def merge(self, other):
'''
Merge another signal into this one.
The signal objects are concatenated horizontally
(column-wise, :func:`np.hstack`).
If the attributes of the two signal are not
compatible, an Exception is raised.
Required attributes of the signal are used.
'''
for attr in self._necessary_attrs:
if 'signal' != attr[0]:
if getattr(self, attr[0], None) != getattr(
other, attr[0], None):
raise MergeError(
"Cannot merge these two signals as the %s differ." %
attr[0])
if self.segment != other.segment:
raise MergeError(
"Cannot merge these two signals as they belong to different segments."
)
if hasattr(self, "lazy_shape"):
if hasattr(other, "lazy_shape"):
if self.lazy_shape[0] != other.lazy_shape[0]:
raise MergeError(
"Cannot merge signals of different length.")
merged_lazy_shape = (self.lazy_shape[0],
self.lazy_shape[1] + other.lazy_shape[1])
else:
raise MergeError(
"Cannot merge a lazy object with a real object.")
if other.units != self.units:
other = other.rescale(self.units)
stack = np.hstack((self.magnitude, other.magnitude))
kwargs = {}
for name in ("name", "description", "file_origin"):
attr_self = getattr(self, name)
attr_other = getattr(other, name)
if attr_self == attr_other:
kwargs[name] = attr_self
else:
kwargs[name] = "merge(%s, %s)" % (attr_self, attr_other)
merged_annotations = merge_annotations(self.annotations,
other.annotations)
kwargs.update(merged_annotations)
kwargs['array_annotations'] = self._merge_array_annotations(other)
signal = self.__class__(stack,
units=self.units,
dtype=self.dtype,
copy=False,
t_start=self.t_start,
sampling_rate=self.sampling_rate,
**kwargs)
signal.segment = self.segment
if hasattr(self, "lazy_shape"):
signal.lazy_shape = merged_lazy_shape
# merge channel_index (move to ChannelIndex.merge()?)
if self.channel_index and other.channel_index:
signal.channel_index = ChannelIndex(
index=np.arange(signal.shape[1]),
channel_ids=np.hstack([
self.channel_index.channel_ids,
other.channel_index.channel_ids
]),
channel_names=np.hstack([
self.channel_index.channel_names,
other.channel_index.channel_names
]))
else:
signal.channel_index = ChannelIndex(
index=np.arange(signal.shape[1]))
return signal
def merge(self, other):
'''
Merge another :class:`AnalogSignal` into this one.
The :class:`AnalogSignal` objects are concatenated horizontally
(column-wise, :func:`np.hstack`).
If the attributes of the two :class:`AnalogSignal` are not
compatible, an Exception is raised.
'''
if self.sampling_rate != other.sampling_rate:
raise MergeError("Cannot merge, different sampling rates")
if self.t_start != other.t_start:
raise MergeError("Cannot merge, different t_start")
if self.segment != other.segment:
raise MergeError(
"Cannot merge these two signals as they belong to different segments."
)
if hasattr(self, "lazy_shape"):
if hasattr(other, "lazy_shape"):
if self.lazy_shape[0] != other.lazy_shape[0]:
raise MergeError(
"Cannot merge signals of different length.")
merged_lazy_shape = (self.lazy_shape[0],
self.lazy_shape[1] + other.lazy_shape[1])
else:
raise MergeError(
"Cannot merge a lazy object with a real object.")
if other.units != self.units:
other = other.rescale(self.units)
stack = np.hstack(map(np.array, (self, other)))
kwargs = {}
for name in ("name", "description", "file_origin"):
attr_self = getattr(self, name)
attr_other = getattr(other, name)
if attr_self == attr_other:
kwargs[name] = attr_self
else:
kwargs[name] = "merge(%s, %s)" % (attr_self, attr_other)
merged_annotations = merge_annotations(self.annotations,
other.annotations)
kwargs.update(merged_annotations)
signal = AnalogSignal(stack,
units=self.units,
dtype=self.dtype,
copy=False,
t_start=self.t_start,
sampling_rate=self.sampling_rate,
**kwargs)
signal.segment = self.segment
# merge channel_index (move to ChannelIndex.merge()?)
if self.channel_index and other.channel_index:
signal.channel_index = ChannelIndex(
index=np.arange(signal.shape[1]),
channel_ids=np.hstack([
self.channel_index.channel_ids,
other.channel_index.channel_ids
]),
channel_names=np.hstack([
self.channel_index.channel_names,
other.channel_index.channel_names
]))
else:
signal.channel_index = ChannelIndex(
index=np.arange(signal.shape[1]))
if hasattr(self, "lazy_shape"):
signal.lazy_shape = merged_lazy_shape
return signal
