import numpy
[docs]class ChannelSelector(object):
"""Select 1ch from multi-channel signal """
def __init__(self, train_channel='random', eval_channel=0, axis=1):
self.train_channel = train_channel
self.eval_channel = eval_channel
self.axis = axis
def __repr__(self):
return ('{name}(train_channel={train_channel}, '
'eval_channel={eval_channel}, axis={axis})'
.format(name=self.__class__.__name__,
train_channel=self.train_channel,
eval_channel=self.eval_channel,
axis=self.axis))
def __call__(self, x, train=True):
# Assuming x: [Time, Channel] by default
if x.ndim <= self.axis:
# If the dimension is insufficient, then unsqueeze
# (e.g [Time] -> [Time, 1])
ind = tuple(slice(None) if i < x.ndim else None
for i in range(self.axis + 1))
x = x[ind]
if train:
channel = self.train_channel
else:
channel = self.eval_channel
if channel == 'random':
ch = numpy.random.randint(0, x.shape[self.axis])
else:
ch = channel
ind = tuple(slice(None) if i != self.axis else ch
for i in range(x.ndim))
return x[ind]