mteb/BrightProStackoverflowRetrieval huggingface dataset:
``` Print # PATHCONTAINS - 04/25/2024 **Applies to:** Calculated column Calculated table Measure Visual calculation Returns `TRUE` if the specified `item` exists within the specified `path`. Section titled: Syntax ## Syntax Copy ```lang-dax PATHCONTAINS(<path>, <item>) ``` Section titled: Parameters ### Parameters Expand table | Term | Definition | | --- | --- | | `path` | A string created as the result of evaluating a PATH function. | | `item` | A text expression to look for in the path result. | Section titled: Return value ## Return value A value of `TRUE` if `item` exists in `path`; otherwise `FALSE`. Section titled: Remarks ## Remarks - If `item` is an integer number it is converted to text and then the function is evaluated. If conversion fails then the function returns an error. - This function is not supported for use in DirectQuery mode when used in calculated columns or row-level security (RLS) rules. Section titled: Example ## Example The following example creates a calculated column that takes a manager ID and checks a set of employees. If the manager ID is among the list of managers returned by the PATH function, the PATHCONTAINS function returns true; otherwise it returns false. Copy ```lang-dax = PATHCONTAINS(PATH(Employee[EmployeeKey], Employee[ParentEmployeeKey]), "23") ``` * * * ## Feedback Was this page helpful? YesNo * * * ## Additional resources Events FabCon Vienna Sep 15, 2 AM - Sep 17, 11 AM The best Power BI community-led event. Sept 2025. Use code FABLEARN to save €200. Get registered Ask Learn is an AI assistant that can answer questions, clarify concepts, and define terms using trusted Microsoft documentation. ```
``` Defined in header <algorithm> template<class ForwardIt, class Generator > void generate( ForwardIt first, ForwardIt last, Generator g ); | (1) | (constexpr since C++20) | template<class ExecutionPolicy, class ForwardIt, class Generator > void generate( ExecutionPolicy&& policy, ForwardIt first, ForwardIt last, Generator g ); | (2) | (since C++17) | 1) Assigns each element in range `` first `, ` last `)` a value generated by the given function object g. 2) Same as (1), but executed according to policy. This overload participates in overload resolution only if all following conditions are satisfied: | | | | --- | --- | | [std::is_execution_policy_v < std::decay_t <ExecutionPolicy>> is true. | (until C++20) | | std::is_execution_policy_v < std::remove_cvref_t <ExecutionPolicy>> is true. | (since C++20) | | | | --- | | ## Contents - 1Parameters - 2Complexity - 3Exceptions - 4Possible implementation - 5Example - 6See also | ### [edit]Parameters | | | | | --- | --- | --- | | first, last | - | the pair of iterators defining the range of elements to generate | | policy | - | the execution policy to use | | g | - | generator function object that will be called. The signature of the function should be equivalent to the following: | | | | | --- | --- | --- | | Ret fun(); | | | | | | | The type Ret must be such that an object of type ForwardIt can be dereferenced and assigned a value of type Ret. ​ | | Type requirements | | - `ForwardIt` must meet the requirements of LegacyForwardIterator. | ### [edit]Complexity Exactly std::distance(first, last) invocations of g() and assignments. ### [edit]Exceptions The overload with a template parameter named `ExecutionPolicy` reports errors as follows: - If execution of a function invoked as part of the algorithm throws an exception and `ExecutionPolicy` is one of the standard policies, std::terminate is called. For any other `ExecutionPolicy`, the behavior is implementation-defined. - If the algorithm fails to allocate memory, std::bad_alloc is thrown. ### [edit]Possible implementation | | | --- | | ``` template<class ForwardIt, class Generator> constexpr // since C++20 void generate(ForwardIt first, ForwardIt last, Generator g) { for (; first != last; ++first) *first = g(); } ``` ```
# <base>: The Document Base URL element BaselineWidely available \* This feature is well established and works across many devices and browser versions. It’s been available across browsers since ⁨July 2015⁩. \\* Some parts of this feature may have varying levels of support. - Learn more - See full compatibility - Report feedback The **`<base>`** HTML element specifies the base URL to use for all _relative_ URLs in a document. There can be only one `<base>` element in a document. A document's used base URL can be accessed by scripts with `Node.baseURI`. If the document has no `<base>` elements, then `baseURI` defaults to `location.href`. ## Attributes This element's attributes include the global attributes. **Warning:** A `<base>` element must have an `href` attribute, a `target` attribute, or both. If at least one of these attributes are specified, the `<base>` element **must** come before other elements with attribute values that are URLs, such as a `<link>`'s `href` attribute. `href` The base URL to be used throughout the document for relative URLs. Absolute and relative URLs are allowed. `data:` and `javascript:` URLs are not allowed. `target` A **keyword** or **author-defined name** of the default browsing context to show the results of navigation from `<a>`, `<area>`, or `<form>` elements without explicit `target` attributes. The following keywords have special meanings: - `_self` (default): Show the result in the current browsing context. - `_blank`: Show the result in a new, unnamed browsing context. - `_parent`: Show the result in the parent browsing context of the current one, if the current page is inside a frame. If there is no parent, acts the same as `_self`. - `_top`: Show the result in the topmost browsing context (the browsing context that is an ancestor of the current one and has no parent). If there is no parent, acts the same as `_self`. ## Usage notes ### Multiple <base> elements If multiple `<base>` elements are used, only the first `href` and first `target` are obeyed — all others are ignored. ### In-page anchors Links pointing to a fragment in the document — e.g., `<a href="#some-id">` — are resolved with the `<base>`, triggering an HTTP request to the base URL with the fragment attached. For example, given `<base href="https://example.com/">` and this link: `<a href="#anchor">To anchor</a>`. The link points to `https://example.com/#anchor`.
Package:

     Microsoft.Web.WebView2 v1.0.2365.46 

Package:

     Microsoft.Web.WebView2 v1.0.2415-prerelease 

Package:

     Microsoft.Web.WebView2 v1.0.2420.47 

Package:

     Microsoft.Web.WebView2 v1.0.2470-prerelease 

Important

Some information relates to prerelease product that may be substantially
modified before itâs released. Microsoft makes no warranties, express or
implied, with respect to the information provided here.

Gets or sets the WebView allow external drop property.

    
    
    public bool AllowExternalDrop { get; set; }
    
    
    member this.AllowExternalDrop : bool with get, set
    
    
    Public Property AllowExternalDrop As Boolean

####  Property Value

[ Boolean ](/en-us/dotnet/api/system.boolean)

##  Examples

    
    
    webView.AllowExternalDrop = !webView.AllowExternalDrop;
    

##  Remarks

The AllowExternalDrop is to configure the capability that dropping files into
webview2 is allowed or permitted. The default value is true.

##  Applies to

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[ base  (version  3.6.2  ) ](/packages/base/versions/3.6.2)

#  search: Give Search Path for R Objects

##  Description

Gives a list of ` [ attach ](/link/attach?package=base&version=3.6.2) ` ed
_packages_ (see ` [ library ](/link/library?package=base&version=3.6.2) ` ),
and  R  objects, usually ` [ data.frame
](/link/data.frame?package=base&version=3.6.2) s ` .

##  Usage

    
    
    search()
    searchpaths()

##  Arguments

##  Value

A character vector, starting with ` " [ .GlobalEnv
](/link/.GlobalEnv?package=base&version=3.6.2) " ` , and ending with `
"package:base" ` which is  R  's  base  package required always.

` searchpaths ` gives a similar character vector, with the entries for
packages being the path to the package used to load the code.

##  References

Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) _The New S Language_ .
Wadsworth & Brooks/Cole. ( ` search ` .)

Chambers, J. M. (1998) _Programming with Data. A Guide to the S Language_ .
Springer. ( ` searchPaths ` .)

##  See Also

` [ .packages ](/link/.packages?package=base&version=3.6.2) ` to list just the
packages on search path.

` [ loadedNamespaces ](/link/loadedNamespaces?package=base&version=3.6.2) ` to
list loaded namespaces.

` [ attach ](/link/attach?package=base&version=3.6.2) ` and ` [ detach
](/link/detach?package=base&version=3.6.2) ` to change the search path, ` [
objects ](/link/objects?package=base&version=3.6.2) ` to find  R  objects in
there.

##  Examples

[ Run this code
](https://app.datacamp.com/workspace/preview?_tag=rdocs&rdocsPath=packages%2Fbase%2Fversions%2F3.6.2%2Ftopics%2Fsearch&utm_source=r-docs&utm_medium=docs&utm_term=search&utm_content=run_example_in_workspace)

    
    
    # NOT RUN {
    search()
    searchpaths()
    # }
    

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[ micropan  (version  1.0  ) ](/packages/micropan/versions/1.0)

#  hmmerCleanOverlap and nonoverlap: Removing overlapping hits from HMMER3
scans

##  Description

Removing hits to avoid overlapping HMMs on the same protein sequence.

##  Usage

    
    
    hmmerCleanOverlap(hmmer.table)
    nonoverlap(hmmer.table)

##  Arguments

hmmer.table

A ` data.frame ` with ` [ hmmerScan
](/link/hmmerScan?package=micropan&version=1.0) ` results, see ` [ readHmmer
](/link/readHmmer?package=micropan&version=1.0) ` .

##  Value

A ` data.frame ` which is a subset of the input, where some rows have been
deleted to avoid overlapping hits.

##  Details

When scanning sequences against a profile HMM database using ` [ hmmerScan
](/link/hmmerScan?package=micropan&version=1.0) ` , we often find that several
patterns (HMMs) match in the same region of the query sequence, i.e. we have
overlapping hits. The function ` [ hmmerCleanOverlap
](/link/hmmerCleanOverlap?package=micropan&version=1.0) ` will remove the
poorest overlapping hit in a recursive way such that all overlaps are
eliminated.

The function ` [ nonoverlap ](/link/nonoverlap?package=micropan&version=1.0) `
is used by ` [ hmmerCleanOverlap
](/link/hmmerCleanOverlap?package=micropan&version=1.0) ` , and not something
you call directly.

The input is a ` data.frame ` of the type produced by ` [ readHmmer
](/link/readHmmer?package=micropan&version=1.0) ` .

##  See Also

` [ hmmerScan ](/link/hmmerScan?package=micropan&version=1.0) ` , ` [
readHmmer ](/link/readHmmer?package=micropan&version=1.0) ` , ` [ dClust
](/link/dClust?package=micropan&version=1.0) ` .

##  Examples

[ Run this code
](https://www.datacamp.com/datalab/preview?_tag=rdocs&rdocsPath=packages%2Fmicropan%2Fversions%2F1.0%2Ftopics%2FhmmerCleanOverlap%20and%20nonoverlap&utm_source=r-docs&utm_medium=docs&utm_term=hmmerCleanOverlap
and nonoverlap&utm_content=run_example_in_datalab)

    
    
    # See the example in the Help-file for dClust.
    

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[ base  (version  3.6.2  ) ](/packages/base/versions/3.6.2)

#  LongVectors: Long Vectors

##  Description

Vectors of \\(2^{31}\\) or more elements were added in  R  3.0.0.

##  Arguments

##  Matrix algebra

It is now possible to use \\(m \times n\\) matrices with more than 2 billion
elements. Whether matrix algebra (including ` [ %*%
](/link/%25*%25?package=base&version=3.6.2) ` , ` [ crossprod
](/link/crossprod?package=base&version=3.6.2) ` , ` [ svd
](/link/svd?package=base&version=3.6.2) ` , ` [ qr
](/link/qr?package=base&version=3.6.2) ` , ` [ solve
](/link/solve?package=base&version=3.6.2) ` and ` [ eigen
](/link/eigen?package=base&version=3.6.2) ` ) will actually work is somewhat
implementation dependent, including the Fortran compiler used and if an
external BLAS or LAPACK is used.

An efficient parallel BLAS implementation will often be important to obtain
usable performance. For example on one particular platform ` chol ` on a
47,000 square matrix took about 5 hours with the internal BLAS, 21 minutes
using an optimized BLAS on one core, and 2 minutes using an optimized BLAS on
16 cores.

##  Details

Prior to  R  3.0.0, all vectors in  R  were restricted to at most \\(2^{31} -
1\\) elements and could be indexed by integer vectors.

Currently all [ atomic ](/link/atomic?package=base&version=3.6.2) (raw,
logical, integer, numeric, complex, character) vectors, [ list
](/link/list?package=base&version=3.6.2) s and [ expression
](/link/expression?package=base&version=3.6.2) s can be much longer on 64-bit
platforms: such vectors are referred to as ‘long vectors’ and have a slightly
different internal structure. In theory they can contain up to \\(2^{52}\\)
elements, but address space limits of current CPUs and OSes will be much
smaller. Such objects will have a [ length
](/link/length?package=base&version=3.6.2) that is expressed as a double, and
can be indexed by double vectors.

Arrays (including matrices) can be based on long vectors provided each of
their dimensions is at most \\(2^{31} - 1\\): thus there are no 1-dimensional
long arrays.

R  code typically only needs minor changes to work with long vectors, maybe
only checking that ` as.integer ` is not used unnecessarily for e.g.lengths.
However, compiled code typically needs quite extensive changes. Note that the
` [ .C ](/link/.C?package=base&version=3.6.2) ` and ` [ .Fortran
](/link/.Fortran?package=base&version=3.6.2) ` interfaces do not accept long
vectors, so ` [ .Call ](/link/.Call?package=base&version=3.6.2) ` (or similar)
has to be used.

Because of the storage requirements (a minimum of 64 bytes per character
string), character vectors are only going to be usable if they have a small
number of distinct elements, and even then factors will be more efficient (4
bytes per element rather than 8). So it is expected that most of the usage of
long vectors will be integer vectors (including factors) and numeric vectors.

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[ base  (version  3.6.2  ) ](/packages/base/versions/3.6.2)

#  outer: Outer Product of Arrays

##  Description

The outer product of the arrays ` X ` and ` Y ` is the array ` A ` with
dimension ` c(dim(X), dim(Y)) ` where element ` A[c(arrayindex.x,
arrayindex.y)] = FUN(X[arrayindex.x], Y[arrayindex.y], …) ` .

##  Usage

    
    
    outer(X, Y, FUN = "*", …)
    X %o% Y

##  Arguments

X, Y

First and second arguments for function ` FUN ` . Typically a vector or array.

FUN

a function to use on the outer products, found _via_ ` [ match.fun
](/link/match.fun?package=base&version=3.6.2) ` (except for the special case `
"*" ` ).

…

optional arguments to be passed to ` FUN ` .

##  Details

` X ` and ` Y ` must be suitable arguments for ` FUN ` . Each will be extended
by ` [ rep ](/link/rep?package=base&version=3.6.2) ` to length the products of
the lengths of ` X ` and ` Y ` before ` FUN ` is called.

` FUN ` is called with these two extended vectors as arguments (plus any
arguments in ` … ` ). It must be a vectorized function (or the name of one)
expecting at least two arguments and returning a value with the same length as
the first (and the second).

Where they exist, the [dim]names of ` X ` and ` Y ` will be copied to the
answer, and a dimension assigned which is the concatenation of the dimensions
of ` X ` and ` Y ` (or lengths if dimensions do not exist).

` FUN = "*" ` is handled as a special case _via_ ` as.vector(X) %*%
t(as.vector(Y)) ` , and is intended only for numeric vectors and arrays.

` %o% ` is binary operator providing a wrapper for ` outer(x, y, "*") ` .

##  References

Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) _The New S Language_ .
Wadsworth & Brooks/Cole.

##  See Also

` [ %*% ](/link/%25*%25?package=base&version=3.6.2) ` for usual ( _inner_ )
matrix vector multiplication; ` [ kronecker
](/link/kronecker?package=base&version=3.6.2) ` which is based on ` outer ` ;
` [ Vectorize ](/link/Vectorize?package=base&version=3.6.2) ` for vectorizing
a non-vectorized function.

##  Examples

[ Run this code
](https://app.datacamp.com/workspace/preview?_tag=rdocs&rdocsPath=packages%2Fbase%2Fversions%2F3.6.2%2Ftopics%2Fouter&utm_source=r-docs&utm_medium=docs&utm_term=outer&utm_content=run_example_in_workspace)

    
    
    # NOT RUN {
    x <- 1:9; names(x) <- x
    # Multiplication & Power Tables
    x %o% x
    y <- 2:8; names(y) <- paste(y,":", sep = "")
    outer(y, x, "^")
    
    outer(month.abb, 1999:2003, FUN = "paste")
    
    ## three way multiplication table:
    x %o% x %o% y[1:3]
    # }
    

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[ base  (version  3.6.2  ) ](/packages/base/versions/3.6.2)

#  levels: Levels Attributes

##  Description

` levels ` provides access to the levels attribute of a variable. The first
form returns the value of the levels of its argument and the second sets the
attribute.

##  Usage

    
    
    levels(x)
    levels(x) <- value

##  Arguments

x

an object, for example a factor.

value

A valid value for ` levels(x) ` . For the default method, ` NULL ` or a
character vector. For the ` factor ` method, a vector of character strings
with length at least the number of levels of ` x ` , or a named list
specifying how to rename the levels.

##  Details

Both the extractor and replacement forms are generic and new methods can be
written for them. The most important method for the replacement function is
that for ` [ factor ](/link/factor?package=base&version=3.6.2) ` s.

For the factor replacement method, a ` NA ` in ` value ` causes that level to
be removed from the levels and the elements formerly with that level to be
replaced by ` NA ` .

Note that for a factor, replacing the levels via ` levels(x) <- value ` is not
the same as (and is preferred to) ` attr(x, "levels") <- value ` .

The replacement function is [ primitive
](/link/primitive?package=base&version=3.6.2) .

##  References

Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) _The New S Language_ .
Wadsworth & Brooks/Cole.

##  See Also

` [ nlevels ](/link/nlevels?package=base&version=3.6.2) ` , ` [ relevel
](/link/relevel?package=base&version=3.6.2) ` , ` [ reorder
](/link/reorder?package=base&version=3.6.2) ` .

##  Examples

[ Run this code
](https://app.datacamp.com/workspace/preview?_tag=rdocs&rdocsPath=packages%2Fbase%2Fversions%2F3.6.2%2Ftopics%2Flevels&utm_source=r-docs&utm_medium=docs&utm_term=levels&utm_content=run_example_in_workspace)

    
    
    # NOT RUN {
    ## assign individual levels
    x <- gl(2, 4, 8)
    levels(x)[1] <- "low"
    levels(x)[2] <- "high"
    x
    
    ## or as a group
    y <- gl(2, 4, 8)
    levels(y) <- c("low", "high")
    y
    
    ## combine some levels
    z <- gl(3, 2, 12, labels = c("apple", "salad", "orange"))
    z
    levels(z) <- c("fruit", "veg", "fruit")
    z
    
    ## same, using a named list
    z <- gl(3, 2, 12, labels = c("apple", "salad", "orange"))
    z
    levels(z) <- list("fruit" = c("apple","orange"),
                      "veg"   = "salad")
    z
    
    ## we can add levels this way:
    f <- factor(c("a","b"))
    levels(f) <- c("c", "a", "b")
    f
    
    f <- factor(c("a","b"))
    levels(f) <- list(C = "C", A = "a", B = "b")
    f
    # }
    

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