Conversions

midiToHz

midiToHz(x)

Converts a midi note value to frequency in Hertz.

Args
x: int or float

Midi note. x can be a number, a list or a tuple, otherwise the function returns None.

>>> a = (48, 60, 62, 67)
>>> b = midiToHz(a)
>>> print(b)
(130.8127826503271, 261.62556530066814, 293.66476791748823, 391.9954359818656)
>>> a = [48, 60, 62, 67]
>>> b = midiToHz(a)
>>> print(b)
[130.8127826503271, 261.62556530066814, 293.66476791748823, 391.9954359818656]
>>> b = midiToHz(60.0)
>>> print(b)
261.625565301

midiToTranspo

midiToTranspo(x)

Converts a midi note value to transposition factor (central key = 60).

Args
x: int or float

Midi note. x can be a number, a list or a tuple, otherwise the function returns None.

>>> a = (48, 60, 62, 67)
>>> b = midiToTranspo(a)
>>> print(b)
    (0.49999999999997335, 1.0, 1.122462048309383, 1.4983070768767281)
>>> a = [48, 60, 62, 67]
>>> b = midiToTranspo(a)
>>> print(b)
[0.49999999999997335, 1.0, 1.122462048309383, 1.4983070768767281]
>>> b = midiToTranspo(60.0)
>>> print(b)
1.0

sampsToSec

sampsToSec(x)

Returns the duration in seconds equivalent to the number of samples given as an argument.

Args
x: int or float

Duration in samples. x can be a number, a list or a tuple, otherwise function returns None.

>>> s = Server().boot()
>>> a = (64, 128, 256)
>>> b = sampsToSec(a)
>>> print(b)
(0.0014512471655328798, 0.0029024943310657597, 0.0058049886621315194)
>>> a = [64, 128, 256]
>>> b = sampsToSec(a)
>>> print(b)
[0.0014512471655328798, 0.0029024943310657597, 0.0058049886621315194]
>>> b = sampsToSec(8192)
>>> print(b)
0.185759637188

secToSamps

secToSamps(x)

Returns the number of samples equivalent to the duration in seconds given as an argument.

Args
x: int or float

Duration in seconds. x can be a number, a list or a tuple, otherwise function returns None.

>>> s = Server().boot()
>>> a = (0.1, 0.25, 0.5, 1)
>>> b = secToSamps(a)
>>> print(b)
(4410, 11025, 22050, 44100)
>>> a = [0.1, 0.25, 0.5, 1]
>>> b = secToSamps(a)
>>> print(b)
[4410, 11025, 22050, 44100]
>>> b = secToSamps(2.5)
>>> print(b)
110250

beatToDur

beatToDur(beat, bpm=120)[source]

Converts a beat value (multiplier of a quarter note) to a duration in seconds.

Args
beat: float

Beat value, in multiplier of the quarter note, to convert, according to the BPM value, which gives the duration of the quarter note. For example, to retrieve the duration of the sixteenth note, for a BPM of 90, we would write beatToDur(1/4, 90). beat can be a number, a list or a tuple.

bpm: float, optional

The beat-per-minute value, which gives the duration of the quarter note. Defaults to 120. bpm can be a number, a list or a tuple.

>>> bpm = 90
>>> # Duration of a sixteenth note.
>>> dur = beatToDur(1/4, 90)
>>> print(dur)
1.666666666666
>>> print(beatToDur(1/4, [60, 90, 120]))
[0.25, 0.166666666, 0.125]
>>> print(beatToDur(1/4, (60, 90, 120)))
(0.25, 0.166666666, 0.125)

linToCosCurve

linToCosCurve(data, yrange=[0, 1], totaldur=1, points=1024, log=False)

Creates a cosinus interpolated curve from a list of points.

A point is a tuple (or a list) of two floats, time and value.

Args
data: list of points

Set of points between which will be inserted interpolated segments.

yrange: list of 2 floats, optional

Minimum and maximum values on the Y axis. Defaults to [0., 1.].

totaldur: float, optional

X axis duration. Defaults to 1.

points: int, optional

Number of points in the output list. Defaults to 1024.

log: boolean, optional

Set this value to True if the Y axis has a logarithmic scale. Defaults to False

>>> s = Server().boot()
>>> a = [(0,0), (0.25, 1), (0.33, 1), (1,0)]
>>> b = linToCosCurve(a, yrange=[0, 1], totaldur=1, points=8192)
>>> t = DataTable(size=len(b), init=[x[1] for x in b])
>>> t.view()

rescale

rescale(data, xmin=0.0, xmax=1.0, ymin=0.0, ymax=1.0, xlog=False, ylog=False)

Converts values from an input range to an output range.

This function takes data in the range xmin - xmax and returns corresponding values in the range ymin - ymax.

data can be either a number or a list. Return value is of the same type as data with all values rescaled.

Argss
data: float or list of floats

Values to convert.

xmin: float, optional

Minimum value of the input range.

xmax: float, optional

Maximum value of the input range.

ymin: float, optional

Minimum value of the output range.

ymax: float, optional

Maximum value of the output range.

xlog: boolean, optional

Set this argument to True if the input range has a logarithmic scaling.

ylog: boolean, optional

Set this argument to True if the output range has a logarithmic scaling.

>>> a = 0.5
>>> b = rescale(a, 0, 1, 20, 20000, False, True)
>>> print(b)
632.453369141
>>> a = [0, .4, .8]
>>> b = rescale(a, 0, 1, 20, 20000, False, True)
>>> print(b)
[20.000001907348633, 316.97738647460938, 5023.7705078125]

floatmap

floatmap(x, min=0.0, max=1.0, exp=1.0)

Converts values from a 0-1 range to an output range.

This function takes data in the range 0 - 1 and returns corresponding values in the range min - max.

Argss
x: float

Value to convert, in the range 0 to 1.

min: float, optional

Minimum value of the output range. Defaults to 0.

max: float, optional

Maximum value of the output range. Defaults to 1.

exp: float, optional

Power factor (1 (default) is linear, les than 1 is logarithmic, greter than 1 is exponential).

>>> a = 0.5
>>> b = floatmap(a, 0, 1, 4)
>>> print(b)
0.0625

distanceToSegment

distanceToSegment(p, p1, p2, xmin=0.0, xmax=1.0, ymin=0.0, ymax=1.0, xlog=False, ylog=False)

Find the distance from a point to a line or line segment.

This function returns the shortest distance from a point to a line segment normalized between 0 and 1.

A point is a tuple (or a list) of two floats, time and value. p is the point for which to find the distance from line p1 to p2.

Args
p: list or tuple

Point for which to find the distance.

p1: list or tuple

First point of the segment.

p2: list or tuple

Second point of the segment.

xmin: float, optional

Minimum value on the X axis.

xmax: float, optional

Maximum value on the X axis.

ymin: float, optional

Minimum value on the Y axis.

ymax: float, optional

Maximum value on the Y axis.

xlog: boolean, optional

Set this argument to True if X axis has a logarithmic scaling.

ylog: boolean, optional

Set this argument to True if Y axis has a logarithmic scaling.

reducePoints

reducePoints(pointlist, tolerance=0.02)

Douglas-Peucker curve reduction algorithm.

This function receives a list of points as input and returns a simplified list by eliminating redundancies.

A point is a tuple (or a list) of two floats, time and value. A list of points looks like:

[ (0, 0), (0.1, 0.7), (0.2, 0.5), … ]

Args
pointlist: list of lists or list of tuples

List of points (time, value) to filter.

tolerance: float, optional

Normalized distance threshold under which a point is excluded from the list. Defaults to 0.02.