-
Notifications
You must be signed in to change notification settings - Fork 0
/
effects.py
200 lines (146 loc) · 5.34 KB
/
effects.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
import time
import numpy as np
import scipy.signal as signal
import scipy.io.wavfile
import scipy.stats as stats
from global_vars import *
from utils import *
"""
All effects must implement:
get_effected_signal(signal)
set_params(**kwargs)
"""
class LowpassFilter(object):
pass_band_loss = 1 # max loss in passing band (dB)
stop_band_loss = 30 # min loss in stopping band (dB)
def __init__(self, cut_off_freq=1000):
self.a = 0.
self.b = 0.
self.set_params(cut_off_freq=cut_off_freq)
def get_effected_signal(self, sig):
return signal.lfilter(self.b, self.a, sig)
def set_params(self, **kwargs):
f = kwargs['cut_off_freq']
normalized_pass = f/(RATE*.5)
normalized_stop = (f+.3*f)/(RATE*.5)
(self.b, self.a) = signal.iirdesign(normalized_pass, normalized_stop,
LowpassFilter.pass_band_loss,
LowpassFilter.stop_band_loss)
class Wah(object):
pass_band_loss = 1 # max loss in passing band (dB)
stop_band_loss = 30 # min loss in stopping band (dB)
def __init__(self, cut_off_freq=600, osc_freq=2):
self.it = 0
self.set_params(cut_off_freq=cut_off_freq, osc_freq=osc_freq)
def get_effected_signal(self, sig):
if self.it >= 1000:
self.it = 0
freq = self.f + self.sin_wave[self.it]
self.it += 1
normalized_pass = freq/(RATE*.5)
normalized_stop = (freq+.3*freq)/(RATE*.5)
(a, b) = signal.iirdesign(normalized_pass, normalized_stop, 1, 30)
out = signal.lfilter(b, a, sig)
return out / np.max(out)
def set_params(self, **kwargs):
self.osc_freq = kwargs['osc_freq']
self.f = kwargs['cut_off_freq']
self.sin_wave = (self.f / 4) * np.sin(np.linspace(0,
self.osc_freq * 2 * np.pi, num=1000, endpoint=True))
self.sin_wave = np.roll(self.sin_wave, -self.it).astype(int)
self.it = 0
class Delay(object):
def __init__(self, predelay=512, wet=8, decay=0.25):
self.set_params(predelay=predelay, wet=wet, decay=decay)
def reverb(self, signal):
if self.iterations == self.wet:
self.iterations = 0
return np.zeros(BUFFER_SIZE)
else:
out = np.roll(signal, self.predelay // (2 ** self.iterations))
out[0 : self.predelay] = 0
self.iterations += 1
out += (self.reverb(out) * self.decay)
#print out
return out
def get_effected_signal(self, signal):
return self.reverb(signal) + (signal * (self.decay / (2 ** self.wet)))
def set_params(self, **kwargs):
self.predelay = kwargs['predelay']
self.wet = kwargs['wet']
self.decay = kwargs['decay']
self.iterations = 0
class SciFiDelay(object):
def __init__(self, sampleDelay=512, ratio=0.75):
self.set_params(sampleDelay=sampleDelay, ratio=ratio)
def get_effected_signal(self, signal):
chunk = signal[0 : self.nSamples]
delay = np.zeros(BUFFER_SIZE)
starts = (np.arange(self.echoes) + 1) * self.sampleDelay
slices = np.array([starts, starts + self.nSamples])
for i in range(self.echoes):
delay[slices[0,i] : slices[1,i]] = chunk * (self.echoes - i)
return signal + delay
def set_params(self, **kwargs):
self.sampleDelay = kwargs['sampleDelay']
self.ratio = kwargs['ratio']
self.nSamples = 256
self.echoes = (BUFFER_SIZE // sampleDelay) - 1
class Chorus(object):
def __init__(self, phase1=0.1, phase2=0.75):
self.set_params(phase1=phase1, phase2=phase2)
def get_effected_signal(self, signal):
return 0.5 * signal * (1 + self.mod1 + self.mod2)
def set_params(self, **kwargs):
self.phase1 = kwargs['phase1']
self.phase2 = kwargs['phase2']
self.mod1 = np.sin(np.linspace(0 + phase1, 10 * np.pi + phase1,
num=BUFFER_SIZE, endpoint=True))
self.mod2 = np.sin(np.linspace(0 + phase2, 10 * np.pi + phase2,
num=BUFFER_SIZE, endpoint=True))
class Tremolo(object):
def __init__(self, freq=2.5, intensity=1.0):
self.set_params(freq=freq, intensity=intensity)
def get_effected_signal(self, signal):
w = np.array(self.sin_wave)
while len(w) < len(signal):
w = np.append(w, self.sin_wave)
self.sin_wave = np.roll(self.sin_wave, len(w)-len(signal))
w = w[0:len(signal)]
return signal*w
def set_params(self, **kwargs):
freq = kwargs['freq']
intensity = kwargs['intensity']
self.length = RATE/freq
factor = float(freq) * np.pi * 2.0 / float(RATE)
self.sin_wave = np.sin(np.arange(self.length) * factor)
self.sin_wave = np.absolute(self.sin_wave)
self.sin_wave = self.sin_wave*intensity
self.sin_wave = self.sin_wave + (1-intensity)
class Harmonizer(object):
def __init__(self, interval='fourth', wetness=.8):
self.set_params(interval=interval, wetness=wetness)
def get_effected_signal(self, signal):
signal = signal + self.wetness*pitch_shift(signal,
self.interval)
return signal
def set_params(self, **kwargs):
self.interval = kwargs['interval']
self.wetness = kwargs['wetness']
class Popcorn(object):
def __init__(self, speed=500):
self.set_params(speed=speed)
def get_effected_signal(self, signal):
shifted = np.roll(signal, int(100 * np.sin(time.clock() * self.speed)))
return signal + shifted
def set_params(self, **kwargs):
self.speed = kwargs['speed']
self.phase = time.clock() * self.speed
class Distortion(object):
def __init__(self, threshold=.1):
self.set_params(threshold=threshold)
def get_effected_signal(self, signal):
signal = stats.threshold(signal, -self.threshold, self.threshold)
return (1.0/float(self.threshold))*signal
def set_params(self, **kwargs):
self.threshold = kwargs['threshold']