DatabaseSplitter

class DatabaseSplitter(train=0.9, test=0.1, validation=0.0, predict=0.0, seed=None)[source]

Bases: Plugin

Plugin for splitting the database into training, test, validation, and prediction sets.

This plugin automatically splits the database according to specified ratios before the fitting process begins.

Parameters:

  • train (float) – Ratio or number of samples for training set. Default is 0.9.

  • test (float) – Ratio or number of samples for test set. Default is 0.1.

  • validation (float) – Ratio or number of samples for validation set. Default is 0.0.

  • predict (float) – Ratio or number of samples for prediction set. Default is 0.0.

  • seed (int) – Random seed for reproducibility. Default is None.

Example:
>>> from ezyrb import ReducedOrderModel as ROM
>>> from ezyrb import POD, RBF, Database
>>> from ezyrb.plugin import DatabaseSplitter
>>> import numpy as np
>>> params = np.random.rand(100, 2)
>>> snapshots = np.random.rand(100, 50)
>>> db = Database(params, snapshots)
>>> pod = POD(rank=5)
>>> rbf = RBF()
>>> splitter = DatabaseSplitter(train=0.7, test=0.2, validation=0.1)
>>> rom = ROM(db, pod, rbf, plugins=[splitter])
>>> rom.fit()

Initialize the DatabaseSplitter plugin.

Parameters:

  • train (float) – Ratio for training set. Default is 0.9.

  • test (float) – Ratio for test set. Default is 0.1.

  • validation (float) – Ratio for validation set. Default is 0.0.

  • predict (float) – Ratio for prediction set. Default is 0.0.

  • seed (int) – Random seed. Default is None.

_abc_impl = <_abc._abc_data object>
fit_preprocessing(rom)[source]

Split the database before fitting begins.

Parameters:

rom (ReducedOrderModel) – The ROM instance.

class DatabaseDictionarySplitter(train_key=None, test_key=None, validation_key=None, predict_key=None)[source]

Bases: Plugin

This plugin class is used to define the train, test, validation and predict databases when the databases are already split: train, test, validation and predict are already database objects stored in a dictionary. Given the desired keys of the dictionary as input, the plugin will assign the corresponding database objects to the train, test, validation and predict attributes of the ROM.

Example:
>>> from ezyrb import ReducedOrderModel as ROM
>>> from ezyrb import POD, RBF, Database
>>> from ezyrb.plugin import DatabaseDictionarySplitter
>>> db_dict = {
...     'train': Database(train_params, train_snaps),
...     'test': Database(test_params, test_snaps)
... }
>>> pod = POD(rank=5)
>>> rbf = RBF()
>>> splitter = DatabaseDictionarySplitter(train_key='train', test_key='test')
>>> rom = ROM(db_dict['train'], pod, rbf, plugins=[splitter])
>>> rom.fit()

Initialize the DatabaseDictionarySplitter plugin.

Parameters:

  • train_key (str) – Dictionary key for training database. Default is None.

  • test_key (str) – Dictionary key for test database. Default is None.

  • validation_key (str) – Dictionary key for validation database. Default is None.

  • predict_key (str) – Dictionary key for prediction database. Default is None.

_abc_impl = <_abc._abc_data object>
fit_preprocessing(rom)[source]

Assign the database splits from the dictionary before fitting.

Parameters:

rom (ReducedOrderModel) – The ROM instance.

Raises:

ValueError – If the database is not a dictionary.