backend.data.RawData

class backend.data.RawData(num_channels=16, buffer_size=2000, buffer=None)

This class holds the full numpy buffer of emg data, the current timestep buffer that is filled by the emg thread, and the full timestep buffer of emg data that the current_timestep is appended to

excluded_params = ['current_buffer', 'raw_timesteps']

__init__(num_channels=16, buffer_size=2000, buffer=None)

Initialize self. See help(type(self)) for accurate signature.

property n_chan

property buffer_size

get_params()

Returns dict of this object’s attributes, excluding any attributes in the excluded_params list

get_settings_params()

Returns only the settings-related params; not the data

update_from_params(params: dict)

Update this object’s attributes using the params dict. Any attributes in the excluded_params list will not be updated

update_current_buffer(idx, idx_step)

Updates the full buffer from the given idx of the timestep buffer

concat_all_timesteps()

useful debugging utility for getting all raw data timesteps into one array

static concatenate(*raw_data_objects)

Used to concatentate multiple RawData objects

clear_data(keep_buffer=False)

Clear the data while leaving settings unchanged

slice(start=None, end=None, bools=None)

Returns a new data object created from slicing the current data from start to end, or using the bools list of indices

process_new_timestep(new_data: numpy.ndarray, save_raw=True, filter_timing_history=None)

Process the newest timestep of raw data, returning the current filtered buffer.

More specifically, this appends the new_data to the current_buffer and to the raw_timesteps list if save_raw is True, and then filters the current buffer and returns it.

IMPORTANT new_data should have the newest samples first