pynapple.Ts.count

Ts.count(bin_size=None, ep=None, time_units='s', dtype=None)

Count occurences of events within bin_size or within a set of bins defined as an IntervalSet. You can call this function in multiple ways :

1. tsd.count(bin_size=1, time_units = ‘ms’) -> Count occurence of events within a 1 ms bin defined on the time support of the object.

2. tsd.count(1, ep=my_epochs) -> Count occurent of events within a 1 second bin defined on the IntervalSet my_epochs.

3. tsd.count(ep=my_bins) -> Count occurent of events within each epoch of the intervalSet object my_bins

4. tsd.count() -> Count occurent of events within each epoch of the time support.

bin_size should be seconds unless specified. If bin_size is used and no epochs is passed, the data will be binned based on the time support of the object.

Parameters:

• bin_size (None or float, optional) – The bin size (default is second)

• ep (None or IntervalSet, optional) – IntervalSet to restrict the operation

• time_units (str, optional) – Time units of bin size (‘us’, ‘ms’, ‘s’ [default])

• dtype (type, optional) – Data type for the count. Default is np.int64.

Returns:

out – A Tsd object indexed by the center of the bins.

Return type:

Tsd

Examples

This example shows how to count timestamps within bins of 0.1 second.

>>> import pynapple as nap
>>> import numpy as np; np.random.seed(42)
>>> t = np.unique(np.sort(np.random.randint(0, 1000, 100))) # random times
>>> ts = nap.Ts(t=t, time_units='s')
>>> ts
Time (s)
1.0
13.0
20.0
21.0
34.0
58.0
71.0
...
897.0
931.0
942.0
955.0
957.0
975.0
shape: 94

ts is a timestamp object.

>>> ep = nap.IntervalSet(start = 0, end = 500, time_units = 's')
>>> ep
  index    start    end
      0        0    500
shape: (1, 2), time unit: sec.

ep is an IntervalSet object defining the epochs.

>>> bincount = ts.count(10.0, ep=ep)
>>> bincount
Time (s)
----------  --
5.0          1
15.0         1
25.0         2
35.0         1
45.0         0
55.0         1
...
445.0        0
455.0        3
465.0        1
475.0        3
485.0        1
495.0        1
dtype: int64, shape: (50,)
>>> bincount.time_support
  index    start    end
      0        0    500
shape: (1, 2), time unit: sec.

bincount automatically inherits ep as time support.