neupy.datasets.reber module
- neupy.datasets.reber.make_reber(n_words=100)[source]
Generate list of words valid by Reber grammar.
Parameters: - n_words : int
Number of reber words, defaults to 100.
Returns: - list
List of Reber words.
Examples
>>> from neupy.datasets import make_reber >>> make_reber(4) ['TPTXVS', 'VXXVS', 'TPPTS', 'TTXVPXXVS']
- neupy.datasets.reber.is_valid_by_reber(word)[source]
Сhecks whether a word belongs to grammar Reber.
Parameters: - word : str or list of letters
The word that you want to test.
Returns: - bool
True if word valid by Reber grammar and False otherwise.
Examples
>>> from neupy.datasets import is_valid_by_reber >>> >>> is_valid_by_reber('TTS') True >>> is_valid_by_reber('STS') False >>> >>> is_valid_by_reber(['T', 'T', 'S']) True >>> is_valid_by_reber(['S', 'T', 'S']) False
- neupy.datasets.reber.make_reber_classification(n_samples, invalid_size=0.5, lenrange=(3, 14), return_indices=False)[source]
Generate random dataset for Reber grammar classification. Invalid words contains the same letters as at Reber grammar, but they are build without grammar rules.
Parameters: - n_samples : int
Number of samples in dataset.
- invalid_size : float
Proportion of invalid words in dataset, defaults to 0.5. Value must be between 0 and 1.
- lenrange : tuple
Length of each word will be bounded by the two numbers specified in this range. Defaults to (3, 14).
- return_indices : bool
If True, each word will be converted to array where each letter converted to the index. Defaults to False.
Returns: - tuple
Return two lists. First contains words and second - labels for them.
Examples
>>> from neupy.datasets import make_reber_classification >>> >>> data, labels = make_reber_classification(10, invalid_size=0.5) >>> data array(['SXSXVSXXVX', 'VVPS', 'VVPSXTTS', 'VVS', 'VXVS', 'VVS', 'PPTTTXPSPTV', 'VTTSXVPTXVXT', 'VSSXSTX', 'TTXVS'], dtype='<U12') >>> labels array([0, 1, 0, 1, 1, 1, 0, 0, 0, 1]) >>> >>> data, labels = make_reber_classification( ... 4, invalid_size=0.5, return_indices=True) >>> data array([array([1, 3, 1, 4]), array([0, 3, 0, 3, 0, 4, 3, 0, 4, 4]), array([1, 3, 1, 2, 3, 1, 2, 4]), array([0, 3, 0, 0, 3, 0, 4, 2, 4, 1, 0, 4, 0])], dtype=object)