Outputs from fps() and afps() (powdRfps and powdRafps objects, respectively) contain an inputs component. This provides a list of each of the arguments (including defaults) used to produce the fit.
summarise_mineralogy() is a new function that creates a summary table from lists containing multiple powdRfps and/or powdRafps objects.
A comprehensive reference library of pure phases from the RockJock computer software is now provided as an example powdRlib object called rockjock. This library covers most clay, non-clay and amorphous phases that may be encountered in soil samples. The library can be loaded into the global environment via data(rockjock). Data of synthetic mineral mixtures are also now provided in the rockjock_mixtures data, which can be used to test the accuracy of full pattern summation via the fps() and afps() functions.
fps() and afps() now accept “L-BFGS-B” in the solver argument. If selected, this uses L-BFGS-B optimisation constrained so that parameters cannot be lower than zero.
fps() now contains an optional shift argument, identical to that already implemented in afps(). This defines the 2\(\theta\) range within with a grid-search algorithm can optimise the aligment of standards to the sample. If not defined in the function call it defaults to 0.
fps() and afps() now have a shift_res argument which accepts a single integer to define the increase in resolution used during grid search shifting. Higher values facilitate finer shifts at the expense of longer computation. If not defined in the function call it defaults to 4.
fps() and afps() now have a logical manual_align argument which specifies whether to manually align the sample to the value specified in the align argument (manual_align = TRUE), or optimise the alignment based on a maximum shift defined in the align argument (manual_align = FALSE).
fps() and afps() now have a logical harmonise argument which specifies whether to automatically harmonise the sample and library onto the same 2\(\theta\) scale via linear interpolation.
The lod argument of afps(), now simply represents an estimate of the limit of detection of the selected internal standard defined by the std argument. The function then uses the reference intensity ratios to estimate limits of detection for all other phases.
fps() now contains an optional remove_trace argument that allows the user to exclude phases below a small trace value that would unlikely be detected. Default = 0.
subset() is a new function that allows simple subsetting of a powdRlib object.
The run_powdR() shiny app now contains tabs for subsetting a powdRlib object via subset() function, editingpowdRfps and powdRafps objects, and video tutorials.
Suggests packages nnls (>=1.4), baseline (>= 1.2) and shinyWidgets (>= 0.4.3) in the DESCRIPTION.
fps() now accepts “NNLS” in the solver argument. If “NNLS” (non-negative least squares) is selected, the algorithm uses non negative least squares instead of minimising an objective function. This is a much faster alternative but less accurate for samples containing amorphous phases.
bkg() is a new function that allows for backgrounds to be fitted to XRPD data. It is a wrapper of the baseline::baseline.fillPeaks() method, and the output is a powdRbkg object.
afps() is a new function that automates the process of full pattern summation by firstly selecting samples from the reference library (using NNLS) and then excluding those estimated to be below detection limit. The output is a powdRafps object.
New plot() methods for powdRbkg and powdRafps objects
The shiny application behind run_powdR() has been updated to accept “NNLS”, and now includes tabs for background fitting (using bkg()) and automated full pattern summation (using afps()).