view carfac/carfac_test.cc @ 648:1c2a5868f23a

Fix memory leak in CARFAC.

Also get rid of most uses of auto, which tend to hurt readability
unless the type name is particularly long, especially when it masks
pointers.

//
//  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.h"

#include <fstream>
#include <string>
#include <vector>

#include "gtest/gtest.h"

#include "agc.h"
#include "car.h"
#include "carfac_output.h"
#include "common.h"
#include "ihc.h"

using std::ifstream;
using std::ofstream;
using std::string;
using std::vector;

// This is the 'test_data' subdirectory of aimc/carfac that specifies where to
// locate the text files produced by 'CARFAC_GenerateTestData.m' for comparing
// the ouput of the Matlab version of CARFAC with this C++ version.
static const char* kTestSourceDir= "./test_data/";
// Here we specify the level to which the output should match (2 decimals).
static const float kPrecisionLevel = 1.0e-2;

// Three helper functions are defined here for loading the test data generated
// by the Matlab version of CARFAC.
// This loads one-dimensional ArrayXs from single-column text files.
void WriteNAPOutput(const CARFACOutput& output, const string filename,
                    int ear) {
  string fullfile = kTestSourceDir + filename;
  ofstream ofile(fullfile.c_str());
  int32_t num_timepoints = output.nap().size();
  int channels = output.nap()[0][0].size();
  if (ofile.is_open()) {
    for (int32_t i = 0; i < num_timepoints; ++i) {
      for (int j = 0; j < channels; ++j) {
        ofile << output.nap()[i][ear](j);
        if (j < channels - 1) {
          ofile << " ";
        }
      }
      ofile << "\n";
    }
  }
  ofile.close();
}

ArrayX LoadTestData(const string filename, const int number_points) {
  string fullfile = kTestSourceDir + filename;
  ifstream file(fullfile.c_str());
  FPType myarray[number_points];
  ArrayX output(number_points);
  if (file.is_open()) {
    for (int i = 0; i < number_points; ++i) {
      file >> myarray[i];
      output(i) = myarray[i];
    }
  }
  file.close();
  return output;
}

// This loads a vector of ArrayXs from multi-column text files.
vector<ArrayX> Load2dTestData(const string filename, const int rows,
                              const int columns) {
  string fullfile = kTestSourceDir + filename;
  ifstream file(fullfile.c_str());
  FPType myarray[rows][columns];
  vector<ArrayX> output;
  output.resize(rows);
  for (ArrayX& 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];
      }
    }
  }
  file.close();
  return output;
}

// This loads two dimensional vectors of audio data using data generated in
// Matlab using the wavread() function.
vector<vector<float>> Load2dAudioVector(string filename, int timepoints,
                                        int channels) {
  string fullfile = kTestSourceDir + filename;
  ifstream file(fullfile.c_str());
  vector<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];
      }
    }
  }
  file.close();
  return output;
}

TEST(CARFACTest, Binaural_Output_test) {
  int num_timepoints = 882;
  int num_channels = 71;
  int num_ears = 2;
  string filename = "binaural_test_nap1.txt";
  vector<ArrayX> nap1 = Load2dTestData(filename, num_timepoints, num_channels);
  filename = "binaural_test_bm1.txt";
  vector<ArrayX> bm1 = Load2dTestData(filename, num_timepoints, num_channels);
  filename = "binaural_test_nap2.txt";
  vector<ArrayX> nap2 = Load2dTestData(filename, num_timepoints, num_channels);
  filename = "binaural_test_bm2.txt";
  vector<ArrayX> bm2 = Load2dTestData(filename, num_timepoints, num_channels);
  filename = "file_signal_binaural_test.txt";
  vector<vector<float>> sound_data = Load2dAudioVector(filename, num_timepoints,
                                                       num_ears);
  CARParams car_params;
  IHCParams ihc_params;
  AGCParams agc_params;
  CARFAC mycf(num_ears, 22050, car_params, ihc_params, agc_params);
  CARFACOutput my_output(true, true, false, false);
  const bool kOpenLoop = false;
  const int length = sound_data[0].size();
  mycf.RunSegment(sound_data, 0, length, kOpenLoop, &my_output);
  filename = "cpp_nap_output_1_binaural_test.txt";
  WriteNAPOutput(my_output, filename, 0);
  filename = "cpp_nap_output_2_binaural_test.txt";
  WriteNAPOutput(my_output, filename, 1);
  int ear = 0;
  int n_ch = 71;
  for (int timepoint = 0; timepoint < num_timepoints; ++timepoint) {
    for (int channel = 0; channel < n_ch; ++channel) {
      FPType cplusplus = my_output.nap()[timepoint][ear](channel);
      FPType matlab = nap1[timepoint](channel);
      ASSERT_NEAR(cplusplus, matlab, kPrecisionLevel);
      cplusplus = my_output.bm()[timepoint][ear](channel);
      matlab = bm1[timepoint](channel);
      ASSERT_NEAR(cplusplus, matlab, kPrecisionLevel);
    }
  }
  ear = 1;
  for (int timepoint = 0; timepoint < num_timepoints; ++timepoint) {
    for (int channel = 0; channel < n_ch; ++channel) {
      FPType cplusplus = my_output.nap()[timepoint][ear](channel);
      FPType matlab = nap2[timepoint](channel);
      ASSERT_NEAR(cplusplus, matlab, kPrecisionLevel);
      cplusplus = my_output.bm()[timepoint][ear](channel);
      matlab = bm2[timepoint](channel);
      ASSERT_NEAR(cplusplus, matlab, kPrecisionLevel);
    }
  }
}

TEST(CARFACTest, Long_Output_test) {
  int num_timepoints = 2000;
  int num_channels = 83;
  int num_ears = 2;
  string filename = "long_test_nap1.txt";
  vector<ArrayX> nap1 = Load2dTestData(filename, num_timepoints, num_channels);
  filename = "long_test_bm1.txt";
  vector<ArrayX> bm1 = Load2dTestData(filename, num_timepoints, num_channels);
  filename = "long_test_nap2.txt";
  vector<ArrayX> nap2 = Load2dTestData(filename, num_timepoints, num_channels);
  filename = "long_test_bm2.txt";
  vector<ArrayX> bm2 = Load2dTestData(filename, num_timepoints, num_channels);
  filename = "file_signal_long_test.txt";
  vector<vector<float>> sound_data = Load2dAudioVector(filename, num_timepoints,
                                                       num_ears);
  CARParams car_params;
  IHCParams ihc_params;
  AGCParams agc_params;
  CARFAC mycf(num_ears, 44100, car_params, ihc_params, agc_params);
  CARFACOutput my_output(true, true, false, false);
  const bool kOpenLoop = false;
  const int length = sound_data[0].size();
  mycf.RunSegment(sound_data, 0, length, kOpenLoop, &my_output);
  filename = "cpp_nap_output_1_long_test.txt";
  WriteNAPOutput(my_output, filename, 0);
  filename = "cpp_nap_output_2_long_test.txt";
  WriteNAPOutput(my_output, filename, 1);
  int ear = 0;
  for (int timepoint = 0; timepoint < num_timepoints; ++timepoint) {
    for (int channel = 0; channel < num_channels; ++channel) {
      FPType cplusplus = my_output.nap()[timepoint][ear](channel);
      FPType matlab = nap1[timepoint](channel);
      ASSERT_NEAR(cplusplus, matlab, kPrecisionLevel);
      cplusplus = my_output.bm()[timepoint][ear](channel);
      matlab = bm1[timepoint](channel);
      ASSERT_NEAR(cplusplus, matlab, kPrecisionLevel);
    }
  }
  ear = 1;
  for (int timepoint = 0; timepoint < num_timepoints; ++timepoint) {
    for (int channel = 0; channel < num_channels; ++channel) {
      FPType cplusplus = my_output.nap()[timepoint][ear](channel);
      FPType matlab = nap2[timepoint](channel);
      ASSERT_NEAR(cplusplus, matlab, kPrecisionLevel);
      cplusplus = my_output.bm()[timepoint][ear](channel);
      matlab = bm2[timepoint](channel);
      ASSERT_NEAR(cplusplus, matlab, kPrecisionLevel);
    }
  }
}