When creating the project
You should check "Include UI Tests" in the project creation dialog.
After creating the project
If you missed checking UI target while creating project, you could always add test target later.
Setps:
While project open go to File -> New -> Target
Fi...
When Accessibility enabled in Utilities
Select storyboard.
Expand the Utilities
Select Identity Inspector
Select your element on storyboard
Add new Accessibility Identifier (in example addButton)
When Accessibility disabled in Utilities
Select storyboard.
Expand the Utilities
Select...
It's a good idea to sanitize get_field() output, especially when using Advanced Custom Fields fields front end (with acf_form()). Otherwise your site is likely vulnerable to cross-site scripting attacks (XSS).
The following function lets you use
echo get_field_escaped('my_custom_field', $post_id, ...
Create
In order to perform a Create operation via REST, you must perform the following actions:
Create an HTTP request using the POST verb.
Use the service URL of the list to which you want to add an entity as the target for the POST.
Set the content type to application/json.
Serialize the JSON...
To compute a signature:
final PrivateKey privateKey = keyPair.getPrivate();
final byte[] data = "FOO BAR".getBytes();
final Signature signer = Signature.getInstance("SHA1withRSA");
signer.initSign(privateKey);
signer.update(data);
final byte[] signature = signer.sign();...
The Longest Increasing Subsequence problem is to find subsequence from the give input sequence in which subsequence's elements are sorted in lowest to highest order. All subsequence are not contiguous or unique.
Application of Longest Increasing Subsequence:
Algorithms like Longest Increasing Subs...
'Note: I use this method to extract non-html data in extracted GET telnet results
'This example effectively grabs every other vehicle that have start and finish
'characters, which in this case is "/".
'Resulting in an array like this:
'extractedData(0) = "/Jeep"
'extractedD...
In the build.sbt file (or where the project is defined if it is in another location), add the following setting:
scalacOptions += "-language:experimental.macros"
For instance, a project might be defined like this:
lazy val main = project.in(file(".")) // root project
.se...
This example covers some advanced features and use-cases for Exceptions.
Examining the callstack programmatically
Java SE 1.4
The primary use of exception stacktraces is to provide information about an application error and its context so that the programmer can diagnose and fix the problem. Som...
Due to way that the float type is represented in computer memory, results of operations using this type can be inaccurate - some values are stored as approximations. Good examples of this are monetary calculations.
If high precision is necessary, other types should be used. e.g. Java 7 provides Big...
typealias SuccessHandler = (NSURLSessionDataTask, AnyObject?) -> Void
This code block creates a type alias named SuccessHandler, just in the same way var string = "" creates a variable with the name string.
Now whenever you use SuccessHandler, for example:
func example(_ handler: S...
typealias Handler = () -> Void
typealias Handler = () -> ()
This block creates a type alias that works as a Void to Void function (takes in no parameters and returns nothing).
Here is a usage example:
var func: Handler?
func = {}
typealias Number = NSNumber
You can also use a type alias to give a type another name to make it easier to remember, or make your code more elegant.
typealias for Tuples
typealias PersonTuple = (name: String, age: Int, address: String)
And this can be used as:
func getPerson(for name: Strin...
A feature that has near zero variance is a good candidate for removal.
You can manually detect numerical variance below your own threshold:
data("GermanCredit")
variances<-apply(GermanCredit, 2, var)
variances[which(variances<=0.0025)]
Or, you can use the caret package to find...
If a feature is largely lacking data, it is a good candidate for removal:
library(VIM)
data(sleep)
colMeans(is.na(sleep))
BodyWgt BrainWgt NonD Dream Sleep Span Gest
0.00000000 0.00000000 0.22580645 0.19354839 0.06451613 0.06451613 0.06451613
Pred ...
Closely correlated features may add variance to your model, and removing one of a correlated pair might help reduce that. There are lots of ways to detect correlation. Here's one:
library(purrr) # in order to use keep()
# select correlatable vars
toCorrelate<-mtcars %>% keep(is.numeric)
...
