mean_sd: Mean and Standard Deviation Calculate mean and standard...
In hyperSpec: Work with Hyperspectral Data, i.e. Spectra + Meta Information (Spatial, Time, Concentration, ...)
Description
Usage
Arguments
Value
Author(s)
See Also
Examples
Description
These functions are provided for convenience.
Usage
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## S4 method for signature 'numeric'
mean_sd(x, na.rm = TRUE, ...)
## S4 method for signature 'matrix'
mean_sd(x, na.rm = TRUE, ...)
## S4 method for signature 'hyperSpec'
mean_sd(x, na.rm = TRUE, ...)
## S4 method for signature 'numeric'
mean_pm_sd(x, na.rm = TRUE, ...)
## S4 method for signature 'matrix'
mean_pm_sd(x, na.rm = TRUE, ...)
## S4 method for signature 'hyperSpec'
mean_pm_sd(x, na.rm = TRUE, ...)
## S4 method for signature 'hyperSpec'
mean(x, na.rm = TRUE, ...)
## S4 method for signature 'hyperSpec'
quantile(x, probs = seq(0, 1, 0.5), na.rm = TRUE,
names = "num", ...)
Arguments
x
a numeric vector
na.rm
handed to mean and sd
...
ignored (needed to make function generic)
probs
the quantiles, see quantile
names
"pretty" results in percentages (like quantile's
names = TRUE), "num" results in the row names being as.character (probs)
(good for ggplot2 getting the order of the quantiles right). Otherwise, no names are assigned.
Value
mean_sd returns a vector with two values (mean and standard
deviation) of x.
mean_sd (matrix) returns a matrix with the mean spectrum in the first row and the standard deviation in the 2nd.
mean_sd returns a hyperSpec object with the mean spectrum in the first row and the standard deviation in the 2nd.
mean_pm_sd returns a vector with 3 values: mean - 1 sd, mean, mean + 1 sd
mean_pm_sd (matrix) returns a matrix containing mean - sd, mean, and mean + sd
rows.
For hyperSpec objects, mean_pm_sd returns a hyperSpec object containing mean - sd,
mean, and mean + sd spectra.
For hyperSpec object, mean returns a hyperSpec object containing the mean
spectrum.
For hyperSpec object, quantile returns a hyperSpec object containing the
respective quantile spectra.
Author(s)
C. Beleites
See Also
Examples
1
2
3
4
5
6
7
8
Example output
Loading required package: lattice
Loading required package: grid
Loading required package: ggplot2
Package hyperSpec, version 0.98-20161118
To get started, try
vignette ("introduction", package = "hyperSpec")
package?hyperSpec
vignette (package = "hyperSpec")
If you use this package please cite it appropriately.
citation("hyperSpec")
will give you the correct reference.
The project homepage is http://hyperspec.r-forge.r-project.org
hyperSpec object
2 spectra
1 data columns
11 data points / spectrum
wavelength: lambda/nm [numeric] 405.0 405.5 ... 410
data: (2 rows x 1 columns)
1. spc: I[fl]/"a.u." [matrix11] 113.90939 63.95161 ... 88.86944
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
mean 113.90939 120.08039 123.88961 128.63661 132.78711 138.26267 142.52667
sd 63.95161 66.68462 68.53711 71.32635 73.27403 76.26193 79.05704
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
mean 146.35206 151.43228 156.09817 161.82439 165.86478 171.5021 176.3894
sd 81.11082 83.44635 86.21839 88.86944 90.86983 93.5278 97.0369
[,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22]
mean 180.51522 185.6836 190.1309 195.8358 200.4855 204.6093 210.0138 214.64
sd 99.25456 102.7686 104.5448 107.9088 110.2483 111.9924 115.4464 118.26
[,23] [,24] [,25] [,26] [,27] [,28] [,29] [,30]
mean 219.1380 224.5761 227.9237 232.8236 237.7171 241.7527 246.4742 250.5289
sd 120.7447 123.9144 126.1828 128.7551 129.8156 132.8904 135.4853 137.1431
[,31] [,32] [,33] [,34] [,35] [,36] [,37] [,38]
mean 254.6781 258.4790 264.0061 267.9860 273.0221 277.4778 281.3341 285.0475
sd 139.3884 141.3262 144.7961 146.7983 149.8890 152.0896 154.3166 156.1366
[,39] [,40] [,41] [,42] [,43] [,44] [,45] [,46]
mean 290.1924 294.2909 298.3123 302.2134 307.5095 312.6365 316.1736 319.8145
sd 159.9184 162.8058 164.8594 165.1881 168.6816 172.6384 173.9014 175.6463
[,47] [,48] [,49] [,50] [,51] [,52] [,53] [,54]
mean 325.3752 328.9191 332.6454 336.7873 340.4211 344.5639 349.2603 351.5914
sd 178.6666 181.0399 183.3152 185.6277 186.6223 189.7741 192.6296 194.1671
[,55] [,56] [,57] [,58] [,59] [,60] [,61] [,62]
mean 354.2620 358.1013 361.8068 363.6526 365.7068 366.8592 369.8816 372.5533
sd 195.5245 196.7954 198.6743 200.5592 200.9523 201.5470 203.8599 204.7726
[,63] [,64] [,65] [,66] [,67] [,68] [,69] [,70]
mean 374.8713 375.8997 378.4399 378.6621 380.7669 382.7149 382.8039 383.6267
sd 206.1331 207.0960 208.1450 208.7843 210.1876 210.3305 210.1147 211.5687
[,71] [,72] [,73] [,74] [,75] [,76] [,77] [,78]
mean 383.4117 384.9124 384.9061 386.2123 386.0671 386.8118 387.1116 387.9868
sd 210.9692 211.1969 212.3513 210.9188 210.6814 211.5056 213.4941 212.2282
[,79] [,80] [,81] [,82] [,83] [,84] [,85] [,86]
mean 388.2645 386.9496 387.7631 387.6842 388.9684 388.8592 387.6974 387.5131
sd 213.8395 213.8715 212.7600 212.7473 214.0275 214.1388 213.7061 213.5430
[,87] [,88] [,89] [,90] [,91] [,92] [,93] [,94]
mean 387.8354 387.7904 388.0669 388.3706 388.3181 388.0719 386.9387 387.4204
sd 213.4142 212.5135 213.5708 211.6471 212.2151 212.5157 211.6122 212.4420
[,95] [,96] [,97] [,98] [,99] [,100] [,101] [,102]
mean 387.2329 385.1973 385.5947 385.0308 384.9724 385.6444 383.5018 382.0557
sd 213.0798 212.6830 211.5552 211.7677 211.6549 211.7323 208.8900 209.5972
[,103] [,104] [,105] [,106] [,107] [,108] [,109] [,110]
mean 380.9131 379.6323 379.4236 376.7526 376.1533 373.7147 371.8777 369.0225
sd 209.3029 208.5275 207.9218 207.2801 206.3606 205.1782 204.3870 202.7046
[,111] [,112] [,113] [,114] [,115] [,116] [,117] [,118]
mean 367.3478 364.0053 363.2114 361.1244 358.5899 354.8971 352.0969 349.0689
sd 202.7634 199.7319 199.7003 197.7912 196.5260 195.9355 193.7476 190.8617
[,119] [,120] [,121] [,122] [,123] [,124] [,125] [,126]
mean 347.7439 344.6271 340.4968 338.4603 335.9258 332.6344 329.3642 325.6729
sd 190.1415 188.8953 186.8400 185.6940 185.2942 183.5705 181.6199 178.8888
[,127] [,128] [,129] [,130] [,131] [,132] [,133] [,134]
mean 322.0702 319.5687 314.7917 312.4208 310.4492 305.3859 302.4756 299.4622
sd 176.0399 176.1274 173.3872 172.4460 170.4795 166.8526 166.5719 163.6277
[,135] [,136] [,137] [,138] [,139] [,140] [,141] [,142]
mean 296.7000 292.2196 288.3032 286.7105 283.4853 280.3511 276.9047 274.8581
sd 162.6267 161.2979 158.8969 157.3042 155.7632 153.7710 151.6023 150.2532
[,143] [,144] [,145] [,146] [,147] [,148] [,149] [,150]
mean 271.2237 269.0067 266.5739 263.3924 260.4180 258.1373 255.791 253.8093
sd 148.9218 148.0351 146.8918 144.1210 143.0114 142.0281 140.028 140.1034
[,151] [,152] [,153] [,154] [,155] [,156] [,157] [,158]
mean 249.5182 248.2199 245.3162 241.8370 240.8851 238.1019 235.3928 232.0592
sd 137.6791 135.9537 134.2462 131.9646 131.4004 130.0671 129.0721 128.4586
[,159] [,160] [,161] [,162] [,163] [,164] [,165] [,166]
mean 230.1664 227.5049 224.4877 221.6313 219.4647 215.9441 213.1634 210.1469
sd 127.6313 124.3675 123.2050 121.3864 120.2081 118.3317 116.9249 114.8779
[,167] [,168] [,169] [,170] [,171] [,172] [,173] [,174]
mean 208.6204 205.8629 203.6631 200.3850 198.2890 195.3428 192.3032 189.3392
sd 114.6096 113.3597 111.3558 109.7793 109.5708 106.8053 105.5473 103.6283
[,175] [,176] [,177] [,178] [,179] [,180] [,181]
mean 186.5108 183.8356 180.6879 178.78053 175.72864 173.40081 170.52147
sd 102.6725 101.4147 99.9830 98.97507 97.29897 95.44527 93.76262
hyperSpec object
2 spectra
1 data columns
181 data points / spectrum
wavelength: lambda/nm [numeric] 405.0 405.5 ... 495
data: (2 rows x 1 columns)
1. spc: I[fl]/"a.u." [matrix181] 113.90939 63.95161 ... 93.76262
mean.minus.sd mean mean.plus.sd
0.08145857 0.17500000 0.26854143
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
mean - sd 49.95778 53.39577 55.3525 57.31027 59.51308 62.00074 63.46963
mean 113.90939 120.08039 123.8896 128.63661 132.78711 138.26267 142.52667
mean + sd 177.86100 186.76501 192.4267 199.96296 206.06114 214.52459 221.58371
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
mean - sd 65.24124 67.98593 69.87977 72.95495 74.99495 77.97425 79.35249
mean 146.35206 151.43228 156.09817 161.82439 165.86478 171.50206 176.38939
mean + sd 227.46287 234.87862 242.31656 250.69383 256.73461 265.02986 273.42629
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
mean - sd 81.26066 82.9150 85.58614 87.92704 90.23721 92.61698 94.56743
mean 180.51522 185.6836 190.13094 195.83583 200.48550 204.60933 210.01383
mean + sd 279.76979 288.4521 294.67575 303.74462 310.73379 316.60168 325.46024
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
mean - sd 96.37996 98.39334 100.6617 101.7409 104.0685 107.9015 108.8622
mean 214.64000 219.13800 224.5761 227.9237 232.8236 237.7171 241.7527
mean + sd 332.90004 339.88266 348.4904 354.1065 361.5787 367.5328 374.6431
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
mean - sd 110.9890 113.3858 115.2896 117.1528 119.2100 121.1877 123.1330
mean 246.4742 250.5289 254.6781 258.4790 264.0061 267.9860 273.0221
mean + sd 381.9595 387.6720 394.0665 399.8052 408.8021 414.7843 422.9111
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
mean - sd 125.3882 127.0175 128.9109 130.2740 131.4851 133.4529 137.0253
mean 277.4778 281.3341 285.0475 290.1924 294.2909 298.3123 302.2134
mean + sd 429.5674 435.6506 441.1841 450.1108 457.0967 463.1717 467.4016
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
mean - sd 138.8279 139.9981 142.2722 144.1681 146.7086 147.8792 149.3303
mean 307.5095 312.6365 316.1736 319.8145 325.3752 328.9191 332.6454
mean + sd 476.1911 485.2749 490.0750 495.4608 504.0418 509.9590 515.9606
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
mean - sd 151.1596 153.7988 154.7898 156.6307 157.4243 158.7375 161.3059
mean 336.7873 340.4211 344.5639 349.2603 351.5914 354.2620 358.1013
mean + sd 522.4151 527.0434 534.3380 541.8899 545.7585 549.7865 554.8966
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
mean - sd 163.1325 163.0934 164.7544 165.3122 166.0218 167.7807 168.7382
mean 361.8068 363.6526 365.7068 366.8592 369.8816 372.5533 374.8713
mean + sd 560.4812 564.2118 566.6591 568.4062 573.7415 577.3258 581.0044
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
mean - sd 168.8037 170.2950 169.8777 170.5793 172.3844 172.6892 172.0580
mean 375.8997 378.4399 378.6621 380.7669 382.7149 382.8039 383.6267
mean + sd 582.9957 586.5849 587.4464 590.9546 593.0454 592.9186 595.1954
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
mean - sd 172.4425 173.7155 172.5548 175.2936 175.3857 175.3063 173.6175
mean 383.4117 384.9124 384.9061 386.2123 386.0671 386.8118 387.1116
mean + sd 594.3809 596.1093 597.2574 597.1311 596.7484 598.3174 600.6056
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
mean - sd 175.7587 174.4250 173.0780 175.0031 174.9369 174.9409 174.7203
mean 387.9868 388.2645 386.9496 387.7631 387.6842 388.9684 388.8592
mean + sd 600.2150 602.1040 600.8211 600.5230 600.4315 602.9959 602.9980
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
mean - sd 173.9914 173.9701 174.4212 175.2769 174.4961 176.7235 176.1030
mean 387.6974 387.5131 387.8354 387.7904 388.0669 388.3706 388.3181
mean + sd 601.4035 601.0562 601.2497 600.3040 601.6376 600.0177 600.5332
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
mean - sd 175.5562 175.3266 174.9784 174.1531 172.5142 174.0396 173.2631
mean 388.0719 386.9387 387.4204 387.2329 385.1973 385.5947 385.0308
mean + sd 600.5876 598.5509 599.8624 600.3128 597.8803 597.1499 596.7985
[,99] [,100] [,101] [,102] [,103] [,104] [,105]
mean - sd 173.3176 173.9120 174.6118 172.4585 171.6102 171.1048 171.5018
mean 384.9724 385.6444 383.5018 382.0557 380.9131 379.6323 379.4236
mean + sd 596.6273 597.3767 592.3918 591.6530 590.2161 588.1597 587.3454
[,106] [,107] [,108] [,109] [,110] [,111] [,112]
mean - sd 169.4725 169.7926 168.5365 167.4907 166.3179 164.5844 164.2734
mean 376.7526 376.1533 373.7147 371.8777 369.0225 367.3478 364.0053
mean + sd 584.0326 582.5139 578.8929 576.2647 571.7271 570.1112 563.7373
[,113] [,114] [,115] [,116] [,117] [,118] [,119]
mean - sd 163.5111 163.3332 162.0640 158.9616 158.3493 158.2073 157.6023
mean 363.2114 361.1244 358.5899 354.8971 352.0969 349.0689 347.7439
mean + sd 562.9118 558.9157 555.1159 550.8326 545.8446 539.9306 537.8854
[,120] [,121] [,122] [,123] [,124] [,125] [,126]
mean - sd 155.7317 153.6568 152.7663 150.6317 149.0639 147.7443 146.7840
mean 344.6271 340.4968 338.4603 335.9258 332.6344 329.3642 325.6729
mean + sd 533.5224 527.3368 524.1543 521.2200 516.2048 510.9840 504.5617
[,127] [,128] [,129] [,130] [,131] [,132] [,133]
mean - sd 146.0302 143.4413 141.4045 139.9748 139.9697 138.5334 135.9037
mean 322.0702 319.5687 314.7917 312.4208 310.4492 305.3859 302.4756
mean + sd 498.1101 495.6961 488.1790 484.8668 480.9288 472.2385 469.0476
[,134] [,135] [,136] [,137] [,138] [,139] [,140]
mean - sd 135.8345 134.0733 130.9217 129.4063 129.4063 127.7221 126.5801
mean 299.4622 296.7000 292.2196 288.3032 286.7105 283.4853 280.3511
mean + sd 463.0900 459.3267 453.5175 447.2001 444.0147 439.2485 434.1220
[,141] [,142] [,143] [,144] [,145] [,146] [,147]
mean - sd 125.3025 124.6049 122.3018 120.9717 119.6821 119.2714 117.4066
mean 276.9047 274.8581 271.2237 269.0067 266.5739 263.3924 260.4180
mean + sd 428.5070 425.1113 420.1455 417.0418 413.4656 407.5134 403.4294
[,148] [,149] [,150] [,151] [,152] [,153] [,154]
mean - sd 116.1092 115.763 113.7058 111.8390 112.2662 111.0700 109.8724
mean 258.1373 255.791 253.8093 249.5182 248.2199 245.3162 241.8370
mean + sd 400.1654 395.819 393.9127 387.1973 384.1735 379.5624 373.8016
[,155] [,156] [,157] [,158] [,159] [,160] [,161]
mean - sd 109.4847 108.0348 106.3207 103.6006 102.5350 103.1374 101.2827
mean 240.8851 238.1019 235.3928 232.0592 230.1664 227.5049 224.4877
mean + sd 372.2856 368.1690 364.4648 360.5178 357.7977 351.8724 347.6928
[,162] [,163] [,164] [,165] [,166] [,167] [,168]
mean - sd 100.2449 99.25656 97.61239 96.23855 95.26908 94.01085 92.50318
mean 221.6313 219.46467 215.94411 213.16344 210.14694 208.62042 205.86292
mean + sd 343.0178 339.67277 334.27583 330.08834 325.02481 323.22998 319.22265
[,169] [,170] [,171] [,172] [,173] [,174] [,175]
mean - sd 92.30722 90.60566 88.71826 88.53754 86.75587 85.71093 83.83838
mean 203.66306 200.38500 198.28903 195.34281 192.30317 189.33922 186.51083
mean + sd 315.01889 310.16434 307.85980 302.14807 297.85047 292.96751 289.18329
[,176] [,177] [,178] [,179] [,180] [,181]
mean - sd 82.42095 80.70487 79.80546 78.42967 77.95554 76.75885
mean 183.83564 180.68786 178.78053 175.72864 173.40081 170.52147
mean + sd 285.25032 280.67086 277.75559 273.02761 268.84607 264.28409
hyperSpec object
3 spectra
1 data columns
181 data points / spectrum
wavelength: lambda/nm [numeric] 405.0 405.5 ... 495
data: (3 rows x 1 columns)
1. spc: I[fl]/"a.u." [matrix181] 49.95778 113.90939 ... 264.2841
hyperSpec documentation built on May 2, 2019, 5:45 p.m.
R Package Documentation
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Description Usage Arguments Value Author(s) See Also Examples
Description
These functions are provided for convenience.
Usage
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | ## S4 method for signature 'numeric'
mean_sd(x, na.rm = TRUE, ...)
## S4 method for signature 'matrix'
mean_sd(x, na.rm = TRUE, ...)
## S4 method for signature 'hyperSpec'
mean_sd(x, na.rm = TRUE, ...)
## S4 method for signature 'numeric'
mean_pm_sd(x, na.rm = TRUE, ...)
## S4 method for signature 'matrix'
mean_pm_sd(x, na.rm = TRUE, ...)
## S4 method for signature 'hyperSpec'
mean_pm_sd(x, na.rm = TRUE, ...)
## S4 method for signature 'hyperSpec'
mean(x, na.rm = TRUE, ...)
## S4 method for signature 'hyperSpec'
quantile(x, probs = seq(0, 1, 0.5), na.rm = TRUE,
names = "num", ...)
|
Arguments
x |
a numeric vector |
na.rm |
handed to |
... |
ignored (needed to make function generic) |
probs |
the quantiles, see |
names |
|
Value
mean_sd returns a vector with two values (mean and standard
deviation) of x.
mean_sd (matrix) returns a matrix with the mean spectrum in the first row and the standard deviation in the 2nd.
mean_sd returns a hyperSpec object with the mean spectrum in the first row and the standard deviation in the 2nd.
mean_pm_sd returns a vector with 3 values: mean - 1 sd, mean, mean + 1 sd
mean_pm_sd (matrix) returns a matrix containing mean - sd, mean, and mean + sd
rows.
For hyperSpec objects, mean_pm_sd returns a hyperSpec object containing mean - sd,
mean, and mean + sd spectra.
For hyperSpec object, mean returns a hyperSpec object containing the mean
spectrum.
For hyperSpec object, quantile returns a hyperSpec object containing the
respective quantile spectra.
Author(s)
C. Beleites
See Also
Examples
1 2 3 4 5 6 7 8 |
Example output
Loading required package: lattice
Loading required package: grid
Loading required package: ggplot2
Package hyperSpec, version 0.98-20161118
To get started, try
vignette ("introduction", package = "hyperSpec")
package?hyperSpec
vignette (package = "hyperSpec")
If you use this package please cite it appropriately.
citation("hyperSpec")
will give you the correct reference.
The project homepage is http://hyperspec.r-forge.r-project.org
hyperSpec object
2 spectra
1 data columns
11 data points / spectrum
wavelength: lambda/nm [numeric] 405.0 405.5 ... 410
data: (2 rows x 1 columns)
1. spc: I[fl]/"a.u." [matrix11] 113.90939 63.95161 ... 88.86944
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
mean 113.90939 120.08039 123.88961 128.63661 132.78711 138.26267 142.52667
sd 63.95161 66.68462 68.53711 71.32635 73.27403 76.26193 79.05704
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
mean 146.35206 151.43228 156.09817 161.82439 165.86478 171.5021 176.3894
sd 81.11082 83.44635 86.21839 88.86944 90.86983 93.5278 97.0369
[,15] [,16] [,17] [,18] [,19] [,20] [,21] [,22]
mean 180.51522 185.6836 190.1309 195.8358 200.4855 204.6093 210.0138 214.64
sd 99.25456 102.7686 104.5448 107.9088 110.2483 111.9924 115.4464 118.26
[,23] [,24] [,25] [,26] [,27] [,28] [,29] [,30]
mean 219.1380 224.5761 227.9237 232.8236 237.7171 241.7527 246.4742 250.5289
sd 120.7447 123.9144 126.1828 128.7551 129.8156 132.8904 135.4853 137.1431
[,31] [,32] [,33] [,34] [,35] [,36] [,37] [,38]
mean 254.6781 258.4790 264.0061 267.9860 273.0221 277.4778 281.3341 285.0475
sd 139.3884 141.3262 144.7961 146.7983 149.8890 152.0896 154.3166 156.1366
[,39] [,40] [,41] [,42] [,43] [,44] [,45] [,46]
mean 290.1924 294.2909 298.3123 302.2134 307.5095 312.6365 316.1736 319.8145
sd 159.9184 162.8058 164.8594 165.1881 168.6816 172.6384 173.9014 175.6463
[,47] [,48] [,49] [,50] [,51] [,52] [,53] [,54]
mean 325.3752 328.9191 332.6454 336.7873 340.4211 344.5639 349.2603 351.5914
sd 178.6666 181.0399 183.3152 185.6277 186.6223 189.7741 192.6296 194.1671
[,55] [,56] [,57] [,58] [,59] [,60] [,61] [,62]
mean 354.2620 358.1013 361.8068 363.6526 365.7068 366.8592 369.8816 372.5533
sd 195.5245 196.7954 198.6743 200.5592 200.9523 201.5470 203.8599 204.7726
[,63] [,64] [,65] [,66] [,67] [,68] [,69] [,70]
mean 374.8713 375.8997 378.4399 378.6621 380.7669 382.7149 382.8039 383.6267
sd 206.1331 207.0960 208.1450 208.7843 210.1876 210.3305 210.1147 211.5687
[,71] [,72] [,73] [,74] [,75] [,76] [,77] [,78]
mean 383.4117 384.9124 384.9061 386.2123 386.0671 386.8118 387.1116 387.9868
sd 210.9692 211.1969 212.3513 210.9188 210.6814 211.5056 213.4941 212.2282
[,79] [,80] [,81] [,82] [,83] [,84] [,85] [,86]
mean 388.2645 386.9496 387.7631 387.6842 388.9684 388.8592 387.6974 387.5131
sd 213.8395 213.8715 212.7600 212.7473 214.0275 214.1388 213.7061 213.5430
[,87] [,88] [,89] [,90] [,91] [,92] [,93] [,94]
mean 387.8354 387.7904 388.0669 388.3706 388.3181 388.0719 386.9387 387.4204
sd 213.4142 212.5135 213.5708 211.6471 212.2151 212.5157 211.6122 212.4420
[,95] [,96] [,97] [,98] [,99] [,100] [,101] [,102]
mean 387.2329 385.1973 385.5947 385.0308 384.9724 385.6444 383.5018 382.0557
sd 213.0798 212.6830 211.5552 211.7677 211.6549 211.7323 208.8900 209.5972
[,103] [,104] [,105] [,106] [,107] [,108] [,109] [,110]
mean 380.9131 379.6323 379.4236 376.7526 376.1533 373.7147 371.8777 369.0225
sd 209.3029 208.5275 207.9218 207.2801 206.3606 205.1782 204.3870 202.7046
[,111] [,112] [,113] [,114] [,115] [,116] [,117] [,118]
mean 367.3478 364.0053 363.2114 361.1244 358.5899 354.8971 352.0969 349.0689
sd 202.7634 199.7319 199.7003 197.7912 196.5260 195.9355 193.7476 190.8617
[,119] [,120] [,121] [,122] [,123] [,124] [,125] [,126]
mean 347.7439 344.6271 340.4968 338.4603 335.9258 332.6344 329.3642 325.6729
sd 190.1415 188.8953 186.8400 185.6940 185.2942 183.5705 181.6199 178.8888
[,127] [,128] [,129] [,130] [,131] [,132] [,133] [,134]
mean 322.0702 319.5687 314.7917 312.4208 310.4492 305.3859 302.4756 299.4622
sd 176.0399 176.1274 173.3872 172.4460 170.4795 166.8526 166.5719 163.6277
[,135] [,136] [,137] [,138] [,139] [,140] [,141] [,142]
mean 296.7000 292.2196 288.3032 286.7105 283.4853 280.3511 276.9047 274.8581
sd 162.6267 161.2979 158.8969 157.3042 155.7632 153.7710 151.6023 150.2532
[,143] [,144] [,145] [,146] [,147] [,148] [,149] [,150]
mean 271.2237 269.0067 266.5739 263.3924 260.4180 258.1373 255.791 253.8093
sd 148.9218 148.0351 146.8918 144.1210 143.0114 142.0281 140.028 140.1034
[,151] [,152] [,153] [,154] [,155] [,156] [,157] [,158]
mean 249.5182 248.2199 245.3162 241.8370 240.8851 238.1019 235.3928 232.0592
sd 137.6791 135.9537 134.2462 131.9646 131.4004 130.0671 129.0721 128.4586
[,159] [,160] [,161] [,162] [,163] [,164] [,165] [,166]
mean 230.1664 227.5049 224.4877 221.6313 219.4647 215.9441 213.1634 210.1469
sd 127.6313 124.3675 123.2050 121.3864 120.2081 118.3317 116.9249 114.8779
[,167] [,168] [,169] [,170] [,171] [,172] [,173] [,174]
mean 208.6204 205.8629 203.6631 200.3850 198.2890 195.3428 192.3032 189.3392
sd 114.6096 113.3597 111.3558 109.7793 109.5708 106.8053 105.5473 103.6283
[,175] [,176] [,177] [,178] [,179] [,180] [,181]
mean 186.5108 183.8356 180.6879 178.78053 175.72864 173.40081 170.52147
sd 102.6725 101.4147 99.9830 98.97507 97.29897 95.44527 93.76262
hyperSpec object
2 spectra
1 data columns
181 data points / spectrum
wavelength: lambda/nm [numeric] 405.0 405.5 ... 495
data: (2 rows x 1 columns)
1. spc: I[fl]/"a.u." [matrix181] 113.90939 63.95161 ... 93.76262
mean.minus.sd mean mean.plus.sd
0.08145857 0.17500000 0.26854143
[,1] [,2] [,3] [,4] [,5] [,6] [,7]
mean - sd 49.95778 53.39577 55.3525 57.31027 59.51308 62.00074 63.46963
mean 113.90939 120.08039 123.8896 128.63661 132.78711 138.26267 142.52667
mean + sd 177.86100 186.76501 192.4267 199.96296 206.06114 214.52459 221.58371
[,8] [,9] [,10] [,11] [,12] [,13] [,14]
mean - sd 65.24124 67.98593 69.87977 72.95495 74.99495 77.97425 79.35249
mean 146.35206 151.43228 156.09817 161.82439 165.86478 171.50206 176.38939
mean + sd 227.46287 234.87862 242.31656 250.69383 256.73461 265.02986 273.42629
[,15] [,16] [,17] [,18] [,19] [,20] [,21]
mean - sd 81.26066 82.9150 85.58614 87.92704 90.23721 92.61698 94.56743
mean 180.51522 185.6836 190.13094 195.83583 200.48550 204.60933 210.01383
mean + sd 279.76979 288.4521 294.67575 303.74462 310.73379 316.60168 325.46024
[,22] [,23] [,24] [,25] [,26] [,27] [,28]
mean - sd 96.37996 98.39334 100.6617 101.7409 104.0685 107.9015 108.8622
mean 214.64000 219.13800 224.5761 227.9237 232.8236 237.7171 241.7527
mean + sd 332.90004 339.88266 348.4904 354.1065 361.5787 367.5328 374.6431
[,29] [,30] [,31] [,32] [,33] [,34] [,35]
mean - sd 110.9890 113.3858 115.2896 117.1528 119.2100 121.1877 123.1330
mean 246.4742 250.5289 254.6781 258.4790 264.0061 267.9860 273.0221
mean + sd 381.9595 387.6720 394.0665 399.8052 408.8021 414.7843 422.9111
[,36] [,37] [,38] [,39] [,40] [,41] [,42]
mean - sd 125.3882 127.0175 128.9109 130.2740 131.4851 133.4529 137.0253
mean 277.4778 281.3341 285.0475 290.1924 294.2909 298.3123 302.2134
mean + sd 429.5674 435.6506 441.1841 450.1108 457.0967 463.1717 467.4016
[,43] [,44] [,45] [,46] [,47] [,48] [,49]
mean - sd 138.8279 139.9981 142.2722 144.1681 146.7086 147.8792 149.3303
mean 307.5095 312.6365 316.1736 319.8145 325.3752 328.9191 332.6454
mean + sd 476.1911 485.2749 490.0750 495.4608 504.0418 509.9590 515.9606
[,50] [,51] [,52] [,53] [,54] [,55] [,56]
mean - sd 151.1596 153.7988 154.7898 156.6307 157.4243 158.7375 161.3059
mean 336.7873 340.4211 344.5639 349.2603 351.5914 354.2620 358.1013
mean + sd 522.4151 527.0434 534.3380 541.8899 545.7585 549.7865 554.8966
[,57] [,58] [,59] [,60] [,61] [,62] [,63]
mean - sd 163.1325 163.0934 164.7544 165.3122 166.0218 167.7807 168.7382
mean 361.8068 363.6526 365.7068 366.8592 369.8816 372.5533 374.8713
mean + sd 560.4812 564.2118 566.6591 568.4062 573.7415 577.3258 581.0044
[,64] [,65] [,66] [,67] [,68] [,69] [,70]
mean - sd 168.8037 170.2950 169.8777 170.5793 172.3844 172.6892 172.0580
mean 375.8997 378.4399 378.6621 380.7669 382.7149 382.8039 383.6267
mean + sd 582.9957 586.5849 587.4464 590.9546 593.0454 592.9186 595.1954
[,71] [,72] [,73] [,74] [,75] [,76] [,77]
mean - sd 172.4425 173.7155 172.5548 175.2936 175.3857 175.3063 173.6175
mean 383.4117 384.9124 384.9061 386.2123 386.0671 386.8118 387.1116
mean + sd 594.3809 596.1093 597.2574 597.1311 596.7484 598.3174 600.6056
[,78] [,79] [,80] [,81] [,82] [,83] [,84]
mean - sd 175.7587 174.4250 173.0780 175.0031 174.9369 174.9409 174.7203
mean 387.9868 388.2645 386.9496 387.7631 387.6842 388.9684 388.8592
mean + sd 600.2150 602.1040 600.8211 600.5230 600.4315 602.9959 602.9980
[,85] [,86] [,87] [,88] [,89] [,90] [,91]
mean - sd 173.9914 173.9701 174.4212 175.2769 174.4961 176.7235 176.1030
mean 387.6974 387.5131 387.8354 387.7904 388.0669 388.3706 388.3181
mean + sd 601.4035 601.0562 601.2497 600.3040 601.6376 600.0177 600.5332
[,92] [,93] [,94] [,95] [,96] [,97] [,98]
mean - sd 175.5562 175.3266 174.9784 174.1531 172.5142 174.0396 173.2631
mean 388.0719 386.9387 387.4204 387.2329 385.1973 385.5947 385.0308
mean + sd 600.5876 598.5509 599.8624 600.3128 597.8803 597.1499 596.7985
[,99] [,100] [,101] [,102] [,103] [,104] [,105]
mean - sd 173.3176 173.9120 174.6118 172.4585 171.6102 171.1048 171.5018
mean 384.9724 385.6444 383.5018 382.0557 380.9131 379.6323 379.4236
mean + sd 596.6273 597.3767 592.3918 591.6530 590.2161 588.1597 587.3454
[,106] [,107] [,108] [,109] [,110] [,111] [,112]
mean - sd 169.4725 169.7926 168.5365 167.4907 166.3179 164.5844 164.2734
mean 376.7526 376.1533 373.7147 371.8777 369.0225 367.3478 364.0053
mean + sd 584.0326 582.5139 578.8929 576.2647 571.7271 570.1112 563.7373
[,113] [,114] [,115] [,116] [,117] [,118] [,119]
mean - sd 163.5111 163.3332 162.0640 158.9616 158.3493 158.2073 157.6023
mean 363.2114 361.1244 358.5899 354.8971 352.0969 349.0689 347.7439
mean + sd 562.9118 558.9157 555.1159 550.8326 545.8446 539.9306 537.8854
[,120] [,121] [,122] [,123] [,124] [,125] [,126]
mean - sd 155.7317 153.6568 152.7663 150.6317 149.0639 147.7443 146.7840
mean 344.6271 340.4968 338.4603 335.9258 332.6344 329.3642 325.6729
mean + sd 533.5224 527.3368 524.1543 521.2200 516.2048 510.9840 504.5617
[,127] [,128] [,129] [,130] [,131] [,132] [,133]
mean - sd 146.0302 143.4413 141.4045 139.9748 139.9697 138.5334 135.9037
mean 322.0702 319.5687 314.7917 312.4208 310.4492 305.3859 302.4756
mean + sd 498.1101 495.6961 488.1790 484.8668 480.9288 472.2385 469.0476
[,134] [,135] [,136] [,137] [,138] [,139] [,140]
mean - sd 135.8345 134.0733 130.9217 129.4063 129.4063 127.7221 126.5801
mean 299.4622 296.7000 292.2196 288.3032 286.7105 283.4853 280.3511
mean + sd 463.0900 459.3267 453.5175 447.2001 444.0147 439.2485 434.1220
[,141] [,142] [,143] [,144] [,145] [,146] [,147]
mean - sd 125.3025 124.6049 122.3018 120.9717 119.6821 119.2714 117.4066
mean 276.9047 274.8581 271.2237 269.0067 266.5739 263.3924 260.4180
mean + sd 428.5070 425.1113 420.1455 417.0418 413.4656 407.5134 403.4294
[,148] [,149] [,150] [,151] [,152] [,153] [,154]
mean - sd 116.1092 115.763 113.7058 111.8390 112.2662 111.0700 109.8724
mean 258.1373 255.791 253.8093 249.5182 248.2199 245.3162 241.8370
mean + sd 400.1654 395.819 393.9127 387.1973 384.1735 379.5624 373.8016
[,155] [,156] [,157] [,158] [,159] [,160] [,161]
mean - sd 109.4847 108.0348 106.3207 103.6006 102.5350 103.1374 101.2827
mean 240.8851 238.1019 235.3928 232.0592 230.1664 227.5049 224.4877
mean + sd 372.2856 368.1690 364.4648 360.5178 357.7977 351.8724 347.6928
[,162] [,163] [,164] [,165] [,166] [,167] [,168]
mean - sd 100.2449 99.25656 97.61239 96.23855 95.26908 94.01085 92.50318
mean 221.6313 219.46467 215.94411 213.16344 210.14694 208.62042 205.86292
mean + sd 343.0178 339.67277 334.27583 330.08834 325.02481 323.22998 319.22265
[,169] [,170] [,171] [,172] [,173] [,174] [,175]
mean - sd 92.30722 90.60566 88.71826 88.53754 86.75587 85.71093 83.83838
mean 203.66306 200.38500 198.28903 195.34281 192.30317 189.33922 186.51083
mean + sd 315.01889 310.16434 307.85980 302.14807 297.85047 292.96751 289.18329
[,176] [,177] [,178] [,179] [,180] [,181]
mean - sd 82.42095 80.70487 79.80546 78.42967 77.95554 76.75885
mean 183.83564 180.68786 178.78053 175.72864 173.40081 170.52147
mean + sd 285.25032 280.67086 277.75559 273.02761 268.84607 264.28409
hyperSpec object
3 spectra
1 data columns
181 data points / spectrum
wavelength: lambda/nm [numeric] 405.0 405.5 ... 495
data: (3 rows x 1 columns)
1. spc: I[fl]/"a.u." [matrix181] 49.95778 113.90939 ... 264.2841
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