cvm package¶

Subpackages¶

cvm.A1 package

Submodules¶

cvm.base module¶

class cvm.base.BaseCVM(meta: dict, *, series: List[dict] = None, experiment: dict = None)[source]¶

Bases: collections.defaultdict

CVM is a general CVM (Cluster Variation Method) calculation framework using NIM (Natural Iteration Method).

Parameters

meta (dict) – Meta information. It can be anything that will be used to describe this calculation set. This information will be passed over the whole calculation.
series (List[dict], optional) – Sample data contains raw energies, and other calculation needed parameters, by default None
experiment (dict, optional) – The experiment data, by default None

__call__(*labels, verbose: bool = False, early_stopping: float = 0.2, sample_paras: dict = {}, reset_paras: dict = {}, update_en_paras: dict = {}, process_paras: dict = {})[source]¶

Run CVM calculation as generator. Will yield calculation details on each step.

Parameters

labels (str) – If not None, only execute listed series samples.
verbose (bool, optional) – Set to True to show extra information when running calculations, by default False
sample_ite_paras (dict, optional) – The parameters will be passed to sample.ite and sample.__call__ method, by default empty.
reset_paras (dict, optional) – The parameters will be passed to self.reset method, by default empty.
update_en_paras (dict, optional) – The parameters will be passed to self.update_energy method, by default empty.
process_paras (dict, optional) – The parameters will be passed to self.process method, by default empty.

add_sample(sample: cvm.sample.Sample)[source]¶

Add sample data

Parameters: sample (Sample) – Instance of Sample.

classmethod from_input_set(path_of_set: str)[source]¶

Build a CVM instance from input set.

Parameters: path_of_set (str) – The path of input set dir.
Returns: New CVM instance.
Return type: BaseCVM

classmethod from_samples(meta: dict, *samples, experiment: dict = None)[source]¶

Build a CVM instance from series samples.

Parameters

meta (dict) – Meta information. It can be anything that will be used to describe this calculation set. This information will be passed over the whole calculation.
samples (Sample) – List of Series sample.
experiment (dict, optional) – The experiment data, by default None

Returns

New CVM instance.

Return type

BaseCVM

abstract process(**kwargs)[source]¶: The main loop to execute a NIM calculation step-by-step..

abstract reset(**kwargs)[source]¶: Reset all conditions for new calculation.

run(*labels, verbose: bool = False, early_stopping: float = 0.2, sample_paras: dict = {}, reset_paras: dict = {}, update_en_paras: dict = {}, process_paras: dict = {})[source]¶

Run CVM calculation.

Parameters

labels (str) – If not None, only execute listed series samples.
verbose (bool, optional) – Set to True to show extra information when running calculations, by default False
sample_ite_paras (dict, optional) – The parameters will be passed to sample.ite and sample.__call__ method, by default empty.
reset_paras (dict, optional) – The parameters will be passed to self.reset method, by default empty.
update_en_paras (dict, optional) – The parameters will be passed to self.update_energy method, by default empty.
process_paras (dict, optional) – The parameters will be passed to self.process method, by default empty.

abstract update_energy(e_ints, **kwargs)[source]¶: Update energies.

property results¶

Get calculated results.

Returns
Return type: results

cvm.normalizer module¶

class cvm.normalizer.Normalizer(energies: pandas.core.frame.DataFrame, clusters, targets)[source]¶

Bases: collections.defaultdict

property interaction_energies¶

cvm.results module¶

cvm.sample module¶

class cvm.sample.Sample(label: str, host: str, impurity: str, *, temperature: list = None, energies: pandas.core.frame.DataFrame = None, clusters: dict = None, mean: str = 'arithmetic', vibration: bool = True, skip: bool = False, x_1: float = 0.001, condition: float = 1e-07, r_0: Union[float, dict, str] = None, normalizer: Union[dict, cvm.normalizer.Normalizer] = None)[source]¶

Bases: collections.defaultdict

Sample is a object which store a group of configuration data for calculation

Parameters

label (str) – The Sample label.
host (str, optional) – The column name of host energies in energies.
host – The column name of impurity energies in energies.
temperature (list, optional) – Temperature steps follow the format [start, stop, # of steps]. By default None.
energies (pd.DataFrame, optional) – A pandas.DataFrame object contain raw energies. By default None.
clusters (dict, optional) – Set how to calculate interaction energy. By default None.
mean (str, optional) – Specific how to mix atom weights. Can be ‘arithmetic’, ‘harmonic’, and ‘geometric’. By default ‘arithmetic’.
vibration (bool, optional) – Specific whether or not to import the thermal vibration effect. By default True.
skip (bool, optional) – Set to true to skip this series sample. By default False.
x_1 (float, optional) – The initialization concentration of impurity. By default 0.001.
condition (float, optional) – Convergence condition. By default 1e-07.
r_0 (Union[float, dict, str], optional) – Set how to estimate r_0 from the given T and c. If local, r_0 will be calculated from each phase respectively. If constant, will ignore T and c. If dict, will do a parabolic curve fitting. By default None.
normalizer (Union[dict, Normalizer], optional) – Configuration of a Normalizer or an instance. If given, this will be used to normalize the long-range interaction energy. By default None.

__call__(*, T: float = None, r: [<class 'float'>, <class 'dict'>, <class 'str'>, None] = None, vibration: bool = None, energy_patch: Callable[[float, float], collections.namedtuple] = None, **kwargs)[source]¶

Get interaction energies at given T, and r.

Parameters

T (float) – Temperature.
r (float, dict, str, or None, optional) – Atomic distance. By default None.
vibration (bool) – Specific whether or not to import the thermal vibration effect.
energy_patch (Callable[[float, float], namedtuple], optional) – A patch that will be used to correct the returns of interaction energy. By default None.

Returns

namedtuple – Named tuple contains calculated interaction energies.

Return type

namedtuple

ite(*, temperature: list = None, k: int = 3, vibration: bool = None, r_0: [<class 'float'>, <class 'dict'>, <class 'str'>, None] = None, **kwargs)[source]¶

Iterate over each temperature

Parameters

temperature (list, optional) – Reset temperature steps, by default None
k (int) – Degree of the smoothing spline. Must be <= 5. Default is k=3, a cubic spline.
vibration (bool) – Specific whether or not to import the thermal vibration effect.

Yields

T (float) – Temperature at current step.
r_func (Callable[[float], float]) – A function receiving impurity concentration c and returns corresponding atomic distance r.

set_clusters(**val)[source]¶

set_energies(energies)[source]¶

set_normalizer(val)[source]¶

set_temperature(temp)[source]¶

property clusters¶

property energies¶

property normalizer¶

property temperatures¶

cvm.solution_limit module¶

cvm.solution_limit.percent(x, pos=0)[source]¶

cvm.solution_limit.process(opt)[source]¶

cvm.utils module¶

class cvm.utils.UnitConvert[source]¶

Bases: object

static ad2lc(d, n=4)[source]¶

static au2K(t)[source]¶

static eV2Kbar(p)[source]¶

static lc2ad(d, n=4)[source]¶

static ry2eV(t)[source]¶

cvm.utils.get_inp(path)[source]¶

cvm.utils.mixed_atomic_weight(formula: str, *, mean='arithmetic')[source]¶

cvm.utils.parse_input_set(path_of_set)[source]¶

cvm.utils.parse_formula(formula)[source]¶

Parameters: formula (str) – A string formula, e.g. Fe2O3, Li3Fe2(PO4)3
Returns: Composition with that formula.

Notes

In the case of Metallofullerene formula (e.g. Y3N@C80), the @ mark will be dropped and passed to parser.

cvm.utils.cvm_context(**kwargs)[source]¶

Set temp environment variable using with statement.

Examples

>>> import os
>>> with cvm_context(simple_print='True'):
>>>    print(os.getenv('simple_print'))
True
>>> print(os.getenv('simple_print'))
None

Parameters: kwargs (dict[str]) – Dict with string value.

cvm.utils.logspace(start: float, end: float, num: int) → numpy.ndarray[source]¶

Generate log scaled series.

Parameters

start (float) – Start point.
end (float.) – End point
num (int) – Steps.

Returns

series

Return type

np.ndarray

cvm.vibration module¶

class cvm.vibration.ClusterVibration(*, label: str, xs: list, ys: list, mass: float, num: int, morse_paras_bounds: list = None)[source]¶

Bases: object

Tools class for cluster vibration

Calculate phase energy using debye-sg model

Parameters

label (str) – Label in chemical composition format.
xs (list) – List of atomic distance.
ys (list) – List of phase energies.
mass (float) – Mixed mass.
num (int) – Number of atoms.
morse_paras_bounds (list, optional) – parameter bounds for fitting, by default None. See also, https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.curve_fit.html

Raises

ValueError – xs and ys must have same shape.

__call__(*, T: float = None, r: [<class 'float'>, <class 'str'>] = 'local', min_x: str = None)[source]¶

Get free energy.

Parameters

T (float, optional) – Temperature. If None, will set parameter vibration to False automatically.
r (float or str, optional) – Atomic distance, If local, will ues the default setting which be set when instancing. by default None.
min_x (str, optional) – By default None. If None, will ues the default setting which be set when instancing. If not None, function will returns equilibrium lattice constant as second result. The string can be ws or lattice.

debye_function(T: float, r: float = None, *, n: int = 3) → float[source]¶

Debye function.

Parameters

T (float) – Temperature.
r (float, optional) – Atomic distance, by default None
n (int, optional) – Dimssion, by default 3

Returns

Return type

float

debye_temperature(r: [<class 'float'>, <class 'str'>] = 'local') → float[source]¶

Debye temperature function.

Parameters: r (float, str, optional) – Atomic distance, by default None
Returns
Return type: float

morse_potential(r: float) → float[source]¶

Morse potential

Parameters: r (float) – Atomic distance
Returns: Potential energy.
Return type: float

property bulk_modulus¶

Estimated bulk modulus.

Returns
Return type: float

property c1¶

Morse potential parameter C1.

Returns
Return type: float

property c2¶

Morse potential parameter C2.

Returns
Return type: float

property equilibrium_lattice_cons¶

Equilibrium lattice constant.

Returns
Return type: float

property gamma_0¶

property lmd¶

Morse potential parameter lambda.

Returns
Return type: float

property r_0¶

Atomic distance at equilibrium status.

Returns
Return type: float

property x_0¶

cvm package¶

Subpackages¶

Submodules¶

cvm.base module¶

cvm.normalizer module¶

cvm.results module¶

cvm.sample module¶

cvm.solution_limit module¶

cvm.utils module¶

cvm.vibration module¶

Module contents¶