denspp.offline.preprocessing.frame_preprocessing

Module Contents

Functions

change_frame_size	Reducing the frame size of input frames to specific values Args: frames_in: input_values sel_pos: List with two elements in order to say position start and end Returns: frames with reduced size
generate_frames	Generating noisy spike frames
generate_zero_frames	Generating zero frames with noise for data augmentation
calculate_frame_mean	Calculating mean waveforms of spike waveforms
calculate_frame_median	Calculating mean waveforms of spike waveforms with median()
calculate_frame_snr	Calculating SNR of each cluster
frame_noise	Generation of noisy spike frames with AWGN with noise power [dB] in specific interval

API

denspp.offline.preprocessing.frame_preprocessing.change_frame_size(frames_in: numpy.ndarray, sel_pos: list) → numpy.ndarray

Reducing the frame size of input frames to specific values Args: frames_in: input_values sel_pos: List with two elements in order to say position start and end Returns: frames with reduced size

denspp.offline.preprocessing.frame_preprocessing.generate_frames(num: int, frame_in: numpy.ndarray, cluster_in: int, snr_out: list, fs: float = 20000.0) → [numpy.ndarray, numpy.ndarray]

Generating noisy spike frames

denspp.offline.preprocessing.frame_preprocessing.generate_zero_frames(frame_size: int, num_frames: int, noise_range: list) → tuple[numpy.ndarray, numpy.ndarray, numpy.ndarray]

Generating zero frames with noise for data augmentation

denspp.offline.preprocessing.frame_preprocessing.calculate_frame_mean(frames_in: numpy.ndarray, frames_cl: numpy.ndarray, do_integer_output: bool = False) → numpy.ndarray

Calculating mean waveforms of spike waveforms

denspp.offline.preprocessing.frame_preprocessing.calculate_frame_median(frames_in: numpy.ndarray, frames_cl: numpy.ndarray, do_integer_output: bool = False) → numpy.ndarray

Calculating mean waveforms of spike waveforms with median()

denspp.offline.preprocessing.frame_preprocessing.calculate_frame_snr(frames_in: numpy.ndarray, frames_cl: numpy.ndarray, frames_mean: numpy.ndarray) → numpy.ndarray

Calculating SNR of each cluster

Parameters:

• frames_in – Numpy array with spike frames

• frames_cl – Numpy array with cluster label to each spike frame

• frames_mean – Numpy array with mean waveforms of cluster

denspp.offline.preprocessing.frame_preprocessing.frame_noise(no_frames: int, frame_in: numpy.ndarray, noise_pwr: list, fs: float) → [numpy.ndarray, numpy.ndarray]

Generation of noisy spike frames with AWGN with noise power [dB] in specific interval