gaitmap.stride_segmentation.BaseDtwTemplate

class gaitmap.stride_segmentation.BaseDtwTemplate(*, scaling: BaseTransformer | None = None, use_cols: Sequence[str | int] | None = None)

Base class for dtw templates.

Note

This algorithm is only available via the gaitmap_mad package and distributed under a AGPL3 licence. To use it, you need to explicitly install the gaitmap_mad package. Learn more about that here.

Methods

clone()	Create a new instance of the class with all parameters copied over.
from_json(json_str)	Import an gaitmap object from its json representation.
get_data()	Return the template data.
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.
transform_data(data, sampling_rate_hz)	Transform external data according to the template scaling.

__init__(*, scaling: BaseTransformer | None = None, use_cols: Sequence[str | int] | None = None) → None

clone() → Self

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

classmethod from_json(json_str: str) → Self

Import an gaitmap object from its json representation.

For details have a look at the this example.

You can use the to_json method of a class to export it as a compatible json string.

Parameters:

json_str

json formatted string

get_data() → ndarray | DataFrame

Return the template data.

get_params(deep: bool = True) → dict[str, Any]

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.

set_params(**params: Any) → Self

Set the parameters of this Algorithm.

To set parameters of nested objects use nested_object_name__para_name=.

to_json() → str

Export the current object parameters as json.

For details have a look at the this example.

You can use the from_json method of any gaitmap algorithm to load the object again.

Warning

This will only export the Parameters of the instance, but not any results!

transform_data(data: DataFrame, sampling_rate_hz: float) → DataFrame

Transform external data according to the template scaling.

This method should be applied to the data before the template is matched. There is usually no need to do this manually, as all the implemented Dtw methods do this automatically internally.

Parameters:

dataSingleSensorData

The data to transform.

sampling_rate_hzfloat

The sampling rate of the data. This will be forwarded to the scaler, incase it is used.

Returns:

SingleSensorData

The transformed data.

Examples using gaitmap.stride_segmentation.BaseDtwTemplate

Optimizable Pipelines

Optimizable Pipelines

Cross Validation

Cross Validation