本文整理汇总了Python中wyrm.types.Data.class_names方法的典型用法代码示例。如果您正苦于以下问题:Python Data.class_names方法的具体用法?Python Data.class_names怎么用?Python Data.class_names使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类wyrm.types.Data
的用法示例。
在下文中一共展示了Data.class_names方法的2个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: load_graz
# 需要导入模块: from wyrm.types import Data [as 别名]
# 或者: from wyrm.types.Data import class_names [as 别名]
def load_graz(filename):
# load the training
data_mat = scio.loadmat('dataset_BCIcomp1.mat')
data = data_mat['x_train'].astype('double')
#print data.shape
data = data.swapaxes(-3, -2)
data = data.swapaxes(-1, -3)
labels = data_mat['y_train'].astype('int').ravel()
#print data.shape
# convert into wyrm Data
axes = [np.arange(i) for i in data.shape]
axes[0] = labels
axes[2] = [str(i) for i in range(data.shape[2])]
names = ['Class', 'Time', 'Channel']
units = ['#', 'ms', '#']
dat_train = Data(data=data, axes=axes, names=names, units=units)
dat_train.fs = 128
dat_train.class_names = ['left', 'right']
# load the test data
#test_data_mat = loadmat(test_file)
data = data_mat['x_test'].astype('double')
data = data.swapaxes(-3, -2)
data = data.swapaxes(-1, -3)
# convert into wyrm Data
axes = [np.arange(i) for i in data.shape]
axes[2] = [str(i) for i in range(data.shape[2])]
names = ['Class','Time', 'Channel']
units = ['#','ms', '#']
dat_test = Data(data=data, axes=axes, names=names, units=units)
dat_test.fs = 128
# map labels 2 -> 0
dat_test.axes[0][dat_test.axes[0] == 2] = 0
dat_train.axes[0][dat_train.axes[0] == 2] = 0
return dat_train, dat_test
示例2: load_bcicomp3_ds1
# 需要导入模块: from wyrm.types import Data [as 别名]
# 或者: from wyrm.types.Data import class_names [as 别名]
def load_bcicomp3_ds1(dirname):
"""Load the BCI Competition III Data Set 1.
This method loads the data set and converts it into Wyrm's ``Data``
format. Before you use it, you have to download the training- and
test data in Matlab format and unpack it into a directory.
.. note::
If you need the true labels of the test sets, you'll have to
download them separately from
http://bbci.de/competition/iii/results/index.html#labels
Parameters
----------
dirname : str
the directory where the ``Competition_train.mat`` and
``Competition_test.mat`` are located
Returns
-------
epo_train, epo_test : epoched ``Data`` objects
Examples
--------
>>> epo_test, epo_train = load_bcicomp3_ds1('/home/foo/bcicomp3_dataset1/')
"""
# construct the filenames from the dirname
training_file = path.sep.join([dirname, 'Competition_train.mat'])
test_file = path.sep.join([dirname, 'Competition_test.mat'])
# load the training data
training_data_mat = loadmat(training_file)
data = training_data_mat['X'].astype('double')
data = data.swapaxes(-1, -2)
labels = training_data_mat['Y'].astype('int').ravel()
# convert into wyrm Data
axes = [np.arange(i) for i in data.shape]
axes[0] = labels
axes[2] = [str(i) for i in range(data.shape[2])]
names = ['Class', 'Time', 'Channel']
units = ['#', 'ms', '#']
dat_train = Data(data=data, axes=axes, names=names, units=units)
dat_train.fs = 1000
dat_train.class_names = ['pinky', 'tongue']
# load the test data
test_data_mat = loadmat(test_file)
data = test_data_mat['X'].astype('double')
data = data.swapaxes(-1, -2)
# convert into wyrm Data
axes = [np.arange(i) for i in data.shape]
axes[2] = [str(i) for i in range(data.shape[2])]
names = ['Epoch', 'Time', 'Channel']
units = ['#', 'ms', '#']
dat_test = Data(data=data, axes=axes, names=names, units=units)
dat_test.fs = 1000
# map labels -1 -> 0
dat_test.axes[0][dat_test.axes[0] == -1] = 0
dat_train.axes[0][dat_train.axes[0] == -1] = 0
return dat_train, dat_test