Safe Haskell  None 

sclang
pattern library functions.
See http://rd.slavepianos.org/?t=hsc3texts for tutorial.
SC3 value patterns: pbrown
(Pbrown), pclutch
(Pclutch),
pcollect
(Pcollect), pconst
(Pconst), pdegreeToKey
(PdegreeToKey), pdiff
(Pdiff), pdrop
(Pdrop), pdurStutter
(PdurStutter), pexprand
(Pexprand), pfinval
(Pfinval), pfuncn
(Pfuncn), pgeom
(Pgeom), pif
(Pif), place
(Place), pn
(Pn),
ppatlace
(Ppatlace), prand
(Prand), preject
(Preject),
prorate
(Prorate), pselect
(Pselect), pseq
(Pseq), pser
(Pser), pseries
(Pseries), pshuf
(Pshuf), pslide
(Pslide),
pstutter
(Pstutter), pswitch1
(Pswitch1), pswitch
(Pswitch),
ptuple
(Ptuple), pwhite
(Pwhite), pwrand
(Pwrand), pwrap
(Pwrap), pxrand
(Pxrand).
SC3 event patterns: padd
(Padd), pbind
(Pbind), pkey
(PKey), pmono
(Pmono), pmul
(Pmul), ppar
(Ppar), pstretch
(Pstretch), ptpar
(Ptpar). pedit
, pinstr
, pmce2
, psynth
,
punion
.
SC3 variant patterns: pbrown
', prand'
, prorate'
, pseq1
,
pseqn
, pser1
, pseqr
, pwhite'
, pwhitei
.
SC3 collection patterns: pfold
Haskell patterns: pappend
, pbool
, pconcat
, pcons
,
pcountpost
, pcountpre
, pcycle
, pempty
,pfilter
, phold
,
pinterleave
,pjoin
, prepeat
, preplicate
, prsd
, pscanl
,
psplitPlaces
, psplitPlaces'
, ptail
, ptake
, ptrigger
,
pzip
, pzipWith
 data P a = P {
 unP_either :: Either a [a]
 undecided :: a > P a
 toP :: [a] > P a
 unP :: P a > [a]
 unP_repeat :: P a > [a]
 liftP :: ([a] > [b]) > P a > P b
 liftP2 :: ([a] > [b] > [c]) > P a > P b > P c
 liftP2_repeat :: ([a] > [b] > [c]) > P a > P b > P c
 liftP3 :: ([a] > [b] > [c] > [d]) > P a > P b > P c > P d
 liftP3_repeat :: ([a] > [b] > [c] > [d]) > P a > P b > P c > P d
 pzipWith :: (a > b > c) > P a > P b > P c
 pzipWith3 :: (a > b > c > d) > P a > P b > P c > P d
 pzip :: P a > P b > P (a, b)
 pzip3 :: P a > P b > P c > P (a, b, c)
 punzip :: P (a, b) > (P a, P b)
 inf :: Int
 nan :: Floating a => a
 pcons :: a > P a > P a
 pnull :: P a > Bool
 prepeat :: a > P a
 psplitAt :: Int > P a > (P a, P a)
 psplitPlaces' :: P Int > P a > P [a]
 psplitPlaces :: P Int > P a > P (P a)
 ptake :: Int > P a > P a
 pcycle :: P a > P a
 pfilter :: (a > Bool) > P a > P a
 preplicate :: Int > a > P a
 pscanl :: (a > b > a) > a > P b > P a
 ptail :: P a > P a
 ptranspose :: [P a] > P [a]
 ptranspose_st_repeat :: [P a] > P [a]
 pflop' :: [P a] > P [a]
 pflop :: [P a] > P (P a)
 pfold :: RealFrac n => P n > n > n > P n
 pnormalizeSum :: Fractional n => P n > P n
 pbrown :: (Enum e, Random n, Num n, Ord n) => e > n > n > n > Int > P n
 pclutch :: P a > P Bool > P a
 pcollect :: (a > b) > P a > P b
 pconst :: (Ord a, Num a) => a > P a > a > P a
 pdegreeToKey :: RealFrac a => P a > P [a] > P a > P a
 pdiff :: Num n => P n > P n
 pdrop :: Int > P a > P a
 pdurStutter :: Fractional a => P Int > P a > P a
 pexprand :: (Enum e, Random a, Floating a) => e > a > a > Int > P a
 pfinval :: Int > P a > P a
 pfuncn :: Enum e => e > (StdGen > (n, StdGen)) > Int > P n
 pgeom :: Num a => a > a > Int > P a
 pif :: P Bool > P a > P a > P a
 place :: [[a]] > Int > P a
 pn :: P a > Int > P a
 ppatlace :: [P a] > Int > P a
 prand :: Enum e => e > [P a] > Int > P a
 preject :: (a > Bool) > P a > P a
 prorate :: Num a => P (Either a [a]) > P a > P a
 pselect :: (a > Bool) > P a > P a
 pseq :: [P a] > Int > P a
 pser :: [P a] > Int > P a
 pseries :: Num a => a > a > Int > P a
 pshuf :: Enum e => e > [a] > Int > P a
 pslide :: [a] > Int > Int > Int > Int > Bool > P a
 pstutter :: P Int > P a > P a
 pswitch :: [P a] > P Int > P a
 pswitch1 :: [P a] > P Int > P a
 ptuple :: [P a] > Int > P [a]
 pwhite :: (Random n, Enum e) => e > n > n > Int > P n
 pwrand :: Enum e => e > [P a] > [Double] > Int > P a
 pwrap :: (Ord a, Num a) => P a > a > a > P a
 pxrand :: Enum e => e > [P a] > Int > P a
 pbrown' :: (Enum e, Random n, Num n, Ord n) => e > P n > P n > P n > Int > P n
 prand' :: Enum e => e > [P a] > Int > P (P a)
 prorate' :: Num a => Either a [a] > a > P a
 pseq1 :: [P a] > Int > P a
 pseqn :: [Int] > [P a] > Int > P a
 pseqr :: (Int > [P a]) > Int > P a
 pser1 :: [P a] > Int > P a
 pwhite' :: (Enum e, Random n) => e > P n > P n > P n
 pwhitei :: (RealFracE n, Random n, Enum e) => e > n > n > Int > P n
 pbool :: (Ord a, Num a) => P a > P Bool
 pconcatReplicate :: Int > P a > P a
 pcountpost :: P Bool > P Int
 pcountpre :: P Bool > P Int
 phold :: P a > P a
 pinterleave2 :: P a > P a > P a
 pinterleave :: [P a] > P a
 pisPrefixOf :: Eq a => P a > P a > Bool
 prsd :: Eq a => P a > P a
 ptrigger :: P Bool > P a > P (Maybe a)
 type P_Bind = (Key, P Field)
 padd :: P_Bind > P Event > P Event
 pbind :: [P_Bind] > P Event
 (<) :: F_Value v => Key > P v > P_Bind
 pkey :: Key > P Event > P Field
 pmono :: [P_Bind] > P Event
 pmul :: P_Bind > P Event > P Event
 ppar :: [P Event] > P Event
 pstretch :: P Field > P Event > P Event
 ptpar :: [(Time, P Event)] > P Event
 pinstr' :: Instr > P Field
 pinstr :: String > P Field
 psynth :: Synthdef > P Field
 pmce2 :: P Field > P Field > P Field
 pmce3 :: P Field > P Field > P Field > P Field
 p_un_mce :: P Event > P Event
 pedit :: Key > (Field > Field) > P Event > P Event
 p_time :: P Event > P Time
 pkey_m :: Key > P Event > P (Maybe Field)
 pmerge :: P Event > P Event > P Event
 pmul' :: P_Bind > P Event > P Event
 ptmerge :: (Time, P Event) > (Time, P Event) > P Event
 punion :: P Event > P Event > P Event
 p_with :: P_Bind > P Event > P Event
 pappend :: P a > P a > P a
 pconcat :: [P a] > P a
 pempty :: P a
 pfoldr :: (a > b > b) > b > P a > b
 pjoin :: P (P a) > P a
 pjoin_repeat :: P (P a) > P a
 pmap :: (a > b) > P a > P b
 pmbind :: P a > (a > P b) > P b
 ppure :: a > P a
 preturn :: a > P a
 ptraverse :: Applicative f => (a > f b) > P a > f (P b)
 pNRT :: P Event > NRT
 pbrownM :: (UId m, Num n, Ord n, Random n) => n > n > n > Int > m (P n)
 pexprandM :: (UId m, Random a, Floating a) => a > a > Int > m (P a)
 prandM :: UId m => [P a] > Int > m (P a)
 pshufM :: UId m => [a] > Int > m (P a)
 pwhiteM :: (UId m, Random n) => n > n > Int > m (P n)
 pwhiteiM :: (UId m, RealFracE n, Random n) => n > n > Int > m (P n)
 pwrandM :: UId m => [P a] > [Double] > Int > m (P a)
 pxrandM :: UId m => [P a] > Int > m (P a)
P
Patterns are opaque. P a
is a pattern with elements of type
a
. Patterns are constructed, manipulated and destructured using
the functions provided, ie. the pattern instances for return
,
pure
and toList
, and the pattern specific functions
undecided
and toP
.
F.toList (toP [1,2,3] * 2) == [2,4,6]
Patterns are Functor
s. fmap
applies a function to each element
of a pattern.
fmap (* 2) (toP [1,2,3,4,5]) == toP [2,4,6,8,10]
Patterns are Monoid
s. mempty
is the empty pattern, and
mappend
(<>
) makes a sequence of two patterns.
1 <> mempty <> 2 == toP [1,2]
Patterns are Applicative
. The pattern instance is pointwise &
truncating, unlike the combinatorial instance for ordinary lists.
pure
lifts a value into an infinite pattern of itself, <*>
applies a pattern of functions to a pattern of values. This is
distinct from the list instance which is monadic, ie. pure
is
return
and <*>
is ap
.
liftA2 (+) (toP [1,2]) (toP [3,4,5]) == toP [4,6] liftA2 (+) [1,2] [3,4,5] == [4,5,6,5,6,7]
Patterns are Monad
s, and therefore allow do notation.
let p = do {x < toP [1,2]; y < toP [3,4,5]; return (x,y)} in p == toP [(1,3),(1,4),(1,5),(2,3),(2,4),(2,5)]
Patterns are Num
erical. The instances can be derived from the
Applicative
instance.
1 + toP [2,3,4] == liftA2 (+) 1 (toP [2,3,4])
P  

Lift a value to a pattern deferring deciding if the constructor
ought to be pure
or return
to the consuming function. The
pattern instances for fromInteger
and fromRational
make
undecided
patterns. In general horizontal functions (ie. <>
)
resolve using return
and vertical functions (ie. zip
) resolve
using pure
.
1 <> toP [2,3] == return 1 <> toP [2,3] toP [1,2] * 3 == toP [1,2] * pure 3
The basic list to pattern function, inverse is unP
.
unP (toP "str") == "str"
audition (pbind [(K_degree,pxrand 'α' [0,1,5,7] inf) ,(K_dur,toP [0.1,0.2,0.1])])
> Pbind(\degree,(Pxrand([0,1,5,7],inf)) > ,\dur,Pseq([0.1,0.2,0.1],1)).play
The pattern above is finite, toP
can sometimes be replaced with
pseq
.
audition (pbind [(K_degree,pxrand 'α' [0,1,5,7] inf) ,(K_dur,pseq [0.1,0.2,0.1] inf)])
unP_repeat :: P a > [a]Source
Lift P
liftP2 :: ([a] > [b] > [c]) > P a > P b > P cSource
Lift binary list function to pattern function.
liftP2 (zipWith (+)) (toP [1,2]) (toP [3,4,5]) == toP [4,6] liftA2 (+) (toP [1,2]) (toP [3,4,5]) == toP [4,6]
liftP2_repeat :: ([a] > [b] > [c]) > P a > P b > P cSource
Lift binary list function to implicitly repeating pattern function.
liftP3 :: ([a] > [b] > [c] > [d]) > P a > P b > P c > P dSource
Lift ternary list function to pattern function.
liftP3_repeat :: ([a] > [b] > [c] > [d]) > P a > P b > P c > P dSource
Lift ternary list function to implicitly repeating pattern function.
Zip P
pzipWith :: (a > b > c) > P a > P b > P cSource
An implicitly repeating pattern variant of zipWith
.
zipWith (*) [1,2,3] [5,6] == [5,12] pzipWith (*) (toP [1,2,3]) (toP [5,6]) == toP [5,12]
It is the basis for lifting binary operators to patterns.
toP [1,2,3] * toP [5,6] == toP [5,12]
let p = pzipWith (,) (pseq [1,2] 2) (pseq [3,4] inf) in p == toP [(1,3),(2,4),(1,3),(2,4)]
zipWith (,) (return 0) (return 1) == return (0,1) pzipWith (,) 0 1 == undecided (0,1)
pzipWith3 :: (a > b > c > d) > P a > P b > P c > P dSource
An implicitly repeating pattern variant of zipWith3
.
pzip :: P a > P b > P (a, b)Source
An implicitly repeating pattern variant of zip
.
zip (return 0) (return 1) == return (0,1) pzip (undecided 3) (undecided 4) == undecided (3,4) pzip 0 1 == undecided (0,1)
Note that pzip
is otherwise like haskell zip
, ie. truncating.
zip [1,2] [0] == [(1,0)] pzip (toP [1,2]) (return 0) == toP [(1,0)] pzip (toP [1,2]) (pure 0) == toP [(1,0),(2,0)] pzip (toP [1,2]) 0 == toP [(1,0),(2,0)]
punzip :: P (a, b) > (P a, P b)Source
Pattern variant on unzip
.
let p = punzip (pzip (toP [1,2,3]) (toP [4,5])) in p == (toP [1,2],toP [4,5])
Math
Type specialised maxBound
, a pseudoinfinite value for use at
pattern repeat counts.
inf == maxBound
Constant NaN (not a number) value.
isNaN nan == True
A frequency value of NaN indicates a rest. This constant value can be
used as a rest indicator at a frequency model input (not at a rest
key).
audition (pbind [(K_dur,pseq [0.1,0.7] inf) ,(K_legato,0.2) ,(K_degree,pseq [0,2,return nan] inf)])
Data.List Patterns
Pattern variant of null
.
pnull mempty == True pnull (undecided 'a') == False pnull (pure 'a') == False pnull (return 'a') == False
psplitPlaces' :: P Int > P a > P [a]Source
Pattern variant of splitPlaces
.
psplitPlaces' (toP [1,2,3]) (pseries 1 1 6) == toP [[1],[2,3],[4,5,6]] psplitPlaces' (toP [1,2,3]) (toP ['a'..]) == toP ["a","bc","def"]
psplitPlaces :: P Int > P a > P (P a)Source
fmap
toP
of psplitPlaces'
.
psplitPlaces (toP [1,2,3]) (toP ['a'..]) == toP (map toP ["a","bc","def"])
ptake :: Int > P a > P aSource
Pattern variant of take_inf
, see also pfinval
.
ptake 5 (pseq [1,2,3] 2) == toP [1,2,3,1,2] ptake 5 (toP [1,2,3]) == toP [1,2,3] ptake 5 (pseq [1,2,3] inf) == toP [1,2,3,1,2] ptake 5 (pwhite 'α' 0 5 inf) == toP [5,2,1,2,0]
Note that ptake
does not extend the input pattern, unlike pser
.
ptake 5 (toP [1,2,3]) == toP [1,2,3] pser [1,2,3] 5 == toP [1,2,3,1,2]
Type specialised mcycle
.
ptake 5 (pcycle 1) == preplicate 5 1 ptake 5 (pcycle (pure 1)) == preplicate 5 1 ptake 5 (pcycle (return 1)) == preplicate 5 1
preplicate :: Int > a > P aSource
pscanl :: (a > b > a) > a > P b > P aSource
Pattern variant of scanl
. scanl
is similar to foldl
, but
returns a list of successive reduced values from the left. pscanl
is an accumulator, it provides a mechanism for state to be threaded
through a pattern. It can be used to write a function to remove
succesive duplicates from a pattern, to count the distance between
occurences of an element in a pattern and so on.
F.foldl (\x y > 2 * x + y) 4 (pseq [1,2,3] 1) == 43 pscanl (\x y > 2 * x + y) 4 (pseq [1,2,3] 1) == toP [4,9,20,43]
F.foldl (flip (:)) [] (toP [1..3]) == [3,2,1] pscanl (flip (:)) [] (toP [1..3]) == toP [[],[1],[2,1],[3,2,1]]
F.foldl (+) 0 (toP [1..5]) == 15 pscanl (+) 0 (toP [1..5]) == toP [0,1,3,6,10,15]
ptranspose :: [P a] > P [a]Source
Variant of transpose
.
L.transpose [[1,2],[3,4,5]] == [[1,3],[2,4],[5]] ptranspose [toP [1,2],toP [3,4,5]] == toP [[1,3],[2,4],[5]]
let p = ptranspose [pseq [1,2] inf,pseq [4,5] inf] in ptake 2 (pdrop (2^16) p) == toP [[1,4],[2,5]]
ptranspose_st_repeat :: [P a] > P [a]Source
An implicitly repeating pattern variant of transpose_st
.
SC3 Collection Patterns
pflop' :: [P a] > P [a]Source
Variant of flop
.
pflop' [toP [1,2],toP [3,4,5]] == toP [[1,3],[2,4],[1,5]] pflop' [toP [1,2],3] == toP [[1,3],[2,3]] pflop' [pseq [1,2] 1,pseq [3,4] inf]
pfold :: RealFrac n => P n > n > n > P nSource
Type specialised ffold
.
pfold (toP [10,11,12,6,7,8]) (7) 11 == toP [10,11,10,6,7,6]
audition (pbind [(K_degree,pfold (pseries 4 1 inf) (7) 11) ,(K_dur,0.0625)])
The underlying primitive is then fold_
function.
let f = fmap (\n > fold_ n (7) 11) in audition (pbind [(K_degree,f (pseries 4 1 inf)) ,(K_dur,0.0625)])
pnormalizeSum :: Fractional n => P n > P nSource
Pattern variant of normalizeSum
.
SC3 Patterns
pbrown :: (Enum e, Random n, Num n, Ord n) => e > n > n > n > Int > P nSource
Pbrown. Lifted brown
. SC3 pattern to generate
psuedobrownian motion.
pbrown 'α' 0 9 1 5 == toP [4,4,5,4,3]
audition (pbind [(K_dur,0.065) ,(K_freq,pbrown 'α' 440 880 20 inf)])
pclutch :: P a > P Bool > P aSource
Pclutch. SC3 sample and hold pattern. For true values in the control pattern, step the value pattern, else hold the previous value.
> c = Pseq([1,0,1,0,0,1,1],inf); > p = Pclutch(Pser([1,2,3,4,5],8),c); > r = [1,1,2,2,2,3,4,5,5,1,1,1,2,3]; > p.asStream.all == r
let {c = pbool (pseq [1,0,1,0,0,1,1] inf) ;p = pclutch (pser [1,2,3,4,5] 8) c ;r = toP [1,1,2,2,2,3,4,5,5,1,1,1,2,3]} in p == toP [1,1,2,2,2,3,4,5,5,1,1,1,2,3]
Note the initialization behavior, nothing is generated until the first true value.
let {p = pseq [1,2,3,4,5] 1 ;q = pbool (pseq [0,0,0,0,0,0,1,0,0,1,0,1] 1)} in pclutch p q == toP [1,1,1,2,2,3]
> Pbind(\degree,Pstutter(Pwhite(3,10,inf),Pwhite(4,11,inf)), > \dur,Pclutch(Pwhite(0.1,0.4,inf), > Pdiff(Pkey(\degree)).abs > 0), > \legato,0.3).play;
let {d = pstutter (pwhite 'α' 3 10 inf) (pwhitei 'β' (4) 11 inf) ;p = [(K_degree,d) ,(K_dur,pclutch (pwhite 'γ' 0.1 0.4 inf) (pbool (abs (pdiff d) >* 0))) ,(K_legato,0.3)]} in audition (pbind p)
pcollect :: (a > b) > P a > P bSource
Pcollect. SC3 name for fmap
, ie. patterns are functors.
> Pcollect({i i * 3},Pseq(#[1,2,3],1)).asStream.all == [3,6,9] pcollect (* 3) (toP [1,2,3]) == toP [3,6,9]
> Pseq(#[1,2,3],1).collect({i i * 3}).asStream.all == [3,6,9] fmap (* 3) (toP [1,2,3]) == toP [3,6,9]
pconst :: (Ord a, Num a) => a > P a > a > P aSource
Pconst. SC3 pattern to constrain the sum of a numerical pattern. Is equal to p until the accumulated sum is within t of n. At that point, the difference between the specified sum and the accumulated sum concludes the pattern.
> p = Pconst(10,Pseed(Pn(1000,1),Prand([1,2,0.5,0.1],inf),0.001)); > p.asStream.all == [0.5,0.1,0.5,1,2,2,0.5,1,0.5,1,0.9]
let p = pconst 10 (prand 'α' [1,2,0.5,0.1] inf) 0.001 in (p,Data.Foldable.sum p)
> Pbind(\degree,Pseq([7,Pwhite(0,11,inf)],1), > \dur,Pconst(4,Pwhite(1,4,inf) * 0.25)).play
let p = [(K_degree,pcons (7) (pwhitei 'α' 0 11 inf)) ,(K_dur,pconst 4 (pwhite 'β' 1 4 inf * 0.25) 0.001)] in audition (pbind p)
pdegreeToKey :: RealFrac a => P a > P [a] > P a > P aSource
PdegreeToKey. SC3 pattern to derive notes from an index into a scale.
let {p = pseq [0,1,2,3,4,3,2,1,0,2,4,7,4,2] 2 ;q = pure [0,2,4,5,7,9,11] ;r = [0,2,4,5,7,5,4,2,0,4,7,12,7,4,0,2,4,5,7,5,4,2,0,4,7,12,7,4]} in pdegreeToKey p q (pure 12) == toP r
let {p = pseq [0,1,2,3,4,3,2,1,0,2,4,7,4,2] 2 ;q = pseq (map return [[0,2,4,5,7,9,11],[0,2,3,5,7,8,11]]) 1 ;r = [0,2,4,5,7,5,4,2,0,4,7,12,7,4,0,2,3,5,7,5,3,2,0,3,7,12,7,3]} in pdegreeToKey p (pstutter 14 q) (pure 12) == toP r
This is the pattern variant of degreeToKey
.
let s = [0,2,4,5,7,9,11] in map (M.degreeToKey s 12) [0,2,4,7,4,2,0] == [0,4,7,12,7,4,0]
> Pbind(\note,PdegreeToKey(Pseq([1,2,3,2,5,4,3,4,2,1],2), > #[0,2,3,6,7,9], > 12),\dur,0.25).play
let {n = pdegreeToKey (pseq [1,2,3,2,5,4,3,4,2,1] 2) (pure [0,2,3,6,7,9]) 12} in audition (pbind [(K_note,n),(K_dur,0.25)])
> s = #[[0,2,3,6,7,9],[0,1,5,6,7,9,11],[0,2,3]]; > d = [1,2,3,2,5,4,3,4,2,1]; > Pbind(\note,PdegreeToKey(Pseq(d,4), > Pstutter(3,Prand(s,inf)), > 12),\dur,0.25).play;
let {s = map return [[0,2,3,6,7,9],[0,1,5,6,7,9,11],[0,2,3]] ;d = [1,2,3,2,5,4,3,4,2,1] ;k = pdegreeToKey (pseq d 4) (pstutter 3 (prand 'α' s 14)) (pn 12 40)} in audition (pbind [(K_note,k),(K_dur,0.25)])
pdiff :: Num n => P n > P nSource
Pdiff. SC3 pattern to calculate adjacent element difference.
> Pdiff(Pseq([0,2,3,5,6,8,9],1)).asStream.all == [2,1,2,1,2,1] pdiff (pseq [0,2,3,5,6,8,9] 1) == toP [2,1,2,1,2,1]
pdrop :: Int > P a > P aSource
Pdrop. Lifted drop
.
> p = Pseries(1,1,20).drop(5); > p.asStream.all == [6,7,8,9,10,11,12,13,14,15,16,17,18,19,20]
pdrop 5 (pseries 1 1 10) == toP [6,7,8,9,10] pdrop 1 mempty == mempty
pdurStutter :: Fractional a => P Int > P a > P aSource
PdurStutter. Lifted durStutter
.
> s = Pseq(#[1,1,1,1,1,2,2,2,2,2,0,1,3,4,0],inf); > d = Pseq(#[0.5,1,2,0.25,0.25],1); > PdurStutter(s,d).asStream.all == [0.5,1,2,0.25,0.25]
let {s = pseq [1,1,1,1,1,2,2,2,2,2,0,1,3,4,0] inf ;d = pseq [0.5,1,2,0.25,0.25] 1} in pdurStutter s d == toP [0.5,1.0,2.0,0.25,0.25]
Applied to duration.
> d = PdurStutter(Pseq(#[1,1,1,1,1,2,2,2,2,2,3,3,3,3,3,4,4,4,4,4],inf), > Pseq(#[0.5,1,2,0.25,0.25],inf)); > Pbind(\freq,440,\dur,d).play
let {s = pseq [1,1,1,1,1,2,2,2,2,2,3,3,3,3,3,4,4,4,4,4] inf ;d = pseq [0.5,1,2,0.25,0.25] inf} in audition (pbind [(K_freq,440),(K_dur,pdurStutter s d)])
Applied to frequency.
let {s = pseq [1,1,1,1,1,2,2,2,2,2,3,3,3,3,4,4,0,4,4] inf ;d = pseq [0,2,3,5,7,9,10] inf + 80} in audition (pbind [(K_midinote,pdurStutter s d),(K_dur,0.15)])
pexprand :: (Enum e, Random a, Floating a) => e > a > a > Int > P aSource
Pexprand. Lifted exprand
.
> Pexprand(0.0001,1,10).asStream.all pexprand 'α' 0.0001 1 10
> Pbind(\freq,Pexprand(0.0001,1,inf) * 600 + 300,\dur,0.02).play
audition (pbind [(K_freq,pexprand 'α' 0.0001 1 inf * 600 + 300) ,(K_dur,0.02)])
pfinval :: Int > P a > P aSource
Pfinval. Alias for ptake
> Pfinval(5,Pseq(#[1,2,3],inf)).asStream.all == [1,2,3,1,2] pfinval 5 (pseq [1,2,3] inf) == toP [1,2,3,1,2]
pfuncn :: Enum e => e > (StdGen > (n, StdGen)) > Int > P nSource
A variant of the SC3 pattern that evaluates a closure at each
step. The haskell variant function has a StdGen
form.
> p = Pfuncn({exprand(0.1,0.3) + #[1,2,3,6,7].choose},inf); > Pbind(\freq,p * 100 + 300,\dur,0.02).play
let {exprand = Sound.SC3.Lang.Random.Gen.exprand ;choose = Sound.SC3.Lang.Random.Gen.choose ;p = pfuncn 'α' (exprand 0.1 0.3) inf ;q = pfuncn 'β' (choose [1,2,3,6,7]) inf} in audition (pbind [(K_freq,(p + q) * 100 + 300),(K_dur,0.02)])
Of course in this case there is a pattern equivalent.
let {p = pexprand 'α' 0.1 0.3 inf + prand 'β' [1,2,3,6,7] inf} in audition (pbind [(K_freq,p * 100 + 300),(K_dur,0.02)])
pgeom :: Num a => a > a > Int > P aSource
Pgeom. SC3 geometric series pattern.
> Pgeom(3,6,5).asStream.all == [3,18,108,648,3888] pgeom 3 6 5 == toP [3,18,108,648,3888]
> Pgeom(1,2,10).asStream.all == [1,2,4,8,16,32,64,128,256,512] pgeom 1 2 10 == toP [1,2,4,8,16,32,64,128,256,512]
Real numbers work as well.
> p = Pgeom(1.0,1.1,6).collect({i (i * 100).floor}); > p.asStream.all == [100,110,121,133,146,161];
let p = fmap (floor . (* 100)) (pgeom 1.0 1.1 6) in p == toP [100,110,121,133,146,161]
> Pbind(\degree,Pseries(7,1,15), > \dur,Pgeom(0.5,0.89140193218427,15)).play;
audition (pbind [(K_degree,pseries (7) 1 15) ,(K_dur,pgeom 0.5 0.89140193218427 15)])
There is a list variant.
> 5.geom(3,6) C.geom 5 3 6 == [3,18,108,648,3888]
pif :: P Bool > P a > P a > P aSource
Pif. SC3 implicitly repeating patternbased conditional expression.
> a = Pfunc({0.3.coin}); > b = Pwhite(0,9,3); > c = Pwhite(10,19,3); > Pfin(9,Pif(a,b,c)).asStream.all
let {a = fmap (< 0.75) (pwhite 'α' 0.0 1.0 inf) ;b = pwhite 'β' 0 9 6 ;c = pwhite 'γ' 10 19 6} in pif a b c * (1) == toP [7,3,11,17,18,6,3,4,5]
place :: [[a]] > Int > P aSource
Place. SC3 interlaced embedding of subarrays.
> Place([0,[1,2],[3,4,5]],3).asStream.all == [0,1,3,0,2,4,0,1,5] C.lace 9 [[0],[1,2],[3,4,5]] == [0,1,3,0,2,4,0,1,5] place [[0],[1,2],[3,4,5]] 3 == toP [0,1,3,0,2,4,0,1,5]
> Place(#[1,[2,5],[3,6]],2).asStream.all == [1,2,3,1,5,6] C.lace 6 [[1],[2,5],[3,6]] == [1,2,3,1,5,6] place [[1],[2,5],[3,6]] 2 == toP [1,2,3,1,5,6]
C.lace 12 [[1],[2,5],[3,6..]] == [1,2,3,1,5,6,1,2,9,1,5,12] place [[1],[2,5],[3,6..]] 4 == toP [1,2,3,1,5,6,1,2,9,1,5,12]
Pn. SC3 pattern to repeat the enclosed pattern a number of times.
pn 1 4 == toP [1,1,1,1] pn (toP [1,2,3]) 3 == toP [1,2,3,1,2,3,1,2,3]
This is related to concat
.replicate
in standard list processing.
concat (replicate 4 [1]) == [1,1,1,1] concat (replicate 3 [1,2,3]) == [1,2,3,1,2,3,1,2,3]
There is a pconcatReplicate
nearalias (reversed argument order).
pconcatReplicate 4 1 == toP [1,1,1,1] pconcatReplicate 3 (toP [1,2]) == toP [1,2,1,2,1,2]
This is productive over infinite lists.
concat (replicate inf [1]) pconcat (replicate inf 1) pconcatReplicate inf 1
ppatlace :: [P a] > Int > P aSource
Ppatlace. SC3 implicitly repeating pattern to lace input patterns.
> p = Ppatlace([1,Pseq([2,3],2),4],5); > p.asStream.all == [1,2,4,1,3,4,1,2,4,1,3,4,1,4]
ppatlace [1,pseq [2,3] 2,4] 5 == toP [1,2,4,1,3,4,1,2,4,1,3,4,1,4]
> p = Ppatlace([1,Pseed(Pn(1000,1),Prand([2,3],inf))],5); > p.asStream.all == [1,3,1,3,1,3,1,2,1,2]
ppatlace [1,prand 'α' [2,3] inf] 5 == toP [1,3,1,2,1,3,1,2,1,2]
> Pbind(\degree,Ppatlace([Pseries(0,1,8),Pseries(2,1,7)],inf), > \dur,0.25).play;
let p = [(K_degree,ppatlace [pseries 0 1 8,pseries 2 1 7] inf) ,(K_dur,0.125)] in audition (pbind p)
prand :: Enum e => e > [P a] > Int > P aSource
Prand. SC3 pattern to make n random selections from a list of patterns, the resulting pattern is flattened (joined).
> p = Pseed(Pn(1000,1),Prand([1,Pseq([10,20,30]),2,3,4,5],6)); > p.asStream.all == [3,5,3,10,20,30,2,2]
prand 'α' [1,toP [10,20],2,3,4,5] 5 == toP [5,2,10,20,2,1]
> Pbind(\note,Prand([0,1,5,7],inf),\dur,0.25).play
audition (pbind [(K_note,prand 'α' [0,1,5,7] inf),(K_dur,0.25)])
Nested sequences of pitches:
> Pbind(\midinote,Prand([Pseq(#[60,61,63,65,67,63]), > Prand(#[72,73,75,77,79],6), > Pshuf(#[48,53,55,58],2)],inf), > \dur,0.25).play
let {n = prand 'α' [pseq [60,61,63,65,67,63] 1 ,prand 'β' [72,73,75,77,79] 6 ,pshuf 'γ' [48,53,55,58] 2] inf} in audition (pbind [(K_midinote,n),(K_dur,0.075)])
The below cannot be written as intended with the list based pattern library. This is precisely because the noise patterns are values, not processes with a state threaded nonlocally.
do {n0 < Sound.SC3.Lang.Random.IO.rrand 2 5 ;n1 < Sound.SC3.Lang.Random.IO.rrand 3 9 ;let p = pseq [prand 'α' [pempty,pseq [24,31,36,43,48,55] 1] 1 ,pseq [60,prand 'β' [63,65] 1 ,67,prand 'γ' [70,72,74] 1] n0 ,prand 'δ' [74,75,77,79,81] n1] inf in return (ptake 24 p)}
preject :: (a > Bool) > P a > P aSource
Preject. SC3 pattern to rejects values for which the predicate is true. reject f is equal to filter (not . f).
preject (== 1) (pseq [1,2,3] 2) == toP [2,3,2,3] pfilter (not . (== 1)) (pseq [1,2,3] 2) == toP [2,3,2,3]
> p = Pseed(Pn(1000,1),Pwhite(0,255,20).reject({x x.odd})); > p.asStream.all == [224,60,88,94,42,32,110,24,122,172]
preject odd (pwhite 'α' 0 255 10) == toP [32,158,62,216,240,20]
> p = Pseed(Pn(1000,1),Pwhite(0,255,20).select({x x.odd})); > p.asStream.all == [151,157,187,129,45,245,101,79,77,243]
pselect odd (pwhite 'α' 0 255 10) == toP [241,187,119,127]
prorate :: Num a => P (Either a [a]) > P a > P aSource
Prorate. SC3 implicitly repeating subdividing pattern.
> p = Prorate(Pseq([0.35,0.5,0.8]),1); > p.asStream.all == [0.35,0.65,0.5,0.5,0.8,0.2];
let p = prorate (fmap Left (pseq [0.35,0.5,0.8] 1)) 1 in fmap roundE (p * 100) == toP [35,65,50,50,80,20]
> p = Prorate(Pseq([0.35,0.5,0.8]),Pseed(Pn(100,1),Prand([20,1],inf))); > p.asStream.all == [7,13,0.5,0.5,16,4]
let p = prorate (fmap Left (pseq [0.35,0.5,0.8] 1)) (prand 'α' [20,1] 3) in fmap roundE (p * 100) == toP [35,65,1000,1000,80,20]
> l = [[1,2],[5,7],[4,8,9]].collect(_.normalizeSum); > Prorate(Pseq(l,1)).asStream.all
let l = map (Right . C.normalizeSum) [[1,2],[5,7],[4,8,9]] in prorate (toP l) 1
> Pfinval(5,Prorate(0.6,0.5)).asStream.all == [0.3,0.2,0.3,0.2,0.3]
pfinval 5 (prorate (fmap Left 0.6) 0.5) == toP [0.3,0.2,0.3,0.2,0.3]
> Pbind(\degree,Pseries(4,1,inf).fold(7,11), > \dur,Prorate(0.6,0.5)).play
audition (pbind [(K_degree,pfold (pseries 4 1 inf) (7) 11) ,(K_dur,prorate (fmap Left 0.6) 0.25)])
pselect :: (a > Bool) > P a > P aSource
Pselect. See pfilter
.
pselect (< 3) (pseq [1,2,3] 2) == toP [1,2,1,2]
pseq :: [P a] > Int > P aSource
Pseq. SC3 pattern to cycle over a list of patterns. The repeats pattern gives the number of times to repeat the entire list.
pseq [return 1,return 2,return 3] 2 == toP [1,2,3,1,2,3] pseq [1,2,3] 2 == toP [1,2,3,1,2,3] pseq [1,pn 2 2,3] 2 == toP [1,2,2,3,1,2,2,3]
There is an inf
value for the repeats variable.
ptake 3 (pdrop (10^5) (pseq [1,2,3] inf)) == toP [2,3,1]
Unlike the SC3 Pseq, pseq
does not have an offset argument to give a
starting offset into the list.
pseq (C.rotate 3 [1,2,3,4]) 3 == toP [2,3,4,1,2,3,4,1,2,3,4,1]
As scale degrees.
> Pbind(\degree,Pseq(#[0,0,4,4,5,5,4],1), > \dur,Pseq(#[0.5,0.5,0.5,0.5,0.5,0.5,1],1)).play
audition (pbind [(K_degree,pseq [0,0,4,4,5,5,4] 1) ,(K_dur,pseq [0.5,0.5,0.5,0.5,0.5,0.5,1] 1)])
> Pseq(#[60,62,63,65,67,63],inf) + Pseq(#[0,0,0,0,12],inf)
let n = pseq [60,62,63,65,67,63] inf + pser [0,0,0,0,12] 25 in audition (pbind [(K_midinote,n),(K_dur,0.2)])
Pattern b
pattern sequences a
once normally, once transposed up a
fifth and once transposed up a fourth.
> a = Pseq(#[60,62,63,65,67,63]); > b = Pseq([a,a + 7,a + 5],inf); > Pbind(\midinote,b,\dur,0.3).play
let {a = pseq [60,62,63,65,67,63] 1 ;b = pseq [a,a + 7,a + 5] inf} in audition (pbind [(K_midinote,b),(K_dur,0.13)])
pser :: [P a] > Int > P aSource
Pser. SC3 pattern that is like pseq
, however the repeats
variable gives the number of elements in the sequence, not the
number of cycles of the pattern.
pser [1,2,3] 5 == toP [1,2,3,1,2] pser [1,pser [10,20] 3,3] 9 == toP [1,10,20,10,3,1,10,20,10] pser [1,2,3] 5 * 3 == toP [3,6,9,3,6]
pseries :: Num a => a > a > Int > P aSource
Pseries. SC3 arithmetric series pattern, see also pgeom
.
pseries 0 2 10 == toP [0,2,4,6,8,10,12,14,16,18] pseries 9 (1) 10 == toP [9,8 .. 0] pseries 1.0 0.2 3 == toP [1.0::Double,1.2,1.4]
pshuf :: Enum e => e > [a] > Int > P aSource
Pshuf. SC3 pattern to return n
repetitions of a shuffled
sequence.
> Pshuf([1,2,3,4],2).asStream.all pshuf 'α' [1,2,3,4] 2 == toP [2,4,3,1,2,4,3,1]
> Pbind(\degree,Pshuf([0,1,2,4,5],inf),\dur,0.25).play
audition (pbind [(K_degree,pshuf 'α' [0,1,2,4,5] inf) ,(K_dur,0.25)])
pslide :: [a] > Int > Int > Int > Int > Bool > P aSource
Pslide. Lifted slide
.
> Pslide([1,2,3,4],inf,3,1,0).asStream.all pslide [1,2,3,4] 4 3 1 0 True == toP [1,2,3,2,3,4,3,4,1,4,1,2] pslide [1,2,3,4,5] 3 3 (1) 0 True == toP [1,2,3,5,1,2,4,5,1]
> Pbind(\degree,Pslide((6,4 .. 12),8,3,1,0), > \dur,Pseq(#[0.1,0.1,0.2],inf), > \sustain,0.15).play
audition (pbind [(K_degree,pslide [6,4 .. 12] 8 3 1 0 True) ,(K_dur,pseq [0.05,0.05,0.1] inf) ,(K_sustain,0.15)])
pstutter :: P Int > P a > P aSource
Pstutter. SC3 implicitly repeating pattern to repeat each element of a pattern n times.
> Pstutter(2,Pseq([1,2,3],1)).asStream.all == [1,1,2,2,3,3] pstutter 2 (pseq [1,2,3] 1) == toP [1,1,2,2,3,3]
The count input may be a pattern.
let {p = pseq [1,2] inf ;q = pseq [1,2,3] 2} in pstutter p q == toP [1,2,2,3,1,1,2,3,3]
pstutter (toP [1,2,3]) (toP [4,5,6]) == toP [4,5,5,6,6,6] pstutter 2 (toP [4,5,6]) == toP [4,4,5,5,6,6]
Stutter scale degree and duration with the same random sequence.
> Pbind(\n,Pwhite(3,10,inf), > \degree,Pstutter(Pkey(\n),Pwhite(4,11,inf)), > \dur,Pstutter(Pkey(\n),Pwhite(0.05,0.4,inf)), > \legato,0.3).play
let {n = pwhite 'α' 3 10 inf ;p = [(K_degree,pstutter n (pwhitei 'β' (4) 11 inf)) ,(K_dur,pstutter n (pwhite 'γ' 0.05 0.4 inf)) ,(K_legato,0.3)]} in audition (pbind p)
pswitch :: [P a] > P Int > P aSource
Pswitch. Lifted switch
.
let p = pswitch [pseq [1,2,3] 2,pseq [65,76] 1,800] (toP [2,2,0,1]) in p == toP [800,800,1,2,3,1,2,3,65,76]
pswitch1 :: [P a] > P Int > P aSource
Pswitch1. Lifted implicitly repeating switch1
.
> l = [Pseq([1,2,3],inf),Pseq([65,76],inf),8]; > p = Pswitch1(l,Pseq([2,2,0,1],3)); > p.asStream.all == [8,8,1,65,8,8,2,76,8,8,3,65];
let p = pswitch1 [pseq [1,2,3] inf ,pseq [65,76] inf ,8] (pseq [2,2,0,1] 6) in p == toP [8,8,1,65,8,8,2,76,8,8,3,65,8,8,1,76,8,8,2,65,8,8,3,76]
ptuple :: [P a] > Int > P [a]Source
Ptuple. pseq
of ptranspose_st_repeat
.
> l = [Pseries(7,1,8),3,Pseq([9,7,4,2],1),Pseq([4,2,0,0,3],1)]; > p = Ptuple(l,1); > p.asStream.all == [[7,3,9,4],[6,3,7,2],[5,3,4,0],[4,3,2,0]]
let p = ptuple [pseries 7 (1) 8 ,3 ,pseq [9,7,4,2] 1 ,pseq [4,2,0,0,3] 1] 1 in p == toP [[7,3,9,4],[6,3,7,2],[5,3,4,0],[4,3,2,0]]
pwhite :: (Random n, Enum e) => e > n > n > Int > P nSource
Pwhite. Lifted white
.
pwhite 'α' 0 9 5 == toP [3,0,1,6,6] pwhite 'α' 0 9 5  pwhite 'α' 0 9 5 == toP [0,0,0,0,0]
The pattern below is alternately lower and higher noise.
let {l = pseq [0.0,9.0] inf ;h = pseq [1.0,12.0] inf} in audition (pbind [(K_freq,pwhite' 'α' l h * 20 + 800) ,(K_dur,0.25)])
pwrand :: Enum e => e > [P a] > [Double] > Int > P aSource
Pwrand. Lifted wrand
.
let w = C.normalizeSum [12,6,3] in pwrand 'α' [1,2,3] w 6 == toP [2,1,2,3,3,2]
> r = Pwrand.new([1,2,Pseq([3,4],1)],[1,3,5].normalizeSum,6); > p = Pseed(Pn(100,1),r); > p.asStream.all == [2,3,4,1,3,4,3,4,2]
let w = C.normalizeSum [1,3,5] in pwrand 'ζ' [1,2,pseq [3,4] 1] w 6 == toP [3,4,2,2,3,4,1,3,4]
> Pbind(\degree,Pwrand((0..7),[4,1,3,1,3,2,1].normalizeSum,inf), > \dur,0.25).play;
let {w = C.normalizeSum [4,1,3,1,3,2,1] ;d = pwrand 'α' (C.series 7 0 1) w inf} in audition (pbind [(K_degree,d),(K_dur,0.25)])
pxrand :: Enum e => e > [P a] > Int > P aSource
Pxrand. Lifted xrand
.
let p = pxrand 'α' [1,toP [2,3],toP [4,5,6]] 9 in p == toP [4,5,6,2,3,4,5,6,1]
> Pbind(\note,Pxrand([0,1,5,7],inf),\dur,0.25).play
audition (pbind [(K_note,pxrand 'α' [0,1,5,7] inf),(K_dur,0.25)])
Variant SC3 Patterns
pbrown' :: (Enum e, Random n, Num n, Ord n) => e > P n > P n > P n > Int > P nSource
Lifted implicitly repeating pbrown'
.
pbrown' 'α' 1 700 (pseq [1,20] inf) 4 == toP [415,419,420,428]
prand' :: Enum e => e > [P a] > Int > P (P a)Source
Unjoined variant of prand
.
let p = prand' 'α' [1,toP [2,3],toP [4,5,6]] 5 in p == toP [toP [4,5,6],toP [4,5,6],toP [2,3],toP [4,5,6],1]
prorate' :: Num a => Either a [a] > a > P aSource
Underlying pattern for prorate
.
prorate' (Left 0.6) 0.5
pseq1 :: [P a] > Int > P aSource
Variant of pseq
that retrieves only one value from each pattern
on each list traversal. Compare to pswitch1
.
pseq [pseq [1,2] 1,pseq [3,4] 1] 2 == toP [1,2,3,4,1,2,3,4] pseq1 [pseq [1,2] 1,pseq [3,4] 1] 2 == toP [1,3,2,4] pseq1 [pseq [1,2] inf,pseq [3,4] inf] 3 == toP [1,3,2,4,1,3]
let {p = prand' 'α' [pempty,toP [24,31,36,43,48,55]] inf ;q = pflop [60,prand 'β' [63,65] inf ,67,prand 'γ' [70,72,74] inf] ;r = psplitPlaces (pwhite 'δ' 3 9 inf) (toP [74,75,77,79,81]) ;n = pjoin (pseq1 [p,q,r] inf)} in audition (pbind [(K_midinote,n),(K_dur,0.13)])
pseqn :: [Int] > [P a] > Int > P aSource
A variant of pseq
to aid translating a common SC3 idiom where a
finite random pattern is included in a Pseq
list. In the SC3
case, at each iteration a new computation is run. This idiom does
not directly translate to the declarative haskell pattern library.
> Pseq([1,Prand([2,3],1)],5).asStream.all pseq [1,prand 'α' [2,3] 1] 5 == toP [1,3,1,3,1,3,1,3,1,3]
Although the intended pattern can usually be expressed using an alternate construction:
> Pseq([1,Prand([2,3],1)],5).asStream.all ppatlace [1,prand 'α' [2,3] inf] 5 == toP [1,3,1,2,1,3,1,2,1,2]
the pseqn
variant handles many common cases.
> Pseq([Pn(8,2),Pwhite(9,16,1)],5).asStream.all
let p = pseqn [2,1] [8,pwhite 'α' 9 16 inf] 5 in p == toP [8,8,10,8,8,9,8,8,12,8,8,15,8,8,15]
pseqr :: (Int > [P a]) > Int > P aSource
A variant of pseq
that passes a new seed at each invocation,
see also pfuncn
.
> pseqr (\e > [pshuf e [1,2,3,4] 1]) 2 == toP [2,3,4,1,4,1,2,3]
let {d = pseqr (\e > [pshuf e [7,3,0,2,4,7] 4 ,pseq [0,1,2,3,4,5,6,7] 1]) inf} in audition (pbind [(K_degree,d),(K_dur,0.15)])
> Pbind(\dur,0.2, > \midinote,Pseq([Pshuf(#[60,61,62,63,64,65,66,67],3)],inf)).play
let m = pseqr (\e > [pshuf e [60,61,62,63,64,65,66,67] 3]) inf in audition (pbind [(K_dur,0.2),(K_midinote,m)])
pser1 :: [P a] > Int > P aSource
Variant of pser
that consumes subpatterns one element per
iteration.
pser1 [1,pser [10,20] 3,3] 9 == toP [1,10,3,1,20,3,1,10,3]
pwhite' :: (Enum e, Random n) => e > P n > P n > P nSource
Lifted implicitly repeating pwhite
.
pwhite' 'α' 0 (pseq [9,19] 3) == toP [3,0,1,6,6,15]
pwhitei :: (RealFracE n, Random n, Enum e) => e > n > n > Int > P nSource
Lifted whitei
.
pwhitei 'α' 1 9 5 == toP [5,1,7,7,8]
audition (pbind [(K_degree,pwhitei 'α' 0 8 inf),(K_dur,0.15)])
NonSC3 Patterns
pinterleave2 :: P a > P a > P aSource
Lifted interleave2
.
let p = pinterleave2 (pwhite 'α' 1 9 inf) (pseries 10 1 5) in [3,10,9,11,2,12,9,13,4,14] `L.isPrefixOf` unP p
pinterleave :: [P a] > P aSource
Lifted interleave
.
pinterleave [pwhitei 'α' 0 4 3,pwhitei 'β' 5 9 3] == toP [2,7,0,5,3,6]
pisPrefixOf :: Eq a => P a > P a > BoolSource
Lifted isPrefixOf
.
prsd :: Eq a => P a > P aSource
Lifted rsd
.
prsd (pstutter 2 (toP [1,2,3])) == toP [1,2,3] prsd (pseq [1,2,3] 2) == toP [1,2,3,1,2,3]
ptrigger :: P Bool > P a > P (Maybe a)Source
Lifted trigger
.
let {tr = pbool (toP [0,1,0,0,1,1]) ;p = ptrigger tr (toP [1,2,3]) ;r = [Nothing,Just 1,Nothing,Nothing,Just 2,Just 3]} in p == toP r
SC3 Event Patterns
padd :: P_Bind > P Event > P EventSource
Padd. Add a value to an existing key, or set the key if it doesn't exist.
> p = Padd(\freq,801,Pbind(\freq,Pseq([100],1))); > p.asStream.all(()) == [('freq':901)]
let p = padd (K_freq,801) (pbind [(K_freq,return 100)]) in p == pbind [(K_freq,return 901)]
> Padd(\freq,Pseq([401,801],2),Pbind(\freq,100)).play
audition (padd (K_freq,pseq [401,801] 2) (pbind [(K_freq,100)]))
let {d = pseq [pshuf 'α' [7,3,0,2,4,7] 2 ,pseq [0,1,2,3,4,5,6,7] 1] 1 ;p = pbind [(K_dur,0.15),(K_degree,d)] ;t n = padd (K_mtranspose,n) p} in audition (pseq [p,t 1,t 2] inf)
pbind :: [P_Bind] > P EventSource
Pbind. SC3 pattern to assign keys to a set of Field
patterns
making an Event
pattern.
Each input pattern is assigned to key in the resulting event pattern.
There are a set of reserved keys that have particular roles in the pattern library.
> p = Pbind(\x,Pseq([1,2,3],1),\y,Pseed(Pn(100,1),Prand([4,5,6],inf))); > p.asStream.all(()) == [('y':4,'x':1),('y':6,'x':2),('y':4,'x':3)]
let p = pbind [(K_param "x",prand 'α' [100,300,200] inf) ,(K_param "y",pseq [1,2,3] 1)] in pkey (K_param "x") p == toP [200,200,300]
K_param
can be elided if OverloadedStrings are in place.
:set XOverloadedStrings
ptake 2 (pbind [("x",pwhitei 'α' 0 9 inf) ,("y",pseq [1,2,3] inf)])
Event
s implement variations on the SC3
Dur
and
Pitch
models.
> Pbind(\freq,Prand([300,500,231.2,399.2],inf), > \dur,0.1).play;
audition (pbind [(K_freq,prand 'α' [300,500,231.2,399.2] inf) ,(K_dur,0.1)])
> Pbind(\freq, Prand([300,500,231.2,399.2],inf), > \dur,Prand([0.1,0.3],inf)).play;
audition (pbind [(K_freq,prand 'α' [300,500,231.2,399.2] inf) ,(K_dur,prand 'β' [0.1,0.3] inf)])
> Pbind(\freq,Prand([1,1.2,2,2.5,3,4],inf) * 200, > \dur,0.1).play;
audition (pbind [(K_freq,prand 'α' [1,1.2,2,2.5,3,4] inf * 200) ,(K_dur,0.1)])
audition (pbind [(K_freq,pseq [440,550,660,770] 2) ,(K_dur,pseq [0.1,0.15,0.1] inf) ,(K_amp,pseq [0.1,0.05] inf) ,(K_param "pan",pseq [1,0,1] inf)])
A finite binding stops the Event
pattern.
> Pbind(\freq,Prand([300,500,231.2,399.2],inf), > \dur,Pseq([0.1,0.2],3)).play;
audition (pbind [(K_freq,prand 'α' [300,500,231.2,399.2] inf) ,(K_dur,pseq [0.1,0.2] 3)])
> Pbind(\freq,Prand([300,500,231.2,399.2],inf), > \dur,Prand([0.1,0.3],inf)).play
All infinite inputs:
audition (pbind [(K_freq,prand 'α' [300,500,231.2,399.2] inf) ,(K_dur,prand 'β' [0.1,0.3] inf)])
Implicit field patterns is this context are infinite.
audition (pbind [(K_freq,prand 'α' [1,1.2,2,2.5,3,4] inf * 200) ,(K_dur,0.1)])
let test = let {freq = control KR "freq" 440 ;amp = control KR "amp" 0.1 ;nharms = control KR "nharms" 10 ;pan = control KR "pan" 0 ;gate = control KR "gate" 1 ;s = blip AR freq nharms * amp ;e = linen gate 0.01 0.6 0.4 RemoveSynth ;o = offsetOut 0 (pan2 s pan e)} in synthdef "test" o
audition (pbind [(K_instr,psynth test) ,(K_freq,prand 'α' [1,1.2,2,2.5,3,4] inf * 200) ,(K_dur,0.1)])
audition (pbind [(K_instr,psynth test) ,(K_param "nharms",pseq [4,10,40] inf) ,(K_dur,pseq [1,1,2,1] inf / 10) ,(K_freq,pn (pseries 1 1 16 * 50) 4) ,(K_sustain,pseq [1/10,0.5,1,2] inf)])
let acid = let {freq = control KR "freq" 1000 ;gate = control KR "gate" 1 ;pan = control KR "pan" 0 ;cut = control KR "cut" 4000 ;res = control KR "res" 0.8 ;amp = control KR "amp" 1 ;s = rlpf (pulse AR freq 0.05) cut res ;d = envLinen 0.01 1 0.3 1 ;e = envGen KR gate amp 0 1 RemoveSynth d ;o = out 0 (pan2 s pan e)} in synthdef "acid" o
> Pbind(\instrument,\acid, > \dur,Pseq([0.25,0.5,0.25],4), > \root,24, > \degree,Pseq([0,3,5,7,9,11,5,1],inf), > \pan,Pfunc({1.0.rand2}), > \cut,Pxrand([1000,500,2000,300],inf), > \rez,Pfunc({0.7.rand +0.3}), > \amp,0.2).play
audition (pbind [(K_instr,psynth acid) ,(K_dur,pseq [0.25,0.5,0.25] 4) ,(K_root,24) ,(K_degree,pseq [0,3,5,7,9,11,5,1] inf) ,(K_param "pan",pwhite 'α' (1.0) 1.0 inf) ,(K_param "cut",pxrand 'β' [1000,500,2000,300] inf) ,(K_param "res",pwhite 'γ' 0.3 1.0 inf) ,(K_amp,0.2)])
> Pseq([Pbind(\instrument,\acid, > \dur,Pseq([0.25,0.5,0.25],4), > \root,24, > \degree,Pseq([0,3,5,7,9,11,5,1],inf), > \pan,Pfunc({1.0.rand2}), > \cut,Pxrand([1000,500,2000,300],inf), > \rez,Pfunc({0.7.rand + 0.3}), > \amp,0.2), > Pbind(\instrument,\acid, > \dur,Pseq([0.25],6), > \root,24, > \degree,Pseq([18,17,11,9],inf), > \pan,Pfunc({1.0.rand2}), > \cut,1500, > \rez,Pfunc({0.7.rand + 0.3}), > \amp,0.16)],inf).play
audition (pseq [pbind [(K_instr,psynth acid) ,(K_dur,pseq [0.25,0.5,0.25] 4) ,(K_root,24) ,(K_degree,pseq [0,3,5,7,9,11,5,1] inf) ,(K_param "pan",pwhite 'α' (1.0) 1.0 inf) ,(K_param "cut",pxrand 'β' [1000,500,2000,300] inf) ,(K_param "res",pwhite 'γ' 0.3 1.0 inf) ,(K_amp,0.2)] ,pbind [(K_instr,psynth acid) ,(K_dur,pn 0.25 6) ,(K_root,24) ,(K_degree,pser [18,17,11,9] inf) ,(K_param "pan",pwhite 'δ' (1.0) 1.0 inf) ,(K_param "cut",1500) ,(K_param "res",pwhite 'ε' 0.3 1.0 inf) ,(K_amp,0.16)]] inf)
> Pbind(\instrument, \acid, > \dur, Pseq([0.25,0.5,0.25], inf), > \root, [24,17], > \degree, Pseq([0,3,5,7,9,11,5,1], inf), > \pan, Pfunc({1.0.rand2}), > \cut, Pxrand([1000,500,2000,300], inf), > \rez, Pfunc({0.7.rand +0.3}), > \amp, 0.2).play;
audition (pbind [(K_instr,psynth acid) ,(K_dur,pseq [0.25,0.5,0.25] inf) ,(K_root,pmce2 (24) (17)) ,(K_degree,pseq [0,3,5,7,9,11,5,1] inf) ,(K_param "pan",pwhite 'α' (1.0) 1.0 inf) ,(K_param "cut",pxrand 'β' [1000,500,2000,300] inf) ,(K_param "res",pwhite 'γ' 0.3 1.0 inf) ,(K_amp,0.2)])
A persistent synthesis node with freq and amp controls.
import Sound.SC3.ID
let {freq = control KR "freq" 440 ;amp = control KR "amp" 0.6 ;n = pinkNoise 'α' AR * amp} in audition (out 0 (pan2 (moogFF n freq 2 0) 0 1))
A pattern to set freq and amp controls at the most recently instantiated synthesis node.
:set XOverloadedStrings
audition (pbind [(K_type,prepeat "n_set") ,(K_id,(1)) ,(K_freq,pwhite 'α' 100 1000 inf) ,(K_dur,0.2) ,(K_amp,toP [1,0.99 .. 0.1])])
let berlinb = let {k = control KR ;o = k "out" 0 ;f = k "freq" 80 ;a = k "amp" 0.01 ;p = k "pan" 0 ;g = k "gate" 1 ;env = decay2 g 0.05 8 * 0.0003 ;syn = rlpf (lfPulse AR f 0 (sinOsc KR 0.12 (mce2 0 (pi/2)) * 0.48 + 0.5)) (f * (sinOsc KR 0.21 0 * 18 + 20)) 0.07 ;syn_env = syn * env ;kil = detectSilence (mceChannel 0 syn_env) 0.1 0.2 RemoveSynth} in mrg2 (out o (a * mix (panAz 4 syn_env (mce2 p (p + 1)) 1 2 0.5))) kil
audition (ppar [pbind [(K_degree,pseq [0,1,2,4,6,3,4,8] inf) ,(K_dur,0.5) ,(K_octave,3) ,(K_instr,psynth (synthdef "berlinb" berlinb))] ,pbind [(K_degree,pseq [0,1,2,4,6,3,4,8] inf) ,(K_dur,0.5) ,(K_octave,pmce2 2 1) ,(K_param "pan",pwhite 'a' (1) 1 inf) ,(K_instr,psynth (synthdef "berlinb" berlinb))]])
pkey :: Key > P Event > P FieldSource
Pkey. SC3 pattern to read Key
at Event
pattern. Note
however that in haskell is usually more appropriate to name the
pattern using let.
pkey K_freq (pbind [(K_freq,return 440)]) == toP [440] pkey K_amp (pbind [(K_amp,toP [0,1])]) == toP [0,1]
> Pbind(\degree,Pseq([Pseries(7,1,14),Pseries(7,1,14)],inf), > \dur,0.25, > \legato,Pkey(\degree).linexp(7,7,2.0,0.05)).play
let {d = pseq [pseries (7) 1 14,pseries 7 (1) 14] inf ;l = fmap (Sound.SC3.Lang.Math.linexp (7) 7 2 0.05) d} in audition (pbind [(K_degree,d) ,(K_dur,0.25) ,(K_legato,l)])
pmono :: [P_Bind] > P EventSource
Pmono. SC3 pattern that is a variant of pbind
for controlling
monophonic (persistent) synthesiser nodes.
let p = [(K_instr,pinstr' (Instr_Ref "default" False)) ,(K_id,100) ,(K_degree,pxrand 'α' [0,2,4,5,7,9,11] inf) ,(K_amp,pwrand 'β' [0.05,0.2] [0.7,0.3] inf) ,(K_dur,0.25)] in audition (pmono p)
pmul :: P_Bind > P Event > P EventSource
Pmul. SC3 pattern to multiply an existing key by a value, or set the key if it doesn't exist.
let p = pbind [(K_dur,0.15),(K_freq,prand 'α' [440,550,660] 6)] in audition (pseq [p,pmul (K_freq,2) p,pmul (K_freq,0.5) p] 2)
ppar :: [P Event] > P EventSource
Ppar. Variant of ptpar
with zero start times.
The result of pmerge
can be merged again, ppar
merges a list of
patterns.
let {a = pbind [(K_param "a",pseq [1,2,3] inf)] ;b = pbind [(K_param "b",pseq [4,5,6] inf)] ;r = toP [e_from_list [(K_param "a",1),(K_fwd',0)] ,e_from_list [(K_param "b",4),(K_fwd',1)]]} in ptake 2 (ppar [a,b]) == r
let {p = pbind [(K_dur,0.2),(K_midinote,pseq [62,65,69,72] inf)] ;q = pbind [(K_dur,0.4),(K_midinote,pseq [50,45] inf)] ;r = pbind [(K_dur,0.6),(K_midinote,pseq [76,79,81] inf)]} in audition (ppar [p,q,r])
Multiple nested ppar
patterns.
let {a u = pbind [(K_dur,0.2),(K_param "pan",0.5),(K_midinote,pseq u 1)] ;b l = pbind [(K_dur,0.4),(K_param "pan",0.5),(K_midinote,pseq l 1)] ;f u l = ppar [a u,b l] ;h = pbind [(K_dur,prand 'α' [0.2,0.4,0.6] inf) ,(K_midinote,prand 'β' [72,74,76,77,79,81] inf) ,(K_db,26) ,(K_legato,1.1)] ;m = pseq [pbind [(K_dur,3.2),(K_freq,return nan)] ,prand 'γ' [f [60,64,67,64] [48,43] ,f [62,65,69,65] [50,45] ,f [64,67,71,67] [52,47]] 12] inf} in audition (ppar [h,m])
ptpar :: [(Time, P Event)] > P EventSource
Ptpar. Merge a set of Event
patterns each with indicated
 start Time
.
ptpar
is a variant of ppar
which allows nonequal start times.
let {f d p n = pbind [(K_dur,d),(K_param "pan",p),(K_midinote,n)] ;a = f 0.2 (1) (pseries 60 1 15) ;b = f 0.15 0 (pseries 58 2 15) ;c = f 0.1 1 (pseries 46 3 15)} in audition (ptpar [(0,a),(1,b),(2,c)])
let {d = pseq [pgeom 0.05 1.1 24,pgeom 0.5 0.909 24] 2 ;f n a p = pbind [(K_dur,d) ,(K_db,a) ,(K_param "pan",p) ,(K_midinote,pseq [n,n4] inf)]} in audition (ptpar [(0,f 53 (20) (0.9)) ,(2,f 60 (23) (0.3)) ,(4,f 67 (26) 0.3) ,(6,f 74 (29) 0.9)])
Instrument Event Patterns
pinstr' :: Instr > P FieldSource
Pattern from Instr
. An Instr
is either a Synthdef
or a
name. In the Synthdef
case the instrument is asynchronously
sent to the server before processing the event, which has timing
implications. The pattern constructed here uses the Synthdef
for
the first element, and the subsequently the name.
audition (pbind [(K_instr,pinstr' defaultInstr) ,(K_degree,toP [0,2,4,7]) ,(K_dur,0.25)])
pinstr :: String > P FieldSource
Instr
pattern from instrument name. See also psynth
(where
the sine instrument below is defined).
let {si = return (F_Instr (Instr_Ref "sine" True)) ;di = return (F_Instr (Instr_Ref "default" True)) ;i = pseq [si,si,di] inf ;p = pbind [(K_instr,i),(K_degree,pseq [0,2,4,7] inf),(K_dur,0.25)]} in audition p
psynth :: Synthdef > P FieldSource
Synthdef
s can be used directly as an instrument using psynth
.
The default synthdef is at def
.
let sineSynth = let {f = control KR "freq" 440 ;g = control KR "gate" 1 ;a = control KR "amp" 0.1 ;d = envASR 0.01 1 1 (EnvNum (4)) ;e = envGen KR g a 0 1 RemoveSynth d ;o = out 0 (sinOsc AR f 0 * e)} in synthdef "sine" o
audition (pbind [(K_instr,psynth sineSynth) ,(K_degree,toP [0,2,4,7]) ,(K_dur,0.25)])
MCE Patterns
pmce2 :: P Field > P Field > P FieldSource
Twochannel MCE for field patterns.
pmce2 (toP [1,2]) (toP [3,4]) == toP [f_array [1,3],f_array [2,4]]
let p = pmce2 (pseq [1,2] inf) (pseq [3,4] inf) in ptake 2 p == toP [f_array [1,3],f_array [2,4]]
p_un_mce :: P Event > P EventSource
Remove one layer of MCE expansion at an event pattern. The pattern will be expanded only to the width of the initial input. Holes are filled with rests.
let {a = pseq [65,69,74] inf ;b = pseq [60,64,67,72,76] inf ;c = pseq [pmce3 72 76 79,pmce2 a b] 1} in audition (p_un_mce (pbind [(K_midinote,c) ,(K_param "pan",pmce2 (1) 1) ,(K_dur,1 `pcons` prepeat 0.15)]))
p_un_mce
translates via ppar
. This allows dur
related fields to
be MCE values. The underlying event processor also implements one
layer of MCE expansion.
audition (p_un_mce (pbind [(K_dur,pmce2 0.25 0.2525) ,(K_legato,pmce2 0.25 2.5) ,(K_freq,pmce2 (pseq [300,400,500] inf) (pseq [302,402,502,202] inf)) ,(K_param "pan",pmce2 (0.5) 0.5)]))
NonSC3 Event Patterns
p_time :: P Event > P TimeSource
Pattern of start times of events at event pattern.
p_time (pbind [(K_dur,toP [1,2,3,2,1])]) == toP [0,1,3,6,8,9] p_time (pbind [(K_dur,pseries 0.5 0.5 5)]) == toP [0,0.5,1.5,3,5,7.5]
Aliases
pfoldr :: (a > b > b) > b > P a > bSource
Type specialised foldr
.
> (Pser([1,2,3],5) + Pseq([0,10],3)).asStream.all == [1,12,3,11,2]
let p = pser [1,2,3] 5 + pseq [0,10] 3 in F.foldr (:) [] p == [1,12,3,11,2]
Indefinte patterns may be folded.
take 3 (F.foldr (:) [] (prepeat 1)) == [1,1,1]
The Foldable
module includes functions for product
, sum
,
any
, elem
etc.
F.product (toP [1,3,5]) == 15 floor (F.sum (ptake 100 (pwhite 'α' 0.25 0.75 inf))) == 51 F.any even (toP [1,3,5]) == False F.elem 5 (toP [1,3,5]) == True
Type specialised join
.
join (replicate 2 [1,2]) == [1,2,1,2] join (preplicate 2 (toP [1,2])) == toP [1,2,1,2]
pjoin_repeat :: P (P a) > P aSource
pmbind :: P a > (a > P b) > P bSource
Type specialised >>=
.
(return 1 >>= return . id) == [1] (undecided 1 >>= undecided . id) == undecided 1
(pseq [1,2] 1 >>= \x > pseq [3,4,5] 1 >>= \y > return (x,y)) == toP [(1,3),(1,4),(1,5),(2,3),(2,4),(2,5)]
ptraverse :: Applicative f => (a > f b) > P a > f (P b)Source
Type specialised traverse
.
let {f i e = (i + e,e * 2) ;(r,p) = T.mapAccumL f 0 (toP [1,3,5])} in (r,p) == (9,toP [2,6,10])
NRT
Transform an event pattern into a nonreal time SC3 score.
let n = pNRT (pbind [(K_freq,prand 'α' [300,500,231.2,399.2] inf) ,(K_dur,pseq [0.1,0.2] 3)]) audition n mapM_ (putStrLn . bundlePP) (nrt_bundles n)
Infinite NRT
scores are productive for audition
ing.
let n' = pNRT (pbind [(K_dur,0.25),(K_freq,pseq [300,600,900] inf)]) audition n' mapM_ (putStrLn . bundlePP) (take 9 (nrt_bundles n'))