ktk.TimeSeries.from_array#

static TimeSeries.from_array(array, /, *, data_key='data', time=[], time_info={'Unit': 's'}, data_info={}, events=[])[source]#

Create a new TimeSeries from an array.

Parameters

  • array (ArrayLike) – An array or list where the first dimension corresponds to time.

  • data_key (str) – Optional. The name of the data (used as the key in the TimeSeries’ data attribute). Default is “data”.

  • time (ArrayLike) – Optional. An array that indicates the time for each sample. Its length must match the first dimension of the data array. If None (default), a matching time attribute of with a period of one second is created.

  • time_info (dict[str, Any]) – Optional. Will be copied to the TimeSeries’ time_info attribute.

  • data_info (dict[str, dict[str, Any]]) – Optional. Will be copied to the TimeSeries’ data_info attribute.

  • events (list[kineticstoolkit.timeseries.TimeSeriesEvent]) – Optional. Will be copied to the TimeSeries’ events attribute.

Returns

The new TimeSeries.

Return type

TimeSeries

See also

ktk.TimeSeries.to_array, ktk.TimeSeries.from_dataframe, ktk.TimeSeries.to_dataframe

Examples

Using default time

>>> ktk.TimeSeries([0.1, 0.2, 0.3, 0.4, 0.5])
TimeSeries with attributes:
         time: array([0., 1., 2., 3., 4.])
         data: {'data': array([0.1, 0.2, 0.3, 0.4, 0.5])}
    time_info: {'Unit': 's'}
    data_info: {}
       events: []

Specifiying time

>>> ktk.TimeSeries([0.1, 0.2, 0.3, 0.4, 0.5], time=[0.1, 0.2, 0.3, 0.4, 0.5])
TimeSeries with attributes:
         time: array([0.1, 0.2, 0.3, 0.4, 0.5])
         data: {'data': array([0.1, 0.2, 0.3, 0.4, 0.5])}
    time_info: {'Unit': 's'}
    data_info: {}
       events: []