tomwalters@305: // Copyright 2010, Thomas Walters
tomwalters@305: //
tomwalters@305: // AIM-C: A C++ implementation of the Auditory Image Model
tomwalters@305: // http://www.acousticscale.org/AIMC
tomwalters@305: //
tomwalters@318: // Licensed under the Apache License, Version 2.0 (the "License");
tomwalters@318: // you may not use this file except in compliance with the License.
tomwalters@318: // You may obtain a copy of the License at
tomwalters@305: //
tomwalters@318: //     http://www.apache.org/licenses/LICENSE-2.0
tomwalters@305: //
tomwalters@318: // Unless required by applicable law or agreed to in writing, software
tomwalters@318: // distributed under the License is distributed on an "AS IS" BASIS,
tomwalters@318: // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
tomwalters@318: // See the License for the specific language governing permissions and
tomwalters@318: // limitations under the License.
tomwalters@305: 
tomwalters@305: /*!
tomwalters@305:  * \author Thomas Walters <tom@acousticscale.org>
tomwalters@305:  * \date created 2010/02/24
tomwalters@305:  * \version \$Id$
tomwalters@305:  */
tomwalters@305: 
tomwalters@305: // Use the boost RNGs to generate Gaussian noise
tomwalters@305: #include <boost/random.hpp>
tomwalters@305: #include <math.h>
tomwalters@305: 
tomwalters@305: #include "Modules/SNR/ModuleNoise.h"
tomwalters@305: 
tomwalters@305: namespace aimc {
tomwalters@305: ModuleNoise::ModuleNoise(Parameters *params) :
tomwalters@305:     Module(params),
tomwalters@305:     gaussian_variate_(boost::mt19937(),
tomwalters@305:                       boost::normal_distribution<float>(0.0f, 1.0f)) {
tomwalters@305:   module_description_ = "Adds noise to a signal";
tomwalters@305:   module_identifier_ = "noise";
tomwalters@305:   module_type_ = "snr";
tomwalters@305:   module_version_ = "$Id$";
tomwalters@305: 
tomwalters@365:   pink_ = parameters_->DefaultBool("noise.pink", true);
tomwalters@305:   // Noise level relative to unit-variance Gaussian noise (ie. 0dB will give a
tomwalters@305:   // noise with an RMS level of 1.0)
tomwalters@305:   float snr_db = parameters_->DefaultFloat("noise.level_db", 0.0f);
tomwalters@305:   multiplier_ = pow(10.0f, snr_db / 20.0f);
tomwalters@305: }
tomwalters@305: 
tomwalters@305: ModuleNoise::~ModuleNoise() {
tomwalters@305: }
tomwalters@305: 
tomwalters@305: bool ModuleNoise::InitializeInternal(const SignalBank &input) {
tomwalters@305:   // Copy the parameters of the input signal bank into internal variables, so
tomwalters@305:   // that they can be checked later.
tomwalters@305:   sample_rate_ = input.sample_rate();
tomwalters@305:   buffer_length_ = input.buffer_length();
tomwalters@305:   channel_count_ = input.channel_count();
tomwalters@305: 
tomwalters@305:   output_.Initialize(input);
tomwalters@365:   ResetInternal();
tomwalters@305:   return true;
tomwalters@305: }
tomwalters@305: 
tomwalters@305: void ModuleNoise::ResetInternal() {
tomwalters@365:   s0_ = 0.0f;
tomwalters@365:   s1_ = 0.0f;
tomwalters@365:   s2_ = 0.0f;
tomwalters@305: }
tomwalters@305: 
tomwalters@305: void ModuleNoise::Process(const SignalBank &input) {
tomwalters@305:   // Check to see if the module has been initialized. If not, processing
tomwalters@305:   // should not continue.
tomwalters@305:   if (!initialized_) {
tomwalters@305:     LOG_ERROR(_T("Module %s not initialized."), module_identifier_.c_str());
tomwalters@305:     return;
tomwalters@305:   }
tomwalters@305: 
tomwalters@305:   // Check that ths input this time is the same as the input passed to
tomwalters@305:   // Initialize()
tomwalters@305:   if (buffer_length_ != input.buffer_length()
tomwalters@305:       || channel_count_ != input.channel_count()) {
tomwalters@305:     LOG_ERROR(_T("Mismatch between input to Initialize() and input to "
tomwalters@305:                  "Process() in module %s."), module_identifier_.c_str());
tomwalters@305:     return;
tomwalters@305:   }
tomwalters@305: 
tomwalters@305:   for (int c = 0; c < input.channel_count(); ++c) {
tomwalters@305:     for (int i = 0; i < input.buffer_length(); ++i) {
tomwalters@305:       float s = input[c][i];
tomwalters@365:       float n =  gaussian_variate_();
tomwalters@365:       if (pink_) {
tomwalters@365:         // Pink noise filter coefficients from 
tomwalters@365:         // ccrma.stanford.edu/~jos/sasp/Example_Synthesis_1_F_Noise.html
tomwalters@365:         // Smith, Julius O. Spectral Audio Signal Processing, October 2008
tomwalters@365:         // Draft, http://ccrma.stanford.edu/~jos/sasp/, online book, 
tomwalters@365:         // accessed 2010-02-27.
tomwalters@365:         float f = 0.049922035 * n + s0_;
tomwalters@365:         s0_ = -0.095993537 * n - (-2.494956002 * f) + s1_;
tomwalters@365:         s1_ = 0.050612699 * n - (2.017265875 * f) + s2_;
tomwalters@365:         s2_ = -0.004408786 * n - (-0.522189400 * f);
tomwalters@365:         n = f;
tomwalters@365:       }
tomwalters@365:       s += multiplier_ * n;
tomwalters@305:       output_.set_sample(c, i, s);
tomwalters@305:     }
tomwalters@305:   }
tomwalters@305:   PushOutput();
tomwalters@305: }
tomwalters@305: }  // namespace aimc
tomwalters@305: