def PDur(n, k, start=0, dur=0.25):
""" Returns the *actual* durations based on Euclidean rhythms (see PEuclid) where dur
is the length of each step.
e.g. `PDur(3, 8)` will return `P[0.75, 0.75, 0.5]` """
data = EuclidsAlgorithm(n, k)
count, seq = 1, []
for item in data[1:]:
if item == 1:
seq.append(count)
count = 1
else:
count += 1
seq.append(count)
pattern = Pattern(seq)
if start != 0:
pattern = pattern.rotate(int(start))
return pattern * dur
def __init__(self, s, dur=0.5):
character = []
durations = []
if type(s) is str:
s = Pattern().fromString(s)
dur = s.dur(dur)
self.data = []
for i, char in s.items():
# Recursively get rhythms
if isinstance(char, PGroup):
character += list(char)
durations += list(self.__class__(char, dur))
else:
character.append(char)
durations.append(dur)
# After recursive collection of durations, adjust for rests (spaces)
self.chars = []
for i, dur in enumerate(durations):
if character[i] == ' ' and i > 0:
self.data[-1] += dur
else:
self.data.append(dur)
self.chars.append(character[i])
def PSum(n, total, **kwargs):
"""
Returns a Pattern of length 'n' that sums to equal 'total'
```
e.g. PSum(3,8) -> P[3, 3, 2]
PSum(5,4) -> P[1, 0.75, 0.75, 0.75, 0.75]
```
"""
lim = kwargs.get("lim", 0.125)
data = [total + 1]
step = 1
while sum(data) > total:
data = [step for x in range(n)]
step *= 0.5
i = 0
while sum(data) < total and step >= lim:
if sum(data) + step > total:
step *= 0.5
else:
data[i % n] += step
i += 1
return Pattern(data)
def __init__(self, start, stop=None):
GeneratorPattern.__init__(self)
if hasattr(start, "__iter__"):
self.data = Pattern(start)
self.func = lambda index: random.choice(self.data)
else:
self.low = start if stop is not None else 0
self.high = stop if stop is not None else start
def PZip(pat1, pat2, *patN):
''' Creates a Pattern that 'zips' together multiple patterns. `PZip([0,1,2], [3,4])`
will create the Pattern `P[(0, 3), (1, 4), (2, 3), (0, 4), (1, 3), (2, 4)]` '''
l, p = [], []
for pat in [pat1, pat2] + list(patN):
p.append(P[pat])
l.append(len(p[-1]))
length = LCM(*l)
return Pattern([tuple(pat[i] for pat in p) for i in range(length)])
def PAlt(pat1, pat2, *patN):
''' Returns a Pattern generated by alternating the values in the given sequences '''
data = []
item = [asStream(p) for p in [pat1, pat2] + list(patN)]
size = LCM(*[len(i) for i in item])
for n in range(size):
for i in item:
data.append(modi(i, n))
return Pattern(data)
def PZip2(pat1, pat2, rule=lambda a, b: True):
''' Like `PZip` but only uses two Patterns. Zips together values if they satisfy the rule. '''
length = LCM(len(pat1), len(pat2))
data = []
i = 0
while i < length:
a, b = modi(pat1, i), modi(pat2, i)
if rule(a, b):
data.append((a, b))
i += 1
return Pattern(data)
def PPairs(seq, func=lambda n: 8 - n):
""" Laces a sequence with a second sequence obtained
by performing a function on the original. By default this is
`lambda n: 8 - n`. """
i = 0
data = []
for item in seq:
data.append(item)
data.append(func(item))
i += 1
if i >= MAX_SIZE:
break
return Pattern(data)
def __getitem__(self, args):
if hasattr(args, '__iter__'):
data = []
for item in args:
if type(item) is slice:
data.extend(sliceToRange(item))
else:
data.append(item)
elif type(args) is slice:
data = sliceToRange(args)
else:
data = args
return Pattern(data)
def PSine(n=16):
""" Returns values of one cycle of sine wave split into 'n' parts """
i = (2 * math.pi) / n
return Pattern([math.sin(i * j) for j in range(int(n))])
def PStretch(seq, size):
''' Returns 'seq' as a Pattern and looped until its length is 'size'
e.g. `PStretch([0,1,2], 5)` returns `P[0, 1, 2, 0, 1]` '''
return Pattern(seq).stretch(size)
def new_function(*args):
pat = Pattern()
for i in range(
LCM(*[len(arg) for arg in args if hasattr(arg, '__len__')])):
pat |= f(*[modi(arg, i) for arg in args])
return pat
def PShuf(seq):
''' PShuf(seq) -> Returns a shuffled version of seq'''
return Pattern(seq).shuffle()
def PStutter(seq, n=2):
""" PStutter(seq, n) -> Creates a pattern such that each item in the array is repeated n times (n can be a pattern) """
return Pattern(seq).stutter(n)
def PSq(a=1, b=2, c=3):
''' Returns a Pattern '''
return Pattern([x**b for x in range(a, a + c)])
def P10(n):
''' Returns an n-length Pattern of a randomly generated series of 1's and 0's '''
return Pattern([random.choice((0, 1)) for i in range(int(n))])
def PEuclid(n, k):
''' Returns the Euclidean rhythm which spreads 'n' pulses over 'k' steps as evenly as possible.
e.g. `PEuclid(3, 8)` will return `P[1, 0, 0, 1, 0, 0, 1, 0]` '''
return Pattern(EuclidsAlgorithm(n, k))
def PStep(n, value, default=0):
''' Returns a Pattern that every n-term is 'value' otherwise 'default' '''
return Pattern([default] * (n - 1) + [value])
def PTri(start, stop=None, step=None):
''' Returns a Pattern equivalent to `Pattern(range(start, stop, step)) with its reversed form appended.'''
rev_step = step if step is not None else 1
data = list(PRange(start, stop, step))
return Pattern(data + [item + rev_step for item in reversed(data)])
def PRange(start, stop=None, step=None):
''' Returns a Pattern equivalent to `Pattern(range(start, stop, step)) '''
return Pattern(
range(*[val for val in (start, stop, step) if val is not None]))
