12 wrassp implementation

The libassp was originally written by Michel Scheffers as a C library which could be linked against or compiled into separate executable signal processing command line tools. To extend the legacy EMU system, the libassp it was integrated into it by using the Tcl Extension Architecture (TEA) to create a native extension to the Tcl programming language. The bulk of this work was done by Lasse Bombien in collaboration with Michel Scheffers. Lasse Bombien also implemented the tkassp user interface module as part of the legacy EMU system to allow the user full access to the functionality of the libassp from a GUI. The wrassp R package was written by Lasse Bombien and Raphael Winkelmann based on a similar approach as the tclassp port using the TEA. Since the libassp was put under the GPL version 3 (see https://www.gnu.org/licenses/gpl-3.0.en.html) by Michel Scheffers, the wrassp also carries this license.

12.1 The libassp port

Here, we briefly describe our strategy for porting the libassp to R. The port of the libassp to the R eco-system was achieved using the foreign language interface provided by the R system as is described in the R Extensions manual (see https://cran.r-project.org/doc/manuals/r-release/R-exts.htmlWriting). To port the various signal processing routines provided by the libassp and to avoid code redundancy a single C function called performAssp() was created. This function acts as a C wrapper function interface to libassp’s internal functions and handles the data conversion between libassp’s internal and R’s data structures. However, to provide the user with a clear and concise API we chose to implement separate R functions for every signal processing function. This also allowed us to formulate more concise manual entries for each of the signal processing function provided by wrassp. The R code snippet below is a pseudo-code example of the layout of each signal processing function wrassp provides.

To provide access to the file handling capabilities of the libassp, we implemented two C interface functions called getDObj2() (where 2 is simply used as a function version marker) and writeDObj(). These functions use libassp’s asspFOpen(), asspFFill(), asspFWrite() and asspFClose() function to read and write files supported by the libassp from and to files on disk into R. The public API functions read.AsspDataObj() and write.AsspDataObj() are the R wrapper functions around getDObj2() and writeDObj().

To be able to access some of libassp’s internal variables further wrapper functions were implemented. It was necessary to have access to these variables to be able to perform adequate parameter checks in various functions. The R code snippet below shows these functions.

##  [1] "RECTANGLE" "TRIANGLE"  "PARABOLA"  "COS"       "HANN"     
##  [6] "COS_3"     "COS_4"     "HAMMING"   "BLACKMAN"  "BLACK_X"  
## [11] "BLACK_3"   "BLACK_M3"  "BLACK_4"   "BLACK_M4"  "NUTTAL_3" 
## [16] "NUTTAL_4"  "GAUSS2_5"  "GAUSS3_0"  "GAUSS3_5"  "KAISER2_0"
## [21] "KAISER2_5" "KAISER3_0" "KAISER3_5" "KAISER4_0"
## [1] "ARF" "LAR" "LPC" "RFC"
## [1] "DFT" "LPS" "CSS" "CEP"

The wrassp package provides two R objects that contain useful information regarding the supported file format types (AsspFileFormats) and the output created by the various signal processing functions. The R code snippet below shows the content of these two objects.

##     RAW   ASP_A   ASP_B   XASSP  IPDS_M  IPDS_S    AIFF    AIFC     CSL 
##       1       2       3       4       5       6       7       8       9 
##    CSRE    ESPS     ILS     KTH   SWELL   SNACK     SFS     SND      AU 
##      10      11      12      13      13      13      14      15      15 
##    NIST  SPHERE PRAAT_S PRAAT_L PRAAT_B    SSFF    WAVE  WAVE_X  XLABEL 
##      16      16      17      18      19      20      21      22      24 
##    YORK     UWM 
##      25      26
## $ext
## [1] "acf"
## 
## $tracks
## [1] "acf"
## 
## $outputType
## [1] "SSFF"

As a final remark, it is worth noting that porting the C library libassp to R enables the functions provided by the wrassp package to run at near native speeds on every platform supported by R and avoids almost any interpreter overhead.