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- #!/usr/bin/python2.5
- #
- # Copyright 2012 Olivier Gillet.
- #
- # Author: Olivier Gillet (ol.gillet@gmail.com)
- #
- # This program is free software: you can redistribute it and/or modify
- # it under the terms of the GNU General Public License as published by
- # the Free Software Foundation, either version 3 of the License, or
- # (at your option) any later version.
- # This program is distributed in the hope that it will be useful,
- # but WITHOUT ANY WARRANTY; without even the implied warranty of
- # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
- # GNU General Public License for more details.
- # You should have received a copy of the GNU General Public License
- # along with this program. If not, see <http://www.gnu.org/licenses/>.
- #
- # -----------------------------------------------------------------------------
- #
- # Waveshaper lookup tables.
-
- import numpy
-
- waveshapers = []
-
- def scale(x, min=-32766, max=32766, center=True):
- if center:
- x -= x.mean()
- mx = numpy.abs(x).max()
- x = (x + mx) / (2 * mx)
- x = x * (max - min) + min
- x = numpy.round(x)
- return x.astype(int)
-
-
- x = ((numpy.arange(0, 257) / 128.0 - 1.0))
- x[-1] = x[-2]
- violent_overdrive = numpy.tanh(8.0 * x)
- overdrive = numpy.tanh(5.0 * x)
- moderate_overdrive = numpy.tanh(2.0 * x)
-
- # Wavefolder curves from the first version
- # tri_fold = numpy.abs(4.0 * x - numpy.round(4.0 * x)) * numpy.sign(x)
- # sine_fold = numpy.sin(5 * numpy.pi * x)
-
- tri_fold = numpy.sin(numpy.pi * (3 * x + (2 * x) ** 3))
-
- # In v1.4 RC
- window = numpy.exp(-x * x * 4) ** 1.5
- sine = numpy.sin(8 * numpy.pi * x)
- sine_fold = sine * window + numpy.arctan(3 * x) * (1 - window)
- sine_fold /= numpy.abs(sine_fold).max()
-
- # Another curve for the sine wavefolder inspired by the uFold response
- # frequency = 4 / (1 + (1.5 * x) ** 2) ** 2
- # window = numpy.exp(-24 * numpy.maximum(numpy.abs(x) - 0.25, 0) ** 2)
- # sine = numpy.sin(2 * numpy.pi * frequency * x) * window
- # cubic = (x ** 3 + 0.5 * x ** 2 + 0.5 * x) / 3
- # knee = numpy.minimum(x + 0.7, 0.0)
- # sine_fold = sine + cubic + knee
-
- waveshapers.append(('moderate_overdrive', scale(moderate_overdrive)))
- waveshapers.append(('violent_overdrive', scale(violent_overdrive)))
- waveshapers.append(('sine_fold', scale(sine_fold, center=False)))
- waveshapers.append(('tri_fold', scale(tri_fold)))
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