Source code for cornac.datasets.movielens

# Copyright 2018 The Cornac Authors. All Rights Reserved.
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# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
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#
#     http://www.apache.org/licenses/LICENSE-2.0
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# ============================================================================
"""Link to the data: https://grouplens.org/datasets/movielens/"""

from typing import List
from collections import namedtuple

from ..utils import validate_format
from ..utils import cache
from ..data import Reader
from ..data.reader import read_text


VALID_DATA_FORMATS = ["UIR", "UIRT"]

MovieLens = namedtuple("MovieLens", ["url", "unzip", "path", "sep", "skip"])
ML_DATASETS = {
    "100K": MovieLens(
        "http://files.grouplens.org/datasets/movielens/ml-100k/u.data",
        False,
        "ml-100k/u.data",
        "\t",
        0,
    ),
    "1M": MovieLens(
        "http://files.grouplens.org/datasets/movielens/ml-1m.zip",
        True,
        "ml-1m/ratings.dat",
        "::",
        0,
    ),
    "10M": MovieLens(
        "http://files.grouplens.org/datasets/movielens/ml-10m.zip",
        True,
        "ml-10M100K/ratings.dat",
        "::",
        0,
    ),
    "20M": MovieLens(
        "http://files.grouplens.org/datasets/movielens/ml-20m.zip",
        True,
        "ml-20m/ratings.csv",
        ",",
        1,
    ),
}


[docs]def load_feedback(fmt="UIR", variant="100K", reader=None): """Load the user-item ratings of one of the MovieLens datasets Parameters ---------- fmt: str, default: 'UIR' Data format to be returned, one of ['UIR', 'UIRT']. variant: str, optional, default: '100K' Specifies which MovieLens dataset to load, one of ['100K', '1M', '10M', '20M']. reader: `obj:cornac.data.Reader`, optional, default: None Reader object used to read the data. Returns ------- data: array-like Data in the form of a list of tuples depending on the given data format. """ fmt = validate_format(fmt, VALID_DATA_FORMATS) ml = ML_DATASETS.get(variant.upper(), None) if ml is None: raise ValueError("variant must be one of {}.".format(ML_DATASETS.keys())) fpath = cache(url=ml.url, unzip=ml.unzip, relative_path=ml.path) reader = Reader() if reader is None else reader return reader.read(fpath, fmt, sep=ml.sep, skip_lines=ml.skip)
[docs]def load_plot(): """Load the plots of movies provided @ http://dm.postech.ac.kr/~cartopy/ConvMF/ Returns ------- texts: List List of text documents, one per item. ids: List List of item ids aligned with indices in `texts`. """ fpath = cache( url="https://static.preferred.ai/cornac/datasets/movielens/ml_plot.zip", unzip=True, relative_path="movielens/ml_plot.dat", ) texts, ids = read_text(fpath, sep="::") return texts, ids