# Copyright 2019 IBM Corporation
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
import tarfile
import urllib.request
import numpy as np
[docs]def load_movie_review():
"""Loads the sentiment classification from a movie reviews dataset.
Read the readme from data/movie_review for more details.
"""
download_base_url = "https://www.cs.cornell.edu/people/pabo/movie%2Dreview%2Ddata/rt-polaritydata.tar.gz"
download_data_dir = os.path.join(
os.path.dirname(__file__), "data", "movie_review", "download_data"
)
data_file_path = os.path.join(download_data_dir, "rt-polaritydata.tar.gz")
if not os.path.exists(download_data_dir):
os.makedirs(download_data_dir)
print(f"created directory {download_data_dir}")
# this request is to a hardcoded https url, so does not risk leaking local data
urllib.request.urlretrieve(download_base_url, data_file_path) # nosec
X = []
y = []
with tarfile.open(data_file_path) as data_file:
data_file.extractall(path=download_data_dir) # nosec B202
with open(
os.path.join(download_data_dir, "rt-polaritydata", "rt-polarity.neg"), "rb"
) as neg_data_file:
for line in neg_data_file.readlines():
X.append(str(line))
y.append(-1)
with open(
os.path.join(download_data_dir, "rt-polaritydata", "rt-polarity.pos"), "rb"
) as pos_data_file:
for line in pos_data_file.readlines():
X.append(str(line))
y.append(1)
X = np.asarray(X, dtype=np.string_)
y = np.asarray(y)
from sklearn.utils import shuffle
X, y = shuffle(X, y)
return X, y