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Adapt to python3.7 version and fix path #5

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Adapt to python3.7 version and fix path #5

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c4058d8
Adapt to python3.7 version and fix path
pomelogo Sep 28, 2021
6af54fd
Adapt to python3.7 version and fix path
pomelogo Sep 28, 2021
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26 changes: 13 additions & 13 deletions cwru/__init__.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2,7 +2,7 @@
import glob
import errno
import random
import urllib
from urllib.request import urlretrieve
import numpy as np
from scipy.io import loadmat

Expand All @@ -11,13 +11,13 @@ class CWRU:

def __init__(self, exp, rpm, length):
if exp not in ('12DriveEndFault', '12FanEndFault', '48DriveEndFault'):
print "wrong experiment name: {}".format(exp)
print("wrong experiment name: {%s}" % exp)
exit(1)
if rpm not in ('1797', '1772', '1750', '1730'):
print "wrong rpm value: {}".format(rpm)
print("wrong rpm value: {%s}" % rpm)
exit(1)
# root directory of all data
rdir = os.path.join(os.path.expanduser('~'), 'Datasets/CWRU')
rdir = os.path.join(os.path.dirname(__file__), 'Datasets\\CWRU')

fmeta = os.path.join(os.path.dirname(__file__), 'metadata.txt')
all_lines = open(fmeta).readlines()
Expand All @@ -41,12 +41,13 @@ def _mkdir(self, path):
if exc.errno == errno.EEXIST and os.path.isdir(path):
pass
else:
print "can't create directory '{}''".format(path)
print("can't create directory {%s}" % path)
exit(1)

def _download(self, fpath, link):
print "Downloading to: '{}'".format(fpath)
urllib.URLopener().retrieve(link, fpath)
print("Downloading to: {%s} " % fpath)
urlretrieve(link,fpath)
# urllib.URLopener().retrieve(link, fpath)

def _load_and_slice_data(self, rdir, infos):
self.X_train = np.zeros((0, self.length))
Expand All @@ -60,30 +61,29 @@ def _load_and_slice_data(self, rdir, infos):
fpath = os.path.join(fdir, info[2] + '.mat')
if not os.path.exists(fpath):
self._download(fpath, info[3].rstrip('\n'))

mat_dict = loadmat(fpath)
key = filter(lambda x: 'DE_time' in x, mat_dict.keys())[0]
key = list(filter(lambda x: 'DE_time' in x, mat_dict.keys()))[0]
time_series = mat_dict[key][:, 0]

idx_last = -(time_series.shape[0] % self.length)
clips = time_series[:idx_last].reshape(-1, self.length)

n = clips.shape[0]
n_split = 3 * n / 4
n_split = int(3 * n / 4)
self.X_train = np.vstack((self.X_train, clips[:n_split]))
self.X_test = np.vstack((self.X_test, clips[n_split:]))
self.y_train += [idx] * n_split
self.y_test += [idx] * (clips.shape[0] - n_split)

def _shuffle(self):
# shuffle training samples
index = range(self.X_train.shape[0])
index = list(range(self.X_train.shape[0]))
random.Random(0).shuffle(index)
self.X_train = self.X_train[index]
self.y_train = tuple(self.y_train[i] for i in index)

# shuffle test samples
index = range(self.X_test.shape[0])
index = list(range(self.X_test.shape[0]))
random.Random(0).shuffle(index)
self.X_test = self.X_test[index]
self.y_test = tuple(self.y_test[i] for i in index)
self.y_test = tuple(self.y_test[i] for i in index)
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