,14 +398,19 @@ const Search = { return acc; }, []); - results = results.reverse(); + return results.reverse(); + }, + + query: (query) => { + const [searchQuery, searchTerms, excludedTerms, highlightTerms, objectTerms] = Search._parseQuery(query); + const results = Search._performSearch(searchQuery, searchTerms, excludedTerms, highlightTerms, objectTerms); // for debugging //Search.lastresults = results.slice(); // a copy // console.info("search results:", Search.lastresults); // print the results - _displayNextItem(results, results.length, searchTerms); + _displayNextItem(results, results.length, searchTerms, highlightTerms); }, /** @@ -458,14 +508,18 @@ const Search = { // add support for partial matches if (word.length > 2) { const escapedWord = _escapeRegExp(word); - Object.keys(terms).forEach((term) => { - if (term.match(escapedWord) && !terms[word]) - arr.push({ files: terms[term], score: Scorer.partialTerm }); - }); - Object.keys(titleTerms).forEach((term) => { - if (term.match(escapedWord) && !titleTerms[word]) - arr.push({ files: titleTerms[word], score: Scorer.partialTitle }); - }); + if (!terms.hasOwnProperty(word)) { + Object.keys(terms).forEach((term) => { + if (term.match(escapedWord)) + arr.push({ files: terms[term], score: Scorer.partialTerm }); + }); + } + if (!titleTerms.hasOwnProperty(word)) { + Object.keys(titleTerms).forEach((term) => { + if (term.match(escapedWord)) + arr.push({ files: titleTerms[term], score: Scorer.partialTitle }); + }); + } } // no match but word was a required one @@ -488,9 +542,8 @@ const Search = { // create the mapping files.forEach((file) => { - if (fileMap.has(file) && fileMap.get(file).indexOf(word) === -1) - fileMap.get(file).push(word); - else fileMap.set(file, [word]); + if (!fileMap.has(file)) fileMap.set(file, [word]); + else if (fileMap.get(file).indexOf(word) === -1) fileMap.get(file).push(word); }); }); @@ -541,8 +594,8 @@ const Search = { * search summary for a given text. keywords is a list * of stemmed words. */ - makeSearchSummary: (htmlText, keywords) => { - const text = Search.htmlToText(htmlText); + makeSearchSummary: (htmlText, keywords, anchor) => { + const text = Search.htmlToText(htmlText, anchor); if (text === "") return null; const textLower = text.toLowerCase(); diff --git a/docs/_static/sphinx_highlight.js b/docs/_static/sphinx_highlight.js index aae669d..8a96c69 100644 --- a/docs/_static/sphinx_highlight.js +++ b/docs/_static/sphinx_highlight.js @@ -29,14 +29,19 @@ const _highlight = (node, addItems, text, className) => { } span.appendChild(document.createTextNode(val.substr(pos, text.length))); + const rest = document.createTextNode(val.substr(pos + text.length)); parent.insertBefore( span, parent.insertBefore( - document.createTextNode(val.substr(pos + text.length)), + rest, node.nextSibling ) ); node.nodeValue = val.substr(0, pos); + /* There may be more occurrences of search term in this node. So call this + * function recursively on the remaining fragment. + */ + _highlight(rest, addItems, text, className); if (isInSVG) { const rect = document.createElementNS( @@ -140,5 +145,10 @@ const SphinxHighlight = { }, }; -_ready(SphinxHighlight.highlightSearchWords); -_ready(SphinxHighlight.initEscapeListener); +_ready(() => { + /* Do not call highlightSearchWords() when we are on the search page. + * It will highlight words from the *previous* search query. + */ + if (typeof Search === "undefined") SphinxHighlight.highlightSearchWords(); + SphinxHighlight.initEscapeListener(); +}); diff --git a/docs/_themes/README.html b/docs/_themes/README.html index c3e1b19..7cf396f 100644 --- a/docs/_themes/README.html +++ b/docs/_themes/README.html @@ -1,16 +1,16 @@ - + - + - krTheme Sphinx Style — pymatgen-diffusion 2023.8.15 documentation + krTheme Sphinx Style — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

    Navigation

  • modules |
    • -
  • pymatgen-diffusion 2023.8.15 documentation »
    • +
  • pymatgen-diffusion 2024.6.10 documentation »
  • krTheme Sphinx Style
    • @@ -46,7 +46,7 @@

    Navigation

    -

    krTheme Sphinx Style

    +

    krTheme Sphinx Style

    This repository contains sphinx styles Kenneth Reitz uses in most of his projects. It is a drivative of Mitsuhiko’s themes for Flask and Flask related projects. To use this style in your Sphinx documentation, follow @@ -89,7 +89,7 @@

    This Page

    rel="nofollow">Show Source
    - +

    diff --git a/docs/change_log.html b/docs/change_log.html index 1fb3755..7cc99c2 100644 --- a/docs/change_log.html +++ b/docs/change_log.html @@ -1,16 +1,16 @@ - + - + - Change Log — pymatgen-diffusion 2023.8.15 documentation + Change Log — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

    Navigation

  • modules |
    • -
  • pymatgen-diffusion 2023.8.15 documentation »
    • +
  • pymatgen-diffusion 2024.6.10 documentation »
  • Change Log
    • @@ -46,28 +46,28 @@

    Navigation

    -

    Change Log

    +

    Change Log

    -

    v2023.8.15

    +

    v2023.8.15

    • Complete migration of pymatgen.analysis.pathfinder over to pymatgen-analysis.diffusion.

    -

    v2022.4.22

    +

    v2022.4.22

    • Make MigrationHop MSONAble. (@acrutt)

    -

    v2021.4.29

    +

    v2021.4.29

    • Fixed msite calc order (@hmlli)

    • Removed magmom (@jmmshn)

    -

    v2021.3.6

    +

    v2021.3.6

    • Fix for bad release due to error in MANIFEST.in.

    • DiffusionAnalyzer has been migration from pymatgen to pymatgen.analysis.diffusion.analyzer for a more @@ -75,26 +75,26 @@

      v2021.3.6 -

      v2021.3.5

      +

      v2021.3.5

      • pymatgen-diffusion is now released as a namespace package pymatgen-analysis-diffusion on PyPI. It should be imported via pymatgen.analysis.diffusion instead pymatgen_diffusion.

    -

    v2019.2.28

    +

    v2019.2.28

    • Py3k cleanup.

    -

    v2018.1.4

    +

    v2018.1.4

    • Compatibility with pymatgen v2018+.

    -

    v0.3.0

    +

    v0.3.0

    • NEB tools, including an implementation of an IDPP solver.

    @@ -136,7 +136,7 @@

    This Page

    rel="nofollow">Show Source
    - +
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diff --git a/docs/doctrees/pymatgen_diffusion.doctree b/docs/doctrees/pymatgen_diffusion.doctree index e617b76784e86169f9360d0c92af7bb22c964a40..70a1bb9532575910266954f8d5702fb2c3f3cca5 100644 GIT binary patch delta 25 hcmZ1>HBXAAfpx0zMivpa%}Q*u85y^4-p8KB3IJiq2ax~( delta 36 scmbOywL*%efpx0vMivn^t{%4h(vpJGk|}*&GVa*Cg*}TE0MQN$w*UYD diff --git a/docs/doctrees/pymatgen_diffusion.neb.doctree b/docs/doctrees/pymatgen_diffusion.neb.doctree index d41e806fa336d0ebbce6020e203f640363511018..40bd23c91ad24baffe95266df5b98bde06ef0477 100644 GIT binary patch delta 25 hcmcblc0!G%fpx0wMwTDko7s3~Gcp=%Uc|eB6##c%2%`W1 delta 36 scmX@1c1ew;fpx0;MwTDkTs>_0r6mQWB~$!1|KXm^$Y{8E2JZ$|00JKk$N&HU diff --git a/docs/genindex.html b/docs/genindex.html index 03c49c1..e6fc10e 100644 --- a/docs/genindex.html +++ b/docs/genindex.html @@ -1,15 +1,15 @@ - + - Index — pymatgen-diffusion 2023.8.15 documentation + Index — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -34,7 +34,7 @@

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    • +
  • pymatgen-diffusion 2024.6.10 documentation »
  • Index
  • modules |

    • @@ -359,8 +359,6 @@

    L

    M

      -
    • maggma_stores() (in module pymatgen.analysis.diffusion.utils.tests.test_maggma) -
    • map_hop_sc2uc() (in module pymatgen.analysis.diffusion.neb.full_path_mapper)
    • mh_eq() (in module pymatgen.analysis.diffusion.utils.edge_data_from_sc) @@ -440,8 +438,6 @@

      M

    • pymatgen.analysis.diffusion.utils.supercells
    • pymatgen.analysis.diffusion.utils.tests.test_edge_data_from_sc -
      • -
    • pymatgen.analysis.diffusion.utils.tests.test_maggma
    • pymatgen.analysis.diffusion.utils.tests.test_parse_entries
      • @@ -717,13 +713,6 @@

      P

      -
    • - pymatgen.analysis.diffusion.utils.tests.test_maggma - -
    • @@ -813,8 +802,6 @@

      S

      T

      - - -
      - + diff --git a/docs/index.html b/docs/index.html index 9186727..0efc61f 100644 --- a/docs/index.html +++ b/docs/index.html @@ -1,16 +1,16 @@ - + - + - Introduction — pymatgen-diffusion 2023.8.15 documentation + Introduction — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -39,7 +39,7 @@

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      Introduction

      +

      Introduction

      This is an add-on to pymatgen for diffusion analysis that is developed by the Materials Virtual Lab. Note that it relies on pymatgen for structural manipulations, file io, and preliminary analyses. In particular, pymatgen’s @@ -61,11 +61,11 @@

      Introduction -

      Change Log

      +

      Change Log

      Change log

      -

      Features (non-exhaustive!)

      +

      Features (non-exhaustive!)

      1. Van-Hove analysis

      2. Probability density

        3. @@ -73,7 +73,7 @@

        Features (non-exhaustive!) -

        API documentation

        +

        API documentation

        For detailed documentation of all modules and classes, please refer to the API docs.

        @@ -87,23 +87,23 @@

        API documentation -

        Citing

        +

        Citing

        If you use this package, please consider citing the relevant publications documented in each analysis.

      -

      Contributing

      +

      Contributing

      We welcome contributions in all forms. If you’d like to contribute, please fork this repository, make changes and send us a pull request!

      -

      Acknowledgements

      +

      Acknowledgements

      This code is funded by the National Science Foundation’s Designing Materials to Revolutionize and Engineer our Future (DMREF) program under Grant No. 1436976.

      -

      License

      +

      License

      Pymatgen is released under the MIT License. The terms of the license are as follows:

      Copyright (c) 2015, Regents of the University of California
@@ -137,7 +137,7 @@ 
      License
-
      Our Copyright Policy
      
+
      Our Copyright Policy
      
 
      This software is Copyright© 2015 The Regents of the University of California.
 All Rights Reserved.
 
@@ -176,7 +176,7 @@ 
      Our Copyright Policy
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      Indices and tables

      +

      Indices and tables

      - + diff --git a/docs/modules.html b/docs/modules.html index 5d5cbc8..90c752e 100644 --- a/docs/modules.html +++ b/docs/modules.html @@ -1,16 +1,16 @@ - + - + - pymatgen — pymatgen-diffusion 2023.8.15 documentation + pymatgen — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -43,7 +43,7 @@

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      Python Module Index

      		    pymatgen.analysis.diffusion.utils.tests.test_edge_data_from_sc
          - pymatgen.analysis.diffusion.utils.tests.test_maggma -
          @@ -227,7 +222,7 @@

      Python Module Index

    • Documentation overview
      • - + diff --git a/docs/pymatgen.analysis.diffusion.aimd.clustering.html b/docs/pymatgen.analysis.diffusion.aimd.clustering.html index f815bc1..bd9aa8c 100644 --- a/docs/pymatgen.analysis.diffusion.aimd.clustering.html +++ b/docs/pymatgen.analysis.diffusion.aimd.clustering.html @@ -1,16 +1,16 @@ - + - + - pymatgen.analysis.diffusion.aimd.clustering module — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.aimd.clustering module — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

      Navigation

    • modules |
      • -
    • pymatgen-diffusion 2023.8.15 documentation »
      • +
    • pymatgen-diffusion 2024.6.10 documentation »
    • pymatgen.analysis.diffusion.aimd.clustering module
      • @@ -46,13 +46,13 @@

      Navigation

      -

      pymatgen.analysis.diffusion.aimd.clustering module

      +

      pymatgen.analysis.diffusion.aimd.clustering module

      This module implements clustering algorithms to determine centroids, with adaption for periodic boundary conditions. This can be used, for example, to determine likely atomic positions from MD trajectories.

      -class Kmeans(max_iterations: int = 1000)[source]
      +class Kmeans(max_iterations: int = 1000)[source]

      Bases: object

      Simple kmeans clustering.

      @@ -62,7 +62,7 @@

      Navigation

      -cluster(points, k, initial_centroids=None)[source]
      +cluster(points, k, initial_centroids=None)[source]
      Parameters:
        @@ -86,7 +86,7 @@

        Navigation

        -static get_centroids(points, labels, k, centroids)[source]
        +static get_centroids(points, labels, k, centroids)[source]

        Each centroid is the geometric mean of the points that have that centroid’s label. Important: If a centroid is empty (no points have that centroid’s label) you should randomly re-initialize it.

        @@ -104,7 +104,7 @@

        Navigation

        -static get_labels(points, centroids)[source]
        +static get_labels(points, centroids)[source]

        For each element in the dataset, chose the closest centroid. Make that centroid the element’s label.

        @@ -119,7 +119,7 @@

        Navigation

        -should_stop(old_centroids, centroids, iterations)[source]
        +should_stop(old_centroids, centroids, iterations)[source]

        Check for stopping conditions.

        Parameters:
        @@ -136,7 +136,7 @@

        Navigation

        -class KmeansPBC(lattice, max_iterations=1000)[source]
        +class KmeansPBC(lattice, max_iterations=1000)[source]

        Bases: Kmeans

        A version of KMeans that work with PBC. Distance metrics have to change, as well as new centroid determination. The points supplied should be @@ -151,7 +151,7 @@

        Navigation

        -get_centroids(points, labels, k, centroids)[source]
        +get_centroids(points, labels, k, centroids)[source]

        Each centroid is the geometric mean of the points that have that centroid’s label. Important: If a centroid is empty (no points have that centroid’s label) you should randomly re-initialize it.

        @@ -169,7 +169,7 @@

        Navigation

        -get_labels(points, centroids)[source]
        +get_labels(points, centroids)[source]

        For each element in the dataset, chose the closest centroid. Make that centroid the element’s label.

        @@ -184,7 +184,7 @@

        Navigation

        -should_stop(old_centroids, centroids, iterations)[source]
        +should_stop(old_centroids, centroids, iterations)[source]

        Check for stopping conditions.

        Parameters:
        @@ -201,7 +201,7 @@

        Navigation

        -get_random_centroid(points)[source]
        +get_random_centroid(points)[source]

        Generate a random centroid based on points.

        Parameters:
        @@ -212,7 +212,7 @@

        Navigation

        -get_random_centroids(points, k)[source]
        +get_random_centroids(points, k)[source]

        Generate k random centroids based on points.

        Parameters:
        @@ -268,7 +268,7 @@

        This Page

        rel="nofollow">Show Source
      - + diff --git a/docs/pymatgen.analysis.diffusion.aimd.html b/docs/pymatgen.analysis.diffusion.aimd.html index df6582d..c6d698a 100644 --- a/docs/pymatgen.analysis.diffusion.aimd.html +++ b/docs/pymatgen.analysis.diffusion.aimd.html @@ -1,16 +1,16 @@ - + - + - pymatgen.analysis.diffusion.aimd package — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.aimd package — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

      Navigation

    • modules |
      • -
    • pymatgen-diffusion 2023.8.15 documentation »
      • +
    • pymatgen-diffusion 2024.6.10 documentation »
    • pymatgen.analysis.diffusion.aimd package
      • @@ -46,14 +46,14 @@

      Navigation

      -

      pymatgen.analysis.diffusion.aimd package

      +

      pymatgen.analysis.diffusion.aimd package

      -

      Subpackages

      +

      Subpackages

      -

      Submodules

      +

      Submodules

      @@ -167,7 +167,7 @@

      This Page

      rel="nofollow">Show Source
      - + diff --git a/docs/pymatgen.analysis.diffusion.aimd.pathway.html b/docs/pymatgen.analysis.diffusion.aimd.pathway.html index fc17832..b9de7c4 100644 --- a/docs/pymatgen.analysis.diffusion.aimd.pathway.html +++ b/docs/pymatgen.analysis.diffusion.aimd.pathway.html @@ -1,16 +1,16 @@ - + - + - pymatgen.analysis.diffusion.aimd.pathway module — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.aimd.pathway module — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

      Navigation

    • modules |
      • -
    • pymatgen-diffusion 2023.8.15 documentation »
      • +
    • pymatgen-diffusion 2024.6.10 documentation »
    • pymatgen.analysis.diffusion.aimd.pathway module
      • @@ -46,12 +46,13 @@

      Navigation

      -

      pymatgen.analysis.diffusion.aimd.pathway module

      -

      Algorithms for diffusion pathway analysis

      +

      pymatgen.analysis.diffusion.aimd.pathway module

      +

      Algorithms for diffusion pathway analysis.

      -class ProbabilityDensityAnalysis(structure, trajectories, interval=0.5, species=('Li', 'Na'))[source]
      +class ProbabilityDensityAnalysis(structure, trajectories, interval=0.5, species=('Li', 'Na'))[source]

      Bases: object

      +

      Probability density analysis class.

      Compute the time-averaged probability density distribution of selected species on a “uniform” (in terms of fractional coordinates) 3-D grid. Note that int_{Omega}d^3rP(r) = 1

      @@ -59,18 +60,15 @@

      Navigation

      Zhu, Z.; Chu, I.-H.; Deng, Z. and Ong, S. P. “Role of Na+ Interstitials and Dopants in Enhancing the Na+ Conductivity of the Cubic Na3PS4 Superionic Conductor”. Chem. Mater. (2015), 27, pp 8318-8325.

      -

      Initialization. -:param structure: crystal structure -:type structure: Structure -:param trajectories: ionic trajectories of the structure

      -
      -

      from MD simulations. It should be (1) stored as 3-D array [ -Ntimesteps, Nions, 3] where 3 refers to a,b,c components; -(2) in fractional coordinates.

      -
      +

      Initialization.

      Parameters:
        +

      • structure (Structure) – crystal structure

        • +

      • trajectories (numpy array) – ionic trajectories of the structure +from MD simulations. It should be (1) stored as 3-D array [ +Ntimesteps, Nions, 3] where 3 refers to a,b,c components; +(2) in fractional coordinates.

      • interval (float) – the interval between two nearest grid points (in Angstrom)

      • species (list of str) – list of species that are of interest

        • @@ -79,7 +77,7 @@

        Navigation

      -classmethod from_diffusion_analyzer(diffusion_analyzer, interval=0.5, species=('Li', 'Na'))[source]
      +classmethod from_diffusion_analyzer(diffusion_analyzer, interval=0.5, species=('Li', 'Na'))[source]

      Create a ProbabilityDensityAnalysis from a diffusion_analyzer object.

      Parameters:
      @@ -96,7 +94,7 @@

      Navigation

      -generate_stable_sites(p_ratio=0.25, d_cutoff=1.0)[source]
      +generate_stable_sites(p_ratio=0.25, d_cutoff=1.0)[source]

      Obtain a set of low-energy sites from probability density function with given probability threshold ‘p_ratio’. The set of grid points with probability density higher than the threshold will further be clustered @@ -120,14 +118,14 @@

      Navigation

      -get_full_structure()[source]
      +get_full_structure()[source]

      Generate the structure with the low-energy sites included. In the end, a pymatgen Structure object will be returned.

      -to_chgcar(filename='CHGCAR.vasp')[source]
      +to_chgcar(filename='CHGCAR.vasp')[source]

      Save the probability density distribution in the format of CHGCAR, which can be visualized by VESTA.

      @@ -136,13 +134,13 @@

      Navigation

      -class SiteOccupancyAnalyzer(structure, coords_ref, trajectories, species=('Li', 'Na'))[source]
      +class SiteOccupancyAnalyzer(structure, coords_ref, trajectories, species=('Li', 'Na'))[source]

      Bases: object

      A class that analyzes the site occupancy of given species using MD trajectories. The occupancy of a site is determined based on the shortest distance scheme.

      -site_occ
      +site_occ
      N x 1 numpy array that stores the occupancy of all sites associated with
      @@ -151,21 +149,21 @@

      Navigation

      -coords_ref
      +coords_ref
      N x 3 numpy array of fractional coordinates of all reference sites.
      -nsites
      +nsites
      Number of reference sites.
      -structure
      +structure
      Initial structure.
      @@ -185,7 +183,7 @@

      Navigation

      -classmethod from_diffusion_analyzer(coords_ref, diffusion_analyzer, species=('Li', 'Na'))[source]
      +classmethod from_diffusion_analyzer(coords_ref, diffusion_analyzer, species=('Li', 'Na'))[source]

      Create a SiteOccupancyAnalyzer object using a diffusion_analyzer object.

      Parameters:
      @@ -202,7 +200,7 @@

      Navigation

      -get_average_site_occupancy(indices)[source]
      +get_average_site_occupancy(indices)[source]

      Get the average site occupancy over a subset of reference sites.

      @@ -253,7 +251,7 @@

      This Page

      rel="nofollow">Show Source
      - + diff --git a/docs/pymatgen.analysis.diffusion.aimd.rdf.html b/docs/pymatgen.analysis.diffusion.aimd.rdf.html index 97ea184..ba58c1f 100644 --- a/docs/pymatgen.analysis.diffusion.aimd.rdf.html +++ b/docs/pymatgen.analysis.diffusion.aimd.rdf.html @@ -1,16 +1,16 @@ - + - + - pymatgen.analysis.diffusion.aimd.rdf module — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.aimd.rdf module — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

      Navigation

    • modules |
      • -
    • pymatgen-diffusion 2023.8.15 documentation »
      • +
    • pymatgen-diffusion 2024.6.10 documentation »
    • pymatgen.analysis.diffusion.aimd.rdf module
      • @@ -46,11 +46,11 @@

      Navigation

      -

      pymatgen.analysis.diffusion.aimd.rdf module

      +

      pymatgen.analysis.diffusion.aimd.rdf module

      RDF implementation.

      -class RadialDistributionFunction(structures: list, indices: list, reference_indices: list, ngrid: int = 101, rmax: float = 10.0, cell_range: int = 1, sigma: float = 0.1)[source]
      +class RadialDistributionFunction(structures: list, indices: list, reference_indices: list, ngrid: int = 101, rmax: float = 10.0, cell_range: int = 1, sigma: float = 0.1)[source]

      Bases: object

      Calculate the average radial distribution function for a given set of structures.

      @@ -74,8 +74,8 @@

      Navigation

      -property coordination_number
      -

      returns running coordination number

      +property coordination_number +

      returns running coordination number.

      Returns:

      numpy array

      @@ -85,7 +85,7 @@

      Navigation

      -export_rdf(filename: str)[source]
      +export_rdf(filename: str)[source]

      Output RDF data to a csv file.

      Parameters:
      @@ -98,7 +98,7 @@

      Navigation

      -classmethod from_species(structures: list, ngrid: int = 101, rmax: float = 10.0, cell_range: int = 1, sigma: float = 0.1, species: tuple | list = ('Li', 'Na'), reference_species: tuple | list | None = None)[source]
      +classmethod from_species(structures: list, ngrid: int = 101, rmax: float = 10.0, cell_range: int = 1, sigma: float = 0.1, species: tuple | list = ('Li', 'Na'), reference_species: tuple | list | None = None)[source]

      Initialize using species.

      Parameters:
      @@ -126,7 +126,7 @@

      Navigation

      -get_rdf_plot(label: str | None = None, xlim: tuple = (0.0, 8.0), ylim: tuple = (-0.005, 3.0), loc_peak: bool = False)[source]
      +get_rdf_plot(label: str | None = None, xlim: tuple = (0.0, 8.0), ylim: tuple = (-0.005, 3.0), loc_peak: bool = False)[source]

      Plot the average RDF function.

      Parameters:
      @@ -144,7 +144,7 @@

      Navigation

      -class RadialDistributionFunctionFast(structures: Structure | list[pymatgen.core.structure.Structure], rmin: float = 0.0, rmax: float = 10.0, ngrid: float = 101, sigma: float = 0.0, n_jobs=None)[source]
      +class RadialDistributionFunctionFast(structures: Structure | list[Structure], rmin: float = 0.0, rmax: float = 10.0, ngrid: float = 101, sigma: float = 0.0, n_jobs=None)[source]

      Bases: object

      Fast radial distribution analysis.

      This method calculates rdf on np.linspace(rmin, rmax, ngrid) points.

      @@ -162,8 +162,8 @@

      Navigation

      -get_coordination_number(ref_species, species, is_average=True)[source]
      -

      returns running coordination number

      +get_coordination_number(ref_species, species, is_average=True)[source] +

      returns running coordination number.

      Parameters:
        @@ -182,9 +182,9 @@

        Navigation

        -get_one_rdf(ref_species: str | list[str], species: str | list[str], index=0)[source]
        +get_one_rdf(ref_species: str | list[str], species: str | list[str], index=0)[source]

        Get the RDF for one structure, indicated by the index of the structure -in all structures

        +in all structures.

        Parameters:
          @@ -203,7 +203,7 @@

          Navigation

          -get_rdf(ref_species: str | list[str], species: str | list[str], is_average=True)[source]
          +get_rdf(ref_species: str | list[str], species: str | list[str], is_average=True)[source]
          Parameters:
            @@ -212,7 +212,7 @@

            Navigation

          • species (list of species or just single specie str) – the species that we are interested in. The rdfs are calculated on these species.

          • is_average (bool) – whether to take the average over -all structures

            • +all structures.

          Returns:
          @@ -265,7 +265,7 @@

          This Page

          rel="nofollow">Show Source
      - + diff --git a/docs/pymatgen.analysis.diffusion.aimd.tests.test_clustering.html b/docs/pymatgen.analysis.diffusion.aimd.tests.test_clustering.html index 825d3db..0ccdb07 100644 --- a/docs/pymatgen.analysis.diffusion.aimd.tests.test_clustering.html +++ b/docs/pymatgen.analysis.diffusion.aimd.tests.test_clustering.html @@ -1,16 +1,16 @@ - + - + - pymatgen.analysis.diffusion.aimd.tests.test_clustering module — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.aimd.tests.test_clustering module — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

      Navigation

    • modules |
      • -
    • pymatgen-diffusion 2023.8.15 documentation »
      • +
    • pymatgen-diffusion 2024.6.10 documentation »
    • pymatgen.analysis.diffusion.aimd.tests.test_clustering module
      • @@ -46,31 +46,31 @@

      Navigation

      -

      pymatgen.analysis.diffusion.aimd.tests.test_clustering module

      +

      pymatgen.analysis.diffusion.aimd.tests.test_clustering module

      -class KmeansPBCTest(methodName='runTest')[source]
      +class KmeansPBCTest(methodName='runTest')[source]

      Bases: TestCase

      Create an instance of the class that will use the named test method when executed. Raises a ValueError if the instance does not have a method with the specified name.

      -test_cluster()[source]
      +test_cluster()[source]
      -class KmeansTest(methodName='runTest')[source]
      +class KmeansTest(methodName='runTest')[source]

      Bases: TestCase

      Create an instance of the class that will use the named test method when executed. Raises a ValueError if the instance does not have a method with the specified name.

      -test_cluster()[source]
      +test_cluster()[source]
      @@ -112,7 +112,7 @@

      This Page

      rel="nofollow">Show Source
      - + diff --git a/docs/pymatgen.analysis.diffusion.aimd.tests.test_pathway.html b/docs/pymatgen.analysis.diffusion.aimd.tests.test_pathway.html index 106ff54..ca0945a 100644 --- a/docs/pymatgen.analysis.diffusion.aimd.tests.test_pathway.html +++ b/docs/pymatgen.analysis.diffusion.aimd.tests.test_pathway.html @@ -1,16 +1,16 @@ - + - + - pymatgen.analysis.diffusion.aimd.tests.test_pathway module — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.aimd.tests.test_pathway module — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

      Navigation

    • modules |
      • -
    • pymatgen-diffusion 2023.8.15 documentation »
      • +
    • pymatgen-diffusion 2024.6.10 documentation »
    • pymatgen.analysis.diffusion.aimd.tests.test_pathway module
      • @@ -46,51 +46,51 @@

      Navigation

      -

      pymatgen.analysis.diffusion.aimd.tests.test_pathway module

      +

      pymatgen.analysis.diffusion.aimd.tests.test_pathway module

      -class ProbabilityDensityTest(methodName='runTest')[source]
      +class ProbabilityDensityTest(methodName='runTest')[source]

      Bases: TestCase

      Create an instance of the class that will use the named test method when executed. Raises a ValueError if the instance does not have a method with the specified name.

      -test_generate_stable_sites()[source]
      +test_generate_stable_sites()[source]
      -test_probability()[source]
      +test_probability()[source]
      -test_probability_classmethod()[source]
      +test_probability_classmethod()[source]
      -test_to_chgcar()[source]
      +test_to_chgcar()[source]
      -class SiteOccupancyTest(methodName='runTest')[source]
      +class SiteOccupancyTest(methodName='runTest')[source]

      Bases: TestCase

      Create an instance of the class that will use the named test method when executed. Raises a ValueError if the instance does not have a method with the specified name.

      -test_site_occupancy()[source]
      +test_site_occupancy()[source]
      -test_site_occupancy_classmethod()[source]
      +test_site_occupancy_classmethod()[source]
      @@ -136,7 +136,7 @@

      This Page

      rel="nofollow">Show Source
      - + diff --git a/docs/pymatgen.analysis.diffusion.aimd.tests.test_rdf.html b/docs/pymatgen.analysis.diffusion.aimd.tests.test_rdf.html index 51bd1e3..767bd00 100644 --- a/docs/pymatgen.analysis.diffusion.aimd.tests.test_rdf.html +++ b/docs/pymatgen.analysis.diffusion.aimd.tests.test_rdf.html @@ -1,16 +1,16 @@ - + - + - pymatgen.analysis.diffusion.aimd.tests.test_rdf module — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.aimd.tests.test_rdf module — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

      Navigation

    • modules |
      • -
    • pymatgen-diffusion 2023.8.15 documentation »
      • +
    • pymatgen-diffusion 2024.6.10 documentation »
    • pymatgen.analysis.diffusion.aimd.tests.test_rdf module
      • @@ -46,22 +46,22 @@

      Navigation

      -

      pymatgen.analysis.diffusion.aimd.tests.test_rdf module

      +

      pymatgen.analysis.diffusion.aimd.tests.test_rdf module

      -class RDFTest(methodName='runTest')[source]
      +class RDFTest(methodName='runTest')[source]

      Bases: TestCase

      Create an instance of the class that will use the named test method when executed. Raises a ValueError if the instance does not have a method with the specified name.

      -test_rdf()[source]
      +test_rdf()[source]
      -test_rdf_coordination_number()[source]
      +test_rdf_coordination_number()[source]
      @@ -100,7 +100,7 @@

      This Page

      rel="nofollow">Show Source
      - + diff --git a/docs/pymatgen.analysis.diffusion.aimd.tests.test_van_hove.html b/docs/pymatgen.analysis.diffusion.aimd.tests.test_van_hove.html index 922b845..44e5174 100644 --- a/docs/pymatgen.analysis.diffusion.aimd.tests.test_van_hove.html +++ b/docs/pymatgen.analysis.diffusion.aimd.tests.test_van_hove.html @@ -1,16 +1,16 @@ - + - + - pymatgen.analysis.diffusion.aimd.tests.test_van_hove module — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.aimd.tests.test_van_hove module — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

      Navigation

    • modules |
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    • pymatgen-diffusion 2023.8.15 documentation »
      • +
    • pymatgen-diffusion 2024.6.10 documentation »
    • pymatgen.analysis.diffusion.aimd.tests.test_van_hove module
      • @@ -46,81 +46,81 @@

      Navigation

      -

      pymatgen.analysis.diffusion.aimd.tests.test_van_hove module

      +

      pymatgen.analysis.diffusion.aimd.tests.test_van_hove module

      -class EvolutionAnalyzerTest(methodName='runTest')[source]
      +class EvolutionAnalyzerTest(methodName='runTest')[source]

      Bases: TestCase

      Create an instance of the class that will use the named test method when executed. Raises a ValueError if the instance does not have a method with the specified name.

      -test_get_df()[source]
      +test_get_df()[source]
      -class RDFTest(methodName='runTest')[source]
      +class RDFTest(methodName='runTest')[source]

      Bases: TestCase

      Create an instance of the class that will use the named test method when executed. Raises a ValueError if the instance does not have a method with the specified name.

      -setUp()[source]
      +setUp()[source]

      Hook method for setting up the test fixture before exercising it.

      -test_raises_ValueError_if_reference_species_not_in_structure()[source]
      +test_raises_ValueError_if_reference_species_not_in_structure()[source]
      -test_raises_ValueError_if_sigma_is_not_positive()[source]
      +test_raises_ValueError_if_sigma_is_not_positive()[source]
      -test_raises_ValueError_if_species_not_in_structure()[source]
      +test_raises_ValueError_if_species_not_in_structure()[source]
      -test_raises_valueerror_if_ngrid_is_less_than_2()[source]
      +test_raises_valueerror_if_ngrid_is_less_than_2()[source]
      -test_rdf()[source]
      +test_rdf()[source]
      -test_rdf_coordination_number()[source]
      +test_rdf_coordination_number()[source]
      -test_rdf_two_species_coordination_number()[source]
      +test_rdf_two_species_coordination_number()[source]
      -class VanHoveTest(methodName='runTest')[source]
      +class VanHoveTest(methodName='runTest')[source]

      Bases: TestCase

      Create an instance of the class that will use the named test method when executed. Raises a ValueError if the instance does not have a method with the specified name.

      -test_van_hove()[source]
      +test_van_hove()[source]
      @@ -173,7 +173,7 @@

      This Page

      rel="nofollow">Show Source
      - + diff --git a/docs/pymatgen.analysis.diffusion.aimd.van_hove.html b/docs/pymatgen.analysis.diffusion.aimd.van_hove.html index 0dd0c1e..9006aac 100644 --- a/docs/pymatgen.analysis.diffusion.aimd.van_hove.html +++ b/docs/pymatgen.analysis.diffusion.aimd.van_hove.html @@ -1,16 +1,16 @@ - + - + - pymatgen.analysis.diffusion.aimd.van_hove module — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.aimd.van_hove module — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

      Navigation

    • modules |
      • -
    • pymatgen-diffusion 2023.8.15 documentation »
      • +
    • pymatgen-diffusion 2024.6.10 documentation »
    • pymatgen.analysis.diffusion.aimd.van_hove module
      • @@ -46,11 +46,11 @@

      Navigation

      -

      pymatgen.analysis.diffusion.aimd.van_hove module

      +

      pymatgen.analysis.diffusion.aimd.van_hove module

      Van Hove analysis for correlations.

      -class EvolutionAnalyzer(structures: list, rmax: float = 10, step: int = 1, time_step: int = 2)[source]
      +class EvolutionAnalyzer(structures: list, rmax: float = 10, step: int = 1, time_step: int = 2)[source]

      Bases: object

      Analyze the evolution of structures during AIMD simulations.

      Initialization the EvolutionAnalyzer from MD simulations. From the @@ -76,7 +76,7 @@

      Navigation

      -static atom_dist(structure: Structure, specie: str, ngrid: int = 101, window: float = 1, direction: str = 'c')[source]
      +static atom_dist(structure: Structure, specie: str, ngrid: int = 101, window: float = 1, direction: str = 'c')[source]

      Get atomic distribution for a given specie.

      Parameters:
      @@ -100,7 +100,7 @@

      Navigation

      -get_df(func: Callable, save_csv: str | None = None, **kwargs)[source]
      +get_df(func: Callable, save_csv: str | None = None, **kwargs)[source]

      Get the data frame for a given pair. This step would be very slow if there are hundreds or more structures to parse.

      @@ -126,6 +126,7 @@

      Navigation

    • save_csv (str) – save pandas DataFrame to csv.

      • +

    • **kwargs – Pass-through to func.

      • Returns:
      @@ -143,7 +144,7 @@

      Navigation

      -static get_min_dist(df: DataFrame, tol: float = 1e-10)[source]
      +static get_min_dist(df: DataFrame, tol: float = 1e-10)[source]

      Get the shortest pair distance from the given DataFrame.

      Parameters:
      @@ -161,7 +162,7 @@

      Navigation

      -static get_pairs(structure: Structure)[source]
      +static get_pairs(structure: Structure)[source]

      Get all element pairs in a structure.

      Parameters:
      @@ -175,7 +176,7 @@

      Navigation

      -plot_atomic_evolution(specie: str, direction: str = 'c', cmap=<matplotlib.colors.LinearSegmentedColormap object>, df: ~pandas.core.frame.DataFrame = None)[source]
      +plot_atomic_evolution(specie: str, direction: str = 'c', cmap=<matplotlib.colors.LinearSegmentedColormap object>, df: ~pandas.core.frame.DataFrame = None)[source]

      Plot the atomic distribution evolution with time for a given species.

      Parameters:
      @@ -195,7 +196,7 @@

      Navigation

      -static plot_evolution_from_data(df: ~pandas.core.frame.DataFrame, x_label: str | None = None, cb_label: str | None = None, cmap=<matplotlib.colors.ListedColormap object>)[source]
      +static plot_evolution_from_data(df: ~pandas.core.frame.DataFrame, x_label: str | None = None, cb_label: str | None = None, cmap=<matplotlib.colors.ListedColormap object>)[source]

      Plot the evolution with time for a given DataFrame. It can be RDF, atomic distribution or other characterization data we might implement in the future.

      @@ -218,7 +219,7 @@

      Navigation

      -plot_rdf_evolution(pair: tuple, cmap=<matplotlib.colors.ListedColormap object>, df: ~pandas.core.frame.DataFrame = None)[source]
      +plot_rdf_evolution(pair: tuple, cmap=<matplotlib.colors.ListedColormap object>, df: ~pandas.core.frame.DataFrame = None)[source]

      Plot the RDF evolution with time for a given pair.

      Parameters:
      @@ -238,7 +239,7 @@

      Navigation

      -static rdf(structure: Structure, pair: tuple, ngrid: int = 101, rmax: float = 10)[source]
      +static rdf(structure: Structure, pair: tuple, ngrid: int = 101, rmax: float = 10)[source]

      Process rdf from a given structure and pair.

      Parameters:
      @@ -259,15 +260,16 @@

      Navigation

      -class VanHoveAnalysis(diffusion_analyzer: DiffusionAnalyzer, avg_nsteps: int = 50, ngrid: int = 101, rmax: float = 10.0, step_skip: int = 50, sigma: float = 0.1, cell_range: int = 1, species: tuple | list = ('Li', 'Na'), reference_species: tuple | list | None = None, indices: list | None = None)[source]
      +class VanHoveAnalysis(diffusion_analyzer: DiffusionAnalyzer, avg_nsteps: int = 50, ngrid: int = 101, rmax: float = 10.0, step_skip: int = 50, sigma: float = 0.1, cell_range: int = 1, species: tuple | list = ('Li', 'Na'), reference_species: tuple | list | None = None, indices: list | None = None)[source]

      Bases: object

      -

      Class for van Hove function analysis. In particular, self-part (Gs) and -distinct-part (Gd) of the van Hove correlation function G(r,t) -for given species and given structure are computed. If you use this class, -please consider citing the following paper:

      -

      Zhu, Z.; Chu, I.-H.; Deng, Z. and Ong, S. P. “Role of Na+ Interstitials -and Dopants in Enhancing the Na+ Conductivity of the Cubic Na3PS4 -Superionic Conductor”. Chem. Mater. (2015), 27, pp 8318-8325

      +

      Class for van Hove function analysis.

      +

      In particular, self-part (Gs) and distinct-part (Gd) of the van Hove correlation function G(r,t) for given species +and given structure are computed. If you use this class, please consider citing the following paper:

      +
      Zhu, Z.; Chu, I.-H.; Deng, Z. and Ong, S. P. "Role of Na+ Interstitials
+and Dopants in Enhancing the Na+ Conductivity of the Cubic Na3PS4
+Superionic Conductor". Chem. Mater. (2015), 27, pp 8318-8325
+
      +

      Initiation.

      Parameters:
      @@ -296,7 +298,7 @@

      Navigation

      -get_1d_plot(mode: str = 'distinct', times: list = [0.0], colors: list | None = None)[source]
      +get_1d_plot(mode: str = 'distinct', times: list | None = None, colors: list | None = None)[source]

      Plot the van Hove function at given r or t.

      Parameters:
      @@ -313,7 +315,7 @@

      Navigation

      -get_3d_plot(figsize: tuple = (12, 8), mode: str = 'distinct')[source]
      +get_3d_plot(figsize: tuple = (12, 8), mode: str = 'distinct')[source]

      Plot 3D self-part or distinct-part of van Hove function, which is specified by the input argument ‘type’.

      @@ -365,7 +367,7 @@

      This Page

      rel="nofollow">Show Source
      - + diff --git a/docs/pymatgen.analysis.diffusion.analyzer.html b/docs/pymatgen.analysis.diffusion.analyzer.html index 6368aff..83ac134 100644 --- a/docs/pymatgen.analysis.diffusion.analyzer.html +++ b/docs/pymatgen.analysis.diffusion.analyzer.html @@ -1,16 +1,16 @@ - + - + - pymatgen.analysis.diffusion.analyzer module — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.analyzer module — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

      Navigation

    • modules |
      • -
    • pymatgen-diffusion 2023.8.15 documentation »
      • +
    • pymatgen-diffusion 2024.6.10 documentation »
    • pymatgen.analysis.diffusion.analyzer module
      • @@ -46,9 +46,9 @@

      Navigation

      -

      pymatgen.analysis.diffusion.analyzer module

      -

      A module to perform diffusion analyses (e.g. calculating diffusivity from -mean square displacements etc.). If you use this module, please consider +

      pymatgen.analysis.diffusion.analyzer module

      +

      A module to perform diffusion analyses.

      +

      For example, calculating diffusivity from mean square displacements etc.). If you use this module, please consider citing the following papers:

      Ong, S. P., Mo, Y., Richards, W. D., Miara, L., Lee, H. S., & Ceder, G.
 (2013). Phase stability, electrochemical stability and ionic conductivity
@@ -63,7 +63,7 @@ 
      Navigation
      -class DiffusionAnalyzer(structure, displacements, specie, temperature, time_step, step_skip, smoothed='max', min_obs=30, avg_nsteps=1000, lattices=None, c_ranges=None, c_range_include_edge=False, structures=None)[source]
      +class DiffusionAnalyzer(structure, displacements, specie, temperature, time_step, step_skip, smoothed='max', min_obs=30, avg_nsteps=1000, lattices=None, c_ranges=None, c_range_include_edge=False, structures=None)[source]

      Bases: MSONable

      Class for performing diffusion analysis.

      This constructor is meant to be used with pre-processed data. @@ -138,13 +138,13 @@

      Navigation

      -as_dict()[source]
      -

      Returns: MSONable dict

      +as_dict()[source] +

      Returns: MSONable dict.

      -export_msdt(filename)[source]
      +export_msdt(filename)[source]

      Writes MSD data to a csv file that can be easily plotted in other software.

      @@ -158,10 +158,10 @@

      Navigation

      -classmethod from_dict(d)[source]
      +classmethod from_dict(d)[source]
      Parameters:
      -

      d (dict) – Dict representation

      +

      d (dict) – Dict representation.

      Returns: DiffusionAnalyzer

      @@ -169,7 +169,7 @@

      Navigation

      -classmethod from_files(filepaths, specie, step_skip=10, ncores=None, initial_disp=None, initial_structure=None, **kwargs)[source]
      +classmethod from_files(filepaths, specie, step_skip=10, ncores=None, initial_disp=None, initial_structure=None, **kwargs)[source]

      Convenient constructor that takes in a list of vasprun.xml paths to perform diffusion analysis.

      @@ -202,7 +202,7 @@

      Navigation

      typically need to supply both variables. This stipulates the initial structure from which the current set of displacements are computed.

      -

    • \*\*kwargs – kwargs supported by the :class:`DiffusionAnalyzer`_. +

    • **kwargs – kwargs supported by the :class:`DiffusionAnalyzer`_. Examples include smoothed, min_obs, avg_nsteps.

      • @@ -211,7 +211,7 @@

      Navigation

      -classmethod from_structures(structures, specie, temperature, time_step, step_skip, initial_disp=None, initial_structure=None, **kwargs)[source]
      +classmethod from_structures(structures, specie, temperature, time_step, step_skip, initial_disp=None, initial_structure=None, **kwargs)[source]

      Convenient constructor that takes in a list of Structure objects to perform diffusion analysis.

      @@ -237,7 +237,7 @@

      Navigation

      typically need to supply both variables. This stipulates the initial structure from which the current set of displacements are computed.

      -

    • \*\*kwargs – kwargs supported by the :class:`DiffusionAnalyzer`_. +

    • **kwargs – kwargs supported by the :class:`DiffusionAnalyzer`_. Examples include smoothed, min_obs, avg_nsteps.

      • @@ -246,7 +246,7 @@

      Navigation

      -classmethod from_vaspruns(vaspruns, specie, initial_disp=None, initial_structure=None, **kwargs)[source]
      +classmethod from_vaspruns(vaspruns, specie, initial_disp=None, initial_structure=None, **kwargs)[source]

      Convenient constructor that takes in a list of Vasprun objects to perform diffusion analysis.

      @@ -267,7 +267,7 @@

      Navigation

      typically need to supply both variables. This stipulates the initial stricture from which the current set of displacements are computed.

      -

    • \*\*kwargs – kwargs supported by the :class:`DiffusionAnalyzer`_. +

    • **kwargs – kwargs supported by the :class:`DiffusionAnalyzer`_. Examples include smoothed, min_obs, avg_nsteps.

      • @@ -276,20 +276,16 @@

      Navigation

      -get_drift_corrected_structures(start=None, stop=None, step=None)[source]
      +get_drift_corrected_structures(start=None, stop=None, step=None)[source]

      Returns an iterator for the drift-corrected structures. Use of iterator is to reduce memory usage as # of structures in MD can be huge. You don’t often need all the structures all at once.

      Parameters:
        -

      • start (int) – applies a start/stop/step to the iterator. -Faster than applying it after generation, as it reduces the -number of structures created.

        • -

      • stop (int) – applies a start/stop/step to the iterator. -Faster than applying it after generation, as it reduces the -number of structures created.

        • -

      • step (int) – applies a start/stop/step to the iterator. +

      • start (int) – Applies a start to the iterator.

        • +

      • stop (int) – Applies a stop to the iterator.

        • +

      • step (int) – Applies a step to the iterator. Faster than applying it after generation, as it reduces the number of structures created.

      @@ -299,7 +295,7 @@

      Navigation

      -get_framework_rms_plot(plt=None, granularity=200, matching_s=None)[source]
      +get_framework_rms_plot(granularity=200, matching_s=None)[source]

      Get the plot of rms framework displacement vs time. Useful for checking for melting, especially if framework atoms can move via paddle-wheel or similar mechanism (which would show up in max framework displacement @@ -307,8 +303,6 @@

      Navigation

      Parameters:
        -

      • plt (matplotlib.pyplot) – If plt is supplied, changes will be made -to an existing plot. Otherwise, a new plot will be created.

      • granularity (int) – Number of structures to match

      • matching_s (Structure) – Optionally match to a disordered structure instead of the first structure in the analyzer. Required when @@ -322,7 +316,7 @@

        Navigation

        -get_msd_plot(plt=None, mode='specie')[source]
        +get_msd_plot(mode='specie')[source]

        Get the plot of the smoothed msd vs time graph. Useful for checking convergence. This can be written to an image file.

        @@ -340,14 +334,14 @@

        Navigation

        -get_summary_dict(include_msd_t=False, include_mscd_t=False)[source]
        +get_summary_dict(include_msd_t=False, include_mscd_t=False)[source]

        Provides a summary of diffusion information.

        Parameters:

        • include_msd_t (bool) – Whether to include mean square displace and time data with the data.

          • -

        • include_msd_t – Whether to include mean square charge displace and +

        • include_mscd_t (bool) – Whether to include mean square charge displace and time data with the data.

        @@ -359,7 +353,7 @@

        Navigation

        -plot_msd(mode='default')[source]
        +plot_msd(mode='default')[source]

        Plot the smoothed msd vs time graph. Useful for checking convergence.

        Parameters:
        @@ -376,9 +370,9 @@

        Navigation

        -fit_arrhenius(temps, diffusivities)[source]
        +fit_arrhenius(temps, diffusivities)[source]
        -
        Returns Ea, c, standard error of Ea from the Arrhenius fit:

        D = c * exp(-Ea/kT)

        +
        Returns Ea, c, standard error of Ea from the Arrhenius fit.

        D = c * exp(-Ea/kT).

        @@ -394,7 +388,7 @@

        Navigation

        -get_arrhenius_plot(temps, diffusivities, diffusivity_errors=None, **kwargs)[source]
        +get_arrhenius_plot(temps, diffusivities, diffusivity_errors=None, **kwargs)[source]

        Returns an Arrhenius plot.

        Parameters:
        @@ -404,7 +398,7 @@

        Navigation

        from DiffusionAnalyzer.diffusivity).

      • diffusivity_errors ([float]) – A sequence of errors for the diffusivities. If None, no error bar is plotted.

        • -

      • \*\*kwargs – Any keyword args supported by matplotlib.pyplot.plot.

        • +

      • **kwargs – Any keyword args supported by matplotlib.pyplot.plot.

      Returns:
      @@ -415,7 +409,7 @@

      Navigation

      -get_conversion_factor(structure, species, temperature)[source]
      +get_conversion_factor(structure, species, temperature)[source]

      Conversion factor to convert between cm^2/s diffusivity measurements and mS/cm conductivity measurements based on number of atoms of diffusing species. Note that the charge is based on the oxidation state of the @@ -438,8 +432,8 @@

      Navigation

      -get_diffusivity_from_msd(msd, dt, smoothed='max')[source]
      -

      Returns diffusivity and standard deviation of diffusivity given by:

      +get_diffusivity_from_msd(msd, dt, smoothed='max')[source] +

      Returns diffusivity and standard deviation of diffusivity.

      D = 1 / 2dt * <mean square displacement>

      @@ -475,7 +469,7 @@

      Navigation

      -get_extrapolated_conductivity(temps, diffusivities, new_temp, structure, species)[source]
      +get_extrapolated_conductivity(temps, diffusivities, new_temp, structure, species)[source]

      Returns extrapolated mS/cm conductivity.

      Parameters:
      @@ -496,8 +490,8 @@

      Navigation

      -get_extrapolated_diffusivity(temps, diffusivities, new_temp)[source]
      -

      Returns (Arrhenius) extrapolated diffusivity at new_temp

      +get_extrapolated_diffusivity(temps, diffusivities, new_temp)[source] +

      Returns (Arrhenius) extrapolated diffusivity at new_temp.

      Parameters:
        @@ -562,7 +556,7 @@

        This Page

        rel="nofollow">Show Source
      - +
      diff --git a/docs/pymatgen.analysis.diffusion.html b/docs/pymatgen.analysis.diffusion.html index 9fd56f3..031228d 100644 --- a/docs/pymatgen.analysis.diffusion.html +++ b/docs/pymatgen.analysis.diffusion.html @@ -1,16 +1,16 @@ - + - + - pymatgen.analysis.diffusion package — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion package — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

      Navigation

    • modules |
      • -
    • pymatgen-diffusion 2023.8.15 documentation »
      • +
    • pymatgen-diffusion 2024.6.10 documentation »
    • pymatgen.analysis.diffusion package
      • @@ -46,9 +46,9 @@

      Navigation

      -

      pymatgen.analysis.diffusion package

      +

      pymatgen.analysis.diffusion package

      -

      Subpackages

      +

      Subpackages

      @@ -328,7 +328,7 @@

      This Page

      rel="nofollow">Show Source
      - + diff --git a/docs/pymatgen.analysis.diffusion.neb.full_path_mapper.html b/docs/pymatgen.analysis.diffusion.neb.full_path_mapper.html index a5c774e..d91715a 100644 --- a/docs/pymatgen.analysis.diffusion.neb.full_path_mapper.html +++ b/docs/pymatgen.analysis.diffusion.neb.full_path_mapper.html @@ -1,16 +1,16 @@ - + - + - pymatgen.analysis.diffusion.neb.full_path_mapper module — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.neb.full_path_mapper module — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

      Navigation

    • modules |
      • -
    • pymatgen-diffusion 2023.8.15 documentation »
      • +
    • pymatgen-diffusion 2024.6.10 documentation »
    • pymatgen.analysis.diffusion.neb.full_path_mapper module
      • @@ -46,44 +46,43 @@

      Navigation

      -

      pymatgen.analysis.diffusion.neb.full_path_mapper module

      -

      Migraiton Graph Analysis

      +

      pymatgen.analysis.diffusion.neb.full_path_mapper module

      +

      Migration Graph Analysis.

      -class ChargeBarrierGraph(structure: Structure, m_graph: StructureGraph, potential_field: VolumetricData, potential_data_key: str, **kwargs)[source]
      +class ChargeBarrierGraph(structure: Structure, m_graph: StructureGraph, potential_field: VolumetricData, potential_data_key: str, **kwargs)[source]

      Bases: MigrationGraph

      -

      A Migration graph with additional charge density analysis on the charge density of the host material

      +

      A Migration graph with additional charge density analysis on the charge density of the host material.

      Construct the MigrationGraph object using a VolumetricData object. -The graph is constructure using the structure, and cost values are assigned based on charge density analysis. -:param potential_field: Input VolumetricData object that describes the field does

      -
      -

      not have to contains all the metastable sites.

      -
      +The graph is constructed using the structure, and cost values are assigned based on charge density analysis.

      Parameters:
        -

      • migrating_specie (Specie-like) – The specie that migrates. E.g., -“Li”.

        • -

      • symprec (float) – Symmetry precision to determine equivalence.

        • +

      • structure (Structure) – Input structure.

        • +

      • m_graph (StructureGraph) – Input structure graph.

        • +

      • potential_field – Input VolumetricData object that describes the field does +not have to contains all the metastable sites.

        • +

      • potential_data_key (str) – Key for potential data.

        • +

      • **kwargs – Passthru for kwargs.

      -get_least_chg_path()[source]
      +get_least_chg_path()[source]

      obtain an intercolating pathway through the material that has the least amount of charge -:returns: list of hops

      +:returns: list of hops.

      -get_summary_dict(add_keys: list[str] | None = None)[source]
      -

      Dictionary format, for saving to database

      +get_summary_dict(add_keys: list[str] | None = None)[source] +

      Dictionary format, for saving to database.

      -populate_edges_with_chg_density_info(tube_radius=1)[source]
      +populate_edges_with_chg_density_info(tube_radius=1)[source]
      Parameters:

      tube_radius – Tube radius.

      @@ -95,7 +94,7 @@

      Navigation

      -class MigrationGraph(structure: Structure, m_graph: StructureGraph, symprec=0.1, vac_mode=False)[source]
      +class MigrationGraph(structure: Structure, m_graph: StructureGraph, symprec=0.1, vac_mode=False)[source]

      Bases: MSONable

      A python object for handling the migratrion graph of a given base structure and mobile specie sites within that base structure.

      @@ -106,15 +105,13 @@

      Navigation

      all mobile sites occupied. A potential_field graph is generated by connecting all sites as specified by the migration graph. The sites are decorated with Migration graph objects and then grouped -together based on their equivalence. -:param structure: Structure with base framework and mobile sites.

      -
      -

      When used with structure_is_base = True, only the base framework -structure, does not contain any migrating sites.

      -
      +together based on their equivalence.

      Parameters:
        +

      • structure – Structure with base framework and mobile sites. +When used with structure_is_base = True, only the base framework +structure, does not contain any migrating sites.

      • m_graph – The StructureGraph object that defines the migration network

      • symprec (float) – Symmetry precision to determine equivalence @@ -125,27 +122,27 @@

        Navigation

      -add_data_to_similar_edges(target_label: int | str, data: dict, m_hop: MigrationHop | None = None)[source]
      +add_data_to_similar_edges(target_label: int | str, data: dict, m_hop: MigrationHop | None = None)[source]

      Insert data to all edges with the same label :param target_label: The edge uniqueness label are adding data :param data: The data to passed to the different edges :param m_hop: If the data is an array, and m_hop is set, it uses the reference migration path to -:param determine whether the data needs to be flipped so that 0–>1 is different from 1–>0:

      +:param determine whether the data needs to be flipped so that 0–>1 is different from 1–>0.:

      -assign_cost_to_graph(cost_keys=['hop_distance'])[source]
      +assign_cost_to_graph(cost_keys=None)[source]

      Read the data dict on each add and populate a cost key :param cost_keys: a list of keys for data on each edge.

      -

      The SC Graph is decorated with a “cost” key that is the product of the different keys here

      +

      The SC Graph is decorated with a “cost” key that is the product of the different keys here.

      -get_path(max_val=100000, flip_hops=True)[source]
      +get_path(max_val=100000, flip_hops=True)[source]

      obtain a pathway through the material using hops that are in the current graph Basic idea:

      @@ -174,7 +171,7 @@

      Navigation

      -static get_structure_from_entries(entries: list[ComputedStructureEntry], migrating_ion_entry: ComputedEntry, **kwargs) → list[Structure][source]
      +static get_structure_from_entries(entries: list[ComputedStructureEntry], migrating_ion_entry: ComputedEntry, **kwargs) → list[Structure][source]

      Read in a list of base entries and inserted entries. Return a list of structures that contains metastable sites for the migration species decorated with a “insertion_energy” property.

      @@ -182,6 +179,7 @@

      Navigation

      • entries – list of entries, must contain a mixture of inserted and empty structures.

      • migrating_ion_entry – The metallic phase of the working ion, used to calculate insertion energies.

        • +

      • **kwargs – Passthrough for kwargs.

      @@ -189,7 +187,7 @@

      Navigation

      Additional Kwargs:

      symprec: symmetry parameter for SpacegroupAnalyzer ltol: Fractional length tolerance for StructureMatcher stol: Site tolerance for StructureMatcher -angle_tol: Angle tolerance fro StructureMatcher and SpacegroupAnalyzer +angle_tol: Angle tolerance for StructureMatcher and SpacegroupAnalyzer only_single_cat: If True, only use single cation insertions so the site energy is more accurate use_strict_tol: halve the ltol and stol parameter for more strict matching.

      @@ -206,41 +204,52 @@

      Navigation

      -get_summary_dict(added_keys: list[str] | None = None) → dict[source]
      -

      Dictionary format, for saving to database

      +get_summary_dict(added_keys: list[str] | None = None) → dict[source] +

      Dictionary format, for saving to database.

      +
      +
      Parameters:
      +

      added_keys – a list of keys for data on each edge.

      +
      +
      Returns:
      +

      Dict.

      +
      +
      -property host_structure: Structure
      -

      A structure that only contains the non-migrating species

      +property host_structure: Structure +

      A structure that only contains the non-migrating species.

      -property only_sites: Structure
      -

      A structure that only contains the migrating species

      +property only_sites: Structure +

      A structure that only contains the migrating species.

      -property symm_structure: SymmetrizedStructure
      -

      The symmetrized structure with the present item’s symprec value

      +property symm_structure: SymmetrizedStructure +

      The symmetrized structure with the present item’s symprec value.

      -property unique_hops
      -

      The unique hops dictionary keyed by the hop label

      +property unique_hops +

      The unique hops dictionary keyed by the hop label.

      -classmethod with_base_structure(base_structure: Structure, m_graph: StructureGraph, **kwargs) → MigrationGraph[source]
      +classmethod with_base_structure(base_structure: Structure, m_graph: StructureGraph, **kwargs) → MigrationGraph[source]
      Parameters:
      -

      base_structure – base framework structure that does not contain any -migrating sites.

      +
        +

      • base_structure – base framework structure that does not contain any migrating sites.

        • +

      • m_graph – The StructureGraph object that defines the migration network.

        • +

      • **kwargs – Passthrough for kwargs.

        • +
      Returns:

      A constructed MigrationGraph object

      @@ -250,30 +259,40 @@

      Navigation

      -classmethod with_distance(structure: Structure, migrating_specie: str, max_distance: float, **kwargs) → MigrationGraph[source]
      -

      Using a specific nn strategy to get the connectivity graph between all the migrating ion sites. -:param max_distance: Maximum length of NEB path in the unit

      -
      -

      of Angstrom. Defaults to None, which means you are setting the -value to the min cutoff until finding 1D or >1D percolating paths.

      -
      +classmethod with_distance(structure: Structure, migrating_specie: str, max_distance: float, **kwargs) → MigrationGraph[source] +

      Using a specific nn strategy to get the connectivity graph between all the migrating ion sites.

      -
      Returns:
      -

      A constructed MigrationGraph object

      +
      Parameters:
      +
        +

      • structure – Input structure that contains all sites.

        • +

      • migrating_specie – The specie that migrates. E.g. “Li”.

        • +

      • max_distance – Maximum length of NEB path in the unit +of Angstrom. Defaults to None, which means you are setting the +value to the min cutoff until finding 1D or >1D percolating paths.

        • +

      • **kwargs – Passthrough for kwargs.

        • +
      +
      +
      Returns:
      +

      A constructed MigrationGraph object

      -classmethod with_local_env_strategy(structure: Structure, migrating_specie: str, nn: NearNeighbors, **kwargs) → MigrationGraph[source]
      -

      Using a specific nn strategy to get the connectivity graph between all the migrating ion sites. -:param structure: Input structure that contains all sites. -:param migrating_specie: The specie that migrates. E.g. “Li”. -:param nn: The specific local environment object used to connect the migrating ion sites.

      +classmethod with_local_env_strategy(structure: Structure, migrating_specie: str, nn: NearNeighbors, **kwargs) → MigrationGraph[source] +

      Using a specific nn strategy to get the connectivity graph between all the migrating ion sites.

      -
      Returns:
      -

      A constructed MigrationGraph object

      +
      Parameters:
      +
        +

      • structure – Input structure that contains all sites.

        • +

      • migrating_specie – The specie that migrates. E.g. “Li”.

        • +

      • nn – The specific local environment object used to connect the migrating ion sites.

        • +

      • **kwargs – Passthrough for kwargs.

        • +
      +
      +
      Returns:
      +

      A constructed MigrationGraph object

      @@ -282,20 +301,24 @@

      Navigation

      -almost(a, b)[source]
      -

      return true if the values are almost equal

      +almost(a, b)[source] +

      Return true if the values are almost equal.

      -check_uc_hop(sc_hop, uc_hop)[source]
      +check_uc_hop(sc_hop, uc_hop)[source]

      See if hop in the 2X2X2 supercell and a unit cell hop -are equilvalent under lattice translation -:param sc_hop: MigrationHop object form pymatgen-diffusion. -:param uc_hop: MigrationHop object form pymatgen-diffusion.

      +are equivalent under lattice translation.

      -
      Returns:
      -

      image vector of lenght 3 +

      Parameters:
      +
        +

      • sc_hop – MigrationHop object form pymatgen-diffusion.

        • +

      • uc_hop – MigrationHop object form pymatgen-diffusion.

        • +
      +
      +
      Returns:
      +

      image vector of length 3 Is the UC hop flip of the SC hop

      @@ -303,54 +326,71 @@

      Navigation

      -generic_groupby(list_in: list, comp: ~typing.Callable = <built-in function eq>)[source]
      -

      Group a list of unsortable objects -:param list_in: A list of generic objects -:param comp: (Default value = operator.eq) The comparator

      +generic_groupby(list_in: list, comp: ~typing.Callable = <built-in function eq>)[source] +

      Group a list of unsortable objects.

      -
      Returns:
      -

      [int] list of labels for the input list

      +
      Parameters:
      +
        +

      • list_in – A list of generic objects

        • +

      • comp – (Default value = operator.eq) The comparator

        • +
      +
      +
      Returns:
      +

      [int] list of labels for the input list

      -get_hop_site_sequence(hop_list: list[dict], start_u: int | str, key: str | None = None) → list[source]
      -

      Read in a list of hop dictionaries and print the sequence of sites (and relevant property values if any). -:param hop_list: a list of the data on a sequence of hops -:param start_u: the site index of the starting sites -:param key: property to track in a hop (e.g.: “hop_distance”) -:type key: optional

      +get_hop_site_sequence(hop_list: list[dict], start_u: int | str, key: str | None = None) → list[source] +

      Read in a list of hop dictionaries and print the sequence of sites (and relevant property values if any).

      -
      Returns:
      -

      String representation of the hop sequence (and property values if any)

      +
      Parameters:
      +
        +

      • hop_list – a list of the data on a sequence of hops

        • +

      • start_u – the site index of the starting sites

        • +

      • key (optional) – property to track in a hop (e.g.: “hop_distance”)

        • +
      +
      +
      Returns:
      +

      String representation of the hop sequence (and property values if any)

      -get_only_sites_from_structure(structure: Structure, migrating_specie: str) → Structure[source]
      -

      Get a copy of the structure with only the migrating sites. -:param structure: The full_structure that contains all the sites -:param migrating_specie: The name of migrating species

      +get_only_sites_from_structure(structure: Structure, migrating_specie: str) → Structure[source] +

      Get a copy of the structure with only the migrating sites.

      -
      Returns:
      -

      Structure with all possible migrating ion sites

      +
      Parameters:
      +
        +

      • structure – The full_structure that contains all the sites

        • +

      • migrating_specie – The name of migrating species

        • +
      -
      Return type:
      -

      Structure

      +
      Returns:
      +

      Structure with all possible migrating ion sites

      +
      +
      Return type:
      +

      Structure

      -map_hop_sc2uc(sc_hop: MigrationHop, mg: MigrationGraph)[source]
      -

      Map a given hop in the SC onto the UC. -:param sc_hop: MigrationHop object form pymatgen-diffusion. -:param mg: MigrationGraph object from pymatgen-diffusion.

      +map_hop_sc2uc(sc_hop: MigrationHop, mg: MigrationGraph)[source] +

      Map a given hop in the SC onto the UC.

      +
      +
      Parameters:
      +
        +

      • sc_hop – MigrationHop object form pymatgen-diffusion.

        • +

      • mg – MigrationGraph object from pymatgen-diffusion.

        • +
      +
      +

      Note

      For now assume that the SC is exactly 2x2x2 of the UC. @@ -363,18 +403,22 @@

      Navigation

      -order_path(hop_list: list[dict], start_u: int | str) → list[dict][source]
      +order_path(hop_list: list[dict], start_u: int | str) → list[dict][source]

      Takes a list of hop dictionaries and flips hops (switches isite and esite) as needed to form a coherent path / sequence of sites according to get_hop_site_sequence(). For example if hop_list = [{iindex:0, eindex:1, etc.}, {iindex:0, eindex:1, etc.}] then the output is [{iindex:0, eindex:1, etc.}, {iindex:1, eindex:0, etc.}] so that -the following hop iindex matches the previous hop’s eindex. -:param hop_list: a list of the data on a sequence of hops -:param start_u: the site index of the starting sites

      +the following hop iindex matches the previous hop’s eindex.

      -
      Returns:
      -

      a list of the data on a sequence of hops with hops in coherent orientation

      +
      Parameters:
      +
        +

      • hop_list – a list of the data on a sequence of hops

        • +

      • start_u – the site index of the starting sites

        • +
      +
      +
      Returns:
      +

      a list of the data on a sequence of hops with hops in coherent orientation

      @@ -436,7 +480,7 @@

      This Page

      rel="nofollow">Show Source
      - +
      diff --git a/docs/pymatgen.analysis.diffusion.neb.html b/docs/pymatgen.analysis.diffusion.neb.html index b3f927c..b4edc13 100644 --- a/docs/pymatgen.analysis.diffusion.neb.html +++ b/docs/pymatgen.analysis.diffusion.neb.html @@ -1,16 +1,16 @@ - + - + - pymatgen.analysis.diffusion.neb package — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.neb package — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

      Navigation

    • modules |
      • -
    • pymatgen-diffusion 2023.8.15 documentation »
      • +
    • pymatgen-diffusion 2024.6.10 documentation »
    • pymatgen.analysis.diffusion.neb package
      • @@ -46,14 +46,14 @@

      Navigation

      -

      pymatgen.analysis.diffusion.neb package

      +

      pymatgen.analysis.diffusion.neb package

      -

      Subpackages

      +

      Subpackages

      -

      Submodules

      +

      Submodules

      @@ -177,7 +177,7 @@

      This Page

      rel="nofollow">Show Source
      - + diff --git a/docs/pymatgen.analysis.diffusion.neb.io.html b/docs/pymatgen.analysis.diffusion.neb.io.html index e13c6d9..fb80b8e 100644 --- a/docs/pymatgen.analysis.diffusion.neb.io.html +++ b/docs/pymatgen.analysis.diffusion.neb.io.html @@ -1,16 +1,16 @@ - + - + - pymatgen.analysis.diffusion.neb.io module — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.neb.io module — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

      Navigation

    • modules |
      • -
    • pymatgen-diffusion 2023.8.15 documentation »
      • +
    • pymatgen-diffusion 2024.6.10 documentation »
    • pymatgen.analysis.diffusion.neb.io module
      • @@ -46,11 +46,11 @@

      Navigation

      -

      pymatgen.analysis.diffusion.neb.io module

      -

      Generate input fiels for NEB calculations.

      +

      pymatgen.analysis.diffusion.neb.io module

      +

      Generate input fields for NEB calculations.

      -class MVLCINEBEndPointSet(structure, **kwargs)[source]
      +class MVLCINEBEndPointSet(structure, **kwargs)[source]

      Bases: MITRelaxSet

      Class for writing NEB end points relaxation inputs.

      @@ -65,15 +65,15 @@

      Navigation

      -class MVLCINEBSet(structures, **kwargs)[source]
      +class MVLCINEBSet(structures, **kwargs)[source]

      Bases: MITNEBSet

      MAVRL-tested settings for CI-NEB calculations. Note that these parameters requires the VTST modification of VASP from the Henkelman group. See -http://theory.cm.utexas.edu/vtsttools/

      +http://theory.cm.utexas.edu/vtsttools/.

      Parameters:
        -

      • structure – Structure

        • +

      • structures – Input structures.

      • **kwargs – Keyword args supported by VaspInputSets.

      @@ -82,26 +82,28 @@

      Navigation

      -get_endpoint_dist(ep_0, ep_1)[source]
      +get_endpoint_dist(ep_0, ep_1)[source]

      Calculate a list of site distances between two endpoints, assuming periodic -boundary conditions. -:param ep_0: the first endpoint structure. -:type ep_0: Structure -:param ep_1: the second endpoint structure. -:type ep_1: Structure

      +boundary conditions.

      -
      Returns:
      -

      a list of distances between two structures.

      +
      Parameters:
      +
        +

      • ep_0 (Structure) – the first endpoint structure.

        • +

      • ep_1 (Structure) – the second endpoint structure.

        • +
      -
      Return type:
      -

      dist (list)

      +
      Returns:
      +

      a list of distances between two structures.

      +
      +
      Return type:
      +

      dist (list)

      -get_endpoints_from_index(structure, site_indices)[source]
      +get_endpoints_from_index(structure, site_indices)[source]

      This class reads in one perfect structure and the two endpoint structures are generated using site_indices.

      @@ -157,7 +159,7 @@

      This Page

      rel="nofollow">Show Source
      - + diff --git a/docs/pymatgen.analysis.diffusion.neb.pathfinder.html b/docs/pymatgen.analysis.diffusion.neb.pathfinder.html index 64bb6c6..e2eb8da 100644 --- a/docs/pymatgen.analysis.diffusion.neb.pathfinder.html +++ b/docs/pymatgen.analysis.diffusion.neb.pathfinder.html @@ -1,16 +1,16 @@ - + - + - pymatgen.analysis.diffusion.neb.pathfinder module — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.neb.pathfinder module — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

      Navigation

    • modules |
      • -
    • pymatgen-diffusion 2023.8.15 documentation »
      • +
    • pymatgen-diffusion 2024.6.10 documentation »
    • pymatgen.analysis.diffusion.neb.pathfinder module
      • @@ -46,11 +46,11 @@

      Navigation

      -

      pymatgen.analysis.diffusion.neb.pathfinder module

      +

      pymatgen.analysis.diffusion.neb.pathfinder module

      Algorithms for NEB migration path analysis.

      -class ChgcarPotential(chgcar, smear=False, normalize=True)[source]
      +class ChgcarPotential(chgcar, smear=False, normalize=True)[source]

      Bases: StaticPotential

      Implements a potential field based on the charge density output from VASP.

      @@ -69,7 +69,7 @@

      Navigation

      -class DistinctPathFinder(structure, migrating_specie, max_path_length=None, symprec=0.1, perc_mode='>1d')[source]
      +class DistinctPathFinder(structure, migrating_specie, max_path_length=None, symprec=0.1, perc_mode='>1d')[source]

      Bases: object

      Determines symmetrically distinct paths between existing sites. The path info can then be used to set up either vacancy or interstitial @@ -93,7 +93,7 @@

      Navigation

      -get_paths()[source]
      +get_paths()[source]
      Returns:

      [MigrationHop] All distinct migration paths.

      @@ -103,7 +103,7 @@

      Navigation

      -write_all_paths(fname, nimages=5, **kwargs)[source]
      +write_all_paths(fname, nimages=5, **kwargs)[source]

      Write a file containing all paths, using hydrogen as a placeholder for the images. H is chosen as it is the smallest atom. This is extremely useful for path visualization in a standard software like VESTA.

      @@ -122,7 +122,7 @@

      Navigation

      -class FreeVolumePotential(struct, dim, smear=False, normalize=True)[source]
      +class FreeVolumePotential(struct, dim, smear=False, normalize=True)[source]

      Bases: StaticPotential

      Implements a potential field based on geometric distances from atoms in the structure - basically, the potential @@ -143,7 +143,7 @@

      Navigation

      -class IDPPSolver(structures)[source]
      +class IDPPSolver(structures)[source]

      Bases: object

      A solver using image dependent pair potential (IDPP) algo to get an improved initial NEB path. For more details about this algo, please refer to @@ -157,7 +157,7 @@

      Navigation

      -classmethod from_endpoints(endpoints, nimages=5, sort_tol=1.0, interpolate_lattices=False)[source]
      +classmethod from_endpoints(endpoints, nimages: int = 5, sort_tol: float = 1.0, interpolate_lattices: bool = False)[source]

      A class method that starts with end-point structures instead. The initial guess for the IDPP algo is then constructed using linear interpolation.

      @@ -169,6 +169,7 @@

      Navigation

    • sort_tol (float) – Distance tolerance (in Angstrom) used to match the atomic indices between start and end structures. Need to increase the value in some cases.

      • +

    • interpolate_lattices (bool) – Whether to interpolate lattices between the start and end structures.

      • @@ -176,14 +177,18 @@

      Navigation

      -static get_unit_vector(vec)[source]
      -

      Calculate the unit vector of a vector. -:param vec: Vector.

      +static get_unit_vector(vec)[source] +

      Calculate the unit vector of a vector.

      +
      +
      Parameters:
      +

      vec – Vector.

      +
      +
      -run(maxiter=1000, tol=1e-05, gtol=0.001, step_size=0.05, max_disp=0.05, spring_const=5.0, species=None)[source]
      +run(maxiter=1000, tol=1e-05, gtol=0.001, step_size=0.05, max_disp=0.05, spring_const=5.0, species=None)[source]

      Perform iterative minimization of the set of objective functions in an NEB-like manner. In each iteration, the total force matrix for each image is constructed, which comprises both the spring forces and true @@ -218,7 +223,7 @@

      Navigation

      -class MigrationHop(isite: Site, esite: Site, symm_structure: SymmetrizedStructure, host_symm_struct: SymmetrizedStructure = None, symprec: float = 0.001)[source]
      +class MigrationHop(isite: Site, esite: Site, symm_structure: SymmetrizedStructure, host_symm_struct: SymmetrizedStructure = None, symprec: float = 0.001)[source]

      Bases: MSONable

      A convenience container representing a migration path.

      @@ -227,15 +232,17 @@

      Navigation

    • isite – Initial site

    • esite – End site

    • symm_structure – SymmetrizedStructure

      • -

    • host_symm_struct – SymmetrizedStructure of the host structure, used to for its spacegroup

      • -

    • symprec – used to determine equivalence

      • +

    • host_symm_struct – SymmetrizedStructure of the host structure, used to for +its spacegroup

      • +

    • symprec – used to determine equivalence.

      • -get_sc_structures(vac_mode: bool, min_atoms: int = 80, max_atoms: int = 240, min_length: float = 10.0, tol: float = 1e-05) → tuple[pymatgen.core.structure.Structure, pymatgen.core.structure.Structure, pymatgen.core.structure.Structure][source]
      -

      Construct supercells that represents the start and end positions for migration analysis.

      +get_sc_structures(vac_mode: bool, min_atoms: int = 80, max_atoms: int = 240, min_length: float = 10.0, tol: float = 1e-05) → tuple[Structure, Structure, Structure][source] +

      Construct supercells that represents the start and end positions for migration +analysis.

      Parameters:
        @@ -257,7 +264,7 @@

        Navigation

        -get_structures(nimages=5, vac_mode=True, idpp=False, **idpp_kwargs)[source]
        +get_structures(nimages=5, vac_mode=True, idpp=False, **idpp_kwargs)[source]

        Generate structures for NEB calculation.

        Parameters:
        @@ -291,14 +298,14 @@

        Navigation

        -property length
        +property length

        Returns: (float) Length of migration path.

        -write_path(fname, **kwargs)[source]
        +write_path(fname, **kwargs)[source]

        Write the path to a file for easy viewing.

        Parameters:
        @@ -314,7 +321,7 @@

        Navigation

        -class MixedPotential(potentials, coefficients, smear=False, normalize=True)[source]
        +class MixedPotential(potentials, coefficients, smear=False, normalize=True)[source]

        Bases: StaticPotential

        Implements a potential that is a weighted sum of some other potentials.

        @@ -332,7 +339,7 @@

        Navigation

        -class NEBPathfinder(start_struct, end_struct, relax_sites, v, n_images=20, mid_struct=None)[source]
        +class NEBPathfinder(start_struct, end_struct, relax_sites, v, n_images=20, mid_struct=None)[source]

        Bases: object

        General pathfinder for interpolating between two structures, where the interpolating path is calculated with the elastic band method with @@ -347,26 +354,27 @@

        Navigation

        Parameters:
          -

        • start_struct – Endpoint structures to interpolate

          • -

        • end_struct – Endpoint structures to interpolate

          • +

        • start_struct – Starting structure

          • +

        • end_struct – End structure to interpolate

        • relax_sites – List of site indices whose interpolation paths should be relaxed

        • v – Static potential field to use for the elastic band relaxation

        • n_images – Number of interpolation images to generate

          • -

        • mid_struct – (optional) additional structure between the start and end structures to help.

          • +

        • mid_struct – (optional) additional structure between the start and end +structures to help.

        -property images
        +property images

        Returns a list of structures interpolating between the start and endpoint structures.

        -interpolate()[source]
        +interpolate()[source]

        Finds a set of n_images from self.s1 to self.s2, where all sites except for the ones given in relax_sites, the interpolation is linear (as in pymatgen.core.structure.interpolate), and for the site indices given @@ -378,14 +386,19 @@

        Navigation

        -plot_images(outfile)[source]
        -

        Generates a POSCAR with the calculated diffusion path with respect to the first endpoint. -:param outfile: Output file for the POSCAR.

        +plot_images(outfile)[source] +

        Generates a POSCAR with the calculated diffusion path with respect to the first +endpoint.

        +
        +
        Parameters:
        +

        outfile – Output file for the POSCAR.

        +
        +
        -static string_relax(start, end, V, n_images=25, dr=None, h=3.0, k=0.17, min_iter=100, max_iter=10000, max_tol=5e-06)[source]
        +static string_relax(start, end, V, n_images=25, dr=None, h=3.0, k=0.17, min_iter=100, max_iter=10000, max_tol=5e-06)[source]

        Implements path relaxation via the elastic band method. In general, the method is to define a path by a set of points (images) connected with bands with some elasticity constant k. The images then relax along the @@ -425,7 +438,7 @@

        Navigation

        -class StaticPotential(struct, pot)[source]
        +class StaticPotential(struct, pot)[source]

        Bases: object

        Defines a general static potential for diffusion calculations. Implements grid-rescaling and smearing for the potential grid. Also provides a @@ -440,7 +453,7 @@

        Navigation

        -gaussian_smear(r)[source]
        +gaussian_smear(r)[source]

        Applies an isotropic Gaussian smear of width (standard deviation) r to the potential field. This is necessary to avoid finding paths through narrow minima or nodes that may exist in the field (although any @@ -455,19 +468,19 @@

        Navigation

        -get_v()[source]
        +get_v()[source]

        Returns the potential.

        -normalize()[source]
        +normalize()[source]

        Sets the potential range 0 to 1.

        -rescale_field(new_dim)[source]
        +rescale_field(new_dim)[source]

        Changes the discretization of the potential field by linear interpolation. This is necessary if the potential field obtained from DFT is strangely skewed, or is too fine or coarse. Obeys @@ -547,7 +560,7 @@

        This Page

        rel="nofollow">Show Source
      - + diff --git a/docs/pymatgen.analysis.diffusion.neb.periodic_dijkstra.html b/docs/pymatgen.analysis.diffusion.neb.periodic_dijkstra.html index 91fe6a4..aeb9a3c 100644 --- a/docs/pymatgen.analysis.diffusion.neb.periodic_dijkstra.html +++ b/docs/pymatgen.analysis.diffusion.neb.periodic_dijkstra.html @@ -1,16 +1,16 @@ - + - + - pymatgen.analysis.diffusion.neb.periodic_dijkstra module — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.neb.periodic_dijkstra module — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

      Navigation

    • modules |
      • -
    • pymatgen-diffusion 2023.8.15 documentation »
      • +
    • pymatgen-diffusion 2024.6.10 documentation »
    • pymatgen.analysis.diffusion.neb.periodic_dijkstra module
      • @@ -46,17 +46,17 @@

      Navigation

      -

      pymatgen.analysis.diffusion.neb.periodic_dijkstra module

      -

      Dijkstra’s path search on a graph where the nodes are on a periodic graph

      +

      pymatgen.analysis.diffusion.neb.periodic_dijkstra module

      +

      Dijkstra’s path search on a graph where the nodes are on a periodic graph.

      -get_optimal_pathway_rev(path_parent: dict, leaf_node: tuple)[source]
      -

      follow a leaf node all the way up to source.

      +get_optimal_pathway_rev(path_parent: dict, leaf_node: tuple)[source] +

      Follow a leaf node all the way up to source.

      -periodic_dijkstra(G: ~networkx.classes.graph.Graph, sources: set, weight: str = 'weight', max_image: int = 2, target_reached: ~typing.Callable = <function <lambda>>)[source]
      +periodic_dijkstra(G: Graph, sources: set, weight: str = 'weight', max_image: int = 2, target_reached: Callable = <function <lambda>>)[source]

      Find the lowest cost pathway from a source point in the periodic graph. Since the search can move many cells away without finding the target we have to limit how many cells away from (0,0,0) to search.

      @@ -66,7 +66,7 @@

      Navigation

    • G (Graph) – The graph object with additional “to_jimage” fields to indicate edges across periodic images.

    • sources (set) – the index of the source node

      • -

    • target (int, optional) – The index of of target node, if None populate all nodes. Defaults to None.

      • +

    • weight – the weight of the edges.

    • max_image (int, optional) – Defaults to 3.

    • target_reached (callable, optional) – A function of (site_index, jimage) used to check for stop iteration. This function is always called on the top of heap so it might miss the optimal path but @@ -85,7 +85,7 @@

      Navigation

      -periodic_dijkstra_on_sgraph(sgraph: ~pymatgen.analysis.graphs.StructureGraph, sources: ~typing.Set, weight: str = 'weight', max_image: int = 1, target_reached: ~typing.Callable = <function <lambda>>)[source]
      +periodic_dijkstra_on_sgraph(sgraph: StructureGraph, sources: set, weight: str = 'weight', max_image: int = 1, target_reached: Callable = <function <lambda>>)[source]

      Find the lowest cost pathway from a source point in the periodic graph. Since the search can move many cells away without finding the target we have to limit how many cells away from (0,0,0) to search.

      @@ -94,7 +94,7 @@

      Navigation

      • sgraph (Graph) – The StructureGraph object used for path searching

      • sources (set) – the index of the source node

        • -

      • target (int, optional) – The index of of target node, if None populate all nodes. Defaults to None.

        • +

      • weight – the weight of the edges.

      • max_image (int, optional) – Defaults to 3.

      • target_reached (callable, optional) – A function of (site_index, jimage) used to check for stop iteration. This function is always called on the top of heap so it might miss the optimal path but @@ -143,7 +143,7 @@

        This Page

        rel="nofollow">Show Source
      • - + diff --git a/docs/pymatgen.analysis.diffusion.neb.tests.test_full_path_mapper.html b/docs/pymatgen.analysis.diffusion.neb.tests.test_full_path_mapper.html index cf3a957..a61e65e 100644 --- a/docs/pymatgen.analysis.diffusion.neb.tests.test_full_path_mapper.html +++ b/docs/pymatgen.analysis.diffusion.neb.tests.test_full_path_mapper.html @@ -1,16 +1,16 @@ - + - + - pymatgen.analysis.diffusion.neb.tests.test_full_path_mapper module — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.neb.tests.test_full_path_mapper module — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

      Navigation

    • modules |
      • -
    • pymatgen-diffusion 2023.8.15 documentation »
      • +
    • pymatgen-diffusion 2024.6.10 documentation »
    • pymatgen.analysis.diffusion.neb.tests.test_full_path_mapper module
      • @@ -46,34 +46,34 @@

      Navigation

      -

      pymatgen.analysis.diffusion.neb.tests.test_full_path_mapper module

      +

      pymatgen.analysis.diffusion.neb.tests.test_full_path_mapper module

      -class ChargeBarrierGraphTest(methodName='runTest')[source]
      +class ChargeBarrierGraphTest(methodName='runTest')[source]

      Bases: TestCase

      Create an instance of the class that will use the named test method when executed. Raises a ValueError if the instance does not have a method with the specified name.

      -setUp()[source]
      +setUp()[source]

      Hook method for setting up the test fixture before exercising it.

      -test_get_summary_dict()[source]
      +test_get_summary_dict()[source]
      -test_integration()[source]
      -

      Sanity check: for a long enough diagonaly hop, if we turn the radius of the tube way up, it should cover the entire unit cell

      +test_integration()[source] +

      Sanity check: for a long enough diagonally hop, if we turn the radius of the tube way up, it should cover the entire unit cell

      -test_populate_edges_with_chg_density_info()[source]
      +test_populate_edges_with_chg_density_info()[source]

      Test that all of the sites with similar lengths have similar charge densities, this will not always be true, but it valid in this Mn6O5F7

      @@ -82,113 +82,114 @@

      Navigation

      -class MigrationGraphComplexTest(methodName='runTest')[source]
      +class MigrationGraphComplexTest(methodName='runTest')[source]

      Bases: TestCase

      Create an instance of the class that will use the named test method when executed. Raises a ValueError if the instance does not have a method with the specified name.

      -setUp()[source]
      +setUp()[source]

      Hook method for setting up the test fixture before exercising it.

      -test_add_data_to_similar_edges()[source]
      +test_add_data_to_similar_edges()[source]
      -test_assign_cost_to_graph()[source]
      +test_assign_cost_to_graph()[source]
      -test_get_key_in_path()[source]
      +test_get_key_in_path()[source]
      -test_get_path()[source]
      +test_get_path()[source]
      -test_group_and_label_hops()[source]
      -

      Check that the set of end points in a group of similiarly labeled hops are all the same

      +test_group_and_label_hops()[source] +

      Check that the set of end points in a group of similarly labeled hops are all +the same.

      -test_not_matching_first()[source]
      +test_not_matching_first()[source]
      -test_order_path()[source]
      +test_order_path()[source]
      -test_periodic_dijkstra()[source]
      +test_periodic_dijkstra()[source]
      -test_unique_hops_dict()[source]
      -

      Check that the unique hops are inequilvalent

      +test_unique_hops_dict()[source] +

      Check that the unique hops are inequivalent

      -class MigrationGraphFromEntriesTest(methodName='runTest')[source]
      +class MigrationGraphFromEntriesTest(methodName='runTest')[source]

      Bases: TestCase

      Create an instance of the class that will use the named test method when executed. Raises a ValueError if the instance does not have a method with the specified name.

      -setUp()[source]
      +setUp()[source]

      Hook method for setting up the test fixture before exercising it.

      -test_m_graph_construction()[source]
      +test_m_graph_construction()[source]
      -test_m_graph_from_entries_failed()[source]
      +test_m_graph_from_entries_failed()[source]
      -class MigrationGraphSimpleTest(methodName='runTest')[source]
      +class MigrationGraphSimpleTest(methodName='runTest')[source]

      Bases: TestCase

      Create an instance of the class that will use the named test method when executed. Raises a ValueError if the instance does not have a method with the specified name.

      -setUp()[source]
      +setUp()[source]

      Hook method for setting up the test fixture before exercising it.

      -test_get_pos_and_migration_hop()[source]
      +test_get_pos_and_migration_hop()[source]

      Make sure that we can populate the graph with MigrationHop Objects

      -test_get_summary_dict()[source]
      +test_get_summary_dict()[source]
      @@ -254,7 +255,7 @@

      This Page

      rel="nofollow">Show Source
      - + diff --git a/docs/pymatgen.analysis.diffusion.neb.tests.test_io.html b/docs/pymatgen.analysis.diffusion.neb.tests.test_io.html index 35c530a..d22545d 100644 --- a/docs/pymatgen.analysis.diffusion.neb.tests.test_io.html +++ b/docs/pymatgen.analysis.diffusion.neb.tests.test_io.html @@ -1,16 +1,16 @@ - + - + - pymatgen.analysis.diffusion.neb.tests.test_io module — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.neb.tests.test_io module — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

      Navigation

    • modules |
      • -
    • pymatgen-diffusion 2023.8.15 documentation »
      • +
    • pymatgen-diffusion 2024.6.10 documentation »
    • pymatgen.analysis.diffusion.neb.tests.test_io module
      • @@ -46,58 +46,58 @@

      Navigation

      -

      pymatgen.analysis.diffusion.neb.tests.test_io module

      +

      pymatgen.analysis.diffusion.neb.tests.test_io module

      -class MVLCINEBEndPointSetTest(methodName='runTest')[source]
      +class MVLCINEBEndPointSetTest(methodName='runTest')[source]

      Bases: TestCase

      Create an instance of the class that will use the named test method when executed. Raises a ValueError if the instance does not have a method with the specified name.

      -endpoint = Structure Summary Lattice     abc : 8.815000056846058 8.815000056846058 9.131710473490111  angles : 61.14080369885537 61.14080369885537 59.9999995733517  volume : 510.2218449146199       A : -4.4075 -7.634014 -0.0       B : 4.4075 -7.634014 0.0       C : -0.0 -5.089343 7.582     pbc : True True True PeriodicSite: Na (0.0, 0.0, 0.0) [0.0, 0.0, 0.0] PeriodicSite: Zr (9.811e-17, -10.18, 0.4774) [0.6457, 0.6457, 0.06296] PeriodicSite: Zr (-2.422e-17, -5.089, 4.268) [0.1457, 0.1457, 0.563] PeriodicSite: Zr (-7.549e-17, -10.18, 7.105) [0.3543, 0.3543, 0.937] PeriodicSite: Zr (-9.811e-17, -15.27, 3.314) [0.8543, 0.8543, 0.437] PeriodicSite: P (-1.837, -7.634, 5.686) [0.4584, 0.0416, 0.75] PeriodicSite: P (3.122, -9.86, 5.686) [0.0416, 0.75, 0.75] PeriodicSite: P (-1.285, -13.04, 5.686) [0.75, 0.4584, 0.75] PeriodicSite: P (-3.122, -10.5, 1.895) [0.9584, 0.25, 0.25] PeriodicSite: P (1.285, -7.315, 1.895) [0.25, 0.5416, 0.25] PeriodicSite: P (1.837, -12.72, 1.895) [0.5416, 0.9584, 0.25] PeriodicSite: O (1.696, -15.14, 6.924) [0.495, 0.8797, 0.9132] PeriodicSite: O (-0.7387, -16.8, 6.924) [0.8797, 0.7121, 0.9132] PeriodicSite: O (-0.9569, -13.86, 6.924) [0.7121, 0.495, 0.9132] PeriodicSite: O (-3.451, -11.32, 3.133) [0.995, 0.2121, 0.4132] PeriodicSite: O (0.7387, -6.621, 3.133) [0.2121, 0.3797, 0.4132] PeriodicSite: O (2.712, -12.6, 3.133) [0.3797, 0.995, 0.4132] PeriodicSite: O (-1.696, -5.215, 0.6581) [0.505, 0.1203, 0.0868] PeriodicSite: O (0.7387, -3.558, 0.6581) [0.1203, 0.2879, 0.0868] PeriodicSite: O (0.9569, -6.495, 0.6581) [0.2879, 0.505, 0.0868] PeriodicSite: O (3.451, -9.039, 4.449) [0.005, 0.7879, 0.5868] PeriodicSite: O (-0.7387, -13.74, 4.449) [0.7879, 0.6203, 0.5868] PeriodicSite: O (-2.712, -7.76, 4.449) [0.6203, 0.005, 0.5868] PeriodicSite: O (0.9463, -11.46, 1.798) [0.564, 0.7787, 0.2372] PeriodicSite: O (-1.581, -10.36, 1.798) [0.7787, 0.4201, 0.2372] PeriodicSite: O (0.6342, -8.72, 1.798) [0.4201, 0.564, 0.2372] PeriodicSite: O (3.773, -11.26, 5.589) [0.064, 0.9201, 0.7372] PeriodicSite: O (-2.827, -12.9, 5.589) [0.9201, 0.2787, 0.7372] PeriodicSite: O (-0.9463, -6.368, 5.589) [0.2787, 0.064, 0.7372] PeriodicSite: O (-0.9463, -8.9, 5.784) [0.436, 0.2213, 0.7628] PeriodicSite: O (1.581, -9.999, 5.784) [0.2213, 0.5799, 0.7628] PeriodicSite: O (-0.6342, -11.64, 5.784) [0.5799, 0.436, 0.7628] PeriodicSite: O (-3.773, -9.093, 1.993) [0.936, 0.0799, 0.2628] PeriodicSite: O (2.827, -7.454, 1.993) [0.0799, 0.7213, 0.2628] PeriodicSite: O (0.9463, -13.99, 1.993) [0.7213, 0.936, 0.2628]
      +endpoint = Structure Summary Lattice     abc : 8.815000056846058 8.815000056846058 9.131710473490111  angles : 61.14080369885537 61.14080369885537 59.9999995733517  volume : 510.2218449146199       A : -4.4075 -7.634014 -0.0       B : 4.4075 -7.634014 0.0       C : -0.0 -5.089343 7.582     pbc : True True True PeriodicSite: Na (0.0, 0.0, 0.0) [0.0, 0.0, 0.0] PeriodicSite: Zr (9.811e-17, -10.18, 0.4774) [0.6457, 0.6457, 0.06296] PeriodicSite: Zr (-2.422e-17, -5.089, 4.268) [0.1457, 0.1457, 0.563] PeriodicSite: Zr (-7.549e-17, -10.18, 7.105) [0.3543, 0.3543, 0.937] PeriodicSite: Zr (-9.811e-17, -15.27, 3.314) [0.8543, 0.8543, 0.437] PeriodicSite: P (-1.837, -7.634, 5.686) [0.4584, 0.0416, 0.75] PeriodicSite: P (3.122, -9.86, 5.686) [0.0416, 0.75, 0.75] PeriodicSite: P (-1.285, -13.04, 5.686) [0.75, 0.4584, 0.75] PeriodicSite: P (-3.122, -10.5, 1.895) [0.9584, 0.25, 0.25] PeriodicSite: P (1.285, -7.315, 1.895) [0.25, 0.5416, 0.25] PeriodicSite: P (1.837, -12.72, 1.895) [0.5416, 0.9584, 0.25] PeriodicSite: O (1.696, -15.14, 6.924) [0.495, 0.8797, 0.9132] PeriodicSite: O (-0.7387, -16.8, 6.924) [0.8797, 0.7121, 0.9132] PeriodicSite: O (-0.9569, -13.86, 6.924) [0.7121, 0.495, 0.9132] PeriodicSite: O (-3.451, -11.32, 3.133) [0.995, 0.2121, 0.4132] PeriodicSite: O (0.7387, -6.621, 3.133) [0.2121, 0.3797, 0.4132] PeriodicSite: O (2.712, -12.6, 3.133) [0.3797, 0.995, 0.4132] PeriodicSite: O (-1.696, -5.215, 0.6581) [0.505, 0.1203, 0.0868] PeriodicSite: O (0.7387, -3.558, 0.6581) [0.1203, 0.2879, 0.0868] PeriodicSite: O (0.9569, -6.495, 0.6581) [0.2879, 0.505, 0.0868] PeriodicSite: O (3.451, -9.039, 4.449) [0.005, 0.7879, 0.5868] PeriodicSite: O (-0.7387, -13.74, 4.449) [0.7879, 0.6203, 0.5868] PeriodicSite: O (-2.712, -7.76, 4.449) [0.6203, 0.005, 0.5868] PeriodicSite: O (0.9463, -11.46, 1.798) [0.564, 0.7787, 0.2372] PeriodicSite: O (-1.581, -10.36, 1.798) [0.7787, 0.4201, 0.2372] PeriodicSite: O (0.6342, -8.72, 1.798) [0.4201, 0.564, 0.2372] PeriodicSite: O (3.773, -11.26, 5.589) [0.064, 0.9201, 0.7372] PeriodicSite: O (-2.827, -12.9, 5.589) [0.9201, 0.2787, 0.7372] PeriodicSite: O (-0.9463, -6.368, 5.589) [0.2787, 0.064, 0.7372] PeriodicSite: O (-0.9463, -8.9, 5.784) [0.436, 0.2213, 0.7628] PeriodicSite: O (1.581, -9.999, 5.784) [0.2213, 0.5799, 0.7628] PeriodicSite: O (-0.6342, -11.64, 5.784) [0.5799, 0.436, 0.7628] PeriodicSite: O (-3.773, -9.093, 1.993) [0.936, 0.0799, 0.2628] PeriodicSite: O (2.827, -7.454, 1.993) [0.0799, 0.7213, 0.2628] PeriodicSite: O (0.9463, -13.99, 1.993) [0.7213, 0.936, 0.2628]
      -test_incar()[source]
      +test_incar()[source]
      -test_incar_user_setting()[source]
      +test_incar_user_setting()[source]
      -class MVLCINEBSetTest(methodName='runTest')[source]
      +class MVLCINEBSetTest(methodName='runTest')[source]

      Bases: TestCase

      Create an instance of the class that will use the named test method when executed. Raises a ValueError if the instance does not have a method with the specified name.

      -structures = [Structure Summary Lattice     abc : 8.815000056846058 8.815000056846058 9.131710473490111  angles : 61.14080369885537 61.14080369885537 59.9999995733517  volume : 510.2218449146199       A : -4.4075 -7.634014 -0.0       B : 4.4075 -7.634014 0.0       C : -0.0 -5.089343 7.582     pbc : True True True PeriodicSite: Na (0.0, 0.0, 0.0) [0.0, 0.0, 0.0] PeriodicSite: Zr (9.811e-17, -10.18, 0.4774) [0.6457, 0.6457, 0.06296] PeriodicSite: Zr (-2.422e-17, -5.089, 4.268) [0.1457, 0.1457, 0.563] PeriodicSite: Zr (-7.549e-17, -10.18, 7.105) [0.3543, 0.3543, 0.937] PeriodicSite: Zr (-9.811e-17, -15.27, 3.314) [0.8543, 0.8543, 0.437] PeriodicSite: P (-1.837, -7.634, 5.686) [0.4584, 0.0416, 0.75] PeriodicSite: P (3.122, -9.86, 5.686) [0.0416, 0.75, 0.75] PeriodicSite: P (-1.285, -13.04, 5.686) [0.75, 0.4584, 0.75] PeriodicSite: P (-3.122, -10.5, 1.895) [0.9584, 0.25, 0.25] PeriodicSite: P (1.285, -7.315, 1.895) [0.25, 0.5416, 0.25] PeriodicSite: P (1.837, -12.72, 1.895) [0.5416, 0.9584, 0.25] PeriodicSite: O (1.696, -15.14, 6.924) [0.495, 0.8797, 0.9132] PeriodicSite: O (-0.7387, -16.8, 6.924) [0.8797, 0.7121, 0.9132] PeriodicSite: O (-0.9569, -13.86, 6.924) [0.7121, 0.495, 0.9132] PeriodicSite: O (-3.451, -11.32, 3.133) [0.995, 0.2121, 0.4132] PeriodicSite: O (0.7387, -6.621, 3.133) [0.2121, 0.3797, 0.4132] PeriodicSite: O (2.712, -12.6, 3.133) [0.3797, 0.995, 0.4132] PeriodicSite: O (-1.696, -5.215, 0.6581) [0.505, 0.1203, 0.0868] PeriodicSite: O (0.7387, -3.558, 0.6581) [0.1203, 0.2879, 0.0868] PeriodicSite: O (0.9569, -6.495, 0.6581) [0.2879, 0.505, 0.0868] PeriodicSite: O (3.451, -9.039, 4.449) [0.005, 0.7879, 0.5868] PeriodicSite: O (-0.7387, -13.74, 4.449) [0.7879, 0.6203, 0.5868] PeriodicSite: O (-2.712, -7.76, 4.449) [0.6203, 0.005, 0.5868] PeriodicSite: O (0.9463, -11.46, 1.798) [0.564, 0.7787, 0.2372] PeriodicSite: O (-1.581, -10.36, 1.798) [0.7787, 0.4201, 0.2372] PeriodicSite: O (0.6342, -8.72, 1.798) [0.4201, 0.564, 0.2372] PeriodicSite: O (3.773, -11.26, 5.589) [0.064, 0.9201, 0.7372] PeriodicSite: O (-2.827, -12.9, 5.589) [0.9201, 0.2787, 0.7372] PeriodicSite: O (-0.9463, -6.368, 5.589) [0.2787, 0.064, 0.7372] PeriodicSite: O (-0.9463, -8.9, 5.784) [0.436, 0.2213, 0.7628] PeriodicSite: O (1.581, -9.999, 5.784) [0.2213, 0.5799, 0.7628] PeriodicSite: O (-0.6342, -11.64, 5.784) [0.5799, 0.436, 0.7628] PeriodicSite: O (-3.773, -9.093, 1.993) [0.936, 0.0799, 0.2628] PeriodicSite: O (2.827, -7.454, 1.993) [0.0799, 0.7213, 0.2628] PeriodicSite: O (0.9463, -13.99, 1.993) [0.7213, 0.936, 0.2628], Structure Summary Lattice     abc : 8.815000056846058 8.815000056846058 9.131710473490111  angles : 61.14080369885537 61.14080369885537 59.9999995733517  volume : 510.2218449146199       A : -4.4075 -7.634014 -0.0       B : 4.4075 -7.634014 0.0       C : -0.0 -5.089343 7.582     pbc : True True True PeriodicSite: Na (0.0, -5.089, 1.895) [0.25, 0.25, 0.25] PeriodicSite: Zr (1.35e-16, -10.18, 0.4774) [0.6457, 0.6457, 0.06296] PeriodicSite: Zr (1.269e-17, -5.089, 4.268) [0.1457, 0.1457, 0.563] PeriodicSite: Zr (1.096e-16, -10.18, 7.105) [0.3543, 0.3543, 0.937] PeriodicSite: Zr (-1.35e-16, -15.27, 3.314) [0.8543, 0.8543, 0.437] PeriodicSite: P (-1.837, -7.634, 5.686) [0.4584, 0.0416, 0.75] PeriodicSite: P (3.122, -9.86, 5.686) [0.0416, 0.75, 0.75] PeriodicSite: P (-1.285, -13.04, 5.686) [0.75, 0.4584, 0.75] PeriodicSite: P (-3.122, -10.5, 1.895) [0.9584, 0.25, 0.25] PeriodicSite: P (1.285, -7.315, 1.895) [0.25, 0.5416, 0.25] PeriodicSite: P (1.837, -12.72, 1.895) [0.5416, 0.9584, 0.25] PeriodicSite: O (1.696, -15.14, 6.924) [0.495, 0.8797, 0.9132] PeriodicSite: O (-0.7387, -16.8, 6.924) [0.8797, 0.7121, 0.9132] PeriodicSite: O (-0.9569, -13.86, 6.924) [0.7121, 0.495, 0.9132] PeriodicSite: O (-3.451, -11.32, 3.133) [0.995, 0.2121, 0.4132] PeriodicSite: O (0.7387, -6.621, 3.133) [0.2121, 0.3797, 0.4132] PeriodicSite: O (2.712, -12.6, 3.133) [0.3797, 0.995, 0.4132] PeriodicSite: O (-1.696, -5.215, 0.6581) [0.505, 0.1203, 0.0868] PeriodicSite: O (0.7387, -3.558, 0.6581) [0.1203, 0.2879, 0.0868] PeriodicSite: O (0.9569, -6.495, 0.6581) [0.2879, 0.505, 0.0868] PeriodicSite: O (3.451, -9.039, 4.449) [0.005, 0.7879, 0.5868] PeriodicSite: O (-0.7387, -13.74, 4.449) [0.7879, 0.6203, 0.5868] PeriodicSite: O (-2.712, -7.76, 4.449) [0.6203, 0.005, 0.5868] PeriodicSite: O (0.9463, -11.46, 1.798) [0.564, 0.7787, 0.2372] PeriodicSite: O (-1.581, -10.36, 1.798) [0.7787, 0.4201, 0.2372] PeriodicSite: O (0.6342, -8.72, 1.798) [0.4201, 0.564, 0.2372] PeriodicSite: O (3.773, -11.26, 5.589) [0.064, 0.9201, 0.7372] PeriodicSite: O (-2.827, -12.9, 5.589) [0.9201, 0.2787, 0.7372] PeriodicSite: O (-0.9463, -6.368, 5.589) [0.2787, 0.064, 0.7372] PeriodicSite: O (-0.9463, -8.9, 5.784) [0.436, 0.2213, 0.7628] PeriodicSite: O (1.581, -9.999, 5.784) [0.2213, 0.5799, 0.7628] PeriodicSite: O (-0.6342, -11.64, 5.784) [0.5799, 0.436, 0.7628] PeriodicSite: O (-3.773, -9.093, 1.993) [0.936, 0.0799, 0.2628] PeriodicSite: O (2.827, -7.454, 1.993) [0.0799, 0.7213, 0.2628] PeriodicSite: O (0.9463, -13.99, 1.993) [0.7213, 0.936, 0.2628], Structure Summary Lattice     abc : 8.815000056846058 8.815000056846058 9.131710473490111  angles : 61.14080369885537 61.14080369885537 59.9999995733517  volume : 510.2218449146199       A : -4.4075 -7.634014 -0.0       B : 4.4075 -7.634014 0.0       C : -0.0 -5.089343 7.582     pbc : True True True PeriodicSite: Na (0.0, -10.18, 3.791) [0.5, 0.5, 0.5] PeriodicSite: Zr (9.811e-17, -10.18, 0.4774) [0.6457, 0.6457, 0.06296] PeriodicSite: Zr (-2.422e-17, -5.089, 4.268) [0.1457, 0.1457, 0.563] PeriodicSite: Zr (-7.549e-17, -10.18, 7.105) [0.3543, 0.3543, 0.937] PeriodicSite: Zr (-9.811e-17, -15.27, 3.314) [0.8543, 0.8543, 0.437] PeriodicSite: P (-1.837, -7.634, 5.686) [0.4584, 0.0416, 0.75] PeriodicSite: P (3.122, -9.86, 5.686) [0.0416, 0.75, 0.75] PeriodicSite: P (-1.285, -13.04, 5.686) [0.75, 0.4584, 0.75] PeriodicSite: P (-3.122, -10.5, 1.895) [0.9584, 0.25, 0.25] PeriodicSite: P (1.285, -7.315, 1.895) [0.25, 0.5416, 0.25] PeriodicSite: P (1.837, -12.72, 1.895) [0.5416, 0.9584, 0.25] PeriodicSite: O (1.696, -15.14, 6.924) [0.495, 0.8797, 0.9132] PeriodicSite: O (-0.7387, -16.8, 6.924) [0.8797, 0.7121, 0.9132] PeriodicSite: O (-0.9569, -13.86, 6.924) [0.7121, 0.495, 0.9132] PeriodicSite: O (-3.451, -11.32, 3.133) [0.995, 0.2121, 0.4132] PeriodicSite: O (0.7387, -6.621, 3.133) [0.2121, 0.3797, 0.4132] PeriodicSite: O (2.712, -12.6, 3.133) [0.3797, 0.995, 0.4132] PeriodicSite: O (-1.696, -5.215, 0.6581) [0.505, 0.1203, 0.0868] PeriodicSite: O (0.7387, -3.558, 0.6581) [0.1203, 0.2879, 0.0868] PeriodicSite: O (0.9569, -6.495, 0.6581) [0.2879, 0.505, 0.0868] PeriodicSite: O (3.451, -9.039, 4.449) [0.005, 0.7879, 0.5868] PeriodicSite: O (-0.7387, -13.74, 4.449) [0.7879, 0.6203, 0.5868] PeriodicSite: O (-2.712, -7.76, 4.449) [0.6203, 0.005, 0.5868] PeriodicSite: O (0.9463, -11.46, 1.798) [0.564, 0.7787, 0.2372] PeriodicSite: O (-1.581, -10.36, 1.798) [0.7787, 0.4201, 0.2372] PeriodicSite: O (0.6342, -8.72, 1.798) [0.4201, 0.564, 0.2372] PeriodicSite: O (3.773, -11.26, 5.589) [0.064, 0.9201, 0.7372] PeriodicSite: O (-2.827, -12.9, 5.589) [0.9201, 0.2787, 0.7372] PeriodicSite: O (-0.9463, -6.368, 5.589) [0.2787, 0.064, 0.7372] PeriodicSite: O (-0.9463, -8.9, 5.784) [0.436, 0.2213, 0.7628] PeriodicSite: O (1.581, -9.999, 5.784) [0.2213, 0.5799, 0.7628] PeriodicSite: O (-0.6342, -11.64, 5.784) [0.5799, 0.436, 0.7628] PeriodicSite: O (-3.773, -9.093, 1.993) [0.936, 0.0799, 0.2628] PeriodicSite: O (2.827, -7.454, 1.993) [0.0799, 0.7213, 0.2628] PeriodicSite: O (0.9463, -13.99, 1.993) [0.7213, 0.936, 0.2628]]
      +structures = [Structure Summary Lattice     abc : 8.815000056846058 8.815000056846058 9.131710473490111  angles : 61.14080369885537 61.14080369885537 59.9999995733517  volume : 510.2218449146199       A : -4.4075 -7.634014 -0.0       B : 4.4075 -7.634014 0.0       C : -0.0 -5.089343 7.582     pbc : True True True PeriodicSite: Na (0.0, 0.0, 0.0) [0.0, 0.0, 0.0] PeriodicSite: Zr (9.811e-17, -10.18, 0.4774) [0.6457, 0.6457, 0.06296] PeriodicSite: Zr (-2.422e-17, -5.089, 4.268) [0.1457, 0.1457, 0.563] PeriodicSite: Zr (-7.549e-17, -10.18, 7.105) [0.3543, 0.3543, 0.937] PeriodicSite: Zr (-9.811e-17, -15.27, 3.314) [0.8543, 0.8543, 0.437] PeriodicSite: P (-1.837, -7.634, 5.686) [0.4584, 0.0416, 0.75] PeriodicSite: P (3.122, -9.86, 5.686) [0.0416, 0.75, 0.75] PeriodicSite: P (-1.285, -13.04, 5.686) [0.75, 0.4584, 0.75] PeriodicSite: P (-3.122, -10.5, 1.895) [0.9584, 0.25, 0.25] PeriodicSite: P (1.285, -7.315, 1.895) [0.25, 0.5416, 0.25] PeriodicSite: P (1.837, -12.72, 1.895) [0.5416, 0.9584, 0.25] PeriodicSite: O (1.696, -15.14, 6.924) [0.495, 0.8797, 0.9132] PeriodicSite: O (-0.7387, -16.8, 6.924) [0.8797, 0.7121, 0.9132] PeriodicSite: O (-0.9569, -13.86, 6.924) [0.7121, 0.495, 0.9132] PeriodicSite: O (-3.451, -11.32, 3.133) [0.995, 0.2121, 0.4132] PeriodicSite: O (0.7387, -6.621, 3.133) [0.2121, 0.3797, 0.4132] PeriodicSite: O (2.712, -12.6, 3.133) [0.3797, 0.995, 0.4132] PeriodicSite: O (-1.696, -5.215, 0.6581) [0.505, 0.1203, 0.0868] PeriodicSite: O (0.7387, -3.558, 0.6581) [0.1203, 0.2879, 0.0868] PeriodicSite: O (0.9569, -6.495, 0.6581) [0.2879, 0.505, 0.0868] PeriodicSite: O (3.451, -9.039, 4.449) [0.005, 0.7879, 0.5868] PeriodicSite: O (-0.7387, -13.74, 4.449) [0.7879, 0.6203, 0.5868] PeriodicSite: O (-2.712, -7.76, 4.449) [0.6203, 0.005, 0.5868] PeriodicSite: O (0.9463, -11.46, 1.798) [0.564, 0.7787, 0.2372] PeriodicSite: O (-1.581, -10.36, 1.798) [0.7787, 0.4201, 0.2372] PeriodicSite: O (0.6342, -8.72, 1.798) [0.4201, 0.564, 0.2372] PeriodicSite: O (3.773, -11.26, 5.589) [0.064, 0.9201, 0.7372] PeriodicSite: O (-2.827, -12.9, 5.589) [0.9201, 0.2787, 0.7372] PeriodicSite: O (-0.9463, -6.368, 5.589) [0.2787, 0.064, 0.7372] PeriodicSite: O (-0.9463, -8.9, 5.784) [0.436, 0.2213, 0.7628] PeriodicSite: O (1.581, -9.999, 5.784) [0.2213, 0.5799, 0.7628] PeriodicSite: O (-0.6342, -11.64, 5.784) [0.5799, 0.436, 0.7628] PeriodicSite: O (-3.773, -9.093, 1.993) [0.936, 0.0799, 0.2628] PeriodicSite: O (2.827, -7.454, 1.993) [0.0799, 0.7213, 0.2628] PeriodicSite: O (0.9463, -13.99, 1.993) [0.7213, 0.936, 0.2628], Structure Summary Lattice     abc : 8.815000056846058 8.815000056846058 9.131710473490111  angles : 61.14080369885537 61.14080369885537 59.9999995733517  volume : 510.2218449146199       A : -4.4075 -7.634014 -0.0       B : 4.4075 -7.634014 0.0       C : -0.0 -5.089343 7.582     pbc : True True True PeriodicSite: Na (0.0, -5.089, 1.895) [0.25, 0.25, 0.25] PeriodicSite: Zr (1.35e-16, -10.18, 0.4774) [0.6457, 0.6457, 0.06296] PeriodicSite: Zr (1.269e-17, -5.089, 4.268) [0.1457, 0.1457, 0.563] PeriodicSite: Zr (1.096e-16, -10.18, 7.105) [0.3543, 0.3543, 0.937] PeriodicSite: Zr (-1.35e-16, -15.27, 3.314) [0.8543, 0.8543, 0.437] PeriodicSite: P (-1.837, -7.634, 5.686) [0.4584, 0.0416, 0.75] PeriodicSite: P (3.122, -9.86, 5.686) [0.0416, 0.75, 0.75] PeriodicSite: P (-1.285, -13.04, 5.686) [0.75, 0.4584, 0.75] PeriodicSite: P (-3.122, -10.5, 1.895) [0.9584, 0.25, 0.25] PeriodicSite: P (1.285, -7.315, 1.895) [0.25, 0.5416, 0.25] PeriodicSite: P (1.837, -12.72, 1.895) [0.5416, 0.9584, 0.25] PeriodicSite: O (1.696, -15.14, 6.924) [0.495, 0.8797, 0.9132] PeriodicSite: O (-0.7387, -16.8, 6.924) [0.8797, 0.7121, 0.9132] PeriodicSite: O (-0.9569, -13.86, 6.924) [0.7121, 0.495, 0.9132] PeriodicSite: O (-3.451, -11.32, 3.133) [0.995, 0.2121, 0.4132] PeriodicSite: O (0.7387, -6.621, 3.133) [0.2121, 0.3797, 0.4132] PeriodicSite: O (2.712, -12.6, 3.133) [0.3797, 0.995, 0.4132] PeriodicSite: O (-1.696, -5.215, 0.6581) [0.505, 0.1203, 0.0868] PeriodicSite: O (0.7387, -3.558, 0.6581) [0.1203, 0.2879, 0.0868] PeriodicSite: O (0.9569, -6.495, 0.6581) [0.2879, 0.505, 0.0868] PeriodicSite: O (3.451, -9.039, 4.449) [0.005, 0.7879, 0.5868] PeriodicSite: O (-0.7387, -13.74, 4.449) [0.7879, 0.6203, 0.5868] PeriodicSite: O (-2.712, -7.76, 4.449) [0.6203, 0.005, 0.5868] PeriodicSite: O (0.9463, -11.46, 1.798) [0.564, 0.7787, 0.2372] PeriodicSite: O (-1.581, -10.36, 1.798) [0.7787, 0.4201, 0.2372] PeriodicSite: O (0.6342, -8.72, 1.798) [0.4201, 0.564, 0.2372] PeriodicSite: O (3.773, -11.26, 5.589) [0.064, 0.9201, 0.7372] PeriodicSite: O (-2.827, -12.9, 5.589) [0.9201, 0.2787, 0.7372] PeriodicSite: O (-0.9463, -6.368, 5.589) [0.2787, 0.064, 0.7372] PeriodicSite: O (-0.9463, -8.9, 5.784) [0.436, 0.2213, 0.7628] PeriodicSite: O (1.581, -9.999, 5.784) [0.2213, 0.5799, 0.7628] PeriodicSite: O (-0.6342, -11.64, 5.784) [0.5799, 0.436, 0.7628] PeriodicSite: O (-3.773, -9.093, 1.993) [0.936, 0.0799, 0.2628] PeriodicSite: O (2.827, -7.454, 1.993) [0.0799, 0.7213, 0.2628] PeriodicSite: O (0.9463, -13.99, 1.993) [0.7213, 0.936, 0.2628], Structure Summary Lattice     abc : 8.815000056846058 8.815000056846058 9.131710473490111  angles : 61.14080369885537 61.14080369885537 59.9999995733517  volume : 510.2218449146199       A : -4.4075 -7.634014 -0.0       B : 4.4075 -7.634014 0.0       C : -0.0 -5.089343 7.582     pbc : True True True PeriodicSite: Na (0.0, -10.18, 3.791) [0.5, 0.5, 0.5] PeriodicSite: Zr (9.811e-17, -10.18, 0.4774) [0.6457, 0.6457, 0.06296] PeriodicSite: Zr (-2.422e-17, -5.089, 4.268) [0.1457, 0.1457, 0.563] PeriodicSite: Zr (-7.549e-17, -10.18, 7.105) [0.3543, 0.3543, 0.937] PeriodicSite: Zr (-9.811e-17, -15.27, 3.314) [0.8543, 0.8543, 0.437] PeriodicSite: P (-1.837, -7.634, 5.686) [0.4584, 0.0416, 0.75] PeriodicSite: P (3.122, -9.86, 5.686) [0.0416, 0.75, 0.75] PeriodicSite: P (-1.285, -13.04, 5.686) [0.75, 0.4584, 0.75] PeriodicSite: P (-3.122, -10.5, 1.895) [0.9584, 0.25, 0.25] PeriodicSite: P (1.285, -7.315, 1.895) [0.25, 0.5416, 0.25] PeriodicSite: P (1.837, -12.72, 1.895) [0.5416, 0.9584, 0.25] PeriodicSite: O (1.696, -15.14, 6.924) [0.495, 0.8797, 0.9132] PeriodicSite: O (-0.7387, -16.8, 6.924) [0.8797, 0.7121, 0.9132] PeriodicSite: O (-0.9569, -13.86, 6.924) [0.7121, 0.495, 0.9132] PeriodicSite: O (-3.451, -11.32, 3.133) [0.995, 0.2121, 0.4132] PeriodicSite: O (0.7387, -6.621, 3.133) [0.2121, 0.3797, 0.4132] PeriodicSite: O (2.712, -12.6, 3.133) [0.3797, 0.995, 0.4132] PeriodicSite: O (-1.696, -5.215, 0.6581) [0.505, 0.1203, 0.0868] PeriodicSite: O (0.7387, -3.558, 0.6581) [0.1203, 0.2879, 0.0868] PeriodicSite: O (0.9569, -6.495, 0.6581) [0.2879, 0.505, 0.0868] PeriodicSite: O (3.451, -9.039, 4.449) [0.005, 0.7879, 0.5868] PeriodicSite: O (-0.7387, -13.74, 4.449) [0.7879, 0.6203, 0.5868] PeriodicSite: O (-2.712, -7.76, 4.449) [0.6203, 0.005, 0.5868] PeriodicSite: O (0.9463, -11.46, 1.798) [0.564, 0.7787, 0.2372] PeriodicSite: O (-1.581, -10.36, 1.798) [0.7787, 0.4201, 0.2372] PeriodicSite: O (0.6342, -8.72, 1.798) [0.4201, 0.564, 0.2372] PeriodicSite: O (3.773, -11.26, 5.589) [0.064, 0.9201, 0.7372] PeriodicSite: O (-2.827, -12.9, 5.589) [0.9201, 0.2787, 0.7372] PeriodicSite: O (-0.9463, -6.368, 5.589) [0.2787, 0.064, 0.7372] PeriodicSite: O (-0.9463, -8.9, 5.784) [0.436, 0.2213, 0.7628] PeriodicSite: O (1.581, -9.999, 5.784) [0.2213, 0.5799, 0.7628] PeriodicSite: O (-0.6342, -11.64, 5.784) [0.5799, 0.436, 0.7628] PeriodicSite: O (-3.773, -9.093, 1.993) [0.936, 0.0799, 0.2628] PeriodicSite: O (2.827, -7.454, 1.993) [0.0799, 0.7213, 0.2628] PeriodicSite: O (0.9463, -13.99, 1.993) [0.7213, 0.936, 0.2628]]
      -test_incar()[source]
      +test_incar()[source]
      -test_incar_user_setting()[source]
      +test_incar_user_setting()[source]
      -class UtilityTest(methodName='runTest')[source]
      +class UtilityTest(methodName='runTest')[source]

      Bases: TestCase

      Unit test for outside methods in io.py

      Create an instance of the class that will use the named test @@ -105,24 +105,24 @@

      Navigation

      not have a method with the specified name.

      -structure = Structure Summary Lattice     abc : 8.815000056846058 8.815000056846058 9.131710473490111  angles : 61.14080369885537 61.14080369885537 59.9999995733517  volume : 510.2218449146199       A : -4.4075 -7.634014 -0.0       B : 4.4075 -7.634014 0.0       C : -0.0 -5.089343 7.582     pbc : True True True PeriodicSite: Na (0.0, 0.0, 0.0) [0.0, 0.0, 0.0] PeriodicSite: Na (0.0, -10.18, 3.791) [0.5, 0.5, 0.5] PeriodicSite: Zr (9.811e-17, -10.18, 0.4774) [0.6457, 0.6457, 0.06296] PeriodicSite: Zr (-2.422e-17, -5.089, 4.268) [0.1457, 0.1457, 0.563] PeriodicSite: Zr (-7.549e-17, -10.18, 7.105) [0.3543, 0.3543, 0.937] PeriodicSite: Zr (-9.811e-17, -15.27, 3.314) [0.8543, 0.8543, 0.437] PeriodicSite: P (-1.837, -7.634, 5.686) [0.4584, 0.0416, 0.75] PeriodicSite: P (3.122, -9.86, 5.686) [0.0416, 0.75, 0.75] PeriodicSite: P (-1.285, -13.04, 5.686) [0.75, 0.4584, 0.75] PeriodicSite: P (-3.122, -10.5, 1.895) [0.9584, 0.25, 0.25] PeriodicSite: P (1.285, -7.315, 1.895) [0.25, 0.5416, 0.25] PeriodicSite: P (1.837, -12.72, 1.895) [0.5416, 0.9584, 0.25] PeriodicSite: O (1.696, -15.14, 6.924) [0.495, 0.8797, 0.9132] PeriodicSite: O (-0.7387, -16.8, 6.924) [0.8797, 0.7121, 0.9132] PeriodicSite: O (-0.9569, -13.86, 6.924) [0.7121, 0.495, 0.9132] PeriodicSite: O (-3.451, -11.32, 3.133) [0.995, 0.2121, 0.4132] PeriodicSite: O (0.7387, -6.621, 3.133) [0.2121, 0.3797, 0.4132] PeriodicSite: O (2.712, -12.6, 3.133) [0.3797, 0.995, 0.4132] PeriodicSite: O (-1.696, -5.215, 0.6581) [0.505, 0.1203, 0.0868] PeriodicSite: O (0.7387, -3.558, 0.6581) [0.1203, 0.2879, 0.0868] PeriodicSite: O (0.9569, -6.495, 0.6581) [0.2879, 0.505, 0.0868] PeriodicSite: O (3.451, -9.039, 4.449) [0.005, 0.7879, 0.5868] PeriodicSite: O (-0.7387, -13.74, 4.449) [0.7879, 0.6203, 0.5868] PeriodicSite: O (-2.712, -7.76, 4.449) [0.6203, 0.005, 0.5868] PeriodicSite: O (0.9463, -11.46, 1.798) [0.564, 0.7787, 0.2372] PeriodicSite: O (-1.581, -10.36, 1.798) [0.7787, 0.4201, 0.2372] PeriodicSite: O (0.6342, -8.72, 1.798) [0.4201, 0.564, 0.2372] PeriodicSite: O (3.773, -11.26, 5.589) [0.064, 0.9201, 0.7372] PeriodicSite: O (-2.827, -12.9, 5.589) [0.9201, 0.2787, 0.7372] PeriodicSite: O (-0.9463, -6.368, 5.589) [0.2787, 0.064, 0.7372] PeriodicSite: O (-0.9463, -8.9, 5.784) [0.436, 0.2213, 0.7628] PeriodicSite: O (1.581, -9.999, 5.784) [0.2213, 0.5799, 0.7628] PeriodicSite: O (-0.6342, -11.64, 5.784) [0.5799, 0.436, 0.7628] PeriodicSite: O (-3.773, -9.093, 1.993) [0.936, 0.0799, 0.2628] PeriodicSite: O (2.827, -7.454, 1.993) [0.0799, 0.7213, 0.2628] PeriodicSite: O (0.9463, -13.99, 1.993) [0.7213, 0.936, 0.2628]
      +structure = Structure Summary Lattice     abc : 8.815000056846058 8.815000056846058 9.131710473490111  angles : 61.14080369885537 61.14080369885537 59.9999995733517  volume : 510.2218449146199       A : -4.4075 -7.634014 -0.0       B : 4.4075 -7.634014 0.0       C : -0.0 -5.089343 7.582     pbc : True True True PeriodicSite: Na (0.0, 0.0, 0.0) [0.0, 0.0, 0.0] PeriodicSite: Na (0.0, -10.18, 3.791) [0.5, 0.5, 0.5] PeriodicSite: Zr (9.811e-17, -10.18, 0.4774) [0.6457, 0.6457, 0.06296] PeriodicSite: Zr (-2.422e-17, -5.089, 4.268) [0.1457, 0.1457, 0.563] PeriodicSite: Zr (-7.549e-17, -10.18, 7.105) [0.3543, 0.3543, 0.937] PeriodicSite: Zr (-9.811e-17, -15.27, 3.314) [0.8543, 0.8543, 0.437] PeriodicSite: P (-1.837, -7.634, 5.686) [0.4584, 0.0416, 0.75] PeriodicSite: P (3.122, -9.86, 5.686) [0.0416, 0.75, 0.75] PeriodicSite: P (-1.285, -13.04, 5.686) [0.75, 0.4584, 0.75] PeriodicSite: P (-3.122, -10.5, 1.895) [0.9584, 0.25, 0.25] PeriodicSite: P (1.285, -7.315, 1.895) [0.25, 0.5416, 0.25] PeriodicSite: P (1.837, -12.72, 1.895) [0.5416, 0.9584, 0.25] PeriodicSite: O (1.696, -15.14, 6.924) [0.495, 0.8797, 0.9132] PeriodicSite: O (-0.7387, -16.8, 6.924) [0.8797, 0.7121, 0.9132] PeriodicSite: O (-0.9569, -13.86, 6.924) [0.7121, 0.495, 0.9132] PeriodicSite: O (-3.451, -11.32, 3.133) [0.995, 0.2121, 0.4132] PeriodicSite: O (0.7387, -6.621, 3.133) [0.2121, 0.3797, 0.4132] PeriodicSite: O (2.712, -12.6, 3.133) [0.3797, 0.995, 0.4132] PeriodicSite: O (-1.696, -5.215, 0.6581) [0.505, 0.1203, 0.0868] PeriodicSite: O (0.7387, -3.558, 0.6581) [0.1203, 0.2879, 0.0868] PeriodicSite: O (0.9569, -6.495, 0.6581) [0.2879, 0.505, 0.0868] PeriodicSite: O (3.451, -9.039, 4.449) [0.005, 0.7879, 0.5868] PeriodicSite: O (-0.7387, -13.74, 4.449) [0.7879, 0.6203, 0.5868] PeriodicSite: O (-2.712, -7.76, 4.449) [0.6203, 0.005, 0.5868] PeriodicSite: O (0.9463, -11.46, 1.798) [0.564, 0.7787, 0.2372] PeriodicSite: O (-1.581, -10.36, 1.798) [0.7787, 0.4201, 0.2372] PeriodicSite: O (0.6342, -8.72, 1.798) [0.4201, 0.564, 0.2372] PeriodicSite: O (3.773, -11.26, 5.589) [0.064, 0.9201, 0.7372] PeriodicSite: O (-2.827, -12.9, 5.589) [0.9201, 0.2787, 0.7372] PeriodicSite: O (-0.9463, -6.368, 5.589) [0.2787, 0.064, 0.7372] PeriodicSite: O (-0.9463, -8.9, 5.784) [0.436, 0.2213, 0.7628] PeriodicSite: O (1.581, -9.999, 5.784) [0.2213, 0.5799, 0.7628] PeriodicSite: O (-0.6342, -11.64, 5.784) [0.5799, 0.436, 0.7628] PeriodicSite: O (-3.773, -9.093, 1.993) [0.936, 0.0799, 0.2628] PeriodicSite: O (2.827, -7.454, 1.993) [0.0799, 0.7213, 0.2628] PeriodicSite: O (0.9463, -13.99, 1.993) [0.7213, 0.936, 0.2628]
      -test_get_endpoint_dist()[source]
      +test_get_endpoint_dist()[source]
      -test_get_endpoints_from_index()[source]
      +test_get_endpoints_from_index()[source]
      -get_path(path_str, dirname='./')[source]
      +get_path(path_str, dirname='./')[source]
      @@ -173,7 +173,7 @@

      This Page

      rel="nofollow">Show Source
      - + diff --git a/docs/pymatgen.analysis.diffusion.neb.tests.test_pathfinder.html b/docs/pymatgen.analysis.diffusion.neb.tests.test_pathfinder.html index c50ec6d..f31f24a 100644 --- a/docs/pymatgen.analysis.diffusion.neb.tests.test_pathfinder.html +++ b/docs/pymatgen.analysis.diffusion.neb.tests.test_pathfinder.html @@ -1,16 +1,16 @@ - + - + - pymatgen.analysis.diffusion.neb.tests.test_pathfinder module — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.neb.tests.test_pathfinder module — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

      Navigation

    • modules |
      • -
    • pymatgen-diffusion 2023.8.15 documentation »
      • +
    • pymatgen-diffusion 2024.6.10 documentation »
    • pymatgen.analysis.diffusion.neb.tests.test_pathfinder module
      • @@ -46,103 +46,103 @@

      Navigation

      -

      pymatgen.analysis.diffusion.neb.tests.test_pathfinder module

      +

      pymatgen.analysis.diffusion.neb.tests.test_pathfinder module

      -class DistinctPathFinderTest(methodName='runTest')[source]
      +class DistinctPathFinderTest(methodName='runTest')[source]

      Bases: PymatgenTest

      Create an instance of the class that will use the named test method when executed. Raises a ValueError if the instance does not have a method with the specified name.

      -test_get_paths()[source]
      +test_get_paths()[source]
      -test_max_path_length()[source]
      +test_max_path_length()[source]
      -class IDPPSolverTest(methodName='runTest')[source]
      +class IDPPSolverTest(methodName='runTest')[source]

      Bases: TestCase

      Create an instance of the class that will use the named test method when executed. Raises a ValueError if the instance does not have a method with the specified name.

      -final_struct = Structure Summary Lattice     abc : 10.411723299877 12.0783517723596 9.47759961582329  angles : 90.0 90.0 90.0  volume : 1191.8693444977544       A : 10.411723299877 0.0 0.0       B : 0.0 12.0783517723596 0.0       C : 0.0 0.0 9.47759961582329     pbc : True True True PeriodicSite: Li (5.185, 6.182, 2.417) [0.498, 0.5118, 0.2551] PeriodicSite: Li (5.227, 11.94, 2.321) [0.502, 0.9882, 0.2449] PeriodicSite: Li (5.182, 12.07, 7.085) [0.4977, 0.999, 0.7475] PeriodicSite: Li (5.23, 6.051, 7.132) [0.5023, 0.501, 0.7525] PeriodicSite: Li (0.0005125, 3.018, 0.004327) [4.922e-05, 0.2499, 0.0004565] PeriodicSite: Li (10.41, 3.021, 4.734) [1.0, 0.2501, 0.4995] PeriodicSite: Li (10.41, 9.058, 0.003074) [0.9995, 0.75, 0.0003243] PeriodicSite: Li (0.005658, 9.059, 4.736) [0.0005434, 0.75, 0.4997] PeriodicSite: Li (5.206, 3.02, 2.369) [0.5, 0.25, 0.25] PeriodicSite: Li (5.206, 3.02, 7.108) [0.5, 0.25, 0.75] PeriodicSite: Li (5.206, 9.059, 7.108) [0.5, 0.75, 0.75] PeriodicSite: Li (10.41, 12.06, 0.008545) [0.9997, 0.9989, 0.0009016] PeriodicSite: Li (0.003162, 12.07, 4.738) [0.0003037, 0.9996, 0.5] PeriodicSite: Li (10.41, 6.043, 0.0004624) [0.9997, 0.5004, 4.879e-05] PeriodicSite: Li (0.002981, 6.053, 4.73) [0.0002863, 0.5011, 0.4991] PeriodicSite: Fe (8.141, 1.511, 2.487) [0.7819, 0.1251, 0.2624] PeriodicSite: Fe (8.141, 1.506, 7.228) [0.7819, 0.1247, 0.7626] PeriodicSite: Fe (8.1, 7.569, 2.472) [0.778, 0.6266, 0.2608] PeriodicSite: Fe (8.137, 7.545, 7.235) [0.7816, 0.6247, 0.7633] PeriodicSite: Fe (2.947, 1.502, 4.613) [0.283, 0.1243, 0.4867] PeriodicSite: Fe (2.938, 1.504, 9.355) [0.2822, 0.1245, 0.9871] PeriodicSite: Fe (2.957, 7.578, 4.609) [0.284, 0.6274, 0.4863] PeriodicSite: Fe (2.96, 7.565, 9.381) [0.2842, 0.6264, 0.9898] PeriodicSite: Fe (2.27, 4.528, 2.252) [0.2181, 0.3749, 0.2376] PeriodicSite: Fe (2.271, 4.533, 6.988) [0.2181, 0.3753, 0.7374] PeriodicSite: Fe (2.312, 10.55, 2.267) [0.222, 0.8734, 0.2392] PeriodicSite: Fe (2.274, 10.57, 6.982) [0.2184, 0.8753, 0.7367] PeriodicSite: Fe (7.465, 4.537, 0.1261) [0.717, 0.3757, 0.0133] PeriodicSite: Fe (7.473, 4.535, 4.861) [0.7178, 0.3755, 0.5129] PeriodicSite: Fe (7.455, 10.54, 0.1303) [0.716, 0.8726, 0.01374] PeriodicSite: Fe (7.452, 10.55, 4.836) [0.7158, 0.8736, 0.5102] PeriodicSite: P (6.198, 1.507, 0.3753) [0.5953, 0.1248, 0.0396] PeriodicSite: P (6.211, 1.514, 5.111) [0.5966, 0.1253, 0.5393] PeriodicSite: P (6.196, 7.548, 0.3633) [0.5951, 0.6249, 0.03833] PeriodicSite: P (6.22, 7.514, 5.12) [0.5974, 0.6221, 0.5402] PeriodicSite: P (0.9887, 1.504, 1.99) [0.09496, 0.1245, 0.2099] PeriodicSite: P (0.9865, 1.513, 6.727) [0.09475, 0.1253, 0.7098] PeriodicSite: P (0.9818, 7.544, 1.993) [0.0943, 0.6246, 0.2102] PeriodicSite: P (0.9911, 7.546, 6.738) [0.09519, 0.6248, 0.7109] PeriodicSite: P (4.214, 4.532, 4.364) [0.4047, 0.3752, 0.4604] PeriodicSite: P (4.2, 4.526, 9.105) [0.4034, 0.3747, 0.9607] PeriodicSite: P (4.216, 10.57, 4.376) [0.4049, 0.8751, 0.4617] PeriodicSite: P (4.191, 10.6, 9.097) [0.4026, 0.8779, 0.9598] PeriodicSite: P (9.423, 4.535, 2.749) [0.905, 0.3755, 0.2901] PeriodicSite: P (9.425, 4.526, 7.489) [0.9053, 0.3747, 0.7902] PeriodicSite: P (9.43, 10.57, 2.746) [0.9057, 0.8754, 0.2898] PeriodicSite: P (9.421, 10.57, 7.479) [0.9048, 0.8752, 0.7891] PeriodicSite: O (6.223, 1.527, 3.577) [0.5977, 0.1264, 0.3775] PeriodicSite: O (6.209, 1.513, 8.315) [0.5964, 0.1252, 0.8774] PeriodicSite: O (6.275, 7.44, 3.601) [0.6027, 0.616, 0.38] PeriodicSite: O (6.212, 7.545, 8.293) [0.5966, 0.6247, 0.875] PeriodicSite: O (0.9902, 1.512, 3.526) [0.0951, 0.1252, 0.372] PeriodicSite: O (0.9889, 1.512, 8.264) [0.09498, 0.1252, 0.8719] PeriodicSite: O (0.9898, 7.548, 3.529) [0.09506, 0.6249, 0.3724] PeriodicSite: O (0.9929, 7.54, 8.274) [0.09536, 0.6243, 0.873] PeriodicSite: O (4.189, 4.512, 1.161) [0.4023, 0.3736, 0.1225] PeriodicSite: O (4.202, 4.527, 5.901) [0.4036, 0.3748, 0.6226] PeriodicSite: O (4.137, 10.68, 1.137) [0.3973, 0.884, 0.12] PeriodicSite: O (4.2, 10.57, 5.923) [0.4034, 0.8753, 0.625] PeriodicSite: O (9.422, 4.527, 1.213) [0.9049, 0.3748, 0.128] PeriodicSite: O (9.423, 4.527, 5.953) [0.905, 0.3748, 0.6281] PeriodicSite: O (9.422, 10.57, 1.209) [0.9049, 0.8751, 0.1276] PeriodicSite: O (9.419, 10.58, 5.943) [0.9046, 0.8757, 0.627] PeriodicSite: O (9.968, 1.514, 1.379) [0.9574, 0.1253, 0.1455] PeriodicSite: O (9.966, 1.522, 6.119) [0.9572, 0.126, 0.6456] PeriodicSite: O (9.963, 7.543, 1.383) [0.9569, 0.6245, 0.1459] PeriodicSite: O (9.972, 7.541, 6.125) [0.9578, 0.6243, 0.6462] PeriodicSite: O (4.766, 1.52, 0.9751) [0.4577, 0.1259, 0.1029] PeriodicSite: O (4.778, 1.513, 5.718) [0.4589, 0.1253, 0.6033] PeriodicSite: O (4.763, 7.503, 0.9219) [0.4574, 0.6212, 0.09727] PeriodicSite: O (4.78, 7.542, 5.712) [0.4591, 0.6244, 0.6027] PeriodicSite: O (0.4439, 4.526, 3.36) [0.04263, 0.3747, 0.3545] PeriodicSite: O (0.4458, 4.517, 8.098) [0.04282, 0.374, 0.8544] PeriodicSite: O (0.4487, 10.57, 3.356) [0.0431, 0.8755, 0.3541] PeriodicSite: O (0.4398, 10.58, 8.092) [0.04224, 0.8757, 0.8538] PeriodicSite: O (5.646, 4.519, 3.764) [0.5423, 0.3741, 0.3971] PeriodicSite: O (5.634, 4.526, 8.498) [0.5411, 0.3747, 0.8967] PeriodicSite: O (5.649, 10.61, 3.817) [0.5426, 0.8788, 0.4027] PeriodicSite: O (5.632, 10.58, 8.505) [0.5409, 0.8756, 0.8973] PeriodicSite: O (6.938, 0.2665, 0.9991) [0.6664, 0.02207, 0.1054] PeriodicSite: O (6.962, 0.2813, 5.739) [0.6687, 0.02329, 0.6056] PeriodicSite: O (6.942, 6.299, 0.9884) [0.6668, 0.5215, 0.1043] PeriodicSite: O (6.941, 6.283, 5.805) [0.6667, 0.5202, 0.6125] PeriodicSite: O (1.738, 2.739, 1.363) [0.1669, 0.2268, 0.1439] PeriodicSite: O (1.739, 2.746, 6.102) [0.167, 0.2274, 0.6438] PeriodicSite: O (1.729, 8.776, 1.362) [0.1661, 0.7266, 0.1437] PeriodicSite: O (1.728, 8.787, 6.117) [0.1659, 0.7275, 0.6454] PeriodicSite: O (3.459, 3.3, 3.737) [0.3322, 0.2732, 0.3942] PeriodicSite: O (3.461, 3.288, 8.468) [0.3324, 0.2722, 0.8934] PeriodicSite: O (3.389, 9.374, 3.797) [0.3255, 0.7761, 0.4006] PeriodicSite: O (3.444, 9.36, 8.482) [0.3308, 0.7749, 0.895] PeriodicSite: O (8.688, 5.775, 3.373) [0.8344, 0.4782, 0.3559] PeriodicSite: O (8.691, 5.764, 8.119) [0.8347, 0.4773, 0.8567] PeriodicSite: O (8.685, 11.81, 3.366) [0.8342, 0.9781, 0.3552] PeriodicSite: O (8.669, 11.8, 8.11) [0.8326, 0.9771, 0.8557] PeriodicSite: O (3.473, 5.773, 3.74) [0.3336, 0.4779, 0.3946] PeriodicSite: O (3.45, 5.758, 8.477) [0.3313, 0.4767, 0.8944] PeriodicSite: O (3.469, 11.82, 3.75) [0.3332, 0.9785, 0.3957] PeriodicSite: O (3.47, 11.83, 8.412) [0.3333, 0.9798, 0.8875] PeriodicSite: O (8.674, 3.3, 3.375) [0.8331, 0.2732, 0.3561] PeriodicSite: O (8.673, 3.293, 8.114) [0.833, 0.2726, 0.8562] PeriodicSite: O (8.682, 9.342, 3.377) [0.8339, 0.7734, 0.3563] PeriodicSite: O (8.684, 9.33, 8.099) [0.8341, 0.7725, 0.8546] PeriodicSite: O (6.952, 2.739, 1.002) [0.6678, 0.2268, 0.1058] PeriodicSite: O (6.951, 2.752, 5.749) [0.6676, 0.2278, 0.6066] PeriodicSite: O (7.022, 8.744, 0.9423) [0.6745, 0.7239, 0.09942] PeriodicSite: O (6.967, 8.757, 5.734) [0.6692, 0.7251, 0.605] PeriodicSite: O (1.724, 0.2638, 1.366) [0.1656, 0.02184, 0.1441] PeriodicSite: O (1.721, 0.2747, 6.097) [0.1653, 0.02274, 0.6433] PeriodicSite: O (1.726, 6.303, 1.372) [0.1658, 0.5219, 0.1448] PeriodicSite: O (1.743, 6.316, 6.107) [0.1674, 0.5229, 0.6443]
      +final_struct = Structure Summary Lattice     abc : 10.411723299877 12.0783517723596 9.47759961582329  angles : 90.0 90.0 90.0  volume : 1191.8693444977544       A : 10.411723299877 0.0 0.0       B : 0.0 12.0783517723596 0.0       C : 0.0 0.0 9.47759961582329     pbc : True True True PeriodicSite: Li (5.185, 6.182, 2.417) [0.498, 0.5118, 0.2551] PeriodicSite: Li (5.227, 11.94, 2.321) [0.502, 0.9882, 0.2449] PeriodicSite: Li (5.182, 12.07, 7.085) [0.4977, 0.999, 0.7475] PeriodicSite: Li (5.23, 6.051, 7.132) [0.5023, 0.501, 0.7525] PeriodicSite: Li (0.0005125, 3.018, 0.004327) [4.922e-05, 0.2499, 0.0004565] PeriodicSite: Li (10.41, 3.021, 4.734) [1.0, 0.2501, 0.4995] PeriodicSite: Li (10.41, 9.058, 0.003074) [0.9995, 0.75, 0.0003243] PeriodicSite: Li (0.005658, 9.059, 4.736) [0.0005434, 0.75, 0.4997] PeriodicSite: Li (5.206, 3.02, 2.369) [0.5, 0.25, 0.25] PeriodicSite: Li (5.206, 3.02, 7.108) [0.5, 0.25, 0.75] PeriodicSite: Li (5.206, 9.059, 7.108) [0.5, 0.75, 0.75] PeriodicSite: Li (10.41, 12.06, 0.008545) [0.9997, 0.9989, 0.0009016] PeriodicSite: Li (0.003162, 12.07, 4.738) [0.0003037, 0.9996, 0.5] PeriodicSite: Li (10.41, 6.043, 0.0004624) [0.9997, 0.5004, 4.879e-05] PeriodicSite: Li (0.002981, 6.053, 4.73) [0.0002863, 0.5011, 0.4991] PeriodicSite: Fe (8.141, 1.511, 2.487) [0.7819, 0.1251, 0.2624] PeriodicSite: Fe (8.141, 1.506, 7.228) [0.7819, 0.1247, 0.7626] PeriodicSite: Fe (8.1, 7.569, 2.472) [0.778, 0.6266, 0.2608] PeriodicSite: Fe (8.137, 7.545, 7.235) [0.7816, 0.6247, 0.7633] PeriodicSite: Fe (2.947, 1.502, 4.613) [0.283, 0.1243, 0.4867] PeriodicSite: Fe (2.938, 1.504, 9.355) [0.2822, 0.1245, 0.9871] PeriodicSite: Fe (2.957, 7.578, 4.609) [0.284, 0.6274, 0.4863] PeriodicSite: Fe (2.96, 7.565, 9.381) [0.2842, 0.6264, 0.9898] PeriodicSite: Fe (2.27, 4.528, 2.252) [0.2181, 0.3749, 0.2376] PeriodicSite: Fe (2.271, 4.533, 6.988) [0.2181, 0.3753, 0.7374] PeriodicSite: Fe (2.312, 10.55, 2.267) [0.222, 0.8734, 0.2392] PeriodicSite: Fe (2.274, 10.57, 6.982) [0.2184, 0.8753, 0.7367] PeriodicSite: Fe (7.465, 4.537, 0.1261) [0.717, 0.3757, 0.0133] PeriodicSite: Fe (7.473, 4.535, 4.861) [0.7178, 0.3755, 0.5129] PeriodicSite: Fe (7.455, 10.54, 0.1303) [0.716, 0.8726, 0.01374] PeriodicSite: Fe (7.452, 10.55, 4.836) [0.7158, 0.8736, 0.5102] PeriodicSite: P (6.198, 1.507, 0.3753) [0.5953, 0.1248, 0.0396] PeriodicSite: P (6.211, 1.514, 5.111) [0.5966, 0.1253, 0.5393] PeriodicSite: P (6.196, 7.548, 0.3633) [0.5951, 0.6249, 0.03833] PeriodicSite: P (6.22, 7.514, 5.12) [0.5974, 0.6221, 0.5402] PeriodicSite: P (0.9887, 1.504, 1.99) [0.09496, 0.1245, 0.2099] PeriodicSite: P (0.9865, 1.513, 6.727) [0.09475, 0.1253, 0.7098] PeriodicSite: P (0.9818, 7.544, 1.993) [0.0943, 0.6246, 0.2102] PeriodicSite: P (0.9911, 7.546, 6.738) [0.09519, 0.6248, 0.7109] PeriodicSite: P (4.214, 4.532, 4.364) [0.4047, 0.3752, 0.4604] PeriodicSite: P (4.2, 4.526, 9.105) [0.4034, 0.3747, 0.9607] PeriodicSite: P (4.216, 10.57, 4.376) [0.4049, 0.8751, 0.4617] PeriodicSite: P (4.191, 10.6, 9.097) [0.4026, 0.8779, 0.9598] PeriodicSite: P (9.423, 4.535, 2.749) [0.905, 0.3755, 0.2901] PeriodicSite: P (9.425, 4.526, 7.489) [0.9053, 0.3747, 0.7902] PeriodicSite: P (9.43, 10.57, 2.746) [0.9057, 0.8754, 0.2898] PeriodicSite: P (9.421, 10.57, 7.479) [0.9048, 0.8752, 0.7891] PeriodicSite: O (6.223, 1.527, 3.577) [0.5977, 0.1264, 0.3775] PeriodicSite: O (6.209, 1.513, 8.315) [0.5964, 0.1252, 0.8774] PeriodicSite: O (6.275, 7.44, 3.601) [0.6027, 0.616, 0.38] PeriodicSite: O (6.212, 7.545, 8.293) [0.5966, 0.6247, 0.875] PeriodicSite: O (0.9902, 1.512, 3.526) [0.0951, 0.1252, 0.372] PeriodicSite: O (0.9889, 1.512, 8.264) [0.09498, 0.1252, 0.8719] PeriodicSite: O (0.9898, 7.548, 3.529) [0.09506, 0.6249, 0.3724] PeriodicSite: O (0.9929, 7.54, 8.274) [0.09536, 0.6243, 0.873] PeriodicSite: O (4.189, 4.512, 1.161) [0.4023, 0.3736, 0.1225] PeriodicSite: O (4.202, 4.527, 5.901) [0.4036, 0.3748, 0.6226] PeriodicSite: O (4.137, 10.68, 1.137) [0.3973, 0.884, 0.12] PeriodicSite: O (4.2, 10.57, 5.923) [0.4034, 0.8753, 0.625] PeriodicSite: O (9.422, 4.527, 1.213) [0.9049, 0.3748, 0.128] PeriodicSite: O (9.423, 4.527, 5.953) [0.905, 0.3748, 0.6281] PeriodicSite: O (9.422, 10.57, 1.209) [0.9049, 0.8751, 0.1276] PeriodicSite: O (9.419, 10.58, 5.943) [0.9046, 0.8757, 0.627] PeriodicSite: O (9.968, 1.514, 1.379) [0.9574, 0.1253, 0.1455] PeriodicSite: O (9.966, 1.522, 6.119) [0.9572, 0.126, 0.6456] PeriodicSite: O (9.963, 7.543, 1.383) [0.9569, 0.6245, 0.1459] PeriodicSite: O (9.972, 7.541, 6.125) [0.9578, 0.6243, 0.6462] PeriodicSite: O (4.766, 1.52, 0.9751) [0.4577, 0.1259, 0.1029] PeriodicSite: O (4.778, 1.513, 5.718) [0.4589, 0.1253, 0.6033] PeriodicSite: O (4.763, 7.503, 0.9219) [0.4574, 0.6212, 0.09727] PeriodicSite: O (4.78, 7.542, 5.712) [0.4591, 0.6244, 0.6027] PeriodicSite: O (0.4439, 4.526, 3.36) [0.04263, 0.3747, 0.3545] PeriodicSite: O (0.4458, 4.517, 8.098) [0.04282, 0.374, 0.8544] PeriodicSite: O (0.4487, 10.57, 3.356) [0.0431, 0.8755, 0.3541] PeriodicSite: O (0.4398, 10.58, 8.092) [0.04224, 0.8757, 0.8538] PeriodicSite: O (5.646, 4.519, 3.764) [0.5423, 0.3741, 0.3971] PeriodicSite: O (5.634, 4.526, 8.498) [0.5411, 0.3747, 0.8967] PeriodicSite: O (5.649, 10.61, 3.817) [0.5426, 0.8788, 0.4027] PeriodicSite: O (5.632, 10.58, 8.505) [0.5409, 0.8756, 0.8973] PeriodicSite: O (6.938, 0.2665, 0.9991) [0.6664, 0.02207, 0.1054] PeriodicSite: O (6.962, 0.2813, 5.739) [0.6687, 0.02329, 0.6056] PeriodicSite: O (6.942, 6.299, 0.9884) [0.6668, 0.5215, 0.1043] PeriodicSite: O (6.941, 6.283, 5.805) [0.6667, 0.5202, 0.6125] PeriodicSite: O (1.738, 2.739, 1.363) [0.1669, 0.2268, 0.1439] PeriodicSite: O (1.739, 2.746, 6.102) [0.167, 0.2274, 0.6438] PeriodicSite: O (1.729, 8.776, 1.362) [0.1661, 0.7266, 0.1437] PeriodicSite: O (1.728, 8.787, 6.117) [0.1659, 0.7275, 0.6454] PeriodicSite: O (3.459, 3.3, 3.737) [0.3322, 0.2732, 0.3942] PeriodicSite: O (3.461, 3.288, 8.468) [0.3324, 0.2722, 0.8934] PeriodicSite: O (3.389, 9.374, 3.797) [0.3255, 0.7761, 0.4006] PeriodicSite: O (3.444, 9.36, 8.482) [0.3308, 0.7749, 0.895] PeriodicSite: O (8.688, 5.775, 3.373) [0.8344, 0.4782, 0.3559] PeriodicSite: O (8.691, 5.764, 8.119) [0.8347, 0.4773, 0.8567] PeriodicSite: O (8.685, 11.81, 3.366) [0.8342, 0.9781, 0.3552] PeriodicSite: O (8.669, 11.8, 8.11) [0.8326, 0.9771, 0.8557] PeriodicSite: O (3.473, 5.773, 3.74) [0.3336, 0.4779, 0.3946] PeriodicSite: O (3.45, 5.758, 8.477) [0.3313, 0.4767, 0.8944] PeriodicSite: O (3.469, 11.82, 3.75) [0.3332, 0.9785, 0.3957] PeriodicSite: O (3.47, 11.83, 8.412) [0.3333, 0.9798, 0.8875] PeriodicSite: O (8.674, 3.3, 3.375) [0.8331, 0.2732, 0.3561] PeriodicSite: O (8.673, 3.293, 8.114) [0.833, 0.2726, 0.8562] PeriodicSite: O (8.682, 9.342, 3.377) [0.8339, 0.7734, 0.3563] PeriodicSite: O (8.684, 9.33, 8.099) [0.8341, 0.7725, 0.8546] PeriodicSite: O (6.952, 2.739, 1.002) [0.6678, 0.2268, 0.1058] PeriodicSite: O (6.951, 2.752, 5.749) [0.6676, 0.2278, 0.6066] PeriodicSite: O (7.022, 8.744, 0.9423) [0.6745, 0.7239, 0.09942] PeriodicSite: O (6.967, 8.757, 5.734) [0.6692, 0.7251, 0.605] PeriodicSite: O (1.724, 0.2638, 1.366) [0.1656, 0.02184, 0.1441] PeriodicSite: O (1.721, 0.2747, 6.097) [0.1653, 0.02274, 0.6433] PeriodicSite: O (1.726, 6.303, 1.372) [0.1658, 0.5219, 0.1448] PeriodicSite: O (1.743, 6.316, 6.107) [0.1674, 0.5229, 0.6443]
      -init_struct = Structure Summary Lattice     abc : 10.411723299877 12.0783517723596 9.47759961582329  angles : 90.0 90.0 90.0  volume : 1191.8693444977544       A : 10.411723299877 0.0 0.0       B : 0.0 12.0783517723596 0.0       C : 0.0 0.0 9.47759961582329     pbc : True True True PeriodicSite: Li (5.187, 8.921, 2.417) [0.4982, 0.7386, 0.255] PeriodicSite: Li (5.206, 12.08, 2.369) [0.5, 1.0, 0.25] PeriodicSite: Li (5.206, 12.08, 7.108) [0.5, 1.0, 0.75] PeriodicSite: Li (5.206, 6.039, 7.108) [0.5, 0.5, 0.75] PeriodicSite: Li (10.41, 3.032, 0.007788) [0.9997, 0.251, 0.0008217] PeriodicSite: Li (0.002969, 3.023, 4.739) [0.0002851, 0.2503, 0.5] PeriodicSite: Li (10.41, 9.055, 4.493e-05) [0.9997, 0.7497, 4.741e-06] PeriodicSite: Li (0.002765, 9.046, 4.731) [0.0002656, 0.749, 0.4992] PeriodicSite: Li (5.224, 3.158, 2.322) [0.5018, 0.2614, 0.245] PeriodicSite: Li (5.182, 3.031, 7.084) [0.4977, 0.2509, 0.7475] PeriodicSite: Li (5.23, 9.047, 7.132) [0.5023, 0.7491, 0.7525] PeriodicSite: Li (0.0003644, 0.0009345, 0.005748) [3.5e-05, 7.737e-05, 0.0006065] PeriodicSite: Li (10.41, 12.08, 4.733) [1.0, 0.9999, 0.4994] PeriodicSite: Li (10.41, 6.039, 0.003601) [0.9995, 0.5, 0.00038] PeriodicSite: Li (0.005541, 6.039, 4.735) [0.0005322, 0.5, 0.4996] PeriodicSite: Fe (8.142, 1.509, 2.487) [0.782, 0.1249, 0.2624] PeriodicSite: Fe (8.141, 1.513, 7.228) [0.7819, 0.1253, 0.7627] PeriodicSite: Fe (8.101, 7.529, 2.472) [0.7781, 0.6233, 0.2608] PeriodicSite: Fe (8.137, 7.552, 7.234) [0.7816, 0.6253, 0.7633] PeriodicSite: Fe (2.947, 1.518, 4.614) [0.283, 0.1257, 0.4868] PeriodicSite: Fe (2.938, 1.517, 9.355) [0.2822, 0.1256, 0.9871] PeriodicSite: Fe (2.956, 7.52, 4.607) [0.2839, 0.6226, 0.4861] PeriodicSite: Fe (2.959, 7.533, 9.38) [0.2842, 0.6237, 0.9897] PeriodicSite: Fe (2.311, 4.549, 2.267) [0.2219, 0.3767, 0.2392] PeriodicSite: Fe (2.274, 4.526, 6.982) [0.2184, 0.3747, 0.7367] PeriodicSite: Fe (2.27, 10.57, 2.252) [0.218, 0.8751, 0.2376] PeriodicSite: Fe (2.271, 10.56, 6.988) [0.2181, 0.8747, 0.7373] PeriodicSite: Fe (7.455, 4.558, 0.1314) [0.7161, 0.3774, 0.01386] PeriodicSite: Fe (7.453, 4.546, 4.836) [0.7158, 0.3763, 0.5103] PeriodicSite: Fe (7.465, 10.56, 0.1251) [0.717, 0.8743, 0.0132] PeriodicSite: Fe (7.473, 10.56, 4.861) [0.7178, 0.8744, 0.5129] PeriodicSite: P (6.198, 1.511, 0.3753) [0.5953, 0.1251, 0.0396] PeriodicSite: P (6.211, 1.505, 5.111) [0.5966, 0.1246, 0.5393] PeriodicSite: P (6.196, 7.55, 0.3633) [0.5951, 0.6251, 0.03833] PeriodicSite: P (6.22, 7.584, 5.119) [0.5974, 0.6279, 0.5401] PeriodicSite: P (0.9888, 1.515, 1.99) [0.09497, 0.1255, 0.2099] PeriodicSite: P (0.9865, 1.506, 6.728) [0.09474, 0.1247, 0.7099] PeriodicSite: P (0.9815, 7.554, 1.992) [0.09427, 0.6254, 0.2102] PeriodicSite: P (0.9909, 7.552, 6.737) [0.09517, 0.6252, 0.7109] PeriodicSite: P (4.216, 4.528, 4.375) [0.4049, 0.3749, 0.4617] PeriodicSite: P (4.192, 4.495, 9.098) [0.4026, 0.3721, 0.9599] PeriodicSite: P (4.214, 10.57, 4.364) [0.4047, 0.8749, 0.4604] PeriodicSite: P (4.2, 10.57, 9.105) [0.4034, 0.8754, 0.9607] PeriodicSite: P (9.43, 4.524, 2.747) [0.9057, 0.3746, 0.2898] PeriodicSite: P (9.421, 4.526, 7.479) [0.9048, 0.3747, 0.7891] PeriodicSite: P (9.423, 10.56, 2.749) [0.905, 0.8745, 0.2901] PeriodicSite: P (9.425, 10.57, 7.488) [0.9053, 0.8753, 0.7901] PeriodicSite: O (6.222, 1.492, 3.577) [0.5976, 0.1236, 0.3775] PeriodicSite: O (6.21, 1.505, 8.315) [0.5965, 0.1246, 0.8774] PeriodicSite: O (6.274, 7.658, 3.601) [0.6026, 0.634, 0.3799] PeriodicSite: O (6.211, 7.552, 8.293) [0.5965, 0.6252, 0.8751] PeriodicSite: O (0.9903, 1.507, 3.526) [0.09511, 0.1248, 0.372] PeriodicSite: O (0.9896, 1.508, 8.264) [0.09505, 0.1248, 0.872] PeriodicSite: O (0.99, 7.55, 3.529) [0.09508, 0.6251, 0.3723] PeriodicSite: O (0.9927, 7.558, 8.273) [0.09534, 0.6258, 0.8729] PeriodicSite: O (4.137, 4.42, 1.138) [0.3974, 0.366, 0.1201] PeriodicSite: O (4.201, 4.527, 5.923) [0.4035, 0.3748, 0.6249] PeriodicSite: O (4.189, 10.59, 1.161) [0.4024, 0.8764, 0.1225] PeriodicSite: O (4.202, 10.57, 5.901) [0.4035, 0.8754, 0.6226] PeriodicSite: O (9.422, 4.528, 1.21) [0.9049, 0.3749, 0.1277] PeriodicSite: O (9.419, 4.52, 5.943) [0.9047, 0.3742, 0.6271] PeriodicSite: O (9.421, 10.57, 1.213) [0.9049, 0.8752, 0.128] PeriodicSite: O (9.422, 10.57, 5.952) [0.905, 0.8752, 0.628] PeriodicSite: O (9.968, 1.505, 1.378) [0.9574, 0.1246, 0.1454] PeriodicSite: O (9.966, 1.497, 6.12) [0.9572, 0.1239, 0.6457] PeriodicSite: O (9.962, 7.555, 1.383) [0.9568, 0.6255, 0.1459] PeriodicSite: O (9.972, 7.557, 6.124) [0.9577, 0.6257, 0.6462] PeriodicSite: O (4.766, 1.5, 0.9756) [0.4577, 0.1242, 0.1029] PeriodicSite: O (4.778, 1.506, 5.719) [0.4589, 0.1247, 0.6034] PeriodicSite: O (4.763, 7.596, 0.9216) [0.4574, 0.6289, 0.09724] PeriodicSite: O (4.779, 7.556, 5.71) [0.459, 0.6256, 0.6024] PeriodicSite: O (0.4493, 4.523, 3.356) [0.04315, 0.3745, 0.3541] PeriodicSite: O (0.44, 4.521, 8.092) [0.04226, 0.3743, 0.8538] PeriodicSite: O (0.4436, 10.57, 3.36) [0.0426, 0.8754, 0.3546] PeriodicSite: O (0.4459, 10.58, 8.097) [0.04283, 0.8761, 0.8543] PeriodicSite: O (5.649, 4.483, 3.817) [0.5426, 0.3711, 0.4028] PeriodicSite: O (5.633, 4.522, 8.507) [0.541, 0.3744, 0.8976] PeriodicSite: O (5.646, 10.58, 3.763) [0.5423, 0.8758, 0.3971] PeriodicSite: O (5.633, 10.57, 8.497) [0.5411, 0.8753, 0.8966] PeriodicSite: O (6.951, 0.2785, 1.003) [0.6676, 0.02306, 0.1058] PeriodicSite: O (6.95, 0.266, 5.748) [0.6675, 0.02202, 0.6065] PeriodicSite: O (7.022, 6.354, 0.9424) [0.6744, 0.5261, 0.09944] PeriodicSite: O (6.966, 6.34, 5.733) [0.669, 0.5249, 0.6049] PeriodicSite: O (1.725, 2.756, 1.366) [0.1657, 0.2281, 0.1441] PeriodicSite: O (1.721, 2.745, 6.097) [0.1653, 0.2272, 0.6433] PeriodicSite: O (1.726, 8.795, 1.372) [0.1657, 0.7282, 0.1447] PeriodicSite: O (1.743, 8.782, 6.106) [0.1674, 0.7271, 0.6442] PeriodicSite: O (3.469, 3.278, 3.752) [0.3332, 0.2714, 0.3959] PeriodicSite: O (3.47, 3.264, 8.411) [0.3333, 0.2702, 0.8875] PeriodicSite: O (3.472, 9.327, 3.74) [0.3335, 0.7722, 0.3946] PeriodicSite: O (3.448, 9.342, 8.477) [0.3312, 0.7734, 0.8944] PeriodicSite: O (8.683, 5.756, 3.377) [0.8339, 0.4765, 0.3563] PeriodicSite: O (8.683, 5.767, 8.099) [0.834, 0.4775, 0.8545] PeriodicSite: O (8.674, 11.8, 3.375) [0.8331, 0.9768, 0.3561] PeriodicSite: O (8.673, 11.81, 8.114) [0.833, 0.9774, 0.8561] PeriodicSite: O (3.39, 5.725, 3.796) [0.3256, 0.474, 0.4006] PeriodicSite: O (3.446, 5.739, 8.484) [0.331, 0.4751, 0.8951] PeriodicSite: O (3.461, 11.8, 3.736) [0.3324, 0.9769, 0.3942] PeriodicSite: O (3.462, 11.81, 8.468) [0.3325, 0.978, 0.8935] PeriodicSite: O (8.686, 3.283, 3.367) [0.8343, 0.2718, 0.3553] PeriodicSite: O (8.669, 3.296, 8.111) [0.8326, 0.2729, 0.8558] PeriodicSite: O (8.687, 9.323, 3.373) [0.8343, 0.7719, 0.3559] PeriodicSite: O (8.691, 9.334, 8.119) [0.8347, 0.7728, 0.8567] PeriodicSite: O (6.94, 2.751, 0.9992) [0.6665, 0.2278, 0.1054] PeriodicSite: O (6.963, 2.736, 5.739) [0.6688, 0.2266, 0.6056] PeriodicSite: O (6.942, 8.8, 0.9868) [0.6668, 0.7286, 0.1041] PeriodicSite: O (6.942, 8.815, 5.805) [0.6667, 0.7298, 0.6125] PeriodicSite: O (1.738, 0.2801, 1.364) [0.1669, 0.02319, 0.1439] PeriodicSite: O (1.739, 0.2732, 6.102) [0.167, 0.02262, 0.6439] PeriodicSite: O (1.729, 6.322, 1.362) [0.1661, 0.5235, 0.1437] PeriodicSite: O (1.729, 6.311, 6.117) [0.166, 0.5225, 0.6455]
      +init_struct = Structure Summary Lattice     abc : 10.411723299877 12.0783517723596 9.47759961582329  angles : 90.0 90.0 90.0  volume : 1191.8693444977544       A : 10.411723299877 0.0 0.0       B : 0.0 12.0783517723596 0.0       C : 0.0 0.0 9.47759961582329     pbc : True True True PeriodicSite: Li (5.187, 8.921, 2.417) [0.4982, 0.7386, 0.255] PeriodicSite: Li (5.206, 12.08, 2.369) [0.5, 1.0, 0.25] PeriodicSite: Li (5.206, 12.08, 7.108) [0.5, 1.0, 0.75] PeriodicSite: Li (5.206, 6.039, 7.108) [0.5, 0.5, 0.75] PeriodicSite: Li (10.41, 3.032, 0.007788) [0.9997, 0.251, 0.0008217] PeriodicSite: Li (0.002969, 3.023, 4.739) [0.0002851, 0.2503, 0.5] PeriodicSite: Li (10.41, 9.055, 4.493e-05) [0.9997, 0.7497, 4.741e-06] PeriodicSite: Li (0.002765, 9.046, 4.731) [0.0002656, 0.749, 0.4992] PeriodicSite: Li (5.224, 3.158, 2.322) [0.5018, 0.2614, 0.245] PeriodicSite: Li (5.182, 3.031, 7.084) [0.4977, 0.2509, 0.7475] PeriodicSite: Li (5.23, 9.047, 7.132) [0.5023, 0.7491, 0.7525] PeriodicSite: Li (0.0003644, 0.0009345, 0.005748) [3.5e-05, 7.737e-05, 0.0006065] PeriodicSite: Li (10.41, 12.08, 4.733) [1.0, 0.9999, 0.4994] PeriodicSite: Li (10.41, 6.039, 0.003601) [0.9995, 0.5, 0.00038] PeriodicSite: Li (0.005541, 6.039, 4.735) [0.0005322, 0.5, 0.4996] PeriodicSite: Fe (8.142, 1.509, 2.487) [0.782, 0.1249, 0.2624] PeriodicSite: Fe (8.141, 1.513, 7.228) [0.7819, 0.1253, 0.7627] PeriodicSite: Fe (8.101, 7.529, 2.472) [0.7781, 0.6233, 0.2608] PeriodicSite: Fe (8.137, 7.552, 7.234) [0.7816, 0.6253, 0.7633] PeriodicSite: Fe (2.947, 1.518, 4.614) [0.283, 0.1257, 0.4868] PeriodicSite: Fe (2.938, 1.517, 9.355) [0.2822, 0.1256, 0.9871] PeriodicSite: Fe (2.956, 7.52, 4.607) [0.2839, 0.6226, 0.4861] PeriodicSite: Fe (2.959, 7.533, 9.38) [0.2842, 0.6237, 0.9897] PeriodicSite: Fe (2.311, 4.549, 2.267) [0.2219, 0.3767, 0.2392] PeriodicSite: Fe (2.274, 4.526, 6.982) [0.2184, 0.3747, 0.7367] PeriodicSite: Fe (2.27, 10.57, 2.252) [0.218, 0.8751, 0.2376] PeriodicSite: Fe (2.271, 10.56, 6.988) [0.2181, 0.8747, 0.7373] PeriodicSite: Fe (7.455, 4.558, 0.1314) [0.7161, 0.3774, 0.01386] PeriodicSite: Fe (7.453, 4.546, 4.836) [0.7158, 0.3763, 0.5103] PeriodicSite: Fe (7.465, 10.56, 0.1251) [0.717, 0.8743, 0.0132] PeriodicSite: Fe (7.473, 10.56, 4.861) [0.7178, 0.8744, 0.5129] PeriodicSite: P (6.198, 1.511, 0.3753) [0.5953, 0.1251, 0.0396] PeriodicSite: P (6.211, 1.505, 5.111) [0.5966, 0.1246, 0.5393] PeriodicSite: P (6.196, 7.55, 0.3633) [0.5951, 0.6251, 0.03833] PeriodicSite: P (6.22, 7.584, 5.119) [0.5974, 0.6279, 0.5401] PeriodicSite: P (0.9888, 1.515, 1.99) [0.09497, 0.1255, 0.2099] PeriodicSite: P (0.9865, 1.506, 6.728) [0.09474, 0.1247, 0.7099] PeriodicSite: P (0.9815, 7.554, 1.992) [0.09427, 0.6254, 0.2102] PeriodicSite: P (0.9909, 7.552, 6.737) [0.09517, 0.6252, 0.7109] PeriodicSite: P (4.216, 4.528, 4.375) [0.4049, 0.3749, 0.4617] PeriodicSite: P (4.192, 4.495, 9.098) [0.4026, 0.3721, 0.9599] PeriodicSite: P (4.214, 10.57, 4.364) [0.4047, 0.8749, 0.4604] PeriodicSite: P (4.2, 10.57, 9.105) [0.4034, 0.8754, 0.9607] PeriodicSite: P (9.43, 4.524, 2.747) [0.9057, 0.3746, 0.2898] PeriodicSite: P (9.421, 4.526, 7.479) [0.9048, 0.3747, 0.7891] PeriodicSite: P (9.423, 10.56, 2.749) [0.905, 0.8745, 0.2901] PeriodicSite: P (9.425, 10.57, 7.488) [0.9053, 0.8753, 0.7901] PeriodicSite: O (6.222, 1.492, 3.577) [0.5976, 0.1236, 0.3775] PeriodicSite: O (6.21, 1.505, 8.315) [0.5965, 0.1246, 0.8774] PeriodicSite: O (6.274, 7.658, 3.601) [0.6026, 0.634, 0.3799] PeriodicSite: O (6.211, 7.552, 8.293) [0.5965, 0.6252, 0.8751] PeriodicSite: O (0.9903, 1.507, 3.526) [0.09511, 0.1248, 0.372] PeriodicSite: O (0.9896, 1.508, 8.264) [0.09505, 0.1248, 0.872] PeriodicSite: O (0.99, 7.55, 3.529) [0.09508, 0.6251, 0.3723] PeriodicSite: O (0.9927, 7.558, 8.273) [0.09534, 0.6258, 0.8729] PeriodicSite: O (4.137, 4.42, 1.138) [0.3974, 0.366, 0.1201] PeriodicSite: O (4.201, 4.527, 5.923) [0.4035, 0.3748, 0.6249] PeriodicSite: O (4.189, 10.59, 1.161) [0.4024, 0.8764, 0.1225] PeriodicSite: O (4.202, 10.57, 5.901) [0.4035, 0.8754, 0.6226] PeriodicSite: O (9.422, 4.528, 1.21) [0.9049, 0.3749, 0.1277] PeriodicSite: O (9.419, 4.52, 5.943) [0.9047, 0.3742, 0.6271] PeriodicSite: O (9.421, 10.57, 1.213) [0.9049, 0.8752, 0.128] PeriodicSite: O (9.422, 10.57, 5.952) [0.905, 0.8752, 0.628] PeriodicSite: O (9.968, 1.505, 1.378) [0.9574, 0.1246, 0.1454] PeriodicSite: O (9.966, 1.497, 6.12) [0.9572, 0.1239, 0.6457] PeriodicSite: O (9.962, 7.555, 1.383) [0.9568, 0.6255, 0.1459] PeriodicSite: O (9.972, 7.557, 6.124) [0.9577, 0.6257, 0.6462] PeriodicSite: O (4.766, 1.5, 0.9756) [0.4577, 0.1242, 0.1029] PeriodicSite: O (4.778, 1.506, 5.719) [0.4589, 0.1247, 0.6034] PeriodicSite: O (4.763, 7.596, 0.9216) [0.4574, 0.6289, 0.09724] PeriodicSite: O (4.779, 7.556, 5.71) [0.459, 0.6256, 0.6024] PeriodicSite: O (0.4493, 4.523, 3.356) [0.04315, 0.3745, 0.3541] PeriodicSite: O (0.44, 4.521, 8.092) [0.04226, 0.3743, 0.8538] PeriodicSite: O (0.4436, 10.57, 3.36) [0.0426, 0.8754, 0.3546] PeriodicSite: O (0.4459, 10.58, 8.097) [0.04283, 0.8761, 0.8543] PeriodicSite: O (5.649, 4.483, 3.817) [0.5426, 0.3711, 0.4028] PeriodicSite: O (5.633, 4.522, 8.507) [0.541, 0.3744, 0.8976] PeriodicSite: O (5.646, 10.58, 3.763) [0.5423, 0.8758, 0.3971] PeriodicSite: O (5.633, 10.57, 8.497) [0.5411, 0.8753, 0.8966] PeriodicSite: O (6.951, 0.2785, 1.003) [0.6676, 0.02306, 0.1058] PeriodicSite: O (6.95, 0.266, 5.748) [0.6675, 0.02202, 0.6065] PeriodicSite: O (7.022, 6.354, 0.9424) [0.6744, 0.5261, 0.09944] PeriodicSite: O (6.966, 6.34, 5.733) [0.669, 0.5249, 0.6049] PeriodicSite: O (1.725, 2.756, 1.366) [0.1657, 0.2281, 0.1441] PeriodicSite: O (1.721, 2.745, 6.097) [0.1653, 0.2272, 0.6433] PeriodicSite: O (1.726, 8.795, 1.372) [0.1657, 0.7282, 0.1447] PeriodicSite: O (1.743, 8.782, 6.106) [0.1674, 0.7271, 0.6442] PeriodicSite: O (3.469, 3.278, 3.752) [0.3332, 0.2714, 0.3959] PeriodicSite: O (3.47, 3.264, 8.411) [0.3333, 0.2702, 0.8875] PeriodicSite: O (3.472, 9.327, 3.74) [0.3335, 0.7722, 0.3946] PeriodicSite: O (3.448, 9.342, 8.477) [0.3312, 0.7734, 0.8944] PeriodicSite: O (8.683, 5.756, 3.377) [0.8339, 0.4765, 0.3563] PeriodicSite: O (8.683, 5.767, 8.099) [0.834, 0.4775, 0.8545] PeriodicSite: O (8.674, 11.8, 3.375) [0.8331, 0.9768, 0.3561] PeriodicSite: O (8.673, 11.81, 8.114) [0.833, 0.9774, 0.8561] PeriodicSite: O (3.39, 5.725, 3.796) [0.3256, 0.474, 0.4006] PeriodicSite: O (3.446, 5.739, 8.484) [0.331, 0.4751, 0.8951] PeriodicSite: O (3.461, 11.8, 3.736) [0.3324, 0.9769, 0.3942] PeriodicSite: O (3.462, 11.81, 8.468) [0.3325, 0.978, 0.8935] PeriodicSite: O (8.686, 3.283, 3.367) [0.8343, 0.2718, 0.3553] PeriodicSite: O (8.669, 3.296, 8.111) [0.8326, 0.2729, 0.8558] PeriodicSite: O (8.687, 9.323, 3.373) [0.8343, 0.7719, 0.3559] PeriodicSite: O (8.691, 9.334, 8.119) [0.8347, 0.7728, 0.8567] PeriodicSite: O (6.94, 2.751, 0.9992) [0.6665, 0.2278, 0.1054] PeriodicSite: O (6.963, 2.736, 5.739) [0.6688, 0.2266, 0.6056] PeriodicSite: O (6.942, 8.8, 0.9868) [0.6668, 0.7286, 0.1041] PeriodicSite: O (6.942, 8.815, 5.805) [0.6667, 0.7298, 0.6125] PeriodicSite: O (1.738, 0.2801, 1.364) [0.1669, 0.02319, 0.1439] PeriodicSite: O (1.739, 0.2732, 6.102) [0.167, 0.02262, 0.6439] PeriodicSite: O (1.729, 6.322, 1.362) [0.1661, 0.5235, 0.1437] PeriodicSite: O (1.729, 6.311, 6.117) [0.166, 0.5225, 0.6455]
      -test_idpp()[source]
      +test_idpp()[source]
      -test_idpp_from_ep()[source]
      +test_idpp_from_ep()[source]
      -test_idpp_from_ep_diff_latt()[source]
      +test_idpp_from_ep_diff_latt()[source]
      -class MigrationHopTest(methodName='runTest')[source]
      +class MigrationHopTest(methodName='runTest')[source]

      Bases: PymatgenTest

      Create an instance of the class that will use the named test method when executed. Raises a ValueError if the instance does not have a method with the specified name.

      -setUp()[source]
      +setUp()[source]

      Hook method for setting up the test fixture before exercising it.

      -test_get_sc_structures()[source]
      +test_get_sc_structures()[source]
      -test_get_sc_structures_vacmode()[source]
      +test_get_sc_structures_vacmode()[source]
      -test_get_start_end_structs_from_hop()[source]
      +test_get_start_end_structs_from_hop()[source]
      -test_get_start_end_structs_from_hop_vac()[source]
      +test_get_start_end_structs_from_hop_vac()[source]
      -test_msonable()[source]
      +test_msonable()[source]
      -get_path(path_str, dirname='./')[source]
      +get_path(path_str, dirname='./')[source]
      @@ -197,7 +197,7 @@

      This Page

      rel="nofollow">Show Source
      - + diff --git a/docs/pymatgen.analysis.diffusion.tests.test_analyzer.html b/docs/pymatgen.analysis.diffusion.tests.test_analyzer.html index 9c1d460..25b3be4 100644 --- a/docs/pymatgen.analysis.diffusion.tests.test_analyzer.html +++ b/docs/pymatgen.analysis.diffusion.tests.test_analyzer.html @@ -1,16 +1,16 @@ - + - + - pymatgen.analysis.diffusion.tests.test_analyzer module — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.tests.test_analyzer module — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

      Navigation

    • modules |
      • -
    • pymatgen-diffusion 2023.8.15 documentation »
      • +
    • pymatgen-diffusion 2024.6.10 documentation »
    • pymatgen.analysis.diffusion.tests.test_analyzer module
      • @@ -46,46 +46,46 @@

      Navigation

      -

      pymatgen.analysis.diffusion.tests.test_analyzer module

      +

      pymatgen.analysis.diffusion.tests.test_analyzer module

      -class DiffusionAnalyzerTest(methodName='runTest')[source]
      +class DiffusionAnalyzerTest(methodName='runTest')[source]

      Bases: PymatgenTest

      Create an instance of the class that will use the named test method when executed. Raises a ValueError if the instance does not have a method with the specified name.

      -test_from_structure_NPT()[source]
      +test_from_structure_NPT()[source]
      -test_init()[source]
      +test_init()[source]
      -test_init_npt()[source]
      +test_init_npt()[source]
      -class FuncTest(methodName='runTest')[source]
      +class FuncTest(methodName='runTest')[source]

      Bases: PymatgenTest

      Create an instance of the class that will use the named test method when executed. Raises a ValueError if the instance does not have a method with the specified name.

      -test_fit_arrhenius()[source]
      +test_fit_arrhenius()[source]
      -test_get_conversion_factor()[source]
      +test_get_conversion_factor()[source]
      @@ -130,7 +130,7 @@

      This Page

      rel="nofollow">Show Source
      - + diff --git a/docs/pymatgen.analysis.diffusion.tests.test_pathfinder.html b/docs/pymatgen.analysis.diffusion.tests.test_pathfinder.html index 575c191..876b15e 100644 --- a/docs/pymatgen.analysis.diffusion.tests.test_pathfinder.html +++ b/docs/pymatgen.analysis.diffusion.tests.test_pathfinder.html @@ -1,16 +1,16 @@ - + - + - pymatgen.analysis.diffusion.tests.test_pathfinder module — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.tests.test_pathfinder module — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

      Navigation

    • modules |
      • -
    • pymatgen-diffusion 2023.8.15 documentation »
      • +
    • pymatgen-diffusion 2024.6.10 documentation »
    • pymatgen.analysis.diffusion.tests.test_pathfinder module
      • @@ -46,17 +46,17 @@

      Navigation

      -

      pymatgen.analysis.diffusion.tests.test_pathfinder module

      +

      pymatgen.analysis.diffusion.tests.test_pathfinder module

      -class PathfinderTest(methodName='runTest')[source]
      +class PathfinderTest(methodName='runTest')[source]

      Bases: PymatgenTest

      Create an instance of the class that will use the named test method when executed. Raises a ValueError if the instance does not have a method with the specified name.

      -test_mhop_msonable()[source]
      +test_mhop_msonable()[source]
      @@ -94,7 +94,7 @@

      This Page

      rel="nofollow">Show Source
      - + diff --git a/docs/pymatgen.analysis.diffusion.utils.edge_data_from_sc.html b/docs/pymatgen.analysis.diffusion.utils.edge_data_from_sc.html index 8ac3ce6..3247fe9 100644 --- a/docs/pymatgen.analysis.diffusion.utils.edge_data_from_sc.html +++ b/docs/pymatgen.analysis.diffusion.utils.edge_data_from_sc.html @@ -1,16 +1,16 @@ - + - + - pymatgen.analysis.diffusion.utils.edge_data_from_sc module — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.utils.edge_data_from_sc module — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

      Navigation

    • modules |
      • -
    • pymatgen-diffusion 2023.8.15 documentation »
      • +
    • pymatgen-diffusion 2024.6.10 documentation »
    • pymatgen.analysis.diffusion.utils.edge_data_from_sc module
      • @@ -46,21 +46,23 @@

      Navigation

      -

      pymatgen.analysis.diffusion.utils.edge_data_from_sc module

      -

      Function to add edge data to MigrationGraph through 2 SC structures

      +

      pymatgen.analysis.diffusion.utils.edge_data_from_sc module

      +

      Function to add edge data to MigrationGraph through 2 SC structures.

      -add_edge_data_from_sc(mg: MigrationGraph, i_sc: Structure, e_sc: Structure, data_array: list, key: str = 'custom_key', use_host_sg: bool = True) → None[source]
      -

      Add a data entry and key to edges within FullPathMapper object with the same hop_label. -These hops are equivalent by symmetry to the 2 positions given in the supercell structures.

      +add_edge_data_from_sc(mg: MigrationGraph, i_sc: Structure, e_sc: Structure, data_array: list, key: str = 'custom_key', use_host_sg: bool = True) → None[source] +

      Add a data entry and key to edges within FullPathMapper object with the same +hop_label. These hops are equivalent by symmetry to the 2 positions given in the +supercell structures.

      Parameters:
        +

      • mg – MigrationGraph object.

      • i_sc – Supercell structure containing working ion at initial position

      • e_sc – Supercell structure containing working ion at ending position

      • data_array – The data to be added to the edges

      • key – Key of the edge attribute to be added

        • -

      • use_host_sg – Flag t whether or not to use the host structure’s spacegroup to initiate MigrationHop

        • +

      • use_host_sg – Flag whether to use the host structure’s spacegroup to initiate MigrationHop

      Returns:
      @@ -71,14 +73,14 @@

      Navigation

      -get_uc_pos(isite: PeriodicSite, esite: PeriodicSite, uc: Structure, sc: Structure, sm: StructureMatcher) → tuple[pymatgen.core.sites.PeriodicSite, pymatgen.core.sites.PeriodicSite, pymatgen.core.sites.PeriodicSite][source]
      -

      Take positions in the supercel and transform into the unitcell positions

      +get_uc_pos(isite: PeriodicSite, esite: PeriodicSite, uc: Structure, sc: Structure, sm: StructureMatcher) → tuple[PeriodicSite, PeriodicSite, PeriodicSite][source] +

      Take positions in the supercell and transform into the unit cell positions.

      Parameters:

      • isite – initial site in the SC

      • esite – ending site in the SC

        • -

      • uc – Unit Cell structre

        • +

      • uc – Unit Cell structure

      • sc – Super Cell structure

      • sm – StructureMatcher object with the working ion ignored

      @@ -91,8 +93,8 @@

      Navigation

      -get_unique_hop(mg: MigrationGraph, sc: Structure, isite: PeriodicSite, esite: PeriodicSite, use_host_sg: bool = True) → tuple[int, pymatgen.analysis.diffusion.neb.pathfinder.MigrationHop][source]
      -

      Get the unique hop label that correspond to two end positions in the SC

      +get_unique_hop(mg: MigrationGraph, sc: Structure, isite: PeriodicSite, esite: PeriodicSite, use_host_sg: bool = True) → tuple[int, MigrationHop][source] +

      Get the unique hop label that correspond to two end positions in the SC.

      Parameters:
        @@ -100,19 +102,20 @@

        Navigation

      • sc – Structure of the supercell used for the NEB calculation

      • isite – Initial position in the supercell

      • esite – Final position in the supercell

        • -

      • use_host_sg – Flag t whether or not to use the host structure’s spacegroup to initiate MigrationHop

        • +

      • use_host_sg – Flag t whether or not to use the host structure’s spacegroup to +initiate MigrationHop

      Returns:
      -

      The index of the unique hop, the MigrationHop object trasformed from the SC

      +

      The index of the unique hop, the MigrationHop object transformed from the SC

      -mh_eq(mh1, mh2)[source]
      -

      Allow for symmetric matching of MigrationPath objects with variable precession

      +mh_eq(mh1, mh2)[source] +

      Allow for symmetric matching of MigrationPath objects with variable precession.

      Parameters:
        @@ -159,7 +162,7 @@

        This Page

        rel="nofollow">Show Source
      - + diff --git a/docs/pymatgen.analysis.diffusion.utils.html b/docs/pymatgen.analysis.diffusion.utils.html index 0222940..09b061c 100644 --- a/docs/pymatgen.analysis.diffusion.utils.html +++ b/docs/pymatgen.analysis.diffusion.utils.html @@ -1,16 +1,16 @@ - + - + - pymatgen.analysis.diffusion.utils package — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.utils package — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

      Navigation

    • modules |
      • -
    • pymatgen-diffusion 2023.8.15 documentation »
      • +
    • pymatgen-diffusion 2024.6.10 documentation »
    • pymatgen.analysis.diffusion.utils package
      • @@ -46,14 +46,14 @@

      Navigation

      -

      pymatgen.analysis.diffusion.utils package

      +

      pymatgen.analysis.diffusion.utils package

      -

      Subpackages

      +

      Subpackages

      -

      Submodules

      +

      Submodules

      @@ -119,7 +119,7 @@

      This Page

      rel="nofollow">Show Source
      - + diff --git a/docs/pymatgen.analysis.diffusion.utils.maggma.html b/docs/pymatgen.analysis.diffusion.utils.maggma.html index 44865bb..351c1d0 100644 --- a/docs/pymatgen.analysis.diffusion.utils.maggma.html +++ b/docs/pymatgen.analysis.diffusion.utils.maggma.html @@ -1,16 +1,16 @@ - + - + - pymatgen.analysis.diffusion.utils.maggma module — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.utils.maggma module — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

      Navigation

    • modules |
      • -
    • pymatgen-diffusion 2023.8.15 documentation »
      • +
    • pymatgen-diffusion 2024.6.10 documentation »
    • pymatgen.analysis.diffusion.utils.maggma module
      • @@ -46,13 +46,13 @@

      Navigation

      -

      pymatgen.analysis.diffusion.utils.maggma module

      +

      pymatgen.analysis.diffusion.utils.maggma module

      Functions for querying Materials Project style MongoStores that contains cathode materials The functions are isolated from the rest of the package so -that the rest of the package will not depend on Maggma

      +that the rest of the package will not depend on Maggma.

      -get_entries_from_dbs(structure_group_store: MongoStore, material_store: MongoStore, migrating_ion: str, material_id: str)[source]
      +get_entries_from_dbs(structure_group_store: MongoStore, material_store: MongoStore, migrating_ion: str, material_id: str)[source]

      Get the entries needed to construct a migration from a database that contains topotactically matched structures.

      @@ -60,10 +60,10 @@

      Navigation

      • structure_group_store – Electrode documents one per each similar group of insertion materials, can also use any db that contains a

        • -

      • material_store – Material documenets one per each similar structure ( +

      • material_store – Material documents one per each similar structure ( multiple tasks)

      • migrating_ion – The name of the migrating ion

        • -

      • structures (material_ids list with topotactic) –

        • +

      • material_id – Material id

      @@ -99,7 +99,7 @@

      This Page

      rel="nofollow">Show Source
      - + diff --git a/docs/pymatgen.analysis.diffusion.utils.parse_entries.html b/docs/pymatgen.analysis.diffusion.utils.parse_entries.html index 0c5f03d..7faa908 100644 --- a/docs/pymatgen.analysis.diffusion.utils.parse_entries.html +++ b/docs/pymatgen.analysis.diffusion.utils.parse_entries.html @@ -1,16 +1,16 @@ - + - + - pymatgen.analysis.diffusion.utils.parse_entries module — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.utils.parse_entries module — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

      Navigation

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      • +
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    • pymatgen.analysis.diffusion.utils.parse_entries module
      • @@ -46,15 +46,16 @@

      Navigation

      -

      pymatgen.analysis.diffusion.utils.parse_entries module

      +

      pymatgen.analysis.diffusion.utils.parse_entries module

      Functions for combining many ComputedEntry objects into MigrationGraph objects.

      -get_inserted_on_base(base_ent: ComputedStructureEntry, inserted_ent: ComputedStructureEntry, migrating_ion_entry: ComputedEntry, sm: StructureMatcher) → Structure | None[source]
      -

      For a structured-matched pair of base and inserted entries, map all of the Li positions in the inserted entry to -positions in the base entry and return a new structure where all the sites are decorated with the insertion -energy. Since the calculation of the insertion energy needs the energy of the metallic working ion, -a migrating_ion_entry must also be provided.

      +get_inserted_on_base(base_ent: ComputedStructureEntry, inserted_ent: ComputedStructureEntry, migrating_ion_entry: ComputedEntry, sm: StructureMatcher) → Structure | None[source] +

      For a structured-matched pair of base and inserted entries, map all of the Li +positions in the inserted entry to positions in the base entry and return a new +structure where all the sites are decorated with the insertion energy. Since the +calculation of the insertion energy needs the energy of the metallic working ion, a +migrating_ion_entry must also be provided.

      Parameters:
        @@ -72,23 +73,31 @@

        Navigation

        -get_insertion_energy(base_entry: ComputedStructureEntry, inserted_entry: ComputedStructureEntry, migrating_ion_entry: ComputedEntry) → float[source]
        +get_insertion_energy(base_entry: ComputedStructureEntry, inserted_entry: ComputedStructureEntry, migrating_ion_entry: ComputedEntry) → float[source]

        Calculate the insertion energy for a given inserted entry :param base_entry: The entry for the host structure :param inserted_entry: The entry for the inserted structure :param migrating_ion_entry: The entry for the metallic phase of the working ion

        Returns:
        -

        The insertion energy defined as (E[inserted] - (E[Base] + n * E[working_ion]))/(n) -Where n is the number of working ions and E[inserted]. -Additionally, and E[base] and E[inserted] are for structures of the same size (sans working ion)

        +

        +
        insertion energy defined as

        (E[inserted] - (E[Base] + n * E[working_ion])) / n

        +
        +
        +

        Where n is the number of working ions and E[inserted]. +Additionally, and E[base] and E[inserted] are for structures of the same size +(sans working ion).

        +

        +
        +
        Return type:
        +

        float

        -get_matched_structure_mapping(base: Structure, inserted: Structure, sm: StructureMatcher)[source]
        +get_matched_structure_mapping(base: Structure, inserted: Structure, sm: StructureMatcher)[source]

        Get the mapping from the inserted structure onto the base structure, assuming that the inserted structure sans the working ion is some kind of SC of the base.

        @@ -112,15 +121,16 @@

        Navigation

        -get_sym_migration_ion_sites(base_struct: Structure, inserted_struct: Structure, migrating_ion: str, symprec: float = 0.01, angle_tol: float = 5.0) → Structure[source]
        -

        Take one inserted entry then map out all symmetry equivalent copies of the cation sites in base entry. -Each site is decorated with the insertion energy calculated from the base and inserted entries.

        +get_sym_migration_ion_sites(base_struct: Structure, inserted_struct: Structure, migrating_ion: str, symprec: float = 0.01, angle_tol: float = 5.0) → Structure[source] +

        Take one inserted entry then map out all symmetry equivalent copies of the cation +sites in base entry. Each site is decorated with the insertion energy calculated +from the base and inserted entries.

        Parameters:
          -

        • inserted_entry – entry that contains cation

          • -

        • base_struct_entry – the entry containing the base structure

          • -

        • migrating_ion_entry – the name of the migrating species

          • +

        • base_struct – the base structure.

          • +

        • inserted_struct – inserted structure.

          • +

        • migrating_ion – Ion that migrates.

        • symprec – the symprec tolerance for the space group analysis

        • angle_tol – the angle tolerance for the space group analysis

        @@ -133,28 +143,34 @@

        Navigation

        -process_entries(base_entries: list[ComputedStructureEntry], inserted_entries: list[ComputedStructureEntry], migrating_ion_entry: ComputedEntry, symprec: float = 0.01, ltol: float = 0.2, stol: float = 0.3, angle_tol: float = 5.0) → list[dict][source]
        -

        Process a list of base entries and inserted entries to create input for migration path analysis Each inserted -entries can be mapped to more than one base entry. Return groups of structures decorated with the working ions -to indicate the metastable sites, ranked by the number of working ion sites (highest number is the first).

        +process_entries(base_entries: list[ComputedStructureEntry], inserted_entries: list[ComputedStructureEntry], migrating_ion_entry: ComputedEntry, symprec: float = 0.01, ltol: float = 0.2, stol: float = 0.3, angle_tol: float = 5.0) → list[dict][source] +

        Process a list of base entries and inserted entries to create input for migration +path analysis Each inserted entries can be mapped to more than one base entry. +Return groups of structures decorated with the working ions to indicate the +metastable sites, ranked by the number of working ion sites (highest number is the +first).

        Parameters:
          -

        • base_entries – Full list of base entires

          • -

        • inserted_entries – Full list of inserted entires

          • -

        • migrating_ion_entry – The metallic phase of the working ion, used to calculate insertion energies.

          • +

        • base_entries – Full list of base entries

          • +

        • inserted_entries – Full list of inserted entries

          • +

        • migrating_ion_entry – The metallic phase of the working ion, used to calculate +insertion energies.

        • symprec – symmetry parameter for SpacegroupAnalyzer

        • ltol – Fractional length tolerance for StructureMatcher

        • stol – Site tolerance for StructureMatcher

          • -

        • angle_tol – Angle tolerance fro StructureMatcher and SpacegroupAnalyzer

          • +

        • angle_tol – Angle tolerance for StructureMatcher and SpacegroupAnalyzer

        • only_single_cat – If True, only use single cation insertions so the site energy is more accurate use_strict_tol: halve the ltol and stol parameter for more strict matching.

        Returns:
        -

        List of dictionaries that each contain -{‘base’ : Structure Object of host, ‘inserted’ : Structure object of all inserted sites}

        +

        +
        List of dictionaries that each contain {‘base’: Structure Object of host,

        ’inserted’: Structure object of all inserted sites}

        +
        +
        +

        Return type:

        list

        @@ -196,7 +212,7 @@

        This Page

        rel="nofollow">Show Source
      - + diff --git a/docs/pymatgen.analysis.diffusion.utils.supercells.html b/docs/pymatgen.analysis.diffusion.utils.supercells.html index bfcdb83..69c3188 100644 --- a/docs/pymatgen.analysis.diffusion.utils.supercells.html +++ b/docs/pymatgen.analysis.diffusion.utils.supercells.html @@ -1,16 +1,16 @@ - + - + - pymatgen.analysis.diffusion.utils.supercells module — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.utils.supercells module — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

      Navigation

    • modules |
      • -
    • pymatgen-diffusion 2023.8.15 documentation »
      • +
    • pymatgen-diffusion 2024.6.10 documentation »
    • pymatgen.analysis.diffusion.utils.supercells module
      • @@ -46,11 +46,11 @@

      Navigation

      -

      pymatgen.analysis.diffusion.utils.supercells module

      -

      Functions for creating supercells for NEB calculations

      +

      pymatgen.analysis.diffusion.utils.supercells module

      +

      Functions for creating supercells for NEB calculations.

      -get_sc_fromstruct(base_struct: Structure, min_atoms: int = 80, max_atoms: int = 240, min_length: float = 10.0) → list[list[int]][source]
      +get_sc_fromstruct(base_struct: Structure, min_atoms: int = 80, max_atoms: int = 240, min_length: float = 10.0) → list[list[int]][source]

      Generate the best supercell from a unitcell. The CubicSupercellTransformation from PMG is much faster but don’t iterate over as many supercell configurations so it’s less able to find the best configuration in a give cell size. @@ -76,15 +76,19 @@

      Navigation

      -get_start_end_structures(isite: PeriodicSite, esite: PeriodicSite, base_struct: Structure, sc_mat: list[list[int | float]], vac_mode: bool, debug: bool = False, tol: float = 1e-05) → tuple[pymatgen.core.structure.Structure, pymatgen.core.structure.Structure, pymatgen.core.structure.Structure][source]
      +get_start_end_structures(isite: PeriodicSite, esite: PeriodicSite, base_struct: Structure, sc_mat: list[list[int | float]], vac_mode: bool, debug: bool = False, tol: float = 1e-05) → tuple[Structure, Structure, Structure][source]

      Obtain the starting and terminating structures in a supercell for NEB calculations.

      Parameters:
        +

      • isite – Initial site index.

        • +

      • esite – End site index.

      • hop – object presenting the migration event

      • base_struct – unit cell representation of the structure

      • sc_mat – supercell transformation to create the simulation cell for the NEB calc

        • -

      • tol – toleranace for identifying isite/esite within base_struct

        • +

      • vac_mode – Vacuum mode.

        • +

      • debug – debug mode.

        • +

      • tol – toleranace for identifying isite/esite within base_struct.

      Returns:
      @@ -124,7 +128,7 @@

      This Page

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      - + diff --git a/docs/pymatgen.analysis.diffusion.utils.tests.test_edge_data_from_sc.html b/docs/pymatgen.analysis.diffusion.utils.tests.test_edge_data_from_sc.html index fdf4b59..916c3fc 100644 --- a/docs/pymatgen.analysis.diffusion.utils.tests.test_edge_data_from_sc.html +++ b/docs/pymatgen.analysis.diffusion.utils.tests.test_edge_data_from_sc.html @@ -1,16 +1,16 @@ - + - + - pymatgen.analysis.diffusion.utils.tests.test_edge_data_from_sc module — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.utils.tests.test_edge_data_from_sc module — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

      Navigation

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    • pymatgen-diffusion 2023.8.15 documentation »
      • +
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      • @@ -46,25 +46,25 @@

      Navigation

      -

      pymatgen.analysis.diffusion.utils.tests.test_edge_data_from_sc module

      +

      pymatgen.analysis.diffusion.utils.tests.test_edge_data_from_sc module

      -test_add_edge_data_from_sc()[source]
      +test_add_edge_data_from_sc()[source]
      -test_get_uc_pos()[source]
      +test_get_uc_pos()[source]
      -test_get_unique_hop_host()[source]
      +test_get_unique_hop_host()[source]
      -test_get_unique_host_nonhost()[source]
      +test_get_unique_host_nonhost()[source]
      @@ -100,7 +100,7 @@

      This Page

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      - + diff --git a/docs/pymatgen.analysis.diffusion.utils.tests.test_maggma.html b/docs/pymatgen.analysis.diffusion.utils.tests.test_maggma.html index 58b4bfc..207da55 100644 --- a/docs/pymatgen.analysis.diffusion.utils.tests.test_maggma.html +++ b/docs/pymatgen.analysis.diffusion.utils.tests.test_maggma.html @@ -1,16 +1,16 @@ - + - + - pymatgen.analysis.diffusion.utils.tests.test_maggma module — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.utils.tests.test_maggma module — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

      Navigation

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      • @@ -45,18 +45,8 @@

      Navigation

      -
      -

      pymatgen.analysis.diffusion.utils.tests.test_maggma module

      -
      -
      -maggma_stores()[source]
      -
      - -
      -
      -test(maggma_stores)[source]
      -
      - +
      +

      pymatgen.analysis.diffusion.utils.tests.test_maggma module

      @@ -65,18 +55,7 @@

      Navigation

      diff --git a/docs/pymatgen.analysis.diffusion.utils.tests.test_parse_entries.html b/docs/pymatgen.analysis.diffusion.utils.tests.test_parse_entries.html index 3a5edfe..0a146f3 100644 --- a/docs/pymatgen.analysis.diffusion.utils.tests.test_parse_entries.html +++ b/docs/pymatgen.analysis.diffusion.utils.tests.test_parse_entries.html @@ -1,16 +1,16 @@ - + - + - pymatgen.analysis.diffusion.utils.tests.test_parse_entries module — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis.diffusion.utils.tests.test_parse_entries module — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

      Navigation

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      • @@ -46,43 +46,43 @@

      Navigation

      -

      pymatgen.analysis.diffusion.utils.tests.test_parse_entries module

      +

      pymatgen.analysis.diffusion.utils.tests.test_parse_entries module

      -class ParseEntriesTest(methodName='runTest')[source]
      +class ParseEntriesTest(methodName='runTest')[source]

      Bases: TestCase

      Create an instance of the class that will use the named test method when executed. Raises a ValueError if the instance does not have a method with the specified name.

      -setUp()[source]
      +setUp()[source]

      Hook method for setting up the test fixture before exercising it.

      -test_filter_and_merge()[source]
      +test_filter_and_merge()[source]
      -test_get_all_sym_sites()[source]
      +test_get_all_sym_sites()[source]
      -test_get_inserted_on_base()[source]
      +test_get_inserted_on_base()[source]
      -test_get_insertion_energy()[source]
      +test_get_insertion_energy()[source]
      -test_process_ents()[source]
      +test_process_ents()[source]
      @@ -125,7 +125,7 @@

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      - + diff --git a/docs/pymatgen.analysis.html b/docs/pymatgen.analysis.html index f490867..2b321ed 100644 --- a/docs/pymatgen.analysis.html +++ b/docs/pymatgen.analysis.html @@ -1,16 +1,16 @@ - + - + - pymatgen.analysis namespace — pymatgen-diffusion 2023.8.15 documentation + pymatgen.analysis namespace — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

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      • @@ -46,9 +46,9 @@

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      pymatgen.analysis namespace

      +

      pymatgen.analysis namespace

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      diff --git a/docs/pymatgen.html b/docs/pymatgen.html index 7fc1529..fab5784 100644 --- a/docs/pymatgen.html +++ b/docs/pymatgen.html @@ -1,16 +1,16 @@ - + - + - pymatgen namespace — pymatgen-diffusion 2023.8.15 documentation + pymatgen namespace — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -39,7 +39,7 @@

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      • @@ -51,7 +51,7 @@

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      pymatgen namespace

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      @@ -75,7 +75,7 @@

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      - + diff --git a/docs/pymatgen_diffusion.aimd.html b/docs/pymatgen_diffusion.aimd.html index f0a0928..eaa14ef 100644 --- a/docs/pymatgen_diffusion.aimd.html +++ b/docs/pymatgen_diffusion.aimd.html @@ -1,16 +1,16 @@ - + - + - pymatgen_diffusion.aimd package — pymatgen-diffusion 2023.8.15 documentation + pymatgen_diffusion.aimd package — pymatgen-diffusion 2024.6.10 documentation - - - + + + @@ -35,7 +35,7 @@

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      • @@ -46,29 +46,29 @@

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      pymatgen_diffusion.aimd package

      +

      pymatgen_diffusion.aimd package

      -

      Subpackages

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      pymatgen_diffusion.aimd.clustering module

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      +

      pymatgen_diffusion.aimd.pathway module

      -

      pymatgen_diffusion.aimd.rdf module

      +

      pymatgen_diffusion.aimd.rdf module

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      pymatgen_diffusion.aimd.van_hove module

      +

      pymatgen_diffusion.aimd.van_hove module

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      Module contents

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      +

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      -

      pymatgen_diffusion.neb.pathfinder module

      +

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      pymatgen_diffusion.neb.periodic_dijkstra module

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      +
      diff --git a/docs/searchindex.js b/docs/searchindex.js index d88cf3d..ff12f08 100644 --- a/docs/searchindex.js +++ b/docs/searchindex.js @@ -1 +1 @@ -Search.setIndex({"docnames": ["_themes/README", "change_log", "index", "modules", "pymatgen", "pymatgen.analysis", "pymatgen.analysis.diffusion", "pymatgen.analysis.diffusion.aimd", "pymatgen.analysis.diffusion.aimd.clustering", "pymatgen.analysis.diffusion.aimd.pathway", "pymatgen.analysis.diffusion.aimd.rdf", "pymatgen.analysis.diffusion.aimd.tests.test_clustering", "pymatgen.analysis.diffusion.aimd.tests.test_pathway", "pymatgen.analysis.diffusion.aimd.tests.test_rdf", "pymatgen.analysis.diffusion.aimd.tests.test_van_hove", "pymatgen.analysis.diffusion.aimd.van_hove", "pymatgen.analysis.diffusion.analyzer", "pymatgen.analysis.diffusion.neb", "pymatgen.analysis.diffusion.neb.full_path_mapper", "pymatgen.analysis.diffusion.neb.io", "pymatgen.analysis.diffusion.neb.pathfinder", "pymatgen.analysis.diffusion.neb.periodic_dijkstra", 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"document": 2, "edge_data_from_sc": 28, "exhaust": 2, "featur": 2, "full_path_mapp": [18, 37], "indic": 2, "introduct": 2, "io": [19, 37], "krtheme": 0, "licens": 2, "log": [1, 2], "maggma": 29, "modul": [6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37], "namespac": [4, 5], "neb": [17, 18, 19, 20, 21, 22, 23, 24, 37], "non": 2, "our": 2, "packag": [6, 7, 17, 27, 35, 36, 37], "parse_entri": 30, "pathfind": [20, 37], "pathwai": [9, 36], "periodic_dijkstra": [21, 37], "polici": 2, "pymatgen": [3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34], "pymatgen_diffus": [35, 36, 37], "rdf": [10, 36], "sphinx": 0, "style": 0, "submodul": [6, 7, 17, 27, 36, 37], "subpackag": [5, 6, 7, 17, 27, 35, 36, 37], "supercel": 31, "tabl": 2, "test": [11, 12, 13, 14, 22, 23, 24, 25, 26, 32, 33, 34], "test_analyz": 25, "test_clust": 11, "test_edge_data_from_sc": 32, "test_full_path_mapp": 22, "test_io": 23, "test_maggma": 33, "test_parse_entri": 34, "test_pathfind": [24, 26], "test_pathwai": 12, "test_rdf": 13, "test_van_hov": 14, "util": [27, 28, 29, 30, 31, 32, 33, 34], "v0": 1, "v2018": 1, "v2019": 1, "v2021": 1, "v2022": 1, "v2023": 1, "van_hov": [15, 36]}}) \ No newline at end of file diff --git a/pyproject.toml b/pyproject.toml index 1cf6a76..e951c7d 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -54,7 +54,7 @@ dependencies = [ "pymatgen>=2024.6.10", "joblib" ] -version = "2023.8.15" +version = "2024.6.24" [project.urls] Homepage = "http://materialsvirtuallab.github.io/pymatgen-analysis-diffusion/"