Description Usage Arguments Details Value See Also Examples
This function inserts a suffix to the output file names of homogen
,
to prevent them from being rewritten by any further function run.
1 |
varcli |
Acronym of the name of the studied climatic variable, as in the data file name. |
anyi |
Initial year of the study period |
anyf |
Final year of the study period |
suffix |
Suffix to be inserted (or removed) in the output file names. |
restore |
Set this parameter to |
The variable (or file base) name is separated from the appended suffix by a
hyphen. The purpose of this function is to allow a new application of
homogen
to the same data with different parameters without overwriting
the previous results.
This function does not return any value.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 | #Set a temporal working directory and write input files:
wd <- tempdir()
wd0 <- setwd(wd)
data(Ptest)
dim(dat) <- c(720,20)
dat[601:720,5] <- dat[601:720,5]*1.8
write(dat[481:720,1:5],'pcp_1991-2010.dat')
write.table(est.c[1:5,1:5],'pcp_1991-2010.est',row.names=FALSE,col.names=FALSE)
homogen('pcp',1991,2010,std=2) #homogenization
#Now run the example:
outrename('pcp',1991,2010,'ok')
#Return to user's working directory:
setwd(wd0)
#Input and output files can be found in directory:
print(wd)
|
Loading required package: maps
Loading required package: mapdata
HOMOGEN() APPLICATION OUTPUT (From R's contributed package 'climatol' 3.1.1)
=========== Homogenization of pcp, 1991-2010. (Thu Jan 17 01:35:10 2019)
Parameters: varcli=pcp anyi=1991 anyf=2010 suf=NA nm=NA nref=10,10,4 std=2 swa=NA ndec=1 dz.max=5 dz.min=-5 wd=0,0,100 snht1=25 snht2=25 tol=0.02 maxdif=0.05 mxdif=0.05 maxite=999 force=FALSE wz=0.001 trf=0 mndat=NA gp=3 ini=NA na.strings=NA vmin=NA vmax=NA nclust=100 cutlev=NA grdcol=#666666 mapcol=#666666 hires=TRUE expl=FALSE metad=FALSE sufbrk=m tinc=NA tz=UTC cex=1.2 verb=TRUE
Read 1200 items
Data matrix: 240 data x 5 stations
-------------------------------------------
Stations in the 2 clusters:
$`1`
Z Code Name
1 183 S031 Station_031
4 129 S051 Station_051
$`2`
Z Code Name
2 125 S047 Station_047
3 100 S098 Station_098
5 79 S081 Station_081
---------------------------------------------
Computing inter-station distances: 1 2 3 4
========== STAGE 1 (SNHT on overlapping temporal windows) ===========
Computation of missing data with outlier removal
(Suggested data replacements are provisional)
Station(rank) Date: Observed -> Suggested (Anomaly, in std. devs.)
S098(3) 1991-10-01: 298.4 -> 92.9 (5.56)
S081(5) 2002-10-01: 724.68 -> 390.7 (6.02)
Performing shift analysis on the 5 series...
========== STAGE 2 (SNHT on the whole series) =======================
Computation of missing data with outlier removal
(Suggested data replacements are provisional)
Station(rank) Date: Observed -> Suggested (Anomaly, in std. devs.)
S098(3) 2008-09-01: 111.3 -> 290.8 (-5.09)
Performing shift analysis on the 5 series...
S081(5) breaks at 2000-12-01 (26.3)
Update number of series: 5 + 1 = 6
Computation of missing data with outlier removal
(Suggested data replacements are provisional)
Station(rank) Date: Observed -> Suggested (Anomaly, in std. devs.)
S081-2(6) 1993-10-01: 309 -> 111.2 (5.58)
Performing shift analysis on the 6 series...
========== STAGE 3 (Final computation of all missing data) ==========
Computing inter-station weights... (done)
Computation of missing data with outlier removal
(Suggested data replacements are provisional)
The following lines will have one of these formats:
Station(rank) Date: Observed -> Suggested (Anomaly, in std. devs.)
Iteration Max.data.difference (Station_code)
2 -5.569 (S081-2)
3 -3.255 (S081-2)
4 -2.049 (S081-2)
5 -1.308 (S081-2)
6 -0.843 (S081-2)
7 -0.547 (S081-2)
8 -0.356 (S081-2)
9 -0.232 (S081-2)
10 -0.152 (S081-2)
11 -0.099 (S081-2)
12 -0.065 (S081-2)
13 -0.043 (S081-2)
Last series readjustment (please, be patient...)
======== End of the homogenization process, after 2.67 secs
----------- Final computations:
ACmx: Station maximum absolute autocorrelations of anomalies
Min. 1st Qu. Median Mean 3rd Qu. Max.
0.2000 0.2275 0.2900 0.2733 0.3000 0.3500
SNHT: Standard normal homogeneity test (on anomaly series)
Min. 1st Qu. Median Mean 3rd Qu. Max.
1.200 2.300 2.400 2.583 2.575 4.600
RMSE: Root mean squared error of the estimated data
Min. 1st Qu. Median Mean 3rd Qu. Max.
30.49 31.56 32.73 36.98 38.67 54.11
POD: Percentage of original data
Min. 1st Qu. Median Mean 3rd Qu. Max.
49.00 57.50 89.50 78.67 96.75 98.00
ACmx SNHT RMSE POD Code Name
1 0.30 2.6 40.5 98 S031 Station_031
2 0.20 2.3 31.3 96 S047 Station_047
3 0.21 2.3 32.2 97 S098 Station_098
4 0.28 2.5 33.3 83 S051 Station_051
5 0.35 1.2 54.1 49 S081 Station_081
6 0.30 4.6 30.5 49 S081-2 Station_081-2
----------- Generated output files: -------------------------
pcp_1991-2010.txt : This text output
pcp_1991-2010_out.csv : List of corrected outliers
pcp_1991-2010_brk.csv : List of corrected breaks
pcp_1991-2010.pdf : Diagnostic graphics
pcp_1991-2010.rda : Homogenization results. Postprocess with (examples):
dahstat('pcp',1991,2010) #get averages in file pcp_1991-2010-me.csv
dahstat('pcp',1991,2010,stat='tnd') #get OLS trends and their p-values
dahgrid('pcp',1991,2010,grid=YOURGRID) #get homogenized grids
... (See other options in the package documentation)
[1] "/work/tmp/tmp/RtmpDj8rfR"
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.