"""
03-fuzz-disto.py - Hand-written asymmetrical tranfert function.

This example implements a fuzz distortion. Bandpass filtered signal is
eavily boosted, then feeded to an asymmetrical transfert function, and
finally lowpass filtered to smooth out the sound. Balance between the
dry and the distorted sound is applied before sending the signal to the 
outputs.

Builtin objects to distort an audio signal:

    Disto, Clip, Mirror, Wrap

Degrade object applies some kind of distortion to a signal by changing
its sampling rate and bit depth. 

"""
from pyo import *

s = Server(duplex=0).boot()

# The audio source (try with your own sounds).
SOURCE = "../snds/flute.aif"

# Distortion parameters
BP_CENTER_FREQ = 400  # Bandpass filter center frequency.
BP_Q = 3  # Bandpass Q (center_freq / Q = bandwidth).
BOOST = 25  # Pre-boost (linear gain).
LP_CUTOFF_FREQ = 3000  # Lowpass filter cutoff frequency.
BALANCE = 0.7  # Balance dry - wet.

src = SfPlayer(SOURCE, loop=True).mix(2)

# The transfert function is build in two phases.

# 1. Transfert function for signal lower than 0.
table = ExpTable([(0, -0.25), (4096, 0), (8192, 0)], exp=30)

# 2. Transfert function for signal higher than 0.
# First, create an exponential function from 1 (at the beginning of the table)
# to 0 (in the middle of the table).
high_table = ExpTable([(0, 1), (2000, 1), (4096, 0), (4598, 0), (8192, 0)], exp=5, inverse=False)
# Then, reverse the table’s data in time, to put the shape in the second
# part of the table.
high_table.reverse()

# Finally, add the second table to the first, point by point.
table.add(high_table)

# Show the transfert function.
table.view(title="Transfert function")

# Bandpass filter and boost gain applied on input signal.
bp = ButBP(src, freq=BP_CENTER_FREQ, q=BP_Q)
boost = Sig(bp, mul=BOOST)

# Apply the transfert function.
sig = Lookup(table, boost)

# Lowpass filter on the distorted signal.
lp = ButLP(sig, freq=LP_CUTOFF_FREQ, mul=0.7)

# Balance between dry and wet signals.
mixed = Interp(src, lp, interp=BALANCE)

# Send the signal to the outputs.
out = (mixed * 0.3).out()

# Show the resulting waveform.
sc = Scope(mixed)

s.gui(locals())