Update audio code to use size_t more correctly, webrtc/modules/audio_processing/

webrtc/modules/audio_processing/intelligibility/intelligibility_enhancer_unittest.cc

 /*
  *  Copyright (c) 2015 The WebRTC project authors. All Rights Reserved.
  *
  *  Use of this source code is governed by a BSD-style license
  *  that can be found in the LICENSE file in the root of the source
  *  tree. An additional intellectual property rights grant can be found
  *  in the file PATENTS.  All contributing project authors may
  *  be found in the AUTHORS file in the root of the source tree.
  */
 
@@ skipping 39 matching lines @@
                                     {0.055556f, 0.f},
                                     {0.055556f, 0.2f},
                                     {0, 0.2f},
                                     {0, 0.2f},
                                     {0, 0.2f},
                                     {0, 0.2f}};
 static_assert(arraysize(kTestCenterFreqs) == arraysize(kTestFilterBank),
               "Test filterbank badly initialized.");
 
 // Target output for gain solving test. Generated with matlab.
-const int kTestStartFreq = 12;  // Lowest integral frequency for ERBs.
+const size_t kTestStartFreq = 12;  // Lowest integral frequency for ERBs.
 const float kTestZeroVar[] = {1.f, 1.f, 1.f, 1.f, 1.f, 1.f, 1.f, 1.f,
                               1.f, 1.f, 1.f, 0.f, 0.f, 0.f, 0.f, 0.f,
                               0.f, 0.f, 0.f, 0.f, 0.f, 0.f};
 static_assert(arraysize(kTestCenterFreqs) == arraysize(kTestZeroVar),
               "Variance test data badly initialized.");
 const float kTestNonZeroVarLambdaTop[] = {
     1.f,     1.f,     1.f,     1.f,     1.f,     1.f,     1.f,     1.f,
     1.f,     1.f,     1.f,     0.f,     0.f,     0.0351f, 0.0636f, 0.0863f,
     0.1037f, 0.1162f, 0.1236f, 0.1251f, 0.1189f, 0.0993f};
 static_assert(arraysize(kTestCenterFreqs) ==
@@ skipping 83 matching lines @@
   }
   for (auto step_type : step_types) {
     std::generate(clear_data_.begin(), clear_data_.end(), float_rand);
     orig_data_ = clear_data_;
     EXPECT_TRUE(CheckUpdate(step_type));
   }
 }
 
 // Tests ERB bank creation, comparing against matlab output.
 TEST_F(IntelligibilityEnhancerTest, TestErbCreation) {
-  ASSERT_EQ(static_cast<int>(arraysize(kTestCenterFreqs)), enh_.bank_size_);
-  for (int i = 0; i < enh_.bank_size_; ++i) {
+  ASSERT_EQ(arraysize(kTestCenterFreqs), enh_.bank_size_);
+  for (size_t i = 0; i < enh_.bank_size_; ++i) {
     EXPECT_NEAR(kTestCenterFreqs[i], enh_.center_freqs_[i], kMaxTestError);
-    ASSERT_EQ(static_cast<int>(arraysize(kTestFilterBank[0])), enh_.freqs_);
-    for (int j = 0; j < enh_.freqs_; ++j) {
+    ASSERT_EQ(arraysize(kTestFilterBank[0]), enh_.freqs_);
+    for (size_t j = 0; j < enh_.freqs_; ++j) {
       EXPECT_NEAR(kTestFilterBank[i][j], enh_.filter_bank_[i][j],
                   kMaxTestError);
     }
   }
 }
 
 // Tests analytic solution for optimal gains, comparing
 // against matlab output.
 TEST_F(IntelligibilityEnhancerTest, TestSolveForGains) {
   ASSERT_EQ(kTestStartFreq, enh_.start_freq_);
   vector<float> sols(enh_.bank_size_);
   float lambda = -0.001f;
-  for (int i = 0; i < enh_.bank_size_; i++) {
+  for (size_t i = 0; i < enh_.bank_size_; i++) {
     enh_.filtered_clear_var_[i] = 0.0f;
     enh_.filtered_noise_var_[i] = 0.0f;
     enh_.rho_[i] = 0.02f;
   }
   enh_.SolveForGainsGivenLambda(lambda, enh_.start_freq_, &sols[0]);
-  for (int i = 0; i < enh_.bank_size_; i++) {
+  for (size_t i = 0; i < enh_.bank_size_; i++) {
     EXPECT_NEAR(kTestZeroVar[i], sols[i], kMaxTestError);
   }
-  for (int i = 0; i < enh_.bank_size_; i++) {
+  for (size_t i = 0; i < enh_.bank_size_; i++) {
     enh_.filtered_clear_var_[i] = static_cast<float>(i + 1);
     enh_.filtered_noise_var_[i] = static_cast<float>(enh_.bank_size_ - i);
   }
   enh_.SolveForGainsGivenLambda(lambda, enh_.start_freq_, &sols[0]);
-  for (int i = 0; i < enh_.bank_size_; i++) {
+  for (size_t i = 0; i < enh_.bank_size_; i++) {
     EXPECT_NEAR(kTestNonZeroVarLambdaTop[i], sols[i], kMaxTestError);
   }
   lambda = -1.0;
   enh_.SolveForGainsGivenLambda(lambda, enh_.start_freq_, &sols[0]);
-  for (int i = 0; i < enh_.bank_size_; i++) {
+  for (size_t i = 0; i < enh_.bank_size_; i++) {
     EXPECT_NEAR(kTestZeroVar[i], sols[i], kMaxTestError);
   }
 }
 
 }  // namespace webrtc