Randomness

This page will present you all the functions that can be used to introduce some randomness in your musical patterns. Each function will be presented following the same model:

• Type signature: how the function is declared on the Haskell side.
• Description: verbal description of the function.
• Examples: a small list of examples that you can copy/paste in your editor.

Pseudo-randomisation

rand

Type: rand :: Fractional a => Pattern a

rand is an oscillator that generates a pattern of (pseudo-)random, floating point numbers between 0.0 and 1.0. For example to randomly pan around the stereo field you can:

d1 $ sound "bd*8" # pan rand

Or to enjoy a randomised speed from 0.5 to 1.5, you can add 0.5 to it.

d1 $ sound "arpy*4" # speed (rand + 0.5)

irand

Type: irand :: Num a => Int -> Pattern a

irand is similar to rand, but generates a continuous oscillator of (pseudo-)random integers between 0 to n-1 inclusive. Notably used to pick random samples from a folder.

d1 $ sound "amencutup*8" # n (irand 8)

Perlin noise

perlin

Type: perlin :: Pattern Double

perlin produces 1D Perlin (smooth) noise. It works like rand but smoothly moves between random values each cycle. For example, you can smoothly and randomly change speed:

d1 $ sound "bd*32" # speed (perlin + 0.5)

The perlin function produces a new random value to move to every cycle. If you want a new random value to be generated more or less frequently, you can use fast or slow, respectively:

d1 $ sound "bd*32" # speed (fast 4 $ perlin + 0.5)
d1 $ sound "bd*32" # speed (slow 4 $ perlin + 0.5)

perlinWith

perlinWith allows you to specify a pattern as input to generate random values instead of using the default cycle count:

d1 $ s "arpy*32" # cutoff (perlinWith (saw * 4) * 2000)

perlin2

perlin2 creates 2D noise by allowing you to specify a custom pattern as a second dimension (cycle number remains as the first dimension):

d1 $ s "bd*32" # speed (perlin2 (sine*4) + 1)

perlin2With

perlin2With is the same as perlinWith except allows you to provide two functions for 2D noise:

d1
 $ s "[arpy*32]"
 # lpf (range 60 5000 $ perlin2With (cosine*2) (sine*2))
 # lpq 0.3

The "sometimes" family

sometimes

Type: sometimes :: (Pattern a -> Pattern a) -> Pattern a -> Pattern a

sometimes is function, that applies another function to a pattern, around 50% of the time, at random. It takes two inputs, the function to be applied, and the pattern you are applying it to.

For example to distort half the events in a pattern:

d1 $ sometimes (# crush 2) $ n "0 1 [~ 2] 3" # sound "arpy"

sometimes has a number of variants, which apply the function with different likelihood:

function	likelihood
always	100%
almostAlways	90%
often	75%
sometimes	50%
rarely	25%
almostNever	10%
never	0%

sometimesBy

If you want to be specific, you can use sometimesBy and a number, for example:

sometimesBy 0.93 (# speed 2)

to apply the speed control on average 93 times out of a hundred.

someCycles

someCycles is similar to sometimes, but instead of applying the given function to random events, it applies it to random cycles. For example the following will either distort all of the events in a cycle, or none of them:

d1 $ someCycles (# crush 2) $ n "0 1 [~ 2] 3" # sound "arpy"

someCyclesBy

As with sometimesBy, if you want to be specific, you can use someCyclesBy and a number. For example:

someCyclesBy 0.93 (# speed 2)

will apply the speed control on average 93 cycles out of a hundred.

Choosing randomly

choose

Type: choose :: [a] -> Pattern a

The choose function emits a stream of randomly choosen values from the given list, as a continuous pattern:

d1 $ sound "drum ~ drum drum" # n (choose [0,2,3])

As with all continuous patterns, you have to be careful to give them structure; in this case choose gives you an infinitely detailed stream of random choices.

chooseby

Type: chooseBy :: Pattern Double -> [a] -> Pattern a

The chooseBy function is like choose but instead of selecting elements of the list randomly, it uses the given pattern to select elements.

chooseBy "0 0.25 0.5" ["a","b","c","d"]

will result in the pattern "a b c" .

wchoose

Type: wchoose :: [(a, Double)] -> Pattern a

wchoose is similar to choose, but allows you to 'weight' the choices, so some are more likely to be chosen than others. The following is similar to the previous example, but the 2 is twice as likely to be chosen than the 0 or 3.

d1 $ sound "drum ~ drum drum" # n (wchoose [(0,0.25),(2,0.5),(3,0.25)])

caution

Prior to version 1.0.0 of Tidal, the weights had to add up to 1, but this is no longer the case.

wchooseby

Type: wchooseBy :: Pattern Double -> [(a,Double)] -> Pattern a

The wchooseBy function is like wchoose but instead of selecting elements of the list randomly, it uses the given pattern to select elements.

cycleChoose

Type: cycleChoose :: [a] -> Pattern a

Similar to choose, but only picks once per cycle:

d1 $ sound "drum ~ drum drum" # n (cycleChoose [0,2,3])

markovPat

Type: markovPat :: Pattern Int -> Pattern Int -> [[Double]] -> Pattern Int

markovPat is a way to generate (pseudo-)random patterns based on Markov chains. Rather than a predefined pattern, a Markov chain is a predefined sequence of probabilities. These probabilities govern the transitions from one step to another. This gives you direct control over the randomness of the pattern that is generated. markovPat takes three arguments: the sequence length, the index of the starting step, and a matrix of probabilities.

First, identify the values for each state. For example, if you want to sequence three sounds bd, sd, and clap:

d1 $ s (fmap (["bd", "sd", "clap"]!!)
     $ -- the Markov chains will go here
)

With this mapping, "bd" has an index of 0, "sd" has an index of 1, and "clap" has an index of 2. Note that you can include rests by including "~" as one of the sounds.

Next, define the probability that each step will transition to each other step. Note, the values will be normalized, so they don't need to add up to 1.

Current Step	bd [0]	sd [1]	clap [2]
bd	0.1	0.7	0.2
sd	0.15	0.1	0.8
clap	0.5	0.3	0.4

In the above example, bd will have a 10% chance to repeat another bd, a 70% chance to transition to a sd, and a 20% chance to transition to a clap. Add this to our pattern with a sequence length of 16 and a starting index of 0:

d1 $ s (fmap (["bd", "sd", "clap"]!!)
       $ markovPat 16 0 [
           [0.1,  0.7, 0.2],
           [0.15, 0.1, 0.8],
           [0.5,  0.3, 0.4]
         ] )

Like other sources of randomness, rhythmic structure can be added using functions such as mask.