flory.common.phases

Module providing common utilities to deal with phases and their composition.

Classes

`Phases`	Contains information about compositions and relative sizes of many phases.
`PhasesResult`	Contains compositions and relative sizes of many phases along with extra information.

class Phases(volumes, fractions)[source]

Bases: object

Contains information about compositions and relative sizes of many phases.

Parameters:

volumes¶ (ndarray) – 1D array with shape \(N_\mathrm{P}\), containing the volume \(J_p\) of each phase.
fractions¶ (ndarray) – 2D array with shape \(N_\mathrm{P} \times N_\mathrm{C}\), containing the volume fractions of the components in each phase \(\phi_{p,i}\). The first dimension must be the same as volumes.

Public Data Attributes:

`num_phases`	Number of phases \(N_\mathrm{P}\).
`num_components`	Number of components \(N_\mathrm{C}\).
`total_volume`	Total volume of entire system
`mean_fractions`	Mean fraction averaged over phases \(\bar{\phi}_i\)

Public Methods:

`normalize`()	normalize the phases so that their volumes adds to one
`sort`()	Sort the phases according to the index of most concentrated components.
`get_clusters`([dist])	Find clusters of compositions.

Private Methods:

_copy(volumes, fractions)

create copy with changed volume and fraction

_copy(volumes, fractions)[source]

create copy with changed volume and fraction

This method helps with subclassing methods that should keep other information intact.

Return type:: Phases

property num_phases: int: Number of phases \(N_\mathrm{P}\).

property num_components: int: Number of components \(N_\mathrm{C}\).

property total_volume: float: Total volume of entire system

property mean_fractions: ndarray: Mean fraction averaged over phases \(\bar{\phi}_i\)

normalize()[source]

normalize the phases so that their volumes adds to one

Return type:: Phases

sort()[source]

Sort the phases according to the index of most concentrated components.

Returns:: The sorted phases.
Return type:: Phases

get_clusters(dist=0.01)[source]

Find clusters of compositions.

Find unique phases from compartments by clustering. The returning results are sorted according to the index of most concentrated components.

Parameters:: dist¶ (float, default: 0.01) – Cut-off distance for cluster analysis.
Returns:: The clustered and sorted phases.
Return type:: Phases

class PhasesResult(volumes, fractions, *, info=None)[source]

Bases: Phases

Contains compositions and relative sizes of many phases along with extra information.

Parameters:

volumes¶ (ndarray) – 1D array with shape \(N_\mathrm{P}\), containing the volume \(J_p\) of each phase.
fractions¶ (ndarray) – 2D array with shape \(N_\mathrm{P} \times N_\mathrm{C}\), containing the volume fractions of the components in each phase \(\phi_{p,i}\). The first dimension must be the same as volumes.
info¶ (dict | None, default: None) – Additional information about how the phases were obtained.

Public Data Attributes:

info

Information for the current collection of phases.

Inherited from Phases:

Public Methods:

from_phases(phases, *[, info])

create phase result from Phases

Inherited from Phases:

Private Methods:

_copy(volumes, fractions)

create copy with changed volume and fraction

Inherited from Phases:

classmethod from_phases(phases, *, info=None)[source]

create phase result from Phases

Parameters:

phases¶ (Phases) – The Phases containing volumes and fractions.
info¶ (dict | None, default: None) – Additional information about how the phases were obtained

Return type:

PhasesResult

property info: dict: Information for the current collection of phases.

_copy(volumes, fractions)[source]

create copy with changed volume and fraction

This method helps with subclassing methods that should keep other information intact.

Return type:: PhasesResult

get_clusters(dist=0.01)

Find clusters of compositions.

Find unique phases from compartments by clustering. The returning results are sorted according to the index of most concentrated components.

Parameters:: dist¶ (float, default: 0.01) – Cut-off distance for cluster analysis.
Returns:: The clustered and sorted phases.
Return type:: Phases

property mean_fractions: ndarray: Mean fraction averaged over phases \(\bar{\phi}_i\)

normalize()

normalize the phases so that their volumes adds to one

Return type:: Phases

property num_components: int: Number of components \(N_\mathrm{C}\).

property num_phases: int: Number of phases \(N_\mathrm{P}\).

sort()

Sort the phases according to the index of most concentrated components.

Returns:: The sorted phases.
Return type:: Phases

property total_volume: float: Total volume of entire system

Functions

get_uniform_random_composition

pick concentrations uniformly from allowed simplex (sum of fractions < 1)

get_uniform_random_composition(num_comps, rng=None)[source]

pick concentrations uniformly from allowed simplex (sum of fractions < 1)

Parameters:

num_comps¶ (int) – the number of components to use
rng¶ (default: None) – The random number generator

Returns:

An array with `num_comps` random fractions

Return type:

ndarray