pynapple.TsdFrame.value_from#
- TsdFrame.value_from(data, ep=None, mode='closest')[source]#
Replace the value with the closest value from Tsd/TsdFrame/TsdTensor argument
- Parameters:
data (Tsd, TsdFrame or TsdTensor) – The object holding the values to replace.
ep (IntervalSet (optional)) – The IntervalSet object to restrict the operation. If None, the time support of the tsd input object is used.
mode (literal, either 'closest', 'before', 'after') – If closest, replace value with value from Tsd/TsdFrame/TsdTensor, if before gets the first value before, if after the first value after.
- Returns:
out – Object with the new values
- Return type:
Examples
In this example, the tsdframe object will receive the closest values in time from a tsd.
>>> 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 >>> tsdframe = nap.TsdFrame(t=t, d=np.random.randn(len(t), 3), time_units='s') >>> tsdframe Time (s) 0 1 2 ---------- ---------- ---------- --------- 1.0 -2.17833 -1.0439 0.172694 13.0 0.324199 0.74586 -1.83658 20.0 0.564464 0.0255007 0.473193 21.0 0.659191 2.34075 1.07099 34.0 0.0964165 0.419102 -0.953028 58.0 -1.04787 -1.87568 -1.36678 71.0 0.636305 -0.906721 0.476043 ... 875.0 -0.9812 -1.23823 -0.824651 897.0 1.95128 -0.0400851 0.529436 931.0 -0.183892 -0.0900786 -0.50588 942.0 0.050744 0.4946 1.67831 955.0 -1.87447 1.61082 0.52796 957.0 -0.367763 -0.547723 1.04368 975.0 0.228979 -1.53407 0.36307 dtype: float64, shape: (94, 3)
tsdframe is a timestamp table with values.
>>> tsd_from = nap.Tsd(t=np.arange(0,1000), d=np.random.choice([1,2,3], 1000), time_units='s') >>> tsd_from Time (s) ---------- -- 0.0 3 1.0 1 2.0 3 3.0 1 4.0 3 5.0 1 6.0 2 ... 993.0 1 994.0 2 995.0 3 996.0 1 997.0 3 998.0 2 999.0 3 dtype: int64, shape: (1000,)
tsd_from contains values, for example the tracking data.
>>> ep = nap.IntervalSet(start = 0, end = 500, time_units = 's') >>> ep index start end 0 0 500 shape: (1, 2), time unit: sec.
An epoch can be passed to restrict the operation.
>>> tsd_after = tsdframe.value_from(tsd_from, ep, mode='closest') >>> tsd_after Time (s) ---------- -- 1.0 1 13.0 3 20.0 3 21.0 2 34.0 1 58.0 3 71.0 3 ... 459.0 2 466.0 2 474.0 3 475.0 1 476.0 2 484.0 2 491.0 3 dtype: int64, shape: (53,)
tsd_after is the same length as ts when restricted to ep.
>>> print(len(tsdframe.restrict(ep)), len(tsd_after)) 53 53