pynapple.core.ts_group.TsGroup.merge#

TsGroup.merge(*tsgroups, reset_index=False, reset_time_support=False, ignore_metadata=False)[source]#

Merge the TsGroup object with other TsGroup objects. Common uses include adding more neurons/channels (supposing each Ts/Tsd corresponds to data from a neuron/channel) or adding more trials (supposing each Ts/Tsd corresponds to data from a trial).

Parameters:

*tsgroups (TsGroup) – The TsGroup objects to merge with
reset_index (bool, optional) – If True, the keys will be reset to range(len(data)) If False, the keys of the TsGroup objects should be non-overlapping and will be preserved
reset_time_support (bool, optional) – If True, the merged TsGroup will merge time supports from all the Ts/Tsd objects in data If False, the time support of the TsGroup objects should be the same and will be preserved
ignore_metadata (bool, optional) – If True, the merged TsGroup will not have any metadata columns other than ‘rate’ If False, all metadata columns should be the same and all metadata will be concatenated

Returns:

A TsGroup of merged objects

Return type:

TsGroup

Raises:

TypeError – If the input objects are not TsGroup objects
ValueError – If ignore_metadata=False but metadata columns are not the same If reset_index=False but keys overlap If reset_time_support=False but time supports are not the same

Examples

>>> import pynapple as nap
>>> time_support_a = nap.IntervalSet(start=-1, end=1, time_units='s')
>>> time_support_b = nap.IntervalSet(start=-5, end=5, time_units='s')

>>> dict1 = {0: nap.Ts(t=[-1, 0, 1], time_units='s')}
>>> tsgroup1 = nap.TsGroup(dict1, time_support=time_support_a)

>>> dict2 = {10: nap.Ts(t=[-1, 0, 1], time_units='s')}
>>> tsgroup2 = nap.TsGroup(dict2, time_support=time_support_a)

>>> dict3 = {0: nap.Ts(t=[-.1, 0, .1], time_units='s')}
>>> tsgroup3 = nap.TsGroup(dict3, time_support=time_support_a)

>>> dict4 = {10: nap.Ts(t=[-1, 0, 1], time_units='s')}
>>> tsgroup4 = nap.TsGroup(dict2, time_support=time_support_b)

Merge with default options if have the same time support and non-overlapping indexes:

>>> tsgroup_12 = tsgroup1.merge(tsgroup2)
>>> tsgroup_12
Index    rate
-------  ------
     0     1.5
    10     1.5

Set reset_index=True if indexes are overlapping:

>>> tsgroup_13 = tsgroup1.merge(tsgroup3, reset_index=True)
>>> tsgroup_13
Index    rate
-------  ------
      0     1.5
      1     1.5

Set reset_time_support=True if time supports are different:

>>> tsgroup_14 = tsgroup1.merge(tsgroup4, reset_time_support=True)
>>> tsgroup_14
>>> tsgroup_14.time_support
Index    rate
-------  ------
      0     0.3
     10     0.3

start end

0 -5 5 shape: (1, 2), time unit: sec.