pymatgen.transformations.standard_transformations module¶

class
AutoOxiStateDecorationTransformation
(symm_tol=0.1, max_radius=4, max_permutations=100000, distance_scale_factor=1.015)[source]¶ Bases:
pymatgen.transformations.transformation_abc.AbstractTransformation
This transformation automatically decorates a structure with oxidation states using a bond valence approach.
Parameters:  symm_tol (float) – Symmetry tolerance used to determine which sites are symmetrically equivalent. Set to 0 to turn off symmetry.
 max_radius (float) – Maximum radius in Angstrom used to find nearest neighbors.
 max_permutations (int) – Maximum number of permutations of oxidation states to test.
 distance_scale_factor (float) – A scale factor to be applied. This is useful for scaling distances, esp in the case of calculationrelaxed structures, which may tend to under (GGA) or over bind (LDA). The default of 1.015 works for GGA. For experimental structure, set this to 1.

apply_transformation
(structure)[source]¶ Applies the transformation to a structure. Depending on whether a transformation is onetomany, there may be an option to return a ranked list of structures.
Parameters:  structure – input structure
 return_ranked_list – Boolean stating whether or not multiple structures are returned. If return_ranked_list is a number, that number of structures is returned.
Returns: depending on returned_ranked list, either a transformed structure or a list of dictionaries, where each dictionary is of the form {‘structure’ = …. , ‘other_arguments’} the key ‘transformation’ is reserved for the transformation that was actually applied to the structure. This transformation is parsed by the alchemy classes for generating a more specific transformation history. Any other information will be stored in the transformation_parameters dictionary in the transmuted structure class.

inverse
¶ Returns the inverse transformation if available. Otherwise, should return None.

is_one_to_many
¶ Determines if a Transformation is a onetomany transformation. If a Transformation is a onetomany transformation, the apply_transformation method should have a keyword arg “return_ranked_list” which allows for the transformed structures to be returned as a ranked list.

class
ChargedCellTransformation
(charge=0)[source]¶ Bases:
pymatgen.transformations.transformation_abc.AbstractTransformation
The ChargedCellTransformation applies a charge to a structure (or defect object).
Parameters: charge – A integer charge to apply to the structure. Defaults to zero. Has to be a single integer. e.g. 2 
apply_transformation
(structure)[source]¶ Applies the transformation to a structure. Depending on whether a transformation is onetomany, there may be an option to return a ranked list of structures.
Parameters:  structure – input structure
 return_ranked_list – Boolean stating whether or not multiple structures are returned. If return_ranked_list is a number, that number of structures is returned.
Returns: depending on returned_ranked list, either a transformed structure or a list of dictionaries, where each dictionary is of the form {‘structure’ = …. , ‘other_arguments’} the key ‘transformation’ is reserved for the transformation that was actually applied to the structure. This transformation is parsed by the alchemy classes for generating a more specific transformation history. Any other information will be stored in the transformation_parameters dictionary in the transmuted structure class.

inverse
¶ Returns the inverse transformation if available. Otherwise, should return None.

is_one_to_many
¶ Determines if a Transformation is a onetomany transformation. If a Transformation is a onetomany transformation, the apply_transformation method should have a keyword arg “return_ranked_list” which allows for the transformed structures to be returned as a ranked list.


class
DeformStructureTransformation
(deformation=((1, 0, 0), (0, 1, 0), (0, 0, 1)))[source]¶ Bases:
pymatgen.transformations.transformation_abc.AbstractTransformation
This transformation deforms a structure by a deformation gradient matrix
Parameters: deformation (array) – deformation gradient for the transformation 
apply_transformation
(structure)[source]¶ Applies the transformation to a structure. Depending on whether a transformation is onetomany, there may be an option to return a ranked list of structures.
Parameters:  structure – input structure
 return_ranked_list – Boolean stating whether or not multiple structures are returned. If return_ranked_list is a number, that number of structures is returned.
Returns: depending on returned_ranked list, either a transformed structure or a list of dictionaries, where each dictionary is of the form {‘structure’ = …. , ‘other_arguments’} the key ‘transformation’ is reserved for the transformation that was actually applied to the structure. This transformation is parsed by the alchemy classes for generating a more specific transformation history. Any other information will be stored in the transformation_parameters dictionary in the transmuted structure class.

inverse
¶ Returns the inverse transformation if available. Otherwise, should return None.

is_one_to_many
¶ Determines if a Transformation is a onetomany transformation. If a Transformation is a onetomany transformation, the apply_transformation method should have a keyword arg “return_ranked_list” which allows for the transformed structures to be returned as a ranked list.


class
DiscretizeOccupanciesTransformation
(max_denominator=5, tol=None, fix_denominator=False)[source]¶ Bases:
pymatgen.transformations.transformation_abc.AbstractTransformation
Discretizes the site occupancies in a disordered structure; useful for grouping similar structures or as a preprocessing step for orderdisorder transformations.
Parameters:  max_denominator – An integer maximum denominator for discretization. A higher denominator allows for finer resolution in the site occupancies.
 tol – A float that sets the maximum difference between the original and discretized occupancies before throwing an error. If None, it is set to 1 / (4 * max_denominator).
 fix_denominator (bool) – If True, will enforce a common denominator for all species. This prevents a mix of denominators (for example, 1/3, 1/4) that might require large cell sizes to perform an enumeration. ‘tol’ needs to be > 1.0 in some cases.

apply_transformation
(structure)[source]¶ Discretizes the site occupancies in the structure.
Parameters: structure – disordered Structure to discretize occupancies Returns: A new disordered Structure with occupancies discretized

inverse
¶ Returns the inverse transformation if available. Otherwise, should return None.

is_one_to_many
¶ Determines if a Transformation is a onetomany transformation. If a Transformation is a onetomany transformation, the apply_transformation method should have a keyword arg “return_ranked_list” which allows for the transformed structures to be returned as a ranked list.

class
OrderDisorderedStructureTransformation
(algo=0, symmetrized_structures=False, no_oxi_states=False)[source]¶ Bases:
pymatgen.transformations.transformation_abc.AbstractTransformation
Order a disordered structure. The disordered structure must be oxidation state decorated for ewald sum to be computed. No attempt is made to perform symmetry determination to reduce the number of combinations.
Hence, attempting to performing ordering on a large number of disordered sites may be extremely expensive. The time scales approximately with the number of possible combinations. The algorithm can currently compute approximately 5,000,000 permutations per minute.
Also, simple rounding of the occupancies are performed, with no attempt made to achieve a target composition. This is usually not a problem for most ordering problems, but there can be times where rounding errors may result in structures that do not have the desired composition. This second step will be implemented in the next iteration of the code.
If multiple fractions for a single species are found for different sites, these will be treated separately if the difference is above a threshold tolerance. currently this is .1
For example, if a fraction of .25 Li is on sites 0,1,2,3 and .5 on sites 4, 5, 6, 7 then 1 site from [0,1,2,3] will be filled and 2 sites from [4,5,6,7] will be filled, even though a lower energy combination might be found by putting all lithium in sites [4,5,6,7].
USE WITH CARE.
Parameters:  algo (int) – Algorithm to use.
 symmetrized_structures (bool) – Whether the input structures are instances of SymmetrizedStructure, and that their symmetry should be used for the grouping of sites.
 no_oxi_states (bool) – Whether to remove oxidation states prior to ordering.

ALGO_BEST_FIRST
= 2¶

ALGO_COMPLETE
= 1¶

ALGO_FAST
= 0¶

apply_transformation
(structure, return_ranked_list=False)[source]¶ For this transformation, the apply_transformation method will return only the ordered structure with the lowest Ewald energy, to be consistent with the method signature of the other transformations. However, all structures are stored in the all_structures attribute in the transformation object for easy access.
Parameters:  structure – Oxidation state decorated disordered structure to order
 return_ranked_list (bool) – Whether or not multiple structures are returned. If return_ranked_list is a number, that number of structures is returned.
Returns: Depending on returned_ranked list, either a transformed structure or a list of dictionaries, where each dictionary is of the form {“structure” = …. , “other_arguments”} the key “transformation” is reserved for the transformation that was actually applied to the structure. This transformation is parsed by the alchemy classes for generating a more specific transformation history. Any other information will be stored in the transformation_parameters dictionary in the transmuted structure class.

inverse
¶ Returns the inverse transformation if available. Otherwise, should return None.

is_one_to_many
¶ Determines if a Transformation is a onetomany transformation. If a Transformation is a onetomany transformation, the apply_transformation method should have a keyword arg “return_ranked_list” which allows for the transformed structures to be returned as a ranked list.

lowest_energy_structure
¶

class
OxidationStateDecorationTransformation
(oxidation_states)[source]¶ Bases:
pymatgen.transformations.transformation_abc.AbstractTransformation
This transformation decorates a structure with oxidation states.
Parameters:  oxidation_states (dict) – Oxidation states supplied as a dict,
 {"Li" (e.g.,) – 1, “O”:2}

apply_transformation
(structure)[source]¶ Applies the transformation to a structure. Depending on whether a transformation is onetomany, there may be an option to return a ranked list of structures.
Parameters:  structure – input structure
 return_ranked_list – Boolean stating whether or not multiple structures are returned. If return_ranked_list is a number, that number of structures is returned.
Returns: depending on returned_ranked list, either a transformed structure or a list of dictionaries, where each dictionary is of the form {‘structure’ = …. , ‘other_arguments’} the key ‘transformation’ is reserved for the transformation that was actually applied to the structure. This transformation is parsed by the alchemy classes for generating a more specific transformation history. Any other information will be stored in the transformation_parameters dictionary in the transmuted structure class.

inverse
¶ Returns the inverse transformation if available. Otherwise, should return None.

is_one_to_many
¶ Determines if a Transformation is a onetomany transformation. If a Transformation is a onetomany transformation, the apply_transformation method should have a keyword arg “return_ranked_list” which allows for the transformed structures to be returned as a ranked list.

class
OxidationStateRemovalTransformation
[source]¶ Bases:
pymatgen.transformations.transformation_abc.AbstractTransformation
This transformation removes oxidation states from a structure.

apply_transformation
(structure)[source]¶ Applies the transformation to a structure. Depending on whether a transformation is onetomany, there may be an option to return a ranked list of structures.
Parameters:  structure – input structure
 return_ranked_list – Boolean stating whether or not multiple structures are returned. If return_ranked_list is a number, that number of structures is returned.
Returns: depending on returned_ranked list, either a transformed structure or a list of dictionaries, where each dictionary is of the form {‘structure’ = …. , ‘other_arguments’} the key ‘transformation’ is reserved for the transformation that was actually applied to the structure. This transformation is parsed by the alchemy classes for generating a more specific transformation history. Any other information will be stored in the transformation_parameters dictionary in the transmuted structure class.

inverse
¶ Returns the inverse transformation if available. Otherwise, should return None.

is_one_to_many
¶ Determines if a Transformation is a onetomany transformation. If a Transformation is a onetomany transformation, the apply_transformation method should have a keyword arg “return_ranked_list” which allows for the transformed structures to be returned as a ranked list.


class
PartialRemoveSpecieTransformation
(specie_to_remove, fraction_to_remove, algo=0)[source]¶ Bases:
pymatgen.transformations.transformation_abc.AbstractTransformation
Remove fraction of specie from a structure.
Requires an oxidation state decorated structure for ewald sum to be computed.
Given that the solution to selecting the right removals is NPhard, there are several algorithms provided with varying degrees of accuracy and speed. Please see
pymatgen.transformations.site_transformations.PartialRemoveSitesTransformation
.Parameters:  specie_to_remove – Specie to remove. Must have oxidation state E.g., “Li+”
 fraction_to_remove – Fraction of specie to remove. E.g., 0.5
 algo – This parameter allows you to choose the algorithm to perform ordering. Use one of PartialRemoveSpecieTransformation.ALGO_* variables to set the algo.

ALGO_BEST_FIRST
= 2¶

ALGO_COMPLETE
= 1¶

ALGO_ENUMERATE
= 3¶

ALGO_FAST
= 0¶

apply_transformation
(structure, return_ranked_list=False)[source]¶ Apply the transformation.
Parameters:  structure – input structure
 return_ranked_list (bool/int) – Boolean stating whether or not multiple structures are returned. If return_ranked_list is an int, that number of structures is returned.
Returns: Depending on returned_ranked list, either a transformed structure or a list of dictionaries, where each dictionary is of the form {“structure” = …. , “other_arguments”} the key “transformation” is reserved for the transformation that was actually applied to the structure. This transformation is parsed by the alchemy classes for generating a more specific transformation history. Any other information will be stored in the transformation_parameters dictionary in the transmuted structure class.

inverse
¶ Returns the inverse transformation if available. Otherwise, should return None.

is_one_to_many
¶ Determines if a Transformation is a onetomany transformation. If a Transformation is a onetomany transformation, the apply_transformation method should have a keyword arg “return_ranked_list” which allows for the transformed structures to be returned as a ranked list.

class
PerturbStructureTransformation
(amplitude=0.01)[source]¶ Bases:
pymatgen.transformations.transformation_abc.AbstractTransformation
This transformation perturbs a structure by a specified distance in random directions. Used for breaking symmetries.
Parameters: amplitude (float) – Amplitude of perturbation in angstroms. All sites will be perturbed by exactly that amplitude in a random direction. 
apply_transformation
(structure)[source]¶ Applies the transformation to a structure. Depending on whether a transformation is onetomany, there may be an option to return a ranked list of structures.
Parameters:  structure – input structure
 return_ranked_list – Boolean stating whether or not multiple structures are returned. If return_ranked_list is a number, that number of structures is returned.
Returns: depending on returned_ranked list, either a transformed structure or a list of dictionaries, where each dictionary is of the form {‘structure’ = …. , ‘other_arguments’} the key ‘transformation’ is reserved for the transformation that was actually applied to the structure. This transformation is parsed by the alchemy classes for generating a more specific transformation history. Any other information will be stored in the transformation_parameters dictionary in the transmuted structure class.

inverse
¶ Returns the inverse transformation if available. Otherwise, should return None.

is_one_to_many
¶ Determines if a Transformation is a onetomany transformation. If a Transformation is a onetomany transformation, the apply_transformation method should have a keyword arg “return_ranked_list” which allows for the transformed structures to be returned as a ranked list.


class
PrimitiveCellTransformation
(tolerance=0.5)[source]¶ Bases:
pymatgen.transformations.transformation_abc.AbstractTransformation
This class finds the primitive cell of the input structure. It returns a structure that is not necessarily orthogonalized Author: Will Richards
Parameters: tolerance (float) – Tolerance for each coordinate of a particular site. For example, [0.5, 0, 0.5] in cartesian coordinates will be considered to be on the same coordinates as [0, 0, 0] for a tolerance of 0.5. Defaults to 0.5. 
apply_transformation
(structure)[source]¶ Returns most primitive cell for structure.
Parameters: structure – A structure Returns: The most primitive structure found. The returned structure is guaranteed to have len(new structure) <= len(structure).

inverse
¶ Returns the inverse transformation if available. Otherwise, should return None.

is_one_to_many
¶ Determines if a Transformation is a onetomany transformation. If a Transformation is a onetomany transformation, the apply_transformation method should have a keyword arg “return_ranked_list” which allows for the transformed structures to be returned as a ranked list.


class
RemoveSpeciesTransformation
(species_to_remove)[source]¶ Bases:
pymatgen.transformations.transformation_abc.AbstractTransformation
Remove all occurrences of some species from a structure.
Parameters: species_to_remove – List of species to remove. E.g., [“Li”, “Mn”] 
apply_transformation
(structure)[source]¶ Applies the transformation to a structure. Depending on whether a transformation is onetomany, there may be an option to return a ranked list of structures.
Parameters:  structure – input structure
 return_ranked_list – Boolean stating whether or not multiple structures are returned. If return_ranked_list is a number, that number of structures is returned.
Returns: depending on returned_ranked list, either a transformed structure or a list of dictionaries, where each dictionary is of the form {‘structure’ = …. , ‘other_arguments’} the key ‘transformation’ is reserved for the transformation that was actually applied to the structure. This transformation is parsed by the alchemy classes for generating a more specific transformation history. Any other information will be stored in the transformation_parameters dictionary in the transmuted structure class.

inverse
¶ Returns the inverse transformation if available. Otherwise, should return None.

is_one_to_many
¶ Determines if a Transformation is a onetomany transformation. If a Transformation is a onetomany transformation, the apply_transformation method should have a keyword arg “return_ranked_list” which allows for the transformed structures to be returned as a ranked list.


class
RotationTransformation
(axis, angle, angle_in_radians=False)[source]¶ Bases:
pymatgen.transformations.transformation_abc.AbstractTransformation
The RotationTransformation applies a rotation to a structure.
Parameters:  axis (3x1 array) – Axis of rotation, e.g., [1, 0, 0]
 angle (float) – Angle to rotate
 angle_in_radians (bool) – Set to True if angle is supplied in radians. Else degrees are assumed.

apply_transformation
(structure)[source]¶ Applies the transformation to a structure. Depending on whether a transformation is onetomany, there may be an option to return a ranked list of structures.
Parameters:  structure – input structure
 return_ranked_list – Boolean stating whether or not multiple structures are returned. If return_ranked_list is a number, that number of structures is returned.
Returns: depending on returned_ranked list, either a transformed structure or a list of dictionaries, where each dictionary is of the form {‘structure’ = …. , ‘other_arguments’} the key ‘transformation’ is reserved for the transformation that was actually applied to the structure. This transformation is parsed by the alchemy classes for generating a more specific transformation history. Any other information will be stored in the transformation_parameters dictionary in the transmuted structure class.

inverse
¶ Returns the inverse transformation if available. Otherwise, should return None.

is_one_to_many
¶ Determines if a Transformation is a onetomany transformation. If a Transformation is a onetomany transformation, the apply_transformation method should have a keyword arg “return_ranked_list” which allows for the transformed structures to be returned as a ranked list.

class
SubstitutionTransformation
(species_map)[source]¶ Bases:
pymatgen.transformations.transformation_abc.AbstractTransformation
This transformation substitutes species for one another.
Parameters: species_map – A dict or list of tuples containing the species mapping in stringstring pairs. E.g., {“Li”:”Na”} or [(“Fe2+”,”Mn2+”)]. Multiple substitutions can be done. Overloaded to accept sp_and_occu dictionary E.g. {“Si: {“Ge”:0.75, “C”:0.25}}, which substitutes a single species with multiple species to generate a disordered structure. 
apply_transformation
(structure)[source]¶ Applies the transformation to a structure. Depending on whether a transformation is onetomany, there may be an option to return a ranked list of structures.
Parameters:  structure – input structure
 return_ranked_list – Boolean stating whether or not multiple structures are returned. If return_ranked_list is a number, that number of structures is returned.
Returns: depending on returned_ranked list, either a transformed structure or a list of dictionaries, where each dictionary is of the form {‘structure’ = …. , ‘other_arguments’} the key ‘transformation’ is reserved for the transformation that was actually applied to the structure. This transformation is parsed by the alchemy classes for generating a more specific transformation history. Any other information will be stored in the transformation_parameters dictionary in the transmuted structure class.

inverse
¶ Returns the inverse transformation if available. Otherwise, should return None.

is_one_to_many
¶ Determines if a Transformation is a onetomany transformation. If a Transformation is a onetomany transformation, the apply_transformation method should have a keyword arg “return_ranked_list” which allows for the transformed structures to be returned as a ranked list.


class
SupercellTransformation
(scaling_matrix=((1, 0, 0), (0, 1, 0), (0, 0, 1)))[source]¶ Bases:
pymatgen.transformations.transformation_abc.AbstractTransformation
The RotationTransformation applies a rotation to a structure.
Parameters: scaling_matrix – A matrix of transforming the lattice vectors. Defaults to the identity matrix. Has to be all integers. e.g., [[2,1,0],[0,3,0],[0,0,1]] generates a new structure with lattice vectors a” = 2a + b, b” = 3b, c” = c where a, b, and c are the lattice vectors of the original structure. 
apply_transformation
(structure)[source]¶ Applies the transformation to a structure. Depending on whether a transformation is onetomany, there may be an option to return a ranked list of structures.
Parameters:  structure – input structure
 return_ranked_list – Boolean stating whether or not multiple structures are returned. If return_ranked_list is a number, that number of structures is returned.
Returns: depending on returned_ranked list, either a transformed structure or a list of dictionaries, where each dictionary is of the form {‘structure’ = …. , ‘other_arguments’} the key ‘transformation’ is reserved for the transformation that was actually applied to the structure. This transformation is parsed by the alchemy classes for generating a more specific transformation history. Any other information will be stored in the transformation_parameters dictionary in the transmuted structure class.

static
from_scaling_factors
(scale_a=1, scale_b=1, scale_c=1)[source]¶ Convenience method to get a SupercellTransformation from a simple series of three numbers for scaling each lattice vector. Equivalent to calling the normal with [[scale_a, 0, 0], [0, scale_b, 0], [0, 0, scale_c]]
Parameters:  scale_a – Scaling factor for lattice direction a. Defaults to 1.
 scale_b – Scaling factor for lattice direction b. Defaults to 1.
 scale_c – Scaling factor for lattice direction c. Defaults to 1.
Returns: SupercellTransformation.

inverse
¶ Returns the inverse transformation if available. Otherwise, should return None.

is_one_to_many
¶ Determines if a Transformation is a onetomany transformation. If a Transformation is a onetomany transformation, the apply_transformation method should have a keyword arg “return_ranked_list” which allows for the transformed structures to be returned as a ranked list.
