| Title: | Wrapper functions for MAESTRA/MAESPA |
|---|---|
| Description: | A bundle of functions for modifying MAESTRA/MAESPA input files, reading output files, and visualizing the stand in 3D. Handy for running sensitivity analyses, scenario analyses, etc. |
| Authors: | Remko Duursma |
| Maintainer: | Remko Duursma <[email protected]> |
| License: | GPL |
| Version: | 1.8.0 |
| Built: | 2024-11-08 03:12:14 UTC |
| Source: | https://github.com/remkoduursma/maeswrap |
The main functions are runmaespa() and
maesparunall(), see their help pages. Functions that read
parameters, and modify parameters or whole namelists are
readPAR(), replacePAR(),
replaceNameList(), and parseFile() to read an entire
file. Functions that read output are readdayflux(),
readhrflux()
| Package: | Maeswrap |
| Type: | Package |
| Version: | 1.2 |
| Date: | 2008-12-03 |
| License: | GPL |
| LazyLoad: | yes |
Remko Duursma Maintainer: Remko Duursma [email protected]
See Belinda Medlyn's MAESTRA homepage at: http://www.bio.mq.edu.au/maestra/
Checks MAESPA water balance by adding up fluxes for the soil water balance calculated by MAESPA. Prints the total fluxes (precipitation, transpiration, canopy interception, and so on), and the difference between ingoing and outgoing. This is a debugging/checking tool: if the model has serious problems, there will be a missing sink or source.
checkwatbal(x = readwatbal(), usemeaset = FALSE)checkwatbal(x = readwatbal(), usemeaset = FALSE)
x |
A dataframe returned by |
usemeaset |
Whether to use measured ET from the met file, or simulated (Default). |
Remko Duursma
Functions for running MAESTRA/MAESPA with parameters read from a .csv file. To make multiple runs, create a comma-separated file (.csv) with each row corresponding to a set of parameter values to be used in a simulation. Each column is for a different parameter, with its first entry being the name of the parameter (see Details below). Also needed is a text file with definitions, i.e. how parameter names in the .csv file correspond to parameter names in one of the MAESTRA input files, which file it is, and in which namelist to look (see Details). See Examples below for useage, and how to deal with the results from a batch run. Note that the batch utilities use the executable 'maespa.exe' (runmaespa), or 'maestra.exe' (runmaestra) by default, but you can use others. See Examples on how to set this.
Users will typically run maesparunall, which runs every row in the
comma-separated file denoted by runfile. Every column in this runfile
is named, with the name corresponding not directly to a parameter or
namelist in one of the fortran input files, but rather to an entry in the
definition file. This file (argument deffile) needs to be in the
current workspace. It is a space (or tab)-separated file, with four columns:
'parname', 'fileparname', 'filename' and 'namelist'. An example of this file
is provided with this package. Entries of each do not need to be quoted. The
namelist entry can be left blank, but it is recommended to provide the
namelist where the parameter occurs, for reliability.
The default executable is maespa.exe when running runmaespa,
but others can of course be used. The function runmaestra is exactly
the same as runmaespa, except that the default is to use the
executable 'maestra.exe'. To set the default for the rest of the session,
see the last Example below.
Note that these functions should be general, in that they can be used for any Fortran compiled program (.exe) that reads parameters from namelists.
By default, Maes(tra/pa) reads and saves the 'hrflux.dat' and 'dayflux.dat' files, and the 'watbal.dat' if it exists (i.e., if Maespa was used for the simulation). The 'extrafiles' argument specified additional output files to read and store.
maesparunall(whichrows = NA, runfile = NA, whichcols = NA, quiet = FALSE, extrafiles = "", ...) maestrarunall(executable = "maestra.exe", ...) runmaespa(whichrow = 1, whichcols = NA, runfile = file.choose(), runit = TRUE, executable = "maespa.exe", deffile = "maeswrapdefinitions.txt", spinup = FALSE, ...) runmaestra(executable = "maestra.exe", ...)maesparunall(whichrows = NA, runfile = NA, whichcols = NA, quiet = FALSE, extrafiles = "", ...) maestrarunall(executable = "maestra.exe", ...) runmaespa(whichrow = 1, whichcols = NA, runfile = file.choose(), runit = TRUE, executable = "maespa.exe", deffile = "maeswrapdefinitions.txt", spinup = FALSE, ...) runmaestra(executable = "maestra.exe", ...)
whichrows |
Which rows of the runfile to run in the simulations? |
runfile |
Name of the runfile, needs to be a .csv file, quoted. If left alone, a menu pops up. |
whichcols |
Which columns in the runfile contain parameters to be changed in the simulations? |
quiet |
If TRUE, no progress is written to the console. |
extrafiles |
Additional files to read and store (See Details). |
... |
Further parameters passed to |
executable |
Name of the executable. |
whichrow |
For one run, which row to run? |
runit |
If FALSE, writes the input files but does not run the model. |
deffile |
Text file with definitions of parameter names in the input files, their locations in files and namelists. See Details. |
spinup |
For Maespa only : if TRUE, the model is run once, and all final values of soil water content and soil temperature are used to initialize the next run, which is the run that is reported. |
For runmaespa, nothing is returned. Assuming you used runit=TRUE, the model is run and output files are written to disk. The function maesparunall returns a list with two components: daily and hourly. These components are itself lists with each element a dataframe with the daily or hourly results from the model output. These dataframes are read from the files dayflux.dat and hrflux.dat.
Remko Duursma
## Not run: #-1. Run the second row of some csv file, using only entries in # columns 2, 3 and 4. Note that all column names in the .csv # file must be documented in the definition file, and that the # definition file must be in the current working directory! runmaespa(2, runfile="runfiletest.csv", runit=FALSE, whichcols=2:4) #-2. Run all rows and all parameters from a comma-separated file. runresults <- maesparunall(runfile="runfiletest.csv") #-3. Look at first run: summary(runresults$daily[[1]]) #-4. Summarize across runs with statements like these. # Sum net photosynthesis across runs: sapply(runresults$daily, function(dfr)sum(dfr$netPs)) #-5. Or write all results to disk: filenames <- paste("MaespaDailyresults",1:length(runresults$daily),".txt",sep="") for(f in 1:length(filenames)){ write.table(runresults$daily[[f]],filenames[f],sep=" ",row.names=FALSE) } #-6. Use different executable: runmaespa(executable="othermaestra.exe") #-7. Or set this other executable as the default for the rest of the session, # so that you only need to set it once (until you restart R anyway). formals(runmaespa)$executable <- "othermaestra.exe" #-8. Specify additional output files to read and save: myrun <- maestrarunall(runfile="myrunfile.csv", extrafiles=c("layflx.dat","resp.dat")) # These two files are then available in the 'myrun' list by names 'layflx' and 'resp'. ## End(Not run)## Not run: #-1. Run the second row of some csv file, using only entries in # columns 2, 3 and 4. Note that all column names in the .csv # file must be documented in the definition file, and that the # definition file must be in the current working directory! runmaespa(2, runfile="runfiletest.csv", runit=FALSE, whichcols=2:4) #-2. Run all rows and all parameters from a comma-separated file. runresults <- maesparunall(runfile="runfiletest.csv") #-3. Look at first run: summary(runresults$daily[[1]]) #-4. Summarize across runs with statements like these. # Sum net photosynthesis across runs: sapply(runresults$daily, function(dfr)sum(dfr$netPs)) #-5. Or write all results to disk: filenames <- paste("MaespaDailyresults",1:length(runresults$daily),".txt",sep="") for(f in 1:length(filenames)){ write.table(runresults$daily[[f]],filenames[f],sep=" ",row.names=FALSE) } #-6. Use different executable: runmaespa(executable="othermaestra.exe") #-7. Or set this other executable as the default for the rest of the session, # so that you only need to set it once (until you restart R anyway). formals(runmaespa)$executable <- "othermaestra.exe" #-8. Specify additional output files to read and save: myrun <- maestrarunall(runfile="myrunfile.csv", extrafiles=c("layflx.dat","resp.dat")) # These two files are then available in the 'myrun' list by names 'layflx' and 'resp'. ## End(Not run)
The MAESTRA/MAESPA wrapper needs a 'definition file', where names of parameters are defined, together with their locations in parameter files and namelists. The 'comment' column is ignored when parsing the definition file.
A white space separated dataset (readable with read.table).
None.
Takes an input file for MAESTRA/MAESPA, and reads all namelists into a nested list. Also reads the first line of the file, which (optionally) contains a title, to be used in Maestra/pa output files.
parseFile(fn)parseFile(fn)
fn |
Filename |
Returns a named list, each element contains a namelist and its parameters.
To read one namelist from a file, see readNameList().
## Not run: # Parse a file con <- parseFile("confile.dat") # Namelists in the file names(con) ## End(Not run)## Not run: # Parse a file con <- parseFile("confile.dat") # Namelists in the file names(con) ## End(Not run)
Reads the MAESTRA trees file, and plots the stand in 3D. Supports all MAESTRA crown shapes except the box shape. Looks for the 'trees.dat' file in the current working directory, unless specified (see Examples). The XY coordinates must be present in the 'trees.dat' file. Users will typically only use the 'Plotstand' function.
Optionally reads the crown shape from the 'str.dat' file, and plots the correct crown shape for each species in the stand by reading the multi-species namelists in 'confile.dat' and 'trees.dat'.
The target trees are colored red (unless specified otherwise, see Details), if the 'itargets' is specified in the confile.
Attempts to read indivradx, indivrady, indivhtcrown, indivdiam, and indivhttrunk namelists from the 'trees.dat' file. If any of these fail, the 'all' versions are tried ('allradx', etc.). Although MAESTRA runs fine when no XY coordinates are provided, this plot function crashes. A future implementation will calculate XY coordinates in the same way as MAESTRA.
If the 'strfiles' parameter is set in 'confile.dat' (one str.dat file for each species in the stand), these files are opened and used to set the crown shape by species. Alternatively, you may specify crownshape as a parameter, and override reading of str.dat by setting readstrfiles=FALSE.
The 'nz' and 'nalpha' arguments specify the 'smoothness' of the crowns: higher values provide more detailed triangulation of the crowns, at the expense of speed.
Plotstand(treesfile = "trees.dat", strfile = "str.dat", crownshape = c("cone", "ellipsoid", "round", "halfellipsoid", "paraboloid", "cylinder"), readstrfiles = TRUE, targethighlight = TRUE, addNarrow = TRUE, xyaxes = TRUE, labcex = 1, axiscex = 1, verbose = FALSE, idate = 1, path = "", ...)Plotstand(treesfile = "trees.dat", strfile = "str.dat", crownshape = c("cone", "ellipsoid", "round", "halfellipsoid", "paraboloid", "cylinder"), readstrfiles = TRUE, targethighlight = TRUE, addNarrow = TRUE, xyaxes = TRUE, labcex = 1, axiscex = 1, verbose = FALSE, idate = 1, path = "", ...)
treesfile |
By default, the 'trees.dat' file in the current dir. |
strfile |
Not used, yet. |
crownshape |
Character, "cone","elipsoid","ellipsoid","halfellipsoid","paraboloid","cylinder", or abbreviation. |
readstrfiles |
Read the 'str.dat' file(s) to find out crown shape? |
targethighlight |
Plot the target trees in red? |
addNarrow |
Logical. Add arrow pointing North? |
xyaxes |
Logical. Add annotated X and Y axes? |
labcex |
Relative size of X and Y axis labels. |
axiscex |
Relative size of X and Y axis annotation. |
verbose |
If TRUE, writes more info to the screen while plotting. |
idate |
If multiple dates are provided for tree size variables, which one to display. |
path |
The folder where the input files are stored. |
... |
See Details for a list of additional arguments recognized by |
For large stands, the plot takes quite a while to complete. This implementation is certainly not optimized for speed. Also, minimize the rgl window to greatly speed up the plotting process.
The Plotstand function accepts a number of additional arguments that are used by subsidiary functions, these are:
CL: Crown length (m).
CW: Crown width (m).
crowncolor: The color of the tree crowns. Default, obviously, forestgreen.
stemcolor: The color of the tree stems. Default brown.
x0,y0,z0: Coordinates of crown base when calculating 3D coordinates.
HCB: Height of crown base (m).
X,Y: X- and Y-coordinates of tree stem base (m).
dbh: Stem diameter (m). Converted to m if appears to be in cm.
nz: Number of z divisions (increase number to get smoother crowns).
nalpha: Number of angular divisions (increase number to plot smoother crowns).
m: 3xN matrix (x,y,z coordinates in rows). Optional.
An rgl device is opened.
Remko Duursma
## Not run: # Plot the 'trees.dat' file in the current working directory: Plotstand() # Open a dialog box to select a trees.dat file: Plotstand(file.choose()) # Save a snapshot to a .png file. # Note: make sure to move the 3D plot into view # (so that other windows are not blocking it!) snapshot3d('myforest.png') # For publication-quality graphs: Plotstand(nz=50, nalpha=50) ## End(Not run)## Not run: # Plot the 'trees.dat' file in the current working directory: Plotstand() # Open a dialog box to select a trees.dat file: Plotstand(file.choose()) # Save a snapshot to a .png file. # Note: make sure to move the 3D plot into view # (so that other windows are not blocking it!) snapshot3d('myforest.png') # For publication-quality graphs: Plotstand(nz=50, nalpha=50) ## End(Not run)
Reads the 'uspar.dat' file in the current working directory, and plots the incident or absorbed (or diffuse, or direct) PAR at the understorey points. Either produces a plot, or makes a pdf with a plot for each hour of the selected day.
Reads the point-wise output file when the understorey was simulated.
plotuspar(what = c("PARbeam", "PARtotal", "PARdiffuse", "APAR"), dataset = NULL, day = 1, hour = NA, xlim = NULL, ylim = NULL, makepdf = FALSE, outputfile = "aparunderstorey.pdf", scaleeach = TRUE, addNarrow = TRUE) readuspar(filename = "uspar.dat")plotuspar(what = c("PARbeam", "PARtotal", "PARdiffuse", "APAR"), dataset = NULL, day = 1, hour = NA, xlim = NULL, ylim = NULL, makepdf = FALSE, outputfile = "aparunderstorey.pdf", scaleeach = TRUE, addNarrow = TRUE) readuspar(filename = "uspar.dat")
what |
Either 'diff', 'apar', 'ipar', or 'beam' (the default). |
dataset |
If left alone, reads the uspar dataset. |
day |
Which day to use, if left alone uses the first day only. |
hour |
Which hour to plot. If left alone, makes a plot for each hour. |
xlim, ylim
|
X- and Y-axis limits. |
makepdf |
Logical. If TRUE, produces a pdf in the working directory. |
outputfile |
Name of the pdf file. |
scaleeach |
Logical. Rescale grey scale for each plot, or same for all hours? |
addNarrow |
Logical. Add an arrow pointing North. |
filename |
The understorey file |
If addNarrow is TRUE, attempts to read the trees.dat file in the current working directory as well. Prints a warning when this file cannot be opened.
A lattice device, or a pdf.
Remko Duursma
## Not run: # Plot one hour of the first day, showing incident PAR on understorey: plotuspar("ipar", day=1,hour=12,makepdf=FALSE) # Make pdf of the whole day, plotting beam radiation: plotuspar("beam", day=1, outputfile="beam uspar") ## End(Not run)## Not run: # Plot one hour of the first day, showing incident PAR on understorey: plotuspar("ipar", day=1,hour=12,makepdf=FALSE) # Make pdf of the whole day, plotting beam radiation: plotuspar("beam", day=1, outputfile="beam uspar") ## End(Not run)
Generates a stand of trees, given a LAI, stocking, and some basic allometry. Very simple implementation that will be expanded (and eventually rolled into Maes*).
randomstand(LAI = 2, height = 20, cwcl = 0.8, ALAC = 0.5, stocking = 500, edge = 10, plotsize = c(25, 25), dbh = 0.3, crownshape = c("ELIP", "BOX", "CONE", "PARA", "CYL"), path = "", maxnotrees = 25)randomstand(LAI = 2, height = 20, cwcl = 0.8, ALAC = 0.5, stocking = 500, edge = 10, plotsize = c(25, 25), dbh = 0.3, crownshape = c("ELIP", "BOX", "CONE", "PARA", "CYL"), path = "", maxnotrees = 25)
LAI |
Leaf area index of the stand (m2 m-2) |
height |
Total tree height (m) |
cwcl |
The ratio of crown width to crown length |
ALAC |
The ratio of tree leaf area to crown surface area (m2 m-2) |
stocking |
Number of trees per hectare |
edge |
An extra edge to be placed around the plot (in addition to plotsize!) |
plotsize |
The size of the plot (m), as a vector (x,y) |
dbh |
Trunk diameter (not relevant, just for plotting) (m) |
crownshape |
One of the Maestra crown shapes |
path |
Path to the directory where the Maestra files should be modified |
maxnotrees |
Maximum number of target trees to be set in confile.dat (affects Maestra radiation calculations, not the plot and tree layout) |
## Not run: # Assuming your working directory contains the Maestra input files, randomstand() Plotstand() ## End(Not run)## Not run: # Assuming your working directory contains the Maestra input files, randomstand() Plotstand() ## End(Not run)
Reads the dayflx.dat MAESTRA/MAESPA output file, returns a clean dataframe. Names of the variables are read from the Columns: line.
readdayflux(filename = "dayflx.dat")readdayflux(filename = "dayflx.dat")
filename |
Default name of the daily flux file. |
Returns a dataframe.
Remko Duursma
## Not run: # Read it: mysim1 <- readdayflux() ## End(Not run)## Not run: # Read it: mysim1 <- readdayflux() ## End(Not run)
Reads the hourly output file (hrflux.dat).
readhrflux(filename = "hrflux.dat")readhrflux(filename = "hrflux.dat")
filename |
Default name of the (half-)hourly output file. |
Returns a dataframe.
Remko Duursma
## Not run: # Simple as this: mysim2 <- readhrflux() ## End(Not run)## Not run: # Simple as this: mysim2 <- readhrflux() ## End(Not run)
Reads the meteorological input data in the met.dat file.
readmet(filename = "met.dat", nlines = -1)readmet(filename = "met.dat", nlines = -1)
filename |
Default name of the met.dat file. |
nlines |
Optional, how many lines of the metfile to read? |
Returns a dataframe.
Remko Duursma
## Not run: # Simple as pi: metdata <- readmet() ## End(Not run)## Not run: # Simple as pi: metdata <- readmet() ## End(Not run)
The readPAR function reads the value of any parameter in a namelist
in one of the MAESTRA/MAESPA input files. Also works for other text files
that have the FORTRAN namelist input structure. Optionally specifies in
which namelist to look for the parameter.
To read an entire namelist into a list, use the readNameList
function.
readPAR(datfile, parname, namelist = NA, fail = TRUE) readNameList(datfile, namelist)readPAR(datfile, parname, namelist = NA, fail = TRUE) readNameList(datfile, namelist)
datfile |
Name of the input file. |
parname |
Name of the parameter. |
namelist |
The namelist to look in, otherwise looks in the whole file. |
fail |
Logical. If TRUE, stops with an error when parameter is not found (if FALSE, returns NA) |
For readPAR, either one value, or a vector, depending on how
many values are specified for the parameter in the input file.
For readNameList, a named list.
Remko Duursma. Thanks to Andreas Ibrom for reporting a bug.
## Not run: # Read the number of trees in the plot: readPAR("confile.dat", "notrees", "plot") # Read the X and Y coordinates: readPAR("confile.dat", "xycoords", "xy") # Read entire namelist readNameList("trees.dat", "plot") ## End(Not run)## Not run: # Read the number of trees in the plot: readPAR("confile.dat", "notrees", "plot") # Read the X and Y coordinates: readPAR("confile.dat", "xycoords", "xy") # Read entire namelist readNameList("trees.dat", "plot") ## End(Not run)
Reads the test flux output file (testflx.dat).
readtestflx(filename = "testflx.dat")readtestflx(filename = "testflx.dat")
filename |
Name of the test output file (default to "testflx.dat". |
Returns a dataframe.
Rémi Vezy
## Not run: # Simple as this: test <- readtestflx() ## End(Not run)## Not run: # Simple as this: test <- readtestflx() ## End(Not run)
Reads the hourly water balance output file ("watbal.dat").
readwatbal(filename = "watbal.dat")readwatbal(filename = "watbal.dat")
filename |
Default name of the (half-)hourly water balance output file. |
Returns a dataframe.
Remko Duursma
## Not run: # Simple as this: mywatbalresult <- readwatbal() # If you want to select the water balance file with a menu: readwatbal(file.choose()) ## End(Not run)## Not run: # Simple as this: mywatbalresult <- readwatbal() # If you want to select the water balance file with a menu: readwatbal(file.choose()) ## End(Not run)
Reads the daily water balance output file ("watbalday.dat").
readwatbalday(filename = "watbalday.dat")readwatbalday(filename = "watbalday.dat")
filename |
Default name of the daily water balance output file. |
Returns a dataframe.
Rémi Vezy
## Not run: # Simple as this: mywatbalresult <- readwatbal() # If you want to select the water balance file with a menu: readwatbalday(file.choose()) ## End(Not run)## Not run: # Simple as this: mywatbalresult <- readwatbal() # If you want to select the water balance file with a menu: readwatbalday(file.choose()) ## End(Not run)
Replaces one (or more) of the weather variables in the met.dat file.
replacemetvar(replacevar, newvalues, oldmetfile = "met.dat", newmetfile = "metNEW.dat") replacemetdata(metdfr, oldmetfile = "met.dat", columns = NULL, newmetfile = oldmetfile, khrs = NA, setdates = TRUE)replacemetvar(replacevar, newvalues, oldmetfile = "met.dat", newmetfile = "metNEW.dat") replacemetdata(metdfr, oldmetfile = "met.dat", columns = NULL, newmetfile = oldmetfile, khrs = NA, setdates = TRUE)
replacevar |
Character. Name(s) of the variable to be replaced. |
newvalues |
Vector of new values for the weather variable, has to be the same length as the number of records in the met.dat file. |
oldmetfile |
Default name of the met.dat file that will be modified. |
newmetfile |
Name of the new met.dat file. |
metdfr |
Dataframe with met data, to be pasted into a met.dat file. |
columns |
Optional character string : if the 'Columns' statement in the met.dat file is to be replaced. |
khrs |
Optional. Number of timesteps per day (by default, read from the met.dat file). |
setdates |
If TRUE (default), fix start and end date in FORMAT field to cover data added. |
Returns nothing.
Remko Duursma
## Not run: #:::1.::: Replace precipitation with random number between 0 and 2. # First find out how many records there are: nrecords <- nrow(readmet("met.dat")) # Make new rain newrain <- runif(nrecords, 0, 2) # And replace replacemetvar("PPT",newrain,"met.dat", "newmet.dat") #:::2.::: Replace multiple weather variables. newtair <- runif(nrecords, 0, 35) # Have to make a matrix of the variables to be replaced: newmat <- matrix(cbind(newrain, newtair),ncol=2) # And give a vector of variable names --in the same order as in the matrix!!--. replacemetvar(c("PPT","TAIR"), newmat, "met.dat", "newmet.dat") ## End(Not run)## Not run: #:::1.::: Replace precipitation with random number between 0 and 2. # First find out how many records there are: nrecords <- nrow(readmet("met.dat")) # Make new rain newrain <- runif(nrecords, 0, 2) # And replace replacemetvar("PPT",newrain,"met.dat", "newmet.dat") #:::2.::: Replace multiple weather variables. newtair <- runif(nrecords, 0, 35) # Have to make a matrix of the variables to be replaced: newmat <- matrix(cbind(newrain, newtair),ncol=2) # And give a vector of variable names --in the same order as in the matrix!!--. replacemetvar(c("PPT","TAIR"), newmat, "met.dat", "newmet.dat") ## End(Not run)
The function replaceNameList replaces the whole namelist in an input file.
All parameters in the namelist must be provided, otherwise MAESTRA/MAESPA will likely crash. Or, you can use
replacePAR to replace a single parameter. If the new parameter value(s) is a vector (or a single value), the values #' will be placed on a single line in the parameter file. If instead a matrix is provided, each row of the matrix is placed on a separate line.
WARNING : The input file is modified. Make sure to backup your original input files!
replaceNameList(namelist, datfile, vals) replacePAR(datfile, parname, namelist, newval, noquotes = TRUE)replaceNameList(namelist, datfile, vals) replacePAR(datfile, parname, namelist, newval, noquotes = TRUE)
namelist |
Name of the namelist. |
datfile |
Name of the input file. |
vals |
A list of values (see example below). |
parname |
Name of the parameter to replace the value of. |
newval |
New value of the parameter. Can be a single value or a vector, or a matrix (see Details). |
noquotes |
Logical. If FALSE, does print quotes around character values. |
Nothing is returned. The input file is modified.
Remko Duursma
## Not run: # Replace an entire namelist replaceNameList(namelist="aerodyn", datfile="trees.dat", vals=list(zht=30,zpd=3,z0ht=0.6)) #' # Replace a parameter with a single value: replacePAR("trees.dat", "notrees", "plot", newval=100) # Replace a number of values: replacePAR("trees.dat", "xycoords", "xy", newval=c(1,1,2,2,3,3)) # Replace a number of values in a different way : this may be useful in # more complicated programs, # rr when reading a string from a file (that should be interpreted as a vector). replacePAR("trees.dat", "xycoords", "xy", newval="1 1 2 2 3 3", noquotes=TRUE) # Replace a parameter so that the new values are placed on multiple rows. # Useful for tree namelists with multiple dates and multiple trees # (where each row corresponds to a tree, and each column to a date.) m <- matrix(c(1,2,3,4,5,6,7,8,9), nrow=3, byrow=TRUE) replacePAR("trees.dat", "values", "indivlarea", newval=m) ## End(Not run)## Not run: # Replace an entire namelist replaceNameList(namelist="aerodyn", datfile="trees.dat", vals=list(zht=30,zpd=3,z0ht=0.6)) #' # Replace a parameter with a single value: replacePAR("trees.dat", "notrees", "plot", newval=100) # Replace a number of values: replacePAR("trees.dat", "xycoords", "xy", newval=c(1,1,2,2,3,3)) # Replace a number of values in a different way : this may be useful in # more complicated programs, # rr when reading a string from a file (that should be interpreted as a vector). replacePAR("trees.dat", "xycoords", "xy", newval="1 1 2 2 3 3", noquotes=TRUE) # Replace a parameter so that the new values are placed on multiple rows. # Useful for tree namelists with multiple dates and multiple trees # (where each row corresponds to a tree, and each column to a date.) m <- matrix(c(1,2,3,4,5,6,7,8,9), nrow=3, byrow=TRUE) replacePAR("trees.dat", "values", "indivlarea", newval=m) ## End(Not run)
Reverses the characters in a character string, unless a vector is supplied, in which case reverses the element of the vector.
revchar(x)revchar(x)
x |
A character vector (typically of length 1). |
When a character vector of length > 1 is provided, reverses the elements of the vector, not the characters itself.
A vector.
Remko Duursma
None.
rev.default(),substr(),strsplit()
## Not run: # Take a substring, counting from the end: substrfromend <- function(x,start,stop)revchar(substr(revchar(x),start,stop)) substrfromend('filename.txt', 1,3) # Check if a word is a palindrome: s <- 'saippuakivikauppias' s == revchar(s) # A semordnilap: cat('I am so stressed, I need to eat', revchar('stressed'),'\n') ## End(Not run)## Not run: # Take a substring, counting from the end: substrfromend <- function(x,start,stop)revchar(substr(revchar(x),start,stop)) substrfromend('filename.txt', 1,3) # Check if a word is a palindrome: s <- 'saippuakivikauppias' s == revchar(s) # A semordnilap: cat('I am so stressed, I need to eat', revchar('stressed'),'\n') ## End(Not run)
Example of a 'run dataset', where each row corresponds to a simulation with parameters set by the column names. The wrapper looks for the column names in the definition file, and sets the parameters based on information in that file.
A comma-separated file.
None.