gaitmap.base.BaseEventDetection#
- class gaitmap.base.BaseEventDetection[source]#
Base class for all event detection algorithms.
Methods
clone()Create a new instance of the class with all parameters copied over.
detect(data, *[, stride_event_list])Find gait events in data within strides provided by roi_list.
from_json(json_str)Import an gaitmap object from its json representation.
get_params([deep])Get parameters for this algorithm.
set_params(**params)Set the parameters of this Algorithm.
to_json()Export the current object parameters as json.
- __init__(*args, **kwargs)#
- clone() Self[source]#
Create a new instance of the class with all parameters copied over.
This will create a new instance of the class itself and all nested objects
- detect(data: DataFrame | dict[Union[collections.abc.Hashable, str], pandas.core.frame.DataFrame], *, stride_event_list: DataFrame | None = None, sampling_rate_hz: float) Self[source]#
Find gait events in data within strides provided by roi_list.
- classmethod from_json(json_str: str) Self[source]#
Import an gaitmap object from its json representation.
For details have a look at the this example.
You can use the
to_jsonmethod of a class to export it as a compatible json string.- Parameters:
- json_str
json formatted string
- get_params(deep: bool = True) dict[str, Any][source]#
Get parameters for this algorithm.
- Parameters:
- deep
Only relevant if object contains nested algorithm objects. If this is the case and deep is True, the params of these nested objects are included in the output using a prefix like
nested_object_name__(Note the two “_” at the end)
- Returns:
- params
Parameter names mapped to their values.
