Running 'mefa4comparisons.R' [178s]
  Running 'mefa4examples.R' [3s]
Running the tests in 'tests/mefa4comparisons.R' failed.
Complete output:
  > ## performance comparison
  > library(mefa)
  mefa 3.2-8 	 2021-10-06
  > library(mefa4)
  Loading required package: Matrix
  mefa4 0.3-9 	 2022-09-08
  
  Attaching package: 'mefa4'
  
  The following objects are masked from 'package:mefa':
  
      samp, taxa, xtab
  
  > 
  > data(abmibirds)
  > ## NONE: no species was recorded (8)
  > ## SNI: Species Not Identified (216)
  > ## VNA: Variable Not Applicable (6)
  > ## DNC: Did Not Collect (13)
  > ## PNA: Protocol Not Available (0 in this case)
  > 
  > ## S3 mefa processing
  > b3 <- abmibirds
  > b3 <- b3[!(b3$Scientific.Name %in% c("VNA", "DNC", "PNA")),]
  > levels(b3$Scientific.Name)[levels(b3$Scientific.Name) %in% c("NONE", "SNI")] <- "zero.pseudo"
  > b3$Counts <- ifelse(b3$Scientific.Name == "zero.pseudo", 0, 1)
  > b3$Label <- with(b3, paste(ABMI.Site, Year, Point.Count.Station, sep="_"))
  > x3 <- b3[!duplicated(b3$Label), c("Label", "ABMI.Site", "Year", "Field.Date", "Point.Count.Station",
  +     "Wind.Conditions", "Precipitation")]
  > rownames(x3) <- x3$Label
  > z3 <- b3[!duplicated(b3$Scientific.Name), c("Common.Name",
  +     "Scientific.Name", "Taxonomic.Resolution", "Unique.Taxonomic.Identification.Number")]
  > rownames(z3) <- z3$Scientific.Name
  > z3 <- z3[z3$Scientific.Name != "zero.pseudo",]
  > t31 <- system.time(s3 <- suppressWarnings(stcs(b3[,c("Label","Scientific.Name","Counts")])))
  > t32 <- system.time(m30 <- mefa(s3))
  > t33 <- system.time(m31 <- mefa(s3, x3, z3))
  > y30 <- m30$xtab
  > t34 <- system.time(m32 <- mefa(y30, x3, z3))
  > 
  > ## S4 mefa4 processing
  > b4 <- abmibirds
  > b4$Label <- with(b4, paste(ABMI.Site, Year, Point.Count.Station, sep="_"))
  > x4 <- b4[!duplicated(b4$Label), c("Label", "ABMI.Site", "Year", "Field.Date", "Point.Count.Station",
  +     "Wind.Conditions", "Precipitation")]
  > rownames(x4) <- x4$Label
  > z4 <- b4[!duplicated(b4$Scientific.Name), c("Common.Name",
  +     "Scientific.Name", "Taxonomic.Resolution", "Unique.Taxonomic.Identification.Number")]
  > rownames(z4) <- z4$Scientific.Name
  > t41 <- system.time(s4 <- Xtab(~ Label + Scientific.Name, b4, cdrop = c("NONE", "SNI"), 
  +     subset = !(b4$Scientific.Name %in% c("VNA", "DNC", "PNA")), drop.unused.levels = TRUE))
  > t42 <- system.time(m40 <- Mefa(s4))
  > t43 <- system.time(m41 <- Mefa(s4, x4, z4))
  > y40 <- as.matrix(m40@xtab)
  > t44 <- system.time(m42 <- Mefa(y40, x4, z4))
  > 
  > res <- cbind("SIZE, *=3"=c("b*"=object.size(b3),
  +     "s*"=object.size(s3),
  +     "y*0"=object.size(y30),
  +     "m*0"=object.size(m30),
  +     "m*1"=object.size(m31),
  +     "m*2"=object.size(m32)),
  + "SIZE, *=4"=c("b*"=object.size(b4),
  +     "s*"=object.size(s4),
  +     "y*0"=object.size(y40),
  +     "m*0"=object.size(m40),
  +     "m*1"=object.size(m41),
  +     "m*2"=object.size(m42)),
  + "TIME, *=3"=c("b*"=NA,
  +     "s*"=t31[3],
  +     "y*0"=NA,
  +     "m*0"=t32[3],
  +     "m*1"=t33[3],
  +     "m*2"=t34[3]),
  + "TIME, *=4"=c("b*"=NA,
  +     "s*"=t41[3],
  +     "y*0"=NA,
  +     "m*0"=t42[3],
  +     "m*1"=t43[3],
  +     "m*2"=t44[3]))
  > (res <- cbind(res, "SIZE"=res[,2]/res[,1], "TIME"=res[,4]/res[,3]))
      SIZE, *=3 SIZE, *=4 TIME, *=3 TIME, *=4      SIZE       TIME
  b*    6522600   5813728        NA        NA 0.8913206         NA
  s*    1458872    704384      0.52      0.05 0.4828278 0.09615385
  y*0   6323296   6323008        NA        NA 0.9999545         NA
  m*0   6324888    705560      2.32      0.00 0.1115530 0.00000000
  m*1   7005368   1385648      1.72      0.00 0.1977980 0.00000000
  m*2   7005368   1385648      0.03      0.02 0.1977980 0.66666667
  > 
  > ## debugging
  > 
  > dim(y30)
  [1] 3534  214
  > dim(y40)
  [1] 3534  214
  > 
  > setdiff(rownames(y30), rownames(y40))
  character(0)
  > setdiff(rownames(y40), rownames(y30))
  character(0)
  > 
  > setdiff(colnames(y30), colnames(y40))
  character(0)
  > setdiff(colnames(y40), colnames(y30))
  character(0)
  > 
  > system.time(xx3 <- aggregate(m31, "ABMI.Site"))
     user  system elapsed 
     0.35    0.06    0.40 
  > system.time(xx4 <- groupSums(m41, 1, m41@samp$ABMI.Site))
     user  system elapsed 
     0.03    0.00    0.03 
  > as.Mefa(xx3)
  Object of class "Mefa"
    ..@ xtab: 330 x 214 sparse Matrix
    ..@ samp: NULL
    ..@ taxa: data frame with 4 variables
    ..@ join: left 
  > xx4
  Object of class "Mefa"
    ..@ xtab: 330 x 214 sparse Matrix
    ..@ samp: NULL
    ..@ taxa: data frame with 4 variables
    ..@ join: left 
  > 
  > 
  > proc.time()
     user  system elapsed 
     7.92    0.62    8.53