fps() from running properly when only one pattern was
supplied now fixed.tabulate_lod() function with methods of powdRfps and powdRafps
objects. Tabulates limit of detection estimates for all quantified phases in
a given sample.afps() function now accepts a logical skip_nnls argument. When
skip_nnls = TRUE, the non-negative least squares part of phase selection
is skipped.afsis data.
The phase IDs in the data have been modified for clarity, and the originals
are found in afsis_codes data that is also included with the package.rockjock and afsis reference libraries
now provided in rockjock_regroup and afsis_regroup, respectively.plot methods for powdRfps and powdRafps objects now accept a logical
group argument. When TRUE this results in reference patterns being
plotted grouped and summed by phase name.run_bkg()as_xy() added, which creates XY objects from data frames that contain
two columns denoting 2theta and counts.as_multi_xy() added, which creates a multiXY objects from a list of
``XYdata frames or a data frame containing data from multiple samples.multiXY` objects can easily be plotted using the new `plot.multiXY`
method, whilst `XY` objects can be plotted using the `plot.XY` method.align_xy() added with associated S3 methods for aligning XRPD data within
XY and multiXY objects to a chosen standard.multi_xy_to_df() added, which converts multiXY objects to data frames.interpolate() added, which contains methods for interpolating XY,
multiXY and powdRlib objects onto a new 2theta scale.merge() method added for powdRlib objects, which allows two powdRlib
objects to be merged into a single powdRlib object.extract_xy() added, which is a wrapper for read_xyData() from the
rxylib package. This function extracts any number of xy data frames from
various proprietary formats of X-ray powder diffraction data.read_xy() added, which reads any number of ASCII XY files.fps() and afps() now accept omit_std and closed arguments which are
used to specify how the phase concentrations are adjusted based on the
internal standard.normalise argument of fps() and afps() is now deprecated and
replaced with closed.omit_std() methods for powdRfps and powdRafps objects allows
for the internal standard concentration to be omitted from the output and
phase concentrations re-computed.close_quant() methods for powdRfps and powdRafps objects allows
for the quantitative composition to be closed so that it sums to 100 percent.delta(),
r() and rwp, respectively.powdRfps and powdRafps objects, derived from fps() and afps(),
respectively, now include data for the full 2theta range, even when discrete
limits are set using the tth_fps argument.plot.powdRfps and plot.powdRafps now include grey boxes for areas
that were excluded from the fitting process via the tth_fps argument. These
boxes can be turned off by setting the show_excluded argument to FALSE.fps_lm() added that facilitates non-quantitative full-pattern summation by
linear regression, yielding a powdRlm object. Derived coefficients may be
either positive or negative, making the function particularly suitable for
fitting the loadings from principal component analysis.plot method for powdRlm objects added.xrpd_pca() facilitates principal component analysis of XRPD patterns. The
derived loading for each dimension can be fitted to patterns within a
powdRlib reference library using fps_lm().fps() and afps() now accept diffraction data that has negative values for count
intensities. In such cases Rwp cannot be used as the objective function and R will
be used as the default instead.rwp item in the outputs from fps() and afps() has been renamed obj, which
contains a named vector of the values for three objective parameters: Rwp, R and
Delta.summarise_mineralogy now accepts two additional arguments: r and delta which are
logical parameters used to specify whether the R and Delta objective parameters,
respectively,are included in the summary table.powdRlib() now accepts a logical check_names argument. If TRUE (the default) then
the names of the variables are checked to ensure that they are syntactically valid and
are not duplicated.fps() and afps() is now supplied
(FALSE)powdRlib() now ensures that the phases object is a dataframe.regroup() allows for an alternative mineral grouping structure to be applied to
powdRfps and powdRafps objects.tth_transform() allows 2theta transformation between different monochromatic X-ray
wavelengths.fps() and afps() now accept a logical normalise argument, which allows the internal standard
concentration to be omitted and phase concentrations subsequently normalised to sum to 100 %.fps() now accepts the force argument, forcing phases to remain in the final output even if their
coefficients are negative.fps() and afps() will now stop if any of the phases specified in the refs argument are not
in the library.fps() and afps().summarise_mineralogy() now accepts single samples (i.e. a list of 1 powdRfps or powdRafps object).utils no longer in imports (hence fixing associated note in CRAN checks).plot() methods for powdRfps and powdRafps objects now include mode
and xlim arguments, allowing for different plot types and x-axis adjustment.DT and shinyWidgets now defined in namespace.powdRlib() no longer orders the reference patterns alphabetically, and instead
retains the original order that they are supplied in.fps() and afps().fps() and afps() no longer require the shift_res argument.fps() and afps().The refs argument of fps() and subset() now accepts phase names as well as phase ID's. For example, if
the phase name "Quartz" in supplied, then all phase ID's associated with Quartz will be selected.
Similarly, the force argument of afps() now accepts both phase names and phase ID's.
summarise_mineralogy() now contains an optional rwp argument (default = FALSE). This is a logical
parameter used to define whether the Rwp should be included in the summary table as a measure of the
difference between the measured and fitted patterns.
When the std_conc argument is supplied to fps() or afps(), the computed phase concentrations now
include that of the internal standard.
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
alignment 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()).