Achieving compile safe indexing with Shapeless - scala

Problem: Let val v = List(0.5, 1.2, 0.3) model a realisation of some vector v = (v_1, v_2, v_3). The index j in v_j is implied by the element's position in the list. A lot of boilerplate and bugs have been due to tracking these indices, eg, when creating modified lists from the original. (How to make sure (in compile-time) that collection wasn't reordered? seems related.)
General question: What could be a good way to ensure correct indexing at compile time? (I assume that performance is not essential.)
My plan is to use subclasses of Nat in shapeless to model the indices as (explicit) types. The current solution is
import shapeless._
import Nat._
trait Elem[+A, +N<:Nat]{
val v: A
val ind: N}
case class DecElem[N<:Nat](v: BigDecimal, ind: N) extends Elem[BigDecimal, N]
object Decimals {
type One = DecElem[ _0]:: HNil
type Two = DecElem[ _0]:: DecElem[_1] :: HNil
//...
}
case class Scalar(v: Decimals.One)
case class VecTwo(v: Decimals.Two)
This, however, gets tedious in larger dimensions.
Another question is how to approach the generic case in trait Elem[+A, +N<:Nat]. As a start, I defined case class ElemVector[A, M<:Nat](vs: Sized[List[Elem[A, Nat]], M]), which loses the specific index type in Elem. What might be a strategy to circumvent this difficulty?
(Note: A better design may be to wrap List[A] by attaching explicit indices and deal with wrapper class. This, however, does not essentially change the question.)
UPDATE Here's is a trivial illustration of accidental swapping of vector elements.
import shapeless.Nat._
import shapeless.{Sized, nat}
type VectorTwo = Sized[IndexedSeq[Double], nat._2]
val f = (p: VectorTwo, x: Double) => {
val V = p(_0)
val K = p(_1)
V * x/(K + x)
}
val V : Double = 500
val K : Double = 1
val correct: VectorTwo = Sized(V, K)
val wrong: VectorTwo = Sized(K, V) //Compiles!
f(correct, 10) // = 454.54
f(wrong, 10) // = 0.02
I'd like to enlist the compiler to prevent such errors in vectors with many elements, and wonder if there could be an elegant solution with Shapeless.

Related

how to normalize a `scala.reflect.api.Types.Type`

How to implement the function normalize(type: Type): Type such that:
A =:= B if and only if normalize(A) == normalize(B) and normalize(A).hashCode == normalize(B).hashCode.
In other words, normalize must return equal results for all equivalent Type instances; and not equal nor equivalent results for all pair of non equivalent inputs.
There is a deprecated method called normalize in the TypeApi, but it does not the same.
In my particular case I only need to normalize types that represent a class or a trait (tpe.typeSymbol.isClass == true).
Edit 1: The fist comment suggests that such a function might not be possible to implement in general. But perhaps it is possible if we add another constraint:
B is obtained by navigating from A.
In the next example fooType would be A, and nextAppliedType would be B:
import scala.reflect.runtime.universe._
sealed trait Foo[V]
case class FooImpl[V](next: Foo[V]) extends Foo[V]
scala> val fooType = typeOf[Foo[Int]]
val fooType: reflect.runtime.universe.Type = Foo[Int]
scala> val nextType = fooType.typeSymbol.asClass.knownDirectSubclasses.iterator.next().asClass.primaryConstructor.typeSignature.paramLists(0)(0).typeSignature
val nextType: reflect.runtime.universe.Type = Foo[V]
scala> val nextAppliedType = appliedType(nextType.typeConstructor, fooType.typeArgs)
val nextAppliedType: reflect.runtime.universe.Type = Foo[Int]
scala> println(fooType =:= nextAppliedType)
true
scala> println(fooType == nextAppliedType)
false
Inspecting the Type instances with showRaw shows why they are not equal (at least when Foo and FooImpl are members of an object, in this example, the jsfacile.test.RecursionTest object):
scala> showRaw(fooType)
val res2: String = TypeRef(SingleType(SingleType(SingleType(ThisType(<root>), jsfacile), jsfacile.test), jsfacile.test.RecursionTest), jsfacile.test.RecursionTest.Foo, List(TypeRef(ThisType(scala), scala.Int, List())))
scala> showRaw(nextAppliedType)
val res3: String = TypeRef(ThisType(jsfacile.test.RecursionTest), jsfacile.test.RecursionTest.Foo, List(TypeRef(ThisType(scala), scala.Int, List())))
The reason I need this is difficult to explain. Let's try:
I am developing this JSON library which works fine except when there is a recursive type reference. For example:
sealed trait Foo[V]
case class FooImpl[V](next: Foo[V]) extends Foo[V]
That happens because the parser/appender it uses to parse and format are type classes that are materialized by an implicit macro. And when an implicit parameter is recursive the compiler complains with a divergence error.
I tried to solve that using by-name implicit parameter but it not only didn't solve the recursion problem, but also makes many non recursive algebraic data type to fail.
So, now I am trying to solve this problem by storing the resolved materializations in a map, which also would improve the compilation speed. And that map key is of type Type. So I need to normalize the Type instances, not only to be usable as key of a map, but also to equalize the values generated from them.
If I understood you well, any equivalence class would be fine. There is no preference.
I suspect you didn't. At least "any equivalence class would be fine", "There is no preference" do not sound good. I'll try to elaborate.
In math there is such construction as factorization. If you have a set A and equivalence relation ~ on this set (relation means that for any pair of elements from A we know whether they are related a1 ~ a2 or not, equivalence means symmetricity a1 ~ a2 => a2 ~ a1, reflexivity a ~ a, transitivity a1 ~ a2, a2 ~ a3 => a1 ~ a3) then you can consider the factor-set A/~ whose elements are all equivalence classes A/~ = { [a] | a ∈ A} (the equivalence class
[a] = {b ∈ A | b ~ a}
of an element a is a set consisting of all elements equivalent (i.e. ~-related) to a).
The axiom of choice says that there is a map (function) from A/~ to A i.e. we can select a representative in every equivalence class and in such way form a subset of A (this is true if we accept the axiom of choice, if we don't then it's not clear whether we get a set in such way). But even if we accept the axiom of choice and therefore there is a function A/~ -> A this doesn't mean we can construct such function.
Simple example. Let's consider the set of all real numbers R and the following equivalence relation: two real numbers are equivalent r1 ~ r2 if their difference is a rational number
r2 - r1 = p/q ∈ Q
(p, q≠0 are arbitrary integers). This is an equivalence relation. So it's known that there is a function selecting a single real number from any equivalence class but how to define this function explicitly for a specific input? For example what is the output of this function for the input being the equivalence class of 0 or 1 or π or e or √2 or log 2...?
Similarly, =:= is an equivalence relation on types, so it's known that there is a function normalize (maybe there are even many such functions) selecting a representative in every equivalence class but how to prefer a specific one (how to define or construct the output explicitly for any specific input)?
Regarding your struggle against implicit divergence. It's not necessary that you've selected the best possible approach. Sounds like you're doing some compiler work manually. How do other json libraries solve the issue? For example Circe? Besides by-name implicits => there is also shapeless.Lazy / shapeless.Strict (not equivalent to by-name implicits). If you have specific question about deriving type classes, overcoming implicit divergence maybe you should start a different question about that?
Regarding your approach with HashMap with Type keys. I'm still reminding that we're not supposed to rely on == for Types, correct comparison is =:=. So you should build your HashMap using =:= rather than ==. Search at SO for something like: hashmap custom equals.
Actually I guess your normalize sounds like you want some caching. You should have a type cache. Then if you asked to calculate normalize(typ) you should check whether in the cache there is already a t such that t =:= typ. If so you should return t, otherwise you should add typ to the cache and return typ.
This satisfies your requirement: A =:= B if and only if normalize(A) == normalize(B) (normalize(A).hashCode == normalize(B).hashCode should follow from normalize(A) == normalize(B)).
Regarding transformation of fooType into nextAppliedType try
def normalize(typ: Type): Type = typ match {
case TypeRef(pre, sym, args) =>
internal.typeRef(internal.thisType(pre.typeSymbol), sym, args)
}
Then normalize(fooType) == nextAppliedType should be true.

How to pick a random value from a collection in Scala

I need a method to pick uniformly a random value from a collection.
Here is my current impl.
implicit class TraversableOnceOps[A, Repr](val elements: TraversableOnce[A]) extends AnyVal {
def pickRandomly : A = elements.toSeq(Random.nextInt(elements.size))
}
But this code instantiate a new collection, so not ideal in term of memory.
Any way to improve ?
[update] make it work with Iterator
implicit class TraversableOnceOps[A, Repr](val elements: TraversableOnce[A]) extends AnyVal {
def pickRandomly : A = {
val seq = elements.toSeq
seq(Random.nextInt(seq.size))
}
}
It may seem at first glance that you can't do this without counting the elements first, but you can!
Iterate through the sequence f and take each element fi with probability 1/i:
def choose[A](it: Iterator[A], r: util.Random): A =
it.zip(Iterator.iterate(1)(_ + 1)).reduceLeft((x, y) =>
if (r.nextInt(y._2) == 0) y else x
)._1
A quick demonstration of uniformity:
scala> ((1 to 1000000)
| .map(_ => choose("abcdef".iterator, r))
| .groupBy(identity).values.map(_.length))
res45: Iterable[Int] = List(166971, 166126, 166987, 166257, 166698, 166961)
Here's a discussion of the math I wrote a while back, though I'm afraid it's a bit unnecessarily long-winded. It also generalizes to choosing any fixed number of elements instead of just one.
Simplest way is just to think of the problem as zipping the collection with an equal-sized list of random numbers, and then just extract the maximum element. You can do this without actually realizing the zipped sequence. This does require traversing the entire iterator, though
val maxElement = s.maxBy(_=>Random.nextInt)
Or, for the implicit version
implicit class TraversableOnceOps[A, Repr](val elements: TraversableOnce[A]) extends AnyVal {
def pickRandomly : A = elements.maxBy(_=>Random.nextInt)
}
It's possible to select an element uniformly at random from a collection, traversing it once without copying the collection.
The following algorithm will do the trick:
def choose[A](elements: TraversableOnce[A]): A = {
var x: A = null.asInstanceOf[A]
var i = 1
for (e <- elements) {
if (Random.nextDouble <= 1.0 / i) {
x = e
}
i += 1
}
x
}
The algorithm works by at each iteration makes a choice: take the new element with probability 1 / i, or keep the previous one.
To understand why the algorithm choose the element uniformly at random, consider this: Start by considering an element in the collection, for example the first one (in this example the collection only has three elements).
At iteration:
Chosen with probability: 1.
Chosen with probability:
(probability of keeping the element at previous iteration) * (keeping at current iteration)
probability => 1 * 1/2 = 1/2
Chosen with probability: 1/2 * 2/3=1/3 (in other words, uniformly)
If we take another element, for example the second one:
0 (not possible to choose the element at this iteration).
1/2.
1/2*2/3=1/3.
Finally for the third one:
0.
0.
1/3.
This shows that the algorithm selects an element uniformly at random. This can be proved formally using induction.
If the collection is large enough that you care about about instantiations, here is the constant memory solution (I assume, it contains ints' but that only matters for passing initial param to fold):
collection.fold((0, 0)) {
case ((0, _), x) => (1, x)
case ((n, x), _) if (random.nextDouble() > 1.0/n) => (n+1, x)
case ((n, _), x) => (n+1, x)
}._2
I am not sure if this requires a further explanation ... Basically, it does the same thing that #svenslaggare suggested above, but in a functional way, since this is tagged as a scala question.

How to define a function as generic across all numbers in scala?

I thought I needed to parameterise my function across all Ordering[_] types. But that doesn't work.
How can I make the following function work for all types that support the required mathematical operations, and how could I have found that out by myself?
/**
* Given a list of positive values and a candidate value, round the candidate value
* to the nearest value in the list of buckets.
*
* #param buckets
* #param candidate
* #return
*/
def bucketise(buckets: Seq[Int], candidate: Int): Int = {
// x <= y
buckets.foldLeft(buckets.head) { (x, y) =>
val midPoint = (x + y) / 2f
if (candidate < midPoint) x else y
}
}
I tried command clicking on the mathematical operators (/, +) in intellij, but just got a notice Sc synthetic function.
If you want to use just the scala standard library, look at Numeric[T]. In your case, since you want to do a non-integer division, you would have to use the Fractional[T] subclass of Numeric.
Here is how the code would look using scala standard library typeclasses. Note that Fractional extends from Ordered. This is convenient in this case, but it is also not mathematically generic. E.g. you can't define a Fractional[T] for Complex because it is not ordered.
def bucketiseScala[T: Fractional](buckets: Seq[T], candidate: T): T = {
// so we can use integral operators such as + and /
import Fractional.Implicits._
// so we can use ordering operators such as <. We do have a Ordering[T]
// typeclass instance because Fractional extends Ordered
import Ordering.Implicits._
// integral does not provide a simple way to create an integral from an
// integer, so this ugly hack
val two = (implicitly[Fractional[T]].one + implicitly[Fractional[T]].one)
buckets.foldLeft(buckets.head) { (x, y) =>
val midPoint = (x + y) / two
if (candidate < midPoint) x else y
}
}
However, for serious generic numerical computations I would suggest taking a look at spire. It provides a much more elaborate hierarchy of numerical typeclasses. Spire typeclasses are also specialized and therefore often as fast as working directly with primitives.
Here is how to use example would look using spire:
// imports all operator syntax as well as standard typeclass instances
import spire.implicits._
// we need to provide Order explicitly, since not all fields have an order.
// E.g. you can define a Field[Complex] even though complex numbers do not
// have an order.
def bucketiseSpire[T: Field: Order](buckets: Seq[T], candidate: T): T = {
// spire provides a way to get the typeclass instance using the type
// (standard practice in all libraries that use typeclasses extensively)
// the line below is equivalent to implicitly[Field[T]].fromInt(2)
// it also provides a simple way to convert from an integer
// operators are all enabled using the spire.implicits._ import
val two = Field[T].fromInt(2)
buckets.foldLeft(buckets.head) { (x, y) =>
val midPoint = (x + y) / two
if (candidate < midPoint) x else y
}
}
Spire even provides automatic conversion from integers to T if there exists a Field[T], so you could even write the example like this (almost identical to the non-generic version). However, I think the example above is easier to understand.
// this is how it would look when using all advanced features of spire
def bucketiseSpireShort[T: Field: Order](buckets: Seq[T], candidate: T): T = {
buckets.foldLeft(buckets.head) { (x, y) =>
val midPoint = (x + y) / 2
if (candidate < midPoint) x else y
}
}
Update: spire is very powerful and generic, but can also be somewhat confusing to a beginner. Especially when things don't work. Here is an excellent blog post explaining the basic approach and some of the issues.

Scala - Enforcing size of Vector at compile time

Is it possible to enforce the size of a Vector passed in to a method at compile time? I want to model an n-dimensional Euclidean space using a collection of points in the space that looks something like this (this is what I have now):
case class EuclideanPoint(coordinates: Vector[Double]) {
def distanceTo(desination: EuclieanPoint): Double = ???
}
If I have a coordinate that is created via EuclideanPoint(Vector(1, 0, 0)), it is a 3D Euclidean point. Given that, I want to make sure the destination point passed in a call to distanceTo is of the same dimension.
I know I can do this by using Tuple1 to Tuple22, but I want to represent many different geometric spaces and I would be writing 22 classes for each space if I did it with Tuples - is there a better way?
It is possible to do this in a number of ways that all look more or less like what Randall Schulz has described in a comment. The Shapeless library provides a particularly convenient implementation, which lets you get something pretty close to what you want like this:
import shapeless._
case class EuclideanPoint[N <: Nat](
coordinates: Sized[IndexedSeq[Double], N] { type A = Double }
) {
def distanceTo(destination: EuclideanPoint[N]): Double =
math.sqrt(
(this.coordinates zip destination.coordinates).map {
case (a, b) => (a - b) * (a - b)
}.sum
)
}
Now you can write the following:
val orig2d = EuclideanPoint(Sized(0.0, 0.0))
val unit2d = EuclideanPoint(Sized(1.0, 1.0))
val orig3d = EuclideanPoint(Sized(0.0, 0.0, 0.0))
val unit3d = EuclideanPoint(Sized(1.0, 1.0, 1.0))
And:
scala> orig2d distanceTo unit2d
res0: Double = 1.4142135623730951
scala> orig3d distanceTo unit3d
res1: Double = 1.7320508075688772
But not:
scala> orig2d distanceTo unit3d
<console>:15: error: type mismatch;
found : EuclideanPoint[shapeless.Nat._3]
required: EuclideanPoint[shapeless.Nat._2]
orig2d distanceTo unit3d
^
Sized comes with a number of nice features, including a handful of collections operations that carry along static guarantees about length. We can write the following for example:
val somewhere = EuclideanPoint(Sized(0.0) ++ Sized(1.0, 0.0))
And have an ordinary old point in three-dimensional space.
You could do something your self by doing a type level encoding of the Natural Numbers like: http://apocalisp.wordpress.com/2010/06/08/type-level-programming-in-scala/. Then just parametrizing your Vector by a Natural. Would not require the extra dependency, but would probably be more complicated then using Shapeless.

Write this Scala Matrix multiplication in Haskell [duplicate]

This question already has answers here:
Closed 11 years ago.
Possible Duplicate:
Can you overload + in haskell?
Can you implement a Matrix class and an * operator that will work on two matrices?:
scala> val x = Matrix(3, 1,2,3,4,5,6)
x: Matrix =
[1.0, 2.0, 3.0]
[4.0, 5.0, 6.0]
scala> x*x.transpose
res0: Matrix =
[14.0, 32.0]
[32.0, 77.0]
and just so people don't say that it's hard, here is the Scala implementation (courtesy of Jonathan Merritt):
class Matrix(els: List[List[Double]]) {
/** elements of the matrix, stored as a list of
its rows */
val elements: List[List[Double]] = els
def nRows: Int = elements.length
def nCols: Int = if (elements.isEmpty) 0
else elements.head.length
/** all rows of the matrix must have the same
number of columns */
require(elements.forall(_.length == nCols))
/* Add to each elem of matrix */
private def addRows(a: List[Double],
b: List[Double]):
List[Double] =
List.map2(a,b)(_+_)
private def subRows(a: List[Double],
b: List[Double]):List[Double] =
List.map2(a,b)(_-_)
def +(other: Matrix): Matrix = {
require((other.nRows == nRows) &&
(other.nCols == nCols))
new Matrix(
List.map2(elements, other.elements)
(addRows(_,_))
)
}
def -(other: Matrix): Matrix = {
require((other.nRows == nRows) &&
(other.nCols == nCols))
new Matrix(
List.map2(elements, other.elements)
(subRows(_,_))
)
}
def transpose(): Matrix = new Matrix(List.transpose(elements))
private def dotVectors(a: List[Double],
b: List[Double]): Double = {
val multipliedElements =
List.map2(a,b)(_*_)
(0.0 /: multipliedElements)(_+_)
}
def *(other: Matrix): Matrix = {
require(nCols == other.nRows)
val t = other.transpose()
new Matrix(
for (row <- elements) yield {
for (otherCol <- t.elements)
yield dotVectors(row, otherCol)
}
)
override def toString(): String = {
val rowStrings =
for (row <- elements)
yield row.mkString("[", ", ", "]")
rowStrings.mkString("", "\n", "\n")
}
}
/* Matrix constructor from a bunch of numbers */
object Matrix {
def apply(nCols: Int, els: Double*):Matrix = {
def splitRowsWorker(
inList: List[Double],
working: List[List[Double]]):
List[List[Double]] =
if (inList.isEmpty)
working
else {
val (a, b) = inList.splitAt(nCols)
splitRowsWorker(b, working + a)
}
def splitRows(inList: List[Double]) =
splitRowsWorker(inList, List[List[Double]]())
val rows: List[List[Double]] =
splitRows(els.toList)
new Matrix(rows)
}
}
EDIT I understood that strictly speaking the answer is No: overloading * is not possible without side-effects of defining also a + and others or special tricks. The numeric-prelude package describes it best:
In some cases, the hierarchy is not finely-grained enough: Operations
that are often defined independently are lumped together. For
instance, in a financial application one might want a type "Dollar",
or in a graphics application one might want a type "Vector". It is
reasonable to add two Vectors or Dollars, but not, in general,
reasonable to multiply them. But the programmer is currently forced to
define a method for '(*)' when she defines a method for '(+)'.
It'll be perfectly safe with a smart constructor and stored dimensions. Of course there are no natural implementations for the operations signum and fromIntegral (or maybe a diagonal matrix would be fine for the latter).
module Matrix (Matrix(),matrix,matrixTranspose) where
import Data.List (transpose)
data Matrix a = Matrix {matrixN :: Int,
matrixM :: Int,
matrixElems :: [[a]]}
deriving (Show, Eq)
matrix :: Int -> Int -> [[a]] -> Matrix a
matrix n m vals
| length vals /= m = error "Wrong number of rows"
| any (/=n) $ map length vals = error "Column length mismatch"
| otherwise = Matrix n m vals
matrixTranspose (Matrix m n vals) = matrix n m (transpose vals)
instance Num a => Num (Matrix a) where
(+) (Matrix m n vals) (Matrix m' n' vals')
| m/=m' = error "Row number mismatch"
| n/=n' = error "Column number mismatch"
| otherwise = Matrix m n (zipWith (zipWith (+)) vals vals')
abs (Matrix m n vals) = Matrix m n (map (map abs) vals)
negate (Matrix m n vals) = Matrix m n (map (map negate) vals)
(*) (Matrix m n vals) (Matrix n' p vals')
| n/=n' = error "Matrix dimension mismatch in multiplication"
| otherwise = let tvals' = transpose vals'
dot x y = sum $ zipWith (*) x y
result = map (\col -> map (dot col) tvals') vals
in Matrix m p result
Test it in ghci:
*Matrix> let a = matrix 3 2 [[1,0,2],[-1,3,1]]
*Matrix> let b = matrix 2 3 [[3,1],[2,1],[1,0]]
*Matrix> a*b
Matrix {matrixN = 3, matrixM = 3, matrixElems = [[5,1],[4,2]]}
Since my Num instance is generic, it even works for complex matrices out of the box:
Prelude Data.Complex Matrix> let c = matrix 2 2 [[0:+1,1:+0],[5:+2,4:+3]]
Prelude Data.Complex Matrix> let a = matrix 2 2 [[0:+1,1:+0],[5:+2,4:+3]]
Prelude Data.Complex Matrix> let b = matrix 2 3 [[3:+0,1],[2,1],[1,0]]
Prelude Data.Complex Matrix> a
Matrix {matrixN = 2, matrixM = 2, matrixElems = [[0.0 :+ 1.0,1.0 :+ 0.0],[5.0 :+ 2.0,4.0 :+ 3.0]]}
Prelude Data.Complex Matrix> b
Matrix {matrixN = 2, matrixM = 3, matrixElems = [[3.0 :+ 0.0,1.0 :+ 0.0],[2.0 :+ 0.0,1.0 :+ 0.0],[1.0 :+ 0.0,0.0 :+ 0.0]]}
Prelude Data.Complex Matrix> a*b
Matrix {matrixN = 2, matrixM = 3, matrixElems = [[2.0 :+ 3.0,1.0 :+ 1.0],[23.0 :+ 12.0,9.0 :+ 5.0]]}
EDIT: new material
Oh, you want to just override the (*) function without any Num stuff. That's possible to o but you'll have to remember that the Haskell standard library has reserved (*) for use in the Num class.
module Matrix where
import qualified Prelude as P
import Prelude hiding ((*))
import Data.List (transpose)
class Multiply a where
(*) :: a -> a -> a
data Matrix a = Matrix {matrixN :: Int,
matrixM :: Int,
matrixElems :: [[a]]}
deriving (Show, Eq)
matrix :: Int -> Int -> [[a]] -> Matrix a
matrix n m vals
| length vals /= m = error "Wrong number of rows"
| any (/=n) $ map length vals = error "Column length mismatch"
| otherwise = Matrix n m vals
matrixTranspose (Matrix m n vals) = matrix n m (transpose vals)
instance P.Num a => Multiply (Matrix a) where
(*) (Matrix m n vals) (Matrix n' p vals')
| n/=n' = error "Matrix dimension mismatch in multiplication"
| otherwise = let tvals' = transpose vals'
dot x y = sum $ zipWith (P.*) x y
result = map (\col -> map (dot col) tvals') vals
in Matrix m p result
a = matrix 3 2 [[1,2,3],[4,5,6]]
b = a * matrixTranspose
Testing in ghci:
*Matrix> b
Matrix {matrixN = 3, matrixM = 3, matrixElems = [[14,32],[32,77]]}
There. Now if a third module wants to use both the Matrix version of (*) and the Prelude version of (*) it'll have to of course import one or the other qualified. But that's just business as usual.
I could've done all of this without the Multiply type class but this implementation leaves our new shiny (*) open for extension in other modules.
Alright, there's a lot of confusion about what's happening here floating around, and it's not being helped by the fact that the Haskell term "class" does not line up with the OO term "class" in any meaningful way. So let's try to make a careful answer. This answer starts with Haskell's module system.
In Haskell, when you import a module Foo.Bar, it creates a new set of bindings. For each variable x exported by the module Foo.Bar, you get a new name Foo.Bar.x. In addition, you may:
import qualified or not. If you import qualified, nothing more happens. If you do not, an additional name without the module prefix is defined; in this case, just plain old x is defined.
change the qualification prefix or not. If you import as Alias, then the name Foo.Bar.x is not defined, but the name Alias.x is.
hide certain names. If you hide name foo, then neither the plain name foo nor any qualified name (like Foo.Bar.foo or Alias.foo) is defined.
Furthermore, names may be multiply defined. For example, if Foo.Bar and Baz.Quux both export the variable x, and I import both modules without qualification, then the name x refers to both Foo.Bar.x and Baz.Quux.x. If the name x is never used in the resulting module, this clash is ignored; otherwise, a compiler error asks you to provide more qualification.
Finally, if none of your imports mention the module Prelude, the following implicit import is added:
import Prelude
This imports the Prelude without qualification, with no additional prefix, and without hiding any names. So it defines "bare" names and names prefixed by Prelude., and nothing more.
Here ends the bare basics you need to understand about the module system. Now let's discuss the bare basics you need to understand about typeclasses.
A typeclass includes a class name, a list of type variables bound by that class, and a collection of variables with type signatures that refer to the bound variables. Here's an example:
class Foo a where
foo :: a -> a -> Int
The class name is Foo, the bound type variable is a, and there is only one variable in the collection, namely foo, with type signature a -> a -> Int. This class declares that some types have a binary operation, named foo, which computes an Int. Any type may later (even in another module) be declared to be an instance of this class: this involves defining the binary operation above, where the bound type variable a is substituted with the type you are creating an instance for. As an example, we might implement this for integers by the instance:
instance Foo Int where
foo a b = (a `mod` 76) * (b + 7)
Here ends the bare basics you need to understand about typeclasses. We may now answer your question. The only reason the question is tricky is because it falls smack dab on the intersection between two name management techniques: modules and typeclasses. Below I discuss what this means for your specific question.
The module Prelude defines a typeclass named Num, which includes in its collection of variables a variable named *. Therefore, we have several options for the name *:
If the type signature we desire happens to follow the pattern a -> a -> a, for some type a, then we may implement the Num typeclass. We therefore extend the Num class with a new instance; the name Prelude.* and any aliases for this name are extended to work for the new type. For matrices, this would look like, for example,
instance Num Matrix where
m * n = {- implementation goes here -}
We may define a different name than *.
m |*| n = {- implementation goes here -}
We may define the name *. Whether this name is defined as part of a new type class or not is immaterial. If we do nothing else, there will then be at least two definitions of *, namely, the one in the current module and the one implicitly imported from the Prelude. We have a variety of ways of dealing with this. The simplest is to explicitly import the Prelude, and ask for the name * not to be defined:
import Prelude hiding ((*))
You might alternately choose to leave the implicit import of Prelude, and use a qualified * everywhere you use it. Other solutions are also possible.
The main point I want you to take away from this is: the name * is in no way special. It is just a name defined by the Prelude, and all of the tools we have available for namespace control are available.
You can implement * as matrix multiplication by defining an instance of Num class for Matrix. But the code won't be type-safe: * (and other arithmetic operations) on matrices as you define them is not total, because of size mismatch or in case of '/' non-existence of inverse matrices.
As for 'the hierarchy is not defined precisely' - there is also Monoid type class, exactly for the cases when only one operation is defined.
There are too many things to be 'added', sometimes in rather exotic ways (think of permutation groups). Haskell designers designed to reserve arithmetical operations for different representations of numbers, and use other names for more exotic cases.