Last updated on 2020-02-19 05:48:02 CET.
| Package | ERROR | NOTE | OK |
|---|---|---|---|
| bSims | 13 | ||
| dclone | 3 | 10 | |
| dcmle | 13 | ||
| detect | 13 | ||
| intrval | 13 | ||
| mefa | 13 | ||
| mefa4 | 1 | 12 | |
| opticut | 13 | ||
| pbapply | 2 | 11 | |
| PVAClone | 13 | ||
| ResourceSelection | 13 | ||
| sharx | 13 |
Current CRAN status: OK: 13
Current CRAN status: NOTE: 3, OK: 10
Version: 2.3-0
Check: package dependencies
Result: NOTE
Package suggested but not available for checking: ‘BRugs’
Flavors: r-patched-solaris-x86, r-release-osx-x86_64, r-oldrel-osx-x86_64
Current CRAN status: OK: 13
Current CRAN status: OK: 13
Current CRAN status: OK: 13
Current CRAN status: OK: 13
Current CRAN status: ERROR: 1, OK: 12
Version: 0.3-6
Check: examples
Result: ERROR
Running examples in 'mefa4-Ex.R' failed
The error most likely occurred in:
> base::assign(".ptime", proc.time(), pos = "CheckExEnv")
> ### Name: Mefa
> ### Title: 'Mefa' Class
> ### Aliases: Mefa Mefa-class MefaDataFrame MefaMatrix mefa stcs
> ### MefaDataFrame-class MefaMatrix-class mefa-class stcs-class
> ### dim,Mefa-method dimnames,Mefa-method dimnames<-,Mefa,list-method
> ### t,Mefa-method show,Mefa-method stack,Mefa-method
> ### Keywords: manip
>
> ### ** Examples
>
> x <- data.frame(
+ sample = paste("Sample", c(1,1,2,2,3,4), sep="."),
+ species = c(paste("Species", c(1,1,1,2,3), sep="."), "zero.pseudo"),
+ count = c(1,2,10,3,4,0))
> samp <- data.frame(samples=levels(x$sample), var1=1:2)
Error in data.frame(samples = levels(x$sample), var1 = 1:2) :
arguments imply differing number of rows: 0, 2
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Version: 0.3-6
Check: tests
Result: ERROR
Running 'mefa4comparisons.R' [11s/13s]
Running 'mefa4examples.R' [2s/3s]
Running the tests in 'tests/mefa4examples.R' failed.
Complete output:
> #devtools::install_github("psolymos/mefa4")
> ## examples
>
> ## load library
> library(mefa)
mefa 3.2-7 2016-01-11
> library(mefa4)
Loading required package: Matrix
mefa4 0.3-6 2019-06-20
Attaching package: 'mefa4'
The following objects are masked from 'package:mefa':
samp, taxa, xtab
>
> ## run examples with \dontrun sections
>
> help_pages <- c("abmibirds",
+ "find_max",
+ "groupSums", "mbind", "Mefa",
+ "Melt",
+ "nameAlnum", "nonDuplicated",
+ "%notin%", "r2rmd",
+ "samp", "Xtab")
>
> for (i in help_pages) {
+ cat("\n\n---------- mefa4 example:", i, "----------\n\n")
+ eval(parse(text=paste0("example('", i,
+ "', package = 'mefa4', run.dontrun = TRUE)")))
+ }
---------- mefa4 example: abmibirds ----------
abmbrd> data(abmibirds)
abmbrd> str(abmibirds)
'data.frame': 59341 obs. of 21 variables:
$ Rotation : Factor w/ 2 levels "Prototype","Rotation 1": 1 1 1 1 1 1 1 1 1 1 ...
$ ABMI.Site : int 630 630 630 630 630 630 630 630 630 630 ...
$ Year : int 2003 2003 2003 2003 2003 2003 2003 2003 2003 2003 ...
$ Field.Date : Factor w/ 132 levels "01-Jun-03","01-Jun-04",..: 46 46 46 46 46 46 46 46 46 46 ...
$ Field.Crew.Members : Factor w/ 67 levels "ABL","ABL/RSW",..: 15 15 15 15 15 15 15 15 15 15 ...
$ Identification.Date : Factor w/ 135 levels "01-Feb-10","01-Jun-08",..: 135 135 135 135 135 135 135 135 135 135 ...
$ Identification.Analyst : Factor w/ 13 levels "CF/CS/TH","CLS/MBI",..: 11 11 11 11 11 11 11 11 11 11 ...
$ Point.Count.Station : int 1 1 1 1 1 1 1 1 2 2 ...
$ Wind.Conditions : Factor w/ 7 levels "0","1","2","3",..: 4 4 4 4 4 4 4 4 4 4 ...
$ Precipitation : Factor w/ 5 levels "DNC","Drizzle",..: 4 4 4 4 4 4 4 4 4 4 ...
$ Start.of.Point.Count : Factor w/ 434 levels "10:00","10:01",..: 152 152 152 152 152 152 152 152 178 178 ...
$ End.of.Point.Count : Factor w/ 42 levels "10:07","10:21",..: 42 42 42 42 42 42 42 42 42 42 ...
$ Common.Name : Factor w/ 217 levels "Accipiters","Alder Flycatcher",..: 184 184 142 142 142 150 208 161 208 181 ...
$ Scientific.Name : Factor w/ 218 levels "Accipiter","Accipiter gentilis",..: 207 207 173 173 173 209 201 149 201 57 ...
$ Taxonomic.Resolution : Factor w/ 5 levels "Family","Genus",..: 3 3 3 3 3 3 3 3 3 3 ...
$ Unique.Taxonomic.Identification.Number: Factor w/ 215 levels "174469","174479",..: 130 130 214 214 214 149 122 161 122 195 ...
$ Time.First.Detected : Factor w/ 129 levels ".1",".2",".3",..: 87 97 112 87 31 40 13 68 31 13 ...
$ Interval.1 : Factor w/ 6 levels "","0","1","DNC",..: 5 5 5 5 5 5 5 5 5 5 ...
$ Interval.2 : Factor w/ 6 levels "","0","1","DNC",..: 5 5 5 5 5 5 5 5 5 5 ...
$ Interval.3 : Factor w/ 6 levels "","0","1","DNC",..: 5 5 5 5 5 5 5 5 5 5 ...
$ Behaviour : Factor w/ 21 levels "Alarm Calling",..: 19 19 19 19 19 19 19 19 19 19 ...
---------- mefa4 example: find_max ----------
fnd_mx> ## numeric vector
fnd_mx> compare_sets(1:10, 8:15)
xlength ylength intersect union xbutnoty ybutnotx
labels 10 8 3 15 7 5
unique 10 8 3 15 7 5
fnd_mx> ## factor with 'zombie' labels
fnd_mx> compare_sets(factor(1:10, levels=1:10), factor(8:15, levels=1:15))
xlength ylength intersect union xbutnoty ybutnotx
labels 10 15 10 15 0 5
unique 10 8 3 15 7 5
fnd_mx> (mat <- matrix(rnorm(10*5), 10, 5))
[,1] [,2] [,3] [,4] [,5]
[1,] -2.25115134 1.1380605 0.39014031 -0.2289808 -1.038531623
[2,] 0.38735324 -0.6412394 0.42222993 -0.1867742 -1.081927051
[3,] 1.50520350 -0.7076390 -1.26998891 -0.1122049 -0.756342239
[4,] 0.98119226 -0.3203242 1.66809595 -0.9666750 0.005817471
[5,] 0.15367711 -1.5652477 -0.40533494 -0.7517001 -0.846028904
[6,] -0.12810679 -1.1541756 0.26077967 -0.1526124 1.668180015
[7,] 0.10064873 0.1204347 0.98762268 0.3968991 -1.178891166
[8,] -0.03572431 -0.0704294 -0.82586354 0.1891311 -1.228069282
[9,] 1.33189159 -1.3036537 0.06572903 -1.1562431 -0.735217530
[10,] -1.01367166 -2.1623647 0.61000271 -0.3152456 1.053303056
fnd_mx> (m <- find_max(mat))
index value
1 X2 1.1380605
2 X3 0.4222299
3 X1 1.5052035
4 X3 1.6680960
5 X1 0.1536771
6 X5 1.6681800
7 X3 0.9876227
8 X4 0.1891311
9 X1 1.3318916
10 X5 1.0533031
fnd_mx> ## column indices
fnd_mx> as.integer(m$index)
[1] 2 3 1 3 1 5 3 4 1 5
fnd_mx> find_min(mat)
index value
1 X1 -2.251151
2 X5 -1.081927
3 X3 -1.269989
4 X4 -0.966675
5 X2 -1.565248
6 X2 -1.154176
7 X5 -1.178891
8 X5 -1.228069
9 X2 -1.303654
10 X2 -2.162365
fnd_mx> map <- cbind(c("a","b","c","d","e","f","g"),
fnd_mx+ c("A","B","B","C","D","D","E"))
fnd_mx> #x <- factor(sample(map[1:6,1], 100, replace=TRUE), levels=map[,1])
fnd_mx> x <- as.factor(sample(map[1:6,1], 100, replace=TRUE))
fnd_mx> x[2] <- NA
fnd_mx> table(x, reclass(x, map, all = FALSE), useNA="always")
x A B C D <NA>
a 20 0 0 0 0
b 0 16 0 0 0
c 0 12 0 0 0
d 0 0 12 0 0
e 0 0 0 21 0
f 0 0 0 18 0
<NA> 0 0 0 0 1
fnd_mx> table(x, reclass(x, map, all = TRUE), useNA="always")
x A B C D E <NA>
a 20 0 0 0 0 0
b 0 16 0 0 0 0
c 0 12 0 0 0 0
d 0 0 12 0 0 0
e 0 0 0 21 0 0
f 0 0 0 18 0 0
<NA> 0 0 0 0 0 1
fnd_mx> map[c(4, 7), 2] <- NA
fnd_mx> table(x, reclass(x, map, all = FALSE, allow_NA = TRUE), useNA="always")
x A B D <NA>
a 20 0 0 0
b 0 16 0 0
c 0 12 0 0
d 0 0 0 12
e 0 0 21 0
f 0 0 18 0
<NA> 0 0 0 1
fnd_mx> table(x, reclass(x, map, all = TRUE, allow_NA = TRUE), useNA="always")
x A B D <NA>
a 20 0 0 0
b 0 16 0 0
c 0 12 0 0
d 0 0 0 12
e 0 0 21 0
f 0 0 18 0
<NA> 0 0 0 1
fnd_mx> (mat2 <- exp(mat) / rowSums(exp(mat)))
[,1] [,2] [,3] [,4] [,5]
[1,] 0.01798856 0.53322737 0.25240319 0.13589828 0.06048261
[2,] 0.31384474 0.11220256 0.32498372 0.17675612 0.07221286
[3,] 0.67827498 0.07419600 0.04228195 0.13457806 0.07066900
[4,] 0.26459929 0.07200245 0.52590483 0.03772599 0.09976743
[5,] 0.39628925 0.07103833 0.22658776 0.16025514 0.14582953
[6,] 0.10165941 0.03643607 0.14998189 0.09919846 0.61272417
[7,] 0.16472492 0.16801662 0.39991453 0.22152318 0.04582075
[8,] 0.25155194 0.24297156 0.11414964 0.31497866 0.07634820
[9,] 0.63971050 0.04585437 0.18034166 0.05313740 0.08095607
[10,] 0.06134889 0.01945072 0.31114266 0.12334721 0.48471052
fnd_mx> (rmat2 <- redistribute(mat2, source = 1, target = 2:4))
[,1] [,2] [,3] [,4] [,5]
[1,] 0 0.54363615 0.2573302 0.13855106 0.06048261
[2,] 0 0.16956003 0.4911140 0.26711309 0.07221286
[3,] 0 0.27465044 0.1565146 0.49816597 0.07066900
[4,] 0 0.10197539 0.7448267 0.05343044 0.09976743
[5,] 0 0.13252093 0.4226960 0.29895353 0.14582953
[6,] 0 0.04940476 0.2033649 0.13450615 0.61272417
[7,] 0 0.20307441 0.4833594 0.26774547 0.04582075
[8,] 0 0.33391037 0.1568733 0.43286812 0.07634820
[9,] 0 0.15086693 0.5933479 0.17482908 0.08095607
[10,] 0 0.02207943 0.3531928 0.14001726 0.48471052
fnd_mx> colMeans(mat2)
[1] 0.2889992 0.1375396 0.2527692 0.1457399 0.1749521
fnd_mx> colMeans(rmat2)
[1] 0.0000000 0.1981679 0.3862620 0.2406180 0.1749521
fnd_mx> stopifnot(abs(sum(mat2) - sum(rmat2)) < 10^-6)
---------- mefa4 example: groupSums ----------
grpSms> x <- data.frame(
grpSms+ sample = paste("Sample", c(1,1,2,2,3,4), sep="."),
grpSms+ species = c(paste("Species", c(1,1,1,2,3), sep="."),
grpSms+ "zero.pseudo"), count = c(1,2,10,3,4,0))
grpSms> samp <- data.frame(samples=levels(x$sample), var1=1:2)
Error in data.frame(samples = levels(x$sample), var1 = 1:2) :
arguments imply differing number of rows: 0, 2
Calls: eval ... source -> withVisible -> eval -> eval -> data.frame
Execution halted
Flavor: r-devel-linux-x86_64-debian-clang
Current CRAN status: OK: 13
Current CRAN status: NOTE: 2, OK: 11
Version: 1.4-2
Check: dependencies in R code
Result: NOTE
No protocol specified
No protocol specified
Flavors: r-release-osx-x86_64, r-oldrel-osx-x86_64
Current CRAN status: OK: 13
Current CRAN status: OK: 13
Current CRAN status: OK: 13