Changes in version 1.2.4

   * Clarifying documentation
   * Debugging seq_mult()

Changes in version 1.2.3

   * Debugging memento()

Changes in version 1.2.2

   * Addition of the memento() function, which remembers and outputs the result
   of a slow function. This is to avoid repeating unnecessary processing while
   tinkering with the code.
   * Debugging weldlog()

Changes in version 1.2.1

   * Debugging in.window()
   * Addition of data sets for illustration (see article in R Journal)

Changes in version 1.2.0

   * Addition of the in.window() function, that computes efficiently which data
   points in time-series fall in specific windows, even with irregular
   sampling rate
   * Improvement of multigons() and multilines() with mapply() rather than
   'for' loops

Changes in version 1.1.2

   * Removal of the welcome message (I got tired of it)
   * Debugging and optimising the pointsvg() function
   * Improving personalisation of the nlegend() function (& slight debugging)

Changes in version 1.1.1

   * Adaptation for R 4.0
   * Addition of the nset() function, that allows among others to take a fixed
   number of repeated succesive measurements of samples (i.e. replicates in
   successive lines in a data table), and reorganise them (for instance take the
   lines of 5 replicates of measurements, and reorganise them in 5 columns),
   typically to average them.
   * Addition of the pkgfind() functions, that allows to find a character
   pattern in the code of functions in an entire package.
   * Addition of a new set of functions to in fine compare sedimentation rates
   between sections correlated by tie-point. The strat.repair() function, among
   others is added to remove instantaneous deposits (e.g. turbidites) and add
   thickness estimated to be lost (i.e. hiatuses). This is still in development.
   * Fixed bug in are.lim.distinct() and shift()

Changes in version 1.1.0

   * Update to dplyr 1.0.0: fixed bug with tie.lim(),
     suppression of the mat.lag() and mat.lead() functions
     made obsolete by dplyr::lag() and dplyr::lead() now usable on matrices
