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train | BoltztrapPlotter.plot_seebeck_eff_mass_mu | Plot respect to the chemical potential of the Seebeck effective mass
calculated as explained in Ref.
Gibbs, Z. M. et al., Effective mass and fermi surface complexity factor
from ab initio band structure calculations.
npj Computational Materials 3, 8 (2017).
Args:
o... | pymatgen/electronic_structure/plotter.py | def plot_seebeck_eff_mass_mu(self, temps=[300], output='average',
Lambda=0.5):
"""
Plot respect to the chemical potential of the Seebeck effective mass
calculated as explained in Ref.
Gibbs, Z. M. et al., Effective mass and fermi surface complexity factor... | def plot_seebeck_eff_mass_mu(self, temps=[300], output='average',
Lambda=0.5):
"""
Plot respect to the chemical potential of the Seebeck effective mass
calculated as explained in Ref.
Gibbs, Z. M. et al., Effective mass and fermi surface complexity factor... | [
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train | BoltztrapPlotter.plot_complexity_factor_mu | Plot respect to the chemical potential of the Fermi surface complexity
factor calculated as explained in Ref.
Gibbs, Z. M. et al., Effective mass and fermi surface complexity factor
from ab initio band structure calculations.
npj Computational Materials 3, 8 (2017).
A... | pymatgen/electronic_structure/plotter.py | def plot_complexity_factor_mu(self, temps=[300], output='average',
Lambda=0.5):
"""
Plot respect to the chemical potential of the Fermi surface complexity
factor calculated as explained in Ref.
Gibbs, Z. M. et al., Effective mass and fermi surface compl... | def plot_complexity_factor_mu(self, temps=[300], output='average',
Lambda=0.5):
"""
Plot respect to the chemical potential of the Fermi surface complexity
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Gibbs, Z. M. et al., Effective mass and fermi surface compl... | [
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train | BoltztrapPlotter.plot_seebeck_mu | Plot the seebeck coefficient in function of Fermi level
Args:
temp:
the temperature
xlim:
a list of min and max fermi energy by default (0, and band gap)
Returns:
a matplotlib object | pymatgen/electronic_structure/plotter.py | def plot_seebeck_mu(self, temp=600, output='eig', xlim=None):
"""
Plot the seebeck coefficient in function of Fermi level
Args:
temp:
the temperature
xlim:
a list of min and max fermi energy by default (0, and band gap)
Returns:
... | def plot_seebeck_mu(self, temp=600, output='eig', xlim=None):
"""
Plot the seebeck coefficient in function of Fermi level
Args:
temp:
the temperature
xlim:
a list of min and max fermi energy by default (0, and band gap)
Returns:
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train | BoltztrapPlotter.plot_conductivity_mu | Plot the conductivity in function of Fermi level. Semi-log plot
Args:
temp: the temperature
xlim: a list of min and max fermi energy by default (0, and band
gap)
tau: A relaxation time in s. By default none and the plot is by
units of relaxatio... | pymatgen/electronic_structure/plotter.py | def plot_conductivity_mu(self, temp=600, output='eig',
relaxation_time=1e-14, xlim=None):
"""
Plot the conductivity in function of Fermi level. Semi-log plot
Args:
temp: the temperature
xlim: a list of min and max fermi energy by default (0, ... | def plot_conductivity_mu(self, temp=600, output='eig',
relaxation_time=1e-14, xlim=None):
"""
Plot the conductivity in function of Fermi level. Semi-log plot
Args:
temp: the temperature
xlim: a list of min and max fermi energy by default (0, ... | [
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train | BoltztrapPlotter.plot_power_factor_mu | Plot the power factor in function of Fermi level. Semi-log plot
Args:
temp: the temperature
xlim: a list of min and max fermi energy by default (0, and band
gap)
tau: A relaxation time in s. By default none and the plot is by
units of relaxatio... | pymatgen/electronic_structure/plotter.py | def plot_power_factor_mu(self, temp=600, output='eig',
relaxation_time=1e-14, xlim=None):
"""
Plot the power factor in function of Fermi level. Semi-log plot
Args:
temp: the temperature
xlim: a list of min and max fermi energy by default (0, ... | def plot_power_factor_mu(self, temp=600, output='eig',
relaxation_time=1e-14, xlim=None):
"""
Plot the power factor in function of Fermi level. Semi-log plot
Args:
temp: the temperature
xlim: a list of min and max fermi energy by default (0, ... | [
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train | BoltztrapPlotter.plot_zt_mu | Plot the ZT in function of Fermi level.
Args:
temp: the temperature
xlim: a list of min and max fermi energy by default (0, and band
gap)
tau: A relaxation time in s. By default none and the plot is by
units of relaxation time
Returns:... | pymatgen/electronic_structure/plotter.py | def plot_zt_mu(self, temp=600, output='eig', relaxation_time=1e-14,
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"""
Plot the ZT in function of Fermi level.
Args:
temp: the temperature
xlim: a list of min and max fermi energy by default (0, and band
gap)
ta... | def plot_zt_mu(self, temp=600, output='eig', relaxation_time=1e-14,
xlim=None):
"""
Plot the ZT in function of Fermi level.
Args:
temp: the temperature
xlim: a list of min and max fermi energy by default (0, and band
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train | BoltztrapPlotter.plot_seebeck_temp | Plot the Seebeck coefficient in function of temperature for different
doping levels.
Args:
dopings: the default 'all' plots all the doping levels in the analyzer.
Specify a list of doping levels if you want to plot only some.
output: with 'average' you get ... | pymatgen/electronic_structure/plotter.py | def plot_seebeck_temp(self, doping='all', output='average'):
"""
Plot the Seebeck coefficient in function of temperature for different
doping levels.
Args:
dopings: the default 'all' plots all the doping levels in the analyzer.
Specify a list of doping ... | def plot_seebeck_temp(self, doping='all', output='average'):
"""
Plot the Seebeck coefficient in function of temperature for different
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Args:
dopings: the default 'all' plots all the doping levels in the analyzer.
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train | BoltztrapPlotter.plot_power_factor_dop | Plot the Power Factor in function of doping levels for different temperatures.
Args:
temps: the default 'all' plots all the temperatures in the analyzer.
Specify a list of temperatures if you want to plot only some.
output: with 'average' you get an average of the thr... | pymatgen/electronic_structure/plotter.py | def plot_power_factor_dop(self, temps='all', output='average',
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"""
Plot the Power Factor in function of doping levels for different temperatures.
Args:
temps: the default 'all' plots all the temperatures in the analyzer.
... | def plot_power_factor_dop(self, temps='all', output='average',
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"""
Plot the Power Factor in function of doping levels for different temperatures.
Args:
temps: the default 'all' plots all the temperatures in the analyzer.
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train | BoltztrapPlotter.plot_zt_dop | Plot the figure of merit zT in function of doping levels for different
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Args:
temps: the default 'all' plots all the temperatures in the analyzer.
Specify a list of temperatures if you want to plot only some.
output: with 'average' you get an aver... | pymatgen/electronic_structure/plotter.py | def plot_zt_dop(self, temps='all', output='average', relaxation_time=1e-14):
"""
Plot the figure of merit zT in function of doping levels for different
temperatures.
Args:
temps: the default 'all' plots all the temperatures in the analyzer.
Specify a list ... | def plot_zt_dop(self, temps='all', output='average', relaxation_time=1e-14):
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Plot the figure of merit zT in function of doping levels for different
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Args:
temps: the default 'all' plots all the temperatures in the analyzer.
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train | BoltztrapPlotter.plot_dos | plot dos
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sigma: a smearing
Returns:
a matplotlib object | pymatgen/electronic_structure/plotter.py | def plot_dos(self, sigma=0.05):
"""
plot dos
Args:
sigma: a smearing
Returns:
a matplotlib object
"""
plotter = DosPlotter(sigma=sigma)
plotter.add_dos("t", self._bz.dos)
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"""
plot dos
Args:
sigma: a smearing
Returns:
a matplotlib object
"""
plotter = DosPlotter(sigma=sigma)
plotter.add_dos("t", self._bz.dos)
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train | BoltztrapPlotter.plot_carriers | Plot the carrier concentration in function of Fermi level
Args:
temp: the temperature
Returns:
a matplotlib object | pymatgen/electronic_structure/plotter.py | def plot_carriers(self, temp=300):
"""
Plot the carrier concentration in function of Fermi level
Args:
temp: the temperature
Returns:
a matplotlib object
"""
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plt.semilogy(self._bz.mu_steps,
... | def plot_carriers(self, temp=300):
"""
Plot the carrier concentration in function of Fermi level
Args:
temp: the temperature
Returns:
a matplotlib object
"""
import matplotlib.pyplot as plt
plt.semilogy(self._bz.mu_steps,
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train | BoltztrapPlotter.plot_hall_carriers | Plot the Hall carrier concentration in function of Fermi level
Args:
temp: the temperature
Returns:
a matplotlib object | pymatgen/electronic_structure/plotter.py | def plot_hall_carriers(self, temp=300):
"""
Plot the Hall carrier concentration in function of Fermi level
Args:
temp: the temperature
Returns:
a matplotlib object
"""
import matplotlib.pyplot as plt
hall_carriers = [abs(i) for i in
... | def plot_hall_carriers(self, temp=300):
"""
Plot the Hall carrier concentration in function of Fermi level
Args:
temp: the temperature
Returns:
a matplotlib object
"""
import matplotlib.pyplot as plt
hall_carriers = [abs(i) for i in
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train | CohpPlotter.add_cohp | Adds a COHP for plotting.
Args:
label: Label for the COHP. Must be unique.
cohp: COHP object. | pymatgen/electronic_structure/plotter.py | def add_cohp(self, label, cohp):
"""
Adds a COHP for plotting.
Args:
label: Label for the COHP. Must be unique.
cohp: COHP object.
"""
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Adds a COHP for plotting.
Args:
label: Label for the COHP. Must be unique.
cohp: COHP object.
"""
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train | CohpPlotter.add_cohp_dict | Adds a dictionary of COHPs with an optional sorting function
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Args:
cohp_dict: dict of the form {label: Cohp}
key_sort_func: function used to sort the cohp_dict keys. | pymatgen/electronic_structure/plotter.py | def add_cohp_dict(self, cohp_dict, key_sort_func=None):
"""
Adds a dictionary of COHPs with an optional sorting function
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Args:
cohp_dict: dict of the form {label: Cohp}
key_sort_func: function used to sort the cohp_dict keys.
"""
if... | def add_cohp_dict(self, cohp_dict, key_sort_func=None):
"""
Adds a dictionary of COHPs with an optional sorting function
for the keys.
Args:
cohp_dict: dict of the form {label: Cohp}
key_sort_func: function used to sort the cohp_dict keys.
"""
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train | CohpPlotter.get_plot | Get a matplotlib plot showing the COHP.
Args:
xlim: Specifies the x-axis limits. Defaults to None for
automatic determination.
ylim: Specifies the y-axis limits. Defaults to None for
automatic determination.
plot_negative: It is common to pl... | pymatgen/electronic_structure/plotter.py | def get_plot(self, xlim=None, ylim=None, plot_negative=None,
integrated=False, invert_axes=True):
"""
Get a matplotlib plot showing the COHP.
Args:
xlim: Specifies the x-axis limits. Defaults to None for
automatic determination.
ylim: Sp... | def get_plot(self, xlim=None, ylim=None, plot_negative=None,
integrated=False, invert_axes=True):
"""
Get a matplotlib plot showing the COHP.
Args:
xlim: Specifies the x-axis limits. Defaults to None for
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train | get_dopants_from_substitution_probabilities | Get dopant suggestions based on substitution probabilities.
Args:
structure (Structure): A pymatgen structure decorated with
oxidation states.
num_dopants (int): The number of suggestions to return for
n- and p-type dopants.
threshold (float): Probability threshold f... | pymatgen/analysis/structure_prediction/dopant_predictor.py | def get_dopants_from_substitution_probabilities(structure, num_dopants=5,
threshold=0.001,
match_oxi_sign=False):
"""
Get dopant suggestions based on substitution probabilities.
Args:
structure (Structur... | def get_dopants_from_substitution_probabilities(structure, num_dopants=5,
threshold=0.001,
match_oxi_sign=False):
"""
Get dopant suggestions based on substitution probabilities.
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structure (Structur... | [
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train | get_dopants_from_shannon_radii | Get dopant suggestions based on Shannon radii differences.
Args:
bonded_structure (StructureGraph): A pymatgen structure graph
decorated with oxidation states. For example, generated using the
CrystalNN.get_bonded_structure() method.
num_dopants (int): The nummber of suggest... | pymatgen/analysis/structure_prediction/dopant_predictor.py | def get_dopants_from_shannon_radii(bonded_structure, num_dopants=5,
match_oxi_sign=False):
"""
Get dopant suggestions based on Shannon radii differences.
Args:
bonded_structure (StructureGraph): A pymatgen structure graph
decorated with oxidation state... | def get_dopants_from_shannon_radii(bonded_structure, num_dopants=5,
match_oxi_sign=False):
"""
Get dopant suggestions based on Shannon radii differences.
Args:
bonded_structure (StructureGraph): A pymatgen structure graph
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train | _get_dopants | Utility method to get n- and p-type dopants from a list of substitutions. | pymatgen/analysis/structure_prediction/dopant_predictor.py | def _get_dopants(substitutions, num_dopants, match_oxi_sign):
"""
Utility method to get n- and p-type dopants from a list of substitutions.
"""
n_type = [pred for pred in substitutions
if pred['dopant_species'].oxi_state >
pred['original_species'].oxi_state
and ... | def _get_dopants(substitutions, num_dopants, match_oxi_sign):
"""
Utility method to get n- and p-type dopants from a list of substitutions.
"""
n_type = [pred for pred in substitutions
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train | _shannon_radii_from_cn | Utility func to get Shannon radii for a particular coordination number.
As the Shannon radii depends on charge state and coordination number,
species without an entry for a particular coordination number will
be skipped.
Args:
species_list (list): A list of Species to get the Shannon radii for... | pymatgen/analysis/structure_prediction/dopant_predictor.py | def _shannon_radii_from_cn(species_list, cn_roman, radius_to_compare=0):
"""
Utility func to get Shannon radii for a particular coordination number.
As the Shannon radii depends on charge state and coordination number,
species without an entry for a particular coordination number will
be skipped.
... | def _shannon_radii_from_cn(species_list, cn_roman, radius_to_compare=0):
"""
Utility func to get Shannon radii for a particular coordination number.
As the Shannon radii depends on charge state and coordination number,
species without an entry for a particular coordination number will
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train | _int_to_roman | Utility method to convert an int (less than 20) to a roman numeral. | pymatgen/analysis/structure_prediction/dopant_predictor.py | def _int_to_roman(number):
"""Utility method to convert an int (less than 20) to a roman numeral."""
roman_conv = [(10, "X"), (9, "IX"), (5, "V"), (4, "IV"), (1, "I")]
result = []
for (arabic, roman) in roman_conv:
(factor, number) = divmod(number, arabic)
result.append(roman * factor)
... | def _int_to_roman(number):
"""Utility method to convert an int (less than 20) to a roman numeral."""
roman_conv = [(10, "X"), (9, "IX"), (5, "V"), (4, "IV"), (1, "I")]
result = []
for (arabic, roman) in roman_conv:
(factor, number) = divmod(number, arabic)
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train | solid_angle | Helper method to calculate the solid angle of a set of coords from the
center.
Args:
center (3x1 array): Center to measure solid angle from.
coords (Nx3 array): List of coords to determine solid angle.
Returns:
The solid angle. | pymatgen/analysis/local_env.py | def solid_angle(center, coords):
"""
Helper method to calculate the solid angle of a set of coords from the
center.
Args:
center (3x1 array): Center to measure solid angle from.
coords (Nx3 array): List of coords to determine solid angle.
Returns:
The solid angle.
"""
... | def solid_angle(center, coords):
"""
Helper method to calculate the solid angle of a set of coords from the
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Args:
center (3x1 array): Center to measure solid angle from.
coords (Nx3 array): List of coords to determine solid angle.
Returns:
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train | vol_tetra | Calculate the volume of a tetrahedron, given the four vertices of vt1,
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Args:
vt1 (array-like): coordinates of vertex 1.
vt2 (array-like): coordinates of vertex 2.
vt3 (array-like): coordinates of vertex 3.
vt4 (array-like): coordinates of vertex 4.
Returns:
... | pymatgen/analysis/local_env.py | def vol_tetra(vt1, vt2, vt3, vt4):
"""
Calculate the volume of a tetrahedron, given the four vertices of vt1,
vt2, vt3 and vt4.
Args:
vt1 (array-like): coordinates of vertex 1.
vt2 (array-like): coordinates of vertex 2.
vt3 (array-like): coordinates of vertex 3.
vt4 (arra... | def vol_tetra(vt1, vt2, vt3, vt4):
"""
Calculate the volume of a tetrahedron, given the four vertices of vt1,
vt2, vt3 and vt4.
Args:
vt1 (array-like): coordinates of vertex 1.
vt2 (array-like): coordinates of vertex 2.
vt3 (array-like): coordinates of vertex 3.
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train | get_okeeffe_params | Returns the elemental parameters related to atom size and
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parameters (bond length) of pairs of atoms on the basis of data
provided in 'Atoms Sizes and Bond Lengths in Molecules and Crystals'
(O'Keeffe & Brese, 1991).
Args:
el_symb... | pymatgen/analysis/local_env.py | def get_okeeffe_params(el_symbol):
"""
Returns the elemental parameters related to atom size and
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"""
Returns the elemental parameters related to atom size and
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train | get_okeeffe_distance_prediction | Returns an estimate of the bond valence parameter (bond length) using
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Returns an estimate of the bond valence parameter (bond length) using
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and Crystals' (O'Keeffe & Brese, 1991). The estimate is based on two
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"""
Returns an estimate of the bond valence parameter (bond length) using
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train | get_neighbors_of_site_with_index | Returns the neighbors of a given site using a specific neighbor-finding
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Args:
struct (Structure): input structure.
n (int): index of site in Structure object for which motif type
is to be determined.
approach (str): type of neighbor-finding approach, where
... | pymatgen/analysis/local_env.py | def get_neighbors_of_site_with_index(struct, n, approach="min_dist", delta=0.1, \
cutoff=10.0):
"""
Returns the neighbors of a given site using a specific neighbor-finding
method.
Args:
struct (Structure): input structure.
n (int): index of site in S... | def get_neighbors_of_site_with_index(struct, n, approach="min_dist", delta=0.1, \
cutoff=10.0):
"""
Returns the neighbors of a given site using a specific neighbor-finding
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struct (Structure): input structure.
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train | site_is_of_motif_type | Returns the motif type of the site with index n in structure struct;
currently featuring "tetrahedral", "octahedral", "bcc", and "cp"
(close-packed: fcc and hcp) as well as "square pyramidal" and
"trigonal bipyramidal". If the site is not recognized,
"unrecognized" is returned. If a site should be ass... | pymatgen/analysis/local_env.py | def site_is_of_motif_type(struct, n, approach="min_dist", delta=0.1, \
cutoff=10.0, thresh=None):
"""
Returns the motif type of the site with index n in structure struct;
currently featuring "tetrahedral", "octahedral", "bcc", and "cp"
(close-packed: fcc and hcp) as well as "sq... | def site_is_of_motif_type(struct, n, approach="min_dist", delta=0.1, \
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"""
Returns the motif type of the site with index n in structure struct;
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train | gramschmidt | Returns that part of the first input vector
that is orthogonal to the second input vector.
The output vector is not normalized.
Args:
vin (numpy array):
first input vector
uin (numpy array):
second input vector | pymatgen/analysis/local_env.py | def gramschmidt(vin, uin):
"""
Returns that part of the first input vector
that is orthogonal to the second input vector.
The output vector is not normalized.
Args:
vin (numpy array):
first input vector
uin (numpy array):
second input vector
"""
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"""
Returns that part of the first input vector
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The output vector is not normalized.
Args:
vin (numpy array):
first input vector
uin (numpy array):
second input vector
"""
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train | calculate_weighted_avg | Returns the weighted average bond length given by
Hoppe's effective coordination number formula.
Args:
bonds (list): list of floats that are the
bond distances between a cation and its
peripheral ions | pymatgen/analysis/local_env.py | def calculate_weighted_avg(bonds):
"""
Returns the weighted average bond length given by
Hoppe's effective coordination number formula.
Args:
bonds (list): list of floats that are the
bond distances between a cation and its
peripheral ions
"""
minimum_bond = min(bonds)
... | def calculate_weighted_avg(bonds):
"""
Returns the weighted average bond length given by
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Args:
bonds (list): list of floats that are the
bond distances between a cation and its
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"""
minimum_bond = min(bonds)
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train | ValenceIonicRadiusEvaluator.radii | List of ionic radii of elements in the order of sites. | pymatgen/analysis/local_env.py | def radii(self):
"""
List of ionic radii of elements in the order of sites.
"""
el = [site.species_string for site in self._structure.sites]
radii_dict = dict(zip(el, self._ionic_radii))
# print radii_dict
return radii_dict | def radii(self):
"""
List of ionic radii of elements in the order of sites.
"""
el = [site.species_string for site in self._structure.sites]
radii_dict = dict(zip(el, self._ionic_radii))
# print radii_dict
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train | ValenceIonicRadiusEvaluator.valences | List of oxidation states of elements in the order of sites. | pymatgen/analysis/local_env.py | def valences(self):
"""
List of oxidation states of elements in the order of sites.
"""
el = [site.species_string for site in self._structure.sites]
valence_dict = dict(zip(el, self._valences))
return valence_dict | def valences(self):
"""
List of oxidation states of elements in the order of sites.
"""
el = [site.species_string for site in self._structure.sites]
valence_dict = dict(zip(el, self._valences))
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train | ValenceIonicRadiusEvaluator._get_ionic_radii | Computes ionic radii of elements for all sites in the structure.
If valence is zero, atomic radius is used. | pymatgen/analysis/local_env.py | def _get_ionic_radii(self):
"""
Computes ionic radii of elements for all sites in the structure.
If valence is zero, atomic radius is used.
"""
radii = []
vnn = VoronoiNN()
def nearest_key(sorted_vals, key):
i = bisect_left(sorted_vals, key)
... | def _get_ionic_radii(self):
"""
Computes ionic radii of elements for all sites in the structure.
If valence is zero, atomic radius is used.
"""
radii = []
vnn = VoronoiNN()
def nearest_key(sorted_vals, key):
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train | ValenceIonicRadiusEvaluator._get_valences | Computes ionic valences of elements for all sites in the structure. | pymatgen/analysis/local_env.py | def _get_valences(self):
"""
Computes ionic valences of elements for all sites in the structure.
"""
try:
bv = BVAnalyzer()
self._structure = bv.get_oxi_state_decorated_structure(
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valences = bv.get_valences(self._struct... | def _get_valences(self):
"""
Computes ionic valences of elements for all sites in the structure.
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self._structure = bv.get_oxi_state_decorated_structure(
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train | NearNeighbors.get_cn | Get coordination number, CN, of site with index n in structure.
Args:
structure (Structure): input structure.
n (integer): index of site for which to determine CN.
use_weights (boolean): flag indicating whether (True)
to use weights for computing the coordina... | pymatgen/analysis/local_env.py | def get_cn(self, structure, n, use_weights=False):
"""
Get coordination number, CN, of site with index n in structure.
Args:
structure (Structure): input structure.
n (integer): index of site for which to determine CN.
use_weights (boolean): flag indicating w... | def get_cn(self, structure, n, use_weights=False):
"""
Get coordination number, CN, of site with index n in structure.
Args:
structure (Structure): input structure.
n (integer): index of site for which to determine CN.
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train | NearNeighbors.get_cn_dict | Get coordination number, CN, of each element bonded to site with index n in structure
Args:
structure (Structure): input structure
n (integer): index of site for which to determine CN.
use_weights (boolean): flag indicating whether (True)
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"""
Get coordination number, CN, of each element bonded to site with index n in structure
Args:
structure (Structure): input structure
n (integer): index of site for which to determine CN.
use_weights (b... | def get_cn_dict(self, structure, n, use_weights=False):
"""
Get coordination number, CN, of each element bonded to site with index n in structure
Args:
structure (Structure): input structure
n (integer): index of site for which to determine CN.
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train | NearNeighbors.get_nn | Get near neighbors of site with index n in structure.
Args:
structure (Structure): input structure.
n (integer): index of site in structure for which to determine
neighbors.
Returns:
sites (list of Site objects): near neighbors. | pymatgen/analysis/local_env.py | def get_nn(self, structure, n):
"""
Get near neighbors of site with index n in structure.
Args:
structure (Structure): input structure.
n (integer): index of site in structure for which to determine
neighbors.
Returns:
sites (list ... | def get_nn(self, structure, n):
"""
Get near neighbors of site with index n in structure.
Args:
structure (Structure): input structure.
n (integer): index of site in structure for which to determine
neighbors.
Returns:
sites (list ... | [
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train | NearNeighbors.get_weights_of_nn_sites | Get weight associated with each near neighbor of site with
index n in structure.
Args:
structure (Structure): input structure.
n (integer): index of site for which to determine the weights.
Returns:
weights (list of floats): near-neighbor weights. | pymatgen/analysis/local_env.py | def get_weights_of_nn_sites(self, structure, n):
"""
Get weight associated with each near neighbor of site with
index n in structure.
Args:
structure (Structure): input structure.
n (integer): index of site for which to determine the weights.
Returns:
... | def get_weights_of_nn_sites(self, structure, n):
"""
Get weight associated with each near neighbor of site with
index n in structure.
Args:
structure (Structure): input structure.
n (integer): index of site for which to determine the weights.
Returns:
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train | NearNeighbors.get_nn_images | Get image location of all near neighbors of site with index n in
structure.
Args:
structure (Structure): input structure.
n (integer): index of site for which to determine the image
location of near neighbors.
Returns:
images (list of 3D integ... | pymatgen/analysis/local_env.py | def get_nn_images(self, structure, n):
"""
Get image location of all near neighbors of site with index n in
structure.
Args:
structure (Structure): input structure.
n (integer): index of site for which to determine the image
location of near neigh... | def get_nn_images(self, structure, n):
"""
Get image location of all near neighbors of site with index n in
structure.
Args:
structure (Structure): input structure.
n (integer): index of site for which to determine the image
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train | NearNeighbors.get_all_nn_info | Get a listing of all neighbors for all sites in a structure
Args:
structure (Structure): Input structure
Return:
List of NN site information for each site in the structure. Each
entry has the same format as `get_nn_info` | pymatgen/analysis/local_env.py | def get_all_nn_info(self, structure):
"""Get a listing of all neighbors for all sites in a structure
Args:
structure (Structure): Input structure
Return:
List of NN site information for each site in the structure. Each
entry has the same format as `get_nn... | def get_all_nn_info(self, structure):
"""Get a listing of all neighbors for all sites in a structure
Args:
structure (Structure): Input structure
Return:
List of NN site information for each site in the structure. Each
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train | NearNeighbors.get_nn_shell_info | Get a certain nearest neighbor shell for a certain site.
Determines all non-backtracking paths through the neighbor network
computed by `get_nn_info`. The weight is determined by multiplying
the weight of the neighbor at each hop through the network. For
example, a 2nd-nearest-neighbor ... | pymatgen/analysis/local_env.py | def get_nn_shell_info(self, structure, site_idx, shell):
"""Get a certain nearest neighbor shell for a certain site.
Determines all non-backtracking paths through the neighbor network
computed by `get_nn_info`. The weight is determined by multiplying
the weight of the neighbor at each h... | def get_nn_shell_info(self, structure, site_idx, shell):
"""Get a certain nearest neighbor shell for a certain site.
Determines all non-backtracking paths through the neighbor network
computed by `get_nn_info`. The weight is determined by multiplying
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train | NearNeighbors._get_nn_shell_info | Private method for computing the neighbor shell information
Args:
structure (Structure) - Structure being assessed
all_nn_info ([[dict]]) - Results from `get_all_nn_info`
site_idx (int) - index of site for which to determine neighbor
information.
... | pymatgen/analysis/local_env.py | def _get_nn_shell_info(self, structure, all_nn_info, site_idx, shell,
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"""Private method for computing the neighbor shell information
Args:
structure (Structure) - Structure being assessed
all_nn_info ... | def _get_nn_shell_info(self, structure, all_nn_info, site_idx, shell,
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"""Private method for computing the neighbor shell information
Args:
structure (Structure) - Structure being assessed
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train | NearNeighbors._get_image | Private convenience method for get_nn_info,
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Image is defined as displacement from original site in structure to a given site.
i.e. if structure has a site at (-0.1, 1.0, 0.3), then (0.9, 0, 2.3) -> jimage = (1, -1, 2).
Note t... | pymatgen/analysis/local_env.py | def _get_image(structure, site):
"""Private convenience method for get_nn_info,
gives lattice image from provided PeriodicSite and Structure.
Image is defined as displacement from original site in structure to a given site.
i.e. if structure has a site at (-0.1, 1.0, 0.3), then (0.9, 0,... | def _get_image(structure, site):
"""Private convenience method for get_nn_info,
gives lattice image from provided PeriodicSite and Structure.
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train | NearNeighbors._get_original_site | Private convenience method for get_nn_info,
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train | NearNeighbors.get_bonded_structure | Obtain a StructureGraph object using this NearNeighbor
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train | NearNeighbors.get_local_order_parameters | Calculate those local structure order parameters for
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train | VoronoiNN.get_voronoi_polyhedra | Gives a weighted polyhedra around a site.
See ref: A Proposed Rigorous Definition of Coordination Number,
M. O'Keeffe, Acta Cryst. (1979). A35, 772-775
Args:
structure (Structure): structure for which to evaluate the
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See ref: A Proposed Rigorous Definition of Coordination Number,
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structure (Structure): structure for which to evaluate th... | def get_voronoi_polyhedra(self, structure, n):
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train | VoronoiNN.get_all_voronoi_polyhedra | Get the Voronoi polyhedra for all site in a simulation cell
Args:
structure (Structure): Structure to be evaluated
Returns:
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"""Get the Voronoi polyhedra for all site in a simulation cell
Args:
structure (Structure): Structure to be evaluated
Returns:
A dict of sites sharing a common Voronoi facet with the site
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structure (Structure): Structure to be evaluated
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train | VoronoiNN._get_elements | Get the list of elements for a Site
Args:
site (Site): Site to assess
Returns:
[Element]: List of elements | pymatgen/analysis/local_env.py | def _get_elements(self, site):
"""
Get the list of elements for a Site
Args:
site (Site): Site to assess
Returns:
[Element]: List of elements
"""
try:
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Get the list of elements for a Site
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train | VoronoiNN._is_in_targets | Test whether a site contains elements in the target list
Args:
site (Site): Site to assess
targets ([Element]) List of elements
Returns:
(boolean) Whether this site contains a certain list of elements | pymatgen/analysis/local_env.py | def _is_in_targets(self, site, targets):
"""
Test whether a site contains elements in the target list
Args:
site (Site): Site to assess
targets ([Element]) List of elements
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site (Site): Site to assess
targets ([Element]) List of elements
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train | VoronoiNN._extract_cell_info | Get the information about a certain atom from the results of a tessellation
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structure (Structure) - Structure being assessed
site_idx (int) - Index of the atom in question
sites ([Site]) - List of all sites in the tessellation
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train | VoronoiNN.get_nn_info | Get all near-neighbor sites as well as the associated image locations
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Args:
structure (Structure): input structure.
n (integer): index of site for which to determine near-neighbor
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Get all near-neighbor sites as well as the associated image locations
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structure (Structure): input structure.
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Get all near-neighbor sites as well as the associated image locations
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structure (Structure): input structure.
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train | VoronoiNN._extract_nn_info | Given Voronoi NNs, extract the NN info in the form needed by NearestNeighbors
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structure (Structure): Structure being evaluated
nns ([dicts]): Nearest neighbor information for a structure
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structure (Structure): Structure being evaluated
nns ([dicts]): Nearest neighbor information for a structure
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train | JmolNN.get_max_bond_distance | Use Jmol algorithm to determine bond length from atomic parameters
Args:
el1_sym: (str) symbol of atom 1
el2_sym: (str) symbol of atom 2
Returns: (float) max bond length | pymatgen/analysis/local_env.py | def get_max_bond_distance(self, el1_sym, el2_sym):
"""
Use Jmol algorithm to determine bond length from atomic parameters
Args:
el1_sym: (str) symbol of atom 1
el2_sym: (str) symbol of atom 2
Returns: (float) max bond length
"""
return sqrt(
... | def get_max_bond_distance(self, el1_sym, el2_sym):
"""
Use Jmol algorithm to determine bond length from atomic parameters
Args:
el1_sym: (str) symbol of atom 1
el2_sym: (str) symbol of atom 2
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train | JmolNN.get_nn_info | Get all near-neighbor sites as well as the associated image locations
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Args:
structure (Structure): input structure.
n (integer): index of site for which to determine near
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Get all near-neighbor sites as well as the associated image locations
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structure (Structure): input structure.
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Get all near-neighbor sites as well as the associated image locations
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train | MinimumDistanceNN.get_nn_info | Get all near-neighbor sites as well as the associated image locations
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Args:
structure (Structure): input structure.
n (integer): index of site for which to determine near
... | pymatgen/analysis/local_env.py | def get_nn_info(self, structure, n):
"""
Get all near-neighbor sites as well as the associated image locations
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Get all near-neighbor sites as well as the associated image locations
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train | OpenBabelNN.get_nn_info | Get all near-neighbor sites and weights (orders) of bonds for a given
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train | OpenBabelNN.get_nn_shell_info | Get a certain nearest neighbor shell for a certain site.
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train | CovalentBondNN.get_nn_info | Get all near-neighbor sites and weights (orders) of bonds for a given
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:param n: index of site for which to determine near neighbors.
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train | MinimumOKeeffeNN.get_nn_info | Get all near-neighbor sites as well as the associated image locations
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structure (Structure): input structure.
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Get all near-neighbor sites as well as the associated image locations
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train | MinimumVIRENN.get_nn_info | Get all near-neighbor sites as well as the associated image locations
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Args:
structure (Structure): input structure.
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train | LocalStructOrderParams.compute_trigonometric_terms | Computes trigonometric terms that are required to
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Args:
thetas ([float]): polar angles of all neighbors in radians.
phis ([float]): azimuth angles of all neighbors in radians.
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Computes trigonometric terms that are required to
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Args:
thetas ([float]): polar angles of all neighbors in radians.
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Computes trigonometric terms that are required to
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train | LocalStructOrderParams.get_q2 | Calculates the value of the bond orientational order parameter of
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polar and azimuthal angles the corresponding trigonometric terms
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compute_trigonometric_terms function ... | pymatgen/analysis/local_env.py | def get_q2(self, thetas=None, phis=None):
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train | LocalStructOrderParams.get_q4 | Calculates the value of the bond orientational order parameter of
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compute_trigonometric_terms function ... | pymatgen/analysis/local_env.py | def get_q4(self, thetas=None, phis=None):
"""
Calculates the value of the bond orientational order parameter of
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Calculates the value of the bond orientational order parameter of
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train | LocalStructOrderParams.get_q6 | Calculates the value of the bond orientational order parameter of
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compute_trigonometric_terms function ... | pymatgen/analysis/local_env.py | def get_q6(self, thetas=None, phis=None):
"""
Calculates the value of the bond orientational order parameter of
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train | LocalStructOrderParams.get_type | Return type of order parameter at the index provided and
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Args:
index (int): index of order parameter for which type is
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Returns:
str: OP type. | pymatgen/analysis/local_env.py | def get_type(self, index):
"""
Return type of order parameter at the index provided and
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Args:
index (int): index of order parameter for which type is
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Returns:
str: OP type.
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Return type of order parameter at the index provided and
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index (int): index of order parameter for which type is
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train | LocalStructOrderParams.get_order_parameters | Compute all order parameters of site n.
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here, but directly access site... | pymatgen/analysis/local_env.py | def get_order_parameters(self, structure, n, indices_neighs=None, \
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"""
Compute all order parameters of site n.
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structure (Structure): input structure.
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"""
Compute all order parameters of site n.
Args:
structure (Structure): input structure.
n (int): index of site in input structure,
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train | CrystalNN.get_nn_info | Get all near-neighbor information.
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structure: (Structure) pymatgen Structure
n: (int) index of target site
Returns:
siw (list of dicts): each dictionary provides information
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ac... | pymatgen/analysis/local_env.py | def get_nn_info(self, structure, n):
"""
Get all near-neighbor information.
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structure: (Structure) pymatgen Structure
n: (int) index of target site
Returns:
siw (list of dicts): each dictionary provides information
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Get all near-neighbor information.
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structure: (Structure) pymatgen Structure
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"""
The main logic of the method to compute near neighbor.
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structure: (Structure) enclosing structure object
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structure: (Structure) enclosing structure object
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train | CrystalNN.get_cn | Get coordination number, CN, of site with index n in structure.
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structure (Structure): input structure.
n (integer): index of site for which to determine CN.
use_weights (boolean): flag indicating whether (True)
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"""
Get coordination number, CN, of site with index n in structure.
Args:
structure (Structure): input structure.
n (integer): index of site for which to determine CN.
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Get coordination number, CN, of site with index n in structure.
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structure (Structure): input structure.
n (integer): index of site for which to determine CN.
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train | CrystalNN._semicircle_integral | An internal method to get an integral between two bounds of a unit
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Args:
dist_bins: (float) list of all possible bond weights
idx: (float) index of starting bond weight
Returns:
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"""
An internal method to get an integral between two bounds of a unit
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Args:
dist_bins: (float) list of all possible bond weights
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"""
An internal method to get an integral between two bounds of a unit
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dist_bins: (float) list of all possible bond weights
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train | CrystalNN._get_default_radius | An internal method to get a "default" covalent/element radius
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site: (Site)
Returns:
Covalent radius of element on site, or Atomic radius if unavailable | pymatgen/analysis/local_env.py | def _get_default_radius(site):
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An internal method to get a "default" covalent/element radius
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site: (Site)
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Covalent radius of element on site, or Atomic radius if unavailable
"""
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An internal method to get a "default" covalent/element radius
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site: (Site)
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train | CrystalNN._get_radius | An internal method to get the expected radius for a site with
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Args:
site: (Site)
Returns:
Oxidation-state dependent radius: ionic, covalent, or atomic.
Returns 0 if no oxidation state or appropriate radius is found. | pymatgen/analysis/local_env.py | def _get_radius(site):
"""
An internal method to get the expected radius for a site with
oxidation state.
Args:
site: (Site)
Returns:
Oxidation-state dependent radius: ionic, covalent, or atomic.
Returns 0 if no oxidation state or appropriate ... | def _get_radius(site):
"""
An internal method to get the expected radius for a site with
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Args:
site: (Site)
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Oxidation-state dependent radius: ionic, covalent, or atomic.
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train | CrystalNN.transform_to_length | Given NNData, transforms data to the specified fingerprint length
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nndata: (NNData)
length: (int) desired length of NNData | pymatgen/analysis/local_env.py | def transform_to_length(nndata, length):
"""
Given NNData, transforms data to the specified fingerprint length
Args:
nndata: (NNData)
length: (int) desired length of NNData
"""
if length is None:
return nndata
if length:
f... | def transform_to_length(nndata, length):
"""
Given NNData, transforms data to the specified fingerprint length
Args:
nndata: (NNData)
length: (int) desired length of NNData
"""
if length is None:
return nndata
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train | CutOffDictNN.from_preset | Initialise a CutOffDictNN according to a preset set of cut-offs.
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preset (str): A preset name. The list of supported presets are:
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Returns:
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Initialise a CutOffDictNN according to a preset set of cut-offs.
Args:
preset (str): A preset name. The list of supported presets are:
- "vesta_2019": The distance cut-offs used by the VESTA
visualisation program.
... | def from_preset(preset):
"""
Initialise a CutOffDictNN according to a preset set of cut-offs.
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preset (str): A preset name. The list of supported presets are:
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train | Mcsqs.to_string | Returns a structure in mcsqs rndstr.in format.
:return (str): | pymatgen/io/atat.py | def to_string(self):
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train | Mcsqs.structure_from_string | Parses a rndstr.in or lat.in file into pymatgen's
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train | get_voronoi_nodes | Analyze the void space in the input structure using voronoi decomposition
Calls Zeo++ for Voronoi decomposition.
Args:
structure: pymatgen.core.structure.Structure
rad_dict (optional): Dictionary of radii of elements in structure.
If not given, Zeo++ default values are used.
... | pymatgen/io/zeopp.py | def get_voronoi_nodes(structure, rad_dict=None, probe_rad=0.1):
"""
Analyze the void space in the input structure using voronoi decomposition
Calls Zeo++ for Voronoi decomposition.
Args:
structure: pymatgen.core.structure.Structure
rad_dict (optional): Dictionary of radii of elements in... | def get_voronoi_nodes(structure, rad_dict=None, probe_rad=0.1):
"""
Analyze the void space in the input structure using voronoi decomposition
Calls Zeo++ for Voronoi decomposition.
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train | get_high_accuracy_voronoi_nodes | Analyze the void space in the input structure using high accuracy
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Calls Zeo++ for Voronoi decomposition.
Args:
structure: pymatgen.core.structure.Structure
rad_dict (optional): Dictionary of radii of elements in structure.
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"""
Analyze the void space in the input structure using high accuracy
voronoi decomposition.
Calls Zeo++ for Voronoi decomposition.
Args:
structure: pymatgen.core.structure.Structure
rad_dict (optional): Dictio... | def get_high_accuracy_voronoi_nodes(structure, rad_dict, probe_rad=0.1):
"""
Analyze the void space in the input structure using high accuracy
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Calls Zeo++ for Voronoi decomposition.
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structure: pymatgen.core.structure.Structure
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train | get_free_sphere_params | Analyze the void space in the input structure using voronoi decomposition
Calls Zeo++ for Voronoi decomposition.
Args:
structure: pymatgen.core.structure.Structure
rad_dict (optional): Dictionary of radii of elements in structure.
If not given, Zeo++ default values are used.
... | pymatgen/io/zeopp.py | def get_free_sphere_params(structure, rad_dict=None, probe_rad=0.1):
"""
Analyze the void space in the input structure using voronoi decomposition
Calls Zeo++ for Voronoi decomposition.
Args:
structure: pymatgen.core.structure.Structure
rad_dict (optional): Dictionary of radii of elemen... | def get_free_sphere_params(structure, rad_dict=None, probe_rad=0.1):
"""
Analyze the void space in the input structure using voronoi decomposition
Calls Zeo++ for Voronoi decomposition.
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train | get_void_volume_surfarea | Computes the volume and surface area of isolated void using Zeo++.
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Args:
structure: pymatgen Structure containing vacancy
rad_dict(optional): Dictionary with short name of elements and their
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"""
Computes the volume and surface area of isolated void using Zeo++.
Useful to compute the volume and surface area of vacant site.
Args:
structure: pymatgen Structure containing v... | def get_void_volume_surfarea(structure, rad_dict=None, chan_rad=0.3,
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Computes the volume and surface area of isolated void using Zeo++.
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train | ZeoCssr.from_string | Reads a string representation to a ZeoCssr object.
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string: A string representation of a ZeoCSSR.
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Reads a string representation to a ZeoCssr object.
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string: A string representation of a ZeoCSSR.
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train | ZeoVoronoiXYZ.from_string | Creates Zeo++ Voronoi XYZ object from a string.
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contents: String representing Zeo++ Voronoi XYZ file.
Returns:
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Creates Zeo++ Voronoi XYZ object from a string.
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contents: String representing Zeo++ Voronoi XYZ file.
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train | QcTask.set_velocities | :param velocities (au): list of list of atom velocities
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Set the maxium allowed memory.
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total: The total memory. Integer. Unit: MBytes. If set to None,
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static: The static memory. Integer. Unit MBytes. If set to None,
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Set the maxium allowed memory.
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total: The total memory. Integer. Unit: MBytes. If set to None,
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train | QcTask.set_scf_algorithm_and_iterations | Set algorithm used for converging SCF and max number of SCF iterations.
Args:
algorithm: The algorithm used for converging SCF. (str)
iterations: The max number of SCF iterations. (Integer) | pymatgen/io/qchem_deprecated.py | def set_scf_algorithm_and_iterations(self, algorithm="diis",
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Set algorithm used for converging SCF and max number of SCF iterations.
Args:
algorithm: The algorithm used for converging SCF. (str)
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Set algorithm used for converging SCF and max number of SCF iterations.
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algorithm: The algorithm used for converging SCF. (str)
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train | QcTask.set_dft_grid | Set the grid for DFT numerical integrations.
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radical_points: Radical points. (Integer)
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"""
Set the grid for DFT numerical integrations.
Args:
radical_points: Radical points. (Integer)
angular_points: Angular points. (Integer)
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Set the grid for DFT numerical integrations.
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train | QcTask.set_scf_initial_guess | Set initial guess method to be used for SCF
Args:
guess: The initial guess method. (str) | pymatgen/io/qchem_deprecated.py | def set_scf_initial_guess(self, guess="SAD"):
"""
Set initial guess method to be used for SCF
Args:
guess: The initial guess method. (str)
"""
availabel_guesses = {"core", "sad", "gwh", "read", "fragmo"}
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... | def set_scf_initial_guess(self, guess="SAD"):
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Set initial guess method to be used for SCF
Args:
guess: The initial guess method. (str)
"""
availabel_guesses = {"core", "sad", "gwh", "read", "fragmo"}
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train | QcTask.set_geom_opt_coords_type | Set the coordinates system used in geometry optimization.
"cartesian" --- always cartesian coordinates.
"internal" --- always internal coordinates.
"internal-switch" --- try internal coordinates first, if fails, switch
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"z-matrix" --- ... | pymatgen/io/qchem_deprecated.py | def set_geom_opt_coords_type(self, coords_type="internal_switch"):
"""
Set the coordinates system used in geometry optimization.
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"internal" --- always internal coordinates.
"internal-switch" --- try internal coordinates f... | def set_geom_opt_coords_type(self, coords_type="internal_switch"):
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Set the coordinates system used in geometry optimization.
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train | QcTask.scale_geom_opt_threshold | Adjust the convergence criteria of geometry optimization.
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gradient: the scale factor for gradient criteria. If less than
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300 × 10E−6
displacement: the scale factor for atomic displacement. If ... | pymatgen/io/qchem_deprecated.py | def scale_geom_opt_threshold(self, gradient=0.1, displacement=0.1,
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"""
Adjust the convergence criteria of geometry optimization.
Args:
gradient: the scale factor for gradient criteria. If less than
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Adjust the convergence criteria of geometry optimization.
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train | QcTask.use_pcm | Set the solvent model to PCM. Default parameters are trying to comply to
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Args:
pcm_params (dict): The parameters of "$pcm" section.
solvent_key (str): for versions < 4.2 the section name is "pcm_solvent"
solvent_params (dict): The parameters of... | pymatgen/io/qchem_deprecated.py | def use_pcm(self, pcm_params=None, solvent_key="solvent", solvent_params=None,
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"""
Set the solvent model to PCM. Default parameters are trying to comply to
gaussian default value
Args:
pcm_params (dict): The parameters of "$pcm" secti... | def use_pcm(self, pcm_params=None, solvent_key="solvent", solvent_params=None,
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Set the solvent model to PCM. Default parameters are trying to comply to
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train | QcTask.from_string | Creates QcInput from a string.
Args:
contents: String representing a QChem input file.
Returns:
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"""
Creates QcInput from a string.
Args:
contents: String representing a QChem input file.
Returns:
QcInput object
"""
mol = None
charge = None
spin_multiplicity = None
params = dict()
... | def from_string(cls, contents):
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Creates QcInput from a string.
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contents: String representing a QChem input file.
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QcInput object
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mol = None
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train | magnetic_deformation | Calculates 'magnetic deformation proxy',
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Adapted from Bocarsly et al. 2017,
doi: 10.1021/acs.chemmater.6b04729
:param structure_A: Structure
:param structure_B: Struct... | pymatgen/analysis/magnetism/analyzer.py | def magnetic_deformation(structure_A, structure_B):
"""
Calculates 'magnetic deformation proxy',
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ferromagnetic structures.
Adapted from Bocarsly et al. 2017,
doi: 10.1021/acs.chemmater.6b04729
... | def magnetic_deformation(structure_A, structure_B):
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Calculates 'magnetic deformation proxy',
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Adapted from Bocarsly et al. 2017,
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... | 4ca558cf72f8d5f8a1f21dfdfc0181a971c186da |
train | CollinearMagneticStructureAnalyzer._round_magmoms | If round_magmoms_mode is an integer, simply round to that number
of decimal places, else if set to a float will try and round
intelligently by grouping magmoms. | pymatgen/analysis/magnetism/analyzer.py | def _round_magmoms(magmoms, round_magmoms_mode: Union[int, float]):
"""
If round_magmoms_mode is an integer, simply round to that number
of decimal places, else if set to a float will try and round
intelligently by grouping magmoms.
"""
if isinstance(round_magmoms_mode, ... | def _round_magmoms(magmoms, round_magmoms_mode: Union[int, float]):
"""
If round_magmoms_mode is an integer, simply round to that number
of decimal places, else if set to a float will try and round
intelligently by grouping magmoms.
"""
if isinstance(round_magmoms_mode, ... | [
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train | CollinearMagneticStructureAnalyzer.get_structure_with_spin | Returns a Structure with species decorated with spin values instead
of using magmom site properties.
:return: Structure | pymatgen/analysis/magnetism/analyzer.py | def get_structure_with_spin(self):
"""
Returns a Structure with species decorated with spin values instead
of using magmom site properties.
:return: Structure
"""
structure = self.structure.copy()
structure.add_spin_by_site(structure.site_properties["magmom"])
... | def get_structure_with_spin(self):
"""
Returns a Structure with species decorated with spin values instead
of using magmom site properties.
:return: Structure
"""
structure = self.structure.copy()
structure.add_spin_by_site(structure.site_properties["magmom"])
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train | CollinearMagneticStructureAnalyzer.get_structure_with_only_magnetic_atoms | Returns a Structure with only magnetic atoms present.
:return: Structure | pymatgen/analysis/magnetism/analyzer.py | def get_structure_with_only_magnetic_atoms(self, make_primitive=True):
"""
Returns a Structure with only magnetic atoms present.
:return: Structure
"""
sites = [site for site in self.structure if abs(site.properties["magmom"]) > 0]
structure = Structure.from_sites(sites... | def get_structure_with_only_magnetic_atoms(self, make_primitive=True):
"""
Returns a Structure with only magnetic atoms present.
:return: Structure
"""
sites = [site for site in self.structure if abs(site.properties["magmom"]) > 0]
structure = Structure.from_sites(sites... | [
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train | CollinearMagneticStructureAnalyzer.get_nonmagnetic_structure | Returns a Structure without magnetic moments defined.
:param make_primitive (bool): Return a primitive
structure, defaults to True.
:return: Structure | pymatgen/analysis/magnetism/analyzer.py | def get_nonmagnetic_structure(self, make_primitive=True):
"""
Returns a Structure without magnetic moments defined.
:param make_primitive (bool): Return a primitive
structure, defaults to True.
:return: Structure
"""
structure = self.structure.copy()
stru... | def get_nonmagnetic_structure(self, make_primitive=True):
"""
Returns a Structure without magnetic moments defined.
:param make_primitive (bool): Return a primitive
structure, defaults to True.
:return: Structure
"""
structure = self.structure.copy()
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train | CollinearMagneticStructureAnalyzer.get_ferromagnetic_structure | Returns a Structure with all magnetic moments positive
or zero.
:param make_primitive (bool): Return a primitive
structure, defaults to True.
:return: Structure | pymatgen/analysis/magnetism/analyzer.py | def get_ferromagnetic_structure(self, make_primitive=True):
"""
Returns a Structure with all magnetic moments positive
or zero.
:param make_primitive (bool): Return a primitive
structure, defaults to True.
:return: Structure
"""
structure = self.structure... | def get_ferromagnetic_structure(self, make_primitive=True):
"""
Returns a Structure with all magnetic moments positive
or zero.
:param make_primitive (bool): Return a primitive
structure, defaults to True.
:return: Structure
"""
structure = self.structure... | [
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train | CollinearMagneticStructureAnalyzer.magnetic_species_and_magmoms | Returns a dict of magnetic species and the magnitude of
their associated magmoms. Will return a set if there are
multiple magmoms per species.
:return: dict of magnetic species and magmoms | pymatgen/analysis/magnetism/analyzer.py | def magnetic_species_and_magmoms(self):
"""
Returns a dict of magnetic species and the magnitude of
their associated magmoms. Will return a set if there are
multiple magmoms per species.
:return: dict of magnetic species and magmoms
"""
structure = self.get_ferr... | def magnetic_species_and_magmoms(self):
"""
Returns a dict of magnetic species and the magnitude of
their associated magmoms. Will return a set if there are
multiple magmoms per species.
:return: dict of magnetic species and magmoms
"""
structure = self.get_ferr... | [
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train | CollinearMagneticStructureAnalyzer.number_of_unique_magnetic_sites | :param symprec (float): same as in SpacegroupAnalyzer
:param angle_tolerance (float): same as in SpacegroupAnalyzer
:return (int): Number of symmetrically-distinct magnetic sites present
in structure. | pymatgen/analysis/magnetism/analyzer.py | def number_of_unique_magnetic_sites(self, symprec=1e-3, angle_tolerance=5):
"""
:param symprec (float): same as in SpacegroupAnalyzer
:param angle_tolerance (float): same as in SpacegroupAnalyzer
:return (int): Number of symmetrically-distinct magnetic sites present
in structure.... | def number_of_unique_magnetic_sites(self, symprec=1e-3, angle_tolerance=5):
"""
:param symprec (float): same as in SpacegroupAnalyzer
:param angle_tolerance (float): same as in SpacegroupAnalyzer
:return (int): Number of symmetrically-distinct magnetic sites present
in structure.... | [
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