- New feature events_find(): is now able to combine multiple digital input channels, retrieve events from the combined events channel and differentiate between the inputs that occur simultaneously.
- eda_sympathetic() has been reviewed: low-pass filter and resampling have been added to be in line with the original paper
- eda_findpeaks() using methods proposed in nabian2018 is reviewed and improved. Differentiation has been added before smoothing. Skin conductance response criteria have been revised based on the original paper.
- Allow for input with NaNs and extrapolation in signal_interpolate()
- Add argument method in find_outliers()
- A lot (see #645)
- Add new time-domain measures in hrv_time(): Prc20NN, Prc80NN, MinNN, and MaxNN
- Argument type changed to out in expspace()
- Add new time-domain measures in hrv_time(): Prc20NN, Prc80NN, MinNN, and MaxNN
- Allow fix_peaks() to account for larger intervals
- Argument r changed to radius in fractal_correlation()
- Argument r changed to tolerance in entropy and complexity utility functions
- Argument r_method changed to tolerance_method in complexity_optimize()
- complexity_lempelziv(), fractal_higuchi(), fractal_katz(), fractal_correlation(), fractal_dfa(), entropy_multiscale(), entropy_shannon(), entropy_approximate(), entropy_fuzzy(), entropy_sample() now return a tuple consisting of the complexity index, and a dictionary comprising of the different parameters specific to the measure. For fractal_katz() and entropy_shannon(), the parameters dictionary is empty.
- Restructure complexity submodules with optimization files starting with optim_*, such as optim_complexity_delay(), optim_complexity_dimension(), optim_complexity_k(), optim_complexity_optimize(), and optim_complexity_tolerance().
- mutual_information() moved from stats module to complexity module.
- Added various complexity indices: complexity_hjorth(), complexity_hurst(), complexity_lyapunov(), complexity_rqa(), complexity_rr(), entropy_coalition(), entropy_permutation(), entropy_range(), entropy_spectral(), fractal_nld(), fractal_psdslope(), fractal_sda(), fractal_sevcik()
- Added mne_templateMRI() as a helper to get MNE's template MRI.
- Added eeg_source() as a helper to perform source reconstruction.
- Added eeg_source_extract() to extract the activity from a brain region.
- Added parallel_run() in misc as a parallel processing utility function.
- Added find_plateau() in misc to find the point of plateau in an array of values.
- Added write_csv() in data to facilitate saving dataframes into multiple parts.
- Added more complexity-related functions, entropy_cumulative_residual(), entropy_differential(), entropy_svd(), fractal_petrosian(), and information_fisher().
- Updates logic to find kmax in fractal_higuchi()
- Add RSP_Amplitude_Baseline in event-related analysis
- Add argument add_firstsamples in mne_channel_extract() to account for first sample attribute in mne raw objects
- Allow plotting of mne.Epochs in epochs_plot()
- Add mne_crop() to crop mne Raw objects with additional flexibility to specify first and last elements
- Plotting function in eeg_badchannels() to visualize overlay of individual EEG channels and highlighting of bad ones
- Add eog_peaks() as wrapper for eog_findpeaks()
- Allow ecg_delineate() to account for different heart rate
- Ensure detected offset in emg_activation() is not beyond signal length
- Raise ValueError in _hrv_sanitize_input() if RRIs are detected instead of peaks
- Ensure that multifractal DFA indices returned by fractal_mdfa() is not Nan when array of slopes contains Nan (due to zero fluctuations)
- Documentation of respiration from peak/trough terminology to inhale/exhale onsets
- Change labelling in rsp_plot() from "inhalation peaks" and "exhalation troughs" to "peaks (exhalation onsets)" and "troughs (inhalation onsets)" respectively.
- Change RSP_Amplitude_Mean/Min/Max parameters to be corrected based on value closest to t=0 in event-related analysis, rather than using all pre-zero values.
- Have rsp_rrv() compute breath-to-breath intervals based on trough indices (inhalation onsets) rather than peak indices
- Compute rsp_rate() based on trough indices (rather than peak indices) in 'periods' method
- Adjust kmax parameter in fractal_higuchi() according to signal length as having kmax more than half of signal length leads to division by zero error
- Ensure that sanitization of input in _hrv_dfa() is done before windows for DFA_alpha2 is computed
- np.seterr is added to fractal_dfa() to avoid returning division by zero warning which is an expected behaviour
- fractal_df() now returns a dictionary of windows, fluctuations and the slope value (see documentation for more information. If multifractal is True, the dictionary additionally contains the parameters of the singularity spectrum (see singularity_spectrum() for more information)
- Add convenience function intervals_to_peaks() useful for RRI or BBI conversion to peak indices
- hrv_nonlinear() and rrv_rsp() now return the parameters of singularity spectrum for multifractal DFA analysis
- Add new complexity measures in fractal_higuchi(), fractal_katz() and fractal_lempelziv()
- Add new time-domain measures in hrv_time(): SDANN and SDNNI
- Add new non-linear measures in hrv_nonlinear(): ShanEn, FuzzyEn, HFD, KFD and LZC
- Add path argument in mne_data() and throw warning to download mne datasets if data folder is not present
- The implementation of TTIN in hrv_time() is amended to its correct formulation.
- The default binsize used for RRI histogram in the computation of geometric HRV indices is set to 1 / 128 seconds
- None
- Add internal function for detecting missing data points and forward filling missing values in nk.*_clean() functions
- Add computation of standard deviation in eventrelated() functions for ECG_Rate_SD, EMG_Amplitude_SD, EOG_Rate_SD, PPG_Rate_SD, RSP_Rate_SD, RSP_Amplitude_SD
- Add labelling for interval related features if a dictionary of dataframes is passed
- Retrun Q peaks and S Peaks information for wavelet-based methods in nk.ecg_delineate()
- Fix epochs columns with dtype: object generated by nk.epochs_create()
- Bug fix ecg_findpeaks_rodrigues for array out of bounds bug
- Additional features for nk.rsp_intervalrelated(): average inspiratory and expiratory durations, inspiratory-to-expiratory (I/E) time ratio
- Add multiscale entropy measures (MSE, CMSE, RCMSE) and fractal methods (Detrended Fluctuation Analysis, Correlation Dimension) into nk.hrv_nonlinear()
- Allow for data resampling in nk.read_bitalino()
- Add bio_resting_8min_200hz into database for reading with nk.data()
- Reading of url links in nk.data()
- Allow for nk.hrv() to compute RSA indices if respiratory data is present
- All hrv functions to automatically detect correct sampling rate if tuple or dict is passed as input
- Add support for PPG analysis: nk.ppg_eventrelated(), nk.ppg_intervalrelated(), nk.ppg_analyze()
- Add Zhao et al. (2018) method for nk.ecg_quality()
- Add tests for epochs module
- Add sub-epoch option for ECG and RSP event-related analysis:
- users can create a smaller sub-epoch within the event-related epoch
- the rate-related features of ECG and RSP signals are calculated over the sub-epoch
- the remaining features are calculated over the original epoch, not the sub-epoch
- Fix propagation of values in nk.signal_formatpeaks() for formatting SCR column outputs generated by eda_peaks()
- Fix docstrings of nk.rsp_phase(), from "RSP_Inspiration" to "RSP_Phase"
- Update signal_filter() method for rsp_clean(): to use sos form, instead of ba form of butterworth (similar to eda_clean())
- Use duration from nk.events_find() as epochs_end in nk.epochs_create()
- Allow customized subsets of epoch lengths in nk.bio_analyze() with window_lengths argument
- Add nk.find_outliers() to identify outliers (abnormal values)
- Add utility function - nk.check_type() to return appropriate boolean values of input (integer, list, ndarray, pandas dataframe or pandas series)
- (experimental) Add error bars in the summary plot method to illustrate standard error of each bin
- Fix type of value in nk.signal_formatpeaks() to ensure slice assignment is done on the same type
- First release on PyPI.