diff carfac/carfac_test.cc @ 626:586b0677aae8

Fourth revision of Alex Brandmeyer's C++ implementation. Fixed more style issues, changed AGC structures to vectors, replaced FloatArray2d with vector<FloatArray>, implemented first tests using GTest to verify coefficients and monaural output against Matlab values (stored in aimc/carfac/test_data/). To run tests, change the path stored in carfac_test.h in TEST_SRC_DIR. Added CARFAC_GenerateTestData to the Matlab branch, fixed stage indexing in CARFAC_Cross_Couple.m to reflect changes in AGCCoeffs and AGCState structs.

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/carfac/carfac_test.cc	Wed May 22 21:30:02 2013 +0000
@@ -0,0 +1,369 @@
+//
+//  carfac_test.cc
+//  CARFAC Open Source C++ Library
+//
+//  Created by Alex Brandmeyer on 5/22/13.
+//
+// This C++ file is part of an implementation of Lyon's cochlear model:
+// "Cascade of Asymmetric Resonators with Fast-Acting Compression"
+// to supplement Lyon's upcoming book "Human and Machine Hearing"
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "carfac_test.h"
+// Three helper functions are defined here for loading the test data generated
+// by the Matlab version of CARFAC.
+// This loads one-dimensional FloatArrays from single-column text files.
+FloatArray LoadTestData(const std::string filename, const int number_points) {
+  std::string fullfile = TEST_SRC_DIR + filename;
+  std::ifstream file(fullfile.c_str());
+  FPType myarray[number_points];
+  FloatArray output(number_points);
+  if (file.is_open()) {
+    for (int i = 0; i < number_points; ++i) {
+      file >> myarray[i];
+      output(i) = myarray[i];
+    }
+  }
+  return output;
+}
+
+// This loads two-dimensional FloatArrays from multi-column text files.
+std::vector<FloatArray> Load2dTestData(const std::string filename, const int rows,
+                            const int columns) {
+  std::string fullfile = TEST_SRC_DIR + filename;
+  std::ifstream file(fullfile.c_str());
+  FPType myarray[rows][columns];
+  std::vector<FloatArray> output;
+  output.resize(rows);
+  for (auto& timepoint : output) {
+    timepoint.resize(columns);
+  }
+  if (file.is_open()) {
+    for (int i = 0; i < rows; ++i) {
+      for (int j = 0; j < columns; ++j) {
+        file >> myarray[i][j];
+        output[i](j) = myarray[i][j];
+      }
+    }
+  }
+  return output;
+}
+
+// This loads two dimensional vectors of audio data using data generated in
+// Matlab using the wavread() function.
+std::vector<std::vector<float>> Load2dAudioVector(std::string filename,
+                                                  int timepoints,
+                                                  int channels) {
+  std::string fullfile = TEST_SRC_DIR + filename;
+  std::ifstream file(fullfile.c_str());
+  std::vector<std::vector<float>> output;
+  output.resize(channels);
+  for (auto& channel : output) {
+    channel.resize(timepoints);
+  }
+  if (file.is_open()) {
+    for (int i = 0; i < timepoints; ++i) {
+      for (int j = 0; j < channels; ++j) {
+        file >> output[j][i];
+      }
+    }
+  }
+  return output;
+}
+
+// The first test verifies that the resulting CAR coefficients are the same as
+// in Matlab when using the default CAR parameter set.
+TEST(CARFACTest, CARCoeffs_Test){
+  // These initialze the CAR Params and Coeffs objects needed for this test.
+  CARParams car_params;
+  CARCoeffs car_coeffs;
+  FPType fs = 22050.0;
+  // We calculate the pole frequencies and number of channels in the same way
+  // as in the CARFAC 'Design' method.
+  int n_ch = 0;
+  FPType pole_hz = car_params.first_pole_theta_ * fs / (2 * PI);
+  while (pole_hz > car_params.min_pole_hz_) {
+    n_ch++;
+    pole_hz = pole_hz - car_params.erb_per_step_ *
+    ERBHz(pole_hz, car_params.erb_break_freq_, car_params.erb_q_);
+  }
+  FloatArray pole_freqs(n_ch);
+  pole_hz = car_params.first_pole_theta_ * fs / (2 * PI);
+  for (int ch = 0; ch < n_ch; ++ch) {
+    pole_freqs(ch) = pole_hz;
+    pole_hz = pole_hz - car_params.erb_per_step_ *
+    ERBHz(pole_hz, car_params.erb_break_freq_, car_params.erb_q_);
+  }
+  // This initializes the CAR coeffecients object and runs the design method.
+  car_coeffs.Design(car_params, 22050, pole_freqs);
+  // Now we go through each set of coefficients to verify that the values are
+  // the same as in MATLAB.
+  std::string filename;
+  FloatArray output;
+  
+  ASSERT_EQ(car_coeffs.v_offset_, 0.04);
+  ASSERT_EQ(car_coeffs.velocity_scale_, 0.1);
+  
+  filename = "r1_coeffs.txt";
+  output = LoadTestData(filename, n_ch);
+  for (int i = 0; i < n_ch; ++i) {
+    ASSERT_NEAR(output(i), car_coeffs.r1_coeffs_(i), PRECISION_LEVEL);
+  }
+  
+  filename = "a0_coeffs.txt";
+  output = LoadTestData(filename, n_ch);
+  for (int i = 0; i < n_ch; ++i) {
+    ASSERT_NEAR(output(i), car_coeffs.a0_coeffs_(i), PRECISION_LEVEL);
+  }
+  
+  filename = "c0_coeffs.txt";
+  output = LoadTestData(filename, n_ch);
+  for (int i = 0; i < n_ch; ++i) {
+    ASSERT_NEAR(output(i), car_coeffs.c0_coeffs_(i), PRECISION_LEVEL);
+  }
+  
+  filename = "zr_coeffs.txt";
+  output = LoadTestData(filename, n_ch);
+  for (int i = 0; i < n_ch; ++i) {
+    ASSERT_NEAR(output(i), car_coeffs.zr_coeffs_(i), PRECISION_LEVEL);
+  }
+  
+  filename = "h_coeffs.txt";
+  output = LoadTestData(filename, n_ch);
+  for (int i = 0; i < n_ch; ++i) {
+    ASSERT_NEAR(output(i), car_coeffs.h_coeffs_(i), PRECISION_LEVEL);
+  }
+  
+  filename = "g0_coeffs.txt";
+  output = LoadTestData(filename, n_ch);
+  for (int i = 0; i < n_ch; ++i) {
+    ASSERT_NEAR(output(i), car_coeffs.g0_coeffs_(i), PRECISION_LEVEL);
+  }
+}
+
+// The second test verifies that the IHC coefficient calculations result in the
+// same set of values as in the Matlab version of the CARFAC.
+TEST(CARFACTest, IHCCoeffs_Test){
+  IHCParams ihc_params;
+  IHCCoeffs ihc_coeffs;
+  FPType fs = 22050.0;
+  ihc_coeffs.Design(ihc_params, fs);
+  
+  std::string filename = "ihc_coeffs.txt";
+  FloatArray output = LoadTestData(filename, 9);
+  
+  // The sequence of the individual coefficients is determined using the
+  // CARFAC_GenerateTestData() function in the Matlab version, with all of the
+  // parameters placed in a single output file for convenience.
+  bool just_hwr = output(0);
+  FPType lpf_coeff = output(1);
+  FPType out_rate = output(2);
+  FPType in_rate = output(3);
+  bool one_cap = output(4);
+  FPType output_gain = output(5);
+  FPType rest_output = output(6);
+  FPType rest_cap = output(7);
+  FPType ac_coeff = output(8);
+  
+  // Once we have the Matlab values initialized, we can compare them to the
+  // output of the IHCCoeffs 'Design' method.
+  ASSERT_EQ(just_hwr, ihc_coeffs.just_hwr_);
+  ASSERT_NEAR(lpf_coeff, ihc_coeffs.lpf_coeff_, PRECISION_LEVEL);
+  ASSERT_NEAR(out_rate, ihc_coeffs.out1_rate_, PRECISION_LEVEL);
+  ASSERT_NEAR(in_rate, ihc_coeffs.in1_rate_, PRECISION_LEVEL);
+  ASSERT_EQ(one_cap, ihc_coeffs.one_cap_);
+  ASSERT_NEAR(output_gain, ihc_coeffs.output_gain_, PRECISION_LEVEL);
+  ASSERT_NEAR(rest_output, ihc_coeffs.rest_output_, PRECISION_LEVEL);
+  ASSERT_NEAR(rest_cap, ihc_coeffs.rest_cap1_, PRECISION_LEVEL);
+  ASSERT_NEAR(ac_coeff, ihc_coeffs.ac_coeff_, PRECISION_LEVEL);
+}
+
+
+TEST(CARFACTest, AGCCoeffs_Test) {
+  AGCParams agc_params;
+  std::vector<AGCCoeffs> agc_coeffs;
+  std::vector<FloatArray> output;
+  output.resize(agc_params.n_stages_);
+  std::string filename = "agc_coeffs_1.txt";
+  output[0] = LoadTestData(filename, 14);
+  filename = "agc_coeffs_2.txt";
+  output[1] = LoadTestData(filename, 14);
+  filename = "agc_coeffs_3.txt";
+  output[2] = LoadTestData(filename, 14);
+  filename = "agc_coeffs_4.txt";
+  output[3] = LoadTestData(filename, 14);
+  agc_coeffs.resize(agc_params.n_stages_);
+  // We initialize the AGC stages in the same was as in Ear::Init.
+  FPType fs = 22050.0;
+  FPType previous_stage_gain = 0.0;
+  FPType decim = 1.0;
+  for (int stage = 0; stage < agc_params.n_stages_; ++stage) {
+    agc_coeffs[stage].Design(agc_params, stage, fs, previous_stage_gain, decim);
+    previous_stage_gain = agc_coeffs[stage].agc_gain_;
+    decim = agc_coeffs[stage].decim_;
+  }
+  // Now we run through the individual coefficients and verify that they're the
+  // same as in Matlab.
+  for (int stage = 0; stage < agc_params.n_stages_; ++stage) {
+    int n_agc_stages = output[stage](1);
+    FPType agc_stage_gain = output[stage](2);
+    int decimation = output[stage](3);
+    FPType agc_epsilon = output[stage](4);
+    FPType agc_polez1 = output[stage](5);
+    FPType agc_polez2 = output[stage](6);
+    int agc_spatial_iterations = output[stage](7);
+    FPType agc_spatial_fir_1 = output[stage](8);
+    FPType agc_spatial_fir_2 = output[stage](9);
+    FPType agc_spatial_fir_3 = output[stage](10);
+    int agc_spatial_n_taps = output[stage](11);
+    FPType agc_mix_coeffs = output[stage](12);
+    FPType detect_scale = output[stage](13);
+    
+    ASSERT_EQ(n_agc_stages, agc_coeffs[stage].n_agc_stages_);
+    ASSERT_NEAR(agc_stage_gain, agc_coeffs[stage].agc_stage_gain_,
+                PRECISION_LEVEL);
+    ASSERT_EQ(decimation, agc_coeffs[stage].decimation_);
+    ASSERT_NEAR(agc_epsilon, agc_coeffs[stage].agc_epsilon_, PRECISION_LEVEL);
+    ASSERT_NEAR(agc_polez1, agc_coeffs[stage].agc_pole_z1_, PRECISION_LEVEL);
+    ASSERT_NEAR(agc_polez2, agc_coeffs[stage].agc_pole_z2_, PRECISION_LEVEL);
+    ASSERT_EQ(agc_spatial_iterations,
+              agc_coeffs[stage].agc_spatial_iterations_);
+    ASSERT_NEAR(agc_spatial_fir_1, agc_coeffs[stage].agc_spatial_fir_[0],
+                PRECISION_LEVEL);
+    ASSERT_NEAR(agc_spatial_fir_2, agc_coeffs[stage].agc_spatial_fir_[1],
+                PRECISION_LEVEL);
+    ASSERT_EQ(agc_spatial_n_taps,
+              agc_coeffs[stage].agc_spatial_n_taps_);
+    ASSERT_NEAR(agc_spatial_fir_3, agc_coeffs[stage].agc_spatial_fir_[2],
+                PRECISION_LEVEL);
+    ASSERT_NEAR(agc_mix_coeffs, agc_coeffs[stage].agc_mix_coeffs_,
+                PRECISION_LEVEL);
+    
+    // The last stage will have the correct detect_scale_ value on the basis of
+    // the total gain accumlated over the stages.
+    if (stage == agc_params.n_stages_ - 1) {
+      ASSERT_NEAR(detect_scale, agc_coeffs[stage].detect_scale_,
+                  PRECISION_LEVEL);
+    }
+  }
+}
+
+// This test verifies the output of the C++ code relative to that of the Matlab
+// version using a single segment (441 samples) of audio from the "plan.wav"
+// file. The single-channel audio data and different output matrices from Matlab
+// are stored in text files and then read into 2d Eigen arrays (for now, this
+// should be changed to a vector of FloatArrays... TODO (alexbrandmeyer)). For
+// reference, see the CARFAC_GenerateTestData() function in the Matlab branch
+// of the repository.
+//
+// A single Ear object is used along with the code from CARFAC.RunSegment() to
+// evaluate the output of the CAR and IHC steps on a sample by sample basis
+// relative to the output read in from Matlab. The test passes with 11 degrees
+// of precision, with the Matlab data stored using 12 decimals.
+//
+// TODO (alexbrandmeyer): A subseqent version of this test will operate directly
+// on the CARFACOutput structure and will evaluate binaural data.
+TEST(CARFACTest, Monaural_Output_Test) {
+  std::string filename = "monaural_test_nap.txt";
+  std::vector<FloatArray> nap = Load2dTestData(filename, 441, 71);
+  filename = "monaural_test_bm.txt";
+  std::vector<FloatArray> bm = Load2dTestData(filename, 441, 71);
+  filename = "monaural_test_ohc.txt";
+  std::vector<FloatArray> ohc = Load2dTestData(filename, 441, 71);
+  filename = "monaural_test_agc.txt";
+  std::vector<FloatArray> agc = Load2dTestData(filename, 441, 71);
+  filename = "file_signal_monaural_test.txt";
+  std::vector<std::vector<float>> sound_data = Load2dAudioVector(filename, 441,
+                                                                 1);
+  // The number of timepoints is determined from the length of the audio
+  // segment.
+  int32_t n_timepoints = sound_data[0].size();
+  
+  CARParams car_params;
+  IHCParams ihc_params;
+  AGCParams agc_params;
+  FPType fs = 22050.0;
+  int n_ch = 0;
+  FPType pole_hz = car_params.first_pole_theta_ * fs / (2 * PI);
+  while (pole_hz > car_params.min_pole_hz_) {
+    n_ch++;
+    pole_hz = pole_hz - car_params.erb_per_step_ *
+    ERBHz(pole_hz, car_params.erb_break_freq_, car_params.erb_q_);
+  }
+  FloatArray pole_freqs(n_ch);
+  pole_hz = car_params.first_pole_theta_ * fs / (2 * PI);
+  for (int ch = 0; ch < n_ch; ++ch) {
+    pole_freqs(ch) = pole_hz;
+    pole_hz = pole_hz - car_params.erb_per_step_ *
+    ERBHz(pole_hz, car_params.erb_break_freq_, car_params.erb_q_);
+  }
+  
+  // This initializes the CARFAC object and runs the design method.
+  Ear ear;
+  ear.InitEar(n_ch, fs, pole_freqs, car_params, ihc_params, agc_params);
+  
+  CARFACOutput seg_output;
+  seg_output.InitOutput(1, n_ch, n_timepoints);
+  
+  // A nested loop structure is used to iterate through the individual samples
+  // for each ear (audio channel).
+  FloatArray car_out(n_ch);
+  FloatArray ihc_out(n_ch);
+  FloatArray matlab_car_out(n_ch);
+  FloatArray matlab_ihc_out(n_ch);
+  bool updated;  // This variable is used by the AGC stage.
+  for (int32_t i = 0; i < n_timepoints; ++i) {
+    int j = 0;
+    // First we create a reference to the current Ear object.
+    // This stores the audio sample currently being processed.
+    FPType input = sound_data[j][i];
+    // Now we apply the three stages of the model in sequence to the current
+    // audio sample.
+    ear.CARStep(input, &car_out);
+    matlab_car_out = bm[i];
+    // This step verifies that the ouput of the CAR step is the same at each
+    // timepoint and channel as that of the Matlab version.
+    for (int channel = 0; channel < n_ch; ++channel) {
+      FPType a = matlab_car_out(channel);
+      FPType b = car_out(channel);
+      ASSERT_NEAR(a, b, PRECISION_LEVEL);
+    }
+    ear.IHCStep(car_out, &ihc_out);
+    matlab_ihc_out = nap[i];
+    // This step verifies that the ouput of the IHC step is the same at each
+    // timepoint and channel as that of the Matlab version.
+    for (int channel = 0; channel < n_ch; ++channel) {
+      FPType a = matlab_ihc_out(channel);
+      FPType b = ihc_out(channel);
+      ASSERT_NEAR(a, b, PRECISION_LEVEL);
+    }
+    
+    updated = ear.AGCStep(ihc_out);
+    // These lines assign the output of the model for the current sample
+    // to the appropriate data members of the current ear in the output
+    // object.
+    seg_output.StoreNAPOutput(i, j, ihc_out);
+    seg_output.StoreBMOutput(i, j, car_out);
+    seg_output.StoreOHCOutput(i, j, ear.za_memory());
+    seg_output.StoreAGCOutput(i, j, ear.zb_memory());
+    if (updated) {
+      FloatArray undamping = 1 - ear.agc_memory(0);
+      // This updates the target stage gain for the new damping.
+      ear.set_dzb_memory((ear.zr_coeffs() * undamping - ear.zb_memory()) /
+                         ear.agc_decimation(0));
+      ear.set_dg_memory((ear.StageGValue(undamping) - ear.g_memory()) /
+                        ear.agc_decimation(0));
+    }
+  }
+}
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