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
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
|
## ----setup, include=FALSE-----------------------------------------------------
library(BiocStyle)
## ----eval=FALSE---------------------------------------------------------------
# if (!require("BiocManager", quietly=TRUE))
# install.packages("BiocManager")
# BiocManager::install("SparseArray")
## ----message=FALSE------------------------------------------------------------
library(SparseArray)
## -----------------------------------------------------------------------------
svt1 <- SVT_SparseArray(dim=c(6, 4))
svt1[c(1:2, 8, 10, 15:17, 24)] <- (1:8)*10L
svt1
svt2 <- SVT_SparseArray(dim=5:3)
svt2[c(1:2, 8, 10, 15:17, 20, 24, 40, 56:60)] <- (1:15)*10L
svt2
## -----------------------------------------------------------------------------
# Coerce a dgCMatrix object to SVT_SparseArray:
dgcm <- Matrix::rsparsematrix(12, 5, density=0.15)
svt3 <- as(dgcm, "SVT_SparseArray")
# Coerce a TENxMatrix object to SVT_SparseArray:
suppressMessages(library(HDF5Array))
M <- writeTENxMatrix(svt3)
svt3b <- as(M, "SVT_SparseArray")
# Sanity check:
stopifnot(identical(svt3, svt3b))
## -----------------------------------------------------------------------------
svt3 <- SVT_SparseArray(dgcm) # same as as(dgcm, "SVT_SparseArray")
svt3b <- SVT_SparseArray(M) # same as as(M, "SVT_SparseArray")
## -----------------------------------------------------------------------------
# Coerce an ordinary matrix to SparseArray:
a <- array(rpois(80, lambda=0.35), dim=c(5, 8, 2))
class(as(a, "SparseArray")) # SVT_SparseArray
# Coerce a dgCMatrix object to SparseArray:
svt3 <- as(dgcm, "SparseArray")
class(svt3) # SVT_SparseArray
# Coerce a TENxMatrix object to SparseArray:
svt3b <- as(M, "SparseArray")
class(svt3) # SVT_SparseArray
## -----------------------------------------------------------------------------
SparseArray(a) # same as as(a, "SparseArray")
svt3 <- SparseArray(dgcm) # same as as(dgcm, "SparseArray")
svt3b <- SparseArray(M) # same as as(M, "SparseArray")
## -----------------------------------------------------------------------------
ngrm <- sparseMatrix(i=c(1, 5, 5, 6), j=c(4, 2, 3, 2), repr="R")
class(ngrm) # ngRMatrix
class(SparseArray(ngrm)) # COO_SparseMatrix
## -----------------------------------------------------------------------------
svt <- as(SparseArray(ngrm), "SVT_SparseArray")
class(svt) # SVT_SparseMatrix
## -----------------------------------------------------------------------------
as.array(svt1) # same as as.matrix(svt1)
as.array(svt2)
## -----------------------------------------------------------------------------
dim(svt2)
length(svt2)
dimnames(svt2) <- list(NULL, letters[1:4], LETTERS[1:3])
svt2
## -----------------------------------------------------------------------------
type(svt1)
type(svt1) <- "double"
svt1
is_sparse(svt1)
## -----------------------------------------------------------------------------
is_nonzero(svt1)
## Get the number of nonzero array elements in 'svt1':
nzcount(svt1)
## Extract the "linear indices" of the nonzero array elements in 'svt1':
nzwhich(svt1)
## Extract the "array indices" (a.k.a. "array coordinates") of the
## nonzero array elements in 'svt1':
nzwhich(svt1, arr.ind=TRUE)
## Extract the values of the nonzero array elements in 'svt1':
nzvals(svt1)
## -----------------------------------------------------------------------------
svt2[5:3, , "C"]
## -----------------------------------------------------------------------------
type(svt2)
svt2[5, 1, 3] <- NaN
type(svt2)
## -----------------------------------------------------------------------------
anyNA(svt2)
range(svt2, na.rm=TRUE)
mean(svt2, na.rm=TRUE)
var(svt2, na.rm=TRUE)
## -----------------------------------------------------------------------------
signif((svt1^1.5 + svt1) %% 100 - 0.6 * svt1, digits=2)
## -----------------------------------------------------------------------------
t(svt1)
## -----------------------------------------------------------------------------
aperm(svt2)
## -----------------------------------------------------------------------------
svt4 <- poissonSparseMatrix(6, 2, density=0.5)
cbind(svt1, svt4)
## -----------------------------------------------------------------------------
svt5a <- poissonSparseArray(c(5, 6, 2), density=0.4)
svt5b <- poissonSparseArray(c(5, 6, 5), density=0.2)
svt5c <- poissonSparseArray(c(5, 6, 4), density=0.2)
abind(svt5a, svt5b, svt5c)
svt6a <- aperm(svt5a, c(1, 3:2))
svt6b <- aperm(svt5b, c(1, 3:2))
svt6c <- aperm(svt5c, c(1, 3:2))
abind(svt6a, svt6b, svt6c, along=2)
## -----------------------------------------------------------------------------
svt7 <- SVT_SparseArray(dim=5:6, dimnames=list(letters[1:5], LETTERS[1:6]))
svt7[c(2, 6, 12:17, 22:30)] <- 101:117
colVars(svt7)
## -----------------------------------------------------------------------------
colVars(svt2)
colVars(svt2, dims=2)
colAnyNAs(svt2)
colAnyNAs(svt2, dims=2)
## -----------------------------------------------------------------------------
rowsum(svt7, group=c(1:3, 2:1))
colsum(svt7, group=c("A", "B", "A", "B", "B", "A"))
## -----------------------------------------------------------------------------
svt7 %*% svt4
## -----------------------------------------------------------------------------
crossprod(svt4)
## -----------------------------------------------------------------------------
randomSparseArray(c(5, 6, 2), density=0.5)
poissonSparseArray(c(5, 6, 2), density=0.5)
## -----------------------------------------------------------------------------
csv_file <- tempfile()
writeSparseCSV(svt7, csv_file)
## -----------------------------------------------------------------------------
readSparseCSV(csv_file)
## -----------------------------------------------------------------------------
suppressMessages(library(HDF5Array))
suppressMessages(library(ExperimentHub))
hub <- ExperimentHub()
oneM <- TENxMatrix(hub[["EH1039"]], group="mm10")
oneM
## -----------------------------------------------------------------------------
nzcount(oneM)
## ----eval=FALSE---------------------------------------------------------------
# # WARNING: This takes a couple of minutes on a modern laptop, and will
# # consume about 25Gb of RAM!
# svt <- as(oneM, "SVT_SparseArray")
## ----eval=FALSE---------------------------------------------------------------
# # This will fail because 'oneM' has more than 2^31 nonzero values!
# as(oneM, "dgCMatrix")
## -----------------------------------------------------------------------------
sessionInfo()
|
