VBTree-package: Vector Binary Tree to Make Your Data Management More...
In VBTree: Vector Binary Tree to Make Your Data Management More Efficient
Description
Details
Author(s)
References
See Also
Examples
Description
Provides a new data structure, vector binary tree, to make
your data visiting and management more efficient. if your data has
very structurized column names with specific connecting pattern, it can
read, split, and factorize these names, then build the mapping from all
string objects to an array or tensor, through vector binary tree, by
which the batched data processing can be implemented easily. The methods
of array and tensor are also applicable.
Details
This package provide an efficient approach to manage data by structurizing the column names. A column name is generally seen as a character object, while if
it has a very organized pattern, such as "*-*-*-*" for example (each * mark presents a different condition), it must has a certain mapping relationship to a
specific tensor. This package uses two data structure: double list and vector binary tree, to implement the conversion between the character vector and tensor.
It affords various inquiry methods, which was mainly drived by vector binary tree, to extract the highly customizable subset from original data.
Author(s)
ZHANG Chen
Maintainer: ZHANG Chen <447974102@qq.com>
References
Sedgewick, Robert & Wayne, Kevin (2011). Algorithms, 4th Edition.. Addison-Wesley
Prakash, P. K. S. & Rao, Achyutuni Sri Krishna (2016). R Data Structures and Algorithms. Packt Publishing
See Also
Examples
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#View the data to be visited:
summary(datatest)
colnames(datatest)
#Structurize colnames of data into vector binary tree:
dl <- chrvec2dl(colnames(datatest))
vbt <- dl2vbt(dl)
vbt
#Setting subset in different forms, for example the pattern
#"Strain-(900~1100)-(0.01, 1)-0.6" is desired:
subunregdl <- list(c(1), c(1:5), c(2,4), c(1)) # undifined double list
subregdl <- advbtinq(vbt, subunregdl) # regularized double list
subvbt <- dl2vbt(subregdl) # sub vector binary tree
subts <- vbt2ts(subvbt) # tensor
subarr <- vbt2arr(subvbt) # array
subchrvec <- as.vector(subarr) # character vector
#Visit the data through different methods:
datavisit(datatest, c(1,2,2,1)) # by integer vector
datavisit(datatest, subunregdl) # by handmade double list
datavisit(datatest, subregdl) # by defined double list
datavisit(datatest, subvbt) # by vector binary tree
datavisit(datatest, subts) # by tensor
datavisit(datatest, subarr) # by array
datavisit(datatest, subchrvec) # by character vector
Example output
Strain-900-0.001-0.6 Stress-900-0.001-0.6 Strain-900-0.01-0.6
Min. :0.000090 Min. : 2.81 Min. :0.000300
1st Qu.:0.003390 1st Qu.: 8.95 1st Qu.:0.002682
Median :0.005220 Median :21.07 Median :0.005180
Mean :0.005010 Mean :30.08 Mean :0.004912
3rd Qu.:0.007045 3rd Qu.:49.20 3rd Qu.:0.007327
Max. :0.008960 Max. :84.24 Max. :0.009040
Stress-900-0.01-0.6 Strain-900-0.1-0.6 Stress-900-0.1-0.6 Strain-900-1-0.6
Min. : 3.37 Min. :0.000500 Min. : 2.670 Min. :0.000260
1st Qu.:10.71 1st Qu.:0.002832 1st Qu.: 7.595 1st Qu.:0.002498
Median :27.55 Median :0.005320 Median :17.785 Median :0.004705
Mean :35.88 Mean :0.004924 Mean :26.076 Mean :0.004305
3rd Qu.:57.76 3rd Qu.:0.006882 3rd Qu.:39.315 3rd Qu.:0.006157
Max. :95.33 Max. :0.008330 Max. :81.400 Max. :0.007600
Stress-900-1-0.6 Strain-950-0.001-0.6 Stress-950-0.001-0.6 Strain-950-0.01-0.6
Min. : 2.160 Min. :0.000560 Min. : 2.387 Min. :0.000270
1st Qu.: 7.157 1st Qu.:0.002645 1st Qu.: 6.160 1st Qu.:0.002537
Median :17.395 Median :0.005470 Median :17.643 Median :0.004865
Mean :26.459 Mean :0.005073 Mean :24.389 Mean :0.004661
3rd Qu.:42.470 3rd Qu.:0.007180 3rd Qu.:39.305 3rd Qu.:0.006768
Max. :78.060 Max. :0.009340 Max. :68.936 Max. :0.008640
Stress-950-0.01-0.6 Strain-950-0.1-0.6 Stress-950-0.1-0.6 Strain-950-1-0.6
Min. : 2.39 Min. :0.000000 Min. : 0.00 Min. :0.000100
1st Qu.: 5.60 1st Qu.:0.002828 1st Qu.: 5.11 1st Qu.:0.002480
Median :16.48 Median :0.005275 Median :10.53 Median :0.004510
Mean :25.44 Mean :0.005228 Mean :15.53 Mean :0.004261
3rd Qu.:41.03 3rd Qu.:0.007955 3rd Qu.:23.11 3rd Qu.:0.006168
Max. :78.17 Max. :0.009510 Max. :48.95 Max. :0.007480
Stress-950-1-0.6 Strain-1000-0.001-0.6 Stress-1000-0.001-0.6
Min. : 2.25 Min. :0.000260 Min. : 2.950
1st Qu.: 7.28 1st Qu.:0.003270 1st Qu.: 4.369
Median :17.52 Median :0.005880 Median : 5.024
Mean :24.50 Mean :0.006108 Mean : 5.871
3rd Qu.:38.03 3rd Qu.:0.009080 3rd Qu.: 7.665
Max. :71.07 Max. :0.012300 Max. :10.635
Strain-1000-0.01-0.6 Stress-1000-0.01-0.6 Strain-1000-0.1-0.6
Min. :0.000520 Min. :3.640 Min. :0.000190
1st Qu.:0.003182 1st Qu.:4.375 1st Qu.:0.002873
Median :0.006360 Median :5.570 Median :0.005715
Mean :0.006232 Mean :5.696 Mean :0.005780
3rd Qu.:0.009217 3rd Qu.:6.897 3rd Qu.:0.008990
Max. :0.011480 Max. :8.850 Max. :0.011160
Stress-1000-0.1-0.6 Strain-1000-1-0.6 Stress-1000-1-0.6 Strain-1050-0.001-0.6
Min. :3.090 Min. :0.000200 Min. :2.810 Min. :0.000190
1st Qu.:4.062 1st Qu.:0.003095 1st Qu.:3.850 1st Qu.:0.002867
Median :5.580 Median :0.006165 Median :5.085 Median :0.005400
Mean :5.905 Mean :0.005970 Mean :5.322 Mean :0.005430
3rd Qu.:7.598 3rd Qu.:0.008648 3rd Qu.:6.355 3rd Qu.:0.007912
Max. :9.820 Max. :0.011500 Max. :8.300 Max. :0.010320
Stress-1050-0.001-0.6 Strain-1050-0.01-0.6 Stress-1050-0.01-0.6
Min. : 3.091 Min. :0.000030 Min. : 2.669
1st Qu.: 7.034 1st Qu.:0.002325 1st Qu.: 5.428
Median :15.970 Median :0.004960 Median :11.305
Mean :19.450 Mean :0.004983 Mean :15.829
3rd Qu.:30.786 3rd Qu.:0.007415 3rd Qu.:24.166
Max. :44.877 Max. :0.009780 Max. :43.249
Strain-1050-0.1-0.6 Stress-1050-0.1-0.6 Strain-1050-1-0.6 Stress-1050-1-0.6
Min. :0.000710 Min. : 3.090 Min. :0.000080 Min. : 2.95
1st Qu.:0.003373 1st Qu.: 4.793 1st Qu.:0.002498 1st Qu.: 5.39
Median :0.005855 Median : 7.670 Median :0.004885 Median : 9.91
Mean :0.005898 Mean :11.775 Mean :0.004587 Mean :14.32
3rd Qu.:0.008735 3rd Qu.:17.562 3rd Qu.:0.006568 3rd Qu.:21.23
Max. :0.010450 Max. :33.930 Max. :0.008540 Max. :41.80
Strain-1100-0.001-0.6 Stress-1100-0.001-0.6 Strain-1100-0.01-0.6
Min. :0.000500 Min. : 3.089 Min. :0.000000
1st Qu.:0.003350 1st Qu.: 4.966 1st Qu.:0.002770
Median :0.005950 Median : 9.199 Median :0.005635
Mean :0.005888 Mean :12.320 Mean :0.005375
3rd Qu.:0.008450 3rd Qu.:18.922 3rd Qu.:0.007853
Max. :0.011200 Max. :30.572 Max. :0.010380
Stress-1100-0.01-0.6 Strain-1100-0.1-0.6 Stress-1100-0.1-0.6
Min. : 0.000 Min. :0.001190 Min. : 2.810
1st Qu.: 4.934 1st Qu.:0.004343 1st Qu.: 4.995
Median : 9.203 Median :0.007315 Median : 8.555
Mean :12.631 Mean :0.006870 Mean :12.035
3rd Qu.:18.730 3rd Qu.:0.009577 3rd Qu.:17.648
Max. :36.425 Max. :0.011720 Max. :34.280
Strain-1100-1-0.6 Stress-1100-1-0.6 Strain-1150-0.001-0.6
Min. :0.000470 Min. : 3.370 Min. :0.000000
1st Qu.:0.002162 1st Qu.: 4.655 1st Qu.:0.002750
Median :0.003980 Median : 6.220 Median :0.005750
Mean :0.004217 Mean : 7.325 Mean :0.005538
3rd Qu.:0.006315 3rd Qu.: 9.715 3rd Qu.:0.008125
Max. :0.008470 Max. :15.550 Max. :0.011000
Stress-1150-0.001-0.6 Strain-1150-0.01-0.6 Stress-1150-0.01-0.6
Min. : 0.000 Min. :0.000100 Min. : 3.091
1st Qu.: 4.199 1st Qu.:0.003550 1st Qu.: 7.098
Median : 7.179 Median :0.005300 Median :11.998
Mean : 8.262 Mean :0.005522 Mean :15.039
3rd Qu.:10.630 3rd Qu.:0.007900 3rd Qu.:22.065
Max. :21.447 Max. :0.010100 Max. :35.747
Strain-1150-0.1-0.6 Stress-1150-0.1-0.6 Strain-1150-1-0.6 Stress-1150-1-0.6
Min. :0.000610 Min. : 2.668 Min. :0.000310 Min. : 3.090
1st Qu.:0.003780 1st Qu.: 5.801 1st Qu.:0.001830 1st Qu.: 3.790
Median :0.006260 Median :10.658 Median :0.004165 Median : 5.870
Mean :0.006118 Mean :14.597 Mean :0.004212 Mean : 6.908
3rd Qu.:0.008650 3rd Qu.:21.486 3rd Qu.:0.006085 3rd Qu.: 8.675
Max. :0.010890 Max. :41.103 Max. :0.008550 Max. :14.860
Strain-1200-0.001-0.6 Stress-1200-0.001-0.6 Strain-1200-0.01-0.6
Min. :0.000540 Min. : 3.089 Min. :0.000130
1st Qu.:0.003565 1st Qu.: 6.572 1st Qu.:0.002875
Median :0.006170 Median :13.585 Median :0.005715
Mean :0.006115 Mean :13.107 Mean :0.005550
3rd Qu.:0.008377 3rd Qu.:19.273 3rd Qu.:0.008215
Max. :0.011280 Max. :21.439 Max. :0.010920
Stress-1200-0.01-0.6 Strain-1200-0.1-0.6 Stress-1200-0.1-0.6
Min. : 3.231 Min. :0.000760 Min. : 3.228
1st Qu.: 6.369 1st Qu.:0.003565 1st Qu.: 6.397
Median :13.384 Median :0.006385 Median :12.327
Mean :15.523 Mean :0.006258 Mean :16.668
3rd Qu.:24.729 3rd Qu.:0.008882 3rd Qu.:25.781
Max. :31.553 Max. :0.011200 Max. :40.532
Strain-1200-1-0.6 Stress-1200-1-0.6
Min. :0.000210 Min. : 2.669
1st Qu.:0.002273 1st Qu.: 4.693
Median :0.004290 Median : 7.543
Mean :0.004131 Mean : 9.101
3rd Qu.:0.005897 3rd Qu.:12.475
Max. :0.007830 Max. :21.546
[1] "Strain-900-0.001-0.6" "Stress-900-0.001-0.6" "Strain-900-0.01-0.6"
[4] "Stress-900-0.01-0.6" "Strain-900-0.1-0.6" "Stress-900-0.1-0.6"
[7] "Strain-900-1-0.6" "Stress-900-1-0.6" "Strain-950-0.001-0.6"
[10] "Stress-950-0.001-0.6" "Strain-950-0.01-0.6" "Stress-950-0.01-0.6"
[13] "Strain-950-0.1-0.6" "Stress-950-0.1-0.6" "Strain-950-1-0.6"
[16] "Stress-950-1-0.6" "Strain-1000-0.001-0.6" "Stress-1000-0.001-0.6"
[19] "Strain-1000-0.01-0.6" "Stress-1000-0.01-0.6" "Strain-1000-0.1-0.6"
[22] "Stress-1000-0.1-0.6" "Strain-1000-1-0.6" "Stress-1000-1-0.6"
[25] "Strain-1050-0.001-0.6" "Stress-1050-0.001-0.6" "Strain-1050-0.01-0.6"
[28] "Stress-1050-0.01-0.6" "Strain-1050-0.1-0.6" "Stress-1050-0.1-0.6"
[31] "Strain-1050-1-0.6" "Stress-1050-1-0.6" "Strain-1100-0.001-0.6"
[34] "Stress-1100-0.001-0.6" "Strain-1100-0.01-0.6" "Stress-1100-0.01-0.6"
[37] "Strain-1100-0.1-0.6" "Stress-1100-0.1-0.6" "Strain-1100-1-0.6"
[40] "Stress-1100-1-0.6" "Strain-1150-0.001-0.6" "Stress-1150-0.001-0.6"
[43] "Strain-1150-0.01-0.6" "Stress-1150-0.01-0.6" "Strain-1150-0.1-0.6"
[46] "Stress-1150-0.1-0.6" "Strain-1150-1-0.6" "Stress-1150-1-0.6"
[49] "Strain-1200-0.001-0.6" "Stress-1200-0.001-0.6" "Strain-1200-0.01-0.6"
[52] "Stress-1200-0.01-0.6" "Strain-1200-0.1-0.6" "Stress-1200-0.1-0.6"
[55] "Strain-1200-1-0.6" "Stress-1200-1-0.6"
$tree
$tree[[1]]
[1] "Strain" "Stress"
$tree[[2]]
$tree[[2]][[1]]
[1] "900" "950" "1000" "1050" "1100" "1150" "1200"
$tree[[2]][[2]]
$tree[[2]][[2]][[1]]
[1] "0.001" "0.01" "0.1" "1"
$tree[[2]][[2]][[2]]
$tree[[2]][[2]][[2]][[1]]
[1] "0.6"
$tree[[2]][[2]][[2]][[2]]
list()
$dims
[1] 2 7 4 1
attr(,"class")
[1] "Vector.Binary.Tree"
$itemid
[1] 6
$colnames
[1] "Strain-950-0.01-0.6"
$coordinate
coo coo coo coo
1 2 2 1
$coldata
[1] 0.00027 0.00066 0.00073 0.00101 0.00123 0.00128 0.00140 0.00162 0.00173
[10] 0.00195 0.00217 0.00227 0.00250 0.00265 0.00287 0.00308 0.00323 0.00333
[19] 0.00359 0.00386 0.00417 0.00427 0.00446 0.00466 0.00480 0.00493 0.00506
[28] 0.00513 0.00532 0.00550 0.00569 0.00576 0.00599 0.00610 0.00627 0.00642
[37] 0.00670 0.00679 0.00706 0.00721 0.00737 0.00752 0.00767 0.00765 0.00775
[46] 0.00790 0.00805 0.00832 0.00848 0.00864
attr(,"class")
[1] "Trav.Inq.Data"
itemid colnames coordinate coldata
item 2 "Strain-900-0.01-0.6" Numeric,4 Numeric,50
item 4 "Strain-900-1-0.6" Numeric,4 Numeric,50
item 6 "Strain-950-0.01-0.6" Numeric,4 Numeric,50
item 8 "Strain-950-1-0.6" Numeric,4 Numeric,50
item 10 "Strain-1000-0.01-0.6" Numeric,4 Numeric,50
item 12 "Strain-1000-1-0.6" Numeric,4 Numeric,50
item 14 "Strain-1050-0.01-0.6" Numeric,4 Numeric,50
item 16 "Strain-1050-1-0.6" Numeric,4 Numeric,50
item 18 "Strain-1100-0.01-0.6" Numeric,4 Numeric,50
item 20 "Strain-1100-1-0.6" Numeric,4 Numeric,50
attr(,"class")
[1] "Trav.Inq.Data"
itemid colnames coordinate coldata
item 2 "Strain-900-0.01-0.6" Numeric,4 Numeric,50
item 4 "Strain-900-1-0.6" Numeric,4 Numeric,50
item 6 "Strain-950-0.01-0.6" Numeric,4 Numeric,50
item 8 "Strain-950-1-0.6" Numeric,4 Numeric,50
item 10 "Strain-1000-0.01-0.6" Numeric,4 Numeric,50
item 12 "Strain-1000-1-0.6" Numeric,4 Numeric,50
item 14 "Strain-1050-0.01-0.6" Numeric,4 Numeric,50
item 16 "Strain-1050-1-0.6" Numeric,4 Numeric,50
item 18 "Strain-1100-0.01-0.6" Numeric,4 Numeric,50
item 20 "Strain-1100-1-0.6" Numeric,4 Numeric,50
attr(,"class")
[1] "Trav.Inq.Data"
itemid colnames coordinate coldata
item 2 "Strain-900-0.01-0.6" Numeric,4 Numeric,50
item 4 "Strain-900-1-0.6" Numeric,4 Numeric,50
item 6 "Strain-950-0.01-0.6" Numeric,4 Numeric,50
item 8 "Strain-950-1-0.6" Numeric,4 Numeric,50
item 10 "Strain-1000-0.01-0.6" Numeric,4 Numeric,50
item 12 "Strain-1000-1-0.6" Numeric,4 Numeric,50
item 14 "Strain-1050-0.01-0.6" Numeric,4 Numeric,50
item 16 "Strain-1050-1-0.6" Numeric,4 Numeric,50
item 18 "Strain-1100-0.01-0.6" Numeric,4 Numeric,50
item 20 "Strain-1100-1-0.6" Numeric,4 Numeric,50
attr(,"class")
[1] "Trav.Inq.Data"
itemid colnames coordinate coldata
item 2 "Strain-900-0.01-0.6" Numeric,4 Numeric,50
item 4 "Strain-900-1-0.6" Numeric,4 Numeric,50
item 6 "Strain-950-0.01-0.6" Numeric,4 Numeric,50
item 8 "Strain-950-1-0.6" Numeric,4 Numeric,50
item 10 "Strain-1000-0.01-0.6" Numeric,4 Numeric,50
item 12 "Strain-1000-1-0.6" Numeric,4 Numeric,50
item 14 "Strain-1050-0.01-0.6" Numeric,4 Numeric,50
item 16 "Strain-1050-1-0.6" Numeric,4 Numeric,50
item 18 "Strain-1100-0.01-0.6" Numeric,4 Numeric,50
item 20 "Strain-1100-1-0.6" Numeric,4 Numeric,50
attr(,"class")
[1] "Trav.Inq.Data"
itemid colnames coordinate coldata
item 2 "Strain-900-0.01-0.6" Numeric,4 Numeric,50
item 4 "Strain-900-1-0.6" Numeric,4 Numeric,50
item 6 "Strain-950-0.01-0.6" Numeric,4 Numeric,50
item 8 "Strain-950-1-0.6" Numeric,4 Numeric,50
item 10 "Strain-1000-0.01-0.6" Numeric,4 Numeric,50
item 12 "Strain-1000-1-0.6" Numeric,4 Numeric,50
item 14 "Strain-1050-0.01-0.6" Numeric,4 Numeric,50
item 16 "Strain-1050-1-0.6" Numeric,4 Numeric,50
item 18 "Strain-1100-0.01-0.6" Numeric,4 Numeric,50
item 20 "Strain-1100-1-0.6" Numeric,4 Numeric,50
attr(,"class")
[1] "Trav.Inq.Data"
itemid colnames coordinate coldata
item 2 "Strain-900-0.01-0.6" Numeric,4 Numeric,50
item 4 "Strain-900-1-0.6" Numeric,4 Numeric,50
item 6 "Strain-950-0.01-0.6" Numeric,4 Numeric,50
item 8 "Strain-950-1-0.6" Numeric,4 Numeric,50
item 10 "Strain-1000-0.01-0.6" Numeric,4 Numeric,50
item 12 "Strain-1000-1-0.6" Numeric,4 Numeric,50
item 14 "Strain-1050-0.01-0.6" Numeric,4 Numeric,50
item 16 "Strain-1050-1-0.6" Numeric,4 Numeric,50
item 18 "Strain-1100-0.01-0.6" Numeric,4 Numeric,50
item 20 "Strain-1100-1-0.6" Numeric,4 Numeric,50
attr(,"class")
[1] "Trav.Inq.Data"
VBTree documentation built on May 2, 2019, 12:39 p.m.
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Description Details Author(s) References See Also Examples
Description
Provides a new data structure, vector binary tree, to make your data visiting and management more efficient. if your data has very structurized column names with specific connecting pattern, it can read, split, and factorize these names, then build the mapping from all string objects to an array or tensor, through vector binary tree, by which the batched data processing can be implemented easily. The methods of array and tensor are also applicable.
Details
This package provide an efficient approach to manage data by structurizing the column names. A column name is generally seen as a character object, while if it has a very organized pattern, such as "*-*-*-*" for example (each * mark presents a different condition), it must has a certain mapping relationship to a specific tensor. This package uses two data structure: double list and vector binary tree, to implement the conversion between the character vector and tensor. It affords various inquiry methods, which was mainly drived by vector binary tree, to extract the highly customizable subset from original data.
Author(s)
ZHANG Chen
Maintainer: ZHANG Chen <447974102@qq.com>
References
Sedgewick, Robert & Wayne, Kevin (2011). Algorithms, 4th Edition.. Addison-Wesley
Prakash, P. K. S. & Rao, Achyutuni Sri Krishna (2016). R Data Structures and Algorithms. Packt Publishing
See Also
Examples
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 | #View the data to be visited:
summary(datatest)
colnames(datatest)
#Structurize colnames of data into vector binary tree:
dl <- chrvec2dl(colnames(datatest))
vbt <- dl2vbt(dl)
vbt
#Setting subset in different forms, for example the pattern
#"Strain-(900~1100)-(0.01, 1)-0.6" is desired:
subunregdl <- list(c(1), c(1:5), c(2,4), c(1)) # undifined double list
subregdl <- advbtinq(vbt, subunregdl) # regularized double list
subvbt <- dl2vbt(subregdl) # sub vector binary tree
subts <- vbt2ts(subvbt) # tensor
subarr <- vbt2arr(subvbt) # array
subchrvec <- as.vector(subarr) # character vector
#Visit the data through different methods:
datavisit(datatest, c(1,2,2,1)) # by integer vector
datavisit(datatest, subunregdl) # by handmade double list
datavisit(datatest, subregdl) # by defined double list
datavisit(datatest, subvbt) # by vector binary tree
datavisit(datatest, subts) # by tensor
datavisit(datatest, subarr) # by array
datavisit(datatest, subchrvec) # by character vector
|
Example output
Strain-900-0.001-0.6 Stress-900-0.001-0.6 Strain-900-0.01-0.6
Min. :0.000090 Min. : 2.81 Min. :0.000300
1st Qu.:0.003390 1st Qu.: 8.95 1st Qu.:0.002682
Median :0.005220 Median :21.07 Median :0.005180
Mean :0.005010 Mean :30.08 Mean :0.004912
3rd Qu.:0.007045 3rd Qu.:49.20 3rd Qu.:0.007327
Max. :0.008960 Max. :84.24 Max. :0.009040
Stress-900-0.01-0.6 Strain-900-0.1-0.6 Stress-900-0.1-0.6 Strain-900-1-0.6
Min. : 3.37 Min. :0.000500 Min. : 2.670 Min. :0.000260
1st Qu.:10.71 1st Qu.:0.002832 1st Qu.: 7.595 1st Qu.:0.002498
Median :27.55 Median :0.005320 Median :17.785 Median :0.004705
Mean :35.88 Mean :0.004924 Mean :26.076 Mean :0.004305
3rd Qu.:57.76 3rd Qu.:0.006882 3rd Qu.:39.315 3rd Qu.:0.006157
Max. :95.33 Max. :0.008330 Max. :81.400 Max. :0.007600
Stress-900-1-0.6 Strain-950-0.001-0.6 Stress-950-0.001-0.6 Strain-950-0.01-0.6
Min. : 2.160 Min. :0.000560 Min. : 2.387 Min. :0.000270
1st Qu.: 7.157 1st Qu.:0.002645 1st Qu.: 6.160 1st Qu.:0.002537
Median :17.395 Median :0.005470 Median :17.643 Median :0.004865
Mean :26.459 Mean :0.005073 Mean :24.389 Mean :0.004661
3rd Qu.:42.470 3rd Qu.:0.007180 3rd Qu.:39.305 3rd Qu.:0.006768
Max. :78.060 Max. :0.009340 Max. :68.936 Max. :0.008640
Stress-950-0.01-0.6 Strain-950-0.1-0.6 Stress-950-0.1-0.6 Strain-950-1-0.6
Min. : 2.39 Min. :0.000000 Min. : 0.00 Min. :0.000100
1st Qu.: 5.60 1st Qu.:0.002828 1st Qu.: 5.11 1st Qu.:0.002480
Median :16.48 Median :0.005275 Median :10.53 Median :0.004510
Mean :25.44 Mean :0.005228 Mean :15.53 Mean :0.004261
3rd Qu.:41.03 3rd Qu.:0.007955 3rd Qu.:23.11 3rd Qu.:0.006168
Max. :78.17 Max. :0.009510 Max. :48.95 Max. :0.007480
Stress-950-1-0.6 Strain-1000-0.001-0.6 Stress-1000-0.001-0.6
Min. : 2.25 Min. :0.000260 Min. : 2.950
1st Qu.: 7.28 1st Qu.:0.003270 1st Qu.: 4.369
Median :17.52 Median :0.005880 Median : 5.024
Mean :24.50 Mean :0.006108 Mean : 5.871
3rd Qu.:38.03 3rd Qu.:0.009080 3rd Qu.: 7.665
Max. :71.07 Max. :0.012300 Max. :10.635
Strain-1000-0.01-0.6 Stress-1000-0.01-0.6 Strain-1000-0.1-0.6
Min. :0.000520 Min. :3.640 Min. :0.000190
1st Qu.:0.003182 1st Qu.:4.375 1st Qu.:0.002873
Median :0.006360 Median :5.570 Median :0.005715
Mean :0.006232 Mean :5.696 Mean :0.005780
3rd Qu.:0.009217 3rd Qu.:6.897 3rd Qu.:0.008990
Max. :0.011480 Max. :8.850 Max. :0.011160
Stress-1000-0.1-0.6 Strain-1000-1-0.6 Stress-1000-1-0.6 Strain-1050-0.001-0.6
Min. :3.090 Min. :0.000200 Min. :2.810 Min. :0.000190
1st Qu.:4.062 1st Qu.:0.003095 1st Qu.:3.850 1st Qu.:0.002867
Median :5.580 Median :0.006165 Median :5.085 Median :0.005400
Mean :5.905 Mean :0.005970 Mean :5.322 Mean :0.005430
3rd Qu.:7.598 3rd Qu.:0.008648 3rd Qu.:6.355 3rd Qu.:0.007912
Max. :9.820 Max. :0.011500 Max. :8.300 Max. :0.010320
Stress-1050-0.001-0.6 Strain-1050-0.01-0.6 Stress-1050-0.01-0.6
Min. : 3.091 Min. :0.000030 Min. : 2.669
1st Qu.: 7.034 1st Qu.:0.002325 1st Qu.: 5.428
Median :15.970 Median :0.004960 Median :11.305
Mean :19.450 Mean :0.004983 Mean :15.829
3rd Qu.:30.786 3rd Qu.:0.007415 3rd Qu.:24.166
Max. :44.877 Max. :0.009780 Max. :43.249
Strain-1050-0.1-0.6 Stress-1050-0.1-0.6 Strain-1050-1-0.6 Stress-1050-1-0.6
Min. :0.000710 Min. : 3.090 Min. :0.000080 Min. : 2.95
1st Qu.:0.003373 1st Qu.: 4.793 1st Qu.:0.002498 1st Qu.: 5.39
Median :0.005855 Median : 7.670 Median :0.004885 Median : 9.91
Mean :0.005898 Mean :11.775 Mean :0.004587 Mean :14.32
3rd Qu.:0.008735 3rd Qu.:17.562 3rd Qu.:0.006568 3rd Qu.:21.23
Max. :0.010450 Max. :33.930 Max. :0.008540 Max. :41.80
Strain-1100-0.001-0.6 Stress-1100-0.001-0.6 Strain-1100-0.01-0.6
Min. :0.000500 Min. : 3.089 Min. :0.000000
1st Qu.:0.003350 1st Qu.: 4.966 1st Qu.:0.002770
Median :0.005950 Median : 9.199 Median :0.005635
Mean :0.005888 Mean :12.320 Mean :0.005375
3rd Qu.:0.008450 3rd Qu.:18.922 3rd Qu.:0.007853
Max. :0.011200 Max. :30.572 Max. :0.010380
Stress-1100-0.01-0.6 Strain-1100-0.1-0.6 Stress-1100-0.1-0.6
Min. : 0.000 Min. :0.001190 Min. : 2.810
1st Qu.: 4.934 1st Qu.:0.004343 1st Qu.: 4.995
Median : 9.203 Median :0.007315 Median : 8.555
Mean :12.631 Mean :0.006870 Mean :12.035
3rd Qu.:18.730 3rd Qu.:0.009577 3rd Qu.:17.648
Max. :36.425 Max. :0.011720 Max. :34.280
Strain-1100-1-0.6 Stress-1100-1-0.6 Strain-1150-0.001-0.6
Min. :0.000470 Min. : 3.370 Min. :0.000000
1st Qu.:0.002162 1st Qu.: 4.655 1st Qu.:0.002750
Median :0.003980 Median : 6.220 Median :0.005750
Mean :0.004217 Mean : 7.325 Mean :0.005538
3rd Qu.:0.006315 3rd Qu.: 9.715 3rd Qu.:0.008125
Max. :0.008470 Max. :15.550 Max. :0.011000
Stress-1150-0.001-0.6 Strain-1150-0.01-0.6 Stress-1150-0.01-0.6
Min. : 0.000 Min. :0.000100 Min. : 3.091
1st Qu.: 4.199 1st Qu.:0.003550 1st Qu.: 7.098
Median : 7.179 Median :0.005300 Median :11.998
Mean : 8.262 Mean :0.005522 Mean :15.039
3rd Qu.:10.630 3rd Qu.:0.007900 3rd Qu.:22.065
Max. :21.447 Max. :0.010100 Max. :35.747
Strain-1150-0.1-0.6 Stress-1150-0.1-0.6 Strain-1150-1-0.6 Stress-1150-1-0.6
Min. :0.000610 Min. : 2.668 Min. :0.000310 Min. : 3.090
1st Qu.:0.003780 1st Qu.: 5.801 1st Qu.:0.001830 1st Qu.: 3.790
Median :0.006260 Median :10.658 Median :0.004165 Median : 5.870
Mean :0.006118 Mean :14.597 Mean :0.004212 Mean : 6.908
3rd Qu.:0.008650 3rd Qu.:21.486 3rd Qu.:0.006085 3rd Qu.: 8.675
Max. :0.010890 Max. :41.103 Max. :0.008550 Max. :14.860
Strain-1200-0.001-0.6 Stress-1200-0.001-0.6 Strain-1200-0.01-0.6
Min. :0.000540 Min. : 3.089 Min. :0.000130
1st Qu.:0.003565 1st Qu.: 6.572 1st Qu.:0.002875
Median :0.006170 Median :13.585 Median :0.005715
Mean :0.006115 Mean :13.107 Mean :0.005550
3rd Qu.:0.008377 3rd Qu.:19.273 3rd Qu.:0.008215
Max. :0.011280 Max. :21.439 Max. :0.010920
Stress-1200-0.01-0.6 Strain-1200-0.1-0.6 Stress-1200-0.1-0.6
Min. : 3.231 Min. :0.000760 Min. : 3.228
1st Qu.: 6.369 1st Qu.:0.003565 1st Qu.: 6.397
Median :13.384 Median :0.006385 Median :12.327
Mean :15.523 Mean :0.006258 Mean :16.668
3rd Qu.:24.729 3rd Qu.:0.008882 3rd Qu.:25.781
Max. :31.553 Max. :0.011200 Max. :40.532
Strain-1200-1-0.6 Stress-1200-1-0.6
Min. :0.000210 Min. : 2.669
1st Qu.:0.002273 1st Qu.: 4.693
Median :0.004290 Median : 7.543
Mean :0.004131 Mean : 9.101
3rd Qu.:0.005897 3rd Qu.:12.475
Max. :0.007830 Max. :21.546
[1] "Strain-900-0.001-0.6" "Stress-900-0.001-0.6" "Strain-900-0.01-0.6"
[4] "Stress-900-0.01-0.6" "Strain-900-0.1-0.6" "Stress-900-0.1-0.6"
[7] "Strain-900-1-0.6" "Stress-900-1-0.6" "Strain-950-0.001-0.6"
[10] "Stress-950-0.001-0.6" "Strain-950-0.01-0.6" "Stress-950-0.01-0.6"
[13] "Strain-950-0.1-0.6" "Stress-950-0.1-0.6" "Strain-950-1-0.6"
[16] "Stress-950-1-0.6" "Strain-1000-0.001-0.6" "Stress-1000-0.001-0.6"
[19] "Strain-1000-0.01-0.6" "Stress-1000-0.01-0.6" "Strain-1000-0.1-0.6"
[22] "Stress-1000-0.1-0.6" "Strain-1000-1-0.6" "Stress-1000-1-0.6"
[25] "Strain-1050-0.001-0.6" "Stress-1050-0.001-0.6" "Strain-1050-0.01-0.6"
[28] "Stress-1050-0.01-0.6" "Strain-1050-0.1-0.6" "Stress-1050-0.1-0.6"
[31] "Strain-1050-1-0.6" "Stress-1050-1-0.6" "Strain-1100-0.001-0.6"
[34] "Stress-1100-0.001-0.6" "Strain-1100-0.01-0.6" "Stress-1100-0.01-0.6"
[37] "Strain-1100-0.1-0.6" "Stress-1100-0.1-0.6" "Strain-1100-1-0.6"
[40] "Stress-1100-1-0.6" "Strain-1150-0.001-0.6" "Stress-1150-0.001-0.6"
[43] "Strain-1150-0.01-0.6" "Stress-1150-0.01-0.6" "Strain-1150-0.1-0.6"
[46] "Stress-1150-0.1-0.6" "Strain-1150-1-0.6" "Stress-1150-1-0.6"
[49] "Strain-1200-0.001-0.6" "Stress-1200-0.001-0.6" "Strain-1200-0.01-0.6"
[52] "Stress-1200-0.01-0.6" "Strain-1200-0.1-0.6" "Stress-1200-0.1-0.6"
[55] "Strain-1200-1-0.6" "Stress-1200-1-0.6"
$tree
$tree[[1]]
[1] "Strain" "Stress"
$tree[[2]]
$tree[[2]][[1]]
[1] "900" "950" "1000" "1050" "1100" "1150" "1200"
$tree[[2]][[2]]
$tree[[2]][[2]][[1]]
[1] "0.001" "0.01" "0.1" "1"
$tree[[2]][[2]][[2]]
$tree[[2]][[2]][[2]][[1]]
[1] "0.6"
$tree[[2]][[2]][[2]][[2]]
list()
$dims
[1] 2 7 4 1
attr(,"class")
[1] "Vector.Binary.Tree"
$itemid
[1] 6
$colnames
[1] "Strain-950-0.01-0.6"
$coordinate
coo coo coo coo
1 2 2 1
$coldata
[1] 0.00027 0.00066 0.00073 0.00101 0.00123 0.00128 0.00140 0.00162 0.00173
[10] 0.00195 0.00217 0.00227 0.00250 0.00265 0.00287 0.00308 0.00323 0.00333
[19] 0.00359 0.00386 0.00417 0.00427 0.00446 0.00466 0.00480 0.00493 0.00506
[28] 0.00513 0.00532 0.00550 0.00569 0.00576 0.00599 0.00610 0.00627 0.00642
[37] 0.00670 0.00679 0.00706 0.00721 0.00737 0.00752 0.00767 0.00765 0.00775
[46] 0.00790 0.00805 0.00832 0.00848 0.00864
attr(,"class")
[1] "Trav.Inq.Data"
itemid colnames coordinate coldata
item 2 "Strain-900-0.01-0.6" Numeric,4 Numeric,50
item 4 "Strain-900-1-0.6" Numeric,4 Numeric,50
item 6 "Strain-950-0.01-0.6" Numeric,4 Numeric,50
item 8 "Strain-950-1-0.6" Numeric,4 Numeric,50
item 10 "Strain-1000-0.01-0.6" Numeric,4 Numeric,50
item 12 "Strain-1000-1-0.6" Numeric,4 Numeric,50
item 14 "Strain-1050-0.01-0.6" Numeric,4 Numeric,50
item 16 "Strain-1050-1-0.6" Numeric,4 Numeric,50
item 18 "Strain-1100-0.01-0.6" Numeric,4 Numeric,50
item 20 "Strain-1100-1-0.6" Numeric,4 Numeric,50
attr(,"class")
[1] "Trav.Inq.Data"
itemid colnames coordinate coldata
item 2 "Strain-900-0.01-0.6" Numeric,4 Numeric,50
item 4 "Strain-900-1-0.6" Numeric,4 Numeric,50
item 6 "Strain-950-0.01-0.6" Numeric,4 Numeric,50
item 8 "Strain-950-1-0.6" Numeric,4 Numeric,50
item 10 "Strain-1000-0.01-0.6" Numeric,4 Numeric,50
item 12 "Strain-1000-1-0.6" Numeric,4 Numeric,50
item 14 "Strain-1050-0.01-0.6" Numeric,4 Numeric,50
item 16 "Strain-1050-1-0.6" Numeric,4 Numeric,50
item 18 "Strain-1100-0.01-0.6" Numeric,4 Numeric,50
item 20 "Strain-1100-1-0.6" Numeric,4 Numeric,50
attr(,"class")
[1] "Trav.Inq.Data"
itemid colnames coordinate coldata
item 2 "Strain-900-0.01-0.6" Numeric,4 Numeric,50
item 4 "Strain-900-1-0.6" Numeric,4 Numeric,50
item 6 "Strain-950-0.01-0.6" Numeric,4 Numeric,50
item 8 "Strain-950-1-0.6" Numeric,4 Numeric,50
item 10 "Strain-1000-0.01-0.6" Numeric,4 Numeric,50
item 12 "Strain-1000-1-0.6" Numeric,4 Numeric,50
item 14 "Strain-1050-0.01-0.6" Numeric,4 Numeric,50
item 16 "Strain-1050-1-0.6" Numeric,4 Numeric,50
item 18 "Strain-1100-0.01-0.6" Numeric,4 Numeric,50
item 20 "Strain-1100-1-0.6" Numeric,4 Numeric,50
attr(,"class")
[1] "Trav.Inq.Data"
itemid colnames coordinate coldata
item 2 "Strain-900-0.01-0.6" Numeric,4 Numeric,50
item 4 "Strain-900-1-0.6" Numeric,4 Numeric,50
item 6 "Strain-950-0.01-0.6" Numeric,4 Numeric,50
item 8 "Strain-950-1-0.6" Numeric,4 Numeric,50
item 10 "Strain-1000-0.01-0.6" Numeric,4 Numeric,50
item 12 "Strain-1000-1-0.6" Numeric,4 Numeric,50
item 14 "Strain-1050-0.01-0.6" Numeric,4 Numeric,50
item 16 "Strain-1050-1-0.6" Numeric,4 Numeric,50
item 18 "Strain-1100-0.01-0.6" Numeric,4 Numeric,50
item 20 "Strain-1100-1-0.6" Numeric,4 Numeric,50
attr(,"class")
[1] "Trav.Inq.Data"
itemid colnames coordinate coldata
item 2 "Strain-900-0.01-0.6" Numeric,4 Numeric,50
item 4 "Strain-900-1-0.6" Numeric,4 Numeric,50
item 6 "Strain-950-0.01-0.6" Numeric,4 Numeric,50
item 8 "Strain-950-1-0.6" Numeric,4 Numeric,50
item 10 "Strain-1000-0.01-0.6" Numeric,4 Numeric,50
item 12 "Strain-1000-1-0.6" Numeric,4 Numeric,50
item 14 "Strain-1050-0.01-0.6" Numeric,4 Numeric,50
item 16 "Strain-1050-1-0.6" Numeric,4 Numeric,50
item 18 "Strain-1100-0.01-0.6" Numeric,4 Numeric,50
item 20 "Strain-1100-1-0.6" Numeric,4 Numeric,50
attr(,"class")
[1] "Trav.Inq.Data"
itemid colnames coordinate coldata
item 2 "Strain-900-0.01-0.6" Numeric,4 Numeric,50
item 4 "Strain-900-1-0.6" Numeric,4 Numeric,50
item 6 "Strain-950-0.01-0.6" Numeric,4 Numeric,50
item 8 "Strain-950-1-0.6" Numeric,4 Numeric,50
item 10 "Strain-1000-0.01-0.6" Numeric,4 Numeric,50
item 12 "Strain-1000-1-0.6" Numeric,4 Numeric,50
item 14 "Strain-1050-0.01-0.6" Numeric,4 Numeric,50
item 16 "Strain-1050-1-0.6" Numeric,4 Numeric,50
item 18 "Strain-1100-0.01-0.6" Numeric,4 Numeric,50
item 20 "Strain-1100-1-0.6" Numeric,4 Numeric,50
attr(,"class")
[1] "Trav.Inq.Data"
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