`gaitmap.base`.BaseSpatialParameterCalculation#

class gaitmap.base.BaseSpatialParameterCalculation[source]#

Base class for spatial parameter calculation.

Methods

`calculate`(stride_event_list, positions, ...)	Find spatial parameters in strides after segmentation and detecting events of each stride.
`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_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.

calculate(stride_event_list: DataFrame | dict[Union[collections.abc.Hashable, str], pandas.core.frame.DataFrame], positions: DataFrame | dict[Union[collections.abc.Hashable, str], pandas.core.frame.DataFrame], orientations: DataFrame | dict[Union[collections.abc.Hashable, str], pandas.core.frame.DataFrame], sampling_rate_hz: float) → Self[source]#: Find spatial parameters in strides after segmentation and detecting events of each stride.

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

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_json method of a class to export it as a compatible json string.

Parameters:

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:

set_params(**params: Any) → Self[source]#

Set the parameters of this Algorithm.

To set parameters of nested objects use nested_object_name__para_name=.

to_json() → str[source]#

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!

Examples using `gaitmap.base.BaseSpatialParameterCalculation`#