| Title: | Vector Binary Tree to Make Your Data Management More Efficient |
|---|---|
| Description: | Vector binary tree provides a new data structure, to make your data visiting and management more efficient. If the data has structured column names, it can read these names and factorize them through specific split pattern, then build the mappings within double list, vector binary tree, array and tensor mutually, through which the batched data processing is achievable easily. The methods of array and tensor are also applicable. Detailed methods are described in Chen Zhang et al. (2020) <doi:10.35566/isdsa2019c8>. |
| Authors: | Chen Zhang [aut, cre, cph] |
| Maintainer: | Chen Zhang <[email protected]> |
| License: | GPL-3 |
| Version: | 0.1.1 |
| Built: | 2025-02-06 03:25:15 UTC |
| Source: | https://github.com/cubiczebra/vbtree |
Vector binary tree provides a new data structure, to make your data visiting and management more efficient. If the data has structured column names, it can read these names and factorize them through specific split pattern, then build the mappings within double list, vector binary tree, array and tensor mutually, through which the batched data processing is achievable easily. The methods of array and tensor are also applicable. Detailed methods are described in Chen Zhang et al. (2020) <doi:10.35566/isdsa2019c8>.
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.
Chen Zhang [aut, cre, cph] (<https://orcid.org/0009-0007-7689-5030>)
Maintainer: Chen Zhang <[email protected]>
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
#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, 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#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, 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
Advanced visiting for the vector binary tree. Return a double list by specific assigment determined by
the argument inq.
advbtinq(x, inq)advbtinq(x, inq)
x |
The vector binary tree to be visited. Traversal is acheivable through invalid assignment in desired layer. |
inq |
An integer double list to determine the location to be visited. The length of |
Return a double list according to the argument inq.
#Make vector binary tree: colnamevbt <- dl2vbt(chrvec2dl(colnames(datatest))) #Visit by specific assignment: visit <- list(c(2), c(3:6), c(2,4), 1) advbtinq(colnamevbt, visit) #Traversal of the second layers: visit <- list(c(2), colnamevbt$dims[2]+1, c(2,4), 1) advbtinq(colnamevbt, visit) #Invalid assignments in 1st and 3rd layers: visit <- list(c(3), c(3:6), c(5), 1) advbtinq(colnamevbt, visit)#Make vector binary tree: colnamevbt <- dl2vbt(chrvec2dl(colnames(datatest))) #Visit by specific assignment: visit <- list(c(2), c(3:6), c(2,4), 1) advbtinq(colnamevbt, visit) #Traversal of the second layers: visit <- list(c(2), colnamevbt$dims[2]+1, c(2,4), 1) advbtinq(colnamevbt, visit) #Invalid assignments in 1st and 3rd layers: visit <- list(c(3), c(3:6), c(5), 1) advbtinq(colnamevbt, visit)
Advanced visiting for the vector binary tree. Generating a sub tree from visited vector binary tree,
through specific assigment determined by the argument inq.
advbtsub(x, inq)advbtsub(x, inq)
x |
The vector binary tree to be visited. Traversal is acheivable through invalid assignment in desired layers. |
inq |
An integer double list to determine the visiting location. The length of |
Return a sub tree from visited vector binary tree, according to the argument inq.
#Make vector binary tree: colnamevbt <- dl2vbt(chrvec2dl(colnames(datatest))) #Visit by specific assignment: visit <- list(c(2), c(3:6), c(2,4), 1) advbtsub(colnamevbt, visit) #Traversal of the second layers: visit <- list(c(2), colnamevbt$dims[2]+1, c(2,4), 1) advbtsub(colnamevbt, visit) #Invalid assignments in 1st and 3rd layers: visit <- list(c(3), c(3:6), c(5), 1) advbtsub(colnamevbt, visit)#Make vector binary tree: colnamevbt <- dl2vbt(chrvec2dl(colnames(datatest))) #Visit by specific assignment: visit <- list(c(2), c(3:6), c(2,4), 1) advbtsub(colnamevbt, visit) #Traversal of the second layers: visit <- list(c(2), colnamevbt$dims[2]+1, c(2,4), 1) advbtsub(colnamevbt, visit) #Invalid assignments in 1st and 3rd layers: visit <- list(c(3), c(3:6), c(5), 1) advbtsub(colnamevbt, visit)
Convert a structured character array to a double list. All character elements in array will be splited by a specific pattern then sorted intrinsically in each layer of the double list.
arr2dl(x, ...)arr2dl(x, ...)
x |
A structured character array to be converted. |
... |
Argument in |
Return a double list based on the input array.
#Write the column names of datatest into a array: arr <- dl2arr(chrvec2dl(colnames(datatest))) #Recover the double list from character array: arr2dl(arr)#Write the column names of datatest into a array: arr <- dl2arr(chrvec2dl(colnames(datatest))) #Recover the double list from character array: arr2dl(arr)
Convert a structured character array to a vector binary tree. All character elements in array will be splited by a specific pattern then sorted intrinsically in each layer of the vector binary tree.
arr2vbt(x, ...)arr2vbt(x, ...)
x |
A structured character array to be converted. |
... |
Argument in |
Return a vector binary tree based on the input array.
#Write the column names of datatest into a array: arr <- dl2arr(chrvec2dl(colnames(datatest))) #Recover the vector binary tree from character array: arr2vbt(arr)#Write the column names of datatest into a array: arr <- dl2arr(chrvec2dl(colnames(datatest))) #Recover the vector binary tree from character array: arr2vbt(arr)
Structurize a character vector to a double list. Layers in the double list will be determined by the given pattern.
chrvec2dl(x, splt = "-")chrvec2dl(x, splt = "-")
x |
a character vector to be converted. |
splt |
a string pattern to make defination for spliting each layer of double list. |
return a character double list splited by defined pattern, the default pattern is "-".
#example using default dataset: charvector <- colnames(datatest) chrvec2dl(charvector, "-")#example using default dataset: charvector <- colnames(datatest) chrvec2dl(charvector, "-")
A test data with 56 different columns.
data("datatest")data("datatest")
A test data structurized column names, with two data type "Strain" and "Stress", 7 different temperatures, 4 kinds strain rates and one level of compression rate.
datatestdatatest
Extract the subset of data by column names using tensor, array, double list, integer vector, or vector binary tree.
datavisit(data, inq)datavisit(data, inq)
data |
A data.frame with structured column names. |
inq |
An argument to determine the subset to be extracted by column names. A tensor, array, double list, integer vector and
vector binary tree is available format of |
Return a list which contains the item index, column name, column coordinate and the data in corresponding column for each
element contained in the assignment of inq.
vbtinq, advbtinq, trvseleinq,
trvsidxinq, trvssubinq.
#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)) # undefined 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, 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#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)) # undefined 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, 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
Convert a double list to an array. The pure numeric layers will be sorted intrinsically then all elements will be bound in certain order as one character element, and filled into the proper location in the array.
dl2arr(x)dl2arr(x)
x |
A double list to be converted. |
Return an array filled with the binding character elements.
#Make column names of datatest into double list: dl <- chrvec2dl(colnames(datatest), "-") #Convert the double list to a tensor: dl2arr(dl)#Make column names of datatest into double list: dl <- chrvec2dl(colnames(datatest), "-") #Convert the double list to a tensor: dl2arr(dl)
Convert a double list to a tensor. The pure numeric layers will be sorted intrinsically then all elements will be bound in certain order as one character element, and filled into the proper location in the tensor.
dl2ts(x)dl2ts(x)
x |
A double list to be converted. |
Return a tensor filled with the binding character elements.
#Make column names of datatest into double list: dl <- chrvec2dl(colnames(datatest), "-") #Convert the double list to a tensor: dl2ts(dl)#Make column names of datatest into double list: dl <- chrvec2dl(colnames(datatest), "-") #Convert the double list to a tensor: dl2ts(dl)
Convert a double list to vector binary tree. The pure numeric layers will be sorted intrinsically then all elements be exported in character form.
dl2vbt(x, regularize = TRUE, splt = "-")dl2vbt(x, regularize = TRUE, splt = "-")
x |
A double list to be converted. |
regularize |
A boolean value to control the treatment of empty layers of double listed to be converted.
The default value |
splt |
A string pattern to split the binding elements in each layer if the sub-constructure exists. The default pattern uses "-". |
Return a vector binary tree.
vbtinq, vbtsub, advbtinq,
advbtsub, trvssubinq, dl2ts,
dl2arr.
#Structurize the column names of datatest: colname <- colnames(datatest) colnamedl <- chrvec2dl(colname, "-") colnamevbt <- dl2vbt(colnamedl) #Simple data cleaning for sub-constructure existing double list; #Make unregulated double list: unregdl <- list(c("7", 2, 10), c("chr", "5"), c(), c("var2", "var1", "var3"), c("M-8-9", "3-2"), c("6-3", "2-7")) regvbt <- dl2vbt(unregdl) regvbt2 <- dl2vbt(unregdl, FALSE) # not recommended#Structurize the column names of datatest: colname <- colnames(datatest) colnamedl <- chrvec2dl(colname, "-") colnamevbt <- dl2vbt(colnamedl) #Simple data cleaning for sub-constructure existing double list; #Make unregulated double list: unregdl <- list(c("7", 2, 10), c("chr", "5"), c(), c("var2", "var1", "var3"), c("M-8-9", "3-2"), c("6-3", "2-7")) regvbt <- dl2vbt(unregdl) regvbt2 <- dl2vbt(unregdl, FALSE) # not recommended
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Generating a table of traversal from given vector binary tree, in order to construct correct mapping relationships within double list, vector binary tree, array and tensor.
trvs(x)trvs(x)
x |
A vector binary tree. |
Return a traversal table from the given vector binary tree.
#Make vector binary tree: colnamevbt <- dl2vbt(chrvec2dl(colnames(datatest))) #Construct traversal table: trvs(colnamevbt)#Make vector binary tree: colnamevbt <- dl2vbt(chrvec2dl(colnames(datatest))) #Construct traversal table: trvs(colnamevbt)
Visit the traversal table generated from a vector binary tree through the character element determined by the argument inq, and return
an inquiry result containing its numeric item index, the character pattern and its corresponding coordinate.
trvseleinq(trvs, inq)trvseleinq(trvs, inq)
trvs |
The traversal table to be visited, which should be generated from the vector binary tree by the function trvs(). |
inq |
A desired character element to match the traversal table. |
Return an inquiry result with a numeric item index, a character pattern and its coordinate in form of integer vector.
#Make traversal table: trav <- trvs(dl2vbt(chrvec2dl(colnames(datatest)))) #Visit specific element by character pattern: trvseleinq(trav,"Strain-1100-0.001-0.6")#Make traversal table: trav <- trvs(dl2vbt(chrvec2dl(colnames(datatest)))) #Visit specific element by character pattern: trvseleinq(trav,"Strain-1100-0.001-0.6")
Visit the traversal table generated from a vector binary tree through the coordinate determined by the argument inq, and return
an inquiry result containing its numeric item index, its corresponding character pattern and the coordinate.
trvsidxinq(trvs, inq)trvsidxinq(trvs, inq)
trvs |
The traversal table to be visited, which should be generated from the vector binary tree by the function trvs(). |
inq |
An integer vector to assign the coordinate corresponding to the element to be visited. |
Return an inquiry result with a numeric item index, a character pattern and its coordinate in form of integer vector.
#Make traversal table: trav <- trvs(dl2vbt(chrvec2dl(colnames(datatest)))) #Visit specific element by its coordinate: trvsidxinq(trav,c(1,2,3,1))#Make traversal table: trav <- trvs(dl2vbt(chrvec2dl(colnames(datatest)))) #Visit specific element by its coordinate: trvsidxinq(trav,c(1,2,3,1))
Visit the traversal table generated from a vector binary tree through the sub vector binary tree determined by the argument inq, and
return an inquiry list containing the numeric index, the character pattern and the corresponding coordinate for each item.
trvssubinq(trvs, inq)trvssubinq(trvs, inq)
trvs |
The traversal table to be visited, which should be generated from the vector binary tree by the function trvs(). |
inq |
A sub tree generated from the original vector binary tree, to determine the subset of elements to be visited. |
Return a list containing the numeric index, the character pattern and the corresponding coordinate for each item.
#Make original vector binary tree and its traversal table: vbt <- dl2vbt(chrvec2dl(colnames(datatest))) trav <- trvs(vbt) #Visit all elements defined by sub vector binary tree: #example 1: visit all "Stress-*-*-*" patterns; #make sub vector binary tree through vbtsub() then execute inquiry: subvbt <- vbtsub(vbt, c(2,-1,-1,-1)) trvssubinq(trav, subvbt) #example 2: visit all "Strain-("950", "1050")-("0.001", "0.1")-*" patterns; #make sub vector binary tree through advbtsub() then execute inquiry: subvbt <- advbtsub(vbt, list(1, c(2,4), c(1,3), 1)) trvssubinq(trav, subvbt)#Make original vector binary tree and its traversal table: vbt <- dl2vbt(chrvec2dl(colnames(datatest))) trav <- trvs(vbt) #Visit all elements defined by sub vector binary tree: #example 1: visit all "Stress-*-*-*" patterns; #make sub vector binary tree through vbtsub() then execute inquiry: subvbt <- vbtsub(vbt, c(2,-1,-1,-1)) trvssubinq(trav, subvbt) #example 2: visit all "Strain-("950", "1050")-("0.001", "0.1")-*" patterns; #make sub vector binary tree through advbtsub() then execute inquiry: subvbt <- advbtsub(vbt, list(1, c(2,4), c(1,3), 1)) trvssubinq(trav, subvbt)
Convert a structured character tensor to a double list. All character elements in tensor will be splited by a specific pattern then sorted intrinsically in each layer of the double list.
ts2dl(x, ...)ts2dl(x, ...)
x |
A structured character tensor to be converted. |
... |
Argument in |
Return a double list based on the input tensor.
#Write the column names of datatest into a tensor: ts <- dl2ts(chrvec2dl(colnames(datatest))) #Recover the double list from character tensor: ts2dl(ts)#Write the column names of datatest into a tensor: ts <- dl2ts(chrvec2dl(colnames(datatest))) #Recover the double list from character tensor: ts2dl(ts)
Convert a structured character tensor to a vector binary tree. All character elements in tensor will be splited by a specific pattern then sorted intrinsically in each layer of the vector binary tree.
ts2vbt(x, ...)ts2vbt(x, ...)
x |
A structured character tensor to be converted. |
... |
Argument in |
Return a vector binary tree based on the input tensor.
#Write the column names of datatest into a tensor: ts <- dl2ts(chrvec2dl(colnames(datatest))) #Recover the vector binary tree from character tensor: ts2vbt(ts)#Write the column names of datatest into a tensor: ts <- dl2ts(chrvec2dl(colnames(datatest))) #Recover the vector binary tree from character tensor: ts2vbt(ts)
Convert a vector binary tree to an array. The pure numeric layers will be sorted intrinsically then all elements will be bound in certain order as one character element, and filled into the proper location in the array.
vbt2arr(x)vbt2arr(x)
x |
A vector binary tree to be converted. |
Return an array filled with the binding character elements.
#Make column names of datatest into vector binary tree: vbt <- dl2vbt(chrvec2dl(colnames(datatest), "-")) #Convert the vector binary tree to an array: vbt2arr(vbt)#Make column names of datatest into vector binary tree: vbt <- dl2vbt(chrvec2dl(colnames(datatest), "-")) #Convert the vector binary tree to an array: vbt2arr(vbt)
Recover a vector binary tree to double list for easy visualization. Empty layers in vector binary tree will be marked by the symbol "*" as default.
vbt2dl(x)vbt2dl(x)
x |
A vector binary tree to be converted. |
Return a double list based on input vector binary tree.
vbtinq, vbtsub, advbtinq,
advbtsub, trvssubinq, vbt2ts,
vbt2arr.
#Recover vector binary tree to a double list for easy visualization: vbt <- dl2vbt(chrvec2dl(colnames(datatest))) #make vector binary tree vbt2dl(vbt)#Recover vector binary tree to a double list for easy visualization: vbt <- dl2vbt(chrvec2dl(colnames(datatest))) #make vector binary tree vbt2dl(vbt)
Convert a vector binary tree to a tensor. The pure numeric layers will be sorted intrinsically then all elements will be bound in certain order as one character element, and filled into the proper location in the tensor.
vbt2ts(x)vbt2ts(x)
x |
A vector binary tree to be converted. |
Return a tensor filled with the binding character elements.
#Make column names of datatest into vector binary tree: vbt <- dl2vbt(chrvec2dl(colnames(datatest), "-")) #Convert the vector binary tree to a tensor: vbt2ts(vbt)#Make column names of datatest into vector binary tree: vbt <- dl2vbt(chrvec2dl(colnames(datatest), "-")) #Convert the vector binary tree to a tensor: vbt2ts(vbt)
Visit the vector binary tree and return a double list through specific assigment determined
by the argument inq.
vbtinq(x, inq)vbtinq(x, inq)
x |
The vector binary tree to be visited. Traversal is available by setting -1 in desired layer. |
inq |
An integer vector to determine desired location. The length of |
Return a double list according to the argument inq.
#Make vector binary tree: colnamevbt <- dl2vbt(chrvec2dl(colnames(datatest))) #Visit by specific assignment: vbtinq(colnamevbt, c(2, 3, 1, 1)) #Traversal of the second layers: vbtinq(colnamevbt, c(2, -1, 1, 1)) #Invalid assignments in 1st and 3rd layers: vbtinq(colnamevbt, c(4, 3, 7, 1))#Make vector binary tree: colnamevbt <- dl2vbt(chrvec2dl(colnames(datatest))) #Visit by specific assignment: vbtinq(colnamevbt, c(2, 3, 1, 1)) #Traversal of the second layers: vbtinq(colnamevbt, c(2, -1, 1, 1)) #Invalid assignments in 1st and 3rd layers: vbtinq(colnamevbt, c(4, 3, 7, 1))
Visit the vector binary tree and generate a sub tree from visited vector binary tree, through
specific assigment determined by the argument inq.
vbtsub(x, inq)vbtsub(x, inq)
x |
The vector binary tree to be visited. Traversal is available by setting -1 in desired layer. |
inq |
An integer vector to determine the visiting location. The length of |
Return a sub tree from visited vector binary tree, according to the argument inq.
#Make vector binary tree: colnamevbt <- dl2vbt(chrvec2dl(colnames(datatest))) #Generating sub tree by specific assignment: vbtsub(colnamevbt, c(2, 3, 1, 1)) #Generating sub tree with traversal in the second layers: vbtsub(colnamevbt, c(2, -1, 1, 1)) #Generating sub tree with invalid assignments in 1st and 3rd layers: vbtsub(colnamevbt, c(4, 3, 7, 1))#Make vector binary tree: colnamevbt <- dl2vbt(chrvec2dl(colnames(datatest))) #Generating sub tree by specific assignment: vbtsub(colnamevbt, c(2, 3, 1, 1)) #Generating sub tree with traversal in the second layers: vbtsub(colnamevbt, c(2, -1, 1, 1)) #Generating sub tree with invalid assignments in 1st and 3rd layers: vbtsub(colnamevbt, c(4, 3, 7, 1))