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]