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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 `XY data 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()).
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.