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### =========================================================================
### 'Compare' operations on SparseArray objects
### -------------------------------------------------------------------------
###
### 'Compare' operations: "==", "!=", "<=", ">=", "<", ">"
###
### See '?S4groupGeneric' for more information.
###
### All the atomic vector types (i.e. all vector types except "list").
COMPARE_INPUT_TYPES <- c("logical", "integer", "double", "complex",
"character", "raw")
check_Compare_input_type <- function(type, what)
{
if (!(type %in% COMPARE_INPUT_TYPES))
stop(wmsg("comparison operation not supported ",
"on ", what, " of type() \"", type , "\""))
}
flip_Compare_op <- function(op)
switch(op, `<=`=">=", `>=`="<=", `<`=">", `>`="<", op)
check_Compare_op_on_complex_vals <- function(op, x_type, y_type)
{
if ((x_type == "complex" || y_type == "complex")
&& op %in% c("<=", ">=", "<", ">"))
stop(wmsg("invalid comparison with complex values"))
}
must_homogenize_for_Compare <- function(x_type, y_type)
{
if (x_type == "raw" && y_type == "logical" ||
x_type == "logical" && y_type == "raw")
{
## This is a case where C-level Compare_Rbyte_int() function
## (defined in src/leaf_vector_Compare.c) won't compare the
## Rbyte values in one object with the int values in the other
## object in a meaningful way. That's because the nonzero Rbyte
## values can be anything between 1 and 255 while the nonzero
## int values are always 1.
## An easy workaround is to set the type() of both objects
## to "logical".
return(TRUE)
}
if (x_type == "character" || y_type == "character") {
## Temporary.
stop(wmsg("comparison operations are not implemented yet between ",
"SVT_SparseArray objects, or between an SVT_SparseArray ",
"object and a single value, when one or the other is of ",
"type() \"character\""))
return(TRUE)
}
FALSE
}
### Supports all 'Compare' ops: "==", "!=", "<=", ">=", "<", ">"
### Returns a "logical" SVT_SparseArray object.
.Compare_SVT1_v2 <- function(op, x, y)
{
stopifnot(isSingleString(op), is(x, "SVT_SparseArray"))
check_svt_version(x)
## Check types.
x_type <- type(x)
check_Compare_input_type(x_type, "SparseArray object")
if (!(type(y) %in% COMPARE_INPUT_TYPES))
stop(wmsg("comparison operations between SparseArray objects ",
"and ", class(y), " vectors are not supported"))
check_Compare_op_on_complex_vals(op, x_type, type(y))
## Check 'y'.
if (length(y) != 1L)
stop(wmsg("comparison operations are not supported between a ",
"SparseArray object and a vector of length != 1"))
if (is.na(y))
error_on_left_sparsity_not_preserved(op,
"y is NA or NaN")
if (type(y) %in% c("logical", "raw") && op %in% c("<=", "<"))
error_on_left_sparsity_not_preserved(op,
"y is a logical or raw value")
biggest_type <- type(c(vector(x_type), y))
if (biggest_type == "character" && op %in% c("<=", "<"))
error_on_left_sparsity_not_preserved(op,
"type(x) is \"character\" or y is a string")
type(y) <- biggest_type
zero <- vector_of_zeros(type(y), length=1L)
if (op == "==" && y == zero)
error_on_left_sparsity_not_preserved(op,
"y is 0 or FALSE or the empty string")
if (op == "!=" && y != zero)
error_on_left_sparsity_not_preserved(op,
"y is not 0, FALSE, or the empty string")
if (op == "<=" && y >= zero)
error_on_left_sparsity_not_preserved(op,
"y is >= 0")
if (op == ">=" && y <= zero)
error_on_left_sparsity_not_preserved(op,
"y is <= 0, or FALSE, or the empty string")
if (op == "<" && y > zero)
error_on_left_sparsity_not_preserved(op,
"y is > 0")
if (op == ">" && y < zero)
error_on_left_sparsity_not_preserved(op,
"y is < 0")
## Handle situations where we need to change the type() of 'x' to
## the type() of 'y'. This is possibly expensive so we do it only
## after all the above checks have passed.
if (must_homogenize_for_Compare(type(x), type(y)))
type(x) <- type(y)
## 'type(y)' is guaranteed to be the same as 'type(x)' or a "bigger" type,
## considering raw < logical < integer < double < complex < character.
new_SVT <- SparseArray.Call("C_Compare_SVT1_v2",
x@dim, x@type, x@SVT, FALSE, y, op)
BiocGenerics:::replaceSlots(x, type="logical", SVT=new_SVT, check=FALSE)
}
setMethod("Compare", c("SVT_SparseArray", "vector"),
function(e1, e2) .Compare_SVT1_v2(.Generic, e1, e2)
)
setMethod("Compare", c("vector", "SVT_SparseArray"),
function(e1, e2) .Compare_SVT1_v2(flip_Compare_op(.Generic), e2, e1)
)
### Supports: "!=", "<", ">"
### Returns a "logical" SVT_SparseArray object.
.Compare_SVT1_SVT2 <- function(op, x, y)
{
stopifnot(isSingleString(op),
is(x, "SVT_SparseArray"),
is(y, "SVT_SparseArray"))
check_svt_version(x)
check_svt_version(y)
## Check types.
check_Compare_input_type(type(x), "SparseArray object")
check_Compare_input_type(type(y), "SparseArray object")
check_Compare_op_on_complex_vals(op, type(x), type(y))
## Check 'op'.
if (!(op %in% c("!=", "<", ">"))) {
suggest <- switch(op, `==`="!=", `<=`="<", `>=`=">")
suggest <- if (is.null(suggest)) "" else
paste0(", but \"", suggest, "\" is")
stop(wmsg("\"", op, "\" is not supported between SparseArray ",
"objects (result wouldn't be sparse in general)", suggest))
}
## Check array conformability.
x_dim <- dim(x)
y_dim <- dim(y)
if (!identical(x_dim, y_dim))
stop(wmsg("non-conformable arrays"))
## Compute 'ans_dimnames'.
ans_dimnames <- S4Arrays:::get_first_non_NULL_dimnames(list(x, y))
## Homogenization is possibly expensive so we do it only after all
## the above checks have passed.
if (must_homogenize_for_Compare(type(x), type(y)))
type(x) <- type(y) <- type(c(vector(type(x)), vector(type(y))))
ans_SVT <- SparseArray.Call("C_Compare_SVT1_SVT2",
x_dim, x@type, x@SVT, FALSE,
y_dim, y@type, y@SVT, FALSE, op)
new_SVT_SparseArray(x_dim, ans_dimnames, "logical", ans_SVT, check=FALSE)
}
setMethod("Compare", c("SVT_SparseArray", "SVT_SparseArray"),
function(e1, e2) .Compare_SVT1_SVT2(.Generic, e1, e2)
)
setMethod("Compare", c("SVT_SparseArray", "array"),
function(e1, e2) .Compare_SVT1_SVT2(.Generic, e1, as(e2, "SVT_SparseArray"))
)
setMethod("Compare", c("array", "SVT_SparseArray"),
function(e1, e2) .Compare_SVT1_SVT2(.Generic, as(e1, "SVT_SparseArray"), e2)
)
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