Conversion of a hyperSpec object into a data frame or matrix

Source: R/as.data.frame.R

as.data.frame() returns x@data (as data.frame), as.matrix() returns the spectra matrix x@data$spc as matrix.

The data.frame returned by as.long.df is guaranteed to have columns spc and .wavelength. If nwl (x) == 0 these columns will be NA.

# S3 method for hyperSpec
as.data.frame(x, row.names = TRUE, optional = NULL, ...)

# S3 method for hyperSpec
as.matrix(x, ...)

as.wide.df(x, wl.prefix = "")

as.long.df(x, rownames = FALSE, wl.factor = FALSE, na.rm = TRUE)

as.t.df(x)

Arguments

x

a hyperSpec object
row.names

if TRUE, a column .row is created containing row names or row indices if no rownames are set. If character vector, the rownames are set accordingly.
optional

ignored
...

ignored
wl.prefix

prefix to prepend wavelength column names
rownames

should the rownames be in column .rownames of the long-format data.frame?
wl.factor

should the wavelengths be returned as a factor (instead of numeric)?
na.rm

if TRUE, rows where spc is not NA are deleted.

Value

x@data and x@data$spc (== x$spc == x[[]]), respectively.

as.wide.df returns a data.frame that consists of the extra data and the spectra matrix converted to a data.frame. The spectra matrix is expanded in place.

as.long.df returns the stacked or molten version of x@data. The wavelengths are in column .wavelength.

as.t.df returns a data.frame similar to as.long.df, but each spectrum in its own column. This is useful for exporting summary spectra, see the example.

See also

base::as.data.frame()

and base::as.matrix()

[[]] for a shortcut to as.matrix

utils::stack() and reshape::melt() or reshape2::melt() for other functions producing long-format data.frames.

Author

C. Beleites

Examples


as.data.frame(faux_cell[1:3, , 600 ~ 620])

#>        x     y region spc.602 spc.606 spc.610 spc.614 spc.618 .row
#> 1 -11.55 -4.77 matrix      15      22      15      13      15    1
#> 2 -10.55 -4.77 matrix     168     166     159     175     160    2
#> 3  -9.55 -4.77 matrix     112     113      99     115     119    3
as.matrix(faux_cell[1:3, , 600 ~ 620])

#>      602 606 610 614 618
#> [1,]  15  22  15  13  15
#> [2,] 168 166 159 175 160
#> [3,] 112 113  99 115 119
lm(c ~ spc, data = flu[, , 450])

#> 
#> Call:
#> lm(formula = c ~ spc, data = flu[, , 450])
#> 
#> Coefficients:
#> (Intercept)          spc  
#>   0.0038493    0.0004407  
#> 

as.wide.df(faux_cell[1:5, , 600 ~ 610])

#>        x     y region 602 606 610
#> 1 -11.55 -4.77 matrix  15  22  15
#> 2 -10.55 -4.77 matrix 168 166 159
#> 3  -9.55 -4.77 matrix 112 113  99
#> 4  -8.55 -4.77 matrix  23  33  39
#> 5  -7.55 -4.77 matrix   3   0   1
summary(as.wide.df(faux_cell[1:5, , 600 ~ 610]))

#>        x                y             region       602             606       
#>  Min.   :-11.55   Min.   :-4.77   cell   :0   Min.   :  3.0   Min.   :  0.0  
#>  1st Qu.:-10.55   1st Qu.:-4.77   matrix :5   1st Qu.: 15.0   1st Qu.: 22.0  
#>  Median : -9.55   Median :-4.77   nucleus:0   Median : 23.0   Median : 33.0  
#>  Mean   : -9.55   Mean   :-4.77               Mean   : 64.2   Mean   : 66.8  
#>  3rd Qu.: -8.55   3rd Qu.:-4.77               3rd Qu.:112.0   3rd Qu.:113.0  
#>  Max.   : -7.55   Max.   :-4.77               Max.   :168.0   Max.   :166.0  
#>       610       
#>  Min.   :  1.0  
#>  1st Qu.: 15.0  
#>  Median : 39.0  
#>  Mean   : 62.6  
#>  3rd Qu.: 99.0  
#>  Max.   :159.0  

as.long.df(flu[, , 405 ~ 410])

#>      .wavelength       spc         filename    c
#> 1          405.0  27.15000 rawdata/flu1.txt 0.05
#> 2          405.0  66.80133 rawdata/flu2.txt 0.10
#> 3          405.0  93.14433 rawdata/flu3.txt 0.15
#> 4          405.0 130.66367 rawdata/flu4.txt 0.20
#> 5          405.0 167.26667 rawdata/flu5.txt 0.25
#> 6          405.0 198.43033 rawdata/flu6.txt 0.30
#> 1.1        405.5  32.34467 rawdata/flu1.txt 0.05
#> 2.1        405.5  63.71533 rawdata/flu2.txt 0.10
#> 3.1        405.5 103.06767 rawdata/flu3.txt 0.15
#> 4.1        405.5 139.99833 rawdata/flu4.txt 0.20
#> 5.1        405.5 171.89833 rawdata/flu5.txt 0.25
#> 6.1        405.5 209.45800 rawdata/flu6.txt 0.30
#> 1.2        406.0  33.37867 rawdata/flu1.txt 0.05
#> 2.2        406.0  66.71200 rawdata/flu2.txt 0.10
#> 3.2        406.0 106.19367 rawdata/flu3.txt 0.15
#> 4.2        406.0 143.79767 rawdata/flu4.txt 0.20
#> 5.2        406.0 177.47067 rawdata/flu5.txt 0.25
#> 6.2        406.0 215.78500 rawdata/flu6.txt 0.30
#> 1.3        406.5  34.41933 rawdata/flu1.txt 0.05
#> 2.3        406.5  69.58233 rawdata/flu2.txt 0.10
#> 3.3        406.5 110.18633 rawdata/flu3.txt 0.15
#> 4.3        406.5 148.42000 rawdata/flu4.txt 0.20
#> 5.3        406.5 184.62467 rawdata/flu5.txt 0.25
#> 6.3        406.5 224.58700 rawdata/flu6.txt 0.30
#> 1.4        407.0  36.53133 rawdata/flu1.txt 0.05
#> 2.4        407.0  72.52967 rawdata/flu2.txt 0.10
#> 3.4        407.0 113.24867 rawdata/flu3.txt 0.15
#> 4.4        407.0 152.13267 rawdata/flu4.txt 0.20
#> 5.4        407.0 189.75233 rawdata/flu5.txt 0.25
#> 6.4        407.0 232.52800 rawdata/flu6.txt 0.30
#> 1.5        407.5  37.64767 rawdata/flu1.txt 0.05
#> 2.5        407.5  74.55833 rawdata/flu2.txt 0.10
#> 3.5        407.5 119.17300 rawdata/flu3.txt 0.15
#> 4.5        407.5 159.31033 rawdata/flu4.txt 0.20
#> 5.5        407.5 198.11533 rawdata/flu5.txt 0.25
#> 6.5        407.5 240.77133 rawdata/flu6.txt 0.30
#> 1.6        408.0  38.13700 rawdata/flu1.txt 0.05
#> 2.6        408.0  77.04800 rawdata/flu2.txt 0.10
#> 3.6        408.0 121.31333 rawdata/flu3.txt 0.15
#> 4.6        408.0 165.05233 rawdata/flu4.txt 0.20
#> 5.6        408.0 205.56267 rawdata/flu5.txt 0.25
#> 6.6        408.0 248.04667 rawdata/flu6.txt 0.30
#> 1.7        408.5  39.17700 rawdata/flu1.txt 0.05
#> 2.7        408.5  80.25967 rawdata/flu2.txt 0.10
#> 3.7        408.5 124.67533 rawdata/flu3.txt 0.15
#> 4.7        408.5 168.68967 rawdata/flu4.txt 0.20
#> 5.7        408.5 208.41933 rawdata/flu5.txt 0.25
#> 6.7        408.5 256.89133 rawdata/flu6.txt 0.30
#> 1.8        409.0  40.73567 rawdata/flu1.txt 0.05
#> 2.8        409.0  82.53867 rawdata/flu2.txt 0.10
#> 3.8        409.0 129.56867 rawdata/flu3.txt 0.15
#> 4.8        409.0 175.45900 rawdata/flu4.txt 0.20
#> 5.8        409.0 217.55267 rawdata/flu5.txt 0.25
#> 6.8        409.0 262.73900 rawdata/flu6.txt 0.30
#> 1.9        409.5  41.38133 rawdata/flu1.txt 0.05
#> 2.9        409.5  84.49167 rawdata/flu2.txt 0.10
#> 3.9        409.5 134.11733 rawdata/flu3.txt 0.15
#> 4.9        409.5 181.58100 rawdata/flu4.txt 0.20
#> 5.9        409.5 224.74633 rawdata/flu5.txt 0.25
#> 6.9        409.5 270.27133 rawdata/flu6.txt 0.30
#> 1.10       410.0  44.25133 rawdata/flu1.txt 0.05
#> 2.10       410.0  88.15167 rawdata/flu2.txt 0.10
#> 3.10       410.0 139.98667 rawdata/flu3.txt 0.15
#> 4.10       410.0 185.69233 rawdata/flu4.txt 0.20
#> 5.10       410.0 231.03567 rawdata/flu5.txt 0.25
#> 6.10       410.0 281.82867 rawdata/flu6.txt 0.30
summary(as.long.df(flu[, , 405 ~ 410]))

#>   .wavelength         spc           filename               c        
#>  Min.   :405.0   Min.   : 27.15   Length:66          Min.   :0.050  
#>  1st Qu.:406.0   1st Qu.: 75.18   Class :character   1st Qu.:0.100  
#>  Median :407.5   Median :137.05   Mode  :character   Median :0.175  
#>  Mean   :407.5   Mean   :137.80                      Mean   :0.175  
#>  3rd Qu.:409.0   3rd Qu.:196.02                      3rd Qu.:0.250  
#>  Max.   :410.0   Max.   :281.83                      Max.   :0.300  
summary(as.long.df(flu[, , 405 ~ 410], rownames = TRUE))

#>  .rownames  .wavelength         spc           filename               c        
#>  1:11      Min.   :405.0   Min.   : 27.15   Length:66          Min.   :0.050  
#>  2:11      1st Qu.:406.0   1st Qu.: 75.18   Class :character   1st Qu.:0.100  
#>  3:11      Median :407.5   Median :137.05   Mode  :character   Median :0.175  
#>  4:11      Mean   :407.5   Mean   :137.80                      Mean   :0.175  
#>  5:11      3rd Qu.:409.0   3rd Qu.:196.02                      3rd Qu.:0.250  
#>  6:11      Max.   :410.0   Max.   :281.83                      Max.   :0.300  
summary(as.long.df(flu[, , 405 ~ 410], wl.factor = TRUE))

#>   .wavelength      spc           filename               c        
#>  405    : 6   Min.   : 27.15   Length:66          Min.   :0.050  
#>  405.5  : 6   1st Qu.: 75.18   Class :character   1st Qu.:0.100  
#>  406    : 6   Median :137.05   Mode  :character   Median :0.175  
#>  406.5  : 6   Mean   :137.80                      Mean   :0.175  
#>  407    : 6   3rd Qu.:196.02                      3rd Qu.:0.250  
#>  407.5  : 6   Max.   :281.83                      Max.   :0.300  
#>  (Other):30                                                      
df <- as.t.df(apply(faux_cell, 2, mean_pm_sd))
head(df)

#>         .wavelength mean.minus.sd     mean mean.plus.sd
#> spc.602         602      42.04492 101.5691     161.0934
#> spc.606         606      42.14042 101.6023     161.0642
#> spc.610         610      41.82034 101.9383     162.0562
#> spc.614         614      42.85471 102.3966     161.9384
#> spc.618         618      42.61228 102.2571     161.9020
#> spc.622         622      42.58845 102.3257     162.0630

if (require(ggplot2)) {
  ggplot(df, aes(x = .wavelength)) +
    geom_ribbon(aes(ymin = mean.minus.sd, ymax = mean.plus.sd),
      fill = "#00000040"
    ) +
    geom_line(aes(y = mean))
}