read.data: Read geochronological data
In pvermees/IsoplotR: Statistical Toolbox for Radiometric Geochronology
read.data R Documentation
Read geochronological data
Description
Cast a .csv file or a matrix into one of IsoplotR's
data classes
Usage
read.data(x, ...)
## Default S3 method:
read.data(
x,
method = "U-Pb",
format = 1,
ierr = 1,
d = diseq(),
Th02i = c(0, 0),
Th02U48 = c(0, 0, 1e+06, 0, 0, 0, 0, 0, 0),
U8Th2 = 0,
...
)
## S3 method for class 'data.frame'
read.data(
x,
method = "U-Pb",
format = 1,
ierr = 1,
d = diseq(),
Th02i = c(0, 0),
Th02U48 = c(0, 0, 1e+06, 0, 0, 0, 0, 0, 0),
U8Th2 = 0,
...
)
## S3 method for class 'matrix'
read.data(
x,
method = "U-Pb",
format = 1,
ierr = 1,
d = diseq(),
Th02i = c(0, 0),
Th02U48 = c(0, 0, 1e+06, 0, 0, 0, 0, 0, 0),
U8Th2 = 0,
...
)
Arguments
x
either a file name (.csv format) OR a matrix
...
optional arguments to the read.csv function
method
one of 'U-Pb', 'Pb-Pb', 'Th-Pb',
'Ar-Ar', 'K-Ca', 'detritals',
'Rb-Sr', 'Sm-Nd', 'Re-Os', 'Th-U',
'U-Th-He', 'fissiontracks' or 'other'
format
formatting option, depends on the value of
method.
if method='U-Pb', then format is one of either:
X=07/35, err[X], Y=06/38, err[Y], rho[X,Y]
X=38/06, err[X],Y=07/06, err[Y] (, rho[X,Y])
X=07/35, err[X], Y=06/38, err[Y],
Z=07/06, err[Z] (, rho[X,Y]) (, rho[Y,Z])
X=07/35, err[X], Y=06/38, err[Y], Z=04/38,
rho[X,Y], rho[X,Z], rho[Y,Z]
X=38/06, err[X], Y=07/06, err[Y],
Z=04/06, err[Z] (, rho[X,Y], rho[X,Z], rho[Y,Z])
07/35, err[07/35], 06/38, err[06/38],
04/38, err[04/38], 07/06, err[07/06],
04/07, err[04/07], 04/06, err[04/06]
W=07/35, err[W], X=06/38, err[X],
Y=08/32, err[Y], Z=32/38, err[Z],
(rho[W,X], rho[W,Y], rho[W,Z], rho[X,Y],
rho[X,Z], rho[Y,Z])
W=38/06, err[W], X=07/06, err[X],
Y=08/06, err[Y], (Z=32/38, err[Z],
rho[W,X], rho[W,Y], rho[W,Z], rho[X,Y],
rho[X,Z], rho[Y,Z])
X=38/06, err[X], Y=04/06, err[Y], (rho[X,Y])
X=35/07, err[X], Y=04/07, err[Y], (rho[X,Y])
X=38/06, err[X], Y=08/06, err[Y],
(Z=32/38, err[Z], rho[X,Y], rho[X,Z], rho[Y,Z])
X=35/07, err[X], Y=08/07, err[Y],
(Z=32/38, err[Z], rho[X,Y], rho[X,Z], rho[Y,Z])
where optional columns are marked in round brackets
if method='Pb-Pb', then format is one of either:
6/4, err[6/4], 7/4, err[7/4], rho
4/6, err[4/6], 7/6, err[7/6], rho
6/4, err[6/4], 7/4, err[7/4], 6/7, err[6/7]
if method='Th-Pb', then format is one of either:
32/04, err[32/04], 08/04, err[08/04], rho
32/08, err[32/08], 04/08, err[08/04], rho
32/04, err[32/04], 08/04,
err[08/04], 32/08, err[32/08]
if method='Ar-Ar', then format is one of either:
9/6, err[9/6], 0/6, err[0/6], rho (, 39)
6/0, err[6/0], 9/0, err[9/0] (, rho) (, 39)
9/0, err[9/0], 6/0, err[6/0], 9/6, err[9/6] (, 39)
if method='K-Ca', then format is one of either:
K40/Ca44, err[K40/Ca44], Ca40/Ca44, err[Ca40/Ca44], rho
K40/Ca40, err[K40/Ca40], Ca44/Ca40, err[Ca44/Ca40], rho
K40/Ca44, err[K40/Ca44], Ca40/Ca44,
err[Ca40/Ca44], K40/Ca40, err[K40/Ca40]
if method='Rb-Sr', then format is one of either:
Rb87/Sr86, err[Rb87/Sr86], Sr87/Sr86, err[Sr87/Sr86] (, rho)
Rb87/Sr87, err[Rb87/Sr87], Sr86/Sr87, err[Sr86/Sr87] (, rho)
Rb, err[Rb], Sr, err[Sr], Sr87/Sr86, err[Sr87/Sr86]
where Rb and Sr are in ppm
if method='Sm-Nd', then format is one of either:
Sm147/Nd144, err[Sm147/Nd144], Nd143/Nd144, err[Nd143/Nd144] (, rho)
Sm147/Nd143, err[Sm147/Nd143], Nd144/Nd143, err[Nd144/Nd143] (, rho)
Sm, err[Sm], Nd, err[Nd], Nd143/Nd144, err[Nd143/Nd144]
where Sm and Nd are in ppm
if method='Re-Os', then format is one of either:
Re187/Os188, err[Re187/Os188], Os187/Os188, err[Os187/Os188] (, rho)
Re187/Os187, err[Re187/Os187], Os188/Os187, err[Os188/Os187] (, rho)
Re, err[Re], Os, err[Os], Os187/Os188, err[Os187/Os188]
where Re and Os are in ppm
if method='Lu-Hf', then format is one of either:
Lu176/Hf177, err[Lu176/Hf177], Hf176/Hf177, err[Hf176/Hf177] (, rho)
Lu176/Hf176, err[Lu176/Hf176], Hf177/Hf176, err[Hf177/Hf176] (, rho)
Lu, err[Lu], Hf, err[Hf], Hf176/Hf177, err[Hf176/Hf177]
where Lu and Hf are in ppm
if method='Th-U', then format is one of either:
X=8/2, err[X], Y=4/2, err[Y], Z=0/2, err[Z],
rho[X,Y], rho[X,Z], rho[Y,Z]
X=2/8, err[X], Y=4/8, err[Y], Z=0/8, err[Z],
rho[X,Y], rho[X,Z], rho[Y,Z]
X=8/2, err[X], Y=0/2, err[Y], rho[X,Y]
X=2/8, err[X], Y=0/8, err[Y], rho[X,Y]
where all values are activity ratios
if method='fissiontracks', then format is one of
either:
the External Detector Method (EDM), which requires a
\zeta-calibration constant and its uncertainty, the induced
track density in a dosimeter glass, and a table with the
spontaneous and induced track densities.
LA-ICP-MS-based fission track data using the
\zeta-calibration method, which requires a 'session
\zeta' and its uncertainty and a table with the number of
spontaneous tracks, the area over which these were counted and one
or more U/Ca- or U-concentration measurements and their analytical
uncertainties.
LA-ICP-MS-based fission track data using the 'absolute
dating' method, which only requires a table with the the number of
spontaneous tracks, the area over which these were counted and one
or more U/Ca-ratios or U-concentration measurements (in ppm) and
their analytical uncertainties.
if method='other', then format is one of either:
1:X
2:X, err[X]
3:f, X, err[X]
4:X, err[X], Y, err[Y], rho
5:X/Z, err[X/Z], Y/Z, err[Y/Z], X/Y, err[X/Y]
6:a n x (n+1) matrix obtained by prepending a
vector of alternating X,Y-values to its covariance matrix
ierr
indicates whether the analytical uncertainties of the
input are provided as:
1: 1\sigma absolute uncertainties.
2: 2\sigma absolute uncertainties.
3: 1\sigma relative uncertainties (\%).
4: 2\sigma relative uncertainties (\%).
d
an object of class diseq.
Th02i
2-element vector with the assumed initial
^{230}Th/^{232}Th-ratio of the detritus (for
Th-U formats 1 and 2) and its standard error.
Th02U48
9-element vector with the measured composition of
the detritus, containing X=0/8, sX, Y=2/8,
sY, Z=4/8, sZ, rXY, rXZ,
rYZ.
U8Th2
^{238}U/^{232}Th activity-ratio of the
whole rock. Used to estimate the initial
^{230}Th/^{238}U disequilibrium (for Th-U formats 3
and 4).
Details
IsoplotR provides the following example input files:
U-Pb: UPb1.csv, UPb2.csv, UPb3.csv,
UPb4.csv, UPb5.csv, UPb6.csv,
UPb7.csv, UPb8.csv
Pb-Pb: PbPb1.csv, PbPb2.csv, PbPb3.csv
Th-Pb: ThPb1.csv, ThPb2.csv, ThPb3.csv
Ar-Ar: ArAr1.csv, ArAr2.csv, ArAr3.csv
K-Ca: KCa1.csv, KCa2.csv, KCa3.csv
Re-Os: ReOs1.csv, ReOs2.csv, ReOs3.csv
Sm-Nd: SmNd1.csv, SmNd2.csv, SmNd3.csv
Rb-Sr: RbSr1.csv, RbSr2.csv, RbSr3.csv
Lu-Hf: LuHf1.csv, LuHf2.csv, LuHf3.csv
Th-U: ThU1.csv, ThU2.csv, ThU3.csv
ThU4.csv
fissiontracks: FT1.csv, FT2.csv,
FT3.csv
U-Th-He: UThHe.csv, UThSmHe.csv
detritals: DZ.csv
other: LudwigMixture.csv, LudwigMean.csv,
LudwigKDE.csv, LudwigSpectrum.csv
The contents of these files can be viewed using the
system.file(...) function. For example, to read the
ArAr1.csv file:
fname <- system.file('ArAr1.csv',package='IsoplotR')
ArAr <- read.data(fname,method='Ar-Ar',format=1)
Value
An object of class UPb, PbPb, ThPb,
KCa, RbSr, SmNd, LuHf, ReOs,
UThHe, fissiontracks, detritals or
PD. See classes for further details.
See Also
examples, settings
Examples
f1 <- system.file("UPb1.csv",package="IsoplotR")
file.show(f1) # inspect the contents of 'UPb1.csv'
d1 <- read.data(f1,method="U-Pb",format=1)
concordia(d1)
f2 <- system.file("ArAr1.csv",package="IsoplotR")
d2 <- read.data(f2,method="Ar-Ar",format=1)
agespectrum(d2)
f3 <- system.file("ReOs1.csv",package="IsoplotR")
d3 <- read.data(f3,method="Re-Os",format=1)
isochron(d2)
f4 <- system.file("FT1.csv",package="IsoplotR")
d4 <- read.data(f4,method="fissiontracks",format=1)
radialplot(d4)
f5 <- system.file("UThSmHe.csv",package="IsoplotR")
d5 <- read.data(f5,method="U-Th-He")
helioplot(d5)
f6 <- system.file("ThU2.csv",package="IsoplotR")
d6 <- read.data(f6,method="Th-U",format=2)
evolution(d6)
# one detrital zircon U-Pb file (detritals.csv)
f7 <- system.file("DZ.csv",package="IsoplotR")
d7 <- read.data(f7,method="detritals")
kde(d7)
# four 'other' files (LudwigMixture.csv, LudwigSpectrum.csv,
# LudwigMean.csv, LudwigKDE.csv)
f8 <- system.file("LudwigMixture.csv",package="IsoplotR")
d8 <- read.data(f8,method="other",format=2)
radialplot(d8)
pvermees/IsoplotR documentation built on Nov. 18, 2024, 1:02 a.m.
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| read.data | R Documentation |
Read geochronological data
Description
Cast a .csv file or a matrix into one of IsoplotR's
data classes
Usage
read.data(x, ...)
## Default S3 method:
read.data(
x,
method = "U-Pb",
format = 1,
ierr = 1,
d = diseq(),
Th02i = c(0, 0),
Th02U48 = c(0, 0, 1e+06, 0, 0, 0, 0, 0, 0),
U8Th2 = 0,
...
)
## S3 method for class 'data.frame'
read.data(
x,
method = "U-Pb",
format = 1,
ierr = 1,
d = diseq(),
Th02i = c(0, 0),
Th02U48 = c(0, 0, 1e+06, 0, 0, 0, 0, 0, 0),
U8Th2 = 0,
...
)
## S3 method for class 'matrix'
read.data(
x,
method = "U-Pb",
format = 1,
ierr = 1,
d = diseq(),
Th02i = c(0, 0),
Th02U48 = c(0, 0, 1e+06, 0, 0, 0, 0, 0, 0),
U8Th2 = 0,
...
)
Arguments
x |
either a file name ( |
... |
optional arguments to the |
method |
one of |
format |
formatting option, depends on the value of
if
where optional columns are marked in round brackets if
if
if
if
if
where if
where if
where if
where if
where all values are activity ratios if
if
|
ierr |
indicates whether the analytical uncertainties of the input are provided as:
|
d |
an object of class |
Th02i |
2-element vector with the assumed initial
|
Th02U48 |
9-element vector with the measured composition of
the detritus, containing |
U8Th2 |
|
Details
IsoplotR provides the following example input files:
U-Pb:
UPb1.csv,UPb2.csv,UPb3.csv,UPb4.csv,UPb5.csv,UPb6.csv,UPb7.csv,UPb8.csvPb-Pb:
PbPb1.csv,PbPb2.csv,PbPb3.csvTh-Pb:
ThPb1.csv,ThPb2.csv,ThPb3.csvAr-Ar:
ArAr1.csv,ArAr2.csv,ArAr3.csvK-Ca:
KCa1.csv,KCa2.csv,KCa3.csvRe-Os:
ReOs1.csv,ReOs2.csv,ReOs3.csvSm-Nd:
SmNd1.csv,SmNd2.csv,SmNd3.csvRb-Sr:
RbSr1.csv,RbSr2.csv,RbSr3.csvLu-Hf:
LuHf1.csv,LuHf2.csv,LuHf3.csvTh-U:
ThU1.csv,ThU2.csv,ThU3.csvThU4.csvfissiontracks:
FT1.csv,FT2.csv,FT3.csvU-Th-He:
UThHe.csv,UThSmHe.csvdetritals:
DZ.csvother:
LudwigMixture.csv,LudwigMean.csv,LudwigKDE.csv,LudwigSpectrum.csv
The contents of these files can be viewed using the
system.file(...) function. For example, to read the
ArAr1.csv file:
fname <- system.file('ArAr1.csv',package='IsoplotR')
ArAr <- read.data(fname,method='Ar-Ar',format=1)
Value
An object of class UPb, PbPb, ThPb,
KCa, RbSr, SmNd, LuHf, ReOs,
UThHe, fissiontracks, detritals or
PD. See classes for further details.
See Also
examples, settings
Examples
f1 <- system.file("UPb1.csv",package="IsoplotR")
file.show(f1) # inspect the contents of 'UPb1.csv'
d1 <- read.data(f1,method="U-Pb",format=1)
concordia(d1)
f2 <- system.file("ArAr1.csv",package="IsoplotR")
d2 <- read.data(f2,method="Ar-Ar",format=1)
agespectrum(d2)
f3 <- system.file("ReOs1.csv",package="IsoplotR")
d3 <- read.data(f3,method="Re-Os",format=1)
isochron(d2)
f4 <- system.file("FT1.csv",package="IsoplotR")
d4 <- read.data(f4,method="fissiontracks",format=1)
radialplot(d4)
f5 <- system.file("UThSmHe.csv",package="IsoplotR")
d5 <- read.data(f5,method="U-Th-He")
helioplot(d5)
f6 <- system.file("ThU2.csv",package="IsoplotR")
d6 <- read.data(f6,method="Th-U",format=2)
evolution(d6)
# one detrital zircon U-Pb file (detritals.csv)
f7 <- system.file("DZ.csv",package="IsoplotR")
d7 <- read.data(f7,method="detritals")
kde(d7)
# four 'other' files (LudwigMixture.csv, LudwigSpectrum.csv,
# LudwigMean.csv, LudwigKDE.csv)
f8 <- system.file("LudwigMixture.csv",package="IsoplotR")
d8 <- read.data(f8,method="other",format=2)
radialplot(d8)
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