library(tiledb)
uri <- "/tmp/tiledb/dt_year"
-arr <- tiledb_array(uri, as.data.frame=TRUE)
+arr <- tiledb_array(uri, return_as="data.frame")
arr[]
## rows a
## 1 2001-01-01 1
@@ -387,7 +387,7 @@ Python
R
library(tiledb)
uri <- "/tmp/tiledb/dt_day"
-arr <- tiledb_array(uri, as.data.frame=TRUE)
+arr <- tiledb_array(uri, return_as="data.frame")
arr[]
## rows a
## 1 2001-01-01 1
@@ -426,7 +426,7 @@ Python
R
library(tiledb)
uri <- "/tmp/tiledb/dt_min"
-arr <- tiledb_array(uri, as.data.frame=TRUE)
+arr <- tiledb_array(uri, return_as="data.frame")
arr[]
## rows a
## 1 2001-01-01 00:00:00 1
@@ -468,7 +468,7 @@ Python
R
library(tiledb)
uri <- "/tmp/tiledb/dt_ms"
-arr <- tiledb_array(uri, as.data.frame=TRUE)
+arr <- tiledb_array(uri, return_as="data.frame")
arr[]
## rows a
## 1 1970-01-01 00:00:00.001 1
@@ -513,7 +513,7 @@ Python
R
library(tiledb)
uri <- "/tmp/tiledb/dt_us"
-arr <- tiledb_array(uri, as.data.frame=TRUE)
+arr <- tiledb_array(uri, return_as="data.frame")
arr[]
## rows a
## 1 1970-01-01 00:00:00.000001 1
@@ -558,7 +558,7 @@ Python
R
library(tiledb)
uri <- "/tmp/tiledb/dt_ns"
-arr <- tiledb_array(uri, as.data.frame=TRUE)
+arr <- tiledb_array(uri, return_as="data.frame")
arr[]
## rows a
## 1 1970-01-01T00:00:00.000000001+00:00 1
@@ -575,7 +575,7 @@ Use integer64 Directly
Sometimes we may want to access the date or datetimes value in their native integer64 format. To do so, we set a toggle when opening the array as shown in the following example which uses the array from the preceding example (at resolution of nanosecond).
library(tiledb)
uri <- "/tmp/tiledb/dt_ns"
-arr <- tiledb_array(uri, as.data.frame=TRUE, datetimes_as_int64=TRUE)
+arr <- tiledb_array(uri, return_as="data.frame", datetimes_as_int64=TRUE)
arr[]
## rows a
## 1 1 1
@@ -587,7 +587,7 @@ Use integer64 Directly
We can also write integer64 types. The following example adds two extra rows:
library(tiledb)
uri <- "/tmp/tiledb/dt_ns"
-arr <- tiledb_array(uri, as.data.frame=TRUE, datetimes_as_int64=TRUE)
+arr <- tiledb_array(uri, return_as="data.frame", datetimes_as_int64=TRUE)
arr[] <- data.frame( rows=bit64::as.integer64(2:3), a=102:103)
arr[]
## rows a
diff --git a/inst/tinytest/test_arrowio.R b/inst/tinytest/test_arrowio.R
index 5f2598e879..de1a3a740f 100644
--- a/inst/tinytest/test_arrowio.R
+++ b/inst/tinytest/test_arrowio.R
@@ -73,7 +73,7 @@ tiledb_query_set_layout(qry, "UNORDERED")
tiledb_query_submit(qry)
tiledb_query_finalize(qry)
-#arr <- tiledb_array(tmp, as.data.frame=TRUE)
+#arr <- tiledb_array(tmp, return_as="data.frame")
#print(arr[])
@@ -162,7 +162,7 @@ tiledb_query_set_layout(qry, "UNORDERED")
tiledb_query_submit(qry)
tiledb_query_finalize(qry)
-arr <- tiledb_array(tmp, as.data.frame=TRUE)
+arr <- tiledb_array(tmp, return_as="data.frame")
df <- arr[]
for (i in 1:10) {
diff --git a/inst/tinytest/test_attr.R b/inst/tinytest/test_attr.R
index a15d3a8a95..79f4d61f0c 100644
--- a/inst/tinytest/test_attr.R
+++ b/inst/tinytest/test_attr.R
@@ -142,7 +142,7 @@ attrib <- c(tiledb_attr("year", type = "DATETIME_YEAR"), # year
schema <- tiledb_array_schema(domain, attrib, sparse=TRUE)
res <- tiledb_array_create(uri, schema)
-arr <- tiledb_array(uri, as.data.frame=TRUE)
+arr <- tiledb_array(uri, return_as="data.frame")
dvec <- 1:3
data <- data.frame(row = dvec,
@@ -162,7 +162,7 @@ data <- data.frame(row = dvec,
)
arr[] <- data
-arr2 <- tiledb_array(uri, as.data.frame=TRUE)
+arr2 <- tiledb_array(uri, return_as="data.frame")
readdata <- arr2[]
expect_true(all.equal(data, readdata, check.attributes=FALSE))
@@ -217,7 +217,7 @@ df <- data.frame(row = 1:10,
arr <- tiledb_array(uri)
arr[] <- df
-newarr <- tiledb_array(uri, as.data.frame=TRUE)
+newarr <- tiledb_array(uri, return_as="data.frame")
chk <- newarr[]
expect_equal(df[,1:10], chk[,1:10])
expect_equivalent(as.numeric(df[,11]), chk[,11]) # we currently return uint64_t as numeric
diff --git a/inst/tinytest/test_dataframe.R b/inst/tinytest/test_dataframe.R
index 18ed7709bc..625cb5a4c2 100644
--- a/inst/tinytest/test_dataframe.R
+++ b/inst/tinytest/test_dataframe.R
@@ -16,7 +16,7 @@ if (tiledb_version(TRUE) < "2.7.0") exit_file("Needs TileDB 2.7.* or later")
fromDataFrame(irisdf, uri)
-arr <- tiledb_array(uri, as.data.frame=TRUE)
+arr <- tiledb_array(uri, return_as="data.frame")
newdf <- arr[]
#if (getRversion() >= '4.0.0') newdf$Species <- as.factor(newdf$Species)
if (getRversion() < '4.0.0') newdf$Species <- as.character(newdf$Species)
@@ -29,7 +29,7 @@ expect_equal(irisdf, newdf[,-1])
## test attrs subselection
-arr <- tiledb_array(uri, as.data.frame=TRUE, extended=FALSE,
+arr <- tiledb_array(uri, return_as="data.frame", extended=FALSE,
attrs = c("Petal.Length", "Petal.Width"))
newdf <- arr[]
expect_equivalent(iris[, c("Petal.Length", "Petal.Width")], newdf) # skip attribute
@@ -58,7 +58,7 @@ df <- data.frame(char=c("abc", "def", "g", "hijk"),
fromDataFrame(df, uri)
-arr <- tiledb_array(uri, as.data.frame=TRUE)
+arr <- tiledb_array(uri, return_as="data.frame")
newdf <- arr[]
## result comes back as factor by default
@@ -78,7 +78,7 @@ df <- data.frame(index=sort(sample(1:1000, rows)),
vals=rnorm(rows) * 100,
stringsAsFactors=FALSE)
fromDataFrame(df, uri)
-arr <- tiledb_array(uri, as.data.frame=TRUE)
+arr <- tiledb_array(uri, return_as="data.frame")
chk <- arr[]
if (getRversion() < '4.0.0') chk$chars <- as.character(chk$chars)
expect_equal(df, chk[,-1]) # omit first col which is added
@@ -87,7 +87,7 @@ if (tiledb_version(TRUE) < "2.1.0") exit_file("Remaining tests require TileDB 2.
if (dir.exists(uri)) unlink(uri, recursive=TRUE)
fromDataFrame(df, uri, col_index=1)
-arr <- tiledb_array(uri, as.data.frame=TRUE)
+arr <- tiledb_array(uri, return_as="data.frame")
chk <- arr[]
if (getRversion() < '4.0.0') chk$chars <- as.character(chk$chars)
expect_equal(df[,2], na.omit(chk)[,2]) # compare column by column
@@ -96,7 +96,7 @@ expect_equal(df[,3], na.omit(chk)[,3])
if (dir.exists(uri)) unlink(uri, recursive=TRUE)
fromDataFrame(df, uri, col_index="index")
-arr <- tiledb_array(uri, as.data.frame=TRUE)
+arr <- tiledb_array(uri, return_as="data.frame")
chk <- arr[]
if (getRversion() < '4.0.0') chk$chars <- as.character(chk$chars)
expect_equal(df[,2], na.omit(chk)[,2]) # compare column by column
@@ -108,7 +108,7 @@ df <- data.frame(chars=olddf$chars,
val=olddf$vals)
if (dir.exists(uri)) unlink(uri, recursive=TRUE)
fromDataFrame(df, uri)
-arr <- tiledb_array(uri, as.data.frame=TRUE)
+arr <- tiledb_array(uri, return_as="data.frame")
chk <- arr[]
if (getRversion() < '4.0.0') {
df$chars <- as.character(df$chars)
@@ -118,7 +118,7 @@ expect_equal(df, chk[,-1]) # omit first col which is added
if (dir.exists(uri)) unlink(uri, recursive=TRUE)
fromDataFrame(df, uri, col_index=2)
-arr <- tiledb_array(uri, as.data.frame=TRUE)
+arr <- tiledb_array(uri, return_as="data.frame")
chk <- arr[]
if (getRversion() < '4.0.0') chk$chars <- as.character(chk$chars)
expect_equal(df[,1], na.omit(chk)[,2]) # compare column by column
@@ -126,7 +126,7 @@ expect_equal(df[,3], na.omit(chk)[,3])
if (dir.exists(uri)) unlink(uri, recursive=TRUE)
fromDataFrame(df, uri, col_index="index")
-arr <- tiledb_array(uri, as.data.frame=TRUE)
+arr <- tiledb_array(uri, return_as="data.frame")
chk <- arr[]
if (getRversion() < '4.0.0') chk$chars <- as.character(chk$chars)
expect_equal(df[,1], na.omit(chk)[,2]) # compare column by column
@@ -155,13 +155,13 @@ df <- data.frame(time=round(Sys.time(), "secs") + trunc(cumsum(runif(nobs)*3600)
if (dir.exists(uri)) unlink(uri, recursive=TRUE)
fromDataFrame(df, uri, sparse=TRUE)
-chk <- tiledb_array(uri, as.data.frame=TRUE, extended=FALSE)
+chk <- tiledb_array(uri, return_as="data.frame", extended=FALSE)
expect_equivalent(df, chk[]) # skip attribute
for (i in seq_len(dim(df)[2])) {
if (dir.exists(uri)) unlink(uri, recursive=TRUE)
fromDataFrame(df, uri, sparse=TRUE, col_index=i)
- chk <- tiledb_array(uri, as.data.frame=TRUE)
+ chk <- tiledb_array(uri, return_as="data.frame")
expect_equal(df, chk[][,colnames(df)]) # index col comes first so need re-order
}
@@ -181,7 +181,7 @@ df <- data.frame(time = round(Sys.time(), "secs") + trunc(cumsum(runif(nobs)*360
if (dir.exists(uri)) unlink(uri, recursive=TRUE)
fromDataFrame(df, uri, sparse=TRUE)
-chk <- tiledb_array(uri, as.data.frame=TRUE, extended=FALSE)
+chk <- tiledb_array(uri, return_as="data.frame", extended=FALSE)
newdf <- chk[]
if (getRversion() < '4.0.0') newdf$txt <- as.character(newdf$txt)
expect_equivalent(df, newdf) # skip attribute
@@ -190,7 +190,7 @@ expect_equivalent(df, newdf) # skip attribute
for (i in seq_len(dim(df)[2])) {
if (dir.exists(uri)) unlink(uri, recursive=TRUE)
fromDataFrame(df, uri, sparse=TRUE, col_index=i)
- chk <- tiledb_array(uri, as.data.frame=TRUE)
+ chk <- tiledb_array(uri, return_as="data.frame")
newdf <- chk[]
if (getRversion() < '4.0.0') newdf$txt <- as.character(newdf$txt)
expect_equal(df, newdf[, colnames(df)])
@@ -201,14 +201,14 @@ combinations <- list(c(1,2), c(1,3), c(2,4), c(3,5), c(4,5), c(2,3,4))
for (comb in combinations) {
if (dir.exists(uri)) unlink(uri, recursive=TRUE)
fromDataFrame(df, uri, sparse=TRUE, col_index=comb) # by index
- chk <- tiledb_array(uri, as.data.frame=TRUE)
+ chk <- tiledb_array(uri, return_as="data.frame")
newdf <- chk[]
if (getRversion() < '4.0.0') newdf$txt <- as.character(newdf$txt)
expect_equal(df, newdf[][, colnames(df)])
if (dir.exists(uri)) unlink(uri, recursive=TRUE)
fromDataFrame(df, uri, sparse=TRUE, col_index=colnames(df)[comb]) # by name
- chk <- tiledb_array(uri, as.data.frame=TRUE)
+ chk <- tiledb_array(uri, return_as="data.frame")
newdf <- chk[]
if (getRversion() < '4.0.0') newdf$txt <- as.character(newdf$txt)
expect_equal(df, newdf[, colnames(df)])
@@ -223,7 +223,7 @@ dat <- data.frame(A=1:10,
dat[3,1] <- NA
dat[4,3] <- NA
fromDataFrame(dat, uri)
-chk <- tiledb_array(uri, as.data.frame=TRUE)
+chk <- tiledb_array(uri, return_as="data.frame")
val <- chk[][,-1] # omit added rows
if (getRversion() < '4.0.0') {
dat$B <- as.character(dat$B)
@@ -239,7 +239,7 @@ D <- data.frame(sample=paste(LETTERS[1:N], as.character(sort(trunc(runif(N, 100,
stringsAsFactors=FALSE)
uri <- tempfile()
fromDataFrame(D, uri, col_index=1, sparse=TRUE)
-arr <- tiledb_array(uri, as.data.frame=TRUE)
+arr <- tiledb_array(uri, return_as="data.frame")
chk <- arr[]
if (getRversion() < '4.0.0') {
chk$sample <- as.character(chk$sample)
@@ -260,7 +260,7 @@ expect_error(fromDataFrame(df, uri, col_index=1, sparse=TRUE, allows_dups=FALSE)
uri <- tempfile()
expect_silent(arr <- fromDataFrame(df, uri, col_index=1, sparse=TRUE, allows_dups=TRUE))
-arr <- tiledb_array(uri, as.data.frame=TRUE)
+arr <- tiledb_array(uri, return_as="data.frame")
chk <- arr[]
if (getRversion() < '4.0.0') chk$char <- as.character(chk$char)
expect_equivalent(df, chk) # skip attribute
diff --git a/inst/tinytest/test_dim.R b/inst/tinytest/test_dim.R
index d474917539..40c370497e 100644
--- a/inst/tinytest/test_dim.R
+++ b/inst/tinytest/test_dim.R
@@ -163,7 +163,7 @@ for (dtype in dimtypes) {
schema <- tiledb_array_schema(domain, attrib, sparse=TRUE)
tiledb_array_create(uri, schema)
- arr <- tiledb_array(uri, as.data.frame=TRUE)
+ arr <- tiledb_array(uri, return_as="data.frame")
dvec <- switch(dtype,
"ASCII" = LETTERS[1:5],
"INT8" =,
@@ -195,7 +195,7 @@ for (dtype in dimtypes) {
data <- data.frame(row = dvec, attr = avec, stringsAsFactors=FALSE)
arr[] <- data
- arr2 <- tiledb_array(uri, as.data.frame=TRUE)
+ arr2 <- tiledb_array(uri, return_as="data.frame")
readdata <- arr2[]
if (dtype == "ASCII" && getRversion() < '4.0.0') readdata$row <- as.character(readdata$row)
if (dtype == "UINT64") readdata[,1] <- as.integer64(readdata[,1]) # return doubles here
@@ -212,7 +212,7 @@ for (dtype in dimtypes) {
}
## subset tests
- arr3 <- tiledb_array(uri, as.data.frame=TRUE)
+ arr3 <- tiledb_array(uri, return_as="data.frame")
if (dtype %in% c("DATETIME_YEAR", "DATETIME_MONTH", "DATETIME_WEEK", "DATETIME_DAY")) {
scaleDate <- function(val, dtype) {
val <- switch(dtype,
@@ -331,7 +331,7 @@ for (dtype in dimtypes) {
schema <- tiledb_array_schema(domain, attrib, sparse=TRUE)
tiledb_array_create(uri, schema)
- arr <- tiledb_array(uri, as.data.frame=TRUE)
+ arr <- tiledb_array(uri, return_as="data.frame")
dvec <- switch(dtype,
"ASCII" = LETTERS[1:5],
"INT8" =,
@@ -363,7 +363,7 @@ for (dtype in dimtypes) {
data <- data.frame(row = dvec, attr = avec, stringsAsFactors=FALSE)
arr[] <- data
- ## arr2 <- tiledb_array(uri, as.data.frame=TRUE)
+ ## arr2 <- tiledb_array(uri, return_as="data.frame")
## readdata <- arr2[]
## if (dtype == "ASCII" && getRversion() < '4.0.0') readdata$row <- as.character(readdata$row)
## if (dtype == "UINT64") readdata[,1] <- as.integer64(readdata[,1]) # return doubles here
@@ -380,7 +380,7 @@ for (dtype in dimtypes) {
## }
## subset tests
- arr3 <- tiledb_array(uri, as.data.frame=TRUE)
+ arr3 <- tiledb_array(uri, return_as="data.frame")
if (dtype %in% c("DATETIME_YEAR", "DATETIME_MONTH", "DATETIME_WEEK", "DATETIME_DAY")) {
scaleDate <- function(val, dtype) {
val <- switch(dtype,
diff --git a/inst/tinytest/test_dimsubset.R b/inst/tinytest/test_dimsubset.R
index e779c48d79..40ac6d04c9 100644
--- a/inst/tinytest/test_dimsubset.R
+++ b/inst/tinytest/test_dimsubset.R
@@ -78,7 +78,7 @@ log_info("re-arranged list object made")
arr[] <- newlst
log_info("array written")
-newarr <- tiledb_array(tmp, as.data.frame=TRUE, query_layout="UNORDERED")
+newarr <- tiledb_array(tmp, return_as="data.frame", query_layout="UNORDERED")
dat <- newarr[]
log_info("array read")
expect_equal(nrow(dat), nrow(flights))
@@ -97,7 +97,7 @@ expect_equal(unique(dat$origin), "JFK")
expect_equal(unique(dat$dest), "BOS")
## same via selected_points
-newarr <- tiledb_array(tmp, as.data.frame=TRUE, query_layout="UNORDERED",
+newarr <- tiledb_array(tmp, return_as="data.frame", query_layout="UNORDERED",
selected_points= list("AA", "JFK", "BOS", NULL))
dat <- newarr[]
expect_equal(unique(dat$carrier), "AA")
@@ -105,7 +105,7 @@ expect_equal(unique(dat$origin), "JFK")
expect_equal(unique(dat$dest), "BOS")
## test named lists with one element
-newarr <- tiledb_array(tmp, as.data.frame=TRUE, query_layout="UNORDERED")
+newarr <- tiledb_array(tmp, return_as="data.frame", query_layout="UNORDERED")
selected_ranges(newarr) <- list(carrier = cbind("AA","AA"))
dat <- newarr[]
expect_equal(unique(dat$carrier), "AA")
diff --git a/inst/tinytest/test_metadata.R b/inst/tinytest/test_metadata.R
index a074ddc2bc..d127cc5720 100644
--- a/inst/tinytest/test_metadata.R
+++ b/inst/tinytest/test_metadata.R
@@ -19,8 +19,7 @@ unlink_and_create_simple <- function(tmp) {
sch <- tiledb_array_schema(dom, c(a1, a2), sparse=TRUE)
tiledb_array_create(tmp, sch)
- #arr <- tiledb_sparse(tmp, as.data.frame=FALSE)
- arr <- tiledb_array(tmp, as.data.frame=FALSE)
+ arr <- tiledb_array(tmp, return_as="asis")
if (tiledb:::libtiledb_array_is_open(arr@ptr)) {
tiledb_array_close(arr)
@@ -44,8 +43,7 @@ unlink_and_create_ptr <- function(tmp) {
arr <- tiledb_array_open(arr, "READ")
##return(arrR)
- #arr <- tiledb_sparse(tmp, as.data.frame=FALSE)
- arr <- tiledb_array(tmp, as.data.frame=FALSE)
+ arr <- tiledb_array(tmp, return_as="asis")
}
close_and_reopen <- function(arr, txt) {
diff --git a/inst/tinytest/test_query.R b/inst/tinytest/test_query.R
index ffc0400cb0..8486a1ca45 100644
--- a/inst/tinytest/test_query.R
+++ b/inst/tinytest/test_query.R
@@ -239,7 +239,7 @@ cfg <- tiledb_config()
cfg["sm.memory_budget"] <- "16"
cfg["sm.memory_budget_var"] <- "32"
ctx <- tiledb_ctx(cfg)
-array <- tiledb_array(tmp, as.data.frame=TRUE)
+array <- tiledb_array(tmp, return_as="data.frame")
if (packageVersion("tiledb") <= "0.11.0") expect_warning(res <- array[]) # newer versions loop, no warning
diff --git a/inst/tinytest/test_querycondition.R b/inst/tinytest/test_querycondition.R
index eef661caad..1101cf5069 100644
--- a/inst/tinytest/test_querycondition.R
+++ b/inst/tinytest/test_querycondition.R
@@ -145,16 +145,16 @@ if (!requireNamespace("palmerpenguins", quietly=TRUE)) exit_file("remainder need
library(palmerpenguins)
uri <- tempfile()
fromDataFrame(penguins, uri, sparse=TRUE)
-unconstr <- tiledb_array(uri, as.data.frame=TRUE)
+unconstr <- tiledb_array(uri, return_as="data.frame")
expect_equal(NROW(unconstr[]), 344L) # no condition -> 344 rows
qc <- tiledb_query_condition_init("year", 2009, "INT32", "EQ")
-arrwithqc <- tiledb_array(uri, as.data.frame=TRUE, query_condition=qc)
+arrwithqc <- tiledb_array(uri, return_as="data.frame", query_condition=qc)
res <- arrwithqc[]
expect_equal(NROW(res), 120L) # year 2009 only -> 120 rows
expect_true(all(res$year == 2009))
-arr2 <- tiledb_array(uri, as.data.frame=TRUE)
+arr2 <- tiledb_array(uri, return_as="data.frame")
expect_equal(NROW(arr2[]), 344L) # no condition -> 344 rows
query_condition(arr2) <- qc
expect_equal(NROW(arr2[]), 120L) # year 2009 only -> 120 rows
@@ -174,13 +174,13 @@ uri <- tempfile()
fromDataFrame(penguins, uri, sparse=TRUE)
arr <- tiledb_array(uri)
qc <- parse_query_condition(year == 2009)
-arrwithqc <- tiledb_array(uri, as.data.frame=TRUE, query_condition=qc)
+arrwithqc <- tiledb_array(uri, return_as="data.frame", query_condition=qc)
res <- arrwithqc[]
expect_equal(NROW(res), 120L) # year 2009 only -> 120 rows
expect_true(all(res$year == 2009))
qc2 <- parse_query_condition(year == 2009 && bill_length_mm <= 39.99)
-arrwithqc2 <- tiledb_array(uri, as.data.frame=TRUE, query_condition=qc2)
+arrwithqc2 <- tiledb_array(uri, return_as="data.frame", query_condition=qc2)
res <- arrwithqc2[]
expect_equal(NROW(res), 34L)
expect_true(all(res$bill_length_mm < 40))
@@ -188,14 +188,14 @@ expect_true(all(res$year == 2009))
if (tiledb_version(TRUE) >= "2.10.0") { # the OR operator is more recent than query conditions overall
qc3 <- parse_query_condition(island %in% c("Dream", "Biscoe"), arr)
- arrwithqc3 <- tiledb_array(uri, as.data.frame=TRUE, strings_as_factors=TRUE, query_condition=qc3)
+ arrwithqc3 <- tiledb_array(uri, return_as="data.frame", strings_as_factors=TRUE, query_condition=qc3)
res <- arrwithqc3[]
expect_equal(NROW(res), 168+124)
expect_true(all(res$island != "Torgersen"))
expect_true(all(res$island == "Dream" | res$island == "Biscoe"))
qc4 <- parse_query_condition(island %in% c("Dream", "Biscoe") && body_mass_g > 3500, arr)
- arrwithqc4 <- tiledb_array(uri, as.data.frame=TRUE, strings_as_factors=TRUE, query_condition=qc4)
+ arrwithqc4 <- tiledb_array(uri, return_as="data.frame", strings_as_factors=TRUE, query_condition=qc4)
res <- arrwithqc4[]
expect_equal(NROW(res), 153+80)
expect_true(all(res$island != "Torgersen"))
@@ -212,13 +212,13 @@ if (Sys.getenv("MY_UNIVERSE", "") != "") exit_file("Skip remainder at r-universe
uri <- tempfile()
fromDataFrame(na.omit(penguins), uri, sparse=TRUE)
qc3 <- parse_query_condition(sex == "male")
-arrwithqc3 <- tiledb_array(uri, as.data.frame=TRUE, query_condition=qc3)
+arrwithqc3 <- tiledb_array(uri, return_as="data.frame", query_condition=qc3)
res <- arrwithqc3[]
expect_equal(NROW(res), 168L)
expect_true(all(res$sex == "male"))
qc <- tiledb_query_condition_init("sex", "female", "ASCII", "EQ")
-arrwithqc <- tiledb_array(uri, as.data.frame=TRUE, query_condition=qc)
+arrwithqc <- tiledb_array(uri, return_as="data.frame", query_condition=qc)
res <- arrwithqc[]
expect_equal(NROW(res), 165L)
expect_true(all(res$sex != "male"))
@@ -230,21 +230,21 @@ uri <- tempfile()
fromDataFrame(edgecases, uri, sparse=TRUE)
qcx1 <- tiledb::parse_query_condition(x1 == "a1")
-arrx1 <- tiledb_array(uri, as.data.frame=TRUE, query_condition=qcx1)
+arrx1 <- tiledb_array(uri, return_as="data.frame", query_condition=qcx1)
res <- arrx1[]
expect_equal(res$x1, "a1")
qcx2 <- tiledb::parse_query_condition(x2 == 1L)
-arrx2 <- tiledb_array(uri, as.data.frame=TRUE, query_condition=qcx2)
+arrx2 <- tiledb_array(uri, return_as="data.frame", query_condition=qcx2)
res <- arrx2[]
expect_equal(res$x2, 1L)
qcx3 <- tiledb::parse_query_condition(x3 == "_1")
-arrx3 <- tiledb_array(uri, as.data.frame=TRUE, query_condition=qcx3)
+arrx3 <- tiledb_array(uri, return_as="data.frame", query_condition=qcx3)
expect_equal(arrx3[]$x3, "_1")
qcx4 <- tiledb::parse_query_condition(x4 == "1.1.1")
-arrx4 <- tiledb_array(uri, as.data.frame=TRUE, query_condition=qcx4)
+arrx4 <- tiledb_array(uri, return_as="data.frame", query_condition=qcx4)
expect_equal(arrx4[]$x4, "1.1.1")
@@ -254,9 +254,9 @@ df <- data.frame(abb = state.abb, # builtin-data
name = state.name) # idem
uri <- tempfile()
fromDataFrame(df, uri, col_index="abb", sparse=TRUE)
-fullarr <- tiledb_array(uri, as.data.frame=TRUE)[]
+fullarr <- tiledb_array(uri, return_as="data.frame")[]
expect_equal(dim(fullarr), c(50,3))
-subarr <- tiledb_array(uri, as.data.frame=TRUE,
+subarr <- tiledb_array(uri, return_as="data.frame",
query_condition=parse_query_condition(region == "Northeast"))[]
expect_equal(dim(subarr), c(9,3))
@@ -272,68 +272,68 @@ fromDataFrame(penguins, uri, sparse=TRUE)
## Basics
qc <- tiledb_query_condition_init("year", 2009, "INT32", "EQ")
-arrwithqc <- tiledb_array(uri, as.data.frame=TRUE, query_condition=qc)
+arrwithqc <- tiledb_array(uri, return_as="data.frame", query_condition=qc)
expect_equal(NROW(arrwithqc[]), 120L)
lhs <- tiledb_query_condition_init("year", 2008, "INT32", "GE")
rhs <- tiledb_query_condition_init("year", 2008, "INT32", "LE")
qc <- tiledb_query_condition_combine(lhs, rhs, "AND")
-arrwithqc <- tiledb_array(uri, as.data.frame=TRUE, query_condition=qc)
+arrwithqc <- tiledb_array(uri, return_as="data.frame", query_condition=qc)
expect_equal(NROW(arrwithqc[]), 114L) # basically a different way of writing EQ via '<= && >='
lhs <- tiledb_query_condition_init("year", 2008, "INT32", "GE")
rhs <- tiledb_query_condition_init("year", 2008, "INT32", "LE")
qc <- tiledb_query_condition_combine(lhs, rhs, "OR")
-arrwithqc <- tiledb_array(uri, as.data.frame=TRUE, query_condition=qc)
+arrwithqc <- tiledb_array(uri, return_as="data.frame", query_condition=qc)
expect_equal(NROW(arrwithqc[]), 344L) # the OR makes it unconstrained via '<= || >='
## simple OR
qc <- parse_query_condition(species == "Adelie" || species == "Chinstrap")
-arr <- tiledb_array(uri, as.data.frame=TRUE, query_condition=qc)
+arr <- tiledb_array(uri, return_as="data.frame", query_condition=qc)
## Note that in R '||' is used for length-1 comparison, and '|' along a vector so '|' here
expect_equal(NROW(arr[]), sum(with(penguins, species == "Adelie" | species == "Chinstrap")))
## three elements works too
qc <- parse_query_condition(species == "Adelie" || species == "Chinstrap" || year >= 2009)
-arr <- tiledb_array(uri, as.data.frame=TRUE, query_condition=qc)
+arr <- tiledb_array(uri, return_as="data.frame", query_condition=qc)
expect_equal(NROW(arr[]),
sum(with(penguins, species == "Adelie" | species == "Chinstrap" | year >= 2009)))
## three elements works too as does mixing AND and OR
qc <- parse_query_condition(species == "Adelie" || species == "Chinstrap" && year >= 2009)
-arr <- tiledb_array(uri, as.data.frame=TRUE, query_condition=qc)
+arr <- tiledb_array(uri, return_as="data.frame", query_condition=qc)
expect_equal(NROW(arr[]),
sum(with(penguins, species == "Adelie" | species == "Chinstrap" & year >= 2009)))
## empty sets are fine
qc <- parse_query_condition(year < 2008 || year > 2010)
-arr <- tiledb_array(uri, as.data.frame=TRUE, query_condition=qc)
+arr <- tiledb_array(uri, return_as="data.frame", query_condition=qc)
expect_equal(NROW(arr[]),
sum(with(penguins, year < 2008 | year > 2010)))
## Overlapping ranges
qc <- parse_query_condition(year < 2009 && year < 2010)
-arr <- tiledb_array(uri, as.data.frame=TRUE, query_condition=qc)
+arr <- tiledb_array(uri, return_as="data.frame", query_condition=qc)
expect_equal(NROW(arr[]),
sum(with(penguins, year < 2009)))
qc <- parse_query_condition(year <= 2009 && year >= 2009)
-arr <- tiledb_array(uri, as.data.frame=TRUE, query_condition=qc)
+arr <- tiledb_array(uri, return_as="data.frame", query_condition=qc)
expect_equal(NROW(arr[]),
sum(with(penguins, year == 2009)))
qc <- parse_query_condition(year < 2009 || year < 2010)
-arr <- tiledb_array(uri, as.data.frame=TRUE, query_condition=qc)
+arr <- tiledb_array(uri, return_as="data.frame", query_condition=qc)
expect_equal(NROW(arr[]),
sum(with(penguins, year < 2010)))
## Last two with single & or |
qc <- parse_query_condition(year <= 2009 & year >= 2009)
-arr <- tiledb_array(uri, as.data.frame=TRUE, query_condition=qc)
+arr <- tiledb_array(uri, return_as="data.frame", query_condition=qc)
expect_equal(NROW(arr[]), sum(with(penguins, year == 2009)))
qc <- parse_query_condition(year < 2009 | year < 2010)
-arr <- tiledb_array(uri, as.data.frame=TRUE, query_condition=qc)
+arr <- tiledb_array(uri, return_as="data.frame", query_condition=qc)
expect_equal(NROW(arr[]), sum(with(penguins, year < 2010)))
## query conditions over different types
diff --git a/inst/tinytest/test_tiledbarray.R b/inst/tinytest/test_tiledbarray.R
index e30e3fe771..b11175e681 100644
--- a/inst/tinytest/test_tiledbarray.R
+++ b/inst/tinytest/test_tiledbarray.R
@@ -30,7 +30,7 @@ tiledb_array_create(tmp, sch)
N <- 10
dat <- matrix(rnorm(N), N, 1)
-arr <- tiledb_array(tmp, is.sparse=TRUE, as.data.frame=TRUE)
+arr <- tiledb_array(tmp, is.sparse=TRUE, return_as="data.frame")
I <- as.Date("2020-01-01") + seq_len(N)
J <- sample(c("ABC","DEF","GHI"), N, replace=TRUE)
@@ -56,7 +56,7 @@ tiledb_array_create(tmp, sch)
N <- 10
dat <- matrix(rnorm(N), N, 1)
-arr <- tiledb_array(tmp, is.sparse=TRUE, as.data.frame=TRUE)
+arr <- tiledb_array(tmp, is.sparse=TRUE, return_as="data.frame")
I <- as.POSIXct("2020-01-01") + seq_len(N)*3600
J <- sample(c("ABC","DEF","GHI"), N, replace=TRUE)
@@ -86,7 +86,7 @@ dat <- readRDS(system.file("sampledata", "bankSample.rds", package="tiledb"))
dir.create(tmpuri <- tempfile())
fromDataFrame(dat[,-1], tmpuri)
-arr <- tiledb_array(tmpuri, as.data.frame=TRUE)
+arr <- tiledb_array(tmpuri, return_as="data.frame")
newdat <- arr[]
expect_equal(dat[,-1], newdat[,-1])
@@ -134,10 +134,10 @@ sch <- tiledb_array_schema(dom, attrs = c(tiledb_attr("age", type="INT32"),
sparse = TRUE)
tiledb_array_create(tmpuri, sch)
-arr <- tiledb_array(tmpuri, as.data.frame=TRUE)
+arr <- tiledb_array(tmpuri, return_as="data.frame")
arr[] <- dat
-newarr <- tiledb_array(tmpuri, as.data.frame=TRUE)
+newarr <- tiledb_array(tmpuri, return_as="data.frame")
newdat <- newarr[]
expect_equivalent(dat, newdat)
@@ -165,10 +165,10 @@ dat <- readRDS(system.file("sampledata", "bankSample.rds", package="tiledb"))
dir.create(tmpuri <- tempfile())
fromDataFrame(dat[,-1], tmpuri)
-arr1 <- tiledb_array(tmpuri, as.data.frame=TRUE)
+arr1 <- tiledb_array(tmpuri, return_as="data.frame")
dat1 <- arr1[]
-arr2 <- tiledb_array(tmpuri, as.data.frame=TRUE, extended=FALSE)
+arr2 <- tiledb_array(tmpuri, return_as="data.frame", extended=FALSE)
dat2 <- arr2[]
## dat2 should have fewer as not extended
expect_true(ncol(dat1) > ncol(dat2))
@@ -208,7 +208,7 @@ dat <- readRDS(system.file("sampledata", "bankSample.rds", package="tiledb"))
dir.create(tmpuri <- tempfile())
fromDataFrame(dat[,-1], tmpuri)
-arr <- tiledb_array(tmpuri, as.data.frame=TRUE, extended=FALSE)
+arr <- tiledb_array(tmpuri, return_as="data.frame", extended=FALSE)
expect_true(length(attrs(arr)) == 0)
sels <- c("age", "job", "education", "duration")
@@ -236,10 +236,10 @@ val <- tiledb_attr("val", type = "FLOAT64")
sch <- tiledb_array_schema(dom, val, sparse=TRUE)
rc <- tiledb_array_create(tmpuri, sch)
-x <- tiledb_array(uri = tmpuri, as.data.frame=TRUE)
+x <- tiledb_array(uri = tmpuri, return_as="data.frame")
x[] <- list(d1=1:10, d2=1:10, val=y)
-x <- tiledb_array(uri = tmpuri, as.data.frame=TRUE)
+x <- tiledb_array(uri = tmpuri, return_as="data.frame")
## intersection: 2 and 8 ... from 1 to 2 and 7 to 9, and 2 and 8
selected_ranges(x) <- list(matrix(c(1,2,7,9),2,byrow=TRUE),
@@ -292,7 +292,7 @@ val <- tiledb_attr("val", type = "FLOAT64")
sch <- tiledb_array_schema(dom, c(val), sparse=TRUE)
tiledb_array_create(tmp, sch)
-x <- tiledb_array(uri = tmp, as.data.frame=TRUE)
+x <- tiledb_array(uri = tmp, return_as="data.frame")
df <- data.frame(d1=integer(0), d2=integer(0), val=numeric(0))
## cannot currently write (corner-case) zero-length data.frame via <-
#x[] <- df
@@ -324,7 +324,7 @@ val <- tiledb_attr("val", type = "FLOAT64")
sch <- tiledb_array_schema(dom, val, sparse=TRUE)
tiledb_array_create(tmp, sch)
-x <- tiledb_array(uri = tmp, as.data.frame=TRUE)
+x <- tiledb_array(uri = tmp, return_as="data.frame")
set.seed(100)
df <- data.frame(d1=sample(100, 10, replace=TRUE),
@@ -363,7 +363,7 @@ J <- c(1L, 2L, 3L)
K <- c(1L, 2L, 4L)
L <- c(1L, 2L, 3L)
data <- c(1.0, 2.1, 3.3)
-A <- tiledb_array(uri = tmp, as.data.frame=TRUE)
+A <- tiledb_array(uri = tmp, return_as="data.frame")
A[] <- data.frame(d1=I, d2=J, d3=K, d4=L, a=data)
## constrain to one row
@@ -405,7 +405,7 @@ if (requireNamespace("bit64", quietly=TRUE)) {
data <- c(1L, 2L, 3L)
A[I,J] <- data
- A <- tiledb_array(uri = tmp, as.data.frame=TRUE)
+ A <- tiledb_array(uri = tmp, return_as="data.frame")
newdata <- A[as.integer64(1:2), as.integer64(2:4)]
expect_equal(newdata[,"a"], c(3L, 2L))
expect_equal(newdata[,"rows"], as.integer64(c(2, 2)))
@@ -439,7 +439,7 @@ if (requireNamespace("bit64", quietly=TRUE)) {
data <- c(1L, 2L, 3L)
A[I,J] <- data
- A <- tiledb_array(uri = tmp, as.data.frame=TRUE)
+ A <- tiledb_array(uri = tmp, return_as="data.frame")
newdata <- A[as.integer64(1:2), as.integer64(2:4)]
expect_equal(newdata[,"a"], c(3L, 2L))
expect_equal(newdata[,"rows"], c(2L, 2L))
@@ -471,7 +471,7 @@ if (requireNamespace("bit64", quietly=TRUE)) {
data <- c(1L, 2L, 3L)
A[I,J] <- data
- A <- tiledb_array(uri = tmp, as.data.frame=TRUE)
+ A <- tiledb_array(uri = tmp, return_as="data.frame")
newdata <- A[1:2, 2:4]
expect_equal(newdata[,"a"], c(3L, 2L))
expect_equal(newdata[,"rows"], c(2L, 2L))
@@ -500,7 +500,7 @@ if (requireNamespace("bit64", quietly=TRUE)) {
data <- c(1L, 2L, 3L)
A[I,J] <- data
- A <- tiledb_array(uri = tmp, as.data.frame=TRUE)
+ A <- tiledb_array(uri = tmp, return_as="data.frame")
newdata <- A[1:2, 2:4]
expect_equal(newdata[,"a"], c(3L, 2L))
expect_equal(newdata[,"rows"], c(2L, 2L))
@@ -529,7 +529,7 @@ if (requireNamespace("bit64", quietly=TRUE)) {
data <- c(1L, 2L, 3L)
A[I,J] <- data
- A <- tiledb_array(uri = tmp, as.data.frame=TRUE)
+ A <- tiledb_array(uri = tmp, return_as="data.frame")
newdata <- A[1:2, 2:4]
expect_equal(newdata[,"a"], c(3L, 2L))
expect_equal(newdata[,"rows"], c(2L, 2L))
@@ -558,7 +558,7 @@ if (requireNamespace("bit64", quietly=TRUE)) {
data <- c(1L, 2L, 3L)
A[I,J] <- data
- A <- tiledb_array(uri = tmp, as.data.frame=TRUE)
+ A <- tiledb_array(uri = tmp, return_as="data.frame")
newdata <- A[1:2, 2:4]
expect_equal(newdata[,"a"], c(3L, 2L))
expect_equal(newdata[,"rows"], c(2L, 2L))
@@ -587,7 +587,7 @@ if (requireNamespace("bit64", quietly=TRUE)) {
data <- c(1L, 2L, 3L)
A[I,J] <- data
- A <- tiledb_array(uri = tmp, as.data.frame=TRUE)
+ A <- tiledb_array(uri = tmp, return_as="data.frame")
newdata <- A[1:2, 2:4]
expect_equal(newdata[,"a"], c(3L, 2L))
expect_equal(newdata[,"rows"], c(2L, 2L))
@@ -618,7 +618,7 @@ if (requireNamespace("bit64", quietly=TRUE)) {
## or with indices
#A[rep(1:4,each=4), rep(1:4,4)] <- data
- A <- tiledb_array(uri = tmp, as.data.frame=TRUE, query_layout="ROW_MAJOR")
+ A <- tiledb_array(uri = tmp, return_as="data.frame", query_layout="ROW_MAJOR")
newdata <- A[1:2, 2:3]
expect_equal(newdata[,"a"], c(2L, 3L, 6L, 7L))
expect_equal(newdata[,"rows"], c(1L, 1L, 2L, 2L))
@@ -649,7 +649,7 @@ if (requireNamespace("bit64", quietly=TRUE)) {
## or with indices
#A[rep(1:4,each=4), rep(1:4,4)] <- data
- A <- tiledb_array(uri = tmp, as.data.frame=TRUE, query_layout="ROW_MAJOR")
+ A <- tiledb_array(uri = tmp, return_as="data.frame", query_layout="ROW_MAJOR")
newdata <- A[1:2, 2:3]
expect_equal(newdata[,"a"], c(2L, 3L, 6L, 7L))
expect_equal(newdata[,"rows"], c(1L, 1L, 2L, 2L))
@@ -680,7 +680,7 @@ if (requireNamespace("bit64", quietly=TRUE)) {
## or with indices
#A[rep(1:4,each=4), rep(1:4,4)] <- data
- A <- tiledb_array(uri = tmp, as.data.frame=TRUE, query_layout="ROW_MAJOR")
+ A <- tiledb_array(uri = tmp, return_as="data.frame", query_layout="ROW_MAJOR")
newdata <- A[1:2, 2:3]
expect_equal(newdata[,"a"], c(2L, 3L, 6L, 7L))
expect_equal(newdata[,"rows"], c(1L, 1L, 2L, 2L))
@@ -711,7 +711,7 @@ if (requireNamespace("bit64", quietly=TRUE)) {
## or with indices
#A[rep(1:4,each=4), rep(1:4,4)] <- data
- A <- tiledb_array(uri = tmp, as.data.frame=TRUE, query_layout="ROW_MAJOR")
+ A <- tiledb_array(uri = tmp, return_as="data.frame", query_layout="ROW_MAJOR")
newdata <- A[1:2, 2:3]
expect_equal(newdata[,"a"], c(2L, 3L, 6L, 7L))
expect_equal(newdata[,"rows"], c(1L, 1L, 2L, 2L))
@@ -742,7 +742,7 @@ if (requireNamespace("bit64", quietly=TRUE)) {
## or with indices
#A[rep(1:4,each=4), rep(1:4,4)] <- data
- A <- tiledb_array(uri = tmp, as.data.frame=TRUE, query_layout="ROW_MAJOR")
+ A <- tiledb_array(uri = tmp, return_as="data.frame", query_layout="ROW_MAJOR")
newdata <- A[1:2, 2:3]
expect_equal(newdata[,"a"], c(2L, 3L, 6L, 7L))
expect_equal(newdata[,"rows"], c(1L, 1L, 2L, 2L))
@@ -773,7 +773,7 @@ if (requireNamespace("bit64", quietly=TRUE)) {
## or with indices
#A[rep(1:4,each=4), rep(1:4,4)] <- data
- A <- tiledb_array(uri = tmp, as.data.frame=TRUE, query_layout="ROW_MAJOR")
+ A <- tiledb_array(uri = tmp, return_as="data.frame", query_layout="ROW_MAJOR")
newdata <- A[1:2, 2:3]
expect_equal(newdata[,"a"], c(2L, 3L, 6L, 7L))
expect_equal(newdata[,"rows"], c(1L, 1L, 2L, 2L))
@@ -804,7 +804,7 @@ if (requireNamespace("bit64", quietly=TRUE)) {
## or with indices
#A[as.integer64(rep(1:4,each=4)), as.integer64(rep(1:4,4))] <- data
- A <- tiledb_array(uri = tmp, as.data.frame=TRUE, query_layout="ROW_MAJOR")
+ A <- tiledb_array(uri = tmp, return_as="data.frame", query_layout="ROW_MAJOR")
newdata <- A[as.integer64(1:2), as.integer64(2:3)]
expect_equal(newdata[,"a"], c(2L, 3L, 6L, 7L))
expect_equal(newdata[,"rows"], as.integer64(c(1L, 1L, 2L, 2L)))
@@ -836,7 +836,7 @@ if (requireNamespace("bit64", quietly=TRUE)) {
## or with indices
#A[as.integer64(rep(1:4,each=4)), as.integer64(rep(1:4,4))] <- data
- A <- tiledb_array(uri = tmp, as.data.frame=TRUE, query_layout="ROW_MAJOR")
+ A <- tiledb_array(uri = tmp, return_as="data.frame", query_layout="ROW_MAJOR")
newdata <- A[as.integer64(1:2), as.integer64(2:3)]
expect_equal(newdata[,"a"], c(2L, 3L, 6L, 7L))
expect_equal(newdata[,"rows"], c(1L, 1L, 2L, 2L))
@@ -887,7 +887,7 @@ if (requireNamespace("bit64", quietly=TRUE)) {
## or with indices
#A[rep(1:4,each=4), rep(1:4,4)] <- data
- A <- tiledb_array(uri = tmp, as.data.frame=TRUE, query_layout="ROW_MAJOR")
+ A <- tiledb_array(uri = tmp, return_as="data.frame", query_layout="ROW_MAJOR")
newdata <- A[1:2, 2:3]
expect_equal(newdata[,"rows"], c(1L, 1L, 2L, 2L))
expect_equal(newdata[,"cols"], c(2L, 3L, 2L, 3L))
@@ -943,7 +943,7 @@ if (requireNamespace("bit64", quietly=TRUE)) {
## or with indices
A[rep(1:4,each=4), rep(1:4,4)] <- data
- A <- tiledb_array(uri = tmp, as.data.frame=TRUE, query_layout="ROW_MAJOR")
+ A <- tiledb_array(uri = tmp, return_as="data.frame", query_layout="ROW_MAJOR")
newdata <- A[1:2, 2:3]
expect_equal(newdata[,"rows"], c(1L, 1L, 2L, 2L))
expect_equal(newdata[,"cols"], c(2L, 3L, 2L, 3L))
@@ -1024,13 +1024,13 @@ A <- tiledb_array(uri = tmp, timestamp_end=now2)
A[I, J] <- data
if (tiledb_version(TRUE) >= "2.10.0") {
- A <- tiledb_array(uri = tmp, as.data.frame=TRUE, timestamp_end=now1 - onet)
+ A <- tiledb_array(uri = tmp, return_as="data.frame", timestamp_end=now1 - onet)
expect_equal(nrow(A[]), 0)
- A <- tiledb_array(uri = tmp, as.data.frame=TRUE, timestamp_end=now1 + onet)
+ A <- tiledb_array(uri = tmp, return_as="data.frame", timestamp_end=now1 + onet)
expect_equal(nrow(A[]), 3)
- A <- tiledb_array(uri = tmp, as.data.frame=TRUE, timestamp_end=now2 - onet)
+ A <- tiledb_array(uri = tmp, return_as="data.frame", timestamp_end=now2 - onet)
expect_equal(nrow(A[]), 3)
- A <- tiledb_array(uri = tmp, as.data.frame=TRUE, timestamp_end=now2 + onet)
+ A <- tiledb_array(uri = tmp, return_as="data.frame", timestamp_end=now2 + onet)
expect_equal(nrow(A[]), 6)
}
@@ -1049,12 +1049,12 @@ arr <- tiledb_array(tmp)
query_layout(arr) <- "COL_MAJOR" # needed if we want column order
arr[] <- mat # we can write directly
-arr2 <- tiledb_array(tmp, as.matrix=TRUE)
+arr2 <- tiledb_array(tmp, return_as="matrix")
mat2 <- arr2[]
expect_true(all.equal(mat, mat2, check.attributes=FALSE)) # check round-turn
## check no double selection
-expect_error(tiledb_array(tmp, as.data.frame=TRUE, as.matrix=TRUE))
+expect_error(tiledb_array(tmp, as.data.frame=TRUE, as.matrix=TRUE)) # TODO: remove when removing as.data.frame and as.matrix
## check matrix return and not data.frame return when row col select
expect_false(is.data.frame(suppressMessages(arr2[1:2,])))
expect_true(is.matrix(suppressMessages(arr2[1:2,])))
@@ -1070,18 +1070,18 @@ selected_ranges(arr2) <- list(cbind(c(1,4),c(2,5)), cbind(2,2))
expect_equivalent(arr2[], cbind(c(6,7,9,10)))
-arr3 <- tiledb_array(tmp, as.data.frame=TRUE)
+arr3 <- tiledb_array(tmp, return_as="data.frame")
df1 <- arr3[]
df1$vals2 <- df1$vals * 10
tmp2 <- tempfile()
fromDataFrame(df1, tmp2)
## check selecting matrix out of multiple cols
-arr4 <- tiledb_array(tmp2, attrs=c("rows", "cols", "vals2"), as.matrix=TRUE)
+arr4 <- tiledb_array(tmp2, attrs=c("rows", "cols", "vals2"), return_as="matrix")
expect_equivalent(arr4[], 10*mat)
-arr5 <- tiledb_array(tmp2, attrs=c("rows", "cols", "vals"), as.matrix=TRUE)
+arr5 <- tiledb_array(tmp2, attrs=c("rows", "cols", "vals"), return_as="matrix")
expect_equivalent(arr5[], mat)
-arr6 <- tiledb_array(tmp2, attrs=c("rows", "cols", "vals", "vals2"), as.matrix=TRUE)
+arr6 <- tiledb_array(tmp2, attrs=c("rows", "cols", "vals", "vals2"), return_as="matrix")
res <- arr6[]
expect_true(is.list(res))
expect_equal(length(res), 2L)
@@ -1104,12 +1104,12 @@ data <- list(a=array(seq(1:50), dim = c(10,5)),
c=array(c(letters[1:26], "brown", "fox", LETTERS[1:22]), dim = c(10,5)))
A <- tiledb_array(uri)
A[] <- data
-obj <- tiledb_array(uri, attrs="a", as.data.frame=TRUE)
+obj <- tiledb_array(uri, attrs="a", return_as="data.frame")
res <- obj[]
expect_equal(colnames(res), c("rows", "cols", "a")) # this was the PR issues
-obj <- tiledb_array(uri, attrs="a", as.matrix=TRUE) # this is the preferred accessor here
+obj <- tiledb_array(uri, attrs="a", return_as="matrix") # this is the preferred accessor here
expect_equivalent(obj[], data[["a"]])
-obj <- tiledb_array(uri, as.matrix=TRUE) # test all three matrices
+obj <- tiledb_array(uri, return_as="matrix") # test all three matrices
res <- obj[]
expect_equal(res[["a"]], data[["a"]])
expect_equal(res[["b"]], data[["b"]])
@@ -1127,7 +1127,7 @@ tiledb_array_create(uri, schema)
obj <- tiledb_array(uri, attrs="x", query_type="WRITE")
M <- matrix(runif(N*K), N, K)
obj[] <- M # prior to #246 this write had a write data type
-chk <- tiledb_array(uri, as.matrix=TRUE)
+chk <- tiledb_array(uri, return_as="matrix")
expect_equivalent(chk[], M)
@@ -1138,7 +1138,7 @@ uri <- tempfile()
fromDataFrame(penguins, uri, sparse = TRUE,
col_index = c("species", "year"),
tile_domain=list(year=c(1966L, 2021L)))
-arr <- tiledb_array(uri, as.data.frame=TRUE)
+arr <- tiledb_array(uri, return_as="data.frame")
## new data
newdf <- penguins[1:2,]
newdf$species <- c("Fred", "Ginger")
@@ -1146,7 +1146,7 @@ newdf$island <- c("Manhattan", "Staten Island")
newdf$year <- c(1966L, 1969L) # int is important
arr[] <- newdf
## check it
-chk <- tiledb_array(uri, as.data.frame=TRUE)
+chk <- tiledb_array(uri, return_as="data.frame")
res <- chk[]
expect_true(1966L %in% res$year)
expect_true(1969L %in% res$year)
@@ -1174,11 +1174,11 @@ expect_equal(res1, res2)
## FYI: 152 tests here
## check for strings_as_factors
-arr <- tiledb_array(uri, as.data.frame=TRUE)
+arr <- tiledb_array(uri, return_as="data.frame")
res <- arr[]
expect_equal(class(res[,"species"]), "character")
expect_equal(class(res[,"sex"]), "character")
-arr <- tiledb_array(uri, as.data.frame=TRUE, strings_as_factors=TRUE)
+arr <- tiledb_array(uri, return_as="data.frame", strings_as_factors=TRUE)
res <- arr[]
expect_equal(class(res[,"species"]), "factor")
expect_equal(class(res[,"sex"]), "factor")
@@ -1201,7 +1201,7 @@ arr[I, J] <- mat[I, J]
I <- 4:5
J <- 1:4
arr[I,J] <- mat[I, J]
-arr2 <- tiledb_array(uri, as.matrix=TRUE)
+arr2 <- tiledb_array(uri, return_as="matrix")
res <- arr2[]
expect_equal(dim(res), c(5,4))
expect_equal(sum(is.na(res[1:3,1:2])), 6) # arr[1:3,1:2] all NA
@@ -1222,9 +1222,9 @@ res <- tiledb_array_create(uri, schema)
data <- list(a=array(seq(1:100), dim = c(10,5, 2)),
b=array(as.double(seq(101,by=0.5,length=100)), dim = c(10,5,2)),
c=array(rep(c(letters[1:26], "brs", "asdf", LETTERS[1:22]), 2), dim = c(10,5,2)))
-A <- tiledb_array(uri = uri, as.data.frame = TRUE, query_layout = "ROW_MAJOR")
+A <- tiledb_array(uri = uri, return_as="data.frame", query_layout = "ROW_MAJOR")
A[] <- data
-chk <- tiledb_array(uri = uri, as.data.frame=TRUE)
+chk <- tiledb_array(uri = uri, return_as="data.frame")
res <- chk[]
expect_equal(dim(res), c(100,6))
expect_equal(colnames(res), c("rows", "cols", "time", "a", "b", "c"))
@@ -1414,7 +1414,7 @@ if (requireNamespace("bit64", quietly=TRUE)) {
library(palmerpenguins)
uri <- tempfile()
fromDataFrame(penguins, uri, sparse = TRUE, col_index = c("species", "year"))
-arr <- tiledb_array(uri, as.data.frame = TRUE, attrs = NA_character_)
+arr <- tiledb_array(uri, return_as="data.frame", attrs = NA_character_)
res <- arr[]
expect_equal(NCOL(res), 2)
expect_equal(colnames(res), c("species", "year"))
@@ -1435,14 +1435,14 @@ if (getRversion() < "4.3.0" && Sys.info()[["sysname"]] == "Windows") exit_file("
## check for incomplete status on unsuccessful query -- this no longer fails following some changes made
#set_allocation_size_preference(128) # too low for penguins to query fully
-#array <- tiledb_array(uri, as.data.frame=TRUE, query_layout="ROW_MAJOR")
+#array <- tiledb_array(uri, return_as="data.frame", query_layout="ROW_MAJOR")
#expect_warning(res <- array[]) # warning emitted
#expect_equal(attr(res, "query_status"), "INCOMPLETE") # and query status reported
if (Sys.getenv("IS_COVR", "no") == "no") {
## check for batched operation -- but not in coverage
set_allocation_size_preference(1024)
- arr <- tiledb_array(uri, as.data.frame=TRUE)
+ arr <- tiledb_array(uri, return_as="data.frame")
lst <- tiledb:::createBatched(arr)
res1 <- tiledb:::fetchBatched(arr, lst)
expect_false(completedBatched(lst))
diff --git a/inst/tinytest/test_tiledbarray_extra.R b/inst/tinytest/test_tiledbarray_extra.R
index c8380127bf..01c1121442 100644
--- a/inst/tinytest/test_tiledbarray_extra.R
+++ b/inst/tinytest/test_tiledbarray_extra.R
@@ -37,7 +37,7 @@ A <- tiledb_array(uri = tmp, encryption_key = encryption_key)
A[I, J] <- data
## read
-A <- tiledb_array(uri = tmp, as.data.frame=TRUE, encryption_key = encryption_key)
+A <- tiledb_array(uri = tmp, return_as="data.frame", encryption_key = encryption_key)
chk <- A[1:2, 2:4]
expect_equal(nrow(chk), 2)
expect_equal(chk[,"rows"], c(2L,2L))
diff --git a/inst/tinytest/test_timetravel.R b/inst/tinytest/test_timetravel.R
index 90a614b866..81e116d320 100644
--- a/inst/tinytest/test_timetravel.R
+++ b/inst/tinytest/test_timetravel.R
@@ -44,11 +44,11 @@ while (deltat < 30) {
## we need an 'epsilon' because when we record 'times' is not exactly where the array timestamp is
epst <- deltat/2
- res1 <- tiledb_array(uri, as.data.frame=TRUE)[] # no limits
- res2 <- tiledb_array(uri, as.data.frame=TRUE, timestamp_start=times[1]-epst, timestamp_end=times[2]+epst)[] # end after 2nd timestamp
- res3 <- tiledb_array(uri, as.data.frame=TRUE, timestamp_start=times[4]+epst)[] # start after fourth
- res4 <- tiledb_array(uri, as.data.frame=TRUE, timestamp_end=times[3]-epst)[] # end before 3rd
- res5 <- tiledb_array(uri, as.data.frame=TRUE, timestamp_start=times[2]-epst, timestamp_end=times[3]+epst)[]
+ res1 <- tiledb_array(uri, return_as="data.frame")[] # no limits
+ res2 <- tiledb_array(uri, return_as="data.frame", timestamp_start=times[1]-epst, timestamp_end=times[2]+epst)[] # end after 2nd timestamp
+ res3 <- tiledb_array(uri, return_as="data.frame", timestamp_start=times[4]+epst)[] # start after fourth
+ res4 <- tiledb_array(uri, return_as="data.frame", timestamp_end=times[3]-epst)[] # end before 3rd
+ res5 <- tiledb_array(uri, return_as="data.frame", timestamp_start=times[2]-epst, timestamp_end=times[3]+epst)[]
if (isTRUE(all.equal(NROW(res1), 40)) && # all four groups
isTRUE(all.equal(NROW(res2), 20)) && # expect group one + two (20 elements)
@@ -67,20 +67,20 @@ while (deltat < 30) {
if (!success) exit_file("Issue with time traveling")
-res1 <- tiledb_array(uri, as.data.frame=TRUE)[] # no limits
+res1 <- tiledb_array(uri, return_as="data.frame")[] # no limits
expect_equal(NROW(res1), 40) # all four observations
-res2 <- tiledb_array(uri, as.data.frame=TRUE, timestamp_start=times[1]-epst, timestamp_end=times[2]+epst)[] # end before 1st timestamp
+res2 <- tiledb_array(uri, return_as="data.frame", timestamp_start=times[1]-epst, timestamp_end=times[2]+epst)[] # end before 1st timestamp
expect_equal(NROW(res2), 20) # expect group one and two (20 elements)
-res3 <- tiledb_array(uri, as.data.frame=TRUE, timestamp_start=times[4]+epst)[] # start after fourth
+res3 <- tiledb_array(uri, return_as="data.frame", timestamp_start=times[4]+epst)[] # start after fourth
expect_equal(NROW(res3), 0) # expect zero data
-res4 <- tiledb_array(uri, as.data.frame=TRUE, timestamp_end=times[3]-epst)[] # end before 3rd
+res4 <- tiledb_array(uri, return_as="data.frame", timestamp_end=times[3]-epst)[] # end before 3rd
expect_equal(NROW(res4), 20) # expect 2 groups, 20 obs
expect_equal(max(res4$grp), 2) # with groups being 1 and 2
-res5 <- tiledb_array(uri, as.data.frame=TRUE, timestamp_start=times[2]-epst, timestamp_end=times[3]+epst)[]
+res5 <- tiledb_array(uri, return_as="data.frame", timestamp_start=times[2]-epst, timestamp_end=times[3]+epst)[]
expect_equal(NROW(res5), 20) # expects 2 groups, 2 and 3, with 20 obs
expect_equal(min(res5$grp), 2)
expect_equal(max(res5$grp), 3)
@@ -93,11 +93,11 @@ expect_equal(n, 4)
times <- do.call(c, lapply(seq_len(n), function(i) tiledb_fragment_info_get_timestamp_range(fi, i-1)[1]))
epstsml <- 0.005
-res1 <- tiledb_array(uri, as.data.frame=TRUE)[] # no limits
-res2 <- tiledb_array(uri, as.data.frame=TRUE, timestamp_end=times[1]+epstsml)[] # end after 1st timestamp
-res3 <- tiledb_array(uri, as.data.frame=TRUE, timestamp_start=times[4]+epstsml)[] # start after fourth
-res4 <- tiledb_array(uri, as.data.frame=TRUE, timestamp_end=times[3]-epstsml)[] # end before 3rd
-res5 <- tiledb_array(uri, as.data.frame=TRUE, timestamp_start=times[2]-epstsml, timestamp_end=times[3]+epstsml)[]
+res1 <- tiledb_array(uri, return_as="data.frame")[] # no limits
+res2 <- tiledb_array(uri, return_as="data.frame", timestamp_end=times[1]+epstsml)[] # end after 1st timestamp
+res3 <- tiledb_array(uri, return_as="data.frame", timestamp_start=times[4]+epstsml)[] # start after fourth
+res4 <- tiledb_array(uri, return_as="data.frame", timestamp_end=times[3]-epstsml)[] # end before 3rd
+res5 <- tiledb_array(uri, return_as="data.frame", timestamp_start=times[2]-epstsml, timestamp_end=times[3]+epstsml)[]
expect_equal(NROW(res1), 40)
expect_equal(NROW(res2), 10) # expect group one (10 elements)
expect_equal(NROW(res3), 0) # expect zero data
diff --git a/inst/tinytest/test_timetravel_extra.R b/inst/tinytest/test_timetravel_extra.R
index 1ecc6fe04e..85ed426fec 100644
--- a/inst/tinytest/test_timetravel_extra.R
+++ b/inst/tinytest/test_timetravel_extra.R
@@ -38,11 +38,11 @@ now2 <- Sys.time()
A <- tiledb_array(uri = tmp, timestamp_start=now2)
A[I, J] <- data
-A <- tiledb_array(uri = tmp, as.data.frame=TRUE, timestamp_end=now1 - epst)
+A <- tiledb_array(uri = tmp, return_as="data.frame", timestamp_end=now1 - epst)
expect_equal(nrow(A[]), 0)
-A <- tiledb_array(uri = tmp, as.data.frame=TRUE, timestamp_start=now1 + epst)
+A <- tiledb_array(uri = tmp, return_as="data.frame", timestamp_start=now1 + epst)
expect_equal(nrow(A[]), 3)
-A <- tiledb_array(uri = tmp, as.data.frame=TRUE, timestamp_start=now1 - epst, timestamp_end=now2 - epst)
+A <- tiledb_array(uri = tmp, return_as="data.frame", timestamp_start=now1 - epst, timestamp_end=now2 - epst)
expect_equal(nrow(A[]), 3)
-A <- tiledb_array(uri = tmp, as.data.frame=TRUE, timestamp_start=now1 - epst, timestamp_end=now2 + epst)
+A <- tiledb_array(uri = tmp, return_as="data.frame", timestamp_start=now1 - epst, timestamp_end=now2 + epst)
expect_true(nrow(A[]) >= 3)
diff --git a/vignettes/documentation.Rmd b/vignettes/documentation.Rmd
index 54f2275328..b15b11caf0 100644
--- a/vignettes/documentation.Rmd
+++ b/vignettes/documentation.Rmd
@@ -390,7 +390,7 @@ sch <- tiledb_array_schema(dom, c(val))
tiledb_array_create(tmp, sch)
dat <- matrix(as.integer(rnorm(25)*100), 5, 5)
-arr <- tiledb_dense(tmp, as.data.frame=FALSE)
+arr <- tiledb_array(tmp, return_as = "data.frame")
arr[] <- dat
@@ -818,7 +818,7 @@ arr@ptr <- tiledb:::libtiledb_array_reopen(arr@ptr)
``` r
# Open the array and read as a data.frame from it.
-A <- tiledb_array(uri = array_name, as.data.frame=TRUE,
+A <- tiledb_array(uri = array_name, return_as = "data.frame",
encryption_key = encryption_key)
# Slice rows 1 and 2, and cols 2, 3 and 4
diff --git a/vignettes/documentation.md b/vignettes/documentation.md
index 6c877d8720..36a9959c48 100644
--- a/vignettes/documentation.md
+++ b/vignettes/documentation.md
@@ -391,7 +391,7 @@ sch <- tiledb_array_schema(dom, c(val))
tiledb_array_create(tmp, sch)
dat <- matrix(as.integer(rnorm(25)*100), 5, 5)
-arr <- tiledb_dense(tmp, as.data.frame=FALSE)
+arr <- tiledb_array(tmp, return_as = "data.frame")
arr[] <- dat
@@ -830,7 +830,7 @@ arr@ptr <- tiledb:::libtiledb_array_reopen(arr@ptr)
```r
# Open the array and read as a data.frame from it.
-A <- tiledb_array(uri = array_name, as.data.frame=TRUE,
+A <- tiledb_array(uri = array_name, return_as = "data.frame",
encryption_key = encryption_key)
# Slice rows 1 and 2, and cols 2, 3 and 4
diff --git a/vignettes/introduction.Rmd b/vignettes/introduction.Rmd
index 373d33cf72..a1b08bc74b 100644
--- a/vignettes/introduction.Rmd
+++ b/vignettes/introduction.Rmd
@@ -77,7 +77,7 @@ the return to be a `data.frame` (instead of a simpler list) and for the
``` r
> A <- tiledb_array(uri = uri, attrs = "b",
-+ as.data.frame=TRUE, extended=FALSE))
++ return_as = "data.frame", extended=FALSE))
> A[1:2,2]
[1] 101.5 104.0
>
@@ -94,7 +94,7 @@ also works (but needs to account for `rows` and `cols`).
``` r
> A <- tiledb_array(uri = uri, attrs = c("a","b"),
-+ as.data.frame = TRUE)
++ return_as = "data.frame")
> A[1:2,2][["a"]]
[1] 2 7
> A[1:2,2]$a
@@ -128,7 +128,7 @@ array.
``` r
> A <- tiledb_dense(uri = uri, attrs = c("b","c"),
-+ as.data.frame = TRUE, extended=FALSE)
++ return_as = "data.frame", extended=FALSE)
> A[6:9,2:4]
b c
1 114.0 brown
@@ -160,7 +160,7 @@ change. We can also override, users can too.)
``` r
> A <- tiledb_array("/tmp/tiledb/ex_1/", attrs=c("b","c"),
-+ as.data.frame = TRUE, extended=TRUE)
++ return_as = "data.frame", extended=TRUE)
> sapply(A[6:9, 3:4], "class")
rows cols b c
"integer" "integer" "numeric" "character"
@@ -252,7 +252,7 @@ illustrates some basic operations on sparse arrays. It also shows date
and datetime types instead of just integer and double precision floats.
``` r
-> A <- tiledb_array(uri = uri, as.data.frame = TRUE)
+> A <- tiledb_array(uri = uri, return_as = "data.frame")
> A[1577858403:1577858408]
rows cols a b d e
1 1577858403 1 3 103 2020-01-11 2020-01-02 18:24:33.844
diff --git a/vignettes/introduction.md b/vignettes/introduction.md
index 90add7c2d5..faddfdece0 100644
--- a/vignettes/introduction.md
+++ b/vignettes/introduction.md
@@ -54,7 +54,7 @@ and for the (row and column, if present as here) indices to not be printed (via
```r
> A <- tiledb_array(uri = uri, attrs = "b",
-+ as.data.frame=TRUE, extended=FALSE))
++ return_as = "data.frame", extended=FALSE))
> A[1:2,2]
[1] 101.5 104.0
>
@@ -70,7 +70,7 @@ returned object works via `[[var]]` or `$var`. A numeric index also works (but
```r
> A <- tiledb_array(uri = uri, attrs = c("a","b"),
-+ as.data.frame = TRUE)
++ return_as = "data.frame")
> A[1:2,2][["a"]]
[1] 2 7
> A[1:2,2]$a
@@ -102,7 +102,7 @@ We can restrict the selection to a subset of attributes when opening the array.
```r
> A <- tiledb_dense(uri = uri, attrs = c("b","c"),
-+ as.data.frame = TRUE, extended=FALSE)
++ return_as = "data.frame", extended=FALSE)
> A[6:9,2:4]
b c
1 114.0 brown
@@ -120,7 +120,7 @@ We can restrict the selection to a subset of attributes when opening the array.
>
```
-This also illustrated the effect of setting `as.data.frame=TRUE` when opening the array.
+This also illustrated the effect of setting `return_as = "data.frame"` when opening the array.
This scheme can be generalized to variable cells, or cells where N>1, as we can expand each
(atomistic) value over corresponding row and column indices.
@@ -131,7 +131,7 @@ which is about to change. We can also override, users can too.)
```r
> A <- tiledb_array("/tmp/tiledb/ex_1/", attrs=c("b","c"),
-+ as.data.frame = TRUE, extended=TRUE)
++ return_as = "data.frame", extended=TRUE)
> sapply(A[6:9, 3:4], "class")
rows cols b c
"integer" "integer" "numeric" "character"
@@ -220,7 +220,7 @@ illustrates some basic operations on sparse arrays. It also shows date and datet
just integer and double precision floats.
```r
-> A <- tiledb_array(uri = uri, as.data.frame = TRUE)
+> A <- tiledb_array(uri = uri, return_as = "data.frame")
> A[1577858403:1577858408]
rows cols a b d e
1 1577858403 1 3 103 2020-01-11 2020-01-02 18:24:33.844