pymatgen.core.composition module

This module implements a Composition class to represent compositions, and a ChemicalPotential class to represent potentials.

class ChemicalPotential(*args, **kwargs)[source]

Bases: dict, MSONable

Class to represent set of chemical potentials. Can be: multiplied/divided by a Number multiplied by a Composition (returns an energy) added/subtracted with other ChemicalPotentials.

Parameters:

  • *args – any valid dict init arguments

  • **kwargs – any valid dict init arguments

get_energy(composition: Composition, strict: bool = True) → float[source]

Calculates the energy of a composition.

Parameters:

  • composition (Composition) – input composition

  • strict (bool) – Whether all potentials must be specified

class Composition(*args, strict: bool = False, **kwargs)[source]

Bases: Hashable, Mapping, MSONable, Stringify

Represents a Composition, which is essentially a {element:amount} mapping type. Composition is written to be immutable and hashable, unlike a standard Python dict.

Note that the key can be either an Element or a Species. Elements and Species are treated differently. i.e., a Fe2+ is not the same as a Fe3+ Species and would be put in separate keys. This differentiation is deliberate to support using Composition to determine the fraction of a particular Species.

Works almost completely like a standard python dictionary, except that __getitem__ is overridden to return 0 when an element is not found. (somewhat like a defaultdict, except it is immutable).

Also adds more convenience methods relevant to compositions, e.g., get_fraction.

It should also be noted that many Composition related functionality takes in a standard string as a convenient input. For example, even though the internal representation of a Fe2O3 composition is {Element(“Fe”): 2, Element(“O”): 3}, you can obtain the amount of Fe simply by comp[“Fe”] instead of the more verbose comp[Element(“Fe”)].

>>> comp = Composition("LiFePO4")
>>> comp.get_atomic_fraction(Element("Li"))
0.14285714285714285
>>> comp.num_atoms
7.0
>>> comp.reduced_formula
'LiFePO4'
>>> comp.formula
'Li1 Fe1 P1 O4'
>>> comp.get_wt_fraction(Element("Li"))
0.04399794666951898
>>> comp.num_atoms
7.0

Very flexible Composition construction, similar to the built-in Python dict(). Also extended to allow simple string init.

Takes any inputs supported by the Python built-in dict function.

  1. A dict of either {Element/Species: amount},

    {string symbol:amount}, or {atomic number:amount} or any mixture of these. E.g., {Element(“Li”): 2, Element(“O”): 1}, {“Li”:2, “O”:1}, {3: 2, 8: 1} all result in a Li2O composition.

  2. Keyword arg initialization, similar to a dict, e.g.,

    Composition(Li = 2, O = 1)

In addition, the Composition constructor also allows a single string as an input formula. E.g., Composition(“Li2O”).

Parameters:

  • *args – Any number of 2-tuples as key-value pairs.

  • strict (bool) – Only allow valid Elements and Species in the Composition. Defaults to False.

  • allow_negative (bool) – Whether to allow negative compositions. Defaults to False.

  • **kwargs – Additional kwargs supported by the dict() constructor.

add_charges_from_oxi_state_guesses(oxi_states_override: dict | None = None, target_charge: float = 0, all_oxi_states: bool = False, max_sites: int | None = None) → Composition[source]

Assign oxidation states based on guessed oxidation states.

See oxi_state_guesses for an explanation of how oxidation states are guessed. This operation uses the set of oxidation states for each site that were determined to be most likely from the oxidation state guessing routine.

Parameters:

  • oxi_states_override (dict) – dict of str->list to override an element’s common oxidation states, e.g. {“V”: [2,3,4,5]}

  • target_charge (int) – the desired total charge on the structure. Default is 0 signifying charge balance.

  • all_oxi_states (bool) – if True, an element defaults to all oxidation states in pymatgen Element.icsd_oxidation_states. Otherwise, default is Element.common_oxidation_states. Note that the full oxidation state list is very inclusive and can produce nonsensical results.

  • max_sites (int) – if possible, will reduce Compositions to at most this many sites to speed up oxidation state guesses. If the composition cannot be reduced to this many sites a ValueError will be raised. Set to -1 to just reduce fully. If set to a number less than -1, the formula will be fully reduced but a ValueError will be thrown if the number of atoms in the reduced formula is greater than abs(max_sites).

Returns:

Composition, where the elements are assigned oxidation states based on the results form guessing oxidation states. If no oxidation state is possible, returns a Composition where all oxidation states are 0.

almost_equals(other: Composition, rtol: float = 0.1, atol: float = 1e-08) → bool[source]

Returns true if compositions are equal within a tolerance.

Parameters:

  • other (Composition) – Other composition to check

  • rtol (float) – Relative tolerance

  • atol (float) – Absolute tolerance

property alphabetical_formula: str[source]

Returns a formula string, with elements sorted by alphabetically e.g., Fe4 Li4 O16 P4.

amount_tolerance = 1e-08[source]
property anonymized_formula: str[source]

An anonymized formula. Unique species are arranged in ordering of increasing amounts and assigned ascending alphabets. Useful for prototyping formulas. For example, all stoichiometric perovskites have anonymized_formula ABC3.

as_dict() → dict[str, float][source]

Note: Subtly different from get_el_amt_dict in that they keys here are str(Element) instead of Element.symbol.

Returns:

element symbol and (unreduced) amount. E.g.

{“Fe”: 4.0, “O”:6.0} or {“Fe3+”: 4.0, “O2-“:6.0}

Return type:

dict[str, float]

property average_electroneg: float[source]

Average electronegativity of the composition.

Type:

return

property chemical_system: str[source]

Get the chemical system of a Composition, for example “O-Si” for SiO2. Chemical system is a string of a list of elements sorted alphabetically and joined by dashes, by convention for use in database keys.

contains_element_type(category: str) → bool[source]

Check if Composition contains any elements matching a given category.

Parameters:

category (str) – one of “noble_gas”, “transition_metal”, “post_transition_metal”, “rare_earth_metal”, “metal”, “metalloid”, “alkali”, “alkaline”, “halogen”, “chalcogen”, “lanthanoid”, “actinoid”, “quadrupolar”, “s-block”, “p-block”, “d-block”, “f-block”

Returns:

True if any elements in Composition match category, otherwise False

copy() → Composition[source]
Returns:

A copy of the composition.

property element_composition: Composition[source]

Returns the composition replacing any species by the corresponding element.

property elements: list[pymatgen.core.periodic_table.Element | pymatgen.core.periodic_table.Species | pymatgen.core.periodic_table.DummySpecies][source]

Returns view of elements in Composition.

property formula: str[source]

Returns a formula string, with elements sorted by electronegativity, e.g., Li4 Fe4 P4 O16.

property fractional_composition: Composition[source]

Returns the normalized composition in which the amounts of each species sum to 1. E.g. “Fe2 O3”.fractional_composition = “Fe0.4 O0.6”.

classmethod from_dict(d) → Composition[source]

Creates a composition from a dict generated by as_dict(). Strictly not necessary given that the standard constructor already takes in such an input, but this method preserves the standard pymatgen API of having from_dict methods to reconstitute objects generated by as_dict(). Allows for easier introspection.

Parameters:

d (dict) – {symbol: amount} dict.

classmethod from_weight_dict(weight_dict) → Composition[source]

Creates a Composition based on a dict of atomic fractions calculated from a dict of weight fractions. Allows for quick creation of the class from weight-based notations commonly used in the industry, such as Ti6V4Al and Ni60Ti40.

Parameters:

weight_dict (dict) – {symbol: weight_fraction} dict.

Returns:

Composition

get_atomic_fraction(el: str | Element | Species | DummySpecies) → float[source]

Calculate atomic fraction of an Element or Species.

Parameters:

el (Element/Species) – Element or Species to get fraction for.

Returns:

Atomic fraction for element el in Composition

get_el_amt_dict() → dict[str, float][source]
Returns:

element symbol and (unreduced) amount. E.g.

{“Fe”: 4.0, “O”:6.0} or {“Fe3+”: 4.0, “O2-“:6.0}

Return type:

dict[str, float]

get_integer_formula_and_factor(max_denominator: int = 10000, iupac_ordering: bool = False) → tuple[str, float][source]

Calculates an integer formula and factor.

Parameters:

  • max_denominator (int) – all amounts in the el:amt dict are first converted to a Fraction with this maximum denominator

  • iupac_ordering (bool, optional) – Whether to order the formula by the iupac “electronegativity” series, defined in Table VI of “Nomenclature of Inorganic Chemistry (IUPAC Recommendations 2005)”. This ordering effectively follows the groups and rows of the periodic table, except the Lanthanides, Actinides and hydrogen. Note that polyanions will still be determined based on the true electronegativity of the elements.

Returns:

A pretty normalized formula and a multiplicative factor, i.e., Li0.5O0.25 returns (Li2O, 0.25). O0.25 returns (O2, 0.125)

get_reduced_composition_and_factor() → tuple[pymatgen.core.composition.Composition, float][source]

Calculates a reduced composition and factor.

Returns:

A normalized composition and a multiplicative factor, i.e., Li4Fe4P4O16 returns (Composition(“LiFePO4”), 4).

get_reduced_formula_and_factor(iupac_ordering: bool = False) → tuple[str, float][source]

Calculates a reduced formula and factor.

Parameters:

iupac_ordering (bool, optional) – Whether to order the formula by the iupac “electronegativity” series, defined in Table VI of “Nomenclature of Inorganic Chemistry (IUPAC Recommendations 2005)”. This ordering effectively follows the groups and rows of the periodic table, except the Lanthanides, Actinides and hydrogen. Note that polyanions will still be determined based on the true electronegativity of the elements.

Returns:

A pretty normalized formula and a multiplicative factor, i.e., Li4Fe4P4O16 returns (LiFePO4, 4).

get_wt_fraction(el: str | Element | Species | DummySpecies) → float[source]

Calculate weight fraction of an Element or Species.

Parameters:

el (Element | Species) – Element or Species to get fraction for.

Returns:

Weight fraction for element el in Composition.

Return type:

float

property hill_formula: str[source]

Hill formula. The Hill system (or Hill notation) is a system of writing empirical chemical formulas, molecular chemical formulas and components of a condensed formula such that the number of carbon atoms in a molecule is indicated first, the number of hydrogen atoms next, and then the number of all other chemical elements subsequently, in alphabetical order of the chemical symbols. When the formula contains no carbon, all the elements, including hydrogen, are listed alphabetically.

Type:

return

property is_element: bool[source]

True if composition is an element.

property iupac_formula: str[source]

Returns a formula string, with elements sorted by the iupac electronegativity ordering defined in Table VI of “Nomenclature of Inorganic Chemistry (IUPAC Recommendations 2005)”. This ordering effectively follows the groups and rows of the periodic table, except the Lanthanides, Actinides and hydrogen. Polyanions are still determined based on the true electronegativity of the elements. e.g. CH2(SO4)2

property num_atoms: float[source]

Total number of atoms in Composition. For negative amounts, sum of absolute values

oxi_prob = None[source]
oxi_state_guesses(oxi_states_override: dict | None = None, target_charge: float = 0, all_oxi_states: bool = False, max_sites: int | None = None) → list[dict[str, float]][source]

Checks if the composition is charge-balanced and returns back all charge-balanced oxidation state combinations. Composition must have integer values. Note that more num_atoms in the composition gives more degrees of freedom. e.g., if possible oxidation states of element X are [2,4] and Y are [-3], then XY is not charge balanced but X2Y2 is. Results are returned from most to least probable based on ICSD statistics. Use max_sites to improve performance if needed.

Parameters:

  • oxi_states_override (dict) – dict of str->list to override an element’s common oxidation states, e.g. {“V”: [2,3,4,5]}

  • target_charge (int) – the desired total charge on the structure. Default is 0 signifying charge balance.

  • all_oxi_states (bool) – if True, an element defaults to all oxidation states in pymatgen Element.icsd_oxidation_states. Otherwise, default is Element.common_oxidation_states. Note that the full oxidation state list is very inclusive and can produce nonsensical results.

  • max_sites (int) – if possible, will reduce Compositions to at most this many sites to speed up oxidation state guesses. If the composition cannot be reduced to this many sites a ValueError will be raised. Set to -1 to just reduce fully. If set to a number less than -1, the formula will be fully reduced but a ValueError will be thrown if the number of atoms in the reduced formula is greater than abs(max_sites).

Returns:

A list of dicts - each dict reports an element symbol and average

oxidation state across all sites in that composition. If the composition is not charge balanced, an empty list is returned.

static ranked_compositions_from_indeterminate_formula(fuzzy_formula: str, lock_if_strict: bool = True) → list[pymatgen.core.composition.Composition][source]

Takes in a formula where capitalization might not be correctly entered, and suggests a ranked list of potential Composition matches. Author: Anubhav Jain

Parameters:

  • fuzzy_formula (str) – A formula string, such as “co2o3” or “MN”, that may or may not have multiple interpretations

  • lock_if_strict (bool) – If true, a properly entered formula will only return the one correct interpretation. For example, “Co1” will only return “Co1” if true, but will return both “Co1” and “C1 O1” if false.

Returns:

A ranked list of potential Composition matches

property reduced_composition: Composition[source]

Returns the reduced composition, i.e. amounts normalized by greatest common denominator. E.g. “Fe4 P4 O16”.reduced_composition = “Fe P O4”.

property reduced_formula: str[source]

Returns a pretty normalized formula, i.e., LiFePO4 instead of Li4Fe4P4O16.

remove_charges() → Composition[source]

Removes the charges from any species in a Composition object.

Returns:

Composition object without charge decoration, for example {“Fe3+”: 2.0, “O2-“:3.0} becomes {“Fe”: 2.0, “O”:3.0}

replace(elem_map: dict[str, str | dict[str, int | float]]) → Composition[source]

Replace elements in a composition. Returns a new Composition, leaving the old one unchanged.

Parameters:

elem_map (dict[str, str | dict[str, int | float]]) – dict of elements or species to swap. E.g. {“Li”: “Na”} performs a Li for Na substitution. The target can be a {species: factor} dict. For example, in Fe2O3 you could map {“Fe”: {“Mg”: 0.5, “Cu”:0.5}} to obtain MgCuO3.

Returns:

New object with elements remapped according to elem_map.

Return type:

Composition

special_formulas = {'Cl': 'Cl2', 'CsO': 'Cs2O2', 'F': 'F2', 'H': 'H2', 'HO': 'H2O2', 'KO': 'K2O2', 'LiO': 'Li2O2', 'N': 'N2', 'NaO': 'Na2O2', 'O': 'O2', 'RbO': 'Rb2O2'}[source]
property to_data_dict: dict[source]

Returns: A dict with many keys and values relating to Composition/Formula, including reduced_cell_composition, unit_cell_composition, reduced_cell_formula, elements and nelements.

to_pretty_string() → str[source]
Returns:

Same as output __str__() but without spaces.

Return type:

str

property to_reduced_dict: dict[str, float][source]

Returns: dict[str, float]: element symbols mapped to reduced amount e.g. {“Fe”: 2.0, “O”:3.0}.

property to_weight_dict: dict[str, float][source]

Returns: dict[str, float] with weight fraction of each component {“Ti”: 0.90, “V”: 0.06, “Al”: 0.04}

property total_electrons: float[source]

Total number of electrons in composition.

Type:

return

property valid: bool[source]

Returns True if Composition contains valid elements or species and False if the Composition contains any dummy species.

property weight: float[source]

Total molecular weight of Composition

exception CompositionError[source]

Bases: Exception

Exception class for composition errors

reduce_formula(sym_amt, iupac_ordering: bool = False) → tuple[str, float][source]

Helper method to reduce a sym_amt dict to a reduced formula and factor.

Parameters:

  • sym_amt (dict) – {symbol: amount}.

  • iupac_ordering (bool, optional) – Whether to order the formula by the iupac “electronegativity” series, defined in Table VI of “Nomenclature of Inorganic Chemistry (IUPAC Recommendations 2005)”. This ordering effectively follows the groups and rows of the periodic table, except the Lanthanides, Actinides and hydrogen. Note that polyanions will still be determined based on the true electronegativity of the elements.

Returns:

(reduced_formula, factor).