Create a synchronous function from a combinational function describing a mealy machine

macT
  :: Int        -- Current state
  -> (Int,Int)  -- Input
  -> (Int,Int)  -- (Updated state, output)
macT s (x,y) = (s',s)
  where
    s' = x * y   s

mac :: HiddenClockResetEnable dom  => Signal dom (Int, Int) -> Signal dom Int
mac = mealy macT 0

>>> simulate @System mac [(0,0),(1,1),(2,2),(3,3),(4,4)]
[0,0,1,5,14...
...

Synchronous sequential functions can be composed just like their combinational counterpart:

dualMac
  :: HiddenClockResetEnable dom
  => (Signal dom Int, Signal dom Int)
  -> (Signal dom Int, Signal dom Int)
  -> Signal dom Int
dualMac (a,b) (x,y) = s1   s2
  where
    s1 = mealy macT 0 (bundle (a,x))
    s2 = mealy macT 0 (bundle (b,y))

Create a synchronous function from a combinational function describing a mealy machine using the state monad. This can be particularly useful when combined with lenses or optics to replicate imperative algorithms.

data DelayState = DelayState
  { _history    :: Vec 4 Int
  , _untilValid :: Index 4
  }
  deriving (Generic, NFDataX)
makeLenses ''DelayState

initialDelayState = DelayState (repeat 0) maxBound

delayS :: Int -> State DelayState (Maybe Int)
delayS n = do
  history   %= (n  >>)
  remaining <- use untilValid
  if remaining > 0
  then do
     untilValid -= 1
     return Nothing
   else do
     out <- uses history last
     return (Just out)

delayTop :: HiddenClockResetEnable dom  => Signal dom Int -> Signal dom (Maybe Int)
delayTop = mealyS delayS initialDelayState

>>> L.take 7 $ simulate @System delayTop [1,2,3,4,5,6,7,8]
[Nothing,Nothing,Nothing,Just 1,Just 2,Just 3,Just 4]
...

A version of mealy that does automatic Bundleing

Given a function f of type:

f :: Int -> (Bool, Int) -> (Int, (Int, Bool))

When we want to make compositions of f in g using mealy, we have to write:

g a b c = (b1,b2,i2)
  where
    (i1,b1) = unbundle (mealy f 0 (bundle (a,b)))
    (i2,b2) = unbundle (mealy f 3 (bundle (c,i1)))

Using mealyB however we can write:

g a b c = (b1,b2,i2)
  where
    (i1,b1) = mealyB f 0 (a,b)
    (i2,b2) = mealyB f 3 (c,i1)

A version of mealyS that does automatic Bundleing, see mealyB for details.

Infix version of mealyB

Create a synchronous function from a combinational function describing a moore machine

macT
  :: Int        -- Current state
  -> (Int,Int)  -- Input
  -> Int        -- Updated state
macT s (x,y) = x * y   s

mac
  :: HiddenClockResetEnable dom
  => Signal dom (Int, Int)
  -> Signal dom Int
mac = moore mac id 0

>>> simulate @System mac [(0,0),(1,1),(2,2),(3,3),(4,4)]
[0,0,1,5,14,30,...
...

Synchronous sequential functions can be composed just like their combinational counterpart:

dualMac
  :: HiddenClockResetEnable dom
  => (Signal dom Int, Signal dom Int)
  -> (Signal dom Int, Signal dom Int)
  -> Signal dom Int
dualMac (a,b) (x,y) = s1   s2
  where
    s1 = moore macT id 0 (bundle (a,x))
    s2 = moore macT id 0 (bundle (b,y))

A version of moore that does automatic Bundleing

Given a functions t and o of types:

t :: Int -> (Bool, Int) -> Int
o :: Int -> (Int, Bool)

When we want to make compositions of t and o in g using moore, we have to write:

g a b c = (b1,b2,i2)
  where
    (i1,b1) = unbundle (moore t o 0 (bundle (a,b)))
    (i2,b2) = unbundle (moore t o 3 (bundle (c,i1)))

Using mooreB however we can write:

g a b c = (b1,b2,i2)
  where
    (i1,b1) = mooreB t o 0 (a,b)
    (i2,b2) = mooreB t o 3 (c,i1)

Create a register function for product-type like signals (e.g. '(Signal a, Signal b)')

rP :: HiddenClockResetEnable dom
   => (Signal dom Int, Signal dom Int)
   -> (Signal dom Int, Signal dom Int)
rP = registerB (8,8)

>>> simulateB @System rP [(1,1),(2,2),(3,3)] :: [(Int,Int)]
[(8,8),(1,1),(2,2),(3,3)...
...

An asynchronous/combinational ROM with space for n elements

See also:

• See Clash.Sized.Fixed and Clash.Prelude.BlockRam for ideas on how to use ROMs and RAMs.
• A large Vec for the content may be too inefficient, depending on how it is constructed. See asyncRomFile and asyncRomBlob for different approaches that scale well.

An asynchronous/combinational ROM with space for 2^n elements

See also:

• See Clash.Sized.Fixed and Clash.Prelude.BlockRam for ideas on how to use ROMs and RAMs.
• A large Vec for the content may be too inefficient, depending on how it is constructed. See asyncRomFilePow2 and asyncRomBlobPow2 for different approaches that scale well.

A ROM with a synchronous read port, with space for n elements

• NB: Read value is delayed by 1 cycle
• NB: Initial output value is undefined, reading it will throw an XException

See also:

• See Clash.Sized.Fixed and Clash.Prelude.BlockRam for ideas on how to use ROMs and RAMs.
• A large Vec for the content may be too inefficient, depending on how it is constructed. See romFile and romBlob for different approaches that scale well.

A ROM with a synchronous read port, with space for 2^n elements

• NB: Read value is delayed by 1 cycle
• NB: Initial output value is undefined, reading it will throw an XException

See also:

• See Clash.Sized.Fixed and Clash.Prelude.BlockRam for ideas on how to use ROMs and RAMs.
• A large Vec for the content may be too inefficient, depending on how it is constructed. See romFilePow2 and romBlobPow2 for different approaches that scale well.

An asynchronous/combinational ROM with space for n elements

See also:

• See Clash.Sized.Fixed and Clash.Prelude.BlockRam for ideas on how to use ROMs and RAMs.

An asynchronous/combinational ROM with space for 2^n elements

See also:

• See Clash.Sized.Fixed and Clash.Prelude.BlockRam for ideas on how to use ROMs and RAMs.

A ROM with a synchronous read port, with space for n elements

• NB: Read value is delayed by 1 cycle
• NB: Initial output value is undefined, reading it will throw an XException

See also:

• See Clash.Sized.Fixed and Clash.Explicit.BlockRam for ideas on how to use ROMs and RAMs.

A ROM with a synchronous read port, with space for 2^n elements

• NB: Read value is delayed by 1 cycle
• NB: Initial output value is undefined, reading it will throw an XException

See also:

• See Clash.Sized.Fixed and Clash.Explicit.BlockRam for ideas on how to use ROMs and RAMs.

Create a RAM with space for n elements

• NB: Initial content of the RAM is undefined, reading it will throw an XException

See also:

• See Clash.Prelude.BlockRam for more information on how to use a RAM.

Create a RAM with space for 2^n elements

• NB: Initial content of the RAM is undefined, reading it will throw an XException

See also:

• See Clash.Prelude.BlockRam for more information on how to use a RAM.

Create a block RAM with space for n elements

• NB: Read value is delayed by 1 cycle
• NB: Initial output value is undefined, reading it will throw an XException

See also:

• See Clash.Prelude.BlockRam for more information on how to use a Block RAM.
• Use the adapter readNew for obtaining write-before-read semantics like this: readNew (blockRam inits) rd wrM.
• A large Vec for the initial content may be too inefficient, depending on how it is constructed. See blockRamFile and blockRamBlob for different approaches that scale well.

Example

bram40
  :: HiddenClock dom
  => Signal dom (Unsigned 6)
  -> Signal dom (Maybe (Unsigned 6, Bit))
  -> Signal dom Bit
bram40 = blockRam (replicate d40 1)

Create a block RAM with space for 2^n elements

• NB: Read value is delayed by 1 cycle
• NB: Initial output value is undefined, reading it will throw an XException

See also:

• See Clash.Prelude.BlockRam for more information on how to use a block RAM.
• Use the adapter readNew for obtaining write-before-read semantics like this: readNew (blockRamPow2 inits) rd wrM.
• A large Vec for the initial content may be too inefficient, depending on how it is constructed. See blockRamFilePow2 and blockRamBlobPow2 for different approaches that scale well.

Example

bram32
  :: HiddenClock dom
  => Signal dom (Unsigned 5)
  -> Signal dom (Maybe (Unsigned 5, Bit))
  -> Signal dom Bit
bram32 = blockRamPow2 (replicate d32 1)

Create a block RAM with space for n elements

• NB: Read value is delayed by 1 cycle
• NB: Initial output value is undefined, reading it will throw an XException

See also:

• See Clash.Prelude.BlockRam for more information on how to use a block RAM.
• Use the adapter readNew for obtaining write-before-read semantics like this: readNew (blockRamBlob content) rd wrM.

Create a block RAM with space for 2^n elements

• NB: Read value is delayed by 1 cycle
• NB: Initial output value is undefined, reading it will throw an XException

See also:

• See Clash.Prelude.BlockRam for more information on how to use a block RAM.
• Use the adapter readNew for obtaining write-before-read semantics like this: readNew (blockRamBlobPow2 content) rd wrM.

Efficient storage of memory content

It holds n words of BitVector m.

Create a MemBlob binding from a list of values

Since this uses Template Haskell, nothing in the arguments given to createMemBlob can refer to something defined in the same module.

Example

createMemBlob "content" Nothing [15 :: Unsigned 8 .. 17]

ram clk en = blockRamBlob clk en content

>>> import qualified Prelude as P
>>> let es = [ Nothing, Just (7 :: Unsigned 8), Just 8 ]
>>> :{
createMemBlob "content0" (Just 0) es
createMemBlob "content1" (Just 1) es
x = 1
:}

>>> let pr = mapM_ (putStrLn . show)
>>> pr $ P.map pack es
0b0_...._....
0b1_0000_0111
0b1_0000_1000
>>> pr $ unpackMemBlob content0
0b0_0000_0000
0b1_0000_0111
0b1_0000_1000
>>> pr $ unpackMemBlob content1
0b0_1111_1111
0b1_0000_0111
0b1_0000_1000
>>> :{
createMemBlob "contentN" Nothing es
x = 1
:}

<interactive>:...: error:...
    packBVs: cannot convert don't care values. Please specify a mapping to a definite value.

Create a MemBlob from a list of values

Since this uses Template Haskell, nothing in the arguments given to memBlobTH can refer to something defined in the same module.

Example

ram clk en = blockRamBlob clk en $(memBlobTH Nothing [15 :: Unsigned 8 .. 17])

>>> import qualified Prelude as P
>>> let es = [ Nothing, Just (7 :: Unsigned 8), Just 8 ]
>>> content0 = $(memBlobTH (Just 0) es)
>>> content1 = $(memBlobTH (Just 1) es)
>>> let pr = mapM_ (putStrLn . show)
>>> pr $ P.map pack es
0b0_...._....
0b1_0000_0111
0b1_0000_1000
>>> pr $ unpackMemBlob content0
0b0_0000_0000
0b1_0000_0111
0b1_0000_1000
>>> pr $ unpackMemBlob content1
0b0_1111_1111
0b1_0000_0111
0b1_0000_1000
>>> $(memBlobTH Nothing es)

<interactive>:...: error:...
    • packBVs: cannot convert don't care values. Please specify a mapping to a definite value.
    • In the untyped splice: $(memBlobTH Nothing es)

Convert a MemBlob back to a list

NB: Not synthesizable

Create a read-after-write block RAM from a read-before-write one

>>> :t readNew (blockRam (0 :> 1 :> Nil))
readNew (blockRam (0 :> 1 :> Nil))
  :: ...
     ...
     ...
     ...
     ... =>
     Signal dom addr -> Signal dom (Maybe (addr, a)) -> Signal dom a

Produces vendor-agnostic HDL that will be inferred as a true dual-port block RAM

Any value that is being written on a particular port is also the value that will be read on that port, i.e. the same-port read/write behavior is: WriteFirst. For mixed-port read/write, when port A writes to the address port B reads from, the output of port B is undefined, and vice versa.

Port operation

Give a pulse when the Signal goes from minBound to maxBound

Give a pulse when the Signal goes from maxBound to minBound

Give a pulse every n clock cycles. This is a useful helper function when combined with functions like regEn or mux, in order to delay a register by a known amount.

To be precise: the given signal will be False for the next n-1 cycles, followed by a single True value:

>>> Prelude.last (sampleN @System 1025 (riseEvery d1024)) == True
True
>>> Prelude.or (sampleN @System 1024 (riseEvery d1024)) == False
True

For example, to update a counter once every 10 million cycles:

counter = regEn 0 (riseEvery (SNat :: SNat 10000000)) (counter   1)

Oscillate a Bool for a given number of cycles. This is a convenient function when combined with something like regEn, as it allows you to easily hold a register value for a given number of cycles. The input Bool determines what the initial value is.

To oscillate on an interval of 5 cycles:

>>> sampleN @System 11 (oscillate False d5)
[False,False,False,False,False,False,True,True,True,True,True]

To oscillate between True and False:

>>> sampleN @System 11 (oscillate False d1)
[False,False,True,False,True,False,True,False,True,False,True]

An alternative definition for the above could be:

>>> let osc' = register False (not <$> osc')
>>> sampleN @System 200 (oscillate False d1) == sampleN @System 200 osc'
True

Fixed size vectors.

• Lists with their length encoded in their type
• Vector elements have an ASCENDING subscript starting from 0 and ending at length - 1.

foldl, applied to a binary operator, a starting value (typically the left-identity of the operator), and a vector, reduces the vector using the binary operator, from left to right:

foldl f z (x1 :> x2 :> ... :> xn :> Nil) == (...((z `f` x1) `f` x2) `f`...) `f` xn
foldl f z Nil                            == z

>>> foldl (/) 1 (5 :> 4 :> 3 :> 2 :> Nil)
8.333333333333333e-3

"foldl f z xs" corresponds to the following circuit layout:

NB: "foldl f z xs" produces a linear structure, which has a depth, or delay, of O(length xs). Use fold if your binary operator f is associative, as "fold f xs" produces a structure with a depth of O(log_2(length xs)).

foldr, applied to a binary operator, a starting value (typically the right-identity of the operator), and a vector, reduces the vector using the binary operator, from right to left:

foldr f z (x1 :> ... :> xn1 :> xn :> Nil) == x1 `f` (... (xn1 `f` (xn `f` z))...)
foldr r z Nil                             == z

>>> foldr (/) 1 (5 :> 4 :> 3 :> 2 :> Nil)
1.875

"foldr f z xs" corresponds to the following circuit layout:

NB: "foldr f z xs" produces a linear structure, which has a depth, or delay, of O(length xs). Use fold if your binary operator f is associative, as "fold f xs" produces a structure with a depth of O(log_2(length xs)).

"map f xs" is the vector obtained by applying f to each element of xs, i.e.,

map f (x1 :> x2 :>  ... :> xn :> Nil) == (f x1 :> f x2 :> ... :> f xn :> Nil)

and corresponds to the following circuit layout:

Convert a BitVector to a Vec of Bits.

>>> let x = 6 :: BitVector 8
>>> x
0b0000_0110
>>> bv2v x
0 :> 0 :> 0 :> 0 :> 0 :> 1 :> 1 :> 0 :> Nil

To be used as the motive p for dfold, when the f in "dfold p f" is a variation on (:>), e.g.:

map' :: forall n a b . KnownNat n => (a -> b) -> Vec n a -> Vec n b
map' f = dfold (Proxy @(VCons b)) (_ x xs -> f x :> xs)

Create a vector of one element

>>> singleton 5
5 :> Nil

Extract the first element of a vector

>>> head (1:>2:>3:>Nil)
1

>>> head Nil

<interactive>:...
    • Couldn't match type ‘1’ with ‘0’
      Expected type: Vec (0   1) a
        Actual type: Vec 0 a
    • In the first argument of ‘head’, namely ‘Nil’
      In the expression: head Nil
      In an equation for ‘it’: it = head Nil

Extract the elements after the head of a vector

>>> tail (1:>2:>3:>Nil)
2 :> 3 :> Nil

>>> tail Nil

<interactive>:...
    • Couldn't match type ‘1’ with ‘0’
      Expected type: Vec (0   1) a
        Actual type: Vec 0 a
    • In the first argument of ‘tail’, namely ‘Nil’
      In the expression: tail Nil
      In an equation for ‘it’: it = tail Nil

Extract the last element of a vector

>>> last (1:>2:>3:>Nil)
3

>>> last Nil

<interactive>:...
    • Couldn't match type ‘1’ with ‘0’
      Expected type: Vec (0   1) a
        Actual type: Vec 0 a
    • In the first argument of ‘last’, namely ‘Nil’
      In the expression: last Nil
      In an equation for ‘it’: it = last Nil

Extract all the elements of a vector except the last element

>>> init (1:>2:>3:>Nil)
1 :> 2 :> Nil

>>> init Nil

<interactive>:...
    • Couldn't match type ‘1’ with ‘0’
      Expected type: Vec (0   1) a
        Actual type: Vec 0 a
    • In the first argument of ‘init’, namely ‘Nil’
      In the expression: init Nil
      In an equation for ‘it’: it = init Nil

Shift in elements to the head of a vector, bumping out elements at the tail. The result is a tuple containing:

• The new vector
• The shifted out elements

>>> shiftInAt0 (1 :> 2 :> 3 :> 4 :> Nil) ((-1) :> 0 :> Nil)
(-1 :> 0 :> 1 :> 2 :> Nil,3 :> 4 :> Nil)
>>> shiftInAt0 (1 :> Nil) ((-1) :> 0 :> Nil)
(-1 :> Nil,0 :> 1 :> Nil)

Shift in element to the tail of a vector, bumping out elements at the head. The result is a tuple containing:

• The new vector
• The shifted out elements

>>> shiftInAtN (1 :> 2 :> 3 :> 4 :> Nil) (5 :> 6 :> Nil)
(3 :> 4 :> 5 :> 6 :> Nil,1 :> 2 :> Nil)
>>> shiftInAtN (1 :> Nil) (2 :> 3 :> Nil)
(3 :> Nil,1 :> 2 :> Nil)

Add an element to the head of a vector, and extract all but the last element.

>>> 1  >> (3:>4:>5:>Nil)
1 :> 3 :> 4 :> Nil
>>> 1  >> Nil
Nil

Add an element to the tail of a vector, and extract all but the first element.

>>> (3:>4:>5:>Nil) <<  1
4 :> 5 :> 1 :> Nil
>>> Nil <<  1
Nil

Shift m elements out from the head of a vector, filling up the tail with Default values. The result is a tuple containing:

• The new vector
• The shifted out values

>>> shiftOutFrom0 d2 ((1 :> 2 :> 3 :> 4 :> 5 :> Nil) :: Vec 5 Integer)
(3 :> 4 :> 5 :> 0 :> 0 :> Nil,1 :> 2 :> Nil)

Shift m elements out from the tail of a vector, filling up the head with Default values. The result is a tuple containing:

• The new vector
• The shifted out values

>>> shiftOutFromN d2 ((1 :> 2 :> 3 :> 4 :> 5 :> Nil) :: Vec 5 Integer)
(0 :> 0 :> 1 :> 2 :> 3 :> Nil,4 :> 5 :> Nil)

Append two vectors.

>>> (1:>2:>3:>Nil)    (7:>8:>Nil)
1 :> 2 :> 3 :> 7 :> 8 :> Nil

Split a vector into two vectors at the given point.

>>> splitAt (SNat :: SNat 3) (1:>2:>3:>7:>8:>Nil)
(1 :> 2 :> 3 :> Nil,7 :> 8 :> Nil)
>>> splitAt d3 (1:>2:>3:>7:>8:>Nil)
(1 :> 2 :> 3 :> Nil,7 :> 8 :> Nil)

Split a vector into two vectors where the length of the two is determined by the context.

>>> splitAtI (1:>2:>3:>7:>8:>Nil) :: (Vec 2 Int, Vec 3 Int)
(1 :> 2 :> Nil,3 :> 7 :> 8 :> Nil)

Concatenate a vector of vectors.

>>> concat ((1:>2:>3:>Nil) :> (4:>5:>6:>Nil) :> (7:>8:>9:>Nil) :> (10:>11:>12:>Nil) :> Nil)
1 :> 2 :> 3 :> 4 :> 5 :> 6 :> 7 :> 8 :> 9 :> 10 :> 11 :> 12 :> Nil

Map a function over all the elements of a vector and concatentate the resulting vectors.

>>> concatMap (replicate d3) (1:>2:>3:>Nil)
1 :> 1 :> 1 :> 2 :> 2 :> 2 :> 3 :> 3 :> 3 :> Nil

Split a vector of (n * m) elements into a vector of "vectors of length m", where the length m is given.

>>> unconcat d4 (1:>2:>3:>4:>5:>6:>7:>8:>9:>10:>11:>12:>Nil)
(1 :> 2 :> 3 :> 4 :> Nil) :> (5 :> 6 :> 7 :> 8 :> Nil) :> (9 :> 10 :> 11 :> 12 :> Nil) :> Nil

Split a vector of (n * m) elements into a vector of "vectors of length m", where the length m is determined by the context.

>>> unconcatI (1:>2:>3:>4:>5:>6:>7:>8:>9:>10:>11:>12:>Nil) :: Vec 2 (Vec 6 Int)
(1 :> 2 :> 3 :> 4 :> 5 :> 6 :> Nil) :> (7 :> 8 :> 9 :> 10 :> 11 :> 12 :> Nil) :> Nil

Merge two vectors, alternating their elements, i.e.,

>>> merge (1 :> 2 :> 3 :> 4 :> Nil) (5 :> 6 :> 7 :> 8 :> Nil)
1 :> 5 :> 2 :> 6 :> 3 :> 7 :> 4 :> 8 :> Nil

The elements in a vector in reverse order.

>>> reverse (1:>2:>3:>4:>Nil)
4 :> 3 :> 2 :> 1 :> Nil

Apply a function of every element of a vector and its index.

>>> :t imap ( ) (2 :> 2 :> 2 :> 2 :> Nil)
imap ( ) (2 :> 2 :> 2 :> 2 :> Nil) :: Vec 4 (Index 4)
>>> imap ( ) (2 :> 2 :> 2 :> 2 :> Nil)
2 :> 3 :> *** Exception: X: Clash.Sized.Index: result 4 is out of bounds: [0..3]
...
>>> imap (\i a -> extend (bitCoerce i)   a) (2 :> 2 :> 2 :> 2 :> Nil) :: Vec 4 (Unsigned 8)
2 :> 3 :> 4 :> 5 :> Nil

"imap f xs" corresponds to the following circuit layout:

Zip two vectors with a functions that also takes the elements' indices.

>>> izipWith (\i a b -> i   a   b) (2 :> 2 :> Nil)  (3 :> 3:> Nil)
*** Exception: X: Clash.Sized.Index: result 3 is out of bounds: [0..1]
...
>>> izipWith (\i a b -> extend (bitCoerce i)   a   b) (2 :> 2 :> Nil) (3 :> 3 :> Nil) :: Vec 2 (Unsigned 8)
5 :> 6 :> Nil

"imap f xs" corresponds to the following circuit layout:

NB: izipWith is strict in its second argument, and lazy in its third. This matters when izipWith is used in a recursive setting. See lazyV for more information.

Right fold (function applied to each element and its index)

>>> let findLeftmost x xs = ifoldr (\i a b -> if a == x then Just i else b) Nothing xs
>>> findLeftmost 3 (1:>3:>2:>4:>3:>5:>6:>Nil)
Just 1
>>> findLeftmost 8 (1:>3:>2:>4:>3:>5:>6:>Nil)
Nothing

"ifoldr f z xs" corresponds to the following circuit layout:

Left fold (function applied to each element and its index)

>>> let findRightmost x xs = ifoldl (\a i b -> if b == x then Just i else a) Nothing xs
>>> findRightmost 3 (1:>3:>2:>4:>3:>5:>6:>Nil)
Just 4
>>> findRightmost 8 (1:>3:>2:>4:>3:>5:>6:>Nil)
Nothing

"ifoldl f z xs" corresponds to the following circuit layout:

Generate a vector of indices.

>>> indices d4
0 :> 1 :> 2 :> 3 :> Nil

Generate a vector of indices, where the length of the vector is determined by the context.

>>> indicesI :: Vec 4 (Index 4)
0 :> 1 :> 2 :> 3 :> Nil

"findIndex p xs" returns the index of the first element of xs satisfying the predicate p, or Nothing if there is no such element.

>>> findIndex (> 3) (1:>3:>2:>4:>3:>5:>6:>Nil)
Just 3
>>> findIndex (> 8) (1:>3:>2:>4:>3:>5:>6:>Nil)
Nothing

"elemIndex a xs" returns the index of the first element which is equal (by ==) to the query element a, or Nothing if there is no such element.

>>> elemIndex 3 (1:>3:>2:>4:>3:>5:>6:>Nil)
Just 1
>>> elemIndex 8 (1:>3:>2:>4:>3:>5:>6:>Nil)
Nothing

zipWith generalizes zip by zipping with the function given as the first argument, instead of a tupling function. For example, "zipWith ( )" applied to two vectors produces the vector of corresponding sums.

zipWith f (x1 :> x2 :> ... xn :> Nil) (y1 :> y2 :> ... :> yn :> Nil) == (f x1 y1 :> f x2 y2 :> ... :> f xn yn :> Nil)

"zipWith f xs ys" corresponds to the following circuit layout:

NB: zipWith is strict in its second argument, and lazy in its third. This matters when zipWith is used in a recursive setting. See lazyV for more information.

zipWith3 generalizes zip3 by zipping with the function given as the first argument, instead of a tupling function.

zipWith3 f (x1 :> x2 :> ... xn :> Nil) (y1 :> y2 :> ... :> yn :> Nil) (z1 :> z2 :> ... :> zn :> Nil) == (f x1 y1 z1 :> f x2 y2 z2 :> ... :> f xn yn zn :> Nil)

"zipWith3 f xs ys zs" corresponds to the following circuit layout:

NB: zipWith3 is strict in its second argument, and lazy in its third and fourth. This matters when zipWith3 is used in a recursive setting. See lazyV for more information.

foldr1 is a variant of foldr that has no starting value argument, and thus must be applied to non-empty vectors.

foldr1 f (x1 :> ... :> xn2 :> xn1 :> xn :> Nil) == x1 `f` (... (xn2 `f` (xn1 `f` xn))...)
foldr1 f (x1 :> Nil)                            == x1
foldr1 f Nil                                    == TYPE ERROR

>>> foldr1 (/) (5 :> 4 :> 3 :> 2 :> 1 :> Nil)
1.875

"foldr1 f xs" corresponds to the following circuit layout:

NB: "foldr1 f z xs" produces a linear structure, which has a depth, or delay, of O(length xs). Use fold if your binary operator f is associative, as "fold f xs" produces a structure with a depth of O(log_2(length xs)).

foldl1 is a variant of foldl that has no starting value argument, and thus must be applied to non-empty vectors.

foldl1 f (x1 :> x2 :> x3 :> ... :> xn :> Nil) == (...((x1 `f` x2) `f` x3) `f`...) `f` xn
foldl1 f (x1 :> Nil)                          == x1
foldl1 f Nil                                  == TYPE ERROR

>>> foldl1 (/) (1 :> 5 :> 4 :> 3 :> 2 :> Nil)
8.333333333333333e-3

"foldl1 f xs" corresponds to the following circuit layout:

NB: "foldl1 f z xs" produces a linear structure, which has a depth, or delay, of O(length xs). Use fold if your binary operator f is associative, as "fold f xs" produces a structure with a depth of O(log_2(length xs)).

fold is a variant of foldr1 and foldl1, but instead of reducing from right to left, or left to right, it reduces a vector using a tree-like structure. The depth, or delay, of the structure produced by "fold f xs", is hence O(log_2(length xs)), and not O(length xs).

NB: The binary operator "f" in "fold f xs" must be associative.

fold f (x1 :> x2 :> ... :> xn1 :> xn :> Nil) == ((x1 `f` x2) `f` ...) `f` (... `f` (xn1 `f` xn))
fold f (x1 :> Nil)                           == x1
fold f Nil                                   == TYPE ERROR

>>> fold ( ) (5 :> 4 :> 3 :> 2 :> 1 :> Nil)
15

"fold f xs" corresponds to the following circuit layout:

scanl is similar to foldl, but returns a vector of successive reduced values from the left:

scanl f z (x1 :> x2 :> ... :> Nil) == z :> (z `f` x1) :> ((z `f` x1) `f` x2) :> ... :> Nil

>>> scanl ( ) 0 (5 :> 4 :> 3 :> 2 :> Nil)
0 :> 5 :> 9 :> 12 :> 14 :> Nil

"scanl f z xs" corresponds to the following circuit layout:

• NB:

  last (scanl f z xs) == foldl f z xs

• For a different trade-off between circuit size and logic depth for associative operators, see Clash.Sized.RTree

scanl with no seed value

>>> scanl1 (-) (1 :> 2 :> 3 :> 4 :> Nil)
1 :> -1 :> -4 :> -8 :> Nil

scanr with no seed value

>>> scanr1 (-) (1 :> 2 :> 3 :> 4 :> Nil)
-2 :> 3 :> -1 :> 4 :> Nil

postscanl is a variant of scanl where the first result is dropped:

postscanl f z (x1 :> x2 :> ... :> Nil) == (z `f` x1) :> ((z `f` x1) `f` x2) :> ... :> Nil

>>> postscanl ( ) 0 (5 :> 4 :> 3 :> 2 :> Nil)
5 :> 9 :> 12 :> 14 :> Nil

"postscanl f z xs" corresponds to the following circuit layout:

scanr is similar to foldr, but returns a vector of successive reduced values from the right:

scanr f z (... :> xn1 :> xn :> Nil) == ... :> (xn1 `f` (xn `f` z)) :> (xn `f` z) :> z :> Nil

>>> scanr ( ) 0 (5 :> 4 :> 3 :> 2 :> Nil)
14 :> 9 :> 5 :> 2 :> 0 :> Nil

"scanr f z xs" corresponds to the following circuit layout:

• NB:

  head (scanr f z xs) == foldr f z xs

• For a different trade-off between circuit size and logic depth for associative operators, see Clash.Sized.RTree

postscanr is a variant of scanr that where the last result is dropped:

postscanr f z (... :> xn1 :> xn :> Nil) == ... :> (xn1 `f` (xn `f` z)) :> (xn `f` z) :> Nil

>>> postscanr ( ) 0 (5 :> 4 :> 3 :> 2 :> Nil)
14 :> 9 :> 5 :> 2 :> Nil

"postscanr f z xs" corresponds to the following circuit layout:

The mapAccumL function behaves like a combination of map and foldl; it applies a function to each element of a vector, passing an accumulating parameter from left to right, and returning a final value of this accumulator together with the new vector.

>>> mapAccumL (\acc x -> (acc   x,acc   1)) 0 (1 :> 2 :> 3 :> 4 :> Nil)
(10,1 :> 2 :> 4 :> 7 :> Nil)

"mapAccumL f acc xs" corresponds to the following circuit layout:

The mapAccumR function behaves like a combination of map and foldr; it applies a function to each element of a vector, passing an accumulating parameter from right to left, and returning a final value of this accumulator together with the new vector.

>>> mapAccumR (\acc x -> (acc   x,acc   1)) 0 (1 :> 2 :> 3 :> 4 :> Nil)
(10,10 :> 8 :> 5 :> 1 :> Nil)

"mapAccumR f acc xs" corresponds to the following circuit layout:

zip takes two vectors and returns a vector of corresponding pairs.

>>> zip (1:>2:>3:>4:>Nil) (4:>3:>2:>1:>Nil)
(1,4) :> (2,3) :> (3,2) :> (4,1) :> Nil

zip3 takes three vectors and returns a vector of corresponding triplets.

>>> zip3 (1:>2:>3:>4:>Nil) (4:>3:>2:>1:>Nil) (5:>6:>7:>8:>Nil)
(1,4,5) :> (2,3,6) :> (3,2,7) :> (4,1,8) :> Nil

zip4 takes four vectors and returns a list of quadruples, analogous to zip.

zip5 takes five vectors and returns a list of five-tuples, analogous to zip.

zip6 takes six vectors and returns a list of six-tuples, analogous to zip.

zip7 takes seven vectors and returns a list of seven-tuples, analogous to zip.

unzip transforms a vector of pairs into a vector of first components and a vector of second components.

>>> unzip ((1,4):>(2,3):>(3,2):>(4,1):>Nil)
(1 :> 2 :> 3 :> 4 :> Nil,4 :> 3 :> 2 :> 1 :> Nil)

unzip3 transforms a vector of triplets into a vector of first components, a vector of second components, and a vector of third components.

>>> unzip3 ((1,4,5):>(2,3,6):>(3,2,7):>(4,1,8):>Nil)
(1 :> 2 :> 3 :> 4 :> Nil,4 :> 3 :> 2 :> 1 :> Nil,5 :> 6 :> 7 :> 8 :> Nil)

unzip4 takes a vector of quadruples and returns four vectors, analogous to unzip.

unzip5 takes a vector of five-tuples and returns five vectors, analogous to unzip.

unzip6 takes a vector of six-tuples and returns six vectors, analogous to unzip.

unzip7 takes a vector of seven-tuples and returns seven vectors, analogous to unzip.

"xs !! n" returns the n'th element of xs.

NB: Vector elements have an ASCENDING subscript starting from 0 and ending at length - 1.

>>> (1:>2:>3:>4:>5:>Nil) !! 4
5
>>> (1:>2:>3:>4:>5:>Nil) !! (length (1:>2:>3:>4:>5:>Nil) - 1)
5
>>> (1:>2:>3:>4:>5:>Nil) !! 1
2
>>> (1:>2:>3:>4:>5:>Nil) !! 14
*** Exception: Clash.Sized.Vector.(!!): index 14 is larger than maximum index 4
...

The length of a Vector as an Int value.

>>> length (6 :> 7 :> 8 :> Nil)
3

"replace n a xs" returns the vector xs where the n'th element is replaced by a.

NB: Vector elements have an ASCENDING subscript starting from 0 and ending at length - 1.

>>> replace 3 7 (1:>2:>3:>4:>5:>Nil)
1 :> 2 :> 3 :> 7 :> 5 :> Nil
>>> replace 0 7 (1:>2:>3:>4:>5:>Nil)
7 :> 2 :> 3 :> 4 :> 5 :> Nil
>>> replace 9 7 (1:>2:>3:>4:>5:>Nil)
1 :> 2 :> 3 :> 4 :> 5 :> *** Exception: Clash.Sized.Vector.replace: index 9 is larger than maximum index 4
...

"take n xs" returns the n-length prefix of xs.

>>> take (SNat :: SNat 3) (1:>2:>3:>4:>5:>Nil)
1 :> 2 :> 3 :> Nil
>>> take d3               (1:>2:>3:>4:>5:>Nil)
1 :> 2 :> 3 :> Nil
>>> take d0               (1:>2:>Nil)
Nil

>>> take d4               (1:>2:>Nil)

<interactive>:...
    • Couldn't match type ‘4   n0’ with ‘2’
      Expected type: Vec (4   n0) a
        Actual type: Vec (1   1) a
      The type variable ‘n0’ is ambiguous
    • In the second argument of ‘take’, namely ‘(1 :> 2 :> Nil)’
      In the expression: take d4 (1 :> 2 :> Nil)
      In an equation for ‘it’: it = take d4 (1 :> 2 :> Nil)

"takeI xs" returns the prefix of xs as demanded by the context.

>>> takeI (1:>2:>3:>4:>5:>Nil) :: Vec 2 Int
1 :> 2 :> Nil

"drop n xs" returns the suffix of xs after the first n elements.

>>> drop (SNat :: SNat 3) (1:>2:>3:>4:>5:>Nil)
4 :> 5 :> Nil
>>> drop d3               (1:>2:>3:>4:>5:>Nil)
4 :> 5 :> Nil
>>> drop d0               (1:>2:>Nil)
1 :> 2 :> Nil

>>> drop d4               (1:>2:>Nil)

<interactive>:...: error:...
    • Couldn't match...type ‘4   n0...
      The type variable ‘n0’ is ambiguous
    • In the first argument of ‘print’, namely ‘it’
      In a stmt of an interactive GHCi command: print it

"dropI xs" returns the suffix of xs as demanded by the context.

>>> dropI (1:>2:>3:>4:>5:>Nil) :: Vec 2 Int
4 :> 5 :> Nil

"at n xs" returns n'th element of xs

NB: Vector elements have an ASCENDING subscript starting from 0 and ending at length - 1.

>>> at (SNat :: SNat 1) (1:>2:>3:>4:>5:>Nil)
2
>>> at d1               (1:>2:>3:>4:>5:>Nil)
2

"select f s n xs" selects n elements with step-size s and offset f from xs.

>>> select (SNat :: SNat 1) (SNat :: SNat 2) (SNat :: SNat 3) (1:>2:>3:>4:>5:>6:>7:>8:>Nil)
2 :> 4 :> 6 :> Nil
>>> select d1 d2 d3 (1:>2:>3:>4:>5:>6:>7:>8:>Nil)
2 :> 4 :> 6 :> Nil

"selectI f s xs" selects as many elements as demanded by the context with step-size s and offset f from xs.

>>> selectI d1 d2 (1:>2:>3:>4:>5:>6:>7:>8:>Nil) :: Vec 2 Int
2 :> 4 :> Nil

"replicate n a" returns a vector that has n copies of a.

>>> replicate (SNat :: SNat 3) 6
6 :> 6 :> 6 :> Nil
>>> replicate d3 6
6 :> 6 :> 6 :> Nil

"repeat a" creates a vector with as many copies of a as demanded by the context.

>>> repeat 6 :: Vec 5 Int
6 :> 6 :> 6 :> 6 :> 6 :> Nil

"iterate n f x" returns a vector starting with x followed by n repeated applications of f to x.

iterate (SNat :: SNat 4) f x == (x :> f x :> f (f x) :> f (f (f x)) :> Nil)
iterate d4 f x               == (x :> f x :> f (f x) :> f (f (f x)) :> Nil)

>>> iterate d4 ( 1) 1
1 :> 2 :> 3 :> 4 :> Nil

"iterate n f z" corresponds to the following circuit layout:

"iterateI f x" returns a vector starting with x followed by n repeated applications of f to x, where n is determined by the context.

iterateI f x :: Vec 3 a == (x :> f x :> f (f x) :> Nil)

>>> iterateI ( 1) 1 :: Vec 3 Int
1 :> 2 :> 3 :> Nil

"iterateI f z" corresponds to the following circuit layout:

"unfoldr n f s" builds a vector of length n from a seed value s, where every element a is created by successive calls of f on s. Unlike unfoldr from Data.List the generating function f cannot dictate the length of the resulting vector, it must be statically known.

a simple use of unfoldr:

>>> unfoldr d10 (\s -> (s,s-1)) 10
10 :> 9 :> 8 :> 7 :> 6 :> 5 :> 4 :> 3 :> 2 :> 1 :> Nil

"unfoldrI f s" builds a vector from a seed value s, where every element a is created by successive calls of f on s; the length of the vector is inferred from the context. Unlike unfoldr from Data.List the generating function f cannot dictate the length of the resulting vector, it must be statically known.

a simple use of unfoldrI:

>>> unfoldrI (\s -> (s,s-1)) 10 :: Vec 10 Int
10 :> 9 :> 8 :> 7 :> 6 :> 5 :> 4 :> 3 :> 2 :> 1 :> Nil

"generate n f x" returns a vector with n repeated applications of f to x.

generate (SNat :: SNat 4) f x == (f x :> f (f x) :> f (f (f x)) :> f (f (f (f x))) :> Nil)
generate d4 f x               == (f x :> f (f x) :> f (f (f x)) :> f (f (f (f x))) :> Nil)

>>> generate d4 ( 1) 1
2 :> 3 :> 4 :> 5 :> Nil

"generate n f z" corresponds to the following circuit layout:

"generateI f x" returns a vector with n repeated applications of f to x, where n is determined by the context.

generateI f x :: Vec 3 a == (f x :> f (f x) :> f (f (f x)) :> Nil)

>>> generateI ( 1) 1 :: Vec 3 Int
2 :> 3 :> 4 :> Nil

"generateI f z" corresponds to the following circuit layout:

Transpose a matrix: go from row-major to column-major

>>> let xss = (1:>2:>Nil):>(3:>4:>Nil):>(5:>6:>Nil):>Nil
>>> xss
(1 :> 2 :> Nil) :> (3 :> 4 :> Nil) :> (5 :> 6 :> Nil) :> Nil
>>> transpose xss
(1 :> 3 :> 5 :> Nil) :> (2 :> 4 :> 6 :> Nil) :> Nil

1-dimensional stencil computations

"stencil1d stX f xs", where xs has stX n elements, applies the stencil computation f on: n 1 overlapping (1D) windows of length stX, drawn from xs. The resulting vector has n 1 elements.

>>> let xs = (1:>2:>3:>4:>5:>6:>Nil)
>>> :t xs
xs :: Num a => Vec 6 a
>>> :t stencil1d d2 sum xs
stencil1d d2 sum xs :: Num b => Vec 5 b
>>> stencil1d d2 sum xs
3 :> 5 :> 7 :> 9 :> 11 :> Nil

2-dimensional stencil computations

"stencil2d stY stX f xss", where xss is a matrix of stY m rows of stX n elements, applies the stencil computation f on: (m 1) * (n 1) overlapping (2D) windows of stY rows of stX elements, drawn from xss. The result matrix has m 1 rows of n 1 elements.

>>> let xss = ((1:>2:>3:>4:>Nil):>(5:>6:>7:>8:>Nil):>(9:>10:>11:>12:>Nil):>(13:>14:>15:>16:>Nil):>Nil)
>>> :t xss
xss :: Num a => Vec 4 (Vec 4 a)

>>> :t stencil2d d2 d2 (sum . map sum) xss
stencil2d d2 d2 (sum . map sum) xss :: Num b => Vec 3 (Vec 3 b)

>>> stencil2d d2 d2 (sum . map sum) xss
(14 :> 18 :> 22 :> Nil) :> (30 :> 34 :> 38 :> Nil) :> (46 :> 50 :> 54 :> Nil) :> Nil

"windows1d stX xs", where the vector xs has stX n elements, returns a vector of n 1 overlapping (1D) windows of xs of length stX.

>>> let xs = (1:>2:>3:>4:>5:>6:>Nil)
>>> :t xs
xs :: Num a => Vec 6 a
>>> :t windows1d d2 xs
windows1d d2 xs :: Num a => Vec 5 (Vec 2 a)
>>> windows1d d2 xs
(1 :> 2 :> Nil) :> (2 :> 3 :> Nil) :> (3 :> 4 :> Nil) :> (4 :> 5 :> Nil) :> (5 :> 6 :> Nil) :> Nil

"windows2d stY stX xss", where matrix xss has stY m rows of stX n, returns a matrix of m 1 rows of n 1 elements. The elements of this new matrix are the overlapping (2D) windows of xss, where every window has stY rows of stX elements.

>>> let xss = ((1:>2:>3:>4:>Nil):>(5:>6:>7:>8:>Nil):>(9:>10:>11:>12:>Nil):>(13:>14:>15:>16:>Nil):>Nil)
>>> :t xss
xss :: Num a => Vec 4 (Vec 4 a)
>>> :t windows2d d2 d2 xss
windows2d d2 d2 xss :: Num a => Vec 3 (Vec 3 (Vec 2 (Vec 2 a)))
>>> windows2d d2 d2 xss
(((1 :> 2 :> Nil) :> (5 :> 6 :> Nil) :> Nil) :> ((2 :> 3 :> Nil) :> (6 :> 7 :> Nil) :> Nil) :> ((3 :> 4 :> Nil) :> (7 :> 8 :> Nil) :> Nil) :> Nil) :> (((5 :> 6 :> Nil) :> (9 :> 10 :> Nil) :> Nil) :> ((6 :> 7 :> Nil) :> (10 :> 11 :> Nil) :> Nil) :> ((7 :> 8 :> Nil) :> (11 :> 12 :> Nil) :> Nil) :> Nil) :> (((9 :> 10 :> Nil) :> (13 :> 14 :> Nil) :> Nil) :> ((10 :> 11 :> Nil) :> (14 :> 15 :> Nil) :> Nil) :> ((11 :> 12 :> Nil) :> (15 :> 16 :> Nil) :> Nil) :> Nil) :> Nil

Forward permutation specified by an index mapping, ix. The result vector is initialized by the given defaults, def, and an further values that are permuted into the result are added to the current value using the given combination function, f.

The combination function must be associative and commutative.

Backwards permutation specified by an index mapping, is, from the destination vector specifying which element of the source vector xs to read.

"backpermute xs is" is equivalent to "map (xs !!) is".

For example:

>>> let input = 1:>9:>6:>4:>4:>2:>0:>1:>2:>Nil
>>> let from  = 1:>3:>7:>2:>5:>3:>Nil
>>> backpermute input from
9 :> 4 :> 1 :> 6 :> 2 :> 4 :> Nil

Copy elements from the source vector, xs, to the destination vector according to an index mapping is. This is a forward permute operation where a to vector encodes an input to output index mapping. Output elements for indices that are not mapped assume the value in the default vector def.

For example:

>>> let defVec = 0:>0:>0:>0:>0:>0:>0:>0:>0:>Nil
>>> let to = 1:>3:>7:>2:>5:>8:>Nil
>>> let input = 1:>9:>6:>4:>4:>2:>5:>Nil
>>> scatter defVec to input
0 :> 1 :> 4 :> 9 :> 0 :> 4 :> 0 :> 6 :> 2 :> Nil

NB: If the same index appears in the index mapping more than once, the latest mapping is chosen.

Backwards permutation specified by an index mapping, is, from the destination vector specifying which element of the source vector xs to read.

"gather xs is" is equivalent to "map (xs !!) is".

For example:

>>> let input = 1:>9:>6:>4:>4:>2:>0:>1:>2:>Nil
>>> let from  = 1:>3:>7:>2:>5:>3:>Nil
>>> gather input from
9 :> 4 :> 1 :> 6 :> 2 :> 4 :> Nil

"interleave d xs" creates a vector:

<x_0,x_d,x_(2d),...,x_1,x_(d 1),x_(2d 1),...,x_(d-1),x_(2d-1),x_(3d-1)>

>>> let xs = 1 :> 2 :> 3 :> 4 :> 5 :> 6 :> 7 :> 8 :> 9 :> Nil
>>> interleave d3 xs
1 :> 4 :> 7 :> 2 :> 5 :> 8 :> 3 :> 6 :> 9 :> Nil

Dynamically rotate a Vector to the left:

>>> let xs = 1 :> 2 :> 3 :> 4 :> Nil
>>> rotateLeft xs 1
2 :> 3 :> 4 :> 1 :> Nil
>>> rotateLeft xs 2
3 :> 4 :> 1 :> 2 :> Nil
>>> rotateLeft xs (-1)
4 :> 1 :> 2 :> 3 :> Nil

NB: Use rotateLeftS if you want to rotate left by a static amount.

Dynamically rotate a Vector to the right:

>>> let xs = 1 :> 2 :> 3 :> 4 :> Nil
>>> rotateRight xs 1
4 :> 1 :> 2 :> 3 :> Nil
>>> rotateRight xs 2
3 :> 4 :> 1 :> 2 :> Nil
>>> rotateRight xs (-1)
2 :> 3 :> 4 :> 1 :> Nil

NB: Use rotateRightS if you want to rotate right by a static amount.

Statically rotate a Vector to the left:

>>> let xs = 1 :> 2 :> 3 :> 4 :> Nil
>>> rotateLeftS xs d1
2 :> 3 :> 4 :> 1 :> Nil

NB: Use rotateLeft if you want to rotate left by a dynamic amount.

Statically rotate a Vector to the right:

>>> let xs = 1 :> 2 :> 3 :> 4 :> Nil
>>> rotateRightS xs d1
4 :> 1 :> 2 :> 3 :> Nil

NB: Use rotateRight if you want to rotate right by a dynamic amount.

Convert a vector to a list.

>>> toList (1:>2:>3:>Nil)
[1,2,3]

NB: This function is not synthesizable

Create a vector literal from a list literal.

$(listToVecTH [1::Signed 8,2,3,4,5]) == (8:>2:>3:>4:>5:>Nil) :: Vec 5 (Signed 8)

>>> [1 :: Signed 8,2,3,4,5]
[1,2,3,4,5]
>>> $(listToVecTH [1::Signed 8,2,3,4,5])
1 :> 2 :> 3 :> 4 :> 5 :> Nil

Vector as a Proxy for Nat

Length of a Vector as an SNat value

What you should use when your vector functions are too strict in their arguments.

doctests setup

>>> let compareSwapL a b = if a < b then (a,b) else (b,a)
>>> :{
let sortVL :: (Ord a, KnownNat (n   1)) => Vec ((n   1)   1) a -> Vec ((n   1)   1) a
    sortVL xs = map fst sorted :< (snd (last sorted))
      where
        lefts  = head xs :> map snd (init sorted)
        rights = tail xs
        sorted = zipWith compareSwapL (lazyV lefts) rights
:}

>>> :{
let sortV_flip xs = map fst sorted :< (snd (last sorted))
      where
        lefts  = head xs :> map snd (init sorted)
        rights = tail xs
        sorted = zipWith (flip compareSwapL) rights lefts
:}

Example usage

For example:

-- Bubble sort for 1 iteration
sortV xs = map fst sorted :< (snd (last sorted))
 where
   lefts  = head xs :> map snd (init sorted)
   rights = tail xs
   sorted = zipWith compareSwapL lefts rights

-- Compare and swap
compareSwapL a b = if a < b then (a,b)
                            else (b,a)

Will not terminate because zipWith is too strict in its second argument.

In this case, adding lazyV on zipWiths second argument:

sortVL xs = map fst sorted :< (snd (last sorted))
 where
   lefts  = head xs :> map snd (init sorted)
   rights = tail xs
   sorted = zipWith compareSwapL (lazyV lefts) rights

Results in a successful computation:

>>> sortVL (4 :> 1 :> 2 :> 3 :> Nil)
1 :> 2 :> 3 :> 4 :> Nil

NB: There is also a solution using flip, but it slightly obfuscates the meaning of the code:

sortV_flip xs = map fst sorted :< (snd (last sorted))
 where
   lefts  = head xs :> map snd (init sorted)
   rights = tail xs
   sorted = zipWith (flip compareSwapL) rights lefts

>>> sortV_flip (4 :> 1 :> 2 :> 3 :> Nil)
1 :> 2 :> 3 :> 4 :> Nil

A dependently typed fold.

doctests setup

>>> :seti -fplugin GHC.TypeLits.Normalise
>>> import Data.Singletons (Apply, Proxy (..), TyFun)
>>> data Append (m :: Nat) (a :: Type) (f :: TyFun Nat Type) :: Type
>>> type instance Apply (Append m a) l = Vec (l   m) a
>>> let append' xs ys = dfold (Proxy :: Proxy (Append m a)) (const (:>)) ys xs

Example usage

Using lists, we can define append (a.k.a. Data.List. ) in terms of Data.List.foldr:

>>> import qualified Data.List
>>> let append xs ys = Data.List.foldr (:) ys xs
>>> append [1,2] [3,4]
[1,2,3,4]

However, when we try to do the same for Vec, by defining append' in terms of Clash.Sized.Vector.foldr:

append' xs ys = foldr (:>) ys xs

we get a type error:

>>> let append' xs ys = foldr (:>) ys xs

<interactive>:...
    • Occurs check: cannot construct the infinite type: ... ~ ...   1
      Expected type: a -> Vec ... a -> Vec ... a
        Actual type: a -> Vec ... a -> Vec (...   1) a
    • In the first argument of ‘foldr’, namely ‘(:>)’
      In the expression: foldr (:>) ys xs
      In an equation for ‘append'’: append' xs ys = foldr (:>) ys xs
    • Relevant bindings include
        ys :: Vec ... a (bound at ...)
        append' :: Vec n a -> Vec ... a -> Vec ... a
          (bound at ...)

The reason is that the type of foldr is:

>>> :t foldr
foldr :: (a -> b -> b) -> b -> Vec n a -> b

While the type of (:>) is:

>>> :t (:>)
(:>) :: a -> Vec n a -> Vec (n   1) a

We thus need a fold function that can handle the growing vector type: dfold. Compared to foldr, dfold takes an extra parameter, called the motive, that allows the folded function to have an argument and result type that depends on the current length of the vector. Using dfold, we can now correctly define append':

import Data.Singletons
import Data.Proxy

data Append (m :: Nat) (a :: Type) (f :: TyFun Nat Type) :: Type
type instance Apply (Append m a) l = Vec (l   m) a

append' xs ys = dfold (Proxy :: Proxy (Append m a)) (const (:>)) ys xs

We now see that append' has the appropriate type:

>>> :t append'
append' :: KnownNat k => Vec k a -> Vec m a -> Vec (k   m) a

And that it works:

>>> append' (1 :> 2 :> Nil) (3 :> 4 :> Nil)
1 :> 2 :> 3 :> 4 :> Nil

NB: "dfold m f z xs" creates a linear structure, which has a depth, or delay, of O(length xs). Look at dtfold for a dependently typed fold that produces a structure with a depth of O(log_2(length xs)).

A combination of dfold and fold: a dependently typed fold that reduces a vector in a tree-like structure.

doctests setup

>>> :seti -XUndecidableInstances
>>> import Data.Singletons (Apply, Proxy (..), TyFun)
>>> data IIndex (f :: TyFun Nat Type) :: Type
>>> type instance Apply IIndex l = Index ((2^l) 1)
>>> :{
let populationCount' :: (KnownNat k, KnownNat (2^k)) => BitVector (2^k) -> Index ((2^k) 1)
    populationCount' bv = dtfold (Proxy @IIndex)
                                 fromIntegral
                                 (\_ x y -> add x y)
                                 (bv2v bv)
:}

Example usage

As an example of when you might want to use dtfold we will build a population counter: a circuit that counts the number of bits set to '1' in a BitVector. Given a vector of n bits, we only need we need a data type that can represent the number n: Index (n 1). Index k has a range of [0 .. k-1] (using ceil(log2(k)) bits), hence we need Index n 1. As an initial attempt we will use sum, because it gives a nice (log2(n)) tree-structure of adders:

populationCount :: (KnownNat (n 1), KnownNat (n 2))
                => BitVector (n 1) -> Index (n 2)
populationCount = sum . map fromIntegral . bv2v

The "problem" with this description is that all adders have the same bit-width, i.e. all adders are of the type:

( ) :: Index (n 2) -> Index (n 2) -> Index (n 2).

This is a "problem" because we could have a more efficient structure: one where each layer of adders is precisely wide enough to count the number of bits at that layer. That is, at height d we want the adder to be of type:

Index ((2^d) 1) -> Index ((2^d) 1) -> Index ((2^(d 1)) 1)

We have such an adder in the form of the add function, as defined in the instance ExtendingNum instance of Index. However, we cannot simply use fold to create a tree-structure of addes:

>>> :{
let populationCount' :: (KnownNat (n 1), KnownNat (n 2))
                     => BitVector (n 1) -> Index (n 2)
    populationCount' = fold add . map fromIntegral . bv2v
:}

<interactive>:...
    • Couldn't match type ‘((n   2)   (n   2)) - 1’ with ‘n   2’
      Expected type: Index (n   2) -> Index (n   2) -> Index (n   2)
        Actual type: Index (n   2)
                     -> Index (n   2) -> AResult (Index (n   2)) (Index (n   2))
    • In the first argument of ‘fold’, namely ‘add’
      In the first argument of ‘(.)’, namely ‘fold add’
      In the expression: fold add . map fromIntegral . bv2v
    • Relevant bindings include
        populationCount' :: BitVector (n   1) -> Index (n   2)
          (bound at ...)

because fold expects a function of type "a -> a -> a", i.e. a function where the arguments and result all have exactly the same type.

In order to accommodate the type of our add, where the result is larger than the arguments, we must use a dependently typed fold in the form of dtfold:

{-# LANGUAGE UndecidableInstances #-}
import Data.Singletons
import Data.Proxy

data IIndex (f :: TyFun Nat Type) :: Type
type instance Apply IIndex l = Index ((2^l) 1)

populationCount' :: (KnownNat k, KnownNat (2^k))
                 => BitVector (2^k) -> Index ((2^k) 1)
populationCount' bv = dtfold (Proxy @IIndex)
                             fromIntegral
                             (\_ x y -> add x y)
                             (bv2v bv)

And we can test that it works:

>>> :t populationCount' (7 :: BitVector 16)
populationCount' (7 :: BitVector 16) :: Index 17
>>> populationCount' (7 :: BitVector 16)
3

Some final remarks:

• By using dtfold instead of fold, we had to restrict our BitVector argument to have bit-width that is a power of 2.
• Even though our original populationCount function specified a structure where all adders had the same width. Most VHDL/(System)Verilog synthesis tools will create a more efficient circuit, i.e. one where the adders have an increasing bit-width for every layer, from the VHDL/(System)Verilog produced by the Clash compiler.

NB: The depth, or delay, of the structure produced by "dtfold m f g xs" is O(log_2(length xs)).

Specialised version of dfold that builds a triangular computational structure.

doctests setup

>>> let compareSwap a b = if a > b then (a,b) else (b,a)
>>> let insert y xs = let (y',xs') = mapAccumL compareSwap y xs in xs' :< y'
>>> let insertionSort = vfold (const insert)

Example usage

compareSwap a b = if a > b then (a,b) else (b,a)
insert y xs     = let (y',xs') = mapAccumL compareSwap y xs in xs' :< y'
insertionSort   = vfold (const insert)

Builds a triangular structure of compare and swaps to sort a row.

>>> insertionSort (7 :> 3 :> 9 :> 1 :> Nil)
1 :> 3 :> 7 :> 9 :> Nil

The circuit layout of insertionSort, build using vfold, is:

The largest element of a non-empty vector

The least element of a non-empty vector

Apply a function to every element of a vector and the element's position (as an SNat value) in the vector.

>>> let rotateMatrix = smap (flip rotateRightS)
>>> let xss = (1:>2:>3:>Nil):>(1:>2:>3:>Nil):>(1:>2:>3:>Nil):>Nil
>>> xss
(1 :> 2 :> 3 :> Nil) :> (1 :> 2 :> 3 :> Nil) :> (1 :> 2 :> 3 :> Nil) :> Nil
>>> rotateMatrix xss
(1 :> 2 :> 3 :> Nil) :> (3 :> 1 :> 2 :> Nil) :> (2 :> 3 :> 1 :> Nil) :> Nil

Convert a Vec of Bits to a BitVector.