DevTut

# Vectors

# Filtering a Vector

Filter odd elements:

Prelude Data.Vector> Data.Vector.filter odd y
fromList [1,3,5,7,9,11] :: Data.Vector.Vector

# Mapping (map) and Reducing (fold) a Vector

Vectors can be map'd and fold'd,filter'd andzip`'d:

Prelude Data.Vector> Data.Vector.map (^2) y
fromList [0,1,4,9,16,25,36,49,64,81,100,121] :: Data.Vector.Vector

Reduce to a single value:

Prelude Data.Vector> Data.Vector.foldl (+) 0 y
66

# Working on Multiple Vectors

Zip two arrays into an array of pairs:

Prelude Data.Vector> Data.Vector.zip y y
fromList [(0,0),(1,1),(2,2),(3,3),(4,4),(5,5),(6,6),(7,7),(8,8),(9,9),(10,10),(11,11)] :: Data.Vector.Vector

# The Data.Vector Module

The Data.Vector (opens new window) module provided by the vector (opens new window) is a high performance library for working with arrays.

Once you've imported Data.Vector, it's easy to start using a Vector:

You can even have a multi-dimensional array:

# Remarks

It [Data.Vector] has an emphasis on very high performance through loop fusion, whilst retaining a rich interface. The main data types are boxed and unboxed arrays, and arrays may be immutable (pure), or mutable. Arrays may hold Storable elements, suitable for passing to and from C, and you can convert between the array types. Arrays are indexed by non-negative Int values.

The Haskell Wiki has these recommendations (opens new window):

In general:

    • End users should use Data.Vector.Unboxed for most cases
    • If you need to store more complex structures, use Data.Vector
    • If you need to pass to C, use Data.Vector.Storable
    For library writers;
    • Use the generic interface, to ensure your library is maximally flexible: Data.Vector.Generic

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