covariance

问题 class Food{} class Meat extends Food{} class Animal{ void feed(Food f){} } class Lion extends Animal{ void feed(Meat m){} } void foo(Animal a){ Food f = new Food(); a.feed(f); } What will happen if we send to foo(new Lion()) ? I know that it will get error but I need the explanation please 回答1: Your Lion can eat Meat , but it can also eat any kind of food (like Spinach). If your Lion could not eat any kind of Food , then it could not be considered an implementation of Animal . This is

问题 I'm having the below error message at compile time: "Invalid variance: The type parameter 'T' must be invariantly valid on 'ConsoleApplication1.IRepository.GetAll()'. 'T' is covariant." and the below is my code: class Program { static void Main(string[] args) { IRepository<BaseClass> repository; repository = new RepositoryDerived1<Derived1>(); Console.ReadLine(); } } public abstract class BaseClass { } public class Derived1 : BaseClass { } public interface IRepository<out T> where T:

问题 I have a ADT as follows: sealed trait Tree[A] case object EmptyTree extends Tree[Nothing] case class Leaf[A](value: A) extends Tree[A] case class Node[A](op: Seq[A] => A, branches: Tree[A]*) extends Tree[A] When i try to build a function to randomly create Trees i get a problem with the EmptyTree, the type system does not let go through def create(acc: Tree[A], currentDepth: Int): Tree[A] = currentDepth match { case maxDepth => Leaf(terminalSet(r.nextInt(terminalSet.length))) case 0 => { val

问题 I'll start with several postulates to better explain the context of my question: Array Covariance Postulate 1.1 An array of a value type is not covariant. int[] cannot pass for object[] . Postulate 1.2 An array of a reference type is covariant with a valid IEnumerable . string[] can pass for IEnumerable<object> ). Postulate 1.3 An array of a reference type is covariant with a valid covariant array. string[] can pass for object[] . List Covariance Postulate 2.1 (same as 1.1) A list of a value

问题 I'm having some inheritance issues as I've got a group of inter-related abstract classes that need to all be overridden together to create a client implementation. Ideally I would like to do something like the following: abstract class Animal { public Leg GetLeg() {...} } abstract class Leg { } class Dog : Animal { public override DogLeg Leg() {...} } class DogLeg : Leg { } This would allow anyone using the Dog class to automatically get DogLegs and anyone using the Animal class to get Legs.

问题 I'm having some inheritance issues as I've got a group of inter-related abstract classes that need to all be overridden together to create a client implementation. Ideally I would like to do something like the following: abstract class Animal { public Leg GetLeg() {...} } abstract class Leg { } class Dog : Animal { public override DogLeg Leg() {...} } class DogLeg : Leg { } This would allow anyone using the Dog class to automatically get DogLegs and anyone using the Animal class to get Legs.

问题 I am having some trouble understanding why the following snippet does not give me an error public void SomeMethod<T>(T arg) where T : MyInterface { MyInterface e = arg; } But this one, which I would expect to work due to the generic type constraint private readonly IList<Action<MyInterface>> myActionList = new List<Action<MyInterface>>(); public IDisposable Subscribe<T>(Action<T> callback) where T: MyInterface { myActionList.Add(callback); // doesn't compile return null } Gives this error

问题 I am interested in calculating estimates and standard errors for linear combinations of coefficients after a linear regression in R. For example, suppose I have the regression and test: data(mtcars) library(multcomp) lm1 <- lm(mpg ~ cyl + hp, data = mtcars) summary(glht(lm1, linfct = 'cyl + hp = 0')) This will estimate the value of the sum of the coefficients on cyl and hp , and provide the standard error based on the covariance matrix produced by lm . But, suppose I want to cluster my

问题 I am trying to plot a bivariate gaussian distribution using matplotlib . I want to do this using the xy coordinates of two scatter points (Group A), (Group B). I want to adjust the distribution by adjusting the COV matrix to account for each Groups velocity and their distance to an additional xy coordinate used as a reference point. I've calculated the distance of each groups xy coordinate to that of the reference point. The distance is expressed as a radius , labelled [GrA_Rad] , [GrB_Rad] .

问题 I wrote a class implementing the command design pattern: class MyCommand[-T, +R](val name: String, val execute: T => R) , prepared two command and stored it in a MutableList: val commands = new mutable.MutableList[MyCommand[Nothing, Any]] commands += new MyCommand[String, String]("lower", s => s.toLowerCase()) commands += new MyCommand[Date, Long]("time", d => d.getTime) Then I have two data to be executed: val data = Array("StRiNG", new Date()) The problem for me is that I don't know how to