| Title: | Spectroscopy Related Utilities |
|---|---|
| Description: | Utility functions for spectroscopy. 1. Functions to simulate spectra for use in teaching or testing. 2. Functions to process files created by 'LoggerPro' and 'SpectraSuite' software. |
| Authors: | Bryan A. Hanson DePauw University, Greencastle Indiana USA |
| Maintainer: | Bryan A. Hanson <[email protected]> |
| License: | GPL-3 |
| Version: | 0.2.7 |
| Built: | 2025-02-03 02:37:32 UTC |
| Source: | https://github.com/bryanhanson/spechelpers |
SpecHelpers: Spectroscopy Related Utilities
Utility functions for spectroscopy. 1. Functions to simulate spectra for use in teaching or testing. 2. Functions to process files created by LoggerPro and SpectraSuite software.
Bryan A. Hanson, DePauw University, Greencastle Indiana USA
This function reads a csv file containing columns of wavelength and absorbances. It rounds the wavelengths to integers and replaces the absorbances corresponding to the rounded values with their averages. NOTE THAT ALL THE csv FILES IN THE CURRENT DIRECTORY ARE PROCESSED AND REPLACED WITH THE MODIFIED FILEs. You should use this function on a copy of the directory.
avgLambda()avgLambda()
The original files are overwritten with the modified files.
Bryan A. Hanson, DePauw University
gatherSpecFiles which is the function the user should
call.
This data set gives wavelengths every 1.0 nm, along with the associated CIE xyz values for the spectral locus of the 1931 CIE chromaticity diagram. They are called xyz values here as they are called that in the original source, but they are also known as xyY or XYZ values.
CIExyzCIExyz
A data frame with 4400 observations each with the following 4 variables:
wavelength in nm
x values
y values
z values
Bryan A. Hanson, DePauw University. [email protected]
Color Vision Research Lab. cvrl.ioo.ucl.ac.uk/index.htm Go to this URL, then choose 'NEW CIE XYZ...' In the new page that opens, go to 'New physiologically-relevant CIE x,y chromaticity coordinates (proposed)' and get the 2-deg coordinates at 1.0 nm resolution
plotCIEchrom for examples of this data in use.
data(CIExyz)data(CIExyz)
This function plots an annotated electromagnetic spectrum. There are options to include annotations about the molecular effects and/or typical applications in technology.
emSpectrum(molecular = TRUE, applications = TRUE)emSpectrum(molecular = TRUE, applications = TRUE)
molecular |
Logical. Add annotations about molecular effects? |
applications |
Logical. Add annotations about applications? |
None. Side effect is a plot.
The diagram is wider than a standard R graphics device.
You should send it to a pdf or similar device
with the width set to 11" or so.
Obviously not to scale, but hopefully aesthetically pleasing!
Bryan A. Hanson, DePauw University. [email protected]
dev.new(width = 10.5, height = 3) emSpectrum() emSpectrum(molecular = FALSE, applications = FALSE) dev.off()dev.new(width = 10.5, height = 3) emSpectrum() emSpectrum(molecular = FALSE, applications = FALSE) dev.off()
This function processes csv files containing two columns, wavelength and absorbance (or intensity etc), into a data frame, which is then written out as a csv file. The files should have no header row.
gatherCsv()gatherCsv()
It is assumed that the csv files have already been cleaned up so that they contain only wavelength and absorbance data. The wavelength data column must be the same in all the files (as they would be if they came from the same instrument with the same settings).
A data frame containing the wavelengths in the first column and the absorbances in the other columns, one per file, with the file name generating the column name. The data frame is written out in a file called "All Spec Files.csv".
Bryan A. Hanson, DePauw University
gatherSpecFiles which is the function the user should
call.
This function will go through all the files of a specified format in a directory and convert them into a data frame with one column containing the wavelength information and the other columns the absorbances of each sample (file). The file names are used to create the column names in the data frame. Optionally, non-integer wavelengths in the file can be combined to give integer wavelengths. Keep in mind that this function specifically modifies formats written by LoggerPro. Each format, as it comes from LoggerPro, has various amounts of crap in it which has to be removed or modified.
gatherSpecFiles(type = "txt", intLambda = FALSE, ...)gatherSpecFiles(type = "txt", intLambda = FALSE, ...)
type |
A character string giving the type of files to be processed. Currently, either "txt", "csv" or "cmbl" extensions can be processed. |
intLambda |
Logical. If TRUE, non-integer wavelengths that round to the same value will be combined and averaged and reported as integer values. |
... |
Other parameters to be passed downstream. Currently none possible. |
All files of a given extension in the directory will be processed, so make certain there are no extra files in the directory. The files will be modified and written back out as .csv files so look for the number of files in the directory to double. In the case of csv files, the original csv files will be overwritten. These files have no header row.
A data frame containing the wavelengths in the first column and the absorbances in the other columns, one column per file, with column names generated from the file names.
Bryan A. Hanson, DePauw University
Computes the y values describing a Gaussian distribution given a range of x values and parameters for mu, sigma, and area. A tail may be introduced into the curve to simulate the behavior of some chromatography peaks.
gaussCurve(x, area, mu, sigma, tail)gaussCurve(x, area, mu, sigma, tail)
x |
A vector of x values which will be used to compute the corresponding y values. Use enough to give good resolution. |
area |
The area of the peak, in arbitrary units. |
mu |
The position of the peak. Must fall in the range of x, of course. |
sigma |
The standard deviation of the peak. |
tail |
A value describing any tailing desired. If NA, no tailing is applied. |
A vector of y values corresponding to the x values supplied.
Bryan A. Hanson, DePauw University. [email protected]
lorentzCurve, makeSpec which uses this
function to make either spectra or chromatograms.
### A pure Gaussian curve myx <- seq(0, 100, length.out = 1000) # use lots of point for resolution myy <- gaussCurve(x = myx, area = 1, mu = 40, sigma = 1.5, tail = NA) plot(myx, myy, type = "l", main = "Pure Gaussian Curve") ### Now with tailing myy2 <- gaussCurve(x = myx, area = 1, mu = 40, sigma = 1.5, tail = 0.1) plot(myx, myy2, type = "l", main = "Gaussian Curve with Tailing")### A pure Gaussian curve myx <- seq(0, 100, length.out = 1000) # use lots of point for resolution myy <- gaussCurve(x = myx, area = 1, mu = 40, sigma = 1.5, tail = NA) plot(myx, myy, type = "l", main = "Pure Gaussian Curve") ### Now with tailing myy2 <- gaussCurve(x = myx, area = 1, mu = 40, sigma = 1.5, tail = 0.1) plot(myx, myy2, type = "l", main = "Gaussian Curve with Tailing")
These functions provide a simple way of storing white point and gamut data for use in drawing CIE chromaticity diagrams.
getGamutValues(gamut) getWhiteValues(white)getGamutValues(gamut) getWhiteValues(white)
gamut |
A character string giving the name of the desired gamut. One of
|
white |
The desired white point value. One of |
A data frame with columns x, y containing the vertices of the requested gamut in CIE chromaticity coordinates, or, for a white point, a data frame containing the coordinates of the requested white point.
Bryan A. Hanson, DePauw University. [email protected]
plotCIEchrom for examples of this function in use.
This function creates sequences, centered on zero, which correspond to odd
or even NMR multiplets. Not intended for direct use. Called by
plotNMRspec.
jSeq(length.out)jSeq(length.out)
length.out |
An integer giving the number of peaks in the sequence. |
A vector describing the spacing of the parts of an NMR multiplet in terms of multiples of the coupling constant, J.
Bryan A. Hanson, DePauw University. [email protected]
plotNMRspec which calls this function.
tmp <- jSeq(5) # a multiplet with an odd number of peaks tmp tmp <- jSeq(6) # an even number tmptmp <- jSeq(5) # a multiplet with an odd number of peaks tmp tmp <- jSeq(6) # an even number tmp
Computes the y values describing a Lorentzian curve such as seen in an NMR peak. Requires a range of x values and parameters for peak position, area, and gamma (half the peak width at half-height).
lorentzCurve(x, x0, area, gamma)lorentzCurve(x, x0, area, gamma)
x |
A vector of x values which will be used to compute the corresponding y values. Use enough to give good resolution. |
x0 |
The position of the peak. Must fall in the range of x, of course. |
area |
The area of the peak, in arbitrary units. |
gamma |
HWHM, half-width at half-maximum. The peak "width" in units corresponding to x. |
A vector of y values corresponding to the x values supplied.
Bryan A. Hanson, DePauw University. [email protected]
gaussCurve, makeSpec,
plotNMRspec
and plot2DNMRspec for drawing NMR spectra.
myx <- seq(0, 100, length.out = 1000) # use lots of point for resolution myy <- lorentzCurve(x = myx, area = 1, x0 = 40, gamma = 5) plot(myx, myy, type = "l", main = "Pure Lorentzian Curve") y = 0.5*max(myy) x = seq(40, 45, 0.5) points(x = x, y = rep(y, length(x)), col = "blue", type = "l") text(x = 42, y = y + 0.005, labels = c("gamma"), col = "blue", srt = 90)myx <- seq(0, 100, length.out = 1000) # use lots of point for resolution myy <- lorentzCurve(x = myx, area = 1, x0 = 40, gamma = 5) plot(myx, myy, type = "l", main = "Pure Lorentzian Curve") y = 0.5*max(myy) x = seq(40, 45, 0.5) points(x = x, y = rep(y, length(x)), col = "blue", type = "l") text(x = 42, y = y + 0.005, labels = c("gamma"), col = "blue", srt = 90)
This function creates a chromatogram or spectrum from a list of appropriate
parameters describing the peaks. The individual curves are computed using
the mathematical definition of either a Gaussian curve, possibly with
tailing, or a Lorentzian curve. Gaussian curves are appropriate for
simulating chromatograms or UV-Vis spectra, while Lorentzians are
used for simulating NMR peaks. The function computes the individual curves
as well as their sum (which is the whole chromatogram or spectrum). A plot
can be made, which may display the separate underlying curves. If you want
to draw NMR spectra, use plotNMRspec which is a much more
natural interface to this function.
makeSpec(peak.list, x.range, plot = TRUE, curves = FALSE, type = "gauss", noise = 0, dd = 1, ...)makeSpec(peak.list, x.range, plot = TRUE, curves = FALSE, type = "gauss", noise = 0, dd = 1, ...)
peak.list |
For a Gaussian curve, a data frame with the following columns: mu, sd, area, tail. mu is the retention time (or center frequency). sd is the standard deviation (or peak width). area is the area under the peak. tail is the tailing parameter - use NA when a pure Gaussian with no tailing is desired. One row of the data frame contains data related to one peak. For a Lorentzian curve, a data frame with the following columns: x0, area, gamma. x0 is the center frequency or chemical shift. gamma is the half the peak width at half-height. area is the area under the peak. |
x.range |
A numeric vector of length 2 giving the retention time range
(or frequency range) desired. Must make sense in light of the peak list
given (i.e. a wider range, possibly much wider depending up the values of
|
plot |
Logical; if TRUE, a plot is produced. |
curves |
Logical; if TRUE, the individual curves are plotted (provided
|
type |
A character string. Use "gauss" to generate Gaussian curves (for chromatograms, or UV-Vis spectra). Use "lorentz" to generate Lorentzian curves as found in NMR spectra. |
noise |
A number giving the amount of noise to be added to the
individual curves (the net spectrum has the noise from the individual
spectra, it has no additional noise added to it). Value corresponds to the
argument |
dd |
The density of data points per unit of |
... |
Additional arguments to be passed downstream. |
A matrix containing the x values (retention times or
frequencies) in the first row, and the complete chromatogram (spectrum) in
the second row. Additional rows contain chromatograms (spectra) of the
individual components. The row names of the data frame are character
strings describing the chromatogram (spectrum) in that row. The matrix
contains dd*abs(diff(x.range)) columns.
Bryan A. Hanson, DePauw University. [email protected]
gaussCurve, lorentzCurve,
plotNMRspec and plot2DNMRspec, the preferred
interfaces for drawing NMR spectra.
### A simple chromatogram chrom <- data.frame(mu = c(2, 5, 11), sd = c(0.5, 1, 2), area = c(1, 0.5, 1), tail = c(NA, NA, 0.1)) ex1 <- makeSpec(chrom, x.range = c(0, 20), plot = TRUE, curves = TRUE, dd = 5, main = "Chromatogram with Underlying Pure Curves") ### Faux ethyl group NMR with J = 0.1 ppm. # Note that a much better # NMR spectrum can be generated using plotNMRspec which also uses # a more natural input format # spec <- data.frame(mu = c(3.5, 3.4, 3.3, 3.2, 1.4, 1.3, 1.2), sd = rep(0.01, 7), tail = rep(NA, 7), area = c(1, 3, 3, 1, 1, 2, 1) * c(0.5, 0.5, 0.5, 0.5, 0.66, 0.66, 0.66)) ex2 <- makeSpec(spec, x.range = c(5, 0), plot = TRUE, curves = FALSE, dd = 100, main = "Simulated 1H NMR of an Ethyl Group")### A simple chromatogram chrom <- data.frame(mu = c(2, 5, 11), sd = c(0.5, 1, 2), area = c(1, 0.5, 1), tail = c(NA, NA, 0.1)) ex1 <- makeSpec(chrom, x.range = c(0, 20), plot = TRUE, curves = TRUE, dd = 5, main = "Chromatogram with Underlying Pure Curves") ### Faux ethyl group NMR with J = 0.1 ppm. # Note that a much better # NMR spectrum can be generated using plotNMRspec which also uses # a more natural input format # spec <- data.frame(mu = c(3.5, 3.4, 3.3, 3.2, 1.4, 1.3, 1.2), sd = rep(0.01, 7), tail = rep(NA, 7), area = c(1, 3, 3, 1, 1, 2, 1) * c(0.5, 0.5, 0.5, 0.5, 0.66, 0.66, 0.66)) ex2 <- makeSpec(spec, x.range = c(5, 0), plot = TRUE, curves = FALSE, dd = 100, main = "Simulated 1H NMR of an Ethyl Group")
This function simulates 2D NMR spectra. Only 1st order coupling can be handled – there is currently no capacity for doublet of doublets and other such peaks. The field strength of the "instrument" is taken into account.
plot2DNMRspec(peaks, x.range = c(0, 12), MHz = 300, ppHz = 1, type = "COSY", M = NULL, levels = seq(0.5, 1, by = 0.1), ...)plot2DNMRspec(peaks, x.range = c(0, 12), MHz = 300, ppHz = 1, type = "COSY", M = NULL, levels = seq(0.5, 1, by = 0.1), ...)
peaks |
A data frame with the following columns: delta, mult (multiplicity), J, area, pw. Multiplicity should be given by a number, so use 2 for a doublet. J is in Hz (use 0 for singlets). pw is the peak width at half-height in Hz. |
x.range |
A numeric vector of length 2 giving the ppm range desired. Must be increasing. |
MHz |
Integer. The operating frequency of the instrument, in MHz. |
ppHz |
Points per Hz: The number of data points per Hz to use in
calculating the spectrum (passed as argument |
type |
The type of 2D spectrum desired. One of |
M |
An adjacency matrix indicating which peaks are coupled.
The order of rows and columns must be the same as in |
levels |
A vector of levels for the contour plot. Must be in (0...1). |
... |
Parameters to be passed to the plotting function. |
Returns a matrix.
Bryan A. Hanson, DePauw University. [email protected]
### ethyl 2-ethyl-3-oxobutyrate ### Set up data peaks1 <- data.frame( # A B C D E F delta = c(4.20, 3.34, 2.23, 1.88, 1.28, 0.94), mult = c(4, 3, 1, 5, 3, 3), J = c(14, 14, 0, 14, 14, 14), area = c(2, 1, 3, 2, 3, 3), pw = c(2, 2, 2, 2, 2, 2)) # A, B, C, D, E, F AM <- matrix(c(0, 0, 0, 0, 1, 0, # A 0, 0, 0, 1, 0, 0, # B 0, 0, 0, 0, 0, 0, # C 0, 1, 0, 0, 0, 1, # D 1, 0, 0, 0, 0, 0, # E 0, 0, 0, 1, 0, 0), # F ncol = 6) ### 1D 1H NMR plot for reference # CRAN checks will skip some examples to save time jnk <- plotNMRspec(peaks = peaks1, x.range = c(0, 5), MHz = 500, main = "1H NMR of ethyl 2-ethyl-3-oxobutyrate") ### 2D COSY plot res <- plot2DNMRspec(peaks = peaks1, x.range = c(0, 5), MHz = 500, ppHz = 1, M = AM, main = "COSY of ethyl 2-ethyl-3-oxobutyrate") ### 2D TOCSY plot ## Not run: res <- plot2DNMRspec(peaks = peaks1, x.range = c(0, 5), MHz = 500, ppHz = 1, levels = c(0.85, 0.9, 0.95), type = "TOCSY", main = "TOCSY of ethyl 2-ethyl-3-oxobutyrate") ## End(Not run)### ethyl 2-ethyl-3-oxobutyrate ### Set up data peaks1 <- data.frame( # A B C D E F delta = c(4.20, 3.34, 2.23, 1.88, 1.28, 0.94), mult = c(4, 3, 1, 5, 3, 3), J = c(14, 14, 0, 14, 14, 14), area = c(2, 1, 3, 2, 3, 3), pw = c(2, 2, 2, 2, 2, 2)) # A, B, C, D, E, F AM <- matrix(c(0, 0, 0, 0, 1, 0, # A 0, 0, 0, 1, 0, 0, # B 0, 0, 0, 0, 0, 0, # C 0, 1, 0, 0, 0, 1, # D 1, 0, 0, 0, 0, 0, # E 0, 0, 0, 1, 0, 0), # F ncol = 6) ### 1D 1H NMR plot for reference # CRAN checks will skip some examples to save time jnk <- plotNMRspec(peaks = peaks1, x.range = c(0, 5), MHz = 500, main = "1H NMR of ethyl 2-ethyl-3-oxobutyrate") ### 2D COSY plot res <- plot2DNMRspec(peaks = peaks1, x.range = c(0, 5), MHz = 500, ppHz = 1, M = AM, main = "COSY of ethyl 2-ethyl-3-oxobutyrate") ### 2D TOCSY plot ## Not run: res <- plot2DNMRspec(peaks = peaks1, x.range = c(0, 5), MHz = 500, ppHz = 1, levels = c(0.85, 0.9, 0.95), type = "TOCSY", main = "TOCSY of ethyl 2-ethyl-3-oxobutyrate") ## End(Not run)
This function draws the 1931 CIE chromaticity diagram with various decorations and annotations.
plotCIEchrom(gradient = NULL, colSpace = "sRGB", ex = 1, opts = c("D65", "specLocus", "purples"), title = NULL, ...)plotCIEchrom(gradient = NULL, colSpace = "sRGB", ex = 1, opts = c("D65", "specLocus", "purples"), title = NULL, ...)
gradient |
Character: either |
colSpace |
Character string giving the color space to use for
drawing the gradient. One of |
ex |
Numeric. The 'exposure' to use. The exposure must be
used with extreme care. Larger values of |
opts |
A character vector of options to be employed. One or
more of c("D65", "D50", "C", "E", "specLocus", "purples", "Munsell",
"sRGB", "SWOP", "Apple", "NTSC", "Adobe", "CIE"). The first few of
these are reference white points. |
title |
A character string to be plotted at the top of the diagram. If NULL, the title defaults to "1931 CIE Chromaticity Diagram". If no title is desired, set it to an empty string. |
... |
Additional arguments to be passed downstream, to |
A plot is drawn using grid graphics.
The appearance of the color gradient will vary with the device, surface and incident light used to view it and is not likely correct anywhere. The appearance varies strongly with exposure.
Bryan A. Hanson, DePauw University. [email protected]
For opts = "Munsell"
the Munsell designation by wavelength are taken from Romney & Indow
pnas.org/cgi/doi/10.1073/pnas.162368999
require("grid") plotCIEchrom() # no gradient ## These are a too slow for CRAN checks: ## Not run: plotCIEchrom(gradient = "sl") # basic plot # Notice there is not much yellow in that plot. Increase # the exposure to bring in some yellow, at the expense of some blues: plotCIEchrom(gradient = "sl", ex = 1.4) # Next show a gradient for the CMYK printing process # and outline the colors a typical monitor can display. plotCIEchrom(gradient = getGamutValues("SWOP"), opts = c("D65", "SWOP", "sRGB")) ## End(Not run)require("grid") plotCIEchrom() # no gradient ## These are a too slow for CRAN checks: ## Not run: plotCIEchrom(gradient = "sl") # basic plot # Notice there is not much yellow in that plot. Increase # the exposure to bring in some yellow, at the expense of some blues: plotCIEchrom(gradient = "sl", ex = 1.4) # Next show a gradient for the CMYK printing process # and outline the colors a typical monitor can display. plotCIEchrom(gradient = getGamutValues("SWOP"), opts = c("D65", "SWOP", "sRGB")) ## End(Not run)
This function simulates simple NMR spectra. Only 1st order coupling can be handled – there is currently no capacity for doublet of doublets and other such peaks. The field strength of the "instrument" is taken into account.
plotNMRspec(peaks, x.range = c(12, 0), MHz = 300, ppHz = 1, nuclei = "1H", pkLabs = TRUE, lab.pos = NULL, plot = TRUE, ...)plotNMRspec(peaks, x.range = c(12, 0), MHz = 300, ppHz = 1, nuclei = "1H", pkLabs = TRUE, lab.pos = NULL, plot = TRUE, ...)
peaks |
A data frame with the following columns: delta, mult (multiplicity), J, area, pw. Multiplicity should be given by a number, so use 2 for a doublet. J is in Hz (use 0 for singlets). pw is the peak width at half-height in Hz. |
x.range |
A numeric vector of length 2 giving the ppm range desired. |
MHz |
Integer. The operating frequency of the instrument, in MHz. |
ppHz |
Integer, but numeric works too!
Points per Hz: The number of data points per Hz to use in
calculating the spectrum (passed as argument |
nuclei |
Character. One of |
pkLabs |
Logical. If |
lab.pos |
A vector of label positions as along as the number of rows in
|
plot |
Logical: Shall a plot be made? |
... |
Other parameters to be passed downstream. These may affect
the plot. You can also include |
Returns a data frame of the type produced by makeSpec.
See there for details. x values are in Hz.
Note that this function uses Hz internally so that the x.range, which
is in ppm, is multiplied by Mhz before being sent to
makeSpec, and once there, makeSpec will multiply it by
ppHz. Thus the total data points used is floor(ppHz * Mhz *
abs(diff(x.range))). This approach ensures that peaks are not distorted
when changing x.range for the same peak.list.
Note that ppHz can be numeric as well, due to the use of floor.
This can be useful: if you wanted your simulated NMR spectrum to be composed
of exactly 16384 data points as real data might be, you can call the function
with ppHz specified like ppHz = 2^14/(12*500) and it works!
Bryan A. Hanson, DePauw University. [email protected]
### A simulated 1H NMR spectrum peaks1 <- data.frame( delta = c(1.3, 3.75, 3.9, 10.2), mult = c(3, 4, 2, 1), J = c(14, 14, 14, 0), area = c(3, 2, 1, 1), pw = c(2, 2, 2, 10)) res <- plotNMRspec(peaks1, x.range = c(12, 0), MHz = 500, main = "500 MHz Simulated 1H NMR Spectrum") ### Compare to the same data at 200 MHz and plot together par(mfrow = c(2,1)) res <- plotNMRspec(peaks1, x.range = c(12, 0), MHz = 500, main = "500 MHz Simulated 1H NMR Spectrum") res <- plotNMRspec(peaks1, x.range = c(12, 0), MHz = 200, main = "200 MHz Simulated 1H NMR Spectrum") par(mfrow = c(1,1)) ### Zoom in to show off par(mfrow = c(2,1)) res <- plotNMRspec(peaks1, x.range = c(4.5, 1), MHz = 500, main = "500 MHz Simulated 1H NMR Spectrum") res <- plotNMRspec(peaks1, x.range = c(4.5, 1), MHz = 200, main = "200 MHz Simulated 1H NMR Spectrum") par(mfrow = c(1,1)) ### A simulated 13C NMR spectrum # This is substantially slower due to the large # chemical shift range peaks2 <- data.frame( delta = c(160, 155, 145, 143, 135, 60, 32), mult = rep(1, 7), J = rep(1, 7), area = c(0.1, 0.3, 0.3, 1, 1, 0.5, 0.5), pw = rep(1, 7)) res <- plotNMRspec(peaks2, x.range = c(180, 0), MHz = 200, main = "200 MHz Simulated 13C NMR Spectrum", ppHz = 4, pkLabs = FALSE, nuclei = "13C") # Try repeating the above with ppHz = 1; note the peaks heights are not quite right # as there are not enough data points to define the peak properly.### A simulated 1H NMR spectrum peaks1 <- data.frame( delta = c(1.3, 3.75, 3.9, 10.2), mult = c(3, 4, 2, 1), J = c(14, 14, 14, 0), area = c(3, 2, 1, 1), pw = c(2, 2, 2, 10)) res <- plotNMRspec(peaks1, x.range = c(12, 0), MHz = 500, main = "500 MHz Simulated 1H NMR Spectrum") ### Compare to the same data at 200 MHz and plot together par(mfrow = c(2,1)) res <- plotNMRspec(peaks1, x.range = c(12, 0), MHz = 500, main = "500 MHz Simulated 1H NMR Spectrum") res <- plotNMRspec(peaks1, x.range = c(12, 0), MHz = 200, main = "200 MHz Simulated 1H NMR Spectrum") par(mfrow = c(1,1)) ### Zoom in to show off par(mfrow = c(2,1)) res <- plotNMRspec(peaks1, x.range = c(4.5, 1), MHz = 500, main = "500 MHz Simulated 1H NMR Spectrum") res <- plotNMRspec(peaks1, x.range = c(4.5, 1), MHz = 200, main = "200 MHz Simulated 1H NMR Spectrum") par(mfrow = c(1,1)) ### A simulated 13C NMR spectrum # This is substantially slower due to the large # chemical shift range peaks2 <- data.frame( delta = c(160, 155, 145, 143, 135, 60, 32), mult = rep(1, 7), J = rep(1, 7), area = c(0.1, 0.3, 0.3, 1, 1, 0.5, 0.5), pw = rep(1, 7)) res <- plotNMRspec(peaks2, x.range = c(180, 0), MHz = 200, main = "200 MHz Simulated 13C NMR Spectrum", ppHz = 4, pkLabs = FALSE, nuclei = "13C") # Try repeating the above with ppHz = 1; note the peaks heights are not quite right # as there are not enough data points to define the peak properly.
This function creates a gradient to fill the CIE chromaticity diagram.
prepCIEgradient(vertices = NULL, colSpace = "sRGB", ex = 1, ...)prepCIEgradient(vertices = NULL, colSpace = "sRGB", ex = 1, ...)
vertices |
The vertices of a polygon that is to be filled with the gradient. |
colSpace |
Character. The color space model to use. |
ex |
Numeric. The exposure factor. This shifts the gradient.
Be extremely careful with this. See |
... |
Arguments to be passed downstream. |
An array containing the data needed to draw the gradient.
Bryan A. Hanson, DePauw University. [email protected]
plotCIEchrom for examples of this function in use.
Given a molecular formula, this function computes the mass of the parent ion, including any M + n peaks due to Br or Cl, and plots it. Intended to draw the parent ion region for small organic molecules, especially those with Br or Cl.
qMS(f = NULL, xlab = "m/z", ylab = "intensity", main = "Mass Spectrum", ...)qMS(f = NULL, xlab = "m/z", ylab = "intensity", main = "Mass Spectrum", ...)
f |
A character string giving the molecular formula of the molecule of interest. Order of elements does not matter. Elements should be given as their atomic symbols, e.g. "Br" not "br". |
xlab |
A character string giving the x axis label. |
ylab |
A character string giving the y axis label. |
main |
A character string giving the title of the plot. |
... |
Additional arguments to be passed downstream. |
The function currently accepts formulas containing C, H, N, O, Br and Cl in any quantities.
Draws a plot. Returns a data frame giving the peak masses and relative intensites.
Bryan A. Hanson, DePauw University. [email protected]
ms <- qMS(f = "C5H8BrCl", xlim = c(150, 200), main = "Parent Ion of C5H8BrCl")ms <- qMS(f = "C5H8BrCl", xlim = c(150, 200), main = "Parent Ion of C5H8BrCl")
These functions clean out extraneous information from exported spectral data
files and then write them out in csv format. txt2csv and cmbl2csv handle
files exported by LoggerPro software. sstab2csv handles files exported by
Spectra Suite software. Not directly called by the user.
txt2csv(in.file = "", out.file = "")txt2csv(in.file = "", out.file = "")
in.file |
The name of the input file. |
out.file |
The name of the output file. |
Extraneous text at the beginning of the file is removed. In the case of cmbl files, lines containing "Z2" or ">" are removed. Absorbances marked as "Z1" are replaced with zero. The data are initially in one long column; the wavelength and absorbances are reunited into two columns.
A modifed file in csv format.
Bryan A. Hanson, DePauw University.
gatherSpecFiles which is the function the user should
call.