ravetools 0.0.6

• Added decibel average in pwelch
• Allowed pwelch sampling frequency to be greater than the signal length
• Adjusted parameters diagnostic plot and pwelch plot to properly handle graph text, margin, axis
• Added plot_signals to plot multiple functional data within the same canvas

ravetools 0.0.5

• Exposed C++ code to inst/includes so other users can dynamically link to the functions (https://github.com/dipterix/ravetools/issues/5)
• Removed confusing in-place arguments in the fftw related code
• Corrected fftw plans to respect the flags
• Added C++ to convert raw binary bytes to uint, int, float, and string

ravetools 0.0.4

Parallel processes might use different temporary directory paths. To improve the performance, it is recommended to set a shared temporary directory, hence this version

• Allows temporary directories to be set via environment variable RAVETOOLS_TEMPDIR or option ravetools.tempdir.

ravetools 0.0.3

This version fixes a memory issue reported by CRAN check (gcc-UBSAN).

• There is a potential integer overflow where NA_INTEGER is subtracted by one before being converted to R_xlen_t type. This update fixes this issue
• Removed RcppParallel and copied part of it into inst/include folder, with TBB removed under the GPL-3 license framework.

ravetools 0.0.2

This is an initial version of ravetools. Although a bare minimal set of signal processing functions are provided, it is sufficient to perform preprocess pipelines on most iEEG signals. Some functions are added from the dipsaus package, with considerable performance improvement. The C++ functions have been tested on all major platforms, with different architectures (ARM, i386, x64).

Documentation

• Added README file to demonstrate basic usage
• Added a NEWS.md file to track changes to the package.

Signal processing functions

• Re-implemented decimate with FIR filters creating the same results as in Matlab
• Added detrend function to
• Added diagnose_channel to visually inspect channel signals
• Added morlet_wavelet to enable fast and memory efficient wavelet decomposition; the result agrees with existing Matlab code with floating errors (10^-7)
• Added multitaper
• Added pwelch (Welch periodogram)
• Added notch_filter to remove line noise

High-performance functions

The following functions are implemented in C++ parallel. They tend to be faster than normal base-R implementations, depending on the number of CPU cores used.

• Added collapse to collapse arrays
• Added shift_array to shift array along certain indices
• Added fast_cov to calculate pearson covariance matrix in parallel
• Added baseline_array to calculate baseline arrays with multiple margins