Various updates and minor improvements

.github/workflows/r.yml

@@ -44,7 +44,7 @@ jobs:
       GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
 
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
 
       - uses: r-lib/actions/setup-pandoc@v2
 

.pre-commit-config.yaml

@@ -0,0 +1,20 @@
+repos:
+  - repo: https://github.com/pre-commit/pre-commit-hooks
+    rev: v5.0.0
+    hooks:
+      - id: mixed-line-ending
+        args: [--fix=lf]
+      - id: end-of-file-fixer
+      - id: trailing-whitespace
+        exclude: '\.(Rd|txt)$'
+      - id: check-merge-conflict
+      - id: check-yaml
+      - id: check-case-conflict
+      - id: check-added-large-files
+      - id: fix-byte-order-marker
+
+# Optional R linting (to be enabled some point in the future):
+# - repo: https://github.com/lorenzwalthert/precommit
+#   rev: v0.4.3
+#   hooks:
+#     - id: lintr

COPYING

@@ -55,7 +55,7 @@ patent must be licensed for everyone's free use or not licensed at all.
 
   The precise terms and conditions for copying, distribution and
 modification follow.
-
+
 		    GNU GENERAL PUBLIC LICENSE
    TERMS AND CONDITIONS FOR COPYING, DISTRIBUTION AND MODIFICATION
 
@@ -110,7 +110,7 @@ above, provided that you also meet all of these conditions:
     License.  (Exception: if the Program itself is interactive but
     does not normally print such an announcement, your work based on
     the Program is not required to print an announcement.)
-
+
 These requirements apply to the modified work as a whole.  If
 identifiable sections of that work are not derived from the Program,
 and can be reasonably considered independent and separate works in
@@ -168,7 +168,7 @@ access to copy from a designated place, then offering equivalent
 access to copy the source code from the same place counts as
 distribution of the source code, even though third parties are not
 compelled to copy the source along with the object code.
-
+
   4. You may not copy, modify, sublicense, or distribute the Program
 except as expressly provided under this License.  Any attempt
 otherwise to copy, modify, sublicense or distribute the Program is
@@ -225,7 +225,7 @@ impose that choice.
 
 This section is intended to make thoroughly clear what is believed to
 be a consequence of the rest of this License.
-
+
   8. If the distribution and/or use of the Program is restricted in
 certain countries either by patents or by copyrighted interfaces, the
 original copyright holder who places the Program under this License
@@ -278,7 +278,7 @@ PROGRAMS), EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE
 POSSIBILITY OF SUCH DAMAGES.
 
 		     END OF TERMS AND CONDITIONS
-
+
 	    How to Apply These Terms to Your New Programs
 
   If you develop a new program, and you want it to be of the greatest

NAMESPACE

@@ -13,7 +13,7 @@ importFrom("stats", "IQR", "approxfun", "coef", "deviance", "dnorm",
              "numericDeriv", "optim", "predict", "printCoefmat", "pt",
              "quantile", "rnorm", "symnum")
 importFrom("utils", "capture.output", "read.table", "tail",
-             "write.table")             
+             "write.table")
 importFrom("fields","image.plot","tim.colors","two.colors")
 importFrom("nnls","nnls","nnnpls")
 importFrom("deSolve","lsoda")
@@ -32,7 +32,7 @@ exportClasses(dat, kin, spec, mass, amp,
 
 exportMethods(getClpindepX, residPart, plotter)
 
-export(readData, preProcess, baseIRF, initModel, 
+export(readData, preProcess, baseIRF, initModel,
        fitModel, examineFit, sumKinSpecEst)
 
 export(dat, kin, spec, mass, amp, theta, multimodel, res, multitheta,

man/amp-class.Rd

@@ -97,4 +97,4 @@ Objects can be created by calls of the form \code{new("amp", ...)} or
     \code{\link{kin-class}}, \code{\link{spec-class}}, \code{\link{opt-class}}
   }
   \keyword{classes}
-
+

man/baseIRF.Rd

@@ -27,4 +27,3 @@ lines(irfvec_corrected, col=2)
 }
 
 \keyword{file}
-

man/divergeZimage.Rd

@@ -60,4 +60,3 @@ divergeZimage(exd, lin=10, title="plot linearly to 10")
 \author{Katharine M. Mullen, Ivo H. M. van Stokkum}
 \seealso{ \code{\link{dat}} }
 \keyword{hplot}
-

man/efit2file.Rd

@@ -22,4 +22,3 @@ efit2file(filename, skip = 2, numcol, nrows=vector())
 \author{Katharine M. Mullen, Ivo H. M. van Stokkum}
 \seealso{ \code{\link{readData}} }
 \keyword{file}
-

man/examineFit.Rd

@@ -28,4 +28,3 @@ used to examine results.
 \seealso{ \code{\link{fitModel}}, \code{\link{opt} }}
 \author{Katharine M. Mullen, Ivo H. M. van Stokkum}
 \keyword{file }
-

man/initModel.Rd

@@ -142,4 +142,3 @@ for (f in file_list_cleanup) {
 \code{\link{fitModel}}}
 
 \keyword{file}
-

man/readData.Rd

@@ -23,4 +23,3 @@ an object of class \code{dat}
 \author{Katharine M. Mullen, Ivo H. M. van Stokkum}
 \seealso{ \code{\link{preProcess}} }
 \keyword{file}
-

man/readclp0.Rd

@@ -29,4 +29,3 @@ constraint, e.g., \code{1 218.800000000000011 220.099999999999994}.
 \author{Katharine M. Mullen, Ivo H. M. van Stokkum}
 \seealso{ \code{\link{initModel}} }
 \keyword{file}
-

man/residPart.Rd

@@ -42,4 +42,3 @@ conditionally linear parameters.
 \keyword{methods}
 \seealso{ \code{\link{dat-class}}, \code{\link{spec-class}},
 \code{\link{kin-class}} } 
-

man/writeAverage.Rd

@@ -32,4 +32,3 @@ writeAverage(filename, ntimes, nwave, scans,
 \author{Katharine M. Mullen, Ivo H. M. van Stokkum}
 \seealso{ \code{\link{readData}} }
 \keyword{file}
-

src/TIMP_init.c

@@ -1,7 +1,7 @@
 #include <stdlib.h> // for NULL
 #include <R_ext/Rdynload.h>
 
-/* FIXME: 
+/* FIXME:
 Check these declarations against the C/Fortran source code.
 */
 

src/ntr.c

@@ -379,4 +379,3 @@ void r_ShiftCurve  (double *source, double *curve, double *shiftparam,
   }
 
 }
-

tests/cp432704.txt

@@ -58,4 +58,4 @@ Intervalnr 32
       4000.0   -0.126935   -0.130437   -0.051907   -0.049243   -0.025468    0.001448   -0.009269   -0.034469   -0.004993    0.015112    0.004591   -0.000325   -0.022176   -0.060636   -0.020398   -0.061835   -0.068047   -0.088709   -0.084846   -0.052776   -0.073668   -0.042461   -0.067557   -0.093212   -0.046617   -0.058758    -0.09643   -0.200879   -0.288366   -0.413487   -0.446774   -0.665556
       4500.0   -0.287226   -0.199561   -0.131996   -0.090379   -0.080615   -0.089427   -0.047825   -0.040071   -0.042969   -0.021777   -0.068934   -0.010184   -0.031449   -0.082132   -0.038011   -0.090518   -0.081269   -0.125011   -0.105967   -0.101456   -0.112074   -0.133302   -0.135132   -0.185979   -0.108661   -0.109846   -0.135039   -0.269572   -0.393002   -0.368709   -0.605479   -0.710526
       5000.0   -0.150652   -0.142447   -0.074923   -0.035518   -0.068344   -0.032002   -0.017734    -0.01965   -0.031751    -0.00745   -0.058985   -0.028062   -0.046932   -0.079923   -0.056799   -0.092247   -0.089361   -0.118415   -0.099252   -0.091571   -0.125333   -0.123225   -0.109232   -0.176052   -0.063067   -0.086861   -0.127057   -0.206568   -0.274212   -0.393552   -0.489718   -0.676398
-
+

tests/kin_ir_simult_script.RRRR

@@ -10,8 +10,8 @@
 require(TIMP)
 
 ##############################
-## Read in and preprocess (by baseline correction) 
-## 4 datasets 
+## Read in and preprocess (by baseline correction)
+## 4 datasets
 ##############################
 
 did1<-readData("0902.txt")
@@ -27,30 +27,30 @@ did4<-readData("1402.txt")
 did4<-preProcess(data = did4, baselinelambda = c(3, 7, 1, 32))
 
 ##############################
-## Make a list of the 4 datasets, to be 
-## used for simulteneous analysis 
+## Make a list of the 4 datasets, to be
+## used for simulteneous analysis
 ##############################
 
-data <- list(did1, did2, did3, did4) 
+data <- list(did1, did2, did3, did4)
 
 ##############################
-## Initial model.  
+## Initial model.
 ##############################
 
-model_allfree <- initModel(mod_type = "kin", 
-kinpar=c(1.1, 0.05, 0.001), 
-irfpar=c(.05, 0.495912E-01), 
+model_allfree <- initModel(mod_type = "kin",
+kinpar=c(1.1, 0.05, 0.001),
+irfpar=c(.05, 0.495912E-01),
 lambdac = 1670,
-parmu = list(-.0158119812957), 
-seqmod=TRUE, positivepar=c("kinpar"), 
-weightpar=list( c(-16,.3,1,2000,.1), c(NA,NA,1590,1612,.1)), 
+parmu = list(-.0158119812957),
+seqmod=TRUE, positivepar=c("kinpar"),
+weightpar=list( c(-16,.3,1,2000,.1), c(NA,NA,1590,1612,.1)),
 cohspec = list( type = "irf"))
 
 ##############################
-## First apply the initial model to each dataset separately. 
+## First apply the initial model to each dataset separately.
 ##############################
 
-didRes1<-fitModel(list(did1), list(model_allfree), opt=kinopt(iter=2, 
+didRes1<-fitModel(list(did1), list(model_allfree), opt=kinopt(iter=2,
 makeps="d1", title = "Dataset 1, single analysis"))
 
 didRes2<-fitModel(list(did2), list(model_allfree), opt=kinopt(iter=2,
@@ -63,121 +63,117 @@ didRes4<-fitModel(list(did4), list(model_allfree), opt=kinopt(iter=2,
 makeps="d4", title = "Dataset 4, single analysis"))
 
 ##############################
-## Apply the initial model to datasets 1 and 2 together. 
-## Make the kinetic and irf parameters free to vary between 
-## datasets, and add a spectral equality constraint between 
-## datasets.  Also add a dataset scaling parameter. 
+## Apply the initial model to datasets 1 and 2 together.
+## Make the kinetic and irf parameters free to vary between
+## datasets, and add a spectral equality constraint between
+## datasets.  Also add a dataset scaling parameter.
 ##############################
 
-didRes<-fitModel(list(did1,did2), modspec = list(model_allfree), 
+didRes<-fitModel(list(did1,did2), modspec = list(model_allfree),
 modeldiffs = list( dscal = list(list(to=1,from=2,value=1)),
 change = list(
 list(what="kinpar", spec= c(1.011, 0.05, 0.005), dataset=2),
 list(what="irfpar", spec= c(.051, 0.496912E-01), dataset=2),
-list(what="clpequspec", spec=list(list(to=3, from=3, low=100, high=1810, 
-dataset=2)), dataset=1), 
+list(what="clpequspec", spec=list(list(to=3, from=3, low=100, high=1810,
+dataset=2)), dataset=1),
 list(what="clpequ", spec=c(1), dataset=1))), opt=kinopt(iter=5))
 
 ##############################
-## Apply the initial model to datasets 3 and 4 together. 
-## Make the kinetic and irf parameters free to vary between 
-## datasets, and add a spectral equality constraint between 
-## datasets.  Also add a dataset scaling parameter -- but this 
-## time also add a higher order polynomial for dispersion to the 
+## Apply the initial model to datasets 3 and 4 together.
+## Make the kinetic and irf parameters free to vary between
+## datasets, and add a spectral equality constraint between
+## datasets.  Also add a dataset scaling parameter -- but this
+## time also add a higher order polynomial for dispersion to the
 ## 2nd dataset (dataset 4) via the parmu parameterization.
 ##############################
 
-didRes<-fitModel(list(did3,did4), list(model_allfree), 
+didRes<-fitModel(list(did3,did4), list(model_allfree),
 modeldiffs = list( dscal = list(list(to=1,from=2,value=1)),
 change = list(
 list(what="kinpar", spec= c(1.0, 0.05, 0.005), dataset=2),
 list(what="irfpar", spec= c(.05, 0.496912E-01), dataset=2),
-list(what="clpequspec", spec=list(list(to=3, from=3, low=100, 
-high=1810, dataset=1)), dataset=2),  
-list(what="clpequ", spec=c(1), dataset=2), 
-list(what = "parmu", spec=list(c(-.0158119812957)), dataset=2))), 
+list(what="clpequspec", spec=list(list(to=3, from=3, low=100,
+high=1810, dataset=1)), dataset=2),
+list(what="clpequ", spec=c(1), dataset=2),
+list(what = "parmu", spec=list(c(-.0158119812957)), dataset=2))),
 opt=kinopt(iter=1))
 
 ##############################
 ## Analyze all 4 datasets (previously put into the list "data") together.
 ## Make all the kinetic and IRF parameters free between datasets, and give
-## the IRF model different starting values for each dataset.  Also add some 
+## the IRF model different starting values for each dataset.  Also add some
 ## spectral relations between dataset (that are actually equalities, since the
 ## linear relations are fixed to 1.  The datasets are related as a whole via
 ## scaling parameters dscal.  For the 3rd dataset dscal is estimated at
 ## at each wavelength (per-clp).
 ##############################
 
-didRes<-fitModel(data, list(model_allfree), 
-modeldiffs = list(dscal = 
+didRes<-fitModel(data, list(model_allfree),
+modeldiffs = list(dscal =
 list(
-list(to=4,from=1,value=1), 
-list(to=2,from=1,value=1), 
+list(to=4,from=1,value=1),
+list(to=2,from=1,value=1),
 list(to=3,from=1,value=rep(1,32), perclp=TRUE)),
 change = list(
 list(what="kinpar", spec= c(1.01, 0.05, 0.005), dataset=2:4,
 type="multifree"),
 list(what="irfpar", spec= c(.067, 0.18), dataset=2:4, type="multifree"),
 
 list(what="clpequspec", spec=list(
-list(to=3, from=3, low=100, high=1810, startrelpar=1, dataset=3), 
-list(to=1, from=1, low=100, high=1810, startrelpar=1, dataset=2)), 
+list(to=3, from=3, low=100, high=1810, startrelpar=1, dataset=3),
+list(to=1, from=1, low=100, high=1810, startrelpar=1, dataset=2)),
 dataset=c(1,4), type="multifree"),
 
-list(what="clpequ", spec=c(1,1), dataset=c(1,4), type="multifree"), 
+list(what="clpequ", spec=c(1,1), dataset=c(1,4), type="multifree"),
 
 list(what = "fixed", spec = list(clpequ=c(1,2)), dataset=c(1,4)))),
 
-opt=kinopt(iter=3, linrange=3, superimpose=1:4, 
+opt=kinopt(iter=3, linrange=3, superimpose=1:4,
 selectedtraces=seq(1,data[[1]]@nl, by=3)))
 
 ##############################
 ## Add a more sophisticated model for the coherent artifact,
-## via the $type = "irfmulti" argument.  The 
+## via the $type = "irfmulti" argument.  The
 ## time profile of the IRF is used for the coherent
 ## artifact/scatter model, but the IRF parameters are taken per
 ## dataset.
 ##############################
 
-model_irfcoh <- initModel(mod_type = "kin", 
-kinpar=c(1.0, 0.05, 0.005), 
-irfpar=c(.05, 0.495912E-01), 
+model_irfcoh <- initModel(mod_type = "kin",
+kinpar=c(1.0, 0.05, 0.005),
+irfpar=c(.05, 0.495912E-01),
 lambdac = 1670,
 fixed = list(irfpar=2),
-parmu = list(c(-.0158119812957)), 
-seqmod=TRUE,iter=2, positivepar=c("kinpar", "coh"), 
-weightpar=list( c(-16,.3,1,2000,.1), c(NA,NA,1590,1612,.1)), 
+parmu = list(c(-.0158119812957)),
+seqmod=TRUE,iter=2, positivepar=c("kinpar", "coh"),
+weightpar=list( c(-16,.3,1,2000,.1), c(NA,NA,1590,1612,.1)),
 cohspec = list( type = "irfmulti", numdatasets = 4))
 
 ##############################
-## Fit with this more sophisticated coherent artifact model, 
-## and fixing the width of the IRF. 
+## Fit with this more sophisticated coherent artifact model,
+## and fixing the width of the IRF.
 ##############################
 
-didRes<-fitModel(data, list(model_irfcoh), 
-modeldiffs = list(dscal = 
+didRes<-fitModel(data, list(model_irfcoh),
+modeldiffs = list(dscal =
 list(
-list(to=4,from=1,value=1), 
-list(to=2,from=1,value=1), 
+list(to=4,from=1,value=1),
+list(to=2,from=1,value=1),
 list(to=3,from=1,value=rep(1,32), perclp=TRUE)),
 change = list(
 list(what="kinpar", spec= c(1.01, 0.05, 0.005), dataset=2:4,
 type="multifree"),
 list(what="irfpar", spec= c(.067, 0.18), dataset=2:4, type="multifree"),
 
 list(what="clpequspec", spec=list(
-list(to=3, from=3, low=100, high=1810, startrelpar=1, dataset=3), 
-list(to=1, from=1, low=100, high=1810, startrelpar=1, dataset=2)), 
+list(to=3, from=3, low=100, high=1810, startrelpar=1, dataset=3),
+list(to=1, from=1, low=100, high=1810, startrelpar=1, dataset=2)),
 dataset=c(1,4), type="multifree"),
 
-list(what="clpequ", spec=c(1,1), dataset=c(1,4), type="multifree"), 
+list(what="clpequ", spec=c(1,1), dataset=c(1,4), type="multifree"),
 
 list(what = "fixed", spec = list(clpequ=c(1,2)), dataset=c(1,4)))),
-list(what = "fixed", spec = list(clpequ=c(1), irfpar=2), dataset=2:3), 
+list(what = "fixed", spec = list(clpequ=c(1), irfpar=2), dataset=2:3),
 
-opt=kinopt(iter=3, linrange=3, superimpose=1:4, 
+opt=kinopt(iter=3, linrange=3, superimpose=1:4,
 selectedtraces=seq(1,data[[1]]@nl, by=3)))
-
-
-
-