music.pan_transitions¶

music.pan_transitions(p=((1, 1), (1, 0), (0, 1), (1, 1)), d=(2, 2, 2), method=('lin', 'circ', 'exp'), sample_rate=44100, sonic_vector=None)[source]¶

Applies pan transitions to a sonic vector.

Parameters:

plist of tuples, optional: List of pan positions, where each tuple represents the amplitude envelope of each channel, by default [(1,1),(1,0),(0,1),(1,1)]
dlist, optional: List of durations for each transition, by default [2,2,2]
methodlist, optional: List of pan transition methods, by default [‘lin’,’circ’,’exp’]
sample_rateint, optional: Sample rate of the audio, by default 44100
sonic_vectorndarray, optional: Input sonic vector, by default None

Returns:

ndarray: Stereo audio signal with pan transitions applied.

Notes

Each pan transition i starts and ends amplitude envelope of channel c in p[i][c] and p[i+1][c].

Consider only one of such fades to understand the pan transition methods:

'lin' fades linearly in and out:
    x*k_i+y*(1-k_i)
    or
    s1_i*x_i +s2_i*(1-x_i) = (s1-s2)*x_i + s_2
'circ' keeps amplitude one using
    cos(x)**2 + sin(y)**2 = 1
'exp' makes the cross_fade using exponentials.

‘exp’ entails linear loudness variation for each channel, but total loudness is not preserved because final amplitude’s ambit is not preserved. ‘lin’ and ‘circ’, on the other hand, preserve total loudness but does not provide a linear variation of loudness for each sound on the cross-fade.

For now, each channel’s signal are kept from mixing. One immediate possibility is to maintain the expected tessiture of the sample amplitudes. Say p = [.5,1,0,.5] ~ [(1,1),(1,0),(0,1),(1,1)]. Then pi,pj = .5,1 might be performed as:

s1 = s1*.5 -> 0
s2 = s1*.5 -> (s1+s2)*.5

Or through sinusoids and expotentials

Make fast and slow fades and parameter transitions using weber-fechner and steven’s laws. E.g.:

pitch_trans = [pitch0*X**(i/Y) for i in range(12)]
pitch_trans = [pitch0 + X*i**Y for i in range(12)]

Examples

>>> p = [(0, 1), (1, 0), (0, 1), (1, 1)]
>>> d = [2, 2, 2]
>>> method = ['lin', 'circ', 'exp']
>>> sonic_vector = np.random.rand(2, 44100 * 6)  # Random stereo signal
>>> result = pan_transitions(p, d, method, sonic_vector=sonic_vector)