iota.coarsegraining

Description

This module provides functionalities to transform the discrete data from particle based simulations (e.g DPM, DEM) into continuum data.

• CoarseGraining

  • settings

  • settings_default

  • settings_merged

  • run

  • output_dataset

  • output_graphs

  • output_padem

  • export_settings

class CoarseGraining

iota.coarse_graining.CoarseGraining(file, settings, dataset)

CoarseGraining class object. This object contains the settings, the output and the run methods for a coarse-graining analysis.

Parameters

• file: (str) path and name to a coarse-graining settings file (Default: None)

• settings: (dict) coarse-graining settings given as a dictionary (Default: None)

• dataset : (iota.dataset.Dataset) a dataset object to be used as input dataset for the coarse-graining analysis. If provided, it overwrites the input dataset of the coarse-graining settings (Default: None)

Examples

Creating a CoarseGraining object with default settings

my_cg = iota.coarse_graining.CoarseGraining()

Creating a CoarseGraining object based on the settings in an existing coarse-graining settings file

my_cg = iota.coarse_graining.CoarseGraining(file='C:/Users/Stephe/CGSettings/my_cg_settings.json')

Creating a CoarseGraining object given on an existing settings dictionary

my_new_cg = iota.coarse_graining.CoarseGraining(settings=my_cg.settings)

Creating a CoarseGraining object with default settings and an existing dataset object as the input dataset

my_cg = iota.coarse_graining.CoarseGraining(dataset=my_dataset)

Creating a CoarseGraining object based on the settings in an existing coarse-graining settings file and using an existing dataset object as the input dataset

my_cg = iota.coarse_graining.CoarseGraining(file='C:/Users/Stephe/CGSettings/my_cg_settings.json', dataset=my_dataset)

Creating a CoarseGraining object given on an existing settings dictionary and using an existing dataset object as the input dataset

my_new_cg = iota.coarse_graining.CoarseGraining(settings=my_cg.settings, dataset=my_dataset)

Attributes

CoarseGraining.settings

Get the coarse-graining settings that the user explicitly has set

Returns

• A dictionary with the settings explicitly set by the user

Example

Getting the settings of a coarse-graining object

my_cg_settings = my_cg.settings
print(my_cg_settings)

Methods

CoarseGraining.settings_default()

Get the default coarse-graining settings

Returns

• A dictionary with the default coarse-graining settings

Example

Getting the default settings of a coarse-graining object

default_cg_settings = my_cg.settings_default()
print(default_cg_settings)

CoarseGraining.settings_merged()

Get the complete coarse-graining settings that result from merging the settings explicitly set by the user and the default settings

Returns

• A dictionary with the complete coarse-graining settings of the CoarseGraining object

Example

Getting the complete settings of a CoarseGraining object

cg_settings = my_cg.settings_merged()
print(cg_settings)

CoarseGraining.run()

Run coarse-graining transformation based on the settings of the CoarseGraining object

Example

Running the coarse-graining transformation for the CoarseGraining object

cg_settings.run()

CoarseGraining.output_dataset()

Get the dataset object that corresponds to the coarse-graining dataset generated after running the coarse-graining transformation

Return

• A iota.dataset.Dataset object that corresponds to the coarse-graining dataset

Example

Getting the coarse-graining dataset generated after running coarse-graining transformation

my_cg.run()
my_cg_dataset = my_cg.output_dataset()

CoarseGraining.output_graphs()

Get a list that contains the graphs object that may have been generated as result of the coarse-graining transformation

Return

• A list of iota.graph.Graph objects that correspond to the graphs generated by the coarse-graining transformation

Example

Getting the list of graph objects generated after running coarse-graining transformation

my_cg.run()
my_cg_graphs = my_cg.output_graphs()
my_cg_graphs[0].display()

CoarseGraining.output_padem()

Get the dataset object that corresponds to the padem dataset that may have been generated after running the coarse-graining transformation. The padem dataset would contain the raw data of the particle based simulation in Particle Analytics format

Return

• A iota.dataset.Dataset object that corresponds to the padem dataset

Example

Getting the padem dataset generated after running coarse-graining transformation

my_cg.run()
my_padem_dataset = my_cg.output_padem()

CoarseGraining.export_settings(file, merged)

Export the settings of a given CoarseGraining object to file in json format

Parameters

• file: (str) path and name for the file where the settings will be exported to.

• merged: (bool) if True, the complete coarse-graining settings are exported, i.e., the settings resulting of merging the user settings and the default ones. If False, only the user settings are exported (Default: False)

Example

Exporting the coarse-graining settings set by the user to a file

my_cg.export(file='C:/Users/Stephen/CGsettings/my_cg_settings.json')

Exporting the complete coarse-graining settings to a file

my_cg.export(file='C:/Users/Stephen/CGsettings/my_cg_settings.json', merged=True)